bluuebunny/crossref_metadata_2025 huggingface dataset:
A Group Resident Daily Load Forecasting Method Fusing Self-Attention Mechanism Based on Load Clustering
Authors: Cao Jie , Zhang Ru-Xuan , Liu Chao-Qiang , Yang Yuan-Bo , Chen Chin-Ling
Published: January 2023

Daily load forecasting is the basis of the economic and safe operation of a power grid. Accurate prediction results can improve the matching of microgrid energy storage capacity allocation. With the popularization of smart meters, the interaction between residential electricity demand and sources and networks is increasing, and massive data are generated at the same time. Previous forecasting methods suffer from poor targeting and high noise. They cannot make full use of the important information of the load data. This paper proposes a new framework for daily load forecasting of group residents. Firstly, we use the singular value decomposition to address the problem of high dimensions of residential electricity data. Meanwhile, we apply a K-Shape-based group residential load clustering method to obtain the typical residential load data. Secondly, we introduce an empirical mode decomposition method to address the problem of high noise of residential load data. Finally, we propose a Bi-LSTM-Attention model for residential daily load forecasting. This method can make full use of the contextual information and the important information of the daily load of group residents. The experiments conducted on a real data set of a power grid show that our method achieves excellent improvements on five prediction error indicators, such as MAPE, which are significantly smaller than the compared baseline methods.
Seabed Terrain-Aided Navigation Algorithm Based on Combining Artificial Bee Colony and Particle Swarm Optimization
Authors: Wang Dan , Liu Liqiang , Ben Yueyang , Dai Pingan , Wang Jiancheng
Published: January 2023

Position errors of inertial navigation systems (INS) increase over time after long-term voyages of the autonomous underwater vehicle. Terrain-aided navigation (TAN) can effectively reduce the accumulated error of the INS. However, traditional TAN algorithms require a long positioning time and need better positioning accuracy, and nonmatching and mismatching are prone to occur, especially when the initial position error is large. To solve this problem, a new algorithm combining the artificial bee colony (ABC) and particle swarm optimization (PSO) was proposed according to the principle of terrain matching, to improve the matching effect. Considering that PSO easily falls into a local optimum, the acceleration factor and inertia weight of PSO were improved. The improved PSO was called WAPSO. ABC was introduced based on WAPSO and could help WAPSO escape local optimum. The final algorithm was termed ABC search-based WAPSO (F-WAPSO). During the continuous iteration of particles, F-WAPSO seeks the optimal position for the particles. Simulation tests show that F-WAPSO can effectively improve the matching accuracy. When the initial position error is 1000 m, the matching error can be reduced to 93.5 m, with a matching time of only 13.7 s.
Performance Evaluation of Different Decision Fusion Approaches for Image Classification
Authors: Alwakeel Ahmed , Alwakeel Mohammed , Hijji Mohammad , Saleem Tausifa Jan , Zahra Syed Rameem
Published: January 2023

Image classification is one of the major data mining tasks in smart city applications. However, deploying classification models that have good generalization accuracy is highly crucial for reliable decision-making in such applications. One of the ways to achieve good generalization accuracy is through the use of multiple classifiers and the fusion of their decisions. This approach is known as “decision fusion”. The requirement for achieving good results with decision fusion is that there should be dissimilarity between the outputs of the classifiers. This paper proposes and evaluates two ways of attaining the aforementioned dissimilarity. One is using dissimilar classifiers with different architectures, and the other is using similar classifiers with similar architectures but trained with different batch sizes. The paper also compares a number of decision fusion strategies.
A Review of Recent Progress of Carbon Capture, Utilization, and Storage (CCUS) in China
Authors: Yao Jia , Han Hongdou , Yang Yang , Song Yiming , Li Guihe
Published: January 2023

The continuous temperature rise has raised global concerns about CO2 emissions. As the country with the largest CO2 emissions, China is facing the challenge of achieving large CO2 emission reductions (or even net-zero CO2 emissions) in a short period. With the strong support and encouragement of the Chinese government, technological breakthroughs and practical applications of carbon capture, utilization, and storage (CCUS) are being aggressively pursued, and some outstanding accomplishments have been realized. Based on the numerous information from a wide variety of sources including publications and news reports only available in Chinese, this paper highlights the latest CCUS progress in China after 2019 by providing an overview of known technologies and typical projects, aiming to provide theoretical and practical guidance for achieving net-zero CO2 emissions in the future.
Evaluation of the Quality of Practical Teaching of Agricultural Higher Vocational Courses Based on BP Neural Network
Authors: Kumar M. Guru Vimal , N Veena , Čepová Lenka , Raja M Arun Manicka , Balaram Allam , Elangovan Muniyandy
Published: January 2023

Agriculture is the backbone of any developing or developed country that makes any living to survive. To make food available throughout the year, it is necessary to know about agriculture and the work and strategies involved. Hence, agricultural courses have to be introduced to higher education students. Additionally, agriculture-related methods are available in many higher education institutions for longer. However, students and teachers will face difficulties in real-time practical classes during certain challenging circumstances. These situations require the teacher to utilize trending technologies to improve the teaching and learning process and to make it more manageable. In this study, for this process, a novel neural network-based recognition algorithm (NN-RA) is implemented that works similarly to a backpropagation neural network (BP-NN) to provide a practical agriculture course. The proposed BP-NN is compared with the existing NN-RA, I-SC, and I-VDT algorithms based on the data transfer and signal-to-noise ratio. From the results, it can be observed that the proposed BP-NN attains a higher accuracy in data transfer of 99%.
Modeling, Load Profile Validation, and Assessment of Solar-Rooftop Energy Potential for Low-and-Moderate-Income Communities in the Caribbean
Authors: Campo-Ossa Daniel D. , Vega Penagos Cesar A. , Garzon Oscar D. , Andrade Fabio
Published: January 2023

This document presents the modeling of load profile consumption for Low-and-Moderate-Income (LMI) communities in the Caribbean Islands, as well as an assessment of the solar-rooftop energy potential. In this work, real data, together with synthetic and electricity bill data, were collected to validate and improve the load profile models. The solar-rooftop energy potential was obtained through a National Renewable Energy Laboratory (NREL) software called the PVWatts calculator, and mathematical analysis. The analysis of rooftop solar energy potential was conducted to enable the minimum size of solar power systems to fit the energy demand in the community. The results obtained allow estimation of the capacity of the energy system for each house or an entire community.
In Vivo and In Vitro Accuracy Analysis of Static Computer-Assisted Implant Surgery in an Edentulous Patient
Authors: Makarov Nikolay , Papi Piero , Santomauro Vincenzo , Di Carlo Gabriele , Polimeni Antonella , Di Murro Bianca , Saccucci Matteo
Published: January 2023

Background: Recently, intraoral scanning (IOS) has been proposed as a new tool to evaluate the accuracy of static computer-assisted implant surgery (s-CAIS); however, further research is needed to improve the precision of IOS for full-arch impressions. The purpose of the study was to assess the accuracy of s-CAIS in an edentulous patient either in vivo or in vitro with two different evaluation techniques and to investigate if their results are comparable. Methods: A patient with terminal dentition was selected and four implants were placed using s-CAIS with a bone-supported stackable template. Segmentation used for designing a template was 3D printed, and then four implants were placed in the model following the same protocol as for s-CAIS. The model then underwent cone beam computed tomography (CBCT) and laboratory scanning to evaluate its accuracy. Data were uploaded to specific software, and accuracy values were automatically generated. Results: A statistical analysis was not attempted since all measurements were performed on the same patient and model. When descriptively comparing the accuracy of the two methods of treatment evaluation in the in vitro scenario, comparable results were obtained between IOS and CBCT, except for the angle. Conclusions: As the intraoral scanning procedure in fully edentulous patients is not yet clinically validated, utilizing CBCT can still be recommended for the accurate evaluation of computer-assisted implant placement.
Infrared Small and Moving Target Detection on Account of the Minimization of Non-Convex Spatial-Temporal Tensor Low-Rank Approximation under the Complex Background
Authors: Wang Kun , Jiang Defu , Yun Lijun , Liu Xiaoyang
Published: January 2023

Infrared point-target detection is one of the key technologies in infrared guidance systems. Due to the long observation distance, the point target is often submerged in the background clutter and large noise in the process of atmospheric transmission and scattering, and the signal-to-noise ratio is low. On the other hand, the target in the image appears in the form of fuzzy points, so that the target has no obvious features and texture information. Therefore, scholars have proposed many object detection methods for dimming infrared images, which has become a hot research topic on account of the flow-rank model based on the image patch. However, the result has a high false alarm rate because the most low-rank models based on the image patch do not consider the spatial-temporal characteristics of the infrared sequences. Therefore, we introduce 3D total variation (3D-TV) to regularize the foreground on account of the non-convex rank approximation minimization method, so as to consider the spatial-temporal continuity of the target and effectively suppress the interference caused by dynamic background and target movement on the foreground extraction. Finally, this paper proposes the minimization of the non-convex spatial-temporal tensor low-rank approximation algorithm (MNSTLA) by studying the related algorithms of the point infrared target detection, and the experimental results show strong robustness and a low false alarm rate for the proposed method compared with other advanced algorithms, such as NARM, RIPT, and WSNMSTIPT.
An Analysis of the Reaction of Frogbit (Hydrocharis morsus-ranae L.) to Cadmium Contamination with a View to Its Use in the Phytoremediation of Water Bodies
Authors: Gałczyńska Małgorzata , Gamrat Renata , Ciemniak Artur
Published: January 2023

Macrophytes play an important role in assessing the condition of aquatic ecosystems. The aim of the study was to assess the effectiveness of cadmium uptake by frogbit (Hydrocharis morsus-ranae) for the phytoremediation of aquatic ecosystems. The study examined cadmium (Cd) uptake by frogbit grown under conditions of low and high fertilizer dose and three cadmium dose levels over three- and six-week exposure times. Cadmium uptake was found to be influenced by water reactivity, mineral nutrient abundance, and exposure time. Its accumulation in frogbit is hence a good bioindicator of cadmium pollution in water bodies. Where the plant had greater access to phosphorus, nitrogen, potassium (PNK) compounds, i.e., high fertilizer level, a higher pH level (7.6) was associated with increased cadmium uptake and decreased plant biomass. A higher PNK level was also associated with greater tolerance to cadmium, while at lower PNK levels, more efficient cadmium uptake was noted after three weeks. Hydrocharis morsus-ranae can be used for water and wastewater treatment in the final stage of phytoremediation, but in combination with other species of pleustophytes that represent different biosorption sites.
Thermodynamics of Hydrogen Storage: Equilibrium Study of Liquid Organic Hydrogen Carrier System 1-Methylindole/octahydro-1-methylindole
Authors: Vostrikov Sergey V. , Konnova Maria E. , Turovtsev Vladimir V. , Müller Karsten , Bara Jason E. , Verevkin Sergey P.
Published: January 2023

Methylated indoles could be potentially interesting components for hydrogen (H2) storage based on the Liquid Organic Hydrogen Carrier (LOHC) approach. It is likely that the methylated forms will preserve the beneficial thermochemical characteristics of indole compared to homocyclic LOHCs. At the same time, 1-methyl-indole is expected to have a higher stability than indole in the reactive cycle of hydrogenation and dehydrogenation. This study investigates whether the expectations regarding reaction thermodynamics and stability are justified. To this end, the chemical equilibria of the hydrogenation (+H2)/dehydrogenation (−H2) reactions of the indole/octahydroindole LOHC system was determined experimentally over a wide range of temperature, pressure, and hydrogen:feedstock ratio. Reaction thermodynamics were calculated from the relationship between temperature and equilibrium constant. In addition, the formation enthalpies of the species involved in the reaction have been determined experimentally utilizing combustion calorimetry. Further validation has been achieved using high-level quantum chemical methods. The evaluation confirms both hypotheses: (1) 1-methyl-indole exhibits less decomposition during reaction as is the case for the indole system. Hence, an improved stability of methylated LOHC molecules can be concluded; (2) The enthalpy of reaction for H2 release from octahydro-1-methyl-indole is estimated from the equilibrium experiments and calorimetric measurements to be about +55.6 kJ mol(H2)−1 for reaction in the liquid phase at standard conditions. This is comparable to the values observed for octahydro-indole.
Significant Increases in Wet Nighttime and Daytime–Nighttime Compound Heat Waves in China from 1961 to 2020
Authors: Chen Xi
Published: January 2023

Heat waves (HWs) with high humidity are dangerous to human health. However, existing studies on different types of HWs considering the effect of humidity are still limited. This study defines three types of wet summer HWs (that is, wet independent daytime and nighttime HWs and wet daytime-nighttime compound HWs) and investigates their spatial-temporal changes across China during 1961–2020. Results show significant upward trends of wet nighttime and compound HWs in terms of frequency, occurring days, duration, intensity and spatial extent, while changes for wet daytime HWs are weak and insignificant in nearly all sub-regions of China except for southwest and eastern northwest China. Compared with wet compound and daytime HWs, wet nighttime HWs accompanied by more elevated relative humidity exhibit larger growth rates in frequency, occurring days, duration and affected areas. Additionally, most wet nighttime and compound HWs with the longest duration and/or the maximum intensity are found to occur after the mid-1990s, compared to fewer than half for wet daytime HWs. Our findings emphasize the prominent intensifying trends in wet nighttime HWs across China for the last 60 years, and suggest more efforts on exploring humid HWs.
Direct Electrical Sensing of Iodine Gas by a Covalent Organic Framework-Based Sensor
Authors: Zhou Wanshuang , Kang Chun , Yu Cong , Cui Zhaojie , Wang Xinbo
Published: January 2023

Rapid and highly sensitive detection of iodine gaseous species is crucial as the first response in case of nuclear accidents and nuclear waste clean-up. A robust and user-friendly sensor-based technology that allows online monitoring is highly desirable. Herein, we report the success of using a covalent organic framework (AQ-COF)-based sensor for real-time iodine gas adsorption and detection by the electrochemical impedance spectroscopy (EIS) technique. The sensor exhibits a high sensitivity and a pronounced electrical response to trace amounts of iodine vapor. Gaseous iodine was readily detected with a significant change in resistance (104×) at 70 °C within 5 min exposure to air. Notably, the EIS response is quite chemoselective to iodine over other common species such as air, methanol, ethanol, and water, with a selectivity of 320, 14, 49, and 1030, respectively. A mechanical study shows that the adsorption of iodine can reduce the optical bandgap of the AQ-COF, causing the impedance to drop significantly. This study demonstrates how the adsorption enrichment effect of selective I2 adsorption by a covalent organic framework can be leveraged to create a highly selective sensor for the direct online electrical detection of radioactive gaseous toxins.
Production of Biocoal from Wastewater Sludge and Sugarcane Bagasse: A Review
Authors: Mkhwanazi Zinhle , Isa Yusuf Makarfi , Vallabh Shadana. T.
Published: January 2023

The rising volume of wastewater sludge and sugarcane bagasse is becoming a prominent concern globally. Furthermore, the growing demand for fuel coupled with the depletion of fossil fuel reserves in South Africa demonstrates the need for alternative energy sources. To minimize the reliance on fossil-based energy sources, a renewable resource such as biomass can be optimized as an energy source. Wastewater sludge and bagasse have the energy potential to produce high-calorific-value biocoal; this will contribute to the supply of energy in South Africa. The synthesis of biocoal from wastewater sludge and bagasse through an artificial synthetic coal production process, i.e., hydrothermal carbonization (HTC), is preferred over other thermal conversion techniques as HTC is capable of handling feed having a high (75–90%) moisture content. This article focuses on the production of biocoal from wastewater sludge and sugarcane bagasse as an alternative to sustainable bioenergy supply and as one of the potential solutions for reducing net CO2 greenhouse gas (GHG) emissions from fossil-fuel power plants, and addresses the use of different thermochemical technologies, previous studies on the composition of wastewater sludge and bagasse, and the benefits of hydrothermal carbonization.
Intraseasonal Oscillation Features of the Two Types of Persistent High Temperature Events over Jiangnan Region
Authors: Li Yan , Gao Qingjiu , You Qi , Yue Yuanbo
Published: January 2023

In order to find potential low-frequency signals and provide new ideas for extended-range forecasting, the intraseasonal oscillation (ISO) characteristics of persistent high temperature events (PHTEs) in the extended summer in Jiangnan area are explored by using daily maximum air temperature (Tmax) data from the China Meteorological Data Network and daily reanalysis data provided by NCEP/DOE. The results show that the low-frequency PHTEs can be classified into three types according to the position variation of the Western Pacific subtropical high (WPSH). For the first two types of PHTEs, a southwestward migrating mid-latitude wave train from the North American coast to the central and eastern China can be clearly seen in the whole troposphere. Whereas the two types of PHTEs show different features in the low-latitude. It is found that a significantly westward extension of the WPSH during the first type of PHTEs, with the low-frequency anticyclone moving westward in the mid-lower troposphere. For the second type of PHTEs, the WPSH is mainly located in the southeastern China with slightly movement. Analysis of the low-frequency vertical circulation and the thermodynamic equation further reveal that the increase of temperature in Jiangnan region is primarily attributed to the descending airflow.
Analysis of Finite Solution Spaces of Second-Order ODE with Dirac Delta Periodic Forcing
Authors: Bagchi Susmit
Published: January 2023

Second-order Ordinary Differential Equations (ODEs) with discontinuous forcing have numerous applications in engineering and computational sciences. The analysis of the solution spaces of non-homogeneous ODEs is difficult due to the complexities in multidimensional systems, with multiple discontinuous variables present in forcing functions. Numerical solutions are often prone to failures in the presence of discontinuities. Algebraic decompositions are employed for analysis in such cases, assuming that regularities exist, operators are present in Banach (solution) spaces, and there is finite measurability. This paper proposes a generalized, finite-dimensional algebraic analysis of the solution spaces of second-order ODEs equipped with periodic Dirac delta forcing. The proposed algebraic analysis establishes the conditions for the convergence of responses within the solution spaces without requiring relative smoothness of the forcing functions. The Lipschitz regularizations and Lebesgue measurability are not considered as preconditions maintaining generality. The analysis shows that smooth and locally finite responses can be admitted in an exponentially stable solution space. The numerical analysis of the solution spaces is computed based on combinatorial changes in coefficients. It exhibits a set of locally uniform responses in the solution spaces. In contrast, the global response profiles show localized as well as oriented instabilities at specific neighborhoods in the solution spaces. Furthermore, the bands of the expansions–contractions of the stable response profiles are observable within the solution spaces depending upon the values of the coefficients and time intervals. The application aspects and distinguishing properties of the proposed approaches are outlined in brief.
Analysis of the Mitogenomes of Two Helotid Species Provides New Insights into the Phylogenetic Relationship of the Basal Cucujoidea (Insecta: Coleoptera)
Authors: Liu Jing , Yang Yuhang , Yan Zihan , Wang Haishan , Bai Ming , Shi Chengmin , Li Jing
Published: January 2023

Helotid beetles are commonly found in places where sap flows from tree trunks and in crevices in bark. The Helotidae family is a rare and primitive group of Cucujoidea. To date, no complete mitochondrial (mt) genome has been sequenced for this family. To better understand the characteristics of the mt genome and the evolution of Cucujoidea, we sequenced and annotated the complete mt genomes of Helota thoracica (Ritsema, 1895) and Helota yehi Lee, 2017 using next-generation sequencing. These are the first record of Helotidae mt genomes. The RNA secondary structures of both species were also predicted in this study. The mt genomes of H. thoracica and H. yehi are circular, with total lengths of 16,112 bp and 16,401 bp, respectively. After comparing the mt genomes of H. thoracica and H. yehi, we observed the gene arrangement, codon usage patterns, base content, and RNA secondary structures of both species to be similar, which has also been noted in other Coleoptera insects. The nucleotide sequence of the coding regions and the control region has small differences. The phylogenetic analysis indicated that Helotidae and Protocucujidae are sister groups and revealed the relationship between seven families; however, the validity of the two series (Erotylid series and Nitidulid series) as larger groups in the superfamily was not supported. The mt phylogenomic relationships have strong statistical support. Therefore, the division of Cucujoidea into series should be re-examined. Our results will provide a better understanding of the mt genome and phylogeny of Helotidae and Cucujoidea and will provide valuable molecular markers for further genetic studies.
Charge Transport across Proteins inside Proteins: Tunneling across Encapsulin Protein Cages and the Effect of Cargo Proteins
Authors: Zinelli Riccardo , Soni Saurabh , Cornelissen Jeroen J. L. M. , Michel-Souzy Sandra , Nijhuis Christian A.
Published: January 2023

Charge transport across proteins can be surprisingly efficient over long distances—so-called long-range tunneling—but it is still unclear as to why and under which conditions (e.g., presence of co-factors, type of cargo) the long-range tunneling regime can be accessed. This paper describes molecular tunneling junctions based on an encapsulin (Enc), which is a large protein cage with a diameter of 24 nm that can be loaded with various types of (small) proteins, also referred to as “cargo”. We demonstrate with dynamic light scattering, transmission electron microscopy, and atomic force microscopy that Enc, with and without cargo, can be made stable in solution and immobilized on metal electrodes without aggregation. We investigated the electronic properties of Enc in EGaIn-based tunnel junctions (EGaIn = eutectic alloy of Ga and In that is widely used to contact (bio)molecular monolayers) by measuring the current density for a large range of applied bias of ±2.5 V. The encapsulated cargo has an important effect on the electrical properties of the junctions. The measured current densities are higher for junctions with Enc loaded with redox-active cargo (ferritin-like protein) than those junctions without cargo or redox-inactive cargo (green fluorescent protein). These findings open the door to charge transport studies across complex biomolecular hierarchical structures.
Microfluidic Gut-on-a-Chip: Fundamentals and Challenges
Authors: Thomas Dimple Palanilkunnathil , Zhang Jun , Nguyen Nam-Trung , Ta Hang Thu
Published: January 2023

The human gut is responsible for food digestion and absorption. Recently, growing evidence has shown its vital role in the proper functioning of other organs. Advances in microfluidic technologies have made a significant impact on the biomedical field. Specifically, organ-on-a-chip technology (OoC), which has become a popular substitute for animal models, is capable of imitating complex systems in vitro and has been used to study pathology and pharmacology. Over the past decade, reviews published focused more on the applications and prospects of gut-on-a-chip (GOC) technology, but the challenges and solutions to these limitations were often overlooked. In this review, we cover the physiology of the human gut and review the engineering approaches of GOC. Fundamentals of GOC models including materials and fabrication, cell types, stimuli and gut microbiota are thoroughly reviewed. We discuss the present GOC model applications, challenges, possible solutions and prospects for the GOC models and technology.
Ketamine as Add-On Treatment in Psychotic Treatment-Resistant Depression
Authors: Gałuszko-Węgielnik Maria , Chmielewska Zuzanna , Jakuszkowiak-Wojten Katarzyna , Wiglusz Mariusz S. , Cubała Wiesław J.
Published: January 2023

Psychotic treatment-resistant depression is a complex and challenging manifestation of mood disorders in the clinical setting. Psychotic depression is a subtype of major depressive disorder characterized by mood-consistent hallucinations and/or delusions. Psychotic depression is often underdiagnosed and undertreated. Ketamine appears to have rapid and potent antidepressant effects in clinical studies, and the Federal Drug Agency approved the use of ketamine enantiomer esketamine-nasal spray for treatment-resistant depression pharmacotherapy in 2019. This study aimed to assess the usage of ketamine for major depressive disorder with psychotic features as an add-on treatment to the standard of care. Here we present four inpatients suffering from treatment-resistant depression with psychotic features, including one with severe suicidal crisis, all treated with 0.5 mg/kg intravenous infusion of ketamine. Subsequent monitoring revealed no exacerbation of psychotic symptoms in short and long-term observation, while stable remission was observed in all cases with imminent antisuicidal effect. Results suggest ketamine may benefit individuals with treatment-resistant depression with psychotic features.
Altered Functional Connectivity Density in Type 2 Diabetes Mellitus with and without Mild Cognitive Impairment
Authors: Zhang Dongsheng , Liu Shasha , Huang Yang , Gao Jie , Liu Weirui , Liu Wanting , Ai Kai , Lei Xiaoyan , Zhang Xiaoling
Published: January 2023

Although disturbed functional connectivity is known to be a factor influencing cognitive impairment, the neuropathological mechanisms underlying the cognitive impairment caused by type 2 diabetes mellitus (T2DM) remain unclear. To characterize the neural mechanisms underlying T2DM-related brain damage, we explored the altered functional architecture patterns in different cognitive states in T2DM patients. Thirty-seven T2DM patients with normal cognitive function (DMCN), 40 T2DM patients with mild cognitive impairment (MCI) (DMCI), and 40 healthy controls underwent neuropsychological assessments and resting-state functional MRI examinations. Functional connectivity density (FCD) analysis was performed, and the relationship between abnormal FCD and clinical/cognitive variables was assessed. The regions showing abnormal FCD in T2DM patients were mainly located in the temporal lobe and cerebellum, but the abnormal functional architecture was more extensive in DMCI patients. Moreover, in comparison with the DMCN group, DMCI patients showed reduced long-range FCD in the left superior temporal gyrus (STG), which was correlated with the Rey auditory verbal learning test score in all T2DM patients. Thus, DMCI patients show functional architecture abnormalities in more brain regions involved in higher-level cognitive function (executive function and auditory memory function), and the left STG may be involved in the neuropathology of auditory memory in T2DM patients. These findings provide some new insights into understanding the neural mechanisms underlying T2DM-related cognitive impairment.
Using the AraBERT Model for Customer Satisfaction Classification of Telecom Sectors in Saudi Arabia
Authors: Aftan Sulaiman , Shah Habib
Published: January 2023

Customer satisfaction and loyalty are essential for every business. Feedback prediction and social media classification are crucial and play a key role in accurately identifying customer satisfaction. This paper presents sentiment analysis-based customer feedback prediction based on Twitter Arabic datasets of telecommunications companies in Saudi Arabia. The human brain, which contains billions of neurons, provides feedback based on the current and past experience provided by the services and other related stakeholders. Artificial Intelligent (AI) based methods, parallel to human brain processing methods such as Deep Learning (DL) algorithms, are famous for classifying and analyzing such datasets. Comparing the Arabic Dataset to English, it is pretty challenging for typical methods to outperform in the classification or prediction tasks. Therefore, the Arabic Bidirectional Encoder Representations from Transformers (AraBERT) model was used and analyzed with various parameters such as activation functions and topologies and simulated customer satisfaction prediction takes using Arabic Twitter datasets. The prediction results were compared with two famous DL algorithms: Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). Results show that these methods have been successfully applied and obtained highly accurate classification results. AraBERT achieved the best prediction accuracy among the three ML methods, especially with Mobily and STC datasets.
Factors Associated with University Students’ Deterioration from Subthreshold Depression to Depression before and during the COVID-19 Pandemic
Authors: Takagaki Koki , Yokoyama Satoshi
Published: January 2023

COVID-19 has exposed university students to high-stress situations, and the percentage of individuals with depressive symptoms was high during the COVID-19 pandemic. Furthermore, subthreshold depression carries a risk for the subsequent development of major depressive disorder (MDD). During the COVID-19 pandemic, we examined whether differences exist between university students who deteriorated from subthreshold depression to MDD and those who remained stable or improved. Four hundred seventeen participants completed all the measures twice over a one-year interval. One hundred twenty-three participants met the criteria for subthreshold depression at Time 1. One year later, 42 participants no longer met the criteria for subthreshold depression, 68 participants maintained the criteria for subthreshold depression, and 13 participants met the criteria for MDD. We conducted two-way repeated measures ANOVA to examine the differences between those who deteriorated from subthreshold depression to MDD and those who did not. The study results suggest that avoidance behavior is associated with the development of MDD from subthreshold depression. Additionally, the study showed that experiencing isolation relates to MDD onset. Therefore, we should monitor avoidance behavior and isolation in pandemic conditions. Consequently, attention to avoidance behavior and isolation may be important; however, further research is required.
Urban–Spatial Analysis of European Historical Railway Stations: Qualitative Assessment of Significant Cases
Authors: Martínez-Corral Aurora , Cárcel-Carrasco Javier , Fonseca Fabiola Colmenero , Kannampallil Flora Francis
Published: January 2023

This perspective analysis aims to show the most recent and relevant interventions in a representative sample of selected European railway stations, balancing different criteria by reviewing the most characteristic cases. We analyse its impact at the urban level, assessing whether there is urban regeneration and to what extent; its impact at a functional level, assessing the change in activity as well as the effect on the user, transfer, or dismantling of the railway activity; its impact at an architectural level, assessing whether the actions are global or merely at the level of facade. As a final reflection, we outline the issue of the possibility of reuse in historical railway stations associating it with heritage preservation. The proposed selection contemplates actions in small and large stations and locations; total, partial, and zero dismantling actions in the tracks or the station plot and, finally, new uses ranging from the mixed solution of railway activity and shopping centre to cultural or exclusively leisure solutions. The timeline covers approximately the last three decades (1985–2022).
Efficiency of an Improved Grouted Corrugated Duct (GCD) Connection Design for Precast Concrete Bridge Pier: Numerical and Parametric Study
Authors: Wang Zhiqiang , Wu Chengjun , Qu Hongya , Xiao Wei
Published: January 2023

In this study, finite element analysis (FEA) has been conducted for an improved grouted corrugated duct (GCD) connection design with a reserved recess in bridge footing. This study aims to understand the damage progression mechanism and to evaluate the contribution of each component in the improved GCD connection design. Numerical model based on the experimental results are first created, validated and calibrated. It is found that the confining effect (support and friction force) provided by recess sidewall keeps the connection in good integrity. It also prevents early deformation and early development of transverse cracks along the connection interface, which further avoids the damage concentration at connection joint, transfers the plastic hinge region. Parametric study is then carried out by considering different recess depths, cushion thicknesses, recess diameters, and mortar strengths. The effect of recess details on mechanical behavior is thus studied. Recess depth can be designed as 6–20% of the column section size to ensure a higher upper limit of overall strength and ductility, and it also influences the stress distribution area of the joint local. The stiffness and strength of recess control the local damage, while has limited impact on the overall performance. In addition, preliminary suggestions on the GCD design of recess depth, thickness of mortar cushion, recess diameter, the strength of mortar are proposed.
Digital Form Generation of Heritages in Historical District Based on Plan Typology and Shape Grammar: Case Study on Kulangsu Islet
Authors: Zhang Kehan , Zhang Na , Quan Fengmei , Li Yuan , Wang Shaosen
Published: January 2023

Architectural heritage in historic districts, as a complex type of heritage, encompasses both the uniqueness of the building itself and also shows cultural and regional characteristics as a group, especially for the heritage site that contains multi-culture features. The digitalization research of this type of heritage often focuses on the digital archiving and modeling of heritages but rarely considers the combination of culture analysis and digitalization. This paper develops a digital form generation method for the heritages in historical districts by means of typological plan analysis, the Shape Grammar method, and Grasshopper software. Based on the case study of the modern Western-style house on Kulangsu, a world heritage site and historical district, this paper include three results: (1) dividing the layout plans of Kulangsu modern Western-style houses into three types, that is, native prototypes, foreign prototypes, and mixed prototypes, with 39 sub-types in total; (2) establishing shape grammar for the layout plans of Kulangsu modern Western-style houses with shape grammar sets and “S, L, R, I” expression rules; (3) creating a digital form generation method based on shape grammar result by Grasshopper software, including function cluster creation, function cluster connection and final model generation. This paper presents an example of quantitative analysis of heritage culture and a rapid modeling method of heritage, providing a reference for the construction of a heritage culture database and digital heritage management in historic districts.
Experimental and Numerical Investigation of an Innovative 3DPC Thin-Shell Structure
Authors: Du Wenfeng , Zhu Liming , Zhang Hao , Zhou Zhiyong , Wang Kewei , Uddin Nasim
Published: January 2023

The development and application of new Fiber Reinforced Polymer (FRP) material and 3D printing construction technology provide a basis for making up for the shortcomings of traditional thin-shell structures and building new thin-shell structures with better performance. In this paper, a new 3D Printing Composite (3DPC) thin-shell structure is proposed, which is prepared using a FRP plate as a permanent base mold and combining it with 3D printing cement technology. Both the typical experiment and finite element numerical simulation analysis of the 3DPC thin-shell structure are carried out. The results show that the maximum load capacity of the 3DPC thin-shell structure is increased by 53.3% as compared with the corresponding traditional concrete thin-shell structure. The presence of the FRP sheet effectively delays the generation of initial cracks and enhances the ductility of components.
Experimental and Theoretical Investigation of Viscoelastic Damper by Applying Fractional Derivative Method and Internal Variable Theory
Authors: Xu Yeshou , He Qi , Guo Ying-Qing , Huang Xing-Huai , Dong Yao-Rong , Hu Zhong-Wei , Kim Jinkoo
Published: January 2023

Viscoelastic dampers are conventional passive vibration control devices with excellent energy dissipation performance. The fractional derivative has a simple form and high accuracy in the modelling of viscoelastic materials/dampers. The internal variables reflect the internal state evolution of materials, and are often used to analyze the deformation and thermal process of materials. In the present work, the mechanical properties of a plate-shear-type viscoelastic damper at room temperature are tested under sinusoidal displacement excitations. The impacts of frequency and displacement amplitude on the dynamic properties of the viscoelastic damper in a wide frequency domain (0.1–25 Hz) are investigated. The higher-order fractional derivative model and the temperature–frequency equivalent principle are employed to characterize the frequency and temperature influence, and the internal variable theory considering the internal/microscale structure evolutions is introduced to capture the displacement affection. The higher-order fractional derivative model modified with the internal variable theory and temperature–frequency equivalent principle (ITHF) is accurate enough in describing the dynamic behaviors of viscoelastic dampers with varying frequencies and displacement amplitudes.
New Method for Solving the Inverse Thermal Conduction Problem (θ-Scheme Combined with CG Method under Strong Wolfe Line Search)
Authors: Djeffal Rachid , Lalmi Djemoui , El Amine Bekkouche Sidi Mohammed , Bechouat Tahar , Younsi Zohir
Published: January 2023

Most thermal researchers have solved thermal conduction problems (inverse or direct) using several different methods. These include the usual discretization methods, conventional and special estimation methods, in addition to simple synchronous gradient methods such as finite elements, including finite and special quantitative methods. Quantities found through the finite difference methods, i.e., explicit, implicit or Crank–Nicolson scheme method, have also been adopted. These methods offer many disadvantages, depending on the different cases; when the solutions converge, limited range stability conditions. Accordingly, in this paper, a new general outline of the thermal conduction phenomenon, called (θ-scheme), as well as a gradient conjugate method that includes strong Wolfe conditions has been used. This approach is the most useful, both because of its accuracy (16 decimal points of importance) and the speed of its solutions and convergence; by addressing unfavorable adverse problems and stability conditions, it can also have wide applications. In this paper, we applied two approaches for the control of the boundary conditions: constant and variable. The θ-scheme method has rarely been used in the thermal field, though it is unconditionally more stable for θ∈ [0.5, 1]. The simulation was carried out using Matlab software.
Study on Summer Overheating of Residential Buildings in the Severe Cold Region of China in View of Climate Change
Authors: Yu Yang , Shao Yu , Zhao Bolun , Yu Jiahui , Guo Haibo , Chen Yang
Published: January 2023

Due to global warming, the overheating risk in the severe cold region of China has attracted attention, but so far, no studies have examined summer overheating in this region. This paper aims to reveal the overheating risk in recent and future climates in the severe cold region of China. An 18-storey residential building in the severe cold region of China was monitored from May to September 2021 to validate the simulation data of the indoor temperature. Weather files of the typical meteorological year (TMY) from 2007 to 2020, observations in 2021, and forecasts for the climate in different carbon emission scenarios (2030, 2060) were used to simulate the indoor temperature and assess the overheating risk. The results revealed the severity of the overheating risk; the overheating hours in the south-facing bedroom were recorded as 884 h (24.07%) with the TMY weather data and 1043 h (28.40%) in 2030 and 1719 h (46.81%) in 2060 under the RCP8.5 carbon emission scenario. Thus, the low carbon emissions policy may significantly alleviate overheating. Moreover, to cope with climate change, it is suggested that the Chinese local design standards should consider the summer overheating risk and make the necessary adjustments.
Effect of Combining the Aggregate Grading with Cementitious Composition on Mechanical Properties of Ultra-High Performance Concrete
Authors: Chu Vinh Thi Hai , Bui Vinh Duc , Nguyen Tue Viet
Published: January 2023

Ultra-High Performance Concrete (UHPC) improves the bearing capacity as well as the durability of structural concrete. This study aims to investigate the constituents of UHPC in both phases: aggregate and cementitious materials. The proper ratio of the mixture was chosen based on combining an aggregate gradation of quartz sand and crushed stone. In addition, the compressive strength of the hardened cement paste was investigated to achieve the optimal ratio of silica powder and blast furnace slag. The combination of aggregate (quartz sand and crushed stone) and cement paste (cement, silica fume, silica powder, and blast furnace slag) showed ultra-high performance. The compressive strength of UHPC reached 135.74 MPa at 7 days, corresponding to 90% of 28 days’ strength (150.98 MPa). The results of the present study provide a new mixture-proportioning for UHPC with economic efficiency. Moreover, the use of slag enhances concrete performance and reduces the negative environmental impact.
Mechanisms of Acquired Resistance and Tolerance to EGFR Targeted Therapy in Non-Small Cell Lung Cancer
Authors: Chhouri Houssein , Alexandre David , Grumolato Luca
Published: January 2023

Non-small cell lung cancers (NSCLC) harboring activating mutations of the epidermal growth factor receptor (EGFR) are treated with specific tyrosine kinase inhibitors (EGFR-TKIs) of this receptor, resulting in clinically responses that can generally last several months. Unfortunately, EGFR-targeted therapy also favors the emergence of drug tolerant or resistant cells, ultimately resulting in tumor relapse. Recently, cellular barcoding strategies have arisen as a powerful tool to investigate the clonal evolution of these subpopulations in response to anti-cancer drugs. In this review, we provide an overview of the currently available treatment options for NSCLC, focusing on EGFR targeted therapy, and discuss the common mechanisms of resistance to EGFR-TKIs. We also review the characteristics of drug-tolerant persister (DTP) cells and the mechanistic basis of drug tolerance in EGFR-mutant NSCLC. Lastly, we address how cellular barcoding can be applied to investigate the response and the behavior of DTP cells upon EGFR-TKI treatment.
Relative Risk of Bladder and Kidney Cancer in Lynch Syndrome: Systematic Review and Meta-Analysis
Authors: Nassour Anthony-Joe , Jain Anika , Hui Nicholas , Siopis George , Symons James , Woo Henry
Published: January 2023

Background: The association between Lynch syndrome (LS) and a higher risk of upper tract urothelial carcinoma is well established, but its effect on the risk of bladder and kidney cancers remains controversial. This review aimed to compare the relative risk (RR) of bladder and kidney cancer in confirmed LS germline mutation carriers compared to the general population. Methods: Medline, Embase, Cochrane Central, and Google Scholar were searched on 14 July 2022 for studies published in English that reported on the rates of urological cancer in adults with confirmed LS germline mutation. The quality of included studies was assessed using Cochrane’s tool to evaluate risk of bias in cohort studies. Random effects meta-analysis estimated the pooled relative risk of bladder and kidney cancer in LS carriers compared to the general population. The quality of the overall evidence was evaluated using GRADE. Results: Of the 1839 records identified, 5 studies involving 7120 participants from 3 continents were included. Overall, LS carriers had a statistically significantly higher RR of developing bladder cancer (RR: 7.48, 95% CI: 3.70, 15.13) and kidney cancer (RR: 3.97, 95% CI: 1.23, 12.81) compared to unaffected participants (p < 0.01). The quality of the evidence was assessed as “low” due to the inclusion of cohort studies, the substantial heterogeneity, and moderate-to-high risk of bias. Conclusion: Lynch syndrome is associated with a significant increase in the relative risk of kidney and bladder cancer. Clinicians should adopt a lower threshold for germline mutation genetic testing in individuals who present with bladder cancer. Further studies evaluating the role and cost-effectiveness of novel urine-based laboratory tests are needed. High-quality studies in histologically proven renal cell carcinoma and their underlying germline mutations are necessary to strengthen the association with LS.