text:
Given the wide-ranging types of human sexuality, the binary gender model is no longer viable.
My first boyfriend, in the eighth grade, turned out to be gay. So did my second, and my third. By the time — at 19 — I finally succeeded in hooking up with a straight man, I was so relieved to be with someone who was actually attracted to me that I married him. However, I continued to fantasize about men with men throughout our 13 years of marriage. As I write this a few decades later, I'm married to a bisexual guy whose romantic liaisons have primarily been with lesbians.
Welcome to the wonderful, and often confusing, world of the girlfag and guydyke.
The word "girlfag" was invented by Jill Nagle in a 2003 article in BUST Magazine ("Manly, Yes, But I Like It Too: The Life and Loves of a Girlfag"). Nobody knows who invented "guydyke," but it seems to have been coined a year or two later. Most members of the English-speaking girlfag/guydyke community are less than thrilled with the terminologies, which began in an era when many minorities were actively seeking to reclaim potentially negative words (as in Dan Savage's "Hey Faggot!" column). As of this writing, though, nobody has yet come up with a viable English synonym for "girlfag," although "male lesbian" for "guydyke" has achieved some currency.
Terminology notwithstanding, girlfag and guydyke identities are a subject of increasing awareness. A growing group of men and women are discovering that they identify with LGBT culture and understand themselves as ineluctably queer, and are drawn erotically and culturally to gay people of another gender.
Flexible Gender
Although the identity is new, the reality of the girlfag predates contemporary notions of flexible gender by at least centuries. Mary Renault, for example, wrote homoerotic novels on Greek and Roman history that inspired several generations of gay men; Renault had a lifelong female partner but was unapologetic about her attraction to male/male sexuality. Before her, Amantine-Arore-Lucile Dupin — better known as George Sand — often dressed as a man and formed erotic attachments to effeminate men such as Frédéric Chopin. We have no way of knowing how many other women fit into this specialized niche of gender and orientation, as only the famous few have come down to us via the written word.
Today's girlfag might express her erotic self by reading or writing "slash" fiction (a predominantly woman-created and consumed genre in which men from popular culture have gay sex together — the word "slash" derives from the virgule in "Kirk/Spock" — one of the first recognized pairings in the field). She might consume yaoi, a form of Japanese hentai comic in which two beautiful boys become lovers. She might or might not present as masculine-of-center.
I do, but some other girlfags think of themselves as "female drag queens" and love dressing in hyper feminine clothing. She might or might not be a "fag hag" — a woman who enjoys the company and culture of gay men without necessarily thinking of herself as one of them or wanting to have sex with them.
Meanwhile, what is her guydyke colleague up to? He might be consuming female/female porn — but unlike his straight brethren, he'll be imagining himself not as the unseen male on whom both women are about to turn their attention, but as one of the women engaging in lesbian sex. (Susie Bright's excellent article, "Men Who Love Lesbians (who don't care for them too much)," in 1993, was one of the first mainstream pieces to suggest male lesbianism as a radical form of queerness rather than as a patriarchal appropriation of women's sexuality.)
Objectifying Sexual Fantasies
Many readers, in learning about girlfag and guydyke identities, might feel some concern for the life path of a woman or man so identified — after all, what are the possibilities for a romantic future for someone whose lust object is, by definition, not interested in them? I'm happy to report that many of us do indeed settle into stable and happy arrangements — sometimes in a relationship (often non-monogamous) — with the gay man or lesbian of our dreams. Sometimes, like me, in a relationship with a bisexual whose affection and values are "gay enough" to meet our desires. Sometimes with a fellow girlfag (leading to a relationship between two female-assigned people who relate and play as gay men) or a fellow guydyke (creating a "lesbian relationship" between two male-assigned people). Some girlfags and guydykes, like other genderqueers, may find their male or female identities waxing and waning over time, and may seek out partners flexible enough to follow their lead.
Girlfags and guydykes are sometimes accused of objectifying gay male/lesbian sexuality — to which I answer, resoundingly, "Duh": Sexual fantasy is inherently objectifying in that it tends to focus on a projected image of the fantasy object rather than on the entire, complex human being. But a well-behaved girlfag or guydyke, like a well-behaved person of any gender or orientation, does not project their fantasies onto non-consenting partners. Female-presenting people who insist on invading men's spaces, or male-presenting people who do the same to women's spaces, are beneath contempt, as are those of any gender who pester uninterested people for attention, dates or sex. Such behaviors have nothing to do with ethical girlfaggery or guydykery.
Viable Gender Models
By far the greatest obstacle facing most girlfags and guydykes, though, is angry resistance from those wedded to binary gender, often monosexuals (entirely gay or entirely heterosexual), who worry that our very existence calls into question the immutability of gender and orientation. For those who consider the world to be clearly divided between men and women (and thus gay and straight people), girlfags and guydykes present an intractable problem: In that worldview, it is impossible for a woman to be a gay man, or a man a lesbian.
Such statements point to simplistic beliefs about gender — that "male" equals "masculine" equals "XY-chromosomed" equals "penis-owning," for example. The reality that one individual may have a vulva, may present as masculine, may have XY chromosomes and androgen insensitivity syndrome and may be legally female — just to pick a random sampling of the chaos of criteria that are supposed to encompass gender in our culture — mocks the reductiveness of the old binary gender system.
Another oversimplification of the girlfag/guydyke identity comes from a controversial and pathologizing theory about cross-dressers and transsexuals, holding that they are expressing "autogynephilia/autoandrophilia" — erotic attraction to the image of themselves as a person of another gender. Given the spectrum of gender presentation among girlfags and guydykes, which ranges from exaggeration of one's assigned gender through full gender transition, and all stations between, this theory appears to be a desperate attempt to cling to a no-longer-viable binary gender model.
Relevant books written for non-academic readers include Straight: The Surprisingly Short History of Heterosexuality by Hanne Blank, The End of Gay (and the Death of Heterosexuality) by Bert Archer, and PoMoSexuals: Challenging Assumptions About Gender and Sexuality by Carol Queen and Lawrence Schimel. You might also want to check out my own Girlfag: A Life Told in Sex and Musicals while you're at it.
And if, after checking out a few of these resources, you find yourself looking with fresh eyes at your history of romantic attractions — remember that beautiful, soft-spoken boy in high school with whom you did everything but, and who still shows up in your fantasies once in a while? Or that softball-playing tomboy whose butt looked amazing in jeans but whose short haircut seemed to be a clear statement that you weren't batting for her team? Well, welcome to our world.
The views expressed in this article are the author's own and do not necessarily reflect Fair Observer's editorial policy.
Photo Credit: Yulia Grigoryeva / Agnieszka Lobodzinska / Shutterstock.com
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text:
Jurgen Klopp wants Steven Gerrard to replace him as Liverpool manager, when he eventually leaves his role at Anfield.
The Reds legend, Gerrard is the current Rangers boss, and has guided the Glasgow club to second in the Scottish Premiership, three points behind bitter rivals, Celtic.
Before managing in Scotland, Gerrard was in charge of Liverpool's Under-18s and worked with Klopp shortly after retiring.
"Kenny and Stevie have both been a really big support from day one.
"Second, my position as a manager has nothing to do with the people around me. If Liverpool were to sack me tomorrow, then maybe Kenny would be the first choice to replace me, but they would probably bring Stevie down from Glasgow.
"If you ask who should follow me, I'd say Stevie. I help him whenever I can. If someone gets your job, it's not about them, it's about you not being good enough.
"I'm old enough to know that I give this job everything. I'm not a genius, I'm not perfect, but I give the club 100 per cent. If that's enough, great. If it's not, then it's just the problem of the situation," Klopp told Four Four Two.

subset: commoncrawl


text:
sri sri guru gauranga jayatah!
Year 2, Issue 6, Amāvasyā
Speical Edition
Posted: 21 June 2020
Dedicated to and Inspired by
nitya-lila pravista om visnupada
Śrī Śrīmad Bhaktivedānta Nārāyaṇa Gosvāmī Māhārāja
Have At Least One Bandhu
Pithy Precepts of Śrīla Gurudeva
Excerpts from a hari-kathā given by
11 March 1993 Śrī Keśavajī Gauḍīya Maṭha, Mathurā
Upadeśāmṛta, Verse 4
If one knowingly or unknowingly is attached to unfavourable association and thus involves oneself in that association, the fruit of that will certainly manifest within him. Similarly, if one develops attachment to sādhusand takes their association, then the glories [glorious qualities] of that sādhu will enter within him. For this reason, one should only associate with sādhus, Vaiṣṇavas. By having a taste for unfavourable association, we'll go into the deepest hell, but by associating with sadhus, we'll attain bhakti and gradually progress. If one wants to have affectionate relationships with sādhus, then one is to interact with them in the following ways:
Dadāti. If an object dear to us is helpful to the bhajana of a Vaiṣṇava but is not in their possession, give it to them. We should give them those objects that are favourable for their bhajana.
Pratigṛhṇāti. When a sādhu-Vaiṣṇava who is affectionate to us mercifully gives us something, we should accept it. Nārada Ṛṣi says, "In my childhood, I used to visit the sādhus who came to our village to observe cāturmāsya-vrata. I used to carry their dry clothes when they went [to the river] to bathe and carry their wet clothes back. [For their honouring of prasāda] I would place leaf plates before them, having cleaned those plates, and then offer water into their water-pots. They then honoured prasāda. If any of the prasāda was particularly nice, they would lovingly instruct me, saying, "I have kept this for you. O son, take this."
Nārada Ṛṣi says, "Simply by honouring that prasāda, I received auspiciousness, my heart became pure and bhāgavad-bhakti entered it. Had I not accepted their remnants, all that would not have been possible."
Therefore, the remnants of Vaiṣṇavas, the hari-kathā emanating from their mouth, their foot-bathing water and their foot-dust – these things give great strength to our bhajana. This should never be doubted. Also, one should never develop such a hateful attitude that one thinks, "How could I possibly take their foot-dust?" Instead, in a hidden way, like Jhaḍu Ṭhākura, one should serve their foot-dust. So, pratigṛhṇāti – accept the prasāda (mercy) they give us.
Guhyam ākhyāti pṛcchati. One should offer [tell] the topics on one's mind to the sādhus and śrī guru, whom one is to consider his bandhus, or well-wishing friends [guardian angels]. One should inquire from them only and one should hear only from them. We should have at least one such bandhu, parama-bāndhava (utmost well-wisher), to whom we can open our heart. We can accept his treatment and follow what he tells us.
We see that, among us, we do not make even one such bandhu. We say externally, "He Gurudeva, you are my bandhu," but internally, there are so many things we aren't able to reveal to him or to the bandhu. This is why we are destroyed. O brothers, you should have at least one bandhu. And if there are several, that is even better. Make at least one bandhu among guru-vaiṣṇavas. Show him all the bad things in your heart, show him that "these things are in me." Mercifully, he will remove all those things and call Bhāgavan to sit there. The least bit of deceit will be like an abscess on your stools' passage way.
Once, a person got an abscess on the private part of his body. Out of shame, he didn't show it to anyone or tell anyone about it, not his mother, father, brother or sister. Gradually, after some days, that abscess turned into a fistula, big enough for his hand to enter. Now what could he do? It was uncurable. In this way, he died, all due to ordinary shyness. It is for this reason that we want a real bandhu, a real doctor, who we can completely trust and open our heart to. And he can take responsibility for us. One should ask for hari-kathā from him and hear from him.
Bhuṅkte bhojayate caiva. One should accept the prasāda given by him, and bhojate ca eva – one should affectionately offer him his favoured foodstuffs.
By this, his moods will be transmitted into our heart and all [unfavourable] things will be dispelled.
Translated by the Rays of The Harmonist team
[On the occasion of the Disappearance day of Saccidānanda Śrīla Bhaktivinoda Ṭhākura, we are presenting his brief Upādeśāmṛta commentary on this verse, the Pīyūṣa-varṣiṇī-vṛtti.]
Upadeśāmṛta, Verse 4
Association That Nourishes Bhakti
dadāti pratigṛhṇāti / guhyam ākhyāti pṛcchati
bhuṅkte bhojayate caiva / ṣaḍ-vidhaṁ prīti-lakṣaṇam
Offering pure devotees items in accordance with their requirements, accepting prasādī or remnant items given by pure devotees, revealing to devotees one's confidential realisations concerning bhajana, inquiring from them about their confidential realisations, eating with great love the prasāda remnants given by devotees and lovingly feeding them prasāda – these are the six symptoms of loving association with devotees.
Bad association is unfavourable to bhakti; therefore it is imperative to abandon such association. Those who are intent on progressing in bhakti should associate with pure devotees, who possess the power to free one from the tendency to fall into bad association. A description of the loving exchanges shared between devotees, which nourish one's bhakti, is found in this fourth verse. Lovingly giving another devotee that which he requires and lovingly accepting those items that are mercifully given by other devotees, revealing one's confidential realisations to devotees and hearing descriptions of confidential tenets (tattva) from pure devotees, lovingly serving devotees prasāda and accepting prasāda offered by devotees – these six kinds of exchanges constitute association with saintly persons (sādhu-saṅga) in its pure form. These six activities are the symptoms of love. One should serve sādhus by the performance of these activities


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Teeth in a Day
Teeth in a Day: Same Day Tooth Replacement
Teeth in a Day: Our cutting edge of implant dentistry allows us to remove teeth and place new fixed teeth back immediately. This is done by fixing new teeth on top of your implants in a very precise controlled method.
Some of the indications for this treatment are:
The tooth being replaced is visible within the smile line
You don't want to wear a removable temporary denture
When all your teeth are being replaced with dental implants
We perform these procedures in a team approach with our dentist, our implant surgeon and our custom dental lab. The surgery can be done while you are local anesthesia.
The beauty of this is that all your extractions, all bone procedures and the fabrication of your new teeth are all completed in one day with minimal recovery time. The result is a functional set of teeth that looks and feels natural and allows individuals to once again experience the foods they most enjoy.
Dental implant surgery often requires multiple surgical procedures and numerous visits. However, often the "Teeth in a Day" procedure is much simpler.
How It's Done
You first come to the office for a consultation with one of our dentist and a CT scan is done. Our custom lab makes a template for the immediate teeth and also produces the custom implant guide for your surgery. These two are matched together so that the implants are precisely placed and that the fixed teeth will fit in the desired positions.
A follow up the next day will ensure the bite and esthetics will be excellent. These temporary tooth are worn for several months until the final bridge is made. It's almost miraculous and the final results in most cases are stunning.
Having fixed teeth is much more comfortable than to wear a temporary denture for up to six months. This prevents the embarrassing inconveniences of a denture dropping loose and perhaps not being able to smile naturally.
Westcoast International's Teeth in a Day procedure can be used for a single, multiple tooth or the famous All-On-4™ dental implant technique. The All-On-4™ procedure is the optimal solution for those who have lost or are about to lose all of their upper and/or lower teeth. Our custom laboratory can come as close to having a new set of permanent tooth for you as is currently possible within a day.
Are Teeth in a Day Possible for Everyone?
We always try to provide a fixed temporary when requested, however there are some circumstances when the procedure should not be used. Softer bone quality and the inability to firmly place the implant may lead to early implant failure, if the implant immediately has a tooth on it. If the Teeth in a Day treatment option is performed, it is absolutely critical to follow our specific home care and diet instructions following the procedure.
Less Downtime
Our Teeth in a Day procedures at Westcoast International focus on minimally invasive surgery to deliver maximum results in the shortest time with the least discomfort. Most patients experience only minor soreness the next day and can eat a light meal that same evening.
Many of our patients that undergo the Teeth in a Day procedure are some of the happiest we treat. If your worried about having no teeth after the procedure, we'll make it a priority to replace them and get you back to normal as fast as possible.
Read More:
Read our Reviews and Testimonials from our Patients for Westcoast International Dental Clinics and our Team of Dentists


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Medtronic has updated the indications for use and the warning statements for its Navlock trackers, following two patient deaths. The trackers—which are part of its StealthStation navigation system—had been used alongside third-party instrumentation in a number of cases resulting in patient injury.
The previous indication for use read, "The NavLock tracker is intended to enable navigation of instrumentation used for pedicle preparation during spinal fusion and interbody procedures with a Medtronic computer-assisted surgery system."
The revised indication now reads, "The NavLock trackers are intended to enable navigation of Medtronic instrumentation used during spinal fusion and interbody procedures with the Medtronic StealthStation surgical navigation system. The NavLock trackers should only be used with Medtronic instruments."
The previous warning statement read, "The NavLock tracker is designed and tested for use only with Medtronic instruments. Use with any unapproved instrument could compromise accuracy and safety."
The strengthened version now reads "The NavLock tracker is designed and tested for use only with Medtronic instruments. The use of non-Medtronic instruments with the NavLock tracker may result in inaccuracy, leading to serious injury or death."
In safety notice issued by the company, Medtronic states, "Medtronic has not assisted in the design, instrument development, software development, process qualification, or validation of any non-Medtronic instrument for use with the NavLock tracker. Instruments manufactured by a non-Medtronic manufacturer have not been evaluated by Medtronic for compatibility with NavLock. Additionally, non-Medtronic instruments do not have corresponding "tool cards" in the StealthStation software."


text:
Recently, I was on the InSight on Business-The News Hour with Michael Libbie. Going on the radio is always a great experience with him, and being able to reach out to their audience with information that is useful to the community is something I look forward to each month.
In this video, Michael and I discuss Part One of my three-part series of What Happens to Your Business if Something Happens to You?
If you, or someone you know, has any questions on succession planning or protecting your business, please feel free to call us at (515) 727-0900 or visit us at http://kreamerlaw.com


text:
(CN) - A coalition of nearly 200 nations has approved a timetable to stop using hydrofluorocarbons (HFCs), greenhouse gases that are significantly more damaging than carbon dioxide.
The agreement inked this week in Rwanda's capital, Kigali, outlines the timetable for nations to reduce their use of the HFCs. Most industrialized nations will begin to cut back on HFCs by 2018, while China, Africa and Brazil will begin by 2024 and others will ramp down beginning in 2028.
HFCs are chemical refrigerants often used in air conditioners, refrigerators and cars, and ironically contribute to global warming. Reducing their usage is regarded as an important aspect of a larger global effort to reduce greenhouse gas emissions and avoid warming the planet to a point where more severe effects of climate change are felt.
"By acting now, we're avoiding up to a full half a degree centigrade (0.9 degrees Fahrenheit) of warming by the end of the century. This is a big deal, because our scientists say very clearly that we must keep our planet's temperature from rising 2 degrees (3.6 degrees Fahrenheit) above our normal temperature," U.S. Environmental Protection Agency Administrator Gina McCarthy said in a statement.
McCarthy and Secretary of State John Kerry participated in the negotiations, which were seven years in the making and required a partnership between rich and poor nations, including some where air conditioners are a newly introduced luxury.
"It is likely the single most important step we could take at this moment to limit the warming of our planet and limit the warming for generations to come," Kerry said during negotiations.
While the Paris climate agreement of 2015 was met with widespread coverage and praise, the Kigali talks have gotten less attention, possibly due to the lack of public awareness of HFCs and their impact on the climate - they represent a small percentage of greenhouse gases in the atmosphere but have 1,000 times the heat-trapping potency of carbon dioxide.
The Paris agreement focused on carbon dioxide emissions from fossils fuels that power electric plants, vehicles and factories.
The deal struck in Kigali is an amendment to the Montreal Protocol, a historic 1987 agreement that aimed to close the hole in the ozone layer by banning ozone-depleting coolants called chlorofluorocarbons, or CFCs. Because it is an amendment to the Montreal Protocol, the Kigali agreement has the legal force of a treaty.
"Yes, there will be challenges ahead. But the past week reminds us that when faced with clear science, when buoyed by the strong partnership of developed and developing countries working together, we can make great strides to protect the one planet we have," McCarthy said.Follow @SeanDuffyCNS
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Dialog Box
Setting out a roadmap to reduce the incidence, increase the survival rate and improve the quality of life of people diagnosed with ovarian cancer in Australia.
Announcing the National Action Plan for Ovarian Cancer (2020 - 2025)
Ovarian Cancer Australia has united with the Australia New Zealand Gynaecological Oncology Group (ANZGOG) and Australian Society of Gynaecologic Oncologists (ASGO) to launch the Ovarian Cancer National Action Plan (NAP) 2020 – 2025.
Women diagnosed with ovarian cancer and their families are at the heart of this plan.
The NAP sets out a roadmap to reduce the incidence, increase the survival rate and improve the quality of life of people diagnosed with ovarian cancer in Australia. It was developed over many months in partnership with women living with ovarian cancer key organisations and leaders in ovarian cancer including researchers, policy makers and ovarian cancer health professionals.
We are most grateful to the women with ovarian cancer who contributed to this plan.
Their feedback reassured us that the priorities outlined in the plan reflect their needs and hopes for the future. Those who responded agreed on the priorities listed below and were resolute that collaboration is essential to attract further investment and expedite progress.
The NAP's five core priorities are:
Patient- and family-centred care
Diagnosis and treatment
Early detection
Together, we can change the story of ovarian cancer.
Caitlin Delaney reflects on the new Ovarian Cancer National Action Plan:
The National Action Plan 2020 - 2025 is available to download:
Read the 2015 - 2020 version below:
Executive Summary
Back to 'I am a health professional'Back to Our impact
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© 2023 Ovarian Cancer Australia


text:
Estimate state-space model using time-domain or frequency-domain data
Estimate State-Space Model
estimates the continuous-time state-space model
sys = ssest(
sys of order
nx, using all the input and output signals in the timetable
You can use this syntax for SISO and MISO systems. The function assumes that the last variable in the timetable is the single output signal.
sys is an
idss model of the following form:
D, and K are state-space matrices.
u(t) is the input,
y(t) is the output,
e(t) is the disturbance, and
x(t) is the vector of
All entries of A, B, C, and
K are free estimable parameters by default. D is
fixed to zero by default, meaning that there is no feedthrough, except for static systems
nx = 0).
To estimate discrete-time models, set
'Ts' to the model sample
time using name-value syntax.
To estimate MIMO models, use name-value syntax to specify the input and output
channels using
'InputName' and
'OutputName' to
the corresponding timetable variable names.
You can also use
'InputName' and
'OutputName' to specify specific channels when you do not want to
use all the available channels in
estimates a discrete-time state-space model using the time-domain input and output signals
in the comma-separated matrices
sys = ssest(
y and the
model sample time
The software assumes that the data sample time is
Ts seconds.
You can use this syntax for SISO, MISO, and MIMO systems.
Estimating a continuous-time model with
by not specifying
Ts is not recommended. The software assumes that
the data sample time is 1 second. You cannot change this sample time. If you want to
estimate a continuous-time model from data with a sample time other than 1 second, you
must first convert your matrix data to a timetable or
iddata object. For
an example of this conversion, see Convert SISO Matrix Data to Timetable or Convert MIMO Matrix Data to Timetable for Continuous-Time Model Estimation.
estimates a continuous-time state-space model using the time-domain or frequency-domain
data in the data object
sys = ssest(
Use this syntax especially when you want to estimate a state-space model using frequency-domain or frequency-response data, or when you want to take advantage of the additional information, such as intersample behavior, data sample time, or experiment labeling, that data objects provide.
Estimate Time Series State-Space Model
estimates the continuous time series model
sys = ssest(
sys to fit the data in the
tt must contain a single numeric
variable. The function interprets the timetable variable data as a time series, which has
no inputs and a single output.
For a time series model, the
idss model has the following form:
estimates a multivariate time series model that uses the timetable output signals that
have the variable names specified in
sys = ssest(
outputVariables. The function
interprets the specified variables as a multivariate time series. If you specify all the
variables in
tt in
'OutputName', you can omit
the specification of
Specify Additional Model Options
incorporates additional options specified by one or more name-value pair arguments.
sys = ssest(___,
For example, specify a discrete-time system from matrix data that has a sample time of
0.1 using
sys = ssest(um,ym,np,'Ts',0.1). Specify input and output
signal variable names that correspond with the variables to use for MIMO timetable data
sys =
ssest(data,nx,'InputName',["u1","u4"],'OutputName',["y1","y3"]). Use the
'Feedthrough', and
'DisturbanceModel' name-value arguments to modify the default
behavior of the A, B, C,
D, and K matrices.
You can use this syntax with any of the previous input-argument combinations.
Configure Initial Parameters
Specify Additional Estimation Options
State-Space Model
Estimate a state-space model and compare its response with the measured output.
Load the input/output data, which is stored in a timetable.
load sdata1 tt1
Estimate a fourth-order state-space model.
nx = 4; sys = ssest(tt1,nx);
Compare the simulated model response with the measured output.
The plot shows that the fit percentage between the simulated model and the estimation data is greater than 70%.
You can view more information about the estimation by exploring the
idss property
ans = Status: 'Estimated using SSEST with prediction focus' Method: 'SSEST' InitialState: 'zero' N4Weight: 'CVA' N4Horizon: [6 10 10] Fit: [1x1 struct] Parameters: [1x1 struct] OptionsUsed: [1x1 idoptions.ssest] RandState: [] DataUsed: [1x1 struct] Termination: [1x1 struct]
For example, find out more information about the termination conditions.
ans = struct with fields:
WhyStop: 'No improvement along the search direction with line search.'
Iterations: 7
FirstOrderOptimality: 85.9760
FcnCount: 123
UpdateNorm: 10.6480
LastImprovement: 0
The report includes information on the number of iterations and the reason the estimation stopped iterating.
Determine Optimal Estimated Model Order
Load the input/output data in matrices
umat1 and
ymat1, as well as the sample time
Ts. These
matrices store the same estimation data as the timetable data used to estimate a
fourth-order model in State-Space Model.
load sdata1 umat1 ymat1 Ts
Determine the optimal model order by specifying argument
nx as a
range from
nx = 1:10;
sys = ssest(umat1,ymat1,nx,'Ts',Ts);
An automatically generated plot shows the Hankel singular values for models of the
orders specified by
States with relatively small Hankel singular values can be safely discarded. The
suggested default order choice is
Select the model order in the Chosen Order list and click
sys is a discrete-time model.
Identify State-Space Model with Input Delay
Load time-domain system response data in the matrix pair
umat7 and
load sdata7 umat7 ymat7 Ts;
Identify a fourth-order state-space model of the data. Specify a known delay of
2 seconds for the first input and
0 seconds for the second input.
nx = 4; sys = ssest(umat7(1:300,:),ymat7(1:300,:),nx,'Ts',Ts,'InputDelay',[2;0]);
Modify Form, Feedthrough, and Disturbance-Model Matrices
Modify the canonical form of the A, B, and C matrices, include a feedthrough term in the D matrix, and eliminate disturbance-model estimation in the K matrix.
Load input-output data and estimate a fourth-order system using the
ssest default options.
load iddata1 z1 sys1 = ssest(z1,4);
Specify the companion form and compare the
A matrix with the default
A matrix.
sys2 = ssest(z1,4,'Form','companion'); A1 = sys1.A
-0.5155 -3.8483 0.6657 -0.2666
5.8665 -2.7285 1.0649 -1.4694
-0.4487 0.9308 -0.6235 18.8148
-0.4192 0.5595 -16.0688 0.5399
A2 = sys2.A
103 ×
0 0 0 -7.1122
0.0010 0 0 -0.9547
0 0.0010 0 -0.3263
0 0 0.0010 -0.0033
Include a feedthrough term and compare
D matrices.
sys3 = ssest(z1,4,'Feedthrough',1);
D1 = sys1.D
D3 = sys3.D
Eliminate disturbance modeling and compare
K matrices.
sys4 = ssest(z1,4,'DisturbanceModel','none'); K1 = sys1.K
K4 = sys4.K
Estimate Initial States as Independent Parameters
ssest initial states as independent estimation parameters.
ssest can handle initial states using one of several methods. By default,
ssest chooses the method automatically based on your estimation data. You can choose the method yourself by modifying the option set using
Load the input/output data
tt1 and estimate a second-order state-space model
sys using the default options. Use the syntax that returns initial states
load sdata1 tt1 [sys,x0] = ssest(tt1,2); x0
x0 = 2×1
By default, the estimation is performed using the
'auto' setting for
InitialState. Find out which method
ssest applied by reviewing the value of
InitialState in
ans = 'zero'
The software applied the
'zero' method, meaning that the software set the initial states to zero instead of estimating them. This selection is consistent with the
0 values returned for
Specify that
ssest estimate the initial states instead as independent parameters using the
'estimate' setting. Use
ssestOptions to create a modified option set and specify that option set to estimate a new model.
opt = ssestOptions('InitialState','estimate'); [sys1,x0] = ssest(tt1,2,opt); x0
x0 = 2×1
x0 now has estimated parameters with nonzero values.
Estimate State-Space Model Using Regularization
Obtain a regularized fifth-order state-space model for a second-order system from a narrow bandwidth signal.
Load estimation data.
load regularizationExampleData eData;
Create the transfer function model used for generating the estimation data (true system).
trueSys = idtf([0.02008 0.04017 0.02008],[1 -1.561 0.6414],1);
Estimate an unregularized state-space model.
opt = ssestOptions('SearchMethod','lm'); m = ssest(eData,5,'form','modal','DisturbanceModel','none','Ts',eData.Ts,opt);
Estimate a regularized state-space model.
opt.Regularization.Lambda = 10; mr = ssest(eData,5,'form','modal','DisturbanceModel','none','Ts',eData.Ts,opt);
Compare the model outputs with the estimation data.
Compare the model impulse responses.
impulse(trueSys,m,mr,50); legend('trueSys','m','mr');
Estimate Partially Known State-Space Model Using Structured Estimation
Configure the parameter constraints and initial values for state-space model estimation.
Create an
idss model to specify the initial parameterization for estimation.
A = blkdiag([-0.1 0.4; -0.4 -0.1],[-1 5; -5 -1]); B = [1; zeros(3,1)]; C = [1 1 1 1]; D = 0; K = zeros(4,1); x0 = [0.1 0.1 0.1 0.1]; Ts = 0; init_sys = idss(A,B,C,D,K,x0,Ts);
Setting all entries of
K to
0 creates an
idss model with no state disturbance element.
Use the
Structure property to fix the values of some of the model parameters. Configure the model so that
B and
K are fixed, and only the nonzero entries of
A are estimable.
init_sys.Structure.A.Free = (A~=0); init_sys.Structure.B.Free = false; init_sys.Structure.K.Free = false;
The entries in
init_sys.Structure.A.Free determine whether the corresponding entries in
init_sys.A are free (
true) or fixed (
Load the measured data and estimate a state-space model using the parameter constraints and initial values specified by
load sdata2 tt2; sys = ssest(tt2,init_sys);
The estimated parameters of
sys satisfy the constraints specified by
Input Arguments
tt — Timetable-based estimation data
timetable | cell array of timetables.
Estimation data, specified as a uniformly sampled
timetable that contains variables representing input and output channels or, for
multiexperiment data, a cell array of timetables.
Use Entire Timetable
If you want to use all the variables in
tt as input or output
channels, and the variables are organized so that the set of input channel variables is
followed by the set of output channel variables, then:
For SISO systems, specify
ttas an Ns-by-2 timetable, where Ns is the number of samples and the two timetable variables represent the measured input channel and output channel respectively.
For MIMO systems, specify
ttas an Ns-by-(Nu+Ny) timetable, where Nu is the number of inputs and Ny is the number of outputs. The first Nu variables must contain the input channels and the remaining Ny variables must contain the output channels.
When you are estimating state space or transfer function models, you must also explicitly specify the input and output channels, as the following section describes.
For multiexperiment data, specify data as an Ne-by-1 cell array of timetables, where Ne is the number of experiments. The sample times of all the experiments must match.
Use Selected Variables from Timetable
If you want to explicitly identify the input and output channels, such as when you want
to use only a subset of the available channels, when the input and output channel variables
are intermixed, or when you are estimating a MIMO state-space or transfer function model,
use the
'InputName' and
'OutputName' name-value
arguments to specify which variables to use as inputs and outputs.
For example, suppose that
tt contains six channel variables:
"u3", and
"y3". For estimation,
you want to use the variables
"u1" and
"u2" as the
inputs and the variables
"y1" and
"y3" as the outputs.
Use the following command to perform the estimation:
sys = ssest(tt,__,'InputName',["u1" "u2"],'OutputName',["y1"
Use Timetable to Estimate Time Series Models
If you want to estimate a time series model rather than an input/output model, use only
output variables from
tt. You can either specify
tt to contain only the output variables that you want, or extract the
output variables from
tt if
tt also contains input
variables. The specification approach is similar to that for input/output model
For a single-output system, specify
ttas an Ns-by-1 timetable.
For a multivariate system, specify
ttas an Ns-by-(Ny) timetable. Even if you plan to use all the variables in
tt, you must specify all of them using the
'OutputName'name-value argument so that the software does not interpret them as input variables.
For a timetable
tt that has variables beyond what you want to use,
such as input variables or additional output variables, specify both the output variables
you want to use and, in
'InputName', an empty array.
For example, suppose that
tt contains six variables:
"u3", and
"y3". For time series
estimation, you want to use the output variables
"y1" and
"y3". Use the following command to perform the estimation:
sys = ssest(tt,__,'OutputName',["y1"
For more information about working with estimation data types, see Data Domains and Data Types in System Identification Toolbox.
y — Matrix-based estimation data
matrices | cell array of matrices
Estimation data, specified for SISO systems as a comma-separated pair of Ns-by-1 real-valued matrices that contain uniformly sampled input and output time-domain signal values. Here, Ns is the number of samples.
For MIMO systems, specify
y as an
input/output matrix pair with the following dimensions:
u— Ns-by-Nu, where Nu is the number of inputs.
y— Ns-by-Ny, where Ny is the number of outputs.
For multiexperiment data, specify
y as a
pair of 1-by-Ne cell arrays, where
Ne is the number of experiments. The
sample times of all the experiments must match.
For time series data, which contains only outputs and no inputs, specify
Matrix-based data does not support estimation from frequency-domain data. You must use a data object such as an
iddataobject or
idfrdobject (see
Using matrices for estimation data is not recommended for continuous-time estimation because the data does not provide the sample time. The software assumes that the data is sampled at 1 Hz. For continuous-time estimation, it is recommended that you convert each matrix to a
timetable. For example, to convert the matrices
ymto a
ttwith a sample time of 0.5 minutes, use the following command.For a more detailed example of converting matrix-based SISO data to a timetable, see Convert SISO Matrix Data to Timetable. For an example of converting a MIMO matrix pair to a timetable, see Convert MIMO Matrix Data to Timetable for Continuous-Time Model Estimation.
tt = timetable(um,ym,'rowtimes',minutes(0.5*(1:size(u,1))))
For more information about working with estimation data types, see Data Domains and Data Types in System Identification Toolbox.
data — Estimation data object
iddata object |
frd object |
idfrd object
Estimation data object, specified as an
iddata object, an
frd object, or an
idfrd object that contains
uniformly sampled input and output values. By default, the software sets the sample time
of the model to the sample time of the estimation data.
For multiexperiment data, the sample times and intersample behavior of all the experiments must match.
For time-domain estimation,
data must be an
iddata object containing the input and output signal values.
For frequency-domain estimation,
data can be one of the
You cannot estimate continuous-time models using discrete-time frequency-domain data.
nx — Order of estimated model
1:10 (default) | positive integer scalar | positive integer vector |
Order of the estimated model, specified as a nonnegative integer or as a vector containing a range of positive integers.
If you already know what order you want your estimated model to have, specify
nxas a scalar.
If you want to compare a range of potential orders to choose the most effective order for your estimated model, specify the range in
ssestcreates a Hankel singular-value plot that shows the relative energy contributions of each state in the system. States with relatively small Hankel singular values contribute little to the accuracy of the model and can be discarded with little impact. The index of the highest state you retain is the model order. The plot window includes a suggestion for the order to use. You can accept this suggestion or enter a different order. For an example, see Determine Optimal Estimated Model Order.
If you do not specify
nx, or if you specify
best, the software automatically chooses
nxfrom the range
If you are identifying a static system, set
opt — Estimation options
ssestOptions option set
Estimation options, specified as an
ssestOptions option set. Options specified by
Estimation objective
Handling of initial conditions
Numerical search method used for estimation
Intersample behavior
For examples showing how to use
opt, see Estimate Initial States as Independent Parameters and Estimate State-Space Model Using Regularization.
init_sys — Linear system that configures initial parameterization of sys
idss model | linear model | structure
Linear system that configures the initial parameterization of
sys, specified as an
idss model or as a structure. You obtain
init_sys by
either performing an estimation using measured data or by direct construction.
init_sys is an
idss model,
ssest uses the parameter values of
as the initial guess for estimating
sys. For information on how to
idss, see Estimate State-Space Models with Structured Parameterization.
ssest honors constraints on the parameters of
init_sys, such as fixed coefficients and minimum/maximum bounds.
Use the
Structure property of
init_sys to
configure initial parameter values and constraints for the A,
B, C, D, and
K matrices. For example:
To specify an initial guess for the A matrix of
init_sys, set
init_sys.Structure.A.Valueas the initial guess.
To specify constraints for the B matrix of
init_sys.Structure.B.Minimumto the minimum B matrix value
init_sys.Structure.B.Maximumto the maximum B matrix value
init_sys.Structure.B.Freeto indicate if entries of the B matrix are free parameters for estimation
To set more complex constraints, such as interdependence of coefficients, use grey-box estimation using
You must assign finite initial values for all matrix parameters.
init_sys is not a state-space (
idss) model, the software first converts
init_sys to an
idss model.
ssest uses the parameters of the
resulting model as the initial guess for estimation.
If you do not specify
opt and
init_sys was
obtained by estimation, then the software uses estimation options from
For an example, see Estimate Partially Known State-Space Model Using Structured Estimation.
Name-Value Arguments
Specify optional pairs of arguments as
Name1=Value1,...,NameN=ValueN, where
Name is
the argument name and
Value is the corresponding value.
Name-value arguments must appear after other arguments, but the order of the
pairs does not matter.
Before R2021a, use commas to separate each name and value, and enclose
Name in quotes.
sys = ssest(data,nx,'Ts',0.1)
InputName — Input channel names
string | character vector | string array | cell array of character vectors
Input channel names, specified as a string, character vector, string array, or cell array of character vectors.
If you are using a timetable for the data source, the names in
InputName must be a subset of the timetable variables.
sys = ssest(tt,__,'InputName',["u1" "u2"]) selects
the variables
u1 and
u2 as the input channels from
the timetable
tt to use for the estimation.
OutputName — Output channel names
string | character vector | string array | cell array of character vectors
Output channel names, specified as a string, character vector, string array, or cell array of character vectors.
If you are using a timetable for the data source, the names in
OutputName must be a subset of the timetable variables.
sys = ssest(tt,__,'OutputName',["y1" "y3"]) selects
the variables
y1 and
y3 as the output channels
from the timetable
tt to use for the estimation.
Ts — Sample time of estimated model
0 (continuous time) (default) | sample time of data | positive scalar
Sample time of the estimated model, specified as the comma-separated pair consisting of
'Ts' and either
0 or a positive scalar.
For continuous-time models, specify
For discrete-time models, specify
'Ts'as the data sample time in units defined by the following:
For timetable-based data — The timetable
For matrix-based data — Seconds
For data objects, such as
iddataobjects — The
To obtain the data sample time for a timetable
tt, use the
timetable property
InputDelay — Input delays
(default) | scalar | vector
Input delay for each input channel, specified as the comma-separated pair
consisting of
'InputDelay' and a numeric vector.
For continuous-time models, specify
'InputDelay'in the time units stored in the timetable, the data object
TimeUnitproperty, or, for matrix data, in seconds.
For discrete-time models, specify
'InputDelay'in integer multiples of the sample time
Ts. For example, setting
3specifies a delay of three sampling periods.
For a system with Nu inputs, set
InputDelay to an
Nu-by-1 vector. Each entry of this vector is
a numerical value that represents the input delay for the corresponding input channel.
For an example, see Identify State-Space Model with Input Delay.
To apply the same delay to all channels, specify
as a scalar.
Form — Type of canonical form
'free' (default) |
'modal' |
'companion' |
Type of canonical form of
sys, specified as the
comma-separated pair consisting of
'Form' and one of the following values:
'free'— All entries of the matrices A, B, C, D, and K are treated as free.
'modal'— Obtain
sysin modal form.
'companion'— Obtain
sysin companion form.
'canonical'— Obtain
sysin the observability canonical form.
For definitions of the canonical forms, see State-Space Realizations.
For more information, see Estimate State-Space Models with Canonical Parameterization. For an example, see Modify Form, Feedthrough, and Disturbance-Model Matrices.
Feedthrough — Direct feedthrough from input to output
0 (default) |
1 | logical vector
Direct feedthrough from input to output, specified as the comma-separated pair
consisting of
'Feedthrough' and a logical vector of length
Nu, where
Nu is the number of inputs. If you
Feedthrough as a logical scalar, that value is applied to
all the inputs. For static systems, the software always assumes
'Feedthrough' is
For an example, see Modify Form, Feedthrough, and Disturbance-Model Matrices.
DisturbanceModel — Option to estimate time-domain noise component parameters
'estimate' (default) |
Option to estimate time-domain noise component parameters in the K matrix,
specified as the comma-separated pair consisting of
'DisturbanceModel' and one of the following values:
'estimate'— Estimate the noise component. The K matrix is treated as a free parameter.
'none'— Do not estimate the noise component. The elements of the K matrix are fixed at zero.
For frequency-domain data, the software assumes that
'DisturbanceModel' is
For an example, see Modify Form, Feedthrough, and Disturbance-Model Matrices.
Output Arguments
sys — Identified state-space model
idss model
Identified state-space model, returned as an
idss model. This model is created using the specified model orders, delays,
and estimation options.
Information about the estimation results and options used is stored in the
Report property of the model.
Report has the
following fields.
|Report Field
Summary of the model status, which indicates whether the model was created by construction or obtained by estimation.
Estimation command used.
How initial states were handled during estimation, returned as one of the following values:
This field is especially useful when the
Weighting scheme used for singular-value decomposition by the N4SID algorithm, returned as one of the following values:
This option is especially useful when the
Forward and backward prediction horizons used by the N4SID algorithm,
returned as a row vector with three elements —
Quantitative assessment of the estimation, returned as a structure. See Loss Function and Model Quality Metrics for more information on these quality metrics. The structure has the following fields:
Estimated values of model parameters.
Option set used for estimation. If no custom options were configured,
this is a set of default options. See
State of the random number stream at the start of estimation. Empty,
Attributes of the data used for estimation. Structure with the following fields:
Termination conditions for the iterative search used for prediction error minimization, returned as a structure with the following fields:
For estimation methods that do not require numerical search optimization,
For more information on using
Report, see Estimation Report.
x0 — Initial states computed during estimation
column vector | matrix
Initial states computed during the estimation, returned as an array containing a column vector corresponding to each experiment.
This array is also stored in the
Parameters field of the model
Report property.
For an example, see Estimate Initial States as Independent Parameters.
ssest initializes the parameter estimates using either a noniterative
subspace approach or an iterative rational function estimation approach. It then refines the
parameter values using the prediction error minimization approach. For more information, see
pem and
[1] Ljung, L. System Identification: Theory for the User, Second Edition. Upper Saddle River, NJ: Prentice Hall PTR, 1999.
Version HistoryIntroduced in R2012a
R2022b: Time-domain estimation data is accepted in the form of timetables and matrices
Most estimation, validation, analysis, and utility functions now accept time-domain
input/output data in the form of a single timetable that contains both input and output data
or a pair of matrices that contain the input and output data separately. These functions
continue to accept
iddata objects as a data source as well, for
both time-domain and frequency-domain data.
R2018a: Advanced Options are deprecated for
SearchOptions when
SearchMethod is
Specification of
lsqnonlin- related advanced options are deprecated,
including the option to invoke parallel processing when estimating using the
lsqnonlin search method, or solver, in Optimization Toolbox™.
See Also
Live Editor Tasks
- Estimate State-Space Models at the Command Line
- Estimate State-Space Models with Free-Parameterization
- Estimate State-Space Models with Canonical Parameterization
- Estimate State-Space Models with Structured Parameterization
- Use State-Space Estimation to Reduce Model Order
- What Are State-Space Models?
- Supported State-Space Parameterizations
- State-Space Model Estimation Methods
- Regularized Estimates of Model Parameters
- Estimating Models Using Frequency-Domain Data


text:
The University of Texas MD Anderson Cancer Center
Peter WT Pisters, M.D., President
Houston, Texas
Main: (713) 792-6161
The University of Texas MD Anderson Cancer Center (MD Anderson) was established by the Texas State Legislature in 1941and is a free-standing, degree-granting health institution within The University of Texas System. Mission areas include patient care, research, education, and prevention. In 1971 MD Anderson became one of the nation's first NCI-designated comprehensive cancer centers. MD Anderson's strength lies in its ability to rapidly translate scientific knowledge into improved cancer therapies and prevention strategies.
MD Anderson houses one of the largest, most developed cancer prevention programs in the nation, conducting research to assess and manage cancer risk through early detection, genetic counseling and clinical interventions, and implementing prevention programs that include genetic testing, chemoprevention, behavioral and nutritional counseling. Translational goals are to develop and deliver comprehensive evidence-based strategies to achieve a measurable lasting reduction in the cancer burden, especially among the underserved.
Cancer is the singular focus for MD Anderson's workforce of more than 19,000 employees with over 1,600 full-time faculty scholars who lead the largest number of NCI-funded grant programs and clinical trials of any institution in the nation. More than 6,500 trainees take part each year in educational programs, including advanced degrees at the Graduate School of Biomedical Science covering training from Cancer Biology to Clinical and Translational Science and bachelor's degrees in allied health disciplines. MD Anderson invested approximately $700 million in research (FY14) which is anticipated to increase with our cancer Moon Shots Program.
The multidisciplinary approach to treating cancer pioneered at MD Anderson brings together teams of experts across disciplines to collaborate on the best treatment plan for patients. A major focus is to increase access to quality cancer care worldwide. This mission is reflected by more than 122,000 patients annually from across the nation and the world who receive care in Houston and 114,000 patients receiving care through our local, national and international affiliations. The global outreach to drive science and improve care also includes academic collaborations with 30 sister institutions in 23 countries as well as the development of a decision support platform known as the MD Anderson Oncology Expert Advisor powered by cognitive computing. Advancing care for patients is also enabled by 800 interventional clinical trial protocols involving more than 12,000 patients each year, engaged in testing approximately one-third of all new FDA-approved cancer drugs. The Institute for Personalized Cancer Therapy and the immune therapy platform provide profiling for more precise patient care and innovative clinical trials.
A goal-oriented Moon Shots Program was launched in 2012 to dramatically accelerate the pace of converting scientific discoveries into clinical advances that would significantly reduce cancer deaths. The program brings together large multi-disciplinary teams focused on high-impact projects that are enabled by professionally-driven technology platforms and resources.
* This profile was provided by the University of Texas MD Anderson Cancer Center.


text:
Published: 03/31/2015 - Updated: 12/29/2017
Author: MSc. Miriam Reyes
Have you ever been told that you need to take cortisone? Do you use it frequently? Before using it, try to see if you truly need it. A lot of times we want to solve things quickly, which could create a long list of unpleasant consequences for the body. There's nothing better than trying to activate the body's healing potential naturally.
There are simple and natural ways of helping the body produce its own cortisol to avoid cortisone, which generally has a long list of undesirable side effects.
Cortisone refers to a synthetic substance or medication that has effects on the body that are similar to those of cortisol. This is a hormone from a group of hormones called corticosteroids, which the human body secretes.
Cortisol in created along with other hormones in the suprarenal glands, located above the kidneys. This group of hormones includes glucocorticoids, which is where cortisone or cortisol is located. They stimulate glucose and remove proteins from all tissue except for the liver, in addition to fats from fatty tissues, towards the blood.
One of the most important functions thatglucocorticoids have is that they are potent inflammation reducers. This makes them useful for treatment severe inflammation, like arthritis, osteoarthritis, muscle tears, etc.
The human body has the ability to create its own anti-inflammatories through the suprarenals, but whenever they begin to fail, the individual usually receives corticoid injections either to reduce pain or inflammation. This will prevent the body from rejecting organ transplants, like a kidney, liver, etc.
Other bodily uses of cortisone are:
Allergy prevention, disease treatment, like asthma, skin conditions, treating nausea and vomiting which could be caused by chemotherapy in cancer patients, etc.
Cortisone's harmful bodily effects
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You need to keep in mind that if you want to use corticoids, the body has the ability to create its own substances. Your body could become lazy and dependent on these medications if you use them frequently and become dependent on them.
Cortisone's prolonged or excessive effects could cause a lot of side effects, like hunchback, diabetes, excessive hair and acne, high blood pressure, weakness, frequent infections, tissue weakness, osteoporosis, etc.
If you want to start creating your own cortisol:
- Reduce your life stress. This is one of the most common causes of poor kidney and suprarenal functioning.
- Try practicing yoga, tai chi, meditation, breathing exercises, etc., all of which help the body free itself of excess energy. You'll be able to concentrate on your activities more peacefully.
- Do not let your time be controlled by hurry. Learn to do your work peacefully and patiently. Don't do too many things at one time and move slowly. Try to enjoy what you're doing.
- Avoid eating junk foods like refined and processed items. These rob the tissues and bodily functions of nutrients.
- Drink at least 2 liters of water a day to keep your kidneys healthy.
- Drink pineapple juice with parsley, lemon and alfalfa daily, in order to help clean excess toxins from the body and to nourish tissues.
- Try to sleep at least 7 to 8 hours a day. the body produces cortisol while you sleep. If you sleep poorly, or if you often times stay up late, or if your sleep is interrupted, your body will lack cortisol and you'll get sick much easier.
- Make your resting place a pleasant environment. Try to isolate yourself from any loud noises. Put of peaceful music and read pleasant things at night. This will help you see life in more grandiose ways.
- Avoid watching action or horror shows at night that stress you out, like the news or political programs. The best way to produce cortisol is to enjoy the things you see or live. It's best to watch shows with countryside or enjoyable images. Watching the news could stress you out, and make you think a lot while sleeping.
- Consuming citrus fruits and raw, green vegetables increases your cortisol levels. This will help cleanse your body.
- Fatty foods, or foods with refined or white sugar, prevent cortisol production.
- Consuming licorice helps increase cortisol levels in the body, little by little. Try to find a licorice supplement in a health food store or an herb shop.
- Avoid arguing or eating when you're angry or anxious, as this could be very harmful for your body and nervous system.
Herbs that aid relaxation and predispose the body to cortisol production:
Orange blossom, Melissa, cat's claw, horse tail, chamomile, and mint, etc.
MORE IN THE JOY OF WELLNESSHow to Make Fermented Food; Youth Activators
Revised by: Dra. Loredana Lunadei on 12/29/2017
About the author


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Exhilarating to watch the dolphins ride the waves, back and forth. It was a low tide so it was possible to walk out far to get a bit closer...a treat on such a spectacular day.
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Connect via USB and you can use the SubConnect Audio Monitor app for a variety of settings. Four fully configurable settings include modes for Plane/Music/Movie and Impact. Refine these settings by adjusting the frequency, slope, adjustment and equalization filters and you have a subwoofer that's perfectly suited to your tastes. If you want to check the sub to listen late at night, simply select "Night Mode" to reduce the dynamics.
Choosing luxury finishes
Once you've decided on this subwoofer, the hardest part is choosing which of the sumptuous finishes to choose from. Choose Black Walnut or Ebony Piano for a rich and traditional style or Piano Gloss Black or Satin White for more contemporary appeal. Whichever color you choose, you can make sure The Audio Monitor is the usual immaculate fit and finish of Monitor Audio. Photo:Monitor Audio
Increase your home theater experience with the W12 Audio Audio Monitor subwoofer.
Monitor Audio Gold W12 Specs:
System Format
Long-throw 12″ driver featuring 'dished' C-CAM cone. Dual 200 mm ABR (auxiliary bass radiator). Front baffle 36 mm, cabinet 25 mm MDF construction with internal bracing and sealed amplifier compartment
Lower Frequency Limit
-3 dB @ 25 Hz / -10 dB @ 20 Hz (Free Field). Music preset (Default): -3 dB @ 19 Hz / -10 dB @ 16 Hz (In Room). Assignable Low Frequency Limit Protection Filter: -3 dB @ 12 Hz
Upper Frequency Limit
-3 dB @ 150 Hz
Drive Unit Complement
1 x 12″ C-CAM subwoofer driver featuring triple suspension and 3″ long throw voice coil
Linear Driver Excursion
19 mm Peak to Peak,
Total displacement 1.6 Litres
Amplifier Output
Amplifier Classification
Class D with high current Switch mode power supply (SMPSU)
50 MIPS DSP Core giving 512 instructions per sample, 138 dB of dynamic range and 56-bit double precision processing, dynamically updated by an up to 50 MHz MCU
Digital Conversion
24 bit/up to 48 kHz ADCs & DACs built into ADAU1701 DSP Core
LED UI Control Panel
Adjustable brightness 0% – 100%, configurable auto off feature. Quick access to menu items: Trim & Mute, LPF, Phase, Preset Select
Global Settings (via SubConnect)
Display Brightness (0-100%), Dim (to 10% or to Off), Default Preset, Mute Link Outputs, 12 V Trigger Assignment (Power On / Off or Preset select), Input gain (Master -80 to +20 dB, Trim -11 to +11 dB, Mute), Phase (0 – 360 in 15-degree steps), Night Mode Threshold (0 dB to -36 dB), Auto On / Off (Enable Signal Sense, Always On, Time to off 5 – 240 mins)
User Presets (via SubConnect)
4 fully configurable user Presets including, Preset Name, LPF Frequency (5 Hz Steps from 20 – 135 Hz), LPF Slope Order (-12 or -24 dB/Oct), Input (Stereo, LFE or Both), Trim Offset (-6 to +6 dB), EQ mode (Impact, Music, Movie or Default), User EQ (6 adjustable filters applied on top of EQ mode), Room EQ (On / Off), Night Mode (On / Off)
User Equalisation (via SubConnect)
6 fully controllable EQ filters and 4 default filters with gain offset per preset, Voreinstellungen: Flat / Music / Movie / Impact
Room Correction EQ
6 System controlled parametric EQ filters set using advanced detection algorithm. Measurement can be initiated from the control panel or the SubConnect with up to microphone 6 positions (default 2)
Night Mode
Night mode, assignable (On or Off) per Preset with global threshold (0 dB to -36 dB). Introduces dynamic range reduction lowering the level of loud sections
Phase Control
0 – 360 degrees Increments of 15 degrees with a pure invert at 180 degrees
Low Pass Filter Alignment
2nd or 4th order (12 or 24 dB/Octave), Increments of 5 Hz from 35 Hz to 135 Hz
Auto Sensing Input Requirements
Line Level >1mV on unbalanced and balanced inputs. Auto Standby feature, adjustable between 5 – 240 minutes in increments of 5 minutes
Digital Volume Level
-11 to +11 dB in 1 dB increments, via the control panel. -80 to +20 in 1 dB increments, via SubConnect application
IR Remote Control Code
Supplied IR remote. Front facing IR receiver with red LED indication
SubConnect (PC Application)
Windows (7 onwards) (32/64 bit) compatible setup application available from the Monitor Audio website. Allows the user to control advanced subwoofer setup features. Settings can be saved while not connected to the subwoofer for off-site setup
Audio Input/Outputs
LFE balanced input (XLR), LFE unbalanced input (RCA), stereo unbalanced inputs (RCA). LFE balanced output (XLR), LFE unbalanced output (RCA), stereo unbalanced outputs (link RCA)
12 V Trigger in (3.5 mm mono mini-jack, 6 V threshold), assignable to On/Off or Pre-set change, 3.5 mm Microphone input jack (mic supplied), RJ45 connector supporting RS232 (EIA/TIA – 561, Tx Pin 6, Rx Pin 5, Gnd Pin 4), IR repeater – Output (3.5 mm mono mini-jack), USB – Type B, for connecting to SubConnect PC application and Firmware update
Electrical Certifications
CE / CB/ ETL / Fcc / CCC/ ErP (Energy saving compliant)
Mains Input Voltage
100 – 120 Vac ~60Hz / 220 – 240 Vac ~50/60 Hz (Manually selected)
Power Consumption
Maximum 600 W, Standby <0.5 W (ErP compliance)
Fuse Type
20 mm T8AL 250 VAC