nils-herrmann/clean_scirepeval huggingface dataset:
A Flyback Converter with SiC Power MOSFET Operating at 10 MHz: Reducing Leakage Inductance for Improvement of Switching Behaviors

A high-frequency flyback converter is investigated in this paper. In order to increase the switching frequency of the flyback converter, we focus on the impacts of the leakage inductance of the transformer at the primary side on the transients of the turn-off characteristics. It is found that the leakage inductance of the transformer limits the turn-off behaviors of the primary side. By reducing the leakage inductance of the transformer on the primary side, the improved flyback converter achieves the 10 MHz operation. The output voltage is controlled by duty ratio from 30% to 60%. The maximum output power of 16 W and the maximum conversion efficiency of 67% are observed in the flyback converter.
Translating English to SQL

Most of the NLDBi that have been presented so far use a process that firstly involves the conversion of a NL statement into its logical representation by using some linguistic knowledge. It then goes through a complicated conversion whereby the representation is converted into a database query. Because of the steps involved with these traditional methods they are very expensive, computationally. In this paper I analyze two methods which achieve the process of conversion of a NL statement to a database query in a lightweight manner. The first approach involves the use of FST and the second approach involves the use of SMT
Encyclopedia of Biophysics

ion of the a-proton from acetyl-CoA by Asp375, creating the enolate form. It was long believed that this was converted into an enol (e.g., by proton transfer from His274), but several computer modeling studies (in particular using high-level QM/MM methods) indicated that the enolate is the true transient intermediate species in the enzyme reaction (e.g., Mulholland et al. 2000; Van der Kamp et al. 2010). The enolate form is stabilized by electrostatic interactions in the enzyme active site, which include conventional hydrogen bonds from His274 and a conserved water molecule to the enolate oxygen ; no “lowbarrier hydrogen bonds” are involved (Mulholland et al. 2000). When the enolate intermediate is formed, the carbonyl carbon of oxaloacetate can undergo a nucleophilic attack. Citryl-CoA is formed as an intermediate, which requires proton donation. Initially, it was suggested that His320 donated the proton, but high-level QM/MM studies indicate that donation by Arg329 is most likely (Van der Kamp et al. 2008) . This unusual role of an arginine as proton donor probably prevents overstabilization of the citryl-CoA intermediate and may trigger opening of the enzyme active site (vide supra), which is likely to be important for hydrolysis. Through its involvement in catalysis, Arg329 thereby is proposed to provide a mechanism for coupling condensation and hydrolysis in citrate synthase, and for coupling the chemical and conformational changes during the catalytic cycle (Van der Kamp et al. 2008). Citryl-CoA subsequently undergoes hydrolysis to form citrate and CoA-SH. Asp375 is implicated to play a role in this step, but the precise mechanism for this step is as yet unknown. The breaking of the thioester-linkage is energetically very favorable, which helps to drive the reaction in the forward direction, making it possible for the citric acid cycle to turn over, even with the typically low concentration of oxaloacetate in vivo (Voet and Voet 2011).
Evaluation of the kidney stone patient.

Kidney stones are one of the most common chronic disorders in industrialized countries. In patients with kidney stones, the goal of medical therapy is to prevent the formation of new kidney stones and to reduce growth of existing stones. The evaluation of the patient with kidney stones should identify dietary, environmental, and genetic factors that contribute to stone risk. Radiologic studies are required to identify the stone burden at the time of the initial evaluation and to follow up the patient over time to monitor success of the treatment program. For patients with a single stone an abbreviated laboratory evaluation to identify systemic disorders usually is sufficient. For patients with multiple kidney stones 24-hour urine chemistries need to be measured to identify abnormalities that predispose to kidney stones, which guides dietary and pharmacologic therapy to prevent future stone events.
THE INTERNET MEME AS A RHETORIC DISCOURSE: INVESTIGATING ASIAN/ASIAN AMERICANS’ IDENTITY NEGOTIATION

Alberto González, Advisor This study draws concepts from rhetorical criticism, vernacular rhetoric, visual rhetoric, and whiteness studies, to investigate how Asian/Asian Americans’ online identities are being constructed and mediated by Internet memes. This study examines the use of Internet memes as persuasive discourses for entertainment, spreading stereotypes, and online activism by examining the meme images and texts, including their content, rhetorical components, and structure. Internet memes that directly depict Asian/Asian Americans are collected from three popular meme websites: Reddit, Know Your Meme, and Tumblr. The findings indicate that Internet memes complicate the construction of racial identity, invoking the negotiation and conflicts concerning racial identities described by dominant as well as vernacular discourses. They not only function as entertaining jokes but also reflect the social conflicts surrounding race. However, the prevalence and development of memes also bring new possibilities for social justice movements. Furthermore, the study provides implications of memes for users and anti-racist activities, as well as suggests future research directions mainly in the context of globalization.
Learning Deep Structure-Preserving Image-Text Embeddings

This paper proposes a method for learning joint embeddings of images and text using a two-branch neural network with multiple layers of linear projections followed by nonlinearities. The network is trained using a large-margin objective that combines cross-view ranking constraints with within-view neighborhood structure preservation constraints inspired by metric learning literature. Extensive experiments show that our approach gains significant improvements in accuracy for image-to-text and text-to-image retrieval. Our method achieves new state-of-the-art results on the Flickr30K and MSCOCO image-sentence datasets and shows promise on the new task of phrase localization on the Flickr30K Entities dataset.
Reverse Engineering PL/SQL Legacy Code: An Experience Report

The reengineering of legacy code is a tedious endeavor. Automatic transformation of legacy code from an old technology to a new one preserves potential problems in legacy code with respect to obsolete, changed, and new business cases. On the other hand, manual analysis of legacy code without assistance of original developers is time consuming and error-prone. For the purpose of reengineering PL/SQL legacy code in the steel making domain, we developed tool support for the reverse engineering of PL/SQL code into a more abstract and comprehensive representation. This representation then serves as input for stakeholders to manually analyze legacy code, to identify obsolete and missing business cases, and, finally, to support the re-implementation of a new system. In this paper we briefly introduce the tool and present results of reverse engineering PL/SQL legacy code in the steel making domain. We show how stakeholders are supported in analyzing legacy code by means of general-purpose analysis techniques combined with domain-specific representations and conclude with some of the lessons learned.
Sensr: evaluating a flexible framework for authoring mobile data-collection tools for citizen science

Across HCI and social computing platforms, mobile applications that support citizen science, empowering non-experts to explore, collect, and share data have emerged. While many of these efforts have been successful, it remains difficult to create citizen science applications without extensive programming expertise. To address this concern, we present Sensr, an authoring environment that enables people without programming skills to build mobile data collection and management tools for citizen science. We demonstrate how Sensr allows people without technical skills to create mobile applications. Findings from our case study demonstrate that our system successfully overcomes technical constraints and provides a simple way to create mobile data collection tools.
Type Classification of Semi-Structured Documents

Semi-structured documents (e.g. journal art,icles, electronic mail, television programs, mail order catalogs, . ..) a.re often not explicitly typed; the only available t,ype information is the implicit structure. An explicit t,ype, however, is needed in order to a.pply objectoriented technology, like type-specific methods. In this paper, we present a.n experimental vector space cla.ssifier for determining the type of semi-structured documents. Our goal was to design a. high-performa.nce classifier in t,erms of accuracy (recall and precision), speed, and extensibility.
Space from Hilbert space : Recovering geometry from bulk entanglement

quantum state in Hilbert space. Given a decomposition of Hilbert spaceH into a tensor product of factors, we consider a class of “redundancy-constrained states” in H that generalize the area-law behavior for entanglement entropy usually found in condensed-matter systems with gapped local Hamiltonians. Using mutual information to define a distance measure on the graph, we employ classical multidimensional scaling to extract the best-fit spatial dimensionality of the emergent geometry. We then show that entanglement perturbations on such emergent geometries naturally give rise to local modifications of spatial curvature which obey a (spatial) analog of Einstein’s equation. The Hilbert space corresponding to a region of flat space is finite-dimensional and scales as the volume, though the entropy (and the maximum change thereof) scales like the area of the boundary. Aversion of the ER 1⁄4 EPR conjecture is recovered, in that perturbations that entangle distant parts of the emergent geometry generate a configuration that may be considered as a highly quantum wormhole.
Stress, burnout and depression: A systematic review on DNA methylation mechanisms.

Despite that burnout presents a serious burden for modern society, there are no diagnostic criteria. Additional difficulty is the differential diagnosis with depression. Consequently, there is a need to dispose of a burnout biomarker. Epigenetic studies suggest that DNA methylation is a possible mediator linking individual response to stress and psychopathology and could be considered as a potential biomarker of stress-related mental disorders. Thus, the aim of this review is to provide an overview of DNA methylation mechanisms in stress, burnout and depression. In addition to state-of-the-art overview, the goal of this review is to provide a scientific base for burnout biomarker research. We performed a systematic literature search and identified 25 pertinent articles. Among these, 15 focused on depression, 7 on chronic stress and only 3 on work stress/burnout. Three epigenome-wide studies were identified and the majority of studies used the candidate-gene approach, assessing 12 different genes. The glucocorticoid receptor gene (NR3C1) displayed different methylation patterns in chronic stress and depression. The serotonin transporter gene (SLC6A4) methylation was similarly affected in stress, depression and burnout. Work-related stress and depressive symptoms were associated with different methylation patterns of the brain derived neurotrophic factor gene (BDNF) in the same human sample. The tyrosine hydroxylase (TH) methylation was correlated with work stress in a single study. Additional, thoroughly designed longitudinal studies are necessary for revealing the cause-effect relationship of work stress, epigenetics and burnout, including its overlap with depression.
17 Cholesterol Metabolism in Huntington ’ s Disease

Cholesterol is present in all vertebrate cells where has several important functions. Being a structural element in plasma membranes it supports the structure and function of lipid bilayers and is regarded to be the most important “fluidity buffer” of the membrane. It is also a precursor of bile acids, steroid hormones and vitamin D. While cholesterol is involved in many cellular processes, a strong indicator of its importance is that it is the only major lipid in mammals not used in energy generation.
The effect of music on discomfort experienced by intensive care unit patients during turning: a randomized cross-over study.

Research consistently demonstrates that intensive care unit (ICU) patients experience pain, discomfort and anxiety despite analgesic and sedative use. The most painful procedure reported by critically ill patients is being turned. Music diminishes anxiety and discomfort in some populations; however, its effect on critically ill patients remains unknown. This research aimed to identify the effect of music on discomfort experienced by ICU patients during turning using a single blind randomized cross-over design. Seventeen post-operative ICU patients were recruited and treatment order randomized. Discomfort and anxiety were measured 15 min before and immediately after two turning procedures. Findings indicated that listening to music 15 min before and during turning did not significantly reduce discomfort or anxiety. Pain management might effectively be addressing discomfort and anxiety experienced during turning. Given previous studies have identified turning as painful, current results are promising and it might be useful to determine if this is widespread.
Auditory time-intensity cues in the binaural interaction component of the auditory evoked potentials

Binaural interaction in the brainstem and middle latency auditory evoked potentials to intensity (dI) and timing differences (dT) between the two ears was studied in 10 normal hearing young adults. A component reflecting binaural interaction in the brainstem potentials occurred at approximately 7 ms and was of largest amplitude when dI and dT were 0. The latency of the binaural interaction component gradually shifted and its amplitude decreased as dI or dT increased and binaural interaction became undetectable when dI = 16 dB or when dT > or = 1.6 ms. In the middle latency potentials binaural interaction components peaking at 20, 32, and 45 ms were defined that were also largest when dI and dT = 0. The latency of the interaction did not shift with changes in dT and dI whereas the amplitude gradually decreased but binaural interaction components were still evident even at the largest values of dI (30 dB) and dT (3 ms). Psychophysical judgments of binaural perceptions showed binaural fusion of the stimuli to persist with dT values up to 1.6 ms and that lateralization of the intracranial image was complete when either dT = 1.6 ms or when dI = 16 dB. The results suggest that the presence of a binaural interaction component of auditory brainstem potentials correlates with the fusion of binaural click stimuli and the amplitude of the binaural interaction component correlates inversely with the degree of lateralization of the intracranial image. Binaural interaction components of middle latency potentials persist and continue to change even after the binaural stimuli cannot be fused.
High-Resolution Direct Position Determination Using MVDR

The direct position determination (DPD) approach is a single-step method, which uses the maximum likelihood estimator to localize sources emitting electromagnetic energy using combined data from all available sensors. The DPD is known to outperform the traditional two-step methods under low signal-to-noise ratio conditions. We propose an improvement to the DPD approach, using the well-known minimum-variance-distortionless-response (MVDR) approach. Unlike maximum likelihood, the number of sources needs not be known before applying the method. The combination of both the direct approach and MVDR yields unprecedented localization accuracy and resolution for weak sources. We demonstrate this approach on the problem of multistatic radar, but the method can easily be extended to general localization problems.
Zinc oxide as a new antimicrobial preservative of topical products: interactions with common formulation ingredients.

Zinc oxide (ZnO) appears as a promising preservative for pharmaceutical or cosmetic formulations. The other ingredients of the formulations may have specific interactions with ZnO that alter its antimicrobial properties. The influence of common formulation excipients on the antimicrobial efficacy of ZnO has been investigated in simple model systems and in typical topical products containing a complex formulation. A wide variety of formulation excipients have been investigated for their interactions with ZnO: antioxidants, chelating agents, electrolytes, titanium dioxide pigment. The antimicrobial activity of ZnO against Escherichia coli was partially inhibited by NaCl and MgSO4 salts. A synergistic influence of uncoated titanium dioxide has been observed. The interference effects of antioxidants and chelating agents were quite specific. The interactions of these substances with ZnO particles and with the soluble species released by ZnO were discussed so as to reach scientific guidelines for the choice of the ingredients. The preservative efficacy of ZnO was assessed by challenge testing in three different formulations: an oil-in-water emulsion; a water-in-oil emulsion and a dry powder. The addition of ZnO in complex formulations significantly improved the microbiological quality of the products, in spite of the presence of other ingredients that modulate the antimicrobial activity.
Quantification of Bone Microarchitecture with the Structure Model Index.

The deterioration of cancellous bone structure due to aging and disease is characterized by a conversion from plate elements to rod elements. Consequently the terms "rod-like" and "plate-like" are frequently used for a subjective classification of cancellous bone. In this work a new morphometric parameter called Structure Model Index (SMI) is introduced, which makes it possible to quantify the characteristic form of a three-dimensionally described structure in terms of the amount of plates and rod composing the structure. The SMI is calculated by means of three-dimensional image analysis based on a differential analysis of the triangulated bone surface. For an ideal plate and rod structure the SMI value is 0 and 3, respectively, independent of the physical dimensions. For a structure with both plates and rods of equal thickness the value lies between 0 and 3, depending on the volume ratio of rods and plates. The SMI parameter is evaluated by examining bone biopsies from different skeletal sites. The bone samples were measured three-dimensionally with a micro-CT system. Samples with the same volume density but varying trabecular architecture can uniquely be characterized with the SMI. Furthermore the SMI values were found to correspond well with the perceived structure type.
A vision-based vehicle identification system

This work presents a vision-based vehicle identification system which consists of object extraction, object tracking, occlusion detection and segmentation, and vehicle classification. Since the vehicles on the freeway may occlude each other, their trajectories may merge or split. To separate the occluded objects, we develop three processed: occlusion detection, motion vector calibration, and motion field clustering. Finally, the segmented objects are classified into seven different categorized vehicles.
High-performance information extraction with AliBaba

A wealth of information is available only in web pages, patents, publications etc. Extracting information from such sources is challenging, both due to the typically complex language processing steps required and to the potentially large number of texts that need to be analyzed. Furthermore, integrating extracted data with other sources of knowledge often is mandatory for subsequent analysis. In this demo, we present the AliBaba system for scalable information extraction from biomedical documents. Unlike many other systems, AliBaba performs both entity extraction and relationship extraction and graphically visualizes the resulting network of inter-connected objects. It leverages the PubMed search engine for selection of relevant documents. The technical novelty of AliBaba is twofold: (a) its ability to automatically learn language patterns for relationship extraction without an annotated corpus, and (b) its high performance pattern matching algorithm. We show that a simple yet effective pattern filtering technique improves the runtime of the system drastically without harming its extraction effectiveness. Although AliBaba has been implemented for biomedical texts, its underlying principles should also be applicable in any other domain.
Soil warming and carbon-cycle feedbacks to the climate system.

In a decade-long soil warming experiment in a mid-latitude hardwood forest, we documented changes in soil carbon and nitrogen cycling in order to investigate the consequences of these changes for the climate system. Here we show that whereas soil warming accelerates soil organic matter decay and carbon dioxide fluxes to the atmosphere, this response is small and short-lived for a mid-latitude forest, because of the limited size of the labile soil carbon pool. We also show that warming increases the availability of mineral nitrogen to plants. Because plant growth in many mid-latitude forests is nitrogen-limited, warming has the potential to indirectly stimulate enough carbon storage in plants to at least compensate for the carbon losses from soils. Our results challenge assumptions made in some climate models that lead to projections of large long-term releases of soil carbon in response to warming of forest ecosystems.
Cognitive Constraints and Island Effects.

Competence-based theories of island effects play a central role in generative grammar, yet the graded nature of many syntactic islands has never been properly accounted for. Categorical syntactic accounts of island effects have persisted in spite of a wealth of data suggesting that island effects are not categorical in nature and that non-structural manipulations that leave island structures intact can radically alter judgments of island violations. We argue here, building on work by Deane, Kluender, and others, that processing factors have the potential to account for this otherwise unexplained variation in acceptability judgments.We report the results of self-paced reading experiments and controlled acceptability studies which explore the relationship between processing costs and judgments of acceptability. In each of the three self-paced reading studies, the data indicate that the processing cost of different types of island violations can be significantly reduced to a degree comparable to that of non-island filler-gap constructions by manipulating a single non-structural factor. Moreover, this reduction in processing cost is accompanied by significant improvements in acceptability. This evidence favors the hypothesis that island-violating constructions involve numerous processing pressures that aggregate to drive processing difficulty above a threshold so that a perception of unacceptability ensues. We examine the implications of these findings for the grammar of filler-gap dependencies.
Performance thresholding in practical text classification

In practical classification, there is often a mix of learnable and unlearnable classes and only a classifier above a minimum performance threshold can be deployed. This problem is exacerbated if the training set is created by active learning. The bias of actively learned training sets makes it hard to determine whether a class has been learned. We give evidence that there is no general and efficient method for reducing the bias and correctly identifying classes that have been learned. However, we characterize a number of scenarios where active learning can succeed despite these difficulties.