Miracle-dz/UniFAR-FTUs huggingface dataset:
The Barriers to Achieve Financial Protection in Iranian Health System: A Qualitative Study in a Developing Country

Background The move to universal health coverage and consequently health promotion is influenced by political, socio-economic and other contextual factors in a country. Iran, as a developing country with an upper-middle national income, has developed policies to achieve universal health coverage through financial protection. This study aims to investigate barriers to develop financial protection as a requirement to achieve universal health coverage. Materials and Methods This qualitative study was conducted using 20 in-depth interviews with experts in social welfare, health insurance and financing. The framework analysis method was used to analyze the data. Results The results have been categorized in three major themes that were extracted from ten sub-themes. The major themes included the political, social and economic context of the country, the context and structure of healthcare system and dimensions of UHC. Conclusion Achieving financial protection as a long-term objective should be considered as a priority among Iranian policy makers that requires an inter-sectoral collaboration with a defined in-charge body. Health policy makers in Iran should develop a more comprehensive benefits package for diseases and health conditions with catastrophic consequences. They also should develop a plan to cover the poor people.
Dissociable Roles of Dopamine Within the Core and Medial Shell of the Nucleus Accumbens in Memory for Objects and Place

There is increasing focus on the role of the nucleus accumbens (NAc) in learning and memory, but there is little consensus as to how the core and medial shell subregions of the NAc contribute to these processes. In the current experiments, we used spontaneous object recognition to test rats with 6-hydroxydopamine lesions targeted at the core or medial shell of the NAc on a familiarity discrimination task and a location discrimination task. In the object recognition variant, control animals were able to discriminate the novel object at both 24-hr and 5-min delay. However, in the lesion groups, performance was systematically related to dopamine (DA) levels in the core but not the shell. In the location recognition task, sham-operated animals readily detected the object displacement at test. In the lesion groups, performance impairment was systematically related to DA levels in the shell but not the core. These results suggest that dopamine function within distinct subregions of the NAc plays dissociable roles in the modulation of memory for objects and place.
Embed user values in system architecture: The Declaration of System Usability

The underlying architecture of complex software products profoundly influences their direction and usability. This paper shares an effort to embed usability within the architecture of complex network products. We began by attempting to build a conceptual model, but we ended by representing customers' and users' values in a Declaration of System Usability to guide product direction and system architecture decisions.
An evaluation and enhancement of densitometric fragmentation for content slicing reuse

Content slicing addresses the need of adaptive systems to reuse open corpus material by converting it into re-composable information objects. However this conversion is highly dependent upon the ability to correctly fragment pages into structurally sound atomic pieces. A recently suggested approach to fragmentation, which relies on densitometric page representation, claims to achieve high accuracy and time performance. Although it has been well received within the research community, a full evaluation of this approach and identification of strengths and weaknesses across a range of characteristics hasn't been performed. This paper proposes an independent evaluation of the approach with respect to granularity control, accuracy, time performance, content diversity and linguistic dependency. Moreover, this paper also provides a significant contribution to address important weaknesses discovered during the analysis, in order to improve the suitability and impact of the original algorithm within the context of content slicing.
Bio‐inspired packet dropping for ad‐hoc social networks

Ad‐hoc social networks (ASNETs) explore social properties of nodes in communications. The usage of various social applications in a resource‐scarce environment and the dynamic nature of the network create unnecessary congestion that might degrade the quality of service dramatically. Traditional approaches use drop‐tail or random‐early discard techniques to drop data packets from the intermediate node queue. Nonetheless, because of the unavailability of the social properties, these techniques are not suitable for ASNETs. In this paper, we propose a Bio‐inspired packet dropping (BPD) algorithm for ASNETS. BPD imitates the matching procedure of receptors and epitopes in immune systems to detect congestions. The drop probability settings depend on the selection of data packets, which is based on node popularity level. BPD selects the most prioritized node through social properties, which is inspired by the B‐cell stimulation in immune systems. To fairly prioritize data packets, two social properties are used: (1) similarity and (2) closeness centrality between nodes. Extensive simulations are carried out to evaluate and compare BPD to other existing schemes in terms of mean goodput, mean loss rate, throughput, delay, attained bandwidth, and overhead ratio. The results show that the proposed scheme outperforms these existing schemes. Copyright © 2014 John Wiley & Sons, Ltd.
CXCR7 Protein Expression in Human Adult Brain and Differentiated Neurons

Background CXCR7 and CXCR4 are receptors for the chemokine CXCL12, which is involved in essential functions of the immune and nervous systems. Although CXCR7 transcripts are widely expressed throughout the central nervous system, little is known about its protein distribution and function in the adult brain. To evaluate its potential involvement in CXCL12/CXCR4 signaling in differentiated neurons, we studied CXCR7 protein expression in human brain and cultured neurons. Methodology/Principal Findings Immunohistochemistry and RT-PCR analyses of cortex and hippocampus from control and HIV-positive subjects provided the first evidence of CXCR7 protein expression in human adult neurons, under normal and pathological conditions. Furthermore, confocal microscopy and binding assays in cultured neurons show that CXCR7 protein is mainly located into cytoplasm, while little to no protein expression is found on neuronal plasma membrane. Interestingly, specific CXCR7 ligands that inhibit CXCL12 binding to CXCR7 do not alter CXCR4-activated survival signaling (pERK/pAkt) in rat cortical neurons. Neuronal CXCR7 co-localizes to some extent with the endoplasmic reticulum marker ERp29, but not with early/late endosome markers. Additionally, large areas of overlap are detected in the intracellular pattern of CXCR7 and CXCR4 expression. Conclusions/Significance Overall, these results implicate CXCR4 as the main CXCL12 signaling receptor on the surface of differentiated neurons and suggest that CXCR7 may interact with CXCR4 at the intracellular level, possibly affecting CXCR4 trafficking and/or coupling to other proteins.
Real-Time Multi-Object Tracking using Random Finite Sets

The multi-object Bayes (MOB) filter uses random finite sets (RFSs) to represent a scene. A drawback of this filter is the computational complexity of the multi-object likelihood function. In this contribution, an approximation of the multi-object likelihood function is presented allowing for real-time implementation on a graphics processing unit using sequential Monte Carlo (SMC) methods. Additionally, a track extraction algorithm using clustering as well as an approach to determine the existence probability of each single object are proposed.
Microwave-assisted preparation of self-doped TiO2 nanotube arrays for enhanced photoelectrochemical water splitting

We report a microwave-assisted chemical reduction method with NaBH4 to prepare bulk abundant Ti3+ self-doped TiO2 nanotube arrays (MR-TNTs). UV-vis diffuse reflection spectra show that the light absorption spectrum range of MR-TNTs extends from the UV to visible light region and the electrochemical impedance spectra indicate that the induced oxygen vacancies of MR-TNTs enhance their electrical conductivity as well as charge transfer. The MR-TNTs show an 8-fold increase in visible light photocurrent density compared to the pristine TNTs, and the optimized saturation photocurrent density and photoconversion efficiency under AM1.5 irradiation are identified to be 3.05 mA cm−2 at 1.23 V vs. RHE and 1.66% respectively, which are the highest values ever reported for doped TNT photoelectrodes. The incident photon to current conversion efficiency (IPCE) spectrum increases both in UV and visible light regions. Moreover, the MR-TNTs exhibit much more stable PEC performance than the NaBH4 treated TNTs without microwave assistance, which is attributed to the self-doped Ti3+ mainly existing in the bulk rather than on the surface.
Convolutive Blind Source Separation of Speech Signals in the Low Frequency Bands

Sub-band methods are often used to address the problem of convolutive blind speech separation, as they offer the computational advantage of approximating convolutions by multiplications. The computational load, however, often remains quite high, because separation is performed on several sub-bands. In this paper, we exploit the well known fact that the high frequency content of speech signals typically conveys little information, since most of the speech power is found in frequencies up to 4kHz, and consider separation only in frequency bands below a certain threshold. We investigate the effect of changing the threshold, and find that separation performed only in the low frequencies can lead to the recovered signals being similar in quality to those extracted from all frequencies.
Effects of Annealling Treatment on the Properties of TiO2/ZnO Thin Film Prepared by Simultaneous RF-Magnetron Sputtering

In this work, TiO2/ZnO nanocomposite films were prepared by simultaneous RF-magnetron sputtering of ZnO and TiO2 targets. The influences of annealing temperature on the properties of the TiO2/ZnO films were investigated. The crystal structure of the deposited TiO2/ZnO films was hexagonal wurtzite at (002) and (101) peaks and the films were highly oriented along the c-axis perpendicular to the substrate. The photoluminescence (PL) spectrum reveals the appearance of two emission peaks from the deposited film that are centred at 384 and 591 nm. The structural, electrical, and optical properties of TiO2/ZnO films were strongly dependent on the annealing temperature. With increasing of the annealing temperature, the optical properties (i.e., UV, transmittance, energy band-gap and crystalline quality) were also improved. However, when the annealing is relatively high (≥ 500° C), the intensity of the optical properties and crystalline quality slightly decreases. The annealing temperature of (≥ 500° C) becoming the threshold temperature limits for the TiO2/ZnO film. The results obtained herein suggest that selecting the appropriate annealing temperature become a key factor for tuning the most desired properties from the as-prepared TiO2/ZnO thin films.
A Hybrid Strategy for Chinese Domain-Specific Terminology Extraction

Automatic Term Extraction is an important issue in Natural Language Processing. This paper presents a new approach of terminology extraction combining with machine learning based on cascaded conditional random fields and corpus-based statistical model. In this approach, firstly, the low-layer and high-layer conditional random fields (CRFs) are used to extract the simple and compound terminologies respectively. Then, Domain Relevance (DR) and Domain Consensus (DC) degrees are calculated to acquire the final domain terminologies. Experimental results show that the precision, recall and F-score are 83.29%, 80.75%, 82.01% respectively. The comparison with CRFs and MI+T-value shows that the proposed method for extracting terminology is effective.
Improved weighted least squares algorithm for the design of quadrature mirror filters

This paper presents an improved weighted least squares (WLS) algorithm for the design of quadrature mirror filters (QMFs), First, a new term is incorporated into the objective function that effectively prevents an optimization algorithm from producing suboptimal QMFs. These suboptimal QMFs exhibit a transition band anomaly; the frequency responses of the filters have large oscillatory components in the transition band. The new term can be applied to the WLS design of any FIR filter to prevent a similar transition band anomaly. Next, we present an algorithm to obtain the QMF coefficients that minimize the objective function incorporating the new term. The computational requirement of this algorithm is also briefly discussed. Last, we include a set of practical design rules for use with our algorithm. These rules simplify the design process by providing good estimation of the design parameters, such as the minimum filter length, to meet a given set of QMF specifications.
Microbiota and Host Nutrition across Plant and Animal Kingdoms Figure 1. Physiological Functions of the Plant Roots and Human Gut in Nutrient Uptake, Spatial Aspects of Microbiota Composition, and Factors Driving Community Establishment

Plants and animals each have evolved specialized organs dedicated to nutrient acquisition, and these harbor specific bacterial communities that extend the host's metabolic repertoire. Similar forces driving microbial community establishment in the gut and plant roots include diet/soil-type, host genotype, and immune system as well as microbe-microbe interactions. Here we show that there is no overlap of abundant bacterial taxa between the microbiotas of the mammalian gut and plant roots, whereas taxa overlap does exist between fish gut and plant root communities. A comparison of root and gut microbiota composition in multiple host species belonging to the same evolutionary lineage reveals host phylogenetic signals in both eukaryotic kingdoms. The reasons underlying striking differences in microbiota composition in independently evolved, yet functionally related, organs in plants and animals remain unclear but might include differences in start inoculum and niche-specific factors such as oxygen levels, temperature, pH, and organic carbon availability. Physiological Functions of the Vertebrate Gut and Plant Roots The vertebrate gut and plant roots evolved independently in animal and plant kingdoms but serve a similar primary physiological function in nutrient uptake (Figure 1). One major difference between plant and animal nutritional modes is their distinct energy production strategy. Plants are autotrophs, producing their own energy through photosynthesis (carbohydrate photo-assimilates), while animals rely entirely on the energy originally captured by other living organisms (heterotrophs). Long-distance transport mechanisms ensure the distribution of carbohydrate photo-assimilates from chloroplasts in leaves to all other body parts, including roots. Nutrient acquisition by roots to support plant growth is therefore almost exclusively limited to uptake of mineral ions and water from soil. In contrast, the mammalian gut has evolved to facilitate the uptake of simple sugars, amino acids, lipids, and vitamins in addition to ions. It is typically compartmentalized into sections with low microbial biomass in which the products of host enzymatic activity are absorbed (i.e., the human small intestine, SI) and a section for the uptake of microbe-derived fermentation products (human large intestine or hindgut, LI). A significant fraction of the soil nutritive complement and of the dietary intake remains unavailable for plants and animals, respectively, and this defines their dietary constraints. Critical nutrients for plant growth and productivity in soil are nitrogen and phosphorus. However, plant roots can absorb only inorganic nitrogen and orthophosphate (Pi), although phosphorus is abundant in soil both in inorganic and organic pools. Pi can be assimilated via low-Pi-inducible (high-affinity) and …
An Empirical Study of BI-based Corporate Performance Management in North America and East Asia

Managing corporate performance is an important yet challenging process. Recently, many enterprises have adopted business intelligence (BI) tools to facilitate more effective corporate performance management. Based on a survey with 290 organizations across North America and East Asia, this paper presents empirical evidence on the key benefits of and barriers to BI-based corporate performance management (CPM). The study reveals that the implementation of BI-based CPM faces multi-dimensional challenges. Organizations in East Asia perceived higher CPM benefits as well as higher CPM barriers than their counterparts in North America. Cultural, economic and environmental differences between the two regions explain these issues. The research findings offer important insights for multinational organizations that are planning or are in the process of implementing or reviewing their BI-based CPM, as well as for consulting companies that are assisting with CPM implementation in different countries.
The flapping-flag instability as a nonlinear eigenvalue problem

We reconsider the classical problem of the instability of a flapping flag in an inviscid background flow with a vortex sheet wake, and reformulate it as a nonlinear eigenvalue problem. We solve the problem numerically for the 20 lowest wave number modes. We find that the lowest wave number mode is the first to become unstable, and has the fastest growth rate within 3.5 decades of the stability boundary in the parameter space of flag mass and flag rigidity. This and subsequent modes become unstable by merging into complex-conjugate pairs, which then lose conjugacy further into the region of instability. Eigenmodes exhibit sharp transitions in shape across the stability boundary. In the corresponding initial value problem, we show a correlation between the wave number of unstable modes in the small-amplitude (growth) regime and the large-amplitude (saturation) regime. Wave number increases with decreasing rigidity and shows a combination of discrete and continuous change in the shape of unstable modes. Usin.
Firm Heterogeneity and the Geography of International Trade

A key distinction which has emerged from heterogeneous firm models of international trade is that of exporting at the intensive and extensive margins. Empirically however, the two are often conflated, leading to biased estimates of the impact of falling trade costs. This paper exploits detailed firm level data, which includes information on the destination of exports to investigate causal links between enterprise productivity and the number of markets a firm serves as well as the relative size of those markets. Our focus is Sweden’s Food and Beverage sector, which is not only highly open, but has been subject to policy induced changes in trade costs (as well as falling natural barriers) over our sample period. We have data on almost 10,000 firm / time / destination observations across 6 years and 138 destinations. Our results confirm that conflating adjustment at the internal and external margins does bias trade resistance effects. Combining detailed firm specific information with data on destination characteristics confirms the importance of a range of country specific characteristics (including exchange rate risk) and facilitates the estimation of both distance and market size elasticities, from firm level data.
THE PERMEABILITY OF GLOMERULAR CAPILLARIES TO GRADED DEXTRANS

Graded dextrans have been used as tracers to identify the primary permeability barrier(s) to macromolecules among the structural elements (endothelium, mesangium, basement membrane, epithelium) of the glomerular capillary wall. Three narrow-range fractions of specified molecular weights and Einstein-Stokes radii (ESR) were prepared by gel filtration: (a) 32,000 mol wt, ESR = 38 Å; (b) 62,000 mol wt, ESR = 55 Å; and (c) 125,000 mol wt, ESR = 78 Å. These fractions are known to be extensively filtered, filtered in only small amounts, and largely retained, respectively, by the glomerular capillaries. Tracer solutions were infused i.v. into Wistar-Furth rats, and the left kidney was fixed after 5 min to 4 h. The preparations behaved as predicted: initially, all three fractions appeared in the urinary spaces, with 32,000 > 62,000 » 125,000. The smallest fraction was totally cleared from the blood and urinary spaces by 2.5 h, whereas the intermediate and largest fractions were retained in the circulation at high concentrations up to 4 h. With all fractions, when particles occurred in high concentration in the capillary lumina, they were present in similarly high concentrations in the endothelial fenestrae and inner (subendothelial) portions of the basement membrane, but there was a sharp drop in their concentration at this level—i.e., between the inner, looser portions of the basement membrane and its outer, more compact portions. With the two largest fractions, accumulation of particles occurred against the basement membrane in the mesangial regions with time. No accumulation was seen with any of the fractions in the epithelial slits or against the slit membranes. Dextran was also seen in phagosomes in mesangial cells, and in absorption droplets in the glomerular and proximal tubule epithelium. It is concluded that the basement membrane is the main glomerular permeability barrier to dextrans, and (since their behavior is known to be similar) to proteins of comparable dimensions (40,000–200,000 mol wt). The findings are discussed in relation to previous work using electron-opaque tracers to localize the glomerular permeability barrier and in relation to models proposed for the functions of the various glomerular structural elements.
Regularizing BWGC/NGARCH Model by Quantum Minimization

A hybrid BPNN-weighted grey-C3LSP prediction (BWGC) is used for resolving the overshooting phenomenon significantly; however, it may lose the localization once volatility clustering occurs. Thus, we propose a compensation to deal with the time-varying variance in the residual errors, that is, incorporating a non-linear generalized autoregressive conditional heteroscedasticity (NGARCH) into BWGC, and quantum minimization is employed to regularize the smoothing coefficients for both BWGC and NGARCH to effectively improve model's robustness as well as to highly balance the generalization and the localization