gebhart/patrepeval huggingface dataset:
<b>DivIB, FtsZ and cell division in <i>Bacillus subtilis</i></b> (1997)

The Bacillus subtilis cell-division protein DivIB is shown to be present at an approximately 100-fold higher abundance (approximately 5000 molecules per cell) than its Escherichia coli FtsQ homologue. B. subtilis contains much more DivIB (at least 60-fold) than is needed to maintain the normal rate of cell division at moderate temperatures (up to 37 degrees C). However, a high level of DivIB is needed to achieve the normal rate of division at high temperature (47 degrees C). It is proposed that membrane-bound DivIB is involved in stabilizing or promoting the assembly of the division complex (which is intrinsically temperature sensitive) in a manner that requires more of the protein at higher temperatures. The (at least) 60-fold accumulation of DivIB and FtsZ from an undetectable level, following germination and outgrowth of spores up until the stage of the first cell division, was unaffected by blocking of initiation of the first round of replication. It is concluded that there is no major synthesis of either of these 'division initiation' proteins linked to initiation, progression or completion of the first round of replication accompanying spore outgrowth.
An Analysis of the Most Used Machine Learning Algorithms for Online Fraud Detection (2019)

Today illegal activities regarding online financial transactions have become increasingly complex and borderless, resulting in huge financial losses for both sides, customers and organizations. Many techniques have been proposed to fraud prevention and detection in the online environment. However, all of these techniques besides having the same goal of identifying and combating fraudulent online transactions, they come with their own characteristics, advantages and disadvantages. In this context, this paper reviews the existing research done in fraud detection with the aim of identifying algorithms used and analyze each of these algorithms based on certain criteria. To analyze the research studies in the field of fraud detection, the systematic quantitative literature review methodology was applied. Based on the most called machine-learning algorithms in scientific articles and their characteristics, a hierarchical typology is made. Therefore, our paper highlights, in a new way, the most suitable techniques for detecting fraud by combining three selection criteria: accuracy, coverage and costs.
Molecular Subtypes and Personalized Therapy in Metastatic Colorectal Cancer (2016)

Development of colorectal cancer occurs via a number of key pathways, with the clinicopathological features of specific subgroups being driven by underlying molecular changes. Mutations in key genes within the network of signalling pathways have been identified; however, therapeutic strategies to target these aberrations remain limited. As understanding of the biology of colorectal cancer has improved, this has led to a move toward broader genomic testing, collaborative research and innovative, adaptive clinical trial design. Recent developments in therapy include the routine adoption of wider mutational spectrum testing prior to use of targeted therapies and the first promise of effective immunotherapy for colorectal cancer patients. This review details current biomarkers in colorectal cancer for molecular stratification and for treatment allocation purposes, including open and planned precision medicine trials. Advances in our understanding, therapeutic strategy and technology will also be outlined.
百年光影流转，曲未终，人未散 (2010)

好莱坞不止有经典影像和文化符号——梦露手扶白裙，金发飞扬，笑靥如花；赫本伫足在纽约第五大道的蒂凡尼橱窗前一脸向往；邦德优雅得体的布莱奥尼西装和飞驰如风的阿斯顿·马丁座驾；上世纪60年代“It Girl”伊迪·塞奇威克万年不变的短发和夸张的假眼睫毛。
Molecular defects in ferrochelatase in patients with protoporphyria requiring liver transplantation. (1998)

Protoporphyria is a genetic disorder in which a deficiency of mitochondrial ferrochelatase activity causes accumulation of protoporphyrin that produces severe liver damage in some patients. In this study, mutations of the ferrochelatase gene were examined in eight unrelated patients who had liver transplantation. RNA was prepared from liver and/ or lymphoblasts, and specific reverse transcriptase-nested polymerase chain reactions amplified and sequenced ferrochelatase cDNAs. Products shorter than normal resulted from an exon 3 deletion in three patients, exon 10 deletion in two, exon 2 deletion in one, and deletion of five nucleotides in exon 5 in one. Sequence of normal-size products revealed no other mutations. Western blot showed a reduced quantity of normal-size ferrochelatase protein in protoporphyria liver compared with normal liver (19-51%, mean 32% of normal). Levels of the mitochondrial protein F1-ATPase beta-subunit were not decreased to a similar degree. Liver ferrochelatase activity was reduced more than could be explained by the decrease in ferrochelatase protein (4-20%, mean 9% of normal). These results establish genetic heterogeneity in the most severe phenotype of protoporphyria. However, the gene mutations found share the property of causing a major structural alteration in the ferrochelatase protein.
An Overexpression Screen in Drosophila for Genes That Restrict Growth or Cell-Cycle Progression in the Developing Eye (2002)

We screened for genes that, when overexpressed in the proliferating cells of the eye imaginal disc, result in a reduction in the size of the adult eye. After crossing the collection of 2296 EP lines to the ey-GAL4 driver, we identified 46 lines, corresponding to insertions in 32 different loci, that elicited a small eye phenotype. These lines were classified further by testing for an effect in postmitotic cells using the sev-GAL4 driver, by testing for an effect in the wing using en-GAL4, and by testing for the ability of overexpression of cycE to rescue the small eye phenotype. EP lines identified in the screen encompass known regulators of eye development including hh and dpp, known genes that have not been studied previously with respect to eye development, as well as 19 novel ORFs. Lines with insertions near INCENP, elB, and CG11518 were characterized in more detail with respect to changes in growth, cell-cycle phasing, and doubling times that were elicited by overexpression. RNAi-induced phenotypes were also analyzed in SL2 cells. Thus overexpression screens can be combined with RNAi experiments to identify and characterize new regulators of growth and cell proliferation.
Applications of continuous time hidden Markov models to the study of misclassified disease outcomes (2003)

Disease progression in prospective clinical and epidemiological studies is often conceptualized in terms of transitions between disease states. Analysis of data from such studies can be complicated by a number of factors, including the presence of individuals in various prevalent disease states and with unknown prior disease history, interval censored observations of state transitions and misclassified measurements of disease states. We present an approach where the disease states are modelled as the hidden states of a continuous time hidden Markov model using the imperfect measurements of the disease state as observations. Covariate effects on transitions between disease states are incorporated using a generalized regression framework. Parameter estimation and inference are based on maximum likelihood methods and rely on an EM algorithm. In addition, techniques for model assessment are proposed. Applications to two binary disease outcomes are presented: the oral lesion hairy leukoplakia in a cohort of HIV infected men and cervical human papillomavirus (HPV) infection in a cohort of young women. Estimated transition rates and misclassification probabilities for the hairy leukoplakia data agree well with clinical observations on the persistence and diagnosis of this lesion, lending credibility to the interpretation of hidden states as representing the actual disease states. By contrast, interpretation of the results for the HPV data are more problematic, illustrating that successful application of the hidden Markov model may be highly dependent on the degree to which the assumptions of the model are satisfied.
An Online Energy Saving Resource Optimization Methodology for Data Center (2013)

In order to reduce energy consumption of data centers while employing infrastructure resource effectively, a comprehensive resource management method using an improved online energy saving mapping algorithm for virtual machines of data centers is proposed. An intelligent feedback management framework is built for online resource optimization. We propose reinforcement learning and threshold based virtual machine migration to find the lowest energy consumption mapping between virtual machines and host of data centers dynamically and avoid the resources contention in physical machines. Our experimental results shows that the proposed effective online energy saving resource optimization methodology can reduce data center energy consumption by at least 30.3% compared to traditional random placement and save at least 10% running time compared to the offline Q-Learning scheduling algorithm.
Performance Evaluation of Machine Learning Models for Diabetes Prediction (2019)

Diabetes is one of the prevalent diseases all over the world. As per the International Diabetes Federation (IDF) report of the year 2017, diabetes is prevalent in about 8.8% of the Indian adult population and is one of the top ten causes of death in India. In untreated and unidentified diabetes could cause fluctuations in the sugar levels and extreme cases, damage organs such as kidneys, eyes, and arteries in the heart. By using Machine learning algorithms to predict the disease from the relevant datasets at an early stage could likely save human lives. The purpose of this investigation is to assess the classifiers that can predict the probability of disease in patients with the greatest precision and accuracy. Experimental work has been carried out using classification algorithms such as K Nearest Neighbor (KNN), Decision Tree(DT), Naive Bayes (NB), Support Vector Machine (SVM), Logistic Regression (LR) and Random Forest(RF) on Pima Indians Diabetes dataset using nine attributes which is available online on UCI Repository. The performance of classifier is evaluated based on precision, recall, accuracy and is estimated over correct and incorrect instances. The results proved that Logistic Regression (LR) performs better with the accuracy of 77.6 % in comparison to other algorithms.
LARGE SUPERCONDUCTING DETECTOR MAGNETS WITH ULTRA THIN COILS FOR USE IN HIGH ENERGY ACCELERATORS AND STORAGE RINGS (1977)

This paper describes the development of a ni!W class of large superconducting soleiwid magJ!l!ts.High energy physics on colJ,iding beam machines sometimes require the use of thin coH' solenoid magnets.,The development of these ,magnets bas proceeded with the substitution of li'ght materials for heavy materials and by ,inCrea9ing the current density in the coils.The Lawrence Beme1ey Laboratory bas developed a 1:adtca1 approach to the pEOblem by ba'ldng the co11 operate at very high cur1:ent, densities.This approach and its implications are described in detail.',' '-:-4.0-1.10 -0.5 0.38Cooling system Bsth Bsth Tube TubeCondu~tive bore tube
ChemInform Abstract: New N‐Ethanethiol Pyrroles as Radioprotectors. (1994)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
An implementation on Domain Name System security extensions framework for the support of IPv6 environment (2011)

Domain Name System Security Extensions (DNSSEC) is a suite of Internet Engineering Task Force (IETF) specifications for securing the information provided by the Domain Name System (DNS). It is a set of extensions to DNS which provide to DNS resolvers origin authentication of DNS data, authenticated denial of existence, and data integrity. The threats from the certain attack on DNS are common and although several tools or devices have been introduced, there still needs to have a better solution in overcoming the issues. The major problem in DNS are it does not offer any form of security and it is vulnerable to spoofing, man-in-the-middle and cache poisoning attacks. At the same time, there are several factors that preventing a widespread implementation of the DNSSEC, such as security testing, performance evaluation and used functionality testing. Thus, this paper will concentrate on implementing DNSSEC framework on IPv6 environment that provides origin authentication of DNS data, data integrity, and authenticated denial of existence.
Formulation, development and evaluation of injectable formulation of Aspirin (2013)

The objective of this study was to develop and manufacture a stable parenteral formulation for Aspirin, a non steroidal anti-inflammatory agent. The solubility and stability of the drug was determined. Solubility studies suggested that Aspirin exhibited poor aqueous solubility but showed appreciable solubility in non-aqueous solvents. Based on the preformulation studies, a lyophilized parenteral formulation containing 25 mg/mL of Aspirin was prepared in a solvent system containing of 80% v/v water and 20% v/v polyethylene glycol-400 (PEG-400). Rubber closures, filter membranes, and liquid transfer tubing were selected on the basis of compatibility studies. The formulation was subjected to accelerated stability studies. After reconstitution with sterile water for injection, Aspirin injection was stable for a period of 8 hr at 2°C to 8°C. Accelerated stability studies suggested that the lyophilized product should be kept at controlled room temperature for longterm storage. The proposed non-aqueous solvent concentration used, are known to safe hence, toxicities/safety related issues may not raise. The proposed techniques would be economical, convenient and safe. Thus, the study opens the chances of preparing lyophilized formulation of poorly-water soluble drugs.
New particles spring to life in two-dimensional electron gases (1995)

New physics and advances in technology often progress hand in hand. Nowhere is this more true than in the field of low dimensional structures, where the ability manufacture devices on length scales comparable with the de Broglie wavelength of the electron has led to the discovery of many new physical phenomena. The state of the art in low dimensional physics was on display at the 11th International Conference on the Electronic Properties of 2-Dimensional Systems (EP2DS) at the University of Nottingham in August. More than 400 delegates heard new results on everything from crystal growth and devices to optical spectroscopy, low temperature physics and many-body theory. (The conference proceedings will be published in Surface Science next year).
Cytoplasmic cyclin D1 regulates glioblastoma dissemination (2019)

Glioblastoma (GBM) is a highly invasive brain neoplasia with an elevated recurrence rate after surgical resection. The cyclin D1 (Ccnd1)/Cdk4-retinoblastoma 1 (RB1) axis is frequently altered in GBM, leading to overproliferation by RB1 deletion or by Ccnd1-Cdk4 overactivation. High levels of Ccnd1-Cdk4 also promote GBM cell invasion by mechanisms that are not so well understood. The purpose of this work is to elucidate the in vivo role of cytoplasmic Ccnd1-Cdk4 activity in the dissemination of GBM. We show that Ccnd1 activates the invasion of primary human GBM cells through cytoplasmic RB1-independent mechanisms. By using GBM mouse models, we observed that evaded GBM cells showed cytoplasmic Ccnd1 colocalizing with regulators of cell invasion such as RalA and paxillin. Our genetic data strongly suggest that, in GBM cells, the Ccnd1-Cdk4 complex is acting upstream of those regulators. Accordingly, expression of Ccnd1 induces focal adhesion kinase, RalA and Rac1 activities. Finally, in vivo experiments demonstrated increased GBM dissemination after expression of membrane-targeted Ccnd1. We conclude that Ccnd1-Cdk4 activity promotes GBM dissemination through cytoplasmic and RB1-independent mechanisms. Therefore, inhibition of Ccnd1-Cdk4 activity may be useful to hinder the dissemination of recurrent GBM. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Computer System Security Threat Evaluation Based Upon Artificial Immunity Model and Fuzzy Logic (2006)

Despite extensive efforts during recent years within the technical community to improve computer security, serious security problems continue to receive increasing coverage in both the popular and technical media. A large part of the problem stems from poor systems engineering of software and networks. In biological systems, natural internal immune system responses identify and protect the organism. A key mechanism in this immunity process is the ability to distinguish between self (i. e. normal organisms or behaviors) and non-self (i. e. abnormal or anomalous behavior). To deal with the ambiguities and imprecision in the process of anomaly detection for computer system security, we introduce a hierarchical fuzzy inference system to capture normal behavior deviations. Fuzzy logic has been widely used in control systems, decision-making, information retrieval, and many other applications. In this paper, we explore its capability in the area of computer security threat evaluation modeling and anomaly detection. Initial studies indicate promising results for this approach.
Encapsulation of Inorganic Nanomaterials inside Virus-Based Nanoparticles for Bioimaging (2017)

Virus-based nanoparticles (VNPs) can serve as containers for inorganic nanomaterials with excellent physical and chemical properties. Incorporation of nanomaterials inside the inner cavity of VNPs has opened up lots of possibilities for imaging applications in the field of biology and medicine. Encapsulation of inorganic nanoparticles (NPs) in VNPs can achieve the labeling of VNPs with nanoprobes and maintain the original outer surface features of VNPs at the same time. In return, VNPs enhance the stability and biocompatibility of the inorganic cargoes. This review briefly summarizes the current typical strategies to encapsulate inorganic nanomaterials in VNPs, i.e. mineralization and self-assembly, as well as the applications of these hybrid nanostructures in the field of bioimaging, including <i>in vitro</i> and <i>in vivo</i> fluorescence imaging, magnetic resonance imaging, and theranostics. Nanophotonic studies based on the VNP platform are also discussed. We anticipate that this field will continue to flourish, with new exciting opportunities stemming from advancements in the rational design of VNPs, the development of excellent inorganic nanomaterials, the integration of multiple functionalities, and the regulation of nano-bio interfacial interactions.
Corrosion resistance of ZnNiP+Ni composite coatings (2010)

Abstract ZnNiP+Ni composite coatings were prepared by embedding nickel particles into ZnNiP alloy using ammonia solution in which Ni powder was suspended by stirring. Such coatings have been deposited on a 0H18N9 stainless steel substrate under galvanostatic conditions ( j = −40 mA cm −2 ), and at a temperature of 293 K. In order to investigate corrosion properties of the as‐deposited and annealed (593 K for 2 h in argon atmosphere) ZnNiP+Ni composite coatings in 5% NaCl environment potentiodynamic technique and electrochemical impedance spectroscopy (EIS) were used. It was stated that thermal treatment strongly improved the corrosion parameters of the examined ZnNiP+Ni composite coatings, and also that better corrosion properties result from i) improved corrosion properties of the oxide layer; and ii) the presence of new γNi 5 Zn 21 phase in composite matrix. Copyright © 2010 John Wiley & Sons, Ltd.
Isolation and purification of caseinase and collagenase from commercial bacillus subtilis enzyme by affinity chromatography (2009)

Bacillus Subtilis is a saprophytic bacteria which has a widespread distribution in nature and can be easily isolated from soil microbes. Bacillus Subtilis AS1.398 is a major strain of Bacillus Subtilis used extensively in light industry and the pharmaceutical industry and is commonly used in the leather industry in China for depilation and bating. The non-collagenolytic activity of caseinase is correlated with the depilation. Collagenolytic protease has little contribution to depilation. It damages the collagen fibres and reduces the quality of leather. Collagenolytic activity should be inhibited during enzymatic depilation. Caseinase and collagenase were isolated and purified to homogeneity from commercial Bacillus Subtilis AS1.398 by affinity chromatography on the basis of modified hide powder as supporter. The purified enzyme had an estimated molecular mass of 44.3kDa determined by SDS-PAGE. Assays were also made on the activities of the two proteases. The specific activity of the caseinase showed a recovery of 42%.
Testing and characterization of PV modules with integrated microinverters (2013)

Photovoltaic (PV) modules with attached microinverters are becoming increasingly popular in PV systems, especially in the residential system market, as such systems offer several benefits not found in PV systems utilizing central inverters. PV modules with fully integrated microinverters are emerging to fill a similar market space. These “AC modules” absorb solar energy and produce AC energy without allowing access to the intermediate DC bus. Existing test procedures and performance models designed for separate DC and AC components are unusable when the inverter is integrated into the module. Sandia National Laboratories is developing a new set of test procedures and performance model designed for AC modules.
A Structured Interview Guide for the Hamilton Depression Rating Scale (1988)

The Hamilton Depression Rating Scale (HDRS) is the most widely used scale for patient selection and follow-up in research studies of treatments of depression. Despite extensive study of the reliability and validity of the total scale score, the psychometric characteristics of the individual items have not been well studied. In the only reliability study to report agreement on individual items using a test-retest interview method, most of the items had only fair or poor agreement. Because this is due in part to variability in the way the information is obtained to make the various rating distinctions, the Structured Interview Guide for the HDRS (SIGH-D) was developed to standardize the manner of administration of the scale. A test-retest reliability study conducted on a series of psychiatric inpatients demonstrated that the use of the SIGH-D results in a substantially improved level of agreement for most of the HDRS items.
RNA-Binding Activity of the E1B 55-Kilodalton Protein from Human Adenovirus Type 5 (1998)

The human adenovirus 5 E1B 55-kDa protein is required for efficient nucleocytoplasmic transport of late viral mRNAs. This protein is shown to have RNA-binding activity which maps to a region of the protein with homology to a family of RNA-binding proteins and which has been shown previously to be essential for functionality of the protein in vivo.
An Experimental Cascade Cell Dynamic Memory (2005)

Series connected storage cells provide greater storage density for a given DRAM technology. We introduce several new features to exploit this advantage: an extra wordline to allow read and restore of the serial bits in the same order, a shift register row decoder with variable size redundancy, and a sense amp exchange configuration to ameliorate inter-bitline noise, We have designed and fabricated an experimental 32M DRAM that shows these ideas are feasible.