Miracle-dz/UniFAR-FTUs huggingface dataset:
Variable X-Ray Absorption in the Seyfert 2 Galaxy Markarian 348

We present Rossi X-Ray Timing Explorer monitoring observations of the Seyfert 2 galaxy Mrk 348 spanning a 6 month period. The time-averaged spectrum in the 3-20 keV band shows many features characteristic of a Compton-thin Seyfert 2 galaxy, namely, a hard underlying power-law continuum (Γ ≈ 1.8) with heavy soft X-ray absorption (NH ~ 1023 cm-2) plus measurable iron Kα emission (equivalent width ~100 eV) and, at high energy, evidence for a reflection component (R ≲ 1). During the first half of the monitoring period, the X-ray continuum flux from Mrk 348 remained relatively steady. However, this was followed by a significant brightening of the source (by roughly a factor of 4) with the fastest change corresponding to a doubling of its X-ray flux on a timescale of about 20 days. The flux increase was accompanied by a marked softening of the X-ray spectrum most likely attributable to a factor of ~3 decline in the intrinsic line-of-sight column density. In contrast, the iron Kα line and the reflection components showed no evidence of variability. These observations suggest a scenario in which the central X-ray source is surrounded by a patchy distribution of absorbing material located within about a light-week of the nucleus of Mrk 348. The random movement of individual clouds within the absorbing screen, across our line of sight, produces substantial temporal variations in the measured column density on timescales of weeks to months and gives rise to the observed X-ray spectral variability. However, as viewed from the nucleus, the global coverage and typical thickness of the cloud layer remains relatively constant.
IT Design for Sustaining Virtual Communities: an Identity-based Approach

Title of Dissertation: IT DESIGN FOR SUSTAINING VIRTUAL COMMUNITIES: AN IDENTITY-BASED APPROACH Meng Ma, Ph.D., 2005 Dissertation Directed By: Professor Ritu Agarwal and Professor Hank Lucas, Decision of Information Technologies Department A variety of information technology (IT) artifacts, such as those supporting reputation management and digital archives of past interactions, are commonly deployed to support virtual communities. Despite the ubiquity of these artifacts, research on the impact of various IT-based features on virtual community communication is still limited. Without such research, the mechanisms through which information technologies influence community success are not well understood, limiting the design of community infrastructures that can enhance interaction in the community and minimize dysfunction. This dissertation proposes that identity management is a critical imperative in virtual communities and concerns related to communication of identity serve to shape an individual’s interactions and perceptions in the community. Sensitivity to this perspective can help in drawing design guidelines for the IT infrastructure supporting the community. Drawing upon the social psychology literature, I propose an identity-based view to understand how the use of IT-based features in virtual communities can improve community sustainability. Specifically, identity consonance, defined as the perceived fit between a focal person’s belief of his or her identity and the recognition and verification of this identity by other community members, is proposed as a core construct that mediates the relationship between the use of community IT artifacts and member satisfaction and knowledge contribution. To test the theoretical model, I surveyed two online communities: Quitnet.com and myIS.com. The former is an online community for people who wish to quit smoking, and the latter is a site for Lexus IS300 sport sedan enthusiasts. The results from surveys support the positive effects of community IT artifacts on identity consonance. The empirical study also finds that a high level of identity consonance is linked to member satisfaction and knowledge contribution. This dissertation offers a fresh perspective on virtual communities and suggests important implications for the design of the supporting IT infrastructure. IT DESIGN FOR SUSTAINING VIRTUAL COMMUNITIES: AN IDENTITYBASED APPROACH
The Effect of Edge Definition of Complex Networks on Protein Structure Identification

The main objective of this study is to explore the contribution of complex network together with its different definitions of vertexes and edges to describe the structure of proteins. Protein folds into a specific conformation for its function depending on interactions between residues. Consequently, in many studies, a protein structure was treated as a complex system comprised of individual components residues, and edges were interactions between residues. What is the proper time for representing a protein structure as a network? To confirm the effect of different definitions of vertexes and edges in constructing the amino acid interaction networks, protein domains and the structural unit of proteins were described using this method. The identification performance of 2847 proteins with domain/domains proved that the structure of proteins was described well when R Cα was around 5.0–7.5 Å, and the optimal cutoff value for constructing the protein structure networks was 5.0 Å (Cα-Cα distances) while the ideal community division method was community structure detection based on edge betweenness in this study.
Teratogenic Potential of Antiepileptic Drugs in the Zebrafish Model

The zebrafish model is an attractive candidate for screening of developmental toxicity during early drug development. Antiepileptic drugs (AEDs) arouse concern for the risk of teratogenicity, but the data are limited. In this study, we evaluated the teratogenic potential of seven AEDs (carbamazepine (CBZ), ethosuximide (ETX), valproic acid (VPN), lamotrigine (LMT), lacosamide (LCM), levetiracetam (LVT), and topiramate (TPM)) in the zebrafish model. Zebrafish embryos were exposed to AEDs from initiation of gastrula (5.25 hours post-fertilization (hpf)) to termination of hatching (72 hpf) which mimic the mammalian teratogenic experimental design. The lethality and teratogenic index (TI) of AEDs were determined and the TI values of each drug were compared with the US FDA human pregnancy categories. Zebrafish model was useful screening model for teratogenic potential of antiepilepsy drugs and was in concordance with in vivo mammalian data and human clinical data.
Archaeal MCM Proteins as an Analog for the Eukaryotic Mcm2–7 Helicase to Reveal Essential Features of Structure and Function

In eukaryotes, the replicative helicase is the large multisubunit CMG complex consisting of the Mcm2–7 hexameric ring, Cdc45, and the tetrameric GINS complex. The Mcm2–7 ring assembles from six different, related proteins and forms the core of this complex. In archaea, a homologous MCM hexameric ring functions as the replicative helicase at the replication fork. Archaeal MCM proteins form thermostable homohexamers, facilitating their use as models of the eukaryotic Mcm2–7 helicase. Here we review archaeal MCM helicase structure and function and how the archaeal findings relate to the eukaryotic Mcm2–7 ring.
Chaotic and quasiperiodic Motions of Three Planar charged Particles

We study two dynamical systems for the motion of three planar charged particles with charges nj ∈ {±1}, j = 1, 2, 3. Both dynamical systems are parametric with a parameter α ∈ [0, 1] and have the same nonlinear terms. As α = 0, 1, the dynamical systems have no chaos. However, one dynamical system may create chaos as α varies from zero to one. This may provide an example to show that the homotopy deformation of dynamical systems cannot preserve the long-time dynamics even though the dynamical systems have the same nonlinear terms.
Iron-Folic Acid Supplementation During Pregnancy Reduces the Risk of Stunting in Children Less Than 2 Years of Age: A Retrospective Cohort Study from Nepal

The aim of the study was to investigate the effect of antenatal iron-folic acid (IFA) supplementation on child stunting in Nepalese children age <2 years. A retrospective cohort study design was used, in which a pooled cohort of 5235 most recent live births 2 years prior to interview from three Nepal Demographic and Health Surveys (2001, 2006 and 2011) was analysed. The primary outcome was stunting in children age <2 years. The main exposure variable was antenatal IFA supplementation. Multivariate Poisson regression analysis was performed. In our sample, 31% and 10% of Nepalese children age <2 years were stunted and severely stunted, respectively. The adjusted relative risk of being stunted was 14% lower in children whose mothers used IFA supplements compared to those whose mothers did not use (aRR = 0.86, 95% CI = 0.77–0.97). Additionally, the adjusted relative risk of being stunted was significantly reduced by 23% when antenatal IFA supplementation was started ≤6 months with ≥90 IFA supplements used during pregnancy (aRR = 0.77, 95% CI = 0.64–0.92). Antenatal IFA supplementation significantly reduced the risk of stunting in Nepalese children age <2 years. The greatest impact on the risk reduction of child stunting was when IFA supplements were started ≤6 months with ≥90 supplements were used.
Augmented Lagrangian and Alternating Direction Methods for Convex Optimization: A Tutorial and Some Illustrative Computational Results

The alternating direction of multipliers (ADMM) is a form of augmented Lagrangian algorithm that has experienced a renaissance in recent years due to its applicability to optimization problems arising from “big data” and image processing applications, and the relative ease with which it may be implemented in parallel and distributed computational environments. This chapter aims to provide an accessible introduction to the analytical underpinnings of the method, which are often obscured in treatments that do not assume knowledge of convex and set-valued analysis. In particular, it is tempting to view the method as an approximate version of the classical augmented Lagrangian algorithm, using one pass of block coordinate minimization to approximately minimize the augmented Lagrangian at each iteration. This chapter, assuming as little prior knowledge of convex analysis as possible, shows that the actual convergence mechanism of the algorithm is quite different, and then underscores this observations with some new computational results in which we compare the ADMM to algorithms that do indeed work by approximately minimizing the augmented Lagrangian. Acknowledgements: This material is based in part upon work supported by the National Science Foundation under Grant CCF-1115638. The author also thanks his student Wang Yao for his work on the computational experiments.Please insert the acknowledgement here.
A Formal Approach for Proof Constructions in Cryptography

— In this article we explore the application of a formal proof system to veriﬁcation problems in cryptography. Cryptographic properties concerning correctness or security of some cryptographic algorithms are of great interest. Beside some basic lemmata, we explore an implementation of a complex function that is used in cryptography. More precisely, we describe formal properties of this implementation that we computer prove. We describe formalized probability distributions ( σ -algebras, probability spaces and conditional probabilities). These are given in the formal language of the formal proof system Isabelle/HOL. Moreover, we computer prove Bayes’ Formula. Besides, we describe an application of the presented formalized probability distributions to cryptography. Furthermore, this article shows that computer proofs of complex cryptographic functions are possible by presenting an implementation of the Miller-Rabin primality test that admits formal veriﬁcation. Our achievements are a step towards computer veriﬁcation of cryptographic primitives. They describe a basis for computer veriﬁcation in cryptography. Computer veriﬁcation can be applied to further problems in cryptographic research, if the corresponding basic mathematical knowledge is available in a database.
Robust automatic speech recognition by the application of a temporal-correlation-based recurrent multilayer neural network to the mel-based cepstral coefficients

In this paper, the problem of robust speech recognition has been considered. Our approach is based on the noise reduction of the parameters that we use for recognition, that is, the Mel-based cepstral coefficients. A Temporal-Correlation-Based Recurrent Multilayer Neural Network (TCRMNN) for noise reduction in the cepstral domain is used in order to get less-variant parameters to be useful for robust recognition in noisy environments. Experiments show that the use of the enhanced parameters using such an approach increases the recognition rate of the continuous speech recognition (CSR) process. The HTK Hidden Markov Model Toolkit was used throughout. Experiments were done on a noisy version of the TIMIT database. With such a pre-processing noise reduction technique in the front-end of the HTK-based continuous speech recognition system (CSR) system, improvements in the recognition accuracy of about 17.77% and 18.58% using single mixture monophones and triphones, respectively, have been obtained at a moderate SNR of 20 dB.
Concrete and other neo-Piagetian forms of reasoning in the novice programmer

This paper brings together a number of empirical research results on novice programmers, using a neo-Piagetian theoretical framework. While there already exists literature connecting programming with classical Piagetian theory, in this paper we apply neo-Piagetian theory. Using that neo-Piagetian perspective, we offer an explanation as to why attempts to predict ability for programming via classical Piagetian tests have yielded mixed results. We offer a neo-Piagetian explanation of some of the previously puzzling observations about novice programmers, such as why many of them make little use of diagrams, and why they often manifest a non-systematic approach to writing programs. We also develop the relatively unexplored relationship between concrete operational reasoning and programming, by exploring concepts such as conservation and reversibility.
Fusion of Face and Fingerprint for Robust Personal Verification System

 Abstract—Personal verification system that uses a single biometric trait often faces numerous limitations such as noisy sensor data, non-universality, non-distinctiveness and spoof attack. These limitations can be overcome by multimodal biometric systems that consolidate the evidence presented by multiple biometric sources and typically has better recognition performance compared to systems based on a single biometric modality. This study proposes fusion of face and fingerprint for robust recognition system. The integration is performed at the matching score level. The matching tasks for both modalities are carried out by using support vector machines (SVM) as the classifier. Experiments on face expression and fingerprint database show that the performances of multimodal biometric system provide better recognition compared to single biometric modality. Based on the fusion techniques evaluated, trait-specific weight was found to be highly effective than the sum rule-based fusion. Equal error rate (EER) percentage for face- only and fingerprint- only systems are 2.50% and 5.56%, respectively, while the EER for system using sum rule- based fusion and system using trait-specific weights are 0.833% and 0.340%, respectively.
An Evolutionary Game of Partners in Peer Review

Peer review is an important tool which is used to improve the software process. The partners that join software peer review are limited rational agent, and their strategies are complex. The paper constructs the strategy models which based on evolutionary game and its further discuss. The factors, i.e., knowledge management, performance appraisal and informal organization, exist in the software process and need to be improved.
Southern African Student Exiles in the United States

The only official United States contact with the liberation movements of Southern Africa has been the educational programmes administered by the African–American Institute under contract to the U.S. Government. In addition to providing education and scholarships to refugee students in Africa, the A.A.I. has since 1962 administered the Southern African Student Program (S.A.S.P.) for refugees in the United States at the college and graduate levels.
Technical efficiency improvement of rice farming in southern Thailand

The objective of this study is to assess the technical efficient frontier of rice farms using input-oriented data envelopment analysis. The frontier represents the minimum applicable level of efficiency of inputs given the current level of yields, technologies, and managerial ability among the farmers which can be used as a benchmark for efficiency improvement of rice farms. Two-stage DEA methodology of efficiency analysis was applied. The empirical results revealed that the technical efficiency of rice farming in southern Thailand could be improved through reduction of inputs by 8-14 % and the current output at 3.5 tons of paddy rice per ha could be maintained. In order to improve technical efficiency of rice farms in southern Thailand, our findings lead us to suggest advisory measures which focus on farm level under existing technology. The optimum rates of inputs for southern Thailand are 123-147 kg of seed, 60-77 kg of N-fertilizer, and 32-35 kg of P-fertilizer per ha. Over the long-run, new rice varieties which suitable for the south are needed. The new rice varieties should be improved from the traditional varieties which included non-photoperiod sensitive qualification.
Lower Bounds on Identiication Criteria for Perceptron-like Learning Rules

We investigate the computational complexity of identifying neural weights using Per-ceptron-like learning rules. These are understood as instructions to change weights by a xed amount after occurrence of an error. We are considering worst-case bounds on the number of correction steps when the training examples are taken from Boolean functions computable by McCulloch-Pitts neu-rons. In order to avoid known exponential lower bounds for exact identiication we de-ne and analyze three criteria that do not require that the learning process generates weights that precisely represent the target function: PAC identiication, order identii-cation, and sign identiication. Our results show that Perceptron-like learning rules cannot satisfy any of these criteria when the number of correction steps is to be bounded by a polynomial. This indicates that even by considerably lowering one's demands one cannot prevent Perceptron-like rules from being computationally infeasible.
Kriging with External Drift in Model Localization

Normal 0 21 false false false FI ZH-CN TH When a large-area model is utilized in smaller sub-areas, the results may be biased, even though the model is unbiased in general. One method for adjusting the large-area models for such bias is kriging, in which the predictions are corrected with the help of neighbouring observations. A variogram represents the spatial correlation between neighbouring observations as a function of distance. With the selected variogram and drift model that describes the general mean, the variable values for given objects are then predicted. The aim of this study was (1) to test for a spatial correlation in the residuals of a global form height model fitted over a large study area and (2) to use this correlation in prediction of the same variable. The dataset consisted of 19 175 Scots pines ( Pinus sylvestris L.) from the 9 th National Forest Inventory of Finland. Nested spherical and Bessel variograms were selected for the kriging calculations. In nested models the short-range intrastand correlation and long-range correlation are modelled separately. We used 10-fold cross-validation to evaluate the variogram models selected. We limited the number of neighbours from 20 to 100, i.e. at distances within an 8-17-km radius. At the global level, 30 neighbours were needed for stable estimates, and with 60 neighbours the RMSEs of kriging were lower than the globally fitted model. At the regional level, we obtained better estimates than with regionally re-fitted models when the number of neighbours was 60 for both variogram models. The biases at the regional level in the kriging were small (0.8% of the regional RMSE). In conclusion, there was an app. 6-km spatial correlation in the residuals, but the size of the kriging neighbourhood required for improving prediction was larger than the range. MCFNS 3(1):1-14.
Recent progress in immunotherapy for malignant glioma: treatment strategies and results from clinical trials.

BACKGROUND Despite advances in surgical and adjuvant radiation therapy and chemotherapy strategies, malignant gliomas continue to be associated with poor prognoses. METHODS We review immune-mediated treatment approaches for malignant glioma and the relevance of recent clinical trials and their outcomes. We specifically address the increasing evidence implicating the role of cytotoxic T cells in ensuring adequate immune-mediated clearance of neoplastic cells and the need for the optimization of therapies that can elicit and support such antitumor T-cell activity. RESULTS The poor outcome of this disease has spurred the search for novel experimental therapies that can address and overcome the root biological phenomena associated with the lethality of this disease. The use of immunotherapy to bolster the otherwise impaired antitumor immune responses in glioma patients has received increasing attention. CONCLUSIONS An effective treatment paradigm for malignant gliomas may eventually require a multifaceted approach combining two or more different immunotherapeutic strategies. Such scenarios may involve the use of local cytokine gene therapy to enhance glioma-cell immunogenicity in conjunction with dendritic cell-based active vaccination to stimulate systemic tumoricidal T-cell immunity. Given the heterogeneity of this disease process and the potential risk of immunoediting out a selected, treatment-refractory tumor cell population, the concurrent use of multiple modalities that target disparate tumor characteristics may be of greatest therapeutic relevance.
A numerical analysis on double acting pneumatic telescopic cylinder motion characteristics

This paper presents the design and development of a mathematical model of dynamic motion of pneumatic telescopic cylinder. The aim of the research is to develop a telescopic pneumatic system that can handle variable load at constant forward and retracting speed. The design analysis carried out is focused and based mainly on identifying the characteristics of the pneumatic cylinder using force-feedback control system. A conceptual model was made and the limitations were identified and further studied on nonlinear behavior and the solutions to improve its characteristics were sought in the process of designing and developing the telescopic cylinder. The control system contained combination of proportional and on-off valve in controlling the telescopic cylinder movement. The determination of the displacement of each stage of the telescopic cylinder, velocity and acceleration were optimized using multi-order PI controller. Method of research is performed by simulation studies using Matlab Simulink to prove the dynamic mathematical modeling of the cylinder. During the last stage of the research, a scale down model of the telescopic cylinder was fabricated incorporating all design aspects derived from the theoretical and simulation analysis. After that an experimental study was conducted on the scale down cylinder in order to validate the data obtained. The validated data shall be used in the design of the full scale of the telescopic cylinder. It is found that from the numerical analysis, the designed system can achieve a constant speed although loaded with varied axial force.