Miracle-dz/UniFAR-FTUs huggingface dataset:
Biallelic loss-of-function ZFYVE19 mutations are associated with congenital hepatic fibrosis, sclerosing cholangiopathy and high-GGT cholestasis

Background For many children with intrahepatic cholestasis and high-serum gamma-glutamyl transferase (GGT) activity, a genetic aetiology of hepatobiliary disease remains undefined. We sought to identify novel genes mutated in children with idiopathic high-GGT intrahepatic cholestasis, with clinical, histopathological and functional correlations. Methods We assembled a cohort of 25 children with undiagnosed high-GGT cholestasis and without clinical features of biliary-tract infection or radiological features of choledochal malformation, sclerosing cholangitis or cholelithiasis. Mutations were identified through whole-exome sequencing and targeted Sanger sequencing. We reviewed histopathological findings and assessed phenotypical effects of ZFYVE19 deficiency in cultured cells by immunofluorescence microscopy. Results Nine Han Chinese children harboured biallelic, predictedly complete loss-of-function pathogenic mutations in ZFYVE19 (c.314C>G, p.S105X; c.379C>T, p.Q127X; c.514C>T, p.R172X; c.547C>T, p.R183X; c.226A>G, p.M76V). All had portal hypertension and, at liver biopsy, histopathological features of the ductal plate malformation (DPM)/congenital hepatic fibrosis (CHF). Four children required liver transplantation for recurrent gastrointestinal haemorrhage. DPM/CHF was confirmed at hepatectomy, with sclerosing small-duct cholangitis. Immunostaining for two primary-cilium axonemal proteins found expression that was deficient intraluminally and ectopic within cholangiocyte cytoplasm. ZFYVE19 depletion in cultured cells yielded abnormalities of centriole and axoneme. Conclusion Biallelic ZFYVE19 mutations can lead to high-GGT cholestasis and DPM/CHF in vivo. In vitro, they can lead to centriolar and axonemal abnormalities. These observations indicate that mutation in ZFYVE19 results, through as yet undefined mechanisms, in a ciliopathy.
Fused Geometry Augmented Images For Analyzing Textured Mesh

In this paper, we propose a multi-modal mesh surface representation by fusing texture and geometric data. Our approach defines an inverse mapping between different geometric descriptors computed on the mesh surface, and the corresponding 2D texture image of the mesh, allowing the construction of fused geometrically augmented images. This new fused modality enables us to learn feature representations from 3D data in a highly efficient manner by employing standard convolutional neural networks in a transfer-learning mode. In contrast to existing methods, the proposed approach is both computationally and memory efficient, preserves intrinsic geometric information and learns highly discriminative feature representations by effectively fusing shape and texture information at the data level. The efficacy is demonstrated on the task of facial expression classification, showing competitive performance with state-of-the-art methods.
Risk of severe COVID-19 disease with ACE inhibitors and angiotensin receptor blockers: cohort study including 8.3 million people

Background There is uncertainty about the associations of angiotensive enzyme (ACE) inhibitor and angiotensin receptor blocker (ARB) drugs with COVID-19 disease. We studied whether patients prescribed these drugs had altered risks of contracting severe COVID-19 disease and receiving associated intensive care unit (ICU) admission. Methods This was a prospective cohort study using routinely collected data from 1205 general practices in England with 8.28 million participants aged 20–99 years. We used Cox proportional hazards models to derive adjusted HRs for exposure to ACE inhibitor and ARB drugs adjusted for sociodemographic factors, concurrent medications and geographical region. The primary outcomes were: (a) COVID-19 RT-PCR diagnosed disease and (b) COVID-19 disease resulting in ICU care. Findings Of 19 486 patients who had COVID-19 disease, 1286 received ICU care. ACE inhibitors were associated with a significantly reduced risk of COVID-19 disease (adjusted HR 0.71, 95% CI 0.67 to 0.74) but no increased risk of ICU care (adjusted HR 0.89, 95% CI 0.75 to 1.06) after adjusting for a wide range of confounders. Adjusted HRs for ARBs were 0.63 (95% CI 0.59 to 0.67) for COVID-19 disease and 1.02 (95% CI 0.83 to 1.25) for ICU care. There were significant interactions between ethnicity and ACE inhibitors and ARBs for COVID-19 disease. The risk of COVID-19 disease associated with ACE inhibitors was higher in Caribbean (adjusted HR 1.05, 95% CI 0.87 to 1.28) and Black African (adjusted HR 1.31, 95% CI 1.08 to 1.59) groups than the white group (adjusted HR 0.66, 95% CI 0.63 to 0.70). A higher risk of COVID-19 with ARBs was seen for Black African (adjusted HR 1.24, 95% CI 0.99 to 1.58) than the white (adjusted HR 0.56, 95% CI 0.52 to 0.62) group. Interpretation ACE inhibitors and ARBs are associated with reduced risks of COVID-19 disease after adjusting for a wide range of variables. Neither ACE inhibitors nor ARBs are associated with significantly increased risks of receiving ICU care. Variations between different ethnic groups raise the possibility of ethnic-specific effects of ACE inhibitors/ARBs on COVID-19 disease susceptibility and severity which deserves further study.
Analysis of patients with suspected diagnosis of spontaneous bacterial peritonitis in the emergency department

Aim: In this study, we aimed to determine the epidemiological characteristics, microbiological and laboratory parameters of the patients diagnosed with spontaneous bacterial peritonitis (SBP) in the tertiary emergency department and to determine the in-hospital mortality rates. Material and Methods: A total of 294 patients who met these criteria and whose data were fully accessible from the hospital information management system included in the study. Demographic data such as age, gender, cirrhosis etiology, laboratory results and in-hospital mortality were recorded on the study form previously prepared. Child-Pugh and model for end stage liver disease (MELD) scores were calculated according to the formulas. Results: The mean age of the patients was 49 Â± 17 years (mean Â± SD) and 212 (72.1%) were male. When the patients were examined in terms of the etiology of cirrhosis; the most common cause was viral hepatitis with 53.4% (n: 157), followed by alcoholic hepatitis with 28.4% (n: 83). In terms of Child-Pugh grades, 45.2% (n: 132) of the patients were Child-Pugh grade C. In acid fluid analysis; there were 57 (19.3%) patients in SBP group, 45 (15.3%) patients in the culture negative neutrocytic ascites group and 192 (65.4%) patients in monomicrobial bacterascites group. Conclusion: Since the first admission address of these patients are mostly ED, especially emergency physicians should always keep this diagnosis in mind for such patients.
Workshop Proposal: Educational A/B Testing at Scale

The emerging discipline of Learning Engineering is focused on putting into place tools and processes that use the science of learning as a basis for improving educational outcomes [3]. An important part of Learning Engineering focuses on improving the effectiveness of educational software. In many software domains, A/B testing has become a prominent technique to achieve the software’s goals [1]. Many large companies (Amazon, Google, Facebook, etc.) run thousands of AB tests and present at the Annual Conference on Digital Experimentation (CODE), but that venue is too broad to address AB testing issues specific to EdTech platforms. We see a need to address issues with running large-scale A/B tests within the educational context, where the use of A/B testing lags other industries. This workshop will explore ways in which A/B testing in educational contexts differs from other domains and proposals to overcome current challenges so that this approach can become a more useful tool in the learning engineer’s toolbox. Issues to be addressed are expected to include:
Operative versus non-operative treatment of humeral shaft fractures: A systematic review

Background Humeral shaft fractures are common but debate still occurs as to whether these are best managed operatively or non-operatively. We sought to undertake a systematic review and meta-analysis of randomised and non-randomised studies to clarify the optimal treatment. Methods We performed a search for all randomised and non-randomised comparative studies on humeral shaft fracture. We included only those with an operative and non-operative cohort in adult patients. We undertook a meta-analysis of the following outcome measures: nonunion, malunion, delayed union, iatrogenic nerve injury and infection. Non-operative management was with a functional brace. Results Non-operative management resulted in a significantly higher nonunion rate of 17.6% compared to 6.3% with fixation. Operative management had a significantly higher iatrogenic nerve injury rate of 3.4% and infection rate of 3.7%. All nonunions within the included studies went on to union after plate fixation. There was no significant difference in delayed union or patient reported outcome measures. There was a significantly increased risk of malunion with non-operative treatment however this did not correlate with the outcome. Discussion Our findings suggest that in the majority of cases, humeral shaft fractures can be managed with non-operative treatment, and any subsequent nonunion should be treated with plate fixation.
Trading Latency for Compute in the Network

This paper proposes a new heterogeneous approach to programmable architecture that extends the capabilities of programmable switch ASICs with FPGAs. It identifies the key challenges in building a heterogeneous network architecture, and presents a concrete design and implementation based around a proof-of-concept data deduplication application. Our prototype demonstrates the use of a programmable network switch and FPGAs to accelerate storage fingerprinting, running at 10G and 100G at line rate. Our approach is modular, scalable and generalizes to a wide range of applications.
Introducing Financial Data and Groups in a Carbon Calculator: Issues With Trust and Opportunities for Social Interaction

A range of carbon footprint calculators have emerged over the years, aiming at promoting pro-environmental behaviour through providing information about what impact people have on the environment. Up until recently, most of these calculators have been focusing on providing feedback on an individual level. This paper presents an exploratory study of a new kind of carbon footprint calculator, which offers a social and collective dimension not found in many other existing calculators. This is done through the introduction of a group feature allowing people to engage with and compare themselves to each other. The calculator also makes use of real-time financial data in combination with user generated data in order to provide reliable and continuous estimates of a person's carbon footprint. Through an explorative study, in which we conducted two in-depth interviews with four participants, we have investigated the reactions to using the carbon calculator for the first time as well as after two to three weeks of unsupervised use. Our study indicates that the use of transaction data does not automatically lead to a higher trust in the calculated carbon footprint due to the numerous insecurities that are revealed. Registry data on the other hand seems to be appreciated because it eases the input that people have to provide anyway. While groups seem to be a promising feature, there is a need to investigate what information about people's carbon footprints should be shared as well as how the groups and the interaction with the carbon calculator can be kept lively and interesting over time.
AlgoPlan: Supporting Planning in Algorithmic Problem-Solving with Subgoal Diagrams

Planning a solution before writing code is essential in algorithmic problem-solving. However, novices often skip planning and jump straight into coding. Even if they set up a plan, some do not connect to their plan when writing code. Learners solving algorithmic problems often struggle with high-level components such as solution techniques and sub-problems, but existing representations that guide learners in planning, such as flowcharts, focus on presenting lower-level details. We use subgoal diagrams -- diagrams made of subgoal labels and the relationships between them -- as a representation that guides learners to focus on high-level plans when they develop solutions. We introduce AlgoPlan, an interface that enables learners to build their own subgoal diagram and use it to guide their problem-solving process. A preliminary study with seven students shows that subgoal diagrams help learners focus on high-level plans and connect these plans to their code.
Data-Driven Hybrid Equivalent Dynamic Modeling of Multiple Photovoltaic Power Stations Based on Ensemble Gated Recurrent Unit

With the increasing penetration of the photovoltaic (PV) in the distributed grid network, the dynamic response analysis of the system becomes more and more complex and costs lots of computational time in the simulation. To cut down the computational resources while guaranteeing the accuracy, this paper proposes a data-driven hybrid equivalent model for the dynamic response process of the multiple PV power stations. The data-driven hybrid equivalent model contains the simple equivalent model and data-driven error correction model. In the equivalent model, the distributed PV power stations in the same branch are equivalent to one power station model based on the parameter equivalence and feeder equivalence. The data-driven error correction model tracks and corrects the difference of dynamic response between the equivalent model and precise model. The ensemble Gated Recurrent Unit (GRU) model based on the bagging ensemble structure utilizes the simple equivalent dynamic response as input to learn the dynamic response errors. The simulation results validate the super-performance of the proposed model both in the response speed and accuracy.
Coaching and Therapy: Similarities and divergences

This paper considers critically the major similarities and differences between coaching and therapy as presented by previous authors. In particular, it considers Jopling’s contribution of the idea of a ‘fuzzy space’ between the professions and argues that coaching psychology is particularly well placed to inhabit this ‘fuzzy space’. Finally, the paper considers three major issues that provide pathways to both convergence and divergence between the professions: contracting; the quality and type of relationship being engendered; and the inter-relational stance.
Towards classification of experimental Laguerre–Gaussian modes using convolutional neural networks

Abstract. Automated detection of orbital angular momentum (OAM) can tremendously contribute to quantum optical experiments. We develop convolutional neural networks to identify and classify noisy images of Laguerre–Gaussian (LG) modes collected from two different experimental set ups. We investigate the classification performance measures of the predictive classification models for experimental conditions. The results demonstrate accuracy and specificity above 90% in classifying 16 LG modes for both experimental set ups. However, the F-score, sensitivity, and precision of the classification range from 57% to 92%, depending on the number of imperfections in the images obtained from the experiments. This research could enhance the application of OAM light in telecommunications, sensing, and high-resolution imaging systems.
Strategies for Managing Early Succession Habitat for Wildlife

Early succession plant communities consisting of a diverse mixture of grasses, forbs, and scattered shrubs are required by a variety of wildlife species. Early seral stages follow some form of disturbance but can become dominated by shrubs and trees rather quickly, especially in areas with abundant rainfall and relatively long growing seasons, such as the southeastern United States. In the absence of natural disturbance regimes, the quality and maintenance of these plant communities for wildlife is largely dependent upon management. Prescribed fire, disking, herbicide applications, and mowing are practices commonly used to maintain early succession plant communities for various wildlife species throughout this region. Prescribed fire consumes vegetative debris, provides open structure at ground level, and facilitates travel and foraging for wildlife throughout the field. Burning during the dormant season may promote cool-season grasses if they are present in the field. Burning in late March or early April generally promotes warm-season grasses and forbs. Late growing-season fire (September) will reduce woody encroachment and may encourage additional forb cover. Disking promotes vegetation decomposition, provides open structure at ground level, and generally promotes annual plant species. Disking in the fall and winter stimulates more forb growth than disking in the spring, which will stimulate undesirable nonnative warm-season grasses if present in the seedbank. Selective herbicides can influence plant composition and can be used to encourage grasses where forbs dominate, to promote forbs where grasses dominate, and to reduce woody cover. Mowing during midsummer encourages additional grasses in fields dominated by forbs but is not recommended for field maintenance because mowing produces thatch, which limits the ability of several wildlife species to travel and forage through the field, suppresses the seedbank, and destroys nests and young wildlife. Several practices can be used in combination to meet specific objectives. Succession should be set back every 2 to 4 yr, depending on plant response and focal wildlife species. It is important to intersperse disturbance in space and time, so that a variety of cover types are always available, even to those animals with small home ranges.
Brief Announcement: Collect in the Presence of Continuous Churn with Application to Snapshots and Lattice Agreement

A popular programming technique that contributes to designing provably-correct distributed applications is to use shared objects for interprocess communication, instead of more low-level techniques. Although shared objects are a convenient abstraction, they are not generally provided in large-scale distributed systems; instead, the processes keep individual copies of the data and communicate by sending messages to keep the copies consistent. Traditional distributed computing considers a static system, with known bounds on the number of fixed computing nodes and the number of possible failures. Dynamic distributed systems allow nodes to enter and leave the system at will, either due to failures and recoveries, moving in the real world, or changes to the systems' composition. Motivating applications include those in peer-to-peer, sensor, mobile, and social networks, as well as server farms.
Interactions Between Different Age-Related Factors Affecting Balance Control in Walking

Maintaining balance during walking is a continuous sensorimotor control problem. Throughout the movement, the central nervous system has to collect sensory data about the current state of the body in space, use this information to detect possible threats to balance and adapt the movement pattern to ensure stability. Failure of this sensorimotor loop can lead to dire consequences in the form of falls, injury and death. Such failures tend to become more prevalent as people get older. While research has established a number of factors associated with higher risk of falls, we know relatively little about age-related changes of the underlying sensorimotor control loop and how such changes are related to empirically established risk factors. This paper approaches the problem of age-related fall risk from a neural control perspective. We begin by summarizing recent empirical findings about the neural control laws mapping sensory input to motor output for balance control during walking. These findings were established in young, neurotypical study populations and establish a baseline of sensorimotor control of balance. We then review correlates for deteriorating balance control in older adults, of muscle weakness, slow walking, cognitive decline, and increased visual dependency. While empirical associations between these factors and fall risk have been established reasonably well, we know relatively little about the underlying causal relationships. Establishing such causal relationships is hard, because the different factors all co-vary with age and are difficult to isolate empirically. One option to analyze the role of an individual factor for balance control is to use computational models of walking comprising all levels of the sensorimotor control loop. We introduce one such model that generates walking movement patterns from a short list of spinal reflex modules with limited supraspinal modulation for balance. We show how this model can be used to simulate empirical studies, and how comparison between the model and empirical results can indicate gaps in our current understanding of balance control. We also show how different aspects of aging can be added to this model to study their effect on balance control in isolation.
Cyclic Voles and Puumala Hantavirus in a Changing Boreal Landscape

Land-use change is causing extinction of species globally, while also increasing the risk of disease exposure to humans through augmented interactions with wildlife, when humans live and work in manipulated ecosystems or when animals seek shelter/refuge in man-made infrastructure. Forestry is one such activity, which is continually altering forest structure worldwide, causing habitat loss for many specialized forest species. This study investigates the population ecology of three cyclic vole species, Myodes rufocanus, Myodes glareolus and Microtus agrestis, in relation to intensive forestry in northern Sweden. M. glareolus is also the natural reservoir of Puumala hantavirus (PUUV) which is important from a public health perspective since PUUV causes nephropathia epidemica in humans. M. rufocanus and M. agrestis declined substantially in density and distribution during the 1970-80s while M. glareolus only marginally declined and is still the most common species in the region. The decline of M. rufocanus was related to habitat loss. The cumulated impact from long-term clear-cutting explained local extinctions of M. rufocanus. The species is also dependent on maintained connectivity between old forest and shelter-providing stone fields. In contrast, local extinction of M. agrestis was not related to forestry, suggesting action of another strong driver. M. agrestis re-colonized most of the study area during 2010-2011, two years that were characterised by cold winters and a thick snow cover, suggesting a climatic driver in this case. Occurrence of PUUV infected M. glareolus was negatively related to the impact of long-term clear-cutting in the surrounding landscape. PUUV infected M. glareolus survived during low density periods of the vole cycle in old forests. In summary, the main driver of the decline in density and distribution of M. rufocanus appeared to be intensive forestry. PUUV infection dynamics also appeared to be related to forestry. Since land-use changes and climate changes have coincided in Fennoscandian forests, I suggest that future studies should focus on estimating the relative impact of these two factors on pathogen and vole population dynamics.