Miracle-dz/UniFAR-FTUs huggingface dataset:
Nurse practitioner comanagement for patients in an academic geriatric practice.

OBJECTIVE To determine whether nurse practitioner (NP) comanagement can improve the quality of care for 5 chronic conditions in an academic geriatrics practice. STUDY DESIGN AND METHODS From September 2006 to September 2007, 18 primary care geriatricians were divided into an intervention group that could refer patients to an NP for comanagement of dementia, depression, falls, heart failure, and/or urinary incontinence, or a control group that indicated which patients would have been referred to the NP for these conditions. The NP used structured visit notes to guide care delivery for the 5 conditions concordant with Assessing Care of Vulnerable Elders-3 (ACOVE-3) quality indicators. We reviewed charts to determine adherence to recommended processes of care. RESULTS A total of 200 patients (108 intervention, 92 control) were eligible for at least 1 process of care recommended by ACOVE-3 for the 5 conditions. Patients' mean (SD) age was 85 years (7 years), 67% were women, and patients were eligible for a mean (SD) of 6.9 (4.4) processes of care. Intervention patients were eligible for more care processes than controls (7.8 vs 5.9 processes per patient; P = .002). Quality of care was higher for patients in the intervention group compared with the control group (54% vs 34% of care processes completed; P <.001). The adjusted absolute difference between intervention and control groups in care processes completed was 20% (95% confidence interval = 13%, 27%). CONCLUSION NP comanagement of 5 chronic conditions was associated with higher quality of care, even in a practice of geriatricians.
Rating prediction using preference relations based matrix factorization

Rating prediction is an important problem for rating based recommender systems. In Rating Prediction, the task is to predict the rating that a user would give to an item that he/she has not rated in the past. Most of the existing algorithms for the task concentrate on the absolute ratings given to different items by different users in the past. However, there are few recent research work that point out some drawbacks of absolute rating based systems and algorithms, and suggest the use of preference relations between pairs of items to capture the users’ interests about the items. In this paper, we propose a rating prediction algorithm that considers the relative ratings given by the users for different pairs of items. The algorithm models the users and items using a matrix factorization framework. The learned model of users and items are first used to predict the personalized utility of an item for a user. This utility is then converted to a valid rating value in a predefined rating scale by employing a personalized scaling. Experimental evaluation on a benchmark dataset reveals that better prediction accuracies may be achieved by modeling the users and items using relative rating information.
DREAM4: Combining Genetic and Dynamic Information to Identify Biological Networks and Dynamical Models

Background Current technologies have lead to the availability of multiple genomic data types in sufficient quantity and quality to serve as a basis for automatic global network inference. Accordingly, there are currently a large variety of network inference methods that learn regulatory networks to varying degrees of detail. These methods have different strengths and weaknesses and thus can be complementary. However, combining different methods in a mutually reinforcing manner remains a challenge. Methodology We investigate how three scalable methods can be combined into a useful network inference pipeline. The first is a novel t-test–based method that relies on a comprehensive steady-state knock-out dataset to rank regulatory interactions. The remaining two are previously published mutual information and ordinary differential equation based methods (tlCLR and Inferelator 1.0, respectively) that use both time-series and steady-state data to rank regulatory interactions; the latter has the added advantage of also inferring dynamic models of gene regulation which can be used to predict the system's response to new perturbations. Conclusion/Significance Our t-test based method proved powerful at ranking regulatory interactions, tying for first out of methods in the DREAM4 100-gene in-silico network inference challenge. We demonstrate complementarity between this method and the two methods that take advantage of time-series data by combining the three into a pipeline whose ability to rank regulatory interactions is markedly improved compared to either method alone. Moreover, the pipeline is able to accurately predict the response of the system to new conditions (in this case new double knock-out genetic perturbations). Our evaluation of the performance of multiple methods for network inference suggests avenues for future methods development and provides simple considerations for genomic experimental design. Our code is publicly available at http://err.bio. nyu.edu/inferelator/.
ASSESSMENT OF MANAGERS' PERFORMANCE AND ITS RELATIONSHIP WITH JOB STRESS THROUGH 360 DEGREE FEEDBACK METHOD

This research was conducted in order to assess the managers’ performance of Lorestan Gas Company using 360 degrees method and its relation with their job stress. The current study is a descriptive one; meanwhile it enjoys the correlational approach as well. The pertaining population comes up to 159 persons. Regarding Tuchman or Morgan-Kuhen tables, we find out that if we wish to reach a reasonable conclusion of the analysis, the sample should involve 113 subjects. The researcher has used two questionnaires. The first one is related to 360 degree feedback model while the second one dealt with the job stress based on the standardized questionnaire proposed by……. (1978). The aforementioned questionnaires include Cronbach’s Alpha coefficients of 93.87 and 92 which are considered as plausible coefficients for the questionnaires. Elsewhere, the validity of questionnaires was determined by the experts’ comments. The findings were given through statistical analyses of one way ANOVA, Tucky test and Pearson’s correlational coefficient. The acquired conclusions have demonstrated that there are meaningful differences among the means of 360 degree as selfassessments, supervisors’ assessment, colleagues’ assessment and employees’ assessment. On the other hand, there are meaningful differences among the assessments of managers, employees and job stress while there is no significant difference between the assessment done on the basis of 360 degree feedback model, self-assessment, the colleagues and managers’ assessments and job stress.
Efficiency improvement by frequency modulation depending on load current for inductor commutation soft-switched PWM inverter

Efficiency of inductor commutation soft-switched PWM inverter is improved by frequency modulation of the carrier signal. In this paper we propose a novel FM technique for more improvement of the efficiency and analyze the loss and efficiency of the inverter. These results are verified experimentally and the effectiveness of FM is shown.
Comprehensive miRNA Expression Analysis in Peripheral Blood Can Diagnose Liver Disease

Background miRNAs circulating in the blood in a cell-free form have been acknowledged for their potential as readily accessible disease markers. Presently, histological examination is the golden standard for diagnosing and grading liver disease, therefore non-invasive options are desirable. Here, we investigated if miRNA expression profile in exosome rich fractionated serum could be useful for determining the disease parameters in patients with chronic hepatitis C (CHC). Methodology Exosome rich fractionated RNA was extracted from the serum of 64 CHC and 24 controls with normal liver (NL). Extracted RNA was subjected to miRNA profiling by microarray and real-time qPCR analysis. The miRNA expression profiles from 4 chronic hepatitis B (CHB) and 12 non alcoholic steatohepatitis (NASH) patients were also established. The resulting miRNA expression was compared to the stage or grade of CHC determined by blood examination and histological inspection. Principal Findings miRNAs implicated in chronic liver disease and inflammation showed expression profiles that differed from those in NL and varied among the types and grades of liver diseases. Using the expression patterns of nine miRNAs, we classified CHC and NL with 96.59% accuracy. Additionally, we could link miRNA expression pattern with liver fibrosis stage and grade of liver inflammation in CHC. In particular, the miRNA expression pattern for early fibrotic stage differed greatly from that observed in high inflammation grades. Conclusions We demonstrated that miRNA expression pattern in exosome rich fractionated serum shows a high potential as a biomarker for diagnosing the grade and stage of liver diseases.
Computational Estimation Skill of College Students

We examined computational estimation skill of 77 college students who estimated answers to problems presented in brief intervals. We categorized 23 "think-aloud" estimation strategies used by 45 participants in individual follow-up sessions. Some categories were based on strategies found in previous studies; others were based on responses in this study. Although students correctly estimated answers to most problems on addition and subtraction of whole numbers, they performed poorly on multiplication and division of decimals and subtraction of fractions. Students were more successful in solving computational problems than in estimating answers. Scores on the estimation tests showed substantial correlation with SAT Mathematics scores and
ShcA Protects against Epithelial–Mesenchymal Transition through Compartmentalized Inhibition of TGF-β-Induced Smad Activation

Epithelial–mesenchymal transition (EMT) is a normal cell differentiation event during development and contributes pathologically to carcinoma and fibrosis progression. EMT often associates with increased transforming growth factor-β (TGF-β) signaling, and TGF-β drives EMT, in part through Smad-mediated reprogramming of gene expression. TGF-β also activates the Erk MAPK pathway through recruitment and Tyr phosphorylation of the adaptor protein ShcA by the activated TGF-β type I receptor. We found that ShcA protects the epithelial integrity of nontransformed cells against EMT by repressing TGF-β-induced, Smad-mediated gene expression. p52ShcA competed with Smad3 for TGF-β receptor binding, and down-regulation of ShcA expression enhanced autocrine TGF-β/Smad signaling and target gene expression, whereas increased p52ShcA expression resulted in decreased Smad3 binding to the TGF-β receptor, decreased Smad3 activation, and increased Erk MAPK and Akt signaling. Furthermore, p52ShcA sequestered TGF-β receptor complexes to caveolin-associated membrane compartments, and reducing ShcA expression enhanced the receptor localization in clathrin-associated membrane compartments that enable Smad activation. Consequently, silencing ShcA expression induced EMT, with increased cell migration, invasion, and dissemination, and increased stem cell generation and mammosphere formation, dependent upon autocrine TGF-β signaling. These findings position ShcA as a determinant of the epithelial phenotype by repressing TGF-β-induced Smad activation through differential partitioning of receptor complexes at the cell surface.
English at Universeum. A Needs Analysis of Communication in English at the Science Center Universeum in Gothenburg

The purpose of this study is to investigate how English is used at Universeum, the largest science center in Scandinavia, and also to identify any needs for improving the communication in English. To do this, a needs analysis is conducted that identifies the present state of Universeum’s English as well as a target situation in which the all the communicative goals for the language are met. In order to triangulate these two situations, the analysis makes use of three separate approaches: a questionnaire, three semi-structured interviews, and a text analysis of sign texts. The analysis shows that English is frequently used, in both written and oral form, in communication with visitors, business partners, and other zoos and science centers, but also between colleagues. The overall level of English is high, but some areas for improvement are identified. The questionnaire and interviews show that formal spoken communication in the form of scheduled guided tours and other activities are needed. The text analysis shows that there are many discrepancies between the signs’ Swedish and English texts, and that the English versions are often more complex. The study ends with a table that summarizes the needs and some suggested actions for improvements.
SEBAL-A: A Remote Sensing ET Algorithm that Accounts for Advection with Limited Data. Part I: Development and Validation

The Surface Energy Balance Algorithm for Land (SEBAL) is one of the remote sensing (RS) models that are increasingly being used to determine evapotranspiration (ET). SEBAL is a widely used model, mainly due to the fact that it requires minimum weather data, and also no prior knowledge of surface characteristics is needed. However, it has been observed that it underestimates ET under advective conditions due to its disregard of advection as another source of energy available for evaporation. A modified SEBAL model was therefore developed in this study. An advection component, which is absent in the original SEBAL, was introduced such that the energy available for evapotranspiration was a sum of net radiation and advected heat energy. The improved SEBAL model was termed SEBAL-Advection or SEBAL-A. An important aspect of the improved model is the estimation of advected energy using minimal weather data. While other RS models would require hourly weather data to be able to account for advection (e.g., METRIC), SEBAL-A only requires daily averages of limited weather data, making it appropriate even in areas where weather data at short time steps may not be available. In this study, firstly, the original SEBAL model was evaluated under advective and non-advective conditions near Rocky Ford in southeastern Colorado, a semi-arid area where afternoon advection is common occurrence. The SEBAL model was found to incur large errors when there was advection (which was indicated by higher wind speed and warm and dry air). SEBAL-A was then developed and validated in the same area under standard surface conditions, which were described as healthy alfalfa with height of 40–60 cm, without water-stress. ET values estimated using the original and modified SEBAL were compared to large weighing lysimeter-measured ET values. When the SEBAL ET was compared to SEBAL-A ET values, the latter showed improved performance, with the ET Mean Bias Error (MBE) reduced from −17.1% for original SEBAL to 2.2% for SEBAL-A and the Root Mean Square Error (RMSE) reduced from 25.1% to 10.9%, respectively. It was therefore concluded that the developed SEBAL-A model was capable of accounting for advection and therefore suitable for arid and semi-arid regions where advection is common.
TomusBlobs: Towards Communication-Efficient Storage for MapReduce Applications in Azure

The emergence of cloud computing brought the opportunity to use large-scale compute infrastructures for a broad spectrum of applications and users. As the cloud paradigm gets attractive for the " elasticity'' in resource usage and associated costs (the users only pay for resources actually used), cloud applications still suffer from the high latencies and low performance of cloud storage services. Enabling high-throughput massive data processing on cloud data becomes a critical issue, as it impacts the overall application performance. In this paper we address the above challenge at the level of the cloud storage. We introduce a concurrency-optimized data storage system which federates the virtual disks associated to VMs. We demonstrate the performance of our solution for efficient data-intensive processing on commercial clouds by building an optimized prototype MapReduce framework for Azure that leverages the benefits of our storage solution. We perform extensive synthetic benchmarks as well as experiments with real-world applications: they demonstrate that our solution brings substantial benefits to data intensive applications compared to approaches relying on state-of-the-art cloud object storage.
SPECT image analysis using statistical parametric mapping in patients with Parkinson's disease.

UNLABELLED This study investigated alterations in regional cerebral blood flow (rCBF) in patients with Parkinson's disease using statistical parametric mapping (SPM). METHODS Noninvasive rCBF measurements using 99mTc-ethyl cysteinate dimer (ECD) SPECT were performed on 28 patients with Parkinson's disease and 48 age-matched healthy volunteers. The Parkinson's disease patients were divided into two groups, 16 patients with Hoehn and Yahr stage I or II and 12 patients with Hoehn and Yahr stage III or IV. We used the raw data (absolute rCBF parametric maps) and the adjusted rCBF images in relative flow distribution (normalization of global CBF for each subject to 50 mL/100 g/min with proportional scaling) to compare these groups with SPM. RESULTS In patients with stage I or II Parkinson's disease, we found a diffuse decrease in absolute rCBF in the whole brain with sparing of the central gray matter, hippocampus and right lower temporal lobe compared with healthy volunteers. Adjusted rCBF increased in both putamina and the right hippocampus. In patients with stage III or IV disease, rCBF decreased throughout the whole brain. Adjusted rCBF increased bilaterally in the putamina, globi pallidi, hippocampi and cerebellar hemispheres (dentate nuclei) and in the left ventrolateral thalamus, right insula and right inferior temporal gyrus. CONCLUSION SPM analysis showed that significant rCBF changes in Parkinson's disease accompanied disease progression and related to disease pathophysiology in the functional architecture of thalamocortex-basal ganglia circuits and related systems.
Monolithic integration of a 10 Gb/s Mach-Zehnder modulator and a widely tunable laser based on a 2-ring loop-filter

A 10-Gb/s Mach-Zehnder modulator is monolithically integrated with a tunable laser source based on a 2-ring loop-filter with a small device dimension (2.5 × 0.9 mm2). Sufficient static extinction ratio of 16.5 dB was obtained both at 1573.92 and 1595.50 nm.
Research Note - Testing File Sharing's Impact on Music Album Sales in Cities

Using a data set including album sales, Internet penetration, and various demographic measures for 99 American cities over the period 1998--2003, this paper empirically examines the extent to which file sharing has caused the U.S. decline in sound-recording sales over that period. Also examined is the impact of the Internet on entertainment activities so as to help cleanse the Internet penetration coefficient of that impact. The conclusion from this analysis is that file sharing appears to have caused the entire decline in record sales and appears to have vitiated what otherwise would have been growth in the industry.
Latest advances on interventions that may prevent, delay or ameliorate dementia

Objectives: In this paper we aim to: (1) identify and review midlife risk factors that may contribute to the development of dementia and that may be amenable to intervention; (2) review advances made in our understanding of the most common cause of dementia, Alzheimer’s disease (AD), where current pharmacological studies have aimed to modify the disease course; and (3) explore other interventions that may slow cognitive decline in those with AD. Methods: A review of the literature was conducted to look for interventions that may modify the risk of incident dementia or that may modify symptom progression in those with diagnosed dementia. Results: (1) Midlife risks identified as amenable to intervention include blood pressure, diabetes, elevated cholesterol, poor psychosocial and lifestyle factors. (2) The leading drugs in development can be grouped by their principal target: anti-amyloid, anti-tau and mitochondrial stability. However to date, there have been no successes in late stage Phase III trials of putative disease-modifying drugs for AD. (3) Once the diagnosis of dementia has been made there is little that can slow the rate of decline. Possible exceptions include the use of exercise and antihypertensive medication with some nootropic medication showing promise in small trials. Conclusion: (1) It is clear that there are several risk factors in midlife that may lead to a greater likelihood of developing dementia. However, there is no simple intervention to modify these risks. It seems sensible to conclude from the data that avoiding high blood pressure, controlling cholesterol and diabetes as well as maintaining a healthy diet and lifestyle may lower the risk of developing dementia. (2) The need for better outcome measures in clinical trials is evident and may, in part, explain the numerous failures in late-stage clinical trials of disease-modifying drugs. Improved diagnostic test batteries to reduce population heterogeneity in early intervention studies will be required for robust clinical trials in the future. (3) Current research indicates that there is little that can delay decline; however, future trials may wish to focus on nootropics.
Functional Connectivity-Based Parcellation of the Thalamus: An Unsupervised Clustering Method and Its Validity Investigation

Node definition or delineating how the brain is parcellated into individual functionally related regions is the first step to accurately map the human connectome. As a result, parcellation of the human brain has drawn considerable attention in the field of neuroscience. The thalamus is known as a relay in the human brain, with its nuclei sending fibers to the cortical and subcortical regions. Functional magnetic resonance imaging techniques offer a way to parcellate the thalamus in vivo based on its connectivity properties. However, the parcellations from previous studies show that both the number and the distribution of thalamic subdivisions vary with different cortical segmentation methods. In this study, we used an unsupervised clustering method that does not rely on a priori information of the cortical segmentation to parcellate the thalamus. Instead, this approach is based on the intrinsic resting-state functional connectivity profiles of the thalamus with the whole brain. A series of cluster solutions were obtained, and an optimal solution was determined. Furthermore, the validity of our parcellation was investigated through the following: (1) identifying specific resting-state connectivity patterns of thalamic parcels with different brain networks and (2) investigating the task activation and psychophysiological interactions of specific thalamic clusters during 8-Hz flashing checkerboard stimulation with simultaneous finger tapping. Together, the current study provides a reliable parcellation of the thalamus and enhances our understating of thalamic. Furthermore, the current study provides a framework for parcellation that could be potentially extended to other subcortical and cortical regions.