bluuebunny/crossref_metadata_2025 huggingface dataset:
The Catechins Profile of Green Tea Extracts Affects the Antioxidant Activity and Degradation of Catechins in DHA-Rich Oil
Authors: Nain Caroline Waingeh , Mignolet Eric , Herent Marie-France , Quetin-Leclercq Joëlle , Debier Cathy , Page Melissa M. , Larondelle Yvan
Published: September 2022

This study investigated the effect of the catechins profile on the antioxidant activity of green tea extracts (GTEs) by comparing the antioxidant activity of an EGC-rich GTE (GTE1, catechin content: 58% EGC, 30.1% EGCG, 7.9% EC, and 3.9% ECG) and an EGCG-rich GTE (GTE2, catechin content: 60.6% EGCG, 17.7% EGC, 11.8% ECG, and 9.8% EC) in a DHA-rich oil. The effects of the individual catechins (EGC, EC, EGCG, and ECG) and reconstituted catechins mixtures (CatMix), prepared to contain the same amount of major catechins as in the GTEs, were also measured. All treatments (GTE1, CatMix1, GTE2, CatMix2, EGC250, EC250, EGCG250, and ECG250), each containing epistructured catechins at a concentration of 250 ppm, as well as the control (oil with no added antioxidant), were stored at 30 °C for 21 days with sampling intervals of 7 days. The antioxidant activity was assessed by measuring the peroxide value (PV) and p-anisidine value (p-AV) of oils. Changes in fatty acid content and catechins content were also monitored. Both GTEs enhanced the oxidative stability of the DHA-rich oil, but GTE1 demonstrated a stronger antioxidant activity than GTE2. No significant difference was observed between the PV of treatments with GTE1 and CatMix1 during storage, whereas the PV of oil with GTE2 was significantly higher than that with CatMix2 after 21 days. Among the individual catechins, EGC was the strongest antioxidant. Overall, the antioxidant activities of the extracts and catechins were observed in the decreasing order GTE1 ≈ EGC250 ≈ CatMix1 > GTE2 > EGCG250 ≈ CatMix2 > ECG250 > EC250. A significant change in fatty acid content was observed for the control and EC250 samples, and the catechins were most stable in GTE1-supplemented oil. Our results indicate that the EGC-rich GTE is a more potent antioxidant in DHA-rich oil than the EGCG-rich GTE.
Long-Tail Instance Segmentation Based on Memory Bank and Confidence Calibration
Authors: Fan Xinyue , Liu Teng , Bao Hong , Pan Weiguo , Liang Tianjiao , Li Han
Published: September 2022

In the field of computer vision, training a well-performing model on a dataset with a long-tail distribution is a challenging task. To address this challenge, image resampling is usually introduced as a simple and effective solution. However, when performing instance segmentation tasks, there may be multiple classes in one image. Hence, image resampling alone is not enough to obtain a sufficiently balanced distribution at the level of target data volume. In this paper, we propose an improved instance segmentation method for long-tail datasets based on Mask R-CNN. Specifically, an object-centric memory bank is used to establish an object-centric storage strategy that can solve the imbalance problem with respect to categories. In the testing phase, a post-processing calibration is used to adjust each class logit to change the confidence score, which improves the prediction score of tail classes. A discrete cosine transform-based mask is used to obtain high-quality masks, which improves segmentation accuracy. The evaluation of the proposed method on the LVIS dataset demonstrates its effectiveness. The proposed method improves the AP performance of EQL by 2.2%.
Target-Oriented Teaching Path Planning with Deep Reinforcement Learning for Cloud Computing-Assisted Instructions
Authors: Yang Tengjie , Zuo Lin , Yang Xinduoji , Liu Nianbo
Published: September 2022

In recent years, individual learning path planning has become prevalent in online learning systems, while few studies have focused on teaching path planning for traditional classroom teaching. This paper proposes a target-oriented teaching path optimization scheme for cloud computing-assisted instructions, in which a sequence of learning contents is arranged to ensure the maximum benefit for a given group of students. First, to evaluate the teaching performance, we investigate various student models and define some teaching objectives, including the pass rate, the excellence rate, the average score, and related constraints. Second, a new Deep Reinforcement Learning (DRL)-based teaching path planning method is proposed to tackle the learning path by maximizing a multi-objective target while satisfying all teaching constraints. It adopts a Proximal Policy Optimization (PPO) framework to find a model-free solution for achieving fast convergence and better optimality. Finally, extensive simulations with a variety of commonly used teaching methods show that our scheme provides nice performance and versatility over commonly used student models.
Applications of Metaheuristics Inspired by Nature in a Specific Optimisation Problem of a Postal Distribution Sector
Authors: Berliński Michał , Warchulski Eryk , Kozdrowski Stanisław
Published: September 2022

This paper presents a logistics problem, related to the transport of goods, which can be applied in practice, for example, in postal or courier services. Two mathematical models are presented as problems occurring in a logistics network. The main objective of the optimisation problem presented is to minimise capital resources (Capex), such as cars or containers. Three methods are proposed to solve this problem. The first is a method based on mixed integer programming (MIP) and available through the CPLEX solver. This method is the reference method for us because, as an exact method, it is guaranteed to find the optimal solution as long as the problem is not too large. However, the logistic problem under consideration belongs to the class of NP-complete problems and therefore, for larger problems, i.e., for networks of large size, the MIP method does not find any integer solution in a reasonable computational time. Therefore, two nature-inspired heuristic methods have been proposed. The first is the evolutionary algorithm and the second is the artificial bee colony algorithm. Results indicate that the heuristics methods solve instances of large size, giving suboptimal solutions and therefore, enabling their application to real-life scenarios.
Space Node Topology Optimization Design Considering Anisotropy of Additive Manufacturing
Authors: Wang Xianjie , Zhang Fan , Weng Zhenjiang , Jiang Xinyu , Wang Rushuang , Ren Hao , Zheng Feiyun
Published: September 2022

At present, a large number of scholars have conducted related research on topology optimization for additive manufacturing (AM). However, there are few relevant research reports on the impact of different directions of additive manufacturing on the optimal design and manufacturing results. In this paper, using the bidirectional evolutionary optimization (BESO) method, anisotropic optimization analysis was carried out on space nodes that are currently popular in the field of additive manufacturing and topology optimization. The elastic constants in different directions were used as anisotropic material properties for optimization research in this paper through tensile testing, which was carried out on 316L stainless-steel specimens fabricated using Selective Laser Melting (SLM) technology. In addition, SEM analyses were performed to explore the microscopic appearance of the material. The study found that additive manufacturing is affected by the printing direction in terms of both macroscopic mechanical properties and microscopic material structure; the deformation obtained by anisotropic optimization was about 1.1–2.3% smaller than that obtained by isotropic optimization.
Internet of Things Meets Computer Vision to Make an Intelligent Pest Monitoring Network
Authors: Cardoso Bruno , Silva Catarina , Costa Joana , Ribeiro Bernardete
Published: September 2022

With the increase of smart farming in the agricultural sector, farmers have better control over the entire production cycle, notably in terms of pest monitoring. In fact, pest monitoring has gained significant importance, since the excessive use of pesticides can lead to great damage to crops, substantial environmental impact, and unnecessary costs both in material and manpower. Despite the potential of new technologies, pest monitoring is still done in a traditional way, leading to excessive costs, lack of precision, and excessive use of human labour. In this paper, we present an Internet of Things (IoT) network combined with intelligent Computer Vision (CV) techniques to improve pest monitoring. First, we propose to use low-cost cameras at the edge that capture images of pest traps and send them to the cloud. Second, we use deep neural models, notably R-CNN and YOLO models, to detect the Whitefly (WF) pest in yellow sticky traps. Finally, the predicted number of WF is analysed over time and results are accessible to farmers through a mobile app that allows them to visualise the pest in each specific field. The contribution is to make pest monitoring autonomous, cheaper, data-driven, and precise. Results demonstrate that, by combining IoT, CV technology, and deep models, it is possible to enhance pest monitoring.
Characteristics of Propagation of Meteorological to Hydrological Drought for Lake Baiyangdian in a Changing Environment
Authors: He Shan , Zhang Enze , Huo Junjun , Yang Mingzhi
Published: September 2022

The analysis of drought propagation has garnered mounting attention in the changing global environment. The current studies tend to focus on the propagation characteristics from meteorological to hydrological drought in rivers. Lakes, despite being a key component of watershed ecosystems, have received little attention to their response to meteorological and hydrological droughts. To this end, here, we investigated the characteristics of propagation from meteorological to hydrological drought for a lake in a changing environment. To determine the drought propagation time from meteorological to hydrological drought, we analyzed correlations between the standardized precipitation index (SPI), standardized runoff index (SRI), and standardized water level index (SWI). Lake Baiyangdian in China served as the case study. The results showed that meteorological droughts occur at high frequency but are short in duration, indicating that not every meteorological drought will necessarily lead to a hydrological drought. By contrast, lake hydrological droughts have low frequency and long duration and feature more severe consequences. Comparing drought characteristics before and after a changing environment, we found a reduced frequency of the SPI, SRI, and SWI, yet their duration was prolonged. For the SWI especially, these results were even more pronounced, which suggests the changing environment enabled further intensification of the lake hydrological drought. In addition, more time was needed for a meteorological drought to transition into a lake hydrological drought after a changing environment.
Regional Predictions of Air Pollution in Guangzhou: Preliminary Results and Multi-Model Cross-Validations
Authors: Qiao Zhi , Cui Shengcheng , Pei Chenglei , Ye Zhou , Wu Xiaoqing , Lei Lei , Luo Tao , Zhang Zihan , Li Xuebin , Zhu Wenyue
Published: September 2022

A precise air pollution forecast is the basis for targeted pollution control and sustained improvements in air quality. It is desirable and crucial to select the most suitable model for air pollution forecasting (APF). To achieve this goal, this paper provides a comprehensive evaluation of performances of different models in simulating the most common air pollutants (e.g., PM2.5, NO2, SO2, and CO) in Guangzhou (23.13° N, 113.26° E), China. To simulate temporal variations of the above-mentioned air pollutant concentrations in Guangzhou in September and October 2020, we use a numerical forecasting model (i.e., the Weather Research and Forecasting model with Chemistry (WRF-Chem)) and two artificial intelligence models (i.e., the back propagation neural network (BPNN) model and the long short-term memory (LSTM) model). WRF-Chem is also used to simulate the meteorological elements (e.g., the 2 m temperature (T2), 2 m relative humidity (RH), and 10 m wind speed and direction (WS, WD)). In order to investigate the simulation accuracies of classical APF models, we simultaneously compare the simulations of the WRF-Chem, BPNN, and LSTM models to ground truth observations. Comparative assessment results show that WRF-Chem simulated air pollutant (i.e., PM2.5, NO2, SO2, and CO) concentrations have the best correlations with ground measurements (i.e., Pearson correlation coefficient R = 0.88, 0.73, 0.61, and 0.61, respectively). Furthermore, to evaluate model performance in terms of accuracy and stability, the normalized mean bias (NMB, %) and mean fractional bias (MFB, %) are adopted as the standard performance metrics (SPMs) proposed by Boylan et al. The comparison results indicate that when simulating PM2.5, WRF-Chem was more effective than the BPNN but less effective than the LSTM. While simulating concentrations of NO2, SO2, and CO, the WRF-Chem model performed better than the BPNN and LSTM models. With regards to WRF-Chem, the NMBs and MFBs for the PM2.5 simulations are, respectively, 6.49% and 0.02%, –11.96% and –0.031% for NO2, 7.93% and 0.019% for CO, and 5.04% and 0.012% for SO2. Our results suggest that WRF-Chem has superior performance and better accuracy than the NN-based prediction models, making it a promising and useful tool to accurately predict and forecast regional air pollutant concentrations on a city scale.
Modeling and Control of Satellite Formations: A Survey
Authors: Andrievsky Boris , Popov Alexander M. , Kostin Ilya , Fadeeva Julia
Published: September 2022

This survey deals with the problem of the group motion of spacecraft, which is rapidly developing and relevant for many applications, in terms of developing the onboard control algorithms to ensure the fulfillment of a given mission. The paper provides a comprehensive overview of spacecraft formation flight control. The bibliography is divided into three main sections: the multiple-input–multiple-output approach, in which the formation is treated as a single entity with multiple inputs and multiple outputs; the leader–follower formation, in which individual spacecraft controllers are linked hierarchically; and a virtual structure formation, in which spacecraft are treated as rigid bodies embedded in a common virtual rigid body. This survey expands a 2004 survey and updates it with recent results.
Object-Based Dynamics: Applying Forman–Ricci Flow on a Multigraph to Assess the Impact of an Object on The Network Structure
Authors: Cohen Haim , Nachshon Yinon , Maril Anat , Naim Paz M. , Jost Jürgen , Saucan Emil
Published: September 2022

Temporal information plays a central role in shaping the structure of a network. In this paper, we consider the impact of an object on network structure over time. More specifically, we use a novel object-based dynamic measure to reflect the extent to which an object that is represented in the network by a vertex affects the topology of the network over time. By way of multigraph and Forman–Ricci flow, we assess the object’s impact on graph weights by comparing two graphs, one in which the object is present and one in which the object is absent. After using a case study to demonstrate the impact of Forman–Ricci flow on the network structure, we apply our measure in a semantic network to assess the effects of a word on the interactions between other words that follow it. In addition, we compare our novel measure to centrality and curvature measures so that we can ascertain the advantages of our measure over ones that already exist.
Chemical Methods for Microbiological Control of Winemaking: An Overview of Current and Future Applications
Authors: Tedesco Francesco , Siesto Gabriella , Pietrafesa Rocchina , Romano Patrizia , Salvia Rosanna , Scieuzo Carmen , Falabella Patrizia , Capece Angela
Published: September 2022

Preservation technologies for winemaking have relied mainly on the addition of sulfur dioxide (SO2), in consequence of the large spectrum of action of this compound, linked to the control of undesirable microorganisms and the prevention of oxidative phenomena. However, its potential negative effects on consumer health have addressed the interest of the international research on alternative treatments to substitute or minimize the SO2 content in grape must and wine. This review is aimed at analyzing chemical methods, both traditional and innovative, useful for the microbiological stabilization of wine. After a preliminary description of the antimicrobial and technological properties of SO2, the additive traditionally used during wine production, the effects of the addition (in must and wine) of other compounds officially permitted in winemaking, such as sorbic acid, dimethyl dicarbonate (DMDC), lysozyme and chitosan, are discussed and evaluated. Furthermore, other substances showing antimicrobial properties, for which the use for wine microbiological stabilization is not yet permitted in EU, are investigated. Even if these treatments exhibit a good efficacy, a single compound able to completely replace SO2 is not currently available, but a combination of different procedures might be useful to reduce the sulfite content in wine. Among the strategies proposed, particular interest is directed towards the use of insect-based chitosan as a reliable alternative to SO2, mainly due to its low environmental impact. The production of wines containing low sulfite levels by using pro-environmental practices can meet both the consumers’ expectations, who are even more interested in the healthy traits of foods, and wine-producers’ needs, who are interested in the use of sustainable practices to promote the profile of their brand.
Smart ECG Biosensor Design with an Improved ANN Performance Based on the Taguchi Optimizer
Authors: Sidhom Lilia , Chihi Ines , Barhoumi Mahfoudh , Ben Afia Nesrine , Kamavuako Ernest Nlandu , Trabelsi Mohamed
Published: September 2022

This paper aims to design a smart biosensor to predict electrocardiogram (ECG) signals in a specific auscultation site from other ECG signals measured from other measurement sites. The proposed design is based on a hybrid architecture using the Artificial Neural Networks (ANNs) model and Taguchi optimizer to avoid the ANN issues related to hyperparameters and to improve its accuracy. The proposed approach aims to optimize the number and type of inputs to be considered for the ANN model. Indeed, different combinations are considered in order to find the optimal input combination for the best prediction quality. By identifying the factors that influence a model’s prediction and their degree of importance via the modified Taguchi optimizer, the developed biosensor improves the prediction accuracy of ECG signals collected from different auscultation sites compared to the ANN-based biosensor. Based on an actual database, the simulation results show that this improvement is significant; it can reach more than 94% accuracy.
Crop Improvement: Where Are We Now?
Authors: Sourdille Pierre , Devaux Pierre
Published: September 2022

Improving the production of all crops is crucial to meeting the challenge of the growing needs related to the simultaneous increase in the world population and demands from farmers and end-users [...]
Dexamethasone-Induced Adipose Tissue Redistribution and Metabolic Changes: Is Gene Expression the Main Factor? An Animal Model of Chronic Hypercortisolism
Authors: de Fatima Silva Flaviane , Komino Ayumi Cristina Medeiros , Andreotti Sandra , Boltes Reis Gabriela , Caminhotto Rennan Oliveira , Landgraf Richardt Gama , de Souza Gabriel Orefice , Sertié Rogerio Antonio Laurato , Collins Sheila , Donato Jose , Bessa Lima Fabio
Published: September 2022

Chronic hypercortisolism has been associated with the development of several metabolic alterations, mostly caused by the effects of chronic glucocorticoid (GC) exposure over gene expression. The metabolic changes can be partially explained by the GC actions on different adipose tissues (ATs), leading to central obesity. In this regard, we aimed to characterize an experimental model of iatrogenic hypercortisolism in rats with significant AT redistribution. Male Wistar rats were distributed into control (CT) and GC-treated, which received dexamethasone sodium phosphate (0.5 mg/kg/day) by an osmotic minipump, for 4 weeks. GC-treated rats reproduced several characteristics observed in human hypercortisolism/Cushing’s syndrome, such as HPA axis inhibition, glucose intolerance, insulin resistance, dyslipidemia, hepatic lipid accumulation, and AT redistribution. There was an increase in the mesenteric (meWAT), perirenal (prWAT), and interscapular brown (BAT) ATs mass, but a reduction of the retroperitoneal (rpWAT) mass compared to CT rats. Overexpressed lipolytic and lipogenic gene profiles were observed in white adipose tissue (WAT) of GC rats as BAT dysfunction and whitening. The AT remodeling in response to GC excess showed more importance than the increase of AT mass per se, and it cannot be explained just by GC regulation of gene transcription.
Investigational Treatments in Phase I and II Clinical Trials: A Systematic Review in Asthma
Authors: Calzetta Luigino , Aiello Marina , Frizzelli Annalisa , Pistocchini Elena , Ritondo Beatrice Ludovica , Rogliani Paola , Chetta Alfredo
Published: September 2022

Inhaled corticosteroids (ICS) remain the mainstay of asthma treatment, along with bronchodilators serving as control agents in combination with ICS or reliever therapy. Although current pharmacological treatments improve symptom control, health status, and the frequency and severity of exacerbations, they do not really change the natural course of asthma, including disease remission. Considering the highly heterogeneous nature of asthma, there is a strong need for innovative medications that selectively target components of the inflammatory cascade. The aim of this review was to systematically assess current investigational agents in Phase I and II randomised controlled trials (RCTs) over the last five years. Sixteen classes of novel therapeutic options were identified from 19 RCTs. Drugs belonging to different classes, such as the anti-interleukin (IL)-4Rα inhibitors, anti-IL-5 monoclonal antibodies (mAbs), anti-IL-17A mAbs, anti-thymic stromal lymphopoietin (TSLP) mAbs, epithelial sodium channel (ENaC) inhibitors, bifunctional M3 receptor muscarinic antagonists/β2-adrenoceptor agonists (MABAs), and anti-Fel d 1 mAbs, were found to be effective in the treatment of asthma, with lung function being the main assessed outcome across the RCTs. Several novel investigational molecules, particularly biologics, seem promising as future disease-modifying agents; nevertheless, further larger studies are required to confirm positive results from Phase I and II RCTs.
Determining Whether Sex and Zygosity Modulates the Association between APOE4 and Psychosis in a Neuropathologically-Confirmed Alzheimer’s Disease Cohort
Authors: Valcic Mila , Khoury Marc A. , Kim Julia , Fornazzari Luis , Churchill Nathan W. , Ismail Zahinoor , De Luca Vincenzo , Tsuang Debby , Schweizer Tom A. , Munoz David G. , Fischer Corinne E.
Published: September 2022

Background: The APOE4 allele is a genetic risk factor for developing late-onset Alzheimer’s disease (AD). Previous work by our group revealed that female APOE4 homozygotes with Lewy body (LB) pathology were more likely to experience psychosis compared to female APOE4 non-carriers, whereas in males there was no APOE4 dose-dependent significant effect. The objective of this study was to refine our previous findings by adjusting for covariates and determining the probability of an APOE4 sex-mediated effect on psychosis. Methods: Neuropathologically confirmed AD patients with LB pathology (n = 491) and without LB pathology (n = 716) were extracted from the National Alzheimer’s Coordinating Center (NACC). Patients were classified as psychotic if they scored positively for delusions and/or hallucinations on the Neuropsychiatric Inventory. Analysis consisted of a preliminary unadjusted binary logistic regression and a Generalized Additive binary logistic regression Model (GAM) to predict the relationship between APOE4 status and sex on the presence of psychosis in both cohorts, adjusting for age, education and MMSE. Results: In the cohort with LB pathology, female APOE4 homozygotes were significantly more likely to experience psychosis compared to female APOE4 non-carriers (OR = 4.15, 95%CI [1.21, 14.2], p = 0.023). Female heterozygotes were also more likely to experience psychosis compared to female APOE4 non-carriers, but to a lesser extent (OR = 2.37, 95%CI [1.01, 5.59], p = 0.048). There was no significant difference in males with LB pathology or in any sex in the cohort without LB pathology. Conclusions: Sex and zygosity influence the effect of APOE4 on psychosis in neuropathologically confirmed AD patients, with the effect being limited to females with LB pathology.
A Study of Common Principles for Decision-Making in Moral Dilemmas for Autonomous Vehicles
Authors: Li Li , Zhang Junyou , Wang Shufeng , Zhou Qian
Published: September 2022

How decisions are made when autonomous vehicles (AVs) are faced with moral dilemmas is still a challenge. For this problem, this paper proposed the concept of common principles, which were drawn from the general public choice and could be generally accepted by society. This study established five moral dilemma scenarios with variables including the number of sacrifices, passenger status, presence of children, decision-making power subjects, and laws. Based on existing questionnaire data, we used gray correlation analysis to analyze the influence of the individual and psychological factors of participants in decision-making. Then, an independent sample t-test and analysis of covariance were selected to analyze the influence relationship between individual and psychological factors. Finally, by induction statistics of decision choices and related parameters of participants, we obtain common principles of autonomous vehicles, including the principle of protecting law-abiding people, the principle of protecting the majority, and the principle of protecting children. The principles have different priorities in different scenarios and can meet the complex changes in moral dilemmas. This study can alleviate the contradiction between utilitarianism and deontology, the conflict between public needs and individualized needs, and it can provide a code of conduct for ethical decision-making in future autonomous vehicles.
Self-Report versus Neuropsychological Tests for Examining Executive Functions in Youth Soccer Athletes—A Cross-Sectional Study
Authors: Heilmann Florian
Published: September 2022

Cognitive diagnostics, especially the measurement of executive functions (EFs) in the context of sports and talent diagnostics, is a popular research topic. However, research is lacking on how self-reports are sufficient to examine the EFs of youth athletes for performance diagnostics. Thus, the current study aims to evaluate the relationships between neuropsychological tasks (3-back task, cued Go/NoGo task, flanker task, and number-letter task) and a self-report for examining EFs (BRIEF-SB). Furthermore, it should be investigated whether it is possible to predict the outcome of EF tasks using a self-report inventory. Therefore, 68 young professional soccer players (Mage = 14.26 ± 1.35 years) from a national youth academy were included in the study. The weak-to-moderate correlations (r = 0.000, p = 0.999 to r = −0.442, p < 0.01) and the results of sensitivity analysis (0.125 to 0.538) do not support using a self-report of EFs for cognitive performance diagnostics. The inventory is only suitable for identifying executive dysfunctions in athletes recovering from head injuries or concussions.
A Comparative Study of the Simulation Accuracy and Efficiency for the Urban Wind Environment Based on CFD Plug-Ins Integrated into Architectural Design Platforms
Authors: Hu Yongyu , Xu Fusuo , Gao Zhi
Published: September 2022

The deterioration of the urban environment is a problem which has captured the attention of governmental departments and researchers, who are committed to improving the urban environment from the perspective of optimizing urban morphology. Although many researchers have applied computational fluid dynamics (CFD) plug-ins to study the problems of urban ventilation and pollutant accumulation, studies on the reliability and simulation accuracy verification of CFD plug-ins are currently scarce. Therefore, we used three CFD plug-ins based on different architectural design platforms to evaluate and compare their operation difficulty, simulation accuracy, and efficiency through the analysis of the simulation results of urban ventilation. This study complements the reliability validation of CFD plug-in simulations and guides urban planners and architects in the selection and application of CFD plug-ins. The results show that the CFD plug-in generally underestimates the wind speed at the pedestrian level and the prediction accuracy is poor in the wake area of obstacles, especially with the GH_Wind plug-in. Under the 0° inflow direction, the simulation results of the Butterfly plug-in were the most consistent with the experimental values. When the inflow direction increased to 22.5° and 45°, the Autodesk CFD showed the best simulation accuracy. Overall, Autodesk CFD achieves a balance between simulation accuracy and speed in urban airflow simulation.
Design of γ-Alumina-Supported Phosphotungstic Acid-Palladium Bifunctional Catalyst for Catalytic Liquid-Phase Citral Hydrogenation
Authors: Shah Abdul Karim , Bukhari Syed Nizam-uddin Shah , Shah Ayaz Ali , Jatoi Abdul Sattar , Usto Muhammad Azam , Hashmi Zubair , Shah Ghulam Taswar , Park Yeung Ho , Choi Moo-Seok , Iqbal Arshad , Seehar Tahir Hussain , Raza Aamir
Published: September 2022

This study primarily addresses the development of dynamic, selective and economical metal–acid (bifunctional) catalysts for one-pot menthol production by citral hydrogenation. Specifically, various metals such as Pd, Pt, Ni, Cs and Sn were doped over alumina support. Additionally, bifunctional composite catalysts were also prepared with the impregnation of heteropoly acids and Pd precursors over alumina support. Analytical techniques (e.g., BET, PXRD, FT-IR, pyridine adsorption and amine titration methods) were applied for characterization of the most efficient and selective catalysts (e.g., Al2O3 and PTA-Cat-I). Similarly, most of the essential operational variables (e.g., loading rate of metal precursor, type of heteropoly acid, temperature, gas pressure and reaction time) were examined during this study. The experimental data shows that the bifunctional catalyst (PTA-Cat-I) produced 45% menthol at full citral substrate conversion (r = 0.038 mmoles.min−1) in liquid-phase citral hydrogenation (at optimized operating conditions: 70 °C, 0.5 MPa and 8 h). However, the heteropoly acid-supported bifunctional catalysts (e.g., PTA-Cat-I, PMA-Cat-I, SMA-Cat-I and STA-Cat-I) resulted in cracking and the dehydration of isopulegol/menthol by the generation of side products (e.g., 4-isopropyl-1-methyl, cyclohex-1-ane/ene); therefore, menthol yield was extensively diminished. On the other hand, non-acidic catalysts (e.g., Cat-I, Cat-II, Cat-III, Cat-IV and Cat-V) readily promoted hydrogenation reactions. The optimum menthol yield occurred due to the presence of strong Lewis and weak Bronsted acid sites. Mass transfer and reaction rate were substantially diminished due to acidity strength, heteropoly acid type and blockage of pores by the applied bifunctional catalysts.
Sirtuin 1 in Host Defense during Infection
Authors: Kim Jin Kyung , Silwal Prashanta , Jo Eun-Kyeong
Published: September 2022

Sirtuins (SIRTs) are members of the class III histone deacetylase family and epigenetically control multiple target genes to modulate diverse biological responses in cells. Among the SIRTs, SIRT1 is the most well-studied, with a role in the modulation of immune and inflammatory responses following infection. The functions of SIRT1 include orchestrating immune, inflammatory, metabolic, and autophagic responses, all of which are required in establishing and controlling host defenses during infection. In this review, we summarize recent information on the roles of SIRT1 and its regulatory mechanisms during bacterial, viral, and parasitic infections. We also discuss several SIRT1 modulators, as potential antimicrobial treatments. Understanding the function of SIRT1 in balancing immune homeostasis will contribute to the development of new therapeutics for the treatment of infection and inflammatory disease.
Macrophage-Secreted CSF1 Transmits a Calorie Restriction-Induced Self-Renewal Signal to Mammary Epithelial Stem Cells
Authors: Kosenko Anna , Salame Tomer Meir , Friedlander Gilgi , Barash Itamar
Published: September 2022

Calorie restriction enhances stem cell self-renewal in various tissues, including the mammary gland. We hypothesized that similar to their intestinal counterparts, mammary epithelial stem cells are insulated from sensing changes in energy supply, depending instead on niche signaling. The latter was investigated by subjecting cultures of mammary epithelial stem cells for 8 days to in vivo paracrine calorie-restriction signals collected from a 4-day-conditioned medium of individual mammary cell populations. Conditioned medium from calorie-restricted non-epithelial cells induced latent cell propagation and mammosphere formation—established markers of stem cell self-renewal. Combined RNA-Seq, immunohistochemistry and immunofluorescence analyses of the non-epithelial population identified macrophages and secreted CSF1 as the energy sensor and paracrine signal, respectively. Calorie restriction-induced pStat6 expression in macrophages suggested that skewing to the M2 phenotype contributes to the sensing mechanism. Enhancing CSF1 signaling with recombinant protein and interrupting the interaction with its highly expressed receptor in the epithelial stem cells by neutralizing antibodies were both affected stem cell self-renewal. In conclusion, combined in vivo, in vitro and in silico studies identified macrophages and secreted CSF1 as the energy sensor and paracrine transmitter, respectively, of the calorie restriction-induced effect on mammary stem cell self-renewal.
Psychoeducation Reduces Alexithymia and Modulates Anger Expression in a School Setting
Authors: Iuso Salvatore , Severo Melania , Ventriglio Antonio , Bellomo Antonello , Limone Pierpaolo , Petito Annamaria
Published: September 2022

Bullying and violence are relevant issues in school settings and negatively impact students’ well-being and mental health. Psychoeducation and anti-bullying programs may prevent violence among students by addressing emotional expression and regulation, alexithymia, and anger. We describe the impact of a psychoeducational intervention delivered to 90 male and 101 female school youths (N = 191), aged 12–14 years old, and aimed to improve their emotional recognition and regulation, as well as to reduce alexithymia in order to prevent aggression and bullying episodes. A psychological assessment has been performed before (T0) and after (T1) the intervention including levels of alexithymia, measured with the Toronto Alexithymia Scale-20 (TAS-20), the State-Trait Anger Expression Inventory (STAXI), Empathy Quotient (EQ), and the Emotion Regulation Questionnaire (ERQ). Females have shown higher levels of alexithymia at baseline whereas other characteristics (anger, empathy quotient and emotional regulation) did not differ among sex groups. The psychoeducational program significantly increased the empathy quotient (+10.2%), the emotional regulation reappraisal (+20.3%), and the assertive anger expression (+10.9%); alexithymia significantly decreased after the intervention in all the samples (−14.4%), above all among students scoring ≥61 at TAS-20 (−48.2%). Limitations include a small sample from a single school setting, the lack of a control group without psychoeducation, and an assessment based on self-reported measures. We may conclude that psychoeducation has significantly reduced levels of alexithymia and improved empathy and emotional regulation among adolescents.
The CSHQ-DE Questionnaire Uncovers Relevant Sleep Disorders in Children and Adolescents with Long COVID
Authors: Werner Sarah , Doerfel Claus , Biedermann Richard , Lorenz Michael , Rasche Marius , Proquitté Hans , Newman Lars , Vilser Daniel
Published: September 2022

Acute SARS-CoV-2 infections in children and adolescents are usually mild. However, they can suffer from ongoing symptoms, generally referred to as long COVID. Sleep disorders are one of the most frequent complaints in long COVID although precise data are missing. We assessed the sleep behavior of children and adolescents who presented at our outpatient clinic between January 2021 and May 2022 with the Children’s Sleep Habits Questionnaire (CSHQ-DE). We compared the sleep behavior at three different time points: pre-COVID-19; post-COVID-19 at the initial presentation; and post-COVID-19 at re-presentation. Data from 45 patients were analyzed. Of those, 64% were female and the median age was 10 years (range: 0–18 years). Asymptomatic or mild COVID-19 disease was experienced in 89% of patients; 11% experienced moderate disease. The initial presentation occurred at a median of 20.4 weeks (6 weeks–14 months) after the infection. The CSHQ-DE score increased significantly from pre-COVID-19 (45.82 ± 8.7 points) to post-COVID-19 (49.40 ± 8.3 points; p ≤ 0.01). The score then normalized at re-presentation (46.98 ± 7.8; p = 0.1). The greatest changes were seen in the CSHQ-DE subscale score “daytime sleepiness”. Our data showed that children and adolescents with long COVID often suffer from sleep disturbances. For most children and adolescents, these sleep disorders decreased over time without any further medical intervention aside from a basic sleep consultation.
Increased Electromagnetic Wave Absorption through Controlled Sonication Processing on BaFe11.2Mg0.4Al0.4O19 Nanoparticles
Authors: Yustanti Erlina , Noviyanto Alfian , Chotimah Laila Chusnul , Saputra Muhamad Abdur Rais , Randa Maulana , Manawan Maykel
Published: September 2022

Electromagnetic waves show rapid development in electronics, telecommunications, and the military. One of the efforts to overcome the effects of electromagnetic interference is by developing microwave-absorbing materials. Barium hexaferrite is the best candidate for development as an absorber material. Microwave absorption in barium hexaferrite can be increased through Mg-Al doping and reducing the particle size. This study aimed to analyze sonication parameters to reduce the particle size by combining destruction methods using mechanical alloying followed by high-power ultrasonic irradiation. Barium hexaferrite was synthesized through mechanical alloying by mixing stoichiometric BaCO3, Fe2O3, Al2O3, and MgO (Sigma-Aldrich p.a 99%) (Mg-Al 0.4%wt). The samples continued the sintering process at 1200 °C for 2 h to grow crystal embryos. The optimal parameters for ultrasonic destruction were using a transducer:reactor diameter ratio of 1:10, a particle density of 5 g/250 mL, and adding a non-ionic surfactant of 0.01% at an amplitude of 55% and a sonication time of 8 h. These methods resulted in the saturation magnetization of 18.50 emu/g and a coercivity of 0.08 Tesla. The reduction in the particle size of BHF doped with Mg-Al was successfully up to 21 nm, resulting in a reflection loss of up to −40.8697 dB at 11.896 GHz (x-band, 8–12 GHz). The BHF nanoparticles doped with Mg-Al effectively absorbed up to 99.99% electromagnetic waves.
Utilizing TPGS for Optimizing Quercetin Nanoemulsion for Colon Cancer Cells Inhibition
Authors: Enin Hadel A. Abo , Alquthami Ahad Fahd , Alwagdani Ahad Mohammed , Yousef Lujain Mahmoud , Albuqami Majd Safar , Alharthi Miad Abdulaziz , Alsaab Hashem O.
Published: September 2022

Background: Colorectal cancer is one of the most challenging cancers to treat. Exploring novel therapeutic strategies is necessary to overcome drug resistance and improve patient outcomes. Quercetin (QR) is a polyphenolic lipophilic compound that was chosen due to its colorectal anticancer activity. Nanoparticles could improve cancer therapy via tumor targeting by utilizing D-tocopheryl polyethylene glycol succinate (vitamin-E TPGS) as a surfactant in a nanoemulsion preparation, which is considered an efficient drug delivery system for enhancing lipophilic antineoplastic agents. Thus, this study aims to develop and optimize QR-loaded nanoemulsions (NE) using TPGS as a surfactant to enhance the QR antitumor activity. Method: The NE was prepared using a self-assembly technique using the chosen oils according to QR maximum solubility and TPGS as a surfactant. The prepared QR-NE was evaluated according to its particle morphology and pH. QR entrapment efficiency and QR in vitro drug release rate were determined from the selected QR-NE then we measured the QR-NE stability. The anticancer activity of the best-selected formula was studied on HT-29 and HCT-116 cell lines. Results: Oleic acid was chosen to prepare QR-NE as it has the best QR solubility. The prepared NE, which had particles size < 200 nm, maximum entrapment efficiency > 80%, and pH 3.688 + 0.102 was selected as the optimal formula. It was a physically stable formula. The prepared QR-NE enhanced the QR release rate (84.52 ± 0.71%) compared to the free drug. QR-NPs significantly improved the cellular killing efficiency in HCT-116 and HT-29 colon cancer cell lines (lower IC50, two folds more than free drug). Conclusion: The prepared QR-NE could be a promising stable formula for improving QR release rate and anticancer activity.
Stress Analysis of KDP Single Crystals Caused by Thermal Expansion Mismatch during Traditional Growth
Authors: Hu Zhitao , Lan Ming , Huang De , Huang Pingping , Wang Shenglai
Published: September 2022

To further elucidate the relationship between the growth stress and cracking of KDP (KH2PO4, potassium dihydrogen phosphate) crystals of different sizes, a three-dimensional finite element calculation was conducted to analyze the growth stress of KDP single crystals grown from Z-plate seeds with varying cooling rates. The mismatch in the coefficient of thermal expansion (CTE), between the cap region and its close vicinity, and among the transparent region, was taken into account. The results indicate that when the cap region is a solid region (when the seed was regenerated with a cooling rate of 0.1 °C/day), the difference in material properties between the cap region and its close vicinity, especially the CTE mismatch along the a-axis, is the main reason of the high stresses. When the cap region is a box-like structure filled with solution (when the seed was regenerated with a cooling rate of 0.3 °C/day), the calculated stress is in proportion to the CTE gradient of the transparent region. Under both models, the stresses induced from an incremental CTE value (from the cap region to the growth front) are greater than those calculated from a diminishing CTE value, implying that the impurities reduce the CTE of KDP crystals, causing the crystals to crack more easily. Despite the maximum stresses inside the crystals changing slightly with an increase in crystal size, the decreased fracture stress of large brittle crystals leads to a higher cracking risk in a large-sized crystal.
Primary Bone Tumors of the Spine—Proposal for Treatment Based on a Single Centre Experience
Authors: Lange Nicole , Jörger Ann-Kathrin , Ryang Yu-Mi , Liesche-Starnecker Friederike , Gempt Jens , Meyer Bernhard
Published: September 2022

This study reports a large single-center series of primary bone tumors of the spine (PBTs). We aimed to review the concepts for management, as this kind of tumor represents a very rare entity, and also propose a new treatment algorithm. Retrospective analysis revealed 92 patients receiving surgery for PBTs from 2007 to 2019 at our center. They were analyzed based on surgical management and the course of the disease. A total of 145 surgical procedures were performed (50 cervical, 46 thoracic, 28 lumbar, and 21 sacral). Complete tumor resection was achieved in 65%, of which 22% showed tumor recurrence during follow-up (mean time to recurrence 334 days). The five-year mortality rate was significantly lower after complete resection (3% versus 25% after subtotal resection). Most of the patients improved in their symptoms through surgery. Regarding the tumor entity, the most common PBTs were vertebral hemangiomas (20%), osteoid osteomas (15%), and chordomas (16%). The Enneking graduation system showed a good correlation with the risk of recurrence and mortality. Complete resection in PBTs increased survival rates and remains the method of choice. Thus, quality of life—especially with a higher extent of resection—should be considered.
Technology-Supported Active Learning in a Flexible Teaching Space
Authors: Sitthiworachart Jirarat , Joy Mike , King Emma , Sinclair Jane , Foss Jonathan
Published: September 2022

Active learning is increasingly of interest within Higher Education. The use of technology provides, in theory, the opportunity for more effective active learning, but in practice the majority of learning technology usage is still for “traditional” approaches. Conventional staff training is failing to address this. The authors’ university has provided an experimental technology-rich teaching space (the Teaching Grid) for supporting teachers as they experiment with the delivery of innovative, technology-based teaching. This study investigates teachers’ experiences of trialling active learning approaches within the Teaching Grid using four case studies. The results suggest that the Teaching Grid can be effectively used to support teacher professional development, and the experience of using the facility encourages teachers to integrate technology into their future teaching plans. Five factors are identified which contribute to the promotion of active learning. Teachers’ perceptions of their experience indicate not only the intention to use technology more but also an increased awareness of its potential and openness to adopt more active, student-focused approaches. The broader significance of this work is to identify an alternative model for teacher development which, in contrast to most current approaches, has a demonstrable positive impact on fostering innovative, technology-based pedagogy.
Methodology for Structured Data-Path Implementation in VLSI Physical Design: A Case Study
Authors: Pudi Dhilleswararao , Harrison Samuel Jigme , Stathis Dimitrios , Boppu Srinivas , Hemani Ahmed , Cenkeramaddi Linga Reddy
Published: September 2022

State-of-the-art modern microprocessor and domain-specific accelerator designs are dominated by data-paths composed of regular structures, also known as bit-slices. Random logic placement and routing techniques may not result in an optimal layout for these data-path-dominated designs. As a result, implementation tools such as Cadence’s Innovus include a Structured Data-Path (SDP) feature that allows data-path placement to be completely customized by constraining the placement engine. A relative placement file is used to provide these constraints to the tool. However, the tool neither extracts nor automatically places the regular data-path structures. In other words, the relative placement file is not automatically generated. In this paper, we propose a semi-automated method for extracting bit-slices from the Innovus SDP flow. It has been demonstrated that the proposed method results in 17% less density or use for a pixel buffer design. At the same time, the other performance metrics are unchanged when compared to the traditional place and route flow.