Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances in Fast Vessel-Wall Magnetic Resonance Imaging Using High-Density Coil Arrays

Arteriosclerosis is the leading cause of stroke, with a fatality rate surpassing that of ischemic heart disease. High-resolution vessel wall magnetic resonance imaging is generally recognized as a non-invasive and panoramic method for the evaluation of arterial plaque; however, this method requires improved signal-to-noise ratio and scanning speed. Recent advances in high-density head and neck coil arrays are characterized by broad coverage, multiple channels, and close-fitting designs. This review analyzes fast magnetic resonance imaging from the perspective of accelerated algorithms for vessel wall imaging and demonstrates the need for effective algorithms for signal acquisition using advanced radiofrequency system. We summarize different phased-array structures under various experimental objectives and equipment conditions, introduce current research results, and propose prospective research studies in the future.
Evolution of Prodromal Multiple System Atrophy from REM Sleep Behavior Disorder: A Descriptive Study

Background: Prodromal multiple system atrophy (MSA) has been characterized mainly by retrospective chart reviews. Direct observation and tracking of prodromal markers in MSA have been very limited Objective: To report the baseline characteristics and evolution of prodromal markers of MSA as they were prospectively measured in patients with idiopathic/isolated REM sleep behavior disorder (iRBD) Methods: Patients with iRBD were evaluated as part of a comprehensive protocol repeated annually. The protocol included assessment of motor, sleep, psychiatric, and autonomic symptoms supplemented by motor examination, quantitative motor testing, neuropsychological examination, orthostatic blood pressure measurement, and tests of olfaction and color vision. Patients who eventually developed MSA were described and compared with those who phenoconverted to Lewy body disease (Parkinson’s disease and dementia with Lewy bodies). Results: Of 67 phenocoverters, 4 developed MSA-P and 63 developed Lewy body disease. An additional 2 MSA-C patients were seen at baseline, already with cerebellar signs. Compared to those with Lewy body disease, those with MSA-P were younger, had less severe loss of tonic REM sleep atonia, more insomnia symptoms, and better olfaction. Clinically-evident autonomic dysfunction was not invariable in prodromal stages, often developing proximate to or after motor phenoconversion. Of the autonomic symptoms, genitourinary dysfunction was the first to develop in all cases. Olfaction and cognition remained normal throughout the prodromal and clinical disease course, in clear contrast to patients with Lewy body disease. Conclusion: Prodromal MSA progresses rapidly, often without substantial autonomic dysfunction, and with preserved olfaction and cognition throughout its prodromal course.
A Novel Method to Use Coordinate Based Meta-Analysis to Determine a Prior Distribution for Voxelwise Bayesian Second-Level fMRI Analysis

Previous research showed that employing results from meta-analyses of relevant previous fMRI studies can improve the performance of voxelwise Bayesian second-level fMRI analysis. In this process, prior distributions for Bayesian analysis can be determined by information acquired from the meta-analyses. However, only image-based meta-analysis, which is not widely accessible to fMRI researchers due to the lack of shared statistical images, was tested in the previous study, so the applicability of the prior determination method proposed by the previous study might be limited. In the present study, whether determining prior distributions based on coordinate-based meta-analysis, which is widely accessible to researchers, can also improve the performance of Bayesian analysis, was examined. Three different types of coordinate-based meta-analyses, BrainMap and Ginger ALE, and NeuroQuery, were tested as information sources for prior determination. Five different datasets addressing three task conditions, i.e., working memory, speech, and face processing, were analyzed via Bayesian analysis with a meta-analysis informed prior distribution, Bayesian analysis with a default Cauchy prior adjusted for multiple comparisons, and frequentist analysis with familywise error correction. The findings from the aforementioned analyses suggest that use of coordinate-based meta-analysis also significantly enhanced performance of Bayesian analysis as did image-based meta-analysis.
Design of Minimal Capacitance Detect Circuit for MEMS Capacitive Sensor

The capacitance among the structure of the accelerometer is rather small, usually at sub-pF level. Detection of the capacitance among the sensor’s tiny structure and analysis of the variation of these capacitances are necessary to improve the sensor’s performance. In this paper, one capacitance detect circuit for minimal capacitance is designed. Simulation and experiment results indicate a good linearity when the circuit is applied to detect capacitance range from 0.5pF to 5pF.
The Organizational Context of Specialized Craft Production in Early Mesopotamian States

In this essay, we examine the organizational context of craft production by comparing ceramic production at the urban center of Leilan (Syria) with the evidence fro textile and metal production at other, contemporaneous Mesopotamian sites. Archaeological and textual data from the mid-third millennium B.C. state societies of Mesopotamia and North Syria provide a particularly useful case study on the political economy of craft specialization. Several researchers have suggested that specialized ceramic production in Mesopotamian city-states was administered by the elite institutions such as the palace and temples. We suggest that the available evidence does not support this view of Mesopotamian political economy.
Effects of Turbulence Modeling and Turbulent Schmidt Number on Supersonic Mixing Simulations

The supersonic mixing flow field of a Helium jet in cross-stream air is numerically simulated in the present study by solving the two-dimensional Reynolds-Averaged Navier-Stokes equations. Turbulence contribution is obtained from the Realizable k-ε and the SST k-ω model. Each model is incorporated separately with four different turbulent Schmidt numbers, i.e., 0.50, 0.35, 0.25, and 0.20. The focus of this paper is to guide the selection of a suitable turbulence model with an appropriate turbulent Schmidt number for these types of complex mixing simulations. The results show that both of the models can predict the general flow behavior while exhibiting their advantages. A better agreement with the experimental data is obtained when the turbulent Schmidt number is gradually decreased. However, examining the critical characteristics like upstream flow separation, bow shock prediction, and mass concentration of Helium the SST k-ω model with turbulent Schmidt number 0.20 can be considered for the reasonable estimation of the supersonic mixing flow field.
Towards an intrusion detection system for detecting web attacks based on an ensemble of filter feature selection techniques

ABSTRACT The use of machine learning models in intrusion detection systems (IDSs) takes more time to build the model with many features and degrade the performance. The present paper proposes an ensemble of filter feature selection techniques (EFFST) to obtain a significant feature subset for web attack detection by selecting one-fourth split of the ranked features. The experimentation on the CICIDS 2017 dataset shows that the proposed EFFST method provides a detection rate of 99.9909%, with J48 using 24 features. The system’s performance is compared to the original features and traditional relevant feature selection methods employed in IDSs.
Robust Localization of Occluded Targets in Aerial Manipulation Via Range-Only Mapping

This letter studies the problem of target localization in aerial manipulation tasks. When an aerial robot flies close to a target to manipulate, the target would be occluded by the onboard robotic manipulator occasionally or for a long period of time. It is, however, necessary to continuously localize the target even when it is occluded. This is a unique problem in aerial manipulation and has not been addressed in other tasks such as ground manipulation. To solve this problem, we propose a new approach of target-centered range-only mapping based on RGB-D measurements. Different from the traditional map representation where the 3D locations of the feature points are stored in a global reference coordinate frame, we store the distances from the target to the environmental feature points only. It thus results in a coordinate-free target-centered range-only map. When the target is occluded, it can still be localized accurately based on the map. The proposed approach is verified by both synthetic and real datasets. The experimental results demonstrate the superior performance of our proposed approach to the state-of-the-art RGB-D ORB-SLAM3 method.
Experimental Verification of Micro-Doppler Radar Measurements of Fall-Risk-Related Gait Differences for Community-Dwelling Elderly Adults

In a previous study, we developed a classification model to detect fall risk for elderly adults with a history of falls (fallers) using micro-Doppler radar (MDR) gait measurements via simulation. The objective was to create daily monitoring systems that can identify elderly people with a high risk of falls. This study aimed to verify the effectiveness of our model by collecting actual MDR data from community-dwelling elderly people. First, MDR gait measurements were performed in a community setting, and the efficient gait parameters for the classification of fallers were extracted. Then, a support vector machine model that was trained and validated using the simulated MDR data was tested for the gait parameters extracted from the actual MDR data. A classification accuracy of 78.8% was achieved for the actual MDR data. The validity of the experimental results was confirmed based on a comparison with the results of our previous simulation study. Thus, the practicality of the faller classification model constructed using the simulated MDR data was verified for the actual MDR data.
An Observer-Based Harmonic Extraction Method with Front SOGI

With the further development of harmonic pollution in the power system, scientists have carried out research on harmonics. Among them, harmonic detection is the first step in harmonic research. In this paper, a harmonic detection method based on an observer is proposed. This method first uses the cascaded Second-Order Generalized Integration (SOGI) algorithm, which can filter the Direct Current (DC) component of the input signal to extract the fundamental frequency, and then uses a time-varying observer to extract the harmonics. This can be used to extract harmonics from a distorted online grid signal. The effectiveness of the proposed method was evaluated on the Speedgoat Rapid Control Prototype (RCP) platform. The results show that it can complete the convergence within 0.05 s, and the standard deviation after stability will not exceed 1%.
Review on developments of bulk functionally graded composite materials

Monolithic components are often insufficient when a combination of conflicting properties, or a variation in properties at different regions within a material is required. Functionally graded composite materials (FGCM) are a relatively new class of materials with a systematic variation of the composition, microstructure, and properties along one direction. The graded structure offers tailorable property combinations not achievable with monolithic composites and significant recent research has been carried out on their development. An effort has been made in this article to review the latest developments on bulk FGCMs since 2015. The different processing techniques used for their fabrication have been discussed, highlighting their advantages, limitations, and recent advancements pertaining to FGCM fabrication. Various physical, mechanical, and thermal properties of FGCMs have been treated separately, and wherever possible, summary plots combining data from various research articles have been developed. Finally, potential areas for directing future FGCM research have been identified. Abbreviations: AM: Additive manufacturing; ANOVA: Analysis of variance; ATZ: Alumina toughened zirconia; BCP: Biphasic calcium phosphate; BEI or BSE: Backscattered electron images; BG: Bioactive glass; CAD: Computer aided design; CDHAp: Calcium-deficient hydroxyapatite; CNT: Carbon nanotube; CoCGO: Cobalt and gadolinium doped ceria; CTE: Coefficient of thermal expansion; DED: Direct energy deposition; DIC: Digital image correlation; ELDS: Electro discharge sintering; EDX: Energy dispersive x-ray analyser; FDM: Fused deposition modelling; FGCC: Functionally graded cemented carbides; FGCM: Functionally graded composite materials; FGHM: Functionally graded hard metals; FSP: Friction stir processing; FSW: Friction stir welding; GDI: Graded density impactor; HA: Hydroxyapatite; HIP: Hot isostatic pressing; LCM: Lithography based ceramic manufacturing; LDMD: Laser direct metal deposition; LMD: Laser metal deposition; LSCF: Lanthanum cobalt ferrite; MLG: Multilayered graphene; MMC: Metal matrix composites; MWCNT: Multi-walled carbon nanotubes; PAS: Plasma activated sintering; PFC: Plasma facing components; PM: Powder metallurgy; RHA: Rice husk ash; RVE: Representative volume element; SEM: Scanning electron microscope; SHAp: Stoichiometric hydroxyapatite; SLA: Stereolithography; SLM: Selective laser melting; SLS: Selective laser sintering; SOFC: Solid oxide fuel cells; SPS: Spark plasma sintering; TEM: Transmission electron microscope; UHTC: Ultra-high temperature ceramics; WAAM: Wire arc additive manufacturing; YSZ: Yttria stabilized zirconia
An Electrospun Scaffold Loaded with an Enteromorpha Polysaccharide for Accelerated Wound Healing in Diabetic Mice

The design and development of innovative multifunctional wound dressing materials in engineered biomaterials is essential for promoting tissue repair. In this study, nanofibrous wound dressing materials loaded with anti-inflammatory ingredients were manufactured by a promising electrospinning strategy, and their capability for treating diabetic wounds was also investigated. A scaffold blend consisting of an Enteromorpha polysaccharide and polyvinyl alcohol (PVA) was fabricated. The in vitro and in vivo studies confirmed the efficacy of PVA/EPP1 fiber. We found that PVA/EPP1 fiber accelerated the repair of a full-thickness skin wound in diabetic mice. The results suggest that this scaffold could effectively shorten the wound healing time by inhibiting inflammatory activity, which makes it a promising candidate for the treatment of hard-to-heal wounds caused by diabetes.
Effects of altitude on soil properties in coastal fog ecosystems in Morro Moreno National Park, Antofagasta, Chile

Rare Pacific coast fog ecosystems are under threat from climate change and local factors. Although coastal fog is known to affect soil properties and microbial diversity, few studies on the Pacific coast have examined the specific microbiomes associated with these ecosystems. We evaluated the effects of coastal fog on the physicochemical, mineralogical, and microbiological properties of bare soils (vegetation‐free) and bulk soils (surrounding plant roots) from different altitudes in the Morro Moreno National Park (MMNP) in the Antofagasta region, Chile. We found that the temperature and relative humidity of the soil varied temporally (daily) and spatially (with altitude). We detected that soil organic matter and organic phosphorus content tended to increase with altitude, whereas the pH, electrical conductivity, and total phosphorus decreased. Our results showed that coastal fog could induce physical weathering below 300 masl and chemical weathering at the intermediate altitudes of ~400–600 masl. The biodiversity of bacteria and fungi increased considerably above 400 masl. Actinobacteria and Bacteroidetes dominated the bacteria in bare soil, and Bacteroidetes dominated the bulk soil communities at all altitudes. Ascomycota and Basidiomycota dominated the fungal community in both soil types. Moreover, the electrical conductivity and CaO content appear to be more closely associated with microbial communities from lower altitudes. In addition, the organic carbon content, humidity, and weathering index 2 (WI2) isolated some communities at 500 and 600 masl. The microbiological diversity reported in this work reflects the variable and different microbial niches comprising the MMNP environment. Linkages between soil property and microbial variations with altitude within this Northern Chilean coastal fog ecosystem were elucidated. This novel scientific knowledge contributes to global network strategies for fog ecosystem conservation, which aim to preserve the microbial niches and diversity in such soils.
Multi-Sensor Vibration Signal Based Three-Stage Fault Prediction for Rotating Mechanical Equipment

In order to reduce maintenance costs and avoid safety accidents, it is of great significance to carry out fault prediction to reasonably arrange maintenance plans for rotating mechanical equipment. At present, the relevant research mainly focuses on fault diagnosis and remaining useful life (RUL) predictions, which cannot provide information on the specific health condition and fault types of rotating mechanical equipment in advance. In this paper, a novel three-stage fault prediction method is presented to realize the identification of the degradation period and the type of failure simultaneously. Firstly, based on the vibration signals from multiple sensors, a convolutional neural network (CNN) and long short-term memory (LSTM) network are combined to extract the spatiotemporal features of the degradation period and fault type by means of the cross-entropy loss function. Then, to predict the degradation trend and the type of failure, the attention-bidirectional (Bi)-LSTM network is used as the regression model to predict the future trend of features. Furthermore, the predicted features are given to the support vector classification (SVC) model to identify the specific degradation period and fault type, which can eventually realize a comprehensive fault prediction. Finally, the NSF I/UCR Center for Intelligent Maintenance Systems (IMS) dataset is used to verify the feasibility and efficiency of the proposed fault prediction method.
Identity and community of practice in the incident of Samuel Orellana at the Neruda Foundation poetry workshop

ABSTRACT This study employed the narrative interview method to examine the incident of Samuel Orellana, a heteronym created in 2003 by two Literature students who invented Orellana to call into question the policies of the Pablo Neruda Foundation poetry workshop, the most prestigious workshop in Chile. More specifically, data were obtained from three sources, including the creators of Orellana (via narrative interviews), publications that mentioned the incident on Twitter in reference to the account name @Estereoscopio_ (profile of one of the creators), and poems written under the Orellana heteronym on Cyber Humanitatis (a Universidad de Chile website). After collecting data following these procedures, we conducted a qualitative case analysis using the ATLAS.ti software, where one code was used as a reference for analysis (i.e. identity): interviews, publications and poems were segmented, codes were assigned to each segment, including comments and annotations (memos). By using this method, we were able to build a relational database from which the programme generated semantic networks, which we then interpreted. This study shows an example of what happens when not all creative identities involved in a creative writing community are allowed to learn and exchange knowledge.
Three-phase inductive-coupled structures for contactless PHEV charging system

ABSTRACT In this article, a new-type three-phase inductive-coupled structure is proposed for the contactless plug-in hybrid electric vehicle (PHEV) charging system regarding with SAE J-1773. Four possible three-phase core structures are presented and subsequently investigated by the finite element analysis. To study the correlation between the core geometric parameter and the coupling coefficient, the magnetic equivalent circuit model of each structure is also established. In accordance with the simulation results, the low reluctance and the sharing of flux path in the core material are achieved by the proposed inductive-coupled structure with an arc-shape and three-phase symmetrical core material. It results in a compensation of the magnetic flux between each phase and a continuous flow of the output power in the inductive-coupled structure. Higher coupling coefficient between inductive-coupled structures is achieved. A comparison of coupling coefficient, mutual inductance, and self-inductance between theoretical and measured results is also performed to verify the proposed model. A 1 kW laboratory scale prototype of the contactless PHEV charging system with the proposed arc-shape three-phase inductive-coupled structure is implemented and tested. An overall system efficiency of 88% is measured when two series lithium iron phosphate battery packs of 25.6 V/8.4 Ah are charged.
Personalized Retail Promotions Through a Directed Acyclic Graph-Based Representation of Customer Preferences

A Framework to Run Personalized Promotions The availability of individual-level transaction data allows retailers to implement personalized operational decisions. Although such decisions have been around for several years now in online platforms, recent technological developments open new opportunities to extend similar practices to bricks-and-mortar settings (e.g., by using electronic price tags to show different prices to different customers or by using beacon-based technology to send promotion offers to targeted customers). In “Personalized Retail Promotions through a DAG-Based Representation of Customer Preferences,” Jagabathula, Mitrofanov, and Vulcano propose a back-to-back procedure for running customized promotions in retail operations contexts, from the construction of a nonparametric choice model where customer preferences are represented by directed acyclic graphs to the formulation of the promotion optimization problem. The empirical validation of their proposal on real supermarket data shows the promising performance of their approach over state-of-the-art benchmarks.