Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Impact Stress Transfer Characteristics of Lunar Rock Coring Drill

In the whole lunar surface drilling and sampling task, it is critical to make the operation of the drilling and sampling impact system efficient and reliable. This paper focuses on how to improve the impact stress obtained at the cutting edge of the drill bit. Firstly, with the objective of maximizing the output impact energy, the design parameters of the percussive mechanism are optimally selected; based on the one-dimensional stress wave transfer theory, the collision input model and transfer models of impact stress in the drilling tool are established. Secondly, in order to verify the above design parameters and theoretical models, the percussive drive characteristics’ test and the transfer characteristics’ tests of impact stress in the drill stem and drilling tool joints are carried out in turn. The experimental results are consistent with the theoretical analysis, which clarifies the transfer characteristics of the impact stress at the various stages of generation, incidence, and transfer to the cutting edge. It was finally found that increasing the percussive frequency and impact energy of the percussive mechanism as well as the contact stiffness of the collision surface can increase the incident impact stress of the drilling tool, while reducing the length of the screw connection between the drill bit and the drill stem can reduce the impact stress loss. This provides a theoretical reference for the design of the percussive mechanism and drilling tools in lunar surface drilling and sampling tasks.
Development of ideal processing parameters for powder bed fusion system processing of AlSi10Mg using design of experiments

The additive manufacturing of aluminium alloys has gained great interest in the transport industry in the past 10 years. This is mainly due to the lightweight and good strength that these alloys offer especially for applications in aerospace and other related industries. However, there is a drawback in using these alloys especially the parts produced by additive manufacturing as they have to be heat treated before application to relieve residual stresses caused by the fast heating and cooling experienced during powder bed fusion (PBF) fabrication. Most of the current PBF metal system offer a variety of processing parameters for part building, however AM uptake and industrial implementation is still slow due to restrictions of the laser power and laser interaction time that are slow and thus the parts take long to produce. Seeing this lag in the market, the CSIR has produced a high speed and high power PBF machine with a build platform larger than the currently available commercial systems. This system allows for the faster production of parts due to its higher consolidation rate and it has already been validated for aluminium alloys, specifically AlSi10Mg. The properties evaluated were microstructure and hardness, which found to be comparable to commercial PBF machines. The samples were analysed for microstructure, mechanical properties using tensile testing procedure. In order to determine that ideal processing window, the response surface methods was used on the Stat-Ease Design Expert software using ultimate tensile strength, elongation and hardness as outputs. Based on the data analysed, the processing window was narrowed to 1400 W laser power and 1.63 – 1.95 s interaction time.
A database of photon mass-energy transfer coefficients for dosimetric materials from 1 keV to 100 MeV

In this technical report, we provided a comprehensive database for mass energy-transfer coefficients and kerma rate constant in a wide range of energy photons from 1 keV to 100 MeV for human tissues and tissue equivalents. According to the authors' knowledge, the mass energy-transfer coefficients have been less investigated than total mass attenuation coefficients and mass-energy absorption coefficients; while, the mass-energy transfer coefficients are necessary to calculate the kerma and dose. Therefore, the present work focuses on calculating mass-energy transfer coefficients and kerma rate constant for photons in a wide range of energies using the Monte Carlo code (MCNP6.1) for 25 materials, which are widely used in radiation dosimetry. In this study, the obtained data have a good agreement with the previous literature. The application of the provided database is in the field of radiation dosimetry, radiation shielding and radiation therapy.
Modelling of hydrogen isotopes trapping, diffusion and permeation in divertor monoblocks under ITER-like conditions

In this work, the deuterium (D) retention in plasma facing components of the divertor of ITER is estimated. Three scenarios are simulated with 3 different surface temperatures, 1456 K, 870 K and 435 K. They represent the exposure of different parts of the divertor during an attached plasma. Our 1D rate equation code MHIMS (migration of hydrogen in materials) is used to model the retention in the super-saturated layer formed in the first 10 nm: the D retention integrated in this 10 nm-layer is ≈1019 D m−2 for the coldest scenarios. It is also used to differentiate the evolution of deuterium retention during pulsed and continuous plasma exposures which shows that: (i) there is a retention during the ramp-down in the first 10 μm which is released during the ramp up and (ii) the bulk retention is not affected by the cycling of plasma exposure. The concentration of mobile deuterium in the implantation zone is used as an input of our finite element code FESTIM (finite element simulation of tritium in materials) which is used to assess the deuterium retention and migration in the 2D complex geometry of the actively cooled plasma facing components. In the end, this work enable to determine the three following macroscopic quantities: the total deuterium retention, the permeation flux to the cooling pipe and the desorption flux from the toroidal edges of the components. It is shown that (i) the coldest scenario leads to the highest retention despite the lowest exposure flux which has already been observed in past retention studies, (ii) the permeation to the cooling pipes happens after few thousands of seconds only for the hottest scenario, (iii) the release of deuterium from the toroidal edges is a small fuel recycling source.
Towards the introduction of elements that contribute to the LRT operation sustainability through technology-based ancillary revenue

Transportation and technology innovation is one of the Sustainable Development Goals (SDGs) elements, and it has been outlined in goal number nine. The high demand for LRT usage requires a large amount of electricity. It contributes to the increase in electricity costs that have to be borne by LRT operators, and it is one of the main contributors to the increase in LRT operating costs. Revenue from fares unable to offset the rising operating cost. Therefore, LRT operators need to explore ancillary revenue activities to cover LRT operating costs. This paper aims to identify the elements involved in generating ancillary income through technology-based businesses from fibre optic cable networks along LRT alignment for the LRT operation sustainability. This study adopted semi-structured interviews for data collection and thematic analysis to analyse the data collected to identify the elements involved in generating ancillary revenue. Eleven themes were identified from the thematic analysis using NVivo. The list of elements involved has been proposed in this study has the potential to be a driver in generating ancillary revenue for the sustainability of LRT operations and contribute to sustainable development in achieving one of the objectives outlined in the SDGs.
Should long-term climate change adaptation be focused on smallholders?

Smallholder agriculture employs the majority of the global poor and produces substantial shares of food in developing countries while also being highly vulnerable to environmental change. This makes it a focus of numerous policies for increased productivity and climate change adaptation. Given demographic and economic processes that are likely to reduce smallholder prevalence, how justified is this focus from a long-term perspective? We estimate future global smallholder distributions using historical trends and demographic projections and calculate indices of its future share of climate change impacts. While past trends of decreasing farm size are likely to reverse in Asia and slow down in Africa, we project smallholders will continue to occupy substantial shares of rural populations and cultivated land and bear a sizable portion of climate change impacts, amounting for about 33% (25%) of an index of human exposure to 1 °C (2 °C) warming. However, increased economic possibilities in rural areas can rapidly attenuate these assessments.
High SARS-CoV-2 Seroprevalence in Rural Peru, 2021: a Cross-Sectional Population-Based Study

Latin America is a global hot spot of the COVID-19 pandemic. Serological studies in Latin America have been mostly performed in urban settings. ABSTRACT Latin America has been severely affected by the COVID-19 pandemic. The COVID-19 burden in rural settings in Latin America is unclear. We performed a cross-sectional, population-based, random-selection SARS-CoV-2 serologic study during March 2021 in the rural population of San Martin region, northern Peru. In total, 563 persons from 288 houses across 10 provinces were enrolled, reaching 0.2% of the total rural population of San Martin. Screening for SARS-CoV-2 IgG antibodies was done using a chemiluminescence immunoassay (CLIA), and reactive sera were confirmed using a SARS-CoV-2 surrogate virus neutralization test (sVNT). Validation of the testing algorithm using prepandemic sera from two regions of Peru showed false-positive results in the CLIA (23/84 sera; 27%) but not in the sVNT, highlighting the pitfalls of SARS-CoV-2 antibody testing in tropical regions and the high specificity of the two-step algorithm used in this study. An overall 59.0% seroprevalence (95% confidence interval [CI], 55 to 63%) corroborated intense SARS-CoV-2 spread in San Martin. Seroprevalence rates between the 10 provinces varied from 41.3 to 74.0% (95% CI, 30 to 84%). Higher seroprevalence was not associated with population size, population density, surface area, mean altitude, or poverty index in Spearman correlations. Seroprevalence and reported incidence diverged substantially between provinces, suggesting regional biases of COVID-19 surveillance data. Potentially, limited health care access due to environmental, economic, and cultural factors might lead to undetected infections in rural populations. Additionally, test avoidance to evade mandatory quarantine might affect rural regions more than urban regions. Serologic diagnostics should be pursued in resource-limited settings to inform country-level surveillance and vaccination strategies and to support control measures for COVID-19. IMPORTANCE Latin America is a global hot spot of the COVID-19 pandemic. Serologic studies in Latin America have been mostly performed in urban settings. Rural populations comprise 20% of the total Latin American population. Nevertheless, information on COVID-19 spread in rural settings is scarce. Using a representative population-based seroprevalence study, we detected a high seroprevalence in rural populations in San Martin, northern Peru, in 2021, reaching 41 to 74%. However, seroprevalence and reported incidence diverged substantially between regions, potentially due to limited health care access or test avoidance due to mandatory quarantine. Our results suggest that rural populations are highly affected by SARS-CoV-2 even though they are sociodemographically distinct from urban populations and that highly specific serological diagnostics should be performed in resource-limited settings to support public health strategies of COVID-19 control.
Probability of Winning in Risky Choices

Media reports say that high earners and syndicates buy lottery tickets in bulk. Experimental evidence shows that agents aggressively bid in auctions and contests. Do people try to trade-off the probability of winning with other basic risk dimensions (for example, cost) to achieve a subjective threshold probability of winning (in environments they can) even when such choices are second-order stochastic dominated? The literature on risky choices suggests so. In the main design of this experiment, we deconstruct the expected value with variance and skewness of a lottery with Bernoulli distribution to examine the decision-making process. Based on the results, a proportion is classified as expected utility maximizer (EUM) while another proportion seems to achieve a subjective threshold probability of winning (termed as target probability of winning (TPW)). More TPWs prefer higher probabilities compared to EUMs in a constant value lottery set which may explain the preference for negative skewness in experiments. Additionally, we test two contest designs and find TPWs in the population which may explain the puzzle of equilibrium effort more than risk-neutral Nash equilibrium in experiments.
Does Economic Policy Uncertainty Reduce Financial Inclusion?

This study investigates whether the level of economic policy uncertainty (EPU) would reduce the level of financial inclusion. It was predicted that a high level of EPU could have a negative effect on the level of financial inclusion. It was argued that a high level of EPU would discourage financial institutions from providing basic financial services to low end customers and unbanked adults, and this would lead to a decrease in the level of financial inclusion. Using a sample of 22 countries, the study found that the level of EPU did not have a significant impact on financial inclusion. None of the nine indicators of financial inclusion were found to have a significant direct relationship with EPU. However, there was some evidence that the combined effect of a high level of EPU and high nonperforming loans could reduce financial inclusion, particularly through bank branch contraction and a reduction in the use of electronic payments. Furthermore, the use of formal accounts and credit cards would increase in times of high credit supply and when there was a high level of EPU.
DNA Methylation Level Changes in Transgenic Chinese Cabbage (Brassica rapa ssp. pekinensis) Plants and Their Effects on Corresponding Gene Expression Patterns

Plant tissue culture is an in vitro technique used to manipulate cells, tissues, or organs, and plays an important role in genetic transformation. However, plants cultured in vitro often exhibit unintended genetic and epigenetic variations. Since it is important to secure the stability of endogenous and exogenous gene expressions in transgenic plants, it is preferable to avoid the occurrence of such variations. In this study, we focused on epigenetic variations, exclusively on methylation level changes of DNA, in transgenic Chinese cabbage (Brassica rapa ssp. pekinensis) plants. To detect these methylation level changes of DNA, bisulfite sequencing was performed and the obtained sequences were compared with the ‘CT001’ reference genome. Differentially methylated regions (DMRs) of DNA between the non-transgenic and transgenic lines were detected by bisulfite sequencing, and ten DMRs located in exonic regions were identified. The regions with methylation variations that were inherited and consistently maintained in the next generation lines were selected and validated. We also analyzed the relationship between methylation status and expression levels of transformant-conserved DMR (TCD) genes by quantitative reverse transcription-PCR. These results suggested that the changes in methylation levels of these DMRs might have been related to the plant transformation process, affecting subsequent gene expression. Our findings can be used in fundamental research on methylation variations in transgenic plants and suggest that these variations affect the expression of the associated genes.
Elephant Endotheliotropic Herpesvirus Impact in the European Asian Elephant (Elephas maximus) Population: Are Hereditability and Zoo-Associated Factors Linked with Mortality?

Simple Summary Elephant Endotheliotropic Herpesvirus hemorrhagic disease (EEHV-HD) is considered the primary cause of calf mortality in the global captive Asian elephant population. Once thought to be exclusively a zoo problem, EEHV-HD is currently acknowledged as a disease also present in wild populations, although the extension of this threat in some free-range countries is still poorly understood. The disease is characterized by an acute hemorrhagic syndrome due to vast endothelial destruction combined with disseminated intravascular coagulation, leading to the sudden death of mainly young elephants. In this study, we aimed at understanding the impact of EEHV-HD in the European captive Asian elephant population and acquiring a better understanding if hereditary or environmental factors could be linked to the manifestation of this disease. The findings of this investigation suggest the involvement of zoo-associated factors with possible sire or dam (or a combination of both) influence on the onset of the disease. This knowledge points us to the importance of continuous retrospective epidemiological studies and stresses the great importance of finding further underlying factors for the development of this disease if we wish to halt the high number of deaths caused by this hemorrhagic disease. Abstract EEHV is a ubiquitous virus, which most likely has co-evolved with elephants and is shed by healthy individuals and maintained in the herds. Yet, the factors determining calf susceptibility to the virus remain unknown. Here, we explored the impact of EEHV-HD in the European captive Asian elephant population in a retrospective statistical study spanning the last 35 years. We show that EEHV-HD was implicated in more than half of all deaths recorded in calves older than one months old. Moreover, the median age across EEHV-HD fatalities was significantly lower compared to other death causes. Finally, we investigated if heredity and zoo-associated factors could be linked to a higher susceptibility of calves to this disease. We used a univariable logistic regression model to evaluate if either fathers, mothers, or zoos could, separately, be considered as risk factors to the development of the disease. Afterwards, we used a two multivariable model, combining: (1) fathers and zoos, and (2) mothers and zoos. Overall, we found that two fathers, one mother, and four zoos had three or more times higher risk of their calves becoming sick when compared to all others, pointing us to the presence of a management or environmental element, which can have paternal and maternal influence and leads to calf susceptibility or resistance to EEHV-HD.
An Insider Data Leakage Detection Using One-Hot Encoding, Synthetic Minority Oversampling and Machine Learning Techniques

Insider threats are malicious acts that can be carried out by an authorized employee within an organization. Insider threats represent a major cybersecurity challenge for private and public organizations, as an insider attack can cause extensive damage to organization assets much more than external attacks. Most existing approaches in the field of insider threat focused on detecting general insider attack scenarios. However, insider attacks can be carried out in different ways, and the most dangerous one is a data leakage attack that can be executed by a malicious insider before his/her leaving an organization. This paper proposes a machine learning-based model for detecting such serious insider threat incidents. The proposed model addresses the possible bias of detection results that can occur due to an inappropriate encoding process by employing the feature scaling and one-hot encoding techniques. Furthermore, the imbalance issue of the utilized dataset is also addressed utilizing the synthetic minority oversampling technique (SMOTE). Well known machine learning algorithms are employed to detect the most accurate classifier that can detect data leakage events executed by malicious insiders during the sensitive period before they leave an organization. We provide a proof of concept for our model by applying it on CMU-CERT Insider Threat Dataset and comparing its performance with the ground truth. The experimental results show that our model detects insider data leakage events with an AUC-ROC value of 0.99, outperforming the existing approaches that are validated on the same dataset. The proposed model provides effective methods to address possible bias and class imbalance issues for the aim of devising an effective insider data leakage detection system.
Targeting Drug Chemo-Resistance in Cancer Using Natural Products

Cancer is one of the leading causes of death globally. The development of drug resistance is the main contributor to cancer-related mortality. Cancer cells exploit multiple mechanisms to reduce the therapeutic effects of anticancer drugs, thereby causing chemotherapy failure. Natural products are accessible, inexpensive, and less toxic sources of chemotherapeutic agents. Additionally, they have multiple mechanisms of action to inhibit various targets involved in the development of drug resistance. In this review, we have summarized the basic research and clinical applications of natural products as possible inhibitors for drug resistance in cancer. The molecular targets and the mechanisms of action of each natural product are also explained. Diverse drug resistance biomarkers were sensitive to natural products. P-glycoprotein and breast cancer resistance protein can be targeted by a large number of natural products. On the other hand, protein kinase C and topoisomerases were less sensitive to most of the studied natural products. The studies discussed in this review will provide a solid ground for scientists to explore the possible use of natural products in combination anticancer therapies to overcome drug resistance by targeting multiple drug resistance mechanisms.
The Usability of an Online Tool to Promote the Use of Evidence-Based Smoking Cessation Interventions

To increase usage of evidence-based smoking cessation interventions (EBSCIs) among smokers, an online decision aid (DA) was developed. The aims of this study were (1) to conduct a usability evaluation; (2) to conduct a program evaluation and evaluate decisional conflict after using the DA and (3) to determine the possible change in the intention to use EBSCIs before and directly after reviewing the DA. A cross-sectional study was carried out in September 2020 by recruiting smokers via the Internet (n = 497). Chi-squared tests and t-tests were conducted to test the differences between smokers who differed in the perceived usability of the DA on the program evaluation and in decisional conflict. The possible changes in intention to use EBSCIs during a cessation attempt before and after reviewing the DA were tested using t-tests, McNemar’s test and χ2 analysis. The participants evaluated the usability of the DA as moderate (MU; n = 393, 79.1%) or good (GU; n = 104, 20.9%). GU smokers rated higher on all the elements of the program evaluation and experienced less decisional conflict, but also displayed a higher intention to quit. After reviewing the DA, the participants on average had a significantly higher intention to use more EBSCIs, in particular in the form of eHealth. Recommendations to make the DA more usable could include tailoring, using video-based information and including value clarification methods. Furthermore, a hybrid variant in which smokers can use the DA independently and with the guidance of a primary care professional could aid both groups in choosing a fitting EBSCI option.