Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating Geospatial Patterns of Elephant Crop Damage Adjacent to the Serengeti National Park and Grumeti Game Reserve, Tanzania

We investigated a spatial configuration of human-elephant interactions in communities bordering the Serengeti National Park and Grumeti Game Reserve. Elephant crop damage was the most common adverse impact of the interactions. Geographic information systems were used to assess the distribution, hot and coldspots and relationships of elephant crop damage and environmental features in the Bunda District, Tanzania. Six hotspots and three coldspots were identified. Of all elephant crop damage incidents, 66% occurred in the wider village areas bordering Grumeti Game Reserve, 28% in the wider village areas bordering the Serengeti National Park and 6% in village areas that did not border the protected areas. There was a high concentration of elephant crop damage near rivers and protected areas, which decreased with increased geographical distance from the edge of these features.
Tolerance of Characteristics and Attributes in Developing Student’s Academic Achievements

A R T I C L E I N F O A B S T R A C T Article history: Received: 03 July, 2020 Accepted: 15 October, 2020 Online: 22 October, 2020 The purpose of this research is to study the relevance of factors for the analysis of the effectiveness of suitable educational institutions that illustrate the significance of the characteristics and attributes of the student’s academic achievements and to identify the acceptance and tolerance of each attribute, which supports lifelong learning. The data used in this research is 1109 students who used and tested the institution recommender system based on student context and educational institution application. The research methodology focuses on the study of user involvement and application analysis. There are six significant phases of the research: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The machine learning tools and data mining techniques are k-means, k-medoids, decision trees, cross-validation methods, and confusion matrix. From the data analysis, it can be concluded that the overall level of satisfaction with the application is accepted (average = 3.70, S.D. = 0.84). In addition, the prototype model has been developed for predicting and recommending appropriate institutions for the learner has moderate accuracy levels (92.25%), and the results of the self-test data model are very accurate at the highest level, which is equal to 93.78%. Finally, this research demonstrates the relevance and success of education engineering projects. It demonstrates a worthy accomplishment. For future research, the researchers aim to construct and develop applications that promote and support the findings of this research.
LIQUID-LIQUID EQUILIBRIUM OF THE SYSTEM WATER-PHOSPHORIC ACID-DI-N-PROPYL ETHER AT 25 AND 40°C. INFLUENCE OF THE ISOMER PROPYL-ISOPROPYL ETHER ON THE APPEARANCE OF THREE LIQUID PHASES AT EQUILIBRIUM.

ABSTRACT Solubility and liquid-liquid phase equilibrium data have been determined for the ternary systems Water-Phosphoric Acid-Di-n-propyl Ether as supplied by Merck (with about 6.4% of the isomer propyl-isopropyl ether), and Water-Phosphoric Acid-Di-n-propyl Ether (rectified up to less than 1% of propyl-isopropyl ether), at 25 and 40°C The temperatures at which three liquid phases at equilibrium appeared were 28.0-28.2°C and 49.0-50.0°C, respectively. The presence of the isomer propyl-isopropyl ether causes these systems to split into three liquid phases at equilibrium
CALCIUM AND FOREST SYSTEMS: DIFFUSION FROM DEEP SOURCES

Input-output budgets of temperate forest systems frequently indicate calcium depletion with time. Anthropic disturbances such as acidic deposition and forest harvesting are presumed to accelerate this loss, yet few studies have shown significant change in ecosystem Ca, including vegetation, surface soil, and forest floor. We propose that diffusion of exchangeable Ca from deep zones of higher concentration associated with less-weathered or unweathered materials to near-surface zones of low Ca concentration can explain some of the enigmatic nutrient budgets. We used data from Walker Branch Watershed, Tennessee (WBW), to explore this hypothesis. Radiotracer data were used to determine a diffusion coefficient for Ca empirically. A numerical model using this coefficient and reasonable estimates of the source concentration and depth yielded both a vertical gradient of soil Ca and a rate of Ca movement to the surface that were consistent with published observations. Diffusion has not previously been recognized as important for ion movement at these larger scales of time (e.g., years) or space (e.g., meters). Although our data were from WBW, the mechanism is universal and we can extend our results to nearly all forest systems with low Ca or other ions in the surface soil and higher concentrations with depth.
A novel antioxidant assay of ferric reducing capacity measurement using ferrozine as the colour forming complexation reagent.

Since antioxidants are health-beneficial compounds capable of removing reactive species, assay of total antioxidant capacity (TAC) by simple and low-cost methods is important. The magenta-coloured iron(II)-ferrozine (Fe(II)-FZ) complex showing an absorbance maximum at 562 nm has previously been utilized for iron-binding assays, but not for antioxidant determination. Ferrozine is a highly ferrous-stabilizing ligand such that ferric ion in the presence of ferrozine easily oxidizes antioxidants and is itself reduced to Fe(II)-FZ, yielding a very high molar absorptivity and thus enhanced sensitivity for most antioxidants. The hierarchic order of antioxidant power for common antioxidants was in accordance with known structure–activity relationships. The Fe(III)-FZ assay was applied to synthetic antioxidant mixtures to yield additive absorbance values, which is a prerequisite for precise determination of antioxidant capacity of complex mixtures. The calibration curves (lines) of trolox and quercetin individually and in herbal infusions—by using the method of standard additions—were parallel, confirming that the herbal antioxidants and trolox did not chemically interact among each other so as to cause apparent deviations from Beer's law. The proposed method was applied to medicinal plant infusions for total antioxidant capacity assay as trolox-equivalents, and the results were compared to those found with CUPRAC (cupric reducing antioxidant capacity), FRAP (ferric reducing antioxidant power) and Folin total phenols assays, the highest correlation being achieved with CUPRAC. In short, a novel ferric reducing assay for food antioxidants was introduced, which was superior to FRAP in regard to its realistic pH, enhanced sensitivity, faster kinetics, and absence of free Fe(II)—which can cause Fenton-type oxidations—in the reaction products.
Irradiated PVdF-HFP-montmorillonite composite membranes for the application of direct ethanol fuel cells

Montmorillonite supported poly vinylidene fluoride–hexa fluoro propylene composite membranes have been functionalized by an irradiation technique for the application of direct ethanol fuel cells. Structural characterizations of the fabricated membranes are examined by infrared and X-ray photoelectron spectroscopy analyses. The montmorillonite particles reduce porosity and stimulate rough nature to the PVdF-HFP membrane. Thermal stability of the irradiated membranes gets increased by the restricted polymeric segmental motion given via the montmorillonite particles. The ion exchange capacity values purely depend on the grafting degree values whereas water uptake values are influenced by the grafting degree as well as the concentration of montmorillonite particles. Irrespective of the grafting degree values, the adsorbed water molecules dissociate sulfonic acid units in a greater extent and favor ionic conductivity values. Tortuous path ways generated by the montmorillonite particles distort the molecular permeation which in turn results in the lower fuel cross over. By the synergistic combination of irradiation and nanocomposite techniques, demerits of the aforementioned individual techniques have been effectively tackled which in turn results in the extended direct ethanol fuel cell efficiencies of the fabricated fuel cell membranes and emerges its large scale applications.
Wine and music: diversification with investments of passion

Investors buy “investments of passion” – like classic cars, stamp collections, and art – for personal interest ahead of any financial benefits. This research aims to study the convergence of the two by examining fine wine and music as alternative asset classes. Analysis of each asset includes a history of price performance over the sample period, the asset's correlation with equity markets, the allocation between the asset and the S&P 500 according to an efficient portfolio frontier, and a maximum Sharpe ratio analysis. While acknowledging caveats such as the storage cost of wine, a short sample period, and market illiquidity, this study shows alternative assets such as wine and music can improve investors’ portfolios and provide financial benefits beyond personal passion.
Aliphatic and Aromatic Intramolecular C−H Activation on Cp*Ir(NHC) Complexes

Facile intramolecular aliphatic and aromatic C−H activations have been observed for a series of complexes based on the “Cp*Ir(NHC)” fragment (NHC = 1-diphenylmethyl-3-methylimidazol-2-ylidene, 1-tert-butyl-3-methylimidazol-2-ylidene, 1-benzyl-3-tert-butylimidazol-2-ylidene, and 1-benzyl-3-isopropylimidazol-2-ylidene). We have performed a series of experiments for elucidating the factors that determine the aromatic or aliphatic C−H activations that occur. In the cases where both aliphatic and aromatic C−H activations are possible, steric factors govern the selectivity of the reaction.
A Hierarchical K-Means-Assisted Scenario-Aware Reconfigurable Convolutional Neural Network

The superiority of convolutional neural network (CNN) has been proven in various object recognition tasks and has received much attention. However, the modern CNN approaches usually that assume the testing data and the training data belong to an identical category. Therefore, the current CNN approaches are not efficient for some applications with multisource data (i.e., the input data come from different sources), such as remote sensing scene. To increase the adaptability of the involved CNN approach, we first propose a $K$ -means-assisted scenario-aware reconfigurable convolutional neural network (KASR-CNN) mechanism. The KASR-CNN is composed of a fully convolutional autoencoder-based $K$ -means clustering (FCA-KC) and a reconfigurable convolutional neural network (RCNN), which are used to perform the coarse-grained classification and fine-grained classification to the input data, respectively. Furthermore, a Lego-like architecture design methodology is proposed to reduce the design complexity and improve computing flexibility. To show the adaptability, the KASR-CNN mechanism has been applied to different CNN models. In addition, the KASR-CNN has been verified on the Xilinx Zynq-ZC706 field-programmable gate array (FPGA) and implemented with TSMC 40-nm technology. Compared with the conventional approaches, the proposed KASR-CNN can help the involved CNN model to improve 3.73%–36.65% classification accuracy with only 0.38%–0.74% area overhead.
An Empirical Analysis of BERT Embedding for Automated Essay Scoring

Automated Essay Scoring (AES) is one of the most challenging problems in Natural Language Processing (NLP). The significant challenges include the length of the essay, the presence of spelling mistakes affecting the quality of the essay and representing essay in terms of relevant features for the efficient scoring of essays. In this work, we present a comparative empirical analysis of Automatic Essay Scoring (AES) models based on combinations of various feature sets. We use 30-manually extracted features, 300-word2vec representation, and 768-word embedding features using BERT model and forms different combinations for evaluating the performance of AES models. We formulate an automated essay scoring problem as a rescaled regression problem and quantized classification problem. We analyzed the performance of AES models for different combinations. We compared them against the existing ensemble approaches in terms of Kappa Statistics and Accuracy for rescaled regression problem and quantized classification problem respectively. A combination of 30-manually extracted features, 300-word2vec representation, and 768-word embedding features using BERT model results up to 77.2 ± 1.7 of Kappa statistics for rescaled regression problem and 75.2 ± 1.0 of accuracy value for Quantized Classification problem using a benchmark dataset consisting of about 12,000 essays divided into eight groups. The reporting results provide directions to the researchers in the field to use manually extracted features along with deep encoded features for developing a more reliable AES model.
Strategic investment decision-making: A theoretical perspective

There is a stream of research that has introduced strategic investment decision-making (SIDM) through case studies and organisation-based fieldwork. However, a systematic theorisation around SIDM processes and practices still under-presented in the literature. This research aims to show how strong structuration theory (SST) could be used as an appropriate theoretical lens to explore how SIDM studies are theorised and conducted. Through employing the parameters and the concepts of SST within the SIDM context, we found that SID is a judgemental decision that is constructed by various influences. SIDs are not isolated from the social, political, and economic aspects. Subjective judgements and the decision-makers’ intuition are crucial throughout the process of SIDM. Therefore, SIDs cannot be abstracted as an objective decision-based on applying investment appraisal technical methods. The theoretical lens presented in this paper will enable researchers to drill down into the ‘ontic’ level to empirically explore in-depth the complex interrelationships between various agents and structures which, arguably, fits the SID context. Furthermore, this paper will help scholars understand how SID is made from SST perspective and guide them to conduct future research to build on and also help executives to be guided by
Mehlich Extractable and Total Elemental Concentrations in South Carolina Soils

Abstract Mehlich‐1 and Mehlich‐3 extracts of soils collected from two depths at 50 sites distributed across South Carolina were compared with total soil digests to determine whether either soil extract would serve as a reliable indicator of total elemental concentration. Eighteen elements, including several of environmental concern, were measured. The sites were located in five different land‐resource regions of the state and had different cropping histories. Compared to the total concentration, recovery ranged from less than 1% of the iron (Fe) to almost 50% of the sodium (Na) for Mehlich‐1. Mehlich‐3 recovered larger amounts of all elements than did Mehlich‐1, but neither extract was a good indicator of total concentration. Although correlations of Mehlich and total concentration were significant for aluminum (Al), cadmium (Cd), copper (Cu), magnesium (Mg), manganese (Mn), and zinc (Zn), only for Cu and Mn was more than 50% of the variation accounted for (R2>0.50). There were regional differences in Mehlich concentrations for a few of the elements, but unlike total concentrations, Mehlich concentrations were not correlated with clay content. There were indications that Mehlich‐3 is more effective than Mehlich‐1 at extracting recently applied Zn, whereas Mehlich‐1 is more effective in extracting indigenous Zn. Land cropped for long time periods to cotton had significantly higher Mehlich‐3 concentrations than land used for production of other field crops, pasture, or forest products. Pastures had significantly higher concentrations of Cu than other sites. Forest sites had lower concentrations of calcium (Ca), Mg, potassium (K), phosphorus (P), and Zn than other sites, as would be expected because these elements are routinely applied to cropland. Technical Contribution No. 4980 of the Clemson University Experiment Station. This material is based upon work supported by the CSREES/USDA, under project number SC‐1700194, and United States Environmental Protection Agency grant number C‐09994629‐97 as part of a 319 grant administered by the South Carolina Department of Health and Environmental Control.
In silico analysis of FLP 18 gene of Anguina tritici and phylogenetic analysis with other nematodes

flp 18is a neuropeptide coding gene of FMRFamide-like peptides family having important role in behavioural regulation such as locomotory, feeding and reproduction of nematodes. Genome annotation of the newly sequenced genome of seed gall nematode (Anguina tritici) has revealed the presence of flp 18 in their genome. flp 18 gene has been proven as effective target for management of Meloidogyne incognita. In view of importance of this gene here we analyse the significance of flp 18 gene in A. tritici in different nematode species through the In silico approach. Homologus nucleotide sequences in other nematode species for the gene flp 18 were obtained on performing nucleotide BLAST in WormBase Parasite database. Multiple sequence alignment, identity and phylogenetic analysis were performed on the retrived homologus sequences using CLUSTAL W programme. The BLAST result revealed the presence of flp 18 hits in different groups of plant parasitic nematodes with best hit (76) to Ditylenchus dipsaci. Based on the finding it has been suggested that the flp 18 of A. tritici is conserved with identical homologs, and might have functional similarity among different nematodes species.
Energy Efficient Resource Allocation in Terahertz Downlink NOMA Systems

Terahertz (THz) band has attracted considerable interest recently due to its superior high frequency and large available bandwidth. THz could act a vital part in the sixth generation (6G) mobile communication networks. In this paper, we introduce the downlink non-orthogonal multiple access (NOMA) technology into THz band small cell networks, where the total performance is optimized considering the two key enabling technologies. In order to decrease the energy consumption triggered by increasing of wireless services, we pay great attention to energy efficiency (EE) optimization and resource allocation in the THz-NOMA downlink systems by solving the subchannel assignment and power optimization. We first exploit a channel model for the THz-NOMA downlink system by using the key features of THz-NOMA networks. Then we utilize Dinkelbach-style algorithm to solve the resource allocation problem and decompose it into two subproblems. A subchannel assignment algorithm and a power optimization based on alternative direction method of multipliers (ADMM) algorithm are developed to get the solution. Finally, to embody the strengths of THz-NOMA performance, we compare our proposed schemes against the conventional schemes. Simulation results yield substantially higher EE and further prove the availability of our proposed schemes.
Bioavailable tests: Alternatives to standard soil extractions

Abstract Due to the complexity of the soil plant system and in spite of the enormous amount of information available, the search for better methods to determine the bioavailability of nutrients to plants continues to be important. The large number of methods of soil analysis available worldwide in routine soil testing is an unquestionable demonstration of the lack of agreement on best alternatives. The question discussed in this paper, based on a literature review, is if those methods, considered here as the “standard methods”; of soil analysis, are the best possible alternatives for the evaluation of bioavailability of elements in soil. As alternative non‐standard methods, electroultrafiltration (EUF), the extraction with 0.01 mol calcium chloride (CaCl2 L‐1solution, the extraction with ion‐exchange resin and the adsorption of phosphorus (P) on iron oxide treated paper filter (Pi), were considered. These four methods were compared with the standard methods Olsen, Mehlich 1, Bray 1, Mehlich 3, AB‐DTPA, Eg.
Negative Emotions and Coping Behaviors of Passenger in the Airline Industry, Vietnam

In Vietnam, the airline service sector plays an important economic role. However, it is a complicated industry that is open to failures. Negative emotions are an essential variable for the airline service industry because they can trigger a variety of coping behaviors that affect consumer loyalty as well as the image and reputation of the airline service providers. However, negative emotions and the accompanying coping behaviors are often investigated partially or as separate issues, thus leading to an incomplete understanding. This study is conducted to fill this gap by proposing and testing the causal relationship between negative emotions (anger, frustration, regret) and coping behaviors (complaint, negative word-of-mouth (WOM), and switching intention) in the context of the airline industry. Eight research hypotheses are tested. Using the partial least squares structural equation modeling (PLS-SEM) on a sample of 587 passengers in Vietnam, the empirical results show that anger and frustration influence complaints, negative WOM, and switching intention, while regret leads to switching intention and negative WOM. Thus, the research has important academic and practical implications. The empirical outcome could be of major importance for airline companies in planning to provide new services and achieve high performance in the long run.
The design of calorimeters for the determination of ion beam intensities

Calorimetric methods for determining the total particle flux of ion beams are discussed. Three types of calorimeter are described which, from experience gained with 25-50 mA, 10 keV and 0.2 mA mean, 500 keV proton beams, have proved suitable for this purpose. The sensitivity of the calorimeters can be either calculated from elementary theory, or obtained directly by a convenient method of calibration.
Continuous Human Activity Recognition in Logistics from Inertial Sensor Data using Temporal Convolutions in CNN

Human activity recognition has been an important task for the research community. With the introduction of deep learning architectures, the performance of activity recognition algorithms has improved significantly. However, most of the research in this area has focused on activity recognition for health/assisted living with other applications being given less attention. This paper considers continuous activity recognition in logistics (order picking and packing operations) using a convolutional neural network with temporal convolutions on inertial measurement sensor data from the recently released LARa dataset. Four variants of the popular CNN-IMU are experimented upon and a discussion of the results is provided. The results indicate that temporal convolutions are able to achieve satisfactory performance for some activities (hand center and cart) whereas they perform poorly for the activities of stand and hand up.
Effect of Calcium Salts of Glutaric Acid and Pimelic Acid on the Formation of β Crystalline Form in Isotactic Polypropylene

The effect of calcium glutarate (Cagt) and calcium pimelate (Capt) on the formation of β crystalline form in isotactic polypropylene (iPP) after isothermal crystallization at 130°C for 30 min has been investigated. The maximum KWAXD and KDSC values were 31.97% and 38.06%, respectively, for iPP doped with 0.2 wt. % Cagt. The maximum values of KWAXD and KDSC were 73.60% and 68.44% for iPP doped with 0.3 wt. % and 0.15 wt. % Capt, respectively. The crystal size of iPP doped with Capt is finer than that of iPP doped with Cagt. It is shown that the β nucleation ability of Capt is superior to that of Cagt. The difference in the β nucleation ability between Cagt and Capt is explained by the structural difference of the nucleators with β-iPP.