Miracle-dz/UniFAR-FTUs huggingface dataset:
A Computational Modeling and Simulation Workflow to Investigate the Impact of Patient-Specific and Device Factors on Hemodynamic Measurements from Non-Invasive Photoplethysmography

Cardiovascular disease is the leading cause of death globally. To provide continuous monitoring of blood pressure (BP), a parameter which has shown to improve health outcomes when monitored closely, many groups are trying to measure blood pressure via noninvasive photoplethysmography (PPG). However, the PPG waveform is subject to variation as a function of patient-specific and device factors and thus a platform to enable the evaluation of these factors on the PPG waveform and subsequent hemodynamic parameter prediction would enable device development. Here, we present a computational workflow that combines Monte Carlo modeling (MC), gaussian combination, and additive noise to create synthetic dataset of volar fingertip PPG waveforms representative of a diverse cohort. First, MC is used to determine PPG amplitude across age, skin tone, and device wavelength. Then, gaussian combination generates accurate PPG waveforms, and signal processing enables data filtration and feature extraction. We improve the limitations of current synthetic PPG frameworks by enabling inclusion of physiological and anatomical effects from body site, skin tone, and age. We then show how the datasets can be used to examine effects of device characteristics such as wavelength, analog to digital converter specifications, filtering method, and feature extraction. Lastly, we demonstrate the use of this framework to show the insensitivity of a support vector machine predictive algorithm compared to a neural network and bagged trees algorithm.
Grupos de Alimentos Asociados Atención Dental por Caries y por Gingivitis en Escuelas Públicas, México

groups associated with dental care for caries and for in ABSTRACT: Associate food groups with (cid:210)dental caries care(cid:211) and (cid:210)for gingivitis(cid:211) in adolescents between 12 and 24 years of age from public schools in Morelos, M(cid:142)xico. The dependent variables: (cid:210)dental care for caries(cid:211) and (cid:210)for gingivi-tis(cid:211) were defined by self-report. The food groups were obtained from a consumption questionnaire in the last year. The daily nutritional intake was estimated calculating each nutritional content of the foods using food tables and then they were added according to the group they belonged to (dairy, fruits, vegetables, legumes, cereals, meat and eggs, fish and seafood, carbonated drinks and bottled juices and sweets. Multilevel logistic models for repeated measurements were used for the analysis to identify associations (OR) between intake of each food group with (cid:210)dental caries care(cid:211) and (cid:210)for gingivitis(cid:211). In the adjusted analysis, (cid:210)dental caries care(cid:211) was associated with: fruits (OR 1.70), carbonated drinks and bottled juices (OR 1.38) and sweets (OR 1.44), while cereals remained at the marginal level (OR 1.34). No association with (cid:210)for gingivitis(cid:211) found. Foods high in refined carbohydrates are essential to go to dental services for dental caries.
Digital Technology in Psychiatry: Survey Study of Clinicians

Background Digital technology has the potential to transform psychiatry, but its adoption has been limited. The proliferation of telepsychiatry during the COVID-19 pandemic has increased the urgency of optimizing technology for clinical practice. Understanding clinician attitudes and preferences is crucial to effective implementation and patient benefit. Objective Our objective was to elicit clinician perspectives on emerging digital technology. Methods Clinicians in a large psychiatry department (inpatient and outpatient) were invited to complete a web-based survey about their attitudes toward digital technology in practice, focusing on implementation, clinical benefits, and expectations about patients’ attitudes. The survey consisted of 23 questions that could be answered on either a 3-point or 5-point Likert scale. We report the frequencies and percentages of responses. Results In total, 139 clinicians completed the survey—they represent a variety of years of experience, credentials, and diagnostic subspecialties (response rate 69.5%). Overall, 83.4% (n=116) of them stated that digital data could improve their practice, and 23.0% (n=32) of responders reported that they had viewed patients’ profiles on social media. Among anticipated benefits, clinicians rated symptom self-tracking (n=101, 72.7%) as well as clinical intervention support (n=90, 64.7%) as most promising. Among anticipated challenges, clinicians mostly expressed concerns over greater time demand (n=123, 88.5%) and whether digital data would be actionable (n=107, 77%). Furthermore, 95.0% (n=132) of clinicians expected their patients to share digital data. Conclusions Overall, clinicians reported a positive attitude toward the use of digital data to not only improve patient outcomes but also highlight significant barriers that implementation would need to overcome. Although clinicians’ self-reported attitudes about digital technology may not necessarily translate into behavior, our results suggest that technologies that reduce clinician burden and are easily interpretable have the greatest likelihood of uptake.
Control of Robot Manipulators Using Time-Delay Estimation and Fuzzy Logic Systems

A highly accurate model-free controller is proposed for trajectory tracking control of robot manipulators. The proposed controller incorporates time-delay estimation (TDE) to estimate and cancel continuous nonlinearities of robot dynamics, and exploits fuzzy logic systems to suppress the effect of the TDE error, which is due to discontinuous nonlinearities such as friction. To this end, integral sliding mode is defined using desired error dynamics, and a Mamdani-type fuzzy inference system is constructed. As a result, the proposed controller achieves the desired error dynamics well. Implementation of the proposed controller is easy because the design of the controller is intuitive and straightforward, and calculations of the complex robot dynamics are not required. The tracking performance of the proposed controller is verified experimentally using a 3-degree of freedom PUMAtype robot manipulator.
Impact of the Potential m6A Modification Sites at the 3′UTR of Alfalfa Mosaic Virus RNA3 in the Viral Infection

We have previously reported the presence of m6A in the AMV (Alfamovirus, Bromoviridae) genome. Interestingly, two of these putative m6A-sites are in hairpin (hp) structures in the 3’UTR of the viral RNA3. One site (2012AAACU2016) is in the loop of hpB, within the coat protein binding site 1 (CPB1), while the other (1900UGACC1904) is in the lower stem of hpE, a loop previously associated with AMV negative-strand RNA synthesis. In this work, we have performed in vivo experiments to assess the role of these two regions, containing the putative m6A-sites in the AMV cycle, by introducing compensatory point mutations to interfere with or abolish the m6A-tag of these sites. Our results suggest that the loop of hpB could be involved in viral replication/accumulation. Meanwhile, in the 1900UGACC1904 motif of the hpE, the maintenance of the adenosine residue and the lower stem hpE structure are necessary for in vivo plus-strand accumulation. These results extend our understanding of the requirements for hpE in the AMV infection cycle, indicating that both the residue identity and the base-pairing capacity in this structure are essential for viral accumulation.
Rosai-Dorfman Disease With Features of IgG4-Related Sclerosing Disease: A Case Report

Rosai-Dorfman disease (RDD) is a rare condition characterized by the proliferation of non-Langerhans cell histiocytes that are associated with phagocytosed lymphocytes (emperipolesis). Clinically, it is classified into nodal, extra-nodal, neoplasia-associated RDD, and immune-related. Here, we present a case of a 65-year-old female who presented with facial pain following a dental procedure with no focal neurologic deficit. The MRI of the head and neck showed a well-defined lobulated soft tissue lesion with homogenous enhancement over the left cheek. Excision of the lesion was done, and the histopathological study reported extra-nodal RDD with features of IgG4-related sclerosing disease. The patient had no recurrence over the two years from the date of diagnosis.
Tuning functions‐based robust adaptive tracking control of a class of nonlinear systems with time delays

In this paper, an adaptive backstepping tracking control scheme is proposed for a class of nonlinear state time‐varying delay systems, which are subject to parametric uncertainties and external disturbances. The bounds of the time delays and their derivatives are assumed to be unknown. Tuning functions method is exploited to construct the control law and adaptive laws. Unknown time‐varying delays are compensated by using appropriate Lyapunov–Krasovskii functional. It is shown that the proposed controller can guarantee the boundedness of all the closed‐loop signals. The tracking performance can be adjusted by choosing suitable design parameters. At the end, a simulation example is provided to illustrate the effectiveness of the design procedure. Copyright © 2011 John Wiley & Sons, Ltd.
Spin photovoltaic cell

Spintronics, which aims at exploiting the spin degree of freedom of carriers inside electronic devices, has a huge potential for quantum computation and dissipationless interconnects. Ideally, spin currents in spintronic devices should be powered by a spin voltage generator able to drive spins out of equilibrium and produce two spatially well-separated populations with opposite spin orientation. Such a generator should work at room temperature, be highly integrable with existing semiconductor technology, and work with neither ferromagnetic materials nor externally applied magnetic fields. We have matched these requirements by realizing the spintronic equivalent of a photovoltaic cell. While the latter spatially separates photoexcited electron and hole charges, our device exploits circularly polarized light to produce two spatially well-defined electron populations with opposite spin. This is achieved by modulating the phase and amplitude of the light wavefronts entering a semiconductor (germanium) with a patterned metal overlayer (platinum). This allows creating a light diffraction pattern with spatially-modulated chirality inside the semiconductor, which locally excites spin-polarized electrons thanks to electric dipole selection rules.
Model-Based Clustering Using Mixtures of Coalesced Generalized Hyperbolic Distributions

Mixtures of coalesced generalized hyperbolic distributions (GHDs) are developed by merging the existing finite mixtures of generalized hyperbolic distributions with a novel mixture of multiple scaled generalized hyperbolic distributions (MSGHDs). Our mixture of coalesced GHDs are a special case of a more general mixture of mixtures, specifically they share model parameters and have a common mode. Herein we detail the development of the mixtures of MSGHDs who arise via the implementation of a multi-dimensional weight function, and derive the density of our coalesced distribution. A parameter estimation scheme is developed using the ever-expanding class of MM algorithms and the Bayesian information criterion (BIC) is used for model selection. We use our mixture of coalesced GHDs for clustering and compare them to finite mixtures of skew-t distributions using simulated and real data sets.
Imposing Healthy Hip Motion Pattern and Range by Exoskeleton Control for Individualized Assistance

Powered exoskeletons are promising devices to improve the walking patterns of people with neurological impairments. Providing personalized external assistance though is challenging due to uncertainties and the time-varying nature of human-robot interaction. Recently, human-in-the-loop (HIL) optimization has been investigated for providing assistance to minimize energetic expenditure, usually quantified by metabolic cost. However, this full-body global effect evaluation may not directly reflect the local functions of the targeted joint(s). This makes it difficult to assess the direct effect when robotic assistance is provided. In addition, the HIL optimization method usually does not take into account local joint trajectories, a consideration that is important in imposing healthy joint movements and gait patterns for individuals with lower limb motor deficits. In this paper, we propose a model-free reinforcement learning (RL)-based control framework to achieve a normative range of motion and gait pattern of the hip joint during walking. Our RL-based control provides personalized assistance torque profile by heuristically manipulating three control parameters for hip flexion and extension, respectively, during walking. A least square policy iteration was devised to optimize a cost function associated with control efforts and hip joint trajectory errors by tuning the control parameters. To evaluate the performance of the design approach, a compression sleeve was used to constrain the hip joint of unimpaired human participants to simulate motor deficits. The proposed RL control successfully achieved the desired goal of enlarging the hip joint's range of motion in three participants walking on a treadmill.
Entanglement of thermal scalar fields in a compact space

Using the thermal Green's function approach we propose a general method to investigate entanglement of the vacuum state or thermal ground states in an arbitrary dimensional space-time. As an application we show quantum separability of the massive thermal scalar field vacuum in the 1+1 dimensional cylindrical space-time. Separability is demonstrated using the positive partial transpose criterion for effective two-mode Gaussian states of collective operators. In this case, for all mass and temperature values entanglement is absent between the collective operators.
Tomosynthesis Feasibility Study for Visualization of Interiors of
 Wood Columns Surrounded with Walls

The need for non-destructive testing and evaluation of Korean traditional wooden buildings is increasing because of their widespread deterioration. Among all types of deterioration, termite damage in wooden columns is the most difficult to detect with the naked eye because it starts inside the wood, and the initial deterioration is small. X-ray computed tomography (CT) is the best technology to investigate the inner state of wood that has less damage, but applying it to wooden columns between walls is challenging. Therefore, the feasibility of tomosynthesis, which is a method to reconstruct a coronal section of a subject with a few X-ray projections from a limited angle of rotation, was studied as an alternative to CT. Pine ( P. densiflora ) with three artificial holes was prepared as a specimen to evaluate the quality of reconstructed tomosynthesis images according to the different number of projections. The quality of the tomosynthesis images in the in-focus plane was evaluated using the contrast-to-noise ratios, while a vertical resolution between the images was assessed by determining the artificial spread function. The quality of the tomosynthesis image in the in-focus plane increased as the number of projections increased and then remained constant as the number of projections reached 21 or over. In the case of vertical resolution, there was no significant difference when 21 projections or more were used to reconstruct the images. A distinct difference between coronal section images was found when the distance was more than 10 mm from one plane to another plane.
The influence of floating exchange rate on economics development in Egypt until 2021

The decision to float the currency is one of the important decisions taken by the state on November 3, 2016; this date is considered an important date for the occurrence of many important events that affected people. Some see these effects as negative and others see them as positive, but the real effects appear on the short run and become clear on the long run, the positive effects appear only through the development of a long-run program. The state must adopt this program to increase exports of high value. Courageous policies are required for this decision to succeed and for the state to reach what it aspires to, so in in this paper, the authors attempts to shed light on the important effects of floating the Egyptian pound, by studying the effects of pricing the national currency before and after the flotation, to find out whether this flotation has negative or positive impact on the economic growth of the Egyptian state. Real Exchange Behavior and Evidence from Egypt, Jordan, Morocco, and Tunisia i , it examines the effect of the real exchange rate misalignment (RERMIS) on the economic growth Morocco, and Tunisia. The paper constructs three measures of exchange rate based on purchasing power parity; a black market exchange rate; and a structured model. The empirical investigation confirmed the negative effect RERMIS on growth, using all measures of RERMIS, as predicted by growth models. The results also highlighted the role of other relationship between rate and The paper uses a structural vector auto-regression (SVAR) model, drawing on Bernanke (1986) and Sims (1986), to empirically examine and analyze the pass-through of exchange rate fluctuations to domestic prices in Egypt.
Predator-Prey Models with Discrete Time Delay

Our goal in this thesis is to study the dynamics of the classical predator-prey model and the predator-prey model in the chemostat when a discrete delay is introduced to model the time between the capture of the prey and its conversion to biomass. In both models we use Holling type I response functions so that no oscillatory behavior is possible in the associated system when there is no delay. In both models, we prove that as the parameter modelling the delay is varied Hopf bifurcation can occur. However, we show that there seem to be differences in the possible sequences of bifurcations. Numerical simulations demonstrate that in the classical predator-prey model period doubling bifurcation can occur, possibly leading to chaos while that is not observed in the chemostat model for the parameters we use. For a delay differential equation, a prerequisite for Hopf bifurcation is the existence of a pair of pure imaginary eigenvalues for the characteristic equation associated with the linerization of the system. In this case, the characteristic equation is a transcendental equation with delay dependent coefficients. For our models, we develop two different methods to show how to find values of the bifurcation parameter at which pure imaginary eigenvalues occur. The method used for the classical predator-prey model was developed first. However, it was necessary to develop a
AMD的非对称优势 Fusion APU解析

在移动处理器领域，AMD一直在主动发力，尤其在2010年，AMD推出的第三代移动平台（代号Danube的主流平台和代号Nile的超轻薄平台）凭借CPU＋GPU＋芯片组全平台协同作战的威力，
Attention Classification and Lecture Video Recommendation Based on Captured EEG Signal in Flipped Learning Pedagogy

Abstract Flipped learning (FL) utilizes blended learning approaches, where students first learn the lesson from preloaded lecture videos (i.e., online lectures). They complete their activities such as assignments, doubt clearing, practical work, real-life problemsolving inside classroom. Learning is directly connected to brain activities, and it becomes crucial to analyze the brain signals to identify the attention level of the learner. In order to analyze students' activity during the lesson, we capture the brain signals of the students and propose a framework for the feature extraction of brain wave (Electroencephalogram (EEG)) signals using variational autoencoder (VAE) in this article. The classification techniques are exploited to identify the weak students in the flipped learning scenario based on their cognitive state; subsequently, cognitive-aware lecture video recommendation system is developed to recommend the non-attentive lecture video/videos to the weak students. This study can be useful for instructors to identify learners who require special care to enhance their learning ability.
Trends and health economic aspects of service delivery of glaucoma

Glaucoma describes a group of optic neuropathies characterised by progressive irreversible loss of visual function. Within this thesis, a health economic model was constructed to map service provision from diagnosis considering two competing strategies: the current practice of annual visual field (VF) monitoring against the proposed guidelines of performing 6 VFs in the first two years. The constructed model found the proposed practice to be cost effective at a willingness to pay ceiling ratio of £30,000 per quality adjusted life year (QALY), identifying an incremental cost effectiveness ratio (ICER) of £21,679. The findings of the model however were potentially sensitive to the modelled infrastructure improvement costs required to undertake the proposed guidelines and a costing study to more accurately ascertain these costs was recommended. Following this study, statistical analysis of 473,252 VFs was undertaken to investigate trends in initial identification and progression rates whilst also narrowing their parameters within the health economic model. Consequently, the average level of glaucomatous vision loss at diagnosis was found to be improving by 0.11 dB per year on average whilst proportions of patients with ‘advanced’ loss at diagnosis fell significantly from 30% to 21%. Average progression rates were found to have fallen from -0.11 dB per year to -0.06 dB per year whilst average rates of loss in older eyes (>70 years) were found to progress faster than in younger eyes (<60 years). Furthermore, testing frequency was found not to vary by visual impairment risk factors. The constructed health economic model was subsequently updated to incorporate the more narrowly defined parameter distributions whilst also being re-specified to incorporate societal costs of visual impairment to count the true costs of the disease. This resulted in an improved ICER of £11,382. In conclusion, it is likely that implementing the proposed guidelines of 6 VFs in the first two years is more cost-effective than annual monitoring. This argument is further reinforced once societal costs are accounted for however a scoping study to examine the required costs of improving the glaucoma monitoring infrastructure is required.
TEC Forecasting using Optimized Variational Mode Decomposition and Elman Neural Networks

Forecasting the ionosphere layer’s total electronic content (TEC) is crucial for its impact on satellite signals and global positioning systems (GPS) and the ability to predict earthquakes. The existing statistical-based forecasting models such as ARMA, ARIMA, and HW suffered from the TEC nonstationarity nature, which requires algorithmic handling of the forecasting and the mathematical part. This study proposes a hybrid method that incorporates several components and is designated as Optimized Variational Mode Decomposition with Recursive Neural Network Forecasting (OVMD-RNN) to forecast TEC. Before using the Elman Network to train each component, Variational Mode Decomposition (VMD) was used to decompose the signal into its essential stationary components. In addition, the proposed method includes an optimization algorithm for determining the best VMD decomposer parameters. The GPS Ionospheric Scintillation and TEC Monitor (GISTM) at Universiti Kebangsaan Malaysia station have been used to evaluate the method based on collected datasets for three years, 2011, 2012, and 2013. The experiment findings show that the model has successfully tracked all the up and down patterns in the time series. The results also reveal that VMD-based training might not always provide good results due to the residual signal. Finally, the evaluation focused on generating loss value and comparing it to the ARIMA benchmark. It showed that OVMDRNN had accomplished a maximum improvement percentage of ARIMA with a value of (99%). Keywords—Elman neural networks; forecast; hybrid model; optimized Variational Mode Decomposition; total electronic content