bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of Novel N-Acylhydrazones and Their C-N/N-N Bond Conformational Characterization by NMR Spectroscopy
Authors: Munir Rubina , Javid Noman , Zia-ur-Rehman Muhammad , Zaheer Muhammad , Huma Rahila , Roohi Ayesha , Athar Muhammad Makshoof
Published: August 2021

In this article, a synthesis of N’-(benzylidene)-2-(6-methyl-1H-pyrazolo[3,4-b]quinolin-1-yl)acetohydrazides and their structural interpretation by NMR experiments is described in an attempt to explain the duplication of some peaks in their 1H- and 13C-NMR spectra. Twenty new 6-methyl-1H-pyrazolo[3,4-b]quinoline substituted N-acylhydrazones 6(a–t) were synthesized from 2-chloro-6-methylquinoline-3-carbaldehyde (1) in four steps. 2-Chloro-6-methylquinoline-3-carbaldehyde (1) afforded 6-methyl-1H-pyrazolo[3,4-b]quinoline (2), which upon N-alkylation yielded 2-(6-methyl-1H-pyrazolo[3,4-b]quinolin-1-yl)acetate (3). The hydrazinolysis of 3 followed by the condensation of resulting 2-(6-methyl-1H-pyrazolo[3,4-b]quinolin-1-yl)acetohydrazide (4) with aromatic aldehydes gave N-acylhydrazones 6(a–t). Structures of the synthesized compounds were established by readily available techniques such as FT-IR, NMR and mass spectral studies. The stereochemical behavior of 6(a–t) was studied in dimethyl sulfoxide-d6 solvent by means of 1H NMR and 13C NMR techniques at room temperature. NMR spectra revealed the presence of N’-(benzylidene)-2-(6-methyl-1H-pyrazolo[3,4-b]quinolin-1-yl)acetohydrazides as a mixture of two conformers, i.e., E(C=N)(N-N) synperiplanar and E(C=N)(N-N)antiperiplanar at room temperature in DMSO-d6. The ratio of both conformers was also calculated and E(C=N) (N-N) syn-periplanar conformer was established to be in higher percentage in equilibrium with the E(C=N) (N-N)anti-periplanar form.
Performance and Mechanism of Alkylimidazolium Ionic Liquids as Corrosion Inhibitors for Copper in Sulfuric Acid Solution
Authors: Tian Guocai , Yuan Kaitao
Published: August 2021

The addition of corrosion inhibitors is an economic and environmental protection method to prevent the corrosion of copper. The adsorption, performance, and mechanism of three 1-alkyl-3-methylimidazolium hydrogen sulfate ([BMIM]HSO4, [HMIM]HSO4, and [OMIM]HSO4) ionic liquids (ILs) on the copper surface in 0.5 M H2SO4 solutions were studied by quantum chemical calculation, quantitative structure-activity relationship (QSAR), and molecular dynamics simulation. It is found that the main reactive site is located on the imidazolium ring (especially the C2, N4, and N7 groups). When the alkyl chain of the imidazolium ring is increasing, the molecular reactivity of the ILs and the interaction between the ILs inhibitor and copper surface are enhanced. The imidazole ring of the ILs tends to be adsorbed on Cu (111) surface in parallel through physical adsorption. The order of adsorption energy is [Bmim]HSO4 < [Hmim]HSO4 < [OMIM]HSO4, which is in agreement with the experimental order of corrosion efficiency. On the imidazole ring, the interaction between the copper surface and the C atom is greater than that between the copper surface and the N atom. It is found that ILs addition can hinder the diffusion of corrosion particles, reduce the number density of corrosion particles and slow down the corrosion rate. The order of inhibition ability of three ILs is [Bmim]HSO4 < [Hmim]HSO4 < [OMIM]HSO4,which agree well with experimental results. A reliable QSAR correlation between the inhibition corrosion efficiency and molecular reactivity parameters of the ILs was established.
Interpretation of Ligand-Based Activity Cliff Prediction Models Using the Matched Molecular Pair Kernel
Authors: Tamura Shunsuke , Jasial Swarit , Miyao Tomoyuki , Funatsu Kimito
Published: August 2021

Activity cliffs (ACs) are formed by two structurally similar compounds with a large difference in potency. Accurate AC prediction is expected to help researchers’ decisions in the early stages of drug discovery. Previously, predictive models based on matched molecular pair (MMP) cliffs have been proposed. However, the proposed methods face a challenge of interpretability due to the black-box character of the predictive models. In this study, we developed interpretable MMP fingerprints and modified a model-specific interpretation approach for models based on a support vector machine (SVM) and MMP kernel. We compared important features highlighted by this SVM-based interpretation approach and the SHapley Additive exPlanations (SHAP) as a major model-independent approach. The model-specific approach could capture the difference between AC and non-AC, while SHAP assigned high weights to the features not present in the test instances. For specific MMPs, the feature weights mapped by the SVM-based interpretation method were in agreement with the previously confirmed binding knowledge from X-ray co-crystal structures, indicating that this method is able to interpret the AC prediction model in a chemically intuitive manner.
Particulate Mycobacterial Vaccines Induce Protective Immunity against Tuberculosis in Mice
Authors: Chen Shuxiong , Quan Diana H. , Wang Xiaonan T. , Sandford Sarah , Kirman Joanna R. , Britton Warwick J. , Rehm Bernd H. A.
Published: August 2021

Currently available vaccines fail to provide consistent protection against tuberculosis (TB). New, improved vaccines are urgently needed for controlling the disease. The mycobacterial antigen fusions H4 (Ag85B-TB10.4) and H28 (Ag85B-TB10.4-Rv2660c) have been shown to be very immunogenic and have been considered as potential candidates for TB vaccine development. However, soluble protein vaccines are often poorly immunogenic, but augmented immune responses can be induced when selected antigens are delivered in particulate form. This study investigated whether the mycobacterial antigen fusions H4 and H28 can induce protective immunity when assembled into particulate vaccines (polyester nanoparticle-H4, polyester nanoparticle-H28, H4 nanoparticles and H28 nanoparticles). The particulate mycobacterial vaccines were assembled inside an engineered endotoxin-free production strain of Escherichia coli at high yield. Vaccine nanoparticles were purified and induced long-lasting antigen-specific T cell responses and protective immunity in mice challenged by aerosol with virulent Mycobacterium tuberculosis. A significant reduction of M. tuberculosis CFU, up to 0.7-log10 protection, occurred in the lungs of mice immunized with particulate vaccines in comparison to placebo-vaccinated mice (p < 0.0001). Polyester nanoparticles displaying the mycobacterial antigen fusion H4 induced a similar level of protective immunity in the lung when compared to M. bovis bacillus Calmette-Guérin (BCG), the currently approved TB vaccine. The safe and immunogenic polyester nanoparticle-H4 vaccine is a promising subunit vaccine candidate, as it can be cost-effectively manufactured and efficiently induces protection against TB.
Alcohol and the Risk of Injury
Authors: Chikritzhs Tanya , Livingston Michael
Published: August 2021

Globally, almost four and a half million people died from injury in 2019. Alcohol’s contribution to injury-related premature loss of life, disability and ill-health is pervasive, touching individuals, families and societies throughout the world. We conducted a review of research evidence for alcohol’s causal role in injury by focusing on previously published systematic reviews, meta-analyses and where indicated, key studies. The review summarises evidence for pharmacological and physiological effects that support postulated causal pathways, highlights findings and knowledge gaps relevant to specific forms of injury (i.e., violence, suicide and self-harm, road injury, falls, burns, workplace injuries) and lays out options for evidence-based prevention.
Development of a Framework and the Content for a Psychoeducational Internet-Delivered Intervention for Women after Treatment for Gynecological Cancer
Authors: Sekse Ragnhild Johanne Tveit , Nordgreen Tine , Flobak Eivind , Lystrup Morten , Braathen Espen , Werner Henrica M. J.
Published: August 2021

The number of women treated for gynecological cancer is increasing. At the same time, the duration of in-patient hospitalization has decreased, and follow-up with its primary focus on early recognition of recurrence does not meet all patients’ needs. One method of follow-up may be digital intervention. This study describes the development of a psychoeducational Internet-delivered intervention targeting women’s psychosocial needs during the follow-up period after treatment for gynecological cancer. The project consisted of three phases following the UK Medical Research Council Framework guidelines for the development of complex interventions. Phase one identified the evidence in the field, phase two identified the relevant theoretical framework, and phase three included a two-year work process including focus group interviews and think aloud interviews with users. Through the steps of literature review, theoretical framework, and an iterative development process with users and other stakeholders, a six-week program was developed. The program included psychoeducational information, multimedia, exercises, and weekly telephone follow-up with a dedicated nurse. This Internet-delivered intervention can be a novel method for addressing the gap in the provision of follow-up for women after treatment for gynecological cancer.
Cystic Fibrosis Clinical Isolates of Aspergillus fumigatus Induce Similar Muco-inflammatory Responses in Primary Airway Epithelial Cells
Authors: McLean Samantha A. , Cullen Leilani , Gardam Dianne J. , Schofield Craig J. , Laucirica Daniel R. , Sutanto Erika N. , Ling Kak-Ming , Stick Stephen M. , Peacock Christopher S. , Kicic Anthony , Garratt Luke W. ,   on behalf of AREST CF,   WAERP
Published: August 2021

Aspergillus is increasingly associated with lung inflammation and mucus plugging in early cystic fibrosis (CF) disease during which conidia burden is low and strains appear to be highly diverse. It is unknown whether clinical Aspergillus strains vary in their capacity to induce epithelial inflammation and mucus production. We tested the hypothesis that individual colonising strains of Aspergillus fumigatus would induce different responses. Ten paediatric CF Aspergillus isolates were compared along with two systemically invasive clinical isolates and an ATCC reference strain. Isolates were first characterised by ITS gene sequencing and screened for antifungal susceptibility. Three clusters (A−C) of Aspergillus isolates were identified by ITS. Antifungal susceptibility was variable, particularly for itraconazole. Submerged CF and non-CF monolayers as well as differentiated primary airway epithelial cell cultures were incubated with conidia for 24 h to allow germination. None of the clinical isolates were found to significantly differ from one another in either IL-6 or IL-8 release or gene expression of secretory mucins. Clinical Aspergillus isolates appear to be largely homogenous in their mucostimulatory and immunostimulatory capacities and, therefore, only the antifungal resistance characteristics are likely to be clinically important.
Anti-Inflammatory Properties of Plasma from Children with Short Bowel Syndrome
Authors: Hajam Irshad Ahmed , Ali Farhana , Young Jocelyn , Garcia Mary Abigail , Cannavino Christopher , Ramchandar Nanda , Liu George Y.
Published: August 2021

Sepsis, resulting from a dysregulated host immune response to invading pathogens, is the leading cause of mortality in critically ill patients worldwide. Immunomodulatory treatment for sepsis is currently lacking. Children with short bowel syndrome (SBS) may present with less severe symptoms during gram-negative bacteremia. We, therefore, tested the hypothesis that plasma from children with SBS could confer protection against Escherichia coli sepsis. We showed that SBS plasma at 5% and 10% concentrations significantly (p < 0.05) inhibited the production of both TNF-α and IL-6 induced by either E. coli- or LPS-stimulated host cells when compared to plasma from healthy controls. Furthermore, mice treated intravenously with select plasma samples from SBS or healthy subjects had reduced proinflammatory cytokine levels in plasma and a significant survival advantage after E. coli infection. However, SBS plasma was not more protective than the plasma of healthy subjects, suggesting that children with SBS have other immunomodulatory mechanisms, in addition to neutralizing antibodies, to alleviate their symptoms during gram-negative sepsis.
High Mortality and Graft Loss after Infective Endocarditis in Kidney Transplant Recipients: A Case-Controlled Study from Two Centers
Authors: Tamzali Yanis , Danthu Clément , Aubry Alexandra , Brousse Romain , Faucher Jean-François , El Ouafi Zhour , Rufat Pierre , Essig Marie , Barrou Benoit , Toure Fatouma , Tourret Jérôme
Published: August 2021

Kidney transplant recipients (KTRs) tend to develop infections with characteristic epidemiology, presentation, and outcome. While infective endocarditis (IE) is among such complications in KTRs, the literature is scarce. We describe the presentation, epidemiology, and factors associated with IE in KTRs. We performed a retrospective case/control study which included patients from two centers. First episodes of definite or possible IE (Duke criteria) in adult KTRs from January 2010 to December 2018 were included, as well as two controls per case, and followed until 31 December 2019. Clinical, biological, and microbiological data and the outcome were collected. Survival was studied using the Kaplan–Meier method. Finally, we searched for factors associated with the onset of IE in KTRs by the comparison of cases and controls. Seventeen cases and 34 controls were included. IE was diagnosed after a mean delay of 78 months after KT, mostly on native valves of the left heart only. Pathogens of digestive origin were most frequently involved (six Enterococcus spp, three Streptococcus gallolyticus, and one Escherichia coli), followed by Staphylococci (three cases of S. aureus and S. epidermidis each). Among the risk factors evaluated, age, vascular nephropathy, and elevated calcineurin inhibitor through levels were significantly associated with the occurrence of IE in our study. Patient and death-censored graft survival were greatly diminished five years after IE, compared to controls being 50.3% vs. 80.6% (p < 0.003) and 29.7% vs. 87.5% (p < 0.002), respectively. IE in KTRs is a disease that carries significant risks both for the survival of the patient and the transplant.
Simple and Fast DNA Based Sensor System for Screening of Small-Molecule Compounds Targeting Eukaryotic Topoisomerase 1
Authors: Petersen Kamilla Vandsø , Selas Asier , Hymøller Kirstine Mejlstrup , Mizielinski Karol , Thorsager Maria , Stougaard Magnus , Alonso Concepcion , Palacios Francisco , Pérez-Pertejo Yolanda , Reguera Rosa M. , Balaña-Fouce Rafael , Knudsen Birgitta R. , Tesauro Cinzia
Published: August 2021

Background: Eukaryotic topoisomerase 1 is a potential target of anti-parasitic and anti-cancer drugs. Parasites require topoisomerase 1 activity for survival and, consequently, compounds that inhibit topoisomerase 1 activity may be of interest. All effective topoisomerase 1 drugs with anti-cancer activity act by inhibiting the ligation reaction of the enzyme. Screening for topoisomerase 1 targeting drugs, therefore, should involve the possibility of dissecting which step of topoisomerase 1 activity is affected. Methods: Here we present a novel DNA-based assay that allows for screening of the effect of small-molecule compounds targeting the binding/cleavage or the ligation steps of topoisomerase 1 catalysis. This novel assay is based on the detection of a rolling circle amplification product generated from a DNA circle resulting from topoisomerase 1 activity. Results: We show that the binding/cleavage and ligation reactions of topoisomerase 1 can be investigated separately in the presented assay termed REEAD (C|L) and demonstrate that the assay can be used to investigate, which of the individual steps of topoisomerase 1 catalysis are affected by small-molecule compounds. The assay is gel-free and the results can be detected by a simple colorimetric readout method using silver-on-gold precipitation rendering large equipment unnecessary. Conclusion: REEAD (C|L) allows for easy and quantitative investigations of topoisomerase 1 targeting compounds and can be performed in non-specialized laboratories.
Hypouricemic Effects of Chrysanthemum indicum L. and Cornus officinalis on Hyperuricemia-Induced HepG2 Cells, Renal Cells, and Mice
Authors: Kim Ok-Kyung , Yun Jeong-Moon , Lee Minhee , Kim Dakyung , Lee Jeongmin
Published: August 2021

Hyperuricemia, abnormally excess accumulation of uric acid, is caused by an imbalance between the production and excretion of uric acid and is a major cause of gout. We compared the effects of extracts from Chrysanthemum indicum L. (Ci) and Cornus officinalis Siebold and Zucc. (Co) on hyperuricemia, both individually and in combination (FSU-CC), using hypoxanthine-treated human liver cancer (HepG2) cells, primary mouse renal proximal tubule cells, and potassium oxonate induced hyperuricemic mice. The Ci contained 7.62 mg/g luteolin and 0 mg/g loganin, Co contained 0 mg/g luteolin and 4.90 mg/g loganin, and FSH-CC contained 3.95 mg/g luteolin and 2.48 mg/g loganin. We found that treatment with Ci, Co, and FSU-CC suppressed the activity of xanthine oxidase and mRNA expression of xanthine dehydrogenase while inducing an increase in the expression levels of the organic anion transporter 1 (OAT1) and organic anion transporter 3 (OAT3) proteins and a decrease in the expression levels of glucose transporter 9 (GLUT9) and urate transporter 1 (URAT1) proteins. Particularly, treatment and supplementation with FSU-CC showed stronger effects than those of supplementation with either Ci or Co alone. We observed that the excretion of creatinine and uric acid in the combination of Ci and Co was higher than that observed in their individual supplementations and was similar to that of the normal group. Therefore, our data suggest that a combination of Ci and Co may potentially be used for the development of effective natural anti-hyperuricemic functional foods.
Coating of ZnO Nanoparticle on Cotton Fabric to Create a Functional Textile with Enhanced Mechanical Properties
Authors: Tania Imana Shahrin , Ali Mohammad
Published: August 2021

The goal of this research is to develop a functional textile with better mechanical properties. Therefore, nano ZnO is synthesized, characterized, and applied to cotton fabric by mechanical thermo-fixation techniques. The synthesized nanoparticles are characterized by SEM and XRD analysis. The ZnO nanoparticle alone, ZnO nanoparticle with a binder, and ZnO with a binder and wax emulsion are then applied on cotton woven fabrics using three different recipes. The surface morphology of the treated fabric is studied using SEM and EDS. Antimicrobial activity, UV protection property, and crease resistance are all tested for their functional characteristics. In addition, all vital mechanical characteristics are assessed. The results suggest that using only nano ZnO or nano ZnO with a binder enhances functional features while deteriorating mechanical capabilities. Nano ZnO treatment with the third recipe, which includes the addition of an emulsion, on the other hand, significantly enhances mechanical and functional characteristics. Consequently, this study provides information to optimize the confidence of textile researchers and producers in using nano ZnO and understanding its features in key functional fabrics.
Optimization of Critical Parameters for Carbodiimide Mediated Production of Highly Modified Chitosan
Authors: Christ Henrik-Alexander , Bourgat Yannick , Menzel Henning
Published: August 2021

An optimization of the 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide and hydroxy benzotriazole mediated conjugation of the polysaccharide chitosan with functional carboxylic acids was shown. Optimal parameters that enable resource-efficient synthesis of highly functionalized chitosan were identified. In particular, use of only catalytic instead of stoichiometric amounts of hydroxy benzotriazole and tight control of pH in reaction mixture resulted in highly efficient incorporation of the desired moieties as side chains in chitosan. As a result, the model reactant 4-azidobenzoic acid was incorporated resulting in a degree of substitution of over 30% with very high coupling efficacy of up to 90%. Similar results were obtained with other carboxylic acids such as methacrylic acid, 3-(2-furyl) propionic acid and 3-maleimido propionic acid, highlighting the broad applicability of our findings for the functionalization of chitosan.
Fluoropolymer/Glycidyl Azide Polymer (GAP) Block Copolyurethane as New Energetic Binders: Synthesis, Mechanical Properties, and Thermal Performance
Authors: Xu Minghui , Lu Xianming , Liu Ning , Zhang Qian , Mo Hongchang , Ge Zhongxue
Published: August 2021

In order to enhance the application performance of glycidyl azide polymer (GAP) in solid propellant, an energetic copolyurethane binder, (poly[3,3-bis(2,2,2-trifluoro-ethoxymethyl)oxetane] glycol-block-glycidylazide polymer (PBFMO-b-GAP) was synthesized using poly[3,3-bis(2,2,2-trifluoro-ethoxymethyl)oxetane] glycol (PBFMO), which was prepared from cationic polymerization with GAP as the raw material and toluene diisocyanate (TDI) as the coupling agent via a prepolymer process. The molecular structure of copolyurethanes was confirmed by attenuated total reflectance-Fourier transform-infrared spectroscopy (ATR–FTIR), nuclear magnetic resonance spectrometry (NMR), and gel permeation chromatography (GPC). The impact sensitivity, mechanical performance, and thermal behavior of PBFMO-b-GAP were studied by drop weight test, X-ray photoelectron spectroscopic (XPS), tensile test, scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and thermal gravimetric analysis (TGA), respectively. The results demonstrated that the introduction of fluoropolymers could evidently reduce the sensitivity of GAP-based polyurethane and enhance its mechanical behavior (the tensile strength up to 5.75 MPa with a breaking elongation of 1660%). Besides, PBFMO-b-GAP exhibited excellent resistance to thermal decomposition up to 200 °C and good compatibility with Al and cyclotetramethylene tetranitramine (HMX). The thermal performance of the PBFMO-b-GAP/Al complex was investigated by a cook-off test, and the results indicated that the complex has specific reaction energy. Therefore, PBFMO-b-GAP may serve as a promising energetic binder for future propellant formulations.
Comparative Transcriptome Analysis of Bombyx mori (Lepidoptera) Larval Hemolymph in Response to Autographa californica Nucleopolyhedrovirus in Differentially Resistant Strains
Authors: Ding Xin-yi , Wang Xue-yang , Kong Yun-hui , Zhao Chun-xiao , Qin Sheng , Sun Xia , Li Mu-wang
Published: August 2021

Bombyx mori nucleopolyhedrovirus (BmNPV) is a kind of pathogen that causes huge economic losses to silkworm production. Although Autographa californica nucleopolyhedrovirus (AcMNPV) and BmNPV are both baculoviruses, the host domains of these two viruses have almost no intersection in nature. Recently, it has been found that some silkworms could be infected by recombinant AcMNPV through a puncture, which provided valuable material for studying the infection mechanism of baculovirus to silkworm. In this study, comparative transcriptomics was used to analyse the hemolymph of two differentially resistant strains following AcMNPV inoculation. There were 678 DEGs in p50 and 515 DEGs in C108 following viral infection. Among them, the upregulation and downregulation of DEGs were similar in p50; however, the upregulated DEGs were nearly twice as numerous as the downregulated DEGs in C108. The DEGs in different resistant strains differed by GO enrichment. Based on KEGG enrichment, DEGs were mainly enriched in metabolic pathways in p50 and the apoptosis pathway in C108. Moreover, 13 genes involved in metabolic pathways and 11 genes involved in the apoptosis pathway were analysed. Among the DEGs involved in apoptosis, the function of BmTex261 in viral infection was analysed. The BmTex261 showed the highest expression in hemolymph and a significant response to viral infection in the hemolymph of C108, indicating that it is involved in anti-AcMNPV infection. This was further validated by the significantly decreased expression of viral gene lef3 after overexpression of BmTex261 in BmN cells. The results provide a theoretical reference for the molecular mechanism of resistance to BmNPV in silkworms.
Research on Influence of Exhaust Characteristics and Control Strategy to DOC-Assisted Active Regeneration of DPF
Authors: Liu Guanlin , Liu Weiqiang , He Yibin , Gong Jinke , Li Qiong
Published: August 2021

For the purpose of designing a reasonable control strategy for DOC-assisted DPF regeneration, a mathematical model that describes the thermal phenomenon both in a diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) during regeneration is developed. All boundary conditions of this model are obtained by experiments. The effects of the main exhaust parameters such as exhaust mass flow rate, exhaust temperature, oxygen concentration and emission of reactants are investigated comprehensively. The effects of two main parameters of control strategy, DOC-out temperature and soot loading, are analyzed as well. To quantify the effects of relevant parameters, the fuzzy grey relational analysis method is utilized to evaluate the correlation coefficient of all factors to key indexes of DPF regeneration such as maximum temperature, maximum rate of temperature increase and regeneration duration. The results of this work will greatly reduce the complexity of analysis and enable more rational control strategy design of DOC–DPF regeneration systems.
A Comprehensive Study of Geochemical Data Storage Performance Based on Different Management Methods
Authors: Cheng Yinyi , Zhou Kefa , Wang Jinlin , Maeyer Philippe De , Voorde Tim Van de , Yan Jining , Cui Shichao
Published: August 2021

The spatial calculation of vector data is crucial for geochemical analysis in geological big data. However, large volumes of geochemical data make for inefficient management. Therefore, this study proposed a shapefile storage method based on MongoDB in GeoJSON form (SSMG) and a shapefile storage method based on PostgreSQL with open location code (OLC) geocoding (SSPOG) to solve the problem of low efficiency of electronic form management. The SSMG method consists of a JSONification tier and a cloud storage tier, while the SSPOG method consists of a geocoding tier, an extension tier, and a storage tier. Using MongoDB and PostgreSQL as databases, this study achieved two different types of high-throughput and high-efficiency methods for geochemical data storage and retrieval. Xinjiang, the largest province in China, was selected as the study area in which to test the proposed methods. Using geochemical data from shapefile as a data source, several experiments were performed to improve geochemical data storage efficiency and achieve efficient retrieval. The SSMG and SSPOG methods can be applied to improve geochemical data storage using different architectures, so as to achieve management of geochemical data organization in an efficient way, through time consumed and data compression ratio (DCR), in order to better support geological big data. The purpose of this study was to find ways to build a storage method that can improve the speed of geochemical data insertion and retrieval by using excellent big data technology to help us efficiently solve problem of geochemical data preprocessing and provide support for geochemical analysis.
Artificial Intelligence Revolutionises Weather Forecast, Climate Monitoring and Decadal Prediction
Authors: Dewitte Steven , Cornelis Jan P. , Müller Richard , Munteanu Adrian
Published: August 2021

Artificial Intelligence (AI) is an explosively growing field of computer technology, which is expected to transform many aspects of our society in a profound way. AI techniques are used to analyse large amounts of unstructured and heterogeneous data and discover and exploit complex and intricate relations among these data, without recourse to an explicit analytical treatment of those relations. These AI techniques are unavoidable to make sense of the rapidly increasing data deluge and to respond to the challenging new demands in Weather Forecast (WF), Climate Monitoring (CM) and Decadal Prediction (DP). The use of AI techniques can lead simultaneously to: (1) a reduction of human development effort, (2) a more efficient use of computing resources and (3) an increased forecast quality. To realise this potential, a new generation of scientists combining atmospheric science domain knowledge and state-of-the-art AI skills needs to be trained. AI should become a cornerstone of future weather and climate observation and modelling systems.
Investigation of Thundercloud Features in Different Regions
Authors: Sin’kevich Andrei , Boe Bruce , Pawar Sunil , Yang Jing , Abshaev Ali , Dovgaluk Yulia , Gekkieva Julduz , Gopalakrishnan Venkatachalam , Kurov Alexander , Mikhailovskii Yurii , Toropova Marina , Veremei Nikolai
Published: August 2021

A comparison of thundercloud characteristics in different regions of the world was conducted. The clouds studied developed in India, China and in two regions of Russia. Several field projects were discussed. Cloud characteristics were measured by weather radars, the SEVERI instrument installed on board of the Meteosat satellite, and lightning detection systems. The statistical characteristics of the clouds were tabulated from radar scans and correlated with lightning observations. Thunderclouds in India differ significantly from those observed in other regions. The relationships among lightning strike frequency, supercooled cloud volume, and precipitation intensity were analyzed. In most cases, high correlation was observed between lightning strike frequency and supercooled volume.
Multi-Modal Residual Perceptron Network for Audio–Video Emotion Recognition
Authors: Chang Xin , Skarbek Władysław
Published: August 2021

Emotion recognition is an important research field for human–computer interaction. Audio–video emotion recognition is now attacked with deep neural network modeling tools. In published papers, as a rule, the authors show only cases of the superiority in multi-modality over audio-only or video-only modality. However, there are cases of superiority in uni-modality that can be found. In our research, we hypothesize that for fuzzy categories of emotional events, the within-modal and inter-modal noisy information represented indirectly in the parameters of the modeling neural network impedes better performance in the existing late fusion and end-to-end multi-modal network training strategies. To take advantage of and overcome the deficiencies in both solutions, we define a multi-modal residual perceptron network which performs end-to-end learning from multi-modal network branches, generalizing better multi-modal feature representation. For the proposed multi-modal residual perceptron network and the novel time augmentation for streaming digital movies, the state-of-the-art average recognition rate was improved to 91.4% for the Ryerson Audio–Visual Database of Emotional Speech and Song dataset and to 83.15% for the Crowd-Sourced Emotional Multi Modal Actors dataset. Moreover, the multi-modal residual perceptron network concept shows its potential for multi-modal applications dealing with signal sources not only of optical and acoustical types.
Deep Convolutional Neural Network Regularization for Alcoholism Detection Using EEG Signals
Authors: Mukhtar Hamid , Qaisar Saeed Mian , Zaguia Atef
Published: August 2021

Alcoholism is attributed to regular or excessive drinking of alcohol and leads to the disturbance of the neuronal system in the human brain. This results in certain malfunctioning of neurons that can be detected by an electroencephalogram (EEG) using several electrodes on a human skull at appropriate positions. It is of great interest to be able to classify an EEG activity as that of a normal person or an alcoholic person using data from the minimum possible electrodes (or channels). Due to the complex nature of EEG signals, accurate classification of alcoholism using only a small dataset is a challenging task. Artificial neural networks, specifically convolutional neural networks (CNNs), provide efficient and accurate results in various pattern-based classification problems. In this work, we apply CNN on raw EEG data and demonstrate how we achieved 98% average accuracy by optimizing a baseline CNN model and outperforming its results in a range of performance evaluation metrics on the University of California at Irvine Machine Learning (UCI-ML) EEG dataset. This article explains the stepwise improvement of the baseline model using the dropout, batch normalization, and kernel regularization techniques and provides a comparison of the two models that can be beneficial for aspiring practitioners who aim to develop similar classification models in CNN. A performance comparison is also provided with other approaches using the same dataset.
Fast and Accurate Object Detection in Remote Sensing Images Based on Lightweight Deep Neural Network
Authors: Lang Lei , Xu Ke , Zhang Qian , Wang Dong
Published: August 2021

Deep learning-based object detection in remote sensing images is an important yet challenging task due to a series of difficulties, such as complex geometry scene, dense target quantity, and large variant in object distributions and scales. Moreover, algorithm designers also have to make a trade-off between model’s complexity and accuracy to meet the real-world deployment requirements. To deal with these challenges, we proposed a lightweight YOLO-like object detector with the ability to detect objects in remote sensing images with high speed and high accuracy. The detector is constructed with efficient channel attention layers to improve the channel information sensitivity. Differential evolution was also developed to automatically find the optimal anchor configurations to address issue of large variant in object scales. Comprehensive experiment results show that the proposed network outperforms state-of-the-art lightweight models by 5.13% and 3.58% in accuracy on the RSOD and DIOR dataset, respectively. The deployed model on an NVIDIA Jetson Xavier NX embedded board can achieve a detection speed of 58 FPS with less than 10W power consumption, which makes the proposed detector very suitable for low-cost low-power remote sensing application scenarios.
An Ensembled Anomaly Detector for Wafer Fault Detection
Authors: Furnari Giuseppe , Vattiato Francesco , Allegra Dario , Milotta Filippo Luigi Maria , Orofino Alessandro , Rizzo Rosetta , De Palo Rosaria Angela , Stanco Filippo
Published: August 2021

The production process of a wafer in the semiconductor industry consists of several phases such as a diffusion and associated defectivity test, parametric test, electrical wafer sort test, assembly and associated defectivity tests, final test, and burn-in. Among these, the fault detection phase is critical to maintain the low number and the impact of anomalies that eventually result in a yield loss. The understanding and discovery of the causes of yield detractors is a complex procedure of root-cause analysis. Many parameters are tracked for fault detection, including pressure, voltage, power, or valve status. In the majority of the cases, a fault is due to a combination of two or more parameters, whose values apparently stay within the designed and checked control limits. In this work, we propose an ensembled anomaly detector which combines together univariate and multivariate analyses of the fault detection tracked parameters. The ensemble is based on three proposed and compared balancing strategies. The experimental phase is conducted on two real datasets that have been gathered in the semiconductor industry and made publicly available. The experimental validation, also conducted to compare our proposal with other traditional anomaly detection techniques, is promising in detecting anomalies retaining high recall with a low number of false alarms.
Opportunistic DF-AF Selection Relaying in Hybrid Wireless and Power Line Communication for Indoor IoT Networks
Authors: Van Hoang Thien , Van Quyet-Nguyen , Le Danh Hong , Van Hoang-Phuong , Jalowiczor Jakub , Nguyen Hoang-Sy , Voznak Miroslav
Published: August 2021

This manuscript investigates the system performance of hybrid wireless and power line communication networks for indoor Internet of Things applications. Differentiating itself from the existing literature, the performance of the direct link and dual-hop energy harvesting relay-aided links is analyzed under the condition of indoor fading modeled by log-normal distribution. Moreover, the manuscript presents the analytical expressions of the successful transmission probability of the deployed opportunistic decode-and-forward and amplify-and-forward relay selection scheme, and validates them with Monte Carlo simulations. Moreover, the impact of different system parameters on the successful transmission probability is revealed. For the considered hybrid system, in general, the opportunistic decode-and-forward relaying scheme outperforms the opportunistic amplify-and-forward relaying scheme. As importantly, increasing the source to relay distance and power splitting ratio over certain limits significantly deteriorates the system performance, indicated by the decrease in the successful transmission probability.
Assessment of a Modified Sandwich Estimator for Generalized Estimating Equations with Application to Opioid Poisoning in MIMIC-IV ICU Patients
Authors: Rogers Paul , Stoner Julie
Published: August 2021

Longitudinal data is encountered frequently in many healthcare research areas to include the critical care environment. Repeated measures from the same subject are expected to correlate with each other. Models with binary outcomes are commonly used in this setting. Regression models for correlated binary outcomes are frequently fit using generalized estimating equations (GEE). The Liang and Zeger sandwich estimator is often used in GEE to produce unbiased standard error estimation for regression coefficients in large sample settings, even when the covariance structure is misspecified. The sandwich estimator performs optimally in balanced designs when the number of participants is large with few repeated measurements. The sandwich estimator’s asymptotic properties do not hold in small sample and rare-event settings. Under these conditions, the sandwich estimator underestimates the variances and is biased downwards. Here, the performance of a modified sandwich estimator is compared to the traditional Liang-Zeger estimator and alternative forms proposed by authors Morel, Pan, and Mancl-DeRouen. Each estimator’s performance was assessed with 95% coverage probabilities for the regression coefficients using simulated data under various combinations of sample sizes and outcome prevalence values with independence and autoregressive correlation structures. This research was motivated by investigations involving rare-event outcomes in intensive care unit settings.
Preliminary Evaluation of Heavy Metal Contamination and Source Identification in Kuala Lumpur SMART Stormwater Pond Sediments Using Pb Isotopic Signature
Authors: Alrabie Nabeel Abdullah , Mohamat-Yusuff Ferdaus , Rohasliney Hashim , Zulkeflee Zufarzaana , Amal Mohammad Noor Azmai , Arshad Aziz , Zulkifli Syaizwan Zahmir , Wijaya Anugrah Ricky , Masood Najat , Sani Muhamad Shirwan Abdullah
Published: August 2021

Uncontrolled urbanization and growing industrialization are major sources of pollutants that affect the urban stormwater quality and, therefore, the receiving aquatic environment. The concentrations of heavy metals (As, Cd, Cr, Cu, Fe, Ni, Pb, and Zn), and Pb isotope ratios in surface sediment samples obtained from SMART holding and storage ponds located in Kuala Lumpur were investigated using inductively coupled plasma-mass spectrometry (ICP-MS). The highest metal concentrations were found at the SMART holding pond (SHP), the first recipient of urban stormwater runoff from the SMART system catchment area. As, Cd, Pb, and Zn are the dominant metal contaminants in the sediments of both SMART ponds, with values exceeding the average shale values. According to contamination indices applied to evaluate the environmental risk caused by heavy metals, As had the highest values among the metals examined, denoting moderate contamination. Hence, it can frequently cause harmful effects on the sediment-living species. The Pb isotope ratios (206Pb/207Pb and 208Pb/207Pb) indicated that coal combustion was the foremost source of anthropogenic Pb in the sediments of both SMART ponds. The control of coal combustion and sites undergoing intensive human activities should be given priority in the foreseeable future.
Household Vulnerability to Food Insecurity and the Regional Food Insecurity Gap in Kenya
Authors: Korir Lilian , Rizov Marian , Ruto Eric , Walsh Patrick Paul
Published: August 2021

Food insecurity remains a vital concern in Kenya. Vulnerable members of the population, such as children, the elderly, marginalised ethnic minorities, and low-income households, are disproportionately affected by food insecurity. Following the pioneering work of Sen, which examined exposure to food insecurity at a household level using his “entitlement approach”, this paper estimates households’ vulnerability to food insecurity. In turn, the outcome variable is decomposed in order to explain the food insecurity gap between households classified as “marginalised” and “non-marginalised”. We applied the Oaxaca-Blinder decomposition method to examine vulnerability to food insecurity and, in particular, contributions of observed differences in socio-demographic characteristics (endowments) or differences in the returns to these characteristics, which, in our context, is associated with poor public services and infrastructure in the vicinity of the household. The results indicated that differences in vulnerability to food insecurity were mainly attributable to observed differences in socio-demographic characteristics such as education, age, and household income. Therefore, policies seeking to attain equity by investment into targeted household characteristics in terms of access to food and other productive resources could effectively combat food insecurity. For example, policymakers could develop programs for household inclusiveness using education and social protection programs, including insurance schemes against risk of endowment loss.
Measuring Average Luminance for Road Lighting from Outside the Carriageway with Imaging Sensor
Authors: Rusu Alexandru Viorel , Galatanu Catalin Daniel , Livint Gheorghe , Lucache Dorin Dumitru
Published: August 2021

The main quality condition in street lighting is luminance distribution. During the carrying out of the literature, average luminance is the most important parameter to check. The standard BS EN 13201-3 imposes that average luminance must be calculated for the observer placed in the center of each circulating lane. As a consequence, according to these standards, the measurements can be done only on streets without traffic. Stopping the traffic on all lanes is very difficult. This paper proposes a solution for measuring the average luminance from outside the carriageway. The research was performed by simulations/calculations and was validated by field measurements. Imaging sensors were used to measure average luminance, while DIALux EVO 9.1 was used for the simulations. For symmetrical, opposite, and staggered lighting arrangements, average luminance measurements were performed with a digital camera positioned outside of the traffic area, with the equipment placed at the edge of the carriageway, giving similar results with standard measurements, with almost no difference. For single sided lighting arrangements, the differences became unacceptable. In this case, the paper proposes a correction function to calculate the average luminance for the observer placed on the carriageway, based on measurements with a digital camera placed outside the traffic area.
Innovation Performance Indicators for Architecture, Engineering and Construction Organization
Authors: Lo Jacqueline Tsz Yin , Kam Calvin
Published: August 2021

It is known that organizations can gain a competitive advantage only by managing effectively for today, while simultaneously creating innovation for tomorrow, and sustainability is one of the innovative strategies in major architecture, engineering, and construction (AEC) organizations. Innovation is vital to AEC organizations’ growth, yet most do not have a comprehensive measurement of innovation performance. Similar to the balanced scorecard approach, key indicators should be identified for the measuring of innovation performance to facilitate management. This article presents a study by using a triangulation approach that integrates systematic literature reviews and two-step consultations with experienced senior professionals to compile a set of key indicators for innovation performance measures for the AEC Industry.
The Whole and the Parts—A New Perspective on Production Diseases and Economic Sustainability in Dairy Farming
Authors: Hoischen-Taubner Susanne , Habel Jonas , Uhlig Verena , Schwabenbauer Eva-Marie , Rumphorst Theresa , Ebert Lara , Möller Detlev , Sundrum Albert
Published: August 2021

The levels of production diseases (PD) and the cow replacement rate are high in dairy farming. They indicate excessive production demands on the cow and a poor state of animal welfare. This is the subject of increasing public debate. The purpose of this study was to assess the effect of production diseases on the economic sustainability of dairy farms. The contributions of individual culled cows to the farm’s economic performance were calculated, based on milk recording and accounting data from 32 farms in Germany. Cows were identified as ‘profit cows’ when they reached their individual ‘break-even point’. Data from milk recordings (yield and indicators for PD) were used to cluster farms by means of a principal component and a cluster analysis. The analysis revealed five clusters of farms. The average proportion of profit cows was 57.5%, 55.6%, 44.1%, 29.4% and 19.5%. Clusters characterized by a high proportion of cows with metabolic problems and high culling and mortality rates had lower proportions of profit cows, somewhat irrespective of the average milk-yield per cow. Changing the perception of PD from considering it as collateral damage to a threat to the farms’ economic viability might foster change processes to reduce production diseases.