bluuebunny/crossref_metadata_2025_split huggingface dataset:
CSPEC: The cold chopper spectrometer of the ESS, a detailed overview prior to commissioning
Authors: Deen P. P. , Longeville S. , Lohstroh W. , Moreira F. , Fabrèges G. , Loaiza L. , Noferini D. 
Published: October 2021

CSPEC is the cold chopper spectrometer of the European Spallation Source (ESS) and will come online with the ESS beam on the target. CSPEC will be the first cold chopper spectrometer on a long pulsed spallation source, which provides great opportunities in terms of signal to noise and novel measuring schemes. We provide a detailed overview of the instrument, scientific design considerations, and engineering requirements.
Research on saliency detection method based on depth and width neural network
Authors: He Guanqi , Lu Guo 
Published: October 2021

Abstract
Image saliency detection is to segment the most important areas in the image. Solving the problem of image saliency detection usually involves knowledge in computer vision, neuroscience, cognitive psychology and other fields. In recent years, as deep learning has made great achievements in the field of computer vision, the application of deep learning has also played a good role in image saliency detection. Therefore, algorithms based on deep convolutional neural networks have become solutions to image saliency The most effective method of detection. For researchers, improving the computational efficiency of neural network-based saliency detection algorithms generally starts from two perspectives. One is to tailor the network structure and combine traditional feature extraction methods for processing. The other is to use a lighter network to solve the saliency detection problem. Based on these two points of thinking, this paper proposes two efficient and accurate neural network-based saliency detection algorithms. In recent years, with the rapid development of multimedia and Internet technologies, a huge amount of picture information is generated on blogs, social networking or shopping platforms every day. Such a lot of information not only enriches people’s lives, but also provides efficient and accurate network management platforms. The management of these image information brings difficulties. Therefore, how to understand and process these image information more intelligently and efficiently has become a hot topic for many image processing and computer vision researchers. Among them, the saliency detection technology plays a key role in solving the problem of intelligent understanding and processing of images. To put it simply, saliency detection is a technology to automatically calculate or detect the most important areas in an image, and its processing results provide a basis for understanding and processing the image content. Saliency detection is a basic problem in computer vision, neuroscience and visual perception. The algorithm detects and extracts the most interesting or significant areas in the image.
Materials selection method using improved TOPSIS without rank reversal based on linear max-min normalization with absolute maximum and minimum values
Authors: Yang Won-Chol , Choe Chol-Min , Kim Jin-Sim , Om Myong-Song , Kim Un-Ha 
Published: October 2021

Abstract
Technique for order preference by similarity to ideal solution (TOPSIS) is a well-known multi attribute decision making (MADM) method and it has been widely used in materials selection. However, the main drawback of the traditional TOPSIS is that it has a rank reversal phenomenon. To overcome this drawback, we propose an improved TOPSIS without rank reversal based on linear max-min normalization with absolute maximum and minimum values by modifying normalization formula and ideal solutions. Moreover, to study the impacts of changing attribute weights on relative closeness values of alternatives, we propose a sensitivity analysis method to attribute weights on the relative closeness values of the alternatives. We applied the proposed method to select best absorbent layer material for thin film solar cells (TFSCs). As a result, copper indium gallium diselinide was selected as the best one and the next cadmium telluride from among five materials. When the alternative is added to or removed from the set of original alternatives, the elements of the normalized decision-matrix, PIS, NIS and the relative closeness values don’t change at all, they are always coincide with the corresponding elements of the original ones. The relative closeness values are absolute values irrelevant to the composition of the alternatives in the improved TOPSIS, while the relative closeness values are relative values relevant to the composition of the alternatives in the traditional TOPSIS. Therefore, the proposed TOPSIS overcomes the rank reversal phenomenon, perfectly. It could be actively applied to practical problems for materials selection.
Torque-compensated bundle of artificial muscle to generate large forces
Authors: Kim Kihyeon , Yang Sang Yul , Park Jae Hyeong , Jung Ho Sang , Ko Jung U , Hwang Seong Taek , Koo Ja Choon , Moon Hyungpil , Rodrigue Hugo , Choi Hyouk Ryeol 
Published: October 2021

Abstract
Recently, owing to the significant advancement in the field of soft robots, various studies have been conducted on soft actuators. Among the several soft actuators, the double helix twisted and coiled actuator (DTCA), which is fabricated by coiling spandex and nylon under twisted conditions, exhibits considerable performance in terms of large contractile force/strain and Joule heating capability. However, the DTCA still cannot produce sufficient force for large-scale applications. Bundling the DTCA in parallel is a well-known solution to improve the force. However, excessive bundling results in unnecessary torque, which causes friction in the entire system. In this paper, we propose a DTCA bundle that can generate a significantly higher force than that previously observed in the field of soft robotics. The proposed bundle compensates for the uncoiling torque by bundling DTCAs fabricated in opposite directions. The fabrication conditions were modified experimentally to satisfy the equivalent performance of each type of DTCA. Consequently, they exhibited as similar performance, including the uncoiling torque with an error of less than 8%.
One pot synthesis of Ti and O co-doped g-C3N4: a novel composite for efficient visible-light-driven photocatalytic inactivation of E. cloacae
Authors: She Peng , Yao Chun , Li Jun , Bao Hegang , Xu Xiuquan , Zhou Hong 
Published: October 2021

Abstract
Co-doping is one of the most facile and efficient strategies for boosting the photocatalytic performance of g-C3N4. Herein, a series of Ti and O co-doped g-C3N4 (Ti/OCN) composites with excellent photocatalytic inactivation activity of Enterobacter cloacae (E. cloacae) were successfully synthesized by simple calcination of urea/formic acid/TiCl4 precursor. The obtained Ti/OCN-3 possessed the optimal photocatalytic capability with complete inactivation of 6.20 log CFU·ml−1
E. cloacae under 60 min of visible light irradiation. The improved photocatalytic disinfection performance was probably attributed to the synergistic effect of Ti and O co-doping, which led to an extended visible light response and accelerated charge transport efficiency. Furthermore, scavenger trapping and electron spin resonance (ESR) experiments revealed that ·O2
−, h+ and ·OH were responsible for the enhanced inactivation activity. Overall, this research provided a promising strategy for fabricating g-C3N4-based catalysts to efficiently deal with the hazards of pathogenic microorganisms.
Friction stir welding parameters and their influence on mechanical properties of welded AA6061 and AA5052 aluminium plates
Authors: M Sindhuja , S Neelakrishnan , Davidson Benjamin Shiloh 
Published: October 2021

Abstract
Friction stir welding (FSW) process is the preferred technique for joining of dissimilar metals. This paper intends to provide comprehensive study on the mechanical and metallurgical properties of dissimilar friction stir welded aluminium alloys, AA6061 and AA5052. The objective of the study is to find the optimum welding parameters at which the maximum weld joint strength can be achieved and to identify the influence of those parameters on the weld strength and microstructure of the AA6061 with AA5052 welded joints. The FSW process parameters such as traverse speed, tool rotational speed, axial force and tilt angle were considered. The mechanical properties measured are yield strength, tensile strength and percentage of elongation. Scanning Electron Microscopy (SEM) and optical microscope were used to observe the microstructure of weld zone (WZ) and heat affected zone (HAZ) of welded samples. Energy Dispersive x-ray Analysis (EDS) was used to obtain the elemental composition at the weld zone. Visual inspection reveals that there is no existence of weld defects like voids and porosity developed on the surface of the joints. The welds produced by the dissimilar aluminium alloys exposed an equiaxed and fine-grained structure in the weld zone. Analysis of variance (ANOVA) Technique is used to check the adequacy of the developed mathematical model. The difference between calculated and adjusted R2 is 0.2 which indicates that the model is adequate. The percentage error is also less for the estimated and predicted values of the properties of welded joints.
Heavy fermion thin films: progress and prospects
Authors: Chatterjee Shouvik 
Published: October 2021

Abstract
Heavy fermion compounds are a remarkable class of inter-metallic systems, where the presence of several competing interactions leads to the emergence of a plethora of exotic properties. Although these compounds have been extensively studied in the last few decades, their epitaxial synthesis in a thin film form has remained poorly explored. The ability to create these materials in a bottoms-up manner opens up the possibility of both controlling and engineering their properties at the atomic scale, and allows fabrication of artificial heterostructures and superlattices that have no bulk analogues. Furthermore, experimental probes, which are compatible with a thin film geometry but are difficult to make use of with bulk single crystals, can be utilized to gain new insights into their electronic structure. Motivated by the recent advances in thin film technology, this review aims to explore the challenges in thin film growth of heavy fermion systems, presents an overview of the recent progress, and outlines unique opportunities that exist, which are of fundamental scientific importance and could be harnessed for potential technological applications.
The scientific principles and technological determinants of haemodialysis membranes
Authors: Bowry Sudhir K , Chazot Charles 
Published: October 2021

ABSTRACT
In most biological or industrial (including medical) separation processes, a membrane is a semipermeable barrier that allows or achieves selective transport between given compartments. In haemodialysis (HD), the semipermeable membrane is in a tubular geometry in the form of miniscule pipes (hollow fibres) and separation processes between compartments involve a complex array of scientific principles and factors that influence the quality of therapy a patient receives. Several conditions need to be met to accomplish the selective and desired removal of substances from blood in the inner cavity (lumen) of the hollow fibres and across the membrane wall into the larger open space surrounding each fibre. Current HD membranes have evolved and improved beyond measure from the experimental membranes available in the early developmental periods of dialysis. Today, the key functional determinants of dialysis membranes have been identified both in terms of their potential to remove uraemic retention solutes (termed ‘uraemic toxins’) as well subsidiary criteria they must additionally fulfill to avoid undesirable patient reactions or to ensure safety. The production of hundreds of millions of kilometres of hollow fibre membranes is truly a technological achievement to marvel, particularly in ensuring that the fibre dimensions of wall thickness and inner lumen diameter and controlled porosity—all so vital to core solute removal and detoxification functions of dialysis—are maintained for every centimetre length of the fragile fibres. Production of membranes will increase in parallel with the increase in the number of chronic kidney disease (CKD) patients expected to require HD therapies in the future. The provision of high-quality care entails detailed consideration of all aspects of dialysis membranes, as quality cannot in any way be compromised for the life-sustaining—like the natural membranes within all living organisms—function artificial dialysis membranes serve.
Mining drug–target and drug–adverse drug reaction databases to identify target–adverse drug reaction relationships
Authors: Galletti Cristiano , Bota Patricia Mirela , Oliva Baldo , Fernandez-Fuentes Narcis 
Published: October 2021

Abstract
The level of attrition on drug discovery, particularly at advanced stages, is very high due to unexpected adverse drug reactions (ADRs) caused by drug candidates, and thus, being able to predict undesirable responses when modulating certain protein targets would contribute to the development of safer drugs and have important economic implications. On the one hand, there are a number of databases that compile information of drug–target interactions. On the other hand, there are a number of public resources that compile information on drugs and ADR. It is therefore possible to link target and ADRs using drug entities as connecting elements. Here, we present T-ARDIS (Target—Adverse Reaction Database Integrated Search) database, a resource that provides comprehensive information on proteins and associated ADRs. By combining the information from drug–protein and drug–ADR databases, we statistically identify significant associations between proteins and ADRs. Besides describing the relationship between proteins and ADRs, T-ARDIS provides detailed description about proteins along with the drug and adverse reaction information. Currently T-ARDIS contains over 3000 ADR and 248 targets for a total of more 17 000 pairwise interactions. Each entry can be retrieved through multiple search terms including target Uniprot ID, gene name, adverse effect and drug name. Ultimately, the T-ARDIS database has been created in response to the increasing interest in identifying early in the drug development pipeline potentially problematic protein targets whose modulation could result in ADRs.
Database URL: http://www.bioinsilico.org/T-ARDIS
Plasma metabolomics of autism spectrum disorder and influence of shared components in proband families
Authors: Chung Ming Kei , Smith Matthew Ryan , Lin Yufei , Walker Douglas I , Jones Dean , Patel Chirag J , Kong Sek Won 
Published: October 2021

Abstract
Prevalence of autism spectrum disorder (ASD) has been increasing in the United States in the past decades. The exact mechanisms remain enigmatic, and diagnosis of the disease still relies primarily on assessment of behavior. We first used a case–control design (75 idiopathic cases and 29 controls, enrolled at Boston Children’s Hospital from 2007-2012) to identify plasma biomarkers of ASD through a metabolome-wide association study approach. Then we leveraged a family-based design (31 families) to investigate the influence of shared genetic and environmental components on the autism-associated features. Using untargeted high-resolution mass spectrometry metabolomics platforms, we detected 19 184 features. Of these, 191 were associated with ASD (false discovery rate &lt; 0.05). We putatively annotated 30 features that had an odds ratio (OR) between &lt;0.01 and 5.84. An identified endogenous metabolite, O-phosphotyrosine, was associated with an extremely low autism odds (OR 0.17; 95% confidence interval 0.06-0.39). We also found that glutathione metabolism was associated with ASD (P = 0.048). Correlations of the significant features between proband and parents were low (median = 0.09). Of the 30 annotated features, the median correlations within families (proband–parents) were −0.15 and 0.24 for the endogenous and exogenous metabolites, respectively. We hypothesize that, without feature identification, family-based correlation analysis of autism-associated features can be an alternative way to assist the prioritization of potentially diagnostic features. A panel of ASD diagnostic metabolic markers with high specificity could be derived upon further studies.
Improved structural design of wind turbine blade based on topology and size optimization
Authors: Zhu Jie , Cai Xin , Ma Dongfang , Zhang Jialiang , Ni Xiaohui 
Published: October 2021

Abstract
In order to compete with traditional power technologies and other energy sources, it is essential to use optimization techniques as part of the design process for wind turbine blades. This paper presents an optimization approach for the improved structural design of blades, aiming at further decreasing the blade mass and bringing down the cost. The optimization approach mainly consists of two steps. In the first step, topology optimization of a full 1.5 MW wind turbine blade is carried out with the expectation of finding an improved internal structural configuration by taking minimum compliance as an objective. In the second step, the topology optimization results are interpreted to create a shell finite element model of the blade to analyse the influence of distinguishing characteristic parameters on the blade performances; then, size optimizations of the blades with improved structural configuration and conventional structure are performed by considering the minimum mass as objective, key structural parameters as variables, strain, deflection, vibration and buckling limits as constraints. The final optimization results show that the blade with improved structural configuration can reach a further mass saving of 3% compared with the optimized conventional structure design, indicating that the proposed approach is effective and reliable.
Predicting inpatient pharmacy order interventions using provider action data
Authors: Balestra Martina , Chen Ji , Iturrate Eduardo , Aphinyanaphongs Yindalon , Nov Oded 
Published: October 2021

Abstract

Objective
The widespread deployment of electronic health records (EHRs) has introduced new sources of error and inefficiencies to the process of ordering medications in the hospital setting. Existing work identifies orders that require pharmacy intervention by comparing them to a patient’s medical records. In this work, we develop a machine learning model for identifying medication orders requiring intervention using only provider behavior and other contextual features that may reflect these new sources of inefficiencies.

Materials and Methods
Data on providers’ actions in the EHR system and pharmacy orders were collected over a 2-week period in a major metropolitan hospital system. A classification model was then built to identify orders requiring pharmacist intervention. We tune the model to the context in which it would be deployed and evaluate global and local feature importance.

Results
The resultant model had an area under the receiver-operator characteristic curve of 0.91 and an area under the precision-recall curve of 0.44.

Conclusions
Providers’ actions can serve as useful predictors in identifying medication orders that require pharmacy intervention. Careful model tuning for the clinical context in which the model is deployed can help to create an effective tool for improving health outcomes without using sensitive patient data.
Effect of Host Volatile Release Rate and Racemic Fuscumol on Trap Catch of Hylurgus ligniperda, Hylastes ater (Coleoptera: Curculionidae), and Arhopalus ferus (Coleoptera: Cerambycidae)
Authors: Kerr Jessica L , Dickson Georgia , O’Connor Brooke C , Somchit Chanatda , Sweeney Jon , Pawson Stephen M 
Published: October 2021

Abstract
Early detection of bark- and wood-boring beetles is critical to support the eradication of recently established populations in novel regions. Flight intercept traps baited with semiochemical lures are essential for surveillance and population monitoring of introduced insects. We present laboratory and field data to test potential improvements in trap sensitivity to detect Hylastes ater (Paykull), Hylurgus ligniperda (Fabricius) (Coleoptera:Scolytinae), and Arhopalus ferus (Mulsant) (Coleoptera:Cerambycidae). We evaluated the effects of type and permeability of plastic material on release rates of host-plant volatiles and the addition of the pheromone racemic E-fuscumol on beetle species catch within an exotic Pinus radiata (D. Don) plantation forest. We trapped 228,278 H. ligniperda, 91 H. ater, and 2,504 A. ferus over two experiments. Our results show strong attraction of H. ligniperda to host-plant volatiles with a positive relationship between increased release rates and trap catch. H. ater follows this trend, with attraction to ethanol and (−)-β-pinene. H. ligniperda was more strongly attracted to host volatiles than H. ater, the average ratio between baited and unbaited traps being 51.25:1 and 3.75:1, respectively for each species. There was no effect of host-plant volatiles or release rate on A. ferus catch, but a weak attraction by A. ferus to racemic E-fuscumol. Overall, we demonstrate species-specific differences in Coleoptera attraction to host-plant volatile release rates and semiochemical blends. Results demonstrate mechanisms to improve trap catch of H. ligniperda and H. ater. Racemic E-fuscumol shows some promise for A. ferus, but further investigation is required to determine whether chirality affects attraction.
Cyber Operations against Civilian Data
Authors: McKenzie Simon 
Published: October 2021

Abstract
Cyber operations are becoming an increasing part of armed conflict. This article assesses whether cyber operations against data during an armed conflict could amount to a war crime in the Statute of the International Criminal Court. It unpacks the plausibility of computer data being included in the categories of ‘object’ and ‘property’ in the Statute, showing there is no doctrinal and jurisprudential unanimity in either case. However, the Court can and should take a wide view of when tangible objects are affected in a legally relevant way by attacks on or through data. Considering this question forces us to reflect about the proper interpretation of the Statute in light of the principle of legality, and about whether and how the Statute will be able to ‘keep up’ with new forms of warfare.