Miracle-dz/UniFAR-FTUs huggingface dataset:
Dimension Measurement and Quality Control during the Finishing Process of Large-Size and High-Precision Components

The accurate measurement and control of the geometric dimensions and shape errors of large-size and high-precision key components are key factor to ensure the machining quality of the equipment package. Aiming to address the urgent problems of poor measurement conditions, complicated error propagation, and difficulty in obtaining accurate measurement results, this research studied the measurement method and control of dimensional accuracy and geometric tolerance in the process of hole machining at room temperature, taking Metso MP 1250 cone level 6 precision point pair workpiece as the object. Through linear analysis and demonstration of quality problems in the existing processing technology, the influence of the expansion coefficient of the workpiece material, measurement error and other factors is analyzed. After correcting the temperature error model, many measurements were carried out in machining experiments, and the normal ability was analyzed by Minitab software. The experimental results showed that the workpiece temperature rises by 1°C, the workpiece will be deformed by 8.503 um. In the measurement process of high-precision and large-size components, the correction accuracy of the temperature error is affected by the combined influence of the model error, the material expansion coefficient error, and the temperature measurement error. The results of this study are of guiding significance for the measurement of the dimension and geometric tolerance precision of large-size and high-precision castings.
Assessment of Mental Workload by Visual Motor Activity among Control Group and Patient Suffering from Depressive Disorder

Major depressive disorder (MDD) is a mood state that is not usually associated with vision problems. Recent research has found that the inhibitory neurotransmitter GABA levels in the occipital brain have dropped. Aim. The aim of the research is to evaluate mental workload by single channel electroencephalogram (EEG) approach through visual-motor activity and comparison of parameter among depressive disorder patient and in control group. Method. Two tests of a visual-motor task similar to reflect drawings were performed in this study to compare the visual information processing of patients with depression to that of a placebo group. The current study looks into the accuracy of monitoring cognitive burden with single-channel portable EEG equipment. Results. The alteration of frontal brain movement in reaction to fluctuations in cognitive burden stages generated through various vasomotor function was examined. By applying a computerised oculomotor activity analogous to reflector image diagram, we found that the complexity of the path to be drawn was more important than the real time required accomplishing the job in determining perceived difficulty in depressive disorder patients. The overall perceived difficulty of the exercise is positively linked with EEG activity measured from the motor cortex region at the start of every experiment test. The average rating for task completion for depression patients and in control group observed and no statistical significance association reported between rating scale and time spent on each trial (p=1.43) for control group while the normalised perceived difficulty rating had 0.512, 0.623, and 0.821 correlations with the length of the pathway, the integer of inclination in the pathway, and the time spent to complete every experiment test, respectively (p < 0.0001) among depression patients. The findings imply that alterations in comparative cognitive burden levels during an oculomotor activity considerably modify frontal EEG spectrum. Conclusion. Patients with depression perceived the optical illusion in the arrays as weaker, resulting in a little bigger disparity than individuals who were not diagnosed with depression. This discovery provided light on the prospect of adopting a user-friendly mobile EEG technology to assess mental workload in everyday life.
NEURAL NETWORKS FROM KERAS IN SKIN LESION DIAGNOSTIC

Abstract. Melanoma is currently one of the most dangerous skin diseases, in addition many others appear in the population. Scientists are developing techniques for early non-invasive skin lesions diagnosis from dermatoscopic images, for this purpose neural networks are increasingly used. Many tools are being developed to allow for faster implementation of the network, including the Keras package. The article presents selected methods of diagnosing skin diseases, including the process of classification, features selection, extracting the skin lesion from the whole image.The described methods have been implemented using deep neural networks available in the Keras package. The article draws attention to the effectiveness, specificity, accuracy of classification based on available data sets, attention was paid to tools that allow for more effective operation of algorithms.
Development and Validation of an Analytical Method for Pesticide Residues Analysis in Crude Cottonseed Oil

This study reports the development and validation of a fast, efficient, and cost effective multiresidue method for determination of 14 lipophilic and analytically problematic pesticides in crude cottonseed oil. Crude cottonseed oil contains high amount of saturated fatty acid and pigments that are problematic in pesticide residues analysis. Modified liquid-liquid partitioning with acetonitrile and n-hexane in 10:1 (v/v) ratio was used to extract pesticides. For clean-up, different combinations of sorbents were used and optimum recovery and minimal matrix effect were obtained with the combination of activated charcoal and primary secondary amine for the selected pesticides. For majority of the analyzed pesticides, the method validation parameters i.e. percent recovery (71.6-140.0%), precision (%RSD 9.7 to 33.0), LOD (0.041 to 0.096 and#181;g/g), LOQ (0.125-0.264 and#181;g/g), linearity (0.998-0.999) and matrix effect (and#177;27%) were in acceptable range as prescribed by EU SANTE guidelines. Two-way Analysis of variance of inter-labs comparison study revealed non-significant interaction effects for most of studied pesticides indicating that the current method can be confidently used in labs for monitoring of these pesticides in crude cottonseed oil.
METHODS FOR ENSURING DATA SECURITY IN MOBILE STANDARDS

The analysis of mobile communication standards is carried out, the functional structure and interfaces of interaction between the structural elements of the cellular network are considered. To understand the principle of communication according to the GSM standard, a block diagram of a mobile switching center (MSC), base station equipment (BSS), control and service center (MCC), mobile stations (MS) is presented. The main algorithms for ensuring the confidentiality and security of mobile subscribers' data, in different types of standards, as well as the vulnerabilities of information flows are considered. In particular, the following dangerous types of attacks have been identified, to which mobile network subscribers are sensitive: sniffing; leakage of personal data; leakage of geolocation data; spoofing; remote capture of SIM-card, execution of arbitrary code (RCE); denial of service (DoS). It is established that the necessary function of the mobile network is the identification of subscribers, which is performed by IMSI, which is recorded in the SIM card of the subscriber and the HLR of the operator. To protect against spoofing, the network authenticates the subscriber before starting its service. In the case of subscriber identification, the subscriber and the network operator are protected from the effects of fraudulent access. In addition, the user must be protected from eavesdropping. This is achieved by encrypting the data transmitted over the radio interface. Thus, user authentication in UMTS, as well as in the GSM network, is carried out using encryption with a common key using the "hack-response" protocol (the authenticating party sends a random number to the authenticated party, which encrypts it according to a certain algorithm using a common key and returns the result back).
Stunting Classification in Children's Measurement Data Using Machine Learning Models

The study conducted a stunting classification of measurement data for children under 5 years old. The dataset has attributes such as: gender, age, weight (BB), height (TB), weight / height (BBTB), weight / age (BBU), and height / age (TBU). The research uses the CRISP-DM methodology in processing the data. The data were tested on several classification models, namely: logistic regression (LR), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbor (KNN), classification and regression trees (CART), nave bayes (NB), support vector machine - linear kernel (SVM-Linear), support vector machine - rbf kernel (SVM-RBF), random forest classifier (RPC), adaboost (ADA), and neural network (MLPC). These models were tested on the dataset to find out the best model in accuracy. The test results show that SVM-RBF produces an accuracy of 78%. SVM-RBF has consistently been at the highest accuracy in several tests. Testing through k-fold cross validation with k=10.
Changes in the Mental Health of Children and Adolescents during the COVID-19 Lockdown: Associated Factors and Life Conditions

This study investigated the psychological impact of the coronavirus disease 2019 (COVID-19) among youth by analyzing their emotional/behavioral problems before and during the long-lasting lockdown in Spain. For that purpose, 699 parents with children aged 6–17 and 552 adolescents aged 12–17, who completed the parent and adolescent version of the Strengths and Difficulties Questionnaire at the beginning of 2019, responded to a survey from 26 May to 15 June 2020 that assessed psychological well-being and life conditions during quarantine (i.e., sociodemographic characteristics, situation before the lockdown, physical environment and accompaniment during the lockdown, COVID-related variables). According to both parent- and self-reports, children and youth experienced a significant worsening in emotional symptoms, conduct problems, hyperactivity/inattention, peer problems, and total difficulties subscales. Findings also suggested that impairment was mainly associated with variables related to the child’s situation prior to home quarantine, the quality and quantity of the child’s social networks during the lockdown, the daily routines the child followed, the concerns the child had about health, and the presence of economic and learning problems caused by the COVID-19. Thus, the present investigation emphasizes the need for carefully monitoring the mental health of younger people, provides guidance for the development of interventions that mitigate some of the psychological difficulties faced in a situation of confinement, and highlights the importance of paying special attention to high-risk groups.
Proteins Do Not Replicate, They Precipitate: Phase Transition and Loss of Function Toxicity in Amyloid Pathologies

Simple Summary Amyloid aggregation of proteins in disease has been known for over a hundred years; however, effective therapeutics for amyloid pathologies such as Alzheimer’s disease and Parkinson’s disease are still lacking. This review divides the amyloid phenomenon into four major questions: What are amyloids? How do amyloids form? Can proteins replicate? How do amyloids cause toxicity? The aim is to answer these questions within a unified physicochemical framework that links the structural biology of amyloids to the thermodynamics of amyloid formation and the pathophysiology of amyloid aggregates in different diseases. We illustrate that the thermodynamics of protein aggregation does not support the prion protein-only replication hypothesis, and how the structural biology of amyloids makes them largely domainless, generic, and inert. The implications of this understanding for the etiology, pathogenesis and potential therapeutics of amyloid diseases are briefly discussed. Abstract Protein aggregation into amyloid fibrils affects many proteins in a variety of diseases, including neurodegenerative disorders, diabetes, and cancer. Physicochemically, amyloid formation is a phase transition process, where soluble proteins are transformed into solid fibrils with the characteristic cross-β conformation responsible for their fibrillar morphology. This phase transition proceeds via an initial, rate-limiting nucleation step followed by rapid growth. Several well-defined nucleation pathways exist, including homogenous nucleation (HON), which proceeds spontaneously; heterogeneous nucleation (HEN), which is catalyzed by surfaces; and seeding via preformed nuclei. It has been hypothesized that amyloid aggregation represents a protein-only (nucleic-acid free) replication mechanism that involves transmission of structural information via conformational templating (the prion hypothesis). While the prion hypothesis still lacks mechanistic support, it is also incompatible with the fact that proteins can be induced to form amyloids in the absence of a proteinaceous species acting as a conformational template as in the case of HEN, which can be induced by lipid membranes (including viral envelopes) or polysaccharides. Additionally, while amyloids can be formed from any protein sequence and via different nucleation pathways, they invariably adopt the universal cross-β conformation; suggesting that such conformational change is a spontaneous folding event that is thermodynamically favorable under the conditions of supersaturation and phase transition and not a templated replication process. Finally, as the high stability of amyloids renders them relatively inert, toxicity in some amyloid pathologies might be more dependent on the loss of function from protein sequestration in the amyloid state rather than direct toxicity from the amyloid plaques themselves.
Systematic Characterization of bZIP Transcription Factors Required for Development and Aflatoxin Generation by High-Throughput Gene Knockout in Aspergillus flavus

The basic leucine zipper (bZIP) is an important transcription factor required for fungal development, nutrient utilization, biosynthesis of secondary metabolites, and defense against various stresses. Aspergillus flavus is a major producer of aflatoxin and an opportunistic fungus on a wide range of hosts. However, little is known about the role of most bZIP genes in A. flavus. In this study, we developed a high-throughput gene knockout method based on an Agrobacterium-mediated transformation system. Gene knockout construction by yeast recombinational cloning and screening of the null mutants by double fluorescence provides an efficient way to construct gene-deleted mutants for this multinucleate fungus. We deleted 15 bZIP genes in A. flavus. Twelve of these genes were identified and characterized in this strain for the first time. The phenotypic analysis of these mutants showed that the 15 bZIP genes play a diverse role in mycelial growth (eight genes), conidiation (13 genes), aflatoxin biosynthesis (10 genes), oxidative stress response (11 genes), cell wall stress (five genes), osmotic stress (three genes), acid and alkali stress (four genes), and virulence to kernels (nine genes). Impressively, all 15 genes were involved in the development of sclerotia, and the respective deletion mutants of five of them did not produce sclerotia. Moreover, MetR was involved in this biological process. In addition, HapX and MetR play important roles in the adaptation to excessive iron and sulfur metabolism, respectively. These studies provide comprehensive insights into the role of bZIP transcription factors in this aflatoxigenic fungus of global significance.
Factors Affecting the Global Health and Cultural Competencies of Nursing Students

Recently, various global health issues, including coronavirus disease 2019 (COVID-19), have been observed in relation to rapid changes in world health conditions; consequently, nurses’ global health and cultural knowledge have become increasingly important. Therefore, this study aimed to identify factors affecting the global health and cultural competencies of nursing students. The study design was a cross-sectional study with 108 participants; all participants were fourth-year nursing college students in S and C cities. Global health competency, cultural competency, global health confidence, cultural nursing confidence, and metacognition were surveyed online, and the data were collected from October 30 to November 7, 2018. The collected data were analyzed using descriptive statistics, independent t-test, Pearson’s correlation, and hierarchical multiple regression. The total mean scores for global health competency and the cultural nursing competency were 63.01 ± 8.78 and 134.94 ± 17.78, respectively. Global health competency had a positive correlation with cultural competency (r = 0.49, p < 0.001), cultural nursing confidence (r = 0.26, p = 0.006), and metacognition (r = 0.22, p = 0.023). Cultural competency showed a positive correlation with global health confidence (r = 0.31, p = 0.001), cultural nursing confidence (r = 0.51, p < 0.001), and metacognition (r = 0.40, p < 0.001). Cultural competency was found to be a significant factor affecting global health competency, with an explanatory power of 23.1% (F = 17.10, p < 0.001). Cultural nursing confidence and metacognition had significant effects on cultural competency, with an explanatory power of 34.3% (F = 14.97, p < 0.001). Cultural confidence and metacognition were important factors influencing cultural competency, and cultural competency was shown to be an important factor influencing global health competency.
Pengembangan Media Pembelajaran Fisika Berbasis Web Menggunakan Pendekatan Guided Discovery Learning

AbstractThe development of physics web based approach using a guided discovery learning has done on SMAK 5 Penabur at XI science class from March until May 2015. Development of the model is based on Borg & Gall with comparative descriptive data. Development of this web-based physical media is expected to assist students in understanding the substance of Physics in 2013 curriculum. After passing through the planning process, judicial review by experts of material and test media by media experts, the revision, the product tested on students are welcomed. Similarly, when disseminated to teachers. Web-based learning media is considered to overcome the limitations of the learning process and can facilitate the learners in understanding physics.Keywords: web-based, Guided Discovery Learning, development researchAbstrakPengembangan media pembelajaran fisika berbasis web menggunakan pendekatan Guided Discovery learning telah dilakukan di SMAK 5 Penabur untuk kelas XI IPA pada bulan Maret sampai Mei 2015. Pengembangan yang digunakan mengacu pada model Borg & Gall dengan data deskriptif komparatif. Pengembangan media fisika berbasis web ini diharapakan dapat membantu siswa dalam memahami substansi Fisika pada kurikulum 2013. Setelah melewatiproses perencanaan, uji materi oleh ahli materi, dan uji media oleh ahli media, revisi, produk diujicobakan pada peserta didik dengan hasil baik. Begitu pula ketika disosialisasikan ke guru se-Penabur. Media pembelajaran berbasis web dinilai dapat mengatasi keterbatasan pada proses belajar mengajar dan dapat memfasilitasi peserta didik dalam memahami materi fisika.Kata-kata kunci : Berbasis Web, Guided Discovery learning, penelitian pengembangan
Efficient CNNs and Energy Efficient SRAM Design for ubiquitous medical devices

Intermittent monitoring of urinary bladder volume aids management of common conditions such as post-operative urinary retention. Urinary retention is prevented by catheterization, an invasive procedure that greatly increases urinary tract infection. Ultrasound imaging has been used to estimate bladder volume as it is portable, non-ionizing, and low-cost. Despite this, ultrasound technology faces fundamental challenges limiting its usability for next generation wearable technologies. (1) Current systems require skilled manual scanning with attendant measurement variability. (2) Current systems are insufficiently energy-efficient to permit ubiquitous wearable device deployment. We propose to develop an energy efficient system capable of real-time bladder volume monitoring. This system will incorporate several key innovations, including (1) Convolutional Neural Network (CNN) based segmentation algorithms employed to generate spatiotemporally accurate bladder volume estimates and (2) energy efficient static random access memory (SRAM) with in-memory dotproduct computation for low-power segmentation network implementation. The aim is to develop platform technology embodiments deployable across a wide range of health-monitoring wearable device applications requiring accurate, real-time and autonomous tissue monitoring. We have selected bladder volume as the initial target application for development of these technologies. Thesis Supervisor: Anantha P. Chandrakasan Title: Vannevar Bush Professor of Electrical Engineering and Computer Science
RESPIRE: Reducing Spatial–Temporal Redundancy for Efficient Edge-Based Industrial Video Analytics

Video camera plays a growing important role in advancing industrial control towards a higher level of automation. Thus, video analytics become highly demanded, especially for low-latency and high-accuracy analytic results. Yet, the data volume produced by camera clusters is prohibitively high. In this article, we propose Respire, a system that can remove redundant frames for reducing the cost of transmission and processing based on edge computing nodes, while maintaining useful frames for high analytic accuracy. Specifically, Respire incorporates a new way for characterizing the spatial–temporal redundancy between frames. Then, Respire prioritizes the uploading of frames for redundancy reduction. As the search space of the entire collected frames is exponential for the set of frames containing the maximal information, we jointly consider offline and online pruning of frames and propose a heuristic algorithm to reduce the search space. Extensive real-world dataset-based experiments demonstrate that the proposed system can significantly reduce communication and computation costs, while providing sufficient information for guaranteed video analytic accuracy.
Some Experiences With Cooperative Interactive Storyboard Prototyping

Certain types of products appear to be continually associated with poor interfaces. Especially for these product types, the need for active end-user participation in development activities is seen increasingly as critical to quality interface development. Cooperative Interactive Storyboard Prototyping (CISP) is a development approach facilitating active enduser participation in design activities that help to address these apparently difficult design problems. Key features of CISP include: 1) reducing the time and effort required to produce iterations of prototype interfaces; 2) support for interactive prototype use, evaluation and modification; and 3) creation and use of modifiable, domain specific buildingblocks.