Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of bankruptcy on industry classification

This study predicts bankruptcy by making predictions after separating the entire industry into individual industries via the decision tree method and support vector machines (SVMs), and then it compares two method, decision tree and SVM. This research predicts bankruptcy in two steps. The first step is to predict using decision tree method and the second step is to predict using support vector machine for 11 industries. The financial statements of the listed companies in the Tokyo Stock Exchange, the Osaka Securities Exchange, and other stock exchanges were used as data in this study. The data of 244 bankrupt companies that went bankrupt between 1991 and 2014 are used. On the other hand, data of 64708 non-bankrupt companies that did not go bankrupt between 1991 and 2014 for 24 years are used. The data is acquired from Nikkei NEEDS database. In the decision tree, the multi-step branching process is stratified, and the bankruptcy prediction is performed in the tree diagram. In SVM, prediction of bankruptcy is almost perfectly conducted to discriminate the companies for each industry.
Poverty, psychological disorder and disability in primary care attenders in Goa, India

Background This study examined the association of common mental disorders in primary health clinic attenders with indicators of poverty and disability in Goa, India. Method Adult attenders (n=303) in two primary health clinics were recruited. Results There were 141 (46.5%) cases of common mental disorder. The following were associated with common mental disorder: female gender; inability to buy food due to lack of money; and being in debt. Cases scored significantly higher on all measures of disability. Primary health clinic staff recognised a third of the morbidity but used multiple oral drugs, injectable vitamins and benzodiazepines to treat common mental disorders. Conclusions Poverty is closely associated with common mental disorder which in turn is associated with deprivation and despair. Primary mental health care priorities in low-income countries need to shift from psychotic disorders which often need specialist care to common mental disorders. Health policy and development agencies need to acknowledge the intimate association of female gender and poverty with these disorders.
Enigma of Public Assistance to Private Investment through Infrastructure: Evidence from Pakistan

Purpose: Public physical infrastructure development has fairly large impacts on private sector investment decisions and through this; it can affect economic performance (growth). The current study intends to explore the course in which public infrastructure affects private sector investment in Pakistan and whether there exist long run equilibrium between them or not. Time series annual data from 1972 to 2015 has been employed. Instead of using a single infrastructure indicator, the study has constructed a multidimensional composite index through principal component analysis (PCA). Real gross fixed capital formation is used as the proxy of private sector investment. The long run relationship is determined by Johansen's co-integration technique after checking for the order of integration. The empirical evidence shows that physical infrastructure availability is positively and significantly affecting private sector investment decisions. In addition, credit to private sector, per capita GDP, work force and inflation rate are positively and significantly affecting private investment. Further, private investment is sensitive to public physical infrastructure availability not only in long run but also in short run. A statistically significant and negative ECT (-1) term confirms the long run relationship and convergence towards equilibrium in case of Pakistan. Findings of the study show that public physical infrastructure services endorse the private investment both in the long run and the short run
Using the web to increase physical activity in college students.

OBJECTIVES To evaluate the effectiveness of a theoretically based and Web-delivered intervention using common course technology for increasing physical activity in a college student sample. METHODS One hundred four students randomly participated in either a Web-based intervention involving 7 theory-based learning lessons or a control group that received minimal physical activity information. Participants reported levels of physical activity and social cognitive theory (SCT) constructs at baseline and after 6 weeks of the intervention. RESULTS Relative to controls, intervention participants reported increased days of moderate and vigorous physical activity, but few changes in SCT constructs. CONCLUSIONS Web-based interventions can successfully increase physical activity among college students.
Functional diversity of electrogenic Na+–HCO3− cotransport in ventricular myocytes from rat, rabbit and guinea pig

The Na+–HCO3− cotransporter (NBC) is an important sarcolemmal acid extruder in cardiac muscle. The characteristics of NBC expressed functionally in heart are controversial, with reports suggesting electroneutral (NBCn; 1HCO3− : 1Na+; coupling coefficient N= 1) or electrogenic forms of the transporter (NBCe; equivalent to 2HCO3− : 1Na+; N= 2). We have used voltage‐clamp and epifluorescence techniques to compare NBC activity in isolated ventricular myocytes from rabbit, rat and guinea pig. Depolarization (by voltage clamp or hyperkalaemia) reversibly increased steady‐state pHi while hyperpolarization decreased it, effects seen only in CO2/HCO3−‐buffered solutions, and blocked by S0859 (cardiac NBC inhibitor). Species differences in amplitude of these pHi changes were rat > guinea pig ≈ rabbit. Tonic depolarization (−140 mV to −0 mV) accelerated NBC‐mediated pHi recovery from an intracellular acid load. At 0 mV, NBC‐mediated outward current at resting pHi was +0.52 ± 0.05 pA pF−1 (rat, n= 5), +0.26 ± 0.05 pA pF−1 (guinea pig, n= 5) and +0.10 ± 0.03 pA pF−1 (rabbit, n= 9), with reversal potentials near −100 mV, consistent with N= 2. The above results indicate a functionally active voltage‐sensitive NBCe in these species. Voltage‐clamp hyperpolarization negative to the reversal potential for NBCe failed, however, to terminate or reverse NBC‐mediated pHi‐recovery from an acid load although it was slowed significantly, suggesting electroneutral NBC may also be operational. NBC‐mediated pHi recovery was associated with a rise of [Na+]i at a rate ∼25% of that mediated via NHE, and consistent with an apparent NBC stoichiometry between N= 1 and N= 2. In conclusion, NBCe in the ventricular myocyte displays considerable functional variation among the three species tested (greatest in rat, least in rabbit) and may coexist with some NBCn activity.
Dose dependence effects of ionizing radiation on bile acid metabolism in the rat

Purpose : To study radiation dose-related changes of individual or total bile acids in various physiological fluids in order to identify potential bio-indicators of radiation-induced gastrointestinal injuries. Materials and methods : Wistar rats were sham- or whole-body gamma irradiated (1-12Gy). Total and individual bile acids were quantified, 3 days after exposure, in bile collected after catheterization of the bile duct. Total bile acid concentrations were also measured in plasma and colonic contents 1, 2 and 3 days after irradiation. These concentrations were determined by an enzymatic method whereas individual bile acids were quantified by HPLC. Results : In bile, whereas total bile acid concentration remained unchanged after irradiation whatever the dose, the proportion of dihydroxy bile acids in the pool of total bile acids was gradually increased with the irradiation dose, especially from 8 Gy. In plasma samples, total bile acid concentrations fell for doses higher than 10 Gy. In colonic contents, bile acid concentrations increased progressively with time (from 1 to 3 days) and with irradiation dose (from 1 to 12Gy), reaching a plateau 3 days after exposure for doses higher than 10 Gy. Conclusions : These results show that changes in colonic bile acid concentrations which are reflected in faeces are perhaps a useful parameter to improve diagnosis and prognosis of radiationinduced gastrointestinal damage since it probably reflects directly intestinal bile acid malabsorption.
SME productivity stakeholders: getting in the right orbit

Successive governments have developed strategies and initiatives over the last two decades to help SME’s increase productivity often through government funded quasi-agencies, the latest of these new industrial strategy document, The research aim of this paper was to explore from the SME perspective who they might consider are key stakeholders or agents for their business in terms of helping increase productivity, and what support these stakeholders might offer. The study uses the LEGO serious play methodology and narrative analysis to develop a stakeholder ‘orbital map’ which shows a small ‘depth of field’ of ‘close’ stakeholders, and the complexity of some of the resulting relationships, and the implications for policy makers.
Unsupervised feature selection for tumor profiles using autoencoders and kernel methods

Molecular data from tumor profiles is high dimensional. Tumor profiles can be characterized by tens of thousands of gene expression features. Due to the size of the gene expression feature set machine learning methods are exposed to noisy variables and complexity. Tumor types present heterogeneity and can be subdivided in tumor subtypes. In many cases tumor data does not include tumor subtype labeling thus unsupervised learning methods are necessary for tumor subtype discovery. This work aims to learn meaningful and low dimensional representations of tumor samples and find tumor subtype clusters while keeping biological signatures without using tumor labels. By using Autoencoders a low dimensional and denoised latent space is learned as a target representation to guide a Multiple Kernel Learning model that selects a subset of genes. By using the selected genes a clustering method is used to group samples. In order to evaluate the performance of the proposed unsupervised feature selection method the obtained features and clusters are analyzed by clinical significance. The proposed method has been applied on three tumor datasets which are Brain, Renal and Lung, each one composed by two tumor subtypes. The results obtained by the proposed method reveal lower redundancy in the selected features and each obtained cluster is significantly enriched by just one tumor subtype when compared with benchmark unsupervised feature selection methods. The proposed method named Latent Kernel Feature Selection (LKFS) is an unsupervised approach for gene selection in tumor gene expression profiles.
Across the life course

There is a huge demand for high-quality longitudinal educational research in Germany. In particular, there is a clear need for both analytical and methodological progress in order to understand educational pathways through the life course and how they lead to different outcomes. This paper identifies the theoretical and methodological challenges of studying education across the life course and describes the structure of the National Educational Panel Study (NEPS) in Germany.
A Multi-Modal and Multi-Objective Journey Planner for Integrating Carpooling and Public Transport

SocialCar is a research project that aims at integrating carpooling with traditional transportation systems in urban areas, while benefiting from social media to enhance the user’s experience. The system is based on route planning and ride matching algorithms to provide the users with alternatives for their trips. In this work, we overview the multiple approaches in the literature to model transportation networks and carpooling services, and a route planning algorithm which integrates multiple transportation types together. Finally, the performance measures of the route planner are reported.
Automatic Generation of Landmark-based Indoor Routing Instructions

This paper addresses the question of how route instructions that include landmarks for indoor navigation can be created automatically based on information available in spatial indoor databases. Existing approaches for the generation of landmark-based routing instructions are designed for outdoor environments and rely mainly on instance-level data about the characteristics of potential landmarks. However, indoor navigation differs from outdoor navigation in various aspects, and indoor spatial databases do not usually contain detailed information about individual objects. Therefore, the proposed method aims to address the specific challenges of indoor navigation and relies only on commonly available data about categories of spatial objects. A case study of a university campus demonstrates that by and large the method produces correct routing instructions that include landmarks. However, it also reveals some gaps in the model and shows possibilities for enhancements for future work.
O papel do retinol sobre a modulação do receptor para produtos finais avançados de glicação (RAGE) em linhagem de câncer de pulmão de não-pequenas células

Vitamin A and its derivatives, the retinoids, participate in cellular processes such as growth, cell division and apoptosis. The effects of vitamin A, in part, are ascribed to gene transcription mediated by nuclear receptors from the family of the steroid receptors, known as retinoic acid receptors (RARs) and retinoid receptors (RXRs). However, excessive vitamin A, or retinoids, in the diet, or by therapeutic use, may be theratogenic. Several studies have shown "in vitro" and "in vivo" that vitamin A and its metabolites are redox active molecules, that is, may act as pro-oxidants and antioxidants, depending on the concentration and the environment in which they are. In this study we demonstrated that treatment with retinol, which is considered to be the principal metabolite of vitamin A, in cell lines of non-small cells lung carcinoma A549 led to a decrease in the expression and immunocontent of receptor for advanced glycation endproducts (RAGE). The RAGE is constitutively expressed in lung cells; a modulation in expression or immunocontent of RAGE is associated with alterations on homeostasis of lung tissue. Here, we found that the modulation of RAGE induced by retinol treatment in our model was redox dependent. Retinol treatment of A549 cells induced an increase in the production of reactive oxygen species, which consequently become the pro-cellular environment favoring the induction of oxidative damage to biomolecules such as lipids and proteins. Furthermore, the increase in production of reactive oxygen species led to activation of p38 MAPK by a redox-dependent mechanism. Activation of p38 subsequently led to activation of the transcription factor NF-kB, which consequently modulates the expression of RAGE in these cells. All effects caused by retinol treatment were blocked with Trolox ® (hydrophilic analogue of Vitamin E) co-treatment, which is an antioxidant molecule. Therefore, our results demonstrated that retinol treatment is able to induce a pro-oxidative status in A549 cells, and that modulation of RAGE expression by retinol is mediated by the redox-dependent activation of p38/NF-kB signaling pathway. Then, based on these results and other data already reported in the literature, we believe that greater care is needed in the use of vitamin A supplementation as therapeutic level.
Computational Methods for a Class of Network Models

In the following article, we provide an exposition of exact computational methods to perform parameter inference from partially observed network models. In particular, we consider the duplication attachment model that has a likelihood function that typically cannot be evaluated in any reasonable computational time. We consider a number of importance sampling (IS) and sequential Monte Carlo (SMC) methods for approximating the likelihood of the network model for a fixed parameter value. It is well-known that, for IS, the relative variance of the likelihood estimate typically grows at an exponential rate in the time parameter (here this is associated with the size of the network); we prove that, under assumptions, the SMC method will have relative variance that can grow only polynomially. In order to perform parameter estimation, we develop particle Markov chain Monte Carlo algorithms to perform Bayesian inference. Such algorithms use the aforementioned SMC algorithms within the transition dynamics. The approaches are illustrated numerically.
SEVERITY BASED CONTINGENCY MANAGEMENT APPROACH: AN INDIAN SCENARIO

In today’s electronic world, secured operation of the electric power system is one of the foremost requirements. Contingency analysis and management thus becomes the basic requirement of system analysis. In this paper, the contingency study has been done on a heavily loaded practical power system in an Indian scenario. A Composite Severity Index (CSI) has been proposed for the determination of critical line. The contingency analysis has been done using Rapid Contingency Ranking Technique (RCRT). By this method the number of lines on which the contingency analysis is to be performed is greatly reduced. Thereafter, an Interline Power Flow Controller (IPFC) has been placed in the system on the basis of CSI for improvement of the system situation postcontingency. An IPFC has been found to be very effective in the improvement of system condition of the heavily loaded Indian system.
Readability challenges in deeply scaled STT-MRAM

Spin transfer torque magnetic random access memory (STT-MRAM) is currently under intensive investigation for one of the possible alternatives to extend the Moore's Law beyond the CMOS technology scaling limit. Its advantageous features, such as nonvolatility, high speed, low power and excellent scalability etc, attract worldwide R&D attention. However as technology scales (e.g., below 40 nm), the process variations introduce big read reliability challenges for STT-MRAM due to the reduced sensing margin (SM) and the increased read disturbance (RD). Therefore the readability, rather than writability, will become an ultimate bottleneck of STT-MRAM at technology nodes below 40 nm. In this paper, we firstly analyze the technology scaling trends on the STT-MRAM read performance; and then we present a RD detection circuit for the case where read current is lower than the write current (e.g., >30 nm); finally we propose a reconfigurable cell design based on the differential sensing scheme to improve the SM and to reduce the RD simultaneously, for the case where read current approaches the write current (e.g., <;30 nm).
Role of trust and relationships in geographically distributed teams: exploratory study on development sector

This study explores the role of trust and relationships in geographically distributed teams (virtual teams) of development sector. Interviewed teams were surrounded by ground realities of their work locations, which included technology limitations, uncertainties and human constraints, which tend to obstruct development of trust and relationships. The needs for developing trust and relationships identified during interviews were personal conduct characteristics of team members, like confidence, competence, reliability, interpersonal relationship, quality output, responsibility and commitment. Trust emerged as the core factor encompassing all relationships, among team members or between leader and members. The study revealed that trust is a precursor to relationships. Geographically distributed teams work within cognitive trust, where its members desire affective trust from the leader. Trust is not only a product of, but also a pre-requisite for optimal technology usage. Trust is not formally evaluated but is manifested in the quality of outcomes.
Evaluation of Image Quality Metrics for the Prediction of Subjective Best Focus

Purpose. Seven existing and three new image quality metrics were evaluated in terms of their effectiveness in predicting subjective cycloplegic refraction. Methods. Monochromatic wavefront aberrations (WA) were measured in 70 eyes using a Shack-Hartmann based device (Complete Ophthalmic Analysis System; Wavefront Sciences). Subjective cycloplegic spherocylindrical correction was obtained using a standard manifest refraction procedure. The dioptric amount required to optimize each metric was calculated and compared with the subjective refraction result. Metrics included monochromatic and polychromatic variants, as well as variants taking into consideration the Stiles and Crawford effect (SCE). WA measurements were performed using infrared light and converted to visible before all calculations. Results. The mean difference between subjective cycloplegic and WA-derived spherical refraction ranged from 0.17 to 0.36 diopters (D), while paraxial curvature resulted in a difference of 0.68 D. Monochromatic metrics exhibited smaller mean differences between subjective cycloplegic and objective refraction. Consideration of the SCE reduced the standard deviation (SD) of the difference between subjective and objective refraction. Conclusions. All metrics exhibited similar performance in terms of accuracy and precision. We hypothesize that errors pertaining to the conversion between infrared and visible wavelengths rather than calculation method may be the limiting factor in determining objective best focus from near infrared WA measurements.