Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of retirement voluntariness on changes in smoking, drinking and physical activity among Dutch older workers.

BACKGROUND Although several studies have investigated the association of health behaviors with retirement, none has examined this relationship in the context of retirement voluntariness. METHODS Using data from the 2001 and 2007 waves of a panel study of retirement in the Netherlands, we used multinomial logistic regression models to investigate the impact of retirement voluntariness on changes in smoking, alcohol use, and physical activity. Participants included 1604 individuals, aged 50-64 years, who were employed in 2001. RESULTS During the 6-year follow-up, 884 (55%) sample members retired: 676 (42%) perceived their retirement as voluntary and 208 (13%) perceived their retirement as involuntary. Results of multinomial logistic analyses indicated that, relative to non-retired participants (n = 720), the voluntarily retired had higher risk of increased physical activity [relative risk ratio (RR) = 2.90, 95% confidence interval (CI): 2.19-3.84] and lower risk of decreased physical activity (RR = 0.35, 95% CI: 0.22-0.56). The involuntarily retired had both higher risk of increased smoking (RR = 3.68, 95% CI: 1.45-9.30) and lower risk of decreased smoking (RR = 0.50, 95% CI: 0.25-0.99), lower risk of decreased alcohol use (RR = 0.47, 95% CI: 0.29-0.73), and both higher risk of increased physical activity (RR = 2.14, 95% CI: 1.47-3.13) and lower risk of decreased physical activity (RR = 0.46, 95% CI: 0.23-0.92). CONCLUSION Accounting for the perceived voluntariness of retirement is essential to obtaining a clear assessment of the behavioral effects of this type of labor force departure.
Molecular organization of the postsynaptic specialization

A specific set of molecules including glutamate receptors is targeted to the postsynaptic specialization of excitatory synapses in the brain, gathering in a structure known as the postsynaptic density (PSD). Synaptic targeting of glutamate receptors depends on interactions between the C-terminal tails of receptor subunits and specific PDZ domain-containing scaffold proteins in the PSD. These scaffold proteins assemble a specialized protein complex around each class of glutamate receptor that functions in signal transduction, cytoskeletal anchoring, and trafficking of the receptors. Among the glutamate receptor subtypes, the N-methyl-d-aspartate receptor is relatively stably integrated in the PSD, whereas the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor moves in and out of the postsynaptic membrane in highly dynamic fashion. The distinctive cell biological behaviors of N-methyl-d-aspartate and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors can be explained by their differential interactions with cytoplasmic proteins.
Visualisation of Complex Business Data: A Neural Network Approach

Reliable and well-audited financial statements attract the capital that finances business. Analytical auditing plays an important role in assisting the auditor in determining the nature, timing and extent of his or her substantive testing and in forming an overall opinion as to the reasonableness of recorded account values. It is used to improve the efficiency of auditing. Basically, in an analytical auditing one compares expected relationships among data items to actual observed relationships. This paper shows how neural networks, especially Kohonen's self-organising map (SOM) can be used in analytical auditing when auditing monthly account values. The SOM is used for clustering monthly data sets. Neural network systems are based on computational intelligence. The purpose is to show how the data sets of various accounts and various years form their own groups. We found that the SOM can add value to auditors in the analytical process: it is a tool for classifying and clustering data sets that reveals if some cluster contains data that a priory should not be in it. Therefore, it can be used for signalling unexpected fluctuations in data. Furthermore, the SOM is a possible technique embedded in the continuous auditing tool.
Impact of oilseed rape expressing the insecticidal serine protease inhibitor, mustard trypsin inhibitor‐2 on the beneficial predator Pterostichus madidus

Insect‐resistant transgenic plants have been suggested to have deleterious effects on beneficial predators feeding on crop pests, through transmission of the transgene product by the pest to the predator. To test this hypothesis, effects of oilseed rape expressing the serine protease inhibitor, mustard trypsin inhibitor −2 (MTI‐2), on the predatory ground beetle Pterostichus madidus were investigated, using diamondback moth, Plutella xylostella as the intermediary pest species. As expected, oilseed rape expressing MTI‐2 had a deleterious effect on the development and survival of the pest. However, incomplete pest mortality resulted in survivors being available to predators at the next trophic level, and inhibition studies confirmed the presence of biologically active transgene product in pest larvae. Characterization of proteolytic digestive enzymes of P. madidus demonstrated that adults utilize serine proteases with trypsin‐like and chymotrypsin‐like specificities; the former activity was completely inhibited by MTI‐2 in vitro. When P. madidus consumed prey reared on MTI‐2 expressing plants over the reproductive period in their life cycle, no significant effects upon survival were observed as a result of exposure to the inhibitor. However, there was a short‐term significant inhibition of weight gain in female beetles fed unlimited prey containing MTI‐2, with a concomitant reduction of prey consumption. Biochemical analyses showed that the inhibitory effects of MTI‐2 delivered via prey on gut proteolysis in the carabid decreased with time of exposure, possibly resulting from up‐regulation of inhibitor‐insensitive proteases. Of ecological significance, consumption of MTI‐2 dosed prey had no detrimental effects on reproductive fitness of adult P. madidus.
A Generalized Probabilistic Topology Control for Wireless Sensor Networks

Topology control is an effective method to improve the energy-efficiency and increase the communication capacity of Wireless Sensor Networks (WSNs). Traditional topology control algorithms are based on deterministic model that fails to consider lossy links which provide only probabilistic connectivity. Noticing this fact, we propose a novel probabilistic network model. We meter the network connectivity using network reachability. It is defined as the minimal of the upper limit of the end-to-end delivery ratio between any pair of nodes in the network. We attempt to find a minimal transmission power for each node while the network reachability is above a given application-specified threshold. The whole procedure is called probabilistic topology control (PTC). We prove that PTC is NP-hard and propose a fully distributed algorithm called BRASP. We prove that BRASP has the guaranteed performance and the communication overhead is O(|E| + |V|). The experimental results show that the network energy-efficiency can be improved by up to 250% and the average node degree is reduced by 50%.
Arbuscular mycorrhizal fungi alter above- and below-ground chemical defense expression differentially among Asclepias species

Below-ground (BG) symbionts of plants can have substantial influence on plant growth and nutrition. Recent work demonstrates that mycorrhizal fungi can affect plant resistance to herbivory and the performance of above- (AG) and BG herbivores. Although these examples emerge from diverse systems, it is unclear if plant species that express similar defensive traits respond similarly to fungal colonization, but comparative work may inform this question. To examine the effects of arbuscular mycorrhizal fungi (AMF) on the expression of chemical resistance, we inoculated 8 species of Asclepias (milkweed)—which all produce toxic cardenolides—with a community of AMF. We quantified plant biomass, foliar and root cardenolide concentration and composition, and assessed evidence for a growth-defense tradeoff in the presence and absence of AMF. As expected, total foliar and root cardenolide concentration varied among milkweed species. Importantly, the effect of mycorrhizal fungi on total foliar cardenolide concentration also varied among milkweed species, with foliar cardenolides increasing or decreasing, depending on the plant species. We detected a phylogenetic signal to this variation; AMF fungi reduced foliar cardenolide concentrations to a greater extent in the clade including A. curassavica than in the clade including A. syriaca. Moreover, AMF inoculation shifted the composition of cardenolides in AG and BG plant tissues in a species-specific fashion. Mycorrhizal inoculation changed the relative distribution of cardenolides between root and shoot tissue in a species-specific fashion, but did not affect cardenolide diversity or polarity. Finally, a tradeoff between plant growth and defense in non-mycorrhizal plants was mitigated completely by AMF inoculation. Overall, we conclude that the effects of AMF inoculation on the expression of chemical resistance can vary among congeneric plant species, and ameliorate tradeoffs between growth and defense.
Test Data Selection and Quality Estimation Based on the Concept of Essential Branches for Path Testing

A new coverage measure is proposed for efficient and effective software testing. The conventional coverage measure for branch testing has such defects as overestimation of software quality and redundant test data selection because all branches are treated equally. These problems can be avoided by paying attention to only those branches essential for path testing. That is, if one branch is executed whenever another particular branch is executed, the former branch is nonessential for path testing. This is because a path covering the latter branch also covers the former branch. Branches other than such nonessential branches will be referred to as essential branches.
Hepatitis C virus: Quantitation and distribution in liver

The optimal method for viral quantitation and the most appropriate site for determining viral load in patients with chronic hepatitis C virus (HCV) infection are unknown. We developed a method for measuring HCV RNA in the liver with the following features: 1) efficient extraction of RNA from tissue (89% of RNA recovered); 2) accurate amplification using branched DNA with strong concordance between a single sample tested on multiple occasions either in the same or in different runs; 3) good sensitivity (95%) and specificity (100%). HCV RNA was detected in as little as 2 mg of tissue, and viral load determined in a needle biopsy was representative of viral load in other parts of the liver. Within individual livers, 68% of the samples quantitated were within 1.5‐fold of the geometric mean, and 95% were within 2.2‐fold of the geometric mean. The mean ratio of virus in the liver and serum was 103, range 17.4–286. A delay of 30 minutes before freezing the liver tissue resulted in a reduction in the measured viral load in some, but not all instances. A sensitive, specific, and reproducible method for quantitating HCV RNA in the liver has been developed. Measurement of viral load at one site was representative of viral load at other sites. While hepatic HCV RNA levels are consistently greater than serum levels, the ratio of liver to serum viral load varies widely. The clinical use of measurement of viral load in the liver remains to be defined. J. Med. Virol. 51:217–224, 1997. © 1997 Wiley‐Liss, Inc.
Compressed sensing MRI by two-dimensional wavelet filter banks

How to speed up the scanning process is the bottleneck problem of magnetic resonance imaging (MRI). As a newly developed mathematical framework of signal sampling and recovery, compressed sensing (CS) provides a solution to this problem because of its potential of reconstructing MR images from fewer samples. Recent work has demonstrated successful application of CS to MRI. However, the frequently used sparsifying transform is the traditional discrete wavelet transform, which has shortcomings, such as oscillations, lack of directionality and shift variance. This paper implements compressed sensing MRI reconstruction based on a new kind of two-dimensional wavelet filter banks which has improved directional selectivity and approximate shift invariance. Our experiments show that the method can significantly reduce aliasing and achieve higher peak signal to noise ratio (PSNR).
Retina Parafoveal Photoreceptor Abnormalities in Asymptomatic Patients With RP 1 L 1 Mutations in Families With Occult Macular Dystrophy

Yu Kato, Gen Hanazono, Kaoru Fujinami, Tetsuhisa Hatase, Yuichi Kawamura, Takeshi Iwata, Yozo Miyake, and Kazushige Tsunoda Division of Vision Research, National Institute of Sensory Organs, Tokyo, Japan Department of Ophthalmology, Tokyo Metropolitan Komagome Hospital, Tokyo, Japan UCL Institute of Ophthalmology, London, United Kingdom Department of Ophthalmology, Keio University, School of Medicine, Tokyo, Japan Division of Ophthalmology and Visual Science, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan Division of Molecular and Cellular Biology, National Institute of Sensory Organs, Tokyo, Japan Aichi Medical University, Aichi, Japan
A Healthy Lifestyle Could Reduce the Onset of First Heart Attack by 80%

Drug therapy for hyperlipidemia and hypertension has significantly contributed to the reduction of coronary heart disease (CHD). However, the burden of CHD remains high, as indicated from a recent report by the American Heart Association (AHA) statistical analysis. For the reduction of CHD, other means in addition to drug therapy, such as healthy lifestyle with a low-risk diet and exercise, are as effective in the prevention of CHD. 13 However, despite the fact that these lifestyle changes are beneficial, inexpensive, and safe, very few people practice these modifications. In this study, data collected from 12,744 participants in the Atherosclerosis Risk in Communities (ARIC) study cohort, aged 45 to 64 years, only 0.1% had practiced ideal cardiovascular health and 17.4% had practiced intermediate cardiovascular health, whereas 82.5% had practiced poor cardiovascular health as defined by the AHA. The beneficial cardiovascular effects of a healthy low-risk diet and exercise were also demonstrated by a recent prospective, population-based study. This study showed that the combination of a low-risk diet and exercise among 20,721 men aged 49 to 75 years free of CHD at onset whowere followed for 11 years could prevent 80%(95% confidence interval [CI], 34%–93%) of primary myocardial infarction (MI).
Learning in 3-D multiuser virtual environments: Exploring the use of unique 3-D attributes for online problem-based learning

The purpose of this article is to present the results of a study conducted to investigate how the attributes of 3-D technology such as avatars, 3-D space, and comic style bubble dialogue boxes affect participants’ social, cognitive, and teaching presences in a blended problem-based learning environment. The community of inquiry model was adopted to analyse and interpret data collected from transcripts and group interviews. The results indicated that although the attributes of 3-D technology promoted participants’ social presence, this positive online social experience did not completely contribute to participants’ cognitive presence due to inherent technology attributes. Additionally, critical technical and instructional features of the 3-D environment were required in order to further enhance teaching presence and overall learning experience.
Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast

Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced REgulation And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAM’s enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells. Author Summary The integration of gene regulatory and metabolic network models is an important goal in computational biology, in order to develop methods that can identify the underlying mechanistic links in biological networks and advance metabolic engineering techniques. In this paper, we develop a framework called Integrated Deduced REgulation And Metabolism (IDREAM) that can improve our ability to predict phenotypes of microorganisms, and particularly it can address the challenges in evaluating phenotypic consequence of perturbing transcriptional regulation of metabolism in a eukaryotic cell. We compare the predictive performance of an IDREAM S. cerevisiae model with a PROM model using a TRN available from the YEASTRACT database. IDREAM outperforms PROM using any of three popular yeast metabolic models and across three experimental growth conditions, making it possible to identify subtle synthetic growth defects, and a new role for Oaf1 in the regulation of acetyl-CoA biosynthesis.
Direct Finger Manipulation of 3D Object Image with Ultrasound Haptic Feedback

In this study, we prototype and examine a system that allows a user to manipulate a 3D virtual object with multiple fingers without wearing any device. An autostereoscopic display produces a 3D image and a depth sensor measures the movement of the fingers. When a user touches a virtual object, haptic feedback is provided by ultrasound phased arrays. By estimating the cross section of the finger in contact with the virtual object and by creating a force pattern around it, it is possible for the user to recognize the position of the surface relative to the finger. To evaluate our system, we conducted two experiments to show that the proposed feedback method is effective in recognizing the object surface and thereby enables the user to grasp the object quickly without seeing it.
Systemic adoptive immunotherapy of a highly immunogenic murine lymphoma growing in the brain

Systemic adoptive immunotherapy with specifically immune lymphocytes was successfully performed in immunodepressed mice challenged intracerebrally with L5178Y/DTIC lymphoma cells, a tumor subline rendered highly immunogenic through In vivo exposure to 5‐(3,3‐dimethyl‐1‐triazenyl)‐1H‐imidazole‐4‐carboxamide (DTIC)1. The systemic immunotherapy relied on the infusion of in vitro‐generated primary cytotoxic T‐lympho‐cytes (CTL), the anti‐tumor activity of which was evaluated by measuring tumor‐cell proliferation In the brain in terms of radiolabel uptake and by recording survival times of recipient leukemic mice. The protection afforded by CTL appeared to be specific and was largely conditioned by dose and time of CTL administration. The levels of protection correlated well with the in vitro killing of L5178Y/DTIC tumor cells.
On the Number of Tests to Detect All Path Delay Faults in Combinational Logic Circuits

The problems involved in handling large numbers of path delay faults were alleviated in previous works, by developing fault simulation and test generation procedures that do not require paths to be explicitly considered. Thus, the methods developed allow the set of all path delay faults to be targeted during test generation and fault simulation. With the problems related to the number of paths removed, a new limiting factor in test generation for path delay faults is revealed, namely, the number of tests required to detect all path delay faults. In this work, the problems related to the number of tests are investigated. A procedure for computing a lower bound on the number of tests is described, and methods for synthesizing circuits with reduced lower bounds on the numbers of tests are developed. Experimental results are presented to demonstrate various aspects of the problem.
How Data Science Workers Work with Data: Discovery, Capture, Curation, Design, Creation

With the rise of big data, there has been an increasing need for practitioners in this space and an increasing opportunity for researchers to understand their workflows and design new tools to improve it. Data science is often described as data-driven, comprising unambiguous data and proceeding through regularized steps of analysis. However, this view focuses more on abstract processes, pipelines, and workflows, and less on how data science workers engage with the data. In this paper, we build on the work of other CSCW and HCI researchers in describing the ways that scientists, scholars, engineers, and others work with their data, through analyses of interviews with 21 data science professionals. We set five approaches to data along a dimension of interventions: Data as given; as captured; as curated; as designed; and as created. Data science workers develop an intuitive sense of their data and processes, and actively shape their data. We propose new ways to apply these interventions analytically, to make sense of the complex activities around data practices.
2 Progress in understanding word reading : Data fi tting versus theory building

Computational modelling is a tool that can be used in different ways for different purposes. There are several distinct styles of modelling research in cognitive science and neuroscience, with differing goals, methods, and evaluation criteria. Nowhere is this clearer that in the area of lexical processing in reading, in which computational models have played a prominent role for over 25 years. In this chapter, we examine two contrasting approaches to computational models of reading, the dual-route approach developed by Max Coltheart and his colleagues, and the parallel distributed processing (PDP) approach developed by ourselves, James L. McClelland, and others. These approaches have spawned a series of implemented models among others). The usual way this research is assessed is by examining individual models with respect to factors such as their fidelity to behavioural data, the breadth of the behavioural phenomena addressed, the limitations of the model, and so on. Our primary goal in this chapter is not to evaluate individual models but rather to examine more basic foundational assumptions of the two approaches. They differ fundamentally with respect to these assumptions, including what models are for, how they are developed, and how they are to be evaluated. Of course, these differences greatly complicate the task of comparing models. Dual-route models are constructed with specific desiderata in mind, some of which are not shared by the other approach, and they necessarily come out " ahead " if those criteria are used in comparing models. The same is true for the PDP models. If all fruits are judged on the basis of what makes a good apple, then apples are necessarily the best fruit. This is unsatisfying if only some of the criteria also apply to oranges. Our goal is to clarify the differences between the approaches and how they affect the interpretation of specific models. We will argue that the more important consideration at this stage in the development of the field is