Miracle-dz/UniFAR-FTUs huggingface dataset:
Organizational Culture Influence On Total Productive Maintenance (TPM) and Operational Performance Using RASCH Model Analysis

Market globalization, competitive product and services, high economic crises are the most critical factors that influence the success of the manufacturing companies in global market.Therefore it is critical to the manufacturing companies to be efficient in production and lean tool may used to achieve that.The most frequently used is the Total Productive Maintenance (TPM), even though there are many studies have been conducted in relation to the TPM but there is limited research in investigating the effects of the TPM on operational performance.However, the result of the studies was not consistent, where TPM practice may have positive and negative impact on operational performance. Among the reason is the culture of the organization that influenced the implementation of TPM and operational performance.Due to that this study attempts to investigate the influence of organizational culture on the TPM implementation and operational performance. Rasch model is used in this study due to its ability in interpreting and analyzing the ability of respondents in performing the difficult items.The online questionnaires were distributed to 63 randomly selected automotive companies located at Northern Region of Malaysia.Results of the study revealed that the organizational culture has influenced on the successful implementation of TPM and operational performance.Therefore by the implementation of TPM in outstanding organizational culture can improve operational performance.
Low‐coverage reduced representation sequencing reveals subtle within‐island genetic structure in Aldabra giant tortoises

Aldabrachelys gigantea (Aldabra giant tortoise) is one of only two giant tortoise species left in the world and survives as a single wild population of over 100,000 individuals on Aldabra Atoll, Seychelles. Despite this large current population size, the species faces an uncertain future because of its extremely restricted distribution range and high vulnerability to the projected consequences of climate change. Captive-bred A. gigantea are increasingly used in rewilding programs across the region, where they are introduced to replace extinct giant tortoises in an attempt to functionally resurrect degraded island ecosystems. However, there has been little consideration of the current levels of genetic variation and differentiation within and among the islands on Aldabra. As previous microsatellite studies were inconclusive, we combined low-coverage and double digest restriction associated DNA (ddRAD) sequencing to analyze samples from 33 tortoises (11 from each main island). Using 5,426 variant sites within the tortoise genome, we detected patterns of population structure within two of the three studied islands, but no differentiation between the islands. These unexpected results highlight the importance of using genome-wide genetic markers to capture higher-resolution genetic structure to inform future management plans, even in a seemingly panmictic population. We show that low-coverage ddRAD sequencing provides an affordable alternative approach to conservation genomic projects of non-model species with large genomes.
A Deep Learning Architecture for Semantic Segmentation of Radar Sounder Data

During the last decades, radar sounders provided direct measurements (radargrams) of the Earth’s polar caps’ subsurface. Radargrams are of critical importance for a better understanding of glaciologic structures and processes of the ice sheet in the framework of climate change. This article aims to automatically extract information on basal boundary conditions given their substantial relevance for modeling the ice-sheet processes, such as the sliding. We introduce a novel automatic method based on deep learning to detect the basal layer and basal units in radargrams acquired in the inland of icy areas. Radargrams are segmented into englacial layers, bedrock, basal units, and noise-limited regions; the latter includes the echo-free zone (EFZ), thermal noise, and signal perturbation. The network is a U-Net with attention gates and the Atrous Spatial Pyramid Pooling (ASPP) module that automatically extract semantically meaningful features at different scales. Experimental results on two datasets acquired in north Greenland and west Antarctica by the Multichannel Coherent Radar Depth Sounder (MCoRDS3) indicate a high overall segmentation accuracy. The accuracy of basal ice and signal perturbation detection is high, and that of the other classes is comparable with the literature techniques based on handcrafted features. The results show the effectiveness of the proposed method in automatically extracting semantically meaningful features to segment radargrams and map the basal layer and basal units.
Mantle Electrical Conductivity and the Magnetic Field at the Core–Mantle Boundary

The Earth’s magnetic field is measured on and above the crust, while the turbulent dynamo in the outer core produces magnetic field values at the core–mantle boundary (CMB). The connection between the two sets of values is usually assumed to be independent of the electrical conductivity in the mantle. However, the turbulent magnetofluid in the Earth’s outer core produces a time-varying magnetic field that must induce currents in the lower mantle as it emerges, since the mantle is observed to be electrically conductive. Here, we develop a model to assess the possible effects of mantle electrical conductivity on the magnetic field values at the CMB. This model uses a new method for mapping the geomagnetic field from the Earth’s surface to the CMB. Since numerical and theoretical results suggest that the turbulent magnetic field in the outer core as it approaches the CMB is mostly parallel to this boundary, we assume that this property exists and set the normal component of the model magnetic field to zero at the CMB. This leads to a modification of the Mauersberger–Lowes spectrum at the CMB so that it is no longer flat, i.e., the modified spectrum depends on mantle conductance. We examined several cases in which mantle conductance ranges from low to high in order to gauge how CMB magnetic field strength and mantle ohmic heat generation may vary.
Research on Technology of Gas Pipeline Leakage Detection Based on Infrasonic Wave

In the field of natural gas pipeline leak detection, based on infrasonic wave method of gas pipeline leak detection technology gradually be taken seriously. This paper introduces the basic features of pipeline leak signals and basic principles of infrasonic wave leak detection technology. It analyzes the key factors, which affect accurate positioning. According to the characteristics of leak signal and performance requirements of leakage monitoring system, the infrasonic wave speed algorithm in gas pipeline is modified. Using correlation analysis and wavelet transform method on the leakage signals, the dynamic response time diversity between sensors installed in first and last stop will be more precise. As a result, it improves the positioning precision of leak detection effectively.
Piloting an Eight-Session Attentional Skills Training (AST) Program for Elementary School Children: Incorporating Mindfulness Concepts and Video Gaming Activities

ABSTRACT This pilot study explored the impact of an eight-session attentional skills training (AST) program for elementary-age school children. Twenty-four students, 3rd through 6th grade, participated in guidance sessions involving exposure to mindfulness exercises and video gaming activities designed to challenge visual attention, memory, and decision-making in engaging and entertaining motivational contexts. Multivariate analyses revealed that students realized a 40–50% increase in their performance on two standardized measures of time sensitive visual decision-making search tasks at the end of the AST intervention, although there were no significant changes in student reports of their mindful attitudes and parent reports of their child’s cognitive functioning. This study adds to literature on the benefits of focused interventions on attentional skills that support executive functioning of children in classroom settings.
Vector Doppler: spatial sampling analysis and presentation techniques for real-time systems

The aim of the vector Doppler (VD) technique is the quantitative reconstruction of a velocity field independently of the ultrasonic probe axis to flow angle. In particular vector Doppler is interesting for studying vascular pathologies related to complex blood flow conditions. Clinical applications require a real-time operating mode and the capability to perform Doppler measurements over a defined volume. The combination of these two characteristics produces a real-time vector velocity map. In previous works the authors investigated the theory of pulsed wave (PW) vector Doppler and developed an experimental system capable of producing off-line 3D vector velocity maps. Afterwards, for producing dynamic velocity vector maps, we realized a new 2D vector Doppler system based on a modified commercial echograph. The measurement and presentation of a vector velocity field requires a correct spatial sampling that must satisfy the Shannon criterion. In this work we tackled this problem, establishing a relationship between sampling steps and scanning system characteristics. Another problem posed by the vector Doppler technique is the data representation in real-time that should be easy to interpret for the physician. With this in mine we attempted a multimedia solution that uses both interpolated images and sound to represent the information of the measured vector velocity map. These presentation techniques were experimented for real-time scanning on flow phantoms and preliminary measurements in vivo on a human carotid artery.
The Endothelin Receptor Antagonist Macitentan Inhibits Human Cytomegalovirus Infection

Human cytomegalovirus (HCMV) infection is an important cause of morbidity and mortality in immunocompromised patients and a major etiological factor for congenital birth defects in newborns. Ganciclovir and its pro-drug valganciclovir are the preferred drugs in use today for prophylaxis and treatment of viremic patients. Due to long treatment times, patients are at risk for developing viral resistance to ganciclovir and to other drugs with a similar mechanism of action. We earlier found that the endothelin receptor B (ETBR) is upregulated during HCMV infection and that it plays an important role in the life cycle of this virus. Here, we tested the hypothesis that ETBR blockade could be used in the treatment of HCMV infection. As HCMV infection is specific to humans, we tested our hypothesis in human cell types that are relevant for HCMV pathogenesis; i.e., endothelial cells, epithelial cells and fibroblasts. We infected these cells with HCMV and treated them with the ETBR specific antagonist BQ788 or ETR antagonists that are approved by the FDA for treatment of pulmonary hypertension; macitentan, its metabolite ACT-132577, bosentan and ambrisentan, and as an anti-viral control, we used ganciclovir or letermovir. At concentrations expected to be relevant in vivo, macitentan, ACT-132577 and BQ788 effectively inhibited productive infection of HCMV. Of importance, macitentan also inhibited productive infection of a ganciclovir-resistant HCMV isolate. Our results suggest that binding or signaling through ETBR is crucial for viral replication, and that selected ETBR blockers inhibit HCMV infection.
Towards a Mobile Gait Analysis for Patients with a Spinal Cord Injury: A Robust Algorithm Validated for Slow Walking Speeds

Spinal cord injury (SCI) patients suffer from diverse gait deficits depending on the severity of their injury. Gait assessments can objectively track the progress during rehabilitation and support clinical decision making, but a comprehensive gait analysis requires far more complex setups and time-consuming protocols that are not feasible in the daily clinical routine. As using inertial sensors for mobile gait analysis has started to gain ground, this work aimed to develop a sensor-based gait analysis for the specific population of SCI patients that measures the spatio-temporal parameters of typical gait laboratories for day-to-day clinical applications. The proposed algorithm uses shank-mounted inertial sensors and personalized thresholds to detect steps and gait events according to the individual gait profiles. The method was validated in nine SCI patients and 17 healthy controls walking on an instrumented treadmill while wearing reflective markers for motion capture used as a gold standard. The sensor-based algorithm (i) performed similarly well for the two cohorts and (ii) is robust enough to cover the diverse gait deficits of SCI patients, from slow (0.3 m/s) to preferred walking speeds.
Collaborative Recommendation based on Implication Field

Recently, recommender systems has grown rapidly in both quantity and quality and has attracted many studies aimed at improving their quality. Especially, collaborative filtering techniques based on rule mining model combined with statistical implication analysis (SIA) technique also achieved some interesting results. This has shown the potential of SIA to improve the performance of recommender systems. However, it is still not rich and there are several problems to be solved for better results such as the problem of non-binary data processing, dealing with bottleneck case of data partitioning method according to the number of transactions on the very sparse transaction sets during training and testing the model, and not paying attention to exploiting the trend of variation of statistical implication. In order to contribute to solving these problems, the paper focuses on proposing a new data partitioning method, and developing the recommendation model based on equipotential planes mining generated by variation of implication intensity or implication index in the implication field on both binary and non-binary data to improve the recommendations further. Experimental results have shown the success of this new approach through its quality comparison with collaborative filtering recommendation models as well as existing SIA-based ones. Keywords—Implication intensity; implication rules; implication field; equipotential surface
Development of an Integrity Evaluation System on the Basis of Cooperative Virtual Reality Environment for Reactor Pressure Vessel

Since early 1950’s, the fracture mechanics has brought significant impact on structural integrity assessment in a wide range of industries such as power, transportation, civil and petrochemical industries, especially in nuclear power plant industries. For the last two decades, significant efforts have been devoted in developing defect assessment procedures, and as a result, various fitness-for-purpose or fitness-for-service codes have been developed. From another aspect, recent advances in IT (Information Technologies) bring rapid changes in various engineering fields. IT enables people to share information through network and thus provides concurrent working environment without limitations of locations. For this reason, a network system based on internet or intranet bas been appeared in various fields of business. Evaluating the integrity of critical components is one of the most critical issues in the nuclear industry. In order to evaluate the integrity of structures, a complicated and collaborative procedure is required including periodical in-service inspection, fracture mechanics analysis, etc. And thus, experts in different fields have to cooperate to resolve the integrity problem. In this paper, an integrity evaluation system on the basis of cooperative virtual reality environment for reactor pressure vessel which adopts IT into a structural integrity evaluation procedure for reactor pressure vessel is introduced. The proposed system uses virtual reality (VR) technique, virtual network computing (VNC) and knowledge based programs. This system is able to support 3-dimensional virtual reality environment and provide experts to co-operate each other by accessing related data through internet. The proposed system is expected to provide a more efficient integrity evaluation for reactor pressure vessel
Experimental and Analytical Investigation on a Liquid Balance Ring for Automatic Washing Machines

A high-speed camera and a Particle Image Velocimetry (PIV) technique are used on a transparent liquid balancing device typical of modern washing machines. Experimental results indicate that the baffles placed inside the ring cavity interact with the fluid for it to develop modes of vibration of circumferential and axial type, thus rendering a complex swirl flow inside the annular cavity comprised of two inertial waves. One of such waves travels backwards relative to the rigid body motion. As as a result, a damping effect is induced and a phase lag with respect to the exciting unbalance occurs. An analytical dynamic model of the unbalanced response is derived and correlated with fluid flow visualization experiments and vibration measurements.Copyright © 2010 by ASME
Development of an industrial CO2 laser with more than 40-kW output power: recent results

Results of power scaling experiments on high power CO2 lasers for industrial applications are given. Rf-excited systems with fast axial gas flow and fast gas flow in an annular discharge gap (coaxial flow) are compared. A resonator for coaxial lasers delivering a beam with high focusability is described.
Delivery of User Intentionality between Computer and Wearable for Proximity-based Bilateral Authentication

Recent research discovers that delivering user intentionality for authentication resolves a random authentication problem in a proximity-based authentication. However, they still have limitations – energy issue, inaccurate data consistency, and vulnerability to shoulder surfing. To resolve them, this paper proposes a new method for user intent delivery and a new proximity-based bilateral authentication system by adopting it. The proposed system designs a protocol for authentication to reduce energy consumption in a powerconstrained wearable, applies a Needleman-Wunsch algorithm to the matching of time values as well, and introduces randomness to a user behavior that a user must perform for authentication. We developed a prototype of our authentication system on which a list of experiments was conducted. Experimental results show that the proposed method results in more accurate data consistency than conventional methods for user authentication intent delivery. Eventually, our system reduces authentication failure rate by 66.7% compared to conventional ones. Keywords—Security; authentication; internet of things; user intentionality; proximity-based authentication; bilateral
A finite-element static analysis of smart turbine blades

Piezoelectric materials are becoming increasingly popular in the emerging field of adaptive structures. In particular, active control of wings and helicopter rotors using these materials is being pursued currently. The present work is an effort at modeling piezoelectric actuated blades for turbomachinery applications. A laminated general quadrilateral shell finite element with eight nodes and curved edges is developed for this purpose. the mathematical formulation of the element is described. Experiments have been conducted on a commercially available piezoceramic bimorph. Our finite-element and experimental results are shown to match very well. The laminated element developed is then used to perform a static analysis of typical turbomachinery blades. Effects of the angle of pre-twisting and aspect ratio have been studied. PVDF and PZT piezoelectric materials have been compared.
Aeroelastic Considerations on Shape Control of an Adaptive Wing

In this work, the aeroelastic effects on the shape control of an adaptive camber wing are studied through numerical simulation. The adaptive camber concept consists of a compliant beam, actuated by a series of piezoelectric actuators, embedded within the rib to deform the wing in an effort to produce a desired lift. Piezoelectric laminated plate theory is used to model the actuation force and the resulting camber line shape of the wing. The aerodynamic forces are calculated using two-dimensional airfoil theory and a feedback shape control algorithm is applied to obtain the desired camber. The results of the simulations demonstrate that the deformations due to aerodynamic forces are large enough to significantly alter the total lift produced by the wing as compared with the lift produced solely through actuation. Using an adaptive control algorithm, aeroelastic shape control of the adaptive camber wing is successfully achieved. Moreover, it is shown that, due to aerodynamic forces, the power requirements of shape control might be reduced.
Two-dimensional simulation of local oxidation of silicon: calibrated viscoelastic flow analysis

Local Oxidation of Silicon (LOCOS) remains the common isolation technology for mass-production of integrated circuits. The work reported in this paper contributes to the improvement of the numerical modeling of the LOCOS process. A physical two-dimensional (2-D) modeling of the thermal oxidation of silicon has been developed based on the explicit treatment of the reaction expansion. The originality of this modeling is to propose a general solution taking into account of the silicon deformation, incorporating the viscoelastic behaviour of oxide and nitride and, particularly, giving a complete calibration of the stress-dependent parameters. The prediction capabilities are demonstrated by the calculations of oxide shapes and oxidation-induced stresses in a silicon substrate for very advanced isolation techniques.
Chitosan mitigates the adverse effects and improves photosynthetic activity in rice (Oryza sativa L.) seedlings under drought condition

ABSTRACT The ability of chitosan to promote rice growth, physiological traits, and photosynthetic performance in rice seedlings under drought stress was investigated. Rice seedlings (Oryza sativa L. cv. KDML105) were treated with 100 mg l−1 low and high molecular weight (MW) chitosan via a combination of seed priming and foliar spray. The seedlings were subjected to drought stress by withholding water for 4 days, which resulted in the U-shaped (scale 5) leaf rolling. The results showed that drought significantly decreased shoot and root growth. Chitosan application, particularly with high MW chitosan, improved shoot and root growth under drought stress. Chitosan treatment also alleviated the effects of drought stress by elevating relative water content, as well as reducing electrolyte leakage and malondialdehyde content. Antioxidant enzyme activities, including guaiacol peroxidase (GPX) and ascorbate peroxidase (APX), were increased in response to chitosan. Additionally, treating the plant with chitosan improved photosynthetic efficiency as evidenced by increased CO2 response, the maximum rate of Rubisco carboxylase activity (Vcmax), and photosynthetic rate. We conclude that the exogenous application of chitosan aids the plant in coping with the severity of drought stress. While both low and high MW chitosans were effective at alleviating the effect of drought on rice seedlings, high MW chitosan might have a slight advantage with respect to increased effective duration.