Miracle-dz/UniFAR-FTUs huggingface dataset:
Solvency Determinants of Conventional Life Insurers and Takaful Operators

The business of insurance is based on the trust of its policyholders, who expect that their losses will be compensated should the need arise at any time. Thus, sound financial conditions constitute the most important criterion for insurance firms, as well as for takaful operators. Although the policyholder may be the most important source of insurer finance, or a debt holder from an economic point of view through premium payments, the policyholder is not well informed in assessing the financial strength or solvency of the life insurer. Various measures of the solvency of the insurer are used in the industry, such as margin of solvency (MOS), risk based capital (RBC), and claim paying ability (CPA) rating. Unfortunately, none of these can provide information to policyholders on the financial position of the insurer. This is because the MOS and RBC for each insurer is the company's and regulator’s confidential information. However, for the CPA rating, it is limited to insurers who wish to be evaluated, and therefore the assessment is not comprehensive. Because of these shortcomings, this study provides a platform for policyholders to get an idea of the solvency of the insurers/takaful operators. Furthermore, this study identifies factors that affect the solvency of the insurers/takaful operators in Malaysia. Using random effects regression on panel data for 2003-2007, it is determined that investment income, total benefit paid to capital and surplus ratio, financial leverage, and liquidity are significantly related to solvency, in which the investment income has a positive relationship, while the other three have a negative relationship. From the results obtained, the policyholders/consumers can assess the insurers’ financial strength through the solvency determinants of the insurers/takaful operators, even though the actual level of solvency is not known. To some extent, this information can help policyholders/consumers make smarter choices in choosing the insurers/takaful operators
Challenges Faced by Dialysis Unit Staff During COVID-19 Times: A Qualitative Study

Background: The Coronavirus has caused an epidemic affecting the whole world for the last two years and has been spreading steadily. The hemodialysis patients are at high risk because of their lowered immunity status. The dialysis staff is also at higher risk of contracting COVID-19 as these patients come for twice/thrice weekly treatment sessions. Objectives: This study was done to study the hardships and problems afflicting the dialysis staff during the infections caused by COVID-19 in a rural hemodialysis unit. Methods: This study setting was the hemodialysis unit located in a rural hospital in Pondicherry, India. Free listing and pile sorting were done to study the structure and salient problems as felt in the cognitive domain by the dialysis team. Smith's S value was calculated for a free listing. Multidimensional scaling and cluster analysis were conducted to do pile sorting of data. Data were analyzed using Anthropac 4.983/X. Group interviews were carried out to get in-depth information and validate the findings obtained from the free list and pile sorting exercise. Results: Twelve salient items were obtained from the free list. Three broad domains emerged: the absence of personal safety, shortage of personal safety equipment, and presence of logistical and operational problems. Surprisingly, RT-PCR testing was not perceived to be of importance for them. Conclusions: Accepting the true feelings, fears, and needs of the dialysis staff, helping to tackle the impediments to personal safety, and the lack of personal safety equipment in a dialysis unit during COVID-19 outbreak are vital in ensuring personal safety and improving working dynamics.
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BACKGROUND Focus is shifting to better understand the lived experiences of children with intellectual disability in relation to their quality of life (QOL). Yet no available QOL measures are grounded in the domains important for this population. We previously conducted qualitative parent caregiver interviews identifying QOL domains in children with intellectual disability to constitute a new measure of QOL. This study describes the content validity of the Quality of Life Inventory – Disability (QI-Disability), a parent-report measure developed for children with intellectual disability
Defenses to Membership Inference Attacks: A Survey

Machine learning (ML) has gained widespread adoption in a variety of fields, including computer vision and natural language processing. However, ML models are vulnerable to membership inference attacks (MIAs), which can infer whether access data was used in training a target model, thus compromising the privacy of training data. This has led researchers to focus on protecting the privacy of ML. To date, although there have been extensive efforts to defend against MIAs, we still lack a comprehensive understanding of the progress made in this area, which can often impede our ability to design the most effective defense strategies. In this article, we aim to fill this critical knowledge gap by providing a systematic analysis of membership inference defense. Specifically, we classify and summarize the existing membership inference defense schemes, focusing on optimization phase and objective, basic intuition, and key technology, and we discuss possible research directions of membership inference defense in the future.
Confronting Race: Women and Indians on the Frontier, 1815-1915

In 1984, when Glenda Riley's 'Women and Indians on the Frontier' was published, it was hailed for being the first study to take into account the roles that gender, race, and class played in Indian/white relations during the westward migration. In the twenty years since, the study of those aspects of western history has exploded. "Confronting Race" reflects the changes in western women's history and in the author's own approach. In spite of white women's shifting attitudes toward Indians, they retained colonialist outlooks toward all peoples. Women who migrated West carried deeply ingrained images and preconceptions of themselves and racially based ideas of the non-white groups they would meet. In their letters home and in their personal diaries and journals, they perpetuated racial stereotypes, institutions, and practices. The women also discovered their own resilience in the face of the harsh demands of the West. Although most retained their racist concepts, they came to realise that women need not be passive or fearful in their interactions with Indians. Riley's sources are the diaries and journals of trail women, settlers, army wives, and missionaries, and popular accounts in newspapers and novels. She has also incorporated the literature in the field published since 1984 and a deeper analysis of relationships between white women and Indians in westward expansion.
Testing for Spatial Lag and Spatial Error Dependence in a Fixed Effects Panel Data Model Using Double Length Artificial Regressions

This paper revisits the joint and conditional Lagrange Multiplier tests derived by Debarsy and Ertur (2010) for a fixed effects spatial lag regression model with spatial auto-regressive error, and derives these tests using artificial Double Length Regressions (DLR). These DLR tests and their corresponding LM tests are compared using an empirical example and a Monte Carlo simulation.
Small-scale farmer responses to the double exposure of climate change and market integration

Anthropologists have long studied how small-scale societies manage climate variation. Here, we investigate how Yucatec Maya subsistence farmers respond to climate stress, and the ways in which market integration may enhance or disturb response stategies. Using information on harvest returns, climate perceptions, household economics and helping networks, modelling results show that as farmers rely more on market inputs (e.g. seed, tractors, fertilizer) for a successful yield, the reasons given for a bad harvest shift from climate variables to access to quality inputs. We also find that social and economic diversification is key to mediating a household's experience of climate and market shocks. The Maya are astute stewards of climate knowledge, and have effective social and economic means to mitigate potential fluctuations in food availability. In the transition from a subsistence to a market integrated economy, these traditional strategies become strained. Reliance on market inputs forges a more rigid food production system that conflicts with the diversity and flexibility on which traditional strategies depend to manage climate variation. Moving forward, the best policies would be those that facilitate maintaining an equal footing in both a subsistence maize economy, while incorporating new market opportunities. This article is part of the theme issue ‘Climate change adaptation needs a science of culture’.
Comparison of Shrinkage–Based Estimators in the Presence of Missing Data: A Multiple Imputation Analysis

In this paper we examined the performance of the mean square error of the Ordinary Least Square (OLS) estimator, Minimum Mean Square Error (MMSE) estimator, N/N shrinkage Estimator (N/NSE) and a proposed Adjusted Minimum Mean Square Error (PAMMSE) estimator in a multiple imputation analysis when data points are missing in different data sets. The program for the proposed adjusted minimum mean square error was written and implemented in R. It is shown by numerical computations that the PAMMSE Estimator seem to be the best choice among OLS, MMSE, N/NSE and PAMMSE estimators in terms of their mean square errors when applied in multiple imputation analysis.
Nitrogen dynamics of organic farming in a crop rotation based on red clover (Trifolium pratense) leys

In agricultural systems which rely on organic sources of nitrogen (N), of which the primary source is biological N fixation (BNF), it is extremely important to use N as efficiently as possible with minimal losses to the environment. The amount of N through BNF should be maximised and the availability of the residual N after legumes should be synchronised to the subsequent plant needs in the crop rotation. Six field experiments in three locations in Finland were conducted in 1994-2006 to determine the productivity and amount of BNF in red clover-grass leys of different ages. The residual effects of the leys for subsequent cereals as well as the N leaching risk were studied by field measurements and by simulation using the CoupModel. N use efficiency (NUE) and N balances were also calculated. The yields of red clover-grass leys were highest in the two-year-old leys (6700 kg/ha) under study, but the differences between 2- and 3-year old leys were not high in most cases. BNF (90 kg/ha in harvested biomass) correlated strongly with red clover dry matter yield, as the proportion of red clover N derived from the atmosphere (>85%) was high in our conditions of organically farmed field with low soil mineral N. A red clover content of over 40 % in dry matter is targeted to avoid negative N-balances and to gain N for the subsequent crop. Surprisingly, the leys had no significant effect on the yields and N uptake of the two subsequent cereals (winter rye or spring wheat, followed by spring oats). On the other hand, yield and C:N of leys, as well as BNF-N and total-N incorporated into the soil influenced on subsequent cereal yields. NUE of cereals from incorporated ley crop residues was rather high, varying from 30 % to 80 % (mean 48 %). The mineral N content of soil in the profile of 0-90 cm was low, mainly 15-30 kg/ha. Simulations of N dynamics by CoupModel functioned satisfactorily and is considered a useful tool to estimate N flows in cropping systems relying on organic N sources. Understanding the long-term influence of cultivation history and soil properties on N dynamics remains to be a challenge to further research.
Posterior parietal cortex and episodic encoding: Insights from fMRI subsequent memory effects and dual-attention theory

The formation of episodic memories—memories for life events—is affected by attention during event processing. A leading neurobiological model of attention posits two separate yet interacting systems that depend on distinct regions in lateral posterior parietal cortex (PPC). From this dual-attention perspective, dorsal PPC is thought to support the goal-directed allocation of attention, whereas ventral PPC is thought to support reflexive orienting to information that automatically captures attention. To advance understanding of how parietal mechanisms may impact event encoding, we review functional MRI studies that document the relationship between lateral PPC activation during encoding and subsequent memory performance (e.g., later remembering or forgetting). This review reveals that (a) encoding-related activity is frequently observed in human lateral PPC, (b) increased activation in dorsal PPC is associated with later memory success, and (c) increased activation in ventral PPC predominantly correlates with later memory failure. From a dual-attention perspective, these findings suggest that allocating goal-directed attention during event processing increases the probability that the event will be remembered later, whereas the capture of reflexive attention during event processing may have negative consequences for event encoding. The prevalence of encoding-related activation in parietal cortex suggests that neurobiological models of episodic memory should consider how parietal-mediated attentional mechanisms regulate encoding. 2008 Elsevier Inc. All rights reserved.
Aalborg Universitet Energy savings in mobile broadband network based on load predictions

The deployment of new network equipment is resulting in increasing energy consumption in mobile broadband networks (MBNs). This contributes to higher CO2 emissions. Over the last 10 years MBNs have grown considerably, and are still growing to meet the evolution in traffic volume carried in wireless networks. To save energy in MBNs, one of the options is to turn off parts of the network equipment in areas where traffic falls below a specific predefined threshold. This paper looks at a methodology for identifying periods of the day when cells or sites carrying low traffic are candidates for being totally or partly switched off, given that the decrease in service quality can be controlled gracefully when the sites are switched off. Based on traffic data from an operational network, potential average energy savings of approximately 30% with some few low traffic cells/sites reaching up to 99% energy savings can be identified.
Effect of channel interaction on vocal cue perception

Understanding speech in the presence of two or more simultaneous talkers poses challenges for CI users. One possible cause of this limitation is the suboptimal representation of vocal cues delivered by the implant, such as the fundamental frequency (F0), and the vocal tract length (VTL) cue. Previous studies have suggested that VTL cues rely heavily on the spectral dimension of the speech signal. On the other hand, F0 perception in implants can rely both on spectral and temporal cues. To clarify how spectral smearing in the implant affects vocal cue perception and speech-on-speech (SoS) intelligibility, parallel channels were added in the CI stimulation pattern to artificially increase channel interaction. The CI stimulation pattern was manipulated by adding simultaneously stimulated channels in 14 Advanced Bionics CI users. Three such patterns were created: Sequential stimulation (one channel consisting of 2 adjacent electrodes were simultaneously stimulated at a time), Paired stimulation (2 such channels), and Triplet stimulation (3 such channels). F0 and VTL just-noticeable differences (JNDs; task 1) and SoS intelligibility (task 2) and comprehension (task 3) were measured for each stimulation strategy (Sequential vs. Paired vs. Triplet). In tasks 2 and 3, four different maskers were used: the same female talker, a male voice obtained by manipulating both F0 and VTL (F0+VTL) relative to the original female speaker, a voice where only F0 was manipulated, and a voice where only VTL was manipulated. JNDs were measured relative to the original voice for the F0, VTL, and F0+VTL manipulations. When spectral smearing was increased, a significant deterioration in performance was observed for all tasks, with no significant interaction effects between voice dimension and stimulation pattern for tasks 1 and 3. The lack of such an interaction suggests that degradations in performance for both tasks are persistent across the vocal dimensions (F0
The Black Sea Catchment Observation System built on a grid-enabled Spatial Data Infrastructure

The Black Sea catchment represents a very large historically rich area of more than 2 million km2 with more than 160 million inhabitants occupying a strategic position between Europe and Asia. It is partially following an unsustainable development caused by inadequate resource management that leads to severe environmental, social and economical problems. The EnviroGRIDS @ Black Sea Catchment project is addressing these issues by bringing several new emerging information technologies that are totally revolutionizing the way we will be looking at our planet in the future. The Global Monitoring for the Environment and Security (GMES) and the Global Earth Observation Systems of Systems (GEOSS) are indeed building a data-driven vision of our planet to explore its past, present and future. The INSPIRE directive is promoting data sharing through interoperability standards at European level, while the UN-SDI is following the same pathway within the United Nations. In order to address the challenges faced by these initiatives of increasing need for data storage and processing, enviroGRIDS will build upon the largest Grid computing infrastructure in the world (EGEE) that will transform elements of software underpinning scenarios and models onto a gridded system. EnviroGRIDS is aiming at building the capacity of scientist to assemble such a system, the data providers to share their data, the capacity of decision makers to use it, and the capacity of the general public to understand the important environmental, social and economical issues at stake.
Using Linear Regression Machine Learning Algorithm for the Prediction

— The Real Estate prediction model is a web-based Machine Learning project which uses the machine learning algorithm to determine the price of the house in the future. This project targets the people who are in search of a place for living with a suitable price and a living standard. To get better and accurate results we have used multiple algorithms and compared them. The findings have indicated that the use of various algorithms can drastically impact the accuracy of the prediction. And, having a poor dataset negatively impacts the prediction. Different factors like interest rates, housing inventory, absorption rates, rental to capitals and many more impact the price of the real estate. So, we would like to make a model which predicts the price precisely keeping these factors in mind.
The generation of global fields of terrestrial biophysical parameters from the NDVI

A coke oven leveling door hatch construction, comprises a hatch pivot bearing adapted to be mounted on the coke oven door or directly adjacent the door. A hatch door for closing a leveling port includes a locking bar extending across the front face thereof which terminates in a forked end having a pair of bearings which engage over the respective ends of the hatch pivot bearing and which are secured to a pivot which extends through the pivot bearing so that the door may be pivoted thereabout. The pivot includes an offset portion or crank arm which is connectable to an opening mechanism which comprises a fluid pressure operated cylinder having a movable piston therein which is connected to a rotatable forked arm which engages the crank to rotate it through an arc to effect turning of the door to open the door. The locking bar includes an inwardly extending portion on the side of the door opposite from the pivot, which terminates in a hook which is engageable by a rotatable arm having a detent which engages with the hook. The arm is biased by a spring to rotate in a direction to cause engagement but the locking bar may be moved against the biasing force to rotate the latching arm having the detent so that the detent moves out of engagement with the hook.
A General Concrete Model in Hydrocodes: Verification and Validation of the RHT model in LS-DYNA

The Riedel-Hiermaier-Thoma (RHT) model, which is available in ANSYS Autodyn since 2000 as a description of concrete and similar geological materials in highly dynamic loading situations, has recently been implemented in the multi-purpose Finite Element code LS-DYNA. This paper gives a brief overview of the physical details and verifies the new implementation by comparing single element test results with the established Autodyn code. Four real cases, ranging from low to very high pressure loading by impact, penetration and blast, are used to demonstrate thereafter the validity of the model in a wide range of applications. Simulation results from both codes are compared to experimental data at several occasions. Although slight differences between the implementations are observed, the overall agreement, both between the codes and with experiments is very good. The systematic work in this publication demonstrate that the RHT-model is a useful addition to the LS-DYNA material library and shall motivate research to apply the model over a wide range of applications. A comprehensive, physically derived dataset is provided for a C70/85 high strength concrete used in one validation case.
A controlled randomised clinical trial to assess post-operative analgesia after 8 thiopental-isoflurane anaesthesia or total intravenous anaesthesia with

17 Alfaxalone, a synthetic neuroactive steroid, has been attributed with properties including sedation, 18 anaesthesia and analgesia. The clinical relevance of any analgesic properties of alfaxalone has not 19 been demonstrated. This study was a prospective, blinded, randomised, negative control clinical trial 20 in 65 healthy dogs presented for ovariohysterectomy. Anaesthesia was induced and maintained; for 21 Group 1 (TIVA) dogs (n=30) with intravenous alfaxalone alone and for Group 2 dogs (n=35) with 22 thiopental followed by isoflurane in 100% oxygen inhalation. After ovariohysterectomy, quantitative 23