Miracle-dz/UniFAR-FTUs huggingface dataset:
Race and cognitive decline among community-dwelling elders with mild cognitive impairment: Findings from the Memory and Medical Care Study

Objective: Previous studies have reported conflicting findings on the relationship between race and cognitive decline in elders with dementia. Few studies have examined the role of race in cognitive decline in mild cognitive impairment (MCI). We investigate the relationship between race and cognitive decline in participants with MCI in a community-based, longitudinal study of cognitively impaired elders. Method: Based on a validated method utilizing a neuropsychiatric battery, 133 subjects [mean age: 78.7 years (SD = 6.5); female: 112 (76.7%); black: 59 (44.4%)] out of 512 participants in the Memory and Medical Care Study were diagnosed with MCI. The main outcome measure was the Telephone Interview for Cognitive Status (TICS) score over three years. Other baseline subject characteristics (demographics, health-related variables, behavioral, and psychiatric symptoms) were included in the analysis. Results: Overall, the three-year decline in mean TICS score was significantly higher among African Americans than non-African Americans [3.31 (SD: 7.5) versus 0.96 (SD: 3.0), t-value = 1.96, p-value = 0.05]. General estimating equation analyses revealed that African American race was associated with a faster rate of cognitive decline in all models. Conclusion: The rate of cognitive decline in MCI appears to be faster in African Americans than non-African Americans in the community. Diagnosis of MCI among African American elders could lead to early interventions to prevent or delay cognitive decline in the future.
Data mining and the impact of missing data

The actual data mining process deals significantly with prediction, estimation, classification, pattern recognition and the development of association rules. Therefore, the significance of the analysis depends heavily on the accuracy of the database and on the chosen sample data to be used for model training and testing. Data mining is based upon searching the concatenation of multiple databases that usually contain some amount of missing data along with a variable percentage of inaccurate data, pollution, outliers and noise. The issue of missing data must be addressed since ignoring this problem can introduce bias into the models being evaluated and lead to inaccurate data mining conclusions. The objective of this research is to address the impact of missing data on the data mining process.
A composite microdose Adaptive Response (AR) and Bystander Effect (BE) model–application to low LET and high LET AR and BE data

Purpose: It has been suggested that Adaptive Response (AR) may reduce risk of adverse health effects due to ionizing radiation. But very low dose Bystander Effects (BE) may impose dominant deleterious human risks. These conflicting behaviors have stimulated controversy regarding the Linear No-Threshold human risk model. A dose and dose rate-dependent microdose model, to examine AR behavior, was developed in prior work. In the prior work a number of in vitro and in vivo dose response data were examined with the model. Recent new data show AR behavior with some evidence of very low dose BE. The purpose of this work is to supplement the microdose model to encompass the Brenner and colleagues BaD (Bystander and Direct Damage) model and apply this composite model to obtain new knowledge regarding AR and BE and illustrate the use of the model to plan radio-biology experiments. Materials and methods: The biophysical composite AR and BE Microdose Model quantifies the accumulation of hits (Poisson distributed, microdose specific energy depositions) to cell nucleus volumes. This new composite AR and BE model provides predictions of dose response at very low dose BE levels, higher dose AR levels and even higher dose Direct (linear-quadratic) Damage radiation levels. Results: We find good fits of the model to both BE data from the Columbia University microbeam facility and combined AR and BE data for low Linear Energy Transfer (LET) and high LET data. A Bystander Factor of about 27000 and an AR protection factor of 0.61 are obtained for the low LET in vivo mouse spleen exposures. A Bystander Factor of 317 and an AR protection factor of 0.53 are obtained for high LET radon alpha particles in human lymphocytes. In both cases the AR is activated at most by one or two radiation induced charged particle traversals through the cell nucleus. Conclusions: The results of the model analysis is consistent with a premise that both Bystander damage and Adaptive Response radioprotection can occur in the same cell type, derived from the same cell species. The model provides an analytical tool to biophysically study the combined effects of BE and AR.
Improving sigma-lognormal parameter extraction

A fully automatic framework based on the kinematic theory of rapid human movements was recently introduced for analyzing and modeling complex human movements patterns such as those involved in handwriting. In this paper, we present a new approach to better extract and estimate the lognormal primitives and parameters. Through a comprehensive evaluation using 32,000 words from a public database, we show that our approach greatly improves the state-of-the-art extractor.
Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements

Because of the advantages of low cost, large coverage and short revisit cycle, Landsat 8 images have been widely applied to monitor earth surface movements. However, there are few systematic studies considering the error source characteristics or the improvement of the deformation field accuracy obtained by Landsat 8 image. In this study, we utilize the 2013 Mw 7.7 Balochistan, Pakistan earthquake to analyze error spatio-temporal characteristics and elaborate how to mitigate error sources in the deformation field extracted from multi-temporal Landsat 8 images. We found that the stripe artifacts and the topographic shadowing artifacts are two major error components in the deformation field, which currently lack overall understanding and an effective mitigation strategy. For the stripe artifacts, we propose a small spatial baseline (<200 m) method to avoid the stripe artifacts effect on the deformation field. We also propose a small radiometric baseline method to reduce the topographic shadowing artifacts and radiometric decorrelation noises. Those performances and accuracy evaluation show that these two methods are effective in improving the precision of deformation field. This study provides the possibility to detect subtle ground movement with higher precision caused by earthquake, melting glaciers, landslides, etc., with Landsat 8 images. It is also a good reference for error source analysis and corrections in deformation field extracted from other optical satellite images.
Do Non-Reflective Thinkers Apply Extreme Personal Meanings to their Activated Moods?

Background: The integrative cognitive model of mood swings proposes that mood symptoms are driven by extreme, self-referent appraisals. For example, if activated mood is appraised positively, this prompts selection of mood regulation strategies that act to up-regulate mood. Appraisals are driven by fast and automatic Type 1 cognitive processes, which, left unchecked, can cause activated mood to escalate. Aims: It was hypothesized that greater propensity to override these automatic processes by engaging in reflective (Type 2) thinking would be negatively associated with extreme appraisals of activation and activation. Method: Study 1 (n = 150) was a cross-sectional survey consisting of measures of activation, extreme appraisals, and an objective performance-based measure of the propensity to engage in reflective thought (cognitive reflection test; CRT). In Study 2 (n = 241) participants completed these measures plus three alternative measures of effortful cognitive engagement (CRT-2, Need for Cognition and Actively Open-Minded Thinking). Results: In Study 1, propensity to engage in reflective thought (higher CRT scores) was not significantly associated with activated mood or extreme appraisals, but activated mood and extreme appraisals were positively correlated. In study 2, the association between activation and extreme appraisals was replicated. Predicted associations between alternative measures of reflective thinking, activated mood, and extreme appraisals were not found. Conclusions: Extreme appraisals of internal states may be a psychological mechanism underlying activated mood. Propensity to reflect on and override default cognitions was unrelated to these extreme appraisals and activated mood. Further research in a clinical sample using mood-relevant measures of reflective thinking is warranted.
All-Optical Clock Recovery Using a Single Fabry–Perot Semiconductor Optical Amplifier

We present and demonstrate all-optical clock recovery (CR) from the input single- and multiwavelength return-to-zero (RZ) data, using a single multiquantum-well Fabry-Pérot semiconductor optical amplifier (FP-SOA) with no additional amplitude equalization measures. The influence of the FP-SOA facet reflectivity on the amplitude equalization of the recovered clock was numerically investigated. A stable 36.55 GHz optical clock with an extinction ratio of 11.0 dB and a root-mean-square timing jitter of 575 fs was extracted from the input, which consisted of pseudorandom binary sequences of RZ data. The presented scheme has the potential to perform CR from more than 100 Gbit/s of RZ data, and it has the advantage of wideband and parallel operation.
Salvage of fetal karyotype information from SNP array data obtained from products of conception with maternal cell contamination

Maternal cell contamination (MCC) is known to increase the risk of misdiagnosis in prenatal diagnosis as well as in diagnostic tests for the products of conception (POC) from miscarriages. We aimed to develop a data correction method to salvage fetal karyotype information from single‐nucleotide polymorphism (SNP) array data for POC with MCC when parental genotype data are available.
Conductance and amantadine binding of a pore formed by a lysine-flanked transmembrane domain of SARS coronavirus envelope protein

The coronavirus responsible for the severe acute respiratory syndrome (SARS‐CoV) contains a small envelope protein, E, with putative involvement in host cell apoptosis and virus morphogenesis. It has been suggested that E protein can form a membrane destabilizing transmembrane (TM) hairpin, or homooligomerize to form a regular TM α‐helical bundle. We have shown previously that the topology of the α‐helical putative TM domain of E protein (ETM), flanked by two lysine residues at C and N termini to improve solubility, is consistent with a regular TM α‐helix, with orientational parameters in lipid bilayers that are consistent with a homopentameric model. Herein, we show that this peptide, reconstituted in lipid bilayers, shows sodium conductance. Channel activity is inhibited by the anti‐influenza drug amantadine, which was found to bind our preparation with moderate affinity. Results obtained from single or double mutants indicate that the organization of the transmembrane pore is consistent with our previously reported pentameric α‐helical bundle model.
Big Data and central banks

This commentary recaps a Centre for Central Banking Studies event held at the Bank of England on 2–3 July 2014. The article covers three main points. First, it situates the Centre for Central Banking Studies event within the context of the Bank’s Strategic Plan and initiatives. Second, it summarises and reflects on major themes from the event. Third, the article links central banks’ emerging interest in Big Data approaches with their broader uptake by other economic agents.
Characterization of BoLA-DRB3.2 Alleles in Hanwoo (Korean cattle) by Sequence Based Typing (SBT)

A study was conducted with 70 Hanwoo (Korean cattle) for genotyping bovine leukocyte antigen (BoLA)-DRB3.2 gene by using the polymerase chain reaction (PCR) and sequence based typing (SBT). Two-step PCR was carried out for amplifying a 284 bp fragment of the target gene and the PCR products were digested with three restriction enzymes namely RsaI, BstYI and HaeIII. Seventeen alleles were detected with frequencies ranging from 1.43 to 18.57% and one (x'aa) of these alleles was identified as a new allele that has not been reported before. The frequency of the new x'aa allele identified in this breed was 12.86%. In addition, the seven most frequently observed alleles (DRB3.2 *10, *15, *16, *26, *27, *54 and x'aa) accounted for 74.28% of the alleles in this population. The phylogenetic tree showed that the BoLA-DRB3.2 allele sequences of Hanwoo were shared with other Bos taurus breeds and no specific clade for Hanwoo was identified. It indicates high heterogeneity of the BoLA-DRB3 gene in this population and may give some ideas for breeding animals having better disease resistance.
A modified Lee–Carter model for analysing short-base-period data

This paper introduces a new modified Lee–Carter model for analysing short-base-period mortality data, for which the original Lee–Carter model produces severely fluctuating predicted age-specific mortality. Approximating the unknown parameters in the modified model by linearized cubic splines and other additive functions, the model can be simplified into a logistic regression when fitted to binomial data. The expected death rate estimated from the modified model is smooth, not only over ages but also over years. The analysis of mortality data in China (2000–08) demonstrates the advantages of the new model over existing models.
Reflections on Relevance: Psychotherapy and Psychosomatics in 2003

The idea of reflecting on whatever was published in this journal during the preceding year came up during my recent E-mail discussion with the Editor, Giovanni Fava. He was trying to appease me as I was telling him about writing critical letters to various journals. Among others, he reminded me that many articles, including those I responded to, are never cited. I was curious –50% are never cited? Articles in any journal, including this one? How many are even read then? We contemplated a bit more and I felt that we should try to reflect on the yearly activity of our peer, the journal – the three of us are about the same age. Well, how did the journal do during 2003? Did anything interesting get published? I would say that a good number of interesting articles appeared in Psychotherapy and Psychosomatics during this year. Some of them touched very important and pertinent issues. Some of them, looking back, seem nebulous or boring to me (but hopefully interesting to some). The topics ranged from the role of folate in depression (folate supplementation might be useful for the prevention of subsequent episodes? ) to SSRIs and suicide, problems of placebo in pharmaceutical trials, alexithymia in vitiligo and, interestingly, posttraumatic embitterment disorder, to name a few. We cannot predict what will ever get cited and thus help the journal in the indefinite quest for the highest impact factor, the ultimate dream of all editors. Only time will tell. However, some articles seem to reflect important contemporary clinical and research issues. I would just like to remind you of them and to bring them to your attention. Actually, there were many more than I am going to mention – so no offense to or misinterpretation about those not mentioned!
Electron induced dissociation in the condensed-phase nitromethane: II. Desorption of neutral fragments

Low energy electron induced dissociation in multilayer films of nitromethane (CD3NO2) was investigated by high resolution electron energy loss spectroscopy (HREELS) and by the electron stimulated desorption (ESD) of neutral species. HREELS measurements show that the lowest electronic states of the condensed molecule are very similar to those seen in the gas phase. Desorbed neutrals were detected using combined non-resonant multi-photon ionization at 355 nm and time of flight mass spectrometry. The most intense signals detected were those of CD3 + and NO + and are attributed primarily to the desorption of CD3 and NO2 fragments following molecular dissociation via low-lying electronic excited states of nitromethane (the detected NO + being the result of the dissociative ionization of NO2). By varying the time delay between the incident electron pulse and the ionizing laser pulse, it is possible to measure the kinetic energy distributions of desorbing fragments. The kinetic energy distributions above ∼ 5 eV appear invariant with incident electron energy, indicating that the same desorption process (dissociation via low-lying electronic states) operates at all the studied incident energies. Nevertheless, measurements of neutral yields as functions of incident electron energy demonstrate that excitation of the dissociative electronic states also proceeds via previously identified transient negative ions. At energies less than ∼ 5 eV, contributions from dissociative electron attachment are also observed in the yield of CD3 and other neutral fragments.
Robustness in neural computation: Random graphs and sparsity

An attempt is made to mathematically codify the belief that fully interconnected neural networks continue to function efficiently in the presence of component damage. Component damage is introduced in a fully interconnected neural network model of n neurons by randomly deleting the links between neurons. An analysis of the outer-product algorithm for this random graph model of sparse interconnectivity yields the following result: If the probability of losing any given link between two neurons is 1- , then the outer-product algorithm can store on the order of pn/log pn/sup 2/ stable memories correcting a linear number of random errors. In particular, the average degree of the interconnectivity graph dictates the memory storage capability, and functional storage of memories as stable states is feasible abruptly when the average number of neural interconnections retained by a neuron exceeds the order of log n links (of a total of n possible links) with other neurons. >
Distributed Representation for Neighborhood-Based Collaborative Filtering

Collaborative filtering is widely used in recommender systems. When training data are extremely sparse, neighbor selection methods work ineffectively. To address this issue, this paper proposes a distributed representation model that represents users as low-dimensional vectors for neighbor selection by considering the chronological order of users' ratings. Experiments show that the proposed method outperforms the state-of-the-art methods solving the sparsity problem with regard to precision and ranking quality.
An Effective Clustering Method Using a Discrete Particle Swarm Optimization Algorithm-Based Hybrid Approach

The purpose of this paper is to present and evaluate an improved Naive Bayes algorithm for clustering. Many researchers search for parameter values using EM algorithm. It is well-known that EM approach has a drawback - local optimal solution, so we propose a novel hybrid algorithm of the discrete particle swarm optimization (DPSO) and the EM approach to improve the global search performance. We evaluate this hybrid approach on 4 real-world data sets from UCI repository. In a number of experiments and comparisons, the hybrid DPSO+EM algorithm exhibits a more effective and outperforms the EM approach
A new autonomous agent approach for the simulation of pedestrians in urban environments

In this paper, a new approach to autonomous agent navigation in real-time applications is presented. Effective driving simulators demand a realistic simulation of both the driven vehicle and the surrounding environment. For example, a variety of pedestrians and autonomous vehicles improve the realism of the simulation. Many studies of virtual environments for autonomous navigation are based on complex spatial subdivisions. Our approach takes advantage of the topological structure of cities, where pedestrians usually walk along straight pavements, to develop a new method for the simulation of autonomous pedestrians. The "smart obstacle" concept is introduced and a method for realistic corner turning is also explained. Our approach has been applied to simulate the motion of pedestrians on train station platforms, the results of which are presented and discussed.
Direct energy cascade in two-dimensional compressible quantum turbulence

We numerically study two-dimensional quantum turbulence with a Gross-Pitaevskii model. With the energy initially accumulated at large scale, quantum turbulence with many quantized vortex points is generated. Due to the lack of enstrophy conservation in this model, direct energy cascade with a Kolmogorov-Obukhov energy spectrum E(k){proportional_to}k{sup -5/3} is observed, which is quite different from two-dimensional incompressible classical turbulence in the decaying case. A positive value for the energy flux guarantees a direct energy cascade in the inertial range (from large to small scales). After almost all the energy at the large scale cascades to the small scale, the compressible kinetic energy realizes the thermodynamic equilibrium state without quantized vortices.
TWEAK, a New Secreted Ligand in the Tumor Necrosis Factor Family That Weakly Induces Apoptosis*

The members of the tumor necrosis factor (TNF) family play pivotal roles in the regulation of the immune system. Here we describe a new ligand in this family, designated TWEAK. The mouse and human versions of this protein are unusually conserved with 93% amino acid identity in the receptor binding domain. The protein was efficiently secreted from cells indicating that, like TNF, TWEAK may have the long range effects of a secreted cytokine. TWEAK transcripts were abundant and found in many tissues, suggesting that TWEAK and TRAIL belong to a new group of widely expressed ligands. Like many members of the TNF family, TWEAK was able to induce interleukin-8 synthesis in a number of cell lines. The human adenocarcinoma cell line, HT29, underwent apoptosis in the presence of both TWEAK and interferon-γ. Thus, TWEAK resembles many other TNF ligands in the capacity to induce cell death; however, the fact that TWEAK-sensitive cells are relatively rare suggests that TWEAK along with lymphotoxins α/β and possibly CD30L trigger death via a weaker, nondeath domain-dependent mechanism.
An Efficient Approach to the Synthesis of Highly Congested 9,10-Dihydrophenanthrene-2,4-dicarbonitriles and Their Biological Evaluation as Antimicrobial Agents

An efficient and novel method for the synthesis in moderate to good yield (72%–84%) of a series of 3-amino-1-substituted-9,10-dihydrophenanthrene-2,4-dicarbonitriles 1–5 via one-pot multi-component reactions of aldehydes, malononitrile, 1-tetralone and ammonium acetate has been delineated. Cyclocondensation attempts of aminocyanophenanthrene derivatives 1, 2, 4 and 5 with acetic anhydride in the presence of conc. H2SO4 failed and instead the diacetylamino derivatives 10–13 were obtained. All prepared compounds were structurally elucidated by various spectroscopic methods and X-ray crystallography. N,N-diacetylamino-derivatives of phenanthrene have shown good antimicrobial activity.