bluuebunny/crossref_metadata_2025 huggingface dataset:
Customer churn prediction using composite deep learning technique
Authors: Khattak Asad , Mehak Zartashia , Ahmad Hussain , Asghar Muhammad Usama , Asghar Muhammad Zubair , Khan Aurangzeb
Published: October 2023

Customer churn, a phenomenon that causes large financial losses when customers leave a business, makes it difficult for modern organizations to retain customers. When dissatisfied customers find their present company's services inadequate, they frequently migrate to another service provider. Machine learning and deep learning (ML/DL) approaches have already been used to successfully identify customer churn. In some circumstances, however, ML/DL-based algorithms lacks in delivering promising results for detecting client churn. Previous research on estimating customer churn revealed unexpected forecasts when utilizing machine learning classifiers and traditional feature encoding methodologies. Deep neural networks were also used in these efforts to extract features without taking into account the sequence information. In view of these issues, the current study provides an effective method for predicting customer churn based on a hybrid deep learning model termed BiLSTM-CNN. The goal is to effectively estimate customer churn using benchmark data and increase the churn prediction process's accuracy. The experimental results show that when trained, tested, and validated on the benchmark dataset, the proposed BiLSTM-CNN model attained a remarkable accuracy of 81%.
Genome-wide identification of candidate copy number polymorphism genes associated with complex traits of Tibetan-sheep
Authors: Tian Dehong , Sun De , Ren Qianben , Zhang Pei , Zhang Zian , Zhang Wenkui , Luo Haizhou , Li Xue , Han Buying , Liu Dehui , Zhao Kai
Published: October 2023

Copy number variation (CNV) is a genetic structural polymorphism important for phenotypic diversity and important economic traits of livestock breeds, and it plays an important role in the desired genetic variation. This study used whole genome sequencing to detect the CNV variation in the genome of 6 local Tibetan sheep groups. We detected 69,166 CNV events and 7230 copy number variable regions (CNVRs) after merging the overlapping CNVs, accounting for 2.72% of the reference genome. The CNVR length detected ranged from 1.1 to 1693.5 Kb, with a total length of 118.69 Mb and an average length of 16.42 Kb per CNVR. Functional GO cluster analysis showed that the CNVR genes were mainly involved in sensory perception systems, response to stimulus, and signal transduction. Through CNVR-based Vst analysis, we found that the CACNA2D3 and CTBP1 genes related to hypoxia adaptation, the HTR1A gene related to coat color, and the TRNAS-GGA and PIK3C3 genes related to body weight were all strongly selected. The findings of our study will contribute novel insights into the genetic structural variation underlying hypoxia adaptation and economically important traits in Tibetan sheep.
The value of serum creatinine as biomarker of disease progression in spinal and bulbar muscular atrophy (SBMA)
Authors: Blasi Lorenzo , Sabbatini Daniele , Fortuna Andrea , Querin Giorgia , Martinelli Ilaria , Vianello Sara , Bertolin Cinzia , Pareyson Davide , Pennuto Maria , Pegoraro Elena , Bello Luca , Sorarù Gianni
Published: October 2023

Serum creatinine has been indicated as a potential marker of motor function in SBMA and results form previous longitudinal studies pointed to its decline over time. This is a longitudinal retrospective study investigating creatinine changes over a 36-month-period in 73 patients with SBMA. Severity and progression of the disease was assessed according to serum creatine kinase (CK) values, manual muscle testing (MMT), SBMA functional rating scale (SBMAFRS) score, 6-min-walk test (6MWT) value, and spirometry (forced vital capacity, fVC%) obtained at the baseline and at each of the annual follow-up visits. Baseline serum creatinine concentrations positively correlated with 6MWT, the MMT megascore score of both the upper (ULM) and lower (LLM) limbs and SBMAFRS. No correlation was found with CK or fVC% values. Similar correlation results were achieved at all the subsequent time points. Longitudinal assessments conducted by the generalized estimating equations (GEE) method returned significant changes for SBMAFRS (− 1.41 points per year, p < 0.001), ULM and LLM (− 0.69, p = 0.01; and − 1.07, p < 0.001, respectively), 6MWT (− 47 m, p < 0.001) but not for creatinine (− 0.82, p > 0.05). We also observed that creatinine levels at baseline did not correlate with changes in the other measures from baseline at each annual visit. Our data do not support a role for serum creatinine as sensitive biomarker of disease progression, and possibily prognosis, in SBMA.
Pharmarcomechanical thrombectomy combined with transluminal balloon angioplasty for treating transplant renal vein thrombosis
Authors: Wu Shao-Jie , Zhang Chi , Wu Min , Ruan Dan-dan , Zhang Yan-ping , Lin Bin , Tang Yi , Chen Xin , Wang Chen , Pan Hong-hong , Zhu Qing-guo , Luo Jie-wei , Ye Lie-fu , Fang Zhu-ting
Published: October 2023

Renal vein thrombosis (RVT) is a rare vascular complication that occurs after renal transplantation and usually results in irreversible kidney damage and graft loss. We report the case of a patient who underwent right iliac fossa allogeneic kidney transplantation and developed RVT combined with ipsilateral thrombosis from the popliteal to the femoral veins, with extension to the common iliac veins, 4 months after transplantation. Under unfractionated heparin anticoagulation, an Aegisy (Life Tech Scientific Co., Ltd., Shenzhen, China) vena cava filter was placed to prevent pulmonary embolism. Percutaneous mechanical thrombectomy combined with balloon angioplasty was performed to aspirate the thrombus and successfully dilate the narrow venous lumen. The patient’s renal function was restored postoperatively. Ultrasonography showed the allograft and ipsilateral lower extremity deep veins to be fluent and patent. To conclude, in patients with RVT after renal transplantation, percutaneous mechanical thrombectomy in conjunction with balloon angioplasty can be performed with desirable outcomes and no severe adverse effects. This method reduces the risk of bleeding from exposure to systemic intravenous thrombolysis and avoids surgery-associated trauma.
General and central obesity prevalence in young adult: a study based on the Rafsanjan youth cohort study
Authors: Abbasifard Mitra , Bazmandegan Gholamreza , Ostadebrahimi Hamid , Amiri Mahsa , Kamiab Zahra
Published: October 2023

Growing prevalence of obesity among youth would have adverse consequences and increased risk of developing chronic diseases at older ages. This study explored the prevalence of obesity and its association with relevant risk factors in the Rafsanjan youth cohort population. This cross-sectional study was done on 3006 individuals from the 15–35-year-old population included in the Rafsanjan youth cohort study. The data were extracted from the youth cohort databases, which had been collected through in-person interview and standard questionnaires. Definition of general obesity was considered as body mass index ≤ 30 and that of central obesity as waist to hip ratio (WHR) ≥ 0.9 for men and ≥ 0.85 for women. Multivariate stepwise proportional odds model and multivariable stepwise logistic regression models were done to explore the factors associated with general obesity and central obesity. The mean age was 25.78 ± 6.06 years with 56% (n = 1683) female. The prevalence of general obesity was 15.80% (95% CI 14.50–17.11) and central obesity was 28.41% (95% CI 26.80–30.02). The risk of general obesity increased with increasing age (OR = 1.053, P < 0.0001), being married (OR = 1.658, P < 0.0001), history of diabetes (OR = 1.609, P = 0.0185), history of hypertension (OR = 1.609, P < 0.0001), elevated triglyceride (OR = 1.007, P < 0.0001) and LDL (OR = 1.015, P < 0.0001), while decreasing with being employed (OR = 0.748, P = 0.0002) and elevated HDL (OR = 0.975, P < 0.0001). Prevalence of obesity was high in study population. Marital status, increasing age, and history of chronic diseases were associated with obesity. Preventing programs should be developed against obesity and for promoting healthy habits in young adult especially during education at schools.
Research on fire resistance and economy of basalt fiber insulation mortar
Authors: Ding Chen , Xue Kaixi , Yi Guangsheng
Published: October 2023

The construction sector has become the most critical source of carbon emissions, but the existing thermal insulation materials such as thermal insulation mortar have obvious limitations, so it is urgent to develop building thermal insulation materials with superior performance and low cost. Aiming at the problem of poor bond strength of foam thermal insulation mortar, this research team selected basalt fiber as admixture to verify the influence of basalt fiber content on its performance and the economic feasibility of thermal insulation mortar. The main finding is that basalt fiber as an additive can obviously improve the crack resistance of thermal insulation mortar. When the content of basalt fiber increases from 0 to 2.5%, the compressive strength of mortar increases at first and then decreases, and the bond strength increases nonlinearly, but the thermal conductivity and dry density also increase. Therefore, the optimal content of basalt fiber is 1.5%. The improvement effect of fire resistance of thermal insulation mortar with 1.5% basalt fiber content is better. After curing for 28 days, the mass loss rate of the sample is reduced by about 11.1% after high temperature, and the relative compressive strength is increased by about 9.71% after high temperature. The raw material cost of the new fireproof thermal insulation mortar improved by basalt fiber is lower, and the cost of the finished product is reduced by 16.98%, 28.18%, 33.05% and 38.96%, respectively, compared with the four types of thermal insulation mortar already used in the market. More importantly, the economic recovery period of the new fireproof and thermal insulation mortar is undoubtedly shorter than that of alternative thermal insulation or energy storage materials, which not only achieves low emission and environmental protection, but also satisfies the economic feasibility.
Rapid and visual detection of Toxoplasma gondii oocyst in cat feces using loop-mediated isothermal amplification (LAMP) assay
Authors: Sheng Lingwei , Xue Qiqi , Xu Sijia , Can Fang , Yao Ning , Zou Minghui , Teng Qiao , Li Yuanyuan , El-Ashram Saeed , Ji Yongsheng , Zhao Jinhong
Published: October 2023

Toxoplasma gondii is an obligate parasitic protozoon that transmits to animals and humans via ingested food. Cats that act as T. gondii’s final hosts play a critical role in T. gondii transmission by shedding millions of oocysts. Timely diagnosis of infected cats is essential for preventing toxoplasmosis because oocysts are a putative T. gondii source in epidemiology. We developed a new visual LAMP assay targeting the B1 gene to analyze single oocysts in cat feces in this study. The amplification result could be visually estimated based on the color change. LAMP assay analytical sensitivity was 101 copies/µL for the B1 gene plasmid, which was tenfold better than the PCR reaction. There were no cross-reactions with other parasites. The LAMP assay can detect a single T. gondii oocyst in 200 mg of cat feces. The LAMP assay detected a single oocyst in 200 mg cat feces at a higher rate than the PCR assay (83.3% vs. 50.0%).
A digital solution framework for enabling electric vehicle battery circularity based on an ecosystem value optimization approach
Authors: Kumar Amit , Huyn Pierre , Vennelakanti Ravigopal
Published: October 2023

A circular economy for batteries is crucial for building a sustainable battery value chain, as end-of-life electric vehicle batteries can be given a second life or valuable raw materials can be harvested to make new batteries. However, significant challenges remain in forecasting availability, predicting remaining value, minimizing reverse logistics costs, and maximizing value recovery from end-of-life batteries. Here we devise an ecosystem value optimization approach powered by a digital solution framework, consisting of innovative analytical models and a trusted data platform, to optimize five key value drivers for battery circularity—safety, regulatory compliance, carbon footprint reduction, quality, and financials. The envisioned solution can help reduce average transportation costs of end-of-life batteries by 11% to 44% compared to current shipping practices, estimate battery health with error rates less than 1%, and improve value recovery by 52% to 60% by routing batteries with good health to second-life application providers.
A stochastic approach for assessing the chronic environmental risk generated by wet-weather events from integrated urban wastewater systems
Authors: Ianes Jessica , Cantoni Beatrice , Remigi Enrico Ulisse , Polesel Fabio , Vezzaro Luca , Antonelli Manuela
Published: October 2023

Environmental chronic risk generated by wet-weather discharges compared to final effluent was stochastically assessed, also from a climate-change perspective, stressing their growing contribution for many (micro-)pollutants.
Consuming almonds with chocolate or lettuce influences oral processing behaviour, bolus properties and consequently predicted lipid release from almonds
Authors: Chen Yao , Stieger Markus , Tonies Floor , Tielens Anki , Capuano Edoardo
Published: October 2023

Chewing almonds in combination with other foods may produce a different fraction of intact cells in the bolus compared to almonds consumed alone and this may affect lipid bioavailability.
Lactobacillus fermentum CKCC1858 alleviates hyperlipidemia in golden hamsters on a high-fat diet via modulating gut microbiota
Authors: Wang Jun , Liu Aijie , Li Ao , Song Hainan , Luo Pengfei , Zhan Meng , Zhou Xiaoli , Chen Lihao , Zhang Jiachao , Wang Ruimin
Published: October 2023

To investigate the effect of probiotic Lactobacillus fermentum CKCC1858, LF on the prevention of hyperlipidemia and its correlation with gut microbiota, golden hamsters were fed a high-fat diet alone or in combination with the probiotic for 6 weeks.
Origin of the switchable photocurrent direction in BiFeO3 thin films
Authors: Wang Yaqiong , Daboczi Matyas , Zhang Man , Briscoe Joe , Kim Ji-Seon , Yan Haixue , Dunn Steve
Published: October 2023

The switchable photocurrent in BiFeO3 photoelectrode arises from its specific bandgap structure, which allows for selective PEC oxidation or reduction, arousing particular interest for its future application in solar energy conversion.
Visible light-mediated hydrogen atom transfer and proton transfer for the conversion of (2-vinylaryl)methanol derivatives to aryl aldehydes or aryl ketones
Authors: Yan Jun , Yu Ziqi , Wei Hao-Zhao , Shi Min , Wei Yin
Published: October 2023

A visible-light-mediated strategy for the efficient conversion of (2-vinylaryl)methanol derivatives to aryl aldehydes or aryl ketones has been developed. The plausible reaction mechanism has been verified by a series of mechanistic studies.
A microbiological system for screening the interference of XNA monomers with DNA and RNA metabolism
Authors: Blanchard Aude , Abramov Mikhail , Hassan Camille , Marlière Philippe , Herdewijn Piet , Pezo Valérie
Published: October 2023

Impact of xenobiotic nucleoside triphosphates on E. coli nucleic acids synthesis.
Homoleptic and heteroleptic ketodiiminate zinc complexes for the ROP of cyclic l-lactide
Authors: Glöckler Eduard , Kapp Leon , Wölper Christoph , Schumacher Marcel , Gröschel André H. , Schulz Stephan
Published: October 2023

We report the structures and activity of homo- and heteroleptic ketodiiminate zinc complexes in the ring-opening polymerization of l-lactide. Homobimetallic complex 2 selectively gave cyclic polylactide, while linear polymers were formed with mononuclear complex 3.
Rheological study of nanoemulsions with repulsive and attractive interdroplet interactions
Authors: Abbasian Chaleshtari Zahra , Foudazi Reza
Published: October 2023

As the potential well between droplets becomes deeper, nanoemulsions show higher  and σy. By superposition of rheological properties of nanoemulsions, a master curve is constructed for dynamic moduli at different volume fractions and interactions.
Self-organized defect-rich RuMOx epitaxial layers (M = Mn, Fe, Co, Ni, Cu) for catalytic applications
Authors: Oda Akira , Ichihashi Risa , Yamamoto Yuta , Sawabe Kyoichi , Satsuma Atsushi
Published: October 2023

We have successfully prepared a unique set of RuMOx epitaxial layers with atomic thickness and abundant defects by a heterometal dopant-assisted epitaxial growth phenomenon and demonstrated their high catalytic applicability.
High strength, self-healing sensitive ionogel sensor based on MXene/ionic liquid synergistic conductive network for human-motion detection
Authors: Wen Xiao , Deng Zhipeng , Wang Hui , Shi Jianyang , Wang Shuang , Wang Haibo , Song Yueming , Du Zongliang , Qiu Jinghong , Cheng Xu
Published: October 2023

The MXene/ionic liquid synergistic network was constructed in this work to solve the problem of poor mechanical properties of ionogel at high ionic liquid content. And, the ionogel was applied to human-motion detection.
A multifunctional bio-patch crosslinked with glutaraldehyde for enhanced mechanical performance, anti-coagulation properties, and anti-calcification properties
Authors: Chang Jiahao , Yu Liyin , Lei Jiao , Liu Xiaoli , Li Chunxiao , Zheng Yali , Chen Hong
Published: October 2023

A multifunctional bio-patch crosslinked with glutaraldehyde for enhanced mechanical performance, anti-coagulation properties, and anti-calcification properties.
Facile synthesis of ytterbium doped cesium lead halide perovskite powder
Authors: Streckaitė Simona , Miklušis Lukas , Maleckaitė Karolina , Abdelrazik Lamiaa , Jašinskas Vidmantas , Pakštas Vidas , Drabavičius Audrius , Rutkauskas Danielis , Franckevičius Marius , Gulbinas Vidmantas
Published: October 2023

A simple mechanosynthesis technique enables fabrication of ytterbium-doped perovskite powder demonstrating more than 100% NIR luminescence yield due to quantum cutting properties.
On the fundamentals of organic mixed ionic/electronic conductors
Authors: Fabiano Simone , Flagg Lucas , Hidalgo Castillo Tania C. , Inal Sahika , Kaake Loren G. , Kayser Laure V. , Keene Scott T. , Ludwigs Sabine , Muller Christian , Savoie Brett M. , Lüssem Björn , Lutkenhaus Jodie L. , Matta Micaela , Meli Dilara , Patel Shrayesh N. , Paulsen Bryan D. , Rivnay Jonathan , Surgailis Jokubas
Published: October 2023

This perspective offers insights from discussions conducted during the Telluride Science meeting on organic mixed ionic and electronic conductors, outlining the challenges associated with understanding the behavior of this intriguing materials class.
Switching threshold event‐triggered critic algorithm for optimal orbit tracking and formation motion
Authors: Yu Rui , Chen Yang‐Yang , Zhang Ya
Published: October 2023

This paper deals with the orbit tracking and formation motion problems with optimal energies and reduced computational cost. First, the orbit tracking and formation motion are decomposed into movements in the normal and tangent directions of level orbits, respectively, and simultaneously, the optimal value functions in both directions are defined. Then, to reduce the computational cost, a switching threshold event‐triggered (STET) mechanism is designed. Based on the STET mechanism, the optimal value functions are constructed to evaluate the optimal energies of orbit tracking and formation motion. Critic neural networks are then designed to approximate the optimal value functions, which yield the optimal policies along the normal and tangent directions of desired orbits, that is, a so‐called switching threshold event‐triggered critic algorithm (STET‐C). Theoretical analysis of system convergence is given in detail. Finally, two comparison simulations are given. The former intends to verify the optimal energy of STET‐C compared to the feedback controllers. The latter shows that STET‐C significantly reduces the computational cost in contrast with the non‐triggered actor‐critic algorithm, non‐triggered critic algorithm, and the relative threshold event‐triggered critic algorithm.
Representation constraint‐based dual‐channel network for face antispoofing
Authors: Li Zuhe , Cui Yuhao , Wang Fengqin , Liu Weihua , Yang Yongshuang , Yu Zeqi , Jiang Bin , Chen Hui
Published: October 2023

Although multimodal face data have obvious advantages in describing live and spoofed features, single‐modality face antispoofing technologies are still widely used when it is difficult to obtain multimodal face images or inconvenient to integrate and deploy multimodal sensors. Since the live/spoofed representations in visible light facial images include considerable face identity information interference, existing deep learning‐based face antispoofing models achieve poor performance when only the visible light modality is used. To address the above problems, the authors design a dual‐channel network structure and a constrained representation learning method for face antispoofing. First, they design a dual‐channel attention mechanism‐based grouped convolutional neural network (CNN) to learn important deceptive cues in live and spoofed faces. Second, they design inner contrastive estimation‐based representation constraints for both live and spoofed samples to minimise the sample similarity loss to prevent the CNN from learning more facial appearance information. This increases the distance between live and spoofed faces and enhances the network's ability to identify deceptive cues. The evaluation results indicate that the framework we designed achieves an average classification error rate (ACER) of 2.37% on the visible light modality subset of the CASIA‐SURF dataset and an ACER of 2.4% on the CASIA‐SURF CeFA dataset, outperforming existing methods. The proposed method achieves low ACER scores in cross‐dataset testing, demonstrating its advantage in domain generalisation.
Short‐term wind power prediction based on combined long short‐term memory
Authors: Zhao Yuyang , Li Lincong , Guo Yingjun , Shi Boming , Sun Hexu
Published: October 2023

Wind power is an exceptionally clean source of energy; its rational utilization can fundamentally alleviate the energy, environment, and development problems, especially under the goals of ‘carbon peak’ and ‘carbon neutrality’. A combined short‐term wind power prediction based on long short‐term memory  (LSTM) artificial neural network has been studied aiming at the non‐linearity and volatility of wind energy. Due to the large amount of historical data required to predict the wind power precisely, the ambient temperature and wind speed, direction, and power are selected as model input. The Complete Ensemble Empirical Mode Decomposition with Adaptive Noise has been introduced as data preprocessing to decompose wind power data and reduce the noise. And the Particle Swarm Optimization is conducted to optimize the LSTM network parameters. The combined prediction model with high accuracy for different sampling intervals has been verified by the wind farm data of Chongli Demonstration Project in Hebei Province. The results illustrate that the algorithm can effectively overcome the abnormal data influence and wind power volatility, thereby providing a theoretical reference for precise short‐term wind power prediction.
Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory
Authors: Jiang Enyu , Zhang Wentao , Xue Ang , Lin Shunfu , Mi Yang , Li Dongdong
Published: October 2023

A method for identifying vulnerable nodes in distribution networks is proposed, which is based on complex networks and optimized TOPSIS. This method aims to address the issues of one‐sided evaluation indicators and inaccurate indicator weights that are present in existing methods for identifying vulnerable nodes in distribution networks. Based on the theory of complex networks, a comprehensive set of vulnerability indicators for distribution network nodes is constructed by considering both the topology structure and system operation status of the distribution network. The TOPSIS comprehensive evaluation model for optimization is proposed to enhance the selection process of optimal and worst indicator values. The advantages and disadvantages of each indicator are characterized using Mahalanobis distance. The calculation of proximity is optimized by establishing a virtual negative ideal solution, which makes the identification of vulnerable nodes more reasonable. The simulation results demonstrate that this method is more effective in identifying vulnerable nodes in the power grid compared to traditional methods, and has significant practical applications.
A pedestrian trajectory prediction method based on improved LSTM network
Authors: Liu Fugang , Duan Songnan , Juan Wang
Published: October 2023

Pedestrian trajectory prediction based on vision is a popular task in autopilot system. As pedestrian trajectories always cross each other, pedestrian targets will frequently obscure each other, which makes the collected pedestrian trajectories produce errors. Moreover, the interaction between pedestrians will have an impact on their trajectories in crowded areas, which leads to great challenge in trajectory prediction. In order to solve the above two problems, a pedestrian trajectory prediction method is proposed. Based on the YOLOv7 algorithm, it is connected with the StrongSORT algorithm. Then adding a feature recognition (ReID) module to the model, the problem of target switching and jumping in the process of pedestrian tracking can be solved. The dot product attention mechanism is also integrated into the long short term memory (LSTM) algorithm, the improved LSTM correlate target position and distance information for the pedestrian trajectory prediction. Extensive experiments on three most challenging datasets showed that this method improves the performance and largely reduces the model size.
A parking occupancy prediction method incorporating time series decomposition and temporal pattern attention mechanism
Authors: Ye Wei , Kuang Haoxuan , Li Jun , Lai Xinjun , Qu Haohao
Published: October 2023

Parking occupancy prediction is an important reference for travel decisions and parking management. However, due to various related factors, such as commuting or traffic accidents, parking occupancy has complex change features that are difficult to model accurately, thus making it difficult for parking occupancy to be accurately predicted. Moreover, how to give appropriate weights to these changing features in prediction becomes a new challenge in the era of machine learning. To tackle these challenges, a parking occupancy prediction method called time series decomposition–long and short‐term memory neural network (LSTM)–temporal pattern attention mechanism, which consists of three modules, namely 1) time series decomposition: modelling parking occupancy changes by extracting features such as trend, period, and effect; 2) encoder: extracting temporal correlations of feature sequences with LSTM; 3) temporal pattern attention mechanism: assigning attention to different features, are proposed. The evaluation results of 30 parking lots in Guangzhou city show that the proposed model 1) improves accuracy over the baseline model LSTM by 9.14% on average; 2) performs outstanding in four prediction time intervals and six types of parking lots, proving its validity and generality; 3) demonstrates its rationality and interpretability through ablation experiments and Shapley additive explanation.
Millimetre‐wave radar‐based spirometry for the preliminary diagnosis of chronic obstructive pulmonary disease
Authors: Wang Wei , Wan Yinghua , Li Chengxi , Chen Zhaoxi , Zhang Wenyu , Zhao Lina , Zhao Jingquan , Mu Xiangdong , Li Gang
Published: October 2023

Chronic respiratory diseases, especially chronic obstructive pulmonary disease (COPD), have high morbidity and mortality worldwide. Spirometry is regarded as the gold standard for the diagnosis of COPD. However, conventional spirometry requires expensive devices and trained personnel. Therefore, it is not feasible for conventional spirometry to popularise outside the hospital. Millimetre‐wave radar has the characteristics of low cost and high integration. It can accurately capture the motion of the chest, which makes it possible to evaluate the pulmonary function of humans. A method to measure important respiratory indices in spirometry based on a 60‐GHz frequency‐modulated continuous‐wave radar system is proposed. The impact of body motion is reduced via a dedicated body twitch correction algorithm. A new fitting formula was utilised to estimate forced expiratory volume in one second and forced vital capacity. Experimental results demonstrated that millimetre‐wave radar‐based spirometry can achieve a high agreement with conventional spirometry. It is potential for radar‐based spirometry to be an alternative to conventional spirometry in the preliminary diagnosis of COPD outside the hospital.
A novel fault diagnosis method for PV arrays using convolutional extension neural network with symmetrized dot pattern analysis
Authors: Lu Shiue‐Der , Wu Chia‐Chun , Sian Hong‐Wei
Published: October 2023

PV fault diagnosis remains difficult due to the non‐linear characteristic of PV output, which makes PV output to be likely disturbed by the ambient environment. This study proposes a novel convolutional extension neural network (CENN) algorithm, which is a jointed architecture based on convolutional neural network (CNN) and extension neural network (ENN), takes advantage of CNN and ENN. The CENN is combined with the symmetrized dot pattern (SDP) analysis method to diagnose the common eight PV array faults. The SDP is used to transform the measured PV signals into the point coordinate feature image; then, the CENN is trained to identify the different PV faults. Experimental results show an obvious improvement in short detection times and high accuracy compared with traditional CNN and the histogram of oriented gradient (HOG) extraction method with support vector machine (SVM), K‐nearest neighbours (KNN), and back propagation neural network (BPNN) classifiers, with 95.3%, 94%, 93.5%, and 93.3% accuracy, respectively. Using the proposed CENN, the accuracy can be raised to 97.3%. Additionally, the signals measured by various sensors are collected using programmable logic controller (PLC). The human–machine interface (HMI) and the proposed algorithm are developed using LabVIEW for graphical design. Finally, the information is transmitted to a tablet PC for performing real‐time remote monitoring.
Counter-rotor hydraulic unit on the basis of a nozzle jet hydro turbine
Authors: Bozarov Oybek , Aliyev Rayimjon , Kodirov Dilshod , Begmatov Eldorjon
Published: October 2023

This article analyzes counter-rotor hydraulic units developed on the basis of jet turbines. A new design of a counter-rotor hydraulic unit developed by the authors, consisting of a jet turbine with a nozzle and a water wheel, the principle of its operation and essence is described. Based on the velocity triangle of water flowing through the reactive and active impellers, the rotational speed of the impeller was analyzed. Accordingly, analytical relationships between the energy parameters of the impellers are presented.
Intensification of heat transfer during condensation of water vapor on a vertical tube
Authors: Eshkuvatov Lutfulla , Babakhodjayev Rakhimjan , Tashbayev Nazim
Published: October 2023

A review of the scientific literature on the intensification of the heat exchange process during condensation of water vapor on the surface of a vertical tube is carried out and the main results of the study are presented. The work on the study of heat transfer during laminar condensation of water vapor in the form of a laminar-flowing liquid in the form of a film both inside and on the outer surfaces of vertical tubes with an ascending steam flow is analyzed. The numerical values of Nusselt and Reynolds, which are also known and proposed for the case under consideration, have been studied. Methods of intensification of the heat exchange process are presented by improving the geometric configuration of the heat exchange surface from the side of the heating steam, on which its condensation occurs during heat transfer, which consists in reducing the thermal resistance of the wall molecular layers of the liquid. This method helps to increase the coefficient of heat transfer from steam to the wall surface by increasing the surface area of heat exchange. Based on the study of the results of well-known works, the authors have developed an experimental laboratory installation to study the increase in the efficiency of water vapor condensation processes on the outer surface of a vertical tube. An important scientific problem to be solved is the breakdown of the laminar-flowing liquid of condensed steam from the heat exchange surface, which leads to the admission and contact of steam directly from the cold surface of the tube.
Study on computerized measurement-control system for determining the condition of electrical network insulation and permitted connections for electrical energy consumption
Authors: Mirzoyev Narzullo
Published: October 2023

In this article electrical distribution in order to ensure the reliability and safe operation of networks, information is provided about the computerized measurement control system that allows determining the state of their insulation. In the article, the functional scheme of the computerized measurement and control system, which allows to determine the state of electrical network insulation and unauthorized connections to electricity, the structural diagram of the connection of the computerized measurement and control device to the electrical network, the structural diagram of the program developed for calculating the electrical network sizes, and the development of mathematical models developed.
Energy characteristics of electrotechnological processing of grape cuttings
Authors: Markaev Nuriddin , Abdiraxmonov Islom , Davletov Ikrom , Tukhtaev Babur
Published: October 2023

The article studies the energy properties of energy input into cuttings during electrical processing of a grape stem, taking into account the state of the system in two media (water and cuttings). At the same time, the energy absorbed by grape cuttings depends on the structure of grape cuttings (bast, xylem, core and peel), resistance between the electrode and water (R1, R7), water resistance between the electrode and the grape cut (R2, R6), resistance between the cut grapes and water (R3, R5), stalk resistance of grapes (R4), conductive water resistance (R8) have been determined and scientifically substantiated. As a result, the distance between the electrode and the grape stem (l1), the length of the stem (l2), the distance between the electrodes (l3), the area of electrode coverage with water (S1), the surface of the grape stems (S2), the diameter of the stems 1.2-1.5 cm, the current density increases with time (0-24 hours) in a humid environment by 1-2 A/m2 at 33.33 V/m2, the electric field strength at 133.33 V/m changes by 7-8 A/m2, and in a dry environment, the useful energy absorbed by the handle between the electrodes placed inside the working chamber decreases to 0.8-0.68 A/m2 at 133.33 V/m2 over time (0-24 hours). It has been established that the absorption depends on the distance (l), processing voltage (U), and time of exposure to electric current (τ).
A review of heat recovery technology for passive ventilation applications
Authors: Shodiyev Bobur , Usmonov Nizomjon , Davirov Alisher , Kobilov Rakhimjon , Tukhtaeva Rano
Published: October 2023

Regenerative heat exchangers are widely used in life support systems, gas turbines, boilers and other high-temperature industrial installations. These heat exchangers are used for cooling and heating gases, humidification and dehumidification of gases, heat recovery from high-potential heat carriers. Today, the increase in energy consumption and the increase in energy prices require a large-scale energy-saving policy in the creation of modern engineering structures – residential, commercial and industrial facilities alike. When designing and creating life support systems to save energy, it is advisable to use secondary energy resources, such as, for example, the heat of the air removed from the room. The energy intensity of conventional ventilation systems is on average 50–80% of the total energy intensity of the engineering systems of the facility where they are operated. The use of rotating regenerative heat exchangers in ventilation and air conditioning systems makes it possible to return up to 85% of heat to the system at a relatively low capital investment. In this regard, when improving such systems, considerable attention should be paid to the calculation, optimization and increase in the efficiency of heat exchangers. Thus, this work is about increasing the efficiency of rotating regenerative heat exchangers in ventilation and air conditioning systems.
Deformation measurement by digital holographic interferometry
Authors: Akbarova Nigora , Azamatov Zakirdjan
Published: October 2023

Nondestructive testing (NDT) methods and techniques play a vital role in enhancing product quality across various industries. Among these methods, the optical approach stands out, relying on the analysis of how optical radiation interacts with the test object. The key information parameters for optical testing of objects encompass their spectral and integral photometric characteristics. These characteristics are influenced by factors such as the substance’s structure, temperature, physical state, microrelief, angle of incident radiation, polarization degree, and wavelength. By leveraging optical methods, defects within materials can be detected without causing damage to the object. These defects encompass voids (discontinuities), delaminations, pores, cracks, inclusions of foreign bodies, internal stresses, alterations in material structure, and variations in physical and chemical properties, as well as deviations from specified geometric shapes. It’s important to note that optical methods are limited to detecting internal defects only in products made of materials that are transparent within the optical spectrum’s region. By harnessing the power of nondestructive optical testing, industries can ensure the integrity and quality of their products, detect potential flaws, and maintain stringent quality standards without causing any harm to the tested objects. The method with use of transformation of Fourier over sequence of the holograms, which are written down in various time points, is described. Possibility of measurement of deformations of composite material when heating is shown by low-power laser radiation.
The impacts of improper curbside parking on traffic flow in semi-urban area, Ethiopia
Authors: Rage Faye Fikedu , Kelecha Abdurrahman Mohammed , Rakhmatov Abdugani , Mannobboyev Shuxratbek , Abdunazarov Jamshid
Published: October 2023

Introduction: For many towns in Ethiopia, traffic management is a crucial concern to accommodate the increased number of vehicles per day. Curbside parking is one of the traffic problem experience in Arba Minch town, especially in the midblock commenced at Sikella market to Gamo Square. This area is one of the central business district areas of Arba Minch Town that experience parking problems. Objective: The study was initiated to investigate the impacts of curbside parking on the traffic flow of the semi-urban area. It was aimed at identifying the cause of curb-side parking and evaluating the parking duration of vehicles. Methods: Various methods were used to accomplish the study. The data needed for the study were; Number of parking vehicles, duration, parking attraction, the length of curbside that is used for parking continuously, parking pattern and composition of parking vehicles investigated and the geometry of the road has been done by direct field observation. Interviews were also conducted with the owners of the businesses located beside the selected road. To show the change in the traffic flow which occurred due to the existence of curbside parking, traffic volume, and speed study has been also done. Results: From the collected data, the reason for continuous parking in the study area was identified. These main reasons were the availability of recreational centers and surrounding business activities. The average number of parking vehicles along 120m long curbside which is used for continuous parking was obtained to be 16 vehicles. The parking pattern shown in the area was irregular which leads to accidents and traffic conflicts. The minimum duration of parking was 10 minutes, whereas the maximum was more than 2 hours. Because of the lack of work and climate conditions, most vehicles were parked in the midmorning and midafternoon. Most drivers were volunteered to use off-street parking if it provided. Using the traffic volume and speed study, the capacity of the road is estimated to be 140 vehicles per hour. Finally, the level of service on the road was determined for every 30 minutes.
Identification of Non-Stationary Objects Based on Training a Neural Network and Tuning the Parameters of a Generalized Model
Authors: Jumanov Isroil , Kholmonov Sunatillo
Published: October 2023

Methods and algorithms have been developed for identifying non-stationary objects of various types using statistical, dynamic, neural network models, which are taken into account when solving problems of conditions of a priori insufficiency, uncertainty, low reliability of data. Mechanisms are proposed that provide effective identification based on combining the features of dynamic models with the properties of random time series. The possibilities of algorithms based on mechanisms that use statistical, dynamic, specific data characteristics, as well as the properties of self-adaptation, approximation, organization, self-learning of neural networks have been expanded. A generalized function identification algorithm has been developed and its functions have been expanded by adaptive segmentation of time series, setting the informative interval of element values, the size of the training set, training multilayer neural networks, database, and knowledge base. The training algorithms for a three-layer neural network are modified based on the mechanisms for regulating interneuronal connections in layers, weight coefficients of neurons, variable activation functions, network architecture, and superposition of continuous input-output dependencies. A software package for identifying random time series in the C++ language in the CUDA parallel computing environment has been developed to predict the annual power consumption of the industrial zone of the Samarkand region using software tools for data preprocessing, filtering, smoothing; determining the boundaries of the informative interval of time series elements.
Architectural design response to population issue in sub-Saharan cities
Authors: Okeke Francis O. , Ezema Emmanuel C. , Nnaemeka-Okeke Rosemary C. , Okosun Andrew E. , Okeke Chioma A.
Published: October 2023

Overpopulation is a serious global problem, and it is predicted to get worse in future if unchecked; accompanied with threat of dwindling resources. The increase in population and its effect on the housing sector is surfacing as clog in the wheel of efforts at reducing Africa’s housing deficits. How then can urban life continue to thrive in the existing housing issues in colonial, sub-Saharan city of Enugu, exploiting architectural design strategies is what the study investigates. It utilized a qualitative research approach of survey and participant observation in which data were collected and analysed based on thematic content analysis. Gross housing deficit, increased housing rent, emergence and expansion of squatter settlement, Land use conversion and slum conditions are some observable effects of population growth due to urbanization and rural-urban drift in the city; Statistics of public housing provision between 1999-2020, showed an over focus on high-income earners, neglecting the majority low-income population. Therefore, architect’s intervention in the housing sector should be strategic, holistic and proactive and encourage use of local materials, vertical development, dry construction and stakeholder’s participation in delivery process. The study concludes that futuristic architecture holds the key to humanity’s continued stewardship on earth and a sustainable housing delivery.
Substantiation of the physics of mathematical calculation of the heat-humidity regime of building envelopes in non-stationary conditions
Authors: Berdiyev Oblokul , Asatov Nurmuhamat , Abdurakhmonov Azizjon , Djurayev Uktam , Sagatov Bakhodir
Published: October 2023

This article explores calculation methods and experimental studies of newly erected, restored, and: reinforced, multi-layer enclosing structures, which most fully considers the specifics of the impact on them of the individual properties of materials, the climate of the construction area, and operating conditions. The calculation of the humidity regime of external enclosing structures in a non-stationary mode will make it possible to more accurately determine the moisture content of materials in the structure, primarily in the heat-insulating layer, and, depending on humidity, establish the actual coefficients of thermal conductivity of materials, which will help to more accurately determine the thermal resistance to heat transfer and predict the effectiveness of thermal protection of enclosing structures of buildings in operational conditions.