bluuebunny/crossref_metadata_2025 huggingface dataset:
Psychological and social consequences of deafblindness for siblings: a systematic literature review
Authors: Arcous Marine , Potier Rémy , Dumet Nathalie
Published: April 2024

The onset of deafblindness profoundly impacts both the individual with this condition and the individual’s family, including siblings. While current studies have primarily focused on the impact felt by parents or spouses, the distinct experiences of siblings have received comparatively less attention. This systematic review addresses the existing research gap regarding the psychological and social consequences experienced by siblings of individuals with deafblindness. A comprehensive search was conducted across multiple electronic databases, including PsycINFO, PsycARTICLES, Dissertations & Theses (on ProQuest), ERIC (Education Resources Information Center), International Bibliography of the Social Sciences (IBSS), Sociological Abstracts, Google Scholar, PubMed, and Cairn Info. Seven studies were identified as meeting the eligibility criteria for inclusion. The review revealed that siblings of individuals with deafblindness face psychological and social challenges, including emotions such as feelings of neglect, resentment, embarrassment, jealousy, and anxiety. Siblings also grapple with communication difficulties, contributing to feelings of exclusion and insecurity. In addition, these siblings take on significant responsibilities within the family and encounter obstacles in forming relationships outside the family. These findings underscore the need of interventions to improve the well-being of siblings of individuals with deafblindness by addressing their psycho-emotional needs and promoting positive social interactions. These findings align with studies conducted on siblings of children with other disabilities. However, additional research is crucial to investigate overlooked dimensions, particularly positive factors like coping mechanisms and resilience, that may influence the mental health and social experiences of these siblings.
Association between sports participation and resilience in school-attending students: a cross-sectional study
Authors: Sheng Xinxin , Liang Kaixin , Li Kai , Chi Xinli , Fan Huiying
Published: April 2024

Aim

This research sought to identify the association between sports participation and resilience in children and adolescents as a means to enhance mental health.

Methods

A comprehensive survey was carried out, encompassing primary, middle, and high school students from chosen educational institutions. The analytical sample comprised 67,281 students of school age. Sports participation and resilience were evaluated using validated assessment tools, while relevant covariates, such as sex and school grade, were assessed through self-reported questionnaires. Generalized Linear Models were applied to ascertain the association between sports participation and resilience for the entire sample, and separately for subgroups divided by gender or school grade, after controlling for covariates.

Results

Among the 67,281 school students, males constituted 51.9% of the sample. Approximately 47.1% of the entire sample reported no sports participation, and the average resilience score was 24.7. The regression model analysis revealed that, in the entire sample, increased in sports participation was linked to higher resilience scores (odds ratio [OR] for 1–3 times per month: 1.20, 95%CI: 1.16–1.24; OR for 1–2 times per week: 1.38, 95%CI: 1.33–1.43; OR for 3 times or more per week: 1.72, 95%CI: 1.65–1.79). Analyses stratified by gender and school grade indicated that sports participation was consistently associated with greater resilience.

Conclusion

This study provides cross-sectional evidence supporting the positive association between sports participation and the resilience of children and adolescents, underscoring the potential of encouraging sports participation as a strategy for promoting mental health resilience. The findings presented herein should be subject to further confirmation or refutation in future research endeavors.
Exposure to workplace bullying: the incremental effect of gelotophobia beyond the big five
Authors: Sulejmanov Filip , Petr Kryštof , Gambová Jana , Platt Tracey , Seitl Martin
Published: April 2024

The role of Big Five personality traits in exposure to workplace bullying has been a focus of numerous studies. Yet less is known about the incremental validity of narrower personality constructs. The aim of the present study was to investigate the incremental effect of gelotophobia (the fear of being laughed at) in predicting exposure to workplace bullying beyond the Big Five personality domains. The sample comprised 328 employees (77% females) from different regions of the Czech Republic. Correlational analysis showed that negative emotionality and gelotophobia were related to workplace bullying in theoretically expected ways. Results from a multiple regression indicated that gelotophobia had an incremental effect in predicting exposure to workplace bullying over and above the personality domains. Overall, this study provides new insights and extends previous investigations concerning the role of gelotophobia in workplace bullying. We also discuss the limitations of our study and provide suggestions for future research.
Real-time genomic surveillance for enhanced control of infectious diseases and antimicrobial resistance
Authors: Struelens Marc J. , Ludden Catherine , Werner Guido , Sintchenko Vitali , Jokelainen Pikka , Ip Margaret
Published: April 2024

This article advocates for mobilizing pathogen genomic surveillance to contain and mitigate health threats from infectious diseases and antimicrobial resistance (AMR), building upon successes achieved by large-scale genome sequencing analysis of SARS-CoV-2 variants in guiding COVID-19 monitoring and public health responses and adopting a One Health approach. Capabilities of laboratory-based surveillance and epidemic alert systems should be enhanced by fostering (i) universal access to real-time whole genome sequence (WGS) data of pathogens to inform clinical practice, infection control, public health policies, and vaccine and antimicrobial drug research and development; (ii) integration of diagnostic microbiology data, data from testing asymptomatic individuals, pathogen sequence data, clinical data, and epidemiological data into surveillance programs; (iii) stronger cross-sectorial collaborations between healthcare, public health, animal health, and environmental surveillance and research using One Health approaches, toward understanding the ecology and transmission pathways of pathogens and AMR across ecosystems; (iv) international collaboration and interconnection of surveillance networks, harmonization of laboratory methods, and standardization of surveillance methods for global reporting, including on pathogen genomic variant or strain nomenclature; (v) responsible data sharing between surveillance networks, databases, and platforms according to FAIR (findability, accessibility, interoperability, and reusability) principles; and (vi) research on genomic surveillance system implementation and its cost-effectiveness for different pathogens and AMR threats across different settings. Regional and global One Health policies and governance initiatives should foster the concerted development and efficient utilization of pathogen genomic surveillance to protect the health of humans, animals, and the environment.
Female blind baseball players against gender discrimination: the “red diamonds” experience
Authors: Carretti Giuditta , Russo Pippo , Manetti Mirko , Marini Mirca
Published: April 2024

Background

Sport has the well-known power of improving body awareness, self-esteem, and social interaction, thus promoting quality of life and psychophysical wellbeing. Specifically referring to adapted disciplines, habitual practice often becomes an effective integration and self-efficacy booster. Among disabilities, visual impairment deeply alters body image perception, autonomy, and environmental/social interaction heavily reducing sport or leisure involvement opportunities. In particular, visually impaired women represent one of the most vulnerable categories to gender and disability discrimination. Moreover, even when congenitally sightless, they perceive social pressure of mainstream beauty ideals, mostly spread by media, comparable to their sighted peers. On these premises and the previously demonstrated psychophysical benefits of Italian blind baseball practice on this target population, the present study aimed to deepen the social and educative potentialities of such adapted sport applying a more sociological research approach.

Methods

The “red diamonds” event, namely, the first ever female blind baseball match, was the setting for the administration of our structured online survey. In detail, our survey comprised different evaluation tools such as the 18-item Psychological Well-Being Scale, the 12-item Short Form questionnaire, the Dresden Body Image questionnaire, the Rosenberg Self-Esteem Scale, and sociological model designed questions. Quality of life, psychological wellbeing, self-esteem, body image, and perceived female sport psychological violence were investigated in the whole women sample (n = 33) voluntarily adhering to the game.

Results

Survey results revealed no statistically significant differences between visually impaired players (n = 13; mean age: 32.84 ± 12.05 years) and sighted on-field subjects (i.e., coaches, assistants, and referees; n = 20; mean age: 47.15 ± 12.31 years) in almost all the inquired variables, thus remarking the social and functional benefits of adapted sport through the “dual embodiment” and empowerment phenomenon.

Conclusions

Given that the event was inspired by and performed on the World Day against women violence, our study deepened not only the topic of disability discrimination but also the currently alarming gender-related one. In such a context, the present research might provide interesting cues for further investigations on disability and gender disparities in sports, hence spreading interest in this under-investigated field. In perspective, the “red diamonds” experience could also contribute to inspiring and progressively developing educative tools against any kind of discrimination by promoting integration and social growth through regular sports practice.
Numerical Investigations on the Effects of Dome Cooling Air Flow on Combustion Characteristics and Emission Behavior in a Can-Type Gas Turbine Combustor
Authors: Ji Chenzhen , Shi Wentao , Ke Enlei , Cheng Jiaying , Zhu Tong , Zong Chao , Li Xinyan
Published: April 2024

To meet the requirements of achieving higher efficiency and lower NOx pollution, the flame temperature in gas turbine combustors increases continually; thus, the effusion-cooling technology has been used to ensure the combustor liner remains within the allowed temperature, by which the combustion characteristics and emission behavior are possibly influenced. In order to investigate the effects of dome cooling air flow on combustion characteristics and NOx emissions, three-dimensional combustion simulations for a swirl-stabilized can-type gas turbine combustor are carried out in this work by using the computational fluid dynamics (CFD) method. Through adjusting the ratio of the dome cooling air flow and the dilution cooling air flow, the characteristics of flow field, temperature distribution and NOx emissions under each work condition are analyzed. At different ratios of the dome-cooling air flow to the total air flow, the flow velocity field in the region near the center of the combustion chamber is not changed much, while the velocity field near the chamber wall shows a more significant difference. The temperature in the outer recirculation zone within the combustion chamber is effectively reduced as the dome cooling air flow increases. By analyzing the distribution characteristics of the concentration of OH*, it is demonstrated that the dome cooling air flow does not have a direct effect on the reaction of combustion. It is also found that as the ratio of the dome cooling air flow to the total air flow increases from 0 to 0.15, the value of the NOx emissions drops from 28.4 to 26.3 ppmv, about a 7.4% decrease. The distribution of the NOx generation rate in the combustion chamber does not vary significantly with the increasing dome cooling air flow. Furthermore, by calculating the residence time in different stages, when the the ratio of the dome cooling air flow to the total air flow varies from 0 to 0.15, the residence time in the pilot stage decreases obviously, from 42 ms to 18 ms. This means that reduction in residence time is the main factor in the decrease of NOx emissions when the dome cooling air flow increases.
Crude Oil Prices Forecast Based on Mixed-Frequency Deep Learning Approach and Intelligent Optimization Algorithm
Authors: Lu Wanbo , Huang Zhaojie
Published: April 2024

Precisely forecasting the price of crude oil is challenging due to its fundamental properties of nonlinearity, volatility, and stochasticity. This paper introduces a novel hybrid model, namely, the KV-MFSCBA-G model, within the decomposition–integration paradigm. It combines the mixed-frequency convolutional neural network–bidirectional long short-term memory network-attention mechanism (MFCBA) and generalized autoregressive conditional heteroskedasticity (GARCH) models. The MFCBA and GARCH models are employed to respectively forecast the low-frequency and high-frequency components decomposed through variational mode decomposition optimized by Kullback–Leibler divergence (KL-VMD). The classification of these components is performed using the fuzzy entropy (FE) algorithm. Therefore, this model can fully exploit the advantages of deep learning networks in fitting nonlinearities and traditional econometric models in capturing volatilities. Furthermore, the intelligent optimization algorithm and the low-frequency economic variable are introduced to improve forecasting performance. Specifically, the sparrow search algorithm (SSA) is employed to determine the optimal parameter combination of the MFCBA model, which is incorporated with monthly global economic conditions (GECON) data. The empirical findings of West Texas Intermediate (WTI) and Brent crude oil indicate that the proposed approach outperforms other models in evaluation indicators and statistical tests and has good robustness. This model can assist investors and market regulators in making decisions.
Selection of Renewable Energy Sources for Modular and Mobile “Green Classroom” Facilities
Authors: Węgiel Tomasz , Borkowski Dariusz , Blazy Rafał , Ciepiela Agnieszka , Łysień Mariusz , Dudek Jakub , Błachut Jakub , Hrehorowicz-Gaber Hanna , Hrehorowicz-Nowak Alicja
Published: April 2024

This article aims to demonstrate the technical capabilities and effectiveness of an energy production and management system for school facilities using a modular solution. The system is assumed to generate electricity from renewable sources, such as wind or sun. The potential of renewable energy sources in Cracow, Poland, was assessed, with a focus on solar energy (photovoltaic panels, PV). Taking into account the installation of heating and other equipment, an analysis of the facility’s electricity demand was carried out. The study recommended the use of a heat pump system to heat and cool the facility. Renewable energy sources will meet 81% of the facility’s projected annual demand, according to the study. An analysis of the energy consumption and production profiles shows that almost 69% of the energy produced by the PV panels is consumed on site. Of the remaining energy, 31% is fed back into the grid and sold to the grid operator or used by other facilities within the shared settlement. The overall balance results in a small electricity deficit that must be covered by the grid. If suitable sites are available, the facilities under study could consider installing a wind turbine as a potential supplement to the energy deficit.
GC-Olfactometric Analysis as a Tool for Comprehensive Characterization of Aromatic Profiles in Cocoa-Based Beverages with a Natural Chocolate Substitute
Authors: Spada Fernanda Papa , de Alencar Severino Matias , Junior Stanislau Bogusz , Purgatto Eduardo
Published: April 2024

Cocoa is the third most important global agricultural export commodity. However, because it is a crop sensitive to climatic change, there has been an active search for cocoa substitutes worldwide. Roasted jackfruit seeds were previously described as having a chocolate aroma and are affordable and accessible. In this study, we characterized and identified by SPME-GC-O and SPME-GC-MS the aroma profile of cocoa-based beverages formulated with jackfruit seed flour as a natural cocoa substitute. Our analysis tentatively identified 71 odor-active aroma descriptors with some similarities between formulations. Overall, 15 odor-active aromas were present in all beverages. The formulation containing only cocoa/chocolate showed the following aroma descriptors: cocoa, hazelnut, peanut butter, earthy, and roast, which are mostly related to the presence of 2,3-dimethylpyrazine and 2,3-diethyl-5-methylpyrazine. The fermented beverage had a content of complex pyrazines such as 2,3,5-trimethyl-6-isopentylpyrazine and methylpropylpyrazine. Our data indicated that both the control and fermented beverages showed a similar aromatic profile, mainly earthy, pyrazine, and chocolate. Qualitative similarities in the pyrazine content were observed between the fermented jackfruit seed flour and cocoa beverages. In conclusion, fermented jackfruit seed flour can be incorporated into cocoa-based beverages as a natural chocolate substitute, offering the potential to elevate the chocolate aroma.
Fabrication of the SiC/HfC Composite Aerogel with Ultra-Low Thermal Conductivity and Excellent Compressive Strength
Authors: Wang Wei , You Qi , Wu Zhanwu , Cui Sheng , Shen Weimin
Published: April 2024

Aerogels, as a new type of high-temperature-resistant insulation material, find extensive application in aerospace, high-temperature industrial furnaces, new energy batteries, and various other domains, yet still face some limitations such as inadequate temperature resistance and pronounced brittleness. In this work, SiC/HfC composite aerogels were prepared through a combination of sol-gel method, atmospheric pressure drying technique, and carbothermal reduction reaction. The effects of different molar ratios, calcination time, and temperatures on the microstructural features and physicochemical properties of the resulting SiC/HfC composite aerogels were investigated. The aerogel exhibited an elevated BET-specific surface area of 279.75 m2/g, while the sample displayed an extraordinarily low thermal conductivity of 0.052 W/(m·K). Most notably, the compressive strength reached an outstanding 5.93 MPa after a carbonization temperature of 1500 °C, far exceeding the values reported in prior aerogel studies. This research provided an innovative approach for advancing the development of carbide aerogels in the realm of high-temperature applications.
Differential Solvent DEEP-STD NMR and MD Simulations Enable the Determinants of the Molecular Recognition of Heparin Oligosaccharides by Antithrombin to Be Disentangled
Authors: Parafioriti Michela , Elli Stefano , Muñoz-García Juan C. , Ramírez-Cárdenas Jonathan , Yates Edwin A. , Angulo Jesús , Guerrini Marco
Published: April 2024

The interaction of heparin with antithrombin (AT) involves a specific sequence corresponding to the pentasaccharide GlcNAc/NS6S-GlcA-GlcNS3S6S-IdoA2S-GlcNS6S (AGA*IA). Recent studies have revealed that two AGA*IA-containing hexasaccharides, which differ in the sulfation degree of the iduronic acid unit, exhibit similar binding to AT, albeit with different affinities. However, the lack of experimental data concerning the molecular contacts between these ligands and the amino acids within the protein-binding site prevents a detailed description of the complexes. Differential epitope mapping (DEEP)-STD NMR, in combination with MD simulations, enables the experimental observation and comparison of two heparin pentasaccharides interacting with AT, revealing slightly different bound orientations and distinct affinities of both glycans for AT. We demonstrate the effectiveness of the differential solvent DEEP-STD NMR approach in determining the presence of polar residues in the recognition sites of glycosaminoglycan-binding proteins.
Insights into Inhalation Drug Disposition: The Roles of Pulmonary Drug-Metabolizing Enzymes and Transporters
Authors: Dong Liuhan , Zhuang Xiaomei
Published: April 2024

The past five decades have witnessed remarkable advancements in the field of inhaled medicines targeting the lungs for respiratory disease treatment. As a non-invasive drug delivery route, inhalation therapy offers numerous benefits to respiratory patients, including rapid and targeted exposure at specific sites, quick onset of action, bypassing first-pass metabolism, and beyond. Understanding the characteristics of pulmonary drug transporters and metabolizing enzymes is crucial for comprehending efficient drug exposure and clearance processes within the lungs. These processes are intricately linked to both local and systemic pharmacokinetics and pharmacodynamics of drugs. This review aims to provide a comprehensive overview of the literature on lung transporters and metabolizing enzymes while exploring their roles in exogenous and endogenous substance disposition. Additionally, we identify and discuss the principal challenges in this area of research, providing a foundation for future investigations aimed at optimizing inhaled drug administration. Moving forward, it is imperative that future research endeavors to focus on refining and validating in vitro and ex vivo models to more accurately mimic the human respiratory system. Such advancements will enhance our understanding of drug processing in different pathological states and facilitate the discovery of novel approaches for investigating lung-specific drug transporters and metabolizing enzymes. This deeper insight will be crucial in developing more effective and targeted therapies for respiratory diseases, ultimately leading to improved patient outcomes.
Comparison of the Snare Loop Technique and the Hungaroring Reinforcement for Physician-Modified Endograft Fenestrations—An In Vitro Study
Authors: Hüttl Artúr , Nguyen Tin Dat , Borzsák Sarolta , Süvegh András , Szentiványi András , Szilvácsku István , Kovács Dóra , Dobránszky János , Sótonyi Péter , Csobay-Novák Csaba
Published: April 2024

Background: We conducted an in vitro comparison of the snare loop reinforcement against a closed-loop reinforcement (Hungaroring) for physician-modified endograft (PMEG) fenestrations regarding preparation time and stability during flaring balloon dilatation. Materials and methods: The time to complete a PMEG fenestration with reinforcement was measured and compared between the Hungaroring and snare loop groups. The number of stitches was counted. Each fenestration was dilated using a 10 mm high-pressure, non-compliant balloon up to 21 atm in pressure, and fluoroscopic images were taken. The presence of indentation on the oversized balloon at the level of the reinforcement was evaluated at each fenestration. Results: Five fenestrations were created in each group (n = 5) for a total of ten pieces. The completion time in the snare loop group was 1070 s (IQR:1010–1090) compared to 760 s (IQR:685–784) in the Hungaroring group (p = 0.008). Faster completion time was achieved by faster stitching (23.2 s/stitch (IQR 22.8–27.3) for the snare loop group and 17.3 s/stitch (IQR 17.3–20.1) for the Hungaroring group (p = 0.016). None of the fluoroscopic images of the snare loop reinforcement showed an indentation on the balloon during the overexpansion; on the contrary, the Hungaroring showed indentation in every case, even at 21 atm. Conclusion: Fenestrations reinforced with Hungaroring can be completed significantly faster. Furthermore, the Hungaroring resists over-dilation even at high pressures, while snare loop reinforcements dilate at nominal pressure.
Current Advances in the Functional Genes of Edible and Medicinal Fungi: Research Techniques, Functional Analysis, and Prospects
Authors: Li Wenyun , Zou Gen , Bao Dapeng , Wu Yingying
Published: April 2024

Functional genes encode various biological functions required for the life activities of organisms. By analyzing the functional genes of edible and medicinal fungi, varieties of edible and medicinal fungi can be improved to enhance their agronomic traits, growth rates, and ability to withstand adversity, thereby increasing yield and quality and promoting industrial development. With the rapid development of functional gene research technology and the publication of many whole-genome sequences of edible and medicinal fungi, genes related to important biological traits have been mined, located, and functionally analyzed. This paper summarizes the advantages and disadvantages of different functional gene research techniques and application examples for edible and medicinal fungi; systematically reviews the research progress of functional genes of edible and medicinal fungi in biological processes such as mating type, mycelium and fruit growth and development, substrate utilization and nutrient transport, environmental response, and the synthesis and regulation of important active substances; and proposes future research directions for functional gene research for edible and medicinal fungi. The overall aim of this study was to provide a valuable reference for further promoting the molecular breeding of edible and medicinal fungi with high yield and quality and to promote the wide application of edible and medicinal fungi products in food, medicine, and industry.
Static Behavior of a 3D-Printed Short Carbon Fiber Polyamide: Influence of the Meso-Structure and Water Content
Authors: Canegrati Andrea , Martulli Luca Michele , Kostovic Milutin , Rollo Gennaro , Sorrentino Andrea , Carboni Michele , Bernasconi Andrea
Published: April 2024

The knowledge of the mechanical behavior of a 3D-printed material is fundamental for the 3D printing outbreaking technology to be considered for a range of applications. In this framework, the significance, reliability, and accuracy of the information obtained by testing material coupons assumes a pivotal role. The present work focuses on an evaluation of the static mechanical properties and failure modes of a 3D-printed short carbon fiber-reinforced polyamide in relation to the specimen’s unique meso-structural morphology and water content. Within the manufacturing limitations of a commercially available printer, specimens of dedicated combinations of geometry and printing patterns were specifically conceived and tested. The specimens’ meso-structure morphologies were investigated by micro-computed tomography. The material failure mechanisms were inferred from an analysis of the specimens’ fracture surfaces and failure morphologies. The outcomes of the present analysis indicate that each test specimen retained proper mechanical properties, thereby suggesting that they should be accurately designed to deliver representative information of the underlying material beads or of their deposition layout. Suggestions on the adoption of preferred test specimens for evaluating specific material properties were proposed.
A Study on the Critical Saturation Response Characteristics of Simple and Sandwich Cylindrical Shells under Long-Duration Blast Loading
Authors: Yang Mao , Zhang Jun , Mu Yunfei , Huang Hanjun , Han Bin , Mao Yongjian
Published: April 2024

Experimental research and numerical simulations of the structural response to shock waves with pulse durations of hundreds of milliseconds, or even seconds, are extremely challenging. This paper takes typical single-layer and sandwich cylindrical shells as the research objects. The response rules of cylindrical shells under long-duration blast loadings were studied. The results show that when the pulse duration is greater than or equal to 4~5 times the first-order period of the structure, the maximum response of the structure tends to be consistent, that is, the maximum response of the cylindrical shells with different vibration shapes shows a saturation effect as the pulse duration increases. This study established the relationship between the saturation loading time and the inherent characteristics of the structure. It was found that the saturation effect was applicable under the following conditions, including different load waveforms, elastic–plastic deformation of the structure, and the loading object being a sandwich shell. This will help transform the long-duration explosion wave problem into a finite pulse-duration shock wave problem that can be realized by both experiments and numerical simulations.
Controlled Synthesis of Triangular Submicron-Sized CeO2 and Its Polishing Performance
Authors: Wang Xingzi , Wang Ning , Zhang Zhenyu , Tan Xianmin , Zheng Yuanyuan , Yang Juanyu
Published: April 2024

CeO2 is widely used in the field of chemical–mechanical polishing for integrated circuits. Morphology, particle size, crystallinity, and Ce3+ concentration are crucial factors that affect polishing performance. In this study, we successfully synthesized two novel triangular CeO2 abrasives with similar particle sizes (600 nm) but different morphologies and Ce3+ concentrations using a microwave-assisted hydrothermal method with high-concentration raw materials, and no surfactants or template agents were added. It is generally believed that CeO2 with a higher Ce3+ concentration leads to better polishing performance. However, the results of polishing indicate that CeO2 synthesized at 200 °C, despite its lower Ce3+ concentration, demonstrates outstanding polishing performance, achieving a polishing rate of 324 nm/min, and the Sa of Si wafers decreased by 3.6% after polishing. This suggests that, under similar particle size conditions, the morphology of CeO2 plays a dominant role in the mechanical effects during the polishing process. Additionally, compared to commercial polishing slurries, the synthesized samples demonstrated better polishing performance. This indicates that, in CMP, the pursuit of smaller spherical abrasives may not be necessary. Instead, the appropriate shape and particle size can better balance the material removal rate and surface roughness.
High-Resolution Ultrasound to Quantify Sub-Surface Wrinkles in a Woven CFRP Laminate
Authors: Amif Md Admay , Jack David A.
Published: April 2024

Carbon fiber reinforced polymer (CFRP) composites are popular materials in the aerospace and automotive industries because of their low weight, high strength, and corrosion resistance. However, wrinkles or geometric distortions in the composite layers significantly reduce their mechanical performance and structural integrity. This paper presents a method for non-destructively extracting the three-dimensional geometry, lamina by lamina, of a laminated composite. A method is introduced for fabricating consistent out-of-plane wrinkled CFRP laminate panels, simulating the in-service wrinkle observed in industries that utilize thick structure composites such as the vertical lift or wind power industries. The individual lamina geometries are extracted from the fabricated coupon with an embedded wrinkle from captured ultrasonic waveforms generated from single-element conventional ultrasonic (UT) scan data. From the extracted waveforms, a method is presented to characterize the wrinkle features within each individual lamina, specifically the spatially varying wrinkle height and intensity for the wrinkle. Parts were fabricated with visibly undetectable wrinkles using a wet layup process and a hot press for curing. Scans were performed in a conventional immersion tank scanning system, and the scan data were analyzed for wrinkle detection and characterization. Extraction of the layers was performed based on tracking the voltage peaks from A-scans in the time domain. Spatial Gaussian averaging was performed to smooth the A-scans, from which the surfaces were extracted for each individual lamina. The extracted winkle surface aligned with the anticipated wrinkle geometry, and a single parameter for quantification of the wrinkle intensity for each lamina is presented.
Rapid Prototyping of Anomalous Reflective Metasurfaces Using Spray-Coated Liquid Metal
Authors: Manio Glan Allan V. , Kouchi Matthew T. , Dacuycuy Saige J. , Ohta Aaron T. , Shiroma Wayne A.
Published: April 2024

Reconfigurable intelligent surfaces (RISs) have the potential to improve wireless communication links by dynamically redirecting signals to dead spots. Although a reconfigurable surface is best suited for environments in which the reflected signal must be dynamically steered, there are cases where a static, non-reconfigurable anomalous reflective metasurface can suffice. In this work, spray-coated liquid metal is used to rapidly prototype an anomalous reflective metasurface. Using a pressurized air gun and a plastic thin-film mask, a metasurface consisting of a 6 × 4 array of Galinstan liquid–metal elements is sprayed within minutes. The metasurface produces a reflected wave at an angle of 28° from normal in response to a normal incident 3.5-GHz electromagnetic plane wave. The spray-coated liquid–metal metasurface shows comparable results to an anomalous reflective metasurface with copper elements of the same dimensions, demonstrating that this liquid–metal fabrication process is a viable solution for the rapid prototyping of anomalous reflective metasurfaces.
Geometric Complexity Control in Topology Optimization of 3D-Printed Fiber Composites for Performance Enhancement
Authors: Wu Tao , Liu Peiqing , Liu Jikai
Published: April 2024

This paper investigates the impact of varying the part geometric complexity and 3D printing process setup on the resulting structural load bearing capacity of fiber composites. Three levels of geometric complexity are developed through 2.5D topology optimization, 3D topology optimization, and 3D topology optimization with directional material removal. The 3D topology optimization is performed with the SIMP method and accelerated by high-performance computing. The directional material removal is realized by incorporating the advection-diffusion partial differential equation-based filter to prevent interior void or undercut in certain directions. A set of 3D printing and mechanical performance tests are performed. It is interestingly found that, the printing direction affects significantly on the result performance and if subject to the uni direction, the load-bearing capacity increases from the 2.5D samples to the 3D samples with the increased complexity, but the load-bearing capacity further increases for the 3D simplified samples due to directional material removal. Hence, it is concluded that a restricted structural complexity is suitable for topology optimization of 3D-printed fiber composites, since large area cross-sections give more degrees of design freedom to the fiber path layout and also makes the inter-layer bond of the filaments firmer.
Genetic Algorithms Application for Pricing Optimization in Commodity Markets
Authors: Li Yiyu , Xu Qingjie , Wang Ying , Liu Bin
Published: April 2024

The perishable nature of vegetable commodities poses challenges for superstores, as reselling them is often unfeasible due to their short freshness period. Reliable market demand analysis is crucial for boosting revenue. This study simplifies the pricing and replenishment decision-making process by making reasonable assumptions about the selling time, wastage rate, and replenishment time for vegetable commodities. A single-objective planning model with the objective of profit maximization was constructed by fitting historical data using the nonparametric method of support vector regression (SVR). The study reveals a specific relationship between sales volume and cost-plus pricing for each category and predicts future cost changes using an LSTM model. Combining these findings, we substitute the relationship between sales volume and pricing as well as the LSTM prediction data into the model, and solve it using genetic algorithms in machine learning to derive the optimal replenishment volume and pricing strategy. Practical results show that the method can provide reasonable pricing and replenishment strategies for vegetable superstores, and after careful accounting, we arrive at an expected profit of RMB 22,703.14. The actual profit of the supermarket was RMB 19,732.89. The method, therefore, increases the profit of the vegetable superstore by 13.08%. By optimizing inventory management and pricing decisions, the superstore can better meet the challenges of vegetable commodities and achieve sustainable development.
Estimating the Complier Average Causal Effect with Non-Ignorable Missing Outcomes Using Likelihood Analysis
Authors: Du Jierui , Wen Gao , Liang Xin
Published: April 2024

Missing data problems arise in randomized trials, which complicates the inference of causal effects if the missing mechanism is non-ignorable. We tackle the challenge of identifying and estimating the complier average causal effect parameters under non-ignorable missingness by increasing the covariates to mitigate the sensitivity to the violation of specific identification assumptions. The missing data mechanism is assumed to follow a logistic model, wherein the absence of the outcome is explained by the outcome itself, the treatment received, and the covariates. We establish the identifiability of the models under mild conditions by assuming that the outcome follows a normal distribution. We develop a computational method to estimate model parameters through a two-step likelihood estimation approach, employing subgroup analysis. The bootstrap method is employed for variance estimation, and the effectiveness of our approach is confirmed through simulation. We applied the proposed method to analyze the household income dataset from the Chinese Household Income Project Survey 2013.
TPTM-HANN-GA: A Novel Hyperparameter Optimization Framework Integrating the Taguchi Method, an Artificial Neural Network, and a Genetic Algorithm for the Precise Prediction of Cardiovascular Disease Risk
Authors: Lin Chia-Ming , Lin Yu-Shiang
Published: April 2024

The timely and precise prediction of cardiovascular disease (CVD) risk is essential for effective prevention and intervention. This study proposes a novel framework that integrates the two-phase Taguchi method (TPTM), the hyperparameter artificial neural network (HANN), and a genetic algorithm (GA) called TPTM-HANN-GA. This framework efficiently optimizes hyperparameters for an artificial neural network (ANN) model during the training stage, significantly enhancing prediction accuracy for cardiovascular disease (CVD) risk. The proposed TPTM-HANN-GA framework requires far fewer experiments than a traditional grid search, making it highly suitable for application in resource-constrained, low-power computers, and edge artificial intelligence (edge AI) devices. Furthermore, the proposed TPTM-HANN-GA framework successfully identified the optimal configurations for the ANN model’s hyperparameters, resulting in a hidden layer of 4 nodes, a tanh activation function, an SGD optimizer, a learning rate of 0.23425849, a momentum rate of 0.75462782, and seven hidden nodes. This optimized ANN model achieves 74.25% accuracy in predicting the risk of cardiovascular disease, which exceeds the existing state-of-the-art GA-ANN and TSTO-ANN models. The proposed TPTM-HANN-GA framework enables personalized CVD prediction to be efficiently conducted on low-power computers and edge-AI devices, achieving the goal of point-of-care testing (POCT) and empowering individuals to manage their heart health effectively.
Sparsity-Constrained Vector Autoregressive Moving Average Models for Anomaly Detection of Complex Systems with Multisensory Signals
Authors: Ma Meng , Zhang Zhongyi , Zhai Zhi , Zhong Zhirong
Published: April 2024

Detecting anomalies in large, complex systems is a critical and challenging task, and this is especially true for high-dimensional anomaly detection due to the underlying dependency structures among sensors. To incorporate the interrelationships among various sensors, a novel sparsity-constrained vector autoregressive moving average (scVARMA) model is proposed for anomaly detection in complex systems with multisensory signals. This model aims to leverage the inherent relationships and dynamics among various sensor readings, providing a more comprehensive and accurate analysis suitable for complex systems’ complex behavior. This research uses convex optimization to search for a parameterization that is sparse based on the principal of parsimony. This sparse model will not only contribute to meeting the real-time requirements of online monitoring strategies but also keeps the correlations among different sensory signals. The performance of the proposed scVARMA model is validated using real-world data from complex systems. The results affirm the superiority of the proposed scheme, demonstrating its enhanced performance and potential in practical applications.
Optimization of the Preparation Process of Glucuronomannan Oligosaccharides and Their Effects on the Gut Microbiota in MPTP-Induced PD Model Mice
Authors: Wang Baoxiang , Geng Lihua , Wang Jing , Wei Yuxi , Yan Changhui , Wu Ning , Yue Yang , Zhang Quanbin
Published: April 2024

Parkinson’s disease (PD) is a prevalent neurodegenerative disorder, and accumulating evidence suggests a link between dysbiosis of the gut microbiota and the onset and progression of PD. In our previous investigations, we discovered that intraperitoneal administration of glucuronomannan oligosaccharides (GMn) derived from Saccharina japonica exhibited neuroprotective effects in a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mouse model. However, the complicated preparation process, difficulties in isolation, and remarkably low yield have constrained further exploration of GMn. In this study, we optimized the degradation conditions in the preparation process of GMn through orthogonal experiments. Subsequently, an MPTP-induced PD model was established, followed by oral administration of GMn. Through a stepwise optimization, we successfully increased the yield of GMn, separated from crude fucoidan, from 1~2/10,000 to 4~8/1000 and indicated the effects on the amelioration of MPTP-induced motor deficits, preservation of dopamine neurons, and elevation in striatal neurotransmitter levels. Importantly, GMn mitigated gut microbiota dysbiosis induced by MPTP in mice. In particular, GM2 significantly reduced the levels of Akkermansia, Verrucomicrobiota, and Lactobacillus, while promoting the abundance of Roseburia and Prevotella compared to the model group. These findings suggest that GM2 can potentially suppress PD by modulating the gut microbiota, providing a foundation for the development of a novel and effective anti-PD marine drug.
3-Ethynyltriimidazo[1,2-a:1′,2′-c:1″,2″-e][1,3,5]triazine Dual Short- and Long-Lived Emissions with Crystallization-Enhanced Feature: Role of Hydrogen Bonds and π-π Interactions
Authors: Malpicci Daniele , Maver Daniele , Rosadoni Elisabetta , Colombo Alessia , Lucenti Elena , Marinotto Daniele , Botta Chiara , Bellina Fabio , Cariati Elena , Forni Alessandra
Published: April 2024

Organic room temperature phosphorescent (ORTP) materials with stimuli-responsive, multicomponent emissive behaviour are extremely desirable for various applications. The derivative of cyclic triimidazole (TT) functionalized with an ethynyl group, TT-CCH, is isolated and investigated. The compound possesses crystallization-enhanced emission (CEE) comprising dual fluorescence and dual phosphorescence of both molecular and supramolecular origin with aggregation-induced components highly sensitive to grinding. The mechanisms involved in the emissions have been disclosed thanks to combined structural, spectroscopic and computational investigations. In particular, strong CH⋯N hydrogen bonds are deemed responsible, for the first time in the TT family, together with frequently observed π⋯π stacking interactions, for the aggregated fluorescence and phosphorescence.
Spatially Resolved, Real-Time Polarization Measurement Using Artificial Birefringent Metallic Elements
Authors: Belle Stefan , Kefer Stefan , Hellmann Ralf
Published: April 2024

Polarization states define a fundamental property in optics. Consequently, polarization state characterization is essential in many areas of both field industrial applications and scientific research. However, a full identification of space-variant Stokes parameters faces great challenges, like multiple power measurements. In this contribution, we present a spatially resolved polarization measurement using artificial birefringent metallic elements, the so-called hollow waveguides. Differently oriented and space-variant hollow waveguide arrays, a stationary analyzer and a CMOS camera form the basis of the experimental setup for one single spatially resolved power measurement. From this power measurement, the Stokes parameters can be calculated in quasi-real-time, with a spatial resolution down to 50 μm in square. The dimensions of the individual hollow waveguides, which are less than or equal to the employed wavelength, determine the spectral range, here in the near infrared around λ = 1550 nm. This method allows for the rapid and compact determination of spatially resolved Stokes parameters, which is experimentally confirmed using defined wave plates, as well as an undefined injection-molded polymer substrate.
Phenotypic Variability in Resistance to Anthracnose, White, Brown, and Blight Leaf Spot in Cassava Germplasm
Authors: Nascimento José Henrique Bernardino , Andrade Luciano Rogerio Braatz de , Oliveira Saulo Alves Santos de , Oliveira Eder Jorge de
Published: April 2024

Despite fungal diseases affecting the aerial parts of cassava (Manihot esculenta Crantz) and causing significant yield losses, there is a lack of comprehensive studies assessing resistance in the species’ germplasm. This study aimed to evaluate the phenotypic diversity for resistance to anthracnose disease (CAD), blight leaf spot (BliLS), brown leaf spot (BLS), and white leaf spot (WLS) in cassava germplasm and to identify genotypes suitable for breeding purposes. A total of 837 genotypes were evaluated under field conditions across two production cycles (2021 and 2022). Artificial inoculations were carried out in the field, and data on yield and disease severity were collected using a standardized rating scale. The top 25 cassava genotypes were selected based on a selection index for disease resistance and agronomic traits. High environmental variability resulted in low heritabilities (h2) for CAD, WLS, and BLS (h2 = 0.42, 0.34, 0.29, respectively) and moderate heritability for BliLS (h2 = 0.51). While the range of data for disease resistance was narrow, it was considerably wider for yield traits. Cluster analysis revealed that increased yield traits and disease severity were associated with higher scores of the first and second discriminant functions, respectively. Thus, most clusters comprised genotypes with hybrid characteristics for both traits. Overall, there was a strong correlation among aerial diseases, particularly between BLS and BliLS (r = 0.96), while the correlation between CAD and other diseases ranged from r = 0.53 to 0.58. Yield traits showed no significant correlations with disease resistance. Although the mean selection differential for disease resistance was modest (between −2.31% and −3.61%), selection based on yield traits showed promising results, particularly for fresh root yield (82%), dry root yield (39%), shoot yield (49%), and plant vigor (26%). This study contributes to enhancing genetic gains for resistance to major aerial part diseases and improving yield traits in cassava breeding programs.