Miracle-dz/UniFAR-FTUs huggingface dataset:
University of Birmingham Clinical effectiveness and cost-effectiveness of pegvisomant for the treatment of acromegaly: a systematic review and economic evaluation

Background: Acromegaly, an orphan disease usually caused by a benign pituitary tumour, is characterised by hyper-secretion of growth hormone (GH) and insulin-like growth factor I (IGF-1). It is associated with reduced life expectancy, cardiovascular problems, a variety of insidiously progressing detrimental symptoms and metabolic malfunction. Treatments include surgery, radiotherapy and pharmacotherapy. Pegvisomant (PEG) is a genetically engineered GH analogue licensed as a third or fourth line option when other treatments have failed to normalise IGF-1 levels. Methods: Evidence about effectiveness and cost-effectiveness of PEG was systematically reviewed. Data were extracted from published studies and used for a narrative synthesis of evidence. A decision analytical economic model was identified and modified to assess the cost-effectiveness of PEG. Results: One RCT and 17 non-randomised studies were reviewed for effectiveness. PEG substantially reduced and rapidly normalised IGF-1 levels in the majority of patients, approximately doubled GH levels, and improved some of the signs and symptoms of the disease. Tumour size was unaffected at least in the short term. PEG had a generally safe adverse event profile but a few patients were withdrawn from treatment because of raised liver enzymes. An economic model was identified and adapted to estimate the lower limit for the cost-effectiveness
Floristic diversity and management of fodder resources of the natural pastures of the Savanna Highlands of Western Cameroon

Sustainable management of pastoral resources requires knowledge in terms of floristic diversity and productivity of the rangelands. The objective of the present study carried out in the Bamboutos Mountains was to assess the floristic diversity and carrying capacity of the natural pastures. Floristic inventory was done using the method of quadrat point aligned in 15 plots of 400 m2. Aerial phytomass of herbaceous plants was measured by the full harvest method. A total of 74 species, including 09 woody plants belonging to 56 genera and 20 families were recorded. The number of taxa recorded in the plots varied from 11 to 36 species. Imperata cylindrica with a specific contribution of presence of 17.45% was the most abundant species in the rangeland. The species-richest families were Poaceae, Fabaceae, Asteraceae and Cyperaceae. The calculated pastoral value of the pasture was 56.21%. These pastures were dominated by phanerophytes (29.72%) and therophytes (24.32%). The forage productivity of the grazed area, estimated based on the regrowth biomass was 6498.57 kg DM/ha while the carrying capacity of the rangeland was 2.31 TLU/ha. These results showed that the fodder potential of the Bamboutos Mountains is enough diversified but remains under exploited.
Higher education funding, welfare and inequality in equilibrium

This paper analyses theoretically and quantitatively the ei¬€ect that dii¬€erent higher education funding policies have on welfare (on aggregate and at the individual level) and wealth inequality. A heterogeneous agent model in continuous time, which has uninsurable income risk and endogenous educational choice is used to evaluate i¬ ve dii¬€erent higher education i¬ nancing schemes. Educational investments can be self i¬ nanced, supported by government guaranteed student loans - that may come with or without income contingent support - or be covered by the public sector. When educational costs are small, dii¬€erences in outcomes amongst systems are negligible. On the other hand, when these costs rise to realistic levels we see that there can be large gains in welfare and signii¬ cant drops in inequality by moving to a system with more public sector support. This support can come in the form of tuition subsidies and/or income contingent student loans. However, as the cost of education and the share of debtors in society gets larger, it is preferable to increase public support in the form of tuition subsidies. The reason is that there is a pecuniary externality of debt that gets magnii¬ ed when student loans become excessive. While I identify large steady state welfare gains from more public sector i¬ nancing, I show that the transition costs can be large enough to justify the status quo.
LABORATORY DIAGNOSIS OF MALARIA INFECTION IN CLINICALLY SUSPECTED CASES USING MICROSCOPIC EXAMINATION, RAPID ANTIGEN TESTS & PCR

Accurate diagnosis of malaria is important for providing malaria burden and preventing misdiagnosis. To analyses the diagnostic performance of conventional blood film microscopic examination, OptiMAL Rapid Antigen Test, Hexagon Malaria Combi, Diaquick Malaria Pf/Pan Cassette in comparison with species-specific nested polymerase chain reaction (nest-PCR) in Makkah and Taif in Kingdom of Saudi Arabia. A total of 100 blood samples collected from febrile cases in Makkah and Taif Cities were screened for malaria by microscopic examination, rapid diagnostic tests (RDTs) using nest-PCR as standard method. The results showed differences in detection rates of nested-PCR, conventional blood film microscopic examination, OptiMAL test, Hexagon Malaria Combi, Diaquick Malaria Pf/Pan Cassette (72%, 57%, 59%, 44% & 52% respectively) in 100 clinically suspected cases. Microscopic examination, OptiMAL test, Hexagon Malaria Combi and Diaquick Malaria Pf/Pan Cassette showed sensitivity (72.2%,72.2%, 62.9%, 65.3%), specificity (82.1%, 75%, 82.1%,& 82.1%), accuracy index (75%, 73%, 62%, 70%), positive predictive value (91.2%, 88.1%, 88.6%,& 90.4%) and negative predictive value (53.5%, 51.2%, 41.1%, 47.9) using nested-PCR as the reference technique. The detection rates of nested-PCR for Pasmodium infection was superior than conventional blood film microscopic examination, OptiMAL test, Hexagon Malaria Combi microscopy and Diaquick Malaria Pf/Pan Cassette. The nest-PCR method was more reliable than conventional microscopic examination for the diagnosis of malaria infections, and this is particularly true in cases of mixed infections and submicroscopic infections.
Different speakers, different grammars: Productivity and representation of Xhosa labial palatalization

While cross-linguistic studies suggest that palatalization is preferentially triggered by high and front vocoids, and that it targets coronals or dorsals, Xhosa has a process of palatalization that is triggered by [w], and that targets only bilabials. This paper presents a wug test experiment, showing that some Xhosa speakers do systematically generalize this phenomenon to nonce words. This suggests that for those speakers, labial palatalization is indeed learned as part of their phonological grammar. Additionally, our findings show that some other speakers systematically do not apply palatalization in nonce words, suggesting that they have learned it as a pattern in the lexicon, and not as part of phonology. Drawing on evidence from a separate wug test experiment, we show that the inter-speaker variation in our results cannot be explained away as a task effect. As such, our results show that different speakers can have fundamentally different grammatical representations of the same sound pattern. Though Xhosa’s labial palatalization pattern is phonetically unnatural, that does not indicate that it is necessarily outside the domain of phonology proper.
NUTRITIONAL EVALUATION OF ELDERLY RESIDENTS IN LONG PERMANENCE INSTITUTIONS AVALIAÇÃO NUTRICIONAL DE IDOSOS RESIDENTES EM INSTITUIÇÕES DE LONGA PERMANÊNCIA EVALUACIÓN NUTRICIONAL DE ADULTOS MAYORES RESIDENTES EN INSTITUCIONES DE LARGA PERMANENCIA

Objective: Evaluate the nutritional state of elderly residents in Long Permanence Institutions. Method: descriptive and cross-sectional study with quantitative approach performed from March to April 2016, with a sample of 78 institutionalized elders. Data gathering occurred by applying the tool of a Mini Nutritional Evaluation during previously scheduled visits. Results: females prevailed, 44 (56%), and it has been identified that there are nutritional risks, with global evaluation average of 17.7 (SD ± 5.2). There was significant statistical association between malnutrition risk and the variables: sex, age and institutionalization time, with p < 0.05. Conclusion: institutionalization is consistent with a factor that is strongly associated with changes in the nutritional state of the elderly, which requires the adoption of adaptive measures by long permanence institutions for this population regarding adequate nutritional support, which is important to maintain health and quality of life.
Investigating the mediating role of social support in the relationship between addiction to social network, media literacy and emotional intelligence

This research aims to provide a theoretical model to explain addiction to social network using media literacy and emotional intelligence as independent variables and social support as the mediator. The study population includes all students of Bojnord’s university in 2017-2018 academic year. It was determined based on three indices: a medium effect size of 0.30, a test power of 0.85, and an alpha of 0.05. A sample of 160 people was determined by G-Power software, and 178 questionnaires were completed. The sampling was conducted using available sampling method. To do so, the link of research questionnaires was offered to volunteer students. The main research instruments were: social support questionnaire, addiction to social network questionnaire, emotional intelligence questionnaire and multidimensional social support questionnaire. The exploratory nature of research data was analyzed by partial least squares method and PLS software. Results showed the reliability of the measurement model, the structural model and the overall research model (GOF=0.66). According to the results, all direct effects were significant. That is, social support(r=0.84, p <0.0001), media literacy (r=0.698, p <0.0001) and emotional intelligence (r=0.798, p <0.0001) were significantly correlated with addiction to virtual social network. Also, Sobel statistics and its significance level suggested the indirect effect of media literacy (p <0.024) and emotional intelligence (p <0.011) on addiction to social network through social support. Emotional impulse control, awareness of media content and processes, and a sense of belonging and relationship with other people in the real world predict addiction to virtual social networks. Hence, the social support of government and authentic sources can mediate the association between addiction to social network and emotional intelligence in university students and improve their media literacy.
Symplectic trisections and the adjunction inequality

In this paper, we establish a version of the adjunction inequality for closed symplectic 4-manifolds. As in a previous paper on the Thom conjecture, we use contact geometry and trisections of 4-manifolds to reduce this inequality to the slice-Bennequin inequality for knots in the 4-ball. As this latter result can be proved using Khovanov homology, we completely avoid gauge theoretic techniques. This inequality can be used to give gauge-theory-free proofs of several landmark results in 4-manifold topology, such as detecting exotic smooth structures, the symplectic Thom conjecture, and exluding connected sum decompositions of certain symplectic 4-manifolds.
The cost of coordination can exceed the benefit of collaboration in performing complex tasks

Humans and other intelligent agents often rely on collective decision making based on an intuition that groups outperform individuals. However, at present, we lack a complete theoretical understanding of when groups perform better. Here, we examine performance in collective decision making in the context of a real-world citizen science task environment in which individuals with manipulated differences in task-relevant training collaborated. We find 1) dyads gradually improve in performance but do not experience a collective benefit compared to individuals in most situations; 2) the cost of coordination to efficiency and speed that results when switching to a dyadic context after training individually is consistently larger than the leverage of having a partner, even if they are expertly trained in that task; and 3) on the most complex tasks having an additional expert in the dyad who is adequately trained improves accuracy. These findings highlight that the extent of training received by an individual, the complexity of the task at hand, and the desired performance indicator are all critical factors that need to be accounted for when weighing up the benefits of collective decision making.
Explaining Gender Differences in Academics' Career Trajectories

Academic fields exhibit substantial levels of gender segregation. To date, most attempts to explain this persistent global phenomenon have relied on limited cross-sections of data from specific countries, fields, or career stages. Here we used a global longitudinal dataset assembled from profiles on this http URL to investigate which characteristics of a field predict gender differences among the academics who leave and join that field. Only two field characteristics consistently predicted such differences: (1) the extent to which a field values raw intellectual talent ("brilliance") and (2) whether a field is in Science, Technology, Engineering, and Mathematics (STEM). Women more than men moved away from brilliance-oriented and STEM fields, and men more than women moved toward these fields. Our findings suggest that stereotypes associating brilliance and other STEM-relevant traits with men more than women play a key role in maintaining gender segregation across academia.
Coronal vertical structure variations in normal branch of GX 17+2: AstroSat’s SXT and LAXPC perspective

We performed spectro-temporal analysis in the 0.8--50 keV energy band of the neutron star Z source GX 17+2 using AstroSat Soft X-ray Telescope (SXT) and Large Area X-ray Proportional Counter (LAXPC) data. The source was found to vary in the normal branch of the Hardness Intensity Diagram. Cross-correlation studies of LAXPC light curves in soft and hard X-ray band unveiled anticorrelated lags of the order of few hundred seconds. For the first time, Cross-correlation studies were performed using SXT soft and LAXPC hard lightcurves and they exhibited correlated and anti-correlated lags of the order of a hundred seconds. Power density spectrum displayed NB oscillations of 6.7--7.8 Hz (quality factor 1.5--4.0). Spectral modeling resulted in inner disk radius of $\sim$ 12--16 km with $\Gamma$ $\sim$ 2.31--2.44 indicating that disk is close to the ISCO and a similar value of disk radius was noticed based on the reflection model. Different methods were used to constrain the corona size in GX 17+2. Using the detected lags, corona size was found to be 27-46 km ($\beta$ = 0.1, $\beta$ = v$_{corona}$/v$_{disk}$) and 138--231 km ($\beta$ = 0.5). Assuming the X-ray emission to be arising from the Boundary Layer (BL), its size was determined to be 57--71 km. Assuming that BL is ionizing the disk's inner region, it's size was constrained to $\sim$ 19--86 km. Using NBO frequency, the transition shell radius was found to be around 32 km. Observed lags and no movement of the inner disk front strongly indicates that the varying corona structure is causing the X-ray variation in the NB of Z source GX 17+2.
INTEGRATING LAYOUT GEOMETRY WITH ARCHITECTURAL REQUIREMENTS TO ACHIEVE ENERGY-EFFICIENT OFFICE BUILDINGS IN EGYPT

Office buildings consume energy intensively for HVAC to maintain their thermal condition. As the form typology is a factor that affects the building's energy consumptions, this research focuses on the impact of form layout on office building energy consumption in hot desert climate. An extensive simulation process takes place to optimize the integration between energyefficiency and design needs. The different tested design alternatives are the window to wall ratios, shading devices, and building orientations. The results exposed that building orientation has a significant role in improving the energy efficiency of longitudinal forms, while complex forms have a remarkable response to fenestration size and shading devices. In addition, the results found that the design alternatives optimization can play a significant role in improving the energy performance of high energy consumption forms.
Attention with Multiple Sources Knowledges for COVID-19 from CT Images

Until now, Coronavirus SARS-CoV-2 has caused more than 850,000 deaths and infected more than 27 million individuals in over 120 countries. Besides principal polymerase chain reaction (PCR) tests, automatically identifying positive samples based on computed tomography (CT) scans can present a promising option in the early diagnosis of COVID-19. Recently, there have been increasing efforts to utilize deep networks for COVID-19 diagnosis based on CT scans. While these approaches mostly focus on introducing novel architectures, transfer learning techniques, or construction large scale data, we propose a novel strategy to improve the performance of several baselines by leveraging multiple useful information sources relevant to doctors' judgments. Specifically, infected regions and heat maps extracted from learned networks are integrated with the global image via an attention mechanism during the learning process. This procedure not only makes our system more robust to noise but also guides the network focusing on local lesion areas. Extensive experiments illustrate the superior performance of our approach compared to recent baselines. Furthermore, our learned network guidance presents an explainable feature to doctors as we can understand the connection between input and output in a grey-box model.
Supersingular O’Grady Varieties of Dimension Six

O'Grady constructed a 6-dimensional irreducible holomorphic symplectic variety by taking a crepant resolution of some moduli space of stable sheaves on an abelian surface. In this paper, we naturally extend O'Grady's construction to fields of positive characteristic $p\neq 2$, called OG6 varieties. Assuming $p\geq 3$, we show that a supersingular OG6 variety is unirational, its rational cohomology group is generated by algebraic classes, and its rational Chow motive is of Tate type. These results confirm in this case the generalized Artin--Shioda conjecture, the supersingular Tate conjecture and the supersingular Bloch conjecture proposed in our previous work, in analogy with the theory of supersingular K3 surfaces.
A CATEGORICAL QUANTUM TOROIDAL ACTION ON THE HILBERT SCHEMES

We categorify the commutation of Nakajima’s Heisenberg operators $P_{\pm 1}$ and their infinitely many counterparts in the quantum toroidal algebra $U_{q_1,q_2}(\ddot {gl_1})$ acting on the Grothendieck groups of Hilbert schemes from [10, 24, 26, 32]. By combining our result with [26], one obtains a geometric categorical $U_{q_1,q_2}(\ddot {gl_1})$ action on the derived category of Hilbert schemes. Our main technical tool is a detailed geometric study of certain nested Hilbert schemes of triples and quadruples, through the lens of the minimal model program, by showing that these nested Hilbert schemes are either canonical or semidivisorial log terminal singularities.
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Large datasets have become commonplace in NLP research. However, the increased emphasis on data quantity has made it challenging to assess the quality of data. We introduce Data Maps---a model-based tool to characterize and diagnose datasets. We leverage a largely ignored source of information: the behavior of the model on individual instances during training (training dynamics) for building data maps. This yields two intuitive measures for each example---the model's confidence in the true class, and the variability of this confidence across epochs---obtained in a single run of training. Experiments across four datasets show that these model-dependent measures reveal three distinct regions in the data map, each with pronounced characteristics. First, our data maps show the presence of "ambiguous" regions with respect to the model, which contribute the most towards out-of-distribution generalization. Second, the most populous regions in the data are "easy to learn" for the model, and play an important role in model optimization. Finally, data maps uncover a region with instances that the model finds "hard to learn"; these often correspond to labeling errors. Our results indicate that a shift in focus from quantity to quality of data could lead to robust models and improved out-of-distribution generalization.
Host Galaxy Properties and Offset Distributions of Fast Radio Bursts: Implications for Their Progenitors

We present observations and detailed characterizations of five new host galaxies of fast radio bursts (FRBs) discovered with the Australian Square Kilometre Array Pathfinder (ASKAP) and localized to ≲1″. Combining these galaxies with FRB hosts from the literature, we introduce criteria based on the probability of chance coincidence to define a subsample of 10 highly confident associations (at z = 0.03–0.52), 3 of which correspond to known repeating FRBs. Overall, the FRB-host galaxies exhibit a broad, continuous range of color (Mu − Mr = 0.9–2.0), stellar mass (M⋆ = 108 − 6 × 1010 M⊙), and star formation rate (SFR = 0.05–10 M⊙ yr−1) spanning the full parameter space occupied by z < 0.5 galaxies. However, they do not track the color–magnitude, SFR–M⋆, nor BPT diagrams of field galaxies surveyed at similar redshifts. There is an excess of “green valley” galaxies and an excess of emission-line ratios indicative of a harder radiation field than that generated by star formation alone. From the observed stellar mass distribution, we rule out the hypothesis that FRBs strictly track stellar mass in galaxies (>99% c.l.). We measure a median offset of 3.3 kpc from the FRB to the estimated center of the host galaxies and compare the host-burst offset distribution and other properties with the distributions of long- and short-duration gamma-ray bursts (LGRBs and SGRBs), core-collapse supernovae (CC-SNe), and SNe Ia. This analysis rules out galaxies hosting LGRBs (faint, star-forming galaxies) as common hosts for FRBs (>95% c.l.). Other transient channels (SGRBs, CC-, and SNe Ia) have host-galaxy properties and offsets consistent with the FRB distributions. All of the data and derived quantities are made publicly available on a dedicated website and repository.
Drug Repurposing for COVID-19 using Graph Neural Network with Genetic, Mechanistic, and Epidemiological Validation

Amid the pandemic of 2019 novel coronavirus disease (COVID-19) infected by SARS-CoV-2, a vast amount of drug research for prevention and treatment has been quickly conducted, but these efforts have been unsuccessful thus far. Our objective is to prioritize repurposable drugs using a drug repurposing pipeline that systematically integrates multiple SARS-CoV-2 and drug interactions, deep graph neural networks, and in-vitro/population-based validations. We first collected all the available drugs (n= 3,635) involved in COVID-19 patient treatment through CTDbase. We built a SARS-CoV-2 knowledge graph based on the interactions among virus baits, host genes, pathways, drugs, and phenotypes. A deep graph neural network approach was used to derive the candidate drug’s representation based on the biological interactions. We prioritized the candidate drugs using clinical trial history, and then validated them with their genetic profiles, in vitro experimental efficacy, and electronic health records. We highlight the top 22 drugs including Azithromycin, Atorvastatin, Aspirin, Acetaminophen, and Albuterol. We further pinpointed drug combinations that may synergistically target COVID-19. In summary, we demonstrated that the integration of extensive interactions, deep neural networks, and rigorous validation can facilitate the rapid identification of candidate drugs for COVID-19 treatment.