Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparisons of intermediately ranked species in avian rank- abundance distributions from four California forests

Biodiversity indices, such as those that measure species richness or evenness, provide limited information about ecological communities. The species abundance distributions from which these indices are derived contain greater detail about community structure. For this reason conservation planners and land managers would benefit from methods that allow more informative comparisons of these distributions than offered by traditional indices. We used bird survey data from four research forests in California to construct rank-abundance distributions. Using bootstrap re-sampling, we created uncertainty bands associated with the empirical shapes of these curves, allowing identification of significant (P<0.05) differences between distributions over a portion of their ranks. We found higher abundances of intermediately ranked species on two of the forests, and ascribe this result to differences in forest productivity and habitat complexity leading to greater niche partitioning of resources. Diversity indices derived from these data were less informative.
1 Rapid Diffusion of Hydrogen Protects the Retina : Administration to the Eye of Hydrogen-Containing Saline in Retinal Ischemia-Reperfusion Injury

PURPOSE. Retinal ischemia-reperfusion (I/R) injury by transient elevation of intraocular pressure (IOP) is known to induce neuronal damage through the generation of reactive oxygen species. Previous studies indicate that molecular hydrogen (H2) is an efficient antioxidant gas that selectively reduces the hydroxyl radical (•OH) and suppresses oxidative stress-induced injury in several organs. This study was conducted to explore the neuroprotective effect of H2-loaded eye drops on retinal I/R injury. METHODS. Retinal ischemia was induced in rats by raising IOP for 60 minutes. H2-loaded eye drops were prepared by dissolving H2 gas into a saline to saturated level and administered to the ocular surface continuously during the ischemia and/or reperfusion periods. One day after I/R injury, apoptotic cells in the retina were quantified and oxidative stress was evaluated by markers such as 4-hydroxynonenal and 8-hydroxy-2-deoxyguanosine. Seven days after I/R injury, retinal damage was quantified by measuring the thickness of the retina. RESULTS. When H2-loaded eye drops were continuously administered, H2 concentration in the vitreous body immediately increased and I/R-induced •OH level decreased. The drops reduced the number of retinal apoptotic and oxidative stress marker-positive cells, and prevented retinal thinning with an accompanying activation of Müller glia, astrocytes, and microglia. The drops improved the recovery of retinal thickness by >70%. CONCLUSIONS. H2 has no known toxic effects on the human body. Thus, our study suggests that H2-loaded eye drops will be a highly useful neuroprotective and anti-oxidative therapeutic treatment for acute retinal I/R injury.
EXOSOME-MIMETIC NANOVESICLE GENERATION SYSTEM

This paper introduces a developed simple device for generating exosome-mimetic nanovesicles by using centrifuge that can apply force to extrude cells through micro pore filters. Using a simple polycarbonate structure, we generate large quantity of nanovesicles which is successfully mimicked exosomes. Also, we verify that the generated exosome mimetic nanovesicles have cellular materials of source cell and can deliver these materials to target cells.
Gender differences in reaction to psychological pressure: evidence from tennis players

ABSTRACT Using data on about 35,000 professional tennis matches, we test whether men and women react differently to psychological pressure arising from the outcomes of sequential stages in a competition. We show that, with respect to men, women losing the first set are much more likely to play poorly the second set. This suggests that women are more discouraged when facing the pressure of falling behind and receiving negative feedback. The gender differential is stronger in high-stake matches. On the other hand, when players are tied in the third set we do not find any gender difference in players’ reactions suggesting that women are as able as men to handle pressure if they do not lag behind. These results are robust controlling for measures of abilities and fitness of players, such as players’ rankings, players’ ex-ante winning probability, players’ rest, monetary prizes, players’ and tournaments’ fixed effects.
Investigation of different topologies of neural networks for data assimilation

Neural networks have emerged as a novel scheme for a data assimilation process. Neural network techniques are applied for data assimilation in the Lorenz chaotic system. A radial basis function and a multilayer perceptron neural networks are trained employing 1000, 2000, and 4000 examples. Three different observation intervals are used: 0.01, 0.06 and 0.1 s. The performance of the data assimilation technique is investigated for different architectures of these neural networks.
RGB-D face recognition in surveillance videos

Biometric analysis of surveillance videos carries inherent challenges in form of variations in pose, distance, illumination and expression. To address these variations, different methodologies are proposed, including utilizing temporal and 3D information. With the introduction of consumer level depth capturing devices such as Microsoft Kinect, research has been performed in utilizing low cost RGB-D depth data for characterizing and matching faces. Face detection being the foremost task in face biometric pipeline has a cascading effect on the performance of any face recognition system that follows. Face detection algorithms generally work best for frontal face images with good illumination and low standoff distance. Developing a face detection system robust to the variates of a surveillance scenario is a highly challenging task. Recognition of the detected faces in surveillance scenarios is a challenging task owing to high variance in pose, illumination, expression and resolution. Also, the quality of depth data in RGB-D videos deteriorates with increase in standoff distance, thus adding to the challenges of RGB-D face recognition. This research introduces the KaspAROV RGB-D video face database which provides face videos and images from Kinect device for over 100 subjects. The database encompasses challenges such as pose, distance, and illumination. Further, a novel face detection system for RGB-D videos taken in unconstrained scenario is proposed. The proposed system makes use of human body detection in color images and fuses it with the corresponding depth map to provide a robust solution for face detection at a distance in RGB-D videos. For recognizing the detected faces we introduce a RGB-D face recognition algorithm which can also work with only RGB probe images in absence of depth data in probe images . The proposed algorithm generates a shared representation from RGB images which contains discriminative information from both the RGB and depth images. This representation is much more discriminative than the RGB images as it gives substantially higher identification accuracy than a conventional fusion based RGB-D recognition pipeline.
ental health of dogs formerly used as ‘ breeding stock ’ in commercial reeding establishments ranklin

Canine commercial breeding establishments (CBEs) are kennel facilities where puppies are produced in large numbers for commercial sale. In the popular media, CBEs are commonly referred to as “puppy mills” or “puppy farms. ” Conditions in CBEs vary widely in quality. Dogs in these facilities are routinely housed for their entire reproductive lives in cages or runs, and provided with minimal to no positive human interaction or other forms of environmental enrichment. Numerous anecdotal reports have suggested that after removal from CBEs many of the former breeding dogs display persistent behavioural and psychological abnormalities when compared with the general pet dog population. The purpose of this study was to determine if this anecdotal evidence could be confirmed empirically. Behavioural evaluations of the dogs were obtained from current owners/fosterers using the Canine Behavioural Assessment and Research Questionnaire (C-BARQ), which utilizes ordinal scales to rate either the intensity or frequency of the dog’s behaviours. A total of 1169 former CBE dogs were included in the study. Among the CBE ex-breeding dogs, 76 different breeds were represented. With the exception of the Bichon Frise (31.5%), all other breeds comprised <5% of the dogs. The sex ratio was 70.3% females and 29.7% males. The dogs had been living in their adoptive homes for an average of 2 years when the C-BARQ was completed. When compared with a convenience sample of pet dogs matched for breed, sex, age and neuter status, former CBE breeding dogs were reported as showing significantly higher rates of health problems (23.5% versus 16.6%, P = 0.026). With respect to behaviour, CBE dogs displayed significantly higher rates of fear (both social and nonsocial; ordinal GLM models, P < 0.001), house-soiling (P < 0.001), and compulsive staring (P < 0.005); and significantly lower rates of aggression (toward strangers and other dogs; P < 0.0001), trainability (P < 0.0001), chasing small animals (P < 0.0001), excitability (P < 0.0001), and energy
Synergist: Collaborative Analyst Assistant

Abstract : Intelligence Analysts work with a significant amount of information expressed in natural language. The textual information that Analysts work with or generate provide important clues on what is known to them, what are their immediate and long term needs, and what aspects are typically explored or missed in the context of a particular topic. For CASE, Lymba developed Synergist: Collaborative Analyst Assistant, an automated system that understands unstructured content, extracts knowledge from text and collaborates with intelligence analysts to model their needs and to aid with their information discovery. Synergist provides a grid-computing framework for state-of-the-art natural language processing to extract rich semantic information from large document collections. With a hierarchical semantic representation of entity, event, relation and context information text, Synergist is able to capture, represent and organize the knowledge from text in ontologies and knowledge bases.
Deep Learning Algorithm for Cyberbullying Detection

Cyberbullying is a crime where one person becomes the target of harassment and hate. Many cyberbullying detection approaches have been introduced, however, they were largely based on textual and user features. Most of the research found in the literature aimed at improving detection through introducing new features. However, as the number of features increases, the feature extraction and selection phases have become harder. On the other hand, no study has examined the meaning of words and semantics in cyberbullying. In order to bridge this gap, we propose a novel algorithms CNN-CB that eliminate the need for feature engineering and produce better prediction than traditional cyberbullying detection approaches. The proposed algorithm adapts the concept of word embedding where similar words have similar embedding. Therefore, bullying tweets will have similar representations and this will advance the detection. CNN-CB is based on convolutional neural network (CNN) and incorporates semantics through the use of word embedding. Experiments showed that CNN-CB algorithm outperform traditional content-based cyberbullying detection with an accuracy of 95%.
THE HOST GALAXIES OF X-RAY QUASARS ARE NOT STRONG STAR FORMERS

We use ultradeep SCUBA-2 850 μm observations (∼0.37 mJy rms) of the 2 Ms Chandra Deep Field-North (CDF-N) and 4 Ms Chandra Deep Field-South X-ray fields to examine the amount of dusty star formation taking place in the host galaxies of high-redshift X-ray active galactic nuclei (AGNs). Supplementing with COSMOS, we measure the submillimeter fluxes of the 4–8 keV sources at z > 1 ? > , finding little flux at the highest X-ray luminosities but significant flux at intermediate luminosities. We determine graybody and MIR luminosities by fitting spectral energy distributions to each X-ray source and to each radio source in an ultradeep Karl G. Jansky Very Large Array (VLA) 1.4 GHz (11.5 μJy at 5 &sgr; ? > ) image of the CDF-N. We confirm the far-infrared (FIR)-radio and mid-infrared (MIR)-radio correlations to z = 4 using the non-X-ray detected radio sources. Both correlations are also obeyed by the X-ray less luminous AGNs but not by the X-ray quasars. We interpret the low FIR luminosities relative to the MIR for the X-ray quasars as being due to a lack of star formation, while the MIR stays high due to the AGN contribution. We find that the FIR luminosity distributions are highly skewed and the means are dominated by a small number of high-luminosity galaxies. Thus, stacking or averaging analyses will overestimate the level of star formation taking place in the bulk of the X-ray sample. We conclude that most of the host galaxies of X-ray quasars are not strong star formers, perhaps because their star formation is suppressed by AGN feedback.
NonCommercial-NoDerivatives 4.0 International License. ORGANIZATIONAL CULTURE AND TQM IMPLEMENTATION IN CONSTRUCTION FIRMS IN SINGAPORE Abstract The adoption and implementation of Total Quality Management (TQM) are related to a company's culture. The relationship between cultural orientation and the

The adoption and implementation of Total Quality Management (TQM) are related to a company's culture. The relationship between cultural orientation and the implementation of TQM practices among certified Singapore contractors is investigated from an organizational culture perspective. The Competing Values Framework was used to assess organizational culture and eight TQM elements were identified to gauge the implementation of TQM practices among contractors. A survey questionnaire was administered. Four organizational culture types have been identified from the survey findings. These are strong comprehensive, clandriven, hierarchy-driven, and weak comprehensive culture. Firms with strong comprehensive culture implement highly the TQM elements of top management leadership, people, process, customer, and supplier management. Firms with clandriven culture implement highly the element of process management while firms with hierarchy-driven and weak comprehensive culture implement lowly to moderately all elements. A cultural-based TQM implementation strategy is proposed. Keyword: competing values framework, contractor, organizational culture, total
Survey on Implementing Privacy Preserving Model for Shared Data in The Cloud

Cloud Computing gives storage services where user can remotely stores and access data. Different types of applications would be developed using cloud services for different purposes such as data sharing in private or public domain, limiting the access rights to some groups or multiple users and as so on. It also reduces the load of maintenance and security of data on intranet network. Currently, the failure in hardware/software and human errors, the integrity, privacy and data access of cloud data is vulnerable, For these type of problems different mechanisms/solutions have been designed. However, maintaining integrity of shared data in cloud using public auditing is a critical task. Therefore user uses third party auditor to maintain and check integrity of data as and when required. Because of effective third party auditing verification process, the privacy maintained and not harmful to any party.So proposed system preserves privacy of shared data in cloud using public auditing. Ring signature could be used to compute and verify data which is required for auditing. With this mechanism the identity of signer on each block is kept private without disclosing data. It improves the data privacy by achieving traceability and the data freshness. Therefore proposed system will perform audit for some specific groups or multiple users efficiently.
MEDUSA: Malware Detection Using Statistical Analysis of System's Behavior

Traditional malware detection techniques have focused on analyzing known malware samples' codes and behaviors to construct an effective database of malware signatures. In recent times, however, such techniques have inherently exposed limitations in detecting unknown malware samples and maintaining the database up-to-date, as many polymorphic and metamorphic malware samples are newly created and spread very quickly throughout the Internet. To address the limitations of existing signature-based malware scanners, we take a different view and focus on designing a novel malware detection framework, called MEDUSA (MalwarE Detection Using Statistical Analysis of system's behavior), for building a model for a system's behaviors with normal processes. Unlike traditional approaches for malware detection, MEDUSA has the potential to effectively detect unknown malware samples because it is designed to monitor a system's behavior and detect significant changes from the system's normal status. In this paper, we specifically discuss several important considerations that must be taken into account to successfully develop MEDUSA in practice.
Cascaded Active Neutral Point Clamped and Flying Capacitor Inverter Topology for Induction Motor Drives Applications

This paper proposes a novel multilevel architecture using active neutral point clamped inverter cascaded with a flying capacitor inverter to form a multilevel inverter topology with higher number of voltage levels for induction motor drives. All the capacitors in the topology can be balanced irrespective of any modulation index or power factor. This topology can be generalized for higher number of voltage levels. The front end DC sources required are of very low value and it can be further halved when using a reconfigured six phase induction machine for higher power. The low value DC sources can be stacked battery cells, hence the topology can find extensive applications in electric vehicles. Detailed experimental results are shown for the steady state and transient operations of the inverter. The proposed topology will be a viable scheme for high power applications.
Modeling collective emotions in online social systems

Collective emotions in online social systems emerge through the interaction of thousands of internet users. We analyse their digital traces, i.e. the messages posted in chatrooms, fora, microblogging sites, or product review communities, by means of statistical methods and sentiment detection, to reveal statistical regularities, or patterns, in their online activity and emotional expressions. These ndings are reproduced by agent-based models. Following the circumplex model of Russel (1980), agents are characterized by their individual valence (the type of emotion) and their arousal (the activity level associated with the emotion). Both variables change according to a stochastic dynamics which follows the concept of Brownian agents. Regarding the emotional in uence we test di erent hypotheses about the agents' responses to emotional information provided through the online medium. After outlining the general framework of emotional communication, we provide two di erent applications to model emotional in uence: (i) in product review communities, (ii) in chatrooms. In both cases, we are able to reproduce the collective behavior observed empirically by means of a speci ed agent-based model. This implies that basic features of emotional in uence are reasonably well covered by our theoretical approach. We further comment on the baseline of emotional expressions in text, verifying the Polyanna hypothesis, and on the sharing of messages dependent on their emotional content. 1 A Modelling Framework for Collective Emotions Everyday, millions of Internet users leave online traces that are publicly accessible. Data about forum comments, video downloads, or product reviews provide a valuable insight into human online behavior. The retrieval of datasets of unprecedented size may eventually also allow to test hypotheses or validate theories that have been developed in the social sciences, for example about preferences, social in uence [17, 21], trust and cooperation [38]. This recent scienti c development has lead to the emerging eld of computational social science [15] which combines methods and tools from di erent technical and social disciplines. Also psychology can bene t from this development by getting access to data without designing expensive experimental setups of limited size. For example, the analysis of user expressions in Twitter allowed to study the in uence of the circadian cycles on human mood [12]. Mechanisms of sentiment analysis of written text allowed to analyse emotional expressions in the indexable web and revealed patterns in human expression that have been predicted by earlier psychological theories [9]. corresponding author: fschweitzer@ethz.ch
MORPHOLOGICAL AND MORPHOMETRICAL ANALYSIS OF FORAMEN MAGNUM: AN ANATOMICAL STUDY

Address for Correspondence: Dr.Jignesh L Patel Assistant Professor, Department Of Anatomy, American International Institute Of Medical Sciences, Udaipur, Rajasthan-313001, India. Mobile No. 09427008883, E-Mail: jignesh29982@gmail.com Background: Foramen magnum (FM) is an important landmark of the skull base and is of particular interest for anthropology, anatomy, forensic medicine and other medical field. It is one of several oval or circular apertures in the base of the skull, through which medulla oblongata is transmitted. Variations of the shape of FM have got diagnostic clinical and radiological importance. The dimensions of FM have clinical importance because the vital structures that pass through it may suffer compression as in cases of FM achondroplasia and FM brain herniation, so this study aimed to access its diameter and determining its various shape. Materials and Methods: Study sample consisted of 75 dry adult human skull of unknown sex, free from any pathology and collected from Department of Anatomy, P.D. U. Medical College, Rajkot, Gujarat and American international institute of medical sciences, Udaipur, Rajasthan, India. Results: The FM was observed to have round shape in 8%, egg shape in 9.33% tetragonal in 25.33%, oval in 33.33%, irregular in 2.67%, hexagonal in 8% and pentagonal in13.33% of the cases. The mean antero-posterior and transverse diameter of the FM was recorded as 34.00+/2.38 mm and 28.68+/-1.88 mm respectively. The Maximum diameter of antero-posterior and transverse diameter was recorded 39.53mm and 32.14mm respectively. The Minimum diameter of antero-posterior and transverse diameter was recorded 28.72 mm and 23.54 mm respectively. Conclusion: Though the present study has a limitation as the exact age and sexes of skull were not determined, this study may provide an important reference and the measurements may be used as a data for the description of normal morphological variants of FM. The present study will be of useful to the neurosurgeons and is also helpful to the anthropologists and clinical anatomists. KEY WORD: Foramen magnum, Morphometry, Shape, Skull. INTRODUCTION International Journal of Anatomy and Research, Int J Anat Res 2018, Vol 6(2.3):5284-87. ISSN 2321-4287 DOI: https://dx.doi. org/10.16965/ijar.2018. 187 Access this Article online Quick Response code International Journal of Anatomy and Research ISSN (E) 2321-4287 | ISSN (P) 2321-8967 https://www.ijmhr. org/ijar.htm DOI-Prefix: https://dx.doi. org/10.16965/ijar DOI: 10.16965/ijar.2018. 187 *1 Assistant Professor, Department of Anatomy, American International Institute of Medical Sciences, Udaipur, Rajasthan, India. 2 Associate Professor, Department of Anatomy, American International Institute of Medical Sciences, Udaipur, Rajasthan, India. 3 Associate Professor, Department of Anatomy, Pandit Dindayal Upadhyay Medical College Rajkot, Gujarat, India. 4 Dean, GMERS Medical College, Junagadh, Gujarat, India. Received: 17 Mar 2018 Peer Review: 18 Mar 2018 Revised: None Accepted: 08 May 2018 Published (O): 05 Jun2018 Published (P): 05 Jun 2018 Journal Information