bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Data Analytics in the Assessment of Pathological Speech—A Critical Appraisal
Authors: Gómez-Vilda Pedro , Gómez-Rodellar Andrés , Palacios-Alonso Daniel , Rodellar-Biarge Victoria , Álvarez-Marquina Agustín
Published: November 2022

Pathological voice characterization has received increasing attention over the last 20 years. Hundreds of studies have been published showing inventive approaches with very promising findings. Nevertheless, methodological issues might hamper performance assessment trustworthiness. This study reviews some critical aspects regarding data collection and processing, machine learning-oriented methods, and grounding analytical approaches, with a view to embedding developed clinical decision support tools into the diagnosis decision-making process. A set of 26 relevant studies published since 2010 was selected through critical selection criteria and evaluated. The model-driven (MD) or data-driven (DD) character of the selected approaches is deeply examined considering novelty, originality, statistical robustness, trustworthiness, and clinical relevance. It has been found that before 2020 most of the works examined were more aligned with MD approaches, whereas over the last two years a balanced proportion of DD and MD-based studies was found. A total of 15 studies presented MD characters, whereas seven were mainly DD-oriented, and four shared both profiles. Fifteen studies showed exploratory or prospective advanced statistical analysis. Eighteen included some statistical validation to avail claims. Twenty-two reported original work, whereas the remaining four were systematic reviews of others’ work. Clinical relevance and acceptability by voice specialists were found in 14 out of the 26 works commented on. Methodological issues such as detection and classification performance, training and generalization capability, explainability, preservation of semantic load, clinical acceptance, robustness, and development expenses have been identified as major issues in applying machine learning to clinical support systems. Other important aspects to be taken into consideration are trustworthiness, gender-balance issues, and statistical relevance.
Estimation of Thermal Radiation in Bed Mattresses
Authors: Park Kye-Won , Mizuno Masayuki , Cho Chang-Geun , Jeong Jong-Jin
Published: November 2022

The population density of cities has been increasing with time and the development of industry. Building fires in large cities with high population density cause extensive human and property damage. To prevent such damage, the characteristics of flames such as the thermal radiation and intensity of the fire source must be considered when designing building structures. However, the consideration of these factors is practically inadequate. Accordingly, in this study, when a mattress was ignited in an open environment at a different installation height (0–515 mm), the measurements from a heat flux meter and the calculated thermal radiation were compared, and a comparative analysis was conducted using the existing prediction formulas by researchers described in ISO 24678-7. We examined the fire risk of mattresses according to the mattress installation height. As a result, the fire risk of the mattress was confirmed according to the mattress installation height; upon comparing the experimental and calculated values for radiant heat, it was found to be necessary to estimate the radiant heat using a calculation method that applies the configuration factor differently depending on the change in the flame shape. In addition, as a result of substituting the experimental value into the calculation method of ISO 24678-7 (a method for estimating the radiant heat of liquid combustibles), the experimental value and the calculated value were found to be significantly different. Therefore, similar to ISO 24678-7 for the radiation heat estimation method for “liquid combustibles”, an international standard for establishing the radiation heat estimation method for “solid combustible materials” as a standard was also required for a reasonable analysis of the fire safety phenomenon of solid materials, such as bed mattresses.
Bacterial Community and Antibiotic Resistance Gene Profiles of Fish Gut Contents and Their Aquaculture Environment in Tianjin, China
Authors: Wang Qiushui , Zhou Xin , Liu Yue , Ding Qi , Wu Zan , Deng Jie , Zuo Jia , Yuan Liyan , Shao Peng , Cheng Bo , Gao Lijuan
Published: November 2022

The continuous expansion of freshwater fish culture is confronted with environmental problems owing to their high antibiotic inputs and antibiotic-resistant bacteria. This study explored the antibiotic resistance gene (ARG) profiles of water and fish gut contents from three fishponds in Tianjin using a metagenomics approach. Proteobacteria, Bacteroidetes, and Actinobacteria were the most abundant phyla in all water samples. However, the microbial composition of the fish guts was distinctly different among the three aquaculture farms. Cetobacterium, Bacillus, Weissella, and Fusobacterium were the dominant genera in the gut contents of all fish. More than 20 unique ARGs with relatively high abundances were detected in both water and fish gut content samples. The dominant genes and pathways of antibiotic resistance mechanisms detected in all samples were antibiotic efflux, antibiotic inactivation, antibiotic target alteration, antibiotic target protection, antibiotic target replacement, and reduced permeability to antibiotics. In addition, our results indicate that antibiotics, such as florfenicol, and heavy metals, such as Zn and Cu, could have a significant correlation with some common ARGs, indicating that antibiotic-resistant bacteria could co-occur with heavy metals. Our study provides a research basis for the development of a strategy for practical antibiotic application and heavy metal monitoring in aquaculture.
Intrinsic Characteristics and Biological Effects of Standard Reference Indoor Dust SRM® 2585 and Its Inhalable Subfractions PM10 and PM2.5
Authors: El Hajjar Carine , Rogez-Florent Tiphaine , Seguin Virginie , Verdin Anthony , Garon David , Pottier Ivannah , André Véronique
Published: November 2022

Standard Reference Material® (SRM®) 2585 can be considered as a model sample of settled indoor dust. At least 168 adsorbed chemicals were identified and quantified, generating a complex and potentially toxic mixture. Inhalable fractions PM10 and PM2.5 were isolated and compared to SRM® 2585 for their intrinsic properties and their respiratory toxicity using pertinent normal human bronchoepithelial (NHBE) cells. The intrinsic oxidative potential (OP) of SRM® 2585 and its subfractions was measured in acellular conditions, together with ROS generation and endotoxin content. For SRM® 2585 and PM10, cellular responses were evaluated on NHBE cells after 72 h exposure (1.1 to 110 µg/mL). The presence of endotoxins associated with an intrinsic prooxidant potential did not lead to the induction of an inflammatory response. Interestingly, cytokine production was decreased, strongly for IL-1β and to a lesser extent for IL-6. Only PM10 induced an acute toxicity. In parallel, mutagenicity was evaluated from organic extracts. Mutagenic profiles indicated the concomitant presence of nitro-PAHs in addition to the previously reported PAHs. This could be of concern for long-term health effects in a context of chronic exposure.
Establishing Correlation between Cruise Ship Activities and Ambient PM Concentrations in the Kotor Bay Area Using a Low-Cost Sensor Network
Authors: Gagic Radmila , Skuric Maja , Djukanovic Gordana , Nikolic Danilo
Published: November 2022

The analysis of cruise ships is focusing on port areas where they may represent a significant source of anthropogenic emissions. In order to determine the correlation between cruise ship activities (hoteling and maneuvering) in ports with the ambient concentration of pollutants associated with marine diesel fuel combustion, the low-cost sensors are finding their market share due to lower prices compared to the referent ones. In this study, a network of four low-cost PM sensors was used to determine the correlation between ambient PM2.5 and PM10 mass concentrations with cruise ship activities in the Kotor Bay area during 27 days in the peak summer season, with a 10-min resolution. Recorded data and the Openair model were used to investigate the potential relationship between cruise ship operations and temporal fluctuations in PM concentrations in the ambient air. Additionally, an Tier 3 methodology developed through the European Monitoring and Evaluation Programme of the European Environmental Agency (EMEP/EEA) was applied in order to estimate the total cruise ship PM emissions. The study has shown that weather conditions play a significant role in local PM concentrations, so that, with predominant ENE wind directions, the west side of the Bay experienced on average higher concentrations of both PM2.5 and PM10. Rain precipitation and higher winds tend to decrease rapidly ambient PM concentrations. Higher PM levels are associated mainly with lower wind speeds and the inflows from neighboring berths/anchorages. During the maneuvering (arrival and departure) of cruise ships, higher spikes in PM values were detected, being more visible for PM10 than PM2.5. A significant correlation between daily average PM concentrations and cruise ships’ daily estimated PM emission was not found. As a result, higher temporal resolution demonstrated a stronger correlation.
A Program Library for Computing Pure Spin–Angular Coefficients for One- and Two-Particle Operators in Relativistic Atomic Theory
Authors: Gaigalas Gediminas
Published: November 2022

A program library for computing pure spin-angular coefficients for any one- and scalar two-particle operators is presented. The method used is based on the combination of the second quantization and quasi-spin techniques with the angular momentum theory and the method of irreducible tensorial sets. A relativistic approach is assumed. This program library is integrated in the General Relativistic Atomic Structure Package but it can be implemented in other program packages, too.
Amoud Class for Hazard-Based and Odds-Based Regression Models: Application to Oncology Studies
Authors: Muse Abdisalam Hassan , Mwalili Samuel , Ngesa Oscar , Chesneau Christophe , Alshanbari Huda M. , El-Bagoury Abdal-Aziz H.
Published: November 2022

The purpose of this study is to propose a novel, general, tractable, fully parametric class for hazard-based and odds-based models of survival regression for the analysis of censored lifetime data, named as the “Amoud class (AM)” of models. This generality was attained using a structure resembling the general class of hazard-based regression models, with the addition that the baseline odds function is multiplied by a link function. The class is broad enough to cover a number of widely used models, including the proportional hazard model, the general hazard model, the proportional odds model, the general odds model, the accelerated hazards model, the accelerated odds model, and the accelerated failure time model, as well as combinations of these. The proposed class incorporates the analysis of crossing survival curves. Based on a versatile parametric distribution (generalized log-logistic) for the baseline hazard, we introduced a technique for applying these various hazard-based and odds-based regression models. This distribution allows us to cover the most common hazard rate shapes in practice (decreasing, constant, increasing, unimodal, and reversible unimodal), and various common survival distributions (Weibull, Burr-XII, log-logistic, exponential) are its special cases. The proposed model has good inferential features, and it performs well when different information criteria and likelihood ratio tests are used to select hazard-based and odds-based regression models. The proposed model’s utility is demonstrated by an application to a right-censored lifetime dataset with crossing survival curves.
A Method for Analyzing the Performance Impact of Imbalanced Binary Data on Machine Learning Models
Authors: Zheng Ming , Wang Fei , Hu Xiaowen , Miao Yuhao , Cao Huo , Tang Mingjing
Published: November 2022

Machine learning models may not be able to effectively learn and predict from imbalanced data in the fields of machine learning and data mining. This study proposed a method for analyzing the performance impact of imbalanced binary data on machine learning models. It systematically analyzes 1. the relationship between varying performance in machine learning models and imbalance rate (IR); 2. the performance stability of machine learning models on imbalanced binary data. In the proposed method, the imbalanced data augmentation algorithms are first designed to obtain the imbalanced dataset with gradually varying IR. Then, in order to obtain more objective classification results, the evaluation metric AFG, arithmetic mean of area under the receiver operating characteristic curve (AUC), F-measure and G-mean are used to evaluate the classification performance of machine learning models. Finally, based on AFG and coefficient of variation (CV), the performance stability evaluation method of machine learning models is proposed. Experiments of eight widely used machine learning models on 48 different imbalanced datasets demonstrate that the classification performance of machine learning models decreases with the increase of IR on the same imbalanced data. Meanwhile, the classification performances of LR, DT and SVC are unstable, while GNB, BNB, KNN, RF and GBDT are relatively stable and not susceptible to imbalanced data. In particular, the BNB has the most stable classification performance. The Friedman and Nemenyi post hoc statistical tests also confirmed this result. The SMOTE method is used in oversampling-based imbalanced data augmentation, and determining whether other oversampling methods can obtain consistent results needs further research. In the future, an imbalanced data augmentation algorithm based on undersampling and hybrid sampling should be used to analyze the performance impact of imbalanced binary data on machine learning models.
Swirling Flow of Chemically Reactive Viscoelastic Oldroyd-B Fluid through Porous Medium with a Convected Boundary Condition Featuring the Thermophoresis Particle Deposition and Soret–Dufour Effects
Authors: Al Elaiw Abeer , Hafeez Abdul , Khalid Asma , AL Nuwairan Muneerah
Published: November 2022

In this study, an analysis of the rotating flow of viscoelastic Oldroyd-B fluid along with porous medium featuring the Soret–Dufour effects is explored. The heat transport mechanism is discussed with the involvement of thermal radiation and heat source/sink. Additionally, the thermophoresis of particle deposition and chemical reaction are taken into the concentration equation in order to investigate the mass transportation in the liquid. To formulate the non-linear ordinary differential equations, the von Karman similarity approach is used in the system of partial differential equations and then integrated numerically by the bvp midrich scheme in Maple programming. Results are provided by graphical framework and tabular form. A quick parametric survey is carried out concerning flow field, thermal, and solutal distributions through graph representation. The curves show that increasing the values of the retardation time parameter decreases the radial velocity while increasing the angular velocity. Additionally, when the relaxation time parameter becomes powerful, the magnitude of the velocity curves decreases considerably in the radial and axial directions. The presence of a radiation parameter indicates that the fluid will absorb a greater amount of heat, which is equivalent to a higher temperature. Further, an increase in the stretching parameter leads to a reduction in the temperature components.
Effects of Current and Ambient Temperature on Thermal Response of Lithium Ion Battery
Authors: Wang Shuping , Wu Tangqin , Xie Heng , Li Changhao , Zhang Jiaqing , Jiang Lihua , Wang Qingsong
Published: November 2022

Both operating current and ambient temperature have a great impact on heat generation and the available residual capacity of the lithium ion battery. The thermal response of the lithium ion battery is investigated under isothermal conditions. Six currents from 1 A to 6 A, with a 1 A interval, are investigated in order to discuss the effect of current under 25 °C; four temperatures from 10 °C to 55 °C, with a 15 °C interval, are investigated to study the effect of temperature under the current of 2 A. The heat generation rate increases with the current increasing during both the charge and discharge stage, but the charge capacity remains independent of current, while the discharge capacity decreases with increasing current. Heat generation decreases with increasing temperature in both the charge and discharge stage, while charge capacity and discharge capacity increase. with the temperature increasing from 10 °C to 55 °C. Heat generation of per charge/discharge capacity is also discussed, and in most cases, the heat generation of per charge capacity during the constant voltage charge stage is larger than that during the constant current charge stage. Heat generation increases at the expense of available capacity, during the discharge stage.
Physics-Based SoH Estimation for Li-Ion Cells
Authors: Iurilli Pietro , Brivio Claudio , Carrillo Rafael E. , Wood Vanessa
Published: November 2022

Accurate state of health (SoH) estimation is crucial to optimize the lifetime of Li-ion cells while ensuring safety during operations. This work introduces a methodology to track Li-ion cells degradation and estimate SoH based on electrochemical impedance spectroscopy (EIS) measurements. Distribution of relaxation times (DRT) were exploited to derive indicators linked to the so-called degradation modes (DMs), which group the different aging mechanisms. The combination of these indicators was used to model the aging progression over the whole lifetime (both in the “pre-knee” and “after-knee” regions), enabling a physics-based SoH estimation. The methodology was applied to commercial cylindrical cells (NMC811|Graphite SiOx). The results showed that loss of lithium inventory (LLI) is the main driving factor for cell degradation, followed by loss of cathode active material (LAMC). SoH estimation was achievable with a mean absolute error lower than 0.75% for SoH values higher than 85% and lower than 3.70% SoH values between 85% and 80% (end of life). The analyses of the results will allow for guidelines to be defined to replicate the presented methodology, characterize new Li-ion cell types, and perform onboard SoH estimation in battery management system (BMS) solutions.
Lithium Plating Detection Based on Electrochemical Impedance and Internal Resistance Analyses
Authors: Pan Yue , Ren Dongsheng , Han Xuebing , Lu Languang , Ouyang Minggao
Published: November 2022

Lithium plating, induced by fast charging and low-temperature charging, is one of the reasons for capacity fading and causes safety problems for lithium-ion batteries. Hence, reliable and effective non-destructive detection methods for lithium plating are needed. In this research, electrochemical impedance and internal resistance for batteries are measured during the rest period after charging. The results for lithium plating batteries and normal batteries are compared and analyzed. Lithium plating detection is realized with multiple indicators extracted from electrochemical impedance and internal resistance results. The effectiveness of the proposed detection methods is verified by the experiments conducted with commercial large-capacity batteries. The proposed methods have further potential to be used in battery management systems to realize online detection of lithium plating and improve the safety of battery systems.
Wide-Field Calcium Imaging of Neuronal Network Dynamics In Vivo
Authors: Nietz Angela K. , Popa Laurentiu S. , Streng Martha L. , Carter Russell E. , Kodandaramaiah Suhasa B. , Ebner Timothy J.
Published: November 2022

A central tenet of neuroscience is that sensory, motor, and cognitive behaviors are generated by the communications and interactions among neurons, distributed within and across anatomically and functionally distinct brain regions. Therefore, to decipher how the brain plans, learns, and executes behaviors requires characterizing neuronal activity at multiple spatial and temporal scales. This includes simultaneously recording neuronal dynamics at the mesoscale level to understand the interactions among brain regions during different behavioral and brain states. Wide-field Ca2+ imaging, which uses single photon excitation and improved genetically encoded Ca2+ indicators, allows for simultaneous recordings of large brain areas and is proving to be a powerful tool to study neuronal activity at the mesoscopic scale in behaving animals. This review details the techniques used for wide-field Ca2+ imaging and the various approaches employed for the analyses of the rich neuronal-behavioral data sets obtained. Also discussed is how wide-field Ca2+ imaging is providing novel insights into both normal and altered neural processing in disease. Finally, we examine the limitations of the approach and new developments in wide-field Ca2+ imaging that are bringing new capabilities to this important technique for investigating large-scale neuronal dynamics.
Machine Learning Approach to Understand Worsening Renal Function in Acute Heart Failure
Authors: Urban Szymon , Błaziak Mikołaj , Jura Maksym , Iwanek Gracjan , Ponikowska Barbara , Horudko Jolanta , Siennicka Agnieszka , Berka Petr , Biegus Jan , Ponikowski Piotr , Zymliński Robert
Published: November 2022

Acute heart failure (AHF) is a common and severe condition with a poor prognosis. Its course is often complicated by worsening renal function (WRF), exacerbating the outcome. The population of AHF patients experiencing WRF is heterogenous, and some novel possibilities for its analysis have recently emerged. Clustering is a machine learning (ML) technique that divides the population into distinct subgroups based on the similarity of cases (patients). Given that, we decided to use clustering to find subgroups inside the AHF population that differ in terms of WRF occurrence. We evaluated data from the three hundred and twelve AHF patients hospitalized in our institution who had creatinine assessed four times during hospitalization. Eighty-six variables evaluated at admission were included in the analysis. The k-medoids algorithm was used for clustering, and the quality of the procedure was judged by the Davies–Bouldin index. Three clinically and prognostically different clusters were distinguished. The groups had significantly (p = 0.004) different incidences of WRF. Inside the AHF population, we successfully discovered that three groups varied in renal prognosis. Our results provide novel insight into the AHF and WRF interplay and can be valuable for future trial construction and more tailored treatment.
EZH2 as a Prognostic Factor and Its Immune Implication with Molecular Characterization in Prostate Cancer: An Integrated Multi-Omics in Silico Analysis
Authors: Du Tian-Qi , Liu Ruifeng , Zhang Qiuning , Luo Hongtao , Liu Zhiqiang , Sun Shilong , Wang Xiaohu
Published: November 2022

Prostate cancer (PCa) is a type of potentially fatal malignant tumor. Immunotherapy has shown a lot of potential for various types of solid tumors, but the benefits have been less impressive in PCa. Enhancer of zeste homolog 2 (EZH2) is one of the three core subunits of the polycomb repressive complex 2 that has histone methyltransferase activity, and the immune effects of EZH2 in PCa are still unclear. The purpose of this study was to explore the potential of EZH2 as a prognostic factor and an immune therapeutic biomarker for PCa, as well as the expression pattern and biological functions. All analyses in this study were based on publicly available databases, mainly containing Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), UCSCXenaShiny, and TISIDB. We performed differential expression analysis, developed a prognostic model, and explored potential associations between EZH2 and DNA methylation modifications, tumor microenvironment (TME), immune-related genes, tumor mutation burden (TMB), tumor neoantigen burden (TNB), and representative mismatch repair (MMR) genes. We also investigated the molecular and immunological characterizations of EZH2. Finally, we predicted immunotherapeutic responses based on EZH2 expression levels. We found that EZH2 was highly expressed in PCa, was associated with a poor prognosis, and may serve as an independent prognostic factor. EZH2 expression in PCa was associated with DNA methylation modifications, TME, immune-related genes, TMB, TNB, and MMR. By gene set enrichment analysis and gene set variation analysis, we found that multiple functions and pathways related to tumorigenesis, progression, and immune activation were enriched. Finally, we inferred that immunotherapy may be more effective for PCa patients with low EZH2 expression. In conclusion, our study showed that EZH2 could be a potentially efficient predictor of prognosis and immune response in PCa patients.
Exploiting DNA Replication Stress as a Therapeutic Strategy for Breast Cancer
Authors: Zhang Jing , Chan Doug W. , Lin Shiaw-Yih
Published: November 2022

Proliferating cells rely on DNA replication to ensure accurate genome duplication. Cancer cells, including breast cancer cells, exhibit elevated replication stress (RS) due to the uncontrolled oncogenic activation, loss of key tumor suppressors, and defects in the DNA repair machinery. This intrinsic vulnerability provides a great opportunity for therapeutic exploitation. An increasing number of drug candidates targeting RS in breast cancer are demonstrating promising efficacy in preclinical and early clinical trials. However, unresolved challenges lie in balancing the toxicity of these drugs while maintaining clinical efficacy. Furthermore, biomarkers of RS are urgently required to guide patient selection. In this review, we introduce the concept of targeting RS, detail the current therapies that target RS, and highlight the integration of RS with immunotherapies for breast cancer treatment. Additionally, we discuss the potential biomarkers to optimizing the efficacy of these therapies. Together, the continuous advances in our knowledge of targeting RS would benefit more patients with breast cancer.
Novel Chromone-Containing Allylmorpholines Induce Anxiolytic-like and Sedative Effects in Adult Zebrafish
Authors: Prikhodko Veronika A. , Sysoev Yuri I. , Gerasimova Elena V. , Okovityi Sergey V.
Published: November 2022

Chromone-containing allylmorpholines (CCAMs) are a novel class of compounds that have demonstrated acetyl- and butyryl-cholinesterase-inhibiting and N-methyl-D-aspartate (NMDA) receptor-blocking properties in vitro, but their in vivo pharmacological activity remains underexplored. In this work, we evaluated the psychotropic activity of five different CCAMs (1 (9a), 2 (9j), 3 (9l), 4 (33a), and 5 (33b)) using the novel tank test (NTT) and light/dark box (LDB) test in adult zebrafish. The CCAMs were screened in the NTT at a range of concentrations, and they were found to induce a dose-dependent sedative effect. Compound 4 (33a) was also evaluated using the LDB test, and it was found to have anxiolytic-like properties at low concentrations. To assess the potential contribution of the glutamate and cholinergic mechanisms in the effects of the CCAMs, we conducted experiments with pre-exposure to putative antagonists, NMDA and biperiden. Neither biperiden nor NMDA were able to diminish or cancel the effects of the CCAMs, countering the in vitro data obtained in previous studies. The apparent discrepancy could be related to the specifics of CCAM metabolism or to the interspecies differences between the putative target proteins, possibly due to the relatively low identity percentage of their sequences. Although further research in mammals is required in order to establish their pharmacological properties, novel CCAMs may represent an appealing group of psychoactive drug candidates.
Aptamer-Gated Mesoporous Silica Nanoparticles for N Protein Triggered Release of Remdesivir and Treatment of Novel Coronavirus (2019-nCoV)
Authors: Zhang Xiaohui , Zhang Xin , Xu Aoqiong , Yu Mengdi , Xu Yu , Xu Ying , Wang Chao , Yang Gege , Song Chunxia , Wu Xiangwei , Lu Ying
Published: November 2022

Since the 2019-nCoV outbreak was first reported, hundreds of millions of people all over the world have been infected. There is no doubt that improving the cure rate of 2019-nCoV is one of the most effective means to deal with the current serious epidemic. At present, Remdesivir (RDV) has been clinically proven to be effective in the treatment of SARS-CoV-2. However, the uncertain side effects make it important to reduce the use of drugs while ensuring the self-healing effect. We report an approach here with targeted therapy for the treatment of SARS-CoV-2 and other coronaviruses illness. In this study, mesoporous silica was used as the carrier of RDV, the nucleocapsid protein (N protein) aptamer was hybridized with the complementary chain, and the double-stranded DNA was combined with gold nanoparticles as the gates of mesoporous silica pores. When the RDV-loaded mesoporous silica is incubated with the N protein, aptamer with gold nanoparticles dissociate from the complementary DNA oligonucleotide on the mesoporous silica surface and bind to the N protein. The releasing of RDV was determined by detecting the UV-vis absorption peak of RDV in the solution. These results show that the RDV delivery system designed in this work has potential clinical application for the treatment of 2019-nCoV.
Childhood Trauma and Dissociation Correlates in Alcohol Use Disorder: A Cross-Sectional Study in a Sample of 587 French Subjects Hospitalized in a Rehabilitation Center
Authors: Baudin Grégoire , Barrault Servane , El Ayoubi Hussein , Kazour François , Ballon Nicolas , Maugé Damien , Hingray Coraline , Brunault Paul , El-Hage Wissam
Published: November 2022

This study aimed to determine whether dissociative symptoms and childhood trauma (CT) may help identify a specific subgroup of patients among those hospitalized for alcohol use disorder (AUD). We assessed 587 patients hospitalized for an AUD in a French addiction rehabilitation center (cross-sectional study) regarding dissociative symptoms (DES-taxon), childhood trauma (CTQ), depression (BDI), anxiety (STAI-state and STAI-trait), posttraumatic stress disorder (PTSD; PCL-5), and AUD symptoms (AUDIT). We ran a hierarchical cluster analysis and compared the clusters in terms of dissociation and CT, as well as AUD, depressive, anxiety, and PTSD symptoms. We identified three clusters of patients: (1) patients with low AUD severity and low dissociation (LALD); (2) patients with high AUD severity and low dissociation (HALD); (3) patients with high AUD severity and high dissociation (HAHD). Patients from the HAHD group had significantly higher dissociation and more severe depression, anxiety, and PTSD symptoms than those with LALD and HALD. They also reported more emotional and sexual abuse than those with LALD. Among patients with an AUD, those with high dissociation may constitute an independent subgroup that exhibits a higher prevalence for CT and higher AUD severity, as well as higher depression, anxiety, and PTSD symptoms. Patients with more severe AUD and associated psychiatric symptoms should be systematically screened for dissociation and provided with tailor-based treatments.
Multiple Machine Learning Approaches for Morphometric Parameters in Prediction of Hydrocephalus
Authors: Xu Hao , Fang Xiang , Jing Xiaolei , Bao Dejun , Niu Chaoshi
Published: November 2022

Background: The diagnosis of hydrocephalus is mainly based on imaging findings. However, the significance of many imaging indicators may change, especially in some degenerative diseases, and even lead to misdiagnosis. Methods: This study explored the effectiveness of commonly used morphological parameters and typical radiographic findings in hydrocephalus diagnosis. The patients’ imaging data were divided into three groups, including the hydrocephalus group, the symptomatic group, and the normal control group. The diagnostic validity and weight of various parameters were compared between groups by multiple machine learning methods. Results: Our results demonstrated that Evans’ ratio is the most valuable diagnostic indicator compared to the hydrocephalus group and the normal control group. But frontal horns’ ratio is more useful in diagnosing patients with symptoms. Meanwhile, the sign of disproportionately enlarged subarachnoid space and third ventricle enlargement could be effective diagnostic indicators in all situations. Conclusion: Both morphometric parameters and radiological features were essential in diagnosing hydrocephalus, but the weights are different in different situations. The machine learning approaches can be applied to optimize the diagnosis of other diseases and consistently update the clinical diagnostic criteria.
Long-Term Management of Generalised Anxiety Disorder with Low-Dose Continuous Infusions of Flumazenil: A Case Series
Authors: Gallo Alexander T. , Addis Stephen , Martyn Vlad , Ramanathan Hishani , Wilkerson Grace K. , Hood Sean D. , Stampfer Hans , Hulse Gary K.
Published: November 2022

Background: Generalised anxiety disorder (GAD) is a common anxiety disorder associated with social and occupational impairment. Recently, a theory was postulated that dysfunctional gamma aminobutyric acid type A receptors (GABAA) are implicated in anxiety symptomology, which could be corrected by flumazenil, an antagonist at the benzodiazepine binding site on the GABAA receptor. Method: Participants had a primary diagnosis of GAD and were treated initially with an eight-day continuous low-dose flumazenil infusion (total 32 mg at a rate of 4 mg/24 h). Some participants were re-treated with a further four- or eight-day infusion. Treatment response was measured as a 50% reduction in anxiety or stress scores on the Depression Anxiety Stress Scale—21 (DASS-21). Remission was measured as scores ≤3 or ≤7 on the anxiety and stress subscales of the DASS-21, respectively. Results: Eight cases are reported. All cases met the criteria for treatment response on the anxiety and stress subscale of the DASS-21. Remission was achieved in seven participants on the anxiety subscale and in five on the stress subscale. No changes in hepatic, renal, or haematological function were likely attributed to flumazenil. Conclusion: Data suggest that low-dose continuous flumazenil infusion manages GAD symptoms and is safe. Although these results are promising, future randomised control trials are required to confirm these results.
Sound Perception of Blind Older Adults in Nursing Homes
Authors: Wu Yue , Huo Sijia , Mu Jingyi , Kang Jian
Published: November 2022

The number of blind older adults is gradually increasing with the aging of world’s population, and their needs and perception of sound are specific. This study investigated the behavioral activities of blind older adults and the dominant sound sources through on-site observation of an all-blind nursing home in China, and it used semi-structured interviews to obtain the sound perceptions of blind older adults. The findings showed that the daily behavioral activities can be categorized into basic living activity, leisure activity, social activity; and physical activity. The dominant sound sources included human, equipment, informational, and environmental sounds. This study developed a sound perception model of blind older adults in nursing homes, which takes three levels: sound requirements, acoustic environment, and sound cognition. Firstly, the blind older adults have a basic understanding of sound from the perspective of their living needs, then they feel the sound environment from the perspective of the living environment, and finally, they perceive the acoustic environment from the dimension of sound cognition in conjunction with contextual memory. This study sheds a light on the aural diversity of older adults, which is expected to support the inclusive design of nursing homes for older adults with visual impairments.
Exploring the Innovation Path of the Digital Construction Industry Using Mixed Methods
Authors: Xue Xiaolong , Tan Xianyu , Huang Qiongyu , Zhu Hui , Chen Jianshuo
Published: November 2022

To provide a theoretical basis for deepening digital reform in the construction industry and explore the innovation path of the digital construction industry, this research uses patent data for Guangdong Province to carry out explanatory sequence research. First, this research analyzes the dynamic evolution process of networks in the digital construction industry by using social network analysis. Then, grounded theory is used to conduct qualitative research to explore the innovation path of the digital construction industry. The results show that the scale of the innovation network of the digital construction industry is continually expanding and the digital carriers are becoming increasingly diverse. Influenced by the diversification of digital carriers, the research theme of the digital construction industry is beginning to develop in the direction of intelligence. The findings indicate that the use of mixed methods improves the robustness of the results and that the quantitative research results are explained by the qualitative research results. This research not only contributes to information development in the construction industry but also provides a theoretical basis for deepening digital reform in the construction industry.
Study on Concrete Deterioration and Chloride Ion Diffusion Mechanism by Different Aqueous NaCl-MgSO4 Concentrations
Authors: Zhang Fei , Wei Feng , Wu Xijun , Hu Zhiping , Li Xiaoguang , Gao Lili
Published: November 2022

Chemical erosion of reinforced concrete by Cl−, SO42− and Mg2+ in saline soil is the main factor of steel corrosion and concrete damage. In this study, the effects of different molar ratios of aqueous NaCl-MgSO4 on concrete macroscopic properties (appearance, weight change, compressive strength, and dynamic elastic modulus), ion content, microstructure, and porosity of concrete were investigated. The effects of different molar ratios on the macroscopic characteristics and erosion depth of concrete were revealed through concrete appearance, weight, mechanical properties, and SO42− and Cl− content. Analysis of the microstructural evolution process and complex mineral composition of concrete using various microscopic testing methods. The results showed that with increased salt concentration and erosion time, the weight change rate, compressive strength change rate, and relative dynamic elastic modulus of concrete samples had a trend of first increasing and then decreasing. The evolutionary process of transition from large pores to medium and small pores and then to large pores. In the early erosion stage, with increased MgSO4, corrosion products were deposited in pores and cracks, which refined the concrete pore structure and reduced ion diffusion speeds of Cl−, SO42−, and Mg2+. In the later erosion stage, corrosion products caused matrix damage and produced intersecting cracks, which promoted ion diffusion rates and induced deterioration of concrete macroscopic properties. During experiments, the binding ability of SO42− and Mg2+ ions to hydration products was found to be higher than that of Cl−.
Integrated Design and Assessment for Indoor Heating, Ventilation and Air-Conditioning in Hot Summer and Cold Winter Area: A Case Study in China
Authors: Yang Ye , Li Zhenyu
Published: November 2022

Integrated design of the heating, ventilation and air-conditioning (HVAC) is indispensable to green design because the increasing demand for HVAC systems has led to the diversification of indoor terminals for residential buildings, either focusing on energy efficiency or specializing in creating comfortable indoor environments, and they have different impacts on architectural and engineering design. The paper discussed the assessment-based integration design of the HVAC system, and by introducing case experiences, the whole process of the collaboration between architects and engineers was explored. Various methods were used in the research. The analytic hierarchy process (AHP) was employed to develop the assessment structure and calculate weightings; employing fuzzy comprehensive evaluation (FCE), the social performances of HVAC systems were subjectively evaluated; simulation technology was used to calculate the energy performances; the final results were ranked by the order of preference by similarity to ideal solution (TOPSIS). The research perspective of the collaboration between architects and engineers contributed to the existing literature. Besides, different indoor terminals were analyzed from the two disciplines; an assessment tool (ATI) was conducted and could be referred to; the current green building rating tools were analyzed, and suggestions were proposed to promote the integrated design.
Shared PV Systems in Multi-Scaled Communities
Authors: Pasina Alina , Canoilas Affonso , Johansson Dennis , Bagge Hans , Fransson Victor , Davidsson Henrik
Published: November 2022

In past years, Sweden has been facing a rapid growth of photovoltaic cells, and the total PV installation capacity increased from 300 kW to 1090 MW (2006–2020). The increased number of PV users was a result of active support from the Swedish government with an aim of achieving multiple sustainable goals regarding renewable energy. This project evaluates the profitability of shared PV systems in communities of different sizes in Sweden. This study aimed to contribute to the literature by filling the research gap of presenting the financial benefits at different community scales. The electricity use profiles consisted of hourly measured electricity use that was derived from 1067 individual Swedish apartments. The profiles were then used to create multi-scaled communities with shared PV systems. The mid-market price model was implemented to simulate electricity trading among prosumers in the community using Visual Basic Applications (VBA) in MS Excel. Further, the electricity costs were used for Life Cycle Cost (LCC) assessment. To demonstrate the increase in profitability, the LCC results of households with shared PV systems were compared to households that own PV individually and households that do not own a PV system. The evaluation showed the financial benefits of shared PV systems in comparison with individually owned PV systems. This study also demonstrated the increase in profitability and the reduction in payback time for the average household if sharing a PV system as part of a larger community.
Strategies to Enhance Contamination Control Performance through Ventilation Improvement in a Biosafety Laboratory Building
Authors: Permana Indra , Wang Fujen , Rakhsit Dibakar , Huang Jingsyong
Published: November 2022

A biosafety level (BSL) laboratory is a set of biocontainment preventative measures used to prevent and isolate hazardous biological agents or their accidental release in a laboratory. It is vital to provide a negative-pressurized environment for disease infection control. The experimental equipment layout may affect the personnel’s exposure to infection. However, the equipment layout and exhaust air grilles were in a fixed position in this investigated BSL. Due to retrofitting, the layout arrangement of HEPA as supply air is investigated numerically. Computational Fluid Dynamics (CFD) simulation is conducted to analyze and determine a better design for contamination control. This study proposes three ventilation arrangements as an alternative design, including vertical arrangement, horizontal arrangement, and L-shaped ventilation arrangements (instead of the supply being arranged in a single line). In addition, the airflow distribution, concentration decay, air of age, ventilation, and removal effectiveness are all examined in the study. The numerical simulation results were verified by a field measurement test. The results revealed that the L-shaped ventilation arrangement for supply air diffusers would achieve better ventilation and removal efficiency. The local mean age of air was also identified as the most satisfactory ventilation performance measure, as it shows the level of contaminant control. It also indicated that ventilation could be improved by arranging the supply air layout with less expenditure through CFD-aided simulation in identifying strategies for best practices for the design stage to reduce the running cost at full operation.
The Renaissance of CDK Inhibitors in Breast Cancer Therapy: An Update on Clinical Trials and Therapy Resistance
Authors: Abdelmalak Mary , Singh Rajanbir , Anwer Mohammed , Ivanchenko Pavel , Randhawa Amritdeep , Ahmed Myra , Ashton Anthony W. , Du Yanming , Jiao Xuanmao , Pestell Richard
Published: November 2022

Cyclin-dependent kinases (CDKs) govern cell-cycle checkpoint transitions necessary for cancer cell proliferation. Recent developments have illustrated nuanced important differences between mono CDK inhibitor (CDKI) treatment and the combination therapies of breast cancers. The CDKIs that are currently FDA-approved for breast cancer therapy are oral agents that selectively inhibit CDK4 and CDK6, include palbociclib (Ibrance), ribociclib (Kisqali), and abemaciclib (Verzenio). CDKI therapy is effective in hormone receptor positive (HR+), and human epidermal growth factor receptor two negative (HER2−) advanced breast cancers (ABC) malignancies, but remains susceptible due to estrogen and progesterone receptor overexpression. Adding a CDK4/6I to endocrine therapy increases efficacy and delays disease progression. Given the side effects of CDKI, identifying potential new treatments to enhance CDKI effectiveness is essential. Recent long-term studies with Palbociclib, including the PALLAS and PENELOPE B, which failed to meet their primary endpoints of influencing progression-free survival, suggest a deeper mechanistic understanding of cyclin/CDK functions is required. The impact of CDKI on the anti-tumor immune response represents an area of great promise. CDKI therapy resistance that arises provides the opportunity for specific types of new therapies currently in clinical trials.