102 research outputs found
Lower and Upper Bounds for Nonzero Littlewood-Richardson Coefficients
Given a skew diagram , we determine a set of lower and upper
bounds that a partition must satisfy for Littlewood-Richards coefficients
. Our algorithm depends on the characterization of
as the number of Littlewood-Richardson tableau of
shape and content and uses the (generalized) dominance
order on partitions as the main ingredient
Gelişimsel Krize Müdahalede Kısa-Yoğun-Acil Psikoterapinin Kullanımı: Bir Olgu Sunumu
Yaşam dönemleri düşünüldüğünde, gelişimsel krizlerin bireyleri etkilemesi beklendiktir. Buna rağmen, gelişimsel krizlere zamanında ve etkili şekilde müdahalede bulunulmazsa, üstesinden gelinmesi daha zor krizlere dönüşebilmektedir. Bu nedenle zaman zaman sorun yaşayan bireyler, yaşadıkları sorunları çözmek için profesyonel bir destek aramaktadır. Bu çalışmanın amacı; depresyon, yas ve travmatik sorunlarda başarıyla kullanılan dinamik yönelimli kısa – yoğun – acil psikoterapi uygulamasını, gelişimsel kriz yaşayan bir üniversite öğrencisinin sorunu üzerinden betimlemektir. Bu çalışmada psikoterapi araştırmaları için önem arz eden bir yöntem olan vaka çalışması yöntemi kullanılmıştır. Bu bağlamda, psikoterapi almaya gönüllü bir üniversite öğrencisi ile dokuz oturumluk kısa – yoğun – acil psikoterapi uygulaması gerçekleştirilmiştir. Danışana Semptom Tarama Listesi (SCL–90 R), Hacettepe Kişilik Envanteri (HKE), Beck Depresyon Envanteri (BDE), Beier Cümle Tamamlama Testi B Formu öntest – sontest – izleme testi olarak uygulanmıştır. Araştırmada kullanılan ölçme araçları psikoterapi sürecine dair nicel verileri ortaya koyarken, anamnestik görüşmeler ve terapi oturumları sürece dair nitel verileri ortaya koymuştur. Ardından bu veriler nitel içerik analizine tabi tutulmuştur. Sonuç olarak bu terapi yönteminin, danışanın sorunlarının çözümünde etkili olduğu tespit edilmiştir.Publisher's Versio
Renormalization Group Analysis of a Gursey Model Inspired Field Theory II
Recently a model, which is equivalent to the scalar form of Gursey model, is
shown to be a nontrivial field theoretical model when it is gauged with a SU(N)
field. In this paper we study another model that is equivalent to the vector
form of the Gursey model. We get a trivial theory when it is coupled with a
scalar field. This result changes drastically when it is coupled with an
additional SU(N) field. We find a nontrivial field theoretical model under
certain conditions.Comment: 10 pages, 10 figures, revtex4, typos corrected, published versio
Unpublished Mediterranean and Black Sea records of marine alien, cryptogenic, and neonative species
To enrich spatio-temporal information on the distribution of alien, cryptogenic, and neonative species in the Mediterranean and the Black Sea, a collective effort by 173 marine scientists was made to provide unpublished records and make them open access to the scientific community. Through this effort, we collected and harmonized
a dataset of 12,649 records. It includes 247 taxa, of which 217 are Animalia, 25 Plantae and 5 Chromista, from 23 countries surrounding the Mediterranean and the Black Sea. Chordata was the most abundant taxonomic group, followed by Arthropoda, Mollusca, and Annelida. In terms of species records, Siganus luridus, Siganus rivulatus,
Saurida lessepsianus, Pterois miles, Upeneus moluccensis, Charybdis (Archias) longicollis, and Caulerpa cylindracea were the most numerous. The temporal distribution of the records ranges from 1973 to 2022, with 44% of the records in 2020–2021. Lethrinus borbonicus is reported for the first time in the Mediterranean Sea, while Pomatoschistus quagga, Caulerpa cylindracea, Grateloupia turuturu, and Misophria pallida are first records for the Black Sea; Kapraunia schneideri is recorded for the second time in the Mediterranean and for the first time in Israel; Prionospio depauperata and Pseudonereis anomala are reported for the first time from the Sea of Marmara. Many first country records are also included, namely: Amathia verticillata (Montenegro), Ampithoe valida (Italy), Antithamnion amphigeneum (Greece), Clavelina oblonga (Tunisia and Slovenia), Dendostrea cf. folium (Syria), Epinephelus fasciatus (Tunisia), Ganonema farinosum (Montenegro), Macrorhynchia philippina (Tunisia), Marenzelleria neglecta (Romania), Paratapes
textilis (Tunisia), and Botrylloides diegensis (Tunisia)
A comparative ID migraine screener study in ophthalmology, ENT and neurology out-patient clinics
Migraine is more likely to be misdiagnosed in patients with comorbid diseases. Not only primary care physicians, but also specialists might misdiagnose it due to the lack of diagnostic criteria awareness. The ID migraine test is a reliable screening instrument that may facilitate and accelerate migraine recognition. This study aimed to compare the prevalence and characteristics of migraine in a large sample of patients admitted to clinics of ophthalmology (OC), ear, nose and throat diseases (ENTC) and neurology (NC), as well as to validate the use of the ID migraine test in OC and ENTC settings. This was a multicentre (11 cites) study of out-patients admitting either to NC, ENTC or OC of the study sites during five consecutive working days within 1 week. From each of the clinics, 100 patients were planned to be recruited. All recruited patients were interviewed and those having a headache complaint received an ID migraine test and were examined for headache diagnosis by a neurologist, blinded to the ID migraine test result. A total of 2625 subjects were recruited. Only 1.3% of OC patients and 5.4% of ENTC patients have been admitted with a primary complaint of headache, whereas the percentage of NC patients suffering from headache was 37.6%. Whereas 138 patients (19.3%) in OC, 154 (17.3%) in ENTC and 347 (34%) in NC were found to be ID migraine test positive, 149 patients (20.8%) in OC, 142 (16%) in ENTC and 338 (33.1%) in NC were diagnosed with migraine. The sensitivity, specificity, and positive and negative predictive ratios of the ID migraine test were found to be similar in all clinics. An important fraction of the patients admitted to NC, as well as to OC and ENTC, for headache and/or other complaints were found out to have migraine by means of a simple screening test. This study validated the ID migraine test as a sensitive and specific tool in OC and ENTC, encouraging its use as a screening instrument.Pfizer-Türkiy
The Amsterdam Declaration on Fungal Nomenclature
The Amsterdam Declaration on Fungal Nomenclature was agreed at an international symposium convened in Amsterdam on 19–20 April 2011 under the auspices of the International Commission on the Taxonomy of Fungi (ICTF). The purpose of the symposium was to address the issue of whether or how the current system of naming pleomorphic fungi should be maintained or changed now that molecular data are routinely available. The issue is urgent as mycologists currently follow different practices, and no consensus was achieved by a Special Committee appointed in 2005 by the International Botanical Congress to advise on the problem. The Declaration recognizes the need for an orderly transitition to a single-name nomenclatural system for all fungi, and to provide mechanisms to protect names that otherwise then become endangered. That is, meaning that priority should be given to the first described name, except where that is a younger name in general use when the first author to select a name of a pleomorphic monophyletic genus is to be followed, and suggests controversial cases are referred to a body, such as the ICTF, which will report to the Committee for Fungi. If appropriate, the ICTF could be mandated to promote the implementation of the Declaration. In addition, but not forming part of the Declaration, are reports of discussions held during the symposium on the governance of the nomenclature of fungi, and the naming of fungi known only from an environmental nucleic acid sequence in particular. Possible amendments to the Draft BioCode (2011) to allow for the needs of mycologists are suggested for further consideration, and a possible example of how a fungus only known from the environment might be described is presented
Deep context of citations using machine‑learning models in scholarly full‑text articles
Information retrieval systems for scholarly literature rely heavily not only on text matching but on semantic- and context-based features. Readers nowadays are deeply interested in how important an article is, its purpose and how influential it is in follow-up research work. Numerous techniques to tap the power of machine learning and artificial intelligence have been developed to enhance retrieval of the most influential scientific literature. In this paper, we compare and improve on four existing state-of-the-art techniques designed to identify influential citations. We consider 450 citations from the Association for Computational Linguistics corpus, classified by experts as either important or unimportant, and further extract 64 features based on the methodology of four state-of-the-art techniques. We apply the Extra-Trees classifier to select 29 best features and apply the Random Forest and Support Vector Machine classifiers to all selected techniques. Using the Random Forest classifier, our supervised model improves on the state-of-the-art method by 11.25%, with 89% Precision-Recall area under the curve. Finally, we present our deep-learning model, the Long Short-Term Memory network, that uses all 64 features to distinguish important and unimportant citations with 92.57% accuracy
Selection of PolSAR Observables for Crop Biophysical Variable Estimation With Global Sensitivity Analysis
The role of global sensitivity analysis (GSA) is to quantify and rank the most influential features for biophysical variable estimation. In this letter, an approximation model, called high-dimensional model representation (HDMR), is utilized to develop a regression method in conjunction with a GSA in the context of determining key input drivers in the estimation of crop biophysical variables from polarimetric synthetic aperture radar data. A multitemporal Radarsat-2 data set is used for the retrieval of three biophysical variables of barley: leaf area index, normalized difference vegetation index, and Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie stage. The HDMR technique is first adopted to estimate a regression model with all available polarimetric features for each biophysical parameter, and sensitivity indices of each feature are then derived to explain the original space with a smaller number of features in which a final regression model is established. To evaluate the applicability of this methodology, root-mean square and coefficient of determination were performed under different amounts of samples. Results highlight that HDMR can be used effectively in biophysical variable estimation for not only reducing computational cost but also for providing a robust regression
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