Miracle-dz/UniFAR-FTUs huggingface dataset:
OPPORTUNITIES FOR THE DEVELOPMENT OF A GREEN ORGANISATION IN THE CONTEXT OF NATIONAL AND INTERNATIONAL STRATEGIC DOCUMENTS AND INICIATIVES

The article emphasizes the aspects of organisational development in the context of green organisation, de- scribing the importance of changes in an external environment for the development of the organisation. Purpose – the purpose of the article is to analyse the relevance of green organisation development at the national and international levels by examining it through the prism of strategic documents and initiatives. In order to determine the development directions of the green organisation on the basis of strategic documents and initiatives. Research methodology – the methods of critical analysis of scientific literature, strategic documents, initiatives and synthesis as well as abstrahation have been applied. Findings – main findings of the research proved that development of green organisation is relevant in the context of key international and national strategic documents. Also the definition of the development of green organisations is proposed by authors. The analysis of strategic documents and initiatives at the national and international levels has shown that their impact on the development of a green organisation can be both direct and indirect. Research limitations – the limitation of this reseach is that mainly key international and national strategic documents were analyzed. Analysis of other strategic documents can be stated as a direction for future research. Practical implications – the results of the research could be used as a basis for the promotion of the development of green organisations at the national and international level both directly and indirectly. Originality/Value – the originality of this research can be defined by complex approach to analysis related to the impact of actual legal regulation to the development of green organisations.
A desert songbird with no confamilials in the Western Hemisphere (Verdin, Auriparus flaviceps) investigates divergent conspecific songs

ABSTRACT Most birds that show geographic variation in their songs discriminate between local and foreign songs, which may help them avoid unnecessary conflicts with vagrant individuals or similar-sounding congeners. However, some species respond equally to foreign and local songs, which may be useful if foreign individuals present territorial threats or if there are no sympatric congeners to avoid. Species without sympatric congeners are not commonly tested in playback studies, but they offer an opportunity to see how song variation and recognition unfolds when the pressure to avoid similar congeners is absent. Here, we use Verdins (Auriparus flaviceps), a monotypic genus of songbird with no confamilials in North America, to explore song variation and recognition in a species living without close relatives. We assessed geographic variation in song across the Verdin range and conducted a playback experiment using exemplars from 2 acoustically divergent and geographically distant regions as treatments. We found significant geographic variation in song that mapped well onto ecologically distinct desert regions. We found that Verdins had stronger vocal responses to local-sounding songs, but had equal movement responses to local-sounding and foreign songs. These results are similar to results found in other species without sympatric congeners and provide an example of a species that investigates acoustically divergent conspecific songs, despite recognizing salient differences in those songs. LAY SUMMARY Many songbirds have geographic variation in their songs. Most species prefer songs that sound local, or familiar, but some will respond to foreign songs just as readily as they respond to local songs. This may be more likely if there are no similar-sounding relatives around, and therefore no risk of mistaken identity. Few species without close relatives have been studied, so we study one that is also a desert specialist, the Verdin (Auriparus flaviceps). We found that Verdins have geographic variation in song that mapped well onto large desert habitat regions, and they sing less to playbacks of songs from distant regions. However, despite recognizing salient differences in foreign songs, they are just as likely to approach foreign songs as local-sounding songs, as are other species that live without close relatives. When close relatives are absent, birds may be more permissive in what they consider a song worth investigating.
OptiMEMS: An Adaptive Lightweight Optimal Microgrid Energy Management System Based on the Novel Virtual Distributed Energy Resources in Real-Life Demonstration

As microgrids have gained increasing attention over the last decade, more and more applications have emerged, ranging from islanded remote infrastructures to active building blocks of smart grids. To optimally manage the various microgrid assets towards maximum profit, while taking into account reliability and stability, it is essential to properly schedule the overall operation. To that end, this paper presents an optimal scheduling framework for microgrids both for day-ahead and real-time operation. In terms of real-time, this framework evaluates the real-time operation and, based on deviations, it re-optimises the schedule dynamically in order to continuously provide the best possible solution in terms of economic benefit and energy management. To assess the solution, the designed framework has been deployed to a real-life microgrid establishment consisting of residential loads, a PV array and a storage unit. Results demonstrate not only the benefits of the day-ahead optimal scheduling, but also the importance of dynamic re-optimisation when deviations occur between forecasted and real-time values. Given the intermittency of PV generation as well as the stochastic nature of consumption, real-time adaptation leads to significantly improved results.
Modeling an effectual multi‐section You Only Look Once for enhancing lung cancer prediction

The shape and size of nodules are significant pointers of malignancy in cancer diagnosis. Moreover, considerable capture of nodules' structural data attained from computed tomography (CT) scans in computer‐aided design is a confronting task. Various investigations deal with computationally deep ensemble approaches/convolutional neural network (CNN) models; however, sampling tumors based on multi‐section‐You Only Look Once (MS‐YOLO) architecture, this anticipated model acquires nodules' multi‐sections from various views and encodes nodule's information to data aggregation from diverse cross‐sections through pooling layers. Subsequently, the features are utilized for the nodule classification task. This MS YOLO does not need any nodules' spatial annotation. However, it works directly over the cross‐section acquired from enclosed nodule volume. This work has been analyzed using LUNA R16 dataset. It attains adequate performance with a mean value of 90.8% classification accuracy. Anticipated architecture is cast‐off to choose cross‐section determination of malignancy that helps in output interpretation. The proposed model shows better trade‐off among previous methodologies. Simulation was carried out in MATLAB environment.
The non-reacting flow characteristics of pylon and wall injections in a dual combustion ramjet engine

The influence of pylon and wall injection in coaxial jets of a Dual Combustion Ramjet engine is numerically investigated in a non-reacting flow field. The supersonic combustor is modeled and analyzed using the commercial CFD software ANSYS 18.0. The three-dimensional compressible Reynolds-averaged Navier-Stokes (RANS) equations coupled with the SST k-ω turbulence model have been used to analyze the coaxial mixing characteristics of the jets. The numerical study is validated with the experimental data of the wall static pressures measured in the combustor’s flow direction. The pylon and wall injectors are located symmetrically at the gas generator’s exit nozzle, and the air is used as the injectant to simulate gaseous fuel. Three injection pressures are used for the study to understand the flow field characteristics in the injector regime. Also, the gas generator downstream direction is investigated. The shock waves generated from the gas generator nozzle enhance the mixing of the coaxial jets with minimum total pressure loss. The shock wave interactions are noticed with reducing intensity within the supersonic combustor for pylon injection, leading to higher total pressure loss than the wall injection. The pylon injection provides the spatial distribution of fuels compared to the wall injection in the coaxial supersonic flow field.
Multiplicity of positive solutions to a critical fractional equation with Hardy potential and concave–convex nonlinearities

The aim of this paper is to study the following fractional critical problem with Hardy potential and concave–convex nonlinearities where is the fractional Laplace operator, , is a smooth bounded domain containing the origin, N>2s, , , with is the fractional critical Sobolev exponent. Under suitable hypotheses on μ and N, we prove the existence of at least two positive solutions for the concave case with for some . Moreover, in the convex power case , we show that there exists at least one positive solution for suitable values of λ depending on the dimension N.
Evaluation of Sentiment Analysis via Word Embedding and RNN Variants for Amazon Online Reviews

Consumer feedback is highly valuable in business to assess their performance and is also beneficial to customers as it gives them an idea of what to expect from new products. In this research, the aim is to evaluate different deep learning approaches to accurately predict the opinion of customers based on mobile phone reviews obtained from Amazon.com . The prediction is based on analysing these reviews and categorizing them as positive, negative, or neutral. Different deep learning algorithms have been implemented and evaluated such as simple RNN with its four variants, namely, Long Short-Term Memory Networks (LRNN), Group Long Short-Term Memory Networks (GLRNN), gated recurrent unit (GRNN), and update recurrent unit (UGRNN). All evaluated algorithms are combined with word embedding as feature extraction approach for sentiment analysis including Glove, word2vec, and FastText by Skip-grams. The five different algorithms with the three feature extraction methods are evaluated based on accuracy, recall, precision, and F1-score for both balanced and unbalanced datasets. For the unbalanced dataset, it was found that the GLRNN algorithms with FastText feature extraction scored the highest accuracy of 93.75%. This result achieved the highest accuracy on this dataset when compared with other methods mentioned in the literature. For the balanced dataset, the highest achieved accuracy was 88.39% by the LRNN algorithm.
Film as Method in the Geohumanities

Filmmaking has become an increasing focus of interest within geography, the geohumanities, and related fields. The use of film ranges from enhanced forms of ethnographic fieldwork to the production of feature-length documentaries shown at international festivals. The making of documentaries has become an increasingly significant research method in itself that has the potential to become a widely recognized type of interdisciplinary research output. How should we interpret the role of film in relation to wider epistemological debates over the production of knowledge? How can we contextualize the methodological turn toward film within the broader historiography of filmmaking and the cinematic apparatus? This article argues that documentary film has a distinctive role to play in expanding the research imagination, enhancing pedagogic practice, reaching new audiences, and producing unique cultural artifacts. At the same time, however, the use of film is also entrained in complex debates concerning the verisimilitude of representational practices and the wider institutional context for the production and evaluation of knowledge.
The Role of Intellectual Capital in Increasing Company Value with Profitability as an Intervening Variable

The company's current value is not only determined by tangible assets. The ability of intangible assets in increasing company value today is very interesting to be studied. Intellectual Capital is an intangible asset in the form of knowledge, talents, skills, information, networking that can be managed by a company to increase its competitive ability. This study investigated the effect of intellectual capital on firm value both directly and indirectly with profitability functioning as an intervening variable. The firm value as a dependent variable is proxied by Tobin's Q, while the profitability variable that functions as an intervening variable is proxied by ROA. Intellectual capital is measured using VAIC, which consists of 3 measurement components, that is Value-Added of Human Capital (VAHU), Value-Added of Employed Capital (VACA), and Structural Capital Value-Added (STVA). The research method used multiple regression analysis tools with a panel data approach and path analysis. The subject of this study is companies that are in the hotel, restaurant, and tourism subsector, which are listed in the Indonesia Stock Exchange in the 2014-2018 period selected using purposive sampling techniques. Research data is in form of secondary data extracted from the company's financial statements during the study period. The results show that profitability, VACA, and VAHU directly affect the value of the company, while only VAHU directly affected the profitability of the company. Meanwhile, in the indirect relationship using the Sobel-Test, the results show that the profitability of the company can only mediate VAHU toward the company value, but profitability cannot mediate the effect of VACA and STVA on
Surprising Drought Tolerance of Fir (Abies) Species between Past Climatic Adaptation and Future Projections Reveals New Chances for Adaptive Forest Management

Research Highlights: Data of advanced-age provenance tests were reanalyzed applying a new approach, to directly estimate the growth of populations at their original sites under individually generated future climates. The results revealed the high resilience potential of fir species. Background and Objectives: The growth and survival of silver fir under future climatic scenarios are insufficiently investigated at the xeric limits. The selective signature of past climate determining the current and projected growth was investigated to analyze the prospects of adaptive silviculture and assisted transfer of silver fir populations, and the introduction of non-autochthonous species. Materials and Methods: Hargreaves’ climatic moisture deficit was selected to model height responses of adult populations. Climatic transfer distance was used to assess the relative drought stress of populations at the test site, relating these to the past conditions to which the populations had adapted. ClimateEU and ClimateWNA pathway RCP8.5 data served to determine individually past, current, and future moisture deficit conditions. Besides silver fir, other fir species from South Europe and the American Northwest were also tested. Results: Drought tolerance profiles explained the responses of transferred provenances and predicted their future performance and survival. Silver fir displayed significant within-species differentiation regarding drought stress response. Applying the assumed drought tolerance limit of 100 mm relative moisture deficit, most of the tested silver fir populations seem to survive their projected climate at their origin until the end of the century. Survival is likely also for transferred Balkan fir species and for grand fir populations, but not for the Mediterranean species. Conclusions: The projections are less dramatic than provided by usual inventory assessments, considering also the resilience of populations. The method fills the existing gap between experimentally determined adaptive response and the predictions needed for management decisions. It also underscores the unique potential of provenance tests.
Structure based virtual screening: Fast and slow

For many decades virtual screening methods have provided a convenient and cost effective in silico solution in the early stages of drug discovery. In particular, molecular docking uses structural information to approximate protein–ligand recognition, providing valuable information for large chemical libraries at a fast pace with multiple success stories to validate the approach. Nevertheless, fast turnaround of results required assumptions and approximations which compromise the accuracy of these algorithms. On the other side of the spectrum, physical‐based molecular simulations offer more precise and realistic models of protein–ligand binding at the cost of being slower and requiring more expensive computing infrastructure. Both fast and slow approaches are useful and solve different aspects of the same problem. Here, we aim to review these approaches focusing on their capabilities, context of usage and limitations, presenting multiple examples along the way.
Factors affecting the spatial distribution and co‐occurrence of two sympatric mountain ungulates in southern Mongolia

Co-occurrence of ungulates in multi-species assemblages has fascinated ecologists because these species seemingly belong to the same guild – feeding on plants. Across large parts of the high mountains of Central Asia, ibex (Capra sibirica) and argali (Ovis ammon), both predominantly grazers, co-occur at local and regional scales. However, little is known about the ecological and anthropogenic factors that influence their spatial distribution, co-occurrence and habitat use. We examined factors affecting the distribution and co-occurrence of these two sympatric species in Tost Tosonbumba Nature Reserve in southern Mongolia using an occupancy modeling approach. Specifically, we used single species occupancy models to examine the influence of road density, livestock density, terrain ruggedness and elevation on occupancy of these two species separately. We then assessed how these two species influence each other’s distribution by using multi-species occupancy models. The model-averaged occupancy probabilities for ibex and argali were 0.64 0.3 SE and 0.44 0.2 SE, respectively. Terrain ruggedness positively influenced ibex distribution, while it negatively affected the occupancy of argali. We found limited evidence of relationship with factors associated with human disturbance. The species interaction factor, which indicates the level of co-occurrence, suggested that ibex and argali occurred independent of each other (φ =0.72 0.3 SE). Together, our results imply that there was limited co-occurrence between the two species and that this was largely driven by terrain ruggedness at the scale of the home range. These results suggest that topography plays an important role in enabling these two species to co-occur at the regional scale.
Stability and performance analysis of wireless powered communication networks

In RF-based wireless powered communication networks (WPCNs), the wireless charging rate at a device is usually low or unstable because of health concerns or time-varying characteristics of wireless channels. Under a low charging rate, the data backlog at a wireless device may be continuously increasing, leading to system performance degradation and data loss. To keep a wireless powered device stable and preserve a finite data backlog, the upper limit of data arrival/acquisition rate at a wireless powered device must be solved under the given data transmission rate and wireless charging rate. Hence, in this paper a novel two-dimensional continuous-time Markov chain model was proposed for analyzing the stability condition of a wireless powered device with a finite energy storage buffer. The average number of data packets, average packet delay, and energy shortage probability at a wireless powered device were analyzed as well. Additionally, simulations were conducted to validate the analytic results and demonstrate that the obtained stability condition is necessary and sufficient for the wireless device.
Psychological performance at work: Theoretical framework

In spite of an increasing number of studies in the field of organizational behavior, little is known about the antecedents of individual performance and its final influence on the organizational outcomes. A lot of factors with physical and psychological contents influence the behaviour of members in an organization. This study examines the literature on psychological performance and its influences upon work. Psychological performance is a new theme in the field of organizational behavior. It is proposed that a lot of factors influence the individual performance which in turn effects the organizational outcomes. Specifically, psychological performance of the members has an important role in working environment. However, no significant research conducted on the subject can be found in the available literature. In view of this, the importance of psychological performance for organizations and its members is presented in this paper. Copyright © AJSSAL, all rights reserved.
Parental participation and connectedness through family social capital theory in the early childhood education community

Abstract This paper examines the ways in which parents talk about their participation in Early Childhood Education and Care (ECEC), and the factors that, according to them, promote parental participation. Although parental participation has been studied to an extent as regards children’s academic attainment, up-to-date knowledge on the broader phenomena related to parental participation is lacking. The data were collected from a Finnish ECEC center that has a long tradition of encouraging parental participation in its operational environment in municipal ECEC center and were analyzed through the Social Capital Index. The results provide targeted knowledge on what tools could perhaps be functional in supporting parental participation. The findings indicate that the feeling of participating and being active is strongly influenced by the feeling of connectedness to and within the ECEC community among parents, children, and ECEC educators. The opportunities, structures, and traditions that enable parental participation are essential.
Bioethanol production from urban cellulosic waste employing Alcaligenes faecalis HI-1 isolated from gut of termite Heterotermes indicola

This study assessed the potential of termite gut inhabiting bacteria towards bioconversion of cellulosic waste into biofuel. Total seven bacterial isolates from the gut of Heterotermes indicola were isolated. Among all the isolates, HI-1 produced the largest zone upon primary screening. Untreated paper had more cellulose content (73.03%) than acid (0.5%) treated paper that was used as a lignocellulosic substrate for saccharification. Among all the isolates tested, glucose yield (1.08mg/mL) was high for HI-1 isolate. Several factors were considered for optimizing augmented glucose yield (8.57mg/mL) and growth (8.07×10cfu/mL), such as temperature 37°C, pH 4.5, 5% (w/v) substrate concentration, 6 % bacterial inoculum size, agitation 150 rpm with PEG 0.25 % and Ca ions 0.002 g/L. Overall 8-fold increase in glucose yield was achieved. Enzyme activity of HI-1 showed higher endoglucanase 0.29 ± 0.01 (U/mL/min) and exoglucanase 0.15±0.01 (U/mL/min) activity under optimum conditions, mentioned above. temperature 37°C, pH 4.5, substrate concentration 5%, inoculum size 6%, surfactants PEG 0.01%, ions Ca(0.002g/L) and agitation (120 rpm). Simultaneous saccharification and fermentation (SSF) of hydrolyzed office paper yielded 5.43mg/mL bioethanol. According to 16S rRNA sequence homology, the bacterial isolate H1 was identified as Alcaligenes faecalis. Bioethanol production from office paper untreated waste proved an effective strategy. Bacteria having natural tendency towards cellulosic waste consumption are promising for bioconversion of cellulosic waste to valuable products.