Miracle-dz/UniFAR-FTUs huggingface dataset:
Engagement Rules That Underpin DBL-DARC Interactions for Ingress of Plasmodium knowlesi and Plasmodium vivax Into Human Erythrocytes

The molecular mechanisms by which P. knowlesi and P. vivax invade human red blood cells have long been studied. Malaria parasite erythrocytic stages comprise of repeated bursts of parasites via cyclical invasion of host RBCs using dedicated receptor-ligand interactions. A family of erythrocyte-binding proteins (EBPs) from P. knowlesi and P. vivax attach to human Duffy antigen receptor for chemokines (DARC) via their Duffy binding-like domains (Pv-DBL and Pk-DBL respectively) for invasion. Here, we provide a comprehensive overview that presents new insights on the atomic resolution interactions that underpin the binding of human DARC with Pk/Pv-DBLs. Based on extensive structural and biochemical data, we provide a novel, testable and overarching interaction model that rationalizes even contradictory pieces of evidence that have so far existed in the literature on Pk/Pv-DBL/DARC binding determinants. We address the conundrum of how parasite-encoded Pk/Pv-DBLs recognize human DARC via its two sulfated tyrosine residues. We collate evidence for two distinct DARC integration sites on Pk/Pv-DBLs that together likely engage the DARC’s sulfated extracellular domain. These analyses are important for both malaria vaccine and inhibitor development efforts that are targeted at abrogating Pk/Pv-DBL/DARC coupling as one avenue to prevent invasion of P. vivax into human red blood cells.
Regularization for high-dimensional covariance matrix

Abstract In many applications, high-dimensional problem may occur often for various reasons, for example, when the number of variables under consideration is much bigger than the sample size, i.e., p >> n. For highdimensional data, the underlying structures of certain covariance matrix estimates are usually blurred due to substantial random noises, which is an obstacle to draw statistical inferences. In this paper, we propose a method to identify the underlying covariance structure by regularizing a given/estimated covariance matrix so that the noises can be filtered. By choosing an optimal structure from a class of candidate structures for the covariance matrix, the regularization is made in terms of minimizing Frobenius-norm discrepancy. The candidate class considered here includes the structures of order-1 moving average, compound symmetry, order-1 autoregressive and order-1 autoregressive moving average. Very intensive simulation studies are conducted to assess the performance of the proposed regularization method for very high-dimensional covariance problem. The simulation studies also show that the sample covariance matrix, although performs very badly in covariance estimation for high-dimensional data, can be used to correctly identify the underlying structure of the covariance matrix. The approach is also applied to real data analysis, which shows that the proposed regularization method works well in practice.
Template-Based Verification of Heap-Manipulating Programs

We propose a shape analysis suitable for analysis engines that perform automatic invariant inference using an SMT solver. The proposed solution includes an abstract template domain that encodes the shape of the program heap based on logical formulae over bit-vectors. It is based on computing a points-to relation between pointers and symbolic addresses of abstract memory objects. Our abstract heap domain can be combined with value domains in a straightforward manner, which particularly allows us to reason about shapes and contents of heap structures at the same time. The information obtained from the analysis can be used to prove memory safety and reachability properties, expressed by user assertions, of programs manipulating dynamic data structures, mainly linked lists. The solution has been implemented in the 2LS framework and compared against state-of-the-art tools that perform the best in heap-related categories of the well-known Software Verification Competition (SV-COMP). Results show that 2LS outperforms these tools on benchmarks requiring combined reasoning about unbounded data structures and their numerical contents.
Characteristics of turbulence in a boundary layer with zero pressure gradient

The results of an experimental investigation of a turbulent boundary layer with zero pressure gradient are presented. Measurements with the hot-wire anemometer were made of turbulent energy and turbulent shear stress, probability density and flattening factor of u-fluctuation (fluctuation in x-direction), spectra of turbulent energy and shear stress, and turbulent dissipation. The importance of the region near the wall and the inadequacy of the concept of local isotropy are demonstrated. Attention is given to the energy balance and the intermittent character of the outer region of the boundary layer. Also several interesting features of the spectral distribution of the turbulent motions are discussed.
Effect of Mechanical Stimulation on Clinical and Radiographical Healing in a Post-Extraction Site

Aim: In a human pilot case, we used a root formed temporary prosthetical device (Intra-alveolar Device - IAD), to investigate the effect of mechanical stimulation on hard tissue clinically and radiographically. Background: The extraction of a tooth determines the resorption of the alveolar bone. This determines challenge to place an implant and to integrate the prosthesis in soft tissue. Mechanical stimulation is fundamental for bone tropism but is not understood the effect of mechanical stimulation on post-extraction site. Case presentation: A 24 years old woman was enrolled. The IAD’s were used as expected by protocol. Clinical healing was uneventfully. Vertical radiographical bone resorption measured on CBCT was -0,14mm (5,6%) while horizontal bone resorption was -0,21mm (12,36%). Conclusion: This study demonstrated the feasibility of the proposed model. We need clinical prospectical studies enrolling more patients
Does Economic Growth Contribute to Poverty Reduction? An Empirical Analysis Evidence from Rwanda

This study empirically analyzes whether economic growth contributed to poverty reduction in Rwanda over the period of 1980-2016. The study applied the Autoregressive - Distribution Lag bounds approach to testing for cointegration, as well Toda and Yamamoto (TY) Granger causality was used in testing for the directional causality among the variables in the study. The Autoregressive - Distribution Lag bounds test results confirm the cointegration between Household final consumption expenditure, Arable land growth rate (hectares), Gross capital formation growth rate (% of GDP), Government final consumption expenditure growth rate (% of GDP) and Service value-added growth rate, when the Household final consumption expenditure, Arable land growth rate and Gross capital formation growth rate are used as dependent variable. Additional, the results from Toda and Yamamoto Granger causality confirms a no evidence of causality association linking the poverty reduction to economic growth and vice versa while considering log Household final consumption expenditure and Arable land growth rate as dependent variables. This means that the neutrality hypothesis grips for Rwanda in the period covered by the study. Furthermore, the study finds out a proof of unidirectional causality running from Gross capital formation growth rate to government final consumption expenditure growth rate, as well as unidirectional causality running from Arable land growth rate to Government final consumption expenditure growth rate and Service value-added growth to Government final consumption expenditure growth rate. The study findings suggested that the government should adopt policy? s objective which is focusing on poverty reduction and economic growth.
Bilevel Feature Learning for Video Saliency Detection

This paper advocates a novel learning solution to the modeling of long-term spatial-temporal saliency consistency in order to boost the accuracy for video saliency detection. Conventional methods typically utilize the “slack” spatial-temporal model to locally ensure the smoothness of the computed video saliency, yet they could easily encounter the performance tradeoff dilemma (i.e., detection’ accuracy and integrity). In contrast, our novel approach proposes the bilevel learning strategy to globally exploit the saliency consistency while overcoming the aforementioned difficulty. Our method first starts with the contrast computation of low-level saliency clues in a frame-wise manner. Then, based on such obtained saliency clues, we devise a novel bilevel Markov Random Field (bMRF) solution to conduct semantic labelling, which can explicitly indicates both the salient salient foregrounds and nonsalient nearby surroundings with high confidence while shrinking the low confidence remains. In such a way, the spatial-temporal consistency constraint is embedded intrinsically into the above explicit semantic labels, and we prevent the performance tradeoff problem from occurring. Next, based on those semantic labels made by our bMRF method, we further propose learnng multiple nonlinear feature transformations to enlarge the feature margin between the salient foregrounds and the non-salient nearby surroundings, whose key rationale is to resort to long-term common consistencies to enforce the spatial-temporal smoothness. Thus, we can utilize these learned non-linear feature transformations to simultaneously suppress those short-term false-alarms and correct those hollow effects. To validate our new approach, we conduct extensive experiments on five publicly available benchmarks, and make comprehensive, quantitative evaluations between our method and 17 state-of-the-art techniques. All of the results demonstrate our method's advantages in terms of accuracy, reliability, robustness, and versatility.
1 Effects of Unfiltered Coffee and Bioactive Coffee 2 Compounds on the Development of Metabolic 3 Syndrome Components in a High ‐ Fat / High ‐ Fructose ‐ 4 Fed Rat Model 5

Literature is inconsistent as to how coffee affects the features of the metabolic syndrome 23 (MetS), and which bioactive compounds are responsible for its metabolic effects. We aimed to 24 compare the in-vivo effects of unfiltered coffee with a selected mixture of its compounds on diet25 induced MetS. 24 male Sprague-Dawley rats were fed a high-fat (35% W/W) food plus 20% W/W 26 fructose in drinking water for 14 weeks, and were randomized into three groups: control, coffee, or 27 nutraceuticals (5-O-caffeoylquinic acid, caffeic acid, and trigonelline). Coffee or nutraceuticals were 28 provided in drinking water in a dosage equal to 4 cups/day in a human. Compared to the controls, 29 only coffee supplementation decreased total food intake, weight gain, and estimated average 30 plasma glucose. Surrogate measures of insulin resistance (fasting insulin, HOMA-IR, and oral 31 glucose tolerance) were improved at endpoint in the coffee group. Circulating triglyceride levels 32 were also reduced by coffee. Histopathological and quantitative measurements indicated lower 33 grades of liver steatosis after long-term coffee consumption. In conclusion, a combination of 34 phenolic acids and trigonelline was not as effective as coffee per se in improving the components of 35 the MetS. This points to the role of other coffee chemicals and a potential synergism between 36 compounds. 37
Tensorial elastodynamics for isotropic media on vertically deformed meshes

Solutions of the equations of 3D isotropic elastodynamics in Cartesian coordinates form the key computational kernel for many applications of isotropic elastic reverse-time migration and full waveform inversion. However, there are numerous situations where solutions are required for computational domains characterized by non-Cartesian geometry, including when handling free-surface topography and irregular internal mesh boundaries such as a depth-varying water bottom. One solution strategy is to compute the elastodynamic response on vertically deformed meshes designed to incorporate irregular topology. By following a tensorial formulation, I develop a system of (semi-)analytic equations governing 3D elastodynamics in a stress-velocity formulation for a broad family of vertically deformed meshes automatically defined by Bézier interpolation functions between two or more non-intersecting surfaces. The analytic coordinate definition also leads to a corresponding analytic free-surface boundary condition as well as expressions for wavefield injection and extraction. Theoretical examples illustrate the utility of the tensorial approach in generating analytic equations of 3D elastodynamics and exact tensorial free-surface boundary conditions for scenarios involving free-surface topography and irregular internal boundaries. Numerical validation of the theoretical results are presented in a companion paper.
Robustness Analysis of a Synthetic Translational Resource Allocation Controller

Recent research in synthetic biology has highlighted the potential of translational resource allocation controllers to improve circuit modularity by dynamically allocating finite cellular resources in response to fluctuating circuit demands. The design of such controllers is complicated by the significant levels of parametric uncertainty that arise in their biological implementations. Tools from robust control, such as <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>-analysis, can be used to determine the robustness of controller designs to parametric uncertainty, but require further development to allow their application to biomolecular control systems, which are typically highly non-linear, and contain multiple uncertainties that cannot be represented using the standard linear fractional transformation formalism. Here, we show how an linear fractional transformation-free formulation of the <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>-analysis problem can be used to analyze and compare the robustness of alternative potential implementations of a translational resource allocation controller that utilises orthogonal “circuit-specific” ribosomes to translate circuit genes. Our results provide useful guidelines for the construction of robust resource allocation circuitry for multiple future biotechnological applications.
Screening of Microalgae for Biodiesel Feedstock

Three heterotrophic microalgae identified as Scenedesmus sp. Y5, Scenedesmus sp. Y7 and Chorellasp. Y9 were isolated and screened from natural water based on biomass yield and lipid productivity. Fatty acids’ composition analysis showed that both Y5 and Y7 mainly contained C16:0, C18:1 (n - 9), C18:2 (n - 6) and C18:3 (n - 3) and Y9 mainly contained C16:0, C18:0 and C18:2 (n - 6), suggesting that these microalgae can be ideal feedstock for biodiesel. Considering the specific growth rate and lipid productivity, the culture conditions were optimized for Scenedesmus sp. Y5, Scenedesmus sp. Y7 and Chorellasp. Y9. Based on the optimization of cultural conditions, all of these three microalgae were tested in fed-batch fermentation, and their biomass productivities were 4.960 g·L-1·d-1, 5.907 g·L-1·d-1 and 4.038 g·L-1·d-1; lipid productivities reached 1.5120 g·L-1·d-1, 1.233 g·L-1·d-1 and 0.8112 g·L-1·d-1, respectively.
Matrix and discrepancy view of generalized random and quasirandom graphs

Abstract We will discuss how graph based matrices are capable to find classification of the graph vertices with small within- and between-cluster discrepancies. The structural eigenvalues together with the corresponding spectral subspaces of the normalized modularity matrix are used to find a block-structure in the graph. The notions are extended to rectangular arrays of nonnegative entries and to directed graphs. We also investigate relations between spectral properties, multiway discrepancies, and degree distribution of generalized random graphs. These properties are regarded as generalized quasirandom properties, and we conjecture and partly prove that they are also equivalent for certain deterministic graph sequences, irrespective of stochastic models.
Review of Biomedical Applications of Contactless Imaging of Neonates Using Infrared Thermography and Beyond

The sick preterm infant monitoring is an intriguing job that medical staff in Neonatal Intensive Care Units (NICU) must deal with on a daily basis. As a standards monitoring procedure, preterm infants are monitored via sensors and electrodes that are firmly attached to their fragile and delicate skin and connected to processing monitors. However, an alternative exists in contactless imaging to record such physiological signals (we call it as Physio-Markers), detecting superficial changes and internal structures activities which can be used independently of, or aligned with, conventional monitors. Countless advantages can be gained from unobtrusive monitoring not limited to: (1) quick data generation; (2) decreasing physical and direct contact with skin, which reduces skin breakdown and minimizes risk of infection; and (3) reduction of electrodes and probes connected to clinical monitors and attached to the skin, which allows greater body surface-area for better care. This review is an attempt to build a solid ground for and to provide a clear perspective of the potential clinical applications of technologies inside NICUs that use contactless imaging modalities such as Visible Light Imaging (VLI), Near Infrared Spectroscopy (NIRS), and Infrared Thermography (IRT).
Optical Characterization of Spins and Defects in Thin Films and Heterostructures

This research focused on using optical techniques to characterize of thin film materials, specifically Quantum Point Defect emitters and spin in heterostructures. These are important in the field of spintronics, with possible application in other fields such as quantum information. This research focused on three materials, hexagonal Boron Nitride (hBN), Tungsten Diselenide (WSe2), and graphene. hBN is used in heterostructures, where defects in the lattice are problematic [1]. However, defects in hexagonal Boron Nitride in previous research has been found to be single photon sources [2]. This research focused on learning more about defects in the hBN lattice by making and characterizing defects in hBN. Tungsten Diselenide is a semiconductor that is also used in heterostructures due to its interesting band structure that allows for spin/valley polarization and long spin/valley lifetimes [3]. Graphene, on the other hand, has a short spin/valley lifetime but can transport spins and charge carriers well [4]. These two materials were studied in heterostructures to learn more about the spin movement and interaction between materials. Photoluminescence was taken on both hBN and heterostructures samples. Timeresolved Kerr rotation was used to investigate the spin/valley lifetimes of grapheneWSe2 heterostructures. In hBN, annealing and depositing an atomic layer of Chromium resulted in single photon source peak being found. In the graphene-WSe2 heterostructures, there was a decrease in excitation decay in the graphene overlap region versus the original Tungsten Diselenide flakes, suggesting the movement of spins and electrons from one material into the other.
Creating Expressive Textual Communication and Anthropomorphic Typography

Despite rapid technological advancement and improvement in network bandwidth, people still like to use text for remote communication. Simplicity, directness and anonymity make textual chat the most popular method of communication in the technology-mediated world. In face-to-face communication, people can use gestures, facial expressions, eye gaze and other body languages to alter, emphasize or strengthen their spoken words. Unfortunately, current textual platforms do not have a proper channel for these cues and signals. These non-linguistic cues are able to convey social and emotional information accompanied by the spoken words. I argue that a well-designed textual communication system can increase the expressiveness of text-based chat environments, and we need to have a better chat interface to improve our social interactions in the digital world. Cheiro is an exploration of user-centered gesture-based interfaces that enable expressive textual communication. My approach is to use common input devices, such as mouse or keyboard, as the gestural interface to amplify or change the tone and meaning of the text, and send non-linguistic signals using graphical elements and anthropomorphized kinetic typography. The goal of this thesis is to find an intuitive mapping between the user's gestural input and the graphically enhanced text output, which constructs a novel expressive textual communication platform. Thesis Supervisor: Judith S. Donath Title: Associate Professor of Media Arts and Sciences
De novo variant in KIF26B is associated with pontocerebellar hypoplasia with infantile spinal muscular atrophy

KIF26B is a member of the kinesin superfamily with evolutionarily conserved functions in controlling aspects of embryogenesis, including the development of the nervous system, though its function is incompletely understood. We describe an infant with progressive microcephaly, pontocerebellar hypoplasia, and arthrogryposis secondary to the involvement of anterior horn cells and ventral (motor) nerves. We performed whole exome sequencing on the trio and identified a de novo KIF26B missense variant, p.Gly546Ser, in the proband. This variant alters a highly conserved amino acid residue that is part of the phosphate‐binding loop motif and motor‐like domain and is deemed pathogenic by several in silico methods. Functional analysis of the variant protein in cultured cells revealed a reduction in the KIF26B protein's ability to promote cell adhesion, a defect that potentially contributes to its pathogenicity. Overall, KIF26B may play a critical role in the brain development and, when mutated, cause pontocerebellar hypoplasia with arthrogryposis.
The Place of In Vitro Maturation in PCO/PCOS

In vitro maturation (IVM) of human oocytes is an emerging treatment option for women with polycystic ovary/polycystic ovary syndrome (PCO/PCOS) in addition to the standard in vitro fertilization (IVF) treatment. There has been significant improvements in pregnancy rates with IVM over the last two decades. This article reviews the place of IVM for women with PCO/PCOS, placing an emphasis on the predictors of successful pregnancy, optimization of culture media, IVM protocols, pregnancy rates, and neonatal outcomes following IVM treatment.