gebhart/patrepeval huggingface dataset:
Based on image processing recognition line system of high-voltage overhead lines (2010)

Power system is an important pillar industry of national, Transmission line technology of high-voltage overhead lines is important and difficult to safe operation. This study introduced several major transmission line approach, and designed a system of transmission line based on image processing. The system uses computer image recognition technology and on-site sensors, automatically determine the abnormal power transmission lines, and alarm. Central control room staff can accurately determine the situation of field failures according to images and sensor information, and can selectively measures, and command a variety of linkage action.
Spatially interacting phosphorylation sites and mutations in cancer (2021)

Advances in mass-spectrometry have generated increasingly large-scale proteomics datasets containing tens of thousands of phosphorylation sites (phosphosites) that require prioritization. We develop a bioinformatics tool called HotPho and systematically discover 3D co-clustering of phosphosites and cancer mutations on protein structures. HotPho identifies 474 such hybrid clusters containing 1255 co-clustering phosphosites, including RET p.S904/Y928, the conserved HRAS/KRAS p.Y96, and IDH1 p.Y139/IDH2 p.Y179 that are adjacent to recurrent mutations on protein structures not found by linear proximity approaches. Hybrid clusters, enriched in histone and kinase domains, frequently include expression-associated mutations experimentally shown as activating and conferring genetic dependency. Approximately 300 co-clustering phosphosites are verified in patient samples of 5 cancer types or previously implicated in cancer, including CTNNB1 p.S29/Y30, EGFR p.S720, MAPK1 p.S142, and PTPN12 p.S275. In summary, systematic 3D clustering analysis highlights nearly 3,000 likely functional mutations and over 1000 cancer phosphosites for downstream investigation and evaluation of potential clinical relevance.
A Perturbation Method for Decoding LDPC Concatenated with CRC (2007)

In this paper, a novel decoding algorithm using perturbation techniques for LDPC concatenated with CRC (LDPC-CRC) is proposed. The CRC is used to check the residual error of the BP algorithm, while a new parameter is introduced to LDPC decoding to describe the reliability of each bit in the iterative decoding algorithm. Upon an error is detected, re-decoding process with perturbation method will be aroused. Simulation results show that this method lowers the error floor for codeword length of several hundred bits effectively.
TTF and TCNQ adducts of trimeric perfluoro-ortho-phenylene mercury (2004)

Combination of trimeric perfluoro- ortho -phenylene mercury (1) with TTF and TCNQ in a 1:1 mixture of CH 2 Cl 2 and CS 2 followed by slow evaporation of the solvent leads to the formation of orange needles of [ (1) 2 ·TTF] (2) and light yellow needles of [ (1) 2 ·TCNQ] (3) , respectively. The structure of both complexes has been determined by X-ray analysis. The solid-state structure of 2 consists of centrosymmetrical supramolecules of [ (1) 2 ·TTF], in which the TTF molecule is sandwiched by two molecules of 1 . This supramolecule is held by multiple Hg···S secondary interactions ranging from 3.467(5) Å to 3.533(5) Å. The solid state of 3 also consists of centrosymmetrical molecules of [ (1) 2 ·TCNQ]. In this case, however, the TCNQ molecule is approximately perpendicular to the neighboring molecules of 1 with which it interacts by coordination of two nitrile groups. Examination of the atomic connectivity indicates the simultaneous coordination of the coordinated nitrile nitrogen atoms to the three mercury centers of 1 . The resulting Hg···N distances range from 3.102(11) to 3.134(11) Å. .
On the Origins of Conductive-Pulse Sensing Inside a Nanopore (2022)

Abstract Nanopore sensing is nearly synonymous with resistive pulse sensing due to the characteristic reduction of ionic flux during molecular occupancy of a pore, particularly at high salt concentrations. However, conductive pulses are widely reported at low salt conditions wherein electroosmotic flow can be quite significant. Aside from transporting molecules like DNA, we investigated whether electroosmotic flow has other potential impacts on sensing attributes such current enhancements due to the analyte molecule. The overwhelming majority of literature reports counterions as the dominant mechanism of conductive events (a molecule-centric theory for conductive events). Conductive events are not well understood due to the complex interplay between (charged) nanopore walls, DNA grooves, ion mobility, and counterion clouds. Yet, the prevailing consensus of counterions being introduced into the pore by the molecule does not fit well with a growing number of experiments including the fact that proteins can generate conductive events despite having a heterogeneous surface charge. Herein, we demonstrate theory and experiments underpinning the translocation mechanism (i.e., electroosmosis or electrophoresis), pulse direction (i.e., conductive or resistive) and shape (e.g., monophasic or biphasic) through fine control of chemical, physical, and electronic parameters. Results from these studies predict strong electroosmosis plays a role in driving DNA events and generating conductive events due to polarization effects (i.e. a pore-centric theory). We believe these findings will stimulate a useful discussion on the nature of conductive events and their impact on molecular sensing in nanoscale pores.
Expression of high‐abundance proteins in sera of patients with endometrial and cervical cancers: Analysis using 2‐DE with silver staining and lectin detection methods (2007)

The expression of high-abundance serum proteins in newly diagnosed patients with endometrial adenocarcinoma (EACa), squamous cell cervical carcinoma (SCCa) and cervical adenocarcinoma (ACCa), relative to control female subjects, was analyzed by subjecting serum samples to 2-DE followed by image analysis of the silver-stained protein profiles. The three cohorts of cancer patients demonstrated different altered expression of serum high-abundance proteins compared to negative control women. The expression of alpha1-antitrypsin, alpha1-B glycoprotein, cleaved high-molecular-weight kininogen (light chain) and antithrombin III were consistently altered in all the patients. However, clusterin was upregulated only in the patients with EACa, while those with SCCa and ACCa were typically characterized by the upregulated expression of zinc alpha-2-glycoprotein. The aberrant expression of selective serum proteins in the various cohorts of cancer patients was validated by competitive ELISA as well as by lectin detection. Analysis by using the champedak galactose binding lectin further highlighted an unidentified protein that may be differently glycosylated in the sera of the EACa patients that were studied.
Deep-Space Optical Transceiver Uplink Detection Analysis (2013)

In this memo, we develop and analyze an uplink signal detection technique for the Deep-Space Optical Transceiver (DOT). Here, the detection is carried out using a set of test statistics obtained from up-down counter (UDC) photon detection systems. Specifically, we address two sets of statistics: the count outputs from a bank of uniformly temporally spaced UDCs as well as the counts from a single UDC that cycles through multiple timing phases. From these test statistics, we derive the Neyman-Pearson decision rule under certain input conditions and analyze the performance of this hypothesis test. We show the performance trade-offs associated with both sets of test statistics, which can then be used to determine which set to use as well as the number of UDCs or timing phases required for implementation. I.
Deep Learning for Sentiment Analysis (2022)

Sentiment analysis is an important area of natural language processing that can help inform business decisions by extracting sentiment information from documents. The purpose of this chapter is to introduce the reader to selected concepts and methods of deep learning and show how deep models can be used to increase performance in sentiment analysis. It discusses the latest advances in the field and covers topics including traditional sentiment analysis approaches, the fundamentals of sentence modelling, popular neural network architectures, autoencoders, attention modelling, transformers, data augmentation methods, the benefits of transfer learning, the potential of adversarial networks, and perspectives on explainable AI. The authors' intent is that through this chapter, the reader can gain an understanding of recent developments in this area as well as current trends and potentials for future research.
3D‐QSAR studies and molecular design on a novel series of pyrimidine benzimidazoles as Lck inhibitors (2014)

The development of selective lymphocyte‐specific kinase (Lck) inhibitors has attracted much attention for the research of the treatment of T‐cell mediated autoimmune and inflammatory diseases. In the present work, three‐dimensional quantitative structure–activity relationship (3D‐QSAR) analyses are performed on a novel series of 4‐amino‐6‐benzimidazole‐pyrimidines acting as Lck inhibitors. The established 3D‐QSAR models show significant statistical quality and satisfactory predictive ability, with high q 2 and R 2 values: the comparative molecular field analysis (CoMFA) model ( q 2 = 0.802, R 2 = 0.991), and the comparative molecular similarity indexes analysis (CoMSIA) model ( q 2 = 0.731, R 2 = 0.982). The systemic external validation indicates that both CoMFA and CoMSIA models are quite robust and possess high predictive abilities with values of 0.881 and 0.877, values of 0.897 and 0.847, values of 0.897 and 0.850, and values of 0.897 and 0.854, respectively. Several key structural features accounting for the inhibitory activities of these compounds are discussed. Based on established models and design considerations, six new compounds with significantly improved activities are theoretically designed, which still await experimental confirmation and evaluation. These theoretical results may provide a useful reference for understanding the action mechanism and designing novel potential Lck inhibitors. © 2014 Wiley Periodicals, Inc.
Weight‐matrix structured regularization provides optimal generalized least‐squares estimate in diffuse optical tomography (2007)

Diffuse optical tomography (DOT) involves estimation of tissue optical properties using noninvasive boundary measurements. The image reconstruction procedure is a nonlinear, ill-posed, and ill-determined problem, so overcoming these difficulties requires regularization of the solution. While the methods developed for solving the DOT image reconstruction procedure have a long history, there is less direct evidence on the optimal regularization methods, or exploring a common theoretical framework for techniques which uses least-squares (LS) minimization. A generalized least-squares (GLS) method is discussed here, which takes into account the variances and covariances among the individual data points and optical properties in the image into a structured weight matrix. It is shown that most of the least-squares techniques applied in DOT can be considered as special cases of this more generalized LS approach. The performance of three minimization techniques using the same implementation scheme is compared using test problems with increasing noise level and increasing complexity within the imaging field. Techniques that use spatial-prior information as constraints can be also incorporated into the GLS formalism. It is also illustrated that inclusion of spatial priors reduces the image error by at least a factor of 2. The improvement of GLS minimization is even more apparent when the noise level in the data is high (as high as 10%), indicating that the benefits of this approach are important for reconstruction of data in a routine setting where the data variance can be known based upon the signal to noise properties of the instruments.
Inflammatory Mechanisms Contributing to Endothelial Dysfunction (2021)

Maintenance of endothelial cell integrity is an important component of human health and disease since the endothelium can perform various functions including regulation of vascular tone, control of hemostasis and thrombosis, cellular adhesion, smooth muscle cell proliferation, and vascular inflammation. Endothelial dysfunction is encompassed by complex pathophysiology that is based on endothelial nitric oxide synthase uncoupling and endothelial activation following stimulation from various inflammatory mediators (molecular patterns, oxidized lipoproteins, cytokines). The downstream signaling via nuclear factor-κB leads to overexpression of adhesion molecules, selectins, and chemokines that facilitate leukocyte adhesion, rolling, and transmigration to the subendothelial space. Moreover, oscillatory shear stress leads to pro-inflammatory endothelial activation with increased monocyte adhesion and endothelial cell apoptosis, an effect that is dependent on multiple pathways and flow-sensitive microRNA regulation. Moreover, the role of neutrophil extracellular traps and NLRP3 inflammasome as inflammatory mechanisms contributing to endothelial dysfunction has recently been unveiled and is under further investigation. Consequently, and following their activation, injured endothelial cells release inflammatory mediators and enter a pro-thrombotic state through activation of coagulation pathways, downregulation of thrombomodulin, and an increase in platelet adhesion and aggregation owing to the action of von-Willebrand factor, ultimately promoting atherosclerosis progression.
The Strength in Anterior Bending of Lumbar Intervertebral Discs (1994)

Disc failure in bending occurs through overstretching of the outer anulus in the vertical direction. In life, the posterior elements may not adequately protect the posterior anulus from fatigue damage.
Content-based retrieval for music collections (1999)

A content-based retrieval model for tackling the mismatch problems specific to music data is proposed and implemented. The system uses a pitch profile encoding for queries in any key and an n-note indexing method for approximate matching in sub-linear time. A distinct function that extracts key melodies for query suggestion is developed. The Web-based system provides flexible user interface for query formulation and result browsing. Users can search the system by a short sequence of notes, by uploading a file created by singing, or by clicking suggested key melodies without input. Experiments show that the pitch profile encoding and a 3-note indexing are able to overcome the key mismatch problem and the random errors caused by pitch error, note deletion and insertion. The use of extracted key melodies improves performance over direct search of the music database. For the type of burst mismatch, a query expansion approach is applied.
Using Competitive Exclusion, Mannan-Oligosaccharide and Other Intestinal Products to Control Necrotic Enteritis (2003)

Clinical and subclinical necrotic enteritis (NE) caused by the ubiquitous bacteria Clostridium perfringens can have a significant economic impact in broiler chickens. This impact is especially apparent when antibiotic feed additives are not used. In this study, the effectiveness of five nonantibiotic feed additives and two competitive exclusion (CE) cultures were compared using an NE challenge model. Untreated male broiler chickens housed in an environmentally controlled facility were challenged with C. perfringens and had high mortality, gross intestinal lesions, poor feed utilization, and reduced body weights. Broilers treated with a defined lactic acid bacterial CE culture at 1 d and fed a diet containing 2 g/ton of mannan-oligosaccharide had the lowest mortality from necrotic enteritis. The feed efficiency of this combined treatment was similar to that of broilers fed a diet containing 50 g/ton of bacitracin methylene disalicylate. The treatment in which broilers were given an undefined CE or the mannan-oligosaccharide alone, as well as three other feed additives, did not have any significant effect on feed efficiency, mortality, or body weight over the NE challenge control birds. The findings of this study are very important in developing nutritional strategies to provide options for prevention of NE without continuously using antibiotics in feed.
CuO nanoparticle penetration through intact and damaged human skin (2019)

Trans-dermal <italic>in vitro</italic> study of CuO nanoparticles in contact with intact and damaged human skin using a Franz cell model.
Argininosuccinate Synthase 1-Deficiency Enhances the Cell Sensitivity to Arginine through Decreased DEPTOR Expression in Endometrial Cancer (2017)

Argininosuccinate synthetase 1 (ASS1) is a rate-limiting enzyme in arginine biosynthesis. Although ASS1 expression levels are often reduced in several tumors and low ASS1 expression can be a poor prognostic factor, the underlying mechanism has not been elucidated. In this study, we reveal a novel association between ASS1 and migration/invasion of endometrial tumors via regulation of mechanistic target of rapamycin complex (mTORC) 1 signaling. ASS1-knockout cells showed enhanced migration and invasion in response to arginine following arginine starvation. In ASS1-knockout cells, DEPTOR, an inhibitor of mTORC1 signal, was downregulated and mTORC1 signaling was more activated in response to arginine. ASS1 epigenetically enhanced DEPTOR expression by altering the histone methylation. Consistent with these findings, tumor cells at the invasive front of endometrioid carcinoma cases showed lower ASS1 and DEPTOR expression. Our findings suggest that ASS1 levels in each tumor cell are associated with invasion capability in response to arginine within the tumor microenvironment through mTORC1 signal regulation.
Problems with Using the Normal Distribution – and Ways to Improve Quality and Efficiency of Data Analysis (2011)

The corresponding shift from the symmetric to the asymmetric view will substantially increase both, recognition of data distributions, and interpretation quality. It will allow for savings in sample size that can be considerable. Moreover, this is in line with ethical responsibility. Adequate models will improve concepts and theories, and provide deeper insight into science and life.
Cover Image (2018)

The cover image, by JiXian Lin et al., is based on the Original Article Hydration prevents chronic hyperglycaemic patients from neurological deterioration post-ischaemic stroke, DOI: 10.1111/ane.12900. Design credit: Qingmei Zhang.
Design Defects Detection and Correction by Example (2011)

Detecting and fixing defects make programs easier to understand by developers. We propose an automated approach for the detection and correction of various types of design defects in source code. Our approach allows to automatically find detection rules, thus relieving the designer from doing so manually. Rules are defined as combinations of metrics/thresholds that better conform to known instances of design defects (defect examples). The correction solutions, a combination of refactoring operations, should minimize, as much as possible, the number of defects detected using the detection rules. In our setting, we use genetic programming for rule extraction. For the correction step, we use genetic algorithm. We evaluate our approach by finding and fixing potential defects in four open-source systems. For all these systems, we found, in average, more than 80% of known defects, a better result when compared to a state-of-the-art approach, where the detection rules are manually or semi-automatically specified. The proposed corrections fix, in average, more than 78%of detected defects.
Viewpoint: Who Should Pay The Bill? (1971)

(1971). Viewpoint: Who Should Pay The Bill? Change: The Magazine of Higher Learning: Vol. 3, No. 3, pp. 6-71.
Synthesis Approaches of Zinc Oxide Nanoparticles: The Dilemma of Ecotoxicity (2017)

Human’s quest for innovation, finding solutions of problems, and upgrading the industrial yield with energy efficient and cost-effective materials has opened the avenues of nanotechnology. Among a variety of nanoparticles, zinc oxide nanoparticles (ZnO) have advantages because of the extraordinary physical and chemical properties. It is one of the cheap materials in cosmetic industry, nanofertilizers, and electrical devices and also a suitable agent for bioimaging and targeted drug and gene delivery and an excellent sensor for detecting ecological pollutants and environmental remediation. Despite inherent toxicity of nanoparticles, synthetic routes are making use of large amount of chemical and stringent reactions conditions that are contributing as environmental contaminants in the form of high energy consumption, heat generation, water consumption, and chemical waste. Further, it is also adding to the innate toxicity of nanoparticles (NPs) that is either entirely ignored or poorly investigated. The current review illustrates a comparison between pollutants and hazards spawned from chemical, physical, and biological methods used for the synthesis of ZnO. Further, the emphasis is on devising eco-friendly techniques for the synthesis of ZnO especially biological methods which are comparatively less hazardous and need to be optimized by controlling the reaction conditions in order to get desired yield and characteristics.
Feature selection using Joint Mutual Information Maximisation (2015)

Feature selection is used in many application areas relevant to expert and intelligent systems, such as data mining and machine learning, image processing, anomaly detection, bioinformatics and natural language processing. Feature selection based on information theory is a popular approach due its computational efficiency, scalability in terms of the dataset dimensionality, and independence from the classifier. Common drawbacks of this approach are the lack of information about the interaction between the features and the classifier, and the selection of redundant and irrelevant features. The latter is due to the limitations of the employed goal functions leading to overestimation of the feature significance. To address this problem, this article introduces two new nonlinear feature selection methods, namely Joint Mutual Information Maximisation (JMIM) and Normalised Joint Mutual Information Maximisation (NJMIM); both these methods use mutual information and the ‘maximum of the minimum’ criterion, which alleviates the problem of overestimation of the feature significance as demonstrated both theoretically and experimentally. The proposed methods are compared using eleven publically available datasets with five competing methods. The results demonstrate that the JMIM method outperforms the other methods on most tested public datasets, reducing the relative average classification error by almost 6% in comparison to the next best performing method. The statistical significance of the results is confirmed by the ANOVA test. Moreover, this method produces the best trade-off between accuracy and stability.
A Sub-$\mu$s Wake-Up Time Power Gating Technique With Bypass Power Line for Rush Current Support (2009)

A sub-mus wake-up time power gating technique was developed for low-power SoCs. It uses two types of power switches and a separated power line bypassing rush current to suppress power-supply-voltage fluctuation. We applied this technique to a heterogeneous dual-core microprocessor fabricated in 90 nm CMOS technology. When wake-up time on the 2M-gate scale circuit was set to 0.24 mus , the supply voltage fluctuation was suppressed to 2.5 mV. The area overhead of this technique was less than 1% of the total die area.