Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperated Traffic Shaping with Traffic Estimation and Path Reallocation to Mitigate Microbursts in IoT Backhaul Network

An aggregating switch (SW) network offers cost-effective accommodation to Internet-of-Things (IoT) traffic by aggregating the traffic. In such a network, it is crucial to eliminate the discarded traffic caused by the simultaneous transmission of massive IoT devices, namely microburst. Traffic shaping is a technique of storing traffic in one SW to mitigate microbursts. Conventional traffic shaping is limited because only one SW performs shaping with a limited queue length. Thus, we propose cooperated traffic shaping using multiple SWs to accommodate more traffic. We formulated equations to derive the minimum queue length with shaping rates which gradually decrease in geometric progression. To acquire the queue length using general SWs without short-cycle monitoring, we propose a scheme for estimating the instantaneous input rate and data size of microburst traffic required for our equations. If the calculated queue length cannot be prepared in the current path, we propose reallocating the path to another one with more SWs. We experimentally demonstrated the proposed coordinated traffic shaping technique by implementing it in commercial SWs with 125 emulated IoT devices. The results showed that the difference between the experimental and numerical results was below 4.2%, and the queue length can be reduced by 40% when there are three SWs. In addition, a path with two SWs was successfully reallocated to one with three SWs.
Classifying Multivariate Signals in Rolling Bearing Fault Detection Using Adaptive Wide-Kernel CNNs

With the developments in improved computation power and the vast amount of (automatic) data collection, industry has become more data-driven. These data-driven approaches for monitoring processes and machinery require different modeling methods focusing on automated learning and deployment. In this context, deep learning provides possibilities for industrial diagnostics to achieve improved performance and efficiency. These deep learning applications can be used to automatically extract features during training, eliminating time-consuming feature engineering and prior understanding of sophisticated (signal) processing techniques. This paper extends on previous work, introducing one-dimensional (1D) CNN architectures that utilize an adaptive wide-kernel layer to improve classification of multivariate signals, e.g., time series classification in fault detection and condition monitoring context. We used multiple prominent benchmark datasets for rolling bearing fault detection to determine the performance of the proposed wide-kernel CNN architectures in different settings. For example, distinctive experimental conditions were tested with deviating amounts of training data. We shed light on the performance of these models compared to traditional machine learning applications and explain different approaches to handle multivariate signals with deep learning. Our proposed models show promising results for classifying different fault conditions of rolling bearing elements and their respective machine condition, while using a fairly straightforward 1D CNN architecture with minimal data preprocessing. Thus, using a 1D CNN with an adaptive wide-kernel layer seems well-suited for fault detection and condition monitoring. In addition, this paper clearly indicates the high potential performance of deep learning compared to traditional machine learning, particularly in complex multivariate and multi-class classification tasks.
Platinum Crosslinked Carbon Dot@TiO2- x p-n Junctions for Relapse-Free Sonodynamic Tumor Eradication via High-Yield ROS and GSH Depletion.

Sonodynamic therapy as a promising noninvasive modality is being developed for tumor therapy, but there is a lack of next-generation sonosensitizers that can generate full ROS at high yields and simultaneously deplete elevated levels of glutathione (GSH) in tumor cells. Semiconductor p-n junctions are engineered as high-efficacy sonosensitizers for sonodynamic tumor eradication using pyridine N-doped carbon dots (N-CDs) as a p-type semiconductor and oxygen-deficient TiO2- x nanosheets as a n-type semiconductor. The rate constants of 1 O2 and •OH generation by ultrasound-excited N-CD@TiO2- x p-n junctions are 4.3 and 4.5 times higher than those of TiO2 , respectively. A Z-scheme carrier migration mechanism in the p-n junction achieving the rapid spatial separation of the ultrasound-generated electron-hole pairs for enhanced full ROS production is proposed. GSH-cleavable, Pt-crosslinked, N-doped CD fluorescent probes to detect the presence of intracellular GSH are also constructed. A GSH-responsive, p-n junction platform (Pt/N-CD@TiO2- x ) with integrated GSH detection, GSH depletion, and enhanced sonodynamic performance is then assembled. Malignant tumors are completely eradicated without relapse via intravenous administration of low-dose Pt/N-CD@TiO2- x under ultrasound irradiation. This work substantiates the great potential of biocompatible, GSH-responsive p-n junctions as next-generation sonosensitizers via p-n junction-enhanced ROS generation and metal ion oxidation of intracellular GSH.
Predicting and Measuring Surface Enlargement in Forward Rod Extrusion

Surface enlargement during bulk metal forming processes is one of the key parameters controlling the tribology at the tool-workpiece interface. Not only the surface roughness evolution but also the integrity of the lubricant layer critically reposes on surface enlargement. As an attempt to address this issue, in the first part of this work, a general, deformation gradient based surface enlargement description is implemented in a commercial finite element program. In the second part, forward rod extrusion tests with different area reductions are conducted using customized steel workpieces in which cylindrical copper rods are embedded through the depth. By sectioning the extruded parts and by identifying the position of the copper rods on the lateral surface, average surface enlargement values could be measured locally at different positions along the extrudate. Comparison of experiments and numerical predictions reveal that the deformation gradient based description performs reasonably well in capturing surface enlargement profiles both qualitatively and quantitatively. [DOI: 10.1115/1.4032261]
Comparative Characterization of Eastern Carrot Accessions for Some Main Agricultural Traits

Background: Unevaluated open-pollinated germplasm represents a promising source of variability to face the problems of worldwide food production under a changing environment. In carrots, this is particularly true for black carrot accessions, which are the most relevant among Eastern carrot germplasm due to their high anthocyanin content and, concomitantly, antioxidant capacity. Methods: In the present work, a comparative characterization was conducted for the first time on 11 Eastern carrot landraces and Night Bird ‘F1′ as the reference cultivar, grown under glasshouse conditions at temperatures up to 33° C. Results: Some landraces showed their potential for ulterior evaluation in terms of plant and taproot size, plant compactness, specific leaf area and leaf area ratio, among other traits. The highest anthocyanin and flavonoid contents were found in the reference cultivar, whereas remarkable differences in these variables were observed for the rest of accessions, which in turn may correlate with very distinct coloration patterns. Premature bolting and taproot shape abnormalities were also recorded. Mineral composition analysis showed the nutritional potential of Eastern carrot leaves, which displayed higher concentration than taproot tissue for several macro- and micronutrients. Moreover, several accessions had higher nutrient concentrations than the reference cultivar, which also highlights their profitability. Conclusions: This work contributes to the knowledge on Eastern black carrot germplasm by characterizing some of its main agricultural traits, and opens up the prospect for complementary evaluation on high-yield accessions.
The Effect of Coronavirus Stress on Job Burnout in Nurses with the Moderating Role of Psychological Capital

Corresponding Author Fariborz Fathi Chegeni PhD Student, Department of Management, Faculty of Management and Economics, Lorestan University, Khorramabad, Iran Email: arifth@gmail.com Background and Objectives: The nursing profession is basically stressful in nature. In the meantime, the spread of the coronavirus and its rapid spread throughout the country has caused the over-normal influx of patients infected with this virus to hospitals and increased nurses' work stress. Therefore, the aim of this study was to investigate the effect of Coronavirus Stress on Job burnout in nurses with the moderating role of psychological capital in Khorramabad Shohadaye Ashayer Hospital, Iran.
Thyristor controlled two-stage magnetic-valve reactor for dynamic VAr-compensation in electric railway power supply systems

The electrification of railway systems is becoming more prevalent throughout the world. The implementation of adjustable speed drives in conjunction with the mobile nature of the trains presents a case where harmonic content varies with time and location along the power supply. Advanced systems implement power factor correction on the rail car system. Existing systems require expensive conversions to accomplish this. A variable saturable reactor is presented here that provides a more economical approach to add power factor correction to existing rail systems. The system includes structure modifications to limit hysteresis and skin effect losses. A 27.5 kV, 2400 kVA system is constructed and tested to confirm the operation of the system.
Underwater Glider System Study

The goals of this study are to determine how to advance from present capabilities of underwater glider (and hybrid motorglider) technology to what could be possible within the next few years; and to identify critical research issues that must be resolved to make such advancements possible. These goals were pursued by merging archival flight data with numerical model results and system spreadsheet analysis to extrapolate from the present state-of-the–art in underwater (UW) gliders to potential future technology levels. Using existing underwater gliders (legacy gliders) as calibration, this merger approach was applied to six basic glider types that were conceived to satisfy the requirements of five functional classes. Functional classes were posed based on an evaluation of the attributes and limitations of underwater gliders in the context of a broad range of potential Navy needs in the littoral and deep-water regimes. Those functional classes included: Depth- Unlimited Roaming; Depth-Limited Roaming; Virtual Station Keeping; Payload Delivery; Level-Flight Hybrids.
E-Commerce in Singapore and Indonesia: Comparison of Policies

New media is a term that refers to products and services that provide information/entertainment using computers or the internet. The emergence of new media also encourages other activities that people usually do in a conventional way to the cyber world. Doing business is one example. Electronic commerce, or also known as e-commerce, is a trading method that uses the internet. Nowadays, e-commerce has become a trend in the world. Comprehensive regulations are needed to manage this activity. This paper will try to describe a comparative public policy on e-commerce in the two ASEAN countries, Singapore and Indonesia. We will see differences in e-commerce development in both countries, and attention to the role of governments as decision-makers in both countries.
Subsumption architecture control system for space proximity maneuvering

An approach to adding autonomy to a teleoperated robotic system designed for on-orbit proximity operations is discussed. In particular, a control system for performing a highly automated approach-to-dock proximity operation is described which has been developed using the subsumption architecture. The control system has been built by successively adding layers of continuously operating autonomy to a teleoperated system in which human operator control is treated as a level of autonomy exactly like the machine levels. The result is a control system evolution that smoothly allows the addition of levels of competence to ease the operator''s control burden. The operation of the control system is demonstrated using a simulation of the orbital environment and two spacecraft.
Experimental sound exposure modifies swimming activities and increases food handling error in adult zebrafish

Anthropogenic noise is increasing globally and is recognized as a source of environmental pollution in terrestrial and aquatic habitats. Sound is an important sensory stimulus for aquatic organisms and it may alter stress-related physiological indices and induce broad behavioural effects in a range of marine and freshwater fishes. Specifically, sound exposure may induce changes in swimming activities, feed efficiency and spatial distribution changes in fish. Here, we experimentally tested sound effects on swimming activities and foraging performance in thirty individually housed, captive adult Zebrafish (Danio rerio). Adult zebrafish and water fleas (Daphnia magna) were used as model predator and prey species, respectively. Acoustic stimuli consisted of four sound treatments with different temporal patterns. All had the same frequency range and were administered on average 121 dB re 1 µPa2/Hz. Our results constitute strong evidence for sound-related effects on zebrafish behaviour. All sound treatments led to a significant increase in the number of startle responses, and the brief and prolonged swimming speed for zebrafish. We found sound effects on the spatial distribution of zebrafish; Although there were no significant sound-related changes for horizontal spatial displacement in all treatments, zebrafish swam significantly more in the lower layer of the tank except during the irregular intermittent 1:1-7 in brief sound exposure treatment. The results of foraging performance showed that food discrimination error was unaffected by sound treatments and was low for the zebrafish. However, food handling error was affected by sound treatments; all treatments induced a significant rise in handling error. This study highlights the impact of sound on zebrafish swimming activities, and that more feeding bouts are needed to consume the same number of food items increasing energy demand under noisy conditions.
Aging changes the interactions between the oculomotor and memory systems

ABSTRACT The use of multi-modal approaches, particularly in conjunction with multivariate analytic techniques, can enrich models of cognition, brain function, and how they change with age. Recently, multivariate approaches have been applied to the study of eye movements in a manner akin to that of neural activity (i.e., pattern similarity). Here, we review the literature regarding multi-modal and/or multivariate approaches, with specific reference to the use of eyetracking to characterize age-related changes in memory. By applying multi-modal and multivariate approaches to the study of aging, research has shown that aging is characterized by moment-to-moment alterations in the amount and pattern of visual exploration, and by extension, alterations in the activity and function of the hippocampus and broader medial temporal lobe (MTL). These methodological advances suggest that age-related declines in the integrity of the memory system has consequences for oculomotor behavior in the moment, in a reciprocal fashion. Age-related changes in hippocampal and MTL structure and function may lead to an increase in, and change in the patterns of, visual exploration in an effort to upregulate the encoding of information. However, such visual exploration patterns may be non-optimal and actually reduce the amount and/or type of incoming information that is bound into a lasting memory representation. This research indicates that age-related cognitive impairments are considerably broader in scope than previously realized.
Reconocimiento e interpretación: dos fases en el análisis de la ironía verbal

This paper is part of a larger research that aims to achieve a clear and consistent pragmatic characterisation of verbal irony. Critical review of the preceding approaches has shown their failure to define this phenomenon. Nevertheless, the irony as relevant innappropriateness theory (Attardo, 2000) and the speech act analysis of irony (Haverkate, 1985) have been identified as potentially valid to explain how irony is recognised and understood, respectively. What we present here are the most significant results obtained after confronting these theories with the samples of an oral corpus of ironies in Spanish produced by us. The analysis has allowed us to corroborate the suitability of its basis, in addition to raising new assumptions about what type of contextual information activates the recognition and what other modes of interpretation of the ironic statement can occur apart from the prototypical one consisting of a contrary meaning. KeywoRds: verbal irony; pragmatic characterisation; recognition; understanding; corpus. sUmmARy:
Analysis of a Hand Geometry-Based Verification System

Hand and finger geometry recognition is the process of identifying an individual through the unique "geometry" (shape, thickness, length, width, etc.) of that individual's hand. Hand geometry recognition systems can be used in several different types of applications, including access control and time and attendance tracking, while time and attendance tracking can be used for security . Biometric systems are widely used for access control, and can be used on various types of assets, including entryways, computers. This paper explores the use of hand geometry as a measure of a person's identity. The system consists of an acquisition devi ce that captures the top view and side view of a user's right hand as he places it on the flat surface of the device. This paper presents an overview of hand geometry system, the benefits and its integration.
Robust Face Recognition from NIR Dataset via Sparse Representation

A biometric identification system may be a pc application for mechanically distinctive or confirmative of an individual from a digital image or a video frame from a video supply. One in all the ways that to try and do this can be by examination designated face expression from the image and a facial information. This paper planned dynamic face recognition from near-infrared images by exploitation sparse representation classifier. Most of the prevailing datasets for facial expressions are captured in a very visible light spectrum. However, the visible light (VIS) will modify with time and placement, causing important variations in look and texture. This new framework was designed to attain strength to pose variation and occlusion and to resolve uncontrolled environmental illumination for reliable biometric identification. This paper gift a unique analysis on a dynamic facial features recognition, exploitation near-infrared (NIR) datasets and LBP(Local binary patterns) feature descriptors. It shows sensible and strong results against illumination variations by exploitation infrared imaging system.
An investigation into the effect of traffic and tillage on soil properties and crop yields

Abstract. Agricultural production systems are increasingly characterised by extensive in-field trafficking of larger and heavier field machinery. The random nature of trafficking, covering 80-90% of the field area, that is characteristic of commercial practice, inevitably leads to negative impacts on soil, water and crop characteristics because of degraded soil structures, impeded root development, yield losses, water infiltration and pollution. Remedial action requires energy, time and cost. The future development of a sustainable agricultural sector needs to balance an increase in production whilst protecting the environment. Emerging technologies and engineering solutions have stimulated a recent shift towards reduced tillage methods and coupled with the development of traffic management systems, aided by Precision Agriculture (PA), aim to reduce the severity of compaction on cropped areas whilst improving efficiency and sustainability. Low Ground Pressure (LGP) systems can facilitate random trafficking and are often used to access fields during wet conditions whilst minimising the negative effects of field traffic. Alternatively, Controlled Traffic Farming (CTF) which is used predominantly in Australia confines field traffic to permanent wheel-ways and significantly reduces the total area trafficked to circa. 30% depending on working widths used. A multidisciplinary long-term project established at Harper Adams University (UK) in October 2011 is investigating the interaction between traffic and tillage on soil, crop and energy responses in a randomised and replicated study to determine the effects of Random Traffic Farming (RTF), Controlled Traffic Farming (CTF) and Low Ground Pressure (LGP) systems with Deep, Shallow and Zero Tillage. The aim of this study is to develop an integrated mechanisation system to optimise soil and water resources, crop growth, yields, system performance and economics in commercial agricultural practice.
Coexistence of fast-scale and slow-scale instability in CUK power factor correction AC-DC pre-regulators under non-linear current-mode control

Power factor correction (PFC) converters using conventional control strategies have been reported tremendously as exhibiting slow- and fast-scale bifurcations. This study investigates the fast-scale and slow-scale instabilities in a PFC CUK converter under non-linear carrier (NLC) control, which is proved advantageous compared with other conventional control strategies. It is found that the fundamental periodic orbit loses its stability via period-doubling bifurcation and later bifurcates to chaos. Bifurcation studies of NLC controlled higher-order converters have not been reported so far in literature. Computer simulations as well as experimental investigations are performed to study the qualitative behaviour of the system under variations of different parameters. It is found that both the fast- and slow-scale instabilities may cause distortion in the line current and degrade the supply power factor. The results offer useful information of parameter space for the design and operation of the converter in the desired fundamental stable regime.
Two-stage classication ofrespiratory sound patterns

The classication problem ofrespiratory sound signals has been addressed by taking into account their cyclic nature, and a novel hierarchical decision fusion scheme based on the cooperation of classiers has been developed. Respiratory signals from three di4erent classes are partitioned into segments, which are later joined to form six di4erent phases of the respiration cycle. Multilayer perceptron classiers classify the parameterized segments from each phase and decision vectors obtained from di4erent phases are combined using a nonlinear decision combination function to form anal decision on each subject. Furthermore a new regularization scheme is applied to the data to stabilize training and consultation. 2003 Elsevier Ltd. All rights reserved.