Miracle-dz/UniFAR-FTUs huggingface dataset:
Uncertainty Assessment of Climate Change Adaptation Options Using an Economic Pluvial Flood Risk Framework

Identifying what, when, and how much adaptation is needed to account for increased pluvial flood risk is inherently uncertain. This presents a challenge to decision makers when trying to identify robust measures. This paper presents an integrated uncertainty analysis to quantify not only the overall uncertainty of individual adaptation scenarios, but also the net uncertainty between adaptation alternatives for a direct comparison of their efficiency. Further, a sensitivity analysis is used to assess the relative contribution of inherent uncertainties in the assessment. A Danish case study shows that the uncertainties in relation to assessing the present hazards and vulnerabilities (e.g., input runoff volume, threshold for damage, and costing of floods) are important to the overall uncertainty, thus contributing substantially to the overall uncertainty in relation to decisions on action or in-action. Once a decision of action has been taken, the uncertainty of the hazards under the current climate, and also the magnitude of future climate change, are less important than other uncertainties such as discount rate and the cost of implementing the adaptation measures. The proposed methodology is an important tool for achieving an explicit uncertainty description of climate adaptation strategies and provides a guide for further efforts (e.g., field data collection) to improve decision-making in relation to climate change.
Shocks and Technology Adoption: Evidence from Electronic Payment Systems

We provide evidence on the importance of coordination frictions in technology adoption, using data from a large provider of electronic wallets during the Indian demonetization. Exploiting geographical variation in exposure to the demonetization, we show that adoption of the wallet increased persistently in response to the large but temporary cash contraction, consistent with the predictions of a technology adoption model with complementarities. Model estimates indicate that adoption would have been 45% lower without complementarities. Our results illustrate how large but temporary interventions can help overcome coordination frictions, though we caution that such interventions may also exacerbate initial differences in adoption.
Deep Fusion Feature Based Object Detection Method for High Resolution Optical Remote Sensing Images

With the rapid growth of high-resolution remote sensing image-based applications, one of the fundamental problems in managing the increasing number of remote sensing images is automatic object detection. In this paper, we present a fusion feature-based deep learning approach to detect objects in high-resolution remote sensing images. It employs fine-tuning from ImageNet as a pre-training model to address the challenge of it lacking a large amount of training datasets in remote sensing. Besides, we improve the binarized normed gradients algorithm by multiple weak feature scoring models for candidate window selection and design a deep fusion feature extraction method with the context feature and object feature. Experiments are performed on different sizes of high-resolution optical remote sensing images. The results show that our model is better than regular models, and the average detection accuracy is 8.86% higher than objNet.
Biases in International Portfolio Allocation and Investor Protection Standards

Economic reasoning suggests that financial globalization that encourages optimal international portfolio investments should improve investor protection standards (IPS) of a country. In practice, however, investors manifest varying degrees of suboptimal international portfolio allocations. Using a panel dataset covering 44 countries spanning over 15 years we examine whether suboptimal equity portfolio allocation in part is associated with the cross-country variations in IPS. Consistent with economic reasoning we find robust indications that international portfolio allocation may play an important role in the development of IPS. More specifically, the quality of IPS improves with higher degrees of optimal international equity portfolio allocation of domestic and foreign investors.
Structural Breaks in the International Transmission of Inflation

To shed light on changes in international inflation, this paper proposes an iterative procedure to discriminate between structural breaks in the coefficients and the disturbance covariance matrix of a system of equations, allowing these components to change at different dates. Conditional on these, recursive procedures are proposed to analyze the nature of change, including tests to identify individual coefficient shifts and to discriminate between volatility and correlation breaks. Using these procedures, structural breaks in monthly cross-country inflation relationships are examined for major G-7 countries (US, Euro area, UK and Canada) and within the Euro area (France, Germany and Italy). Overall, we find few dynamic spillovers between countries, although the Euro area leads inflation in North America, while Germany leads France. Contemporaneous inflation correlations are generally low in the 1970s and early 1980s, but inter-continental correlations increase from the end of the 1990s, while Euro area countries move from essentially idiosyncratic inflation to co-movement in the mid-1980s.
Evaluation of the female reproductive toxicity of aqueous extract of Labisia pumila var. alata in rats

Objective: To detect potential adverse effects of aqueous extract of Labisia pumila var. alata (LPE) or `Kacip Fatimah' on the estrous cycle, reproductive performance, post-natal growth and offspring survival of rats. Materials and Methods: Forty eight (48) female Sprague Dawley rats with consecutive 4 to 6 days estrous cycle were given distilled water (as control) or LPE at 2, 20, 200, 400 or 800 mg/kg daily by gavaging ten days prior to mating, mating (a maximum period of ten days), gestation and lactation periods of seven days. Dams and fetuses were sacrificed on day seven postnatal. Results: Labisia pumila extracts did not alter the estrous cycle and general health of all rats. All the animals proceed towards successful mating and pregnancies. There was no significant difference in the duration of pregnancy and all pregnant rats delivered normally. Statistically no test agent-related changes in the maternal body weight, number of implantations, litter size and pup body weights were observed. Other parameters measured include pup sex ratio, live birth index, pup viability index and percentage of implantation death which also showed no significant difference. Conclusion: The present findings indicate that water based extracts of Labisia pumila var. alata do not pose any significant reproductive toxicity or complication in pregnancy and delivery in rats. The extract did not significantly alter the duration of pregnancy in rats, however the duration of delivery was not evaluated in this study.
Impact of Rewards on Employee Behaviour

There are many factors that influence employee behaviour at work. In the competitive business world, organizations realize that intellectual capital is critical to business success and to keep ahead with frequent demand for change, there is need to attract, retain and engage the best minds. Behavior is widely determined by the level of perception born of value attached to the outcomes of work. It has been known that individuals adjust to their working terms and conditions aiming for fairness so as to give back as much value as they receive. Poor rewards will be reflected by negative behaviours or lack enthusiasm towards work among employees while well rewarded employees are equivalently productive, efficient and creative. Data was collected from 108 employees selected thorugh stratified random sampling and analyzed by descriptive and inferential statistics . This study established that rewards significantly affect individuals’ behaviors either positively or negatively and recommends that organizations should identify the kind of rewards that are more suitable to employees in different scenarios. The Authors view rewards as the main recipe for initiating positive change in employee attitude in favour of the organization and its goals. Managers can therefore employ this tool to develop, build and sustain desired culture entailing high performance, commitment to work and loyalty while discouraging negative behaviours such as absenteeism and lateness. Keywords: Total reward, reward system, performance, absenteeism, lateness and turnover.
A Review of Meta-Analysis Packages in R

Meta-analysis is a statistical technique that allows an analyst to synthesize effect sizes from multiple primary studies. To estimate meta-analysis models, the open-source statistical environment R is quickly becoming a popular choice. The meta-analytic community has contributed to this growth by developing numerous packages specific to meta-analysis. The purpose of this study is to locate all publicly available meta-analytic R packages. We located 63 packages via a comprehensive online search. To help elucidate these functionalities to the field, we describe each of the packages, recommend applications for researchers interested in using R for meta-analyses, provide a brief tutorial of two meta-analysis packages, and make suggestions for future meta-analytic R package creators.
Restored topography of the Po Plain‐Northern Adriatic region during the Messinian base‐level drop—Implications for the physiography and compartmentalization of the palaeo‐Mediterranean basin

The Messinian Salinity Crisis (MSC) involved the progressive isolation of the Mediterranean Sea from the Atlantic between 5.97 and 5.33 Ma, and a sea‐level fall whose timing, modalities, and magnitude remain actively debated. At that time, the central Mediterranean was undergoing strong tectonic activity due to the rollback of the Adria slab and eastward migration of the Apenninic belt. The combined effects of the post‐evaporitic MSC sea‐level drop and morphostructural changes (due to the Intra‐Messinian phase) resulted in a regional unconformity, which shows erosive markers and conformable relationships with the Messinian and Mio–Pliocene boundary in the Po Plain and Northern Adriatic Foreland. Here, we produce a palaeotopographic reconstruction of the Po Plain‐Northern Adriatic region (PPNA) during the Messinian peak desiccation event based on such regional unconformity. We mapped this surface through wells and 2D seismic data form Eni's private dataset. The unconformity shows V‐shaped incisions matching the present‐day southern Alpine valleys and filled with Messinian post‐evaporitic and Pliocene deposits, suggesting that the modern drainage network is at least of late Messinian age. The Messinian unconformity has been restored to its original state through flexural‐backstripping numerical modelling. The resulting landscape suggests a maximum sea‐level drop of 800–900 m during the MSC peak, and is consistent with stratigraphic and sedimentologic data provided by previous works. The modelled shoreline separates the subaerially eroded land from an elongated basin composed by two ca. 400 and 1,000 m deep depocentres during the maximum sea‐level drop. These results suggest that the Mediterranean was split in at least three sub‐basins subject to independent base levels, fresh‐water budgets, and flexural responses during the maximum lowstand.
Collagen I Promotes Adipocytogenesis in Adipose-Derived Stem Cells In Vitro

A hallmark of ageing is the redistribution of body fat. Particularly, subcutaneous fat decreases paralleled by a decrease of skin collagen I are typical for age-related skin atrophy. In this paper, we hypothesize that collagen I may be a relevant molecule stimulating the differentiation of adipose-derived stem cells (ASCs) into adipocytes augmenting subcutaneous fat. In this context lipogenesis, adiponectin, and collagen I receptor expression were determined. Freshly isolated ASCs were characterized by stemness-associated surface markers by FACS analysis and then transdifferentiated into adipocytes by specific medium supplements. Lipogenesis was evaluated using Nile Red staining and documented by fluorescence microscopy or quantitatively measured by using a multiwell spectrofluorometer. Expression of adiponectin was measured by real-time RT-PCR and in cell-free supernatants by ELISA, and expression of collagen I receptors was observed by western blot analysis. It was found that supports coated with collagen I promote cell adhesion and lipogenesis of ASCs. Interestingly, a reverse correlation to adiponectin expression was observed. Moreover, we found upregulation of the collagen receptor, discoidin domain-containing receptor 2; receptors of the integrin family were absent or downregulated. These findings indicate that collagen I is able to modulate lipogenesis and adiponectin expression and therefore may contribute to metabolic dysfunctions associated with ageing.
DART : A Machine-Learning Approach to Trajectory Prediction and Demand-Capacity Balancing

The current Air Traffic Management (ATM) system worldwide is managing a high (and growing) amount of demand that sometimes leads to demand-capacity balancing (DCB) issues. These further impose limitations to the ATM system that are resolved via airspace management or flow management solutions, including regulations that generate delays (and costs) for the entire system. These demand-capacity imbalances are difficult to predict in the pre-tactical phase (prior to operation), as the existing ATM information is not accurate enough during this phase. With the aim of overcoming these drawbacks, the ATM system is moving towards a new, trajectory-based operations (TBO) paradigm, where the trajectory becomes the cornerstone upon which the ATM capabilities rely on. This transformation, however, requires reliable information available in pre-tactical phase or, at least, high-fidelity aircraft trajectory prediction capabilities to reach sufficient levels of confidence in the available planning information. In this scenario, the DART (Data-driven Aircraft Trajectory Prediction Research) project from SESAR 2020 Exploratory Research aims at reaching this goal, by means of machine learning and agent-based modeling methods in two different operational use cases: trajectory prediction and demand-capacity balancing. This paper presents the machine learning approach followed, as well as the promising results already achieved by the project. KeywordsDCB; data-driven; trajectory prediction; machinelearning; collaborative reinforcement.
A Modified Semantic Feature Analysis Approach With Two Individuals With Chronic Aphasia

ABSTRACT: Purpose: The use of a modified semantic feature analysis (SFA) treatment on confrontation naming and functional communication was investigated using 2 case studies of adults with chronic subcortical aphasia. Method: Participants participated in individual treatment twice a week for 8 weeks. The modified SFA treatment used in this study included the feature of episodic memory and excluded the previously used semantic features of association and action. The other features included in the modified treatment were use, properties, category, and location. Results: Baseline measures, treatment, and 2-month follow-up data were obtained. Both participants showed improvement from baseline to the final A
the public health risks related to the consumption of raw drinking milk

Raw drinking milk (RDM) has a diverse microbial flora which can include pathogens transmissible to humans. The main microbiological hazards associated with RDM from cows, sheep and goats, horses and donkeys and camels were identified using a decision tree approach. This considered evidence of milk-borne infection and the hazard being present in the European Union (EU), the impact of the hazard on human health and whether there was evidence for RDM as an important risk factor in the EU. The main hazards were Campylobacter spp. , Salmonella spp. , shigatoxin-producing Escherichia coli (STEC), Brucella melitensis, Mycobacterium bovis and tick-borne encephalitis virus, and there are clear links between drinking raw milk and human illness associated with these hazards. A quantitative microbiological risk assessment for these hazards could not be undertaken because country and EU-wide data are limited. Antimicrobial resistance has been reported in several EU countries in some of the main bacterial hazards isolated from raw milk or associated equipment and may be significant for public health. Sale of RDM through vending machines is permitted in some EU countries, although consumers purchasing such milk are usually instructed to boil the milk before consumption, which would eliminate microbiological risks. With respect to internet sales of RDM, there is a need for microbiological, temperature and storage time data to assess the impact of this distribution route. Intrinsic contamination of RDM with pathogens can arise from animals with systemic infection as well as from localised infections such as mastitis. Extrinsic contamination can arise from faecal contamination and from the wider farm environment. It was not possible to rank control options as no single step could be identified which would significantly reduce risk relative to a baseline of expected good practice, although potential for an increase in risk was also noted. Improved risk communication to consumers is recommended. © European Food Safety Authority, 2015
DON’T FORGET THE BIOLOGY: A REPLY TO GREEN

In our 1998 paper (Eberhard et al. 1998), we tested several hypotheses regarding the possible selective factors involved in the evolution of animal genitalia. We compared the slopes of log-log ordinary least squares (OLS) regressions of genitalia on indicators of body size with the slopes of other body parts on the same indicators in 20 species of insects and spiders. Our major conclusions regarding the rejection of male-female conflict, good viability genes, and lock and key arguments (see Abstract) are unaffected by the reanalysis proposed by Green (1999), even if it were more appropriate than ours, which we doubt (see below). In neither our OLS regressions nor Green’s reduced major axis (RMA) regressions are the slopes of genitalia greater than those of other body parts, as would be expected if genitalia were used as weapons in forceful intraspecific battles (the male-female conflict hypothesis) or as signals of male size (good viability genes hypothesis). Instead, the slopes show a statistically significant trend to be lower in both analyses. In addition, neither we nor Green found differences on comparing the slopes of the genitalia of the species in which lock and key considerations might be important (species in which male genitalia fit against rigid female genitalic structures) with the slopes in species in which lock and key can be ruled out because of the mechanical mesh of the male’s genitalia with those of the female. So, conservatively, we conclude that the major conclusions of our paper are not affected under Green’s reanalysis. It is important not to lose sight of the biological questions being tested in debates over statistical methods. There are a number of reasons, however, to doubt several of Green’s points. Green’s claim that reanalysis is needed, the analysis he performed, and the additional explanations that he proposed in preference to those we mentioned in our original paper all have serious problems. We will discuss first the statistical questions, and then the more directly biological questions. Is RMA Regression More Appropriate?
Improving Energy Efficiency of Multimedia Content Dissemination by Adaptive Clustering and D 2 D Multicast

While achieving desired performance, there exist still many challenges in current cellular networks to support the multimedia content dissemination services. e conventional multimedia transmission schemes tend to serve all multicast group members with the data rate supported by the receiving user with the worst channel condition. e recent work discusses how to provide satisfactory quality of service (QoS) for all receiving users with different quality of experience (QoE) requirements, but the energy efficiency improvement of multimedia content dissemination is not its focus. In this paper, we address it based on adaptive clustering and device-to-device (D2D)multicast and propose an energy-efficient multimedia content dissemination scheme under a consistent QoE constraint. Our scheme extends the recent work with the proposed K-means-based D2D clustering method and the proposed game-based incentive mechanism, which can improve energy efficiency of multimedia content dissemination on the premise of ensuring the desired QoE for most multicast group members. In the proposed scheme, we jointly consider the cellular multicast, intracluster D2D multicast, and intercluster D2D multicast for designing the energy-efficient multimedia content dissemination scheme. In particular, we formulate the energy-efficient multicast transmission problem as a Stackelberg game model, where the macro base station (MBS) is the leader and the candidate D2D cluster heads (DCHs) are the followers. Also, the MBS acts as the buyer who buys the power from the candidate DCHs for intracluster and intercluster D2D multicast communications, and the candidate DCHs act as the sellers who earn reward by helping the MBS with D2D multicast communications. rough analyzing the above game model, we derive the Stackelberg equilibrium as the optimal allocation for cellular multicast power, intracluster D2D multicast power, and intercluster D2D multicast power, which can maximize the MBS’s utility function. Finally, the proposed scheme is verified through the simulation experiments designed in this paper.
Contribution Physical Activity and Albuminuria

Higher urinary albumin excretion predicts future cardiovascular disease, hypertension, and chronic kidney disease. Physical activity improves endothelial function so activity may reduce albuminuria. Among diabetics, physical activity decreases albuminuria. In nondiabetics, prior studies have shown no association. The authors explored the cross-sectional association between physical activity and albuminuria in 3,587 nondiabetic women in 2 US cohorts, the Nurses’ Health Study I in 2000 and the Nurses’ Health Study II in 1997. Physical activity was expressed as metabolic equivalents per week. The outcome was the top albumin/creatinine ratio (ACR) decile. Multivariate logistic regression was used. Secondary analyses explored the ACR association with strenuous activity and walking. The mean age was 58.6 years. Compared with women in the lowest physical activity quintile, those in the highest quintile had a multivariate-adjusted odds ratio for the top ACR decile of 0.65 (95% confidence interval (CI): 0.46, 0.93). The multivariate-adjusted odds ratio for the top ACR decile for those with greater than 210 minutes per week of strenuous activity compared with no strenuous activity was 0.61 (95% CI: 0.37, 0.99), and for those in the highest quintile of walking compared with the lowest quintile, it was 0.69 (95% CI: 0.47, 1.02). Greater physical activity is associated with a lower ACR in nondiabetic women.
A Printed Capacitance Sensor for Soil Moisture Measurement

The introduction and evaluation of a novel sensor design for a soil moisture sensor that can be manufactured on a PCB. The PCB acts as a capacitor, which uses the fringe effect to allow changes in permittivity of its surrounding medium to be identified, and this capacitance is measured via relatively simple charge and discharge times between two voltages through a series resistor. The system is implemented in a low-cost microcontroller, and coupled with being printable on a PCB, has the potential to make a highly cost-effective sensor. A custom Android Bluetooth application was produced to provide communication with and configuration of the sensor.