bluuebunny/crossref_metadata_2025 huggingface dataset:
Anthocyanin Delivery Systems: A Critical Review of Recent Research Findings
Authors: Al-Khayri Jameel Mohammed , Asghar Waqas , Akhtar Aqsa , Ayub Haris , Aslam Iram , Khalid Nauman , Al-Mssallem Muneera Qassim , Alessa Fatima Mohammed , Ghazzawy Hesham Sayed , Attimarad Mahesh
Published: December 2022

Anthocyanins (ACNs) are polyphenolic, water-soluble pigments, and phytochemicals, which in recent years, have garnered the interest of consumers, researchers, and industries for their various potential preventative and/or therapeutic health benefits and applications in the food industry. ACN-based processed foods have emerged as functional foods with significant therapeutic potential against various health conditions. However, their wider application in food and pharmaceutical formulations is hindered by their inherent instability under different environmental conditions, such as pH, light, and temperature, rendering them non-functional due to loss of biological activity. The current review focuses on the frequently used bio-based encapsulation materials for ACN-based delivery systems and their formulation techniques. Various bio-based materials including pectin, gums, pectin, proteins, lipids, phospholipids, and their conjugates are being widely used for targeted delivery and controlled release of bioactive compounds and drugs. The incorporation of advanced technologies seems to be promising in the context of extraction, encapsulation, and storage of ACNs. However, more comprehensive studies are required for the application of encapsulated ACNs in various food products, and improvements in their stability under different processing conditions.
Performance Analysis of Hardware Implementations of Reverse Conversion from the Residue Number System
Authors: Kuchukov Viktor , Telpukhov Dmitry , Babenko Mikhail , Mkrtchan Ilya , Stempkovsky Alexander , Kucherov Nikolay , Ermakova Tatiana , Grigoryan Marine
Published: December 2022

The Residue Number System (RNS) is a non-positional number system that allows parallel computations without transfers between digits. However, some operations in RNS require knowledge of the positional characteristic of a number. Among these operations is the conversion from RNS to the positional number system. The methods of reverse conversion for general form moduli based on the Chinese remainder theorem and the mixed-radix conversion are considered, as well as the optimized methods for special form moduli. In this paper, a method is proposed that develops the authors’ ideas based on the modified mixed-radix conversion and reference points. The modified method based on the mixed-radix conversion in this case makes it possible to replace the operation of finding the residue of division by a large modulo with the sequential calculation of the residue. The method of reference points allows to reduce the size of the stored information compared to the use of ROM to store all the residues of RNS. The application of this approach makes it possible to find a balance between the speed of the calculation and the hardware used, by varying the number of moduli of one method and the other.
Influence Analysis of Traveling Wave Effect on Rail Interaction of Long-Span Suspension Bridge
Authors: Yu Xiangdong , Wang Chuhao , Jing Haiquan
Published: December 2022

At present, there are few research results on the seismic response of the track system on railway suspension bridges, and relevant research has not yet formed a certain standard. In order to provide a certain reference for the development of industry standards and the design of seamless lines on railway suspension bridges, based on the large-mass method based on multi-point excitation, taking China’s longest high-speed railway suspension bridge-Wufengshan Yangtze River Bridge as the engineering background, a beam–rail integrated dynamic calculation space model was established with ANSYS, and the influence of traveling wave effect on the beam-rail interaction of large span suspension bridges was studied. The study shows that: the traveling wave effect will increase the relative displacement of the beam and rail, and then increase the stress of the rail; the traveling wave effect will cause the stress of the rail far from the source measurement to lag behind the stress of the rail near the source side, and the lag phenomenon gradually disappears with the increase of the apparent wave speed; the traveling wave effect has a greater effect on the displacement of the main bridge end than that of the approach bridge end; the longitudinal displacement of the main bridge end on the north and south side keeps changing synchronously under high apparent wave speed and consistent excitation, and no longer keeps changing synchronously under low apparent wave speed. The longitudinal displacement of the north-south side of the main bridge end keeps changing synchronously at high apparent wave speed and consistent excitation, but no longer at low apparent wave speed.
Papain Hydrolysates of Lupin Proteins with Antioxidant, Antimicrobial, and Acetylcholinesterase Inhibitory Activities
Authors: Garmidolova Alexandra , Desseva Ivelina , Mihaylova Dasha , Fidan Hafize , Terziyska Margarita , Pavlov Atanas
Published: December 2022

Dietary proteins are no longer just nutritional ingredients in our food. During hydrolysis, some of the released peptides may possess properties that favor the health of the human body. In our study enzymatic hydrolysis of lupin proteins was performed using papain. Three enzyme-to-substrate ratios were set for three different duration times. The SDS-PAGE of the samples was performed. Each hydrolysate was studied for the degree of hydrolysis (DH), acetylcholinesterase (AChE) inhibitory, antimicrobial, and antioxidant activities (AOA, according to four spectrophotometric methods). The DH varied from 9.06 ± 0.20 to 27.97 ± 0.37%. According to the results, the best AOA was measured by the ABTS method (from 0.76 ± 0.03 to 1.15 ± 0.46 M TE/100 g protein). All the hydrolysates displayed AChE inhibitory activity (IC50), which varied between 155.58 ± 1.87 and 199.63 ± 0.41 mg/g protein. To the best of our knowledge, this is the first report of the acetylcholinesterase inhibitory activity of lupin protein hydrolysates. In conclusion, lupin proteins prove to have a high potential to serve as a source of bioactive peptides.
Improving the Analysis of Sulfur Content and Calorific Values of Blended Coals with Data Processing Methods in Laser-Induced Breakdown Spectroscopy
Authors: Choi Jae Seung , Ryu Choong Mo , Choi Jung Hyun , Moon Seung Jae
Published: December 2022

In Situ monitoring of the calorific value of coal has the advantage of reducing the amount of unburned carbon by injecting an appropriate amount of combustion air immediately to induce complete combustion. High sulfur concentrations cause severe environmental problems such as acid rain. In order to estimate the calorific value and measure the sulfur concentration, a new powerful technique for mixed coals was studied. Laser-induced breakdown spectroscopy (LIBS) does not require sample preparation. Several blended coals were used for the experiment to replicate the actual coal-fired power plant conditions. Two well-known data processing methods in near-infrared spectroscopy have been adopted to enhance the weak sulfur emission lines. The performance of the partial least square regression model was established by the parameters such as coefficient of determination, R2, relative error, and root mean square error (RMSE). The RMSE average was compared with the results of previous studies. As a result, the values from this study were smaller by 6.02% for the calibration line and by 4.5% for the validation line in near-infrared spectroscopy. The RMSE average values for calorific values were calculated to be less than 1%.
Visualization System for Transparency Requirement Analytics
Authors: Fadloun Samiha , Meshoul Souham , Hosseini Mahmood , Amokrane Abdennour , Bennaceur Hichem
Published: December 2022

Access to corporate information systems by consumers via the Internet has increased dramatically over the past several decades. In a separate organization, extensive research has been conducted on the free flow of information generated by both external and internal keywords. Research on transparency should aid the audience in making informed decisions. Few have, however, created clear and compelling visual representations of transparency requirements (stakeholders, data, process, policy, and their relationships) utilizing current information visualization and visual analytics methodologies. Maintaining both the quality and visual representation of transparency requirements is a difficult challenge. In this paper, we propose TranspVis, a new visual analytics tool designed for transparency analytics. It consists of multiple views that aid domain experts in efficiently analyzing, updating, and saving application transparency datasets. TranspVis is an interactive tool for displaying TranspLan (i.e., Transparency Language) representations manually generated by experts utilizing the Shield, Infolet, and SitReq forms. In addition to the new circle view, TranspVis generates and synchronizes these latter representations automatically. TranspVis is evaluated using AWS and WhatsApp policy datasets as two case studies. Results show that TranspVis extends the initial TranspLan representation and significantly improves transparency requirement analytics in terms of visual encoding, interactions, and insight extraction.
Analytical and Numerical Study on the Stability of Highway Subgrade with Embedded Loading Berm in Soft Soil Area
Authors: Xiong Feng , Wang Xuebin , Yang Fan , Yang Jiaqiang , Hu Li , Li Rui
Published: December 2022

Loading berm is an effective method for improving highway subgrade stability in soft soil areas. However, this method requires lots of construction space. It is not applicable in some areas with narrow construction spaces. To address this problem, an embedded loading berm (ELB) is proposed to improve highway subgrade stability, and the effects of ELB on the stability of the highway subgrade were investigated by analytical and numerical methods. Firstly, an analytical model was proposed to analyze the relationship between the ELB dimensions and subgrade stability factors. Then, numerical simulations were carried out to further reveal the stability factor of an actual subgrade with different ELBs. Lastly, ELB parameters’ sensitivity to the ELB stability factors was studied. The results show that the stability of the highway subgrade in soft soil areas can be significantly improved by the proposed ELB. With the loading berm width and height increasing, the subgrade stability factors can increase. The stability factors’ increase ratio with the increased ELB width is greater than that with the increased ELB height. The ELB parameter sensitivity order on the subgrade stability is as follows: width > height > density > cohesion > internal friction. In the design process, the ELB width and height can be mainly focused on. The research is significant for promoting the application of ELB in soft soil areas.
The Bernoulli Assembly Line: The Analytical and Semi-Analytical Evaluation of Steady-State Performance
Authors: Hadžić Neven , Ložar Viktor , Opetuk Tihomir , Kunkera Zoran
Published: December 2022

Assembly lines are one of the cornerstones of modern production systems, significantly affecting the global society, economy, and other ancillary sectors. This is why the evaluation of assembly lines is particularly significant. Hence, the research on modeling approaches is presented in this paper, yielding an efficient mathematical tool that enables the evaluation of the steady-state performance of assembly lines at low CPU cost. First, the analytical model and the transition matrix were developed for the general case, and second, dimensionality issues and demanding computational requirements were tackled by applying the finite state method. Both approaches were employed in different theoretical cases in order to validate the finite state method against the analytical solution. Additionally, the developed evaluation framework was applied in the case of a realistic assembly system, and the obtained results were successfully validated against the factory floor measurements. The comparison of the obtained results proves the finite state method as a reliable and CPU-efficient method, suitable for the evaluation of its key performance indicators as well as implementation within more sophisticated design procedures. This kind of predictive analytics is intended to support production management and enhance the reliability of long- and short-term decision-making in the context of the digital twinning of production systems.
Segregation Modeling in Stockpile Using Discrete Element Method
Authors: Gómez René , Skrzypkowski Krzysztof , Moncada Manuel , Castro Raúl , Lazo Rodrigo
Published: December 2022

During stockpile feeding, the small particles migrate to the center of the stock while large particles end up around the edges. This phenomenon influences how the mineral is fragmented in the subsequent stages of size reduction. In this study, the primary variables involved in this phenomenon were studied using the discrete element to simulate particle segregation. Results show that the ratio between coarse and fine particles strongly affects particle segregation. The segregation phenomenon was not observed when there were fewer coarse particles in the mix. The feeding height was also found to influence segregation and to affect the angles of repose and dumping. Finally, the rounded polyhedral shape of particles generated the simulation performance most similar to actual particle segregation based on a case study analyzed.
K-RBBSO Algorithm: A Result-Based Stochastic Search Algorithm in Big Data
Authors: Park Sungjin , Kim Sangkyun
Published: December 2022

Clustering is widely used in client-facing businesses to categorize their customer base and deliver personalized services. This study proposes an algorithm to stochastically search for an optimum solution based on the outcomes of a data clustering process. Fundamentally, the aforementioned goal is achieved using a result-based stochastic search algorithm. Hence, shortcomings of existing stochastic search algorithms are identified, and the k-means-initiated rapid biogeography-based silhouette optimization (K-RBBSO) algorithm is proposed to overcome them. The proposed algorithm is validated by creating a data clustering engine and comparing the performance of the K-RBBSO algorithm with those of currently used stochastic search techniques, such as simulated annealing and artificial bee colony, on a validation dataset. The results indicate that K-RBBSO is more effective with larger volumes of data compared to the other algorithms. Finally, we describe some prospective beneficial uses of a data clustering algorithm in unsupervised learning based on the findings of this study.
Complementary Photothermal Heating Effects Observed between Gold Nanorods and Conjugated Infrared-Absorbing Dye Molecules
Authors: Culhane Kyle , Savchuk Viktoriia , Pinchuk Anatoliy O. , McNear Kelly
Published: December 2022

Due to their biocompatibility, ease of surface modification, and heating capabilities, gold nanomaterials are considered excellent candidates for the advancement of photothermal therapy techniques and related applications in cancer treatment. Various morphologies of gold nanomaterials have been shown to heat when exposed to high-powered laser irradiation, especially that which is from the near-infrared (NIR) region. While these lasers work well and are effective, light-emitting diodes (LEDs) may offer a safe and low-powered alternative to these high energy lasers. We investigated the heating capability of NIR-dye conjugated gold nanorods when exposed to an 808 nm LED light source using polyethylene glycol (PEG)-coated gold nanorods as the control. In this way, since the rods exhibited a surface plasmon resonance peak between 795 and 825 nm for both the PEG-coated rods and the dye-conjugated rods, which are fairly close to the frequency of the 530 mW, 850 nm LED light source, we were able to reveal the heating effect of the dye modification. While both morphologies heat when irradiated with the LED light, we demonstrated that the addition of an NIR dye increases the rate of heating and cooling, compared to the PEGylated counterpart. To our knowledge, the complementary effect given by the conjugated NIR-dye has not been previously reported in the literature. The targeting abilities of the NIR-dye combined with the increased heating rate of the modified particles used in this proof-of-concept work suggests that these particles may be exceptional candidates for theranostic applications.
Comparative Study of Audiovestibular Symptoms between Early and Late Variants of COVID-19
Authors: Almishaal Ali A.
Published: December 2022

Audiovestibular symptoms during the acute phase of the corona virus disease 2019 (COVID-19), have been reported for earlier waves of the pandemic, while no studies investigated nor compared audiovestibular manifestations during subsequent waves of COVID-19. In the current study, we aimed to compare the occurrence of audiovestibular symptoms associated with COVID-19 between the alpha/beta, delta, and omicron variants. An online questionnaire was distributed to individuals with confirmed test results for COVID-19. We asked participants to report whether they experienced audiovestibular symptoms during the acute phase of the disease. The study included 939 participants; 120 un-infected controls and infected participants during alpha/beta (n = 301), delta (n = 102), and omicron (n = 416) predominance periods. Self-reported audiovestibular symptoms were found to be statistically significantly different between un-infected controls and COVID-19 infected individuals in all analyzed variants. Furthermore, our results showed no significant differences in audiovestibular symptoms among individuals infected during alpha/beta, delta, and omicron waves. Although individuals infected during the delta variant predominance period reported higher percentages of audiovestibular symptoms (ranging from 11.8% to 26.5% for auditory symptoms and from 12.7% to 34.3% for vestibular symptoms) than for the alpha/beta (ranging from 6.3% to 18.9% for auditory symptoms and 8.3% to 29.9% for vestibular symptoms) and omicron (ranging from 9.6% to 21.2% for auditory and 12.5 to 29.1% for vestibular symptoms) variants, this did not achieve statistical significance. With regards to auditory symptoms, the most commonly reported symptoms were aural fullness followed by hearing loss and tinnitus. With regards to vestibular symptoms, dizziness was the most commonly reported symptom followed by vertigo and unsteadiness. Logistic regression revealed that experiencing auditory symptoms were associated with other neurological symptoms, back and joint pain, and chest pain as COVID-19 symptoms. Vestibular symptoms were associated with anemia, gender, fatigue, headache, and breathing difficulties. In conclusion, our study shows that audiovestibular symptoms are common during the acute phase of early and late COVID-19 variants with no significant differences between them.
A Complete Characterization of Bipartite Graphs with Given Diameter in Terms of the Inverse Sum Indeg Index
Authors: Su Guifu , Song Guanbang , Du Junfeng , Yang Weixing , Rao Gang , Yin Jun
Published: December 2022

In 2010, Vukičević introduced an new graph invariant, the inverse sum indeg index of a graph, which has been studied due to its wide range of applications. Let Bnd be the class of bipartite graphs of order n and diameter d. In this paper, we mainly characterize the bipartite graphs in Bnd with the maximal inverse sum indeg index. Bipartite graphs with the largest, second-largest, and smallest inverse sum indeg indexes are also completely characterized.
Forecasting High-Dimensional Covariance Matrices Using High-Dimensional Principal Component Analysis
Authors: Shigemoto Hideto , Morimoto Takayuki
Published: December 2022

We modify the recently proposed forecasting model of high-dimensional covariance matrices (HDCM) of asset returns using high-dimensional principal component analysis (PCA). It is well-known that when the sample size is smaller than the dimension, eigenvalues estimated by classical PCA have a bias. In particular, a very small number of eigenvalues are extremely large and they are called spiked eigenvalues. High-dimensional PCA gives eigenvalues which correct the biases of the spiked eigenvalues. This situation also happens in the financial field, especially in situations where high-frequency and high-dimensional data are handled. The research aims to estimate the HDCM of asset returns using high-dimensional PCA for the realized covariance matrix using the Nikkei 225 data, it estimates 5- and 10-min intraday asset-returns intervals. We construct time-series models for eigenvalues which are estimated by each PCA, and forecast HDCM. Our simulation analysis shows that the high-dimensional PCA has better estimation performance than classical PCA for the estimating integrated covariance matrix. In our empirical analysis, we show that we will be able to improve the forecasting performance using the high-dimensional PCA and make a portfolio with smaller variance.
New Financial Ratios Based on the Compositional Data Methodology
Authors: Linares-Mustarós Salvador , Farreras-Noguer Maria Àngels , Arimany-Serrat Núria , Coenders Germà
Published: December 2022

Due to the type of mathematical construction, the use of standard financial ratios in studies analyzing the financial health of a group of firms leads to a series of statistical problems that can invalidate the results obtained. These problems originate from the asymmetry of financial ratios. The present article justifies the use of a new methodology using Compositional Data (CoDa) to analyze the financial statements of an industry, improving analyses using conventional ratios, since the new methodology enables statistical techniques to be applied without encountering any serious drawbacks, such as skewness and outliers, and without the results depending on the arbitrary choice as to which of the accounting figures is the numerator of the ratio and which is the denominator. An example with data on the wine industry is provided. The results show that when using CoDa, outliers and skewness are much reduced, and results are invariant to numerator and denominator permutation.
Identification of Bioactive Peptides from Nannochloropsis oculata Using a Combination of Enzymatic Treatment, in Silico Analysis and Chemical Synthesis
Authors: Hayes Maria , Mora Leticia , Lucakova Simona
Published: December 2022

In vitro ACE-1 inhibitory peptides were characterised previously from a number of microalgal species including Spirulina platensis (peptide IAPG), Chlorella vulgaris (peptides FDL, AFL, VVPPA), Isochrysis galbana (peptide YMGLDLK), Chlorella sorokiniana (peptides IW and LW) and indeed Nannochloropsis oculata (peptides GMNNLTP and LEQ). The isolation of protein from Nannochloropsis oculata using a combination of ammonium salt precipitation and xylanase treatment of resulting biomass combined with molecular weight cut off filtration to produce a permeate and characterisation of bioactive peptides is described. The Angiotensin-1-converting enzyme (ACE-1) IC50 value for the generated permeate fraction was 370 µg/mL. Ninety-five peptide sequences within the permeate fraction were determined using mass spectrometry and eight peptides were selected for chemical synthesis based on in silico analysis. Synthesized peptides were novel based on a search of the literature and relevant databases. In silico, simulated gastrointestinal digestion identified further peptides with bioactivities including ACE-1 inhibitory peptides and peptides with antithrombotic and calcium/calmodulin-dependent kinase II (CAMKII) inhibition. This work highlights the potential of Nannochloropsis oculata biomass as both a protein and bioactive peptide resource, which could be harnessed for use in the development of functional foods and feeds.
Different Extracellular β-Amyloid (1-42) Aggregates Differentially Impair Neural Cell Adhesion and Neurite Outgrowth through Differential Induction of Scaffold Palladin
Authors: Zhang Tianyu , Song Chuli , Li He , Zheng Yanru , Zhang Yingjiu
Published: December 2022

Extracellular amyloid β-protein (1-42) (Aβ42) aggregates have been recognized as toxic agents for neural cells in vivo and in vitro. The aim of this study was to investigate the cytotoxic effects of extracellular Aβ42 aggregates in soluble (or suspended, SAβ42) and deposited (or attached, DAβ42) forms on cell adhesion/re-adhesion, neurite outgrowth, and intracellular scaffold palladin using the neural cell lines SH-SY5Y and HT22, and to elucidate the potential relevance of these effects. The effect of extracellular Aβ42 on neural cell adhesion was directly associated with their neurotrophic or neurotoxic activity, with SAβ42 aggregates reducing cell adhesion and associated live cell de-adherence more than DAβ42 aggregates, while causing higher mortality. The reduction in cell adhesion due to extracellular Aβ42 aggregates was accompanied by the impairment of neurite outgrowth, both in length and number, and similarly, SAβ42 aggregates impaired the extension of neurites more severely than DAβ42 aggregates. Further, the disparate changes of intracellular palladin induced by SAβ42 and DAβ42 aggregates, respectively, might underlie their aforementioned effects on target cells. Further, the use of anti-oligomeric Aβ42 scFv antibodies revealed that extracellular Aβ42 aggregates, especially large DAβ42 aggregates, had some independent detrimental effects, including physical barrier effects on neural cell adhesion and neuritogenesis in addition to their neurotoxicity, which might be caused by the rigid C-terminal clusters formed between adjacent Aβ42 chains in Aβ42 aggregates. Our findings, concerning how scaffold palladin responds to extracellular Aβ42 aggregates, and is closely connected with declines in cell adhesion and neurite outgrowth, provide new insights into the cytotoxicity of extracellular Aβ42 aggregates in Alzheimer disease.
Path Planning with Time Windows for Multiple UAVs Based on Gray Wolf Algorithm
Authors: Zhang Changchun , Liu Yifan , Hu Chunhe
Published: December 2022

The Gray Wolf (GWO) algorithm aims to address the path planning problem of multiple UAVs, and the scene setting is mainly to avoid threats, meet the constraints of UAVs themselves and avoid obstacles between UAVs. The scene setting is relatively simple. To address such problems, the problem of time windows is considered in this paper, so that the UAV can arrive at the same time, and the Gray Wolf algorithm is used to optimize the problem. Finally, the experimental results verify that the proposed method can plan a safe flight path in the process of multi-UAV flight and reach the goal point at the same time. The mean error of flight time between UAVs of the GWO is 0.213, which is superior to PSO (0.382), AFO (0.315) and GA (0.825).
Biomechanical and Sensory Feedback Regularize the Behavior of Different Locomotor Central Pattern Generators
Authors: Deng Kaiyu , Hunt Alexander J. , Szczecinski Nicholas S. , Tresch Matthew C. , Chiel Hillel J. , Heckman C. J. , Quinn Roger D.
Published: December 2022

This work presents an in-depth numerical investigation into a hypothesized two-layer central pattern generator (CPG) that controls mammalian walking and how different parameter choices might affect the stepping of a simulated neuromechanical model. Particular attention is paid to the functional role of features that have not received a great deal of attention in previous work: the weak cross-excitatory connectivity within the rhythm generator and the synapse strength between the two layers. Sensitivity evaluations of deafferented CPG models and the combined neuromechanical model are performed. Locomotion frequency is increased in two different ways for both models to investigate whether the model’s stability can be predicted by trends in the CPG’s phase response curves (PRCs). Our results show that the weak cross-excitatory connection can make the CPG more sensitive to perturbations and that increasing the synaptic strength between the two layers results in a trade-off between forced phase locking and the amount of phase delay that can exist between the two layers. Additionally, although the models exhibit these differences in behavior when disconnected from the biomechanical model, these differences seem to disappear with the full neuromechanical model and result in similar behavior despite a variety of parameter combinations. This indicates that the neural variables do not have to be fixed precisely for stable walking; the biomechanical entrainment and sensory feedback may cancel out the strengths of excitatory connectivity in the neural circuit and play a critical role in shaping locomotor behavior. Our results support the importance of including biomechanical models in the development of computational neuroscience models that control mammalian locomotion.
Kinematic Analysis of Bionic Elephant Trunk Robot Based on Flexible Series-Parallel Structure
Authors: Huang Qitao , Wang Peng , Wang Yuhao , Xia Xiaohua , Li Songjing
Published: December 2022

Researchers borrow ideas from biological characteristics and behavior in design to make bionic robots that can meet unstructured and complex operating environments. The elephant trunk has been widely imitated by bionic robots because of its strong dexterity and stiffness adjustability. Due to the complex structure of the current elephant trunk robot, a series-parallel elephant trunk robot based on flexible rod actuation and a 6-degree-of-freedom (6-dof) parallel module is proposed in this paper. The bionic robot has a simple structure and redundant kinematics, which can realize the control of stiffness. This work focuses on the modeling of the flexible driving rod, the kinematics of a single parallel module, and the whole biomimetic robot. The kinematics are verified by simulation, which lays a foundation for future research on stiffness regulation.
Carob Seed Peels Effect on Cognitive Impairment and Oxidative Stress Status in Methionine-Induced Mice Models of Schizophrenia
Authors: Lakkab Imane , Ouakil Abdelmoughite , El Hajaji Hanane , Lachkar Nadya , Lefter Radu , Ciobica Alin , El Bali Brahim , Dobrin Romeo , Hritcu Luminita Diana , Lachkar Mohammed
Published: December 2022

Background:Ceratonia siliqua L. (Carob tree) is a Mediterranean evergreen, well known for its medicinal properties. The different parts of Carob were proven to exert antidiabetic, antibacterial, antifungal, and antiproliferative effects. Hence, the present paper aims to validate the positive correlation between the high antioxidant activity of carob seed peels and the improvement of negative symptoms of schizophrenia. Materials & Methods: The antioxidant activity was carried out using the β-carotene test. Methionine and carob seed peels (CSP) extracts (50 and 100 mg/kg) were orally administrated to mice for a week. After administration, behavioral tests were assessed using the Y-maze, elevated plus maze, and forced swimming tests, as well as the novel object recognition task. Furthermore, the oxidative stress status was evaluated by analyzing the levels of the antioxidant enzymes: Superoxide dismutase (SOD), glutathione peroxidase (GPx), and malondialdehyde levels (MDA). Results: Both extracts exhibited remarkable antioxidant activity and showed antibacterial effect against Gram-positive bacteria tested (Bacillus subtilis and Staphylococcus aureus) and against Pseudomonas aeruginosa (Gram-negative). Therefore, Escherichia coli was very resistant. The behavioral tests proved the efficacy of CSP in enhancing the cognitive impairment of animal models of schizophrenia. Hence, the stated correlation between oxidative stress and schizophrenia was confirmed by the increased SOD and GPx activities and the decreased MDA level. Conclusions: The present study gave further confirmation of the potential correlation between oxidative stress and the development of psychiatric disorders and highlighted the use of natural antioxidants, especially Ceratonia siliqua L. in the improvement of cognitive impairment in the dementia of schizophrenia.
Sex Differences in Emotions and Eating Behaviors among People Affected by Obesity
Authors: Mento Carmela , Rizzo Amelia , Bruno Antonio , Silvestri Maria Catena , Cedro Clemente , Komaei Iman , Navarra Giuseppe , Muscatello Maria Rosaria Anna
Published: December 2022

Relatively little research has examined sex differences among people affected by obesity. The aim of this study is to assess the relationship between negative emotions and eating behaviors, taking into account the role of biological sex. The final sample consists of 200 candidates for bariatric surgery, 62 males (31%) and 138 females (69%), aged from 18 to 60 years (M = 40.71; SD = 11.30). Participants were screened with the Binge Scale Questionnaire (BSQ) and individually evaluated with the Eating Disorder Inventory (EDI) and the Profile of Mood States (POMS). Correlations were calculated by splitting the sample by sex. Analyses of the relationship between negative emotions and eating behavior showed a large number of correlations in the sample of women and few correlations in men. The differences between women and men with obesity suggest the need for a different theoretical construct that explains the differentiated mechanisms of functioning and lays the foundations for specific therapeutic paths.
Mechanisms Underlying Cognitive Impairment Induced by Prenatal Alcohol Exposure
Authors: Alhowail Ahmad
Published: December 2022

Alcohol is one of the most commonly used illicit substances among pregnant women. Clinical and experimental studies have revealed that prenatal alcohol exposure affects fetal brain development and ultimately results in the persistent impairment of the offspring’s cognitive functions. Despite this, the rate of alcohol use among pregnant women has been progressively increasing. Various aspects of human and animal behavior, including learning and memory, are dependent on complex interactions between multiple mechanisms, such as receptor function, mitochondrial function, and protein kinase activation, which are especially vulnerable to alterations during the developmental period. Thus, the exploration of the mechanisms that are altered in response to prenatal alcohol exposure is necessary to develop an understanding of how homeostatic imbalance and various long-term neurobehavioral impairments manifest following alcohol abuse during pregnancy. There is evidence that prenatal alcohol exposure results in vast alterations in mechanisms such as long-term potentiation, mitochondrial function, and protein kinase activation in the brain of offspring. However, to the best of our knowledge, there are very few recent reviews that focus on the cognitive effects of prenatal alcohol exposure and the associated mechanisms. Therefore, in this review, we aim to provide a comprehensive summary of the recently reported alterations to various mechanisms following alcohol exposure during pregnancy, and to draw potential associations with behavioral changes in affected offspring.
Altered White Matter Microstructure in Herpes Zoster and Postherpetic Neuralgia Determined by Automated Fiber Quantification
Authors: Wu Ying , Gu Lili , Hong Shunda , Li Jiahao , Yang Jiaojiao , Xiong Jiaxin , Lv Huiting , Jiang Jian
Published: December 2022

This study aimed to explore changes in the white matter microstructure in herpes zoster (HZ) and postherpetic neuralgia (PHN) patients and to estimate the correlation of these changes with clinical data. Diffusion tensor imaging (DTI) data were collected from 33 HZ patients, 32 PHN patients, and 35 well-matched healthy controls (HCs). Subsequently, these data were analyzed by automated fiber quantification (AFQ) to accurately locate alterations in the white matter microstructure. Compared with HCs, HZ and PHN patients both showed a wide range of changes in the diffusion properties of fiber tracts. HZ patients exhibited changes primarily in the left superior longitudinal fasciculus (SLF), whereas PHN patients predominantly exhibited changes in the left inferior fronto-occipital fasciculus. The bilateral SLF and the left corticospinal tract were altered in the PHN patients compared with HZ patients. In addition, PHN patients showed a trend toward more expansive white matter alterations compared with those observed in HZ patients; additionally, in PHN patients, changes in the left cingulum cingulate were significantly correlated with changes in emotion and the duration of disease. These findings may help to elucidate the transformation from HZ to PHN and provide new ideas regarding the reasons for intractable neuropathic pain in PHN.
Population Perspectives on Impact of the COVID-19 Pandemic on Essential Health Services—Behavioral Insights from the Federation of Bosnia and Herzegovina
Authors: Cilović-Lagarija Šeila , Musa Sanjin , Hasanica Nino , Čerkez Goran , Palo Mirza , Majdan Marek , Scherzer Martha , Habersaat Katrine Bach , Smallwood Catherine , Tahirukaj Ardita , Nitzan Dorit
Published: December 2022

The aim of this study was to analyze the impact of the COVID-19 pandemic on patterns of use of essential health services (EHS), health-seeking behaviors, and population health and wellbeing in the Federation of Bosnia and Herzegovina (FBiH) from the perspective of its adult population. A population-based survey was implemented in the FBiH in December 2020 on a sample of 1068 adults. Overall, 64% of respondents received care, significantly more being women (67% vs. 61%, p = 0.046), those with a chronic disease (CD) (75% vs. 65%, p < 0.001), and of an older age (58% in 18–34 vs. 67% in older, p = 0.031). These groups also postponed care more often (39% in 55+ vs. 31% in 18–34 years old, p = 0.01; 55% with CD vs. 31% without, p < 0.001; and 43% in females vs. 32% males, p < 0.001). Main reasons for postponing care were lack of available appointments and fear of infection. The presence of a CD was the strongest predictor of need, access, and disruptions of health care. Respondents reported increased expenses for medicines (40%) and health services (30%). The findings of the survey add user insights into EHS disruptions to existing health statistics and other data and may be used to inform strategies for mitigating the impact of COVID-19 on the disruption of health care services, strengthening health system preparedness and building resilience for future emergencies.
Axial Compression Test and Numerical Investigation of Concrete-Filled Double-Skin Elliptical Tubular Short Columns
Authors: Li Jingzhe , Shen Qihan , Wang Jingfeng , Li Beibei , Li Guoqiang
Published: December 2022

To probe into the performance of concrete-filled double-skin elliptical steel tubular (CFDEST) members, this paper designs and conducts an experiment on CFDEST short columns imposed with axial pressure, and finite element (FE) models of the axially compressed CFDEST stub columns are established and verified by the test outcomes, taking the influences of elliptical cross-section and hollow ratio into account. The impressions of various parameters, such as hollow ratio, diameter-to-thickness ratio, aspect ratio and so on, on the load-bearing capacity, initial rigidity and ductility property were investigated systematically. Moreover, the typical failure modes, contact pressure and concrete longitudinal stress of the axially compressed CFDEST short column are revealed. In light of the findings acquired by the laboratory tests and numerical analyses, the calculation formulae for evaluating the axial compress capacity of the CFDEST short column are proposed by taking the impact of the sectional aspect ratio and hollow ratio into account. The results indicate that the failure morphologies of axially compressed CFDEST short columns mainly include outward local bulges of the outside EST, the inward bulges of the inside EST and the crushing of core concrete. The axial compress capacity of the CFDEST short column would increase with the decrease in the sectional hollow ratio and aspect ratio. The calculation method is proved to be an accurate and reliable approach to evaluate the axial compress capacity of the CFDEST short column.
Contribution of New Digital Technologies to the Digital Building Logbook
Authors: Gómez-Gil Marta , Espinosa-Fernández Almudena , López-Mesa Belinda
Published: December 2022

According to the European Commission, the Digital Building Logbook (DBL) is a repository of all of the relevant data of a building. It was first introduced at the European scale in the Renovation Wave strategy and was first defined in the proposal for the recast of the energy performance of buildings Directive in December 2021. The European DBL has not been implemented yet, since a common model does not yet exist. Even though great efforts are being made to establish it, some relevant issues need to be addressed first. One of them is the identification of data sources that will feed the DBL. Existing digital data sources have already been explored in some countries and they have been found to be insufficient. In this paper, new digital data sources suitable for the logbook are identified, and their contribution in terms of indicators and interoperability is analysed. The analysis shows that these sources have great potential to contribute to the DBL, because they bring the possibility to collect a great amount of real data on buildings. However, the main barrier for these tools to be incorporated into the DBL is that their linkage still requires further research.
Research on Displacement Field of Soil around Pile with Different Density Based on Particle Image Testing Technology
Authors: Zhang Xiujie , Li Hongzhong , Xu Kaiyan , Ma Zhanwu , Wang Yonghong , Yan Rongtao
Published: December 2022

Particle image testing technology has the advantages of non-intervention and high precision. In this paper, the particle image testing technology is combined with the indoor model test to explore the displacement development trend of the soil around the horizontal loaded pile under the difference of soil properties between layers. The principle of PIV technology is described, and the single-layer soil test group and the layered soil test group are set up, respectively. To this end, the indoor model test is carried out by changing the soil density. The study reveals that particle image testing technology can reduce the influence of data acquisition equipment on model tests in the maximum range, and restore the development trend of surface soil displacement in the horizontal load pile test to the greatest extent. Under the same load, the displacement influence area formed in front of and behind the pile of the two groups of tests takes the shape of a spindle centred on the pile body. The influence range of surface soil decreases with the increase of density. Moreover, the results of Tecplot analysis show that the soil stiffness is ranked from small to large as follows: single layer coarse sand, upper layer large particle size and lower layer small particle size test group, upper layer small particle size and lower layer large particle size test group, single layer fine sand. The test results can provide reference for the deepening of practical engineering.
Effects of Vertical Ground Motion on Pedestrian-Induced Vibrations of Footbridges: Numerical Analysis and Machine Learning-Based Prediction
Authors: Wei Xinxin , Fu Bo , Wu Wenyan , Liu Xinrui
Published: December 2022

Current codes and guidelines for the dynamic design of footbridges often only specify the pedestrian-induced excitations. However, earthquakes may occur during the passing stage of pedestrians in earthquake-prone regions. In addition, modern footbridges tend to be slender and are sensitive to vertical ground motions. Therefore, we investigate the effects of vertical ground motion on pedestrian-induced vibrations of footbridges. A total of 138 footbridges with different materials, dimensions, and structural types are considered as the target structures. The classical social force model combined with the pedestrian-induced load is used to simulate crowd loads for the scenarios with six typical pedestrian densities. Furthermore, 59 vertical ground motions with four seismic intensities are taken as the seismic inputs. An amplification factor is introduced to quantify the amplification effects of vertical ground motion on human-induced vibrations of footbridges. Four machine learning (ML) algorithms are used to predict the amplification factor. The feature importance indicates that the scaled peak ground acceleration, the pedestrian density, and the bridge span are the three most important parameters influencing the amplification factor. Finally, the vibration serviceability of the footbridge subjected to both crowd load and vertical ground motion is assessed.
Good Timing Matters: The Spatially Fractionated High Dose Rate Boost Should Come First
Authors: Schültke Elisabeth , Jaekel Felix , Bartzsch Stefan , Bräuer-Krisch Elke , Requardt Herwig , Laissue Jean Albert , Blattmann Hans , Hildebrandt Guido
Published: December 2022

Monoplanar microbeam irradiation (MBI) and pencilbeam irradiation (PBI) are two new concepts of high dose rate radiotherapy, combined with spatial dose fractionation at the micrometre range. In a small animal model, we have explored the concept of integrating MBI or PBI as a simultaneously integrated boost (SIB), either at the beginning or at the end of a conventional, low-dose rate schedule of 5x4 Gy broad beam (BB) whole brain radiotherapy (WBRT). MBI was administered as array of 50 µm wide, quasi-parallel microbeams. For PBI, the target was covered with an array of 50 µm × 50 µm pencilbeams. In both techniques, the centre-to-centre distance was 400 µm. To assure that the entire brain received a dose of at least 4 Gy in all irradiated animals, the peak doses were calculated based on the daily BB fraction to approximate the valley dose. The results of our study have shown that the sequence of the BB irradiation fractions and the microbeam SIB is important to limit the risk of acute adverse effects, including epileptic seizures and death. The microbeam SIB should be integrated early rather than late in the irradiation schedule.