Miracle-dz/UniFAR-FTUs huggingface dataset:
Precautionary Saving over the Business Cycle Dall, for Their Comments on an Earlier Version of This Paper. We Greatly Bene…ted from Discussions With

We study the macroeconomic implications of time-varying precautionary saving in a tractable general equilibrium model with both aggregate and uninsurable idiosyncratic risk. In the model, agents facing incomplete markets and borrowing constraints respond to countercyclical changes in unemployment risk by altering their bu¤er stock of wealth, with a direct impact on aggregate consumption. In a calibrated version of the model, the response of aggregate consumption to a typical NBER recession is found to be twice as large as that implied by a comparable representative agent economy, and about 30% larger than that implied by a comparable economy with full insurance but wherein a fraction of households permanently faces a binding borrowing constraint.nique, Gains/Université du Mans, Bank of France and Bank of Portugal for their feedback. Eric Mengus provided outstanding research assistance, and the French Agence Nationale pour la Recherche provided funding (ANR grant no 06JCJC0157). The usual disclaimers apply.
The Impact of Results Blind Science Publishing on Statistical Consultation and Collaboration

Abstract The author has previously proposed results blind manuscript evaluation (RBME) as a method of ameliorating often cited problems of statistical inference and scientific publication, notably publication bias, overuse/misuse of null hypothesis significance testing (NHST), and irreproducibility of reported scientific results. In RBME, manuscripts submitted to scientific journals are assessed for suitability for publication without regard to their reported results. Criteria for publication are based exclusively on the substantive importance of the research question addressed in the study, conveyed in the Introduction section of the manuscript, and the quality of the methodology, as reported in the Methods section. Practically, this policy is implemented by a two stage process whereby the editor initially distributes only the Introduction and Methods sections of a submitted manuscript to reviewers and a provisional decision regarding acceptance is made, followed by a second stage in which the complete manuscript is distributed for review but only if the decision of the first stage is for acceptance. The present paper expands upon this recommendation by addressing implications of this proposed policy with respect to statistical consultation and collaboration in research. It is suggested that under RBME, statisticians will become more integrated into research endeavors and called upon sooner for their input.
The Impact of AMSU-A Radiance Assimilation in the U.S. Navy's Operational Global Atmospheric Prediction System (NOGAPS)

Abstract : The Navy Operational Global Atmospheric Prediction System (NOGAPS) is the U.S. Department of Defense's high-resolution global weather prediction system, which is used for operational mesoscale and oceanographic models and numerical weather prediction (NWP) research. The analysis for NOGAPS is produced by the NRL Atmospheric Variational Data Assimilation System (NAVDAS). On June 9, 2004, NAVDAS began operational assimilation of ASMU-A radiances from the Advanced TIROS Operational Vertical Sounder (ATOVS) sensor suite onboard NOAA 15 and 16 for NOGAPS. The direct assimilation of AMSU-A radiances replaced the assimilation of ATOVS temperature retrievals produced by NOAA's National Environmental Satellite, Data and Information Service (NESDIS). The results of medium-range forecast tests of radiance assimilation versus NESDIS ATOVS retrieval assimilation show substantial improvement in the forecasts of height, wind, and temperature in both the Northern and Southern Hemispheres. In the tropics, the tropical cyclone track errors are smaller with radiance assimilation, even though the upper- and lower-level errors are essentially the same. Overall, there are fewer forecast "busts" with radiance assimilation, especially in the Southern Hemisphere.
First principles study on the structural, electronic, mechanical and lattice dynamical properties of XRhSb (X = Ti and Zr) paramagnet half-Heusler antimonides

The half-Heusler TiRhSb and ZrRhSb alloys in the formation of face-centered cubic MgAgAs-type structure, which conforms to the F 4 ¯ 3 m space group with 216 as the space number, have been investigated using Generalized Gradient Approximation (GGA) implemented in Density Functional Theory (DFT). The calculated formation enthalpies and the plotted energy-volume curves of different types of structural phases (α, β, and γ) in these alloys indicate that the γ-phase structure is the best energetically suitable structure. In addition, TiRhSb and ZrRhSb alloys have been found as paramagnetic (PM) with the investigation of antiferromagnetic (AFM), ferromagnetic (FM), and paramagnetic (PM) orders in the most stable γ-phase structure. Therefore, their electronic, mechanical, and dynamical properties have been examined in the γ structural phase and paramagnetic order. These alloys have semiconducting nature due to the observed same band gaps in both the majority and minority spin channels of the calculated spin-polarised electronic band structure. These calculated band gaps are 0.75 eV for γ-TiRhSb and 1.18 eV for γ-ZrRhSb. The predicted elastic constants indicate that the alloys in this study are mechanically stable and show nearly isotropic behavior in the γ structural phase. Also, the minimum and the diffuson thermal conductivites have been determined for these alloys. Finally, the calculated phonon dispersion spectras for the γ-TiRhSb and γ-ZrRhSb half-Heusler antimonide alloys show the dynamic stability of these systems.
UvA-DARE (Digital Academic Repository) Bringing it All Together

mediation-type pattern: Power Distance—Gentle Sleep techniques—INT; Power Distance—late bed times—INT; and Power Distance—late wake times—INT. For the other 10 models, the independent variable beta dropped, but the effect of the mediator did not reach < 0.10, and in other cases the independent variable beta change with the entry of the mediator was negligible.
Intuitionistic Fuzzy Twin Support Vector Machines

Fuzzy twin support vector machine (FTSVM) is an effective machine learning technique that is able to overcome the negative impact of noise and outliers in tackling data classification problems. In the FTSVM, the degree of membership function in the sample space describes the space between input data and class center, while ignoring the position of input data in the feature space and simply miscalculated the ledge support vectors as noises. This paper presents an intuitionistic FTSVM (IFTSVM) that combines the idea of intuitionistic fuzzy number with twin support vector machine (TSVM). An adequate fuzzy membership is employed to reduce the noise created by the pollutant inputs. Two functions, i.e., linear and nonlinear, are used to formulate two nonparallel hyperplanes. An IFTSVM not only reduces the influence of noises, it also distinguishes the noises from the support vectors. Further, this modification can minimize a newly formulated structural risk and improve the classification accuracy. Two artificial and eleven benchmark problems are employed to evaluate the effectiveness of the proposed IFTSVM model. To quantify the results statistically, the bootstrap technique with the ${95\%}$ confidence intervals is used. The outcome shows that an IFTSVM is able to produce promising results as compared with those from the original support vector machine, fuzzy support vector machine, FTSVM, and other models reported in the literature.
role of downregulated mir-133a-3p expression in bladder cancer: a bioinformatics study

: It has been discovered that miR-133a-3p acts as a tumor suppressor in bladder cancer (BC). Nevertheless, the function of miR-133a-3p in BC remains unclarified. Thus, we carried out this study to validate the expression of miR-133a-3p in BC and provide insights into the molecular mechanism underlying it. To assess the expression of miR-133a-3p in BC, we searched eligible studies from literature and Gene expression Omnibus (GEO) to perform a meta-analysis. We also plotted the summary receiver operating characteristic (SROC) curve to evaluate the diagnostic ability of miR-133a-3p in BC. Additionally, the potential target genes of miR-133a-3p were acquired from 14 online software programs and GEO database. Protein-protein interaction (PPI) network was created to identify the hub genes. Then, Gene Ontology (GO) functional annotation analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were carried out to investigate the regulatory network of the target genes. From the meta-analysis, miR-133a-3p was remarkably downregulated in BC tissues compared with that in non-cancer tissues (standard mean difference =− 3.84, 95% confidence interval =− 6.99–0.29). Moreover, results from SROC suggested that miR-133a-3p exhibited the ability to diagnose BC (area under curve = 0.8418). As for the bioinformatics study, 488 genes were chosen as the potential targets of miR-133a-3p in BC, among which 10 genes were defined as hub genes (all degrees  5). Further GO and KEGG pathway analysis indicated that the target genes of miR-133a-3p aggregated in specific biological process and pathways. In conclusion, miR-133a-3p possessed great diagnostic potential with its downregulation in BC, and miR-133a-3p might serve as a novel biomarker for
Metabolomic evolution of the postpartum dairy cow uterus

High rates of early pregnancy loss are a critical issue in dairy herds, particularly in seasonal, grazing systems. Components of the uterine luminal fluid (ULF), on which the early embryo depends for sustenance and growth, partly determine early pregnancy losses. Here, changes in ULF from early to mid‐postpartum in crossbred dairy cows were explored, linking them with divergent embryo development. For this, the uteri of 87 cows at Day 7 of pregnancy at first and third estrus postpartum were flushed to collect ULF. Eighteen metabolites (chiefly organic acids and sugars) significantly varied in abundance across postpartum, indicating a molecular signature of physiological recovery consistent of the upregulation of pyrimidine metabolism and glycerophospholipid metabolism, and downregulation of pentose phosphate and taurine metabolism pathways. Joint pathway analysis of metabolomics data and a previously generated proteomics data set on the same ULF samples suggests key links between postpartum recovery and subsequent successful embryo development. These include upregulation of VEGFA and downregulation of metabolism, NRF2, T‐cell receptor, which appear to improve the ULF's capacity of sustaining normal embryo development, and a putative osmo‐protectant role of beta‐alanine. These relationships should be further investigated to develop tools to detect and reduce early pregnancy loss in dairy cows.
The archaeology of infancy and infant death

A unique study of infancy and infant death that is wide-ranging and diverse in its approach. Eleanor Scott looks at theoretical issues, gender, women's power, childbirth, burial practices, infanticide and much more besides. The social and cultural attitudes to babies, infants and young adults within societies from the Neolithic to the Medieval period are explored, with examples from Britain, Europe, Scandinavia, the Americas, and Asia.
Implementing the 1D and 2D Conservation Element/Solution Element scheme coupled with the Van der Waals model

The CE/SE scheme is a fast and accurate method for solving ﬂow problems. The current version of the scheme depends on the perfect gas law, which works ﬁne for atmospheric pressures, but breaks down at higher pressures. The aim of this thesis was to change the CE/SE scheme such that it depends on the Van der Waals equation of state instead. This new algorithm should be able to simulate dense gas ﬂows with higher precision. Next, this has been used to simulate ﬂows around a wing proﬁle and to explore the differences between the perfect gas law and the Van der Waals gas law. In this thesis, the NACA-0012 wing proﬁle is used, because a lot of experimental data is available for this airfoil and it has been widely used throughout literature to test the accuracy of new algorithms. For 1D, the results were promising and the new CE/SE method was able to calculate the Sod Shock tube with much higher accuracy compared to the original CE/SE scheme. For the 2D case, two different algorithms have been written, one using a structured mesh and one using an unstructured mesh. The structured mesh has been validated using Brown and Argrow (1998) and matched visually very well. The unstructured mesh also gave visually correct results for a wave on a 30 degree wedge, but failed to calculate the ﬂow around the wing proﬁle properly. Possible causes have been listed, which can be used in further research on this topic. This thesis presents the theoretical background and a 1D and 2D implementation of the Van der Waals CE/SE scheme for structured grids.
A multiple catheter tips tracking method in X‐ray fluoroscopy images by a new lightweight segmentation network and Bayesian filtering

During percutaneous coronary intervention, the guiding catheter plays an important role. Tracking the catheter tip placed at the coronary ostium in the X‐ray fluoroscopy sequence can obtain image displacement information caused by the heart beating, which can help dynamic coronary roadmap overlap on X‐ray fluoroscopy images. Due to a low exposure dose, the X‐ray fluoroscopy is noisy and low contrast, which causes some difficulties in tracking. In this paper, we developed a new catheter tip tracking framework. First, a lightweight efficient catheter tip segmentation network is proposed and boosted by a self‐distillation training mechanism. Then, the Bayesian filtering post‐processing method is used to consider the sequence information to refine the single image segmentation results. By separating the segmentation results into several groups based on connectivity, our framework can track multiple catheter tips. The proposed tracking framework is validated on a clinical X‐ray sequence dataset.
Interaction of Large Scale Zonal Flow Anomalies and Topography

Abstract : Relatively long-term fluctuations are evident in the low level circulations surrounding the Andes and the Rocky Mountains. Some of these fluctuations are commonly explained by local, thermal influences that characterize monsoons as well as by regional responses to remote, tropical forcings. This study - first explores the seasonal cycle of low level circulations in the vicinity of the Andes and compares it to other mountainous regions such as the Rockies and the Tibetan plateau. Pronounced mechanical flow modifications appear to be associated with orographic deflection over both the Andes and the Rockies. Reanalysis diagnostics, and medium range and month-long integrations of the Utah Global Model (UGM) are presented. Analyses of orographically forced, stationary Rossby waves suggest that climatological, annual and interannual variations observed around the largest mountain ranges may be explained in terms of mechanical, orographic flow deflection. Over South America, this effect tends to produce an orographic ally bound cyclone in all seasons, with a poleward low-level jet (LLJ) east of the Andes.
MRNAV: Multi-Robot Aware Planning and Control Stack for Collision and Deadlock-free Navigation in Cluttered Environments

Multi-robot collision-free and deadlock-free navigation in cluttered environments with static and dynamic obstacles is a fundamental problem for many applications. We introduce MRNAV, a framework for planning and control to effectively navigate in such environments. Our design utilizes short, medium, and long horizon decision making modules with qualitatively different properties, and defines the responsibilities of them. The decision making modules complement each other and provide the effective navigation capability. MRNAV is the first hierarchical approach combining these three levels of decision making modules and explicitly defining their responsibilities. We implement our design for simulated multi-quadrotor flight. In our evaluations, we show that all three modules are required for effective navigation in diverse situations. We show the long-term executability of our approach in an eight hour long wall time (six hour long simulation time) uninterrupted simulation without collisions or deadlocks.
A Bayesian Active Learning Approach to Comparative Judgement

Assessment is a crucial part of education. Traditional marking is a source of inconsistencies and unconscious bias, placing a high cognitive load on the assessors. An approach to address these issues is comparative judgement (CJ). In CJ, the assessor is presented with a pair of items and is asked to select the better one. Following a series of comparisons, a rank is derived using a ranking model, for example, the BTM, based on the results. While CJ is considered a reliable method for marking, there are concerns around transparency, and the ideal number of pairwise comparisons to generate a reliable estimation of the rank order is not known. Additionally, there have been attempts to generate a method of selecting pairs that should be compared next in an informative manner, but some existing methods are known to have created their own bias within results inflating the reliability metric used. As a result, a random selection approach is usually deployed. We propose a novel Bayesian approach to CJ (BCJ) for determining the ranks of compared items alongside a new way to select the pairs to present to the marker(s) using active learning (AL), addressing the key shortcomings of traditional CJ. Furthermore, we demonstrate how the entire approach may provide transparency by providing the user insights into how it is making its decisions and, at the same time, being more efficient. Results from our experiments confirm that the proposed BCJ combined with entropy-driven AL pair-selection method is superior to other alternatives. We also find that the more comparisons done, the more accurate BCJ becomes, which solves the issue the current method has of the model deteriorating if too many comparisons are performed. As our approach can generate the complete predicted rank distribution for an item, we also show how this can be utilised in devising a predicted grade, guided by the assessor.
Black-hole mergers in disklike environments could explain the observed 
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 correlation

Current gravitational-wave data from stellar-mass black-hole binary mergers suggest a correlation between the binary mass ratio $q$ and the effective spin $\chi_\mathrm{eff}$: more unequal-mass binaries consistently show larger and positive values of the effective spin. Multiple generations of black-hole mergers in dense astrophysical environments may provide a way to form unequal-mass systems, but they cannot explain the observed correlation on their own. We show that the symmetry of the astrophysical environment is a crucial feature to shed light on this otherwise puzzling piece of observational evidence. We present a toy model that reproduces, at least qualitatively, the observed correlation. The model relies on axisymmetric, disk-like environments where binaries participating in hierarchical mergers share a preferential direction. Migration traps in AGN disks are a prime candidate for this setup, hinting at the exciting possibility of constraining their occurrence with gravitational-wave data.
The Arrangement of Marks Impacts Afforded Messages: Ordering, Partitioning, Spacing, and Coloring in Bar Charts

Data visualizations present a massive number of potential messages to an observer. One might notice that one group's average is larger than another's, or that a difference in values is smaller than a difference between two others, or any of a combinatorial explosion of other possibilities. The message that a viewer tends to notice – the message that a visualization ‘affords’ – is strongly affected by how values are arranged in a chart, e.g., how the values are colored or positioned. Although understanding the mapping between a chart's arrangement and what viewers tend to notice is critical for creating guidelines and recommendation systems, current empirical work is insufficient to lay out clear rules. We present a set of empirical evaluations of how different messages-including ranking, grouping, and part-to-whole relationships–are afforded by variations in ordering, partitioning, spacing, and coloring of values, within the ubiquitous case study of bar graphs. In doing so, we introduce a quantitative method that is easily scalable, reviewable, and replicable, laying groundwork for further investigation of the effects of arrangement on message affordances across other visualizations and tasks. Pre-registration and all supplemental materials are available at https://osf.io/np3q7 and https://osf.io/bvy95, respectively.
Signal Detection with Quadratically Convex Orthosymmetric Constraints

This paper is concerned with signal detection in Gaussian noise under quadratically convex orthosymmetric (QCO) constraints. Specifically the null hypothesis assumes no signal, whereas the alternative considers signal which is separated in Euclidean norm from zero, and belongs to the QCO constraint. Our main result establishes the minimax rate of the separation radius between the null and alternative purely in terms of the geometry of the QCO constraint -- we argue that the Kolmogorov widths of the constraint determine the critical radius. This is similar to the estimation problem with QCO constraints, which was first established by Donoho et al. (1990); however, as expected, the critical separation radius is smaller compared to the minimax optimal estimation rate. Thus signals may be detectable even when they cannot be reliably estimated.
Parental Health Penalty on Adult Children's Employment: Gender Difference and Long-Term Consequence

This paper examines the long-term gender-specific impacts of parental health shocks on adult children's employment in China. We build up an inter-temporal cooperative framework to analyze household work decisions in response to parental health deterioration. Then employing an event-study approach, we establish a causal link between parental health shocks and a notable decline in female employment rates. Male employment, however, remains largely unaffected. This negative impact shows no abatement up to eight years that are observable by the sample. These findings indicate the consequence of"growing old before getting rich"for developing countries.
Kissing to Find a Match: Efficient Low-Rank Permutation Representation

Permutation matrices play a key role in matching and assignment problems across the fields, especially in computer vision and robotics. However, memory for explicitly representing permutation matrices grows quadratically with the size of the problem, prohibiting large problem instances. In this work, we propose to tackle the curse of dimensionality of large permutation matrices by approximating them using low-rank matrix factorization, followed by a nonlinearity. To this end, we rely on the Kissing number theory to infer the minimal rank required for representing a permutation matrix of a given size, which is significantly smaller than the problem size. This leads to a drastic reduction in computation and memory costs, e.g., up to $3$ orders of magnitude less memory for a problem of size $n=20000$, represented using $8.4\times10^5$ elements in two small matrices instead of using a single huge matrix with $4\times 10^8$ elements. The proposed representation allows for accurate representations of large permutation matrices, which in turn enables handling large problems that would have been infeasible otherwise. We demonstrate the applicability and merits of the proposed approach through a series of experiments on a range of problems that involve predicting permutation matrices, from linear and quadratic assignment to shape matching problems.