Miracle-dz/UniFAR-FTUs huggingface dataset:
Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901–2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011–2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data.
A Systematic Review of Research on Pet Ownership and Animal Interactions among Older Adults

ABSTRACT Research on the impact of companion animals in the lives of older adults is considered from two perspectives: pet ownership and in animal-assisted interventions (AAI). This paper first presents a discussion of potential theoretical explanations of the impact of animals on human health and wellbeing among older adults, and then provides a systematic review and evaluation of existing research on the topics of human–animal interaction (HAI) and physical health and exercise, depression and anxiety, and loneliness and social functioning. Each of the studies in this review (n = 145) are rated according to modified Oxford Center for Evidence Based Medicine (OCEBM) levels and the role of theory, in conceptualizing the study or interpreting outcomes, is discussed. The quality of evidence for each topical area of HAI and aging research is summarized, and recommendations are made for future research directions that will increase our knowledge of the relationship between HAI and health outcomes for older adults in different settings.
DESIGN AND IMPLEMENTATION OF A RELIABLE RISK ASSESSMENT TECHNIQUE FOR SOFTWARE PROJECTS

DESIGN AND IMPLEMENTATION OF A RELIABLE RISK ASSESSMENT TECHNIQUE FOR SOFTWARE PROJECTS Discovering defects is one of the main struggles of software development process. As the size of the software grows, it gets more expensive to accomplish the task of preserving the quality and the reliability of the software. Such software projects need more sophisticated testing and evaluation procedures. Software metrics do supply considerable information about the quality of the code being generated. A detailed analysis of metric data gathered from a software project both gives clues about the error generating potentials of specific code segments, and helps possible errors to come out as well. The aim of this research is to establish a technique for identifying software defects using machine learning methods. The experiments in this research are done with the software metric data repository at NASA IV & V Facility Metrics Data Program. The repository at NASA IV & V Facility MDP contains software metric data and error data at the function/method level. Throughout the tests of our model, the data set is normalized and cleaned against correlated and irrelevant values initially, and then, machine learning techniques are applied for error prediction. Our learning process incorporates k-nearest neighborhood, k-means, artificial neural networks and decision tree approaches. From the results of our experiments, we are able to conclude that the proposed technique brings out successful results in terms of defect prediction. Accordingly, the problem of predicting the magnitude of the impacts that the defects cause is divided into two subproblems: predicting whether there is a defect and then predicting its magnitude value. So improving the performance of the first prediction results in much better outcomes, since the second type of predictions are already successful using machine learning techniques.
The anti-tumor role of NK cells in vivo pre-activated and re-stimulated by interleukins in acute lymphoblastic leukemia

Although natural killer cells (NK cells) were traditionally classified as members of the innate immune system, NK cells have recently been found also to be an important player in the adaptive immune systems. In this context, in vitro activation of NK cells by cytokines leads to generation of NK cells with memory-like properties characterized by increased interferon-γ (IFNγ) production. However, it remains to be defined whether these memory-like NK cells exist in vivo after cytokine activation. Furthermore, it is also unclear whether such memory-like NK cells induced in vivo by cytokines could have effective anti-leukemia response. To address these issues, we used an in vivo pre-activation and re-stimulation system that was able to produce NK cells with increased IFNγ secretion. It was found that after in vivo pre-activation and re-stimulation with interleukins (ILs), NK cells retained a state to produce increased amount of IFNγ. Of note, whereas this intrinsic capacity of enhanced IFNγ production after in vivo IL pre-activation and re-stimulation could be transferred to the next generation of NK cells and was associated with prolonged survival of the mice with acute lymphoid leukemia. Moreover, the anti-leukemia activity of these memory-like NK cells was associated with IFNγ production and up-regulation of NK cells activation receptor-NK Group 2 member D (NKG2D). Together, these findings argue strongly that in vivo IL pre-activation and re-stimulation is capable to induce memory-like NK cells as observed previously in vitro, which are effective against acute lymphoblastic leukemia, likely via NKG2D-dependent IFNγ production, in intact animals.
PERBANDINGAN PERILAKU MENGEMUDI BERISIKO ANTARA PENGEMUDI MOBIL DAN PENGENDARA SEPEDA MOTOR DAN KAITANNYA DENGAN FAKTOR-FAKTOR KEPRIBADIAN

Abstract The first aim of the study was to examine the difference of behavioral pattern in risky driving between car drivers and motorcycle riders. The second aim was to examine if the risky driving behavior could be predicted by some personality factors (ie. sensation seeking and locus of control). A sample of car drivers (N = 85) and motorcycle riders (N = 136) completed series of questionnaires including questions based on the traffic locus of control (TLoC) scale as well as questions about their risky driving behaviour and sensation seeking tendency. The results showed that there’s no significant difference between drivers and riders in overall risky driving behavior. Furthermore, internal locus of control and sensation seeking could be used to predict drivers' risky behaviour on road, while external locus of control was found uncorrelated to risky driving behavior. Keywords : risky driving behavior, sensation seeking, traffic locus of control Abstrak Tujuan pertama dari penelitian ini adalah menguji perbedaan pola perilaku mengemudi berisiko antara pengemudi mobil dan pengendara sepeda motor. Kedua, studi ini bertujuan untuk menguji apakah perilaku mengemudi berisiko dapat diprediksi oleh faktor-faktor kepribadian (dalam hal ini adalah sensation seeking dan locus of control ). Sebanyak 85 pengemudi mobil dan 136 pengendara sepeda motor mengisi serangkaian kuesioner yang mencakup skala traffic locus of control (TLoC), skala sensation seeking , dan perilaku mengemudi berisiko. Hasil penelitian menunjukkan bahwa tidak terdapat perbedaan yang signifikan antara pengemudi mobil dan pengendara sepeda motor dalam perilaku mengemudi berisiko secara keseluruhan. Terkait dengan peran faktor kepribadian, locus of control internal dan sensation seeking ditemukan dapat memprediksi perilaku berisiko di jalan, sedangkan locus of control eksternal tidak ditemukan berkorelasi dengan perilaku mengemudi berisiko. Kata-kata kunci : perilaku mengemudi berisiko, sensation seeking , traffic locus of control
Crumbling morals? An experimental study on how a social framing can affect embezzlement

With data from a laboratory experiment we show that the interpersonal experience can either encourage or reduce subsequent immoral decision-making; in this case the immoral decision to engage in embezzlement. In the experiment, subjects first received initial endowments, either as a share from a previous dictator (social framing treatment) or by random determination (neutral framing treatment). Next, subjects could increase their payoff by embezzling, i.e. taking away part of a donation that they are entrusted with, before forwarding the rest. We find that after receiving a less-than-half share in the social framing treatment, in comparison to receiving an equally large amount in the neutral framing treatment, subjects are significantly more likely to embezzle. Thus, depending on the height of endowment, the social framing encourages forfeiting moral behavior. We argue that this effect is driven by self-deception: observing the dictator's decision to share less than half facilitates excusing one's own immoral choice. We conclude that socially framing a moral decision situation, even though this may remind individuals of what is socially acceptable, does not have an unanimously beneficial effect on the moral decision to embezzle.
Magnetoacoustic wave propagation in off-limb polar regions

Aims. To find evidence of magnetoacoustic waves in off-limb polar regions. Methods. Using temporal series data from the Coronal Diagnostic Spectrometer (CDS) on SOHO, we study oscillations found in radiant flux and velocity measurements from transition region and coronal spectral lines. We use Fourier techniques to measure phase delays between flux (“intensity”) oscillations and between velocity oscillations of different transition region-corona and corona-corona line pairs. We also measure the phase delays between flux and velocity oscillations (I − V). Results. The phase delays measured between different line pairs, when plotted over a –180 ◦ to +180 ◦ range, line up along diagonal lines corresponding to measurable and fixed time delays. The slopes of these diagonal lines suggest the outward propagation of waves. Using the measured time delays, we estimate propagation speeds for the different line pairs that indicate that the waves producing the observed phase delays are magnetoacoustic waves propagating at speeds close to the sound speed. In addition, we find that the phases occur at fixed integer frequencies of f / 4( 90 ◦ )a nd 3f /16 (67.5 ◦ ), instead of the expected interval of f (360 ◦ ), indicating that a “Doppler effect” is acting on the waves. Conclusions. From I − V measurements, we find evidence for fast magnetoacoustic waves to be predominantly present at coronal temperatures, while at transition region temperatures slow magnetoacoustic waves are more common. We find strong evidence for outwardly propagating slow magnetoacostic waves in off-limb polar regions and an indication that these propagating waves are influenced by some form of resonant cavity through which they pass.
The Persistence of In#ation in the United States

An adjustable support means including a pair of cooperating members. A first member has a tray type device and a horizontal arm including locking means and a vertical arm with a foam pad. A second member has a pair of slotlike extensions on a horizontal arm which engages the sides of the horizontal arm of the first member and coacts with the locking means. The second member also has a vertical member with a foam pad to coat with the first vertical arm to lock on a supporting structure.
FPGA-Based Parallel Hardware Architecture for Real-Time Image Classification

This paper proposes a parallel hardware architecture for real-time image classification based on scale-invariant feature transform (SIFT), bag of features (BoFs), and support vector machine (SVM) algorithms. The proposed architecture exploits different forms of parallelism in these algorithms in order to accelerate their execution to achieve real-time performance. Different techniques have been used to parallelize the execution and reduce the hardware resource utilization of the computationally intensive steps in these algorithms. The architecture takes a 640 × 480 pixel image as an input and classifies it based on its content within 33 ms. A prototype of the proposed architecture is implemented on an FPGA platform and evaluated using two benchmark datasets: 1) Caltech-256 and 2) the Belgium Traffic Sign datasets. The architecture is able to detect up to 1270 SIFT features per frame with an increment of 380 extra features from the best recent implementation. We were able to speedup the feature extraction algorithm when compared to an equivalent software implementation by 54× and for classification algorithm by 6×, while maintaining the difference in classification accuracy within 3%. The hardware resources utilized by our architecture were also less than those used by other existing solutions.
Physicochemical Characteristics of Bone Substitutes Used in Oral Surgery in Comparison to Autogenous Bone

Bone substitutes used in oral surgery include allografts, xenografts, and synthetic materials that are frequently used to compensate bone loss or to reinforce repaired bone, but little is currently known about their physicochemical characteristics. The aim of this study was to evaluate a number of physical and chemical properties in a variety of granulated mineral-based biomaterials used in dentistry and to compare them with those of autogenous bone. Autogenous bone and eight commercial biomaterials of human, bovine, and synthetic origins were studied by high-resolution X-ray diffraction, atomic absorption spectrometry, and laser diffraction to determine their chemical composition, calcium release concentration, crystallinity, and granulation size. The highest calcium release concentration was 24. 94 mg/g for Puros and the lowest one was 2.83 mg/g for Ingenios β-TCP compared to 20.15 mg/g for natural bone. The range of particles sizes, in terms of median size D50, varied between 1.32 μm for BioOss and 902.41 μm for OsteoSponge, compared to 282.1 μm for natural bone. All samples displayed a similar hexagonal shape as bone, except Ingenios β-TCP, Macrobone, and OsteoSponge, which showed rhomboid and triclinic shapes, respectively. Commercial bone substitutes significantly differ in terms of calcium concentration, particle size, and crystallinity, which may affect their in vivo performance.
Energy-Saving Service Scheduling for Low-End Cyber-Physical Systems

Energy consumption and timely requirements are two key factors affecting the performance of mission-critical cyber-physical systems. Little work deals with scheduling a set of time-sensitive services in a finite time interval. We consider a server serving N users in time interval [0, T]. Each user demands its service to be completed in a strict deadline. Based on convex power-speed relationship, a lazy schedule policy is designed to minimize energy expenditure of N mission-critical services without violating temporal constraints. Simulations show its significant energy efficiency comparing to a non-lazy schedule.
Parameterization of Quasigeostrophic Eddies in Primitive Equation Ocean Models.

A parameterization of mesoscale eddy fluxes in the ocean should be consistent with the fact that the ocean interior is nearly adiabatic. Gent and McWilliams have described a framework in which this can be approximated in z-coordinate primitive equation models by incorporating the effects of eddies on the buoyancy field through an eddy-induced velocity. It is also natural to base a parameterization on the simple picture of the mixing of potential vorticity in the interior and the mixing of buoyancy at the surface. The authors discuss the various constraints imposed by these two requirements and attempt to clarify the appropriate boundary conditions on the eddy-induced velocities at the surface. Quasigeostrophic theory is used as a guide to the simplest way of satisfying these constraints.
Process Evaluation of Preventing Violent Extremism Programmes for Young People

The original Prevent Strategy, launched by the previous Labour government in 2007, aimed to stop radicalisation, reduce support for terrorism and violent extremism and discourage people from becoming terrorists. The strategy had five central objectives, which were to:  challenge violent extremist ideology and support mainstream voices  disrupt those who promote violent extremism and support the institutions where they are active  support individuals who are being targeted and recruited to the cause of violent extremism1  increase the resilience of communities to violent extremism  address the grievances which ideologues are exploiting. I n 2008, under the original Prevent Strategy, the Youth Justice Board (YJB) secured resources from the Office of Security and Counter Terrorism (OSCT) at the Home Office to fund the development of programmes within youth offending teams (YOTs) and the secure estate to prevent at-risk young people2 (primarily young Muslims) from becoming involved in Islamic radicalisation and violent extremism.3 The money was directed towards YOTs located in areas which intelligence suggested were at the highest risk of violent extremism. For the most part, the projects were given responsibility for designing their own interventions within the parameters of the 2007 Prevent objectives and with the OSCT exercising high-level oversight. The aims of this evaluation, which was commissioned4 by the YJB, were to:  collate and assess the existing evidence relating to preventing violent extremism (PVE)  describe and evaluate the implementation of the funded PVE programmes within the youth justice system 1 Later changed to “support individuals who are vulnerable to recruitment or who have already been recruited by violent extremists” (Home Office, 2009). 2 ‘At-risk young people’ were defined by both the YOT age range (from 10 to 18 years old) and by more pragmatic concerns at the individual project level. Therefore, it was not unusual for the project staff to extend their programme provision to older youths where there was a perception of a persistent vulnerability and risk, or to make allowances for natural peer groups. 3 ‘Radicalisation’ can be defined as the move towards active support for violent extremism, and, as such, it is a process of change which is downstream of, and prior to, violent extremism, although importantly it does not necessitate it. Therefore, a radicalised individual may not become involved in any violent action (and indeed could be opposed in principle to such action). 4 The research was commissioned to run from February 2009 to February 2011. 6  identify emerging good and promising practice by relating the findings of the process evaluation to the evidence identified in the literature review.
The economics of student loan borrowing and repayment

Reports in the popular press and policymakers? concerns about student loans have greatly intensified in recent years because of rising student loan balances and defaults. Even greater cause for concern arose as student loans outstanding passed credit card debt to become the single largest nonmortgage household debt in 2012. Worries about the risk of massive default have even prompted a comparison with the subprime mortgage crisis
Disagreement and the Stock Market

A large catalog of variables with no apparent connection to risk has been shown to forecast stock returns, both in the time series and the cross-section. For instance, we see medium-term momentum and post-earnings drift in returnsâ€”the tendency for stocks that have had unusually high past returns or good earnings news to continue to deliver relatively strong returns over the subsequent six to twelve months (and vice-versa for stocks with low past returns or bad earnings news); we also see longer-run fundamental reversionâ€”the tendency for â€œglamourâ€ stocks with high ratios of market value to earnings, cashflows, or book value to deliver weak returns over the subsequent several years (and vice-versa for â€œvalueâ€ stocks with low ratios of market value to fundamentals). To explain these patterns of predictability in stock returns, we advocate a particular class of heterogeneous-agent models that we call â€œdisagreement models. â€ Disagreement models may incorporate work on gradual information flow, limited attention, and heterogeneous priors, but all highlight the importance of differences in the beliefs of investors. Disagreement models hold the promise of delivering a comprehensive joint account of stock prices and trading volumeâ€”and some of the most interesting empirical patterns in the stock market are linked to volume.
Face Recognition and Privacy in the Age of Augmented Reality

We investigate the feasibility of combining publicly available Web 2.0 data with off-the-shelf face recognition software for the purpose of large-scale, automated individual re-identification. Two experiments illustrate the ability of identifying strangers online (on a dating site where individuals protect their identities by using pseudonyms) and offline (in a public space), based on photos made publicly available on a social network site. A third proof-of-concept experiment illustrates the ability of inferring strangers' personal or sensitive information (their interests and Social Security numbers) from their faces, by combining face recognition, data mining algorithms, and statistical re-identification techniques. The results highlight the implications of the convergence of face recognition technology and increasing online self-disclosure, and the emergence of "personally predictable'' information, or PPI. They raise questions about the future of privacy in an "augmented'' reality world in which online and offline data will seamlessly blend.
Faculteit Economie En Bedrijfskunde Tweekerkenstraat 2 B-9000 Gent Mining Ideas from Textual Information Mining Ideas from Textual Information

This approach introduces idea mining as process of extracting new and useful ideas from unstructured text. We use an idea definition from technique philosophy and we focus on ideas that can be used to solve technological problems. The rationale for the idea mining approach is taken over from psychology and cognitive science and follows how persons create ideas. To realize the processing, we use methods from text mining and text classification (tokenization, term filtering methods, Euclidean distance measure etc.) and combine them with a new heuristic measure for mining ideas. As a result, the idea mining approach extracts automatically new and useful ideas from a user given text. We present these problem solution ideas in a comprehensible way to support users in problem solving. This approach is evaluated with patent data and it is realized as a web-based application, named 'Technological Idea Miner' that can be used for further testing and evaluation.