Miracle-dz/UniFAR-FTUs huggingface dataset:
THE EFFECT OF SPIRITUAL EMOTIONAL FREEDOM TECHNIQUE (SEFT) THERAPY METHODS ON CHANGES IN ADOLESCENT SMOKING BEHAVIOR

Smoking behavior in adolescents is a difficult behavior to change. In cigarettes there are addictive ingredients that make dependence on the wearer. The phenomenon obtained in Bendungan Village, there are 42 teenagers aged 15-19 years who have smoking behavior due to invitations from friends, curiosity, often seeing parents smoking and the desire of teenagers themselves. The Spiritual Emotional Freedom Technique (SEFT) method by tapping 2 fingers on 18 key points in the body's 12 energy pathways. The purpose of this study was to determine the effect of the SEFT therapy method on changes in smoking behavior in adolescents in Bendungan Village, Pabelan District, Semarang Regency. The research design used is a quantitative method using a pre-experimental type with a one group pretest-posttest design. The sampling technique used 30 respondents. The research instrument is a questionnaire that has been tested for validity in research (Anggraeni, 2019) with the title "Peer Peer Relationships with Smoking Behavior in Early Adolescents" the number of respondents in this assessment is 15 people with an r value of 0.518 provided that the value of r product moment > r table (0.514), then it is declared valid. The analytical method used is Paired Sample T-test. The results showed that smoking behavior before SEFT therapy was in the moderate category (86.7%) than after being given SEFT therapy in the good category (63.3%). The results of the analysis with the Paired Sample T-test test obtained p value = 0.000 means p value
Effects of sliding window variation in the performance of acceleration-based human activity recognition using deep learning models

Deep learning (DL) models are very useful for human activity recognition (HAR); these methods present better accuracy for HAR when compared to traditional, among other advantages. DL learns from unlabeled data and extracts features from raw data, as for the case of time-series acceleration. Sliding windows is a feature extraction technique. When used for preprocessing time-series data, it provides an improvement in accuracy, latency, and cost of processing. The time and cost of preprocessing can be beneficial especially if the window size is small, but how small can this window be to keep good accuracy? The objective of this research was to analyze the performance of four DL models: a simple deep neural network (DNN); a convolutional neural network (CNN); a long short-term memory network (LSTM); and a hybrid model (CNN-LSTM), when variating the sliding window size using fixed overlapped windows to identify an optimal window size for HAR. We compare the effects in two acceleration sources’: wearable inertial measurement unit sensors (IMU) and motion caption systems (MOCAP). Moreover, short sliding windows of sizes 5, 10, 15, 20, and 25 frames to long ones of sizes 50, 75, 100, and 200 frames were compared. The models were fed using raw acceleration data acquired in experimental conditions for three activities: walking, sit-to-stand, and squatting. Results show that the most optimal window is from 20–25 frames (0.20–0.25s) for both sources, providing an accuracy of 99,07% and F1-score of 87,08% in the (CNN-LSTM) using the wearable sensors data, and accuracy of 98,8% and F1-score of 82,80% using MOCAP data; similar accurate results were obtained with the LSTM model. There is almost no difference in accuracy in larger frames (100, 200). However, smaller windows present a decrease in the F1-score. In regard to inference time, data with a sliding window of 20 frames can be preprocessed around 4x (LSTM) and 2x (CNN-LSTM) times faster than data using 100 frames.
Synthesis of Robust Lane Keeping Systems: Impact of Controller and Design Parameters on System Performance

The lane keeping system (LKS), a promising driver assistance system, is essential for autonomous vehicles. In real-world road conditions, it can be quite challenging because LKS must stay within the lane without causing passenger discomfort while both disturbances (e.g., road curvature, wind gusts, and hydroplaning) and model uncertainties in parameters [e.g., vehicle mass, center of gravity (CG), and tire cornering stiffness] are present. In this paper, the performance limits and tradeoffs between three performance criteria (lane tracking, stability robustness, and passenger comfort) are first investigated by exploring the entire design space of three prominent controllers, i.e., proportional–integral–derivative, linear–quadratic–Gaussian, and H-infinity ( $\text{H}_{\infty }$ ). Then, a sensitivity study on the vehicle parameters is conducted in order to investigate the impact of the parameters on the three performance metrics. Based on the aforementioned studies, this paper concludes that a robust controller can provide the maximum performance limit with respect to the lane tracking and stability robustness, when properly designed. However, it is observed that the robust controller is still sensitive to a few design and model parameters, such as look-ahead distance and CG. Therefore, the sensitivity study suggests that for vehicles with excessive mass and CG changes, such as SUVs and trucks, the adaptation of controller and look-ahead distance may be necessary to maximize both tracking performance and passenger comfort over a wide range of vehicle speeds.
Family Dysfunction and Cyberchondria among Chinese Adolescents: A Moderated Mediation Model

Cyberchondria has become a severe health problem and a significant public concern. In addition to the impacts that cyberchondria involves, individual psychological and behavioral factors have been identified. However, the role of family function and the mediating and moderating mechanisms underlying these relations are not understood well, especially among adolescents. Based on family functioning and cognitive-behavioral theory, this study sought to examine whether family dysfunction was associated with cyberchondria, and a moderated mediation model was prepared as a means of exploring whether health anxiety was a mediator of relationships between family dysfunction and cyberchondria, as well as whether optimism moderated these mediating processes. A total of 2074 Chinese adolescents (mean = 15.08 years, SD = 1.79) reported their demographic information, family dysfunction, health anxiety, optimism, and cyberchondria. The findings showed that family dysfunction was positively related to cyberchondria. Moreover, health anxiety partially mediated the relationship between family dysfunction and cyberchondria. Finally, optimism moderated the interplay among health anxiety and cyberchondria. Consistent with the expectancy-value models, this positive relationship was weaker for adolescents with a higher level of optimism. These results suggest that it is vital to simultaneously consider individual and family factors as a means of understanding adolescent cyberchondria when performing cyberchondria intervention programs.
Molecular Characterization of Wolbachia in Rugose Spiralling Whitefly Aleurodicus rugioperculatus and its Parasitoid Encarsia guadeloupae

Wolbachia is a common maternally inherited bacterial endosymbiont of insects. Many species of whiteflies and their endoparasitoids exhibit interspecific variations/ species complexes which can be analysed through the variations between the host and the parasitoid using molecular markers. This study characterized the occurrence of Wolbachia in the whitefly Aleurodicus rugioperculatus and its parasitoid Encarsia guadeloupae. The Wolbachia surface protein(wsp) (450-600 bp) sequenced from the host-parasitoid collected from the field populations at Karnataka was analysed. The comparison of these sequences in the NCBI database through BLAST and ORF analysis revealed the presence of two new sequences infected with Wolbachia from the samples collected on the coconut palms (Cocos nucifera). The genetic relatedness of these has been brought out using the wsp gene through PCR.
Bacteriocin‐phage interaction (BaPI): Phage predation of Lactococcus in the presence of bacteriocins

Bacteriophages infecting dairy starter bacteria are a leading cause of milk fermentation failure and strategies to reduce the risk of phage infection in dairy settings are demanded. Along with dairy starters, bacteriocin producers (protective cultures) or the direct addition of bacteriocins as biopreservatives may be applied in food to extend shelf‐life. In this work, we have studied the progress of infection of Lactococcus cremoris MG1363 by the phage sk1, in the presence of three bacteriocins with different modes of action: nisin, lactococcin A (LcnA), and lactococcin 972 (Lcn972). We aimed to reveal putative bacteriocin‐phage interactions (BaPI) that could be detrimental and increase the risk of fermentation failure due to phages. Based on infections in broth and solid media, a synergistic effect was observed with Lcn972. This positive sk1‐Lcn972 interaction could be correlated with an increased burst size. sk1‐Lcn972 BaPI occurred independently of a functional SOS and cell envelope stress response but was lost in the absence of the major autolysin AcmA. Furthermore, BaPI was not exclusive to the sk1‐Lcn972 pairing and could be observed with other phages and lactococcal strains. Therefore, bacteriocins may facilitate phage predation of dairy lactococci and their use should be carefully evaluated.
Lumbar Disk Herniation: A Clinical Epidemiological and Radiological Evaluation

BACKGROUND: A herniated disc in the spine is a condition during which a nucleus pulposus is displaced from intervertebral space. AIM: The study aimed to investigate and observe variation of clinical, epidemiological, and radiological aspects for patients suspected of lumbar herniation based on observed evaluation of CT and MRI imagery. METHODS: This is a cross-sectional study conducted during the periods March 2015 and November 2019. Patients were subjected to MRI and CT based on the emergency or scheduled of diagnose. All MRI scans were obtained with 1.5 tesla MRI machine and for CT had undergone examinations with one of the following equipment: Siemens with 128 slice and Phillips 64 slice. The patients were placed in supine position. RESULTS: Overall 194 symptomatic patients were recruited as a participant in this study, 118 men and 76 women with an average age of 44.9 ±10.4 years. Patients belong to the active age (35–44-years-old and 45–54-years-old) appeared to have the highest percentage of lumbar disk herniation (LDH) 30.9% and 25.8%, respectively. There were a significant association between such as epidemiological data (such as gender, BMI, age groups, and employment status) and presence of LDH, p ˂ 0.05. Acute pain was presented in 69.07% of patients and according to complaint associated with low back pain (LBP), most of them 47.4% appeared with Right Sciatica. MRI is the most diagnostic methods used in evaluation of LDH in 52% of patients, and CT was used in 48% of them. The most common changes were between L2-L3, L3-L4, and L4-L5. Furthermore, the grading findings which corresponding to lumbosacral segment were Grade I and Grade II. Grade V was less common. CONCLUSION: This study involving patients with lumbar disk herniation and associated LBP showed that a combination of clinical features and epidemiological predicted the presence or absence of a significant association. Further research is required to validate these findings in different types of LDH and LBP for other findings and conditions.
Early neurodevelopmental problems and risk for avoidant/restrictive food intake disorder (ARFID) in 4‐7‐year‐old children: A Japanese birth cohort study

Abstract Background An overrepresentation of neurodevelopmental problems (NDPs) has been observed in individuals with avoidant/restrictive food intake disorder (ARFID). Previous studies on the association between ARFID and NDPs have been limited by cross‐sectional data from clinical samples of small size. This study aimed to extend previous research by using prospectively collected data in a non‐clinical child cohort. We examined the occurrence of early NDPs in 4–7‐year‐old children with suspected ARFID and how predictive early NDPs are of ARFID. Methods Data were collected via parent‐report a sub‐sample of the Japan Environment and Children's Study (JECS) including 3728 children born 2011–2014 in Kochi prefecture. NDPs were assessed biannually between 0.5 and 3 years of age with the Ages and Stages Questionnaire‐3, at age 2.5 years with the ESSENCE‐Q, and at age 1 and 3 years via parent‐reported clinical diagnoses. ARFID was identified cross‐sectionally (at age 4–7 years) using a newly developed screening tool. Logistic regressions were used to test association of (1) a composite early NDP risk score, (2) specific early NDPs, and (3) neurodevelopmental trajectories over time with ARFID. Results Children in the highest risk percentiles of the NDP risk score had roughly three times higher odds of having suspected ARFID; the absolute risk of later ARFID for children above the 90th percentile was 3.1%. Early NDPs (excluding early feeding problems) were more predictive of later ARFID than were early feeding problems. Specific NDPs predictive of ARFID were problems with general development, communication/language, attention/concentration, social interaction, and sleep. Neurodevelopmental trajectories of children with and without suspected ARFID started to divert after age 1 year. Conclusions The results mirror the previously observed overrepresentation of NDPs in ARFID populations. In this non‐clinical child cohort, early feeding problems were common and rarely developed into ARFID; however, our findings imply that they should be monitored closely in children with high NDP risk to prevent ARFID.
Nonlinear Hybrid Piezoelectric and Electromagnetic Energy Harvesting Driven by Colored Excitation

It is well known that when excited by a stochastic base acceleration, the power absorbed by a nonlinear Duffing-type piezoelectric (PE) or electromagnetic (EM) energy harvester might not be increased effectively compared to a linear one. When intentionally introducing nonlinear magnetic forces into a doubly-clamped hybrid PE and EM energy harvester subjected to narrow-band (colored) excitation however, the power output could be improved to a much higher value. Also, in comparison with the typical nonlinear PE or EM generator, the influence of load and excitation parameters on the performance of a nonlinear hybrid energy harvester under colored excitation has been proven rather different as well. These results are derived analytically by solving the Fokker-Planck (FP) equation, and numerically by Monte Carlo (MC) simulations for validation. Besides, for a nonlinear hybrid configuration excited by colored noise approaching white Gaussian excitation, theoretical output characteristics are discussed and compared with results from a reported theory for white Gaussian excited case, which again verifies the feasibility of the theoretical analysis.
Incorporating Sparse and Quantized Carbohydrates Suggestions in Model Predictive Control for Artificial Pancreas in Type 1 Diabetes

People with type 1 diabetes (T1D) face the challenge of administering exogenous insulin to maintain blood glucose (BG) levels in a safe physiological range, so as to avoid (possibly severe) complications. By automatizing insulin infusion, the artificial pancreas (AP) assists patients in this challenge. While insulin can decrease BG, having another input inducing glucose increase could further improve BG control. Here, we develop a model predictive control (MPC) algorithm that, in addition to insulin infusion, also provides suggestions of carbohydrates (CHOs) as a second, glucose-increasing, control input. Since CHO consumption has to be manually actuated, great care is paid in limiting the extra burden that may be caused to patients. By resorting to a mixed logical-dynamical MPC formulation, CHO intake is designed to be sparse in time and quantized. The algorithm is validated on the UVa/Padua T1D simulator, a well-established large-scale model of T1D metabolism, accepted by Food and Drug Administration (FDA). Compared with an insulin-only MPC, the new algorithm ensures increased time spent in the safe physiological range in 75% of patients. The improvement is limited for those already well controlled by the state-of-art strategy but relevant for the others: the 25th percentile of this metric is increased from 74.75% to 79.06% in the population. This is achieved while simultaneously decreasing time spent in hypoglycemia (from 0.5% to 0.12% in median) and with limited manual interventions (2.86 per day in median).
Implementation of Autonomous Vehicle Technology using Renewable Source

: The fuel demand is pinnacle, this can be tackled by electric origin. A renewable source for electric energy is making elegant adaptation in this trendy globe. In forth coming days renewable electric source will be a lofty revolution and it also aids the society. The utility of renewable energy with self-driving technology will be a progressive novelty & Eco friendly. The competence of e-car is in hike, when paired to the fuel car. The smog is enhancing a drastical issue in this universe, and it has a impact over the sustenance, but it can be winced by this project. The IR sensors are used as an obstacle detector, the IR addresses a wide variety of wireless applications. The IR sensor emits and detects infra-red radiation to sense it surrounding. The basic concept of an IR sensor used as a obstacle detector is to transmit an IR signal. This IR signal bounces from the surface of an object and the signal is received at IR receiver. In the electromagnetic spectrum, the IR protection is divided into 3 regions.
Future Activities Prediction Framework in Smart Homes Environment

Smart homes have been recently important sources for providing Activity of Daily Living (ADL) data about their residents. ADL data can be a great asset while analyzing residents’ behavior to provide residents with better and optimized services. A popular example is to analyze residents’ behavior to predict their future activities and optimize smart homes performance accordingly. This paper proposes a forecasting framework that utilizes ADL data to predict residents’ next activities in a smart home environment. Forecasting is performed via the conjunction of embedding algorithm to encode the data and Bidirectional Long Short-Term Memory (BiLSTM) deep neural networks to process the data. The proposed framework is evaluated over five real ADL datasets where the experiments show the outperformance of the proposed framework with accuracy scores ranging from 98.7% to 93.8%.
A new host record for the invasive thrips Thrips parvispinus Karny from India

The present study on the diversity of thrips on cotton in Tamil Nadu revealed the occurrence of the invasive species Thrips parvispinus Karny during kharif 2019-20. The thrips were found to occur on Gossypium barbadens variety Suvin. The diagnostics of this species are illustrated herein. The status of new record is also discussed.
DEVELOPMENT OF A SUBJECT SPECIFIC FINITE ELEMENT MODEL USED TO PREDICT THE EFFECTS OF A SINGLE LEG EXTENSION EXERCISE

The study presented attempts to prove the concept that mechanical changes in the structure of a bone can be predicted for a specific exercise by a subject specific model created from CT data, MRI data, EMG data, and a physiologic FE model. Previous work generated a subject specific FE model of a femur via CT and MRI data as well as created a set of subject specific biomechanical muscle forces that are required to perform a single leg extension exercise. The FE model and muscle forces were implemented into a single leg extension FE code (ABAQUS) along with a specialized bone remodeling UMAT. The UMAT updated the mechanical properties of the femur via a damage-repair bone remodeling algorithm. The single leg extension FE code was verified by applying walking loads to the femur and allowing the system to equilibrate. The results were used to apply the appropriate walking loads to the final FE simulation for the single leg extension exercise. The final FE simulation included applying the single leg extension loads over a one year period and plotting the change in porosity at various regions of the femoral neck. Although only two regions were found to generate valid results, the data seemed counterintuitive to Wolff's Law which states that bone adaptation is promoted when the material is stressed. The model was successful in creating a subject specific model that is capable of predicting changes in the mechanical properties of bone. However, in order to generate valid FE model results, further understanding of the bone remodeling process and application via a FE model is required.
Dual-Circularly Polarized Array Antenna Based on Gap Waveguide Utilizing Double-Grooved Circular Waveguide Polarizer

This article presents a dual-circularly polarized array antenna based on gap waveguide technology operating at E-band. Double-grooved circular waveguide polarizers that utilize two annulus grooves placed at 45° and 135° offset from both excitation ports are used in this work. The operating principles of the polarizer are analyzed. Multilayer design using gap waveguide is implemented on the basis of the polarizer. The antenna consists of six layers, including three layers for the feeding networks, one layer for the polarizer, one layer of back cavity, and another layer of radiating grid. A 2 $\times $ 2 unit cell is proposed first and employed to realize an 8 $\times $ 8 planar array. Corporate feeding networks that use compact E-plane T-junctions and H-plane T-junctions are proposed. The antenna has been fabricated and verified by measurements. The measured results of S-parameters agree well with the simulation and show that reflection coefficients are better than −10 dB for both circular polarizations (CPs) from 76 to 81 GHz. The measured isolation between the input ports is larger than 25 dB in the operating band. The far-field measurements show that the antenna has realized gain larger than 24 dBi and axial ratios less than 1.5 dB from 76 to 81 GHz at boresight direction.
Recategorization of Conservation Units in Brazil: A systematic literature review

The Brazilian National System of Conservation Units (SNUC) has a wide spectrum of conservationist strategies, so that often the choice of a protected area typology is not adequate to the proposed conservation objectives. The recategorization of a Conservation Unit (CU) is a legal and widely used procedure to resolve conflicts of interest that exist even before the SNUC implementation. This research carried out a Systematic Literature Review (SLR) with the objective of identifying the methods applied in recategorizations and factors that led to the occurrence of this phenomenon in Brazilian CUs. Three bibliographic databases (Research gate, PubMed and Repositório UFSC) were searched, in addition to Google Scholar, obtaining total number of 1,068 articles. The results indicate increase in the number of publications on the theme in the last three years, and that there are twenty methods used in CU recategorization processes in Brazil. A variation of instruments used for recategorization was also identified, and it was found that in most cases, more than one instrument is used, with the implementation of a decree or law being the most used. Several factors are also responsible for recategorization, being territorial conflicts and their overlapping on traditional communities the most relevant.