Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of bilingualism on the white matter structure of the brain

Significance This article fills an important gap in the literature on structural changes in the brain that are induced by speaking two languages. It has been suggested that early lifelong bilingualism affects the structure of white matter (WM) of the brain and preserves its integrity in older age. Here we show that similar WM effects are also found in bilingual individuals who learn their second language (L2) later in life and are active users of both languages. This finding presents a strong argument for the general benefits of additional language learning and the importance of language learning and use in a naturalistic environment. Recent studies suggest that learning and using a second language (L2) can affect brain structure, including the structure of white matter (WM) tracts. This observation comes from research looking at early and older bilingual individuals who have been using both their first and second languages on an everyday basis for many years. This study investigated whether young, highly immersed late bilinguals would also show structural effects in the WM that can be attributed to everyday L2 use, irrespective of critical periods or the length of L2 learning. Our Tract-Based Spatial Statistics analysis revealed higher fractional anisotropy values for bilinguals vs. monolinguals in several WM tracts that have been linked to language processing and in a pattern closely resembling the results reported for older and early bilinguals. We propose that learning and actively using an L2 after childhood can have rapid dynamic effects on WM structure, which in turn may assist in preserving WM integrity in older age.
Short-Term Memory Demands of Reaction-Time Tasks That Differ in Complexity

Four experiments were conducted to determine whether the increased reaction time produced by loading memory with a set of irrelevant items depended on the complexity of the stage structure or of the stimulus-response (S-R) mapping rules underlying the task. In each experiment, reaction-time tasks varying in complexity were performed alone and in the retention interval of a short-term memory task requiring ordered recall of eight digits. Experiment 1 compared simple, choice, and go/no-go tasks over 3 days of practice and found no interaction between memory load and task complexity. Experiment 2 replicated the first day of Experiment 1 with more power and again found no interaction. Since the different tasks required different numbers of stages, this ruled out stage structure as a factor loading memory. However, in Experiment 1 and 2, the same subjects performed all three tasks with the same set of letters and may have developed one comprehensive set of mapping rules for all three tasks, essentially eliminating differences in memory demands between tasks. Experiment 3 used different groups of subjects for a simple and a choice task with letters as stimuli to encourage the development of separate, differentially complex mapping rules for each task and found more interference in the choice task than in the simple task. Experiment 4 involved one group that performed the choice task with letters and the simple task with dots presented at different positions in the visual field, and another group that performed the simple task with letters and the choice task with dots. Comparisons within subjects between materials and between subjects within materials showed that with letters as stimuli, the choice task suffered more interference than the simple task. However, the choice task with dots showed no such pattern, perhaps because of high ideomotor compatibility. It is concluded that S-R mapping rules are held in memory to enable performance on reaction-time tasks, and the findings are discussed in terms of strategies, preparation, and attentional control.
Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers.

BACKGROUND Controlling costs and achieving health care quality improvements require the participation of activated and informed consumers and patients. OBJECTIVES We describe a process for conceptualizing and operationalizing what it means to be "activated" and delineate the process we used to develop a measure for assessing "activation," and the psychometric properties of that measure. METHODS We used the convergence of the findings from a national expert consensus panel and patient focus groups to define the concept and identify the domains of activation. These domains were operationalized by constructing a large item pool. Items were pilot-tested and initial psychometric analysis performed using Rasch methodology. The third stage refined and extended the measure. The fourth stage used a national probability sample to assess the measure's psychometric performance overall and within different subpopulations. STUDY SAMPLE Convenience samples of patients with and without chronic illness, and a national probability sample (N=1,515) are included at different stages in the research. CONCLUSIONS The Patient Activation Measure is a valid, highly reliable, unidimensional, probabilistic Guttman-like scale that reflects a developmental model of activation. Activation appears to involve four stages: (1) believing the patient role is important, (2) having the confidence and knowledge necessary to take action, (3) actually taking action to maintain and improve one's health, and (4) staying the course even under stress. The measure has good psychometric properties indicating that it can be used at the individual patient level to tailor intervention and assess changes.
Catalysis of recombination and its limitation on open circuit voltage for dye sensitized photovoltaic cells using phthalocyanine dyes.

In order to increase the energy efficiency of dye-sensitized solar cells beyond 10%, an improved dye needs to be developed with greater light absorption in the red and near-infrared. Many dyes have been tested for this purpose; however, no dye with significant absorption beyond 750 nm has functioned properly. We have examined a series of ruthenium phthalocyanines, a dye class with large and tunable absorption in the red. For these dyes we observe a large reduction in the output voltage of the cells relative to the benchmark dye (N719). By examination of photovoltage transients and charge density measurements, we demonstrate that this reduction in voltage is caused by a 100-fold increase in the rate constant for recombination (iodine reduction) at the TiO2/electrolyte interface. N719, however, does not seem to catalyze this reaction. By examination of the literature, we propose that catalysis of the recombination reaction may be occurring for many other classes of potentially useful dyes including porphyri.
Mycoloop: chytrids in aquatic food webs

Parasites are ecologically significant in various ecosystems through their role in shaping food web structure, facilitating energy transfer, and controlling disease. Here in this review, we mainly focus on parasitic chytrids, the dominant parasites in aquatic ecosystems, and explain their roles in aquatic food webs, particularly as prey for zooplankton. Chytrids have a free-living zoosporic stage, during which they actively search for new hosts. Zoospores are excellent food for zooplankton in terms of size, shape, and nutritional quality. In the field, densities of chytrids can be high, ranging from 101 to 109 spores L−1. When large inedible phytoplankton species are infected by chytrids, nutrients within host cells are transferred to zooplankton via the zoospores of parasitic chytrids. This new pathway, the “mycoloop,” may play an important role in shaping aquatic ecosystems, by altering sinking fluxes or determining system stability. The grazing of zoospores by zooplankton may also suppress outbreaks of parasitic chytrids. A food web model demonstrated that the contribution of the mycoloop to zooplankton production increased with nutrient availability and was also dependent on the stability of the system. Further studies with advanced molecular tools are likely to discover greater chytrid diversity and evidence of additional mycoloops in lakes and oceans.
A subpopulation of B220+ cells in murine bone marrow does not express CD19 and contains natural killer cell progenitors

Bone marrow of both normal and rearrangement-deficient mice contains a small population of B220(CD45R)+ cells, which do not express the B lineage marker CD19. Instead, part of this population coexpresses the surface marker CD43 and lacks or expresses very low levels of heat stable antigen (HSA) and BP-1, thus representing a part of Hardy's fraction A (B220(+)-CD43+HSA-, BP-1-) of B lineage development. However, some 20-40% of these B220(+)-CD19- cells also coexpress the NK1.1 surface molecule and do not express genes like VpreB or B29 restricted to the B cell lineage. These cells respond to recombinant interleukin 2 in vitro, and develop into killer cells that can lyse the prototypic NK target tumor cell, YAC-1, as well as syngeneic normal lipopolysaccharide or concanavalin A blasts, providing they lack the surface expression of major histocompatibility complex class I molecules. The implications of these findings for studies on B lymphopoiesis are discussed. It is suggested that the CD19-specific monoclonal antibody is more reliable, as in humans, than B220(CD45R) to detect B lineage cells in mice.
Training Deep Convolutional Neural Networks for Land–Cover Classification of High-Resolution Imagery

Deep convolutional neural networks (DCNNs) have recently emerged as a dominant paradigm for machine learning in a variety of domains. However, acquiring a suitably large data set for training DCNN is often a significant challenge. This is a major issue in the remote sensing domain, where we have extremely large collections of satellite and aerial imagery, but lack the rich label information that is often readily available for other image modalities. In this letter, we investigate the use of DCNN for land–cover classification in high-resolution remote sensing imagery. To overcome the lack of massive labeled remote-sensing image data sets, we employ two techniques in conjunction with DCNN: transfer learning (TL) with fine-tuning and data augmentation tailored specifically for remote sensing imagery. TL allows one to bootstrap a DCNN while preserving the deep visual feature extraction learned over an image corpus from a different image domain. Data augmentation exploits various aspects of remote sensing imagery to dramatically expand small training image data sets and improve DCNN robustness for remote sensing image data. Here, we apply these techniques to the well-known UC Merced data set to achieve the land–cover classification accuracies of 97.8 ± 2.3%, 97.6 ± 2.6%, and 98.5 ± 1.4% with CaffeNet, GoogLeNet, and ResNet, respectively.
Patient-derived xenograft models: an emerging platform for translational cancer research.

UNLABELLED Recently, there has been an increasing interest in the development and characterization of patient-derived tumor xenograft (PDX) models for cancer research. PDX models mostly retain the principal histologic and genetic characteristics of their donor tumor and remain stable across passages. These models have been shown to be predictive of clinical outcomes and are being used for preclinical drug evaluation, biomarker identification, biologic studies, and personalized medicine strategies. This article summarizes the current state of the art in this field, including methodologic issues, available collections, practical applications, challenges and shortcomings, and future directions, and introduces a European consortium of PDX models. SIGNIFICANCE PDX models are increasingly used in translational cancer research. These models are useful for drug screening, biomarker development, and the preclinical evaluation of personalized medicine strategies. This review provides a timely overview of the key characteristics of PDX models and a detailed discussion of future directions in the field.
Network, personality and social capital

We present a study on the relationship between social network structure on Facebook and social capital, and how this relationship is moderated by personality traits. The findings suggest that one's number of friends does not necessarily have an effect on the amount of bridging social capital. Conversely, the extent of structural holes and isolated friends in the network have an effect on bridging social capital. In addition, individuals low on agreeableness benefit more from isolated friends in terms of bridging social capital. In terms of bonding social capital, introverts benefit more from networks with higher transitivity. Women overall report higher bonding social capital, but there are no significant gender differences when it comes to leveraging one's network structure for bridging or bonding social capital.
Gas Emissivity of a Modified Cellulose Mix at the Temperature of 900°C

This paper presents the findings of a study of gas emissivity and the volumetric gas flow rate from a patented modified cellulose mix used in production of disposable sand casting moulds. The modified cellulose mix with such additives as expanded perlite, expanded vermiculite and microspheres was used as the study material. The results for gas emissivity and the gas flow rate for the modified cellulose mix were compared with the gas emissivity of the commercial material used in gating systems in disposable sand casting moulds. The results have shown that the modified cellulose mix is characterized by a lower gas emissivity by as much as 50% and lower gas flow rate per unit mass during the process of thermal degradation at the temperature of 900°C, compared to the commercial mix. It was also noted that the amount of microspheres considerably affected the amount of gas produced
No Bad Dogs: Ethological Lessons for Learning in Hamsterdam*

We present an architecture for autonomous creatures that allows learning to be combined with action selection, based on ideas from ethology. We show how temporal-difference learning may be used within the context of an ethologically inspired animat architecture to build and modify portions of the behavior network, and to set fundamental parameters including the strength associated with individual Releasing Mechanisms, the time course associated with appetitive behaviors, and the learning rates to be used based on the observed reliability of specific contingencies. The learning algorithm has been implemented as part of the Hamsterdam toolkit for building autonomous animated creatures. When implemented in Silas, a virtual dog, the algorithm enables Silas to be trained using classical and instrumental conditioning.
Management of Premature Rupture of Membranes and Unfavorable Cervix in Term Pregnancy

One hundred thirty-four indigent patients at term who had premature rupture of membranes and a cervix unfavorable for induction of labor (80% effacement or less, 2 cm dilation or less) were randomized to compare expectant with intervention management. Women with any medical or obstetric condition warranting immediate intervention were excluded from the study. Patients treated expectantly were placed at bed rest and observed for labor or infection. Patients managed by intervention were given oxytocin if labor did not ensue within 12 hours of rupture of the membranes. Patients in the intervention protocol had longer labor (P<.02) and a higher incidence of both cesarean delivery (P<.05) and intraamniotic infection (P<.05). There was only one case of proven neonatal sepsis, and this occurred in a patient managed by induction of labor. There was no statistically significant difference between groups in mean length of maternal hospitalization.
Genetic basis of olfactory cognition: extremely high level of DNA sequence polymorphism in promoter regions of the human olfactory receptor genes revealed using the 1000 Genomes Project dataset

The molecular mechanism of olfactory cognition is very complicated. Olfactory cognition is initiated by olfactory receptor proteins (odorant receptors), which are activated by olfactory stimuli (ligands). Olfactory receptors are the initial player in the signal transduction cascade producing a nerve impulse, which is transmitted to the brain. The sensitivity to a particular ligand depends on the expression level of multiple proteins involved in the process of olfactory cognition: olfactory receptor proteins, proteins that participate in signal transduction cascade, etc. The expression level of each gene is controlled by its regulatory regions, and especially, by the promoter [a region of DNA about 100–1000 base pairs long located upstream of the transcription start site (TSS)]. We analyzed single nucleotide polymorphisms using human whole-genome data from the 1000 Genomes Project and revealed an extremely high level of single nucleotide polymorphisms in promoter regions of olfactory receptor genes and HLA genes. We hypothesized that the high level of polymorphisms in olfactory receptor promoters was responsible for the diversity in regulatory mechanisms controlling the expression levels of olfactory receptor proteins. Such diversity of regulatory mechanisms may cause the great variability of olfactory cognition of numerous environmental olfactory stimuli perceived by human beings (air pollutants, human body odors, odors in culinary etc.). In turn, this variability may provide a wide range of emotional and behavioral reactions related to the vast variety of olfactory stimuli.
Defining perfect location privacy using anonymization

The popularity of mobile devices and location-based services (LBS) has created great concerns regarding the location privacy of users of such devices and services. Anonymization is a common technique that is often being used to protect the location privacy of LBS users. In this paper, we provide a general information theoretic definition for location privacy. In particular, we define perfect location privacy. We show that under certain conditions, perfect privacy is achieved if the pseudonyms of users are changed before O(N(2/r-1)) observations by the adversary, where N is the number of users and r is the number of sub-regions or locations.
Pollen grains as allergenic environmental factors--new approach to the forecasting of the pollen concentration during the season.

INTRODUCTION AND OBJECTIVES It is important to monitor the threat of allergenic pollen during the whole season, because of practical application in allergic rhinitis treatment, especially in the specific allergen immunotherapy. The aim of the study was to propose the forecast models predicting the pollen occurrence in the defined pollen concentration categories related to the patient exposure and symptom intensity. MATERIAL AND METHODS The study was performed in Cracow (southern Poland), pollen data were collected using the volumetric method in 1991-2012. For all independent variables (meteorological elements) and the daily pollen concentrations the running mean for periods: 2-, 3-, 4-, 5-, 6- and 7 days before the predicted day were calculated. The multinomial logistic regression was used to find the relation between the probability of the pollen concentration occurrence in the selected categories and meteorological elements and pollen concentration in days preceding the predicted daily concentration. The models were constructed for each taxon using data in 1991-2011 (without 1992 and 1996 due to missing data in these years) and 1998-2011 pollen seasons. RESULTS The days classified among the lowest category (0-10 PG/m3) (pollen grains/m 3 of air) dominated for all the studied taxa. The percentage of the obtained predictions of the pollen occurrence fluctuated between 35-78% which is a sufficient value of model predictions. Considering the studied taxon, the best model accuracy was obtained for models forecasting Betula pollen concentration (both data series), and Poaceae (both data series). CONCLUSIONS The application of the recommended threshold values during the predictive models construction seems to be really useful to estimate the real threat of allergen exposure. It was indicated that the polynomial logistic regression models could be a practical tool for effective forecasting in biological monitoring of pollen exposure.
The Effects of Augmented Reality-based Otago Exercise on Balance, Gait, and Falls Efficacy of Elderly Women

[Purpose] The purpose of this study was to determine the effects of augmented reality-based Otago exercise on balance, gait, and falls efficacy of elderly women. [Subjects] The subjects were 21 elderly women, who were randomly divided into two groups: an augmented reality-based Otago exercise group of 10 subjects and an Otago exercise group of 11 subjects. [Methods] All subjects were evaluated for balance (Berg Balance Scale, BBS), gait parameters (velocity, cadence, step length, and stride length), and falls efficacy. Within 12 weeks, Otago exercise for muscle strengthening and balance training was conducted three times, for a period of 60 minutes each, and subjects in the experimental group performed augmented reality-based Otago exercise. [Results] Following intervention, the augmented reality-based Otago exercise group showed significant increases in BBS, velocity, cadence, step length (right side), stride length (right side and left side) and falls efficacy. [Conclusion] The results of this study suggest the feasibility and suitability of this augmented reality-based Otago exercise for elderly women.
Randomized Trial of Mycophenolate Mofetil Versus Enteric-Coated Mycophenolate Sodium in Primary Renal Transplantation With Tacrolimus and Steroid Avoidance: Four-Year Analysis

Background. Our single-center, open-labeled randomized trial of 150 adult, primary kidney transplant recipients receiving 2 g mycophenolate mofetil (group A, n=75) versus 1.440 g enteric-coated mycophenolate sodium (group B, n=75), with reduced maintenance tacrolimus dosing, steroid elimination at 1 week, and combined rabbit antithymocyte globulin/daclizumab induction, previously showed at 1 year posttransplant low biopsy-proven acute rejection (BPAR), acceptably high renal function, and no differences in incidence of symptomatic gastrointestinal (GI) side effects between the two groups. This report includes 3 additional years of follow-up with similar endpoints as in the original study. Methods. Rates of developing first BPAR, graft failure (death censored and uncensored), death, and adverse events (GI toxicity, infections requiring hospitalization, and new onset diabetes mellitus after transplantation) during the first 48 months posttransplant were compared between the two groups using an intent-to-treat approach. Results. At 48 months posttransplant, patient/graft survival in groups A and B was 97%/90% vs. 96%/86%, respectively (not significant [NS]). Twenty-seven patients experienced BPAR (including borderline), with actuarial 19% (14/75) vs. 18% (13/75) in groups A and B, respectively (NS). Geometric mean*/standard error serum creatinine level and arithmetic mean calculated glomerular filtration rate (±standard error) at 48 months in groups A and B, respectively, were 1.25*/1.06 and 69.2±3.9 vs. 1.20*/1.05 and 71.2±3.2 (NS). Incidence of new onset diabetes mellitus after transplantation (22% vs. 15%), infections requiring hospitalization (31% vs. 39%), and GI side effects (45% vs. 52%) seemed equivalent. Conclusions. This is the first long-term, randomized trial comparing enteric-coated mycophenolate sodium versus mycophenolate mofetil along with reduced maintenance tacrolimus dosing and steroid avoidance, which resulted in similarly low-BPAR rates, acceptably high renal function at 48 months, and an equivalent side effect profile.