Miracle-dz/UniFAR-FTUs huggingface dataset:
FUNGI AND RED-COCKADED WOODPECKER CAVITY TREES

It is widely thought that red heart fungus (Phellinus pini [Thore ex. Fr.]), syn. Fomes pini, must decay the heartwood of living pine trees (Pinus spp.) before Red-cockaded Woodpeckers (Picoides borealis) can excavate a cavity into the tree (Steirly 1957, Ligon 1971). Jackson (1977) reported that 20% of the red-cockaded cavity trees in the shortleaf (P. echinata) and loblolly (P. taeda) pines he sampled with an increment borer did not have visually detectable signs of red heart disease. He suspected, however, that the decay may have been in early stages or completely removed when the cavity was made. P. pini has been the only fungus known to be found in red-cockaded cavity trees. Woodpeckers other than red-cockaded are dependent on trees with decayed heartwood, a condition that softens the heartwood and facilitates nest cavity excavation (Conner et al. 1976). In this instance, oaks (Quercus spp.) and hickories (Carya spp.) were the predominant tree species and the heart rot usually associated with them was Spongipellis pachyodon (Pers.) Kotl and Pouz. The objectives of this study were to examine the internal conditions of red-cockaded cavity trees and determine presence or absence of decay, species of fungi involved and mode of entry of heartwood-decaying fungi into the trees.
Learning to Predict Human Behavior from Video

Author(s): Felsen, Panna | Advisor(s): Malik, Jitendra | Abstract: In recent times, the field of computer vision has made great progress with recognizing and tracking people and their activities in videos. However, for systems designed to interact dynamically with humans, tracking and recognition are insufficient; the ability to predict behavior is requisite. In this thesis, we introduce various general frameworks for predict human behavior at three levels of granularity: events, motion, and dynamics. In Chapter 2, we present a system that is capable of predicting future events. In Chapter 3, we present a system that is capable of personalized prediction of the future motion of multi-agent, adversarial interactions. Finally, in Chapter 4, we present a framework for learning a representation of human dynamics that we can: 1) use to estimate the 3d pose and shape of people moving in videos, and 2) use to hallucinate the motion surrounding a single-frame snapshot. We conclude with several promising future directions for learning to predict human behavior from video.
Efficient Constraint-Based Dynamic Strategies For Generating Counterexamples

Checking safety properties is mandatory in the validation process of critical software. When formal verification tools fail to prove some properties, testing is necessary. Generation of counterexamples violating some properties is therefore an important issue, especially for tricky programs the test cases of which are very difficult to compute. We propose in this paper different constraint based dynamic strategies for generating structural test cases that violate a postcondition of C or JAVA programs. These strategies have been evaluated on standard benchmarks and on real applications. Experiments on a real industrial Flasher Manager controller and on the public available implementation of the Traffic Collision Avoidance System (TCAS) show that our system outperforms state of the art model checking tools and constraint based test generation systems.
Resources for Indian languages

This paper discusses a consortium effort with the design of database for a high-quality corpus, primarily for building text to speech(TTS) synthesis systems for 13 major Indian languages. Importance of language corpora is recognized since long before in many countries. The amount of work in speech domain for Indian languages is comparatively lower than that of other languages. This demands the speech corpus for Indian languages. The corpus presented here is a database of speech audio files and corresponding text transcriptions. Various criteria are addressed while building the database for these languages namely, optimal text selection, speaker selection, pronunciation variation, recording specification, text correction for handling out-of-the-vocabulary words and so on. Furthermore, various characteristics that affect speech synthesis quality like encoding, sampling rate, channel, etc is considered so that the collected data will be of high quality with defined standards. Database and text to speech synthesizers are built for all the 13 languages, namely, Assamese, Bengali, Bodo, Gujarati, Hindi, Kannada, Malayalam, Manipuri, Marathi, Odiya, Rajasthani, Tamil and Telugu.
Changes and clinical significance of liver function and myocardial zymogram in children with rotavirus enteritis

Rotavirus (RV) enteritis is a diarrheal disease highly occurred in children in autumn and winter, and mostly occurred in infants aged from 6 to 24 months. RV is a main pathogen for developing enteritis, and about 40%-60% enteritis in children is caused by RV[1,2]. RV infection can cause systemic organic damage, including gastrointestinal tract, respiratory tract, and other organs, which can induce extraintestinal impairment, and cardiogenic shock or sudden death will occur in a severe condition[3,4]. Some researches demonstrate that RV infection can cause viral myocarditis and liver function damage in children[5,6]. The study is aimed to explore the changes and clinical significance of liver function and myocardial zymogram in children with RV enteritis.
THE INVESTIGATION OF THE SOME PHYSICOCHEMICAL PARAMETERS OF WATER QUALITY AND AQUATIC COLEOPTERA DIVERSITY IN IŞIKLI LAKE ( DENİZLİ )

This study was conducted to determine the physicochemical parameters (pH, temperature, electrical conductivity, salinity and dissolved oxygen) of water quality at Işıklı Lake in Denizli province. Additionally, we determined the effects of these parameters on aquatic Coleoptera diversity by taking water and insect samples every month from this lake between May 2009-September 2009 and April 2010-September 2010. As a result of the study 52 aquatic Coleoptera species were identified in lakes. The study also showed that the monthly fluctuations in the physicochemical parameters and the differences in the mean values are considered to be effective in the distributions of aquatic Coleoptera.
BELARUSIAN LEARNERS OF FARSI : PRONUNCIATION PROBLEMS AND SOLUTIONS

Learning a foreign language with an acceptable pronunciation forms an important part of learning processes. The more unrelated the native language of the learner to the foreign language to be learned, the more difficult the procedure of language learning would be. This paper aims at scrutinizing pronunciation problems Belarusian learners of Farsi (BLF) may face in learning this language. Since Russian and Farsi belong to two different language families, the learners are expected to have serious pronunciation problems due to differences of the two languages in the realms sounds, letters, alphabet, writing system, supra-segmental features, syllable patterns and structures. These domains are proved to be most important sources of errors and difficulties for BLF. Based on his observations and practical evidence, the writer, as a teacher of Farsi to Belarusian university students, identifies, discusses and analyzes all pronunciation problems the students face during learning Farsi. Finally, he proposes feasible solutions to the problems.
ROCZNIKI PSYCHOLOGICZNE/ ANNALS OF PSYCHOLOGY

Artykuł przedstawia prób" empirycznej analizy zwi zku zró nicowania koncepcji siebie z poczuciem to samo ci. Wykorzystano poj"cie zło ono ci Ja Patricii Linville oraz wielowymiarowe uj"cie poczucia to samo ci. Ze wzgl"du na postulowane powi zania tych strukturalnych wła ciwo ci osobowo ci z samoocen , przeanalizowano tak e te relacje. Rezultaty bada# wskazuj na brak zwi zków zło ono ci poj"cia Ja z poczuciem spójno ci, stabilno ci, odr"bno ci, dost"pno ci tre ci to samo ciowych i samoocen . Analiza skupie# ujawniła jednak obecno trzech grup o specyficznych kombinacjach wymiarów to samo ci i zło ono ci Ja i ró nej samoocenie. Przeprowadzono dyskusj" nad psychologicznym znaczeniem tych ró nic.
Estimating trends in monthly maximum and minimum temperatures in GCMs for which these data are not archived

Information on future trends in maximum and minimum temperatures is central to the problem of plant growth modelling. Whilst these variables were available for seven global climate models in the CMIP3 dataset, they were not archived for fourteen. This paper addresses the problem of producing estimated monthly trends for these two variables from monthly trends in other more available variables. We are currently engaged in a project called “Consistent Climate Scenarios” which aims to produce a consistent data source for input into agricultural projects for any location in Australia. It is important that the datasets must be “weather-like” and be internally consistent in terms of variation of variables and crossvariable variation at point scale, and spatially and temporally correlated in a weather-like fashion. The approach is to combine climate change projections from GCMs and historical daily data from the SILO patched point and gridded data sets (http://www.longpaddock.qld.gov.au/silo/). The initial phase of the project involves using trends derived from monthly patterns of change provided by CSIRO and made available from their OzClim 3 TM web site (http://www.csiro.au/ozclim). During the course of this work we needed to incorporate trends from variables which were not available in OzClim. CSIRO also supplied us with pattern-scaled data for a number of additional climate variables including cloud cover (CLT), and precipitable water (PRW). Our approach to estimating the trends in maximum and minimum temperatures (Tasmax and Tasmin respectively) is a multistage one, combining genetic programming tool (the free software tool "Eureqa" from Cornell Creative Machines Lab) to explore possible relationships, with expert knowledge to produce a multiple regression model. Additionally, a simpler method of estimation was applied. Taking the GCMs for which we had data, we computed the ensemble deviation of maximum and minimum temperatures from the ensemble mean at each point and then adjusted the means of the two models of interest using the ensemble deviation. We find that trends in monthly maximum and minimum average temperature can be predicted over Australia at GCM native resolutions using trends in mean temperature, cloud cover, and precipitable water, and that the resulting statistical model explains better than 95% of variance over all available GCMs. The final statistical model derived in our work is, m m m m m m m m m m m m m prw tas P clt tas P clt P prw P tas P T ⋅ + ⋅ + ⋅ + ⋅ + ⋅ = 5 4 3 2 1 , where Tm is either maximum or minimum temperature for each month m, tas m, prw m, and clt m are trends per degree of global warming in mean surface temperature, precipitable water, and cloud cover respectively. The five parameters were derived by multiple linear regression using all grid points over continental Australia, at native grid scale from six of seven GCMs for which we were provided the trends.
Internship Proposal: Enabling clusters with Dynamic Distributed Systems

The availability of wireless communications has drastically increased in recent years and established new applications. Humans, agents, devices, robots, and applications interact together through more and more heterogeneous infrastructures, such as mobile ad hoc networks (MANET), vehicular networks (VANET), (mobile) sensor and actuator networks (SAN), body area networks (BAN), as well as always evolving network infrastructures on the Internet. In such networks, items (users, links, equipments, etc.) may join, leave, or move inside the network at unforeseeable times. The dynamics of such networks, the heterogeneity of devices, usages, and participants, and often the unprecedented scale to consider, make the design of such infrastructures extremely challenging. For a vast majority of them, the dynamics are also unpredictable. Furthermore, designing applications on top of such networks requires to deal with the lack of infrastructure and numerous topological changes. Therefore, it becomes necessary to define and to develop new accurate models capturing the features of the considered objects: users’ mobility, system stability, dynamics of applications, etc. On the top of this, operating systems and applications are required to have self-* attributes, such as self-organized, self-healing, self-configuring, self-managed, self-optimized, etc. Such distributed architectures are sometime gathered under the generic term of Autonomic Computing, referring to self-* properties of distributed systems adapting to unpredictable topological changes.
A Novel Instrument for Real-Time Measurement of Attenuation of Weather Radar Radome Including Its Outer Surface . Part I : The Concept

This paper presents a unique instrument for characterizing the impact of wet radomes in radar systems. The proposed technique enables full radio frequency (RF) characterization of the radome, by evaluating its performance under a variety of conditions, including dirtiness, wetness, ice formation, and varying temperature, and providing a potential solution for future wet radome calibration methods. The reflections generated from the wet radome surface, measured from a high-resolution probe, are combined with an estimation of water absorption as a function of the precipitation rain rate, to calculate the attenuation introduced by the wet radome. This instrument is a cost-effective solution that can be integrated into an existing or new radar system.
Learning to Synthesize Motion Blur Supplement

Because our synthetic dataset contains a validation set, we report performance of our model and its ablations in Table 1. We do not report the performance of our baseline techniques, as their performance on this synthetic data is unlikely to be meaningful when compared to our real test dataset, and also because some of our baselines needed to be run by the respective authors of each paper whom we did not wish to burden by requesting they process 15000 images in addition to our test set. In the table we see that the relative ordering of our model with respect to its ablations is consistent with their ordering in our test-set, though absolute performance is consistently higher.
Energy monitoring and its impact on individual user privacy

Introduction. Resource monitoring holds a very important position within the energy efficient computing paradigm. The underlying idea is to monitor the energy consumption behavior of appliances in different scenarios to develop consumption signatures. The signatures can help to deduce detailed consumption information which can be used to improve energy savings. There are many contemporary works being done in this direction where researchers investigate resource monitoring systems and their application. Additionally, efforts are being made to utilize collected samples of monitored information in useful ways [1]. Though the overall idea is very strong, there are certain research challenges which need to be overcome before turning this vision into reality. One of the most widely discussed among these is the privacy implications of such systems [3] and usability of collected information in a constructive manner. Detection theory through hypothesis testing is a tool that can be used to advance state-ofthe-art in privacy in energy monitoring. Compromising privacy can be thought of as deducing the profile of a user from observed data. In the context of process energy data monitoring, a profile corresponds to selecting one out of a finite set of N possible processes that are ran on a physical machine. Privacy concerns are raised when a malicious entity builds a set of empirical probability mass functions (p.m.f.), one for each process. Each p.m. f. captures the statistics of instantaneously consumed energy of the process. This task can be performed easily offline by taking multiple observations from each process that is running separately on every machine. A privacy breach exists, if, during the time a process runs on a physical machine, the malicious entity takes observations of the energy consumption level. Various factors may inherently limit the amount of observations taken. The question for the entity that seeks to compomise privacy is to identify the process that is running with good accuracy. Virtualization comes into stage to the support of privacy preservation; By appropriately mixing two or more processes (and thus p.m.f’s) on a virtualized machine, the privacy is protected, in the sense that the individual processes are made indistinguishable. This is also one of the core research questions in EuroNF SJRP SPEC where we want to address this interrelation between energy consumption monitoring and their impact on user privacy.
Human experience–inspired path planning for robots

In this article, we present a human experience–inspired path planning algorithm for service robots. In addition to considering the path distance and smoothness, we emphasize the safety of robot navigation. Specifically, we build a speed field in accordance with several human driving experiences, like slowing down or detouring at a narrow aisle, and keeping a safe distance to the obstacles. Based on this speed field, the path curvatures, path distance, and steering speed are all integrated to form an energy function, which can be efficiently solved by the A* algorithm to seek the optimal path by resorting to an admissible heuristic function estimated from the energy function. Moreover, a simple yet effective fast path smoothing algorithm is proposed so as to ease the robots steering. Several examples are presented, demonstrating the effectiveness of our human experience–inspired path planning method.
The 4 th International Conference on Electrical Engineering and Informatics ( ICEEI 2013 ) Reviews on Cybercrime Affecting Portable Devices

The popularity of mobile devices in the market is impressive, but this influx of different products has made it difficult for users to secure their infrastructures from potential data breaches. As the number of exposures and attacks increase, there has been a corresponding rise in security solutions offered by researchers. This article reviews the literature to prevent the cybercrime affecting portable devices especially smartphones running Android OS. Extant researches are analyzed and opportunities for future research are identified. Four research questions have been developed and out of 493 articles retrieved, 33 articles have been selected to be analyzed. From the analysis, we have found that Data leakage resulting from device loss or theft, unintentional disclosure of data and phishing attacks are most common between attackers. With no doubt, security investigators have stressed the grandness of protecting classified personal data residing in Android portable devices. They have suggested to use the permission-based security model and behavior-based detection method for protecting classified information. In result we found that Android OS can handle and apply the integrated protection model but still there are opportunities for us to improve the security of personal data. © 2013 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of the Faculty of Information Science & Technology, Universiti Kebangsaan
TGF b signaling underlies hematopoietic dysfunction and bone marrow failure in Shwachman-Diamond Syndrome

Shwachman-Diamond Syndrome (SDS) is a rare and clinically-heterogeneous bone marrow (BM) failure syndrome caused by mutations in the Shwachman-Bodian-Diamond Syndrome (SBDS) gene. Although SDS was described over 50 years ago, the molecular pathogenesis is poorly understood due, in part, to the rarity and heterogeneity of the affected hematopoietic progenitors. To address this, we used single cell RNA sequencing to profile scant hematopoietic stem and progenitor cells from SDS patients. We generated a single cell map of early lineage commitment and found that SDS hematopoiesis was left-shifted with selective loss of granulocyte-monocyte progenitors. Transcriptional targets of transforming growth factor-beta (TGFb) were dysregulated in SDS hematopoietic stem cells and multipotent progenitors, but not in lineage-committed progenitors. TGFb inhibitors (AVID200 and SD208) increased hematopoietic colony formation of SDS patient BM. Finally, TGFb3 and other TGFb pathway members were elevated in SDS patient blood plasma. These data establish the TGFb pathway as a novel candidate biomarker and therapeutic target in SDS and translate insights from single cell biology into a potential therapy. Concise Communication Hematology
Life Expectancy and Life-Cycle Wages: Evidence from the Cardiovascular Revolution in U.S. States∗

This paper exploits quasi-experimental variation in mortality from cardiovascular diseases across U.S. states to establish a positive causal link between adult life expectancy and average wages per worker. A cohort-specific analysis reveals that wage gains accrue to prime-age workers between 25 and 54 as well as old-age workers above 65. This pattern is consistent with a shift in life-cycle earnings toward a profile that increases more steeply for young ages and that flattens out more slowly at advanced ages. Health improvements, higher educational attainment, and changes in individual behavior constitute potential channels for this shift. JEL-classification: I15, J11, J24, O40
MOSSBAUER STUDY OF IRON COMPOUNDS IN HYPERACCUMULATOR PLANT

PËRMBLEDHJE Hekuri është një nga elementët themelore për bimët. Ne kemi studiuar përqendrimet dhe gjendjet kimike të hekurit në bimën hiperakumulatore Alyssum Murale duke përdorur tëkniken FRX dhe spektroskopinë Mossbauer të 57 Fe. Eksperimentët u kryen me bimë (rrënjë dhe gjethe) që u gjendën në zona minerare të pjesës lindore të Shqipërisë. Nga matjet FRX, vumë re se Alyssum Murale akumulon Ni dhe përqendrimi i tij në gjethe ishtë 7 deri 9 herë më i madh se sa në rrënjë. Spektrat Mossbauer të mostrave të dheut u përshtatën me komponentë paramagnetike të Fe 3+ dhe Fe 2+ dhe një komponent magnetik, ndërsa spektrat Mossbauer të bimëve (rrënjëve dhe gjetheve) u përshtatën vetëm me komponentë paramagnetikë. Analiza e spektrave Mossbauer të rrënjëve dhe gjetheve tregoi praninë e komponimeve të ndryshme të Fe 3+ , që janë identifikuar si ferrihidriti, lepidokrositi dhe Fe-nikotianamina. Në disa mostra ne dalluam një komponim të Fe 2+ në sasi të vogël, me hekurin në vendndodhje oktahedrale. Fjalë kyçe: bimë hiperakumulatore, komponime hekuri, spektroskopia Mossbauer, FRX
In-vivo pilot study on physical absorption enhancement of active skin whitening ingredients by heat and ultrasound

In Q3 of 2011, Philips Research received a brief from the Skin Carecategory of the Philips Consumer Lifestyle sector to explore the feasibility of heat and ultrasound to increase skin uptake of active skin whitening ingredients from cosmetics. Philips Research Asia-Shanghai performed an in-vivo study which aimed to answer two questions:1. Shows heat or ultrasound any efficacy in this context? 2. If an enhancement can be achieved, which technology is more suitable for ahome-use device? This report summarizes the research activities which have been conducted in Shanghai over Q3-Q4 of 2011 to answer thesequestions. Furthermore, mechanisms behind heat- and ultrasound-mediated permeation enhancement are introduced and discussed including mathematical models which can be used to predict permeation behaviourbased on physiochemical properties of a penetrant.