Miracle-dz/UniFAR-FTUs huggingface dataset:
Heart age gap estimated by explainable advanced electrocardiography is associated with cardiovascular risk factors and survival

Abstract Aims Deep neural network artificial intelligence (DNN-AI)–based Heart Age estimations have been presented and used to show that the difference between an electrocardiogram (ECG)-estimated Heart Age and chronological age is associated with prognosis. An accurate ECG Heart Age, without DNNs, has been developed using explainable advanced ECG (A-ECG) methods. We aimed to evaluate the prognostic value of the explainable A-ECG Heart Age and compare its performance to a DNN-AI Heart Age. Methods and results Both A-ECG and DNN-AI Heart Age were applied to patients who had undergone clinical cardiovascular magnetic resonance imaging. The association between A-ECG or DNN-AI Heart Age Gap and cardiovascular risk factors was evaluated using logistic regression. The association between Heart Age Gaps and death or heart failure (HF) hospitalization was evaluated using Cox regression adjusted for clinical covariates/comorbidities. Among patients [n = 731, 103 (14.1%) deaths, 52 (7.1%) HF hospitalizations, median (interquartile range) follow-up 5.7 (4.7–6.7) years], A-ECG Heart Age Gap was associated with risk factors and outcomes [unadjusted hazard ratio (HR) (95% confidence interval) (5 year increments): 1.23 (1.13–1.34) and adjusted HR 1.11 (1.01–1.22)]. DNN-AI Heart Age Gap was associated with risk factors and outcomes after adjustments [HR (5 year increments): 1.11 (1.01–1.21)], but not in unadjusted analyses [HR 1.00 (0.93–1.08)], making it less easily applicable in clinical practice. Conclusion A-ECG Heart Age Gap is associated with cardiovascular risk factors and HF hospitalization or death. Explainable A-ECG Heart Age Gap has the potential for improving clinical adoption and prognostic performance compared with existing DNN-AI-type methods.
Detection of Phase Transition via Convolutional Neural Networks

A convolutional neural network (CNN) is designed to study correlation between the temperature and the spin configuration of the two-dimensional Ising model. Our CNN is able to find the characteristic feature of the phase transition without prior knowledge. Also a novel order parameter on the basis of the CNN is introduced to identify the location of the critical temperature; the result is found to be consistent with the exact value.
Molecular Characteristics, Sources, and Health Risk Assessment of Gaseous Carbonyl Compounds in Residential Indoor and Outdoor Environments in a Megacity of Northwest China

Carbonyl compounds (CCs) in indoor air pose a significant threat to residents’ health and have garnered considerable attention in recent years. However, most studies have focused on low-molecular-weight carbonyl compounds (LMW-CCs) and have underestimated the impact of high-molecular-weight ones (HMW-CCs), causing a failure to comprehensively understand their effects on health. In this study, we analyzed twenty carbonyls in the indoor and outdoor air at typical residential communities in a megacity in Northwest China by using high-performance liquid chromatography (HPLC) coupled with a photodiode array detector (DAD). The total concentration of indoor carbonyls was 1.4-3.4 times that of outdoor carbonyls. In addition, the concentration of indoor carbonyls was much higher during the heating season than that during the nonheating season. Conversely, the concentration of outdoor carbonyls was higher during the nonheating season than that during the heating season. The principal component analysis (PCA) revealed that indoor carbonyl pollution was primarily influenced by building materials, cooking fume, and wooden furniture. Formaldehyde exposure in indoor environments posed a greater health risk to children than acetaldehyde exposure. HMW-CCs were the primary contributors to indoor odor pollution, which was considered a significant cause of sick building syndrome (SBS). Our findings underscore the crucial role of HMW-CCs in indoor environments in exerting adverse impacts on health.
Dosimetric Investigation of Six Ru-106 Eye Plaques by EBT3 Radiochromic Films and Monte Carlo Simulation

Background: Ophthalmic brachytherapy using radioactive plaques is an effective technique for the treatment of uveal melanoma. Ru-106 eye plaques are considered as interesting issue due to their steep gradient dose. The pre-planning evaluation of dosimetric parameters is essential for the treatment planning system. Objective: The current study aims at providing dose distributions of six Ru-106 eye plaques (CCA, CCB, CGD, CIB, COB and COD) using radiochromic EBT3 film, Geant4 Monte Carlo toolkit and the treatment planning software (Plaque Simulator). Material and Methods: In this experimental study, an in-house phantom was employed for depth dose measurements with EBT3 films. Also, Geant4.10. 5 scoring mesh was implemented to obtain the 2D dose distribution of the plaques. The results were compared with Plaque Simulator software and the manufacturer’s (BEBIG) data. The gamma index criterion (3%/3 mm) was used to evaluate dose distributions obtained by the film measurements and Geant4 simulation. Results: A good agreement was achieved between simulation and experimental results. Gamma index passing rate was 94.2%, 89.3%, 88.2%, 82.2%, 92.2% and 90.1% for CCA, CCB, CGD, CIB, COB and COD plaques, respectively. Absolute dose rate (mGy/min) obtained by EBT3 film at the depth of 2 mm was 79.4 mGy/min, 81.0 mGy/min, 78.6 mGy/min, 62.2 mGy/min, 75.2 mGy/min and 81.2 mGy/min for CCA, CCB, CGD, CIB, COB and COD plaques, respectively. Conclusion: The measured dose distributions and lateral dose profiles may be utilized in the treatment planning system to cover clinical volumes such as the clinical target volume and the gross tumor volume.
Recursive estimation procedure of Sobol' indices based on replicated designs

In the field of sensitivity analysis, Sobol' indices are widely used to assess the importance of inputs of a model to its output. Among the methods that estimate these indices, the replication procedure is noteworthy for its efficient cost. A practical problem is how many model evaluations must be performed to guarantee a sufficient precision on the Sobol' estimates. This paper tackles this issue by rendering the replication procedure recursive. We consider the ability of adding new points to progressively increase the accuracy of the estimates. The key feature of this approach is the construction of nested space-filling designs. For the estimation of first-order indices, we exploit a nested Latin hypercube already introduced in the literature. For the estimation of closed second-order indices, two constructions of a nested orthogonal array are proposed. Regularity and uniformity properties of the nested designs are studied.
Robust detection algorithm with triple constraints for cooperative target based on spectral residual

: The accurate detection of cooperative targets plays a key and foundational role in unmanned aerial vehicle (UAV) landing autonomously. The standard method based on ﬁxed threshold is too susceptible to both illumination variations and interference. To overcome issues above, a robust detection algorithm with triple constraints for cooperative targets based on spectral residual (TCSR) is proposed. Firstly, by designing an asymmetric cooperative target, which comprises red background, green H and triangle target, the captured original image is converted into a Lab color space, whose saliency map is yielded by constructing the spectral residual. Then, the triple constraints are developed according to the prior knowledge of the cooperative target. Finally, the salient region in saliency map is considered as the cooperative target, and it meets the triple constraints. Experimental results in complex environments show that the proposed TCSR outperforms the standard methods in higher detection accuracy and lower false alarm rate.
Prevalence of Geographic Atrophy in Advanced Age-Related Macular Degeneration (AMD) in Daily Practice

Purpose: To investigate the prevalence of geographic atrophy (GA) in advanced age-related macular degeneration (AMD) and the proportion of eyes that would meet the indication criteria for treatment with the first intravitreal anti-C3 agent (pegcetacoplan). Methods: This retrospective cross-sectional study included all AMD patients who visited the Macular-Retina-Centre Oberkassel in 2021. Eyes were classified according to AMD stages. Eyes with GA were divided into two groups regarding foveal involvement. Baseline factors were compared between eyes with foveal GA (FGA) and eyes with non-foveal GA (NFGA) to identify predictive factors for foveal involvement. Results: A total of 2033 eyes from 1027 patients were included. AMD stage was early in 296 (14.5%) cases, intermediate in 368 (18.1%) cases, and advanced in 1249 (61.4%) cases. A total of 1204 (60%) eyes had GA [932 (77%) FGA and 272 (23%) NFGA], while 125 eyes (27.4% from eyes with advanced dry AMD) met the indication criteria for treatment with intravitreal pegcetacoplan. The proportion of eyes with neovascular AMD was significantly higher in the FGA group compared to the NFGA group [598 (64.2%) vs. 152 (55.8%), p = 0.01]. Conclusions: At least a quarter of eyes with advanced AMD would be suitable for the upcoming intravitreal pegcetacoplan therapy. Foveal involvement of GA in advanced AMD seems to be more likely in neovascular AMD than in dry AMD.
Development of composite panels based on porous glass aerogels for acoustic applications

In this work, we present the results of research on manufacturing composite materials based on porous glass beads for acoustic treatment. A new material with fire resistance, heat resistance, impermeability, longevity, and insulation is made from foam glass beads (made from waste glass) and cement mortar. Firstly, the composite concrete panels with a high level of porosity 66%–82% and spherical pores in millimeter scale (i.e., ranging from 0.15mm to 10mm) are fabricated. Then, acoustical measurements are performed to characterize the sound absorbing coefficient and the transport properties of the selected composite panels. The measurement data are compared to the semi-phenomenological Johnson-Champoux-Allard-Lafarge model to show a good agreement in terms of predicting the sound absorption property. From the obtained results it can be stated that the open porosity and the thickness of the fabricated materials affect strongly their sound absorption performance. Within a panel thickness of 33.3mm, the aerogel-based concrete panel can provide a good sound absorption coefficient which could be more than 0.60 in the frequency range of [820 1290]Hz and reach the value of 0.84 at a low resonance frequency of ~1032Hz. The methodology, therefore, enables the identification and validation of acoustical models for specific porous glass aerogel-based materials and paves the way for an efficient exploration of the parameter space for acoustical materials design.
Assessment of Dispensing Malpractice in Community Drug Retail Outlets in South Gondar Zone, Northwest Ethiopia: A Simulated Patient Experience

Background Pharmacy professionals in community drug retail outlets, as the most accessible personnel for the community, are engaged in consultation and responding to health problems in addition to filling prescriptions. In doing so, different dispensing malpractices are observed and much is not known on the issue in Ethiopia. Objective The study aimed at assessing dispensing malpractice at pharmacies, drug stores and drug vendors in South Gondar zone. Methodology A cross-sectional study design with a descriptive approach was applied from April 1 to June 30. The data was collected using the simulated patient method. Seven prescription-only medicines and a diarrheal case were requested during visit. All drug retail outlets in South Gondar zone that were in service during data collection were visited. Results Almost all prescription-only medications were dispensed without prescription at all community drug retail outlets. Of all the dispensaries, 19 (82.6%) provided a partial dosage regimen of amoxicillin. Presence of fever and pregnancy status were asked about by dispensers in only 8% and 20% of visits for diarrhea, respectively. Medication history was also rarely requested. Medication was dispensed in 80% of visits for diarrhea, all of which included antimicrobials. Oral rehydration salt was considered in only two (10%) dispensaries. Conclusion Dispensing medications without a prescription is common in community drug retail outlets in South Gondar zone in Amhara Regional State. Our findings also showed that detailed assessments of patients’ signs and symptoms are not performed properly by the dispensers to understand the diarrheal case. Training of pharmacy professionals and strict regulatory control are needed.
Metal Nanoparticles in Alzheimer’s Disease

Nanotechnology has emerged in different fields of biomedical application, including lifestyle diseases like diabetes, hypertension, and chronic kidney disease, neurodegenerative diseases like Alzheimer’s disease (AD), Parkinson’s disease, and different types of cancers. Metal nanoparticles are one of the most used drug delivery systems due to the benefits of their enhanced physicochemical properties as compared to bulk metals. Neurodegenerative diseases are the second most cause affecting mortality worldwide after cancer. Hence, they require the most specific and targeted drug delivery systems for maximum therapeutic benefits. Metal nanoparticles are the preferred drug delivery system, possessing greater blood-brain barrier permeability, biocompatibility, and enhanced bioavailability. But some metal nanoparticles exhibit neurotoxic activity owing to their shape, size, surface charge, or surface modification. This review article has discussed the pathophysiology of AD. The neuroprotective mechanism of gold, silver, selenium, ruthenium, cerium oxide, zinc oxide, and iron oxide nanoparticles are discussed. Again, the neurotoxic mechanisms of gold, iron oxide, titanium dioxide, and cobalt oxide are also included. The neuroprotective and neurotoxic effects of nanoparticles targeted for treating AD are discussed elaborately. The review also focusses on the biocompatibility of metal nanoparticles for targeting the brain in treating AD. The clinical trials and the requirement to develop new drug delivery systems are critically analyzed. This review can show a path for the researchers involved in the brain-targeted drug delivery for AD.
Biodegradation of Wheat Straw/PLA Composites by Four Kinds of Microorganisms

ABSTRACT In order to compare the degradation of PLA composites by different microorganisms, and reveal the degradation mechanism. Actinomyces israelii, Aspergillus niger, Trichoderma harzianum and Phanerochaete chrysosporium were selected to degrade PLA composites. The weight loss, functional groups, thermal properties and crystallinity of the PLA composites before and after degradation were analyzed. The results indicated that A. israelii and A. niger had the strongest ability to degrade the composites, and the weight loss of the PLA composites reached 7.14% and 6.99% respectively after degradation for 28 days, which were significantly higher than that of the control treatment. According to the characterizations, it was found that the degradation was mainly hydrolysis by the microorganisms and their protease and lipase. Microbial degradation would lead to cracks and dents on the surface of the samples, and increase their contact area with microorganisms, thus accelerating the degradation rate. A. israelii and T. harzianum were more inclined to degrade the PLA in the composites during microbial degradation. Microbial degradation destroyed the crystalline region of the composites, which made they easier to degrade. The results would be helpful to explore the microbial degradation mechanism of PLA composites, and promotes its application in different fields.
A Family of High Step-Up DC–DC Converters Based on Enhanced Boost Cells With Coupled Inductor

In this article, a family of high voltage gain dc–dc converters based on enhanced boost cells with coupled inductor are proposed. Moreover, the derived principle of the boost cells with coupled inductor is proposed and different step-up structures are obtained. Furthermore, the voltage spikes are suppressed and leakage energy of the coupled inductor is recycled by the clamped circuits. Meanwhile, soft switching can be achieved by constructing the resonant circuit with the parasitic capacitor of the switch. The coupled inductor works in discontinuous conduction mode to ensure the resonance, which further improves the voltage gain. To verify theoretical analysis, the laboratorial prototype is built, of which the efficiency is up to 95.55% under full load condition.
The Impact of Commitment to Apply the Standards of the European Model of Excellence in Functional Performance: A Case Study of the Sudanese Electricity Distribution Company

This study aimed to find out the effect of applying the standards of the European model of excellence on the functional performance of the Sudanese Electricity Distribution Company Limited (SEDCL) in Sudan. And come up with results that show the reality of the ability of the Sudanese company to apply this model, the best standards for applying it, and the standards where there is weakness in applying them. 200 questionnaires were distributed to the respondents, of which only 172 were valid for analysis. They were retrieved at a retrieval rate of 86%, which is a high response rate that exceeds the acceptable limit of 75%. There is a weak effect of adherence to the application of the standard (leadership, strategy, partnerships, resources, personnel, and operations) on the functional performance of the Sudanese Electricity Distribution Company Limited. The study concluded that the Sudanese company is committed to apply the standards of the European model, and the commitment to apply the standards (customer results, employee results, community results, key performance) affects the functional performance of the Sudanese Electricity Distribution Company Limited. The best model to use (operations, community results, employee results, key results, partnerships, and resources) in terms of their impact on the Functional performance of the Sudanese Electricity Distribution Company Limited The study recommends that Sudanese Electricity Distribution Company Limited review the application of some elements of the European model that have a weak impact on Functional performance (such as leadership, strategy, employees, and customer results) to achieve the greatest benefit from applying this model.
Numerical Representation of Symbolic Data

: A method of direct numerical representation of symbolic data is proposed. The method starts with parsing a sequence into an ordered set (spectrum) of distinct, non-overlapping short strings of symbols (words). Next, the words spectrum is mapped onto a vector of binary components in a high dimensional, linear space. The numerical representation allows for some arithmetical operations on symbolic data. Among them is a meaningful average spectrum of two sequences. As a test, the new numerical representation is used to build centroid vectors for the k -means clustering algorithm. It signiﬁcantly enhanced the clustering quality. The advantage over the conventional approach is a high score of correct clustering several real character sequences like novel, DNA and protein.
Algorithms and Proofs of Concept for Massive MIMO Systems

This thesis focuses on algorithms and proofs of concepts in the area of wireless systems operating with a large number of antennas, especially at the base station side.The first studied topic concerns the design and implementation of massive multiple-input multiple-output (MIMO) testbeds, primarily for communications. This is an entirely new engineering challenge on its own, due to the unprecedented use of a large number of base station antennas together with time division duplex (TDD)-based operation. We consider hardware and system-level aspects of extending current Long Term Evolution (LTE) systems in order to integrate a massive number of antennas at the base station side. We materialize our testbed design into the Lund University massive MIMO (LuMaMi) testbed, and finalize with (measured) proof-of-concept results to validate our design claims.The second researched topic addresses transceiver calibration to re-establish the reciprocity assumption of a wireless link. This aspect is crucial to be dealt due to the preferred operation mode of massive MIMO, i.e. TDD. To overcome the practical hassles of hardware-based calibration schemes, we propose a convenient over-the-air sounding method between all pairs of base station antennas that allows gathering enough measurements in order to estimate robust calibration coefficients. We provide algorithmic contributions and experimental evidence that corroborate the use of this calibration methodology in practice. This calibration approach is also applied to the case of calibrating the transmitter and receiver chains individually, for classical array beamforming applications.The topic of detection in block fading (massive) SIMO systems is also addressed. This system setup is very representative to those of many existing systems as of today, e.g., in low power sensor networks. Using an estimation framework learned from our work in transceiver calibration, namely the generalized method of moments (GMM), we study a closed-form estimator that balances complexity and performance nicely.The last part of the thesis aims to bring together the emerging topic ofDeep Learning with ngerprint-based terminal positioning using uplink massiveMIMO channels. The key idea is that the intricate structure of raw massiveMIMO channels can be learned by deep learning networks and therefore usedfor positioning purposes. We study the applicability of a particular case of deeplearning methods, namely, convolutional neural networks, which are state-of-the-art learning machines in the context of image processing. (Less)
High speed fluorescence imaging with compressed ultrafast photography

Fluorescent lifetime imaging is an optical technique that facilitates imaging molecular interactions and cellular functions. Because the excited lifetime of a fluorophore is sensitive to its local microenvironment,1, 2 measurement of fluorescent lifetimes can be used to accurately detect regional changes in temperature, pH, and ion concentration. However, typical state of the art fluorescent lifetime methods are severely limited when it comes to acquisition time (on the order of seconds to minutes) and video rate imaging. Here we show that compressed ultrafast photography (CUP) can be used in conjunction with fluorescent lifetime imaging to overcome these acquisition rate limitations. Frame rates up to one hundred billion frames per second have been demonstrated with compressed ultrafast photography using a streak camera.3 These rates are achieved by encoding time in the spatial direction with a pseudo-random binary pattern. The time domain information is then reconstructed using a compressed sensing algorithm, resulting in a cube of data (x,y,t) for each readout image. Thus, application of compressed ultrafast photography will allow us to acquire an entire fluorescent lifetime image with a single laser pulse. Using a streak camera with a high-speed CMOS camera, acquisition rates of 100 frames per second can be achieved, which will significantly enhance our ability to quantitatively measure complex biological events with high spatial and temporal resolution. In particular, we will demonstrate the ability of this technique to do single-shot fluorescent lifetime imaging of cells and microspheres.