On the analyzed section of 2.4 km of the national road No. 50 of the Młodzieszyn bypass, it was carried out by a consortium of OAT and SAT companies in the period April-September 2019, under constant traffic in the field of repairing the concrete pavement by replacing slabs, levelling them and sealing expansion joints, roughening and roadside reinforcements.

During the casting in a warmer tropical temperature, a setting time delay is required to maintain the workability of the concrete, commonly achieved by the addition of admixtures i.e. silica fume (SF), fly ash (FA), and Plastrocrete®. However, high sugar content Coca-Cola in niche conditions is proposed as an ingredient for delaying concrete setting time in combination with conventional admixtures. This research aims to compare the setting time of admixtures from Coca-Cola and Plastocrete® RT6 plus in concrete mixing with control data of concrete mixed with SF or FA. The second aim is to measure the compression strengths between combinations of Coca-Cola and Plastocrete® RT6 plus. Concretes were produced with admixtures of SF, FA, Plastocrete® RT6plus, or Coca-Cola. The concrete used to control was f'c20 and f'c 25, while other concrete mixes were produced with the addition of Coca-Cola at 0.15% from the weight of cement at variation of moisture treatments. The first method to produce concrete (f'c20+Plas0.23%+Cola0.15% and f'c25+Plas0.23%+Cola0.15%) did not employ water reduction. The second concrete productions (f'c25+Plas0.46%+Cola0.15% and f'c25+Plas0.46%+Cola0.15%) reduced the addition of water at 8.8% (v/w). The first concrete production method had a setting time 44% longer than control. The reduced water concrete in the second productions had a setting time 34% longer than control. Meanwhile, the Plastocrete® RT6 Plus admixture with the reduced water delayed the concrete setting time by 26% longer than control. The delayed setting time of Plastocrete® RT6 Plus admixture with reduction of water was shorter than in the treatment with Coca-Cola. The combination of the addition of Coca-Cola with Plastocrete® RT6 plus by reducing the amount of adding Coca-Cola to 0.10% with Plastocrete® RT6 plus can delay concrete setting time by 51% longer than normal concrete and increase concrete compressive strength by 13% higher than normal concrete. Mixing Coca-Cola with Plastocrete® RT6 plus not only provided an optimal delay effect on setting time but also significantly increase the compressive strength that was desired during the casting in warm tropical weather applied in building construction of Mulawarman University, Samarinda, Indonesia.

In order to foster a more sustainable and eco-friendly trajectory for the construction industry, while concurrently mitigating environmental pollution and energy inefficiency, it is imperative to cultivate an environmentally conscious building and urban environment. Under the background of carbon peak and carbon neutrality, green building evaluation system (GBRS) has become a research hotspot in the field of green building. This paper systematically summarizes the current research progress based on GBRS, focuses on the current weight and indicators setting, analyzes it with Cite Space software, and puts forward its future development direction. The results show that the weight setting method of green building evaluation system is determined by multidimensional and multi-method. From the perspective of environment, society and economy, the scope of indicators setting is expanding. The green building evaluation system will play a guiding role in green building design, and the evaluation process will continue to be optimized and developed in the direction of intelligence and automation.

This paper presents a study on optimization of Overcurrent relay (OCR) coordination protection scheme for Sustainable Standalone Hydrokinetic Renewable Energy (SHRE) distribution network at Batang Rajang river, located at Kapit Sarawak, Malaysia by turning river stream into power generation source. The purpose of the project is to develop rural electrification system for native long houses along the river. The research study is tested on a DigSILENT develop model of the SHRE distribution network and in accordance with all respectively unique parameters and relevant standards. Since this is a new standalone distribution system, an efficient and properly coordinated overcurrent protection system must be provided. Improper and miscoordination among OCRs result in maloperation of the protection system that can lead to false tripping and an unnecessary outage and power system instability. Thus, the objective of this work is to employ Genetic Algorithm (GA) technique in Matlab/Simulink for optimal overcurrent coordination and settings among all OCRs in the proposed distribution network in order to improve the speed of OCR tripping operation. The GA is used because the project is fast track and requiring the simplest method available. In this strategy, time dial setting (TDS) is optimized by using plug setting multiplier (PSM) as the constraint. The obtained results show a significant improvement of the relay operating time of 36.01% faster than that of conventional numerical technique during fault occurrence. Thus, an efficient and reliable overcurrent protection scheme has been achieved for the SHRE distribution network.

The liquid droplet cooling technique for fast scanning chip calorimetry (FSC) is introduced, increasing the cooling rate for large samples on a given sensor. Reaching higher cooling rates and using a gas as the cooling medium, the common standard for ultra-fast temperature control in cooling, requires reducing the lateral dimensions of the sample and sensor. The maximum cooling rate is limited by the heat capacity of the sample and the heat exchange between the gas and the sample. The enhanced cooling performance of the new liquid droplet cooling technique is demonstrated for both metals and polymers, on examples of solidification of large samples of indium, high-density polyethylene (HDPE), and poly (butylene 2,6-naphthalate) (PBN). It was found that the maximum cooling rate can be increased up to 5 MK/s in room temperature environment, that is, by 2 orders of magnitude, compared to standard gas cooling. Furthermore, modifying the droplet size and using coolants at different temperatures provide options to adjust the cooling rate in the temperature ranges of interest.

Disseminated or military tuberculosis (TB) is defined as the presence of at least two non-contiguous sites of Mycobacterium tuberculosis, occurring as a result of progressive primary infection, reactivation and spread of a latent focus or due to iatrogenic origin. Disseminated TB represents a life-threatening condition, especially in at-risk children and when the diagnosis and treatment are delayed. We report on a case of a 3-year old boy who presented with long-lasting unrecognised disseminated TB that was successfully managed in a low-resource setting.

In recent times, there has been a growing interest in the use of control charts as a feedback process monitoring technique. Particularly, CUSUM schemes have been proven to be efficient for monitoring processes where the magnitude of the sustained mean shifts is small or moderate. However, because of the constant control limits, the detection ability of CUSUM schemes becomes slow at the initial set-up of the process. The fast initial response FIR feature has often been used to enhance it at the process startup. Meanwhile, the dynamism of real-life problems has always encouraged a more sensitive CUSUM scheme capable of detecting process shifts more rapidly. In this paper, an improved CUSUM scheme for monitoring process mean is proposed. This scheme will be substantial for monitoring processes whose observations are obtained at a distant time interval for example hourly, daily or weekly and where the sustained shifts are assumed to be small or moderate. To demonstrate the practical applications of the proposed scheme, we present its real-life application using datasets from a bottling company and petroleum refinery laboratory.

A reliable and practical renal-lipid quantification and imaging method is needed. Here, the feasibility of an accelerated MRSI method to map renal fat fractions (FF) at 3T and its repeatability were investigated. A 2D density-weighted concentric-ring-trajectory MRSI was used to accelerate acquiring 48×48 voxels (each of 0.25 ml spatial-resolution) without respiratory navigation implementations. The data was collected over 512 complex-FID timepoints with a 1250 Hz spectral bandwidth. The MRSI sequence was designed with a metabolite-cycling technique for lipid-water separation. The in vivo repeatability performance of the sequence was assessed by conducting a test-reposition-retest study within healthy subjects. The coefficient of variation (CV) in the estimated FF from the test-retest measurements showed a high degree of repeatability of the MRSI-FF (CV= 4.3 ±2.5%). Additionally, the matching level of spectral signature within the same anatomical region was also investigated, and their intrasubject repeatability was also high, with a small standard deviation (8.1 ±6.4%). The MRSI acquisition duration was ~3 minutes only. The proposed MRSI technique can be a reliable technique to quantify and map renal metabolites within a clinically acceptable scan time at 3T that supports the future application of this technique for the non-invasive characterization of heterogeneous renal diseases and tumors.

The study focuses on solving urban challenges such as temperature reduction, urban stormwater management, noise reduction, air quality improvement, and CO2 concentrations reduction, and suggests terrestrial and freshwater habitat types (HTs) found in Europe, as innovative forms of nature-based solutions (NBS) for them. Establishment of native HTs in different urban environments to solve urban challenges would enhance biodiversity at different levels and integrate this aspect in urban planning. This contribution builds on the recognition that surfaces of vegetated terrain are the most versatile NBS in addressing the broadest range of environmental problems in urban areas and that the processes running within these green spaces offer the key to socio-ecological improvements of such areas. Employing narrative literature review, qualitative content analysis, and interdisciplinary expert discussion this paper defines why and how native HTs of unchanged nature can be implemented as NBS in the urban environment, indicate potential HTs for specific urban challenges and presents an approach to the inclusion of HTs as NBS into spatial planning documents at national, regional, and local levels. The proposed planning approach attributes added value to HT, and by linking the concepts of NBS and HT integrates them into urban planning.

The study focuses on the crucial aspect of lossless compression for FAST pulsar search data. The deep generative model PixelCNN, stacking multiple masked convolutional layers, achieves neural network autoregressive modeling, making it one of the most excellent image density estimators. However, the local nature of convolutional networks causes PixelCNN to concentrate only on nearby information, neglecting important information at greater distances. Although deepening the network can broaden the receptive field, excessive depth can compromise model stability, leading to issues like gradient degradation. To address these challenges, the study combines causal attention modules with residual connections, proposing the Causal Residual Attention Module to enhance the PixelCNN model. This innovation not only resolves convergence problems arising from network deepening but also widens the receptive field. It effectively utilizes global features, particularly capturing vertically correlated features prominently present in subgraphs of candidates. This significantly enhances its capability to model pulsar data.In the experiments, the model is trained and validated using the HTRU1 dataset. The study compares the average negative log-likelihood score with baseline models like GMM, STM, and PixelCNN. The results demonstrate the superior performance of the our model over other models. Finally, the study introduces the practical compression encoding process by combining the proposed model with arithmetic coding.

For better understanding the corrosion and corrosion products behavior in the primary circuit of lead-bismuth eutectic (LBE) coolant reactor, the concentration distribution of soluble impurities and the transport of solid particles are investigated through finite-element method. An axisymmetric model of the primary circuit of LBE reactor was constructed to accelerate the calculation the thermal hydraulic filed of circuit. The saturation concentration of solute Fe, Cr and Ni in LBE coolant are identified through the equilibrium of their oxides and PbO. And the very different saturation concentrations of Fe/Cr/Ni in LBE will lead to significant element selective corrosion. The migration of solid oxides particles in the primary circuit is also investigated by the Euler-Lagrange tracing model. The simulation shows that driving force for the movement of particles >100 μm is buoyancy, which lets particles float on a free surface, while particles <10 μm tend to suspend in coolant. However, the behavior of particles also depends on the formation position, the particles formed above the core have the high possibility of re-entering in the core.

Background: Few studies have examined multifaceted aspects of fast food consumption and dietary patterns for their effects on obesity. We examined the independent associations of obesity with fast food consumption and dietary pattern in Korean adults. Methods: A total of 19,017 adults aged 19–64y participated from KNHANES 2010-2014. Fast food items were removed from diet and then dietary patterns were generated. Multivariate logistic regression analysis was used to examine the odds for overweight/obesity and central obesity according to fast food consumption and dietary patterns. Results: Fast food consumers were about 10% of Korean adults. Both of White rice and kimchi pattern and Meat and alcohol pattern were associated with low intakes of fiber, calcium, vitamin C, grains, fruit, and milk(p<0.05). Fast food consumers had higher the Meat and alcohol pattern and the Grains, fruit, and milk pattern, and they had lower the White rice and kimchi pattern than non-fast-food-consumers. Fast food consumer were not associated with overweight/obesity, whereas the participants with Meat and alcohol pattern had 14% higher overweight/obesity(95%CI:1.01,1.28) and 16% higher central obesity(95%CI:1.00,1.34). Conclusions: Fast food consumption was not directly associated with obesity, whereas the Meat and alcohol pattern had independent associations with overweight/obesity and central obesity among Korean adults.

The cell case temperature versus time profiles of a multistage fast charging technique (4C-1C-CV)/fast discharge (4C) in a 2.3 Ah cylindrical lithium-ion cell are analyzed using a 1D thermal model. Heat generation is dominated by the irreversible component associated to cell overpotential, although evidences of the reversible component are also observed, associated to the heat related to entropy from the electrode reactions. The final charging stages (i.e., 1C-CV) significantly reduce heat generation and cell temperature during charge, resulting in a thermally safe charging protocol. Cell heat capacity was determined from cell specific heats and cell materials thickness. The 1D model adjustment of the experimental data during the 2 min. resting period between discharge and charge allowed us to calculate both the time constant of the relaxation process and the cell thermal resistance. The obtained values of these thermal parameters used in the proposed model are almost equal to those found in the literature for the same cell model, which suggests that the proposed model is suitable for its implementation in thermal management systems.

The purpose of this systematic review is to examine the various articles published in the field of neuropsychology of anxiety research in terms of publication type and volume, methodology, and subject matter. The significance of this topic derives from the clinical and functional consequences of cognitive symptoms. Generalized anxiety disorder refers to the cluster of clinical symptoms characterized by predominant anxious anticipation and difficulty controlling worry. In order for the review to be systematic and reproducible, a search of the PsycINFO, Scopus, PubMed, Elsevier databases and an analysis using the PRISMA method are suggested. After analyzing the research data, empirical studies evaluating the clinical neuropsychology of generalized anxiety disorder are discussed.

Since the end of 2019 and throughout 2020 the world has been devastated by the SARS COVID-19 pandemic. The sport world suddenly had to deal with a massive reorganization of events with important implications on the physical and psychological preparation of athletes and coaches. The purpose of this study was to explore how these changes impacted coaches’ and athletes’ goal setting strategies and their experience of goal adjustment. As part of a wider mixed-method project involving 2162 coaches and 1354 athletes, an online qualitative survey was used, and data collected were analyzed using reflexive thematic analysis. Findings highlighted three overarching themes, in response to goal adjustment: “Moving on toward new goals”, “Letting go of goals”, and “Trying to hold on”, with several themes and sub-themes identifying different nuances of athletes’ and coaches’ experience. The implications of such findings for the mental preparation of high-level athletes are discussed in two ways. Firstly, in light of existing literature on goal setting from an applied perspective; secondly, in the broader perspective of the sport culture and the application of our themes to other challenging moments that sport professionals might encounter.

Barcode medication administration (BCMA) is advocated as a technology that reduces medication errors relating to incorrect patient identity, drug or dose. Little is known, however, about the impact it has on nursing workflow. Our aim was to investigate the impact of BCMA on nursing activity and workflow. A comparative study was conducted on two similar surgical wards within an acute UK hospital. We observed nurses during drug rounds on a non-BCMA ward and a BCMA ward. Data were collected on drug round duration, timeliness of medication administration, patient identification, medication verification and general workflow patterns. BCMA appears not to alter drug round duration, although it may reduce the administration time per dose. Workflow was streamlined, with a reduction in use of the medicines room. The rate of patient identification increased from 74% (of 47) patients to 100% (of 43), with 95% of 255 scannable medication doses verified using the system. This study suggests that BCMA does not affect drug round duration; further research is required to determine the impact it has on timeliness of medication administration. There was reduced variability in the medication administration workflow of nurses, along with an increased patient identification rate and high medication scan rate, representing potential benefits to patient safety.

The aim of our study is to utilise longitudinal and representative national data to explore the extent that the association between the fast food environment and overweight in adolescents is confounded by neighbourhood deprivation. Longitudinal data from the Millennium Cohort Study for England were obtained for waves 5 (ages 11/12; 2011/12; n=13,469) and 6 (ages 14/15; 2014/15; n=11,884). Our outcome variable was overweight/obesity defined using age and sex-specific International Obesity Task Force cut points. Individuals were linked, based on their residential location, to data on the density of fast food outlets and neighbourhood deprivation. Structural Equation Models were used to model associations at both ages and explicitly test for confounding. While we found some evidence for an association between the number of fast food outlets and overweight, any associations disappeared following accounting for the confounding nature of neighbourhood deprivation. Neighbourhood deprivation was consistently associated to overweight, with adolescents who resided in deprived areas more likely to be overweight. Results were largely consistent depending on different methodological decisions. Our findings suggest that policy efforts should prioritise focusing on tackling the social determinants of excess body mass which will be more effective than interventions aimed at the built environment.

The present paper investigates numerically the resistance at full-scale of a zero-emission, high-speed catamaran in both deep and shallow water, with the Froude number ranging from 0.2 to 0.8. The numerical methods are validated by two means: a) comparison with available model tests; b) a blind validation using two different flow solvers. The resistance, sinkage and trim of the catamaran, as well as the wave pattern, longitudinal wave cuts and cross-flow fields, are examined. The total resistance curve in deep water shows a continuous increase with the Froude number while in shallow water, a hump is witnessed near the critical speed. This difference is mainly caused by the pressure component of total resistance, which is significantly affected by the interaction between the wave systems created by the demihulls. The pressure resistance in deep water is maximised at a Froude number around 0.58, whereas the peak in shallow water is achieved near the critical speed (Froude number ≈ 0.3). Insight into the underlying physics is obtained by analysing the wave creation between the demihulls. Profoundly different wave patterns within the inner region are observed in deep and shallow water. Specifically, in deep water, both crests and troughs are generated and moved astern as the increase of the Froude number. The maximum pressure resistance is accomplished when the secondary trough is created at the stern, leading to the largest trim angle. In contrast, the catamaran generates a critical wave normal to the advance direction in shallow water, which significantly elevates the bow and creates the highest trim angle as well as pressure resistance. Moreover, significant wave elevations are observed between the demihulls at supercritical speeds in shallow water which may affect the decision for the location of the wet deck.

Timely processing of observations from hyper-spectral imagers, such as SEVIRI (Spinning Enhanced Visible and Infrared Imager), largely depends on fast radiative transfer calculations. This paper mostly concerns the development and implementation of a new forward model for SEVIRI to be applied to real time processing of infrared radiances for the physical retrieval of surface temperature and emissivity. The new radiative transfer model improves computational time by a factor of ≈ 7 compared to the previous versions and makes it possible to process SEVIRI data at nearly real time. The new forward model has been applied for the simultaneous retrieval of surface temperature and emissivity in three infrared channels (8.7, 10.8, 12 μm). The inverse scheme relies on a Kalman filter approach, which allows us to exploit a sequential processing of SEVIRI observations. Based on the new forward model, the paper also presents a validation retrieval performed with in situ observations acquired during a field experiment carried out in 2017 at Gobabeb (Namib desert) validation station. Furthermore, a comparison with IASI (Infrared Atmospheric Sounder Interferometer) emissivity retrievals has been performed as well. It has been found that the retrieved emissivities are in good agreement with each other and with in situ observations, i.e. average differences are generally well below 0.01.

The concept of Emotional Intelligence (EI) has gained prominence due to its substantial impact on a range of life outcomes, including academic performance. The present study aims to examine the relationship between Emotional Intelligence and academic accomplishment in the context of a school environment. Analyzing students' emotional skills and competencies makes it possible to uncover the potential of emotional intelligence (EI) in predicting their academic achievement. Additionally, the study emphasizes the importance of integrating emotional intelligence (EI) training within the educational curriculum. Developing students' emotional awareness, empathy, self-regulation, and social skills can yield notable academic benefits, cultivating an environment more favorable to learning. This systematic review examines the relationship between emotional intelligence and its impact on children and teachers by synthesizing several relevant research studies. This study encompasses a comprehensive review conducted from 2016 to 2023. A total of 64 publications were examined in this study, specifically chosen based on their relevance to the review's parameters. These articles were sourced from reputable academic databases, including Scopus, PsycINFO, PubMed, and WoS. The study revealed a correlation between the five dimensions of personality and emotional intelligence, creativity, resilience, the educational framework, and specific experimental programs about its education. The results mentioned above are of great significance, as they demonstrate that emotional intelligence (EI) is not solely a non-essential skill but a vital factor in education that can provide significant perspectives for students, educators, and politicians.

In this paper we provide a highly selected review and synthesis on some of the recent and notable contribution to research in portfolio analysis. A unique perspective on this development in the literature is offered in this paper by judiciously identifying a few sample eigenvalues adjustment patterns in a portfolio that leads to an improvement in the out-of-sample portfolio Sharpe ratio when the population covariance matrix admits a high-dimensional factor model. These patterns unveil a key insight into a portfolio performance improvement and shed an important light on the effectiveness of a few recently introduced ”robust to estimation errors” covariance matrix estimation approaches, which were not originally designed with the goal to improve the out-of-sample portfolio performance.

Poly-DADMAC (PD) is a commonly used organic polymer in water treatment, known for its effectiveness as a coagulant. However, its presence as a residue in water raises concerns related to membrane fouling and the potential formation of carcinogenic compounds. Therefore, fast and simple quantification is necessary to efficiently control and monitor the optimal dose of poly-DADMAC with minimal negative effects. This study introduces a new colorimetric quantification method for poly-DADMAC, based on complexation with a cationic dye (fast green- FG). The method was examined through varying conditions which included different analytical and commercial poly-DADMAC formulations and concentrations. The experiments confirm its effectiveness in quantifying poly-DADMAC with a detection limit of 3.22 µg L^-1 (0.02 µM based on monomers' molecular weight), which is one order of magnitude lower than regulatory requirements (50 µg L^-1). To validate the method, the effect of pH was examined, and implementation demonstrations were conducted on cyanobacteria and cowshed polluted water samples. This research introduces a fast, cost-effective innovative method to accurately quantify poly-DADMAC, enhancing water treatment strategies for high-quality purification and water reuse

Due to the advantages of low latency, low power consumption and high flexibility of FPGA-based acceleration technology, it has been more and more widely studied and applied in the field of computer vision in recent years. An FPGA-based feature extraction and tracking accelerator for real-time visual odometry (VO) and visual simultaneous localization and mapping (V-SLAM) is proposed, which can realize the complete acceleration processing capability of the image front-end and directly output the feature point ID and coordinates to the backend. The accelerator consists of image preprocessing, pyramid processing, optical flow processing, and feature extraction and tracking modules. For the first time, it implements a hardware solution that combines features from accelerated segment test (FAST) corners with Gunnar Farneback (GF) dense optical flow, to achieve better feature tracking performance and provide more flexible technical route selection. In order to solve the scale invariance and rotation invariance lacking problem of FAST features, an efficient pyramid module with a five-layer thumbnail structure is designed and implemented. The accelerator is implemented on a modern Xilinx Zynq FPGA. The evaluation result shows that the accelerator can achieve stable tracking of features of violently shaking images, and is consistent with the results of MATLAB code running on PC. When operating at 100MHz, the accelerator can process 108 frames per second for 720P images and 48 frames per second for 1080P images. Compared to PC CPUs that consume seconds of time, the processing latency is greatly reduced to the order of milliseconds, making GF dense optical flow an efficient and practical technical solution on the edge side.

Photosynthesis is one the most important biological processes on earth, producing life-giving oxygen and is the basis for a large variety of plant products. Measurable properties of photosynthesis provide information about its biophysical state and, in turn, the physiological conditions of a photoautotrophic organism. For instance, chlorophyll fluorescence of an intact photosystem is not linear as in the case of a single fluorescent dye in solution, but shows temporal changes related to the quantum yield of the photosystem. Commercial photosystem analyzers already use the fluorescence kinetics characteristics of photosystems to infer the viability of organisms under investigation. Here, we provide a novel approach based on an optical Fabry-Pérot microcavity or that enables the readout of photosynthetic properties and activity for an individual cyanobacterium. This approach offers a completely new dimension of information, which would normally be lost due to averaging in ensemble measurements obtained from a large population of bacteria.

The recent Planck Legacy release confirmed the existence of an enhanced lensing amplitude in the cosmic microwave background (CMB) power spectra, which endorses the positive curvature of the early Universe with a confidence level exceeding 99%. In this study, the pre-existing curvature is incorporated to extend the field equations where the derived wave function of the Universe is utilized to model Universe evolution with reference to the scale factor of the early Universe and its radius of curvature upon the emission of the CMB. The wave function reveals both positive and negative solutions, implying that matter and antimatter of early Universe plasma evolve in opposite directions as distinct Universe sides. The wave function indicates that a nascent hyperbolic expansion is followed by a first phase of decelerating expansion away from early plasma during the first 10 Gyr, and then, a second phase of accelerating expansion in reverse directions, whereby both Universe sides free-fall towards each other under gravitational acceleration. Simulations of the predicted conformal curvature evolution demonstrate the fast orbital speed of outer stars owing to the external fields exerted on galaxies as they travel through conformally curved space-time. Finally, the wave function predicts an eventual time-reversal phase comprising rapid spatial contraction that culminates in a Big Crunch, signalling a cyclic Universe. These findings reveal that early plasma could have separated and evolved into distinct sides that collectively and geometrically influencing the Universe evolution, physically explanting the effects attributed to dark matter and energy.

Many corner detector techniques have already been used in extracting information from UAV images to perform various photogrammetric and mapping activities. Among these techniques is the Feature from Accelerated Segment Test (FAST) and the Harris corner detector. It is widely agreed that the evaluation of detectors is of great importance because it evaluates and enhances the accuracy of the detected features. This research evaluates the performance of FAST-9 and FAST-12 as well as the Harris detector in terms of the repeatability rate, completeness, and correctness under different threshold values. Each method is evaluated in terms of its ability for detection UAV objects (crowd and cars features). Then the common detected features between both FAST versions and the Harris detector are extracted. This is to determine which method performs best under different image conditions (e.g., illumination variations, camera position and orientation, and image noise). The results show that the size of the threshold plays a crucial role in determining the number of detected feature points. An increase in the threshold value leads to a decrease in the number of detected points and vice versa. Thus, the correctness decreases whereas the completeness increases as a function of the threshold values. Furthermore, the relationship between the FAST-9 and the Harris detector is slightly better than those between the FAST-12 and the Harris detector. This is because the number of common features between the FAST-9 and the Harris detector are relatively higher than those between the FAST-12 and the Harris detector.

Precise determination of the tectonothermal events at the Qinling-Qilian junction is extremely significant for understanding the tectonic evolution of the eastern branch of the Paleo-Tethys. The Banpo porphyry outcrops in the northern margin of the North Qinling were chosen as the research subject, and its formation and tectonic environment were analyzed using Zircon U-Pb age estimation and geochemical studies. The results indicated the final stage of the Triassic orogeny and the closure phase of the Paleo-Tethys. The weighted average values of 206Pb/238U ages of samples from 3 sites of the Banpo porphyry corresponded to 213.4 ±2.1 Ma (MSWD = 0.56), 213.0 ±1.6 Ma (MSWD = 0.92), and 213.2 ±4.4 Ma (MSWD = 1.6). This study revealed that the Banpo porphyry was formed during the Late Triassic (Norian). The porphyry with high SiO2 and high alkali is typical A-type granite, which belongs to the weak peraluminous shoshonite series. All the samples are rich in low rare earth elements. However, the heavy rare earth elements are low, especially Eu, which exhibits a seagull-type right-leaning partitioning curve. In addition, based on the regional geological data, it can be concluded that the Banpo porphyry was formed during the transition period from a post-orogenic environment to a non-orogenic environment. This study indicated the closure of the Paleo-Tethys-Mianxian-Lveyang Ocean by the Late Triassic as well as the completion of the collision between the North China and Yangtze Blocks along the Qinling orogenic belt.

This study proposes a novel flexible bus dispatching system where a fleet of fully automated modular bus units, together with conventional buses, serves the passenger demand. These modular bus units can either operate individually or combined (forming larger modular buses with a higher passenger capacity). This provides enormous flexibility to manage the service frequencies and vehicle allocation, reducing thereby the operating cost and improving passenger mobility. We develop an optimization model used to determine the optimal composition of bus units and the optimal service frequency at which the buses (both conventional and modular) are dispatched across each bus line. We explicitly account for the dynamics of traffic congestion and complex interactions between the modes at the network level based on the recently proposed three-dimensional macroscopic fundamental diagram (3D-MFD). To the best of our knowledge, this is the first application of the 3D-MFD and modular bus units for the frequency setting problem in the domain of bus operations. Numerical results show the improvements in the total system cost made by adapting the number of combined modular bus units and their dispatched frequencies to the evolution of both, the car and the passenger demand. A comparison with the commonly used approach that considers only the bus system (neglecting the complex multimodal interactions and congestion propagation) reveals the value of the proposed modeling framework.

Calcium carbonate cements have been synthesized by mixing amorphous calcium carbonate and vaterite powders with water to form a cement paste and study how mechanical strength is created during the setting reaction. In-situ XRD was used to monitor the transformation of ACC and vaterite phases into calcite and a rotational rheometer was used to monitor the strength evolution. There are two characteristic time scales of the strengthening of the cement paste. The short timescale of the order 1 hour is controlled by smoothening of the vaterite grains, allowing closer and therefore adhesive contacts between the grains. The long timescale of the order 10-50 hours is controlled by the phase transformation of vaterite into calcite. This transformation is, unlike in previous studies using stirred reactors, found to be mainly controlled by diffusion in the liquid phase. The evolution of shear strength with solid volume fraction is best explained by a fractal model of the paste structure.

Objectives: The purpose of this systematic review was to ascertain critical care nurses’ understanding and experiences of patient advocacy in adult critical care settings. The specific objectives were to identify how critical care nurses define patient advocacy, to explore the understanding and experiences of critical care nurses regarding patient advocacy, to explore critical care nurses’ role in patient advocacy, and to ascertain the barriers to encouraging advocacy in the critical care setting. Research design: Systematic literature search of CINAHL and Medline databases, Google Scholar, and Cochrane Database of Systematic Reviews, as well as grey literature search, was conducted. Search dates were restricted from January 2005 to 2015 in both CINAHL and Medline. Findings: 62 studies were identified, of which 6 qualitative research papers were included. Nurses gave varied definitions of patient advocacy, which were categorized into three themes: communication, protection, and doing. Nurses perceive advocacy as truly listening to patients and their families. Conclusion: For critical care nurses to be effective advocates, there must be support, collaboration, and improved working relationship between professional groups. Moreover, nurses must be empowered to be able to give power to patients and family.

Polyvinyl alcohol-engineering cementitious composites (PVA-ECC) has been widely applied in bridge deck repairing or widening, the common practice for doing this is that a portion of a bridge is left open to traffic while the closed portion is constructed, which expose the early age PVA-ECC to the vehicle-induced vibrations. However, whether vehicle-induced vibrations affect the tensile performance of early age PVA-ECC remains unknow. The purpose of this study was to conduct laboratory test programs on how much vehicle-induced vibrations during early ages affected the tensile performance of PVA-ECC. A self-improved device was used to simulate the vehicle-induced vibrations, and after vibrating with the designed variables, both a uniaxial tensile test and a grey correlation analysis were performed. The results indicated that: the effects of vehicle-induced vibrations on the tensile performance of early age PVA-ECC were significant, and they generally tended to be negative in this investigation. In particular, for all of the vibrated PVA-ECC specimens, the most negative age when vibrated occurred during the period between the initial set and the final set. We concluded that although vehicle-induced vibrations during the setting periods had no substantial effects on the inherent strain-hardening characteristics of PVA-ECC, the effects should not be ignored.

The electric vehicle (EV) industry is experiencing rapid growth, accompanied by continuous advancements in charging infrastructure to satisfy the rising need for fast and reliable charging. Particularly, the focus has shifted towards EV fast charging (EVFC) and its impact on the power grid. This paper presents a comprehensive analysis and survey of scholarly literature and projects conducted in this field over the past decade. The findings highlight the rising demand for EVFC and the need to address its potential adverse effects on the power grid. However, there is a noticeable lack of clear research guidance regarding charging time. To tackle these challenges and pave the way for future solutions, extensive research on DC fast charging, ultra-fast charging, and the integration of vehicle-to-grid (V2G) systems is required. This review paper thoroughly investigates the development of fast charging technology for electric vehicles (EVs), including its advantages and comparative analyses from various perspectives. Furthermore, it delves into the advancements in DC fast charging infrastructure, emphasizing charging standards and control modes. The study also investigates different categories of battery chargers for both on-board and off-board charging. Additionally, it explores the classification of DC-DC converters in the context of DC fast charging stations, discusses control strategies for EV systems, identifies existing challenges, and outlines future trends in EV fast charging.

The minimum dominating tree (MDT) problem consists of finding a minimum weight sub-graph from an undirected graph, such that each vertex not in this sub-graph is adjacent to at least one of the vertices in it, and the sub-graph is connected without any ring structures. This paper presents a Dual Neighborhoods Search (DNS) algorithm for solving the MDT problem, which integrates several distinguishing features, such as two neighborhoods collaboratively working for optimizing the objective function, a fast neighborhood evaluation method to boost the searching effectiveness, and several diversification techniques to help the searching process jump out of the local optimum trap thus obtaining better solutions. DNS improves the previous best-known results for 4 public benchmark instances while providing competitive results for the remaining ones. Several ingredients of DNS are investigated to demonstrate the importance of the proposed ideas and techniques.

To ensure the safety in aircraft flying, we aim use of the deep learning methods of nondestructive examination with multiple defect detection paradigms for X-ray image detection posed. The use of the Fast Region-based Convolutional Neural Networks (Fast R-CNN) driven model seeks to augment and improve existing automated Non-Destructive Testing (NDT) diagnosis. Within the context of X-ray screening, limited numbers insufficient types of X-ray aeronautics engine defect data samples can thus pose another problem in training model tackling multiple detections perform accuracy. To overcome this issue, we employ a deep learning paradigm of transfer learning tackling both single and multiple detection. Overall the achieve result get more then 90% accuracy based on the AE-RTISNet retrained with 8 types of defect detection. Caffe structure software to make networks tracking detection over multiples Fast R-CNN. We consider the AE-RTISNet provide best results to the more traditional multiple Fast R-CNN approaches simpler translate to C++ code and installed in the Jetson™ TX2 embedded computer. With the use of LMDB format, all images using input images of size 640 × 480 pixel. The results scope achieves 0.9 mean average precision (mAP) on 8 types of material defect classifiers problem and requires approximately 100 microseconds.

In this paper, a voice coil motor (VCM) actuated fast tool servo (FTS) system is developed for diamond turning. To guide motions of the VCM actuator, a crossed double parallelogram flexure mechanism is selected featuring totally symmetric structure with high lateral stiffness. To facilitate the determination of the multi-physical parameters, analytical models of both electromagnetic and mechanical systems are developed. The designed FTS with balanced stroke and natural frequency is then verified through the finite element analysis. Finally, the prototype of the VCM actuated FTS is fabricated and experimentally demonstrated to have a stroke of ±59.02 μm and a first natural frequency of 253 Hz. By constructing a closed-loop control using PID controller with the internal-model based resonant controller, the error for tracking a harmonic trajectory with ±10 μm amplitude and 120 Hz frequency is obtained to be ±0.2 μm, demonstrating the capability of the FTS for high accuracy trajectory tracking.

Electric vehicles (EVs) are being endorsed as the uppermost successor to fuel-powered cars, with timetables for banning the sale of petrol-fueled vehicles announced in many countries. However, the range and charging times of EVs are still considerable concerns. Fast charging could be a solution to consumers' range anxiety and the acceptance of EVs. Nevertheless, it is a complicated and systematized challenge to realize the fast charging of EVs because it includes the coordinated development of battery cells, including electrode materials, EV battery power systems, charging piles, electric grids, etc. This paper aims to serve as an analysis for the development of fast-charging technology, with a discussion of the current situation, constraints and development direction of EV fast-charging technologies from the macroscale and microscale perspectives of fast-charging challenges. It is emphasized that to essentially solve the problem of fast charging, the development of new battery materials, especially anode materials with improved lithium ion diffusion coefficients, is the key. It is highlighted that red phosphorus is the most promising anode that can simultaneously satisfy the double standards of high-energy density and fast-charging performance to a maximum degree.

The lipid fraction of margarines and fast-food French-fries, two types of foods traditionally high in trans fatty acids (TFA), is assessed. TFA data reported worldwide during the last 20 years have been gathered, and show that some countries still report high TFA amounts in these products. The content of TFA was analysed in margarines (2 store and 4 premium brands) and French-fries from fast-food restaurants (5 chains). Margarines showed mean values of 0.68% and 0.43% (gTFA/100g fat) for store and premium brands, respectively. French-fries values ranged from 0.49% to 0.89%. All samples were lower than the 2% set by some European countries as the maximum legal content of TFA in fats, and contained less than 0.5g/serving, so they could also be considered “trans free products”. This work confirmed that the presence of TFA is not significant in the two analysed products and contributes to update food composition tables, key tools for epidemiological and nutrition studies.

In the current paper, a residual generation filter with finite memory structure is proposed for sensor fault detection. The proposed finite memory residual generation filter provides the residual by real-time filtering of fault vector using only the most recent finite observations and inputs on the window. It is shown that the residual given by the proposed residual generation filter provides the exact fault for noise-free systems. The proposed residual generation filter is specified to the digital filter structure for the amenability to hardware implementation. Finally, to illustrate the capability of the proposed residual generation filter, numerical examples are performed for the discretized DC motor system having the multiple sensor faults.

The 2019 Coronavirus pandemic which was initially referred to as 2019-nCoV, was first identified in Wuhan, China. Early response from the Chinese government included quarantine of infected persons, isolation and total lockdown of Wuhan province to prevent further spread. With the spread of the disease across national borders and declaration of the disease as a global pandemic, there has been a robust response by the international community to contain this deadly virus and prevent its further spread worldwide. Africa is not left out of this rampaging pandemic with documented cases in over 40 countries and still rising. Although extensive studies have been carried out on the novel SARS-CoV-2 on its pathogenesis, mode of infection and virulence but much is still unknown. However, potentially infectious samples are received routinely in the medical laboratory for analysis. This technical note reviews good laboratory practice (GLP) and processes across the different specialities of Medical Laboratory practice that should minimize the risk of infection to laboratory staff especially in resource-limited settings.

In this paper, we consider a manufacturer who produces and sells a kind of innovative product in the monopoly market environment. Because the life cycle of innovative product is usually shorter than its procurement lead time, one unique demand quantity (scenario) will occur in the selling season, thus there is only one chance for the manufacturer to determine both optimal production quantity and optimal sale price. Considering this one-time feature of such a decision problem, a price-setting newsvendor model for innovative products is proposed. Different to the existing price-setting newsvendor models, the proposed models determine the optimal production quantity and sale price based on some specific state (scenario) which is most applicable for the manufacturer. The theoretical analysis provides managerial insights into the manufacturers’ behaviors in a monopoly market of an innovative product and several phenomena in the luxury goods market are well explained.

The present study aimed to clarify the relationship between brand awareness and word-of-mouth communication in the fast-food sector, Lambayeque Region, 2023. By adopting a quantitative approach, statistical tools were utilized to measure variables and address hypotheses and objec-tives. The study was correlational in nature, as it demonstrated the relationship between brand awareness and word-of-mouth communication. It was also applied in scope, disseminating learning based on the research that will assist the studied area. Furthermore, this study employed a nonexperimental, cross-sectional design because the variables were only analyzed in the workplace environment at a single point in time and were not manipulated. According to the results, it is evident that consumers will easily recall their favorite brands, provided these brands meet their expectations are deemed significant, and the information on social networks is updated, detailed, useful, and valuable. Moreover, they are likely to recommend them if they recognize and have a positive valuation of the brand, sharing favorable information about it on their social networks and with their peers. The study concludes that virtual interactivity and the quality of information are linked to the generation of brand awareness, which in turn was shown to be a predictor of eWOM.

Epilepsy is a chronic neurological disorder characterized by recurring seizures resulting from abnormal neuronal hyperexcitability. In the case of pharmacoresistant epilepsy requiring resection surgery, identifying the epileptogenic zone (EZ) is crucial. Fast ripples (FRs; 200-600 Hz) are one of the promising biomarkers that can aid in EZ delineation. However, recording FRs requires small surface electrodes. These microelectrodes suffer from high impedance, which significantly impacts FR observability and detection. In this study, we explored the potential of a conductive polymer coating to enhance FR observability. We employed biophysical modeling to compare two types of microelectrodes: Gold (Au) and Au coated with the conductive polymer poly(3,4-ethylenedioxythiophene)-poly(styrene sulfonate) (Au/PEDOT:PSS). These electrodes were then implanted in the CA1 hippocampal neural network of epileptic mice to record FRs during epileptogenesis. Results showed that polymer-coated electrodes demonstrate two-order lower impedance and a higher transfer function amplitude and cut-off frequency. Consequently, FRs recorded with the PEDOT:PSS coated microelectrode yielded significantly higher signal energy compared to the uncoated one. The coating with PEDOT:PSS improved the observability of recorded FRs and therefore their detection. This work paves the way for the development of signal-specific microelectrodes design allowing better targeting of pathological biomarkers.

This research explores the enhancement of bio-oil quality through upgrading with the magnetic bimetallic oxide (CuO-Fe3O4) catalysts supported on the activated rice straw biochar (AcB). These catalysts were employed in a supercritical ethanol-based upgrading process. Various characterization techniques, including elemental analysis, XRD, BET, TGA, and SEM, were utilized to characterize the prepared catalyst. The study revealed significant improvements in the physical characteristics and chemical composition of the bio-oil, with higher heating value (HHV) increasing from 21.3 to 32.1 MJ/kg. Esterification and transesterification were identified as key reactions contributing to this improvement. Notably, the pH of bio-oil increased from 4.3 (raw bio-oil) to 5.63 (after upgrading), signifying reduced acidity. The analysis of the bio-oil's chemical composition highlighted a decrease in oxygen content and an increase in carbon and hydrogen content. At the optimum conditions, the application of supercritical ethanol proved to be an efficient method for enhancing the bio-oil's properties. A crucial transformation occurred during the upgrading process and more than 90% % of carboxylic acids were converted into esters, primarily ethyl acetate at the optimal conditions. This study has demonstrated the effective enhancement of raw bio-oil from rice straw through the utilization of carbon-based bimetallic oxide catalysts in a supercritical upgrading procedure.

NMR spin relaxation times have been an instrumental tool in deciphering the local en-vironment of ionic species, the various interactions they engender and the effect of these interactions on their dynamics in conducting media. Of particular importance has been their application in studying the wide range of electrolytes for energy storage, on which this chapter is based. Here we highlight some of the research carried out on electrolytes in recent years using NMR relaxometry techniques. Specifically, studies on liquid electro-lytes, such as ionic liquids and organic solvent; on semi-solid-state electrolytes, such as ionogels and polymer gels, and solid electrolytes such as glasses, glass ceramics and polymers. Although this chapter focuses on a small selection of materials, we believe they demonstrate the breadth of application and the invaluable nature of NMR relaxometry.

The article presents research results of the γ-ray and fast neutrons impact on various rice species, in order to obtain mutant forms resistant to salinity (NaCl) and drought factors (sorbitol. They are going to be used as initial forms in synthetic selection when creating varieties, adapted to the stressful conditions of, both, soil and climate in the Kazakhstan Aral Sea. The average lethal doses (LD50) of γ-rays and fast neutrons, as well as the average NaCl and sorbitol lethal concentrations were established. Such environment is best suited for clear manifestation of the mutagenic effect of ionizing radiation and the resistance of rice plants to salinity and drought. A distinct dependence in the effect of ionizing radiation and stress factors on the number of induced resistant mutant forms has been related to the initial rice sort. The largest number of mutant forms was obtained from the local variety Syr Suluy, followed by Leader and AyKerim varieties. From all varieties, the number of mutants obtained from exposure to γ-rays was 43 pieces out of 4500 grains, and from the impact of fast neutrons - 115 pieces out of 2700 grains. M1 mutant plants significantly differ from the initial forms in terms of morphological features – plant height, panicle length, grain size Most plants are characterized by short growth and even dwarfism (˂80 cm). They are lodging tolerant, have short and highly sterile panicles, indicating that they are mutants and resistant to salinity, drought, or both.

Time series data having low signal-to-noise ratio, non-stationarity and non-linearity are commonly seen in high-frequency stock trading, where the objective is to increase the likelihood of profit by taking advantage of tiny discrepancies in prices and trading on them quickly and in huge quantities. For this purpose, it is essential to apply a trading method that is capable of fast and accurate prediction from such time series data. In this paper, we develop an online time series forecasting method for high-frequency trading (HFT) by integrating three neural network deep learning models, i.e., Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU) and Transformer; and we abbreviate the new method to online LGT or O-LGT. The key innovation underlying our method is its efficient storage management, which enables super-fast computing. Specifically, when computing the forecast for the immediate future time, we use only the output calculated from the previous trading data (rather than the previous trading data themselves) together with the current trading data. Thus, the computing involves updating only the current data into the process. We evaluate the performance of O-LGT by analyzing the high-frequency Limit Order Book (LOB) data from the China market. It shows that our model in most cases achieves similar speed with much higher accuracy than the conventional fast supervised learning models for HFT. However, with a slight sacrifice in accuracy, O-LGT is approximately 40 times faster than the existing high-accuracy neural network models for the LOB data in China market.

Previous studies implied the different behavioral intention formation of a specific object for individuals in different age groups, but few research to Chinese consumers’ sustainable fast fashion behaviour were found considering the enormous amount of consumption and waste of fast fashion products in China. Meanwhile, as a fast developing country, it might be insufficient to conduct research ignoring the consequences of different education level and growing environment among different generations. Thus, to generate in-depth and heuristic Chinese consumers information, this study developed proposed theoretical framework (TORA) based on research by Fishbein and Ajzen (1975), while the validity among Chinese consumers was tested as well. Following the TORA model, this study aims to investigate if consumers’ age will moderate the relationship between attitude and intention, and the relationship between subjective norms to behavioral intention. Through structural equation modelling in AMOS, it was found that the model has a well fit to large sample of Chinese consumers, while the moderation effect of age was not significant in the whole sample. Further hierarchical regression analysis conducted in SPSS and Process was able to locate the moderation effect of if divide the consumers into groups by age. Which is, age is significantly and positively moderating the path subjective norms to intention in younger generation (18-25), but significantly positive moderating attitude to intention in consumers aged 26-39. Implications in marketing and to policy makers are discussed at the end of this research.

In this study, we report a new epoxy acrylate based shape memory polymer(SMP) fabricated by Liquid crystal display (LCD) Stereolithographic 3D printing. The printed 3D object has a high resolution and high transparency in visible light region. The uniaxial tensile tests showed enhanced tensile toughness and tunable mechanical properties. The fix-recovery and cycle tests indicated high shape recovery properties including high shape recovery rate and excellent cycling stability. In addition, a smart electrical valve actuator was fabricated that can be used in fast heat or electricity responsive electrical circuits. LCD 3D printing provides a low-cost and high efficient way to fabricate fast responsive SMP, which can be used in wide applications in various fields on aerospace engineering, biomedical devices, soft robots and electronic devices.

Background: Best Possible Medication History (BPMH) collected by clinical pharmacists is crucial for effective medication review but, in Italy, it is often left to the nursing staff. This study aims to compare the quality and accuracy of a clinical pharmacist-documented BPMH with the current standard practice of ward staff-collected BPMH at an Italian perioperative surgical setting. Methods: A 20-week prospective observational non-profit study was conducted in a major University hospital. The study comprised a feasibility, an observational, and an interventional phase. During the feasibility phase, 10 items for obtaining a correct BPMH were identified. The control group consisted of retrospectively analyzed BPMHs collected by the ward staff during the observational phase, while interventions included BPMHs collected by the clinical pharmacist during the third phase. Omissions between the two groups were compared. Results: 14 (2%) omissions were found in the intervention group, compared with 400 (57.4%) found in the controls (p<0.05); data collection was more complete when collected by pharmacists compared to the current modalities (98.0% versus 42.6%; p<0.05). Conclusions: The involvement of a pharmacist significantly reduced the number of omissions in perioperative surgical-collected BPMHs. This intervention holds the potential to decrease the risk of medication errors associated with inaccurate or incomplete BPMHs prior to surgical hospitalization.

Being hospitalized is a threatening and stressful experience for many children. From a psychological point of view, children may experience increased feelings of anxiety and fear that can negatively interfere with behavioral, cognitive, and emotional outcomes. To limit these impacts on children's well-being and mental health, interventions that could contribute to protecting the emotional domain of hospitalized children are welcomed. The present research reported a single-setting case study intervention to evaluate the impact of educational play-based activity with a CoderBot robot in a pediatric short-term recovery ward (N=61). The methodology included multiple sources of data (i.e., children, parents, nurses), observations on the field, and a sequential (quantitative-qualitative) mixed-method approach to data analysis. Results supported the idea that robot-based activities were associated with increased participant well-being (particularly positive emotions). The conclusions of this pilot study discuss the strengths, limitations, and further developments of using robots with hospitalized children.

Management of demand and capacity for airport operation is important. The effect of capacity setting on slot adjustment, maximum adjustment and flight delay has been extensively investigated and discussed in previous slot adjustment models. But its effect on characteristics of flight waves has not been studied deeply. At present, in order to resolve the problem that Linear Integer Programming (LIP) is limited in slot allocation due to its fast dimension growth and large memory consumption, the general practice is to optimize the slot application according to data-splitting technology. However, the relationship among data splitting method, capacity setting and characteristics of slot wave has not been investigated in detail, which limits the application of LIP in slot allocation. Through the detailed analysis and testing, we found that the waveform and amplitude of slot wave can be controlled and designed by appropriate virtual capacity settings, while the number of capacity constraints and the computing time is reduced by adopting appropriate data feeding method. Our research also provides clues for further research on the construction of the flight waves for airlines operating at specific airports in order to establish direct or indirect connectivity, and increase hit rate by using our approaches.

The ageing of workers is one of the most important issues for occupational health and safety in Europe. A number of intervention studies on health promotion for older workers were conducted in European workplaces between 2000 and 2015. This review gives an overview of these studies and considers perspectives for workplace health promotion.

Plasmonic nanocomposites have the ability to enhance light-matter interaction due to the 1 plasmonic effects leading to promising potential applications. In this paper, we theoretically study the 2 group index of the silver nanoparticle-gold nanoparticle-quantum dot plasmonic hybrid system in 3 the optical region of the electromagnetic spectrum using the density matrix approach. The quantum 4 dot is considered to be a three-level atomic system of a lambda configuration, interacting with strong 5 control and weak probe fields. We find that the plasmonic hybrid system exhibits at near resonance a 6 strong switching between slow and fast light, which can be controlled by the inclination angle of the 7 gold nanoparticle and the size of the metals nanoparticles, in addition to the strength and detuning 8 of the control field. Thus, the silver nanoparticle-gold nanoparticle-quantum dot could potentially be 9 used in optoelectronic devices.10

The article presents the results of the γ-ray and fast neutrons impact on various rice species, in order to obtain mutant forms resistant to salinity (NaCl) and drought factors (sorbite). They are going to be used as initial forms in synthetic selection when creating varieties, adapted to the stressful conditions of, both, soil and climate in the Kazakhstan Aral Sea. The average lethal doses (LD50) of γ-rays and fast neutrons, as well as, the average NaCl and sorbite lethal concentrations were established. A distinct dependence on the effect of ionizing radiation and stress factors on the number of induced resistant mutant forms has been related to the initial rice variety. The largest number of mutant forms was obtained from the local variety Syr Suluy, followed by Leader and Aikerim varieties. Out of all varieties, only 1% of the initially irradiated by γ-rays seeds survived, while after fast neutron irradiation – 4,3%. M1 mutant plants significantly differ from the initial forms in terms of morphological features – plant height, panicle length, and grain size. They are tolerant to lodging, and have short and highly sterile panicles, indicating that they are mutants.

The crystal nucleation and overall crystallization kinetics of cross-linked poly(ε-caprolactone) was studied experimentally by fast scanning calorimetry in a wide temperature range. With an increasing degree of cross-linking, both the nucleation and crystallization half-times increase. Concurrently, the glass transition range shifts to higher temperatures. In contrast, the temperatures of the maximum nucleation and the overall crystallization rates remain the same independent of the degree of cross-linking. The cold crystallization peak temperature generally increases as a function of heating rate, reaching an asymptotic value near the temperature of the maximum growth rate. A theoretical interpretation of these results is given in terms of classical nucleation theory. In addition, it is shown that the average distance between the nearest cross-links is smaller than the estimated lamellae thickness, which indicates the inclusion of cross-links in the crystalline phase of the polymer.

One of the research priorities in atmospheric chemistry is to advance our understanding of heterogeneous reactions and their effect on the composition of the troposphere. Chemistry on aqueous surfaces is particularly important in this regard because of their ubiquity and expanse. They range from the surfaces of oceans (360 million km²), cloud and aerosol drops (~10 trillion km²) to the fluids lining the human lung (~200 m²). Typically, ambient air contains reactive gases that may affect human health, influence climate and participate in biogeochemical cycles. Despite their importance, reactions between gases and solutes at air-aqueous interfaces are not well understood. New, surface-specific techniques are required that detect and identify the intermediates and products of such reactions as they happen on liquids. This is a tall order because genuine interfacial reactions are faster than mass diffusion into bulk liquids, and may produce novel species at low concentrations. Herein, we review evidence that validates online pneumatic ionization mass spectrometry of liquid microjets dosed by reactive gases as a technique meeting such requirements. Next, we call attention to results obtained by this approach on reactions of ozone, nitrogen dioxide and hydroxyl radicals with various solutes on aqueous surfaces. The overarching conclusion is that the outermost layers of aqueous solutions are unique media, where equilibria shift and reactions proceed faster than, in some cases along different pathways from the bulk liquids. The fact that the rates and mechanisms of reactions at air-aqueous interfaces may not be deduced from experiments in bulk liquids opens new conceptual frameworks and lines of research, and adds an overlooked dimension to atmospheric chemistry.

E-scooters are a micromobility transportation option for completing short trips. In recent years, many ‎cities welcomed shared e-scooters in an effort to offer more mode choices, increase travelers' ‎convenience, and reduce automobile use in their service areas. However, a knowledge gap still remains ‎regarding the acceptability of shared e-scooters as a transportation option, which motivates additional ‎research on user and non-user preferences and attitudes toward e-scooter use. This study investigates ‎latent variables impacting the adoption of shared e-scooters in urban areas, focusing on mode choice ‎factors and attitudes towards e-scooter use and car use. The study utilizes machine learning (ML) ‎techniques and SHAP analysis to analyze survey data (N=1196) collected from travelers in Washington, ‎D.C., Miami, FL, and Los Angeles, CA, in 2021 and 2022. A comparative analysis is performed to develop ‎comprehensive demographic profiles of e-scooter users. The analysis reveals gender (male), age (25-39 ‎years age group), higher income, and educational background as the most relevant factors toward e-‎scooter use. Attitudinal variations among e-scooter users and non-users underscore the complexity of ‎perceptions toward e-scooter use, with significant differences in mode choice factors and attitudes ‎toward the use of e-scooters and private vehicles. Notably, educational background ranked as a significant ‎factor in Washington, D.C., and Miami, while Factor 3, derived from factor analysis and encompassing car ‎use attitudes and the utilization of technology, emerged as influential in Los Angeles. This research ‎contributes fresh insights into factors shaping e-scooter adoption, offering a foundation for informed ‎urban transportation planning and policymaking. The holistic approach showcased in this study enhances ‎understanding of shared micromobility and its implications for urban mobility.

Background/aim: Sexual harassment has become a serious social and public health problem in adolescence, causing adverse effects on mental health. Nevertheless, some behaviours arise that, due to their characteristics, might be misinterpreted as sexual harassment. A field study, a survey with a non-probabilistic accidental sampling, was designed in order to estimate the prevalence of sexual harassment victimization in the Spanish adolescent population, as well as to quantify the harms. Method: 1028 Spanish adolescents, 54.3% females and 45.7% males, aged 13-17 years (M = 15.21, SD = 1.03), responded to a diagnostic measure of sexual harassment victimization and an inventory measure of internalizing and externalizing Mental Health Problems (MHPs). Results: The results showed a significant prevalence of diagnosed sexual harassment victimization of school-aged adolescents, 24.1%, 95% [.215, 267], with adverse effects on internalizing and externalizing MHPs. As for the internalizing MHPs, the results showed moderate adverse effects on depression, anxiety, somatic burns, posttraumatic symptoms, and obsessive-compulsive symptoms; and mild adverse effects on social anxiety. With regard to externalizing MHPs, the results revealed moderate adverse effects on hyperactivity-impulsivity, anger control and antisocial behaviour; and mild adverse effects on attention problems, aggression and defiant behaviour. In addition, it was corroborated that sexual harassment victimization affects adolescent females to a greater extent, with the effect being significantly greater in internalizing than in externalizing MHPs. Conclusions: The results obtained are discussed and future lines of research and intervention are proposed to promote the implementation of prevention and intervention programs that address this phenomenon and, in turn, improve the physical, psychological, and social well-being of adolescents.

Jabulile Ndlovu1 and Kebogile Mokwena1, 2 1 Department of Public Health, Sefako Makgatho Health Sciences University, Pretoria, South Africa 2 Research Chair in Substance abuse and population Mental Health, Sefako Makgatho Health Sciences University, Pretoria, South Africa Corresponding author: jabulilendlovu5@gmail.com Abstract An estimated 6% of the world population has serious mental illness, with one in four families having a member with some form of psychiatric disorder, who are mostly cared for by their relatives within a family setting. Although caregiving in a home setting is reported to be associated with significant mental distress, the burden of such distress is rarely measured. The purpose of this study was to quantify the burden of care among family caregivers of relatives with serious mental disorders, as well as to explore possible association between the caregiver burden of care and a range of caregiver and Mental Health Care User (MHCU) variables in a rural district in Kwa-Zulu Natal, South Africa. The Zarit Burden Interview (ZBI) scale was used to collect data from 357 caregivers, and STATA 14 was used to analyze data. The ages of the sample ranged from 18 to 65, with a mean of 50.29, and the majority (86%) were female and unemployed (83%). The ZBI scores ranged from 8 to 85, with a mean of 41.59. The majority (91%) tested positive for caregiver burden of care, which ranged from mild to severe. Using the Pearson Chi-square test of association (p=0.05), variables that were significantly associated with the burden of care were clinically related (caregiver self-reported depression, MHCU diagnosis, recent relapse of the MHCU), socio-economic (caregiver family monthly income, MHCU disability grant status and MHCU employment status) and socio-demographic (MHCU gender and MHCU level of education). The prevalence of burden of care is high and severe, and scarcity of resources in families and communities contribute to the high burden of care in these rural communities.

Background. There are scant data about the effectiveness of high flow nasal cannula (HFNC) oxygen therapy in patients hospitalized with severe acute respiratory failure (ARF) in non-intensive medical wards, particularly regarding the effect on arterial oxygenation compared to conventional oxygen therapy (COT) and non-invasive ventilation (NIV) or continuous positive airway pressure (CPAP). Methods. In a retrospective observational study, oxygenation parameters were measured before and immediately after HFNC initiation in 37 consecutive patients hospitalized in a geriatric ward in 2017. Results. HFNC was used as escalation therapy for untreatable hypoxia after failure of NIV/CPAP (n=18) or COT (n=19). Twenty-two patients died, 2 were transferred to the intensive care unit, while 13 were discharged alive. A “do not intubate” status was identified in 17 of the 22 deceased patients. Partial pressure of oxygen (pO2, p< 0.0001), oxygen saturation (SO2, p< 0.0001), pO2/fraction of inspired oxygen ratio (p=0.004) and peripheral SO2 measured by pulse oximetry (p< 0.0001) significantly increased soon after HFNC application. Oxygenation improvements were greater after escalation from NIV/CPAP and in patients discharged alive. Conclusion. HFNC significantly improved oxygenation in severe ARF after failure of COT or NIV/CPAP and may be particularly suitable for older patients hospitalized in non-intensive medical wards.

Fault line detection timely and accurately when single-phase-to-earth fault occurs in resonant grounding system is still a focus of research. This paper presents a new approach for fault detection based on data fusion and it has non-artificial setting. Firstly, the fault criterion for interphase difference energy ratio and time-frequency correlation coefficient of each line is proposed. Subsequently, the paper establish a coordinate system with the interphase difference energy ratio as X axis and the time-frequency correlation coefficient as Y axis, and it uses the Euclidean distance algorithm to get the characteristic distance of each line by fusing two-dimensional information. Finally, comparing the sound distance and the fault distance of each line to discriminate the fault line. Electromagnetic Transients Program (EMTP) simulation results and adaptability analysis have confirmed the effectiveness and reliability of the proposed scheme.

Diffusion-controlled cyclic voltammograms at fast scan rates show peak shifts as well as decreases in the peak currents from the predicted diffusion-controlled currents especially when currents are large in low concentration of supporting electrolyte. This has been conventionally recognized as an IR-drop effect by solution resistance on the peaks as well as heterogeneous kinetics. It is also brought about by negatively capacitive currents associated with charge transfer reactions. The reaction product generates dipoles with counterions to yield a capacitance, of which current flows oppositely to that of the double layer capacitance. The three effects are specified here in the oxidation of a ferrocenyl derivative by fast scan voltammetry. The expression for voltammograms complicated with IR-drop is derived analytically, and yields deformed voltammograms. The peak shift is approximately linear with the IR-term, but exhibits a convex variation. Dependence of some parameters on the peaks by the IR-drop is compared with those by the negative capacitance. The latter is more conspicuous than the former under conventional conditions. The two effects cannot be distinguished specifically except for variations of conductance of the solution.

The market for microfluidic chips is experiencing significant growth; however, their development is hindered by a complex design process and low efficiency. Enhancing microfluidic chips’ design quality and efficiency has emerged as an integral approach to foster their advancement. Currently, the existing structural design schemes lack careful consideration regarding the impact of chip area, microchannel length, and the number of intersections on chip design. This inadequacy leads to redundant chip structures resulting from the separation of layout and wiring design. This study proposes a structural optimization method for microfluidic chips to address these issues utilizing a simulated annealing algorithm. The simulated annealing algorithm generates an initial solution in advance using the fast sequence pair algorithm. Subsequently, an improved simulated annealing algorithm is employed to obtain the optimal solution for the device layout. During the wiring stage, an advanced wiring method is used to designate the high wiring area, thereby increasing the success rate of microfluidic chip wiring. Furthermore, the connection between layout and routing is reinforced through an improved layout adjustment method, which reduces the length of microchannels and the number of intersections. Finally, the effectiveness of the structural optimization approach is validated through six sets of test cases, successfully achieving the objective of enhancing the design quality of microfluidic chips.

Food analysis demands fast methods for routine control and high throughput of samples. Chromatographic separation enables simultaneous determination of numerous compounds in complex matrices, several approaches increasing separation efficiency and speed of analysis were involved. In this work, modern types of column with monolithic rod or superficially porous particles were employed and compared for determination of eight synthetic food dyes, their chromatographic performance was evaluated. During method optimization, cyano stationary phase Chromolith Performance CN 100 × 4.6 mm and Ascentis Express ES-CN 100 × 4.6 mm, 5 µm were selected for the separation of polar colorants. The separation was performed by gradient elution of acetonitrile/methanol and 2% water solution of ammonium acetate at flow rate 2.0 ml min-1. Mobile phase composition and the gradients were optimized in order to enable efficient separation on both columns. The method using fused-core particle column provided higher separation efficiency, narrow peaks of analytes resulted in increased peak capacity and shortening of analysis time. After the validation, the method was applied for analysis of colored beers, soft drinks and candies.

Commercially pure (c.p.) iron powders with a deliberate high degree of oxidation were consolidated by medium-frequency electrical resistance sintering (MF-ERS). This is a consolidation technique where pressure, and heat coming from a low-voltage and high-intensity electrical current, are simultaneously applied to a powder mass. In this work, the achieved densification rate is interpreted according to a qualitative microscopic model, based on the compacts global porosity and electrical resistance evolution. The effect of current intensity and sintering time on compacts was studied on the basis of micrographs revealing the porosity distribution inside the sintered compact. The microstructural characteristics of compacts consolidated by the traditional cold-press and furnace-sinter powder metallurgy route are compared with results of MF-ERS consolidation. The goodness of MF-ERS versus the problems of conventional sintering when working with oxidized powders is analyzed. The electrical consolidation allows to obtain higher densifications than the traditional route under non-reducing atmospheres.

Background: The proven efficacy of mTOR inhibitors (mTORI), tyrosine kinase inhibitors (TKI) or immune checkpoint inhibitors (ICI) therapies in metastatic renal cell carcinoma (RCC), suggested that these agents should be investigated as adjuvant therapy with the aim of eliminating any residual undetectable microscopic disease after curative resection. Our study aimed to compare the efficacy of these treatments through the application of an innovative method that reconstructs individual patient data. Methods: Nine phase III studies describing different treatment options for adjuvant RCC were selected. Individual patient data were reconstructed from Kaplan–Meier (KM) curves through the “IPDfromKM method”. Disease-free survival (DFS) were compared among combination treatments and control arm (placebo). Results were summarized as multi-treatment KM curves. Standard statistical testing was used, including hazard ratio and likelihood ratio tests for heterogeneity. Results: In the overall population, this study showed that two ICIs (pembrolizumab and nivolumab plus ipilimumab) and one TKI (sunitinib) showed superiority over placebo, whereas both TKI and mTORI did not. As we assessed DFS as the primary endpoint for the adjuvant comparison, the overall survival benefit remains unknown.. Conclusion: This novel approach to investigating survival has allowed us to conduct all of the indirect head-to-head comparisons between these agents in a context where no "real" comparative trials have been conducted.

Repetitive transcranial magnetic stimulation (rTMS) with intensive occupational therapy improves upper limb motor paralysis and activities of daily living after stroke; however, amount of improvement according to paralysis severity remains unverified. Target activities for daily living using patients’ upper limb functions can be established by predicting the amount of change after treatment for each severity level of upper limb motor paralysis and further aid practice planning. This study estimated post-treatment score changes for each severity level of motor paralysis (no, poor, limited, notable, and full) stratified according to Action Research Arm Test (ARAT) scores before combined rTMS and intensive occupational therapy. Severity of motor paralysis was the fixed factor for analysis of covariance, delta (post-pre) of the scores was the dependent variable. Ordinal logistic regression analysis was used to compare changes in ARAT subscores in patients, divided according to paralysis severity before treatment. A multicenter retrospective cohort dataset analyzed 907 patients with stroke hemiplegia. Largest treatment-related changes in scores were observed in the Limited recovery group for upper limb motor paralysis and Full recovery group for quality-of-life activities using paralyzed upper limb. These results will help predict treatment effects and determine exercises and goal movements for occupational therapy after rTMS.

Based on a reflection on the tensions between play, education, and learning in early childhood, this article aims to identify and analyze the factors that limit or negatively condition the possibilities for play at school during the transition between Early Childhood Education and Primary Education in Chile. The study was conducted in four Chilean schools, with the Transition Levels of Chilean Early Childhood Education (children aged 4 and 5) and the first two levels of Primary Education (children aged 6 and 7). Based on an ethnographic approach, we combined 22 ethnographic observation days spread over two consecutive years and 59 interviews of various types with children, educators, and parents. The results show structural-material limitations on school play that mainly affect children in Primary Education. Beyond, factors associated with routines, indications, and statements governing functioning and participation in this level tend to limit or prevent play, often considered a "non-legitimate" activity. Conclusions highlight the potentialities that children's restricted or resisted play can present in terms of learning.

This paper presents a study of the 2D roughness profiles on a flat surface generated on a steel work piece, by ball nose end milling, with linear equidistant tool paths (pick-intervals). The milled surface exploration with a surface roughness tester (on pick and feed directions) produces usually 2D roughness profiles having periodical evolutions. These evolutions can be seen as time-dependent signals, describable as a sum of sinusoidal components (the wavelength of each component being regarded as a period). In order to detect a well approximated description of these components, two appropriate signal processing techniques are used in this work: first technique provides a direct mathematical (analytical) description and is based on computer aided curve (signal) fitting (more accurate), the second technique (providing an indirect and incomplete description) is based on the spectrum generated by fast Fourier transform (less accurate). This study can be seen as a way for a better understanding the interaction between the tool and the work piece or to achieve a mathematical description of the machined surface microgeometry in terms of roughness (e. g. its description being a collection of closely spaced 2D roughness profiles).

The testing requirements of the active phased array antennas are very different from those of traditional passive antennas, due to its beam steering capability. Usually, each beam profile of the active phased array needs a separate radiation pattern test, which makes the overall testing time extremely long. Thus the traditional antenna test method can no longer meet the efficiency and cost requirements of new active phased array antennas test. In this paper, a fast test method tailored for phased array antennas is proposed that offers significantly reduced testing time at the expense of slight sacrifice of the accuracy. Using the simulated element pattern in array and ideal port excitation, the beam profile in any direction can be predicted by testing only a certain beam profile. Through theoretical derivation and experiments, the effectiveness of the method is verified, and the testing efficiency of the phased array antenna is demonstrated to be improved by ten times or even more.

Fast neutron (FN) radiation mediated mutagenesis is a unique approach among the several induced mutagenesis methods being used in plant science in terms of impacted mutations. The FN mutagenesis usually creates deletions from a few bases to several million bases (Mb). A library of random deletion generated using FN mutagenesis lines can provide indispensable resources for the reverse genetic approaches. In this review, information from several efforts made using FN mutagenesis has been compiled to understand the type of induced mutations, frequency, and genetic stability. Concerns regarding the utilization of FN mutagenesis technique for a plant with different level of ploidy and genome complexity are discussed. We have highlighted the utility of next-generation sequencing techniques which can be efficiently utilized for the characterization of mutant lines as well as for the mapping of causal mutations. Pros and cons of Mut-map, MutChromSeq, exon capture, whole genome sequencing, MutRen-Seq, and different tilling approaches can be used for the detection of FN-induced mutation has also been discussed. Genomic resources developed using the FN mutagenesis have been catalogued wooing to meaningful utilization of the available resources. The information provided here will be helpful for the efficient exploration for the crop improvement programs and for better understanding of genetic regulations.

Objective: to evaluate the effects of excitatory repetitive transcranial magnetic stimulation (rTMS) of the international 10-20 system P3 point (intraparietal sulcus region) in chronic patients with a frontal lesion and parietal sparing due to stroke on the impaired upper (UL) and lower limb (LL) as measured by Fugl-Meyer Assessment (FMA). Methods: three patients (C1: 49.83/2.75, C2: 53.17/3.83, C3: 63.33/3.08 years-old at stroke/ years post-stroke, respectively) received two weeks (five days/ week) of rTMS at 10 Hz of P3. A patient was treated in similar conditions with a sham coil (S1: 56.58/4.33). No complimentary therapy was delivered during the study. Patients were evaluated before, after- and two months post-treatment (A1, A2 and A3, respectively). Results: we found increased scores for LL in motor function subsection for C1 and C3 and in sensory function for C2 by A2 that remained at A3. We also found an increased score for UL motor function for C2 and C3, but the score decreased by A3 for C2. C3 score for UL range of motion increased by A3 compared to A1 and A2. Conclusion: In a variable way, P3 excitatory rTMS increased FMA scores in different upper and lower limb subsections of our three treated patients.

Through a partnership with three Federally Qualified Health Centers (FQHCs), the local health department in Los Angeles County implemented a produce prescription program (PPR) to increase fresh fruit and vegetable purchases among patients with diabetes or prediabetes. The PPR, which began in 2020, provided eligible patients with a $40 voucher every month for 6 months to promote the purchase of fresh produce at large chain grocery stores. This qualitative assessment describes staff experiences with the PPR, documenting the facilitators and barriers they encountered while implementing the program. Fifteen clinic staff (i.e., PPR implementers) were interviewed for this assessment. Thematic analysis and coding were conducted using the ATLAS.ti software; the coding was carried out by two separate coders. Interviewees discussed the importance of having preexisting partnerships and programs to support the PPR at their clinic site. Hidden costs related to implementing the program included a large and unexpected amount of staff time devoted to enrolling patients into the program. Collecting quality data and having limited expertise to rigorously evaluate the program were other challenges. Because patients often share their food with their family, the monthly $40 incentive was generally not enough to support their needs; interviewees suggested giving a higher inventive amount to those with a larger household. Future PPR efforts and similar food incentive programs should consider these and other facilitators and barriers to implementation and sustainability, especially when making adjustments to these programs to improve services and access to food resources.

The performance of laser beams in tracking Lissajous scan trajectories is severely limited by beam jitter. To enhance the performance of fast steering mirror (FSM) control in tracking Lissajous scan trajectories, this paper proposed a fractional order active disturbance rejection controller (FOADRC) and verified its effectiveness in improving system scanning tracking accuracy. A dynamic mathematical model of fast steering mirror was studied and the design of parameters for the control mode of the closed-loop system was determined. A reduced order linear active disturbance rejection controller suitable for FSM systems was designed and the corresponding fractional order proportional differentiation (FOPD) controller were determined according to the mathematical model. The use of the designed controller enabled high-performance tracking of high-frequency Lissajous scanning curves (X-axis 500 Hz, Y-axis 350 Hz) and met the need for high-frequency repetitive scanning. The controller has the characteristics of simple implementation and low computational complexity and is suitable for closed-loop control applications in engineering.

The rapid development of electric vehicles, unmanned aerial vehicles, and wearable electronic devices has led to a high interest in research related to the synthesis of graphene with a high specific surface area for energy applications. However, the problem of graphene synthesis scalability, as well as the lengthy duration and high energy intensity of the activation processes of carbon materials, are significant disadvantages. In this study, a reactor was developed for the green, simple, and scalable electrochemical synthesis of graphene oxide with a low oxygen content of 14.1 %. The resulting material was activated using a fast joule heating method. The processing of mildly oxidized graphene with a high–energy short electrical pulse (32 ms) made it possible to obtain a graphene–based porous carbon material with a specific surface area of up to 1984.5 m2/g. The low energy intensity, simplicity, and use of environmentally friendly chemicals render the proposed method scalable.

Proper species identification from ancient DNA samples is a difficult task that sheds light on the evolutionary history of pathogenic microorganisms. The field of palaeomicrobiology has undoubtedly benefited from the advent of untargeted metagenomic approaches that use next-generation sequencing methodologies. Nevertheless, assigning ancient DNA at the species level is a challenging process. Recently, the gut microbiome analysis of three pre-Columbian Andean mummies [1](Santiago-Rodriguez et al. 2016) has called into question the identification of Leishmania in South America. Here, the metagenomic data filed in MG-RAST (Metagenomics RAST server) were used for a further attempt to identify members of the Trypanosomatidae family infecting these ancient remains. For this purpose, we used two metagenomic analysis tools. In the first step, data were analysed using the ultrafast metagenomic sequence classifier, based on exact alignment of k-mers (Kraken). In the second step, we used Bowtie2, an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. We then compared the output results. These approaches highlight some interesting findings on potential infections by human pathogenic trypanosomatids in these three pre-Columbian mummies.

Bayesian formulations of learning imply that whenever the evidence for a correlation between events in an animal’s habitat is sufficient, the correlation is learned. This implies that regularities can be learnt rapidly, from small numbers of learning examples. This speed of learning gives maximum possible fitness, and no faster learning is possible. There is evidence in many domains that animals and people can learn at nearly Bayesian optimal speeds. These domains include associative conditioning, and the more complex domains of navigation and language. There are computational models of learning which learn at near-Bayesian speeds in complex domains, and which can scale well – to learn thousands of pieces of knowledge (i.e., relations and associations). These are not neural net models. They can be defined in computational terms, as algorithms and data structures at David Marr’s [1] Level Two. Their key data structures are composite feature structures, which are graphs of multiple linked nodes. This leads to the hypothesis that animal learning results not from deep neural nets (which typically require thousands of training exam-ples), but from neural implementations of the Level Two models of fast learning; and that neu-rons provide the facilities needed to implement those models at Marr’s Level Three. The required facilities include feature structures, dynamic binding, one-shot memory for many feature struc-tures, pattern-based associative retrieval, unification and generalization of feature structures. These may be supported by multiplexing of data and metadata in the same neural fibres.

There is a systematic exclusion of gender-based violence, safe abortion, reproductive cancers, infertility services, comprehensive sexuality education, sexuality services, and STI’s other than HIV in essential health packages in LMICs. To accelerate progress on sexual reproductive health (SRH), the Guttmacher–Lancet Commission proposed the adoption of these interventions into an essential health package of SRH services that should be universally available. In this commentary, we use a healthcare priority-setting processes lens to review the importance of these services for universal health coverage. We isolate inherent challenges in social value judgments for terminal, process and content evidence for their healthcare priority-setting. We then advance promising emerging practical examples from low to middle-income countries on evidence-informed decision-making processes. We recommend capacity development through regional support, generating equity and efficiency evidence and strengthening political and publicly acceptable processes to institutionalise and operationalise evidence-informed decision-making.

One of the frequently used classes of the sparse reconstruction algorithms is based on the iterative shrinkage/thresholding procedure, where the thresholding parameter controls a trade-off between the algorithm accuracy and the execution time. In order to avoid this trade-off, we propose using a fast intersection of confidence interval method in order to adaptively control the threshold value through the reconstruction algorithm iterations. We have upgraded the two-step iterative shrinkage thresholding algorithm with a such procedure, improving its performance. The proposed algorithm, denoted as the FICI-TwIST, along with a few selected state-of-the-art sparse reconstruction algorithms have been tested on the classical problem of image recovery by emphasizing the image sparsity in the discrete cosine and the discrete wavelet domain. Furthermore, we have derived a single wavelet transformation matrix which avoids wrapping effects achieving significantly faster execution times when compared to more traditional function based transformation. The obtained results indicate competitive performance of the proposed algorithm, even in cases where all algorithm parameters have been individually fine-tuned for best performances.

Yaw misalignment can make a wake steer, which is an effective method to increase the power of wind farms, but it also increases the fatigue load of the turbines. In this paper, the method of combining yaw misalignment and pitch control (CYMP) is proposed to investigate the potential to mitigate wake interference, the wind velocity distribution and turbulence distribution in the wake, as well as the power and load changes of the wind turbine are studied, focusing on power in-crement and fatigue damage reduction. Although some studies have found that the method of CYMP are beneficial to increase power generation and reduce fatigue loads, there are no papers that have made a detailed analysis of the effects of wake turbulence, wind speed distribution, power, especially fatigue damage under this control. Simulation tool FAST.Farm is used to model and analyze wind farms, obtain the variation details of wake and provide simulation data for calculating power and fatigue load. The pitch control brings bias to the CYMP optimization results was neglected, the case studies show that the method of CYMP can reduce the fatigue load by 10.29% and increase the total power by 1.7% compared with only wake steering. The Model Predictive Control collaborative method based on CYMP is proposed, which can increase power by more than 2% and reduce thrust by more than 4% under 10m/s turbulent wind.

In today’s world face detection is the most important task. Due to the chromosomes disorder sometimes a human face suffers from different abnormalities. For example, one eye is bigger than the other, cliff face, different chin-length, variation of nose length, length or width of lips are different, etc. For computer vision currently this is a challenging task to detect normal and abnormal face and facial parts from an input image. In this research paper a method is proposed that can detect normal or abnormal faces from a frontal input image. This method used Fast Fourier Transformation (FFT) and Discrete Cosine Transformation of frequency domain and spatial domain analysis to detect those faces.

The diagnosis of Cardio-Vascular diseases (CVD) is highly dependent on analysis of ECG signals. ECG analysis can be helpful in estimating the underlying cause and condition of heart in cardiac abnormality. The effectiveness of ECG signal analysis in detection of CVDs is widely accepted by professional healthcare service provider. Many algorithms have been proposed but almost all of them have some kind of limitations, and these limitations largely influence the effectiveness of ECG analysis. The performed research work is dedicated for design of unique self-organizing maps (SOMs) based neural network for classification of arrhythmia according to a particular ECG signal, the generation of SOMs is based on the certain unique signatures of ECG signals and have potential to classify different cardiac conditions. For extraction of unique features from ECG signals, we have proposed to use Fast Discrete Stockwell Transform (FDST). Since the proposed technique is a result of combining two different techniques hence called as hybrid technology. The purpose of using FDST is to identify unique signatures of ECG signals in a more improved manner than existing one, the term improved is used because it has several advantages over existing techniques such as wavelet and Fourier Transform based methods. Results obtained from the implementation of the technique are capable in visualizing the ECG sinus rhythm and arrhythmia conditions in form of unique SOM for each associated arrhythmia condition. This unique SOM based classification makes them ideal for being used as a diagnostic tool. This ability of arrhythmia classification using FDST and SOMs makes the technique unique and useful providing valuable information about patient condition. Using proposed technology a portable diagnosis tool for monitoring of patient at their site may be facilitated later, that will improve the quality of life of the patient by diagnosing cardiac condition.

Compared with the traditional slow charging loads, random integration of large scale fast charging loads will exert more serious impacts on the security of power network operation. Besides, to maximize social benefits, effective scheduling strategy guiding fast charging behaviors should be formulated rather than simply increasing infrastructure construction investments on the power grid. This paper has analyzed the charging users’ various responses to the elastic charging service fee, introduced the index of charging balance degree to a target region by considering the influence of fast charging loads on power grid. Then, a multi-objective optimization model of the fast charging service fee is constructed, whose service fee can be further optimized by employing fuzzy programming method. Therefore, both users’ satisfaction degree and the equilibrium of charging loads can be maintained simultaneously by guiding EVs to different fast charging stations reasonably. The simulation results demonstrate the effectiveness of proposed dynamic charging service pricing and the proposed fast charging load guidance strategy.

This study presents an effective control algorithm to improve the robustness of fast steering mirror (FSM)-based laser beam steering systems against dynamic disturbances such as repetitive disturbances resulting from operating conditions. A stable control system must be able to maintain the required high-precision control even when dynamic disturbances affect the FSM system. In this study, an improved control method is proposed using an internal model principle (IMP)-based nonlinear controller with a disturbance observer (DOB) for the FSM system. This IMP-based controller with DOB can attenuate the residual control error signal under dynamic disturbance conditions.

Fast Field-Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometry is a powerful non-destructive magnetic resonance technique that enables, among other things, the investigation of slow molecular dynamics at low magnetic field intensities. FFC-NMR relaxometry measurements provide insight into molecular motion across various timescales within a single experiment. This study focuses on a \textit{model-free} approach, representing the NMRD profile $R_1$ as a linear combination of Lorentzian functions, thereby addressing the challenges of fitting data within an ill-conditioned linear least-squares framework. Tackling this problem, we present a comprehensive review and experimental validation of three regularization approaches to implement the model-free approach to analysing NMRD profiles. These include: (1) \nameUpe, utilizing locally adapted $L_2$ regularization; (2) \nameL, based on $L_1$ penalties; and (3) a hybrid approach combining locally adapted $L_2$ and global $L_1$ penalties. Each method's regularization parameters are determined automatically, according to the Balancing and Uniform Penalty principles. % Our contributions include the implementation and experimental validation of the \nameUpe{} and \nameUp{} algorithms, and the development of a "dispersion analysis" technique to assess the existence range of the estimated parameters. The objective of this work is to delineate the variance in fit quality and correlation time distribution yielded by each algorithm, thus broadening the set of software tools for the analysis of sample structures in FFC-NMR studies. The findings underline the efficacy and applicability of these algorithms in the analysis of NMRD profiles from samples representing different potential scenarios. 1

1,3,5-Tris-(α-naphthyl)benzene is an organic non-electrolyte with notable stability of an amorphous phase. Its glassy and supercooled liquid states were previously studied by spectroscopic and calorimetric methods. However, the thermodynamic parameters of phase transitions available from the literature are inconsistent. In this work, the heat capacities of crystalline and liquid phases, the temperature dependence of the saturated vapor pressures, fusion and vaporization enthalpies were determined using differential and fast scanning calorimetry and verified using the estimates based on solution calorimetry. The structural features of 1,3,5-tris-(α-naphthyl)benzene are discussed based on the computations performed and the data on the molecular refractivity. The consistency between the values obtained by independent techniques was demonstrated. The deviations in the previously published data were attributed to possible polymorphism.

Examining the similarity of event environments or surroundings, more precisely settings, provides additional insight in analyzing event sequences as it provides information about the context and potential common factors that may have influenced them. This article proposes a new similarity measure for event setting sequences, which involve the space and time in which events occur. While similarity measures for spatiotemporal event sequences have been studied, the settings and setting sequences have not yet been studied. While modeling event setting sequences we consider spatial and temporal scales to define the bounds of the setting and incorporates dynamic variables alongside static variables. Using a matrix-based representation and an extended Jaccard index we developed new similarity measures that allow for the use of all variable data types. We successfully used these similarity measures coupled with other multivariate statistical analysis approaches in a case study involving setting sequences and pollution event sequences associated with the same monitoring stations, which validate the hypothesis that more similar spatial-temporal settings or setting sequences may generate more similar events or event sequences. In conclusion, these similarity measures have many potential real-world applications, and offer researchers a powerful tool for understanding different factors and their dynamics corresponding to occurrences of spatiotemporal event sequences.

Growing evidence suggests that healthcare provider advice may increase tobacco cessation, reduce alcohol use, and improve the adoption of desirable lifestyle behaviors among patients. However, how brief interventions and other provider-patient interactions can shape cumulative adoption of multiple modifiable behaviors is less well studied for diabetes prevention and control. Using weighted internet panel survey data from a large socio-demographically diverse urban population in the United States (n=1,003), the present study describes differences in group characteristics among those who had been “ever diagnosed” with prediabetes/diabetes versus those who had not. It also examines the associations between the cumulative adoption of lifestyle behaviors and each of the following: a) lifetime prediabetes/diabetes diagnosis; b) brief lifestyle intervention exposure (i.e., received provider advice/encouragement); and c) recent provider-patient communication about diabetes. There were several group differences in “ever diagnosed” prediabetes/diabetes status by age, employment status, health status, nutrition knowledge, blood pressure/hypertension diagnosis, and diabetes-related health behaviors (p<0.05). Each of the three provider-patient interactions of interest were positively associated with a higher cumulative sum of adopted modifiable lifestyle behaviors for diabetes prevention and management. Results suggest that provider advice/provider-patient interactions of any type can have a salutary impact on whether individuals with prediabetes or type 2 diabetes will engage in recommended lifestyle behavior modifications.

The aim of this study is to solve the problems of complicated pretreatment and high analytical cost in the detection technology of trace drug toxicants in municipal wastewater. A high-performance magnetic sorbent was synthesized for enrichment of trace drug substances in wastewater to develop magnetic solid-phase extraction pretreatment combined with the acoustic ejection mass spectrometry (AEMS) analytical methods for the molecules in wastewater drug toxicants. The magnetic nanospheres was successfully prepared by magnetic nanoparticles modified with divinylbenzene and vinyl pyrrolidone.The results showed that the linear dynamic range of 17 drugs was 1-500 ng/L, the recovery was 43%-105%, the matrix effect was more than 67%, the limit of quantitative detection was 1-2 ng/L, and the detection time of each sample was 2.98s. It can be seen that the developed magnetic solid-phase extraction (MSPE) method is a good solution to the problem of complicated pre-treatment and analytical cost in the detection of drugs in wastewater. The developed magnetic material and acoustic excitation coupled mass spectrometry analysis method can realize the low-cost, efficient enrichment and fast analysis of different kinds of drug molecules in urban sewage.

The study of coordination practices in health policy and, especially in emergency situations is a central aspect. The COVID-19 pandemic has highlighted the need for further research on such practices, especially those that are deployed in complex and unforeseen situations to respond quickly while minimising errors. These dialogic coordination practices (DP) have been identified through case studies but have not been validated. The purpose of this study is to develop and validate a DP questionnaire for healthcare teams. The development of the items was based on a literature review and the content validation was carried out by means of a Delphi study. A total of 10 experts assessed the clarity and appropriateness of the items and their corresponding measurement scales. Consensus was reached after the second round, with a percentage of agreement greater than or equal to 90% for all items. The validation of these items constitutes a methodological innovation that responds to the call in the literature to open up new avenues for comparative studies, the possibility of generalising the findings obtained and the possibility of bringing together different approaches to the problem of coordination, key in health policy.

Plasmonic nanocomposites have the ability to enhance light-matter interaction due to the plasmonic effects leading to promising potential applications. In this paper, we theoretically study the group index of the silver nanoparticle-gold nanoparticle-quantum dot plasmonic hybrid system in the optical region of the electromagnetic spectrum using the density matrix approach. The quantum dot is considered to be a three-level atomic system of a lambda configuration, interacting with strong control and weak probe fields. We find that the plasmonic hybrid system exhibits at near resonance a strong switching between slow and fast light, which can be controlled by the inclination angle of the gold nanoparticle and the size of the metals nanoparticles, in addition to the strength and detuning of the control field. Thus, the silver nanoparticle-gold nanoparticle-quantum dot could potentially be used in optoelectronic devices.

Fault detection at the early stage of development is of great importance in the maintenance of electric motors. In this regard, Motor Current Signature Analysis (MCSA) is cited in many articles to detect rotor bar fracture. The popularity of MCSA is due to its non-invasive and non-destructive nature, simplicity, and, compatibility with several signal processing tools. The vast variety of the signal processing tools which are commonly used for detecting the broken rotor bar fault is based on the Fast Fourier Transform (FFT) of the stator current signal and analysis of the produced Fourier spectrum; however, because of the small amplitude at the fault frequency relative to the main frequency amplitude, the former cannot be easily discriminated from the latter. Therefore, the peak at the fault frequency is hidden in the shadow of the main frequency component, hence the fault will not be detectable. As a solution to vanish the base frequency component, a method based on the Algebraic Identity of trinomial expansion is proposed in this paper which enables us to display the difference between the frequency of the fault signature and the base frequency. In this article, the fault of the broken rotor bars of the squirrel cage induction motor is revealed by the proposed method. In addition, a frequency weighting technique is presented to magnify the component at the fault related frequency compared to the lower frequencies. To validate the proposed methods, they are examined on the laboratory data obtained from three different operating conditions including the direct online start, the direct torque control, and the scalar control and the results show the ability of the proposed methods in fault detection of an induction motor.

Solar power innately has issues with weather, grid demand and time of day, which for the case of concentrating solar power (CSP) can be mitigated through use of thermal energy storage. Nuclear reactors, including lead-cooled fast reactors (LFRs), can load follow, but have high fixed and low operating costs which can make this economically unattractive. We investigate potential synergies through coupling CSP and LFR together in a single supercritical CO$_2$ Brayton cycle and/or using the same thermal energy storage. Combining these cycles allows for the LFR to thermally charge the salt storage in the CSP cycle during low demand periods to be dispatched when grid demand increases. The LFR/CSP coupling into one cycle is modeled to find the preferred location of the LFR heat exchanger, CSP heat exchanger, sCO$_2$-to-salt heat exchanger (C2S), turbines, and recuperators within the supercritical CO$_2$ Brayton cycle. Three cycle configurations have been studied: two-cycle configuration, which uses CSP and LFR heat for dedicated turbocompressors, has the highest efficiencies but with less component synergies; a combined cycle with CSP and LFR heat sources in parallel is the simplest with the lowest efficiencies; and a combined cycle with separate high temperature recuperators for both the CSP and LFR is a compromise between efficiency and component synergies. Additionally, four thermal energy storage charging techniques are studied: the turbine positioned before C2S, requiring a high LFR outlet temperature for viability; the turbine after the C2S, reducing turbine inlet temperature and therefore power; the turbine parallel to the C2S producing moderate efficiency; and a dedicated circulator loop. While all configurations have pros and cons, use of a single cycle offers component synergies with limited efficiency penalty. Using a turbine in parallel with the C2S heat exchanger is feasible but results in a low charging efficiency, while a dedicated circulator loop offers flexibility and near perfect heat storage efficiency but increasing cost with additional cycle components.

A time-sequential working, spatially multiplexed autostereoscopic 3D display design consisting of a fast switchable RGB-color filter array is presented. The wavelength-selective filter barrier emits the light from a display over a larger active area than common autostereoscopic barrier displays. An optical modelling of wavelength-selective barriers has been used for instance to calculate the light ray distribution properties of that arrangement. To find well working display designs, automated searches by simulation and computational evaluation has been proceeded. Wavelength-selective filter barrier arrangements exhibit characteristics different from common barrier displays with similar barrier pitch and ascent. In particular, these constructions show strong angular luminance dependency under barrier inclination specified by correspondent slant angle. In time-sequential implementation it is important to avoid that quick eye or eyelid movement lead to visible color artifacts. In the millisecond regime tunable liquid crystal Fabry-Pérot color filters for the colors red, green and blue are presented. They consist of a sub-micrometer thick nematic layer sandwiched between dielectric mirrors and ITO-electrodes. These cells shall switch narrow-banding light of red, green or blue. An array for a glasses-free 3D display has to be equipped with several thousand switchable filter elements having different color apertures. The newly introduced design is usable as a multi user display as well as a single user system with user adaptive control.

We describe a vision for a national-scale heavy mineral (HM) map generated through automated mineralogical identification and quantification of HMs contained in floodplain sediments from large catchments covering most of Australia. The composition of the sediments reflects the dominant rock types in each catchment, with the generally resistant HMs largely preserving the mineralogical fingerprint of their host protoliths through the weathering-transport-deposition cycle. Heavy mineral presence/absence, absolute and relative abundance, and co-occurrence are metrics useful to map, discover and interpret catchment lithotype(s), geodynamic setting, magmatism, metamorphic grade, alteration or mineralization. Underpinning this vision is a pilot project, focusing on a subset of the national sediment sample archive, which is used to demonstrate the feasibility of the larger, national-scale project. We preview a bespoke, cloud-based mineral network analysis (MNA) tool to visualize, explore and discover relationships between HMs as well as between them and geological setting or mineral deposits. We envisage that the Heavy Mineral Map of Australia and MNA tool will contribute significantly to mineral prospectivity analysis and modeling here, particularly for technology critical elements and their host minerals, which are central to the global economy transitioning to a more sustainable, decarbonized paradigm.

Recognition, decoding and tracking of vortex patterns is of increasing importance in many fields reaching from astronomical observation of distant galaxies to turbulence phenomena in liquids or gases. Currently, coherent light beams with orbital angular momentum (OAM) are of particular interest for optical communication, metrology, micro-machining or particle manipulation. One common task is to identify characteristic spiral patterns in pixelated intensity maps at real-world signal-to-noise ratios. Recently, Fast Fourier Transform (FFT) was applied to the quantitative analysis of spiral interference patterns of OAM beams. Our study considers this approach in more detail. It is demonstrated that specific information can be extracted by combining conformal mapping by polar transform with determining one- or two-dimensional angular frequency spectra either in spatially fixed or scanning mode. Results of proof-of-principle experiments are presented.

The structure of existing activated models is inherently deficient in reflecting the major role of the membrane filtration. This study developed and proposed a novel model, MASM, for the membrane activated process. The effective filtration size imposed by the membrane module, entrapping larger size particles was adopted as the basis of the proposed model. The model defined a modified COD fractionation, accounting for the captured COD fractions as additional model components and utilizing related mass balance relationships. It was implemented for testing the fate of soluble hydrolysable COD and system performance of super-fast membrane activated sludge based on real data for the characterization and process kinetics of domestic sewage and denim processing effluents. Model evaluation was carried for parallel systems with gravity settling and membrane filtration operated at a sludge age range of 0.5-2.0 d. Results reflected significantly better performance of super-fast membrane activated sludge system for both wastewaters, underlining that it was crucially important to account for the captured COD fractions to provide an accurate evaluation of system behavior and effluent quality. This should also be identified as the major shortcoming of the ASM models for evaluating and predicting system performance of activated sludge configurations with membrane separation.

The new observations, including the fastest star, the circular velocity curve of the Milky Way and the fast galaxy bar, should imply that the mass of the center of the Milky Way is almost 10¹¹ times the mass of the Sun.

Rapid and extensive urbanization has adversely impacted humans and ecological entities in the recent decades through a decrease in surface permeability and the emergence of urban heat islands (UHI). While detailed and continuous assessments of surface permeability and UHI are crucial for urban planning and management of landuse zones, they have mostly involved time consuming and expensive field studies, and single sensor derived large scale aerial and satellite imageries. We demonstrated the advantage of fusing imageries from multiple sensors for landuse and landcover (LULC) change assessments as well as for assessing surface permeability and UHI emergence in Tirunelveli, Tamilnadu, India. Cartosat-2 and Landsat-7 ETM+ imageries from 2007 and 2017 were fused and classified using a Rotation Forest (RF), while surface permeability and temperature were quantified using Soil-Adjusted Vegetation Index (SAVI) and Land Surface Temperature (LST) index, respectively. Fused images exhibited higher classification accuracies than non-fused images, i.e. overall kappa coefficient values 0.83 and 0.75, respectively. We observed an overall increase of 20 km2 (45%) in the coverage of urban (dry, real estate plots and built-up) areas, while a decrease of 27 km2 (37%) for vegetated (cropland and forest) areas in Tirunelveli between 2007 and 2017. The SAVI values indicated an extensive decrease in surface permeability for Tirunelveli overall (0.4) and also for almost all LULC zones. The LST values exhibited an associated overall increase (1.30C) of surface temperature in Tirunelveli with the highest increase (2.40C) for urban built-up areas between 2007 and 2017. The SAVI-LST combined metric depicted the Southeastern built-up areas in Tirunelveli as a potential UHI hotspot, while a caution for the Western riparian zone for UHI emergence in 2017. Our results provide important metrics for surface permeability and UHI monitoring, and inform urban and zonal planning authorities about the advantages of satellite image fusion.

The core motivation for this study emanates from Voronin S.'s seminal work on the universality of the zeta function. This universality positions the zeta function as a pivotal element in the conceptual framework of global artificial intelligence, suggesting its potential as a foundational component. A critical barrier to harnessing this promising universality has been the absence of efficient algorithms capable of actualizing this concept.