bluuebunny/crossref_metadata_2025 huggingface dataset:
A Multi-Faceted Exploration Incorporating Question Difficulty in Knowledge Tracing for English Proficiency Assessment
Authors: Kim Jinsung , Koo Seonmin , Lim Heuiseok
Published: October 2023

Knowledge tracing (KT) aims to trace a learner’s understanding or achievement of knowledge based on learning history. The surge in online learning systems has intensified the necessity for automated measurement of students’ knowledge states. In particular, in the case of learning in the English proficiency assessment field, such as TOEIC, it is required to model the knowledge states by reflecting on the difficulty of questions. However, previous KT approaches often overly complexify their model structures solely to accommodate difficulty or consider it only for a secondary purpose such as data augmentation, hindering the adaptability of potent and general-purpose models such as Transformers to other cognitive components. Addressing this, we investigate the integration of question difficulty within KT with a potent general-purpose model for application in English proficiency assessment. We conducted empirical studies with three approaches to embed difficulty effectively: (i) reconstructing input features by incorporating difficulty, (ii) predicting difficulty with a multi-task learning objective, and (iii) enhancing the model’s output representations from (i) and (ii). Experiments validate that direct inclusion of difficulty in input features, paired with enriched output representations, consistently amplifies KT performance, underscoring the significance of holistic consideration of difficulty in the KT domain.
Inverter Fault Diagnosis for a Three-Phase Permanent-Magnet Synchronous Motor Drive System Based on SDAE-GAN-LSTM
Authors: Feng Li , Luo Honglin , Xu Shuiqing , Du Kenan
Published: October 2023

In this study, a novel intelligent inverter fault diagnosis approach based on a stacked denoising autoencoder–generative adversarial network–long short-term memory (SDAE-GAN-LSTM) under an imbalanced sample is proposed for a three-phase permanent-magnet synchronous motor (PMSM) drive system. The proposed method can address the problem of unbalanced fault data samples and improve the accuracy of fault classification. Concretely speaking, firstly, the stacked denoising autoencoder (SDAE) is pre-trained to obtain the optimum decoder network. Afterward, a new generator of generative adversarial networks (GANs) is designed to generate high-quality samples by migrating the pre-trained optimal decoder network to the hidden layer and output layer of the generator of GANs. Additionally, a new model of long short-term memory (LSTM) based on the second discriminator of the GANs is presented for fault diagnosis. The generator of GANs is cross-trained using the reconstruction error gained by SDAE and the fault diagnosis error obtained by LSTM, resulting in the generation of high-quality samples for fault discrimination. Simulation and experimental results demonstrate the effectiveness of the proposed fault diagnosis approach, and the average fault identification accuracy reaches 98.63%.
Toward Unified and Quantitative Cinematic Shot Attribute Analysis
Authors: Li Yuzhi , Tian Feng , Xu Haojun , Lu Tianfeng
Published: October 2023

Cinematic Shot Attribute Analysis aims to analyze the intrinsic attributes of movie shots, such as movement and scale. In previous methods, specialized architectures were designed for each specific task and relied on the use of optical flow maps. In this paper, we consider shot attribute analysis as a unified task of motion–static weight allocation, and propose a motion–static dual-path architecture for recognizing various shot attributes. In this architecture, we design a new action cue generation module for adapting the end-to-end training process instead of a pre-trained optical flow network; and, to address the issue of limited samples in movie shot datasets, we design a fixed-size adjustment strategy to enable the network to directly utilize pre-trained vision transformer models while adapting to shot data inputs at arbitrary sample rates. In addition, we quantitatively analyze the sensitivity of different shot attributes to motion and static features for the first time. Subsequent experimental results on two datasets, MovieShots and AVE, demonstrate that our proposed method outperforms all previous approaches without increasing computational cost.
Optimization of Multi-Phase Motor Drive System Design through Thermal Analysis and Experimental Validation of Heat Dissipation
Authors: Park Jun-Shin , Lee Tae-Woo , Lee Jae-Woon , Park Byoung-Gun , Kim Ji-Won
Published: October 2023

In power semiconductor systems such as inverters, managing losses is critical for optimizing performance. Inverters, which convert DC to AC for applications such as renewable energy systems, motor drives, and power supplies, are significantly affected by the thermal performance of components such as metal-oxide-semiconductor field-effect transistors (MOSFETs). Efficient thermal management is critical for the longevity and performance of power electronic systems, especially in high-power applications. Designing effective thermal management strategies for inverters reduces losses, increases efficiency, and improves performance while considering space constraints and complex component interactions. In this study, power electronics simulations and computational fluid dynamics (CFD) thermal analysis were integrated to design the inverter. Using an integrated simulation, a thermal analysis was performed based on the inverter losses per module. A power electronics simulation was used to verify the validity of the loss values in the inverter design, and the CFD thermal analysis facilitated the visual analysis of the variables to be considered. The validity of the design was evaluated through experimental verification of the inverter system. A temperature saturation of 63.9 ℃ at 60Arms was recorded in the simulation, and a temperature saturation of 45 ℃ or less at 59Arms to 60Arms was obtained for each phase in the actual test. Considering the ambient temperature difference, it showed a difference of approximately 9.9 ℃. This conclusion allows us to reduce the high probability of risk derived by considering a small margin of safety for each variable in the design. This solution can be used to compactly design real inverters and solve complex thermal problems in power semiconductor-based systems. Finally, this study analyzes the similarities and differences between CFD simulations, power electronics simulations, and real-world experimental validation, highlighting the importance of thermal management in improving the efficiency of power electronic systems, particularly inverters.
RepRCNN: A Structural Reparameterisation Convolutional Neural Network Object Detection Algorithm Based on Branch Matching
Authors: Li Xudong , Lv Xinyao , Sun Linghui , Zhang Jingzhi , Lan Ruoming
Published: October 2023

A CNN object detection method based on the structural reparameterisation technique using branch matching is proposed to address the problem of balancing accuracy and speed in object detection techniques. By the structural reparameterisation of the convolutional layer in the object detection network, the amount of computation and the number of parameters in the network inference are reduced, the memory overhead is lowered, and the use of the branch-matching method to improve the structural reparameterisation model improves the computational efficiency and speed of the network while maintaining the detection accuracy. Optimisation is also carried out in terms of target screening and loss function, and a new CPC NMS screening strategy was introduced to further improve the performance of the model. The experimental results show that the proposed method achieves competitive results on the PASCAL VOC2012 and MS COCO2017 datasets compared to the traditional object detection methods and the current mainstream models, achieving a better balance between the detection accuracy and detection speed.
Semantic Positioning Model Incorporating BERT/RoBERTa and Fuzzy Theory Achieves More Nuanced Japanese Adverb Clustering
Authors: Odle Eric , Hsueh Yun-Ju , Lin Pei-Chun
Published: October 2023

Japanese adverbs are difficult to classify, with little progress made since the 1930s. Now in the age of large language models, linguists need a framework for lexical grouping that incorporates quantitative, evidence-based relationships rather than purely theoretical categorization. We herein address this need for the case of Japanese adverbs by developing a semantic positioning approach that incorporates large language model embeddings with fuzzy set theory to achieve empirical Japanese adverb groupings. To perform semantic positioning, we (i) obtained multi-dimensional embeddings for a list of Japanese adverbs using a BERT or RoBERTa model pre-trained on Japanese text, (ii) reduced the dimensionality of each embedding by principle component analysis (PCA), (iii) mapped the relative position of each adverb in a 3D plot using K-means clustering with an initial cluster count of n=3, (iv) performed silhouette analysis to determine the optimal cluster count, (v) performed PCA and K-means clustering on the adverb embeddings again to generate 2D semantic position plots, then finally (vi) generated a centroid distance matrix. Fuzzy set theory informs our workflow at the embedding step, where the meanings of words are treated as quantifiable vague data. Our results suggest that Japanese adverbs optimally cluster into n=4 rather than n=3 groups following silhouette analysis. We also observe a lack of consistency between adverb semantic positions and conventional classification. Ultimately, 3D/2D semantic position plots and centroid distance matrices were simple to generate and did not require special hardware. Our novel approach offers advantages over conventional adverb classification, including an intuitive visualization of semantic relationships in the form of semantic position plots, as well as a quantitative clustering “fingerprint” for Japanese adverbs that express vague language data as a centroid distance matrix.
Digital Twins Temporal Dependencies-Based on Time Series Using Multivariate Long Short-Term Memory
Authors: Isah Abubakar , Shin Hyeju , Oh Seungmin , Oh Sangwon , Aliyu Ibrahim , Um Tai-won , Kim Jinsul
Published: October 2023

Digital Twins, which are virtual representations of physical systems mirroring their behavior, enable real-time monitoring, analysis, and optimization. Understanding and identifying the temporal dependencies included in the multivariate time series data that characterize the behavior of the system are crucial for improving the effectiveness of Digital Twins. Long Short-Term Memory (LSTM) networks have been used to represent complex temporal dependencies and identify long-term links in the Industrial Internet of Things (IIoT). This paper proposed a Digital Twin temporal dependency technique using LSTM to capture the long-term dependencies in IIoT time series data, estimate the lag between the input and intended output, and handle missing data. Autocorrelation analysis showed the lagged links between variables, aiding in the discovery of temporal dependencies. The system evaluated the LSTM model by providing it with a set of previous observations and asking it to forecast the value at future time steps. We conducted a comparison between our model and six baseline models, utilizing both the Smart Water Treatment (SWaT) and Building Automation Transaction (BATADAL) datasets. Our model’s effectiveness in capturing temporal dependencies was assessed through the analysis of the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF). The results of our experiments demonstrate that our enhanced model achieved a better long-term prediction performance.
Frontal Lobe Functions and Quality of Life in Individuals with Obesity with and without Binge Eating Disorder
Authors: Gameiro Fátima , Rosa Beatriz , Faria Miguel
Published: October 2023

Frontal lobe functions (FLFs) play an important role in human behavioral regulation and can be a determinant of eating behavior. The aim of this study was to analyse FLFs in individuals with obesity, with and without binge eating disorder (BED), compared to individuals with normal weight (NW), and to analyse the effect of sex and binge disorder on quality of life, with age and BMI as covariates. A total of 114 participants, comprising three different groups (NW individuals, individuals with obesity but without BED, and individuals with obesity and BED), completed the Frontal Assessment Battery (FAB) and Impact of Weight on Quality of Life (IWQOL-lite) questionnaires. The results showed that individuals with obesity, with and without BED, have poorer frontal lobe functioning than the NW group. Individuals with obesity and BED have lower performance in terms of FLFs than individuals with obesity but without BED. Male participants have a higher perception of quality of life in all dimensions, with women showing lower values in self-esteem and sex life. Individuals with obesity and BED show greater weaknesses in physical function. These results suggest that low FLFs and worse quality of life characterize individuals with obesity, and this is more evident in these individuals with BED.
Evaluation of the Black Tea Taste Quality during Fermentation Process Using Image and Spectral Fusion Features
Authors: An Ting , Yang Chongshan , Zhang Jian , Wang Zheli , Fan Yaoyao , Fan Shuxiang , Huang Wenqian , Qi Dandan , Tian Xi , Yuan Changbo , Dong Chunwang
Published: October 2023

The rapid and intelligent evaluation of black tea taste quality during the fermentation process is an unsolved problem because of the complexity and hysteretic of the current taste evaluation method. Common infrared spectroscopy and machine vision technologies can rapidly evaluate the taste quality of black tea, but they can not obtain comprehensive sample information. To obtain comprehensive sample information and achieve the rapid evaluation of the taste quality of black tea, the fusion data from hyperspectral images of fermentation samples were applied to predict the taste quality. The successive projection algorithm (SPA) and ant colony optimization (ACO) were used to select effective bands for spectral data. Subsequently, the color images were synthesized using three carefully selected effective bands obtained through the SPA and ACO. The 18 image features were extracted from each synthesized color image and fused with spectral effective bands. The fusion data and three different algorithms, such as partial least squares regression (PLSR), support vector machine regression (SVR), and extreme learning machine (ELM), were employed to establish the regression model for taste quality. Specifically, the fusion-SPA-PLSR model exhibited the best performance. This study provides a novel method for the intelligent evaluation of taste quality during black tea fermentation and lays a theoretical foundation for the intelligent processing and control of black tea.
Got Whey? Sustainability Endpoints for the Dairy Industry through Resource Biorecovery
Authors: Giulianetti de Almeida Maria Paula , Mockaitis Gustavo , Weissbrodt David G.
Published: October 2023

Whey has applications in food, beverages, personal care products, pharmaceuticals, and the medical sector. However, it remains a massive dairy residue worldwide (160.7 million m3 year−1), with high organic and nutrient loads. About 42% is used for low-value products such as animal feed and fertilizers or is even directly discharged into water streams, leading to ecosystem damage via eutrophication. We reviewed the uses and applications of cheese whey, along with associated environmental impacts and innovative ways to mitigate them using affordable and scalable technologies. Recycling and repurposing whey remain challenges for remote locations and poor communities with limited access to expensive technology. We propose a closed-loop biorefinery strategy to simultaneously mitigate environmental impacts and valorize whey resources. Anaerobic digestion utilizes whey to produce biogas and/or carboxylates. Alternative processes combining anaerobic digestion and low-cost open photobioprocesses can valorize whey and capture organic, nitrogenous, and phosphorous nutrients into microalgal biomass that can be used as food and crop supply or processed into biofuels, pigments, and antioxidants, among other value-added products. The complete valorization of cheese whey also depends on facilitating access to relevant information on whey production, identifying stakeholders, reducing technology gaps among countries, enforcing legislation and compliance, and creating subsidies and fostering partnerships with industries and between countries.
Overcoming Challenges and Limitations Regarding the Atomic Force Microscopy Imaging and Mechanical Characterization of Nanofibers
Authors: Kontomaris Stylianos Vasileios , Stylianou Andreas , Chliveros Georgios , Malamou Anna
Published: October 2023

Atomic force microscopy (AFM) is a powerful tool that enables imaging and nanomechanical properties characterization of biological materials. Nanofibers are the structural units of many biological systems and their role in the development of advanced biomaterials is crucial. AFM methods have proven to be effective towards the characterization of fibers with respect to biological and bioengineering applications at the nanoscale. However, both the topographical and mechanical properties’ nanocharacterizations of single fibers using AFM are challenging procedures. In particular, regarding imaging procedures, significant artifacts may arise from tip convolution effects. The geometrical characteristics of the AFM tip and the nanofibers, and the fact that they have similar magnitudes, may lead to significant errors regarding the topographical imaging. In addition, the determination of the mechanical properties of nanofibers is also challenging due to their small dimensions and heterogeneity (i.e., the elastic half-space assumption is not valid in most cases). This review elucidates the origins of errors in characterizing individual nanofibers, while also providing strategies to address limitations in experimental procedures and data processing.
Effect of Edible Coating Made from Arrowroot Flour and Kaffir Lime Leaf Essential Oil on the Quality Changes of Pork Sausage under Prolonged Refrigerated Storage
Authors: Venkatachalam Karthikeyan , Ieamkheng Supaporn , Noonim Paramee , Lekjing Somwang
Published: October 2023

Edible coatings are pivotal in enhancing the quality of processed meat products, acting as barriers to environmental and microbial influences by adhering directly to the food surface. Arrowroot flour, a widely produced edible tuber in Thailand, is uncharted in terms of its capability and effectiveness as an edible coating on food materials. This study aims to elucidate the composition and spectral properties of arrowroot tuber flour (ATF) to discern its viability as an edible coating for pork sausages. ATF exhibited a composition predominantly featuring carbohydrates (74.78%), moisture (9.59%), and protein (8.89%), underlining its appropriateness as an edible coating. Rapid visco amylograph revealed ATF’s significant pasting capability. This study incorporated kaffir lime leaves essential oil (KEO) into the ATF coating in diverse concentrations (0–3%). Fourier-transform Infrared spectroscopy illuminated characteristic peaks and bands, showing observable shifts with the integration of KEO, yet the majority of peak placements remained essentially unchanged. The microstructure of the coatings maintained its homogeneity at heightened KEO concentrations, reflecting compatibility with ATF. The efficacy of the ATF-KEO coatings was evaluated on pork sausages, using uncoated samples as controls. While color modifications were evident, coated sausages maintained consistent moisture content, water activity, and pH levels throughout the storage duration. The coated samples also manifested enhanced textural attributes and a decline in lipid oxidation, as evidenced by reduced TBARS levels compared to controls. A subsequent microbial examination corroborated the inhibitory capacity of the ATF-KEO coatings on the microbial proliferation in pork sausages, encapsulating Total Viable Count (TVC), psychrotrophic bacteria, and lactic acid bacteria. In conclusion, the findings substantiate the promising application of ATF, especially in synergy with KEO, as a proficient edible coating for meat products. This combination aids in preserving color and texture, impeding microbial advancement, and moderating lipid oxidation, thereby contributing to the overall quality and safety of the products.
Fabrication and Characterization of Complex Coacervation: The Integration of Sesame Protein Isolate-Polysaccharides
Authors: Dong Zeng , Yu Shirong , Zhai Kefeng , Bao Nina , Rashed Marwan M. A. , Wu Xiao
Published: October 2023

The exceptional biocompatibility of emulsion systems that rely on stabilizing protein–polysaccharide particles presents extensive possibilities for the transportation of bioactive carriers, making them highly promising for various biological applications. The current work aimed to explore the phenomenon of complex coacervation between sesame protein isolate (SPI) and four distinct polysaccharides, namely, Arabic gum (GA), carrageenan (CAR), sodium carboxymethyl cellulose (CMC), and sodium alginate (SA). The study objective was achieved by fabricating emulsions through the blending of these polymers with oil at their maximum turbidity level (φ = 0.6), followed by the measurement of their rheological properties. The turbidity, ζ-potential, and particle size were among the techno-parameters analyzed to assess the emulsion stability. The microstructural characterization of the emulsions was conducted using both transmission electron microscopy (TEM) and scanning electron microscopy (SEM). Furthermore, the functional properties were examined using Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The SPI incorporated with SA, CMC, and CAR reached the maximum turbidity (0.2% w/v) at a ratio of 4:1, corresponding to the pH values of 4.5, 3, or 3.5, respectively. The SPI–GA mixture exhibited the maximum turbidity at a ratio of 10:1 and pH 4.5. Results from the FTIR and XRD analyses provided evidence of complex formation between SPI and the four polysaccharides, with the electrostatic and hydrogen bond interactions facilitating the binding of SPI to these polysaccharides. SPI was bound to the four polysaccharides through electrostatic and hydrogen bond interactions. The SPI–CMC and SPI–SA emulsions were more stable after two weeks of storage.
Would Altruistic Consumers Place A Higher Value on Sustainable Foods?
Authors: Li Haoyang , Lin Wen
Published: October 2023

To advance sustainable food systems, it is necessary to explore consumer preferences and valuations of sustainable food labels. This study utilizes a discrete choice experiment to examine consumers’ willingness to pay for various sustainable labels using a 12 oz ground coffee package and investigates the impact of altruism orientation on consumer valuation of sustainable coffee. The results from US consumers surveyed in spring 2020 indicate that the USDA organic claim commands the highest price premium, followed by the Carbon Trust and Fairtrade labels. Furthermore, individuals’ altruism orientation positively and significantly influences their preference and willingness to pay for sustainable labels, with selfless individuals valuing them more. These findings offer insights into effectively promoting sustainable food consumption through targeting consumer subgroups and prioritizing fair trade and organic foods over newer green labels.
Re-Rolling Treatment in the Fermentation Process Improves the Aroma Quality of Black Tea
Authors: Chen Qincao , Yu Penghui , Li Ziyi , Wang Yuhang , Liu Yafang , Zhu Yin , Fu Haihui
Published: October 2023

Aroma is a vital factor influencing tea quality and value. It is a challenge to produce a kind of black tea with a floral/fruity aroma, good taste, and without a green/grassy odor simultaneously using small- and medium-leaf tea species. In this study, the effect of re-rolling treatment on the aroma quality of small-leaf Congou black tea was investigated using the methods of the equivalent quantification of aroma and gas chromatography–mass spectrometry (GC-MS). Sensory evaluation showed that re-rolling treatment improved the aroma quality of Congou black tea by conferring upon it floral and fruity scents. In total, 179 volatile compounds were identified using GC-MS, of which 97 volatiles showed statistical differences (Tukey s-b(K), p < 0.05). Re-rolling treatment significantly reduced the levels of alcoholic fatty acid-derived volatiles (FADVs) and volatile terpenoid (VTs), but increased the levels of aldehydic and ester FADVs, most amino acid-derived volatiles (AADVs), carotenoid-derived volatiles (CDVs), alkene VTs, and some other important volatile compounds. Based on the odor characteristics and fold changes of differential volatile compounds, hexanoic acid, hexyl formate, cis-3-hexenyl hexanoate, (Z)-3-hexenyl benzoate, hexyl hexanoate, phenylacetaldehyde, benzyl alcohol, β-ionone, α-ionone, dihydroactinidiolide, ipsenone, β-farnesene, β-octalactone, melonal, etc., were considered as the potential key odorants responsible for the floral and fruity scents of re-rolled black tea. In summary, this study provides a novel and simple processing technology to improve the aroma quality of small-leaf Congou black tea, and the results are beneficial to enriching tea aroma chemistry.
Untargeted Metabolomics and Physicochemical Analysis Revealed the Quality Formation Mechanism in Fermented Milk Inoculated with Lactobacillus brevis and Kluyveromyces marxianus Isolated from Traditional Fermented Milk
Authors: Ao Xiao-Lin , Liao Yi-Mo , Kang Hai-Yan , Li Hong-Li , He Tian , Zou Li-Kou , Liu Shu-Liang , Chen Shu-Juan , Yang Yong , Liu Xing-Yan
Published: October 2023

Traditional fermented milk from the western Sichuan plateau of China has a unique flavor and rich microbial diversity. This study explored the quality formation mechanism in fermented milk inoculated with Lactobacillus brevis NZ4 and Kluyveromyces marxianus SY11 (MFM), the dominant microorganisms isolated from traditional dairy products in western nan. The results indicated that MFM displayed better overall quality than the milk fermented with L. brevis NZ4 (LFM) and K. marxianus SY11 (KFM), respectively. MFM exhibited good sensory quality, more organic acid types, more free amino acids and esters, and moderate acidity and ethanol concentrations. Non-targeted metabolomics showed a total of 885 metabolites annotated in the samples, representing 204 differential metabolites between MFM and LFM and 163 between MFM and KFM. MFM displayed higher levels of N-acetyl-L-glutamic acid, cysteinyl serine, glaucarubin, and other substances. The differential metabolites were mainly enriched in pathways such as glycerophospholipid metabolism, arginine biosynthesis, and beta-alanine metabolism. This study speculated that L. brevis affected K. marxianus growth via its metabolites, while the mixed fermentation of these strains significantly changed the metabolism pathway of flavor-related substances, especially glycerophospholipid metabolism. Furthermore, mixed fermentation modified the flavor and quality of fermented milk by affecting cell growth and metabolic pathways.
An Update on the Pivotal Roles of Probiotics, Their Components, and Metabolites in Preventing Colon Cancer
Authors: Deng Xue , Yang Jing , Zhang Yu , Chen Xiaoyong , Wang Chen , Suo Huayi , Song Jiajia
Published: October 2023

Diet, lifestyle, and gut microbiota composition are key risk factors for the progression of colon cancer. Probiotics are living microorganisms that can offer health benefits to the parasitifer when ingested in competent quantities. Several in vivo, in vitro, and clinical studies have demonstrated that probiotics can prevent and mitigate the development of colon cancer. The anti-colon cancer mechanisms of probiotics include the suppression of cell proliferation and the promotion of cancer cell apoptosis, immunomodulation, the modulation of intestinal microorganisms and their metabolism, strengthening the intestinal barrier, and antioxidant effects. This article describes the pathogenesis of colon cancer and the available therapeutic options. In addition, this paper reviews the mechanisms by which probiotics mitigate colon cancer as well as the mitigating effects of probiotic components and metabolites on colon cancer.
Effect of Physical Modifications on Physicochemical and Functional Properties of Walnut Protein
Authors: Li Shanshan , Liu Zhe , Hei Xue , Wu Chao , Ma Xiaojie , Hu Hui , Jiao Bo , Zhu Jinjin , Adhikari Benu , Wang Qiang , Shi Aimin
Published: October 2023

Walnut protein is a high-quality vegetable protein with promising applications in the food industry; however, its potential is hindered by low solubility and associated properties. We utilized various physical modification techniques (cold plasma; ball milling; superfine grinding; ultrasound; wet ball milling; and high-pressure microjet) to enhance walnut proteins’ physicochemical and functional properties. The changes in particle size, microstructure, surface hydrophobicity, fluorescence, solubility, foaming, and emulsification were investigated. Cold plasma and ultrasound treatments minimally affected particle size and morphology. Cold plasma increased the particle size D4,3 from 145.20 μm to 152.50 μm. Ultrasonication reduced the particle size D4,3 to 138.00 μm. The variation was within ±10 μm, while the particle size of walnut protein significantly decreased after the other four modification treatments. The greatest variation in particle size was in the superfine grinding, with the D4,3 being reduced to 23.80 μm. Ultrasound treatment converted the β-sheet into an α-helix, while the other methods transformed the α-helix into a β-sheet. The dispersion stability notably improved after wet ball milling and high-pressure microjet treatments, which was accompanied by a significant increase in solubility from 6.9% (control) to 13.6% (wet ball milling) and 31.7% (high-pressure microjet). The foaming and emulsification properties were also enhanced through these modifications (foaming improved from 47% to 55.33% and emulsification improved from 4.32 m2/g to 8.27 m2/g). High-pressure microjet treatment proved most effective at improving solubility in the functional properties of walnut protein. These findings are expected to help broaden the potential utilization of walnut protein in the food industry, including in beverages and emulsions.
Stepanov Almost Periodic Type Functions and Applications to Abstract Impulsive Volterra Integro-Differential Inclusions
Authors: Kostić Marko , Du Wei-Shih
Published: October 2023

In this paper, we analyze various classes of Stepanov-p-almost periodic functions and Stepanov-p-almost automorphic functions (p>0). The class of Stepanov-p-almost periodic (automorphic) functions in norm (p>0) is also introduced and analyzed. Some structural results for the introduced classes of functions are clarified. We also provide several important theoretical examples, useful remarks and some new applications of Stepanov-p-almost periodic type functions to the abstract (impulsive) first-order differential inclusions and the abstract (impulsive) fractional differential inclusions.
Hotel Comment Emotion Classification Based on the MF-DFA and Partial Differential Equation Classifier
Authors: Duanzhu Sangjie , Wang Jian , Jia Cairang
Published: October 2023

Due to the significant value that hotel reviews hold for both consumers and businesses, the development of an accurate sentiment classification method is crucial. By effectively distinguishing the authenticity of reviews, consumers can make informed decisions, and businesses can gain insights into customer feedback to improve their services and enhance overall competitiveness. In this paper, we propose a partial differential equation model based on phase-field for sentiment analysis in the field of hotel comment texts. The comment texts are converted into word vectors using the Word2Vec tool, and then we utilize the multifractal detrended fluctuation analysis (MF-DFA) model to extract the generalized Hurst exponent of the word vector time series to achieve dimensionality reduction of the word vector data. The dimensionality reduced data are represented in a two-dimensional computational domain, and the modified Allen–Cahn (AC) function is used to evolve the phase values of the data to obtain a stable nonlinear boundary, thereby achieving automatic classification of hotel comment texts. The experimental results show that the proposed method can effectively classify positive and negative samples and achieve excellent results in classification indicators. We compared our proposed classifier with traditional machine learning models and the results indicate that our method possesses a better performance.
Centralized versus Decentralized Cleanup of River Water Pollution: An Application to the Ganges
Authors: Batabyal Amitrajeet A. , Beladi Hamid
Published: October 2023

We exploit the public good attributes of Ganges water pollution cleanup and theoretically analyze an aggregate economy of two cities—Kanpur and Varanasi—through which the Ganges flows. Our specific objective is to study whether water pollution cleanup in these two cities ought to be provided in a centralized or in a decentralized manner. We first determine the efficient cleanup amounts that maximize the aggregate surplus from making the Ganges cleaner in the two cities. Second, we compute the optimal amount of water pollution cleanup in the two cities in a decentralized regime in which spending on cleanup is financed by a uniform tax on the city residents. Third, we ascertain the optimal amount of water pollution cleanup in the two cities in a centralized regime subject to equal provision of cleanup and cost sharing. Fourth, we show that if the two cities have the same preference for pollution cleanup, then centralization is preferable to decentralization as long as there is a spillover from pollution cleanup. Finally, we show that if the two cities have dissimilar preferences for pollution cleanup, then centralization is preferable to decentralization as long as the spillover exceeds a certain threshold.
Genome Sequencing of Consanguineous Family Implicates Ubiquitin-Specific Protease 53 (USP53) Variant in Psychosis/Schizophrenia: Wild-Type Expression in Murine Hippocampal CA 1–3 and Granular Dentate with AMPA Synapse Interactions
Authors: Kanwal Ambreen , Sheikh Sohail A. , Aslam Faiza , Yaseen Samina , Beetham Zachary , Pankratz Nathan , Clabots Connie R. , Naz Sadaf , Pardo José V.
Published: October 2023

Psychosis is a severe mental disorder characterized by abnormal thoughts and perceptions (e.g., hallucinations) occurring quintessentially in schizophrenia and in several other neuropsychiatric disorders. Schizophrenia is widely considered as a neurodevelopmental disorder that onsets during teenage/early adulthood. A multiplex consanguineous Pakistani family was afflicted with severe psychosis and apparent autosomal recessive transmission. The first-cousin parents and five children were healthy, whereas two teenage daughters were severely affected. Structured interviews confirmed the diagnosis of DSM-V schizophrenia. Probands and father underwent next-generation sequencing. All available relatives were subjected to confirmatory Sanger sequencing. Homozygosity mapping and directed a priori filtering identified only one rare variant [MAF < 5(10)−5] at a residue conserved across vertebrates. The variant was a non-catalytic deubiquitinase, USP53 (p.Cys228Arg), predicted in silico as damaging. Genome sequencing did not identify any other potentially pathogenic single nucleotide variant or structural variant. Since the literature on USP53 lacked relevance to mental illness or CNS expression, studies were conducted which revealed USP53 localization in regions of the hippocampus (CA 1–3) and granular dentate. The staining pattern was like that seen with GRIA2/GluA2 and GRIP2 antibodies. All three proteins coimmunoprecipitated. These findings support the glutamate hypothesis of schizophrenia as part of the AMPA-R interactome. If confirmed, USP53 appears to be one of the few Mendelian variants potentially causal to a common-appearing mental disorder that is a rare genetic form of schizophrenia.
Effect of Glucose Supplementation on Apoptosis in the Pectoralis major of Chickens Raised under Thermoneutral or Heat Stress Environment
Authors: Kwakye Josephine , Ariyo Oluwatomide W. , Ghareeb Ahmed F. A. , Hartono Evan , Sovi Selorm , Aryal Bikash , Milfort Marie C. , Fuller Alberta L. , Rekaya Romdhane , Aggrey Samuel E.
Published: October 2023

Reduced feed intake during heat stress (HS) disrupts glucose homeostasis, thereby resulting in endoplasmic reticulum (ER) stress and triggering apoptosis in chickens. We hypothesize that glucose supplementation could reduce apoptosis in chickens raised under HS. This study comprised 456 28-day-old broiler chickens randomly assigned to four treatment combinations under glucose supplementation and HS. The treatments were TN0, TN6, HS0, and HS6 with two glucose levels (0% and 6%) and two temperature levels (25 °C (thermoneutral-TN) and 35 °C (8.00 AM to 8.00 PM, (HS)). After 7 days post-HS, the blood glucose level for the HS6 group was higher than for TN0, TN6, and HS0. We studied the mRNA expression of genes and caspase-3 activity in the four experimental groups. The expressions of GCN2, ATF4, CHOP, and FOXO3a increased during HS regardless of glucose supplementation, while PERK and MAFbx increased only under HS with glucose supplementation. We show that under TN conditions, glucose supplementation led to a significant increase in cellular apoptosis in the Pectoralis (P.) major. However, under HS with glucose, the level of apoptosis was similar to that of chickens raised under TN conditions with no glucose supplementation. The utility of glucose to curtail apoptosis under HS should be tested under other intense models of HS.
Metamorphic Remnants of the Variscan Orogeny across the Alps and Their Tectonic Significance
Authors: Roda Manuel , Spalla Maria Iole , Filippi Marco , Lardeaux Jean-Marc , Rebay Gisella , Regorda Alessandro , Zanoni Davide , Zucali Michele , Gosso Guido
Published: October 2023

Lithospheric slices preserving pre-Alpine metamorphic imprints are widely described in the Alps. The Variscan parageneses recorded in continental, oceanic, and mantle rocks suggest a heterogeneous metamorphic evolution across the Alpine domains. In this contribution, we collect quantitative metamorphic imprints and ages of samples that document Variscan tectonometamorphic evolution from 420 to 290 Ma. Based on age distribution and metamorphic imprint, three main stages can be identified for the Variscan evolution of the Alpine region: Devonian (early Variscan), late Devonian–late Carboniferous (middle Variscan), and late Carboniferous–early Permian (late Variscan). The dominant metamorphic imprint during Devonian times was recorded under eclogite and HP granulite facies conditions in the Helvetic–Dauphinois–Provençal, Penninic, and eastern Austroalpine domains and under Ep-amphibolite facies conditions in the Southalpine domain. These metamorphic conditions correspond to a mean Franciscan-type metamorphic field gradient. During the late Devonian–late Carboniferous period, in the Helvetic–Dauphinois–Provençal and central Austroalpine domains, the dominant metamorphic imprint developed under eclogite and HP granulite facies conditions with a Franciscan field gradient. Amphibolite facies conditions dominated in the Penninic and Southalpine domains and corresponded to a Barrovian-type metamorphic field gradient. At the Carboniferous–Permian transition, the metamorphic imprints mainly developed under amphibolite-LP granulite facies conditions in all domains of the Alps, corresponding to a mean metamorphic field gradient at the transition between Barrovian and Abukuma (Buchan) types. This distribution of the metamorphic imprints suggests a pre-Alpine burial of oceanic and continental crust underneath a continental upper plate, in a scenario of single or multiple oceanic subductions preceding the continental collision. Both scenarios are discussed and revised considering the consistency of collected data and a comparison with numerical models. Finally, the distribution of Devonian to Triassic geothermal gradients agrees with a sequence of events that starts with subduction, continues with continental collision, and ends with the continental thinning announcing the Jurassic oceanization.
Geomorphology, Geoarchaeology, and Geochronology of the Upper Pleistocene Archaeological Site of El Olivo Cave (Llanera, Asturias, Northern Spain)
Authors: Jordá Pardo Jesús F. , Álvarez-Alonso David , de Andrés-Herrero María , Ballesteros Daniel , Carral Pilar , Hevia-Carrillo Aitor , Sanjurjo Jorge , Giralt Santiago , Jiménez-Sánchez Montserrat
Published: October 2023

El Olivo Cave (Pruvia de Arriba, Llanera, Asturias, Spain) is a small karst cave located in the Aboño River basin and formed in the Cretaceous limestone of the Mesozoic cover of the Cantabrian Mountains (north of the Iberian Peninsula). It contains an important upper Pleistocene sedimentary, archaeological, and paleontological record, with abundant technological evidence and faunal remains. The archaeological record shows a first occupation that could correspond to the Middle Paleolithic and a second occupation in the Middle Magdalenian. The stratigraphic sequence inside and outside the cave was studied with geoarchaeological methodology. In this paper, the lithostratigraphic sequence is analyzed, and the data from the granulometric, mineralogical, edaphological, and radiometric analyses are presented. The results of these analyses enable an accurate interpretation of both the lithostratigraphy of the deposit and the processes responsible for its formation and subsequent evolution. The available numerical dates allow us to locate the first sedimentation episode in the cave in OIS 7a, in the Middle Pleistocene, the base of the outer fluvial sedimentation in the cold OIS 3a stage of the Upper Pleistocene and the Magdalenian occupation in the Last Glacial Maximum (OIS 2) at the end of the Late Pleistocene.
Psychometric Properties of the Perceived Collective Family Efficacy Scale in Algeria
Authors: Sabah Aiche , Aljaberi Musheer A. , Lee Kuo-Hsin , Lin Chung-Ying
Published: October 2023

The Perceived Collective Family Efficacy Scale is a tool utilized to assess the effectiveness of a family as a functioning system. The scale has a single-factor structure with good validity and reliability. However, there is a shortage of psychometric evidence of the scale in an Arab context. This study aimed to assess the psychometric properties of the Perceived Collective Family Efficacy Scale among Algerian students. A cross-sectional study was conducted to recruit 300 students from Algerian universities. The students completed the 20-item Perceived Collective Family Efficacy Scale, Arabic version, to measure their beliefs regarding collective efficacy within families. Confirmatory factor analysis (CFA) and the Rasch model were employed to assess the psychometric properties and unidimensionality of the scale. Both CFA and Rasch findings supported the single-factor structure for the Perceived Collective Family Efficacy Scale. Specifically, the CFA indicated that the data aligned with a one-dimensional model. The Rasch analysis revealed favorable indicators of unidimensionality for the scale. Moreover, a thorough examination of the Principal Component Analysis of the Rasch residuals confirmed the existence of a single dimension, which is consistent with the original structure of the Perceived Collective Family Efficacy Scale. These findings provide scientific evidence for the validity and unidimensional nature of the Perceived Collective Family Efficacy Scale. Specifically, the satisfactory psychometric properties findings indicate that the Perceived Collective Family Efficacy Scale could be applied in an Arab context (i.e., in Algerian). The scale’s unidimensional structure underscores its effectiveness in measuring beliefs in collective efficacy within families. These results enhance our understanding of family dynamics and provide a reliable measurement tool for assessing family efficacy in similar cultural contexts.
Effects of 12-Month Training Intervention on Physical Fitness, Body Composition, and Health Markers in Finnish Navy Soldiers
Authors: Myllylä Mikko , Parkkola Kai I. , Ojanen Tommi , Heinonen Olli J. , Ruohola Juha-Petri , Vahlberg Tero , Kyröläinen Heikki
Published: October 2023

Background: Most Western adults do not meet the recommendations for sufficient activity, and obesity is a global problem. Similar trends are also seen among Western military personnel. Many successful physical training interventions have been carried out in military environments, but the interventions have been quite short term, and the training has been supervised. Therefore, the aim of this study was to investigate the effects of a 12-month voluntary motivational training intervention among the Finnish Defence Forces’ (FDF) Navy soldiers. Methods: In total, 77 FDF Navy soldiers, serving in missile patrol boats, took part in the study. The intervention group (IG) contained 45 participants and the control group (CG) contained 32 participants. The IG was divided into four teams that carried out the intervention, while the CG took part in only the measurements. Results: Most of the participants (65%) in the IG reported that they had increased their exercise volume during the intervention, but no major beneficial impacts on the physical fitness, body composition, or health markers were observed. Nevertheless, there was a clear diversity visible between the subgroups in the IG. The team that reported the most exercise had the best motivation and the most motivated team coach and also had the most improved physical fitness and body composition results. Conclusions: The present study points out that in military environments, long-term voluntary training interventions may not be as successful as short-term supervised interventions. The results also suggest that in voluntary training interventions among military personnel, the participants’ motivation to exercise is a key factor when improving physical fitness.