bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of multi-dimensional environmental knowledge on residents' waste sorting intention: Moderating effect of environmental concern
Authors: He Zhihua , Liu Yong , Liu Xiaochun , Wang Feng , Zhu Huijia
Published: November 2022

With the rapid increase in household waste, environmental degradation becomes more serious. It is imperative to promote waste sorting in China. This study proposes an extended KAB model to explore the impact mechanism of different dimensions of subjective environmental knowledge on urban residents' waste sorting intention. The study also explores the moderating role of environmental concern in the relationship between three types of subjective environmental knowledge and attitude toward waste sorting. Based on 308 valid questionnaires, through structural equation model, multiple regression analysis, and simple slope test, we found that system knowledge, action-related knowledge, and effectiveness knowledge all have positive impacts on residents' attitudes toward waste sorting, and effectiveness knowledge has the most significant impact. Meanwhile, environmental concern positively moderates the relationship between system knowledge, effectiveness knowledge, and attitude toward waste sorting. This study makes an important theoretical contribution to enrich the existing literature on residents' waste sorting behavior and provides theoretical insights for governmental waste sorting policy formulation at the practical level.
When combining injunctive and descriptive norms strengthens the hypocrisy effect: A test in the field of discrimination
Authors: Mauduy Maxime , Priolo Daniel , Margas Nicolas , Sénémeaud Cécile
Published: November 2022

The induced-hypocrisy is a paradigm in which people promote a normative behavior (normative salience step) and then recall their past transgressions (transgression salience step). It is an effective two-step procedure for encouraging prosocial behaviors. This study aims to explore whether discrimination can be reduced using the hypocrisy paradigm combining two kinds of social norms, namely injunctive and descriptive norms. We assigned 80 participants to descriptive norm-related hypocrisy, injunctive norm-related hypocrisy, combined-norm hypocrisy, and control conditions. Results showed that intention to adopt active normative behaviors was higher in the combined-norms than in the single norm hypocrisy conditions. We observed the same pattern in reducing discriminatory behaviors in the Cyberball game, which measures passive discrimination (exclusion). Our findings have both practical and theoretical implications. First, they provide a new and effective means for producing behavioral changes in the field of discrimination. Second, they contribute to further investigating the explanatory processes underlying the hypocrisy effect.
Remote PEERS® for preschoolers: A pilot parent-mediated social skills intervention for young children with social challenges over telehealth
Authors: Factor Reina S. , Glass Leila , Baertschi Daliah , Laugeson Elizabeth A.
Published: November 2022

Introduction

Social differences characteristic of autism spectrum disorder (ASD) and other developmental disabilities are evident in early childhood and are associated with later difficulties. Unfortunately, there is a paucity of evidence-based interventions explicitly targeting social skills development for young children, few actively integrate parents and caregivers, and even fewer have remote models. The importance of providing accessible, tailored services for families in the wake of the COVID-19 pandemic, prompted the creation of a parent-mediated telehealth version of Program for the Education and Enrichment of Relational Skills (PEERS®) for Preschoolers (P4P), a pre-existing, evidence-based social skills intervention for children 4–6 years focused on making and keeping friends.

Method

This methodological paper documents the implementation, feasibility, and satisfaction of a novel telehealth group-based delivery of P4P.

Results

Qualitative results indicate acceptable feasibility and satisfaction. Additionally, following completion there was an increase in parental confidence in social coaching and increased use of child social skills.

Discussion

Future work will evaluate quantitative outcomes and comparisons between delivery methods (e.g., telehealth vs. in-person).
Spike protein of SARS-CoV-2 Omicron variant: An in-silico study evaluating spike interactions and immune evasion
Authors: Jimenez Ruiz Jose A. , Lopez Ramirez Cecilia , Lopez-Campos Jose Luis
Published: November 2022

Background

The fundamentals of the infectivity and immune evasion of the SARS-CoV-2 Omicron variant are not yet fully understood. Here, we carried out an in-silico study analyzing the spike protein, the protein electrostatic potential, and the potential immune evasion.

Methods

The analysis was based on the structure of the spike protein from two SARS-CoV-2 variants, the original Wuhan and the Botswana (Omicron). The full-length genome sequences and protein sequences were obtained from databanks. The interaction of the spike proteins with the human Angiotensin Converting Enzyme 2 (ACE2) receptor was evaluated through the open-source software. The Immune Epitope Database was used to analyze the potential immune evasion of the viruses.

Results

Our data show that the Omicron spike protein resulted in 37 amino acid changes. The physicochemical properties of the spike had changed, and the electrostatic potentials differed between both variants. This resulted in a decrease in protein interactions, which does not establish a greater interaction with the ACE2 receptor. These changes compromise key receptor-binding motif residues in the SARS-CoV-2 spike protein that interact with neutralizing antibodies and ACE2.

Conclusions

These mutations appear to confer enhanced properties of infectivity. The Omicron variant appears to be more effective at evading immune responses.
Sexual and reproductive health and access: Results of a rapid epidemiological assessment among migrant peoples in transit through Darién, Panamá
Authors: Erausquin Jennifer Toller , Sánchez Joanne , Yu Pon Anyi , Jhangimal Mónica , Millender Eugenia , Peña Yudith , Ng Winroy , Reina Adelys , Nakad Candy , Quintana Joselid , Herrera Veces Roberto , Vistica Grace , Pinzón-Espinosa Justo , Cabezas-Talavero Gonzalo , Katz Jennifer , Pascale Juan Miguel , Rodríguez-Álvarez Fátima , Gabster Amanda
Published: November 2022

Background

The foot transit of migrant peoples originating from the Caribbean, South America, Asia, and Sub-Saharan Africa through the Darién Forest (DF) in Eastern Panamá towards North America has increased in recent years from approximately 30,000 people/year to >133,000 in 2021. In the DF, there is no food/housing provision nor healthcare access. Very little is known of sexual and reproductive health (SRH) among this population. This study used rapid epidemiological methods to describe the SRH situation among migrant peoples in transit through the DF.

Methods

This cross-sectional study randomly selected migrant people in transit (men and women) at a Migrant Reception Station in Darién, Panamá, between January 4–11, 2022. Data collection included a self-applied questionnaire (≥18 years); clinical screening (≥12 years); and HCG, treponemal antibodies, and HIV(I/II) lateral-flow tests with blood samples (≥12 years). Descriptive analyses were used to report findings.

Results

In all, 69 men and 55 women participated in the self-applied questionnaire, 70 men and 51 women in clinical screening; 78 men and 63 women in HCG, treponemal antibody and HIV testing. Overall, 26.1% (18/69) men and 36.4% (20/55) women reported sexual intercourse within the past month. The last sex partner was casual among 43.0% (21/49) of men and 27.8% (10/36) of women; of those, 42.9% (9/21) of men and 80.0% (8/10) of women reported this sex was condomless. Among women, 20.0% (11/55) tested positive for pregnancy; 5 of these pregnancies were planned. Of those screened, a reproductive tract infection symptom was reported by 5.7% (4/70) of men and 58.8% (30/51) of women. A total of 32.7% (18/55) of men and 18.2% (8/44) of women reported no prior HIV testing. Of 78 men, HIV and treponemal antibodies were found among 1.3% (n = 1) and 2.6% (n = 2), and among 63 women, 3.2% (n = 2) and 3.2% (n = 2), respectively.

Conclusions

This rapid epidemiological assessment found high recent sexual activity, low condom use with casual partners, and a need for increased HIV and syphilis testing and treatment. There is a need for increased testing, condom provision, and SRH healthcare access at migrant reception stations that receive migrant peoples in transit through Panamá.
Temporal changes in the urban system in South Korea
Authors: Chun Yongwan , Kim Kamyoung
Published: November 2022

South Korea has experienced a dramatic economic change since the Korean War. Its economic structure has developed from one with a primary industry-centric in the 1950s to a manufacturing or service-centric structure. The economic development has been accompanied by a steady growth of population specifically in urban areas. In addition, economic development also has triggered changes in its population distribution and, ultimately, its urban system. The purpose of this paper is to investigate changes in the urban system in South Korea using two approaches, which are primacy indices and spatial interaction indices. While the primacy indices focus on the population sizes of cities, an investigation with spatial interaction allows an examination of linkages among cities. The results show that the Korean urban system had a primacy structure in which Seoul dominates until the 1990s, after which this primacy structure of the city weakened. The spatial interaction patterns show that many cities have developed in large metropolitan areas and are highly interconnected with each other. But this new development has dominantly occurred still in the Seoul metropolitan area. These results present that urban developments have been highly concentrated in peripheral areas of Seoul that are still in the Seoul metropolitan area, with the dominance of the metropolitan area getting stronger over time.
Assessing the demographics of the 2021 and 2022 CEDAR workshop
Authors: Jones McArthur , Maute Astrid
Published: November 2022

The Coupling, Energetics and Dynamics of Atmospheric Regions (CEDAR) community is made of engineers, scientists, physicists, and students with a mission to understand the fundamental properties and predictability of the space-atmosphere interaction region, including the mesosphere, thermosphere, ionosphere, and inner magnetosphere. At the 2020 CEDAR annual workshop, community-wide feedback received on diversity, equity, and inclusion (DEI) in CEDAR warranted a grassroots effort focused on addressing the DEI issues raised. This led to the creation of the CEDAR DEI task force, whose goals were to 1) Assess and formalize DEI efforts in CEDAR; 2) Establish and normalize a DEI presence in the CEDAR community; and 3) Foster improvement in CEDAR through implementation of actionable initiatives that promote diversity, equity, and inclusion. Of these actionable items collecting demographic information on those participating in the Annual CEDAR Workshop was identified as the top priority. This paper therefore, reports the demographic information obtained from CEDAR registrants for the virtual workshop in 2021 and in-person workshop in 2022. In general, the demographics of CEDAR are consistent with those in broader science, technology, engineering, and mathematics (STEM) fields, that is, most participants identify as male, White, and or Asian/Middle Eastern. On average, women and historically underrepresented races and ethnicities in STEM fields make up roughly 30% and 10%, respectively, of all 2021 and 2022 CEDAR Workshop registrants over the past 2 years. We further discuss the demographics of CEDAR relative to reports published in recent years by other organizations, where possible.
Recognizing the importance of protein quality in an era of food systems transformation
Authors: Pikosky Matthew A. , Ragalie-Carr Jean , Miller Gregory D.
Published: November 2022

A transformation of current food systems is needed to nourish the growing global population in more sustainable ways. To support this, some are advocating for a shift to plant-based or -exclusive diets. These recommendations – typically borne out of concerns for the environment – often fail to account for unintended nutritional consequences, which could be particularly pronounced for protein intake. While there is enough protein to meet current global needs, the issue of protein quality is often overlooked and oversimplified. High-quality protein, including from animal source foods (ASF), is needed to meet nutritional demands in low- and middle-income countries (LMIC), particularly among vulnerable population groups. In high-income countries (HIC), protein quality is important for at-risk populations who have higher protein requirements and lower energy and/or protein intakes. Further, as the global population increases, driven primarily by population growth in LMIC, it is possible that protein production will need to increase in HIC to support exports to help feed the global population. The global dialogue and resulting dietary recommendations must therefore become more nuanced to consider the interaction between nutritional value and environmental impact to help better reflect trade-offs across multiple domains of sustainability. Nutritional life cycle assessments are one way to help accomplish this nuance and evaluate how all types of food production systems should be refocused to improve their environmental efficiency and nutritional impact.
Non-genetic factors affecting the meat quality and flavor of Inner Mongolian lambs: A review
Authors: Liu Yuning , Li Runhang , Ying Ying , Zhang Yandong , Huang Yiying , Wu Hongxin , Lin Kejian
Published: November 2022

The Inner Mongolia Autonomous Region ranks first among the five major pastoral areas in terms of lamb breeding of China. The Inner Mongolia Autonomous Region has a vast territory, with many famous grasslands and thousands of forage plants and multiple local high-quality lamb breeds. After hundreds of years of artificial breeding and improvement, Mongolian sheep have developed many varieties. Different diets, feeding and treatment methods have effects on the production performance, lipid deposition and flavor composition of mutton sheep. Therefore, understanding the relationship among Inner Mongolian lamb, meat quality, and flavor will improve the production of high-quality mutton. The regulation of meat quality and flavor will have a profound impact on the deep processing and income-generating capabilities of mutton. Non-genetic factors affect the quality and flavor of mutton, which are more intuitive than genetic factors. In this review, we cover the contributions made by scientists to explore and improve the quality and flavor of Inner Mongolia lambs through non-genetic means, compare the differences between grazing and drylot-feeding in detail, and summarize some feed additives. We hope that based on our review, we can provide some inspiration to improve the meat quality of Mongolian sheep.
Optimisation of an Automatic Online Post-Processing Service for Static Observations as Realised in the Polish ASG-EUPOS System
Authors: Kudas Dawid , Wnęk Agnieszka , Gargula Tadeusz
Published: November 2022

The paper presents an assessment of the accuracy and precision of point positioning using a currently available online service for automatic post-processing (APPS) of GNSS observations made by the Polish Active Geodetic Network—European Position Determination System (ASG-EUPOS). The ASG-EUPOS network is part of the national EUPOS project and was selected for the study because of its substantial spatial reach in Europe. A modification to the current APPS algorithm is proposed to limit the number of baseline vectors used in positioning and change the method for adjusting post-processing results. Currently, the APPS of the ASG-EUPOS determines point coordinates based on the method for adjusting direct and equally accurate observations with the least-squares method (equally accurate method, EAM). The modification proposes to determine the coordinates based on post-processing results adjustment using the unequally accurate observations method (unequally accurate method, UAM). Our analysis diagnoses the uncertainty of the ASG-EUPOS’s APPS, and the modification optimises the adjustment. The proposed modification facilitates a much lower standard deviation of positioning in relation to reference positions. It is demonstrated that, if modified, the ASG-EUPOS service can provide automatic post-processing for 1 h GPS observations with a 1 s interval at 0.03 m accuracy for 99% of cases.
Sequence-to-Sequence Multi-Agent Reinforcement Learning for Multi-UAV Task Planning in 3D Dynamic Environment
Authors: Liu Ziwei , Qiu Changzhen , Zhang Zhiyong
Published: November 2022

Task planning involving multiple unmanned aerial vehicles (UAVs) is one of the main research topics in the field of cooperative unmanned aerial vehicle control systems. This is a complex optimization problem where task allocation and path planning are dealt with separately. However, the recalculation of optimal results is too slow for real-time operations in dynamic environments due to a large amount of computation required, and traditional algorithms are difficult to handle scenarios of varying scales. Meanwhile, the traditional approach confines task planning to a 2D environment, which deviates from the real world. In this paper, we design a 3D dynamic environment and propose a method for task planning based on sequence-to-sequence multi-agent deep deterministic policy gradient (SMADDPG) algorithm. First, we construct the task-planning problem as a multi-agent system based on the Markov decision process. Then, the DDPG is combined sequence-to-sequence to learn the system to solve task assignment and path planning simultaneously according to the corresponding reward function. We compare our approach with the traditional reinforcement learning algorithm in this system. The simulation results show that our approach satisfies the task-planning requirements and can accomplish tasks more efficiently in competitive as well as cooperative scenarios with dynamic or constant scales.
Multivariate Fence: Using Parallel Coordinates to Locate and Compare Attributes of Adjacency Matrix Nodes in Immersive Environment
Authors: Li Tiemeng , Jin Yanning , Wu Songqian , Liu Shiran
Published: November 2022

Adjacency matrix visualization is a common method for presenting graph data, and the Focus+Context technique can be used to explore the details of the ROI (region of interest). Embedded views and multi-view approaches are usually applied when locating and comparing attributes among multiple nodes. However, the embedded view has an issue of edge occlusion, while the multi-view would cause repeated perspective switching. In this paper, we propose a Multivariate Fence (MVF) model as a focus view of the adjacency matrix to locate and compare attributes among nodes. An additional spatial parallel coordinate is added to the 2D adjacency matrix in an immersive environment so that the attribute information can be shown in a single view without blocking edge information. We also conduct a user study to evaluate the performance of the MVF. The results show that the MVF has better efficiency and accuracy in locating and comparing the multivariate adjacency matrix in the immersive environment against the existing focus model. Moreover, the MVF model is easier to understand and is preferred by users.
Meta-Learning for Mandarin-Tibetan Cross-Lingual Speech Synthesis
Authors: Zhang Weizhao , Yang Hongwu
Published: November 2022

The paper proposes a meta-learning-based Mandarin-Tibetan cross-lingual text-to-speech (TTS) to realize both Mandarin and Tibetan speech synthesis under a unique framework. First, we build two kinds of Tacotron2-based Mandarin-Tibetan cross-lingual baseline TTS. One is a shared encoder Mandarin-Tibetan cross-lingual TTS, and another is a separate encoder Mandarin-Tibetan cross-lingual TTS. Both baseline TTS use the speaker classifier with a gradient reversal layer to disentangle speaker-specific information from the text encoder. At the same time, we design a prosody generator to extract prosodic information from sentences to explore syntactic and semantic information adequately. To further improve the synthesized speech quality of the Tacotron2-based Mandarin-Tibetan cross-lingual TTS, we propose a meta-learning-based Mandarin-Tibetan cross-lingual TTS. Based on the separate encoder Mandarin-Tibetan cross-lingual TTS, we use an additional dynamic network to predict the parameters of the language-dependent text encoder that could realize better cross-lingual knowledge sharing in the sequence-to-sequence TTS. Lastly, we synthesize Mandarin or Tibetan speech through the unique acoustic model. The baseline experimental results show that the separate encoder Mandarin-Tibetan cross-lingual TTS could handle the input of different languages better than the shared encoder Mandarin-Tibetan cross-lingual TTS. The experimental results further show that the proposed meta-learning-based Mandarin-Tibetan cross-lingual speech synthesis method could effectively improve the voice quality of synthesized speech in terms of naturalness and speaker similarity.
Effect of pH Change on the Microalgae-Based Biogas Upgrading Process
Authors: Meier Leslie , Vilchez Carlos , Cuaresma María , Torres-Aravena Álvaro , Jeison David
Published: November 2022

An alternative way to remove CO2 from biogas is the use of photosynthetic microorganisms, such as microalgae. This can be achieved by the operation of an open photobioreactor, connected with a mass transfer column, such as a counterflow column. This technology provides up-graded biogas with high quality. The microalgal uptake of CO2 from the biogas in counterflow columns generates pH changes in microalgae culture. To clarify the potential effect of these dynamic pH conditions in the culture, the effect of pH change on the photosynthetic activity and PSII quantum yield was studied for microalgae Chlorella sorokiniana. Thus, assays were carried out, where the pH drop reported in the counterflow columns was replicated in batch microalgae culture through HCl addition and CO2 injection, moving the culture pH from 7.0 to 5.0 and from 7.0 to 5.8, respectively. Moreover, the effect of light/darkness on photosynthetic activity was tested when the pH decreased. The results obtained in this research showed that the photosynthetic activity decreased for the light conditions when the pH was shifted by HCl addition and CO2 injection. Despite this, the value of the PSII quantum yield remained at 0.6–0.7, which means that the microalgae culture did not suffer a negative effect on the photosynthetic system of cells because a high value of PSII efficiency remained. In the same way, the results indicated that when the pH change was corrected, the photosynthetic activity recovered. Moreover, the apparent affinity constant for dissolved inorganic carbon (KDIC) was 0.9 µM at pH 5 and 112.0 µM at pH 7, which suggests that the preferred carbon source for C.sorokniana is CO2. Finally, all the results obtained indicated that the pH drop in the counter-flow column for biogas upgrading did not cause permanent damage to the photosynthetic system, and the decrease in the photosynthetic activity as a result of the pH drop can be recovered when the pH is corrected.
Quantitative Aspect of Bacillus subtilis σB Regulatory Network—A Computational Simulation
Authors: Vohradsky Jiri
Published: November 2022

Bacillus subtilis is a model organism used to study molecular processes in prokaryotic cells. Sigma factor B, which associates with RNA polymerase, is one of the transcriptional regulators involved in the cell’s response to environmental stress. This study addresses the key question of how the levels of free SigB, which acts as the actual regulator of gene expression, are controlled. A set of chemical equations describing the network controlling the levels of free SigB was designed, leading to a set of differential equations quantifying the dynamics of the network. Utilizing a microarray-measured gene expression time series then allowed the simulation of the kinetic behavior of the network in real conditions and investigation of the role of phosphatases RsbU/RsbP transmitting the environmental signal and controlling the amounts of free SigB. Moreover, the role of kinetic constants controlling the formation of the molecular complexes, which consequently influence the amount of free SigB, was investigated. The simulation showed that although the total amount of sigma B is relatively high in the unstressed population, the amount of free SigB, which actually controls its regulon, is quite low. The simulation also allowed determination of the proportion of all the network members that were free or bound in complexes. While previously the qualitative features of B. subtilis SigB have been studied in detail, the kinetics of the network have mostly been ignored. In summary, the computational results based on experimental data provide a quantitative insight into the functioning of the SigB-dependent circuit and provide a roadmap for its further exploration in this industrially important bacterium.
MaCts1, an Endochitinase, Is Involved in Conidial Germination, Conidial Yield, Stress Tolerances and Microcycle Conidiation in Metarhizium acridum
Authors: Zou Yuneng , Li Chan , Wang Shuqin , Xia Yuxian , Jin Kai
Published: November 2022

Entomopathogenic fungi are promising biocontrol agents of insect-mediated crop damage. Microcycle conidiation has shown great potential in enhancing the conidial yield and quality of entomopathogenic fungi. Homologs of Cts1, an endochitinase of Saccharomyces cerevisiae, participate in cell separation in several fungal spp. and may contribute to the morphological differences that occur during the shift to microcycle conidiation. However, the precise functions of Cts1 in entomopathogenic fungi remain unclear. Herein, the endochitinase gene, MaCts1, was characterized in the model entomopathogen, Metarhizium acridum. A loss of function line for MaCts1 led to a delay of 1 h in the median germination time, a 28% reduction in conidial yield and significant defects in fungal resistances to UV-irradiation (18%) and heat-shock (15%), while fungal tolerances to cell wall stressors, oxidative and hyperosmotic stresses and virulence remained unchanged. The MaCts1-disruption strain displayed typical conidiation on the microcycle conidiation induction medium, SYA. In contrast, deletion of key genes in the morphogenesis-related NDR kinase network (MOR pathway)/regulation of Ace2 and morphogenesis (RAM pathway) did not affect the SYA-induction of microcycle conidiation. This indicates that MaCts1 makes contributions to the microcycle conidiation, which may not be dependent on the MOR/RAM pathway in M. acridum.
Fibromyalgia Pathophysiology
Authors: Gyorfi Michael , Rupp Adam , Abd-Elsayed Alaa
Published: November 2022

This article examines the biological, genetic, and environmental aspects of fibromyalgia that may have an impact on its pathogenesis. Symptoms of fibromyalgia may be related to aberrations in the endogenous inhibition of pain as well as changes in the central processing of sensory input. Genetic research has revealed familial aggregation of fibromyalgia and other related disorders like major depressive disorder. Dysfunctional pain processing may also be influenced by exposure to physical or psychological stressors, abnormal biologic reactions in the autonomic nervous system, and neuroendocrine responses. With more research the pathophysiology of fibromyalgia will be better understood, leading to more logical and focused treatment options for fibromyalgia patients.
Attention Cost-Sensitive Deep Learning-Based Approach for Skin Cancer Detection and Classification
Authors: Ravi Vinayakumar
Published: November 2022

Deep learning-based models have been employed for the detection and classification of skin diseases through medical imaging. However, deep learning-based models are not effective for rare skin disease detection and classification. This is mainly due to the reason that rare skin disease has very a smaller number of data samples. Thus, the dataset will be highly imbalanced, and due to the bias in learning, most of the models give better performances. The deep learning models are not effective in detecting the affected tiny portions of skin disease in the overall regions of the image. This paper presents an attention-cost-sensitive deep learning-based feature fusion ensemble meta-classifier approach for skin cancer detection and classification. Cost weights are included in the deep learning models to handle the data imbalance during training. To effectively learn the optimal features from the affected tiny portions of skin image samples, attention is integrated into the deep learning models. The features from the finetuned models are extracted and the dimensionality of the features was further reduced by using a kernel-based principal component (KPCA) analysis. The reduced features of the deep learning-based finetuned models are fused and passed into ensemble meta-classifiers for skin disease detection and classification. The ensemble meta-classifier is a two-stage model. The first stage performs the prediction of skin disease and the second stage performs the classification by considering the prediction of the first stage as features. Detailed analysis of the proposed approach is demonstrated for both skin disease detection and skin disease classification. The proposed approach demonstrated an accuracy of 99% on skin disease detection and 99% on skin disease classification. In all the experimental settings, the proposed approach outperformed the existing methods and demonstrated a performance improvement of 4% accuracy for skin disease detection and 9% accuracy for skin disease classification. The proposed approach can be used as a computer-aided diagnosis (CAD) tool for the early diagnosis of skin cancer detection and classification in healthcare and medical environments. The tool can accurately detect skin diseases and classify the skin disease into their skin disease family.
Effect of Adjuvant Radiation Dose on Survival in Patients with Esophageal Squamous Cell Carcinoma
Authors: Han Weiming , Chang Xiao , Zhang Wencheng , Yang Jingsong , Yu Shufei , Deng Wei , Ni Wenjie , Zhou Zongmei , Chen Dongfu , Feng Qinfu , Liang Jun , Hui Zhouguang , Wang Lvhua , Gao Shugeng , Lin Yu , Chen Xiaohui , Chen Junqiang , Xiao Zefen
Published: November 2022

Background: For patients with esophageal squamous cell carcinoma (ESCC) treated with surgery alone, the incidence of local-regional recurrence remains unfavorable. Postoperative radiotherapy (PORT) has been associated with increased local-regional recurrence-free survival (LRFS), although its application is limited by concerns of PORT-related toxicities. Methods: Among 3591 patients with ESCC analyzed in this study, 2765 patients with T3-4N0 and T1-4N1-3 lesions and specific local-regional status information were analyzed in a subsequent analysis of adjuvant radiation dose (aRTD) effect. Application of the restricted cubic spline regression model revealed a non-linear relationship between aRTD and survival/radiotoxicity. Linear regression analysis (LRA) was performed to evaluate correlations between LRFS and overall survival (OS)/ disease-free survival (DFS). Results: For patients staged T1–2N0, T1–2N1–3, T3–4N0, and T3–4N1–3, 5-year OS in PORT and non-PORT groups were 77.38% vs. 72.91%, p = 0.919, 52.35% vs. 46.60%, p = 0.032, 73.41% vs. 61.19%, p = 0.005 and 38.30% vs. 25.97%, p < 0.001. With aRTD escalation, hazard ratios (HRs) of OS/DFS declined until aRTD exceeded 50Gy, then increased, whereas that of LRFS declined until aRTD exceeded 50 Gy, then remained steady. HR of treatment-related mortality was stable until aRTD exceeded 50 Gy, then increased. LRA revealed strong correlations between LRFS and OS/DFS (r = 0.984 and r = 0.952, respectively). An absolute 1% advancement in LRFS resulted in 0.32% and 0.34% improvements in OS and DFS. Conclusions: An aRTD of 50Gy was well-tolerated, with favorable survival resulting from PORT-related LRFS improvement in patients staged T3–4N0 or T1-4N1–3. Further stratification analyses based on tumor burden would help determine potential PORT-beneficiaries.
High Surface Area ZnO-Nanorods Catalyze the Clean Thermal Methane Oxidation to CO2
Authors: Kessaratikoon Tanika , Saengsaen Sawarin , Del Gobbo Silvano , D’Elia Valerio , Sooknoi Tawan
Published: November 2022

ZnO nanostructures were synthesized by a combination of non-aqueous and aqueous sol-gel techniques to obtain morphologically different ZnO nanostructures, nanorods, and nanopyramids, featuring oxygen vacancies-rich exposed lattice faces and exhibiting different catalytic properties and activity. In particular, ZnO nanorods with high surface area (36 m2/g) were obtained through a rapid, scalable, and convenient procedure. The materials were tested for complete methane oxidation as an important benchmark reaction that is sensitive to surface area and to the availability of oxygen vacancies. Simple ZnO nanorods derived from nanosized quantum dots showed the best catalytic performance that compared well to that of several literature-reported perovskites, mixed metal oxides, and single-metal oxides in terms of T50 (576 °C) and T90 (659 °C) temperatures. Such a result was attributed to their high surface-to-volume ratio enhancing the availability of catalytically active sites such as oxygen vacancies whose abundance further increased following catalytic application at high temperatures. The latter effect allowed us to maintain a nearly stable catalytic performance with over 90% conversion for 12 h at 700 °C despite sintering. This research shows that ZnO-based nanomaterials with a high surface area are viable alternatives to oxides of commonly applied (but of potentially limited availability) transition metals (La, Mn, Co, Ni) for the complete combustion of methane when working at moderate temperatures (600–700 °C).
The Role of Bone Morphogenetic Protein Receptor Type 2 (BMPR2) and the Prospects of Utilizing Induced Pluripotent Stem Cells (iPSCs) in Pulmonary Arterial Hypertension Disease Modeling
Authors: Devendran Anichavezhi , Kar Sumanta , Bailey Rasheed , Trivieri Maria Giovanna
Published: November 2022

Pulmonary arterial hypertension (PAH) is a progressive disease characterized by increased pulmonary vascular resistance (PVR), causing right ventricular hypertrophy and ultimately death from right heart failure. Heterozygous mutations in the bone morphogenetic protein receptor type 2 (BMPR2) are linked to approximately 80% of hereditary, and 20% of idiopathic PAH cases, respectively. While patients carrying a BMPR2 gene mutation are more prone to develop PAH than non-carriers, only 20% will develop the disease, whereas the majority will remain asymptomatic. PAH is characterized by extreme vascular remodeling that causes pulmonary arterial endothelial cell (PAEC) dysfunction, impaired apoptosis, and uncontrolled proliferation of the pulmonary arterial smooth muscle cells (PASMCs). To date, progress in understanding the pathophysiology of PAH has been hampered by limited access to human tissue samples and inadequacy of animal models to accurately mimic the pathogenesis of human disease. Along with the advent of induced pluripotent stem cell (iPSC) technology, there has been an increasing interest in using this tool to develop patient-specific cellular models that precisely replicate the pathogenesis of PAH. In this review, we summarize the currently available approaches in iPSC-based PAH disease modeling and explore how this technology could be harnessed for drug discovery and to widen our understanding of the pathophysiology of PAH.
Quantitative Estimation of COD Values from an Array of Metal Nanoparticle Modified Electrodes and Artificial Neural Networks
Authors: Wang Qing , Cetó Xavier , Valle Manel del
Published: November 2022

Water quality monitoring has become critical in modern societies in multiple areas and at different stages. In this regard, chemical oxygen demand (COD) has become a key index in water testing, as it readily allows the determination of its overall quality and the presence of organic contaminants. However, conventional COD determination presents several drawbacks in view of the use of toxic reagents and possible interferences. The electrochemical determination of COD can be an alternative with many advantages, especially if using an array of sensors. Herein, the use of an electronic tongue (ET) for the estimation of COD was explored. The proposed ET was formed by an array of five voltammetric electrodes modified with different metal nanoparticles. An artificial neural network (ANN) model was built based on the responses of the array towards glucose and glycine as standards. This model was then used with real and spiked water samples, and the results compared to the electrochemical calibration and the commercial COD colorimetric methods. While the COD values of the real samples were low and outside the range of the ANN model, a satisfactory prediction for the spiked samples was achieved, showing a good agreement with the reference colorimetric method, that was better than the performance of the conventional electrochemical calibration method.
Laser-Scribed Graphene-Based Electrochemical Sensors: A Review
Authors: Ameku Wilson A. , Negahdary Masoud , Lima Irlan S. , Santos Berlane G. , Oliveira Thawan G. , Paixão Thiago R. L. C. , Angnes Lúcio
Published: November 2022

Laser scribing is a technique that converts carbon-rich precursors into 3D-graphene nanomaterial via direct, single-step, and maskless laser writing in environmental conditions and using a scalable approach. It allows simple, fast, and reagentless production of a promising material with outstanding physicochemical features to create novel electrochemical sensors and biosensors. This review addresses different strategies for fabricating laser-scribed graphene (LSG) devices and their association with nanomaterials, polymers, and biological molecules. We provide an overview of their applications in environmental and health monitoring, food safety, and clinical diagnosis. The advantages of their integration with machine learning models to achieve low bias and enhance accuracy for data analysis is also addressed. Finally, in this review our insights into current challenges and perspectives for LSG electrochemical sensors are presented.
Temporal Acoustic Patterns of the Oriental Turtle Dove in a Subtropical Forest in China
Authors: Wang Mei , Mei Jinjuan , Liu Fanglin
Published: November 2022

There is an abundance of bird species in subtropical areas, but studies on the vocal behavior of non-passerines in subtropical regions are limited. In this study, passive acoustic monitoring was used to investigate the temporal acoustic patterns of the vocal activities of the Oriental Turtle Dove (Streptopelia orientalis) in Yaoluoping National Nature Reserve (YNNR) in eastern China. The results show that the vocal production of the Oriental Turtle Dove exhibited a seasonal variation, peaking in the period April–August. Additionally, its diurnal vocal activity displayed a bimodal pattern in late spring and summer, with the first peak in the morning and a secondary peak at dusk. Among weather factors, temperature significantly affected the temporal sound pattern of the Oriental Turtle Dove, instead of humidity and precipitation. This study, which was focused on sound monitoring technology, provides knowledge for further research on bird behavior and ecology. In the future, long-term sound monitoring could be used for managing and conserving bird biodiversity.
Population Structure of White Sturgeon (Acipenser transmontanus) in the Columbia River Inferred from Single-Nucleotide Polymorphisms
Authors: Willis Stuart C. , Parker Blaine , Schreier Andrea D. , Beamesderfer Ray , Miller Donella , Young Shawn , Narum Shawn R.
Published: November 2022

White sturgeon (Acipenser transmontanus) are the largest freshwater fish in North America, with reproducing populations in the Sacramento-San Joaquin, Fraser, and Columbia River Basins. Of these, the Columbia River is the largest, but it is also highly fragmented by hydroelectric dams, and many segments are characterized by declining abundance and persistent recruitment failure. Efforts to conserve and supplement these fish requires an understanding of their spatial genetic structure. Here, we assembled a large set of samples from throughout the Columbia River Basin, along with representative collections from adjacent basins, and genotyped them using a panel of 325 single-nucleotide markers. Results from individual- and group-based analyses of these data indicate that white sturgeon in the uppermost Columbia River Basin, in the Kootenai and upper Snake Rivers, are the most distinct, while the remaining populations downstream in the basin can be described as a genetic gradient consistent with an isolation-by-distance effect. Notably, the population in the lowest reaches of the Columbia River is more distinct from the middle or upper reaches than from outside basins, and suggests historically a higher or more recent gene exchange through coastal routes than with populations in the interior Columbia Basin. Nonetheless, proximal reaches were generally only marginally or non-significantly divergent, suggesting that transplanting larvae or juveniles from nearby sources poses relatively little risk of outbreeding depression. Indeed, we inferred examples of dispersal between reaches via close-kin mark-recapture and genetic mark-recapture that indicate movement between nearby reaches is not unusual. Samples from the Kootenai and upper Snake Rivers exhibited notably lower genetic diversity than the remaining samples as a result of population bottlenecks, genetic drift, and/or historical divergence. Conservation actions, such as supplementation, are underway to maintain population viability and will require balanced efforts to increase demographic abundance while maintaining genetic diversity.
Security Access Control Method for Wind-Power-Monitoring System Based on Agile Authentication Mechanism
Authors: Shu Yingli , Yuan Quande , Ke Wende , Kou Lei
Published: November 2022

With the continuous increase in the proportion of wind power construction and grid connection, the deployment scale of state sensors in wind-power-monitoring systems has grown rapidly with an aim on the problems that the communication authentication process between the wind turbine status sensor and the monitoring gateway is complex and the adaptability of the massive sensors is insufficient. A security access control method for a wind-power-monitoring system based on agile authentication mechanism is proposed in this paper. First, a lightweight key generation algorithm based on one-way hash function is designed. The algorithm realizes fixed-length compression and encryption of measurement data of any length. Under the condition of ensuring security, the calculation and communication cost in the later stage of authentication are effectively reduced. Second, to reduce the redundant process of wind turbine status sensor authentication, an agile authentication model of wind turbine status sensor based on a lightweight key is constructed. Constrained by the reverse order extraction of key information in the lightweight keychain, the model can realize lightweight communication between massive wind turbine status sensors and regional gateways. Finally, the proposed method is compared and verified using the wind turbine detection data set provided by the National New Energy Laboratory of the United States. The experimental results show that this method can effectively reduce the certification cost of a wind-power-monitoring system. Additionally, it can improve the efficiency of status sensor identity authentication and realize the agility and efficiency of the authentication process.
Adaptive Fault-Tolerant Control for Second-Order Multiagent Systems with Unknown Control Directions via a Self-Tuning Distributed Observer
Authors: Gu Rongrong , Sun Xudong , Pu Dongyi
Published: November 2022

In this paper, we first design a self-tuning distributed observer for second-order multi-agent systems which is capable of providing the estimation of the leader’s signal to various followers. We then further develop an adaptive sliding-mode controller to solve the cooperative tracking problem between leader and followers for second-order multi-agent systems subject to time-varying actuator faults and unknown external disturbances, which can ensure that the leader-following cooperative tracking errors converge to zero asymptotically. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed controller. This control law offers three advantages: first, the problem of communication barriers among the leader and followers can be solved by the self-tuning distributed observer, which can calculate the observer gain online; second, a new type of adaptive sliding-mode controller is proposed by introducing a Nussbaum function; and lastly, the bounds of unknown actuator faults and unknown external disturbances can be adaptively estimated.
An Adaptive Rational Fitting Technique of Sommerfeld Integrals for the Efficient MoM Analysis of Planar Structures
Authors: Zhao Zi-Hao , Wu Bi-Yi , Li Ze-Lin , Yang Ming-Lin , Sheng Xin-Qing
Published: November 2022

The integral equation method is one of the most successful computational models for microwave devices or integrated circuits in planar layered media. However, the efficient and accurate evaluation of the associated Green’s function consisting of Sommerfeld integrals (SIs) is still a remaining challenge. To mitigate this difficulty, this work proposes a spatial domain rational function fitting technique (RFFT) for SIs so that the approximation accuracy is controllable. In conjunction with an adaptive sampling strategy, the proposed RFFT minimizes the orders of rational functions, and the resultant SI evaluation efficiency is optimized. In addition, we investigate the semi-analytical singularity treatment for the rational expression of SIs in method of moment (MoM) implementation. Extensive simulation of representative planar devices validates the correctness of the proposed method and demonstrates its superior performance over conventional SI approximation methods.
The Influence of Nonthermal Plasma Technology on Oxidation Characteristics of Soot Operated on Direct Injection Internal Combustion Engines
Authors: Neamyou Pichitpon , Theinnoi Kampanart , Sawatmongkhon Boonlue , Wongchang Thawatchai , Wongkhorsub Chonlakarn , Sittichompoo Sak , Chuepeng Sathaporn
Published: November 2022

The combination of porous material with nonthermal plasma (NTP) technology to reduce the amount of particulate matter emitted from a direct-injection compression-ignition engine was investigated in this study. The investigation aimed at regulating particulate matter under long-term operation. A porous materials filter thickness of 4 mm was installed in the NTP reactor. The common rail diesel engine was fueled with 7%-vol biodiesel fuel (B7), and the experiment was carried out at steady-state conditions at 2000 rpm and indicated mean effective pressure (IMEP) of 6 bar. The effects of NTP high-voltage discharge (e.g., 2, 4, 5, 6, 8, and 10 kV) and the porous filter thickness (e.g., 0, 2, 4, and 6 mm) on particle number size distributions were examined. The protype of combine porous filter and NTP illustrated good particulate removal (>70%) operated with a thickness of 4 mm of porous materials filter and a high voltage of 6 kV under the same power rating.