Miracle-dz/UniFAR-FTUs huggingface dataset:
Dendritic Silica Particles with Well-Dispersed Ag Nanoparticles for Robust Antireflective and Antibacterial Nanocoatings on Polymeric Glass

Robust nanocoatings with both antireflective (AR) and antibacterial properties for transparent plastic substrates are not only significantly attractive in science but also urgently needed in wide applications. However, it is still a great challenge to realize the fabrication of this kind of multifunctional nanocoatings on plastic/polymer substrates. In this work, a series of single-particle-layered nanocoatings were prepared by partially embedding dendritic fibrous nanosilica (DFNS) with well-dispersed Ag nanoparticles (NPs) onto the surface of poly(methyl methacrylate) (PMMA) polymeric glass via organic vapor treatment. The optimal coated PMMA slide not only exhibits the enhanced transmittance with the highest one of 94.5% but also shows excellent antibacterial activity (at least killing 80% bacteria) toward both Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli. Moreover, both long-term ultrasonic processing and pencil hardness tests proved strong adhesion of particles on PMMA subst.
Impedance matching control between a human arm and a haptic joystick for long-term

Abstract An impedance matching control framework between a human and a haptic joystick for long-term teleoperation is proposed in this research. An impedance model of the human arm is established analyzing the characteristics of human perception, decision, and action. The coefficients of the human arm’s impedance have been identified using a least squares method. The human arm’s impedance matching algorithm generates a corresponding motion vector for the human arm, which is determined by the interaction force measured by a force/torque sensor considering the impedance modeling of the human arm. The impedance control has been adopted for the haptic joystick to match the desired impedance to that of the human arm, which is aimed to minimize the energy consumption of the human arm for long-term teleoperation. By minimizing the fatigue of the operator, the remote control accuracy of the teleoperation can be improved. A PD control with gravity compensation algorithm has been adopted to maintain desired trajectory for the joystick by the operator more conveniently. The effectiveness of matching control has been demonstrated by trajectory following experiments for a mobile robot.
Drug risk perception and risk management strategies among Israeli functioning drug users: a qualitative exploration

Abstract Drug use studies have mainly examined risk management among vulnerable populations that are commonly categorized by their risk-taking behavior. They have not, however, investigated functioning users’ perceptions of risks and harms. The current study attempts to fill this gap by examining how functioning people who are in the process of building their careers or family lives perceive and manage the risks and harms of drug use. We interviewed 29 Israelis who use drugs, dividing them into two different groups: the first comprised 16 regular or previously regular cannabis users and one cocaine user who didn’t describe themselves as problematic users and were not in treatment; the second comprised 13 regular users of cannabis, methadone, MDA, and cocaine who described themselves as problematic users and were in treatment. We conducted content analysis of these interviews which refers to both risk management and harm management and defined three different options. The first option refers to participants who described feeling no risk or harm from their drug use. The second focuses on participants’ perceptions of the subjective risks and their ability to manage them via the following domains: social relationships, profession, social status, finances, and health and lifestyle. The third deals with participants who recognized the harms in the domains of family and social relationships, health, and daily functioning. An understanding of these three options could help counselors when encountering such users.
Reinforcement Learning Based, Staircase Negotiation Learning: Simulation and Transfer to Reality for Articulated Tracked Robots

Autonomous control of reconfigurable robots is crucial for their deployment in diverse environments. However, its development is hampered by the diversity of hardware and task constraints. We advocate the use of artificial intelligence-based approaches to improve scalability to different conditions and portability to platforms of comparable traversability skills. In particular, we succeed in tackling the problem of staircase traversal via a reinforcement learning (RL)-based control framework applicable to different articulated, tracked robots and powerful enough to generalize to varying conditions learned in simulation and transferred to reality in a zero-shot setting. Our extensive experiments demonstrate the robustness of the framework in learning tasks with increased risk and difficulty induced by platform diversification and increased control dimensionality.
Effect of solvent types on phenolics content and antioxidant activities of Acacia polyacantha gum

Acacia polyacantha gum (APG) is a dried exudate which obtained from the stems and branches of Acacia polyacantha trees. APG is rich in soluble dietary fibers as well as organic compounds. In this study quantitation of the levels of total phenolics content (TPC) and antioxidant activities were conducted using ABTS and CUPRAC assays for APG extraction using pure solvents (methanol, ethanol, acetone) and their aqueous mixtures at 50% and 100%. The antioxidant levels were evaluated by 2,2’-azino-bis-(3-mthylbenzothiazoline-6-sulfonic acid) (ABTS+) radical cation deculturization and cupric iron reducing capacity in the presence of neocuproine (CUPRAC) for the evaluation of reducing power, and (TPC) was evaluated by the Folin-Ciocalteu method. The solvent Methanol (50%) gave the best extraction ratio for APG presented by highest (TPC 60.78 mg GAE/100g of DW, CUPRAC 34.65 mg TE/100g DW, and, ABTS about 37.65 mg TE/100g DW respectively), followed by ethanol 50% extract. On the other hand, pure methanol showed the lowest TPC 5.33 mg GAE/100g of DW, ABTS 10.9 mg TE/100g DW, and CUPRAC 7.80 mg TE/100g DW, values respectively. Therefore, the variation in the antioxidant capacity of extracts was possibly due to the difference of polarity, immiscibility and the nature of the APG compounds extracted using various solvents. The higher content of antioxidant activity in APG shall be useful to human health if it is properly utilized.
Validation of the Arabic and French Versions of a Knowledge, Attitudes and Practices (KAP) Questionnaire on Tranquilizer Misuse

Tranquilizer misuse is an emerging international public health concern. The psychosocial determinants of this misuse remain understudied. Instruments to measure the Knowledge, Attitudes and Practices (KAP) of tranquilizer misuse are unavailable, except for a recently published questionnaire validated in the Spanish language. We translated the KAP questionnaire into Arabic and French, adapted it and undertook a complete validation procedure in the general adult population in Lebanon. The content validity indicators were good: item content validity index ranged between 0.89 and 1.00, the content validity index scale average was ≥0.95 and the modified Kappa statistic for each of the KAP items was equal to I-CVI. The intra-class correlation coefficient values (n = 100) were ≥0.62 for all Knowledge and Attitudes items, demonstrating the item reliability. Confirmatory factorial analysis (n = 1450) showed that the selected model of Knowledge and Attitude constructs has adequate fit indicators and encompassed three factors that showed acceptable internal reliability: Knowledge (Cronbach’s alpha = 0.72), personal Attitudes towards tranquilizers (Cronbach’s alpha = 0.79) and Attitudes towards healthcare providers (Cronbach’s alpha = 0.65). The Arabic/French questionnaire was highly accepted, with a response rate of 95.72% and item non-response rate ≤3.6%. The availability of a cross-cultural adapted and multilingual validated questionnaire would stimulate research on tranquilizer misuse.
Similarity Analysis of Modern Genre Music Based on Billboard Hits

Mainstream music can be popularly categorized into specific genres: Rock, Country, Hip Hop, contemporary rhythm and blues (R&B) and Pop. Music of these genres are continually complied on the Billboard music charts based on popularity. This paper explores the uniqueness of these genres and the possible melding of acoustic characteristics over time. Principal Component Analysis (PCA) are applied to timbral and non-timbral characteristics and compared for each genre. Results show that Hip Hop and Pop maintained a unique distinction over time compared to the other genres while Rock, Country and R&B began to share similar acoustic characteristics within recent times. Further analysis make an attempt to predict the trend of the acoustic nature of genres.
The effectiveness of schema therapy in offenders with intellectual disabilities: a case series design

ABSTRACT Background In forensic settings, patients with intellectual disabilities are overrepresented. A relative novel treatment approach for this population is schema therapy. The goals of schema therapy for offenders with intellectual disabilities are to reduce maladaptive emotional states and to reinforce healthy emotional states and enhancing the patient's ability to ask for help. No studies are examining the effectiveness of this approach. Method We examined the effectiveness of Schema Therapy for offenders with intellectual disabilities (ST-ID) in terms of emotional states, psychological complaints, and violence risk in six participants. Results Reliable change analyses showed significant improvements in emotional states and certain psychological complaints. Conclusions While many questions remain about the effectiveness of ST-ID, our study shows that offenders with ID can benefit from this psychological treatment.
Data-Injection-Proof-Predictive Vehicle Platooning: Performance Analysis With Cellular-V2X Sidelink Communications

The increasing demand for road freight has raised tremendous attention to vehicle platooning, which reduces air resistance and improves fuel economy. To achieve a small and safe spacing between vehicles while ensuring platoon stability, wireless communication assistance is indispensable. However, the imperfection of communication brings degradation of platooning performance (i.e., spacing error) and more possibilities for adversarial attacks. This article proposes a prediction-assisted platooning mechanism from the perspective of performance optimization, wherein each vehicle establishes its local platoon model based on the information received from the communication network, thereby reducing information latency. Then, to secure the system against malicious vehicles, we carry out analysis and design of a detection algorithm for a typical attack type, i.e., the data-injection attack. The detection is based on three indicators: 1) absolute spacing error; 2) spacing prediction error; and 3) acceleration prediction error. The advantages of the novel platooning mechanism and detection algorithm are ultimately demonstrated on a road-traffic simulation platform that considers the imperfection of realistic vehicle perceptions and Cellular-Vehicle-to-Everything (C-V2X) communication.
The development of mass spectrometry-based methodologies for the high throughput quantitation of peptides in biological matrices

The aim of this research was the development of mass spectrometry-based methodologies for the high-throughput quantitation of peptides in biological matrices. Glucagon and GLP-1, which are of interest as biomarkers and in the development of therapeutics, were chosen as model peptides. Immunoassays that are traditionally used to quantify these often perform poorly; therefore, necessitating the development of alternative methodologies. Application of mass spectrometry-based methodologies to these analytes has, however, been limited, primarily due to sensitivity challenges, but also due to analytical challenges associated with their endogenous nature and instability in biological matrices. Chapter 2 describes the development and qualification of the first liquid-chromatography coupled tandem mass spectrometry (LC-MS/MS) method for the quantitation of endogenous glucagon from human plasma. A novel 2D extraction procedure was developed to ensure robustness and sensitivity, whilst a novel surrogate matrix quantitation strategy took into account the endogenous nature of the analyte. A lower limit of quantitation (LLOQ) of 25 pg/mL was qualified, which was a considerable improvement over that previously reported in the literature (250 pg/mL) for a LC-MS/MS method. Clinical samples were cross-validated against a conventional radioimmunoassay (RIA), and similar pharmacokinetic (PK) profiles resulted, demonstrating that the methods were complementary. In Chapter 2 glucagon instability in biological matrix was noted. To characterise this further, in Chapter 3 in vitro glucagon metabolites were identified using high-resolution mass spectrometry (HRMS). Metabolites observed by others (glucagon19-29, glucagon3 29 and [pGlu]3glucagon3 29) in alternative matrices were identified, alongside novel metabolites (glucagon20-29 and glucagon21-29). Cross-interference of these metabolites in immunoassays may help to explain their poor performance, whilst knowledge of metabolism may also aid the development of future stabilisation strategies. The method developed in Chapter 2 was refined in Chapter 4 to improve sensitivity, robustness and throughput, and to add GLP-1 as a secondary analyte. The sensitivity achieved (glucagon: 15 pg/mL LLOQ, GLP-1: 25 pg/mL LLOQ) is the highest reported for both peptides for an extraction avoiding immunoenrichment. Specificity of endogenous glucagon quantitation was assured using a novel approach with a supercharging mobile phase additive to access a sensitive qualifier transition. A cross-validation against established immunoassays using physiological study samples demonstrated some similarities between the methods. Differences between the immunoassay results exemplified the need to develop alternative methodologies. The resulting LC-MS/MS method is considered a viable alternative to immunoassays, for the quantitation of endogenous glucagon, dosed glucagon and/or dosed GLP-1 in human plasma.
Impact of Extra-curricular Activities on Students’ Academic Performance at Bhutanese HSS level: A Case of Orong Central School

The purpose of the study was to investigate the impact of extracurricular activities on the academic performance and students’ assessment towards the extra-curricular activities at higher secondary school ( HSS) level. The sample consisted of 156 students from five different classes (IX-XII). The classes were selected randomly. The study used a mixed method approach. The quantitative component integrated was 24 items of 4 Likert scale survey questionnaires categorized under three themes. The qualitative component incorporated students’ assessment on impact of extracurricular activities in academic performance were collected through open-ended questions. Data form survey questionnaires were analyzed using descriptive analysis (means and standard deviation) and inferential t-test was use for analysis of hypothesis. The qualitative raw date was thematically analyzed (transcribed, coded and categorized). The findings of the study indicated that that student who participated in extra-curricular activities either in Games or sports activities have high academic performance as compared to those who did not participate. It is recommended that the school should give facilities and proper time to the participants of extra-curricular activities and ensure every student’s participation.
3D Detection and Tracking for On-road Vehicles with a Monovision Camera and Dual Low-cost 4D mmWave Radars

High resolution 4D millimeter wave radar has been increasingly used for robust 3D detection and tracking of on-road vehicles. Rich point clouds generated by 4D radars can not only provide more reliable detection in harsh weather environments, but also offers 3D tracking capabilities for on-road objects. In this paper, a convolutional neural network (CNN) with cross fusion strategy is proposed for 3D on-road vehicle detection. The trained CNN model was also tested with dual low-cost 4D millimeter wave radars and a single monovision camera. An extended version of radar-camera calibration in three dimensions and 3D tracking with an extended Kalman filter (EKF) were also presented. The detection results showed that the proposed convolutional neural network model outperformed the one used on the Astyx dataset which provided up to 1500 radar detection points, on average, per frame.
Rigorous silica solubility estimation in superheated steam: Smart modeling and comparative study

One of the main issues of wastewater treatment is the silica deposition in steam turbines. Evaporation of silica with the steam in adequate concentration is one of the main sources of scale formation in steam turbines. In this study, the authors introduce the utilization of a genetic‐based approach—gene expression programming (GEP)—for solubility prognostication of the silica in superheated steam of boilers with respect to water silica content and pressure. The result of GEP mathematical approach is a new algebraic formula to achieve our goals. Developed model predicts the silica solubility in the range of 0.8–22.1 MPa and 1–500 mg/kg for pressure and boiler water silica content, respectively. The results show that the constructed model outperforms pre‐existing method and provides acceptable predictions with average absolute relative deviation (AARD%) of 9.46% and determination coefficient (R2) of 0.98. Outcomes of the performed sensitivity analysis reveal that the effect of pressure is more pronounced than the impact of the boiler water silica content on the estimation of the silica solubility. Moreover, an outlier analysis based on Leverage approach was performed confirming the validity of the used database in this study. Finally, it can be concluded that the recommended tool in this study can be a suitable candidate for prognosticating the silica scaling in industries dealing with steam. © 2018 American Institute of Chemical Engineers Environ Prog, 38:e13089, 2019
Control Barrier Function-based Lateral Control of Autonomous Vehicle for Roundabout Crossing

A lateral control scheme is presented to control Autonomous Vehicles (AVs) utilizing the nonlinear dynamics of the vehicle, based on the concepts of Control Lyapunov Functions (CLFs) to enforce stability and High Order Control Barrier Functions (HOCBFs) to impose safety constraints for the vehicle. The control input is then calculated using Quadratic Programming (QP) optimization while limiting the control input due to vehicle limitations and passenger comfort at a roundabout crossing. Simulation results are presented to show the performance of the proposed lateral controller.
Toward the Sustainable Synthesis of Propanols from Renewable Glycerol over MoO3-Al2O3 Supported Palladium Catalysts

The catalytic conversion of glycerol to value-added propanols is a promising synthetic route that holds the potential to overcome the glycerol oversupply from the biodiesel industry. In this study, selective hydrogenolysis of 10 wt% aqueous bio-glycerol to 1-propanol and 2-propanol was performed in the vapor phase, fixed-bed reactor by using environmentally friendly bifunctional Pd/MoO3-Al2O3 catalysts prepared by wetness impregnation method. The physicochemical properties of these catalysts were derived from various techniques such as X-ray diffraction, NH3-temperature programmed desorption, scanning electron microscopy, 27Al NMR spectroscopy, surface area analysis, and thermogravimetric analysis. The catalytic activity results depicted that a high catalytic activity (>80%) with very high selectivity (>90%) to 1-propanol and 2-propanol was obtained over all the catalysts evaluated in a continuously fed, fixed-bed reactor. However, among all others, 2 wt% Pd/MoO3-Al2O3 catalyst was the most active and selective to propanols. The synergic interaction between the palladium and MoO3 on Al2O3 support and high strength weak to moderate acid sites of the catalyst were solely responsible for the high catalytic activity. The maximum glycerol conversion of 88.4% with 91.3% selectivity to propanols was achieved at an optimum reaction condition of 210 ∘ C and 1 bar pressure after 3 h of glycerol hydrogenolysis reaction.
Plasma-relevant electron scattering cross sections of propene

Propene (C3H6) is considered to be an important molecule in the field of plasma science due to it being recognized as a by-product of plasma irradiation at the diverter regions and plasma facing walls in modern fusion devices. This article reports electron scattering elastic, momentum transfer, differential and excitation cross sections of propene. The rate coefficients for the elastic and momentum transfer cross sections are also reported. The data reported in this article are considered to be important in the field of plasma physics due to their direct influence on plasma modeling applications. Two theoretical methods were used for the present study; the R-matrix method for low energy and spherical complex optical potential formalism for high energy. The R-matrix calculation was performed using the correlation-consistent polarized valence-only triple-zeta basis set and a reasonable agreement with the target properties was obtained. The scattering calculations were then performed using these parameters to compute various cross sections. The present cross sections compare reasonably well with the only available data in the literature. More experimental studies of a similar nature are encouraged for the validation of the present results.
Comparison of Machine Learning Methods towards Developing Interpretable Polyamide Property Prediction

Polyamides are often used for their superior thermal, mechanical, and chemical properties. They form a diverse set of materials that have a large variation in properties between linear to aromatic compounds, which renders the traditional quantitative structure–property relationship (QSPR) challenging. We use extended connectivity fingerprints (ECFP) and traditional QSPR fingerprints to develop machine learning models to perform high fidelity prediction of glass transition temperature (Tg), melting temperature (Tm), density (ρ), and tensile modulus (E). The non-linear model using random forest is in general found to be more accurate than linear regression; however, using feature selection or regularization, the accuracy of linear models is shown to be improved significantly to become comparable to the more complex nonlinear algorithm. We find that none of the models or fingerprints were able to accurately predict the tensile modulus E, which we hypothesize is due to heterogeneity in data and data sources, as well as inherent challenges in measuring it. Finally, QSPR models revealed that the fraction of rotatable bonds, and the rotational degree of freedom affects polyamide properties most profoundly and can be used for back of the envelope calculations for a quick estimate of the polymer attributes (glass transition temperature, melting temperature, and density). These QSPR models, although having slightly lower prediction accuracy, show the most promise for the polymer chemist seeking to develop an intuition of ways to modify the chemistry to enhance specific attributes.