Miracle-dz/UniFAR-FTUs huggingface dataset:
Permanent Magnet Synchronous Motor Control Interface Design and Implementation with TI F28335 DSP on Simulink External Mode

In recent years Permanent Magnet Synchronous Motors (PMSMs) are more preferred due to have several advantageous traits, such as high-power density, improved efficiency, enhanced torque capabilities, and precise speed control. In this study, speed control algorithm and a user interface panel aredesigned for PMSM on Simulink. Control algorithm is downloaded to TI F28335 DSP over Simulink embedded coder. Control panel is connected the DSP over Simulink external mode. Thanks to the external mode, the system data can be displayed on the panel in real time and the parameters can be changed. The system has been tested on the experimental setup and has been shown to work successfully.
Feasibility of Conducting Sit-to-Stand Tests Using Video Consultation

Objective. This study is aimed at ascertaining the feasibility of conducting the 1-minute sit-to-stand (1MSTS) and 30-second sit-to-stand (30SSTS) tests for healthy participants via video consultation. A secondary aim was to compare the relationship between the 1MSTS and 30SSTS. Methods. A total of 63 participants were recruited via the Singapore Institute of Technology emails and social media in 2020 during the peak of COVID-19. Prior to the sit-to-stand testing, all participants completed the consent form and physical activity questionnaires. Anthropometric data such as height and weight were also collected prior to testing. An instructional video detailing the sit-to-stand (STS) movement and the requirements for the environment set-up were sent to the participants via email. All STS tests were conducted virtually via the Zoom application. Healthy participants aged 21 to 55 years old performed a 1MSTS and 30SSTS each in random order. Results. All recruited participants completed the STS tests with no reported adverse events. Majority of participants were from the 21- to 25-year-old age groups, and the average number of repetitions performed by this group was 21.9 ± 5.6 for the 30SSTS and 44.7 ± 12.6 for the 1MSTS. Conclusion. Conducting the STS tests via video consultation was demonstrated to be safe and feasible. The number of repetitions performed in the 1MSTS is correlated to that of the 30SSTS, but 1MSTS has the ability to elicit a greater HR response among younger adults.
Opening museums' science communication to dialogue and participation: the “Experimental Field for Participation and Open Science” at the Museum für Naturkunde Berlin

The Museum für Naturkunde Berlin (Natural History Museum — MfN) established participation and exchange as central elements of the entire institution alongside its research. In order to experiment with formats and settings for dialogue-oriented exchange and participation, an area within the exhibition round walk was designated for this purpose in 2018. Over the course of three years, the “Experimental Field for Participation and Open Science” has developed the practice of opening the museum's research and collection in a dialogue-oriented, participatory way. Focus lies on museum visitors and on reaching new groups who are not in close contact with science yet. The practice of opening and participation was tested, reflectively accompanied, and further developed during the whole time period. This article describes idea, concept, design, and the results of the external evaluation of the formats of dialogue-oriented and participatory outreach in the Experimental Field at the MfN. It gives an overview of underlying ideas, design of the space, and how the goal of creating mutually beneficial encounters and enabling participation and co-creation was addressed.
Microservice reference architecture design: A multi‐case study

Microservice architecture (MSA) is an architectural style that is designed to support the modular development of software systems within a particular domain. It is characterized by the use of small, independently deployable services, which can be developed and deployed autonomously. The benefits of MSA include improved scalability, fault‐tolerance, and ease of deployment and maintenance. However, developing MSA for a specific domain can be challenging and requires a thorough consideration of various concerns such as service boundaries, communication protocols, and security. To support the easy development and guidance of an MSA for practitioners, we present a reference architecture design for MSA. The reference architecture has been designed after a comprehensive domain analysis of MSA in the literature and the MSAs of key vendors. This analysis has been used to identify best practices and common patterns that can be applied to the development of MSA. Additionally, relevant architecture viewpoints have been selected to model the corresponding architecture views, providing a clear and comprehensive understanding of the architecture. To validate the proposed reference architecture, a multi‐case study research approach has been used. In this approach, two industrial case studies have been used to demonstrate the practical applicability of the proposed reference architecture. The results of these case studies have shown that the reference architecture can be used to effectively guide the development of MSA in real‐world scenarios.
On a quantum particle in laser channels

In this paper the effective potential describing interaction of a scalar quantum particle with arbitrary nonuniform laser field is derived for a wide spectrum of the particle energies. The presented method allows to take into account all the features of the effective potential for a scalar particle. The derived expression for effective potential for quantum particle has the same form as the one presented earlier for a classical particle. A special case for channeling of a quantum particle as well as accompanying channeling radiation in a field formed by two crossed plane laser waves is considered. It is shown that relativistic particles moving near the laser channel bottom should be examined as quantum ones at both arbitrarily large longitudinal energies and laser fields of accessible intensities.
An alternative measure of ordinal association as a value-validity correction of the Goodman–Kruskal gamma

ABSTRACT Even though the Goodman–Kruskal gamma (γ) is perhaps the most popular measure of association between two ordinal categorical variables, it does have some well-known limitations. In particular, it is widely recognized that its sample form takes on values that may be highly inflated, making it incomparable with other measures such as the frequently used Kendall's tau-b (). Such overstatement of a characteristic, varying in extent, has important implications for the validity and reliability of results and conclusions. By imposing a value–validity condition on association measures, this paper derives an alternative measure as a simple correction of . The new measure takes on reasonable values throughout its range from −1 to 1 and is quite comparable with , but has advantages over it. Numerical values of are compared with those of and other measures for various reported datasets, and a statistical inference procedure is discussed.
Granger Causal Network Learning and the Depth Wise Grouped LASSO

In this thesis we study the notion of Granger-causality, a statistical concept originally developed to estimate causal effects in econometrics. First, we suggest a more general notion of Granger-causality in which to frame the proceeding practical developments. And second, we derive a proximal optimization algorithm to fit large and sparse vector autoregressive models, a task closely connected to the estimation Grangercausality amongst jointly wide sense stationary process. Experimental results from our so called “Depth Wise Grouped LASSO” convex program are obtained for both simulated data, as well as Canadian meteorology data. We conclude by discussing some applications and by suggesting future research questions.
In-the-Wild Affect Analysis of Children with ASD Using Heart Rate

Recognizing the affective state of children with autism spectrum disorder (ASD) in real-world settings poses challenges due to the varying head poses, illumination levels, occlusion and a lack of datasets annotated with emotions in in-the-wild scenarios. Understanding the emotional state of children with ASD is crucial for providing personalized interventions and support. Existing methods often rely on controlled lab environments, limiting their applicability to real-world scenarios. Hence, a framework that enables the recognition of affective states in children with ASD in uncontrolled settings is needed. This paper presents a framework for recognizing the affective state of children with ASD in an in-the-wild setting using heart rate (HR) information. More specifically, an algorithm is developed that can classify a participant’s emotion as positive, negative, or neutral by analyzing the heart rate signal acquired from a smartwatch. The heart rate data are obtained in real time using a smartwatch application while the child learns to code a robot and interacts with an avatar. The avatar assists the child in developing communication skills and programming the robot. In this paper, we also present a semi-automated annotation technique based on facial expression recognition for the heart rate data. The HR signal is analyzed to extract features that capture the emotional state of the child. Additionally, in this paper, the performance of a raw HR-signal-based emotion classification algorithm is compared with a classification approach based on features extracted from HR signals using discrete wavelet transform (DWT). The experimental results demonstrate that the proposed method achieves comparable performance to state-of-the-art HR-based emotion recognition techniques, despite being conducted in an uncontrolled setting rather than a controlled lab environment. The framework presented in this paper contributes to the real-world affect analysis of children with ASD using HR information. By enabling emotion recognition in uncontrolled settings, this approach has the potential to improve the monitoring and understanding of the emotional well-being of children with ASD in their daily lives.
Whole-Genome Sequencing of Mycobacterium tuberculosis Isolates from Diabetic and Non-Diabetic Patients with Pulmonary Tuberculosis

The association of tuberculosis and type 2 diabetes mellitus has been a recognized re-emerging challenge in management of the convergence of the two epidemics. Though much of the literature has studied this association, there is less knowledge in the field of genetic diversities that might occur in strains infecting tuberculosis patients with and without diabetes. Our study focused on determining the extent of diversity of genotypes of Mycobacterium tuberculosis in both these categories of patients. We subjected 55 M. tuberculosis isolates from patients diagnosed with pulmonary TB with and without type 2 diabetes mellitus to whole-genome sequencing on Illumina Hi Seq platform. The most common lineage identified was lineage 1, the Indo-Oceanic lineage (n = 22%), followed by lineage 4, the Euro-American lineage (n = 18, 33%); lineage 3, the East-African Indian lineage (n = 13, 24%); and lineage 2, the East-Asian lineage (n = 1, 2%). There were no significant differences in the distribution of lineages in both diabetics and non-diabetics in the South Indian population, and further studies involving computational analysis and comparative transcriptomics are needed to provide deeper insights.
Object-Level Attention Prediction for Drivers in the Information-Rich Traffic Environment

An object-level attention prediction framework for drivers in the urban environment with rich semantic and motion information is proposed in this article. The proposed framework is based on the visual working memory mechanism, which decomposes the perception process into three phases, external stimuli, cognitive constructing, and memory search. In the external stimuli phase, semantic and motion information of surrounding objects is obtained. In the cognitive constructing phase, the neighbor-based hierarchical clustering method is applied to extract both independent and dependent features of traffic participants and driving events. In the memory search phase, the heterogeneous motif graph neural network is utilized to construct visual memory layers and integrate multilevel features for attention reasoning. Finally, the feature embedding is fed into a multilayer perceptron to predict the object-level visual attention. Training and testing data are collected from crowded and dynamic traffic scenes. Experimental results show that the proposed framework can achieve a superior object-level prediction performance in the information-rich environments compared with the state-of-the-art methods. In addition, the proposed framework can reduce the time bias of visual attention effectively.
Diploid mycelia of Ustilago esculenta fails to maintain sustainable proliferation in host plant

Smut fungi display a uniform life cycle including two phases: a saprophytic phase in vitro and a parasitic phase in host plants. Several apathogenic smut fungi are found, lacking suitable hosts in their habitat. Interestingly, MT-type Ustilago esculenta was found to maintain a parasitic life, lacking the saprophytic phase. Its long period of asexual proliferation in plant tissue results in severe defects in certain functions. In this study, the growth dynamics of U. esculenta in plant tissues were carefully observed. The mycelia of T- and MT-type U. esculenta exhibit rapid growth after karyogamy and aggregate between cells. While T-type U. esculenta successfully forms teliospores after aggregation, the aggregated mycelia of MT-type U. esculenta gradually disappeared after a short period of massive proliferation. It may be resulted by the lack of nutrition such as glucose and sucrose. After overwintering, infected Zizania latifolia plants no longer contained diploid mycelia resulting from karyogamy. This indicated that diploid mycelia failed to survive in plant tissues. It seems that diploid mycelium only serves to generate teliospores. Notably, MT-type U. esculenta keeps the normal function of karyogamy, though it is not necessary for its asexual life in plant tissue. Further investigations are required to uncover the underlying mechanism, which would improve our understanding of the life cycle of smut fungi and help the breeding of Z. latifolia.
Distinctive features of the central synaptic organization of Drosophila larval proprioceptors

Proprioceptive feedback is critically needed for locomotor control, but how this information is incorporated into central proprioceptive processing circuits remains poorly understood. Circuit organization emerges from the spatial distribution of synaptic connections between neurons. This distribution is difficult to discern in model systems where only a few cells can be probed simultaneously. Therefore, we turned to a relatively simple and accessible nervous system to ask: how are proprioceptors’ input and output synapses organized in space, and what principles underlie this organization? Using the Drosophila larval connectome, we generated a map of the input and output synapses of 34 proprioceptors in several adjacent body segments (5–6 left-right pairs per segment). We characterized the spatial organization of these synapses, and compared this organization to that of other somatosensory neurons’ synapses. We found three distinguishing features of larval proprioceptor synapses: (1) Generally, individual proprioceptor types display segmental somatotopy. (2) Proprioceptor output synapses both converge and diverge in space; they are organized into six spatial domains, each containing a unique set of one or more proprioceptors. Proprioceptors form output synapses along the proximal axonal entry pathway into the neuropil. (3) Proprioceptors receive few inhibitory input synapses. Further, we find that these three features do not apply to other larval somatosensory neurons. Thus, we have generated the most comprehensive map to date of how proprioceptor synapses are centrally organized. This map documents previously undescribed features of proprioceptors, raises questions about underlying developmental mechanisms, and has implications for downstream proprioceptive processing circuits.
Effective Communication between IoT Devices using Machine Learning

The Internet of Things (IoT) consisting of several interconnected sensors capable of transferring the data over the network without human involvement. All these interconnected sensors can be managed through internet remotely. The Sensors connected in the networks are deployed randomly and are mobile in nature. The loss of sensor’s energy occurs due to the mobility nature, communication between the sensors and operations performed. The perfectly suitable sensor nodes as relay nodes and Cluster Heads (CH), and energy efficient path to the Base Station (BS) should be selected at each and every stage in the IoT network for effective communication. This paper presenting the method for effective communication between IoT Devices using ML comprising of Sensor Deployment, Clustering, Data Aggregation, Data Routing, and Reconstruction. In this paper for maximum coverage across the BS, relay sensors are deployed in hexagonal fashion. The sensors in the network transmit the diverse data and data aggregation is performed at CH level by machine learning algorithm that is Particle Swarm Optimization (PSO). The Ant Colony Optimization (ACO) algorithm is used to effectively routing the data over the network and dimensionality of the data is reduced with the Principle Component Analysis (PCA). The effective communication is established here by reducing the residual nodes. The total of 600 mobile sensor nodes and 12 relay sensor nodes are considered in the simulation of this work by the Network Simulation-3 (NS-3), only 42 joules energy is consuming over 200 milliseconds with network life time of 3000 milliseconds.
ANALISIS METODE CONNECTED VERTICES CLUSTERING AND STAR TOPOLOGY PADA SERANGAN GEOMETRI TERHADAP WATERMARKING OBJEK 3D

Dalam usaha untuk melindungi hak cipta dan keaslian dari suatu objek tiga dimensi, diperlukan sebuah algoritma untuk menyisipkan informasi rahasia yang tidak nampak oleh indera penglihatan manusia namun dapat dideteksi dengan menggunakan suatu media, misalnya komputer. Oleh karena itu watermark menjadi sebuah solusi terbaik untuk permasalahan tersebut. Metode yang digunakan untuk menanamkan watermark ke dalam objek 3 dimensi adalah metode connected vertices clustering and topology star , dimana sebuah objek 3 dimensi dibagi-bagi menjadi beberapa topologi star berdasarkan vertex-vertex -nya yang saling terhubung. Dari topologi star ini dipilih edge-edge untuk disisipi informasi watermark dan dengan menggunakan sebuah PN sequensial dipilih edge yang vertex- nya disisipi oleh watermark . Hasil yang diperoleh dari simulasi sitem watermarking ini adalah didapat sebuah skema penanaman watermark dengan kualitas imperceptibility yang baik karena memiliki nilai BER dan VER yang mendekati 0 serta nilai SNR yang besar. Selain itu watermark dapat diekstrak dengan sangat baik setelah diberi serangan rotasi, scaling, translasi, serta kombinasi serangan scaling dan translasi dengan nilai BER 0. Skema ini tidak robust terhadap serangan cropping.
Using the area under an estimated ROC curve to test the adequacy of binary predictors*

ABSTRACT We consider using the area under an empirical receiver operating characteristic curve to test the hypothesis that a predictive index combined with a range of cutoffs performs no better than pure chance in forecasting a binary outcome. This corresponds to the null hypothesis that the area in question, denoted as AUC, is 1/2. We show that if the predictive index comes from a first-stage regression model estimated over the same data set, then testing the null based on the standard asymptotic normality results leads to severe size distortion in general settings. We then analytically derive the proper asymptotic null distribution of the empirical AUC in a special case; namely, when the first-stage regressors are Bernoulli random variables. This distribution can be utilised to construct a fully in-sample test of with correct size and more power than out-of-sample tests based on sample splitting, though practical application becomes cumbersome with more than two regressors.
Statistical analysis of ST segments in ECG signals for detection of ischaemic episodes

This paper highlights a new method for the detection of ischaemic episodes using statistical features derived from ST segment deviations in electrocardiogram (ECG) signal. Firstly, ECG records are pre-processed for the removal of artifacts followed by the delineation process. Then region of interest (ROI) is defined for ST segment and isoelectric reference to compute the ST segment deviation. The mean thresholds for ST segment deviations are used to differentiate the ischaemic beats from normal beats in two stages. The window characterization algorithm is developed for filtration of spurious beats in ischaemic episodes. The ischaemic episode detection is made through the coefficient of variation (COV), kurtosis and form factor. A bell-shaped normal distribution graph is generated for normal and ischaemic ST segments. The results show average sensitivity (Se) 97.71% and positive predictivity (+P) 96.89% for 90 records of the annotated European ST-T database (EDB) after validation. These results are significantly better than those of the available methods reported in the literature. The simplicity and automatic discarding of irrelevant beats makes this method feasible for use in clinical systems.
The scattering of the sound field by thin unclosed spherical shell and ellipsoid

In this paper the result of solution of the axisymmetric problem of the scattering of sound field by unclosed spherical shell and a soft prolate ellipsoid of rotation is presented. Spherical radiator is located in a thin unclosed spherical shell as the source of acoustic field. The equation of the spheroidal boundary is given in spherical coordinates. Scattered pressure field is expressed in terms of spherical wave functions. Using corresponding theorems of addition and assuming small eccentricity of ellipse, the solution of boundary value problem is reduced to solving dual equations with Legendre's polynomials, which are converted to infinite system of linear algebraic equations of the second kind with completely continuous operator. Numerical results are given for various values of the parameters of the problem.
Exploring Day Center Activities in Norway: How do Employees Facilitate Participation for Workers with Intellectual Disabilities through Interaction and Social Support? An Ethnographic Study

Many people with intellectual disabilities in Norway attend municipal day centers where they engage in activities and work-tasks with support from staff. The purpose of day centers is to offer meaningful activities for individuals who are not included in ordinary work. Little research has been done on day centers, and we have limited knowledge of which social and cultural norms apply in such a sheltered context. This article focuses on how employees facilitated the participation of workers with intellectual disabilities through social support and in interaction. This study has a qualitative ethnographic design. Data were collected through participatory observation and interviews and analyzed thematically. We found that the participants alternated between roles and frames of interaction: a work frame and a care frame. Each frame had different norms for interaction and role performance. This study adds to our knowledge about day centers for people with intellectual disabilities