nils-herrmann/clean_scirepeval huggingface dataset:
Does sodium hyaluronate and carboxymethylcellulose based bioresorbable membrane (Seprafilm) decrease operative time for loop ileostomy closure?
Venue: Techniques in Coloproctology
Year: 2006

AbstractBackgroundAdhesions can result in serious clinical complications and make ileostomy closure, which is relatively simple procedure into a complicated and prolonged one. The use of sodium hyaluronate and carboxymethyl cellulose membrane (Seprafilm(r) was proven to significantly reduce the postoperative adhesions at the site of application. The aim of this study was to assess the incidence and severity of adhesions around a loop ileostomy and to analyze the lenght of time and morbidity for mobilization at the time of ileostomy closure with and without the use of Seprafilm.MethodsTwenty nine surgeons from 15 institutions participated in this multicenter prospective randomized study. 191 patients with loop ileostomy construction were randomly assigned to either receive Seprafilm under the midline incision and around the stoma (Group I) only under the midline incision (Group II) or not to receive Seprafilm (Group III) At ileostomy closure, adhesions were quantified and graded; operative morbidity was also measured.ResultsAll 3 groups were comparable relative to gender, mean age and number of patients with prior operations (26, 25 and 19, respectively) Group II patients were significantly more likely to have pre existing adhesions than Group III patients (30.6% vs. 14.1% p=0.025) At stoma mobilization, significantly more patients in Group III than in Group I had adhesions around the stoma (95.2% vs. 82.3% p=0.021) Mean operative times were 27, 25, and 28 minutes, respectively (p=0.38) with significant differences among sites. There was no significant difference in the number of patients needing myotomy or enterotomy (29, 27 and 24 patients, respectively) nor in the number of postoperative complications (7, 9 and 7 patients, respectively).ConclusionsWhen consistently applied, Seprafilm significantly decreased adhesion formation around the stoma but not operative times without any increase in the need for myotomy or enterotomy. These findings were not seen in the overall study population possibly due to the large number of surgeons using a variety of application techniques.
Women and Islam in Bangladesh: Beyond Subjection and Tyranny
Year: 2016

Preface and Acknowledgements  Women in  A Reappraisal Mullas, Popular Islam and Misogyny Women as Victims of the Salish: Fatwas, Mullas and the Village Community NGOs and Empowerment of Women: Some Problematic Prognoses Militant Feminism, Islam and Patriarchy: Taslima Nasreen, Ulama and the Polity Conclusions Index
COVID 19: The Prospects for Nonprofit Human Resource Management
Year: 2020

This article explores the impacts of COVID 19 on nonprofit employees and human resource management (HRM) The pandemic is wreaking havoc on people's health and well being and threatening the primary institutions that support the functioning of society. For nonprofits, COVID 19 is a call to action at many levels. As the devasting impacts of the pandemic evolve, nonprofits have continued to provide essential services and help the vulnerable. At the same time, the impacts of COVID 19 portend serious and potentially crippling strains on nonprofits, which are already overstretched. Since the context in which nonprofits operate is critical to their effectiveness and the outcomes of their employment relations, the impacts of COVID 19 could shape nonprofit HRM and employees' ability to assist people.
The Impact of Marketing Variables on Business Performance: An Analysis of FMCG, Consumer Durables and Textile Industries
Year: 2015

The changes in the structure of economy have brought about a significant change in market dynamics. The increased competition from every corner of the world is forcing companies to bring changes in their marketing, human resource and operations strategies. One question that continues to dominate thinking in organizations is the impact of marketing expenditures on sales performance. This question provided the trigger to explore and analyze the impact of marketing expenditures on sales. Thirty companies were analyzed in FMCG, consumer durables and textile industries each. Separate regression analysis was done to analyze the impact of marketing expenditures on sales in all the three industries. The results showed that marketing expenditures had differential impact on the sales of the companies across the three industries.
Resonant DC/DC converter with Class Ph2inverter and Class DE rectifier based on GaN HEMT
Venue: 2020 22nd European Conference on Power Electronics and Applications (EPE'20 ECCE Europe)
Year: 2020

A resonant DC/DC converter with Class Ph2 inverter and Class DE rectifier based on GaN HEMT is designed and validated. A PCB plane transformer is designed to realize the isolation of the primary side and the secondary side of the converter. The output voltage is regulated by hysteresis ON/OFF control. The operation principle and design procedure are introduced in detail.
Towards Machine Learning Explainability in Text Classification for Fake News Detection
Venue: 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA)
Year: 2020

The digital media landscape has been exposed in recent years to an increasing number of deliberately misleading news and disinformation campaigns, a phenomenon popularly referred as fake news. In an effort to combat the dissemination of fake news, designing machine learning models that can classify text as fake or not has become an active line of research. While new models are continuously being developed, the focus so far has mainly been aimed at improving the accuracy of the models for given datasets. Hence, there is little research done in the direction of explainability of the deep learning (DL) models constructed for the task of fake news detection.In order to add a level of explainability, several aspects have to be taken into consideration. For instance, the pre processing phase, or the length and complexity of the text play an important role in achieving a successful classification. These aspects need to be considered in conjunction with the model's architecture. All of these issues are addressed and analyzed in this paper. Visualizations are further employed to grasp a better understanding how different models distribute their attention when classifying fake news texts. In addition, statistical data is gathered to deepen the analysis and to provide insights with respect to the model's interpretability.
Ambient Pressure Relithiation of Degraded Li x Ni 0.5 Co 0.2 Mn 0.3 O 2 (0 x 1) via Eutectic Solutions for Direct Regeneration of Lithium Ion Battery Cathodes
Venue: Advanced Energy Materials
Year: 2019

DOI: 10.1002/aenm.201900454 Today's lithium ion batteries (LIBs) can offer high energy density (260 Wh kg 1 and 700 Wh L 1 at cell level) and high Coulombic efficiency (99.98% and long cycling life >1000 cycles) making them the dominating power sources for portable electronics and electric vehicles (EVs)[1,2] Due to With the rapid growth of the lithium ion battery (LIBs) market, recycling and re use of end of life LIBs to reclaim lithium (Li) and transition metal (TM) resources (e.g. Co, Ni) as well as eliminating pollution from disposal of waste batteries, has become an urgent task. Here, for the first time the ambient pressure relithiation of degraded LiNi0.5Co0.2Mn0.3O2 (NCM523) cathodes via eutectic Li+ molten salt solutions is successfully demonstrated. Combining such a low temperature relithiation process with a well designed thermal annealing step, NCM523 cathode particles with significant Li loss (40% and capacity degradation (50% can be successfully regenerated to achieve their original composition and crystal structures, leading to effective recovery of their capacity, cycling stability, and rate capability to the levels of the pristine materials. Advanced characterization tools including atomic resolution electron microscopy imaging and electron energy loss spectroscopy are combined to demonstrate that NCM523's original layered crystal structure is recovered. For the first time, it is shown that layer to rock salt phase change on the surfaces and subsurfaces of the cathode materials can be reversed if lithium can be incorporated back to the material. The result suggests the great promise of using eutectic Li+ molten salt solutions for ambient pressure relithiation to recycle and remanufacture degraded LIB cathode materials.
Simultaneous Speech Recognition and Speaker Diarization for Monaural Dialogue Recordings with Target Speaker Acoustic Models
Venue: 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)
Year: 2019

This paper investigates the use of target speaker automatic speech recognition (TS ASR) for simultaneous speech recognition and speaker diarization of single channel dialogue recordings. TS ASR is a technique to automatically extract and recognize only the speech of a target speaker given a short sample utterance of that speaker. One obvious drawback of TS ASR is that it cannot be used when the speakers in the recordings are unknown because it requires a sample of the target speakers in advance of decoding. To remove this limitation, we propose an iterative method, in which (i) the estimation of speaker embeddings and (ii) TS ASR based on the estimated speaker embeddings are alternately executed. We evaluated the proposed method by using very challenging dialogue recordings in which the speaker overlap ratio was over 20% We confirmed that the proposed method significantly reduced both the word error rate (WER) and diarization error rate (DER) Our proposed method combined with i vector speaker embeddings ultimately achieved a WER that differed by only 2.1 from that of TS ASR given oracle speaker embeddings. Furthermore, our method can solve speaker diarization simultaneously as a by product and achieved better DER than that of the conventional clustering based speaker diarization method based on i vector.
A TPO Receptor Agonist, ALXN4100TPO, Mitigates Radiation Induced Lethality and Stimulates Hematopoiesis in CD2F1 Mice
Venue: Radiation research
Year: 2011

Thrombopoietin (TPO) receptor agonists lacking sequence homology to TPO were designed by grafting a known peptide sequence into the hinge and/or kappa constant regions of a human anti anthrax antibody. Some of these proteins were equipotent to TPO in stimulating cMpl r activity in vitro and in increasing platelet levels in vivo. ALXN4100TPO (4100TPO) the best agonist in this series with a Kd of 30 nM for cMpl r, exhibited potent activity as a radiation countermeasure in CD2F1 mice exposed to lethal total body radiation from a cobalt 60 g ray source. 4100TPO (2 mg/kg, s.c. administered once either 24 h before or 6 h after TBI showed superior protection to five daily doses given before or after TBI. Prophylactic administration (69 to 94% survival) was superior to therapeutic schedules (60% survival) 4100TPO conferred a significant survival benefit (P 0.01) when administered 4 days before or even 12 h after exposure and across a dose range of 0.1 to 8 mg/kg. The dose reduction factors (DRFs) with a single dose of 1 mg/kg 4100TPO 24 h before or 12 h after TBI were 1.32 and 1.11, respectively (P 0.0001) Furthermore, 4100TPO increased bone marrow cellularity and megakaryocytic development and accelerated multi lineage hematopoietic recovery in irradiated mice, demonstrating the potential of 4100TPO as both a protector and a mitigator in the event of a radiological incident.
Low cost feedback controlled syringe pressure pumps for microfluidics applications
Venue: PloS one
Year: 2017

Microfluidics are widely used in research ranging from bioengineering and biomedical disciplines to chemistry and nanotechnology. As such, there are a large number of options for the devices used to drive and control flow through microfluidic channels. Commercially available syringe pumps are probably the most commonly used instruments for this purpose, but are relatively high cost and have inherent limitations due to their flow profiles when they are run open loop. Here, we present a low cost $110) syringe pressure pump that uses feedback control to regulate the pressure into microfluidic chips. Using an open source microcontroller board (Arduino) we demonstrate an easily operated and programmable syringe pump that can be run using either a PID or bang bang control method. Through feedback control of the pressure at the inlets of two microfluidic geometries, we have shown stability of our device to within 1% of the set point using a PID control method and within 5% of the set point using a bang bang control method with response times of less than 1 second. This device offers a low cost option to drive and control well regulated pressure driven flow through microfluidic chips.
Adversarial Examples Improve Image Recognition
Venue: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2020

Adversarial examples are commonly viewed as a threat to ConvNets. Here we present an opposite perspective: adversarial examples can be used to improve image recognition models if harnessed in the right manner. We propose AdvProp, an enhanced adversarial training scheme which treats adversarial examples as additional examples, to prevent overfitting. Key to our method is the usage of a separate auxiliary batch norm for adversarial examples, as they have different underlying distributions to normal examples. We show that AdvProp improves a wide range of models on various image recognition tasks and performs better when the models are bigger. For instance, by applying AdvProp to the latest EfficientNet B7 [28] on ImageNet, we achieve significant improvements on ImageNet +0.7% ImageNet C +6.5% ImageNet A +7.0% Stylized ImageNet +4.8% With an enhanced EfficientNet B8, our method achieves the state of the art 85.5% ImageNet top 1 accuracy without extra data. This result even surpasses the best model in [20] which is trained with 3.5B Instagram images ~3000X more than ImageNet) and ~9.4X more parameters. Code and models will be made publicly available.
Love wave phase velocity models of the southeastern margin of Tibetan Plateau from a dense seismic array
Year: 2017

Love wave dispersion maps across the southeastern margin of the Tibetan Plateau are obtained using earthquake data recorded by the temporary ChinArray and permanent China Digital Seismic Array. Fundamental mode Love wave phase velocity curves are measured by inverting Love wave amplitude and phase with the two plane wave method. The phase velocity maps with resolution better than 150 km are presented at periods of 20 100 s, which is unprecedented in the study area. The maps agree well with each other and show clear correlations with major tectonic structures. The Love wave phase velocity could provide new information about structures in the crust and upper mantle beneath the southeast margin of Tibetan Plateau, like the radial anisotropy.
The complete mitochondrial genome of the fire coral inhabiting barnacle Megabalanus ajax (Sessilia: Balanidae) gene rearrangements and atypical gene content
Venue: Mitochondrial DNA. Part A, DNA mapping, sequencing, and analysis
Year: 2016

The complete mitochondrial genome of Megabalanus ajax Darwin, 1854 (Sessilia: Balanidae) is reported. Compared to typical gene content of metazoan mitochondrial genomes, duplication of one tRNA gene (trnL2) and absence of another tRNA gene (trnS1) are identified in M. ajax mitochondrial genome. There is a replacement of one tRNA (trnS1) by another tRNA (trnL2) in M. ajax mitochondrial genome compared to Megabalanus volcano mitochondrial genome. Inversion of a six gene block (trnP nd4L nd4 trnH nd5 trnF) is found between M. ajax/M. volcano and Tetraclita japonica mitochondrial genomes. With reference to the pancrustacean mitochondrial ground pattern, there is an inversion of a large gene block from the light strand to heavy strand in the two Megabalanus mitochondrial genomes, including three PCGs and two tRNAs (nd4L nd4 trnH nd5 trnF) Furthermore, four tRNAs (trnA, trnE, trnQ and trnC) exhibit translocation, while translocation and inversion occur in three tRNAs (trnP, trnY and trnK)
Non Hodgkin Lymphoma and Occupational Exposure to Agricultural Pesticide Chemical Groups and Active Ingredients: A Systematic Review and Meta Analysis
Venue: International journal of environmental research and public health
Year: 2014

This paper describes results from a systematic review and a series of meta analyses of nearly three decades worth of epidemiologic research on the relationship between non Hodgkin lymphoma (NHL) and occupational exposure to agricultural pesticide active ingredients and chemical groups. Estimates of associations of NHL with 21 pesticide chemical groups and 80 active ingredients were extracted from 44 papers, all of which reported results from analyses of studies conducted in high income countries. Random effects meta analyses showed that phenoxy herbicides, carbamate insecticides, organophosphorus insecticides and the active ingredient lindane, an organochlorine insecticide, were positively associated with NHL. In a handful of papers, associations between pesticides and NHL subtypes were reported; B cell lymphoma was positively associated with phenoxy herbicides and the organophosphorus herbicide glyphosate. Diffuse large B cell lymphoma was positively associated with phenoxy herbicide exposure. Despite compelling evidence that NHL is associated with certain chemicals, this review indicates the need for investigations of a larger variety of pesticides in more geographic areas, especially in low and middle income countries, which, despite producing a large portion of the world's agriculture, were missing in the literature that were reviewed.
mTOR Signaling in Growth, Metabolism, and Disease
Venue: Cell
Year: 2017

The mechanistic Target of Rapamycin (mTOR) coordinates eukaryotic cell growth and metabolism with environmental inputs including nutrients and growth factors. Extensive research over the past two decades has established a central role for mTOR in regulating many fundamental cell processes, from protein synthesis to autophagy, and deregulated mTOR signaling is implicated in the progression of cancer and diabetes, as well as the aging process. Here, we review recent advances in our understanding of mTOR function, regulation, and importance in mammalian physiology. We also highlight how the mTOR signaling network contributes to human disease, and discuss the current and future prospects for therapeutically targeting mTOR in the clinic.
CDK targets Sae2 to control DNA end resection and homologous recombination
Venue: Nature
Year: 2008

DNA double strand breaks (DSBs) are repaired by two principal mechanisms: non homologous end joining (NHEJ) and homologous recombination (HR) HR is the most accurate DSB repair mechanism but is generally restricted to the S and G2 phases of the cell cycle, when DNA has been replicated and a sister chromatid is available as a repair template. By contrast, NHEJ operates throughout the cell cycle but assumes most importance in G1 (refs 4, 6) The choice between repair pathways is governed by cyclin dependent protein kinases (CDKs) with a major site of control being at the level of DSB resection, an event that is necessary for HR but not NHEJ, and which takes place most effectively in S and G2 (refs 2, 5) Here we establish that cell cycle control of DSB resection in Saccharomyces cerevisiae results from the phosphorylation by CDK of an evolutionarily conserved motif in the Sae2 protein. We show that mutating Ser 267 of Sae2 to a non phosphorylatable residue causes phenotypes comparable to those of a sae2D null mutant, including hypersensitivity to camptothecin, defective sporulation, reduced hairpin induced recombination, severely impaired DNA end processing and faulty assembly and disassembly of HR factors. Furthermore, a Sae2 mutation that mimics constitutive Ser 267 phosphorylation complements these phenotypes and overcomes the necessity of CDK activity for DSB resection. The Sae2 mutations also cause cell cycle stage specific hypersensitivity to DNA damage and affect the balance between HR and NHEJ. These findings therefore provide a mechanistic basis for cell cycle control of DSB repair and highlight the importance of regulating DSB resection.
Physics based analytical model for high impedance fault location in distribution networks
Year: 2020

This paper presents a physics based analytical model for high impedance fault location in power distribution systems. The presented analytical solution is composed by two interdependent processes. First, fault distance is estimated through a Weighted Least Square approach applied to solve an overdetermined and nonlinear algebraic system of equations. Second, an analytical method based on the statistical behavior of the estimates obtained from the frequency domain system model solution is presented to address the multiple estimates problem, identifying the faulted section. The presented fault location physics based analytical model considers the capacitive effect of distribution lines. Furthermore, voltages and currents measured from only one terminal are used. The formulation is evaluated using the IEEE 13 bus and a modified version of the IEEE 34 bus test feeders. Comparative analysis with state of the art methods is presented. Average errors of 1.95% are obtained. Easy to implement analytical model, without hard to derive parameters, built on the weighted least squares state estimator, highlight potential aspects for real life applications.
DeepDRK: a deep learning framework for drug repurposing through kernel based multi omics integration
Venue: Briefings Bioinform.
Year: 2021

Recent pharmacogenomic studies that generate sequencing data coupled with pharmacological characteristics for patient derived cancer cell lines led to large amounts of multi omics data for precision cancer medicine. Among various obstacles hindering clinical translation, lacking effective methods for multimodal and multisource data integration is becoming a bottleneck. Here we proposed DeepDRK, a machine learning framework for deciphering drug response through kernel based data integration. To transfer information among different drugs and cancer types, we trained deep neural networks on more than 20 000 pan cancer cell line anticancer drug pairs. These pairs were characterized by kernel based similarity matrices integrating multisource and multi omics data including genomics, transcriptomics, epigenomics, chemical properties of compounds and known drug target interactions. Applied to benchmark cancer cell line datasets, our model surpassed previous approaches with higher accuracy and better robustness. Then we applied our model on newly established patient derived cancer cell lines and achieved satisfactory performance with AUC of 0.84 and AUPRC of 0.77. Moreover, DeepDRK was used to predict clinical response of cancer patients. Notably, the prediction of DeepDRK correlated well with clinical outcome of patients and revealed multiple drug repurposing candidates. In sum, DeepDRK provided a computational method to predict drug response of cancer cells from integrating pharmacogenomic datasets, offering an alternative way to prioritize repurposing drugs in precision cancer treatment. The DeepDRK is freely available via https:/github.com/wangyc82/DeepDRK.