Miracle-dz/UniFAR-FTUs huggingface dataset:
Adjunctive High-Definition Transcranial Direct Current Stimulation in Brain Glutamate-Glutamine and γ-Aminobutyric Acid, Withdrawal and Craving During Early Abstinence Among Patients With Opioid Use Disorder on Buprenorphine-Naloxone

Objective Our study aimed to (1) examine the effect of adjunctive high-definition transcranial direct current stimulation (HD-tDCS) in craving and withdrawal among patients with opioid use disorder on buprenorphine-naloxone, and (2) examine effect of HD-tDCS changes in glutamate-glutamine and γ-aminobutyric acid (GABA) at the left dorsolateral prefrontal cortex (DLPFC) among patients with opioid use disorder on buprenorphine-naloxone. Methods This was a pilot randomized double-blind, sham-controlled parallel-group study. A total of 28 patients on buprenorphine-naloxone (6/1.5 mg/d) were randomly allocated into 2 groups for active and sham HD-tDCS stimulation. High-definition transcranial direct current stimulation was administered twice daily for consecutive 5 days, from days 2 to 6. The Clinical Opiate Withdrawal Scale (COWS), the Desire for Drug Questionnaire (DDQ), the Obsessive-Compulsive Drug Use Scale (OCDUS), and glutamate-glutamine and GABA at DLPFC via proton magnetic resonance spectroscopy were measured at baseline and on day 7. Results Both active and sham groups had comparable changes in DDQ, OCDUS (except 2 subcomponents), COWS, and glutamate-glutamine and GABA at DLPFC. In the active HD-tDCS group, statistically significant reductions were observed in DDQ, OCDUS, and COWS but not in glutamate-glutamine and GABA. Conclusions The adjunctive active HD-tDCS group showed comparable changes in craving and withdrawal, and glutamate-glutamine and GABA at DLPFC compared with sham HD-tDCS. Craving and withdrawal but not glutamate-glutamine and GABA at DLPFC decreased significantly with adjunctive HD-tDCS. Future studies with larger sample size and online assessment of glutamate-glutamine and GABA would enhance our knowledge.
Dynamics of a Fractional-Order Chikungunya Model with Asymptomatic Infectious Class

In this paper, a nonlinear fractional-order chikungunya disease model that incorporates asymptomatic infectious individuals is proposed and analyzed. The main interest of this work is to investigate the role of memory effects on the dynamics of chikungunya. Qualitative analysis of the model's equilibria showed that there exists a threshold quantity which governs persistence and extinction of the disease. Model parameters were estimated based on the 2015 weekly reported cases in Colombia. The Adams-Bashforth-Moulton method was used to numerically solve the proposed model. We investigated the role of asymptomatic infectious patients on short- and long-term dynamics of the diseases. We also determined threshold levels for the efficacy of preventative strategies that results in effective management of the disease. We believe that our model can provide invaluable insights for public health authorities to predict the effect of chikungunya transmission and analyze its underlying factors and to guide new control efforts.
Cycle Time and Human Fatigue Minimization for Human-Robot Collaborative Assembly Cell

Human fatigue, which is one of the main causes of efficiency decline and health damage, cannot be overlooked in the task scheduling of HRC that is becoming one of the latest frontiers of manufacturing. In this letter, we proposed a task scheduling model that integrated micro-breaks within job-cycles to provide recovery from fatigue accumulation by taking advantage of the characteristic of HRC. Furthermore, an improved Chemical Reaction Optimization (CRO) algorithm is developed to solve the trade-off between cycle time and human fatigue. Greedy strategy is applied in the global and local search reaction of CRO to solve the multi-objective problem which includes two conflicting goals of cycle time and fatigue minimization. The proposed model and algorithm are demonstrated on assembly cases inspired by an industry application. The results from the case study suggest that the proposed model outperforms the comparison model. Finally, computational results have demonstrated that the superiority of the proposed algorithm is proved by comparing with genetic algorithm (GA), imperialist competitive algorithm (ICA), and standard CRO.
Sensorimotor norms for Chinese nouns and their relationship with orthographic and semantic variables

ABSTRACT Sensorimotor information is vital to the conceptual representation of our knowledge system. This study collects perceptual and action ratings for 664 disyllabic nouns among 438 native speakers and creates the first and largest dataset of sensorimotor norms for nouns in Chinese. Using aggregated semantic covariates, including concreteness ratings from a concreteness rating study, as well as the reaction times and error rates from a lexical decision study, our current work demonstrates the strengths of sensory modalities and action effectors in Chinese nouns and explores the contributions of embodied experiences in reflecting orthographic representations and semantic processing in the Chinese language. This study contributes valuable data sources to the study of Chinese lexical processing and highlights the importance of sensorimotor information and embodied manifestations in the semantic representations of concepts. Our results also support the language universal that orthographic awareness in lexical processing and reading supersedes phonological awareness.
The Impact of Microsponge and Microsphere on Improving Oral Bioavailability of Medications: A Short Review

While many diseases require an efficient drug delivery technology that has the ability to improve bioavailability and alleviate side effects, various types of gastroretentive drug delivery systems (GRDDS) have been developed in order to overcome the obstacles, which are related to a narrow absorption window, instability, site of action, side effects, and dosing frequency. In this context, microsponge and microsphere systems depict two different types of GRDDS, aiming to provide adequate time for active ingredients to be absorbed in the stomach despite the variation in releasing mechanisms of the entrapped ingredients. For the successful designing of these systems, it is essential to optimize the characterizations of the formulated microparticles by considering physiological, pharmaceutical, and patient-related factors, which have a dramatic impact on the efficacy. Consequently, they will demonstrate different behaviors at the desired site of action, determining which systems are showing superiority compared to others. However, each microparticle system has some advantages over the others, providing more options for researchers to ease the difficulties that exist with conventional oral dosage forms. Therefore, this review aims to shed the light on critical factors that have significant impacts on microsponge and microsphere systems and addresses their advantages and disadvantages, providing an understanding of these criteria in order to optimize the drug systems.
Practical Demonstration of 5G NR Transport Over-Fiber System with Convolutional Neural Network

This study describes an experimental realization using digital predistortion (DPD) for a fifth generation (5G) multiband new radio (NR) optical front haul (OFH) based Radio over Fiber (RoF) link. For the performance enhancement and complexity reduction of RoF links, a novel Convolutional Neural Network (CNN) based DPD technique is proposed, followed by comparisons with the generalised memory polynomial (GMP) based DPD method. To support enhanced mobile broad band scenario, the experimental testbed uses the 5G NR waveforms at 10 GHz with 20 MHz bandwidth and a flexible-waveform signal at 3 GHz with 20 MHz bandwidth. For 10 km of typical single mode fiber, a Mach Zehnder Modulator with two distinct radio frequency waveforms modulates a 1310 nm optical carrier utilizing distributed feedback laser. The error vector magnitude and number of estimated coefficients, and multiplications are all used to describe the experimental outcomes. The goal of the research is to see if CNN-based DPD improves performance while lowering complexity levels to meet 3GPP Release 17 criteria.
Design and Implementation of Training Simulator System for Photoelectric Collimator Based on Personal Computer

Photoelectric collimator is a kind of simple fire-control system equipped on a weapon system. Training simulator system for photoelectric collimator is designed for the manual operation of photoelectric collimator. Firstly, this paper introduces the principle of photoelectric collimator, and then brings out a principle of design for the simulator. Then details the composition of system hardware of simulator and brings out the flow of work of system software . At last, analyses the factor influencing the system of simulator. This project is of great value to the development of analogous simulating system.
Theoretic Studies of the Three-moment Equation and Its Application in the Vessel's Propulsion Shafting Alignment

The design quality of vessel's propulsion shafting is decided by the operation r eliability of the power plant. The shafting check calculation is absolutely nece ssary and the alignment calculation is the crux of the matter. Therefore, it is e ssential to carry out the studies of calculation theory and its application. The theoretic studies of the traditional three-moment equation were carried throug h in three respects by taking the additive moment, uniform load and shear deform ation of the shafting into consideration. Then the general three-moment equatio n, which meet the vessel's propulsion shafting alignment's needs well, was put f orward and was used in the shafting alignment calculation software. Compared wit h the correlative foreign authoritative software, the results of calculation wer e consistent, which proves that it was correct and available.
Generating direct diamond shaping tool paths using special-purpose computer-aided-machining post-processor

ABSTRACT Ultra-precision direct diamond shaping (DDS) is an attractive method for manufacturing highly accurate and complex features. DDS employs 4 of the 5-axes in an Ultra-Precision Machine (UPM) with a conventional diamond tool to machine features on a workpiece mounted on a rotary axis. It has been proven to be effective and flexible in manufacturing intricate features, from microfluidics to Fresnel lenses. However, a significant technical hurdle in the practical implementation of DDS is the complexity of its non-conventional tool path generation. Current practices in generating DDS tool paths rely on programming and significant mathematical manipulation. This is not only time consuming but also requires the user to overcome a steep learning curve. Moreover, conventional Computer-Aided Machining (CAM) software does not support DDS tool paths, but instead supports tool path generation for common machining processes like milling and turning. This paper discusses the use of a special-purpose post processor to bridge the compatibility gap between CAM and DDS tool path generation. The mathematics and logic of converting CAM milling tool paths to DDS would be discussed. Finally, the post processor was experimentally verified using a case study.
Predicting readiness to plant trees in urban settings: an adaptation of the ecological model among a cohort of nigerian workers

ABSTRACT The need for urban greening is more evident in the African context because Africa is poised to become the global hub of urbanisation. This makes it crucial especially for urban African dwellers to be favourably disposed towards tree-planting. The socio-ecological model (SEM) affords a fine framework for understanding the importance of psychosocial and cultural variables. Hence, a socio-ecological model of Readiness to Plant Trees (RPT) which encompasses self-efficacy, interpersonal drive towards tree-planting, perceived prevalence of tree-planting and ethnic attitudes towards tree-planting was developed and tested. Data collection, using survey design and composite measures, featured a self-administered structured-questionnaire among 400 randomly sampled federal civil servants in Ibadan, Nigeria. Stepwise multiple linear regression was used to evaluate the predictors and correlates of RPT. Interpersonal drive and ethnic attitudes were significant predictors and explained 34.3% of the variation in RPT (multiple R = 0.585; R2 = 0.343; p < 0.001). Perceived prevalence is not a significant predictor, but it has a significant and positive relationship with RPT. Self-efficacy is not a significant predictor and also maintained an insignificant and negative relationship with RPT. This partly-novel socio-ecological model of RPT is largely apt in explaining and ultimately instilling RPT.
Digital Modulation Signal Separation Received by Single Antenna using TDL-ICA

: Recently, signal source separation technique using independent component analysis (ICA) have been attracting attention in the field of wireless communications. Furthermore, TDL-ICA, which combined a tapped delay line with ICA to increase the number of separatable signals with fewer elements, has been proposed. However, the application to the digital modulation has not been considered enough. In this paper, it is shown that the TDL-ICA can separate the overlapped digital modulated signals in the frequency domain by setting the appropriate parameters of the TDL, and the relationship between the number of taps of the TDL and the separation performance is clarified.
Identification of positions in literature using thematic network analysis: the case of early childhood inquiry-based science education

ABSTRACT Reviews of literature often summarize research within a given field to provide succinct information about state of the art as well as gaps for future research to address. In educational research, such information includes different positions within a field; for example, theoretical positions underpinning empirical studies. Such theoretical positions may influence interpretations of research results and remain a challenge to map and present. Here, we show how to use thematic analysis and network analysis to construct maps, analyse and synthesize theoretical positions within educational research. We use early childhood inquiry-based science education (ECIBSE) literature as a case because of its historical roots in Dewey’s educational philosophy. This allows us to discuss findings in light of a well-known theoretical framework. Using our methodology, we analyse four theoretical positions for teaching and learning: (1) science should be learned through inquiry, (2) teaching should model scientific practices, (3) children should develop science-related competencies (4) child’s experience should take precedence. After discussing these positions, we turn to methodological possibilities and challenges of using thematic network analysis for literature reviews. R-code, data and instructions for reproducing our results are available at: https://github.com/jbruun/thematicDiscourseNetworkAnalysis/.
Synthesis of macromolecular brush and its thermal degradation studies

Abstract The di-1,2-propanediol ester of fumaric acid (Diol) is synthesized and polymerized to yield the macromolecular brush (PDiol). The structure of monomers and their polymer is confirmed by Fourier transform infrared spectroscopy (FTIR) studies. The PDiol material shows the number average molecular weight (Mn ) as 951 g/mol, weight average molecular weight (Mw ) as 4,378 g/mol, and a polydispersity index (PDI) of 4.6. The hydroxyl value for PDiol is 471 (mg KOH/g). The thermal degradation property of the brush is investigated using thermogravimetric analysis (TGA). The cyclic intra and inter loops are formed while annealing at a temperature of around 200 °C. Using the TG curves recorded at different heating rates and by applying advanced isoconversional methods by model-free kinetics, the apparent activation energy for the thermal degradation (Ea-D) at different reaction extents (α) are calculated and discussed. Advanced methods are also used to refine the apparent activation energy data. The Ea-D values for PDiol range from 100 to 155 kJ/mol. For a lifetime of 20,000 h, the 20% degraded PDiol can withstand a temperature of 39 °C. Graphical Abstract HIGHLIGHTS Synthesis of fumaric acid and 1,2-propane diol-based biodegradable ester diol applicable for tissue engineering applications. Monomeric unsaturated ester diol capable of undergoing polymerization leading to the formation of an aliphatic backbone having hydroxyl-terminated ester bearing bristles. Application of model-free kinetic methods for the thermal degradation of a molecular brush having ester and hydroxyl groups.
“It’s not just a picture”: The effects of an international two-week field experience on student geoscience involvement and persistence

Abstract Recruitment and retention are critical for geoscience and the need for innovative ways of building these bridges to the geosciences is growing. Field experiences are a common attractor for students to the field sciences such as geoscience, but many research- and field-based experiences are limited to those who are already majors. Innovative, experiential approaches to geoscience recruitment and retention could be a new way to attract more students to geoscience. International field and research experiences designed for undergraduates from any academic discipline aim to provide opportunities for students to explore their (geo)science interests and potential career paths. A single, exploratory case study approach with semi-structured interviews combined with quantitative pre- and post-survey results is used to highlight the experiences of four students and their plans for continuing in the geosciences. Students (including geoscience and non-geoscience majors) were found to have had inherent, pre-college, and college influences for participation in the field experience; all students indicated plans to continue in the geosciences. Two years after the experience, researchers followed-up with the students and found that three of the four were still involved in the geosciences. Many international geoscience field experiences are exclusively for majors, but experiential learning opportunities like these should also be considered for potential majors. These results are beneficial for departments interested in designing and adapting their recruitment and retention efforts to better train the next generation of geoscientists.
Biodegradation of LDPE plastic by local strain of Bacillus sp. isolated from dump soil of Pekanbaru, Indonesia

Abstract. Fibriarti BL, Feliatra, Amin B, Darwis. 2021. Biodegradation of LDPE plastic by local strain of Bacillus sp. isolated from Dump Soil Pekanbaru, Indonesia. Biodiversitas 22: 5484-5490. Plastic is a compound resistant to degradation and takes tens to hundreds of years to decompose completely. The diversity of microbial metabolism allows microbes to degrade plastic and utilize it as a source of energy and carbon for growth. One type of plastic widely used in packaging is LDPE (Low-Density Polyethylene). The purpose of this study was to test the ability of local isolates of Bacillus sp. strains BP4 and BP6 isolated from waste soil and to identify them at molecular level. In LDPE plastic degradation test, pieces of LDPE plastic were added as a carbon source to a mineral solution medium and incubated for 30 days on shaker incubator at 150 rpm. The percentage of plastic degradation was calculated by subtracting the percentage of the initial weight of the plastic with the final weight. The test results showed that two isolates i.e. BP4 and BP6 were able to degrade LDPE plastics with degradation percentages of 7.23 ± 0.64% and 8.19 ± 0.12%, respectively. Molecular identification results revealed that Bacillus sp. strain BP4 showed a similarity of 99.72% with Bacillus anthracis strain X11, while Bacillus sp. strain BP6 showed a similarity of 99.93% with Bacillus paramycoides strain 8929.
DEFLECTIONS IN NON-PRISMATIC SIMPLY SUPPORTED PRESTRESSED CONCRETE BEAMS

Pre-stressing is becoming a most common and indispensable technique in the recent past for beams and girders in buildings and bridges. This paper presents the application of Finite Difference Method (FDM) for finding deflections in Pre-Stressed Concrete (PSC) beams with non-prismatic sections. Equations are derived for dead and live load bending moment, eccentricity, and depth at any required section. Based on these equations, it is initially established that conventional techniques cannot be adopted for finding deflections in prestressed concrete beams with non-prismatic cross-sections and hence FDM was adopted as an alternative. The calculated deflections using FDM are compared with those obtained from equivalent STAAD.Pro. Model and they found to be in close agreement.
Heterogeneous Knowledge Distillation for Simultaneous Infrared-Visible Image Fusion and Super-Resolution

Recently, infrared–visible image fusion has attracted more and more attention, and numerous excellent methods in this field have emerged. However, when the low-resolution images are being fused, most fusion results are of low resolution, limiting the practical application of the fusion results. Although some methods can simultaneously realize the fusion and super-resolution of low-resolution images, the improvement of fusion performance is limited due to the lack of guidance of high-resolution fusion results. To address this issue, we propose a heterogeneous knowledge distillation network (HKDnet) with multilayer attention embedding to jointly implement the fusion and super-resolution of infrared and visible images. Precisely, the proposed method consists of a high-resolution image fusion network (teacher network) and a low-resolution image fusion and super-resolution network (student network). The teacher network mainly fuses the high-resolution input images and guides the student network to obtain the ability of joint implementation of fusion and super-resolution. In order to make the student network pay more attention to the texture details of the visible input image, we designed a corner embedding attention mechanism. The mechanism integrates channel attention, position attention, and corner attention to highlight the visible image’s edge, texture, and structure. For the input infrared image, the dual-frequency attention (DFA) is constructed by mining the relationship of interlayer features to highlight the role of salient targets of the infrared image in the fusion result. The experimental results show that compared with the existing methods, the proposed method preserves the image information of both visible and infrared modalities, achieves sound visual effects, and displays accurate and natural texture details. The code of the proposed method can be available at https://github.com/firewaterfire/HKDnet.
Enhancing 3-D Land Seismic Data Using Nonlinear Beamforming Based on the Efficiency-Improved Genetic Algorithm

Seismic data acquired in a desert environment often have a low signal-to-noise ratio, posing a significant challenge to seismic processing, imaging, and inversion. Nonlinear beamforming is one effective method that uses local second-order mathematical operators to describe seismic events and then enhance them. However, estimating the operator coefficients from input data is a nonlinear and compute-intensive optimization problem. We propose a new method for this estimation based on a recently developed efficiency-improved genetic algorithm. We demonstrate that it delivers an excellent balance between improved data quality and computational efficiency. We also introduce a “spatial consistency” feature to further speed up the algorithm by using available nonlinear-beamforming operators as initial trial solutions for the neighboring data ensembles. These findings are supported by applying the new approach to land seismic datasets from the desert environment.