Miracle-dz/UniFAR-FTUs huggingface dataset:
Cell adhesion strength and tractions are mechano-diagnostic features of cellular invasiveness

The adhesion of cells to substrates occurs via integrin clustering and binding to the actin cytoskeleton. Oncogenes modify anchorage-dependent mechanisms in cells during cancer progression. Fluid shear devices provide a label-free, non-invasive way to characterize cell-substrate interactions and heterogeneities in the cell populations. We quantified the critical adhesion strengths of MCF7, MDAMB-231, A549, HPL1D, HeLa, and NIH3T3 cells using a custom fluid shear device. The detachment response was sigmoidal for each cell type. A549 and MDAMB-231 cells had significantly lower adhesion strengths at τ50 than their non-invasive counterparts, HPL1D and MCF7. Detachment dynamics was inversely correlated with cell invasion potentials. A theoretical model, based on τ50 values and the distribution of cell areas on substrates, provided good fits to data from de-adhesion experiments. Quantification of cell tractions, using the Reg-FTTC method on 10 kPa polyacrylamide gels, showed highest values for invasive, MDAMB-231 and A549, cells compared to non-invasive cells. Immunofluorescence studies show differences in vinculin distributions: non-invasive cells have distinct vinculin puncta, whereas invasive cells have more dispersed distributions. The cytoskeleton in non-invasive cells was devoid of well-developed stress fibers, and had thicker cortical actin bundles in the boundary. These correlations in adhesion strengths with cell invasiveness, demonstrated here, may be useful in cancer diagnostics and other pathologies featuring misregulation in adhesion.
Principles for Designing Effective and Efficient Training of Complex Cognitive Skills

This chapter describes principles for the design of training of complex cognitive tasks that pose relatively great challenges to the cognitive capacity of the trainee. Using the theoretical framework of cognitive load, we argue that the structures that constitute human cognitive architecture need to be taken into account in the design of effective and efficient training. For training complex cognitive tasks, this means that cognitive load needs to be controlled by optimizing the relationship between (a) the intrinsic load imposed by the complexity of the training task and (b) the effective (germane) and ineffective (extraneous) loads imposed by the design of the training tasks. Design principles for training tasks, for sequences of training tasks in fixed training programs (in which all trainees receive the same sequence), and for ways to create adaptive or personalized training programs (in which each trainee receives a personalized sequence) are discussed. Simple to complex sequencing of training tasks,.
Oak Ridge National Laboratory Annual Progress Report for the Electric Drive Technologies Program

Executive Summary Almost all hybrid electric vehicle (HEV) and electric vehicle (EV) motors (machines) use permanent magnets (PMs) with rare earth (RE) materials such as neodymium and dysprosium because they facilitate the achievement of high power densities, specific powers, and efficiencies. However, there has been significant market volatility associated with RE materials in recent years, including a price increase in dysprosium by a factor of 40 within 1 year. Therefore, alternatives to RE PM motors are of very high interest to original equipment manufacturers and suppliers and will continue to be, particularly as vehicles become more electrified and uses for RE materials in other applications expand in the future. Achieving competitive performance and efficiency with alternative motor technologies having comparable mass, volume, voltage, and other key metrics requires a highly advanced multidiscipline research approach including high accuracy modeling; the research, use, and development of soft and hard magnetic materials; and comprehensive nonlinear computational optimization of geometric features and winding parameters.
Cultural Maintenance in the Face of Language Shift- Young Sindhi Muslims in Karachi, Pakistan

The Sindhi language, a descendent of a pre-Vedic Prakit language is the most widely spoken language in South Asia. Sindhi speech community comprises both Muslims, and Hindus which have distinct cultural and religious practices, yet they are socially connected because of the geographical link with their land. However, due to the partitioning of the Indian sub-continent, many Sindhi Hindus migrated to India, Malaysia, Singapore, Indonesia, the United Kingdom, Hong Kong, and many other countries. There has not only been an external diaspora but within Pakistan, there has also been an internal diaspora of younger Sindhi Muslims who have moved to cities like Karachi, Hyderabad, and Sukkur to pursue tertiary education. These young speakers have acquired and learned the dominant languages Urdu and English as their second and third languages while shifting away from their native Sindhi language. This study investigates the identity markers which have enabled them to retain their Sindhiness[1]. Semi-structured interviews were conducted with 20 male and female young Sindhis and shadow observation of three participants in Karachi. The analysis shows that young Sindhi speakers have a high sense of group solidarity with their community and retain the use of culturally loaded identity markers which include naming patterns, cuisine, dressing, music, customs, rituals, social values, and networking. According to Fishman (1996), there is a deep relationship between language and culture. Despite a shift away from the habitual use of the Sindhi language these respondents have maintained their cultural values and norms. Keywords: cultural maintenance, language shift, Sindhi community, Karachi
Studi Mekanisme Injeksi Surfaktan-Polimer pada Reservoir Berlapis Lapangan NR Menggunakan Simulasi Reservoir

The rapid oil industry growth, the increasing needs of fossil fuel, the decreasing and becoming more difficult oil discovery, and the decreasing production from the getting-old assets cause the industry to apply alternative production methods. The most common method to decide on has been applying enhanced oil recovery (EOR) technique. One of the most applied EOR methods these days is the surfactant-polymer injection. This injection process extremely depends on reservoir flow characteristics i.e. rock heterogeneity and fluid-rock interaction. Therefore, it is necessary to conduct a particular study to understand the mechanism of the injection. This can be done using a reservoir simulator. The study was carried out through a comparative analyses of 4 (four) types of injection namely water injection, polymer injection, surfactant injection, and surfactant-polymer injection. It was found that the water injection was no longer optimal since the water cut has reached a value as high as 98%. The polymer injection could sweep the oil contained in low-permeability zones of about 4% from the previous oil saturation. The surfactant injection could reduce the oil saturation (ROS) of about 5% from the previous oil saturation in high-permeability zones. The surfactant-polymer injection could sweep the oil contained in both high and low permeability zones that the residual oil saturation after waterflood (SORW) and ROS reach the values of 7% and 11% from the previous oil saturation, respectively. Thus, the surfactant-polymer injection was considered as the most suitable EOR technique to apply at NR Field. Keywords: Enhanced Oil Recovery, residual oil saturation, heterogenity, surfactant, polymer, stratified reservoirs.
Intermodulation Distortion in GaN HEMT

This work treats intermodulation distortion performance of GaN-HEMT high-power transistors. A detailed study on the physical parameters influencing third-order intermodulation distortions is carried out, based on the large-signal model and on physical device simulation. Devices are characterized in terms of linearity by setting up a sophisticated measurement system. Among others, an electronic fuse is used at the drain side to avoid catastrophic failure during measurement. The bias-dependent transconductance characteristic is identified as the dominating source for intermodulation distortion in GaN HEMTs, while drain-source capacitance and access resistances have only minor influence. The corresponding physical parameters governing the transconductance behavior are determined and optimized structures for high linearity are proposed. Besides characterization and analysis of conventional designs, a novel device architecture for very high linearity is presented. Finally, performance of GaN HEMTs within a hybrid amplifier configuration is shown and the combination of high power, high linearity, and low-noise characteristics is highlighted.
High School Students’ Use of Digital General Resources During Lockdown

There is not a large body of literature about digital resources found and accessed autonomously by high school students while studying mathematics, whereas this topic has become more and more relevant in times of lockdown due to the pandemic. Italy has been one of the first countries facing lockdown for an extended time, making this country a paradigmatic example: in this paper we investigate what kind of digital resources are accessed by the Italians high school students who actually use them and why. According to our results, students’ aims and expectations vary according to the school grade, but are not as much devoted to procedural learning as previous literature has shown. Also, we observe that the type of searched media (text, video, image, etc.) is related to the mathematical contents and to students’ objectives. © 2022 by the authors;licensee EJSME.
Prediction of Fuel Consumption of Agricultural Tractors

A mathematical model was developed to predict fuel consumption of agricultural tractors using their official OECD tractor test data. It was found from the data analysis that the fuel consumption at varying load with full throttle is proportional to engine power, and the difference in fuel consumptions at varying load with full and reduced throttles is equal regardless of engine power if their speed difference is the same. The model developed based on this assumption can predict the fuel consumption under any operational conditions. The model was validated by comparing the predicted and measured fuel consumptions of the selected four tractor models tested by the OECD test code. The percentage errors of the predicted fuel consumptions ranged from 0.11% to 4.67% at varying load with full throttle at standard PTO speed and from 1.36% to 9.15% at partial load with reduced throttle. Although the prediction model needs further improvement, the method developed in this study may be used to estimate reasonably the fuel consumptions of a given tractor under various operational conditions.
Human Factors Assessment of International Space Station (ISS) Medical Equipment Packs

A human factors assessment was performed on several International Space Station (ISS) medical packs to evaluate the organization of items and provide recommendations for redesign. The overall goal was to recommend solutions that will improve the efficiency of identifying and locating items in the medical packs, thereby, potentially increasing the survival rate of crewmembers in the event of a medical emergency. Currently, each ISS crew remains on-orbit for six-month intervals. As there is not a standing requirement for a physician crewmember, the maintenance of crew health is dependant on individual crewmembers delivering care via telemedicine and their own limited training. In addition, medical procedures must be carried out within the limitations imposed by the unique physical environment of the space station. Given these challenges, the procedures and equipment designed to aid the crewmember in delivering that care should follow human-centered design principles in order to be as easy and simple to use as possible. The evaluation revealed six main categories of issues: Labeling, Location/Collocation of items, Clear Presentation of Information, Error Prevention, Stowage, and Equipment Design. Recommendations for each category are provided, and should be considered for efficiency and effectiveness in any medical environment.
A ROBUST DEEP LEARNING APPROACH TO ENHANCE THE ACCURACY OF POMEGRANATE FRUIT DISEASE DETECTION UNDER REAL FIELD CONDITION

Pomegranate fruits are infected by various diseases and pests, which negatively affect food security, productivity, and quality. Recent advancements in deep learning with Convolutional Neural Networks (CNNs) have significantly improved the accuracy of fruit disease detection and classification. The main objective of this investigation is to find the most suitable deep-learning architecture to enhance fruit disease detection and classification accuracy. The current study proposed an efficient deep learning-based approach to detect the most prominent diseases of pomegranate such as bacterial blight, anthracnose, fruit spot, wilt, and fruit borer. For experimentation, a total of 1493 stagewise diseases development images of fruits and leaves are captured via a camera of an interval of 25 days for a total of six months duration. Additionally, extensive data augmentation was performed to increase the dataset, data diversity and to achieve a more robust model for disease detection. For this, the performance of three CNN-based architectures i.e., ResNet50, ResNet18, and Inception-V3 on a real field environment dataset was measured. Experimental results revealed that the proposed CNN-based ResNet50 architecture has effectively detected and classified five different types of diseases whose symptoms are not well defined and with the capability to deal with complex backgrounds. The optimized ResNet50 model achieved 97.92 % test accuracy over ResNet18 (87.5 %) and Inception-V3 (78.75 %) on learning rate 0.001. The multiclass cross-entropy loss function is applied for determining the error rate. To deal with CNN ‘Black Box’ problem Grad-CAM model can be used in the future. The proposed method will help the agricultural industry in detecting the most prominent diseases of pomegranate, which are likely to cause a decrease in productivity, thereby avoiding economic loss.
Budget participation, information asymmetry, and job insecurity as a predictor of budgetary slack

Budgetary slack occurs because of the potential difference with the revenue budget target. the difference in potential revenue with the revenue budget target indicates the occurrence of individual behavior lowering the income target to facilitate the achievement of the government budget. The purpose of this study is to empirically prove the effect of budget participation, information asymmetry, and job insecurity that trigger budgetary slack. The population of this research is officials of the Indonesian: Regional Working Unit in the province of East Java, Indonesia. The sampling technique used is proportional sampling, the research respondents were 84 people. The results show that budget participation, information asymmetry, and job insecurity have a positive effect on budgetary slack. The high budget participation of public sector employees can trigger budgetary slack. Information asymmetry motivates budget implementers to take action to reduce revenue targets and increase government spending. High job insecurity in the work environment creates pressure on employees so that budgetary slack is created.
Guided wave based structural health monitoring: A review

The paper provides a state of the art review of guided wave based structural health monitoring (SHM). First, the fundamental concepts of guided wave propagation and its implementation for SHM is explained. Following sections present the different modeling schemes adopted, developments in the area of transducers for generation, and sensing of wave, signal processing and imaging technique, statistical and machine learning schemes for feature extraction. Next, a section is presented on the recent advancements in nonlinear guided wave for SHM. This is followed by section on Rayleigh and SH waves. Next is a section on real-life implementation of guided wave for industrial problems. The paper, though briefly talks about the early development for completeness, is primarily focussed on the recent progress made in the last decade. The paper ends by discussing and highlighting the future directions and open areas of research in guided wave based SHM.
CALCULATION OF POTENTIAL DISTRIBUTION FOR ZINC-OXIDE SURGE ARRESTER BY FINITE ELEMENT METHOD

Finite element method (FEM) is applied to the calculation of potential distribution for ZnO surge arrester with open boundary. The open boundary field problem is transformed to the bounded field problem through setting artificially truncating boundary with asymptotic boundary condition. The vitual homogeneous imposed boundary is presented to deal with a great number of floating conductors in the surge arrester. The potential distributions of 330 kV and 500 kV ZnO surge arrester are calculated and measured. The numerical results show that the method is correct and efficient. Some conclusions are also concluded as follow. The potential distribution of ZnO elements tends to be uniform with the increase of mounting height. The maximum ratio of born potential will be decreased greatly in presence of equalizer ring so that the potential distribution of ZnO elements could be improved. Compared with other methods based on simulation electric charge, our method is advantageous for its simplicity,generality and sufficient utilization of existing program. It can well satisfy the demands of engineering design and application.
1200 V and 5000 A Peak Reverse Blocking Diode Thyristor

The Reverse Blocking Diode Thyristor (RBDT) is a pnpn two-terminal solid state device which is capable of blocking forward voltage until rapidly switched to a forward conducting state. This paper describes a new high power device of about one inch crystal diameter which is called the T62R RBDT and is suitable for radar modulator switching duty. Processing is described and explanation given for a unique diffusion profile, which was required to be other than a simple scaleup of a successful smaller T40R device. Capability of repetitively switching 5000 V and 5000 A is shown, while electrical power measurements are given interpretation in terms of rating utility. The presentation of actual high power switching evidence, with loss data is intended to provide firm evidence of the suitability of the T62R for modulator-type duty.
Genetic polymorphism of ALDH2 in Indonesia’s Minang ethnic

Background: In some people, acetaldehyde, a toxic product from ethanol oxidation, cannot be oxidized to acetate. The excess of acetaldehyde could cause facial flushing, dizziness, and hypertension when they consume ethanol. This ethanol sensitivity is caused by a deficiency of ALDH2. Objective: This study aims to analyze and count the polymorphism frequency of the ALDH2 gene in Indonesia’s Minang ethnic. Methods: DNA samples were taken randomly from hair bulbous of 60 subjects (male and female, 3rd generation). A nested polymerase chain reaction was conducted to amplify the ALDH2 in the samples. Afterward, restriction fragment length polymorphism (RFLP) was conducted to the amplicons using the EcoRI restriction enzyme. The measured parameters were the distribution of the wildtype, atypical homozygote, and heterozygote. Results: Results showed that out of 60 subjects, 53.33% have an atypical homozygote gene (subjects prone to hypersensitive to alcohol), 28.33% have a heterozygote gene, and 18.33% have a wildtype gene. The frequency of the atypical alleles in Minang ethnic is 0.675. Conclusion: The atypical ALDH2 allele was much higher than the normal ALDH2 allele, in which most participants have atypical homozygote ALDH2, suggesting the samples are sensitive to alcohol.
The Study of Implementation Effectiveness in the Various Criminal Law Policies During the Covid-19 Pandemic

There are various pros and cons to the criminal law policies by the Indonesian government in the context of dealing with covid 19. So it is necessary to have a study related to the effectiveness of implementing these various policies. The author's background is to discuss the formulation of the problem in this article: What is the criminal law policy during the covid 19 pandemic? And how is the effectiveness in the implementation of these policies? This article uses a normative juridical research method that examines various positive laws from the applicable laws and regulations, and then it is analyzed in analytical descriptive. The Indonesian government has established various policies to prevent the covid 19 transmission. The guidelines consist of: the formation of various legal regulations related to the covid pandemic; a policy of criminal sanctions for violators of social policies during the covid 19 pandemic; prisoner assimilation policy; electronic trial of criminal cases during the covid 19 pandemic; corruption prevention policies; policies on workplaces in public areas. Regarding the effectiveness of implementing these policies, it can be said that the execution tends to be less optimal because the policies are contrary to one another. So this article provides suggestions to the government and the community should have mutual support for the implementation of criminal law policies during the COVID-19 pandemic can be effective.
SEASONAL VARIATION OF HEAVY METAL POLLUTION OF GROUNDWATER AND SOIL IN THE M’NASRA REGION (GHARB, MOROCCO)

M’nasra region is well known for increasing levels of heavy metal pollution in the environment, mainly due to waste discharge of Ouled Berjal, the irrational use of fertilizers, and the discharge of waste from several industries. The objective of this study was to access the seasonal variations in the groundwater and soil quality with respect to heavy metal pollution. Water samples from wells and samples from soil near them were taken during wet (January - March 2017) and dry (July 2017) seasons and concentrations of Cd, Cu, Cr, Mn, Ni, Pb, and Zn were determined using an Atomic Absorption Spectrophotometer (AAS). Contamination factor for each heavy metal and Nemerow pollution index was calculated. Results of the study revealed a decrease in pollution degree from wet to dry for soil and an increase in the case of groundwater. Cu had the lowest and Ni had the highest concentration in irrigation water whereas, for soil, Cd had the lowest and Zn had the highest concentration. During the wet season, all the concentrations of heavy metals decreased compared to the dry season, this can be explained by the dilution of these concentrations by precipitation water and therefore to lower absorption of these heavy metals in the water of irrigations and/or soil. Vertical transfer of pollutants from topsoil to groundwater was assessed using Hierarchical Cluster Analysis to identify associations between heavy metals and soil texture. In the case of Ni and Cr, the variables corresponding to the concentrations from soil and groundwater were part of the same cluster, in both seasons, the distribution maps of concentrations confirmed the pattern of transfer. This study can be considered as a baseline for the seasonal variation of heavy metal pollution of groundwater and soil. This study can be used not only for monitoring the study area but also as a tool for the implementation of environmental protection policies.