Miracle-dz/UniFAR-FTUs huggingface dataset:
The Arts Transform The Cognitive Science of Religion

The Cognitive Science of Religion (CSR) is becoming increasingly experimental. Its methods are winning the hearts of next-generation humanities scholars of religion. Yet many present-generation humanities scholars of religion remain unaware of recent advances and have yet to participate. I hope to persuade such scholars that it is worth attempting collaborative science. CSR research will benefit from a fuller participation of mature humanities scholars of religion because their training affords a rich knowledge of religious facts. By the same token, humanities scholars of religion should be interested in scientific approaches because cumulative intellectual progress in every empirical discipline relies on hypothesis-driven research. My argument comes in three parts. First, I clarify the exciting possibilities for cumulative intellectual progress that hypothesis-driven research uniquely affords. Second, I describe recent advances from humanities/CSR collaborations, hazarding a few predictions about what to expect next. Third, I offer practical advice to humanities scholars about how to pursue productive CSR collaborations.
Maximum likelihood parametric blur identification based on a continuous spatial domain model

A new formulation is proposed for maximum likelihood (ML) blur identification that is based on a parametric description of the blur in the continuous spatial coordinates. The aim of this formulation is to find the ML estimate of the extent of certain point spread functions (PSF). It is shown that this can be achieved by formulating the problem in the continuous spatial coordinates, as opposed to using the conventional discrete spatial domain model. Experimental results are presented for the cases of uniform motion blur, out of focus blur and truncated Gaussian blur at various signal-to-noise ratios. <<ETX>>
On the Use of the Adaptive Integral Method in the Presence of Perfectly Conducting Perpendicular Planes

The adaptive integral method (AIM) is widely used to solve electromagnetic scattering and radiation problems involving large objects in free space. In the presence of one or more perfectly conducting perpendicular planes, the AIM formulation can be applied by exploiting the principle of images at the cost of increasing the number of fast Fourier transforms evaluated in the method. In this letter, we show how to obtain an efficient scheme with respect to a plain application of the principle of images.
CAPTCHA Challenge Tradeoffs: Familiarity of Strings versus Degradation of Images

It is a well documented fact that, for human readers, familiar text is more legible than unfamiliar text. Current-generation computer vision systems also are able to exploit some kinds of prior knowledge of linguistic context: for example, many OCR systems can use known lexica (word-lists, such as of commonly occurring English words) to disambiguate interpretations. It is interesting that human readers can exploit various degrees of familiarity; for example, strings of characters which, while not found in dictionaries, are similar to spelled words: e.g. "pronounceable" strings, or strings made up of frequently occurring character n-grams. In contrast to this, computer vision technologies for exploiting such poorly characterized constraints (absent an explicit, complete lexicon) are not yet well developed. This gap in ability may allow us to design stronger CAPTCHAs. We measure the familiarity of challenge strings generated by four methods (described by Bentley and Mallows) and we use the ScatterType CAPTCHA to degrade challenge images. We report the results of a human legibility trial which supports the hypothesis that more familiar strings are indeed more legible in CAPTCHAs. Our measurements may enable engineering CAPTCHAs with a more uniform distribution of difficulty by balancing image degradations against familiarity
Effectiveness and efficiency of methodology for recruiting participants in natural recovery from alcohol and drug addiction

The goal of this descriptive study is to analyse the effectiveness and efficiency in economic and temporal terms of different strategies for the recruitment of participants who have recovered without help from problems with alcohol and other drugs. Diverse recruitment strategies were implemented (press advertisements, publicizing through the media, posters, snowball technique and request for help from healthcare professionals) over a two-year period in two different countries, and the results compared in terms of effectiveness and efficiency in the recruitment of self-changers. This study was carried out in various regions of Spain and in South Florida (USA). With these strategies a total of 54 Spanish-speaking participants were recruited who had changed their consumption habits without therapeutic help, 29 of them in Spain and 25 in Florida. Economic cost and time spent for the implementation of each strategy were assessed. These costs were divided by the number of participants recruited in order to obtain the economic and temporal efficiency of each strategy. Effectiveness was analysed by means of the number of participants recruited. Advertisements emerged as the most effective and efficient strategy in terms of time, while posters was the most efficient strategy in economic terms. The recruitment of self-changers is one of the greatest obstacles facing studies that set out to analyse self-change in drug use. The economic and temporal costs are high. Further work is needed to improve the effectiveness and efficiency of recruitment strategies with the aim of optimizing the resources employed in studies on natural recovery in addictive behaviours.
Methodological and Ethical Challenges to Conducting Human Trafficking Studies: A Case Study of Korean Trafficking and Smuggling for Sexual Exploitation to the United States

The objective of this article is to review a range of serious methodological and ethical challenges to studying human trafficking. In particular, the article focuses on lessons learned from a field research study of Korean sex trafficking and smuggling to the United States. We first introduce the general background of the field study as well as its findings. Then we discuss the ethnographic approach and its implementation. Finally, we discuss the various methodological challenges and ethical issues related to studying active Korean traffickers and smugglers as well as Korean victims in the U.S. sex industry.
Di-μ-oxido-bis({2,2′-[ethane-1,2-diylbis(nitrilomethanylylidene)]diphenolato}titanium(IV)) chloroform disolvate

In the title compound, [Ti2(C16H14N2O2)2O2]·2CHCl3, the TiIV atom in the centrosymmetric complex has a distorted octahedral N2O4 coordination environment and is linked via two μ2-oxido bridges into a dinuclear centrosymmetric complex, with a Ti⋯Ti separation of 2.7794 (8) Å. In the salen (N,N′-ethylenebis(salicylimine)) ligand, the two salicylimine units make a dihedral angle of 45.31 (5)°. The complex molecules are stacked parallel to [100], forming channels in which the solvent chloroform molecules are located. C—H⋯O hydrogen-bonding interactions between the complex molecules and the solvent molecules consolidate the crystal packing.
The General Mixture Diffusion Sde and its Relationship with an Uncertain-Volatility Option Model with Volatility-Asset Decorrelation

In the present paper, given an evolving mixture of probability densities, we define a candidate diffusion process whose marginal law follows the same evolution. We derive as a particular case a stochastic differential equation (SDE) admitting a unique strong solution and whose density evolves as a mixture of Gaussian densities. We present an interesting result on the comparison between the instantaneous and the terminal correlation between the obtained process and its squared diffusion coefficient. As an application to mathematical finance, we construct diffusion processes whose marginal densities are mixtures of lognormal densities. We explain how such processes can be used to model the market smile phenomenon. We show that the lognormal mixture dynamics is the one-dimensional diffusion version of a suitable uncertain volatility model, and suitably reinterpret the earlier correlation result. We explore numerically the relationship between the future smile structures of both the diffusion and the uncertain volatility versions.
Content Based Image Retrieval using Interest Point Algorithms in Context of Scientific Cultural Image Collections of Hebraic Tombstones

The Digital Research Infrastructure for the Arts and Humanities-project (Dariah-DE) is dedicated to evaluate information retrieval technologies for research infrastructures of social, human- and cultural studies like universities. One on of the main project-participants is the Salomon-Ludwig-Steinheim Institute of German-Jewish-History which documents Hebraic tombstones as a part of Jewish history and life. A query-by-example could help to improve investigations in this image-database. The content based image retrieval(CBIR) could be done using different features like interest point algorithms (IPA). These algorithms find the most stable points like corner in images and calculate a comparable representation for this point using the surrounding pixel intensities. An amount of these stable keypoints will describe the content of the image. In this paper an example collection of Hebraic tombstone is used to evaluate IPA-detectordescriptor-pairs like SIFT-SIFT, SIFT-BRISK, SURF-SURF, SURF-SIFT, SURF-BRISK and CenSurE-SIFT. Their tolerances in the difference of object-scale, illumination and perspective angle are tested. Further user-driven test-scenarios for CBIR are used to investigate the applicability of the IPAs when similar images in context of scientific cultural research have to be retrieved.
Treatment outcomes of pulpotomy in primary molars using two endodontic biomaterials. A 2-year randomised clinical trial.

AIM To compare the treatment outcomes of calcium-enriched mixture (CEM) cement and mineral trioxide aggregate (MTA) as pulp dressing biomaterials in vital pulpotomy of carious primary molars. STUDY DESIGN split-mouth randomised clinical trial. MATERIALS AND METHODS Forty children aged 4-8 years with 2 carious teeth requiring pulpotomy were selected and randomly assigned to MTA (n = 40) or CEM (n = 40) groups. After coronal pulp removal, the remaining radicular pulp was covered with an appropriate biomaterial; the teeth were then permanently restored. Clinical/radiographic success/failures were blindly evaluated at 6-, 12- and 24-month follow-ups. STATISTICS the recorded data were analyzed with McNemar test and GEE. RESULTS A total of 36, 33 and 35 patients were available for 6-, 12- and 24-month follow-ups, respectively. At the 12-month follow-up only one and three teeth in the CEM and MTA groups had pathologic external root resorption, respectively. The resorbed teeth were then missed due to extraction/exfoliation at the 24-month follow-up; all other treated teeth were sign/symptom-free. Overall, clinical and radiographic outcomes in both MTA/CEM groups were comparable at the three follow-ups without significant differences. Time had no significant effect on the success. CONCLUSION MTA and CEM demonstrated favourable treatment outcomes for pulpotomy of carious primary molars; CEM may be an effective pulp dressing biomaterial.
Multi/many-core programming: Where are we standing?

This paper presents different views exposed in a special session on the current standing of programming and design tools for multi and manycores in the embedded domain. After approximately ten years of the advent of multicore architectures, we take a look at state-of-the-art and trends in model-based programming methodologies from an academic point of view. This view is contrasted with early experiences in transferring multicore compiler research to industry, and complemented with a critical view on the performance gap introduced by compilers for complex architectures. Today, multicores permeate new applications domains, creating new requirements and forcing researchers to rethink some underlying assumptions. This paper exposes the requirements of one such new domain, namely automotive. Applications in this domain require not only programming tools that comply to standards (e.g., ISO 26262) but also tools for high-level simulation, performance analysis and debugging. In this context, we discuss the role of virtual platforms in managing complexity of hardware-software interactions and accelerating the design of multicore systems for automotive applications.
High-dosage intravenous immunoglobulin-associated macrovacuoles are associated with chronic tubulointerstitial lesion worsening in renal transplant recipients.

BACKGROUND AND OBJECTIVES Intravenous immunoglobulins (IVIg) may induce acute renal failure associated with tubular vacuolization. Although the use of IVIg is increasing in kidney transplantation, their impact on graft histology and function remains unknown. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Twenty-seven kidney transplant recipients who had high immunologic risk and were treated with four courses of IVIg after transplantation were studied retrospectively at a transplant center, and findings were compared with those of 27 control subjects. Protocol kidney biopsies were performed at time of transplantation and at 3 mo and 1 yr after transplantation. RESULTS No episode of IVIg-related acute renal failure occurred. Nevertheless, screening biopsies revealed the presence of "microvacuoles" and "macrovacuoles. " Widespread microvacuolizations were often detected (70%) on preimplantation biopsy and not associated with IVIg. Macrovacuoles, which were absent on preimplantation biopsies, were observed exclusively in IVIg-treated patients. Macrovacuoles among IVIg-treated patients were seen in kidneys from older donors and were associated with chronic tubulointerstitial changes at 3 mo, with similar trends at 1 yr. Macrovacuoles were associated with lower creatinine clearance at last follow-up in IVIg-treated patients. CONCLUSIONS IVIg frequently induce tubular macrovacuoles in kidney transplant recipients. These are more frequently observed in grafts from older donors, suggesting a higher vulnerability to IVIg. These data suggest a deleterious impact of IVIg-induced macrovacuoles on chronic tubulointerstitial changes and long-term renal function.
Recommending interesting activity-related local entities

When searching for entities with a strong local character (e.g., a museum), people may also be interested in discovering proximal activity-related entities (e.g., a café). Geographical proximity is a necessary, but not sufficient, qualifier for recommending other entities such that they are related in a useful manner (e.g., interest in a fish market does not imply interest in nearby bookshops, but interest in other produce stores is more likely). We describe and evaluate methods to identify such activity-related local entities.
Least cost design of green buildings by genetic algorithms

In order to keep pace with the trend of "sustainable development", "green building" has become an important design concept in the construction industry. However, the envelope forms and materials of a green building are usually chosen based merely on the architects' experiences instead of on a systematic assessment method. This study employs genetic algorithms to find the least-cost designs for building shells which meet the requirements of a daily energy conservation index. The results show that genetic algorithms can successfully optimize the shell designs, and may be a useful tool for green building designs.
Similarity Based Retrieval in Case Based Reasoning for Analysis of Medical Images

— Content Based Image Retrieval (CBIR) coupled with Case Based Reasoning (CBR) is a paradigm that is becoming increasingly popular in the diagnosis and therapy planning of medical ailments utilizing the digital content of medical images. This paper presents a survey of some of the promising approaches used in the detection of abnormalities in retina images as well in mammographic screening and detection of regions of interest in MRI scans of the brain. We also describe our proposed algorithm to detect hard exudates in fundus images of the retina of Diabetic Retinopathy patients.
Self-Disclosure in Friendships as the Moderator of the Association Between Peer Victimization and Depressive Symptoms in Overweight Adolescents

The objective of the study was to examine the effects of self-disclosure in best friendships on the pathway from peer victimization to depressive symptoms as mediated by self-esteem for physical appearance (SEPA) in overweight adolescents. Utilizing data from 610 French-speaking Canadian adolescents in Grades 7 and 8, the current study examined self-reports of peer victimization, SEPA, self-disclosure in their best friendship, and depressive symptoms and researcher measured height and weight during two time periods over 1 year in overweight adolescents (n = 137). Self-disclosure in friendships buffered the link between peer victimization and depressive symptoms in overweight adolescents. In addition, the protective effect of self-disclosure for the overweight adolescents was through the indirect pathway through SEPA.
Modernist Creativity and the Construction of Reality in Einstein and Kandinsky

In this article, I limn the remarkable ascent of Albert Einstein and Wassily Kandinsky into our cultural pantheon. I depict how both figures mastered and transcended their respective fields, and how they called into question long-established disciplinary assumptions and practices. I also demonstrate how the creative works of Einstein and Kandinsky constructed, and were constructed by, the reality we now call “modern. ”
Transparent fuzzy modeling using fuzzy clustering and GAs

A combined approach to data-driven fuzzy rule-based modeling is described. The rules of an initial model are derived from data by means of a supervised clustering method that to a certain degree ensures the transparency of the resulting rule base. This model is, however suboptimal and a real-coded genetic algorithm (GA) is proposed to optimize simultaneously both the antecedent and the consequent variables. The GA is subjected to constraints concerning the semantic properties of the rule base, inherited from the initial model. Two modeling problems illustrate the power of the combined approach.
Ltv1 Is Required for Efficient Nuclear Export of the Ribosomal Small Subunit in Saccharomyces cerevisiae

In eukaryotes, 40S and 60S ribosomal subunits are assembled in the nucleus and exported to the cytoplasm independently of one another. Nuclear export of the 60S requires the adapter protein Nmd3, but no analogous adapter has been identified for the 40S. Ltv1 is a nonessential, nonribosomal protein that is required for 40S subunit biogenesis in yeast. Cells lacking LTV1 grow slowly, are hypersensitive to inhibitors of protein synthesis, and produce about half as many 40S subunits as do wild-type cells. Ltv1 interacts with Crm1, co-sediments in sucrose gradients with 43S/40S subunits, and copurifies with late 43S particles. Here we show that Ltv1 shuttles between nucleus and cytoplasm in a Crm1-dependent manner and that it contains a functional NES that is sufficient to direct the export of an NLS-containing reporter. Small subunit export is reduced in Δltv1 mutants, as judged by the altered distribution of the 5′-ITS1 rRNA and the 40S ribosomal protein RpS3. Finally, we show a genetic interaction between LTV1 and YRB2, a gene that encodes a Ran-GTP-, Crm1-binding protein that facilitates the small subunit export. We propose that Ltv1 functions as one of several possible adapter proteins that link the nuclear export machinery to the small subunit.
Issues in Cloud Computing

s Cloud computing moved away from personal computers and the individual enterprise application server to services provided by the cloud of computers. The emergence of cloud computing has made a tremendous impact on the Information Technology (IT) industry over the past few years. Currently IT industry needs Cloud computing services to provide best opportunities to real world. Cloud computing is in initial stages, with many issues still to be addressed. The objective of this paper is to explore the different issues of cloud computing and identify important research opportunities in this increasingly important area. We present different design challenges categorized under security challenges, Data Challenges, Performance challenges and other Design Challenges. GJCST Classification : C.1. 4, C.2. 1 Research Issues in Cloud Computing Strictly as per the compliance and regulations of: Research Issues in Cloud Computing V. Krishna Reddy , B. Thirumala Rao , Dr. L.S. S. Reddy , P. Sai Kiran ABSTRACT : Cloud computing moved away from personal computers and the individual enterprise application server to services provided by the cloud of computers. The emergence of cloud computing has made a tremendous impact on the Information Technology (IT) industry over the past few years. Currently IT industry needs Cloud computing services to provide best opportunities to real world. Cloud computing is in initial stages, with many issues still to be addressed. The objective of this paper is to explore the different issues of cloud computing and identify important research opportunities in this increasingly important area. We present different design challenges categorized under security challenges, Data Challenges, Performance challenges and other Design Challenges. Cloud computing moved away from personal computers and the individual enterprise application server to services provided by the cloud of computers. The emergence of cloud computing has made a tremendous impact on the Information Technology (IT) industry over the past few years. Currently IT industry needs Cloud computing services to provide best opportunities to real world. Cloud computing is in initial stages, with many issues still to be addressed. The objective of this paper is to explore the different issues of cloud computing and identify important research opportunities in this increasingly important area. We present different design challenges categorized under security challenges, Data Challenges, Performance challenges and other Design Challenges.
Mass Cultivation of Marine Micro alga Nannochloropsis gaditana KF 410818 Isolated from Visakhapatnam offshore and Fatty Acid Profile Analysis for Biodiesel Production

Economically viable algae based oil industry will depend on the high lipid content of microalgal strains. In this paper, native isolate of Nanochloropsis gaditana proved that, it is a promising strain for large scale production of biomass and biodiesel. Not all algal oils are adequate for making biodiesel, but suitable oils commonly occur. In this study, the algal growth rate, biomass production, transestrification process, lipid content and productivity of microalgae culture isolated from onshore water was determined. Furthermore, lipid extract from the isolate and its further converted to biodiesel was investigated. Results from the mass culture, 2.67 g L biomass were founded on the 10 day under indoor condition with 24 h light intensities in annular column. Maximum FAME yields 20% was observed under direct transestrification process. Fatty acid profile showed that no matter which conditions are provided for growth, but produce profitable biomass under low cost is economical. The approaches present in the study could be employed for the large scale biomass and biodiesel production.