bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetic profiles and phenotypic patterns in Taiwanese Phalaenopsis orchids: a two-step phenotype and genotype strategy using modified genetic distance algorithms
Authors: Lai Ya-Syuan , Chen Shu-Yun , Wu Yan-Jeng , Chen Wen-Huei , Chen Hong-Hwa , Lin Yung-Yu , Lin Te-Cheng , Lin Te-Ju , Kao Chung-Feng
Published: September 2024

This study establishes the first core collection (CC) for Taiwanese Phalaenopsis orchids to preserve genetic diversity and key traits essential for breeding and research, thereby enhancing breeding efficiency without the need for a large maintained parent population. We examined 207 commercial orchid cultivars from ten nurseries, characterized by two phenotypes and genotypic data from eight simple sequence repeat markers. Multiple imputation was applied to estimate missing phenotypes, minimizing potential uncertainties and ensuring the reliability of population structure analysis. Weighted k-means clustering identified seven distinct clusters, highlighting substantial genetic diversity. We proposed a two-step phenotype and genotype strategy and modified genetic distance algorithms to effectively preserve both phenotypic and genetic diversity while retaining key features. Consequently, 22 core accessions were selected, distributed across seven clusters, and representing the orchid germplasm collection. Our evaluation revealed significant diversity preservation, particularly in distinct characteristics and rare features, outperforming other methodologies. Pedigree background analysis further confirmed the representativeness of the CC in maintaining diverse genetic materials. We emphasized the importance of evaluating the CC by detailing the criteria and statistical analyses used to ensure the quality, representativeness, and effectiveness of the selected accessions. This study contributes to orchid breeding, conservation efforts, and sustainable agricultural practices by providing a valuable and comprehensive resource. In conclusion, our research establishes a groundbreaking CC, offering insights into the genetic landscape of Taiwanese Phalaenopsis orchids and highlighting potential advancements in breeding commercially desirable varieties.
Cell size differences affect photosynthetic capacity in a Mesoamerican and an Andean genotype of Phaseolus vulgaris L.
Authors: Egesa Andrew Ogolla , Vallejos C. Eduardo , Begcy Kevin
Published: September 2024

The efficiency of CO2 flux in the leaf is hindered by a several structural and biochemical barriers which affect the overall net photosynthesis. However, the dearth of information about the genetic control of these features is limiting our ability for genetic manipulation. We performed a comparative analysis between three-week-old plants of a Mesoamerican and an Andean cultivar of Phaseolus vulgaris at variable light and CO2 levels. The Mesoamerican bean had higher photosynthetic rate, maximum rate of rubisco carboxylase activity and maximum rate of photosynthetic electron transport at light saturation conditions than its Andean counterpart. Leaf anatomy comparison between genotypes showed that the Mesoamerican bean had smaller cell sizes than the Andean bean. Smaller epidermal cells in the Mesoamerican bean resulted in higher stomata density and consequently higher stomatal conductance for water vapor and CO2 than in the Andean bean. Likewise, smaller palisade and spongy mesophyll cells in the Mesoamerican than in the Andean bean increased the cell surface area per unit of volume and consequently increased mesophyll conductance. Finally, smaller cells in the Mesoamerican also increased chlorophyll and protein content per unit of leaf area. In summary, we show that different cell sizes controls the overall net photosynthesis and could be used as a target for genetic manipulation to improve photosynthesis.
Music and reading activities in early childhood associated with improved language development in preterm infants at 2–3 years of age
Authors: Kostilainen Kaisamari , Fontell Noora , Mikkola Kaija , Pakarinen Satu , Virtala Paula , Huotilainen Minna , Fellman Vineta , Partanen Eino
Published: September 2024

Introduction

Children born preterm are at increased risk for adverse neurodevelopmental outcomes. Music and reading activities in childhood could ameliorate these difficulties, as they have shown benefits on both neural and behavioral levels. However, only a few studies have assessed these potential benefits in preterm-born children. We investigated whether music and language activities in early childhood are associated with improved developmental outcomes of preterm-born children.

Methods

The cognitive, language, and motor skills of 45 children, born between 24 and 34 gestational weeks, were tested at 23–38 months of corrected age with the Bayley Scales of Infant and Toddler Development, Third Edition. Background information, including parental education, and the weekly amount of music and language-related activities was collected using parental questionnaires.

Results

The amount of singing, playing musical instruments and reading aloud was associated with better language skills. Moreover, children who had participated in a music playschool had better language skills when compared to those children who had not participated in a music playschool. Maternal education was associated with music playschool participation and better language and motor skills in children attending music playschool.

Discussion

Interactive music and language activities in early childhood may improve language skills in preterm-born children. Informing and guiding parents at an early stage to integrate these activities into their daily lives could be a one way of supporting the development of preterm-born children.
A project co-created with the community to mitigate loneliness in midlife women
Authors: Corsini Nadia , Dorman Fiona , Scott Jodie , Wright Amanda , Turnbull Deborah , Williams Carmel , Bates Deborah , Reading Bernadette , Everuss Hayley , Peng Fanke , Pearse Rachael , Eckert Marion
Published: September 2024

This paper describes how a team of researchers, policy stakeholders and community members came together to co-create prevention-oriented and community-informed solutions to address loneliness in women—The Loneliness Project. Our aim is to encourage community partnerships and collective effort to address public health approaches to loneliness by developing a shared understanding of the issue from multiple perspectives and through the co-creation process, highlighting the key factors for co-creating a funding application for a community demonstration project.
National trends in loneliness and social isolation in older adults: an examination of subgroup trends over three decades in Sweden
Authors: Dahlberg Lena , von Saenger Isabelle , Naseer Mahwish , Lennartsson Carin , Agahi Neda
Published: September 2024

Introduction

Loneliness and social isolation are public health concerns. This study aimed to examine levels and trends in loneliness and social isolation among older adults (77+ years) in Sweden, assess subgroup variations, and determine associations between loneliness and social isolation.

Methods

The 1992, 2002, 2004, 2011, 2014 and 2021 waves of the Swedish Panel Study of Living Conditions of the Oldest Old (SWEOLD) were analysed through ordered logistic and linear regressions.

Results

On average, 12.5 percent of the participants experienced loneliness often/nearly always, while 6 percent were categorised as severely isolated. Loneliness and social isolation were more common in women, those aged 85+, and persons with basic education, in psychological distress or with mobility limitations. Loneliness was also associated with living alone. No increases in loneliness or isolation were identified; instead, loneliness tended to decrease in groups already experiencing lower levels of loneliness. Loneliness and social isolation were moderately associated each survey year.

Discussion

This study challenges perceptions of high and increasing levels of loneliness and social isolation. Given the impact on health and wellbeing and the ageing of populations, policy and practice should still address these issues and target vulnerable groups. Subgroup analyses in trends are scarce and should be explored further in future research.
Systematic review of statistical methods for the identification of buildings and areas with high radon levels
Authors: Rey Joan F. , Antignani Sara , Baumann Sebastian , Di Carlo Christian , Loret Niccolò , Gréau Claire , Gruber Valeria , Goyette Pernot Joëlle , Bochicchio Francesco
Published: September 2024

Radon is a natural and radioactive noble gas, which may accumulate indoors and cause lung cancers after long term-exposure. Being a decay product of Uranium 238, it originates from the ground and is spatially variable. Many environmental (i.e., geology, tectonic, soils) and architectural factors (i.e., building age, floor) influence its presence indoors, which make it difficult to predict. However, different methods have been developed and applied to identify radon prone areas and buildings. This paper presents the results of a systematic literature review of suitable statistical methods willing to identify buildings and areas where high indoor radon concentrations might be found. The application of these methods is particularly useful to improve the knowledge of the factors most likely to be connected to high radon concentrations. These types of methods are not so commonly used, since generally statistical methods that study factors predictive of radon concentration are focused on the average concentration and aim to identify factors that influence the average radon level. In this paper, an attempt has been made to classify the methods found, to make their description clearer. Four main classes of methods have been identified: descriptive methods, regression methods, geostatistical methods, and machine learning methods. For each presented method, advantages and disadvantages are presented while some applications examples are given. The ultimate purpose of this overview is to provide researchers with a synthesis paper to optimize the selection of the method to identify radon prone areas and buildings.
Aligning valid research outcomes with stakeholder values—what do they need for decision-making?
Authors: Renter David G. , Sargeant Jan M. , O’Connor Annette M. , Ruple Audrey
Published: September 2024

This paper is derived from a presentation given by the first author at the 2024 Symposium for the Calvin Schwabe Award, presented to Dr. Jan Sargeant for Lifetime Achievement in Veterinary Epidemiology and Preventive Medicine. Researchers must work toward ensuring validity throughout the research process, but we also should ensure that our resulting outcomes are specified to appropriately inform and enable decision-making by the end-users. Given the scope and diversity of topics addressed by veterinary researchers, the potential beneficiaries or stakeholders of our research also varies. Stakeholders or end-users may include veterinary practitioners, other researchers, livestock owners, “pet parents,” government officials, corporate entities, or the general public in the case of public health or food security and safety issues. Current research in animal agriculture provides an opportunity to consider research outcomes in a sustainability framework which concurrently values social, economic, and environment impacts of animal health and management decisions. In companion animals, contemporary issues of affordability and access to care, quality of life, or compliance effects on efficacy, also extend the spectrum of relevant research outcomes. In these cases, traditional measures of animal health, such as morbidity, mortality, or weight gain, may not be the most relevant for the end-users. Furthermore, if studies are not designed and analyzed with well-defined primary outcomes that are informed by stakeholders’ values, but rather post-hoc considerations of these values are made based on indirect or surrogate measures, there is the potential to incorporate error and bias into our conclusions and the end-users’ decision-making processes.
Interactive 3D Vase Design Based on Gradient Boosting Decision Trees
Authors: Wang Dongming , Xu Xing , Xia Xuewen , Jia Heming
Published: September 2024

Traditionally, ceramic design began with sketches on rough paper and later evolved into using CAD software for more complex designs and simulations. With technological advancements, optimization algorithms have gradually been introduced into ceramic design to enhance design efficiency and creative diversity. The use of Interactive Genetic Algorithms (IGAs) for ceramic design is a new approach, but an IGA requires a significant amount of user evaluation, which can result in user fatigue. To overcome this problem, this paper introduces the LightGBM algorithm and the CatBoost algorithm to improve the IGA because they have excellent predictive capabilities that can assist users in evaluations. The algorithms are also applied to a vase design platform for validation. First, bicubic Bézier surfaces are used for modeling, and the genetic encoding of the vase is designed with appropriate evolutionary operators selected. Second, user data from the online platform are collected to train and optimize the LightGBM and CatBoost algorithms. Finally, LightGBM and CatBoost are combined with an IGA and applied to the vase design platform to verify their effectiveness. Comparing the improved algorithm to traditional IGAs, KD trees, Random Forest, and XGBoost, it is found that IGAs improve with LightGBM, and CatBoost performs better overall, requiring fewer evaluations and less time. Its R2 is higher than other proxy models, achieving 0.816 and 0.839, respectively. The improved method proposed in this paper can effectively alleviate user fatigue and enhance the user experience in product design participation.
Mechanical Design of a New Hybrid 3R-DoF Bioinspired Robotic Fin Based on Kinematics Modeling and Analysis
Authors: Cortés Torres Eliseo de J. , García Gonzales Luis E. , Villamizar Marin Luis E. , García Cena Cecilia E.
Published: September 2024

The field of bioinspired underwater robots aims to replicate the capabilities of marine animals in artificial systems. Stingrays have emerged as highly promising species to be mimicked because of their flat body morphology and size. Furthermore, they are considered high-performance species due to their maneuverability, propulsion mode, and sliding efficiency. Designing and developing mechanisms to imitate their pectoral fins is a challenge for underwater robotic researchers mainly because the locomotion characteristics depend on the coordinated movement of the fins. In the state of the art, several mechanisms were proposed with 2 active rotation degrees of freedom (DoFs) to replicate fin movement. In this paper, we propose adding an additional active DoF in order to improve the realism in the robotic manta ray movement. Therefore, in this article, we present the mechanical design, modeling, and kinematics analysis of a 3-active-and-rotational-DoF pectoral fin inspired by the Mobula Alfredi or reef manta ray. Additionally, by using the kinematics model, we were able to simulate and compare the behaviour of both mechanisms, that is, those with 2 and 3 DoFs. Our simulation results reveal an improvement in the locomotion, and we hypothesized that with the third DoF, some specific missions, such as hovering or fast emergence to the surface, will have a better performance.
Cotton Disease Recognition Method in Natural Environment Based on Convolutional Neural Network
Authors: Shao Yi , Yang Wenzhong , Wang Jiajia , Lu Zhifeng , Zhang Meng , Chen Danny
Published: September 2024

As an essential component of the global economic crop, cotton is highly susceptible to the impact of diseases on its yield and quality. In recent years, artificial intelligence technology has been widely used in cotton crop disease recognition, but in complex backgrounds, existing technologies have certain limitations in accuracy and efficiency. To overcome these challenges, this study proposes an innovative cotton disease recognition method called CANnet, and we independently collected and constructed an image dataset containing multiple cotton diseases. Firstly, we introduced the innovatively designed Reception Field Space Channel (RFSC) module to replace traditional convolution kernels. This module combines dynamic receptive field features with traditional convolutional features to effectively utilize spatial channel attention, helping CANnet capture local and global features of images more comprehensively, thereby enhancing the expressive power of features. At the same time, the module also solves the problem of parameter sharing. To further optimize feature extraction and reduce the impact of spatial channel attention redundancy in the RFSC module, we connected a self-designed Precise Coordinate Attention (PCA) module after the RFSC module to achieve redundancy reduction. In the design of the classifier, CANnet abandoned the commonly used MLP in traditional models and instead adopted improved Kolmogorov Arnold Networks-s (KANs) for classification operations. KANs technology helps CANnet to more finely utilize extracted features for classification tasks through learnable activation functions. This is the first application of the KAN concept in crop disease recognition and has achieved excellent results. To comprehensively evaluate the performance of CANnet, we conducted extensive experiments on our cotton disease dataset and a publicly available cotton disease dataset. Numerous experimental results have shown that CANnet outperforms other advanced methods in the accuracy of cotton disease identification. Specifically, on the self-built dataset, the accuracy reached 96.3%; On the public dataset, the accuracy reached 98.6%. These results fully demonstrate the excellent performance of CANnet in cotton disease identification tasks.
OPTIMILK: A Web-Based Tool for Least-Cost Dairy Ration Optimization Using Linear Programming
Authors: Mijić Danijel , Vico Grujica , Popović Božidar , Popović Nataša , Ljubojević Miloš , Savić Mihajlo
Published: September 2024

Feed costs represent a significant component of milk production expenses, making up a share of 50% or more of the total cost. The optimization of feed costs is important to achieve financial stability, competitiveness, and sustainability in dairy farming. Optimizing dairy rations not only improves economic efficiency but also plays a significant role in reducing the environmental impact of dairy farming. On the other hand, dairy rations need to meet the specific nutritional requirements of cattle to ensure their health, well-being, and maximum milk production. The formulation of an optimal dairy ration is not an easy task for farmers due to the many challenges they face in this process. This study presents an intuitive web-based tool called OPTIMILK that is used for the optimization of dairy rations using the Simplex method of linear programming. This tool enables farmers to efficiently find a least-cost ration considering the nutritional needs of dairy cows, feed availability and costs, and the nutritional composition of feed. The tool was created for a dairy farmers’ association in Bosnia and Herzegovina and made available to its members for free. After almost four years of operation, the tool’s usage was evaluated by analyzing the collected data. The results show that after an initial period of low activity, there was evidence of an increase in the level of use, which implies the gradual adoption of the tool in dairy farming practice.
Exploring the Factors Affecting Terrestrial Soil Respiration in Global Warming Manipulation Experiments Based on Meta-Analysis
Authors: Chen Xue , Hu Haibo , Wang Qi , Wang Xia , Ma Bing
Published: September 2024

Warming significantly impacts soil respiration in terrestrial ecosystems, thereby altering global carbon cycle processes. Numerous field experiments have investigated the effects of warming on soil respiration (Rs), but the results have been inconsistent due to various factors such as ecosystem type, soil warming amplitude, duration, and environmental conditions. In this study, we conducted a meta-analysis of 1339 cases from 70 studies in terrestrial ecosystems to evaluate the response of Rs, heterotrophic respiration (Rh), and autotrophic respiration (Ra) to global warming. The results indicated that Rs, Rh, and Ra increased by 13.88%, 15.03%, and 19.72%, respectively, with a significant rise observed across different ecosystems. Generally, Rs increased with rising temperatures within a specific range (0–4 °C), whereas higher temperatures (>4 °C) did not significantly affect Rs. Moreover, Rs, Rh, and Ra exhibited an initial increase followed by a decrease with prolonged duration, indicating an adaptive response to climate warming. Additionally, Rs and Rh exhibit significant seasonal variations, with levels in winter being markedly higher than in summer. Furthermore, environmental factors exerted direct or indirect effects on soil respiration components. The factors’ importance for Rs was ranked as microbial biomass carbon (MBC) > mean annual temperature (MAT) > mean annual precipitation (MAP), for Rh as soil organic carbon (SOC) > MBC > MAT > MAP, and for Ra as belowground biomass (BGB) > aboveground biomass (AGB) > SOC. Future research should focus on the interactions among explanatory factors to elucidate the response mechanisms of soil respiration under global warming conditions.
Evaluation of Biodegradable Mulch Films on Melon Production and Quality under Mediterranean Field Conditions
Authors: Sellami Mohamed Houssemeddine , Di Mola Ida , Ottaiano Lucia , Cozzolino Eugenio , del Piano Luisa , Mori Mauro
Published: September 2024

This study examines the effects of biodegradable mulches on melon production and quality in a Mediterranean environment, specifically focusing on Mater-Bi and Ecovio in comparison to conventional (low-density polyethylene) LDPE mulch. Biodegradable mulches influenced soil temperature, with Mater-Bi maintaining higher maximum soil temperatures conducive to crop growth, while Ecovio exhibited lower maximum temperatures beneficial in hot summer months. Results revealed a significant increase in melon yield with biodegradable mulches, with both Ecovio and Mater-Bi demonstrating higher yields at approximately 20.41 t ha−1, showing an improvement of 23.4% compared to LDPE. Although mulching did not impact the number, weight, or distal diameter of marketable fruits, it affected the apical diameter, with Ecovio-treated plants displaying an 8.4% larger apical diameter compared to the average of all treatments. Furthermore, mulching influenced fruit quality parameters such as consistency, pulp thickness, sugar content, and anti-oxidant activity, with Mater-Bi exhibiting the best performance. Since both Mater-Bi and Ecovio possess strengths and weaknesses, selecting the optimal mulch depends on the farmer’s specific objectives and local growing conditions. Overall, the study suggests that biodegradable mulches, particularly Ecovio, offer a sustainable alternative to traditional plastic films, contributing to environmental preservation and enhancing melon yield and quality in Mediterranean agricultural settings.
Assessing the Impacts of Climate Change on Geographical Distribution of Tea (Camellia sinensis L.) in Kenya with Maximum Entropy Model
Authors: Tesfay Goitom , Zhao Yuncheng , Zhao Mingyue , Li Kuo , Demelash Tsedale , Xu Yinlong
Published: September 2024

Climate change has been disturbing the present species distribution ranges, resulting in the shifting of cultivation areas and decreases in production and quality. Tea (Camellia sinensis L.), which seeks optimum climatic resources, is a key cash crop economically in Kenya. In this study, the shifting of tea suitability was projected with the MaxEnt model under the SSP (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) climate scenarios for the 2050s and 2090s relative to the 1970–2000 distribution. Analysis under the current climatic condition showed that the proportions of optimal and medium- and marginal-suitable areas were 2%, 3%, and 24% of the total area, respectively, and located in south-western (SW), central, and north-eastern (NE) Kenya and, to some extent, in the Rift Valley. It was projected that the potential suitable tea-growing areas would migrate from the western areas to the central, eastern, and north-eastern highlands in Kenya. It was detected that the precipitation of the driest period (July), precipitation of the wettest quarter (April, May, and June), and annual temperature range could be the main climatic factors determining the shift in tea distribution. Compared to the current distribution (29%), the climatically suitable areas for tea production could reach 32.58% of Kenya’s land area under the SSP1-2.6 scenarios in the 2050s and 35.08% in the 2090s under the SSP5-8.5 scenario. On the contrary, it was found that the optimal climate-suitable habitats were projected to shrink by 2% and 1% in the 2050s and 2090s under all scenarios on the west side of the Great Rift Valley compared to the current distribution. In comparison, the sizes of medium- and marginal-suitable habitats would increase by 1% and 3%, respectively. The findings indicated that unless adaptive climate actions are taken, climate change could reduce the tea planting areas in western Kenya. Meanwhile, climate suitability was projected to expand upward on the east side of the Rift Valley, enhancing the potential distribution of tea. The developed climate information could be used to design and implement adaptation interventions in the lower elevation areas. Finally, we highlight that the available scientific literature on the climate suitability of tea in Kenya should be broadened by adding non-climatic factors.
Post-Antibiotic and Post-Antibiotic Sub-Minimum Inhibitory Concentration Effects of Carvacrol against Salmonella Typhimurium
Authors: Boyer Eva , Galán-Relaño Ángela , Romero-Salmoral Antonio , Barraza Paula , Gómez-Gascón Lidia , Tarradas Carmen , Luque Inmaculada , de Aguiar Fabiana Carolina , Huerta Lorenzo Belén
Published: September 2024

Carvacrol is a compound present in essential oils with proven antimicrobial activity against numerous pathogens. We firstly determine the post-antibiotic effect (PAE) of carvacrol (1×, 2×, 4× MIC) and post-antibiotic sub-minimum inhibitory concentration (MIC) effect (1× + 0.25× MIC and 2× + 0.25× MIC) for two concentrations of Salmonella Typhimurium ATCC14028 (106 and 108 CFU/mL). Prior to testing, the minimum concentration and exposure time to achieve the bacterial inhibition (MIC 0.6 mg/mL and 10 min) were determined by broth microdilution and time–kill curve methods, respectively. At the MIC, carvacrol did not generate any PAE. At twice the MIC, the PAE was 2 h with the standard inoculum (106 CFU/mL) and 1 h with the high-density inoculum (108 CFU/mL). At 4× MIC concentrations, the PAE was higher in both cases > 43.5 h. Continuous exposure of post-antibiotic phase bacteria (1× and 2× MIC) to carvacrol at 0.25× MIC (0.15 mg/mL) resulted in an increase in PAE (PA-SME) above 43.5 h with both inocula. These results suggest that the PA-SME of carvacrol for S. Typhimurium can be significantly prolonged by increasing the sub-MICs, which would allow dose spacing, reduce adverse effects and improve its efficacy in the treatment of infected animals and as a disinfectant in agri-food facilities.
Effects of Nutrient Manipulation during Peripartum and Suckling Period on Productivity of Hanwoo Cows and Offspring
Authors: Son Gi-Hwal , Kim Na-Hui , Lee So-Hee , Kim Young-Lae , Ahn Jun-Sang , Kim Min-Ji , Shin Jong-Suh , Park Byung-Ki
Published: September 2024

This study investigated the effects of nutrient manipulation during the peripartum and suckling periods on the productivity of Hanwoo cows and their offspring. A total of 183 pregnant cows and their 180 offspring were randomly assigned to either a control group, fed a formula feed with 13.5% crude protein (CP) and 70.5% total digestible nutrients (TDN), or a treatment group, fed nutrient-enriched formula feed with 18.0% CP and 72.5% TDN. Offspring were similarly divided and fed either 17.0% CP and 69.5% TDN (control) or 21.5% CP and 72.5% TDN (treatment). Results showed that body weight recovery was higher in the treatment group, although wither height, body length, and body condition scores were similar between groups. The treatment group exhibited increased chest girth, reduced intervals for first return to estrus, and shorter days open compared to the control group. Plasma non-esterified fatty acids, albumin, and progesterone concentrations of Hanwoo cows varied between groups at the 3 months before and after calving. Offspring in the treatment group had higher body weight and average daily gain at birth, three and six months of age, with higher dry matter intake. These findings suggest that nutrient-enriched formula feed positively influences the reproductive efficiency of Hanwoo cows and the growth performance of their offspring.
Chest Wall Reconstruction Using Titanium Mesh in a Dog with Huge Thoracic Extraskeletal Osteosarcoma
Authors: Jung Woo-June , Kwak Ho-Hyun , Kim Junhyung , Woo Heung-Myong
Published: September 2024

A 6-year-old castrated male mixed dog presented with a rapidly growing mass at the right chest wall two weeks after initial detection. A mesenchymal origin of the malignancy was suspected based on fine-needle aspiration. Computed tomography (CT) revealed that the mass originated from the right chest wall and protruded externally (6.74 × 5.51 × 4.13 cm3) and internally (1.82 × 1.69 × 1.50 cm3). The patient revisited the hospital because of breathing difficulties. Radiography confirmed pleural effusion, and ultrasonography-guided thoracocentesis was performed. The effusion was hemorrhagic, and microscopic evaluation showed no malignant cells. Before surgery, CT without anesthesia was performed to evaluate the status of the patient. The 7–10th ribs were en bloc resected at a 3-cm margin dorsally and ventrally, and two ribs cranially and caudally from the mass. After recovering the collapsed right middle lobe of the lung due to compression from the internal mass with positive-pressure ventilation, a 3D-printed bone model contoured titanium mesh was tied to each covering rib and surrounding muscles using 2-0 blue nylon and closed routinely. The thoracic cavity was successfully reconstructed, and no flail chest was observed. The patient was histo-pathologically diagnosed with extraskeletal osteosarcoma. A CT scan performed 8 months after surgery showed no evident recurrence, metastasis, or implant failure. This is the first case report of chest wall reconstruction using titanium mesh in a dog. The use of a titanium mesh allows for the reconstruction of extensive chest wall defects, regardless of location, without major postoperative complications.
Assessing Temperature Distribution inside Commercial Stacked Cage Broiler Houses in Winter
Authors: Deng Senzhong , Li Zonggang , Wei Yongxiang , Wang Yang , Li Baoming , Zheng Weichao
Published: September 2024

The temperature inside broiler houses is crucial to broiler health, welfare, and productivity. High stocking density in broiler houses can easily lead to nonuniform temperature conditions, which would cause broilers to suffer cold and heat stress. It is essential to assess the temperature distribution inside broiler houses and investigate the factors that affect temperature uniformity. Therefore, in this study, temperature, wind velocity, and differential pressure were monitored in the aisle, at the sidewall inlet, and outside the sidewalls of a commercial stacked-deck cage broiler house in Northeast China aiming to continuously monitor the temperature throughout the entire fattening period. Results show that the maximum temperature difference increased from 1.85 °C to 6.43 °C, while the daily fluctuation increased from 2.27 °C to 5.80 °C. The highest temperature was consistently recorded at the side of the exhaust fans (p < 0.001) in the longitudinal direction. In the lateral direction, the temperature difference varies periodically with solar radiation. The average temperature at the southern location (23.58 ± 1.97 °C), which faces the sun, was higher than that at the northern location (23.35 ± 1.38 °C), which is in the shade, during periods of solar radiation (p < 0.001) at the last testing period. However, without solar radiation, the northern location recorded a warmer temperature (23.19 ± 1.41 °C) compared to the southern location (22.30 ± 1.67 °C) (p < 0.001). The lateral temperature differences are strongly positively correlated with solar radiation and wind speed (p < 0.001). In conclusion, the inside temperature nonuniformity and fluctuation increased as the broiler age increased, which affected the production performance of broilers. Nonuniform solar radiation and wind speed can lead to differences in the inlet temperature and air volume between both sidewalls, thereby affecting the uniformity of the lateral temperature inside the house.
Detachment Energy Evaluation in Nano-Particle Cleaning Using Lateral Force Microscopy
Authors: Terayama Yutaka , Khajornrungruang Panart , Seo Jihoon , Hamada Satomi , Wada Yutaka , Hiyama Hirokuni
Published: September 2024

It has been difficult to detach abrasive particles smaller than 50 nm from polished surfaces in post-CMP cleaning. During the cleaning process, the residual nano-particles exert shear force in the inevitable shear flow. In order to understand the cleaning mechanism, it is indispensable to investigate not only the force but also the energy acting on different-sized nano-particles. In this article, we proposed the evaluation of detachment energy (the energy required to detach nano-particles) by using Lateral Force Microscopy. As an example, the dominant detachment energy of the silica nano-particle between the oxide film is the potential energy of the hydrogen bond. It suggested that the silica nano-particle detachment involves the breaking of hydrogen bonds.
Secure Cognitive Radio Vehicular Ad Hoc Networks Using Blockchain Technology in Smart Cities
Authors: Asif Fatima , Ghafoor Huma , Koo Insoo
Published: September 2024

Security is an important consideration when delivering information-aware messages to vehicles that are far away from the current location of the information-sending vehicle. This information helps the receiver to save fuel and time by making wise decisions to avoid damaged or blocked roads. To ensure the safety and security of this type of information using blockchain technology, we propose a new cognitive vehicular communication scheme to transfer messages from source to destination. Due to spectrum scarcity in vehicular networks, there needs to be a wireless medium available for every communication link since vehicles require it to communicate. The primary user (PU) makes a public announcement about a free channel to all secondary users nearby and only gives it to authentic vehicles. The authenticity of vehicles is guaranteed by a roadside unit (RSU) that offers secure keys to any vehicle that joins this blockchain network. Those who participate in this network must pay a certain amount and receive rewards for their honesty that exceed the amount spent. To test the performance of various parameters, the proposed scheme utilizes the Ethereum smart contract and compares them to blockchain and non-blockchain methods. Our results show a minimum delivery time of 0.16 s and a minimum overhead of 350 bytes in such a dynamic vehicle environment.
Machine Learning for Prediction of Cognitive Deterioration in Patients with Early Parkinson’s Disease
Authors: Martinez-Eguiluz Maitane , Arbelaitz Olatz , Gurrutxaga Ibai , Muguerza Javier , Gomez-Esteban Juan Carlos , Gabilondo Iñigo , Murueta-Goyena Ane
Published: September 2024

Parkinson’s disease (PD) is a neurodegenerative disorder marked by motor and cognitive impairments. The early prediction of cognitive deterioration in PD is crucial. This work aims to predict the change in the Montreal Cognitive Assessment (MoCA) at years 4 and 5 from baseline in the Parkinson’s Progression Markers Initiative database. The predictors included demographic and clinical variables: motor and non-motor symptoms from the baseline visit and change scores from baseline to the first-year follow-up. Various regression models were compared, and SHAP (SHapley Additive exPlanations) values were used to assess domain importance, while model coefficients evaluated variable importance. The LASSOLARS algorithm outperforms other models, achieving lowest the MAE, 1.55±0.23 and 1.56±0.19, for the fourth- and fifth-year predictions, respectively. Moreover, when trained to predict the average MoCA score change across both time points, its performance improved, reducing its MAE by 19%. Baseline MoCA scores and MoCA deterioration over the first-year were the most influential predictors of PD (highest model coefficients). However, the cumulative effect of other cognitive variables also contributed significantly. This study demonstrates that mid-term cognitive deterioration in PD can be accurately predicted from patients’ baseline cognitive performance and short-term cognitive deterioration, along with a few easily measurable clinical measurements.
Image Analysis in Autonomous Vehicles: A Review of the Latest AI Solutions and Their Comparison
Authors: Kozłowski Michał , Racewicz Szymon , Wierzbicki Sławomir
Published: September 2024

The integration of advanced image analysis using artificial intelligence (AI) is pivotal for the evolution of autonomous vehicles (AVs). This article provides a thorough review of the most significant datasets and latest state-of-the-art AI solutions employed in image analysis for AVs. Datasets such as Cityscapes, NuScenes, CARLA, and Talk2Car form the benchmarks for training and evaluating different AI models, with unique characteristics catering to various aspects of autonomous driving. Key AI methodologies, including Convolutional Neural Networks (CNNs), Transformer models, Generative Adversarial Networks (GANs), and Vision Language Models (VLMs), are discussed. The article also presents a comparative analysis of various AI techniques in real-world scenarios, focusing on semantic image segmentation, 3D object detection, vehicle control in virtual environments, and vehicle interaction using natural language. Simultaneously, the roles of multisensor datasets and simulation platforms like AirSim, TORCS, and SUMMIT in enriching the training data and testing environments for AVs are highlighted. By synthesizing information on datasets, AI solutions, and comparative performance evaluations, this article serves as a crucial resource for researchers, developers, and industry stakeholders, offering a clear view of the current landscape and future directions in autonomous vehicle image analysis technologies.
Study of Heat Distribution in Railway Switch Using Resistive Heater in Cold Climate Conditions
Authors: Lotfi Arefeh , Yousuf Adeel , Virk Muhammad Shakeel
Published: September 2024

The railway is an essential source of logistics and transportation in cold regions, but low temperatures and icing can be challenging for uninterrupted railway operations in these regions. Icing on railway switches is a safety hazard, and presently, one of the industry’s adaptive approaches for ice mitigation is the use of resistive heaters. This method is efficient but consumes a great amount of electricity, leading to high financial costs in terms of the operation and maintenance of railway tracks in ice-prone regions. In this paper, a study is carried out using experiments and computational simulations to analyze the heat distribution in a cross-section of a rail at below-freezing temperatures. Experiments are performed in a cold room using an actual rail switch, thermocouples, and infrared imaging, while numerical analyses are carried out using a MATLAB-based analytical model to simulate the heat transfer, considering a section of stock rail and a heating element. Results show a considerable loss of heat from the heater to the surroundings of the rail, especially towards the ground ballast. Numerical simulation results provide a good insight into heat transfer along railway sections, and results are validated with experiments, where a good agreement is found. This study provides a good base for further optimization of resistive heating operations for ice mitigation along railway switches.
Introducing Cement-Enhanced Clay-Sand Columns under Footings Placed on Expansive Soils
Authors: Shaker Abdullah A. , Dafalla Muawia
Published: September 2024

The risk posed by expansive soils can be lessened by placing foundations at a more deep level below the surface. Structures are able to withstand uplift forces because overburden pressure partially suppresses swelling pressure. In order to transfer the forces to a sufficiently deep depth, this study suggests introducing shafts of a low-expansion overburden material. Soil improved with cement is chosen for this purpose. This study suggests using sand with added excavated natural clay and cement. The expansive clay is added to sand in ratios of 10, 20, 30, 40 and 60%. The clay–sand mixture is then enhanced by cement of 1, 2, 4 and 8% by the weight of the mixture under four curing periods of 1, 7, 28, and 90 days. This material is recommended for use under lean concrete to transfer the loads to lower levels below the foundation depth. The thickness of this material depends on the stresses exerted, the type and the properties of the subsurface soils. The cement-enhanced clay–sand shaft’s properties are examined in this work with regard to the swelling potential, compressibility, and the unconfined compressive strength for different clay contents and curing conditions. Stiff shafts were formed and found to support stresses from 600 to 3500 kPa at cement additions in the range of 1% to 8%. Clay content above 30% is found to be not suitable for Al-Qatif clay due to the compressibility and low strength of the mixture. When two percent or more of cement is added, the swelling potential is significantly reduced. This is reliant on the pozzolanic interactions of soils and cement as well as the clay mineralogy. Determining how cement affects clay–sand combinations in regions with expansive soils would facilitate the introduction of a novel, inexpensive technology to support loads applied by the superstructure.
Empirical Trials on Unmanned Agriculture in Open-Field Farming: Ridge Forming
Authors: Kang Seokho , Kim Yonggik , Han Joonghee , Park Hyunggyu , Son Jinho , Han Yujin , Woo Seungmin , Ha Yushin
Published: September 2024

The decreasing rural population and migration to urban areas for high-tech opportunities have weakened the agricultural labor force. While data technology has been adopted in protected agriculture, numerous challenges remain in field agriculture. In this study, we focus on one of the fundamental steps of field operations, i.e., ridge forming, specifically in unmanned agriculture. We compared the performance of a conventional tractor with an implement to that of a ridge-forming robot. The operation data were collected using an acquisition system, and a comparison between the results of both methods was conducted. Additionally, we analyzed the linearity of autonomous driving and the expenses associated with the selected operation. Our findings indicate that the developed robot for ridge forming caused less torque damage and achieved a more accurate target soil depth, with a linearity performance showing a distance error of only 0.267 m. Furthermore, it eliminated the need for hiring an operator and significantly reduced fuel consumption, which accounts for 50.81% of the operational expenses. These results suggest that field operations can be effectively replaced by autonomous systems, and further research on unmanned agriculture is warranted.
The Maintenance Factor as a Necessary Parameter for Sustainable Artificial Lighting in Engineering Production—A Software Approach
Authors: Dupláková Darina , Sloboda Patrik
Published: September 2024

The presented article addresses the issue of the maintenance factor, which forms a part of the design variables in artificial lighting within engineering practices from a sustainability perspective. The maintenance factor was monitored using two simulation tools—Dialux, version 5.12.0.5527 and Relux, version 2024.2.8.0. In a production hall, inadequate lighting was identified with a value below 300 lx, prompting a redesign of the lighting system. The overall methodology of the Ergonomic Rationalization Sequence was expanded in the “Design of Lighting System” phase to include the determination of the maintenance factor as a necessary parameter for sustainability, which was subsequently verified in a virtual environment using two options in a practical study. According to the in situ measurements, the virtual environments of the production hall were created for both software, in which four alternatives for the lighting system were developed. The illuminance values met the normative requirements in each alternative; however, the first two (illuminance values 1000 lx–1200 lx) were predicted to have long-term high-energy consumption. In alternatives 3 and 4, the number of luminaires was therefore reduced from 6 pieces to 4, with a total illuminance in the range of 680 lx–780 lx. The determination of the variations in the methods for establishing the maintenance factor identified a deviation of 5%, which, indicating the changes in illuminance values, can be considered as the occurrence of a gross error in lighting design.
Research on Speed Guidance Strategies for Mixed Traffic Flow Considering Uncertainty of Leading Vehicles at Signalized Intersections
Authors: Liu Huanfeng , Niu Keke , Wang Hanfei , Zhang Zishuo , Song Anning , Wu Ziyan
Published: September 2024

In the context of intelligent connected environments, this study explores methods to guide the speed of mixed traffic flow to improve intersection efficiency. First, the composition of traffic flow is analyzed, and a car-following model for mixed traffic flow is established, considering reaction time and the psychology of human drivers. Secondly, considering the uncertainty factors of the leading vehicle, we establish a speed guidance model for mixed traffic flow platoons. Finally, a simulation environment is built using Python and SUMO, evaluating the speed guidance effect from the perspectives of different traffic volumes and CAV penetration rates based on average stop times and average delays. The research findings indicate that the speed guidance algorithm proposed in this paper can reduce the number of parking times and delays at intersections. When the mixed traffic flow remains constant, the higher the penetration rate of CAV, the more effective the guidance becomes. However, when the traffic flow reaches a certain level, congestion intensifies, and the effectiveness of the guidance gradually diminishes. Therefore, this study is more applicable to long-distance intersections or key intersections on interconnected roads outside urban areas.