Miracle-dz/UniFAR-FTUs huggingface dataset:
A Population-Based Case-Control Study of Marijuana Use and Head and Neck Squamous Cell Carcinoma

Cannabinoids, constituents of marijuana smoke, have been recognized to have potential antitumor properties. However, the epidemiologic evidence addressing the relationship between marijuana use and the induction of head and neck squamous cell carcinoma (HNSCC) is inconsistent and conflicting. Cases (n = 434) were patients with incident HNSCC disease from nine medical facilities in the Greater Boston, MA area between December 1999 and December 2003. Controls (n = 547) were frequency matched to cases on age (±3 years), gender, and town of residence, randomly selected from Massachusetts town books. A questionnaire was adopted to collect information on lifetime marijuana use (decade-specific exposures) and associations evaluated using unconditional logistic regression. After adjusting for potential confounders (including smoking and alcohol drinking), 10 to 20 years of marijuana use was associated with a significantly reduced risk of HNSCC [odds ratio (OR)10-<20 years versus never users, 0.38; 95% confidence interval (CI), 0.22-0.67]. Among marijuana users moderate weekly use was associated with reduced risk (OR0.5-<1.5 times versus <0.5 time, 0.52; 95% CI, 0.32-0.85). The magnitude of reduced risk was more pronounced for those who started use at an older age (OR15-<20 years versus never users, 0.53; 95% CI, 0.30-0.95; OR≥20 years versus never users, 0.39; 95% CI, 0.17-0.90; Ptrend < 0.001). These inverse associations did not depend on human papillomavirus 16 antibody status. However, for the subjects who have the same level of smoking or alcohol drinking, we observed attenuated risk of HNSCC among those who use marijuana compared with those who do not. Our study suggests that moderate marijuana use is associated with reduced risk of HNSCC.
Quasi-Cyclic Low-Density Parity-Check Codes for Space-Time Bit-Interleaved Coded Modulation

In this letter, it is shown that the diversity order of space-time bit-interleaved coded modulation (ST-BICM) system is determined by the number of submatrices having linearly independent column vectors in a parity-check matrix of quasicyclic low-density parity-check (QC-LDPC) code. It is also proved that this diversity order can be derived from the base matrix of QC-LDPC code, which can make it easy to design QC-LDPC codes suitable for ST-BICM systems. Finally, the simulation results are provided to confirm the analytical results.
Field Evaluation of Personal Sampling Methods for Multiple Bioaerosols

Ambient bioaerosols are ubiquitous in the daily environment and can affect health in various ways. However, few studies have been conducted to comprehensively evaluate personal bioaerosol exposure in occupational and indoor environments because of the complex composition of bioaerosols and the lack of standardized sampling/analysis methods. We conducted a study to determine the most efficient collection/analysis method for the personal exposure assessment of multiple bioaerosols. The sampling efficiencies of three filters and four samplers were compared. According to our results, polycarbonate (PC) filters had the highest relative efficiency, particularly for bacteria. Side-by-side sampling was conducted to evaluate the three filter samplers (with PC filters) and the NIOSH Personal Bioaerosol Cyclone Sampler. According to the results, the Button Aerosol Sampler and the IOM Inhalable Dust Sampler had the highest relative efficiencies for fungi and bacteria, followed by the NIOSH sampler. Personal sampling was performed in a pig farm to assess occupational bioaerosol exposure and to evaluate the sampling/analysis methods. The Button and IOM samplers yielded a similar performance for personal bioaerosol sampling at the pig farm. However, the Button sampler is more likely to be clogged at high airborne dust concentrations because of its higher flow rate (4 L/min). Therefore, the IOM sampler is a more appropriate choice for performing personal sampling in environments with high dust levels. In summary, the Button and IOM samplers with PC filters are efficient sampling/analysis methods for the personal exposure assessment of multiple bioaerosols.
Adaptive Multicast Routing in Wormhole Networks

Multicast communication has applications in a number of fundamental operations in parallel computing. An eeective multicast routing algorithm must be free from both livelock and deadlock while minimizing communication latency. We describe two classes of multicast wormhole routing algorithms that employ the multi-destination wormhole hardware mechanism proposed by Lin et al. 12] and Panda et al. 17]. Speciic examples of these classes of algorithms are described and experimental results suggest that such algorithms enjoy low communication latencies across a range of network loads.
Data Management and Data Sharing in Science and Technology Studies

This paper presents reports on discussions among an international group of science and technology studies (STS) scholars who convened at the US National Science Foundation (January 2015) to think about data sharing and open STS. The first report, which reflects discussions among members of the Society for Social Studies of Science (4S), relates the potential benefits of data sharing and open science for STS. The second report, which reflects discussions among scholars from many professional STS societies (i.e., European Association for the Study of Science and Technology [EASST], 4S, Society for the History of Technology [SHOT], History of Science Society [HSS], and Philosophy of Science Association [PSA]), focuses on practical and conceptual issues related to managing, storing, and curating STS data. As is the case for all reports of such open discussions, a scholar’s presence at the meeting does not necessarily mean that they agree with all aspects of the text to follow.
Knowledge management about food analysis for dissemination to the public

Measurements and chemical analysis of the nutritional content of food has been widely applied in various research and studies, and can be used as adequate of the databases and information to be managed. Developing of digital media makes it possible to realize the `repository' for information and knowledge management in health food and integrating a variety of potential resources on information and knowledge in Polytechnic Ministry of Health. The main purpose is to serve the needs of the dissemination of knowledge to the public. Various aspects related to the services is a topic of discussion in the planning of this digital media. The concept of cloud services and social networks can be a significant solution to overcome the obstacles in availability of services.
Problems of Decentralized Control : Using Randomized Coordination to Deal with Uncertainty and Avoid Conflicts

We explore certain problems that inhibit coordination in distributed systems based on decentralized control. The most fundamental of these problems are those due to state-information uncertainty and mutually conflicting decisions. We present an integrated view of a series of experiments we carried out in previous studies, showing the common thread of how randomization can be used to directly attack the fundamental problems of decentralized control, and we show the resultant performance gains that are achieved.
Can Biological Markers Partially Explain the Link Between the Social Environment and Oral Health

Understanding how the social world affects humans´ health by “getting under the skin” and penetrating the cells, organs and physiological systems of the body is a key tenet in public health research. Here, we propose the idea that socioeconomic position (SEP) can be biologically embodied, potentially leading to the production of health inequalities in oral health across population groups. Recent studies show that being exposed to chronic stress across the life course could impact our health. Allostatic load (AL) is a composite biological measure of overall physiological wear-and-tear that could allow a better understanding of the potential biological pathways playing a role in the construction of the social gradient in adult health. However, to use biological measures to better understand the mechanisms that construct health inequalities in oral health has not been tested systematically. The purposes of this New Perspective is to discuss the value of using composite biological markers, such as AL, to analyze oral health. This can allow a better understanding of the mechanisms leading to health inequalities in oral health, and add some valuable information for implementing health interventions.
Quantum stochastic equation for the low density limit

A new derivation of the quantum stochastic differential equation for the evolution operator in the low density limit is presented. We use the distribution approach and derive a new algebra for quadratic master fields in the low density limit by using the energy representation. We formulate the stochastic golden rule in the low density limit case for a system coupling with a Bose field via quadratic interaction. In particular, the vacuum expectation value of the evolution operator is computed and its exponential decay is shown.
USING COLOR VARIATION TO MIMIC HUMAN VISUAL PERCEPTION FOR COLOR IMAGE QUANTIZATION

Color quantization is an important part of image processing, image formation, and related research. This paper presents a novel color image quantization algorithm which addresses the question of how to incorporate principles of human perception of color variation into the process of quantization. The color variation measure, calculated first in CIE Lab color space, is used to evaluate color variation and to coarsely segment the image. Considering both color variation and homogeneity of the image, the number of colors that should be used for each segmented region can be determined. Finally, the CF-tree algorithm is applied to classify pixels into their corresponding palette colors. The quantized error of the proposed algorithm is small because it considers color variation and because it is based on a model of human visual perception. Experimental results suggest that the proposed algorithm is more effective in quantizing color images than a wide variety of previously proposed algorithms.
The Effect of Sample Age and Prediction Resolution on Myocardial Infarction Risk Prediction

Myocardial infarction (MI) is one of the leading causes of death in many developed countries. Hence, early detection of MI events is critical for effective preventative therapies, potentially reducing avoidable mortality. One approach for early disease prediction is the use of risk prediction models developed using machine learning techniques. One important component of these models is to provide clinicians with the flexibility to customize (e.g., the prediction range) and use the risk prediction model that they deemed most beneficial for their patients. Therefore, in this paper, we develop MI prediction models and investigate the effect of sample age and prediction resolution on the performance of MI risk prediction models. The cardiovascular health study dataset was used in this study. Results indicate that the prediction model developed using SVM algorithm is capable of achieving high sensitivity, specificity, and balanced accuracy of 95.3%, 84.8%, and 90.1%, respectively, over a time span of 6 years. Both sample age and prediction resolution were found not to have a significant impact on the performance of MI risk prediction models developed using subjects aged 65 and above. This implies that risk prediction models developed using different sample age and prediction resolution is a feasible approach. These models can be integrated into a computer aided screening tool which clinicians can use to interpret and predict the MI risk status of the individual patients after performing the necessary clinical assessments (e.g., cognitive function, physical function, electrocardiography, general changes to health/lifestyle, and medications) required by the models. This could offer a means for clinicians to screen the patients at risk of having MI in the near future and prescribe early medical intervention to reduce the risk
International Conference on Information Systems ( ICIS ) 1-1-2009 The Role of Social Capital in People-to-People Lending Marketplaces

The objective of this paper is to investigate the role of social capital in for-profit People-to-People (P2P) lending marketplaces such as Prosper, the largest P2P lending marketplace in the US. We examine whether marketplace members (lenders, borrowers) are able to capitalize on borrowers' accumulated social capital. From a borrower's perspective, we investigate the influence of social capital on borrowers' chances to obtain funding and better interest rates in general as well as by borrower groups and over time. From a lender's perspective, we investigate the influence of borrowers' social capital on loan payment. We use data over a time span of two and a half years from Prosper, and analyze more than 200,000 loan requests and 27,500 loans. Our results suggest that social capital does not provide equal benefits to all members of Prosper and that mechanisms to promote social capital should be carefully designed.
Bayesian Covariance Selection ∗

We present a novel structural learning method called HdBCS that performs covariance selection in a Bayesian framework for datasets with tens of thousands of variables. HdBCS is based on the intrinsic connection between graphical models on undirected graphs and graphical models on directed acyclic graphs (Bayesian networks). We show how to produce and explore the corresponding association networks by Bayesian model averaging across the models identified. We illustrate the use of HdBCS with an example from a large-scale gene expression study of breast cancer.
Integration of organic LEDs and amorphous Si TFTs onto flexible and lightweight metal foil substrates

We report the integration of organic light emitting devices (OLEDs) and amorphous Si (a-Si) thin-film transistors (TFTs) on both glass, and unbreakable and lightweight thin stainless steel foil substrates. The doped-polymer OLEDs were built following fabrication of driver TFTs in a stacked structure. Due to the opacity of the steel substrate, top-emitting OLED structures were developed. It is shown that the a-Si TFTs provide adequate current levels to drive the OLEDs at video brightness (/spl sim/100 cd/m/sup 2/). This work demonstrates that lightweight and rugged TFT backplanes with integrated OLEDs are essential elements for robust and highly portable active-matrix emissive flat-panel displays.
Structure of the cerebral cortex of the humpback whale, Megaptera novaeangliae (Cetacea, Mysticeti, Balaenopteridae)

Cetaceans diverged from terrestrial mammals between 50 and 60 million years ago and acquired, during their adaptation to a fully aquatic milieu, many derived features, including echolocation (in odontocetes), remarkable auditory and communicative abilities, as well as a complex social organization. Whereas brain structure has been documented in detail in some odontocetes, few reports exist on its organization in mysticetes. We studied the cerebral cortex of the humpback whale (Megaptera novaeangliae) in comparison to another balaenopterid, the fin whale, and representative odontocetes. We observed several differences between Megaptera and odontocetes, such as a highly clustered organization of layer II over the occipital and inferotemporal neocortex, whereas such pattern is restricted to the ventral insula in odontocetes. A striking observation in Megaptera was the presence in layer V of the anterior cingulate, anterior insular, and frontopolar cortices of large spindle cells, similar in morphology and distribution to those described in hominids, suggesting a case of parallel evolution. They were also observed in the fin whale and the largest odontocetes, but not in species with smaller brains or body size. The hippocampal formation, unremarkable in odontocetes, is further diminutive in Megaptera, contrasting with terrestrial mammals. As in odontocetes, clear cytoarchitectural patterns exist in the neocortex of Megaptera, making it possible to define many cortical domains. These observations demonstrate that Megaptera differs from Odontoceti in certain aspects of cortical cytoarchitecture and may provide a neuromorphologic basis for functional and behavioral differences between the suborders as well as a reflection of their divergent evolution. Anat Rec, 290:1–31, 2007. © 2006 Wiley‐Liss, Inc.
Compliance in heart failure patients: the importance of knowledge and beliefs.

AIMS Non-compliance in patients with heart failure (HF) contributes to worsening HF symptoms and may lead to hospitalization. Several smaller studies have examined compliance in HF, but all were limited as they only studied either the individual components of compliance and its related factors or several aspects of compliance without studying the related factors. The aims of this study were to examine all dimensions of compliance and its related factors in one HF population. METHODS AND RESULTS Data were collected in a cohort of 501 HF patients. Clinical and demographic data were assessed and patients completed questionnaires on compliance, beliefs, knowledge, and self-care behaviour. Overall compliance was 72% in this older HF population. Compliance with medication and appointment keeping was high (>90%). In contrast, compliance with diet (83%), fluid restriction (73%), exercise (39%), and weighing (35%) was markedly lower. Compliance was related to knowledge (OR=5.67; CI 2.87-11.19), beliefs (OR=1.78; CI 1.18-2.69), and depressive symptoms (OR=0.53; CI 0.35-0.78). CONCLUSION Although some aspects of compliance had an acceptable level, compliance with weighing and exercise were low. In order to improve compliance, an increase of knowledge and a change of patient's beliefs by education and counselling are recommended. Extra attention should be paid to patients with depressive symptoms.
A Note on Noncommutative String Theory and its Low Energy Limit

The noncommutative string theory is described by embedding open string theory in a constant second rank antisymmetric Bμν field and the noncommutative gauge theory is defined by a deformed ⋆ product. As a check, the study of various scattering amplitudes in both noncommutative string and noncommutative gauge theory confirms that in the α′ → 0 limit, the noncommutative string theoretic amplitude goes over to the noncommutative gauge theoretic amplitude and the couplings are related as . Furthermore, we show that in this limit there will not be any correction to the gauge theoretic action because of the absence of massive modes. We get sin/cos factors in the scattering amplitudes depending on the odd/even number of external photons.
Performance evaluation of OpenDaylight SDN controller

Enourmous amount of data has resulted into large data centres. Virtual machines and virtual networks are an integral part of large data centres. As a result, software defined network controllers have emerged as viable solution to manage such networks. The performance analysis of network controllers is generally carried out through benchmarking. Although several benchmarking studies exist, recently launched OpenDaylight SDN Controller is not considered in any benchmarking study yet. In this paper, we present initial results of benchmarking of Open-Daylight SDN Controller with well known Floodlight controller. We present latency and throughput results of OpenDaylight SDN Controller and Floodlight under different scenarios. We find that OpenDaylight SDN Controller has low average responses as compared to Floodlight. We also note that the standard benchmarking tool - Cbench - has no support for real traffic patterns in a data centre, since data centre traffic is considerably complex. In addition to benchmarking of OpenDaylight SDN Controller, we propose modifications in Cbench to accommodate models of real traffic in data centres. We also discuss our initial implementation.
Hydroclimatic risk to economic growth in Sub-Saharan Africa

In order to plan strategies for adaptation to climate change, the current effects of climate on economic growth needs to be understood. This study reviews evidence of climate effects on economic growth and presents original analysis of the effect in Sub-Saharan Africa (SSA). Case studies from the literature demonstrate that historically, climate has had significant and negative effects on household income, agricultural productivity and economic growth in SSA. This study focuses on the effects hydroclimatic variability on economic growth in the countries of SSA. We utilize a new national level precipitation statistic that incorporates spatial and temporal variability within each country. Country level economic growth statistics are analyzed with crosscountry and panel regressions. Persistent negative precipitation anomalies (drought) are found to be the most significant climate influence on economic growth. This result is consistent across all model specifications and across several measures of welfare and economic activity. Temperature and precipitation variability show significant effects in some cases. Results imply the consideration of hydroclimatic risks, namely drought, may be the priority concern for adaptation to a changing climate for Sub-Saharan Africa. This conclusion is contrary to the focus of many climate change impact assessments that focus on temperature increases as the primary concern.
Multi-agent Negotiation for User-centric Elasticity Management in the Cloud

Application Service Providers (ASP) are increasingly adopting the cloud computing paradigm to provision remote resources for their applications. Elasticity management solutions have been proposed in the domain to enable flexible and autonomic cloud resource provisioning. However, only few solutions consider the key issue of the conflict between ASP business goals and end-users preferences, that is to say Quality of Experience of the end-user. This paper proposes EMan, a decentralized approach for user-centric Elasticity Management. We use multi-agent automated negotiation strategies and tactics that allow the ASP to address the tradeoff between its customers satisfaction and its business objectives and achieve conflict-free solutions. We use Repast simulation environment to simulate EMan. The results show that the ASP can achieve the desired balance between its end-users satisfaction and its business objectives by combining different negotiation strategies and tactics.
A new courtesy amount recognition module of a Check Reading System

A new courtesy amount recognition module of CENPARMIpsilas check reading system (CRS) is proposed in this paper. The module consists of 3 main segments: pre-processing, segmentation and recognition, and post-processing. A new feedback-based segmentation algorithm is adopted for the segmentation task. Besides one individual numeral recognizer for numerals from dasia0psila to dasia9psila, one convolutional neural network(CNN) recognizer for ldquo00rdquo and ldquo000rdquo numeral strings is also integrated into our module for the recognition task. The experimental results on the Quebec Bell Check database show that the recognition rate of the courtesy amount has improved from 41.2% to 74.3%.
Using edge bundle views for clone visualization

Clone detection results are often voluminous and difficult to present. Most clone presentations focus on the quantitative clone results but do not relate them to the structure of the analyzed system. This makes it difficult to interpret the results and draw conclusions. We suggest using edge bundle views to interrelate the system's structure with the clone detection results. Using this technique, it is easier to interpret the clone results and direct further analysis effort.