bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Study on Flexural Properties of Polyurethane–Cement Composites under Temperature Load
Authors: Li Bochen , Liu Hongbo , Jian Jiashuo , Duan Hourui , Gao Hongshuai
Published: December 2022

Polyurethane cement composite is a new organic–inorganic composite material with high strength, corrosion resistance, and fast curing. It is a complement and alternative to traditional cement materials. The flexural properties of polyurethane cement composites are the basic mechanical index of the material. In order to study the flexural properties under different temperature loads, a molecular model was established, the chemical reaction process of polyurethane cement and the temperature response mechanism was analyzed, and the preparation process of polyurethane cement was proposed. Then, bending tests were carried out in strain-controlled mode to obtain the specimens’ bending strength and stiffness modulus under different temperature loads. The test results showed that the tensile strength of polyurethane cement decreased first, then increased, and finally decreased with the increase in temperature, while the bending stiffness modulus decreased with the increase in temperature. Combined with the theoretical derivation, the damage mode of the samples under different temperature loads was analyzed, and the “L-type” damage strain curve was obtained. The results showed that the proposed theory could effectively explain the mechanism of action and flexural properties of polyurethane cement composites under temperature loading, which is a significant improvement to the application of polyurethane cement composites in practical engineering.
Study on Fire Smoke Distribution and Safety Evacuation of Subway Station Based on BIM
Authors: Zhang Nian , Liang Yan , Zhou Caifeng , Niu Mengmeng , Wan Fei
Published: December 2022

A subway station is a confined space, so it is very important to evacuate people safely in case of a fire. It is necessary to study and analyze the smoke distribution and evacuation ability of different station layout schemes when fire occurs. Taking a subway station as an example, this paper combines BIM (Building Information Model) technology with the fire safety evacuation of the subway station. First, we optimize the layout of the public area of the subway station and use BIM technology to establish a subway station model. Then, we use the PyroSim software to establish a subway station fire model to analyze fire development in different locations of the station in the optimization scheme, and determine the time it takes for CO concentration, smoke temperature and visibility to reach the critical value of danger. Finally, a subway station fire evacuation model is established using the Pathfinder software to study the safety evacuation of people in the subway station fire. The results show that it takes the shortest time for the visibility in the station to reach the critical value under fire conditions, and the threat to safety evacuation is the greatest. The available safe evacuation time of the optimized subway station is greater than the required safe evacuation time under different fire conditions, that is, the optimized subway station arrangement can ensure the safety evacuation of the personnel in the subway station under fire conditions. The research results can serve as reference for the optimization of safety evacuation designs of similar subway stations.
High-Tc Superconducting Josephson Junction Harmonic Mixers with Stub Tuners on Integrated Bowtie Antennas
Authors: Yu Mei , Li Chun , Gao Xiang , Wang Zhenguo , Liang Tu-Lu , Shi Jin , Shi Jian-Xin , Xu Weiwei
Published: December 2022

Ordinary mixers can hardly meet the requirements in terahertz (THz) communications due to the low-power and expensive THz sources. Sensitive harmonic mixers have been widely studied to avoid this problem, owing to the fact that the higher the number of harmonics, the lower the local oscillator (LO) frequency, and the lower the cost. High-Tc superconducting (HTS) Josephson junction (JJ) mixers are performing candidates for THz receiver frontends because of the advantages of excellent sensitivity, wide bandwidth, high harmonic number and low LO power requirement. However, the normal-state resistance of HTS JJ is so low that traditional antennas are difficult to match it. In other words, it is quite a challenge to match the input impedance to a low input impedance for traditional antennas, especially for antennas fed by coplanar striplines (CPSs). In this work, based on the structure of bowtie, two types of stub tuners were integrated to decrease the impedance of the bowtie antenna so as to improve the coupling efficiency between the traditional bowtie antenna and the JJ. Furthermore, HTS YBa2Cu3O7-δ (YBCO) JJ harmonic mixers coupled with the proposed structures and fed by CPSs are fabricated and measured. The measurements show that the JJ mixer coupled with a pair of open-end stubs of the bowtie antenna achieves up to 88 harmonics, with a conversion efficiency of −69.6 dB. In contrast, the JJ mixer coupled with a pair of lumped-element stubs of the bowtie antenna only attains to 30 harmonics, with a conversion efficiency of −73.4 dB. Additional numerical simulations indicate that the coupling efficiency is enhanced when the complex impedance of the antenna is explicitly considered. Compared with other coupled traditional antennas, the JJ mixer with bowtie antenna has the largest harmonic number. This work paves the way for the future application of low-frequency and low-cost LO for THz communications.
A Location–Time-Aware Factorization Machine Based on Fuzzy Set Theory for Game Perception
Authors: Xie Xiaoxia , Jia Zhenhong , Shi Hongzhan , Zhu Xianxing
Published: December 2022

Game user perception is of great significance for game developers and network operators for improving service quality and operational efficiency. At present, the most common approach is to use the linear model that considers only the impact of network factors evaluation on user perception. The interpretation process is complex and useful, but invisible feature interaction data are not taken into account. As a result, user perception evaluation can only be interpreted by experienced experts, which is both time-consuming and laborious. In this paper, aiming at the shortcomings of existing algorithms, a location–time-aware factorization machine model (LTFM) is proposed by exploiting the location projection and time projection of users and services and fuzzy set theory. Our proposed LTFM can be decomposed into two parts: first, an original game quality of experience (QoE) dataset is extended. LTFM uses location and time information to map to latent vectors, which increases the number of records in each game data, involving no additional information. Then, LTFM utilizes fuzzy set theory to strengthen the positive feature interactions and reduce the negative feature interactions. The factorization machine is used to mine a number of potential features in the user’s invoking service behavior. The multiplayer online battle arena (MOBA) game perception dataset is obtained with reference to the ITU-T standard to verify the advanced nature of the proposed model. Experimental results show that LTFM outperforms existing algorithms in terms of prediction accuracy and model interpretability. Not only can accurate user experience quality categories be produced, but also the impact of individual characteristics and their feature interactions can be explained, which helps operators to make better optimization decisions.
Detecting Hateful and Offensive Speech in Arabic Social Media Using Transfer Learning
Authors: Boulouard Zakaria , Ouaissa Mariya , Ouaissa Mariyam , Krichen Moez , Almutiq Mutiq , Gasmi Karim
Published: December 2022

The democratization of access to internet and social media has given an opportunity for every individual to openly express his or her ideas and feelings. Unfortunately, this has also created room for extremist, racist, misogynist, and offensive opinions expressed either as articles, posts, or comments. While controlling offensive speech in English-, Spanish-, and French- speaking social media communities and websites has reached a mature level, it is much less the case for their counterparts in Arabic-speaking countries. This paper presents a transfer learning solution to detect hateful and offensive speech on Arabic websites and social media platforms. This paper will compare the performance of different BERT-based models trained to classify comments as either abusive or neutral. The training dataset contains comments in standard Arabic as well as four dialects. We will also use their English translations for comparative purposes. The models were evaluated based on five metrics: Accuracy, Precision, Recall, F1-Score, and Confusion Matrix.
Mechanical Behaviour of a Metal-CFRP-Hybrid Structure and Its Components under Quasi-Static and Dynamic Load at Elevated Temperature
Authors: Jost Hendrik , Grossmann Felix , Herrmann Hans-Georg
Published: December 2022

Hybrid materials containing a light metal and CFRP are capable to make a relevant contribution in lightweight design and thereby in reducing greenhouse gases causing global warming. An aluminium CFRP-hybrid specimen with a thermoplastic interlayer that is suitable for application for the A-, B-, or C-pillar in a car is investigated in this work regarding the mechanical behaviour due to temperature variation. For this purpose, quasi-static as well as dynamic tensile tests are carried out not only for those hybrid specimens but also for their respective single-material components. Those are supported by various non-destructive testing (NDT) techniques such as thermography and CT-scans of X-ray tomography. The examination of the single materials as well as the hybrid specimens gives us the possibility to understand if a change in the damage process of the hybrid is caused by one of the single materials or the interaction of them. The use of the NDT techniques in combination with the mechanical experiments allows us to obtain a deeper look at the mechanisms causing the respective damage. It stands out that temperature changes affect the damage mechanisms in the hybrid significantly without having great influence on the single materials. In quasistatic testing, the maximum displacement of the hybrid specimens rises at elevated temperature, and in dynamic testing the initial stiffness and the sustained cycles decline significantly. It therefore can be concluded that the interfaces inside the hybrids are affected by temperature changes and play a major role concerning the damage mechanisms. The pure knowledge about the temperature behaviour of single materials is not sufficient for anticipating the behaviour of hybrid specimens under these restrictions.
Automatic Correction of an Automated Guided Vehicle’s Course Using Measurements from a Laser Rangefinder
Authors: Dobrzanska Magdalena , Dobrzanski Pawel
Published: December 2022

In order for AGVs to be able to effectively carry out the tasks assigned to them, it is important to accurately determine their position and orientation in the working space. Having data on the location of an AGV is crucial for the navigation process, and the most commonly used odometry method is unreliable due to errors. To correct these errors, additional measuring systems are used. These systems use a variety of sensors. Some of the most widely used types are laser rangefinders. These sensors are also used in the automatic course correction methodology that is developed and presented in this article. The measurements from laser rangefinders are used to determine the shift of the actual trajectory from the set one, and then to guide the AGV to the previously set course. The developed methodology is experimentally verified on the basis of several dozen test drives. The conducted experimental studies prove the correctness of the developed methodology. The proposed course correction algorithm can be implemented in most working conditions, and guarantees correct passage over the given route.
Modified Barnacles Mating Optimization with Deep Learning Based Weed Detection Model for Smart Agriculture
Authors: Albraikan Amani Abdulrahman , Aljebreen Mohammed , Alzahrani Jaber S. , Othman Mahmoud , Mohammed Gouse Pasha , Ibrahim Alsaid Mohamed
Published: December 2022

Weed control is a significant means to enhance crop production. Weeds are accountable for 45% of the agriculture sector’s crop losses, which primarily occur because of competition with crops. Accurate and rapid weed detection in agricultural fields was a difficult task because of the presence of a wide range of weed species at various densities and growth phases. Presently, several smart agriculture tasks, such as weed detection, plant disease detection, species identification, water and soil conservation, and crop yield prediction, can be realized by using technology. In this article, we propose a Modified Barnacles Mating Optimization with Deep Learning based weed detection (MBMODL-WD) technique. The MBMODL-WD technique aims to automatically identify the weeds in the agricultural field. Primarily, the presented MBMODL-WD technique uses the Gabor filtering (GF) technique for the noise removal process. For automated weed detection, the presented MBMODL-WD technique uses the DenseNet-121 model as feature extraction with the MBMO algorithm as hyperparameter optimization. The design of the MBMO algorithm involves the integration of self-population-based initialization with the standard BMO algorithm. At last, the Elman Neural Network (ENN) method was applied for the weed classification process. To demonstrate the enhanced performance of the MBMODL-WD approach, a series of simulation analyses were performed. A comprehensive set of simulations highlighted the enhanced performance of the presented MBMODL-WD methodology over other DL models with a maximum accuracy of 98.99%.
Evolution of Performance Indicators in Soccer during the Last Decade
Authors: Fernández-Cortés José , Gómez-Ruano Miguel Angel , Mancha-Triguero David , Ibáñez Sergio J. , García-Rubio Javier
Published: December 2022

Due to the worldwide negative impact on sport of the COVID-19 pandemic declared by the WHO in 2020, the first aim of this study was to analyze the influence of COVID-19 on performance indicators as a natural experiment, according to the moment in time: pre-COVID, COVID and post-COVID. The second aim was to analyze and ascertain the persistence of the performance indicators (PIs) over the analyzed seasons. To this end, 5320 teams’ match data corresponding to the 2014/2015 to 2020/2021 seasons of the LaLiga (first division of Spanish men’s soccer) were analyzed. All the seasons developed normally except the 2019/2020 season in which there was a three-month hiatus because of the COVID-19 pandemic, representing a natural experiment without spectators. Statistical tests including ANOVA, general multivariate linear analysis with three independent variables (covidtime, venue and result) and an autocorrelation were performed. The results obtained showed that there were significant differences in the PIs regarding the moment in time, the result, the venue, and the pairwise interactions among them. The evolution of the PIs has changed over the years, showing a decrease in the means of most of them, leading to a more passive game with tighter results; differences which could be generated by the change in the rules (from 3 to 5 substitutions), the total or partial absence of spectators, three months of confinement and inactivity, or the accumulation of matches and minutes played by the individual players. The teams’ technical staffs should bear all of these types of situations in mind as the seasons evolve to adapt as quickly as possible to a more effective game style in order to achieve objectives.
Coincidence Theory of a Nonlinear Periodic Sturm–Liouville System and Its Applications
Authors: Zhao Kaihong
Published: December 2022

Based on the second derivative, this paper directly establishes the coincidence degree theory of a nonlinear periodic Sturm–Liouville (SL) system. As applications, we study the existence of periodic solutions to the S–L system with some special nonlinear functions by applying Mawhin’s continuation theorem. Some examples and simulations are furnished to inspect the correctness and availability of the chief findings.
Parameterized Quantum Fractional Integral Inequalities Defined by Using n-Polynomial Convex Functions
Authors: Liko Rozana , Srivastava Hari Mohan , Mohammed Pshtiwan Othman , Kashuri Artion , Al-Sarairah Eman , Sahoo Soubhagya Kumar , Soliman Mohamed S.
Published: December 2022

Convexity performs the appropriate role in the theoretical study of inequalities according to the nature and behaviour. There is a strong relation between symmetry and convexity. In this article, we consider a new parameterized quantum fractional integral identity. Following that, our main results are established, which consist of some integral inequalities of Ostrowski and midpoint type pertaining to n-polynomial convex functions. From our main results, we discuss in detail several special cases. Finally, an example and an application to special means of positive real numbers are presented to support our theoretical results.
Strategies for Minimizing Charging Time in Commercial Nickel-Rich/Silicon-Graphite Lithium-Ion Batteries
Authors: Alonso-del-Valle Jorge , González Manuela , Viera Juan , Valdés Enrique , García Víctor , Anseán David
Published: December 2022

The emerging nickel-rich/silicon-graphite lithium-ion technology is showing a notable increase in the specific energy, a main requirement for portable devices and electric vehicles. These applications also demand short charging times, while actual charging methods for this technology imply long time or a significant reduction in cycling life. This study analyses the factors that affect the charge behavior for 18,650 commercial nickel-rich/silicon-graphite batteries. For that, long-term cycling tests have been carried out, including electric vehicle standard tests. It can be concluded that this technology has two key issues to develop an efficient charge method: high charge rates should be avoided, mainly below 15% state of charge, and the charge should be finished at 95% of actual cell capacity. This allows that, regardless of application and cell degradation level, cells can be recharged in 2 h without a negative impact on cycling life. For faster charge applications, a new method has been developed to minimize charging time without compromising the cycle life as much as the high current manufacturer method. The proposed fast charge method has proven to be notably faster, recharging in an average 1.3 h (48% less than the high current method and 68% less than the standard method).
Locating Source Code Bugs in Software Information Systems Using Information Retrieval Techniques
Authors: Alawneh Ali , Alazzam Iyad M. , Shatnawi Khadijah
Published: December 2022

Bug localization is the process through which the buggy source code files are located regarding a certain bug report. Bug localization is an overwhelming and time-consuming process. Automating bug localization is the key to help developers and increase their productivities. Expanding bug reports with more semantic and increasing software understanding using information retrieval and natural language techniques will be the way to locate the buggy source code file, in which the bug report works as a query and source code as search space. This research investigates the effect of segmenting open source files into executable code and comments, as they have a conflicting nature, seeks the effect of synonyms on the accuracy of bug localization, and examines the effect of “part-of-speech” techniques on reducing the manual inspection for appropriate synonyms. This research aims to approve that such methods improve the accuracy of bug localization tasks. The used approach was evaluated on three Java open source software, namely Eclipse 3.1, AspectJ 1.0, and SWT 3.1; we implement our dedicated Java tool to adopt our methodology and conduct several experiments on each software. The experimental results reveal a considerable improvement in recall and precision levels, and the developed methods display an accuracy improvement of 4–10% compared with the state-of-the-art approaches.
Contribution of Deep Learning in the Investigation of Possible Dual LOX-3 Inhibitors/DPPH Scavengers: The Case of Recently Synthesized Compounds
Authors: Bakalis Dimitrios , Lambrinidis George , Kourounakis Angeliki , Manis George
Published: December 2022

Even though non-steroidal anti-inflammatory drugs are the most effective treatment for inflammatory conditions, they have been linked to negative side effects. A promising approach to mitigating potential risks, is the development of new compounds able to combine anti-inflammatory with antioxidant activity to enhance activity and reduce toxicity. The implication of reactive oxygen species in inflammatory conditions has been extensively studied, based on the pro-inflammatory properties of generated free radicals. Drugs with dual activity (i.e., inhibiting inflammation related enzymes, e.g., LOX-3 and scavenging free radicals, e.g., DPPH) could find various therapeutic applications, such as in cardiovascular or neurodegenerating disorders. The challenge we embarked on using deep learning was the creation of appropriate classification and regression models to discriminate pharmacological activity and selectivity as well as to discover future compounds with dual activity prior to synthesis. An accurate filter algorithm was established, based on knowledge from compounds already evaluated in vitro, that can separate compounds with low, moderate or high activity. In this study, we constructed a customized highly effective one dimensional convolutional neural network (CONV1D), with accuracy scores up to 95.2%, that was able to identify dual active compounds, being LOX-3 inhibitors and DPPH scavengers, as an indication of simultaneous anti-inflammatory and antioxidant activity. Additionally, we created a highly accurate regression model that predicted the exact value of effectiveness of a set of recently synthesized compounds with anti-inflammatory activity, scoring a root mean square error value of 0.8. Eventually, we succeeded in observing the manner in which those newly synthesized compounds differentiate from each other, regarding a specific pharmacological target, using deep learning algorithms.
Mathematical Model of Blood Circulation with Compression of the Prototype’s Mechanical CPR Waveform
Authors: Xu Xingyuan , Wang Shaoping , Wang Shangyu , Liu Guiling
Published: December 2022

The waveform of chest compressions directly affects the blood circulation of patients with cardiac arrest. Currently, few pieces of research have focused on the influence of the cardiopulmonary resuscitation (CPR) device’s mechanical waveform on blood circulation. This study investigates the effect of the mechanical waveform from a novel CPR prototype on blood circulation and explores the optimal compression parameters of the mechanical waveform to optimize blood circulation. A novel CPR prototype was designed and built to establish a kinetic model during compressions. The prototype’s mechanical waveforms at various operating conditions were obtained for comparison with manual waveforms and the investigation of the optimal compression parameters. The novel CPR prototype can complete chest compressions quickly and stably. The cardiac output (CO), coronary perfusion pressure (CPP), and cerebral flow (CF) obtained by mechanical waveform compressions (1.22367 ± 0.00942 L/min, 30.95083 ± 0.24039 mmHg, 0.31992 ± 0.00343 L/min, respectively) were significantly better than those obtained by manual waveform compressions (1.10783 ± 0.03601 L/min, 21.39210 ± 1.42771 mmHg, 0.29598 ± 0.01344 L/min, respectively). With the compression of the prototype, the blood circulation can be optimized at the compression depth of 50 mm, approximately 0.6 duty cycle, and approximately 110 press/min, which is of guiding significance for the practical use of CPR devices to rescue patients with cardiac arrest.
Comprehensive Identification and Expression Profiling of the VQ Motif-Containing Gene Family in Brassica juncea
Authors: Zheng Jie , Li Haibo , Guo Ziqi , Zhuang Xiaoman , Huang Weifeng , Mao Cui , Feng Huimin , Zhang Yang , Wu Hao , Zhou Yong
Published: December 2022

Valine-glutamine (VQ) motif-containing proteins are a class of highly conserved transcriptional regulators in plants and play key roles in plant growth, development, and response to various stresses. However, the VQ family genes in mustard have not yet been comprehensively identified and analyzed. In this study, a total of 120 VQ family genes (BjuVQ1 to BjuVQ120), which were unevenly distributed on 18 chromosomes (AA_Chr01 to BB_Chr08), were characterized in mustard. A phylogenetic tree analysis revealed that the BjuVQ proteins were clustered into nine distinct groups (groups I to IX), and members in the same group shared a highly conserved motif composition. A gene structure analysis suggested that most BjuVQ genes were intronless. A gene duplication analysis revealed that 254 pairs of BjuVQ genes were segmentally duplicated and one pair was tandemly duplicated. Expression profiles obtained from RNA-seq data demonstrated that most BjuVQ genes have different gene expression profiles in different organs, including leaf, stem, root, flower bud, pod, and seed. In addition, over half of the BjuVQ genes were differentially expressed at some time points under low temperature treatment. The qRT-PCR data revealed that BjuVQ23, BjuVQ55, BjuVQ57, BjuVQ67, BjuVQ100, and BjuVQ117 were upregulated in response to cold stress. Taken together, our study provides new insights into the roles of different BjuVQ genes in mustard and their possible roles in growth and development, as well as in response to cold stress.
Non-Modified CpG Oligodeoxynucleotide Forming Guanine-Quadruplex Structure Complexes with ε-Poly-L-Lysine Induce Antibody Production as Vaccine Adjuvants
Authors: Zhao Dandan , Tu Anh Thi Tram , Shobo Miwako , Le Nguyen Bui Thao , Yoshikawa Chiaki , Sugai Kazuhisa , Hakamata Yoji , Yamazaki Tomohiko
Published: December 2022

Unmethylated cytosine-phosphate-guanosine oligodeoxynucleotides (CpG ODNs) induce inflammatory cytokines and type I interferons (IFNs) to activate the immune system. To apply CpG ODNs as vaccine adjuvants, the cellular uptake and stability of phosphodiester-based, non-modified ODNs require further improvement. Previously developed new CpG ODNs forming guanine-quadruplex (G4) structures showed higher nuclease resistance and cellular uptake than linear CpG ODNs; however, the complex formation of G4-CpG ODNs with antigen proteins is necessary for their application as vaccine adjuvants. In this study, we utilized a cationic polymer, ε-poly-L-lysine (ε-PLL), as a carrier for G4-CpG ODNs and antigen. The ε-PLL/G4-CpG ODN complex exhibited enhanced stability against nucleases. Cellular uptake of the ε-PLL/G4-CpG ODN complex positively correlated with the N/P ratio. In comparison to naked G4-CpG ODNs, the ε-PLL/G4-CpG ODN complex induced extremely high levels of interleukin (IL)-6, IL-12, and IFN-β. Relative immune cytokine production was successfully tuned by N/P ratio modification. Mice with the ε-PLL/G4-CpG ODN/ovalbumin (OVA) complex showed increased OVA-specific immunoglobulin (Ig)G, IgG1, and IgG2c levels, whereas total IgE levels did not increase and weight gain rates were not affected. Therefore, ε-PLL can serve as a safe and effective phosphodiester-based, non-modified CpG ODN delivery system, and the ε-PLL/G4-CpG ODN/antigen complex is a highly promising candidate for vaccine adjuvants and can be further used in clinical research.
Efficient Synthesis for Altering Side Chain Length on Cannabinoid Molecules and Their Effects in Chemotherapy and Chemotherapeutic Induced Neuropathic Pain
Authors: Raup-Konsavage Wesley M. , Sepulveda Diana E. , Morris Daniel P. , Amin Shantu , Vrana Kent E. , Graziane Nicholas M. , Desai Dhimant
Published: December 2022

(1) Background: Recently, a number of side chain length variants for tetrahydrocannabinol and cannabidiol have been identified in cannabis; however, the precursor to these molecules would be based upon cannabigerol (CBG). Because CBG, and its side chain variants, are rapidly converted to other cannabinoids in the plant, there are typically only small amounts in plant extracts, thus prohibiting investigations related to CBG and CBG variant therapeutic effects. (2) Methods: To overcome this, we developed an efficient synthesis of corresponding resorcinol fragments using the Wittig reaction which, under acid catalyzed coupling with geraniol, produced the desired side chain variants of CBG. These compounds were then tested in an animal model of chemotherapeutic-induced neuropathic pain and to reduce colorectal cancer cell viability. (3) Results: We found that all side-chain variants were similarly capable of reducing neuropathic pain in mice at a dose of 10 mg/kg. However, the molecules with shorter side chains (i.e., CBGV and CBGB) were better at reducing colorectal cancer cell viability. (4) Conclusions: The novel synthesis method developed here will be of utility for studying other side chain derivatives of minor cannabinoids such as cannabichromene, cannabinol, and cannabielsoin.
Cerebral Ischemic Preconditioning Aggravates Death of Oligodendrocytes
Authors: Guan Teng , Guo Ying , Li Chengren , Zhou Ting , Yu Qiang , Yang Chaoxian , Zhang Guohui , Kong Jiming
Published: December 2022

Neurodegeneration can benefit from ischemic preconditioning, a natural adaptive reaction to sublethal noxious stimuli. Although there is growing interest in advancing preconditioning to preserve brain function, preconditioning is not yet considered readily achievable in clinical settings. One of the most challenging issues is that there is no fine line between preconditioning stimuli and lethal stimuli. Here, we show deleterious effect of preconditioning on oligodendrocyte precursor cells (OPCs). We identified Bcl-2/adenovirus E1B 19-kDa interacting protein 3 (BNIP3), a mitochondrial BH3-only protein specifically involved in OPCs loss after preconditioning. Repeated ischemia stabilized BNIP3 and increased the vulnerability of OPCs to subsequent ischemic events. BNIP3 became mitochondrial-bound and was concurrent with the dysfunction of monocarboxylate transporter 1 (MCT1). Inhibition of BNIP3 by RNAi or necrostatin-1 (Nec-1) and knocking out of BNIP3 almost completely prevented OPCs loss and preserved white matter integrity. Together, our results suggest that the unfavorable effect of BNIP3 on OPCs should be noted for safe development of ischemic tolerance. BNIP3 inhibition appears to be a complementary approach to improve the efficacy of preconditioning for ischemic stroke.
Impact of Adenomyosis on Infertile Patients—Therapy Options and Reproductive Outcomes
Authors: Günther Veronika , Allahqoli Leila , Gitas Georgios , Maass Nicolai , Tesch Karolin , Ackermann Johannes , Rosam Paula , Mettler Liselotte , von Otte Sören , Alkatout Ibrahim
Published: December 2022

Adenomyosis is associated with a negative impact on reproductive outcomes. Although adenomyosis is detected more frequently in women of late reproductive age, its impact on pregnancy rates is important because, in today’s world, family planning has shifted towards the late reproductive phase of life for many women. Although the diagnostic indications for imaging studies are well-known, we lack strict diagnostic criteria and classification systems concerning the extent of the disease. Selecting the optimal evidence-based treatment option for adenomyosis is difficult because of the paucity of evidence concerning the association between fertility and the degree and composition of adenomyosis. Furthermore, the treatment of infertility might interfere with the treatment of adenomyosis due to the presence of pain. The aim of this review is to analyze the association between adenomyosis and infertility, and describe treatment options to enhance reproductive outcomes. The following aspects will be addressed in detail: (a) prevalence and causes of adenomyosis, (b) diagnostic tools with imaging techniques, (c) clinical symptoms, (d) proposed pathomechanism of adenomyosis and infertility, and (e) different treatment approaches (pharmacological, surgical, others) and their impact on reproductive outcomes.
Is Aesthetic Good? A Study on the Aesthetic and Vitality Judgment of Pictorial Representations of the Dead, Saints and Non-Saints
Authors: Schieppati Sara Valentina , Di Dio Cinzia , Marchetti Antonella , Massaro Davide , Gilli Gabriella Maria
Published: December 2022

In the history of the Western world, there has always been an association between good and beautiful. Starting from a brief history of beauty, two questions arise: is beauty linked to good even in art? How important are people’s religious beliefs in aesthetic and vitality judgments? The psychology of art could answer these questions by studying people’s reactions to the images of Saints as testimonials of goodness. Moreover, the study of Saints’ paintings would allow us to investigate vitality, understood as one’s perception of a living being. The research aimed to investigate the aesthetic and vitality judgments of faces representing the dead, Saints and non-Saints. More than a hundred participants were asked to evaluate the aesthetics and vitality of these paintings; moreover, two tests assessing spirituality and religiosity were administered. Overall, these data suggest Saints were judged more beautiful than non-Saints, and non-Saints were judged more vital than Saints. This might suggest a relationship between ethics and aesthetics, also in the perception of art, and offers reflections on the theme of vitality. The religion and spirituality of participants are not correlated to aesthetic or vitality judgments; this fact could support that these judgments are linked to the basic bottom-up reactions to images.
A Study of the Impact of Strategic Human Resource Management on Organizational Resilience
Authors: Yu Jingjing , Yuan Lingling , Han Guosheng , Li Hui , Li Pengfei
Published: December 2022

Organizational resilience is a key capability for modern firms to survive and thrive in the VUCA environment. The purpose of this study is to investigate the mechanism of strategic human resource management on organizational resilience and the mediating and moderating roles of self-efficacy and self-management, respectively, in the relationship between the two. A total of 379 valid questionnaires were obtained from employees of Chinese companies in August 2022, and the data were analyzed using SPSS 22.0 and Amos. The results showed that strategic HRM can effectively contribute to organizational resilience; self-efficacy plays a mediating role in the relationship between strategic HRM and organizational resilience; self-management can effectively contribute to the impact of self-efficacy on organizational resilience; and self-management can hinder the ability of strategic HRM to contribute to organizational resilience. This paper breaks with the previous literature that studied organizational resilience from a single perspective by studying organizational resilience from the perspective of strategic human resource management (SHRM) and verifies that SHRM can be a possible path for Chinese firms to improve organizational resilience.
A Qualitative Exploration of Parents’ Perceptions of Risk in Youth Contact Rugby
Authors: Anderson Eric , White Adam , Hardwicke Jack
Published: December 2022

The purpose of this study was to explore the understandings and perceptions of risk related to brain trauma amongst parents of children that play contact rugby. A qualitative approach was taken, using semi-structured interviews with 7 mothers and 27 fathers of children that participate in contact rugby. A thematic analysis of data suggests that parents used two primary cognitive strategies to process the risk they consented to with their children’s participation in rugby; (1) minimalizing rugby risk to be equivalent to less injurious sports; and (2) elevating physical and social advantages above what they think other sports are capable of providing. From the findings it is suggested that parents who permit their children to play contact rugby are both aware of the high risks of injury in the sport, but simultaneously utilize two cognitive distortion techniques to rectify the dissonance caused between their choice to have their children play, and the salient number of concussions they observe. These results suggest that it will take properly informed consent, inclusive of concussion rates compared to other sports, in order to reduce cognitive distortion and effectively communicate risks associated with participation in contact rugby.
Wire Rope Isolators for the Vibration Protection of Heavy Equipment: Exploratory Research
Authors: Leblouba Moussa , Balaji Palani Selvaraj , Rahman Muhammad Ekhlasur
Published: December 2022

Wire rope isolators (WRI) are devices that dissipate vibrational energy. They are used in various industrial applications to protect equipment and machinery. Heavy machinery and limited space are still some of the constraints engineers face when designing the WRI system. Heavy equipment requires increased vertical stiffness; however, using larger WRIs decreases their lateral flexibility, which is the target property in the first place. Using several small-sized WRIs is not possible in the case of limited space. Therefore, the present study proposes two improvements to WRIs to overcome the challenges caused by heavy-weight equipment and a lack of the space required to insert the appropriate number and size of WRIs. Two new configurations for WRIs are proposed, Spring-WRI (S-WRI) and Double-WRI (D-WRI), to improve the stiffness and damping properties in order to expand their applications. Monotonic and quasi-static cyclic loading tests were performed on the conventional and proposed WRI variants. Exploratory tests showed that the WRI’s stiffness greatly depends on the wire rope diameter. Adding springs inside a conventional WRI (S-WRI) can improve vertical stiffness while maintaining the required lateral flexibility. The D-WRI was found to preserve the necessary flexibility and to be capable of solving the problem of limited space. The hysteresis behavior of the D-WRI can be expressed as the sum of the hysteresis of each WRI. The proposed configurations effectively improve the stiffness and damping properties of WRIs and expand their applicability for the vibration isolation of heavy equipment and in limited space.
Using a Smart Living Environment Simulation Tool and Machine Learning to Optimize the Home Sensor Network Configuration for Measuring the Activities of Daily Living of Older People
Authors: Naccarelli Riccardo , Casaccia Sara , Pirozzi Michela , Revel Gian Marco
Published: December 2022

This paper describes a methodology to optimize the home sensor network to measure the Activities of Daily Living (ADLs) of older people using Machine Learning (ML) applied to synthetic data generated via a newly developed Smart Living Environment (SLE) simulation tool. A home sensor network consisting of Passive InfraRed (PIR) and door sensors allows people to age in place, avoiding invasiveness of the technology by keeping track of the older users’ behaviour and health conditions. However, it is difficult to identify a priori the optimal sensor network configuration to measure users’ behaviour. To ensure better user acceptability without losing measurement accuracy, the authors proposed a methodology to optimize the home sensor network consisting of simulating human activities, and therefore sensor activations, in the reconstructed SLE and analysing the datasets generated through ML. Four ML classifiers, namely the Decision Tree (DT), Gaussian Naïve Bayes (GNB), Support Vector Machine (SVM) and K-Nearest Neighbors (KNN), were tested to measure the accuracy of ADL classification. Optimization analysis was made, providing the most suitable home sensor network configuration for two home environment case studies by exploiting the DT classifier results, as it proved to achieve the highest mean accuracy (over 94%) in measuring ADLs.
Testing Olmsted’s Lasting Legacy—Comparing Design Theory and the Post-Occupancy Conditions of New York Central Park
Authors: Zhu Xun , Zhang Bo , Xiang Shurong , Zhao Wei , Mihalko Cheryl
Published: December 2022

Social media is a rapidly developing field in architecture and landscape research, which is used to understand public opinions and landscape use. The year 2022 sees the 200th birthday of Olmsted, the founding father of landscape architecture in America. While we commemorate Olmsted’s ground-breaking contribution to the landscape architecture discipline, in-depth analyses are always required to examine historic legacies for their current relevancy. Taking his first practical work, New York Central Park, as an example, this paper systematically revisits Olmsted’s park design theory and vision, and investigates its post-occupancy conditions from 11,501 posts on TripAdvisor. The results show that the current park use pattern confirms the validity of his scenic image theory. At the same time, his design works have become increasingly popular as public projects to foster social interaction.
Rheological Properties and Structural Build-Up of Cement Based Materials with Addition of Nanoparticles: A Review
Authors: Li Qiuchao , Fan Yingfang , Shah Surendra P.
Published: December 2022

Nanoparticles improve the mechanical properties and durability of cement-based materials. However, owing to the high surface energy and specific surface areas of nanoparticles, the packing characteristic of cementitious particles will be affected. With the action of the electrostatic attraction and Van der Waals force, the cementitious particles are agglomerated into flocculation structures, and the free water is entrapped. Furthermore, as the water consumption of cement-based materials increases, the flowability gets worse, which is thought to be one of the reasons limiting its application in practical engineering. In addition, nanoparticles increase the viscosity and thixotropy of fresh cement-based materials and provide more nucleation sites in cement paste, accelerating the cement hydration process in early hydration. In this paper, the research progress on the rheological properties and structural build-up of cement-based materials with the addition of nanoparticles was reviewed. The applicability of rheological test methods and rheological models was summarized. The variation of rheological parameters of fresh cement-based materials affected by nanoparticles species, contents, dispersion method, superplasticizer, etc., were discussed. Based on the packing density, water film thickness, and flocculation structures, the action mechanism of nanoparticles on the rheological properties of cement-based materials was analyzed. Further research topics on the rheology and structural build-up of nano-modified cement-based materials are suggested as well.
Evaluating Energy Efficiency and Colorimetric Quality of Electric Light Sources Using Alternative Spectral Sensitivity Functions
Authors: Song Wangyang , Durmus Dorukalp
Published: December 2022

Photometric and colorimetric quantities are calculated using spectral luminous efficiency and color matching functions (CMFs), respectively. Past studies highlighted the limitations of the standard sensitivity functions based on visual experiments conducted over a century ago. There have been new alternatives proposed, but the effect of the proposed alternatives functions on energy efficiency, and the colorimetric quality of light sources has rarely been investigated. It is reasonable to assume that updating photometric and colorimetric calculation procedures will make significant impacts on the characterization of electric light sources. Here, the impact of six luminous efficiency functions and six CMFs on luminous efficacy of radiation and chromaticity calculations were analyzed. Results indicate a significant effect of alternative functions on luminous efficacy of radiation (LER), chromaticity coordinates (CIE 1931 x,y and CIE 1976 u′,v′) and Duv. The biggest impact was caused by the change in the visual field of view (2-degree vs. 10-degree observer), highlighting the importance of visual field size for color and luminosity function. Updating the standardized luminous efficiency function may impact the performance characterization of electric light sources, but cost-benefit analysis should be studied to understand the broad impacts.
Influence of Calcination Temperature on Photocatalyst Performances of Floral Bi2O3/TiO2 Composite
Authors: Wang Mingjun , Li Che , Liu Bingfang , Qin Wenzhen , Xie Yu
Published: December 2022

Heterojunction photocatalytic materials show excellent performance in degrading toxic pollutants. This study investigates the influence of calcination temperature on the performances of floral Bi2O3/TiO2 composite photocatalyst crystal, which was prepared with glycerol, bismuth nitrate, and titanium tetrachloride as the major raw materials via the solvothermal method. XRD, SEM/TEM, BET, Uv-vis, and XPS were employed to analyze the crystal structure, morphology, specific surface area, band gap, and surface chemical structure of the calcined temperature catalysts. The calcination temperature influence on the catalytic performance of composite photocatalysis was tested with rhodamine B (RhB) as the degradation object. The results revealed the high catalytic activity and higher photocatalytic performance of the Bi2O3/TiO2 catalyst. The degradation efficiency of the Bi2O3/TiO2 catalyst to RhB was 97%, 100%, and 91% at 400 °C, 450 °C, and 500 °C calcination temperatures, respectively, in which the peak degradation activity appeared at 450 °C. The characterization results show that the appropriate calcination temperature promoted the crystallization of the Bi2O3/TiO2 catalyst, increased its specific surface area and the active sites of catalytic reaction, and improved the separation efficiency of electrons and holes.
Imaging Cataract-Specific Peptides in Human Lenses
Authors: Schey Kevin L. , Wang Zhen , Rose Kristie L. , Anderson David M. G.
Published: December 2022

Age-related protein truncation is a common process in long-lived proteins such as proteins found in the ocular lens. Major truncation products have been reported for soluble and membrane proteins of the lens, including small peptides that can accelerate protein aggregation. However, the spatial localization of age-related protein fragments in the lens has received only limited study. Imaging mass spectrometry (IMS) is an ideal tool for examining the spatial localization of protein products in tissues. In this study we used IMS to determine the spatial localization of small crystallin fragments in aged and cataractous lenses. Consistent with previous reports, the pro-aggregatory αA-crystallin 66–80 peptide as well as αA-crystallin 67–80 and γS-crystallin 167–178 were detected in normal lenses, but found to be increased in nuclear cataract regions. In addition, a series of γS-crystallin C-terminal peptides were observed to be mainly localized to cataractous regions and barely detected in transparent lenses. Other peptides, including abundant αA3-crystallin peptides were present in both normal and cataract lenses. The functional properties of these crystallin peptides remain unstudied; however, their cataract-specific localization suggests further studies are warranted.