Miracle-dz/UniFAR-FTUs huggingface dataset:
Transect plate-forme-bassin dans les series carbonatees du berriasien et du valanginien inferieur (domaines jurassien et nord-vocontien)

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Transect plate-forme-bassin dans les séries carbonatées du Berriasien supérieur et du Valanginien inférieur (domaines jurassien et nord-vocontien) : chronostratigraphie-transferts des sédiments Eric Blanc
UNITED NATIONS ECONOMIC COMMISSION FOR EUROPE CONFERENCE OF EUROPEAN STATISTICIANS Expert meeting on Statistical Data Confidentiality 26–28 September 2023, Wiesbaden COACH: COmputer-Assisted output CHecking with Human-in-the-Loop

In this paper, we introduce COACH (COmputer-Assisted output CHecking with Human-in-the-loop). COACH combines the power of machine learning models with human checkers’ expertise to semi-automate output checking. By semi-automating output checking, we aim to facilitate the task of human checkers to check and decide whether output produced by a researcher using unprotected data from a statistical institute (e.g. in a Research Data Center) is safe for release to the public or not. First, we reproduce Domingo-Ferrer and Blanco-Justicia (2021) by leveraging simulated data and exploring diverse machine-learning algorithms. Then, our contributions extend prior work, by evaluating simulated data on real-world use cases and proposing preprocessing techniques to align simulated and real data. Next, our approach COACH empowers human checkers to review model predictions, providing valuable feedback to retrain and enhance model performance. Also, by utilizing global and local explainable AI method, COACH gains insights into model decision-making and influential variables. Our proposed approach revolutionizes output validation, fostering reliable and interpretable models for data-driven decision-making with human-in-the-loop interactions. 1The views expressed in this paper are those of the authors and do not necessarily reflect the policy of Statistics Netherlands.
Working Childhoods: Youth, Agency and the Environment in India

1. Working with young people in the Himalayas 2. The High Himalayas 3. A delicate dance: young people's work 4. Herding, fun and difference 5. Friendship in practice: collecting leaves in Bemni 6. Harvesting identities: Mukku, gender and development 7. Conclusions.
Measurements of integrated and differential cross sections for isolated photon pair production in pp collisions at ﬃﬃ s p = 8 TeV with the ATLAS detector

A measurement of the production cross section for two isolated photons in proton-proton collisions at a center-of-mass energy of ﬃﬃﬃ s p ¼ 8 TeV is presented. The results are based on an integrated luminosity of 20 . 2 fb − 1 recorded by the ATLAS detector at the Large Hadron Collider. The measurement considers photons with pseudorapidities satisfying j η γ j < 1 . 37 or 1 . 56 < j η γ j < 2 . 37 and transverse energies of respectively E γ T ; 1 > 40 GeV and E γ T ; 2 > 30 GeV for the two leading photons ordered in transverse energy produced in the interaction. The background due to hadronic jets and electrons is subtracted using data-driven techniques. The fiducial cross sections are corrected for detector effects and measured differentially as a function of six kinematic observables. The measured cross section integrated within the fiducial volume is 16 . 8 (cid:2) 0 . 8 pb. The data are compared to fixed-order QCD calculations at next-to-leading-order and next-to-next-to-leading-order accuracy as well as next-to-leading-order computations including resummation of initial-state gluon radiation at next-to-next-to-leading logarithm or matched to a parton shower, with relative uncertainties varying from 5% to 20%.
A review and taxonomy of distortion-oriented presentation techniques

One of the common problems associated with large computer-based information systems is the relatively small window through which an information space can be viewed. Increasing interest in recent years has been focused on the development of distortion-oriented presentation techniques to address this problem. However, the growing number of new terminologies and techniques developed have caused considerable confusion to the graphical user interface designer, consequently making the comparison of these presentation techniques and generalization of empirical results of experiments with them very difficult, if not impossible. This article provides a taxonomy of distortion-oriented techniques which demonstrates clearly their underlying relationships. A unified theory is presented to reveal their roots and origins. Issues relating to the implementation and performance of these techniques are also discussed.
Lessons Learned from Fixing the Dead Nonce List in NFD

Recent experimentation with NDN networking under ad hoc mobile conditions with intermittent connectivity revealed several issues regarding the existing design and implementation of the “dead nonce list” (DNL). DNL is a mechanism to stop Interest packets from looping after they are removed from an NDN node’s the Pending Interest Table (PIT). A detailed analysis of the observed problems leads to the discovery of a few design flaws and implementation shortcomings in the existing solution. This report explains the intended role of DNL in NDN forwarding, the identified flaws in the original design assumption about the DNL usage, and the implementation issues identified. Through this exercise of discovering and fixing the DNL design and implementation problems, we gain a deeper understanding in the complementary roles played by DNL and HopLimit in packet looping mitigation. We also learned that simply running an NDN testbed cannot be a sufficient proof for the absence of the NDN protocol design issues or implementation bugs; instead, it is necessary to perform thorough measurement and analysis to identify them.
Statistical and Combinatorial Methods to Predict Gene Expression and Identify eQTLs from Haplotype Sequences

Genome-wide association studies (GWAS) have discovered thousands of significant genetic effects on disease phenotypes. By considering gene expression as the intermediary between genotype and disease phenotype, expression quantitative trait loci studies have interpreted many of these variants by their regulatory effects on gene expression. However, there remains a considerable gap between genotype-to-gene expression association and genotype-to-gene expression prediction. Accurate prediction of gene expression enables gene-based association studies to be performed post hoc for existing GWAS, reduces multiple testing burden, and can prioritize genes for subsequent experimental investigation. In this work, we develop gene expression prediction methods that relax the independence and additivity assumptions between genetic markers. First, we consider gene expression prediction from a regression perspective and develop the HAPLEXR algorithm which combines haplotype clusterings with allelic dosages. Second, we introduce the new gene expression classification problem, which focuses on identifying expression groups rather than continuous measurements; we formalize the selection of an appropriate number of expression groups using the principle of maximum entropy. Third, we develop the HAPLEXD algorithm that models haplotype sharing with a modified suffix tree data structure and computes expression groups by spectral clustering. In both models, we penalize model complexity by prioritizing genetic clusters that indicate significant effects on expression. We compare HAPLEXR and HAPLEXD with three state-of-the-art expression prediction methods and two novel logistic regression approaches across five GTEx v8 tissues. HAPLEXD exhibits significantly higher classification accuracy overall; HAPLEXR shows higher prediction accuracy on approximately half of the genes tested and the largest number of best predicted genes (r2> 0.1) among all methods. We show that variant and haplotype features selected by HAPLEXR are smaller in size than competing methods (and thus more interpretable) and are significantly enriched in functional annotations related to gene regulation. These results demonstrate the importance of explicitly modeling non-dosage dependent and intragenic epistatic effects when predicting expression.
PREVALENCE OF OBESITY AMONG ADOLESCENT SCHOOL CHILDREN IN RURAL AND URBAN SOUTH ODISHA

Despite obesity and overweight being such a pressing health problem of the country, data regarding its magnitude is scarce. Furthermore, there is scarcity of studies regarding the prevalence of obesity and overweight in this part of the country, more so in the regions of southern Odisha and in the age group of adolescents. This study was conducted with an objective of estimating the prevalence of obesity among rural and urban adolescent school children and to assess the risk factors associated with adolescent obesity. This was a cross sectional study conducted in the schools of urban and rural areas of Ganjam district of the state of Odisha between October 2015 to November 2017. The study participants were recruited from among Adolescent high school (8th, 9th, 10th) students from rural and urban areas of Ganjam district. Assuming the prevalence of adolescent obesity as 12.3% from a previous study conducted in Odisha, confidence level as 95% and absolute allowable error as 5% sample size was calculated to be 173 and was rounded off to include total 180 students. Data was collected using standardized questionnaires and descriptive analyses performed. A total of 180 school students were taken out of which 90 were from rural and 90 were from urban schools. The overall prevalence of overweight among urban and rural high school students was found to be 9.44%, and obesity was 5%. Significant associations were found between prevalence of obesity/ overweight with Physical activity pattern like time spent on sedentary activities like TV viewing, studying, using mobile and laptop, time spent on physical activities like outdoor games and mode of
Concentrations of amino acids in hydrothermal sediments collected from the Izena and Yoron Cauldrons, Okinawa Trough

Copyright © 2015 by The Geochemical Society of Japan. each amino acid; the amino acids were also more stable under reducing conditions than oxidative conditions (Rosenfeld, 1979). The behavior of amino acids drastically changes under hydrothermal conditions: oligomerization, degradation, maturation, and racemization are promoted in high temperature and pressure conditions. When α-amino acids were heated in a simulated hydrothermal solution (200°C, 50 bar) for 50 h, most of them rapidly decomposed (Andersson and Holm, 2000). Other studies also support that amino acids become labile with increasing temperature in hydrothermal solutions and do not exist at temperatures >200°C (White, 1984; Miller and Bada, 1988; Qian et al., 1993; Bada et al., 1995). Amino acids rarely survive in hydrothermal solutions for long periods of time. On the other hand, Svensson et al. (2004) found that natural hydrothermal fluids (42–82°C) contained 3–114 times higher amino acid concentrations than the ambient seawater of Vucano Island, Italy. Higher concentrations of amino acid polymers were found in high-temperature fluids (>208°C) than in low-temperature fluids (<53°C) Concentrations of amino acids in hydrothermal sediments collected from the Izena and Yoron Cauldrons, Okinawa Trough
We've Got You Covered: Employer and Employee Responses to Dobbs V. Jackson

Following the June 24, 2022 Dobbs v. Jackson Supreme Court ruling, which overturned the federal right to abortion established in Roe v. Wade, hundreds of employers publicly announced policies covering out-of-state employee travel for abortions and related care. Leveraging data from Indeed and Glassdoor, we first document that companies with more female and more Democratic-leaning employees and executives were more likely to announce these policies. We then examine the causal impact such announcements had on recruitment, job satisfaction, and pay by introducing a new methodology to recover similar employers who did not make announcements using workers' revealed preferences in job search. Difference-in-differences estimates reveal that for announcing companies: (i) vacancies received more job seeker interest, particularly in Democratic-leaning states and female-dominated jobs in states with "trigger" laws that outlawed abortion, (ii) satisfaction with management fell amongst existing employees, particularly in male-dominated jobs, and (iii) posted wages increased, especially for companies where employee sentiment declined. These results highlight the complicated trade-off employers face from engaging in sociopolitical dialogue, in particular how signals of company culture can help recruit new workers but alienate current ones.
Life Satisfaction, Household Income and Personality Theory

We show that personality traits mediate the effect of income on Life Satisfaction. The effect is strong in the case of Neuroticism, which measures the sensitivity to threat and punishment, in both the British Household Panel Survey and the German Socioeconomic Panel. Neuroticism increases the usually observed concavity of the relationship: Individuals with higher Neuroticism score enjoy income more than those with lower score if they are poorer and enjoy income less if they are richer. When the interaction between income and neuroticism is introduced, income does not have significant effect on his own. To interpret the results, we present a simple model where we assume that (i) Life Satisfaction is dependent from the gap between aspired and realized income, and this is modulated by Neuroticism and (ii) income increases in aspirations with a slope less than unity, so that the gap between aspired and realized income increase with aspirations. From the estimation of this model we argue that poorer tend to overshoot in their aspiration, while rich tend to under-shoot. The estimation of the model also shows substantial effect of traits on income.
SCoDA: Domain Adaptive Shape Completion for Real Scans

Synthetic Scan Generation To get point clouds from the ShapeNet models, we adopt a popular simulation toolbox, BlenSor [3], which supports scanning simulation with different sensors (e.g. Velodyne, Kinect, and Time of Flight camera) and parameters. To simulate the sparsity in real scans from the ScanNet dataset, we conduct a random down-sampling with ratio 13%, which is computed according to the average point number of scans in ScanNet and simulated point clouds from ShapeNet. We also add Gaussian noise with a max scale 0.01 to simulate the noise in scanning. The incompleteness is also introduced in the simulated scanning by self-occlusion. Besides, we adopt the unsupervised clustering-based way introduced in the main paper to partition the point clouds and randomly drop 1∼4 clusters in the training process. Some simulation results (before dropping some clusters in training) are presented in the second row of Fig. S1. As shown in Fig. S1, in spite of careful simulation, the generated synthetic scans are still different from real scans (the first row of Fig. S1) in (i) sparsity: dependent of the object materials and object-scanner distance, the sparsity of real scans has a larger variance; (ii) noise: both the scanning intrinsic error the segmentation from background can introduce complex noise; and (iii) incompleteness: the incompleteness of real scans results from the occlusion and surroundings, which is more complex. Thus, there still exists a domain gap between two kinds of point clouds, which can hardly be handled by simulation. Figure S1. Comparison between real scans (the first row, from the ScanNet dataset) and synthetic scans (the second row, simulated from models in the ShapeNet dataset).
Oxygen fugacity values of Apollo 12, 14, and 15 lunar samples and reduced state of lunar magmas

The oxygen fugacity values of lunar samples were measured directly with an improved solid-electrolyte oxygen cell between 1000 and 1200 C with an accuracy mostly better than 0.2 log f(02) unit. The bulk rock f(02) values of basaltic igneous rocks 12009, 12053, 15058, and 15595 ranged from 10 to -15.4 power to 10 to the -15.7 power at 1000 C and from 10 to the -12.3 power to 10 to the -12.8 power at 1200 C. Those of microbreccia 14321 also fell in this range, but the change of oxygen fugacity with temperature was irregular in the first heating cycle in comparison to the smooth changes observed with the basaltic igneous rocks. Two different samples of rock 14310 also showed similar f(02) values below 1170 C, but exhibited irreversible sudden rise in f(02) at this temperature for reasons yet to be determined. The data on the phenocryst olivine and the groundmass of basalt 12009 do not conclusively indicate progressive reduction of the lunar magma during cooling.
Cardiovascular Disease Prediction System Using Extra Trees Classi�er

Heart Disease as cardiovascular disease is the leading cause of death for both men and women. It is the major cause of morbidity and mortality in present society. Therefore, researchers are working to help health care professionals in diagnosing process by using data mining techniques. Although the health care industry is richer in the database this data is not properly mined in order to discover hidden patterns and can able to make decisions based on these patterns. The major goal of this learning refers the extraction of hidden layers by applying numerous data mining techniques that probably give remarkable results in order to ensure the presence of cardiovascular disease among peoples. Data mining classiﬁcation techniques are used to discover these patterns for research in medical industry. The dataset containing 13 attributes has analyzed for prediction system. The dataset contains some commonly used medical terms like blood pressure, cholesterol level, chest pain and 11 other attributes used to predict cardiovascular disease. The most common and effective classiﬁcation techniques that are used in mining process are Verdict Tree commonly known as Decision Tree, Extra Trees Classiﬁer, Random Forest, Support Vector Machine, Naive Bays and Logistic Regression has analyzed in this paper. Diagnosing and controlling ratio of deaths from cardiovascular disease Extra classiﬁer trees consider is the best approach. We evaluate these prediction models by using evaluation parameters which are Accuracy, Precision, Recall, and F1-score. As per our experimental results shows accuracy of Extra trees classiﬁer, Logistic Model tree classiﬁer, support vector machine, and naive bays classiﬁers are 90%, 88%, 87%, 86% respectively. So as per our experiment analysis Extra Tree classiﬁer with highest accuracy considered best approach for predication cardiovascular disease.
The Spatial Form of Houses Built by Italian Migrantsin Post World War II Brisbane, Australia

The literature reveals that despite the study of the relationship between human behavior, activities and built form has focused on physical spatial environments at any scale, ranging from built environment to built form, the investigation of micro-scale housing has been neglected in the past. Namely, regardless of the interest to this relationship, direct assessment of the extent to which migrants' human behavior and activities influence and are also influenced by the spatial form of their houses is still rare in the field. This paper focuses on the exploration of the relationship between human behavior, activities and the spatial form of houses built by Italian migrants in post WWII Brisbane. The paper argues that the spatial form of migrants' houses was influenced by two factors: the need to perform working and social activities dictated by culture as a way of life; urbanization patterns present in migrants' native and host built environment.
Association of subcutaneous or intravenous route of administration of casirivimab and imdevimab monoclonal antibodies with clinical outcomes in COVID-19.

Importance: Monoclonal antibody (mAb) treatment decreases hospitalization and death in outpatients with mild to moderate COVID 19; however, only intravenous administration has been evaluated in randomized clinical trials of treatment. Subcutaneous administration may expand outpatient treatment capacity and qualified staff available to administer treatment, but association with patient outcomes is understudied. Objective: To evaluate whether or not, i. ) subcutaneous casirivimab and imdevimab treatment is associated with reduced 28 days hospitalization/death than non-treatment among mAb-eligible patients, and ii. ) subcutaneous casirivimab and imdevimab treatment is clinically and statistically similar to intravenous casirivimab and imdevimab treatment. Design, Setting, and Participants: Prospective cohort study of outpatients in a learning health system in the United States with mild to moderate COVID 19 symptoms from July 14 to October 26, 2021 who were eligible for mAb treatment under emergency use authorization. A nontreated control group of eligible patients was also selected. Intervention: Subcutaneous injection or intravenous administration of the combined single dose of casirivimab 600mg and imdevimab 600mg. Main Outcomes and Measures: The primary outcome was the 28 day adjusted risk ratio or adjusted risk difference for hospitalization or death. Secondary outcomes included 28 day adjusted risk ratios/differences of hospitalization, death, composite endpoint of ED admission and hospitalization, and rates of adverse events. Results: Among 1,956 matched adults with mild to moderate COVID 19, patients who received casirivimab and imdevimab subcutaneously had a 28-day rate of hospitalization/death of 3.4% (n=652) compared to 7.8% (n=1,304) in nontreated controls [risk ratio 0.44 (95% confidence interval: 0.28 to 0.68, p < .001)]. Among 2,185 patients treated with subcutaneous (n=969) or intravenous (n=1,216) casirivimab and imdevimab, the 28 day rate of hospitalization/death was 2.8% vs. 1.7%, respectively which resulted in an adjusted risk difference of 1.5% (95% confidence interval: -0.5% to 3.5%, p=.14). The 28 day adjusted risk differences (subcutaneous and intravenous) for death, ICU admission, and mechanical ventilation were 0.3% or less, although the 95% confidence intervals were wide. Conclusions and Relevance: Subcutaneously administered casirivimab and imdevimab is associated with reduced risk adjusted hospitalization or death amongst outpatients with mild to moderate COVID 19 compared to no treatment and indicates low adjusted risk difference compared to patients treated intravenously.