Miracle-dz/UniFAR-FTUs huggingface dataset:
Foreign aid, institutional quality, and income inequality in Africa: A dynamic panel threshold approach

This study examines the impact of foreign aid and institutions on income inequality in 23 African countries during the period from 2005 to 2017. The study used a newly proposed novel dynamic panel threshold technique. The results of the study found an institutional quality threshold value of 1.622. Below the threshold, foreign aid was found to positively and significantly influence income inequality. However, above the threshold, the coefficient of foreign aid was negative with statistical significance. This implies that foreign aid tends to diminish income inequality in the presence of quality institutions. The study also used the quantile regression method to check for robustness. It showed that the conclusion between aid and inequality is the same in most of the quantiles (0.1 and 0.2). The findings can be worthwhile for sketching proper aid policies to lessen inequality. Policymakers in Africa should prioritize establishing high-quality institutions and developing measures to improve existing ones. Thus, aid could potentially reduce income inequality. This study suggests that it is important to note that aid programs can be effective when tailored to the particular needs and circumstances of each beneficiary country, as one-size-fits-all methods may not produce the anticipated outcomes.
Emergence of Respiratory Streptococcus agalactiae Isolates in Cystic Fibrosis Patients

Streptococcus agalactiae is a well-known pathogen for neonates and immunocompromized adults. Beyond the neonatal period, S. agalactiae is rarely found in the respiratory tract. During 2002–2008 we noticed S. agalactiae in respiratory secretions of 30/185 (16%) of cystic fibrosis (CF) patients. The median age of these patients was 3–6 years older than the median age CF patients not harboring S. agalactiae. To analyze, if the S. agalactiae isolates from CF patients were clonal, further characterization of the strains was achieved by capsular serotyping, surface protein determination and multilocus sequence typing (MLST). We found a variety of sequence types (ST) among the isolates, which did not substantially differ from the MLST patterns of colonizing strains from Germany. However serotype III, which is often seen in colonizing strains and invasive infections was rare among CF patients. The emergence of S. agalactiae in the respiratory tract of CF patients may represent the adaptation to a novel host environment, supported by the altered surfactant composition in older CF patients.
Household Water Handling Practices in the Arid and Semi-Arid Lands in Kenya

Utilisation of water from unimproved water sources coupled with inadequate access to sanitation can adversely affect human health. This study undertaken from November 2014 to March, 2015 sought to assess the household water handling practices and relate them to the prevalent diseases in Baringo Central and South, Kenya. A Household sanitary survey was conducted and questionnaires were administered to 100 household heads within the study area. The data was analysed using descriptive and inferential statistics. The results indicated that 72% of the households (n = 100) collected water for cooking and drinking from the water pans. Only 34% of the households treated water commonly using boiling (19%), filtration with cloth (2%), chlorine (11%) before using it for drinking. There was a positive correlation between methods used in accessing water from drinking water storage containers and water related diseases prevalent in the study area (p < 0.05). Household drinking water in the study area did not meet the WHO drinking water quality guidelines mainly due to poor handling practices at the household level. There is a need to promote water, sanitation and hygiene campaigns in the study area to prevent water related diseases at the household level.
Multiple Avirulence Loci and Allele-Specific Effector Recognition Control the Pm3 Race-Specific Resistance of Wheat to Powdery Mildew[OPEN]

Three genetically interacting loci in wheat powdery mildew regulate avirulence to six alleles of Pm3, where recognition of an allele-specific effector mediates race-specific avirulence. In cereals, several mildew resistance genes occur as large allelic series; for example, in wheat (Triticum aestivum and Triticum turgidum), 17 functional Pm3 alleles confer agronomically important race-specific resistance to powdery mildew (Blumeria graminis). The molecular basis of race specificity has been characterized in wheat, but little is known about the corresponding avirulence genes in powdery mildew. Here, we dissected the genetics of avirulence for six Pm3 alleles and found that three major Avr loci affect avirulence, with a common locus_1 involved in all AvrPm3-Pm3 interactions. We cloned the effector gene AvrPm3a2/f2 from locus_2, which is recognized by the Pm3a and Pm3f alleles. Induction of a Pm3 allele-dependent hypersensitive response in transient assays in Nicotiana benthamiana and in wheat demonstrated specificity. Gene expression analysis of Bcg1 (encoded by locus_1) and AvrPm3 a2/f2 revealed significant differences between isolates, indicating that in addition to protein polymorphisms, expression levels play a role in avirulence. We propose a model for race specificity involving three components: an allele-specific avirulence effector, a resistance gene allele, and a pathogen-encoded suppressor of avirulence. Thus, whereas a genetically simple allelic series controls specificity in the plant host, recognition on the pathogen side is more complex, allowing flexible evolutionary responses and adaptation to resistance genes.
Prevalence and Prognostic Significance of Heart Failure Stages: Application of the American College of Cardiology/American Heart Association Heart Failure Staging Criteria in the Community

Background— Heart failure (HF) is a progressive disorder associated with frequent morbidity and mortality. An American Heart Association/American College of Cardiology staging classification of HF has been developed to emphasize early detection and prevention. The prevalence of HF stages and their association with mortality are unknown. We sought to estimate HF stage prevalence in the community and to measure the association of HF stages with mortality. Methods and Results— A population-based, cross-sectional, random sample of 2029 Olmsted County, Minnesota, residents aged ≥45 years was identified. Participants were classified by medical record review, symptom questionnaire, physical examination, and echocardiogram as follows: stage 0, healthy; stage A, HF risk factors; stage B, asymptomatic cardiac structural or functional abnormalities; stage C, HF symptoms; and stage D, severe HF. In the cohort, 32% were stage 0, 22% stage A, 34% stage B, 12% stage C, and 0.2% stage D. Mean B-type natriuretic peptide concentrations (in pg/mL) increased by stages: stage 0=26, stage A=32, stage B=53, stage C=137, and stage D=353. Survival at 5 years was 99% in stage 0, 97% in stage A, 96% in stage B, 75% in stage C, and 20% in stage D. Conclusions— The present study provides prevalence estimates and prognostic validation for HF staging in a community cohort. Of note, 56% of adults ≥45 years of age were classified as being in stage A (risk factors) or B (asymptomatic ventricular dysfunction). HF staging underscores the magnitude of the population at risk for progression to overt HF.
Inhibition of DPP4 activity in humans establishes its in vivo role in CXCL10 post‐translational modification: prospective placebo‐controlled clinical studies

Biochemical experiments, animal models, and observational studies in humans all support a role of dipeptidyl peptidase 4 (DPP4) in the N‐terminal truncation of CXCL10, which results in the generation of an antagonist form of the chemokine that limits T‐cell and NK cell migration. Motivated by the ability to regulate lymphocyte trafficking in vivo, we conducted two prospective clinical trials to test the effects of DPP4 inhibition on CXCL10 processing in healthy donors and in chronic hepatitis C patients, a disease in which DPP4 levels are found to be elevated. Participants were treated daily with 100 mg sitagliptin, a clinically approved DPP4 inhibitor. Plasma samples were analyzed using an ultrasensitive single‐molecule assay (Simoa) to distinguish the full‐length CXCL101–77 from the NH2‐truncated CXCL103–77, as compared to the total CXCL10 levels. Sitagliptin treatment resulted in a significant decrease in CXCL103–77 concentration, a reciprocal increase in CXCL101–77, with only minimal effects on total levels of the chemokine. These data provide the first direct evidence that in vivo DPP4 inhibition in humans can preserve the bioactive form of CXCL10, offering new therapeutic opportunities for DPP4 inhibitors.
A Practical Approach to Adaptive Coding for the Three-Node Relay Channel

In this paper we propose a new adaptive coding scheme for distributed channel coding for the three-node relay channel. In order to make it feasible for application in wireless sensor networks, the distributed code is built from standard components like Turbo and convolutional codes, and adaptation at the relay is obtained by puncturing the input and output of the employed channel code. The proposed code structure includes distributed Turbo codes and distributed serially concatenated codes as special cases. As the results of our optimization show, significant improvements in terms of rate and coverage are obtained. Compared to theoretical limits a decent performance is achieved considering that the focus is on feasibility.
Prediction of User Ratings of Oral Presentations using Label Relations

Predicting the users' impressions on a video talk is an important step for recommendation tasks. We propose a method to accurately predict multiple impression-related user ratings for a given video talk. Our proposal considers (a) multimodal features including linguistic as well as acoustic features, (b) correlations between different user ratings (labels), and (c) correlations between different feature types. In particular, the proposed method models both label and feature correlations within a single Markov random field (MRF), and jointly optimizes the label assignment problem to obtain a consistent and multiple set of labels for a given video. We train and evaluate the proposed method using a collection of 1,646 TED talk videos for 14 different tags. Experimental results on this dataset show that the proposed method obtains a statistically significant macro-average accuracy of 93.3%, outperforming several competitive baseline methods.
Comparison of the effect between pegaptanib and ranibizumab on exudative age-related macular degeneration with small lesion size

Purpose To compare the effect of pegaptanib versus ranibizumab on exudative age-related macular degeneration (AMD) with small lesion size. Methods This is a retrospective study of 81 eyes from 78 patients with exudative AMD treated and followed up over 12 months. Patients with baseline best corrected visual acuity (BCVA) under 20/400 and with a greatest linear dimension of lesion over 4500 μm were excluded from the study. Twenty-six eyes from 25 patients were treated with three consecutive intravitreal injections of pegaptanib (IVP group) and 55 eyes from 54 patients were treated with three consecutive ranibizumab injections (IVR group). Each therapy was repeated as needed. The alteration in BCVA was evaluated in the IVP and IVR groups. Results No differences were detected in baseline parameters between the IVP and IVR groups. The mean BCVA (logMAR) at month 1, 3, 6 and 12 after the initial treatment was improved from baseline in the IVP group (−0.095, −0.17, −0.18 and −0.18, respectively) and in the IVR group (−0.077, −0.15, −0.17 and −0.11, respectively), which was statistically significant. There was no difference in the change in mean BCVA between IVP and IVR groups at the same time periods. Conclusions The visual outcome of IVP was equivalent with IVR in exudative AMD with small lesion size.
Bhattacharyya distance based emotional dissimilarity measure in multi-dimensional space for emotion classification

Emotion classiﬁcation is essential for understanding human interactions and hence is an important module in Human-Computer Interaction (HCI) systems. Well-performed emotion classiﬁcation systems have potential to integrate into the HCI systems to provide additional user state details. This paper presents an emotion classiﬁcation system that employs Emotional Dissimilarity (ED) measure. Instead of measuring ED in Single Dimensional (SD) space, we propose an approach to measure ED in Multi-Dimensional (MD) space. Proposed approach measures ED between emotions using GMM-SVM kernel with Bhattacharyya based GMM distance. In addition, we also formulate ED measure using GMM-SVM kernel with Kull-back Leibler (KL) based GMM distance. We observe the effectiveness of employing ED measure in MD space over that in SD space using different kernels. Experiments were conducted using SVM classiﬁer to classify emotions of anger, happiness, neutral and sadness. We achieve average accuracy of 81.25% for speaker independent emotion classiﬁcation.
Multilineage hematopoietic progenitor activity generated autonomously in the mouse yolk sac: analysis using angiogenesis-defective embryos.

The capacity of the yolk sac to generate multilineage, adult-type hematopoiesis was investigated in vivo using vascular endothelial-cadherin deficient embryos. In these mutants, the yolk sac is not connected to the vasculature of the embryo and therefore all hematopoietic activity detected therein is intrinsic to the yolk sac and not derived from intraembryonic sources. At embryonic days 9.5 and 10.5, the yolk sac contains blood cells from the first wave of hematopoiesis, i.e. primitive erythrocytes and monocytes, but also multipotent progenitors from definitive hematopoiesis and a few granulocytes. Reverse transcription-polymerase chain reaction analysis revealed expression of specific genes of all lineages except lymphoid cells. Moreover, hematopoietic colony assays showed the existence of committed progenitors of the second wave of embryonic hematopoiesis, namely for definitive erythrocytes, megakaryocytes, granulocytes and monocytes. Conversely, the number of lymphocytes after lymphoid culture was insignificant. Our data provide evidence for multilineage hematopoiesis (but not lymphopoiesis) in the yolk sac in the absence of seeding from the embryo. The small number of definitive mature blood cells indicates however that the yolk sac is not an effective environment for the terminal differentiation of committed progenitors from the second wave of hematopoiesis.
THE EFFECT OF FINANCIAL DEEPENING, FOREIGN DIRECT INVESTMENT, AND INTEREST RATES ON ECONOMIC GROWTH IN INDONESIA

Economic growth determines the extent to which the activities of the economy are able to manifest additional income and sustainable economic development. Therefore, it cannot be separated from the existence of the financial sector, foreign direct investment, and interest rates for the economy. This study aims to determine the effect of financial deepening, foreign direct investment, and interest rates on economic growth in Indonesia in 1988-2020. Empirically, this study uses time series data with the Error Correction Model Engle-Granger (ECM-EG) method. The results show that financial deepening, FDI, and interest rates have a significant effect on economic growth. The variables of FDI and interest rates have a positive and significant effect on economic growth, while financial deepening has a negative and significant effect on economic growth. Likewise, national economic policies must be directed at maintaining overall economic activity and achieving sustainable growth.
Computed Tomography Imaging Features in Acute Uncomplicated Stanford Type-B Aortic Dissection Predict Late Adverse Events

Background— Medical treatment of initially uncomplicated acute Stanford type-B aortic dissection is associated with a high rate of late adverse events. Identification of individuals who potentially benefit from preventive endografting is highly desirable. Methods and Results— The association of computed tomography imaging features with late adverse events was retrospectively assessed in 83 patients with acute uncomplicated Stanford type-B aortic dissection, followed over a median of 850 (interquartile range 247–1824) days. Adverse events were defined as fatal or nonfatal aortic rupture, rapid aortic growth (>10 mm/y), aneurysm formation (≥6 cm), organ or limb ischemia, or new uncontrollable hypertension or pain. Five significant predictors were identified using multivariable Cox regression analysis: connective tissue disease (hazard ratio [HR] 2.94, 95% confidence interval [CI]: 1.29–6.72; P=0.01), circumferential extent of false lumen in angular degrees (HR 1.03 per degree, 95% CI: 1.01–1.04, P=0.003), maximum aortic diameter (HR 1.10 per mm, 95% CI: 1.02–1.18, P=0.015), false lumen outflow (HR 0.999 per mL/min, 95% CI: 0.998–1.000; P=0.055), and number of intercostal arteries (HR 0.89 per n, 95% CI: 0.80–0.98; P=0.024). A prediction model was constructed to calculate patient specific risk at 1, 2, and 5 years and to stratify patients into high-, intermediate-, and low-risk groups. The model was internally validated by bootstrapping and showed good discriminatory ability with an optimism-corrected C statistic of 70.1%. Conclusions— Computed tomography imaging-based morphological features combined into a prediction model may be able to identify patients at high risk for late adverse events after an initially uncomplicated type-B aortic dissection.
The relation between statistical power and inference in fMRI

Statistically underpowered studies can result in experimental failure even when all other experimental considerations have been addressed impeccably. In fMRI the combination of a large number of dependent variables, a relatively small number of observations (subjects), and a need to correct for multiple comparisons can decrease statistical power dramatically. This problem has been clearly addressed yet remains controversial—especially in regards to the expected effect sizes in fMRI, and especially for between-subjects effects such as group comparisons and brain-behavior correlations. We aimed to clarify the power problem by considering and contrasting two simulated scenarios of such possible brain-behavior correlations: weak diffuse effects and strong localized effects. Sampling from these scenarios shows that, particularly in the weak diffuse scenario, common sample sizes (n = 20–30) display extremely low statistical power, poorly represent the actual effects in the full sample, and show large variation on subsequent replications. Empirical data from the Human Connectome Project resembles the weak diffuse scenario much more than the localized strong scenario, which underscores the extent of the power problem for many studies. Possible solutions to the power problem include increasing the sample size, using less stringent thresholds, or focusing on a region-of-interest. However, these approaches are not always feasible and some have major drawbacks. The most prominent solutions that may help address the power problem include model-based (multivariate) prediction methods and meta-analyses with related synthesis-oriented approaches.
Cross-Talk between Cancer Cells and the Tumour Microenvironment: The Role of the 5-Lipoxygenase Pathway

5-lipoxygenase is an enzyme responsible for the synthesis of a range of bioactive lipids signalling molecules known collectively as eicosanoids. 5-lipoxygenase metabolites such as 5-hydroxyeicosatetraenoic acid (5-HETE) and a number of leukotrienes are mostly derived from arachidonic acid and have been shown to be lipid mediators of inflammation in different pathological states including cancer. Upregulated 5-lipoxygenase expression and metabolite production is found in a number of cancer types and has been shown to be associated with increased tumorigenesis. 5-lipoxygenase activity is present in a number of diverse cell types of the immune system and connective tissue. In this review, we discuss potential routes through which cancer cells may utilise the 5-lipoxygenase pathway to interact with the tumour microenvironment during the development and progression of a tumour. Furthermore, immune-derived 5-lipoxygenase signalling can drive both pro- and anti-tumour effects depending on the immune cell subtype and an overview of evidence for these opposing effects is presented.
A Way out of the Odyssey: Analyzing and Combining Recent Insights for LSTMs

LSTMs have become a basic building block for many deep NLP models. In recent years, many improvements and variations have been proposed for deep sequence models in general, and LSTMs in particular. We propose and analyze a series of architectural modifications for LSTM networks resulting in improved performance for text classification datasets. We observe compounding improvements on traditional LSTMs using Monte Carlo test-time model averaging, deep vector averaging (DVA), and residual connections, along with four other suggested modifications. Our analysis provides a simple, reliable, and high quality baseline model.
The Athens System for Novel Information Discovery

Discovering novel information, that is information whose existence is not suspected or for which suitable descriptors are not known, is di‐cult in large information repositories. The Athens system flnds novel information, given an initial set of keywords representing known information, using a focused and contextualized search. We present the design of the system and show its use in a number of difierent settings.
Near-Optimal Scheduling of Distributed Algorithms

This paper studies the question of how to run many distributed algorithms, solving independent problems, together as fast as possible. Suppose that we want to run distributed algorithms A_1, . , A_k in the CONGEST model, each taking at most $dilation$ rounds, and where for each network edge, at most $congestion$ messages need to go through it, in total over all these algorithms. A celebrated work of Leighton, Maggs, and Rao[Combinatorica 1994] shows that in the special case where each of these algorithms is simply a packet routing---that is, sending a message from a source to a destination along a given path---there is an $O(congestion+dilation)$ round schedule. Note that this bound is trivially optimal. Generalizing the framework of LMR, we study scheduling general distributed algorithms and present two results: (a) an existential schedule-length lower bound of Ω(congestion + dilation log n/log log n) rounds, (b) a distributed algorithm that produces a near-optimal O(congestion + dilation log n) round schedule, after O(dilation log2 n) rounds of pre-computation. A key challenge in the latter result is to solve the problem with only private randomness, as globally-shared randomness simplifies it significantly. The technique we use for this problem is in fact more general, and it can be used to remove the assumption of having shared randomness from a broad range of distributed algorithms, at the cost of a slow down factor of O(log2 n).