Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Metabolism and Disposition of the Novel Anti-Tuberculosis Agent PA-824 in Mycobacteria, Mammals and Phagocytes

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Cellular automata for simulating land-use change with a constrained irregular space representation: A case study in Nanjing city, China

Traditional cell-based cellular automata (CA) models use a regular cellular grid to represent geographic space, and new approaches to CA models have explored the use of a vector representation of space instead of a regular grid to characterize urban space more realistically. However, less attention has been paid to modeling the interaction between the geospatial information and the irregular cells. To date, the majority of spatial boundaries have been created by individual agencies in an uncoordinated manner. As a consequence, the potential uses of the data collected for land-use change models are limited. In this paper, we propose a new vector-based CA model based on a new constrained irregular space representation using the theory of hierarchical spatial reasoning. For dividing the geographic space considering different items, first land patches are considered as the minimum division unit; then aggregation rules, including attribute, geometric and boundary barrier constraints, are defined; and finally different levels of spatial units are formed through land patches based on aggregation rules. The proposed model is used to simulate the land-use changes in Nanjing, Jiangsu Province, China. The performance validation and comparison illustrate the feasibility of the proposed space representation in a CA model. By using this model, it is expected that the use of the real spatial boundaries that are employed in urban planning could help provide a flexible paradigm to consider various drivers or constraints for realistically simulating land-use changes.
Dokmaia monthadangii gen. et sp. nov., a synnematous anamorphic fungus on Manglietia garrettii

Dokmaia monthadangii gen. et sp. nov. is described from dead leaves of Manglietia garrettii collected in Doi Suthep-Pui National Park, Thailand. The genus is synnematous and is compared with the similar genus, Phaeoisaria. Dokmaia monthadangii has cylindrical brown synnemata, which are covered by white conidia and conidiogenous cells towards the apex. Conidiogenous cells are polydenticulate and arise from small parenchymatous-like cells and are arranged in parallel rows at right angles to the axis of the synnemata. The denticles are cylindrical. Conidia are hyaline and ovoid or fusiform. Conidial secession is rhexolytic, leaving a basal frill, on the conidia. The new taxon is described and illustrated.
General Intelligence: An Ecumenical Heuristic for Artificial Consciousness Research?

The science of consciousness has made great strides in recent decades. However, the proliferation of competing theories makes it difficult to reach consensus about artificial consciousness. While for purely scientific purposes we might wish to adopt a ‘wait and see’ attitude, we may soon face practical and ethical questions about whether, for example, agents artificial systems are capable of suffering. Moreover, many of the methods used for assessing consciousness in humans and even non-human animals are not straightforwardly applicable to artificial systems. With these challenges in mind, I propose that we look for ecumenical heuristics for artificial consciousness to enable us to make tentative assessments of the likelihood of consciousness arising in different artificial systems. I argue that such heuristics should have three main features: they should be (i) intuitively plausible, (ii) theoretically-neutral, and (iii) scientifically tractable. I claim that the concept of general intelligence — understood as a capacity for robust, flexible, and integrated cognition and behavior — satisfies these criteria and may thus provide the basis for such a heuristic, allowing us to make initial cautious estimations of which artificial systems are most likely to be conscious.
Revisiting disturbance accommodating control for wind turbines

Disturbance accommodating control has received considerable interest in the wind turbine research community for its ability to explicitly account for disturbances in the incoming wind field. Early work was based around estimating the disturbance from feedback information, while more recent research into disturbance accommodating control (as well as other feedforward control laws) has considered disturbance measurements produced by lidar. This work compares the two methods (estimating and measuring the disturbance) while keeping all other aspects of the controller the same. By doing so, we shed light on the performance improvements that can be attained using preview disturbance measurements of the wind.
Synthetic analysis of natural variants yields insights into the evolution and function of auxin signaling F-box proteins in Arabidopsis thaliana

The evolution of complex body plans in land plants has been paralleled by gene duplication and divergence within nuclear auxin-signaling networks. A deep mechanistic understanding of auxin signaling proteins therefore may allow rational engineering of novel plant architectures. Towards that end, we analyzed natural variation in the auxin receptor F-box family of wild accessions of the reference plant Arabidopsis thaliana and used this information to populate a structure/function map. We employed a synthetic assay to identify natural hypermorphic F-box variants, and then assayed auxin-associated phenotypes in accessions expressing these variants. To more directly measure the impact of the strongest variant in our synthetic assay on auxin sensitivity, we generated transgenic plants expressing this allele. Together, our findings link evolved sequence variation to altered molecular performance and auxin sensitivity. This approach demonstrates the potential for combining synthetic biology approaches with quantitative phenotypes to harness the wealth of available sequence information and guide future engineering efforts of diverse signaling pathways.
Divergent Hydraulic Strategies Explain the Interspecific Associations of Co-Occurring Trees in Forest–Steppe Ecotone

Research Highlights: Answering how tree hydraulic strategies explain the interspecific associations of co-occurring trees in forest–steppe ecotone is an approach to link plant physiology to forest dynamics, and is helpful to predict forest composition and function changes with climate change. Background and Objectives: The forest–steppe ecotone—the driest edges of forest distribution—is continuously threatened by climate change. To predict the forest dynamics here, it is crucial to document the interspecific associations among existing trees and their potential physiological drivers. Materials and Methods: Forest–steppe ecotone is composed of forest and grassland patches in a mosaic pattern. We executed two years of complete quadrat surveys in a permanent forest plot in the ecotone in northern China, calculated the interspecific association among five main tree species and analyzed their hydraulic strategies, which are presented by combining leaf-specific hydraulic conductivity (Kl) and important thresholds on the stem-vulnerability curves. Results: No intensive competition was suggested among the co-occurring species, which can be explained by their divergent hydraulic strategies. The negative associations among Populus davidiana Dode and Betula platyphylla Suk. , and P. davidiana and Betula dahurica Pall. can be explained as the result of their similar hydraulic strategies. Tilia mongolica Maxim. got a strong population development with its effective and safe hydraulic strategy. Generally, hydraulic-strategy differences can explain about 40% variations in interspecific association of species pairs. Oppositely, species sensitivity to early stages of drought is convergent in the forest. Conclusions: The divergent hydraulic strategies can partly explain the interspecific associations among tree species in forest–steppe ecotone and may be an important key for semiarid forests to keep stable. The convergent sensitivity to early stages of drought and the suckering regeneration strategy are also important for trees to survival. Our work revealing the physiological mechanism of forest compositions is a timely supplement to forest–steppe ecotone vegetation prediction.
Overview of the Mammal Diversity Observation Network of Sino BON

: Mammals are key indicators for biodiversity conservation and management due to their high diversity, wide distribution range, and sensitivity to habitat changes. Recently launched by the Chinese Academy of Sciences, the Mammal Diversity Monitoring Network of Sino BON (Sino BON-Mammal) is a key member of the Biodiversity Monitoring Networks of Sino BON for the monitoring and inventory of terrestrial mammal resources in China. Firstly, this paper reviews several major advances in terrestrial mammal diversity observations in both China and other parts of the world. We then provide an overview of Sino BON-Mammal, including the major scientific goals, monitoring framework, methods, and data products. In addition, we also summarize some working advances of the Mammal Diversity Observation Network of Sino BON since 2011. This overview will be helpful for the development of national observation programs of mammal diversity in China.
Firms’ Attributes and Environmental Disclosure: Evidence from Listed Firms in Bangladesh

A B S T R A C T Research aim: This paper aims at finding out the quality of environmental reporting and its association with company characteristics considering listed companies from various sectors through the lens of legitimacy theory and stakeholder theory in Bangladesh. Design/ Methodology/ Approach: Secondary data relevant to company characteristics and environmental disclosure have been collected from various parts of the annual reports of firms for the year 2016. This study considers one dependent variable breaking down into three levels and four independent variables. Level of environmental disclosure (LED) is the dependent variable while size, profitability, leverage and industry type are independent variables. Research finding: By employing Ordinary Least Square (OLS), the level of environmental disclosures (LED-1) is significantly associated with firm size, unlike the profitability, leverage and production attributes. The moderate disclosure level (LED-2) is likely to be affected by the firm size, unlike the other factors. Furthermore, the greatest disclosure level (LED-3) is to be strongly affected by business size and profitability. Moreover, the study confirms that firm type has no impact on environmental disclosure. Theoretical contribution/ Originality: This paper provides insights into the quality of environmental disclosure of Bangladeshi companies. It reveals that only leverage and size affect the total environmental disclosure of firms, unlike type and other features. This has a perfect alignment with the legitimacy theory that larger firms tend to disclose more to legitimise their activities and scale up their image. Practitioner/ Policy implication: This paper helps firms in implementing environmental disclosure policies and make them more environmentally responsible. Limitation/ Implication: Exploring the qualitative environmental disclosures among various types of industries in Bangladesh in a longitudinal manner by addressing more control variables may contribute to future research on determinants of corporate environmental reporting.
Co-occurrence patterns of fish species in two aquatic habitats of the Arauca River floodplain, Venezuela

The study of co-occurrence patterns has been extensively applied to propose assembly rules for community organization. Recently, a new interest has grown in the effect of gradients on these patterns and to analyze them through new approximations such as co-occurrence networks, through which keystone species can be identified. Neotropical floodplains represent interesting systems to study such patterns, because of their spatial heterogeneity, temporal variability and their high fish species richness. With this in mind, our goal was to study the co-occurrence patterns of fish in a segment of the Arauca River’s floodplain and the influence of the spatial and temporal variability on them. One stream and one floodplain lake were sampled with gill nets during 2014 – 2015 across a hydrological cycle and 5 matrices for each 5 sampled months in each water body were prepared to explore the co-occurrence patterns in each water body across months and 2 for the entire period, through a probabilistic pair-wise analysis of species co-occurrence that identified aggregated and segregated species pairs. With the observed cooccurrences × water body × month, the species weighted degrees and betweenness were calculated, and co-occurrence networks were constructed. The networks structures, in terms of the degrees of every species, were compared spatially and temporally through a generalized linear model. The stream showed the highest numbers of aggregated species pairs, and in general showed the most complex networks in terms of nodes, edges and degrees. The habitat type and the hydrological phases significantly influenced the structure of the fish co-occurrence networks. Two species, Loricariichthys brunneus and Pygocentrus cariba were identified as the core of the fish communities of the floodplain and as keystone species because they contribute to the connection of the networks by having a series of links with less frequent species.
Regional Climate Responses in East Asia to the Black Carbon Aerosol Direct Effects from India and China in Summer

Black carbon (BC) aerosol is a significant and short-lived climate forcing factor. Here, the direct effects of BC emissions from India (IDBC) and China (CNBC) are investigated in East Asia during summer using the state-of-the-art regional climate model RegCM4. In summer, IDBC and CNBC account for approximately 30% and 46% of the total BC emissions in Asia, respectively. The total BC column burden from the two countries and corresponding TOA effective radiative forcing are 1.58 mg m−2and +1.87 W m−2in East Asia, respectively. The regional air temperature increases over 0.3 K at maximum and precipitation decreases 0.028 mm day−1on average. Individually, IDBC and CNBC each can bring about rather different effects on regional climate. IDBC can result in a cooling perturbation accompanied by a substantially increased cloud amount and scattering aerosol loading, resulting in a complex response in the regional precipitation, while CNBC can lead to regional warming, and further induce a local flood in northern China or drought in southern China depending on the opposite but significant circulation anomalies. CNBC plays a dominant role in modulating the regional climate over East Asia due to its higher magnitude, wider coverage, and stronger climate feedback. The direct effect of the total BC from both countries is not a linear combination of that of IDBC and CNBC individually, suggesting that the regional climate responses are highly nonlinear to the emission intensity or aerosol loading, which may be greatly related to the influences of the perturbed atmospheric circulations and climate feedback.
Predicting Politician's Supporters' Network on Twitter Using Social Network Analysis and Semantic Analysis

Politics is one of the hottest and most commonly mentioned and viewed topics on social media networks nowadays. Microblogging platforms like Twitter and Weibo are widely used by many politicians who have a huge number of followers and supporters on those platforms. It is essential to study the supporters’ network of political leaders because it can help in decision making when predicting their political futures. This study focuses on the supporters’ network of three famous political leaders of Pakistan, namely, Imran Khan (IK), Maryam Nawaz Sharif (MNS), and Bilawal Bhutto Zardari (BBZ). This is done using social network analysis and semantic analysis. The proposed method (1) detects and removes fake supporter(s), (2) mines communities in the politicians’ social network(s), (3) investigates the supporters’ reply network for conversations between supporters about each leader, and, finally, (4) analyses the retweet network for information diffusion of each political leader. Furthermore, sentiment analysis of the supporters of politicians is done using machine learning techniques, which ultimately predicted and revealed the strongest supporter network(s) among the three political leaders. Analysis of this data reveals that as of October 2017 (1) IK was the most renowned of the three politicians and had the strongest supporter’s community while using Twitter in a very controlled manner, (2) BBZ had the weakest supporters’ network on Twitter, and (3) the supporters of the political leaders in Pakistan are flexible on Twitter, communicating with each other, and that any group of supporters has a low level of isolation.
PERFORMANCE COMPARISON OF SPATIAL SEARCH ALGORTIHMS FOR SPECIFIC DATASETS IN SMART CITIES

Dijitallesen cagda akilli sehir kavrami ortaya cikmistir. Akilli sehirlerin temel amaclarindan biride zaman verimi saglayacak bilesenler sunmaktir. Akilli ulasim ve otopark hizmetleri bu konsepte dahildir. Bu hizmetlerin temeli gercek zamanli uzamsal arama algoritmalarina dayanmaktadir. Gercek zamanli uzamsal aramalar icin performansli uzamsal arama algoritmalari kullanmamiz gerekmektedir. Populer uzamsal arama algoritmalari; k en yakin komsu, dortgen sorgular, r-agaci ve kd-agacidir. Uzamsal duzlemin icerisinde yer alan bir noktadan yapilan sorguda dogru algoritmanin secimi performans acisindan onemlidir. Bu calismanin amaci; secilen merkez noktasi icin kucuk boyutlu sinirlari belirli bir veri setindeki en yakin komsuyu en hizli sekilde saptayan algoritmayi belirlemektir. Python dilinde yazilan 4 uzamsal arama algoritmasi yapilan testler ile karsilastirilmis ve veri seti icin en uygun algoritma belirlenmistir. Tespit edilen algoritma veri setine benzer sehir bileseni modelinde kullanilabilir bu sayede zamanin degerli oldugu sehir hayatinda verimli zaman yonetimi saglanmis olur.
DT-VAR: Decision Tree Predicted Compatibility-Based Vehicular Ad-Hoc Reliable Routing

Reliable routing and efficient message delivery in vehicular ad-hoc networks (VANETs) is a significant challenge owing to underlying environment constraints, such as dynamic nature, mobility, and limited connectivity. With the increasing number of machine learning (ML) applications in wireless networks, VANETs can benefit from these data-driven predictions. In this letter, we innovate and investigate ML-based classifications in VANETs to predict the most suitable path with the longest compatibility time and trust using a fog node based VANET architecture. The proposed scheme in SUMO VANET traces achieves up to a 16% packet delivery ratio (PDR) with a 99% accuracy and longer connectivity with only 3 ~ 4 hops, compared with existing AOMDV and TCSR solutions with merely a 4% PDR.
Une généralisation du théorème de Liouville effectif pour les variétés projectives

Résumé On démontre un analogue du théorème de Liouville eﬀectif valable pour des points fermés sur une variété projective déﬁnie sur un corps de nombres. Ce résultat est une version eﬀective d’un théorème récent de McKinnon et Roth. Une partie importante de cet article est consacrée à la démonstration d’une version eﬀective d’un cas particulier d’un théorème remarquable de géométrie diophantienne dû à Faltings et Wüstholz. Combiné à de nouvelles comparaisons explicites entre l’évaluation d’une section d’un ﬁbré en droites et une fonction distance donnée, ce résultat entraîne le théorème principal. Nous présentons également une autre approche, en montrant comment rendre eﬀectifs les arguments de McKinnon et Roth. Ces deux points de vue conduisent à des versions distinctes du théorème principal, fournissant des majorations diﬀérentes de la hauteur des points satisfaisant une inégalité analogue à celle du théorème de Liouville classique. Abstract We prove an eﬀective analogue of Liouville’s theorem for closed points on an arbitrary projective variety deﬁned over a number ﬁeld. Our result can be interpreted as an eﬀective version of a recent theorem proved by McKinnon and Roth. A central part of the paper is dedicated to giving an eﬀective proof of a particular case of a powerful theorem in diophantine geometry proved by Faltings and Wüstholz. This result, combined with new explicit comparisons between evaluation of sections of a line bundle and a given distance function, leads to the expected theorem. We also deal with another approach, showing how to make the arguments of McKinnon and Roth eﬀective. These two points of view lead to distinct versions of our main result, giving diﬀerent upper bounds for the height of points satisfying a Liouville type inequality.
Nature Interpretation and Visitor Management Objectives: A Survey of Tourist Attitudes at Maasai Mara National Reserve, Kenya

Nature interpretation has been advocated as a soft and non-obtrusive on-site visitor management strategy to enhance visitor knowledge and understanding of the resource, mitigate visitor impacts, encourage the conservation and improvement of attraction areas, and assist visitors in enjoying their visit. However, the way in which nature interpretation programs are implemented, and the subsequent attitudes created amongst visitors can pose a challenge to the effectiveness of nature interpretation as a visitor management strategy. The situation becomes more complicated with limited resources to implement, monitor, and evaluate nature interpretation in expansive wilderness areas like Masai Mara National Reserve (MMNR). The question therefore is, does nature interpretation in MMNR create favourable attitudes amongst wildlife tourists, consequently leading to enhanced visitor experiences and satisfaction of the support for conservations, or not? This research, therefore, sought to establish the extent to which the attitudes created by nature interpretation affect visitor satisfaction or the enhanced visitor experience and support for conservation, broadly termed as visitor management objectives in MMNR Kenya. Thus, Ho1 postulated that attitudes created by nature interpretation do not influence visitors’ support for conservation in MMNR, and Ho2, that attitudes created by nature interpretation do not enhance visitor experience and satisfaction in MMNR. This study used a structured questionnaire for the survey to collect data from a sample of 351 respondents as a proportion of visitors into MMNR. Research findings revealed that a moderate relationship between attitudes created by nature interpretation and support to conservation with rs = 0.426 and p = 0.000, thus null hypothesis H01 was rejected. Secondly, results showed that attitudes created by nature interpretation moderately affected visitor satisfaction rs = 0.478 and p = 0.000, while similarly, null hypothesis H02 was rejected. The research concluded that various forms of NI result in the formation of attitudes that moderately affect support for conservation and visitor satisfaction. The study concluded that enhanced nature interpretation training and awareness creation, along with continual improvement initiatives, could unlock its full potential as a visitor management strategy. This consistent, well-coordinated, and diligent implementation of nature interpretation initiatives by all stakeholders in MMNR would sustain a cumulative, long-term impact.