Miracle-dz/UniFAR-FTUs huggingface dataset:
Systematic Review of Gut Microbiota and Major Depression

Background: Recently discovered relationships between the gastrointestinal microbiome and the brain have implications for psychiatric disorders, including major depressive disorder (MDD). Bacterial transplantation from MDD patients to rodents produces depression-like behaviors. In humans, case-control studies have examined the gut microbiome in healthy and affected individuals. We systematically reviewed existing studies comparing gut microbial composition in MDD and healthy volunteers. Methods: A PubMed literature search combined the terms “depression,” “depressive disorder,” “stool,” “fecal,” “gut,” and “microbiome” to identify human case-control studies that investigated relationships between MDD and microbiota quantified from stool. We evaluated the resulting studies, focusing on bacterial taxa that were different between MDD and healthy controls. Results: Six eligible studies were found in which 50 taxa exhibited differences (p < 0.05) between patients with MDD and controls. Patient characteristics and methodologies varied widely between studies. Five phyla—Bacteroidetes, Firmicutes, Actinobacteria, Fusobacteria, and Protobacteria—were represented; however, divergent results occurred across studies for all phyla. The largest number of differentiating taxa were within phylum Firmicutes, in which nine families and 12 genera differentiated the diagnostic groups. The majority of these families and genera were found to be statistically different between the two groups in two identified studies. Family Lachnospiraceae differentiated the diagnostic groups in four studies (with an even split in directionality). Across all five phyla, nine genera were higher in MDD (Anaerostipes, Blautia, Clostridium, Klebsiella, Lachnospiraceae incertae sedis, Parabacteroides, Parasutterella, Phascolarctobacterium, and Streptococcus), six were lower (Bifidobacterium, Dialister, Escherichia/Shigella, Faecalibacterium, and Ruminococcus), and six were divergent (Alistipes, Bacteroides, Megamonas, Oscillibacter, Prevotella, and Roseburia). We highlight mechanisms and products of bacterial metabolism as they may relate to the etiology of depression. Conclusions: No consensus has emerged from existing human studies of depression and gut microbiome concerning which bacterial taxa are most relevant to depression. This may in part be due to differences in study design. Given that bacterial functions are conserved across taxonomic groups, we propose that studying microbial functioning may be more productive than a purely taxonomic approach to understanding the gut microbiome in depression.
Analysis of LoRaWAN Uplink with Multiple Demodulating Paths and Capture Effect

Low power wide area networks (LPWANs), such as the ones based on the LoRaWAN protocol, are seen as enablers of large number of IoT applications and services. In this work, we assess the scalability of LoRaWAN by analyzing the frame success probability (FSP) of a LoRa frame while taking into account the capture effect and the number of parallel demodulation paths of the receiving gateway. We have based our model on the commonly used SX1301 gateway chipset, which is capable of demodulating up to eight frames simultaneously; however, the results of the model can be generalized to architectures with arbitrary number of demodulation paths. We have also introduced and investigated three policies for Spreading Factor (SF) allocation. Each policy is evaluated in terms of coverage probability, FSP, and throughput. The overall conclusion is that the presence of multiple demodulation paths introduces a significant change in the analysis and performance of the LoRa random access schemes.
The TAM-TB Assay—A Promising TB Immune-Diagnostic Test With a Potential for Treatment Monitoring

Tuberculosis (TB) epidemiology is changing in Western and Central Europe due to the rise in immigration and refugees fleeing high-TB-burden areas of war and devastation. The change in local demography and the lack of sensitive and specific TB diagnostic and monitoring tools, especially for cases of childhood TB, leads to either missed cases or over-treatment of this group. Here we present a promising new diagnostic approach, the T cell activation marker (TAM)-TB assay, and its performance in a case of extra-pulmonary TB occurring in a 16 year old refugee from Afghanistan. This assay is based on the characterization of 3 activation markers (CD38, HLA-DR, and Ki67) and one maturation marker (CD27) on M. tuberculosis-specific CD4 T cells. It was performed at time-points T0 (10 days), T1 (1 month), T2 (6 months), and T3 (12 months) post-treatment initiation. All markers were able to detect active tuberculosis (aTB) within this patient at T0 and reverted to a healthy/LTBI phenotype at the end of treatment. Tantalizingly, there was a clear trend toward the healthy/LTBI phenotype for the markers at T1 and T2, indicating a potential role in monitoring anti-TB treatment in the future. This assay may therefore contribute to improved TB diagnostic algorithms and TB treatment monitoring, potentially allowing for individualization of TB treatment duration in the future.
A Review of Heterogeneity in Attention Deficit/Hyperactivity Disorder (ADHD)

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that affects approximately 8%–12% of children worldwide. Throughout an individual’s lifetime, ADHD can significantly increase risk for other psychiatric disorders, educational and occupational failure, accidents, criminality, social disability and addictions. No single risk factor is necessary or sufficient to cause ADHD. The multifactorial causation of ADHD is reflected in the heterogeneity of this disorder, as indicated by its diversity of psychiatric comorbidities, varied clinical profiles, patterns of neurocognitive impairment and developmental trajectories, and the wide range of structural and functional brain anomalies. Although evidence-based treatments can reduce ADHD symptoms in a substantial portion of affected individuals, there is yet no curative treatment for ADHD. A number of theoretical models of the emergence and developmental trajectories of ADHD have been proposed, aimed at providing systematic guides for clinical research and practice. We conducted a comprehensive review of the current status of research in understanding the heterogeneity of ADHD in terms of etiology, clinical profiles and trajectories, and neurobiological mechanisms. We suggest that further research focus on investigating the impact of the etiological risk factors and their interactions with developmental neural mechanisms and clinical profiles in ADHD. Such research would have heuristic value for identifying biologically homogeneous subgroups and could facilitate the development of novel and more tailored interventions that target underlying neural anomalies characteristic of more homogeneous subgroups.
FuNP (Fusion of Neuroimaging Preprocessing) Pipelines: A Fully Automated Preprocessing Software for Functional Magnetic Resonance Imaging

The preprocessing of functional magnetic resonance imaging (fMRI) data is necessary to remove unwanted artifacts and transform the data into a standard format. There are several neuroimaging data processing tools that are widely used, such as SPM, AFNI, FSL, FreeSurfer, Workbench, and fMRIPrep. Different data preprocessing pipelines yield differing results, which might reduce the reproducibility of neuroimaging studies. Here, we developed a preprocessing pipeline for T1-weighted structural MRI and fMRI data by combining components of well-known software packages to fully incorporate recent developments in MRI preprocessing into a single coherent software package. The developed software, called FuNP (Fusion of Neuroimaging Preprocessing) pipelines, is fully automatic and provides both volume- and surface-based preprocessing pipelines with a user-friendly graphical interface. The reliability of the software was assessed by comparing resting-state networks (RSNs) obtained using FuNP with pre-defined RSNs using open research data (n = 90). The obtained RSNs were well-matched with the pre-defined RSNs, suggesting that the pipelines in FuNP are reliable. In addition, image quality metrics (IQMs) were calculated from the results of three different software packages (i.e., FuNP, FSL, and fMRIPrep) to compare the quality of the preprocessed data. We found that our FuNP outperformed other software in terms of temporal characteristics and artifacts removal. We validated our pipeline with independent local data (n = 28) in terms of IQMs. The IQMs of our local data were similar to those obtained from the open research data. The codes for FuNP are available online to help researchers.
Quantitative and Qualitative Evaluation of Photoreceptor Synapses in Developing, Degenerating and Regenerating Retinas

Quantitative and qualitative evaluation of synapses is crucial to understand neural connectivity. This is particularly relevant now, in view of the recent advances in regenerative biology and medicine. There is an urgent need to evaluate synapses to access the extent and functionality of reconstructed neural network. Most of the currently used synapse evaluation methods provide only all-or-none assessments. However, very often synapses appear in a wide spectrum of transient states such as during synaptogenesis or neural degeneration. Robust evaluation of synapse quantity and quality is therefore highly sought after. In this paper we introduce QUANTOS, a new method that can evaluate the number, likelihood, and maturity of photoreceptor ribbon synapses based on graphical properties of immunohistochemistry images. QUANTOS is composed of ImageJ Fiji macros, and R scripts which are both open-source and free software. We used QUANTOS to evaluate synaptogenesis in developing and degenerating retinas, as well as de novo synaptogenesis of mouse iPSC-retinas after transplantation to a retinal degeneration mouse model. Our analysis shows that while mouse iPSC-retinas are largely incapable of forming synapses in vitro, they can form extensive synapses following transplantation. The de novo synapses detected after transplantation seem to be in an intermediate state between mature and immature compared to wildtype retina. Furthermore, using QUANTOS we tested whether environmental light can affect photoreceptor synaptogenesis. We found that the onset of synaptogenesis was earlier under cyclic light (LD) condition when compared to constant dark (DD), resulting in more synapses at earlier developmental stages. The effect of light was also supported by micro electroretinography showing larger responses under LD condition. The number of synapses was also increased after transplantation of mouse iPSC-retinas to rd1 mice under LD condition. Our new probabilistic assessment of synapses may prove to be a valuable tool to gain critical insights into neural-network reconstruction and help develop treatments for neurodegenerative disorders.
Evaluation of Information Retrieval Systems: A Simulation and Cost Approach.

Michael David Cooper This dissertation manines problems of how to evaluate an information retrieval system. Two specific approaches are explored. The first is a mathematical model for use in studying how to minimize the cost of operating a mechanized retrieval system. Through the use of cost analysis, the model provides a method for comparative evaluation between systems. The cost model divides the costs of a retrieval system into two components: system costs and user costs. In addition, it suggests that a trade off exists between the performance level of the system and the combination of user and system time that is expended in working with the system. With this approach it is possible to determine the allocation of user and system time that minimizes the total cost of operating the system. This allocation is done for a given performance level and for a given cost per unit of user and system time. The second approach to the evaluation of literature searching systems is the development of a simulation model as a preliminary step toward the creation of a tool for system design and evaluation. The simulation program creates a well specified collection of documents and analyzes the effect Of changes in query file characteristics on system performance. First a thesaurus of term relations is generated. Then, employing the thesaurus; routines generate pseudo-documents and pseudoqueries. These pseudo-documents and pseudo-queries are then compared
Adjoint Based Uncertainty Quantification and Sensitivity Analysis for Nuclear Thermal-Fluids Codes.

Adjoint Based Uncertainty Quantification and Sensitivity Analysis for Nuclear Thermal-Fluids Codes by Timothy J. Drzewiecki Chair: Prof. Thomas J. Downar and Prof. Annalisa Manera Safety analysis in nuclear engineering has been adopting a best estimate plus uncertainty (BEPU) approach over a traditional conservative approach in order to provide more realistic estimates of plant safety margins. Traditionally, these BEPU approaches have relied on an expensive phenomena identification and table (PIRT) process to identify the most significant contributors to uncertainty. More recent work has utilized statistical-based sensitivity measures (e.g. the Spearman rank correlation coefficient) to highlight the important contributors to uncertainty. Currently, the most popular method for dealing with uncertainty is based on the Wilks’ formula, where a specified number of calculations needs to be performed in order to establish a certain confidence level of a certain reliability. These methods have the advantage that a relatively limited number of runs needs to be performed, typically less than 100. Situations exist, however, where one is required to exhaustively sample the space of uncertain input parameters. In these situations, where tens of thousands of calculations may be required, sampling the true function may be too computationally expensive and a surrogate is sampled in place of the true function.
The Book of Laughter and Forgetting

Commissioned and closely monitored by Milan Kundera himself, this new translation brings a clarity and unmatched fidelity to the author's original text. Widely held as a work of genius, "The Book of Laughter and Forgetting" is the novel that first brought him to the forefront of the international literary scene. Rich in stories, characters and imaginative range, it was written while Kundera was still forbidden to publish in his home country of Czechoslovakia, which was then behind the Iron Curtain. In seven wonderfully integrated parts, different aspects of modern existence -- from the posthumous erasure of "enemies" of communism from the historical record, to the subtle agony of the fading memory of a lost love, to the bizarre sexlessnes of modern promiscuity -- are explored with boldness, subversive humor and the magical power of fiction.
D2.5.5 Next Steps for OWL

EU-IST Network of Excellence (NoE) IST-2004-507482 KWEB Deliverable D2.5. 5 (WP2.5) OWL 1.1 is a simple extension to the OWL DL species of the W3C OWL Web Ontology Language. OWL 1.1 has been designed to provide some interesting and useful expressive additions to OWL DL while retaining the desirable characteristics of OWL DL, including decidability and implementability. Keyword list: description logics, ontology language, RDF, OWL DL, OWL, W3C, standardization
SQUALID: A deductive DBMS

Most modern companies probably could not function without a database management system (DBMS). Although current DBMSs are becoming increasingly sophisticated, they are still deficient in several areas. One of these areas is deduction. Human beings have the interesting ability to derive facts from a set of data, even though these facts are not explicitly represented in the data. That is, given appropriate information, humans can deduce new information by applying rules. A deductive database is a database which can perform similar deductions on the data stored within it. This has the advantage that some data can be stored implicitly using rules, rather than explicitly. This reduces the amount of storage the database occupies. The use of rules also allows us to store new kinds of data, such as recursive data or indefinite data. Several deductive database systems have been developed, but many of them only approach the problem from a theoretical point of view; practical considerations such as efficiency and ease of use for end-users have often been neglected. Many systems were also developed completely from scratch, rather than taking advantage of existing facilities. That is, it should be possible to take an existing DBMS, and extend it with deductive capabilities. In this work we introduce the concept of a deductive database, and some of the problems associated with implementing such a system. We then discuss the implementation of a system called SQUALID (for Structured Query And Logical Inference Database). This system is based on an existing DBMS, Rdb/VMS, which has been extended with facilities for creating and manipulating rules. An extended version of the standard query language SQL is used. All rules and data are stored in a conventional database, allowing SQUALID to take advantage of the efficiency of the underlying DBMS.
Motor Imagery: Does Strategy Matter?

Motor imagery requires individuals to form an internal representation of a specific action within working memory without any overt output. Motor imagery has proven effective in improving motor performance of specific skills. This study explored whether different motor imagery strategies influence corticospinal excitability in young (20-35 years) and older subjects (over 55 years). In addition, the effectiveness of these strategies in targeting modulations in motor cortical output and whether the hand " performing " the task was important were also examined. Motor imagery ability was measured using the Kinesthetic and Visual Imagery Questionnaire (KVIQ) and mental chronometry. Working memory including visuospatial, verbal and kinesthetic domains was measured by immediate serial recall. To determine the effect of imagery on corticospinal excitability transcranial magnetic stimulation (TMS) was applied over the contralateral motor cortex as subjects imagined abducting their index finger. Motor evoked potentials (MEPs) were recorded from first dorsal interosseous (FDI), abductor pollicis brevis and abductor digiti minimi muscles (ADM). As subjects performed motor imagery, they were guided by visual, auditory or a combination of visual and auditory cues. Strategies were introduced in randomized sequence interspersed with a rest and a muscle activation condition. Motor imagery ability and verbal working memory were comparable between young and older subjects (p > 0.05). In both groups, MEP amplitudes in the FDI muscle were significantly increased during motor imagery compared to rest regardless of the strategy used (p < 0.001). Visual cueing was the most effective at isolating facilitation to the target muscle (FDI), whereas with the auditory and combined strategies both FDI and ADM muscles generated MEPs that were comparable in amplitude (p > 0.05). TMS induced MEPs were greater in amplitude when the left hemisphere was stimulated during motor imagery of iii the right finger while being guided by either auditory or visual cueing. In combination, these findings suggest that motor imagery increases corticospinal excitability and the strategy used may serve to target the facilitation. iv Acknowledgements
Long-term unix file system activity and the efficacy of automatic file migration

This dissertation studies long-term file system activity in order to develop new migration algorithms for tertiary storage systems (e.g., tape robots). To enable this study, I collected file traces from four different computing facilities and analyzed file activity patterns in the areas of size, usage, access, creation, deletion, and modification rates and patterns, inter-reference periods, and lifetimes. My file activity results include: most files are never used, accesses dominate file activity, files which are modified grow or shrink very little, file activity has reference locality, and there are significant differences between how the Unix operating system deals with files and what users perceive the operating system does with their files (i.e., the Unix operating system's numeric index versus the hierarchical name space used by people). I also analyzed the collected data for self-similar behavior, and was able to show that file system traffic is self-similar, or fractal. This has profound implications for computer simulations and modeling because normal simulation assumptions (i.e., Poisson models with finite variance arrival rates) are invalid for self-similar traffic. Thus, most existing file system simulators and models are probably inaccurate. Finally, I developed a new migration algorithm that is an order of magnitude more effective than any existing migration algorithm when measured using on-disk misses. Other measures of effectiveness, such as number of files and bytes move to tertiary storage, and the number of forced mid-day migrations are also improved.
Analysis of 2D Color Spaces for Highlight Elimination in 3D Shape Reconstruction

We develop a method to separate matte and specular reflection components in color images using the dichromatic reflection model. Three-dimensional color descriptors are transformed to a pair of two-dimensional descriptors. This representation allows to perform the reflection analysis for multi-colored objects in a fast and robust manner. Further, it enables us to consider multiple dichromatic clusters in a single dichromatic plane. The method suggests that a pure color space analysis is sufficient in most situations. The matte reflection component is applied to a fast three-dimensional surface reconstruction scheme. Applying the proposed method it is not necessary to know reflection parameters such as matte and specular albedo or roughness values for surface recovery in advance.
Another Two-Level Failure Recovery Scheme

This report deals with the design and evaulation of a "two-level" failure recovery scheme for distributed systems. In our previous work [30, 32], we motivated a "two-level" recovery approach that tolerates the more probable failures with a low overhead, and less probable failures with possibly higher overhead. The two-level approach can achieve a smaller overhead as compared to traditional recovery schemes. In this report, we present and evaluate a "two-level" recovery scheme that is suitable for a network of workstations, each workstation having a local disk. The recovery scheme presented in the report can tolerate trasient processor failures with a low overhead, while other failures require a larger overhead. The report presents analysis of the average (expected) task completion time using the proposed scheme. This scheme has been implemented on a workstation cluster. Our analysis indicates that the proposed two-level recovery scheme can achieve better performance as compared to existing "one-level" recovery schemes. The report also evaluates the impact of checkpoint latency on the performance of the recovery scheme. To our knowledge, no analysis of the performance impact of checkpoint latency has been carried out previously. Experimental measurements of checkpoint latency for four applications are presented.