Miracle-dz/UniFAR-FTUs huggingface dataset:
A prospective high-risk study of the association among maternal negativity, apparent frontal lobe dysfunction, and the development of bipolar disorder

In a previous paper, the authors found that impairment on the Wisconsin Card Sorting Test (WCST) in adolescence was predictive of bipolar disorder in young adulthood among offspring of mothers with bipolar illness. In the present study, the authors explore the contribution of maternal characteristics, beyond maternal mood disorder, to the prediction of offspring dysfunction on the WCST. Results showed that maternal bipolar disorder and maternal negativity were both predictive of impaired performance on the WCST during adolescence. The contribution of maternal negativity to offspring WCST impairment was not better explained by maternal personality disorder, mother's functional impairment, family loading for bipolar disorder, or offspring disruptive behavioral disturbance. Findings did not support a moderator model. However, support was found for a mediation model in which maternal negativity contributed to risk for offspring bipolar disorder through its negative association with apparent frontal lobe functioning, as measured by the WCST. Findings are discussed from the perspective of a vulnerability–stress model. In addition, the authors consider the possibility that maternal negativity and offspring impairment on the WCST may be reflective of a common heritable trait.The findings presented in this paper come from the doctoral dissertation of the first author, which was funded by an NIMH Intramural Research Training Award. The authors are enormously grateful to Anne Mayfield, without whom this project would not have been possible. We are deeply indebted to Ann S. Masten, W. Andrew Collins, L. Alan Sroufe, Monica Luciana, and Carrie Borchardt, who provided support and guidance throughout all stages of this project. We are also thankful to Robert Asarnow for his advice and encouragement, and to Roger E. Meyer and Daniel N. Klein for their comments on earlier drafts of this paper. In addition, we acknowledge the contributions of Gail Inoff-Germain, who administered diagnostic interviews and neuropsychological measures at adolescent follow-up; Rula B. Garside, who undertook the painstaking job of establishing interrater reliability; Erika Sundstrom, who devoted many hours to data organization and quality assurance; and Sara Avery Torvik and Patricia Kasdan, whose combined gifts of organization and warmth created a comfortable atmosphere for study participants. Finally, we thank the extraordinary research participants of the NIMH Childrearing Study, who have shown enormous bravery and dedication by sharing with us 23 years of their lives.
N-methyl-D-aspartic acid receptor expression in the dorsolateral prefrontal cortex of elderly patients with schizophrenia.

OBJECTIVE The N-methyl-D-aspartic acid (NMDA) class of glutamate receptors has received attention in the pathophysiology of schizophrenia because of the similarity between some schizophrenic symptoms and symptoms caused by NMDA antagonists. To determine if NMDA receptor abnormalities were present at the mRNA level, expression of NMDA receptor (NR) subunits NR(1), NR(2A), and NR(2B) was measured in specimens from the dorsolateral prefrontal cortex and the occipital cortex of elderly patients with schizophrenia and normal elderly subjects. METHOD Postmortem specimens from antemortem assessed and diagnosed elderly patients with schizophrenia (N=26) were compared with those from a neuropathologically and neuropsychiatrically normal elderly comparison group (N=13) and from patients with Alzheimer's disease (N=10). The mRNA expression of the NR(1), NR(2A), and NR(2B) subunits and of postsynaptic density 95 (PSD-95), a protein associated with postsynaptic NMDA receptors, was studied with quantitative real-time reverse transcriptase polymerase chain reaction. RESULTS Expression of NR(1) and NR(2A) but not NR(2B) subunits was higher in the dorsolateral prefrontal cortex and the occipital cortex of patients with schizophrenia than in the normal and Alzheimer's disease groups. In contrast, NR(1) expression was significantly lower in the Alzheimer's disease group. Occipital cortex expression of PSD-95 was higher in the schizophrenic subjects and correlated strongly with the expression of NR(2A) and NR(2B) in both cortical regions and with expression of NR(1) in the occipital cortex. These results were not influenced by neuroleptic exposure history, postmortem interval, or age of the subject. CONCLUSIONS NMDA receptor subunits are abnormally expressed in elderly patients with schizophrenia. The disproportionate expression of the NR(1) and NR(2A) subunits relative to NR(2B) expression may have implications for the pathophysiology of schizophrenia and the sensitivity of schizophrenic patients to glutamate and glutamatergic drugs.
INVESTIGATION ON THE FLOW BEHAVIOUR OF A VENTURI TYPE GAS MIXER DESIGNED FOR DUAL FUEL DIESEL ENGINES

The consumption of energy is increasing at staggering rate around the globe due to a rise in population and its standard of living. The energy is obtained from fossil fuels at the cost global warming. It results several harmful effects for both environmental and human welfare. These impacts can be narrowed down by using alternative renewable energy that is generated from natural resources such as biomass, solar heat and light, wind, rain, tides, waves etc. Dual fuel diesel engines allow the cultivation of alternative fuels for a cleaner combustion. Biogas, a fuel derived from biomass, mainly contains methane (CH4) along with a certain quantity of carbon dioxide (CO2). In a dual fuel engine, biogas can be used as a primary fuel and diesel as a pilot fuel. This requires the necessary modification in the engine that includes the installation of a gas mixer at the inlet manifold of the engine. A properly designed gas mixer for a biogas premixed charge dual fuel engine can result in a proper mixing of biogas with air. This ensures to a better combustion and higher efficiency of the engine. In this paper, the flow behavior in a newly designed gas mixer has been investigated with the help of computational fluid dynamics based software. The contours of pressure, turbulence intensity, velocity and mass fraction of CH4 obtained are discussed, and compared across an existing design. It is observed that the new design of the mixer promotes a homogenous mixing of biogas with air.
Classification system for mortgage arrear management

Due to the economic recession in the recent years, more and more mortgage customers default on the payments. This brings tremendous losses to banks and forces their arrear management departments to develop more efficient processes. In this paper, we propose a classification system to predict the outcome of a mortgage arrear. Each customer who delays a monthly mortgage rate payment is assigned a label with two possible values: a delayer, who will pay the rate before the end of the month, and a defaulter, who will fail to do so. In this way, the arrear management department only needs to treat defaulters intensively. We use arrear history records obtained from a data warehouse of one Dutch bank. We apply basic classifiers, ensemble methods and sampling techniques to this classification problem. The obtained results show that sampling techniques and ensemble learning improve the performance of basic classifiers considerably. We choose balanced random forests to build the ultimate classification system. The resulting system has already been deployed in the daily work of the arrear management department of the concerned bank, and this leads to huge cost savings.
Detecting and Measuring Selection from Gene Frequency Data

The recent advent of high-throughput sequencing and genotyping technologies makes it possible to produce, easily and cost effectively, large amounts of detailed data on the genotype composition of populations. Detecting locus-specific effects may help identify those genes that have been, or are currently, targeted by natural selection. How best to identify these selected regions, loci, or single nucleotides remains a challenging issue. Here, we introduce a new model-based method, called SelEstim, to distinguish putative selected polymorphisms from the background of neutral (or nearly neutral) ones and to estimate the intensity of selection at the former. The underlying population genetic model is a diffusion approximation for the distribution of allele frequency in a population subdivided into a number of demes that exchange migrants. We use a Markov chain Monte Carlo algorithm for sampling from the joint posterior distribution of the model parameters, in a hierarchical Bayesian framework. We present evidence from stochastic simulations, which demonstrates the good power of SelEstim to identify loci targeted by selection and to estimate the strength of selection acting on these loci, within each deme. We also reanalyze a subset of SNP data from the Stanford HGDP–CEPH Human Genome Diversity Cell Line Panel to illustrate the performance of SelEstim on real data. In agreement with previous studies, our analyses point to a very strong signal of positive selection upstream of the LCT gene, which encodes for the enzyme lactase–phlorizin hydrolase and is associated with adult-type hypolactasia. The geographical distribution of the strength of positive selection across the Old World matches the interpolated map of lactase persistence phenotype frequencies, with the strongest selection coefficients in Europe and in the Indus Valley.
Designing Human-Centered Distributed Information Systems

Many computer systems are designed according to engineering and technology principles and are typically difficult to learn and use. The fields of human-computer interaction, interface design, and human factors have made significant contributions to ease of use and are primarily concerned with the interfaces between systems and users, not with the structures that are often more fundamental for designing truly human-centered systems. The emerging paradigm of human-centered computing (HCC)-which has taken many forms-offers a new look at system design. HCC requires more than merely designing an artificial agent to supplement a human agent. The dynamic interactions in a distributed system composed of human and artificial agents-and the context in which the system is situated-are indispensable factors. While we have successfully applied our methodology in designing a prototype of a human-centered intelligent flight-surgeon console at NASA Johnson Space Center, this article presents a methodology for designing human-centered computing systems using electronic medical records (EMR) systems.
An evaluation of the prescribing patterns for under-five patients at a Tertiary Paediatric Hospital in Sierra Leone

Purpose: There is limited information on pediatric prescribing in Sierra Leone. This study evaluated prescribing patterns for under-five patients at Ola During Children's Hospital (ODCH) and assessed the extent of rational prescribing. Methods: A descriptive, cross-sectional, retrospective study of 294 prescriptions, selected by systematic random sampling was conducted at the outpatient department of ODCH. The World Health Organisation prescribing indicators were analyzed using the SPSS package 16.0. The index of rational drug prescribing (IRDP) was calculated to assess rational prescribing. Results: The average number of medicines per prescription was 3.77. The percentage of medicines prescribed by generic names was 71.0%, while 74.8% and 21.1% of prescriptions had an antibiotic and injection, respectively. The percentage of medicines prescribed from the national essential medicines list was 70.6%. The most commonly prescribed pharmacological groups of medicines were vitamins (85.37%) and antibiotics (82.99%). The IRDP was 2.71, instead of the ideal value of 5. Conclusion: Pediatric prescribing patterns at the outpatient department of ODCH cannot be said to be entirely rational, especially with regards to antibiotic and injection prescribing.
Ieee Transactions on Evolutionary Computation on the Performance of Indirect Encoding across the Continuum of Regularity

—This paper investigates how an evolutionary algorithm with an indirect encoding exploits the property of phenotypic regularity, an important design principle found in natural organisms and engineered designs. We present the first comprehensive study showing that such phenotypic regularity enables an indirect encoding to outperform direct encoding controls as problem regularity increases. Such an ability to produce regular solutions that can exploit the regularity of problems is an important prerequisite if evolutionary algorithms are to scale to high-dimensional real-world problems, which typically contain many regularities, both known and unrecognized. The indirect encoding in this case study is HyperNEAT, which evolves artificial neural networks (ANNs) in a manner inspired by concepts from biological development. We demonstrate that, in contrast to two direct encoding controls, HyperNEAT produces both regular behaviors and regular ANNs, which enables HyperNEAT to significantly outperform the direct encodings as regularity increases in three problem domains. We also show that the types of regularities HyperNEAT produces can be biased, allowing domain knowledge and preferences to be injected into the search. Finally, we examine the downside of a bias toward regularity. Even when a solution is mainly regular, some irregularity may be needed to perfect its functionality. This insight is illustrated by a new algorithm called HybrID that hybridizes indirect and direct encodings, which matched HyperNEAT's performance on regular problems yet outperformed it on problems with some irregularity. HybrID's ability to improve upon the performance of HyperNEAT raises the question of whether indirect encodings may ultimately excel not as stand-alone algorithms, but by being hybridized with a further process of refinement, wherein the indirect encoding produces patterns that exploit problem regularity and the refining process modifies that pattern to capture irregularities. This paper thus paints a more complete picture of indirect encodings than prior studies because it analyzes the impact of the continuum between irregularity and regularity on the performance of such encodings, and ultimately suggests a path forward that combines indirect encodings with a separate process of refinement.
A study of antimicrobial use in children admitted to pediatric medicine ward of a tertiary care hospital

Objectives: Antimicrobials are frequently used in tertiary care hospitals. We conducted an observational study on children admitted to a teaching hospital in Eastern India, to generate a profile of antimicrobial use and suspected adverse drug reactions (ADRs) attributable to them. Materials and Methods: Hospitalized children of either sex, aged between 1 month and 12 years, were studied. Baseline demographic and clinical features, duration of hospital stay, antimicrobials received in hospital along with dosing and indications and details of suspected ADRs attributable to their use were recorded. Every patient was followed up till discharge, admission to the Pediatric Intensive Care Unit, or death. Results: Over the 1 year study period, 332 admissions were screened. The prevalence of antimicrobial use was 79.82%. The majority of the 265 children who received antimicrobials were males (61.10%) and hailed from rural and low socioeconomic background. Median age was 36 months. Six children died, 43 were transferred out, and the rest discharged. In most instances, either 2 (40%) or a single antibiotic (39.6%) was used. Ceftriaxone, co-amoxiclav, amikacin, vancomycin, and ampicillin were predominantly used. Antivirals, antimalarials, and antiprotozoals were used occasionally. Average number of antimicrobials per patient was 2.0 ± 1.27; the majority (84.1%) were by parenteral route and initial choice was usually empirical. Prescriptions were usually in generic name. The antimicrobial treatment ranged between 1 and 34 days, with a median of 7 days. Six ADRs were noted of which half were skin rash and the rest loose stools. Conclusions: The profile of antimicrobial use is broadly similar to earlier Indian studies. Apparent overuse of multiple antimicrobials per prescription and the parenteral route requires exploration. Antimicrobials are being used empirically in the absence of policy. ADRs to antimicrobials are occasional and usually mild. The baseline data can serve in situation analysis for antibiotic prescribing guidelines.
Mitochondrial Membrane Potential Is Required for MAVS-Mediated Antiviral Signaling

The contribution of mitochondria to antiviral immune responses extends beyond their role as a platform for antiviral signaling molecules. Antiviral Mitochondrial Action Mitochondria are the energy generators of the cell, but they also act as platforms upon which complexes of proteins respond to RNA-containing viruses within the cytosol. Through genetic and pharmacological means, Koshiba et al. present evidence that suggests that the contribution of mitochondria to these antiviral responses is not as passive as originally thought. Indeed, their data suggest that successful resistance to viral infections depends on maintenance of the internal physiological functions of mitochondria coupled with the functions of the external protein complexes. Mitochondria, dynamic organelles that undergo cycles of fusion and fission, are the powerhouses of eukaryotic cells and are also involved in cellular innate antiviral immunity in mammals. Mitochondrial antiviral immunity depends on activation of the cytoplasmic retinoic acid–inducible gene I (RIG-I)–like receptor (RLR) signaling pathway and the participation of a mitochondrial outer membrane adaptor protein called MAVS (mitochondrial antiviral signaling). We found that cells that lack the ability to undergo mitochondrial fusion as a result of targeted deletion of both mitofusin 1 (Mfn1) and mitofusin 2 (Mfn2) exhibited impaired induction of interferons and proinflammatory cytokines in response to viral infection, resulting in increased viral replication. In contrast, cells with null mutations in either Mfn1 or Mfn2 retained their RLR-induced antiviral responses. We also found that a reduced mitochondrial membrane potential (ΔΨm) correlated with the reduced antiviral response. The dissipation in ΔΨm did not affect the activation of the transcription factor interferon regulatory factor 3 downstream of MAVS, which suggests that ΔΨm and MAVS are coupled at the same stage in the RLR signaling pathway. Our results provide evidence that the physiological function of mitochondria plays a key role in innate antiviral immunity.
Guidelines for the treatment of pressure ulcers

1. Co-chaired this panel 2. University of Washington, Seattle, WA 3. University of Texas Medical Branch Galveston, Galveston, TX 4. Sinai Hospital, Baltimore, MD 5. Johns Hopkins Medical Institutions, Baltimore, MD 6. University of Southern Denmark, Odense University Hospital, Odense, Denmark 7. University of South Florida, Tampa, FL 8. University of Virginia Health System, Charlottesville, VA 9. St. Louis Medical Center, St. Louis, MO, and 10. University of San Francisco, San Francisco, CA
Efficient Likelihood Learning of a Generic CNN-CRF Model for Semantic Segmentation

Deep Models, such as Convolutional Neural Networks (CNNs), are omnipresent in computer vision, as well as, structured models, such as Conditional Random Fields (CRFs). Combining them brings many advantages, foremost the ability to in-cooperate prior knowledge into CNNs, e.g. by explicitly modelling the dependencies between output variables. In this work we present a CRF model were unary factors are dependent on a CNN. Our main contribution is an efficient and scalable, maximum likelihood-based, learning procedure to infer all model parameters jointly. Previous work either concentrated on piecewise-training, or maximum likelihood learning of restricted model families, such as Gaussian CRFs or CRFs with a few variables only. In contrast, we are the first to perform maximum likelihood learning for large-sized factor graphs with non-parametric potentials. We have applied our model to the task of semantic labeling of body parts in depth images. We show that it is superior to selected competing models and learning strategies. Furthermore, we empirically observe that our model can capture shape and context information of relating body parts.
Numerical Simulation of Heat Transfer and Gas Flow Characteristics in Honeycomb Ceramics

Honeycomb ceramics is the key component of the thermal flow-reversal reactor, which is for oxidation of coal mine ventilation air methane. In this paper, numerical simulation method was used to study the honeycomb ceramics' heat transfer process, and the effects of temperature difference and hole side length on heat transfer and the resistance losses were investigated. The calculating results show that the temperature difference between the gas and honeycomb ceramics is larger, then the heat transfer effect is better, and the resistance loss is bigger. In the situation other parameters are the same, then the hole side length is longer, the heat transfer efficiency is lower, and the resistance loss is smaller.
Renal cell carcinoma: preoperative assessment for enucleative surgery with angiography, CT, and MRI.

PURPOSE Our purpose was to assess various imaging methods in detecting a pseudocapsule of renal cell carcinoma (RCC), which is critical for successful tumor enucleation. METHOD In 42 patients with histopathologically proven RCC, images obtained at angiography (n = 42), CT (n = 30), and MRI (n = 19) were investigated retrospectively. All patients underwent treatment (enucleation: n = 15; nephrectomy: n = 27). The imaging criteria for the presence of a pseudocapsule were as follows: a surrounding radiolucent rim on angiography, a low or high density rim on CT, and a low intensity rim on MRI. All images were retrospectively reviewed by three radiologists without knowledge of the clinical and histological findings. RESULTS Thirty-three of 42 RCCs showed a pseudocapsule on the surgical specimen. A pseudocapsule was detected in 67% of tumors (22/33) on angiography, 26% (6/23) on CT, 27% (4/15) on T1-weighted MRI, 93% (14/15) on T2-weighted MRI, 67% (8/12) on dynamic enhanced T1-weighted MRI, and 15% (2/13) on delayed enhanced T1-weighted MRI. CONCLUSION T2-weighted MR images are superior for visualizing a pseudocapsule of RCC and for providing reliable selection criteria for tumor enucleation.
Dynamic partitioning of mitotic kinesin-5 cross-linkers between microtubule-bound and freely diffusing states

The dynamic behavior of homotetrameric kinesin-5 during mitosis is poorly understood. Kinesin-5 may function only by binding, cross-linking, and sliding adjacent spindle microtubules (MTs), or, alternatively, it may bind to a stable “spindle matrix” to generate mitotic movements. We created transgenic Drosophila melanogaster expressing fluorescent kinesin-5, KLP61F-GFP, in a klp61f mutant background, where it rescues mitosis and viability. KLP61F-GFP localizes to interpolar MT bundles, half spindles, and asters, and is enriched around spindle poles. In fluorescence recovery after photobleaching experiments, KLP61F-GFP displays dynamic mobility similar to tubulin, which is inconsistent with a substantial static pool of kinesin-5. The data conform to a reaction–diffusion model in which most KLP61F is bound to spindle MTs, with the remainder diffusing freely. KLP61F appears to transiently bind MTs, moving short distances along them before detaching. Thus, kinesin-5 motors can function by cross-linking and sliding adjacent spindle MTs without the need for a static spindle matrix.