bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of digital empowerment on open innovation performance of enterprises from the perspective of SOR
Authors: Lingling Liang , Ye Li
Published: February 2023

Introduction

As China’s digital transformation index continues to climb and market openness increases, the active implementation of open innovation embedded in digital innovation eco-networks is key to implementing sustainable innovation-driven strategies. The widespread use of digital technologies has broken through the traditional closed boundaries of enterprises and enhanced technology exchange, information communication and R&D collaboration with other innovation agents.However, many enterprises’ digital empowerment efforts only stay at the level of digital technology, but do not rise to the level of corporate strategy. How to comprehensively promote the change of enterprise digital empowerment and help enterprises build a sustainable open innovation ecosystem needs further research.

Methods

This article uses the structure equation model and the necessary condition analysis methods to combine the stimulus-organization-reaction (SOR) theory to analyze the conduction mechanism of digital authorization to open innovation from a cognitive perspective.

Results

(1) In the era of digital economy, digital empowerment emphasizes the initiative and adaptability of enterprises, and explores a sustainable digital road suitable for enterprises themselves; (2) Organizational emotional ability and organizational disordered atmosphere play a mediating role between digital empowerment and open innovation, but organizational emotional ability has a positive impact on open innovation, while organizational disordered atmosphere is the opposite. (3) Organizational identity positively regulates the relationship between the disordered atmosphere and open innovation.

Discussion

The development of digital technology has adapted deviations with traditional management models. Organizing the investment in digital construction should also pay attention to the digital training and digital thinking of organizational members.Organizations should provide organizational support through various channels, enhance employees’ organizational commitments to create a relationship -shaped psychological contract, regularly carry out digital education and organizational culture, reduce the differential atmosphere between teams, enhance the team’s awareness of cooperation and trust in the teamAnd overall consciousness.
Personality traits and mental distress after COVID-19 testing. Prospective long-term analysis in a Viennese cohort
Authors: Guttmann-Ducke Claudia , Klinger Sonja , Ziesche Rolf , Otzelberger Bernd , Idzko Marco , Ponocny Armin , Prantl Simon Gabriel , Ponocny-Seliger Elisabeth
Published: February 2023

Background

Symptoms of mental stress are a hallmark of the COVID-19 pandemic. We hypothesized that just testing for COVID-19 could act as an effective stressor for persisting symptoms of mental distress including posttraumatic stress disorder. Our study aimed to determine whether personal beliefs on individual control and competence (locus of control, LoC) correlate with symptoms of mental distress and positive screening for post-traumatic stress disorder during a 9-month observational period.

Methods

Between March and December 2021, we applied online versions of the Questionnaire on Competence and Control Expectations (FKK), the Depression, Anxiety, and Stress Score (DASS), the Short Screening Scale for DSM-IV Posttraumatic Stress Disorder (PTSD), and a medical history questionnaire for COVID-19 symptoms (visit 1). 48 hours after negative COVID-19 testing, DASS was repeated to address relief effects on mental distress (visit 2). Following 90 days (visit 3), development of mental distress was addressed by a combination of DASS and PTSD, while the possible long-term manifestation of PTSD was evaluated 9 months later (visit 4).

Results

At visit 1, 7.4 percent of the total sample (n = 867) demonstrated a positive screening for PTSD, while after nine months (at visit 4), 8.9 percent of the remaining sample (n = 204) had positive screening results. The mean age was 36.2 years; 60.8% were women, 39.2% men. In contrast to individuals with negative PTSD screening, these participants demonstrated a significantly different LoC personality profile. This was confirmed by the results of both DASS and the COVID-19 medical history questionnaire.

Conclusion

Following testing for COVID-19, individuals with positive long-term PTSD screening present with significantly different personality traits than those w/o suggesting that self-confidence and effective control over one’s own actions serve as a protective function against mental distress.
Drawing a pandemic vulnerabilities' map: The SoNAR-global Vulnerabilities Assessment digital and its output
Authors: Vaccaro Concetta , Lenzi Francesca Romana , Addonisio Gabriella , Gianfrilli Daniele , Volkmann Anna Maria , Napier David , Giles-Vernick Tamara
Published: February 2023

This paper describes the process, advantages and limitations of a qualitative methodology for defining and analyzing vulnerabilities during the COVID-19 pandemic. Implemented in Italy in two sites (Rome and outside Rome, in some small-medium sized municipalities in Latium) in 2021, this investigation employed a mixed digital research tool that was also used simultaneously in four other European countries. Its digital nature encompasses both processes of data collection. Among the most salient is that the pandemic catalyzed new vulnerabilities in addition to exacerbating old ones, particularly economic. Many of the vulnerabilities detected, in fact, are linked to previous situations, such as the uncertainties of labor markets, having in COVID-19 to the greatest negative effects on the most precarious workers (non-regular, part-time, and seasonal). The consequences of the pandemic are also reflected in other forms of vulnerability that appear less obvious, having exacerbated social isolation, not only out of fear of contagion, but because of the psychological challenges posed by containment measures themselves. These measures created not mere discomfort, but behavioral changes characterized by anxiety, fearfulness, and disorientation. More generally, this investigation reveals the strong influence of social determinants throughout the COVID-19 pandemic, creating new forms of vulnerability, as the effects of social, economic, and biological risk factors were compounded, in particular, among already marginalized populations.
A nomogram based on radiological features of MRI for predicting the risk of severe pain in patients with osteoarthritis of the knee
Authors: Shao Zhuce , Liang Zhipeng , Hu Peng , Bi Shuxiong
Published: February 2023

Methods

This study aimed to develop and validate a nomogram for predicting the risk of severe pain in patients with knee osteoarthritis. A total of 150 patients with knee osteoarthritis were enrolled from our hospital, and nomogram was established through a validation cohort (n = 150). An internal validation cohort (n = 64) was applied to validate the model.

Results

Eight important variables were identified using the Least absolute shrinkage and selection operator (LASSO) and then a nomogram was developed by Logistics regression analysis. The accuracy of the nomogram was determined based on the C-index, calibration plots, and Receiver Operating Characteristic (ROC) curves. Decision curves were plotted to assess the benefits of the nomogram in clinical decision-making. Several variables were employed to predict severe pain in knee osteoarthritis, including sex, age, height, body mass index (BMI), affected side, Kellgren—Lawrance (K–L) degree, pain during walking, pain going up and down stairs, pain sitting or lying down, pain standing, pain sleeping, cartilage score, Bone marrow lesion (BML) score, synovitis score, patellofemoral synovitis, bone wear score, patellofemoral bone wear, and bone wear scores. The LASSO regression results showed that BMI, affected side, duration of knee osteoarthritis, meniscus score, meniscus displacement, BML score, synovitis score, and bone wear score were the most significant risk factors predicting severe pain.

Conclusions

Based on the eight factors, a nomogram model was developed. The C-index of the model was 0.892 (95% CI: 0.839–0.945), and the C-index of the internal validation was 0.822 (95% CI: 0.722–0.922). Analysis of the ROC curve of the nomogram showed that the nomogram had high accuracy in predicting the occurrence of severe pain [Area Under the Curve (AUC) = 0.892] in patients with knee osteoarthritis (KOA). The calibration curves showed that the prediction model was highly consistent. Decision curve analysis (DCA) showed a higher net benefit for decision-making using the developed nomogram, especially in the >0.1 and <0.86 threshold probability intervals. These findings demonstrate that the nomogram can predict patient prognosis and guide personalized treatment.
Clinical study of early rehabilitation training combined with negative pressure wound therapy for the treatment of deep partial-thickness hand burns
Authors: Liu Canbin , Xie Hongteng , Wei Pei , Gong Teng , Wu Guohua , Xu Zhaorong , Chen Shun
Published: February 2023

Objective

This study aims to explore the clinical effect of early rehabilitation training combined with negative pressure wound therapy (NPWT) for treating deep partial-thickness hand burns.

Methods

Twenty patients with deep partial-thickness hand burns were randomly divided into an experimental group (n = 10) and a control group (n = 10). In the experimental group, early rehabilitation training combined with NPWT was performed, including the proper sealing of the negative pressure device, intraoperative plastic brace, early postoperative exercise therapy during negative pressure treatment, and intraoperative and postoperative body positioning. Routine NPWT was conducted in the control group. Both groups received 4 weeks of rehabilitation after wounds healed by NPWT with or without skin grafts. Hand function was evaluated after wound healing and 4 weeks after rehabilitation, including hand joint total active motion (TAM) and the brief Michigan Hand Questionnaire (bMHQ).

Results

Twenty patients were involved in this study, including 16 men and 4 women, aged 18–70 years, and the hand burn area ranged from 0.5% to 2% of the total body surface area (TBSA). There was no significant difference in TAM and bMHQ scores between the two groups after negative pressure removal. After 4 weeks of rehabilitation training, the TAM scores and bMHQ scores were significantly improved in both groups (p < 0.05); among them, those of the experimental group were both significantly better than those of the control group (p < 0.05).

Conclusion

The application of early rehabilitation training combined with NPWT to treat deep partial-thickness hand burns can effectively improve hand function.
Experience with successful treatment of severe recurrent vulvar adhesions: A case report
Authors: Bi Yingying , Chen Yuhang , Li Wu , Jiang Huici , Qin Jinlong , Cheng Jiajing
Published: February 2023

Vulvar adhesions are defined as partial or complete adherence of the labia minora and/or labia majora. Vulvar adhesions are rare, especially in postmenopausal women.This article describes a case of postmenopausal recurrent vulvar adhesions successfully treated with surgery. The patient was a 52-year-old woman who had undergone manual separation and surgical adhesion release due to vulvar adhesions, which recurred soon after treatment. The patient then came to our hospital for treatment because of complete dense adhesions to the vulva and laboured urination. The patient received surgical treatment, the anatomical structure of the vulva recovered well, and the symptoms affecting the urinary system disappeared. There was no readhesion during the 3-month follow-up.
Previous exposure to common coronavirus HCoV-NL63 is associated with reduced COVID-19 severity in patients from Cape Town, South Africa
Authors: Lesmes-Rodríguez Lida C. , Lambarey Humaira , Chetram Abeen , Riou Catherine , Wilkinson Robert J. , Joyimbana Wendy , Jennings Lauren , Orrell Catherine , Jaramillo-Hernández Dumar A. , Schäfer Georgia
Published: February 2023

Background

Globally, the most significant risk factors for adverse COVID-19 outcome are increasing age and cardiometabolic comorbidities. However, underlying coinfections may modulate COVID-19 morbidity and mortality, particularly in regions with high prevalence of infectious diseases.

Methods

We retrospectively analyzed serum samples for IgG antibodies against the common circulating coronaviruses HCoV-NL63, HCoV-229E, HCoV-OC43 and HCoV-HKU1 from non-hospitalized and hospitalized confirmed COVID-19 patients recruited during the first (June-August 2020) and second (October 2020-June 2021) COVID-19 wave in Cape Town, South Africa. Patients were grouped according to COVID-19 disease severity: Group 1: previously SARS-CoV-2 infected with positive serology and no symptoms (n=94); Group 2: acutely SARS-CoV-2 infected, hospitalized for COVID-19 and severe symptoms (n=92).

Results

The overall anti-HCoV IgG seroprevalence in the entire patient cohort was 60.8% (95% CI: 53.7 – 67.8), with 37.1% HCoV-NL63 (95% CI: 30 – 44), 30.6% HCoV-229E (95% CI: 24 – 37.3), 22.6% HCoV-HKU1 (95% CI: 16.6 – 28.6), and 21.0% HCoV-OC43 (95% CI: 15.1 – 26.8). We observed a significantly higher overall HCoV presence (72.3% versus 48.9%) and coinfection frequency (43.6% versus 19.6%) in group 1 compared to group 2 patients with significantly higher presentation of HCoV-NL63 (67.0% versus 6.6%) and HCoV-HKU1 (31.1% versus 14.1%). However, only antibody titers for HCoV-NL63 were significantly higher in group 1 compared to group 2 patients (p< 0.0001, 1.90 [95% CI: 0.62 – 2.45] versus 1.32 [95% CI: 0.30 – 2.01]) which was independent of the participants’ HIV status. Logistic regression analysis revealed significantly protective effects by previous exposure to HCoV-NL63 [p< 0.001, adjusted OR = 0.0176 (95% CI: 0.0039 – 0.0786)], while previous HCoV-229E exposure was associated with increased COVID-19 severity [p = 0.0051, adjusted OR = 7.3239 (95% CI: 1.8195–29.4800)].

Conclusion

We conclude that previous exposure to multiple common coronaviruses, and particularly HCoV-NL63, might protect against severe COVID-19, while no previous HCoV exposure or single infection with HCoV-229E might enhance the risk for severe COVID-19. To our knowledge, this is the first report on HCoV seroprevalence in South Africa and its possible association with cross-protection against COVID-19 severity.
The Use of Correlation Features in the Problem of Speech Recognition
Authors: Andriyanov Nikita
Published: February 2023

The problem solved in the article is connected with the increase in the efficiency of phraseological radio exchange message recognition, which sometimes takes place in conditions of increased tension for the pilot. For high-quality recognition, signal preprocessing methods are needed. The article considers new data preprocessing algorithms used to extract features from a speech message. In this case, two approaches were proposed. The first approach is building autocorrelation functions of messages based on the Fourier transform, the second one uses the idea of building autocorrelation portraits of speech signals. The proposed approaches are quite simple to implement, although they require cyclic operators, since they work with pairs of samples from the original signal. Approbation of the developed method was carried out with the problem of recognizing phraseological radio exchange messages in Russian. The algorithm with preliminary feature extraction provides a gain of 1.7% in recognition accuracy. The use of convolutional neural networks also provides an increase in recognition efficiency. The gain for autocorrelation portraits processing is about 3–4%. Quantization is used to optimize the proposed models. The algorithm’s performance increased by 2.8 times after the quantization. It was also possible to increase accuracy of recognition by 1–2% using digital signal processing algorithms. An important feature of the proposed algorithms is the possibility of generalizing them to arbitrary data with time correlation. The speech message preprocessing algorithms discussed in this article are based on classical digital signal processing algorithms. The idea of constructing autocorrelation portraits based on the time series of a signal has a novelty. At the same time, this approach ensures high recognition accuracy. However, the study also showed that all the algorithms under consideration perform quite poorly under the influence of strong noise.
Defect Detection Methods for Industrial Products Using Deep Learning Techniques: A Review
Authors: Saberironaghi Alireza , Ren Jing , El-Gindy Moustafa
Published: February 2023

Over the last few decades, detecting surface defects has attracted significant attention as a challenging task. There are specific classes of problems that can be solved using traditional image processing techniques. However, these techniques struggle with complex textures in backgrounds, noise, and differences in lighting conditions. As a solution to this problem, deep learning has recently emerged, motivated by two main factors: accessibility to computing power and the rapid digitization of society, which enables the creation of large databases of labeled samples. This review paper aims to briefly summarize and analyze the current state of research on detecting defects using machine learning methods. First, deep learning-based detection of surface defects on industrial products is discussed from three perspectives: supervised, semi-supervised, and unsupervised. Secondly, the current research status of deep learning defect detection methods for X-ray images is discussed. Finally, we summarize the most common challenges and their potential solutions in surface defect detection, such as unbalanced sample identification, limited sample size, and real-time processing.
Data-Driven Nonlinear Iterative Inversion Suspension Control
Authors: Wen Tao , Zhou Xu , Li Xiaolong , Long Zhiqiang
Published: February 2023

The commercial operation of the maglev train has strict requirements for the reliability and safety of the suspension control system. However, due to a large number of unmodeled dynamics of the suspension system, it is difficult to obtain the precise mathematical model of the suspension system. After the suspension system has been operated for a long time with high load, the system model will change due to the wear, aging and failure of components, as well as the settlement of the line and track. The control performance is degraded. Therefore, this paper proposes a data-driven nonlinear iterative inversion suspension control algorithm, which can achieve high-precision tracking performance recovery control after control performance degradation without depending on the suspension system model. The control performance of the suspension system is improved by learning the measured data of the historical suspension system, and the fast convergence of the tracking error and high-precision stable suspension control are realized in the presence of unmodeled dynamics and external noise interference. Based on the historical suspension data of the maglev train suspension control system, the inverse dynamics model of the suspension system is identified by iterative inversion learning based on data drive, and the suspension control framework based on iterative inversion is designed. Then, the nonlinear input update strategy is used to realize the rapid convergence of the learning process. Finally, the simulation experiment of the maglev train suspension system and the physical experiment of the maglev system experimental platform are combined. It is verified that the proposed levitation control algorithm can achieve high-precision fast tracking performance recovery control after the system control performance degrades under noise environment.
An Obstacle-Avoidance Motion Planning Method for Redundant Space Robot via Reinforcement Learning
Authors: Huang Zeyuan , Chen Gang , Shen Yue , Wang Ruiquan , Liu Chuankai , Zhang Long
Published: February 2023

On-orbit operation tasks require the space robot to work in an unstructured dynamic environment, where the end-effector’s trajectory and obstacle avoidance need to be guaranteed simultaneously. To ensure the completability and safety of the tasks, this paper proposes a new obstacle-avoidance motion planning method for redundant space robots via reinforcement learning (RL). First, the motion planning framework, which combines RL with the null-space motion for redundant space robots, is proposed according to the decomposition of joint motion. Second, the RL model for null-space obstacle avoidance is constructed, where the RL agent’s state and reward function are defined independent of the specific information of obstacles so that it can adapt to dynamic environmental changes. Finally, a curriculum learning-based training strategy for RL agents is designed to improve sample efficiency, training stability, and obstacle-avoidance performance. The simulation shows that the proposed method realizes reactive obstacle avoidance while maintaining the end-effector’s predetermined trajectory, as well as the adaptability to unstructured dynamic environments and robustness to the space robot’s dynamic parameters.
Effect of Enzyme Activity Changes on Decomposition Characteristics of Leaf Litter Mixed Decomposition of Configurated Tree Species in Ecological Tea Garden
Authors: Liu Shaqian , Yang Rui , Hou Chunlan
Published: February 2023

In the management of eco-tea gardens, the recycling of weathered leaves of the configured tree species plays an important role in the nutrients of the tea garden ecosystem. The in situ decomposition method was used to analyze the decomposition rate, elemental release, and enzymatic activity of different combinations of leaf litter in tea garden soil. The results showed that mixed decomposition accelerates the decomposition turnover period of Jiu’an ecological tea garden. The higher release rate of the litter improved the nutrient effectiveness in the ecological tea garden. The trends of CAT (catalase), AP (acid phosphatase), and PPO (polyphenol oxidase) activities were similar during the decomposition of different mixed leaf litters, while all other enzyme activities showed some differences. There were also some differences in the relationship between the enzyme activity and decomposition rate of leaf litter and the nutrient release rate related to the substrate mass content during the decomposition of leaf litter. Overall, the changes in the nutrient content of the leaf litter during decomposition promoted an increase in enzyme activity, which in turn promoted the release of leaf litter elements, shortened the turnover period of leaf litter decomposition, and accelerated the recycling of elements in the ecological tea garden.
Forage Mass and Nutritive Value of Grain- and Forage-Type Soybean Cultivars Managed under Different Row Spacings and Clipping Heights
Authors: Thompson Serena J. , Koebernick Jenny , Silva Liliane S. , Mullenix Mary K. , Heaton Courtney , Carrell Russell C. , Dillard Sandra L.
Published: February 2023

Soybean (Glycine max L.) is a high value crop that has been used as a forage since the early 1900s in the southern U.S. (e.g., Mississippi, Alabama, Georgia, South Carolina, and Florida). Renewed interest has increased the use of soybean as a viable and economical high protein alternative to forage growers in the southern region. The objective of this study was to determine herbage mass (HM) and nutritive value of forage soybean managed under two row spacing (36 and 72 cm) and three stubble heights (10, 15, and 20 cm). Five cultivars were used ‘Stonewall’, ‘Laredo’, ‘Tower of Leaves’, Asgrow® ‘AG64X8’, and Asgrow® ‘AG79X9’ and sown at two locations (Shorter and Headland, AL). Forage was harvested in July and August during both years and HM was determined. Crude protein (CP) and fiber fractions were determined using near-infrared spectroscopy. Years and location did vary, but overall, Stonewall had the greatest (p < 0.026) HM (1706 kg DM ha−1) with a high nutritive value (124 g CP kg−1, 449 g NDF kg−1, and 372 g ADF kg−1). Laredo had the lowest HM (1169 kg DM ha−1; p < 0.025). The 10 cm stubble height resulted in increased HM (1898 kg DM ha−1; p < 0.0001) but decreased nutritive value (149 g CP kg−1; 331 g ADF kg−1; 413 g NDF kg−1; p = 0.001) compared to 20 cm (179, 282, and 375 g kg−1 for CP, ADF, and NDF, respectively). Row spacing did not consistently influence either HM or nutritive values. Due to its relatively good nutritive value and HM, forage soybean should be considered as a monoculture or in a mixed sward with other warm-season annual forages for inclusion in forage-based livestock diets.
Simulation Analysis and Test on the Effect of Picking Up the Residual Film of Typical Film Lifting Parts
Authors: Wang Feng , Dai Fei , Zhang Fengwei , Song Xuefeng , Shi Ruijie , Zhao Wuyun , Ma Haijun
Published: February 2023

The agronomic technology of whole plastic-film mulching on double ridges has been widely promoted in the arid region of northwest China, which has caused serious residual film pollution in the field. Mechanized residual plastic-film collecting is the main way, but this way of residual plastic-film collecting is more complicated. To prove the effect of typical film-lifting parts on residual plastic-film collecting performance by a numerical simulation method, further evaluate and select the working parts suitable for residual plastic-film collecting and improve the collecting efficiency, virtual whole plastic-film mulching on double ridges needs to be established. In this study, the film-lifting parts and the double ridge with flexible, deformable, mulching, film interaction model was developed using the discrete element method (DEM). The interaction model was used to simulate the operation process of a typical third-order shovel, hug plate and elastic teeth film-lifting parts. Furthermore, the operation resistance, seed bed disturbance and collecting residual film form under different working conditions were analyzed. The simulation results show that: the disturbance of the ridge from strong to weak is the third-order shovel, elastic teeth and hug plate film-lifting parts; the crushing of the ridge soil from strong to weak is the elastic teeth, the hug plate and the third-order shovel film-lifting parts; the collecting film from strong to weak is the hug plate, elastic teeth and the third-order shovel film-lifting parts; the median value of the horizontal force fluctuation range of the ridge soil on the film-lifting parts is increased, and the increase trend is from large to small in the third-order shovel, elastic teeth and hug plate film-lifting parts (the third-order shovel is 5250 N, 6250 N and 7750 N; the hug plate is 3250 N, 3500 N and 4000 N; and the elastic teeth are 4150 N, 4550 N and 5450 N). The comparative analysis results show that the hug plate film-lifting parts are more suitable for the residual-film collecting of whole plastic-film mulching on double ridges. Field trials were carried out to verify the operational effectiveness of the hug plate film-lifting parts. The results show that the morphological changes of the recovered residual film and the simulated mulching film during the operation of the hug plate-type residual film machine, and the distribution of the surface properties of the ridge after the residual-film collecting are basically consistent with the simulation results, and the film pick-up rate of hug plate film-lifting parts reaches 95.20%, and the established discrete element interaction model is reliable. The research results can provide reference for the research and development of full film duopoly furrow-mechanized residual film-collecting agricultural equipment in the arid region of northwest China.
The Effect of Babassu Industry By-Products as an Alternative Feed for Dairy Cows
Authors: Zanine Anderson , De Sá Cledson , Ferreira Daniele , Parente Henrique , Parente Michelle , Santos Edson Mauro , Rodrigues Rosane , Santos Francisco Naysson , Lima Anny Graycy , Cunha Ivo Alexandre , de Sousa Francisca Claudia , Costa Renata , Pereira Danillo , Gomes Paloma Gabriela , Dórea João Ricardo
Published: February 2023

The objective of this study was to evaluate the fermentative characteristics, chemical composition, and in vitro digestibility of a total mixed ration silage containing two babassu by-products, starchy flour and babassu cake. The treatments were distributed in a completely randomised design containing four treatments and five replications. The treatments consisted of corn silage, corn silage based on the standard corn and soybean diet, corn silage with babassu flour, and corn silage with babassu cake. No significant difference was observed in the pH values (p = 0.256) for the studied silages. Higher values for dry matter recovery were observed for the silages of the total diets. The corn silage presented lower lactic acid production (55.15 g/kg DM) and acetic acid (11.54 g/kg DM) in relation to the total ration silages. The inclusion of babassu by-products increased the dry matter (p < 0.001), crude protein (p < 0.001), and total digestible nutrient content (p < 0.001) in the total ration silages. Silage in the form of the total ration containing regional babassu by-products improved the fermentative profile of the silages and the nutritional value of the diets, endowing them with potential for use as a feed alternative for dairy cattle.
Recent Advances in Infrared Face Analysis and Recognition with Deep Learning
Authors: Mahouachi Dorra , Akhloufi Moulay A.
Published: February 2023

Besides the many advances made in the facial detection and recognition fields, face recognition applied to visual images (VIS-FR) has received increasing interest in recent years, especially in the field of communication, identity authentication, public safety and to address the risk of terrorism and crime. These systems however encounter important problems in the presence of variations in pose, expression, age, occlusion, disguise, and lighting as these factors significantly reduce the recognition accuracy. To prevent problems in the visible spectrum, several researchers have recommended the use of infrared images. This paper provides an updated overview of deep infrared (IR) approaches in face recognition (FR) and analysis. First, we present the most widely used databases, both public and private, and the various metrics and loss functions that have been proposed and used in deep infrared techniques. We then review deep face analysis and recognition/identification methods proposed in recent years. In this review, we show that infrared techniques have given interesting results for face recognition, solving some of the problems encountered with visible spectrum techniques. We finally identify some weaknesses of current infrared FR approaches as well as many future research directions to address the IR FR limitations.
Structural Features Governing the Metabolic Stability of Tetraethyl-Substituted Nitroxides in Rat Liver Microsomes
Authors: Rančić Aleksandra , Babić Nikola , Orio Maylis , Peyrot Fabienne
Published: February 2023

Nitroxides are potent tools for studying biological systems by electron paramagnetic resonance (EPR). Whatever the application, a certain stability is necessary for successful detection. Since conventional tetramethyl-substituted cyclic nitroxides have insufficient in vivo stability, efforts have recently been made to synthesize more stable, tetraethyl-substituted nitroxides. In our previous study on piperidine nitroxides, the introduction of steric hindrance around the nitroxide moiety successfully increased the resistance to reduction into hydroxylamine. However, it also rendered the carbon backbone susceptible to modifications by xenobiotic metabolism due to increased lipophilicity. Here, we focus on a new series of three nitroxide candidates with tetraethyl substitution, namely with pyrrolidine, pyrroline, and isoindoline cores, to identify which structural features afford increased stability for future probe design and application in in vivo EPR imaging. In the presence of rat liver microsomes, pyrrolidine and pyrroline tetraethyl nitroxides exhibited a higher stability than isoindoline nitroxide, which was studied in detail by HPLC-HRMS. Multiple metabolites suggest that the aerobic transformation of tetraethyl isoindoline nitroxide is initiated by hydrogen abstraction by P450-FeV = O from one of the ethyl groups, followed by rearrangement and further modifications by cytochrome P450, as supported by DFT calculations. Under anaerobic conditions, only reduction by rat liver microsomes was observed with involvement of P450-FeII.
Dynamic Analysis and Parameter Optimization of the Cutting System for Castor Harvester Picking Devices
Authors: Kong Fanting , Wang Defu , Shi Lei , Huang Huinan , Xie Qing , Wu Teng , Sun Yongfei , Chen Changlin
Published: February 2023

Our study aimed to identify a design which would reduce cutting resistance during the harvesting of castor. This paper presents a theoretical study of the wave-type disc cutter, which plays an important role in castor harvesting. Based on the SPH–FEM coupling algorithm, a combined orthogonal rotation experiment was performed to study the effects of disc cutter thickness, edge angle, disc cutter rotation speed, and feeding speed on the maximum cutting force. The response surface method was used to achieve an optimal combination of all the test factors. Mathematical modeling of the maximum cutting force and influencing factors was utilized to obtain the optimal parameters for a cutting system consisting of wave-type disc cutters. The optimal results were obtained with a computer-simulated disc cutter rotation speed of 844.2–942.1 r/min, a feeding speed of 0.89–1.01 m/s, a disc cutter thickness of 2.71–3.15 mm, and an edge angle of 29.2–33.9°. Under these conditions, the maximum cutting force was less than 50 N. Finally, the experimental data and numerical computer simulation results were compared using cutting performance test verification. The analysis found that the test results and simulation results were largely consistent. Therefore, the simulation model was judged to be effective and reasonable.
Approaches to the Functionalization of Organosilicon Dendrones Based on Limonene
Authors: Ryzhkov Aleksei I. , Drozdov Fedor V. , Cherkaev Georgij V. , Muzafarov Aziz M.
Published: February 2023

Previously, we reported the synthesis of carbosilane and carbosilane-siloxane dendrons of various generations based limonene, a natural terpene. Limonene that contains two double bonds, namely cyclohexene and isoprenyl ones, was shown to undergo regioselective hydrosilylation exclusively at its isoprenyl double bond. This finding was used to prepare carbosilane dendrons (CDs) with a limonene moiety at the focal point. In this study, we present variants for the functionalization of the cyclohexene double bond by an epoxidation reaction in order to use the resulting dendrons for the preparation of various macromolecular objects, including Janus dendrimers (JDs), dendronized polymers, and macroinitiators. Moreover, it was shown that dendrons with peripheral azide functions could be obtained. These methods offer both the possibilities of the further growth of branches and the addition of polymers with a different nature by the azide–alkyne cycloaddition reaction.
Open-Set Signal Recognition Based on Transformer and Wasserstein Distance
Authors: Zhang Wei , Huang Da , Zhou Minghui , Lin Jingran , Wang Xiangfeng
Published: February 2023

Open-set signal recognition provides a new approach for verifying the robustness of models by introducing novel unknown signal classes into the model testing and breaking the conventional closed-set assumption, which has become very popular in real-world scenarios. In the present work, we propose an efficient open-set signal recognition algorithm, which contains three key sub-modules: the signal representation sub-module based on a vision transformer (ViT) structure, a set distance metric sub-module based on Wasserstein distance, and a class space compression sub-module based on reciprocal point separation and central loss. In this algorithm, the representing features of signals are established based on transformer-based neural networks, i.e., ViT, in order to extract global information about time series-related data. The employed reciprocal point is used in modeling the potential unknown space without using the corresponding samples, while the distance metric between different class spaces is mathematically modeled in terms of the Wasserstein distance instead of the classical Euclidean distance. Numerical experiments on different open-set signal recognition tasks show that the proposed algorithm can significantly improve the recognition efficiency in both known and unknown categories.
Investigation of Chinese Herbal Decoctions with Enzymatic Hydrolysis and Sequential Fermentation as Potential Nutrient Supplements
Authors: Han Shanshan , Zhang Hongyan , Wang Yongliang
Published: February 2023

Chinese herbal medicine has attracted increasing attention due to its therapeutic effects. It demands increasing understanding of the processing methods and the generated changes to control quality and offer better final products. In this study, extraction differences were compared among direct plant extracts (DE), standard decoction (SD), spontaneous fermentation (SF) and inoculated sequential fermentation (IF). Results showed that the extraction with the transformation of probiotics positively contributed to the release of functional compounds from Chinese herbs. It provided the strongest antioxidant capacity and the best amino acid profile. The flavor and the compositions of the herbal decoctions were further characterized. Distinctive volatile differences were found, indicating that the different treatments profoundly altered the spectrum of volatile components. The most aromatic changes were in the IF group, which corresponded with the greatest number of upregulated and the lowest number of downregulated differential compounds. Beneficial intestinal microbiota with voluntary intake of herbal tea suggested a possible positive metabolism shift in the healthy host. In conclusion, the combination of enzymatic hydrolysis and sequential fermentation provided better extraction efficiency than direct plant extraction and traditional herbal decoction. It may enable a broader utilization of traditional Chinese herbs as potential nutrient supplements, such as antibiotic alternatives in animal husbandry.
Dynamic-Breakdown of the Ball-Screw Inerter in ISD System
Authors: Li Yuehao , Hu Niaoqing , Cheng Zhe , Zhang Lun , Yang Yi , Yin Zhengyang , Huang Liangyuan
Published: February 2023

Inerter is a novel type of mechanical element. As the important composition of vibration control systems, inerters are widely used. Meanwhile, the operation security issue of the inerter is becoming increasingly prominent. Dynamic-breakdown of the inerter (DBoI) means that the inerter’s two terminals come into contact, which can cause a huge impact force and destroy the system. The ball-screw inerter is an essential protype of inerters. The existence of dynamic-breakdown of a single inerter has been already proved by previous research. To confirm whether DBoI exists in the inerter-spring-damper (ISD) system, the research focuses on the dynamic-breakdown of a ball-screw inerter (DBoBSI) in the ISD system. The dynamic model of the DBoI in the ISD system is established and analyzed. On account of the model and analysis, DBoBSI is analyzed. A novel experimental system is established and experiments of DBoBSI in the ISD system are carried out. The coefficient of restitution et changes slightly with a value of about 0.5. The variation of momentum is nearly equal to the impulse, with an error within 15%. On account of the experimental data collected, the conclusions are that there is a DBoBSI in the ISD system, and the impact force during DBoI in the ISD system ought to be avoided.
Feedback-Controlled Adaptive Signal Detection Scheme for Diffusion-Based Molecular Communication Systems
Authors: Byun Heejung
Published: February 2023

This paper proposes a feedback-controlled adaptive method for detecting signals in diffusion-based molecular communication (MC) systems. Signal detection via a receiver nanomachine is a critical challenge for the exchange of information in MC systems. Incorrect estimations or small errors in signal detection can lead to high data detection errors. Existing methods for improving detection performance require high time costs or computational complexity. This paper proposes a simple and practical method that enables receiver nanomachines to automatically estimate signal detection times according to the measured molecular concentrations and weighted feedback errors. The proposed method adjusts the detection time even when the initial parameter values of the system are unknown to the receiver nanomachines. Simulations were performed to evaluate the bit error rate performance of the proposed and existing methods in terms of different data rates, transmission distances, and estimation error lengths under different initial conditions. The simulation results reveal that the implementation of the proposed method is simpler and demonstrates superior performance compared with that of existing methods.
Impact of Air Pollution on Residents’ Health in China: Moderating Effect Analysis Based on a Hierarchical Linear Model
Authors: Liu Yu , Wang Zi-Shuang , Fang Xin-Ge
Published: February 2023

Background: Air pollution is an important factor affecting residents’ health. Methods: Based on the health data of 9959 residents from 28 provinces in China in the 2017 Chinese General Social Survey (CGSS), this paper uses a hierarchical linear model (HLM) to scientifically analyze the impact of air pollution on residents’ health and to explore the moderating role of air pollution in various factors influencing residents’ health. Results: Air pollution has significant negative effects on residents’ health (coef. −0.103, p < 0.01), while frequency of exercise (coef. 0.070, p < 0.01), education level (coef. 0.012, p < 0.1) and income level (coef. 0.383, p < 0.01) have positive effects on residents’ health. Air pollution has a negative moderating effect on the positive impact of exercise frequency on residents’ health (coef. −0.015, p = 0.004). Conclusions: Air pollution causes serious damage to residents’ health and it is necessary to control air pollution. Increasing residents’ income, education level and exercise frequency can help improve residents’ health level. Air pollution significantly reduce the positive impact of exercise frequency on residents’ health. In order to effectively improve their own health, it is a better choice for residents to exercise when the air quality is good.
FedGR: Federated Graph Neural Network for Recommendation Systems
Authors: Ma Chuang , Ren Xin , Xu Guangxia , He Bo
Published: February 2023

Social recommendation systems based on the graph neural network (GNN) have received a lot of research-related attention recently because they can use social information to improve recommendation accuracy and because of the benefits derived from the excellent performance of the graph neural network in graphic data modeling. A large number of excellent studies in this area have been proposed one after another, but they all share a common requirement that the data should be centrally stored. In recent years, there have been growing concerns about data privacy. At the same time, the introduction of numerous stringent data protection regulations, represented by general data protection regulations (GDPR), has challenged the recommendation models with conventional centralized data storage. For the above reasons, we have designed a flexible model of recommendation algorithms for social scenarios based on federated learning. We call it the federated graph neural network for recommendation systems (FedGR). Previous related work in this area has only considered GNN, social networks, and federated learning separately. Our work is the first to consider all three together, and we have carried out a detailed design for each part. In FedGR, we used the graph attention network to assist in modeling the implicit vector representation learned by users from social relationship graphs and historical item graphs. In order to protect data privacy, we used FedGR flexible data privacy protection by incorporating traditional cryptography encryption techniques with the proposed “noise injection” strategy, which enables FedGR to ensure data privacy while minimizing the loss of recommended performance. We also demonstrate a different learning paradigm for the recommendation model under federation. Our proposed work has been validated on two publicly available popular datasets. According to the experimental results, FedGR has decreased MAE and RMSE compared with previous work, which proves its rationality and effectiveness.
The Potential Effects of Light Irradiance in Glaucoma and Photobiomodulation Therapy
Authors: Ahn Sang-Hyun , Suh Jung-Soo , Lim Gah-Hyun , Kim Tae-Jin
Published: February 2023

Human vision is mediated by the retina, one of the most critical tissues in the central nervous system. Glaucoma is a complex retinal disease attributed to environmental, genetic, and stochastic factors, all of which contribute to its pathogenesis. Historically, glaucoma had been thought of primarily as a disease of the elderly; however, it is now becoming more problematic as the incidence rate increases among young individuals. In recent years, excessive light exposure has been suggested as contributing to the rise in glaucoma among the younger generation. Blue light induces mitochondrial apoptosis in retinal ganglion cells, causing optic damage; red light increases cytochrome c oxidase activity in the electron transport system, reducing inflammation and increasing antioxidant reactions to promote cell regeneration. In conclusion, the minimization of blue light exposure and the general application of red light treatment strategies are anticipated to show synergistic effects with existing treatments for retinal disease and glaucoma and should be considered a necessary prospect for the future. This review introduces the recent studies that support the relationship between light exposure and the onset of glaucoma and discusses new treatments, such as photobiomodulation therapy.