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Penn State Softball Avoids Sweep Against Illinois
Penn State softball (8-39, 4-16 Big Ten) dropped both in a Saturday doubleheader to Illinois (33-16, 11-7 Big Ten), but found a way to snap its 11-game losing streak in an extra-innings battle against the Illini on Sunday.
The Nittany Lions lacked the pitching to keep up with Illinois' aggressive offense in the opening two games. Senior Jessica Cummings changed that to help Penn State grab the third game — pitching five clean innings in relief down the stretch before hit Tori Dubois a walk-off home run in the ninth inning.
How It Happened
Game One
The series opened Friday night, but only made it through an inning and a half before a lightning delay. The Nittany Lions jumped out to a 3-0 lead thanks to a Paige Johnson home run before the game was pushed to Saturday.
Madison Shaffer came on for relief for Jessica Cummings in the fifth and had a 4-2 lead in the sixth. She would give up a run and load the bases before Cummings returned to close out the game.
The Illini blew the game wide open at that point — scoring seven runs in total during the sixth and taking on another in the seventh to win 10-4.
Game Two
Despite a record crowd for the doubleheader at Nittany Lion Softball Park, the Illini jumped out to an early lead once again with a Kiana Sherlund solo home run in the first inning and four runs off one hit and a couple walks/hit-by-pitches in the second.
Illinois had an offensive showing against the Nittany Lions' pitching combination of Ashton Mensinger, Madison Shaffer, and Jessica Cummings — putting up a total of 11 runs and 10 hits. Penn State couldn't keep up, registering runs off a Paige Johnson two-run homer and a Gianna Arrizurieta two-run double, but never really staying in the game during its 11-4 loss.
Game Three
Penn State and Illinois went through four innings tied 3-3 thanks to an RBI triple from Meghan Williams and a couple errors from the Illini.
Jessica Cummings entered the game in relief for starter Madison Shaffer in the fifth inning, and the senior was the game changer for the Nittany Lions in her final game at Beard Field.
She pitched five straight scoreless innings — giving up just two hits — and setting up top slugger Tori Dubois for a walk-off solo home run in the ninth inning to close out the series with a 4-3 win.
Player of the Series
Jessica Cummings | Pitcher | Senior
It hasn't been an easy season by any stretch for Cummings, but she closed out her Penn State career with a solid performance to set the Nittany Lions up to win on Senior Day.
What's Next
The win gives the Nittany Lions a little more hope they can reach the conference tournament than they would've had heading to face two-time defending Big Ten Champions Minnesota (32-14, 15-3 Big Ten) next weekend. The final regular season series begins Friday at 7 p.m., with games Saturday and Sunday at 2 p.m.
Penn State needs at least one win to grab the final Big Ten Tournament spot. With a win, it would clinch if Iowa sweeps Purdue and Rutgers doesn't sweep Indiana.
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About the Author
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Samavanem, Samāvaṇēṃ, Samāvaṇeṃ: 2 definitions
Samavanem means something in Marathi. If you want to know the exact meaning, history, etymology or English translation of this term then check out the descriptions on this page. Add your comment or reference to a book if you want to contribute to this summary article.
Languages of India and abroad
Marathi-English dictionary
samāvaṇēṃ (समावणें).—v i (samāvēśa S) To enter and be contained (as in a vessel or receptacle). 2 To enter in, into, amidst, under &c. congenially, kindly, conveniently, suitably; to enter and blend with; to enter and lie amongst without enlargement, derangement, disturbance, alteration of appearance &c. Ex. śēra dudhānta pāvaśēra pāṇī samāvēla śērabhara ghātalēṃ tara dūdha nāsēla; śambhara pātrāñcē saimpākānta pāñca pātrēṃ samāvatīla; tumacyā kaṇṭhāḷīntalyā ōjhyānta mājhēṃ sōvaḷēṃ bhāṇḍēṃ kāṃ samāvaṇāra nāhīṃ; pāṇī pāṇyānta samāvatēṃ tēla tēlānta samāvatēṃ.
sāmavaṇēṃ (सामवणें).—v i (Properly and commonly samāvaṇēṃ q. v.) To enter and be contained in (as in a vessel or receptacle).
sāmāvaṇēṃ (सामावणें).—v i sāmēṇēṃ v i R (Properly samāvaṇēṃ) To enter and be contained in.Source: DDSA: The Aryabhusan school dictionary, Marathi-English
samāvaṇēṃ (समावणें).—v t Enter and be contained; enter in.
sāmāvaṇēṃ (सामावणें).—v i Enter and be contain- ed in.
Marathi is an Indo-European language having over 70 million native speakers people in (predominantly) Maharashtra India. Marathi, like many other Indo-Aryan languages, evolved from early forms of Prakrit, which itself is a subset of Sanskrit, one of the most ancient languages of the world.
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Tourism Calendar
If you have an event that you would like to promote on the Mark Twain Country website, please submit a tourism event. For more information on posting your event, please contact us.
- This event has passed.
Ugly Christmas Sweater Day
December 21, 2019 @ 10:00 am - 5:00 pm
- Wear your ugly Christmas sweater in today for a surprise (nope…no hints:-)
- Decorate your Ugly Christmas Sweater cookie at our tasting station today. We'll provide the "sweater" cookies and all of the toppings to make your cookie the ugliest!


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Executive chefs and purchasing managers of large hotel chains, importers, distributors and international marketers, as well as opinion leaders, have an appointment at the Spanish EVOO Experience and the Spanish Mocktail Bar, the two gastronomic spaces available in the Spanish pavilion at the Gulfood fair, which was held in Dubai from the 16th to the 20th of February. These areas, which will be accessible by closed invitation, will have a specific program of activities that will include seminars, tastings, product exhibitions and information spaces.
ICEX Spain Export and Investment has intensified the promotion of food and non-alcoholic beverages at this fair, which will welcome professional visitors with great purchasing decision capacity from countries in the Persian Gulf area and the Middle East, as well as from Africa, Southeast Asia, Europe and Oceania.
According to this organization, the tariff changes and the commercial policy applied by the American Administration have made market diversification more necessary than ever. In this way, the Spanish companies dedicated to the production of olive oil have been forced to go to the markets of the Middle East looking for to increase their sales to balance the more than predictable fall of the market share of the United States. Therefore, Spanish EVOO Experience aims to present and train the professional public about the differentiated quality of the Spanish product, as well as to boost sales even more.
In 2018, Spanish olive oil exports to the countries of the Arabian Peninsula exceeded 71 million euros, registering an increase of 178% during the last decade, and concentrating Saudi Arabia and the United Arab Emirates three quarters of the demand in the region.
Thus, the objective of these high added value spaces is to attract visitors to the Spanish pavilion, composed of 142 food and beverage companies, so that, among other things, they can develop networking actions with professional guests and project an integrated image of our international promotion strategy.
Torres y Ribelles, with its BETIS brand, is participating in GULFOOD for the 9th consecutive year. You can find us at Hall Oils & Fat - Za'abeel Plaza, stand Z3-B39.
Furthermore, due to the nature of the fair and in parallel, the commercial offices in Riyadh, Amman, Cairo, Muscat and Doha have organized guided tours for buyers and distributors from their regions, who will also be present at Gulfood and who will participate in the seminars organized in the gastronomic spaces.
A growing area
For ICEX, Gulfood is an essential event, not only to identify market niches and take advantage of business opportunities in an area of the world with high economic growth and a high demand for quality food, but also to establish commercial contacts from a wide variety of geographical origins.
During the first 11 months of 2019, Spanish agri-food products were exported to the Arabian Peninsula for a value of 703 million euros, which represents a growth of 3.5% with respect to the same period of the previous year. Saudi Arabia has become our main client in the area, with purchases exceeding 304 million euros, followed by the United Arab Emirates with 261 million and Kuwait with 44 million. Olive oil, with 52 million, is one of the most demanded Spanish products.
Source: Mercacei


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Eye tracking is a widely used tool for behavioral research in the field of psychology. With technological advancement, we now have specialized eye-tracking devices that offer high sampling rates, up to 2000 Hz, and allow for measuring eye movements with high accuracy. They also offer high spatial resolution, which enables the recording of very small movements, like drifts and microsaccades. Features and parameters of interest that characterize eye movements need to be algorithmically extracted from raw data as most eye trackers identify only basic parameters, such as blinks, fixations, and saccades. Eye-tracking experiments may investigate eye movement behavior in different groups of participants and in varying stimuli conditions. Hence, the analysis stage of such experiments typically involves two phases, (i) extraction of parameters of interest and (ii) statistical analysis between different participants or stimuli conditions using these parameters. Furthermore, the datasets collected in these experiments are usually very large in size, owing to the high temporal resolution of the eye trackers, and hence would benefit from an automated analysis toolkit. In this work, we present PyTrack, an end-to-end open-source solution for the analysis and visualization of eye-tracking data. It can be used to extract parameters of interest, generate and visualize a variety of gaze plots from raw eye-tracking data, and conduct statistical analysis between stimuli conditions and subject groups.
Relatively recent advancements in computer science and related technologies have resulted in greater automation and increased efficiency in analyzing large datasets when compared to manual processes. The field of psychology has greatly benefited from this in the form of advanced computational methods and tools. However, most of these software and tools are expensive and not freely accessible to everyone. Automating data processing with simple but effective computational pipelines provides the benefit of quicker and easier analyses. In turn, this allows more time for greater emphasis to be placed on designing paradigms, executing experiments, and arriving at the rationale for analyses.
While psychology is a broad discipline, a growing area of research is the analysis of eye movement and behavior as a tool for psychological insight. More specifically, eye tracking offers several interesting metrics, which can be beneficial for areas such as game design, visual marketing, medicine, and behavioral research like human emotion and deception detection. Some of the most important metrics, or parameters, include blinks, saccades, fixations, and pupil size. Each of these can act as proxies for different behavioral and physical conditions. For example, pupil dilation is known to be an indicator of stress (Pedrotti et al., 2014; Ren et al., 2014), while blink rate has been used to identify fatigue (Stern, Boyer, & Schroeder, 1994) as well as medical conditions such as schizophrenia (Chan & Chen, 2004). Eye tracking is also utilized in areas such as visual marketing (Wedel & Pieters, 2008) to gain insight into consumer behavior while searching for products in supermarkets or shops, and for gaining insight into user interaction with websites (Granka, Joachims, & Gay, 2004) in order to ameliorate user interface (UI) and user experience (UX) design for an improved experience. In the domain of behavioral research, eye tracking has proven to be a useful tool in the areas of human emotion and arousal analysis (Bradley, Miccoli, Escrig, & Lang, 2008) and has recently gained traction as a tool for deception detection (Cook et al., 2012; Kircher, 2018; Vrij, Oliveira, Hammond, & Ehrlichman, 2015). Considering its widespread influence over myriad domains, an open-source and freely accessible automated pipeline for parameter extraction and comparative analysis would be a beneficial addition to the eye-tracking community.
Here, we present PyTrack, an end-to-end analysis toolkit, built using the Python programming language, that allows users to analyze eye-tracking datasets using a few lines of code, as shown in a sample segment in Listing 1. After the initial process of recording eye movement data for multiple participants in multiple stimulus conditions, the raw data exported from the eye tracker can be directly fed into PyTrack in order to perform parameter extraction, generate plots and conduct statistical analysis on the extracted parameters. The toolkit can generate gaze plots, gaze heat maps, dynamic pupil and gaze plots, and aggregate heat maps for a group of participants. PyTrack also extracts parameters related to pupil size, blinks, fixations, saccades, microsaccades, and reading behavior. We have also implemented a feature that allows the user to indicate an area of interest (AOI) for the stimuli, in order to extract more advanced parameters such as number of revisits. If the experiment involves different groups of participants or stimulus conditions, PyTrack also provides the functionality of performing statistical tests such as the t test and variants of ANOVA for combinations of between and within group parameters. However, if desired, PyTrack can export a formatted file containing the extracted parameters without performing any statistical analysis, in order to allow the users to perform their own analyses. This facilitates a high degree of flexibility for the end-user in terms of analytical requirements because it can easily be used for rapid automated end-to-end analysis of eye-tracking experiments or simply as a parameter extraction tool. The programming required to utilize most features of PyTrack is minimal and can be accomplished by adapting parameters of the sample code segments. The visualization component has a simple graphic user interface (GUI) for ease of navigation and selection of participants and stimuli. For the more advanced and experienced programmers, PyTrack's functions can also be used and modified by importing it as a Python library. We discuss the toolkit in greater detail in sections 'Framework Structure' and 'Features of PyTrack'.
Related work
Most existing software and libraries for eye-tracking analysis are hardware specific proprietary software that is provided with the eye-tracking device. However, there have also been some significant contributions by individuals to the open-source community of eye-tracking research.
Among the hardware specific proprietary software, the first we will discuss is the SMI BeGaze™ (Sensomotoric Instruments, 2016) analysis suite. It supports various functionalities such as semantic gaze mapping, heat map generation, fixation mapping, area of interest (AOI) analysis, and extraction of key performance indicators such as number of revisits to AOI. Additionally, it provides (i) duration and velocity dispersion-based event detection for saccades and fixations, and (ii) extraction and exporting of several parameters related to saccades, fixations, blinks, and pupil size. Any reference to 'events' from here on will refer to fixations, saccades and blinks. Tobii provides its own software called Tobii Pro Lab™ (Tobii Technology, 2019) for design of experiments as well as analysis of collected data. It supports similar functionalities to BeGaze™ such as heat map and gaze plot visualization, area of interest analysis, and extraction of events. SR Research provides the Data Viewer™ (SR Research, 2018) software for EyeLink devices. It is mainly used for visualizing gaze and pupil-size data. It also allows event detection and generation of aggregate event and AOI reports and there is extended support available via MATLAB®, Psychtoolbox ® and E-Prime ®. However, what is common among these software programs is that they must be purchased in order to access the advanced functionalities. Of particular note is that the above software does not facilitate the extraction of microsaccade parameters from fixations and do not support multiple data formats from other hardware.
Other than the software accompanying eye-tracking hardware, there are some proprietary software such as iMotions™ (iMotions, 2019) that act as presentation, data collection and analysis software. iMotions™ provides several analysis tools that allow parameter extraction from raw data after the process of data collection. For example, iMotions™ supports aggregate heat map generation, fixation plot generation and AOI analysis including totaling number of revisits, time spent etc. It also has the provision of the dynamic viewing of pupil size, eye distance and gaze data. However, it is an expensive software and, at the time of writing, does not support some advanced eye trackers such as the EyeLink 1000 Plus.
Among the open-source eye-tracking tools, PyGaze (Dalmaijer, Mathôt, & Van der Stigchel, 2014) is a commonly used library. Its main functionality is enabling recording of eye-tracking data using presentation software such as OpenSesame (Mathôt, Schreij, & Theeuwes, 2012). It facilitates the sending of triggers and messages. It also provides some basic analysis functionality such as event detection, heat map generation and fixation plot generation. However, it does not provide any advanced parameter extraction, aggregate experiment analysis, or statistical tests. As its main functionality is to act as a wrapper around several existing packages, it does not provide a lot of functionality for post recording analysis. Another open-source package available for analysis in the R programming language is eyetrackingR (Dink & Ferguson, 2015). It supports most of the widely used eye trackers such as EyeLink and Tobii. The functionalities it provides are 'cleaning-up' and performing different analyses on time series data such as growth-curve analysis and onset-contingent reaction time analysis. It also provides the functionality of generating plots corresponding to the analyses. However, it does not provide support for the extraction of parameters related to fixations, saccades, microsaccades, pupillometry, and blinks. A similar package for Matlab® is the EMA Toolbox (Gibaldi & Sabatini, n.d.). It supports EyeLink, SMI, and Tobii eye trackers. The functionality provided by EMA includes: data conversion from normalized to pixel to degrees; saccade identification; saccade kinematics; generation of saliency maps; and generation of main sequence plots. Main sequence is a plot that shows the relationship between the peak velocity (on the vertical axis) and amplitude (on the horizontal axis) of saccadic eye movements. OGAMA – Open Gaze and Mouse Analyzer (Voßkühler, Nordmeier, Kuchinke, & Jacobs, 2008) is another open-source software which is similar to the iMotions™ software discussed earlier. It allows creation and presentation of stimuli, recording of eye-tracking data and finally, analysis and visualization of the collected data. It provides the functions of dynamic replay of data, generation of fixation path plots, and attention maps. Users can specify subject, trial, gaze, and mouse event parameters that OGAMA calculates and then exports into a results file. The OGAMA software only supports extraction of parameters related to fixations and saccades.
Framework structure
The PyTrack framework is designed using principles of object-oriented programming (OOP) and is structured in a manner that provides maximum flexibility to the user. The first design component takes into consideration the users' varying knowledge of Python programming. We understand that users require different levels of access to, and flexibility with, the framework, depending upon their programming knowledge. For users with limited programming experience, PyTrack can act as an end-to-end toolkit taking raw data as input, perform all the required parameter extractions and producing the results of statistical analysis as output. Advanced programmers, on the other hand, have the flexibility of accessing the extracted parameters, member functions and variables, and using them for their custom requirements.
The second design component of PyTrack takes into consideration how a given user may wish to use PyTrack, either in the 'experiment design' or 'stand-alone design'. This is achieved by the entire functionality being broken-up into different objects that interact with each other, as can be seen in Fig. 1.
In the experiment design, PyTrack can analyze an entire experiment containing n subjects responding to k stimuli each. Path 'A [Experiment]' in Fig. 1 illustrates the structure of this design. In this setup, the user interacts with the Experiment object and PyTrack effectively acts as a black box, thus removing any need of the user to consider internal functionalities. However, as the objects at different levels interact with each other, if the user wishes, the member variables and functions of the internal objects can also be accessed through the Experiment object. This, of course, would require programming knowledge in Python, as discussed earlier.
The stand-alone design is for those users who wish to analyze a single stimulus for a given subject or make use of the parameter extraction functions and visualization tools for their custom needs. The user–toolkit interaction can be seen in Path 'B [Stand-alone]' of Fig. 1. The user interacts directly with the internal objects and parameter extraction modules. Hence, this is designed for those who wish to access PyTrack at a lower level of the abstraction model to directly control the algorithms and visualization functionality.
Features of PyTrack
In the following section we discuss the salient features of PyTrack, giving an overview of its robust functionality and how it acts as an end-to-end toolkit.
Format agnostic and quick data access
The format bridge module in PyTrack enables the analysis and visualization of data collected using three different types of eye trackers - EyeLink, Tobii, and SMI. This functionality was achieved by adapting and modifying the code in PyGazeAnalyser (Dalmaijer et al., 2014). The recording software of the eye trackers provide the option of exporting the data as raw text files. The format bridge module accepts these files as its input and converts them to a base format readable by PyTrack, a comma separated value (CSV) file. Following this, an SQL database is generated containing an aggregation of all the participants. The rationale for generating an SQL database and using it to access the data instead of the CSV files is that it reduces the time required to read data when conditional querying is implemented. Working with raw SQL files is inconvenient and hence, we transform the SQL data into a Pandas DataFrame for internal usage.
We conducted data access tests on two different systems using datasets of varying number of rows in CSV and SQL formats. Table 1 shows the difference in data access times for each of the cases with and without conditional querying. With an increase in the number of rows, systems with better processors and higher random-access memory (RAM) are able to read the entire data much quicker. This is because a higher RAM allows more data from the SQL or CSV tables to be loaded into the main memory for quick access. This in turn leads to a lower number of page faults (data that need to be accessed but are not present in the main memory) and reduces the latency of accessing the secondary memory (hard disk, solid-state drive etc.). The SQL data access time shown is the cumulative time for accessing the raw SQL data in Python and to convert it to a Pandas DataFrame. The benefit of using Pandas is that it allows easy and efficient manipulation of SQL and CSV data in Python. As can be seen, if all the stimuli from an experiment are being analyzed, the CSV reading option is the faster approach. However, if only a subset of stimuli is being analyzed which involves conditional data access, SQL provides a significant decrease in access time. Therefore, depending on the task, the user may toggle the access method from CSV to SQL or vice-versa.
Parameter extraction
PyTrack extracts 21 parameters in all, which are commonly used in eye-tracking research. These comprise pupil size, blinks, fixations, saccades, microsaccades and reading behavior.
Pupil size
Pupil size, and parameters derived from it, have been used to study the dynamics of cognitive brain functions (Beatty, 1982). Research suggests that changes in pupil size can be used as an index for attentional effort (Kang, Huffer, & Wheatley, 2014) and non-emotional perceptual tasks (Webb, Honts, Kircher, Bernhardt, & Cook, 2009). The pupil size parameters that are provided by PyTrack are: average pupil size; time to pupil size peak; peak pupil size; and area under the pupil curve.
Parameters related to blinking are used as proxies to medical conditions and fatigue as mentioned in 'Introduction'. Blinks can easily be detected from eye-tracking data by finding segments of the raw data where the pupil size falls to zero. However, Hershman, Henik, and Cohen (2018) proposed a noise-based blink detection algorithm that detects the onset and offset of the blinks more accurately. Hence, we adapted their algorithm to implement a python version and validated it with the original implementations in R and MATLAB. The comparison of the two implementations is shown in Supplementary Fig. 1. The first step of the algorithm is to identify the missing values in the pupil size data and mark the last valid sample before and after the missing segment as the initial blink onset (sample n) and offset (sample m). The pupillometry data is then smoothened using a moving average filter with a window size of 10 ms and the difference between adjacent samples is calculated. For example, if pt (t =1, 2, 3, 4, 5, …) is the pupil size at any time t, the values calculated are p2 – p1, p3 – p2, p4 – p3, and so on. This difference is calculated in order to identify monotonic sequences in the smoothened pupillometry data, which in turn is used to update the old blink onset and offset (sample n and m, respectively). The blink onset is updated by starting at the initial onset (sample n) and moving backward (sample n-1, n-2, …) while the pattern is monotonically increasing. The index of the last value in this pattern before the initial onset is selected as the new blink onset. Similarly, for the blink offset, we move forward from the initial offset (from sample m to m+1, m+2, …) while the pattern is monotonically increasing and select the last value in the pattern after the initial offset as the new blink offset. The blink parameters that PyTrack provides are: blink count; peak blink duration; and average blink duration.
The duration and rate of fixations have been used in the past for studying deception by Cook et al. (2012), and cognitive process by Just and Carpenter (1976). Furthermore, the ratio of fixation count and duration inside and outside an AOI can also help in determining the level of focus of the subject in the given AOI, which is of importance in a variety of tasks such as visual marketing research and reading research (Daneman & Reingold, 1993; Just & Carpenter, 1980). The fixation sequences are obtained from the raw data exported from the eye tracker's software. In cases where the data does not contain this information, the dispersion-based threshold identification (I-DT) algorithm is applied to the gaze data in order to identify the fixations (Salvucci & Goldberg, 2000). The first step is selecting a window within which the dispersion D is to be calculated. We consider a window size Wthresh of 50 ms as the minimum duration for a segment to be classified as a fixation. Starting with the minimum window size i.e. W = Wthresh, the dispersion is calculated using Eq. (1). In the equation, Gx and Gy are the gaze position vectors in the x and y axes for a given window and D is the dispersion of that window. If the D <= Dthresh, the window size is increased by 1, i.e., W = W+1, and the previous step is repeated. Finally, if D > Dthresh and W > Wthresh, the points in the window excluding the last point are considered to be part of a fixation sequence. Then the window resets to Wthresh and starts at the first point after the last fixation sequence.
After this, for a given stimulus, PyTrack extracts the fixation count, maximum duration and average duration. In order to get fixation parameter values inside an AOI, the area can be specified before analysis, as explained in 'area of interest (AOI)'.
Saccades and microsasccades
Saccade sequences are usually marked by the eye tracker's recording software in the raw data. For data in which the saccade sequences are not marked, the velocity-based threshold identification (I-VT) algorithm is applied (Salvucci & Goldberg, 2000). The first step in the algorithm is to calculate the pointwise velocity of the gaze data. Points with velocities of more than around 40 pixels/second are classified as saccades. Equation (2) shows the computation of the velocities from gaze data. In the equation, Vt is the velocity in x or y direction at time t, and Gt is the gaze position in x or y axis at time t.
A well-known and widely used algorithm for the detection of microsaccades was first proposed by Engbert and Kliegl (2003) followed by improvements made by Engbert and Mergenthaler (2006). In PyTrack, we provide an implementation of this algorithm in order to extract parameters such as count, duration, velocity, and amplitude. The first step is to calculate the velocity from the gaze data using a moving average , as shown in Equation (3a). The next step is the calculation of the velocity threshold Vthresh using Equation (3b). The k value is calculated using Equation (3c), and all points with k > 1 are considered to be part of a microsaccade sequence, provided the sequence contains at least six samples. Finally, the velocity and amplitude of the microsaccade sequence are calculated using Equation (3d & e). The last two equations are also used to calculate the velocity and amplitude of the saccades. In Equation (3): Vt is the velocity in x or y axis at time t; Gt is the gaze position in x or y axis at time t; Sfreq is the sampling frequency of the eye tracker; Vthresh is the microsaccade threshold velocity in the x or y axis; Vfac is a constant value that is used to calculate the microsaccade threshold velocity in the x or y axis (default value used is 5); V→ is the velocity vector in the x or y axis; G→ is the gaze position vector in the x or y axis; Vpeak is the peak velocity of the microsaccade sequence; and A is the microsaccade sequence amplitude.
In order to ensure that our implementation is in accordance with the original algorithm adapted for R, we compared the output plots on the same data file. The plot in Supplementary Fig. 2a shows the microsaccade gaze position and gaze velocity plots generated by PyTrack. Supplementary Fig. 2b shows the same plots generated by the MS Toolbox for R (Ralf Engbert, Mergenthaler, Sinn, & Pikovsky, 2011; Ralf Engbert, Sinn, Mergenthaler, & Trukenbrod, 2015) as an implementation of their own algorithm. A comparison of the two plots shows that both implementations work identically.
Reading behavior
PyTrack also extracts parameters to look at reading behavior of subjects. Cook et al., (Cook et al., 2012) saw that, during deception detection, reading patterns could be used for differentiating between participants assigned to an 'innocent' group and participants assigned to a 'guilty' group. One reading of the text located in the AOI is defined as the set of consecutive fixations which are located in the specified region. The reading parameters included in PyTrack are: number of readings; duration of first reading (first pass); and duration of second reading (second pass).
Area of interest (AOI)
PyTrack facilitates user specification of an AOI from which parameters of interest can be extracted. If there is a common AOI for all stimuli, it can be drawn or specified as coordinates. The accepted drawn shapes are rectangles, ellipses, and polygons. If the coordinates are specified, they can be one of the following shapes: the top-left and bottom-right coordinates of a rectangle, center and size of axes (width and height) of an ellipse, or the coordinates of a polygon's vertices. However, if the AOI is different for each stimulus, the values must be specified as rectangle, ellipse, or polygon coordinates in a CSV file, along with the corresponding stimulus name. The drawing functionality is not supported in this case because the task of drawing an AOI for all the stimuli is rather tedious and as the AOIs are usually defined at the time of conducting the experiment, it is more convenient to specify them in a CSV file. Several experiment presentations and recording software such as OpenSesame allow exporting such parameters as CSV files. Figure 2 shows the different types of AOI PyTrack accepts.
Statistical analysis
The analysis stage of experiments usually involves the comparison of (i) a subject or subject group's response to different types or classes of stimuli and (ii) the response of different subject groups to the same stimulus type. PyTrack has inbuilt statistical analysis functions (e.g., ANOVA, mixed ANOVA, t test, etc.) that allows the users to conduct a variety of tests to compare the various subject and stimuli groups. These tests provide statistical analyses of the extracted parameters discussed earlier. The users can either conduct the tests on all the extracted parameters, or alternatively specify the parameters of interest and test for statistically significant differences on the specified parameters. Lines 9 and 13 in Listing 2, respectively, contain sample code segments to execute these functionalities.
A basic test that is supported is a mixed ANOVA, which considers stimuli type to be a within group factor and subject type as the between group factor. In addition to this, as shown in line 17 of Listing 2, PyTrack also allows for advanced analysis where the user can specify additional within and between group factors on which statistical analysis can be performed. It provides for n-way ANOVA, repeated measures ANOVA (RMANOVA), pairwise Student's t test and pairwise Welch t test. The n-way ANOVA accepts any number of between group factors while the RMANOVA accepts up to two within group factors. The pairwise Student's t test can be used when analysis is conducted for the within-subject factor, in within-subject designs (one-way) or mixed designs (with one between group and one within-group factor). The Welch t test accepts only one within group or one between group factor. The Mixed ANOVA, RMANOVA, and pairwise t test are performed by using the functions defined in the pingouin package (Vallat, 2018), while statsmodels (Seabold & Perktold, 2010) is used for n-way ANOVA. Scipy (Oliphant, 2007) provides the functionality to perform the Welch t test.
Users can perform analysis of a select few parameters, instead of all of them, by specifying the parameters of interest. The results of these tests are printed out in the computer terminal and saved into CSV files for later reference. PyTrack also provides the option of allowing users to export all the extracted parameters in the form of a CSV file without performing any tests, as shown in line 23 of Listing 2. The data present in the CSV file contains all the extracted parameters along with the name of the subject and stimuli that was being observed. This is especially useful if the users wish to perform statistical tests independent of PyTrack.
Ease of modifying analysis factors
The analysis of the entire experiment is controlled by an intuitive JSON file. Users can easily specify the list of participants and stimuli to be analyzed. Participants and stimuli can also be grouped as required. They also can be added or removed from the JSON file in order to modify the analysis and focus on a subset of the entire corpus. Additionally, every participant or stimulus can be assigned a list of attributes such as gender and age for participants, and brightness level for stimuli. This enables the users to apply the statistical tests to more than one between group factor. To form a baseline for comparisons, the names of control stimuli can also be specified in PyTrack. The parameters extracted from these are used to normalize the parameters extracted from the rest of the stimuli. Parameters relevant to the hardware used in the experiment such as display screen dimensions and sampling frequency of the eye tracker can also be specified here. Essentially, all the parameters involved with analyzing the experiment data can be specified in a single file, thereby simplifying and speeding up the process of analysis. The structure of this JSON file can be seen in Listing 3. The users need not write this file from scratch as a template can be downloaded as part of the sample data.
Another set of important features of PyTrack are the visualization tools it provides. These vary based on the mode PyTrack is being used in, as mentioned in 'Framework Structure'. The interaction in the Experiment Design is via a simple GUI that allows easy and convenient navigation with two broad categories—individual subject and aggregate. The visualization windows are shown in Fig. 3. In the Stand-alone Design, the visualization is for the individual stimulus. Function invocations by code can generate the same plots as in the Experiment Design, with the exception of the aggregated subject plots.
The individual subject category includes fixation plots, gaze heat maps and dynamic gaze, and pupil size plots. The fixation plot, as shown in Fig. 4a, is a gaze plot with numbered fixation points which enables the user to view the order in which the subject viewed the stimulus and what regions they fixated on. Fig. 4b shows the gaze heat map, which is essentially a smoothed two-dimensional histogram of the subject's gaze data. It is a visual representation of the frequency with which regions of the stimulus were viewed. The gaze coordinates of the subject, over time t, are taken and the 'histogram2d' function of NumPy (Oliphant & Millma, 2006) is applied. If the number of rows and columns of pixels in the original image are nrows and ncols, the number of histogram bins assigned are (nrows)/4 and (ncols)/4. This is followed by a Gaussian filter that smooths the histogram, and a contour plot of the filtered 2D histogram is generated using an appropriate color map to produce the final heat map. The last type of plot is the dynamic pupil and gaze plot, which is shown in Fig. 4c. It is a dynamic (moving) plot of the gaze on the stimulus along with the corresponding pupil size of the subject at that time instance. As the navigation is via a GUI, it is convenient to close a particular plot and generate another one for the same subject or a different subject. Furthermore, there is an option to save the plots generated into the experiment folder which can be accessed at a later time as needed.
The aggregated subject plot is available if used in the Experiment Design and shows aggregated heat maps for a given stimulus. The user has the freedom to select the subjects that are required for the aggregate analysis and if desired the plots can be saved along with a text document containing the list of subjects included in that plot. Aggregated heat maps act as a visual representation of the average time spent by all the subjects in viewing the various regions of a stimulus. In cases where there are different groups of subjects, this may help provide an insight into the differences in viewing patterns between said groups.
Additional features available in the Stand-alone Design include the generation of microsaccade position and velocity plots and main sequence plots. The main sequence, in this case, is the plot between the peak velocity and amplitude of the microsaccades. These can be generated in the Experiment Design also, but as it is an advanced feature it requires the user to add an additional line of code. Some samples of the plots generated are shown in Fig. 4d and Fig. 4e.
Using PyTrack as a parameter extraction tool
PyTrack can also be used just as a parameter extraction tool instead of an end-to-end solution. The parameters extracted can then be used to generate custom plots or perform custom analyses as desired by the users. Listing 4 contains a code segment showing one possible use of PyTrack as an extraction tool. The code segment generates pupil size plots, comparing various stimulus conditions for each participant or subject group. Lines 15–28 in the code listing demonstrate how the extracted parameters can be accessed using Python code. The example parameter accessed in the listing is InterpPupilSize, which stands for interpolated pupil size, and demonstrates the generation of comparative pupil size plots. All parameters can be accessed in a similar fashion. Lines 35–45 contain the code to generate the pupil size plots mentioned earlier. This can be replaced by the users' code to generate custom plots or perform their own analyses. The principle behind accessing the extracted parameters remains the same. Figure 5 shows the plots generated by this code listing using the provided sample data.
PyTrack offers the same essential functionality present in the existing toolkits and frameworks discussed in 'Related Work'. However, there are several features that differentiate it from existing software: it has the added benefits of being format agnostic; it is an end-to-end solution with the addition of statistical analysis capabilities; it is open source; and it is free to use. The visualization interface is straight-forward and easy to navigate, and the analysis tools are easy to use. Furthermore, it can be used in different modes - Experiment and Stand-alone - and at various levels of abstraction based on the desired flexibility and modification.
A comparison with SMI BeGaze™, Tobii Pro Lab™, EyeLink Data Viewer™, iMotions™, PyGaze, eyetrackingR, EMA Toolbox and OGAMA can be seen in Table 2. There are certain areas in which PyTrack can be improved, as discussed in 'Conclusions', but several more in which it proves to be a beneficial tool when compared to similar software.
Considering a trade-off between cost and ease of use, as outlined in Table 2, PyTrack is a promising option that is free-for-all. However, we believe that there is scope for including more advanced analysis methods, improving the user interface, and improving parameter detection algorithms with advances in eye-tracking research.
Analysis methods
The methods provided are variants of the ANOVA and t test, which are purely statistical methods. There are several machine learning methods which can aid in further analysis and build classification models based on the experiment data. Therefore, it is possible to integrate these methods into the toolkit which will enable researchers without expertise in machine learning to train their own models without worrying about the intricacies of the underlying algorithms and networks.
Parameter extraction
PyTrack extracts a total of 21 parameters related to the various eye movement events. These parameters have been selected after conducting a thorough survey of the most widely used parameters in the eye-tracking community. However, it is possible to add more parameters to the current list based on the requirements of the users.
Data format support
Currently PyTrack offers support for EyeLink, SMI and Tobii devices as they are the most popular and widely used. However, there is scope for adding support for other eye trackers which are not commonly used or are relatively new in the industry.
Currently, in order to supply multiple AOIs for a given stimulus, the analyze function of PyTrack has to be run multiple times. Although this is a relatively quick process, we plan on including the support for multiple and dynamic AOIs in the next release, in order to simplify the process.
User Interface
PyTrack's visualization GUI is a convenient and easy to use interface but the analysis relies on basic coding. With that in mind, it is possible to convert the analysis component to a GUI also, thereby improving the user experience.
We believe that PyTrack can be integrated with ease into the analysis stage of an eye-tracking experiment to simplify the analysis process by providing a fully automated end-to-end pipeline that performs the necessary tasks of parameter extraction, statistical analysis and visualization. At the same time, PyTrack is flexible enough to allow users to access the internal workings and modify them according to their needs. As such, it is a solution that provides the dual functionality of (i) acting as a black box, thus removing complexities associated with computation; and (ii) acting as a white box, allowing the users to modify the pipeline at any stage to suit their needs.
The code, along with installation instructions and documentation, for PyTrack can be found at https://github.com/titoghose/PyTrack. Sample data has been provided to test the toolkit, which can be downloaded from https://osf.io/f9mey/files/. The SMI and Tobii files provided in the sample data have been obtained from the EYE-EEG toolbox (Dimigen, Sommer, Hohlfeld, Jacobs, & Kliegl, 2011).
Author note
We would like to thank Dr Dominique Makowski (School of Social Sciences, NTU, Singapore) for his helpful discussions and advice in developing PyTrack. We would also like to thank Nadine Garland for proofreading the manuscript. The support and assistance of Mr. Shivaprasad G (Dept. CSE, Manipal Institute of Technology), Dr. Jabez Christopher (Dept. of CSIS, BITS, Pilani - Hyderabad Campus), and Dr. Rishi Kumar (Dept. of Economics and Finance, BITS, Pilani - Hyderabad Campus) is greatly appreciated.
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Electronic supplementary material
Supplementary Fig. 1:
Comparison of blink detection plots generated by (a) PyTrack and (b) Hershman's Matlab code. The pairs of red circles mark the onset and offset of a blink. The data used to generate the plots are Trial 17 and 33 of the sample data provided by Hershman (https://osf.io/gjt8v/). (PDF 214 kb)
Supplementary Fig. 2:
Comparison of microsaccade position-velocity plots generated by (a) PyTrack and (b) Engbert's Microsaccade Toolbox for R. The plots generated are for the sample data file "f01.005.dat" provided with the toolbox. (PDF 72 kb)
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Ghose, U., Srinivasan, A.A., Boyce, W.P. et al. PyTrack: An end-to-end analysis toolkit for eye tracking. Behav Res (2020). https://doi.org/10.3758/s13428-020-01392-6
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Small fishing charter/guide company in West Hawk Lake, Manitoba. Specializing in lake trout, walleye, smallmouth bass, pike, and crappie. Run by a young fishing guide who operates one on one tours and fishing lessons...
Got One Fishing Charters
Local Bahamian Dive Guides specializing in Freediving and Spearfishing offering Private Freedive and Spearfishing charters in the Bahamas.
Bahamas Dive Guides
Fishing flathead catfish
FlatHead Hunter
Fishing retailer for tackle & apparel.
MK Jigs & Tackle Co.
We are branding our fishing/outdoors mantra, "LivingProof". We are "LivingProof" that with enough drive, ambition and faith you can do anything you set your mind to. We really want this to be as much or more about creating a unique, strong and catchy font as it is about the image that goes with it.
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I am a military vet developing a You tube channel for other vets with stress conditions due to military service. Fly fishing, fly tying and outdoor activities is my niche
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Local news after CBS World News 6 a.m. to 5 p.m.
Sandwich Fair canceled
The Sandwich Fair Association has canceled the annual fair that has been held in Sandwich since the 1880's due to coronavirus concerns. It was planned for September. A statement from the fair association says the decision is based on information from the DeKalb County Health Department and the Illinois Department of Public Health. The announcement…… read more »
Volunteers of all skill levels needed for home rehab in Ottawa
In one week, Habitat for Humanity of LaSalle, Bureau, and Putnam Counties wants to start its part of a rehab project on Ottawa's west side. The home belongs to 34-year old Marine Corps veteran Jeremy Close. Floors, walls, and ceilings need to be installed. There's also plumbing work to do. Executive Director Sally Van Cura…… read more »
LaSalle County COVID-19 count up to 215 with 151 recoveries
The LaSalle County Health Department says there are five new coronavirus cases in the county. The total is at 215. Recoveries remain at 151. Illinois announced 724 new cases on Tuesday and 23 new deaths. The state is up to 143,185 cases and 6,923 deaths.… read more »
Illinois Senator doesn't believe that President Trump wasn't aware of bounties reportedly placed on U.S. troops
Illinois Democratic Senator Tammy Duckworth is finding it hard to believe that President Trump was unaware of an alleged plot to put bounties on U.S. troops in Afghanistan by Russia. Duckworth says if the president's staff didn't tell him about it, it means they don't trust him with the information. Duckworth says she knows of…… read more »
Democratic Congressional Candidate thinks Pres. Trump knew about alleged plot on U.S. troops
16th Congressional District Congressional Candidate Dani Brzozowski says Republican Adam Kinzinger is covering for President Trump's inaction to deal with a plot to encourage harm to U.S. soldiers in Afghanistan. Kinzinger said in an interview with CNN Monday that the president wasn't briefed on a report that Russia was putting bounties on U.S. troops. Brzozowski…… read more »
Rick Koshko
Rick Koshko lived the first half of his life in southern Illinois, then moved to Ottawa early in his broadcasting career. His first thoughts of broadcasting as a career occurred to him at age five–when it was bed time and he realized the guy on the radio didn't have to go to bed yet. Some irony: for most of the time he's worked in radio, Rick has had to get up very early in the morning to be on the air, sometimes in addition to being up late at night like he wanted.
Rick is a graduate of Southern Illinois University Edwardsville's broadcasting program. He speaks Esperanto, likes astronomy (SkyCaramba), and makes a hobby of photography.
Ethan Kruger
Ethan Kruger started his broadcasting career in college after realizing that he liked hearing himself talk a little bit too much. After a brief stint of spinning records at Eastern Illinois University's student FM station, Ethan realized his love for reporting the news. He loves where he works and is always excited to discuss what's happening in the community. Ethan sees it as a privilege to serve the good people of LaSalle County through broadcasting.
Ethan likes board games, the outdoors, and watching all the different versions of Ridley Scott's Blade Runner.


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"II. The second base of operations available for the army of the Potomac is that of the lower Chesapeake bay, which affords the shortest possible land route to Richmond, and strikes directly at the heart of the enemy's power in the east. -
"The roads in that region are passable at all seasons of the year.
"The country now alluded to is much more favorable for offensive operations than that in front of Washington, (which is very unfavorable,) much more level, more cleared land, the woods less dense, the soil more sandy, and the spring some two or three weeks earlier. A movement in force on that line obliges the enemy to abandon his intrenched position at Manassas, in order to hasten to cover Richmond and Norfolk. He must do this; for should he permit us to occupy Richmond, his destruction can be averted only by entirely defeating us in a battle, in which he must be the assailant. This movement, if successful, gives us the capital, the communications, the supplies of the rebels; Norfolk would fall; all the waters of the Chesapeake would be ours; all Virginia would be in our power, and the enemy forced to abandon Tennessee and North Carolina. The alternative presented to the enemy would be, to beat us in a position selected by ourselves, disperse, or pass beneath the Candine forks.
"Should we be beaten in a battle, we have a perfectly secure retreat down
the Peninsula upon Fort Monroe, with our flanks perfectly covered by the fleet. "During the whole movement our left flank is covered by the water. Our right is secure, for the reason that the enemy is too distant to reach us in time; he can only oppose us in front; we bring our fleet into full play. "After a successful battle our position would be—Burnside forming our left— Norfolk held securely—our centre connecting Burnside with Buell, both by Raleigh and Lynchburg—Buell in Eastern Tennessee and North Alabama— Halleck at Nashville and Memphis. "The next movement would be to connect with Sherman on. the left, by reducing Wilmington and Charleston; to advance our centre into South Carolina and Georgia; to push Buell either towards Montgomery, or to unite with the main army in Georgia; to throw Halleck southward to meet the naval expedition from New Orleans. o "We should then be in a condition to reduce at our leisure all the southern seaports; to occupy all the avenues of communication; to use the great outlet of the Mississippi; to re-establish our government and arms in Arkansas, Louisiana and Texas; to force the slaves to labor for our subsistence, instead of that of the rebels; to bid defiance to all foreign interference. Such is the object I have ever had in view—this is the general plan which I hope to accomplish. "For many long months I have labored to prepare the army of the Potomac to play its part in the programme; from the day when I was placed in command of all our armies, I have exerted myself to place all the other armies in such a condition that they, too, could perform their allotted duties. "Should it be determined to operate from the lower Chesapeake, the point of landing which promises the most brilliant result is Urbana, on the lower Rappahannock. This point is easily reached by vessels of heavy draught; it is neither occupied nor observed by the enemy—it is but one march from West Point, the key of that region, and thence but two marches to Richmond. A rapid movement from Urbana would probably cut off Magruder in the Peninsula, and enable us to occupy Richmond, before it could be strongly re-enforced. Should we fail in that, we could, with the co-operation of the navy, cross the James and throw ourselves in rear of Richmond, thus forcing the enemy to come out and attack us, for his position would be untenable, with us on the Southern bank of the river. "Should circumstances render it not advisable to land at Urbana, we can use Mobjack bay; or, the worst coming to the worst, we can take Fort Monroe
as a base, and operate with complete security, although with less celerity and brilliancy of results, up the Peninsula. "To reach whatever point may be selected as a base, a large amount of cheap water transportation must be collected, consisting mainly of canal-boats, barges, wood-boats, schooners, &c., towed by small steamers, all of a very different character from those required for all previous expeditions. This can certainly be accomplished within thirty days from the time the order is given. I propose, as the best possible plan that can, in my judgment, be adopted, to select Urbana as a landing place for the first detachments; to transport by water four divisions of infantry with their batteries, the regular infantry, a few wagons, one bridge train and a few squadrons of cavalry, making the vicinity of Hooker's P. the place of embarkation for as many as possible; to move the reguar cavalry and reserve artillery, the remaining bridge trains and wagons, to a point somewhere near Cape Lookout, then ferry them over the river by means of North River ferry-boats, march them over to the Rappahannock, (covering the movement by an infantry force near Heathsville,) and to cross the Rappa. hannock in a similar way. The expense and difficulty of the movement will then be very much diminished, (a saving of transportation of about 10,000 horses,) and the result none the less certain. "The concentration of the cavalry, &c., on the lower counties of Maryland can be effected without exciting suspicion, and the movement made without delay from that cause. "This movement, if adopted, will not at all expose the city of Washington to danger. "The total force to be thrown upon the new line would be, according to circumstances, from 110,000 to 140,000. I hope to use the latter number by bringing fresh troops into Washington, and still leaving it quite safe. I fully realize that in all projects offered, time will probably be the most valuable consideration. It is my decided opinion that, in that point of view, the second plan should be adopted. It is possible, nay, highly probable, that the weather and state of the roads may be such as to delay the direct movement from Washington, with its unsatisfactory results and great risks, far beyond the time required to complete the second plan. In the first case we can fix no definite time for an advance. The roads have gone from bad to worse. Nothing like their present condition was ever known here before; they are impassable at present. We are entirely at the mercy of the weather. It is by no means certain that we can beat them at Manassas. On the other line I regard success as certain by all the chances of war. We demoralize the enemy by forcing him to abandon his prepared position for one which we have chosen, in which all is in our favor, and where success must produce immense results. "My judgment, as a general, is clearly in favor of this project. Nothing is certain in war, but all the chances are in favor of this movement. So much am I in favor of the southern line of operations, that I would prefer the move from Fortress Monroe as a base—as a certain though less brilliant movement than that from Urbana, to an attack upon Manassas. "I know that his excellency the President, you, and I, all agree in our wishes; and that these wishes are, to bring this war to a close as promptly as the means in our possession will permit. I believe that the mass of the people have entire confidence in us—I am sure of it. Let us, then, look only to the great result to be accomplished, and disregard everything else. I am, very respectfully, your obedient servant, "GEO. B. McCLELLAN, "Major General, Commanding. "Hon. E. M. STANTON, "Secretary of War."
This letter must have produced some effect upon the mind of the President, since the execution of his order was not required, although it was not revoked as formally as it had been issued. Many verbal conferences ensued, in which, among other things, it was determined to collect as many canal-boats as possible, with a view to employ them largely in the transportation of the army to the lower Chesapeake. The idea was at one time entertained by the President to use them in forming a bridge across the Potomac near Liverpool point, in order to throw the army over that point; but this was subsequently abandoned. It was also found by experience that it would require much time to prepare the canal boats for use in transportation, to the extent that had been anticipated. Finally, on the 27th of February, 1862, the Secretary of War, by the authority of the President, instructed Mr. John Tucker, Assistant Secretary of War, to procure at once the necessary steamers and sailing craft to transport the army of the Potomac to its new field of operations. The following extract from the report of Mr. Tucker, dated April 5, will show the nature and progress of this well-executed service: * >k # # # # # # # #: "I was called to Washington by telegraph, on 17th January last, by Assistant Secretary of War Thomas A. Scott. I was informed that Major General McClellan wished to see me. From him I learned that he desired to know if transportation on smooth water could be obtained to move at one time, for a short distance, about 50,000 troops, 10,000 horses, 1,000 wagons, 13 batteries, and the usual equipment of such an army. ' He frankly stated to me that he had always supposed such a movement entirely feasible, until two experienced }. had recently reported it impracticable, in their judgment. A few ays afterwards, I reported to General McClellan that I was entirely confident the transports could be commanded, and stated the mode by which his object could be accomplished. A week or two afterwards I had the honor of an interview with the President and General McClellan, when the subject was further discussed, and especially as to the time required. "I expressed the opinion that, as the movement of the horses and wagons would have to be made chiefly by schooners and barges, that as each schooner would require to be properly fitted for the protection of the horses, and furnished with a supply of water and forage, and each transport for the troops provided with water, I did not deem it prudent to assume that such an expedition could start within thirty days from the time the order was given. "The President and General McClellan both urgently stated the vast importance of an earlier movement. I replied that if favorable winds prevailed, and there was great despatch in loading, the time might be materially diminished. "On the 14th February you (Secretary of War) advertised for transports of various descriptions, inviting bids on the 27th February. I was informed that the proposed movement by water was decided upon. That evening the Quartermaster General was informed of the decision. Directions were given to secure the transportation—any assistance was tendered. He promptly detailed to this duty two most efficient assistants in his department. Colonel Rufus Ingalls was stationed at Annapolis, where it was then proposed to embark the troops, and Captain Henry C. Hodges was directed to meet me in Philadelphia, to attend to chartering the vessels. With these arrangements I left Washington on the 28th February. # # # # # # # # "I beg to hand herewith a statement, prepared by Captain Hodges, of the vessels chartered, which exhibits the prices paid, and parties from whom they were taken:
113 steamers, at an average price per day.............. $215 10 188 schooners, " 44 " - - - - - - - - - - - - - - 24 45 88 barges, " 6 & " - - - - - - - - - - - - - - 14 27
H. Ex. Doc. 15—4
"In thirty-seven days from the time I received the order in Washington, (and most of it was accomplished in thirty days,) these vessels transported from Perryville, Alexandria, and Washington to Fort Monroe (the place of departure having been changed, which caused delay,) 121,500 men, 14,592 animals, 1,150 wagons, 44 batteries, 74 ambulances, besides pontoon bridges, telegraph materials, and the enormous quantity of equipage, &c., required for an army of such magnitude. The only loss of which I have heard is eight mules and nine barges, which latter went ashore in a gale within a few miles of Fort Monroe– the cargoes being saved. With this trifling exception, not the slightest accident has occurred, to my knowledge,
"I respectfully, but confidently, submit that, for economy and celerity of
movement, this expedition is without a parallel on record. # # # # >k # # +
"JOHN TUCKER, "Assistant Secretary of War."
In the mean time the destruction of the batteries on the lower Potomac, by crossing our troops opposite them, was considered, and preparations were even made for throwing Hooker's division across the river, to carry them by assault. Finally, however, after an adverse report from Brigadier General J. G. Barnard, Chief Engineer, given below, who made a reconnoissance of the positions, and in view of the fact that it was still out of the power of the Navy Department to furnish suitable vessels to co-operate with land troops, this plan was abandoned as impracticable. A close examination of the enemy's works and their approaches, made after they were evacuated, showed that the decision was a wise one. The only means, therefore, of accomplishing the capture of these works, so much desired by the President, was by a movement by land, from the left of our lines, on the right bank of the Potomac—a movement obviously unwise. The attention of the Navy Department, as early as August 12, 1861, had been called to the necessity of maintaining a strong force of efficient war vessels on the Potomac. "HEADQUARTERS Division of THE PoToMAC, "Washington, August 12, 1861.
"SIR: I have to-day received additional information which convinces me"that it is more than probable that the enemy will, within a very short time, attempt to throw a respectable force from the mouth of Aquia creek into Maryland. This attempt will probably be preceded by the erection of batteries at Matthias and White House points. Such a movement on the part of the enemy, in connexion with others probably designed, would place Washington in great jeopardy. I most earnestly urge that the strongest possible naval force be at once concentrated near the mouth of Aquia creek, and that the most vigilant watch be maintained day and night, so as to render such passage of the river absolutely impossible.
"I recommend that the Minnesota and any other vessels available from Hampton Roads be at once ordered up there, and that a great quantity of coal be sent to that vicinity, sufficient for several weeks' supply. At least one strong war vessel should be kept at Alexandria, and I again urge the concentration of a strong naval force on the Potomac without delay.
"If the Naval Department will render it absolutely impossible for the enemy to cross the river below Washington, the security of the capital will be greatly increased.
"I cannot too earnestly urge an immediate compliance with these requests.
"I am, sir, very respectfully, your obedient servant, "GEORGE B. McCLELLAN, "Major General Commanding. "Hon. GIDEoN WELLEs, "Secretary of the United States Navy."
It was on the 27th of September, 1861, that General Barnard, Chief Engineer, in company with Captain Wyman of the Potomac flotilla, had been instructed to make a reconnoissance of the enemy's batteries as far as Matthias point. In his report of his observations he says: "Batteries at High point and Cockpit point, and thence down to Chopawampsic, cannot be prevented. We may, indeed, prevent their construction on eertain points, but along here somewhere the enemy can establish, in spite of us, as many batteries as he chooses. What is the remedy? Favorable circumstances, not to be anticipated nor made the basis of any calculations, might justify and render successful the attack of a particular battery. To suppose that we can capture all, and by mere attacks of this kind prevent the navigation being molested, is very much the same as to suppose that the hostile army in our own front can prevent us building and maintaining field-works to protect Arlington and Alexandria by capturing them, one and all, as fast as they are built." In another communication upon the subject of crossing troops for the purpose of destroying the batteries on the Virginia side of the Potomac, General Barnard says: "The operation involves the forcing of a very strong line of defence of the enemy, and all that we would have to do if we were really opening a campaign against them there. "It is true we hope to force this line by turning it, by landing on Freestone point. With reason to believe that this may be successful, it cannot be denied that it involves a risk of failure. Should we, then, considering all the consequences which may be involved, enter into the operation, merely to capture the Potomac batteries? I think not. Will not the Ericsson, assisted by one other gunboat capable of keeping alongside these batteries, so far control their fire as to keep the navigation sufficiently free as long as we require it? Captain Wyman says yes." It was the opinion of competent naval officers, and I concur with them, that had an adequate force of strong and well-armed vessels been acting on the Potomac from the beginning of August, it would have been next to impossible for the rebels to have constructed or maintained batteries upon the banks of the river. The enemy never occupied Matthias point, nor any other point on the river, which was out of supporting distance from the main army. When the enemy commenced the construction of these batteries, the army of the Potomac was not in a condition to prevent it. Their destruction by our army would have afforded but a temporary relief unless we had been strong enough to hold the entire line of the Potomac. This could be done either by driving the enemy from Manassas and Aquia creek, by main force, or by manoeuvring to compel them to vacate their positions. The latter course was finally pursued, and with success. About the 20th of February, 1862, additional measures were taken to secure the reopening of the Baltimore and Ohio railroad. The preliminary operations of General Lander for this object are elsewhere described. I had often observed to the President and to members of the cabinet that the reconstruction of this railway could not be undertaken until we were in a condition to fight a battle to secure it. I regarded the possession of Winchester and Strasburg as necessary to cover the railway in the rear, and it was not till the month of February that I felt prepared to accomplish this very desirable but not vital purpose. The whole of Banks's division and two brigades of Sedgwick's division were thrown across the river at Harper's Ferry, leaving one brigade of Sedgwick's division to observe and guard the Potomac from Great Falls to the mouth of the Monocacy. A sufficient number of troops of all arms were held in readiness in the vicinity of Washington, either to march via Leesburg or to move by rail