Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Distribution Patterns of Culex Disease Vectors by Molecular Assays

Culex pipiens complex taxa and sibling species Cx. torrentium are morphologically difficult to distinguish, but differ in behaviour and ecophysiology and, accordingly, in epidemiology. With a view of their epidemiological importance, knowledge of the distribution of morphologically similar mosquitoes in nature is important for the understanding of their vector–pathogen dynamics and for their control. Mosquitoes of the genus Culex are vectors of many dangerous human and animal infections, such as filariasis, avian malaria and arboviruses West Nile virus, Japanese encephalitis, St. Louis encephalitis, Sindbis virus and others. Beside this, people attacked by mosquitoes suffer from itching and allergic reactions. Mosquitoes of the Culex pipiens complex are of special interest. The complex includes closely related ubiquitous species. Common in Europe are Cx. pipiens Linnaeus, 1758 and sibling species Cx. torrentium Martini, 1925. The subspecies Cx. pipiens includes two forms, the nominate pipiens form and the molestus form. Within the temperate zone, these forms are biotopically isolated and have somewhat opposite biological features. C. pipiens form pipiens are unautogenous (able to produce of the first egg raft only after taking a blood meal), diapausing (able to enter reproductive diapause) and eurygamous (they need a large space for mating) mosquitoes, inhabit the open water bodies. While Cx. pipiens form molestus are autogenous (produce of the first egg raft without taking a blood meal), non-diapausing, stenogamous (able to mate in confined space, without swarming), and usually inhabit the underground water bodies. Cx. torrentium is morphologically and ecologically very similar to Cx. pipiens form pipiens, the mosquitoes are unautogenous, diapausing and eurygamous.
Examining the link between health measures, management practices and establishment performance

"We examine the relationship between establishment-level health measures, Anglo-Saxon management practices and labor productivity, as well as median wages. Based on the observation that management practices are positively associated with establishment outcomes, we test whether health measures have a distinct effect on their own, or if they are already comprised in management practices. Using representative survey data from the German Management and Organizational Practices Survey, we find a strong increase in the use of health measures from 2008 to 2013, predominantly in large establishments. Fixed effects regressions confirm that management practices significantly increase labor productivity, however, health measures do not. The reverse is true for median wages, such that health measures are positively associated with median wages, but management practices are not. " (Author's abstract, IAB-Doku) ((en))
Effect of Craniocervical Flexion on Muscle Activities of Abdominal and Cervical Muscles During Abdominal Curl-Up Exercise

Abdominal curl-up exercise may excessively increased superficial neck flexor such as sternocleidomastoid (SCM) muscle. Also, the muscle activity of the abdominal muscles haven't investigated during abdominal curl-up with craniocervical flexion (CCF). Therefore, the purpose of our study was to determine the effect of CCF on the muscle activity of the abdominal and SCM muscles during abdominal curl-up. Twelve healthy subjects (six men and six women) with no history of abdominal or lower back pain within 6 weeks were recruited. Surface electromyographic signals were collected on SCM, rectus abdominis (RA), internal oblique (IO), and external oblique (EO) muscles bilaterally during performing the traditional abdominal curl-up and the abdominal curl-up with CCF. Paired t-tests were used to compare the differences in the muscle activity of the bilateral SCM, RA, EO, and IO muscles between the traditional abdominal curl-up and the abdominal curl-up with CCF (p; Left SCM, ) than with the traditional abdominal curl-up (Right SCM, ; Left SCM, ) (p
An Approach of Detecting Discontinuities in Images

: Edge detection is the procedure of identifying and tracing sharp discontinuities in an image. The discontinuities are sudden changes in pixel intensity which describe boundaries of objects in a scene. The reason for that is that edges form the outline of an object. A benefit could be the linking a thing and the backdrop and shows the boundary between overlying objects. Image edge detection also decreases the amount of data and filters out inadequate information, while maintaining the important structural properties in an image. Edge detection is found in various fields like image analysis and pattern recognition. This paper describes the various edge detection techniques along with discussing their advantages and limitations. The techniques discussed here are Roberts operator, Sobel operator, Prewitt's cross operator, Laplacian, Laplacian of Guassian and Canny's edge detection. In this paper, The Experiments shows the completed edge information with the accuracy and reduced the errors, increasing the PSNR values which predict the signal are better rather than error and also the comparison of these techniques is carried out with an experiment by using MATLAB software.
Analysis of social-ecological dynamics driving conflict in linked surface-groundwater systems

Conflict over water resources emerges from complex interactions among biophysical, social, and economic processes operating at multiple scales. Competing use of linked surface-groundwater (LSGW) resources is an excellent yet relatively unexplored example of such conflict. Dynamic circumstances surrounding the contested installation of a high capacity municipal well in southeastern Wisconsin were examined through the theoretical lens of adaptive governance using document analysis and open-ended key stakeholder interviews. A framework analysis method extracted 16 controlling variables from the qualitative data. These controlling variables were placed on a threshold matrix at their appropriate geospatial scale (Property, Watershed, State) and process domain (Biophysical, Economic, Social), which revealed several social-ecological feedbacks not currently addressed by management authorities. Three dynamic feedback loops were identified that explain the emergence and resolution of LSGW conflict in the case study area. Conflict emerged when processes driving new development in southeastern Wisconsin threatened to impact a highly valued groundwater dependent lake. Lake groups engaged in collective learning, utilized information networks, and displayed leadership to address the issue. However, lack of participatory avenues for dispute resolution at the scale of occurrence drove lake groups to challenge the regulatory authority of the Wisconsin Department of Natural Resources (WDNR). Through order-based legitimacy, legal resolution affected governance of LSGW resources across the state, but did little to address the underlying stakeholder values driving conflict. We conclude this system will continue to be subjected to “legal back and forth,” recurrent conflict, and uncertainty for both environmental and developmental interests until a more participatory process is developed with regulatory authorities to resolve conflicts over LSGW.
Does Authenticity Predict Sense of Community of Turkish University Students

The aim of this study is to investigate the predictive role of authenticity on sense of community. The study was conducted with 402 graduate students (237 women, 165 men; M age= 20.6 yr.). Participants completed the Authenticity Scale and the Sense of Community Scale. Sense of community was correlated negatively with two sub-factors of authenticity: accepting external influence and self-alienation and positively with the authentic living factor of authenticity. In regression analysis, self-alienation and accepting external influence predicted negatively and authentic living predicted positively to sense of community, accounting for 14% of the variance collectively.
Ceramic Materials as an Alternative to Titanium for Dental Implant Fabrication

Titanium is the gold standard material to produce dental implants from more than 30 years, showing high success rate in different clinical scenarios. Zirconia implants were recently introduced to overwhelm some aesthetic and biological problems that can arise from titanium. Preclinical studies show that, from a mechanical point of view, zirconia may be a suitable substitute for titanium in implant fabrication. Three-dimensional finite element analysis (FEA) models found no difference between titanium and titanium-zirconium alloy implants, neither for early nor conventional functional loading. Nevertheless, zirconia presents the same osseoconductive properties of the titanium, even if the few clinical studies show survival and success rates slightly inferior for zirconia implants comparing to titanium ones, and long-term follow-ups are missing. For these reasons, the majority of authors agree to be cautious for proposing zirconia implants as widespread substitute of titanium implants.
Dynamic sharings of Gaussian densities using phonetic features

This paper describes a way to adapt the recognizer to pronunciation variability by dynamically sharing Gaussian densities across phonetic models. The method is divided in three steps. First, given an input utterance, an HMM recognizer outputs a lattice of the most likely word hypotheses. Then, the canonical pronunciation of each hypothesis is checked by comparing its theoretical phonetic features to those automatically extracted from speech. If the comparisons show that a phoneme of an hypothesis has likely been pronounced differently, its model is transformed by sharing its Gaussian densities with the ones of its possible alternate phone realization(s). Finally, the transformed models are used in a second-pass recognition. Sharings are dynamic because they are automatically adapted to each input speech. Experiments showed a 5.4% relative reduction in word error rate compared to the baseline and a 2.7% compared to a static method.
Diagnosis of Diabetes Mellitus using K Nearest Neighbor Algorithm

Diabetes is one of the major global health problems. According to WHO 2011 report, around 346 million people worldwide are suffering from diabetes mellitus. Diabetes Mellitus is a metabolic disease where the improper management of blood glucose levels lead to the risk of many diseases like heart attack, kidney disease and renal failure. In Diabetes Mellitus, body does not properly use the insulin hormone secreted by Pancreas gland. There are so many computerized methods for the diagnosis of Diabetes Mellitus but the main drawback of these methods is that the patient has to undergo several medical tests to provide the input values to the computerized diagnostic system which proves to be very costly and time consuming. With the rapid advancement in the field of Artificial Intelligence, there are so many techniques and algorithms in A.I. that can be effectively used for the prediction and diagnosis of various diseases. These algorithms in artificial intelligence prove to be cost-effective and time saving for diabetic patients and doctors. In this paper, we are diagnosing Diabetes Mellitus using K-Nearest neighbour algorithm which is one of the most important techniques of A.I. The dataset is taken from www.stanford. edu/~hastie/Papers /LARS/diabetes.data.
Proximity coupled Rectangular Microstrip Antenna with X-slot for WLAN Application

One of the major limitations of microstrip antenna is narrow bandwidth. Various techniques can be used to improve it’s BW. In this paper, Proximity coupling technique and X slot are employed to enhance the BW of Rectangular Microstrip antenna (RMSA). A RMSA with X slot has been designed at a frequency of 2.45GHz on FR4, one substrate and it is proximity coupled with microstrip feed, which is on the other substrate. Various parameters viz. Return loss, VSWR, input impedance, Gain, are obtained from HFSS simulation and Networkanalyzer test is performed to obtain VSWR. Percentage BW of VSWR from network analyzer is obtained as 7.14, which is more than that of a microstrip feed RMSA.
Environmental impact of mining activity in Bor area as indicated by the distribution of heavy metals and bacterial population dynamics in sediment

The environmental impact of inorganic pollution is pronounced in water adjacent to Bor Copper Smelter Complex (RTB Bor, Serbia), with Cu, Zn, Pb, and As being the main determinants of aquatic pollution pattern. Communities of microorganisms present in the sediments are mainly affected by heavy metal pollution. Some groups of bacteria can be considered pollution bio-indicators, due to their sensibility and ability to bioaccumulate heavy metals, thus contributing to reducing pollution. This study investigates the relationships between trace element accumulation and heterogeneity in sediment bacteria community structure found in water streams adjacent to the Bor Copper Smelter Complex (RTB Bor, Serbia). Our results showed no contamination with copper, zinc, nickel, iron, and chromium, but did show a low to moderate contamination with lead and a moderate to high contamination with arsenic in aquatic sediments within the area of interest. Spatial heterogeneity in sediment-associated bacterial communities did not relate significantly to location of sampling sites, except for iron reducing bacteria. Iron reducing bacteria and nitrifying bacteria were the best distinguishing groups of bacteria. However, only iron reducing bacteria were significantly influenced by sampling locations. The iron reducing bacteria has correlated negatively with the degree of sediment contamination with lead, and therefore, we suggest that this group of bacteria could serve as potential bio-indicators of inorganic water contamination in Bor RTB area.
Visual motion computation in recurrent neural networks

Populations of neurons in primary visual cortex (V1) transform direct thalamic inputs into a cortical representation which acquires new spatio-temporal properties. One of these properties, motion selectivity, has not been strongly tied to putative neural mechanisms, and its origins remain poorly understood. Here we propose that motion selectivity is acquired through the recurrent mechanisms of a network of strongly connected neurons. We first show that a bank of V1 spatiotemporal receptive fields can be generated accurately by a network which receives only instantaneous inputs from the retina. The temporal structure of the receptive fields is generated by the long timescale dynamics associated with the high magnitude eigenvalues of the recurrent connectivity matrix. When these eigenvalues have complex parts, they generate receptive fields that are inseparable in time and space, such as those tuned to motion direction. We also show that the recurrent connectivity patterns can be learnt directly from the statistics of natural movies using a temporally-asymmetric Hebbian learning rule. Probed with drifting grating stimuli and moving bars, neurons in the model show patterns of responses analogous to those of direction-selective simple cells in primary visual cortex. These computations are enabled by a specific pattern of recurrent connections, that can be tested by combining connectome reconstructions with functional recordings. * Author summary Dynamic visual scenes provide our eyes with enormous quantities of visual information, particularly when the visual scene changes rapidly. Even at modest moving speeds, individual small objects quickly change their location causing single points in the scene to change their luminance equally fast. Furthermore, our own movements through the world add to the velocities of objects relative to our retinas, further increasing the speed at which visual inputs change. How can a biological system process efficiently such vast amounts of information, while keeping track of objects in the scene? Here we formulate and analyze a solution that is enabled by the temporal dynamics of networks of neurons.
Bodily transition out of elite sport: A one‐year study of physical self and global self‐esteem among transitional athletes

Abstract Sports career termination implies a transition during which ex‐elite athletes face social, professional, and bodily changes and adjustments. This study evaluated the repercussions of the bodily transition and adjustment process on physical self and global self‐esteem. Athletes (n =16) in transition following the Sydney Olympic Games were compared with active elite athletes (n =16) four times during the first post‐career termination year using the Physical Self Inventory (Ninot, Delignieres, & Fortes, 2000). The results revealed that perceived physical condition, physical self‐worth, and global self‐esteem decreased during the first six months of transition out of elite sport. This stage of crisis was followed by a period of increase in these dimensions, as well as in perceived sports competence and physical strength, illustrating an adjustment to new bodily references. Transitional athletes presented lower global self‐esteem, physical self‐worth, perceived physical condition, sports competence, and physical attractiveness than active elite athletes, because of decreased training and social recognition of the “performing body. ”
MOLECULAR BIOLOGY AND PHYSIOLOGY Nitrogen Metabolism in Cotton Stems and Roots During Reproductive Development

Cotton is a perennial plant grown as an annual row crop in much of the world. Cotton stems and roots store starch prior to reproduction that is subsequently available to support reproduction. Aspects of nitrogen metabolism in cotton stems and roots were investigated to determine whether these tissues also provided nitrogen to support reproduction. Measurements of total nitrogen, soluble proteins, and individual amino acids indicated that nitrogen metabolism was altered after flowering began. Analysis of gene expression from previous microarray experiments also showed patterns consistent with a role of altered nitrogen metabolism during seed set. Changes in transcript levels of genes associated with amino acid biosynthesis, biosynthesis of nitrogenous compounds, and protein turnover also indicated that nitrogen metabolism changed in roots during seed set. We confirm that stem and roots provide nitrogen to support reproduction, and propose that the transport of nitrogenous compounds from these tissues to reproductive tissue could affect seed set by communicating the nitrogen status of the plant.
Mesh-adaptive simulations of horizontal-axis turbine arrays using the actuator line method

Numerical models of the flow and wakes due to turbines operating within a real-scale offshore wind farm can lead to a prohibitively large computational cost, particularly when considering blade-resolved simulations. With the introduction of turbine parametrizations such as the actuator disk (AD) or the actuator line (AL) models, this problem has been partially addressed, yet the computational cost associated with these simulations remains high. In this work, we present an implementation and validation of an AL model within the mesh-adaptive three-dimensional fluid dynamics solver, Fluidity, under a unsteady Reynolds-averaged Navier-Stokes based turbulence modelling approach. A key feature of this implementation is the use of mesh optimization techniques, which allow for the automatic refinement or coarsening of the mesh locally according to the resolution needed by the fluid flow solver. The model is first validated against experimental data from wind tunnel tests. Finally, we demonstrate the benefits of mesh-adaptivity by considering flow past the Lillgrund offshore wind farm.
Latency and Availability Driven VNF Placement in a MEC-NFV Environment

Multi-access Edge Computing (MEC) is gaining momentum as it is considered as one of the enablers of 5G ultra-Reliable Low-Latency Communications (uRLLC) services. MEC deploys computation resources close to the end user, enabling to reduce drastically the end-to-end latency. ETSI has recently leveraged the MEC architecture to run all MEC entities, including MEC applications, as Virtual Network Functions (VNF) in a Network Functions Virtualization (NFV) environment. This evolution allows taking advantage of the mature architecture and the enabling tools of NFV, including the potential to apply a variety of service-tailored function placement algorithms. However, the latter need to be carefully designed in case of MEC applications such as uRLLC, where service access latency is critical. In this paper, we propose a novel placement scheme applicable to a MEC in NFV environment. In particular, we propose a formulation of the problem of VNF placement tailored to uRLLC as an optimization problem of two conflicting objectives, namely minimizing access latency and maximizing service availability. To deal with the complexity of the problem, we propose a Genetic Algorithm to solve it, which we compare with a CPLEX implementation of our model. Our numerical results show that our heuristic algorithm runs efficiently and produces solutions that approximate well the optimal, reducing latency and providing a highly-available service.
APPLICATION OF THE PARTICLE SWARM OPTIMIZATION TO THE COMPUTATION OF THE GO/UTD REFLECTION POINTS OVER NURBS SURFACES

A new method to flnd the Geometrical Optics/Uniform Theory of Difiraction re∞ection points over Non Uniform Rational B- Splines surfaces is presented. The approach is based on the Particle Swarm Optimization (PSO) technique, and the cost function used to flnd the re∞ection points is based on Snell's law. The technique can be used as an alternative to classic minimization techniques in cases where convergence problems arise.
Gemini/GMOS IFU gas velocity ‘tomography’ of the narrow line region of nearby active galaxies

We present two-dimensional (2D) mapping of the gas velocity field of the inner few hundred parsecs of six nearby active galaxies, using spectra obtained with the integral field unit of the Gemini Multi-Object Spectrograph instrument at the Gemini North telescope. In our previous paper, we reported the 2D mapping of the stellar kinematics extracted from the calcium triplet absorption lines. In this paper, we use the [S m] λ9069 emission line to obtain the flux distribution and kinematics of the gas in the narrow-line region (NLR). The gas emission is extended by a few hundred parsecs and its kinematics are dominated by rotation in the galaxy plane. Subtraction of the rotation component reveals outflows along the NLR which show spatial correlation with radio structures seen in Very Large Array radio 3.6 and 20 cm flux images, suggesting that the radio jet is pushing the circumnuclear interstellar medium. This interpretation is also supported by the observation of high-velocity dispersion (σ ≥ 500 km s ―1 ) structures in association with the outflowing gas. The gas outflows and radio jets are oriented at random angles relative to the galaxy major axis, indicating that they are not launched perpendicularly to the galaxy plane. Slicing the emission-line profiles into velocity channels, we create maps of the NLR gas distribution at different radial velocities. In at least half of our sample, the highest velocities are observed close to the nucleus suggesting that the emitting gas is decelerating outwards, from projected blueshifts exceeding 400 km s ―1 to values of 100-200 km s ―1 at 100-200 pc from the nucleus. We have estimated mass outflow rates in the NLR of ≈1 to 50 x 10 ―3 M ⊙ yr ―1 , which are ≈10―20 times the accretion rate necessary to feed the active nucleus. The kinetic energy of the ouflow is estimated to be 4-5 orders of magnitude smaller than the bolometric luminosity. Assuming kinetic energy transfer between the radio jet and the NLR outflows, the mass ejection rate in the radio jet is 5-6 orders of magnitude smaller than the mass accretion rate necessary to feed the nuclear supermassive black hole.