Miracle-dz/UniFAR-FTUs huggingface dataset:
Tract‐specific analysis and neurocognitive functioning in sickle cell patients without history of overt stroke

Sickle cell disease (SCD) is a hereditary blood disorder in which the oxygen‐carrying hemoglobin molecule in red blood cells is abnormal. SCD patients are at increased risks for strokes and neurocognitive deficit, even though neurovascular screening and treatments have lowered the rate of overt strokes. Tract‐specific analysis (TSA) is a statistical method to evaluate microstructural WM damage in neurodegenerative disorders, using diffusion tensor imaging (DTI).
Development of a Smartphone-Based University Library Navigation and Information Service Employing Wi-Fi Location Fingerprinting

A guidance and information service for a University library based on Wi-Fi signals using fingerprinting as chosen localization method is under development at TU Wien. After a thorough survey of suitable location technologies for the application it was decided to employ mainly Wi-Fi for localization. For that purpose, the availability, performance, and usability of Wi-Fi in selected areas of the library are analyzed in a first step. These tasks include the measurement of Wi-Fi received signal strengths (RSS) of the visible access points (APs) in different areas. The measurements were carried out in different modes, such as static, kinematic and in stop-and-go mode, with six different smartphones. A dependence on the positioning and tracking modes is seen in the tests. Kinematic measurements pose much greater challenges and depend significantly on the duration of a single Wi-Fi scan. For the smartphones, the scan durations differed in the range of 2.4 to 4.1 s resulting in different accuracies for kinematic positioning, as fewer measurements along the trajectories are available for a device with longer scan duration. The investigations indicated also that the achievable localization performance is only on the few meter level due to the small number of APs of the University own Wi-Fi network deployed in the library. A promising solution for performance improvement is the foreseen usage of low-cost Raspberry Pi units serving as Wi-Fi transmitter and receiver.
Physics of surface vibrational resonances: pillared phononic crystals, metamaterials, and metasurfaces

The introduction of engineered resonance phenomena on surfaces has opened a new frontier in surface science and technology. Pillared phononic crystals, metamaterials, and metasurfaces are an emerging class of artificial structured media, featuring surfaces that consist of pillars—or branching substructures—standing on a plate or a substrate. A pillared phononic crystal exhibits Bragg band gaps, while a pillared metamaterial may feature both Bragg band gaps and local resonance hybridization band gaps. These two band-gap phenomena, along with other unique wave dispersion characteristics, have been exploited for a variety of applications spanning a range of length scales and covering multiple disciplines in applied physics and engineering, particularly in elastodynamics and acoustics. The intrinsic placement of pillars on a semi-infinite surface—yielding a metasurface—has similarly provided new avenues for the control and manipulation of wave propagation. Classical waves are admitted in pillared media, including Lamb waves in plates and Rayleigh and Love waves along the surfaces of substrates, ranging in frequency from hertz to several gigahertz. With the presence of the pillars, these waves couple with surface resonances richly creating new phenomena and properties in the subwavelength regime and in some applications at higher frequencies as well. At the nanoscale, it was shown that atomic-scale resonances—stemming from nanopillars—alter the fundamental nature of conductive thermal transport by reducing the group velocities and generating mode localizations across the entire spectrum of the constituent material well into the terahertz regime. In this article, we first overview the history and development of pillared materials, then provide a detailed synopsis of a selection of key research topics that involve the utilization of pillars or similar branching substructures in different contexts. Finally, we conclude by providing a short summary and some perspectives on the state of the field and its promise for further future development.
AMPA and NMDA Receptor Trafficking at Cocaine-Generated Synapses

Cocaine experience generates AMPA receptor (AMPAR)-silent synapses in the nucleus accumbens (NAc), which are thought to be new synaptic contacts enriched in GluN2B-containing NMDA receptors (NMDARs). After drug withdrawal, some of these synapses mature by recruiting AMPARs, strengthening the newly established synaptic transmission. Silent synapse generation and maturation are two consecutive cellular steps through which NAc circuits are profoundly remodeled to promote cue-induced cocaine seeking after drug withdrawal. However, the basic cellular processes that mediate these two critical steps remains underexplored. Using a combination of electrophysiology, viral-mediated gene transfer, and confocal imaging in male rats as well as knock-in (KI) mice of both sexes, our current study characterized the dynamic roles played by AMPARs and NMDARs in generation and maturation of silent synapses on NAc medium spiny neurons after cocaine self-administration and withdrawal. We report that cocaine-induced generation of silent synapses not only required synaptic insertion of GluN2B-containing NMDARs, but also, counterintuitively, involved insertion of AMPARs, which subsequently internalized, resulting in the AMPAR-silent state on withdrawal day 1. Furthermore, GluN2B NMDARs functioned to maintain these cocaine-generated synapses in the AMPAR-silent state during drug withdrawal, until they were replaced by nonGluN2B NMDARs, a switch that allowed AMPAR recruitment and maturation of silent synapses. These results reveal dynamic interactions between AMPARs and NMDARs during the generation and maturation of silent synapses after cocaine experience and provide a mechanistic basis through which new synaptic contacts and possibly new neural network patterns created by these synapses can be manipulated for therapeutic benefit. SIGNIFICANCE STATEMENT Studies over the past decade reveal a critical role of AMPA receptor-silent, NMDA receptor-containing synapses in forming cocaine-related memories that drive cocaine relapse. However, it remains incompletely understood how AMPA and NMDA receptors traffic at these synapses during their generation and maturation. The current study characterizes a two-step AMPA receptor trafficking cascade that contributes to the generation of silent synapses in response to cocaine experience, and a two-step NMDA receptor trafficking cascade that contributes to the maturation of these synapses after cocaine withdrawal. These results depict a highly regulated cellular procedure through which nascent glutamatergic synapses are generated in the adult brain after drug experience and provide significant insight into the roles of glutamate receptors in synapse formation and maturation.
Improving the Accuracy of the Fast Inverse Square Root by Modifying Newton–Raphson Corrections

Direct computation of functions using low-complexity algorithms can be applied both for hardware constraints and in systems where storage capacity is a challenge for processing a large volume of data. We present improved algorithms for fast calculation of the inverse square root function for single-precision and double-precision floating-point numbers. Higher precision is also discussed. Our approach consists in minimizing maximal errors by finding optimal magic constants and modifying the Newton–Raphson coefficients. The obtained algorithms are much more accurate than the original fast inverse square root algorithm and have similar very low computational costs.
Optimum Length of Silver Nanorods for Fabrication of Hot Spots

The optimum length of silver nanorods for surface-enhanced Raman scattering (SERS) was studied. Uniform silver nanorods in diameter and length were fabricated on porous anodic aluminum oxide templates prepared in sulfuric acid, and their lengths were varied by controlling the electrodeposition time. The diameter of the nanorods was approximately 37 nm, and the distance between the nanorods was very uniform at 65 nm. The nanorods were highly ordered with a hexagonal pattern and perfectly vertical with respect to the plane of the templates. A good SERS spectrum was observed for benzenethiol adsorbed at the tip of the isolated silver nanorods. The SERS intensity sensitively varied with the length of the nanorods and attained the maximum when the length was approximately 62 nm for excitation with a 632.8-nm laser line. The enhancement factor calculated by comparing the SERS intensity with the normal Raman intensity and by excluding the resonance effect of molecules was 3.9 × 107, while that calculated from th.
Inorganic and Polymeric Nanoparticles for Human Viral and Bacterial Infections Prevention and Treatment

Infectious diseases hold third place in the top 10 causes of death worldwide and were responsible for more than 6.7 million deaths in 2016. Nanomedicine is a multidisciplinary field which is based on the application of nanotechnology for medical purposes and can be defined as the use of nanomaterials for diagnosis, monitoring, control, prevention, and treatment of diseases, including infectious diseases. One of the most used nanomaterials in nanomedicine are nanoparticles, particles with a nano-scale size that show highly tunable physical and optical properties, and the capacity to a wide library of compounds. This manuscript is intended to be a comprehensive review of the available recent literature on nanoparticles used for the prevention and treatment of human infectious diseases caused by different viruses, and bacteria from a clinical point of view by basing on original articles which talk about what has been made to date and excluding commercial products, but also by highlighting what has not been still made and some clinical concepts that must be considered for futures nanoparticles-based technologies applications.
Gradient Internal Standard Method for Absolute Quantification of Microbial Amplicon Sequencing Data

To solve the problem of amplicon sequencing cannot discern the microbiota absolute abundance, we proposed a gradient internal standard absolute quantification method. We used Chinese liquor fermentation as a model system to demonstrate the reliability and accuracy of the method. ABSTRACT High-throughput amplicon sequencing is a critical tool for studying microbiota; however, it results only in relative abundance data. Thus, changes in absolute abundance of microbiota cannot be determined, which hinders further microbiology research. We have therefore established a gradient internal standard absolute quantification (GIS-AQ) method to overcome this issue, which can simultaneously obtain the absolute abundances of bacteria and fungi. Deviations from the quantitative equations of microbes and internal standards were eliminated through calibration. Compared with traditional quantitative real-time PCR and microscopy quantifications, this method is reliable (R2average = 0.998; P < 0.001) and accurate (Pinternals versus microscopy > 0.05). The GIS-AQ method can be adapted to any amplicon primer choice (e.g., 336F/806R and ITS3/ITS4), rendering it applicable to ecosystem studies including food, soil, and water samples. Crucially, when using solid-state fermentation samples from various temporal dimensions, the results obtained from the relative and absolute abundance are different. The absolute abundance can be used to study the difference in communities between different samples, and the GIS-AQ method allows this to be done rapidly. Therefore, combining the absolute abundance with relative abundance can accurately reflect the microbiota composition. IMPORTANCE To solve the problem of amplicon sequencing cannot discern the microbiota absolute abundance, we proposed a gradient internal standard absolute quantification method. We used Chinese liquor fermentation as a model system to demonstrate the reliability and accuracy of the method. By comparing the relative and absolute abundances of microbiota in various temporal dimensions, we found dynamic changes in the absolute abundance of communities under various temporal dimensions from the relative abundance. Based on its design principle, this method can be widely applied to different ecosystems. Therefore, we believe that the GIS-AQ method can play an immeasurably useful role in microbiological research.
Above and Below Ground Measurements of Greenhouse Gases from Swine Effluent Amended Soil

Abstract As a means of economic disposal and to reduce need for chemical fertilizer, waste generated from swine production is often applied to agricultural land. However, there remain many environmental concerns about this practice. Two such concerns, contribution to the greenhouse effect and stratospheric ozone depletion by gases emitted from waste‐amended soils, have not been thoroughly investigated. An intact core study at Auburn University (32 36′N, 85 36′W) was conducted to determine the source‐sink relationship of three greenhouse gases in three Alabama soils (Black Belt, Coastal Plain, and Appalachian Plateau regions) amended with swine waste effluent. Soil cores were arranged in a completely random design, and treatments used for each soil type consisted of a control, a swine effluent amendment (112 kg N ha−1), and an ammonium nitrate (NH4NO3) fertilizer amendment (112 kg N ha−1). During a 2‐year period, a closed‐chamber technique was used to determine rates of emission of nitrous oxide (N2O)–nitrogen (N), carbon dioxide (CO2)–carbon (C), and methane (CH4)–C from the soil surface. Gas probes inserted into the soil cores were used to determine concentrations of N2O‐N and CO2‐C from depths of 5, 15, and 25 cm. Soil water was collected from each depth using microlysimeters at the time of gas collection to determine soil‐solution N status. Application of swine effluent had an immediate effect on emissions of N2O‐N, CO2‐C, and CH4‐C from all soil textures. However, greatest cumulative emissions and highest peak rates of emission of all three trace gases, directly following effluent applications, were most commonly observed from sandier textured Coastal Plain and Appalachian Plateau soils, as compared to heavier textured Black Belt soil. When considering greenhouse gas emission potential, soil type should be a determining factor for selection of swine effluent waste disposal sites in Alabama.
Efficient gene expression signature for a breast cancer immuno-subtype.

MOTIVATION AND BACKGROUND The patient's immune system plays an important role in cancer pathogenesis, prognosis and susceptibility to treatment. Recent work introduced an immune related breast cancer. This subtyping is based on the expression profiles of the tumor samples. Specifically, one study showed that analyzing 658 genes can lead to a signature for subtyping tumors. Furthermore, this classification is independent of other known molecular and clinical breast cancer subtyping. Finally, that study shows that the suggested subtyping has significant prognostic implications. RESULTS In this work we develop an efficient signature associated with survival in breast cancer. We begin by developing a more efficient signature for the above-mentioned breast cancer immune-based subtyping. This signature represents better performance with a set of 579 genes that obtains an improved Area Under Curve (AUC). We then determine a set of 193 genes and an associated classification rule that yield subtypes with a much stronger statistically significant (log rank p-value < 2 × 10-4 in a test cohort) difference in survival. To obtain these improved results we develop a feature selection process that matches the high-dimensionality character of the data and the dual performance objectives, driven by survival and anchored by the literature subtyping.
An IoE and Big Multimedia Data Approach for Urban Transport System Resilience Management in Smart Cities

Today, the complexity of urban systems combined with existing and emerging threats constrains administrations to consider smart technologies and related huge amounts of data generated as a means to take timely and informed decisions. The smart city needs to be prepared for both expected and unexpected situations, and the possibility to mitigate the effect of the uncertainty behind the causes of disruptions through the analysis of all the possible data generated by the city open new possibility for resilience operationalization. This article aims at introducing a new conceptualization for resilience and presenting an innovative full stack solution to exploit Internet of Everything (IoE) and big multimedia data in smart cities to manage resilience of urban transport systems (UTS), which is one of the most critical infrastructures of the city. The approach is based on a novel data driven approach to resilience engineering and functional resonance analysis method (FRAM), to understand and model an UTS in the context of smart cities and to support evidence driven decision making. The paper proposes an architecture taking into account: (a) different kinds of available data generated in the smart city, (b) big data collection and semantic aggregation and enrichment; (c) data sense-making process composed by analytics of different data sources like social media, communication networks, IoT, user behavior; (d) tools for knowledge driven decisions able to combine different information generated by analytics, experience, and structural information of the city into a comprehensive and evidence driven decision model. The solution has been applied in Florence metropolitan city in the context of RESOLUTE H2020 research project of the European Commission.
Factors that affect the duration of wearing disposable personal protective equipment by healthcare professionals in Wuhan during treatment of COVID‐19 patients: An epidemiological study

Abstract The purpose of this study of healthcare workers who cared for COVID‐19 patients was to identify factors that affected the duration of wearing personal protective equipment (PPE). The results of this study will provide initial guidance to practicing clinicians and a foundation for further research on this topic. This cross‐sectional study examined 139 frontline healthcare professionals who worked at a single hospital in Wuhan, China, from March 16 to April 1, 2020. General and demographic data, physical and mental status, use of personal protective equipment, type of hospital work, and duration of wearing personal protective equipment were recorded. The mean duration of wearing personal protective equipment was 194.17 min (standard deviation: 3.71). Multiple linear regression analysis indicated that the duration of wearing personal protective equipment was significantly associated with the presence of a chronic disease, working hours when feeling discomfort, lack of patient cooperation and subsequent psychological pressure, prolonged continuous wearing of personal protective equipment, feeling anxious about physical strength, and the presence of fatigue when wearing personal protective equipment. These factors should be considered by practicing healthcare professionals and in future studies that examine the optimal duration of wearing personal protective equipment.
Intervention experiences among children with congenital and neonatal conditions impacting brain development: patterns of service utilization, barriers and future directions

Abstract Objective The current study examined reported patterns of utilization and barriers to early and school-age interventions, as well as directions for future care, among families of children with congenital or neonatal conditions with known-risk for poor neurocognitive development. The impact of the child’s severity of injury, condition and adaptive functioning, as well as family sociodemographic factors were considered. Methods The sample included 62 parents (53 mothers, 5 fathers, 4 mother-father pairs) of children diagnosed with neonatal stroke, hypoxia ischemic encephalopathy (HIE), and congenital heart disease (CHD) ranging in age between 3 to 9 years (mean age = 4.5 years, SD = 1.82). Results In this sample, approximately 80% of children were reported to have had utilized one or more therapies. The most frequent services utilized included: (a) speech and language therapy, (b) occupational therapy, and (c) physical therapy. Less than 10% of sample reported utilizing any psychological therapies. Common family barriers to all interventions included time off work, lack of childcare, and transportation. Parents of children with more severe injury or condition reported that their children were utilizing a greater number of interventions and also perceived a greater number of barriers. Over half of the parents expressed a need for more parent support groups, remote psychosocial services, and individualized psychological therapy for themselves or their family. Conclusions Findings highlight patterns of utilization and perceived gaps in early and school-age interventions for children with congenital or neonatal conditions that impact neurodevelopment. Direction for clinical care and improved intervention opportunities are discussed.
WSN-SES/MB: System Entity Structure and Model Base Framework for Large-Scale Wireless Sensor Networks

Large-scale wireless sensor networks are characterized by stringent energy and computation restrictions. It is exceedingly difficult to change a sensor network’s environment configurations, such as the number of sensor nodes, after deployment of the nodes. Although several simulators are able to variously construct simulation models for sensor networks before their deployment, the configurations should be modified with extra human effort as the simulators cannot freely generate diverse models. In this paper, we propose a novel framework, called a system entity structure and model base for large-scale wireless sensor networks (WSN-SES/MB), which is based on discrete event system specification formalism. Our proposed framework synthesizes the structure and models for sensor networks through our modeling construction process. The proposed framework achieves time and cost savings in constructing discrete event simulation-based models. In addition, the framework increases the diversity of simulation models by the process’s pruning algorithm. The simulation results validate that the proposed framework provides up to 8% time savings and up to 23% cost savings as compared to the manual extra effort.