Miracle-dz/UniFAR-FTUs huggingface dataset:
Topology from the Bottom Up

Every soccer ball has 12 pentagons, even when it is deflated. In his Perspective, [Kamien][1] describes how [ Bausch et al . ][2] exploit this topological property in the design of complex new materials based on the self-assembly of two-dimensional colloidal crystals on spheres. The work is an example of a growing trend in materials science to control not only the geometry but also the connectivity (and hence topology) of molecules in self-assembled materials. The approach reported by Bausch et al . is particularly powerful because it is not dependent on specific interactions and should therefore allow the assembly of a wide range of hierarchical, self-assembled materials. [1]: http://www.sciencemag. org/cgi/content/full/299/5613/1671 [2]: http://www.sciencemag. org/cgi/content/short/299/5613/1716
On the Explainable Detection of Stress Levels Using Heart Rate Variability Based Deep Neural Networks

This paper presents one of the first explorations of transparency and explainability of Heart Rate Variability (HRV) based deep learning models designed for stress detection. We employed Shapley additive explanations (SHAP) as an explainable AI (XAI) method, and cross-validated the results with saliency maps, which provides valuable insights into the main contributing factors for decision-making process of these deep models.
Study on the Detection Technology of Multiple Mixed Gas Concentration

In this paper, to solve the problem of cross-response when a single sensor detects gas, a multi-component gas concentration detection method based on information fusion technology is studied, which can accurately detect the concentration of any gas mixture. The detection method of multi-component gas concentration is to identify and detect multi-component gas by support vector machine and BP neural network, optimize the parameters of BP neural network by the steepest descent method, and finally get the best fitting curve, and the output result is the gas concentration of each component.
Scene Graph Generation from Images

Image understanding by computer is advancing exponentially these days due to the phenomenal success of deep learning, but there is still much work left for the computers to reach human level perception. Image classification (sometimes with localization) is one of the standard task, but this is far from the image understanding. The other tasks such as image caption generation or visual question answering have also reached to practical level of quality, but these are still far from the complete image understanding. Image caption generation, which is a task that generates a summary sentence from an image, cannot fully describe rich scenery in an image. Visual question answering also answers simple questions, but cannot answer questions that requires complex reasoning. In order to fully understand an image, we need to know; what objects are in the image, what are the characteristics of objects, and how these objects interact to each other.
Direct Cell-Cell Contact between Mesenchymal Stem Cells and Endothelial Progenitor Cells Induces a Pericyte-Like Phenotype In Vitro

Tissue engineering techniques for the regeneration of large bone defects require sufficient vascularisation of the applied constructs to ensure a sufficient supply of oxygen and nutrients. In our previous work, prevascularised 3D scaffolds have been successfully established by coculture of bone marrow derived stem cells (MSCs) and endothelial progenitor cells (EPCs). We identified stabilising pericytes (PCs) as part of newly formed capillary-like structures. In the present study, we report preliminary data on the interactions between MSCs and EPCs, leading to the differentiation of pericyte-like cells. MSCs and EPCs were seeded in transwell cultures, direct cocultures, and single cultures. Cells were cultured for 10 days in IMDM 10% FCS or IMDM 5% FCS 5% platelet lysate medium. Gene expression of PC markers, CD146, NG2, αSMA, and PDGFR-β, was analysed using RT-PCR at days 0, 3, 7, and 10. The upregulation of CD146, NG2, and αSMA in MSCs in direct coculture with EPCs advocates the MSCs' differentiation towards a pericyte-like phenotype in vitro. These results suggest that pericyte-like cells derive from MSCs and that cell-cell contact with EPCs is an important factor for this differentiation process. These findings emphasise the concept of coculture strategies to promote angiogenesis for cell-based tissue engineered bone grafts.
Collaborative gaming in augmented reality

We introduce a local collaborative environment for gaming. In our setup multiple users can interact with the virtual game and the real surroundings at the same time. They are able to communicate with other players during the game. We describe an augmented reality setup for multiple users with see-trough head-mounted displays, allowing dedicated stereoscopic views and individualized interaction for each user. We use face-snapping for fast and precise direct object manipulation. With face snapping and the subdivision of the gaming space into spatial regions, the semantics of actions can be derived out of geometric actions of the user. Further, we introduce a layering concept allowing individual views onto the common data structure. The layer concept allows to make privacy management very easy by simply manipulating the common data structure. Moreover, assigning layers to spatial regions carefully, a special privacy management is often not necessary. Moving objects from one region into another will automatically change their visibility and privacy for each participant. We demonstrate our system with two example board-games: Virtual Roulette and MahJongg, both relying heavily on social communication and the need of a private space.
Neuron-specific enolase and S100B protein levels in recreational scuba divers with neurological decompression sickness.

INTRODUCTION Neuron-specific enolase (NSE) and S100B protein are brain-origin proteins commonly described to assess the presence and severity of neurological injury. To date, there are limited data examining the influence of scuba diving on these biomarkers, particularly when symptoms of decompression sickness (DCS) occur. The purpose of this controlled study was to determine whether these serum neurochemical markers could be used as 1) indicators of neurological DCS and 2) predictors of incomplete recovery. METHODS Fifty-nine divers with neurological DCS and 37 asymptomatic divers admitted for inadequate decompression, serving as controls, were consecutively enrolled between 2010 and 2012. Blood samples were collected at initial presentation up to 6 hours after dive completion (controls) or onset of symptoms (DCS divers). Biomarkers were quantified in nonhaemolysed samples only. Clinical outcome was assessed at 6 months post-injury. RESULTS The two groups did not differ regarding the variables examined, except for the total dive time which was slightly shorter in the control group. NSE, but not S100B protein, was higher in the DCS group than in controls (P < 0.0001). An NSE level > 15.9 µg L⁻¹ determined by ROC analysis predicted DCS development with a specificity of 100% (95% confidence interval (CI) 90 to 100) and a sensitivity of 24% (95% CI 14 to 36). There was a trend towards a higher likelihood of residual neurological deficits above this cut-off value (P = 0.08). CONCLUSIONS Early determination of NSE was found to be useful for the diagnosis of neurological DCS with a high specificity. However, its clinical applicability in decision making for determining treatment as well as its prognostic value remains to be established. Reliability of S100B protein was not demonstrated in the present study.
Procedural Primitives in a High Performance, Hardware Accelerated, Z-Buffer Renderer

In the past, very few types of primitives have been directly supported by graphics accelerators, in spite of the fact that a great variety of complex primitives are routinely used for high-quality rendering. We explore the issues associated with the support of arbitrary procedural primitives, and describe a machine-independent language as well as an extension to OpenGL designed to support userdefined procedural primitives. We have created a prototype implementation on PixelFlow, a highperformance graphics accelerator.
Tolerating data access latency with register preloading

By exploiting fine grain parallelism, superscalar processors can potentially increase the performance of future supercomputers. However, supercomputers typically have a long access delay to their first level memory which can severely restrict the performance of superscalar processors. Compilers attempt to move load instructions far enough ahead to hide this latency. However, conventional movement of load instructions is limited by data dependence analysis. This paper introduces a simple hardware scheme, referred to as preload register update, to allow the compiler to move load instructions even in the presence of inconclusive data dependence analysis results. Preload register update keeps the load destination registers coherent when load instructions are moved past store instructions that reference the same location. With this addition, superscalar processors can more effectively tolerate longer data access latencies.
Dose-Dependent Effects of Glyburide on Insulin Secretion and Glucose Uptake in Humans

Objective To examine the relationship between plasma glyburide concentrations (0, 50, 100, 200, 400, and 800 nM) and the insulin response and glucose metabolism during euglycemic (4.6 ± 0.1 mM) and hyperglycemic (11.6 ± 0.2 mM) conditions. Research Design and Methods Nine healthy subjects participated in the study. Steady-state plasma glyburide concentrations were achieved by primed continuous intravenous infusion of glyburide. Results During both euglycemia and hyperglycemia, glyburide enhanced insulin secretion and glucose disposal only to drug levels of 100–200 nM corresponding to an oral dose ≤ 10 mg. Conclusions The data suggest that glyburide (and probably other sulfonylureas), operates within a narrow range of plasma concentrations (50–200 nM), which can be achieved with very low doses of the drug. It remains to be shown whether the threshold of maximal effect also in clinical practice is achieved with lower sulfonylurea doses than that currently used.
Effect of Cement Characteristics on Concrete Properties

This publication discusses how different cement characteristics affect properties of fresh and hardened concrete. Cement characteristics include chemical composition (main composition, Bogue calculation, alkalies, sulfates, minor components, loss on ignition, insoluble residue) and physical properties (fineness, particle size distribution, setting, compressive strength, heat of hydration, soundness). Concrete properties cover fresh concrete (workability, water requirement, slump, rheology, setting time, bleeding, admixture compatibility, heat of hydration) and hardened concrete (strength, shrinkage, air content, transport properties) including durability (alkali silica reation (ASR), chloride permeability, sulfate resistance)). Summary tables compare the changes in characteristics of cement with predicted or observed concrete behavior.
Examining the school governing bodies’ and their financial management roles and functions in public schools

The purpose of this paper is to examine the school governing bodies (SGBs) and their financial management roles and functions in public schools. Participants were 24 members of the SGBs’ finance committees who were selected through a purposive sampling technique. A qualitative research approach was followed, and an exploratory case study design was applied. Data was collected through in-depth interviews, focus group discussions and secondary documents, and it was analyzed through thematic and document analysis techniques. The findings revealed that members of SGBs do not understand their financial management roles and functions as they do not have the requisite knowledge and skills (Bisschoff & Thurlow, 2005; Dlomo et al., 2022; Sebidi et al., 2023). The findings also revealed that some financial decisions are not taken by designated finance committees, and this compromises the financial management responsibility of SGBs. Furthermore, this study finds that parent members of the SGBs are mostly financially illiterate and passive in meetings, hence their reliance on the school principal for financial decisions (Kruger et al., 2022). This study concludes that members of SGBs must be adequately trained in financial management skills so that they can effectively support their schools.
Neonatal Thrombocytopenia as a Consequence of Maternal Preeclampsia

Abstract Introduction Preeclampsia (preE) is pregnancy-induced hypertension affecting a significant proportion of pregnant women worldwide and can cause detrimental effects in the mother and newborn. Some of the effects in the newborn include neonatal thrombocytopenia. Pertaining specifically to neonatal thrombocytopenia, several questions remain unanswered. Discussion According to the current literature, neonatal thrombocytopenia due to maternal preE is highly prevalent in the general population and the incidence is reported to be around 30% worldwide. This review gives an insight into the syndrome and summarizes the possible pathological mechanisms, the diagnostic approach, complications, and therapeutic interventions of neonatal thrombocytopenia. It also identifies the involvement of other cell lines, apart from platelets in the newborns. Furthermore, we suggest a future prospective study to investigate the pathogenesis of preE and plan a study involving animal models to come up with a possible therapeutic intervention to prevent preE and its various consequences in neonates.
BORT-RD: An Improved Model for Software Engineering Design Feature Generation

By studying the connections and dependencies between requirement features and design features in software development documentation, and incorporating the advantages of various Transformer-like models, a BORT-RD model applicable to generating design features is proposed in this text. This model is based on the syntactic decomposition of requirement documents and design documents to train feature phrases. The model has been improved in terms of input embedding, attention calculation and fine-turning, targeting the characteristics of software engineering documents. Through experiments, the model’s precision, accuracy and recall have been increased to 81.18%, 94.4%, and 83.1%, respectively, showing significant improvements compared to traditional classical Transformer models.
Automatic Classification of Volcano Seismic Signatures

The prediction of volcanic eruptions and the evaluation of associated risks remain a timely and unresolved issue. This paper presents a method to automatically classify seismic events linked to volcanic activity. As increased seismic activity is an indicator of volcanic unrest, automatic classification of volcano seismic events is of major interest for volcano monitoring. The proposed architecture is based on supervised classification, whereby a prediction model is built from an extensive data set of labeled observations. Relevant events should then be detected. Three steps are involved in the building of the prediction model: (i) signals preprocessing, (ii) representation of the signals in the feature space, and (iii) use of an automatic classifier to train the model. Our main contribution lies in the feature space where the seismic observations are represented by 102 features gathered from both acoustic and seismic fields. Ideally, observations are separable in the feature space, depending on their class. The architecture is tested on 109,609 seismic events that were recorded between June 2006 and September 2011 at Ubinas Volcano, Peru. Six main classes of signals are considered: long‐period events, volcanic tremors, volcano tectonic events, explosions, hybrid events, and tornillos. Our model reaches 93.5% ± 0.50% accuracy, thereby validating the presented architecture and the features used. Furthermore, we illustrate the limited influence of the learning algorithm used (i.e., random forest and support vector machines) by showing that the results remain accurate regardless of the algorithm selected for the training stage. The model is then used to analyze 6 years of data.
A Change Detection Method for Misaligned Point Clouds in Mobile Robot System

3D change detection of point clouds measured by 3D sensors such as LiDAR is become more widespread and is now being used in various tasks related to natural disaster evaluation, agricultural assessment, and so on. Such tasks are increasingly being automated by mobile robots such as Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs). For efficient task execution with robots, realtime change detection is required. Some degree of localization error of robots when performing tasks is inevitable, and this makes it difficult to align point clouds measured at different times. The point clouds need to be converted into a global coordinate system in order to compare them, and the misalignments caused by localization error degrade the accuracy of the change detection. In this paper, we propose a change detection method that is robust to the misalignment of point clouds. Our method does not require training and takes a feature-based approach utilizing occupied, free, and unknown attributes created by analyzing the point clouds. Using a realistic robotics simulator, we generate synthetic point clouds of warehouse scenes for change detection tasks, and the misalignment of point clouds is reproduced. We evaluated the proposed and conventional methods with the point clouds, and the proposed method proved to be more accurate than conventional methods.
Room Temperature Lasing in 1-μm Microdisk Quantum Dot Lasers

Lasing characteristics of InAs/InGaAs quantum dot microdisks with diameter varied from 1 to 6 μm were studied under optical pumping. The disks were fabricated with standard photolithography and two-step wet etching. We demonstrate room temperature lasing in the 1.29-1.32-μm wavelength range (ground-state transition) in microlasers as small as 1 μm in diameter. The microlasers demonstrate narrow linewidths (40-60 pm), low thermal impedance (85°C/mW), and low threshold powers (50-100 μW).
Anti-Monocyte Chemoattractant Protein-1 Gene Therapy Limits Progression and Destabilization of Established Atherosclerosis in Apolipoprotein E–Knockout Mice

Background—Monocyte infiltration into the arterial wall and its activation is the central event in atherogenesis. Thus, monocyte chemoattractant protein-1 (MCP-1) might be a novel therapeutic target against atherogenesis. We and others recently reported that blockade or abrogation of the MCP-1 pathway attenuates the initiation of atheroma formation in hypercholesterolemic mice. It remains unclear, however, whether blockade of MCP-1 can limit progression or destabilization of established lesions. Methods and Results—We report here that blockade of MCP-1 by transfecting an N-terminal deletion mutant of the MCP-1 gene limited progression of preexisting atherosclerotic lesions in the aortic root in hypercholesterolemic mice. In addition, blockade of MCP-1 changed the lesion composition into a more stable phenotype, ie, containing fewer macrophages and lymphocytes, less lipid, and more smooth muscle cells and collagen. This strategy decreased expression of CD40 and the CD40 ligand in the atherosclerotic plaque and normalized the increased chemokine (RANTES and MCP-1) and cytokine (tumor necrosis factor &agr;, interleukin-6, interleukin-1&bgr;, and transforming growth factor &bgr;1) gene expression. These data suggest that MCP-1 is a central mediator in the progression and destabilization of established atheroma. Conclusions—The results of the present study suggest that the inflammatory responses mediated by MCP-1 are important in atherosclerosis and its complications.
Designing an Interpretable Credit Scoring System Using Fuzzy Association Rules

“Credit Scoring (CS)” refers to methods for evaluating the creditworthiness of individuals or legal entities applying for bank loans. The credit rating is typically expressed as a numerical score, with higher scores indicating more creditworthy loan applicants. However, this process carries severe risks in financial management. For this reason, Credit Risk(CR) analysis has become an important topic and, recently, one of the primary goals of the banking and financial sectors. The use of credit risk analysis for personal and business bank credits has become very common. This paper employs fuzzy association rule mining to extract frequent rules for good and bad credit applicants from a dataset. The extracted rules were applied to the CS system and correctly classified 79.9% of the credit requests. A key advantage of this method is that it provides an interpretable model capable of classifying requests with adequate accuracy. ”
Levels and predictors of physical activity in a sample of pre-retirement and retired civil servants in Nigeria.

BACKGROUND Lack or inadequate physical activity may have dire health implications on both pre-retirement and retired individuals. Previous studies on the socioeconomic and demographic predictors of physical activity in this population may not fully apply in African because most were conducted outside the continent, hence this study. METHODS A cross sectional survey of pre-retirement and retired civil servants in Kano State, North-Western Nigeria. A total of 532 participants comprising equal halves of sex-matched pre-retired and retirees met the inclusion criteria. We investigated their socioeconomic and demographic background as well as participation in vigorous and moderate physical activities, walking and sitting using the International Physical Activity Questionnaire. Regression analyses were conducted to identify predictors of moderate physical activities. RESULTS Only 38.3% of pre-retired and 22.1% of the retirees engaged in moderate physical activities level. Being male, lower age, living in a rural settlement (OR = 1.56; 95% CI = 1.27-1.82), lower income and lower job/retirement years increased the odds of moderate activities in the pre-retired and retirees (except age and gender). Additionally, unavailability of recreational facilities (OR = 0.42; 95% CI = 0.33-0.61) was linked to lesser engagement in moderate physical activities in the retirees. CONCLUSION Pre-retirement civil servants and retirees were physically active in both work and leisure mainly at the sub-moderate level, with lesser engaging in moderate level but below the recommended frequency. Settlement type, income and years of job/retirement were the common predictors of moderate physical activity in both groups.