Miracle-dz/UniFAR-FTUs huggingface dataset:
Testing general game players against a Simplified Boardgames player using temporal-difference learning

In this paper we assess the progress of General Game Playing by comparing some state-of-the-art GGP players with an exemplary program dedicated to playing games in a smaller class called Simplified Boardgames. Conclusions on further possible development are made. The paper is also the first step in creating a standard test class for measuring performance of GGP players.
Isolation and Characterization of Rana catesbeiana Lectin and Demonstration of the Lectin-binding Glycoprotein of Rodent and Human Tumor Cell Membranes 1

A lectin isolated from Rana catesbeiana eggs preferentially aggluti nates a large variety of human and animal tumor cells but not normal red blood cells, lymphocytes, or fibroblasts. The phenomenon correlates with a higher binding activity of the lectin with tumor cells. Chemical and physical analysis of the purified lectin indicates that the lectin is a low molecular weight basic polypeptide with five intrachain disulfide bonds. Its agglutination of tumor cells was abolished by blocking the amino group. The lectin strongly binds with a large variety of tumor cells but binds only minimally with fibroblasts, lymphocytes, and erythrocytes. Tumor cell agglutination induced by this lectin was strongly inhibited by submaxillary mucin, to a lesser degree by fetuin and keratan sulfate, and not at all by less-sialylated glycoproteins, such as transferrin. Inhibition by mucin or fetuin was greatly reduced by desialylation of glycoprotein with sialidase. Treatment of tumor cells with sialidase greatly reduced the lectin-dependent agglutination, and the sialidase-dependent reduction of tumor cell agglutination was inhibited by the sialidase inhibitor 2,3dehydro-2-deoxy-jY-acetylneuraminic acid. However, tumor cell agglutin ation was not inhibited by chondroitin sulfates or hyaluronic acid. Thus, the lectin-dependent tumor cell agglutination is due to a high density of sialic acid at the cell surface. The receptor glycoprotein that interacts with this lectin was demonstrated in the detergent-insoluble fraction of a variety of tumor cells by sodium dodecyl sulfate:polyacrylamide gel electrophoresis, followed by Western blotting with lectin and anti-lectin antibodies. The presence of a common high molecular weight lectinbinding glycoprotein in various tumor cells was demonstrated.
Advancing Multinomial Regression and Topic Modeling with Beta-Liouville Distributions

This research explores the Beta-Liouville (BL) distribution as an alternative to the classic Dirichlet distribution in Dirichlet multinomial regression (DMR) and topic modelling. We examine the inherent limitations presented by the Dirichlet distribution in DMR, particularly in handling sparse data and complex correlations, then propose that the BL distribution, with its inherent flexibility and ability to handle higher-dimensional data, presents a substantial upgrade. We demonstrate the advantages of this new approach through a series of simulated and real-world datasets, highlighting improvements in model performance and inference quality. We discuss the impact of this change in the realm of topic modelling, as well as how the BL distribution enhances the interpretability and specificity of topics extracted. We anticipate our work to inspire further research and development in this field, aiming for continued refinement and enhancement of predictive modelling.
Translational Deep Learning-Based Diagnostics: Enhancing Pathology With AI

Transformative innovation in healthcare is led by the constantly changing field of deep learning techniques, especially designed for cellular imaging in diagnostic pathology. This paper provides a thorough examination of several deep learning approaches in the field of pathology, highlighting new uses and tackling important issues that are essential to the field's progress. The successful deployment of AI in clinical settings depends on the seamless integration of these apps into processes in digital pathology. This all-inclusive diagnostic method not only simplifies processes but also provides pathologists with cutting-edge instruments that accelerate work, improve diagnosis accuracy, and lower mistakes. The US has recently approved a limited number of manufacturers' digital pathology products for diagnostic usage, which offers a strong basis for the creation of useful AI solutions. Researchers, physicians, business executives, government agencies, and patient advocacy organizations working together will make it much easier for these cutting-edge technologies to spread and become widely used by medical professionals. These technologies usher in a new age in healthcare, distinguished by their exceptional performance, faster processing rates, cost effectiveness, increased accuracy, and strict safety regulations. AI and computational pathology will continue to develop in harmony, opening the door to a new age of improved healthcare delivery.
One-Pass Learning Algorithm for Fast Recovery of Bayesian Network

An efficient framework is proposed for the fast recovery of Bayesian network classifier. A novel algorithm, called Iterative Parent-Child learningBayesian Network Classifier (IPC-BNC), is proposed to learn a BNC without having to learn the complete Bayesian network first. IPC-BNC was proved correct and more efficient compared with a traditional global learning algorithm, called PC, by requiring much fewer conditional independence (CI) tests. Besides, we recognize and introduce AD-tree into the implementation so that computational efficiency is further increased through collecting full statistics within a single data pass. The IPC-BNC and AD-tree combination is demonstrated very efficient in time by our empirical study, making itself an attractive solution in very large applications.
A Study on Effective Segmentation Network in MRI Images for Diagnosis of Brain Tumor

Brain glioma type's tumors are among the most toxic cancers worldwide. Now-a-days, due to the advance of convolutional neural networks, many brain tumor segmentation systems aid clinicians to diagnose and operate. To support clinicians in the accurate automatic semantic segmentation of brain tumors, we investigate two convolutional encoding-decoding neural network i.e. UNet and PSPNet for brain glioma tumour segmentation from multimodal MRI images. The study is trained from the 2020 Brain Tumour Segmentation (BraTS) challenge. A rigorous assessment and comparative evaluation on the BraTS'20 validation set and test set, respectively, evolved with the PSPN et architecture achieving dice scores of 0.876 and 0.905 for enhancing tumour region and necrotic tumour/core region, respectively and with the UN et architecture achieving dice scores of 0.842 and 0.908 for enhancing tumour region and necrotic tumour/core region, respectively.
Blessings, Banes, and Possibilities in the Study of Childhood Personality

In this commentary I make three points. First, the four articles presented in this special issue are critical examples of the viability and importance of the idea of childhood personality. Second, I identify several concerns, including the narrow scope of the study of childhood personality, the lack of focus on environmental factors that might facilitate development in childhood personality, and the conceptual overlap between measures of childhood personality and outcomes such as externalizing behavior. Third, I recommend that the gap between childhood and adult personality be bridged more systematically so that we can detail the path of development across the life course.
Degradation of nuclease-stabilized RNA oligonucleotides in Mycoplasma-contaminated cell culture media.

Artificial RNA reagents such as small interfering RNAs (siRNAs) and aptamers often must be chemically modified for optimal effectiveness in environments that include ribonucleases. Mycoplasmas are common bacterial contaminants of mammalian cell cultures that are known to produce ribonucleases. Here we describe the rapid degradation of nuclease-stabilized RNA oligonucleotides in a human embryonic kidney 293 (HEK) cell culture contaminated with Mycoplasma fermentans, a common species of mycoplasma. RNA with 2'-fluoro- or 2'-O-methyl- modified pyrimidines was readily degraded in conditioned media from this culture, but was stable in conditioned media from uncontaminated HEK cells. RNA completely modified with 2'-O-methyls was not degraded in the mycoplasma-contaminated media. RNA zymogram analysis of conditioned culture media and material centrifuged from the media revealed several distinct protein bands (ranging from 30 to 68 kDa) capable of degrading RNA with 2'-fluoro- or 2'-O-methyl-modified pyrimidines. Finally, the mycoplasma-associated nuclease was detected in material centrifuged from the contaminated culture supernatants in as little as 15 minutes with an RNA oligo-containing 2'-O-methyl-modified pyrimidines and labeled with a 5'-fluorescein amidite (FAM) and 3'-quencher. These results suggest that mycoplasma contamination may be a critical confounding variable for cell culture experiments involving RNA-based reagents, with particular relevance for applications involving naked RNA (e.g., aptamer-siRNA chimeras).
Preprocessing Search Spaces for Branch and Bound Search

Heuristic search procedures are useful in a large number of problems of practical importance. Such procedures operate by searching several paths in a search space at the same time, expanding some paths more quickly than others depending on which paths look most promising. Often large amounts of time are required in keeping track of the control knowledge. For some problems, this overhead can be greatly reduced by preprocessing the problem in appropriate ways. In particular, we discuss a data structure called a threaded decision graph, which can be created by preprocessing the search space for some problems, and winch captures the control knowledge for prob lern solving We show how this can be done, and we present an analysis showing that by us ing such a method, a great deal of time can be saved during problem solving processes.
Clinical outcomes of dacryocystorhinostomy with or without intraoperative use of mitomycin C: a systematic review and meta-analysis.

PURPOSE To examine the possible benefit of intraoperative use of mitomycin C (MMC) application in dacryocystorhinostomy (DCR) and to assess its potential risk. METHODS Systematic review and meta-analysis of randomized-controlled trials (RCTs). A comprehensive literature search was performed according to a protocol set in advance. The participants included 811 patients of which 820 eyes were sampled for 14 RCTs. Only pertinent RCTs were identified and included in this meta-analysis. The primary efficacy measure was "patency of irrigation" at follow-up end point. The subjective outcome of "symptom relief" was also extracted as a secondary efficacy measure. For each study, relative risk was extracted. Heterogeneity, publication bias, subgroup, and meta-regression analyses were performed. RESULTS RevMan version 5.0 software was used for statistical analysis. In the primary efficacy measure, the use of MMC can significantly increase the rate of "patency of irrigation" [risk ratio (RR), 1.10; 95% confidence interval (CI), 1.04-1.17; P=0.0006]; the outcome of "symptom relief" was also affected by the use of MMC (RR, 1.15; 95% CI, 1.05-1.26; P=0.003). Sensitivity analysis suggested that the result was comparatively reliable. CONCLUSION Intraoperative use of MMC can bring about a positive effect to the outcomes of "patency of irrigation" and "symptom relief," which increases the success rate of DCR surgery.
Development and Stem Cells Research Article 267

INTRODUCTION Mammalian preimplantation development is a critical period resulting in the commitment to, and segregation of, pluripotent versus extra-embryonic lineages. The implanting mouse blastocyst comprises three spatially and molecularly distinct cell lineages. The trophectoderm (TE) forms an epithelium that encloses a fluid-filled cavity, termed the blastocoel, and an inner cell mass (ICM). The ICM is itself composed of two distinct layers: an inner population of epiblast (EPI) cells and a superficial layer of primitive endoderm (PrE) positioned adjacent to the blastocyst cavity. After implantation, the EPI will go on to form most of the embryo proper as well as extra-embryonic mesoderm (Gardner and Papaioannou, 1975; Gardner and Rossant, 1979). PrE contributes descendants to the visceral and parietal yolk sacs as well as gut endoderm The mechanisms by which EPI and PrE precursors arise and segregate are beginning to be elucidated, and it is now believed that
Defend Your Castle – A Mobile Augmented Reality Multiplayer Game

In today's increasingly digital world, integrating Augmented Reality and multiplayer functionality enhances user engagement. This paper presents an approach for implementing multiplayer in Mobile Augmented Reality environments. Using the Photon Networking Engine, it was implemented a use-case for a medieval-themed game that demonstrates its practical application, addressing challenges such as multiplayer synchronization, scenario loading, and camera stability. Usability tests resulted in a positive System Usability Scale, suggesting good usability. The paper contributes to scientific discourse by offering a solution for multiplayer Mobile Augmented Reality gaming. Future work includes scalability testing and cross-device application.
A Review of Image Segmentation Strategies from Classical Methods to Deep Learning

The intended to achieve from this paper is to provide a thorough examination of digital image segmentation technology by analyzing the strategies and developments that have impacted its evolution. In doing so, we will emphasize the importance of image segmentation in various fields and discuss the techniques used, their origins, and operational principles. Additionally, we will explore how these techniques can be applied in tracing and representing real-world objects historically, from literal depictions to social features that represent future eras. By presenting the events in image segmentation in chronological order, we aim to contextualize them within social and cultural contexts. Furthermore, we will attempt to answer pertinent questions such as who, when, where, what, and why technologies related to the subject were discovered, developed, implemented, and improved. Ultimately, our goal is to explain the significance of image segmentation in remote sensing science, research, and cultural influence more broadly.
Designing a Robust Control System Based on Sliding Mode Control for Two-axis Gimbal Systems

Two-axis gimbals are used in stabilizing and controlling the aiming of optical systems. The main task is to isolate the angular motion of the payload and the disturbances affecting the optical axis of the camera while maintaining the camera’s orientation locked onto the target. Currently, two commonly used gimbal structures are the Yaw-Pitch type and the Roll-Swing type. In this paper, we delve into an in-depth study to develop the full mathematical models for both types, thereby analyzing and evaluating the influence of the cross-channel noise moment effects caused by gimbal imbalance on the stability and aiming control quality under complex angular motion conditions of the payload. Simulation results conducted using MATLAB/SIMULINK with the two-axis gimbal model demonstrate that employing a robust control system significantly reduces the impact of disturbances and enhances the quality of control and stability of the transmission system.
Recent Advances and Future Direction in Lyophilisation and Desiccation of Mesenchymal Stem Cells

Mesenchymal Stem Cells (MSCs) are a promising mammalian cell type as they can be used for the reconstruction of human tissues and organs. MSCs are shown to form bone, cartilage, fat, and muscle-like cells under specific cultivation conditions. Current technology of MSCs cryopreservation has significant disadvantages. Alternative technologies of mammalian cells preservation through lyophilisation or desiccation (air-drying) are among the upcoming domains of investigation in the field of cryobiology. Different protectants and their combinations were studied in this context. Loading of the protectant in the live cell can be a challenging issue but recent studies have shown encouraging results. This paper deals with a review of the protectants, methods of their delivery, and physical boundary conditions adopted for the desiccation and lyophilisation of mammalian cells, including MSCs. A hybrid technique combining both methods is also proposed as a promising way of MSCs dry preservation.
PENGEMBANGAN PERANGKAT PEMBELAJARAN MATEMATIKA DENGAN STRATEGI IDEAL PROBLEM SOLVING BERMUATAN PENDIDIKAN KARAKTER

This research is the development research, done by applying 4-D Thiagarajan model, thathas been modified, by four phases of developing process. They are: defining, planning,developing, and disseminating. One that is developed is learning devices that includessyllabus, lesson plan, student work sheet, student book, and ability problem solving testinstrument. Techniques of data collection in this research by using validation sheetlearning teaching process set, observation of student activity sheet, questionnaire ofmotivates to study sheet, observation teacher capability sheet in learning teachingmanagement and the test of student’s ability of problem solving. The result of thisresearch shows that learning devices is valid and effective. The validity and the effectivitylearning devices shown by from result of try out are: students’ ability in problem solvinghas reached the mastery learning, higher than KKM; the average of students’ ability inproblem solving by using learning devices with IDEAL problem solving strategy withcharacter education content is 74,69 is higher than the average of students’ ability inproblem solving using expository with conventional teamwork that is only 70,75; thestudents’ activity and studying motivation in the learning process influence positively tothe students’ ability problem solving. The character education content that is observed isgood category in observation of student activity. Keywords : Character Education, Development, Problem Solving
Attributional Processes and Alienation: A Typology of Worker Responses to Unequal Power Relationships

This paper represents an attempt to understand the lack of strong empirical evidence for the alienation of workers under conditions of task specialization, task routinization, and limited worker control. Based on a review of the literature and informed by'attribution theory, a typology is presented of worker responses to the unequal power relationships in the workplace. The typology identifies responses by the attributions underlying them and suggests the consequent probability of alienation for each response.
An Improved YOLOv5 Detection Algorithm with Pruning and OpenVINO Quantization

In order to address the problem of current object detection models being too large to be deployed on robot controllers, this paper proposes improvements to YOLOv5 for real-time detection. The YOLOv5s model is pruned at the Batch Normalization (BN) layer, and further optimized using the OpenVINO tool for quantization. The results demonstrate that our improvements effectively improve the model's inference speed while maintaining its accuracy. Compared to the original YOLOv5 model, the pruned model achieves the same accuracy without degradation, with a 36.6% reduction in parameter count and a 35% reduction in weight storage file size. Furthermore, after optimization with OpenVINO, the final model achieves a FPS of 56.
The effects of intranasal oxytocin administration on resting state electroencephalography frontal asymmetry

Research suggests that the nonapeptide oxytocin plays an important role in social functioning, and that the intranasal administration of exogenous oxytocin promotes prosocial behaviours. The mechanisms underlying oxytocin’s effects on social cognition and behaviour are not yet well understood. One viable hypothesis is that oxytocin acts upon frontal asymmetry. Relative left frontal neural activation has been consistently associated with approach behaviours and shares a number of other similarities with intranasal oxytocin administration. For the first time, we examined the hypothesis that oxytocin increases relative left frontal neural activation using electroencephalography methodology. In a double-blind within-subject experiment, 48 participants self-administered a 24 I.U. dose of intranasal oxytocin and placebo approximately one week apart. Following drug administration, alpha band power was recorded at frontal and parietal sites during eight 60 second trials. Intranasal oxytocin administration did not produce any significant changes in frontal asymmetry (F(1, 47) = . 273, p= . 604, partial η2 = . 006). This relation did not interact with sex nor measures of depression, which have been shown to moderate the effects of intranasal oxytocin in prior investigations. Oxytocin administration does not appear to increase relative left frontal neural activation. Additional considerations and interpretations are discussed.
The personal experience of chronic benign lower back pain: An interpretative phenomenological analysis

This thesis is a qualitative study of chronic benign low back pain (CBLBP). Psychological factors play an important role in the genesis and maintenance of CBLBP but the processes involved are poorly understood. The meaning of the pain for the sufferer is considered to be important and more research into this area that takes an idiographic approach is recommended in the literature. Three empirical studies are reported which employ Interpretative Phenomenological Analysis (IPA) to explore the personal experience of CBLBP. A range of themes are discussed that capture the meaning of the pain for the sufferer and help to understand the dynamic relationship between the pain sensation, distress and disability. The first study is exploratory, the participants' struggle to make a coherent sense of their pain is revealed along with the related personal and social implications. In the second study the experience of pain itself is focused on more closely in the context of a simple intervention. Descriptions of the pain are given which reveal its threatening aspect and suggest that the participants' self-appraisal in the face of this threat is important. The factors underlying change are discussed and the contribution of contextual factors is emphasised. The first two studies indicated that the self-concept was worthy of further study and it became the explicit focus of the third study. The relevance of the self was highlighted and it was shown to be indivisible from the lived experience of CBLBP. The three studies reveal the multi-dimensional complexity of CBLBP and highlight how its inherent `unpleasantnessr'e presentsm ore than a noxious sensory experience but unfolds within a dynamic personal and social context. The emergent themes are reviewed and discussed in relation to the literature and implications for further research and clinical practice are suggested.
Using Hidden Markov Modeling to Decompose Human-Written Summaries

Professional summarizers often reuse original documents to generate summaries. The task of summary sentence decomposition is to deduce whether a summary sentence is constructed by reusing the original text and to identify reused phrases. Specifically, the decomposition program needs to answer three questions for a given summary sentence: (1) Is this summary sentence constructed by reusing the text in the original document? (2) If so, what phrases in the sentence come from the original document? and (3) From where in the document do the phrases come? Solving the decomposition problem can lead to better text generation techniques for summarization. Decomposition can also provide large training and testing corpora for extraction-based summarizers. We propose a hidden Markov model solution to the decomposition problem. Evaluations show that the proposed algorithm performs well.