Miracle-dz/UniFAR-FTUs huggingface dataset:
EEG/MEG source imaging using fMRI informed time‐variant constraints

Multimodal functional neuroimaging by combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) or magnetoencephalography (MEG) is able to provide high spatiotemporal resolution mapping of brain activity. However, the accuracy of fMRI‐constrained EEG/MEG source imaging may be degraded by potential spatial mismatches between the locations of fMRI activation and electrical source activities. To address this problem, we propose a novel fMRI informed time‐variant constraint (FITC) method. The weights in FITC are determined by combining the fMRI activities and electrical source activities in a time‐variant manner to reduce the impact of the fMRI extra sources. The fMRI weights are modified using cross‐talk matrix and normalized partial area under the curve to reduce the impact of fMRI missing sources. Monte Carlo simulations were performed to compare the source estimates produced by L2‐minimum norm estimation (MNE), fMRI‐weighted minimum norm estimation (fMNE), FITC, and depth‐weighted FITC (wFITC) algorithms with various spatial mismatch conditions. Localization error and temporal correlation were calculated to compare the four algorithms under different conditions. The simulation results indicated that the FITC and wFITC methods were more robust than the MNE and fMNE algorithms. Moreover, FITC and wFITC were significantly better than fMNE under the fMRI missing sources condition. A human visual‐stimulus EEG, MEG, and fMRI test was performed, and the experimental data revealed that FITC and wFITC displayed more focal areas than fMNE and MNE. In conclusion, the proposed FITC method is able to better resolve the spatial mismatch problems encountered in fMRI‐constrained EEG/MEG source imaging.
The Neuronal Calcium Sensor Protein Acrocalcin: A Potential Target of Calmodulin Regulation during Development in the Coral Acropora millepora

To understand the calcium-mediated signalling pathways underlying settlement and metamorphosis in the Scleractinian coral Acropora millepora, a predicted protein set derived from larval cDNAs was scanned for the presence of EF-hand domains (Pfam Id: PF00036). This approach led to the identification of a canonical calmodulin (AmCaM) protein and an uncharacterised member of the Neuronal Calcium Sensor (NCS) family of proteins known here as Acrocalcin (AmAC). While AmCaM transcripts were present throughout development, AmAC transcripts were not detected prior to gastrulation, after which relatively constant mRNA levels were detected until metamorphosis and settlement. The AmAC protein contains an internal CaM-binding site and was shown to interact in vitro with AmCaM. These results are consistent with the idea that AmAC is a target of AmCaM in vivo, suggesting that this interaction may regulate calcium-dependent processes during the development of Acropora millepora.
Democratic Population Decisions Result in Robust Policy-Gradient Learning: A Parametric Study with GPU Simulations

High performance computing on the Graphics Processing Unit (GPU) is an emerging field driven by the promise of high computational power at a low cost. However, GPU programming is a non-trivial task and moreover architectural limitations raise the question of whether investing effort in this direction may be worthwhile. In this work, we use GPU programming to simulate a two-layer network of Integrate-and-Fire neurons with varying degrees of recurrent connectivity and investigate its ability to learn a simplified navigation task using a policy-gradient learning rule stemming from Reinforcement Learning. The purpose of this paper is twofold. First, we want to support the use of GPUs in the field of Computational Neuroscience. Second, using GPU computing power, we investigate the conditions under which the said architecture and learning rule demonstrate best performance. Our work indicates that networks featuring strong Mexican-Hat-shaped recurrent connections in the top layer, where decision making is governed by the formation of a stable activity bump in the neural population (a “non-democratic” mechanism), achieve mediocre learning results at best. In absence of recurrent connections, where all neurons “vote” independently (“democratic”) for a decision via population vector readout, the task is generally learned better and more robustly. Our study would have been extremely difficult on a desktop computer without the use of GPU programming. We present the routines developed for this purpose and show that a speed improvement of 5x up to 42x is provided versus optimised Python code. The higher speed is achieved when we exploit the parallelism of the GPU in the search of learning parameters. This suggests that efficient GPU programming can significantly reduce the time needed for simulating networks of spiking neurons, particularly when multiple parameter configurations are investigated.
Serious games for effective learning

This paper presented researches in serious games for learning. The old issue of using digital games simply because it is the latest technology which led to the "chocolate-covered broccoli" phenomenon is addressed by designing an adaptive component of the game as a representation of learning materials and learning experience to provide challenge. Implementing game design motivational model is another approach to developing effective serious game. Game modding and visual approach on the other hand help students to learn difficult subjects such as programming.
Macroinvertebrate identity mediates the effects of litter quality and microbial conditioning on leaf litter recycling in temperate streams

Abstract Plant litter decomposition is an essential ecosystem function that contributes to carbon and nutrient cycling in streams. Aquatic shredders, mainly macroinvertebrates, can affect this process in various ways; they consume leaf litter, breaking it down into fragments and creating suitable habitats or resources for other organisms through the production of fine particulate organic matter (FPOM). However, measures of litter‐feeding traits across a wide range of aquatic macroinvertebrates are still rare. Here, we assessed the contributions of 11 species of freshwater macroinvertebrates to litter decomposition, by measuring consumption rate, FPOM production, and assimilation rate of highly decomposable (Alnus glutinosa) or poorly decomposable (Quercus robur) leaf litter types. In general, an increase in the quality of litter improved the litter consumption rate, and fungal conditioning of the leaf litter increased both the litter consumption rate and FPOM production. Macroinvertebrates specializing in leaf litter consumption also appeared to be the most sensitive to shifts in litter quality and the conditioning process. Contrary to expectations, the conditioning process did not increase the assimilation of low‐quality litter. There was a strong correlation between the relative consumption rate (RCR) of the two litter types, and the relative FPOM production (RFP) was strongly correlated to the RCR. These findings suggest a consistent relationship between RCR and macroinvertebrate identity that is not affected by litter quality, and that the RFP could be inferred from the RCR. The varying responses of the macroinvertebrate feeding traits to litter quality and the conditioning process suggest that the replacement of a shredder invertebrate species by another species could have major consequences for the decomposition process and the detritus‐based food web in streams. Further studies onto the importance of invertebrate identity and the effects of litter quality in a variety of freshwater ecosystems are needed to understand the whole ecosystem functioning and to predict its response to environmental changes.
SOD2 gene polymorphism and response of oxidative stress parameters in young wrestlers to a three-month training

Abstract The aim of the study was to analyse the effect of Val 16Ala polymorphism in SOD2 gene on oxidative stress parameters and lipid profile of the blood during a three-month wrestling training. The study included 53 Polish young wrestlers. Blood samples were collected at the beginning of the programme and following three months of the training. The list of analysed parameters included erythrocyte and serum activities of superoxide dismutase (SOD), whole blood glutathione peroxidase (GPx) activity, total glutathione (tGSH) level, concentration of lipid hydroperoxides (LHs), total antioxidant capacity (TAC) and creatine kinase (CK) activity in the serum, as well as lipid profile parameters: triglycerides (TG), total cholesterol (TC), high-density (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Three-month training resulted in a decrease in CK activity, an increase in serum SOD activity, as well as in unfavourable changes in serum lipid profile: an increase in TC, LDL-C, and TG, and a decrease in HDL-C. Aside from CK activity, all these changes seemed to be associated with presence of Val allele. Prior to the training programme, subjects with Ala/Ala genotype presented with lower levels of LHs, lower whole blood GPx activity, and lower serum concentrations of TC than the individuals with Ala/Val genotype. Both prior to and after three-month training, higher levels of tGSH were observed in Val/Val genotype as compared to Ala/Val genotype carriers. Moreover, multiple regression analysis demonstrated that SOD2 genotype was a significant predictor of pre-training whole blood GPx activity and erythrocyte SOD activity (Val/Val > Ala/Val > Ala/Ala). Altogether, these findings suggest that Val 16Ala polymorphism in SOD2 gene contributes to individual variability in oxidative stress status and lipid profile of the blood in young wrestlers, and may modulate biochemical response to training.
The impact of population growth and climate change on food security in Africa: looking ahead to 2050

ABSTRACT Providing nutritious and environmentally sustainable food to all people at all times is one of the greatest challenges currently facing society. This problem is particularly acute in Africa where an estimated one in four people still lack adequate food to sustain an active and healthy life. In this study, we consider the potential impact of future population growth and climate change on food security in Africa, looking ahead to 2050. A modelling framework termed FEEDME (Food Estimation and Export for Diet and Malnutrition Evaluation) was used which was characterized to model the impacts of future climate changes (utilizing the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios projections) and projected population growth on food availability and subsequent undernourishment prevalence in 44 African countries. Our results indicate that projected rapid population growth will be the leading cause of food insecurity and widespread undernourishment across Africa. Very little to no difference in undernourishment projections were found when we examined future scenarios with and without the effects of climate change, suggesting population growth is the dominant driver of change. Various adaptation options are discussed, such as closing the yield gap via sustainable intensification and increasing imports through trade and aid agreements. These strategies are likely to be critical in preventing catastrophic future food insecurity.
Acoustic holography of piezoelectric materials by Coulomb excitation

Electric surface excitation of ultrasound in the Coulomb field of scanned electrically conductive spherical local probes and similar detection has been employed for imaging of the transport properties of acoustic waves in piezoelectric materials including singlecrystalline wafers. The employed Coulomb scheme leads to a fully predictable and almost ideal point excitation and detection. In combination with two-channel quadrature transient detection it allows high precision spatially and temporally resolved holographic imaging. Via modeling of the excitation and propagation properties, the effective elastic tensor and the piezoelectric properties of the observed materials can be determined with high resolution from a single measurement. The generation and detection scheme as well as the theoretical background are demonstrated and applications are exemplified.
Men and Masculinity in Men ’ s Stylish

This paper discusses qualitative findings from a series of focus group discussions with six adult Malaysian men, aged 24-34, on the representation of men and masculinity in Men’s Folio, a stylish lifestyle men’s magazine. It highlights the extent to which the language used in the magazine’s editorial content and advertisements that feature musculature images, fashion and style, and feminized grooming products and practices that have diversed impacts on the respondents’ notions of a modern male identity.
Green Tea Consumption and the Risk of Liver Cancer: A Meta-Analysis

ABSTRACT Green tea is a commonly consumed beverage in Asia and has been suggested to have anticarcinogenic properties. To date, epidemiological evidence of the effect of green tea consumption on liver cancer risk remains ambiguous. The aim of this meta-analysis is to evaluate the association between green tea consumption and the risk of liver cancer. The summary relative risk for the highest consumption (≥5 cups/day) of green tea on liver cancer incidence compared with nondrinkers was 0.62 (95% confidence interval: 0.49–0.79). We also found a trend that the incidence of liver cancer was reduced with the increasing years of green tea intake (significance at >20 yr). A significant dose–response association was found between green tea drinking and liver cancer risk. The downward trend was most obvious when the consumption of green tea increased up to about 4 cups/day. The results showed that the increasing green tea intake may have a preventive effect against liver cancer.
Metabolomic data suggest regulation of black howler monkey (Alouatta pigra) diet composition at the molecular level

In addition to macronutrients, foods consist of a complex set of chemical compounds that can influence dietary selectivity and consumer physiology. Metabolomics allow us to describe this complexity by quantifying all small molecules, or metabolites, in a food item. In this study we use GC‐MS based metabolomics to describe the metabolite profiles of foods consumed by one population of Mexican black howler monkeys (Alouatta pigra) over a 10‐month period. Our data indicate that each food exhibited a distinct metabolite profile, and the average weekly intake of metabolites such as neochlorogenic acid and serotonin (5‐hydroxytryptamine) was correlated with the consumption of certain plant parts. We speculate that these patterns result in temporal changes in howler monkey physiology such as food retention time. In contrast, variation in the weekly intake of metabolites such as oxalic acid was 70% less than variation in the concentration of the same metabolites across food items, suggesting that howler monkeys regulated the intake of these metabolites, possibly to avoid physiological consequences such as kidney stone formation. Finally, seasonal variation in the consumption of individual nutrient and non‐nutrient metabolites were correlated with changes in the relative abundances of associated gut microbial taxa, implying indirect effects of food item metabolites on howler monkey nutritional ecology that likely drive foraging decisions. While additional research is needed to validate these findings, the patterns we report serve as important baseline data for understanding the effects of plant metabolites on the food choice in primates.
Recovery of ego-motion using image stabilization

A method for computing the 3D camera motion (the ego-motion) in a static scene is introduced, which is based on computing the 2D image motion of a single image region directly from image intensities. The computed image motion of this image region is used to register the images so that the detected image region appears stationary. The resulting displacement field for the entire scene between the registered frames is affected only by the 3D translation of the camera. After canceling the effects of the camera rotation by using such 2D image registration, the 3D camera translation is computed by finding the focus-of-expansion in the translation-only set of registered frames. This step is followed by computing the camera rotation to complete the computation of the ego-motion. The presented method avoids the inherent problems in the computation of optical flow and of feature matching, and does not assume any prior feature detection or feature correspondence. <<ETX>>
Genome-wide association study identifies seven novel susceptibility loci for primary open-angle glaucoma

Primary open-angle glaucoma (POAG) is the leading cause of irreversible blindness worldwide for which 15 disease-associated loci had been discovered. Among them, only 5 loci have been associated with POAG in Asians. We carried out a genome-wide association study and a replication study that included a total of 7378 POAG cases and 36 385 controls from a Japanese population. After combining the genome-wide association study and the two replication sets, we identified 11 POAG-associated loci, including 4 known (CDKN2B-AS1, ABCA1, SIX6 and AFAP1) and 7 novel loci (FNDC3B, ANKRD55-MAP3K1, LMX1B, LHPP, HMGA2, MEIS2 and LOXL1) at a genome-wide significance level (P < 5.0×10-8), bringing the total number of POAG-susceptibility loci to 22. The 7 novel variants were subsequently evaluated in a multiethnic population comprising non-Japanese East Asians (1008 cases, 591 controls), Europeans (5008 cases, 35 472 controls) and Africans (2341 cases, 2037 controls). The candidate genes located within the new loci were related to ocular development (LMX1B, HMGA2 and MAP3K1) and glaucoma-related phenotypes (FNDC3B, LMX1B and LOXL1). Pathway analysis suggested epidermal growth factor receptor signaling might be involved in POAG pathogenesis. Genetic correlation analysis revealed the relationships between POAG and systemic diseases, including type 2 diabetes and cardiovascular diseases. These results improve our understanding of the genetic factors that affect the risk of developing POAG and provide new insight into the genetic architecture of POAG in Asians.
Blood-Based Gene Expression in children with Autism spectrum disorder

Comparative gene expression profiling analysis is useful in discovering differentially expressed genes associated with various diseases, including mental disorders. Autism spectrum disorder (ASD) is a severe neuropsychiatric disorder which has complex pathobiology with profound influences of genetic factors in its development. Although numerous autism susceptible genes were identified, the etiology of autism is not fully explained. The study aimed to examine gene expression profiling in peripheral blood from 60 individuals divided into two groups: children with ASD and age- and gender-matched healthy subjects (ASD control). A genome-wide sequencing of copy DNA molecules was conducted to obtain information for quantitative expression of all genes subject to this study and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway-based analysis was used to further understand genes' biological functions. Based on the conducted expression analysis 23 differentially expressed genes and 21 KEGG signaling pathways with statistical significant change were identified. Blood- based comparative gene expression profiling analysis is useful in discovering genetic markers associated with ASD. Our data will provide a valuable resource for discovery purposes and for comparison to other gene expression-based, genome-wide studies and other functional data.
Satisfying Complex Data Needs using Pull-Based Online Monitoring of Volatile Data Sources

Emerging applications on the Web require better management of volatile data in pull-based environments. In a pull based setting, data may be periodically removed from the server. Data may also become obsolete, no longer serving client needs. In both cases, we consider such data to be volatile. To model such constraints on data usability, and support complex user needs we define profiles to specify which data sources are to be monitored and when. Using a novel abstraction of execution intervals we model complex profiles that access simultaneously several servers to gain from the used data. Given some budgetary constraints (e.g., bandwidth), the paper formalizes the problem of maximizing completeness.
The first complete mitochondrial genome of the Pundamilia nyererei

Abstract Pundamilia nyererei, a member of the family cichlid lived in individual African lakes, regarded as a significant evolution model. Recently the genome sequencing had been done, but no more information of its mitochondrial reported. Herein, we first assembled the complete mitochondrial genome sequence of Pundamilia nyererei. It is a 16 758 bp long sequence with most mitogenome’s characteristic structure, 13 protein-coding genes, 20 of tRNA genes, two of rRNA genes, and one putative control region. The GC-content of our fresh sequence is 45.24%, similar to closely related species Oreochromis niloticus. It can verify the accuracy and the utility of new determined mitogenome sequences by the phylogenetic analysis, based on whole mitogenome alignment with Dimidiochromis compressiceps, which is closest relative to Pundamilia nyererei, and seven others. We expect that using the full mitogenome to address taxonomic issues and study the related evolution events. Moreover, this is the first report of the mitogenome of genus Pundamilia nyererei.
Phosphorylation of 4E-BP1 in the Mammalian Brain Is Not Altered by LRRK2 Expression or Pathogenic Mutations

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene are a common cause of autosomal dominant familial Parkinson's disease (PD). LRRK2 encodes a multi-domain protein containing GTPase and kinase enzymatic domains. Disease-associated mutations in LRRK2 variably influence enzymatic activity with the common G2019S variant leading to enhanced kinase activity. Mutant LRRK2 induces neuronal toxicity through a kinase-dependent mechanism suggesting that kinase activity is important for mediating the pathogenic effects of LRRK2 mutations. A number of LRRK2 kinase substrates have been identified in vitro but whether they represent authentic physiological substrates in mammalian cells or tissues is not yet clear. The eukaryotic initiation factor 4E (eIF4E)-binding protein, 4E-BP1, was recently identified as a potential substrate of LRRK2 kinase activity in vitro and in Drosophila with phosphorylation occurring at Thr37 and Thr46. Here, we explore a potential interaction of LRRK2 and 4E-BP1 in mammalian cells and brain. We find that LRRK2 can weakly phosphorylate 4E-BP1 in vitro but LRRK2 overexpression is not able to alter endogenous 4E-BP1 phosphorylation in mammalian cells. In mammalian neurons LRRK2 and 4E-BP1 display minimal co-localization, whereas the subcellular distribution, protein complex formation and covalent post-translational modification of endogenous 4E-BP1 are not altered in the brains of LRRK2 knockout or mutant LRRK2 transgenic mice. In the brain, the phosphorylation of 4E-BP1 at Thr37 and Thr46 does not change in LRRK2 knockout or mutant LRRK2 transgenic mice, nor is 4E-BP1 phosphorylation altered in idiopathic or G2019S mutant PD brains. Collectively, our results suggest that 4E-BP1 is neither a major nor robust physiological substrate of LRRK2 in mammalian cells or brain.