Miracle-dz/UniFAR-FTUs huggingface dataset:
A Shim Layer for Transparently Adding Meta Data to MPI Handles

MPI tool or abstraction libraries often have the need to bind meta data information to different kinds of MPI opaque handles. Communicator, window and datatype handles allow to associate key-value pairs as a mean to store meta information. The more short-living request handles, however, do not provide such functionality. As a result, several tool libraries use map-like data structures to bind internal meta information to MPI opaque handles and track those handles across their lifetime, using the handle value as a key. This results in several challenges. In this paper we make the case that request handles associated with different concurrent communication operations are not guaranteed to be unique when returned from the MPI library, so that a simple map may result in conflicts. Furthermore, MPI handles are not guaranteed to be constant over their lifetime, making the use of a map even more questionable. In this work, we present a shim layer wrapping MPI opaque handles that is transparent to the application and that allows tool and abstraction libraries to uniquely distinguish semantically different handles. At the same time, the handle shim layer allows to store the meta information in the wrapped handle avoiding the map-like data structures and also sand-boxes the MPI handle so that changes over its lifetime do not cause any harm. We provide a thread-safe proof-of-concept implementation for most relevant MPI-4 functions that can be used with multi-threaded MPI applications. The implementation transparently supports the different underlying base-language types for handles chosen by the MPI implementations. We evaluate the integration into several tools and abstraction libraries. In an overhead evaluation on synthetic benchmarks, our handle shim layer reduces the runtime overhead compared to a map-like data structure by about in most single-threaded cases.
Suboptimal gestational weight gain and neonatal outcomes in low and middle income countries: individual participant data meta-analysis

Abstract Objective To estimate the associations between gestational weight gain (GWG) during pregnancy and neonatal outcomes in low and middle income countries. Design Individual participant data meta-analysis. Setting Prospective pregnancy studies from 24 low and middle income countries. Main outcome measures Nine neonatal outcomes related to timing (preterm birth) and anthropometry (weight, length, and head circumference) at birth, stillbirths, and neonatal death. Analysis methods A systematic search was conducted in PubMed, Embase, and Web of Science which identified 53 prospective pregnancy studies published after the year 2000 with data on GWG, timing and anthropometry at birth, and neonatal mortality. GWG adequacy was defined as the ratio of the observed maternal weight gain over the recommended weight gain based on the Institute of Medicine body mass index specific guidelines, which are derived from data in high income settings, and the INTERGROWTH-21st GWG standards. Study specific estimates, adjusted for confounders, were generated and then pooled using random effects meta-analysis models. Maternal age and body mass index before pregnancy were examined as potential modifiers of the associations between GWG adequacy and neonatal outcomes. Results Overall, 55% of participants had severely inadequate (<70%) or moderately inadequate (70% to <90%) GWG, 22% had adequate GWG (90-125%), and 23% had excessive GWG (≥125%). Severely inadequate GWG was associated with a higher risk of low birthweight (adjusted relative risk 1.62, 95% confidence interval 1.51 to 1.72; 48 studies, 93 337 participants; τ2=0.006), small for gestational age (1.44, 1.36 to 1.54; 51 studies, 93 191 participants; τ2=0.016), short for gestational age (1.47, 1.29 to 1.69; 40 studies, 83 827 participants; τ2=0.074), and microcephaly (1.57, 1.31 to 1.88; 31 studies, 80 046 participants; τ2=0.145) compared with adequate GWG. Excessive GWG was associated with a higher risk of preterm birth (1.22, 1.13 to 1.31; 48 studies, 103 762 participants; τ2=0.008), large for gestational age (1.44, 1.33 to 1.57; 47 studies, 90 044 participants; τ2=0.009), and macrosomia (1.52, 1.33 to 1.73; 29 studies, 68 138 participants; τ2=0) compared with adequate GWG. The direction and magnitude of the associations between GWG adequacy and several neonatal outcomes were modified by maternal age and body mass index before pregnancy. Conclusions Inadequate and excessive GWG are associated with a higher risk of adverse neonatal outcomes across settings. Interventions to promote optimal GWG during pregnancy are likely to reduce the burden of adverse neonatal outcomes, however further research is needed to assess optimal ranges of GWG based on data from low and middle income countries.
Towards Safe Autonomy in Hybrid Traffic: Detecting Unpredictable Abnormal Behaviors of Human Drivers via Information Sharing

Hybrid traffic which involves both autonomous and human-driven vehicles would be the norm of the autonomous vehicles’ practice for a while. On the one hand, unlike autonomous vehicles, human-driven vehicles could exhibit sudden abnormal behaviors such as unpredictably switching to dangerous driving modes – putting its neighboring vehicles under risks; such undesired mode switching could arise from numbers of human driver factors, including fatigue, drunkenness, distraction, aggressiveness, etc. On the other hand, modern vehicle-to-vehicle (V2V) communication technologies enable the autonomous vehicles to efficiently and reliably share the scarce run-time information with each other [1]. In this paper, we propose, to the best of our knowledge, the first efficient algorithm that can (1) significantly improve trajectory prediction by effectively fusing the run-time information shared by surrounding autonomous vehicles, and can (2) accurately and quickly detect abnormal human driving mode switches or abnormal driving behavior with formal assurance without hurting human drivers’ privacy. To validate our proposed algorithm, we first evaluate our proposed trajectory predictor on NGSIM and Argoverse datasets and show that our proposed predictor outperforms the baseline methods. Then through extensive experiments on SUMO simulator, we show that our proposed algorithm has great detection performance in both highway and urban traffic. The best performance achieves detection rate of \(97.3\% \) , average detection delay of 1.2s, and 0 false alarm.
Association of sleep disorders with asthma: a meta-analysis

Background Animal experiments and clinical trials have revealed a potential relationship between sleep disorders and asthma. However, the associations between these factors remain unclear. Material and methods We searched PubMed, Embase, Web of Science and Cochrane Library databases for eligible studies published before 30 December 2022. Studies investigating the association between sleep disorders (insomnia, poor sleep quality and insufficient sleep time) and asthma were selected. Sleep disorders were assessed using questionnaires, interviews, or medical records. Asthma was diagnosed based on medical history and drug use. The Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality checklist were employed for quality assessment. We used OR with 95% CI as the effect measures and forest plots to display the results. Heterogeneity was evaluated using I2 statistics and subgroup analyses were performed for bias analysis. Publication bias was evaluated using the funnel plots and Egger’s test. Results Twenty-three studies were included in the primary analysis, which suggested a positive association between sleep disorders and asthma (OR: 1.38, 95% CI 1.10 to 1.74). Subgroup analyses were conducted according to the study design, age, family history of asthma and type of sleep disorders. We did not find any association between sleep disorders and asthma in children aged ˂12 years (OR: 1.13, 95% CI 0.97 to 1.32). The association was insignificant in studies where the family history of asthma was adjusted for (OR: 1.16, 95% CI 0.94 to 1.42). Funnel plot and Egger’s test indicated a significant publication bias. Conclusion Sleep disorders are associated with an increased prevalence and incidence of asthma. However, the quality of the evidence was low because of potential biases. PROSPERO registration number CRD42023391989.
A Case Study of Data-Enabled Design for Cardiac Telemonitoring

Data-enabled design (DED) is a novel design methodology that is gaining momentum given the growing availability and maturity of IoT technologies. Experiences with this method are limited, for which it is interesting to study how different design teams apply and appropriate the method in different contexts. Our case concerns the design of a smartwatch app and an online dashboard to facilitate self-monitoring in cardiac health to prevent heart failure. We report on the design and evaluation of contextual experiences with the overall system, offering an accessible foundation for future iterative improvements. Our case demonstrates how the DED method can facilitate the participation of stakeholders and especially end-users, in co-designing within a heavily regulated and technologically rich context.
Effects of betaine supplementation on inflammatory markers: a systematic review and meta-analysis of randomised controlled trials

Abstract Several studies have suggested that betaine is closely related to inflammatory biomarkers that contribute to the development of metabolic diseases, but the effect remains controversial. This meta-analysis aimed to assess the effects of betaine supplementation on inflammatory markers based on randomised controlled trials (RCTs). PubMed, Web of Science and ResearchGate databases were searched up to March 2023. A total of 6 RCTs with 7 intervention trials involving 277 participants were included. Betaine supplementation led to a slight reduction in levels of circulating IL-1β of 0.65 pg/mL (95% CI, −1.23 to −0.06) with high heterogeneity (I2 = 95%). Betaine produced a small but nonsignificant reduction in levels of circulating CRP (0.33 mg/L; 95% CI, −1.79 to 1.14), IL-6 (0.47 pg/mL; 95% CI, −1.13 to 0.18) and TNF-α (0.25 pg/mL; 95% CI, −0.98 to 0.48). The present meta-analysis does not provide sufficient evidence to conclude that betaine supplementation improved the inflammation state.
Microbial characterization of a mine soil subjected to different remediation technologies combining organic and inorganic treatments and plant cultivation

Basanta R. , de Varennes A. , Bååth E. , Díaz-Raviña M. Instituto Superior de Agronomia, TULisbon, Tapada da Ajuda, 1349-017 Lisboa, Portugal, Tel: +351 21 3653424, fax: +351 21 3653180. rosariobasan@isa.utl. pt 2 Department of Microbial Ecology, Ecology Building, Lund University, SE-22362 Lund, Sweden. 3 Departamento de Bioquímica del Suelo, Instituto de Investigaciones Agrobiológicas de Galicia (CSIC) Apartado 122, Avda Vigo s/n, 15780 Santiago de Compostela, Spain.
User Experience of Digital Voice Assistant: Conceptualization and Measurement

With the development of digital virtual assistants (DVA), academics and practitioners have increased attention to the DVA user experience. However, the measurement scale of DVA user experience is still under-researched, which may hinder further empirical study on human-DVA interaction. This study rigorously developed dimensions and associated scales of the DVA user experience. We employed a mixed-method approach that integrated qualitative and quantitative methods. This study first developed multilevel dimensions of DVA user experience based on consumers’ online reviews (n = 21,314), then adopted the ten-step method to develop the associate measurement scale with reliability and validity by collecting and examining three data sets (pretest: n = 368, refinement and validation: n = 585, cross-validation: n = 567). This study fills the gap of a lack of research on the classification and measurement of DVA user experience and provides a reference for practitioners in developing DVA and continuously improving the DVA user experience.
Web-Scale Search-Based Data Extraction and Integration

Abstract : In the current age of abundant, digitized geographic data, the classic, manual approach to geospatial feature discovery and gazetteer creation is cost-prohibitive. While geographic data has become increasingly prevalent on the open Web, it remains largely unstructured and difficult to study. This, the GeoEngine project, has developed generalizable methods for automatic gazetteer generation based on the ample, but unstructured data on the open Web. GeoEngine solves this problem with a three tiered architecture: automatic data discovery and extraction, machine-based semantic aggregation and human validation. GeoEngine has produced specific, but generalizable solutions in the following areas: sub-city feature discovery in domestic and foreign locales; neighborhood boundary discovery and refinement; physical feature gazetteer generation and attribute addition; Wikipedia traversal, extraction and auto-correction; and a comprehensive Places Profile of Afghanistan. These methods allow for fast, automated gazetteer generation and support for geospatial research by leveraging the abundance of unstructured data on the open Web and provides new ways of thinking about old problems in geographic information systems.
Unsupervised GAN epoch selection for biomedical data synthesis

Abstract Supervised Neural Networks are used for segmentation in many biological and biomedical applications. To omit the time-consuming and tiring process of manual labeling, unsupervised Generative Adversarial Networks (GANs) can be used to synthesize labeled data. However, the training of GANs requires extensive computation and is often unstable. Due to the lack of established stopping criteria, GANs are usually trained multiple times for a heuristically fixed number of epochs. Early stopping and epoch selection can lead to better synthetic datasets resulting in higher downstream segmentation quality on biological or medical data. This article examines whether the Frechet Inception Distance (FID), the Kernel Inception Distance (KID), or the WeightWatcher tool can be used for early stopping or epoch selection of unsupervised GANs. The experiments show that the last trained GAN epoch is not necessarily the best one to synthesize downstream segmentation data. On complex datasets, FID and KID correlate with the downstream segmentation quality, and both can be used for epoch selection.
Stripped and layered fabrication of minimal surface tectonics using parametric algorithms

Abstract This article describes a parametric design and fabrication workflow influenced by Frei Otto’s form-finding experiments on soap films. The research investigates minimal surface geometry by combining physical and digital experiments in a computational framework. Operating on mesh topology, various parametric design tools and plug-ins in Rhinoceros/Grasshopper are presented to discuss the translation of minimal surfaces to flat strips suitable for planar fabrication using flexible materials. These tools are tested on a case study to show the automated design and manufacture of double-curved surfaces as double-layered strips running in perpendicular directions that can be affixed at point connections for structural stability. The development of the parametric workflow, material constraints, and stripped fabrication of layers are discussed.
Coenogonium nimisii – a new isidiate epiphytic lichen similar to Porina rosei

Abstract Our floristic work in British ancient forests resulted in a description of a frequently reported but misidentified species, Coenogonium nimisii. Its thallus is very similar to Porina rosei, but the apothecia and pycnidia correspond with C. luteum. Sterile collections are not easy to distinguish but the new species differs from P. rosei in several microscopic characters of the isidia. Coenogonium nimisii is so far known from bark and epiphytic bryophytes, rarely mossy rocks, in ancient humid forests of Great Britain and Ireland. The genus Coenogonium is poorly represented by molecular data in the GenBank database. Our preliminary results revealed distinct genetic lineages within two traditionally circumscribed species, C. luteum and C. pineti, which may represent cryptic species.
Parallel pathways carrying direction and orientation selective retinal signals to layer 4 of mouse visual cortex

Parallel functional and anatomical visual pathways from the retina to primary visual cortex (V1) via the lateral geniculate nucleus (LGN) are common to many mammalian species, including mice, carnivores and primates. However, the much larger number of retinal ganglion cell (RGC) types that project to the LGN, as well as the more limited lamination of both the LGN and the thalamocortical-recipient layer 4 (L4) in mice, leaves considerable uncertainty about which visual features present in both retina and V1 might be inherited from parallel pathways versus extracted by V1 circuits in the mouse visual system. Here, we explored the relationships between functional properties of L4 V1 neurons and their RGC inputs by taking advantage of two Cre-expressing mouse lines — Nr5a1-Cre and Scnn1a-Tg3-Cre — that each label functionally and anatomically distinct populations of L4 neurons. Visual tuning properties of L4 V1 neurons were evaluated using Cre-dependent expression of GCaMP6s followed by 2-photon calcium imaging. RGCs providing input to these neurons (via LGN) were labeled and characterized using Cre-dependent trans-synaptic retrograde labeling with G-deleted rabies virus. We find significant differences in the tuning of Nr5a1-Cre versus Scnn1a-Tg3-Cre neurons for direction, orientation, spatial frequency, temporal frequency, and speed. Strikingly, a subset of the RGCs had tuning properties that matched the direction and orientation tuning properties of the L4 V1 neurons to which they provided input. Altogether, these results suggest that direction and orientation tuning of V1 neurons may be at least partly inherited from parallel pathways originating in the retina.
Gene regulatory network inference from CRISPR perturbations in primary CD4+ T cells elucidates the genomic basis of immune disease

The effects of genetic variation on complex traits act mainly through changes in gene regulation. Although many genetic variants have been linked to target genes in cis, the trans-regulatory cascade mediating their effects remains largely uncharacterized. Mapping trans-regulators based on natural genetic variation, including eQTL mapping, has been challenging due to small effects. Experimental perturbation approaches offer a complementary and powerful approach to mapping trans-regulators. We used CRISPR knockouts of 84 genes in primary CD4+ T cells to perturb an immune cell gene network, targeting both inborn error of immunity (IEI) disease transcription factors (TFs) and background TFs matched in constraint and expression level, but without a known immune disease association. We developed a novel Bayesian structure learning method called Linear Latent Causal Bayes (LLCB) to estimate the gene regulatory network from perturbation data and observed 211 directed edges among the genes which could not be detected in existing CD4+ trans-eQTL data. We used LLCB to characterize the differences between the IEI and background TFs, finding that the gene groups were highly interconnected, but that IEI TFs were much more likely to regulate immune cell specific pathways and immune GWAS genes. We further characterized nine coherent gene programs based on downstream effects of the TFs and linked these modules to regulation of GWAS genes, finding that canonical JAK-STAT family members are regulated by KMT2A, a global epigenetic regulator. These analyses reveal the trans-regulatory cascade from upstream epigenetic regulator to intermediate TFs to downstream effector cytokines and elucidate the logic linking immune GWAS genes to key signaling pathways.
The Neural Correlates of Ambiguity and Risk In Human Decision-Making Under an Active Inference Framework

Active inference integrates perception, decision-making, and learning into a united theoretical frame-work, providing an efflcient way to trade off exploration and utilization by minimizing (expected) free energy. In this study, we asked how the brain represents values, uncertainty, and resolves the uncertainty under the active inference framework in the exploration-exploitation trade-off. 25 participants performed a contextual two-step two-armed bandit task, with electroencephalogram (EEG) recordings. By comparing the fltting results from the active inference and reinforcement learning model, we show that active inference can better capture the exploration instinct of humans, which helps resolve the uncertainty of the environment. The EEG sensor-level results show that the activity in the frontal, central, and parietal regions is associated with uncertainty, while activity in the frontal and central brain regions is associated with risk. The EEG source-level results indicate that the expected free energy is encoded in the lateral occipital cortex and the uncertainty in the middle temporal pole. Our study dissociates the expected free energy and the uncertainty in active inference theory and their neural correlates, suggesting the reliability of active inference in characterizing cognitive processes of human decisions. It provides behavioral and neural evidence of active inference in decision processes and insights into the neural mechanism of human decision under different kinds of uncertainty.
A Functional Exodermal Suberin is Key for Plant Nutrition and Growth in Potato

Angiosperm roots, except in Arabidopsis, have both endodermis and exodermis, which regulate radial water and solute movement through lignin and suberin deposition. While endodermal suberin in Arabidopsis acts as a barrier to water and solute uptake and backflow, its implications in other angiosperms with both layers and the role of exodermal suberin remain unclear. We examined potato roots (Solanum tuberosum) and found that exodermis lacks the typical Casparian strip but forms an outer lignin cap, and quickly suberizes near the root tip. In contrast, a few endodermal cells, with Casparian strip, start suberizing much later. The continuous early exodermal suberization covering the root underlines its potential role in mineral nutrient radial movement. To demonstrate it, we used plants downregulating the suberin biosynthetic gene CYP86A33, which had the root suberin reduced in a 61%. Phenotypic analyses of the suberin-deficient mutant showed altered mineral nutrient concentration, slightly reduced water content and compromised growth. Micro-PIXE analyses identified the distribution of elements within the roots and highlighted anatomical compartments defined by apoplastic barriers. These findings advance our understanding of nutrient radial transport, demonstrate exodermal suberin as a bidirectional and selective barrier to element movement, and underscore its importance in nutrient homeostasis and plant growth.