Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of serum adiponectin levels with breast cancer risk.

PURPOSE Adiponectin is a peptide hormone secreted from the adipose tissue, affecting the proliferation and insulin sensitivity of various types of cells. Because association of obesity with breast cancer risk is well established, it is possible that adiponectin plays some role in the development of breast cancer. Thus, in the present study, the association of the serum adiponectin levels with breast cancer risk was investigated. EXPERIMENTAL DESIGN A case-control study was conducted on 102 breast cancer patients (cases) and 100 healthy women (controls). The serum adiponectin levels of cases and controls were examined in their association with breast cancer risk after adjustment for the various classical risk factors (family history, age at menarche, parity, body mass index, and so forth). In addition, the relationship between the serum adiponectin levels and the various clinicopathological characteristics of breast cancers was studied. RESULTS Women in the low tertile of serum adiponectin levels were associated with a significantly (P < 0.005) increased risk for breast cancer compared with women in the high tertile [odds ratio (OR), 3.63; 95% confidence interval (CI), 1.61-8.19]. Such an association was observed both in the premenopausal women (OR, 3.46; 95% CI, 0.89-13.50) and in the postmenopausal women (OR, 3.90; 95% CI, 1.23-12.44). The frequency of large (>2 cm) tumors and that of high histological grade (2+3) tumors were significantly (P < 0.005 and P < 0.05, respectively) higher in breast cancer patients in the low tertile of the serum adiponectin levels than those in the high and intermediate tertiles. CONCLUSIONS These results suggest that the low serum adiponectin levels are significantly associated with an increased risk for breast cancer and that tumors arising in women with the low serum adiponectin levels are more likely to show a biologically aggressive phenotype. The association between obesity and breast cancer risk might be partly explained by adiponectin.
Exploiting spatial diversity in multiagent reinforcement learning based spectrum sensing

In this paper a multiband, multiagent reinforcement learning based distributed sensing policy for cognitive radio networks is proposed. In the proposed sensing policy the secondary users (SUs) collaborate with neighboring users by exchanging information locally. The objective is to maximize the amount of free spectrum found for secondary use while guaranteeing a certain probability of detection. The SUs employ spatial diversity through collaborative sensing to control the false alarm rate and thus the probability of finding available spectrum opportunities. The SUs in the cognitive radio network make local decisions based on their own and their neighbors' local test statistics to identify unused spectrum locally. Simulation results show that the proposed sensing policy provides a straightforward approach for obtaining a good tradeoff between sensing more spectrum and the reliability of the sensing results.
Conjugal vectors for cloning, expression, and insertional mutagenesis in gram-negative bacteria.

Figure 1. Physical map of the vectors presented in this study. (A) TA-cloning conjugal suicide vector. (B) Broad host-range cloning vector. (C) Broad host-range expression vector. Only the relevant restriction sites are shown. Antibiotic markers: strA, streptomycin resistance protein A; strB, streptomycin resistance protein B; tet, tetracycline resistance protein; kan, kanamycin resistance protein. ori, origin of replication. tet
Distinct Regions of the Mouse Cyclin A1 Gene, Ccna1, Confer Male Germ-Cell Specific Expression and Enhancer Function1

Abstract The gene encoding mouse cyclin A1, Ccna1, is expressed at highest levels in late pachytene-diplotene spermatocytes, where it is required for meiotic cell division. To begin to understand the mechanisms responsible for its highly restricted pattern of expression, transgenic mouse lines carrying constructs consisting of the cyclin A1 regulatory region fused with the reporter gene lacZ were generated. Analysis of tissue-specific and testicular cell-type-specific transgene expression indicated that sequences within −1.3 kilobases (kb) of the cyclin A1 putative transcriptional start site were sufficient to direct transgene expression uniquely to late spermatocytes while maintaining repression in other tissues. However, sequences located between −4.8 kb and −1.3 kb of the putative transcriptional start site were apparently required to transcribe the reporter at levels needed for consistent X-gal staining. Comparison of the mouse, rat, and human proximal promoters revealed regions of high sequence conservation and consensus sequences both for known transcription factors, some of which are coexpressed with Ccna1, such as A-myb and Hsf2, and for elements that control expression of genes in somatic cell cycles, such as CDE, CHR, and CCAAT elements. Thus, the promoter region within 1.3 kb upstream of the putative Ccna1 transcriptional start can direct expression of lacZ to spermatocytes, while sequences located between −4.8 kb and −1.3 kb of the putative transcriptional start site may enhance expression of lacZ.
A modified eigenvalue-based cooperative spectrum sensing algorithm

Spectrum sensing is an essential function in cognitive radio (CR) to dynamically detect temporarily unused frequency bands, which improve the efficiency of utilization of frequency spectrum. In this paper, based on traditional maximum and minimum eigenvalue detection (MME), a modified algorithm is presented by proposing a new decision statistic and the corresponding decision threshold is also deduced based on Random Matrix Theory. The modified algorithm is robust against noise uncertainty and has good performance in low SNR for the nature of correlation of primary signal. The modified algorithm is simulated in MATLAB and results are analyzed. Compared with traditional MME algorithm, the modified algorithm has better performance in detecting probability.
Confidence factor and feature selection for semi-supervised multi-label classification methods

In this paper, we investigate two important problems in multi-label classification algorithms, which are: the number of labeled instances and the high dimensionality of the labeled instances. In the literature, we can find several papers about multi-label classification problems, where an instance can be associated with more than one label simultaneously. One of the main issues with multi-label classification methods is that many of these require a high number of instances to be able to generalize in an efficient way. In order to solve this problem, we used semi-supervised learning, which combines labeled and unlabeled instances during the training process. In this sense, the semi-supervised learning may become an essential tool to define, efficiently, the process of automatic assignment of labels. Therefore, this paper presents four semi-supervised methods for the multi-label classification, focusing on the use of a confidence parameter in the process of automatic assignment of labels. In order to validate the feasibility of these methods, an empirical analysis will be conducted using high-dimensional datasets, aiming to evaluate the performance of such methods in different situations. In this case, we will apply a feature selection algorithm in order to reduce, in an efficient way, the number of features to be used by the classification methods.
Analysis and Problems on Fuzzy Vault Scheme

This paper discusses the problem existed in the UNLOCK algorithm of a fuzzy vault scheme. After analyzing the construction of the fuzzy vault scheme and the principle of the Reed-Solomon error correction code, it is proved that the special use of the Reed- Solomon code in the UNLOCK algorithm of the scheme is not appropriate. Therefore, the computation complexity analysis of the scheme, which is based on the Reed-Solomon code, also needs reconsideration. A practical UNLOCK algorithm and computation complexity analysis are also presented in the paper.
Fuzzy-set based models of neurons and knowledge-based networks

We will introduce and study different fuzzy-set oriented computational models of neurons. The generic topologies of the neurons emerging there are significantly influenced by basic logic operators(AND, OR, NOT) encountered in the theory of fuzzy sets. The logical flavor of the proposed constructs is expressed in terms of operators used in their formalization and a way of their superposition in the neurons. The two broad categories of neurons embrace basic aggregation neurons (named AND and OR neurons) and referential processing units (such as matching, dominance, inclusion neurons). The specific features of the neurons are flexibly modeled with the aid of triangular norms. The inhibitory and excitatory characteristics are captured by embodying direct and complemented (negated) input signals. We will propose various topologies of neural networks put together with the use of these neurons and demonstrate straightforward relationships coming off between the problem specificity and the resulting architecture of the network. This limpid way of mapping the domain knowledge onto the structure of the network contributes significantly toward enhancements in learning processes in the network and substantially facilitates its interpretation. >
The RapidOWL Methodology--Towards Agile Knowledge Engineering

Agile methodologies have recently gained growing success in many economic and technical spheres. This is due to the fact that flexibility, in particular fast and efficient reactions to changed prerequisites, is becoming increasingly important in the information society. To support adaptive, semantic collaboration between domain experts and knowledge engineers, a new, agile knowledge engineering methodology, called RapidOWL is proposed. This methodology is based on the idea of iterative refinement, annotation and structuring of a knowledge base. A central paradigm for the RapidOWL methodology is the concentration on smallest possible information chunks. The collaborative aspect comes into play, when those information chunks can be selectively added, removed, annotated with comments or ratings. Design rationales for the RapidOWL methodology are to be light-weight, easy-to-implement, and support of spatially distributed and highly collaborative scenarios
Coordinate Descent Method for Large-scale L 2-loss Linear SVM

Linear support vector machines (SVM) are useful for classifying largescale sparse data. Problems with sparse features are common in applications such as document classification and natural language processing. In this paper, we propose a novel coordinate descent algorithm for training linear SVM with the L2-loss function. At each step, the proposed method minimizes a one-variable sub-problem while fixing other variables. The sub-problem is solved by Newton steps with the line search technique. The procedure globally converges at the linear rate. Experiments show that our method is more efficient and stable than state of the art methods such as Pegasos and TRON.
ASSESSING DIVERSITY AND SIMILARITY OF CONCEPTUAL UNDERSTANDING VIA SEMI-AUTOMATED SEMANTIC ANALYSIS OF CONCEPT MAPS

The development of common conceptual understanding is one of the essential steps in professionalization of a field of practice. To support this process, we collected Concept Maps (CMaps) from practitioners in the field answering the same focus question. Our goal was to expose variability in the understanding of the concept under investigation and to identify common themes, which could be later taken as the basis for the development of a common definition. Collected maps were open-ended, they consisted of varying numbers of concepts and propositions, had different structures, and had little overlap of concepts and concept connections. In order to extract common themes from this set of maps, we used Latent Semantic Analysis to compare CMaps’ semantic elements (e.g., concepts, propositions and maps) to each other. Based on this semi-automated analysis we were able to extract a set of concepts and propositions that are semantically representative of the collection.
Merton's portfolio optimization problem in a Black and Scholes market with non‐Gaussian stochastic volatility of Ornstein‐Uhlenbeck type

We study Merton's classical portfolio optimization problem for an investor who can trade in a risk‐free bond and a stock. The goal of the investor is to allocate money so that her expected utility from terminal wealth is maximized. The special feature of the problem studied in this paper is the inclusion of stochastic volatility in the dynamics of the risky asset. The model we use is driven by a superposition of non‐Gaussian Ornstein‐Uhlenbeck processes and it was recently proposed and intensively investigated for real market data by Barndorff‐Nielsen and Shephard (2001) . Using the dynamic programming method, explicit trading strategies and expressions for the value function via Feynman‐Kac formulas are derived and verified for power utilities. Some numerical examples are also presented.
UX , Usability and ISO Standards

The paper explores the relationship between UX and current approaches to usability in ISO standards, and how the ISO approach could potentially be extended to incorporate UX in guidance for product developers. Three approaches to usability are identified: 1. System Usability: Meeting organizational goals for user performance, safety and satisfaction resulting from interaction. 2. User Experience (satisfaction): Meeting user pragmatic and hedonic goals related to the experience and outcomes of interaction. 3. Product usability: providing product attributes to support system usability and the user experience.
Parents’ and Stakeholders’ Perspectives on Strategies to Reduce Fast Food Consumption Among Iranian Adolescents: A Qualitative Study

Background: Many people are concerned with the problems and side effects caused by increased levels of fast food (FF) consumption, especially among adolescents. Several studies have assessed the problems of FF consumption particularly weight gain and obesity. However, few address the methods, strategies, and policies needed to reduce this issue. Objectives: This study aims to explore parent and stakeholder views and perspectives on the means to reduce adolescent FF consumption. Patients and Methods: The present paper is based on original research conducted from June to December 2012. In this study, 19 participants were selected using purposive sampling. Their experiences and perspectives were explored using in-depth semi-structured interviews; a thematic content analysis with a conventional approach was conducted to analyze the data. Using this approach, the transcripts were coded openly, and subcategories and categories were chosen based on similarities. Subsequently, themes were defined at a more abstract level. Results: Three main themes were identified as approaches and strategies suggested by parents and stakeholders to reduce FF consumption. These included culture building, supporting healthy eating styles, and controlling and supervising healthy eating styles. Conclusions: Based on the extracted themes, some interventions can be suggested to reduce FF consumption among young people. A holistic approach that incorporates a change of culture, social support, and supervision is promising. Further quantitative studies are also recommended. Keywords: Fast Food; Adolescent; Parents; Qualitative Research
Experimental evidence for water formation on interstellar dust grains by hydrogen and oxygen atoms

Context. The synthesis of water is one necessary step in the origin and development of life. It is believed that pristine water is formed and grows on the surface of icy dust grains in dark interstellar clouds. Until now, there has been no experimental evidence whether this scenario is feasible or not on an astrophysically relevant template and by hydrogen and oxygen atom reactions. Aims. We present here the first experimental evidence of water synthesis by such a process on a realistic analogue of grain surface in dense clouds, i.e., amorphous water ice. Methods. Atomic beams of oxygen and deuterium are aimed at a porous water ice substrate (H2O) held at 10 K. Products are analyzed by the temperature-programmed desorption technique. Results. We observe the production of HDO and D2O, indicating that water is formed under conditions of the dense interstellar medium from hydrogen and oxygen atoms. This experiment opens up the field of a little explored complex chemistry that could occur on dust grains,which is believed to be the site where key processes lead to the molecular diversity and complexity observed in the Universe.
Response Properties from Turtle Auditory Hair Cell Afferent Fibers Suggest Spike Abbreviated Title: Synchronous Release at Auditory Hair Cell-afferent Fiber Synapse Running Head: Turtle Auditory Hair Cell Afferent Fiber Response Properties

Inner ear hair cell afferent fiber synapses are capable of transferring 20 information at high rates, for long periods of time with extraordinary fidelity. As at other 21 sensory synapses, hair cells rely on graded receptor potentials and unique vesicle 22 trafficking and release properties of ribbon synapses to relay intensity information. 23 Postsynaptic recordings from afferent fibers of the turtle auditory papilla identified 24 EPSCs that were fast AMPA receptor-based responses with rapid onset and decay 25 times. EPSCs varied in amplitude by about 15x per fiber, with kinetics that showed a 26 tendency to slow at larger amplitudes. Complex EPSCs, were produced by temporal 27 summation of single events, likely across synapses. Complex EPSCs were more 28 efficient at generating action potentials than were single EPSCs. Potassium-evoked 29 release increased the frequency of EPSCs, in particular complex events, but did not 30 increase EPSC amplitudes. Temporal summation of EPSCs across synapses may 31 underlie action potential generation at these synapses. The broad amplitude histograms 32 were probed for mechanisms of multivesicular release using reduced external Ca or 33 the introduction of Cd or Sr to uncouple release. Results are consistent with broad 34 amplitude histograms being generated by a combination of the variability in synaptic 35 vesicle size and by coordinated release of these vesicles. It is posited that 36 multivesicular release plays less of role in multisynaptic ribbon synapses than in single 37 synaptic afferent fibers. 38 39
A New PDE Model for Image Restoration

The ill posedPerona-Malik equation of image processing and the regularizedP-M model i. e. C-model are studied. The convex composition of the two models is presentedin the form of thesystem of partial differential equations. The algorithm for the proposed model is given. Some images are employed to do the numericalexperiments. The results show that our model yieldsbetter smoothing and edge detection results and has higher PSNRand less RMSE than other two methods.
Antiferromagnetic sawtooth chain with Heisenberg and Ising bonds

The sawtooth chain with pairs of S = 1=2 spins interacting with XXZ-interactions placed on each second tooth is considered. All other interaction bonds are taken to be of Ising type. Exact statistical mechanical solution of the model within the direct transfer-matrix technique is obtained. The solution allows one to obtain exact analytic expressions for all thermodynamic functions of the model. Ground state properties are also investigated, the corresponding ground state phase diagram is presented.
Anquiro: enabling efficient static verification of sensor network software

We present Anquiro, a domain-specific model checker for statically verifying the correctness of sensor network software. In this context, static verification has hitherto received little attention, as state space explosion problems may prevent applying these techniques. Anquiro overcomes this limitation by providing different abstraction levels depending on the functionality to verify, and by implementing domain-specific state abstractions within the checking engine. We demonstrate the use of Anquiro in verifying the correctness of a widely used data dissemination protocol. This study allows us to identify issues that the protocol may overlook. Moreover, our evaluation of Anquiro's performance shows that it drastically reduces the number of states generated during the verification, preventing state space explosion problems.
On the Economic Value of Supply Chain Visibility: The Example of Improved Emergency Ordering

Location technologies such as GPS or GSM cell tracking can be used to improve the control of production and transport processes along the entire supply chain. In this paper, we particularly consider the benefits of location systems with regard to supply chain visibility for improving emergency ordering decisions. For this purpose, we first present an overview of the underlying base technologies that can be used for supply chain monitoring today and a review of prior research on inventory control with emergency ordering. With the help of a simulation model, we show that higher supply chain visibility can be used to identify and avoid unnecessary emergency orders, resulting in cost savings for the overall inventory system. In addition, we identify optimal levels of supply chain granularity and discuss why the maximum resolution that may be achievable from a technological perspective does not necessarily lead to cost-optimal results.
Hardware Implementation of ADABOOST ALGORITHM and Verification

Adaboost algorithm is difficult to implement on embedded platform for real-time face detection by software due to its high computation load and data throughput. This article presents a cell array architecture using parallel technology. Detection procedure can be greatly speeded up with its multi- pipeline. Besides it makes use of the continuity of image data to decrease the accesses to RAM. This article uses Electronic System Level (ESL) tools to develop and simulate a cycle-accurate model of the cell array architecture. The result shows that cell array architecture with 200 MHz clock can process 12 million HAAR features per second and detect faces on a 176*144 image at the frame rate of 103 frames per second, which is 14 times speedup compared with software implementation.
On the aggregatability of multicast forwarding state

It has been claimed that multicast state cannot be aggregated. In this paper, we will debunk this myth and present a simple technique that can be used to aggregate multicast forwarding state. In particular, we present an interface-centric data structure model which allows aggregation of ranges of multicast addresses in the forwarding table. Understanding the limits of possible aggregation is critical to our knowledge of how IP multicast will scale as it becomes widely deployed. We show through analysis and simulation that some aggregation is possible, even under purely random address allocation and purely random group membership distribution. We further show how other methods of allocation can significantly improve the ability to aggregate, and how non-random distributions of membership can affect aggregation both positively and negatively.
Control of loop parallelism in multithreaded code

Due to the large amount of potential parallelism, resource management is a critical issue in multithreaded architectures. The challenge in code generation is to control the parallelism without reducing the machines ability to exploit it. Controlled parallelism reduces idle time, communication, and delay caused by synchronization. At the same time it increases the potential for exploitation of program *data structure* locality. In this paper we present and evaluate two methods, slicing and chunking, to control program parallelism. We present the compilation strategy and evaluate its e ectiveness in terms of performance characteristics such as run time and matching store