Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic and Environmental Risk for Alzheimer's

Vascular cognitive impairment (VCI), including its severe form vascular dementia (VaD), is the second most common form of dementia. The genetic aetiology of sporadic VCI remains largely unknown. We previously conducted a systematic review and meta-analysis (MA) of all published genetic association studies of sporadic VCI prior to 6 July 2012, which demonstrated that APOE (  4,  2) and MTHFR (rs1801133) variants were associated with susceptibility for VCI. De novo genotyping was conducted in a new independent relatively large collaborative European cohort of VaD (n max = 549) and elderly non-demented samples (n max = 552). Where available, genotype data derived from Illumina’s 610-quad array for 1210 GERAD1 control samples were also included in analyses of genes examined. Associations were tested using the Cochran-Armitage trend test: MTHFR rs1801133 (OR= 1.36, 95% CI 1.16-1.58, p= <0.0001), APOE rs7412 (OR= 0.62, 95% CI 0.42-0.90, p= 0.01), and APOE rs429358 (OR= 1.59, 95% CI 1.17-2.16, p= 0.003). Association was also observed with APOE epsilon alleles;  4 (OR= 1.85, 95% CI 1.35-2.52, p= <0.0001); and APOE  2, (OR= 0.67, 95% CI 0.46-0.98, p= 0.03). Logistic regression and Bonferroni correction in a subgroup of the cohort adjusted for gender, age and population maintained the association of APOE rs429358 and  4 allele.
Analyse mathématique et numérique d'équations aux dérivées partielles issues de la mécanique des fluides : applications aux écoulements en milieux poreux

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Analyse mathématique et numérique d’équations aux dérivées partielles issues de la mécanique des fluides : applications aux écoulements en milieux poreux Clément Cancès
Opinion: A critical evaluation of the evidence for aerosol invigoration of deep convection

Abstract. Deep convective updraft invigoration via indirect effects of increased aerosol number concentration on cloud microphysics is frequently cited as a driver of correlations between aerosol and deep convection properties. Here, we critically evaluate the theoretical, modeling, and observational evidence for warm- and cold-phase invigoration pathways. Though warm-phase invigoration is plausible and theoretically supported via lowering of the supersaturation with increased cloud droplet concentration in polluted conditions, the significance of this effect depends on substantial supersaturation changes in real-world convective clouds that have not been observed. Much of the theoretical support for cold-phase invigoration depends on unrealistic assumptions of instantaneous freezing and unloading of condensate in growing, isolated updrafts. When applying more realistic assumptions, impacts on buoyancy from enhanced latent heating via fusion in polluted conditions are largely canceled by greater condensate loading. Many foundational observational studies supporting invigoration have several fundamental methodological flaws that render their findings incorrect or highly questionable. Thus, much of the evidence for invigoration has come from numerical modeling, but different models and setups have produced a vast range of results. Furthermore, modeled aerosol impacts on deep convection are rarely tested for robustness, and microphysical biases relative to observations persist, rendering many results unreliable for application to the real world. Without clear theoretical, modeling, or observational support, and given that enervation rather than invigoration may occur for some deep convective regimes and environments, it is entirely possible that the overall impact of cold-phase invigoration is negligible. Substantial mesoscale variability of dominant thermodynamic controls on convective updraft strength coupled with substantial updraft and aerosol variability in any given event are poorly quantified by observations and present further challenges to isolating aerosol effects. Observational isolation and quantification of convective invigoration by aerosols is also complicated by limitations of available cloud condensation nuclei and updraft speed proxies, aerosol correlations with meteorological conditions, and cloud impacts on aerosols. Furthermore, many cloud processes, such as entrainment and condensate fallout, modulate updraft strength and aerosol–cloud interactions, varying with cloud life cycle and organization, but these processes remain poorly characterized. Considering these challenges, recommendations for future observational and modeling research related to aerosol invigoration of deep convection are provided.
Response le(cid:425)er to the reviewers: Manuscript hess-2022-426

The authors collected a valuable data set on DOC export in small catchment, which is partly covered by peat. They highlighted the relationship between water table depths and DOC export, calculated area specific DOC export and analyzed DOC export mechanisms during individual flood events. Their data contributes to the ongoing discussion on mechanisms for DOC 10 mobilization and its link to hydrological connectivity. I generally think that the paper is worthy for publication. However, there are a few points that need to be carefully addressed, especially regarding the calculation of area specific DOC export and peatland coverage.
Auger recombination in two-dimensional Dirac materials

The peculiar electron dispersion in gapped Dirac materials prohibits the lowest-order Auger processes, while in the gapless case they are allowed only for collinear carriers. Thus, Auger recombination in these materials is very sensitive to many-body effects. Using nonequilibrium Green's function method in the GW approximation, we theoretically investigate the impact of dynamic screening, collision-induced spectrum broadening, and Coulomb renormalization on Auger recombination in weakly pumped undoped graphene. We find that incorrect treatment of many-body effects may lead to an order-of-magnitude error in the recombination rate. We show that the room-temperature recombination time can be tuned by metal gate screening from ~1 to ~7 ps in gapless graphene, and further increased up to ~10 ns in the presence of substrate-induced band gap ~0.2 eV typical for graphene on SiC. Comparison with available experimental data reveals additional recombination channels that can be attributed to substrate phonons.
Sim2Real Transfer of Visual Grounding for Natural Human-Robot Interaction

Service robots need to interact naturally with non-expert human users, not only to help them in various tasks but also to receive verbal guidance from users in order to resolve ambiguities, e.g. through visual grounding of objects to natural language queries. Even though modern visual grounding methods can be applied in an open-ended fashion, they heavily rely on model size, and their transfer performance in robotic-speciﬁc domains suffers due to high domain discrepancy between the benchmark and real-time sensory data. In this work, we seek to address these limitations by adopting the Sim2Real transfer methodology for visual grounding in tabletop RGB-D domains. Towards this goal, we develop a novel multi-modal deep learning model for visual grounding. To train the network, we design an algorithm to generate visual grounding queries for tabletop RGB-D scenes, by extracting and parsing scene graph representations of the objects. We deal with the domain discrepancy problem by pre-segmenting objects and perform learning on the extracted RGB crops instead of entire scenes. We evaluate the proposed method using a subset of the Washington RGB-D scene dataset. Experimental results show that the synthetic model can achieve transfer accuracy parallel to the one trained in real data with minimal ﬁne-tuning, while gaining performance boosts when used solely as a pre-training resource.
Decoupling and MIMO performance of two planar monopole antennas with protruded strips

This paper proposes a simple yet elegant approach to reduce mutual coupling between two closely spaced planar monopole antennas with an inter‐element spacing of 2 mm operating in the 2.45 GHz ISM band by employing two thin metallic strips attached to the adjacent corners of the antenna elements and extending above the partial ground plane. Experimental results revealed a 19.6% measured bandwidth over which the transmission coefficient, S21 ≤ −20 dB, and the reflection coefficient, S11 ≤ −10 dB, extending from 2.25 GHz to 2.74 GHz with a realized gain of 2.86 dB at 2.45 GHz. The proposed array offers excellent MIMO performance in terms of envelope correlation coefficient and link efficiency in realistic MIMO propagation environments.
On the expression of spatial concepts in Lahu

Author(s): Matisoff, James | Abstract: Spatial/locative/directional concepts are sometimes highly grammaticalized in Tibeto-Burman, notably in the Qiangic languages, which are famous for their systems of “directional prefixes” preposed to verbs to indicate the literal or figurative direction of the verbal event.
The Resolved Mutual Information Function for Characterization of Spatial Correlations in Sequences and Labeled Graphs

In this technical report we collect and propose some useful quantities, notations, and approaches regarding information theoretic concepts, which might be helpful in machine learning when analyzing sequences and labeled graphs. In particular, we introduce resolved mutual information functions, which can be seen as a determining feature (proﬁle) to characterize the spatial correlations in those data objects.
A Novel Surface Mesh Simpliﬁcation Method for Flux-Dependent Topography Simulations of Semiconductor Fabrication Processes

In etching and deposition simulations of a semiconductor fabrication process the calculation of the surface rates of particles is an essential but also the computationally most demanding step. A promising approach is to preprocess the simulation domain by simplifying the surface. We thus propose a new surface mesh simpliﬁcation method that takes advantage of geometric domain-speciﬁc surface properties that are prevalent in topography simulations. We compare our method to a suitable reference algorithm and show that our method maintains higher geometric accuracy and accordingly maintains the original geometry in great detail. Furthermore, the evaluation of the simpliﬁed meshes show an enhanced performance of the particle surface rate calculation.
Human Comprehensible Active Learning of Genome-Scale Metabolic Networks

An important application of Synthetic Biology is the engineering of the host cell system to yield useful products. However, an increase in the scale of the host system leads to huge design space and requires a large number of validation trials with high experimental costs. A comprehensible machine learning approach that efficiently explores the hypothesis space and guides experimental design is urgently needed for the Design-Build-Test-Learn (DBTL) cycle of the host cell system. We introduce a novel machine learning framework ILP-iML1515 based on Inductive Logic Programming (ILP) that performs abductive logical reasoning and actively learns from training examples. In contrast to numerical models, ILP-iML1515 is built on comprehensible logical representations of a genome-scale metabolic model and can update the model by learning new logical structures from auxotrophic mutant trials. The ILP-iML1515 framework 1) allows high-throughput simulations and 2) actively selects experiments that reduce the experimental cost of learning gene functions in comparison to randomly selected experiments.
Managing γ[subscript 5] in Dimensional Regularization II: the Trace with more γ[subscript 5]’s

In the present paper we evaluate the anomaly for the abelian axial current in a non abelian chiral gauge theory, by using dimensional regularization. This amount to formulate a procedure for managing traces with more than one γ5. The suggested procedure obeys Lorentz covariance and cyclicity, at variance with previous approaches (e.g. the celebrated ’t Hooft and Veltman’s where Lorentz is violated) The result of the present paper is a further step forward in the program initiated by a previous work on the traces involving a single γ5. The final goal is an unconstrained definition of γ5 in dimensional regularization. Here, in the evaluation of the anomaly, we profit of the axial current conservation equation, when radiative corrections are neglected. This kind of tool is not always exploited in field theories with γ5, e.g. in the use of dimensional regularization of infrared and collinear divergences. PACS: 11.10. Gh, 11.30. Rd, 11.40. Ha This work is supported in part by funds provided by the U.S. Department of Energy (D.O.E.) under cooperative research agreement #DE FG02-05ER41360 e-mail: ruggferr@mit.edu
Wild Animal Detection And Identification Using Deep Learning

: Now a days, object discovery is used encyclopedically in multitudinous fields similar as, videotape surveillance, rambler displays, vilification discovery, tone-driving buses and appearance recognition etc. Efficient and reliable monitoring of wild animals in their natural habitats is essential to inform conservation and management decisions. Since there are large number of different animals, manually relating them can be a delicate task. So, it's delicate to classify animals grounded on their images and cover them more efficiently. Also, it's important to make a count of animals as they're being defunct now a days, so to save them we've to keep a note duly so that we can take important measures to save them. In being system there's only homemade checking where a mortal being need to present to keep a count of animals. Which take so much of time to identify the animals. To overcome those problems, we're introducing an automatic relating and counting the animals by using deep learning methods. This process gives an accurate result to detects and keep proper count of animals.
Detecting and Handling IoT Interaction Threats in Multi-Platform Multi-Control-Channel Smart Homes

A smart home involves a variety of entities, such as IoT devices, automation applications, humans, voice assistants, and companion apps. These entities interact in the same physical environment, which can yield undesirable and even hazardous results, called IoT interaction threats . Existing work on interaction threats is limited to considering automation apps, ignoring other IoT control channels, such as voice commands, companion apps, and physical operations. Second, it becomes increasingly common that a smart home utilizes multiple IoT platforms, each of which has a partial view of device states and may issue conflicting commands. Third, compared to detecting interaction threats, their handling is much less studied. Prior work uses generic handling policies, which are unlikely to fit all homes. We present I O TM EDIATOR , which provides accurate threat detection and threat-tailored handling in multi-platform multi-control-channel homes. Our evaluation in two real-world homes demonstrates that I O TM EDIATOR significantly outperforms prior state-of-the-art work.
New Version, New Answer: Investigating Cybersecurity Static-Analysis Tool Outputs

—Automated detection of vulnerabilities and weaknesses in binary code is a pressing and critical need at the frontier of cybersecurity research. Cybersecurity static-analysis tools are a promising avenue for the detection and enumeration of such vulnerabilities and weaknesses. Two commonly used tools for the evaluation of binaries are CVE Binary Tool (cve-bin-tool) and cwe-checker. Cve-bin-tool reports vulnerabilities using Common Vulnerabilities and Exposures (CVE) whereas cwe-checker reports weaknesses using Common Weakness Enumeration (CWE). Despite their widespread use, the consistency with which these tools report vulnerabilities and weaknesses (herein, “findings”) in code was unaddressed in the academic literature. We conducted a systematic investigation of 646 unique binaries taken from a single Kali Linux distribution. We evaluated each binary with multiple versions of the static-analysis tools. We then investigated how the sum of findings changed according to the version of the static-analysis tool used. We expected some variation in the reported findings commensurate with the software development life cycle. However, we were surprised by the number and magnitude of the changes in reported findings across versions. New versions gave new answers. Future work will address the changes associated with the addition of new static-analysis tool functionality and the removal of false positives. We will identify the specific CWEs and CVEs driving the variability in the tool outputs, and investigate the instrument fidelity of the tools via systematic code injection.
Exploring hail and lightning diagnostics over the Alpine-Adriatic region in a km-scale climate model

Abstract. The north and south of the Alps, as well as the eastern shores of the Adriatic Sea, are hot spots of severe convective storms, including hail and lightning associated with deep convection. With advancements in computing power, it has become feasible to simulate deep convection explicitly in climate models by decreasing the horizontal grid spacing to less than 4 km. These kilometer-scale models improve the representation of orography and reduce uncertainties associated with the use of deep convection parameterizations. In this study, we perform km-scale simulations for eight observed cases of severe convective storms (seven with and one without observed hail) over the Alpine-Adriatic region. The simulations are performed with the climate version of the regional model Consortium for Small-scale Modeling (COSMO) that runs on graphics processing units (GPUs) at a horizontal grid spacing of 2.2 km. To analyze hail and lightning we have explored the hail growth model (HAILCAST) and lightning potential index (LPI) diagnostics integrated with the COSMO-crCLIM model. Comparison with available high-resolution observations reveals good performance of the model in simulating total precipitation, hail, and lightning. By performing a detailed analysis of three of the case studies, we identified the importance of significant meteorological factors for heavy thunderstorms that were reproduced by the model. Among these are the moist unstable boundary layer and dry mid-level air, the topographic barrier, as well as an approaching upper-level trough and cold front. Although COSMO HAILCAST tends to underestimate the hail size on the ground, the results indicate that both HAILCAST and LPI are promising candidates for future climate research.
Climate Change, Population Growth, and Population Pressure

We develop a novel method for assessing the effect of constraints imposed by spatially-fixed natural resources on aggregate economic output. We apply it to estimate and compare the projected effects of climate change and population growth over the course of the 21st century, by country and globally. We find that standard population growth projections imply larger reductions in income than even the most extreme widely-adopted climate change scenario (RCP8.5). Climate and population impacts are correlated across countries: climate change and population growth will have their most damaging effects in similar places. Relative to previous work on macro climate impacts, our approach has the advantages of being disciplined by a simple macro growth model that allows for adaptation and of assessing impacts via a large set of climate moments, not just annual average temperature and precipitation. Further, our estimated effects of climate are by construction independent of country-level factors such as institutions. ∗Henderson: London School of Economics. Jang: Brown University. Storeygard: Tufts University. Weil: Brown University. We are grateful to Lint Barrage, Greg Casey, Maureen Cropper, Eric Galbraith, and Zeina Hasna for helpful advice; to Lucy Li, Frankie Fan, William Yang, and Raymond Yeo for research assistance; and to seminar audiences at the Bank of Italy, University of Bologna, Université catholique de Louvain, University of Chicago, University of Chile, ETH Zurich, IIASA, Korea University, Lahore School of Economics, University of Manchester, NYU Abu Dhabi, Osaka University, Oxford University, RIDGE forum on Sustainable Growth, Schumpeter Seminar (Humboldt University), Sungkyunkwan University, University of Tokyo, and the World Bank for useful feedback. Research was supported by the Population Studies and Training Center at Brown University through the generosity of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (P2C HD041020 and T32 HD007338).
Patterns of Centennial-to-Millennial Holocene Climate Variation in the North American Mid-Latitudes

Noise in Holocene paleoclimate reconstructions can hamper detection of centennial-to-millennial climate variations and diagnoses of the dynamics involved. This paper uses multiple ensembles of reconstructions to separate signal and noise 10 and determine what, if any, centennial-to-millennial variations influenced North America during the past 7000 yr. To do so, ensembles of temperature and moisture reconstructions were compared across four different spatial scales: continental, regional, sub-regional, and local scales. At each scale, two independent multi-record ensembles were compared to detect any centennial-to-millennial departures from the long Holocene trends, which correlate more than expected from random patterns. In all cases, the potential centennial-to-millennial variations had small magnitudes. However, at least two patterns of 15 centennial-to-millennial variability appear evident. First, large-scale variations included a prominent Mid-Holocene anomaly from 5600-4500 YBP that increased mean effective moisture and produced temperature anomalies of different signs in different regions. The changes steepened the north-south temperature gradient in mid-latitude North America with a pattern similar to the positive mode of the North Atlantic Oscillation (NAO). Second, correlated multi-century (~500 yr) variations produce a distinct spectral signature in temperature and hydroclimate records along the western Atlantic margin. Both patterns 20 differ from random autocorrelated variations but expressed distinct spatiotemporal characteristics consistent with separate controlling dynamics.
Silne kliki w grafach

A strong edge coloring of a graph G is an edge coloring of G such that every two edges which are at distance at most 2 receive di erent colors (a distance between two edges e, f of G is the distance in the line graph of G between vertices corresponding to e and f). A strong chromatic index of a graph G, denoted by χs(G), is the minimum number of colors in a strong edge coloring of G. A strong edge coloring is a model of a channel assignment in a wireless radio network consisting of a group of transceivers which can send and receive data. Each transceiver has a range in which it can communicate with others. Communication between a pair of nodes is possible if both are in range of each other. We can construct a graph that models this network. Vertices of our graph correspond to transceivers, two vertices are adjacent if and only if they can communicate with each other (see Figure 1). We say that a primary interference occurs if one node communicates with two other nodes by the same channel; a secondary interference occurs if two adjacent nodes n1, n2 use the same channel to communicate with some of their neighbour (di erent from n1, n2). Assigning channels to all pairs of communicating nodes to avoid primary and secondary interference corresponds to nding a strong edge coloring of the graph that models the network ([1],