Miracle-dz/UniFAR-FTUs huggingface dataset:
A Bayesian Framework for MultiModality Analysis of Mental Health

We develop statistical methods for multi-modality assessment of mental health, based on four forms of data: (i) self-reported answers to a set of classical questionnaires, (ii) single-nucleotide polymorphism (SNP) data, (iii) fMRI data measured in response to visual stimuli, and (iv) scores for psychiatric disorders. The data were acquired from hundreds of college students. We utilize the data and model to ask a timely and novel clinical question: can one predict brain activity associated with risk for mental illness and treatment response based on knowledge of how the subject answers questionnaires, and using genetic (SNP) data? Also, in another direction: can one predict an individual’s fundamental propensity for psychopathology based on observed self-report, SNP and fMRI data (separately or in combination)? The data are analyzed with a multi-modality factor model, with sparsity imposed on the factor loadings, linked to the particular type of data modality. The analysis framework encompasses a wide range of problems, such as matrix completion and clustering, leveraging information in all the data sources. We use an efficient variational inference algorithm to fit the model, which is especially flexible in dealing with ordinal-valued views (self-report answers and SNP data). The variational inference is validated with slower but rigorous sampling methods. We demonstrate the effectiveness of the model to perform accurate predictions for clinically relevant brain activity relative to baseline models, and to identify meaningful associations between data views.
An Engineering Perspective on Structural Computing: Developing Structure Services for the Web

The emergence of Component-Based Open Hypermedia Systems aims at releasing hypermedia and web applications from the monocracy of link as an information structuring primitive. Instead, an open set of structure servers - each one providing abstractions and semantics relevant to a specific data-organization domain - are employed by an open set of client applications. Nonetheless, the lack of an engineering framework guiding the development and deployment process of structure servers has a part in their limited exploitation. In this paper, we analyze the characteristics of structure servers from an engineering approach, and we propose a software methodology and a set of potential tools in order to direct their development. In addition, we present how this methodology is supported by the Callimachus CB-OHS, emphasizing on the tools enabling rapid prototyping of new structure servers.
USAGE OF ANALYTIC HIERARCHY PROCESS IN MEDICAL EQUIPMENT PURCHASING DECISIONS: A UNIVERSITY HOSPITAL CASE BİR ÜNİVERSİTE HASTANESİNDE TIBBİ CİHAZ SATIN ALMA KARAR SÜRECİ

For acquiring the advantages of high technologies managers of health sector institutions occasionally must make important investment decisions. The most rational and maximum benefit must be required from these investments. In managing the hospitals which are financed by the government chiefly, decisions related to purchasing of the medical equipments convert into complex decision problems which require consideration of a good many criteria (financial criteria, medical benefits, other benefits, requirements, etc.). Purchased equipments will be used not only for taking the best yield from the existing resources, but also for different aims of following and applying the improved technologies and scientific techniques, and increasing the service quality. In this study, medical equipment purchasing decision stages applied in a university hospital have been examined, and priorities of the medical equipments which are planned to be purchased have been determined with the help of Analytic Hierarchy Process which is one of the multicriteria decision making techniques.
A 3-phase threshold algorithm for smartphone-based fall detection

Falls are one of the prominent causes of injury in elderly. A fall detection could help reduce the health risk following the fall that would otherwise get overlooked. Many research studies mostly focus on distinguish a fall from other activities in daily life using smartphone. However, one major problem is a false positive created by a smartphone drop. In this paper, we propose a 3-phase threshold based fall detection algorithm for smartphone which can distinguish a fall from a smartphone drop. The experimental results show that our algorithm achieves a better performance than 2-phase threshold algorithm. Moreover, in smartphone drop cases, our algorithm has 72% specificity higher than 2-phase threshold algorithm which has 31% specificity.
The analysis of the drug–targets based on the topological properties in the human protein–protein interaction network

Analyzing topological properties of drug-target proteins in the biology network is very helpful in understanding the mechanism of drug action. However, comprehensive studies to elaborately characterize the biological network features of drug-target proteins are still lacking. In this paper, we compared the topological properties of drug–targets with those of the non–drug-target sets, by mapping the drug–targets in DrugBank to the human protein interaction network. The results indicate that the topological properties of drug-targets are significantly distinguishable from those of non–drug-targets. Moreover, the potential possibility of drug-target prediction based on these properties is discussed. All proteins in the interaction network were ranked by their topological properties. Among the top 200 proteins, 94 overlapped with drug-targets in DrugBank and some novel predictions were found to be drug–targets in public literatures and other databases. In conclusion, our method explores the topological properties of drug-targets in the human protein interaction network by exploiting the large–scale drug-targets and protein interaction data.
High throughput 32-bit AES implementation in FPGA

Advance Encryption Standard (AES) hardware implementation in FPGA as well as in ASIC has been intensely discussing, especially in high-throughput (over several tens Gbps). However, low area designs have also been investigated in recent years for the embedded hardware applications. This paper presents a 32-bit AES implementation with a low area of 156 slices and a throughput of 876 Mbps, which outperformed the best reported result of 648 Mbps throughput found in literature.
Crystal structure and mutagenesis analysis of chitinase CrChi1 from the nematophagous fungus Clonostachys rosea in complex with the inhibitor caffeine.

Chitinases are a group of enzymes capable of hydrolysing the β-(1,4)-glycosidic bonds of chitin, an essential component of the fungal cell wall, the shells of nematode eggs, and arthropod exoskeletons. Chitinases from pathogenic fungi have been shown to be putative virulence factors, and can play important roles in infecting hosts. However, very limited information is available on the structure of chitinases from nematophagous fungi. Here, we present the 1.8 Å resolution of the first structure of a Family 18 chitinase from this group of fungi, that of Clonostachys rosea CrChi1, and the 1.6 Å resolution of CrChi1 in complex with a potent inhibitor, caffeine. Like other Family 18 chitinases, CrChi1 has the DXDXE motif at the end of strand β5, with Glu174 as the catalytic residue in the middle of the open end of the (β/α)(8) barrel. Two caffeine molecules were shown to bind to CrChi1 in subsites -1 to +1 in the substrate-binding domain. Moreover, site-directed mutagenesis of the amino acid residues forming hydrogen bonds with caffeine molecules suggests that these residues are important for substrate binding and the hydrolytic process. Our results provide a foundation for elucidating the catalytic mechanism of chitinases from nematophagous fungi and for improving the pathogenicity of nematophagous fungi against agricultural pest hosts.
Thermal performance of Inkjet-assisted spray cooling in a closed system

As the number of processors per die increase, chip thermal hotspots become increasingly more concentrated within smaller and smaller areas. Furthermore, these hotspots can change as processors are dynamically throttled or taken in and out of sleep mode based upon load and overall thermal budgets. Current cooling solutions (e.g. heatsinks, heatpipes, and even liquid cooling solutions) extract heat from the chip level but cannot independently control temperature at the hotspot level. The presented solution utilizes InkJet heads to deliver precise coolant flow rate independently to each chip location to maintain very high heat transfer rate via sustained liquid-to-vapor phase change. The result is a 10-100x improvement in thermal extraction rates over existing cooling solutions, achieving heat transfer rate as high as 4.5kW/cm2. Additionally, because each hotspot is maintained independently eliminating any large temperature gradient over the entire chip surface area, the ability to operate chips at higher operating points is now possible. This paper presents a heat sink prototype based on the inkjet-assisted spray cooling technology. The heat sink utilizes an air-cooled vapor chamber to condense and recirculate the evaporated liquid to achieve a fully closed system within the vapor chamber enclosure. The design of the prototyped solution is presented.
Leader-following rendezvous with connectivity preservation of a class of multi-agent systems

This paper studies a leader-following rendezvous problem with connectivity preservation for a double integrator multi-agent system subject to a class of external disturbances. Motivated by some techniques in output regulation theory, we propose a dynamic distributed state feedback control protocol that is able to maintain the connectivity of an initially connected communication network, and, at the same time, achieve the objective of the asymptotic tracking of all followers to the leader regardless of external disturbances.
Amiodarone induces a caffeine‐inhibited, MID1‐depedent rise in free cytoplasmic calcium in Saccharomyces cerevisiae

Calcium signalling is involved in myriad cellular processes such as mating morphogenesis. Mating in yeast induces changes in cell morphology with a concomitant increase in calcium uptake that is dependent on the MID1 and CCH1 genes. Mid1p and Cch1p are believed to function in a capacitive calcium entry (CCE)‐like process. Amiodarone alters mammalian calcium channel activity but, despite its clinical importance, its molecular mechanisms are not clearly defined. We have shown previously that amiodarone has fungicidal activity against a broad array of fungi. We show here that amiodarone causes a dramatic increase in cytoplasmic calcium ([Ca2+]cyt) in Saccharomyces cerevisiae. The majority of this increase is dependent on extracellular Ca2+ nonetheless, a significant increase in [Ca2+]cyt is still induced by amiodarone when no uptake of extracellular Ca2+ can occur. The influx of extracellular Ca2+ may be a direct effect of amiodarone on a membrane transporter or may be by a CCE mechanism. Uptake of the extracellular Ca2+ is inhibited by caffeine and reduced in strains deleted for the mid1 gene, but not in cells deleted for cch1. Our data are the first demonstrating control of yeast calcium channels by amiodarone and caffeine.
From Knowledge Production to Implementation: Research Challenges and Imperatives

As evidence-based practice is increasingly accepted in social work, the challenges associated with its actual implementation become more apparent and pressing. This article identifies implementation as a critical issue for research; implementation itself must be better understood if evidence-based practices are to be used and resultant improvements to practice are to be realized. Social work needs to engage more fully in (a) service system research and (b) implementation research, each of which complements and has potential to extend the benefits of efficacy and effectiveness research. Service system research can enhance the fit of empirically supported treatments to the needs of real-world practice and thus facilitate their implementation. Implementation studies examine the acceptability of evidence-based interventions, the feasibility and likelihood of their sustained use, and the decision-support procedures that can help practitioners apply probabilistically based, empirically supported treatments to the individual case in real-world practice.
A TECNOLOGIA DA INFORMAÇÃO INOVANDO A TRANSPARÊNCIA NAS UNIVERSIDADES PÚBLICAS

RESUMO O Governo eletrônico tem sido visto como um promotor da interação do cidadão com o governo, um modo de melhorar a gestão interna das universidades e da integração com parceiros e fornecedores. Pode ainda proporcionar: maior eficiência; universalização dos serviços; aumento da transparência; modernização do Estado; melhora da qualidade de vida dos cidadãos; melhora da qualidade dos serviços prestados; diminuição da corrupção; entre outros. Com auxílio das tecnologias da informação e comunicação, como a Internet, o combate à corrupção pode ser potencializado, pois permite uma maior facilidade de acesso aos dados e informações nas Universidades Pública. O objetivo desse artigo é construir um referencial teórico sobre as perspectivas do uso das tecnologias da informação e da comunicação como ferramentas de combate à corrupção e apresentar uma pesquisa exploratória de duas iniciativas do Governo Federal de combate à corrupção: o ComprasNet e o Portal da Transparência. A metodologia utilizada foi a pesquisa bibliográfica sobre os conceitos-chave (transparência e governo eletrônico) e as relações que ostentam entre si e uma pesquisa exploratória no Portal de Compras do Governo Federal, denominado ComprasNet, e o Portal da Transparência. Palavras-chave: Tecnologia da informação, Administração Pública, Universidades Públicas; Governo eletrônico, Comprasnet, Portal da transparência.
Epidermal cells adhere preferentially to type IV (basement membrane) collagen

Epidermal cells from adult guinea pig skin attach and differentiate preferentially on substrates of type IV (basement membrane) collagen, compared to those of types I--III collagen. In contrast, guinea pig dermal fibroblasts attach equally well to all four collagen substrates. Fibronectin mediates the attachment of fibroblasts but not of epidermal cells to collagen.
Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives

Abstract Microalgae are well known for their ability to accumulate lipids intracellularly, which can be used for biofuels and mitigate CO2 emissions. However, due to economic challenges, microalgae bioprocesses have maneuvered towards the simultaneous production of food, feed, fuel, and various high-value chemicals in a biorefinery concept. On-line and in-line monitoring of macromolecules such as lipids, proteins, carbohydrates, and high-value pigments will be more critical to maintain product quality and consistency for downstream processing in a biorefinery to maintain and valorize these markets. The main contribution of this review is to present current and prospective advances of on-line and in-line process analytical technology (PAT), with high-selectivity – the capability of monitoring several analytes simultaneously – in the interest of improving product quality, productivity, and process automation of a microalgal biorefinery. The high-selectivity PAT under consideration are mid-infrared (MIR), near-infrared (NIR), and Raman vibrational spectroscopies. The current review contains a critical assessment of these technologies in the context of recent advances in software and hardware in order to move microalgae production towards process automation through multivariate process control (MVPC) and software sensors trained on “big data”. The paper will also include a comprehensive overview of off-line implementations of vibrational spectroscopy in microalgal research as it pertains to spectral interpretation and process automation to aid and motivate development.
PENGARUH KEUANGAN, KUALITAS AUDITOR, KEPEMILIKAN PERUSAHAAN TERHADAP PENERIMAAN OPINI AUDIT GOING CONCERN

This research is meant to analysis some factors that have influence to the going concern audit opinion. The thing that can become the consideration of the auditor in giving going concern audit opinion can be done by seeing internal factor e.g. financial condition and audit quality that is related to the auditor performance in giving going concern audit opinion from the previous year as a consideration for giving going concern audit opinion for the following year, and company ownership can be a consideration in giving going concern audit opinion since the company will be protected from financial difficulty with the presence of company ownership. This research has been carried out by means of secondary data search and by using 12 samples from the list of manufacturing companies in Indonesia Stock Exchange during the periods of 2009, 2010, 2010, 2011, and 2012. The logistic regression analysis is employed as the technique in this research to test the hypothesis. The result of hypothesis test shows that audit quality has positive influence on going concern audit opinion. The financial condition variable and company ownership has negative influence on going concern audit opinion. Keywords: Going Concern Audit Opinion, Previous Year Opinion, Financial Condition, Audit Quality, Company Ownership
Estimating Hidden Semi-Markov Chains From Discrete Sequences

This article addresses the estimation of hidden semi-Markov chains from nonstationary discrete sequences. Hidden semi-Markov chains are particularly useful to model the succession of homogeneous zones or segments along sequences. A discrete hidden semi-Markov chain is composed of a nonobservable state process, which is a semi-Markov chain, and a discrete output process. Hidden semi-Markov chains generalize hidden Markov chains and enable the modeling of various durational structures. From an algorithmic point of view, a new forward-backward algorithm is proposed whose complexity is similar to that of the Viterbi algorithm in terms of sequence length (quadratic in the worst case in time and linear in space). This opens the way to the maximum likelihood estimation of hidden semi-Markov chains from long sequences. This statistical modeling approach is illustrated by the analysis of branching and flowering patterns in plants.
Roles of complement and complement receptor type 3 in phagocytosis of Listeria monocytogenes by inflammatory mouse peritoneal macrophages

Listeria monocytogenes is a facultative intracellular bacterium that is phagocytosed by and can proliferate within cells of the mononuclear phagocyte system. However, the receptors used by macrophages to internalize this organism have not been identified. In the experiments described here, the contributions of serum complement component C3 and macrophage complement receptor type 3 (CR3) to opsonization and phagocytosis of L. monocytogenes by mouse inflammatory peritoneal macrophages were studied. An assay which allowed the distinction of adherent versus internalized bacteria was used to show that following mixing of L. monocytogenes with inflammatory macrophages, greater than 95% of the bacteria bound were internalized by these phagocytes. When immunofluorescent antibodies to C3 and immunoglobulin were used, C3 but not immunoglobulin was detected on L. monocytogenes following incubation in normal serum or ethylene glycol-bis(beta-aminoethyl ether)-N,N'-tetracetic acid-Mg(2+)-chelated serum. When macrophages were incubated with 5% serum and L. monocytogenes in a standard assay, approximately 80% of the phagocytosis was inhibited by heat-inactivated serum or by the addition of F(ab')2 anti-C3 antibody. The role of macrophage CR3 was demonstrated by the ability of anti-CR3 monoclonal antibody M1/70 to decrease phagocytosis to the same levels as those seen with heat-inactivated serum. These experiments indicated that in the presence of normal serum, L. monocytogenes is phagocytosed by inflammatory macrophages primarily because CR3 on these cells binds to C3 deposited on the bacterial surface.
2 Nonlinear Sigma Model and 2-dim Black Hole

We study D-branes of N = 2 supersymmetric sigma models. Supersymmetric nonlinear sigma models with 2-dimensional target space have D0,D1,D2-branes, which are realized as A-,B-type supersymmetric boundary conditions on the worldsheet. When we embed the models in the string theory, the Kähler potential is restricted and leads to a 2-dim black hole metric with a dilaton background. The D-branes in this model are susy cycles and consistent with the analysis of conjugacy classes. The generalized metrics with U(n) isometry is proposed and dynamics on them are realized by linear sigma models. We investigate D-branes of the linear sigma models and compare the results with those in the nonlinear sigma models. e-mail address: nakayama@phys.h. kyoto-u.ac. jp e-mail address: sugiyama@phys.h. kyoto-u.ac. jp
Study on application of image recognition technique in the cow body condition score

The traditional cow body condition score method requires the professionals who master the standards of body condition score. And there are some subjective differences between the scores from different raters. This paper presents an automatic method of cow body condition score using digital image recognition technology. Preprocess the images of cow tail and then use the PCA method for image recognition. The experimental results show that this new method is practical in a certain range of error.
On the equivalence of fanout-point faults

At the gate level, practical equivalence rules exist only for the faults on the inputs and output of a Boolean gate. It is shown that, under some conditions, equivalence can be stated between faults on a fanout stem and on its branches. A practical procedure for identifying such faults is given, with actual design examples to which these rules apply. In one case this leads to the identification of logic redundancy. <<ETX>>
Identification of Synchronous Generator Using Nonlinear Feedback Model

Abstract In this paper, the new approach for identification of synchronous generator using nonlinear feedback model and with piecewise linear map is investigated. In this method, synchronous generator model consists of a linear-dynamic block in forward path and a nonlinear-static block in feedback path. The identification method simultaneously approximates these blocks without requiring prior assumptions on the form of the static non-linearity. In this study, the field voltage is considered as the input and the active output power and the terminal voltage are considered as the outputs of the synchronous generator. The proposed method has been tested on a synchronous machine. Experimental results show good accuracy of the identified model.