Miracle-dz/UniFAR-FTUs huggingface dataset:
Ain’t no mountain high enough? New records of Notiomastodon platensis (Mammalia, Proboscidea) from Colombia and the Quaternary dry corridor of the Cauca valley

ABSTRACT In this study, we present new records of the extinct South American proboscidean Notiomastodon platensis from three new fossiliferous sites in the riverbed of Cauca River, in the department of Valle del Cauca, Colombia. The fossil specimens were found in late Pleistocene deposits and include immature to senile Notiomastodon platensis individuals, comprising abundant dental and post-cranial materials. A review of the geographic distribution of the Notiomastodon platensis records in Colombia suggests that this giant mammal used the inter-Andean valleys as migratory corridors, possibly due to the presence of more suitable environmental conditions (lower temperatures and dry-forest) and energy-saving terrains, avoiding more prominent Andean hills. In addition, the Cauca Valley deposits stand out as having palaeontological significance to the comprehension of the late Pleistocene of the western region of South America.
The application of machine learning techniques in prediction of quality of life features for cancer patients

Quality of life (QoL) is one of the major issues for cancer patients. With the advent of medical databases containing large amounts of relevant QoL information it becomes possible to train predictive QoL models by machine learning (ML) techniques. However, the training of predictive QoL models poses several challenges mostly due to data privacy concerns and missing values in patient data. In this paper, we analyze several classification and regression ML models predicting QoL indicators for breast and prostate cancer patients. Three different approaches are employed for imputing missing values, and several settings for data privacy preserving are tested. The examined ML models are trained on datasets formed from two databases containing a large number of anonymized medical records of cancer patients from Sweden. Two learning scenarios are considered: centralized and federated learning. In the centralized learning scenario all patient data coming from different data sources is collected at a central location prior to model training. On the other hand, federated learning enables collective training of machine learning models without data sharing. The results of our experimental evaluation show that the predictive power of federated models is comparable to that of centrally trained models for short-term QoL predictions, whereas for long-term periods centralized models provide more accurate QoL predictions. Furthermore, we provide insights into the quality of data preprocessing tasks (missing value imputation and differential privacy).
Lower Bounds to Error Probability for Coding on Discrete Memoryless Channels. I

New lower bounds are presented for the minimum error probability that can be achieved through the use of block coding on noisy discrete memoryless channels. Like previous upper bounds, these lower bounds decrease exponentially with the block length N . The coefficient of N in the exponent is a convex function of the rate. From a certain rate of transmission up to channel capacity, the exponents of the upper and lower bounds coincide. Below this particular rate, the exponents of the upper and lower bounds differ, although they approach the same limit as the rate approaches zero. Examples are given and various incidental results and techniques relating to coding theory are developed. The paper is presented in two parts: the first, appearing here, summarizes the major results and treats the case of high transmission rates in detail; the second, to appear in the subsequent issue, treats the case of low transmission rates.
Factors Related to the Event of Stunting in Toddlers Aged 24 – 59 Months in the Work Area of the Katobu Community Health Center, Muna Regency

One of the Sustainable Development Goals (SDGs) is to end hunger and all types of malnutrition by 2030 and to ensure that everyone has access to sufficient, safe, and nutritious food. Stunting, a developmental delay that often manifests itself in children older than 2 years old, is caused by persistent malnutrition throughout pregnancy and the first few years of life. In 2018, 27.7% of toddlers in Southeast Sulawesi were stunted, making it a significant public health issue. The goal of this study is to identify risk factors for stunting among children between the ages of 24- and 59-months old living in the catchment area of Katobu Health Center. Research method combining analytical observing with a case-control setup. Information collected via surveys, in-person interviews, the use of a height chart for children, and files from Katobu Health Center were analyzed. Birth weight and maternal upper arm circumference (LiLA) during pregnancy were not associated with a higher risk of stunting (each p value = 0.5). However, the odds ratio for stunting was significantly lower among children who were exclusively breastfed (p = 0.03). One of the ways to prevent children from becoming too short is to nurse them exclusively. Therefore, promoting advice on exclusive breastfeeding is important to improve toddlers' nutritional condition.
Winds from T Tauri stars. I: Spherically symmetric models

Line fluxes and profiles are computed for a sequence of spherically symmetric T Tauri wind models. The calculations indicate that the H-alpha emission of T Tauri stars arises in an extended and probably turbulent circumstellar envelope at temperatures above about 8000 K. The models predict that Mg II resonance line emission should be strongly correlated with H-alpha fluxes; observed Mg II/H-alpha ratios are inconsistent with the models unless extinction corrections have been underestimated. The models predict that most of the Ca II resonance line and IR triplet emission arises in dense layers close to the star rather than in the wind. H-alpha emission levels suggest mass loss rates of about 10 to the -8th solar mass/yr for most T Tauri stars, in reasonable agreement with independent analysis of forbidden emission lines. These results should be useful for interpreting observed line profiles in terms of wind densities, temperatures, and velocity fields. 67 refs.
Prevention of Skin Cancer: Healthy Sun Exposure and No sunscreen for Intense Intermittent Exposure; Photoaging Theories Questioned and New Strategies

Currently the FDA adopts a zero-tolerance policy toward sun exposure in order to prevent skin cancer and premature skin aging (photoaging). This is apparently based on classical concept that damage from sunlight, a carcinogen, is cumulative and un-reparable. Such concept is apparently flawed both theoretically and in reality. The nature’s design to achieve genomic stability of body health and appearance for smooth passage of generations in our normal daily lives would require virtually complete repair of damages of DNA and other tissue components from daily Exposure to Non-Burning Sunlight (ENS). In other words, ENS is generally not expected to cause skin cancer and photoaging. Such notion is evidenced by, for example, low worldwide skin-cancer incidences, severe sunburn as overwhelming skin-cancer etiology, and intrinsic aging as overwhelming skin aging. Since ENS can provide numerous health benefits, such exposure can be regarded as healthy sun exposure and used to help prevent skin cancer. Due to unintended sunburn effect, use of sunscreens for intense intermittent exposure is strongly discouraged. As photoaging and skin cancer may be closely related, some questions related to conventional theories and practices in photoaging are also raised. They include the following: Schuster’s pioneering study in 1975; invalidation of accelerated aging theory; questionable theory on etiology of wrinkles and age spots; Fisher’s studies on metalloproteinases; bolus doing vs constant-rate dosing in irradiation; moisturizers as anti-photoaging/anti-cancer agents; inclusion of blood and water in skin-aging exosome; wind effect; differences in usage pattern between countries in sunscreen evaluation; replacement of UVA in tanning beds.
Effects of vorticity on rocket combustion stability

Combustion stability computations are currently based on an irrotational model that allows slip flow at the burning surface. However, the no-slip boundary condition must be satisfied when gas motions are parallel to the combustion zone. Then waves of vorticity are created that distort the acoustic wave structure and modify the fluctuating normal velocity component upon which system stability is so strongly dependent. This flow problem is solved here in analytical form to bring the physical details into focus. Crocco's theorem shows that the creation of vorticity is due primarily to the axial unsteady pressure gradient across mean flow streamlines at the surface. Hence, there is a transfer of energy from the pressure oscillations (acoustic field) to the rotational waves (vorticity field). It is in this interaction that the incoming flow acquires the axial motion of the acoustic wave. Stability calculations based on this model yield the three-dimensional form of Culick's one-dimensional flow-turning correction and clarify its origin. However, continuity at the burning surface requires a correction to the radial velocity fluctuations. Incorporation of this new driving effect leads to a motor system that is significantly less stable than in the classical prediction (Standard Stability Prediction Program) for some configurations.
The effects of proposal power on incumbents' vote share: updated results from a naturally occurring experiment

A pioneering study by Loewen et al. made use of the Canadian legislature's newly instituted lottery, which enabled non-cabinet Members of Parliament (MPs) to propose a bill or motion. Their study used this lottery in order to identify the causal effect of proposal power on incumbents' vote share in the next election. Analyzing the first two parliaments to use the lottery, Loewen et al. found that proposal power benefits incumbents, but only incumbents who belong to the governing party. Our study builds on these initial results by adding data from four subsequent parliaments. The pooled results no longer support the hypothesis that MPs—even those who belong to the governing party—benefit appreciably from proposal power. These updated findings resolve a theoretical puzzle noted by Loewen et al., as proposal power would not ordinarily be expected to confer electoral benefits in strong party systems, such as Canada's.
Deep Learning Models Applied to Prediction of 5G Technology Adoption

The issue addressed by this research study is the public’s scepticism about the benefits of adopting 5G technology. Some have even gone so far as to say that the technology can be harmful to people, while others are still looking for reassurance. This is why it is crucial to comprehend the primary factors that will affect the spread of 5G networks. The method used for this heavily relies on a deep learning algorithm. Channel metrics, context metrics, cell metrics, and throughput data are the conceptualized variables that will serve as the primary indicators for determining the adoption of 5G technology. Three deep learning models—deep reinforcement (DR), long-short term memory (LSTM), and a convolutional neural network (CNN)—were applied. The results show that the DR model and the CNN model are the most effective at predicting the elements that would affect 5G adoption. Despite the fact that LSTM models appear to have a high degree of accuracy, the quality of the data they output is quite poor. However, this is the case even when the models appear to be rather accurate. The logical inferences drawn from these findings show that the DR model and the CNN model’s applicability to the problem of predicting the rate at which 5G will be adopted can be put into practice with a high degree of accuracy. The novelty of this study is in its emphasis on using channel metrics, context metrics, cell metrics, and throughput data to focus on predictions for the development of 5G networks themselves and on the generation of the elements that determine the adoption of 5G. Previous efforts in the literature failed to establish methods for adopting 5G technology related to the criteria considered in this study; hence, this research fills a gap.
Bayes Factors for Smoothing Spline ANOVA

This paper describes an approach for variable selection and hypothesis testing in semiparametric additive models using Bayes factors in smoothing spline analysis of variance (SSANOVA) models. Eﬀects can be linear or nonparametric (i.e., smooth or interactions between selected linear and smooth eﬀects). To evaluate the importance of each term in the model, we develop Bayes factors for both linear and nonparametric terms. We compute approximate Bayes factors by Monte Carlo and Laplace integration. These Bayes factors can be computed to compare any two sub-models including one model nested in another. This permits formal tests of any portion or simultaneous portions of an SSANOVA model. We demonstrate this approach with an example.
POINTS OF FINITE ORDER ON AN ABELIAN VARIETY

In this paper it is shown that the image of the Galois group under an -adic representation in the Tate module of an abelian variety has an algebraic Lie algebra which contains the scalar matrices as a subalgebra (Serre's conjecture). This paper also proves the finiteness of the intersection of a subgroup of an abelian variety all of whose elements have order equal to a power of a fixed number with a wide class of subvarieties. Bibliography: 13 titles.
Betulin Acid Ester Derivatives Inhibit Cancer Cell Growth by Inducing Apoptosis through Caspase Cascade Activation: A Comprehensive In Vitro and In Silico Study

Betulin, or naturally occurring triterpene, possesses promising antiproliferative activity. To further explore this potential, thirty-eight betulin acid ester derivatives modified at the C-28 position were tested for antitumor activities. Four human cancer cell lines, MV4-11 (leukemia), A549 (lung), PC-3 (prostate), MCF-7 (breast) as well as the normal BALB/3T3 (mouse fibroblasts) cell line were examined using MTT and SRB assays. A few derivatives exhibited strong antiproliferative activity with IC50 values between 2 and 5 µM. Subsequent mechanistic studies revealed that some derivatives induced apoptosis by inducing caspase-3/7 activity. A strong structure–activity correlation of tested compounds has been proposed along with experimental and in silico pharmacokinetic properties.
A higher-order boundary layer analysis for lipid vesicles with two fluid domains

We obtain approximate solutions to the equations that govern the shape of giant unilamellar vesicles (GUVs) with two fluid phases. The equations involve a dimensionless small parameter related to the resistance to changes in its local mean curvature. Asymptotic solutions for the shape are obtained up to and including terms of first order in the small parameter. At this order, we determine a relationship between the tangent angle at the interface and the difference in the Gaussian curvature stiffnesses of the co-existing phases. This relationship demonstrates that a difference in the Gaussian curvature stiffnesses moves the phase boundary away from the neck, as determined in previous numerical studies. The analytical expression for the tangent angle obtained here can be used to determine elastic parameters for the membranes from experimental data. Use of the analytical expression will eliminate the need for the repeated generation of numerical solutions in the estimation of the material parameters. Our analytical solution also reduces the number of measurements needed as inputs for an existing boundary layer analysis.
Logic, Logic, and Logic

Part 1 Studies on set theory and the nature of logic: the iterative conception of set reply to Charles Parsons' "Sets and Classes" on second-order logic to be is to be a value of a variable (or to be some values of some variables) nominalist platonism iteration again introductory note to Kurt Godel's "Some Basic Theorems on the Foundations of Mathematics and their Implications" must we believe in set theory? Part 2 Frege studies: Gottlob Frege and the foundations of arithmetic reading the "Bergriffsschrift" saving Frege from contradiction the conspiracy of Frege's "Foundations of Arithmetic" the standard of equality of numbers whence the contradiction? 1879? the advantages of honest toil over theft on the proof of Frege's theorem Frege's theorem and the Peano Postulates is Hume's principle analytic? Die Grundlagen der Arithmetik 82-83 (Richard Heck) constructing Cantorian counterexamples. Part 3 Various logical studies and lighter papers: zooming down the slippery slope don't eliminate cut the justification of mathematical induction a curious inference a new proof of the Godel Incompleteness theorem on "seeing" the truth of the Godel sentence quotational amibguity the hardest logical puzzle ever Godel's Second Incompleteness theorem explained in words of one syllable.
Severe COVID-19 May Impact Hepatic Fibrosis /Hepatic Stellate Cells Activation as Indicated by a Pathway and Population Genetic Study

Coronavirus disease 19 (COVID-19) has affected over 112 million people and killed more than 2.5 million worldwide. When the pandemic was declared, Spain and Italy accounted for 29% of the total COVID-19 related deaths in Europe, while most infected patients did not present severe illness. We hypothesised that shared genomic characteristics, distinct from the rest of Europe, could be a contributor factor to a poor prognosis in these two populations. To identify pathways related to COVID-19 severity, we shortlisted 437 candidate genes associated with host viral intake and immune evasion from SARS-like viruses. From these, 21 were associated specifically with clinically aggressive COVID-19. To determine the potential mechanism of viral infections, we performed signalling pathway analysis with either the full list (n = 437) or the subset group (n = 21) of genes. Four pathways were significantly associated with the full gene list (Caveolar-mediated Endocytosis and the MSP-RON Signalling) or with the aggressive gene list (Hepatic Fibrosis/Hepatic Stellate Cell (HSC) Activation and the Communication between Innate and Adaptive Immune Cells). Single nucleotide polymorphisms (SNPs) from the ±1 Mb window of all genes related to these four pathways were retrieved from the dbSNP database. We then performed Principal Component analysis for these SNPs in individuals from the 1000 Genomes of European ancestry. Only the Hepatic Fibrosis/HSC Activation pathway showed population-specific segregation. The Spanish and Italian populations clustered together and away from the rest of the European ancestries, with the first segregating further from the rest. Additional in silico analysis identified potential genetic markers and clinically actionable therapeutic targets in this pathway, that may explain the severe disease.
On the Use of Hot-Wire Anemometers for Turbulence Measurements in Clouds

Abstract The use of a hot-wire anemometer for high-resolution turbulence measurements in a two-phase flow (e.g., atmospheric clouds) is discussed. Experiments in a small wind tunnel (diameter of 0.2 and 2 m in length) with a mean flow velocity in the range between 5 and 16 m s−1 are performed. In the wind tunnel a spray with a liquid water content of 0.5 and 2.5 g m−3 is generated. After applying a simple despiking algorithm, power spectral analysis shows the same results as spectra observed without spray under similar flow conditions. The flattening of the spectrum at higher frequencies due to impacting droplets could be reduced significantly. The time of the signal response of the hot wire to impacting droplets is theoretically estimated and compared with observations. Estimating the fraction of time during which the velocity signal is influenced by droplet spikes, it turns out that the product of liquid water content and mean flow velocity should be minimized. This implies that for turbulence measureme.
A NUMERICAL STUDY OF EFFECT OF INITIAL CONDITION ON LARGE EDDY SIMULATION OF THERMAL PLUME

Large eddy simulations of thermal plume in two different scenarios have been carried out using a self-developed parallel computational fluid dynamics (CFD) code, SMAFS (Smoke Movement And Flame Spread), with subgrid-scale turbulence modeled using the Smagorinsky model. Two different initial conditions were used in the simulations, and the results were compared to show that the initial condition has a significant effect on the prediction of the plume's evolution behavior. The filtered governing equations were discretized using the finite-volume method, with the variables at the cell faces in the finite-volume discrete equations approximated by a second-order bounded QUICK scheme and the diffusion term computed based on the central difference scheme. All the computations were explicitly time-marched, with the momentum equations solved based on a second-order fractional-step Adams-Bashford scheme and the enthalpy computed using a second-order Runge-Kutta method. The Poisson equation for pressure from the continuity equation was solved using a multigrid solver.
Fear, Risk Perception, and Engagement in Preventive Behaviors for COVID-19 during Nationwide Lockdown in Nepal

The world has faced huge negative effects from the COVID-19 pandemic between early 2020 and late 2021. Each country has implemented a range of preventive measures to minimize the risk during the COVID-19 pandemic. This study assessed the COVID-19-related fear, risk perception, and preventative behavior during the nationwide lockdown due to COVID-19 in Nepal. In a cross-sectional study, conducted in mid-2021 during the nationwide lockdown in Nepal, a total of 1484 individuals completed measures on fear of COVID-19, COVID-19 risk perception, and preventive behavior. A multiple linear regression analysis was used to identify factors associated with COVID-19 fear. The results revealed significant differences in the fear of COVID-19 in association with the perceived risk of COVID-19 and preventive behaviors. Age, risk perception, preventive behavior, and poor health status were significantly positively related to fear of COVID-19. Perceived risk and preventive behaviors uniquely predicted fear of COVID-19 over and above the effects of socio-demographic variables. Being female and unmarried were the significant factors associated with fear of COVID-19 among study respondents. Higher risk perception, poor health status, and being female were strong factors of increased fear of COVID-19. Targeted interventions are essential to integrate community-level mental health care for COVID-19 resilience.
Cloud Shading Retrieval and Assimilation in a Satellite-Model Coupled Mesoscale Analysis System

Abstract A retrieval-assimilation method has been developed as a quantitative means to exploit the information in satellite imagery regarding shading of the ground by clouds, as applied to mesoscale weather analysis. Cloud radiative parameters are retrieved from satellite visible image data and used, along with parameters computed by a numerical model, to control the model's computation of downward tadiative fluxes at the ground. These fluxes, in turn, influence the analysis of ground surface temperatures under clouds. The method is part of a satellite-model coupled four-dimensional analysis system that merges information from visible image data in cloudy areas with infrared sounder data in clear areas, where retrievals of surface temperatures and water vapor concentrations are assimilated. The substantial impact of shading on boundary-layer development and mesoscale circulations was demonstrated in simulations, and the value of assimilating shading retrievals was demonstrated with a case study and with a.