bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Effect of Capillary Water Absorption on the Resistivity of Cementitious Materials
Authors: He Xiangyu , Zeng Xiaohui , Dong Rongzhen , Yang Jiangfan
Published: March 2023

In a humid environment, the stray current generated by subway operation will corrode the underground pipe network and the internal steel structure of the track plate, which will seriously affect the service life of the subway track plate and increase the maintenance cost later. Groundwater in subway projects mainly enters the concrete interior through capillary action and affects the concrete resistivity, and there is a lack of research on the mechanism of groundwater effect on concrete resistance. In this study, the variation of cement mortar resistivity with capillary water absorption time for cement mortar with different amounts of mineral admixtures (fly ash, ground-granulated blast furnace slag, and silica fume) was measured by the four-electrode method, and the mechanism of the influence of the electrical properties of cementitious materials under the effect of capillary water absorption was analyzed based on the mercury-pressure method (MIP) and thermogravimetric method (TG-DTG). The results show that with the increase in capillary water absorption time, the change curve of cement mortar resistivity can be divided into two stages; in the first stage, capillary water absorption leads to gel pores and transition pores quickly connecting to capillary pores and other large pores to form a water-saturated conductive pathway, resulting in a rapid decrease in resistivity, when the gel pores and excessive pores have a greater impact on resistivity. The second stage is that of capillary water absorption, to a certain extent, after the specimen’s internal water upward development rate slows down; at this time, the formation speed of the conductive pathway decreases, resulting in the rate of change in resistivity decreasing and gradually stabilizing. The incorporation of silica fume can effectively improve the resistivity of cementitious materials under the action of capillary water absorption, in which the resistivity of specimens incorporated with 15% silica fume after 36 days of capillary water absorption is 10.39 times that of the reference group, which is mainly due to its lower porosity and a higher percentage of gel pores.
Electrocardiogram Analysis by Means of Empirical Mode Decomposition-Based Methods and Convolutional Neural Networks for Sudden Cardiac Death Detection
Authors: Centeno-Bautista Manuel A. , Rangel-Rodriguez Angel H. , Perez-Sanchez Andrea V. , Amezquita-Sanchez Juan P. , Granados-Lieberman David , Valtierra-Rodriguez Martin
Published: March 2023

Sudden cardiac death (SCD) is a global health problem, which represents 15–20% of global deaths. This type of death can be due to different heart conditions, where ventricular fibrillation has been reported as the main one. These cardiac alterations can be seen in an electrocardiogram (ECG) record, where the heart’s electrical activity is altered. The present research uses these variations to be able to predict 30 min in advance when the SCD event will occur. In this regard, a methodology based on the complete ensemble empirical mode decomposition (CEEMD) method to decompose the cardiac signal into its intrinsic mode functions (IMFs) and a convolutional neural network (CNN) for automatic diagnosis is proposed. Results for the ensemble empirical mode decomposition (EEMD) method and the empirical mode decomposition (EMD) method are also compared. Results demonstrate that the combination of the CEEMD and the CNN is a potential solution for SCD prediction since 97.5% of accuracy is achieved up to 30 min in advance of the SCD event.
Cyclodextrin Polymers as a Promising Drug Carriers for Stabilization of Meropenem Solutions
Authors: Yakupova Linara R. , Skuredina Anna A. , Markov Pavel O. , Le-Deygen Irina M. , Kudryashova Elena V.
Published: March 2023

Here we report the development of new drug carriers for meropenem based on the hydroxypropyl-β-cyclodextrin (HPCD) polymers with variable linkers, namely, 1,6-hexamethylenediisocyanate (HMD), citric acid (CA), succinic anhydride (SA). The structures of obtained polyesters and polyurethanes nanoparticles (120–200 nm) were investigated by NMR and FTIR-spectroscopy. The PXRD pattern demonstrated that HPCD polymers form complexes with meropenem (MP), and the majority of MP molecules are encapsulated into a complex. MP’s imprinting in the HPCD-HMD polymer matrix lead to an encapsulation efficiency of up to 82%. HPCD-HMD and HPCD-SA polymers increase MP’s stability during the storage of its aqueous solution (in 1.4 and 1.2 times, respectively). In contrast, HPCD-CA polymer negatively affects MP’s stability. In prospect, the HPCD-HMD polymer may be promising for the development of a highly efficient drug delivery system for MP.
Structure Defects and Photovoltaic Properties of TiO2:ZnO/CuO Solar Cells Prepared by Reactive DC Magnetron Sputtering
Authors: Wisz Grzegorz , Sawicka-Chudy Paulina , Wal Andrzej , Sibiński Maciej , Potera Piotr , Yavorskyi Rostyslaw , Nykyruy Lyubomyr , Płoch Dariusz , Bester Mariusz , Cholewa Marian , Chernikova Olena M.
Published: March 2023

The problem of copper diffusion in semiconductor devices has been known for several decades as copper has been used as an interconnecting (bonding) metal and has been intensively studied due to its high diffusion coefficient. The influence of the intensive diffusion of copper, depending on the technology of the deposition regimes, has been investigated in thin-film solar cells based on copper, zinc, and titanium oxides obtained by DC-reactive magnetron sputtering. The observed effect significantly changes the structure of the CuO films and affects the properties of the TiO2:ZnO/CuO photocell. The composition of the layers and the copper diffusion in the photocells were studied using a cross-section obtained by scanning electron microscopy (SEM). The influence of the copper diffusion in the layers on the current–voltage (I-V) and power–voltage (P-V) characteristics and optical properties was investigated. The photoelectric behavior of two structures of thin-film solar cells was confirmed through -V research. The values of the open-circuit voltage (VOC) and short-circuit current density (JSC) of photovoltaic devices reached (11 ÷ 15) mV and (6.1 ÷ 6.8) μA, respectively. Furthermore, the Pmax, FF, RS, and RSH values were calculated and analyzed. The difference in the composition of the upper layer of the structure caused changes in the reflection spectra in the wavelength range of 190–2500 nm and, depending on the wavelength, varies in the range of 0–27%.
Coordinated Control Method for Passive Bus Priority Arterials Considering Multi-Conversion Standard and Bus Stopping Time
Authors: Zou Liang , Li Zhifan , Zhu Lingxiang , Yu Zhitian
Published: March 2023

Public transport priority is the development trend in public transport, and signal priority is its main means. In order to further improve the accuracy of delay calculation and realize the priority of bus signals, this paper proposes the idea of multiple conversion criteria and consideration of stop time for the coordination and control of bus and car mixed traffic flow trunk roads. First of all, on the basis of in-depth analysis of the differences in the characteristics of bus and car models, a multi-conversion standard delay calculation method is proposed, and its effectiveness is verified by simulation. The results show that compared with the single conversion standard delay calculation method, the average delay error of cars and buses calculated by this method is reduced by 22.54% and 82.21%, respectively. Then, the influence of bus stops on bus speed and delay is further analyzed, and the coordinated control model of bus priority trunk roads considering bus stops is constructed with the passenger capacity of each bus line and the per capita delay as the goal, and the solution is given. Finally, 178 randomly generated examples are used to verify and analyze the effectiveness and sensitivity of this model.
A Reinforcement Learning-Based Congestion Control Approach for V2V Communication in VANET
Authors: Liu Xiaofeng , Amour Ben St. , Jaekel Arunita
Published: March 2023

Vehicular ad hoc networks (VANETs) are crucial components of intelligent transportation systems (ITS) aimed at enhancing road safety and providing additional services to vehicles and their users. To achieve reliable delivery of periodic status information, referred to as basic safety messages (BSMs) and event-driven alerts, vehicles need to manage the conflicting requirements of situational awareness and congestion control in a dynamic environment. To address this challenge, this paper focuses on controlling the message transmission rate through a Markov decision process (MDP) and solves it using a novel reinforcement learning (RL) algorithm. The proposed RL approach selects the most suitable transmission rate based on the current channel conditions, resulting in a balanced performance in terms of packet delivery and channel congestion, as shown by simulation results for different traffic scenarios. Additionally, the proposed approach offers increased flexibility for adaptive congestion control through the design of an appropriate reward function.
Response of Seismically Damaged Steel Reduced Beam Section Joints under Fire
Authors: Tartaglia Roberto , D’Aniello Mario , Landolfo Raffaele
Published: March 2023

The behaviour of seismically damaged steel joints with reduced beam section (RBS) at elevated temperatures has not been widely investigated yet. Therefore, the study summarized in this article aimed to (i) analyse the response of RBS joints at high temperatures and (ii) investigate the influence of plastic damage, due to cyclic loading, on the fire performance of the joints. A set of RBS joints with rib stiffeners on the both lower and upper beam flanges was designed according to European standards and the following parameters were considered: (i) location of the joint (i.e., internal or external joint) and (ii) reduction in the beam flexural resistance (i.e., 65% or 80% of the beam plastic moment). The mechanical response of these joints was simulated by means of finite element models (FEM). The accuracy and effectiveness of the adopted modelling assumptions to mimic the seismic response of the joints were validated against experimental results available from the existing literature. The numerical results highlight that under cyclic loading, all investigated joints exhibit ductile behaviour, allowing the concentration of the plastic deformation within the reduced segment of the beam. The designed reduction in the beam flexural resistance influences the joint fire performance, being impaired in the cases with lower flexural resistance. In contrast, the imposed cyclic pre-damage does not appreciably affect the fire resistance of the investigated joints.
Apportioning Human-Induced and Climate-Induced Land Degradation: A Case of the Greater Sekhukhune District Municipality
Authors: Kgaphola Motsoko Juniet , Ramoelo Abel , Odindi John , Mwenge Kahinda Jean-Marc , Seetal Ashwin
Published: March 2023

Land degradation (LD) is a global issue that affects sustainability and livelihoods of approximately 1.5 billion people, especially in arid/semi-arid regions. Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate sustainable land management interventions. Therefore, using vegetation as a proxy for LD, this study aimed to distinguish anthropogenic from rainfall-driven LD in the Greater Sekhukhune District Municipality from 1990 to 2019. It is widely established that rainfall highly correlates with vegetation productivity. A linear regression was performed between the Normalized Difference Vegetation Index (NDVI) and rainfall. The human-induced LD was then distinguished from that of rainfall using the spatial residual trend (RESTREND) method and the Mann–Kendall (MK) trend. RESTREND results showed that 11.59% of the district was degraded due to human activities such as overgrazing and injudicious rangeland management. While about 41.41% was degraded due to seasonal rainfall variability and an increasing frequency of droughts. Climate variability affected vegetation cover and contributed to different forms of soil erosion and gully formation. These findings provide relevant spatial information on rainfall or human-induced LD, which is useful for policy formulation and the design of LD mitigation measures in semi-arid regions.
Application of Radial Type Multifiber Media Filtration Process for Combined Sewer Overflow Treatment
Authors: Kim Heejin , Shim Intae , Lee Donghyeon , Hong Bongchang , Kim Hyungjun , Lee Sangmin , Hwang Tae-Mun
Published: March 2023

Fiber media filtration for combined sewer overflow (CSO) treatment was evaluated in this work. Pilot-scale experiments of CSO treatment involve seven layers that form radial-type fiber media filters. The fiber media filter was characterized using analysis techniques and exhibited extremely high hydrophobicity and negative charge. The results obtained for a sewer treatment plant at Tancheon in Seoul revealed potential for suspended solid, total organic carbon, and biochemical oxygen demand removal with efficiencies of 89.6%, 56%, and 42%, respectively. The results are consistent with the sieving effects and electrostatic repulsion between fiber media and pollutants. Head loss was induced by organic pollutants and was 10.5 cm after 20 h of operation. To mitigate the head loss induced by organic pollutants on the fiber media filter, sodium hypochlorite (NaClO) was used as a chemical backwashing agent. An NaClO concentration of 2000 mg/L with a soaking time of 24 h yielded an optimal head loss recovery of 96.2% of the initial head loss obtained for the virgin fiber media filter without media filter degradation. The result of the present study will provide practical insight and act as a technical guide for CSO treatment plant engineers.
IoT-Based Bi-Cluster Forecasting Using Automated ML-Model Optimization for COVID-19
Authors: Tariq Hasan , Touati Farid , Crescini Damiano , Mnaouer Adel Ben
Published: March 2023

The current COVID-19 pandemic has raised huge concerns about outdoor air quality due to the expected lung deterioration. These concerns include the challenges associated with an increase of harmful gases like carbon dioxide, the iterative/repetitive inhalation due to mask usage, and harsh environmental temperatures. Even in the presence of air quality sensing devices, these challenges can hinder the prevention and treatment of respiratory diseases, epidemics, and pandemics in severe cases. In this research, a dual time series with a bi-cluster sensor data-stream-based novel optimized regression algorithm was proposed with optimization predictors and responses that use an automated iterative optimization of the model based on the similarity coefficient index. The algorithm was implemented over SeReNoV2 sensor nodes data, i.e., a multi-variate dual time-series sensor, of the environmental and US Environmental Protection Agency standard, which measures variables for the air quality index using air quality sensors with geospatial profiling. The SeReNoV2 systems were placed at four locations that were 3 km apart to monitor the air quality and their data was collected at Ubidots IoT platform over GSM. The results have shown that the proposed technique achieved a root mean square error (RMSE) of 1.0042 with a training time of 469.28 s for the control and an RMSE of 1.646 in a training time of 28.53 s when optimized. The estimated R-Squared error was 0.03, with the Mean-Square Error for temperature being 1.0084 °C, and 293.98 ppm for CO2. Furthermore, the Mean-Absolute Error (MAE) for temperature was 0.66226 °C and 10.252 ppm for the correlated-CO2 at a predicted speed of ~5100 observations/s. In the sample cluster for temperature, 45,000 observations/s for CO2 was achieved due to the iterative optimization of the training time (469.28 s). The correlated temperature and a time of 28.53 s for CO2 were very promising in forecasting COVID-19 countermeasures before time.
Distribution and Meteorological Control of PM2.5 and Its Effect on Visibility in Northern Thailand
Authors: Amnuaylojaroen Teerachai , Kaewkanchanawong Phonwilai , Panpeng Phatcharamon
Published: March 2023

In the dry season, the north of Thailand always experiences reduced air quality, reduced visibility, and public health exposure from the burning of biomass domestically and in surrounding countries. The purpose of this research was to investigate the distribution and the meteorological control of PM2.5 accumulation, as well as its effect on visibility in northern Thailand in 2020. The Geographic Information System (GIS) was applied for the analysis of the spatial distribution, while Pearson’s correlation coefficient was utilized to examine the association between PM2.5 and meteorological variables. The results showed that the PM2.5 concentrations were in the range of 16–195 μg/m3 in 2020. The high level of PM2.5 in Lampang, Chiang Rai, and Chiang Mai provinces was in the range of 150 to 195 μg/m3 from January to May. Favorable meteorological conditions included low wind and relative humidity, and high temperatures contributed to high PM2.5 concentrations in northern Thailand. Domestic burning and burning in neighboring countries contribute to huge amounts of smoke that cause low visibility in northern Thailand, especially at 1 km above ground level, with a reduced visibility in the range of 70–90% for all provinces in April.
Responses of Runoff and Its Extremes to Climate Change in the Upper Catchment of the Heihe River Basin, China
Authors: Li Zhanling , Li Wen , Li Zhanjie , Lv Xiaoyu
Published: March 2023

Understanding the impact of climate change on runoff and its extremes is of great significance for water resource assessment and adaptation strategies, especially in water-scarce regions. This study aims to analyze the impact of future climate change on runoff and its extremes in the upper reaches of the Heihe River basin in northwest China. The projected runoff was derived using the Soil Water Assessment Tool with climate data from the CSIRO-MK-3-6-0 model under the scenario of RCP4.5, and a frequency analysis of runoff was performed by generalized extreme value distribution. The results indicate that, compared with the baseline period of 1961 to 2000, the minimum and maximum temperatures in the period 2031 to 2070 were predicted to increase by 2.5 °C on average. The precipitation in most months was also predicted to increase, with an average rise of 16.5%. The multi-year average runoff was projected to increase by 8%. The annual mean and extreme flows were also expected to rise under future climate change at different return periods, and the low flow was expected to increase the most.
Deployment and Evaluation of a Network of Open Low-Cost Air Quality Sensor Systems
Authors: Schneider Philipp , Vogt Matthias , Haugen Rolf , Hassani Amirhossein , Castell Nuria , Dauge Franck R. , Bartonova Alena
Published: March 2023

Low-cost air quality sensors have the potential to complement the regulatory network of air quality monitoring stations, with respect to increased spatial density of observations, however, their data quality continues to be of concern. Here we report on our experience with a small network of open low-cost sensor systems for air quality, which was deployed in the region of Stavanger, Norway, under Nordic winter conditions. The network consisted of AirSensEUR sensor systems, equipped with sensors for, among others, nitrogen dioxide and fine particulate matter. The systems were co-located at an air quality monitoring station, for a period of approximately six weeks. A subset of the systems was subsequently deployed at various roadside locations for half a year, and finally co-located at the same air quality monitoring station again, for a post-deployment evaluation. For fine particulate matter, the co-location results indicate a good inter-unit consistency, but poor average out-of-the-box performance (R2 = 0.25, RMSE = 9.6 μg m−3). While Köhler correction did not significantly improve the accuracy in our study, filtering for high relative humidity conditions improved the results (R2 = 0.63, RMSE = 7.09 μg m−3). For nitrogen dioxide, the inter-unit consistency was found to be excellent, and calibration models were developed which showed good performance during the testing period (on average R2 = 0.98, RMSE = 5.73 μg m−3), however, due to the short training period, the calibration models are likely not able to capture the full annual variability in environmental conditions. A post-deployment co-location showed, respectively, a slight and significant decrease in inter-sensor consistency for fine particulate matter and nitrogen dioxide. We further demonstrate, how observations from even such a small network can be exploited by assimilation in a high-resolution air quality model, thus adding value to both the observations and the model, and ultimately providing a more comprehensive perspective of air quality than is possible from either of the two input datasets alone. Our study provides valuable insights on the operation and performance of an open sensor system for air quality, particularly under challenging Nordic environmental conditions.
Interdecadal Variation in Rossby Wave Source over the Tibetan Plateau and Its Impact on the East Asia Circulation Pattern during Boreal Summer
Authors: Ding Yihui , Sun Xiaoting , Li Qingquan , Song Yafang
Published: March 2023

The wave activity flux representing the energy propagation direction of planetary Rossby wave generally originates from a large wave source area. This study investigates the interdecadal variability and formation mechanism of Rossby wave source over the Tibetan Plateau (TP-RWS) and its impact on the atmospheric circulation and precipitation pattern in East Asia based on the ERA-20C reanalysis dataset in summer (June–July–August) during 1900 to 2010. Results show that the region with the maximum variabilities of Rossby wave source (RWS) in the past 110 years appears over the Tibetan Plateau (TP) during boreal summer, and the TP-RWS shows prominent characteristics of interdecadal oscillation. Secondly, the TP-RWS is mainly composed of the vortex stretching term (RWS-S1) and the absolute vorticity advection term (RWS-S2). The interdecadal TP-RWS is a synergistic result of the snow cover over northwestern TP associated with the RWS-S1, and the deep convection over southeastern TP associated with the RWS-S2. Furthermore, the interdecadal TP-RWS can lead to an alternatively positive and negative pattern of geopotential height anomalies from the northwestern TP to the North Pacific, which has a great climate effect on the precipitation in Huang-huai River Basin, South Korea and Japan Island. Under the guidance of the anomalous cyclonic circulation in East Asia, the prevailing southerly and easterly winds occur over the West Pacific and the Huang-huai River Basin, which lead to the water vapor convergence and upward movement at middle and lower troposphere.
Extreme Low-Visibility Events Prediction Based on Inductive and Evolutionary Decision Rules: An Explicability-Based Approach
Authors: Peláez-Rodríguez César , Marina Cosmin M. , Pérez-Aracil Jorge , Casanova-Mateo Carlos , Salcedo-Sanz Sancho
Published: March 2023

In this paper, we propose different explicable forecasting approaches, based on inductive and evolutionary decision rules, for extreme low-visibility events prediction. Explicability of the processes given by the rules is in the core of the proposal. We propose two different methodologies: first, we apply the PRIM algorithm and evolution to obtain induced and evolved rules, and subsequently these rules and boxes of rules are used as a possible simpler alternative to ML/DL classifiers. Second, we propose to integrate the information provided by the induced/evolved rules in the ML/DL techniques, as extra inputs, in order to enrich the complex ML/DL models. Experiments in the prediction of extreme low-visibility events in Northern Spain due to orographic fog show the good performance of the proposed approaches.
Nonparametric Directional Dependence Estimation and Its Application to Cryptocurrency
Authors: Noh Hohsuk , Jang Hyuna , Kim Kun Ho , Kim Jong-Min
Published: March 2023

This paper proposes a nonparametric directional dependence by using the local polynomial regression technique. With data generated from a bivariate copula having a nonmonotone regression structure, we show that our nonparametric directional dependence is superior to the copula directional dependence method in terms of the root-mean-square error. To validate the directional dependence with real data, we use the log returns of daily prices of Bitcoin, Ethereum, Ripple, and Stellar. We conclude that our nonparametric directional dependence, by using the local polynomial regression technique with asymmetric-threshold GARCH models for marginal distributions, detects the directional dependence better than the copula directional dependence method by an asymmetric GARCH model.
Learning the Parameters of ELECTRE-Based Primal-Dual Sorting Methods that Use Either Characteristic or Limiting Profiles
Authors: Navarro Jorge , Fernández Eduardo , Solares Efrain , Flores Abril , Díaz Raymundo
Published: March 2023

Two multicriteria-sorting methods that generalize the relational paradigm have been recently presented in the literature. One uses objects representative of classes, the other uses objects in the limiting boundaries of classes; both can use either a reflexive or an asymmetric preference relation. However, defining the parameters of relation-based methods is not straightforward. The present work operationalizes those methods with a methodology that takes examples provided by the decision-maker and, using an accuracy measure that specifically fits the characteristics of the methods, exploits an evolutionary algorithm to determine the parameters that best reproduce such examples. The assessment of the proposal showed that (i) it can achieve considerably high levels of out-of-sample effectiveness with only a few decision examples; (ii) the inference process is more effective learning the parameters of the method based on representative objects; (iii) it tends to be more effective with a reflexive relation; (iv) the effectiveness decreases while increasing the number of classes, which is not always the case when increasing the number of criteria. Theoretical properties of the proposed methodology will be investigated in future works.
Genetic Diversity and Connectivity of Ocypode ceratophthalmus in the East and South China Seas and Its Implications for Conservation
Authors: Zhao Feng , Liu Yue , Wang Zihan , Lu Jiaying , Cao Ling , Zeng Cong
Published: March 2023

The East and South China Seas are rich in marine resources, but they are also under great pressure from climate change and human activities. Maintaining diversity and connectivity between communities is thought to be effective in mitigating these pressures. To assess the diversity and connectivity among the populations of Ocypode ceratophthalmus in the East and South China Seas, 15 populations from or near 15 marine protected areas in the two seas were studied using COI and D-Loop as genetic markers. The results showed that O. ceratophthalmus populations had high diversity, and the results of a hierarchical analysis of molecular variance and fixation index found that there were no significant genetic structures among these populations. High historical gene flow and high migration rates were further observed among populations by Migrate-n. Furthermore, the COI sequences further showed the asymmetric migration rate with a higher migration rate from south to north than from north to south. This information could provide recommendations for the management of marine protected areas in the East and South China Seas.
Zingiber officinale Roscoe Rhizome Extract Exerts Senomorphic and Anti-Inflammatory Activities on Human Endothelial Cells
Authors: Matacchione Giulia , Borgonetti Vittoria , Ramini Deborah , Silvestrini Andrea , Ojetti Marta , Galeotti Nicoletta , Olivieri Fabiola
Published: March 2023

Aging is related to a low-grade and sterile inflammation called inflammaging, recognized as the main risk factor for age-related disease (ARD) development. Inflammaging is fostered by the repeated activation of immune cells, as well as by the accumulation of senescent cells. Recently, a number of natural compounds have gained attention to be tested as anti-aging therapies, based on their anti-inflammatory activity and/or ability to reduce the pro-inflammatory secretome of senescent cells (senomorphyc activity). Here, we investigated the anti-inflammatory and senomorphic properties of an Asian-native Zingiber officinale Roscoe extract (ZOE), commonly consumed as a food spice and herbal medicine. We employed two models of primary endothelial cells (HUVECs), such as the replicative-senescence and LPS-induced response, to investigate the anti-inflammatory/senomorphic effect of ZOE, and one cellular model of neuroinflammation, i.e., immortalized murine microglial cells (BV2). First, we found that the ZOE treatment induced the inhibition of NF-kB activation in BV2 cells. Among the constituents of ZOE, we showed that the terpenoid-enriched fraction (ZTE) was the component able to counteract the phosphorylation of NF-kB(p65), while 6-gingerol (GIN) and 6-shogaol (SHO) did not produce any significant effect. Further, we observed that the treatment with 10 µg/mL of ZOE exerted anti-inflammatory activity on LPS-stimulated young (y)HUVEC and senomorphyc activity on replicative senescent (s)HUVEC, significantly reducing the expression levels of IL-1β, TNF -α, IL-8, MCP-1, and ICAM-1. Moreover, the ZTE treatment was able to significantly reduce the IL-8 levels secreted in the medium of both LPS-stimulated yHUVEC and sHUVEC. Overall, our data suggest a potential protective role of ZOE on neuroinflammation and endothelial inflammation/activation, thus suggesting its potential relevance in delaying/postponing ARD development and progression, characterized by endothelial dysfunction.
Screening of EWI-2-Derived Peptides for Targeting Tetraspanin CD81 and Their Effect on Cancer Cell Migration
Authors: Suwatthanarak Thanawat , Usuba Kei , Kuroha Kotomi , Tanaka Masayoshi , Okochi Mina
Published: March 2023

CD81, a transmembrane protein belonging to the tetraspanin family, has recently been suggested as a therapeutic target for cancers. Here, we screened peptides that bind to the tetraspanin CD81 protein, and evaluated their inhibitory activity in cancer cell migration. To screen for CD81-binding peptides (CD81-BP), a peptide array membrane was prepared from the amino acid sequence of the EWI-2 protein, a major partner of CD81, before binding to fluorescently labeled CD81. As a result, four candidate CD81-BPs were identified and characterized. In particular, the CFMKRLRK peptide (called P152 in this study) was found to be the best candidate that preferentially binds to the extracellular loop of CD81, with an estimated dissociation constant of 0.91 µM. Since CD81 was reported to promote cancer cell migration, an initial step in metastasis, the Boyden chamber assay, was next performed to assess the effect of CD81-BP candidates on the migration of MDA-MB-231 human breast cancer cells. Interestingly, our result indicated that P152 could suppress MDA-MB-231 cell migration at the level comparable to that of an anti-human CD81 antibody (5A6). Thus, we propose these CD81-BPs with the anti-migration property against cancer cells for the development of novel therapeutic strategies.
Actions and Consequences of Insulin in the Striatum
Authors: Patel Jyoti C. , Carr Kenneth D. , Rice Margaret E.
Published: March 2023

Insulin crosses the blood–brain barrier to enter the brain from the periphery. In the brain, insulin has well-established actions in the hypothalamus, as well as at the level of mesolimbic dopamine neurons in the midbrain. Notably, insulin also acts in the striatum, which shows abundant expression of insulin receptors (InsRs) throughout. These receptors are found on interneurons and striatal projections neurons, as well as on glial cells and dopamine axons. A striking functional consequence of insulin elevation in the striatum is promoting an increase in stimulated dopamine release. This boosting of dopamine release involves InsRs on cholinergic interneurons, and requires activation of nicotinic acetylcholine receptors on dopamine axons. Opposing this dopamine-enhancing effect, insulin also increases dopamine uptake through the action of insulin at InsRs on dopamine axons. Insulin acts on other striatal cells as well, including striatal projection neurons and astrocytes that also influence dopaminergic transmission and striatal function. Linking these cellular findings to behavior, striatal insulin signaling is required for the development of flavor–nutrient learning, implicating insulin as a reward signal in the brain. In this review, we discuss these and other actions of insulin in the striatum, including how they are influenced by diet and other physiological states.
Copper-Guanosine Nanorods (Cu-Guo NRs) as a Laccase Mimicking Nanozyme for Colorimetric Detection of Rutin
Authors: Davoodi-Rad Kowsar , Shokrollahi Ardeshir , Shahdost-Fard Faezeh , Azadkish Kamal
Published: March 2023

Inspired by laccase activity, herein, Cu-guanosine nanorods (Cu-Guo NRs) have been synthesized for the first time through a simple procedure. The activity of the Cu-Guo NR as the laccase mimicking nanozyme has been examined in the colorimetric sensing of rutin (Rtn) by a novel and simple spectrophotometric method. The distinct changes in the absorbance signal intensity of Rtn and a distinguished red shift under the optimum condition based on pH and ionic strength values confirmed the formation of the oxidized form of Rtn (o-quinone) via laccase-like nanozyme activity of Cu-Guo NRs. A vivid and concentration-dependent color variation from green to dark yellow led to the visual detection of Rtn in a broad concentration range from 770 nM to 54.46 µM with a limit of detection (LOD) of 114 nM. The proposed methodology was successfully applied for the fast tracing of Rtn in the presence of certain common interfering species and various complex samples such as propolis dry extract, human biofluids, and dietary supplement tablets, with satisfactory precision. The sensitivity and selectivity of the developed sensor, which are bonuses in addition to rapid, on-site, cost-effective, and naked-eye determination of Rtn, hold great promise to provide technical support for routine analysis in the real world.
Highly Sensitive Electrochemical Non-Enzymatic Uric Acid Sensor Based on Cobalt Oxide Puffy Balls-like Nanostructure
Authors: Nagal Vandana , Masrat Sakeena , Khan Marya , Alam Shamshad , Ahmad Akil , Alshammari Mohammed B. , Bhat Kiesar Sideeq , Novikov Sergey M. , Mishra Prabhash , Khosla Ajit , Ahmad Rafiq
Published: March 2023

Early-stage uric acid (UA) abnormality detection is crucial for a healthy human. With the evolution of nanoscience, metal oxide nanostructure-based sensors have become a potential candidate for health monitoring due to their low-cost, easy-to-handle, and portability. Herein, we demonstrate the synthesis of puffy balls-like cobalt oxide nanostructure using a hydrothermal method and utilize them to modify the working electrode for non-enzymatic electrochemical sensor fabrication. The non-enzymatic electrochemical sensor was utilized for UA determination using cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The puffy balls-shaped cobalt oxide nanostructure-modified glassy carbon (GC) electrode exhibited excellent electro-catalytic activity during UA detection. Interestingly, when we compared the sensitivity of non-enzymatic electrochemical UA sensors, the DPV technique resulted in high sensitivity (2158 µA/mM.cm2) compared to the CV technique (sensitivity = 307 µA/mM.cm2). The developed non-enzymatic electrochemical UA sensor showed good selectivity, stability, reproducibility, and applicability in the human serum. Moreover, this study indicates that the puffy balls-shaped cobalt oxide nanostructure can be utilized as electrode material for designing (bio)sensors to detect a specific analyte.
The Effects of Social Processing and Role Type on Attention Networks: Insights from Team Ball Athletes
Authors: Passarello Noemi , Mellone Michela , Sorrentino Pierpaolo , Chirico Andrea , Lucidi Fabio , Mandolesi Laura , Federico Francesca
Published: March 2023

(1) Background: Several findings have shown how social stimuli can influence attentional processes. Social attention is crucial in team ball sports, in which players have to react to dynamically changing, unpredictable, and externally paced environments. Our study aimed at demonstrating the influence of social processing on team ball sports athletes’ attentional abilities. (2) Methods: A total of 103 male players divided by sport (soccer, handball, and basketball) and by role (striker, midfielder, or defender) were tested through a modified version of the Attention Network Test (ANT) in which they were exposed to both social and non-social stimuli. (3) Results: Social stimuli positively impacted the athletes’ abilities to focus on target stimuli and ignore conflicting environmental requests (t = −2.600, p = 0.011 *). We also found that the athletes’ roles impacted their performance accuracy. Specifically, differences were found in the ability to maintain a general state of reactivity between athletes (strikers vs. midfielders: t = 3.303, p = 0.004 **; striker vs. defenders: t = −2.820, p = 0.017 *; midfielders vs. defenders: t = −5.876, p < 001 ***). (4) Conclusion: These findings revealed that social stimuli are crucial for performance enhancement in team ball sports athletes. Further, we suggest that it is possible to draw specific attentional profiles for athletes in different roles.
Efficient Pause Extraction and Encode Strategy for Alzheimer’s Disease Detection Using Only Acoustic Features from Spontaneous Speech
Authors: Liu Jiamin , Fu Fan , Li Liang , Yu Junxiao , Zhong Dacheng , Zhu Songsheng , Zhou Yuxuan , Liu Bin , Li Jianqing
Published: March 2023

Clinical studies have shown that speech pauses can reflect the cognitive function differences between Alzheimer’s Disease (AD) and non-AD patients, while the value of pause information in AD detection has not been fully explored. Herein, we propose a speech pause feature extraction and encoding strategy for only acoustic-signal-based AD detection. First, a voice activity detection (VAD) method was constructed to detect pause/non-pause feature and encode it to binary pause sequences that are easier to calculate. Then, an ensemble machine-learning-based approach was proposed for the classification of AD from the participants’ spontaneous speech, based on the VAD Pause feature sequence and common acoustic feature sets (ComParE and eGeMAPS). The proposed pause feature sequence was verified in five machine-learning models. The validation data included two public challenge datasets (ADReSS and ADReSSo, English voice) and a local dataset (10 audio recordings containing five patients and five controls, Chinese voice). Results showed that the VAD Pause feature was more effective than common feature sets (ComParE: 6373 features and eGeMAPS: 88 features) for AD classification, and that the ensemble method improved the accuracy by more than 5% compared to several baseline methods (8% on the ADReSS dataset; 5.9% on the ADReSSo dataset). Moreover, the pause-sequence-based AD detection method could achieve 80% accuracy on the local dataset. Our study further demonstrated the potential of pause information in speech-based AD detection, and also contributed to a more accessible and general pause feature extraction and encoding method for AD detection.
Applied Fence-Post Techniques Using Deep Electrodes Instead of Catheters for Resection of Glioma Complicated with Frequent Epileptic Seizures: A Case Report
Authors: Nakae Shunsuke , Kumon Masanobu , Teranishi Takao , Ohba Shigeo , Hirose Yuichi
Published: March 2023

Fence-post catheter techniques are used to use tumor margins when resecting gliomas. In the present study, deep electrodes instead of catheters were used as fence-posts. The case of a 25-year-old female patient whose magnetic resonance images (MRI) revealed a tumor in the left cingulate gyrus is presented in this study. She underwent daily seizures without loss of consciousness under the administration of anti-seizure medications. Despite video electroencephalography (EEG) monitoring, the scalp inter-ictal EEG did not show obvious epileptiform discharges. We were consequently uncertain whether such frequent seizures were epileptic seizures or not. As a result, deep electrodes were used as fence-posts: three deep electrodes were inserted into the tumor’s anterior, lateral, and posterior margins using a navigation-guided method. The highest epileptic discharge was detected from the anterior deep electrode. As a result, ahead of the tumor was extendedly resected, and epileptic discharges were eliminated using EEG. The postoperative MRI revealed that the tumor was resected. The patient has never experienced seizures after the surgery. In conclusion, when supratentorial gliomas complicated by frequent seizures are resected, intraoperative EEG monitoring using deep electrodes as fence-posts is useful for estimating epileptogenic areas.
Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG–fMRI Investigation
Authors: Liu Yuchao , Zhang Yin , Jiang Zhongyi , Kong Wanzeng , Zou Ling
Published: March 2023

Background: It is crucial to understand the neural feedback mechanisms and the cognitive decision-making of the brain during the processing of rewards. Here, we report the first attempt for a simultaneous electroencephalography (EEG)–functional magnetic resonance imaging (fMRI) study in a gambling task by utilizing tensor decomposition. Methods: First, the single-subject EEG data are represented as a third-order spectrogram tensor to extract frequency features. Next, the EEG and fMRI data are jointly decomposed into a superposition of multiple sources characterized by space-time-frequency profiles using coupled matrix tensor factorization (CMTF). Finally, graph-structured clustering is used to select the most appropriate model according to four quantitative indices. Results: The results clearly show that not only are the regions of interest (ROIs) found in other literature activated, but also the olfactory cortex and fusiform gyrus which are usually ignored. It is found that regions including the orbitofrontal cortex and insula are activated for both winning and losing stimuli. Meanwhile, regions such as the superior orbital frontal gyrus and anterior cingulate cortex are activated upon winning stimuli, whereas the inferior frontal gyrus, cingulate cortex, and medial superior frontal gyrus are activated upon losing stimuli. Conclusion: This work sheds light on the reward-processing progress, provides a deeper understanding of brain function, and opens a new avenue in the investigation of neurovascular coupling via CMTF.
Association between Negative Life Events and Somatic Symptoms: A Mediation Model through Self-Esteem and Depression
Authors: Lv Sijia , Chang Tong , Na Siyu , Lu Lei , Zhao Erying
Published: March 2023

The purpose of this study was to investigate the serial multiple mediation of self-esteem and depression in the relationship between negative life events and somatic symptoms in Chinese medical students. We recruited a total of 3383 medical students for this study, and used the Patient Health Questionnaire-15 to assess the somatic symptoms of subjects; the Adolescent Self-Rating Life Events Check List to assess negative life events; the Rosenberg Self-Esteem Scale to assess self-esteem; and the Patient Health Questionnaire for depression. Descriptive analysis and statistical tests were then performed on the collected data. We showed that 39.17% of the medical students had mild somatic symptoms, 24.14% had moderate somatic symptoms, and 5.66% had severe somatic symptoms; we observed significant differences in somatic symptoms among genders, living expenses, and one-child. For negative life events, interpersonal stress was the most important predictor of somatization during the regression analysis. In addition, we observed significance for both the direct and part of the indirect paths from negative life events to somatic symptoms using mediation model analysis. However, we noted that there was no significance for the path through negative life events and self-esteem to somatic symptoms. This study revealed a high prevalence of somatic symptoms among Chinese medical students, and the findings suggested that interventions aimed at reducing somatization in this population should consider the impact of negative life events, particularly those related to interpersonal stress. One potential approach to mitigating the effects of negative life events on somatization is to enhance self-esteem and decrease the level of depression among medical students.
Exploring the Evolution of Human Resource Analytics: A Bibliometric Study
Authors: Bonilla-Chaves Eithel F. , Palos-Sánchez Pedro R.
Published: March 2023

The objective of this study is to identify and analyze the most relevant scientific work being undertaken in HR analytics. Additionally, it is to understand the evolution of the conceptual, intellectual, and social structure of this topic in a way that allows the expansion of empirical and conceptual knowledge. Bibliometric analysis was performed using Bibliometrix and Biblioshiny software packages on academic articles indexed on the Scopus and Web of Science (WoS) databases. Search criteria were applied, initially resulting in a total of 331 articles in the period 2008–2022. Finally, after applying exclusion criteria, a total of 218 articles of interest were obtained. The results of this research present the relevant notable topics in HR analytics, providing a quantitative analysis that gives an overview of HR analytics featuring tables, graphs, and maps, as well as identifying the main performance indicators for the production of articles and their citations. The scientific literature on HR analytics is a novel, adaptive area that provides the option to transform traditional HR practices. Through the use of technology, HR analytics can improve HR strategies and organisational performance, as well as people’s experiences.
Fluid Flow Characteristics for Four Lattice Settings in Brick Tunnel Kiln: CFD Simulations
Authors: Refaey Hassanein A. , Alharthi Mathkar A. , Abdel-Aziz Ali A. , Elattar Hassan F. , Almohammadi Bandar Awadh , Abdelrahman Hany E. , Karali Mohamed A. , Attia El-Awady , Al-Dosoky Mamdouh W.
Published: March 2023

The higher the process efficiency, the lower the fuel consumption, and the less impact carbon emissions have on the environment. The flow characteristics around brick settings are an important field of investigation to acquire control over the energy intake and production process. The current work is a numerical CFD investigation to demonstrate fluid flow characterization inside the cooling zone in a brick tunnel kiln for lattice settings (the number of bricks in each layer is identical). Four different lattice settings were examined, and three were validated with published experimental data (settings 1, 2 and 3). In the current study, the BSL κ-ω turbulent model agrees well with the published experimental results. The numerical investigation presents the flow characteristics through four different lattice brick settings (e.g., velocity vectors, velocity contours and streamlines) that could not be measured experimentally. The investigation also looks at the flow zones of the vortex formation upstream, downstream and through the brick column. It was discovered that for settings 1 and 11, the quick air flow in the wall channels is much greater than in the column channels. Setting 3 has a larger vortex formation region, whereas setting 1 has a weaker vortex than the other settings. The cooling of the lattice bricks in Setting 3 is superior to the cooling in the other settings.