Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetics of Multiple System Atrophy and Progressive Supranuclear Palsy: A Systemized Review of the Literature

Multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) are uncommon multifactorial atypical Parkinsonian syndromes, expressed by various clinical features. MSA and PSP are commonly considered sporadic neurodegenerative disorders; however, our understanding is improving of their genetic framework. The purpose of this study was to critically review the genetics of MSA and PSP and their involvement in the pathogenesis. A systemized literature search of PubMed and MEDLINE was performed up to 1 January 2023. Narrative synthesis of the results was undertaken. In total, 43 studies were analyzed. Although familial MSA cases have been reported, the hereditary nature could not be demonstrated. COQ2 mutations were involved in familial and sporadic MSA, without being reproduced in various clinical populations. In terms of the genetics of the cohort, synuclein alpha (SNCA) polymorphisms were correlated with an elevated likelihood of manifesting MSA in Caucasians, but a causal effect relationship could not be demonstrated. Fifteen MAPT mutations were linked with PSP. Leucine-rich repeat kinase 2 (LRRK2) is an infrequent monogenic mutation of PSP. Dynactin subunit 1 (DCTN1) mutations may imitate the PSP phenotype. GWAS have noted many risk loci of PSP (STX6 and EIF2AK3), suggesting pathogenetic mechanisms related to PSP. Despite the limited evidence, it seems that genetics influence the susceptibility to MSA and PSP. MAPT mutations result in the MSA and PSP pathologies. Further studies are crucial to elucidate the pathogeneses of MSA and PSP, which will support efforts to develop novel drug options.
Theoretical study of the properties of Nb-doped Li3YbCl6 solid-state electrolytes

Halide solid-state electrolytes have recently received significant attention because of their superior properties of electrochemical stability and high ionic conductivity. Experimentally, doping by tetravalent cations (such as Zr4+ and Hf4+) is usually adopted to further improve the ionic transport properties. To explore more dopant possibilities, we have thoroughly investigated the stabilities, ionic conductivities and electrochemical properties of pentavalent Nb-doped Li3YbCl6 by using first-principles calculations. Our calculated results have revealed that the most stable phase of Nb-doped Li3YbCl6 might be the structures with an orthorhombic space group. Also, it can be expected that a small amount of Nb doping can increase the ionic conductivity with a slightly decreased width of the electrochemical window of Li3YbCl6. This work demonstrates the potential of pentavalent cation doping for improving the performance of halide solid-state electrolytes.
Diffusion Coefficients of Impurities in Silicon Melt

Silicon single crystals are grown by the Czochralski method with a variety of growth rates and rotation rates. Segregation coefficients of impurities are found to depend on the growth conditions as is expected by the existing theory. Diffusion coefficients of impurities in silicon melt are determined for B, Al, Ga, In, P, As and Sb. Diffusion coefficients of group V impurities are found to increase as the tetrahedral covalent radius of the impurity atom decreases. In the case of group III impurities, the dependence of diffusion coefficients on the tetrahedral covalent radius is not so clear as in the case of group V impurities.
On a unified approach to the analysis of two-sided cumulative sum control schemes with headstarts

The necessary and sufficient conditions for various modes of interactions of the upper and lower schemes with headstarts are derived. The expression for the Laplace transform of the run-length distribution (for both interacting and non-interacting schemes) is obtained and used to develop a method of analysis for general two-sided cumulative sum schemes with headstarts. The results are shown to be relevant in the case when the schemes are supplemented by Shewhart’s control limits.
DRL-assisted joint allocation of antenna, radio, and front-haul resources in TWDM-PON-based NG-RANs with mMIMO-enabled beamforming

The high spectrum efficiency of massive multiple input multiple output (mMIMO)-enabled beamforming is attractive for solving the massive number of connections in next-generation radio access networks (NG-RANs). However, the beamforming based on multiple antenna sub-arrays to support multi-connections would introduce extra 2D antenna sub-array selection and radio resource block (RB) allocation; meanwhile, considering the front-haul bandwidth consumption would reduce as much as possible the redundant data transmitting over front-haul in the NG-RANs. Therefore, a key issue is how to coordinate 2D antenna sub-array selection and radio RB allocation to minimize the front-haul bandwidth and maximize the radio RB utilization when accommodating a set of beam antenna array (BAA) requests. In this paper, we first establish a 3D BAA mapping model to jointly optimize 2D antenna sub-array selection and radio RB allocation, which would in turn affect the allocation of the front-haul wavelength bandwidth in a time and wavelength division multiplexed passive optical network (TWDM-PON)-based front-haul with the mMIMO antenna system. An integer linear programming mathematical model is formulated, and a novel deep reinforcement learning (DRL)-based algorithm is proposed to optimize the front-haul bandwidth and radio RB utilization. Besides, two heuristic algorithms are developed with different antenna sub-array selection policies as the benchmarks. The extensive simulation results show that our proposed DRL-based algorithm can attain the lowest average cost (AC) for different numbers of BAA requests considered by seeking the optimal trade-off between the front-haul bandwidth consumption and the number of the used antennas. Compared with the inter-sub-array benchmark, the DRL-based algorithm can achieve up to 7.5% AC reduction, which is mainly attributed to the 21.2% reduction of the front-haul bandwidth without increasing the number of used antennas.
The Gaia-ESO Survey and Massive Stars

Abstract As part of the Gaia-ESO Survey (GES), a number of clusters will be observed that were chosen specifically for their massive-star content. We report on the procedures we followed to determine the stellar parameters from the massive-star spectra of this survey. We intercompare the results from the different techniques used by the nodes of our group to determine these parameters and discuss some of the problems encountered. We present preliminary results for NGC 6705, NGC 3293, and Trumpler 14. We study microturbulence in A-type stars, we use the repeat observation to investigate binarity, and we determine cluster membership from the radial velocity information. The large number of massive-star spectra obtained by the Gaia-ESO Survey will allow us to critically test stellar evolution modelling.
Stellar kinematics and interstellar turbulence

It is well known that the velocity dispersion of nearby stars increases systematically with age, and this fact is conventionally explained by postulating that stars are randomly accelerated by encounters with massive gas clouds (Spitzer & Schwarzschild 1951, 1953; Wielen 1977). However, a strong constraint on the possible role of random accelerations is provided by the apparent existence of fairly old moving groups of stars (Eggen 1969, Boyle & McClure 1975). An alternative explanation (Tinsley & Larson 1978) is that the age dependence of the velocity dispersion of stars older than 10 yr 1 S produced by a gradual decay with time of interstellar turbulent motions, as predicted by plausible collapse models. This effect cannot account directly for the variation of velocity dispersion with age observed for stars younger than 10 yr, but Tinsley & Larson suggested that this could be explained if the velocity dispersion of the youngest stars reflects only the local turbulent motions of the gas, while the velocity dispersion of older stars reflects in addition larger-scale non-circular motions in the galactic gas layer. If the interstellar medium possesses a hierarchy of motions whose velocity dispersion increases with the size of the region considered, older stars which have traveled farther since their formation will sample the gas motions over a larger volume of space, and thus will have a larger velocity dispersion than the younger stars.
Reliability and Criterion Validity for Three Potential Algebra Measures

This technical report summarizes the results of a study in which we examined the technical adequacy of three potential algebra measures for progress monitoring. One hundred thirteen students (18 of whom were receiving special education services) completed two forms of a Basic Skills probe, an Algebra Concepts probe, and a Content Analysis probe. In addition, we gathered data on criterion variables including grades, classroom assessment records, teacher ratings, and standardized test scores. We used multiple timing periods for the Basic Skills and Algebra Concepts probes to examine the efficacy of differing durations. We examined both test-retest and alternate form reliability for individual probes of all three types and for aggregated scores from two of the probe types. Criterion validity was examined using correlations between students’ probe scores and their scores from other indicators of algebra proficiency. The results of the study indicate that the Algebra Concepts probe is the most promising of the three measures investigated. It has adequate reliability and demonstrated the strongest correlations with the criterion measures. The Basic Skills probe had lower levels of reliability and more limited relations to the criterion measures (with the exception of the computation subtests of the standardized achievement tests). The Content Analysis probe had the highest levels of reliability among the three probes and moderate to moderately high correlations with several of the criterion measures. Concerns were identified about the difficulty of this probe because a large proportion of the students had scores of 10 or fewer points on the probe. Further research is needed to investigate more appropriate timing duration for the Basic Skills and Algebra Concepts probes. In the current study, the duration of the former was too short, while the duration of the latter was too long. The study should be replicated with additional, and more diverse student populations to determine the generalizability of the findings. Finally, subsequent research should examine the effects of routine progress monitoring on the measures’ stability and sensitivity to growth.
A simulative comparison of linear, quadratic and kernel discrimination

Three discriminant analysis models: linear discriminant analysis, quadratic discriminant analysis and a model using kernel estimation, are compared in a simulation study. Data are generated from multinormal, lognormal and mixtures of distributions. Some measures of performance that are based upon posterior probabilities are used for the comparison. The influence on performance of sample size, dimensionality and distance between populations is investigated. An algorithm to estimate the smoothness parameters for the kernel model is evaluated. Finally some remarks are made with respect to the so-called variable kernel model.
Spherical Hybrid Nanoparticles for Homann Stagnation-Point Flow in Porous Media via Homotopy Analysis Method

Non-axisymmetric stagnant-point flows for flat plates in porous media containing spherical Cu-Al2O3-H2O nanoparticles are studied using the homotopy analysis method (HAM). The governing equations are transformed into three coupled non-linear ordinary differential equations through similarity transformations. A large degree of freedom is provided by HAM when selecting auxiliary linear operators. By transforming nonlinear coupled ordinary differential equations with variable coefficients into linear ordinary differential equations with constant coefficients, nonlinear coupled ordinary differential equations can be solved. Over the entire domain, these equations can be solved approximately analytically. The analysis involves a discussion of the impact of many physical parameters generated in the proposed model. The results have shown that skin friction coefficients of Cfx and Cfy increase with volume fraction of hybrid nanofluid and the coefficient of permeability increasing. For the axisymmetric case of γ = 0, when volume fraction, φ, φ1, φ2 = 0, 5%, 10%, 20%, Cfx = Cfy = 1.33634, 1.51918, 1.73905, 2.33449, it can be found that the wall shear stress values increase by 13.68%, 30.14%, and 74.69%, respectively. In response to an increase in hybrid nanofluid volume fractions, local Nusselt numbers Nux increase. Nux decrease and change clearly with the coefficient of permeability increasing in the range of γ < 0; the values of Nux are less affected in the range of γ > 0.
Cell atlas of CCl4-induced progressive liver fibrosis reveals stage-specific responses

Chronic liver injury leads to progressive liver fibrosis and ultimately cirrhosis, a major cause of morbidity and mortality worldwide. However, there are currently no effective anti-fibrotic therapies available, especially for late-stage patients, which is partly attributed to the major knowledge gap regarding liver cell heterogeneity and cell-specific responses in different fibrosis stages. To reveal the multicellular networks regulating mammalian liver fibrosis from mild to severe phenotypes, we generated a single-nucleus transcriptomic atlas encompassing 49 919 nuclei corresponding to all main liver cell types at different stages of murine carbon tetrachloride (CCl4)-induced progressive liver fibrosis. Integrative analysis distinguished the sequential responses to injury of hepatocytes, hepatic stellate cells and endothelial cells. Moreover, we reconstructed the cell-cell interactions and gene regulatory networks implicated in these processes. These integrative analyses uncovered previously overlooked aspects of hepatocyte proliferation exhaustion and disrupted pericentral metabolic functions, dysfunction for clearance by apoptosis of activated hepatic stellate cells, accumulation of pro-fibrotic signals, and the switch from an anti-angiogenic to a pro-angiogenic program during CCl4-induced progressive liver fibrosis. Our dataset thus constitutes a useful resource for understanding the molecular basis of progressive liver fibrosis using a relevant animal model.
High-speed railway and shadow banking: evidence from finance leases

ABSTRACT This paper empirically investigates the effect of improved transportation infrastructure on finance leases, a representative form of China’s shadow banking sector, using a sample of Chinese listed companies. We find robust evidence that there is a significant decline in firms’ finance leases after the opening of the high-speed railway (HSR). Furthermore, HSR brings more favourable contract terms of leasing, including larger financing size, longer maturity, and lower cost. The heterogeneity analysis shows that HSR mainly reduces the costly nonbank-affiliated leases, and finance leases are reduced primarily in state-owned enterprises.
Intelligent Hybrid Scheme for Health Monitoring of Degrading Rotary Machines: An Adaptive Fuzzy c-Means Coupled With 1-D CNN

The development of a health monitoring (HM) scheme for complex rotary machines using unlabeled and imbalanced multivariate data is a well-recognized challenging problem. The challenges and complexity further increase when the health of the machine degrades over time. To utilize unlabeled and imbalanced multivariate degradation data, this article develops an intelligent HM scheme for rotary machines based on the proposed adaptive fuzzy $c$ -means clustering algorithm followed by ensemble learning, mean-variance-based samples generation method, and 1-D convolutional neural network. The adaptive fuzzy $c$ -means clustering algorithm uses nondominated sorting genetic algorithm II to automatically determine the different health state (HS) labels from unlabeled degradation data. The principle of ensemble learning is used to increase the robustness of the obtained HS labels. Further, based on obtained HSs, a new solution is presented to construct the true remaining useful life (RUL) adaptively. The proposed framework presents a novel method for generating samples based on mean-variance to deal with imbalanced HSs. Furthermore, an architecture of 1-D convolutional neural networks for multivariate data is designed to predict the HSs and RUL of rotary machines. The proposed approach has been validated through aero-engine and XJTU-SY bearing datasets. The HS prediction accuracy is as high as 99.97% and 100% for aero-engine and XJTU-SY datasets, respectively, using the proposed scheme. The results and comparative studies show the effectiveness of the proposed scheme.
Use of In Vitro Dynamic Colon Model (DCM) to Inform a Physiologically Based Biopharmaceutic Model (PBBM) to Predict the In Vivo Performance of a Modified-Release Formulation of Theophylline

A physiologically based biopharmaceutic model (PBBM) of a modified-release formulation of theophylline (Uniphyllin Continus® 200 mg tablet) was developed and implemented to predict the pharmacokinetic (PK) data of healthy male volunteers by integrating dissolution profiles measured in a biorelevant in vitro model: the Dynamic Colon Model (DCM). The superiority of the DCM over the United States Pharmacopeia (USP) Apparatus II (USP II) was demonstrated by the superior predictions for the 200 mg tablet (average absolute fold error (AAFE): 1.1–1.3 (DCM) vs. 1.3–1.5 (USP II). The best predictions were obtained using the three motility patterns (antegrade and retrograde propagating waves, baseline) in the DCM, which produced similar PK profiles. However, extensive erosion of the tablet occurred at all agitation speeds used in USP II (25, 50 and 100 rpm), resulting in an increased drug release rate in vitro and overpredicted PK data. The PK data of the Uniphyllin Continus® 400 mg tablet could not be predicted with the same accuracy using dissolution profiles from the DCM, which might be explained by differences in upper gastrointestinal (GI) tract residence times between the 200 and 400 mg tablets. Thus, it is recommended that the DCM be used for dosage forms in which the main release phenomena take place in the distal GI tract. However, the DCM again showed a better performance based on the overall AAFE compared to the USP II. Regional dissolution profiles within the DCM cannot currently be integrated into Simcyp®, which might limit the predictivity of the DCM. Thus, further compartmentalization of the colon within PBBM platforms is required to account for observed intra-regional differences in drug distribution.
High-Accuracy Relative Event Locations Using a Combined Multiplet Analysis and the Double-Difference Inversion.

Summary In this work we apply multiplet analysis together with the double difference method (DD) to improve the accuracy of relative locations between microseismic events. We first identify multiplet groups, or groups of events that have similar waveforms and source mechanisms, by crosscorrelating all events with each other. Next we apply the double-difference algorithm. This is a relative location method that tries to minimize the residuals between observed and calculated travel-time differences for pairs of microseismic events at each station, done by iteratively adjusting the differences between all pairs of events in each multiplet group. Both techniques are applied to a microseismic data set from the mining industry. Results of DD are shown for one major multiplet group containing 29 events, revealing a clearer linear feature with a NE-SW strike after relocation.
Competition, open innovation, and growth challenges in the semiconductor industry: the case of Europe’s clusters

In recent years, public policymakers in Europe have become increasingly aware of the need to support Europe’s failing semiconductor industry. This is an emerging policy area, and this paper examines the current state of the industry in Europe and assesses its potential future. It contends that the competitiveness of the industry will be related to its innovative capacity, especially its capability to engage in processes of open innovation. The industry in Europe is largely located in a number of discrete regional clusters, and the analysis focuses on data collected from a series of interviews with lead representatives of these clusters. The analysis indicates that the challenges facing the industry stem from the structure of the industry in Europe and the structure of the wider European technology industry. It is concluded that policies, such as the introduction of the European Chips Act, are likely to have a limited, or even negative, impact on the types of open innovation–led growth that will improve long-term competitiveness.
Size distributions for excursion sets

By "thresholding" a random field, excursion set models for binary images can be obtained. For random set models, the behaviour of the size distributions is important. Unfortunately, the study of size distributions for excursion sets of random fields represents a difficult problem. However, there is a connection between Linear size distributions for excursion sets and certain first passage distributions for one dimensional processes and their Palm processes following an upcrossing. There are existing computational methods for rapidly calculating these first passage distributions and these can be exploited for studying excursion set geometry.
Hesperetin Ameliorates Inhibition of Neuronal and Oligodendroglial Cell Differentiation Phenotypes Induced by Knockdown of Rab2b, an Autism Spectrum Disorder-Associated Gene Product

Autism spectrum disorder (ASD) is a central nervous system (CNS) neurodevelopmental disorder that includes autism, pervasive developmental disorder, and Asperger’s syndrome. ASD is characterized by repetitive behaviors and social communication deficits. ASD is thought to be a multifactorial disorder with a range of genetic and environmental factors/candidates. Among such factors is the rab2b gene, although it remains unclear how Rab2b itself is related to the CNS neuronal and glial developmental disorganization observed in ASD patients. Rab2 subfamily members regulate intracellular vesicle transport between the endoplasmic reticulum and the Golgi body. To the best of our knowledge, we are the first to report that Rab2b positively regulates neuronal and glial cell morphological differentiation. Knockdown of Rab2b inhibited morphological changes in N1E-115 cells, which are often used as the neuronal cell differentiation model. These changes were accomplished with decreased expression levels of marker proteins in neuronal cells. Similar results were obtained for FBD-102b cells, which are used as the model of oligodendroglial cell morphological differentiation. In contrast, knockdown of Rab2a, which is another Rab2 family member not known to be associated with ASD, affected only oligodendroglial and not neuronal morphological changes. In contrast, treatment with hesperetin, a citrus flavonoid with various cellular protective effects, in cells recovered the defective morphological changes induced by Rab2b knockdown. These results suggest that knockdown of Rab2b inhibits differentiation in neuronal and glial cells and may be associated with pathological cellular phenotypes in ASD and that hesperetin can recover their phenotypes at the in vitro level at least.