Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of strong to ultratight protein interactions using differential scanning calorimetry.

Data from differential scanning calorimetry (DSC) may be used to estimate very large binding constants that cannot be conveniently measured by more conventional equilibrium techniques. Thermodynamic models have been formulated to describe interacting systems that involve either one thermal transition (protein-ligand) or two thermal transitions (protein-protein) and either 1:1 or higher binding stoichiometry. Methods are described for obtaining binding constants and heats of binding by two different methods: calculation or simulation fitting of data. Extensive DSC data on 2'CMP binding to RNase are presented and analyzed by the two methods. It is found that the methods agree when binding sites are completely saturated, but substantial errors arise in the calculation method when site saturation is incomplete and the transition of liganded molecules overlaps that of unliganded molecules. This arises primarily from an inability to determine TM (i.e., the temperature where concentrations of folded and unfolded protein are equal) under weak-binding conditions. Results from simulation show that the binding constants and heats of binding from the DSC method agree quantitatively with corresponding estimates obtained from equilibrium methods when extrapolated to the same temperature. It was also found from the DSC data that the binding constant decreases with increasing concentration of ligand, which might arise from nonideality effects associated with dimerization of 2'CMP. Simulations show that the DSC method is capable of estimating binding constants for ultratight interactions up to perhaps 10(40) M-1 or higher, while most equilibrium methods fail well below 10(10) M-1. DSC data from the literature on a number of interacting systems (trypsin-soybean trypsin inhibitor, trypsin-ovomucoid, trypsin-pancreatic trypsin inhibitor, chymotrypsin-subtilisin inhibitor, subtilisin BPN-subtilisin inhibitor, RNase S protein-RNase S peptide, avidin-biotin, ovotransferrin-Fe3+, superoxide dismutase-Zn2+, alkaline phosphatase-Zn2+, and assembly of regulatory and catalytic subunits of aspartate transcarbamoylase) were analyzed by simulation fitting or by calculation. Apparent single-site binding constants ranged from ca. 10(5) to 10(20) M-1, while the interaction constant for assembly of aspartate transcarbamoylase was estimated as 10(37) in molarity units. For most of these systems, the DSC interaction constants compared favorably with other literature estimates, for some it did not for reasons unknown, while for still others this represented the first estimate. Simulations show that for proteins having two binding sites for the same ligand within a single cooperative unit, ligand rearrangement will occur spontaneously during a DSC scan as the transition temperature of the unliganded protein is approached. (ABSTRACT TRUNCATED AT 400 WORDS)
PGC-1α and PGC-1β Regulate Mitochondrial Density in Neurons*

Recent studies indicate that regulation of cellular oxidative capacity through enhancing mitochondrial biogenesis may be beneficial for neuronal recovery and survival in human neurodegenerative disorders. The peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) has been shown to be a master regulator of mitochondrial biogenesis and cellular energy metabolism in muscle and liver. The aim of our study was to establish whether PGC-1α and PGC-1β control mitochondrial density also in neurons and if these coactivators could be up-regulated by deacetylation. The results demonstrate that PGC-1α and PGC-1β control mitochondrial capacity in an additive and independent manner. This effect was observed in all studied subtypes of neurons, in cortical, midbrain, and cerebellar granule neurons. We also observed that endogenous neuronal PGC-1α but not PGC-1β could be activated through its repressor domain by suppressing it. Results demonstrate also that overexpression of SIRT1 deacetylase or suppression of GCN5 acetyltransferase activates transcriptional activity of PGC-1α in neurons and increases mitochondrial density. These effects were mediated exclusively via PGC-1α, since overexpression of SIRT1 or suppression of GCN5 was ineffective where PGC-1α was suppressed by short hairpin RNA. Moreover, the results demonstrate that overexpression of PGC-1β or PGC-1α or activation of the latter by SIRT1 protected neurons from mutant α-synuclein- or mutant huntingtin-induced mitochondrial loss. These evidences demonstrate that activation or overexpression of the PGC-1 family of coactivators could be used to compensate for neuronal mitochondrial loss and suggest that therapeutic agents activating PGC-1 would be valuable for treating neurodegenerative diseases in which mitochondrial dysfunction and oxidative damage play an important pathogenic role.
The Persuasive Impact of Emoticons in Online Word-of-Mouth Communication

The present research proposes a conceptual framework to examine the effect of emoticons on online WOM persuasion. Using a laboratory experiment, we demonstrate that emoticons enhance recipients’ empathy for the communicator, and this effect is moderated by message valence. Enhanced empathy heightens perceived trustworthiness of the communicator and perceived quality of the message, both of which lead to an increase in the persuasiveness of the WOM message. We conclude by discussing the contributions of this research and identifying the directions for future research.
Vascular cognitive impairment

Cerebrovascular disease typically manifests with stroke, cognitive impairment, or both. Vascular cognitive impairment refers to all forms of cognitive disorder associated with cerebrovascular disease, regardless of the specific mechanisms involved. It encompasses the full range of cognitive deficits from mild cognitive impairment to dementia. In principle, any of the multiple causes of clinical stroke can cause vascular cognitive impairment. Recent work further highlights a role of microinfarcts, microhemorrhages, strategic white matter tracts, loss of microstructural tissue integrity, and secondary neurodegeneration. Vascular brain injury results in loss of structural and functional connectivity and, hence, compromise of functional networks within the brain. Vascular cognitive impairment is common both after stroke and in stroke-free individuals presenting to dementia clinics, and vascular pathology frequently coexists with neurodegenerative pathology, resulting in mixed forms of mild cognitive impairment or dementia. Vascular dementia is now recognized as the second most common form of dementia after Alzheimer’s disease, and there is increasing awareness that targeting vascular risk may help to prevent dementia, even of the Alzheimer type. Recent advances in neuroimaging, neuropathology, epidemiology, and genetics have led to a deeper understanding of how vascular disease affects cognition. These new findings provide an opportunity for the present reappraisal of vascular cognitive impairment. We further briefly address current therapeutic concepts.
XML Functional Dependencies Based on Tree Homomorphisms

Functional dependencies form an important class of integrity constraints which has been well studied in the context of relational databases. Recently, the eXtensible Markup Language (XML) has emerged as a popular and flexible standard for modelling and managing data in a variety of domains. Although several attempts have been made to generalise the concept of functional dependencies to the context of XML, the search for an interesting yet practical formalisation of XML functional dependencies still poses a challenge. In this dissertation I propose and investigate a new class of XML functional dependencies with properties (called pXFDs) defined on the basis of tree homomorphism. My first contribution is to demonstrate that one can reason about pXFDs efficiently. Through establishing a semantic equivalent between pXFD implication and logical consequence of propositional Horn clauses, I show that the problem of pXFD implication can be decided in time linear in the total number of essential v-properties in a set of pXFDs. My second contribution is to identify and prove a sound and complete axiomatisation for pXFDs. This yields an alternative approach for deciding the implication problem for pXFDs. Based on these findings, I investigate the application of pXFDs in classifying well-designed XML schemas. The absence of redundancy is used as a suitable indicator of “good” design. For that I generalise two notions of redundancy (i.e., fact and value redundancy) from the relational data model and identify two corresponding normal forms for characterising them. I also show that the proposed normal forms can be checked efficiently: it is sufficient to examine pXFDs in a cover set rather than the set of all implied pXFDs. Finally, I consider the problem of pXFD acquisition and discovery. To be able to benefit from pXFDs, it is imperative to have a good specification of pXFDs that describe the semantics of the data to be stored in an XML database. Discovery and acquisition are two complementary tasks which help in determining such a specification. The logical characterisation of pXFD implication allows me to develop a sample-based approach to support pXFD acquisition. For pXFD discovery, on the other hand, I adapt a method using difference sets and hypergraph transversals in the context of XML. My investigations also demonstrate that pXFDs exhibit certain characteristics which are reminiscent of functional dependencies in the relational data model.
A Globally Convergent Conjugate Gradient Method for Minimizing Self-Concordant Functions on Riemanni

Abstract Self-concordant functions are a special class of convex functions in Euclidean space introduced by Nesterov. They are used in interior point methods, based on Newton iterations, where they play an important role in solving efficiently certain constrained optimization problems. The concept of self-concordant functions has been defined on Riemannian manifolds by Jiang et al. and a damped Newton method developed for this context. As a further development, this paper proposes a damped conjugate gradient method, which is an ordinary conjugate gradient method but with a novel step-size selection rule which is proved to ensure the algorithm converges to the global minimum. The advantage of the damped conjugate gradient algorithm over the damped Newton method is that the former has a lower computational complexity. To illustrate the advantages, the algorithm is applied to find the center of mass of given points on a hyperboloid model, known as the Karcher mean.
Magnetic structure and equation of state of bcc solid hydrogen: A variational quantum Monte Carlo study.

Solid hydrogen in the atomic bcc structure is studied using a variational quantum Monte Carlo approach. Various magnetic phases are investigated at densities between Wigner-Seitz radius of {ital r}{sub {ital s}}=1.6 and 3.0 a.u. Correlated wave functions of Jastrow-Slater form are used with their antisymmetric part constructed from the Kohn-Sham self-consistent orbitals. A transition from paramagnetic to antiferromagnetic phase at lower density is found at {ital r}{sub {ital s}}=2.4. There is, however, no evidence for metastable partial ferromagnetic structure.
Exencephaly induction by valproic acid in the genetic polydactyly/arhinencephaly mouse, Pdn/Pdn

ABSTRACT Non‐treated homozygous polydactyly/arhinencephaly (Pdn/Pdn) mouse fetuses exhibited exencephaly in 16.7% of cases. Treatment of Pdn/Pdn mice with 350 mg/kg of valproic acid (VPA) on days 8.5 and 9.5 of gestation increased the rate of exencephaly to 66.7%. The responsible gene for the Pdn mouse phenotype has been determined to be Gli3, and the suppression of Gli3 gene expression has been documented in Pdn/Pdn embryos. We investigated how the sonic hedgehog (Shh) and Fgf8 genes, the correlated genes of Gli3, are expressed in the VPA‐treated exencephalic Pdn/Pdn embryos on day 10 of gestation, using whole mount in situ hybridization (WISH) and real‐time PCR methods. We could not detect any alterations in Shh expression by real‐time PCR, or WISH in the non‐treated Pdn/Pdn and VPA‐treated exencephalic Pdn/Pdn embryos. Altered Fgf8 expression patterns were observed in the commissural plate and dorsal isthmal neuroepithelium in the non‐treated Pdn/Pdn embryos. We speculated that the altered expression of Fgf8 might be the result of down‐regulation of Gli3 in Pdn/Pdn embryos. Fgf8 gene expression in the commissural plate and dorsal isthmal neuroepithelium exhibits wide or altered signal patterns in the VPA‐treated exencephalic Pdn/Pdn embryo. From these findings, it was suggested that down‐regulation of Gli3 gene expression induced the altered expression of Fgf8 in the Pdn/Pdn embryos, and that VPA treatment accelerated the alterations of Fgf8 gene expression in the Pdn/Pdn embryos. It was further speculated that altered expression of Fgf8 in the commissural plate may be the fundamental cause of exencephaly, and that the synergistic effect between gene and drug shown in this experiment may explain the differences of sensitivity in the side‐effects of the drug.
Advances in Feature Selection Methods for Hyperspectral Image Processing in Food Industry Applications: A Review

There is an increased interest in the applications of hyperspectral imaging (HSI) for assessing food quality, safety, and authenticity. HSI provides abundance of spatial and spectral information from foods by combining both spectroscopy and imaging, resulting in hundreds of contiguous wavebands for each spatial position of food samples, also known as the curse of dimensionality. It is desirable to employ feature selection algorithms for decreasing computation burden and increasing predicting accuracy, which are especially relevant in the development of online applications. Recently, a variety of feature selection algorithms have been proposed that can be categorized into three groups based on the searching strategy namely complete search, heuristic search and random search. This review mainly introduced the fundamental of each algorithm, illustrated its applications in hyperspectral data analysis in the food field, and discussed the advantages and disadvantages of these algorithms. It is hoped that this review should provide a guideline for feature selections and data processing in the future development of hyperspectral imaging technique in foods.
Using high spatial and temporal resolution data blended from SPOT-5 and MODIS to map biomass of summer maize

Crop biomass plays an important role in food security and global carbon cycle. Recently, remote sensing technology has been proven to be an effective tool for biomass estimation with fewer field surveys. In this study, we try to map summer maize biomass using SPOT-5 (Systeme Probatoire d'Observation de la Terre-5) and MODIS (Moderate Resolution Imaging Spectroradiometer) MOD09Q1/A1 data. First, the STARFM (spatial and temporal adaptive reflectance fusion model) algorithm was applied to generate high spatio-temporal resolution NDVI (normalized difference vegetation index) and LSWI (land surface water index) datasets through fusing SPOT-5 and MODIS data. The blended NDVI and LSWI exhibited high correlations with the referenced SPOT-5 NDVI and LSWI (0.72 ≤ R2NDVI ≤ 0.76, 0.74 ≤ R2LSWI <; 0.86). Afterwards, a MLC (maximum likelihood classification) and ISODATA (Iterative Self-Organizing Data Analysis Technique) method was employed to cluster time series NDVI, result shows that 91.3% maize fields were correctly identified and the overall accuracy was 89.8% with a kappa of 0.7957, which was 10-20% higher than the classification of MODIS-NDVI. Finally, NDVI, LSWI and meteorological data were inserted into a light use efficiency model to estimate aboveground biomass, the estimated results that involved blended data correlated well with the measured values (0.66 ≤ R2 ≤ 0.75, 23.5 ≤ RMSE <; 163.4 g/m2), and more accurate than the estimation using MODIS data (0.51 ≤ R2 ≤ 0.66, 27.1 ≤ RMSE ≤ 174.4 g/m2). In addition, biomass distribution maps were generated based on the crop classification and estimation results. Our research provided a reliable method for the biomass mapping of summer maize with SPOT-5 and MODIS data, which is also very meaningful for the precision agriculture.
Stabilizing control of TCP/AQM networks with time delay in state variables

This paper studies how to design a congestion controller in TCP/AQM networks. In Hollot et al. (IEEE Trans. on Automatic Control, Vol. 47, No.6, 2002), the congestion controller is conservatively designed due to using the linearized model of the TCP/AQM networks in which a structured time-delay related term is treated as an unstructured uncertainty. Without treating any time-delay related term as uncertainty, we provide a necessary and sufficient a condition of existence of PI stabilizing controller for the system, and we propose a new design of the congestion controller via solving a stabilization problem of the system with a time delay in the variables of both state and input. The simulation results are provided to validate the proposed design method.
Neural Question Answer Systems : Biased Perspectives and Joint Answer Predictions

In the field of question answering, a fascinating subtask is the identification of contextual evidence that answers a given question. We demonstrate a deep learning model for this reading comprehension task, based on the Multi-Perspective Context Matching (MPCM) architecture that attains the reasonably high performance on the SQuAD dataset of 58.6% for F1 and 44.6% for EM. By combining ideas from MPCM with a variety of creative experimental extensions, we find that of the explored modifications, adding bias terms to perspective weights and predicting joint distributions increase performance, whereas other changes, such as changing relevancy filtering, introducing nonlinearity into the perspective layer, or predicting answer excerpts from a joint distribution, do not meaningfully improve the model.
Decomposition of the electromagnetic field in lossless inhomogeneous dispersive dielectrics.

The interaction of the electromagnetic field with lossless Lorentz oscillators modeling the inhomogeneous dielectrics is diagonalized in a closed Fabry-P\'erot resonator using the generalized polariton transformation. Resulting dispersion relations coincide with the classical ones obtained by the solution of the wave equation. The corresponding decomposition is, however, orthogonal and complete in the enlarged Hilbert space. \textcopyright{} 1996 The American Physical Society.
A texture-based metric extension for simplification methods

A card rack includes parallel pairs of coplanar fins that extend inwardly from side walls whose spacing is adjustable. The inner edges of the coplanar fins are spaced apart so as to provide a passage for an elongated stop member that extends through all the compartments. Holes in tabs at both ends of the stop member receive self-tapping screws. The threaded portions of the screws engage opposed faces of upper and lower pairs of fins to secure the stop member in place. The screws can be loosened to slide the stop member along the upper and lower compartments and thereby adjust the depth of all the compartments.
Treatment with a C5aR Antagonist Decreases Pathology and Enhances Behavioral Performance in Murine Models of Alzheimer’s Disease1

Alzheimer’s disease (AD) is an age-related dementia, characterized by amyloid plaques, neurofibrillary tangles, neuroinflammation, and neuronal loss in the brain. Components of the complement system, known to produce a local inflammatory reaction, are associated with the plaques and tangles in AD brain, and thus a role for complement-mediated inflammation in the acceleration or progression of disease has been proposed. A complement activation product, C5a, is known to recruit and activate microglia and astrocytes in vitro by activation of a G protein-coupled cell-surface C5aR. Here, oral delivery of a cyclic hexapeptide C5a receptor antagonist (PMX205) for 2–3 mo resulted in substantial reduction of pathological markers such as fibrillar amyloid deposits (49–62%) and activated glia (42–68%) in two mouse models of AD. The reduction in pathology was correlated with improvements in a passive avoidance behavioral task in Tg2576 mice. In 3xTg mice, PMX205 also significantly reduced hyperphosphorylated tau (69%). These data provide the first evidence that inhibition of a proinflammatory receptor-mediated function of the complement cascade (i.e., C5aR) can interfere with neuroinflammation and neurodegeneration in AD rodent models, suggesting a novel therapeutic target for reducing pathology and improving cognitive function in human AD patients.
Dental caries experience of disabled children and young adults in Kuwait.

OBJECTIVE The aim of the study was to assess the caries experience of disabled children and young adults in Kuwait, to set baseline data, and to determine their treatment need. METHOD Dental caries was scored by surface in accordance with WHO criteria. The study population comprised 832 disabled children and young adults (3-29 years; mean age 12.1 years) who were visually impaired, hearing impaired, had physical handicaps or developmental disorders, attending special needs schools. RESULTS The proportion of caries free subjects in the primary dentition (3-12-year-old children) was 11.2%. The mean dmft was 5.4, and dmfs 15.2, being highest in the Down's syndrome and lowest in the blind. The proportion of caries-free subjects in permanent dentition, over 5 years of age was 24.2%. The smallest percentage of caries-free subjects was found in the hearing impaired (16.4%) and highest percentage in the blind (35.5%). The mean DMFT was 4.5 and the DMFS 8.7, being highest in the Down's syndrome and lowest in the blind. Prevalence of untreated decay was highest in hearing impaired (86%). The caries experience of first permanent molars represented the largest proportion of the DMFT score (53.6%). In the permanent dentition increasing age, impaired hearing, and poor oral hygiene were significantly associated with caries risk. CONCLUSIONS Caries experience among this disabled population was clearly higher than among the respective age groups in a previous national population survey. The study confirmed the need for strengthening organised preventive and restorative care for this population in Kuwait.
Technological Progress and Population Growth: Do We Have Too Few Children?

Do we have too few children? We intend to address this question. In developed countries, the fertility rate has declined since WWII. This may cause a slowdown in the growth of GDP in developed countries. However, important factors for the well-being of individuals are per capita variables, like per capita growth and per capita consumption. In turn, the rate of technological progress determines the growth rates of per capita variables. If the population size is increasing, the labour inputs for R&D activity increase, and thus speed up technological progress. As individuals do not take account of this positive effect when deciding on the number of their own children, the number of children may become smaller than the socially optimal number of children. However, an increase in the number of children reduces the assets any one child owns: that is, there is a capital dilution effect. This works in the opposite direction. We examine this issue using an endogenous growth model where the head of a dynastic family decides the number of children.
Crystal structure of 2-[2-(benzyloxy)benzylidene]malononitrile

In the title benzylidenemalononitrile derivative, C17H12N2O, the dihedral angles between the central benzene ring and the Y-shaped C=C(CN)2 group (r.m.s. deviation = 0.006 Å) and the terminal benzene ring are 12.72 (8) and 37.60 (11)°, respectively. The Car—O—Csp 3—Car torsion angle is −174.52 (13)° and the major twist between the aromatic rings occurs about the Csp 3—Car bond. Weak aromatic π–π stacking [centroid–centroid separation = 3.7784 (13) Å; slippage = 1.21 Å] between inversion-related pairs of the central benzene rings is observed in the crystal.