Miracle-dz/UniFAR-FTUs huggingface dataset:
Two Types of KY Buck–Boost Converters

A novel voltage-bucking/boosting converter, named as KY buck-boost converter (i.e., 2D converter), is presented herein. Unlike the traditional buck-boost converter, this converter possesses fast transient responses, similar to the behavior of the buck converter with synchronous rectification. In addition, it possesses the non-pulsating output current, thereby not only decreasing the current stress on the output capacitor but also reducing the output voltage ripple. Furthermore, it has the positive output voltage, different from the negative output voltage of the traditional buck-boost converter. Above all, there are two types of KY buck-boost converters presented herein. In this paper, the basic operating principles of the proposed converters are first illustrated in detail, and second, some experimental results are offered to verify the effectiveness of the proposed topologies.
Development of a comprehensive clinical performance assessment system for nursing students: A programmatic approach.

AIM Evaluation of achievement of learning objectives needs an accurate assessment program. Hence, nursing educators should move away from the use of individual assessment methods to apply a programmatic approach. The aim of this study was to develop a comprehensive assessment system for nursing students in their critical care rotation based on a programmatic approach. METHODS The population of this study was nursing students in their critical care course. The learning objectives of the course were determined using an expert panel and classified into three categories. Suitable assessment methods were identified for each category according to the consensus of experts. Then, the assessment tools were designed and the content validity was established using content validity ratio (CVR) and index (CVI). The reliability was determined by Cronbach's alpha coefficient. The satisfaction of the participants was investigated using a questionnaire. RESULTS According to the findings, all items of the assessment system had a high CVR (P < 0.05) and CVI ranged 0.93-0.97. The alpha coefficient of the whole system was more than 0.90 and for subsystems ranged 0.72-0.96. The findings showed that 87.5% of the instructors and 89.47% of students believed that the new assessment system had a positive impact on learning. In addition, the majority of them were satisfied with the new assessment system. CONCLUSION A programmatic approach should be used for effective evaluation of clinical performance of nursing students in critical care settings because of high validity and reliability, multidimensionality, positive educational impact, and acceptability.
Ten-year predicted coronary heart disease risk in HIV-infected men and women.

BACKGROUND Highly active antiretroviral therapy (HAART), in addition to traditional vascular risk factors, may affect coronary heart disease (CHD) risk in individuals with human immunodeficiency virus (HIV) infection. METHODS Among HIV-infected (931 men and 1455 women) and HIV-uninfected (1099 men and 576 women) adults, the predicted risk of CHD was estimated on the basis of age, sex, lipid and blood pressure levels, the presence of diabetes, and smoking status. RESULTS Among HIV-infected men, 2% had moderate predicted risk of CHD (10-year CHD risk, 15%-25%), and 17% had high predicted risk (10-year CHD risk of > or = 25% or diabetes). Among HIV-infected women, 2% had moderate predicted CHD risk, and 12% had high predicted CHD risk. Compared with users of protease inhibitor-based HAART, the adjusted odds ratio (OR) for moderate-to-high risk of CHD was significantly lower among HAART-naive individuals (OR, 0.57; 95% confidence interval [CI], 0.36-0.89). Users of HAART that was not protease inhibitor based (OR, 0.74; 95% CI, 0.53-1.01) and former HAART users (OR, 0.68; 95% CI, 0.46-1.03) were also less likely than users of protease inhibitor-based HAART to have moderate-to-high CHD risk, although 95% CIs overlapped the null. Low income was associated with increased likelihood of moderate-to-high CHD risk (for annual income < $10,000 vs. > $40,000: OR, 2.32; 95% CI, 1.51-3.56 ). Elevated body mass index (calculated as weight in kilograms divided by the square of height in meters) predicted increased likelihood of moderate-to-high CHD risk (for BMI of 18.5-24.9 vs. BMI of 25-30: OR, 1.41 [95% CI, 1.03-1.93]; for BMI of 18.5-24.9 vs. BMI > or = 30: OR, 1.79 [95% CI, 1.25-2.56]). CONCLUSIONS Among HIV-infected adults, in addition to antiretroviral drug exposures, being overweight and having a low income level were associated with increased predicted CHD risk. This suggests a need to target HIV-infected men and women with these characteristics for vascular risk factor screening.
Less frequent eating predicts greater BMI and waist circumference in female adolescents 1-3

Background: Little is known about the effect of eating frequency on adiposity. Objective: The study aim was to assess the prospective relation of an objective measure of eating frequency with adiposity in girls from ages 9–10 to 19–20 y. Design: By using data from 3-d diet records collected from 2372 girls in the National Heart, Lung, and Blood Institute Growth and Health Study, meal, snack, and total eating frequencies aggregated over the first 2 study years were examined in relation to 10-y change in BMI and waist circumference (WC). Results: Eating frequency was lower in black and older girls than in white and younger girls (P , 0.0001). In whites, lower initial snack and total eating frequencies were related to greater 10-y increases in BMI (P = 0.023 and 0.012, respectively) and WC (P = 0.030 and 0.015, respectively). In blacks, lower initial meal and snack frequencies were related to greater increases in BMI (P = 0.004 and 0.022, respectively) and WC (P = 0.052 and 0.005, respectively). Also, in blacks, lower initial total eating frequency was related to greater increases in WC (P = 0.010). After adjustment for baseline adiposity measure, race, parental education, physical activity, television and video viewing, total energy intake, and dieting for weight loss, lower initial total eating frequency remained related to greater 10-y increases in BMI ( P= 0.013) and WC (P = 0.036). Conclusions: A lower eating frequency predicts a greater gain in adiposity in adolescent females. Intervention trials are needed to test if changing the frequency of eating can affect obesity risk. Am J Clin Nutr doi: 10.3945/ajcn.111. 016881.
Effects of Molecular Weight and Loading on Matrix Metalloproteinase-2 Mediated Release from Poly(Ethylene Glycol) Diacrylate Hydrogels

Herein, we report on continued efforts to understand an implantable poly(ethylene glycol) diacrylate (PEGDA) hydrogel drug delivery system that responds to extracellular enzymes, in particular matrix metalloproteinase-2 (MMP-2) to provide controlled drug delivery. By attaching peptide as pendant groups on the hydrogel backbone, drug release occurs at an accelerated rate in the presence of active protease. We investigated MMP-2 entry and optimized parameters of the drug delivery system. Mesh size for different PEGDA molecular weight macromers was measured with PEGDA 3,400 hydrogels having a mesh size smaller than the dimensions of MMP-2 and PEGDA 10,000 and PEGDA 20,000 hydrogels having mesh sizes larger than MMP-2. Purified MMP-2 increased release of peptide fragment compared to buffer at several loading concentrations. Cell-stimulated release was demonstrated using U-87 MG cells embedded in collagen. GM6001, an MMP inhibitor, diminished release and altered the identity of the released peptide fragment. The increase in ratio of release from PEGDA 10,000 and PEGDA 20,000 hydrogels compared to PEGDA 3,400 hydrogels suggests MMP-2 enters the hydrogel. PEGDA molecular weight of 10,000 and 15 % (w/V) were the optimal conditions for release and handling. The use of protease-triggered drug delivery has great advantage particularly with the control of protease penetration as a parameter for controlling rate of release.
Hadza sleep biology: Evidence for flexible sleep-wake patterns in hunter-gatherers.

OBJECTIVES Cross-cultural sleep research is critical to deciphering whether modern sleep expression is the product of recent selective pressures, or an example of evolutionary mismatch to ancestral sleep ecology. We worked with the Hadza, an equatorial, hunter-gatherer community in Tanzania, to better understand ancestral sleep patterns and to test hypotheses related to sleep segmentation. METHODS We used actigraphy to analyze sleep-wake patterns in thirty-three volunteers for a total of 393 days. Linear mixed effects modeling was performed to assess ecological predictors of sleep duration and quality. Additionally, functional linear modeling (FLM) was used to characterize 24-hr time averaged circadian patterns. RESULTS Compared with post-industrialized western populations, the Hadza were characterized by shorter (6.25 hr), poorer quality sleep (sleep efficiency = 68.9%), yet had stronger circadian rhythms. Sleep duration time was negatively influenced by greater activity, age, light (lux) exposure, and moon phase, and positively influenced by increased day length and mean nighttime temperature. The average daily nap ratio (i.e., the proportion of days where a nap was present) was 0.54 (SE = 0.05), with an average nap duration of 47.5 min (SE = 2.71; n = 139). DISCUSSION This study showed that circadian rhythms in small-scale foraging populations are more entrained to their ecological environments than Western populations. Additionally, Hadza sleep is characterized as flexible, with a consistent early morning sleep period yet reliance upon opportunistic daytime napping. We propose that plasticity in sleep-wake patterns has been a target of natural selection in human evolution.
Dynamics of particle-particle collisions in a viscous liquid

When two solid spheres collide in a liquid, the dynamic collision process is slowed by viscous dissipation and the increased pressure in the interparticle gap as compared with dry collisions. This paper investigates liquid-immersed head-on and oblique collisions, which complements previously investigated particle-on-wall immersed collisions. By defining the normal from the line of centers at contact, the experimental findings support the decomposition of an oblique collision into its normal and tangential components of motion. The normal relative particle motion is characterized by an effective coefficient of restitution and a binary Stokes number with a correlation that follows the particle-wall results. The tangential motion is described by a collision model using a normal coefficient of restitution and a friction coefficient that are modified for the liquid effects.
Protective effects of dietary arginine supplementation against oxidative stress in weaned piglets

Oxidative stress is detrimental to animals. Previous studies have indicated that arginine (Arg) may function as a potential substance against oxidative stress. The present study was conducted to explore the potential mechanisms behind the Arg-induced protective effects against oxidative stress in piglets. A total of thirty-six piglets were randomly allocated to six groups with six replicates per group. Piglets were subjected to three dietary treatments (namely two groups per treatment) in week 1 and fed with a basal diet (ArgL) or the basal diet supplemented with 0·8 % (ArgM) or 1·6 % (ArgH) l-Arg, respectively. On day 8, piglets were injected intraperitoneally either with diquat (10 mg/kg body weight) or sterile saline. The whole trial lasted 11 d. Results showed that dietary Arg supplementation did not affect growth performance in week 1. Oxidative stress significantly decreased the growth performance of piglets (P< 0·05). However, ArgH attenuated the negative effects of oxidative stress on feed intake and significantly increased the total antioxidant capacity in the liver under oxidative stress (P< 0·05). Both ArgM and ArgH enhanced the activities of plasma glutathione peroxidases and superoxide dismutases and decreased the IL-6 and TNF-α mRNA level in the liver under oxidative stress (P< 0·05). The present study not only shows that Arg can function as a potential nutrient to alleviate oxidative stress responses through the enhancement of antioxidant capacity, and inhibition of the expression of inflammatory cytokines, but the results also suggest that alleviation of oxidative stress responses using dietary nutrient components deserves further attention in the future.
The Prognostic Value of Adaptive Nuclear Texture Features from Patient Gray Level Entropy Matrices in Early Stage Ovarian Cancer

Background: Nuclear texture analysis gives information about the spatial arrangement of the pixel gray levels in a digitized microscopic nuclear image, providing texture features that may be used as quantitative tools for prognosis of human cancer. The aim of the study was to evaluate the prognostic value of adaptive nuclear texture features in early stage ovarian cancer. Methods: 246 cases of early stage ovarian cancer were included in the analysis. Isolated nuclei (monolayers) were prepared from 50 μm tissue sections and stained with Feulgen-Schiff. Local gray level entropy was measured within small windows of each nuclear image and stored in gray level entropy matrices. A compact set of adaptive features was computed from these matrices. Results: Univariate Kaplan-Meier analysis showed significantly better relapse-free survival (p < 0.001) for patients with low adaptive feature values compared to patients with high adaptive feature values. The 10-year relapse-free survival was about 78% for patients with low feature values and about 52% for patients with high feature values. Adaptive features were found to be of independent prognostic significance for relapse-free survival in a multivariate analysis. Conclusion: Adaptive nuclear texture features from entropy matrices contain prognostic information and are of independent prognostic significance for relapse-free survival in early stage ovarian cancer.
Space Reduction for Contextual Transaction Trust Computation in E-Commerce and E-Service Environments

In the literature, Contextual Transaction Trust computation (termed as CTT computation) is considered an effective approach to evaluate the trustworthiness of a seller. Specifically, it computes a seller's reputation profile to indicate his/her dynamic trustworthiness in different product categories, price ranges, time periods, and any necessary combination of them. Then, in order to promptly answer a buyer's requests on the results of CTT computation, CMK-tree has been designed to appropriately index the precomputed aggregation results over large-scale ratings and transaction data. Nevertheless, CMK-tree requires additional storage space. In practice, a seller usually has a large volume of transactions. Moreover, with significant increase of historical transaction data (e.g., Over one or two years), the size of storage space consumed by CMK-tree will become much larger. In reducing storage space consumption for CTT computation, the aggregation results that are generated based on the ratings and transaction data from remote history, e.g., "12 months ago" can be deleted, as the ratings from remote history are less important for evaluating a seller's recent behavior. However, to achieve nearly linear and robust query performance, the deletion operations in the CMK-tree become complicated. In this paper, we propose three deletion strategies for CTT computation based on CMK-tree. With our proposed deletion strategies, the additional storage space consumption can be restricted to a limited range, which offers great benefit to trust management with millions of sellers. Finally, we have conducted experiments to illustrate both advantages and disadvantages of the proposed deletion strategies.
Evolution and Functional Impact of Rare Coding Variation from Deep Sequencing of Human Exomes

A Deep Look Into Our Genes Recent debates have focused on the degree of genetic variation and its impact upon health at the genomic level in humans (see the Perspective by Casals and Bertranpetit). Tennessen et al. (p. 64, published online 17 May), looking at all of the protein-coding genes in the human genome, and Nelson et al. (p. 100, published online 17 May), looking at genes that encode drug targets, address this question through deep sequencing efforts on samples from multiple individuals. The findings suggest that most human variation is rare, not shared between populations, and that rare variants are likely to play a role in human health. Most functionally consequential variants in protein-coding genes are rare and, thus, difficult to find. As a first step toward understanding how rare variants contribute to risk for complex diseases, we sequenced 15,585 human protein-coding genes to an average median depth of 111× in 2440 individuals of European (n = 1351) and African (n = 1088) ancestry. We identified over 500,000 single-nucleotide variants (SNVs), the majority of which were rare (86% with a minor allele frequency less than 0.5%), previously unknown (82%), and population-specific (82%). On average, 2.3% of the 13,595 SNVs each person carried were predicted to affect protein function of ~313 genes per genome, and ~95.7% of SNVs predicted to be functionally important were rare. This excess of rare functional variants is due to the combined effects of explosive, recent accelerated population growth and weak purifying selection. Furthermore, we show that large sample sizes will be required to associate rare variants with complex traits.
Joint Dimensionality Reduction for Two Feature Vectors

Many machine learning problems, especially multi-modal learning problems, have two sets of distinct features (e.g., image and text features in news story classification, or neuroimaging data and neurocognitive data in cognitive science research). This paper addresses the joint dimensionality reduction of two feature vectors in supervised learning problems. In particular, we assume a discriminative model where low-dimensional linear embeddings of the two feature vectors are sufficient statistics for predicting a dependent variable. We show that a simple algorithm involving singular value decomposition can accurately estimate the embeddings provided that certain sample complexities are satisfied, without specifying the nonlinear link function (regressor or classifier). The main results establish sample complexities under multiple settings. Sample complexities for different link functions only differ by constant factors.
Human detection in crowded scenes

In this paper, our focus is to segment the foreground area for human detection. It is assumed that the foreground region has been detected. Accurate foreground contours are not required. The developed approach adopts a modified ISM (Implicit Shape Model) to collect some typical local patches of human being and their location information. Individuals are detected by grouping some local patches in the foreground area. The method can get good results in crowded scenes. Some examples based on CAVIAR dataset have been shown. A main contribution of the paper is that ISM model and joint occlusion analysis are combined for individual segmentation. There are mainly two advantages: First, with more sufficient information inside the foreground region, even the individuals inside a dense area can also be handled. Secondly, the method does not require an accurate foreground contour. A rough foreground area can be easily obtained in most situations.
Challenges and advances in optimizing liver allografts from donation after circulatory death donors

In recent years, there has been a shift in the donor demographics with an increase in donation after circulatory death (DCD). Livers obtained from DCD donors are known to have poorer outcomes when compared to donors after brainstem death and currently only a small proportion of DCD livers are used. This review outlines the recent technological developments in liver DCD donation, including clinical studies using normothermic regional perfusion and extracorporal machine perfusion of livers from DCD donors.
A Selection Bias Conflict and Frequentist versus Bayesian Viewpoints

In many branches of modern science, researchers first study or mine large datasets, and then select the parameters they estimate and the data they use and publish. Such data-based selection complicates formal statistical inference. An example discussed here for the purpose of illustration, is that of pharmaceutical companies that typically conduct many experiments but may publish only selected data. The selection often depends on the outcomes of the experiments since naturally there is interest in potentially useful drugs, and it is in general unclear how it should affect inference. Is this effect the same for the company and the public? Does it matter if they are Bayesian or frequentist? Should the company reveal all experiments it conducts and, if so, how should this change the conclusions? This note discusses these questions in terms of a simple example of a sequence of binomial experiments conducted by a pharmaceutical company, where results are published only if the number of “failures” is small. We do not suggest that this example corresponds to reality in the pharmaceutical industry, nor in science in general; our goal is to elaborate on the importance and difficulties of taking selection into account when performing statistical analysis.
Suppression of Insulin Receptor Substrate 1 (IRS-1) Promotes Mammary Tumor Metastasis

ABSTRACT The insulin receptor substrate (IRS) proteins are cytoplasmic adaptors that organize signaling complexes downstream of activated cell surface receptors. Here, we show that IRS-1 and IRS-2, despite significant homology, play critical yet distinct functions in breast cancer, and we identify specific signaling pathways that are influenced by IRS-1 using the polyoma virus middle-T (PyV-MT) transgenic mouse model of mammary carcinoma and Irs-1 null (Irs1−/−) mice. The absence of Irs-1 expression enhanced metastatic spread significantly without a significant effect on primary tumor growth. Orthotopic transplant studies revealed that the increased metastatic potential of Irs1-deficient tumor cells is cell autonomous. Mammary tumors that developed in PyV-MT::Irs1−/− mice exhibited elevated Irs-2 function and enhanced phosphatidylinositol 3-kinase/Akt/mTor activity, suggesting that one mechanism by which Irs-1 impedes metastasis is to suppress Irs-2-dependent signaling. In support of this mechanism, reduction of Irs-2 expression in Irs1−/− tumor cells restored mTor signaling to wild-type levels. PyV-MT::Irs1−/− tumors also exhibited a significant increase in vascular endothelial growth factor expression and microvessel density, which could facilitate their dissemination. The significance of our findings for human breast cancer is heightened by our observation that Irs-1 is inactivated in wild-type, metastatic mammary tumors by serine phosphorylation. Collectively, our findings reveal that inactivation of IRS-1 enhances breast cancer metastasis and support the novel hypothesis that IRS-1 has metastasis suppressor functions for breast cancer.
An ultra-compliant, scalable neural probe with molded biodissolvable delivery vehicle

This paper describes an ultra-compliant parylene-platinum neural probe embedded in a biodissolvable delivery vehicle. High probe compliance is achieved using thin wires (width of 10.0 μm and thickness of 2.7 μm) and by meandering the probe. The insertion of the ultra-compliant probe is achieved by encasing it in a dissolvable delivery vehicle made from molded carboxy-methylcellulose. In vivo implantations of delivery vehicles with 1.5 mm long shanks, widths of 100 μm and 300 μm and a targeted thickness of 135 μm have been done through the dura in the cortex of Sprague-Dawley rats at a speed of 80 mm-s-1. The delivery vehicle becomes a gel over a period of less than three minutes, after which the handling portions of the delivery vehicle are removed leaving the shanks embedded in the brain.