Miracle-dz/UniFAR-FTUs huggingface dataset:
Master Thesis Enhancing Monte Carlo Tree Search by Using Deep Learning Techniques in Video Games

The main goal of this master thesis is to extend Monte Carlo Tree Search (MCTS) in real-time video games by using Deep Learning. MCTS is a heuristic search algorithm which is most often used for decision making in games. It tries to determine a good move given the current game state. Although, an MCTS has important advantages compared to αβ search and similar algorithms it does not converge very fast. Additionally, the search may not investigate a path, which leads to a loss. Consequently, that path cannot be taken into account. By using Deep Learning, the MCTS should be improved to for example find optimal paths easier by better determining the value of a given game state. For that, a Convolutional Neural Network (CNN) is trained by using the Java library DL4J. CNNs usually take an image as their input, which is then passed through the network to classify certain aspects of that picture. In this case, the network takes a game state as its input and estimates a move policy for that game state. By that, an estimation for the player’s best next move is given. This concept is similar to what Deepmind’s AlphaGo does. The agent uses CNNs to determine either a value for a certain game state or a move policy that could then be used by an MCTS. This improves the search algorithm to work with better estimates and converge faster. In this thesis, a concept that resembles the AlphaGo approach is applied to the real-time video game Ms. Pac-Man. Furthermore, it is successfully shown that a CNN can in principle improve an MCTS in this real-time video game. However, Deep Learning techniques are time-consuming and the time a CNN needs to process a game state is too much to compensate for the decreased number of play-outs in the MCTS. Moreover, this thesis provides information about how to combine a CNN with an MCTS, how to configure a good performing CNN for real-time video games and possibilities of training such a network with game state samples.
A novel role for SHARPIN in amyloid-β phagocytosis and inflammation by peripheral blood-derived macrophages in Alzheimer's disease

INTRODUCTION Defective immune cell-mediated clearance of amyloid-beta (Aβ) and Aβ-associated inflammatory activation of immune cells are key contributors of Aβ accumulation and neurodegeneration in Alzheimer’s disease (AD), however, the underlying mechanisms remain elusive. METHODS Differentiated THP-1 cells treated with Aβ and AD patient-derived macrophages were used as in-vitro model. The role of SHARPIN was analysed in differentiated THP-1 cells using siRNA-mediated knockdown followed by immunoblotting, ELISA, real-time PCR, immunoprecipitation and flow cytometry. Differentiated SHSY5Y cells were used to study inflammation-mediated apoptosis. RESULTS SHARPIN was found to regulate Aβ-phagocytosis and NLRP3 expression in THP-1 derived macrophages. Further, it was found to promote macrophage polarization to an M1 (pro-inflammatory) phenotype resulting in enhanced inflammation and associated neuronal death, demonstrated using in-vitro culture systems. SHARPIN expression by blood-derived macrophages was further found to be higher in the early stages of AD, which correlates with Aβ40/42 concentration in the plasma and age of the study subjects. DISCUSSION The novel protein, SHARPIN has been shown to play critical roles in regulation of Aβ-phagocytosis and inflammation in AD and the mechanism by which SHARPIN is activated by Aβ in macrophages has been elucidated.
CELLULAR GRAPH GRAMMAR ENCODING OF NEURAL NETWORKS

This paper presents a novel approach to neural network evolution. Genomes used in this evolution are based on a well-described cellular encoding and a general mathematical idea of graph grammar. These genomes are then optimized with genetic programming. This approach has been tested on the Iris flower data set to classify three Iris flower species according to four measured quantities of each plant. Disadvantages and possible future improvements of this approach are listed in the end of the paper.
Moth-inspired methods for particle capture on a cylinder

We study particle capture on an angled cylinder at a range of Péclet numbers. This system was inspired by the plumose antennae of certain species of male moths that intercept female pheromones at low Péclet numbers of 0.9–23. We use confocal microscopy to measure the branching patterns of 49 moths, spanning 12 families and two orders of magnitude in mass. Among the three levels of hierarchy in antennae, we find the middle level has a prevalent branching angle, $52^{\circ }\pm 12^{\circ }$ across our study set. Such intermediate branching angles are a surprising way to intercept molecules because they do not maximize the exposed surface area. To understand the benefits of angling cylinders into the flow, we study particle collection at high Péclet number using $10~\unicode[STIX]{x03BC}\text{m}$ drops that are several orders of magnitude larger than moth pheromones. Wind tunnel tests show that cylinders angled at $30^{\circ }{-}60^{\circ }$ are optimal for collection of particles, collecting 30 % more than when perpendicular to the flow. Simulations and smoke visualization show that angled cylinders bend incoming streamlines, creating a lingering effect near the cylinder that can enhance deposition by diffusion. We surmise that the optimal angle arises from a trade-off between the lingering effect, which decreases with increasing angle of the cylinder, and the cylinder’s increasing projected area as it is turned more perpendicular to the flow. Using a mathematical model, we show that only cylinders at low Péclet number show improved collection at intermediate angles. Thus, we cannot rationalize the high collection rates in our wind tunnel experiments at high Péclet number. We hope that our study will inspire more research into bio-inspired particle collection of angled surfaces, and find applications in sensors and filters.
Group Contributions in TU games : The k-lateral value

In this paper we introduce the notion of group contributions in TU games and propose a new value which we call the k-lateral value. The Shapley like values implicitly assume that players are independent in deciding to leave or join a coalition. However, in many real life situations players are bound by the decisions taken by their peers. This leads to the idea of group contributions where we consider the marginality of groups upto a certain size. We show that group contributions can play an important role in determining players’ shares in the total resource they generate. The proposed value considers both egalitarianism and marginalism and thus is a member of the class of solidarity values. We provide two characterizations of our value.
Weighted-Probability Random Number Generator for PLC Channel Transfer Function Generation

The concept of randomization shows many realistic scenarios and has enormous applications in everyday life. However, existing random number generators have poor adaptability when representing some of the actual occurrences in natural environment, such as in biology, mobile communications, and even electrical behavior. For PLC channel transfer function generation, biased sampling of the channel is more applicable. This paper proposes a weighted-probability method to generate random numbers to emulate the real-world variations of a power line communications channel. Existing PLC channel emulator can mimic the random behavior of the channel, altered by several parameters such as cable length, cable type, presence of loads, and ejecting different noises. However, the scenario of integrating the effect of changing the state of the loads and channel variation due to time is not well represented in the normal random channel generation. The best concept for this scenario is the weighted random number generator (WRNG). This work developed an algorithm in Matlab and VHDL, implemented it in FPGA and integrated it with an existing PLC channel emulator. The emulator is implemented using Kintex-7 FPGA. In this study, ten different weights corresponding to the probability of occurrence of the actual household appliances and eighty transfer functions were used as inputs to the program. The randomness and periodicity of the WRNG are tested and passed the Runs test. Autocorrelation and histograms are used to determine the correct implementation of the weights.
University of Groningen Demethionylation of Pro-1 variants of 4-oxalocrotonate tautomerase in Escherichia coli by co- expression with an engineered methionine aminopeptidase Baas,

4-Oxalocrotonate tautomerase (4-OT) catalyzes the enol-keto tautomerization of 2-hydroxymuconate, utilizing its N-terminal proline (Pro-1) as general base catalyst. Substituting Pro-1 with bulky or charged residues will result in poor or no post-translational removal of the translation-initiating methionine by the methionine aminopeptidase (MetAP) of the Escherichia coli expression host. Here, we set out to investigate whether co-expression with previously engineered aminopeptidase MetAP⁄TG can be used to produce the P1S, P1H and P1Q variants of 4-OT in a demethionylated form. The P1S variant, which carries a small residue at the penultimate position (the first position after the initiating methionine), was found to be fully processed by wild-type MetAP. The P1S variant has lowlevel 2-hydroxymuconate tautomerase and promiscuous oxaloacetate decarboxylase activity. The P1Q and P1H variants of 4-OT, which carry bulky residues at the penultimate position, could only be obtained in a demethionylated form (a minor fraction of the purified protein is still composed of methionylated enzyme) by co-expression with MetAP-⁄TG. Interestingly, the Gln-1 residue of the demethionylated P1Q variant undergoes intramolecular cyclization to form pyroglutamate (pE), yielding variant P1pE. Whereas the P1H/M1P2H mixture has low-level tautomerase activity, the P1pE/M1P2Q mixture has robust tautomerase activity. The substitution of Pro-1 by Gln, followed by removal of the initiating Met and cyclization of Gln-1 to form pE, is a unique way to obtain a structural analogue of proline on the N-terminus of 4-OT. This opens up new possibilities to study the importance of Pro-1 in recently discovered C–C bond-forming activities of this highly promiscu-
Preliminary Results of a System-theoretic Assessment of Maritime Autonomous Surface Ships’ Safety

While a system‐theoretic approach to the safety analysis of innovative socio‐technical systems gains a growing acceptance among academia, safety issues of Maritime Autonomous Surface Ships (MASS) remain largely unexplored. Therefore, we applied a System‐Theoretic Process Analysis to develop and analyze a preliminary model of the unmanned shipping system in order to elaborate safety recommendations for future developers of the actual system. Results indicate that certain advancements shall be undertaken in relation to MASS’ software solutions in particular. http://www.transnav. eu the International Journal on Marine Navigation and Safety of Sea Transportation Volume 13
Inflammatory response in osteoporotic fracture healing Abstract Fracture healing is a well-orchestrated and coordinated process and begins with the inflammatory stage involving the infiltration of immune cells and the release of cytokines, including tumour necrosis factor-alpha (TNF-α), interleukin-

Fracture healing is a well-orchestrated and coordinated process and begins with the inflammatory stage involving the infiltration of immune cells and the release of cytokines, including tumour necrosis factor-alpha (TNF-α), interleukin-6 (IL-6) and interleukin-10 (IL-10). Low-magnitude high-frequency vibration (LMHFV) stimulation is effective in promoting fracture healing. The study hypothesis was that the innate immune response was impaired in osteoporotic fracture and LMHFV could positively modulate it. 9-month-old ovariectomy (OVX)-induced osteoporotic rats were randomised into sham (SHAM), OVX control (OVX), OVX-vibration (OVX-VT) or OVX vibration plus administration of COX-2 specific non-steroid anti-inflammatory drugs (OVX-VT-NSAID). LMHFV (35 Hz, 0.3 ×g) was given 20 min/d and 5 d/week to the treatment groups. Healing and innate immune response were evaluated by weekly radiographs, endpoint micro-computed tomography (μCT), enzyme-linked immunosorbent assay (ELISA) and histomorphometry at weeks 1, 2, 4 and 8 post-treatment. Results showed that OVX slightly elevated systemic inflammation but impaired the innate immune response locally at the fracture site, with significantly lower expressions of TNF-α and IL-6 but higher IL-10 expression during the early stage of healing. LMHFV was effective in accelerating the delayed fracture healing in OVX bones by partly restoring the impaired innate immune response at the fracture site, accompanied by promoted progression of macrophage polarisation from M1 (pro-inflammatory) to M2 (anti-inflammatory) phenotype. In conclusion, vibration treatment could positively modulate the impaired innate immune response and promote macrophage polarisation in osteoporotic-fracture healing.
Benefit/Risk Estimates in Clinical Trials

Most current benefit/risk analyses of drugs in clinical trials are qualitative and subjective. This study details the development of scientific and objective equations to numerically estimate the benefit/risk (B/R) ratio. The methodology in this study is to consider different severity levels of adverse events and improvement of symptoms by assigning different weights to them. The set of equations to calculate the B/R ratio take into consideration the clinical data’s inherent uncertainties due to sample size, adverse event reporting, and many other factors. Furthermore, the uncertainties of clinical trial data are taken into account by treating the benefit and risk as random variables, utilizing the reliability index, and performing the first-order analysis to evaluate the benefit and risk of the treatment. The methodology discussed can be used on quantitative assessments of not only drugs in clinical trials but also drug treatments of patients. To test the B/R ratio calculation, we applied the method to two large clinical trials obtained from published literature. This experimental approach could assist clinical investigators and regulatory oversight groups in comparing and determining the suitability of various clinical trials and drug treatments by providing a quantitative analysis beyond the existing subjective methods.
A New Framework for Sentiment Analysis with Six-Tuples

Text analytics is one of the growing fields of interest from the scientific and the business communities in recent times.In this paper a new framework is introduced which consists of six elements for presenting a structured and organized form of describing any opinionated sentiment. The basic elements of this frameworkare opinion holder, an entity which is the intended target of the opinion, time of the expressed opinion, sentiment of the opinion, aspect or attribute of the opinion and representation of the opinion. This framework has been constructed keeping in mind the importance of the influence an opinion can inflict in the minds of those to whom the opinion is expressed by the opinion maker. The framework has been assumed from the perspective of the potential influence an opinion can have on the receivers of the opinion. The proposed framework is more improved than other existing works done so far.
A Similarity-Driven Sequential Model for Predicting Medical Treatment Initiation via Graph Laplacian

A diverse range of computational models have been proposed to extract temporal patterns from clinical time series data for each patient and among patient group for predictive healthcare, including multivariate regression, neural network, and decision tree, etc. These models typically learn an analytical mapping from the numerical or categorical patients’ medical data to the targeted labels. However, the common relations among patients (e.g., share the same doctor, or receive the same medical treatments) were rarely considered. In this paper, we represent the relation between patients and clinicians by bipartite graphs to explicitly address relations such as from which clinician a patient is diagnosed or offered a medical service. We then solve for the top eigenvectors of the Laplacian matrix of the bipartite graph, and include the eigenvectors as latent representations of the similarity between patient-clinician pairs into a time-sensitive prediction model. We conducted experiments using real-world data to predict the initiation of first-line treatment for Chronic Lymphocytic Leukemia (CLL) patients. Results show that the relational similarity uncovered from the patient-clinician bipartite graph can enhance prediction accuracies over multiple baselines, for example, a 5% increment over the long short-term memory sequential model in terms of area under precision-recall curve.
Endmember Extraction From Hyperspectral Imagery Based on Probabilistic Tensor Moments

This letter presents a novel hyperspectral endmember extraction approach that integrates a tensor-based decomposition scheme with a probabilistic framework in order to take advantage of both technologies when uncovering the signatures of pure spectral constituents in the scene. On the one hand, statistical unmixing models are generally able to provide accurate endmember estimates by means of rather complex optimization algorithms. On the other hand, tensor decomposition techniques are very effective factorization tools which are often constrained by the lack of physical interpretation within the remote sensing field. In this context, this letter develops a new hybrid endmember extraction approach based on the decomposition of the probabilistic tensor moments of the hyperspectral data. Initially, the input image reflectance values are modeled as a collection of multinomial distributions provided by a family of Dirichlet generalized functions. Then, the unmixing process is effectively conducted by the tensor decomposition of the third-order probabilistic tensor moments of the multivariate data. Our experiments, conducted over four hyperspectral data sets, reveal that the proposed approach is able to provide efficient and competitive results when compared to different state-of-the-art endmember extraction methods.
mRNA with Mammalian Codon Bias Accumulates in Yeast Mutants with Constitutive Stress Granules

Stress granules and P bodies are cytoplasmic structures assembled in response to various stress factors and represent sites of temporary storage or decay of mRNAs. Depending on the source of stress, the formation of these structures may be driven by distinct mechanisms, but several stresses were shown to stabilize mRNAs via inhibition of deadenylation. A recent study identified yeast gene deletion mutants with constitutive stress granules and elevated P bodies; however, the mechanisms which trigger its formation remain poorly understood. Here, we investigate the possibility of accumulating mRNA with mammalian codon bias, which we termed the model RNA, in these mutants. We found that the model RNA accumulates in dcp2 and xrn1 mutants and in four mutants with constitutive stress granules overlapping with P bodies. However, in eight other mutants with constitutive stress granules the model RNA is downregulated, or its steady state levels vary. We further suggest that the accumulation of the model RNA is linked to its protection from the main mRNA surveillance path. However, there is no obvious targeting of the model RNA to stress granules or P bodies. Thus, accumulation of the model RNA and formation of constitutive stress granules occur independently and only some paths inducing formation of constitutive stress granules will stabilize mRNA as well.
Exploration and Characterization of Novel Glycoside Hydrolases from the Whole Genome of Lactobacillus ginsenosidimutans and Enriched Production of Minor Ginsenoside Rg3(S) by a Recombinant Enzymatic Process

Background: Several studies have reported that ginsenoside Rg3(S) is effective in treating metastatic diseases, obesity, and various cancers, however, its presence in white ginseng cannot be estimated, and only a limited amount is present in red ginseng. Therefore, the use of recombinant glycosidases from a Generally Recognized As Safe (GRAS) host strain is a promising approach to enhance production of Rg3(S), which may improve nutritional activity, human health, and quality of life. Method: Lactobacillus ginsenosidimutans EMML 3041T, which was isolated from Korean fermented pickle (kimchi), presents ginsenoside-converting abilities. The strain was used to enrich the production of Rg3(S) by fermenting protopanaxadiol (PPD)-mix-type major ginsenosides (Rb1, Rb2, Rc, and Rd) in four different types of food-grade media (1, MRS; 2, Basel Food-Grade medium; 3, Basel Food-Grade medium-I, and 4, Basel Food-Grade medium-II). Due to its tendency to produce Rg3(S), the presence of glycoside hydrolase in Lactobacillus ginsenosidimutans was proposed, the whole genome was sequenced, and the probable glycoside hydrolase gene for ginsenoside conversion was cloned. Results: The L. ginsenosidimutans EMML 3041T strain was whole genome sequenced to identify the target genes. After genome sequencing, 12 sets of glycoside hydrolases were identified, of which seven sets (α,β-glucosidase and α,β-galactosidase) were cloned in Escherichia coli BL21 (DE3) using the pGEX4T-1 vector system. Among the sets of clones, only one clone (BglL.gin-952) showed ginsenoside-transforming abilities. The recombinant BglL.gin-952 comprised 952 amino acid residues and belonged to glycoside hydrolase family 3. The enzyme exhibited optimal activity at 55 °C and a pH of 7.5 and showed a promising conversion ability of major ginsenoside Rb1→Rd→Rg3(S). The recombinant enzyme (GST-BglL.gin-952) was used to mass produce Rg3(S) from major ginsenoside Rb1. Scale-up of production using 50 g of Rb1 resulted in 30 g of Rg3(S) with 74.3% chromatography purity. Conclusion: Our preliminary data demonstrated that this enzyme would be beneficial in the preparation of pharmacologically active minor ginsenoside Rg3(S) in the functional food and pharmaceutical industries.
Corporate social responsibility and Rule 144A debt offerings: Empirical evidenc

Rule 144A allows a firm to issue securities without a public registration statement with the Securities and Exchange Commission, and only qualified institutional investors can purchase such securities. In this study, focusing on corporate bonds issued under Rule 144A, we empirically investigate the relationship between the corporate social responsibility (CSR) of issuing firms and the bond yield spread at issuance. We document a significant and positive relation between CSR concerns, whereas CSR strengths seem to play an insignificant role in determining bond yield spread. Our main findings are robust to the instrumental variable approach and simultaneous equation estimation to address the potential endogeneity issues. We further explore the time-series changes in issuing firms’ CSR profiles, and report that institutional investors demand a higher bond yield spread when issuing firms’ exposure to higher social, environmental, and stakeholder concerns. Our analyses reveal that the main sources of such risk exposure are stakeholder conflict and concerns from primary stakeholder groups.