bluuebunny/crossref_metadata_2025 huggingface dataset:
Updated Review on Clinically-Relevant Properties of Delafloxacin
Authors: Turban Adrien , Guérin François , Dinh Aurélien , Cattoir Vincent
Published: July 2023

The extensive use of fluoroquinolones has been consequently accompanied by the emergence of bacterial resistance, which triggers the necessity to discover new compounds. Delafloxacin is a brand-new anionic non-zwitterionic fluoroquinolone with some structural particularities that give it attractive proprieties: high activity under acidic conditions, greater in vitro activity against Gram-positive bacteria—even those showing resistance to currently-used fluoroquinolones—and nearly equivalent affinity for both type-II topoisomerases (i.e., DNA gyrase and topoisomerase IV). During phases II and III clinical trials, delafloxacin showed non-inferiority compared to standard-of-care therapy in the treatment of acute bacterial skin and skin structure infections and community-acquired bacterial pneumonia, which resulted in its approval in 2017 by the Food and Drug Administration for indications. Thanks to its overall good tolerance, its broad-spectrum in vitro activity, and its ease of use, it could represent a promising molecule for the treatment of bacterial infections.
Evidence-Based Utility of Adjunct Antioxidant Supplementation for the Prevention and Treatment of Dermatologic Diseases: A Comprehensive Systematic Review
Authors: Tran Jasmine Thuy , Diaz Michael Joseph , Rodriguez Daphnee , Kleinberg Giona , Aflatooni Shaliz , Palreddy Siri , Abdi Parsa , Taneja Kamil , Batchu Sai , Forouzandeh Mahtab
Published: July 2023

Skin conditions are a significant cause of fatal and nonfatal disease burdens globally, ranging from mild irritations to debilitating diseases. Oxidative stress, which is an imbalance between reactive oxygen species and the cells’ ability to repair damage, is implicated in various skin diseases. Antioxidants have been studied for their potential benefits in dermatologic health, but the evidence is limited and conflicting. Herein, we conducted a systematic review of controlled trials, meta-analyses, and Cochrane review articles to evaluate the current evidence on the utility of antioxidant supplementation for adjunct prevention and treatment of skin disease and to provide a comprehensive assessment of their role in promoting dermatologic health. The Cochrane Library, PubMed, EMBASE, and Epistemonikos databases were queried. Eligibility criteria included (1) primary focus on nanoparticle utility for skin cancer; (2) includes measurable outcomes data with robust comparators; (3) includes a number of human subjects or cell-line types, where applicable; (4) English language; and (5) archived as full-text journal articles. A total of 55 articles met the eligibility criteria for the present review. Qualitative analysis revealed that topical and oral antioxidant supplementation has demonstrated preliminary efficacy in reducing sunburns, depigmentation, and photoaging. Dietary exogenous antioxidants (namely vitamins A, C, and E) have shown chemopreventive effects against skin cancer. Antioxidant supplementation has also shown efficacy in treating non-cancer dermatoses, including rosacea, psoriasis, atopic dermatitis, and acne vulgaris. While further studies are needed to validate these findings on a larger scale, antioxidant supplementation holds promise for improving skin health and preventing skin diseases.
Construction of Half Masks for the Respiratory Tract Protection and the Speech Intelligibility Assessed from the Measured Suppression of Sound
Authors: Nowacki Krzysztof , Marczak Wojciech , Łakomy Karolina , Almásy László
Published: July 2023

Half masks (a.k.a. filtering facepieces, FFP) are personal protective equipment against dust in a work environment. Their filtration efficiency is legally regulated. Occupational safety and health services have not paid enough attention to speech disruption caused by FFPs, even though the latter could impair verbal communication and result in discomfort or increased risk of accidents. This study deals with the objective differences in speech suppression between masks of various construction belonging to the same filtration class, FFP2, and equipped with exhalation valves. We applied an objective method of white noise attenuation, suggested in our previous work. Its uniqueness lies in the fact that the acoustic apparati are applied in the whole procedure, and no human speakers/listeners participation is required. We compared seven types of masks: three moulded, one moulded with folded elements, two folded horizontally, and one vertically. We determined attenuation caused by the masks in 1/3 octave-wide bands with centre frequency from 100 Hz to 20 kHz. All the studied FFPs attenuated sound waves in a frequency range responsible for 80–90% of the perceived speech intelligibility. The attenuations of moulded masks were ca. 3 dB higher in 1–16 kHz bands than those of folded ones. The moulded mask with foldable parts for better fitting the face suppressed the high-pitch tones considerably more than the other masks. These observations were confirmed quantitatively by the cluster analysis based on the Euclidean distances between the acoustic spectra.
BUU-LSPINE: A Thai Open Lumbar Spine Dataset for Spondylolisthesis Detection
Authors: Klinwichit Podchara , Yookwan Watcharaphong , Limchareon Sornsupha , Chinnasarn Krisana , Jang Jun-Su , Onuean Athita
Published: July 2023

(1) Background: Spondylolisthesis, a common disease among older individuals, involves the displacement of vertebrae. The condition may gradually manifest with age, allowing for potential prevention by the research of predictive algorithms. However, one key issue that hinders research in spondylolisthesis prediction algorithms is the need for publicly available spondylolisthesis datasets. (2) Purpose: This paper introduces BUU-LSPINE, a new dataset for the lumbar spine. It includes 3600 patients’ plain film images annotated with vertebral position, spondylolisthesis diagnosis, and lumbosacral transitional vertebrae (LSTV) ground truth. (4) Methods: We established an annotation pipeline to create the BUU-SPINE dataset and evaluated it in three experiments as follows: (1) lumbar vertebrae detection, (2) vertebral corner points extraction, and (3) spondylolisthesis prediction. (5) Results: Lumbar vertebrae detection achieved the highest precision rates of 81.93% on the AP view and 83.45% on the LA view using YOLOv5; vertebral corner point extraction achieved the lowest average error distance of 4.63 mm on the AP view using ResNet152V2 and 4.91 mm on the LA view using DenseNet201. Spondylolisthesis prediction reached the highest accuracy of 95.14% on the AP view and 92.26% on the LA view of a testing set using Support Vector Machine (SVM). (6) Discussions: The results of the three experiments highlight the potential of BUU-LSPINE in developing and evaluating algorithms for lumbar vertebrae detection and spondylolisthesis prediction. These steps are crucial in advancing the creation of a clinical decision support system (CDSS). Additionally, the findings demonstrate the impact of Lumbosacral transitional vertebrae (LSTV) conditions on lumbar detection algorithms.
Amortized Bayesian Meta-Learning with Accelerated Gradient Descent Steps
Authors: Zhang Zhewei , Li Xuejing , Wang Shengjin
Published: July 2023

Recent meta-learning models often learn priors from observed tasks using a network optimized via stochastic gradient descent (SGD), which usually takes more training steps to convergence. In this paper, we propose an accelerated Bayesian meta-learning structure with a stochastic inference network (ABML-SIN). The proposed model aims to solve the training procedure of Bayesian meta-learning to improve the training speed and efficiency. Current approaches of meta-learning hardly converge within a few descent steps, owing to the small number of training samples. Therefore, we introduce an accelerated gradient descent learning network based on teacher–student architecture to learn the meta-latent variable θt for task t. With this amortized fast inference network, the meta-learner is able to learn the task-specific latent θt within a few training steps; thus, it improves the learning speed of the meta-learner. To refine the latent variables generated from the transductive amortization network of the meta-learner, SIN—followed by a conventional SGD-optimized network—is introduced as the student–teacher network to online-update the parameters. SIN extracts the local latent variables and accelerates the convergence of the meta-learning network. Our experiments on simulation data demonstrate that the proposed method provides generalization and scalability on unseen samples, and produces competitive/superior uncertainty estimations on few-shot learning tasks on two widely adopted 2D datasets with fewer training epochs compared to the state-of-the-art meta-learning approaches. Furthermore, the parameters generated by SIN act as perturbations on latent weights, enhancing the probability of accelerating the training efficiency of the meta-learner. Extensive qualitative experiments show that our method performs well across different meta-learning tasks in both simulated and real-world circumstances.
Influence of the Sphericity Coefficient on the Deposition Characteristics of Aerosol Particles on the Surface of Photovoltaic (PV) Modules: Numerical Simulation
Authors: Wei Chuan , Wang Yahui , Qiu Yunfeng , Guo Xiao
Published: July 2023

The deposition of aerosol particles has a significant impact on the output capacity of photovoltaic modules. Therefore, studying the deposition characteristics of aerosol particles on photovoltaic modules is of great importance for improving their output capacity. Particle morphology is one of the important parameters affecting the deposition characteristics of aerosol particles. This study introduces the spherical coefficient as a quantification method for characterizing the morphology of aerosol particles. Numerical simulations using FLUENT 2022 software were conducted to investigate the influence of the spherical coefficient on the deposition characteristics of aerosol particles on photovoltaic modules. The reliability of the numerical simulations was further validated through experimental studies. Based on the research, the following conclusions can be drawn: the airflow velocity near the surface of the photovoltaic panel increases from bottom to top, with the lowest wind speed recorded near the ground at a minimum value of 2.2 m/s and a maximum value of 3.89 m/s. The air pressure near the surface of the photovoltaic panel shows a decreasing trend from bottom to top, with the highest pressure recorded near the ground at a maximum value of 10 pa and a minimum value ranging from 3.33~5.56 pa. During the deposition process, the accumulation of particles increases with an increase in the sphericity factor. Furthermore, as the sphericity factor gradually increases, the distribution of particles on the surface of the photovoltaic panel becomes more dispersed, covering the entire surface.
Horizontally Layered and Vertically Encased Geosynthetic Reinforced Stone Column: An Experimental Analysis
Authors: Srijan  , Gupta Ashok Kumar
Published: July 2023

Because of the smaller confinement of the neighbouring soil in very weak soils, the carrying capacity of stone columns may not substantially increase. Geosynthetics can be used to reinforce columns by employing vertical encasement or horizontal layers. In the present study, large-scale laboratory investigations were carried out to evaluate the efficacy of vertical encasement and horizontal layering geosynthetics on the performance behaviour of soft clay. A series of tests were carried out for a horizontal layering of a geotextile with an equal distance throughout the height of the column (the total height of the column is ‘L’); horizontal layering over only the top half (i.e., 0.5 L from the head of the considered column); and horizontal layering over only the bottom half of the column (0.5 L from the centre to the foot of the column). Tests were also carried out for vertical encasement in the form of vertically encased stone columns (VESCs) that were employed for various lengths of encasement (i.e., L, 0.75 L, 0.5 L, 0.25 L). The tests were conducted for three different diameters of stone columns, i.e., 50 mm, 75 mm, and 100 mm. As per the findings, the utilisation of horizontal and vertical reinforcing layers enhances the carrying capability of stone columns. Moreover, because of their interlocking and frictional actions with the aggregates of stone columns, the layering decreases the lateral bulging of the considered stone columns. A comparison was performed to find the effectiveness of the horizontal and vertical types of reinforcement, and it was observed that VESCs with full-length encasement and a geotextile with a higher tensile strength for a 100 mm diameter of the stone column were the most desirable arrangements among all.
Evaluating the Effect of Road Surface Potholes Using a Microscopic Traffic Model
Authors: Ali Faryal , Khan Zawar Hussain , Khattak Khurram Shehzad , Gulliver Thomas Aaron
Published: July 2023

Road surface wear leads to the formation of cracks and holes known as potholes. Potholes disrupt the smooth flow of traffic and can lead to accidents. The Intelligent Driver (ID) model is commonly employed but it assumes uniform traffic behavior for all conditions. This oversimplified approach is unrealistic as it does not consider the impact of real-world factors such as potholes on traffic patterns. This paper proposes a microscopic traffic model to address the impact of these road surface irregularities on traffic. The effect of small, medium, and large conical potholes is investigated using fundamental diagrams for traffic flow and velocity. The results obtained indicate that the proposed model outperforms the ID model as it can more accurately characterize how potholes and driver sensitivity affect vehicle behavior.
Classification of Human Motion Data Based on Inertial Measurement Units in Sports: A Scoping Review
Authors: Kranzinger Christina , Bernhart Severin , Kremser Wolfgang , Venek Verena , Rieser Harald , Mayr Sebastian , Kranzinger Stefan
Published: July 2023

Inertial measurement units (IMU) are widely used in sports applications to digitise human motion by measuring acceleration and rotational velocity in three-dimensional space. A common machine learning problem is the classification of human motion primitives from IMU data. In order to investigate the classification methods used in the existing literature and to analyse whether and how the time-dependent data structure is considered in the classification process of motion data analysis in sports, a scoping review was conducted. Based on a keyword search, articles from 2010 to 2021 were extracted, and 93 articles were relevant for data extraction. Over- and undersampling of data and data augmentation techniques were rarely used. The classification methods applied can be divided into three main branches: classic machine learning and deep learning models, threshold-based approaches, and dynamic time warping. The most often applied algorithms were support vector machines (SVM), followed by neural networks and k-nearest neighbours. In comparative works, when more than one classifier was applied, random forests, neural networks, boosting models and SVM were found to be the methods that achieved the highest accuracy. If the time-dependent data structure was taken into account, it was incorporated either within the models, for example, by using long-short-term memory models or within the feature calculation step by using rolling windows with an overlap, which was the most common method of considering the time dependency of the IMU data.
Remote Sensing Image Target Detection Method Based on Refined Feature Extraction
Authors: Tian Bo , Chen Hui
Published: July 2023

To address the challenges posed by the large scale and dense distribution of small targets in remote sensing images, as well as the issues of missed detection and false detection, this paper proposes a one-stage target detection algorithm, DCN-YOLO, based on refined feature extraction techniques. First, we introduce DCNv2 and a residual structure to reconstruct a new backbone network, which enhances the extraction of shallow feature information and improves the network’s accuracy. Then, a novel feature fusion module is employed in the neck network to adaptively adjust the fusion weight for integrating texture information from shallow features with deep semantic information. This targeted approach effectively suppresses noise caused by extracting shallow features and enhances the representation of key features. Moreover, the normalized Gaussian Wasserstein distance loss, replacing Intersection over Union (IoU), is used as the regression loss function in the model, to enhance the detection capability of multi-scale targets. Finally, comparing our evaluations against recent advanced methods such as YOLOv7 and YOLOv6 demonstrates the effectiveness of the proposed approach, which achieves an average accuracy of 20.1% for small targets on the DOTAv1.0 dataset and 29.0% on the DIOR dataset.
Prototype Results of an Internet of Things System Using Wearables and Artificial Intelligence for the Detection of Frailty in Elderly People
Authors: Ciubotaru Bogdan-Iulian , Sasu Gabriel-Vasilică , Goga Nicolae , Vasilățeanu Andrei , Marin Iuliana , Goga Maria , Popovici Ramona , Datta Gora
Published: July 2023

As society moves towards a preventative approach to healthcare, there is growing interest in scientific research involving technology that can monitor and prevent adverse health outcomes. The primary objective of this paper is to develop an Internet of Things (IoT) wearable system based on Fried’s phenotype that is capable of detecting frailty. To determine user requirements, the system’s architecture was designed based on the findings of a questionnaire administered to individuals confirmed to be frail. A functional prototype was successfully developed and tested under real-world conditions. This paper introduces the methodology that was used to analyze the data collected from the prototype. It proposes an interdisciplinary approach to interpret wearable sensor data, providing a comprehensive overview through both visual representations and computational analyses facilitated by machine learning models. The findings of these analyses offer insights into the ways in which different types of activities can be classified and quantified as part of an overall physical activity level, which is recognized as an important indicator of frailty. The results provide the foundations for a new generation of affordable and non-intrusive systems able to detect and assess early signs of frailty.
Modelling and Predicting the Growth of Escherichia coli and Staphylococcus aureus in Co-Culture with Geotrichum candidum and Lactic Acid Bacteria in Milk
Authors: Ačai Pavel , Koňuchová Martina , Valík Ľubomír
Published: July 2023

The growth of two pairs of co-cultures (Escherichia coli/Geotrichum candidum and Staphylococcus aureus/Geotrichum candidum) with a starter culture of lactic acid bacteria was studied in milk at temperatures ranging from 15 °C to 21 °C, related to the ripening of artisanal cheese. For an inoculum of approximately 106 CFU/mL, LAB not only induced an early stationary phase of E. coli (two isolates BR and PS2) and S. aureus (isolates 2064 and 14733) but also affected their death phase. In co-cultures with LAB and G. candidum, the numbers of E. coli and S. aureus increased in 2 logs and 1 log, respectively, reaching maximum population densities (MPDs) of less than 5 and 4 logs, respectively. After that, the populations of both bacteria represented with two isolates decreased in more than 2 logs and 3 logs within 2 days compared to their MPDs, respectively. G. candidum was found to be the subject of interactions with LAB within a given temperature range only partially. To develop a tertiary model for the growth curves of the populations, a one-step approach was used, combining the Huang-Gimenez and Dalgaard primary model with secondary square-root models for growth rate and lag time. Furthermore, the reparametrized Gompertz-inspired function with the Bigelow secondary model was used to describe the death phase of the E. coli and S. aureus isolates. The prediction ability of the growth of the H-GD tertiary model for co-cultures was cross-validated within the isolates and datasets in milk and milk medium with 1% NaCl. The study can be used as knowledge support for the hygiene guidelines of short-ripened raw milk cheeses, as was our case in Slovakia.
Evaluation of Mechanical Performance of a New Disc Spring-Cable Counter Pressure Shock Absorber
Authors: Wang Yanfeng , Wu Xiaohui , Ji Shaofeng , Xiao Faping , Wang Dayang
Published: July 2023

Mechanical performance evaluation of a new disc spring-cable counter pressure shock absorber is focused on in this study. The proposed shock absorber is always in a compressive working state with energy dissipation capacity under both tension and compression loadings. The design formulas of its axial bearing capacity, vertical stiffness, deformation energy of the shock absorber were derived, and the corresponding specific design process was provided in detail. Experimental and numerical investigations of the mechanical performance were conducted under static and dynamic loadings. The parameters influencing the laws of the mechanical performance of the shock absorber, including loading frequency, pre-compression deformation and loading amplitude, were investigated. The rationality of the proposed shock absorber was firstly verified through comparative analysis using experimental, numerical and theoretical calculations. The shock absorber with a friction coefficient of 0.005 between disc springs, and a friction coefficient of 0.3 between the disc spring and cover plate has the smallest error between experiment and theory for the flattening force. The bearing capacity of the shock absorber exhibits a linear relationship with the loading displacement in static loading. In dynamic loading, however, the bearing capacity shows a trend of slow growth followed by rapid growth. The energy dissipation capacity of the shock absorber shows an increase with the increase of loading displacement. The minimum equivalent damping ratio of all of the dynamic test cases is 7%, with a maximum up to 15.3%. Under the same loading frequency, the equivalent stiffness and equivalent damping ratio have a linear amplification trend with the increase of pre-compression deformation, and the maximum increase of equivalent stiffness is equal to 41.37%. Under the same loading frequency and pre-compression deformation, the energy consumption capacity can be improved by increasing the loading amplitude.
The Role of Decision-Making Styles in Shaping Cybersecurity Compliance Behavior
Authors: Duzenci Ahmet , Kitapci Hakan , Gok Mehmet Sahin
Published: July 2023

The growing number of attacks on crucial cyber networks is one of humanity’s most significant security threats. Combining technological solutions with the convenient cybersecurity behavior of the human factor is necessary to reduce the effects of these attacks. In this study, the impact of individual decision-making styles on cybersecurity compliance behavior was examined. A conceptual framework was developed based on the protective motivation theory, and it was tested with a data set representing the survey results of 668 employees and students with work experience. Regression analyses were performed to evaluate the impacts of individuals’ decision-making styles on cybersecurity compliance behaviors. Results showed that the decision-making styles of individuals affected their cybersecurity compliance behaviors, and these effects showed significant differences according to their decision-making styles. The study also confirmed that security awareness was another important indicator of cybersecurity compliance behavior. Our research provided new insight into the effects of individual decision-making styles on cybersecurity compliance behavior.
Listeners’ Spectral Reallocation Preferences for Speech in Noise
Authors: Simantiraki Olympia , Cooke Martin
Published: July 2023

Modifying the spectrum of recorded or synthetic speech is an effective strategy for boosting intelligibility in noise without increasing the speech level. However, the wider impact of changes to the spectral energy distribution of speech is poorly understood. The present study explored the influence of spectral modifications using an experimental paradigm in which listeners were able to adjust speech parameters directly with real-time audio feedback, allowing the joint elicitation of preferences and word recognition scores. In two experiments involving full-bandwidth and bandwidth-limited speech, respectively, listeners adjusted one of eight features that altered the speech spectrum, and then immediately carried out a sentence-in-noise recognition task at the chosen setting. Listeners’ preferred adjustments in most conditions involved the transfer of speech energy from the sub-1 kHz region to the 1–4 kHz range. Preferences were not random, even when intelligibility was at the ceiling or constant across a range of adjustment values, suggesting that listener choices encompass more than a desire to maintain comprehensibility.
Mesospheric Ozone Depletion Depending on Different Levels of Geomagnetic Disturbances and Seasons
Authors: Mironova Irina , Grankin Dmitry , Rozanov Eugene
Published: July 2023

Energetic electron precipitation (EEP) into the atmosphere are considered to play an important role in the natural forcing of the ozone variability and dynamics of the middle atmosphere during magnetospheric and geomagnetic disturbances. Energetic electrons from the radiation belt spill out into the atmosphere during geomagnetic disturbances and cause additional ionization rates in the polar middle atmosphere. These rates of induced atmospheric ionization lead to the formation of radicals in ion-molecular reactions at the heights of the mesosphere with the formation of reactive compounds of odd nitrogen groups NOy and odd hydrogen groups HOx. These compounds are involved in catalytic reactions that destroy ozone. The percentage of ozone destruction can depend not only intensity of EEP but also on season where it happens. In this work, we study mesospheric ozone depletion depending on seasons and precipitating energetic electrons with energies from keV up to relativistic energies about 1 MeV, based on the NOAA POES satellites observations in 2003. For estimation ozone deplation we use a one-dimensional radiative-convective model with ion chemistry. As one of the main results, we show that, despite the intensity of EEP-induced ionization rates, polar mesospheric ozone cannot be destroyed by EEP in summer in the presence of UV radiation. In winter time, the maximum ozone depletion, at altitude of about 80 km, can reach up to 80% during strong geomagnetic disturbances. In fall and spring, the maximum ozone depletion is less intense and can reach 20% during strong geomagnetic disturbances. Linear relation of EEP induced maximum mesospheric ozone depletion depending on geomagnetic disturbances and seasons have been obtained.
Characteristics and Establishment of Objective Identification Criteria and Predictors for Foehn Winds in Urumqi, China
Authors: Ayitikan Maoling , Li Xia , He Qing , Musha Yusufu , Tang Hao , Li Shuting , Zhong Yuting , Ren Gang
Published: July 2023

The special terrain of Urumqi (in the valley area) often triggers strong foehn winds, causing huge losses to local people’s lives and social economies. By using the surface observation data of the hourly temperature, pressure, humidity, and wind from the downwind Urumqi Meteorological Station and the upwind Dabancheng Meteorological Station in the Middle Tianshan Canyon and the NCEP/NCAR reanalysis data during 2008–2022, this paper establishes the dataset of foehn processes at Urumqi Station in the past 15 years and analyzes the variation rules of the associated meteorological variables during the foehn processes. In addition, based on the physical mechanism of the occurrence of foehn, a three-element identification criterion (i.e., 94° ≤ 2 min average wind direction ≤ 168°, 2 min average wind speed ≥ 2.0 m/s, and Δθ between Urumqi station and Dabancheng station ≥ 0.29 K) for foehn in Urumqi is established by comparing and analyzing the variations of wind direction (WD), wind speed (WS), and the potential temperature difference (Δθ) between the two weather stations during the periods of foehn and non-foehn winds from 2013 to 2022. In addition, the performance of the three-element identification criterion is verified, and the results suggest that this criterion has an accuracy of 82.96% and a hit rate of 89.50% for the 2008–2012 foehn events in Urumqi. Moreover, the hit rate of this criterion for foehn wind of gale or above level (i.e., a 2 min wind ≥ 10.8 m/s on average) is 100%. In addition, combined with two predictors of sea-level pressure difference (ΔP) and Δθ between downwind stations and upwind stations, the foehn forecast can be more accurate than that provided by a single predictor. With ΔP ≤ −12 hPa and Δθ ≥ 5 K, the chances for foehn to occur are over 90%. This finding would have some reference and application values for the foehn forecasting.
PWV Inversion Model Based on Random Forest and the Trend of Its Conversion Rate with Precipitation in Hubei from 1960 to 2020
Authors: Xiong Zhaohui , Long Sichun , Liu Maoqi , Wu Wenhao , Kuang Lijun , Lai Xiangen
Published: July 2023

In the context of anomalous global climate change and the frequent occurrence of droughts and floods, studying trends in the conversion rate between precipitable water vapor (PWV) and actual precipitation in a certain region can help in analyzing the causes of these natural disasters. This paper examines the variation trend in the conversion rate between PWV and actual precipitation on a monthly scale in Hubei from 1960 to 2020. To estimate historical PWV data, we propose a new method for estimating PWV using water vapor pressure based on the RF algorithm. The new method was evaluated by radiosonde data and improved the accuracy by 1 mm over the traditional method in Hubei. Based on this method, we extrapolate the monthly average PWV in Hubei from 1960 to 2020 and analyze the conversion rate between PWV and precipitation during this period. Our results showed that there was no obvious cyclical pattern in the conversion rate in either the longitude or latitude directions. In Hubei, where the topography varies significantly in the longitude direction, the conversion rate is influenced by topography, with the smallest conversion rate being in the transition zone between the mountainous region of western Hubei and the Jianghan Plain. In the latitudinal direction, the conversion rate decreases with increasing latitude.
Enhancing Contractor Selection Process by a New Interval-Valued Fuzzy Decision-Making Model Based on SWARA and CoCoSo Methods
Authors: Karami Sajjad , Mousavi Seyed Meysam , Antucheviciene Jurgita
Published: July 2023

Contractor selection is a crucial aspect of construction projects, with a significant impact on project success. However, traditional methods may not effectively handle the complexities and uncertainties involved in decision-making. To address this, advanced techniques like Multi-Criteria Decision-Making (MCDM) have been developed. In this study, we propose a new approach based on two uncertain methods, Interval-Valued Fuzzy Step-Wise Weight Assessment Ratio Analysis (IVF-SWARA) and Interval-Valued Fuzzy Combined Compromise Solution (IVF-CoCoSo), for contractor selection in construction projects. These methods use interval-valued fuzzy numbers (IVFNs) to handle decision-making under uncertainty and imprecision. By leveraging the benefits of IVFNs, the proposed methods enhance accuracy and flexibility, enabling more informed and reliable decisions. An application example illustrates the effectiveness of the methods, and sensitivity analysis examines how varying criteria weights affect contractor rankings. The study concludes that the IVF-SWARA and IVF-CoCoSo methods assist decision-makers in selecting suitable contractors and achieving project success. These methods provide a robust framework to navigate complexities and uncertainties, leading to improved decision-making in contractor selection for construction projects.
Sugeno Integral Based on Overlap Function and Its Application to Fuzzy Quantifiers and Multi-Attribute Decision-Making
Authors: Mao Xiaoyan , Temuer Chaolu , Zhou Huijie
Published: July 2023

The overlap function is an important class of aggregation function that is closely related to the continuous triangular norm. It has important applications in information fusion, image processing, information classification, intelligent decision-making, etc. The usual multi-attribute decision-making (MADM) is to select the decision object that performs well on all attributes (indicators), which is quite demanding. The MADM based on fuzzy quantifiers is to select the decision object that performs well on a certain proportion or quantification (such as most, many, more than half, etc.) of attributes. Therefore, it is necessary to study how to express and calculate fuzzy quantifiers such as most, many, etc. In this paper, the Sugeno integral based on the overlap function (called the O-Sugeno integral) is used as a new information fusion tool, and some related properties are studied. Then, the truth value of a linguistic quantified proposition can be estimated by using the O-Sugeno integral, and the O-Sugeno integral semantics of fuzzy quantifiers is proposed. Finally, the MADM method based on the O-Sugeno integral semantics of fuzzy quantifiers is proposed and the feasibility of our method is verified by several illustrative examples such as the logistics park location problem.
An Extended AHP-Based Corpus Assessment Approach for Handling Keyword Ranking of NLP: An Example of COVID-19 Corpus Data
Authors: Chen Liang-Ching , Chang Kuei-Hu
Published: July 2023

The use of corpus assessment approaches to determine and rank keywords for corpus data is critical due to the issues of information retrieval (IR) in Natural Language Processing (NLP), such as when encountering COVID-19, as it can determine whether people can rapidly obtain knowledge of the disease. The algorithms used for corpus assessment have to consider multiple parameters and integrate individuals’ subjective evaluation information simultaneously to meet real-world needs. However, traditional keyword-list-generating approaches are based on only one parameter (i.e., the keyness value) to determine and rank keywords, which is insufficient. To improve the evaluation benefit of the traditional keyword-list-generating approach, this paper proposed an extended analytic hierarchy process (AHP)-based corpus assessment approach to, firstly, refine the corpus data and then use the AHP method to compute the relative weights of three parameters (keyness, frequency, and range). To verify the proposed approach, this paper adopted 53 COVID-19-related research environmental science research articles from the Web of Science (WOS) as an empirical example. After comparing with the traditional keyword-list-generating approach and the equal weights (EW) method, the significant contributions are: (1) using the machine-based technique to remove function and meaningless words for optimizing the corpus data; (2) being able to consider multiple parameters simultaneously; and (3) being able to integrate the experts’ evaluation results to determine the relative weights of the parameters.
Partial Oxidation Synthesis of Prussian Blue Analogues for Thermo-Rechargeable Battery
Authors: Moritomo Yutaka , Sarukura Masato , Iwaizumi Hiroki , Nagai Ichiro
Published: July 2023

A thermo-rechargeable battery or tertiary battery converts thermal energy into electric energy via an electrochemical Seebeck coefficient. The manufacturing of the tertiary batteries requires a pre-oxidation step to align and optimize the cathode and anode potentials. The pre-oxidation step, which is not part of the secondary battery manufacturing process, makes the manufacturing of tertiary batteries complex and costly. To omit the pre-oxidation step, we used partially oxidized Prussian blue analogs, i.e., NaxCo[Fe(CN)6]yzH2O (Co-PBA) and NaxNi[Fe(CN)6]yzH2O (Ni-PBA), as cathode and anode materials. The modified tertiary battery without the pre-oxidation step shows good thermal cyclability between 10 ∘C and 50 ∘C without detectable deterioration of the thermal voltage (Vcell) and discharge capacity (Qcell).
Administration of Collagen Peptide Prevents the Progression of Pulmonary Fibrosis in Bleomycin-Treated Mice
Authors: Yoshihara Minami , Asatsuma Chisaki , Masuko Ayuna , Iwaasa Keiya , Saito-Matsuzawa Yuki , Sone Hideyuki , Kamiyama Shin
Published: July 2023

Collagen peptides (CPs) are food-derived peptides that possess a variety of bioactive properties. Our study investigates the effects of CP on pulmonary fibrosis in bleomycin (BLM)-treated mice. C57BL/6J mice were subcutaneously injected with BLM for two weeks followed by a three-week experimental diet containing 25 mg/g of CP derived from chicken feet. Supplementation with CP suppressed the increase in lung weight and disruption of lung architecture observed in mice treated with BLM. BLM-treated mice also exhibited higher hydroxyproline content and increased expression levels of type I and III collagen subunit genes in the lungs. CP supplementation exerted no effect on these collagen-related factors; however, it significantly suppressed the gene expression of fibronectin and inflammation-related molecules in the lungs of BLM-treated mice. These findings suggest that CP administration prevents the development of pulmonary fibrosis by acting as an anti-inflammatory agent.
Advances in Metabolic Engineering of Plant Monoterpene Indole Alkaloids
Authors: Salim Vonny , Jarecki Sara-Alexis , Vick Marshall , Miller Ryan
Published: July 2023

Monoterpene indole alkaloids (MIAs) encompass a diverse family of over 3000 plant natural products with a wide range of medical applications. Further utilizations of these compounds, however, are hampered due to low levels of abundance in their natural sources, causing difficult isolation and complex multi-steps in uneconomical chemical syntheses. Metabolic engineering of MIA biosynthesis in heterologous hosts is attractive, particularly for increasing the yield of natural products of interest and expanding their chemical diversity. Here, we review recent advances and strategies which have been adopted to engineer microbial and plant systems for the purpose of generating MIAs and discuss the current issues and future developments of manufacturing MIAs by synthetic biology approaches.
Identification of Two Subsets of Subcompartment A1 Associated with High Transcriptional Activity and Frequent Loop Extrusion
Authors: Yin Zihang , Cui Shuang , Xue Song , Xie Yufan , Wang Yefan , Zhao Chengling , Zhang Zhiyu , Wu Tao , Hou Guojun , Wang Wuming , Xie Sheila Q. , Wu Yue , Guo Ya
Published: July 2023

Three-dimensional genome organization has been increasingly recognized as an important determinant of the precise regulation of gene expression in mammalian cells, yet the relationship between gene transcriptional activity and spatial subcompartment positioning is still not fully comprehended. Here, we first utilized genome-wide Hi-C data to infer eight types of subcompartment (labeled A1, A2, A3, A4, B1, B2, B3, and B4) in mouse embryonic stem cells and four primary differentiated cell types, including thymocytes, macrophages, neural progenitor cells, and cortical neurons. Transitions of subcompartments may confer gene expression changes in different cell types. Intriguingly, we identified two subsets of subcompartments defined by higher gene density and characterized by strongly looped contact domains, named common A1 and variable A1, respectively. We revealed that common A1, which includes highly expressed genes and abundant housekeeping genes, shows a ~2-fold higher gene density than the variable A1, where cell type-specific genes are significantly enriched. Thus, our study supports a model in which both types of genomic loci with constitutive and regulatory high transcriptional activity can drive the subcompartment A1 formation. Special chromatin subcompartment arrangement and intradomain interactions may, in turn, contribute to maintaining proper levels of gene expression, especially for regulatory non-housekeeping genes.
Evaluation of Acute and Sub-Acute Toxicity, Oxidative Stress and Molecular Docking of Two Nitrofuranyl Amides as Promising Anti-Tuberculosis Agents
Authors: Dimitrov Simeon , Slavchev Ivaylo , Simeonova Rumyana , Mileva Milka , Pencheva Tania , Philipov Stanislav , Georgieva Almira , Tsvetanova Elina , Teneva Yoanna , Rimpova Nadezhda , Dobrikov Georgi , Valcheva Violeta
Published: July 2023

Tuberculosis (TB) remains a widespread infectious disease and one of the top 10 causes of death worldwide. Nevertheless, despite significant advances in the development of new drugs against tuberculosis, many therapies and preventive measures do not lead to the expected favorable health results for various reasons. The aim of this study was to evaluate the acute and sub-acute toxicity and oxidative stress of two selected nitrofuranyl amides with high in vitro antimycobacterial activity. In addition, molecular docking studies were performed on both compounds to elucidate the possibilities for further development of new anti-tuberculosis candidates with improved efficacy, selectivity, and pharmacological parameters. Acute toxicity tests showed that no changes were observed in the skin, coat, eyes, mucous membranes, secretions, and vegetative activity in mice. The histological findings include features consistent with normal histological architecture without being associated with concomitant pathological conditions. The observed oxidative stress markers indicated that the studied compounds disturbed the oxidative balance in the mouse liver. Based on the molecular docking, compound DO-190 showed preferable binding energies compared to DO-209 in three out of four targets, while both compounds showed promising protein–ligand interactions. Thus, both studied compounds displayed promising activity with low toxicity and can be considered for further evaluation and/or lead optimization.
S100s and HMGB1 Crosstalk in Pancreatic Cancer Tumors
Authors: Mandarino Angelo , Thiyagarajan Swetha , Martins Allana C. F. , Gomes Roberto da Silva , Vetter Stefan W. , Leclerc Estelle
Published: July 2023

Pancreatic cancer remains a disease that is very difficult to treat. S100 proteins are small calcium binding proteins with diverse intra- and extracellular functions that modulate different aspects of tumorigenesis, including tumor growth and metastasis. High mobility group box 1 (HMGB1) protein is a multifaceted protein that also actively influences the development and progression of tumors. In this study, we investigate the possible correlations, at the transcript level, between S100s and HMGB1 in pancreatic cancer. For this purpose, we calculated Pearson’s correlations between the transcript levels of 13 cancer-related S100 genes and HMGB1 in a cDNA array containing 19 pancreatic cancer tumor samples, and in 8 human pancreatic cancer cell lines. Statistically significant positive correlations were found in 5.5% (5 out of 91) and 37.4% (34 of 91) of the possible S100/S100 or S100/HMGB1 pairs in cells and tumors, respectively. Our data suggest that many S100 proteins crosstalk in pancreatic tumors either with other members of the S100 family, or with HMGB1. These newly observed interdependencies may be used to further the characterization of pancreatic tumors based on S100 and HMGB1 transcription profiles.
The Role of Oxidative Stress in Manganese Neurotoxicity: A Literature Review Focused on Contributions Made by Professor Michael Aschner
Authors: Dorman David C.
Published: July 2023

This literature review focuses on the evidence implicating oxidative stress in the pathogenesis of manganese neurotoxicity. This review is not intended to be a systematic review of the relevant toxicologic literature. Instead, in keeping with the spirit of this special journal issue, this review highlights contributions made by Professor Michael Aschner’s laboratory in this field of study. Over the past two decades, his laboratory has made significant contributions to our scientific understanding of cellular responses that occur both in vitro and in vivo following manganese exposure. These studies have identified molecular targets of manganese toxicity and their respective roles in mitochondrial dysfunction, inflammation, and cytotoxicity. Other studies have focused on the critical role astrocytes play in manganese neurotoxicity. Recent studies from his laboratory have used C. elegans to discover new facets of manganese-induced neurotoxicity. Collectively, his body of work has dramatically advanced the field and presents broader implications beyond metal toxicology.
Renin–Angiotensin System Components and Arachidonic Acid Metabolites as Biomarkers of COVID-19
Authors: Ghimire Biwash , Pour Sana Khajeh , Middleton Elizabeth , Campbell Robert A. , Nies Mary A. , Aghazadeh-Habashi Ali
Published: July 2023

Through the ACE2, a main enzyme of the renin–angiotensin system (RAS), SARS-CoV-2 gains access into the cell, resulting in different complications which may extend beyond the RAS and impact the Arachidonic Acid (ArA) pathway. The contribution of the RAS through ArA pathways metabolites in the pathogenesis of COVID-19 is unknown. We investigated whether RAS components and ArA metabolites can be considered biomarkers of COVID-19. We measured the plasma levels of RAS and ArA metabolites using an LC-MS/MS. Results indicate that Ang 1–7 levels were significantly lower, whereas Ang II levels were higher in the COVID-19 patients than in healthy control individuals. The ratio of Ang 1–7/Ang II as an indicator of the RAS classical and protective arms balance was dramatically lower in COVID-19 patients. There was no significant increase in inflammatory 19-HETE and 20-HETE levels. The concentration of EETs was significantly increased in COVID-19 patients, whereas the DHETs concentration was repressed. Their plasma levels were correlated with Ang II concentration in COVID-19 patients. In conclusion, evaluating the RAS and ArA pathway biomarkers could provide helpful information for the early detection of high-risk groups, avoid delayed medical attention, facilitate resource allocation, and improve patient clinical outcomes to prevent long COVID incidence.
Reversible Effects of Functional Mandibular Lateral Shift on Masticatory Muscles in Growing Rats
Authors: Guan Hao , Yonemitsu Ikuo , Ikeda Yuhei , Ono Takashi
Published: July 2023

In this study, we aimed to determine the effects of functional mandibular lateral shift (FMLS) on the muscle mass, fiber size, myosin heavy chain fiber type, and related gene expression in masticatory muscles (masseter and temporalis), as well as whether the baseline levels could be recovered after FMLS correction in growing rats. The FMLS appliance was placed to shift the mandible leftward by approximately 2 mm. After FMLS placement for 2 and 4 weeks, the muscles on the left side had significantly lower wet weight, mean cross-sectional area, and proportion of type IIa fibers than those on the right side or in the control groups (p < 0.05), with downregulation and upregulation of IGF-1 and GDF-8 gene expression, respectively (p < 0.05). Following 2 weeks devoted to recovery from FMLS, the muscle parameters in the recovery group were not significantly different to those of the control group, and IGF-1 expression in the left-side muscles was enhanced and GDF-8 expression was simultaneously suppressed. These findings indicate that the masticatory muscle changes induced via FMLS tend to revert to normal conditions if the intervention is eliminated at an early stage. Therefore, appropriate orthodontic treatment for FMLS during the growth period is advisable to prevent asymmetric alterations in masticatory muscles.