Miracle-dz/UniFAR-FTUs huggingface dataset:
Can the Treatment of Normal-Pressure Hydrocephalus Induce Normal-Tension Glaucoma? A Narrative Review of a Current Knowledge

Ventriculoperitoneal shunt placement is the most commonly used treatment of normal-pressure hydrocephalus (NPH). It has been hypothesized that normal-tension glaucoma (NTG) is caused by the treatment of NPH by using the shunt to reduce intracranial pressure (ICP). The aim of this study is to review the literature published regarding this hypothesis and to emphasize the need for neuro-ophthalmic follow-up for the concerned patients. The source literature was selected from the results of an online PubMed search, using the keywords “hydrocephalus glaucoma” and “normal-tension glaucoma shunt”. One prospective study on adults, one prospective study on children, two retrospective studies on adults and children, two case reports, three review papers including medical hypotheses, and one prospective study on monkeys were identified. Hypothesis about the association between the treatment of NPH using the shunt to reduce ICP and the development of NTG were supported in all reviewed papers. This suggests that a safe lower limit of ICP for neurological patients, especially shunt-treated NPH patients, should be kept. Thus, we proposed to modify the paradigm of safe upper ICP threshold recommended in neurosurgery and neurology into the paradigm of safe ICP corridor applicable in neurology and ophthalmology, especially for shunt-treated hydrocephalic and glaucoma patients.
NEW METHOD FOR BATCH TESTING of RED TART CHERRIES FOR the PRESENCE of PITS

A method was developed to determine the number of pits in samples of red tart pitted (RTP) cherries. the method is based on pulping the sample in a modified kitchen blender and detecting pits either from the noise of pits rattling in the blender or by pouring the resulting pulp through a trap designed to retain the pits. the method is more rapid and convenient than the present method and allows the recovery of tested product as juice. Screening missed a total of 1 1/2 pits when 1 pit was added to each of 233 samples consisting of fresh, fresh frozen, individually quick frozen and bulk frozen RTP cherries.
Psoriasis: Pathogenesis, Comorbidities, and Therapy Updated

Psoriasis is a chronic inflammatory skin disease characterized by IL-17-dominant abnormal innate and acquired immunity, and the hyperproliferation and aberrant differentiation of epidermal keratinocytes, and comorbid arthritis or cardiometabolic diseases. This Special Issue presented updated information on pathogenesis, comorbidities, and therapy of psoriasis. The pathogenesis of psoriasis may involve the dysfunction of indoleamine 2,3-dioxygenase 2 or of UBA domain containing 1-mediated regulation of CARD14/CARMA2sh. The blood cells of psoriasis patients showed the enhanced oxidative stress/autophagy flux and decreased 20S proteasome activity. Elafin, clusterin, or selenoprotein P may act as biomarkers for psoriasis and comorbid metabolic diseases. The proteomic profile of psoriasis lesions showed the dysfunction of dermal fibroblasts; up-regulation of proinflammatory factors and signal transduction or down-regulation of structural molecules. The skin inflammation in psoriasis may populate certain gut bacteria, such as Staphylococcus aureus and Streptococcus danieliae, which worsen the skin inflammation in turn. The psoriasis-associated pruritus may be caused by immune, nervous, or vascular mechanisms. In addition to current oral treatments and biologics, a new treatment option for psoriasis is now being developed, such as retinoic-acid-receptor-related orphan nuclear receptor γt inhibitors, IL-36 receptor antagonist, or aryl hydrocarbon receptor agonist. Antimicrobial peptides and innate immune cells, involved in the pathogenesis of psoriasis, may be novel therapeutic targets. The pathomechanisms and responses to drugs in collagen diseases are partially shared with and partially different from those in psoriasis. Certain nutrients can exacerbate or regulate the progress of psoriasis. The articles in this Special Issue will encourage attractive approaches to psoriasis by future researchers.
COVID-19 and Neurological Impairment: Hypothalamic Circuits and Beyond

In December 2019, a novel coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, the capital of Hubei, China. The virus infection, coronavirus disease 2019 (COVID-19), represents a global concern, as almost all countries around the world are affected. Clinical reports have confirmed several neurological manifestations in COVID-19 patients such as headaches, vomiting, and nausea, indicating the involvement of the central nervous system (CNS) and peripheral nervous system (PNS). Neuroinvasion of coronaviruses is not a new phenomenon, as it has been demonstrated by previous autopsies of severe acute respiratory syndrome coronavirus (SARS-CoV) patients who experienced similar neurologic symptoms. The hypothalamus is a complex structure that is composed of many nuclei and diverse neuronal cell groups. It is characterized by intricate intrahypothalamic circuits that orchestrate a finely tuned communication within the CNS and with the PNS. Hypothalamic circuits are critical for maintaining homeostatic challenges including immune responses to viral infections. The present article reviews the possible routes and mechanisms of neuroinvasion of SARS-CoV-2, with a specific focus on the role of the hypothalamic circuits in mediating the neurological symptoms noted during COVID-19 infection.
Deriving Leaf Area Index Reference Maps Using Temporally Continuous In Situ Data: A Comparison of Upscaling Approaches

To further progress the validation of global leaf area index (LAI) products, temporally continuous reference data are a key requirement, as periodic field campaigns fail to adequately characterize temporal dynamics. Progress in cost-effective automated measurement techniques has been made in recent years, but appropriate upscaling methodologies are less mature. Recently, the use of multitemporal transfer functions has been proposed as a potential solution. Using data collected during an independent field campaign, we evaluated the performance of both vegetation index-based multitemporal transfer functions and a radiative transfer model (RTM)-based upscaling approach. Whether assessed using cross validation or data from the independent field campaign, the RTM-based approach provided the best performance (r2 ≥ 0.88, RMSE ≤ 0.41, NRMSE < 13%). For upscaling temporally continuous in situ data, the ability of RTM-based approaches to account for seasonal changes in sun-sensor geometry is a key advantage over vegetation index-based multitemporal transfer functions.
Assessing Young Consumers’ Responses to Sustainable Labels: Insights from a Factorial Experiment in Italy

This study provides insights into young consumers’ responses to sustainable labels. Drawing on signaling theory, the article studies how third-party labels (TPLs) act and interact with company-level claims, trying to better understand their impact on young consumers’ perceptions and willingness to buy (pay for) a chocolate bar. A between-subjects factorial experiment—conducted by manipulating third-party sustainable labels (presence/absence of the labels) and self-declared claims (absence of the claim, formal claim, and friendly claim)—was used to test: (a) the effect of TPLs and self-declared claims on consumers’ perceptions, purchase intention, and willingness to pay, (b) whether this effect was mediated through the perceived credibility of the sustainability message, and (c) what kind of tone-of-voice adopted in the company’s claim was more effective. Data were collected via an online survey among a sample of 315 consumers (age range: 18–39 years) in South Italy. We found that third-party labels, “alone” were not effective in influencing consumers’ perceptions and willingness to buy/pay, while a self-declared claim, especially if characterized by a formal tone of voice, had a much more relevant impact. The combination of TPLs and self-declaration affected most consumers’ willingness to pay when the copy claim was informal. The perceived credibility of the sustainability message mediated the relationships between self-declared claims and the majority of the dependent variables, while, with reference to the relationship between TPLs and dependent variables, it did not act as a mediator.
Stretching response of discrete semiflexible polymers

We demonstrate that semiflexible polymer chains (characterized by a persistence length 𝓁 ) made up of discrete segments or bonds of length b show at large stretching forces a crossover from the standard wormlike chain (WLC) behavior to a discrete-chain (DC) behavior. In the DC regime, the stretching response is independent of the persistence length and shows a different force dependence than in the WLC regime. We perform extensive transfer-matrix calculations for the force-response of a freely rotating chain (FRC) model as a function of varying bond angle γ (and thus varying persistence length) and chain length. The FRC model is a first step toward the understanding of the stretching behavior of synthetic polymers, denatured proteins, and single-stranded DNA under large tensile forces. We also present scaling results for the force response of the elastically jointed chain (EJC) model, that is, a chain made up of freely jointed bonds that are connected by joints with some bending stiffness; this is the dis.
Cooling System with PCM Storage for an Office Building: Experimental Investigation Aided by a Model of the Office Thermal Dynamics

The application of energy storage filled with phase-change material (PCM) is recently increasingly considered in active cooling systems. Such a design offers a higher density of thermal energy accumulation when compared with water storage. However, the optimum use of PCM storage is possible when its dynamic characteristics during the loading and unloading process are well recognized. Due to the complexity of the interaction between all elements of the heating/cooling system, a theoretical estimation of the profits is hard to perform in a reliable way. This is a significant problem at the design stage of the installation. In order to solve this problem, a laboratory experiment supported by a simulation was performed. The main aim of the experiment was to understand how the storage filled with the PCM in real-like conditions works. A test stand was made to investigate the effect of this solution on a reduced scale of 1:10. The PCM tested was RT15, a commercially available material that melts in the temperature range of 10–17 °C. The main parts of the stand are a chiller, an electric heater and thermal energy storage. The first two elements allowed a simulation of the thermal properties of the heat receiver, and their operation depended on the results from the numerical calculations. A lumped parameter model was used in mathematical description of the office building and its cooling system. The heat capacity of the system components as well as heat losses to the ambient environment were taken into account. The obtained results allowed the optimization of the control procedure and proved the validity of the applied investigation methods. This study confirmed the possibility of testing thermal energy storage with phase change material in real-like conditions.
EDGES: An Efficient Distributed Graph Embedding System on GPU Clusters

Graph embedding training models access parameters sparsely in a “one-hot” manner. Currently, the distributed graph embedding neural network is learned by data parallel with the parameter server, which suffers significant performance and scalability problems. In this article, we analyze the problems and characteristics of training this kind of models on distributed GPU clusters for the first time, and find that fixed model parameters scattered among different machine nodes are a major limiting factor for efficiency. Based on our observation, we develop an efficient distributed graph embedding system called EDGES, which can utilize GPU clusters to train large graph models with billions of nodes and trillions of edges using data and model parallelism. Within the system, we propose a novel dynamic partition architecture for training these models, achieving at least one half of communication reduction compared to existing training systems. According to our evaluations on real-world networks, our system delivers a competitive accuracy for the trained embeddings, and significantly accelerates the training process of the graph node embedding neural network, achieving a speedup of 7.23x and 18.6x over the existing fastest training system on single node and multi-node, respectively. As for the scalability, our experiments show that EDGES obtains a nearly linear speedup.
Diffusion of interacting lattice gases on heterogeneous surfaces

The Monte Carlo method is used to simulate diffusion of interacting lattice gases on heterogeneous surfaces. The fluctuation and Kubo-Green methods are utilized for determining the tracer and chemical surface diffusion coefficients. Simulations are carried out on a square array of64 x 64 lattice sites applying periodic boundary conditions. Surface heterogeneity is introduced in terms of the bivariate trap model with random topography. Simulations are performed for a trap concentration θ trap = 0.2 and various values of the trap binding energies ∈ 2 , ∈ 1 and the nearest neighbor interaction energy φ NN . For φ NN < 0 (repulsion) the system exhibits c(2 x 2) ordering at half coverage and low temperatures. Due to the low compressibility of the well-ordered c(2 x 2) lattice gas phase, the chemical diffusion coefficient is large under these circumstances. The effects of surface heterogeneity, ∈ 1 ¬= ∈ 2 , are largely pronounced at low total coverages 0 and low temperatures T where most of the adatoms are trapped by the deep traps. At higher coverages the effects are relatively small albeit significant. The existence of deep traps disturbs c(2 x 2)ordering at θ = 0.5 and low temperatures. It is shown that the breakdown ofthe order substantially affects surface diffusion.
Intelligent Tuning of Microwave Cavity Filters Using Granular Multi-Swarm Particle Swarm Optimization

The tuning of microwave cavity filters (MCFs) is a complex process to improve the filtering performance. In practice, the tuning is mostly conducted in a manual way, and thus is time and resource intensive. Toward the demand for automatic tuning of MCFs with high accuracy and efficiency, this article proposes an intelligent tuning method for MCFs via modeling and optimization. The main contributions are threefold as follows: 1) A series of performance evaluation functions are defined to comprehensively characterize the tuning output; 2) a block modeling method is proposed to construct the electromechanical characteristic model to facilitate the calculation of the cost function; 3) an improved particle swarm optimization (PSO) algorithm, named granular multi-swarm PSO (GMS-PSO), is proposed to achieve quick search of optimal combinations of the tunable components. The effectiveness and practicality of the proposed method are demonstrated by experiments with a real intelligent tuning system.
Amorphous and crystalline blends from polytyrosine and pyridine-functionalized anthracene: hydrogen-bond interactions, conformations, intramolecular charge transfer and aggregation-induced emission

A new pyridine-terminated fluorophore of (E)-4-(2-(anthracen-9-yl)vinyl)pyridine (AnPy) with intramolecular charge transfer (ICT) and aggregation-induced emission (AIE) properties was synthesized and was blended with different amounts of polytyrosine (PTyr) through preferable hydrogen-bond (H-bond) interactions. In blends of a low AnPy content, the rigid PTyr peptide chains serve as templates to H-bond to AnPys, imposing rotational restriction and reinforcing the AIE-related emission intensity of AnPys, resulting in amorphous blends with the observed glass transitions dependent on the composition of the blends. In contrast, when large amounts of AnPys were added, excess AnPys will form new crystals, in between the amorphous regions, constituted of the near parallel dimers of AnPys. With the hampered molecular rotation, the parallel dimers of AnPys in the highly AnPy-loaded blends emit strongly with intensity much higher than those for the amorphous blends. In this study, conformations of the blends and the degree of restricted molecular rotation were assessed in order to correlate with the AIE-related fluorescence behaviour.
Unmodified glassy carbon electrode as a reliable sensor for sensitive voltammetric quantification of vitamin D3

In this paper a sensitive voltammetric method was developed for determination of vitamin D3 in commercial dietetic supplements using unmodified glassy carbon electrode as a working electrode. Following the optimization of the square-wave voltammetric method, the linear relationship between the peak current and vitamin D3 concentration was perceived in the concentration range of 1.25-105 ? mol/L. The calculated values of detection limit and quantification limit were 0.24 and 0.73 ? mol/L, respectively. In addition, the developed analytical procedure revealed exceptional precision with RSD values for intra- and inter-day (n=7) lower than 3%. Finally, developed voltammetric method was successfully applied for the determination of vitamin D3 in dietetic supplements using standard addition method.
Syntheses, structures, and IR spectroscopic characterization of new uranyl sulfate/selenate 1D-chain, 2D-sheet and 3D-framework

Abstract Three uranyl sulfates, (C6H20N4)[(UO2)2(SO4)4 · (H2O)2](H2O)6 (TETAUS), (C15H14N3)[(UO2)(SO4)2](NO3) · (H2O)2 (TPUS), and K2[(UO2)(SO4)2(H2O)] · H2O (KUS), and two uranyl selenates, K(H3O)[(UO2)2(SeO4)3 · (H2O)](H2O)6 (KUSe) and (H3O)2[(UO2)2(SeO4)3 · (H2O)] (USe), were synthesized by slow evaporation of aqueous solutions at room temperature. TETAUS crystallizes in space group P-1, a = 6.7186(5) Å, b = 9.2625(7) Å, c = 13.1078(9) Å, α = 72.337(2)°, β = 89.198(2)°, γ = 70.037(1)°, V = 726.89(9) Å3, Z = 1. TPUS is triclinic, P-1, a = 6.9732(7) Å, b = 13.569(1) Å, c = 13.641(1) Å, α = 111.809(2)°, β = 102.386(2)°, γ = 93.833(2)°, V = 1150.0(2) Å3, Z = 2. KUS is orthorhombic, Cmca, a = 12.171(2) Å, b = 16.689(3) Å, c = 10.997(2) Å, V = 2233.8(6) Å3, Z = 8. These uranyl sulfates are built from infinite one-dimensional uranyl sulfate chains with different topologies. KUSe is monoclinic, P21/n, a = 14.715(1) Å, b = 10.1557(7) Å, c = 15.833(1) Å, β = 114.415(1)°, V = 2154.5(3) Å3, Z = 4. Its structure is based on a two-dimensional uranyl selenate sheet. USe crystallizes in space group P21/c, a = 10.6124(2) Å, b = 14.7717(3) Å, c = 13.7139(3) Å, β = 96.989(1)°, V = 2133.86(8) Å3, Z = 4, with a complex three-dimensional uranyl selenate framework containing channels extending in three directions.
Bathymetric Retrieval Selectively Using Multiangular High-Spatial-Resolution Satellite Imagery

This article introduces multiangular imagery into physics-based bathymetry in order to compensate for the shortage of bathymetric spectral bands caused by the low spectral resolution of current high-spatial-resolution satellite multispectral imagery. The focus is to propose a selective bathymetric retrieval method to eliminate the negative effect of nonoptimal image data on depth retrieval in multiangular imagery-based bathymetry. The elimination of the negative effect is implemented by excluding nonoptimal pixels in every individual image from bathymetric retrieval. An empirical criterion is designed for the determination of nonoptimal pixels. The proposed method can use multiangular image data selectively, avoiding situations where bathymetric retrieval results from the whole multiangular imagery are poorer than that from a part of the individual images. The method was tested in two typical areas within the Xisha (Paracel) Islands of the South China Sea using two-angle WorldView-2 multispectral images. The test showed that the derived depths of the method (i.e., depths derived from the selective image data) provided a better fit to the validation depths than those from the entirety of both images. The underestimation of depths derived from the entirety of both images was also improved to some extent.
Do students and canteen vendors think differently about food segregation?

In university “X” (UX), littering is no longer a problem, but segregating waste is still not evident. Logically, students and canteen vendors are the ones who produce most of the waste. In this study, the authors want to explore whether students would think differently about handling waste compared to canteen vendors. Using the theory of planned behavior as the theoretical framework, the authors indeed found that students compared with canteen vendors had significantly different attitudes, norms, and perceived behavior control. Students have a more positive attitude towards waste segregation, but they do not perceive it as an essential norm that the canteen vendors perceive. Interestingly, canteen vendors segregate food waste, but students do not segregate. After checking it qualitatively, canteen vendors segregate their waste because they are obliged to the faculty management rules. And the reason for students’ lower performance in segregating waste is that they do not know the campus’ program of waste management. It is concluded that the lack of socialization hinders student’s pro-environmental behavior, and the waste segregating behavior from canteen vendors is affected by the existing norms and rules.