bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling the chloride transport in concrete from microstructure generation to chloride diffusivity prediction
Authors: Tong Liang‐yu , Liu Qing‐feng , Xiong Qingxiang , Meng Zhaozheng , Amiri Ouali , Zhang Mingzhong 
Published: August 2024

AbstractPore structure characteristics of cementitious materials play a critical role in the transport properties of concrete structures. This paper develops a novel framework for modeling chloride penetration in concrete, considering the pore structure‐dependent model parameters. In the framework, a multi‐scale transport model was derived by linking the chloride diffusivities with pore size distributions (PSDs). Based on the three‐dimensional (3D) microstructure generated by “porous growth” and “hard core‐soft shell” methods, two sub‐models were computationally developed for determining the multi‐modal PSDs and pore size‐related chloride diffusivities. The predicted results by these series of models were compared with corresponding experimental data. The results indicated that by adopting pore size‐related diffusivities, even if the total porosities were the same, the proposed multi‐scale chloride transport model could better capture the effect of different PSDs on chloride penetration profiles, while the model without pore structure‐depended parameters would ignore the differences. Compared with the reference transport models, which adopt averaged chloride diffusivities, the chloride penetration depths predicted by the proposed multi‐scale model are in better agreement with experimental data, with 10%–25% reduced prediction error. This multi‐scale transport model is hoped to provide a novel computational approach on 3D microstructure generation and better reveal the underlying mechanism of the chloride penetration process in concrete from a microscopic perspective.
Losing control: REF 2029 and the downgrading of academic outputs
Authors: Gandy Matthew 
Published: August 2024

AbstractIn June 2023 UKRI (UK Research and Innovation) announced that the contribution of research outputs to the next REF (Research Excellence Framework) exercise will be radically reduced. In addition, the link between individuals and research publications is to be replaced by a more generic emphasis on ‘research culture’. In this commentary I argue that this change in policy poses a significant threat to the legitimacy of the entire process and will endanger the kind of individual scholarship that is typical within much of the social sciences and the humanities.
Development of Camera System for Monitoring Robotic Polishers
Authors: Nagamine Kota , Mori Kotaro , Kono Daisuke , Beaucamp Anthony 
Published: August 2024

Abstract
Industrial robots have been in increasing demand in recent years, although their lower positioning accuracy and velocity controllability (compared to CNC machine tools) makes it difficult to adopt them in machining processes such as milling. However, precision polishing using compliant tools, fluid jets, etc., belongs to the class of time-dependent processes where the amount of material removed depends on the surface feed rate of tool influence on the workpiece. Therefore, there is a possibility to maintain high accuracy even when using industrial robots, so long as the velocity profile is well predicted. In this paper, the attitude and motion of an industrial robot tool center point is estimated using a stereoscopic high-speed camera setup. 3 light markers are mounted above a fluid jet polishing nozzle attached to the robot end-effector. Their positional relationship to the tool center point is ascertained by collecting posture data while maintaining a precision ball at a fixed location with an R-test device. Next, raster paths are generated and the robot motion is recorded with the cameras. This data is used to predict the surface profile to be generated when polishing a BK7 optical window. Actual polishing confirms a good correlation, within 10 nanometers, between measured and predicted material removal.
Effect of Thermal Load on Specific Energy Consumption in Heavy-Duty Cutting
Authors: Mori Kotaro 
Published: August 2024

Abstract
Energy efficiency is an important issue in recent manufacturing. Previous studies reported that specific energy consumption (SEC) improves with a higher material removal rate (MRR). However, they did not consider the effect of cooling energy required during machining. This study presents a method to calculate the SEC that considers the heat generated by the machining loads by combining the SEC that is measured by short-time experiments without considering the heat generation and that considering the output characteristics of the cooling system obtained by the preliminary experiments. The calculated results were applied to analyze the effect of cooling on SEC in heavy-duty cutting. The results indicate that the cooling energy does not affect the power-law model much in the case of the investigated machine, while a slight difference is observed in the high MRR range. Even at an MRR of 100,000 mm3/min, the difference in SEC with and without considering cooling energy is less than 10%. However, differences may not be negligible in older machines with low efficiency.
Geometric Error Identification Method for Swiss-Type Automatic Lathe by Using Reference Sphere and Displacement Sensor
Authors: Kawai Ryota , Sato Ryuta 
Published: August 2024

Abstract
Accuracy of machined parts are deteriorated due to geometric errors between axes in five-axis machine tools. Therefore, many research works have been carried out to identify and compensate the geometric errors. Swiss-type automatic lathes are widely applied to machine small parts with complex shapes. Although many geometric errors exist in Swiss-type automatic lathes, conventional measurement methods cannot evaluate geometric accuracy due to small working space of the automatic lathes. In addition, the influence of geometric errors onto machining accuracy has not been clarified. In this study, a mathematical model with geometric errors of a Seiss-type automatic lathe that represents the tool tip position in the workpiece coordinate system is developed. The correctness of the model has confirmed through comparing the simulated machined grooves and real ones. A method to identify the geometric errors using a reference sphere and a displacement sensor is also developed based on the model and measurement tests are carried out. As a result, it is confirmed that five geometric errors can be identified by three different measurement methods. It is also confirmed that the measured deviation by the displacement sensor can be decreased by adjusting the coordinate offset parameters on NC controller. Machined shape of the grooves are also be improved by the parameter adjustment based on the identified geometric errors.
Geometric Simulation of 5-Axis Machining With Descrete Placement of Tool Models
Authors: Inui Masatomo , Iuchi Shogo , Umezu Nobuyuki 
Published: August 2024

Abstract
This study reports on the development of a geometric simulation method for 5-axis machining that eliminates the need for tool swept volume in the calculation. This method repeatedly subtracts the tool shape model, which gradually changes its position and posture along the cutter path, from the workpiece model to obtain the workpiece shape after machining. This method was commonly used in early machining simulation software, but had a disadvantage that the tool spacing had to be sufficiently small to obtain accurate results, leading to high computational costs. The current research differs from previous studies in three key aspects: (1) it leverages the parallel processing function of the graphics processing unit to achieve high processing speeds, (2) it clarifies the relationship between tool spacing and calculation accuracy to achieve optimal tool placement, and (3) it employs a highly accurate polyhedral representation of the tool shape to realize a general-purpose method that can be applied to any cutting tools.
Nonlinear Modeling of Ball Rolling Motion on a Horizontal Surface for Improving Grasp-Less Handling by Applying Rolling Friction Torque
Authors: Hanai Hiroaki , Yuma Mita , Wada Yuiga , Nakagawa Masao , Hirogaki Toshiki , Aoyama Eiichi 
Published: August 2024

Abstract
In this study, rolling friction was applied to model the rolling motion of a ball on a horizontal surface to achieve grasp-less handling operation with a dual-arm SCARA robot. The rolling friction acts in the direction that prevents the ball from rolling, i.e., in the direction opposite to the angular velocity. Here, rolling friction is a torque, i.e., rolling friction torque. In the model without rolling friction torque, the ball moves relative to the plate no matter how small the acceleration of the plate on the horizontal plane. This is different from the real phenomenon. Rolling friction torque is applied to the rolling motion of a ball on a horizontal plane in a form that allows for a frequency response.
Ball End Milling and Cutting-Force Monitoring of Small Number of Circular Arc Tooth Gears by 4-Axis-Controlled Machining Center
Authors: Yang Zhiming , Tanaka Kaito , Nakagawa Masao , Hirogaki Toshiki , Aoyama Eiichi 
Published: August 2024

Abstract
Improving gear accuracy in advanced machinery and equipment, such as automobiles and airplanes, has become increasingly important in recent years. To realize a compact and energy-efficient transmission, gear pairs with high gear ratios are required. Although the worm gear has the lowest number of teeth, a pinion gear is a more efficient reduction gear for power transmission. Moreover, the pinion gear with fewer teeth allows for a larger reduction ratio. Employing a pinion gear when designing the electric actuator of vehicles has several advantages. The high power-transfer efficiency of the pinion gear enables the vehicle to achieve the same power with a reduced motor and actuator size. In addition, the use of smaller motors improves the power efficiency and thereby reduces the amount of power required to operate the actuator. In high-precision gear manufacturing, small-number gear-cutting end milling is gaining attention as an essential machining method. Particularly, for precisely machining small number of teeth, the 4-axis-controlled Robodrill is more widely used than the 5-axis-controlled Robodrill, although they are more expensive.
Efficient Fault Detection in Bearings: Synergizing Transformer Adaptations With Convolutional Kernel
Authors: Zhou Qianyu , Tang Jiong 
Published: August 2024

Abstract
Efficient and accurate bearing fault diagnosis and prognostics are crucial for predictive maintenance in industrial settings. Deep learning approaches have significantly advanced the field of time series classification, bringing powerful models to the forefront of prognostic and health management. Despite these advancements, current methods, including conventional Transformer models, encounter specific limitations with computational efficiency and the effective processing of long sequences. Addressing these challenges, our research presents an optimized Transformer-based model tailored for surmounting these hurdles, enhancing efficiency and ensuring high performance. By eschewing the traditional decoder in favor of an encoder-only architecture, our model capitalizes on the encoder’s ability to distill contextual information from sensor data. Enhanced with random convolutional kernel transform (ROCKET) for its exceptional feature extraction in time sequences and refined through principal component analysis (PCA) for dimensionality reduction, the proposed approach significantly boosts model efficiency, markedly trimming training duration, while achieving an exemplary accuracy of 99.10% on the benchmark bearing dataset. The proven efficiency and outstanding performance of our model hold significant promise for real-time predictive maintenance, offering a powerful tool for prompt and accurate fault detection.
An Improved Method for Job Shop Scheduling by Means of Machine Learning and Mathematical Optimization
Authors: Morinaga Eiji , Oda Atsuya 
Published: August 2024

Abstract
This paper is concerned with solving a job shop scheduling problem (JSSP) optimally in a shorter time by predicting a good solution based on a database of scheduling performed previously and then providing it as an initial solution in the optimization algorithm. Although several methods based on this framework have been developed, they have a problem that a considerable time is required for building learners. For reduction of learning time, an improved method using multiclass classification is provided in this paper. By numerical evaluation, it was shown that the learners in the proposed method can be built in a considerably shorter time than the previous method when the same hyperparameters are used. But, from the point of view of solution time, a clear advantage could not be confirmed. Further investigation considering accuracy of the learners and appropriate settings of hyperparameters will be performed in a future work.
A Recurrent Neural Network Enhanced Unscented Kalman Filter for Human Motion Prediction
Authors: Liu Wansong , Tian Sibo , Hu Boyi , Liang Xiao , Zheng Minghui 
Published: August 2024

Abstract
This paper presents a deep learning enhanced adaptive unscented Kalman filter (UKF) for predicting human arm motion in the context of manufacturing. Unlike previous network-based methods that solely rely on captured human motion data, which is represented as bone vectors in this paper, we incorporate a human arm dynamic model into the motion prediction algorithm and use the UKF to iteratively forecast human arm motions. Specifically, a Lagrangian-mechanics-based physical model is employed to correlate arm motions with associated muscle forces. Then a Recurrent Neural Network (RNN) is integrated into the framework to predict future muscle forces, which are transferred back to future arm motions based on the dynamic model. Given the absence of measurement data for future human motions that can be input into the UKF to update the state, we integrate another RNN to directly predict human future motions and treat the prediction as surrogate measurement data fed into the UKF. A noteworthy aspect of this study involves the quantification of uncertainties associated with both the data-driven and physical models in one unified framework. These quantified uncertainties are used to dynamically adapt the measurement and process noises of the UKF over time. This adaption, driven by the uncertainties of the RNN models, addresses inaccuracies stemming from the data-driven model and mitigates discrepancies between the assumed and true physical models, ultimately enhancing the accuracy and robustness of our predictions. One unique point of our method is that it integrates a dynamic model of human arms and two RNN models, and uses Monte Carlo dropout sampling to quantify the uncertainties inherent in our RNN prediction models and transforms them into the covariances of the UKF’s measurement and process noises respectively. Compared to the traditional RNN-based prediction, our method demonstrates improved accuracy and robustness in extensive experimental validations of various types of human motions.
Digital Fringe Projection for Interlayer Print Defect Characterization in Directed Energy Deposition
Authors: Hu Guanzhong , Zha Rujing , Wang Yaoke , Cao Jian , Guo Ping 
Published: August 2024

Abstract
Directed Energy Deposition (DED) is one of the main additive manufacturing (AM) families, enabling the fabrication of multi-material parts with high material addition rates. However, the incremental nature of DED fabrication makes it prone to local defect formation due to process condition fluctuations. Known for its rapid and precise 3D surface measurement capabilities, digital fringe projection (DFP) was previously demonstrated in process monitoring for powder bed AM. This study brings DFP to the DED process through development of a custom motor stage system and validates its effectiveness in assessing surface topography and build height measurement. Measurements were taken on both correctly deposited builds and builds with off-nominal deposition conditions, where the system was able to detect pitting as small as 0.425 mm in the lateral size and 0.154 mm in depth in the case of reduced laser energy. This work paves the way for future machine learning-enabled interlayer defect identification, classification, and healing via altering subsequent processing settings.
New Damaeidae (Acari, Oribatida) from Ethiopia
Authors: Ermilov Sergey G. , Kolesnikov Vasiliy , Rybalov Leonid 
Published: August 2024

Two new species of oribatid mites (Oribatida) of the family Damaeidae are described, based on adults collected from litter in the wet highland locality in Bale Mountains National Park, southeastern Ethiopia. Coronabelba adiscidialis Ermilov & Kolesnikov sp. nov. differs from the other species of the genus by larger body size, long, rod-like bothridial seta, truncated interlamellar seta, the location of dorsal notogastral setae on the slightly developed tubercles, the presence of 10 setae on leg femur I, and the absence of discidium. Metabelbella baleensis Ermilov & Kolesnikov sp. nov. differs from the other species of the genus by the larger body size, comparatively large tubercle-like parastigmatic tubercle Sa shifted in the epimeral region, and the presence of long, straight thorn-like dorsal notogastral setae. Identification keys to the known species of Coronabelba and Metabelbella are provided.
ВПЛИВ ДИСТАНЦІЙНОГО НАВЧАННЯ ПІД ЧАС СУВОРИХ КАРАНТИННИХ ОБМЕЖЕНЬ НА САМООЦІНКУ СТАНУ ЗДОРОВ’Я СТУДЕНТСЬКОЮ МОЛОДДЮ
Authors: Лепканич А. О. 
Published: August 2024

Мета: вивчити оцінку впливу дистанційного навчання під час суворих карантинних обмежень в умовах епідемії COVID-19 на загальний стан свого здоров’я студентською молоддю.
Матеріали і методи. Використано метод спеціального соціологічного дослідження, метод структурно-фунціонального, системного аналізу та епідеміологічний. У соціологічному дослідженні використано онлайн-опитувальник «Інтернет-залученість» із використанням сервісу Google-форми. Цільова група дослідження – студенти Ужгородського національного університету денної форми навчання.
Результати. Отримано 523 заповнені опитувальники респондентів, серед яких переважну більшість склали жінки (353 особи, що склало 67,5 % респондентів). У дослідженні взяли участь здобувачі освіти всіх курсів навчання. 328 респондентів ((62,7±2,1) %) вважають, що не відчувають негативного впливу на стан здоров’я під час дистанційного навчання, 195 осіб ((37,3±4,5) % опитаних) вказали, що відчувають негативний вплив. Серед тих респондентів, які відмітили негативний вплив на стан власного здоров’я дистанційного навчання, найбільша частка у групі студентів із високим рівнем залученості до щоденного перебування в мережі «Інтернет» (7 і більше годин на добу) – (45,1±3,3) % опитаних даної групи. Застосування визначення співвідношення шансів (OR) у групах дослідження показали, що погіршення стану здоров’я під час дистанційного навчання, відмічене респондентами, може бути пов’язано з впливом вказаного фактора і роль його є значимою (AF 43,8–44,4 %).
Висновки. Хоча переважна більшість студентської молоді не відзначає, що дистанційне навчання в періоди карантинних обмежень негативно впливає на стан їх здоров’я, серед тих респондентів, які відмітили негативний вплив на стан власного здоров’я дистанційного навчання, найбільша частка таких у групі студентів із високим рівнем залученості до щоденного перебування в мережі «Інтернет» (7 і більше годин на добу). Погіршення стану здоров’я під час дистанційного навчання, відмічене респондентами, може бути пов’язано з впливом вказаних факторів, і роль цих факторів є значимою.
ПСИХІАТРИЧНЕ ВІДДІЛЕННЯ У БАГАТОПРОФІЛЬНІЙ ЛІКАРНІ: ДОСВІД СТВОРЕННЯ ТА ПОТРЕБА ДЛЯ СУЧАСНОЇ СИСТЕМИ ОХОРОНИ ЗДОРОВ’Я УКРАЇНИ
Authors: Березюк О. Р. , Самчук О. О. , Фільц О. О. , Гутор Т. Г. , Самсонова Л. О. , Євченко Ю. О. , Костецький М. С. 
Published: August 2024

Мета: аналіз перших результатів роботи новоствореного спеціалізованого лікувально-консультативного психіатричного відділення у складі багатопрофільної лікарні у місті Львові.
Матеріали і методи. У роботі проведено пошук та аналіз сучасної релевантної літератури з питань надання стаціонарної психіатричної допомоги в загальних ЗОЗ у світі з використанням бібліосемантичного методу. Оцінено роботу психіатричного відділення за представленими даними ЛСП КНП 1 ТМО Львова за вересень 2021 – червень 2022 рр. із застосуванням структурно-логічного методу.
Результати. Показано існуючі переваги надання стаціонарної психіатричної допомоги населенню у психіатричному відділенні в структурі БЛІЛ ІІ рівня на прикладі психіатричного відділення багатопрофільної лікарні Львова. Встановлено, що значну частину контингенту цього відділення складають пацієнти, переведені за встановленими консультативними показами «in situ» з інших відділень лікарні. Такі пацієнти виявляють ознаки не лише органічних психічних розладів, а й додаткових патопластичних розладів психіки, пов’язаних з перебігом і лікуванням важких соматичних захворювань.
Висновки. Інтеграція служби охорони ментального здоров’я в систему загальної охорони здоров’я може суттєво сприяти зменшенню стигматизації, оптимізації забезпечення потреб та розширенню функціональних можливостей лікарів-психіатрів, а також підвищити ймовірність раннього виявлення психічних розладів у хворих із психосоматичними симптомами, які звертаються в загальну лікувальну мережу з іншими проблемами.