Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduced coenzyme Q10 in female smokers and its association with lipid profile in a young healthy adult population

Introduction Cigarette smoking has a negative effect on body reserve of antioxidants and cholesterol metabolism. Coenzyme Q10 (CoQ10), a potent antioxidant synthesized as part of the cholesterol pathway, is a potential biomarker for systemic oxidative stress. We aimed to investigate gender variation in plasma lipid profile and CoQ10 concentrations in healthy non-smokers and in smokers. Material and methods The study included 55 cigarette smokers (25 females and 30 males) and 51 non-smokers (25 females and 26 males) with the age range from 21 to 45 years, and who had no history of alcohol abuse or chronic diseases such as diabetes mellitus or obesity. Coenzyme Q10 plasma concentrations were measured by reverse-phase high performance liquid chromatography (HPLC) with ultraviolet detection. Fasting plasma glucose and lipid levels were determined by standard colorimetric methods. Results Our results showed that CoQ10 concentrations were significantly decreased in smokers, especially in females, than their non-smoker counterparts. Female smokers also exhibited a significant decrease in plasma concentrations of total cholesterol (TC), HDL-C, LDL-C, and atherogenic ratios HDL-C/TC and CoQ10/LDL-C than male counterparts. Plasma triglyceride concentrations were increased in smokers irrespective of gender. Plasma CoQ10 was relatively more associated with TC and LDL-C in female smokers than male smokers. Conclusions The adverse effects of smoking on body reserve of antioxidants and cholesterol metabolism are greater in females than in males, partially as a result of decreased CoQ10 plasma concentrations, HDL-C and total-cholesterol and abnormal atherogenicity indices.
Analisis Kesulitan Mahasiswa Semester VI dalam Memahami Teks Dokkai Tingkat Menengah

Dokkai adalah salah satu mata kuliah wajib yang harus ditempuh oleh mahasiswa pendidikan bahasa jepang unnes dari semester I sampai semester VI. Dokkai adalah membaca untuk memahami apa yang dibaca. Pada semester VI mata kuliah Dokkai menjadi semakin komplek. Dengan materi yang semakin rumit dan menuntut pemahaman untuk memahami suatu teks bahasa Jepang. Setelah melakukan studi pendahuluan berupa tanya jawab kepada mahasiswa semester VI yang mengikuti mata kuliah Dokkai Enshu, diperoleh fakta bahwa mereka mengalami kesulitan pada mata kuliah Dokkai Enshu untuk memahami teks bahasa Jepang yang menjadi pokok bahasan materi. Permasalahan dalam penelitian ini adalah kesulitan apa saja yang dialami mahasiswa dalam memahami teks dokkai tingkat menengah, serta factor yang menyebabkan kesulitan tersebut. Tujuan dalam penelitian ini adalah mengetahui kesulitan apa saja dan factor yang menyebabkannya. Populasi dan sample dalam penelitian ini adalah mahasiswa Prodi Pendidikan Bahasa Jepang semester VI angkatan 2010 yang mengikuti mata kuliah Dokkai Enshu sebanyak 40 orang. Metode pengumpulan data yang digunakan dalam penelitian ini adalah metode angket dan tes. Bentuk penelitian ini adalah analisis deskriptif kuantitatif kualitatif. Berdasarkan hasil penelitian dapat disimpulkan bahwa kesulitan mahasiswa dalam memahami teks dokkai tingkat menengah yaitu kurangnya pemahaman kosakata, kanji, dan pola kalimat. Kesulitan tersebut disebabkan karena kurangnya minat mahasiswa pada teks bahasa Jepang dan kurangnya kesadaran mahasiswa dalam memperbaiki cara belajar
Shared Dilemmas in the Management of Bipolar Disorder

A hermeneutic phenomenological analysis reveals the complexity of bipolar disorder. Operating at biological, psychological, and social levels this phenomenon creates dilemmas and people must account for their choices in a moral order. Two participants suffer from the condition, whereas a third is employed to deliver mental health treatment. Three themes are identified showing that all the participants struggle to feel they are competent and consistent decision makers. They feel exposed, fearing that others will impose interpretations on their behavior. They resist the imposition of a medical model, wanting to believe that choices are personal and related to life experiences. This person-centered interpretation is favored because it offers the potential for learning, for achieving autonomy, and growth. By attending to the interpersonal aspects of emotion and subjectivity, this analysis challenges the idea that autonomy can be undermined by a disease process in a simple manner. It is suggested that mental health care systems need to deliver services in which the personal and interpersonal aspects of recovery are adequately managed.
A decentralized framework to achieve max-min fair bandwidth allocation for ATM networks

We consider a flow control algorithm to allocate bandwidth in a network subject to throughput and fairness constraints. Our algorithm achieves a max-min fair allocation among contending users, and has desirable properties in that it can operate in a decentralized and asynchronous manner accounting in part for heterogeneity in round trip delays. The algorithm is simple in that (1) the network links make local measurements of capacity and calculate local 'explicit rates' which are fed back to sources without requiring knowledge of the number of on-going connections, while (2), sources adjust their transmission rate so as not to exceed the received explicit rate indication. We discuss its stability, convergence, and feasibility related to fair allocation and rate-based flow control. We also consider its use for 'ABR flow control' in ATM networks.
Verifying a hash table and its iterators in higher-order separation logic

We describe the specification and proof of an (imperative, sequential) hash table implementation. The usual dictionary operations (insertion, lookup, and so on) are supported, as well as iteration via folds and iterators. The code is written in OCaml and verified using higher-order separation logic, embedded in Coq, via the CFML tool and library. This case study is part of a larger project that aims to build a verified OCaml library of basic data structures.
Characterization of radio wave propagation into buildings at 1800 MHz

The paper presents the results of signal strength measurements at 1800 MHz in four office buildings in The Hague, illuminated by an outdoor base station with an antenna above the rooftop. The objectives of these experiments are to study the behavior of the received signal strength at different floors of a building and to determine the main characteristics concerning cell coverage, namely, signal attenuation and variation within these buildings. It is shown that large fluctuations occur between average signal levels in line-of-sight (LOS) and non-LOS areas of multifloor buildings.
State Assignment and Optimization of Ultra-High-Speed FSMs Utilizing Tristate Buffers

The logic synthesis of ultra-high-speed FSMs is presented. The state assignment is based on a well-known method that uses output vectors. This technique is adjusted to include elements of two-level minimization and takes into account the limited number of terms contained in the programmable-AND/fixed-OR logic cell. The state assignment is based on a special form of the binary decision tree. The second phase of the FSM design is logic optimization. The optimization method is based on tristate buffers, thus making possible a one-logic-level FSM structure. The key point is to search partition variables that control the tristate buffers. This technique can also be applied to combinational circuits or the output block of FSMs only. Algorithms for state assignment and optimization are presented and richly illustrated by examples. The method is dedicated to using specific features of complex programmable logic devices. Experimental results prove its effectiveness (e.g., the implementation of the the 16-bit counter requires 136 logic cells and one-logic-cell level instead of 213 cells and four levels). The optimization method using tristate buffers and a state assignment binary decision tree can be directly applied to FPGA-dedicated logic synthesis.
Genotypic recognition and spatial responses by rice roots

Root system growth and development is highly plastic and is influenced by the surrounding environment. Roots frequently grow in heterogeneous environments that include interactions from neighboring plants and physical impediments in the rhizosphere. To investigate how planting density and physical objects affect root system growth, we grew rice in a transparent gel system in close proximity with another plant or a physical object. Root systems were imaged and reconstructed in three dimensions. Root–root interaction strength was calculated using quantitative metrics that characterize the extent to which the reconstructed root systems overlap each other. Surprisingly, we found the overlap of root systems of the same genotype was significantly higher than that of root systems of different genotypes. Root systems of the same genotype tended to grow toward each other but those of different genotypes appeared to avoid each other. Shoot separation experiments excluded the possibility of aerial interactions, suggesting root communication. Staggered plantings indicated that interactions likely occur at root tips in close proximity. Recognition of obstacles also occurred through root tips, but through physical contact in a size-dependent manner. These results indicate that root systems use two different forms of communication to recognize objects and alter root architecture: root-root recognition, possibly mediated through root exudates, and root-object recognition mediated by physical contact at the root tips. This finding suggests that root tips act as local sensors that integrate rhizosphere information into global root architectural changes.
Sparse Bayesian approach for feature selection

This paper employs sparse Bayesian approach to enable the Probabilistic Classification Vector Machine (PCVM) to select a relevant subset of features. Because of probabilistic outputs and the ability to automatically optimize the regularization items, the sparse Bayesian framework has shown great advantages in real-world applications. However, the Gaussian priors that introduce the same prior to different classes may lead to instability in the classifications. An improved Gaussian prior, whose sign is determined by the class label, is adopt in PCVM. In this paper, we present a joint classifier and feature learning algorithm: Feature Selection Probabilistic Classification Vector Machine (FPCVM). The improved Gaussian priors, named as truncated Gaussian prior, are introduced into the feature space for feature selection, and into the sample space to generate sparsity to the weight parameters, respectively. The expectation-maximization (EM) algorithm is employed to obtain a maximum a posteriori (MAP) estimation of these parameters. In experiments, both the accuracy of classification and performance of feature selection are evaluated on synthetic datasets, benchmark datasets and high-dimensional gene expression datasets.
Research, part of a Special Feature on Education and Differential Vulnerability to Natural Disasters Effects of Educational Attainment on Climate Risk Vulnerability

In the context of still uncertain specific effects of climate change in specific locations, this paper examines whether education significantly increases coping capacity with regard to particular climatic changes, and whether it improves the resilience of people to climate risks in general. Our hypothesis is that investment in universal primary and secondary education around the world is the most effective strategy for preparing to cope with the still uncertain dangers associated with future climate. The empirical evidence presented for a cross-country time series of factors associated with past natural disaster fatalities since 1980 in 125 countries confirms this overriding importance of education in reducing impacts. We also present new projections of populations by age, sex, and level of educational attainment to 2050, thus providing an appropriate tool for anticipating societies' future adaptive capacities based on alternative education scenarios associated with different policies.
AdHocSign : an Ad Hoc Group Signature Scheme for Accountable and Anonymous Access to Outsourced Data

This paper presents a new group signature scheme (named AdHocSign) for dynamically formed groups, to support accountable and anonymous access to outsourced data. Specifically, assume each user is assigned a certain set of attributes and the secrets associated with these attributes when he/she joins the system; the access to each piece of outsourced data is regulated by an access structure (i.e., a logical expression of attributes) which defines an adhoc group of users allowed to access the data. The proposed AdHocSign enables a user who is allowed to access a piece of data to authenticate himself/herself to the host of the data using its preloaded secrets and some auxiliary information provided by the host; no extra secrets are needed to be distributed to the users when new access structures are constructed or existing access structures are modified. Rigorous security analysis of the AdHocSign scheme has been conducted to prove its selfless-anonymity and traceability, based on the hardness assumption of the q-SDH and the Decisional Linear problems. The scheme has also been implemented and the evaluation results show that its computational cost is comparable to that of a state-of-the-art group signature scheme.
Image restoration with edge-preserving regularization in wavelet domain

Image restoration is an ill posed problem and must be regularized. Usually, the difficulty of regularization is to suppress the noise but not smooth the edges. In order to preserve the edges of restored image effectively, a general wavelet-domain edge-preserving regularization scheme which is analogous to the space-domain maximum a posterior probability (MAP) estimation in Markov random field (MRF) is proposed. The corresponding solving strategy of the wavelet-domain regularization is also put forward. Several potential functions which have the ability of edge-preserving are analyzed and tested. To get rid of the Gibbs effects brought during the wavelet-domain restoration, the horizontal (or vertical) continuity in horizontal (or vertical) subband of natural image is employed in the form of an additional penalty. And, experiments are presented to verify the theoretical results.
Mixture Hidden Markov Models for Sequence Data: The seqHMM Package in R

Sequence analysis is being more and more widely used for the analysis of social sequences and other multivariate categorical time series data. However, it is often complex to describe, visualize, and compare large sequence data, especially when there are multiple parallel sequences per subject. Hidden (latent) Markov models (HMMs) are able to detect underlying latent structures and they can be used in various longitudinal settings: to account for measurement error, to detect unobservable states, or to compress information across several types of observations. Extending to mixture hidden Markov models (MHMMs) allows clustering data into homogeneous subsets, with or without external covariates. The seqHMM package in R is designed for the efficient modeling of sequences and other categorical time series data containing one or multiple subjects with one or multiple interdependent sequences using HMMs and MHMMs. Also other restricted variants of the MHMM can be fitted, e.g., latent class models, Markov models, mixture Markov models, or even ordinary multinomial regression models with suitable parameterization of the HMM. Good graphical presentations of data and models are useful during the whole analysis process from the first glimpse at the data to model fitting and presentation of results. The package provides easy options for plotting parallel sequence data, and proposes visualizing HMMs as directed graphs.
Cybersecurity as a Politikum: implications of security discourses for infrastructures

In the cybersecurity community it is common to think of security as a design feature for systems and infrastructures that may be difficult to balance with other requirements. What is less studied is how security requirements come about, for which reasons, and what their influence is on the actions the system facilitates. Security is for example often used as an argument for or against granting access rights that are of importance to stakeholders, such as in the discussion on counterterrorism and privacy. This paper argues that the ongoing politicization of security issues calls for a paradigm to study cybersecurity as a Politikum: a matter of political concern, embedded in existing and future infrastructures. We summarize literature which inspired this paper and explain the role of security arguments for infrastructure governance. Then we outline the new paradigm and its core concepts and contribution, including the notion of framing. Finally, we present discourse analysis and infrastructure ethnography as research methods and discuss cases in which discourses (may) shape infrastructures, in particular smart cities.
Conflict-based Selection of Branching Rules in SAT-Algorithms

ABSTRACTThe problem of proving that a propositional boolean formula is satisﬁable (SAT) is one of the funda-mental problems in computer science. The application of SAT solvers in VLSI CAD has become ofmajor interest. The most popular SAT algorithms are based on the well known Davis-Putnam procedure.There, to guide the search, a branching rule is applied for selecting and assigning unassigned variables.Additionally, conﬂict analysis methods are available that result in non-chronological backtracking thatprevents the SAT algorithm from searching nonrelevant parts of the search space.In this paper we focus on the impact of different branching rules and present an approach which (1)allows the use of several branching rules to be applied (not limited to one static rule) and (2) uses in-formation from non-chronological backtracking to dynamically adapt the probabilities of the branchingrules to be selected.Our approach results in a faster and more robust behaviour of the SAT algorithm. 1 Introduction
Implementation of a Generalized Critical Region Construct

The critical region construct can be usefully extended by adding region entry conditions and replacing the mutual exclusion restriction by a more general restriction. This paper discusses an extended construct of this nature, and presents an implementation approach based on Dijkstra's secretary process concept, with the code for the secretary process generated automatically during program compilation. This type of implementation can produce efficient solutions to many complex synchronization problems. It is also applicable in a wide range of hardware/software environments, including many existing systems. The use of the construct is demonstrated by a number of programming examples.
SPATIALLY CORRELATED CLUSTER POPULATIONS IN THE OUTER DISK OF NGC 3184

We use deep (∼27.5 mag V-band point-source limiting magnitude) V- and U-band Large Binocular Telescope imaging to study the outer disk (beyond the optical radius R25) of the non-interacting, face-on spiral galaxy NGC 3184 (D = 11.1 Mpc; R25 = 11.1 kpc) and find that this outer disk contains >1000 objects (or marginally resolved “knots”) resembling star clusters with masses ∼102–104 M☉ and ages up to ∼1 Gyr. We find statistically significant numbers of these cluster-like knots extending to ∼1.4 R25, with the redder knots outnumbering bluer at the largest radii. We measure clustering among knots and find significant correlation to galactocentric radii of 1.5 R25 for knot separations <1 kpc. The effective integrated surface brightness of this outer disk cluster population ranges from 30–32 mag arcsec−2 in V. We compare the H i extent to that of the correlated knots and find that the clusters extend at least to the damped Lyman-α threshold of H i column density (2 × 1020 cm-2; ∼1.62 R25). The blue knots are correlated with H i spiral structure to ∼1.5 R25, while the red knots may be correlated with the outer fringes of the H i disk to ∼1.7 R25. These results suggest that outer disks are well populated, common, and long-lasting features of many nearby disk galaxies.
Workers’ motivations and managerial practices in not-for-profit social enterprises

The literature has always pointed out that social enterprise (SE) worker have a specific motivational profile compared to their counterparts in for-profit organizations (FPOs). Usually, SE workers have been identified as being intrinsically motivated. Nevertheless, the interpretation of what covers intrinsic motivation remains ambiguous in the literature on SEs. Hence, the first objective of this article is to use both economic and psychological literature in order to understand the exact nature of motivation to work for an SE. We propose that rather than considering the motivation to work in SEs as intrinsic, it should be considered as prosocial. Further, the self-determination theory allows for the understanding that prosocial motivation may be based on different types of extrinsic regulation (introjected – identified – integrated) but not on intrinsic motivation. The second aim of this article is to propose a discussion on managerial practices related to this new conceptualization. In particular, we discuss the practices that SEs might use, on the one hand, to attract and select workers who are motivated by their social mission, and on the other hand, to sustain and favor their employees’ motivation over time.
Enabling HLA-based Simulations on the Cloud

The HLA framework is widely used to formalize simulations and achieve reusability and interoperability of simulation components. In order to manage the underlying system of HLA-based simulations, Grid Computing and Cloud Computing are employed to tackle the details of operation, configuration, and maintenance of simulation platforms that simulation applications run on. However, to make a simulation-run-ready environment among different types of computing resources and network environments is challenging, especially for modelers who may not be familiar with the management of distributed systems. In this article, we propose a new cloud-based scheme for HLA based simulations, aiming to ease the management of underlying resources, particularly for those located on geographically distributed locations, and to achieve rapid elasticity that can provide adequate computing capability to end users. An approach for handling diverse network environments is given, by adopting it, idle public resources can be easily configured as additional computing resources for the local cloud infrastructure. In the experiments, compared with its corresponding Grid Computing platform, this Cloud Computing platform achieves a similar performance but with many advantages that Cloud can provide, such as energy consumption, security, and multi-user availability.
A Simple , FullyEnzymicBioluminescentAssayfor Triglyceridesin Serum

in this fully enzymic bioluminescent assay, triglycerides are cleaved by lipase (EC 3.1.1.3) and carboxylesterase (EC 3.1.1.1), and the glycerol obtained is phosphorylated with ATP and glycerol kinase (EC 2.7.1.30). The ATP consumed in the latter reaction is determined by the firefly luciferin-luciferase reaction, and corresponds to the concentration of triglycerides. All the enzymic reactions and the bioluminescent reading can be performed in the same test tube. The precision (CV) of the assay varied between 1 and 7% at different concentrations of triglycerides. There was a good agreement with a fully enzymic method based on spectrophotometry (r = 0.98).