Miracle-dz/UniFAR-FTUs huggingface dataset:
The Potential of Nano-Porous Surface Structure for Pain Therapeutic Applications: Surface Properties and Evaluation of Pain Perception

The objective of this study was to evaluate the biomaterial properties of nano-modified surface acupuncture needles and the effect of such needles on human pain perception by using pressure pain threshold (PPT) measurements. It is known that changing a material’s surface nano-topography or nanostructure has strong effects on its physical, chemical, and biological surface properties. However, there is no information in the literature about the stimulation characteristics of acupuncture needles with nano-topography or nanostructured surfaces. Based on the knowledge on nanostructured surfaces, it may be possible to potentiate the effects of acupuncture needle stimulation. The pressure pain sensitivity of the masseter muscle in the orofacial region was studied in 21 healthy volunteers in two randomized, double-blinded sessions: an active session of manual acupuncture manipulation with nano-modified surface needles, and an inactive session of sham acupuncture stimulation to control for possible placebo effects. Three acupuncture points were selected from classical Chinese medicine literature: LI4 (Hegu) on the hand, ST6 (Jiache) on the lower masseter region, and ST7 (Xiaguan) on the upper masseter region. PPT measurements, perceived sensations, and pain from the acupuncture were recorded. The results showed discrete yet significant differences in PPT values between the active and inactive acupuncture treatments and significantly higher pain scores from active acupuncture stimulation than from sham acupuncture. These results indicate subtle but significant effects of acupuncture stimulation with nano-modified surface needles, compared to sham acupuncture in healthy participants.
THE INFLUENCE OF TECHNICAL SUPPORT, PERCEIVED SELF-EFFICACY, AND INSTRUCTIONAL DESIGN ON STUDENTS’ USE OF LEARNING MANAGEMENT SYSTEMS

Learning Management System is a software-based technology that is widely adopted by universities. While the implementation of LMS has been successful in developed countries, the utilisation of LMS in developing countries is still considered low. It is believed that there are some barriers that may influence the use of LMS which include Technical Support, Instructional Design and Self-Efficacy. The present research aims at examining the influence of these factors on students’ use of LMS. Thus, a research model will be developed based on extending Technology Acceptance Model (TAM). Using the Stratified Random Sampling (SRS), 400 students were selected from three Saudi universities. The participants completed the survey questionnaire that measures their responses to the seven constructs. The data was analysed using Structural Equation Modelling by AMOS. The results showed that the three proposed external factors including technical support, instructional design and perceived self-efficacy had a significant influence on students’ use of LMS. These factors had significant direct effects on both perceived ease of use and perceived usefulness of LMS. The results confirmed the validity of the extended TAM model in determining users’ usage of LMS. The study also addressed several significant implications for the practitioners and researchers in the field.
The Role of Fire in the Coevolution of Soils and Temperate Forests

Climate drives the coevolution of vegetation and the soil that supports it. Wildfire dramatically affects many key eco‐hydro‐geomorphic processes, but its potential role in coevolution of soil‐forest systems has been largely overlooked. The steep landscapes of southeastern Australia provide an excellent natural laboratory to study the role of fire in the coevolution of soil and forests, as they are characterized by temperate forest types, fire frequencies, and soil depths that vary systematically with aridity. The aims of this study were (i) to test the hypothesis that in Southeastern Australia, fire‐related processes are critical to explain the variations in coevolved soil‐forest system states across an aridity gradient and (ii) to identify the key processes and (iii) feedbacks involved. To achieve these aims, we developed a numerical model that simulates the coevolution of soil‐forest systems which employ eco‐hydro‐geomorphic processes that are typical of the flammable forests of southeastern Australia. A stepwise model evaluation, using measurements and published data, confirms the robustness of the model to simulate eco‐hydro‐geomorphic processes across the aridity gradient. Simulations that included fire replicated patterns of observed soil depth and forest cover across an aridity gradient, supporting our hypothesis. The contribution of fire to coevolution increased in magnitude with aridity, mainly due to the higher fire frequency and lower post‐fire infiltration capacity, increasing the rates of fire‐related surface runoff and erosion. Our results show that critical feedbacks between soil depth, vegetation, and fire frequency dictate the trajectory and pace of the coevolution of flammable temperate forests and soils.
External Debt and Capital Accumulation Nexus: Evidence from
 Pakistan

The rising public debt burden is a common feature of developing countries like Pakistan. This study is an attempt to empirically analyse the external debt and capital accumulation nexus for Pakistan from 1972 to 2016. The ARDL bound testing technique was employed to estimate two models which incorporate different indicators of external debt. Results indicate the existence of a negative relationship between external debt to revenue ratio and stock of capital that supports the debt overhang hypothesis for Pakistan. The debt overhang hypothesis states that large accumulated debt leads to a decrease in overall capital accumulation in an economy. Similarly, other indicators of external debt, namely, external debt service to revenue ratio, external debt to export ratio, and external debt service to export ratio tend to bring a fall in stock of capital in Pakistan. Based on its findings, the study suggests the need for better and productive use of external debt in public sector development projects to foster the capital accumulation process in Pakistan.
A Review on PDIS (Plant Disease Identification Systems)

— Plant diseases are one of the most important factor which can harm agricultural crops. Advances in image processing and other information technologies are serving as promising solutions for real time crop disease detection and recognition. Researchers from all around the world have put forward their ideas for developing such systems but success still seems too far away because proposed and developed systems have few limitations. This review will provide aid to researchers for understanding image processing applications in plant disease detection and recognition as it summarizes various plant diseases, disease detection systems, their challenges and their working.
Synthesis and molecular docking study of 6-chloropyrazine-2-carboxylic acid derivatives

One of the most lethal and frequent infectious diseases worldwide is tuberculosis. Multi and extensively tuberculosis drug-resistant constitutes a serious problem and emphasizes the need for novel anti-tubercular agents. Accordingly, various pyrazine-2-carboxamides were synthesized and evaluated as potential anti-tuberculosis agents. The synthesis involved reaction of pyrazinoic acids with thionyl chloride to yield acyl chlorides which on treatment with various anilines gave various pyrazine-2-carboxamides. Based on structure-activity relationships extracted from previously published, this paper reported the synthesis and molecular docking study of 6-chloropyrazine-2-carboxamides. Synthesis involved reaction of 6-chloropyrazinoic acid with 2,4,6-trichlorobenzoyl chloride instead of thionyl chloride which listed under the Chemical Weapons Convention as it may use for the production of chemical weapons. Structure identification of 6-chloropyrazine-2-carboxamides was carried out by 1H NMR, 13C NMR, FTIR, and high-resolution mass spectroscopy. It is predicted that 6-chloro-N-octylpyrazine-2-carboxamide has better bioactivity against Mycobacterium tuberculosis, based on molecular docking study.
Anammox reactor treating low strength domestic wastewater: a review

Anaerobic ammonia oxidation (anammox) is a promising biological wastewater treatment process. It has been widely implemented in many industries due to lower oxygen consumptions besides being an environmental friendly method for wastewater treatment. However, there are several challenges in the process for potential application such as low anammox bacterial abundance and slow growth rate that lower the efficiency of the reaction. Therefore, several factors are being considered during operation of the anammox process. There are various anammox bacteria, which may be enriched using special techniques. Lower nitrogen content of influent brings great challenges for anammox performance due to inhibition caused by ammonium-oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) in nitrification process. This review highlighted the anammox process in various industry as well their anammox bacteria morphology, mechanism and strategies to enrich the bacteria. Coupled anammox process with low strength domestic wastewater requires more research to enable potential application in wastewater treatment.
Video-based Tancho Koi Fish Tracking System Using CSK, DFT, and LOT

In this paper, a comparison of Circulant Structure of Tracking-by-detection with Kernels (CSK), Distribution Fields for Tracking (DFT) and Locally Orderless Tracking (LOT) methods is proposed for the process of video-based object tracking. The object in question is the tancho koi fish and its variants, in the form of video recordings. All three methods are applied to trace the red roundabout in the head of the koi fish. The purpose of this study is to provide the best tracking process recommendations for this case. From the experimental results, it is found that the average sample accuracy of the DFT tracking method is more recommended than the other two methods, even though it has an average frame rate that is no better than the CSK method.
Handling non-linearity between classes using spectral and spatial information with kernel based modified possibilistic c-means classifier

Abstract In this research work, non-linearity in data has been handled by incorporating kernel with the Modified Possibilistic c-Means (MPCM) algorithm. Nine different types of kernel function have been proposed to classify nine different classes and have non-linearity among them. Gaussian has been identified as the best performing kernel at an optimized fuzzified value m = 1.5 with an overall accuracy 92.45%. The composite kernels have been generated with an aim of improvement of accuracy in comparison to single kernel. Further, role of spatial constraints has been analyzed by adding neighboring pixel information to handle the noise. It was observed that overall accuracy depends on the spatial parameter that has been included. Thus, local information having local similarity measure parameters (Sir)in the image produces highest accuracy compared to others. Moreover, the identified best kernel (Gaussian Kernel) has been then used for extraction of the burnt paddy fields in a different test site.
The Design and Implementation of a Single-Actuator Soft Robot Arm for Lower Back Pain Reduction

This paper presents a simple and fast design and implementation for a soft robot arm. The proposed continuum arm has been built by a single self-bending contraction actuator (SBCA) with two-fingers soft gripper. Because of the valuable advantages of the pneumatic artificial muscle (PAM), this continuum arm provides a high degree of safety to individuals. The proposed soft robot arm has a bending behaviour of more 180° at 3.5 kg, while, its weight is 0.7 kg. Moreover, it is designed to assist the people by reducing the number of backbends and that leads to a decrease in the possibility of lower back pain.
Comparison of EMD, VMD and EEMD Methods in Respiration Wave Extraction Based on PPG Waves

Plethysmographic (PPG) wave analysis can provide interesting information including heart rate and oxygen saturation. Since PPG signals are modulated by breathing waves, further analysis can provide additional information that is the respiration rate (RR). This is a way to simplify sensor devices. This paper discusses a respiration wave extraction mechanism to calculate RR using the signal decomposition approach. Decomposition methods which are applied in this study include empirical mode decomposition (EMD), variational mode decomposition (VMD) and ensemble empirical mode decomposition (EEMD). This paper specifically addresses the performance of EEMD to EMD and VMD. This proposed method has been tested on an open PPG dataset (containing PPG and RR wave signals). Test results on 20 PPG signals, each of which had a duration of 1 minute showed that the EEMD was able to estimate the RR with an accuracy of more than 90% with an average error rate of 1 rate/minute.
Modeling the Dielectric Properties of Minerals From Crystals to Bulk Powders for Improved Interpretation of Asteroid Radar Observations

Planetary radar has provided a growing number of data sets on the inner planets and near‐Earth and main belt asteroid populations in the solar system. Physical interpretation of radar data for inference of surface properties requires constraints on the constitutive parameters of the material making up a given surface. In this study, the complex permittivity of seven minerals as a function of frequency and porosity is measured using the coaxial transmission line method to determine the mixing equation that best describes the relationship between the real part of the complex permittivity of single mineral crystals and granular mineral powders. We find the Looyenga‐Landau‐Lifshitz and Bruggeman symmetric mixing equations to describe our experimental results with the highest accuracy. The variation in the real part of the permittivity of solid mineral crystals between different minerals is shown to depend on the grain density and the chemical composition of the minerals. These mixing relationships are incorporated into an asteroid radar model and used to calculate the porosity in the near‐surface of seven asteroids visited by robotic spacecraft using Earth‐based radar observations. The results of the asteroid radar model support the presence of significant porosity in the boulders on the surface of asteroid 101955 Bennu. This research highlights the ability of radar to measure the porosity on asteroid surfaces and provides theoretical and experimental justification for the inversion of permittivity to bulk density assumed by the asteroid radar model.
Political connections and firm performance in non-financial firms listed on Johannesburg stock exchange

This study concerns with the how political connections affects firm performance. Extant literature in subject presented mixed and inconclusive findings. The aim of the study was two fold: to examine the effect of political connections on firm performance and to whether or not different of political connections affect firm performance differently. Fifty (50) firms listed on Johannesburg Stock Exchange (JSE) were used as the sample size of the study based on a study period from 2012 to 2018. A dynamic regression using GMM estimation technique was used to test the relationship. The results indicate that in general, political connections positively affect firm performance, but not all types of such connections affect firm performance. It was recommended that political connections should be discouraged in non government linked companies because of instability of such types of connections. Government linked companies on the other hand, should explore other types of political connections in order to enhance performance.
Why Food Safety Will Continue Driving Growth in Demand for Organic Food

_______________________________________________________________________________________ 1 Remarks prepared for delivery January 24, 2003 at the 2003 EcoFarm Conference, Monterey, California. Contact Dr. Benbrook at Benbrook Consulting Services, 5085 Upper Pack River Road, Sandpoint, Idaho 83864. (benbrook@hillnet.com; 208-263-5236). Imagine if Ford Motor Company designed an engine that could double gas mileage with no loss in performance, or if General Electric discovered a fully recyclable light bulb that lasts three times longer than those on the market today. Would these companies tout these attributes in their advertising campaigns? You bet they would.
From Text to Thought: How Analyzing Language Can Advance Psychological Science

Humans have been using language for millennia but have only just begun to scratch the surface of what natural language can reveal about the mind. Here we propose that language offers a unique window into psychology. After briefly summarizing the legacy of language analyses in psychological science, we show how methodological advances have made these analyses more feasible and insightful than ever before. In particular, we describe how two forms of language analysis—natural-language processing and comparative linguistics—are contributing to how we understand topics as diverse as emotion, creativity, and religion and overcoming obstacles related to statistical power and culturally diverse samples. We summarize resources for learning both of these methods and highlight the best way to combine language analysis with more traditional psychological paradigms. Applying language analysis to large-scale and cross-cultural datasets promises to provide major breakthroughs in psychological science.
MeSH-Based Semantic Indexing Approach to Enhance Biomedical Information Retrieval

Owing to the tremendous size of electronic biomedical documents, users encounter difficulties in seeking useful biomedical information. An efficient and smart access to the relevant biomedical information has become a fundamental need. In this research paper, we set forward a novel biomedical MeSH-based semantic indexing approach to enhance biomedical information retrieval. The proposed semantic indexing approach attempts to strengthen the content representation of both documents and queries by incorporating unambiguous MeSH concepts as well as the adequate senses of ambiguous MeSH concepts. For this purpose, our proposed approach relies on a disambiguation method to identify the adequate senses of ambiguous MeSH concepts and introduces four representation enrichment strategies so as to identify the best appropriate representatives of the adequate sense in the textual entities representation. To prove its effectiveness, the proposed semantic indexing approach was evaluated by intensive experiments. These experiments were carried out on OHSUMED test collection. The results reveal that our proposal outperforms the state-of-the-art approaches and allow us to highlight the most effective strategy.
Ultrafast photo-switching of spin crossover crystals : coherence and cooperativity

The main topic of this thesis is the study of the ultrafast photo-switching of photo-magnetic molecular materials showing transition between spin states. These molecular crystals are prototypes of molecular bistability between two distinct electronic states, HS and LS. The molecules can be switched between these two states by a light pulse. The emergence of ultrafast techniques allows us to study in real time these photo-switching processes and also the associated out-of-equilibrium dynamics down to the femtosecond scale (10-15s). We have combined probes sensitive to the change of electronic state, on the hand, and to structural rearrangements, on the other hand, in order to observe these photo-switching processes. The measurements of ultrafast transient absorption spectroscopy have been made using the laser plateform at the IPR. Complementary time resolved X-ray diffraction and absorption experiments have been performed on large facilities. The first part of this manuscript is focused on the photo-switching dynamics at molecular scale. It reveals a complicated interaction between electronic and structural degrees of freedom. The generation and damping of coherent optical phonons is identified as a key parameter in the trapping in HS potential. Several experiments on different compounds show the linear and local character of such ultrafast photo-switching. The second part of this thesis presents studies on the complete out of equilibrium dynamics. It reveals a cascading process with activation of elastic and thermal effects at different time scales. Cooperative processes following a light excitation are observed. These complexes dynamics are driven by propagating and diffusive process sensitive to the size of the sample. The study of nanocrystals yields high conversion and faster response to elastics effect than single-crystals. These studies further elucidate the out of equilibrium processes underlying the photo-induced phase transitions on time and length scales, from the molecule to material scale.
Team learning as boundary crossing: incubating collaboration

ABSTRACT Academic incubators are used to support collaborative and entrepreneurial projects in order to catalyze innovative ideas into viable ventures. This study examined five seed-phase entrepreneurial teams who participated in an academic incubator at a graduate school of business in order to better understand what differentiated successful teams from unsuccessful teams. While traditional learning models describe the processes observed in successful teams, frameworks for understand internal team communication challenges help explain why some teams were able to develop success processes while others faltered. Unique features of high-innovation contexts and seed-phase entrepreneurs highlight the importance of communication across internal and external boundaries as well as honing external communication regarding the business case. Findings from this study suggest the value of learning to communicate across knowledge boundaries by making those boundaries explicit through the use of tools and protocols, which can be introduced by HRD professionals supporting teams in workplaces, academic incubator directors, research leads, mentors, and faculty instructing courses with collaborative learning components.
Human disturbance and the activity patterns and temporal overlap of tapirs and jaguars in reserves of NW Belize

Human disturbance from tourism and other non‐consumptive activities in protected areas may be stressful to wildlife. Animals may move away in space or time to avoid human interaction. For species of particular conservation concern, such as Baird's tapirs (Tapirus bairdii) and jaguars (Panthera onca), a better understanding of how they respond to different levels and types of disturbance is needed in order to manage human visitation to parks in ways that minimize negative outcomes for wildlife. We describe the overlap in activity patterns of tapirs, jaguars, and humans at logged and unlogged sites and at places with low versus high human visitation using camera survey data from protected areas of NW Belize, 2013–2016. Tapirs were nocturnal in all study sites, with > 80% of all tapir detections occurring between 1900 hr and 0500 hr. Their activity patterns were not different in unlogged versus logged sites and did not change with increased human traffic. Jaguars were cathemeral across sites but had more nocturnal activity at the site with the most human impact. Activity pattern overlap between tapirs and jaguars did not differ significantly between logged and unlogged sites, nor between areas with low and high human activity. Human traffic increased from 2013 to 2016 at most of the study locations. In conclusion, this camera trap dataset suggests that non‐consumptive human disturbance does not alter the activity patterns of tapirs and jaguars in protected areas lacking hunting pressure.