Miracle-dz/UniFAR-FTUs huggingface dataset:
Tropical Cyclone Intensity Change Prediction Based on Surrounding Environmental Conditions with Deep Learning

Tropical cyclone (TC) motion has an important impact on both human lives and infrastructure. Predicting TC intensity is crucial, especially within the 24 h warning time. TC intensity change prediction can be regarded as a problem of both regression and classification. Statistical forecasting methods based on empirical relationships and traditional numerical prediction methods based on dynamical equations still have difficulty in accurately predicting TC intensity. In this study, a prediction algorithm for TC intensity changes based on deep learning is proposed by exploring the joint spatial features of three-dimensional (3D) environmental conditions that contain the basic variables of the atmosphere and ocean. These features can also be interpreted as fused characteristics of the distributions and interactions of these 3D environmental variables. We adopt a 3D convolutional neural network (3D-CNN) for learning the implicit correlations between the spatial distribution features and TC intensity changes. Image processing technology is also used to enhance the data from a small number of TC samples to generate the training set. Considering the instantaneous 3D status of a TC, we extract deep hybrid features from TC image patterns to predict 24 h intensity changes. Compared to previous studies, the experimental results show that the mean absolute error (MAE) of TC intensity change predictions and the accuracy of the classification as either intensifying or weakening are both significantly improved. The results of combining features of high and low spatial layers confirm that considering the distributions and interactions of 3D environmental variables is conducive to predicting TC intensity changes, thus providing insight into the process of TC evolution.
APPLYING THE SCATTER SEARCH META-HEURISTIC TO THE HISTORY MATCHING PROBLEM

Numerical simulation plays an important role in managerial decisions in the E&P field. The quality of such decisions is deeply dependent on the quality of the forecasts rendered by the simulation models. History Matching (HM) is a standard procedure to which simulation models are subjected to in order to increase the quality of their predictions. The HM Problem (HMP) can be viewed as an Optimization Problem (OP) when a set reservoir parameters, their variation range and a match evaluation objective function is defined. This paper shows how the HMP can be modeled as a combinatorial optimization problem so it can be solved by the metaheuristic algorithm Scatter Search (SS). The proposed methodology is then tested with two synthetic reservoir models with increasing level of complexity and the method’s performance is evaluated. Overall, SS shows a good scalability when the solution grid is refined and/or the number of variables increases. Finally, it is shown that the proposed SS methodology is simulation intensive so it is
The Importance of Clinical Genotype in Patients with Klinefelter Syndrome. A Genetic Disorder Asociated to Taurodontism

Taurodontism is a clinical condition found in the molar teeth of humans whereby the body of the tooth and pulp chamber is enlarged vertically at the expense of the roots. As a result, the floor of the pulp and the furcation of the tooth is moved apically down the root. It is due to the failure or late invagination of Hertwig’s epithelial root sheath, which is responsible for root formation and shaping causing an apical shift of the root furcation. The constriction at the amelocemental junction is abnormally formed. Taurodontism is most commonly found in permanent dentition although the term is traditionally applied to molar teeth. It has been reported that taurodontism follows an autosomal dominant type of inheritance. Meanwhile, Mutations or chromosome aberrations are considered alterations in the chromosome number or structure. They are mainly considered due to gametogenesis inborn error at meiosis, where DNA loses are seen due to DNA repair processes deficiency. Some chromosome studies were performed were 34.6% (1596 patients) showed different chromosome alterations. Among the studies population, male and female pediatric patients with sexual genetic diseases were chosen. These chromosome changes are classified as numeric or structural alterations, respectively. A wide variety of pediatric patients with genetic diseases chromosome alterations are described in this study analyzing their clinical characteristics, medical, surgical treatments and their clinical evolution according to the genetic disease.
NEST SUCCESS RATES OF FOUR SHRUBLAND SPECIALISTS IN CONSERVATION-MANAGED FIELDS WITH COMPARISIONS TO OTHER MANAGED AND UNMANAGED SHRUBLANDS

Shrubland birds are disturbance dependent species and are experiencing population declines of 1–3%/year rangewide. In our study, we determined nest success rates of four shrubland species, Blue-winged Warbler (Vermivora pinus), Prairie Warbler (Dendroica discolor), Indigo Bunting (Passerina cyanea), and Field Sparrow (Spizella pusilla), at Bent of the River Audubon Center, Southbury, Connecticut, USA. Field sites were conservation-managed fi elds that were actively managed for shrubland specialists. Data were collected on 123 nests (May–August, 2004–2006) and nest success rates (calculated using the Mayfi eld method) were 0.37 ± 0.003 for Blue-winged Warbler, 0.35 ± 0.013 for Prairie Warbler, 0.65 ± 0.009 for Indigo Bunting, and 0.50 ± 0.014 for Field Sparrow. Our study of these species is one of only three from the New England/ Mid-Atlantic Coast Region. We compiled data from studies from all regions reporting nest success of these species, conducted in a variety of managed and unmanaged shrublands. We compared our results to these studies and found nest success rates in conservation-managed fi elds to be similar to or higher than studies in different habitat management types in different regions. Based on our comparision of results from the limited number of studies on nest success rates of shrubland birds, the rotational mowing, selective tree removal, and invasive plant control regimes used to maintain conservation-managed shrublands are effective management practices to maintain high to moderate rates of nest success and may even be preferable to other management practices where shrubland species are targets for conservation.
Low-Variance Software Reliability Estimation Using Statistical Testing

—Software statistical testing establishes a basis for statistical inference about the expected ﬁeld quality of software based on an expected operational proﬁle. The standard statistical testing approach draws randomly test cases from the expected operational proﬁle according to the statistical distribution on the expected inputs. Standard Statistical testing is in the most of the cases impractical. The number of required test cases to reach a target reliability with a given conﬁdence is too large. In this paper, we present a test selection approach to minimize the variance of reliability estimator and reduce the overhead of estimating reliability. The presented approach combines the idea of statistical testing with the concepts of stratiﬁed sampling. Experiments are conducted to validate the efﬁciency of our approach.
Inhibiteurs du Quorum Sensing de Vibrio harveyi issus d'éponges de Polynésie française

La resistance bacterienne induite par l’utilisation massive d’antibiotiques en aquaculture, conduit a la recherche de nouveaux modes de traitement, des traitements anti-virulents et non toxiques. Differentes strategies sont etudiees parmi lesquelles l’inhibition d’un systeme de regulation : le quorum sensing. Vibrio harveyi est une bacterie pathogene en aquaculture qui regule sa bioluminescence et la production de proteines de virulence par l’intermediaire du quorum sensing. L’etude des eponges Leucetta chagosensis, Dysidea sp. 2669 et Cacospongia sp. 2110 collectees en Polynesie francaise, a permis l’isolement de huit metabolites secondaires dont quatre nouveaux : l’isonaamine D, le bis-isonaamidine A-Zn, la leucettamine D et le tuamotuolol. Leurs effets et leurs modes d’action ont ete evalues sur deux phenotypes controles par le quorum sensing chez V. harveyi: la bioluminescence et la production de metalloproteases. Trois molecules ont ainsi montre une activite inhibitrice du quorum sensing de V. harveyi : l’isonaamine D, l’isonaamidine A et l’ilimaquinone.
EPH tyrosine kinase receptors regulate epithelial morphogenesis and phosphorylate the PAR-3 scaffold protein to modulate downstream signaling networks

The EPH family is the largest among receptor tyrosine kinases (RTKs) in humans. In contrast to other RTKs, EPH receptors (EPHRs) cognate ligands, ephrins, are tethered to the cell surface. This results in EPHRs-ephrin signaling being mainly involved in short-range cell-cell communication events that regulate cell adhesion, migration and tissue boundary formation. Although EPHRs functions have been broadly studied, the molecular mechanisms by which they mediate these processes are far from being understood. To address this question, we sought to identify new downstream effector proteins for EPHRs and to determine their requirement for EPHR-regulated functions. To unravel EPHR-associated signaling complexes under native conditions, we applied a mass spectrometry-based approach, namely BioID proximity labeling. We obtained a composite proximity network from EPHA4, -B2, -B3 and -B4 receptors that comprises 395 proteins, most of which were not previously linked to EPH signaling. A gene ontology and pathway term analysis of the most common candidates highlighted cell polarity as a novel function associated with EPHR activity. We found that EPHA1 and EPHB4 expression is restricted to the basal and lateral membrane domains in polarized Caco-2 3D spheroidal cell cultures. We further discovered that their depletion impairs spheroid morphogenesis. In parallel, we examined the contribution of a number of candidates, selected from EPHR proximity networks, via loss-of-function in an EPHR-dependent cell segregation assay. We showed that depletion of the signaling scaffold PAR-3 blocks cell sorting. We also delineated a signalling complex involving C-terminal SRC kinase (CSK), whose recruitment to PAR-3 complexes is dependent on EPHR signals. Our work sheds light on EPHR signaling networks and provides a better understanding of the mechanisms by which EPHRs signal at the membrane to contribute to the establishment of cellular phenotypes.
Dynamic Information Collection and Fusion

Abstract : The project is aimed at developing a comprehensive framework for control of information collection, fusion, and inference from diverse modalities Our research has been organized under three inter-related thrusts. The first thrust addresses system modeling and local information processing. The second thrust emphasizes the interaction between information and control at different abstraction levels. The third thrust is focused on decentralized processing and interactive fusion. Within Thrust 1. we focused on exploring, developing, and utilizing mathematical models for hard and soft observations, the physical and abstract information states, and the sensing state for local information processing and inference. Within Thrust 2. we have obtained a number of results on sensor scheduling for target tracking, controlled sequential multi hypothesis testing, controlled sensing for graph classification, universal outlier hypothesis testing, and optimal search and stop. Within Thrust 3, we have obtained a number of results on interactive fusion, data reduction with quantization constraints, network consensus and quantized alternate direction method of mutlipliers (ADMM), and resource management in sensor networks.
Modeling Techniques for Quantifying Climate Change Impacts on Agriculture Productions: Models Comparisons and Impact Assessment Research Framework

Additional warming caused by climate change will negative impacts on agricultural sectors. The problem is expected to be most harsh in regions were lacking in adaptive capacity in terms of information needed to make adaptive decisions to combat climate change impacts. Many strides have been made to understand and quantify climate impact on sensitive regions to climate change. However, for many food-insecurity hot-spot areas, the comprehensive data for impact assessment are rarely available. This paper outlined a research framework for providing knowledge for policymakers, local authorities, and agricultural organizations to make informative climate change adaptive decisions for such areas. Several models are compared and discussed to show their advantage and disadvantage for appropriate model applications. We propose a framework to facilitate future impact assessment research, especially for regions where relevant data are lacking. This paper provides a research method of linking different models and combines the useful information acquired from models to make climate policies and adaption schemes cost-effectively with limited local data and farm information. Original Research Article Li; AJAAR, 14(1): 35-42, 2020; Article no.AJAAR. 59450 36
Short-Term and Long-Term Forecasting for Changing 2 the Position of Points in the space by using Artificial 3 Neural Networks

: Forecasting is one of the most growing areas in most sciences attracting the attention of 13 many researchers for more extensive study. Therefore, the goal of this study is to develop an 14 integrated forecasting methodology based on an Artificial Neural Network (ANN), which is a 15 modern and attractive intelligent technique. The final result is to provide short-term and long-term 16 forecasts for changing the position of points, i.e. the displacement or deformation of the surface 17 they belong to. The motivation was the combination of two thoughts, the introduction of the 18 concept of forecasting in most scientific disciplines (e.g. economics, medicine) and the desire to 19 know the future behavior and location of a construction or an area of the natural earth surface. This 20 methodology was designed to be accurate, stable and general in deferent kind of geodetic data. The 21 basic procedures, which are involved, are the definition of the problem, the data pre-processing, 22 the definition of the most suitable ANN, the evaluation using the proper criteria and the 23 production and use of forecasts. The methodology gives great importance to the stages of the 24 pre-processing and the evaluation. The forecasting intervals are also emphasized. Finally the most 25 appropriate ANN is presented and evaluated also it is proved that the use of ANNs in order to 26 make short-term and long-term forecasts gives more accurate forecasts compared to other 27 conventional-statistical forecasting methods. 28
Squeeze dispersion : modulation of diapycnal mixing by 1 diapycnal strain 2

16 We describe a process called ‘squeeze dispersion’ in which the squeezing of isopycnal sur17 faces by waves, eddies, and bathymetric flow modulates the diapycnal diffusion of oceanic 18 tracers by centimeter to meter-scale turbulence. Squeeze dispersion typically enhances dif19 fusion — especially when diffusivity positively correlates with squeezing. We introduce squeeze 20 dispersion with an idealized example, and derive an equation for the circulation of oceanic 21 tracers that establishes the fundamental role of squeeze dispersion and its associated ef22 fective diffusivity in oceanic diapycnal mixing. We use the squeeze dispersion effective dif23 fusivity to interpret observations of abyssal flow through the Samoan Passage reported by 24 Alford et al. (2013) and find that correlations between squeezing and turbulent diffusivity 25 enhance tracer dispersion across some isopycnals by factors of 2–3. 26 Plain language summary 27 Vertical ocean mixing, which is weak and mediates Earth’s climate by drawing atmospheric 28 carbon and heat in the deep ocean, depends on turbulence that churns the ocean on the 29 tiny scales of centimeters to meters. We demonstrate that vertical ocean mixing depends 30 not only on this small scale turbulence as previously thought, but on the correlation be31 tween small scale turbulence and larger-scale motions like currents and eddies on horizon32 tal scales of ten to hundreds of kilometers — the oceanic versions of jet streams and hur33 ricanes. In particular, when a patch of ocean is mixed by small-scale turbulence while be34 ing ‘squeezed’ in the vertical at the same time by currents and eddies, the patch ultimately 35 mixes more quickly than the turbulence would cause alone. This means that we need to 36 know something both about about typical rates of oceanic squeezing as well as typical oceanic 37 small-scale turbulence to estimate the total rate of oceanic vertical mixing. 38
Coastal tourism development in Sinop as an emerging rural destination: A preliminary study from the residents’ perspective

This study proposes to explore the economic, sociocultural, and environmental effects of coastal tourism development in a Turkish context. It adopts a quantitative approach and performed a random sampling technique. The survey data was collected from a sample of local people in Sinop/Turkey and total number of 252 utilizable questionnaires was gathered and analyzed through descriptive statistics. ANOVA test was also applied in order to compute the perceptional differences among demographical groups. The findings demonstrate that while majority of residents have positive perceptions in general, some agree with negative economic, sociocultural, and environmental effects of coastal tourism in the area. Specifically, they perceive that tourism raises the cost of products and services and as a result of an increase in living costs. ANOVA test shows that there were differences between educational groups in negative environmental impacts and age groups in positive economic impacts. In terms of sustainable coastal tourism, the present work procures further addition to tourism literature and also offers beneficial implications to industry practitioners.
Importance and Challenges of Social Media Text

: The rapid growth of social media like twitter, Facebook, WhatsApp, messenger etc. has increased the availability of unstructured data (texts, images, videos) amount on internet. These texts are different from traditional text. The text written on social media are called Social Media Text. In India more than 50% comments on social media are written in Indian Languages using Unicode and Phonetic typing. The Pre-processing of these texts for application of Natural Language Processing (NLP) is a challenging task. This paper will help the researchers to understand the concept of code mixing, social media text, code mixed text and various challenges of social media text.
The Next Pharmaceutical Path: Determining Technology Evolution in Drug Delivery Products Fabricated with Additive Manufacturing

Additive manufacturing (AM) is increasingly gaining a presence in the pharmaceutical industry, specifically in the reconfiguration of drug delivery systems wherein new products are being developed for administering pharmaceuticals inside the body, and drug testing systems wherein complex tissues are created to analyze medical treatments. This paper proposes a novel methodology of Competitive Technology Intelligence (CTI) to uncover the evolution of new drug delivery products where additive manufacturing is present. Using the multiple linear regression analysis and hype cycle model as a conceptual basis, we processed data from scientific papers and patents indexed by Scopus and PatSnap for the period of 2004-2019. The outcomes of this study can create a relevant knowledge base for decision-making on introducing novel technologies such as AM. Industrial and academic communities are devoting important efforts toward the advancement of AM in the health industry, especially pharmaceuticals. It is expected that this technology will bring new solutions to address fundamental global health problems. However, this technology is still in its very early stage. Therefore, investments should focus on research and development (R&D) to build a solid foundation for commercialization in the next decade.
New species of Orbilia (Orbiliales) from arid ecosystems of the Canary Islands (Spain)

The genus Orbilia Fr. (Orbiliaceae Nannf.) was currently thought to comprise some dozens of species, being particularly common in temperate regions on woody substrates in moist habitats. During monographic work on the family Orbiliaceae over many years by the second author, species diversity turned out to be extremely higher, with presently about 330 species of Orbilia, and a strong preference of semihumid to arid, subtropical to tropical vegetation zones. The characterization of the genus and classification history of Orbiliaceae has been reviewed, e.g., in Liu et al. (2005) and Zhang et al. (2007, 2009).
REVIEW OF NANOEMULSION: FORMULATION APPROACHES AND APPLICATION OF NANOEMULSION.

In pharmaceutical formulations nano emulsions are composed of practical within nanometer range. They have capacity to encapsulate drugs that are poorly water soluble due to their hydrophobic nature and also they are composed of safe gradient excipients which makes them safer and stable option to drug delivery. For several decades cancer therapy has been an issue because drugs developed to treat this disease and not always successful or and up failing, mainly due to low solubility and unspecific toxicity. This problem can be resolved by nanoemulsion because it not only solve water solubility problems but also provides specific targeting to cancer cells. This chapter includes overview about the nanoemulsion and various approaches for production of nanoemulsions which include high energy approach such as microfluidizer high pressure valve homogenization, ultrasonic homogenization. In low energy approaches, spontaneous emulsification phase inversion composition, phase inversion temperature and emulsion inversion point are discussed in detail.
Statistical analysis of functional divergence in gene families

Duplication of genes has been thought as a major resource for function innovation in a large number of gene families. The prediction of critical residues for functional divergence between homologous genes is important for functional genomics. The Toll-like receptor (TLR) gene family plays an important role in innate immunity and adaptive immune response. All available TLR protein sequences from vertebrate animals were collected to investigate functional divergence and evolutionary pattern between TLR gene clusters. Four independent clusters were identified. Functional divergence of the domains in the TLR family was characterized by a site-specific posterior profile analysis, and critical residues for altered selective constraints of amino acid sites after gene duplication were predicted. The extracellular domain of TLR gene showed higher functional divergence than the cytoplasmic domain. Further analysis indicated that the region between leucine-rich repeats (LRR) 10 and 14 of TLR4 was a potential target for functional genomics study in the future. For study of a large set of gene families study, we collected the cDNA sequences of all orthologous genes of human, mouse or rat of two-gene cluster, three-gene cluster, and four-gene cluster from all available gene families in the database. The nonsynonymous and synonymous substitution rate for all orthologs between human and mouse or rat were estimated. The ratio of nonsynonymous to synonymous substitutions rate were calculated. The nonsynonymous substitution rate was positively correlated with synonymous substitution rate, and the ratio of nonsynonymous to synonymous substitution rate, which suggested that the nonsynonymous substitution rate is a major resource of the ratio of nonsynonymous to synonymous substitutions rate. The significant differences of nonsynonymous substitution rate in most