Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal trees for prediction and prescription

For the past 30 years, decision tree methods have been one of the most widelyused approaches in machine learning across industry and academia, due in large part to their interpretability. However, this interpretability comes at a price—the performance of classical decision tree methods is typically not competitive with stateof-the-art methods like random forests and gradient boosted trees. A key limitation of classical decision tree methods is their use of a greedy heuristic for training. The tree is therefore constructed one locally-optimal split at a time, and so the final tree as a whole may be far from global optimality. Motivated by the increase in performance of mixed-integer optimization methods over the last 30 years, we formulate the problem of constructing the optimal decision tree using discrete optimization, allowing us to construct the entire decision tree in a single step and hence find the single tree that best minimizes the training error. We develop highperformance local search methods that allow us to efficiently solve this problem and find optimal decision trees with both parallel (axes-aligned) and hyperplane splits. We show that our approach using modern optimization results in decision trees that improve significantly upon classical decision tree methods. In particular, across a suite of synthetic and real-world classification and regression examples, our methods perform similarly to random forests and boosted trees whilst maintaining the interpretability advantage of a single decision tree, thus alleviating the need to choose between performance and interpretability. We also adapt our approach to the problem of prescription, where the goal is to make optimal prescriptions for each observation. While constructing the tree, our method simultaneously infers the unknown counterfactuals in the data and learns to make optimal prescriptions. This results in a decision tree that optimizes both the predictive and prescriptive error, and delivers an interpretable solution that offers significant improvements upon the existing state-of-the-art in prescriptive problems. Thesis Supervisor: Dimitris Bertsimas Title: Boeing Professor of Operations Research Co-director, Operations Research Center
The Clinical Status of Meningothelial Meningioma Patients

Background: Understanding the clinical status of patients with meningothelial meningioma is crucial for accurate prognosis, treatment planning, and monitoring disease progression. Numerous factors, including tumor characteristics, patient demographics, and histopathological features, contribute to the clinical status and overall management of these patients. Objective: To assess the clinical status of meningothelial meningioma patients. Method: This descriptive cross-sectional study was carried out at the Department of Pathology, Dhaka Medical College over a period of two years from January 2018 to December 2019. A total of 60 Patient of any age group with histologically diagnosed meningiomas of the central nervous system were included as a sample population. During the collection of specimen, all relevant information were recorded systematically in a prepared proforma. All the cases were numbered chronologically and the same number was given to H&E as well as in immunohistochemically stained slides. Results: During the study, majority were belong to 51-60 years and 61-70 years age group, 26.7% and majority were female, 70%. It revealed that maximum lesions (86.7%) were at brain and 13.3% were at the spinal cord. It was observed that meningioma was widely distributed throughout the CNS. Majority of the lesions were at the parietal region (28.3%). 18.3% lesions were at frontal region. Plus, according to the tumor grade, It was observed that more than three fourth (80.5%) patients had grade I tumor, 17.8 % patients had grade II tumor and 1.7 % patients had grade III tumor. Moreover, that 55% cases were meningothelial meningioma and 8 (13.3%) patients had atypical meningioma. Conclusion: In our study, maximum patients had lesions were at brain which was widely distributed throughout the CNS. Plus, more than three fourth patients had grade I tumor where meningothelial meningioma was most common.
DeepFaceReshaping: Interactive Deep Face Reshaping via Landmark Manipulation

Deep generative models allow the synthesis of realistic human faces from freehand sketches or semantic maps. However, while being flexible, sketches and semantic maps provide too much freedom for manipulation and are thus not very easy to control by novice users. In this work, we present DeepFaceReshaping, a novel landmark-based deep generative framework for interactive face reshaping. To realistically edit the shape of a face by manipulating a small number of face landmarks, we employ neural shape deformation to reshape individual face components. We then propose a novel Transformer-based partial refinement network to synthesize the reshaped face components conditioned on the edited landmarks, and fuse the components to generate the entire face in a local-to-global approach. In this way, we limit possible reshaping effects within a feasible component-based face space. Our interface is thus intuitive even for novice users, as confirmed by a user study. Our experiments show that our method outperforms a traditional warping-based approach and the recent deep generative techniques.
New Orbits for 18 Binaries

Orbital elements of 18 visual binaries are computed using the measurements collected in the Fourth Catalog of Interferometric Measurements of Binary Stars; 15 orbits are determined for the first time and three orbits are revised. Eleven of the binaries, denoted as HDS, were discovered during the Hipparcos mission. The remaining binaries were discovered a few years earlier or later than 1991. All studied pairs are close, and all measured separations are less than . The shortest orbital period is 10 years and the longest orbital period is 127 years. Dynamical parallaxes and total masses of systems are derived from the orbital elements. We also give absolute magnitudes, spectral types, and residuals in θ and ρ.
On the use of full particle trajectories and vorticity transport for dense velocity field reconstruction

A procedure is proposed to reconstruct the instantaneous velocity field from full particle trajectories in a data assimilation framework that includes the vorticity transport equation. The technique is christened as time-segment assimilation (TSA). The work addresses the common problem of low seeding concentration in 3D experiments, usually leading to limited spatial resolution. In the present study the measurement fidelity and spatial resolution are increased by considering finite time-segments as a whole for instantaneous velocity reconstruction. The use of a time-segment for velocity field reconstruction from measurement data extends previously proposed data assimilation techniques that consider only instantaneous measurement data (e.g. VIC+ and FlowFit), to use finite measurement time-segments. The assessment with sinusoids indicates lower errors due to modulation. However, the appearance of a range of amplified peaks is not fully understood. In the case of a simulated turbulent boundary layer measurement more vortical structures are recovered when a longer time-segment is used for the velocity field reconstruction.
GOMME: A Generic Ontology Modelling Methodology for Epics

Ontological knowledge modelling of epic texts, though being an established research arena backed by concrete multilingual and multicultural works, still suffers from two key shortcomings. Firstly, all epic ontological models developed till date have been designed following ad-hoc methodologies, most often combining existing general purpose ontology development methodologies. Secondly, none of the ad-hoc methodologies consider the potential reuse of existing epic ontological models for enrichment, if available. This paper presents, as a unified solution to the above shortcomings, the design and development of GOMME - the first dedicated methodology for iterative ontological modelling of epics, potentially extensible to works in different research arenas of digital humanities in general. GOMME is grounded in transdisciplinary foundations of canonical norms for epics, knowledge modelling best practices, application satisfiability norms, and cognitive generative questions. It is also the first methodology (in epic modelling but also in general) to be flexible enough to integrate, in practice, the options of knowledge modelling via reuse or from scratch. The feasibility of GOMME is validated via a first brief implementation of ontological modelling of the Indian epic Mahabharata by reusing an existing ontology. The preliminary results are promising, with the GOMME-produced model being both ontologically thorough and competent performance-wise.
Thermal Expansion Investigations of Oilwell Cements Using a Novel Apparatus.

In the coming future, renewable energies will become an essential source to fulfill the increasing global demand for energy. Geothermal energy is a form of renewable energy and is being widely adopted around the world where suitable temperature exists in subsurface layers. Therefore, for the extraction of geothermal energy, wells have to be drilled and assurance should be made that well integrity is not compromised. In that respect, cementation plays an important role as the cement in the geothermal well is continuously exposed to thermal cyclic loading. These loads might affect the behavior and properties of cement and therefore can jeopardize the well integrity. For that reason, knowing the geometrical changes that cement might have due to the thermal loadings should be properly investigated. This paper will be presenting experimental results on linear thermal expansion of the different classes of cement that are exposed to high temperatures which will help in understanding the behavior of the cement in the geothermal environment. The paper will present the setup that has been designed and the results obtained on several cement recipes as well as few reference materials. Our results provide extremely reliable results for future well integrity simulations.
Towards Integration of Sustainable User Experience Aspects in Software Systems Design: A Human-Centered Framework

The usage of software systems has immense impacts on human psychological well-being (a primary user experience outcome). The World Health Organization refers to well-being as “a positive state”, encompassing e.g., a good quality of life. Studies have shown that the human well-being is dependent on the satisfaction of certain psychological needs. However, normally, the software system development processes capture requirements that are needed to fulfill the purpose of the system itself and not the psychological requirements of humans who use and interact with these systems on an everyday basis. In order to address this challenge, we present a framework, named as SUXEH (Sustainable User eXperiences Enabled Human-centered) framework, that addresses human psychological needs explicitly as one of the main modelling efforts in the early stages of the development process. The framework does so in a way that eases the integration of sustainable user experience aspects (mediated by the human needs) in the systems design phase of the overall development process.
Chaos induced by weak A-coupled-expansion of non-autonomous discrete dynamical systems

Abstract This paper focuses on chaos induced by weak A-coupled-expansion of non-autonomous discrete systems in compact subsets of metric spaces and in bounded and closed subsets of complete metric spaces, separately. A new concept of weak A-coupled-expansion for non-autonomous discrete systems, whose condition is weaker than that of A-coupled-expansion, is introduced, and several new criteria of chaos induced by weak A-coupled-expansion of non-autonomous discrete systems are established. By applying some close relationships between chaotic dynamical behaviours of the original system and its induced systems, two criteria of chaos are established. One example is provided for illustration.
Establishing a Hierarchical Approach to Explore Biological Contributors to Dynamic Response and Failure in the Human Thorax

This paper has not been screened for accuracy nor refereed by any body of scientific peers and should not be referenced in the open literature. ABSTRACT Establishing thoracic response targets and injury thresholds are important for design and validation of biofidelic Anthropomorphic Test Devices (ATDs) and computational models utilized to mitigate injury risk of vehicle occupants. This is done through extensive exploration of post-mortem human subject (PMHS) whole thoracic and rib properties, which has occurred for many decades with considerable success. However, the majority of research has focused on the 50 th percentile male and relies heavily on population means or a select few individuals thought to best represent those population means. Little attempt has been made to understand the full breadth of human variation, mostly because of test sample limitations. Ultimately, a significant gap in knowledge remains; the biological mechanisms and anatomical variability that determines an individual’s thoracic response and injury risk are not fully understood. It is therefore important to explore innovative ways to fully expand our understanding of thoracic variation to improve the tools used to decrease injury risk and protect ALL vehicle occupants. The objective of this study is to explore contributions to thoracic response and injury risk using a multi-phase, hierarchical approach to experimental testing and data analysis to elucidate mechanistic explanations. Dynamic (2 m/s) experiments simulating a frontal impact conducted in the laboratory on ribs from donors of all ages (4-108 years) form the basis of this work (n=272). From individual ribs tests, structural properties are assessed (e.g., linear structural stiffness), and explanatory variables collected or calculated include curve length of the entire rib (global geometry) and total subperiosteal area (cross-sectional geometry). Novel cross-sectional geometric
Integrating Information Technology in Healthcare: Recent Developments, Challenges, and Future Prospects for Urban and Regional Health

The use of technology in healthcare has become increasingly popular in recent years, with the potential to improve how healthcare is delivered, patient outcomes, and cost-effectiveness. This review paper provides an overview of how technology has been used in healthcare, particularly in cities and for personalized medicine. The paper discusses different ways technology is being used in healthcare, such as electronic health records, telemedicine, remote monitoring, medical imaging, wearable devices, and artificial intelligence. It also looks at the challenges and problems that come with using technology in healthcare, such as keeping patient data private and secure, making sure different technology systems can work together, and ensuring patients are comfortable using technology. In addition, the paper explores the potential of technology in healthcare, including improving how easily patients can get care, the quality of care they receive, and the cost of care. It also talks about how technology can help personalize care to individual patients. Finally, the paper summarizes the main points, makes recommendations for healthcare providers and policymakers, and suggests directions for future research. Overall, this review shows how technology can be used to improve healthcare, while also acknowledging the challenges that come with using technology in this way.
Prevalence and Virulence Genes of Vibrio and Aeromonas Species Isolated from Nile Tilapia and Mugil Fish Farms in Egypt

| The present study was designed to determine the prevalence of Vibrio and Aeromonas in Nile tilapia and Mugil fish farms in Egypt and monitoring some virulence genes associated with V. parahaemolyticus and A. hydrophila isolates. One hundred diseased fishes (50 for each Nile tilapia and Mullet fish) were collected over 10 months from January to October 2019 and submitted to bacteriological and biochemical examination. Randomly selected 5 isolates of Vibrio species were submitted for molecular identification using species-specific PCR ( tox R gene for V. parahaemolyticus and collagenase for V. alginolyticus ) and the molecular detection of virulence genes including rec A and trh in V. parahaemolyticus isolates. Other 5 A. hydrophila isolates were examined for the molecular detection of virulence genes including fla , aer A, hly A, and ahcytoen genes. Vibrio species isolated with a prevalence of 65.0% for 100 examined fishes. Vibrio parahaemolyticus, V. alginolyticus, and V. cholerae were isolated with a prevalence of 55.4, 33.8, and 10.8%, respectively. Aeromonas species were isolated with a prevalence of 72.0% for 100 examined fishes where A. hydrophila and A. caviae were isolated with a prevalence of 99.3 and 9.7%, respectively. PCR results showed tox R gene was detected in all five isolated Vibrio species, rec A virulence gene was detected in three out of the five tested V. parahaemolyticus isolates. Meanwhile, the trh gene was not detected. On the other hand, aer A and hly A virulence genes were detected in all five isolated A. hydrophila . Ahcytoen was detected in 4 out of 5. Meanwhile, the fla gene was detected in 1 out of the tested 5 A. hydrophila isolates. The high prevalence of Vibrio and Aeromonas species in this study with an elevated coexistence of their virulence genes threatens the aquaculture industry in Egypt and poses a public health concern.
Lip position in the smile aesthetic: Literature review

Objective: Determine the lip position influence on dental aesthetics in adults older than 19 years according to academic publications in the last 5 years. Material and methods: A systematic research was carried out in the medical literature (UNAM, Cochrane, BVS, Scielo, PubMed), using the following search strategy: (lip line) OR (smile line) AND (parameters) AND (analysis) AND (evaluation) to identify articles that reported data on lip position parameters that influence dental aesthetics. The results of each study were extracted and classified as follows: smile line or lip line, length of the lip with the smile line, gingival display, smile arc, smile type and upper lip curvature. Results: From the 4497 articles analyzed, 17 studies were selected for the final review process. Considering the studies in this literature review, the most frequent criteria are: a midline smile, a low gummy smile line, a consonant smile arc, a static smile, a commissural type of smile, and an upward curvature of the upper lip. Conclusions: An aesthetically attractive smile includes different parameters, among those that have a positive influence are a high or medium anterior smile line, a parallel smile arc, straight or upward upper lip curvature, type of commissural smile and a gingival exposure less than 2 mm.
Mesh sensitivity investigation in the discrete adjoint framework

Aerodynamic optimisation using gradient-based methods has found a wide range of academic applications in the last 30 years. This framework is also becoming more and more popular in the industrial world where, most of the time, unstructured grids are largely used. In this framework, apart from the need to solve the flow field, there is the need to quickly map the aerodynamic surface in terms of some aerodynamic figure of merits such as the drag coefficient, without being limited by the computational expense related to the grid size. This is a concrete industrial need which requires the efficient computation of the grid sensitivity. A novel method based on the DGM (Delaunay Graph Mapping) mesh movement is proposed to efficiently compute the grid sensitivity required in the discrete adjoint optimisation framework. The method makes use of a one-to-one explicit algebraic mapping between the volume mesh and the solid boundary nodes. This procedure results in a straightforward computation of the gradient without the need to invert a large, sparse and stiff matrix generally associated with implicit mesh movements such as the spring or LE (Linear Elastic) analogy. The method is verified using FDs (Finite Difference) and a thorough comparison in terms of CPU time, formulation against the LE-based mesh movement and adjoint gradient is presented. The DGM-based gradient chain allows to comfortably obtain the gradient with respect to each surface mesh point. Unfortunately, these gradients cannot be used directly because of their inherent poor smoothness feature. In order to address this issue one has to use a parameterisation technique which inevitably sacrifices the design space explorablity. To bridge the gap between the free-nodes and the parameterisation approaches, a novel formulation of the CST (Class Shape Transformation) was developed and termed l-CST (local-CST). The method is based on a simple trigonometric function which works as a cut-off filter on the BPs (Bernstein Polynomials) which are used to enforce a strong on-demand local control. The method is tested on an inverse geometric fitting and its effect on the resulting aerodynamic coefficients and the pressure distribution is also analysed. The DGM-based chain allows the efficient mapping of the entire surface while the l-CST allows the combination of excellent explorablity and surface smoothness. The former is tested within the non-consistent mesh movement and sensitivity framework because there are situations where one method may be preferred over the other based on the grounds that mesh movement is a very different task than mesh sensitivity although strongly related to each other. The latter is instead tested against the free-nodes approach which offers a similar advantage in terms of discrete control although without maintaining a C2 curve unless properly smoothed.
Real-time High-Resolution Video Object Segmentation

Semi-supervised video object segmentation aims to segment a speciﬁc object throughout a video sequence with only the ﬁrst-frame annotation. Though recent state-of-the-art methods have achieved high accuracy, the expensive computation cost and heavy memory usage are impractical for most applications. In this paper, we propose an efﬁcient semi-supervised video object segmentation approach that processes the high-resolution video cases at real-time speed with less memory usage. Speciﬁcally, we encode video frames and masks independently in the encoding stage, signiﬁcantly reducing the computation cost caused by large, repeated encoding in previous state-of-the-art methods. On the other hand, we use a lightweight global memory module to represent the feature extracted from all the past video frames, which can be easily updated automatically over time. In addition, to reduce the confusion caused by distractors, the prediction masks of the previous frames are used to constrain the segmentation location of the foreground, and a channel-wise attention operation is adopted to enhance the representation of all foreground objects. In the experiments, our method achieves state-of-the-art on both the DAVIS and YouTube-VOS datasets. It has an accuracy of 84 . 9% and an average single-frame segmentation speed of 0 . 04 s on the DAVIS 2017 dataset. The re-sults demonstrate the proposed method signiﬁcantly reduces the computation cost and memory usage for high-resolution video cases while maintaining a competitive accuracy compared with other recent methods.