Miracle-dz/UniFAR-FTUs huggingface dataset:
Genotyping by sequencing reveals contrasting patterns of population structure, ecologically mediated divergence, and long‐distance dispersal in North American palms

Abstract Comparative studies can provide powerful insights into processes that affect population divergence and thereby help to elucidate the mechanisms by which contemporary populations may respond to environmental change. Furthermore, approaches such as genotyping by sequencing (GBS) provide unprecedented power for resolving genetic differences among species and populations. We therefore used GBS to provide a genomewide perspective on the comparative population structure of two palm genera, Washingtonia and Brahea, on the Baja California peninsula, a region of high landscape and ecological complexity. First, we used phylogenetic analysis to address taxonomic uncertainties among five currently recognized species. We resolved three main clades, the first corresponding to W. robusta and W. filifera, the second to B. brandegeei and B. armata, and the third to B. edulis from Guadalupe Island. Focusing on the first two clades, we then delved deeper by investigating the underlying population structure. Striking differences were found, with GBS uncovering four distinct Washingtonia populations and identifying a suite of loci associated with temperature, consistent with ecologically mediated divergence. By contrast, individual mountain ranges could be resolved in Brahea and few loci were associated with environmental variables, implying a more prominent role of neutral divergence. Finally, evidence was found for long‐distance dispersal events in Washingtonia but not Brahea, in line with knowledge of the dispersal mechanisms of these palms including the possibility of human‐mediated dispersal. Overall, our study demonstrates the power of GBS together with a comparative approach to elucidate markedly different patterns of genomewide divergence mediated by multiple effectors.
Cross-Polarization Suppression in Probe-Fed Circular Patch Antenna Using Two Circular Clusters of Shorting Pins

A novel aspect in cross-polarization (XP) reduction in probe-fed circular microstrip patch antenna has been proposed employing a pair of symmetric circular clusters of shorting pins (CCSP) peripherally located along the radius of the patch. The proof of the concept is first established using a pair of shorting pins located symmetrically on the circular patch. Once the optimum position of the shorting pins for maximized XP reduction was identified, the design was modified by replacing an individual shorting pin using multiple numbers of shorting pins arranged in a circular geometry that is defined as CCSP. Effect of the incorporation of the CCSP structures on the antenna characteristics like resonance frequency, co-polarized radiation, and cross-polarized radiation has been studied extensively. The design concept has been discussed and experimentally established using simulated and measured results of the CCSP integrated circular patch over conventional circular patch for S-band. The integration of CCSP resulted in a relative suppression in XP levels of around 51 dB at the boresight and an average of 30 dB around ±60° on either side of the boresight in both the principal radiation planes.
The Domain Transform Solver

We present a novel framework for edge-aware optimization that is an order of magnitude faster than the state of the art while maintaining comparable results. Our key insight is that the optimization can be formulated by leveraging properties of the domain transform, a method for edge-aware filtering that defines a distance-preserving 1D mapping of the input space. This enables our method to improve performance for a wide variety of problems including stereo, depth super-resolution, render from defocus, colorization, and especially high-resolution depth filtering, while keeping the computational complexity linear in the number of pixels. Our method is highly parallelizable and adaptable, and it has demonstrable linear scalability with respect to image resolutions. We provide a comprehensive evaluation of our method w.r. t speed and accuracy for a variety of tasks.
Genetic and population structure of sweet cassava (Manihot esculenta Crantz) germplasm collected from Campo Grande, Mato Grosso do Sul, Brazil

Knowledge of germplasm diversity and its genetic characterization is crucial to crop improvement and conservation strategies. This study aimed at characterization of diversity genetic and population structure of traditional sweet cassava germplasm at the molecular level. A total of 60 sweet cassava accessions from Campo Grande city, Mato Grosso do Sul State, Brazil, and a commercial variety, were analyzed using microsatellite markers. Allelic frequencies were used in order to assess the genetic diversity indexes for each marker. Population structure was analyzed using genetic distances and Bayesian model. A total of 88 alleles were identified from the 19 SSR markers, with an average of 4.63 alleles per marker. The mean of polymorphic information content (PIC) was 0.525 and indicated that the markers used were informative and polymorphic, especially the marker SSRY 13. The heterozygosity observed (Ho) ranged from 0.569 to 0.984, with a mean of 0.862, evidencing the existence of high natural heterozygosis in cassava. The genetic diversity mean was of 0.601 and revealed considerable genetic diversity among the genotypes. Population structure analysis resulted in the distribution of the 61 accessions in two distinct sub-populations, by Bayesian analysis, Neighbor-Joining Tree and Principal Coordinates Analysis, indicating the existence of significant genetic diversity between sub-populations. Combination of cassava accessions BGM 570 × BGM 613 and BGM 570 × IAC 576/70 is recommended for obtaining superior segregation in order to improve yield. The results will contribute to the conservation of the Mato Grosso do Sul germplasm and sweet cassava breeding.
Antidepressant utilisation and incidence of weight gain during 10 years’ follow-up: population based cohort study

Abstract Objective To evaluate the long term association between antidepressant prescribing and body weight. Design Population based cohort study. Setting General practices contributing to the UK Clinical Practice Research Datalink, 2004-14. Participants 136 762 men and 157 957 women with three or more records for body mass index (BMI). Main outcome measures The main outcomes were antidepressant prescribing, incidence of ≥5% increase in body weight, and transition to overweight or obesity. Adjusted rate ratios were estimated from a Poisson model adjusting for age, sex, depression recording, comorbidity, coprescribing of antiepileptics or antipsychotics, deprivation, smoking, and advice on diet. Results In the year of study entry, 17 803 (13.0%) men and 35 307 (22.4%) women with a mean age of 51.5 years (SD 16.6 years) were prescribed antidepressants. During 1 836 452 person years of follow-up, the incidence of new episodes of ≥5 weight gain in participants not prescribed antidepressants was 8.1 per 100 person years and in participants prescribed antidepressants was 11.2 per 100 person years (adjusted rate ratio 1.21, 95% confidence interval 1.19 to 1.22, P<0.001). The risk of weight gain remained increased during at least six years of follow-up. In the second year of treatment the number of participants treated with antidepressants for one year for one additional episode of ≥5% weight gain was 27 (95% confidence interval 25 to 29). In people who were initially of normal weight, the adjusted rate ratio for transition to overweight or obesity was 1.29 (1.25 to 1.34); in people who were initially overweight, the adjusted rate ratio for transition to obesity was 1.29 (1.25 to 1.33). Associations may not be causal, and residual confounding might contribute to overestimation of associations. Conclusion Widespread utilisation of antidepressants may be contributing to long term increased risk of weight gain at population level. The potential for weight gain should be considered when antidepressant treatment is indicated.
Saraca asoca (Ashoka): A Review

Ashoka is the most ancient tree of India, generally known as a “ashok briksh”, botanist known as a Saraca asoca (Roxb.), De.wild or Saraca indica belonging family Caesalpinaceae . Medicinal herbs are moving from fringe to mainstream use with a great number of people seeking remedies and health approaches free from side effects caused by synthetic chemicals. Saraca asoca is reported to contain glycoside, flavanoids, tannins and saponins. It is used as spasmogenic, oxytocic, uterotonic, anti-bacterial, anti-implanta tion, anti-tumour, anti-progestational, antiestrogenic activity against menorrhagia and anti-ca ncer. This review contains the Pharmacognostical account of various parts of plant , Phytochemical constituent and different reported pharmacological activity.
Is there a role for minimally invasive thermal ablations in the treatment of autonomously functioning thyroid nodules?

ISSN: 0265-6736 (Print) 1464-5157 (Online) Journal homepage: https://www.tandfonline. com/loi/ihyt20 Is there a role for minimally invasive thermal ablations in the treatment of autonomously functioning thyroid nodules? Claudio M. Pacella & Giovanni Mauri To cite this article: Claudio M. Pacella & Giovanni Mauri (2018) Is there a role for minimally invasive thermal ablations in the treatment of autonomously functioning thyroid nodules? , International Journal of Hyperthermia, 34:5, 636-638, DOI: 10.1080/02656736.2018. 1462537 To link to this article: https://doi.org/10.1080/02656736.2018. 1462537
Pseudo-Pilot Coding Based Phase Noise Estimation for Coherent Optical FBMC-OQAM Transmissions

We propose a cost-efficient scheme called pseudo-pilot coding based phase noise estimation (PC-PNE) to compensate laser phase noises for filter-bank multicarrier (FBMC) transmission systems. The performance of the proposed PC-PNE with rectangular quadratic-amplitude modulation (QAM) is evaluated and compared with the state-of-the-art modified blind phase search (M-BPS) approach via extensive Monte Carlo simulations. Under 200 kHz combined laser linewidth, 32 Gbaud 256-subcarriers FBMC optical transmission equipped with PC-PNE provides a comparable performance with the complicated M-BPS method for QPSK, 16QAM and 64QAM. Moreover, a significant reduction in computational complexity (up to 50 times) is obtained with PC-PNE in comparison with M-BPS method at the cost of 3.1% spectral efficiency loss.
Evaluating radial component current measurements from CODAR high frequency radars and moored in situ current meters

The performance of a network of five CODAR (Coastal Ocean Dynamics Application Radar) high frequency (HF) radars is described based on comparisons with an array of nine moorings in the Santa Barbara Channel and Santa Maria Basin deployed between June 1997 and November 1999. Eight of the moorings carried vector measuring current meters (VMCM’s), the ninth an upward-looking acoustic Doppler current profiler (ADCP). Measurement depths were ~1 m for the HF radars, 5 m for the VMCM’s, and 3.2 m for the ADCP bin nearest to the surface. Comparison of radial components of nearsurface currents from 18 HF radar-mooring pairs yielded root mean square (rms) speed differences of 7-19 cm s -1 . The radial components were significantly correlated with r 2 in the range 0.39-0.77. Other studies based on radar-mooring comparisons have found similar rms speed differences and r 2 based on total velocity vectors. Spectral analysis showed significant coherence for frequencies below 2.3 cycles day -1 (periods longer than 11 hr). At higher frequencies no significant coherence was found. Comparisons revealed bearing errors in locating radial currents on the sea surface by some of the HF radars. These were typically 5-10 o with a maximum error of 19 o . The effects of bearing errors on total velocity vector estimates were evaluated using a simple flow field and measured bearing errors, showing up to 15% differences in computed flow speeds, and up to ~9 o
Limitations of current monoclonal antibodies for plaque-type psoriasis and an outlook for the future

Psoriasis is a chronic immune-mediated disease; although its pathogenesis is complex and still largely unknown, over the past several years, it has become clear that psoriasis goes beyond the skin. Improvements in our understanding of the pathogenesis have subsequently led to the development of novel drugs that act systemically on specific molecular components of the immune response [1]. Several cytokine pathways have been identified and investigated as targets for systemic therapies. Biologic agents have revolutionized the way to manage the psoriatic disease. They selectively inhibit cytokines associated with psoriatic plaque formation, such as tumor necrosis factor (TNF)-α, interleukin (IL)-12/ 23, and IL-17A. Current consensus is that mild psoriasis can be effectively treated with topical agents, whereas systemic or biologic therapies are indicated for moderate to severe disease [1]. However, psoriasis at any severity grade can negatively impact on patient’s quality of life, thereby challenging the tag of “mild” disease. For this reason, in addition to body surface area affected and Psoriasis Area and Severity Index (PASI), other factors must be considered to evaluate treatment strategies, such as Dermatology Life Quality Index score and the burdens associated with symptoms of pain and itching [1]. An earlier use of biologics, targeting the underlying inflammation, may slow disease progression and prevent associated comorbidities, such as atherosclerosis and metabolic syndrome [2]. Patients affected by debilitating disease cannowenjoy clear or almost-clear skin inmost caseswithbiologic therapies. All biologics yield greater efficacy rates (PASI-75 responses ranging from 40% to 90%) with fewer adverse events and better overall tolerability when compared with conventional systemic therapies [3]. From a patient perspective, biologics seems to be as “wonder drugs,” nevertheless, they are not lacking of risks and limitations.
THE IDENTITY OF THE CAVERNICOLOUS FRESHWATER CRAB POTAMON (THELPHUSA) BIDIENSE LANCHESTER, 1900 (CRUSTACEA: DECAPODA: BRACHYURA: GECARCINUCIDAE) FROM SARAWAK, BORNEO, WITH DESCRIPTION OF A NEW GENUS

A new genus of cave-dwelling freshwater crab, Stygothelphusa, is described from Sarawak, Borneo, with Potamon (Thelphusa) bidiense Lanchester, 1900 as type species. This species was synonymised with Thelphusula melanippe by Bott (1970) and regarded as a separate species of Thelphusula by Holthuis (1986). Its distinctive carapace, leg and gonopod features however, warrant the establishment of a separate genus for it. A neotype for the type species is also designated.
Bending, Buckling and Vibration of a Functionally Graded Porous Beam Using Finite Elements

This study presents the effect of porosity on mechanical behaviors of a power distribution functionally graded beam. The Euler-Bernoulli beam is assumed to describe the kinematic relations and constitutive equations. Because of technical problems, particle size shapes and micro-voids are created during the fabrication which should be taken into consideration. Two porosity models are proposed. The first one describes properties in the explicit form as linear functions of the porosity parameter. The second is a modified model which presents porosity and Young’s modulus in an implicit form where the density is assumed as a function of the porosity parameter and Young’s modulus as a ratio of mass with porosity to the mass without porosity. The modified proposed model is more applicable than the first model. The finite element model is developed to solve the problem by using the MATLAB software. Numerical results are presented to show the effects of porosity on mechanical behaviors of functionally graded beams.
SoftBox: A Customizable, Low-Latency, and Scalable 5G Core Network Architecture

We propose a novel cellular core network architecture, SoftBox, combining software-defined networking and network function virtualization to achieve greater flexibility, efficiency, and scalability compared to today’s cellular core. Aligned with 5G use cases, SoftBox enables the creation of customized, low latency, and signaling-efficient services on a per user equipment (UE) basis. SoftBox consolidates network policies needed for processing each UE’s data and signaling traffic into a light-weight, in-network, and per-UE agent. We design a number of mobility-aware techniques to further optimize: 1) resource usage of agents; 2) forwarding rules and updates needed for steering a UE’s traffic through its agent; 3) migration costs of agents needed to ensure their proximity to mobile UEs; and 4) complexity of distributing the LTE mobility function on agents. Extensive evaluations demonstrate the scalability, performance, and flexibility of the SoftBox design. For example, basic SoftBox has 86%, 51%, and 87% lower signaling overheads, data plane delay, and CPU core usage, respectively, than two open source EPC systems. Moreover, our optimizations efficiently cut different types of data and control plane loads in the basic SoftBox by 51%–98%.
The Differentiation of Visual Sensorimotor Processes in the Representatives of Various Sport Disciplines

Sport activities usually require a high efficiency of visual information processing. Therefore, it seems justified to determine the efficiency of visual sensorimotor processes in sports requiring a variety of perception competencies. The aim of this study was to assess the differentiation of sensorimotor processes in terms of simple and choice reaction time, and visual stimulus discrimination in various athletes and untrained persons. The study involved 119 men, of which 95 were athletes: football players (n = 24), volleyball players (n = 22), boxers (n = 26), and rowers (n = 23). The efficiency of sensorimotor processes was evaluated with the Vienna Test System (Schuhfried, Austria). The evaluations included simple reaction time (SRT), choice reaction time (CRT), and visual stimulus discrimination. Analysis of the results showed that volleyball and football players had shorter (p < 0.01) reaction times compared to non-athletes and representatives of the other sports. We found significant differences (p < 0.01) between athletes and non-athletes in visual stimulus discrimination. In addition, boxers showed fewer correct reactions than volleyball players, and shorter times of stimulus detection than in volleyball and soccer players.
Accelerating Search-Based Program Repair

Automatic program repair techniques offer the possibility of reducing, or even eliminating, the substantial manual effort that currently goes into the patching of software defects. However, current repair techniques take minutes or hours, to generate rather simple repairs, severely limiting their practical applicability. Search-based program repair represents a popular class of automatic repair techniques. Patch compilation and test case execution are the dominant contributors to runtime in this class of repair techniques. In this work we propose two complementary techniques, namely Location Selection and Test-Case Pruning, to improve the efficiency of search-based repair techniques. Location Selection reduces the number of repair candidates examined in arriving at a repair, thereby reducing the number of patch compilations as well as the overall number of test case evaluations during the repair process. Test-Case Pruning, on the other hand, optimizes the number of test cases executed per examined candidate. We implement the proposed techniques in the context of SPR, a state-of-the-art search-based repair tool, evaluate them on the GenProg benchmarks and observe that the proposed techniques provide a 3.9X speed-up, on average, without any degradation in repair quality.
Detection of Power Grid Harmonic Pollution Sources based on Upgraded Power Meters

Abstract The paper suggests a new and efficient method for location of nonlinear loads on a grid. It is based on measuring of distortion power. The paper reviews different definitions of distortion power and proves that the method is feasible independently on particular definition. The obtained results of simulation and measurement confirm the effectiveness and applicability of the method. The proposed solution is suitable for software update of existing electronic power-meters or can be implement as hardware upgrade.
Deep Feature Fusion for Iris and Periocular Biometrics on Mobile Devices

The quality of iris images on mobile devices is significantly degraded due to hardware limitations and less constrained environments. Traditional iris recognition methods cannot achieve high identification rate using these low-quality images. To enhance the performance of mobile identification, we develop a deep feature fusion network that exploits the complementary information presented in iris and periocular regions. The proposed method first applies maxout units into the convolutional neural networks (CNNs) to generate a compact representation for each modality and then fuses the discriminative features of two modalities through a weighted concatenation. The parameters of convolutional filters and fusion weights are simultaneously learned to optimize the joint representation of iris and periocular biometrics. To promote the iris recognition research on mobile devices under near-infrared (NIR) illumination, we publicly release the CASIA-Iris-Mobile-V1.0 database, which in total includes 11 000 NIR iris images of both eyes from 630 Asians. It is the largest NIR mobile iris database as far as we know. On the newly built CASIA-Iris-M1-S3 data set, the proposed method achieves 0.60% equal error rate and 2.32% false non-match rate at false match rate $=10^{-5}$ , which are obviously better than unimodal biometrics as well as traditional fusion methods. Moreover, the proposed model requires much fewer storage spaces and computational resources than general CNNs.
Influence Propagation Model for Clique-Based Community Detection in Social Networks

Social media community detection is a fundamental challenge in social data analytics, in order to understand user relationships and improve social recommendations. Although the problem has been extensively investigated, the majority of research has been based on social networks with static structures. Our findings within large social networks, such as Twitter, show that only a few users have interactions or communications at fixed time intervals. Finding active communities that demonstrate constant interactions between its members comprises a reasonable perspective. Communities examined from this perspective will provide time-variant social relationships, which may greatly improve the applicability of social data analytics. In this paper, we address the problem of temporal interaction-biased community detection using a four-step process. First, we develop a partition approach using an objective function based on clique structure, to enhance the time efficiency of our methodology. Second, we develop an influence propagation model that gives greatest weight to active edges or to inactive edges in close proximity to active edges. Third, we develop expansion-driven algorithms to efficiently find the activity-biased densest community. Finally, we verify the effectiveness of the extended community metric and the efficiency of the algorithms using three real data sets and a case study conducted on Twitter dynamic data set.