julilili42/papers huggingface dataset:
COVID-19 and the Incidence of Acute Myocardial Injury
2021-10-01

Abstract Cardiovascular manifestations are frequent in COVID-19 infection and are predictive of adverse outcomes. Elevated cardiac biomarkers are common findings in patients with cardiovascular comorbidities and severe COVID-19 infection. Troponin, inflammatory and thrombotic markers may also improve risk prediction in COVID-19. In our comprehensive review, we provide an overview of the incidence, potential mechanisms and outcome of acute cardiac injury in COVID-19. Thereby, we discuss coagulation abnormalities in sepsis and altered immune response as contributing factors favoring myocardial injury. We further highlight the role of endothelial damage in the pathophysiological concepts. Finally, observational studies addressing the incidence of myocardial infarction during COVID-19 pandemic are discussed.
Dutch preposition stranding and ellipsis: ‘Merchant’s Wrinkle’ ironed out
2021-10-01

Abstract This paper provides an explanation for the unexpected ban on preposition stranding by wh -R-pronouns under sluicing in Dutch. After showing that previous prosodic and syntactic explanations are untenable, we propose that the observed ban is a by-product of an EPP condition that applies in the PP domain in Dutch. Our analysis revolves around the idea that ellipsis bleeds EPP-driven movement, an idea that already has empirical support from independent patterns of ellipsis found in English and in other structural domains in Dutch. Our claim is that: (1) R-pronominalization involves a pronominal argument of P moving to the periphery of its extended PP domain (PlaceP) in order to satisfy a PP-internal EPP condition, (2) this EPP-driven movement is bled under sluicing, and (3) because SpecPlaceP is the ‘escape hatch’ through which R-pronouns must move in order to exit the PP domain to form preposition stranding configurations, bleeding the EPP-driven movement of R-pronouns to SpecPlaceP therefore precludes R-pronouns from undergoing the wh- movement required to form a sluicing configuration.
Reappraisal of the late Miocene elasmotheriine Parelasmotherium schansiense from Kutschwan (Shanxi Province, China) and its phylogenetic relationships
2021-10-01

Elasmotheres, such as the huge Siberian unicorn (Elasmotherium sibiricum), are amongst the most iconic large mammals ever to roam Eurasia. Several different elasmotheriine taxa are also known from the upper Miocene of Asia, including the large genus Parelasmotherium. Herein we present the re-examination of the holotype of its type species Parelasmotherium schansiense, using high resolution X-ray computed tomography. The μCT analysis reveals thus far unknown morphological features of the M1 and the unerupted P4 and M2, thereby adding to our knowledge about this species. This allows comparisons with other species that have been referred to Parelasmotherium, ‘Parelasmotherium’ simplum and ‘Parelasmotherium’ linxiaense, which, according to the results of the phylogenetic analysis, should not be included in the same genus as P. schansiense. Furthermore, based on comparisons to other Miocene elasmotheriines the diagnosis of Parelasmotherium schansiense was amended and its phylogenetic position was assessed. Parelasmotherium schansiense is placed in a monophyletic group of ‘derived elasmotheriines,’ which also includes the genera Elasmotherium, Sinotherium, and Ninxiatherium.
KBE009: A Bestatin-Like Inhibitor of the Trypanosoma cruzi Acidic M17 Aminopeptidase with In Vitro Anti-Trypanosomal Activity
2021-10-01

Chagas disease, caused by the kinetoplastid parasite Trypanosoma cruzi, is a human tropical illness mainly present in Latin America. The therapies available against this disease are far from ideal. Proteases from pathogenic protozoan have been considered as good drug target candidates. T. cruzi acidic M17 leucyl-aminopeptidase (TcLAP) mediates the major parasite’s leucyl-aminopeptidase activity and is expressed in all parasite stages. Here, we report the inhibition of TcLAP (IC50 = 66.0 ± 13.5 μM) by the bestatin-like peptidomimetic KBE009. This molecule also inhibited the proliferation of T. cruzi epimastigotes in vitro (EC50 = 28.1 ± 1.9 μM) and showed selectivity for the parasite over human dermal fibroblasts (selectivity index: 4.9). Further insight into the specific effect of KBE009 on T. cruzi was provided by docking simulation using the crystal structure of TcLAP and a modeled human orthologous, hLAP3. The TcLAP-KBE009 complex is more stable than its hLAP3 counterpart. KBE009 adopted a better geometrical shape to fit into the active site of TcLAP than that of hLAP3. The drug-likeness and lead-likeness in silico parameters of KBE009 are satisfactory. Altogether, our results provide an initial insight into KBE009 as a promising starting point compound for the rational design of drugs through further optimization.
An adaptive time-stepping method based on a posteriori weak error analysis for large SDE systems
2021-10-01

Abstract We develop an adaptive algorithm for large SDE systems, which automatically selects (quasi-)deterministic time steps for the semi-implicit Euler method, based on an a posteriori weak error estimate. Main tools to construct the a posteriori estimator are the representation of the weak approximation error via Kolmogorov’s backward equation, a priori bounds for its solution and the Clark–Ocone formula. For a certain class of SDE systems, we validate optimal weak convergence order 1 of the a posteriori estimator, and termination of the adaptive method based on it within <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>O</mml:mi> <mml:mo>(</mml:mo> <mml:msup> <mml:mi>Tol</mml:mi> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> steps.
Outcome uncertainty influences probability perception and risk attitudes
2021-10-01

Subjective inferences of probability play a critical role in decision-making. How we learn about choice options, through description or experience, influences how we perceive their likelihoods, an effect known as the description–experience (DE) gap. Classically, the DE gap details how low probability described options are perceptually inflated as compared to equiprobable experience ones. However, these studies assessed probability perception relative to a ‘sure-bet’ option, and it remained unclear whether the DE gap occurs when humans directly trade-off equiprobable description and experience options and whether choice patterns are influenced by the prospects of gain and loss. We addressed these questions through two experiments where humans chose between description and experience options with equal probabilities of either winning or losing points. Contrary to early studies, we found that gain-seeking participants preferred experience options across all probability levels and, by contrast, loss-mitigating participants avoided the experience options across all probability levels, with a maximal effect at 50%. Our results suggest that the experience options were perceived as riskier than descriptive options due to the greater uncertainty associated with their outcomes. We conclude by outlining a novel theory of probabilistic inference where outcome uncertainty modulates probability perception and risk attitudes.
Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothing
2021-10-01

We present Neural Generalized Implicit Functions(Neural-GIF), to animate people in clothing as a function of the body pose. Given a sequence of scans of a subject in various poses, we learn to animate the character for new poses. Existing methods have relied on template-based representations of the human body (or clothing). However such models usually have fixed and limited resolutions, require difficult data pre-processing steps and cannot be used with complex clothing. We draw inspiration from template-based methods, which factorize motion into articulation and non-rigid deformation, but generalize this concept for implicit shape learning to obtain a more flexible model. We learn to map every point in the space to a canonical space, where a learned deformation field is applied to model non-rigid effects, before evaluating the signed distance field. Our formulation allows the learning of complex and non-rigid deformations of clothing and soft tissue, without computing a template registration as it is common with current approaches. Neural-GIF can be trained on raw 3D scans and reconstructs detailed complex surface geometry and deformations. Moreover, the model can generalize to new poses. We evaluate our method on a variety of characters from different public datasets in diverse clothing styles and show significant improvements over baseline methods, quantitatively and qualitatively. We also extend our model to multiple shape setting. To stimulate further research, we will make the model, code and data publicly available at: https://virtualhumans.mpi-inf.mpg.de/neuralgif/
COVID-19: Cardio-pulmonary and Vascular Manifestations
2021-10-01

Abstract The COVID-19 pandemic is still threatening us, our patients, and the global health care system. Since the first outbreak at the end of 2019 in China, it became rapidly clear that a new variant of a SARS virus, SARS-CoV-2, is threatening our human society worldwide. Since then, the scientific community has accumulated an incredibly large amount of knowledge about the pathophysiology of this virus, primarily affecting the respiratory tract and, in severe cases, subsequently resulting in acute respiratory distress syndrome and multiple organ failure due to uncontrolled systemic inflammatory response syndrome.1 2
The Effect of Formation Processes on The Frequency of Palaeolithic Cave Sites in Semi-Arid Zones: Insights From Kazakhstan
2021-10-01

Central Asian caves with Palaeolithic deposits are few but they provide a rich record of human fossils and cultural assemblages that has been used to model Late Pleistocene hominin dispersals. However, previous research has not yet systematically evaluated the formation processes that influence the frequency of Palaeolithic cave sites in the region. To address this deficiency, we combined field survey and micromorphological analyses in the piedmont zone of south Kazakhstan. Here we present our preliminary results focusing on selected sites of the Qaratau mountains. Sediment cover varies among the surveyed caves and loess-like sediments dominate the cave sequences. The preservation of cave deposits is influenced by reworking of cave sediments within the caves but also by the broader erosional processes that shape semi-arid landscapes. Ultimately, deposits of potentially Pleistocene age are scarce. Our study provides new data in the geoarchaeologically neglected region of Central Asia and demonstrates that micromorphology has great analytical potential even within the limitations of rigorous survey projects. We outline some of the processes that influence the formation and preservation of cave deposits inKazakhstan, as well as broader implications for the distribution of Palaeolithic cave sites in Central Asia and other semi-arid environments.
Development of Josephson Traveling-Wave Parametric Amplifier Based on Aluminum SIS Junctions
2021-10-01

Prototypes of the design of Josephson traveling-wave parametric amplifier based on aluminum superconductor–insulator–superconductor junctions in the form of direct-current SQUIDs included in central conductor of coplanar line are developed, fabricated, and investigated. Three manufacturing methods for the fabrication of such devices are tested: two of them using shadow evaporation and one using magnetron sputtering and direct electron-beam lithography. Current–voltage characteristics of the junctions are measured at 0.3 K. A cryogenic setup for the measurement of spectral characteristics of such amplifier containing cold semiconductor amplifier with circulator and cooled attenuators of the channels of input signal and pump is developed. The absorption spectrum of coplanar directional coupler with a quarter-wave resonator dedicated for measurements of short chains from one to 27 SQUIDs is measured.
382 Molecular classification of endometrial carcinoma substantially changing risk-assessment: Results from a european multicentre initiative
2021-10-01

<h3>Introduction/Background*</h3> Endometrial carcinoma patient care was based on histopathologic examination for many years. However, conventional pathologic features are known to suffer from high inter-observer variability and may be irreproducible in many cases. TCGA-derived molecular classification was shown to provide clinically meaningful data and was recently introduced to ESGO/ESTRO/ESP endometrial carcinoma consensus guidelines. It was the aim of this study to quantify alterations in risk-assessment if molecular classification is added to conventional prognosticators. <h3>Methodology</h3> Consecutive primary endometrial carcinoma patients diagnosed in 2016 were identified in participating centres. Original risk classification ('ORC16', ESGO/ESMO guidelines 2016) was compared to current molecular-based risk assessment ('MBR21', ESGO/ESMO guidelines 2021). Clinical and histopathological data were collected and tumor specimens were retrospectively submitted to PMS2, MSH6 and p53 immunohistochemistry and POLE mutation testing. <h3>Result(s)*</h3> 226 patients were identified across five major European gynecologic oncology centres. Complete molecular and clinical data were available from 198 cases with a median follow-up time of 52.1 months. Median age was 64.9 years (30.9-90.9), 165 cases (83,3%) were endometrioid histotype. Grade distribution included 85(42.9%) G1, 63(31.8%) G2, and 46(23.3%) G3 tumors. 98(49.5%) patients had stage IA disease, with the remaining stage IB (n=51;25.8%), stage II (n=16;8.0%), and stage III/IV (n=33;16.7%). Molecular classification yielded 43(21.7%) MMR-D, 18(9.1%) POLE, 43(21.7%) p53abn, and 94(47.5%) p53wt tumors. If ORC16 was compared to MBR21, risk was found to be higher in 15(7.6%) cases, whereas 27(13.6%) cases were assigned to a lower risk group. No survival events were observed in the 9 patients where risk was changed from high-intermediate or high to low-risk. <h3>Conclusion*</h3> We were able to demonstrate clinically relevant alterations of endometrial carcinoma risk assessment in a significant number of patients after adding TCGA-derived molecular data to conventional risk classification. Potential molecular-guided changes in patient management may help to avoid over- and undertreatment and will ultimately give rise to precision medicine strategies in endometrial carcinoma patient care.
Glacial Catchment Erosion From Detrital Zircon (U‐Th)/He Thermochronology: Patagonian Andes
2021-10-01

Abstract Alpine glacial erosion exerts a first‐order control on mountain topography and sediment production, but its mechanisms are poorly understood. Observational data capable of testing glacial erosion and transport laws in glacial models are mostly lacking. New insights, however, can be gained from detrital tracer thermochronology. Detrital tracer thermochronology works on the premise that thermochronometer bedrock ages vary systematically with elevation, and that detrital downstream samples can be used to infer the source elevation sectors of sediments. We analyze six new detrital samples of different grain sizes (sand and pebbles) from glacial deposits and the modern river channel integrated with data from 18 previously analyzed bedrock samples from an elevation transect in the Leones Valley, Northern Patagonian Icefield, Chile (46.7°S). We present 622 new detrital zircon (U‐Th)/He (ZHe) single‐grain analyses and 22 new bedrock ZHe analyses for two of the bedrock samples to determine age reproducibility. Results suggest that glacial erosion was focused at and below the Last Glacial Maximum and neoglacial equilibrium line altitudes, supporting previous modeling studies. Furthermore, grain age distributions from different grain sizes (sand, pebbles) might indicate differences in erosion mechanisms, including mass movements at steep glacial valley walls. Finally, our results highlight complications and opportunities in assessing glacigenic environments, such as dynamics of sediment production, transport, transient storage, and final deposition, that arise from settings with large glacio‐fluvial catchments.
Pseudoaneurysm of the uterine artery – a rare complication in a patient with deep infiltrating endometriosis
2021-10-01

A 52-year old female patient was referred to our tertiary center due to left sided abdominal pain radiating to the left flank 3 months after abdominal surgery of extended deep endometriosis (rASRM Stage IV) with right adnexectomy, left salpingectomy and adhesiolysis. The patient also showed clear signs of anemia being very fatigued and short of breath. Transvaginal ultrasound (including dopplersonography) revealed signs of a covered ruptured pseudoaneurysm of the left uterine artery. A capsulated hematoma with a diameter of 8,5 cm and a central pulsating cystic area could be demonstrated. Dopplersonography revealed a turbulent blood flow rising from the uterine artery with high velocities into this pseudoaneurysm. ([Fig. 1], [2], [3]) A contrast-enhanced CT scan and an angiography confirmed the sonographic diagnosis. ([Fig. 4]) Hemoglobin concentration was decreased to a level of 7,9 g/dl, furthermore there was as a grade III° left-sided urinary congestion. Hence an emergency selective transarterial embolization of the left uterine artery with liquid embolic agent was performed, successfully stopping the blood flow. The rest of the stay turned out to be inconspicuous and the patient was discharged into outpatient care in good general condition.
Automated HW/SW Co-design for Edge AI: State, Challenges and Steps Ahead: Special Session Paper
2021-10-01

Gigantic rates of data production in the era of Big Data, Internet of Thing (IoT), and Smart Cyber Physical Systems (CPS) pose incessantly escalating demands for massive data processing, storage, and transmission while continuously interacting with the physical world using edge sensors and actuators. For IoT systems, there is now a strong trend to move the intelligence from the cloud to the edge or the extreme edge (known as TinyML). Yet, this shift to edge AI systems requires to design powerful machine learning systems under very strict resource constraints. This poses a difficult design task that needs to take the complete system stack from machine learning algorithm, to model optimization and compression, to software implementation, to hardware platform and ML accelerator design into account. This paper discusses the open research challenges to achieve such a holistic Design Space Exploration for a HW/SW Co-design for Edge AI Systems and discusses the current state with three currently developed flows: one design flow for systems with tightly-coupled accelerator architectures based on RISC-V, one approach using loosely-coupled, application-specific accelerators as well as one framework that integrates software and hardware optimization techniques to built efficient Deep Neural Network (DNN) systems.
Ex VivoandIn VivoCD46 Receptor Utilization by Species D Human Adenovirus Serotype 26 (HAdV26)
2021-10-01

ABSTRACT Human adenovirus serotype 26 (Ad26) is used as a gene-based vaccine against SARS-CoV-2 and HIV-1. Yet, its primary receptor portfolio remains controversial, potentially including sialic acid, CAR, integrins, and CD46. We and others have shown that Ad26 can use CD46, but these observations were questioned by the inability to co-crystallize Ad26 fiber with CD46. Recent work demonstrated that Ad26 binds CD46 with its hexon protein rather than its fiber. We examined the functional consequences of Ad26 for infection in vitro and in vivo . Ectopic expression of human CD46 on Chinese hamster ovary cells increased Ad26 infection significantly. Deletion of the complement control protein domains CCP1 or CCP2 or the serine-threonine-proline (STP) region of CD46 reduced infection. Comparing wild type and sialic acid-deficient CHO cells, we show that the usage of CD46 is independent of its sialylation status. Ad26 transduction was increased in CD46 transgenic mice after intramuscular (IM) injection, but not after intranasal (IN) administration. Ad26 transduction was 10-fold lower than Ad5 after intratumoral (IT) injection of CD46-expressing tumors. Ad26 transduction of liver was 1000-fold lower than Ad5 after intravenous (IV) injection. These data demonstrate the use of CD46 by Ad26 under certain situations, but also show that the receptor has little consequence by other routes of administration. Finally, IV injection of high doses of Ad26 into CD46 mice induced release of liver enzymes in the bloodstream and reduced white blood cell counts, but did not induce thrombocytopenia. This suggests that Ad26 virions do not induce direct clotting side effects seen during COVID-19 vaccination with this serotype of adenovirus. IMPORTANCE Human species D Ad26 is being pursued as a low seroprevalence vector for oncolytic virotherapy and gene-based vaccination against HIV-1 and SARS-CoV-2. However, there is debate in the literature about its tropism and receptor utilization, which directly influence its efficiency for certain applications. This work was aimed at determining which receptor(s) this virus uses for infection, and its role in virus biology, vaccine efficacy, and importantly, in vaccine safety.
Keep CALM and Improve Visual Feature Attribution
2021-10-01

The class activation mapping, or CAM, has been the cornerstone of feature attribution methods for multiple vision tasks. Its simplicity and effectiveness have led to wide applications in the explanation of visual predictions and weakly-supervised localization tasks. However, CAM has its own shortcomings. The computation of attribution maps relies on ad-hoc calibration steps that are not part of the training computational graph, making it difficult for us to understand the real meaning of the attribution values. In this paper, we improve CAM by explicitly incorporating a latent variable encoding the location of the cue for recognition in the formulation, thereby subsuming the attribution map into the training computational graph. The resulting model, class activation latent mapping, or CALM, is trained with the expectation-maximization algorithm. Our experiments show that CALM identifies discriminative attributes for image classifiers more accurately than CAM and other visual attribution baselines. CALM also shows performance improvements over prior arts on the weakly-supervised object localization benchmarks. Our code is available at https://github.com/naver-ai/calm.