Miracle-dz/UniFAR-FTUs huggingface dataset:
Omega 3 fatty acids and cognitive health in older people

Oily fish and other sources of long-chain n-3 polyunsaturated fatty acids (n-3 LCPs) have been proposed as protective against dementia and age related cognitive impairment. The basic mechanisms underlying these proposed benefits have been postulated and experimental studies supporting the plausibility of the putative effects have been published. Observational epidemiological and case control studies also largely support a protective role of fish consumption on cognitive function with advancing age, albeit with important unexplained heterogeneity in findings. In this review we report the findings of the latest Cochrane review on the benefits of n-3 LCP supplementation on cognitive function among cognitively healthy older people and expand the review by including trials conducted with individuals with prevalent poor cognitive function or dementia. We identified seven relevant trials, four among cognitively healthy older people, and three among individuals with pre-existing cognitive decline or dementia, and overall conclude that there is no evidence to support the routine use of n-3 LCPs supplements for the prevention, or amelioration, of cognitive decline in later life. We identified several challenges in the design of intervention studies for the prevention of dementia and cognitive decline in older people that require careful consideration especially in recruitment and retention in long-term trials. Whether the lack of agreement in findings from mechanistic and observational data and from intervention studies reflects a real absence of benefit on cognitive function from n-3 LCP supplementation, or whether it reflects intrinsic limitations in the design of published studies remains open to question.
To “See” Is to Feel Grateful? A Quasi-Signal Detection Analysis of Romantic Partners’ Sacrifices

Although gratitude plays a central role in the quality of relationships, little is known about how gratitude emerges, such as in response to partners’ sacrifices. Do people need to accurately see these acts to feel grateful? In two daily experience studies of romantic couples (total N = 426), we used a quasi-signal detection paradigm to examine the prevalence and consequences of (in)accurately “seeing” and missing partners’ sacrifices. Findings consistently showed that sacrifices are equally likely to be missed as they are to be accurately detected, and about half of the time people “see” a sacrifice when the partner declares none. Importantly, “seeing” partners’ sacrifices—accurately or inaccurately—is crucial for boosting gratitude. In contrast, missed sacrifices fail to elicit gratitude, and the lack of appreciation negatively colors the partner’s satisfaction with the relationship when having sacrificed. Thus, these findings illustrate the power that perception holds in romantic couples’ daily lives.
Towards Open String Mirror Symmetry for One-Parameter Calabi-Yau Hypersurfaces

This work is concerned with branes and differential equations for one-parameter Calabi-Yau hypersurfaces in weighted projective spaces. For a certain class of B-branes we derive the inhomogeneous Picard--Fuchs equations satisfied by the brane superpotential. In this way we arrive at a prediction for the real BPS invariants for holomorphic maps of worldsheets with low Euler characteristics, ending on the mirror A-branes.
A Quantitative Approach for Modelling and Personalizing Player Experience in First-Person Shooter Games

In this paper, we describe a methodology for capturing player experience while interacting with a game and we present a data-driven approach for modeling this interaction. We believe the best way to adapt games to a specific player is to use quantitative models of player experience derived from the in-game interaction. Therefore, we rely on crowd-sourced data collected about game context, players behavior and players self-reports of different affective states. Based on this information, we construct estimators of player experience using neuroevolutionary preference learning. We present the experimental setup and the results obtained from a recent case study where accurate estimators were constructed based on information collected from players playing a firstperson shooter game. The framework presented is part of a bigger picture where the generated models are utilized to tailor content generation to particular player’s needs and playing characteristics.
Extracellular vesicles: structure, function, and potential clinical uses in renal diseases

Interest in the role of extracellular vesicles in various diseases including cancer has been increasing. Extracellular vesicles include microvesicles, exosomes, apoptotic bodies, and argosomes, and are classified by size, content, synthesis, and function. Currently, the best characterized are exosomes and microvesicles. Exosomes are small vesicles (40-100 nm) involved in intercellular communication regardless of the distance between them. They are found in various biological fluids such as plasma, serum, and breast milk, and are formed from multivesicular bodies through the inward budding of the endosome membrane. Microvesicles are 100-1000 nm vesicles released from the cell by the outward budding of the plasma membrane. The therapeutic potential of extracellular vesicles is very broad, with applications including a route of drug delivery and as biomarkers for diagnosis. Extracellular vesicles extracted from stem cells may be used for treatment of many diseases including kidney diseases. This review highlights mechanisms of synthesis and function, and the potential uses of well-characterized extracellular vesicles, mainly exosomes, with a special focus on renal functions and diseases.
A MapReduceMerge-based Data Cube Construction Method

The pre-computation of data cubes is critical to improve the response time of On-Line Analytical Processing (OLAP) system. However, as the size of data grows, the time it takes to construct data cubes becomes a significant performance bottleneck. Therefore, we need the parallel pre-computation approach to further improve the performance of OLAP. Current parallel approaches can be grouped into two categories: work partitioning and data partitioning. But the first one can not guarantee the load balance among processors and the second one produces massive data movement between processors. This paper proposes a MapReduceMerge-based parallel data cube construction method with a read-optimized data storage strategy which is more suitable for OLAP. Our method can ensure good load balancing and reduce the large amount of data movement compared with traditional approaches. MapReduceMerge is the expansion of Map Reduce which is a programming model that enables easy development of parallel applications to process massive data on large clusters and it is the key element of Hadoop(an cloud computing framework) which used to support the businesses of Face book under cloud environment. We modify the original MapReduceMerge framework to make it meet the needs of cuboids construction and show the implementation in details through an example of 2-dimension cuboids construction. In the mean time, we discuss the optimization for the construction of multi-dimension cuboids.
Can We Derive Socioeconomic Benefits from Social Network Sites

Previous studies have estimated the relationship between social network site (SNS) usage and social capital using Williams’s Internet Social Capital Scales (ISCS). These studies have found that SNS usage is positively associated with social capital. However, ISCS mainly focuses on emotional support, such as helping solve personal problems and making users try new things. Because social capital can also promote socioeconomic support, which can be obtained through SNS usage, the relationship between SNS usage and socioeconomic social capital should be elucidated. In this study, Lin’s definition was utilized to measure the socioeconomic social capital via a position generator. Additionally, previous studies have only used general regression to estimate the association between SNS usage and social capital. However, this could involve crucial problems in estimating. To avoid these problems, propensity score matching was used to estimate the “net effects” of SNS usage on socioeconomic social capital. A dataset (N = 2,255) collected nationwide in the United States was utilized in the analyses. The results suggest that SNSs negatively affect users’ socioeconomic social capital, which means that SNS usage may decrease users’ socioeconomic support and lead to disadvantageous socioeconomic positions. In other words, we may not benefit from SNS usage.
Comparing Life-Cycle Carbon and Energy Impacts for Biofuel, Wood Product, and Forest Management Alternatives*

The different uses of wood result in a hierarchy of carbon and energy impacts that can be characterized by their efficiency in displacing carbon emissions and/or in displacing fossil energy imports, both being current national objectives. When waste wood is used for biofuels (forest or mill residuals and thinnings) fossil fuels and their emissions are reduced without significant land use changes. Short rotation woody crops can increase yields and management efficiencies by using currently underused land. Wood products and biofuels are coproducts of sustainable forest management, along with the other values forests provide, such as clean air, water, and habitat. Producing multiple coproducts with different uses that result in different values complicates carbon mitigation accounting. It is important to understand how the life-cycle implications of managing our forests and using the wood coming from our forests impacts national energy and carbon emission objectives and other forest values. A series of articles published in this issue of the Forest Products Journal reports on the life-cycle implications of producing ethanol by gasification or fermentation and producing bio-oil by pyrolysis and feedstock collection from forest residuals, thinnings, and short rotation woody crops. These are evaluated and compared with other forest product uses. Background information is provided on existing life-cycle data and methods to evaluate prospective new processes and wood uses. Alternative management, processing, and collection methods are evaluated for their different efficiencies in contributing to national objectives.
A Methodology for the Performance Analysis of Cluster Based Image Segmentation

Partitioning of an image into several constituent components is called image segmentation. Numerous algorithms using different approaches have been proposed for image segmentation. Today many data clustering algorithms are being used for segmenting images. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity. As there is a glut of image segmentation techniques available today, customer who is the real user of these techniques may get obfuscated. In this paper to address the above described problem a review is done on different types of clustering methods used for image segmentation. Also a methodology is proposed to classify and quantify different clustering algorithms based on their consistency in different applications. This paper also describes the various performance parameters on which consistency will be measured in the proposed
Energy-aware Spray and Wait routing in mobile opportunistic sensor networks

The Spray and Wait routing may achieve low routing and energy efficiency due to the blindness in the spray phase. To address this issue, we propose an opportunistic routing with bounded message copies, called the Energy-aware Spray and Wait (ESW), that utilizes the information about speed and residual energy to allocate the number of copies between the corresponding pair nodes in the spray phase. Simulation experiments using the ONE simulator show that our proposed scheme avoids the blind spraying of message copies and outperforms the optimal Spray and Wait in terms of delivery probability, overhead ratio and network lifetime.
Interplay Between Childhood Physical Abuse and Familial Risk in the Onset of Psychotic Disorders

Background: Childhood abuse is considered one of the main environmental risk factors for the development of psychotic symptoms and disorders. However, this association could be due to genetic factors influencing exposure to such risky environments or increasing sensitivity to the detrimental impact of abuse. Therefore, using a large epidemiological case-control sample, we explored the interplay between a specific form of childhood abuse and family psychiatric history (a proxy for genetic risk) in the onset of psychosis. Methods: Data were available on 172 first presentation psychosis cases and 246 geographically matched controls from the Aetiology and Ethnicity of Schizophrenia and Other Psychoses study. Information on childhood abuse was obtained retrospectively using the Childhood Experience of Care and Abuse Questionnaire and occurrence of psychotic and affective disorders in first degree relatives with the Family Interview for Genetic Studies. Results: Parental psychosis was more common among psychosis cases than unaffected controls (adjusted OR = 5.96, 95% CI: 2.09–17.01, P = .001). Parental psychosis was also associated with physical abuse from mothers in both cases (OR = 3.64, 95% CI: 1.06–12.51, P = .040) and controls (OR = 10.93, 95% CI: 1.03–115.90, P = .047), indicative of a gene-environment correlation. Nevertheless, adjusting for parental psychosis did not measurably impact on the abuse-psychosis association (adjusted OR = 3.31, 95% CI: 1.22–8.95, P = .018). No interactions were found between familial liability and maternal physical abuse in determining psychosis caseness. Conclusions: This study found no evidence that familial risk accounts for associations between childhood physical abuse and psychotic disorder nor that it substantially increases the odds of psychosis among individuals reporting abuse.
Design of optimal lattice space-time codes

In this paper we propose a systematic procedure for designing optimal lattice (space-time) codes. By employing stochastic optimization techniques we design lattice codes with minimum error rates when lattice decoders are employed at the receiver. Our design methodology can be tailored to obtain optimal lattice (space-time) codes for any fading statistics and SNR of interest. Further, we obtain fundamental lower bounds on the error probabilities yielded by lattice decoders and characterize their asymptotic behavior
Local Regulatory Variation in Saccharomyces cerevisiae

Naturally occurring sequence variation that affects gene expression is an important source of phenotypic differences among individuals within a species. We and others have previously shown that such regulatory variation can occur both at the same locus as the gene whose expression it affects (local regulatory variation) and elsewhere in the genome at trans-acting factors. Here we present a detailed analysis of genome-wide local regulatory variation in Saccharomyces cerevisiae. We used genetic linkage analysis to show that nearly a quarter of all yeast genes contain local regulatory variation between two divergent strains. We measured allele-specific expression in a diploid hybrid of the two strains for 77 genes showing strong self-linkage and found that in 52%–78% of these genes, local regulatory variation acts directly in cis. We also experimentally confirmed one example in which local regulatory variation in the gene AMN1 acts in trans through a feedback loop. Genome-wide sequence analysis revealed that genes subject to local regulatory variation show increased polymorphism in the promoter regions, and that some but not all of this increase is due to polymorphisms in predicted transcription factor binding sites. Increased polymorphism was also found in the 3′ untranslated regions of these genes. These findings point to the importance of cis-acting variation, but also suggest that there is a diverse set of mechanisms through which local variation can affect gene expression levels.
Oh Classification Influence Index and its Application for k-Nearest Neighbor Classifier C

is an important topic in machine learning and bioinformatics. Many datasets have been introduced for classification tasks. A dataset contains multiple features, and the quality of features influences the classification accuracy of the dataset. The power of classification for each feature differs. In this study, we suggest the Classification Influence Index (CII) as an indicator of classification power for each feature. CII enables evaluation of the features in a dataset and improved classification accuracy by transformation of the dataset. By conducting experiments using CII and the k-nearest neighbor classifier to analyze real datasets, we confirmed that the proposed index provided meaningful improvement of the classification accuracy.
A Flipped Design of College English Speaking Class in the Perspective of Wisdom Teaching

Based on the wisdom teaching concept, the flipped classroom is applied to the college spoken English teaching with the help of modern communicative technology and mobile micro-learning. The design of the teaching procedures is introduced in four aspects—the preparation before the class, the demonstration and interaction in the class, the enhancement and practice after class, and the feedback. The teaching mode is specified to perfect the flipped college English speaking class and to achieve the wisdom teaching objectives. It is beneficial for the teacher to integrate the teaching materials and for the students to develop their language and skills, autonomic learning ability, self-cognition, self-discipline, cooperative ability, inquiry ability and practical
Binary star formation from ring fragmentation

We present a simple model of binary star formation based on the assumption that rotating prestellar cores collapse to form rings and these rings then fragment into protostars. We assume that each ring spawns a small number ( ${\cal N} \leq 6$) of protostars, and that the condensation of the protostars is sufficiently rapid that they can subsequently be treated as point masses. The first part of the model is therefore to simulate the dynamical evolution of a ring of ${\cal N}$ stars and record the properties of the single stars, binaries and higher multiples that form as a result of the dissolution of the ring. The masses of the individual stars in a ring are drawn from a log-normal distribution with dispersion $\sigma_{\log M}$. This part of the model is perfomed for many different realizations of the ring, to obtain good statistics. It can be formulated using dimensionless variables and immediately yields the overall multiplicity. The second part of the model is to convolve the results of these dimensionless simulations, first with the distribution of core masses, which yields the distributions of multiplicity, mass ratio and eccentricity, as a function of primary mass; and second with the distribution of core angular momenta, which yields the distributions of semi-major axis and period, again as a function of primary mass. Using the observed distribution of core masses, and a distribution of core angular momenta which is consistent with the observations, our model is able to reproduce the observed IMF, the observed high multiplicity frequency of pre-Main Sequence stars, the observed distribution of separations, and - for long-period systems - the observed distributions of eccentricity and mass-ratio, provided we invoke ${\cal N} = 4\;{\rm or}\;5$ and $\sigma_{\log M} = 0.6$. We presume that for short-period systems the distributions of eccentricity and mass-ratio are modified by the dissipative effects of subsequent tidal interaction and competitive accretion; and that the reduced multiplicity frequency in the field, compared with young clusters, is the result of dynamical interactions between stars formed in different cores but the same cluster, following ring dissolution. Further numerical experiments are required to explore the consequences of such interactions.
Multiwavelength observations of the M15 intermediate-velocity cloud

We present Westerbork Synthesis Radio Telescope H I images, Lovell telescope multibeam H I wide-field mapping, William Herschel Telescope long-slit echelle Can observations, Wisconsin Ha Mapper (WHAM) facility images, andIRAS ISSA 60- and 100-μm co-added images towards the intermediate-velocity cloud (IVC) at +70 km s - 1 , located in the general direction of the M1 5 globular cluster. When combined with previously published Arecibo data, the HI gas in the IVC is found to be clumpy, with a peak HI column density of ∼ 1.5 × 10 2 0 cm - 2 , inferred volume density (assuming spherical symmetry) of ∼ 24 cm - 3 /D (kpc) and a maximum brightness temperature at a resolution of 81 x 14 arcsec 2 of ∼14 K. The major axis of this part of the IVC lies approximately parallel to the Galactic plane, as does the low-velocity H I gas and IRAS emission. The H I gas in the cloud is warm, with a minimum value of the full width at half-maximum velocity width of 5 km s - 1 corresponding to a kinetic temperature, in the absence of turbulence, of ∼540 K. From the H I data, there are indications of two-component velocity structure. Similarly, the Ca II spectra, of resolution 7 km s - 1 , also show tentative evidence of velocity structure, perhaps indicative of cloudlets. Assuming that there are no unresolved narrow-velocity components, the mean values of log 1 0 [N(Ca II K) cm - 2 ] ∼ 12.0 and Ca II/HI ∼2.5 x 10 - 8 are typical of observations of high Galactic latitude clouds. This compares with a value of Ca II/HI>10 - 6 for IVC absorption towards HD 203664, a halo star of distance 3 kpc, some 3°. 1 from the main M15 IVC condensation. The main IVC condensation is detected by WHAM in Ha with central local-standard-of-rest velocities of ∼60-70 km s - 1 , and intensities uncorrected for Galactic extinction of up to 1.3 R, indicating that the gas is partially ionized. The FWHM values of the Ha IVC component, at a resolution of 1°, exceed 30 km s - 1 . This is some 10 km s - 1 larger than the corresponding H I value at a similar resolution, and indicates that the two components may not be mixed. However, the spatial and velocity coincidence of the Ha and HI peaks in emission towards the main IVC component is qualitatively good. If the Ha emission is caused solely by photoionization, the Lyman continuum flux towards the main IVC condensation is ∼2.7 x 10 6 photon cm - 2 s - 1 . There is not a corresponding IVC Hα detection towards the halo star HD 203664 at velocities exceeding ∼60 km s - 1 . Finally, both the 60- and 100-μm IRAS images show spatial coincidence, over a 0.675 x 0.625 deg 2 field, with both low- and intermediate-velocity H I gas (previously observed with the Arecibo telescope), indicating that the IVC may contain dust. Both the Ha and tentative IRAS detections discriminate this IVC from high-velocity clouds, although the HI properties do not. When combined with the HI and optical results, these data point to a Galactic origin for at least parts of this IVC.