Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence of anxiety and depressive symptoms among patients with hypothyroidism

Context: The association between depression and thyroid function is well known. Both conditions express many similar symptoms, thus making the diagnosis and treatment difficult. Aims: To find the prevalence of anxiety and depressive symptoms among patients with hypothyroid. Settings and Design: Cross-sectional study. Materials and Methodology: A total of 100 patients diagnosed as hypothyroidism were evaluated using Hamilton depression rating scale (HDRS) and Hamilton scale for anxiety (HAM-A). Statistical Analysis Used: The data were analyzed using the SPSS for Windows version 17.0 software. The quantitative data were expressed in number and percentage. The results obtained were compared using the Chi-square test. Results: Females constituted 70% of the sample. A total of 60% reported some degree of depression based on HDRS (males – 56.63% and females – 64.29%) whereas about 63% out of the total patients screened showed some degree of anxiety (males –56.66% and females – 65.72%) based on HAM-A. The most common depressive symptom among the males was depressed mood (73.33%) and among females was gastrointestinal somatic symptoms (68.54%). The most common anxiety symptom among the males was depressed mood (70.0%) and among females was anxious mood (92.85%). Conclusions: Psychiatric symptoms/disorders are common in patients with thyroid dysfunction.
Vertex Nomination Via Local Neighborhood Matching

Let G and G' be two graphs on potentially different vertex sets such that a subset of the vertices of G correspond to a subset of the vertices of G'. Given vertices of interest in G, we seek to identify the corresponding vertices, if any exist, in the second network G'. While in moderately sized networks graph matching methods can be applied directly to recover the missing correspondences, herein we present a principled methodology appropriate for situations in which the networks are too large for brute-force graph matching. Our methodology identifies vertices in a local neighborhood of the vertices of interest in the first network that have verifiable corresponding vertices in the second network. Leveraging these known correspondences, referred to as seeds, we match the induced subgraphs in each network generated by the neighborhoods of these verified seeds, and rank the vertices of the second network in terms of the most likely matches to the original vertices of interest. We demonstrate the applicability of our methodology through simulations and real data examples.
Osteosarcoma Segmentation in MRI Based on Zernike Moment and SVM

Osteosarcoma is primary malignant neoplasms derived from cells of mesenchymal origin, and often has distinct phenotypes at different stages. The location of tumor and reaction zone can be identified by an expert in magnetic resonance imaging (MRI), with MRI being one of the choices for evaluating the extent of osteosarcoma. However, it is still a challenge to automatically extract tumor from its surrounding tissues because of their low intensity differences in MRI. We investigated an approach based on Zernike moment and support vector machine (SVM) for osteosarcoma segmentation in T1-weighted image (TIWI). Firstly, the different order moments around each pixel are calculated in small windows. Secondly, the grayscale and the module values of different order moments are used as a texture feature vector which is then used as the training set for SVM. Finally, an SVM classifier is trained based on this set of features to identify the osteosarcoma, and the segmented tumor tissue is rendered in 3D by the ray casting algorithm based on graphics processing unit (GPU). The performance of the method is validated on T1WI, showing that the segmentation method has a high similarity index with the expert’s manual segmentation.
Doppler Radar Analysis of a Tornadic Miniature Supercell during the Landfall of Typhoon Mujigae (2015) in South China

AbstractOn 4 October 2015, a miniature supercell embedded in an outer rainband of Typhoon Mujigae produced a major tornado in Guangdong province of China, leading to 4 deaths and up to 80 injuries. This study documents the structure and evolution of the tornadic miniature supercell using coastal Doppler radars, a sounding, videos, and a damage survey. This tornado is rated at least EF3 on the enhanced Fujita scale. It is by far the strongest typhoon rainband tornado yet documented in China, and possessed double funnels near its peak intensity.Radar analysis indicates that this tornadic miniature supercell exhibited characteristics similar to those found in United States landfalling hurricanes, including a hook echo, low-level inf low notches, an echo top below 10 km, a small and shallow mesocyclone, and a long lifespan (3 h). The environmental conditions—which consisted of moderate convective available potential energy (CAPE), a low lifting condensation level, a small surface dewpoint depression, a large .
Some Properties Of Meson Excited States From Lattice QCD

The work presented here is devoted to the calculations of the decay constants of the pion and its excited states. All calculations were carried out in the framework of lattice quantum chromodynamics, a well-established formalism of strong interactions enabling the ab initio solution of the theory. After a short introduction and review of the fundamental approaches and methods commonly used in lattice QCD, I provide a detail description of the numerical simulations which were performed at three values of the pion mass between 400 and 700 MeV, using an anisotropic clover fermion action with three flavors of quarks. The results obtained indicate th a t the decay constant of the first excitation, and more notably of the second, is suppressed with respect to that of the ground-state pion, but th a t the suppression shows little dependence on the quark mass. The second part of this thesis is focused on applications of the methods of perturbation theory to lattice QCD. Here, I give some motivation, and describe the main techniques of perturbative calculations on the lattice, emphasizing its distinctions from the continuum counterpart. I then employ the same anisotropic clover action th a t was used in numerical study for derivation of lattice Feynman rules which might be used for the calculations of the renormalization param eters helping to connect bare lattice results with real physics.
Optimum Design of Frequency-Response-Masking Filters Using Convex-Concave Procedure

The class of frequency-response-masking (FRM) filters, first investigated by Y.C. Lim in 1980s, has shown to provide considerably improved performance for the design of finite impulse response (FIR) filters with narrow transition bandwidth relative to its conventional counterparts. In this project report, we present a design method for FRM filters by using a technique known as convex-concave procedure (CCP). For illustration purposes, we begin by reviewing several basic concepts and properties of FIR filters as well as a popular design technique based on windowed Fourier series. This is followed by a chapter to introduce the structure of basic FRM filters and to explain how they work. The CCP is then studied in the next chapter as an effective heuristic for nonconvex constrained optimization problems. In the last chapter, we present a formulation procedure that converts a frequency-weighted minimax design of FRM filters to a problem which can be solved by iteratively performing CCP. Simulation runs are included to illustrate the proposed algorithm and evaluate the design performance in comparison with those achieved by several existing methods.
Neuromuscular electrical stimulation for preventing skeletal-muscle weakness and wasting in critically ill patients

Background: Neuromuscular electrical stimulation (NMES) therapy may be useful in early musculoskeletal rehabilitation during acute critical illness. The objective of this systematic review was to evaluate the effectiveness of NMES for preventing skeletal-muscle weakness and wasting in critically ill patients, in comparison with usual care. Methods: We searched PubMed, CENTRAL, CINAHL, Web of Science, and PEDro to identify randomized controlled trials exploring the effect of NMES in critically ill patients, which had a well-defined NMES protocol, provided outcomes related to skeletal-muscle strength and/or mass, and for which full text was available. Two independent reviewers extracted data on muscle-related outcomes (strength and mass), and participant and intervention characteristics, and assessed the methodological quality of the studies. Owing to the lack of means and standard deviations (SDs) in some studies, as well as the lack of baseline measurements in two studies, it was impossible to conduct a full meta-analysis. When means and SDs were provided, the effect sizes of individual outcomes were calculated, and otherwise, a qualitative analysis was performed. Results: The search yielded 8 eligible studies involving 172 patients. The methodological quality of the studies was moderate to high. Five studies reported an increase in strength or better preservation of strength with NMES, with one study having a large effect size. Two studies found better preservation of muscle mass with NMES, with small to moderate effect sizes, while no significant benefits were found in two other studies. Conclusions: NMES added to usual care proved to be more effective than usual care alone for preventing skeletal-muscle weakness in critically ill patients. However, there is inconclusive evidence for its benefit in prevention of muscle wasting.
Seismological constraints on inner core properties

We constrain seismic properties of the inner core using various body wave observations. In the epicentral distance range of 10−70 o , our high quality measurements of the amplitude ratio of PKiKP and PcP provide a new estimate of the density contrast (0.6-0.9 g/cm 3) at the Inner Core Boundary (ICB). This estimate is compatible with a recent reevaluation of normal mode data, and thus reconciles the long-term discrepancy between body wave and normal mode measurements. Our Q α study based on the amplitude ratio of PKIKP and PKiKP reveals an attenuation transition at the top of the inner core. In the western hemisphere Q α decreases first with depth from the ICB and then turns to increase at a depth of ∼ 85km, and in the eastern hemisphere we infer that the attenuation transition takes place at the top ∼ 32km beneath the ICB. We find high Q α and low velocity in the western hemisphere, and low Q α and high velocity in the eastern hemisphere. This remarkable hemispherical pattern starts to disappear at a depth of ∼ 85km. This might constrain the depth extent of the mushy zone at the top of the inner core. Taking advantage of the long-term high quality broadband Gräf enberg seismic array, we observed a reliable inner core shear wave phase PKJKP. Four kinds of evidence (travel time, slowness, back-azimuth, and comparison with a pseudo-liquid inner core model) are jointly presented. The high signal-to-noise waveform of PKJKP, for the first time, gives us an opportunity to constrain the inner core shear wave velocity and attenuation directly using body waves. The envelope modeling results suggest that, in the inner core, the shear wave velocity 2 may be slightly faster (∼ 1.5%) and Q β may be significantly larger (∼ 315 ± 150) than obtained from normal mode observations. Taking into account the fact that normal mode data mainly sample the shallow portion of the inner core and PKJKP samples the central part, this implies that both shear wave velocity and Q β increase with depth in the inner core.
Automatic Detection of Abstract–Concrete Relationships between Attack Patterns of ATT&CK and CAPEC with Fine-tuned BERT

Security threats and attacks have recently increased in complexity, requiring rapid understanding of vulnerabilities and responses to attacks. ATT&CK and CAPEC are databases that compile attack patterns against vulnerabilities and help develop countermeasures and defenses in the security domain. Although the relationships between attack patterns are defined in these databases, the databases are manually manipulated, potentially resulting in delays in reflecting information and in relationship omissions. This paper proposes applying fine-tuned bidirectional encoder representations from transformers (BERT) to use ATT&CK, CAPEC, and their combined datasets to detect abstract–concrete relationships between attack patterns. In our evaluation, the model trained on the combined dataset of ATT&CK and CAPEC achieved the highest accuracy. For the models trained on each individual dataset, differences in the similarity of the attack pattern pair descriptions between ATT&CK and CAPEC resulted in differences in the accuracy of the binary classification task.
Antonymy in Contrast Relations.

In this paper we report on experiments to determine if antonymy is a good predictor of contrast, using 124 texts from the British National Corpus and the antonymy relations for adjectives recognized by WordNet. Further, we considered whether antonyms are key arguments in the inferences that license contrast. We looked at the frequency of both indirect and direct antonym pairs in contrastive sentences marked with but and sentences with antonym pairs without but. Antonyms and but co-occurred in only 1% of the 218,017 sentences studied. However, in 81% of but marked sentences with true antonyms pairs, the feature the antonyms described was a source of the contrast. In the non-but marked sentences, antonymy alone was a poor predictor, licensing a contrast in only 15% of the cases. We also found that direct antonyms are better predictors of contrast than indirect antonyms, and certain antonym pairs, like same-different, are consistently good predictors. These results could be used to find unmarked contrast relations with antonyms alone.
Characterization of the Novel Defective CYP2C9*24 Allele

CYP2C9 is one of the major drug-metabolizing enzymes, and it is involved in the oxidative metabolism of approximately 10% of clinically important drugs, among which some, such as the anticoagulant warfarin, have a narrow therapeutic index. The human CYP2C9 gene is highly polymorphic. We found a new sequence variation in exon 7 of the CYP2C9 gene (1060G>A) resulting in a substitution of acidic amino acid glutamate to basic lysine (E354K) when translated. The allele, designated CYP2C9*24, was present in heterozygous state in one warfarin-treated patient. To characterize the CYP2C9*24 allele, we expressed the wild-type and CYP2C9.24 protein in a recombinant yeast expression system and a human embryonic kidney (HEK)-293 cell system. Carbon monoxide difference spectra were recorded on dithionite-reduced microsomes, and protein was determined by Western blotting. Transfection with CYP2C9.1 cDNA resulted in detectable CYP2C9 protein in yeast or HEK-293 cells, whereas only small amounts of the protein were detected in yeast transfected with CYP2C9.24 cDNA. A strong differential absorption peak at 450 nm was observed with microsomes of yeast transfected with CYP2C9.1 cDNA, whereas no peak was detected with microsomes of yeast transfected with CYP2C9.24 cDNA or empty pYeDP60 plasmid. These results suggest that CYP2C9.24 may be improperly folded, both in yeast and mammalian cells, resulting in improper heme incorporation and rapid intracellular degradation. The data obtained in the expression systems are consistent with our findings in vivo. In conclusion, we have identified a novel defective CYP2C9 variant allele of potential importance for drug metabolism in vivo.
Prenatal ultrasonographic detection of the tracheal atresia sequence

We report on a rare case of tracheal atresia, without fistula, in a 29 weeks' female fetus. The abnormality was detected by prenatal ultrasonography, which demonstrated a bilateral and uniform hyperechogenicity and enlargement of the lungs, associated with ascites and moderate oligohydramnios. We suggest that oligohydramnios may be helpful in distinguishing the upper respiratory tract obstruction from congenital cystic adenomatoid malformation of the lungs, type III. A morphometric study revealed a three‐fold more dense pulmonary vasculature in comparison with two control cases of the same gestational age. The pathological finding of pulmonary and vascular hyperplasia as well as the pathophysiology of the syndrome are discussed. Copyright © 1997 International Society of Ultrasound in Obstetrics and Gynecology
Temporal Cascade Model for Analyzing Spread in Evolving Networks with Disease Monitoring Applications

Current approaches for modeling propagation in networks (e.g., spread of disease) are unable to adequately capture temporal properties of the data such as order and duration of evolving connections or dynamic likelihoods of propagation along these connections. Temporal models in evolving networks are crucial in many applications that need to analyze dynamic spread. For example, a disease-spreading virus has varying transmissibility based on interactions between individuals occurring over time with different frequency, proximity, and venue population density. To capture such behaviors, we first develop the Temporal Independent Cascade (T-IC) model and propose a novel spread function, that we prove to be submodular, with a hypergraph-based sampling strategy that efficiently utilizes dynamic propagation probabilities. We then introduce the notion of 'reverse spread' using the proposed T-IC processes, and develop solutions to identify both sentinel/detector nodes and highly susceptible nodes. The proven guarantees of approximation quality enable scalable analysis of highly granular temporal networks. Extensive experimental results on a variety of real-world datasets show that the proposed approach significantly outperforms the alternatives in modeling both if and how spread occurs, by considering evolving network topology as well as granular contact/interaction information. Our approach has numerous applications, including its utility for the vital challenge of monitoring disease spread. Utilizing the proposed methods and T-IC, we analyze the impact of various intervention strategies over real spatio-temporal contact networks. Our approach is shown also to be highly effective in quantifying the importance of superspreaders, designing targeted restrictions for controlling spread, and backward contact tracing.
Unsupervised Domain Generalization for Person Re-identification: A Domain-specific Adaptive Framework

Domain generalization (DG) has attracted much attention in person re-identiﬁcation (ReID) recently. It aims to make a model trained on multiple source domains generalize to an unseen target domain. Although achieving promising progress, existing methods usually need the source domains to be labeled, which could be a signiﬁcant burden for practical ReID tasks. In this paper, we turn to investigate “unsupervised” domain generalization for ReID, by assuming that no label is available for any source domains. To address this challenging setting, we propose a simple and efﬁcient domain-speciﬁc adaptive framework, and realize it with an adaptive normalization module designed upon the batch and instance normalization techniques. In doing so, we successfully yield reliable pseudo-labels to implement training and also enhance the domain generalization capability of the model as required. In addition, we show that our framework can even be applied to improve person ReID under the settings of supervised domain generalization and unsupervised domain adaptation, demonstrating competitive performance with respect to relevant methods. Extensive experimental study on benchmark datasets is conducted to validate the proposed framework. A signiﬁcance of our work lies in that it shows the potential of unsupervised domain generalization for person ReID and sets a strong baseline for the further research on this topic.
Reconciling actors' preferences in agricultural policy ; towards a new management of public decisions /ed by Frank Jésus, Robin Bourgeois

To attain sustainable development in the 21st century, the world's population still has to overcome many challenges; hunger, poverty, environmental degradation and depletion. Policy design in such a context is and will remain a complex task. On one hand, policy makers often lack information on stakeholders' strategies and constraints as well as on potential options for improvement. On the other hand, stakeholders do not always adhere to policies for lack of understanding of the pursued goals. It is not unusual to observe that often, real policy effects are not those initially expected. Furthermore, existing decision-making mechanisms for public intervention are increasingly questioned due to pressure for market liberalization, decentralization processes and the increasing role of the civil society. However, while the classical role of government is challenged, few methods have been proposed to enable the design of viable alternatives. The approach presented in this book is a contribution to the improvement of efficiency in public decision-making. Based on practical experience from Viet Nam, Indonesia and other countries, it proposes new methods for the identification of policy objective, stakeholders and issues at stake, and for the definition and implementation of concrete actions. It also provides means and guidance to foster progressive actors' participation and involvement in decision-making and policy implementation processes. Key Words: analytical methods, tools, decision making, agricultural policies
Does Online Investor Sentiment Affect the Asset Price Movement? Evidence from the Chinese Stock Market

With the quick development of the Internet, online platforms that provide financial news and opinions have attracted more and more attention from investors. The question whether investor sentiment expressed on the Internet platforms has an impact on asset return has not been fully addressed. To this end, this paper uses the Baidu Searching Index as the agent variable to detect the effect of online investor sentiment on the asset price movement in the Chinese stock market. The empirical study shows that although there is a cointegration relationship between online investor sentiment and asset return, the sentiment has a poor ability to predict the price, return, and volatility of asset price. Meanwhile, the structural break points of online investor sentiment do not lead to changes in the asset price movement. Based on the empirical mode decomposition of online investor sentiment, we find that high frequency components of online investor sentiment can be used to predict the asset price movement. Thus, the obtained results could be useful for risk supervision and asset portfolio management.
Quality of life among people living with acquired immune deficiency syndrome receiving anti-retroviral therapy: a study from nepal

Purpose: The present study was undertaken to determine the impact of acquired immune deficiency syndrome (AIDS) on the quality of life of affected individuals in Nepal. Patients and methods: A cross sectional study was done among 70 individuals attending the Anti-Retroviral Therapy clinic of the University Hospital in Nepal. Quality of life (QOL) was evaluated using World Health Organization Quality of life questionnaire (WHO QOL-BREF) instrument. Statistical analysis was done using SPSS Version 17.0. Results: The median scores with interquartile range (IQR) in four domains of QOL in descending order were physical (61; IQR 22), social (58; IQR 33), environmental (56; IQR 13), and psychological (54; IQR 8). Older age was associated with lower perceived overall QOL. Females were more likely to have lower QOL scores in the social and psychological domains. Higher CD4 counts and a married status were significant predictors of higher QOL scores in the environmental domain. Conclusion: Being older, female, single, and having advanced clinical stage is associated with lower QOL scores in people living with AIDS. Lowest QOL scores were seen in the psychological domain suggesting the need of psychological interventions.