bluuebunny/crossref_metadata_2025 huggingface dataset:
Hypnotizability and Disordered Personality Styles in Cluster A Personality Disorders
Authors: Zhang Bingren , Pan Bing , Chen Jueying , Wang Junjie , Zhu Zhenyu , Lajunen Timo Juhani , Wang Wei
Published: January 2023

Aim: Interpersonal sensitivity and mistrust are the main characteristics of cluster A personality disorders (CAPD) which might be due to the high accessibility to negative suggestions from environments. Yet the exact associations between hypnotic suggestibility and their personality disorder functioning styles remain unclear. Methods: We invited 36 patients with CAPD and 115 healthy volunteers to undergo the Stanford Hypnotic Susceptibility Scale: Form C (SHSS:C) and Parker Personality Measure (PERM). Results: Compared to controls; patients scored higher on PERM paranoid; schizoid; schizotypal; borderline; avoidant; and dependent styles; on the SHSS:C total and “challenge suggestions”, and the passing rates of “hand lowering”, “arm rigidity”, “dream”, and “arm immobilization”. In patients, “dream” negatively predicted the schizoid; “hallucinated voice” negatively the schizotypal; “mosquito hallucination” positively the histrionic and dependent; and “arm immobilization” negatively the avoidant style. Conclusions: Our results suggested that the insusceptibility to perceptual suggestions from others and the high control over body contribute to the paranoid attitude and interpersonal avoidance in CAPD. These findings help to understand the cause of interpersonal problems in these patients and suggest the trial of hypnotherapy for them.
Non-Association of Driver Alterations in PTEN with Differential Gene Expression and Gene Methylation in IDH1 Wildtype Glioblastomas
Authors: Mallik Mrinmay Kumar , Majumdar Kaushik , Mujtaba Shiraz
Published: January 2023

During oncogenesis, alterations in driver genes called driver alterations (DAs) modulate the transcriptome, methylome and proteome through oncogenic signaling pathways. These modulatory effects of any DA may be analyzed by examining differentially expressed mRNAs (DEMs), differentially methylated genes (DMGs) and differentially expressed proteins (DEPs) between tumor samples with and without that DA. We aimed to analyze these modulations with 12 common driver genes in Isocitrate Dehydrogenase 1 wildtype glioblastomas (IDH1-W-GBs). Using Cbioportal, groups of tumor samples with and without DAs in these 12 genes were generated from the IDH1-W-GBs available from “The Cancer Genomics Atlas Firehose Legacy Study Group” (TCGA-FL-SG) on Glioblastomas (GBs). For all 12 genes, samples with and without DAs were compared for DEMs, DMGs and DEPs. We found that DAs in PTEN were unassociated with any DEM or DMG in contrast to DAs in all other drivers, which were associated with several DEMs and DMGs. This contrasting PTEN-related property of being unassociated with differential gene expression or methylation in IDH1-W-GBs was unaffected by concurrent DAs in other common drivers or by the types of DAs affecting PTEN. From the lists of DEMs and DMGs associated with some common drivers other than PTEN, enriched gene ontology terms and insights into the co-regulatory effects of these drivers on the transcriptome were obtained. The findings from this study can improve our understanding of the molecular mechanisms underlying gliomagenesis with potential therapeutic benefits.
Explaining the Consumption Technology Acceptance in the Elderly Post-Pandemic: Effort Expectancy Does Not Matter
Authors: Ramírez-Correa Patricio , Grandón Elizabeth Eliana , Ramírez-Santana Muriel , Arenas-Gaitán Jorge , Rondán-Cataluña F. Javier
Published: January 2023

Consumer technology has been enormously boosted by the COVID-19 pandemic, with one of the primary consumers being the elderly. In this scenario, it is necessary to consider the impact of technologies on different older generational cohorts to understand the future of a data-driven digital society fully. This research aims to explain the acceptance of social networking sites, a particular consumer technology, in the post-pandemic elderly population. Data were obtained from 1555 older adults in Chile based on a consumer technology acceptance model. The respondents were grouped according to their technological predisposition and their generation into three groups. Applying a multigroup analysis based on structural equation modelling reveals significant differences in the explanatory variables of the intention and use of this technology between the groups. And more remarkably, the effort expectancy is not statistically significant as a variable to explain this acceptance globally in either of the three groups. There are two principal contributions of this study. First, it shows why adults adopt consumer technology after the pandemic. Second, it validates a classification of elderly adults who use consumption technologies that are useful in understanding the heterogeneity of this phenomenon.
Comprehensive Social Cultural and Economic Benefits of Green Buildings Based on Improved AHP–FCE Method
Authors: Zhao Weishu , Peng Peng , Guo Bao , Deng Xinran , Wu Weidong
Published: January 2023

Green buildings can effectively alleviate energy scarcity and improve environmental quality, and are becoming the mainstream mode of transformation and upgrading of the construction industry. It is given great importance by all sectors of society committed to implementing the “carbon peak” and “carbon neutral” goals earnestly. However, the unclear comprehensive benefits of green buildings restrict their development in China. The existing studies tend to be limited to a single aspect, such as economic benefits or environmental benefits. The purpose of this study is to establish a more systematic and complete evaluation system for green buildings’ comprehensive benefits. It can increase the consideration of the impact of social and cultural benefits, along with the first two benefits. Firstly, by also considering the triple bottom line principle and benefit principle, four primary indicators and twenty secondary indicators were selected to establish a comprehensive benefit evaluation system for green buildings. Secondly, an improved AHP–FCE method was adopted to determine the weights of each secondary indicator. Finally, the feasibility of the evaluation system was verified through a case study, and some suggestions for improving the comprehensive benefits of green buildings were put forward.
Machine Learning Approach to Predict Building Thermal Load Considering Feature Variable Dimensions: An Office Building Case Study
Authors: Chen Yongbao , Ye Yunyang , Liu Jingnan , Zhang Lixin , Li Weilin , Mohtaram Soheil
Published: January 2023

An accurate and fast building load prediction model is critically important for guiding building energy system design, optimizing operational parameters, and balancing a power grid between energy supply and demand. A physics-based simulation tool is traditionally used to provide the building load demand; however, it is constrained by its complex model development process and requirement for engineering judgments. Machine learning algorithms (i.e., data-driven models) based on big data can bridge this gap. In this study, we used the massive energy data generated by a physics-based tool (EnergyPlus) to develop three data-driven models (i.e., LightGBM, random forest (RF), and long-short term memory (LSTM)) and compared their prediction performances. The physics-based models were developed using office prototype building models as baselines, and ranges were provided for selected key input parameters. Three different input feature dimensions (i.e., six-, nine-, and fifteen-input feature selections) were investigated, aiming to meet different demands for practical applications. We found that LightGBM significantly outperforms the RF and LSTM algorithms, not only with respect to prediction accuracy but also in regard to computation cost. The best prediction results show that the coefficient of variation of the root mean squared error (CVRMSE), squared correction coefficient (R2), and computation time are 5.25%, 0.9959, and 7.0 s for LightGBM, respectively, evidently better than the values for the algorithms based on RF (18.54%, 0.9482, and 44.6 s) and LSTM (22.06%, 0.9267, and 758.8 s). The findings demonstrate that a data-driven model is able to avoid the process of establishing a complicated physics-based model for predicting a building’s thermal load, with similar accuracy to that of a physics-based simulation tool.
Data-Driven Shear Strength Prediction of FRP-Reinforced Concrete Beams without Stirrups Based on Machine Learning Methods
Authors: Yang Yuanzhang , Liu Gaoyang
Published: January 2023

Due to the intrinsic complexity, there has been no widely accepted mechanics-based estimation model of the shear performance of Fiber-Reinforced Polymer (FRP)-reinforced concrete beams. Capitalizing on a large amount of previous experimental data, data-driven machine learning (ML) models could be potentially suitable for addressing this problem. In this paper, four existing shear design provisions are reviewed and four typical ML models are analyzed. The accuracy of codified methods and ML models are compared and analyzed based on our established extensive database of FRP-reinforced concrete beams with rectangular cross sections. A series of artificially selected features considering the shear-carrying mechanisms of FRP-reinforced beams are incorporated into the proposed ML models to show their influence on the model validity. Bayesian optimization is utilized to automatically tune the hyperparameters of different ML models. Compared to the most satisfying codified predictions from CSA S806, the best ML model, XGBoost, can provide more accurate and consistent predictions for the database, with R2 enhanced by 15% and the MAE and RMSE reduced by 59% and 52%, respectively. With the selected features based on domain knowledge, the performance of ML models is further enhanced, shown by the most important features being the added ones. With outstanding performance on a large database and singular test, the ML approaches have great potential in guiding the shear design of FRP-reinforced concrete.
DNN-Based Estimation of the Maximum Lateral Flange Moments of Horizontally Curved I-Girder Bridges
Authors: Ryu Seongbin , Lee Jeonghwa , Kang Young Jong
Published: January 2023

Horizontally curved I-girder bridges are known to be complex. Bending and torsion forces are imposed on the bridges owing to their shapes with initial curvatures. This torsion is a combination of pure and warping forces. The horizontally curved I-girder is significantly affected by warping behavior, which decreases the bending rigidity of its member. To investigate the warping behavior of the horizontally curved I-girder bridges a finite element analysis (FEA) must be performed. In this study, an FEA was performed to investigate the warping torsional behavior of a horizontally curved I-girder bridge, and a structural response database was obtained. Based on the database, the least absolute shrinkage and selection operator was employed to select features affecting the warping behavior. Subsequently, deep neural network models were trained with selected features for an input layer and maximum lateral flange moment data for an output layer. Several models were constructed and compared according to the number of hidden layers and neurons, and the model with the highest performance was proposed. Finally, it was confirmed that the estimated lateral flange moments computed by the proposed model showed a good correlation with the FEA results.
Seismic Hazard Curve as Dynamic Parameters in Earthquake Building Design for Sabah, Malaysia
Authors: Harith Noor Sheena Herayani , Tongkul Felix , Adnan Azlan
Published: January 2023

This paper presents the significance of a seismic hazard curve plot as a dynamic parameter in estimating earthquake-resistant structures. Various cases of structural damages in Malaysia are due to underestimating earthquake loadings since mostly buildings were designed without seismic loads. Sabah is classified as having low to moderate seismic activity due to a few active fault lines. Background point, area, and line sources are the three tectonic features that have impacted Sabah. Data on earthquakes from 1900 to 2021 have been collected by a number of earthquake data centers. The seismicity is based on a list of historical seismicities in the area, which stretches from latitudes 4 °S to 8 °N and longitudes 115 °E to 120 °E. The goal of this research is to develop a seismic hazard curve based on a conventional probabilistic seismic hazard analysis being examined for the maximum peak ground acceleration at 10% probability of exceedance as published in MSEN1998-1:2015. This study extended to 5% and 2% probability of exceedance combined with the seismic hazard curve by using Ranau as a case study. To calculate the expected ground motion recurrence, such as peak ground acceleration at the site, earthquake recurrence models were combined with selected ground motion models. A logic tree structure was used to combine simple quantities such as maximum magnitudes and the chosen ground motion models to describe epistemic uncertainty. The result demonstrates that peak ground acceleration values at the bedrock were estimated to be 0.16, 0.21, and 0.28 g of the total seismic hazard curve at 10%, 5%, and 2% PE in a 50-year return period, respectively. The seismic hazard study at a Ranau site basically depends on the seismicity of a region and the consequences of failure in the past. Thus, the results can be used as a basis for benchmarking design or evaluation decisions and for designing remedial measures for Sabah constructions to minimize structural failure.
Photogrammetry as a Digital Tool for Joining Heritage Documentation in Architectural Education and Professional Practice
Authors: Salagean-Mohora Irina , Anghel Anamaria Andreea , Frigura-Iliasa Flaviu Mihai
Published: January 2023

Given the accelerated technological advance in all fields, vast knowledge of digital tools becomes mandatory for future interior designers and architects. Thus, experimenting with as many such methods and technologies must become a priority for the teaching process. Noticing a high demand for digitalization during the COVID-19 pandemic, the Polytechnic University of Timisoara has decided to encourage the implementation of digital teaching throughout disciplines, preparing students for their future careers. Photogrammetry as a study method, among others, has the potential to outrank traditional documentation techniques currently applied in architectural education and practice. The presented research was divided into two main phases: an educational, experimental workshop and a project restoration application. After learning, testing, and refining the close-range photogrammetry workflow, the authors and students took the best practices and applied them to an ongoing facade restoration project in Timisoara, scanning original and restored plaster ornaments and finally 3D printing one of the models. The article aims to show that, unlike traditional teaching methods, using photogrammetry as a documentation process creates a coherent link between theoretical education and restoration practice. Consequently, the exercise brings students closer to the applicable side of their careers through a contemporary digital technique.
Research on Seismic Performance of 735 MPa High-Strength Reinforced Concrete Frame Joints
Authors: Zhang Xiao , Han Fei , Wang Xuekun , Sun Lele , Wang Qi , Wang Peijun
Published: January 2023

To study the seismic performance of high-strength reinforced concrete frame joints, cyclic loading tests were carried out on six concrete beam-column joints configured with the new Cold-rolled Ribbed Bar (CRB) 735 high-strength steel reinforcement and one joint with Hot-rolled Ribbed Bar (HRB) 400 ordinary steel reinforcement to obtain the effects of the axial compression ratio and the stirrup ratio in the joint core on the seismic performance of the joints. The test results show that the following: (1) Increasing the axial compression ratio can improve the energy dissipation characteristics of the joints configured with CRB735, but cannot effectively improve the ultimate shear capacity of the joints. Larger axial compression ratio will cause earlier cracks in the core area and reduce the ductility of the specimens by 6.1~27.9%. (2) Increasing the stirrup ratio in the joint core will increase the shear capacity of the joint by 5.3~8.1% while also increasing the failure displacement by 2.8~14.9%. (3) When the joints are configured with CRB735 stirrups, the rate of stiffness degradation from core cracking to the yielding stage of the specimens will be effectively delayed. (4) Compared with the joint configured with HRB400, the ultimate loading process of the joints using CRB735 is shorter, the yield load and yield displacement are higher, and the specimens are close to the ultimate state when they reach yield. Finally, the shear capacity of concrete beam-column joints configured with CRB735 can be calculated using the relevant shear capacity equation in GB50010-2010 Code for Design of Concrete Structures, and has a certain safety reserve. In the equation, the yield strength of CRB735 steel reinforcement is recommended to be 735 MPa.
Study on the Evolution Law of Internal Force and Deformation and Optimized Calculation Method for Internal Force of Cantilever Anti-Slide Pile under Trapezoidal Thrust Load
Authors: Jin Honghua , Ren Qingyang , Xiao Songqiang
Published: January 2023

The evolution law of internal force and deformation of an anti-slide pile affects the slope stability and prevention design in a significant way. Based on the similarity theory, a test system for the bearing characteristics of a cantilever anti-slide pile was constructed, and the physical model test for the bearing characteristics of a cantilever anti-slide pile under trapezoidal thrust load was carried out. The distribution laws of internal force and deformation of a cantilever anti-slide pile were revealed, and the optimized calculation method for internal force of a cantilever anti-slide pile was proposed by taking the elastoplastic characteristics of steel bars and concrete into consideration. Furthermore, a numerical model was employed to conduct a parametric analysis of a cantilever anti-slide pile. The results show that the whole process of stress and deformation of a cantilever anti-slide pile can be classified as the uncracked stage, the cracks emerging and developing stage, and the steel bars yielding–failing stage. In the uncracked stage, the bending moment of the cantilever anti-slide pile calculated by the traditional method is smaller than that calculated by the optimized calculation method established in this paper. The traditional calculation method is no longer applicable in the stage of cracks emerging and developing. The lateral displacement and bending moment of the cantilever anti-slide pile are negatively and positively correlated with the strength of the pile material, respectively, and the influence of the deterioration of steel bars’ strength on the ultimate bearing performance of the anti-slide pile is more obvious than that of the deterioration of concrete strength. The bearing capacity of the anti-slide pile could not be significantly improved by increasing the length of the anchored section when the strength of the rock stratum embedded in anchored section was large enough. As the thrust load behind the pile increased, the difference of the bearing performances of the cantilever anti-slide pile under the uniform load and trapezoidal load increased gradually. The research results can provide guidance for the evaluation of the service performance of the cantilever anti-slide pile and the slope stability.
Study of the Data Augmentation Approach for Building Energy Prediction beyond Historical Scenarios
Authors: Fang Haizhou , Tan Hongwei , Kosonen Risto , Yuan Xiaolei , Jiang Kai , Ding Renrong
Published: January 2023

Building energy consumption predictive modeling using data-driven machine learning is currently highly prevalent. However, the model typically performs poorly when the predicted day’s energy consumption exceeds the upper bound of the historical data. In this study, energy consumption projections are examined outside of historical boundary scenarios, including three occupancy behavior data (HVAC system, lighting, and equipment) and three operating future scenarios (Scenario 1: utilization rate is highest simultaneously; Scenario 2: energy-saving lighting renovation; Scenario 3: the number of people working is decreased). We propose using data augmentation based on the occupancy behavior (DAOB) method, which expands the building’s three occupancy behaviors. The case study showed that, among the three future operating scenario prediction tasks, scenario 1’s performance was the least accurate, with an average relative error of 50.21% compared to the DAOB method’s average relative error of 7.07%. The average relative error in Scenario 2 decreased from 15.83% to 10.10%. The average relative error in Scenario 3 decreased from 20.97% to 6.5%. This provided an efficient method of combining physical models with data-driven models, which significantly increased robustness and reliability of the model.
Risk Group Stratification for Recurrence-Free Survival and Early Tumor Recurrence after Radiofrequency Ablation for Hepatocellular Carcinoma
Authors: Cha Dong Ik , Ahn Soo Hyun , Lee Min Woo , Jeong Woo Kyoung , Song Kyoung Doo , Kang Tae Wook , Rhim Hyunchul
Published: January 2023

Purpose: Although the prognosis after radiofrequency ablation (RFA) for hepatocellular carcinoma (HCC) may vary according to different risk levels, there is no standardized follow-up protocol according to each patient’s risk. This study aimed to stratify patients according to their risk of recurrence-free survival (RFS) and early (≤2 years) tumor recurrence (ETR) after RFA for HCC based on predictive models and nomograms and to compare the survival times of the risk groups derived from the models. Methods: Patients who underwent RFA for a single HCC (≤3 cm) between January 2012 and March 2014 (n = 152) were retrospectively reviewed. Patients were classified into low-, intermediate-, and high-risk groups based on the total nomogram points for RFS and ETR, respectively, and compared for each outcome. Restricted mean survival times (RMSTs) in the three risk groups were evaluated for both RFS and ETR to quantitatively evaluate the difference in survival times. Results: Predictive models for RFS and ETR were constructed with c-indices of 0.704 and 0.730, respectively. The high- and intermediate-risk groups for RFS had an 8.5-fold and 2.9-fold higher risk of events than the low-risk group (both p < 0.001), respectively. The high- and intermediate-risk groups for ETR had a 17.7-fold and 7.0-fold higher risk than the low-risk group (both p < 0.001), respectively. The RMST in the high-risk group was significantly lower than that in the other two groups 9 months after RFA, and that in the intermediate-risk group became lower than that in the low-risk group after 21 months with RFS and 24 months with ETR. Conclusion: Our predictive models were able to stratify patients into three groups according to their risk of RFS and ETR after RFA for HCC. Differences in RMSTs may be used to establish different follow-up protocols for the three risk groups.
Merkel Cell Polyomavirus Large T Antigen Induces Cellular Senescence for Host Growth Arrest and Viral Genome Persistence through Its Unique Domain
Authors: Pham Alexander M. , Ortiz Luz E. , Lukacher Aron E. , Kwun Hyun Jin
Published: January 2023

Senescent cells accumulate in the host during the aging process and are associated with age-related pathogeneses, including cancer. Although persistent senescence seems to contribute to many aspects of cellular pathways and homeostasis, the role of senescence in virus-induced human cancer is not well understood. Merkel cell carcinoma (MCC) is an aggressive skin cancer induced by a life-long human infection of Merkel cell polyomavirus (MCPyV). Here, we show that MCPyV large T (LT) antigen expression in human skin fibroblasts causes a novel nucleolar stress response, followed by p21-dependent senescence and senescence-associated secretory phenotypes (SASPs), which are required for MCPyV genome maintenance. Senolytic and navitoclax treatments result in decreased senescence and MCPyV genome levels, suggesting a potential therapeutic for MCC prevention. Our results uncover the mechanism of a host stress response regulating human polyomavirus genome maintenance in viral persistency, which may lead to targeted intervention for MCC.
Mitophagy Effects of Protodioscin on Human Osteosarcoma Cells by Inhibition of p38MAPK Targeting NIX/LC3 Axis
Authors: Huang Chien-Feng , Hsieh Yi-Hsien , Yang Shun-Fa , Kuo Chao-Hung , Wang Pei-Han , Liu Chung-Jung , Lin Renn-Chia
Published: January 2023

Protodioscin (PD) is a steroidal saponin with various pharmacological activities, including neuro-protective, anti-inflammatory, and anti-tumor activities. However, the effect of PD on human osteosarcoma (OS) cells is unclear. In this study, we found that PD significantly inhibits the growth of human HOS and 143B OS cells through the upregulation of apoptotic-related proteins (cleaved caspase-3, cleaved caspase-9, and cleaved PARP) and mitophagy-related proteins (LC3B and NIX), which contribute to the induction of apoptosis, and MMP (mitochondrial membrane potential) dysfunction and mitophagy. The inhibition of LC3 or NIX was shown to decrease apoptosis and mitophagy in PD-treated OS cells. The knockdown of p38MAPK by siRNA decreased mitochondrial dysfunction, autophagy, mitophagy, and the NIX/LC3B expression in the PD-treated OS cells. A binding affinity analysis revealed that the smaller the KD value (−7.6 Kcal/mol and −8.9 Kcal/mol, respectively), the greater the binding affinity in the PD-NIX and PD-LC3 complexes. These findings show the inhibitory effects of PD-induced mitophagy in human OS cells and may represent a novel therapeutic strategy for human OS, by targeting the NIX/LC3 pathways.
Mass-Mediated Phase Modulation of Thin Molybdenum Nitride Crystals on a Liquid Cu-Mo Alloy
Authors: Li Minghui , Zhang Qing , Fan Yixuan , Li Lin , Geng Dechao , Hu Wenping
Published: January 2023

The high-quality and controllable preparation of molybdenum nitrides (MoxNy) will significantly advance the fields of heterogeneous catalysis, energy storage, and superconductivity. However, the complex structure of MoxNy, which contains multiple phases, makes exploring the structure-property relationship challenging. The selective preparation of MoxNy with distinct phases is undoubtedly an effective method for addressing this issue, but it is lacking experimental cases and theoretical reports. Here we demonstrate a feasible chemical vapor deposition (CVD) strategy for selectively producing γ-Mo2N or δ-MoN through modulating the mass quantity of N precursors. A liquid Cu-Mo alloy was used as a Mo precursor and catalyst in this system. The resulting γ-Mo2N was systematically characterized and found to be of high quality. Furthermore, the morphology evolutions of γ-Mo2N and δ-MoN with growth time were summarized in detail, as a result of growth and etching dynamics. This work promotes the phase modulation of MoxNy and provides a framework for future research on the structure-property relationship.
Highly Efficient, Non-Covalent Functionalization of CVD-Graphene via Novel Pyrene-Based Supporter Construct
Authors: Shahzadi Misbah , Nisar Sobia , Kim Deok-Kee , Sarwar Nasir , Rasheed Aamir , Ahmad Waqas , Afzal Amir Muhammad , Imran Muhammad , Assiri Mohammed Ali , Shahzad Zafar M. , Dastgeer Ghulam
Published: January 2023

Ultra-thin two-dimensional (2D) materials have attained huge interest for biosensing applications because of their strong electrostatic coupling with target molecules such as spike proteins and DNA. One such 2D material is graphene, which is extremely thin and flexible and has a strong non-covalent interaction with the supporting constructs needed to detect biomolecules. This work aimed to develop a way to efficiently functionalize the surface of 2D material using a pyrene-based supporter construct to detect the target protein. For this purpose, high-quality, pristine graphene was grown via the chemical vapor deposition (CVD) method and transferred over the Si/SiO2 substrate for its functionalization using our engineered pyrene–lysine-based supporter construct (PLB). The construct was synthesized using the solid-phase peptide synthesis (SPPS) method and utilized to functionalize the graphene-channel-based field-effect transistor (FET) device via non-covalent π−π stacking interaction. The optimum concentration of the functionalized PLB was evaluated via atomic force microscopy (AFM), Raman spectroscopy, and real-time electrical measurements. The characterization techniques successfully provide an overview of the effect of the concentration of PLB used for functionalization. Moreover, the performance was tested and compared in terms of the percentage response of the device generated after the detection of various concentrations of the streptavidin protein. This research could be useful in determining how to functionalize any 2D material by designing a supporter construct without material degradation and owing to over-stacking or bypassing surface screening effects.
Chiral Recognition of Phenylglycinamide Enantiomer Based on Electrode Modified by Silver-Ammonia Ion-Functionalized Carbon Nanotubes Complex
Authors: Yao Wenyan , Li Sha , Kong Yong , Xie Licheng , Jiang Yan
Published: January 2023

Polyacrylic acid (PAA) chains were used to decorate the surface of multi-walled carbon nanotubes (MWCNTs) via in situ free radical polymerization, and sulfonated chitosan (SCS) was synthesized via a simple and environmental method. Silver-ammonia ions were introduced as the fixative with PAA-MWCNTs as the basic framework, and SCS was used to decorate the surface, thereby obtaining PAA-MWCNTs-Ag-SCS. The modified electrode exhibited excellent cyclic voltammogram (CV) stability after 100 cycles of scanning. According to differential pulse voltammetry (DPV), the peak current value was approximately 250 μA, exhibiting outstanding sensitivity to phenylglycinamide (Pen) enantiomers. The peak current ratio of D-Pen to L-Pen reached 2.16, showing excellent selectivity. The detection limit (DL) was calculated as 0.015 mM and 0.036 mM for L-Pen and D-Pen, respectively, using the signal-to-noise ratio (S/N = 3). This study provides a new idea for the construction of a chiral-sensing platform with outstanding sensitivity, superior stability, and excellent recognition efficiency.
Evaluation of the Impact of Seasonal Agroclimatic Information Used for Early Warning and Farmer Communities’ Vulnerability Reduction in Southwestern Niger
Authors: Seydou Tinni Halidou , Agali Alhassane , Aissatou Sita , Seydou Traore B. , Issaka Lona , Ibrahim Bouzou Moussa
Published: January 2023

In Niger (a fully Sahelian country), the use of climate information is one of the early warning strategies (EWSs) for reducing socio-economic vulnerabilities in farmer communities. It helps farmers to better anticipate risks and choose timely alternative options that can allow them to generate more profit. This study assesses the impacts of the use of climate information and services that benefit end-users. Individual surveys and focus groups were conducted with a sample of 368 people in eight communes in Southwestern Niger. The survey was conducted within the framework of the ANADIA project implemented by the National Meteorological Direction (NMD) of Niger. The survey aims to identify different types of climate services received by communities and evaluates the major benefits gained from their use. Mostly, the communities received climate (73.6%) and weather (99%) information on rainfall, temperature, dust, wind, clouds, and air humidity. Few producers in the area (10%) received information on seasonal forecasts of the agrometeorological characteristics of the rainy season. The information is not widely disseminated in the villages during the roving seminars conducted by the NMD. For most people, this information is highly relevant to their needs because of its practical advice for options to be deployed to mitigate disasters for agriculture, livestock, health, water resources, and food security. In those communities, 82% of farmers have (at least once) changed their routine practices as a result of the advice and awareness received according to the climate information. The information received enables farmers (64.4%) to adjust their investments according to the profile of the upcoming rainfall season. The use of climate information and related advice led to an increase of about 64 bunches (equivalent to 10 bags of 100 kg) in annual millet production, representing an income increase of about 73,000 FCFA from an average farmland of 3 ha per farmer. In addition, the use of climate information helps to reduce the risks of floods and droughts, which often cause massive losses to crop production, animal and human life, infrastructure, materials, and goods. It has also enabled communities to effectively manage seeds and animal foods and to plan social events, departures and returns to rural exodus. These analyses confirm that the use of climate information serves as an EWS that contributes to increasing the resilience of local populations in the Sahel.
Highly Conductive Flexible Conductor Based on PEDOT:PSS/MWCNTs Nano Composite
Authors: Alhashmi Alamer Fahad
Published: January 2023

Flexible textiles with strong electrical conductivities have enormous potential as active components in wearable electronics. In this study, we fabricated highly flexible electrical conductors based on cotton fabrics using multiwalled carbon nanotubes (MWCNTs) and poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate) (PEDOT:PSS) nanocomposites. We propose that mixing and drop-casting with different amounts of MWCNTs and a fixed amount of doped PEDOT:PSS using a cotton fabric provides a wide range of conductivities depending on the amount of MWCNTs in the mixture. Scanning electron microscopy (SEM) confirmed that the distribution of MWCNTs in the PEDOT:PSS films coated the surface of the cotton fabric, thereby increasing its electrical conductivity. We found that the amount of MWCNTs significantly affected the electrical properties of the nanocomposite cotton in two ways. First, the sheet resistance of the nanocomposite cotton decreased from 78.35 Ω/□ to 2.86 Ω/□ when the concentration of the nanocomposite was increased from 9.21 wt% to 60.27 wt%. This implies that the electrical properties of the nanocomposite cotton can be adjusted by controlling the amount of MWCNTs in the blend. Moreover, we found that the relationship between the sheet resistance and nanocomposite concentration obeys the power law with an exponent α ~ 1.676. Second, the study of the effect of temperature on the resistance indicates that the conductive nanocomposite exhibits semiconductor behavior in the temperature range 24–120 °C and obeys the variable range hopping model. The characteristic temperatures, resistance prefactor, and density of localized states and activation energies depend on the concentration of MWCNTs and can be described by power laws with exponents of 0.470, −1.292, −0.470 and 0.118, respectively. The novel nanocomposite cotton fabric developed in this study exhibits suitable electrical and thermal properties and good long-term electrical stability, which make the nanocomposite cotton fabric a potential flexible conductor with a wide range of electrical conductivities, making it suitable for various applications.
Study on the Surface Structure of N-Doped 4H-SiC Homoepitaxial Layer Dependence on the Growth Temperature and C/Si Ratio Deposited by CVD
Authors: Tang Zhuorui , Gu Lin , Ma Hongping , Dai Kefeng , Luo Qian , Zhang Nan , Huang Jiyu , Fan Jiajie
Published: January 2023

The quality of the N-doped 4H-SiC homoepitaxial layers grown via hot-wall horizontal chemical vapor deposition (CVD) was evaluated at various C/Si ratios (1.0–1.2) and growth temperatures (1570–1630 °C). The microstructure and morphology of the epilayers were studied through a comparative analysis of the AFM patterns under different growth conditions. X-ray photoelectron spectroscopy and Raman spectroscopy revealed the quality of the 4H-SiC epilayers and the amount of N-doping. It was found that an increase in the C/Si ratio enabled obtaining a quite smooth epitaxial layer surface. Moreover, only the 4H-SiC crystal type was distinguished in the epilayers. In addition, the epitaxial quality was gradually improved, and the amount of defect-related C-C bonds significantly dropped from 38.7% to 17.4% as the N doping content decreased from 35.3% to 28.0%. An increase in the growth temperature made the epitaxial layer surface smoother (the corresponding RMS value was ~0.186 nm). According to the Raman spectroscopy data, the 4H-SiC forbidden mode E1(TO) in the epilayers was curbed at a higher C/Si ratio and growth temperature, obtaining a significant enhancement in epitaxial quality. At the same time, more N dopants were inserted into the epilayers with increasing temperature, which was opposite to increasing the C/Si ratio. This work definitively shows that the increase in the C/Si ratio and growth temperature can directly enhance the quality of the 4H-SiC epilayers and pave the way for their large-scale fabrication in high-power semiconductor devices.
Defective Graphene Effects on Primary Displacement Damage and He Diffusion at a Ni–Graphene Interface: Molecular Dynamics Simulations
Authors: Huang Hai , Yuan Xiaoting , Ge Xiaoxin , Peng Qing
Published: January 2023

Ni–graphene nanocomposites with high-density interfaces have enormous potential as irradiation-tolerant materials applied in Gen-IV reactors. Nevertheless, the mechanism wherein the intrinsic and/or irradiation-induced defects of graphene affect the irradiation tolerance of the composites remains poorly understood. Here, we investigate the effects of the two types of defective graphene on the displacement damage and He diffusion of the composites, respectively, using atomistic simulations. The introduction of the intrinsic defects of graphene has a significant effect on the Ni lattice structure near the Ni–graphene interface, especially showing that after displacement cascades, the number of defects gradually increases with the increase in graphene-defective size due to the formation and growth of stacking fault tetrahedra. The existence of the irradiation-induced defects of graphene does not diminish the ability of the interface to trap He atoms/clusters and even may be maintained or improved, mainly reflected in the fact that many isolated He atoms and small clusters can gradually migrate toward the interface and the fraction of He within the interface is up to 37.72% after 1 ns. This study provides an important insight into the understanding of the association relationships of defective graphene with the irradiation tolerance of composites.
Transverse Microradiography Evidence on the Effect of Phosphoryl Oligosaccharides of Calcium (POs-Ca) in Toothpaste on Decalcified Enamel
Authors: Inoue Go , Chen Xuefei , Shimada Yasushi
Published: January 2023

In the current study, we sought to evaluate the effects of phosphoryl-oligosaccharides of calcium (POs-Ca) and/or fluoride-containing toothpaste on enamel. Six groups of experimental toothpaste were prepared by adding various concentrations of POs-Ca and/or fluoride. A 5 × 10-mm window on the enamel of the bovine incisor was immersed in resin and divided into three areas for “sound”, “demineralized (DEM)”, and “after pH cycle (aft. pH cycle)”. All specimens were subjected to pH cycling, including soaking in a slurry with toothpaste diluted threefold for 5 min. Transverse microradiography was employed to evaluate the mineral recovery, and the pH values of each demineralization solution were measured. The high fluoride concentration group showed a significantly better mineral recovery rate than the others, with no statistical differences between before and after pH cycling among the POs-Ca with low fluoride, POs-Ca only, low fluoride only, and control groups. In the low-concentration fluoride groups, the group containing POs-Ca tended to have a higher remineralization effect than the non-POs-Ca group. After pH cycling, the demineralization solution showed no pH changes in any group. The addition of POs-Ca and fluoride to toothpaste may recover the mineral density in enamel subsurface lesions at low-fluoride concentrations, but the high-fluoride concentrations did not show a meaningful difference in the two groups with and without POs-Ca.
Cannibalism as Competition Strategy in Larvae of the Acorn Weevil Curculio glandium (Coleoptera: Curculionidae)
Authors: Reut Michał , Bonal Raul , Chrabąszcz Mariusz , Moniuszko Hanna
Published: January 2023

Curculio glandium is one of the pre-dispersal seed predators occurring in Central Europe. It is associated with Quercus robur, the acorns of which are shelter and food sources for developing larvae. Females of the species, to our knowledge, are lacking in marking pheromones or do not use them; therefore, in nature, multiple infestations (over 10 eggs or larvae) of the same host fruit can be found. Such density can provoke very strong competition, which was verified in this study. The survival rate and body mass of 695 second-instar larvae, competing in various test groups (one, three, five, eight and ten larvae) offered one acorn, were measured and video recordings made in order to describe their behavior and determine differences between groups. Experimental observations indicated that when the density of larvae in an acorn increased, the survival rate and body mass significantly decreased—being the lowest in test groups consisting of eight and ten individuals. In the latter groups, also the acorn embryo was completely consumed. Video footage, along with the presence of dead, nibbled larvae and living ones covered with scars resembling mouthparts, is evidence for aggression and cannibalism in the second and the third larval instars—behavior scarce in weevils and in phytophagous insects in general. Results confirm the assumption that in heavily infested oak fruits, competition between individuals is so strong that it involves cannibalism, which at the same time provides the strongest larvae with additional nutrients.
Are Intermittent Rivers in the Karst Mediterranean Region of the Balkans Suitable as Mayfly Habitats?
Authors: Vilenica Marina , Rebrina Fran , Ružanović Lea , Rumišek Mario , Matoničkin Kepčija Renata , Brigić Andreja
Published: January 2023

Intermittent rivers, common in dry parts of the world, such as the Mediterranean region, are hydrologically harsh habitats characterized by periodical flow cessation. Ephemeroptera are aquatic insects common in both lotic and lentic waterbodies, where they show a high sensitivity to anthropogenic modifications of their habitat. Therefore, they are widely used as bio-indicators of the freshwater’s health. However, mayfly assemblages and their ecological requirements in the karst Mediterranean intermittent habitats are still not sufficiently known. Thus, the work presented here includes an analysis of mayfly assemblages and their relationship with environmental variables in the lotic phase of four intermittent rivers in the karst Mediterranean region of Croatia. Considering that the studied intermittent rivers are hydrologically extreme environments, a total of 12 recorded mayfly species could be considered as rather high species richness. Nevertheless, species richness per river was quite low (between three and six), and was highly influenced by river morphology, physico-chemical water properties (especially conductivity, water velocity, and concentrations of dissolved oxygen), and anthropogenic pressures. Our results could contribute to the mayfly species protection in karst Mediterranean intermittent freshwater habitats in the Balkans, as well as to the development of conservation measures for those threatened habitats.
Novel Prediction Method Applied to Wound Age Estimation: Developing a Stacking Ensemble Model to Improve Predictive Performance Based on Multi-mRNA
Authors: Dang Lihong , Li Jian , Bai Xue , Liu Mingfeng , Li Na , Ren Kang , Cao Jie , Du Qiuxiang , Sun Junhong
Published: January 2023

(1) Background: Accurate diagnosis of wound age is crucial for investigating violent cases in forensic practice. However, effective biomarkers and forecast methods are lacking. (2) Methods: Samples were collected from rats divided randomly into control and contusion groups at 0, 4, 8, 12, 16, 20, and 24 h post-injury. The characteristics of concern were nine mRNA expression levels. Internal validation data were used to train different machine learning algorithms, namely random forest (RF), support vector machine (SVM), multilayer perceptron (MLP), gradient boosting (GB), and stochastic gradient descent (SGD), to predict wound age. These models were considered the base learners, which were then applied to developing 26 stacking ensemble models combining two, three, four, or five base learners. The best-performing stacking model and base learner were evaluated through external validation data. (3) Results: The best results were obtained using a stacking model of RF + SVM + MLP (accuracy = 92.85%, area under the receiver operating characteristic curve (AUROC) = 0.93, root-mean-square-error (RMSE) = 1.06 h). The wound age prediction performance of the stacking models was also confirmed for another independent dataset. (4) Conclusions: We illustrate that machine learning techniques, especially ensemble algorithms, have a high potential to be used to predict wound age. According to the results, the strategy can be applied to other types of forensic forecasts.