Miracle-dz/UniFAR-FTUs huggingface dataset:
Tax Composition and Growth: A Broad Cross-country Perspective

Abstract We investigate how changes in the composition of tax revenue affect long-run growth in a broad cross-section of countries. To do this, we construct a new dataset that covers 70 countries (23 high-, 23 middle- and 24 low-income countries), with at least 20 years of observations during the period 1970-2009. In the context of revenue-neutral reallocations, we find that increasing consumption and property taxes while reducing income taxes boosts long-term growth. Among income taxes, we find that social security contributions and personal income taxes tend to have a stronger negative association with growth relative to corporate income taxes. Results, however, depend on countries’ development levels, suggesting nonlinearities in the relation between taxes and growth even after controlling for convergence effects. Although results are robust for high- and middle-income countries, these are generally not significant for low-income countries.
Waste Not , Want Not : Why Rarefying Microbiome Data is Inadmissible . October 1 , 2013

The interpretation of count data originating from the current generation of DNA sequencing platforms requires special attention. In particular, the per-sample library sizes often vary by orders of magnitude from the same sequencing run, and the counts are overdispersed relative to a simple Poisson model [1]. These challenges can be addressed using an appropriate mixture model that simultaneously accounts for library size differences and biological variability. This approach is already wellcharacterized and implemented for RNA-Seq data in R packages such as edgeR [2] and DESeq [3]. Unfortunately, this class of techniques has been overlooked in the microbiome literature [4, 5], where the currentlyrecommended library size normalization is done by computing proportions or by rarefying counts through random subsampling until each library has the same sum [6]. We use statistical theory, extensive simulations, and empirical data to show that variance stabilizing normalization using a mixture model like the negative binomial is appropriate for microbiome count data. In simulations detecting differential abundance, normalization procedures based on a Gamma-Poisson mixture model provided systematic improvement in performance over crude proportions or rarefied counts – both of which led to a high rate of false positives. In simulations evaluating clustering accuracy, we found that the rarefying procedure discarded samples that were nevertheless accurately clustered by alternative methods, and that the choice of minimum library size threshold was critical in some settings, but with an optimum that is unknown in practice. Techniques that use variance stabilizing transformations by modeling microbiome count data with a mixture distribution, such as those implemented in edgeR and DESeq, substantially improved upon techniques that attempt to normalize by rarefying or crude proportions. Based on these results and well-established statistical theory, we advocate that investigators avoid rarefying altogether. We have provided microbiome-specific extensions to these tools in the R package, phyloseq.
Reynolds number effect on drag reduction in pipe flows by a transverse wall oscillation

Direct numerical simulations of turbulent pipe flow with transverse wall oscillation (WWO) and with no transverse wall oscillation (NWO) are carried out at friction Reynolds numbers Re{\tau} = 170, 360, and 720. The period and amplitude of the oscillation are selected to achieve high drag reduction in this Reynolds number range, and the effect of increasing Reynolds number on the amount of drag reduction achievable is analyzed. Of a particular interest in this study is the identification of the scales of motion most affected by drag reduction at different Reynolds numbers. To answer this question, both one-dimensional and two-dimensional spectra of different statistical quantities are analyzed with and without transverse wall oscillation. The effect of wall oscillation is found to suppress the intermediate- and large-scale motions in the buffer layer of the flow, while large-scale and very-large-scale motions in the log layer and the wake region are enhanced. While suppression of the near-wall turbulence promotes drag reduction, enhancement of the large-scale motions in the log and the wake region is found to oppose drag reduction. Since higher Reynolds number flows support development of a growing range of large-scale structures, it is suggested that their prevalence in the energy spectra combined with their negative effect on drag reduction account for a reduced effectiveness of wall oscillation as a drag reduction mechanism with increasing Reynolds numbers.
Invariance & Causal Representation Learning: Prospects and Limitations

In causal models, a given mechanism is assumed to be invariant to changes of other mechanisms. While this principle has been utilized for inference in settings where the causal variables are observed, theoretical insights when the variables of interest are latent are largely missing. We assay the connection between invariance and causal representation learning by establishing impossibility results which show that invariance alone is insufficient to identify latent causal variables. Together with practical considerations, we use these theoretical findings to highlight the need for additional constraints in order to identify representations by exploiting invariance.
Seasonal Variations of Subtropical Precipitation Associated with the Southern Annular Mode

AbstractSeasonal variations of subtropical precipitation anomalies associated with the southern annular mode (SAM) are explored for the period 1979–2011. In all seasons, high-polarity SAM, which refers to a poleward-shifted eddy-driven westerly jet, results in increased precipitation in high latitudes and decreased precipitation in midlatitudes as a result of the concomitant poleward shift of the midlatitude storm track. In addition, during spring–autumn, high SAM also results in increased rainfall in the subtropics. This subtropical precipitation anomaly is absent during winter. This seasonal variation of the response of subtropical precipitation to the SAM is shown to be consistent with the seasonal variation of the eddy-induced divergent meridional circulation in the subtropics (strong in summer and weak in winter). The lack of an induced divergent meridional circulation in the subtropics during winter is attributed to the presence of the wintertime subtropical jet, which causes a broad latitudinal spa.
Detection of Lead (Pb) and Cadmium (Cd) Concentrations and Hazards in Some Baby Food Samples

This study was conducted to detect the concentration of lead and cadmium in baby foods, (18) samples were examined, which are the most available from various local markets in the city of Baghdad (at a rate of (9) samples of baby food consisting of cereals and (9) samples of baby foods consisting of vegetables). All samples were examined using an atomic flame absorptiometry (AAS-7000), all results showed the presence of lead and cadmium and the highest concentration value of lead in baby foods consisting of cereals (1.0986) and cadmium in baby foods consisting of vegetables (0.0015) ppm. Lead exceeded 100% limitations and cadmium did not exceed that. The results reported on the risks of contamination, as the mean daily intake (g/kg/d) for lead (1.3538) and cadmium amounted to (0.010), and the target hazard quotient index was high for the index (THQ>10) for lead in most of the samples examined and reached (THQ<10) in some samples examined, while cadmium all samples reached an index of (THQ<10). The study showed an increase in lead concentrations and perceptible risks and did not report an increase in cadmium concentrations outside the determinants, but it warns of imperceptible risks to the consumer. The study showed statistically significant differences between the levels of lead and cadmium and between the studied species and did not show statistically significant differences between the origins at the level of significance (0.05). It has been shown that these products pose a risk to children when consumed, so these products must be banned and ways must be found to reduce or prevent these pollutants with these products or find appropriate alternatives.
Linear polarization of the stochastic gravitational-wave background with pulsar timing arrays

Pulsar-timing collaborations have recently reported evidence for the detection of an isotropic stochastic gravitational-wave background consistent with one sourced by a population of inspiralling supermassive black hole binaries. However, a certain degree of anisotropy and polarization may be present. Thus, the characterization of the energy density and polarization of the background at different angular scales is important. In this paper, we describe the signatures of linear polarization in the stochastic gravitational-wave background on the timing residuals obtained with pulsar-timing arrays. We expand the linear polarization map in terms of spin-weighted spherical harmonics and recast it into the $E$-mode (parity even) and $B$-mode (parity odd) basis. We provide expressions for the minimum-variance estimators for the coefficients of that expansion and evaluate the smallest detectable signal as a function of the signal-to-noise ratio with which the isotropic GW signal is detected and the number of pulsars in the survey. We evaluate the covariance between the estimators for the spherical-harmonic coefficients of the linear polarization $E$-modes and those for the intensity anisotropy. We also show that there is no covariance between the spherical-harmonic coefficients for the $B$-modes of the linear polarization and those for the circular polarization, even though both have the same parity. Our approach results in simple, elegant, and easily evaluated expressions for the overlap reduction functions for linear polarization.
Synthesizing Physical Backdoor Datasets: An Automated Framework Leveraging Deep Generative Models

Backdoor attacks, representing an emerging threat to the integrity of deep neural networks, have garnered significant attention due to their ability to compromise deep learning systems clandestinely. While numerous backdoor attacks occur within the digital realm, their practical implementation in real-world prediction systems remains limited and vulnerable to disturbances in the physical world. Consequently, this limitation has given rise to the development of physical backdoor attacks, where trigger objects manifest as physical entities within the real world. However, creating the requisite dataset to train or evaluate a physical backdoor model is a daunting task, limiting the backdoor researchers and practitioners from studying such physical attack scenarios. This paper unleashes a recipe that empowers backdoor researchers to effortlessly create a malicious, physical backdoor dataset based on advances in generative modeling. Particularly, this recipe involves 3 automatic modules: suggesting the suitable physical triggers, generating the poisoned candidate samples (either by synthesizing new samples or editing existing clean samples), and finally refining for the most plausible ones. As such, it effectively mitigates the perceived complexity associated with creating a physical backdoor dataset, transforming it from a daunting task into an attainable objective. Extensive experiment results show that datasets created by our"recipe"enable adversaries to achieve an impressive attack success rate on real physical world data and exhibit similar properties compared to previous physical backdoor attack studies. This paper offers researchers a valuable toolkit for studies of physical backdoors, all within the confines of their laboratories.
Inoculant arbuscular mycorrhizal fungi compatibility test using sweet corn plants on peatlands

Corn is a food ingredient that is widely consumed by Indonesian people. The purpose of this study is to determine the compatibility of AMF isolates from several host plants with the yield components of sweet corn on peatlands. The field experiments were carried out with a randomized block design (RCBD) with 5 treatments and 3 replications. The treatments referred to are m0 (without AMF inoculation), m1 (AMF inoculum from the host Pueraria Javanica), m2 (AMF inoculum from the soybean plant host), m3 (AMF inoculum from the corn plant host) and m4 (AMF inoculum from the sorghum plant host). Observations were made on mycorrhizal infections, absorption of N, P, K nutrients, and plant yield components including weight per ear with weight, weight per ear without husk, ear length, ear diameter, and ear weight per plot. The data acquired from the observation were statistically analyzed using analysis of variance (F test), while further tests were done with Duncan's multiple distance test (DMRT). The results showed that AMF inoculant derived from maize rhizosphere is most compatible with corn plants compared to AMF inoculant from rhizosphere sorghum, P.javanica, soybeans, and without inoculation. AMF inoculant from maize rhizosphere can increase root infection, absorption.
Social Movement Organizations Beyond The Beltway: Understanding The Diversity Of One Social Movement Industry

This article utilizes a unique data set on a nationally representative sample of one social movement industry (groups working for peace) operating in the U.S. during the late 1980s. The data include the full spectrum of SMOs, which we divide into organizational domains that roughly parallel prior research and currently available secondary data sources: (1) numerous, but generally quite small groups that operate without tax-exempt status; (2) small, non-national, tax-exempt groups; (3) large, non-national, tax-exempt groups; (4) national organizations that have been the focus of most research in the field. First, the population parameters of the peace movement industry is estimated and groups typical of each domain profiled. We then undertake a series of analyses to examine how the groups in each of these four domains differ from each other on a variety of organizational attributes, including organizational form, co-sponsoring events, tactics and activities, membership type, participation in formal democra.
The new database of the Global Terrestrial Network for Permafrost (GTN-P)

Abstract. The Global Terrestrial Network for Permafrost (GTN-P) provides the first dynamic database associated with the Thermal State of Permafrost (TSP) and the Circumpolar Active Layer Monitoring (CALM) programs, which extensively collect permafrost temperature and active layer thickness (ALT) data from Arctic, Antarctic and mountain permafrost regions. The purpose of GTN-P is to establish an early warning system for the consequences of climate change in permafrost regions and to provide standardized thermal permafrost data to global models. In this paper we introduce the GTN-P database and perform statistical analysis of the GTN-P metadata to identify and quantify the spatial gaps in the site distribution in relation to climate-effective environmental parameters. We describe the concept and structure of the data management system in regard to user operability, data transfer and data policy. We outline data sources and data processing including quality control strategies based on national correspondents. Assessment of the metadata and data quality reveals 63 % metadata completeness at active layer sites and 50 % metadata completeness for boreholes. Voronoi tessellation analysis on the spatial sample distribution of boreholes and active layer measurement sites quantifies the distribution inhomogeneity and provides a potential method to locate additional permafrost research sites by improving the representativeness of thermal monitoring across areas underlain by permafrost. The depth distribution of the boreholes reveals that 73 % are shallower than 25 m and 27 % are deeper, reaching a maximum of 1 km depth. Comparison of the GTN-P site distribution with permafrost zones, soil organic carbon contents and vegetation types exhibits different local to regional monitoring situations, which are illustrated with maps. Preferential slope orientation at the sites most likely causes a bias in the temperature monitoring and should be taken into account when using the data for global models. The distribution of GTN-P sites within zones of projected temperature change show a high representation of areas with smaller expected temperature rise but a lower number of sites within Arctic areas where climate models project extreme temperature increase. GTN-P metadata used in this paper are available at doi: 10.1594/PANGAEA.842821 .
Slave River delta: geomorphology, sedimentology, and Holocene reconstruction

The Holocene Slave River delta (8300 km2) is a long (170 km), narrow (42 km average width) alluvial sand body, which extends north from the Slave River rapids at Fort Smith to Great Slave Lake, Northwest Territories. The delta is flanked by the Talston and Tethul rivers and Canadian Shield to the east and by the Little Buffalo River to the west. Wave-associated sedimentary structures in lithostratigraphic logs from river cutbanks indicate that the sandy delta was wave influenced. Most of the logs (34) consist of three facies: basal laminated mud (unknown thickness), interbedded mud and sand (2.5 m), and planar-tabular ripple sets interbedded with cross-laminated to flat-bedded sand (3.0–14.5 m). Eleven radiocarbon-dated wood samples from river cutbanks were used to reconstruct the delta paleoshoreface and to calculate the rate of progradation, which averaged 20.7 m/year from 8070 BP to the present. In the same period isostatic rebound of the delta region relative to the Liard River delta averaged 12 cm/km .
Evidence for fish predation on a coleoid cephalopod from the Lower Jurassic Posidonia Shale of Germany

A specimen of the Early Jurassic actinopterygian fish Pachycormus sp. from the Lower Jurassic Posidonia Shale of Germany has a well preserved filling of the alimentary canal. The region interpreted as the stomach contains numerous hooklets that can be referred to the coleoid cephalopod Phragmoteuthis Mojsisovics, 1882. The presence of arm hooklets clearly demonstrates predation on coleoid cephalopods by actinopterygian fishes.
Physical activity modifies the association of the composite dietary antioxidant index with all-cause mortality in the US osteoarthritis population

Background It remains unclear how antioxidant intake affects all-cause mortality in osteoarthritis (OA) patients. In this prospective cohort study, we aim to explore the association of the Composite Dietary Antioxidant Index (CDAI) with all-cause mortality and investigate the interaction of physical activity (PA) and CDAI on all-cause mortality in OA populations. Methods A total of 3,197 adults with OA in the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2018 were included in this study. Death outcomes were obtained from National Death Index (NDI) records. Multivariable Cox regression analyses with cubic spines were applied to estimate the association of CDAI with all-cause mortality. The interaction between CDAI and PA on all-cause mortality was further assessed in stratified analysis and interaction tests. Results The hazard ratios for all-cause mortality were 0.95 (0.77–1.17) for Q2, 0.75 (0.59–0.97) for Q3, and 0.71 (0.55–0.92) for Q4 (P for trend <0.001), compared with the lowest quartile of CDAI. A negative linear association was found between CDAI and all-cause mortality. In the stratified analyses, CDAI was negatively associated with all-cause mortality in the insufficient PA group. While in the low and sufficient PA group, there were nonlinear relationships of CDAI with all-cause mortality. Conclusion A negative linear relationship was observed between CDAI and all-cause mortality in OA patients, and this association was significantly modified by PA. Higher intake of dietary antioxidants might be the interventional objective to reduce the risk of all-cause mortality in the US OA population.
Burnout and depression among college students pursuing Bachelor of Physiotherapy and Occupational Therapy, in Delhi NCR - a cross sectional study

Stressors from everyday life, along with those from work and academic environment, may compromise the mental health and well-being of allied health professionals. With this study, we tried to estimate the prevalence and factors associated with burnout and depression among students of Bachelor of Physical Therapy and Occupational Therapy in Delhi NCR region. This cross-sectional study was carried out among 197 students pursuing a Bachelor of Physiotherapy (BPT) and Occupational Therapy (BOT) in Delhi, NCR region. Data collection was online, using Oldenburg Burnout Inventory (OLBI) and Patient Health Questionnaire (PHQ-9) to assess burnout and depression, respectively, along with basic socio-demographic information. Data analysis was carried out on Stata 15.1. Prevalence was estimated, and factors associated with Burnout and depression were explored using Linear and logistic regression models, respectively. Among 197 participants, the majority were females and the mean age was 22 years. The prevalence of burnout and depression was 79.7% (95% CI: 73.4, 84.7) and 66.5% (95% CI: 59.6, 72.7), respectively. Some factors, like experiencing symptoms of physical exhaustion and satisfaction with academic support from faculty at college, were associated with both burnout and depression separately. The prevalence of burnout and depression among BPT/BOT students in Delhi, NCR, was alarming yet comparable to other health professionals in India and globally. The study provides a narrative of these issues along with associated factors identified among the study population. A need for a longitudinal study to establish a causal association of factors with burnout and depression among this study population is iterated.
Conference on ‘ Diet , gut microbiology and human health ’ Symposium 3 : Diet and gut metabolism : linking microbiota to bene fi cial products of fermentation Human gut microbiota : does diet matter ?

The human oro-gastrointestinal (GI) tract is a complex system, consisting of oral cavity, pharynx, oesophagus, stomach, small intestine, large intestine, rectum and anus, which all together with the accessory digestive organs constitute the digestive system. The function of the digestive system is to break down dietary constituents into small molecules and then absorb these for subsequent distribution throughout the body. Besides digestion and carbohydrate metabolism, the indigenous microbiota has an important influence on host physiological, nutritional and immunological processes, and commensal bacteria are able to modulate the expression of host genes that regulate diverse and fundamental physiological functions. The main external factors that can affect the composition of the microbial community in generally healthy adults include major dietary changes and antibiotic therapy. Changes in some selected bacterial groups have been observed due to controlled changes to the normal diet e.g. high-protein diet, high-fat diet, prebiotics, probiotics and polyphenols. More specifically, changes in the type and quantity of non-digestible carbohydrates in the human diet influence both the metabolic products formed in the lower regions of the GI tract and the bacterial populations detected in faeces. The interactions between dietary factors, gut microbiota and host metabolism are increasingly demonstrated to be important for maintaining homeostasis and health. Therefore the aim of this review is to summarise the effect of diet, and especially dietary interventions, on the human gut microbiota. Furthermore, the most important confounding factors (methodologies used and intrinsic human factors) in relation to gut microbiota analyses are elucidated.