In order to reduce the influence of ground vibration generated by tractor during driving and operation on driving stability and driver ride comfort, this paper proposes a control method of tractor active seat suspension based on model predictive control. By establishing a 3-degree of freedom tractor active seat suspension model and a ground excitation input model, a new model predictive controller for the active seat suspension system is designed. The vertical acceleration of the seat center of mass, the seat suspension stroke and the tire dynamic displacement are optimized by limiting the dynamic deflection of the seat suspension and the active force output of the actuator. The control model of MPC tractor active seat suspension system is built and its performance is simulated and verified. The results show that compared with the passive seat suspension and the PID seat suspension, the tractor active seat suspension based on model predictive control (MPC) has better damping characteristics and improves ride comfort.

In order to coordinate the damping performance and energy regenerative performance of energy regenerative suspension, this paper proposes a structure of vehicle semi-active energy regenerative suspension with electro-hydraulic actuator (EHA). In light of the proposed concept, a specific energy regenerative scheme is designed and the mechanical properties test is carried out. Based on the test results, the parameter identification for the system model is conducted using recursive least squares algorithm. On the basis of system principle, the nonlinear model of the semi-active energy regenerative suspension with EHA is built. Meanwhile, LQG control strategy of the system is designed. And then the influence of the main parameters of EHA on the damping performance and energy regenerative performance of suspension is analyzed. Finally, the main parameters of EHA actuator are optimized via genetic algorithm. The test results show that when sinusoidal is input at the frequency of 2Hz and the amplitude of 30mm, the spring mass acceleration RMS value of optimized EHA semi-active energy regenerative suspension is reduced by 22.23% and energy regenerative power RMS value is increased by 40.51%, which means while meeting the requirements of certain vehicle ride comfort and driving safety, energy regenerative performance is improved significantly.

The semi-active cab suspension system for trucks is gaining increasing importance due to its economic advantages, low energy consumption, and significant enhancement of ride comfort. This paper investigates the effects of three control methods on improving ride comfort of semi-active cab suspension systems under random and bump road conditions: Proportional-Integral-Derivative (PID) control, fuzzy PID control, and Model Predictive Control (MPC). Initially, an accurate multi-degree-of-freedom truck cab suspension model was developed and validated through actual road tests. Based on this model, three control strategies were designed and implemented. Finally, the effectiveness of each control strategy was evaluated under various road conditions, including random and bump road scenarios. The results demonstrate that these control strategies can effectively reduce vibrations and impacts, significantly enhancing ride comfort, which is crucial for reducing driver fatigue and improving driving safety.

Due to the nonlinear stiffness and fractional-order damping characteristics of some real suspension systems, coupled with the presence of viscoelastic materials, fractional-order nonlinear suspension system modeling has become a focus of research in recent years. In this study, an electric oil and gas actuator based on fractional-order PID position feedback control is proposed, through which the damping coefficient of the suspension system is adjusted to realize the active control of the suspension. A fractional order PID algorithm is used to control the motor's rotational angle to realize the damping adjustment of the suspension system. In this process, the road roughness is collected by the sensors as the criterion of damping adjustment, and the particle swarm algorithm is utilized to find the optimal objective function under different road surface slopes, to obtain the optimal cornering value. According to the mathematical and physical model of the suspension system, the simulation model and the corresponding test platform of this type of suspension system are built. The simulation and experimental results show that the simulation results of the fractional-order nonlinear suspension model are closer to the actual experimental values than those of the traditional linear suspension model, and the accuracy of each performance index is improved by more than 18.5%. The designed active suspension system optimizes the body acceleration, suspension dynamic deflection, and tire dynamic load to 89.8%, 56.7%, and 73.4% of the passive suspension, respectively. Notably, the designed fractional order PID control circuit for the motor shows better control results compared to the conventional PID control circuit. This study provides an effective theoretical and empirical basis for the control and optimization of fractional-order nonlinear suspension systems.

Reusing the tactile knowledge of some previously explored objects helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT), and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10% when it used only one training sample plus the feature observations of prior objects. By incorporating the auxiliary features, the transfer learning improved the discrimination accuracy by over 20%. The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer).

In this paper, the Phase-Scheduled-Command FXLMS algorithm with the phase error between the disturbance and command signal is analyzed in detail. The influence of the phase error on the convergence time constant, convergence rate, and performance of convergence is explained for both stationary and nonstationary disturbance signals case. For stationary disturbance, the phase error slightly increases the convergence rate but heavily increases the distance of the optimum vector from the initial value, leading to poor convergence time constant performance. For nonstationary disturbance, the existence of phase error leads to poor convergence performance in every step, resulting in poor sound profiling performance. And the estimation of the phase error influence is developed in the closed form. Simulations are performed to demonstrate the validity of the analysis results.

Kamchatka berries (Lonicera caerulea L.) are known for their high content of phenolic compounds or vitamins, which is reflected in their antibacterial, detoxifying and anti-inflammatory properties. They are used in the production of jams, juices, wines and as natural dye. A bioferment was prepared from the pomace of the Kamchatka berry varieties Aurora and Indigo Gem and the strains Saccharomyces cerevisiae and Lacticaseibacillus paracasei, which was used to prepare a cosmetic preparation with a concentration of 5% in accordance with the guidelines of the COSMOS certification body. Conducted physico-chemical and organoleptic analyses and bioactive profile characterisation (UHPLC-DAD and UHPLC-ESI-MS/MS). The results showed that the presence of caffeic acid 4.47 ± 0.07 mg/100g was detected after fermentation of Kamchatka berry pomace. Vitamin C content increased by 141% after fermentation of Kamchatka berry pomace. The results of stability tests showed that in the process of physicochemical analysis of cosmetic preparation with bioferment of Kamchatka berry pomace the pH should oscillate in the range of 4.38-4.76 ± 0.01. Stability tests showed that the cosmetic should be protected from high temperatures and UV radiation and proved that the product is stable under changing conditions, resulting in lower transport and storage costs.

Grid energy storage system for PV Applications is connected with three different power sources i.e. PV Array, Battery and the Grid. It is advisable to have Isolation between these three different sources to provide safety for the equipment. The configuration proposed in this paper provides the complete isolation between the three sources. A Power Balancing Control (PBC) for this configuration is proposed to operate the system in three different modes of operation. Control of a dual active bridge (DAB) based battery charger which provides a galvanic isolation between batteries and other sources is explained briefly. Various modes of operation of a Grid energy storage system are also presented in this paper. Hardware-In-Loop (HIL) Simulation is carried out to check the performance of the system and the PBC algorithm. Power circuit (comprises of inverter, dual active bridge based battery charger, grid, PV cell, batteries, contactors and switches) is simulated and the controller hardware and user interface panel are connected as HIL with the simulated power circuit through Real Time Digital Simulator (RTDS). HIL simulation results are presented to explain the control operation, steady state performance in different modes of operation and the dynamic response of the system.

Self-esteem, the evaluation of one's own worth or value, is a critical aspect of psychological well-being and mental health. In this paper, we propose an active inference account of self-esteem, casting it as a sociometer, or an inferential capacity to interpret one's standing within a social group. This approach allows us to explore the interaction between an individual's self-perception and the expectations of their social environment.When there's a mismatch between these perceptions and expectations, the individual needs to adjust their actions or update their self-perception to better align with their current experiences. We also consider this hypothesis in relation to recent research on affective inference, suggesting that self-esteem enables the individual to track and respond to this discrepancy through affective states such as anxiety or positive affect. By acting as an inferential sociometer, self-esteem allows individuals to navigate and adapt to their social environment, ultimately impacting their psychological well-being and mental health.

A systematic investigation of the dynamic clustering behavior of active particles under confinement, including the effects of both particle density and active driving force is presented based on a hybrid coarse-grained molecular dynamics simulation. First, a series of scaling laws were derived with power relationships for the dynamic clustering time as a function of both particle density and active driving force. Notably, the average number of clusters N ̅ assembled from active particles in the simulation system exhibits a scaling relationship with clustering time t described by N ̅∝t^(-m). Simultaneously, the scaling behavior of the average cluster size S ̅ is characterized by S ̅∝t^m. Our findings reveals the presence of up to four distinct dynamic regions concerning clustering over time, with transitions contingent upon the particle density within the system. Furthermore, as the active driving force increases, the aggregation behavior also accelerates, while an increase in density of active particles induce alterations in the dynamic procession of the system.

Some key issues in AGN and galaxy formation are discussed. Very successful Unified Models explain much of the variety of AGN with orientation effects; ingredients are shadowing by a dusty “torus" and relativistic beaming. A spinoff result is described which is important for the formation of massive elliptical galaxies. It’s the most spectacular and unequivocal AGN feedback phenomenon known. This is the so-called “alignment effect" in powerful radio galaxies at z > 1. One of them is a BAL radio galaxy! I explain a very robust derivation of the reddening law for nuclear dust, which reveals a dearth of small grains. Then the quasistatic thin accretion disk model, thought by many to explain the energetically dominant optical/UV continuum, is thoroughly debunked. Much of this was known when the model was proposed 35 years ago. A new argument is given that trivially falsifies a huge superset of such models. It’s possible to see the central engine spectrum with the atomic and dust emission surgically removed! Few noticed this breakthrough work. The far IR dust emission in Cygnus A is 10% polarized, and so far high nuclear dust polarization is seen in all radio loud objects, but no radio quiet ones.

Background: Active ageing is a multidimensional, relative, and context-dependent concept with different paths and outcomes. The purpose of this qualitative study was to explore personal active ageing strategies in a specific context. Method: Following a directed content analyze procedure, we conduct semi structured individual interview with 39 elder (men and women) between the ages of 60-97 years that selected with purposeful sampling .data collection and analysis were concurrent. We analyzed the data from interviews, written narratives, and field notes using directed content analyze. The Reliability of data was fulfilled in accordance Lincoln and Guba criteria. We stopped data collection when no new concept was added and data saturation occurred. Results: Based on the experience of elders, we identified 5 categories: 1) Preventive 2) Coping 3) Internal self-control 4) Coherence maintenance strategies 5) Opportunity exploiting strategies. These described the active ageing strategies when encountering with age related change. Utilizing these strategies, the elder accompanied the life time. Conclusion: The finding suggests that active ageing is a continuous process in confronting age related change. The identified strategies can help to promote active ageing by familiarizing older with opportunities of life and training them in how to use these strategies.

This paper sets out three visions for the year 2035 which bring about a radical change in the level of walking, cycling and public transport in Turkish urban areas. A participatory visioning technique was structured according to a three-stage technique: (i) Extensive online comprehensive survey. In which potential transport measures were researched for their relevance to promoting sustainable transport in future Turkish urban areas; (ii) Semi-structured interviews. Where transport strategy suggestions were developed in the context of the possible imaginary urban areas and their associated contextual description of the imaginary urban areas for each vision; (iii) Participatory workshops. Where an innovative method was developed to explore various creative future choices and alternatives. Overall, this paper indicates that the content of the visions was reasonable, but such visions need a considerable degree of consensus and radical approaches to tackling them.

In a recent paper, we calculate spectral energy distributions (SEDs) for 1425 Fermi blazars, classifications of low synchrotron peak sources (LSPs) if log $\nu_{\rm p} (\rm Hz) \leq $ 14.0, intermediate synchrotron peak sources (ISPs) if $14.0 < \,\log\, \nu_{\rm p} (\rm Hz) \leq 15.3 $, and high synchrotron peak sources (HSPs) if $ \log\, \nu_{\rm p} (\rm Hz) > 15.3$ are made based on 999 logarithms of synchrotron peak frequencies with known redshift, and we obtain an empirical relation to estimate the synchrotron peak frequency, $\nu_{\rm p}^{\rm Eq.}$ from effective spectral indexes $\alpha_{ox}\, {\rm and}\, \alpha_{ro}$ as $\log \nu_{\rm p}^{\rm Eq.} = 16+4.238X $ if $X < 0$, and $\log \nu_{\rm p}^{\rm Eq.} = 16+4.005Y $ if $X > 0$, where $X = 1.0 - 1.262 \alpha_{ro} - 0.623 \alpha_{ox}$, and $Y = 1.0 + 0.034 \alpha_{ro} - 0.978 \alpha_{ox}$ \cite{Fan16}. In the present work, we investigate the correlation between the peak frequency and the radio to X-ray spectral index, that between peak luminosity (integrated luminosity) and $\gamma$-ray/optical luminosity, and that between peak luminosity and integrated luminosity. Some discussions are presented.

Medical research has suggested that the anterior-posterior (AP)-diameter of the inferior vena cava (IVC) and its associated temporal variation as imaged by bedside ultrasound is useful in guiding fluid resuscitation of the critically-ill patients. This paper develops semi-automatic active ellipse and rectangle algorithms for measurement and tracking of the AP-diameter. The proposed algorithms are compared with an expert manual measurement and the previous work based on active circle model. It is shown that regardless of the shape of the IVC, the rectangle model always outperforms the two other models and performs very close to manual measurement.

Deep learning methods have been widely applied to time series classification tasks. Although deep learning methods perform excellently on these tasks, they require much training data. Labeling time series data for training is very time-consuming and labor-intensive. Active learning can be used to select the most informative data for labeling in time series classification tasks to save human labeling efforts. In this paper, we propose a new active learning (AL) framework for time series data. First, a temporal classifier for pixel-level temporal classification tasks is designed. Next, We propose an effective active learning method to select informative time series samples for labeling, which combines representativeness and uncertainty. For representativeness, We use the K-shape method to cluster time series data. For uncertainty, we construct an auxiliary deep network to evaluate the uncertainty of unlabeled data. The features of the middle hidden layer with rich temporal information of the classifier will be fed into the auxiliary deep network, which is equipped with a self-attention mechanism to utilize the temporal dependencies of time series data fully. Then, we define a new loss function with the aim of improving the deep model’s performance. Finally, the proposed method in this paper was evaluated on two temporal remote-sensing image datasets. The results demonstrate a significant advantage of our method over other approaches to time series data. Code is available at https://github.com/Fighting-Golion/time_series_active_learning

Energy from biogas is one of the most promising renewable energy sources. Significant, for technical, economic, and environmental reasons, is the construction of agricultural microgas plants next to households specialising in cattle rearing. The availability of free substrate makes it possible not only to produce one's electricity and heat but also to produce a more environmentally and human-friendly manure. The operation of biogas plants is, unfortunately, associated with technical problems. This paper presents the results of a study of the quality of electricity generated in an agricultural biogas plant built at a farm specialising in dairy cows, where the owner reported a problem with the voltage in the power supply network. Therefore, selected power quality parameters occurring at the connection point of the biogas plant were analysed in detail. As the authors' research showed, in the case in question, the agricultural biogas plant was connected via a cable with too small a conductor cross-section, which resulted in significant voltage exceedances, making it impossible to switch on the second of the biogas plant's generators. Replacement of the feed-in cable has enabled both generators to run, but significant fluctuations in the feed-in voltage values were still noticeable. Analysis of the subsequent measurements revealed the need for changes in the design of the digester itself. The proposal for change is to replace the two current digester mixers (each rated at 9 kW) with more mixers of lower power. The new mixers would operate in an alternating system, where only one would always be activated.

In this paper we explore the known connection among sustainability, resilience, and well-being within the framework of active inference. Initially, we revisit how the notions of well-being and resilience intersect within active inference before defining sustainability. We adopt a holistic concept of sustainability denoting the enduring capacity to meet needs over time without depleting crucial resources. It extends beyond material wealth to encompass community networks, labor, and knowledge. Using the Free Energy Principle, we can emphasize the role of fostering resource renewal, harmonious system-entity exchanges, and practices that encourage self-organization and resilience as pathways to achieving sustainability, both in an agent and in collectives. We start by connecting Active Inference with well-being, building on exsiting work. We then attempt to link resilience with sustainability, asserting that resilience alone is insufficient for sustainable outcomes. While crucial for absorbing shocks and stresses, resilience must be intrinsically linked with sustainability to ensure that adaptive capacities do not merely perpetuate existing vulnerabilities. Rather, it should facilitate transformative processes that address the root causes of unsustainability. Sustainability, therefore, must manifest across extended timescales and all system strata, from individual components to the broader system, to uphold ecological integrity, economic stability, and social well-being. We explain how sustainability manifests at the level of an agent, and then at the level of collectives and systems. To model and quantify the interdependencies between resources and their impact on overall system sustainability, we introduce the application of network theory and dynamical systems theory. We emphasize the optimization of precision or learning rates through the active inference framework, advocating for an approach that fosters the elastic and plastic resilience necessary for long-term sustainability and abundance.

Introduction: The Get Active Questionnaire (GAQ), developed by the Canadian Society for Ex-ercise Professionals (CSEP) was recently recommended for pre-participation screening for the general population in Singapore before increasing exercise levels. This review examines the evi-dence behind the GAQ and relevance to our tropical environment. Methods: Searches were done via Pubmed, MEDLINE and the Cochrane Central Register of Controlled Trials. Resources referenced by the CSEP were hand-searched. The CSEP was also contacted for further information. Evidence behind each GAQ question was compared to inter-national literature and guidelines, where applicable. Results: Out of 273 studies, 49 were suitable for analysis. Two GAQ studies commissioned by the CSEP showed a high negative predictive value but high false negative rate. Of the nine GAQ questions, those on dizziness, joint pains and chronic diseases appear justified. Those on heart disease/stroke, hypertension, breathlessness and concussion require modification. That on syncope can be amalgamated into the dizziness question. The remaining question may be deleted. No long-term studies were available to validate use of the GAQ. Heat disorders were not considered in the GAQ. Conclusions: Modification of the GAQ, including inclusion of environmental factors, may make it more suitable for the general population and should be considered.

In this paper, we unite concepts from Husserlian phenomenology, the active inference framework in theoretical biology, and category theory in mathematics to develop a comprehensive framework for understanding social action premised on shared goals. We begin with an overview of Husserlian phenomenology, focusing on aspects of inner time consciousness, namely, retention, primal impression, and protention. We then review active inference as a formal approach to modeling agent behavior, based on variational (approximate Bayesian) inference. Expanding upon Husserl’s model of time consciousness, we consider collective goal-directed behavior, emphasizing shared protentions among agents and their connection to the shared generative models of active inference. This integrated framework aims to formalize shared goals in terms of shared protentions, and to thereby shed light on the emergence of group intentionality. Building on this foundation, we incorporate mathematical tools from category theory; particularly, sheaf and topos theory, to furnish a mathematical image of individual and group interactions within a stochastic environment. Specifically, we employ morphisms between polynomial representations of individual agent models, allowing predictions not only of their own behaviors but also those of other agents and environmental responses. Sheaf and topos theory facilitate the construction of coherent agent worldviews and provides a way of representing consensus or shared understanding. We explore the emergence of shared protentions, bridging the phenomenology of temporal structure, multi-agent active inference systems, and category theory. Shared protentions are highlighted as pivotal for coordination and achieving common objectives. We conclude by acknowledging the intricacies stemming from stochastic systems and uncertainties in realizing shared goals.

Research and development on innovative packaging materials have advanced significantly to safeguard packaged food against microbial contamination and oxidation. To combat demanding issues, active packaging has evolved as a viable method for minimizing oxidation/microbial growth in packaged goods, extending their shelf life, and ensuring the consumer's safety. Active food packaging includes O2, CO2 scavengers, moisture absorbers, U.V. barriers, and carriers of antioxidant and antimicrobial agents. Various antimicrobial agents are carried and/or incorporated into food packaging formulations. Consumers demand natural antimicrobials over chemical/synthetic ones, such as bacteriocins, bacteriophages, and essential oils. Bacteriophages (viruses) have emerged as a feasible option for decontaminating and eliminating infections from food sources. These viruses can target specific food-borne pathogens without impairing beneficial bacteria and, most critically, without causing disease in humans or animals. Fortifying bacteriophages into food packaging films will not only kill specific food microorganisms but has evolved as a new weapon to combat antimicrobial-resistant (AMR) issues. The present review summarises recent developments in active antimicrobial packaging focused particularly on bacteriophage-food packaging applications and advantages, drawbacks, and future trends for active food packaging.

Natural products endowed of biological activity represent a primary source of commodities ranging from nutrition to therapeutic agents, as well as cosmetic tools, and recreational principles. These natural means have been used by mankind since centuries if not millennia. They are commonly used all over the world and socio-economical contexts but are particularly attractive in disadvantaged area or economically emerging situations all over the world. This is very likely due to the relatively easy recovery of these bioactive principles from the environment, to the low if any cost as well as ease of administration and to the general popular compliance concerning their consumption/ingestion. In this concise review, we focus on some popular bioactive principles of botanical origin which find a wide use in the Madagascan populations. But, due to space limitations only some most common and largely diffused principles in this country are considered. Finally, a possible nanotechnological administration is discussed in the case where a potential therapeutic usage is envisaged.

The launch of the RadioAstron space radio telescope provides a unique opportunity to study the extreme high brightness temperature of Active Galactic Nuclei (AGNs) with unprecedented long baselines of up to 28 Earth diameters. A coordinated ground-based flux density monitoring of RadioAstron targets is essential to determine the effect of interstellar scintillation (ISS) on the Space Very Long Baseline Interferometry (SVLBI) visibilities. Moreover, a combination/comparison of scintillation with SVLBI observations is expected to reveal the relative influence of source brightness temperature, compactness, and properties of the interstellar medium on the observed variability at centimeter wavelengths. In 2014 we started a RadioAstron target triggered flux monitoring with the Effelsberg 100-m radio telescope in support of this SVLBI mission. A total of 112 targets were observed during the five-session monitoring performed so far. In this paper we present a statistical study on the short-term flux density variability of the sample, which is focused on the variability characteristics and derived physical properties of the observed sources.

Active contour models present a robust segmentation approach which make efficient use of specific information about objects in the input data rather than processing all the data. They have been widely used in many applications including image segmentation, object boundary localisation, motion tracking, shape modelling, stereo matching and object reconstruction. In this paper, we investigate the potential of active contour models in extracting roads from Mobile Laser Scanning (MLS) data. The categorisation of active contours based on their mathematical representation and implementation are discussed in detail. We discuss an integrated version in which active contour models are combined to overcome their limitations. We review various active contour based methodologies which have been developed to extract roads and other features from LiDAR and digital imaging datasets. We present a small case study in which an integrated version of active contour models is applied to automatically extract road edges from MLS dataset. An accurate extraction of left and right edges from the tested road section validates the use of active contour models. The present study provides a valuable insight on the potential of active contours for extracting roads and other infrastructures from 3D LiDAR point cloud data.

Open source software such as OpenDSS has given a lot of help to distribution network researchers and educators. With high penetration of distributed renewable energy resources into distribution network, tradition distribution steady state analysis software such as OpenDSS is faced with difficulty in handling distributed generators. Three-phase distributed generators are often modeled in sequence frame while unbalanced distribution network are usually modeled in phase frame. So a load flow in sequence-phase coupled frame is proposed to handle models described in both frames. Voltage controlled DGs which are difficult to cope with in OpenDSS are handled in proposed program. The steady state analysis platform is programmed with open source Modelica language and the main aim of this paper is to introduce an open source platform for active distribution network steady analysis include load flow and short circuit analysis which can be easily adopted and improved by other educators and researchers.

Relativistic shocks are one of the most plausible sites of the emission of strongly variable, polarized multi-wavelength emission from relativistic jet sources such as blazars, via diffusive shock acceleration (DSA) of relativistic particles. This paper summarizes recent results on a self-consistent coupling of diffusive shock acceleration and radiation transfer in blazar jets. We demonstrate that the observed spectral energy distributions (SEDs) of blazars strongly constrain the nature of hydromagnetic turbulence responsible for pitch-angle scattering by requiring a strongly energy-dependent pitch-angle mean free path. The prominent soft X-ray excess (``Big Blue Bump'') in the SED of the BL Lac object AO 0235+164 can be modelled as the signature of bulk Compton scattering of external radiation fields by the thermal electron population, which places additional constraints on the level of hydromagnetic turbulence. It has further been demonstrated that internal shocks propagating in a jet pervaded by a helical magnetic field naturally produce polarization-angle swings by 180$^o$, in tandem with multi-wavelength flaring activity, without requiring any helical motion paths or other asymmetric jet structures. The specific application of this model to 3C279 presents the first consistent, simultaneous modeling of snap-shot SEDs, multi-wavelength light curves and time-dependent polarization signatures of a blazar during a polarization-angle (PA) rotation. This model has recently been generalized to a lepto-hadronic model, in which the high-energy emission is dominated by proton synchrotron radiation. It is shown that in this case, the high-energy (X-ray and $\gamma$-ray) polarization signatures are expected to be significantly more stable (not showing PA rotations) than the low-energy (electron-synchrotron) signatures.

An extended classification of active RC- and RLC- filters with Sallen-Key architectures, including those created in the last three years, is proposed. This makes it possible to formulate new design directions for an extended family of active RC- and RLC- Sallen-Key filters (PF, LPF, HPF, RF) for the tasks of high-speed and ultra-fast analog-to-digital signal conversion.

This paper introduces an open-source active high-precision signal amplifier designed for enhancing biodata acquisition, specifically focusing on EEG signals. The compact device, with a diameter of 18 mm, seamlessly integrates electronics, signal processing, and meticulous design considerations. Incorporated within the single board are circuits for low-noise amplification, an analog interface equipped with bandpass filters, and an integrated ADC for precise digitization. A comprehensive evaluation of signal quality has been conducted, encompassing aspects such as noise levels, electrode bias tolerance, and common mode rejection ratio. To facilitate this evaluation, the widely recognized Silver Chloride electrode (Ag/AgCl) has been employed. Additionally, this paper delves into an extensive discussion concerning diverse sources of noise, along with strategies to curtail input noise and minimize noise originating from electrodes and amplifiers. Leveraging the substantial advancements achieved in the design of dry contact electrodes, this specific device is poised to carve a notable niche in the realm of brain-computer interface.

Global warming and climate change have been the major concern for multiple disciplines. Population growth, urbanization, and industrialization are major contributing factors to such a problem by escalating the use of fossil fuels to meet their energy demands. The building sector has the largest share in using the total globally produced energy and emitting tons of greenhouse gas emissions. Emerging eco-friendly technologies such as solar and wind energy harvesting are being extensively explored but still, they are insufficient. Nature-inspired technologies can be the solution to our problem. For instance, algae are microorganisms that use water, light, and CO2 to produce energy and sustain life. Exploiting such characteristics in the built environment is termed algae building technology, a very efficient and green application for a sustainable future. Algae-integrated façades show great versatility through biomass and energy production, wastewater treatment, shading, and thermal and acoustic insulation. In this paper, algae will be introduced as a robust tool toward a greener and more sustainable future, The algae-building technology and its implementation will be demonstrated. Steps for applying this sustainable approach in Egypt will be discussed.

Comparative metatranscriptomics of bacterial and yeast communities of two milk kefir beverages (MKAA1 and MKAA2) obtained by fermentation with two different frozen stocks of the kefir grain CIDCA AGK1, and differing in rheological features and organic acid amounts production was carried out to figure out the relation between differences in physicochemical and rheological properties of kefir and the microbial active profile associated with each product. The dominance of lactic acid bacteria and yeast and a marginal amount of acetic acid bacteria marked the microbiome. The bacterial families Lactobacillaceae and Streptococcaceae account for almost all bacterial gene transcripts, with Lactobacillus helveticus, L. kefiranofaciens, L. gallinarum and Lactococcus lactis being most frequent in the microbiome of MKAA1 beverage, and L. kefiranofaciens, Lc. lactis and Leuconostoc mesenteroides being most prevalent in the MKAA2. Dipodascaceae and Saccharomycetaceae were the leading yeast families represented by Yarrowia lipolytica, Saccharomyces unisporus, and Kluyveromyces marxianus. The MKAA1 and MKAA2 shared >75% KEGG Ortologs (KO) in bacteria and yeast libraries. Considerable decreases in total expressed genes (KEGG Ortolog) assigned to Lactobacillus helveticus and L. gallinarum might be related to the variations in rheological features of the beverages, probably by compromising the interrelations with L. kefiranofaciens which might explain the variations in rheological features of the beverages.

In this study, we present comprehensive climatologies of effective ultraviolet (UV) quantities and photosynthetically active radiation (PAR) over Cyprus for the period 2004 to 2023, leveraging the synergy of earth observation (EO) data and radiative transfer model simulations. The EO dataset, encompassing satellite and re-analysis data for aerosols, total ozone column, and water vapor, alongside cloud modification factors, to capture the nuanced dynamics of Cyprus's atmospheric conditions. With a temporal resolution of 15 minutes and a spatial of 0.05°x0.05°, these climatologies undergo rigorous validation against established satellite datasets and are further evaluated through comparisons with ground-based global horizontal irradiance measurements provided by the Meteorological Office of Cyprus. This dual-method validation approach not only underscores the models' accuracy but also highlights their proficiency in capturing intra-daily cloud coverage variations. Our analysis extends to investigating the long-term trends of these solar radiation quantities, examining their interplay with changes in cloud attenuation, aerosol optical depth (AOD), and total ozone column (TOC). Significant decreasing trends in the noon ultraviolet index (UVI), of -2 to -4% per decade have been found in Autumn, especially marked on the island’s Northeastern part, mainly originating from the (significant) positive trends in TOC. The significant decreasing trends in TOC, of -2 to -3% per decade that were found in Spring do not result in correspondingly significant positive trends in the noon UVI since variations in cloudiness and aerosols also have a strong impact on the UVI in this season. The seasonal trends in the Daylight Integral (DLI) were generally not significant. These insights provide a valuable foundation for further studies aimed at developing public health strategies and enhancing agricultural productivity, highlighting the critical importance of accurate and high-resolution climatological data.

This review provides a comprehensive and updated information on chalcones, presenting their sources, methods of identification and properties putting emphasis on applications in agricultural industry. Vast exploitation of synthetic pesticides led to the weed and pest resistance issue, causing economic loss but more importantly health risk due to pesticide overuse. Because one of the aim of the European Green Deal 2030 is the Farm to Fork strategy which targets on reducing by 50% the use of chemical pesticides by 2030, and push towards natural pesticides which are more environmentally friendly and restore natural resources, chalcones and their derivatives seem to fit perfectly. They have herbicidal, fungicidal, bactericidal and antiviral properties. Moreover, chalcones are naturally occurring substances, known for their favorable health effect for years, working on many areas. This review is complementary to the previous ones describing chalcones use in agriculture, updates them but additionally shows methods of detection.

Machine learning approaches are currently used to understand or model complex physical systems. In general, a substantial number of samples must be collected to create a model with reliable results. However, collecting numerous data is often relatively time-consuming or expensive. Moreover, the problems of industrial interest tend to be more and more complex and depending on a high number of parameters. High dimensional problems intrinsically involve the need of large data amount through the curse of dimensionality. That is why, new approaches based on smart sampling techniques are investigated to minimize the number of samples to be given to train the model, such as Active Learning methods. Here, we propose a technique based on a combination of Fisher information matrix and of Sparse Proper Generalized Decomposition that enables the definition of a new Active Learning informativeness criterion in high dimensions. We provide examples proving the performances of this technique on a theoretical 5D polynomial function and on an industrial crash simulation application. The results prove that the proposed strategy over-perform the usual ones.

Active-case finding (ACF) using chest X-ray is an essential method of finding and diagnosing TB cases that may be missed in Indonesia's routine TB case finding. This study compares active and passive TB case-finding strategies. A retrospective study of TB case notification was conducted. Data between January 1 and December 31, 2021, was used. The population in this study were TB cases notified from Kulon Progo District health facilities, including those found through routine activities or active-case finding. A total of 255 TB cases were diagnosed in Kulon Progo in 2021, and 106 (41.6%) were bacteriologically confirmed. The TB patients' mean age was 46.3 (SD 21.4, range 0-85 years). The majority of cases were male (58.8%) and mostly among people aged 16-60 years old (63.5%). ACF diagnosed 91 TB cases (35.7% total cases, 91/255). The proportion of clinical TB cases (n=68, 74.7%) among those found through ACF was higher than found through passive-case finding. Use of chest X-ray in ACF likely contributed to the detection of a higher proportion of clinical TB than bacteriologically confirmed.

In this research, the antioxidant and antibacterial activities of active films based on potato starch containing Viola odorata extract (VOE) were investigated both in vitro and in chicken fillets. The VOE was added to the starch film formulation at 0, 1, 2, and 3% (w/v). The results showed that by increasing the extract level, the total phenol content and antioxidant and antibacterial activity of the films against Escherichia coli, Staphylococcus aureus, and Salmonella typhimurium improved remarkability. The results of meat tests indicated significant antioxidant and antimicrobial activity of active films containing different levels of VOE in chicken fillets, and a direct relationship was observed between the concentration of the extract and the functional activity of the films, so with the increase in the concentration of the extract in the films, the rate of lipid oxidation and growth of microorganisms in chicken fillets decreased significantly during the storage period, and less volatile nitrogen bases, metmyoglobin, and oxidation products were produced in the fillets. In general, the results of this research demonstrated that active film based on potato starch containing VOE (especially 2 and 3% levels) has the ability to extend the oxidative and microbiological shelf life of chicken fillets during cold storage for at least eight days.

In permafrost regions, ground surface deformations induced by freezing and thawing threaten the integrity of the built environment. Mapping the frost susceptibility of the ground at a high spatial resolution is of practical importance for the construction and planning sectors. We processed Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) data from thawing seasons 2015 to 2019, acquired over the area of Ilulissat, West Greenland. We used a least-squares inversion scheme to retrieve the average seasonal displacement (S) and long-term deformation rate (R). We secondly investigated two different methods to extrapolate active layer thickness (ALT) measurements, based on their statistical relationship with remotely-sensed surface characteristics. A Generalized Linear Model (GLM) was first implemented, but the model was not able to fit the data and represent the ALT spatial variability over the entire study domain. ALT were alternatively averaged per vegetation class, using a land cover map derived by supervised classification of Sentinel-2 images. We finally estimated the active layer ice content and used it as a proxy to map the frost susceptibility of the ground at the community scale. Fine-grained sedimentary basins in Ilulissat were typically frost susceptible and subject to average seasonal downward displacements of 3 to 8 cm. Areas following a subsiding trend of up to 2.6 cm/yr were likely affected by permafrost degradation and melting of ground ice below the permafrost table. Our approach enabled us to identify frost-susceptible areas subject to severe seasonal deformations, and/or long-term subsidence induced by degrading permafrost. Used in combination with traditional site investigations, InSAR maps provide valuable information for risk management and community planning in the Arctic.

Future climate change is expected to affect components of the hydrological cycle. However geologic factors can sometimes be more important than the climate with regarding to change hydrological processes. The Keriya River is a large glacier-fed river in the western Tibet Plateau, its upper reaches flow across active fault zones, which have experienced four medium-sized earthquakes within four months 1974. These active faults have made difficult to identify normal meltwater changes using a snow-ice melt model. Because of the seismic events, the river has experienced substantial changes in their drainage systems and complex hydrological processes. Both the Mann-Kendall trend test and a correlation analysis were applied to detect the monthly patterns of stream flows, the change points and the correlations among both summer discharge and air temperature before and after seismic events. We found significant correlations between monthly air temperature and meltwater flow in the summer June during the pre-earthquake of 1958-1974, but none in July and August in the post-earthquake of 1975-1980, and we found no correlation following the earthquake. The correlations were the inverse by losing the former and setting up the latter alternately since the multiple earthquakes. Clearly, the earthquakes and changes in the faults can greatly induce hydrological processes.

This study investigates the power production and blade fatigue of a three-turbine array subjected to active yaw control (AYC) in full-wake and partial-wake configurations. A framework of two-way coupled large-eddy simulation (LES) and aeroelastic blade simulation is applied to simulate the atmospheric boundary-layer (ABL) flow through the turbine array and the structural responses of the turbine blades. Mean power outputs and blade fatigue loads are extracted from the simulation results. By exploring the feasible AYC decision space, we find that (a) in the full-wake configuration, the local power-optimal AYC strategy with positive yaw angles endures less flapwise blade fatigue and more edgewise blade fatigue than the global power-optimal strategy; (b) in the partial-wake configuration, applying positive AYC in certain inflow wind directions achieves higher optimal power gains than that in the full-wake scenario and reduces the blade fatigue from the non-yawed benchmark. Through a theoretical analysis based on the blade element momentum theory, we reveal that the aforementioned differences in flapwise blade fatigue between the positively and negatively yawed turbine are due to the differences in the azimuthal distributions of the local relative velocity on blade sections, resulting from the combined effects of vertical wind shear and blade rotation. Furthermore, the difference in the blade force between the positively and negatively yawed front-row turbine induces different wake velocity and turbulence distributions, causing different fatigue loads on the downwind turbine exposed to the wake.

Background: Recent work has investigated significant force transmission between the compo-nents of myofascial chains. Misalignments in the body due to fascial thickening and shortening can therefore lead to complex compensatory patterns. For the treatment of such nonlinear cause-effect pathology, a comprehensive neuro-musculoskeletal therapy such as the Rolf Meth-od of Structural Integration (SI) could be targeted. Methods: A total of 727 subjects were retro-spectively screened from the medical records of an SI practice over a 23-year period. 383 subjects who had completed 10 basic SI sessions met eligibility criteria and were assessed for active range of motion (AROM) of the shoulder and hip before and after SI treatment. Results: Shoulder flex-ion, external and internal rotation, and hip flexion improved significantly (all p < 0.0001) after 10 SI sessions. Left shoulder flexion and external rotation of both shoulders increased more in men than in women (p < 0.0001), but were not affected by age. Conclusions: SI intervention produces multiple changes in the components of myofascial chains that could help maintain upright pos-ture in humans and reduce inadequate compensatory patterns. SI affects differently the outcome of some AROM parameters in women and men.

The spread of ideas is a fundamental concern of today’s news ecology. Understanding the dynamics of the spread of information and its co-option by interested parties is of critical importance. Research on this topic has shown that individuals tend to cluster in echo-chambers and are driven by confirmation bias. In this paper, we leverage the active inference framework to provide an in silico model of confirmation bias and its effect on echo-chamber formation. We build a model based on active inference, where agents tend to sample information in order to justify their own view of reality, which eventually leads to them to have a high degree of certainty about their own beliefs. We show that, once agents have reached a certain level of certainty about their beliefs, it becomes very difficult to get them to change their views. This system of self-confirming beliefs is upheld and reinforced by the evolving relationship between agent's beliefs and its observations, which over time will continue to provide evidence for their ingrained ideas about the world. The epistemic communities that are consolidated by these shared beliefs, in turn, tend to produce perceptions of reality that reinforce those shared beliefs. We provide an active inference account of this community formation mechanism. We postulate that agents are driven by the epistemic value that they obtain from sampling or observing the behaviors of other agents. Inspired by digital social networks like Twitter, we build a generative model in which agents generate observable social claims or posts (e.g. `tweets') while reading the socially-observable claims of other agents, that lend support towards one of two mutually-exclusive abstract topics. Agents can choose which other agent they pay attention to at each timestep, and crucially who they attend to and what they choose to read influences their beliefs about the world. Agents also assess their local network’s perspective, influencing which kinds of posts they expect to see other agents making. The model was built and simulated simulated using the freely-available Python package pymdp. The proposed active inference model can reproduce the formation of echo-chambers over social networks, and gives us insight into the cognitive processes that lead to this phenomenon.

Traditional education, particularly at a university level isn’t necessarily very engaging1 or strong at building teamwork skills. Educational escape rooms are a recent game based learning2 approach which combines team based problem solving with a story-line and cryptic clues. In this3 paper we apply the concept of educational escape rooms to the telecommunications engineering4 classroombycreatingaseriesoftwoseparatescenarios,eachcontainingthreepuzzles. Ourevaluation5 is based on beta tester survey results which suggest that this will be an engaging and challenging6 tool for teaching telecommunications engineering. Although educational escape rooms are rapidly7 being deployed in education, these are the first educational escape rooms that specifically addresses8 the field of telecommunications engineering.

The flipped classroom is gaining prominence as an active learning pedagogy to engage a new generation of students. However, all courses do not lend themselves to a fully flipped design and instructors are often reluctant to flip lectures. In this study, I experimented with a “partial” flipped classroom design in a first-year undergraduate economics course. In this partial flipped format, traditional lectures were substituted with micro-lectures and the remaining class time was devoted to activities like quizzes, group work and student presentations. The full lectures were panopto recorded and put up on the e-learning site, Blackboard. This format enabled me to combine the benefits of a traditional lecture with a flipped classroom design. In order to evaluate the effectiveness of the partial flipped classroom format, I compared the final exam scores of students in the partial flipped classroom with those in the control group, which followed a traditional lecture-based approach. The key results from the analysis revealed that students in the partial flipped classroom performed better in the final exams vis-à-vis students in the traditional classroom format. Furthermore, the partial flipped classroom format was associated with lower odds of students failing in the module. This format also resulted in better student engagement, more flexibility and enhanced student-tutor interaction within the classroom.

If students do not fully apply themselves, then they may be considered responsible for the result of being inadequately prepared. +- Nevertheless, student outcomes are more likely to reflect a combination of both effort and systematic problems with overall course architecture. Deficiencies in course design result in inadequate preparation that adversely and directly impacts students’ productivity upon entering the workforce. Such an impact negatively influences students' ability to maintain gainful employment and provide for their families, which inevitably contributes to the development of issues concerning their psychological well-being. It is well-documented that incorporating active learning strategies in course design and delivery can enhance student learning outcomes. Despite the benefit of implementing active learning techniques, rarely in the real world will it be possible for techniques to be used in isolation of one another. Therefore, the purpose of this proposed study is to determine the interactive effects of two active learning strategies because, at a minimum, technique-pairs more accurately represent the application of active learning in the natural educational setting. There is a paucity of evidence in the literature directed toward investigating the interactive effects of multiple active learning techniques that this study is aimed at filling. The significance of this research is that, by determining the interactive effects of paired active learning strategies, other research studies on the beneficial effects of using particular active learning technique-pairs will be documented contributing to the literature so that ultimately classroom instruction may be customized according to the determination of optimal sequencing of strategy-pairs for particular courses, subjects, and desired outcomes that maximize student learning.

Over the past decade, our knowledge of the $\gamma$-ray sky has been revolutionized by ground- and space-based observatories by detecting photons up to several hundreds of tera-electron volt (TeV) energies. A major population of the $\gamma$-ray bright objects are active galactic nuclei (AGN) with their relativistic jets pointed along our line-of-sight. Gamma-ray emission is also detected from nearby mis-aligned AGN such as radio galaxies. While the TeV-detected radio galaxies ($TeVRad$) only form a small fraction of the $\gamma$-ray detected AGN, their multi-wavelength study offers a unique opportunity to probe and pinpoint the high-energy emission processes and sites. Even in the absence of substantial Doppler beaming $TeVRad$ are extremely bright objects in the TeV sky (luminosities detected up to $10^{45}~erg~s^{-1}$), and exhibit flux variations on timescales shorter than the event-horizon scales (flux doubling timescale less than 5 minutes). Thanks to the recent advancement in the imaging capabilities of high-resolution radio interferometry (millimeter very long baseline interferometry, mm-VLBI), one can probe the scales down to less than 10 gravitational radii in $TeVRad$, making it possible not only to test jet launching models but also to pinpoint the high-energy emission sites and to unravel the emission mechanisms. This review provides an overview of the high-energy observations of $TeVRad$ with a focus on the emitting sites and radiation processes. Some recent approaches in simulations are also sketched. Observations by the near-future facilities like Cherenkov Telescope Array, short millimeter-VLBI, and high-energy polarimetry instruments will be crucial for discriminating the competing high-energy emission models.

Addition of the bulky redox-active diphosphine 1,8-bis(diphenylphosphino)naphthalene (dppn) to [Fe2(CO)6(-edt)] (1) (edt = 1,2-ethanedithiolate) affords [Fe2(CO)4(2-dppn)(-edt)] (3) as the major product, together with small amounts of a P-C bond cleavage product [Fe2(CO)5{1-PPh2(1-C10H7)}(-edt)] (2). The redox properties of 3 have been examined by cyclic voltammetry and it has been tested as a proton-reduction catalyst. It undergoes a reversible reduction at E1/2 = –2.18 V and exhibits two overlapping reversible oxidations at E1/2 = –0.08 V and E1/2 = 0.04 V. DFT calculations show that while the HOMO is metal-centred (Fe-Fe -bonding), the LUMO is primarily ligand-based but also contains an antibonding Fe-Fe contribution, highlighting the redox-active nature of the diphosphine. It is readily protonated upon addition of strong acids to afford two isomeric hydride complexes and catalyzes the electrochemical reduction of protons at Ep = –2.00 V in the presence of CF3CO2H. The catalytic current indicates that it is one of the most efficient diiron electrocatalysts for the reduction of protons, albeit operating at quite negative potential.

Pheidole oxyops Forel, 1908 is a generalist ant, which forages actively for plant debris to dead arthropods. In addition, its nest has an entrance that allows the ants gather resources passively by capturing falling preys into the nest. Our objective was to verify if different day periods, temperature and residual soil accumulation (ground pile in the side of nest entrance) could influence the patterns of foraging activity. Foraging activities were registered in the morning, afternoon and twilight. We measured direction and vector of trails, air temperature and humidity during foraging events. Our results showed that foraging routes are independent of residual soil accumulation and other nearby nests. However, air temperature and the time daily period are significant factors to foragers’ exits. Higher air temperatures influenced negatively the exits. In the period of the afternoon, the ants do not show any preference for routes, different from the morning and twilight. In addition, foraging activities were significantly more frequent during twilight period. Leaving the nest at twilight could allow ants foraging in an environment with less exposition to potential predators and competitors. Moreover, it may be also related to opportunism to hunt other nocturnal insects.

This paper focuses on the new users cold-start issue in the context of recommender systems. New users who do not receive pertinent recommendations may abandon the system. In order to cope with this issue, we use active learning techniques. These methods engage the new users to interact with the system by presenting them with a questionnaire that aim to understand their preferences to the related items. Example of questions may include "do you like this book?" and the users answer,"yes", "no", "I have not read it (unknown)", will reflect the degree of interest for the item by the users. As a consequence, the system can learn the users' preferences from these answers. The goal of active learning is to correctly choose the questions (items) for users. Thus it is necessary to personalize the questionnaires to retrieve the maximum information by avoiding "unknown" answers. In this paper, we propose an active learning technique that exploits past users' interests and past users' predictions in order to identify the best questions to ask.

The official recommendations to manage COVID-19 in the outpatient setting focus on high-cost drugs (remdesivir, nirmatrelvir-ritonavir, molnupiravir), suffering from many problems. Therefore, one may consider also other treatments meeting these criteria: • promising effectiveness, based on favorable randomized controlled trials (RCTs) of sufficient validity. Even without definitive evidence, physicians and informed patients can consider them if they are also: • safe, to the state of knowledge • with a very favorable opportunity cost • biologically plausible/not implausible • accessible • without major commercial sponsors in the trials promoting them, and with researchers without major conflicts of interests. The main focus is on a limited group of functional foods and some their active ingredients, with further mention of other substances of different origin, yet fully meeting all the aforementioned criteria. The functional foods and substances described and discussed certainly do not cover all the known effective therapies for COVID-19 (in one case also for Long-COVID), but the only therapies proposed in this paper currently satisfy all the above criteria. The supporting scientific evidence will favor meta-analyses of RCTs that include the most definitive outcome: all-cause mortality, i.e. the outcome that most fully informed people tend to prioritize. Furthermore, the reported evidence favors clinical studies of the most valid design, i.e. RCTs.

The autonomous displacement and displacement measurement functions of the maglev ruler are performed by the mover core. The stability of the four magnetic field in air gaps and the levitation position of the maglev ruler is one of the key factors for the stability of the thrust force on the power core, and it is also one of the key factors for ensuring the precision of the maglev ruler. There is cross-coupling between the two ends of the mover core of the maglev ruler, resulting in a strongly coupled, nonlinear, multi-input and multi-output system for the levitating system of the maglev ruler. This paper establishes a mathematical model for the levitating system of the maglev ruler, and designs a levitating control system for the maglev ruler based on ADRC control algorithm to achieve decoupling and disturbance suppression. Through simulation analysis and experimental testing of the levitating system with starting and disturbance, it is proved that the levitating control system of the maglev ruler has good dynamic characteristics, static characteristics, and robustness.

The aim of the study was to assess the effects of an 8-week cognitive-motor training program on postural control and knee proprioception under single and dual-task conditions. Design: Randomized clinical trial. Methods: 20 healthy and physically active older adults (73.255.98 years) volunteered to participate and were randomly assigned into an experimental and a control group (EG and CG). Postural control was measured with the Romberg test, with open (RBOE), closed eyes (RBCE) and under unipodal dominant side (RUDL) conditions. Proprioception was assessed by measuring participants’ ability to reposition their dominant knee at 45º. Finally, performance on the cognitive task was measured through a subscale of the Barcelona Test called “categorical evocation in associations.” The EG and the CG completed 8-week training programme with two sessions the 30 minutes per week of postural control and proprioception exercises. The EG additionally included music in each session. Results: The results showed significant differences in both group at the postural control tests (RBOE and RBCE) and proprioceptive test post intervention. Conclusion: The 8-week training program had a positive impact on the post-intervention results for motor control and proprioception, but not on the results of the cognitive task. There were no significant differences between the groups that carried out sessions with or without music.

Diabetes mellitus (DM) is a metabolic disorder characterized by the deficiency of insulin production and is one of the concerning health problems worldwide, especially in developing countries. Considering the systemic toxicity associated with current antidiabetic medications and their limited efficacy, there is an urgent need to discover new plant-based natural antidiabetics. Since time immemorial, medicinal plants have played an important role in the management of health disorders. In recent years, herbal medicine has experienced exponential growth in popularity worldwide, owing to its natural origin and fewer side effects, appealing to both developing and developed nations. Ecuador has a rich cultural history in ethnobotany that plays a crucial role in their people's lives. Several Ecuadorian medicinal plants have hypoglycemic or an-ti-hyperglycemic properties that are rich with bioactive phytochemicals. These medicinal plants were extensively used in traditional medicine preparation in Ecuador for many decades to treat diabetes because of their cost-effectiveness, available traditional knowledge, and low toxicity. Many Ecuadorian medicinal plants are reported to have antidiabetic properties that reduce blood sugar levels, and oxidative stress, regulate intestinal function, improve insulin resistance, inhibit α-amylase and α-glucosidase, lower gluconeogenic enzymes, stimulate glucose uptake mechanisms, and play an important role in glucose and lipid metabolism, yet there is a substantial lack of integrated approach between the existing ethnomedicinal practice and pharmacological research. Therefore, this review aims to discuss and explore the traditional medicinal plants used in Ecuador for treating DM and their bioactive phytochemicals, which are mainly responsible for their anti-diabetic properties.

Among the major systems of high-speed rail, the arch network relationship, wheel-rail relationship and fluid-structure coupling relationship are important links affecting the performance of high-speed rail, and also the main control factors affecting the speed limit of high-speed rail. From this perspective, the contact state and interactive relationship between pantograph and catenary are the key factors affecting the forward performance of high-speed rail. As a key component in the pantograph system, the actuator is responsible for adjusting the contact force and position between the pantograph and the contact line. The performance characteristics of the actuator, such as response speed, accuracy, stability and durability, directly affect the control performance of the whole pantograph system. In this paper, the research status of the active control technology of high-speed railway pantograph is reviewed, and the future development direction is pointed out, which provides a new idea for the development of pantograph technology.

Natural products from medicinal plants, either as pure compounds or as standardized extracts, provide unlimited opportunities for new drug leads because of the unmatched availability of chemical diversity. The objects of the study are medicinal plant raw materials Saussurea sordida Kar&Kir and Saussurea alpina DC. collected from South Kazakhstan during the flowering period in the spring-summer months of 2021. The present study was aimed to investigate the toxic effects acute administration of ethanol extracts from plants S. sordida and S. alpina in male Wistar rats. The ethanol extract by subjected to Phytochemical Screening, Fourier transform infrared spec-troscopy (FTIR) analysis. Phytochemical screening of the extract revealed the presence of phenolic compounds. FT-IR spectroscopic analysis revealed various characteristic band values with various functional groups in the formulation extract such as amines, alcohol, phenol, alkane, alkene, and conjugated acid groups. FT-IR analysis of peak values with various functional compounds such as alcohols, phenols, carboxylic acids, aldehydes, amides, amino acids, anhydrides, esters, ketones, unsaturated aliphatic, aromatics, unsaturated heterocycles, amines, nitro compound, alkanes, al-kenes and sugars. Histological examination of organ samples after studying the chronic toxicity of ex-tracts of two plant species (S. sordida . and S. alpina) revealed no pathological changes. The acute toxicity study revealed no lethal effects and behavioral signs of toxicity at the tested doses indicating that LD50 is greater than 2000 mg/kg. These results show low toxicity of on short-term use and liver toxicity on long-term use. This study helps to predict the formula and structure of active molecules which can be used as medicinal drugs. This result also enhances the traditional usage of S. sordida and S. alpina , which possesses a number of bioactive compounds.

In contemporary construction, the prevalence of vibration serviceability issues in lightweight and slender structures has become increasingly common, owing to advancements in building materials and construction methods. While these structures often meet the criteria for ultimate limit states, they can still elicit complaints due to excessive vibrations induced by human activity. To address this challenge, the Integral Resonant Control (IRC) technique has emerged as a favored approach for actively damping vibrations in various systems. This study introduces a fresh perspective on implementing a multi-input multi-output (MIMO) IRC scheme for active vibration control (AVC) specifically tailored for pedestrian structures utilizing inertial mass actuators. Building upon a common framework and design methodology outlined in previous research, this work presents a novel application of MIMO IRC for AVC. The designed controller is rigorously tested and implemented on a laboratory floor structure to validate its efficacy.

Passive balancing is a traditional choice for lithium-ion battery packs although it is regarded as highly inefficient. One opportunity to improve traditional balancing in sub-medium size battery packs is to combine two balancing methods: passive and active. Statistical analysis have been performed to rationalize battery pack division in smaller packs and use of higher level selective charging method to decrease losses of passive balancing. An experimental balancing prototype have been designed and tested for efficiency. Results indicate energy performance degradation if cells of the pack are with low capacity variation. Proposed balancing approach could improve performance under high cell mismatch conditions.

This paper proposes to combat active eavesdropping by intelligent reflecting surface (IRS) backscatter techniques. To be specific, the source (Alice) sends the confidential information to the intended user (Bob), while the eavesdropper (Willie) transmits jamming signal to interrupt the transmission for more data interception. To enhance the secrecy, an IRS is deployed and connected with Alice through fiber to transform the jamming signal into the confidential signal by employing backscatter techniques. Based on the considered model, an optimization problem is formulated to maximize signal-to-interference-plus-noise ratio (SINR) at Bob under the constraints of the transmit power at Alice, the reflection vector at the IRS and the allowable maximum SINR at Willie. To address the optimization problem, an alternate optimization algorithm is developed. The simulation results verify the achievable secrecy gain of the proposed scheme.

We used ab initio molecular dynamics simulations to compare the activation of 2-propanol on the low index Co3O4 (111), (110) and (001) surfaces in dry conditions. The thermal and surface assisted decomposition of a film of 2-propanol to 2-propoxide on the B-termination of each surface was monitored and analyzed. The investigations suggest an activity order of Co3O4 (111) > (110) > (001). On the B-terminated (111) surface, full dissociation of all 2-propanol molecules at the interface is observed, accompanied by a Mars-van Krevelen-type mechanism upon hydroxylation of the surface. On the (110) surface, 2-propanol dissociation is driven by temperature, which activates the two-fold coordinatively unsaturated surface oxygens. The (001) surface on which almost no dissociation occurs is the least active. No formation of acetone is observed in the simulations conditions.

We investigate the influence of a self-propelling, out-of-equilibrium active particle on generalized elastic systems, including flexible and semiflexible polymers, fluid membranes, and fluctuating interfaces, while accounting for long-ranged hydrodynamic effects. We derive the fractional Langevin equation governing the dynamics of the active particle, as well as that of any other passive particle (or probe) bound to the elastic system. Our study explores the diffusional behavior emerging for both the active particle and a distant probe.

Accidents between right-turning commercial vehicles and crossing vulnerable road users (VRU) in urban environments often lead to serious or fatal injuries and therefore play a significant role in forensic accident analysis. To reduce the risk of accidents, blind spot assistance systems have been installed in commercial vehicles for several years, among other things, to detect VRUs and warn the driver in time. However, since such systems cannot reliably prevent all turning accidents, an investigation by experts must clarify how the accident occurred and to what extent the blind spot assistance system influenced the course of the accident. The occurrence of the acoustic warning message can be defined as an objective reaction prompt for the driver, so that the blind spot assistance system can significantly influence the avoidability assessment. In order to be able to integrate the system into forensic accident analysis, a precise knowledge of how the system works and its limitations is required. For this purpose, tests with different systems and accident constellations were conducted and evaluated. It was found that the type of sensor used for the assistance systems has a great influence on the system’s performance. The lateral distance between the right side of the commercial vehicle and the VRU as well as obstacles between them and the speed difference can take great influence on the reliability of the assistance system. Depending on the concrete time of the system’s warning signal the accident can be avoided or not by the driver when reacting on this signal.

This article presents a comprehensive overview of the utilisation of nanotechnology in the cosmetics industry, with a specific focus on developing nanoparticles for the efficient delivery of active ingredients through skin penetration. The review delves into incorporating natural ingredients in cosmetics, exploring their therapeutic properties and the advantages and limitations associated with their use. Furthermore, the article examines the benefits of integrating natural ingredients into skincare products to enhance skin conditions, highlighting the application of nonfibrous technology in areas such as UV protection, anti-ageing effects, moisturisation improvement, and wound healing. Ultimately, the article emphasises the immense potential of nanotechnology to create innovative opportunities and positive societal impacts across various industries.

The objective of this study is to investigate the viability of employing waste derived from Syzygium cumini seeds as an environmentally sustainable antioxidant adjunct within the framework of PLA-PCL-Nanochitosan active packaging for food preservation. The method involves the manufacturing of a food packaging film by combining a PLA/PCL polymer blend with chloroform, followed by an evaporation process. This polymer blend is subsequently mixed with an extract derived from Syzygium cumini seed waste and nano chitosan. The mechanical mixing process takes 45 minutes and is carried out at a temperature of 160°C. The results of this study show that the active film has excellent mechanical properties, and an even surface texture, and was able to significantly reduce S. aureus colony counts by up to 98%. Active packaging film is also able to maintain pH and total volatile basic nitrogen (TVBN) in chicken breast.

Active transportation, such as walking, cycling, and micro-mobility modes, has received a lot of attention in recent years due to its potential benefits to urban residents, such as less traffic, better air quality, more opportunities to get exercise, and an overall higher quality of life. In this study, we used Classification and Regression Trees (CART) to compare and contrast three mobility options: shared micro-mobility, individual micro-mobility, and walking. We surveyed 219 people living in Budapest, Hungary, to learn more about their travel habits and investigate the demographic elements that influence people's mode choice, such as age, gender, ownership of micro-mobility modes, education, job, and income. Results showed that ownership of personal micro-mobility modes, and age as important predictors of active travel mode choice. Males seem to prioritize cost and weather conditions when choosing shared micromobility modes, while females value safety and weather conditions. Our findings can guide policy decisions and urban planning initiatives by identifying the most significant predictors of mode choice and evaluating the possible benefits and drawbacks of each mode.

Recently, new advanced techniques have been proposed to improve the quality of smart grids that use intermittent renewable energy sources. One of the most effective techniques is active filtering, which utilizes a power electronic converter in the smart load. This technique has the potential to enhance the power quality of the supply voltage by minimizing current harmonics, which is crucial. In this article, we propose a new command intelligence system based on Fuzzy PI fractional (fuzzy FOPI) and GA to control the harmonic currents generated by an active filter powered by a wind system.

In this paper, we describe the surface modification of Polytetrafluoroethylene (PTFE) through plasma treatment process. Several parameters including different active gases; RF power; dis-tance between the plasma source and sample; and plasma duration were optimized to reduce the hydrophobic nature of PTFE. Three different active gases were used [i.e., N2, O2 and (Ar+H2)], in which N2 was effective to reduce the hydrophobicity of PTFE within shorter plasma duration of 2 minutes. Several surface characterizations including ATR-FTIR, water contact angle, FE-SEM and XPS were utilized to verify the neat and modified PTFE surface after plasma treatment. The plasma treatment using N2 as an active gas improved the wettability of PTFE membrane, show-ing a water contact angle of 108° when compared with the neat PTFE (140°). The SEM images of plasma treated PTFE shows greater modifications on the surface indicating non-uniform fiber alignment and torn fibers at several places. The obtained results confirm the fact that plasma treatment is an effective way to modify the PTFE surface without altering its bulk property.

In the past decade, considerable efforts have been devoted to the development of semitransparent organic solar cells. Numerous materials and architectures have been proposed for the future commercialization of these devices. Among these, the use of ternary active layers demonstrated a great promise for the development of efficient semi-transparent organic solar cells with the potential for future applications including self-powered greenhouses and powered windows. Researchers seek alternative solutions to the trade-off between device power conversion efficiency (PCE) and average visible transmittance (AVT), with photoactive materials being the key parameters that govern both (PCE) and (AVT) as well as device stability. Several new organic materials, including polymers and small molecules, were synthesized, and used in conjunction with a variety of techniques to achieve semitransparent conditions. In this review paper, we will look at the working principle and key parameters of semi-transparent organic solar cells, as well as the methods that have been used to improve the performance of ternary-based semi-transparent organic solar cells. The main approaches were concluded to be spectral enhancement and transparency increment of the active layer through bandgap tuning, utilizing novel organic semiconductors, and design architecture of the active layers.

Alginate films (2% w·v-1) were prepared with varying concentrations (5-20% w/w) of citric acid and aqueous grape seed extract (GSE) filtrate (11.66 ± 1.32 g GAE/L) by the solvent-evaporation method. Crosslinking alginate via ester bonds (FTIR analysis) with citric acid up to 10% (w/w) led to a 33% increase in tensile strength, a 34% reduction in water vapor transmission rate (WVTR), and had no impact on elongation at break. Crosslinking alginate with citric acid in presence of GSE increased the tensile strength by 17%, decreased WVTR by 21%, and significantly improved DPPH scavenging activity. Moreover, after incubation for 24 h at 37°C, the film-forming solutions exhibited increased antimicrobial activity, resulting in 0.5 and 2.5-log reductions for Escherichia coli and Staphylococcus aureus, respectively, compared to the values obtained without the addition of GSE. The stronger inhibitory effect observed against Gram-positive bacteria can be attributed to the unique composition and structure of their cell walls, which create a barrier that restricts the penetration of polyphenols into the cells. pH adjustment of the GSE film-forming solution from 2.0 to 10.0 shifted the UV/VIS absorption spectra, resulting in a colour change from yellow to red. The findings of this study have showcased the potential of combining GSE and citric acid to enhance the functionality and bioactivity of alginate films for applications in smart food packaging.

We present a crack-free optically active SiO2 glass-composite material containing YAG:Ce synthesized by a modified sol-gel technique. A glass-composite material consisting of yttrium aluminum garnet doped with Ce3+ (YAG:Ce) entrapped into a SiO2 xerogel. This composite material has been prepared by sol–gel technique with modified gelation and drying process to obtain crack-free optically active SiO2 glass. The concentration of the YAG:Ce was from 0.5 to 2.0 wt%. All synthesized samples were characterized by X-ray diffraction (XRD) and scanning electron microscope (SEM) techniques. The luminescence properties of the obtained materials were studied.

The emergence of various electronic devices and equipment such as electric vehicles and drones requires higher energy density energy storage devices. Lithium-sulfur batteries (LSBs) are considered as the most promising new generation energy storage system owing to high theoretical specific capacity and energy density. However, the severe shuttle behaviors of soluble lithium polysulfides (LiPSs) and the slow redox kinetics lead to low sulfur utilization and poor cycling stability, which seriously hinder the commercial application of LSBs. Therefore, various catalytic materials have been employed to solve these troublesome problems. High entropy materials (HEMs), as advanced materials, can provide unique surface and electronic structures that expose plentiful catalytic active sites, which opens new ideas for the regulation of LiPSs redox kinetics. Notwithstanding many instructive reviews in the land of LSBs, while this review aims to offer a complete and shrewd summary of the current progresses in HEMs-based LSBs, including in-depth interpretation of design principles and mechanistic electrocatalysis functions as well as pragmatic perspectives.

Ion-complementary self-assembling peptides have been studied in many fields for their distinct advantages mainly due to their self-assembly properties. However, their shortcomings, such as insufficient specific activity and poor mechanical properties, also limited their application. For better and wider application of this kind of promising biomaterials, ion-complementary self-assembling peptides can be modified with their self-assembly properties not being destroyed to the greatest extent. The modification strategies were reviewed by taking RADA16-Ⅰ as an example. For the insufficient specific activity, RADA16-Ⅰ can be structurally modified with active motifs derived from the active domain of the extracellular matrix or other related active factors. For weak mechanical properties, materials with strong mechanical properties or materials that can undergo chemical crosslinking were used to mix with RADA16-Ⅰto enhance the mechanical properties of RADA16-Ⅰ. To improve the performance of RADA16-Ⅰ as drug carriers, appropriate adjustment of the RADA16-Ⅰ sequence and/ or modification of the RADA16-Ⅰ-related delivery system with polymer materials or specific molecules can be considered to achieve sustained and controlled release of specific drugs or active factors. The modification strategies reviewed in this paper may provide some references for the further basic research and clinical application of ion-complementary self-assembling peptides and their derivatives.

We considered a vacuum polarization around a massive object in the eikonal approximation and found two types of vacuum polarization. The first type has the equation of state similar to radiation and can produce a halo that increases the rotation velocity of a test particle with a radial distance. The second type of vacuum polarization has a more complicated equation of state. As a static physical effect, it produces renormalization of the gravitational constant. Besides, we demonstrate that a nonstationary polarization of the second type caused by a swift increase of the galactic nuclei mass results in a gravitational potential looking like a dark matter halo.

Shape-memory hydrogels (SMH) are as multifunctional, actively-moving polymers of interest in biomedicine. In loosely crosslinked polymer networks gelatin chains may form triple helices, which can act as temporary netpoints in SMH, depending on the presence of salts. Here, we show programming and initiation of the shape-memory effect of such networks based on a thermomechanical process compatible with the physiological environment. The SMH were synthesized by reaction of glycidylmethacrylated gelatin with OEG α,ω-dithiols of varying crosslinker length and amount. Triple helicalization of gelatin chains is shown directly by wide-angle X-ray scattering and indirectly via the mechanical behavior at different temperatures. The ability to form triple helices increased with the molar mass of the crosslinker. Hydrogels had storage moduli of 0.27-23 kPa and Young’s moduli of 215-360 kPa at 4 °C. The hydrogels were hydrolytically degradable, with full degradation to water soluble products within one week at 37 °C and pH = 7.4. A thermally-induced shape-memory effect is demonstrated in bending as well as in compression tests, in which shape recovery with excellent shape recovery rates Rr close to 100% were observed. In the future, the material presented here could be applied e.g. as self-anchoring devices mechanically resembling the extracellular matrix.

In the context of improving the comfort and dynamics of the vehicle, the suspension system has been continuously developed and improved, especially using magnetorheological (MR) shock absorbers. The development of this technology which is relatively new has not been easy. Thus, the first widespread commercial use of MR fluid in a semi-active suspension system was implemented in passenger cars. The magnetorheological shock absorber can combine the comfort with the dynamic driving, because it allows the damping characteristic to be adapted to the road profile. The main objective of the paper is to analyze the dynamic behavior of the magnetorheological shock absorber in the semi-active suspension. In this sense, the author carried out a set of experimental measurements with a damping test bench, specially built and equipped with modern equipment. The results obtained from the experimental determinations show a significantly improved comfort when using a magnetorheological shock absorber, compared to a classic one, by the fact that the magnetorheological shock absorber allows to modify the damping coefficient according to the road conditions, thus maintaining the permanent contact between the tire and the road due to increased damping force.

From single-cell organisms to complex neural networks, all evolved to provide control solutions to generate context and goal-specific actions. Neural circuits performing sensorimotor computation to drive navigation employ inhibitory control as a gating mechanism, as they hierarchically transform (multi)sensory information into motor actions. Here, we focus on this literature to critically discuss the proposition that prominent inhibitory projections form sensorimotor circuits. After reviewing the neural circuits of navigation across various invertebrate species, we argue that with increased neural circuit complexity and the emergence of parallel computations inhibitory circuits acquire new functions. The contribution of inhibitory neurotransmission for navigation goes beyond shaping the communication that drives motor neurons, instead, include encoding of emergent sensorimotor representations. A mechanistic understanding of the neural circuits performing sensorimotor computations in invertebrates will unravel the minimum circuit requirements driving adaptive navigation.

A key concern in an ageing society is citizens’ mobility. As populations age, disability impairments can affect active ageing, health-related wellbeing and quality of life. In this paper, we present the on-going research project SeriousGiggle—Game-based learning for triggering active ageing. Its goal is to assess the potential of game-based learning for active ageing and contribute to a sense of wellbeing and quality of life. It also seeks to improve the mobility of older adults by creating a set of journey plans with route guidance that are rated in terms of safety, community support, environment and age-friendliness. Drawn on our field work with 33 co-designers, 40 end users and 10 semi-structured interviews with Subject Matter Experts, we identify a set of necessary design requirements to an Age-friendly Playable City. This study recommends the use of gamification and playful techniques to engage the end-users to provide information about local traffic signs, pavement conditions, wayfinding and, therefore, help to create route guidance and walking assistance that are personalized to older adults’ context in terms of location, travel fitness, mobility impairments and motivations.

Background: Few studies have assessed built environment correlates of active commuting in low-and-middle-income countries, but the different context could yield distinct findings. This cross-sectional study investigated associations between home neighbourhood environment characteristics and active commuting in Chennai, India. Methods: Adults (N = 370, 47.2% female, mean age = 37.9 years) were recruited from 155 wards in the metropolitan area of Chennai in southern India between January and June 2015. Participants self-reported their usual mode of commute to work, with responses recoded into three categories: (1) multi-modal or active commuting (walking and bicycling); (2) public transit; and (3) private transport. Environmental attributes around participants’ homes were assessed using the Neighborhood Environment Walkability Scale-India (NEWS-India). Associations between environmental characteristics and likelihood of active commuting and public transit use were modelled using logistic regression with private transport (driving alone or carpool) as the reference category, adjusting for age, gender, and household car ownership. Results: Consistent with other international studies, participants living in neighbourhoods with a mix of land-uses and a transit stop within a 10-minute walk from home were more likely to use active commuting (both p < 0.01). Land-use mix was significantly associated with the use of public transit compared to private transport (aOR = 5.2, p = 0.002). Contrary to findings in high-income countries, the odds of active commuting were reduced with improved safety from crime (aOR = 0.2, p = 0.003), aesthetics (aOR = 0.2, p = 0.05) and street connectivity (aOR = 0.2, p = 0.003). Conclusions: Different environmental attributes were associated with active commuting, suggesting that these relationships are complex and may distinctly differ from those in high-income countries. Unexpected inverse associations of perceived safety from crime and aesthetics with active commuting emphasize the need for high quality epidemiologic studies with greater context-specificity in the study of physical activity in LMICs. Findings have public health implications for India and suggest that caution should be taken when translating evidence across countries.

Active ageing is defined as the process of optimizing opportunities for physical, social and mental health to enable older people to take an active part in society without discrimination and to enjoy an independent and good quality of life. The World Health Organization assumed this as a process for increasing and maintaining an individual’s participation in activities to enhance his/her quality of life. In this survey, the authors addressed the following question: “Is assistive technology (AT) for mobility contributing to enhancement of lifelong capacity and performance?”. From June 2015 until February 2016, 96 community dwelling adults, AT users for mobility (powered wheelchairs, manual wheelchairs, lower limb prostheses, walkers, crutches and canes), aged 45-97, mean 67.02 +/- 14.24 years old, 56.3% female, were interviewed using the Psychosocial Impact of Assistive Devices Scale (P-PIADS), the Activities and Participation Profile related to Mobility (APPM) and demographics, clinical and questions about AT use and training. The participants’ profiles revealed moderate limitation and restrictions in participation, measured by the APPM (2.03). Most participants showed positive impact of AT; average scores obtained from the P-PIADS subscales were: Self-esteem 0.62, Competency 1.11 and Adaptability 1.10. P-PIADS total was 0.96, with the powered wheelchair users scoring the highest (1.53) and the walker users scoring the lowest (0.73). All subscales and P-PIADS total were positively correlated with the activities and participation profile. There was no relation between age and the psychosocial impact of AT or activities and participation profile. These results encourage the authors to follow these participants up for a lifelong intervention. To accomplish that aim, currently, the protocol is implemented at the AT prescribing centers in Coimbra, Portugal in order to assess the impact of AT on participation in society, one of the domains of the Active Ageing Index, a new analytical tool to help policy makers in developing policies for active and healthy ageing.

High redshift blazars are among the most powerful objects in the Universe. Although they represent a significant fraction of the extragalactic hard X-ray sky, they are not commonly detected in gamma-rays. High redshift (z>2) objects represent <10 per cent of the AGN population observed by Fermi so far, and gamma-ray flaring activity from these sources is even more uncommon. The characterization of the radio-to-gamma-ray properties of high redshift blazars represents a powerful tool for the study of the energetics of such extreme objects and the Extragalactic Background Light. This contribution will present results of multi-band campaigns, from radio to gamma-rays, on PKS 0836+710, PKS 2149-306, and TXS 0536+145. The latter is the highest redshift detection of a flaring gamma-ray blazar so far. At the peaks of their respective flares these sources reached an apparent isotropic gamma-ray luminosity of about 10^50 erg/s, which is comparable with the luminosity observed from the most powerful blazars. The physical properties derived from the multi-wavelength observations of these sources are then compared with those shown by the high redshift population.

This paper presents an Application Based Active Learning (ABAL) methodology on Power Electronics (PE) and Electric Machines (EM) as a hybrid laboratory course for the undergraduate students to design and implement the real-world engineering problems. The ABAL is a type of active learning which is a branch of Learner-centered teaching (LCT). The DC/DC converter along with the speed control of DC separately excites the motor. In addition, a DC/AC converter is designed to control the speed of an induction motor. The results are then investigated on a hardware platform under the ABAL experimental methodology. This paper also discusses the problem identification selection of the equipment, circuit design, hardware mounting and critical analysis of the results acquired from the hybrid laboratory. The ABAL methodology was evaluated based on student satisfaction, feedback, grades and interest to solve the real-world problem rather than cramming the engineering concepts and fulfill so-called lab routine and tasks

Background/Objectives: Distance or urbanisation settings may affect active commuting to school (ACS). This study aimed to (i) detect home-school threshold distances of walking to school and (ii) predict walkable distances among adolescents in different urbanisation settings and both sexes, and (iii) to identify variables predicting adolescents’ ACS, in a central Spain region. Methods: The PACOyPACA (Spanish acronym for Pedal-and-Walk to School, Pedal-and-Walk Home) study evaluated adolescents attending urban, semi-urban and rural schools from Castilla-La Mancha region. The sample included 448 adolescents [48.9% females, mean age 14.80 (SD=0.60)] living closer than 5,100m from school. Distance was divided into deciles to detect which adolescents walked more. Most walkable distances within the whole sample, by sex and by urbanisation settings were predicted using Receiver Operating Characteristic (ROC) curves. Variables affecting ACS were found with binary logistic regression. Significance was set at p≤0.05. Results: Most adolescents walked to school (73.1%). Commuting modes differed significantly by urbanisation settings (p=0.001), but not by sex. Most walked when living around 1,400m from school or closer within the whole sample, in both sexes and in urban and semi-urban settings, and adolescents within rural settings did it until 750-900m. Walkable distances were 1,350m for the whole sample and both sexes, and 1,450, 1,350 and 800 within urban, semi-urban and rural settings, respectively. Distance was the only predictor of ACS (p&lt;0.001). Conclusions: Walkable home-school distances differed based on urbanisation settings, which may be due to the classification of urbanisation settings. This study addresses schools within scarcely populated areas.

Physical inactivity is a leading risk factor for non-communicable diseases. Climate change is now regarded as the biggest threat to global public health. Electric micromobility (e-micromobility, including e-bikes e-cargo bikes and e-scooters) has the potential to simultaneously increase people’s overall physical activity while decreasing greenhouse gas emissions where it substitutes for motorised transport. The ELEVATE study aims to understand the impacts of e-micromobility, including identifying the people, places and circumstances where they will be most beneficial in terms of improving people’s health while also reducing mobility-related energy demand and carbon emissions. A complex mixed methods design collected detailed quantitative and qualitative data from multiple UK cities. First, a nationally representative (n=2000), city-wide (n = 1200) and targeted study area surveys have collected data on travel behaviour, levels of physical activity, vehicle ownership and use as well as attitudes towards e-micromobility. Then, to provide insights on an understudied type of e-micromobility, 49 households have been recruited to take part in e-cargo bike one-month trials. Self-reported data from participants are validated with objective data using methods such as GPS trackers and smartwatches recording of routes and activities. CO₂ impacts of e-micromobility use are also calculated. Participant interviews provided detailed information on preferences, expectations, experiences, barriers and enablers of e-micromobility.

This paper explores Augmented Reality (AR) as an innovative active methodology for student assessment in the Higher Education Authority of Arcoverde, proposing an alternative to the traditional assessment model. It investigates how AR can transform the educational process, making assessments more interactive, engaging and effective. The study focuses on three main issues: the impact of AR on student motivation and engagement, its effectiveness in improving content comprehension and retention, and the challenges and limitations of its implementation as an assessment method. Employing dialectical methods, action research and literature reviews, this research documents a 34% increase in students’ content comprehension and a 47% increase in their participation in practical activities. These findings suggest that, despite the technical and curricular integration challenges, AR not only improves assessment methodologies, but also enhances learning, promoting a more dynamic and interactive environment. The overall objective is to demonstrate the ability of AR to replace conventional approaches with a more innovative and efficient practice, highlighting the importance of this technology in advancing pedagogical practices and improving student performance. This study sheds light on the relevance of AR in the educational field, encouraging its adoption to enrich the learning and assessment experience.

Electrowetting display (EWD) device is a new type of electrowetting-on-dielectric (EWOD) equipment which can achieve a paper-like display effect under the control of electric field. In this microfluidic system, the stability of grayscale could be affected by various factors, such as the physicochemical properties of materials, device structure, and electric field distribution. To improve the grayscale stability of active matrix electrowetting displays (AM-EWDs), the impact of different polarities of driving voltage on oil backflow was investigated in this study. Based on the driving principles of AM-EWD, an optimized inter-frame bipolar reset driving waveform was designed to overcome oil backflow. The proposed driving waveform maintained the stability of the oil state by periodically and rapidly releasing trapped charges in the dielectric layer through a reverse driving voltage. Additionally, the effect of feed through voltage on the pixel driving voltage was eliminated by compensating for the driving voltage on common electrode. Finally, the performance of the designed driving waveform was evaluated with a 6-inch AM-EWD driving platform. Compared to the conventional unipolar reset driving waveform, the backflow speed decreased by 2.70 a.u./s. The standard deviation of the display luminance was also reduced by 11.24 a.u. Experimental results indicated that both the oil backflow speed and the fluctuation range of luminance were effectively suppressed by the proposed driving waveform.

Drug residues that contaminate food and water represent a serious concern for human health, since their irrational use is constantly increasing the amplitude of exposure. Multiple sources contribute to the overall exposure to contaminants, including agriculture, domestic use, personal, public, and veterinary healthcare, increasing the possible origin of contamination. In this review, we focus on crop pesticides and veterinary drug residues because of their extensive use in modern agriculture and farming, which ensures food production and security for the ever-growing population around the world. We discuss crop pesticides and veterinary drug residues with respect to their worldwide distribution and impacts, with special attention on their harmful effects on human reproduction and embryo development, as well as their link to epigenetic alterations, leading to intergenerational and transgenerational diseases. Among the contaminants, the most commonly implicated in causing such disorders are organophosphates, glyphosate and antibiotics, with tetracyclines being the most frequently reported. This review highlights the importance of finding new management strategies for pesticides and veterinary drugs. Moreover, due to the still limited knowledge on inter- and transgenerational effects of these contaminants, we underlie the need to strengthen research in this field, so as to better clarify the specific effects of each contaminant and their long-term impact.

A comprehensive multi-jet physics program is anticipated for experiments at future colliders. Key physics processes necessitate detectors that can distinguish signals from W and Z bosons and the recently discovered Higgs boson. Typical examples include channels with W^{+}W^{-} or Z^{o}Z^{o} pairs and processes involving New Physics, in those cases where neutral particles must be disentangled from charged ones due to the presence of W or Z bosons in their final states. Such a physics program demands calorimetric energy resolution at or beyond the limits of traditional calorimetric techniques. Multiple-readout calorimetry, which aims to reduce fluctuations in energy measurements of hadronic showers, is a promising approach. The first part of this article reviews dual and triple readout calorimetry within a mathematical framework describing the underlying compensating mechanism. The second part proposes a potential implementation using an integrally active and total absorption detector. This model serves as the basis for several Monte Carlo studies, illustrating how the response of a multiple-readout calorimeter depends on construction parameters. Among the layouts considered, one configuration operating in triple-readout mode shows the potential to achieve an energy resolution approaching 20\%/\sqrt{E}.

The representation of intelligence is achieved by patterns of connections among neurons in brains and machines. Brains grow continuously, such that their patterns of connections develop through activity-dependent specification with the continuing ontogenesis of individual experience. The theory of active inference proposes that the developmental organization of sentient systems reflects general processes of informatic self-evidencing, through the minimization of free energy, that may be described in information terms that are not dependent on a specific physical substrate. At a certain level of complexity, self-evidencing of living (self-organizing) information systems becomes hierarchic and reentrant, such that effective consciousness emerges as the consequence of a good regulator. These principles imply that an adequate reconstruction of the computational dynamics of an individual human brain is possible with a sufficient neuromorphic emulation.

In this paper, a novel microwave catalyst Ni@SiC/CNFs (NSC), C/Ni (NC), and C/SiC (SC) were successfully synthesized by electrostatic spinning method, and proved to degrade methylene blue with high efficiency under microwave irradiation. The results imply that the catalyst Ni@SiC/CNFs with double shell structure gave a 99.99 % removal rate in 90 s for the degradation of methylene blue under microwave irradiation, outperformed the C/Ni and C/SiC and most other reported catalysts in similar studies. On the one hand, the possible mechanism of the methylene blue degradation should be ascribed to that double shell structure increases the polarization source of the material, resulting in excellent microwave absorption properties; and on the other, the in-situ generation of active species OH• and O2 - under microwave radiation and the synergistic coupling effect of metal plasma greatly improved the degradation efficiency of methylene blue. The findings of this study could provide a valuable reference for the green degradation of industrial dye wastewater and its sustainable development process.

We present a study of the radio variability of bright, $S_{1.4}\geq100$ mJy, high-redshift quasars at $z\geq3$ on timescales up to 30--40 years. The study involved simultaneous RATAN-600 measurements at frequencies of 2.3, 4.7, 8.2, 11.2, and 22.3 GHz in 2017--2020. In addition, data from the literature were used. We have found that the variability index $V_S$ of the quasars ranges from 0.02 to 0.96, with about half of the objects in the sample showing a variability index in the range of 0.25--0.50, which is comparable to that of the blazars at lower redshifts. The distribution of $V_S$ at 22.3 GHz is significantly different from that at 2.3--11.2 GHz, which may be attributed to the fact that a compact AGN core dominates at the source's rest frame frequencies greater than 45 GHz, leading to higher variability indices obtained at 22.3 GHz (the $V_S$ distribution peaks around 0.4) compared to the lower frequencies (the $V_S$ distribution peaks around 0.1--0.2). Several source groups with distinctive variability characteristics were found using cluster analysis of quasars. We propose 7 new candidates for gigahertz peaked-spectrum (GPS) sources and 5 new megahertz peaked-spectrum (MPS) sources based on their spectrum shape and variability features. Only 6 out of 23 sources previously reported as GPS demonstrate a low variability level typical of classical GPS sources ($V_{S} < 0.25$) at 4.7--22.3~GHz. When excluding the highly variable peaked-spectrum blazars, we expect no more than 20\% of the sources in the sample to be GPS candidates and no more than 10\% to be MPS candidates.

Physical inactivity, highly dependent on community and environmental conditions, is the fourth leading cause of death worldwide. The objective of Every Walk You Take initiative was to co-design and test a mHealth intervention prototype (mobile app) to promote active living, and to identify barriers and facilitators for active living in individuals older than 55 years. Community stakeholders that included citizen scientists, teachers, researchers, health professionals and policy makers, familiar with the social and economic burden of aging in developed societies, codesigned the prototype. The app functionalities included recommendations on healthy routes in the city (parks, pedestrian lanes and streets) according to environmental variables (air quality and climate) and personal preferences (route difficulty, distance and geolocalization); and the collection of ecological momentary assessments (pictures and voice notes) to identify the barriers and facilitators to perform the routes. The prototype was tested in a pilot study in two deprived neighbourhoods of Barcelona. A total of 21 citizen scientists [mean age=67 (standard deviation=7)], 86% of them female collected, during two 7-day cycles, 112 comments and 48 pictures describing the barriers and facilitators for active living. The negative impact of dirty or damaged roads on citizen scientists’ motivation to engage in physical activity was highly reported as a barrier indicating that city infrastructure directly influences the public's inclination towards adopting active lifestyles. However, citizen scientists highlighted murals and urban green spaces they encountered, which made their walks more enjoyable and stimulating, as facilitators for active living. Every Walk You Take initiative constitutes the foundation for the development of novel models of health surveillance to address gaps in the current research landscape of active living. Moreover, the increased health literacy of the individuals ensures that they are more conscious about the role of physical activity in healthy ageing.

The article presents the issues related to load sharing in direct current grid and a novel control method which has advantages over known solutions. Unlikely of many similar sounding papers this article shows attempt of creation fully controllable non-isolated system which allows load sharing between permanent magnet alternator equipped with machine side converter (MSC) and dual active bridge (DAB) tied to batteries or supercapacitor. The power sharing is essential feature of parallel connected direct current generators and all types of voltage sources in this way are contributing power to the system. Such system should have possibility of the rapid voltage build up in the case of sudden electrical load changes. To keep the optimal efficiency of the alternator the rotational speed changes according to proper mapping of driving combustion engine. When rotational speed is too low then sudden electrical load can cause significant voltage drop and time needed for voltage build up will vary according to RPM increase. In such situations the undervoltage system can trip the breaker and finally there may be a blackout. To avoid such problem the DC systems which consist of batteries and supercapacitor were introduced. System components include a self-excited synchronous generator (SESG) operating at variable shaft speed as well as batteries and supercapacitors that provide electricity for sudden electrical load changes on the distribution grid. The core of presented system is in power distribution method which consists of programmed controllers structure allowing precise currents distribution. A novelty in the proposed method is the use of a cascaded system of current and DC voltage regulators which allows power distribution precise control. In contrary to previously presented solutions, the proposed system allows fast and accurate control of currents loading parallel connected DC voltage sources for wide range generator speed changes. In presented solution both converters have been equipped with Schottky diodes preventing flow of equalizing currents between closed transistors in the parallel mode of operation. An experimental test-stand of the described system is presented with its theoretical basis and experimental results.

Reflux esophagitis, a treatment for gastric ulcers known as Ilaprazole (Ila), is not stable during storage and handling at room temperature, requiring storage at 5 degrees celsius. In this study, to address these issues with Ila, coformers rich in oxygen (O) and hydroxyl (OH) groups capable of forming hydrogen bonds with were selected. These coformers included Xylitol (Xyl), Meglumine (Meg), Nicotinic acid (Nic), L-Aspartic acid (Asp), and L-Glutamic acid (Glu). A 1:1 physical mixture of Ila and each coformer was prepared, and the potential for cocrystal for-mation was predicted using differential scanning calorimetry (DSC) screening. The results indi-cated the potential for cocrystal formation in the Ila/Xyl physical mixture. Subsequently, Ila and Xyl were mixed in ethyl acetate (EA) in a 1:1 ratio, and after 28 hours of slurry, the formation of Ila/Xyl cocrystal was confirmed through solid-state CP/MAS 13C NMR spectrum analysis, showing intermolecular hydrogen bonding and conformational changes. Furthermore, the 1:1 ratio of Ila/Xyl cocrystal was confirmed through solution-state NMR (1H, 13C, and 2D) molecular structure analysis. To assess the stability of Ila/Xyl cocrystal at room temperature, it was stored and com-pared with Ila at 25±2°C and relative humidity (RH) of 65±5% over three months. The results showed that the purity of Ila/Xyl cocrystal remained at 99.8% from the initial purity of 99.75% over the three months, while Ila was predicted to decrease from an initial 99.8% purity to 90% after three months. Additionally, at 25±2°C and RH 65±5%, a specific impurity B in Ila/Xyl cocrystal was observed to be 0.03% over three months, whereas Ila was predicted to increase from an initial 0.032% to 2.28% after three months. To evaluate the dissolution rate of Ila/Xyl cocrystal, a formulation was prepared and compared with Ila at pH 10, with a dosage equivalent to 10mg of Ila. The results showed that Ila/Xyl cocrystal reached 55% within 15 minutes and 100% within 45 minutes, while Ila was predicted to reach 32% at 15 minutes and 100% only after 60 minutes. However, overall, the Ila/Xyl cocrystal showed results equivalent to or exceeding the dissolution rate of Ila. Therefore, it is predicted that the Ila/Xyl cocrystal will maximize its effectiveness as a more convenient crystal structure for formulation development, allowing storage and preservation at room temperature without the need for the problematic 5°C refrigeration during ambient con-ditions and storage, addressing the issues associated with Ila.

Reconfigurable chiral metasurfaces with dynamic polarization manipulation capability are highly required in optical integrated systems. In this paper, we simultaneously realized giant and large-range switchable asymmetric transmission (AT) and circular conversion dichroism (CCD) in a vanadium dioxide (VO2) based metasurface. The AT and CCD of the insulator VO2 based metasurface reach 0.95 and 0.92, respectively. Utilizing the insulator-to-metallic phase transition of VO2, the AT and CCD could be continuously switched to near zero. Furthermore, the physics mechanism of the giant and switchable AT and CCD are analyzed. The proposed metasurface with large-range switchable AT and CCD is promising in the applications of biochemistry detection, chiral imaging and biosensing.

Deploying UAVs as aerial base stations is an exceptional approach to reinforce terrestrial infrastructure owing to their remarkable flexibility and superior agility. However, it is essential to design their flight trajectory effectively to make the most of UAV-assisted wireless communications. This paper presents a novel method for improving wireless connectivity between UAVs and terrestrial users through effective path planning. This is achieved by developing a goal-directed trajectory planning method using active inference. First, we create a global dictionary using TSPWP instances executed on various training examples. This dictionary contains letters representing available hotspots, tokens representing local paths, and words depicting complete trajectories and hotspot order. By using this world model, the UAV can understand the TSPWP’s decision-making grammar and how to use the available letters to form tokens and words at various levels of abstraction and time scales. With this knowledge, the UAV can assess encountered situations and deduce optimal routes based on the belief encoded in the world model. Our proposed method outperforms traditional Q-learning by providing fast, stable, and reliable solutions with good generalization ability.

Blazars are a subclass of Active Galactic Nuclei (AGN) having relativistic jets aligned within a few degrees of our line-of-sight and form the majority of the AGN detected in the TeV regime. The Fermi-Large Area Telescope (LAT) is a pair-conversion telescope, sensitive to photons having energies between 20 MeV-2 TeV, and is capable of scanning the entire gamma-ray sky every three hours. Despite the remarkable success of the Fermi mission, many questions still remain unanswered, such as the site of gamma-ray production and the emission mechanisms involved. The Asteroid Terrestrial-impact Last Alert System (ATLAS) is a high cadence all sky survey system optimized to be efficient for finding potentially dangerous asteroids, as well as in tracking and searching for highly variable and transient sources, such as AGN. In this study, we investigate possible correlations between the \textit{Fermi}-LAT observations in the 100 MeV-300 GeV energy band and the ATLAS optical data in the R-band, centered at 679 nm, for a sample of 18 TeV-detected northern blazars over 8 years of observations between 2015-2022. Under the assumption that the optical and gamma-ray flares are produced by the same outburst propagating down the jet, the strong correlations found for some sources suggest a single-zone leptonic model of emission.

A printed Vivaldi antenna that is optically transparent, ultra-wideband (UWB), and reconfigurable has been developed, fabricated, and tested at millimeter wave frequencies. It covers a broad frequency range of 20-30 GHz by using three PIN diodes. The diodes control the current flow to direct the beam of the antenna. The results of numerical simulations and measurements match at millimeter wave frequencies. The design of this antenna is unique as it allows for a reduction in size and ease of integration while also providing the ability to change the radiation pattern by up to 300 degrees, making it suitable for 5G and 6G communications. Additionally, this antenna can also be useful for RF applications that require dynamic switching of radiation patterns and cognitive radio.

As an effective active remote sensing (ARS) technology for shallow underground targets, ground penetrating radar (GPR) is a detection method to obtain the characteristic information of underground targets by transmitting electromagnetic wave from the antenna and analyzing the propagation law of the electromagnetic wave underground. Due to the high frequency(1MHz-3GHz) of GPR, the depth of geological exploration is shallow(0.1m-30m). In order to remote sensing the deep earth, it is necessary to increase the size of the radiation source in order to reduce the radiation frequency. At the same time, for most separated GPRs, a single dipole antenna (SD) is used as the radiation source and another antenna device placed along the electromagnetic wave propagation direction in the far field as a remote sensing sensor (RSS), both of which are horizontally linearly polarized (LP) antennas. In some cases, such a design is apt to cause problems such as multipath effect (ME) and polarization mismatch (PM). When GPR in ARS of deep earth is performed, it often results in increased errors, signal attenuation during data reception and processing. In contrast, at the radiation source, with the use of large aperture multiple-dipole antennas (MD) and multi-channel sequential rotational excitation, the electromagnetic wave can radiate outward in the form of circular polarization at a low frequency. At the RSS, the trouble caused by ME and PM can be reduced even if the LP antennas are used. A novel sequential rotationally excited (SRE) circularly polarized (CP) MD array for separated GPR in ARS of deep earth is proposed in this paper, which uses a large aperture CP MD array instead of a small size LP SD. The analysis and simulation results demonstrate that under the premise of the same transmitting power, comparing circular polarization and linear polarization, by using SRE CP MD antennas array radiation source, a significant enhancement (about 7dB) of the Signal to Noise Ratio (SNR) will occur by collecting the radiant energy at the RSS. More importantly, by reducing the exploration frequency to 10KHz, the exploration depth will also be greatly increased by about 10 times.

About a decade ago, active optical crop canopy sensors are being used to manage in-season variable nitrogen (N) fertilization in cornfields to match the plant demand that occurs mid season, increasing the efficiency compared to broadcast N applications. There were also initiatives of using ultrasonic sensors to measure plant height on-the-go for N application and crop water demand estimation, but no studies have integrated the optical, ultrasonic and canopy temperature for crop water stress assessment. The objective of this chapter is to evaluate the crop water status using infrared thermometry integrated with optical and ultrasonic sensors. Specifics objectives are: (i) evaluate the corn canopy temperature under different previous crop, N rates and irrigation levels; (ii) test a procedure for water stress assessment in commercial cornfields using the integration of sensors, (iii) correlate plant based sensor measurements (N status, plant height and canopy temperature) with grain yield, soil attributes and detailed topographical features, and (iv) study the spatial dependence of canopy temperature. This study was conducted in one small plot study area and on three producer’s fields in 2010. The small plot experiment consisted of two irrigation levels (70 and 100% of evapotranspiration – ET), two previous crop schemes (corn after corn – CC and corn after soybeans – CS), and four N rates (0, 75, 150, 225 kg N ha^-1). Canopy temperature, optical reflectance and plant height was measured from R2 until R6 in the small plots. At the producer’s fields, three long strips across center pivots were used to have a non-limited N and water crop and then continuous georeferenced sensors measurements were taken during side-dress (V11 growth stage) in about 10 hectares in each field. In the small plot study the crop canopy temperature was influenced by the irrigation levels and N rates. The procedure proposed could be used to identify zones in the producer’s field where water stress can be a yield limiting factor other than N derived. Inside the zones considered that water stress played a major whole, there were low correlations between plant height, plant N status and canopy temperature, indicating that the canopy temperature had more influence from water stress than vegetation cover. Concave and lower elevation areas had higher yields compared to convex and high elevation, showing that the detailed elevation mapping can be beneficial to delineate stables zones that possibly could be used in variable irrigation systems. The spatial dependence of canopy temperature was over 65 meters across producers’ sites, showing that the commercial high clearance applicator’s swath width was adequate to obtain accurate maps. The integration of plant N status, plant height and canopy temperature was beneficial to detect water stressed zones in the field. Opportunities can be foresee also for on-the-go N fertilization using integration of these sensors because is likely that water stress can be confounded with different N supply during the growing season and in different zones in the field.

A key goal of modern neuroscience involves understanding how connections in the brain form and function. Such a knowledge is essential to better inform how defects in the exquisitely complex steps of nervous system growth underlie neuropsychiatric and neurodevelopmental disorders. In the last 40 years, studies of the nervous system in the fruit fly Drosophila melanogaster enabled the discovery of a wealth of molecular and genetic mechanisms that drive the development of these synaptic connections – specialized cell-to-cell connections that are the essential substrate for information flow and processing in the nervous system. The major driver of knowledge focused on studies at the neuromuscular junction due to its ease of examination. Analogous studies in the central nervous system lagged behind due to a lack of genetic accessibility of specific central neuron classes, appropriate synaptic labels compatible with cell-type specific access, and high resolution, quantitative imaging strategies. However, understanding how synapses in central circuits form remains a prerequisite to understanding brain development. In the last decade, a host of new tools and techniques made possible the extension of genetic studies of synapse organization into central circuits and greatly enhanced our understanding of central synapse formation, organization, and maturation. In this review, we consider the current state-of-the-field, focusing on two major elements. We first discuss the tools, technologies, and strategies developed to visualize and quantify synapses in vivo in genetically identifiable neurons of the Drosophila CNS. Second, we explore in depth how these tools enabled a clearer understanding of synaptic development and organization in different circuits of the fly brain and discovered novel molecular mechanisms that underlie synapse formation. These studies establish multiple brain regions in the fly as powerful in vivo genetic models that offer novel insights into synaptogenic regulators and mechanisms of neural development.

The Particulate Matter (PM), particles of variable but small diameter could penetrate the respiratory system via inhalation, causing respiratory and/or cardiovascular diseases. This study aims to evaluate the association of environmental particulate matter (PM2.5) and black carbon (BC) with respiratory health and physical activity in users traveling by transportation modes over four roads in Bogotá. This was a mixed-method study, in 300 healthy participants, based on a convergent parallel design. Including a descriptive qualitative component focused on asserting the individual perception of air pollution by semi-structured interviews and a cross-sectional study measuring the individual exposure to PM2.5 and BC to evaluate the pulmonary function by spirometry. The analysis included concurrent triangulation and a Poisson regression. This study provides integration of air pollution exposure variables and respiratory health effects in different transport microenvironments. To our knowledge, this is the first mixed-methods study focused on PM2.5, BC, and respiratory health effects in a city above 2.000 meters above sea level.

Machine learning applications often need large amounts of training data to perform well. Whereas unlabeled data can be easily gathered, the labeling process is difficult, time-consuming, or expensive in most applications. Active learning can help solve this problem by querying labels for those data points that will improve the performance the most. Thereby, the goal is that the learning algorithm performs sufficiently well with fewer labels. We provide a library called scikit-activeml that covers the most relevant query strategies and implements tools to work with partially labeled data. It is programmed in Python and builds on top of scikit-learn.

The management of a cultural change in higher education is becoming necessary and unavoidable: changes in teaching, changes in research and changes in governance. Digital transformation is an essential part of many countries’ modernisation agendas. The aim of this non-experimental, descriptive, survey-based study was to explore the perceptions of university students toward the digital transformation that took place in university teaching as a consequence of COVID-19. The specific objectives proposed were to: a) analyse the perceptions of students toward digital transformation in university teaching; b) determine the valuation of students about the digital transformation that occurred in university teaching as a result of COVID-19; and c) explore the resources (hardware-software), professional collaboration, digital pedagogy and student empowerment (motivation) with respect to digital education and the recent changes in university teaching due to the pandemic. The results show that a large number of items are positively correlated. In conclusion, further research should delve into motivation, collaboration, reflective experience sharing, self-learning and initiatives that promote the development of competences in future teachers.