Miracle-dz/UniFAR-FTUs huggingface dataset:
Does infrastructure development matter for the shadow economy in African countries?

ABSTRACT Understanding the determinants of the informal economy is a crucial issue in economic development due to its far-reaching effects on development efforts. Previous studies focused exclusively on factors that can potentially reduce the relative size of the shadow economy. However, these attempts have not enjoyed much success to date in Africa, where informality has continued to thrive. We contend that realistic medium-term goals, as opposed to obligatory formalisation, could increase the output of informal businesses by providing enough infrastructure and a welcoming business climate, which would at the same time foster formalisation. Using OLS, FE and system GMM with data on 42 African countries covering 2003–2018, we find that infrastructure development reduces the relative size of the shadow economy in African countries. Our results remained consistent when we controlled for the effects of other determinants of the informal economy, employed other estimators, and used an alternative measure of the informal economy.
Comparison of Nonparametric Estimators for the Renewal Function

This paper addresses the problem of nonparametric estimation of the renewal function. Two estimators are discussed. The first estimator, introduced by Frees, is based on the sum of the convolutions without replacement of the empirical distribution function. We suggest a polynomial time algorithm to compute this estimator. The second estimator is based on the renewal function of the empirical distribution. We show how this estimator may be computed efficiently by solving a discretized renewal equation. In a simulation study the estimations are compared with respect to bias, mean-squared error and computing time
O pewnych formalnych założeniach semantycznych niektórych sformalizowanych argumentów ontologicznych

The paper considers some formal limitations in ways of interpretations of certain formalizations of K. Godel's ontological argument on the existence of the absolute. Submitted formalizations are theories based on the second order modal calculus of predicates S5. The aim of the analysis (done in the framework of semantics of possible worlds) is to point out certain formal properties of semantic structures which can be used as interpretations of chosen formalizations - the properties which are forced by structure of given language itself and by a formal base. In the paper, various interpretations of some notions involved in ontological arguments, admissible from formal point of view, such as necessity, existence, perfection are also described.
A Robust Immersed Boundary-Lattice Boltzmann Method for Simulation of Fluid-Structure Interaction Problems

A robust immersed boundary-lattice Boltzmann method (IB-LBM) is proposed to simulate fluid-structure interaction (FSI) problems in this work. Compared with the conventional IB-LBM, the current method employs the fractional step technique to solve the lattice Boltzmann equation (LBE) with a forcing term. Consequently, the non-physical oscillation of body force calculation, which is frequently encountered in the traditional IB-LBM, is suppressed greatly. It is of importance for the simulation of FSI problems. In the meanwhile, the no-slip boundary condition is strictly satisfied by using the velocity correction scheme. Moreover, based on the relationship between the velocity correction and forcing term, the boundary force can be calculated accurately and easily. A few test cases are first performed to validate the current method. Subsequently, a series of FSI problems, including the vortex-induced vibration of a circular cylinder, an elastic filament flapping in the wake of a fixed cylinder and sedimentation of particles, are simulated. Based on the good agreement between the current results and those in the literature, it is demonstrated that the proposed IB-LBM has the capability to handle various FSI problems effectively.
A Novel Aging-Related Prognostic lncRNA Signature Correlated with Immune Cell Infiltration and Response to Immunotherapy in Breast Cancer

Breast cancer (BC) is among the most universal malignant tumors in women worldwide. Aging is a complex phenomenon, caused by a variety of factors, that plays a significant role in tumor development. Consequently, it is crucial to screen for prognostic aging-related long non-coding RNAs (lncRNAs) in BC. The BC samples from the breast-invasive carcinoma cohort were downloaded from The Cancer Genome Atlas (TCGA) database. The differential expression of aging-related lncRNAs (DEarlncRNAs) was screened by Pearson correlation analysis. Univariate Cox regression, LASSO–Cox analysis, and multivariate Cox analysis were performed to construct an aging-related lncRNA signature. The signature was validated in the GSE20685 dataset from the Gene Expression Omnibus (GEO) database. Subsequently, a nomogram was constructed to predict survival in BC patients. The accuracy of prediction performance was assessed through the time-dependent receiver operating characteristic (ROC) curves, Kaplan–Meier analysis, principal component analyses, decision curve analysis, calibration curve, and concordance index. Finally, differences in tumor mutational burden, tumor-infiltrating immune cells, and patients’ response to chemotherapy and immunotherapy between the high- and low-risk score groups were explored. Analysis of the TCGA cohort revealed a six aging-related lncRNA signature consisting of MCF2L-AS1, USP30-AS1, OTUD6B-AS1, MAPT-AS1, PRR34-AS1, and DLGAP1-AS1. The time-dependent ROC curve proved the optimal predictability for prognosis in BC patients with areas under curves (AUCs) of 0.753, 0.772, and 0.722 in 1, 3, and 5 years, respectively. Patients in the low-risk group had better overall survival and significantly lower total tumor mutational burden. Meanwhile, the high-risk group had a lower proportion of tumor-killing immune cells. The low-risk group could benefit more from immunotherapy and some chemotherapeutics than the high-risk group. The aging-related lncRNA signature can provide new perspectives and methods for early BC diagnosis and therapeutic targets, especially tumor immunotherapy.
Experimental Study on Low-Cost Satellite-Based Geodetic Monitoring over Short Baselines

AbstractThe use of geodetic techniques, in particular of the global positioning system (GPS), or other global navigation satellite systems (GNSS), for monitoring different kinds of deformations is a common practice. This is typically performed by setting a network of geodetic GPS/GNSS receivers, allowing accuracies in the order of millimeters. The use of lower-cost devices has been recently studied, showing that good results can be achieved. In this paper, the impact of the software used for the data analysis is also investigated to verify whether a fully low-cost monitoring system, i.e., both hardware and software, can be set up. This is done by performing a series of relative positioning experiments in which data are processed by different software packages. The main result is that by using a low-cost u-blox EVK-6T GPS receiver and analyzing its data with free and open-source software, movements of the order of a few millimeters can be detected when a short baseline with daily solutions is used.
Microbiological Screening of the Environments of Two Hospitals in Nablus

Both blood agar and MacConkey plates were used for the isolation of bacteria from the environments of two hospitals in Nablus. Pseudomonas aeruginosa, Escherichia coli and Staphylococci were isolated from saline solution kept in glass bottles for washing and cleansing wounds, suction machines, respirators, endotracheal tubings, oxygen pumps and sinks. Alcaligenes odorans was isolated from the suction machines and Dettol solution. Aeromonas species were isolated from deionized water and sinks, the implications of these findings were also discussed.
An Intelligent Intrusion Detection System for 5G-Enabled Internet of Vehicles

The deployment of 5G technology has drawn attention to different computer-based scenarios. It is useful in the context of Smart Cities, the Internet of Things (IoT), and Edge Computing, among other systems. With the high number of connected vehicles, providing network security solutions for the Internet of Vehicles (IoV) is not a trivial process due to its decentralized management structure and heterogeneous characteristics (e.g., connection time, and high-frequency changes in network topology due to high mobility, among others). Machine learning (ML) algorithms have the potential to extract patterns to cover security requirements better and to detect/classify malicious behavior in a network. Based on this, in this work we propose an Intrusion Detection System (IDS) for detecting Flooding attacks in vehicular scenarios. We also simulate 5G-enabled vehicular scenarios using the Network Simulator 3 (NS-3). We generate four datasets considering different numbers of nodes, attackers, and mobility patterns extracted from Simulation of Urban MObility (SUMO). Furthermore, our conducted tests show that the proposed IDS achieved F1 scores of 1.00 and 0.98 using decision trees and random forests, respectively. This means that it was able to properly classify the Flooding attack in the 5G vehicular environment considered.
Asymptotic behavior of spacing distributions for the eigenvalues of random matrices

It is known that the probability Eβ(0, S) that an arbitrary interval of length S contains none of the eigenvalues of a random matrix chosen from the orthogonal (β = 1), unitary (β = 2) or symplectic (β = 4) ensemble can be expressed in terms if infinite products ∏n=0∞[1−λ2n(S)] and ∏n=0∞[1=λ2n+1(S)], where λn(S) is an eigenvalue of a certain integral equation. Using values of λn(S), valid for S large, obtained in connection with a recent study of spheroidal functions, we derive asymptotic expressions (S ≫ 1) for Eβ(0, S).
Sampling of the Diurnal Cycle of Precipitation Using TRMM

Abstract The temporal sampling of tropical regions is examined using observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR). It is concluded that PR estimates at any one hour, even using three years of data, are inadequate to describe the diurnal cycle of precipitation over regions smaller than 12°, due to high spatial variability in sampling. It is shown that the optimum period of accumulation is 4 h. Diurnal signatures display half as much sampling error when averaged over 4 h of local time. A similar pattern of sampling variability is found in the TMI data, despite the TMI's wider swath and increased sampling. These results are verified using an orbital model. The sensitivity of the sampling to satellite altitude is presented, as well as sampling patterns at the new TRMM altitude of 402.5 km.
The relationship between profitability and capital buffer in the Indonesian banking sector

This study examines profitability as a mediating variable to explore variables that affect the capital buffer in commercial banks. The research population is conventional commercial banks operating in Indonesia, with an observation period of 2017–2020. A purposive sampling method was used, during which 90 observations were found. Data analysis used multiple regression and the Sobel test to test for the mediating role of profitability. The results show that profitability acts as a mediating variable for non-performing loans and the ratio of loans to deposits in the capital buffer. Therefore, it is suggested that banks must maintain their ability to generate profitability in order to avoid liquidity risk. Another finding that is also important for bank managers is that non-performing loans have a significant effect on reducing profitability, while loans to total assets have a positive impact. Loan-to-deposit ratio and income diversification are not significant to profitability. Profitability, debt-to-total assets ratio, and income diversification have a negative impact on the capital buffer. Non-performing loans are not significant, while the loan-to-deposit ratio has a significant positive impact on the capital buffer.
Cannabis, research ethics, and a duty of care

Despite growing evidence to the contrary, researchers continue to posit causal links between cannabis, crime, psychosis, and violence. These spurious connections are rooted in history and fueled decades of structural limitations that shaped how researchers studied cannabis. Until recently, research in this area was explicitly funded to link cannabis use and harm and ignore any potential benefits. Post-prohibition cannabis research has failed to replicate the dire findings of the past. This article outlines how the history of controlling cannabis research has led to various harms, injustices, and ethical complications. We compare commonly cited research from both the prohibition and post-prohibition eras and argue that many popular claims about the dangers of cannabis are the result of ethical lapses by researchers, journals, and funders. We propose researchers in this area adopt a duty of care in cannabis research going forward. This would oblige individual researchers to establish robust research designs, employ careful analytic strategies, and acknowledge limitations in more detail. This duty involves the institutional recognition by funders, journals, and others that cannabis research has been deliberately misconstrued to criminalize, stigmatize, and pathologize.
Analyse of mean wind load of lattice tower based on CFD simulation

In order to ascertain the influence of solidity,wind direction,the rate of length and width and taper,CFD simulations of angled lattice tower under wind load were carried out in different cases.Simulation results were compared with codes and tests.The results show that the expression of drag coefficients of 0° wind angle is a quadratic polynomial of solidities.The rate of drag coefficients of other wind direction and the one of 0° wind angle is a quadratic polynomial of wind angle.The maximum point is about 30°. There are significant differences between codes and tests.The drag coefficients in Chinese BG 50009 "Load Code for the Design of Building Structures" is the lowest limit,while the drag coefficients in Japanese "AIJ Recommendations for Loads on Buildings" is the highest limit,the maximum error between them is 46.2%. The modified CFD results according to uniform wind velocity are close to those in Japanese "AIJ Recommendations for Loads on Buildings". The shielding effect is relatively minor when solidities are small and the shielding effect increases with the increase of solidities.With the increase of taper,drag coefficients increase.For towers with tapers in common use,the influence is little.
Optimization for Bursting Neural Models

This thesis concerns parameter estimation for bursting neural models. Parameter estimation for differential equations is a difficult task due to complicated objective function landscapes and numerical challenges. These difficulties are particularly salient in bursting models and other multiple time scale systems. Here we make use of the geometry underlying bursting by introducing defining equations for burst initiation and termination. Fitting the timing of these burst events simplifies objective function landscapes considerably. We combine this with automatic differentiation to accurately compute gradients for these burst events, and implement these features using standard unconstrained optimization algorithms. We use trajectories from a minimal spiking model and the Hindmarsh-Rose equations as test problems, and bursting respiratory neurons in the preBotzinger complex as an application. These geometrical ideas and numerical improvements significantly enhance algorithm performance. Excellent fits are obtained to the preBotzinger data both in control conditions and when the neuromodulator norepinephrine is added. The results suggest different possible neuromodulatory mechanisms, and help analyze the roles of different currents in shaping burst duration and period. iii To my family iv ACKNOWLEDGEMENTS I am very grateful to my advisor, John Guckenheimer, for consistent guidance and support throughout. Thanks also to Ron Harris-Warrick and Lars Wahlbin for serving on my committee. My path through graduate school has been a wandering one. Several individuals took a chance and gave me the opportunity to study applied math. John Guck-enheimer and Steve Strogatz encouraged me to explore my interests and apply to CAM. Carlos Castillo-Chavez allowed a curious ecology and evolutionary biology graduate student to attend his computational biology training grant meetings. To them I am deeply thankful. I had the good fortune to work with Mary Lou Zeeman through the IGERT program. The National Science Foundation provided funding for several years of my graduate studies. Thanks to Dolores Pendell, without whom CAM would swiftly crumble. CAM has been home for these past years – may it always keep its good cheer. Thanks most of all to my parents and brother for their love through the years.
Studies in Resource Allocation Processes: Appendix: An optimality criterion for decision-making under ignorance

Introduction It is intended here to offer a possible characterization of the concept of complete ignorance. Like other formulations, the problem is taken to be that of choice of an action from a given set when the consequences of any action are functions of an unknown state of nature. However, the properties regarded as defining an optimal choice are designed to reflect completely the idea that there is no a priori information available which gives any state of nature a distinguished position. Most importantly, the optimality criterion differs from those in the now more standard subjective probability framework by not presupposing a fixed list of states of nature. As we note shortly, the arguments and conclusions are much closer to Shackle's than to those of Ramsey, de Finetti, and Savage. The axiom systems of these last authors imply the existence of subjective probabilities as weights to be assigned to the different possible states of nature. These authors thus provide a foundation for the centuries-old use of probability as a guide to action. The concept of complete ignorance can be expressed in this subjective probability framework only by the assignment of equal probabilities to all the states of nature, which is the principle of indifference or insufficient reason implicit in the earliest combinatorial probability calculations of Pascal and Fermat and explicit in Jacob Bernoulli, Bayes, and Laplace.
Drug Combination Therapy for Malaria using Deep Learning

Drug Combination has been effective for treating complex disorders like cancer and infectious diseases. Malaria remains a major global health challenge, with millions of cases and hundreds of thousands of deaths reported annually. While several drugs are available for malaria treatment, drug resistance has emerged as a significant problem. Combination therapy is now recommended as the first-line treatment for malaria. Due to the impossibility and high cost of considering every possible drug combination, it is necessary to put a lot of work into screening new drug combinations. Recently, deep learning techniques have shown promising results in discovering synergistic combinations. We present synergistic drug combinations for malaria and compare and analyze various models that predict effective drug combinations using deep learning techniques
P53 and survivin expression in renal cell carcinoma

Objective: Mutation of p53 is detected in more than 50% of human cancers, expression of p53 has a potential prognostic value in patients with renal cell carcinoma (RCC). Survivin is a member of the inhibitor of apoptosis protein family, its overexpression is observed in many malignancies, including RCC. The aim of the study was to estimate a correlation between survivin and p53 expression in tumor samples and the histologic type of a tumor, tumor stage, tumor grade, and survival of patients. Materials and Methods: Tumor samples were collected from surgical specimens of 90 patients who underwent radical or partial nephrectomy for RCC between November 2017 and July 2020. Tumors were staged according to the UICC (The Union for International Cancer Control) TNM classification system and histopathologically graded according to Fuhrman nuclear grade system. Histopathological diagnosis was confirmed with standard light microscopic evaluation, using hematoxylin and eosin staining and standard p53 and survivin antibodies. Results: Positive p53 staining was observed in 36.7% of tumor specimens and 24.4% were survivin positive. There was a statistically significant correlation between p53 or survivin expression and histologic subtype of clear cell RCC as well as Type I and II of papillary RCC. There was a statistically significant correlation between p53 expression and tumor size, stage, and grade. The p53 or survivin expression was related to lower overall survival. Conclusion: The results of this study suggest that p53 overexpression and survivin positivity in RCC patients could be associated with poor prognosis. Thus, these proteins could be used as prognostic markers in RCC.
Obesity Is Associated with Distorted Proteoglycan Expression in Adipose Tissue

Proteoglycans are central components of the extracellular matrix (ECM) and binding partners for inflammatory chemokines. Morphological differences in the ECM and increased inflammation are prominent features of the white adipose tissues in patients with obesity. The impact of obesity and weight loss on the expression of specific proteoglycans in adipose tissue is not well known. This study aimed to investigate the relationship between adiposity and proteoglycan expression. We analyzed transcriptomic data from two human bariatric surgery cohorts. In addition, RT-qPCR was performed on adipose tissues from female and male mice fed a high-fat diet. Both visceral and subcutaneous adipose tissue depots were analyzed. Adipose mRNA expression of specific proteoglycans, proteoglycan biosynthetic enzymes, proteoglycan partner molecules, and other ECM-related proteins were altered in both human cohorts. We consistently observed more profound alterations in gene expression of ECM targets in the visceral adipose tissues after surgery (among others VCAN (p = 0.000309), OGN (p = 0.000976), GPC4 (p = 0.00525), COL1A1 (p = 0.00221)). Further, gene analyses in mice revealed sex differences in these two tissue compartments in obese mice. We suggest that adipose tissue repair is still in progress long after surgery, which may reflect challenges in remodeling increased adipose tissues. This study can provide the basis for more mechanistic studies on the role of proteoglycans in adipose tissues in obesity.