Miracle-dz/UniFAR-FTUs huggingface dataset:
An Interpretable Prediction Model for Stroke Based on XGBoost and SHAP

: Objective: To establish a stroke prediction and feature analysis model integrating XGBoost and SHAP to aid the clinical diagnosis and prevention of stroke. Methods: Based on the open data set on Kaggle, with the help of data preprocessing and grid parameter optimization, an interpretable stroke risk prediction model was established by integrating XGBoost and SHAP and an explanatory analysis of risk factors was performed. Results: The XGBoost model’s accuracy, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were 96.71%, 93.83%, 99.59%, and 99.19%, respectively. Our explanatory analysis showed that age, type of residence, and history of hypertension were key factors affecting the incidence of stroke. Conclusion: Based on the data set, our analysis showed that the established model can be used to identify stroke, and our explanatory analysis based on SHAP increases the transparency of the model and facilitates medical practitioners to analyze the reliability of the model.
A randomised comparison between everolimus-eluting stent and sirolimus-eluting stent in chronic coronary total occlusions. Rationale and design of the CIBELES (non-acute Coronary occlusion treated by EveroLimus-Eluting Stent) trial.

Chronic total coronary occlusions constitute a sub-group of lesions at very high risk of restenosis after successful percutaneous coronary intervention. The sirolimus-eluting coronary stent is the only drugeluting stent that has demonstrated to reduce angiographic restenosis and the need for new revascularisation procedures in comparison with bare-metal stents in randomised clinical trials focusing on these lesions. Everolimus-eluting stents have shown to offer optimal angiographic and clinical outcomes in comparison with bare-metal stents and paclitaxel-eluting stents, but no randomised trials have tested the device in chronic total occlusions. The CIBELES (non-acute Coronary occlusIon treated By EveroLimusEluting Stent) will randomise 208 patients with chronic total coronary occlusions in 13 centres from Portugal and Spain to receive everolimus- or sirolimus-eluting coronary stents. The primary endpoint will be angiographic in-stent late loss.
Analyse du contexte à l'aide de méthodes probabilistes pour l'interaction hommes-robots

Mobile robots are gradually appearing in our daily environments. In order to autonomously navigate in real world environments and interact with objects and humans, robots are facing various major technological challenges. Among the required key competences of such robots is their ability to perceive the environment and reason about it in order to plan appropriate actions. However, sensory information perceived from real world situations is error prone and incomplete and thus often results in ambiguous interpretations. This work proposes a new approach for objects recognition that incorporates visual and range information with spatial arrangement between objects (context information). It is based on Bayesian networks enabling to fuses and infer information probabilistically. The proposed framework firstly extracts potential objects from the scene image using simple features / characteristics like colors or the relation between height and width. This basic information is easy to extract, but results often in ambiguous situation between similar objects. In order to disambiguate the detected objects, the relative spatial arrangement (context information) of the objects is used in a second step. Consider for example a Coke can and a red trash-can that are both cylindrical, have similar ratios between width and height and have a very similar color. Dependant on their distance from the robot, they can therefore often hardly be distinguished. However, if we further consider their spatial arrangement with other objects, e.g. a table, they might be clearly differentiable, the Coke typically standing on a table and the trash-can on the floor. This contextual information is therefore a very efficient way to drastically increase the reliability in object recognition and scene interpretation. Moreover, range information from a laser scanner and speech recognition offer complementary information to further improve reliability. Thus an approach using laser range data to recognize places (corridor, crossing, room, doors, etc.) using Bayesian programming is also developed for both topological navigation in a typical indoor environment and object recognition. The proposed approach is verified through different real world experiences. The characteristics and typical spatial arrangements of the objects in various test scenarios are first used to train a Bayesian network through a series of example images (learning) and than verified on the test images. By fusing the extracted object probability from images and range data with spatial relations among the objects, ambiguities are reliability solved and the reliability of the detection is drastically increased. The results show the validity and performance of the proposed Bayesian approach that combines context information with simple object recognition.
SRF Cavity Instability Detection with Machine Learning at CEBAF

During the operation of the Continuous Electron Beam Accelerator Facility (CEBAF), one or more unstable super-conducting radio-frequency (SRF) cavities often cause beam loss trips while the unstable cavities themselves do not necessarily trip off or present a fault. Identifying an unstable cavity out of the hundreds of cavities installed at CEBAF is difficult and time-consuming. The present RF controls for the legacy cavities report at only 1 Hz, which is too slow to detect fast transient instabilities. A fast data acquisition system for the legacy SRF cavities is being developed which samples and reports at 5kHz to allow for detection of transients. A prototype chassis has been installed and tested in CEBAF. An autoencoder based machine learning model is being developed to identify anomalous SRF cavity behavior. The model is presently being trained on the slow (1 Hz) data that is currently available, and a separate model will be developed and trained using the fast (5 kHz) DAQ data once it becomes available. This paper will discuss the present status of the new fast data acquisition system and results of testing the prototype chassis. This paper will also detail the initial performance metrics of the autoencoder model, which indicate good results on the available 1Hz data. This paper will also discuss high-level software applications developed to support the project.
Logistics capacity planning : A stochastic bin packing formulation and a progressive hedging metaheuristic

We consider the logistics capacity planning problem arising in the context of supply-chain management. We address the tactical-planning problem of determining the quantity of capacity units, hereafter called bins, of different types to secure for the next period of activity, given the uncertainty on future needs in terms of demand for loads (items) to be moved or stored, and the availability and costs of capacity for these movements or storage activities. We propose a modeling framework introducing a new class of bin packing problems, the Stochastic Variable Cost and Size Bin Packing Problem. The resulting two-stage stochastic formulation with recourse assigns to the first stage the tactical capacity-planning decisions of selecting bins, while the second stage models the subsequent adjustments to the plan, securing extra bins and packing the items into the selected bins, performed each time the plan is applied and new information becomes known. We propose a new meta-heuristic based on progressive hedging ideas that includes advanced strategies to accelerate the search and efficiently address the symmetry strongly present in the problem considered due to the presence of several equivalent bins of each type. Extensive computational results for a large set of instances support the claim of validity for the model, efficiency for the solution method proposed, and quality and robustness for the solutions obtained. The method is also used to explore the impact on the capacity plan and the recourse to spot-market capacity of a quite wide range of variations in the uncertain parameters and the economic environment of the firm.
Effects of hyperbaric oxygenation therapy on symptomatic pneumocephalus

Background: Pneumocephalus (PNC) is defined as a pathological collection of gas within the cranial cavity. The authors studied the effects of hyperbaric oxygenation (HBO2) therapy on a group of patients with PNC, comparing them with a control group to determine the relative impact on pneumocephalus volume, clinical symptoms, and duration of hospitalization. Methods: Twenty-four patients with PNC treated at our hospital were consecutively studied. These patients were divided into a treated group (n = 13) and a control group (n = 11). Thirteen patients (treated group) were treated with HBO2 therapy sessions in a monoplace hyperbaric chamber at 2.5 atmospheres with 100% oxygen concentration. The control group was treated with normobaric oxygenation. Results: Clinical improvement was seen in all patients. In the treated group, a decrease of the gas bubble was observed on the computerized tomography scan after each session of HBO2. The treated group also experienced a lower rate of meningitis compared with the control group. The length of hospital stay was significantly higher in the control group compared with the treated group. Conclusions: HBO2 therapy in selective cases may lead to clinical and radiological improvement in patients with PNC.
Factors associated with attitudes towards intimate partner violence against women : a comparative analysis of 17 sub-Saharan countries

Background: Violence against women, especially by intimate partners, is a serious public health problem that is associated with physical, reproductive and mental health consequences. Even though most societies proscribe violence against women, the reality is that violations against women's rights are often sanctioned under the garb of cultural practices and norms, or through misinterpretation of religious tenets. Methods: We utilised data from 17 Demographic and Health Surveys (DHS) conducted between 2003 and 2007 in sub-Saharan Africa to assess the net effects of socio-demographic factors on men's and women's attitudes toward intimate partner violence against women (IPVAW) using multiple logistic regression models estimated by likelihood ratio test. Results: IPVAW was widely accepted under certain circumstances by men and women in all the countries studied. Women were more likely to justify IPVAW than men. "Neglecting the children" was the most common reason agreed to by both women and men for justifying IPVAW followed by "going out without informing husband" and "arguing back with the husband". Increasing wealth status, education attainment, urbanization, access to media, and joint decision making were associated with decreased odds of justifying IPVAW in most countries. Conclusion: In most Sub-Saharan African countries studied where IPVAW is widely accepted as a response to women's transgressing gender norms, men find less justification for the practice than do women. The present study suggests that proactive efforts are needed to change these norms, such as promotion of higher education and socio-demographic development. The magnitude and direction of factors associated with attitudes towards IPVAW varies widely across the countries, thus suggesting the significance of capitalizing on need-adapted interventions tailored to fit conditions in each country. Background Intimate partner violence against women (IPVAW) is deep-rooted in many African societies, where it is considered a prerogative of men [1,2] and a purely domestic matter in the society [3,4]. IPVAW is one of the greatest barriers to ending the subordination of women. Women, for fear of violence, are unable to refuse sex or negotiate safer sexual practices, thus increasing their vulnerability to Published: 20 July 2009 BMC International Health and Human Rights 2009, 9:14 doi:10.1186/1472-698X-9-14 Received: 14 July 2008 Accepted: 20 July 2009 This article is available from: http://www.biomedcentral. com/1472-698X/9/14 © 2009 Uthman et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Lagrangian modeling and control of switching networks with integrated coupled magnetics

In this paper a method is presented to build an Euler-Lagrange model for electrical networks, including switches and integrated (non-ideal) coupled-magnetics, in a structured general way. One of the advantages of emphasizing the physical structure of these systems is its functionality during the controller design stage. In a case a switching network contains coupled-inductor structures, an additional path for the energy transfer is introduced. For this reason, a basic building block is proposed that describes the dynamical behaviour of a pair of magnetically coupled-inductors. This building block is applicable to all types of switching converters, and easily predicts the existence of reduced or zero-ripple current. The switches make the dynamic models nonlinear. It is shown that under certain coupling conditions it is possible to design a globally stable controller. The approach is illustrated by means of the coupled-inductor Cuk converter with zero-output ripple, in closed loop with an adaptive passivity-based controller.
On Laboratory Gait Analysis via Computer Vision

We describe a marker-less system for analysing and classifying human gait motion by combining a statistical approach and motion tracking with topological analysis guided by anatomical knowledge. The marker-less gait analysis system consists of three stages: detection and extraction of the moving human body and its contour from image sequences; extraction of human gait motion by the joint angles and body points; and kinematic analysis and feature extraction for classifying the gait pattern. The periodic motion of human gait is described by symmetry, and a 2D stick figure is used to rep-resent the human gait model. The usefulness of proposed method is demonstrated in marker-less gait analysis with comparison to biomechanical data.
3D Content Encryption Using Multi-Level Chaotic Maps

Nowadays, 3D content is becoming an essential part of multimedia applications, when the 3D content is not protected, hackers may attack and steal it. This paper introduces a proposed scheme that provides high protection for 3D content by implementing multiple levels of security with preserving the original size using weight factor (w). First level of security is implemented by encrypting the texture map based on a 2D Logistic chaotic map. Second level is implemented by shuffling vertices (confusion) based on a 1D Tent chaotic map. Third level is implemented by modifying the vertices values (diffusion) based on a 3D Lorenz chaotic map. Results illustrate that the proposed scheme is completely deform the entire 3D content according to Hausdorff Distance (HD) approximately around 100 after the encryption process. It provides a high security against brute force attack because it has large key space equal to 10 165 and secret key sensitivity using NPCR near 99:6% and UACI near 33:4%. The histogram and HD indicate the decrypted 3D content is identical to the origin where HD values approximate zero.
Short-term forecasts on time series for tourism in Lombardy

Data from official statistics are often available with a few months delay with respect to their collection. Tourism data collection is one of this kind and the statistics team in PoliS-Lombardia receives a lot of requests about predictions or provisional data in order to have real time insights about the tourism performance. In these last years, because of the pandemic emergency due to Covid-19, the curiosity of public stakeholders about an economic recovery after 2020 downfall (and partially 2021) has increased and so the need to get official data as soon as possible. This paper aims at filling this need with short-term predictions in time series as temporary substitutes while waiting for official data to be published. The context of this work is in the tourism sector, one of the most damaged economic sectors by the limitations due to Covid-19. Many contributions are already present in literature about the strategy and the estimation for the recovery of the travel sector after the pandemic emergency (Fotiadis et al., 2021; Yeh, 2021). In this context, an objective of this work is to verify the presence of a full or partial recover of tourists in provinces of Lombardy using short-term predictions for 2022. This issue has also been treated by Provenzano and Volo (2022). This contribution is the result of a collaboration with PoliS-Lombardia, a public institution of Regione Lombardia. It is included in the list of institutional units belonging to the public sector published by Istat. PoliS-Lombardia has been instituted in 2018 and it is the regional institute for the support to the policies of Lombardy. Its mission is the implementation and the evaluation of the policies in Lombardy. The main functions of PoliS-Lombardia are: support to the integrated policies of education and labour coherently with fixed objectives by the administration; studies and research projects related to the institutional, local, economic and social processes; management of the regional statistical function in collaboration with ISTAT; management and coordination of the regional observatories; education of the regional employees. Given this scopes, it represents a very important stakeholders in the field of data management in Lombardy involved in a large amount of data, as for example in the tourism sector. In this paper, using a short-term forecasts approach, some preliminary results will be presented for detecting a recovery in the travel sector for 2022 using the total number of presences in Lombard provinces. These short-term predictions will be obtained using a very well-known methodology in time-series literature, such as the ARIMA (Auto-Regressive Integrated Moving Average) models (Box et al., 2015; Hamilton, 2020; Wei, 2006). In these models, an exogenous variable representing the working positions in the food services and hospitality industry has been added supposing an high correlation between the two phenomena.
Essential Elements of Lessons Designed to Promote Critical Thinking

While many educators commonly identify critical thinking as a goal for learning, they struggle with creating lessons that encourage students to take charge of their own thinking. This paper presents four essential elements of lessons designed to promote critical thinking including ill-structured problems, criteria for assessing thinking, student assessment of thinking, and improvement of thinking. With these four elements in place an iterative process of lesson planning emerges which simplifies the planning process for teachers while engaging students’ thinking to benefit their learning.
CENTRAL EUROPEAN REVIEW OF ECONOMICS AND MANAGEMENT

Design / research methods: The paper uses panel data to measure the influence of the short-term ECB deposit rate and the 10-years German bond yield on short-term and long-term firm variables. Cross section fixed effects are applied to first differences and dummy variables. For liquidity and non-liquid assets the effects are also measured for small and large companies, for sectors, and for countries.
Modélisation morphodynamique d'une embouchure tidale : Application aux Passes d'entrée du Bassin d'Arcachon

Soumises a de forts courants de maree et a de rudes conditions de houle, les passes du Bassin d'Arcachon presentent une morphologie particulierement active. Au cours des 300 dernieres annees, l'excursion de l'extremite de la Fleche du Cap Ferret a atteint 8 km tandis qu'alternativement une ou deux passes assuraient la circulation entre l'interieur du bassin et l'ocean. Un modele morphodynamique bidimensionnel horizontal a ete developpe afin de simuler l'evolution du systeme sous l'action de la maree seule ou de la maree et de la houle combinees. La modelisation a l'echelle de plusieurs decennies requiert la determination de conditions de houle et de maree annuelles moyennes, representatives au regard du transport sedimentaire. Les resultats a moyen terme fournissent par consequent des tendances generales d'evolution. Le modele permet dans ces conditions de reproduire, a partir d'une topographie initiale de l'embouchure fictive de profondeur constante, la formation d'une passe et d'un systeme de bancs comparables aux configurations observees par le passe. Les evolutions morphologiques simulees a partir de la situation de 1993 sont moins probantes, par suite des hypotheses limitantes imposees lors du developpement du modele, et par l'absence de representation des tempetes principales responsables du remaniement des passes.
Erratum: Correction to `effect of coupled anthropogenic perturbations on stratospheric ozone'

Since 1976 the greatest concern about potential perturbations to stratospheric ozone has been in regard to the atmospheric release of chlorofluorocarbons. Consequently, atmospheric measurements of ozone have usually been compared with model calculations in which only chlorocarbon perturbations are considered. However, in order to compare theoretical calculations with recent measurements of ozone and to project expected changes to atmospheric ozone levels over the next few decades, one must consider the effect from other perturbations as well. In this paper, we consider the coupling between several possible anthropogenic atmospheric perturbations. Namely, we examine the effects of past and possible future increases of chlorocarbons, CO/sub 2/, N/sub 2/O, and NO/sub x/. The focus of these calculations is on the potential changes in ozone due to chlorocarbon emissions, how other anthropogenic perturbations may have influenced the actual change in ozone over the last decade, and how these perturbations may influence future changes in ozone. Although calculations including future chlorocarbon emissions alone result in significant reductions in ozone, there is very little change in total ozone over the coming decades when other anthropogenic sources are included. Increasing CO/sub 2/ concentrations have the largest offsetting effect on the change in total ozone due to chlorocarbons.more » Owing to the necessity of considering emissions from a number of trace gases simultaneously, determining expected global-scale chemical and climatic effects is more complex than was previously recognized. « less
Family Values and the Regulation of Labor ∗

Flexible labor markets require geographically mobile workers to be effi cient. Otherwise firms can take advantage of the immobility of workers and extract rents at the expense of workers. In cultures with strong family ties, moving away from home is costly. Thus, to limit the rents of firms and avoid moving, individuals with strong family ties rationally choose regulated labor markets, even though regulation generates lower employment and income. Empirically, we do find that individuals who inherit stronger family ties are less mobile, have lower wages, are less often employed and support more stringent labor market regulations. We find a positive association between labor market rigidities at the beginning of the twenty first century and family values prevailing before World War II, and between family structures in the Middle Ages and current desire for labor market regulation. Both results suggest that labor market regulations have deep cultural roots.