bluuebunny/crossref_metadata_2025 huggingface dataset:
The Characterization of the Th1/Th2 Ratio in Moderate-Severe Alzheimer’s Disease Patients and Its Response to an Aloe Polymannose-Based Dietary Supplement
Authors: Lewis John E. , Reginald McDaniel H. , Woolger Judi M. , Khan Sher Ali
Published: November 2023

Background: Alzheimer’s disease (AD) is a leading killer of Americans, imparting a tremendous societal toll. Relationships between immune function and inflammation with cognition are well-established in AD, but the Th1/Th2 ratio of immune function is unknown. Describing the Th1/Th2 ratio and its relationship with cognition may shed light on the disease’s clinical context. How the Th1/Th2 ratio responds to dietary supplementation is another unknown question in this population. Objective: The objectives of the study were to: 1) characterize the Th1/Th2 ratio according to IL-2/IL-10, IFN-γ/IL-10, IL-2/IL-4, IFN-γ/IL-4, IL-2/TNF-α, and IFN-γ/TNF-α in subjects with moderate-to-severe AD and in comparison to healthy adults; 2) investigate the effect of an aloe polymannose multinutrient complex (APMC) dietary supplement on the Th1/Th2 ratios over 12 months; and 3) compare the changes in the Th1/Th2 ratios with the changes in cognition from baseline to 12 months. Methods: Subjects consumed 2.5 g of the APMC four times per day for 12 months, and they were assessed on cognition and cytokines at baseline and 12 months. Results: The Th1/Th2 ratios in AD patients were significantly higher than the healthy controls, and five of the six ratios decreased from baseline to 12 months follow-up (other than IL-2/TNF-α). Several significant relationships were noted between the changes in Th1/Th2 ratios with cognitive assessments. Conclusions: Our results showed an overall rebalancing of the Th1/Th2 ratio in response to APMC, these changes were related to improved cognition in subjects with moderate-to-severe AD, and the APMC supplement was safely tolerated.
Register-based census in Thailand: A case study in Chachoengsao province
Authors: Charoenruk Nuttirudee , Asavaroungpipop Narongrid , Pattanapradit Pannee , Ku-kiattikun Kittiya , Amornbunchornvej Chainarong
Published: November 2023

The use of registers has been increasingly popular in the field of population census because of its advantages over the traditional census. While the traditional census requires a large amount of fieldwork and data collection, the registered-based census can rely on pre-existing administrative data. As a result, the register-based census can save both time and budget. Thailand explored a use of the register-based census in 2020. In this paper, the authors layout the methodology in an aspect of data preparation and integration as well as analyze data quality of the register-based census compared with the traditional census in Chachoengsao province, Thailand. In addition, we compared conceptual frameworks that are commonly used for a register-based census in several countries and the number of databases (a recent single database VS multiple databases) used to construct the register-based census. We found that using a conceptual framework that counts the number of populations based on the main census variables on a single recent database is better than using a framework that counts population who appears on many registers in term of overcoverage and data distribution regarding to sex. This provides the evidence of using one recent and complete database is sufficient for conducting the register-based census. The authors end up with recommendations for conducing the register-based census.
Artificial intelligence predicts direct-acting antivirals failure among hepatitis C virus patients: A nationwide hepatitis C virus registry program
Authors: Lu Ming-Ying , Huang Chung-Feng , Hung Chao-Hung , Tai Chi‐Ming , Mo Lein-Ray , Kuo Hsing-Tao , Tseng Kuo-Chih , Lo Ching-Chu , Bair Ming-Jong , Wang Szu-Jen , Huang Jee-Fu , Yeh Ming-Lun , Chen Chun-Ting , Tsai Ming-Chang , Huang Chien-Wei , Lee Pei-Lun , Yang Tzeng-Hue , Huang Yi-Hsiang , Chong Lee-Won , Chen Chien-Lin , Yang Chi-Chieh , Yang Sheng‐Shun , Cheng Pin-Nan , Hsieh Tsai-Yuan , Hu Jui-Ting , Wu Wen-Chih , Cheng Chien-Yu , Chen Guei-Ying , Zhou Guo-Xiong , Tsai Wei-Lun , Kao Chien-Neng , Lin Chih-Lang , Wang Chia-Chi , Lin Ta-Ya , Lin Chih‐Lin , Su Wei-Wen , Lee Tzong-Hsi , Chang Te-Sheng , Liu Chun-Jen , Dai Chia-Yen , Kao Jia-Horng , Lin Han-Chieh , Chuang Wan-Long , Peng Cheng-Yuan , Tsai Chun-Wei- , Chen Chi-Yi , Yu Ming-Lung ,   TACR Study Group
Published: November 2023

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy.Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset.Conclusions: Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.
Practical and Rapid Motor Sizing Technique Using Existing Electrical Motor
Authors: Kim Yong-Chul , Han Jung-Ho , Lee Ju
Published: November 2023

Electrical motor design requires considerable work and resources. In the field, motor designers need to decide on competitive motor sizing quickly to compete with other motor suppliers. Generally, expensive FEM S/W is required to obtain accurate motor sizing results, but buying and maintaining many licenses is costly. Moreover, patience is required to obtain the results from FEM analysis. In this paper, a motor sizing technique using an existing production motor is presented to enable responding to urgent requests from customers without using FEM analysis. In order to enhance the fidelity of the results, magnetic flux losses due to magnet coatings and non-linear characteristics are considered during the motor sizing process. The proposed sizing method is verified via a comparison with FEM analysis and the test results and shows reasonable performance. Also, this method has the substantial advantage of outputting accurate results instantly. The method can help with the modification design of electrical motors without using expensive FEM S/W and does not require a certain level of skill or experience.
Biochar Regulates 2-Acetyl-1-Pyrroline, Grain Yield and Quality in Fragrant Rice Cropping Systems in Southern China
Authors: Zhang Xuechan , Qiu Xinfeng , Yao Xiangbin , Wei Jianjiao , Tong Shaojie , Mo Zhaowen , Qi Jianying , Duan Meiyang , Tang Xiangru
Published: November 2023

With the existing model of chemical fertilizer application faces, improving grain yield and quality is challenging. Fragrant rice is known for its distinctive aroma and flavor, but it generally produces less grain than non-fragrant rice varieties. Limited research has been conducted on the potential of biochar as a solution for increasing the grain yield of fragrant rice. In a two-year field trial conducted in 2022 and 2023, two fragrant rice cultivars, Meixiangzhan2 (MXZ2) and Xiangyaxiangzhan (XYXZ), were selected as the experimental materials. These rice cultivars were subjected to four different rates of biochar application: no biochar treatment(T1); biochar with 0.375 t ha−1 (T2); biochar with 0.75 t ha−1 (T3); and biochar with 1.50 t ha−1 (T4). The results showed that the grain yield of both cultivars increased to an extent in both 2022 and 2023 (an 8.57–33.77% increase for MXZ2; a 6.00–21.59% increase for XYXZ). Furthermore, under the T2, T3, and T4 treatments, there was an increase in the number of effective panicles, seed setting rate, 1000-grain weight, biomass accumulation, net photosynthetic rate, and intercellular CO2 concentration. However, the transpiration rate and stomatal conductance decreased. The content of 2-acetyl-1-pyrroline (2-AP) increased with an increased rate of biochar application, and the highest content was observed under the T4 treatment (153.54–178.32 µg kg−1 in 2022; 163.93–180.28 µg kg−1 in 2023). The activities of proline dehydrogenase (PDH) and 1-pyrrolin-5-carboxylic acid synthase (P5CS), as well as the contents of proline (PRO), 1-pyrrolin-5-carboxylic acid (P5C), ∆1-pyrroline, and methylglyoxal, were improved under the T2, T3, and T4 treatments compared to the T1 treatment. Moreover, under the T2, T3, and T4 treatments, the brown rice rate, milled rice rate, and head rice rate increased, while the chalkiness degree and chalk rice rate decreased. Our correlation analysis showed that grain yield was positively correlated with total biomass accumulation, the number of grains per panicle, and the seed setting rate. Additionally, the content of 2-AP showed positive correlations with PRO, P5C, ∆1-pyrroline and methylglyoxal, and the activities of PDH and P5CS. In conclusion, applying biochar at a rate of 1.5 t ha−1 can be more effective in increasing the grain yield and 2-AP content of fragrant rice.
Diallel Crosses of Cotton (Gossypium hirsutum L.)—Enhancement of Fiber Properties in Future Cultivars for Burkina Faso
Authors: Bourgou Larbouga , Dever Jane K. , Sheehan Monica , Kelly Carol M. , Diané Sidiki K. , Sawadogo Mahamadou
Published: November 2023

The market value of cotton in exporting countries, such as Burkina Faso, depends on the quality of major fiber properties. A lack of variation among the genetic resources available in Burkina Faso hinders breeding progress to meet fiber quality demands in future cultivars. F1 populations from a half diallel crossing scheme between lines developed at Texas A&M AgriLife cotton breeding program at Lubbock and germplasm accessed from Burkina Faso were evaluated for fiber property enhancement. Crosses exclusively within common origin materials did not result in highly enhanced hybrids. Hybrids within American materials expressed significant SCA effects undesirable for future cultivars in Burkina Faso. Five hybrids within the Burkina Faso material expressed significant SCA effects: two of them implicating FK37 as the better parent in transmitting superior targeted fiber traits to its progenies. Hybrid FK37xE9 significantly enhanced UHML, Str, UI and SFI but not Mic and Rd. Inter-program hybrids with at least one significant SCA effect were crosses with female American lines and male Burkina Faso parents. Hybrids E53x16-2-216FQ, E53x15-10-610-7 and E32x15-10-610-7 showed significantly improved Str and UI for the most economically important traits, which also include Mic, UHML, SFI, Rd and +b. Together, the GCA and SCA effects, heritability and correlations showed more additive than non-additive gene actions. Therefore, knowledge of the best combiners and hybrids could be used in the cultivar development process to enhance value with improved fiber characteristics.
Pixel Self-Attention Guided Real-Time Instance Segmentation for Group Raised Pigs
Authors: Jia Zongwei , Wang Zhichuan , Zhao Chenyu , Zhang Ningning , Wen Xinyue , Hu Zhiwei
Published: November 2023

Instance segmentation is crucial to modern agriculture and the management of pig farms. In practical farming environments, challenges arise due to the mutual adhesion, occlusion, and dynamic changes in body posture among pigs, making accurate segmentation of multiple target pigs complex. To address these challenges, we conducted experiments using video data captured from varying angles and non-fixed lenses. We selected 45 pigs aged between 20 and 105 days from eight pens as research subjects. Among these, 1917 images were meticulously labeled, with 959 images designated for the training set, 192 for validation, and 766 for testing. To enhance feature utilization and address limitations in the fusion process between bottom-up and top-down feature maps within the feature pyramid network (FPN) module of the YOLACT model, we propose a pixel self-attention (PSA) module, incorporating joint channel and spatial attention. The PSA module seamlessly integrates into multiple stages of the FPN feature extraction within the YOLACT model. We utilized ResNet50 and ResNet101 as backbone networks and compared performance metrics, including AP0.5, AP0.75, AP0.5-0.95, and AR0.5-0.95, between the YOLACT model with the PSA module and YOLACT models equipped with BAM, CBAM, and SCSE attention modules. Experimental results indicated that the PSA attention module outperforms BAM, CBAM, and SCSE, regardless of the selected backbone network. In particular, when employing ResNet101 as the backbone network, integrating the PSA module yields a 2.7% improvement over no attention, 2.3% over BAM, 2.4% over CBAM, and 2.1% over SCSE across the AP0.5-0.95 metric. We visualized prototype masks within YOLACT to elucidate the model’s mechanism. Furthermore, we visualized the PSA attention to confirm its ability to capture valuable pig-related information. Additionally, we validated the transfer performance of our model on a top-down view dataset, affirming the robustness of the YOLACT model with the PSA module.
Adapted Original Music as an Environmental Enrichment in an Intensive Pig Production System Reduced Aggression in Weaned Pigs during Regrouping
Authors: Alvarez-Hernandez Natalia , Vallejo-Timarán Darío , de Jesús Rodriguez Berardo
Published: November 2023

In intensive swine production systems,, the practice of regrouping unfamiliar pigs is common, often leading to aggressive behavior. Although the effect of different musical genres composed for humans has been evaluated in pigs to mitigate aggression, there have been few attempts to create music specifically for pigs. Here, we assess whether sensory stimulation through music, created by adapting the acoustic parameters in the sound mix, induces changes in the aggressive behaviors of pigs during regrouping. Six litters of 10-week-old piglets were randomly selected and assigned to different treatments. The control group (Group A) received no intervention, while Group B was exposed to music for two continuous hours in the morning and afternoon from the time of regrouping. Group C received musical stimulation for one continuous hour in the morning following regrouping. A significant reduction in the frequency and duration of aggressive behaviors was observed in the groups that received musical stimulation during regrouping. Additionally, social, and individual play behaviors showed a decrease in the musical stimulation groups. These findings provide evidence for the effectiveness of created music as a strategy in reducing aggressive behavior during pig regrouping, which can enhance the welfare of pigs and offer a practical solution for pig producers to minimize aggression and its associated negative impacts.
Resveratrol Reduces ROS by Increasing GSH in Vitrified Sheep Embryos
Authors: González-Garzón Andrea Carolina , Ramón-Ugalde Julio Porfirio , Ambríz-García Demetrio Alonso , Vazquez-Avendaño José Roberto , Hernández-Pichardo José Ernesto , Rodríguez-Suastegui José Luis , Cortez-Romero César , Navarro-Maldonado María del Carmen
Published: November 2023

The in vitro production and cryopreservation of mammalian embryos generates reactive oxygen species (ROS) due to conditions of the system that can overcome their antioxidant protection. Resveratrol is an antioxidant used in in vitro systems to improve blastocyst rates, but its effect on antioxidant enzymes such as glutathione (GSH) in embryos produced by in vitro fertilization (IVF) after vitrification has not been reported. The objective of this study was to evaluate the effects of resveratrol on the in vitro maturation medium (IVM) of sheep oocytes (Ovis aries) on the levels of ROS and GSH in embryos produced by IVF subjected to vitrification. Resveratrol was added at 0 µM, 0.25 µM, 0.5 µM, and 1 µM during oocyte in vitro maturation (IVM). Matured oocytes were fertilized with thawed ram sperm. Embryos were cultured in sequential media until blastocysts, were then vitrified for 24 h, and, after heating, they were stained with DCFH-DA (2′,7′-dichlorodihydrofluorescein diacetate) to determine the presence of ROS and with Cell Tracker Blue® for the presence of GSH. The quantitative values of ROS and GSH were obtained through the Image J image processor. The results showed that resveratrol increased GSH and decreased ROS production (p < 0.05) in a dose-dependent manner. It is concluded that its use in sheep oocytes during IVM has a beneficial effect on embryos produced by IVF subjected to vitrification by decreasing reactive oxygen species levels and facilitating the generation of embryo antioxidant enzymes like glutathione.
Performance and Impact on Antibiotic Prescriptions of a Multiplex PCR in a Real-Life Cohort of Critically Ill Patients with Suspected Ventilated Pneumonia: A Retrospective Monocentric Observational Study
Authors: Chambe Emma , Bortolotti Perrine , Diesnis Rémy , Laurans Caroline , Héquette-Ruz Rozenn , Panaget Sophie , Herbecq Patrick , Vachée Anne , Meybeck Agnès
Published: November 2023

Pulmonary multiplex polymerase chain reaction (m-PCR) allows rapid pathogen detection. We aimed to assess its impact on initial antibiotic prescriptions in ventilated patients with suspected pneumonia. Between November 2020 and March 2022,ventilated patients with suspected pneumonia hospitalized in our ICU who benefited from respiratory sampling simultaneously tested using conventional microbiological methods and m-PCR were included. The proportion of appropriate changes in the initial antibiotic therapy following m-PCR results was assessed. We analyzed 104 clinical samples. Of the 47 negative m-PCR results, 16 (34%) led to an appropriate antibiotic strategy: 8 cessationsand 8 lack of initiation. Of the 57 positive m-PCR results, 51 (89%) resulted in an appropriate antibiotic strategy: 33 initiations, 2 optimizations, and 9 de-escalations. In the multivariate analysis, a positive m-PCR was associated with an appropriate antibiotic change (OR: 96.60; IC95% [9.72; 960.20], p < 0.001). A higher SAPS II score was negatively associated with an appropriate antibiotic change (OR: 0.96; IC95% [0.931; 0.997], p = 0.034). In our cohort, a positive m-PCR allowed for early initiation or adjustment of antibiotic therapy in almost 90% of cases. A negative m-PCR spared antibiotic use in onethird of cases. The impact of m-PCR results was reduced in the most severe patients.
Elamipretide(SS-31) Attenuates Idiopathic Pulmonary Fibrosis by Inhibiting the Nrf2-Dependent NLRP3 Inflammasome in Macrophages
Authors: Nie Yunjuan , Li Jiao , Zhai Xiaorun , Wang Zhixu , Wang Junpeng , Wu Yaxian , Zhao Peng , Yan Gen
Published: November 2023

Idiopathic pulmonary fibrosis (IPF) is a progressive fatal lung disease with a limited therapeutic strategy. Mitochondrial oxidative stress in macrophages is directly linked to IPF. Elamipretide(SS-31) is a mitochondrion-targeted peptide that has been shown to be safe and beneficial for multiple diseases. However, whether SS-31 alleviates IPF is unclear. In the present study, we used a bleomycin (BLM)-induced mouse model followed by SS-31 injection every other day to investigate its role in IPF and explore the possible mechanism. Our results showed that SS-31 treatment significantly suppressed BLM-induced pulmonary fibrosis and inflammation, with improved histological change, and decreased extracellular matrix deposition and inflammatory cytokines release. Impressively, the expression percentage of IL-1β and IL-18 was downregulated to lower than half with SS-31 treatment. Mechanistically, SS-31 inhibited IL-33- or lipopolysaccharide(LPS)/IL-4-induced production of IL-1β and IL-18 in macrophages by suppressing NOD-like receptor thermal protein domain associated protein 3(NLRP3) inflammasome activation. Nuclear factor erythroid 2-related factor 2(Nrf2) was dramatically upregulated along with improved mitochondrial function after SS-31 treatment in activated macrophages and BLM-induced mice. Conversely, there was no significant change after SS-31 treatment in Nrf2−/− mice and macrophages. These findings indicated that SS-31 protected against pulmonary fibrosis and inflammation by inhibiting the Nrf2-mediated NLRP3 inflammasome in macrophages. Our data provide initial evidence for the therapeutic efficacy of SS-31 in IPF.
Identification of Dynamic Vibration Parameters of Partial Interaction Composite Beam Bridges Using Moving Vehicle
Authors: Wu Tao , Chen Bowen , Chen Yong , Hu Biao , Lin Jian-Ping
Published: November 2023

The vibration response of a partial composite beam bridge under the influence of moving vehicular loads was investigated. Due to the coupling effect between the vehicle and the bridge, the vibration information of the vehicle encompassed the vibration information of the bridge. Consequently, the dynamic response of the vehicle could be utilized to extract the dynamic information of the composite beam. A moving mass-spring-damping system and composite beam elements considering interfacial slips were used for the interaction vibration of a vehicle-composite bridge. A finite element program for the interaction vibration analysis of the vehicle-composite beam bridge was developed. The program was used to extract the vibration information of the composite beam bridge by analyzing the vehicle displacement, velocity, and acceleration in the interaction vibration of the beam and the vehicle. Taking the Hangzhou Jiubao Bridge as the engineering background, the influences of structural parameters such as shear stiffness of connections, prestress magnitude, as well as vehicle parameters, including vehicle stiffness, damping, and mass, on frequency identification were analyzed. Furthermore, the influences of road roughness, disturbance force generated by vehicle random vibrations, and interference signals generated by signal transmission on frequency identification of the bridge were investigated.
Three-Dimensional Model-Based Line-of-Sight Analysis for Optimal Installation of IoT Monitoring Devices in Underground Mines
Authors: Lee Woo-Hyuk , Han Seong-Soo , Kim Sung-Min
Published: November 2023

Internet of things (IoT)-based wireless communication technology has been applied for efficient work and safety in mines. However, underground mines are surrounded by walls and have numerous curves, which reduce communication stability. For smooth communication between devices, a line of sight (LOS) must be connected without obstacles. If optimal installation locations in a virtual space can be confirmed before installing the device in the field, trial and error can be avoided. In this study, a 3D model-based LOS analysis technology was developed using Python and a ray-casting algorithm. A place with numerous LOS connections has good communication with other places; consequently, it is a suitable location to install the device. To indicate the degree of communication smoothness, a smooth communication index was proposed. A preliminary experiment was conducted in an indoor space within the Samcheok Campus of the Kangwon National University, and a field experiment was conducted at the Samdo Mine in Dogye-eup, Samcheok-si, Gangwon-do. Based on these results, an effective wireless sensor network (WSN) was established by installing a ZigBee-based monitoring device. The results of this study can be further improved and used for constructing smooth WSNs in underground mines in the future.
CommuSpotter: Scene Text Spotting with Multi-Task Communication
Authors: Zhao Liang , Wilsbacher Greg , Wang Song
Published: November 2023

Scene text spotting is a challenging multi-task modulation for locating and recognizing texts in complex scenes. Existing end-to-end text spotters generally adopt sequentially decoupled multi-tasks, consisting of text detection and text recognition modules. Although customized modules are designed to connect the tasks closely, there is no interaction among multiple tasks, resulting in compatible information loss for the overall text spotting. Moreover, the independent and sequential modulation is unidirectional, accumulating errors from early to later tasks. In this paper, we propose CommuSpotter, which enhances multi-task communication by explicitly and concurrently sharing compatible information in overall scene text spotting. To address task-specific inconsistencies, we propose a Conversation Mechanism (CM) to extract and exchange expertise in each specific task with others. Specifically, the detection task is rectified by the text recognition task to filter out duplicated results and false positives, while the text recognition task is corrected by the rectified text detection task to replenish missing characters and decrease non-text interruptions. Consequently, the communication compensates for interaction information and breaks the sequential pipeline of error propagation. In addition, we adopt text semantic segmentation in the text recognition task, which reduces the complex design of customized modules and corresponding extra annotations. Compared with state-of-the-art methods, experimental results show that our method achieves competitive results with computation efficiency.
Research and Application of Edge Computing and Deep Learning in a Recommender System
Authors: Hao Xiaopei , Shan Xinghua , Zhang Junfeng , Meng Ge , Jiang Lin
Published: November 2023

Recommendation systems play a pivotal role in improving product competitiveness. Traditional recommendation models predominantly use centralized feature processing to operate, leading to issues such as excessive resource consumption and low real-time recommendation concurrency. This paper introduces a recommendation model founded on deep learning, incorporating edge computing and knowledge distillation to address these challenges. Recognizing the intricate relationship between the accuracy of deep learning algorithms and their complexity, our model employs knowledge distillation to compress deep learning. Teacher–student models were initially chosen and constructed in the cloud, focusing on developing structurally complex teacher models that incorporate passenger and production characteristics. The knowledge acquired from these models was then transferred to a student model, characterized by weaker learning capabilities and a simpler structure, facilitating the compression and acceleration of an intelligent ranking model. Following this, the student model underwent segmentation, and certain computational tasks were shifted to end devices, aligning with edge computing principles. This collaborative approach between the cloud and end devices enabled the realization of an intelligent ranking for product listings. Finally, a random selection of the passengers’ travel records from the last five years was taken to test the accuracy and performance of the proposed model, as well as to validate the intelligent ranking of the remaining tickets. The results indicate that, on the one hand, an intelligent recommendation system based on knowledge distillation and edge computing successfully achieved the concurrency and timeliness of the existing remaining ticket queries. Simultaneously, it guaranteed a certain level of accuracy, and reduced computing resource and traffic load on the cloud, showcasing its potential applicability in highly concurrent recommendation service scenarios.
Industrial Soldering Process Simulator
Authors: Bąkała Marcin
Published: November 2023

Determination of the physico-chemical interactions between liquid and solid substances is a key technological factor in many industrial processes in metallurgy, electronics or the aviation industry, where technological processes are based on soldering/brazing technologies. Understanding of the bonding process, reactions between materials and their dynamics enables to make research on new materials and joining technologies, as well as to optimise and compare the existing ones. The paper focuses on a wetting force measurement method and its practical implementation in industrial applications. Soldering simulation is a process in which simulation tools are used to model and simulate soldering processes. With simulation, different soldering methods and parameters can be tested to identify the best approach and minimize the risk of errors and failures in the real process. Soldering simulation can be used to optimize the soldering process and increase productivity, as well as to train personnel.
Influence of Nigella sativa L. Oil Addition on Physicochemical and Sensory Properties of Freezer-Stored Ground Pork for Pâté
Authors: Górska-Horczyczak Elżbieta , Brodowska-Trębacz Marta , Hanula Monika , Pogorzelska-Nowicka Ewelina , Wierzbicka Agnieszka , Wojtasik-Kalinowska Iwona , Półtorak Andrzej
Published: November 2023

The purpose of this study was to investigate the effect of Nigella sativa L. (NS) oil addition on the quality of ground pork for pâté stored for one month and two months (−20 ± 1 °C). The study was conducted on a negative control (C), a positive control with the addition of antioxidant (CB) butylated hydroxyanisole (E320), and two groups with the addition of NS oil at the level of 1.9% (O1) and 3.8% (O2). The quality parameters tested in the meat were colour (measured in the CIELab system), lipid oxidation products, the fatty acid profile, thrombogenicity (T1), atherogenicity (A1), and the ratio of hypocholesterolemia to hypercholesterolemia (h/H). After roasting the pâtés, their volatile compound profiles were studied and sensory tests were conducted. A significant effect of NS oil additive on meat colour was found and ΔE for C-O2 increased faster during storage than for C-O1 and C-CB. NS oil additive in pork pâté improved the fatty acid profile. Significant differences in the rate of the fatty acid profile change during storage were observed with the addition of 3.8% NS oil compared to the other groups. Only the O2 group showed no change in PUFA content, while the h/H ratio was approximately 20% higher in the groups with added oil. The addition of NS oil also slowed the growth of TBARSs compared to the C and CB groups. The volatile compound profile of the raw pâté was most influenced by the proportion of terpenes in the NS oil. After two months of meat storage, the O1 pâté received the highest sensory ratings.
Analysis of Evacuation Efficiency for Differently-Abled People in Multi-Layered Buildings Based on Assistance Ratio
Authors: Li Kailing , Fu Wenjing , Cai Jialiang , Qu Lu , Yao Tiantian , Lin Xue
Published: November 2023

The term “differently-abled” refers to people with mobility difficulties, including the disabled and the elderly. In order to explore the optimal evacuation efficiency, in emergencies, of different floors in multi-layered buildings where differently-abled people reside, this study has established a mixed evacuation model based on the characteristics of the evacuation behavior of differently-abled people and non-differently-abled people. This model simulated the impact of evacuation strategies on different floors for differently-abled people at various assistance ratios. Through the comparative analysis of various evacuation strategies, an evacuation efficiency analysis model was constructed, which is suitable for multi-layered buildings where differently-abled people reside. The research indicates that, for stair-determined evacuation strategies, when the proportion of assisting personnel exceeds 70%, there is a noticeable improvement in overall evacuation efficiency. For elevator-determined evacuation strategies, evacuating middle floors with unrestricted methods can enhance evacuation efficiency. The analysis model for optimal evacuation efficiency on each floor that is presented in this study, using a five-story building as an example, can clearly and accurately determine evacuation strategies for multi-layered buildings where differently-abled people reside.
A Systematic Review of the Trends and Advances in IFC Schema Extensions for BIM Interoperability
Authors: Yu Youngsu , Kim Sihyun , Jeon Haein , Koo Bonsang
Published: November 2023

Numerous studies have developed extensions to the IFC schema to meet the needs of specialized domains or represent nascent technologies, and in turn have expanded the scope of interoperability for BIM data exchanges. However, these studies used varying approaches for IFC extensions and validation, making it difficult to identify research gaps and agree on legitimate extension protocols. This study collected 64 studies of IFC schema extensions spanning over two decades, from 2001 to 2022. The analysis first focused on categorizing these cases with respect to their target domains and sectors, their purpose and extension approaches, as well as their methods for implementation and validation. Timeline analyses were also conducted to track the temporal trends over the specified period. The results revealed that architectural cases have recently shifted from process to product representations due to new technology adoptions, while infrastructure cases, initially centered on major sector elements, have transitioned towards operation and maintenance processes. The findings also showed the need for a more holistic and organized approach for extensions, as current ad hoc developments were limited to products and processes only applicable for specific sectors.
Solving the Distributed Permutation Flow-Shop Scheduling Problem Using Constrained Programming
Authors: Gogos Christos
Published: November 2023

The permutation flow-shop scheduling problem is a classical problem in scheduling that aims at identifying the optimal sequence of jobs that should be processed in a number of machines in an effort to minimize makespan or some other performance criterion. The distributed permutation flow-shop scheduling problem adds multiple factories where copies of the machines exist and asks for minimizing the makespan on the longest-running location. In this paper, the problem is approached using Constraint Programming and its specialized scheduling features, such as interval variables and non-overlap constraints, while a novel heuristic is proposed for computing lower bounds. Two constraint programming models are proposed: one that solves the Distributed Permutation Flow-shop Scheduling problem, and another one that drops the constraint of processing jobs under the same order for all machines of each factory. The experiments use an extended public dataset of problem instances to validate the approach’s effectiveness. In the process, optimality is proved for many problem instances known in the literature but has yet to be proven optimal. Moreover, a high speed of reaching optimal solutions is achieved for many problems, even with moderate big sizes (e.g., seven factories, 20 machines, and 20 jobs). The critical role that the number of jobs plays in the complexity of the problem is identified and discussed. In conclusion, this paper demonstrates the great benefits of scheduling problems that stem from using state-of-the-art constraint programming solvers and models that capture the problem tightly.
Exploring BIM Implementation Challenges in Complex Renovation Projects: A Case Study of UBC’s BRDF Expansion
Authors: Zadeh Puyan A. , Han Seungho , Staub-French Sheryl
Published: November 2023

Renovation of existing buildings pose unique challenges to the projects, especially when facilities must remain operational during construction. Building Information Modeling (BIM) methods offer a potential solution by enhancing project management and coordination. Nevertheless, comprehensive case study research on BIM implementation challenges and benefits in renovation projects is lacking. This research addresses this gap through an ethnographic investigation of BIM implementation in a complex renovation project. The ethnographic methods involved direct observation of project meetings, active engagement in all project communications, and access to project data resources. Additionally, surveys and expert interviews with key decision-makers were conducted. The findings reveal how BIM implementation streamlined project management and improved communication, decision making, and output quality, despite limited prior BIM expertise among the major stakeholders. Challenges included a lack of BIM skills, absence of standardized practices, and unclear data management. Furthermore, valuable lessons were identified, including that the necessity of BIM requirements and proper procurement methods encompassing the entire project workflow, formalizing information exchange, preventing information fragmentation, facilitating model accessibility, and ensuring clarity in model detail and content are crucial for project success. This research sheds light on the potential of BIM in renovation projects and highlights key considerations for successful implementation.
A Damage Index for Assessing Seismic-Resistant Designs of Masonry Wall Buildings Reinforced with X-Bracing Concrete Frames
Authors: Chonratana Yossakorn , Chatpattananan Vuttichai
Published: November 2023

In this paper, a suitable damage index is demonstrated to assess the seismic-resistant design of masonry wall buildings reinforced with double x-bracing concrete frames. As a criterion indicative of the damage level that might occur after an earthquake, the damage index can be calculated by using analytic results, by using the Park–Ang formula on masonry wall buildings reinforced with concrete structures, and by adjusting the index values in accordance with the results of the analysed models. The data used in this study are collected from the results of four-storey concrete structures with masonry walls under cyclical lateral forces. To simulate the masonry walls’ structural behaviours for damage assessment, x-bracings placed as crosses on each bracing are used to support the compressive strength. Then, the analysis results are used to assess the damage that occurs to the masonry wall building structure by considering deformation and energy decay; additionally, a suitable damage index is calculated for each damage level. The damage index can be considered in the seismic-resistant design of masonry walls reinforced with x-bracing concrete frames.
Land-Use Regression Analysis of Summer Tropospheric Ozone Concentrations in Ireland
Authors: McHugh Keelan , Cummins Thomas , Aherne Julian
Published: November 2023

Tropospheric ozone is a powerful oxidant that can damage living organisms; it is widely monitored, as air concentrations have more than doubled since the Industrial Revolution. However, in general air quality monitoring stations are limited spatially to large urban centres; accordingly, accurate prediction of concentrations outside of cities is important for protecting human and plant health. Land-use regression has been successfully used for modelling air pollutant concentrations by establishing a relationship between observed concentrations and landscape features representing sources and sinks. In this study, we developed a land-use regression model that explained 68% of the variance of summer average ozone concentrations in the Republic of Ireland. Ozone was measured at 14 active and 20 passive monitoring sites; air concentrations varied spatially, with the highest ozone measured in rural upland (64.5 µg/m3) and Atlantic coastal (50.2–60.5 µg/m3) sites and the lowest generally in urban centres (38.9–45.7 µg/m3). A total of 74 land-use predictor variables were tested, and their inclusion in the model was based on their impact on the coefficient of determination (R2). The final model included variables linked primarily to deposition processes and included “forest woodland and scrub area” and “distance to coast”. The meteorological variable “rain” and an indicator for NOx emissions “distance to EPA Integrated Pollution Control facilities” were also included in the final model. Our results demonstrate the potential effectiveness of land-use regression modelling in predicting ozone concentrations, at a scale relevant for ecosystem protection.
Lightning Nowcasting Using Solely Lightning Data
Authors: Mansouri Ehsan , Mostajabi Amirhosein , Tong Chong , Rubinstein Marcos , Rachidi Farhad
Published: November 2023

Lightning is directly or indirectly responsible for significant human casualties and property damage worldwide. A timely prediction of its occurrence can enable authorities and the public to take necessary precautionary actions resulting in diminishing the potential hazards caused by lightning. In this paper, based on the assumption that atmospheric phenomena behave in a continuous manner, we present a model based on residual U-nets where the network architecture leverages this inductive bias by combining information passing directly from the input to the output with the necessary required changes to the former, predicted by a neural network. Our model is trained solely on lightning data from geostationary weather satellites and can be used to predict the occurrence of future lightning. Our model has the advantage of not relying on numerical weather models, which are inherently slow due to their sequential nature, enabling it to be used for near-future prediction (nowcasting). Moreover, our model has similar performance compared to other machine learning based lightning predictors in the literature while using significantly less amount of data for training, limited to lightning data. Our model, which is trained for four different lead times of 15, 30, 45, and 60 min, outperforms the traditional persistence baseline by 4%, 12%, and 22% for lead times of 30, 45, and 60 min, respectively, and has comparable accuracy for 15 min lead time.
Viability of Artificial Rain for Air Pollution Control: Insights from Natural Rains and Roadside Sprinkling
Authors: Haleem Noor , Kumar Pradeep , Uguz Seyit , Jamal Yousuf , McMaine John , Yang Xufei
Published: November 2023

Artificial rain, a technology primarily used for drought relief, has recently been used for combating regional air pollution. However, there are limited available measurement data to confirm the effectiveness of this control practice. In this study, we summarize control theories and indirect but relevant observations/findings, including air pollutant reduction after natural rain events and roadside sprinkling. A brief review of artificial rain basics is also provided. Our work shows that artificial rain appears to be a promising management strategy for air pollution control. However, field measurements are needed to further assess the cost-effectiveness of the practice, as well as the other benefits or challenges it may create.
City-Scale Aerosol Loading Changes in the Sichuan Basin from 2001 to 2020 as Revealed by MODIS 1 km Aerosol Product
Authors: Wang Ruixin , Cai Hongke
Published: November 2023

Long-term high-resolution monitoring of aerosol optical depth (AOD) is necessary to understand air pollution problems and climate change at regional to urban scales. Based on the 1 km AOD dataset retrieved by the MODIS Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC), the spatial-temporal evolutionary trends of AOD in the Sichuan Basin (SCB), Southwest China, and its 17 subordinate cities were analyzed from 2001 to 2020. In the past 20 years, the annual average AOD in SCB gradually decreased from south to north. The highest AOD of SCB in spring was 0.62, followed by an average AOD value of 0.60 in winter. At the city scale, Zigong, Neijiang, and Ziyang were identified as the three most polluted cities within the SCB. The average AOD in the SCB increased to 0.68 and 0.69 in February and March, respectively, and significantly decreased to 0.41 and 0.43 in June and July, respectively. The interannual AOD in the SCB presented an increasing trend from 2001 to 2010, with a range of 0.50 to 0.70, whereas it showed a decreasing trend from 2011 to 2020, with a range of 0.68 to 0.35. In spring, the annual average AOD at the district level showed significant high values from 2005 to 2012. In winter, the interannual AOD increased significantly, with high values concentrated in 2008, 2010, 2011, and 2013. The occurrence frequency of AOD in the SCB was mainly distributed between 0.2~0.5 and 1.5. There also was an increasing trend of AOD in the SCB from 2001 to 2008 and a decreasing trend from 2009 to 2020. The results of this study hold significance for further understanding the climatic characteristics and environmental effects of regional atmospheric aerosols.
The Relativistic Rotation Transformation and the Observer Manifold
Authors: Kichenassamy Satyanad
Published: November 2023

We show that relativistic rotation transformations represent transfer maps between the laboratory system and a local observer on an observer manifold, rather than an event manifold, in the spirit of C-equivalence. Rotation is, therefore, not a parameterised motion on a background space or spacetime, but is determined by a particular sequence of tetrads related by specific special Lorentz transformations or boosts. Because such Lorentz boosts do not form a group, these tetrads represent distinct observers that cannot put together their local descriptions into a manifold in the usual sense. The choice of observer manifold depends on the dynamical situation under consideration, and is not solely determined by the kinematics. Three examples are given: Franklin’s rotation transformation for uniform plane rotation, the Thomas precession of a vector attached to an electron, and the motion of a charged particle in an electromagnetic field. In each case, at each point of its trajectory, there is a distinguished tetrad and a special Lorentz transformation that maps Minkowski space to the spacetime of the local observer on the curve.