Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Overmodulation Scheme for Improved Current Regulation in PMSM Drives

The overmodulation scheme plays an essential role in the dynamic performance of the current regulation under voltage limitation. This article analyses how the nonlinearity of the voltage hexagon affects dynamic overmodulation. Most dynamic overmodulation schemes had considered the voltage hexagon as the limit of the output voltage to maximize the voltage utilization. However, these schemes do not show uniform dynamic performance according to the rotor position on the voltage hexagon. To overcome this limitation, this article proposes an overmodulation scheme that is robust against the rotor position variation. The computer simulation and experimental results verify that the proposed method has the consistent performance regardless of the rotor position with less d-axis current overshoot keeping the fast dynamics.
Design of 3D-Printed Air-Like Structural Supports for Meanderline Polarizers at L-Band

A design approach and demonstration of a 3D-printed lattice structure as a low permittivity foam spacer replacement in meanderline polarizers (MLP) are discussed. Reduced complexity model that relies on the extracted parameters from the lattice structure calculated using the Nicolson-Ross-Weir (NRW) method as frequency-dependent material characteristics is developed and showed to accurately represents the physics in the infinite array environment. Effective parameters of fabricated 3D-printed air-like supports are extracted using NRW method and compared to simulation through multiple iterations to compensate for systematic errors introduced by the utilized 3D printer. Simulated results integrating such a 3D-printed structure with a meanderline polarizer and planar inverted-F antenna (PIFA) unit-cell for a tightly-coupled array (TCA) at GPS L1, L2, and L5 bands are presented as well.
Chamber-Decay Time in a mm-Wave Reverberation Chamber

In this work, we present results of a novel mm-wave reverberation chamber, where we discuss the role of the chamber quality factor and chamber decay time, or time constant, for mm-wave applications. For the first time, we analyze the uncertainty due to antenna positioning for these metrics in such a chamber, where we show that the quality factor computed in the frequency domain has a higher uncertainty due to antenna positioning than its time domain counterpart. We describe that the the chamber decay time and quality factor are lower for mm-wave chambers as compared to lower-frequency (sub-6 GHz) chambers, but that they can still function as ideal candidates for metrics revolving around losses.
A Hybrid SIE-PDE Formulation Without Additional Boundary Conditions for Electromagnetic Analysis

A hybrid surface integral equation partial differential equation (SIE-PDE) formulation without boundary condition requirement is proposed to solve the challenging electromagnetic problems. The computational domain is first decomposed into the overlapping SIE and PDE domains. An equivalent model with only the surface equivalent electric current density on the bound-ary is constructed in the SIE domain. Then, through embedding the surface equivalent current density into the inhomogeneous Helmholtz equation, a hybrid SIE-PDE formulation is derived. This new hybrid formulation is mathematically equivalent to the original physical model, which does not require boundary conditions to couple the SIE and PDE formulations. Numerical results demonstrate its accuracy and efficiency.
A Decomposed Deep Training Solution for Fog Computing Platforms

Legacy machine learning solutions collect user data from data sources and place computation tasks in the Cloud. Such solutions eat communication capacity and compromise privacy with possible sensitive user data leakage. These concerns are resolved by Fog computing that integrates computation and communication in Fog nodes at the edge of the network enabling and pushing intelligence closer to the machines and devices. However, pushing computational tasks to the edge of the network requires high-end Fog nodes with powerful computation resources. This paper proposes a method whose computation tasks are decomposed and distributed among all the available resources. The more resource-demanding computation is placed in the Cloud, and the remainder is mapped to the Fog nodes using migration mechanisms in Fog computing platforms. Our presented method makes use of all available resources in a Fog computing platform while protecting user privacy. Furthermore, the proposed method optimizes the network traffic such that the high-critical applications running on the Fog nodes are not negatively impacted. We have implemented the (deep) neural networks - using our proposed method and evaluated the method on MNIST and CIFAR100 as the data source for the test cases. The results show advantages of our proposed method comparing to other methods, i.e., Cloud computing and Federated Learning, with better data protection and resource utilization.
SQuaFL: Sketch-Quantization Inspired Communication Efficient Federated Learning

Federated Learning (FL) is a fast-growing distributed learning paradigm with widespread applications especially over mobile devices, since it trains high-quality deep learning models while keeping the data private. This aspect is most suitable in multi-access edge computing settings where FL leverages distributed data from numerous mobile edge devices for training. However, FL involves frequent global synchronization of periodic updates over links often with transmission rate limits, inflicting communication burdens. Moreover, the intensive on-device computation of local updates results in computation and memory overhead on resource constricted mobile devices. To address these challenges, in this paper, we introduce SQuaFL, a sketched quantization based novel FL method which aims at communication efficiency while preserving privacy. In particular, we compress the accumulation of local gradients using quantization and Count Sketches without adding explicit noise, sacrificing the learning performance, or introducing a computation overhead. We provide theoretical guarantees of convergence of our proposed scheme and perform extensive simulations to demonstrate its efficacy over baseline methods.
Processors' Experience in the Use of Flash Dryer for Cassava-derived Products in Nigeria

This study was designed and carried out to ascertain the situation and perceptions of end users of cassava flash drying equipment in Nigeria with the aim of giving suggestions to policies and approaches for improved technology. Forty-one processing firms were selected and interviewed. Descriptive analyses were used and a logistic regression model was estimated. The results revealed that 49% of the firms stopped using their flash dryers due to the low demand for high-quality cassava flour (HQCF) resulting from the high cost of processing occasioned by an inefficient heat-generating component. The estimated model provides evidence that cost effectiveness (p < 0.05) and energy cost (p < 0.10) are the two major determinants of the continuous usage of flash dryers in the study area. Forty-one percent of the firms indicated willingness to pay for any technical adjustment of their flash dryers, supposing such adjustment would improve on drying and the energy efficiency of the equipment up to 40%. The study recommends that machine fabricators in Nigeria and other African countries should be trained on the production of energy- and cost-efficient small-scale flash dryers. Again, the design and commercialization of flash dryers that can be mounted on mobile trucks for farm-gate processing should be encouraged to facilitate farm-gate processing, thereby reducing postharvest losses resulting from transporting perishable and bulky roots over a long distance.
Analysis of Subset Chimerism for MRD-Detection and Pre-Emptive Treatment in AML

Allogeneic hematopoietic stem cell transplantation (alloHCT) represents the only potentially curative treatment in high-risk AML patients, but up to 40% of patients suffer from relapse after alloHCT. Treatment of overt relapse poses a major therapeutic challenge and long-term disease control is achieved only in a minority of patients. In order to avoid post-allograft relapse, maintenance as well as pre-emptive therapy strategies based on MRD-detection have been used. A prerequisite for the implementation of pre-emptive therapy is the accurate identification of patients at risk for imminent relapse. Detection of measurable residual disease (MRD) represents an effective tool for early relapse prediction in the post-transplant setting. However, using established MRD methods such as multicolor flow cytometry or quantitative PCR, sensitive MRD monitoring is only applicable in about half of the patients with AML and advanced MDS undergoing alloHCT. Donor chimerism analysis, in particular when performed on enriched leukemic stem and progenitor cells, e.g. CD34+ cells, is a sensitive method and has emerged as an alternative option in the post alloHCT setting. In this review, we will focus on the current strategies for lineage specific chimerism analysis, results of pre-emptive treatment using this technology as well as future developments in this field.
Decreased Functional Connectivities of Low-Degree Level Rich Club Organization and Caudate in Post-stroke Cognitive Impairment Based on Resting-State fMRI and Radiomics Features

Background Stroke is an important cause of cognitive impairment. Rich club organization, a highly interconnected network brain core region, is closely related to cognition. We hypothesized that the disturbance of rich club organization exists in patients with post-stroke cognitive impairment (PSCI). Methods We collected data on resting-state functional magnetic resonance imaging (rs-fMRI) with 21 healthy controls (HC), 16 hemorrhagic stroke (hPSCI), and 21 infarct stroke (iPSCI). 3D shape features and first-order statistics of stroke lesions were extracted using 3D slicer software. Additionally, we assessed cognitive function using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). Results Normalized rich club coefficients were higher in hPSCI and iPSCI than HC at low-degree k-levels (k = 1–8 in iPSCI, k = 2–8 in hPSCI). Feeder and local connections were significantly decreased in PSCI patients versus HC, mainly distributed in salience network (SN), default-mode network (DMN), cerebellum network (CN), and orbitofrontal cortex (ORB), especially involving the right and left caudate with changed nodal efficiency. The feeder and local connections of significantly between-group difference were positively related to MMSE and MoCA scores, primarily distributed in the sensorimotor network (SMN) and visual network (VN) in hPSCI, SN, and DMN in iPSCI. Additionally, decreased local connections and low-degree ϕnorm(k) were correlated to 3D shape features and first-order statistics of stroke lesions. Conclusion This study reveals the disrupted low-degree level rich club organization and relatively preserved functional core network in PSCI patients. Decreased feeder and local connections in cognition-related networks (DMN, SN, CN, and ORB), particularly involving the caudate nucleus, may offer insight into pathological mechanism of PSCI patients. The shape and signal features of stroke lesions may provide an essential clue for the damage of functional connectivity and the whole brain networks.
Speech Perception in Older Adults: An Interplay of Hearing, Cognition, and Learning?

Older adults with age-related hearing loss exhibit substantial individual differences in speech perception in adverse listening conditions. We propose that the ability to rapidly adapt to changes in the auditory environment (i.e., perceptual learning) is among the processes contributing to these individual differences, in addition to the cognitive and sensory processes that were explored in the past. Seventy older adults with age-related hearing loss participated in this study. We assessed the relative contribution of hearing acuity, cognitive factors (working memory, vocabulary, and selective attention), rapid perceptual learning of time-compressed speech, and hearing aid use to the perception of speech presented at a natural fast rate (fast speech), speech embedded in babble noise (speech in noise), and competing speech (dichotic listening). Speech perception was modeled as a function of the other variables. For fast speech, age [odds ratio (OR) = 0.79], hearing acuity (OR = 0.62), pre-learning (baseline) perception of time-compressed speech (OR = 1.47), and rapid perceptual learning (OR = 1.36) were all significant predictors. For speech in noise, only hearing and pre-learning perception of time-compressed speech were significant predictors (OR = 0.51 and OR = 1.53, respectively). Consistent with previous findings, the severity of hearing loss and auditory processing (as captured by pre-learning perception of time-compressed speech) was strong contributors to individual differences in fast speech and speech in noise perception. Furthermore, older adults with good rapid perceptual learning can use this capacity to partially offset the effects of age and hearing loss on the perception of speech presented at fast conversational rates. Our results highlight the potential contribution of dynamic processes to speech perception.
Affecting Effects on Affect: The Impact of Protocol Permutations on Affective Responses to Sprint Interval Exercise; A Systematic Review and Meta-Analysis of Pooled Individual Participant Data

Responses to sprint interval exercise (SIE) are hypothesized to be perceived as unpleasant, but SIE protocols are diverse, and moderating effects of various SIE protocol parameters on affective responses are unknown. We performed a systematic search to identify studies (up to 01/05/2021) measuring affective valence using the Feeling Scale during acute SIE in healthy adults. Thirteen studies involving 18 unique trials and 316 unique participant (142 women and 174 men) affective responses to SIE were eligible for inclusion. We received individual participant data for all participants from all studies. All available end-of-sprint affect scores from each trial were combined in a linear mixed model with sprint duration, mode, intensity, recovery duration, familiarization and baseline affect included as covariates. Affective valence decreased significantly and proportionally with each additional sprint repetition, but this effect was modified by sprint duration: affect decreased more during 30 s (0.84 units/sprint; 95% CI: 0.74–0.93) and 15–20 s sprints (1.02 units/sprint; 95% CI: 0.93–1.10) compared with 5–6 s sprints (0.20 units/sprint; 95% CI: 0.18–0.22) (both p < 0.0001). Although the difference between 15–20 s and 30 s sprints was also significant (p = 0.02), the effect size was trivial (d = −0.12). We observed significant but trivial effects of mode, sprint intensity and pre-trial familiarization, whilst there was no significant effect of recovery duration. We conclude that affective valence declines during SIE, but the magnitude of the decrease for an overall SIE session strongly depends on the number and duration of sprints. This information can be applied by researchers to design SIE protocols that are less likely to be perceived as unpleasant in studies of real-world effectiveness. Systematic Review Registration Open Science Framework, https://osf.io/sbyn3.
The Role of Tumor Necrosis Factor Associated Factors (TRAFs) in Vascular Inflammation and Atherosclerosis

TNF receptor associated factors (TRAFs) represent a family of cytoplasmic signaling adaptor proteins that regulate, bundle, and transduce inflammatory signals downstream of TNF- (TNF-Rs), interleukin (IL)-1-, Toll-like- (TLRs), and IL-17 receptors. TRAFs play a pivotal role in regulating cell survival and immune cell function and are fundamental regulators of acute and chronic inflammation. Lately, the inhibition of inflammation by anti-cytokine therapy has emerged as novel treatment strategy in patients with atherosclerosis. Likewise, growing evidence from preclinical experiments proposes TRAFs as potent modulators of inflammation in atherosclerosis and vascular inflammation. Yet, TRAFs show a highly complex interplay between different TRAF-family members with partially opposing and overlapping functions that are determined by the level of cellular expression, concomitant signaling events, and the context of the disease. Therefore, inhibition of specific TRAFs may be beneficial in one condition and harmful in others. Here, we carefully discuss the cellular expression and signaling events of TRAFs and evaluate their role in vascular inflammation and atherosclerosis. We also highlight metabolic effects of TRAFs and discuss the development of TRAF-based therapeutics in the future.
Turning in Circles: Understanding Manual Wheelchair Use Towards Developing User-Friendly Steering Systems

For people with physical disabilities, manual wheelchairs are essential enablers of mobility, participation in society, and a healthy lifestyle. Their most general design offers great flexibility and direct feedback, but has been described to be inefficient and demands good coordination of the upper extremities while critically influencing users’ actions. Multiple research groups have used Inertial Measurement Units (IMUs) to quantify physical activities in wheelchairs arguing that knowledge over behavioural patterns in manual wheelchair usage can guide technological development and improved designs. The present study investigates turning behaviour among fulltime wheelchair users, laying the foundation of the development of novel steering systems that allow directing kinetic energy by means other than braking. Three wearable sensors were installed on the wheelchairs of 14 individuals for tracking movement over an entire week. During detected “moving windows”, phases where the velocities of the two rear wheels differed by more than 0.05 m/s were considered as turns. Kinematic characteristics for both turns-on-the-spot as well as for moving turns were then derived from the previously reconstructed wheeled path. For the grand total of 334 km of recorded wheelchair movement, a turn was detected every 3.6 m, which equates to about 900 turns per day on average and shows that changing and adjusting direction is fundamental in wheelchair practice. For moving turns, a median turning radius of 1.09 m and a median turning angle of 39° were found. With a median of 89°, typical turning angles were considerably larger for turns-on-the-spot, which accounted for roughly a quarter of the recognised turns and often started from a standstill. These results suggest that a frequent pattern in daily wheelchair usage is to initiate movement with an orienting turn-on-the-spot, and cover distances with short, straightforward sections while adjusting direction in small and tight moving turns. As large bends often require simultaneous pushing and breaking, this is, perhaps, the result of users intuitively optimising energy efficiency, but more research is needed to understand how the design of the assistive devices implicitly directs users’ movement.
The Spino-Parabrachial Pathway for Itch

Itch-induced scratching is an evolutionarily conserved behavioral response that protects organisms from potential parasites/irritants in their immediate vicinity. How the exposure to a pruritogen is translated to the perception of itch and how that perception drives scratching directed towards the site of exposure remains poorly understood. In this review, we focus on the recent findings that shed light on the neural pathways in the brain that underlie itch-induced scratching. We compare the molecularly defined itch pathways with the known pain circuits as they have anatomical and functional overlap. We review the roles played by the neurons in the spinoparabrachial pathway—comprising of the neurons in the spinal cord and the parabrachial nucleus (PBN), which acts as a hub for transmitting itch information across the brain. Lastly, we deliberate on scratching as a behavioral measure of the intensity of itch and its implication in unraveling the underlying supraspinal mechanisms. In summary, we provide a resource on the recent advances and discuss a path forward on our understanding of the neural circuits for itch.
Dietary Patterns Are Associated With Multi-Dimensional Cognitive Functions Among Adults Aged 55 and Older in China

Background The intake of certain food and nutrients may play a crucial role in cognitive health. However, research on the relationship between dietary patterns and cognitive function is limited. This study aims to investigate the associations between dietary patterns and multi-dimensional cognitive functions, such as global cognitive status and related domain profiles, mild cognitive impairment (MCI), and four major subtypes of Chinese adults. Methods Using the baseline data from the Community-based Cohort Study on Nervous System Diseases (2018–2019), we selected 4,309 Chinese adults aged 55 years and older as subjects with complete diet, cognition, and other related data. We collected food data for the past 12 months with a valid semi-quantitative food frequency questionnaire. Diving 49 food items into 13 subgroups, we used factor analysis to derive the main dietary patterns. We evaluated cognitive functions based on the scores of the Montreal Cognitive Assessment (MoCA) and used quantile regression and multivariable logistic regression to examine the relationship between dietary patterns and cognitive-related outcomes. Results We identified four dietary patterns, explaining 50.11% of the total variance: “meat-preferred” pattern, “plant-preferred” pattern, “eggs- and dairy-preferred” pattern, and “grain-preferred” pattern. After adjusting for all potential confounders, the “meat-preferred” pattern and the “plant-preferred” pattern were associated with higher scores of global cognition and several cognitive domains (p <0.05), while the “grain-preferred” pattern was associated with lower scores of global cognition (β = −0.36, p <0.05), execution (β = −0.19, p <0.05), visuospatial (β = −0.09, p <0.05), and language (β = −0.05, p <0.05). Adults adhering to the “meat-preferred” pattern and the “plant-preferred” pattern had decreased odds of MCI and some MCI subtypes (p-trend <0.05); in contrast, those in the top quartiles of the “grain-preferred” pattern had increased odds of MCI [adjusted odds ratio (AOR) = 1.34, 95% CI: 1.11–1.63, p-trend = 0.003]. Conclusions Adhering to the “plant-preferred” pattern and the “meat-preferred” pattern may help improve the multi-dimensional cognitive functions; on the contrary, adhering to the “grain-preferred” pattern may worse cognitive health. More prospective studies in this field are needed to strengthen the evidence.