Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of Quality Indicators of Iron Ore Processing Operations Using Deep Neural Networks

Taking into consideration the development of computing power and algorithms to process big data, machine learning technologies are more widely used to solve production tasks. In this paper, our aim is to develop a prediction system that allows to show the possible trend of the processing of iron ore concentrate in real time. Currently, the operator controls the quality of final product on the basis of laboratory analysis results. They are made in a discrete way every 2 hours. But such period of time is much longer than the time, which is needed by ore to get through the process line from start to finish. Therefore, setpoints values of the process state variables are chosen by the operator conservatively, having a negative scenario in mind. But that results in decrease of the energy efficiency of the technological process.Complexity of development of such system lies in the fact that the given stage of production is a discretely continuous distributed process. It includes many technological objects, the functioning of which cannot be approximated by linear dependencies. Also there is an unsteadiness of properties of incoming raw materials, which causes changes in characteristics of the working equipment. For approximation of complex dependencies, which are curves of technological indexes, the authors have used the multilayer artificial neural networks. It allowed to obtain high quality of modeling. However, it has been revealed that such method of modeling of functioning dynamics of objects leads to negative effect - occurrence of autocorrelation, negatively affecting the predictive properties of the model. In order to avoid such a phenomenon, we studied the application of deep neural networks. It allowed to obtain the prediction results, which meet the requirements of technology and without the autocorrelation effect. It leaded to increase of the stability of the models of technological units.
Techniques Improving the Robustness of Deep Learning Models for Industrial Sound Analysis

The field of Industrial Sound Analysis (ISA) aims to automatically identify faults in production machinery or manufactured goods by analyzing audio signals. Publications in this field have shown that the surface condition of metal balls and different types of bulk materials (screws, nuts, etc.) sliding down a tube can be classified with a high accuracy using audio signals and deep neural networks. However, these systems suffer from domain shift, or dataset bias, due to minor changes in the recording setup which may easily happen in real-world production lines. This paper aims at finding methods to increase robustness of existing detection systems to domain shift, ideally without the need to record new data or retrain the models. Through five experiments, we implement a convolutional neural network (CNN) for two publicly available ISA datasets and evaluate transfer learning, data normalization and data augmentation as approaches to deal with domain shift. Our results show that while supervised methods with additional labeled data are the best approach, an unsupervised method that implements data augmentation with adaptive normalization is able to improve the performance by a large margin without the need of retraining neural networks.
Efficiency of TV-regularized algorithms in computed tomography with Poisson-Gaussian noise

Regularized algorithms are the state-of-the-art in computed tomography, but they are also very demanding in computer resources. In this work we test two data-fidelity formulations and some associated algorithms for the resolution of the Total-Variation regularized tomographic problem. We compare their computational cost for a mixture of Poisson and Gaussian noises. We show that a recently proposed MAP-EM algorithm outperforms the TV-regularized SIRT and the Chambolle-Pock algorithms on synthetic data for the considered noise. We illustrate this result on experimental data from transmission electron microscopy.
The 5G MEC Applications in Smart Manufacturing

We introduce the first pre-commercial 5G MEC deployment upon which applications are redesigned and implemented handling real smart manufacturing tasks. We propose a 5G MEC system architecture composed of two decoupled domains, and reorganized the service structure for applications based on that architecture. By deploying the applications in the real industrial environment, the functionality and performance have been validated.
Service Load Prediction based on User Knowledge Level Evolution for Software Development Knowledge Base

When using the microservice architecture to build a software development knowledge base, due to the differences in the user's knowledge level, different users have different needs for knowledge, which causes the problem of unpredictable system load. This paper proposes a load prediction model based on User Knowledge Level Evolution (UKLE). We use user historical access data and user private data to build user portraits, learn the evolution law of user knowledge levels, and thus describe the diverse knowledge growth paths of users. Finally, we predict the future knowledge access trends of users. And we use a hybrid prediction model based on linear and non-linear methods to perform load prediction for service load. The final load prediction model combines the characteristics of user knowledge level evolution and a hybrid prediction model based on service historical load, which improves the model's prediction accuracy and robustness.
Optimal Scheduling Scheme for Urban Crowdsourcing Distribution Task Based on Path Planning

At present, in the “last mile” urban crowdsourcing distribution process, there are shortcomings such as unreasonable task assignment and unclear distribution path planning, which reduce the distribution efficiency and waste a lot of manpower and time. Aiming at these problems, this paper proposes a task scheduling scheme and mathematically models it. The optimization goal is to minimize the total distribution path length when all tasks are assigned. A variable neighborhood search algorithm (VNS) is designed, four neighborhood operations are constructed, and a selection probability is set for every neighborhood operation to reduce the solution time of the algorithm. In addition, a heuristic solving algorithm (HSA) is implemented as a comparison. The experimental results show that VNS has a higher solution quality in solving the urban crowdsourcing distribution task scheduling problem, and VNS can improve the scheduling efficiency of the urban crowdsourcing task.
Construction of Health Index for Aircraft Air-conditioning System Health Prediction

Constructing a reasonable health index(HI) to evaluate the health status of industrial equipment is the key to equipment fault prediction and health management. Nowadays, data-driven HI construction methods have been widely used. However, these methods usually require a large number of sample data and data for the whole life cycle. To solve this problem, in this paper, we propose a method to create a mapping between working condition parameters and fault parameters and then transform working condition parameters to the same specified working condition. We regard the transformed fault parameters as HI, then health status of future flights can be predicted by recurrent neural network(RNN) in terms of the constructed HI. The experimental results show that this method can effectively indicate and predict the health status of the aircraft air-conditionina system (ACS).
Experimental Validation of Bias in Checkerboard Corner Detection

The sub-pixel corner refinement algorithm in OpenCV is widely used to refine checkerboard corner location estimates to sub-pixel precision. This paper shows using both simulations and a large dataset of real images that the algorithm produces estimates with significant bias and noise which depend on the sub-pixel corner location. In the real images, the noise ranged from around 0.013 px at the pixel centre to 0.0072 px at the edges, a difference of around $1.8\times$. The bias could not be determined from the real images due to residual lens distortion; in the simulated images it had a maximum magnitude of 0.043 px.
Simultaneous Spline Quantile Regression Under Shape Constraints

As data analysis methods, hypothesis testing and regression analysis are famous. However, the hypothesis testing can only detect significant differences between two groups divided by some characteristic or some empirical threshold, and the regression analysis can only construct one averaged model whose information is limited. Quantile regression is a robust and flexible analysis method, and can construct multilevel models, e.g., the median and the first and third quartiles. To make the most of the quantile regression, existing papers employed spline regression models as generalizations of polynomial regression models, but the regression of each level was individually executed. In this paper, we propose simultaneous spline quantile regression which considers the similarity between the adjacent quantiles. Further, the proposed method enforces the non-crossing and one shape (non-decreasing/non-increasing/convex/concave) constraints. Experiments demonstrate that the proposed method recovers harmonious quantiles.
Manipulation of surface properties: the use of nanomembrane as a nanometre-thick decal

Precise control of surfaces and interfaces is essential for the fabrication of various functional materials. Although various methods have been applied to the functionalization of surfaces, these methods are specialized for the fabrication of specific surfaces for specific purpose. In this context, a versatile, yet efficient tool for the surface manipulation is strongly desired. Here, we demonstrate a simple method of functionalizing various surfaces through a decal-like transfer of a giant nanomembrane. Control of wettability was chosen as an example, and a hydrophobic nanomembrane was transferred to various other substrates, including Si, polymer film, and metal. A drastic change in contact angle clearly indicated that the wettability of the processed material was identical to that of the surface-functionalized nanomembrane. In contrast, other physical properties such as the mechanical properties of the processed material remain unchanged. The decal-like transfer of nanomembrane will become a powerful means for the fabrication of unique functional surfaces.
Benign fibrous histiocytoma of the maxilla: A rare case report and literature review

Benign fibrous histiocytoma (FH) is a benign soft-tissue tumor that can present as a fibrous tissue mass anywhere in the body. The involvement of the paranasal sinuses is extremely rare, and very few cases have been reported in literature till date. We here report a case of benign FH localized in the maxillary sinus. The clinical and histological features of the lesion are discussed with a brief literature review of this pathology in the paranasal sinuses.
Formation of a Self-Assembled Monolayer of Diaminododecane and a Heteropolyacid Monolayer on the ITO Surface

The formation of SAMs on oxides and semiconductor surfaces has become a significant issue recently in its various technological applications. We report an easy and convenient method for the tailoring of an ITO surface with an amine functional group. A dense self-assembled monolayer of 1,12-diaminododecane was formed on the ITO surface. The long alkyl chain amine was observed for the first time to form a stable self-assembled monolayer. The amine group in diaminododecane was found to have good affinity for the ITO material. The diamine functionality of diaminododecane was utilized for the preparation of another layer of heteropolyacid on the SAM/ITO surface.
Effects of gasoline engine emissions on health status of auto rickshaw drivers at DIR (L) Khyber Pukhtunkhwa

A total of 50 blood samples were collected from auto rickshaw drivers who were exposed to environmental gasoline in different sites of Dir (L), Khyber Pukhtunkhwa, Pakistan, in July and August, 2009. Control group was selected among the individuals who were not regularly exposed to gasoline emissions. The samples were analyzed for calcium, cholesterol, glucose, phosphorus, potassium, and triglycerides levels. A significant increase was found in the blood levels of calcium, glucose, phosphorus, and triglycerides. A significant decrease was detected in the blood levels of potassium without any significant effect on the blood levels of cholesterol and magnesium.
Ventricular Septal Defect: Echocardiography Evaluation

Ventricular septal defects (VSDs) are among the most common congenital heart defects. These defects may be isolated, associated with other defects, or occur as an intrinsic component of some complex heart defects. There is wide variation in size and location of VSD. Echocardiography plays an important role in evaluation of anatomy, hemodynamic significance, and planning of management of VSDs. With the emerging trends in transcatheter closure of VSD, echocardiography plays a crucial role in decision-making and intra- and postprocedure evaluation. A stepwise approach of echocardiography is necessary for accurate evaluation and management of VSDs.
A History of Antidementic Drug Development in Japan

Objective: Japan is the top runner in the world in society aging, in which the number of patients with Alzheimer's disease has significantly increased and still keeps increasing. Many countries and societies are still struggling with people with dementia and the burden related to the high number of the elderly. In this study, both authors have been involved with research works on elucidating the pathological process of Alzheimer's disease and developing antidementic drugs for more than 30 years. Methods: Based on lifetime professional experiences in basic research and clinical work as well as our own contribution in the areas of expertise, we describe in this review the changes of the number of dementia patients and the concept of dementia, as well as the development of antidementic drugs in Japan. Results: In this review, we define the super-aged society first. Historical concept changes in Alzheimer's disease, perspectives of research on Alzheimer's disease and drug development, history of antidementic drug developments (for nootropics and drugs for improving brain metabolism and circulation, development of symptom-modifying drugs; hormones, neurotrophic factors, etc.; acetylcholinergic drugs; and glutamatergic drugs), and development of disease-modifying drugs (with amyloid cascade hypothesis, nonsteroidal anti-inflammatory drugs, and amyloid vaccine) have been outlined as review sections. Finally, we devote discussion in two review sections – failure of new drugs and development from the existing drugs as well as development of preemptive medicine. Conclusion: We hope that the whole society, including the elderly with and without cognitive decline, can resolve this issue in the near future.
Chemical Constituents of the Essential Oil of Otostegia michauxii Briq. From Iran

Abstract The essential oil of Otostegia michauxii Briq. growing wild in the Fars province of Iran was obtained by hydrodistallation and analyzed by GC and GC/MS techniques. Forty-five components representing 97.9% of the total oil were identified. The main components of the oil were dillapiole (23.9%), 2-methylbenzofuran (12.9%) and α-pinene (8.1%).
Social ties of individuals in psychic distress: contributions for psychiatric nursing

Objetivo: comprender la formacion de vinculos sociales de los individuos en sufrimiento psicologico residentes de Servicio Residencial Terapeutico. Metodo: un estudio cualitativo del tipo estudio de caso caracterizado como observacional. Se utilizo la tecnica de la observacion-participante de un residente de Caxias do Sul. El analisis de datos fue por el metodo de asignacion. El proyecto de investigacion fue aprobado por el Comite de Etica en la Investigacion, Opinion no. 073/2009. Resultados: se entiende que los lazos entre los residentes y sus afectos estaban rotas y debilitados por las duras certezas de modo de asilo, que se separaron, ya sea por control o culpar a la enfermedad. Conclusion: los lazos sociales de los residentes, de este servicio-casa, se pueden fortalecer a traves de este equipo de salud mental
Adsorption behaviors of lead ion onto acetate modified activated carbon fiber

Activated carbon fiber (ACF) was modified with acetates of sodium, potassium and lithium at concentration of 15% and tested to adsorb lead from aqueous solution. The effect of acetate treatments of ACF was studied in adsorption behavior of lead ion. Acetate treatment reduced surface area and pore volume of ACF, but the adsorption amount of lead ion on the modified ACF (MACF) was greater than that on the pristine ACF. The adsorbed lead could be fully desorbed by using 0.01 mol/L HNO3 solution. The maximum adsorption capacity of lead ion on acetate lithium modified ACF was 165.1 mg/g and the adsorption isotherm follows Langmuir isotherm model better than the Freundlich isotherm model. The adsorption kinetic data could be described well by the Lagergren pseudo-second-order kinetic equation.
GROWING CAPACITY OF DIFFERENT THALLUS STRUCTURE AND SIZE OF Parmotrema tinctorum LICHEN ON ARTIFICIAL SUBSTRATES

Lichen regenerates by spore discharging and germination of broken thallus. The latter is more efficient because both the algae and fungi are together at symbiosis stage, whereas the former needs to wait for compatible algae. However, different part of thallus has dissimilar capacity to grow. It was hypothesized that large lichen thallus has higher growth rate than the small ones, and complete lobe tip has the highest growth rate. The objectives of this study were to observe 1) effect of thallus size on growth and 2) growing capacity of different parts of thallus. The study was performed by transplantation thallus fragments of P. tinctorum on nylon meshes in secondary forest at KYNP. Twenty fragments of small thalli with diameter less than 3.8 cm and ten larger thalli were attached on nylon meshes. In addition, 30 different parts of thalli consisted of complete lobe tip, without lobe tip and isidia lobe were transplanted. Twelve months after transplantation, the small thalli had higher growth rate than the large ones accounting for 0.93 and 0.76 mm/month, respectively. Thallus fragment with complete lobe tip had the highest growth rate of 1.04 mm/month, which was significantly higher than those without lobe tip and with isidia, which accounting for 0.64 and 0.42 mm/month, respectively, after transplantation for 6 months. The complete thalli with lobe tips consisted of active growing zone of lichen, which enhance thallus growth. However we anticipated that the transplanted thalli without lobe tip and those with isidia would grow better and have larger biomass production in the future because some new lobules germinate from these thalli. However, time frame required for this establishment is not known, and it needs a long term investigation. Introduction: Thailand is situated in tropical region, where high biodiversity and luxurious lichen flora could be found. Record in 2009 showed that the country hosted 1,692 species consisting of 450 species of new records and 150 taxa. Lichens have high potential to be utilized for dyes and several applications because of their unique chemical products. The lichen Parmotrema tinctorum (Despr. ex Nayl.) Hale is a foliose macrolichen which is widely distributed in all types of forests in Thailand. This lichen had high growth rate compared with other species and has a potential to be used in pharmacy, agriculture and environment. It has been used as a bioindicator for air pollution This lichen would be in great demand in the future because of its prospective uses. Therefore, the increased biomass production of this lichen is necessary for sustainable utilization and conservation. The objectives of this study were to observe 1) effect of thallus size on growth and 2) growing capacity of different parts of thallus. It was hypothesized that large lichen thallus has higher growth rate than the small ones, and complete lobe tip has the highest growth rate.
Scaling laws for parallel motor-gearbox arrangements

Research towards (compliant) actuators, especially redundant ones like the Series Parallel Elastic Actuator (SPEA), has led to the development of drive trains, which have demonstrated to increase efficiency, torque-to-mass-ratio, power-to-mass ratio, etc. In the field of robotics such drive trains can be implemented, enabling technological improvements like safe, adaptable and energy-efficient robots. The choice of the used motor and transmission system, as well as the compliant elements composing the drive train, are highly dependent of the application and more specifically on the allowable weight and size. In order to optimally design an actuator adapted to the desired characteristics and the available space, scaling laws governing the specific actuator can simplify and enhance the reliability of the design process. Although scaling laws of electric motors and links are known, none have been investigated for a complete redundant drive train. The present study proposes to fill this gap by providing scaling laws for electric motors in combination with their transmission system. These laws are extended towards parallelization, i.e. replacing one big motor with gearbox by several smaller ones in parallel. The results of this study show that the torque/mass ratio for a motor-gearbox can not be increased by parallelization, but that it can increase the torque/volume ratio. This is however only the case if a good topology is chosen.
Performance of an n-type organic field-effect transistor prepared with fluorinated copper phthalocyanine (F16CuPc) as an organic semiconductor and polycarbonate as a gate insulating material

The structural and transport properties of evaporated fluorinated copper phthalocyanine organic field effect transistors with polymer dielectric layer polycarbonate were reported. A high field effect mobility of 5.7×10-3 cm2/ Vs, an on/off ratio of 104 and a threshold voltage of 5V were obtained under atmospheric conditions. χ-ray diffraction and atomic force microscopy show a clear correlation between the morphology and structure of F16CuPc film on the polycarbonate dielectric surface. Temperature dependent measurements of the mobility were performed. X-ray diffraction results show that the crystallinity and orientation of F16CuPc on polycarbonate thin film are enhanced with increasing surface temperature.