Miracle-dz/UniFAR-FTUs huggingface dataset:
SATISFACTION IN CARING FOR OLDER ADULTS WITH ALZHEIMER'S: PERCEPTIONS OF THE FAMILY CAREGIVERS

4 ABSTRACT: This study aimed to ascertain the conditions of satisfaction of family caregivers for older adults with Alzheimer's Disease in the municipality of Umuarama in the Brazilian state of Parana (PR). It is a qualitative, descriptive and exploratory study, undertaken with eight family caregivers. The data were collected in the period July - September 2013, through semistructured interviews held in the caregivers' homes and later subjected to analysis, from which four categories emerged: The experience with the care allows the development of skills; The provision of well-being to the older adult affords satisfaction to the family caregiver; Religiosity promotes satisfaction in caring; and Demonstrating love and gratitude through the care promotes the satisfaction of the family caregiver. The results indicated that satisfaction also exists in the act of caring, demystifying the imaginary that this activity is permeated only by dissatisfaction and overload. DESCRIPTORS: Alzheimer's Disease; Older adults; Caregiver; Personal satisfaction.
Distribution of quantum entanglement : principles and applications

Quantum entanglement is a form of correlation between quantum particles that has now become a crucial part in quantum information and communication science. For example, it has been shown to enable or enhance quantum processing tasks such as quantum cryptography, quantum teleportation, and quantum computing. However, quantum entanglement is prone to decoherence as a result of interactions with environmental scatterers, making it an expensive resource. Therefore, it is crucial to understand its creation. We centre our attention to a situation where one would like to distribute quantum entanglement between principal particles that are apart. In this case, it is necessary to use ancillary systems that are communicated between them or interact with them continuously. Cubitt et al. showed that the ancillary systems need not be entangled with the principal particles in order to distribute entanglement. This has been demonstrated experimentally in the case of communicated ancillary particles and it is now known that the bound on the distributed entanglement is given by a communicated quantum discord. On the other hand, little is understood about the setting with continuous interactions, despite its abundant occurrence in nature. The main focus of this thesis is to study the distribution of quantum entanglement via continuous interactions with ancillary particles, which I will call mediators. I will present my work regarding the necessary conditions for entanglement distribution, the factors that are relevant for the distributed amount, and the speed limit to achieving maximum entanglement gain. Finally, I present some notable applications that can benefit from our work. This includes, among others, indirect probing of the quantum nature of optomechanical mirrors, photosynthetic organisms, and gravitational interactions.
Ensemble learning in CNN augmented with fully connected subnetworks

Convolutional Neural Networks (CNNs) have shown remarkable performance in general object recognition tasks. In this paper, we propose a new model called EnsNet which is composed of one base CNN and multiple Fully Connected SubNetworks (FCSNs). In this model, the set of feature-maps generated by the last convolutional layer in the base CNN is divided along channels into disjoint subsets, and these subsets are assigned to the FCSNs. Each of the FCSNs is trained independent of others so that it can predict the class label from the subset of the feature-maps assigned to it. The output of the overall model is determined by majority vote of the base CNN and the FCSNs. Experimental results using the MNIST, Fashion-MNIST and CIFAR-10 datasets show that the proposed approach further improves the performance of CNNs. In particular, an EnsNet achieves a state-of-the-art error rate of 0.16% on MNIST.
NeRF

We present a method that achieves state-of-the-art results for synthesizing novel views of complex scenes by optimizing an underlying continuous volumetric scene function using a sparse set of input views. Our algorithm represents a scene using a fully connected (nonconvolutional) deep network, whose input is a single continuous 5D coordinate (spatial location (x, y, z) and viewing direction (θ, ϕ)) and whose output is the volume density and view-dependent emitted radiance at that spatial location. We synthesize views by querying 5D coordinates along camera rays and use classic volume rendering techniques to project the output colors and densities into an image. Because volume rendering is naturally differentiable, the only input required to optimize our representation is a set of images with known camera poses. We describe how to effectively optimize neural radiance fields to render photorealistic novel views of scenes with complicated geometry and appearance, and demonstrate results that outperform prior work on neural rendering and view synthesis.
A Comparison of Hurst Exponent Estimators in Long-range Dependent Curve Time Series

Abstract The Hurst exponent is the simplest numerical summary of self-similar long-range dependent stochastic processes. We consider the estimation of Hurst exponent in long-range dependent curve time series. Our estimation method begins by constructing an estimate of the long-run covariance function, which we use, via dynamic functional principal component analysis, in estimating the orthonormal functions spanning the dominant sub-space of functional time series. Within the context of functional autoregressive fractionally integrated moving average (ARFIMA) models, we compare finite-sample bias, variance and mean square error among some time- and frequency-domain Hurst exponent estimators and make our recommendations.
A Hybrid Model-Based and Data-Driven Approach to Spectrum Sharing in mmWave Cellular Networks

Inter-operator spectrum sharing in millimeter-wave bands has the potential of substantially increasing the spectrum utilization and providing a larger bandwidth to individual user equipment at the expense of increasing inter-operator interference. Unfortunately, traditional model-based spectrum sharing schemes make idealistic assumptions about inter-operator coordination mechanisms in terms of latency and protocol overhead, while being sensitive to missing channel state information. In this paper, we propose hybrid model-based and data-driven multi-operator spectrum sharing mechanisms, which incorporate model-based beamforming and user association complemented by data-driven model refinements. Our solution has the same computational complexity as a model-based approach but has the major advantage of having substantially less signaling overhead. We discuss how limited channel state information and quantized codebook-based beamforming affect the learning and the spectrum sharing performance. We show that the proposed hybrid sharing scheme significantly improves spectrum utilization under realistic assumptions on inter-operator coordination and channel state information acquisition.
The 2016 Vela glitch: a key to neutron star internal structure and dynamics

High resolution, pulse to pulse observation of the 2016 Vela glitch and its relaxation provided an opportunity to probe the neutron star internal structure and dynamics with unprecedented detail. We use the observations of this glitch to infer superfluid characteristics in the framework of the vortex creep model. The glitch rise time constraint of 12.6 seconds put stringent limits on the angular momentum exchange between the crustal superfluid and the observed crust. Together with the observed excess acceleration in the rotation rate as compared to the post-glitch equilibrium value this discriminates crustal superfluid-crust lattice and core superfluid-crustal normal matter coupling time-scales. An evident decrease in the crustal rotation rate immediately before the glitch is consistent with the formation of a new vortex trap zone that initiates the large scale vortex unpinning avalanche. Formation of vortex trap by a crust breaking quake induces short-lived magnetospheric changes. The long term post-glitch spin-down rate evolution reveals the moments of inertia and recoupling time-scales of the superfluid layers participating in the glitch and leads to an estimation of the time to the next glitch which agrees with the time interval between the 2016 and 2019 glitches. Our results are consistent with theoretical estimates of effective neutron and proton masses in the superfluid. We also constrain the vortex line-flux tube pinning energy per intersection as 2 MeV.
Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions

Creating open-ended algorithms, which generate their own never-ending stream of novel and appropriately challenging learning opportunities, could help to automate and accelerate progress in machine learning. A recent step in this direction is the Paired Open-Ended Trailblazer (POET), an algorithm that generates and solves its own challenges, and allows solutions to goal-switch between challenges to avoid local optima. However, the original POET was unable to demonstrate its full creative potential because of limitations of the algorithm itself and because of external issues including a limited problem space and lack of a universal progress measure. Importantly, both limitations pose impediments not only for POET, but for the pursuit of open-endedness in general. Here we introduce and empirically validate two new innovations to the original algorithm, as well as two external innovations designed to help elucidate its full potential. Together, these four advances enable the most open-ended algorithmic demonstration to date. The algorithmic innovations are (1) a domain-general measure of how meaningfully novel new challenges are, enabling the system to potentially create and solve interesting challenges endlessly, and (2) an efficient heuristic for determining when agents should goal-switch from one problem to another (helping open-ended search better scale). Outside the algorithm itself, to enable a more definitive demonstration of open-endedness, we introduce (3) a novel, more flexible way to encode environmental challenges, and (4) a generic measure of the extent to which a system continues to exhibit open-ended innovation. Enhanced POET produces a diverse range of sophisticated behaviors that solve a wide range of environmental challenges, many of which cannot be solved through other means.
A court file analysis of child protection cases: What do children say?

Correspondence Nicole Kratky, Department of Psychology, Technische Universität Darmstadt, Alexanderstraße 10, 64283 Darmstadt, Germany. Email: kratky@psychologie.tu-darmstadt.de Abstract Children's participation in legal proceedings affecting them personally has been gaining importance. So far, a primary research concern has been how children experience their participation in court proceedings. However, little is known about the child's voice itself: Are children able to clearly express their wishes, and if so, what do they say in child protection cases? In this study, we extracted information about children's statements from court file data of 220 child protection cases in Germany. We found 182 children were asked about their wishes. The majority of the statements found came either from reports of the guardians ad litem or from judicial records of the child hearings. Using content analysis, three main aspects of the statements were extracted: wishes concerning main place of residence, wishes about whom to have or not contact with, and children granting decision-making authority to someone else. Children's main focus was on their parents, but others (e.g., relatives and foster care providers) were also mentioned. Intercoder agreement was substantial. Making sure that child hearings are as informative as possible is in the child's best interest. Therefore, the categories developed herein might help professionals to ask questions more precisely relevant to the child.
Intergenerational Transfers and Socioeconomic Inequality in Brazil: a First Look

There is an increasing concern of how demographic changes, especially population aging, might affect intergenerational transfers, macroeconomic variables and the public fiscal balance. However, there is little research discussing whether intergenerational transfers, private and public, are equally distributed across different socioeconomic groups and whether they contribute to the reduction of income inequality and poverty, especially in less developed economies. This paper examines the interactions between demographic changes, intergenerational transfers and socioeconomic inequality in Brazil. Our results indicate that family transfers have greater importance for children, especially those in wealthier families. Children of poorer families rely more heavily on public transfers. This is not true, however, for the elderly. We show that elderly consumption, for all socioeconomic groups, depends largely on public transfers. The paper shows that poor children receive the least amount of public and private transfers, at least in the cross section perspective. We argue that differences in political power across age groups and socioeconomic status as well as which socioeconomic groups benefit from the same programs might help explain those outcomes. The paper provides important insights into how differences in intergenerational transfers across socioeconomic groups help explain the perverse cycle of inequality and poverty in Brazil.
Psychological, social, and motivational factors in the drug user care-seekers

Background In addition to the family and society’s support, the drug user plays a key role in the process of treatment and rehabilitation. Therefore, it is imperative to find the psychological, social, and motivational factors that can help them in the treatment process. The present study is an attempt to determine the relationship of psychological, social, and motivational factors and demographics of drug user care-seekers. Methods An analytical cross-sectional study was carried out. Psychological, Social, and Motivational Performance Questionnaire for drug users was first translated into Farsi and validated after securing a permission from the copyright holder of the tool. Participants were 250 drug user care-seekers under methadone therapy who were selected through convenient sampling. Before analyzing the collected data, validity and reliability of the tool were confirmed using confirmatory and exploratory factor analyses. Given the scale of demographical data, suitable statistics were used to analyze the relationship between demographical variables and psychological, social, and motivational factors. Results The results of exploratory and confirmatory factor analyses showed that out of 83 statements in the original questionnaire, 55 statements categorized into 11 aspects were usable for Iranian population. The results showed that gender, income, and marital status were effective in psychological performance of the drug users (P<0.05). However, education level, domicile, and type of drug and consumption did not have a significant relationship with social performance of the participants (p>0.05). There was a significant relationship between age, number of children, and history of using drug and psychological performance of the participants (P<0.01). The results showed that the demographics did not have a notable effect on the participants’ motivation for treatment; only marital status had a significant relationship with the participants’ readiness for treatment (P<0.05). Conclusion As the results showed, the demographical variables could affect physical, psychological, and motivational readiness in the participants.
Effect of Ohmic Heating on Quality Parameters of Sapota Juice

Sapota fruit is a good source of sugars, ascorbic acid, iron and calcium but due to high moisture (72-75%) and TSS content (12-20 ̊Brix), the fruit gets spoiled fast and need to be processed into value added product to extend the shelf life. Experiments were conducted to study the effect of ohmic heating on quality parameters of sapota juice and to extend its shelf life. The study was designed using response surface methodology employing the rotatable central composite design which generated 13 experiments. The independent variables were: electric field strength (15 V/cm – 30 V/cm) and processing time (30 s – 120 s). The responses were pH, titratable acidity, total soluble solids, ascorbic acid, reducing sugars, total colour change. The pH and titratable acidity were significantly (p<0.05) affected by ohmic heating, whereas there was no significant effect of ohmic heating on ascorbic acid, reducing sugars, total soluble solids and total colour change of sapota juice. The sapota juice processed with optimum parameters had a shelf life of 10 days whereas fresh unpasteurized juice stored at refrigerated conditions deteriorated within 5 days.
STUDYING THE PREVALENCE OF OCCUPATIONAL BURNOUT IN STAFF WORKING AT A HOSPITAL IN THE CITY OF JAVANROOD- KERMANSHAH (IRAN)

Occupational burnout is a syndrome, which by causing negative self-image, negative attitude toward the job and lack communication sense to client leads to severe loss of health-care services quality. The health-care sector is one of the most important fields of sustainable development in human societies that requires healthy, enthused and high motivated therapists. The aim of this study was to investigate the prevalence of occupational burnout in staff working at a hospital in the city of javanroodKermanshah (Iran). Current studywas carried out by cross-sectional method on 100 staffat a hospital in the city of javanroodKermanshah (Iran). In order to measure occupational burnout, Galdard Burnout inventory questionnaire (GBI) was used. At the end of study, obtained information was entered to SPSS-16 software andwasanalyzed. The results showed that 28% of subjects were experiencedless occupational burnout, 57% were experienced high occupational burnout and 15% were experienced very high occupational burnout.In addition, the highest value of occupational burnout had belonged to the age range of 23-35 years by work experience of 1-7 years in women than in men, personnel by having associate degree and therapists than other groups respectively. The prevalence of occupational burnout was high in current study and it recommends to perform some measures such as increasing job stability and performance dimension, clarifying the person's accountability toward work done and separating duty among the members as well as appropriating environmental, economic, personnel and management conditions in order to reduce work load which places at organizational priorities.
Adaptive and Stable Integration of Energy Harvesting Aware Body Sensor Networks with Clouds

This paper considers a multi-tier architecture for cloud-integrated body sensor networks (BSNs), called Body-in-the-Cloud (BitC), which is intended to support home healthcare with on-body energy harvesting devices (e.g., piezoelectric and thermoelectric generators) as well as on-body physiological and activity monitoring sensors. This paper formulates a conﬁguration problem in BitC and approaches the problem with an evolutionary game theoretic algorithm to conﬁgure BSNs in an adaptive and stable manner. BitC allows BSNs to adapt their conﬁgurations (i.e., sensing intervals and sampling rates as well as data transmission intervals) to operational conditions (e.g., data request patterns) with respect to multiple conﬂicting performance objectives such as resource consumption and data yield. In BitC, evolutionary multiobjective games are performed on conﬁguration strategies (i.e., solution candidates) with an aid of local search mechanisms. BitC theoretically guarantees that each BSN performs an evolutionarily stable conﬁguration strategy, which is an equilibrium solution under given operational conditions. Simulation results verify this theoretical analysis; BSNs seek equilibria to perform adaptive and evolutionarily stable conﬁguration strategies. This paper evaluates ﬁve algorithmic variants of BitC under various settings and demonstrates that BitC allows BSNs to successfully leverage harvested energy to balance their performance in different objectives such as resource consumption and data yield.
Homogenization of Symmetric Stable-like Processes in Stationary Ergodic Media

This paper studies homogenization of symmetric non-local Dirichlet forms with $\alpha$-stable-like jumping kernels in one-parameter stationary ergodic environment. Under suitable conditions, we establish homogenization results and identify the limiting effective Dirichlet forms explicitly. The coefficients of the jumping kernels of Dirichlet forms and symmetrizing measures are allowed to be degenerate and unbounded; and the coefficients in the effective Dirichlet forms can be degenerate.
Performance Verification of the EXtreme PREcision Spectrograph

The EXtreme PREcision Spectrograph (EXPRES) is a new Doppler spectrograph designed to reach a radial-velocity measurement precision sufficient to detect Earth-like exoplanets orbiting nearby, bright stars. We report on extensive laboratory testing and on-sky observations to quantitatively assess the instrumental radial-velocity measurement precision of EXPRES, with a focused discussion of individual terms in the instrument error budget. We find that EXPRES can reach a single-measurement instrument calibration precision better than 10 cm s−1, not including photon noise from stellar observations. We also report on the performance of the various environmental, mechanical, and optical subsystems of EXPRES, assessing any contributions to radial-velocity error. For atmospheric and telescope related effects, this includes the fast tip-tilt guiding system, atmospheric dispersion compensation, and the chromatic exposure meter. For instrument calibration, this includes the laser fRequency comb (LFC), flat-field light source, CCD detector, and effects in the optical fibers. Modal noise is mitigated to a negligible level via a chaotic fiber agitator, which is especially important for wavelength calibration with the LFC. Regarding detector effects, we empirically assess the impact on the radial-velocity precision due to pixel-position nonuniformities and charge transfer inefficiency (CTI). EXPRES has begun its science survey to discover exoplanets orbiting G-dwarf and K-dwarf stars, in addition to transit spectroscopy and measurements of the Rossiter–McLaughlin effect.
PtHAK5, a candidate for mediating high-affinity K uptake in the halophytic grass, Puccinellia tenuiflora

Puccinellia tenuiflora is a typical salt-excluding halophytic grass with strong salt-tolerance, which enhances tolerance by restricting Na influx as well as having a strong selectivity for K over Na. The HAK5 K transporters generally modulate effective K acquisition in plants, especially under low K condition. In this study, PtHAK5 from P. tenuiflora was isolated by RT-PCR and characterized using yeast complementation. The results showed PtHAK5 consisted of 784 amino acids and shared over 80% homology with the identified high-affinity K transporter HAK5 from other higher plants. The expression of PtHAK5 rescued the K-uptake-defective phenotype of yeast strain CY162. In conclusion, PtHAK5 is a candidate for mediating high-affinity K uptake under low K conditions.