Miracle-dz/UniFAR-FTUs huggingface dataset:
Studies on diversity and abundance of avifauna in and around Laxminarayan Institute of Technology campus, Nagpur, Central India

Nagpur city harbours wide variety of avifauna. The objective of the present study was the assessment of diversity and seasonal abundance of avifauna with vegetation, composition of habitat and foraging pattern among birds in and around Laxminarayan Institute of Technology (L.I.T.) campus, Nagpur, Central India. A total of 62 species of birds belonging to 11 orders and 38 families were recorded during January 2013 to December 2014. The species recorded included 57 residents, two passage migrants, one breeding migrant and two winter migrants. Passeriformes was recorded as the most dominating order represented by 36 species. Insectivore bird community was found to be dominant among foraging pattern.
Imperative Self-Adjusting Computation

Self-adjusting computation enables writing programs that can automatically and efficiently respond to changes to their data (e.g., inputs). The idea behind the approach is to store all data that can change over time in modifiable references and to let computations construct traces that can drive change propagation. After changes have occurred, change propagation updates the result of the computation by re-evaluating only those expressions that depend on the changed data. Previous approaches to self-adjusting computation require that modifiable references be written at most once during execution—this makes the model applicable only in a purely functional setting. In this paper, we present techniques for imperative self-adjusting computation where modifiable references can be written multiple times. We define a language SAIL (Self-Adjusting Imperative Language) and prove consistency, i.e., that change propagation and from-scratch execution are observationally equivalent. Since SAIL programs are imperative, they can create cyclic data structures. To prove equivalence in the presence of cycles in the store, we formulate and use an untyped, step-indexed logical relation, where step indices are used to ensure well-foundedness. We show that SAIL accepts an asymptotically efficient implementation by presenting algorithms and data structures for its implementation. When the number of operations (reads and writes) per modifiable is bounded by a constant, we show that change propagation becomes as efficient as in the non-imperative case. The general case incurs a slowdown that is logarithmic in the maximum number of such operations. We describe a prototype implementation of SAIL as a Standard ML library.
REGIONÁLNÍ ROZVOJ A RIO PO 20 LETECH

Access to medical staff differs across Europe and the particular countries. Poland is a country that has the smallest number of physicians in whole European Union. This country struggles with healthcare provider shortages, but another problem is an uneven distribution of workers. It means that shortages are often more profound in rural areas. This problem affecting the nation's healthcare system will be presented on the example of a region of Plock. The aim of the study is to analyse the availability of medical staff in a region of Plock in the years 20072015. Particular attention is paid to the number of health personnel per 10.000 inhabitants in the city of Plock. The analysis regards the physicians, nurses and midwives. The problem of availability of medical staff in Plock region is shown on the background of the average for the Mazovia province and the whole country. The research material is based on the statistical data extracted from Central Statistical Office of Poland.
Evaluation of Ultrasonic Velocity Tests to Characterize Extraterrestrial Rock Masses

Evaluation of Ultrasonic Velocity Tests to Characterize Extraterrestrial Rock Masses Thomas Wesley Edge II NASA and other private companies are currently developing mission concepts to explore and extract resources from various extraterrestrial resources, including asteroids, lunar ice, and Martian regolith. Unfortunately, information on the geotechnical and mechanical properties of these potential resources is extremely sparse and often based on limited test data from surrogate samples (e.g. meteorites). Since Earthbased observational measurements alone cannot quantify these critical geotechnical properties, target specimens must be tested in-situ using non-destructive techniques. This data will mitigate risks caused by uncertainty in material properties. While numerous nondestructive rock characterization techniques are common for terrestrial applications, these methods must be adapted to account for physical properties and environmental conditions of space. This thesis investigates the use of ultrasonic pulse velocity (UPV) tests for extraterrestrial rock characterization by evaluating the e ects of physical sample properties on the signal attenuation of ultrasonic waves. An initial review of standard laboratory UPV testing methods and expected space conditions isolated four key disparities between the two testing environments: (1) sample dimensions, (2) regolith cover, (3) sample surface roughness, and (4) utility of a gel couplant. Laboratory tests were then performed to assess the in uence of these parameters in simulated space conditions, using concrete beams to simulate large sample sizes, and ground limestone to simulate regolith cover. The ensuing data analysis identi ed strategies to ensure adequate signal transmission and data interpretation. Overall, the experimental results show that the signal attenuation curves can be constructed and simple regression curves can provide estimations of the true Pwave velocity even without a gel couplant. For the case of large sample sizes, simple exponential regression of the measured P-wave velocity at various transmission lengths can be extrapolated to zero length to estimate the true value. For the case of regolith cover, the particle top size and particle size distribution a ect signal attenuation; however, an exponential t to measured velocity versus depth data can be used to accurately predict true sample velocity at zero depth. Additionally, testing with rough samples showed that compacted regolith can be used to ensure contact between the sample and the UPV transmitter, and this method produced similar attenuation curves to those determined from smooth samples. Altogether, these data indicate the reliability of UPV to characterize material in-situ; however, without a gel couplant, UPV measurements become increasingly imprecise.
ScholarWorks @ UTRGV ScholarWorks @ UTRGV

—It’s critical for an autonomous vehicle to acquire accurate and real-time information of the objects in its vicinity, which will fully guarantee the safety of the passengers and vehicle in various environment. 3D LIDAR can directly obtain the position and geometrical structure of the object within its detection range, while vision camera is very suitable for object recognition. Accordingly, this paper presents a novel object detection and identification method fusing the complementary information of two kind of sensors. We first utilize the 3D LIDAR data to generate accurate object-region proposals effectively. Then, these candidates are mapped into the image space where the regions of interest (ROI) of the proposals are selected and input to a convolutional neural network (CNN) for further object recognition. In order to identify all sizes of objects precisely, we combine the features of the last three layers of the CNN to extract multi-scale features of the ROIs. The evaluation results on the KITTI dataset demonstrate that : (1) Unlike sliding windows that produce thousands of candidate object-region proposals, 3D LIDAR provides an average of 86 real candidates per frame and the minimal recall rate is higher than 95%, which greatly lowers the proposals extraction time; (2) The average processing time for each frame of the proposed method is only 66.79ms, which meets the real-time demand of autonomous vehicles; (3) The average identification accuracies of our method for car and pedestrian on the moderate level are 89.04% and 78.18% respectively, which outperform most previous methods.
voom : precision weights unlock linear model analysis tools for RNA-seq read counts ∗ Charity

In the past few years, RNA-seq has emerged as a revolutionary new technology for expression profiling. RNA-seq expression data consists of read counts, and many recent publications have argued therefore that RNA-seq data should be analyzed by statistical methods designed specifically for counts. Yet all the statistical methods developed for RNA-seq counts rely on approximations of various kinds. This article revisits the idea of applying normal-based microarray-like statistical methods to RNA-seq read counts, with the idea that it is more important to model the mean-variance relationship correctly than it is to specify the exact probabilistic distribution of the counts. Log-counts per million are used as expression values. Two methods are developed for modeling the mean-variance relationship in the context of a normal-based analysis. One method, called limma-trend, accommodates the mean-variance relationship as part of the empirical Bayes procedure. The second method, called voom, estimates the mean-variance relationship robustly and generates a precision weight for each individual normalized observation. The normalized log-counts per million and associated precision weights are then entered into the limma analysis pipeline, or indeed into any statistical pipeline for microarray data that is precision weight aware. Either method opens access for RNA-seq analysts to a large body of methodology developed for microarrays, allowing RNA-seq and microarray data to be analyzed in closely comparable ways. The performance of voom and limma-trend is compared to that of edgeR, DESeq, baySeq, TSPM, PoissonSeq, and DSS. Simulation studies show that the limma-based pipelines more than hold their own against the count-based RNA-seq methods in terms of power and error rate control even when the data are generated according to the assumptions of the earlier methods. Several data sets are analyzed to demonstrate how voom and limma-trend can handle heterogeneous data and complex experiments as well as facilitating pathway analysis and gene set testing methods.
ANALYTICAL APPROACH FOR OPINION DYNAMICS ON SOCIAL NETWORKS

The opinion dynamics is a class of agent based models arising from the study of the origins and evolutions of languages and now attracts a lot of interest. These models consist of a large number of individuals updating their states through pairwise interactions. These models provide powerful tools to simulate and investigate the collective behavior in complex systems in sociology, physics and computer science. The main object of this thesis is to provide a framework for analyzing the opinion dynamics, in particular the 2-word Naming Game(NG). We develop one random walk model which works for complete graph and highly connected networks without community structures. We also develop an improved ODE model which works for sparse networks without community structures. Both models are based on a so-called coarse-graining approach which requires an underlining mean field assumption. We derive analytical results according to these models and confirm our results by numerical simulations of NG dynamics. The thesis is organized as follows. Chapter 2 introduces two basic models based on coarse-graining approach: the ODE model and the random walk model, and analyze a prototypical opinion dynamics, the voter model, as a random walk. Chapter 3 further applies the random walk model on the 2-word Naming Game on complete graphs, calculates the expectation of the total consensus time Tc and the expected time spent on each macrostate before consensus T (nA, nB) in three cases: (i)purely symmetric case; (ii)with biased central influence; (iii)with committed agents. The tipping point of committed fraction and different dynamics behavior below and above the tipping point are also discussed. Chapter 4 analyzes the distribution of the consensus time Tc of 2-word Naming Game on complete graphs in several ways, calculates the variance of Tc through a martingale approach, and provide a path integral approximation for the variance of Tc. Chapter 5 develops an improved ODE model using the homogeneous pairwise assumption, a variation of mean field assumption, which works for sparse networks with narrow degree distribution and no community structures. This model shows the dependence of the
Brill – Noether with ramification at unassigned points

We discuss, how via limit linear series and standard facts about divisors on moduli spaces of pointed curves, one can establish a non-existence Brill–Noether results for linear series with prescribed ramification at unassigned points. © 2013 Elsevier B.V. All rights reserved. In the course of developing their theory of limit linear series, among many other applications, Eisenbud and Harris [2,3] also considered the Brill–Noether problem with prescribed ramification at assigned points. For a smooth curve C of genus g , a point p ∈ C and a linear series l = (L, V ) ∈ Gd(C), one denotes by α(p) : 0 ≤ α 0(p) ≤ · · · ≤ α l r (p) ≤ d − r the ramification sequence of l at p. Having fixed points p1, . , pn ∈ C , Schubert indices ᾱj : 0 ≤ α j 0 ≤ · · · ≤ α j r ≤ d − r of type (r, d) for j = 1, . , n, the locus of linear series on C having prescribed ramification at p1, . , pn ∈ C , that is, Gd  C, (pj, ᾱj)  := {l ∈ Gd(C) : α (pj) ≥ ᾱj for j = 1, . , n} is a generalized determinantal variety of expected dimension ρ(g, r, d, ᾱ1, . . . , ᾱn) := ρ(g, r, d)− n 
Supervisory control: Air traffic control specialist performance in shared versus traded states

The National Airspace System (NAS) is currently undergoing a restructuring in order to reduce flight delays and to increase airspace capacity, flight predictability, process visibility and safety. In general the reduction of constraints and the redistribution of information, authority and decision making capability has been termed "free flight. " One aspect of this process of restructuring involves exploring the possibility of delegating some portions of aircraft separation authority to the flight deck. This process of delegation for self-separation to the flight deck and its implications for pilots and air traffic controllers was the topic of this simulation experiment. Seventeen Air Traffic Control Specialists performed in shared and traded supervisory control states. Shared control is the performance of a task by a human operator with the concurrent assistance of automation. Traded control is the process of shifting the handling of a task by either the human operator or automation. In the shared condition, the specialists monitored the airspace with the assistance of a conflict probe. In the traded condition, the specialists performed a secondary task, in addition to monitoring the traffic with the assistance of the conflict probe. The researcher also manipulated the percentage of planes in free flight, 80% and 100%. Indices included controller workload, separation performance, secondary task performance, and questionnaire data. Results indicated that workload was significantly higher in the traded condition, and that there were less separation violations in the shared condition. The participants also performed better on the secondary task in the Traded/100% condition than the Traded 80% condition. The study was funded by the FAA and NASA.
Voluntary Turnover in the Omani Public Sector: An Islamic Values Perspective

Following four decades of economic growth the public sector, Oman is experiencing an emerging problem of labor turnover to the private sector. We examine this phenomenon through semi-structured interviews with 26 current and former public employees. The rate of turnover is low but this masks the impact of losses on key technical and management roles. The main reasons for turnover are dissatisfaction with management style, reward practices, and promotion opportunities. Findings are interpreted in the context of Islamic work values and implications for public management reform in Oman are provided.
To what extent have laterites contributed to the geochemical, surface reflectance and magnetic properties of adjacent tropical soils? Evidence from Niger and Burkina Faso

The present study is based on a suite of surface samples from exposures of eroded laterite, considered to be Tertiary in age, and nearby soils in the Sahelian region of SW Niger and Burkina Faso. X‐ray fluorescence, X‐ray diffraction, computer‐controlled scanning electron microscopy, energy‐dispersive X‐ray spectroscopy, diffuse UV–visible reflectance spectroscopy and a suite of magnetic measurements have been used to shed light on the origin of the soils and their possible derivation from the adjacent, eroded laterite outcrops. On the basis of the wide range of data obtained, we conclude that the mineralogy and magnetic properties of the soils preclude direct derivation from the laterites without further weathering and modification. Nor does the evidence support the view that the soils have evolved entirely independently, uninfluenced by input from the laterites. The only conclusion that is consistent with all the lines of evidence is that the erosion of the laterites provided at least a significant part of the material upon which soil formation took place. This must have occurred at a time early enough to permit a long period of subsequent soil development during which the iron oxides, specifically haematite and ferrimagnetic minerals, were significantly modified. From this, we infer that eroded material from discontinuous laterite exposures has contributed significantly to the remotely sensed, distinctive reflectance characteristics of the Sahel surfaces. The magnetic properties of the soils provide evidence for the in situ neo‐formation of fine, secondary, pedogenic magnetite/maghemite grains typical of those found in many soils across the Sahel region and elsewhere in both temperate and tropical environments. Copyright © 2017 John Wiley & Sons, Ltd.
Super wide viewer using catadioptrical optics

Many applications have used a Head-Mounted Display (HMD), such as in virtual and mixed realities, and tele-presence. The advantage of HMD systems is the ease of feeling a 3D world in the display of animation or movies. However, the field of view (FOV) of commercial HMD systems is too narrow for feeling immersion. The horizontal FOV of many commercial HMDs is around 60 degrees, significantly narrower than that of humans. In this paper, we propose a super wide field of view head-mounted display consisting of an ellipsoidal and a hyperboloidal curved mirror. The horizontal FOV of the proposed HMD is 180 degrees and includes the peripheral view of humans. It increases reality and immersion of users. As well, the central region (60 degrees) of the FOV can measure 3D distances using stereoscopics.
A Prehistoric Rock Shelter Burial Site and Enclosure at Scabba Wood, Sprotbrough, South Yorkshire

Abstract In 1992 two Middle Neolithic adult skeletons were excavated by South Yorkshire Archaeological Services from beneath a rock overhang at Scabba Wood (SE527019), near Sprotbrough, within one of the valleys north of the Don Gorge. In 1994, the Yorkshire Archaeological Society’s Doncaster branch carried out a geophysical survey of a rectangular enclosure (SE530019), previously recognised by air photography, north-east of the wood, and in 1996 they began the excavation of a stone-walled, sub-rectangular enclosure within the wood, 150 m south of the rock overhang (SE530107). In 1997 and 1998 they were joined by a team from Sheffield University that also continued investigations at the stone-walled enclosure and along the rock overhang. Finds indicate occupation from the Late Iron and Roman period and Neolithic and Early Bronze Age use of the rock overhang for the disposal of the dead.
A Theory of IPO Underpricing, Issue Activity, and Long-Run Underperformance

We present a dynamic model of an IPO market in which firms go public to raise capital for investment. The original shareholders have inside information with respect to the quality of their firm's investment opportunities, and they decide whether to go public, how much capital to raise and invest, and how to price the IPO. Outside investors are of one of two types: some investors know and understand even the not directly observable economic incentives of the original shareholders, whereas all other investors learn about the IPO market only from the publicly observable IPO market data. Market participation by the latter investors can upset the stationary rational equilibrium and give rise to a dynamic equilibrium that is characterized by: (1) IPO underpricing, (2) underperformance of IPO shares in the long run, and (3) cyclical variations in IPO volume. Learning investors upset the stationary equilibrium not because of ex ante unreasonable beliefs, but because they fail to condition their beliefs on variables that convey only redundant information in the stationary equilibrium. The model provides a joint explanation for the three empirically documented IPO market "anomalies," and it yields a number of new testable empirical predictions.
0 R-GPU : a Reconfigurable GPU Architecture

Over the last decade GPU architectures have evolved from a fixed-function graphics pipeline to a programmable, energy efficient compute accelerator for massively parallel applications. The compute power arises from the GPU’s SIMT architecture: concurrently running many threads, executing them as SIMD style vectors. However, compute power is still lost due to cycles spent on data movement and control instructions instead of data-computations. Even more cycles are lost on pipeline stalls resulting from long latency (memory) operations. To improve not only performance but also energy efficiency, we introduce R-GPU: a reconfigurable GPU architecture with communicating cores. R-GPU is an addition to a GPU, which can still be used as such, but also has the ability to reorganize the cores of a GPU in a reconfigurable network. In R-GPU data movement and control is implicit in the configuration of the network. Each core executes a fixed instruction, reducing instruction decode count and increasing energy efficiency. On a number of benchmarks we show an average performance improvement of 2.1×. We further make a conservative power estimation of R-GPU which shows that power consumption can be reduced by 6%, while area increases by a mere 4%, leading to an energy consumption reduction of 55%.
TDAPNet: Prototype Network with Recurrent Top-Down Attention for Robust Object Classification under Partial Occlusion

Despite deep convolutional neural networks' great success in object classification, it suffers from severe generalization performance drop under occlusion due to the inconsistency between training and testing data. Because of the large variance of occluders, our goal is a model trained on occlusion-free data while generalizable to occlusion conditions. In this work, we integrate prototypes, partial matching and top-down attention regulation into deep neural networks to realize robust object classification under occlusion. We first introduce prototype learning as its regularization encourages compact data clusters, which enables better generalization ability under inconsistent conditions. Then, attention map at intermediate layer based on feature dictionary and activation scale is estimated for partial matching, which sifts irrelevant information out when comparing features with prototypes. Further, inspired by neuroscience research that reveals the important role of feedback connection for object recognition under occlusion, a top-down feedback attention regulation is introduced into convolution layers, purposefully reducing the contamination by occlusion during feature extraction stage. Our experiment results on partially occluded MNIST and vehicles from the PASCAL3D+ dataset demonstrate that the proposed network significantly improves the robustness of current deep neural networks under occlusion. Our code will be released.