Miracle-dz/UniFAR-FTUs huggingface dataset:
Mathematics in Language

Elementary mathematics is deeply rooted in ordinary language, which in some respects anticipates and supports the learning of mathematics, but which in other respects hinders this learning. This paper explores a number of areas of arithmetic and other elementary areas of mathematics, considering for each area whether it helps or hinders the young learner: counting and larger numbers, sets and brackets, algebra and variables, zero and negation, approximation, scales and relationships, and probability. The conclusion is that ordinary language anticipates the mathematics of counting, arithmetic, algebra, variables and brackets, zero and probability; but that negation, approximation and probability are particularly problematic because mathematics demands a different way of thinking, and different mental capacity, compared with ordinary language. School teachers should be aware of the mathematics already built into language so as to build on it; and they should also be able to offer special help in the conflict zones.
Seasonal Water Level Fluctuation and Concomitant Change of Nutrients Shift Microeukaryotic Communities in a Shallow Lake

Seasonal water level fluctuations (WLFs) impose dramatic influences on lake ecosystems. The influences of WLFs have been well studied for many lake biotas but the microeukaryotic community remains one of the least-explored features. This study employed high-throughput 18S rRNA gene sequencing to investigate the spatiotemporal patterns of microeukaryotic communities in the dry and wet seasons with concomitant change of nutrients in Poyang Lake, which experiences huge seasonal WLFs. The results showed that the dry season and wet season had distinct microeukaryotic community compositions and structures. In the dry season, Ciliophora (13.86–40.98%) and Cryptomonas (3.69–18.64%) were the dominant taxa, and the relative abundance of these taxa were significant higher in the dry season than wet season. Ochrophyta (6.88–45.67%) and Chlorophyta (6.31–22.10%) was the dominant taxa of microeukaryotic communities in the wet season. The seasonal variation of microeukaryotic communities was strongly correlated to seasonal nutrient variations. Microeukaryotic communities responded significantly to dissolved organic carbon, total nitrogen, nitrate, and soluble reactive phosphorus in the dry season, and correlated to nitrate and total phosphorus in the wet season. The microeukaryotic community showed different modular structures in two seasons, and nutrient variations were the key factors influencing seasonal variations of the modular structures. Moreover, microeukaryotic community networks based on different seasons indicated that the microeukaryotic community co-occurrence patterns were not constant but varied largely associating with the nitrogen and phosphorus variations under the effects of WLFs. Our results are important for understanding how microeukaryotic communities respond to nutrient variation under seasonal water level fluctuation.
New Approaches to ‘Converts’ and ‘Conversion’ in Africa: An Introduction to the Special Issue

It is our goal in this special issue on “Religious Conversion in Africa” to examine the limitations of a long-standing bias toward Christianity with respect to the study of “conversion. ” Furthermore, we want to use this issue to prime other scholarly approaches to cultural change on the continent, beginning as early as the medieval period, including the colonial and early postcolonial eras, and extending to the contemporary. There are several reasons for making these interventions. One is the emergence of the anthropology of Christianity as a scholarly literature and sub-discipline. This literature has often focused on issues of religious change in relation to its own predilection for charismatic and Pentecostal expressions of Christianity and the distinct characteristics of cultural discontinuity within those communities. Another reason for this special issue on religious “conversion” in Africa is the relative lack of studies that engage with religious change beyond Pentecostal, charismatic, and evangelical Protestant contexts. As such, studies on the “conversion” of Ahmadi in West Africa, medieval Ethiopian women, Mormons in twentieth-century southeastern Nigeria, and Orthodox Christians in Uganda are included, as is a fascinating case of what it means to “trod the path” of Rastafari in Ghana. Taken together, these contributions suggest new and important paths forward with respect to “conversion,” including critiquing and perhaps even discarding the term in certain contexts. Ultimately, we want these articles to illuminate the many ways that Africans across the continent have engaged (and continue to engage) with beliefs, practices, ideas, and communities—including the changes they make in their own lives and in the lives of those communities.
Do single Pollard transects represent the local butterfly community? A case study from the Spitzberg near Tübingen, Germany

Information on butterfly population size and distribution is a key tool for verifying species conservation status. Such data are rare and tend to be available on local rather than on regional scales. One important data source are monitoring schemes that have been implemented in several countries, e.g. the German butterfly monitoring scheme (TMD). The main goal of the present study was to examine how representative single transects of the TMD are able to identify local or regional diversity patterns of butterflies. Total butterfly population size, density of individuals and species diversity pattern of a 624 ha large study area (Spitzberg) were recorded by intensive surveys. Almost all butterfly species present at the Spitzberg were recorded by the TMD transects. For 22 species, local estimates based on records of the TMD transects ranged between 0 and 10% of the regional population size. Accordingly, the study demonstrates that population size changes of most of the species can potentially be identified. Increasing cover of forest has a negative effect on species diversity and butterfly density, while the cover of nutrient‐poor grassland and the diversity of biotope types has a positive impact on butterfly density and species diversity. Solar insolation has a positive effect on butterfly density. Based on the results of the species–habitat relationships, the location of TMD transects could be optimised by aiming to cover the complete butterfly diversity of the study area. Additionally, monitoring of some of the species might be improved if winter surveys of eggs and larvae were implemented in the monitoring scheme.
Fostering Social Project Impact with Twitter: Current Usage and Perspectives

Social impact assessment has become a major concern within the research community. While different methodological advancements have been made to better display, as well as to measure, achieved impacts, social media has proved to be a potential domain to generate many new opportunities to support both the communication as well as the realization of social impact. Within this context, the current research presents an analysis of how Twitter is used among a subset of research projects to maximize social impact. The research focuses on the use of Twitter, as one of the most often used social media, by the members of scientific projects funded under one part of the FP7 funding framework of the European Union called Science in Society. The data were analyzed using NVivo, and WordStat Provalis software. The results presented in this study include exploratory data analysis, topic mining and the analysis of the impact of projects on Twitter. The results indicate moderate use of Twitter among the observed projects, but with a strong focus on the dissemination of project results, thus indicating a trend towards the usage of social media for communicating the social impact of research projects.
An accurate and efficient machine fault diagnosis approach using a recurring broad learning model

In most of previous machine fault diagnosis, the performance of traditional methods was over-dependent on high-quality feature extraction from original signals. Recently, deep learning–based fault recognition methods can successful automatically learn high-level hidden features from measured signals, but a deep neural network has too much hyperparameter tuning and a complicated architecture, so the training process is time-consuming. To address these issues, a novel machine fault diagnosis approach using a recurring broad learning model is reported in this article. This method uses a recurring broad learning model first proposed in this article, which learns high-level hidden features from sensor signals with different working status of a machine effectively and efficiently. Experimental results conducted on two public machine fault datasets verify the accuracy and efficiency of the proposed approach for machine fault diagnosis separately. Compared with many existing mainstream methods, the state-of-the-art framework presented reveals its superiority on both datasets. The accuracy achieves nearly 100% on both bearing dataset (Dataset 1) and gearbox-bearing dataset (Dataset 2). In addition, it can obviously realize faster training than most of the methods reported in this article.
Epidemiology of Fusarium oxysporum causing root and crown rot of cannabis (Cannabis sativa L., marijuana) plants in commercial greenhouse production

Abstract Fusarium oxysporum causes root browning and crown infection on marijuana (Cannabis sativa L.) plants, resulting in stunted growth, yellowing of leaves, and plant death. Pathogen presence and diversity were assessed in samples of diseased crowns, stems, pith tissues and roots from five commercial production facilities in British Columbia and Ontario. PCR of the elongation factor (EF-1 α) region and sequence analysis confirmed the identity and phylogenetic relationships among 33 representative isolates from over 200 isolates collected. Stock (mother) plants of eight cannabis strains (genotypes) with symptoms of yellowing, crown rot and internal stem decay yielded F. oxysporum at a frequency of 70–100%. Cuttings obtained from asymptomatic plants showed pathogen recovery rates of 1–2% on potato dextrose agar at distances of 90–150 cm from the crowns. Symptoms of damping-off were observed on cuttings in a rooting and propagation facility. Pathogenicity tests confirmed the development of characteristic symptoms on cuttings and rooted plants inoculated with F. oxysporum. Phylogenetic analysis indicated that isolates of F. oxysporum from BC belonged to a separate clade from ON isolates and that clonal spread was occurring within licenced facilities. Air sampling conducted in a greenhouse facility revealed F. oxysporum was present in areas used for rooting, vegetative propagation, and where stock plants were grown. The pathogen was also recovered from inflorescences. These findings indicate that F. oxysporum is present in several commercial production facilities in Canada and reduces root development and establishment of rooted cuttings, and causes yellowing and stunting on flowering plants of many cannabis strains.
The Study of Intention to Apply Live Video Transmission System in Disaster Sites for Firefighters through UTAUT model

With the rapid development of network technology, the live video transmission system (LVTS) has improved the work efficiency because of the visual communication combining both images and data. In order to strengthen the effectiveness of disaster prevention through instant communication, the Fire Department in Taiwan has used the “VVLINK” videoconferencing system to provide multi-functional online conferences, and even grasp on-site dynamic situation of disasters in the first time, and then giving order to the disaster relief site online. Here, a research about the application of LVTS system in disaster sites was carried out to study the intention for firefighters in Fire Bureau of Changhua County, Taiwan. In this study “behavioural intension (BI)” and “usage behaviour (UB)” on LVTS system are explored through the Integrated Technology Acceptance Model (UTAUT). In addition, moderate variables such as gender, age, experience and voluntary are needed to be considered. “Performance expectation (PE)”, “effort expectation (EE)” and “social influence (SI)” can affect BI to be very significant; BI and “facilitating conditions (FC)” can also affect UB. Questionnaire analysis was applied. The results show that PE, EE, and SI have a positive direct impact on BI, and BI also has a positive direct impact on UB. It was also found that the FC had a positive and direct impact on BI as well as SI impacting on UB. All the moderate variables have significant difference on each UTAUT categories.
Convex Q-Learning, Part 1: Deterministic Optimal Control

It is well known that the extension of Watkins' algorithm to general function approximation settings is challenging: does the projected Bellman equation have a solution? If so, is the solution useful in the sense of generating a good policy? And, if the preceding questions are answered in the affirmative, is the algorithm consistent? These questions are unanswered even in the special case of Q-function approximations that are linear in the parameter. The challenge seems paradoxical, given the long history of convex analytic approaches to dynamic programming. The paper begins with a brief survey of linear programming approaches to optimal control, leading to a particular over parameterization that lends itself to applications in reinforcement learning. The main conclusions are summarized as follows: (i) The new class of convex Q-learning algorithms is introduced based on the convex relaxation of the Bellman equation. Convergence is established under general conditions, including a linear function approximation for the Q-function. (ii) A batch implementation appears similar to the famed DQN algorithm (one engine behind AlphaZero). It is shown that in fact the algorithms are very different: while convex Q-learning solves a convex program that approximates the Bellman equation, theory for DQN is no stronger than for Watkins' algorithm with function approximation: (a) it is shown that both seek solutions to the same fixed point equation, and (b) the ODE approximations for the two algorithms coincide, and little is known about the stability of this ODE. These results are obtained for deterministic nonlinear systems with total cost criterion. Many extensions are proposed, including kernel implementation, and extension to MDP models.
Mechanism of the disproportionation of superoxide radicals

New measurements are reported on the rate of the spontaneous uncatalyzed second-order decay of the superoxide radical in aqueous solution at 23/sup 0/C. By extreme purification of reagents, and addition of small amounts of EDTA to sequester traces of catalytic metal ions, purely second-order kinetics were found up to pH 13.2. The pH effects clearly show that the ionic form O/sub 2//sup -/ never reacts with itself but only with the HO/sub 2/ in equilibrium with it, even when the ratio HO/sub 2//O/sub 2//sup -/ is as small as 2 x 1/sup -8/; the rate constant for O/sub 2//sup -/ + O/sub 2//sup -/ is less than 0.3 M/sup -1/ s/sup -1/. The pK of HO/sub 2/ was determined as 4.75 +- 0.08, and the bimolecular rate constants were k/sub 1/ = (7.61 +- 0.55) x 10/sup 5/ M/sup -1/ s/sup -1/ for HO/sub 2/ + HO/sub 2/ and k/sub 2/ = (8.86 +- 0.43) x 10/sup 7/ M/sup -1/ s/sup -1/ for HO/sub 2/ + O/sub 2//sup -/, all in good agreement with published values. The change in the spontaneous decay of superoxide radicals with pH follows the equation k/sub obsd/ = (k/sub 1/ + k/sub 2/K/sub HO/sub 2///(H/supmore » +/))/(1 + K/sub HO/sub 2///(H/sup +/))/sup 2/. The optical extinction coefficients of hydrogen peroxide were determined over the pH range 6.1 to 13.8 at wavelengths from 280 to 230 nm. « less
Application of Thermal Insulation Gunite Material to the High Geo-Temperature Roadway

Thermal insulation gunite (TIG) in roadways is an effective method for regional thermal hazard control in mines. The development of mine TIG materials is the foundation of thermal insulation technique. However, some conventional and advanced insulation materials are inapplicable to deep mines which are rather humid with high in situ stress and high geo-temperature. In this study, a kind of fly ash-inorganic mineral TIG material was developed and applied to the modelling of a high geo-temperature roadway. Moreover, the thermal insulation effect of the TIG layer was analyzed, and the temperature field characteristics of the TIG surrounding rock were discussed. Results reveal that (1) the TIG layer has a significant impact on the heat release of the wall and stability of the surrounding rock temperature field; (2) the initial temperature disturbance times, temperature disturbance ranges, and temperature drop rates differ with whether a TIG layer exists or not; (3) after the TIG roadway starts to be ventilated, the thermal flux densities tend to be consistent, which indicates the end of temperature disturbance; besides, the dimensionless temperature shares an exponential relation with the dimensionless radius; and (4) the characteristics of temperature drops vary with the radial positions of the surrounding rock. The research results provide a certain reference for thermal hazard control, temperature prediction, and ventilation network adjustment.
Association of attention‐deficit/hyperactivity disorder with diabetes mellitus in US adults

Attention‐deficit/hyperactivity disorder (ADHD) is a childhood‐onset neurodevelopmental disorder that usually persists into adulthood. However, limited evidence is available regarding its influence on adult health outcomes beyond neuropsychiatric comorbidities. This study aimed to examine the association of ADHD with diabetes in US adults.
Protein Structure Prediction in Structural Genomics without Alignment Using Support Vector Machine with Fuzzy Logic

Protein secondary structure prediction from amino acid sequences is a challenging and complex task as it has become a must in oder to identifying the similarities/dissimilarities between protein structure. The protein secondary structure is used for studying the biological functionality of species in order to develop new drugs. A sustainable number of research has been done for predicting protein structure but yet the performance is not satisfactory. For this reason, it is necessary and time demanding to develop a technique for predicting protein structure that gives the satisfactory performance for large datasets termed as big datasets. In this article, propose a method based on the support vector machine and fuzzy logic in order to predict protein secondary structure without alignment. In this case, generate the optimal hyper plane of support vector machine using the membership values. Moreover, in order to increase the generalization ability a hybrid kernel support vector machine is propose that gives the better results in terms of classification and learning ability. We have tested the proposed method performance on the several benchmark datasets. The simulation results shows that the proposed technique outperforms better than other existing conventional techniques.
The effect of the chosen distribution form on reaction probability estimates from drop-weight impact results

ABSTRACT The consequences of choosing one distribution form in the analysis of drop-weight impact results were explored, and the importance of reporting both the L50 and the distribution spread-parameter for estimation of reaction probabilities at low-stimuli was demonstrated. The drop-weight impact results of pressed PBX9501 were reported alongside drop-weight results tendered by AFRL. Three distribution forms were fit to the data sets; similar reaction probabilities across all stimulus levels were obtained. It was found that there is little benefit to choosing the normal distribution over the logistic distribution or vice-versa for the sequential test design or analysis of drop-weight impact results.
Exotic ladybirds for biological control of herbivorous insects – a review

Since the late 19th century, exotic ladybirds (Coleoptera: Coccinellidae) have been used extensively for suppressing herbivorous insects of economic importance. In recent decades, the introduction of non‐native biological control (BC) agents has been greatly limited due to the awareness of the potential non‐target effects of introductions. Nonetheless, recent episodes of biological invasions of economically important pests have raised the need to carefully consider whether the expected benefits of pest control go beyond the possible environmental risks of introduction. To better understand the factors that contributed to successful BC programs, here we review the literature behind classical and augmentative BC using exotic ladybirds. Additionally, by means of case studies, we discuss the BC efficacy of selected exotic species, e.g., Coccinella septempunctata L. , Harmonia axyridis (Pallas), and Hippodamia variegata (Goeze), and their position within the communities of predators in the introduced areas of USA, Canada, and Chile. In Europe, much of the research on exotic ladybirds has been conducted on the undesired impact of H. axyridis. Therefore, we summarize the risk assessment data for this species and review the field research investigating the ecological impact on European aphidophagous predators. According to the BIOCAT database of classical BC programs, 212 ladybird species belonging to 68 genera have been released in about 130 years of BC activity, with 14.6% of introductions having resulted in partial, substantial, or complete control of the target pest. However, because post‐release evaluation of establishment and BC success has not always been conducted, this rate could underestimate the successful cases. Among other factors, ladybird establishment and pest suppression mostly depend on (1) intrinsic factors, i.e., high voracity, synchronized predator‐prey life cycle, and high dispersal ability, and (2) extrinsic factors, i.e., adaptability to the new environment and landscape composition. This review contributes to improved understanding of ladybirds as exotic BC agents.
Effects of Dicalcium Phosphate (DCP) and Vitamin E on Growth Performance and Hemato-Biochemical Parameters in Broilers

This study was conducted to assess the effect of DCP and vitamin E supplementation on body weight, hematological(TEC, Hb content, PCV and ESR) and biochemical (AST and ALT) parameters of “Cobb 500” broiler. A total of 20 chicks (14 days old) were reared and randomly divided into four equal groups (n=5). Body weight was measured at each 7 days interval up to the end of the 35 days of experimental period. Group A was considered as control, fed with commercial ration. Group B, C and D were treated with 1 gm DCP per kg feed, 1 ml vitamin E per litre of drinking water, and 1 gm DCP per kg feed plus 1 ml vitamin E per litre of drinking water with commercial ration, respectively from day 14 to day 35. It was observed that DCP and vitamin E supplementation significantly (p<0.01) increased body weight. Moreover, TEC and Hb content increased significantly (p<0.01) in the treated groups as compared to control. Besides, ESR, AST and ALT values decreased significantly (p<0.01) in the treated groups. Therefore, it may be concluded that DCP and vitamin E could be used to improve body weight gain and blood profiles without any detrimental effect to liver and muscle on broilers.