Miracle-dz/UniFAR-FTUs huggingface dataset:
The Survey of the Relationship between Information Technology Acceptance and Organizational Agility from the Perspective of the Public Institutions

─ According to the extensive aspects of the organizational agility in the science of management and also the considerable role played by information technology in the development of agility in an organization, the current study aims at the survey of the relationship between information technology acceptance and organizational agility from the perspectives of the public organization staff members who made a constant use of information technology. In the present study the survey-field study method has been applied and the questionnaire reliability and content validity had been previously confirmed by taking advantage of Cronbach’s alpha method, and the study population of the current study were public organizations’ staff members and due to the low number of the study population members we decided to select all of the public organizations’ staff as the study sample volume. Also, the data were analyzed by making use of descriptive statistics and linear regression test. The study findings were indicative of the positive relationship between four factors of perceived usefulness, perceived ease of use and attitude towards using and intention to use technology with agility. Also, the study results indicated that the agility level in an organization increases along with the increase in the technology acceptance rate in public sector and the key to this increase was the improvement in the intention to use technology and institutionalization of positive mental norms for making use of technology among the staff.
Towards Automated Video Game Commentary Using Generative AI

In recent years, video game streaming has enjoyed ever-growing popularity. While streaming gameplay, a streamer is also expected to provide commentary on gameplay and otherwise entertain the audience. The mental burden for providing such commentary while also playing the game may provide a barrier of entry for new streamers. In this paper, we present an approach to automatically generate streaming commentary during gameplay for the game League of Legends. Our system recognizes key events, and uses generative AI services to generate voice output. We also present a preliminary evaluation of our system, both in quantitative terms of event recognition accuracy, as well as qualitatively by discussing the generated commentary.
Performance of Trichoderma fortiﬁed composts in controlling collar rot caused by Sclerotium rolfsii of soybean

Seedling diseases and collar rot/stem rot ( Sclerotium rolfsii ) are the main constrains for soybean production in Bangladesh. Number of experiments were undertaken to control seedling mortality and stem rot of soybean using Trichoderma fortiﬁed compost at Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU) research ﬁeld. Pathogenicity test conﬁrmed that S. rolfsii (isolate SR4) causes 95% seedling mortality therefore, considered as the most aggressive isolate. Trichoderma harzianum (Isolate-Chan 6) was used for inocula preparation with different composting substrates like cow dung, saw dust, rice straw, water hyacinth and poultry manure to prepare Trichoderma fortiﬁed composts. Among the composts, Trichoderma fortiﬁed poultry manure was found as the best treatment in reducing 75.45% pre-and post-emergence seedling mortality and diseases severity (84.53% reduction) as well as increased yield (80.91% increase) and yield attributing characters such as 55% increase of plant height and 27% increase of 1000-grain weight compared to the control. However, other composts also showed good response in reducing seedling mortality and growth promotion though they were not similar in performance with Trichoderma fortiﬁed poultry manure. Therefore, Trichoderma fortiﬁed composts have the immense potentiality to suppress diseases and improve yield of soybean. These studies should be conducted at the farmer’s ﬁeld before validating the substrates as Trichoderma fortiﬁed composts.
Assessment of Validity of MODIS Active Fire Products for Monitoring of Small Fires in Caspian Forests of Northern Iran

: MODIS active fire products are commonly used to study the pattern of fire distribution. However, the accuracy of the products varies in different places. In this study the accuracy of MODIS active fire products in the Caspian forests of Northern Iran have been examined. 231 reference fires were collected through 2006-2010. Most fires are small in Caspian forests of Northern Iran; therefore 75.6% of fires through 2006-2010 were less than 10 hectare in size. These data were used to evaluate Terra and Aqua MODIS active fire products, if the fire products matched the reference data, the detection was considered as successful. 26 cases of the selected reference fires were successfully detected. It was found that the chances of successful detections decreased from the east to the west of the Caspian region. The number of successful detections in the Golestan, Mazandaran and Gilan provinces were 14, 10 and 2, respectively. Also, 50 undetected reference fires coincided with satellite passes (64 passes) and were selected to find out the reasons of unsuccessful detections. In situ, brightness temperature in 4-µm channel, t and reflectance in 0.86-µm channel were extracted for this purpose. The brightness temperature in 62 satellite passes out of 64 was less than 310 k. Low temperatures, cloud cover, satellite passes that did not coincide with firing time, dense canopy and small fire size were found the main reasons for unsuccessful fire detection. The study showed that fire products are not fitting for accurate fire detection in the Caspian forests of Northern Iran. Therefore, the fire detection algorithm should be improved for such regions.
Community perspectives on cruise tourism in Akaroa, New Zealand

This paper reports on research undertaken to examine community perspectives on cruise tourism in Akaroa, New Zealand. Since the 2011/2012 Canterbury earthquakes, Akaroa has been hosting the majority of cruise ship arrivals to Canterbury. This has had significant impacts, both positive and negative, on the Akaroa community. A survey of 316 respondents from the community was undertaken in May 2013, and yielded an overall response rate of 56.6 per cent. The results indicate that despite a significant increase in cruise ship arrivals, the community holds a largely favourable opinion of cruise tourism. Contrary to other social impact research in tourism, increasing numbers of tourists does not appear to be the main issue or concern. Rather, the particular pattern of cruise visitation, and the impact of this on existing patterns of tourist visitation over the summer period, is of greater significance to the Akaroa community.
Indigenous Malaria and Mosquito Control in England after the War, by P. G. SHUTE, F.R.E.S., Assistant Malaria Officer, Ministry of Health

BEFORE discussing the problem of potential post-war indigenous malaria in JLJ England, it will be worth while to consider briefly what happened towards the end of, and for a few years following, the war of igi4-i8. In the strictest sense, the word indigenous denotes of local origin. But by indigenous malaria we mean cases of malaria which were beyond doubt contracted in this country ; the parasites being of exotic origin and transmitted from one person to another by local mosquitoes. After the third year of the last war, very large numbers of troops who were suffering from malaria were invalided home and distributed to various special centres in England for treatment, convalescence and observation. By an unfortunate coincidence, some
Graph Self-supervised Learning via Proximity Divergence Minimization

Self-supervised learning (SSL) for graphs is an essential problem since graph data are ubiquitous and labeling can be costly. We argue that existing SSL approaches for graphs have two limitations. First, they rely on corruption techniques such as node attribute perturbation and edge dropping to generate graph views for contrastive learning. These unnatural corruption techniques require extensive tuning efforts and provide marginal improvements. Second, the current approaches require the computation of multiple graph views, which is memory and computationally inefficient. These shortcomings of graph SSL call for a corruption-free single-view learning approach, but the strawman approach of using neighboring nodes as positive examples suffers two problems: it ignores the strength of connections between nodes implied by the graph structure on a macro level, and cannot deal with the high noise in real-world graphs. We propose Proximity Divergence Minimization (PDM), a corruption-free single-view graph SSL approach that overcomes these problems by leveraging node proximity to measure connection strength and denoise the graph structure. Through extensive experiments, we show that PDM achieves up to 4.55% absolute improvement in ROC-AUC on graph SSL tasks over state-of-the-art approaches while being more memory efficient. Moreover, PDM even outperforms supervised training on node classification tasks of ogbn-proteins dataset. Our code is publicly available a .
Research Article Deep Graph Embedding for IoT Botnet Traffic Detection

Botnet attacks have mainly targeted computers in the past, which is a fundamental cybersecurity problem. Due to the booming of Internet of things (IoT) devices, an increasing number of botnet attacks are now targeting IoT devices. Researchers have proposed several mechanisms to avoid botnet attacks, such as identifcation by communication patterns or network topology and defence by DNS blacklisting. A popular direction for botnet detection currently relies on the specifc topological characteristics of botnets and uses machine learning models. However, it relies on network experts’ domain knowledge for feature engineering. Recently, neural networks have shown the capability of representation learning. Tis paper proposes a new approach to extracting graph features via graph neural networks. To capture the particular topology of the botnet, we transform the network trafc into graphs and train a graph neural network to extract features. In our evaluations, we use graph embedding features to train six machine learning models and compare them with the performance of traditional graph features in identifying botnet nodes. Te experimental results show that botnet trafc detection is still challenging even with neural networks. We should consider the impact of data, features, and algorithms for an accurate and robust solution.
Train 'n Trade: Foundations of Parameter Markets

Organizations typically train large models individually. This is costly and time-consuming, particularly for large-scale foundation models. Such vertical production is known to be suboptimal. Inspired by this economic insight, we ask whether it is possible to leverage others' expertise by trading the constituent parts in models, i.e., sets of weights, as if they were market commodities. While recent advances in aligning and interpolating models suggest that doing so may be possible, a number of fundamental questions must be answered to create viable parameter markets. In this work, we address these basic questions, propose a framework containing the infrastructure necessary for market operations to take place, study strategies for exchanging parameters, and offer means for agents to monetize parameters. Excitingly, compared to agents who train siloed models from scratch, we show that it is possible to mutually gain by using the market, even in competitive settings. This suggests that the notion of parameter markets may be a useful paradigm for improving large-scale model training in the future.
Performance of wide band connected arrays in scanning : the equivalent circuit and its validation through a dual-band prototype

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
or cooperation in the courtship display of the

We used experimental manipulations to test adaptive explanations for the courtship display of the male widow spider, Latrodectus paUidus O. Pickard-Cambridge 1872. Two hypotheses have been suggested to explain a long and complex male display: a) Cooperation of males and females in the effort to physically stimulate the female. As the time of male arrival is not predictable, females may delay sexual readiness until the appearance of a courting male, b) Conflict between males and females regarding the display cost. Females impose on the males an energetically costly display that may last several hours as a test of their quality. To test both hypotheses, we manipulated the previous experience of either the male or the female. We presented naive or experienced males (males that had courted and were accepted by females but were prevented from copulating) to females that were either naive or experienced (had been courted by a male but prevented from copulating). We also presented naive males to mated females. Following the stimulation hypothesis, courted females were presumed to have been stimulated to mate and thus were expected to accept non-courting males as mates. Both naive and mated females, however, were expected to await male stimulation before allowing copulation. In contrast, the conllict of interest hypothesis predicts that the female tests each male for quality indicators and therefore a non-courting male should not be accepted as a mate. Mated females, however, should apply a less stringent test to courting males. Our results show that 1) naive females prevented males that did not perform a full courtship display from entering the nest and mounting; 2) naive males courted virgin females with the full display, independent of the female previous courting history; and 3) naive males shortened their courtship when presented with mated females. The results are consistent with the conllict of interest hypothesis.
MIT Open Access Articles CHANDRA OBSERVATIONS OF SN 1987A: THE SOFT X-RAY LIGHT CURVE REVISITED

We report on the present stage of SN 1987A as observed by the Chandra X-Ray Observatory . We reanalyze published Chandra observations and add three more epochs of Chandra data to get a consistent picture of the evolution of the X-ray ﬂuxes in several energy bands. We discuss the implications of several calibration issues for Chandra data. Using the most recent Chandra calibration ﬁles, we ﬁnd that the 0.5–2.0 keV band ﬂuxes of SN 1987A have increased by ∼ 6 × 10 − 13 erg s − 1 cm − 2 per year since 2009. This is in contrast with our previous result that the 0.5–2.0 keV light curve showed a sudden ﬂattening in 2009. Based on our new analysis, we conclude that the forward shock is still in full interaction with the equatorial ring
Effect of Biochar with Traditional Farming Practices on the Growth and Yield of Wheat ( Triticum aestivum L.) At Reduced Irrigated Condition

: Wheat ( Triticum aestivum L.) is a leading cereal crop and important source of vegetable protein in human diet worldwide. Improving soil fertility in drought areas to ensure food security through increase wheat production is a major challenge. An experiment was conducted to evaluate the effect of biochar with conventional farming practices on growth and yield of wheat under different level of water stress condition in 2017 to 2018 at Sher-e-Bangla Agricultural University, Dhaka-1207. The field experiment was laid out in two factors split plot design with three replications. Five different levels of biochar (B = 0 t ha , B = 2 t ha , 1 2 1
Geothermal reservoir simulation: 1. Mathematical models for liquid‐ and vapor‐dominated hydrothermal systems

Two alternative mathematical models are presented that are suitable for numerical simulation of geothermal reservoirs. The general mathematical model describes the three-dimensional flow of single-component water (both one and two phase) and the transport of heat in porous media. It is composed of two nonlinear partial differential equations, posed in terms of fluid pressure and enthalpy, and appropriate boundary conditions. An alternative quasi-three-dimensional model is derived by partial integration (in the vertical dimension) of the three-dimensional equations. The reservoir is assumed to have good vertical communication so that vertical equilibrium (gravity segregation) between steam and water is achieved. The resulting equations, posed in terms of vertically averaged pressure and enthalpy, include effects of an inclined, variable-thickness reservoir and mass and energy leakage to confining beds.
Russian Disinformation in Eastern Europe. Vaccination Media Frames in ro.sputnik.md

The news site ro.sputnik. md is the Romanian language version of the Sputnik news website platform, owned by the Russian government, one of the main channels used by the Kremlin to disseminate mis- and disinformation across Russian borders. The current research aims to identify the frames associated with anti-COVID-19 vaccines, and the news values employed in constructing news discourse on vaccination in ro.sputnik. md media texts. To map the media frames and the lexical and discursive constructions, the research proposes a mixed methods content-based approach, where automated text analysis (frequency, co-occurrence, n-grams) is combined with thematic and discourse analysis. Six emphasis frames are identified in the corpus (N=1,165): Superiority of the Russian Sputnik V Vaccine, Fatal/Side Effects of EU Authorized Vaccines, Limitations of Individual Rights and Freedoms, EU and/or Romanian Authorities' Struggle, Children and Teenagers' Protection, and Big Pharma Conspiracy. The findings show that specific discursive patterns are associated with the negative news value: death, side effects (blood clot, thrombosis, coagulation), restrictions, and interdictions or warnings (serious, risk, negative, panic, etc.), while the conflict news value is associated with warfare vocabulary (defense, threat, battle, fire, gunpowder, etc.), and eliteness, with well-known actors (state leaders, European leaders, famous "conspirators") and countries (powerful international actors, meaningful neighbours).
Training to Human Resource and Entrepreneurship Development

─ Develop a process improvement according to a set of indicators, norms, and values. Process development and scale various purposes. In a broad sense, these dimensions include aspects of political, economic, social, and cultural. The concept of human development in general and in particular, one of the most important and controversial issues and challenges is among the world countries, especially developing countries. Human development and national aspirations of the people of all countries. The development of the direct subordination of the values and beliefs of each community, and the issues and challenges facing the human era. Developing better and more humane life to the population donates. Achievement of sustainable development, although difficult and complicated, but not impossible and should not be discouraged from trying to achieve it. In the present article, with the aim of introduction of entrepreneurship and human development, as well as some important issues associated with them, brief definitions, the importance of teaching entrepreneurship to human development and its history, as well as the results of some studies related to entrepreneurship and human development, goals and required training related to entrepreneurship and human development provided at the end of the article, the conclusion of these in the form of Conclusions, applications, management, and related suggestions for future research follow-up is provided
Using Melodic Motifs for Automatic Transcription of White Mensural Notation via N-Grams

Manually transcribing music sheets is a time consuming task, and it is therefore desirable to have a system that performs the task automatically. Optical music recognition (OMR) is a field of research that investigates how to build such a system. The field has seen many developments over the years, but the problem remains far from solved. This research focuses on building a system capable of automatically translating music scores written in early notation. While traditional methods perform symbol detection once, this paper performs it twice. The first detection is carried out in order to recognise the musical symbols, and the second to detect the note heads. Doing so should achieve a greater performance in recognising the notes. A novel approach is introduced by supplying the process with knowledge about motifs derived from N-grams. These N-grams form the patterns in pieces and are used to train a Random Forest (RF) model. The output of the OMR system is then parsed into the model in order to catch errors. The output of the OMR system is then fed into the model in order to fill in missing notes. Furthermore, a second approach is introduced, by means of n-gram matching using a sliding window approach. In this paper, both N-grams derived from a gold standard and from the output from the OMR system are researched. While both approaches in N-gram processing improve the system, a clear difference in performance is not found, both using gold standard N-grams and those derived from the OMR output. However, the N-grams derived differ from each other heavily. This paper shows promises in not only the usage of pattern recognition, but also in fully automating the process of inserting knowledge into OMR systems.
As Parcerias para o Desenvolvimento Produtivo em saúde na nova agenda de desenvolvimento nacional Production Development Partnership in Healthcare: Public procurement within the Brazilian development agenda

By reflecting their systemic nature, the Production Development Partnerships (PDP) in Healthcare represent a shift in healthcare policy and constitute the main instrument of public action on the part of the healthcare development policy community. Considering the importance of healthcare to a national development trajectory that combines economic competitiveness and social inclusion, this article aims to analyze the political and institutional factors that affect national development in healthcare policy, by highlighting the PDP. In order to do so
Agile Text Detection for Active Real World Visual Representation

: In recent years, vision system of Text detection in natural scene images is an important requirement for much content-based retrieval in image analysis tasks. Most of the existing methods have only focused on detecting horizontal texts. In this paper, we define a system which detects text of arbitrary orientation in natural scene images and also an effective pruning algorithm is designed to extract as character candidates using the strategy of minimizing regularized variations for better estimation of our algorithm compare it with other algorithms, we produce a new data-set, which includes different texts in real-world scenarios. The proposed experimental result shows that our algorithm produces better and enhanced performance on texts of arbitrary orientations in complex natural scenes.