Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavioural Diversity in Chimpanzees and Bonobos: Costs and benefits of grouping for female chimpanzees at Gombe

INTRODUCTION Most diurnal primates live in permanent social groups. Chimpanzees, however, exhibit a fission–fusion social structure in which individuals of the social group or community spend some time alone and the rest of the time in parties of varying composition. These, in turn, comprise subsets of the total community. In this regard, chimpanzees resemble several other species of large-bodied, frugivorous primates. A common explanation is that in such species, predation risk, a major factor in producing group living, is relaxed because of large body size. Group size then adjusts to the distribution and abundance of food sources, which vary over time (van Schaik & van Hooff 1983; Terborgh & Janson 1986; Dunbar 1988). These explanations regard plentiful food as a permissive factor for group formation. The possibility that individuals actually gain more food by joining groups through information transfer or better exploitation of resources has received less attention in primate than in other animal studies (Wilson 1975; Rodman 1988) and deserves further study. A number of researchers have investigated variables important in controlling party formation in chimpanzees. Besides grouping at plentiful food sources, the benefits of grouping they have considered include mating prospects, measured by the presence of sexually receptive females (Goodall 1986; Sakura 1994; Boesch 1996; Wrangham 2000; Anderson et al ., Chapter 6; Mitani et al ., Chapter 7; Wrangham, Chapter 15), cooperative hunting (Boesch 1996) and safety in numbers, either from predation (Boesch 1991), conspecific threat (Bauer 1980), or human disturbance (Sakura 1994). Research investigating party size in chimpanzees has focused on limits to party size, assuming that benefits of grouping are always high enough that observed patterns are a product of the costs (Wrangham 1979, 2000).
FIRST REPORT OF FUNCTIONAL IDENTIFICATION OF MUSCARINIC RECEPTORSIN THE SMALL INTESTINE OF JAPANESE QUAIL (Coturnix coturnix japonica)

Motility of small intestine which determines the efficacy of digestion and assimilation of nutrients and thus the rate of growth in the animals and birds is modulated mainly by muscarinic cholinergic receptor system. The efficacy of agonists and antagonists in modulating the gastrointestinal motility is governed by subtypes of muscarinic receptors present in the organs. So far, there are no reports of muscarinic receptors of quail intestine. Hence the current study was conducted for identifying the muscarinic receptor subtypes for better pharmacological management of dysfunctions of the small intestine of Japanese quail. Eight healthy quails of either sex were raised under uniform management conditions. Birds were euthanized and two to three centimetres length ileum was separated from a region five centimetres away from the ileo-caecal junction and transferred to Tyrode solution at 37.2 °C. The ileum tissue was mounted under 1 g tension in an organ bath chamber with constant aeration. The contractile responses to the agonist alone, agonist in presence of antagonists and relaxant effect of muscarinic receptor antagonists with submaximal contraction of ACh were recorded with isometric transducer connected to a recorder. The median effective concentration 50 (EC50) and pD2 values were determined. From the results it is evident that muscarinic acetylcholine receptors are present in the ileum of Japanese quail which, as per our knowledge is the first report of this receptor in Japanese quail intestine. The EC50 values of acetylcholine alone in ileum of Japanese quail varied from 1.235 X 10 -7 M to 2.344 X 10 -7 M with mean * Corresponding author KEYWORDS
Problems and Prospects: A Study on the Development History of Chinese Football Industry

Abstract The paper proposes that the governance of the Chinese football industry since 1994 can be best described as having undergone three stages of development: a primary stage (1994–2003) in which the early form of a Chinese football industry was established; a stage of development challenges (2004–2012) in which the Chinese football industry faced a slowdown of growth and challenges of governance failure and a decline in market appeal; and a revitalized development stage (from 2013 to 2019) in which the Chinese football industry gave signs of strong recovery. After more than two decades of development, China’s football industry has become more economically independent of government, though the industry still faces a series of problems and dilemmas. These problems include a poor management system; the on-going financial deficits of its football clubs; inadequate market expansion; the football bubble economy phenomenon; and the absence of a brand culture for the football clubs. All of these factors continue to restrict the healthy development of the governance of China’s football industry. However, escalating reform in the industry and the increasing importance attached to it by the Chinese Central Government suggests improved prospects for the industry.
Identification of Fusarium Species Associated with Onion (Allium cepa L.) Plants in Field in Burkina Faso

Many fungi limit onion production in Burkina Faso. This study aims to identify the main Fusarium species associated with onion plant in field in order to determine those involved in seedling damping-off and bulb rot, and develop adequate management strategies of these diseases. For this purpose, 36 isolates of Fusarium were isolated from onion plants in 17 sites and subjected to molecular analysis and biometric characterization. The results revealed that the isolates belong to five Fusarium species: Fusarium oxysporum (44.44% of the isolates), Fusarium proliferatum (41.66%), Fusarium solani (5.55%), Fusarium fujikuroi (5.55%) and Fusarium thapsinum (2.77%). Fusarium oxysporum, F. proliferatum, F. solani and F. fujikuroi had faster mycelial development, with a growth rate of 7.72 - 8.27 mm/d, than F. thapsinum (6.52 mm/d). Conidia of F. oxysporum, F. proliferatum and F. solani were longer (4.74 - 5.96 μm) than those of F. fujikuroi and F. thapsinum (3.20 - 4.04 μm). Fusarium solani and F. oxysporum, respectively, had the largest and most partitioned conidia.
Research and Application of Entomopathogenic Fungi as Pest Management Option: A Review

Entomopathogenic fungi are myco-biocontrol, potentially the most versatile biological control agents with a wide host range and are an environmentally sound and effective means of reducing insect-pests. The use of microbial control agents particularly entomopathogenic fungi, have been investigated for the control of a wide range of orchard and field crop pests and are a widespread component of most terrestrial ecosystems. Entomopathogenic fungi are a major component of integrated pest management techniques as biological control agents against insect pests and other arthropods in horticulture, forestry and agriculture and are found in the divisions of Zygomycota, Ascomycota, Deuteromycota, Chytridiomycota and Oomycota, which were previously classified within fungi. Insect control using entomopathogenic fungi is achieved when sufficient infective propagules, conidia contact a susceptible host and conditions are suitable for a lethal mycosis to develop. A wide range of fungi occur in the soil environment and they have various ecological functions. Most of these fungi, along with a range of bacteria, can grow on artificial media in vitro . Several methods have been used to describe the variation within a species of entomopathogenic and mycoparasitic fungi including morphological characteristics of spores and colonies, extracellular protein profiles, pathogenecity, growth and nutrient requirements. Furthermore, immune taxonomic and chemotaxonomic methods have been used, though only with limited success. Taxonomic procedures are becoming more and more complex and it is generally accepted that some forms of molecular identification techniques are needed in addition to the traditional morphological characteristics formally used to classify fungal species. During the last four decades, over 80 companies worldwide have developed 171 mycoinsecticides and myco-acaricides. Use of mycoinsecticdes is likely to rise if research is focus on; improving its performance under challenging environmental conditions, formulations that will increase persistence, longer shelf life, ease of application, pathogen virulence and wider spectrum of action. Keywords: Eco-friendliness, fungi , insect pest , myco-acaricides, mycoinsecticdes DOI: 10.7176/JEES/10-3-03 Publication date: March 31 st 2020
Sources of dwarfism in pigeonpea.

Twelve dwarf pigeonpea (Cajanus cajan) stocks from ICRISAT were characterized according to phenology and agronomic traits. Variation among the cultivars was highly significant for all the traits studied. Plant spread, number of primary branches, length of fruiting branches, pods/cluster and pods/plant were positively associated with plant height and yield. All the 12 cultivars had lower yields than standard tall varieties. Dominance relationships suggested the presence of non-allelic genes for dwarfism in 7 of the stocks. , 11 ref. , Twelve dwarf pigeonpea (Cajanus cajan) stocks from ICRISAT were characterized according to phenology and agronomic traits. Variation among the cultivars was highly significant for all the traits studied. Plant spread, number of primary branches, length of fruiting branches, pods/cluster and pods/plant were positively associated with plant height and yield. All the 12 cultivars had lower yields than standard tall varieties. Dominance relationships suggested the presence of non-allelic genes for dwarfism in 7 of the stocks.
Application of PCR and DGGE to characterise the microflora of farmed fish

Farming of fish has become an increasingly important part of the Norwegian fishing industry. Furthermore, the Norwegian fishing sector represents one of the largest national industries in terms of economic value. Fish is a perishable product and a suitable substrate for chemical degradation and bacterial growth. Determinations of shelf-life of fish and fish products have traditionally been based on microbial, chemical and sensory evaluation. It is, however, important to have methods for a rapid and reliable assessment of the microflora, and to aid in the determination of the shelf-life of the fish products. This thesis discusses and describes the use of PCR and denaturing gradient gel electrophoresis (DGGE) to detect and characterise the microflora of farmed Atlantic halibut and cod. The aims were to introduce and apply molecular biological methods for characterisation of the microflora, and to use these methods to detect the changes in the microflora as a function of shelf-life extending treatments. An additional aim was to compare the results obtained from molecularbased and culture-based methods. The DGGE and subsequent sequencing approach displayed the bacterial flora of the farmed fish, and identified the predominant microflora. When applying the sequencing approach, Photobacterium spp. , Pseudomonas spp. , Brochothrix thermosphacta, Serratia sp. , Yersinia sp. , Micrococcus luteus and Shewanella spp. were found to be the predominant bacteria in farmed Atlantic cod and halibut, stored under modified atmosphere (MA). The method detected a more diverse bacterial flora than previously obtained when culture-based methods were applied. Bacterial DNA extracted directly from the sample, without prior cultivation, gave a more diverse bacterial community. Furthermore, the molecular methods have been used to study the effects of MA packaging and ozone treatment on the microflora composition. There was no observable effect of ozone treatment of farmed cod.
Functional connectivity between Bötzinger complex glycinergic neurons and parafacial late‐expiratory neurons for expiratory and sympathetic control (712.17)

Our computational model predicts that post‐inspiratory (post‐I) neurons expressing the glycine transporter 2 (GLYT2) located in the Bötzinger Complex (BötC) suppress generation of abdominal and sympathetic late‐expiratory (late‐E) activities in eucapnia. Hypercapnia allows parafacial late‐E neurons to escape this inhibition. To test functional connectivity between glycinergic BötC and late‐E neurons, we used cell‐type specific viral vector expression of channelrhodopsin (ChETA) or hallorhodopsin (eNpHR3.0) to excite/inhibit GLTY2 neurons in the BötC of rats. Intracellular recordings of parafacial late‐E neurons (n=9) confirmed that inhibition during post‐I prevents generation of late‐E activity under eucapnia. eNpHR3.0‐mediated inhibition of GLYT2 neurons in the BötC evoked abdominal and sympathetic late‐E activities and increased arterial pressure (n=4). In contrast, ChETA‐mediated excitation of GLYT2 neurons in the BötC abolished the CO2‐induced abdominal and sympathetic late‐E activities (n=4), due to inhibition of parafacial late‐E neurons (n=3). These results indicate an emergence of parafacial late‐E activity with hypercapnia which is normally suppressed by BötC glycinergic neurons.
SOPHIA: An Event-Based IoT and Machine Learning Architecture for Predictive Maintenance in Industry 4.0

Predictive Maintenance (PdM) is a prominent strategy comprising all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the main challenges of PdM is to design and develop an embedded smart system to monitor and predict the health status of the machine. In this work, we use a data-driven approach based on machine learning applied to woodworking industrial machines for a major woodworking Italian corporation. Predicted failures probabilities are calculated through tree-based classification models (Gradient Boosting, Random Forest and Extreme Gradient Boosting) and calculated as the temporal evolution of event data. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime (RUL) of woodworking machines. The effectiveness of the proposed method is showed by testing an independent sample of additional woodworking machines without presenting machine down. The Gradient Boosting model achieved accuracy, recall, and precision of 98.9%, 99.6%, and 99.1%. Our predictive maintenance approach deployed on a Big Data framework allows screening simultaneously multiple connected machines by learning from terabytes of log data. The target prediction provides salient information which can be adopted within the maintenance management practice.
Assessment of the Teleconnection Patterns Affecting July Precipitation in China and Their Forcing Mechanisms in the Met Office Unified Model

In this study, we evaluate the ability of the MetUM to reproduce the Silk Road (SR) and Europe–China (EC) teleconnection patterns and their relationship with precipitation over China. The SR and EC patterns are the main modes of interannual variability of July upper-tropospheric meridional wind. The three main factors to the formation of these patterns are analyzed: 1) the tropical precipitation anomalies, which act as a forcing mechanism; 2) the emission of Rossby waves in the Mediterranean–Caspian Sea region; and 3) the basic state of the tropospheric jet over Eurasia. It was found that the model has some difficulty reproducing the main modes of variability in atmosphere-only mode (SR and EC pattern correlation of 0.31 and 0.54, respectively) with some improvement in coupled mode (pattern correlations of 0.56 and 0.44, respectively). Relaxation experiments were used to assess the impact that improving circulation in key regions has on the teleconnections. It was found that nudging wind and temperatures in the forcing regions within the tropics improved the Silk Road pattern whereas nudging in the region where the jet transitions between the North Atlantic Ocean and Eurasian continent—correcting the basic state—had the most impact on the EC teleconnection pattern. This suggests that while the Silk Road pattern is more sensitive to changes in the forcing, the Europe–China pattern is more sensitive to the basic state.
Structure and tectonics of the continental margins of India and the adjacent deep ocean basins: current status of knowledge and some unresolved problems

The Indian Ocean and the bordering continental margins are characterized by a number of tectonic features consisting of deep ocean basins, aseismic ridges/ submarine plateaus and seamounts. Marine geophysical studies carried out over these regions for the past four decades have led to an increased understanding of the formation and evolution of these features. The present paper synthesizes an up-to-date compilation of the results of the salient inferences of those studies to describe the structure and tectonic evolution of these features as well as the Indian Ocean in general. A review of the existing knowledge on the structure and tectonics of the continental margins of India and the adjacent ocean basins reveal the existence of several unresolved problems, primarily due to the inherent tectonic complexities or the paucity of adequate data. Some of the major problems that need to be addressed/examined are: the existence and extent of the Prathap and Kori-Comorin ridges; the locations of the continent-ocean boundaries around the continental margins of India; the timing of formation of the deep offshore regions adjacent to the Indian continental margins; the deeper crustal structure and trend of the 85°E Ridge; the crustal configuration as well as the extent of the postulated micro-continental slivers; and the cause of intense seismicity over the Chagos Bank segment of the Laccadive-Chagos Ridge. In addition to addressing these questions, the present paper suggests ways to go forward by acquiring high-resolution and deep penetration multichannel seismic reflection data, seismic refraction data using Ocean Bottom Seismometers (OBS) and closely spaced sea-surface and deep-tow magnetic profiles along with high-resolution seafloor mapping. by V. Yatheesh
Scalable Video Transmission in Cache-Aided Device-to-Device Networks

Scalable video coding (SVC) and video caching are two promising techniques in the 5th generation networks to improve the users’ quality of experience (QoE) in terms of video retrieval. In this paper, we study the video content retrieval in cache-aided device-to-device (D2D) networks, where each video content is coded into multiple layers via SVC. In video caching placement phase, the probabilistic caching placement policy is applied, while in content retrieval phase, the non-orthogonal transmission scheme is utilized. Besides, different D2D transmitter selection algorithms are considered and cache-aided data rate (CADR) is formulated as a metric in this paper, and it is maximized by jointly optimizing the probability caching policy and the power allocation policy in two phases. Analytical results show that probabilistic caching policy incorporated with power domain non-orthogonal transmission scheme can achieve significant benefits compared with other benchmark schemes.
Trade-Offs between Economic Benefits and Ecosystem Services Value under Three Cropland Protection Scenarios for Wuhan City in China

Over the past few decades urbanization and population growth have been the main trend all over the world, which brings the increase of economic benefits (EB) and the decrease of cropland. Cropland protection policies play an important role in the urbanization progress. In this study, we assess the trade-offs between EB and ecosystem services value (ESV) under three cropland protection policy scenarios using the LAND System Cellular Automata for Potential Effects (LANDSCAPE) model. The empirical results reveal that trade-offs between EB and ESV in urbanizing areas are dynamic, and that they considerably vary under different cropland protection policy scenarios. Especially, the results identify certain “turning points” for each policy scenario at which a small to moderate growth in EB would result in greater ESV losses. Among the three scenarios, we found that the cropland protection policy has the most adverse effect on trade-offs between EB and ESV and the results in the business as usual scenario have the least effect on the trade-offs. Furthermore, the results show that a strict balance between requisition and compensation of cropland is an inappropriate policy option in areas where built-up areas are increasing rapidly from the perspective of mitigating conflict between EB and ESV and the numbers of cropland protection that restrained by land use planning policy of Wuhan is a better choice.
Spatio-Temporal Analysis of Oil Spill Impact and Recovery Pattern of Coastal Vegetation and Wetland Using Multispectral Satellite Landsat 8-OLI Imagery and Machine Learning Models

Oil spills are a global phenomenon with impacts that cut across socio-economic, health, and environmental dimensions of the coastal ecosystem. However, comprehensive assessment of oil spill impacts and selection of appropriate remediation approaches have been restricted due to reliance on laboratory experiments which offer limited area coverage and classification accuracy. Thus, this study utilizes multispectral Landsat 8-OLI remote sensing imagery and machine learning models to assess the impacts of oil spills on coastal vegetation and wetland and monitor the recovery pattern of polluted vegetation and wetland in a coastal city. The spatial extent of polluted areas was also precisely quantified for effective management of the coastal ecosystem. Using Johor, a coastal city in Malaysia as a case study, a total of 49 oil spill (ground truth) locations, 54 non-oil-spill locations and Landsat 8-OLI data were utilized for the study. The ground truth points were divided into 70% training and 30% validation parts for the classification of polluted vegetation and wetland. Sixteen different indices that have been used to monitor vegetation and wetland stress in literature were adopted for impact and recovery analysis. To eliminate similarities in spectral appearance of oil-spill-affected vegetation, wetland and other elements like burnt and dead vegetation, Support Vector Machine (SVM) and Random Forest (RF) machine learning models were used for the classification of polluted and nonpolluted vegetation and wetlands. Model optimization was performed using a random search method to improve the models’ performance, and accuracy assessments confirmed the effectiveness of the two machine learning models to identify, classify and quantify the area extent of oil pollution on coastal vegetation and wetland. Considering the harmonic mean (F1), overall accuracy (OA), User’s accuracy (UA), and producers’ accuracy (PA), both models have high accuracies. However, the RF outperformed the SVM with F1, OA, PA and UA values of 95.32%, 96.80%, 98.82% and 95.11%, respectively, while the SVM recorded accuracy values of F1 (80.83%), OA (92.87%), PA (95.18%) and UA (93.81%), respectively, highlighting 1205.98 hectares of polluted vegetation and 1205.98 hectares of polluted wetland. Analysis of the vegetation indices revealed that spilled oil had a significant impact on the vegetation and wetland, although steady recovery was observed between 2015-2018. This study concludes that Chlorophyll Vegetation Index, Modified Difference Water Index, Normalized Difference Vegetation Index and Green Chlorophyll Index vegetation indices are more sensitive for impact and recovery assessment of both vegetation and wetland, in addition to Modified Normalized Difference Vegetation Index for wetlands. Thus, remote sensing and Machine Learning models are essential tools capable of providing accurate information for coastal oil spill impact assessment and recovery analysis for appropriate remediation initiatives.