Miracle-dz/UniFAR-FTUs huggingface dataset:
Healthcare professionals' perspectives on HIV disclosure of a parent's and a child's illness in Kenya

Background: Many HIV-affected families have both parent(s) and child(ren) infected. HIV disclosure to children continues to be a great global challenge for HIV-positive parents and healthcare professionals (HCPs); parents and HCPs differ on how and when to disclose to children. Methods: Six HCPs including a physician, clinical officer, psychologist, registered nurse, social worker, and a peer educator participated in a larger qualitative phenomenological study conducted to describe the lived experiences of HIV-positive parents and their children during the disclosure process in Kenya. Each HCP underwent an in-depth, semi-structured interview; transcribed data were analyzed using the modified Van Kaam method in NVivo8. Results: Despite HCPs providing parents with regular advice on the benefits of HIV disclosure, fear of stigma, discrimination, and disclosure consequences caused parents to delay disclosure of a parent’s and/or a child’s illness to their HIV-negative and positive children respectively for lengthy periods. While awaiting parental consent for full disclosure, HCPs were forced to provide age-appropriate diseaserelated information to children. HCPs preference however, was to fully disclose to children in their parents’ presence at the clinic, when children started asking questions and/or displayed maturity and understanding of the illness. Conclusion: Parents are known to prefer disclosing to their children at a time and place of their choosing. Conversely, it appears that HCPs may prefer to disclose to children when they judge the time as being right. For favorable disclosure outcomes, further studies are needed to reconcile the most suitable timing, setting, and person to disclose to HIV-positive and negative children.
Statistical Determination of Parents’ Use of Gamification Applications According to the Technology Acceptance Model

Gamification is used to motivate the targeted behaviors using game elements in non-game environments through the implementation of designs outlined in the theories of behavior. The main purpose of this study is to examine the use of gamification applications by parents based on the Technology Acceptance Model 2. The study results show that the use of gamification applications increases parenting performance, productivity, and effectiveness, that parents will use gamification applications in the future and that they can easily explain the results of the use of gamification applications to others. It shows that parents are not obliged to use gamification in their occupations and that people who influence their behaviors do not think that they should use gamification applications. The study uses a quantitative approach and data analysis is performed using the SPSS program. The data are analyzed and interpreted by tabulating frequency, percentages, t-test and Anova tests. Future studies will provide training on how parents can use gamification applications for their children’s education within the framework of the Technology Acceptance Model 2.
Travel needs in school trips in Tanzania and Namibia: analyzing relationship between use of in-vehicle travel time and willingness to avoid crowding

In this paper, we study travel needs in school trips and we present the results of the survey conducted in Tanzania and Namibia. We analyze relationship between use of in-vehicle travel time and willingness to avoid crowding. In the light of the empirical results, we discuss how travel needs and preferences related to the use of in-vehicle time and crowding should be taken into account in designing and providing new public transportation services for students and commuters.
The high-level benefits of low-level sandboxing

Sandboxing is a common technique that allows low-level, untrusted components to safely interact with trusted code. However, previous work has only investigated the low-level memory isolation guarantees of sandboxing, leaving open the question of the end-to-end guarantees that sandboxing affords programmers. In this paper, we fill this gap by showing that sandboxing enables reasoning about the known concept of robust safety, i.e., safety of the trusted code even in the presence of arbitrary untrusted code. To do this, we first present an idealized operational semantics for a language that combines trusted code with untrusted code. Sandboxing is built into our semantics. Then, we prove that safety properties of the trusted code (as enforced through a rich type system) are upheld in the presence of arbitrary untrusted code, so long as all interactions with untrusted code occur at the “any” type (a type inhabited by all values). Finally, to alleviate the burden of having to interact with untrusted code at only the “any” type, we formalize and prove safe several wrappers, which automatically convert values between the “any” type and much richer types. All our results are mechanized in the Coq proof assistant.
Multivariate Spline Estimation and Inference for Image-on-Scalar Regression

: Motivated by recent analyses of data in biomedical imaging studies, we consider a class of image-on-scalar regression models for imaging responses and scalar predictors. We propose using ﬂexible multivariate splines over triangulations to handle the irregular domain of the objects of interest on the images, as well as other characteristics of images. The proposed estimators of the coeﬃcient functions are proved to be root- n consistent and asymptotically normal under some regularity conditions. We also provide a consistent and computationally eﬃcient estimator of the covariance function. Asymptotic pointwise conﬁdence intervals and data-driven simultaneous conﬁdence corridors for the coeﬃcient functions are constructed. Our method can simultaneously estimate and make inferences on the coeﬃcient functions, while incorporating spatial heterogeneity and spatial correlation. A highly eﬃcient and scalable estimation algorithm is developed. Monte Carlo simulation studies are conducted to examine the ﬁnite-sample performance of the proposed method, which is then applied to the spatially normalized positron emission tomography data of the Alzheimer’s Disease Neuroimaging Initiative.
University of Southern Denmark The Screen-ICD trial. Screening for anxiety and cognitive therapy intervention for patients with implanted cardioverter defibrillator (ICD) a randomised controlled trial protocol

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A new symbolic representation method to support conceptual design of mechatronic system

Regarding the typical mechatronic system that realizes controlled motion behaviour as the research object, the mechatronic system is composed of three subsystems, they are generalized executive mechanism subsystem, sensing and testing subsystem, and information processing and control subsystem. Based on the three subsystems, a new kind of symbolic representation method to represent a design scheme of mechatronic system is presented. This symbolic representation method includes graphical symbols, literal symbols and port information flows on the abstract layer of basic mechatronic function units in common use. Two applied instances are given. The method standardizes scheme representation of mechatronic system. The purpose is that the computer can identify and operate the standardized scheme representation. Furthermore, the method can be implemented in connection with related knowledge base to produce creative scheme. The symbolic representation method provides theoretical basis for computer aided conceptual design of mechatronic system.
The trouble with 2 nd order models or how to generate stop-and-go traffic in a 1 st order model

Classical second order models of pedestrian dynamics, like the social-force model, suffer from various unrealistic behaviors in the dynamics, e.g. backward motion, oscillations and overlapping of pedestrians. These effects are not related to the discretization of the equations of motion, but intrinsic to the dynamics. They are the consequence of strong inertia effects that usually appear in second order models. We show that the experimentally observed stop-and-go behavior, which is an important test for any pedestrian model, can be reproduced with a stochastic first order model that does not suffer from the dynamical artefacts resulting from strong inertia. The model provides a new mechanism for stop-and-go behavior which is based on correlated noise.
Improving BLE deterministic fingerprinting by using a weighted k-NN algorithm over filtered RSSI data

Fingerprinting systems are a simple and eﬃcient way to build positioning systems for Location Based Services (LBS) applications in smartphones. The technologies that can be used for radio frequency ﬁngerprinting with oﬀ-the-shelf smartphones are Wi-Fi, which has been deeply studied, and Bluetooth Low Energy (BLE), which is receiving more attention in the last years. This work presents an improvement in deterministic ﬁngerprinting using a ﬁltering process and a new function to compute the Weighted k Nearest Neighbours (W k -NN) location algorithm. Results with a BLE data set show that these improvements reduce the localization error and give a simple way to build a ﬁnger-printing positioning system for smartphones with an average precision of less than a meter.
Classification of Language Proficiency Levels in Swedish Learners’ Texts

We evaluate a system for the automatic classification of texts written by learners of Swedish as a second language into levels of language proficiency. Since the amount of available annotated learner essay data for our target language is rather small, we explore also the potentials of domain adaptation for this task. The additional domain consists of coursebook texts written by experts for learners. We find that already with a smaller amount of in-domain Swedish learner essay data it is possible to obtain results that compare well to state-of-the-art systems for other languages, with domain adaptation methods yielding a slight
Particle Filter Network: A Model-free Approach for POMDP

In this paper, we consider the problem of model-free POMDP learning without knowing the hidden state transition dynamics, either in the form of probability models or simulators. We propose to solve it using a neural-network based particle filter, and combine it with an LSVI planning module with a Q-value network. Our preliminary experiments show that the particle filter network can be well-learned without the decision making part. It remains to be studied how the inclusion of the planning module will perform when nontrivial decision making is involved.
Should OCDBe Recognized as a Differential Diagnosis for Separation Anxiety Disorder ?

243 tHeRe ARe tOPOGRAPHICAL similarities between separation anxiety disorder (SAD) and certain forms of obsessive-compulsive disorder (OCD), particularly in terms of excessive, persistent, and recurrent fears of losing a major attachment figure and/or harm befalling a loved one. the DSM-5 (APA, 2013) included anxiety disorders as a differential diagnosis for OCD. However, OCD is not listed as a differential diagnosis for SAD. this discrepancy is concerning for different reasons. First, OCD and the OC spectrum disorders (e.g, trichotillomania, excoriation disorder, body dysmorphic disorder) have now been independently classified in the DSM-5 away from anxiety disorders (Regier, Kuhl, & Kupfer, 2013). As such, it is inconsistent that OCD is not listed as a rule-out for SAD. Second, the differential diagnosis section of the DSM-5 is intended to be helpful in guiding diagnostic decisions in clinical and/or research settings. Without a comprehensive reference of rule-out diagnoses, misdiagnosis can occur, to the detriment of treatment effectiveness and reliable research. In this article, we compared diagnostic features of SAD and certain forms of OCD, and discussed a case example, in order to explore whether OCD should be recognized as a differential diagnosis for SAD. Our approach is consistent with functional analysis (Holman, Rohl, & Andover, 2017), which involves determining antecedent internal and external events that precede target behaviors, as well as the consequences of those behaviors (for a case example, see May et al., 2008).
VISUALIZING PSEUDOSPECTRA FOR POLYNOMIAL EIGENVALUE PROBLEMS

The use of pseudospectra is widespread in various applications, e.g. control theory, acoustics, vibrating systems. Through pseudospectra we can gain insight into the sensitivity of the eigenvalues of a matrix to perturbations that is convenient for robust control. We have implemented in Matlab a method to visualize ε-pseudospectra for n×n polynomial matrix of degree greater than 2. We compute pseudospectrum for each point of the complex plane using transfer function approach. Although it might seem to be time consuming, we have testified that other methods as for instance curve tracing algorithm don’t give good results. They show problems with convergence. We have also tested straighforward computing after the definition which was more time consuming than the transfer function approach. To visualize pseudospectra we used above all functions contour and contourf.
Effect of Reaction Conditions on Catalytic and Noncatalytic Lignin Solvolysis in Water Media Investigated for a 5 L Reactor

The high content of oxygen in the lignin polymer and the prevalence of phenolic functional groups make the conversion of lignin to fuels and value-added products with well-defined chemical properties challenging. The lignin-to-liquid process using a water/formic acid reaction medium has been shown to convert the lignin polymer to monomers with a molecular weight range of 300–600 Da. The bio-oil comprises a complex mixture of monomeric phenols, aromatics, and aliphatic hydrocarbons with a high H/C and low O/C ratio. This study investigates the effect of the stirring rate, level of loading, and catalyst at 305 and 350 °C in a 5 L pilot scale reactor. The oil yields are found to be highest for experiments conducted using the maximum stirring rate, maximum level of loading, and Ru/Al2O3 catalyst with yields of more than 69 wt % on lignin intake. Goethite as a catalyst does not show good conversion efficiency at either reaction temperatures. The carbon recovery is highest for products produced at 305 °C. Furthermore, results from solid phase extraction on a DSC-CN solid phase show that 65–92 wt % the bio-oils can be recovered as fractions separated based on polarity.
Karyotype of Polyommatus (Agrodiaetus) eriwanensis Forster, 1960 and taxonomic position of P. (A.) interjectus de Lesse, 1960 (Lepidoptera, Lycaenidae)

Abstract The karyotype of Polyommatus (Agrodiaetus) eriwanensis Forster, 1960 from the type locality (“Eriwan” [Yerevan, Armenia]) and other localities in Armenia was investigated. The number of chromosomal elements (bivalents+ multivalents) observed in male meiosis I was found to vary from 29 to 34. In individuals with n = 34, all observed elements were represented by bivalents. In other specimens, heterozygosity for different number of chromosomal fusions resulted in multivalent formation at MI stage and consequently in a lower number of recognizable chromosomal elements. We show that all karyotype peculiarities of P. (A.) interjectus de Lesse, 1960 (n = 29–32) from Turkey are similar to those in A. eriwanensis. The butterflies of these taxa have allopatric distribution and can be considered as conspecific.
General and selective deoxygenation by hydrogen using a reusable earth-abundant metal catalyst

A Co-Ce catalyst permits the hydrodeoxygenation of alcohols, aldehydes, and ketones, tolerating numerous functional groups. Chemoselective deoxygenation by hydrogen is particularly challenging but crucial for an efficient late-stage modification of functionality-laden fine chemicals, natural products, or pharmaceuticals and the economic upgrading of biomass-derived molecules into fuels and chemicals. We report here on a reusable earth-abundant metal catalyst that permits highly chemoselective deoxygenation using inexpensive hydrogen gas. Primary, secondary, and tertiary alcohols as well as alkyl and aryl ketones and aldehydes can be selectively deoxygenated, even when part of complex natural products, pharmaceuticals, or biomass-derived platform molecules. The catalyst tolerates many functional groups including hydrogenation-sensitive examples. It is efficient, easy to handle, and conveniently synthesized from a specific bimetallic coordination compound and commercially available charcoal. Selective, sustainable, and cost-efficient deoxygenation under industrially viable conditions seems feasible.
Factors associated with longitudinal bone mineral density loss in a tobacco-exposed cohort

The prevalence of low bone mineral density (BMD) is increased in individuals with chronic obstructive pulmonary disease (COPD) independent of traditional osteoporosis risk factors. COPD-specific guidelines for BMD assessment do not exist and general guidelines for osteoporosis screening do not recognize COPD as a risk factor for fracture. Nonetheless, osteoporotic fractures are of major public health importance given the negative impact of fractures on morbidity and mortality in COPD patients. Furthermore, increased bone turnover independently contributes to fracture risk yet cannot be determined by cross-sectional dual x-ray absorptiometry (DXA) assessment alone. We established a longitudinal cohort of male and female smokers with and without smoking-related lung disease (i.e. emphysema or airflow obstruction) to determine factors related to accelerated BMD loss in smokers. We obtained baseline and 2-year measurements of pulmonary function, BMD, radiographic emphysema, and demographic and clinical characteristics. We assayed baseline blood samples for markers of bone metabolism, matrix metalloproteinases (MMP) and their inhibitors, interleukin-6, and tumor necrosis factor alpha. Of those with lung disease, 48.6% had evidence of osteopenia or osteoporosis at baseline compared to 29.4% without lung disease (p=0.01). The incidence of accelerated hip or lumbar spine BMD loss was 33.8% in subjects with lung disease versus 19.6% in those participants without lung disease (p=0.01). Both type I collagen C telopeptide (CTx), a marker of bone resorption, and radiographic emphysema were independent predictors of accelerated BMD loss (OR 5.5 [2.1,14.4] for moderate/severe emphysema; OR 2.9 [1.3,6.4] for highest tertile CTx) when adjusted for age, gender, steroid use, and current smoking status. Tissue inhibitor of matrix metalloproteinase (TIMP) 4 was independently associated with BMD decline at the hip (p=0.04) and higher in subjects with emphysema progression (p=0.03). TIMP1 and MMP7 levels were also higher in subjects with emphysema progression. These findings suggest that accessible and easily measured biomarkers may be used to guide early and serial DXA BMD assessments in a subset of smokers at risk for accelerated BMD decline. TIMP4 and MMPs may further be involved in the regulation of lung and bone matrix degradation in individuals with emphysema-related BMD decline.
Reduction of acute mild stress corticosterone response and changes in stress‐responsive gene expression in male Balb/c mice after repeated administration of a Rhodiola rosea L. root extract

Abstract Rhodiola rosea L. (R. rosea) is an adaptogenic plant increasing body resistance to stress. Its efficacy has been evidenced mainly in chronic stress models, data concerning its effect in acute stress and underlying mechanisms being scarce. The objective was to investigate the effect of repeated doses of a R. rosea hydroethanolic root extract (HRE) on hypothalamic pituitary adrenal response in a murine model of acute mild stress and also the mechanisms involved. Stress response was measured in Balb/c mice having received by gavage HRE (5 g/kg) or vehicle daily for 2 weeks before being submitted to an acute mild stress protocol (open‐field test then elevated plus maze). Corticosterone was measured in plasma from mandibular vein blood drawn before and 30, 60, and 90 min after initiation of the stress protocol. Mice were sacrificed at 90 min, and the hippocampus, prefrontal cortex, and amygdala were excised for high‐frequency RT‐PCR gene expression analysis. At 30 min after acute mild stress induction, corticosterone level in mice having received the HRE was lower than in control mice and comparable to that in nonstressed mice in the HRE group. HRE administration induced brain structure‐dependent changes in expression of several stress‐responsive genes implicated in neuronal structure, HPA axis activation, and circadian rhythm. In the acute mild stress model used, R. rosea HRE decreased corticosterone level and increased expression of stress‐responsive genes, especially in the hippocampus and prefrontal cortex. These findings suggest that R. rosea HRE could be of value for modulating reactivity to acute mild stress.
A Novel SLC1A4 Mutation (p.Y191*) Causes Spastic Tetraplegia, Thin Corpus Callosum, and Progressive Microcephaly (SPATCCM) With Seizure Disorder

Spastic tetraplegia, thin corpus callosum, and progressive microcephaly is a recently described very rare autosomal recessive neurodevelopmental disorder. This disease was first described in 2015 in several families from the Ashkenazi Jewish ancestry with a founder mutation in SLC1A4 (p.E256K) as the underlying genetic cause. SLC1A4 gene encodes for the amino acid transporter ASCT1 that is necessary for serine cellular transport to neurons. We clinically evaluated 2 Pakistani siblings with severe global developmental delay, progressive microcephaly, and seizure disorder. We performed exome sequencing, Sanger sequencing, and segregation analysis to identify the genetic cause of the phenotype followed by in silico analysis to evaluate the pathogenicity of the identified mutation. We identified a novel homozygous variant (c.573T>G) in both patients. The mutation is predicted to cause nonsense mutation (p.Y191*) in the ASCT1 protein. Here, we report the fifth disease causing mutation in SLC1A4 gene and review all previously reported cases.