Miracle-dz/UniFAR-FTUs huggingface dataset:
TL-moments and L-moments Estimation of the Generalized Logistic Distribution

The generalized logistic (GLO) distribution has been used widely in extreme value event evaluation and also popular in hydrological risk analysis. In estimating the high return period events, censoring the data from below might be advantageous since the small floods are less significant to large ones, so the used of small floods can sometimes be only a nuisance value. In this paper the method of trimmed L-moments with one smallest value were trimmed (TLMOM1) was introduced as an alternative ways in estimating the flood for higher return period. TLMOM1 has an ability to reduce undesirable influence of small sample might have compared to former TL-moments (TLMOM) and L-moments (LMOM) method. The main objective of this study is to derive the TLMOM1 for GLO distribution. The performance of TLMOM1 was compared with LMOM and TLMOM through Monte Carlo simulation and stream flows data over station in Terengganu, Malaysia. The result shows that in certain cases, TLMOM1 is a better option as compared to LMOM and TLMOM in modelling those series.
Obstetrician–gynecologists and self‐identified depression: personal and clinical

A survey was designed to explore the effect of obstetrician–gynecologists' subjective awareness of depression in themselves and close family/friends on screening patients for depression and on assessing and treating depression in three scenarios describing hypothetical patients during the adolescence, postpartum, and perimenopausal periods. Questionnaires were mailed to 397 members of the American College of Obstetricians and Gynecologists (ACOG) who participate in the Collaborative Ambulatory Research Network (CARN). Fifty‐five percent of the questionnaires were returned. One third of physicians reported having suffered from depression occasionally (28.1%), often (3.8%), or all the time (2.4%) during the past year. Having personally suffered from depression was associated with elevated assessment of depression in the scenarios but not with elevated rates of screening for depression in actual practice, nor with aggressiveness of treatment choices in the scenarios. Awareness that a close friend suffered from depression was not associated with lowered mood as measured, but was associated with increased rates of screening for depression in adolescent, postpartum, and perimenopausal patients, and with elevated assessment of depression and more aggressive treatment practices for depression in hypothetical patients at these three life stages. As such, physicians' practices regarding depression may be influenced by something other than reactivity to their own emotional state. Depression and Anxiety 23:83–89, 2006. © 2006 Wiley‐Liss, Inc.
A Polyhedral Modeling Based Source-to-Source Code Optimization Framework for GPGPU

In this paper, we propose a source-to-source code optimization framework for general purpose computing on graphics processing units (GPGPU). Our framework is based on a re-formulation of the polyhedral loop transformation theory under the context of GPGPU. We prove that the number of actual memory transactions can be used as a performance metric to guide the code optimization process. In addition, we show how to analytically derive such a metric from a GPU program's polyhedral model. We also develop formations of GPGPU-specific optimization problems and propose corresponding affine transformations, which can be applied to an initial parallelized solution derived from input C/C++ code. The experiment results demonstrate the effectiveness of our work. On average, the code generated by our work outperforms a leading GPGPU compiler and NVIDIA handcrafted CUBLAS 4.0 by 20% and 17%, respectively.
Opening up the Cul-de-Sac of Youth Drug Studies: A Contribution to the Construction of Some Alternative Truths

In this article I attempt to set down some starting points for the construction of ways of understanding alcohol and other drug use among young people that differ from those already established in the drug research field. I open with a discussion of the developmental model of “adolescence” and “youth,” arguably the dominant discourse in youth drug research; in particular, its focus on biology, the environment, and the acquisition of personal identity. I then focus on selected elements of the sociological, anthropological and historical literatures on young people that chart a very different set of empirical, analytical and theoretical concerns from those established by the “science” of development; namely, culture, social class, generational conflict, social organization, gender, race/ethnicity, sexuality, spatiality, subjectivity and Eurocentrism. I conclude by arguing that those from outside the dominant drug-research disciplines of epidemiology, medicine and psychology must continually press their case for the relevance of new ideas in order to contribute to a more open and theoretically dynamic field.
Low cost permanent fault detection using ultra-reduced instruction set co-processors

In this paper, we propose a new, low hardware overhead solution for permanent fault detection at the micro-architecture/instruction level. The proposed technique is based on an ultra-reduced instruction set co-processor (URISC) that, in its simplest form, executes only one Turing complete instruction — the subleq instruction. Thus, any instruction on the main core can be redundantly executed on the URISC using a sequence of subleq instructions, and the results can be compared, also on the URISC, to detect faults. A number of novel software and hardware techniques are proposed to decrease the performance overhead of online fault detection while keeping the error detection latency bounded including: (i) URISC routines and hardware support to check both control and data flow instructions; (ii) checking only a subset of instructions in the code based on a novel check window criterion; and (iii) URISC instruction set extensions. Our experimental results, based on FPGA synthesis and RTL simulations, illustrate the benefits of the proposed techniques.
Fungal Bioweathering of Mimetite and a General Geomycological Model for Lead Apatite Mineral Biotransformations

ABSTRACT Fungi play important roles in biogeochemical processes such as organic matter decomposition, bioweathering of minerals and rocks, and metal transformations and therefore influence elemental cycles for essential and potentially toxic elements, e.g., P, S, Pb, and As. Arsenic is a potentially toxic metalloid for most organisms and naturally occurs in trace quantities in soil, rocks, water, air, and living organisms. Among more than 300 arsenic minerals occurring in nature, mimetite [Pb5(AsO4)3Cl] is the most stable lead arsenate and holds considerable promise in metal stabilization for in situ and ex situ sequestration and remediation through precipitation, as do other insoluble lead apatites, such as pyromorphite [Pb5(PO4)3Cl] and vanadinite [Pb5(VO4)3Cl]. Despite the insolubility of mimetite, the organic acid-producing soil fungus Aspergillus niger was able to solubilize mimetite with simultaneous precipitation of lead oxalate as a new mycogenic biomineral. Since fungal biotransformation of both pyromorphite and vanadinite has been previously documented, a new biogeochemical model for the biogenic transformation of lead apatites (mimetite, pyromorphite, and vanadinite) by fungi is hypothesized in this study by application of geochemical modeling together with experimental data. The models closely agreed with experimental data and provided accurate simulation of As and Pb complexation and biomineral formation dependent on, e.g., pH, cation-anion composition, and concentration. A general pattern for fungal biotransformation of lead apatite minerals is proposed, proving new understanding of ecological implications of the biogeochemical cycling of component elements as well as industrial applications in metal stabilization, bioremediation, and biorecovery.
Enzyme-Linked Immunospot Assay Detection of Mumps-Specific Antibody-Secreting B Cells as an Alternative Method of Laboratory Diagnosis

ABSTRACT Although high measles, mumps, and rubella (MMR) vaccination coverage has been successful in dramatically reducing mumps disease in the United States, mumps (re)infections occasionally occur in individuals who have been either previously vaccinated or naturally infected. Standard diagnostics that detect virus or virus-specific antibody are dependable for confirming primary mumps infection in immunologically naïve persons, but these methods perform inconsistently for individuals with prior immune exposure. We hypothesized that detection of activated mumps-specific antibody-secreting B cells (ASCs) by enzyme-linked immunospot (ELISPOT) assay could be used as a more reliable diagnostic. To test this, a time course of virus-specific ASC responses was measured by ELISPOT assay following MMR vaccination of 16 previously vaccinated or naturally exposed adult volunteers. Mumps-specific ASCs were detectable in 68% of these individuals at some point during the first 3 weeks following revaccination. In addition, mumps-specific ASCs were detected in 7/7 previously vaccinated individuals who recently had been infected as part of a confirmed mumps outbreak. These data suggest that ELISPOT detection of mumps-specific ASCs has the potential for use as an alternative method of diagnosis when suspect cases cannot be confirmed by detection of IgM or virus. In addition, it was determined that mumps-specific memory B cells are detected at a much lower frequency than measles- or rubella-specific cells, suggesting that mumps infection may not generate robust B-cell memory.
Image Processing Based Girth Monitoring and Recording System for Rubber Plantations

Measuring the girth and continuous monitoring of the increase in girth is one of the most important processes in rubber plantations since identification of girth deficiencies would enable planters to take corrective actions to ensure a good yield from the plantation. This research paper presents an image processing based girth measurement & recording system that can replace existing manual process in an efficient and economical manner. The system uses a digital image of the tree which uses the current number drawn on the tree to identify the tree number & its width. The image is threshold first & then filtered out using several filtering criterion to identify possible candidates for numbers. Identified blobs are then fed to the Tesseract OCR for number recognition. Threshold image is then filtered again with different criterion to segment out the black strip drawn on the tree which is then used to calculate the width of the tree using calibration parameters. Once the tree number is identified & width is calculated the girth the measured girth of the tree is stored in the data base under the identified tree number. The results obtained from the system indicated significant improvement in efficiency & economy for main plantations. As future developments we are proposing a standard commercial system for girth measurement using standardized 2D Bar Codes as tree identifiers
Neural network forecasting of an opening cash price index

The study investigates the information content of SGX-DT Nikkei 225 futures prices during the non-cash-trading (NCT) period using an artificial neural network model. The cash market closing index, the futures prices from a period in the same trading day and on the following trading day are utilized to determine the appropriate input nodes of a back propagation neural network model in forecasting the opening cash price index. Sensitivity analysis is first employed to address and solve the issue of finding the appropriate network topology. Extensive studies are then performed on the robustness of the constructed network by using different training and testing sample sizes. The effectiveness of the method is demonstrated on data from a 6-month historical record (1998-99). Analytic results demonstrate that the proposed neural network model outperforms a neural network model with the previous day's closing index as the input node and the random walk model forecasts. It, therefore, indicates that there is valuable information involved in futures prices during the NCT period that can be used to forecast the opening cash market price index.
Four Decades of the Advanced Placement Program

"The college work was too easy. So I drank, and wasted time, and ran down to New York. I didn't have to work so I didn't. My grades were excellent and if I had bothered to work they would have been better. I disliked all the courses, knew none of the professors, and didn't care to. It was a game. I was seeing how little work I could do and still keep good grades, and how much I could drink in the weeks before exam period. In the second half of my sophomore year, I got an inspiring tutor and took four fine courses. I started working for the first time in 18 months. I also stopped drinking. Even now with the objectivity of two more years I am seriously convinced that I was magnificently prepared at school and that my first 3 terms at college were a total loss. "2
Ramanujan Primes: Bounds, Runs, Twins, and Gaps

The $n$th Ramanujan prime is the smallest positive integer $R_n$ such that if $x \ge R_n$, then the interval $(x/2,x]$ contains at least $n$ primes. We sharpen Laishram's theorem that $R_n < p_{3n}$ by proving that the maximum of $R_n/p_{3n}$ is $R_5/p_{15} = 41/47$. We give statistics on the length of the longest run of Ramanujan primes among all primes $p<10^n$, for $n\le9$. We prove that if an upper twin prime is Ramanujan, then so is the lower; a table gives the number of twin primes below $10^n$ of three types. Finally, we relate runs of Ramanujan primes to prime gaps. Along the way we state several conjectures and open problems. The Appendix explains Noe's fast algorithm for computing $R_1,R_2,. ,R_n$.
Exploiting prosodic features for dialog act tagging in a discriminative modeling framework

Cue-based automatic dialog act tagging uses lexical, syntactic and prosodic knowledge in the identification of dialog acts. In this paper, we propose a discriminative framework for automatic dialog act tagging using maximum entropy modeling. We propose two schemes for integrating prosody in our modeling framework: (i) Syntaxbased categorical prosody prediction from an automatic prosody labeler, (ii) A novel method to model continuous acoustic-prosodic observation sequence as a discrete sequence through the means of quantization. The proposed prosodic feature integration results in a relative improvement of 11.8% over using lexical and syntactic features alone on the Switchboard-DAMSL corpus. The performance of using the lexical, syntactic and prosodic features results in an dialog act tagging accuracy of 84.1%, close to the human agreement of 84%.
Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation

Background Gene-set enrichment analysis is a useful technique to help functionally characterize large gene lists, such as the results of gene expression experiments. This technique finds functionally coherent gene-sets, such as pathways, that are statistically over-represented in a given gene list. Ideally, the number of resulting sets is smaller than the number of genes in the list, thus simplifying interpretation. However, the increasing number and redundancy of gene-sets used by many current enrichment analysis software works against this ideal. Principal Findings To overcome gene-set redundancy and help in the interpretation of large gene lists, we developed “Enrichment Map”, a network-based visualization method for gene-set enrichment results. Gene-sets are organized in a network, where each set is a node and edges represent gene overlap between sets. Automated network layout groups related gene-sets into network clusters, enabling the user to quickly identify the major enriched functional themes and more easily interpret the enrichment results. Conclusions Enrichment Map is a significant advance in the interpretation of enrichment analysis. Any research project that generates a list of genes can take advantage of this visualization framework. Enrichment Map is implemented as a freely available and user friendly plug-in for the Cytoscape network visualization software (http://baderlab.org/Software/EnrichmentMap/).
Marginal bone level around implants assessed in digital and film radiographs: in vivo study in the dog.

BACKGROUND One of the objectives of postoperative radiographic examinations of implants is to evaluate the marginal bone height and its changes over time. PURPOSE The purpose of this study was to assess the influence of digital image processing on measurements of the marginal bone level around implants. MATERIAL AND METHODS Implants in beagle dogs, used to study the development of peri-implantitis and subsequent healing following treatment, were monitored with conventional radiography and a digital image plate system. Five observers measured the distance between a reference point and the bone level. Measurements in conventional radiographs were made with the use of an x-ray viewer (2x) and a magnifying lens (7x). For the digital images, the system's built-in measuring function was used together with five image processing techniques: edge enhancement (matrixes set on 5 and 25), inverted grey scale, single color highlight, and color intensity mapping together with the brightness and contrast control. From the time of maximum breakdown and the end of the experiment, histologic values were available. RESULTS Differences between techniques and observers increased toward the end of the healing period. Measurements made at maximum breakdown did not differ significantly from the histologic value. Measurements made after healing all methods, except that using edge enhancement and a 25 x 25 kernel, differed significantly from the histologic value by underestimating the bone level. CONCLUSIONS Measurements of bone level around implants from digital radiographs are as accurate and precise as those from film images. In particular cases, the use of specific image processing algorithms may improve both accuracy and precision. After healing, the histologic specimens showed an incomplete bone fill in the crater with a remaining thin layer of connective tissue in contact with the fixture, and in such situations, the morphology of the bone will give a more complicated diagnostic task.
From Virtual Power Plant (VPP) to Sustainable Energy Microsystem (SEM): An opportunity for buildings energy management

The current attention to energy management leads to the necessity to tack new challenges for a best integration of renewable energies, mobility systems and new technologies for the energy efficiency, creating several micro grids with an active interaction with the main energy distribution networks. The integration of more energy systems seems to be the key of the future development and at present it is mainly applied to industrial systems, where Virtual Power Plants (VPPs) are very promising instruments for promoting an effective integration. Since the built environment is one of the biggest consumers of primary energy worldwide and considering the complexity of some residential and tertiary users, the paper proposes the application of the basic principles of the VPP to the building environment introducing new functions typical of the urban context. The paper shows how an optimization algorithms, traditionally used in the industrial sector to schedule and operate a cluster of energy resources, can be successfully adapted also to residential and tertiary frameworks, proposing the aggregation of several energy sub-systems (SS), generally operated as independent, in a single one named Sustainable Energy Microsystem (SEM).
The effect of religion on the perception of health states among adults in the United Arab Emirates: a qualitative study

Objectives Investigate how religion may affect the perception of health states among adults in the United Arab Emirates and the implications for research on self-reported health and quality of life and the use of values in cost-effectiveness analysis. Design Qualitative analysis of short-structured interviews with adult Emiratis carried out by a market research agency.The COREQ criteria have been used where appropriate to guide the reporting of our findings. Setting Participants were recruited from shopping malls and other public places in the cities of Al Ain and Abu Dhabi. Participants Two hundred adult Emiratis broadly representative of the Emirati population in terms of age and gender. Results Eighty one per cent of participants said that their perception of health states was influenced by their spiritual or religious beliefs. The two overarching themes that seemed to explain or classify these influences were ‘fatalism’ and ‘preservation of life’. Subthemes included powerlessness to change what is preordained by God, fear of disability (particularly diminished mobility) and appreciation of health and life and the requirement to look after one’s health. A final theme was that of acceptance, with respondents expressing a willingness to endure suffering and disability with patience in the expectation of rewards in the hereafter. Conclusions Our results emphasise the need for further work to establish locally relevant value sets for Muslim majority countries in the Middle East and elsewhere for use in health technology assessment decision-making, rather than relying on value sets from other regions.
Optimal random multiaccess in energy harvesting Wireless Sensor Networks

We consider a Wireless Sensor Network where each sensor device is able to harvest energy from the environment, and randomly accesses the channel to transmit packets of random importance to a fusion center. If a collision occurs, the transmission fails and all packets involved are discarded. We design distributed transmission schemes where each sensor node, based on its own energy level and the importance of its own data packet, decides whether to transmit the packet or remain idle, so as to maximize the network utility, defined as the average long-term aggregate network importance of the data packets successfully reported to the fusion center. Due to the generally non-convex structure of the optimization problem, we resort to approximate solutions. In particular, we use a mathematical artifice based on a game theoretic formulation of the multiaccess problem, where each sensor node is a player that attempts to selfishly maximize the network utility. We characterize the Symmetric Nash Equilibrium (SNE) of this game, where all the sensor nodes employ the same policy. We prove the existence and uniqueness of the SNE, and we show that it is a local maximum of the original optimization problem. Moreover, we derive an algorithm to compute it.
From Bikers to Surfers: Visual Recognition of Urban Tribes

Iljung S. Kwak1 iskwak@cs.ucsd. edu Ana C. Murillo2 acm@unizar.es Peter N. Belhumeur3 belhumeur@cs.columbia. edu David Kriegman1 kriegman@cs.ucsd. edu Serge Belongie1 sjb@cs.ucsd. edu 1 Dept. of Computer Science and Engineering University of California, San Diego, USA. 2 Dpt. Informatica e Ing. Sistemas Inst. Investigacion en Ingenieria de Aragon. University of Zaragoza, Spain. 3 Department of Computer Science Columbia University, USA.