Miracle-dz/UniFAR-FTUs huggingface dataset:
Motor Cortex Encodes A Temporal Difference Reinforcement Learning Process

Temporal difference reinforcement learning (TDRL) accurately models associative learning observed in animals, where they learn to associate outcome predicting environmental states, termed conditioned stimuli (CS), with the value of outcomes, such as rewards, termed unconditioned stimuli (US). A component of TDRL is the value function, which captures the expected cumulative future reward from a given state. The value function can be modified by changes in the animal’s knowledge, such as by the predictability of its environment. Here we show that primary motor cortical (M1) neurodynamics reflect a TD learning process, encoding a state value function and reward prediction error in line with TDRL. M1 responds to the delivery of reward, and shifts its value related response earlier in a trial, becoming predictive of an expected reward, when reward is predictable due to a CS. This is observed in tasks performed manually or observed passively, as well as in tasks without an explicit CS predicting reward, but simply with a predictable temporal structure, that is a predictable environment. M1 also encodes the expected reward value associated with a set of CS in a multiple reward level CS-US task. Here we extend the Microstimulus TDRL model, reported to accurately capture RL related dopaminergic activity, to account for M1 reward related neural activity in a multitude of tasks. Significance statement There is a great deal of agreement between aspects of temporal difference reinforcement learning (TDRL) models and neural activity in dopaminergic brain centers. Dopamine is know to be necessary for sensorimotor learning induced synaptic plasticity in the motor cortex (M1), and thus one might expect to see the hallmarks of TDRL in M1, which we show here in the form of a state value function and reward prediction error during. We see these hallmarks even when a conditioned stimulus is not available, but the environment is predictable, during manual tasks with agency, as well as observational tasks without agency. This information has implications towards autonomously updating brain machine interfaces as others and we have proposed and published on.
Internal and External Dispersal of Plants by Animals: An Aquatic Perspective on Alien Interference

Many alien plants use animal vectors for dispersal of their diaspores (zoochory). If alien plants interact with native disperser animals, this can interfere with animal-mediated dispersal of native diaspores. Interference by alien species is known for frugivorous animals dispersing fruits of terrestrial plants by ingestion, transport and egestion (endozoochory). However, less attention has been paid to possible interference of alien plants with dispersal of diaspores via external attachment (ectozoochory, epizoochory or exozoochory), interference in aquatic ecosystems, or positive effects of alien plants on dispersal of native plants. This literature study addresses the following hypotheses: (1) alien plants may interfere with both internal and external animal-mediated dispersal of native diaspores; (2) interference also occurs in aquatic ecosystems; (3) interference of alien plants can have both negative and positive effects on native plants. The studied literature revealed that alien species can comprise large proportions of both internally and externally transported diaspores. Because animals have limited space for ingested and adhering diaspores, alien species affect both internal and external transport of native diaspores. Alien plant species also form large proportions of all dispersed diaspores in aquatic systems and interfere with dispersal of native aquatic plants. Alien interference can be either negative (e.g., through competition with native plants) or positive (e.g., increased abundance of native dispersers, changed disperser behavior or attracting additional disperser species). I propose many future research directions, because understanding whether alien plant species disrupt or facilitate animal-mediated dispersal of native plants is crucial for targeted conservation of invaded (aquatic) plant communities.
Brain Tumor Segmentation

Tumor is an uncontrolled growth of tissues in any part of the body. Tumors are of different types and they have different characteristics and different treatment. As it is known, brain tumor is inherently serious and life threatening. Brain tumor analysis is done by doctors but its grading gives different conclusion which may vary from one doctor to another. However this method of detection resists the accurate determination of size of tumor. To avoid that, uses computer aided method for segmentation of brain tumor based on the combination of three algorithms. This algorithm allows the segmentation of tumor tissue with accuracy comparable to manual segmentation. It also reduces time analysis. At the end of the process the tumor is extracted for MR image and its exact position and its shape is also determined.
A multipage cell architecture for high-speed programming multilevel NAND flash memories

To realize low-cost, highly reliable, high-speed programming, and high-density multilevel flash memories, a multipage cell architecture has been proposed. This architecture enables both precise control of the V/sub th/ of a memory cell and fast programming without any area penalty. In the case of a four-level cell, a high programming speed of 236 /spl mu/s/512 bytes or 2.2 Mbytes/s can be obtained, which is 2.3 times faster than the conventional method. A small die size can be achieved with the newly developed compact four-level column latch circuit. A preferential page select method has also been proposed so as to improve the data retention characteristics. The IC error rate can be decreased by as much as 33%, and a highly reliable operation can be realized.
Effects of pH and Salt Concentration on Stability of a Protein G Variant Using Coarse-Grained Models

The importance of charge-charge interactions in the thermal stability of proteins is widely known. pH and ionic strength play a crucial role in these electrostatic interactions, as well as in the arrangement of ionizable residues in each protein-folding stage. In this study, two coarse-grained models were used to evaluate the effect of pH and salt concentration on the thermal stability of a protein G variant (1PGB-QDD), which was chosen due to the quantity of experimental data exploring these effects on its stability. One of these coarse-grained models, the TKSA, calculates the electrostatic free energy of the protein in the native state via the Tanford-Kirkwood approach for each residue. The other one, CpHMD-SBM, uses a Coulomb screening potential in addition to the structure-based model Ca. Both models simulate the system in constant pH. The comparison between the experimental stability analysis and the computational results obtained by these simple models showed a good agreement. Through the TKSA method, the role of each charged residue in the protein’s thermal stability was inferred. Using CpHMD-SBM, it was possible to evaluate salt and pH effects throughout the folding process. Finally, the computational pKa values were calculated by both methods and presented a good level of agreement with the experiments. This study provides, to our knowledge, new information and a comprehensive description of the electrostatic contribution to protein G stability.
Modeling acute myeloid leukemia in a continuum of differentiation states

Here we present a mathematical model of movement in an abstract space representing states of cellular differentiation. We motivate this work with recent examples that demonstrate a continuum of cellular differentiation using single cell RNA sequencing data to characterize cellular states in a high-dimensional space, which is then mapped into ℝ2 or ℝ3 with dimension reduction techniques. We represent trajectories in the differentiation space as a graph, and model directed and random movement on the graph with partial differential equations. We hypothesize that flow in this space can be used to model normal differentiation processes as well as predict the evolution of abnormal differentiation processes such as those observed during pathogenesis of acute myeloid leukemia (AML).
YES1 amplification: a mechanism of acquired resistance to EGFR inhibitors identified by transposon mutagenesis and clinical genomics

In approximately 30% of patients with EGFR-mutant lung adenocarcinomas whose disease progresses on EGFR inhibitors, the basis for acquired resistance remains unclear. We have integrated transposon mutagenesis screening in an EGFR-mutant cell line and clinical genomic sequencing in cases of acquired resistance to identify novel mechanisms of resistance to EGFR inhibitors. The most prominent candidate genes identified by insertions in or near the genes during the screen were MET, a gene whose amplification is known to mediate resistance to EGFR inhibitors, and the gene encoding the Src family kinase YES1. Cell clones with transposon insertions that activated expression of YES1 exhibited resistance to all three generations of EGFR inhibitors and sensitivity to pharmacologic and siRNA-mediated inhibition of YES1. Analysis of clinical genomic sequencing data from cases of acquired resistance to EGFR inhibitors revealed amplification of YES1 in 5 cases, 4 of which lacked any other known mechanisms of resistance. Pre-inhibitor samples, available for 2 of the 5 patients, lacked YES1 amplification. None of 136 post-inhibitor samples had detectable amplification of other Src family kinases (SRC, FYN). YES1 amplification was also found in 2 of 17 samples from ALK fusion-positive lung cancer patients who had progressed on ALK TKIs. Taken together, our findings identify acquired amplification of YES1 as a novel, recurrent, and targetable mechanism of resistance to EGFR inhibition in EGFR-mutant lung cancers, and demonstrate the utility of transposon mutagenesis in discovering clinically relevant mechanisms of drug resistance. SIGNIFICANCE Despite high response rates to treatment with small molecule inhibitors of EGFR tyrosine kinase activity, patients with EGFR-mutant lung adenocarcinomas eventually develop resistance to these drugs. In many cases, the basis of acquired resistance remains unclear. We have used a transposon mutagenesis screen in an EGFR-mutant cell line and clinical genomic sequencing in cases of acquired resistance to identify amplification of YES1 as a novel and targetable mechanism of resistance to EGFR inhibitors in EGFR-mutant lung cancers.
New insights on adaptation and population structure of cork oak using genotyping by sequencing

Species respond to global climatic changes in a local context. Understanding this process is paramount due to the pace of these changes. Tree species are particularly interesting to study in this regard due to their long generation times, sedentarism, and ecological and economic importance. Quercus suber L. is an evergreen forest tree species of the Fagaceae family with an essentially Western Mediterranean distribution. Despite frequent assessments of the species’ evolutionary history, large-scale genetic studies have mostly relied on plastidial markers, whereas nuclear markers have been used on studies with locally focused sampling strategies. The potential response of Q. suber to global climatic changes has also been studied, under ecological modelling. In this work, “Genotyping by Sequencing” (GBS) is used to derive 2,547 SNP markers to assess the species’ evolutionary history from a nuclear DNA perspective, gain insights on how local adaptation may be shaping the species’ genetic background, and to forecast how Q. suber may respond to global climatic changes from a genetic perspective. Results reveal an essentially unstructured species, where a balance between gene flow and local adaptation keeps the species’ gene pool somewhat homogeneous across its distribution, but at the same time allows variation clines for the individuals to cope with local conditions. “Risk of Non-Adaptedness” (RONA) analyses, suggest that for the considered variables and most sampled locations, the cork oak does not require large shifts in allele frequencies to survive the predicted climatic changes. However, more research is required to integrate these results with those of ecological modelling.
Principal Component Analysis based Feature Vector Extraction

Objectives: A simple and efficient method is employed to extract feature vector from images and to reduce the dimension of data. Once the feature vectors are extracted, it can be used in face recognition module. Methods/Analysis: Principal Components Analysis (PCA) is used for face recognition technique for feature identification in large data sets and to highlight their similarities and differences is more essential step in face recognition. PCA is used as efficient tool in data analysis to reduce dimension and to obtain maximum variance of data. Findings: Experiment is conducted using Yale database B. The face images are formed with multiple factors on different lighting conditions, background interference, and face rotation etc. The experimental results on Yale database B are given to illustrate the proposed method. Conclusion/Application: A simple and effective feature extraction method is analyzed for face images and experimental results are shown.
Genome-based transmission modeling separates imported tuberculosis from recent transmission within an immigrant population

In many Western countries tuberculosis (TB) incidence is low and largely shaped by immigrant populations originating from high-burden countries. A variable latent period, low rates of evolution and structured social networks, makes separating repeated import from within-border transmission a major conundrum to TB-control efforts in many low-incidence countries. This is the case in Norway, where TB incidence dropped to very low levels during the second half of the 20th century (6 per 100,000 in 2016) and more than 80 per cent of TB cases are now found among immigrants from high-incidence countries. Immigrants from the Horn of Africa constitute the largest group of TB patients in Norway, making up a third of all TB cases in the country over the last decade. One particular genotype-cluster strongly associated with people originating in this region has been identified regularly over a 20-year period. Here we apply transmission modeling methods to whole-genome sequence data to estimate the times at which individual patients were originally infected. By contrasting these estimates with time of arrival in Norway, we estimate on a case-by-case basis whether individual patients were likely to have been infected before or after arrival. Although import was responsible for the majority of cases, we find that transmission is also occurring in Norway. Our approach is very broadly applicable and relevant to many settings where TB control programs can benefit from an understanding of when (and consequently where) individuals have acquired a tuberculosis infection.
Modeling acoustic-phonetic detail in an HMM-based large vocabulary speech recognizer

The acoustic recognizer of the INRS-Telecommunications 60000-word-vocabulary isolated-word recognition system is discussed. The task of the acoustic recognizer is to generate a list of word hypotheses and their likelihoods based on the acoustic data for each input word. Two sets of experiments are reported in which such knowledge is incorporated into the hidden Markov models (HMMs) used during recognition. In the first set, vowel duration properties are used in the HMMs. In the second set, word-initial and word-final stop consonants are modeled as a sequence of context-dependent subphonemes. The performance of the recognizer is significantly improved by appropriate utilization of the context-dependent vowel-duration information and the context-dependent microsegmental properties of stop consonants. <<ETX>>
A note on scheduling jobs with missing operations in permutation flow shops

Flowshop scheduling problems are usually handled as permutation flowshops because of computational complexity although the technical framework in realworld problems often allows that jobs pass each other. Having a missing operation of a job on a machine, this job passing becomes a natural way to process jobs unless the underlying system is not an inflexible flow-line. However, when scheduling, missing operations are usually handled as zero processing time operations not allowing for any job passing. It is shown that even permitting job passing for missing operations while keeping the permutation constraint improves total completion time only under rather specific circumstances. We propose 'partial permutation flowshop sequencing' to overcome these specific formal requirements with respect to the real-world problem setting.
Using mutual information for extractingbiclusters from gene expression data

With the advances in DNA microarray technology, expression levels of a large number of genes can be measured in parallel. This leads to generation of huge amount of gene expression data. Analysis of the microarray data to extract biologically significant information from it is a challenging task. Many people have used biclustering for this analysis. Most of these biclustering algorithms are based either on the Euclidean distance or correlation coefficient as the similarity measure. These measures capture only linear relationships between the genes but non linear dependencies may exist amongst them. Different measures are required to capture complete dependence (i.e. both linear and nonlinear). Mutual information provides a more general measure to investigate relationships (positive, negative correlation and non linear relationships as well). As it depends upon the distribution and not the actual values, no normalization of the data is required. It works well for both scaled and shifted data. The measure is also robust towards noise and outliers. In our work we propose a set of algorithms based on an approach using mutual information for extracting biclusters from gene expression data. To the best of our knowledge, none of the existing algorithms for biclustering have used mutual information as a similarity measure between two genes or conditions. Experiments were conducted on synthetic data and expression data of Arabidopsis thaliana, Saccharomyces cerevisiae, Human breast cancer data and Diffuse large B cell lymphoma data. We were able to extract the implanted biclusters from the synthetic datasets. On real datasets our experiments show the effectiveness of our algorithms in extracting biclusters from gene expression datasets. We used DAVID, an online biological tool for the validation of our biclusters. It was found that the obtained biclusters were biologically more significant as compared to the biclusters obtained by the other existing algorithms. We also studied the promoter regions of the genes belonging to a bicluster for common patterns / Transcription Factor Binding Sites (TFBS) or motifs using another online biological tool named RSA Toolbox. Promoter regions of the genes of most of the biclusters were found to have common motif patterns. We believe our work delivers relevant information and provides a useful tool for the analysis of gene expression datasets.
Studies on crystallization of peptidyl-prolyl cis-trans isomerase and AreB from Aspergillus flavus

Peptidyl-prolyl cis-trans isomerases (PPIase) is also known as rotamase or cyclophilins [1], catalyze cis-trans isomerization of peptide bonds, preferring those preceding proline residues [2]. The enzyme can be found in a large variety of organisms such as bacteria, plants, and mammals, sometimes as single domain proteins, but also as components in larger complexes [3]. PPIase accelerate protein folding both in vivo and in-vitro. They bind to and mediate the biological effects of the immunosuppressive agent cyclosporine A [4], they participate in cell surface recognition [5] and heat-shock response [6]. Cyclophilins are a diverse family regarding function and have incriminated in protein folding processes which rely on catalytic/chaperone-like activities [7]. Biological processes that reliable on the action of proteins and their domains, for example, folding collaborator proteins assist protein folding as disulfide isomerases or peptidylprolyl cis/trans isomerases [8]. These proteins have evolved to recognize precise signatures of protein sequences and manage in vivo protein folding [9]. A considerable number of proteins have acknowledged holding peptidyl-prolyl cis/trans isomerase a domain that has been constituting another specific protein recognition unit [10]. The peptidyl-prolyl cis/trans isomerases are enzymes that gather speed the slow cis/trans isomerization of peptidyl-prolyl bonds in different folding states of an intention protein. PPIase-catalysed protein conformational changes happened during the refolding of denatured proteins [11], de novo protein synthesis and the arrangement of biologically active conformations of polypeptides [12], Based on drug specificity and primary sequence homology. PPIases have been separated into three distinct families [13]: a) the cyclosporin A (CsA)binding proteins, cyclophilins,) the FK506 and rapamycin binding proteins, FKBPs,). The parvulins, do not bind immunosuppressant drugs [14]. Even though cyclophilins and FKBPs were identified for some decades, the cellular purpose of these enzymes is not yet absolutely understood. They concerned in the folding of newly synthesized proteins, transport and gathering of fundamental cellular protein complexes [15], In contrast, the purpose of a part of the third PPIase family, Pin1 could expose in much more details, and a significant task in the cell cycle mechanism in eukaryotes was proved [16].
Polymorphism rs10483727 in the SIX1/SIX6 Gene Locus Is a Risk Factor for Primary Open Angle Glaucoma in a Saudi Cohort.

AIMS Variant rs10483727 in the SIX1/SIX6 locus has been significantly associated with primary open angle glaucoma (POAG) in multiple ethnic groups. We conducted a case-control study to investigate the association between this variant and POAG in a Saudi cohort. MATERIALS AND METHODS Polymorphism rs10483727 was genotyped by using a TaqMan® assay in 186 subjects comprising 92 unrelated POAG cases and 94 controls all of Saudi origin. RESULTS The "C" allele frequency was 0.33 and 0.45 among POAG cases and controls, respectively (odds ratio [OR] = 0.58, 95% confidence interval [CI] = 0.38-0.89; p = 0.013), suggesting a protective effect; and the "T" allele was associated with increased susceptibility to POAG (OR = 1.7, 95% CI = 1.11-2.58; p = 0.013). Genotype distribution was also significantly associated with POAG (χ2 = 6.41, df = 2, p = 0.041). Endophenotype traits such as intraocular pressure and cup/disk ratio did not show any significant genotype distribution in POAG cases. A binary logistic regression analysis used to evaluate the effects of age, gender, and genotype on the likelihood of having POAG showed that genotype distribution (p = 0.012) significantly affected the disease outcome as compared with age (p = 0.055) and sex (p = 0.432). CONCLUSION The "T" allele of the rs10483727 polymorphism is an independent significant risk factor for POAG in the Saudi population.