bluuebunny/crossref_metadata_2025 huggingface dataset:
On translational control by ribosome speed in S. cerevisiae
Authors: Kazana Eleanna , von der Haar Tobias
Published: August 2023

Introduction: In addition to the widespread and well documented control of protein synthesis by translation initiation, recent evidence suggests that translation elongation can also control protein synthesis rates. One of the proposed mechanisms leading to elongation control is the interference of slow ribosome movement around the start codon with efficient translation initiation. Here we estimate the frequency with which this mode of control occurs in baker’s yeast growing in rich medium.

Methods: We interrogate published genome-wide datasets for evidence of transcripts associated with queueing small ribosomal subunits, and confirm results from these surveys using additional experimental work.

Results: Our analyses reveal that transcripts from around 20% of yeast genes show evidence of queueing ribosomes, which may be indicative of translation elongation control. Moreover, this subset of transcripts is sensitive to distinct regulatory signals compared to initiation-controlled mRNAs, and such distinct regulation occurs, for example, during the response to osmotic stress.

Discussion: Our analyses provide a first quantitative estimate for the prevalence of translational control exerted via the elongation stage in a commonly used model organism, and suggest that transcript under elongation control form a separately addressable RNA regulon.
Designing circular innovation ecosystems: insights from stakeholders, values, and investment policies
Authors: Asgari Amir , Asgari Reza
Published: August 2023

Adopting the circular economy principles as a solution to overcome the challenges of the linear economy is increasing globally. In this regard, the related studies showed that circularity is a property of systems, not individual entities. Therefore, any ecosystem design process, including the implementation of circular innovation ecosystems (CIEs), needs in-depth and comprehensive insights into the design process, transformation of ecosystem components, and transition requirements toward circular ecosystems. This study utilized a two-step research methodology consisting of a systematic literature review on sustainable innovation ecosystems and CIEs alongside using grounded theory coding procedures to analyze 10 interviews based on an analytical ecosystem modeling tool to investigate the transformation of ecosystem components in circular ecosystems. Our findings illustrated that circular ecosystem design needs ecosystem actors' synchronic and incremental evolvement. The results also showed that implementing the CIEs requires broader networks of stakeholders, a new interactive economic model, an open platform for co-innovation and co-creation, transforming ecosystem value propositions, and defining new investment models and policies. The findings also inform policymakers and ecosystem researchers about the requirements of any transition toward CE ecosystems. Accordingly, proper policy-making structures and models for tackling transformation obstacles are provided.
Diagnostic Performance of a Mnemonic for Warning Symptoms in Predicting Acute Coronary Syndrome Diagnosis: A Retrospective Cross-Sectional Study
Authors: Sattayaraksa Attakowit , Ananchaisarp Thareerat , Vichitkunakorn Polathep , Chichareon Ply , Tantarattanapong Siriwimon
Published: August 2023

Objectives: We aimed to create a mnemonic for acute coronary syndrome (ACS) warning symptoms and determine its diagnostic performance.

Methods: This retrospective cross-sectional study included patients visiting the emergency room with symptoms of suspected ACS during 2020–2021. The mnemonic was created using symptoms with an odds ratio (OR) for predicting ACS >1.0. The mnemonic with the highest OR and sensitivity was identified. Sensitivity analysis was performed to test the diagnostic performance of the mnemonic by patient subgroups commonly exhibiting atypical symptoms.

Results: ACS prevalence was 12.2% (415/3,400 patients). The mnemonic, “RUSH ChesT” [if you experience referred pain (R), unexplained sweating (U), shortness of breath (S), or heart fluttering (H) together with chest pain (C), visit the hospital in a timely (T) manner] had the best OR [7.81 (5.93–10.44)] and sensitivity [0.81 (0.77–0.85)]. This mnemonic had equal sensitivity in men and women, the elderly and adults, smokers and non-smokers, and those with and without diabetes or hypertension.

Conclusion: The “RUSH ChesT” mnemonic shows good diagnostic performance for patient suspected ACS. It may effectively help people memorize ACS warning symptoms.
A Stealth–Distance Dynamic Weight Deep Q-Network Algorithm for Three-Dimensional Path Planning of Unmanned Aerial Helicopter
Authors: Wang Zeyang , Huang Jun , Yi Mingxu
Published: August 2023

Unmanned aerial helicopters (UAHs) have been widely used recently for reconnaissance operations and other risky missions. Meanwhile, the threats to UAHs have been becoming more and more serious, mainly from radar and flights. It is essential for a UAH to select a safe flight path, as well as proper flying attitudes, to evade detection operations, and the stealth abilities of the UAH can be helpful for this. In this paper, a stealth–distance dynamic weight Deep Q-Network (SDDW-DQN) algorithm is proposed for path planning in a UAH. Additionally, the dynamic weight is applied in the reward function, which can reflect the priorities of target distance and stealth in different flight states. For the path-planning simulation, the dynamic model of UAHs and the guidance model of flight are put forward, and the stealth model of UAHs, including the radar cross-section (RCS) and the infrared radiation (IR) intensity of UAHs, is established. The simulation results show that the SDDW-DQN algorithm can be helpful in the evasion by UAHs of radar detection and flight operations, and the dynamic weight can contribute to better path-planning results.
Research on Unmanned Aerial Vehicle Cluster Collaborative Countermeasures Based on Dynamic Non-Zero-Sum Game under Asymmetric and Uncertain Information
Authors: Wu Pengcheng , Wang Hongqiao , Liang Gaowei , Zhang Peng
Published: August 2023

Unmanned aerial vehicle (UAV) swarm coordinated confrontation is a hot topic in academic research at home and abroad, and dynamic maneuver decision-making is one of the most important research fields for UAV countermeasures. Aiming at the complexity, uncertainty and confrontation of UAV cooperative confrontation, concepts such as relative advantage degree and advantage coefficient are introduced, and game theory is used as a framework to construct a dynamic non-zero-sum game UAV cluster cooperative confrontation decision-making model, and finally convert it into an optimization problem. On this basis, using the Nash equilibrium solution method of multi-strategy fusion particle swarm algorithm, by introducing adaptive inertia weight and local mutation strategy, while enhancing the diversity of the population, it can ensure the local accurate search ability of the particle swarm. The simulation results of the example are verified. The effectiveness of the proposed model and method is confirmed.
The Development of an Advanced Air Mobility Flight Testing and Simulation Infrastructure
Authors: Altun Arinc Tutku , Hasanzade Mehmet , Saldiran Emre , Guner Guney , Uzun Mevlut , Fremond Rodolphe , Tang Yiwen , Bhundoo Prithiviraj , Su Yu , Xu Yan , Inalhan Gokhan , Hardt Michael W. , Fransoy Alejandro , Modha Ajay , Tena Jose Antonio , Nieto Cesar , Vilaplana Miguel , Tojal Marta , Gordo Victor , Menendez Pablo , Gonzalez Ana
Published: August 2023

The emerging field of Advanced Air Mobility (AAM) holds great promise for revolutionizing transportation by enabling the efficient, safe, and sustainable movement of people and goods in urban and regional environments. AAM encompasses a wide range of electric vertical take-off and landing (eVTOL) aircraft and infrastructure that support their operations. In this work, we first present a new airspace structure by considering different layers for standard-performing vehicles (SPVs) and high-performing vehicles (HPVs), new AAM services for accommodating such a structure, and a holistic contingency management concept for a safe and efficient traffic environment. We then identify the requirements and development process of a testing and simulation infrastructure for AAM demonstrations, which specifically aim to explore the decentralized architecture of the proposed concept and its use cases. To demonstrate the full capability of AAM, we develop an infrastructure that includes advanced U-space services, real and simulated platforms that are suitable for future AAM use cases such as air cargo delivery and air taxi operations, and a co-simulation environment that allows all of the AAM elements to interact with each other in harmony. The considered infrastructure is envisioned to be used in AAM integration-related efforts, especially those focusing on U-space service deployment over a complex traffic environment and those analyzing the interaction between the operator, the U-space service provider (USSP), and the air traffic controller (ATC).
On-the-Go Vis-NIR Spectroscopy for Field-Scale Spatial-Temporal Monitoring of Soil Organic Carbon
Authors: Reyes Javier , Ließ Mareike
Published: August 2023

Agricultural soils serve as crucial storage sites for soil organic carbon (SOC). Their appropriate management is pivotal for mitigating climate change. Continuous monitoring is imperative to evaluate spatial and temporal changes in SOC within agricultural fields. In-field datasets of Vis-NIR soil spectra were collected on a long-term experimental site using an on-the-go spectrophotometer. Data processing for continuous SOC prediction involves a two-step modeling approach. In Step 1, a partial least square (PLSR) regression model is trained to establish a relationship between the SOC content and spectral information, including spectral preprocessing. In Step 2, the predicted SOC content obtained from the PLSR models is interpolated using ordinary kriging. Among the tested spectral preprocessing techniques and semivariogram models, Savitzky–Golay and the Gap-Segment derivative preprocessing along with a Gaussian semivariogram model, yielded the best performance resulting in a root mean square error of 1.24 and 1.26 g kg−1. A striping effect due to the transect-based data collection was addressed by testing the effectiveness of extending the spatial separation distance, employing data aggregation, and defining the distribution based on treatment plots using block kriging. Overall, the results highlight the high potential of on-the-go spectral Vis-NIR data for field-scale spatial-temporal monitoring of SOC.
Lettuce Plant Trace-Element-Deficiency Symptom Identification via Machine Vision Methods
Authors: Lu Jinzhu , Peng Kaiqian , Wang Qi , Sun Cong
Published: August 2023

Lettuce is one of the most widely planted leafy vegetables in plant factories. The lack of trace elements in nutrient solutions has caused huge losses to the lettuce industry. Non-obvious symptoms of trace element deficiency, the inconsistent size of the characteristic areas, and the difficulty of extraction in different growth stages are three key problems affecting lettuce deficiency symptom identification. In this study, a batch of cream lettuce (lactuca sativa) was planted in the plant factory, and its nutrient elements were artificially controlled. We collected images of the lettuce at different growth stages, including all nutrient elements and three nutrient-deficient groups (potassium deficiency, calcium deficiency, and magnesium deficiency), and performed feature extraction analysis on images of different defects. We used traditional algorithms (k-nearest neighbor, support vector machine, random forest) and lightweight deep-learning models (ShuffleNet, SqueezeNet, andMobileNetV2) for classification, and we compared different feature extraction methods (texture features, color features, scale-invariant feature transform features). The experiment shows that, under the optimal feature extraction method (color), the random-forest recognition results are the best, with an accuracy rate of 97.6%, a precision rate of 97.9%, a recall rate of 97.4%, and an F1 score of 97.6%. The accuracies of all three deep-learning models exceed 99.5%, among which ShuffleNet is the best, with the accuracy, precision, recall, and F1 score above 99.8%. It also uses fewer floating-point operations per second and less time. The proposed method can quickly identify the trace elements lacking in lettuce, and it can provide technical support for the visual recognition of the disease patrol robot in the plant factory.
Morley: Image Analysis and Evaluation of Statistically Significant Differences in Geometric Sizes of Crop Seedlings in Response to Biotic Stimulation
Authors: Emekeeva Daria D. , Kusainova Tomiris T. , Levitsky Lev I. , Kazakova Elizaveta M. , Ivanov Mark V. , Olkhovskaya Irina P. , Kuskov Mikhail L. , Zhigach Alexey N. , Glushchenko Nataliya N. , Bogoslovskaya Olga A. , Tarasova Irina A.
Published: August 2023

Image analysis is widely applied in plant science for phenotyping and monitoring botanic and agricultural species. Although a lot of software is available, tools integrating image analysis and statistical assessment of seedling growth in large groups of plants are limited or absent, and do not cover the needs of researchers. In this study, we developed Morley, a free, open-source graphical user interface written in Python. Morley automates the following workflow: (1) group-wise analysis of a few thousand seedlings from multiple images; (2) recognition of seeds, shoots, and roots in seedling images; (3) calculation of shoot and root lengths and surface area; (4) evaluation of statistically significant differences between plant groups; (5) calculation of germination rates; and (6) visualization and interpretation. Morley is designed for laboratory studies of biotic effects on seedling growth, when the molecular mechanisms underlying the morphometric changes are analyzed. The performance was tested using cultivars of Triticum aestivum and Pisum sativum on seedlings of up to 1 week old. The accuracy of the measured morphometric parameters was comparable with that obtained using ImageJ and manual measurements. Possible applications of Morley include dose-dependent laboratory tests for germination affected by new bioactive compounds and fertilizers.
Long-Term Dietary Fish Meal Substitution with the Black Soldier Fly Larval Meal Modifies the Caecal Microbiota and Microbial Pathway in Laying Hens
Authors: Zhao Junliang , Ban Takuma , Miyawaki Hironori , Hirayasu Hirofumi , Izumo Akihisa , Iwase Shun-ichiro , Kasai Koji , Kawasaki Kiyonori
Published: August 2023

Feeding laying hens with black soldier fly larval (BSFL) meal improves their performance. However, the beneficial mechanism of BSFL meals in improving the performance of laying hens remains unclear. This study investigated the effects of the BSFL diet on liver metabolism, gut physiology, and gut microbiota in laying hens. Eighty-seven Julia hens were randomly assigned to three groups based on their diets and fed maize grain-and soybean meal-based diets mixed with either 3% fish meal (control diet), 1.5% fish and 1.5% BSFL meals, or 3% BSFL meal for 52 weeks. No significant differences were observed in biochemical parameters, hepatic amino acid and saturated fatty acid contents, intestinal mucosal disaccharidase activity, and intestinal morphology between BSFL diet-fed and control diet-fed laying hens. However, the BSFL diet significantly increased the abundance of acetic and propionic acid-producing bacteria, caecal short-chain fatty acids, and modified the caecal microbial pathways that are associated with bile acid metabolism. These findings indicate that consuming a diet containing BSFL meal has minimal effects on plasma and liver nutritional metabolism in laying hens; however, it can alter the gut microbiota associated with short-chain fatty acid production as well as the microbial pathways involved in intestinal fat metabolism. In conclusion, this study provides evidence that BSFL can enhance enterocyte metabolism and gut homeostasis in laying hens.
Evaluation of a Saccharomyces cerevisiae Fermentation Product on the Feedlot Performance and Carcass Merit of Hair Lambs Offered an Annual Ryegrass-Hay-Based Finishing Diet: A Pilot Study
Authors: Burt Justin C. , Boyd Jamie A. , Baxter Lisa L. , Garcia-Galicia Ivan A. , Kerley Brittany P.
Published: August 2023

Hair sheep production has increased in recent years, which has resulted in an increased presence in feedlots. Additionally, grass-based finishing systems for ruminant animal production have increased. Data are limited for finishing hair lambs on diets based on cool-season hay. The objective was to evaluate a Saccharomyces cerevisiae fermentation product (SCFP) on the feedlot performance and carcass characteristics of Katahdin lambs offered an annual ryegrass (Lolium multiflorum)-hay-based diet. Twenty-four Katahdin lambs (21.5 ± 2.5 kg BW) were assigned to either the control (CON) or the yeast-supplemented group (SCFP) in a completely randomized design. Lambs were offered a 14% crude protein total mixed ration diet based on annual ryegrass hay. The SCFP group also received the yeast supplement in their diet. Lambs in the SCFP group had a higher final body weight (p < 0.01) and ADG (p = 0.01). Less maximum and total energy were required to cut SCFP lamb meat compared to CON lamb meat (p < 0.03). Results from this study indicated that SCFP supplementation may prove to be beneficial in hair lamb finishing diets. Future research will need to specifically evaluate the use of these products in hair lambs with a larger sample size.
Colonization of the Gastrointestinal Tract of Chicks with Different Bacterial Microbiota Profiles
Authors: Franco Laura , Boulianne Martine , Parent Eric , Barjesteh Neda , Costa Marcio C.
Published: August 2023

This study aimed to investigate the consequences of early-life microbiota transplantation using different caecal content sources in broiler chicks. We hypothesized that chicks receiving at-hatch microbiota from organic hens would harbour a distinct microbiota from chicks receiving industry-raised broiler microbiota after six weeks of age. Three hundred Cobb broilers eggs were randomly assigned to one of four groups according to the caecal content received: organic laying hens (Organic); autoclaved caecal content of organic laying hens (Autoclaved); conventionally grown broilers (Conventional); and sterile saline (Control). caecal microbiota transplantation was given by gavage on day 1. Ten birds/group were euthanized on days 2, 7, 14, 28, and 42. The caecal tonsils and contents were collected for cytokines and microbiota analyses. The microbiota from chicks receiving live inocula resembled the donors’ microbiota from day seven until day 42. The microbiota composition from the chickens who received the Organic inoculum remained markedly different. Starting on day 7, the Organic group had higher richness. Simpson and Shannon’s indices were higher in the Conventional group on days 2 and 7. Chickens in the Conventional group presented higher production of IL-1β and IL-6 in plasma on days 2 and 28, increased IL-6 expression in the caecal tonsils at days 7 and 42, and increased IL-12 expression on day 7. However, the Conventional group was infected with Eimeria spp., which likely caused inflammation. In conclusion, microbiota transplantation using different microbiota profiles persistently colonized newly hatched broiler chicks. Future studies evaluating the importance of microbiota composition during infections with common enteropathogens are necessary. This study also highlights the need for a strict screening protocol for pathogens in the donors’ intestinal content.
Early Intra-Abdominal Bacterial Infections after Orthotopic Liver Transplantation: A Narrative Review for Clinicians
Authors: Taddei Riccardo , Riccardi Niccolò , Tiseo Giusy , Galfo Valentina , Biancofiore Giandomenico
Published: August 2023

Despite recent advances in the transplant field, infectious complications after orthotopic liver transplantation (OLT) are major causes of morbidity and mortality. Bacterial intra-abdominal infections (IAIs) are predominant during the first month post-transplantation and affect patient and graft survival. Recently, the emergence of multidrug resistant bacteria has generated great concern in OLT patients. We performed this narrative review of the literature in order to propose a “ready-to-use” flowchart for reasoned empirical antibiotic therapy in the case of suspected post-OLT IAIs. The review was ultimately organized into four sections: “Epidemiology and predisposing factors for IAI”; “Surgical-site infections and perioperative prophylaxis”; “MDRO colonization and infections”; and “Reasoned-empirical antibiotic therapy in early intra-abdominal infections post OLT and source control”. Multidisciplinary teamwork is warranted to individualize strategies for the prevention and treatment of IAIs in OLT recipients, taking into account each patient’s risk factors, the surgical characteristics, and the local bacterial epidemiology.
Comparison between Colistin and Polymyxin B in the Treatment of Bloodstream Infections Caused by Carbapenem-Resistant Pseudomonas aeruginosa and Acinetobacter baumannii-calcoaceticus Complex
Authors: Garcia Rebeca Carvalho Lacerda , Rodrigues Rodrigo Douglas , Garcia Ester Carvalho Lacerda , Rigatto Maria Helena
Published: August 2023

Polymyxins are still widely used for the treatment of carbapenem-resistant Acinetobacter baumannii and Pseudomonas aeruginosa bloodstream infections (BSIs). This study seeks to evaluate the impact of polymyxin B versus colistin on mortality and nephrotoxicity in BSI caused by these bacteria. We conducted a retrospective cohort study from 2014 to 2021 in Porto Alegre, Brazil. We included patients aged ≥18 years and excluded patients with polymicrobial infection or treatment for ≤48 h. The 30-day mortality was the primary outcome evaluated through Cox regression. We included 259 patients with BSI episodes: 78.8% caused by A. baumannii and 21.2% caused by P. aeruginosa. Polymyxin B did not impact mortality compared to colistin (adjusted hazard ratio (aHR), 0.82; 95% confidence interval (CI), 0.52–1.30; p = 0.40 (when adjusted for COVID-19 comorbidity, p = 0.05), Pitt bacteremia score, p < 0.01; Charlson comorbidity index, p < 0.001; time to start active antimicrobial therapy, p = 0.02). Results were maintained in the subgroups of BSI caused by A. baumannii (aHR, 0.92; 95% CI, 0.55–1.54; p = 0.74), P. aeruginosa (aHR, 0.47; 95% CI, 0.17–1.32; p = 0.15) and critical care patients (aHR, 0.77; 95% CI, 0.47–1.26; p = 0.30). Treatment with polymyxin B or colistin did not impact 30-day mortality in patients with carbapenem-resistant A. baumannii or P. aeruginosa BSI.
Genetics of Plasma Bilirubin and Associations between Bilirubin and Cardiometabolic Risk Profiles in Danish Children and Adolescents
Authors: Ullah Asmat , Stankevic Evelina , Holm Louise Aas , Stinson Sara E. , Juel Helene Bæk , Fonvig Cilius E. , Lund Morten A. V. , Trier Cæcilie , Engelbrechtsen Line , Ängquist Lars , Jonsson Anna E. , Pedersen Oluf , Grarup Niels , Holm Jens-Christian , Hansen Torben
Published: August 2023

Bilirubin is the end product of heme catabolism, mainly produced by the breakdown of mature red blood cells. Due to its anti-inflammatory, antioxidant, antidiabetic, and antilipemic properties, circulating bilirubin concentrations are inversely associated with the risk of cardiovascular disease, type 2 diabetes, and all-cause mortality in adults. Some genetic loci associated with circulating bilirubin concentrations have been identified by genome-wide association studies in adults. We aimed to examine the relationship between circulating bilirubin, cardiometabolic risk factors, and inflammation in children and adolescents and the genetic architecture of plasma bilirubin concentrations. We measured fasting plasma bilirubin, cardiometabolic risk factors, and inflammatory markers in a sample of Danish children and adolescents with overweight or obesity (n = 1530) and in a population-based sample (n = 1820) of Danish children and adolescents. Linear and logistic regression analyses were performed to analyze the associations between bilirubin, cardiometabolic risk factors, and inflammatory markers. A genome-wide association study (GWAS) of fasting plasma concentrations of bilirubin was performed in children and adolescents with overweight or obesity and in a population-based sample. Bilirubin is associated inversely and significantly with a number of cardiometabolic risk factors, including body mass index (BMI) standard deviation scores (SDS), waist circumference, high-sensitivity C-reactive protein (hs-CRP), homeostatic model assessment for insulin resistance (HOMA-IR), hemoglobin A1c (HbA1c), low-density lipoprotein cholesterol (LDL-C), triglycerides, and the majority of measured inflammatory markers. In contrast, bilirubin was positively associated with fasting plasma concentrations of alanine transaminase (ALT), high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SDS), and the inflammatory markers GH, PTX3, THBS2, TNFRSF9, PGF, PAPPA, GT, CCL23, CX3CL1, SCF, and TRANCE. The GWAS showed that two loci were positively associated with plasma bilirubin concentrations at a p-value threshold of <5 × 10−8 (rs76999922: β = −0.65 SD; p = 4.3 × 10−8, and rs887829: β = 0.78 SD; p = 2.9 × 10−247). Approximately 25% of the variance in plasma bilirubin concentration was explained by rs887829. The rs887829 was not significantly associated with any of the mentioned cardiometabolic risk factors except for hs-CRP. Our findings suggest that plasma concentrations of bilirubin non-causally associates with cardiometabolic risk factors in children and adolescents.
Analytical Modeling and Application for Semi-Circular Notch Flexure Hinges
Authors: Meng Qiaoling , Chen Zhongzhe , Kang Haolun , Shen Zhijia , Yu Hongliu
Published: August 2023

Flexure-based compliant mechanisms can be used to achieve bio-imitability and adaptability in the applications of biomedical engineering. However, a nonlinear load-displacement profile increases the design complexity of this type of compliant mechanism, especially when the cross-section of the flexure hinge is not constant. This paper proposes two general analytical models by analyzing the compliance and stress characteristics of the semi-circular notch flexure hinge undergoing large deflections, which is a typical variable cross-section of a flexure hinge, based on the Castigliano’s second theorem and the finite elements analysis method. As a case study for verification, three compliant four-bar linkage mechanisms are designed based on the proposed design approach, the design method proposed by Howell, and the equations proposed by Lobontiu, respectively. The results show that the design accuracy is improved 36% in comparison with designs from Howell and Lobontiu. Finally, a flexure-based artificial finger is designed and manufactured based on the proposed optimization approach. The performance test of the prototype shows that the artificial finger has good bio-imitability and adaptability with respect to joint movements.
Design Method for Automatic Assembly Production Line of Electric Valves in Space Propulsion Systems
Authors: Zang Xiaohua , Zeng Zhaoqi , Pan Mingqiang , Cai Kun , Liu Quancheng , Wang Xudong , Wei Yanming
Published: August 2023

This article proposes a design method for a valve automatic assembly production line in response to the automation assembly requirements of electric valve products in space propulsion systems and the engineering problems of inaccurate loading force control and low valve measurement accuracy in existing process methods. This method can achieve five assembly processes during the assembly process of electric valves, including pre-tightening force control, valve-core stroke measurement, performance testing, and shell structure welding. The article introduces the design of platform components such as process execution, positioning, and transportation, as well as the design and operation process of workstations. By combining the design of a three-axis motion mechanism, a small turntable, and a robotic arm, the product can achieve professional, positioning, full process automation, and equipment miniaturization design across multiple workstations. Through the design of precise control of loading force and non-contact optical measurement method of moving structure, compared with the original method, the parameters affecting product performance are precisely controlled and the precision is improved. And the multivariable decoupling of valve product performance is realized by this method. Through application verification, this automatic assembly production line can significantly improve the assembly efficiency of electric valve products and solve difficult problems in product engineering.
Shadow Hunter: Low-Illumination Object-Detection Algorithm
Authors: Wu Shuwei , Liu Zhenbing , Lu Haoxiang , Huang Yingxing
Published: August 2023

Recently, object detection, which is focused on images with normal illumination levels, has achieved great success. However, the accuracy of object detection is reduced in suboptimal environments due to the images plagued by noise and low contrast. For boosting the performance of object-detection tasks under low-illumination conditions, we propose three modules for improvement: (1) the low-level feature attention (LFA) module learns to focus on the regional feature information of the object in the low-illumination environment, highlighting important features and filtering noisy information; (2) the feature fusion neck (FFN) obtains enriched feature information by fusing the feature information of the feature map after backbone; (3) the context-spatial decoupling head (CSDH) enables the classification head to focus on contextual semantic information so that the localization head obtains richer spatial details. Extensive experiments show that our algorithm realizing end-to-end detection shows good performance in low-illumination images.
A Neural-Network-Based Landscape Search Engine: LSE Wisconsin
Authors: Haffner Matthew , DeWitte Matthew , Rozario Papia F. , Ovando-Montejo Gustavo A.
Published: August 2023

The task of image retrieval is common in the world of data science and deep learning, but it has received less attention in the field of remote sensing. The authors seek to fill this gap in research through the presentation of a web-based landscape search engine for the US state of Wisconsin. The application allows users to select a location on the map and to find similar locations based on terrain and vegetation characteristics. It utilizes three neural network models—VGG16, ResNet-50, and NasNet—on digital elevation model data, and uses the NDVI mean and standard deviation for comparing vegetation data. The results indicate that VGG16 and ResNet50 generally return more favorable results, and the tool appears to be an important first step toward building a more robust, multi-input, high resolution landscape search engine in the future. The tool, called LSE Wisconsin, is hosted publicly on ShinyApps.io.
Investigating the Impact of Different Partial Overlap Levels on the Perception of Visual Variables for Categorical Data
Authors: Santos Diego , Freitas Alexandre , Lima Rodrigo , Santos Carlos Gustavo , Meiguins Bianchi
Published: August 2023

The overlap of visual items in data visualization techniques is a known problem aggravated by data volume and available visual space issues. Several methods have been applied to mitigate occlusion in data visualizations, such as random jitter, transparency, layout reconfiguration, focus+context techniques, etc. This paper aims to present a comparative study of the reading of visual variables values with partial overlap. The study focuses on categorical data representations varying the percentage limits of partial overlap and the number of distinct values for each visual variable: hue, lightness, saturation, shape, text, orientation, and texture. A computational application generated random scenarios for a unique visual pattern target to perform location tasks. Each scenario involved presentation of the visual items in a grid layout with 160 elements (10 × 16), each visual variable had from three to five distinct values encoded, and the partial overlap percentages applied, represented by a gray square in the center of each grid element, were 0% (control), 50%, 60%, and 70%. Similar to the preliminary tests, the tests conducted in this study involved 48 participants organized into four groups, with 126 tasks per participant, and the application captured the response and time for each task performed. The results analysis indicated that the hue, lightness, and shape visual variables were robust to high percentages of occlusion and gradual increase in encoded visual values. The text visual variable showed promising results for accuracy, and the resolution time was a little higher than for the last visual variables mentioned. In contrast, the texture visual variable presented lower accuracy to high levels of occlusion and more different visual encoding values. Finally, the orientation and saturation visual variables exhibited the highest error and worst perfomance rates during the tests.
Analysis of Failure Mode of Reinforced Embankments Overlying Voids Based on Discrete Method
Authors: Zhang Qi , Lin Yongliang
Published: August 2023

The mode of the reinforced embankment overlying voids was generated based on discrete element software. By changing the vertical distance H and the horizontal distance L, the influence of the void position on the bearing capacity characteristics, displacement field, stress field and its reinforcement deformation law of the reinforced embankment was analyzed when a local overload was applied. Numerical simulation results show that the vertical displacement of the geogrid is symmetrical around the center of the loading plate, and the transverse displacement of the geogrid shows a centrosymmetric trend around the center of the loading plate at different void locations. In addition, the failure mode of the embankment at different void positions is proposed. Four different failure modes exist for the reinforced embankments overlying voids under local overloading: perforation failure, collapse perforation failure, void side failure and no impact failure. When L = 0, as H increases, the embankment failure mode changes from perforation failure to collapse perforation failure; and when L > 0, as L increases, the failure mode changes from void side failure to no impact failure.
Diurnal Evolution and Estimates of Hourly Diffuse Radiation Based on Horizontal Global Radiation, in Cerrado-Amazon Transition, Brazil
Authors: de Souza Adilson Pacheco , Zamadei Tamara , Borella Daniela Roberta , Martim Charles Campoe , de Almeida Frederico Terra , Escobedo João Francisco
Published: August 2023

In the Cerrado-Amazonian ecotone in the State of Mato Grosso, intensely altered by anthropic action, the knowledge and processes of energy conversion and energy balance are still incipient, making the monitoring and modeling of diffuse radiation essential for several applications. The objective of this study was to evaluate the seasonality of the diurnal evolution and estimate the hourly diffuse radiation (Hdh) and incident radiation in the horizontal plane between June 2011 and October 2016. The instantaneous measurements (5 min) of diffuse radiation underwent geometric, astronomical, and anisotropic corrections, with subsequent hourly integrations. The seasonality of diffuse radiation and its radiometric fractions was evaluated. The estimates were made considering total and seasonal data groupings (water stations in the region) and in different cloudiness classes (atmospheric transmissivity index—KTh). The diurnal behavior of diffuse radiation (Hdh) was similar to that of global radiation and at the top of the atmosphere, with maximum values at solar noon. The correlations between Kdh and KTh showed third-order polynomial behavior, with maximum observed values of Kdh ranging from 0.8 to 0.9, for KTh less than 0.2. Estimation equations based on radiometric fractions underestimated the values of diffuse radiation, with a better performance presented by models adjusted in annual data groupings. Among the parameterized models for estimating diffuse radiation obtained in the literature, those calibrated regionally in this study, together with those developed for tropical regions, presented better statistical performances.
N2O Emissions from Aquatic Ecosystems: A Review
Authors: Pan Huixiao , Zhou Zheyan , Zhang Shiyu , Wang Fan , Wei Jing
Published: August 2023

Emissions of nitrous oxide (N2O) from aquatic ecosystems are on the rise due to the dramatic increase in global reactive nitrogen input by anthropogenic activities (e.g., agricultural nitrogen fertilizer use). However, uncertainties exist in the estimation of aquatic N2O budgets due to limited knowledge of mechanisms involved in aquatic N2O emissions, as well as the N2O flux measurements and modelling. To give a full picture of aquatic N2O emissions, this review discusses the biotic and abiotic mechanisms involved in aquatic N2O emissions, common methods used in aquatic N2O flux measurements (including field measurement methods and formula simulation methods), and alternatives for aquatic N2O budget estimation. In addition, this review also suggests that stable isotope technology is promising in the application of aquatic N2O source partitioning.
Neonatal Hearing Rescreening in a Second-Level Hospital: Problems and Solutions
Authors: Gómez-Delgado Marta , Sequi-Sabater Jose Miguel , Marco-Sabater Ana , Lora-Martin Alberto , Aparisi-Climent Victor , Sequi-Canet Jose Miguel
Published: August 2023

Second-level hospitals face peculiarities that make it difficult to implement hearing rescreening protocols, which is also common in other settings. This study analyzes the hearing rescreening process in these kinds of hospitals. A total of 1130 individuals were included; in this cohort, 61.07% were hospital newborns who failed their first otoacoustic emission test after birth (n = 679) or were unable to perform the test (n = 11), and who were then referred to an outpatient clinic. The remaining 38.93% were individuals born in another hospital with their first test conducted in the outpatient clinic (n = 440). A high number of rescreenings were made outside of the recommended time frame, mainly in children referred from another hospital. There was a high lost-to-follow-up rate, especially regarding otolaryngologist referrals. Neonatal hearing screening at second-level hospitals is difficult because of staffing and time constraints. This results in turnaround times that are longer than recommended, interfering with the timely detection of hearing loss. This is particularly serious in outpatient children with impaired screening. Referral to out-of-town centers leads to unacceptable follow-up loss. Legislative support for all these rescreening issues is necessary. In this article, these findings are discussed and some solutions are proposed.
On Approximation by an Absolutely Convergent Integral Related to the Mellin Transform
Authors: Laurinčikas Antanas
Published: August 2023

In this paper, we consider the modified Mellin transform of the product of the square of the Riemann zeta function and the exponentially decreasing function, and we discuss its probabilistic and approximation properties. It turns out that this Mellin transform approximates the identical zero in the strip {s∈C:1/2<σ<1}.
Exploring the Efficiency of the q-Homotopy Analysis Transform Method for Solving a Fractional Initial Boundary Value Problem with a Nonlocal Condition
Authors: Mesloub Said , Alsaud Huda
Published: August 2023

This article employs the q-homotopy analysis transformation method (q-HATM) to numerically solve, subject to an integral condition, a fractional IBVP. The resulting numerical scheme is applied to solve, in which the exact solution is obtained, several test examples in order to illustrate its efficiency.
AdaBoost.Rt-LSTM Based Joint SOC and SOH Estimation Method for Retired Batteries
Authors: Li Ran , Liu Pengdong , Li Kexin , Zhang Xiaoyu
Published: August 2023

Achieving accurate retired battery state of health (SOH) and state of charge (SOC) estimation is a safe prerequisite for securing the battery secondary utilization and thus effectively improving the energy utilization efficiency. The data-driven approach is efficient and accurate, and does not rely on accurate battery models, which is a hot direction in battery state estimation research. However, the huge number of retired batteries and obvious consistency differences bring bottleneck problems such as long learning time and low model updating efficiency to the traditional data-driven algorithm. In view of this, this paper proposes an integrated learning algorithm based on AdaBoost. Rt-LSTM to realize the joint estimation of SOC and SOH of retired lithium batteries, which relies on the LSTM neural network model and completes the correlation adaption in the spatio-temporal dimension of the whole life cycle sample data. The LSTM model is used as the base learner to construct the AdaBoost. Rt-LSTM strong learning model. The LSTM weak predictor is combined with weights to form a strong predictor, which greatly solves the problem of low accuracy of state estimation due to the large number and variability of retired batteries. Simulation and experimental comparison show that the integrated algorithm proposed in this paper is suitable for improving the SOC and SOH prediction accuracy and the generalization performance of the model.
Prediction of Feed Efficiency and Performance-Based Traits in Fish via Integration of Multiple Omics and Clinical Covariates
Authors: Young Tim , Laroche Olivier , Walker Seumas P. , Miller Matthew R. , Casanovas Paula , Steiner Konstanze , Esmaeili Noah , Zhao Ruixiang , Bowman John P. , Wilson Richard , Bridle Andrew , Carter Chris G. , Nowak Barbara F. , Alfaro Andrea C. , Symonds Jane E.
Published: August 2023

Fish aquaculture is a rapidly expanding global industry, set to support growing demands for sources of marine protein. Enhancing feed efficiency (FE) in farmed fish is required to reduce production costs and improve sector sustainability. Recognising that organisms are complex systems whose emerging phenotypes are the product of multiple interacting molecular processes, systems-based approaches are expected to deliver new biological insights into FE and growth performance. Here, we establish 14 diverse layers of multi-omics and clinical covariates to assess their capacities to predict FE and associated performance traits in a fish model (Oncorhynchus tshawytscha) and uncover the influential variables. Inter-omic relatedness between the different layers revealed several significant concordances, particularly between datasets originating from similar material/tissue and between blood indicators and some of the proteomic (liver), metabolomic (liver), and microbiomic layers. Single- and multi-layer random forest (RF) regression models showed that integration of all data layers provide greater FE prediction power than any single-layer model alone. Although FE was among the most challenging of the traits we attempted to predict, the mean accuracy of 40 different FE models in terms of root-mean square errors normalized to percentage was 30.4%, supporting RF as a feature selection tool and approach for complex trait prediction. Major contributions to the integrated FE models were derived from layers of proteomic and metabolomic data, with substantial influence also provided by the lipid composition layer. A correlation matrix of the top 27 variables in the models highlighted FE trait-associations with faecal bacteria (Serratia spp.), palmitic and nervonic acid moieties in whole body lipids, levels of free glycerol in muscle, and N-acetylglutamic acid content in liver. In summary, we identified subsets of molecular characteristics for the assessment of commercially relevant performance-based metrics in farmed Chinook salmon.
Deletion of Gtf2i via Systemic Administration of AAV-PHP.eB Virus Increases Social Behavior in a Mouse Model of a Neurodevelopmental Disorder
Authors: Ophir Omer , Levy Gilad , Bar Ela , Kimchi Feldhorn Omri , Rokach May , Elad Sfadia Galit , Barak Boaz
Published: August 2023

Williams syndrome (WS) is a neurodevelopmental disorder characterized by distinctive cognitive and personality profiles which also impacts various physiological systems. The syndrome arises from the deletion of about 25 genes located on chromosome 7q11.23, including Gtf2i. Prior research indicated a strong association between pre-natal Gtf2i deletion, and the hyper-social phenotypes observed in WS, as well as myelination deficits. As most studies addressed pre-natal Gtf2i deletion in mouse models, post-natal neuronal roles of Gtf2i were unknown. To investigate the impact of post-natal deletion of neuronal Gtf2i on hyper-sociability, we intravenously injected an AAV-PHP.eB virus expressing Cre-recombinase under the control of αCaMKII, a promoter in a mouse model with floxed Gtf2i. This targeted deletion was performed in young mice, allowing for precise and efficient brain-wide infection leading to the exclusive removal of Gtf2i from excitatory neurons. As a result of such gene deletion, the mice displayed hyper-sociability, increased anxiety, impaired cognition, and hyper-mobility, relative to controls. These findings highlight the potential of systemic viral manipulation as a gene-editing technique to modulate behavior-regulating genes during the post-natal stage, thus presenting novel therapeutic approaches for addressing neurodevelopmental dysfunction.
Sound Reception in the Yangtze Finless Porpoise and Its Extension to a Biomimetic Receptor
Authors: Song Zhongchang , Ou Wenzhan , Li Jiao , Zhang Chuang , Fu Weijie , Xiang Wenjie , Wang Ding , Wang Kexiong , Zhang Yu
Published: August 2023

Sound reception was investigated in the Yangtze finless porpoise (Neophocaena phocaenoides asiaeorientalis) at its most sensitive frequency. The computed tomography scanning, sound speed, and density results were used to develop a three-dimensional numerical model of the porpoise sound-reception system. The acoustic fields showed that sounds can reach the ear complexes from various pathways, with distinct receptivity peaks on the forward, left, and right sides. Reception peaks were identified on the ipsilateral sides of the respective ears and found on the opposite side of the ear complexes. These opposite maxima corresponded to subsidiary hearing pathways in the whole head, especially the lower head, suggesting the complexity of the sound-reception mechanism in the porpoise. The main and subsidiary sound-reception pathways likely render the whole head a spatial receptor. The low-speed and -density mandibular fats, compared to other acoustic structures, are significant energy enhancers for strengthening forward sound reception. Based on the porpoise reception model, a biomimetic receptor was developed to achieve directional reception, and in parallel to the mandibular fats, the silicon material of low speed and density can significantly improve forward reception. This bioinspired and biomimetic model can bridge the gap between animal sonar and artificial sound control systems, which presents potential to be exploited in manmade sonar.