Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Preservice STEM Teachers’ Smartphone Addiction

Smartphones amount of time spent on a phone increases. Excessive smartphone use and addiction have developed into big social issues. Addiction to smartphones is a negative and pathological concept that is assessed by a set of subjective and behavioral symptoms including fixation, loss of control, and withdrawal symptoms. Teachers in STEM fields have a higher degree of involvement with their students in the use of digital tools. STEM teacher candidates must demonstrate an understanding of how to incorporate technology successfully into classroom activities. Determine the incidence of smartphone addiction among prospective STEM educators to justify future awareness training. The association between pre-service STEM instructors ’ smartphone addiction was studied. The research included 242 persons, 180 of whom were females and 62 males. The SAI is self-administered and scored independently for each dimension. Data is analyzed using machine learning techniques. Cluster analysis is used to analyze the inventory ’ s dimensions. The k-means technique is used for cluster analysis. The library ’ s SHAP (SHapley additive explanations) approach was used to evaluate the classification result and assess the impact of attributes on the classification result. According to the findings, the highest level was judged to be 30 participants. Approximately 3%4 participants are deemed moderate (high and very high). Also, 48 people are at a low level. In terms of the overall group, it is modest. Being in the lowest cluster is linked to 100+ uses, whereas being in the highest cluster is linked to 6-10 uses. The exact degree of smartphone use linked to smartphone addiction is unknown. Females inversely correlate with the highest and lowest clusters.
Colonization of Group B Streptococcus in Pregnant Women and Their Neonates from a Sri Lankan Hospital

We investigated the molecular epidemiology of Streptococcus agalactiae (Group B Streptococcus, GBS) from carriage in a cohort of pregnant mothers and their respective newborns in a Teaching Hospital in Sri Lanka. GBS vaginal carriage was assessed on pregnant mothers at pre-delivery (n = 250), post-delivery (n = 130), and from peri-rectal swabs of neonates (n = 159) in a prospective study. All colonizing, non-duplicate GBS isolates (n = 60) were analyzed for antimicrobial susceptibilities, capsular serotyping, and whole-genome sequencing (WGS). The percentage of GBS carriage in mothers in the pre-delivery and post-delivery cohorts were 11.2% (n = 28) and 19.2% (n = 25), respectively, and 4.4% (n = 7) in neonates. GBS isolates predominantly belonged to serotype VI (17/60, 28.3%). The isolates spanned across 12 sequence types (STs), with ST1 (24/60, 40%) being the most predominant ST. Concomitant resistance to erythromycin, tetracyclines, and gentamicin was observed in eight strains (13.3%). WGS revealed the presence of antimicrobial resistance genes including ermA (5/60), mefA (1/60), msrD (1/60), and tetLMO (2/60, 28/60, and 1/60, respectively) among 60 strains. The study provides insight into the diversity of vaccine targets of GBS since serotype VI is yet to be covered in the vaccine development program.
Within sniffing distance: impact of ambient scent and physical distancing on consumer comfort with frontline employees

Abstract Many sales and service interactions with frontline employees take place in scented places. This research focuses on the effect of ambient scents on consumer comfort with frontline employees and subsequently on the perceived quality of product and service offers. Two experimental studies carried out in actual setting in Paris, in taxis (242 respondents interacting with drivers) and in a small shop (120 respondents interacting with advisors), show that consumer comfort with frontline employees and perceived quality are higher (lower) in the presence of an ambient scent when the frontline employees maintain strong (low) physical proximity with consumers. This study shows the impact of ambient scents in consumers-employee’s relationships and questions their relevance when social interactions are constrained by distancing rules.
A Doherty Power Amplifier With Extended High-Efficiency Range Using Three-Port Harmonic Injection Network

In this paper, a Doherty power amplifier (DPA) using a novel three-port harmonic injection network (HIN) to extend its high-efficiency range is proposed. With the help of a part of the three-port HIN, which is placed between the carrier and peaking branches, the optimal drain fundamental frequency termination for the carrier device at back-off and saturation can be realized simultaneously thus enhancing the efficiency at back-off significantly. Meanwhile, this three-port HIN can also realize second harmonic drain terminations for the carrier and peaking device with the quasi-open and quasi-short circuit at the current plane, respectively. Consequently, the saturated power ratio between peaking and carrier devices is increased, which further extends the back-off range of the asymmetric drain-biased DPA. For demonstration purposes, an extended high efficiency range DPA was designed and fabricated using commercially available GaN HEMT (Cree CGH 40010F) devices. Measured results for this novel idea gave drain efficiencies better than 62.5% at 9-9.5 dB back-off point from 1.60 to 1.95 GHz.
A novel high step-up DC-DC converter with coupled inductor and switched clamp capacitor techniques for photovoltaic systems

In this study, a novel high step-up DC-DC converter was successfully integrated using coupled inductor and switched capacitor techniques. High step-up DC-DC gain was achieved using a coupled inductor when capacitors charged and discharged energy, respectively. In addition, energy was recovered from the leakage inductance of the coupled inductor by using a passive clamp circuit. Therefore, the voltage stress of the main power switch was almost reduced to 1/7 V o (output voltage). Moreover, the coupled inductor alleviated the reverse-recovery problem of the diode. The proposed circuit efficiency can be further improved and high voltage gain can be achieved. The operation principle and steady-state analysis of the proposed converter were discussed. Finally, a hardware prototype circuit with input voltage of 24 V, output voltage of up to 400 V, and maximum power of 150 W was constructed in a laboratory; the maximum efficiency was almost 96.2%.
Assessing the Sensitivity of Vegetation Cover to Climate Change in the Yarlung Zangbo River Basin Using Machine Learning Algorithms

Vegetation is a key indicator of the health of most terrestrial ecosystems and different types of vegetation exhibit different sensitivity to climate change. The Yarlung Zangbo River Basin (YZRB) is one of the highest basins in the world and has a wide variety of vegetation types because of its complex topographic and climatic conditions. In this paper, the sensitivity to climate change for different vegetation types, as reflected by the Normalized Difference Vegetation Index (NDVI), was assessed in the YZRB. Three machine learning models, including multiple linear regression, support vector machine, and random forest, were adopted to simulate the response of each vegetation type to climatic variables. We selected random forest, which showed the highest performance in both the calibration and validation periods, to assess the sensitivity of the NDVI to temperature and precipitation changes on an annual and monthly scale using hypothetical climatic scenarios. The results indicated there were positive responses of the NDVI to temperature and precipitation changes, and the NDVI was more sensitive to temperature than to precipitation on an annual scale. The NDVI was predicted to increase by 1.60%–4.68% when the temperature increased by 1.5 °C, while it only changed by 0.06%–0.24% when the precipitation increased by 10% in the YZRB. Monthly, the vegetation was more sensitive to temperature changes in spring and summer. Spatially, the vegetation was more sensitive to temperature increases in the upper and middle reaches, where the existing temperatures were cooler. The time-lag effects of climate were also analyzed in detail. For both temperature and precipitation, Needleleaf Forest and Broadleaf Forest had longer time lags than those of other vegetation types. These findings are useful for understanding the eco-hydrological processes of the Tibetan Plateau.
The gray body approximation for radiative heat transfer in evacuated tube solar collectors: Effects of envelope infrared transparency

A theoretical and experimental analysis is carried out of radiative heat transfer in the coaxial geometry of evacuated tube solar collectors. The gray body approximation implicit in the use of an effective emissivity does not strictly apply to evacuated tube solar collectors due to selective absorber coating and partially transmitting outer glass in the thermal infrared, especially when constructed from borosilicate. We develop analytic expressions for the heat transfer through the outer envelope and show the equations no longer follow a simple form where an effective emissivity for the system can be defined. To test all approximations in practice, an experiment is performed using an evacuated solar collector manufactured in the 1980s by the Nitto Kohki company in Japan using the effective emissivity approximation to determine the typical heat transfer characteristics using net radiative heat flows in both directions. This method enabled a good fit to temperature–time data for cooling and heating of the inner tube for temperatures between 10 and 85 °C. The results confirm that the effective emittance method can be used in situations with typical glass wall thickness and temperatures. At temperatures greater 100 °C, the spectral distribution of the emitted radiation falls significantly within the transmitting region of the outer glass and can no longer be neglected. The work has verified the stability of the vacuum in this type of collector as the tube still functions well, maintaining a low emissivity and good vacuum after approximately 40 years in storage conditions.
Emergent Systems and Intelligent Agents for Simulation of PowerSystems

This paper deals with the role of biologically motivated emergent systems and intelligent agents in the simulation of electric power networks. The main aim is to provide a platform to analyze the power system of the Czech Republic (and a part of Slovakia) and to point out where the potential weak points are. We shortly introduce the area of emergent systems and intelligent agents. To motivate our further considerations, we also characterize the field of biologically motivated artificial intelligence. We bring a list of basic characteristics of such systems -- emergence, local interaction and adaptation. A new simulation system Kairos is briefly introduced with justifications for ``mapping'' the artificial-life systems properties to the domain of electric power systems.
Tightly-Coupled Fusion of VINS and Motion Constraint for Autonomous Vehicle

In this paper, we develop a novel visual-inertial navigation system with motion constraint (VINS-Motion), which extends the visual-inertial navigation system (VINS) to incorporate vehicle motion information for improving the autonomous vehicles localization accuracy. We introduce the vehicle stop detection module in the pre-processing measurement procedure. During the back-end processing, if the vehicle is detected to be in a stopping state, we perform optimization based on the stop constraint to help eliminate the abnormal jitter of the estimated pose, thus ensuring the reasonability of the trajectory. Otherwise, besides the prior information, IMU measurement residual, and visual measurement residual utilized in VINS, vehicle orientation/velocity constraint built by Ackerman steering model is first exploited to constitute residuals. We minimize the sum of priors and Mahalanobis norms of three kinds of residuals to obtain a maximum posterior estimation, thus increasing system consistency and accuracy. The proposed approach is validated on public datasets and compared with state-of-the-art algorithms, which demonstrates that the motion constraint proposed in this paper improves the standard VINS performance and achieves significantly higher positioning accuracy.
A Pseudo-Exhaustive Software Testing Framework for Embedded Digital Devices in Nuclear Power

The major challenge faced by the nuclear industry related to software testing of digital embedded devices is the identification of practical software (SW) testing solutions that provide a strong technical basis and are at the same time effective in establishing credible evidence of software common cause failures (SCCF) reduction. Towards this effort, we conducted a systematic empirical study on pseudo-exhaustive SW testing methods for embedded digital devices. In this paper, we describe the realization of a testbed for conducting an automated pseudo-exhaustive software testing on embedded digital devices and the intricate interactions between the multiple software tools involved in the workflow. The collected results and derived findings confirm the ability of the automated pseudo-exhaustive testing methodology to economically exercise the interaction input/state space in a systematic, rigorous, and comprehensive manner.
Salt Stress Differentially Affects the Primary and Secondary Metabolism of Peppers (Capsicum annuum L.) According to the Genotype, Fruit Part, and Salinity Level

A total of four Capsicum annuum L. genotypes (‘Caro F1’, ‘Berenyi F1’, ‘Somborka’ and ‘Novosadka’) were exposed to two intensities of salt stress. We observed a significant decrease in the sugar content in all salt stressed treatments, except for the sucrose content of the pericarp of the ‘Caro F1’ cultivar. Salt stress had a largely negative effect on the total and individual organic acid content, although the effect differed among cultivars. Using high performance liquid chromatography coupled with a mass spectrometer, most phenolics were identified in the pericarp (18), followed by the placenta (7) and seeds (8). Treatment with 40 mM NaCl caused the highest increase in individual phenols, followed by treatment with 20 mM NaCl. The cultivar ‘Berenyi F1’ was less affected by salt stress treatment than the other three cultivars in terms of content of individual and total phenols. Salt stress increased the content of capsaicinoids in all the cultivars. The pericarp of the cultivar ‘Novosadka’ showed 17.5 and 50 times higher total capsaicinoid content than the control in the 20 mM and 40 mM NaCl, respectively. With the results of several metabolite groups, we confirmed that the reaction and metabolic content to salt stress within the genus Capsicum is genotype-, fruit part-, and salinity level-dependent.
HVDC Grid Segmentation Analysis for Blackouts Reduction

Segmentation of large AC systems through DC links introduces a new concept that utilizes the advantages of direct current transmission to improve network reliability and increase power transfer capacity. Technical literature argues that the segmentation of the AC network and the introduction of DC links at these systems connection points bring benefits to system operation, once contingencies generated on one side of the DC connection point would not be reflected on the other side of DC connection, thereby reducing the likelihood of cascading shutdowns and blackouts due to load restraint on transmission lines and transformers. Amidst this scenario, this paper presents a study of the main topics regarding the use of this new network segmentation philosophy, bringing a practical point of view for the use of this concept at the electrical power system planning. The effect of DC segmentation before a contingency that would initiate major outages in an adapted electrical system model IEEE-14 bus is studied and simulations have been performed with test HVAC systems and segmented by HVDC link. The results have been compared, principally in relation to the voltage bus, reactive power generation, system losses and power flow at the lines, and demonstrated that this new concept improved the grid reliability.
Early Prediction and Evaluation of Risk of Autism Spectrum Disorders

Autism is a neuro-developmental condition that first appears at less than three years of age. Autism spectrum disorders (ASD) include several symptoms, such as social communication impairment, stereotyping behaviors, speech abnormalities, and impairment of eye contact. Its prevalence has increased recently, and several factors play a role in increasing the risk of autism. Multiple studies and research explain the factors affecting the rate of autism, and in this article, we will review most of these factors. The aim of this review article is to increase awareness of the problem of autism and provide scientifically relevant information about the etiology, pathogenesis, risk factors, and management of ASD. Our perception of autism has evolved over time. A few years ago, the condition was nothing more than an unrecognized developmental delay, generally with intellectual disabilities. Today, it is recognized as a major public health issue and a topic of much research. Researchers have struggled to find a cause for ASD, and numerous treatments have been developed to maximize the potential to learn and become socially fluent, no matter how strong the impairments may be. Although there is no cure, there have been significant strides in identifying and developing treatments. Early prediction of autism is beneficial in an individual's treatment, which can be carried out by recognizing the risk factors of infants, thus leading to improved outcomes or even a complete cure. The prevalence of ASD has increased, and earlier prediction leads to the best outcomes.
Biometric Authentication for Intelligent and Privacy-Preserving Healthcare Systems

Secure identification is a critical system requirement for patients seeking health-related services. In the event of critical, aged, or disabled patients who require frequent health treatments, quick and easy identification is vital. Researchers describe the notion of the unprotected environment in this study, in which patients can receive health services from the hospital's smart and intelligent surroundings without the use of explicit equipment. Patients would interact directly with the environment and be identified through it. We suggest a biometric-based authentication technique for the unprotected hospital environment that also safeguards the patient's identity privacy. Furthermore, we demonstrate that this authentication technique is resistant to many well-known assaults, including insider attacks, replay attacks, and identity privacy. Doctors and other staff members showed enthusiastic responses after installing 2-factor authentications, as it makes their workflow efficient and makes things easier for patients. It also lets them focus on other factors rather than worrying about data security; hence, we need biometric authentication in intelligent and privacy-preserving healthcare systems. The paper deals with two-factor biometric authentication, and despite the added security, two-factor authentication adoption is said to be poor. It is due to a lack of awareness and difficulty to use and configure two-factor authentication (2FA) into a particular application by some individuals who struggle with the concept of authentication and its technology. Also, many 2FA methods in widespread use today have not been subjected to adequate usability testing. Research focuses on the point that there is still a large section of people unaware of the use of biometric systems to protect their online data. Researchers collected quantitative and qualitative data from 96 individuals during a two-week between-subjects usability survey of some common and rarely used 2FA approaches. The survey allowed the researcher to investigate which authentication methods are given higher priority and why, along with the relationship between different usage patterns and perceived usability, and identify user misconceptions and insecure habits to determine ease of use. It was observed that the biometric-based method was given the utmost preferability.
Sequential Membrane Filtration to Recover Polyphenols and Organic Acids from Red Wine Lees: The Antioxidant Properties of the Spray-Dried Concentrate

The vinification process produces a considerable amount of waste. Wine lees are the second most generated byproduct, representing around 14% of total vinification wastes. They are a valuable source of natural antioxidants, mainly polyphenols, as well as organic acids, such as tartaric acid. This paper deals with the application of an integrated, environment friendly membrane separation process to recover polyphenols and organic acids. A two-step membrane process is described, consisting of an ultra- and a nano-filtration process. The physicochemical and antioxidant properties of all the process streams were determined. High Pressure Liquid Chromatography (HPLC) was employed for identifying certain individual organic acids and polyphenols, while the antioxidant potential was determined by the 2,2′-diphenyl-1-picrylhydrazyl radical) (DPPH) radical scavenging ability and ferric reducing ability. A liquid concentrate stream containing 1351 ppm of polyphenols was produced and then spray dried. The resulting powder retained most of the polyphenols and antioxidant properties and was successfully applied to a real food system to retard lipid oxidation, followed by Thiobarbituric Acid Reactive Substances (TBARS) and the determination of oxymyoglobin content. The results show that membrane separation technology is an attractive alternative process for recovering value-added ingredients from wine lees.
Simulations of Lightning Strokes near Transmission Lines in Urban Environments by Using the Finite-Difference Time-Domain Method

Numerical full-wave solutions of induced voltages on low-voltage energy lines due to atmospheric discharges on cell phone radio base stations (RBS), installed at the proximities of such lines, are presented for the first time in this work. Structures, such as towers and buildings, which present high structural complexity, have been modeled in order to obtain realistic results. In particular, this paper shows the importance of considering the effects related to real electrical conductivity and permittivity of the soil (in technical literature, PECs have been used to represent the soil in similar problems). For this purpose, a software has been developed in which Maxwell's equations are numerically solved by using a parallel implementation of the Finite-Difference Time-Domain Method (FDTD), producing full wave solutions for the problem. The thin wire formulation has been implemented for representing thin cylindrical electric conductors and transmission lines.