Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of temporary and periodic emersion on the growth of Fucus spiralis and Pelvetia canaliculata germlings

The stress tolerance ability of Pelvetia canaliculata (L.) Dcne. Et Thur. and Fucus spiralis L. to temporary and periodic emersion stress was examined in order to test the following hypotheses: The upper shore alga, P. canaliculata is more tolerant to desiccation than F. spiralis in the germling stage and the former outgrows the latter under desiccation stress; Germling stress tolerance of the two species is age-specific; Crowding of germlings protects them from desiccation, ir respective of the species involved. Germling growth of the two species was retarded with increasing exposure period and was age-specific, as they were air-exposed at an earlier stage. After 16 days, the length of Pelvetia germlings was similar between 2-day-old germlings (125-140 µm) and 7-day-old germlings (134-140 µm), which were air-exposed during the same period (0, 6, 12, 24, 48, and 72 h) at the two different ages. However, Fucus germlings were significantly larger at 7-day-old germlings (211-277 µm) than at 2-day-old germlings (184-278 µm), especially in the treatments of 48 and 72 h. These results indicate that Fuscus grow faster than Pelvetia and that the growth response of germlings to temporary emersion stress is more sensitive in Fucus than that in Pelvetia. Growth of germlings of both species was reduced with increasing density under favorable growth conditions (submerged control and 6 h / 12 h exposure treatments) in the periodic air-exposed experiments using tidal tanks, but was enhanced under severe emersion stress conditions. P. canaliculata showed better growth at 6 h exposure treatment than that of the control, under continuous submergence, indicating that Pelvetia germlings require a periodic exposure period. Fucus germlings always grew faster than those of Pelvetia and did best in mixed cultures, whereas Pelvetia did least well when mixed with Fucus germlings. The adverse effects of F. spiralis on P. canaliculata were greater than those of Pelvetia cohorts. The outcome of interspecific competi tion between F. spiralis and P. canaliculata gemlings was slightly altered by exposure period but not to such an extent as to change the outcome.
Wearable Antenna for Radar Applications

This paper presents a compact square shaped micro strip patch antenna at an operating frequency of 8.5GHz. The radiating element of the swastika shaped patch using dielectric substrate 4.6 and having the substrate height 1.6mm. The antenna size is very compact (30mm x 30mm x 1.6mm) and covers 5GHz to 10GHz. It can be used for military and marine impulse radar applications. Using ADS (Advance design system) software. The design antenna is simulated. The software simulation results shows that the antenna can realize wide band characteristics having bandwidth of 78MHz (VSWR<=2) for all resonant frequencies. Our aim is to reduce the size of an antenna as well as increase the bandwidth and return loss of an antenna.
NITS-Hinglish-SentiMix at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text Using an Ensemble Model

Sentiment Analysis refers to the process of interpreting what a sentence emotes and classifying them as positive, negative, or neutral. The widespread popularity of social media has led to the generation of a lot of text data and specifically, in the Indian social media scenario, the code-mixed Hinglish text i.e, the words of Hindi language, written in the Roman script along with other English words is a common sight. The ability to effectively understand the sentiments in these texts is much needed. This paper proposes a system titled NITS-Hinglish to effectively carry out the sentiment analysis of such code-mixed Hinglish text. The system has fared well with a final F-Score of 0.617 on the test data.
Dataflow Analysis With Prophecy and History Variables

Leveraging concepts from state machine refinement proofs, we use prophecy variables, which predict information about the future program execution, to enable forward reasoning for backward dataflow analyses. Drawing prophecy and history variables (concepts from the dynamic execution of the program) from the same lattice as the static program analysis results, we require the analysis results to satisfy both the dataflow equations and the transition relations in the operational semantics of underlying programming language. This approach eliminates explicit abstraction and concretization functions and promotes a more direct connection between the analysis and program executions, with the connection taking the form of a bisimulation relation between concrete executions and an augmented operational semantics over the analysis results. We present several classical dataflow analyses with this approach (live variables, very busy expressions, defined variables, and reaching definitions) along with proofs that highlight how this approach can enable more streamlined reasoning. To the best of our knowledge, we are the first to use prophecy variables for dataflow analysis.
Bridging the Imitation Gap by Adaptive Insubordination

Why do agents often obtain better reinforcement learning policies when imitating a worse expert? We show that privileged information used by the expert is marginalized in the learned agent policy, resulting in an "imitation gap. " Prior work bridges this gap via a progression from imitation learning to reinforcement learning. While often successful, gradual progression fails for tasks that require frequent switches between exploration and memorization skills. To better address these tasks and alleviate the imitation gap we propose 'Adaptive Insubordination' (ADVISOR), which dynamically reweights imitation and reward-based reinforcement learning losses during training, enabling switching between imitation and exploration. On a suite of challenging tasks, we show that ADVISOR outperforms pure imitation, pure reinforcement learning, as well as sequential combinations of these approaches.
Evaluation of colistin-associated acute renal failure in intensive care unit

Aim: Colistinâ€™s parenteral use was limited due to nephrotoxicity related to decreased renal perfusion, nephrotoxins and ischemia-reperfusion injury. Colistin became popular again because of multiple drug resistance (1, ). This study aimed to retrospectively evaluate the characteristics of intensive care patient groups with and without colistin-induced acute kidney injury. Material and Methods: Following approval of local ethics committee, information of the patients, who were treated in the anesthesia and surgical intensive care units between 01/01/2016 and 30/06/2017, were analyzed retrospectively. Results: Twenty patients (59%) developed acute kidney injury during colistin treatment. No statistically significant difference was observed between the groups with and without acute kidney injury in terms of age, gender and duration of stay in the intensive care unit, however, patients with acute kidney injury were found to be older and stayed in the intensive care unit for a longer period of time. The comparison made between the groups in terms of inotropic agent use showed that the duration of inotropic agent use was statistically longer in the acute kidney injury group. Discussion: Rate of colistin-induced acute kidney injury varies between 5-55%. In addition, fluid balance of patients is important in acute kidney injury development. Fluid therapy, hourly urine output and central venous pressure trends of the patients should be closely monitored particularly when nephrotoxic medicines are used. There is a need for large-scale studies with more advanced methodologies for the early detection and prevention of colistin-induced nephrotoxicity.
Polylidar3D-Fast Polygon Extraction from 3D Data

Flat surfaces captured by 3D point clouds are often used for localization, mapping, and modeling. Dense point cloud processing has high computation and memory costs making low-dimensional representations of flat surfaces such as polygons desirable. We present Polylidar3D, a non-convex polygon extraction algorithm which takes as input unorganized 3D point clouds (e.g., LiDAR data), organized point clouds (e.g., range images), or user-provided meshes. Non-convex polygons represent flat surfaces in an environment with interior cutouts representing obstacles or holes. The Polylidar3D front-end transforms input data into a half-edge triangular mesh. This representation provides a common level of abstraction for subsequent back-end processing. The Polylidar3D back-end is composed of four core algorithms: mesh smoothing, dominant plane normal estimation, planar segment extraction, and finally polygon extraction. Polylidar3D is shown to be quite fast, making use of CPU multi-threading and GPU acceleration when available. We demonstrate Polylidar3D’s versatility and speed with real-world datasets including aerial LiDAR point clouds for rooftop mapping, autonomous driving LiDAR point clouds for road surface detection, and RGBD cameras for indoor floor/wall detection. We also evaluate Polylidar3D on a challenging planar segmentation benchmark dataset. Results consistently show excellent speed and accuracy.
Domestic and CITES regulations controlling the international snake trade in China

Abstract Trade records show that since the 1990s China has changed from a net exporting to a net importing country with respect to some species of snakes. Imports of snakes to China increased up to 2002, when the National Wildlife Management Authority imposed a suspension of international trade in snakes. We investigated the impact of the ban using the same methods as an earlier study of this trade for the period 1990–2001. We found that both imports and exports of snakes recorded in the CITES Trade Database and the Wild Animal and Plant International Trade Database of China have decreased markedly since 2004. The combination of national-level control measures and CITES regulations appear to have controlled the previously unsustainable utilization of snakes in China.
Comparative Analysis of Polynomial and Rational Approximations of Hyperbolic Tangent Function for VLSI Implementation

Deep neural networks yield the state-of-the-art results in many computer vision and human machine interface applications such as object detection, speech recognition etc. Since, these networks are computationally expensive, customized accelerators are designed for achieving the required performance at lower cost and power. One of the key building blocks of these neural networks is non-linear activation function such as sigmoid, hyperbolic tangent (tanh), and ReLU. A low complexity accurate hardware implementation of the activation function is required to meet the performance and area targets of the neural network accelerators. Even though, various methods and implementations of tanh activation function have been published, a comparative study is missing. This paper presents comparative analysis of polynomial and rational methods and their hardware implementation.
Distribution of the Endangered Hermann's tortoise Testudo hermanni hermanni in Var, France, and recommendations for its conservation

Abstract Censuses of population fragments of the Endangered, endemic Hermann's tortoise Testudo hermanni hermanni were carried out during 2001–2005 in mainland France to reassess their status and provide guidelines for conservation management. Comparisons with previous censuses suggest a decline in abundance since 1992, although the total area of distribution remains unchanged. If conservation and management decisions only consider sites where there is a high encounter rate of tortoises, 19 sites would be protected. If indicators of effective reproduction (presence of both sexes, juveniles and subadults) are taken into account, 31 sites would deserve attention, of which only 10 have high encounter rates. Discarding sites with low encounter rates omits c. 70% of sites where the species appears to be reproducing. I provide a new map that includes demographic parameters, and thus describe 16 reproductive fragments plus four where reproduction is suspected. In the long-term the major conservation goal should be to protect these fragments and facilitate their reconnection. The global population of Hermann's tortoise could thus be largely contained in eight large fragments, enhancing the persistence of this species in mainland France.
Efficacy and functional outcome of bone marrow aspirate concentrate injection in osteoarthritis of knee– A prospective study

Introduction: Primary osteoarthritis is a very common progressive disease which usually ends up in deformities and morbidity. Osteoarthritis usually presents with joint pain, tenderness, limitation of movement, crepitus. BMAC can be useful in reducing pain and improve functional outcome with also in progressive of disease. Materials and Methods: This is an observational study conducted during the period of April 2015 to June 2017 on 30 samples. The descriptive statistical analysis was performed. The surgical procedure of Bone marrow aspirate concentration was carried out. Evaluation of Pre-Operative and Post-Operative functional outcome. Results: In this 19 (63.3%) patient presented with left knee osteoarthritis and 11 (36%) patients right knee osteoarthritis. 19 patients presented with grade 2 osteoarthritis and 11 patients presented with grade 3 osteoarthritis. VAS pain score 86.6% were in score range of 3-4 preoperatively which decreased to score range of 0-2 100% of the patients after BMAC Injection postoperatively at 6 months follow up. Conclusion: The use of Bone marrow concentrate injection (BMAC) in Osteoarthritis of knee was found to be more efficacious with good clinical and functional outcome. Keywords: Osteoarthritis, BMAC, WOMAC score, Knee society score.
Reachability Queries With Label and Substructure Constraints on Knowledge Graphs

Since knowledge graphs (KGs) describe and model the relationships between entities and concepts in the real world, reasoning on KGs often correspond to the <underline>r</underline>eachability queries with <underline>l</underline>abel and <underline>s</underline>ubstructure <underline>c</underline>onstraints (LSCR queries). Specifically, for a search path <inline-formula><tex-math notation="LaTeX">$p$</tex-math><alternatives><mml:math><mml:mi>p</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq1-3161375.gif"/></alternatives></inline-formula>, LSCR queries not only require that the labels of the edges passed by <inline-formula><tex-math notation="LaTeX">$p$</tex-math><alternatives><mml:math><mml:mi>p</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq2-3161375.gif"/></alternatives></inline-formula> are in a certain label set, but also claim that a vertex in <inline-formula><tex-math notation="LaTeX">$p$</tex-math><alternatives><mml:math><mml:mi>p</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq3-3161375.gif"/></alternatives></inline-formula> could satisfy a certain substructure constraint. They are much more complex than existing label-constraint reachability (LCR) queries. LSCR queries on KGs can be addressed by two natural ways (EA-1) an online search algorithm and (EA-2) a combined search strategy, to the best of our knowledge. This paper presents two optimized algorithms for EA-1 and EA-2, but the optimized algorithms are still inefficient, since their efficiencies are highly dominated by their search directions as analyzed in this paper. Motivated by that, this paper presents an efficient <underline>in</underline>formed <underline>s</underline>earch strategy on <underline>K</underline>Gs, named INSK, with a lightweight index, named local index. An extensive experimental evaluation, on both synthetic and real KGs, illustrates that our INSK can efficiently process LSCR queries on KGs.
Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild

Detecting objects and estimating their viewpoints in images are key tasks of 3D scene understanding. Recent approaches have achieved excellent results on very large benchmarks for object detection and viewpoint estimation. However, performances are still lagging behind for novel object categories with few samples. In this paper, we tackle the problems of few-shot object detection and few-shot viewpoint estimation. We demonstrate on both tasks the benefits of guiding the network prediction with class-representative features extracted from data in different modalities: image patches for object detection, and aligned 3D models for viewpoint estimation. Despite its simplicity, our method outperforms state-of-the-art methods by a large margin on a range of datasets, including PASCAL and COCO for few-shot object detection, and Pascal3D+ and ObjectNet3D for few-shot viewpoint estimation. Furthermore, when the 3D model is not available, we introduce a simple category-agnostic viewpoint estimation method by exploiting geometrical similarities and consistent pose labeling across different classes. While it moderately reduces performance, this approach still obtains better results than previous methods in this setting. Last, for the first time, we tackle the combination of both few-shot tasks, on three challenging benchmarks for viewpoint estimation in the wild, ObjectNet3D, Pascal3D+ and Pix3D, showing very promising results.
Scaling up the lattice dynamics of amorphous materials by orders of magnitude

We generalise the non-affine theory of viscoelasticity for use with large, well-sampled systems of arbitrary chemical complexity. Having in mind predictions of mechanical and vibrational properties of amorphous systems with atomistic resolution, we propose an extension of the Kernel Polynomial Method (KPM) for the computation of the vibrational density of states (VDOS) and the eigenmodes, including the $\Gamma$-correlator of the affine force-field, which is a key ingredient of lattice-dynamic calculations of viscoelasticity. We show that the results converge well to the solution obtained by direct diagonalization (DD) of the Hessian (dynamical) matrix. As is well known, the DD approach has prohibitively high computational requirements for systems with $N=10^4$ atoms or larger. Instead, the KPM approach developed here allows one to scale up lattice dynamic calculations of real materials up to $10^6$ atoms, with a hugely more favorable (linear) scaling of computation time and memory consumption with $N$.
Nasopharyngeal carriage of neisseria meningitidis among medical school students in Turkey.

Objective: Neisseria meningitidis can colonise healthy human nasopharynx and is one of the most important etiologic agent of epidemic meningitis. The purpose of this study is to investigate the carriage rate, serogroup distribution and antibiotic resistance of Neisseria meningitidis in medical faculty students. Methods: Nasopharyngeal swab cultures were evaluated. Identification is made by convensional and semi-otomatised system. Serogroup analysis was performed with slide agglutination method. Minimum inhibitor concentration results were evaluated by gradient test. Risk factors for carriage were investigated. Results: Neisseria meningitidis was isolated from 3 out of 475 (0.6%) students. Two of them were serogroup A and one was serogroup C. All strains were susceptible to penicillin and ceftriaxone. Living in a dormitory and sharing the room with three other students and smoking were found as risk factors. None of the students reported upper respiratory tract infection or antibiotic usage. Other potential pathogenic microorganisms colonising nasopharynx were also identified and most detected of them is methicillin susceptible Staphylococcus aureus (n: 87). Conclusion: Neisseria meningitidis is one of the leading pathogen in our country as it’s in the world. Since serogroups of isolated strains differ from region to region, it’s important that every country should conduct regular surveillance in order to utilize an effective vaccine for prevention and outbreak management against this infection.
Biomechanical Properties of Small-Size Hamstring Autografts

Purpose To evaluate small-size hamstring (HS) autografts for biomechanical properties and determine a threshold diameter necessary for appropriate reconstruction. Methods In a controlled laboratory setting, biomechanical testing was performed upon 15 hamstring autografts. The grafts were divided into three groups by diameter, with five grafts each at diameter sizes of 6, 7, and 8 mm. Testing of the specimens was performed using an MTS 858 (Materials Testing System, Eden Prairie, MN). We determined load to failure by looking at the maximum load as well as the stiffness of the graft. Statistical analysis was performed via analysis of variance (ANOVA) testing with Tukey's post-hoc test and P-values set at 0.05. Results There was a significant difference in ultimate tensile strength for the different size grafts: 1990 +/- 302.42 N for 6 mm grafts (n=5), 2179 +/- 685.36 N for the 7 mm grafts (n=5), and 3074 +/- 781 N for 8 mm grafts (n=5). This was statistically significant for the group overall (p=0.039), as well as between the 6 mm and 8 mm grafts (p=0.044). Graft stiffness for the 6 mm grafts was 317 +/- 85 N (n=5), 288.6 +/- 66 for 7 mm grafts (n=5), and 428.053 +/- 83 for 8 mm grafts (n=5). This achieved statistical significance for the group overall (p =0.037) as well as between the 8 mm and 7 mm grafts. Conclusions The biomechanical data presented here demonstrate that graft diameter is highly correlated with ultimate tensile strength and stiffness. Clinical relevance When viewing this biomechanical data in conjunction with prior clinical data, consideration should be given for the supplementation of an HS autograft as the size decreases below 8 mm.
Radar observation and aerial capture of mountain pine beetle, Dendroctonus ponderosae Hopk. (Coleoptera: Scolytidae) in flight above the forest canopy

An outbreak of the mountain pine beetle (Dendroctonus ponderosae Hopk.) in central British Columbia, Canada, has reached an unprecedented size and intensity and has been spreading. The 2005 emergence and subsequent flight of mountain pine beetle was studied using direct observation of emergence, weather radar imagery, and aerial capture. To verify that the daytime, clear-air radar returns seen during this period were indeed generated by airborne mountain pine beetles, aerial sampling in the area covered by the radar was performed using a drogue capture net towed by a single-engine light aircraft. Results verify that airborne mountain pine beetles are being detected by the weather radar and that, during the emergence period, significant numbers of mountain pine beetles can be found at altitudes up to more than 800 m above the forest canopy. An estimate of transport distance indicates that mountain pine beetles in flight above the forest canopy may move 30–110 km·day–1. An estimate of the instantaneous dens.
Effect of water deficit on 15N shoot allocation during seed filling in soybeans

Drought strongly limits crop productivity in semi-arid and many subhumid areas. Since soybean plants are sensitive to limited water supply at the beginning of the seed filling period, we studied effects of water deficits on protein synthesis in different organs of different ages during seed filling in two genotypes under well watered conditions, water deficit and after stress release. We used a flexible stem injection technique of 15 N application in order to quantify the importance of the internal cycling of N to support new protein. Restricted irrigation reduced seed mass accumulation in PI 416937, but not in Hutcheson. Leaves were susceptible to mild water deficits with regard to daily incorporation of 15 N into protein. During the rewatering period, this capacity remained on a low level, this was most pronounced in Hutcheson. Seed protein synthesis rate was only partially affected by water deficit. These findings suggest that the two genotypes differ with respect to source-sink relationships in response to a water restriction and following rewatering period. 15 N-incorporation rate, Glycine max. (L.), protein , drought, seed filling