Miracle-dz/UniFAR-FTUs huggingface dataset:
Blending cybersecurity education with IoT devices: A u-Learning scenario for introducing the man-in-the-middle attack

ABSTRACT Nowadays, due to the increasing number of cyberattacks, cybersecurity education, training, and awareness are considered crucial for preparing current and future IT professionals. Thus, it is essential for educational institutions to foster well-designed learning strategies in the field of cybersecurity that will not only focus on theory-based learning interventions but also on encapsulating authentic learning practices. In this context, the paper at hand presents a ubiquitous scenario-based learning (SBL) intervention, blended with IoT devices for introducing the topic of the man-in-the-middle attack to 1st-grade students in vocational education. The learning scenario enables two-way plain text communication through a LoRa network. For securing the transmission and assure confidentiality, basic encryption techniques are enabled for the transmitted messages. Meanwhile, an eavesdropper, acting as the man-in-the-middle attacker, tries to intercept the communication, by applying different decryption techniques. For this purpose, a u-Learning app was developed. The app was evaluated by ninety 1st-grade students of an educational institute of vocational training, in terms of effectiveness, efficiency, knowledge acquisition, and learners’ satisfaction. Among others, the results show that the effectiveness and the efficiency of the proposed learning process were 92.03%, and 89.63%, respectively. Finally, learners’ satisfaction was high, and their knowledge acquisition was improved.
Case Analysis of the Assessment Practices of Oral Communication Teachers in a Private School in the Philippine Setting

With the recent entry of the Senior High School program in the Philippines, success of it maybe viewed to lie in the teachers‟ ability to manage the whole teaching-learning process, including their means of assessing their students. It is for this reason that a focus on teachers‟ Language Assessment Literacy (LAL) comes essential. Hence, the present study aimed at conducting a case analysis of the assessment practices of three Senior High School teachers in one of the private schools in the Philippines. Recognizing the crucial role classroom assessment has in a language classroom, the case analysis sought to provide focus on the purposes of assessment realized by oral communication teachers, the belief towards assessment that they hold, and their unique assessment practices. The case analysis employed interview and document analysis to gather data. After careful analysis and reflection, it was concluded that, first, despite the individuality observed on the primed purposes of assessment of the teacher-participants, the influence of the institutional character of assessment to the teachers were still observed. Second, the teachers‟ beliefs and attitude towards assessment were noted to follow a personal stance, realizing their personal interpretive framework. Lastly, the two prior conclusions generated provided explanations to the observed cornerstone violations in the practices of teachers. Hence, the paper highlights the need for an understanding of teachers‟ beliefs, attitudes, and perceived purposes of assessment to make sense of the actual assessment practices they employ. In turn, this understanding may be used to effectively design a program for teachers‟ continuous LAL development.
IMPLEMENTASI WALL TOSS TEST SECARA DARING UNTUK MENGUKUR ASPEK KEBUGARAN JASMANI KOORDINASI MATA DAN TANGAN PADA SISWA SMPN 1 BANGKALAN

Bangkalan menggunakan instrumen wall toss test. Penelitian ini dilaksanakan dikelas VII A, VII B, VII C, dan VII D yang berjumlah 30 siswa. Dengan menggunakan penelitian deskriptif kuantitatif dimana siswa akan melakukan praktek wall toss 0,793 0,05. normal/baik.
Meeting Coflow Deadlines in Data Center Networks With Policy-Based Selective Completion

Recently, the abstraction of coflow is introduced to capture the collective data transmission patterns among modern distributed data-parallel applications. During processing, coflows generally act as barriers; accordingly, time-sensitive applications prefer their coflows to complete within deadlines, and deadline-aware coflow scheduling becomes very crucial. Regarding these data-parallel applications, we notice that many of them, including large-scale query systems, distributed iterative training, and erasure codes enabled storage, are able to tolerate loss-bounded incomplete inputs by design. This tolerance indeed brings a flexible design space for the schedule of their coflows: when getting overloaded, the network can trade coflow completeness for the timeliness, and balance the completeness of different coflows on demand. Unfortunately, existing coflow schedulers neglect this tolerance, resulting in inflexible and inefficient bandwidth allocations. In this paper, we explore this fundamental trade-off and design POCO, a POlicy-based COflow scheduler, along with a transport layer enhancement scheme, to achieve customizable selective coflow completion for emerging time-sensitive distributed applications. Internally, POCO employs a suite of novel designs along with admission controls to make flexible, work-conserving, and performance-guaranteed rate allocation to online coflow requests very efficiently. Extensive trace-based simulations indicate that POCO is highly flexible and achieves optimal coflow schedules respecting the requirements specified by applications.
First measurement of the forward rapidity gap distribution in pPb collisions at 8 TeV

We present the forward rapidity gap spectra from proton-lead collisions for both \mathrm{I\! P}IP-Pb and \mathrm{I\! P}IP-p topologies measured at the CMS at a center-of-mass energy of 8.16 TeV. For the \mathrm{I\! P}IP-Pb topology, the cross-section predicted by EPOS-LHC is a factor of two lower than the data while has reasonable description of the spectrum shape. For the \mathrm{I\! P}IP-p topology, the EPOS-LHC, QGSJET~II and HIJING predictions are significantly lower than the data, what can be explained by a contribution of ultra-peripheral photoproduction events. The obtained data may be of significant input for understanding the high energy limit of QCD and modeling cosmic ray air showers.
Equilibration of a two-level primitive equation model on the sphere

Summary. — The equilibration of a two-level primitive equation model forced by relaxation towards a fixed axisymmetric temperature profile is studied as a function of the forcing equator-to-pole temperature difference. We find that the mean equilibrated temperature gradient rises quickly with the forcing. It is found also that the mean eddy momentum flux convergence induces a strong barotropic jet at mid-to-high latitudes. We suggest that, as found in previous work, the barotropic governor effect induced by the jet is responsible for the sensitivity of the equilibrated temperature gradient to the forcing. PACS 92.60. Bh – General circulation.
From Scratch to Sketch: Deep Decoupled Hierarchical Reinforcement Learning for Robotic Sketching Agent

We present an automated learning framework for a robotic sketching agent that is capable of learning stroke-based rendering and motor control simultaneously. We formulate the robotic sketching problem as a deep decoupled hierarchical reinforcement learning; two policies for stroke-based rendering and motor control are learned independently to achieve sub-tasks for drawing, and form a hierarchy when cooperating for real-world drawing. Without hand-crafted features, drawing sequences or trajectories, and inverse kinematics, the proposed method trains the robotic sketching agent from scratch. We performed experiments with a 6-DoF robot arm with 2F gripper to sketch doodles. Our experimental results show that the two policies successfully learned the sub-tasks and collaborated to sketch the target images. Also, the robustness and flexibility were examined by varying drawing tools and surfaces.
Conceptualizaciones de la naturaleza y su relación con características sociodemográficas y el comportamiento pro-ambiental, Mar del Plata, Argentina

Una de las mayores dificultades para alcanzar soluciones efectivas a los problemas ambientales proviene de la profunda desconexión del ser humano con la naturaleza. Esta desconexión conduce a la pérdida de la capacidad inherente al humano de sentirse parte de la naturaleza, ignorando que su existencia depende de ella y que sus acciones la afectan significativamente. La forma en que se conceptualiza a la naturaleza puede influir en su percepción y vinculación con ella. La conceptualización depende de múltiples factores sociodemográficos (por ej., el lugar de nacimiento de las personas, la educación, las actividades recreativas), y puede influir en el comportamiento de las personas hacia el ambiente. El objetivo de este trabajo fue explorar la conceptualización que las personas de la localidad bonaerense de Mar del Plata (Argentina) tienen de naturaleza y su relación con algunas características sociodemográficas y de comportamiento proambiental. En esta investigación predominó la perspectiva metodológica cualitativa, a la cual se sumó el análisis cuantitativo (Análisis de Correspondencia Múltiple) de los datos para visualizar e interpretar las relaciones entre las variables. Se utilizó la encuesta autogestionada como método de recolección de información. A partir de 220 respuestas, se registró que las definiciones más frecuentes de naturaleza refirieron a la exclusión del ser humano del mundo natural y a todo lo que está vivo. Las personas con estudios en Ciencias Sociales, Humanas y de las Salud, y las que realizan actividades al aire libre y Biodanza mencionaron definiciones más diversas de naturaleza, asociándolas a una visión trascendente o espiritual. No se encontró un patrón que vincule la conceptualización que las personas tienen de naturaleza con el comportamiento proambiental. Este trabajo permitió explorar una de las formas de percibir a la naturaleza a través de su descripción con palabras, lo cual puede contribuir a la comprensión de nuestro accionar hacia ella. Abstract
Microprocessor feet improve prosthetic mobility and physical function relative to non-microprocessor feet

Introduction: The clinical benefits associated with the microprocessor regulation of prosthetic ankle position and resistance have largely been reported through manufacturer conducted research in controlled laboratory environments. Measures with greater ecological validity are needed. This study aimed to understand if there are differences in physical function and mobility outcomes as patients transitioned from a non-Microprocessor to Microprocessor Feet. Method: A retrospective analysis of patient outcomes was performed. Patient-reported benefits associated with the adoption of such prosthetic foot-ankle mechanisms were collected from 23 individuals through the longitudinal use of a custom short form of the Patient-Reported Outcomes Measurement Information System-Physical Function and individual items from the Prosthesis Evaluation Questionnaire. Results: The impact of Microprocessor Feet upon physical function and mobility were observed in a significant increase in physical function (mean increase in t-score of 5.4 ± 1.25; p = .0004) and significant improvements in several mobility items. Conclusions: Collectively, these measures support the beneficial impact of Microprocessor Feet on improving socket comfort, reducing back pain, improving sit to stand transfers and enhancing hill ascent and descent as well as stair negotiation.
Strengthening the Case for Universal Health Literacy: The Dispersion of Health Literacy Experiences Across a Southern U.S. State

Background: How individuals perceive their health literacy may differ based on demographic and individual characteristics. Objective: The purpose of this study was to understand the dispersion of health literacy across demographics in the state of Georgia in 2021 and to determine which factors influence health literacy. Methods: Study participants were age 18 years and older and completed an on-line Health Literacy Questionnaire (N = 520). The participant pool was stratified to mirror state-wide demographics of geography and race. Results were further collapsed into composite scales reflecting basic, communicative, and critical health literacy. Descriptive statistics, bivariate Pearson's correlations, and multiple regression analyses were used. A two-step cluster analysis was performed with the nine health literacy scales. Key Results: Rural county and no health insurance were negatively related to all three composite scales (rs = .093-.254, ps < .05). Demographic predictors accounted for 6.7% of the variance in basic (F[6, 439] = 5.287, p < .001), 10% in communicative (F[6, 438] = 8.154, p < .001), and 6% for critical (F[6, 439] = 4.675, p < .0010. In all scales, health insurance status was the strongest primary unique predictor (βs = .236, .295, .181, ps <.05, respectively). In a two-step cluster analysis only health insurance status differentiated the health literacy level clusters (X2(3) = 9.43, 34.51, ps = 024, <. 001 respectively). Conclusion: Lacking health insurance is the most consistent and largest contributor to low health literacy across the state of Georgia; population demographics are not. Health literacy policies and practices should be developed for universal application and not focus on specific populations. [HLRP: Health Literacy Research and Practice. 2022;6(3):e182–e190. ] Plain Language Summary: In this study, demographics that are usually associated with low health literacy like age, sex, race, educational attainment, and type of county (rural or urban) were not associated with; the only significant factor was lack of health insurance. This relationship strengthens the case for universal health literacy precautions that go beyond population demographics.
Manganese Utilization in Salmonella Pathogenesis: Beyond the Canonical Antioxidant Response

The metal ion manganese (Mn2+) is equally coveted by hosts and bacterial pathogens. The host restricts Mn2+ in the gastrointestinal tract and Salmonella-containing vacuoles, as part of a process generally known as nutritional immunity. Salmonella enterica serovar Typhimurium counteract Mn2+ limitation using a plethora of metal importers, whose expression is under elaborate transcriptional and posttranscriptional control. Mn2+ serves as cofactor for a variety of enzymes involved in antioxidant defense or central metabolism. Because of its thermodynamic stability and low reactivity, bacterial pathogens may favor Mn2+-cofactored metalloenzymes during periods of oxidative stress. This divalent metal catalyzes metabolic flow through lower glycolysis, reductive tricarboxylic acid and the pentose phosphate pathway, thereby providing energetic, redox and biosynthetic outputs associated with the resistance of Salmonella to reactive oxygen species generated in the respiratory burst of professional phagocytic cells. Combined, the oxyradical-detoxifying properties of Mn2+ together with the ability of this divalent metal cation to support central metabolism help Salmonella colonize the mammalian gut and establish systemic infections.
A Robust Feature Extraction for Automatic Fault Diagnosis of Rolling Bearings Using Vibration Signals

Bearing faults are one of the main reasons for rotary machine failure. Monitoring bearing vibration signals is an effective method for diagnosing faults and preventing catastrophic failures in rotary mechanisms. The state-of-the-art vibration monitoring algorithms are mainly based on frequency or time-frequency domain analysis of rotary machines that are operating in steady state. However, the steady state assumption is not valid in applications where the loads and speeds are time-varying. Finding a method for capturing the variability in vibration signals, which are caused by varying loads and speeds, is still an open research problem with potentially many applications in emerging areas such as electric vehicles. In this paper, we address the problem of vibration signal monitoring by applying a feature extraction algorithm to rotary machine signals measured by accelerometers. The proposed method, which is based on the wavelet scattering transform, achieves overall high accuracy while being computationally affordable for real-time implementation purposes. In order to verify the effectiveness of the proposed methodology, we apply our technique to a well-known vibration benchmark dataset with variable load. Our algorithm can diagnose various faults with different intensities with an average accuracy of 99% and thus effectively outperforming all prior reported work on this dataset. INTRODUCTION MOTIVATION A rolling bearing carries load by placing rolling elements such as balls or rollers between two adjacent bearing rings, which are also known as races. The relative motion of the races causes the rolling element to roll with low friction. Due to the low friction, rolling bearings are among the most frequently used components in rotary machines. On the other hand, a fault in bearings can result in catastrophic rotary machine failures. Accordingly, real-time monitoring of bearings for safety critical applications such as transportation and aviation is of crucial importance. PRIOR WORK Prior fault diagnosis algorithms fall within two broad categories, namely, model-based and data-driven approaches. Model-based fault diagnosis methods, when there exists a precise knowledge of the underlying governing dynamics of the system, generate reliable results [1–3]. However, accurate physical modeling of rotary machines is a very challenging and demanding task. Furthermore, model-based fault diagnosis algorithms are difficult to generalize to systems with different models [4, 5]. On the other hand, data-driven fault diagnosis methods are considered as pattern recognition problems. In the data-driven approaches, signal processing techniques are applied to the measured vibration signals in order to extract important system features. The health state of the machine is then diagnosed by classifying the extracted features [6, 7]. The key difference between prior data-driven methods is Proceedings of the ASME 2017 Dynamic Systems and Control Conference DSCC2017 October 11-13, 2017, Tysons, Virginia, USA
A Simple Dual-Polarized Patch Antenna Array for Wi-Fi 6/6E Application

A simple, high gain, and dual-polarized patch antenna array for Wi-Fi 6/6E application is proposed in this communication. Different from the conventional feeding method, the patches are driven by coupling dipoles that are printed on the same board. The dipoles are specially designed to be T-shaped to adjust the impedance matching. Broadband covering both 5 and 6 GHz bands of Wi-Fi 6/6E is achieved. The feeding circuit is easily integrated on the board with only parallel dual line utilized. A prototype is fabricated and tested to validate the concept. The measured and simulated results are in good agreement. The measured bandwidth with $S_{11} < -10$ dB for two ports are 5.12–7.50 and 5.15–7.50 GHz with the isolation higher than 30 dB. Moreover, the measured gains are higher than 9.76 and 9.61 dBi for two ports over the operating band with a peak value of 12.05 dBi. The proposed antenna array shows great potential in the application of Wi-Fi mesh.
A numerical simulation of vehicle dynamics behavior for a four-wheel steering vehicle with the passive control system

The Advanced Driver Assistance System (ADAS) is a technology in the vehicle to assist drivers in mitigating road risk and improving maneuverability. The system is capable of providing warnings to drivers and even executing an action if necessary. However, these systems are limited to the sensors and capability of the vehicle. Increasing the degree of freedom of a vehicle could potentially develop new ADAS with more efficiency. Along with the X-By-Wire technology, a four-wheel drive and independent steering (4WDIS) can be produced as a part of ADAS, especially for electric vehicles. In this research, an understanding of the steering characteristic of a 4WDIS during steady-state cornering (SSC) is presented using numerical simulation in MATLAB. An actual Segment B type vehicle is used as a simulation model and a preliminary two-wheel steering SSC simulation was performed to determine the steering characteristics. The model is modified to include a rear steer angle with a passive control system and the SSC simulation was repeated. The results show that the vehicle can perform SSC by increasing the yaw rate at high speed using the opposite steering mode. Meanwhile, parallel steering mode is suitable during low-speed cornering which can increase the yaw rate while maintaining stability.
Effect and Safety of ALA-PDT Combined with 1550 nm Fractional Therapy Laser in Treating Rosacea

Objective To explore the clinical effect and safety of 5-aminolevulinic acid photodynamic therapy (ALA-PDT) combined with 1550 nm fractional laser therapy in the treatment of rosacea. Methods 114 patients with type I and type II rosacea treated in our hospital from March 2018 to April 2020 were recruited. They were randomly assigned (1 : 1 : 1) to receive ALA-PDT (photodynamic group), 1550 nm fractional laser (laser group), or ALA-PDT and 1550 nm fractional laser therapy (combination group). Outcome measures included skin lesion scores, efficacy, and adverse reactions. Results After treatment, patients in the three groups showed lower skin lesion scores than before treatment, and the combination group showed significantly lower results than the other groups (P < 0.05). There was no significant difference in the total efficacy among the three groups (P > 0.05), but the combination group outperformed the other groups in the comparison of the efficacy levels (P < 0.05). Edema with lupus erythematosus, pain, and burning sensation was found in some cases but disappeared within 2 to 4 days after symptomatic treatment without interference with subsequent treatment. No patients had pigmentation, hypopigmentation, scars, or other serious adverse reactions. Conclusion In the treatment of rosacea, ALA-PDT combined with a 1550 nm fractional laser can reduce redness and facilitate skin remodeling, with high efficacy and safety, so it is worthy of clinical promotion and application.
Life cycle assessment of drop-in biofuels from prairie cordgrass

Abstract. This study uses the life cycle assessment framework to compare the effects on human health and the environment of drop-in biofuels produced from switchgrass and prairie cordgrass using a variety of low-input farming methods. Biofuel scenarios were developed using experimental data from South Dakota State University's Felt Farm, pretreatment and biomass conversion testing through South Dakota State University, and process models of biomass catalytic fast pyrolysis to biogasoline and biodiesel from the National Renewable Energy Laboratory. In particular, we examined the influence of low-input cropping systems, biomass densification and pretreatment (such as pelleting and AFEX) at regional biomass preprocessing depots, and transportation distance on net greenhouse gas emissions, human health, and ecotoxicity. Results show that greenhouse gas emissions from biogasoline from catalytic fast pyrolysis of prairie grasses provide emissions reductions of up to 80% compared to fossil fuels, though the extent of emissions reductions vary greatly by scenario. Biomass pretreatment and preprocessing steps, particularly drying biomass prior to catalytic fast pyrolysis, can have large contributions to net greenhouse gas emissions. Notably, differences in biomass composition between crop species could play a large role in the energy requirements, fuel yield, and carbon balance of catalytic fast pyrolysis. We conclude that biogasoline from both prairie cordgrass and switchgrass has potential to provide substantial emissions reductions. Catalytic fast pyrolysis is the primary contributor to human health and ecotoxicity metrics. This conversion process, for which little data is available, should be a key target for improved modeling of environmental outcomes from drop-in biofuels.