bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced sleep staging with artificial intelligence: a validation study of new software for sleep scoring
Authors: Grassi Massimiliano , Daccò Silvia , Caldirola Daniela , Perna Giampaolo , Schruers Koen , Defillo Archie
Published: December 2023

Manual sleep staging (MSS) using polysomnography is a time-consuming task, requires significant training, and can lead to significant variability among scorers. STAGER is a software program based on machine learning algorithms that has been developed by Medibio Limited (Savage, MN, USA) to perform automatic sleep staging using only EEG signals from polysomnography. This study aimed to extensively investigate its agreement with MSS performed during clinical practice and by three additional expert sleep technicians. Forty consecutive polysomnographic recordings of patients referred to three US sleep clinics for sleep evaluation were retrospectively collected and analyzed. Three experienced technicians independently staged the recording using the electroencephalography, electromyography, and electrooculography signals according to the American Academy of Sleep Medicine guidelines. The staging initially performed during clinical practice was also considered. Several agreement statistics between the automatic sleep staging (ASS) and MSS, among the different MSSs, and their differences were calculated. Bootstrap resampling was used to calculate 95% confidence intervals and the statistical significance of the differences. STAGER's ASS was most comparable with, or statistically significantly better than the MSS, except for a partial reduction in the positive percent agreement in the wake stage. These promising results indicate that STAGER software can perform ASS of inpatient polysomnographic recordings accurately in comparison with MSS.
Effects of agricultural subsidies on farm household decisions: a separable household model approach
Authors: Lal Priyanka , Chandel B. S. , Tiwari Rahul Kumar , El-Sheikh Mohamed A. , Mansoor Sheikh , Kumar Alok , Singh Gyanendra , Lal Milan Kumar , Kumar Ravinder
Published: December 2023

Introduction

This study employs a separable household model to estimate the effect of agricultural subsidies on production and consumption decisions taken by farm households. The study used data from a household survey using a pre-tested schedule to develop and calibrate an agricultural household model.

Method

First, we calculated a price index for the model. The index was higher for non-agricultural commodity groups in all the categories of farm households. Expenditure on non-agricultural commodity groups was more than agricultural commodity groups.

Result and Discussion

Results indicated that for the agricultural commodity group, the estimated coefficients of linear expenditure system (LES) model were positive and less than one for all farm household categories except for the wage-price coefficient which was found to be negative. The estimates of profit function in the study area depict that the variable inputs were negatively related to the profit function and the fixed inputs were positively related to profit. Our study highlights a few crucial points – First, the removal of subsidies will decrease the demand for electricity, concentrate and irrigation by 80, 73 and 70 %, respectively. Second, removing subsidies will not only affect the demand for inputs but will also lead to a decline in the consumption demand for both agricultural and non-agricultural commodities. Third, this effect was found to be more prominent in the small and medium categories of farm households.
Adjustment of Meat Consumption Structure under the Dual Goals of Food Security and Carbon Reduction in China
Authors: Zhao Sicheng , Li Tingyu , Wang Guogang , Zhang Yongxiang
Published: December 2023

With the progress of economic development and increase in income, there have been significant transformations in the food consumption patterns among Chinese residents. Grain consumption has declined while the consumption of livestock products such as meat, poultry, eggs, and milk has gradually risen. Moreover, noteworthy adjustments have been observed in the meat consumption structure itself, with a substantial increase in poultry consumption and a significant decrease in pork consumption as representative of red meat. This study collects data mainly from the “Brick Agricultural Database” and “China National Grain & Oils Information Center”. And then, we employ the China Agricultural Industry Model (CASM) to simulate the economic and ecological consequences of augmenting poultry consumption as a substitute for red meat intake. The research findings demonstrate that ensuring an adequate intake of livestock products for residents without any decline will stimulate the doubling of China’s poultry meat demand by 2035 compared to 2020 while replacing pork. This would reduce feed grain requirements by 50 million tons and achieve carbon emission reductions amounting to 82 million tons. If we consider the consumption of poultry consumption growth in conjunction with its substitution for other red meats such as pork, beef, and mutton, this will save approximately 20 million tons of feed grains and lead to a reduction of around 103 million tons in carbon emissions. In conclusion, promoting future increases in poultry consumption as a substitute for pork and other red meat will yield extensive economic andecological benefits contributing toward international food security goals, as well as global carbon reduction targets. Additionally, advocating for increasing poultry consumption will also reduce the risk of chronic diseases and malignant tumors; this will significantly improve the national health states.
How Does Network Infrastructure Construction Affect Livestock Carbon Emissions?
Authors: Yin Menglei , Song Peng , Yan Weifeng
Published: December 2023

Against the backdrop of new carbon peak and carbon neutrality targets, China must address livestock carbon emissions (LCEs), which account for the largest proportion of agricultural carbon emissions in China. China has been promoting network infrastructure construction (NIC) for digital transformation. This study explores whether NIC can affect LCEs. To capture the potential effects of NIC, a conceptual framework is constructed originally and its impacts on LCEs are tested empirically through a two-way fixed effect model. The results show that NIC can significantly reduce LCEs. The results hold steady in various robustness checks, and the impacts express heterogeneities across provinces with different LCE levels, NIC levels, and regions. Mechanism analysis reveals that NIC can increase LCEs through the livestock industry scale effect, which is nevertheless outweighed by technological innovation and factor allocation’s reduction effects triggered by NIC. Additionally, transportation infrastructure construction serves a moderating role by reinforcing the reduction effect of NIC on LCEs. The conclusions are crucial for advancing the understanding of NIC’s potential benefits and policymaking for carbon emissions reduction in China.
Agromorphological and Chemical Characterization of Pear Cultivars Grown in Central–West Iberian Peninsula
Authors: Pérez-Sánchez Rodrigo , Morales-Corts María Remedios
Published: December 2023

Seventeen traditional pear cultivars grown in the Central–Western Iberian Peninsula, all of them clearly in decline or close to extinction, have been characterized from the point of view of agromorphological and chemical. A total of twenty-one agromorphological and chemical traits, mainly defined by the International Union for the Protection of New Varieties of Plants, were used to describe the fruits during a 3-year period from 2020 to 2022. Some of the genotypes showed distinctive and interesting agronomical characteristics from a commercial point of view, such as high yields and fruit quality. This was the case of the pear cultivars called “Pera Temprana”, “Muslo de Dama”, and “Pera de Cristal de Peñacaballera”. Their fruits were quite heavy (125.32–142.56 g) and had a good sweetness/acidity balance (12.67–14.92° Brix/2.76–3.42 g malic acid/L). The rest of the pear cultivars, with the exception of the “Cermeños” group and “Pera Canela” genotype, also presented interesting commercial characteristics given that their fruits had equatorial diameters greater than 6 cm and total soluble solids levels close to or above 13° Brix. The results of the PCA and cluster analysis showed that agromorphological and chemical analysis can provide reliable information on the variability in pear cultivars. The loss of these traditional crops has enormous significance given that they have unique characteristics and are perfectly adapted to the edapho-climatic conditions of the region. This work constitutes an important step in the conservation of genetic pear resources in the Central–Western Iberian Peninsula.
Physicochemical and Microstructural Characteristics of Sulfated Polysaccharide from Marine Microalga
Authors: Fimbres-Olivarria Diana , Marquez-Escalante Jorge , Martínez-Robinson Karla G. , Miranda-Arizmendi Valeria , Anda-Flores Yubia De , Rascon-Chu Agustín , Brown-Bojorquez Francisco , Carvajal-Millan Elizabeth
Published: December 2023

Marine algae are a valuable source of polysaccharides. However, the information available on sulfated polysaccharides from microalgae is limited. Navicula sp. is a microalga present in the Sea of Cortez, of which little is known regarding their polysaccharides’ properties. This study investigated the physicochemical and microstructural characteristics of Navicula sp. sulfated polysaccharide (NSP). The Fourier transform infrared spectrum of NSP showed distinctive bands (1225 and 820 cm−1, assigned to S–O and C–O–S stretching, respectively), confirming the molecular identity. NSP registered molecular weight, intrinsic viscosity, a radius of gyration, and a hydrodynamic radius of 1650 kDa, 197 mL/g, 61 nm, and 36 nm, respectively. The zeta potential, electrophoretic mobility, conductivity, and diffusion coefficient of the molecule were −5.8 mV, −0.45 µm cm/s V, 0.70 mS/cm, and 2.9 × 10−9 cm2/s, respectively. The characteristic ratio and persistence length calculated for NSP were 4.2 and 1.3 nm, suggesting a nonstiff polysaccharide chain conformation. The Mark–Houwink–Sakurada α and K constants were 0.5 and 1.67 × 10−1, respectively, indicating a molecular random coil structure. NSP scanning electron microscopy revealed a rough and porous surface. Knowing these polysaccharides’ physicochemical and microstructural characteristics can be the starting point for elucidating their structure–function relationship as a valuable tool in advanced biomaterial design.
Eradication of PRRS from Hungarian Pig Herds between 2014 and 2022
Authors: Szabó István , Nemes Imre , Bognár Lajos , Terjék Zsolt , Molnár Tamás , Abonyi Tamás , Bálint Ádám , Horváth Dávid G. , Balka Gyula
Published: December 2023

Porcine reproductive and respiratory syndrome (PRRS) is a widespread infectious disease that is currently a major cause of economic losses in pig production. In Hungary, a National PRRS Eradication Program has been introduced to attain a more efficient, economic, and competitive international market position. The program has been also approved by the EU, but the resulting legal obligations have imposed a burden on Hungarian producers to comply with EU competition rules. The implementation of the program has been carried out by the veterinary authorities with the consent of, continuous support from and monitoring conducted by organisations within the pig sector as well as a scientific committee. The PRRS eradication program in Hungary was based on a regional territorial principle and was compulsory for all pig holdings within the regions. In Hungary, large fattening farms operate as all-in/all-out or continuous flow systems. Large-scale breeding herds are predominantly farrow-to-finish types. Although its significance has decreased in recent decades, 20% of the Hungarian pig population is still kept on small (backyard) farms (<100 animals). All PRRSV-infected large-scale farms had to develop a unit-adapted eradication plan, including external and internal biosecurity measures, vaccinations, etc. It was crucial to render each fattening unit free of the disease, as fattening units play a significant role in spreading the virus within the country. The eradication efforts mainly implemented were depopulation–repopulation methods, but on some farms a testing and removal method has been used. As the eradication progressed over the years, the introduction of infected fattening pigs was restricted. Thanks to these measures, Hungarian large-scale fattening farms became PRRSV-free by the end of 2018. The PRRSV-free status of small-scale herds was achieved by the end of 2015 and was maintained between 2016 and 2021. By 31 December 2021, all breeding pigs in large-scale farms in Hungary were free of wild-type PRRS virus. By 31 March 2022, the total pig population of the country, including all backyard farms and fattening units, achieved PRRSV-free status. The future goal is to ensure and maintain the PRRSV-free status of Hungary via strict import regulations of live animals combined with the continuous and thorough screening of incoming and resident herds for the presence of the virus.
Selective Sweeps in the Austrian Turopolje and Other Commercial Pig Populations
Authors: Atrian-Afiani Farzad , Berger Beate , Draxl Christian , Sölkner Johann , Mészáros Gábor
Published: December 2023

The goal of our study was to identify signatures of selection in the Turopolje pigs and other commercial pig breeds. We conducted a comprehensive analysis of five datasets, including one local pig breed (Turopolje) and four commercial pig breeds (Large White, Landrace, Pietrain, and Duroc), using strict quality control measures. Our final dataset consisted of 485 individuals and 54,075 single nucleotide polymorphisms (SNPs). To detect selection signatures within these pig breeds, we utilized the XP-EHH and XP-nSL methodologies, which allowed us to identify candidate genes that have been subject to positive selection. Our analysis consistently highlighted the PTBP2 and DPYD genes as commonly targeted by selection in the Turopolje breed. DPYD is associated with muscular development in pigs and other species and PTBP2 emerges as one of the potential genes linked to seminal characteristics. Furthermore, in the Large White breed, a number of genes were detected with the two methods, such as ATP1A1, CASQ2, CD2, IGSF3, MAB21L3, NHLH2, SLC22A15, VANGL1. In the Duroc breed, a different set of genes was detected, such as ARSB, BHMT, BHMT2, DMGDH, JMY. The function of these genes was related to body weight, production efficiency and meat quality, average daily gain, and other similar traits. Overall, our results have identified a number of genomic regions that are under selective pressure between local and commercial pig breeds. This information can help to improve our understanding of the mechanisms underlying pig breeding, and ultimately contribute to the development of more efficient and sustainable pig production practices. Our study highlights the power of using multiple genomic methodologies to detect genetic signatures of selection, and provides important insights into the genetic diversity of pig breeds.
Homeostatic Regulation of Pro-Angiogenic and Anti-Angiogenic Proteins via Hedgehog, Notch Grid, and Ephrin Signaling in Tibial Dyschondroplasia
Authors: Nawaz Shah , Kulyar Muhammad Fakhar-e-Alam , Mo Quan , Yao Wangyuan , Iqbal Mudassar , Li Jiakui
Published: December 2023

Precise coupling of two fundamental mechanisms, chondrogenesis and osteogenesis via angiogenesis, plays a crucial role during rapid proliferation of growth plates, and alteration in their balance might lead to pathogenic conditions. Tibial dyschondroplasia (TD) is characterized by an avascular, non-mineralized, jade-white “cartilaginous wedge” with impaired endochondral ossification and chondrocyte proliferation at the proximal end of a tibial bone in rapidly growing poultry birds. Developing vascular structures are dynamic with cartilage growth and are regulated through homeostatic balance among pro and anti-angiogenic proteins and cytokines. Pro-angiogenic factors involves a wide spectrum of multifactorial mitogens, such as vascular endothelial growth factors (VEGF), platelet-derived growth factors (PDGF), basic fibroblast growth factor (bFGF), placental growth factors, transforming growth factor-β (TGF-β), and TNF-α. Considering their regulatory role via the sonic hedgehog, notch-gridlock, and ephrin-B2/EphB4 pathways and inhibition through anti-angiogenic proteins like angiostatin, endostatin, decoy receptors, vasoinhibin, thrombospondin, PEX, and troponin, their possible role in persisting inflammatory conditions like TD was studied in the current literature review. Balanced apoptosis and angiogenesis are vital for physiological bone growth. Any homeostatic imbalance among apoptotic, angiogenetic, pro-angiogenic, or anti-angiogenic proteins ultimately leads to pathological bone conditions like TD and osteoarthritis. The current review might substantiate solid grounds for developing innovative therapeutics for diseases governed by the disproportion of angiogenesis and anti-angiogenesis proteins.
Suspected Primary Intracranial Melanoma with Widespread Distant Metastases in a Cat
Authors: Deacon Jonathan , Beck Samuel , Pitorri Francesca , Stalin Catherine
Published: December 2023

An 8-year-old female Domestic Shorthair presented with signs of intracranial disease. Magnetic resonance imaging (MRI) of the head showed an extra-axial space-occupying mass within the cranial vault with a similar intensity lesion within the overlying temporalis muscle. Postmortem examination found masses within the head, lung, liver, spleen, and kidney consistent with malignant melanoma. Intracranial melanoma is rarely reported in cats and is typically only seen as a metastatic lesion associated with an ocular mass. Melanomas can be readily recognised on MRI as they are one of the few lesions which are hyperintense on T1-weighted images.
Dual-Stream Fusion Network with ConvNeXtV2 for Pig Weight Estimation Using RGB-D Data in Aisles
Authors: Tan Zujie , Liu Junbin , Xiao Deqin , Liu Youfu , Huang Yigui
Published: December 2023

In the field of livestock management, noncontact pig weight estimation has advanced considerably with the integration of computer vision and sensor technologies. However, real-world agricultural settings present substantial challenges for these estimation techniques, including the impacts of variable lighting and the complexities of measuring pigs in constant motion. To address these issues, we have developed an innovative algorithm, the moving pig weight estimate algorithm based on deep vision (MPWEADV). This algorithm effectively utilizes RGB and depth images to accurately estimate the weight of pigs on the move. The MPWEADV employs the advanced ConvNeXtV2 network for robust feature extraction and integrates a cutting-edge feature fusion module. Supported by a confidence map estimator, this module effectively merges information from both RGB and depth modalities, enhancing the algorithm’s accuracy in determining pig weight. To demonstrate its efficacy, the MPWEADV achieved a root-mean-square error (RMSE) of 4.082 kg and a mean absolute percentage error (MAPE) of 2.383% in our test set. Comparative analyses with models replicating the latest research show the potential of the MPWEADV in unconstrained pig weight estimation practices. Our approach enables real-time assessment of pig conditions, offering valuable data support for grading and adjusting breeding plans, and holds broad prospects for application.
Rumination Detection in Sheep: A Systematic Review of Sensor-Based Approaches
Authors: Schneidewind Stephanie Janet , Al Merestani Mohamed Rabih , Schmidt Sven , Schmidt Tanja , Thöne-Reineke Christa , Wiegard Mechthild
Published: December 2023

The use of sensors to analyze behavior in sheep has gained increasing attention in scientific research. This systematic review aims to provide an overview of the sensors developed and used to detect rumination behavior in sheep in scientific research. Moreover, this overview provides details of the sensors that are currently commercially available and describes their suitability for sheep based on the information provided in the literature found. Furthermore, this overview lists the best sensor performances in terms of achieved accuracy, sensitivity, precision, and specificity in rumination detection, detailing, when applicable, the sensor position and epoch settings that were used to achieve the best results. Challenges and areas for future research and development are also identified. A search strategy was implemented in the databases PubMed, Web of Science, and Livivo, yielding a total of 935 articles. After reviewing the summaries of 57 articles remaining following filtration (exclusion) of repeated and unsuitable articles, 17 articles fully met the pre-established criteria (peer-reviewed; published between 2012 and 2023 in English or German; with a particular focus on sensors detecting rumination in sheep) and were included in this review. The guidelines outlined in the PRISMA 2020 methodology were followed. The results indicate that sensor-based systems have been utilized to monitor and analyze rumination behavior, among other behaviors. Notably, none of the sensors identified in this review were specifically designed for sheep. In order to meet the specific needs of sheep, a customized sensor solution is necessary. Additionally, further investigation of the optimal sensor position and epoch settings is necessary. Implications: The utilization of such sensors has significant implications for improving sheep welfare and enhancing our knowledge of their behavior in various contexts.
Saliva Sampling Material Matters: Effects on the Results of Saliva Analysis in Pigs
Authors: Ortín-Bustillo Alba , Botía María , López-Arjona Marina , Pardo-Marín Luis , Cerón José J. , Martínez-Subiela Silvia , López-Martínez María José , Tvarijonaviciute Asta , Muñoz-Prieto Alberto , Rubio Camila P. , Martínez-Miró Silvia , Escribano Damián , Tecles Fernando
Published: December 2023

The use of saliva as a biological sample from pigs is of high practical interest because blood collection from pigs is difficult and stressful. In this study, the influence of two different materials, a cotton roll and a polypropylene sponge, in porcine saliva collection was evaluated. For this purpose, the effect of the material used for sampling was evaluated in a panel of 13 analytes, including those related to stress (cortisol and oxytocin), inflammation and immunity (adenosine deaminase, haptoglobin and myeloperoxidase), redox homeostasis (the cupric reducing ability of saliva, the ferric reducing activity of saliva, and the Trolox equivalent antioxidant capacity), and sepsis (procalcitonin), as well as other routine analytes related to metabolism and different tissues and organs, such as lactate dehydrogenase, creatine kinase, urea, and total protein concentration. The polypropylene sponge provided a higher sample volume than the cotton roll. Although the results of some salivary analytes were equivalent for both materials, other analytes, such as creatine kinase, haptoglobin and total proteins, showed significant differences depending on the material used for saliva collection. Therefore, the type of material used for salivary collection in pigs should be considered when interpreting the results of analyses of the salivary analytes.
Synchronous Grouting Analysis of Shield Tunneling through High Water Pressure Fault Fracture Zone
Authors: Zeng Yi , Wang Shun , Zhang Xiaolong , Luo Miaotong , Zhu Junzhou , Bian Yuewei , Gong Chenjie , Fu Yanbin , Lv Qi , Liang Ning , Yu Zhengyi
Published: December 2023

Using numerical software to establish a three-dimensional geological model of shield tunneling through fault fracture zones, considering the synchronous grouting effect at the shield tail, the disturbance of various geotechnical structures in the fault fracture zone under deep burial and high water pressure conditions is studied. According to the comparison between the numerical model analysis results and the on-site inspection results of the entire process of Shiziyang B3 section, synchronous grouting at the shield tail is the main reason for the changes in soil and water pressure in the fault fracture zone area. The soil and water pressure changes strongly during shield tunneling, and the maximum excess pore pressure value occurs when the shield tail passes. When the shield tunneling machine is far away, the soil and water stress shows a downward trend. The impact of synchronous grouting decreases with the increase in tunneling distance. Due to the difference in permeability, the variation law of pore pressure in the fault fracture zone is significantly different from the original rock, leading to a faster increase in pore pressure in the fracture zone area and a wider range of influence.
Molecular Simulation Study on the Effect of Co-Associated Minerals on Methane Adsorption and Mechanical Properties of Coal
Authors: Zhang Xiaoyu , Liu Yingjie , Zhou Tianbai , Cai Yongbo , Zhang Bin
Published: December 2023

When rockbursts and coal and gas outbursts simultaneously occur in a coal mine, changes in gas adsorption (concentration of ambient methane) and displacement of coal and rock must occur. The co-associated minerals in coal reservoirs can affect the mechanical properties and methane adsorption capacity, which are commonly disregarded. It is important to construct compound molecular structure models of coal and rock and conduct molecular dynamic simulations to gain a microscopic understanding of underground disasters. In this work, the molecular structure models of anthracite and coking coal–rock compound models containing different contents of calcite and kaolinite were constructed, and the methane adsorption amount and mechanical properties considering temperature, pressure, and mineral contents were simulated and analysed. The results showed that the methane adsorption amount of the compound models increased rapidly, then increased moderately, and stabilized eventually with increasing adsorption pressure, and the Langmuir fitting findings were good. The saturation adsorption amount of methane in the coal models linearly decreased with increasing temperature, while the methane adsorption heat increased. The presence of minerals adsorbed a certain amount of methane, and the methane adsorption amount increased with increasing mineral contents. The mechanical properties of coal molecules changed when mineral molecules such as calcite and kaolinite were present, which had opposite contribution effects. The addition of kaolinite minerals to the coal molecular model always increased the bulk modulus and shear modulus, while the addition of calcite decreased the bulk modulus of the anthracite, causing an increase in the brittleness of the models. The results of the study further explain the adsorption behaviour and mechanical properties of methane in coal and minerals.
YOLO-SE: Improved YOLOv8 for Remote Sensing Object Detection and Recognition
Authors: Wu Tianyong , Dong Youkou
Published: December 2023

Object detection remains a pivotal aspect of remote sensing image analysis, and recent strides in Earth observation technology coupled with convolutional neural networks (CNNs) have propelled the field forward. Despite advancements, challenges persist, especially in detecting objects across diverse scales and pinpointing small-sized targets. This paper introduces YOLO-SE, a novel YOLOv8-based network that innovatively addresses these challenges. First, the introduction of a lightweight convolution SEConv in lieu of standard convolutions reduces the network’s parameter count, thereby expediting the detection process. To tackle multi-scale object detection, the paper proposes the SEF module, an enhancement based on SEConv. Second, an ingenious Efficient Multi-Scale Attention (EMA) mechanism is integrated into the network, forming the SPPFE module. This addition augments the network’s feature extraction capabilities, adeptly handling challenges in multi-scale object detection. Furthermore, a dedicated prediction head for tiny object detection is incorporated, and the original detection head is replaced by a transformer prediction head. To address adverse gradients stemming from low-quality instances in the target detection training dataset, the paper introduces the Wise-IoU bounding box loss function. YOLO-SE showcases remarkable performance, achieving an average precision at IoU threshold 0.5 (AP50) of 86.5% on the optical remote sensing dataset SIMD. This represents a noteworthy 2.1% improvement over YOLOv8 and YOLO-SE outperforms the state-of-the-art model by 0.91%. In further validation, experiments on the NWPU VHR-10 dataset demonstrated YOLO-SE’s superiority with an accuracy of 94.9%, surpassing that of YOLOv8 by 2.6%. The proposed advancements position YOLO-SE as a compelling solution in the realm of deep learning-based remote sensing image object detection.
Prediction of the Productivity Ratio of Perforated Wells Using Least Squares Support Vector Machine with Particle Swarm Optimization
Authors: Wang Haijing , Zhang Chao , Zhou Bo , Xue Shifeng , Wang Feifei
Published: December 2023

The productivity ratio is a vital metric for assessing the efficiency of perforated completions. Accurate and rapid prediction of this ratio is essential for optimizing the perforation design. In this study, we propose a novel approach that combines three-dimensional finite element numerical simulation and machine learning techniques to predict the productivity ratio of perforated wells. Initially, we obtain the productivity ratio of perforated wells under various perforation parameters using three-dimensional finite element numerical simulation. This generates a sample set for machine learning. Subsequently, we employ the least squares support vector machine (LSSVM) algorithm to establish a prediction model for the productivity ratio of perforated wells. To optimize the parameters of the LSSVM algorithm, we utilize the particle swarm optimization (PSO) algorithm. We compare our proposed PSO-LSSVM model with that established based on other parameter optimization methods and machine learning algorithms, such as Grid search-LSSVM, PSO-ANN, and PSO-RF. Our results demonstrate that the PSO-LSSVM model exhibits rapid convergence, high prediction accuracy, and strong generalization ability in predicting the productivity ratio of perforated wells. This research provides a valuable reference and guidance for optimizing perforation design. Additionally, it offers new insights into predicting the productivity of complex completions.
Advanced Digital Tools for Data-Informed and Performance-Driven Design: A Review of Building Energy Consumption Forecasting Models Based on Machine Learning
Authors: Di Stefano Andrea Giuseppe , Ruta Matteo , Masera Gabriele
Published: December 2023

Cities and buildings represent the core of human life, the nexus of economic activity, culture, and growth. Although cities cover less than 10% of the global land area, they are notorious for their substantial energy consumption and consequential carbon dioxide (CO2) emissions. These emissions significantly contribute to reducing the carbon budget available to mitigate the adverse impacts of climate change. In this context, the designers’ role is crucial to the technical and social response to climate change, and providing a new generation of tools and instruments is paramount to guide their decisions towards sustainable buildings and cities. In this regard, data-informed digital tools are a viable solution. These tools efficiently utilise available resources to estimate the energy consumption in buildings, thereby facilitating the formulation of effective urban policies and design optimisation. Furthermore, these data-driven digital tools enhance the application of algorithms across the building industry, empowering designers to make informed decisions, particularly in the early stages of design. This paper presents a comprehensive literature review on artificial intelligence-based tools that support performance-driven design. An exhaustive keyword-driven exploration across diverse bibliographic databases yielded a consolidated dataset used for automated analysis for discerning the prevalent themes, correlations, and structural nuances within the body of literature. The primary findings indicate an increasing emphasis on master plans and neighbourhood-scale simulations. However, it is observed that there is a lack of a streamlined framework integrating these data-driven tools into the design process.
A Simple and Easily Implementable Model for the Prediction of Solar Irradiance for All-Sky Conditions: Model Development, Preliminary Evaluation and Application
Authors: Micallef Alfred
Published: December 2023

A simple and easily implementable model and the associated computer code for predicting the solar irradiance at the earth’s surface have been developed. The input requirements of the model include Julian day, time, geographical latitude, atmospheric pressure and cloud cover. If the latter is not available, then the program user has the option of entering either the daily global solar flux or the duration of sunshine, from which the average cloud cover is estimated. Preliminary model evaluation has been carried out using data from two meteorological stations situated in rural and semi-rural areas of the East Midlands, United Kingdom. The scatter plots of predicted versus observed solar irradiance gave correlation coefficients approximately equal to 0.6 and slopes in the range of 0.80–0.93. The model is being implemented as a submodule within an urban air quality model. This specific application of the solar radiation model is discussed as a typical implementation. This work shows that by adopting relatively simple ‘textbook’ material, i.e., basic theory/information, one can achieve reasonably good solar radiation modelling, with outcomes that can be used for applications where accuracy is not a major requirement.
Statistical Characteristics of Stress Changes in Tunnel Surrounding Rock Based on Random Discrete Variability of Geotechnical Materials
Authors: Jiang Rong , Yang Zhao , Chen Song , Yuan Ying , Liu Liang
Published: December 2023

In the construction of underground engineering, the determination of surrounding rock stresses has important theoretical significance for the design of tunnel structure reliability. In this paper, the nonlinear criterion is introduced to modify and improve the friction resistance in the calculation formula of Bierbaumer’s loose surrounding rock stresses, and the improved application is carried out in view of the situation of composite formation. Due to the variability and discreteness of geotechnical parameters, combined with engineering examples, Monte Carlo random sampling is carried out for various geotechnical parameters in engineering, and the characteristics of loose surrounding rock stresses are analyzed from the perspective of statistical reliability by using the improved shallow tunnel formula. By using the standard regression coefficient, the weight influence of the parameters in various shallow surrounding rock stress formulas is analyzed, and the confidence degree of the calculated results of various formulas is analyzed from a statistical point of view, which verifies the rationality of the improved formula in the statistical sense.
Research on the Digital Twin System of the Centring Process for High-Precision Lens
Authors: Chen Zexiang , Li Yanyan , Ma Guannan , Wang Yaman , Qin Botao
Published: December 2023

In the manufacturing process of optical lenses, the lack of monitoring and detection of the central processing process leads to low processing efficiency and difficulty in ensuring product consistency. We propose a digital twin system for alignment processing to address this issue. The system adopts a hierarchical architecture based on the digital twin five-dimensional model, aiming to improve the fidelity and interactivity of the virtual model of the centring lathe by combining dimension-driven virtual models with integrated data and physical models of the turning mechanism. We have successfully achieved the semantic and physical fusion of multi-source heterogeneous data during centring processing using information models and OPC UA-based data interaction methods. In addition, we adopted the VMD-GRU method based on feature fusion for real-time monitoring of critical components of the centring lathe. Finally, we validated the feasibility and effectiveness of the digital twin system for the central lathe through development examples. The application of this system is expected to promote the digital and intelligent development of high-precision optical component processing, providing references including references for related manufacturing fields. In summary, we propose a digital monitoring and detection system for the centring process of optical lens manufacturing. The application of this system will help improve product consistency and processing efficiency while reducing risks and costs in the manufacturing process.
A Microalgae Photobioreactor System for Indoor Air Remediation: Empirical Examination of the CO2 Absorption Performance of Spirulina maxima in a NaHCO3-Reduced Medium
Authors: Han Myungho , Park Jinsuck , Kim Inhan , Yi Hwang
Published: December 2023

Microalgae-based photobioreactors (PBRs) have gained attention as a sustainable solution for indoor air quality (IAQ) control. This study investigates indoor CO2 absorption performance of Spirulina maxima (S. maxima) in NaHCO3-limited cultivation (standard: NaHCO3-free medium = 1:1 v/v%) of a lab-scale PBR system. Cultivation performance of three medium amendments (standard, 50% NaHCO3, and NaHCO3-free) was compared by observing cell growth for 30 days in a controlled environment. Empirical examinations were conducted to evaluate the algal CO2 uptake, and overall system performance in the culture volumes of 2, 4, and 7 L and natural indoor CO2 concentration of ~1100 ppm. We found CO2 was reduced by ~55%, in an air chamber of 0.064 m3, showing the greatest mitigation rate (~20%) on Day 4. Under a high concentration of CO2 (10,000 ppm), the CO2 levels were decreased up to ~90% before saturation. This research provides valuable insights into the development of S. maxima-activated IAQ control systems for airtight buildings.
Comprehensive Analysis of Mammography Images Using Multi-Branch Attention Convolutional Neural Network
Authors: Al-Mansour Ebtihal , Hussain Muhammad , Aboalsamh Hatim A. , Al-Ahmadi Saad A.
Published: December 2023

Breast cancer profoundly affects women’s lives; its early diagnosis and treatment increase patient survival chances. Mammography is a common screening method for breast cancer, and many methods have been proposed for automatic diagnosis. However, most of them focus on single-label classification and do not provide a comprehensive analysis concerning density, abnormality, and severity levels. We propose a method based on the multi-label classification of two-view mammography images to comprehensively diagnose a patient’s condition. It leverages the correlation between density type, lesion type, and states of lesions, which radiologists usually perform. It simultaneously classifies mammograms into the corresponding density, abnormality type, and severity level. It takes two-view mammograms (with craniocaudal and mediolateral oblique views) as input, analyzes them using ConvNeXt and the channel attention mechanism, and integrates the information from the two views. Finally, the fused information is passed to task-specific multi-branches, which learn task-specific representations and predict the relevant state. The system was trained, validated, and tested using two public domain benchmark datasets, INBreast and the Curated Breast Imaging Subset of DDSM (CBIS-DDSM), and achieved state-of-the-art results. The proposed computer-aided diagnosis (CAD) system provides a holistic observation of a patient’s condition. It gives the radiologists a comprehensive analysis of the mammograms to prepare a full report of the patient’s condition, thereby increasing the diagnostic precision.
SPinDP: A High-Speed Distributed Processing Platform for Sampling and Filtering Data Streams
Authors: Gil Myeong-Seon , Moon Yang-Sae
Published: December 2023

Recently, there has been an explosive generation of streaming data in various fields such as IoT and network attack detection, medical data monitoring, and financial trend analysis. These domains require precise and rapid analysis capabilities by minimizing noise from continuously generated raw data. In this paper, we propose SPinDP (Stream Purifier in Distributed Platform), an open source-based high-speed stream purification platform, to support real-time stream purification. SPinDP consists of four major components, Data Stream Processing Engine, Purification Library, Plan Manager, and Shared Storage, and operates based on open-source systems including Apache Storm and Apache Kafka. In these components, stream processing throughput and latency are critical performance metrics, and SPinDP significantly enhances distributed processing performance by utilizing the ultra-high-speed network RDMA (Remote Direct Memory Access). For the performance evaluation, we use a distributed cluster environment consisting of nine nodes, and we show that SPinDP’s stream processing throughput is more than 28 times higher than that of the existing Ethernet environment. SPinDP also significantly reduces the processing latency by more than 2473 times on average. These results indicate that the proposed SPinDP is an excellent integrated platform that can efficiently purify high-speed and large-scale streams through RDMA-based distributed processing.
Improved Computer Vision Framework for Mesoscale Simulation of Xiyu Conglomerate Using the Discrete Element Method
Authors: Zhang Yutao , He Zijie , Jiang Ruonan , Liao Lei , Meng Qingxiang
Published: December 2023

The complex mechanical characteristics of the Xiyu conglomerate significantly influence the resistance and deformation features of its caverns’ surrounding rock, thereby constraining the construction of related water diversion tunnels. This paper introduces an improved SegFormer framework developed for the detection of mesoscale geomaterial structures. Computerized tomography (CT) scan images of the Xiyu conglomerate were employed to establish a high-precision numerical model. From the results of segmentation, the proposed algorithm outperformed UNet, HRNet, and the original SegFormer neural network. The segmentation results were used to calculate the porosity, and biaxial compression numerical simulation experiments based on the real structure were carried out using the particle flow code (PFC). We observed the failure process of the model and obtained the shear strength of the Xiyu conglomerate. We explored the causes and influencing factors of the anisotropy of the Xiyu conglomerate from the microstructure perspective and provide a micro-observation basis for establishing an anisotropic mechanical model.
Effect of Postharvest UVB Irradiation on the Fruit of cv. Dottato (Ficus carica L.)
Authors: Giordano Cristiana , Benelli Carla , Faraloni Cecilia , Grifoni Daniele , Anichini Monica , Ieri Francesca , Traversi Laura , Beghè Deborah , Petruccelli Raffaella
Published: December 2023

Exposing fruits and vegetables to UVB radiation post-harvest is a technique used to modify secondary metabolites and prolong their shelf life. The aim of the present study was to evaluate the effects of UVB irradiation on the chemical and physical characteristics of fig cv. Dottato fruits. The UVB irradiation was 2.26 Wm−2. Two exposure times were carried out: 10 and 60 min resulting in a UVB dose of 1.4 and 8.1 kJm−2, respectively. In the control, the UVB was eliminated by a polyester film (control −UVB). After treatment, the fig fruits were stored and analyzed at different times until decay. Quality parameters (decay, weight loss, color, chlorophyll, and firmness) and physicochemical parameters (soluble solids content, pH parameters, and titratable acidity) were positively influenced by irradiation. Total and individual sugars increased gradually during the storage period in both the skin and the flesh, with glucose being higher after 10 days in the UVB treated samples. Total carotenoid content increased gradually during the storage period, with a marked increase in the +UVB fruit. The content of total and individual polyphenols was positively influenced by UVB treatment, with the UVB treated samples showing the highest values at both 7 and 10 days. The study showed an increase in by-products in both the skin and the flesh. This research confirms the effectiveness of UVB radiation in improving the nutritional qualities and shelf life of Ficus carica fruits.
Spatiotemporal Analysis of Extreme Rainfall and Meteorological Drought Events over the Angat Watershed, Philippines
Authors: Tejada Allan T. , Sanchez Patricia Ann J. , Faderogao Francis John F. , Gigantone Catherine B. , Luyun Roger A.
Published: December 2023

Understanding the spatiotemporal distribution of extreme rainfall and meteorological drought on a watershed scale could be beneficial for local management of any water resources system that supports dam operation and river conservation. This study considered the watershed of Angat as a case, given its economic importance in the Philippines. A series of homogeneity tests were initially conducted on each rainfall dataset from monitoring stations in and near the watershed, followed by trend analysis to determine the rate and direction of change in the annual and seasonal rainfall extreme indices in terms of intensity, duration, and frequency. Three indices, using the rainfall deviation method (%DEV), percent of normal rainfall index (PNRI), and Standardized Precipitation Index (SPI), were also used to identify meteorological drought events. Generally, rainfall in the watershed has an increasing annual PCPTOT (4–32 mm/year), with increasing frequency and intensity in heavy rainfall and wet days. A significant increasing trend (α = 5%) in the seasonal PCPTOT (7–65 mm/year) and R10mm (1.7–10.0 days/decade) was particularly observed in all stations during the Amihan Monsoon Season (Dec–Feb). The observed increasing rainfall intensity and frequency, if it continues in the future, could have an implication both for the water resources operation to satisfy the multiple objectives of Angat Reservoir and for the flood operation that prevents damage in the downstream areas. The effect of each ENSO (El Niño- Southern Oscillation) phase on the rainfall is unique in magnitude, intensity, and duration. The seasonal reversal of the ENSO in the extreme rainfall and meteorological drought signals in Angat Watershed was also evident. The identified meteorological drought events in the watershed based on SPI-12 persisted up to 12–33 months, could reduce more than 60% (PNRI < 40%) of the normal rainfall. Insights from the study have implications for the hydrology of the watershed that should be considered for the water resources management of the Angat Reservoir.