bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of multi-stage forward osmosis membrane process for concentrating high-osmotic acrylamide solution
Authors: Hao Shuang , Zhang Zhaoqian , Zhao Xin , An Xiaochan , Hu Yunxia
Published: June 2024

Acrylamide is an important chemical in great global demand for the synthesis of polyacrylamide. A facile and benign approach of concentrating high osmotic acrylamide aqueous solution at a low temperature is needed to replace the current energy-intensive and cost-expensive thermal flash evaporation process. For the first time, a multi-stage forward osmosis (FO) process has been developed to concentrate acrylamide solution from 200 g/L to 600 g/L. Thin-film composite (TFC) membrane was fabricated and used for the multi-stage FO process. Acrylamide feed solution (FS) with various concentrations was systematically characterized in terms of viscosity and osmotic pressure (OP). Draw solutes including NaCl and MgCl2 were tested, and their reverse salt fluxes were measured with the quantification of their accumulative contents in the resultant concentrated acrylamide solution. Different operation modes including AL-FS (active layer facing FS) and AL-DS (active layer facing DS) were explored to optimize the system efficiency of the FO concentration process. Both single- and multi-stage FO operations were investigated, and their performances were quantified to assess the efficiency of the concentration of acrylamide solution. The results demonstrate that the multi-stage FO operation could dramatically improve the system efficiency for the concentration of acrylamide solution better than the single-stage FO process, and the draw concentration renewal at Stages II, III, and IV led to a water flux increase of 18.56%, 17.52%, and 18.43%, respectively. Moreover, the accumulated MgCl2 in the final 600 g/L acrylamide solution was below 3.7 g/L, less than 0.62 wt% impurity in the product of acrylamide. Our work provides a practical insight into the viability and optimization of a multi-stage FO process for concentrating high osmotic chemicals.
Urban agriculture as a landscape approach for sustainable urban planning. An example of Songzhuang, Beijing
Authors: Huan Yu , Nijhuis Steffen , Tillie Nico
Published: June 2024

Cities serve as both political and economic hubs. Sustainable development has long been acknowledged as crucial to the well-being of the environment, people, and society. In order to improve the current state of spatial affairs and attain long-term resilience, humanity is looking for reliable and sustainable urban planning approaches. Urban agriculture has received a lot of attention in recent years as an enduring and pervasive kind of landscape. Although the contribution of urban agriculture has been well documented in many studies on economic, social and ecological aspects, there has been little discussion of its practical value as a tool for spatial development. Additionally, the potential of urban agriculture as a landscape approach remains underdeveloped. In summary, current research and practice lacks a scientific framework for considering urban agriculture as a landscape approach to intervene in urban spaces. To this end, this paper explores the potential of urban agriculture as a landscape approach in sustainable urban planning and design through qualitative case study. Taking Songzhuang in Beijing as an example, we discuss and summarise the operational value and potential of urban agriculture from a design perspective. The findings suggest that landscape-based urbanism that includes urban agriculture can harmonise social, economic, environmental and ecological elements. Finally, in order to provide a generalised approach, this paper proposes a scientific framework for articulating a landscape approach to urban agriculture to guide future research and practice.
Importance of shoulder girdle and finger flexor muscle endurance in advanced male climbers
Authors: Draga Paweł , Rokowski Robert , Sutor Alexander , Pandurevic Dominik , Michailov Michail Lubomirov
Published: June 2024

Aim

This study aimed to: (a) assess the relationships between climbing performance and finger and shoulder girdle muscle endurance; and (b) provide evidence on the validity of the specialized exercise tests used for the purpose.

Materials and methods

28 male sport climbers (climbing ability 23 ± 2.43 IRCRA scale) performed four tests muscle failure, including two-finger hang tests (using 2.5 and 4 cm holds) and two variants of pull-up exercises (classical pull-ups and a combination of dynamic and isometric actions – the so-called Edlinger). Climbing performance and test results were subjected to correlation, taxonomic and regression analysis.

Results

The correlations between the results from all tests and climbing performance were notably strong (r between 0.54 and 0.61) and statistically significant (p<0.05). The taxonomic analysis indicated that the two variants of each test type reflect two different latent variables 2.5 cm and 4 cm finger hang durations were highly correlated (r=0.76,p<0.01). A similar correlation was found between the results from the pull-up tests (r=0.72,p<0.01). Thus, the finger hang and pull-up test results were determined to a high extent (43% and 49%, respectively) by factors that cannot be assessed when only one test of each type is used. The regression model of the two-finger tests allowed individual endurance profiles to be assessed.

Conclusions

The muscular endurance of the elbow flexors and shoulder girdle muscles predicts climbing performance within the specific sport level studied to a comparable degree as finger flexor endurance.The use of two variants of a test intended to assess one physical ability provided important details on a climber’s fitness.
Case Report: Lumbar spondylolisthesis with unilateral pedicle cleft and contralateral spondylolysis: a report of two cases and literature review
Authors: Chang Sheng , Wang Yu , Liu Yong , Wang Chao
Published: June 2024

Background

The causes of pedicle cleft include congenital dysplasia and stress fractures, both of which are rare conditions. Secondary lumbar spondylolisthesis with combined unilateral pedicle cleft and contralateral spondylolysis is extremely rare and can be easily misdiagnosed. We report two cases with these conditions from different causes and discuss the diagnostic and therapeutic features in the context of the literature review.

Case description

Case 1 was a 58-year-old female with a stress fracture change at the left L5 pedicle. Case 2 was a 47-year-old female with a pedicle cleft due to hypoplasia of the left L5 pedicle. Both patients had a combined contralateral spondylolysis and Meyerding grade one lumbar spondylolisthesis, while neither had a clear history of lumbar trauma. After initial conservative treatments failed, both patients underwent a single-segment posterior lumbar interbody fusion with bilateral pedicle screw fixation. Both patients were followed up for more than 1 year postoperatively with clinical symptom relief and bony fusion at the pedicle cleft suggested by a CT scan.

Conclusion

Lumbar spondylolisthesis with unilateral pedicle cleft and contralateral spondylolysis is rarely reported and can be clinically misdiagnosed as simple spondylolisthesis with bilateral spondylolysis. There is no widely accepted surgical option for patients for whom conservative treatment has failed. Our experience suggests that good clinical results may be achieved by single-segment posterior interbody fusion and bilateral pedicle screw fixation. Precise screw placement into the deficient pedicle and sufficient exiting nerve decompression are prerequisites for the success of this surgical option.
Development of a modified C-BARQ for evaluating behavior in working dogs
Authors: Hare Elizabeth , Essler Jennifer Lynn , Otto Cynthia M. , Ebbecke Dana , Serpell James A.
Published: June 2024

Introduction

Current high demand for effective odor detection dogs calls for the development of reliable methods for measuring performance-related behavioral phenotypes in these highly specialized working animals. The Canine Behavioral Assessment & Research Questionnaire (C-BARQ) is a widely used behavioral assessment tool among working dog organizations with a demonstrated ability to predict success/failure of dogs in training. However, this instrument was developed originally to study the prevalence of behavior problems in the pet dog population, and it therefore lacks the capacity to measure specific behavioral propensities that may also be important predictors of working dog success. The current paper examines the factor structure, internal reliability, and content validity of a modified version of the C-BARQ designed to evaluate four new domains of canine behavior in addition to those encompassed by the original C-BARQ. These domains, labeledPlayfulness,Impulsivity,Distractibility, andBasophobia(fear of falling), respectively, describe aspects of canine behavior or temperament which are believed to contribute substantially to working dog performance.

Methods

Exploratory factor analysis (EFA) of owner/handler questionnaire responses based on a sample of 1,117 working odor detection dogs.

Results

A total of 15 factors were extracted by EFA, 10 of which correspond to original C-BARQ factors. The remaining 5 comprise the four new domains–Playfulness,Impulsivity,Distractibility, andBasophobia– as well as a fifth new factor labeledFood focus.

Discussion

The resulting Working Dog Canine Behavioral Assessment & Research Questionnaire (WDC-BARQ) successfully expands the measurement capacities of the original C-BARQ to include dimensions of behavior/temperament of particular relevance to many working dog populations.
Seroprevalence of Mycobacterium avium subsp. paratuberculosis in Swiss dairy herds and risk factors for a positive herd status and within-herd prevalence
Authors: Ottardi Martina , Lechner Isabel , Wang Jessica , Schmitt Sarah , Schneeberger Marianne , Schmid Robin Michael , Stephan Roger , Meylan Mireille
Published: June 2024

Introduction

Bovine paratuberculosis (PTB) is a chronic enteric disease caused by Mycobacterium avium subsp. paratuberculosis (MAP). Control of PTB is important given its negative economic consequences and the potential zoonotic role of MAP in Crohn’s disease in humans.

Methods

To determine the seroprevalence of MAP in Swiss dairy herds and to identify risk factors associated with seropositive herd status and high within-herd seroprevalence, 10,063 serum samples collected from cattle over 12 months of age in 171 Swiss dairy farms were analyzed using a commercial ELISA test. Eight herds were excluded due to non-interpretable ELISA results. Risk factors associated with seropositive herd status and high within-herd seroprevalence were investigated with regression models using results from a questionnaire on management practices possibly associated with the introduction or spread of MAP in the remaining 163 herds. Univariable logistic regression was performed, carrying forward for multivariable regression analysis when p < 0.2.

Results

The calculated between-herd true seroprevalence was 3.6% (95% CI, 0.96–8.4%). Due to the low within-herd seroprevalence, it was not possible to calculate the true seroprevalence at animal level; the apparent within-herd seroprevalence ranged from 2.3 to 5.5% with a median of 3.6% in nine positive farms. Herd size (p = 0.037) and the common grazing of lactating cows with cows from other herds (p = 0.014) were associated with seropositive herd status, while heifers sharing alpine pasture with dairy cattle from other herds were associated with a decreased probability of the herd to test seropositive (p = 0.042). Reliable identification of significant risk factors associated with MAP spread and high seroprevalence of PTB within seropositive herds was not possible due to low observed seroprevalence within herds and low sensitivity of the ELISA test.

Discussion

These results highlight the limitation of serology for MAP diagnosis in small herds with low infection prevalence.
Diagnosis of Teleworking in Argentina during the Pandemic: Application of the Telework Efficiency Index
Authors: Maresca Gabriel Gustavo
Published: June 2024

Present the most significant findings that were obtained within the framework of the Support Program for Teaching Researchers “PROAPI2021” of the Secretariat of Research and Technological and Institutional Linkage of the National University of Avellaneda of Argentina. (1) Background: Investigate the strengths and weaknesses of companies when implementing teleworking during the COVID-19 pandemic to continue with the productive matrix; (2) Methods: The fieldwork focuses on the study of 19 companies from the five productive sectors with the greatest representation in the town of Avellaneda, Argentina, using a teleworking efficiency index as a measurement instrument; (3) Results: The main results in terms of efficiency occur with the possibility of combining work with family life at 97.05%, the enthusiasm and motivation to telework at 84.45%, and the assurance of optimal internet connection quality by 74.6%; (4) Conclusions: The study shows that the variables that present the greatest efficiency are those that are more related to the traditional work scheme, and not to the new modality offered by teleworking. We continue to think about a conventional work model.
Global Attention-Based DEM: A Planet Surface Digital Elevation Model-Generation Method Combined with a Global Attention Mechanism
Authors: Yang Li , Zhu Zhijie , Sun Long , Zhang Dongping
Published: June 2024

Digital elevation models (DEMs), which can provide an accurate description of planetary surface elevation changes, play an important role in scientific tasks such as long-distance path planning, terrain analysis, and planetary surface reconstruction. However, generating high-precision planetary DEMs currently relies on expensive equipment together with complex remote sensing technology, thus increasing the cost and cycle of the task. Therefore, it is crucial to develop a cost-effective technology that can produce high-quality DEMs on the surfaces of planets. In this work, we propose a global attention-based DEM generation network (GADEM) to convert satellite imagery into DEMs. The network uses the global attention mechanism (GAM) together with a multi-order gradient loss function during training to recover precise terrain. The experimental analysis on lunar and Martian datasets not only demonstrated the effectiveness and accuracy of GADEM in bright regions, but also showed its promising reconstruction ability in shadowed regions.
Identification and Functional Characterization of an Odorant Receptor Expressed in the Genitalia of Helicoverpa armigera
Authors: Liu Weihao , Sun Dongdong , Wang Xiaoqing , Wang Zhiqiang , Liu Yang
Published: June 2024

Olfaction is critical for guiding the physiological activities of insects, with antennae being the primary olfactory organs. However, recent evidence suggests that other tissues may also participate in olfactory recognition. Among these, the genitalia of moths have received attention due to their roles in mating and oviposition. Sensilla and odorant receptors (ORs) in moth genitalia highlight the potential olfactory function of these structures. In this study, we examined the olfactory sensing capacity of the genitalia in Helicoverpa armigera by analyzing their structure in males and females and characterizing the expressed ORs. Scanning electron microscopy uncovered many sensilla distributed throughout the male and female genitalia. Transcriptome sequencing identified 20 ORs in the genitalia, with HarmOR68 exhibiting significant responses to methyl esters: methyl benzoate and salicylate. Our findings provide theoretical evidence that H. armigera genitalia may have significant olfactory perception functions.
High-Resolution Yield Mapping for Eucalyptus grandis—A Case Study
Authors: Dias Rafael Donizetti , Molin José Paulo , Wei Marcelo Chan Fu , Alvares Clayton Alcarde
Published: June 2024

Yield data represent a valuable layer for supporting decision-making as they reflect crop management results. Forestry decision-makers often rely on coarse spatial resolution data (e.g., forest inventory plots) despite the availability of modern harvesters that can provide high-resolution forestry yield data. The objectives of this study were to present a method for generating high-resolution Eucalyptus grandis yield data (individual tree-level) and explore their applications, such as correlation analysis with soil attributes to aid nutrient recommendations. Two evaluations were conducted at two sites in Brazil: (a) assessing the positioning accuracy of the global navigation satellite system (GNSS) receiver positioning, and (b) analyzing the yield data and their correlation with the soil attributes. The results indicated that positioning the GNSS receiver at the harvesting head provided higher accuracy than placement at the top of the harvester cabin for individual tree-level data. Reliable yield data were generated despite the GNSS receiver’s increased susceptibility to damage when mounted on a harvest head. The linear correlation analysis between the Eucalyptus grandis yield data and soil attributes showed both negative (Clay, B, S, coarse sand, and potential acidity − H + Al) and positive correlations (K, Mg, pH-SMP, Ca, sum of bases, pH, base saturation, fine sand, total sand, and silt content). This study demonstrates the feasibility of obtaining high-resolution yield data at the individual tree-level and their correlation with soil attributes, providing valuable insights for improving forestry decision-making.
A Review of Natural-Language-Instructed Robot Execution Systems
Authors: Liu Rui , Guo Yibei , Jin Runxiang , Zhang Xiaoli
Published: June 2024

It is natural and efficient to use human natural language (NL) directly to instruct robot task executions without prior user knowledge of instruction patterns. Currently, NL-instructed robot execution (NLexe) is employed in various robotic scenarios, including manufacturing, daily assistance, and health caregiving. It is imperative to summarize the current NLexe systems and discuss future development trends to provide valuable insights for upcoming NLexe research. This review categorizes NLexe systems into four types based on the robot’s cognition level during task execution: NL-based execution control systems, NL-based execution training systems, NL-based interactive execution systems, and NL-based social execution systems. For each type of NLexe system, typical application scenarios with advantages, disadvantages, and open problems are introduced. Then, typical implementation methods and future research trends of NLexe systems are discussed to guide the future NLexe research.
Artificial Intelligence-Driven Facial Image Analysis for the Early Detection of Rare Diseases: Legal, Ethical, Forensic, and Cybersecurity Considerations
Authors: Kováč Peter , Jackuliak Peter , Bražinová Alexandra , Varga Ivan , Aláč Michal , Smatana Martin , Lovich Dušan , Thurzo Andrej
Published: June 2024

This narrative review explores the potential, complexities, and consequences of using artificial intelligence (AI) to screen large government-held facial image databases for the early detection of rare genetic diseases. Government-held facial image databases, combined with the power of artificial intelligence, offer the potential to revolutionize the early diagnosis of rare genetic diseases. AI-powered phenotyping, as exemplified by the Face2Gene app, enables highly accurate genetic assessments from simple photographs. This and similar breakthrough technologies raise significant privacy and ethical concerns about potential government overreach augmented with the power of AI. This paper explores the concept, methods, and legal complexities of AI-based phenotyping within the EU. It highlights the transformative potential of such tools for public health while emphasizing the critical need to balance innovation with the protection of individual privacy and ethical boundaries. This comprehensive overview underscores the urgent need to develop robust safeguards around individual rights while responsibly utilizing AI’s potential for improved healthcare outcomes, including within a forensic context. Furthermore, the intersection of AI and sensitive genetic data necessitates proactive cybersecurity measures. Current and future developments must focus on securing AI models against attacks, ensuring data integrity, and safeguarding the privacy of individuals within this technological landscape.
Preamble for the “Feature Paper Collection of Advanced Research on Alloys”
Authors: Stanford Nikki
Published: June 2024

This year, several hot topics have emerged in alloy research and design; we have collected a few of these in this feature paper collection for your enjoyment [...]
Veterinary Telemedicine in Lithuania: Analysis of the Current Market, Animal Owner Knowledge, and Success Factors for Digital Transformation of Clinics
Authors: Juodžentė Dalia , Burbaitė Evelina , Stankevičius Rolandas , Karvelienė Birutė , Rudejevienė Jūratė , Daunorienė Asta
Published: June 2024

Veterinary telemedicine is used to provide animal health care information, education, and care remotely. Digital transformation of veterinary clinics is a fundamental process for the evolution of telemedicine and is changing the way veterinary care and animal health services are delivered. This study aimed to evaluate the current televeterinary market and to assess the knowledge of animal owners and clinic managers. The goals of this study were met by conducting an analysis of the current televeterinary market through a pet owner (n = 200) survey as well as clinic owner (n = 5) interviews. In contrast to other countries, only 1.85% of Lithuanian veterinary clinics offered a paid veterinary remote consultation service on their websites. In addition, more than half of animal owners who participated in the survey did not even know that remote veterinary consultations existed. The most important established factors for the success of digital transformation of veterinary telemedicine were investments in the marketing of the services, management leadership, the competencies and experience of veterinarians, convenient working hours for the client, faster service availability, and lower price. It is recommended to involve marketing and information technology company professionals and to invest in the specialty, digital, and communication skills of veterinarians.
Current View on Major Natural Compounds Endowed with Antibacterial and Antiviral Effects
Authors: Arrigoni Roberto , Ballini Andrea , Jirillo Emilio , Santacroce Luigi
Published: June 2024

Nowadays, infectious diseases of bacterial and viral origins represent a serious medical problem worldwide. In fact, the development of antibiotic resistance is responsible for the emergence of bacterial strains that are refractory even to new classes of antibiotics. Furthermore, the recent COVID-19 pandemic suggests that new viruses can emerge and spread all over the world. The increase in infectious diseases depends on multiple factors, including malnutrition, massive migration of population from developing to industrialized areas, and alteration of the human microbiota. Alternative treatments to conventional antibiotics and antiviral drugs have intensively been explored. In this regard, plants and marine organisms represent an immense source of products, such as polyphenols, alkaloids, lanthipeptides, and terpenoids, which possess antibacterial and antiviral activities. Their main mechanisms of action involve modifications of bacterial cell membranes, with the formation of pores, the release of cellular content, and the inhibition of bacterial adherence to host cells, as well as of the efflux pump. Natural antivirals can interfere with viral replication and spreading, protecting the host with the enhanced production of interferon. Of note, these antivirals are not free of side effects, and their administration to humans needs more research in terms of safety. Preclinical research with natural antibacterial and antiviral compounds confirms their effects against bacteria and viruses, but there are still only a few clinical trials. Therefore, their full exploitation and more intensive clinical studies represent the next steps to be pursued in this area of medicine.
Antioxidant Profile, Amino Acids Composition, and Physicochemical Characteristics of Cherry Tomatoes Are Associated with Their Color
Authors: Baek Min Woo , Lee Jong Hwan , Yeo Chang Eun , Tae Su Ho , Chang Se Min , Choi Han Ryul , Park Do Su , Tilahun Shimeles , Jeong Cheon Soon
Published: June 2024

This study was conducted to characterize different colored lines of cherry tomatoes and derive information regarding their metabolite accumulation. Different colored cherry tomato cultivars, namely ‘Jocheong’, ‘BN Satnolang’, ‘Gold Chance’, ‘Black Q’, and ‘Snacktom’, were assessed for their firmness, taste characteristics, and nutritional metabolites at the commercial ripening stage. The cultivars demonstrated firmness to withstand impacts during harvesting and postharvest operations. The significant variations in the Brix to acid ratio (BAR) and the contents of phenylalanine, glutamic acid, and aspartic acid highlight the distinct taste characteristics among the cultivars, and the nutritional metabolites are associated with the color of the cultivars. The cultivar choices would be the black-colored ‘Black Q’ for chlorophylls, β-carotene, total flavonoids, and anthocyanins; the red-colored ‘Snacktom’ for lycopene; the orange-colored ‘Gold Chance’ for total phenolics; and the green-colored ‘Jocheong’ for chlorophylls, vitamin C, GABA, glutamic acid, essential amino acids, and total free amino acids. The antioxidant capacity varied among the cultivars, with ‘Gold Chance’ consistently exhibiting the highest activity across the four assays, followed by ‘Snacktom’. This study emphasizes the importance of screening cultivars to support breeding programs for improving the nutritional content and encourages the inclusion of a diverse mix of different colored cherry tomatoes in packaging to obtain the cumulative or synergistic effects of secondary metabolites.
Open-Source Robotic Study Companion with Multimodal Human–Robot Interaction to Improve the Learning Experience of University Students
Authors: Baksh Farnaz , Zorec Matevž Borjan , Kruusamäe Karl
Published: June 2024

Remote, online learning provides opportunities for flexible, accessible, and personalised education, regardless of geographical boundaries. This study mode also promises to democratise education, making it more adaptable to individual learning styles. However, transitioning to this digital paradigm also brings challenges, including issues related to students’ mental health and motivation and communication barriers. Integrating social robots into this evolving educational landscape presents an effective approach to enhancing student support and engagement. In this article, we focus on the potential of social robots in higher education, identifying a significant gap in the educational technology landscape that could be filled by open-source learning robots tailored to university students’ needs. To bridge this gap, we introduce the Robotic Study Companion (RSC), a customisable, open-source social robot developed with cost-effective off-the-shelf parts. Designed to provide an interactive and multimodal learning experience, the RSC aims to enhance student engagement and success in their studies. This paper documents the development of the RSC, from establishing literature-based requirements to detailing the design process and build instructions. As an open development platform, the RSC offers a solution to current educational challenges and lays the groundwork for personalised, interactive, and affordable AI-enabled robotic companions.
A Method for Evaluating User Interface Satisfaction Using Facial Recognition Technology and a PSO-BP Neural Network
Authors: Li Qingchen , Zheng Bingzhu , Wu Tianyu , Li Yajun , Hao Pingting
Published: June 2024

User satisfaction serves as a crucial reference for iteratively optimizing software interface designs. This paper introduces a comprehensive measurement model of user satisfaction, employing Notability and Goodnotes for case studies. The proposed model incorporates facial recognition technology to gauge the intensity of users’ facial expressions while interacting with various functions of the target interface. Additionally, an experimental observation method is employed to gather objective data, including task completion time, task success rates, and operational procedures, alongside users’ subjective evaluations. Leveraging objective data as input and subjective ratings as output, a user satisfaction prediction model based on a PSO-BP neural network has been devised. The results demonstrate an impressive accuracy rate of 86.26%, indicating a high accuracy in subjective perception prediction. This model has proven to be effective for measuring user satisfaction and evaluating software interface usability. Moreover, this research contributes to expanding the repertoire of user interface satisfaction evaluation methods, enhancing the objectivity of measurements and surpassing the efficiency of conventional experimental evaluation techniques. The proposed model holds practical significance for software interface usability assessment and optimization design.
Research on Automated Fiber Placement Surface Defect Detection Based on Improved YOLOv7
Authors: Wen Liwei , Li Shihao , Dong Zhentao , Shen Haiqing , Xu Entao
Published: June 2024

Due to the black and glossy appearance of the carbon fiber prepreg bundle surface, the accurate identification of surface defects in automated fiber placement (AFP) presents a high level of difficulty. Currently, the enhanced YOLOv7 algorithm demonstrates certain performance advantages in this detection task, yet issues with missed detections, false alarms, and low confidence levels persist. Therefore, this study proposes an improved YOLOv7 algorithm to further enhance the performance and generalization of surface defect detection in AFP. Firstly, to enhance the model’s feature extraction capability, the BiFormer attention mechanism is introduced to make the model pay more attention to small target defects, thereby improving feature discriminability. Next, the AFPN structure is used to replace the PAFPN at the neck layer to strengthen feature fusion, preserve semantic information to a greater extent, and finely integrate multi-scale features. Finally, WIoU is adopted to replace CIoU as the bounding box regression loss function, making it more sensitive to small targets, enabling more accurate prediction of object bounding boxes, and enhancing the model’s detection accuracy and generalization capability. Through a series of ablation experiments, the improved YOLOv7 shows a 10.5% increase in mAP and a 14 FPS increase in frame rate, with a maximum detection speed of 35 m/min during the AFP process, meeting the requirements of online detection and thus being able to be applied to surface defect detection in AFP operations.
Glass Defect Detection with Improved Data Augmentation under Total Reflection Lighting
Authors: Ding Pengfei , Yang Liangen
Published: June 2024

To address the technical challenge of identifying tiny defects, especially dust and point defects, on mobile phone flat glass, an automatic optical inspection system is established. The system investigates algorithms including imaging principles, target detection models, data augmentation, foreground segmentation, and image fusion. The system builds an automatic optical inspection platform to collect glass defect samples. It illuminates the glass samples with a combined total reflection–grazing light source, collects the defect sample data, segments the background and defects of the collected data, generates the defect mask, and extracts the complete defects of the cell phone flat glass. The system then seamlessly integrates the extracted defects with a flawless background using Poisson editing and outputs the location information of the defects and the label output to automatically generate the dataset. The deep learning network YOLOv5 works as the core algorithm framework, into which the Constructive Block Attention Module and the small target detection layer are specifically added to enhance the capability of the model to detect small defects. According to the experimental results, the combined lighting effectively improves the precision of detecting dust and bright spots. Additionally, with the adoption of novel data augmentation techniques, the enhanced YOLOv5 model is capable of effectively addressing the challenges posed by inefficient sample data and non-uniform distribution, thus mitigating network generalization issues. Furthermore, this data augmentation approach facilitates the rapid adaptation of the same detection tasks to diverse environmental scenarios, enabling the expedited and efficient deployment of the model across various industrial settings. The mean average precision (MAP) of the optimal model in the validation set reached 98.36%, 2.62% higher than that of the original YOLOv5. In addition, its false acceptance rate (FAR) is 1.27%, its false rejection rate (FRR) was 2.47%, its detection speed was 64 fps, and its correct detection rate in the validation set was 98.75%, which meets the current industrial detection requirements by and large. In this way, this paper achieved the automated inspection of mobile phone flat glass with high robustness, high precision, and a low false acceptance rate and false rejection rate, significantly reducing material losses in the factories and the likelihood of error occurrence in follow-on products. This method can be applied to the multi-scale and multi-type detection of glass defects.
Electric Auditory Brainstem Response Audiometry in Cochlear Implants: New Recording Paradigm
Authors: Gabr Takwa , Debis Hossam , Hafez Ahmed
Published: June 2024

(1) Background: Cochlear implants (CIs) are widely applied to recover audition for patients with severe degrees of or total hearing loss. Electrical stimulation using the electrically evoked ABR (E-ABR) can be recorded in CI recipients through the device. This work was designed to study E-ABR recorded individually from different channels located at the apical, middle, and basal cochlear regions in comparison to their simultaneous separated or adjacent combined recordings. (2) Methods: This study included 17 children fitted with unilateral cochlear implants. All children were subjected to impedance measurement, electrical compound action potentials (ECAP), and E-ABR recording of three channels located at the apical, middle, and basal cochlear regions. This was followed by simultaneous E-ABR recording of the three “separated” channels in comparison to E-ABR recording from three adjacent channels located at the middle cochlear region. (3) Results: Similar E-ABR latencies and amplitudes were found using either individual or simultaneously separated or adjacent combined recording. However, the mean amplitude measures of E-ABR for combined adjacent channels showed a positive correlation with the applied current level. (4) Conclusions: Combined E-ABR recording from adjacent channels is a faster and more reliable technique that can be used effectively without compromising the results of the recorded E-ABR.
Interaction between Plants and Growth-Promoting Rhizobacteria (PGPR) for Sustainable Development
Authors: Mitra Debasis , Pellegrini Marika , Guerra-Sierra Beatriz E.
Published: June 2024

The relationship between plants and microorganisms is of paramount importance in maintaining the delicate balance of life on Earth, as evidenced by their interconnectedness in the intricate tapestry of nature [...]
Validation of Pelvis and Trunk Range of Motion as Assessed Using Inertial Measurement Units
Authors: Ali Farwa , Hogen Cecilia A. , Miller Emily J. , Kaufman Kenton R.
Published: June 2024

Trunk and pelvis range of motion (ROM) is essential to perform activities of daily living. The ROM may become limited with aging or with neuromusculoskeletal disorders. Inertial measurement units (IMU) with out-of-the box software solutions are increasingly being used to assess motion. We hypothesize that the accuracy (validity) and reliability (consistency) of the trunk and pelvis ROM during steady-state gait in normal individuals as measured using the Opal APDM 6 sensor IMU system and calculated using Mobility Lab version 4 software will be comparable to a gold-standard optoelectric motion capture system. Thirteen healthy young adults participated in the study. Trunk ROM, measured using the IMU was within 5–7 degrees of the motion capture system for all three planes and within 10 degrees for pelvis ROM. We also used a triad of markers mounted on the sternum and sacrum IMU for a head-to-head comparison of trunk and pelvis ROM. The IMU measurements were within 5–10 degrees of the triad. A greater variability of ROM measurements was seen for the pelvis in the transverse plane. IMUs and their custom software provide a valid and reliable measurement for trunk and pelvis ROM in normal individuals, and important considerations for future applications are discussed.
Integrating PointNet-Based Model and Machine Learning Algorithms for Classification of Rupture Status of IAs
Authors: Shou Yilu , Chen Zhenpeng , Feng Pujie , Wei Yanan , Qi Beier , Dong Ruijuan , Yu Hongyu , Li Haiyun
Published: June 2024

Background: The rupture of intracranial aneurysms (IAs) would result in subarachnoid hemorrhage with high mortality and disability. Predicting the risk of IAs rupture remains a challenge. Methods: This paper proposed an effective method for classifying IAs rupture status by integrating a PointNet-based model and machine learning algorithms. First, medical image segmentation and reconstruction algorithms were applied to 3D Digital Subtraction Angiography (DSA) imaging data to construct three-dimensional IAs geometric models. Geometrical parameters of IAs were then acquired using Geomagic, followed by the computation of hemodynamic clouds and hemodynamic parameters using Computational Fluid Dynamics (CFD). A PointNet-based model was developed to extract different dimensional hemodynamic cloud features. Finally, five types of machine learning algorithms were applied on geometrical parameters, hemodynamic parameters, and hemodynamic cloud features to classify and recognize IAs rupture status. The classification performance of different dimensional hemodynamic cloud features was also compared. Results: The 16-, 32-, 64-, and 1024-dimensional hemodynamic cloud features were extracted with the PointNet-based model, respectively, and the four types of cloud features in combination with the geometrical parameters and hemodynamic parameters were respectively applied to classify the rupture status of IAs. The best classification outcomes were achieved in the case of 16-dimensional hemodynamic cloud features, the accuracy of XGBoost, CatBoost, SVM, LightGBM, and LR algorithms was 0.887, 0.857, 0.854, 0.857, and 0.908, respectively, and the AUCs were 0.917, 0.934, 0.946, 0.920, and 0.944. In contrast, when only utilizing geometrical parameters and hemodynamic parameters, the accuracies were 0.836, 0.816, 0.826, 0.832, and 0.885, respectively, with AUC values of 0.908, 0.922, 0.930, 0.884, and 0.921. Conclusion: In this paper, classification models for IAs rupture status were constructed by integrating a PointNet-based model and machine learning algorithms. Experiments demonstrated that hemodynamic cloud features had a certain contribution weight to the classification of IAs rupture status. When 16-dimensional hemodynamic cloud features were added to the morphological and hemodynamic features, the models achieved the highest classification accuracies and AUCs. Our models and algorithms would provide valuable insights for the clinical diagnosis and treatment of IAs.
Effect of Young Plasma Therapy on Cognition, Oxidative Stress, miRNA-134, BDNF, CREB, and SIRT-1 Expressions and Neuronal Survey in the Hippocampus of Aged Ovariectomized Rats with Alzheimer’s
Authors: Habibi Parisa , Shahidi Siamak , Khajvand-Abedini Maryam , Shahabi Zahra , Ahmadiasl Nasser , Alipour Mohammad Reza , Ramezani Mahdi , Komaki Alireza
Published: June 2024

Menopause may increase the risk of Alzheimer’s disease (AD) dementia. This study aimed to use young plasma therapy (YPT) to improve dementia caused by AD in aged ovariectomized rats. Female Wistar rats were used in the following groups: (a) young (CY) (180–200 g, 2–3 months, n = 10) and (b) old groups (250–350 g, 22–24 months, n = 60). The old rats were randomly assigned to six sub-groups: (1) control, (2) sham, (3) ovariectomized group (OVX), (4) OVX + Alzheimer disease (OVX + AD), (5) OVX + AD+ 17β-Estradiol (OVX + AD + E), and (6) OVX + AD + young plasma (OVX + AD + YP). Cognitive behaviors were evaluated using NOR, MWM, and PAL tests. MiR-134a, SIRT-1, CREB, and BDNF expressions were measured using real-time PCR and western blot, respectively. Oxidative stress in hippocampal tissue was assayed using ELISA kits. OVX and AD caused significant cognitive impairment (p < 0.001), up-regulated miR-134a (p < 0.001), down-regulated SIRT-1, CREB, and BDNF protein expression (p < 0.001), and decreased antioxidant marker levels (p < 0.001) compared to the sham group. YPT significantly restored miR-134a (p < 0.001), SIRT-1 (p < 0.001), CREB (p < 0.001), and BDNF (p < 0.001) protein expression in OVX + AD rats. YPT, as much as or more than estrogen therapy (ERT), significantly improved oxidative stress and down-regulated miR-134a expression and the up-regulation of SIRT-1, CREB, and BDNF proteins in OVX + AD rats (p < 0.001). YPT significantly improved histological alteration compared to the OVX + AD group (p < 0.001). As a non-pharmacological treatment, YPT can improve the expression of miR-134a and SIRT-1, CREB, and BDNF proteins as much as or more than estrogen therapy, ameliorating AD-induced dementia in aged OVX rats.
Vibration-Induced Alteration in Trunk Extensor Muscle Proprioception as a Model for Impaired Trunk Control in Low Back Pain
Authors: Gilliam John R. , Mandal Debdyuti , Wattananon Peemongkon , Banerjee Sourav , Herter Troy M. , Silfies Sheri P.
Published: June 2024

This study examined the impact of personalizing muscle vibration parameters on trunk control. We assessed how altered trunk extensor muscle (TEM) proprioception affects seated trunk control in healthy controls (HCs). To explore the link between altered TEM proprioception and impaired trunk control in chronic low back pain (cLBP), we performed equivalence testing between HCs undergoing TEM vibration and cLBP without vibration. Twenty HCs performed active joint reposition error (AJRE) testing to determine personalized vibration parameters. Each participant maintained balance on an unstable chair with eyes open and closed, with and without TEM vibration. We compared trunk control between HCs and twenty age- and sex-matched cLBP participants, using mean velocity and 95% confidence ellipse area of center-of-pressure changes to quantify trunk postural control. Equivalence was examined by comparing mean difference scores to minimal detectable change values and calculating between-group effect sizes. Personalized vibration parameters led to larger lumbopelvic repositioning errors (d = 0.89) than any single vibration frequency (d = 0.31–0.36). In healthy adults with no back pain, vision had large effects on postural control (ηp2 = 0.604–0.842), but TEM vibration had no significant effects (p > 0.105) or interactions with vision (p > 0.423). Between-group effect sizes (d = 0.32–0.51) exceeded our threshold for performance equivalence (d < 0.2). Muscle vibration altered position sense during AJRE testing, and personalizing parameters amplified this effect. However, TEM vibration had minimal impact on seated trunk postural control in adults with no back pain and did not lead to performance degradation comparable to that in cLBP.
Optimizing and Predicting Antidepressant Efficacy in Patients with Major Depressive Disorder Using Multi-Omics Analysis and the Opade AI Prediction Tools
Authors: Corrivetti Giulio , Monaco Francesco , Vignapiano Annarita , Marenna Alessandra , Palm Kaia , Fernández-Arroyo Salvador , Frigola-Capell Eva , Leen Volker , Ibarrola Oihane , Amil Burak , Caruson Mattia Marco , Chiariotti Lorenzo , Palacios-Ariza Maria Alejandra , Hoekstra Pieter J. , Chiang Hsin-Yin , Floareș Alexandru , Fagiolini Andrea , Fasano Alessio
Published: June 2024

According to the World Health Organization (WHO), major depressive disorder (MDD) is the fourth leading cause of disability worldwide and the second most common disease after cardiovascular events. Approximately 280 million people live with MDD, with incidence varying by age and gender (female to male ratio of approximately 2:1). Although a variety of antidepressants are available for the different forms of MDD, there is still a high degree of individual variability in response and tolerability. Given the complexity and clinical heterogeneity of these disorders, a shift from “canonical treatment” to personalized medicine with improved patient stratification is needed. OPADE is a non-profit study that researches biomarkers in MDD to tailor personalized drug treatments, integrating genetics, epigenetics, microbiome, immune response, and clinical data for analysis. A total of 350 patients between 14 and 50 years will be recruited in 6 Countries (Italy, Colombia, Spain, The Netherlands, Turkey) for 24 months. Real-time electroencephalogram (EEG) and patient cognitive assessment will be correlated with biological sample analysis. A patient empowerment tool will be deployed to ensure patient commitment and to translate patient stories into data. The resulting data will be used to train the artificial intelligence/machine learning (AI/ML) predictive tool.
Differential Reinforcement without Extinction: An Assessment of Sensitivity to and Effects of Reinforcer Parameter Manipulations
Authors: MacNaul Hannah , Cividini-Motta Catia , Randall Kayla
Published: June 2024

Although functional communication training (FCT) usually includes extinction, withholding reinforcement is not possible or ethical with certain individuals, for some topographies of problem behavior, or in certain contexts. The current study evaluates the effects of two variations of FCT, both without extinction, on problem behavior and communication. Further, the intervention procedures were designed to evaluate participant reactivity to reinforcer parameters (e.g., magnitude, delay, and quality) in the context of the FCT variations. The parameter sensitivity assessments were effective at identifying relevant reinforcer parameters for each participant and both FCT interventions were effective in decreasing problem behavior and increasing communication for all participants. The results demonstrated that FCT was effective regardless of which reinforcer parameter was manipulated. Moreover, all sessions were conducted in participants’ homes and caregivers reported high degrees of social validity for the intervention procedures and outcomes.