bluuebunny/crossref_metadata_2025 huggingface dataset:
Genome-wide analysis of UDP-glycosyltransferases family and identification of UGT genes involved in drought stress of Platycodon grandiflorus
Authors: Chen Bowen , Wang Xinrui , Yu Hanwen , Dong Nan , Li Jing , Chang Xiangwei , Wang Jutao , Jiang Chao , Liu Juan , Chi Xiulian , Zha Liangping , Gui Shuangying
Published: April 2024

Introduction

The uridine diphosphate (UDP)-glycosyltransferase (UGT) family is the largest glycosyltransferase family, which is involved in the biosynthesis of natural plant products and response to abiotic stress. UGT has been studied in many medicinal plants, but there are few reports on Platycodon grandiflorus. This study is devoted to genome-wide analysis of UGT family and identification of UGT genes involved in drought stress of Platycodon grandiflorus (PgUGTs).

Methods

The genome data of Platycodon grandiflorus was used for genome-wide identification of PgUGTs, online website and bioinformatics analysis software was used to conduct bioinformatics analysis of PgUGT genes and the genes highly responsive to drought stress were screened out by qRT-PCR, these genes were cloned and conducted bioinformatics analysis.

Results

A total of 75 PgUGT genes were identified in P.grandiflorus genome and clustered into 14 subgroups. The PgUGTs were distributed on nine chromosomes, containing multiple cis-acting elements and 22 pairs of duplicate genes were identified. Protein-protein interaction analysis was performed to predict the interaction between PgUGT proteins. Additionally, six genes were upregulated after 3d under drought stress and three genes (PGrchr09G0563, PGrchr06G0523, PGrchr06G1266) responded significantly to drought stress, as confirmed by qRT-PCR. This was especially true for PGrchr06G1266, the expression of which increased 16.21-fold after 3d of treatment. We cloned and conducted bioinformatics analysis of three candidate genes, both of which contained conserved motifs and several cis-acting elements related to stress response, PGrchr06G1266 contained the most elements.

Discussion

PgGT1 was confirmed to catalyze the C-3 position of platycodin D and only eight amino acids showed differences between gene PGr008G1527 and PgGT1, which means PGr008G1527 may be able to catalyze the C-3 position of platycodin D in the same manner as PgGT1. Seven genes were highly expressed in the roots, stems, and leaves, these genes may play important roles in the development of the roots, stems, and leaves of P. grandiflorus. Three genes were highly responsive to drought stress, among which the expression of PGrchr06G1266 was increased 16.21-fold after 3d of drought stress treatment, indicating that PGrchr06G1266 plays an important role in drought stress tolerance. To summarize, this study laied the foundation to better understand the molecular bases of responses to drought stress and the biosynthesis of platycodin.
Do the elderly and those with comorbid chronic physical conditions have improved access to outpatient psychotherapy post structural reforms in Germany? Results of the ES-RiP study
Authors: Jedamzik Johanna , Kampling Hanna , Christoffer Andrea , Szardenings Carsten , Heuft Gereon , Friederich Hans-Christoph , Kruse Johannes
Published: April 2024

Background

In 2017, a reform of the German outpatient psychotherapy guideline was carried out, aiming to reduce waiting times and facilitate low-threshold access. This study analyzes the extent to which the implementation of the two new service elements ‘psychotherapeutic consultation times’ and ‘acute short-term psychotherapeutic interventions’ improved psychotherapeutic care for patients with mental disorders and chronic physical conditions (cMPs), for patients with mental disorders without chronic physical conditions (MnoP), and elderly patients.

Methods

In a quantitative secondary analysis, we analyzed health insurance data of patients with psychotherapy billing codes obtained from the National Association of Statutory Health Insurance Physicians (KBV) for the years 2015-2019, evaluating descriptive statistical parameters for specific patient groups and care services.

Results

Between 2015 and 2019, the number of mentally ill receiving psychotherapy at least once in the corresponding year increased by 30.7%. Among these, the proportion of cMPs-patients increased from 26.8% to 28.2% (+1.4%), while that of MnoP-patients decreased from 68.3% to 66.4% (-1.9%). The number of elderly people receiving treatment also increased.

Conclusion

Since increases and decreases in the percentage shares occur evenly over the years investigated, it is questionable whether the reform in 2017 has had a direct influence on these changes.

Study registration

ID DRKS00020344, URL: https://www.bfarm.de/DE/Das-BfArM/Aufgaben/Deutsches-Register-Klinischer-Studien/_node.html.
Assessing interstate racial and socioeconomic disparities in newborn screening policies in the United States
Authors: Bedford Shanaya , Vachuska Karl
Published: April 2024

Introduction

This paper explores racial and socioeconomic disparities in newborn screening (NBS) policies across the United States. While inter-state inequality in healthcare policies is often considered a meaningful source of systemic inequity in healthcare outcomes, to the best of our knowledge, no research has explored racial and socioeconomic disparities in newborn screening policies based on state of residence.

Methods

We investigate these disparities by calculating weighted average exposure to specific NBS tests by racial and socioeconomic group. We additionally estimate count models of the number (and type) of NBS conditions screened for by state racial and socioeconomic composition.

Results

Adding to the knowledge base that social determinants of health and health disparities are linked, our analysis surprisingly reveals little evidence of substantial inter-state inequity in newborn screenings along racial and socioeconomic lines.

Discussion

While there is substantial nationwide racial and socioeconomic inequity in terms of infant health, the distribution of state-level policies does not appear to be structured in a manner to be a driver of these disparities. Our findings suggest that efforts to reduce inequities in outcomes related to NBS should shift focus toward the delivery of screening results and follow-up care as discussion builds on expanding NBS to include more conditions and genomic testing.
Widening Educational Inequalities in Physical Health Due to the Obesity Trend?—A Mediation Analysis Using the German Socio-Economic Panel Study
Authors: Sperlich Stefanie , Beller Johannes , Safieddine Batoul , Tetzlaff Juliane , Geyer Siegfried
Published: April 2024

Objectives:

This study examined the contribution of obesity to the development of educational inequalities in physical health.

Methods:

We used data from the German Socio-Economic Panel for the period 2002–2020. Physical health was measured with the modified SF12-questionnaire. Logistic regression analyses were applied to estimate time trends. The Relative Index of Inequality (RII) and the Slope Index of Inequality (SII) were calculated to examine educational inequalities. The role of obesity as a mediator was analyzed using the Karlson-Holm-Breen (KHB) method.

Results:

Over time, educational inequalities in obesity as well as impaired physical health widened in men and women, particularly among those aged 30–49 years. For individuals with a low level of education at this age, the probability of impaired physical health increased significantly by 7.7%-points in women and 9.4%-points in men. Of this increase, 25.9% for women and 14.8% for men could be attributed to the increase in obesity.

Conclusion:

Our findings suggest that the steeper rise in obesity among individuals with a low level of education partly explains the observed widening in educational inequalities in physical health.
CentralBark Image Dataset and Tree Species Classification Using Deep Learning
Authors: Warner Charles , Wu Fanyou , Gazo Rado , Benes Bedrich , Kong Nicole , Fei Songlin
Published: April 2024

The task of tree species classification through deep learning has been challenging for the forestry community, and the lack of standardized datasets has hindered further progress. Our work presents a solution in the form of a large bark image dataset called CentralBark, which enhances the deep learning-based tree species classification. Additionally, we have laid out an efficient and repeatable data collection protocol to assist future works in an organized manner. The dataset contains images of 25 central hardwood and Appalachian region tree species, with over 19,000 images of varying diameters, light, and moisture conditions. We tested 25 species: elm, oak, American basswood, American beech, American elm, American sycamore, bitternut hickory, black cherry, black locust, black oak, black walnut, eastern cottonwood, hackberry, honey locust, northern red oak, Ohio buckeye, Osage-orange, pignut hickory, sassafras, shagbark hickory silver maple, slippery elm, sugar maple, sweetgum, white ash, white oak, and yellow poplar. Our experiment involved testing three different models to assess the feasibility of species classification using unaltered and uncropped images during the species-classification training process. We achieved an overall accuracy of 83.21% using the EfficientNet-b3 model, which was the best of the three models (EfficientNet-b3, ResNet-50, and MobileNet-V3-small), and an average accuracy of 80.23%.
Application of Evolutionary Computation to the Optimization of Biodiesel Mixtures Using a Nature-Inspired Adaptive Genetic Algorithm
Authors: Vasileiadis Vasileios , Kyriklidis Christos , Karayannis Vayos , Tsanaktsidis Constantinos
Published: April 2024

The present research work introduces a novel mixture optimization methodology for biodiesel fuels using an Evolutionary Computation method inspired by biological evolution. Specifically, the optimal biodiesel composition is deduced from the application of a nature-inspired adaptive genetic algorithm that first examines percentages of the ingredients in the optimal mixtures. The innovative approach’s effectiveness lies in problem simulation with improvements in the evaluation of the specific function and the way to define and tune the genetic algorithm. Environmental imperatives in the era of climate change currently impose the optimized production of alternative environmentally friendly biofuels to replace fossil fuels. Biodiesel in particular, appears to be more attractive in recent years, as it originates from renewable bio-derived resources. The main ingredients of the specific biofuel mixture investigated in this research are diesel and biodiesel (100% from bioresources). The assessment of the new biodiesel examined was performed using a fitness function that estimated both the density and cost of the fuel. Beyond the evaluation criterion of cost, density also influences the suitability of this biofuel for commercial use and market sale. The outcomes from the modeling process can be beneficial in saving cost and time for new biodiesel production by using this novel decision-making tool in comparison with randomized laboratory experimentations.
Algorithm Based on Morphological Operators for Shortness Path Planning
Authors: Perez-Ramos Jorge L. , Ramirez-Rosales Selene , Canton-Enriquez Daniel , Diaz-Jimenez Luis A. , Xicotencatl-Ramirez Gabriela , Herrera-Navarro Ana M. , Jimenez-Hernandez Hugo
Published: April 2024

The problem of finding the best path trajectory in a graph is highly complex due to its combinatorial nature, making it difficult to solve. Standard search algorithms focus on selecting the best path trajectory by introducing constraints to estimate a suitable solution, but this approach may overlook potentially better alternatives. Despite the number of restrictions and variables in path planning, no solution minimizes the computational resources used to reach the goal. To address this issue, a framework is proposed to compute the best trajectory in a graph by introducing the mathematical morphology concept. The framework builds a lattice over the graph space using mathematical morphology operators. The searching algorithm creates a metric space by applying the morphological covering operator to the graph and weighing the cost of traveling across the lattice. Ultimately, the cumulative traveling criterion creates the optimal path trajectory by selecting the minima/maxima cost. A test is introduced to validate the framework’s functionality, and a sample application is presented to validate its usefulness. The application uses the structure of the avenues as a graph. It proposes a computable approach to find the most suitable paths from a given start and destination reference. The results confirm that this is a generalized graph search framework based on morphological operators that can be compared to the Dijkstra approach.
Synesth: Comprehensive Syntenic Reconciliation with Unsampled Lineages
Authors: Delabre Mattéo , El-Mabrouk Nadia
Published: April 2024

We present Synesth, the most comprehensive and flexible tool for tree reconciliation that allows for events on syntenies (i.e., on sets of multiple genes), including duplications, transfers, fissions, and transient events going through unsampled species. This model allows for building histories that explicate the inconsistencies between a synteny tree and its associated species tree. We examine the combinatorial properties of this extended reconciliation model and study various associated parsimony problems. First, the infinite set of explicatory histories is reduced to a finite but exponential set of Pareto-optimal histories (in terms of counts of each event type), then to a polynomial set of Pareto-optimal event count vectors, and this eventually ends with minimum event cost histories given an event cost function. An inductive characterization of the solution space using different algebras for each granularity leads to efficient dynamic programming algorithms, ultimately ending with an O(mn) time complexity algorithm for computing the cost of a minimum-cost history (m and n: number of nodes in the input synteny and species trees). This time complexity matches that of the fastest known algorithms for classical gene reconciliation with transfers. We show how Synesth can be applied to infer Pareto-optimal evolutionary scenarios for CRISPR-Cas systems in a set of bacterial genomes.
A Spacecraft Onboard Autonomous Task Scheduling Method Based on Hierarchical Task Network-Timeline
Authors: Zhang Junwei , Lyu Liangqing
Published: April 2024

To address the inherent challenges of deep space exploration, such as communication delays and the unpredictability of spacecraft environments, this study focuses on enhancing spacecraft adaptability and autonomy, which are essential for Autonomous Space Scientific Exploration. A pivotal aspect of this endeavor is the advancement of spacecraft task scheduling, which is integral to increasing spacecraft autonomy. Current research in this domain predominantly revolves around mission timing planning and is primarily executed from ground stations. However, these plans often lack the granularity required for direct implementation by spacecraft. In response, our study proposes an innovative approach to augment spacecraft autonomy, introducing a method that articulately describes mission objectives and resource information. We designed a novel hierarchical task network-timeline (HTN-T) algorithm, an amalgamation of the HTN scheduling method and the distinctive elements of existing research. This algorithm addresses time constraints through horizontal and vertical expansions, building upon the resolution of logical constraints found in conventional planning methods. Furthermore, it introduces a priority-based strategy for resolving resource conflicts in spacecraft tasks. This algorithm is substantiated through validation, including proof-of-principle demonstrations and assessments within a Space–ground Collaborative Management and Control System encompassing both ground and spacecraft operations. The findings indicate that our proposed algorithm achieves high rates of scheduling success and operational efficiency within a feasible timeframe, thus effectively navigating the complexities of autonomous spacecraft task scheduling.
Electric Vehicle Battery Disassembly Using Interfacing Toolbox for Robotic Arms
Authors: Rastegarpanah Alireza , Mineo Carmelo , Contreras Cesar Alan , Aflakian Ali , Paragliola Giovanni , Stolkin Rustam
Published: April 2024

This paper showcases the integration of the Interfacing Toolbox for Robotic Arms (ITRA) with our newly developed hybrid Visual Servoing (VS) methods to automate the disassembly of electric vehicle batteries, thereby advancing sustainability and fostering a circular economy. ITRA enhances collaboration between industrial robotic arms, server computers, sensors, and actuators, meeting the intricate demands of robotic disassembly, including the essential real-time tracking of components and robotic arms. We demonstrate the effectiveness of our hybrid VS approach, combined with ITRA, in the context of Electric Vehicle (EV) battery disassembly across two robotic testbeds. The first employs a KUKA KR10 robot for precision tasks, while the second utilizes a KUKA KR500 for operations needing higher payload capacity. Conducted in T1 (Manual Reduced Velocity) mode, our experiments underscore a swift communication protocol that links low-level and high-level control systems, thus enabling rapid object detection and tracking. This allows for the efficient completion of disassembly tasks, such as removing the EV battery’s top case in 27 s and disassembling a stack of modules in 32 s. The demonstrated success of our framework highlights its extensive applicability in robotic manufacturing sectors that demand precision and adaptability, including medical robotics, extreme environments, aerospace, and construction.
Long Non-Coding RNAs as Determinants of Thyroid Cancer Phenotypes: Investigating Differential Gene Expression Patterns and Novel Biomarker Discovery
Authors: DeSouza Nicole R. , Jarboe Tara , Carnazza Michelle , Quaranto Danielle , Islam Humayun K. , Tiwari Raj K. , Geliebter Jan
Published: April 2024

Thyroid Cancer (TC) is the most common endocrine malignancy, with increasing incidence globally. Papillary thyroid cancer (PTC), a differentiated form of TC, accounts for approximately 90% of TC and occurs predominantly in women of childbearing age. Although responsive to current treatments, recurrence of PTC by middle age is common and is much more refractive to treatment. Undifferentiated TC, particularly anaplastic thyroid cancer (ATC), is the most aggressive TC subtype, characterized by it being resistant and unresponsive to all therapeutic and surgical interventions. Further, ATC is one of the most aggressive and lethal malignancies across all cancer types. Despite the differences in therapeutic needs in differentiated vs. undifferentiated TC subtypes, there is a critical unmet need for the identification of molecular biomarkers that can aid in early diagnosis, prognosis, and actionable therapeutic targets for intervention. Advances in the field of cancer genomics have enabled for the elucidation of differential gene expression patterns between tumors and healthy tissue. A novel category of molecules, known as non-coding RNAs, can themselves be differentially expressed, and extensively contribute to the up- and downregulation of protein coding genes, serving as master orchestrators of regulated and dysregulated gene expression patterns. These non-coding RNAs have been identified for their roles in driving carcinogenic patterns at various stages of tumor development and have become attractive targets for study. The identification of specific genes that are differentially expressed can give insight into mechanisms that drive carcinogenic patterns, filling the gaps of deciphering molecular and cellular processes that modulate TC subtypes, outside of well-known driver mutations.
Cloning and Functional Analysis of CsROP5 and CsROP10 Genes Involved in Cucumber Resistance to Corynespora cassiicola
Authors: Yu Guangchao , Jia Lian , Yu Ning , Feng Miao , Qu Yue
Published: April 2024

The cloning of resistance-related genes CsROP5/CsROP10 and the analysis of their mechanism of action provide a theoretical basis for the development of molecular breeding of disease-resistant cucumbers. The structure domains of two Rho-related guanosine triphosphatases from plant (ROP) genes were systematically analyzed using the bioinformatics method in cucumber plants, and the genes CsROP5 (Cucsa.322750) and CsROP10 (Cucsa.197080) were cloned. The functions of the two genes were analyzed using reverse-transcription quantitative PCR (RT-qPCR), virus-induced gene silencing (VIGS), transient overexpression, cucumber genetic transformation, and histochemical staining technology. The conserved elements of the CsROP5/CsROP10 proteins include five sequence motifs (G1-G5), a recognition site for serine/threonine kinases, and a hypervariable region (HVR). The knockdown of CsROP10 through VIGS affected the transcript levels of ABA-signaling-pathway-related genes (CsPYL, CsPP2Cs, CsSnRK2s, and CsABI5), ROS-signaling-pathway-related genes (CsRBOHD and CsRBOHF), and defense-related genes (CsPR2 and CsPR3), thereby improving cucumber resistance to Corynespora cassiicola. Meanwhile, inhibiting the expression of CsROP5 regulated the expression levels of ROS-signaling-pathway-related genes (CsRBOHD and CsRBOHF) and defense-related genes (CsPR2 and CsPR3), thereby enhancing the resistance of cucumber to C. cassiicola. Overall, CsROP5 and CsROP10 may participate in cucumber resistance to C. cassiicola through the ROS and ABA signaling pathways.
Trajectory Tracking Control of Variable Sweep Aircraft Based on Reinforcement Learning
Authors: Cao Rui , Lu Kelin
Published: April 2024

An incremental deep deterministic policy gradient (IDDPG) algorithm is devised for the trajectory tracking control of a four-wing variable sweep (FWVS) aircraft with uncertainty. The IDDPG algorithm employs the line-of-sight (LOS) method for path tracking, formulates a reward function based on position and attitude errors, and integrates long short-term memory (LSTM) units into IDDPG algorithm to enhance its adaptability to environmental changes during flight. Finally, environmental disturbance factors are introduced in simulation to validate the designed controller’s ability to track climbing trajectories of morphing aircraft in the presence of uncertainty.
Biped Gait Stability Classification Based on the Predicted Step Viability
Authors: Parik-Americano Pedro , Igual Jorge , Driemeier Larissa , Becman Eric Cito , Forner-Cordero Arturo
Published: April 2024

In this paper, we address the challenge of ensuring stability in bipedal walking robots and exoskeletons. We explore the feasibility of real-time implementation for the Predicted Step Viability algorithm (PSV), a complex multi-step optimization criterion for planning future steps in bipedal gait. To overcome the high computational cost of the PSV algorithm, we performed an analysis using 11 classification algorithms and a stacking strategy to predict if a step will be stable or not. We generated three datasets of increasing complexity through PSV simulations to evaluate the classification performance. Among the classifiers, k Nearest Neighbors, Support Vector Machine with Radial Basis Function Kernel, Decision Tree, and Random Forest exhibited superior performance. Multi-Layer Perceptron also consistently performed well, while linear-based algorithms showed lower performance. Importantly, the use of stacking did not significantly improve performance. Our results suggest that the feature vector applied with this approach is applicable across various robotic models and datasets, provided that training data is balanced and sufficient points are used. Notably, by leveraging classifiers, we achieved rapid computation of results in less than 1 ms, with minimal computational cost.
Influence of Immediate Dentin Sealing on Bond Strength of Resin-Based CAD/CAM Restoratives to Dentin: A Systematic Review of In Vitro Studies
Authors: Antoniou Iliana , Mourouzis Petros , Dionysopoulos Dimitrios , Pandoleon Panagiotis , Tolidis Kosmas
Published: April 2024

Immediate dentin sealing (IDS) is a method of improving the bond strength of indirect dental restorative materials to dentin and belongs to the biomimetic protocols of contemporary dentistry. The purpose of this systematic review was to evaluate the effect of IDS on the bond strength of resin-based CAD/CAM materials to dentin. PubMed and MEDLINE, Scopus, and the Web of Science were searched by two individual researchers, namely for studies that have been published in English between 1 January 2005 and 31 December 2023 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The inclusion criteria encompassed articles related to in vitro studies, measuring the bond strength through microtensile bond strength (μ-TBS), micro-shear bond strength (μ-SBS), tensile bond strength (TBS) or shear bond strength (SBS) tests after the use of the IDS technique. The included restorative materials comprised resin-based CAD/CAM materials bonded to dentin. A total of 1821 studies were identified, of which 7 met the inclusion criteria. A meta-analysis was not deemed appropriate due to the high level of diversity inthe publications and techniques. The use of IDS yielded higher bond strength outcomesin various experimental conditions and resin-based CAD/CAM materials. Overall, IDS in CAD/CAM restorations may contribute to better clinical outcomesand improved restoration longevity due to this property.
Surface Thermodynamic Properties of Poly Lactic Acid by Inverse Gas Chromatography
Authors: Hamieh Tayssir
Published: April 2024

Poly lactic acid (PLA) is one of the most commonly used bio-derived thermoplastic polymers in 3D and 4D printing applications. The determination of PLA surface properties is of capital importance in 3D/4D printing technology. The surface thermodynamic properties of PLA polymers were determined using the inverse gas chromatography (IGC) technique at infinite dilution. The determination of the retention volume of polar and non-polar molecules adsorbed on the PLA particles filling the column allowed us to obtain the dispersive, polar, and Lewis’s acid–base surface properties at different temperatures from 40 °C to 100 °C. The applied surface method was based on our recent model that used the London dispersion equation, the new chromatographic parameter function of the deformation polarizability, and the harmonic mean of the ionization energies of the PLA polymer and organic molecules. The application of this new method led to the determination of the dispersive and polar free surface energy of the adsorption of molecules on the polymeric material, as well as the glass transition and the Lewis acid–base constants. Four interval temperatures were distinguished, showing four zones of variations in the surface properties of PLA as a function of the temperature before and after the glass transition. The acid–base parameters of PLA strongly depend on the temperature. The accurate determination of the dispersive and polar surface physicochemical properties of PLA led to the work of adhesion of the polar organic solvents adsorbed on PLA. These results can be very useful for achieving reliable and functional 3D and 4D printed components.
A Multi-Objective Optimization Problem Solving Method Based on Improved Golden Jackal Optimization Algorithm and Its Application
Authors: Jiang Shijie , Yue Yinggao , Chen Changzu , Chen Yaodan , Cao Li
Published: April 2024

The traditional golden jackal optimization algorithm (GJO) has slow convergence speed, insufficient accuracy, and weakened optimization ability in the process of finding the optimal solution. At the same time, it is easy to fall into local extremes and other limitations. In this paper, a novel golden jackal optimization algorithm (SCMGJO) combining sine–cosine and Cauchy mutation is proposed. On one hand, tent mapping reverse learning is introduced in population initialization, and sine and cosine strategies are introduced in the update of prey positions, which enhances the global exploration ability of the algorithm. On the other hand, the introduction of Cauchy mutation for perturbation and update of the optimal solution effectively improves the algorithm’s ability to obtain the optimal solution. Through the optimization experiment of 23 benchmark test functions, the results show that the SCMGJO algorithm performs well in convergence speed and accuracy. In addition, the stretching/compression spring design problem, three-bar truss design problem, and unmanned aerial vehicle path planning problem are introduced for verification. The experimental results prove that the SCMGJO algorithm has superior performance compared with other intelligent optimization algorithms and verify its application ability in engineering applications.
Parental Educational Expectations and Academic Achievement of Left-Behind Children in China: The Mediating Role of Parental Involvement
Authors: Li Jian , Xue Eryong , You Huiyuan
Published: April 2024

Migrant workers from rural China often leave their children at home to be raised by grandparents or other family members. This study explored the relationship between parents’ educational expectations, parental involvement, and the academic performance of left-behind children in China. A total of 19,487 student samples were obtained from the China Education Panel Survey (CEPS), and 5078 of these met the criteria for being considered as ‘left behind’ children. Results indicated: (1) a significant positive correlation between parents’ educational expectations and left-behind children’s academic achievement; (2) parental education involvement plays a partial mediating role between parents’ educational expectations and left-behind children’s academic performance; (3) a significant negative correlation between parental intellectual involvement and educational expectations of left-behind children; (4) parental management involvement was not significantly correlated with parents’ educational expectations and left-behind children’s academic performance; and (5) a significant positive correlation between parental emotional involvement and educational expectations of left-behind children. The findings highlight the important role of parental educational expectations and have implications for the improvement of educational outcomes in China.
Learning in Deep Radial Basis Function Networks
Authors: Wurzberger Fabian , Schwenker Friedhelm
Published: April 2024

Learning in neural networks with locally-tuned neuron models such as radial Basis Function (RBF) networks is often seen as instable, in particular when multi-layered architectures are used. Furthermore, universal approximation theorems for single-layered RBF networks are very well established; therefore, deeper architectures are theoretically not required. Consequently, RBFs are mostly used in a single-layered manner. However, deep neural networks have proven their effectiveness on many different tasks. In this paper, we show that deeper RBF architectures with multiple radial basis function layers can be designed together with efficient learning schemes. We introduce an initialization scheme for deep RBF networks based on k-means clustering and covariance estimation. We further show how to make use of convolutions to speed up the calculation of the Mahalanobis distance in a partially connected way, which is similar to the convolutional neural networks (CNNs). Finally, we evaluate our approach on image classification as well as speech emotion recognition tasks. Our results show that deep RBF networks perform very well, with comparable results to other deep neural network types, such as CNNs.
Phase Space Spin-Entropy
Authors: Geiger Davi
Published: April 2024

Quantum physics is intrinsically probabilistic, where the Born rule yields the probabilities associated with a state that deterministically evolves. The entropy of a quantum state quantifies the amount of randomness (or information loss) of such a state. The degrees of freedom of a quantum state are position and spin. We focus on the spin degree of freedom and elucidate the spin-entropy. Then, we present some of its properties and show how entanglement increases spin-entropy. A dynamic model for the time evolution of spin-entropy concludes the paper.
Research on Multi-Objective Optimization Design of University Student Center in China Based on Low Energy Consumption and Thermal Comfort
Authors: Liu Ming , Que Yufei , Yang Nanxin , Yan Chongyi , Liu Qibo
Published: April 2024

Ensuring optimal building performance is vital for enhancing student activity comfort and fostering energy-saving initiatives toward low-carbon objectives. This paper focuses on university student centers in China, aiming to diminish building energy consumption while enhancing indoor thermal comfort. Parametric modeling of typical cases is executed using the Grasshopper 1.0.0007 software package, and the simulation of building energy consumption and indoor thermal comfort relies on the Ladybug and Honeybee plug-in. Employing a multi-objective optimization design method and the Octopus multi-objective optimization algorithm, this study integrates numerical simulations and on-site surveys to analyze how factors like building form, orientation, envelope structure, and others impact the indoor and outdoor environment. A comprehensive optimization design approach is implemented for the building’s exterior components, including the walls, windows, roof, and shading system. After conducting a comparative analysis of the annual comprehensive energy consumption and indoor thermal comfort before and after the optimization plan, it is determined that implementing these measures reduces the annual comprehensive energy consumption of the building under study by 58.8% and extends the duration of indoor thermal comfort by 53.0%. This study presents a practical optimization design methodology for university student center architecture in China, aiding architects in decision making and advocating for energy-efficient building designs.
Industrial Waste Heat Utilization in the European Union—An Engineering-Centric Review
Authors: Turek Vojtěch , Kilkovský Bohuslav , Daxner Ján , Babička Fialová Dominika , Jegla Zdeněk
Published: April 2024

The efficient utilization of waste heat from industrial processes can provide a significant source of energy savings for production plants, as well as be a driver of sustainable operations and the abatement of emissions. Industrial waste heat usually is contained in liquid or gaseous outlet streams. Although the possible ways to utilize waste heat are discussed in a wide variety of papers, these either provide only a general overview of utilization options and opportunities or focus on a narrow range of industrial processes. The aim of the present paper is to discuss the practical aspects of waste heat utilization in the European Union so that the reader can gain perspective on (i) the thermal classification of waste heat, (ii) liquid and gaseous waste streams and their typical temperatures for industrial use cases, (iii) the technical, economic, physical, and environmental aspects barring full utilization of the available waste heat, (iv) waste heat sources in various industries, and (v) standardized equipment and technologies applicable to industrial waste heat utilization, including their advantages, disadvantages, and weak points.
Optimizing Solar Heating for Thangka Exhibition Halls: A Case Study in Malkang Cultural Village
Authors: Han Wenyang , Bai Yan , Du Miao , Tao Yujie , Zhang Yin , Yang Qianru
Published: April 2024

With the continuous development of rural revitalization and urbanization in China, the sustainable transformation of traditional rural architecture has become increasingly important. This study takes the Thangka exhibition hall in rural Malkang, Sichuan Province, as the research object and proposes a Thangka exhibition hall architectural design centered around solar heating and aiming for near-zero energy consumption. The research method involves establishing a solar energy system model on the roof of the exhibition hall and utilizing solar angle and area calculation formulas along with simulation software to calculate the optimal installation angle and area of solar panels, with the aim of achieving indoor temperatures that meet Thangka protection requirements while achieving zero-energy heating. Preliminary results indicate that this solar-centric near-zero energy architectural design can effectively promote the increase in indoor temperature through solar thermal conversion. Additionally, through calculation and simulation, the optimal installation angle for the solar panels achieving zero-energy heating is determined to be 24.25 with an azimuth angle of −1.2. The optimum installation area for solar panels is 8.2 square meters in the showroom and 2.7 square meters in the storeroom. Among these, the solar panel area for the Thangka exhibition hall constitutes 4.12% of the total area and is required for maintaining Thangka protection temperature requirements throughout the year, while the solar panel area for the storage room constitutes 1.88% and is also needed for the same purpose. Studying the optimal installation angle and area of solar panels can transform the exhibition hall into a near-zero-energy building, meeting the temperature requirements for Thangka preservation and human thermal comfort, while also achieving optimal economic benefits. This provides guidance and a reference for promoting near-zero-energy buildings in rural areas.
Dynamics Power Quality Cost Assessment Based on a Gradient Descent Method
Authors: Zhang Jingyi , Sheng Tongtian , Gu Pan , Yu Miao , Yan Jiaxin , Sun Jianqun , Liu Shanhe
Published: April 2024

The escalating demand for power load is increasingly prone to triggering power quality (PQ) issues, leading to severe economic losses. Aiming at reducing the economic losses, this paper focuses on the coordinated relationship between PQ and economic costs. Firstly, a multilayer multiple linear stepwise regression method is employed to screen PQ indicators, identifying harmonic and voltage deviation as the primary influencing factors of PQ. Secondly, a gradient descent optimization algorithm based on the Least Absolute Shrinkage and Selection Operator (LASSO) is proposed, enabling rapid computation of the minimum PQ cost. Finally, through validations of two case studies, the results confirm that the proposed method can rapidly calculate the minimum PQ cost based on real-time load demands, enabling the dynamic adjustment of PQ cost to meet the evolving needs of power system development.
Research on Optimal Operation of Power Generation and Consumption for Enterprises with Captive Power Plants Participating in Power Grid Supply–Demand Regulation
Authors: Liu Hangming , Zhao Huirong , Yang Jincheng , Peng Daogang
Published: April 2024

Wind and solar power curtailment and the difficulty of peak regulation are issues that urgently need to be addressed in the process of China’s new electric power system. Enterprises with captive power plants (ECPPs) are large-capacity power consumers and producers, with significant optimization and adjustment potential on both the supply and demand sides. This paper aims to promote the active participation of ECPPs in grid supply–demand regulation and proposes an optimization model for the power generation and consumption of ECPPs based on a day-ahead, intra-day two-stage dispatching model. First, targeting demand response scenarios, mathematical models for analyzing the potential of ECPPs to participate in power grid supply–demand regulation are proposed. Then, an optimization model for ECPP generation and consumption with load regulation is established, and a two-stage dispatching model is proposed to fully mobilize the regulation flexibility of ECPPs. Finally, a robust dispatching model considering price uncertainty is established based on information gap decision theory. The case results show that ECPPs can reduce the curtailment rate in a region by approximately 9%, alleviate the peak pressure of the power grid, reduce carbon emissions by 1373.55 tons, and promote low-carbon development for themselves. Meanwhile, considering price uncertainty strengthens the risk resistance capability of ECPPs and provides a basis for their willingness to participate in supply–demand regulation.
Enhancing the Efficiency of Rotary Thermal Propulsion Systems
Authors: Shen Xuankun , Costall Aaron W.
Published: April 2024

Transport electrification is essential for reducing CO2 emissions, and technologies such as hybrid and range-extended electric vehicles will play a crucial transitional role. Such vehicles employ an internal combustion engine for on-board chemical energy conversion. The Wankel rotary engine should be an excellent candidate for this purpose, offering a high power-to-weight ratio, simplicity, compactness, perfect balance, and low cost. Until recently, however, it has not been in production in the automotive market, due, in part, to relatively low combustion efficiency and high fuel consumption and unburnt hydrocarbon emissions, which can be traced to constraints on flame speed, an elongated combustion chamber, and relatively low compression ratios. This work used large eddy simulations to study the in-chamber flow in a peripherally ported 225cc Wankel rotary engine, providing insight into these limitations. Flow structures created during the intake phase play a key role in turbulence production but the presence of the pinch point inherent to Wankel engine combustion chambers inhibits flame propagation. Two efficiency-enhancement technologies are introduced as disruptive solutions: (i) pre-chamber jet ignition and (ii) a two-stage rotary engine. These concepts overcome the traditional efficiency limitations and show that the Wankel rotary engine design can be further enhanced for its role as a range extender in electrified vehicles.
Charge Carrier Formation following Energy Gap Law in Photo-Activated Organic Materials for Efficient Solar Cells
Authors: Rana Aniket , Vashistha Nikita , Kumar Amit , Kumar Mahesh , Singh Rajiv K.
Published: April 2024

The charge carrier formation and transport in the pristine polymers as well as in the polymer–fullerene blend is still a hot topic of discussion for the scientific community. In the present work, the carrier generation in some prominent organic molecules has been studied through ultrafast transient absorption spectroscopy. The identification of the exciton and polaron lifetimes of these polymers has led to device performance-related understanding. In the Energy Gap Law, the slope of the linear fit gradient (γ) of lifetimes vs. bandgap are subjected to the geometrical rearrangements experienced by the polymers during the non-radiative decay from the excited state to the ground state. The value of gradient (γ) for excitons and polarons is found to be −1.1 eV−1 and 1.14 eV−1, respectively. It suggests that the exciton decay to the ground state is likely to involve a high distortion in polymer equilibrium geometry. This observation supports the basis of Stokes shift found in the conjugated polymers due to the high disorder. It provides the possible reasons for the substantial variation in the exciton lifetime. As the bandgap becomes larger, exciton decay rate tends to reduce due to the weak attraction between the holes in the HUMO and electron in the LUMO. The precise inverse action is observed for the polymer–fullerene blend, as the decay of polaron tends to increase as the bandgap of polymer increases.
The Reliability and Profitability of Virtual Power Plant with Short-Term Power Market Trading and Non-Spinning Reserve Diesel Generator
Authors: Nadimi Reza , Takahashi Masahito , Tokimatsu Koji , Goto Mika
Published: April 2024

This study examines the profitability and reliability of a virtual power plant (VPP) with the existence of a diesel genset (DG) in the day-ahead (DA) and intra-day (ID) power markets. The study’s unique contribution lies in integrating the VPP system with non-spinning reserve DG while limiting the DG operation via minimum running time and maximum number of switching times (on/off) per day. This contribution decreases the renewables’ uncertainty and increases the VPP’s reliability. Moreover, the study proposes an optimization model as a decision-making support tool for power market participants to choose the most profitable short-term market. The proposed model suggests choosing the DA market in 62% of time (from 579 days) based on estimated VPP power supply, and market prices. Even though there is uncertainty about VPP power supply and market prices, the division between the plan and actual profits is 1.8 × 106 Japanese yen [JPY] per day on average. The share of surplus power sold from the mentioned gap is 5.5%, which implies the opportunity cost of inaccurate weather forecasting. The results also show that the reliability of the VPP system in the presence of a DG increases from 64.9% to 66.2% for 14 h and mitigates the loss of power load by 1.3%.
Illumina Sequencing and Metabolomic Analysis Explored the Effects of the Mixed Silage of Rice Straw and Chinese Cabbage Waste on Fecal Microorganisms and Metabolites in Hu Sheep
Authors: Li Chuang , Lu Zhiqi , Qi Ruxin , Zhang Zhenbin , Lu Yue , Zafar Muhammad Hammad , Yang Kailun , Wang Mengzhi
Published: April 2024

Silage is the most important component of a ruminant diet and has important production and health significance in ruminant production. The aim of the research was to investigate how the mixed silage of Chinese cabbage waste and rice straw (mixed silage) impacts the fecal microorganisms and metabolites in Hu sheep using Illumina sequencing and metabolomic analysis. A total of 16 Hu sheep (8 rams and 8 ewes) weighing about 39 kg and 5.5 months old were used as experimental sheep and divided into two groups (4 rams and 4 ewes, n = 8) using the principle of randomized trials: the control group with peanut sprouts, corn husks, and sorghum husks as roughage and the silage group with the mixed silage as roughage. There were no significant differences in the average daily gain (ADG), dry matter intake (DMI), or feed conversion rate (FCR) between the control group and the mixed silage groups (p > 0.05). Microbiome results showed that 15 microorganisms such as Ruminococcaceae UCG 010, Breznakia, Erysipelothrix, Desulfovibrio, Succiniclasticum, and Shuttleworthia were significantly different between the two groups. In addition, metabolomics showed that the mixed silage modulated the concentrations and metabolic pathways of metabolites in the manure. Significantly different metabolites were mainly enriched in amino acid anabolism (“glycine, serine, and threonine metabolism”, “valine, leucine, and isoleucine biosynthesis”, “arginine biosynthesis”, etc.), nucleic acid metabolism (pyrimidine metabolism). In conclusion, the addition of mixed silage to the diet of Hu sheep can alter the structure of the hindgut microflora and regulate the metabolism of amino acids and nucleotides, which affects health performance.