Miracle-dz/UniFAR-FTUs huggingface dataset:
A context-independent situational judgment test to measure prosocial implicit trait policy

ABSTRACT Two studies developed and validated a context-independent situational judgment test (SJT) of prosocial implicit trait policy (ITP). The first study developed a SJT based on critical incidents about the prosocial behavior of physicians, lawyers, community service volunteers, and human factors engineers. In a sample of 396 undergraduates, scores obtained from this SJT were internally consistent and correlated significantly with other trait constructs related to prosocial ITP. In the second study with 134 undergraduates, the SJT was significantly correlated with relevant trait constructs and prosocial performance in role-plays simulating scenarios in which others needed help. These results show that a generic SJT developed from items that describe situations and actions specific to several occupations can predict behavior in situations unlike any that appear in its items.
Stone age cultures of Mayurbhanj District, Orissa

Extensive exploration in the Baripada sadar, Bisoi, Rairangpur and Karanjia Tehsils, spanning two seasons in 1994 and 1995, resulted in the discovery of 4 lower paleolithic sites and 9 Mesolithic sites in the Mayurbhanj district, Orissa. Many of these sites are primary in nature and have preserved habitational deposits. Handaxes and choppers made of quartzite are the main components of the lower palaeolithic industry. In Mesolithic sites, in addition to microlithic artifacts, the most noteworthy feature of the assamblage is the common occurrence of heavy-duty implements, the raw materials selected for these are different from those used for manufacturing microliths. A summary effort is being made by the authors at integrating and interpreting the data recovered from the sites.
Fractal Complex Dimensions, Riemann Hypothesis and Invertibility of the Spectral Operator

A spectral reformulation of the Riemann hypothesis was obtained in (LaMa2) by the second author and H. Maier in terms of an inverse spectral problem for fractal strings. The inverse spectral problem which they studied is related to answering the question "Can one hear the shape of a fractal drum? "and was shown in (LaMa2) to have a positive answer for fractal strings whose dimension is c ∈ (0, 1) −{ 1 } if and only if the Riemann hypothesis is true. Later on, the spectral operator was introduced semi-heuristically by M. L. Lapidus and M. van Frankenhuijsen in their development of the theory of fractal strings and their complex dimensions (La-vF2, La-vF3) as a map that sends the geometry of a fractal string onto its spectrum. In this survey article, we focus on presenting the results obtained by the authors in (HerLa1) about the invertibility (in a suitable sense) of the spectral operator, which turns out to be intimately related to the critical zeroes of the Riemann zeta function. More specifically, given any c ≥ 0, we show that the spectral operator a = ac, now precisely defined as an unbounded normal operator acting in an appropriate weighted Hilbert space Hc, is 'quasi-invertible' (i.e., its truncations are invertible) if and only if the Riemann zeta function ζ = ζ(s )d oes not have any zeroes on the vertical line Re(s )= c. It follows, in particular, that the associated inverse spectral problem has a positive answer for all possible dimensions c ∈ (0, 1), other than the mid-fractal case when c = 1 , if and only if the Riemann hypothesis is true. Therefore, in this latter result from (HerLa1), a spectral reformulation of the Riemann hypothesis is obtained from a rigorous operator theoretic point of view, thereby further extending the earlier work of the second author and H. Maier in their study of the inverse spectral problem.
Investigating children's opinions of games: Fun Toolkit vs. This or That

Over the past decade many new evaluation methods have emerged for evaluating user experience with children, but the results of these studies have tended to be reported in isolation of other techniques. This paper reports on a comparative analysis of 2 user experience evaluations methods with children. A within-subject design was adopted using 20 children aged between 7 and 8. The children played 2 different games on a tablet PCs and their experiences of each were captured using 2 evaluation methods which have been validated with children: the Fun Toolkit and This or That. The results showed that the Fun Toolkit and This or That method yielded similar results and were able to establish a preference for one game over the other. However, there were some inconsistencies between the results of individual tools within the Fun toolkit and some of the constructs being measured in the This or That method. Further research will try to identify any ordering effects within each method and redundancies within the questions.
Approximating Betweenness Centrality in Large Evolving Networks

Betweenness centrality ranks the importance of nodes by their participation in all shortest paths of the network. Therefore computing exact betweenness values is impractical in large networks. For static networks, approximation based on randomly sampled paths has been shown to be significantly faster in practice. However, for dynamic networks, no approximation algorithm for betweenness centrality is known that improves on static recomputation. We address this deficit by proposing two incremental approximation algorithms (for weighted and unweighted connected graphs) which provide a provable guarantee on the absolute approximation error. Processing batches of edge insertions, our algorithms yield significant speedups up to a factor of $10^4$ compared to restarting the approximation. This is enabled by investing memory to store and efficiently update shortest paths. As a building block, we also propose an asymptotically faster algorithm for updating the SSSP problem in unweighted graphs. Our experimental study shows that our algorithms are the first to make in-memory computation of a betweenness ranking practical for million-edge semi-dynamic networks. Moreover, our results show that the accuracy is even better than the theoretical guarantees in terms of absolutes errors and the rank of nodes is well preserved, in particular for those with high betweenness.
Tsunami hazard in the Black Sea and the Azov Sea: a new tsunami catalogue

Abstract. Data on tsunamis occurring in the Black Sea and the Azov Sea from antiquity up to the present were updated, critically evaluated and compiled in the standard format developed since the 90's for the New European Tsunami Catalogue. Twenty nine events were examined but three of them, supposedly occurring in 557 AD, 815 AD and 1341 or 1343, were very likely falsely reported. Most of the remaining 26 events were generated in Crimea, offshore Bulgaria as well as offshore North Anatolia. For each of the 26 events examined, 22 events were classified as reliable ones receiving a score of 3 or 4 on a 4-grade reliability scale. Most of them were caused by earthquakes, such as the key event 544/545 of offshore Varna, but a few others were attributed either to aseismic earth slumps or to unknown causes. The tsunami intensity was estimated using the traditional 6-grade scale and the new 12-grade scale introduced by Papadopoulos and Imamura (2001). From 544/545 up to now, only two reliable events of high intensity K ≥ 7 have been reported, which very roughly indicates that the mean repeat time is ∼ 750 years. Five reliable tsunamis of moderate intensity 4 ≤ K
Evaluation of the Zucker Diabetic Fatty (ZDF) Rat as a Model for Human Disease Based on Urinary Peptidomic Profiles

Representative animal models for diabetes-associated vascular complications are extremely relevant in assessing potential therapeutic drugs. While several rodent models for type 2 diabetes (T2D) are available, their relevance in recapitulating renal and cardiovascular features of diabetes in man is not entirely clear. Here we evaluate at the molecular level the similarity between Zucker diabetic fatty (ZDF) rats, as a model of T2D-associated vascular complications, and human disease by urinary proteome analysis. Urine analysis of ZDF rats at early and late stages of disease compared to age- matched LEAN rats identified 180 peptides as potentially associated with diabetes complications. Overlaps with human chronic kidney disease (CKD) and cardiovascular disease (CVD) biomarkers were observed, corresponding to proteins marking kidney damage (eg albumin, alpha-1 antitrypsin) or related to disease development (collagen). Concordance in regulation of these peptides in rats versus humans was more pronounced in the CVD compared to the CKD panels. In addition, disease-associated predicted protease activities in ZDF rats showed higher similarities to the predicted activities in human CVD. Based on urinary peptidomic analysis, the ZDF rat model displays similarity to human CVD but might not be the most appropriate model to display human CKD on a molecular level.
AppInsight: Mobile App Performance Monitoring in the Wild

The mobile-app marketplace is highly competitive. To maintain and improve the quality of their apps, developers need data about how their app is performing in the wild. The asynchronous, multithreaded nature of mobile apps makes tracing difficult. The difficulties are compounded by the resource limitations inherent in the mobile platform. To address this challenge, we develop AppInsight, a system that instruments mobile-app binaries to automatically identify the critical path in user transactions, across asynchronous-call boundaries. AppInsight is lightweight, it does not require any input from the developer, and it does not require any changes to the OS. We used AppInsight to instrument 30 marketplace apps, and carried out a field trial with 30 users for over 4 months. We report on the characteristics of the critical paths that AppInsight found in this data. We also give real-world examples of how AppInsight helped developers improve the quality of their app.
Intergenerational transmission of childhood conduct problems: a Children of Twins Study.

CONTEXT The familial nature of childhood conduct problems has been well documented, but few genetically informed studies have explicitly explored the processes through which parental conduct problems influence an offspring's behavior problems. OBJECTIVE To delineate the genetic and environmental processes underlying the intergenerational transmission of childhood conduct problems. DESIGN We used hierarchical linear models to analyze data from a Children of Twins Study, a quasiexperimental design, to explore the extent to which genetic factors common to both generations, unmeasured environmental factors that are shared by twins, or measured characteristics of both parents confound the intergenerational association. SETTING Participants were recruited from the community and completed a semistructured diagnostic telephone interview. PARTICIPANTS The research used a high-risk sample of twins, their spouses, and their young adult offspring (n = 2554) from 889 twin families in the Australian Twin Registry, but the analyses used sample weights to produce parameter estimates for the community-based volunteer sample of twins. Main Outcome Measure Number of conduct disorder symptoms. RESULTS The magnitude of the intergenerational transmission was significant for all offspring, though it was stronger for males (effect size [Cohen d] = 0.21; 95% confidence interval, 0.15-0.17) than females (d = 0.09; 95% confidence interval, 0.05-0.14). The use of the Children of Twins design and measured covariates indicated that the intergenerational transmission of conduct problems for male offspring was largely mediated by environmental variables specifically related to parental conduct disorder (d = 0.13; 95% confidence interval, 0.02-0.23). In contrast, the intergenerational transmission of conduct problems was not because of environmentally mediated causal processes for female offspring (d = - 0.09; 95% confidence interval, - 0.20 to 0.03); a common genetic liability accounted for the intergenerational relations. CONCLUSIONS The mechanisms underlying the intergenerational transmission of conduct problems depend on the sex of the offspring. The results are consistent with an environmentally mediated causal role of parental conduct problems on behavior problems in males. Common genetic risk, however, confounds the entire intergenerational transmission in female offspring.
Relation Between Secretory Status of Growth Hormone , Serum Concentration of Insulin-like Growth Factor I , and Insulin-like Growth Factor

Although the decline in sex steroid levels, particularly estradiol, may be largely responsible for age-related bone loss and osteoporotic fractures in older women, the insulin-like growth factor (IGF) system may also play a key role. This study aimed at evaluating the relation between the secretory status of growth hormones (GH), insulin-like growth factor I (IGF-I) and Insulin-like growth factor binding protein 3 (IGFBP3) and bone mineral density (BMD) in postmenopausal women. Materials & Methods: In a descriptive crosssectional study, 150 postmenopausal healthy women were selected from among 1328 patients, referred to Tabriz Sina Hospital for bone densitometry, and divided into three groups according to their bone mineral density (BMD) (normal, osteopenic and osteoporotic). The GH response to provocation by clonidine was assessed in all patients. Results: One hundred and fifty patients with a mean age of 65.6±6.6 years, were enrolled in this study. The impaired GH response to provocation by clonidine was significantly more common in the group with osteoporosis compared to their healthy and osteopenic counterparts (72% vs. 56% and 44%, respectively; p=0.018). Mean levels of serum IGF-I and IGFBP3 were not significantly different in healthy, osteopenic and osteoporotic patients (55.4±20.7 μg/L, 57.5±21.7 μg/L, and 56.7±19.2 μg/L; p=0.880 and 2648.3±786.4 ng/ml, 2374.0±707.2 ng/ml, and 2613.5±1023.6 ng/ml; p=0.217, respectively). There was no strong correlation between the level of serum IGF-I or IGFBP3 and T-Score (r=-0.026, p=0.753 for IGF-1 and r=0.046, p=0.575 for IGFBP3). Conclusion: The results of this study showed that the defective release of GH is more prevalent in postmenopausal women suffering from osteoporosis; such a defect was not observed regarding serums of IGF1 and IGFBP3. Prescription of supplementary doses of synthetic GH might be beneficial in this population.
Spectral Goodness of Fit for Network Models

We introduce a new statistic, 'spectral goodness of fit' (SGOF) to measure how well a network model explains the structure of an observed network. SGOF provides an absolute measure of fit, analogous to the standard R-squared in linear regression. Additionally, as it takes advantage of the properties of the spectrum of the graph Laplacian, it is suitable for comparing network models of diverse functional forms, including both fitted statistical models and algorithmic generative models of networks. After introducing, defining, and providing guidance for interpreting SGOF, we illustrate the properties of the statistic with a number of examples and comparisons to existing techniques. We show that such a spectral approach to assessing model fit fills gaps left by earlier methods and can be widely applied.
Predicting Equity Returns from Securities Data

Our experiments with capital markets data suggest that the domain can be e ectively modeled by classi cation rules induced from available historical data for the purpose of making gainful predictions for equity investments. New classi cation techniques developed at IBM Research, including minimal rule generation (R-MINI) and contextual feature analysis, seem robust enough for consistently extracting useful information from noisy domains such as nancial markets. We will brie y introduce the rationale for our minimal rule generation technique, and the motivation for the use of contextual information in analyzing features. We will then describe our experience from several experiments with the S&P 500 data, illustrating the general methodology, and the results of correlations and simulated managed investment based on classi cation rules generated by R-MINI. We will sketch how the rules for classi cations can be e ectively used for numerical prediction, and eventually to an investment policy. Both the development of robust \minimal" classi cation rule generation, as well as its application to the nancial markets, are part of an
Some blowup results for a nonlinear parabolic equation with a gradient term

Under some conditions, a blowup result is proved for the solution u of: \[\begin{gathered} u_t = \Delta u - \left| {\nabla u} \right|^q + \left| {u} \right|^{p - 1} u,\quad t > 0,\quad x \in \Omega \hfill \\ u(t,x) = 0,\quad t > 0,\quad x \in \Gamma , \hfill \\ u(0,x) = \varphi (x),\quad x \in \Omega . \hfill \\ \end{gathered} \] The associated elliptic problem is also studied.
The Protective Role of School Adjustment Between Risky Neighborhood Environment and Adolescent Drinking and Smoking

Objective: To prevent adolescent drinking and smoking, this study proposed a strategy based on the ecological perspective. Methods: The study applied multilevel moderated logistic regression analysis on nationally representative individual-level (2,046 9th grade adolescents) and neighborhood-level (92 geographic areas) data. Results: There was a positive association between risky neighborhood environments (e.g., rate of smoking, drinking, and presence of saloon/bars accommodation) and rates of adolescent drinking and smoking. Furthermore, the interplay between risky neighborhood environments and school adjustment pointed to a possible protective effect of a high level of school adjustment in predicting smoking and drinking among adolescents. Conclusion: Findings highlighted the importance of considering multiple neighborhood social contexts surrounding adolescents to understand their risky behavior. Furthermore, positive intervention strategies that focus on adolescents` positive development within the school domain may act to protect adolescents from harmful neighborhood environments.
A Linguistically Constrained Model of Short-Term Memory for Nonwords ☆

Abstract Errors in the repetition and serial recall of nonwords indicate that structural properties of the syllable are represented in short-term memory. We develop a connectionist model of short-term memory for such unfamiliar phonological sequences, based on insights from existing models of speech production and short-term memory. The results of simulations of experiments involving nonword recall and repetition are presented, and the mechanisms which produce the common error types are discussed. We also show how the proposed model can be extended to develop and make use of long-term representations of phonological forms, and how a global reduction in short-term memory capacity (such as is commonly observed in developmental dyslexia, and acquired disorders of output phonology) could differentially affect performance on tasks involving familiar and unfamiliar materials.
A 90nm CMOS bio-potential signal readout front-end with improved powerline interference rejection

This paper describes a 90nm CMOS low-noise low-power biopotential signal readout front-end (RFE). The front-stage instrumentation amplifier (IA) features a chopper; an AC-coupler and a novel chopper notch filter for minimizing the dc-offset; transistors' flicker noise and 50Hz powerline interference concurrently. A noise-aware transistor selection (thin- and thick-oxide) in the IA enables a flexible tradeoff between noise and input impedance performances. The 2nd stage is a spike filter clocked by a parallel use of two non-overlapping clock generators, effectively tracking and suppressing the chopper spikes. The last stage is a gain-bandwidth-controllable amplifier for boosting the gain and alleviating different bio-potential signal measurements through simple digital controls. Simulation results showed that the RFE is capable of tolerating a differential electrode offset up to ±50mV, while achieving 140dB CMRR and 51.4nV/√Hz inputreferred noise density. The notch at 50Hz achieves 41dB rejection. The entire RFE consumes 16.55 to 35. 5µA at 3V.
Limitations of Experiments in Education Research

Research based on randomized experiments (along with high-quality quasi-experiments) has gained traction in education circles in recent years. There is little doubt this has been driven in large part by the shift in research funding strategy by the Department of Education's Institute of Education Sciences under Grover Whitehurst's lead, described in more detail in his article in this issue.
Accurate Real-time Map Matching for Challenging Environments

We present the SnapNet system, which provides accurate real-time map matching for cellular-based trajectory traces. Such traces are characterized by input locations that are far from the actual road segment, errors on the order of kilometers, back-and-forth transitions, and highly sparse input data. SnapNet applies a series of filters to handle the noisy locations and an interpolation stage to address the data sparseness. At the core of SnapNet is a novel incremental HMM algorithm that combines digital map hints in the estimation process and a number of heuristics to reduce the noise and provide real-time estimations. Evaluation of SnapNet using actual traces from different cities covering more than 400 km shows that it can achieve a precision and recall of more than 90% under noisy coarse-grained input location estimates. This maps to over 97% and 34% enhancement in precision and recall, respectively, when compared to the traditional HMM map-matching algorithms. Moreover, SnapNet has a latency of 0.58 ms per location estimate.
Sparse Distributed Learning Based on Diffusion Adaptation

This article proposes diffusion LMS strategies for distributed estimation over adaptive networks that are able to exploit sparsity in the underlying system model. The approach relies on convex regularization, common in compressive sensing, to enhance the detection of sparsity via a diffusive process over the network. The resulting algorithms endow networks with learning abilities and allow them to learn the sparse structure from the incoming data in real-time, and also to track variations in the sparsity of the model. We provide convergence and mean-square performance analysis of the proposed method and show under what conditions it outperforms the unregularized diffusion version. We also show how to adaptively select the regularization parameter. Simulation results illustrate the advantage of the proposed filters for sparse data recovery.