Prior to clinical trials, preclinical testing of oncology drug candidates is performed by evaluating drug candidates with in vitro and in vivo platforms. For in vivo testing, animal models are used to evaluate the toxicity and efficacy of drug candidates. However, animal models often display poor translational results as many drugs that pass preclinical testing fail when tested in humans, with oncology drugs exhibiting especially poor acceptance rates. The FDA Modernization Act 2.0 promotes alternative preclinical testing techniques, presenting the opportunity to use higher complexity in vitro models as an alternative to in vivo testing, including 3D cell culture models. 3D tissue cultures address many of the shortcomings of 2D cultures by more closely replicating the tumour microenvironment through a combination of realistic drug diffusion, paracrine signaling, cellular phenotype, and vascularization that can better mimic native human tissue. This review will discuss the common forms of 3D cell culture, including cell spheroids, organoids, organs-on-a-chip, and 3D bioprinted tissues. Their advantages and limitations will be presented, aiming to discuss the use of these 3D models to accurately represent human tissue and as an alternative to animal testing. The use of 3D culture platforms for preclinical drug development is expected to accelerate as these platforms continue to improve in complexity, reliability, and translational predictivity.

Light Detection and Ranging (LiDAR) technology, a cutting-edge advancement in mobile applications, presents a myriad of compelling use cases, including enhancing low-light photography, capturing and sharing 3D images of fascinating objects, and elevating the overall augmented reality (AR) experience. However, its widespread adoption has been hindered by the prohibitive costs and substantial power consumption associated with its implementation. To surmount these obstacles, this paper proposes a low-power, low-cost, SPAD-based system-on-chip (SoC) which packages the microlens arrays (MLA) and incorporates with a light-weight RGB-guided sparse depth imaging completion neural network for 3D LiDAR imaging. The proposed SoC integrates an 8x8 Single-Photon Avalanche Detectors (SPADs) macro pixel array with time-to-digital converters (TDC) and charge pump, fabricated using a 180nm bipolar-CMOS-DMOS (BCD) process. A random MLA-based homogenizing diffuser efficiently transforms Gaussian beams into flat-topped beams with a 45° field of view (FOV), enabling flash projection at the transmitter. To further enhance resolution and broaden application possibilities, a lightweight neural network employing RGB-guided sparse depth complementation is proposed, enabling a substantial expansion of image resolution from 8x8 to quarter video graphics array level (QVGA; 256x256). Experimental results demonstrate the effectiveness and stability of the hardware encompassing the SoC and optical system, as well as the lightweight features and accuracy of the algorithmic neural network. This integrated state-of-the-art hardware-software solution offers a promising and inspiring foundation for developing consumer-level 3D imaging applications.

The lab-on-a-chip concept, enabled by microfluidic technology, promises the integration of multi-ple discrete laboratory techniques into a miniaturised system. Research into microfluidics has generally focused on the development of individual elements of the total system (often with rela-tively limited functionality), without full consideration for integration into a complete fully opti-mised and miniaturised system. Typically, the operation of many of the reported lab-on-a-chip devices is dependent on the support of a laboratory framework. In this paper, a demonstrator platform for routine laboratory analysis is designed and built, which fully integrates a number of technologies into a single device with multiple domains such as fluidics, electronics, pneumatics, hydraulics, and photonics. This facilitates the delivery of breakthroughs in research, by incorpo-rating all physical requirements into a single device. To highlight this proposed approach, this demonstrator microsystem acts as a fully integrated biochemical assay reaction system. The re-sulting design determines enzyme kinetics in an automated process and combines reservoirs, three-dimensional fluidic channels, optical sensing, and electronics in a low-cost, low-power and portable package.

Precision agriculture and open-source data repositories provide a plethora of field-specific ecological data about agroecosystems, but few mechanisms have been developed to turn that information into management recommendations for crop production. The On-Farm Precision Experiments (OFPE) framework is an agroecological model-based methodology to improve crop manager’s abilities to make field-scale agronomic input decisions. This work evaluates the use of field-specific experiments that employ open-source data and the data emanating from precision agriculture technologies to gain local knowledge of the spatial and temporal variability in agroeconomic performance at the sub-field scale. Quantification of the temporal variability in crop response to inputs (e.g., crop seeding rates, crop rotations, fertilizers, other soil amendments, pesticides, etc.) allows for estimation of the probability that a future management scenario will outcompete another, in terms of crop yield, crop quality, farmer net return, or environmental quality. The challenge is to integrate OFPE into applied management with minimal disruption of stakeholder practices while drawing on historic knowledge about the field and economic constraints. OFPE is the basis of a decision support system that includes a six-step cyclical process that harnesses precision agriculture technology to apply experiments and gather field-specific data, incorporates modern data management and analytical approaches, and generates management recommendations as probabilities of outcomes. The OFPE framework allows field managers to assess the tradeoffs in agronomic input management between the maximization of crop production, quality and profits from production while considering environmental effects.

Recently, there has been increasing attention toward inhaled nanoparticles (NPs) to develop in-halation therapies for diseases associated with the pulmonary system and investigate the toxic ef-fects of hazardous environmental particles on human lung health. Taking advantage of microfluidic technology for cell culture applications, lung-on-a-chip devices with great potential in replicating the lung air-blood barrier (ABB) have opened new research insights in preclinical pathology and therapeutic studies associated with aerosol NPs. Surprisingly, the air interface in such devices, which makes them tremendously unique among the other common liquid-based cellular mi-crosystems and enables exposure of cultivated cells to the drug/toxic aerosols, has been largely disregarded. Accordingly, there exists a significant research gap in the comprehensive under-standing of the NPs’ dynamics in the lung-on-a-chip devices, which is momentous to control the injection of aerosols to the target area and attain a desired physiochemical efficacy. To address this research gap, a numerical parametric study is presented to provide a deep insight into the dynamic behavior of the airborne NPs in a gas-liquid dual-channel lung-on-a-chip device with a porous membrane separating the channels. A finite element multi-physics model is developed to enable a particle tracing investigation simultaneously in both air and medium phases to replicate the in vivo conditions avoiding laborious and costly experimental trials. The results include the impact of fluid flow as well as geometrical properties on the distribution, deposition, and translocation of the NPs with diameters ranging from 10 nm to 900 nm in the lung-on-a-chip. The obtained results strongly suggest the aerosol injection of NPs instead of the aqueous solution for more efficient deposition on the substrate of the air channel and higher translocation to the media channel. The current study proposes to optimize the affecting parameters to control the injection and delivery of aerosol par-ticles into the lung-on-chip device depending on the objectives of biomedical investigations and provides optimized values for some specific cases. Therefore, this study can assist scientists and researchers in complementing their experimental investigation in future preclinical studies on pulmonary pathology associated with inhaled hazardous and toxic environmental particles, as well as therapeutic studies for developing inhalation drug delivery.

Recent improvements within the fields of high-throughput screening and 3D tissue culture have provided the possibility of developing in vitro micro-tissue models that can be used to study diseases and screen potential new therapies. This paper reports a proof of concept study on the use of microvalve-based bioprinting to create laminar MSC-chondrocyte co-cultures as an in vitro model of autologous chondrocyte implantation (ACI), an established cellular therapy for osteoarthritis. Microvalve-based bioprinting uses microvalves to deposit cells suspended in a liquid in a consistent and repeatable manner. In this case MSCs and chondrocytes have been sequentially deposited into an insert based transwell system in order to create a laminar co-culture, with variations in the ratios of the cell types used to investigate the potential for MSCs to stimulate improved repair. Histological and indirect immunofluorescence staining revealed the formation of dense tissue structures within the chondrocyte and MSC-chondrocyte cell co-cultures, alongside the establishment of a proliferative region at the base of the tissue. No stimulatory or inhibitory effect in terms of ECM production was observed through the introduction of MSCs, although the potential for an immunomodulatory benefit remains. This proof-of-concept study therefore provides a novel method to enable the scalable production of therapeutically relevant micro-tissue models that can be used for in vitro research to optimise ACI procedures.

The present study compared the contralateral suppression and the amplitude of distortion product otoacoutsic emissions (DPOAEs) between smokers and non-smokers to determine the influence of smoking. Thirty smokers and thirty non-smokers within the age range of 18-40 years with a normal hearing sensitivity were considered for the study. For both the groups, DPOAEs were measured and the efferent auditory system functioning was measured by presenting the white noise of 50 dB HL to the contralateral side, while recording the DPOAEs. There was no significant effect of age on the amplitude of DPOAEs in both the groups. However, there were significant differences in the amplitude of DPOAEs between smokers and non-smokers. The amount of suppression and DPOAE amplitude were reduced in smokers when compared to non-smokers. The study found no significant correlation between the amount of smoking and amount of suppression between smokers and non-smokers. However, there were significant correlations between the amount of smoking and DPOAE at low and mid frequencies between smokers and non-smokers. Therefore, the present study highlights the increased damage to the efferent auditory system risk and the smoking ill-effects on the efferent auditory system.

Non-genuine medical products, including diagnostic devices, have become a lucrative business for fraudsters, causing significant damage to revenues and reputation of companies, as well as posing a significant risk to the health of people and societies. Along a “digital twin” representing centrifugal microfluidic flow control on exemplary “Lab-on-a-Disc” (LoaD) systems, a novel, two-pronged strategy to safeguard miniaturized point-of-care devices by means of secret features and manufacturing challenges is outlined; such “hardware encryption” is flexibly programmed for each chip during production, and deciphered from a secure, local or online database at the time of use. This way, unlicensed copying may be efficiently deterred by an unfavourable economy-of-scale, even in absence of legal prosecution.

The purpose of this paper is to build a new bridge between category theory and a generalized probability theory known as noncommutative probability or quantum probability, which was originated as a mathematical framework for quantum theory, in terms of states as linear functional defined on category algebras. We clarify that category algebras can be considered as generalized matrix algebras and that the notions of state on category as linear functional defined on category algebra turns out to be a conceptual generalization of probability measures on sets as discrete categories. Moreover, by establishing a generalization of famous GNS (Gelfand-Naimark-Segal) construction, we obtain a representation of category algebras of †-categories on certain generalized Hilbert spaces which we call semi-Hilbert modules over rigs.

This research analyzed the impact of quality of service as perceived by Hapkido students on their exercise continuation and recommendation intentions. It also identified the measures to reduce the rate of student dropout, strengthen competitiveness, and create more efficient marketing strategies for consumer patterns that are rapidly diversifying Hapkido. A questionnaire survey method was conducted with 300 middle and high school students aged 14–19 years having Hapkido training of three months to two years in Incheon and Bucheon during March–April 2019. Frequency, factor, reliability, correlation, and standard multiple regression analyses were conducted on the surveyed data. The conclusions are as follows. First, considering the impact of service quality on exercise continuation intention, service quality positively affects reliability, personification, and perceptual openness; in terms of possibility, it positively affects typicality, personification, and perceptual openness; and in terms of reinforcement, it positively affects reliability and perceptual openness. Second, examining the impact of service quality on recommendation intention positively affects reliability, personification, and perceptual openness. Third, exercise continuation intention positively affects recommendation intention.

We study strong optical coupling of metal nanoparticle arrays with dielectric substrates. Based on the Fermi Golden Rule, the particle-substrate coupling is derived in terms of the photon absorption probability assuming a local dipole field. An increase in photocurrent gain is achieved through the optical coupling. In addition, we describe light-induced, mesoscopic electron dynamics via the nonlocal hydrodynamic theory of charges. At small nanoparticle size (<20nm), the impact of this type of spatial dispersion becomes sizable. Both absorption and scattering cross section of the nanoparticle are significantly increased through the contribution of additional nonlocal modes. We observe a splitting of local optical modes spanning several tenths of nanometers. This is a signature of semi-classical, strong optical coupling via the dynamic Stark effect, known as Autler-Townes splitting. The photocurrent generated in this description is increased by up to 2%, which agrees better with recent experiments than compared to identical classical setups with up to 6%. Both, the expressions derived for the particle-substrate coupling and the additional hydrodynamic equation for electrons are integrated into COMSOL for our simulations.

Identifying appropriate animal models is critical in developing translatable in vitro and in vivo systems for therapeutic development and investigating disease pathophysiology. These animal models should have direct biological and translational relevance to the underlying disease they are supposed to mimic. Aging dogs naturally develop a cognitive decline in many aspects including learning and memory, but also exhibit human-like individual variability in the aging process. Neurodegenerative processes that can be observed in both human and canine brains include the progressive accumulation of β-amyloid (Aβ) found as diffuse plaques in the prefrontal cortex, including the gyrus proreus, the hippocampus, and in the cerebral vasculature. A growing body of epidemiological data shows that human patients with neurodegenerative diseases have concurrent intestinal lesions, and histopathological changes in the gastrointestinal (GI) tract occurs decades that evolve before neurodegenerative changes. Gut microbiome alterations also have been observed in many neurodegenerative diseases including Alzheimer’s and Parkinson’s diseases, and inflammatory CNS diseases. Interestingly, only recently has the dog gut microbiome been recognized to more closely resemble in composition and in functional overlap with the human gut microbiome as compared to rodent models. This article aims to review the physiology of the gut-brain axis (GBA), and its involvement with neurodegenerative diseases in dogs and humans. Additionally, we outline the advantages and disadvantages of traditional in vitro and in vivo models and discuss future research directions investigating major human neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases using dogs.

This paper reports 2 × 4 hybrid Mach-zehnder interferometer (MZI) - multi-mode interferometers (MMI) based compact thermo-optical switch consisting of slab waveguides on silicon-on-insulator, SOI, platform. The device consists of two identical MMIs, each of 6 μm wide and 140 μm long connected with two phase shifters MMIs each with 2 μm wide and 8 μm long and linear tappers each 4 μm long, connected at both ends of the MMIs to minimize the power coupling loss. The loss for linear taper is found to be below 0.02dB. The footprint of the whole device is six 6 μm × 324 μm. This structure is based on unique multimode region shape, which leads optical switch to have less coupling loss and reduced cross-talk. The average thermo-optical switching power consumption is 1.4 mW, the excess losses are 0.8 dB, and the imbalances are 0.1 dB. Aluminum is used as a heating pad, and a trench is created around this pad to prevent from spreading of heat and reduce power loss almost by a factor of 2 to the adjacent phase shifter. Our new heating method has advantages of compact size and ease of fabrication with the current CMOS technology.

Three-dimensional (3D) cell culture systems can be regarded as suitable platforms to bridge the huge gap between animal studies and two-dimensional (2D) monolayer cell culture to study chronic diseases such as cancer. In particular, the preclinical platforms for multicellular spheroid formation and culture can be regarded as ideal in vitro tumor models. The complex tumor microenvironment such as hypoxic region and necrotic core can be recapitulated in 3D spheroid configuration. Cells aggregated in spheroid structures can better illustrate the performance of anti-cancer drugs as well. Various methods have been proposed so far to create such 3D spheroid aggregations. Both conventional techniques and microfluidic methods can be used for generation of multicellular spheroids. In this review paper, we first discuss various spheroid formation phases. Then, the conventional spheroid formation techniques such as bioreactor flasks, liquid overlay and hanging droplet technique are explained. Next, a particular topic of the hydrogel in spheroid formation and culture is explored. This topic has received less attention in the literature. Hydrogels entail some advantages to the spheroid formation and culture such as size uniformity, the formation of porous spheroids or hetero-spheroids as well as chemosensitivity and invasion assays and protecting from shear stress. Finally, microfluidic methods for spheroid formation and culture are briefly reviewed.

Besides the Lagrangian and the Eulerian descriptions, the motion of a body can also be expressed relative to the present configuration of the body, known as the relative motion description. It is interesting to consider such a relative motion description in general to formulate the basic system of field equations for solid bodies. In doing so, when the time increment from the present state is small enough, the nonlinear constitutive equations can be linearized relative to the present state so that the resulting system becomes linear. This will be done for thermoelastic materials with a brief comment on the exploitation of entropy principle in general. Relative Lagrangian formulation is based on the well-known ``small-on-large'' idea, and can be implemented for solving problems with large deformation in successive incremental manner. Some applications of such a formulation in numerical simulations are briefly reviewed.

Intercalation of noble metals can produce giant Rashba-type spin-orbit splittings in graphene. The spin-orbit splitting more than 100 meV has not yet been achieved in graphene on a metallic or a semiconductor substrate. Here, we report the p-type graphene obtained by Pt intercalation of zero-layer graphene on SiC substrate. The spin splitting of ∼200 meV was observed at a wide range of binding energies. Comparing the results of theoretical studies of different models with the experimantal ones measured by spin-ARPES, XPS and STM methods, we came to the conclusion that inducing giant spin-orbit splitting requires not only a fairly close arrangement of graphene to Pt layer, but also the presence of graphene corrugation caused by non-flat Pt layer. This makes it possible to find a compromise between strong hybridization and increased spin-orbit interaction. In our case, this is achieved by forming Pt submonolayer ordered on a nanometer scale under graphene.

Plant biotechnology is dependent today on accessing broader plant genetic resources for food and agriculture (PGRFA) diversity for ensuring food security for our future. Heterogenous agricultural lands are considered today as hotspot for biodiversity, and they also exist in the hilly mountain areas of Romanian’s Carpathians. The scope of this review is to describe traditional home-hardens related to the land use of households and cultivated species from Moșna commune, Sibiu County, Romania. The survey was realized with the support of authorities and local stakeholders from 2010 up to 2019. The results of this survey revealed that maintenance of crop species structure and land use of traditional households is longer than 100 years. Consequently at least 15 traditional Saxon home-gardens of 120 taken into the study may be defined. Today these home-garden covers a media of 26% of the total area of a household and should be part of a surface ranging between 5,000 and 1,500 m2. The first Local Council Decision in Romania in 2019 supporting the recognition of landraces and home-gardens as heritage values was officially adopted supporting the need to more access bottom-up approaches for supporting biodiversity conservation.

In this study, we considered the structural stability, electronic properties, and phonon dispersion of the cubic (c-ZrO₂), tetragonal (t-ZrO₂), and monoclinic (m-ZrO₂) phases of ZrO₂. We found that the monoclinic phase of zirconium dioxide is the most stable among the three phases in terms of total energy, lowest enthalpy, highest entropy, and other thermodynamic properties. The smallest negative modes were found for m-ZrO₂. Our analysis of the electronic properties showed that during the m–t phase transformation of ZrO₂, the Fermi level first shifts by 0.125 eV toward higher energies and then decreases by 0.08 eV in the t–c cross-section. The band gaps for c-ZrO₂, t-ZrO₂, and m-ZrO₂ are 5.140 eV, 5.898 eV, and 5.288 eV, respectively. Calculations based on the analysis of the influence of doping 3.23, 6.67, 10.35, and 16.15 mol. %Y₂O₃ onto the m-ZrO₂ structure showed that the enthalpy of m-YSZ decreases linearly, which accompanies further stabilization of monoclinic ZrO₂ and an increase in its defectiveness. The doping-induced and concentration-dependent phase transition of zirconium dioxide under the influence of yttrium oxide was studied, after which the position of the Fermi level changes and the energy gap decreases. It has been established that, not only for pure systems but including those doped with Y₂O₃, the main contribution to the formation of the conduction band is made by the p-states of electrons. The t-ZrO₂ (101) and t-YSZ (101) surface models were selected as optimal surfaces for water adsorption based on a comparison of their surface energies. An analysis of the mechanism of water adsorption on the surface of t-ZrO₂ (101) and t-YSZ (101) showed that H₂O on unstabilized t-ZrO₂ (101) is adsorbed dissociatively with an energy of -1.22 eV, as well as by the method of molecular chemisorption with an energy of -0.69 eV and the formation of a hydrogen bond with a bond length of 1.01 Å. In the case of t-YSZ (101), water is molecularly adsorbed onto the surface with an energy of -1.84 eV. Dissociative adsorption of water occurs at an energy of -1.23 eV, near the yttrium atom. The calculations showed that ab initio research methods are capable of describing the mechanism of phase transitions of materials under the influence of alloying. That is, by optimizing the parameters of DFT calculations, it is possible to observe the effects of doping on other physical and chemical properties of materials, which are still beyond the scope of quantum chemical modeling. The obtained results complement the database of research works carried out in the field of the application of biocompatible zirconium dioxide crystals and ceramics in green energy generation and can be used in designing humidity-to-electricity converters and creating solid oxide fuel cells based on ZrO₂.

Aiming at the prediction of environmental vibrations induced by elevated high-speed railway, a machine-learning method is developed by combining random forest algorithm and Bayesian optimization, which using the dataset from on-site experiments . When it comes to achieving a rapid and effective prediction of environmental vibration, there is few research on com-parisons and verifications of different algorithms, and neither on parameter tuning and optimi-zation of machine learning algorithms. In this paper, a field experiment is firstly carried out to measure the ground vibrations caused by high-speed trains running on bridge, and then the en-vironmental vibration characteristics are analyzed in view of ground accelerations and weighted vibration levels. Subsequently, three machine-learning algorithms of linear regression, support vector machine and random forest are developed by using experimental database, and their prediction performance are discussed. Finally, two optimization models for the hyperparameter set of random forest algorithm are further compared. It turns out that the integrated random forest algorithm has higher accuracy in predicting environmental vibration than linear regression and support vector machine; the Bayesian optimization has excellent performance and high efficiency in achieving efficient and in-depth optimization of parameters, and can be combined with the RF machine learning algorithm to effectively predict the environmental vibrations induced by the high-speed railway.

Companion animals play a central role in many families and are especially valued by those who are socially isolated. Crisis situations such as acute hospitalizations, homelessness and natural disasters can make it difficult to preserve the human-animal bond and can result in animals being surrendered or euthanized. Social support programs like the RSPCA NSW Emergency Boarding and Homelessness program support people experiencing crisis situations with emergency pet boarding, access veterinary treatment and individualized case management. This study aimed to estimate the social return on investment (SROI) for this program using standard SROI methodology. In-depth interviews were conducted with 13 program stakeholders and questionnaire responses were received from 29 program clients. Outcomes were quantified for four stakeholder groups: program clients, client’s animals, RSPCA Inspectors, animal pounds and shelters. Clients and their animals experienced the bulk of the benefit from the program, estimated to have a combined value of over $5 million AUD for the 2020-21 financial year. The estimated social return on investment was $8.21 for each $1 invested. The study demonstrates that keeping people together with their companion animals, or ensuring they are reunited as soon as possible, can reduce stressors, and improve outcomes for people and animals.

Autonomous vehicles (AVs) may not only reduce parking demand, but also free up on-street parking spaces. From the perspective of bus priority, converting on-street parking lots into dedicated bus lanes can both ensure bus priority and accommodate non-bus traffic, helping to reduce congestion and pollution. In order to study the impact of conversion of on-street parking lots to bus lanes on traffic flow, a microscopic simulation framework based on VISSIM is proposed in this paper. Data was collected using the floating car method and video recording method to quantify the factors affecting traffic flow due to the conversion of on-street parking. The VISSIM simulation model was then calibrated. According to the proportion of the on-street parking lots into a bus lane, the on-street parking lots conversion simulation model of different scenarios was established, and the influence of different on-street parking lots conversion ratio on traffic efficiency and pollution emission was quantitatively analyzed. Finally, the optimization method based on bus lane network connectivity is discussed. The results indicate that: When the on-street parking lots conversion ratio is approximately 100%, bus speed increases by 21.03%, bus delays decrease by 14.27%, and bus parking instances decrease by 11.31%. Total emissions are negatively correlated with vehicle speed. As the conversion rate of on-street parking increases, the emissions of road segments and the entire road network gradually decrease. At a conversion ratio of 100%, the average total emissions for road segments have the highest reduction rate, decreasing by 4.12%. At a conversion ratio of 50%, the average emission total for the road network shows the largest reduction, falling by 2.88%.

Nowadays, in low voltage (LV) electric distribution networks (EDNs), the Distribution Network Operators (DNOs) are encountering a high number of connected small-scale distributed generation units, mainly photovoltaic (PV) prosumers. The irregular behavior of the prosumers, together with the uncertainty degree of the requested and injected powers associated with all end-users from the LV EDN, can cause voltage variations with violations of the allowable limits. In this context, the paper developed an efficient and resilient expert system integrating the rule-based reasoning applied to the On-load Tap Changer (OLTC)-fitted transformer to improve the efficiency of the voltage control in the PV-rich LV EDNs. An in-depth analysis based on 75 scenarios, resulting from the combinations of three indicators: the penetration degree of the PV prosumers, consumption evolution associated with the consumers, and energy production of the PV systems, has been performed to demonstrate the efficiency of the proposed expert system in an LV EDN from a rural area belonging to a Romanian DNO. The success rate of the expert system has been 86.7% (65 out of 75 scenarios didn't have voltage issues, all values being between the allowable limits in 100% of the time slots associated with the analyzed period). For the other scenarios (representing 13.3%), the values have been inside the range [-10%, +10%] at least 95% of the time slots, according to the European Power Quality Standard, and for the rest of the time slots up to 100% being very close to the upper and lower limits of the range, with highly mitigating of the voltage variations.

Understanding cell migration is a key step to unravel many physiological phenomena and predict several pathologies, like cancer metastasis. In particular, mechanical confinement has been proved to be a key factor in the cellular migration strategy choice. As our insight in the field improves, new tools are needed in order to empower biologists’ analysis capabilities. In this framework, microfluidic devices have been used to engineer the mechanical stimuli and to investigate cellular migration response in a more controlled way. In this work, we will review the existing technologies employed in the realization of microfluidic cellular migration assays, namely soft lithography of PDMS and hydrogels and femtosecond laser micromachining. We will give an overview of the state of the art of these devices, focusing on the different geometrical configurations that have been exploited to study specific aspects of cellular migration. Our scope is to highlight the advantages and possibilities given by each approach and to envisage the future developments in in-vitro migration studies under mechanical confinement in microfluidic devices.

Assisted reproductive technology has been developed significantly throughout the past few years, particularly diagnosing and treating male infertility. Many studies have been performed showing that Intracytoplasmic Sperm Injection (ICSI) is a successful method to attain clinical pregnancy and live birth through impaired spermatozoa characteristics or low sperm count, such as severe oligospermia. Severe oligospermia indicates low sperm count, which in some cases leads to azoospermia. Severe oligospermia can be caused by several factors such as genetics or medication. In search of efficient treatment for couples with Severe oligospermia, numerous retrospective and prospective researches have reported high pregnancy and live birth rates through testicular sperm for men with severe oligospermia and cryptozoospermia with or without high sperm DNA damage. The research showed that the use of testicular sperm in combination with ICSI yielded a high pregnancy rate and live births over another source of sperm, such as ejaculated sperms. Moreover, the use of ICSI in severe oligospermia has shown successful fertilization and pregnancy.

Enhancing the degree of functional multiplexing while assuring operational reliability and manufacturability at competitive costs are crucial ingredients for enabling comprehensive sample-to-answer automation, e.g., for use in common, decentralized “Point-of-Care” or “Point-of-Use” scenarios. This paper demonstrates a model-based ‘digital twin’ approach which efficiently supports the algorithmic design optimization of exemplary centrifugo-pneumatic (CP) dissolvable-film (DF) siphon valves towards larger-scale integration (LSI) of well-established “Lab-on-a-Disc” (LoaD) systems. Obviously, the spatial footprint of the valves and their upstream laboratory unit operations (LUOs) have to fit, at a given radial position prescribed by its occurrence in the assay protocol, into the locally accessible disc space. At the same time, the retention rate of a rotationally actuated CP-DF siphon valve and, most challenging, its band width related to unavoidable tolerances of experimental input parameters, need to slot into a defined interval of the practically allowed frequency envelope. To accomplish particular design goals, a set of parametrized metrics is defined, which are to be met within their practical boundaries while (numerically) minimizing the band width in the frequency domain. While each LSI scenario needs to be addressed individually on the basis of the digital twin, a suite of qualitative design rules and instructive showcases structures are presented.

Cutaneous wound healing is a complex multi-stage process involving direct and indirect cell communication events with the aim of efficiently restoring the barrier function of the skin. One key aspect in cutaneous wound healing is associated with cell movement and migration into the physically, chemically and biologically injured area resulting in wound closure. Understanding the conditions under which cell migration is impaired and elucidating the cellular and molecular mechanisms that improve healing dynamics is therefore crucial in devising novel therapeutic strategies to elevate patient suffering, reduce scaring and eliminate chronic wounds. Following the global trend towards automation, miniaturization and integration of cell-based assays into microphysiological systems, conventional wound healing assays such as the scratch assay or cell exclusion assay have recently been translated and improved using microfluidics and lab-on-a-chip technologies. These miniaturized cell analysis systems allow precise spatial and temporal control over a range of dynamic microenvironmental factors including shear stress, biochemical and oxygen gradients to create more reliable in vitro models that resemble the in vivo microenvironment of a wound more closely on a molecular, cellular, and tissue level. The current review provides (a) an overview on the main molecular and cellular processes that take place during wound healing, (b) a brief introduction into conventional in vitro wound healing assays, and (c) a perspective on future cutaneous and vascular wound healing research using microfluidic technology.

The science‐policy interface in climate change adaptation became better managed over the past decades. However, the scientists and other knowledge producers, as well as policy makers still need to take bolder steps to more effectively engage with others to apply science and shape up policies. This paper aims to provide practical recommendations, intended to promote conversations between science and policy sectors to address climate change issues. Here, I used two different approaches to synthesize experiences and identify recommendations: a literature review and a case study. The paper stress main findings: (1) The linear communication model is still commonly involved in the science - policy dialogue and proved to be useful to increase the relevance of science and data products to decision makers. (2) When a gap between knowledge producer and knowledge user or decision maker exists, the need for a third party to specialize in bridging the gap become essential. (3) Indigenous people and knowledge must be involved in adaptation policy making based on legitimation local and traditional knowledge, designing the consultation process to broadly engage local and indigenous people, facilitating meaningful dialogues between traditional knowledge and science, and developing initiatives to strengthen skills and capacity of indigenous communities.

In the electric distribution systems, the “Smart Grid” concept is implemented to encourage energy savings and integration of the innovative technologies, helping the Distribution Network Operators (DNOs) in choosing the investment plans which to lead the optimal operation of the networks and increasing the energy efficiency. In this context, a new phase load balancing algorithm was proposed to be implemented in the low voltage distribution networks with hybrid structures of the consumption points (switchable and non-switchable consumers). It can work in both operation modes (on-line and off-line), uploading information from different databases of the DNO which contain: the consumers’ characteristics, the real loads of the consumers integrated into the Smart Metering System (SMS), and the typical load profiles for the consumers non-integrated in the SMS. The algorithm was tested in a real network, having a hybrid structure of the consumption points, on a time interval by 24 hours. The obtained results were analyzed and compared with other algorithms from the heuristic (Minimum Count of Loads Adjustment algorithm) and the metaheuristic (Particle Swarm Optimization and Genetic Algorithms) categories. The best performances were provided by the proposed algorithm, such that the unbalance coefficient resulted in the smallest value (1.0017). The phase load balancing led to the following technical effects: decreasing the average current in the neutral conductor with 94% and for the energy losses with 61.75 %, and increasing the minimum value of the phase voltage at the farthest pillar with the 7.14 %, compared to the unbalanced case.

The article reviews the current status of label-free integrated optical sensors focusing on the evolution over the years of their analytical performance. At first a short introduction to the evanescent wave optics is provided followed by detailed description of the main categories of label-free optical sensors including sensors based on surface plasmon resonance (SPR), grating coupler, photonic crystals, ring resonators and interferometric transducers. After a short reference to SPR techniques, including localized SPR, integrated optical sensors i.e., grating-couplers, interferometers, photonic crystals, microring resonators are reviewed. For each type of sensor, the detection principle is first provided followed by description of the different transducer configurations so far developed and their performance as biosensors. Finally, a short discussion about the current limitations and future perspectives of integrated label-free biosensors optical sensors is provided

The VisionCube is a 2-unit CubeSat developed in-house, of which the primary mission is aimed at detecting the occurrence of transient luminous events in the upper atmosphere and obtaining corresponding images from the low Earth orbit. An on-board TLE observation system of the VisionCube cubesat is designed and developed by incorporating a photon-sensitive MaPMT and a CMOS image sensor. Also, a distinctive TLE observation software which enables detecting the TLEs and capturing images in a timely manner is devised. By taking into account the limited resources of a small CubeSat in size and power, the on-board observation system is developed employing a system-on-chip design architecture by which both hardware and software can be integrated seamlessly. The purpose of this study is to investigate the functionality of the hardware and the validity of the software algorithm to show the on-board system will operate properly with no human intervention during the space operation. To this end, a ground simulation facility is constructed to emulate the space environment of the TLE occurrence using a set of UV LEDs inside a darkbox. Based on the analysis of the spectral and temporal properties of the TLEs, the randomly generated UV LED pulses are opted for verification scenarios for the TLE observation system. The validation results show that the hardware and the software algorithm of the on-board observation system can effectively detect the TLEs and obtain the images during the on-orbit operation.

Collision avoidance is an important feature in advanced driver-assistance systems, aiming at providing correct, timely and reliable warnings before an imminent collision (objects, vehicles, pedestrians, etc.). A co-simulation framework is proposed in this paper to address the design and evaluation of collision avoidances in a cyber-physical system. The co-simulation framework is supported on the interaction between SCANeR and Matlab/Simulink. From the best of authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip LIDAR sensors in a cyber-physical system (CPS) considering traffic scenarios is presented. The CPS is designed and implemented in SCANeR. Secondly, an obstacle recognition library with three specific Artificial Intelligence-based methods is also designed based on sensory information database provided by SCANeR. Three methods for collision avoidance detection are considered, i.e.; a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods for detecting obstacles before different weather conditions is done with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and fog conditions, the support vector machine in rainy and self-organized map in snowy conditions.

An on-site, ultra-sensitive, and quantitative sensing method was developed based on quantum dot nanobeads (QDNBs) and test strip for the determination of total aflatoxins (AFTs) in rice and peanut. The monoclonal antibody against AFT (mAbAFT) was home-made and labeled with QDNB. After the pre-coating of the AFT antigen on the test line (T line), the competitive immunoreactions were conducted between AFT and AFT antigen on the T line with QDNBs-mAbAFT. Under optimal conditions, this approach allowed a rapid response towards AFT with a considerable sensitivity of 1.4 pg/mL and 2.9 pg/mL in rice and peanut matrices, respectively. The put-in and put-out duration were within 10 min. The recoveries for AFT in rice and peanut samples matrices were recorded from 86.25–118.0% with the relative deviations (RSD) below 12%. The assay was further validated via the comparison between this QDNB strip and the conventional HPLC method using spiked samples. Thus, the design provided a potential alternative for on-site, ultra-sensitive, and quantitative sensing of AFT that could also be expanded to other chemical contaminants for food safety.

In the paper the experimental methodology for the single-crystal circular plate deformation measurement and subsequent procedure for mechanical properties quantitation are developed. The procedure is based on a new numerical-analytical solution of nonlinear boundary-value problem for finite deformations of a circular anisotropic plate. Using the developed method, a study of the deformation of single-crystal circular plates formed on the basis of a silicon-on-insulator structure was carried out. The values of residual stresses are determined and it is shown that the presence of these stresses increases the flexural rigidity of the plate in several times.

Analytical chemistry applied to medical and diagnostic analysis, recently focused on the development of cost-effective biosensors able to monitor the health status or to assess the level of specific biomarkers that can be indicative for several diseases. The improvement of technologies relating to the possibility of non-invasive sampling of biological fluids, as well as sensors for the detection of analytical signals and the computational capabilities of the systems routinely employed in everyday life (e.g. smartphones, computers, etc.), make the complete integration of self-standing analytical devices more accessible. This review aims to discuss the biosensors that have been proposed in the last 5 years focusing on two principal detecting approaches, optical and electrochemical, which have been employed for quantifying different kind of target analytes reaching detection limits below the clinical sample levels required. These detection principles applied to Point-of-care (POC) devices, have been extensively reported in literature and even the limited examples found on the market are based on these strategies. This work will show the latest innovations considering the integration of optical and electrochemical detection with the most commonly reported analytical platforms for POC applications such as paper-based or wearable and implantable devices.

To address the problem of limited fault diagnosis accuracy in oil-immersed on-load tap changers (OLTC), this paper introduces a novel fault diagnosis method that combines the analysis of mechanical vibration signals and high-frequency current signals. The proposed approach aims to enhance the accuracy of fault diagnosis. To begin, an experimental platform is constructed to simulate the OLTC contact. Mechanical vibration signals and high-frequency current signals are collected from the testing platform under various operating states. These signals are then subjected to wavelet packet transform for denoising, followed by correlation analysis to capture the relationship between signals in different states. Based on these preliminary steps, the features of the signals are extracted and analyzed using ensemble empirical mode decomposition and the Hilbert-Huang transform. Subsequently, a support vector machine (SVM) is employed to analyze both the mechanical vibration signal and high-frequency current signal, enabling the classification of the OLTC contact state. The results demonstrate that the combination of characteristic analysis of mechanical vibration signals and high-frequency current signals provides a more comprehensive reflection of the actual OLTC contact state under different conditions. Through the SVM classification, the error between the predicted values and real values of the two types of signals remains below 10%, validating the efficiency and feasibility of the proposed method for fault diagnosis of OLTC contacts. These research findings serve as a reliable foundation for the diagnosis of operational states of on-site oil-immersed on-load tap changers, offering valuable insights for practical applications.

Existing research lacks studies that explore the impact of government fiscal support on the high-quality development of regional economy and society from the perspective of livelihood-based infrastructure construction. The investigation in this paper explores the economic and social effects of government fiscal support behavior from the perspective of livelihood infrastructure construction. On the basis of the TOPSIS-Entropy Method, this paper constructs an evaluation indicator that closely conforms to the denotation and requirements of high-quality development and then carries out empirical regressions in combination with government expenditure on people's livelihood to verify the theoretical hypothesis, whose transmission mechanism and moderating effect are further empirically tested. The results reveal that increasing government expenditure on people's livelihoods can effectively improve regional high-quality development, but the marginal improvement degree varies with different periods and locations. The mechanism test proves that the regional consumption level plays a significant part in the mediating effect, accounting for 24.27% of the total effect. Urbanization is also the critical impetus for regional high-quality development and positively moderates the promotion effect of people's livelihood fiscal expenditure. Our study presents a theoretical basis and policy inspiration for improving residents' quality of life and welfare level and improving people's livelihood in the midst of high-quality economic development.

Conventional diagnostic techniques are based on utilization of analyte sampling, sensing and signalling on separate platforms for detection purposes, that must be evaded and integrated to a single step procedure in point of care (POC) testing devices. Therefore, the trend has been shifted towards utilization of microfluidic platforms for detection of analytes in biochemical, clinical and food technology due to its being expeditious. Microfluidic systems moulded with polymer substances or glass offer specific and sensitive detection of infectious and non-infectious diseases by providing innumerable benefits including less cost, good biological affinity, strong capillary action and simple process of fabrication. In the case of nucleic acid-based nanosensors, there are some challenges that need to be addressed such as cellular lysis, isolation and amplification of nucleic acid required to be accomplished prior to its detection. To avoid utilization of laborious steps for executing these steps, advances have been deployed in this perspective for on-chip sample preparation, amplification and detection which not only improves sensitivity and selectivity but also saves time and resources. This review emphasizes the significance of microfluidic technology for nucleic acid detection of infectious and non-infectious diseases. The implementation of isothermal amplification in concomitance with lateral flow assay greatly increases the binding efficiency of nanoparticles and biomolecules, improves limit of detection and sensitivity. Most importantly deployment of paper-based material made of cellulose reduces the overall cost. Microfluidic technology in nucleic acid testing has been discussed by explicating its applications in different fields. This review concludes with the prospects and proposes future directions in microfluidic based methods in disease diagnosis.

Cancer stem cells remain a challenge to isolate and characterize because of their plastic phenotype. Using a microfluidic lab-on-a-chip based on ultra-high frequency dielectophoresis, we measured the electromagnetic signature of colorectal cancer cells and demonstrated that cancer stem cells show a distinct and lower electromagnetic signature than differentiated cells. The release of extracellular vesicles from tumor cells can drive tumor progression and metastasis development. As extracellular vesicles from cancer stem cells carry more aggressive content, we treated colorectal cancer cells with these vesicles to test whether the lab-on-a-chip can detect a change in phenotype. The electromagnetic signature of treated cells is modified in comparison to untreated cells and sometimes even when no biological change is observed. The lab-on-a-chip provides rapid and relevant result without prior labeling compared to conventional biological approaches. It could be useful in the clinic for early detection of cancer stem cells in the tumor mass and for monitoring the aggressive potential of extracellular vesicles in the bloodstream in order to adapt therapeutic management and prevent relapse.

Organ-on-a-Chip (OoC) systems bring together cell biology, engineering, and material science for creating systems that recapitulate the in vivo microenvironment of tissues and organs. The versatility of OoC systems enables in vitro models for studying physiological processes, drug development, and testing in both academia and industry. This paper evaluates current platforms from the end-user perspective, elaborating on usability, complexity, and robustness. We surveyed 165 peers in over 30 countries and grouped the responses according to preliminary knowledge and the source of the OoC systems that are used. The survey clearly shows that current commercial OoC platforms provide a substantial level of robustness and usability - which is also indicated by an increasing adaptation of the pharmaceutical industry but a lack of complexity can challenge their use as a predictive platform. Self-made systems on the other hand are less robust and standardized but provide the opportunity to develop customized and more complex models which are often needed for human disease modeling. This review serves as a guide for researchers in the OoC field and encourages the development of next-generation OoCs.

Pandemics caused by viruses have threatened lives of thousands of people. Viral infection is a complex and diverse process, and substantial studies have been complemented in understanding the biochemical and molecular interactions between viruses and hosts. However, the physical microenvironment where infections implement is often less carefully considered, and the role of mechanobiology in viral infection remains elusive. Mechanobiology focuses on sensation, transduction and response to intracellular and extracellular physical factors by tissues, cells and extracellular matrix. The intracellular cytoskeleton and mechanosensors have been proved to be extensively involved in virus life cycle. Furthermore, innovative methods in vivo and in vitro are being utilized to elucidate how extracellular factors including stiffness, forces and topography in regulating viral infection. Our current review covers how physical factors from different sources coordinate virus infection. We further discuss how this knowledge can be harnessed in future research on cross-fields of mechanobiology and virology.

This paper presents results on tribological characteristics for polymer blends made of polybutylene terephthalate (PBT) and polytetrafluoroethylene (PTFE). This blend is relatively new in research as PBT has restricted processability because of its processing temperature near the degradation one. Tests were done block-on-ring tribotester, in dry regime, the variables being the PTFE concentration (0%, 5%, 10% and 15%wt) and the sliding regime parameters (load: 1 N, 2.5 N and 5 N, the sliding speed: 0.25 m/s, 0.5 m/s and 0.75 m/s, and the sliding distance: 2500 m, 5000 m and 7500 m). Results are encouraging as PBT as neat polymer has very good tribological characteristics in terms of friction coefficient and wear rate. SEM investigation reveals a quite uniform dispersion of PTFE drops in the PBT matrix.

Nowadays, mindfulness-based interventions (MBI) have experimented a remarkable development of studies among childhood and adolescent interventions. For this reason, dispositional mindfulness (DM) measures for children and adolescents have been developed to determine the effectiveness of MBI at this age stage. However, little is known about how key elements of DM (f. e., cognitive de/fusion or experiential avoidance that both conform psychological inflexibility) are involved in the mechanisms of the children and adolescents’ mental health outcomes. This research examined the mediating effect of cognitive fusion between DM and anxiety and other negative emotional states in a sample of 318 Spanish primary-school students (aged between 8 and 16 years, M=11.24, SD=2.19, 50.8% males). Participants completed the AFQ-Y, which is a measure of psychological inflexibility that encompasses cognitive defusion and experiential avoidance; CAMM (DM for children and adolescents), PANAS-N (positive and negative affect measure for children, the Spanish version of PANASC), and STAIC (an anxiety measure for children). The study accomplished ethical standards. As MBI relevant literature has suggested, cognitive defusion was a significant mediator between DM and symptoms of both negative emotions and anxiety in children and adolescents. However, experiential avoidance did not show any significant mediating relationship. Probably, it is needed improvement of the assessment of experiential avoidance. MBI programs for children and adolescents may include more activities for reducing the effects of the cognitive defusion on their emotional distress.

Aneuploidy should compromise cellular proliferation but paradoxically favours tumour progression and poor prognosis. Here, we consider this paradox in terms of our most recent observations of chemo/radio-resistant cells undergoing reversible polyploidy. The latter perform segregation of two parental groups of end-to-end linked dyads by pseudo-mitosis creating tetraploid cells through a dysfunctional spindle. This is followed by autokaryogamy and homologous pairing preceding a bi-looped endo-prophase. The associated RAD51 and DMC1/γ-H2AX double-strand break repair foci are tandemly situated on the AURKB/REC8/kinetochore doublets along replicated chromosome loops, indicative of recombination events. MOS-associated REC8-positive peri-nucleolar centromere cluster organises a monopolar spindle. The process is completed by reduction divisions (bi-polar or with radial cytotomy including pedogamic exchanges) and release of secondary cells and/or formation of an embryoid. Together this process preserves genomic integrity and chromosome pairing, while tolerating aneuploidy by by-passing the mitotic spindle and meiotic SC checkpoints. Concurrently, it reduces the chromosome number and facilitates recombination that decreases the mutation load of aneuploidy and lethality in the chemo-resistant tumour cells. This cancer life-cycle has parallels both within the cycling polyploidy of the asexual life cycles of ancient unicellular protists and cleavage embryos of early multicellulars, supporting the atavistic theory of cancer.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

We introduce a modelling framework for the investigation of on-line machine learning processes in non-stationary environments. We exemplify the approach in terms of two specific model situations: In the first, we consider the learning of a classification scheme from clustered data by means of prototype-based Learning Vector Quantization (LVQ). In the second, we study the training of layered neural networks with sigmoidal activations for the purpose of regression. In both cases, the target, i.e. the classification or regression scheme, is considered to change continuously while the system is trained from a stream of labeled data. We extend and apply methods borrowed from statistical physics which have been used frequently for the exact description of training dynamics in stationary environments. Extensions of the approach allow for the computation of typical learning curves in the presence of concept drift in a variety of model situations. First results are presented and discussed for stochastic drift processes in classification and regression problems. They indicate that LVQ is capable of tracking a classification scheme under drift to a non-trivial extent. Furthermore, we show that concept drift can cause the persistence of sub-optimal plateau states in gradient based training of layered neural networks for regression.

In this paper, we study the p-adic integral representation on Z_p of q-Bernoulli numbers arising from two variable q-Bernstein polynomials and investigate some properties for the q-Bernoulli numbers. In addition, we give some new identities of q-Bernoulli numbers.

Cropland area per capita and pressure index on cropland is the important parameters measuring the social vulnerability and sustainability in the perspective of food security in a certain region in China during the historical periods. This study reconstructs the spatial distribution change of cropland area per labor/household and pressure index on cropland during the 17th-20th century by the methods of historical documents, regression analysis, pressure index model and GIS. Then it analyzed the impacting process of climate change and sustainability of cropland use during the different periods. It draws conclusions: (i) the spatial difference of labor/household density was obvious which had the same pattern as cropland distribution during the same periods, which is higher density in three agricultural areas. (ii) Cropland area per capita was relatively higher during the 17th-18th century, which were above 0.4 ha/person in majority counties and distributed homogenously. Till the 19th century and the beginning of 20th century, cropland area per capita in large amount of regions decreased below 0.2 ha/person embodying the increase of social vulnerability and unsustainability at that time. (iii) Pressure index on cropland also showed the similar spatial pattern as cropland area per capita which presented lower threshold than nowadays. During the 17th-18th century there was no pressure on cropland. While, in the 19th century and at the beginning of 20th century, two high value centers of pressure index on cropland appeared in Middle Shandong and the Jiaodong region, pressure on sustainable cropland use increased obviously and a food crisis is probably created. (iv) Higher sustainable extent of cropland use corresponds to cold period, and lower sustainable extent of cropland use corresponds to warm period in Shandong over the past 300 years. The turning point of 1680s from dry to wet attributes to the decrease of sustainable extent of cropland use in Shandong not very distinctively. More and more pressure on sustainability of cropland use finally since the beginning of 20th century would intensify the social conflict and increase the probability of social revolts.

Soft-Core architecture for Analogue to Digital Converter (ADC) sampling is useful for mixed signal applications. Soft-core architecture for cutting edge odd or even ADC sampling with interface to block RAM memory has not been found. Soft-core architecture as a concept has become popular due to the advantage of customization for different applications as compared to general-core architecture suited for single application. The latest generation of piece wise sampling is odd sampling and was introduced in the second decade of the 20th century. Odd and even order sampling techniques are analogue in nature driven by a tuned (tuned for odd or even) mixer. This paper proposes a third-generation piece wise sampling with soft-core architecture that enables an option to select both odd and even while interfacing to memory mapping. The proposed odd/even has superior SNR performance of 6 dB as compared to existing architecture such as Mod-∆ which recorded worst performance of 18 dB. Advances in soft-core technology have allowed a niche odd/even switching field to be identified and studied, the study has also been extended to include memory architecture.

We propose a correspondence between partition functions of ideal gases consisting of both bosons and fermions and algebraic bases of supersymmetric polynomials on the Banach space of absolutely summable two-sides sequences ℓ1(Z0). Such an approach allows us to interpret some combinatorial identities for supersymmetric polynomials from a physical point of view. We consider a relation of equivalence on ℓ1(Z0) induced by the supersymmetric polynomials, and semiring algebraic structures on the quotient set with respect to this relation. The quotient set is a natural model for the set of energy levels of a quantum system. We introduce two different topological semiring structures on this set and discuss their possible physical interpretations.

The paper considers the issues of structural stability, electronic properties, and phonon dispersion of the cubic, tetragonal, and monoclinic phases of ZrO2. It was found that the monoclinic phase of zirconium dioxide is the most stable among the other two phases in terms of total energy, lowest enthalpy, highest entropy, and other thermodynamic values. The smallest negative modes were found for m-ZrO2. An analysis of the electronic properties showed that during the m–t phase transformation of ZrO2, the Fermi level first shifts by 0.125 eV towards higher energies, and then decreases by 0.08 eV in the t–c cross section. The band gap for c-ZrO2, t-ZrO2, and m-ZrO2 is 5.140 eV, 5.898 eV, and 5.288 eV, respectively. Calculations based on the analysis of the influence of doping 3.23, 6.67, 10.35 and 16.15 mol. %Y2O3 on the m-ZrO2 structure showed that the enthalpy of m-YSZ decreases linearly, which accompanies further stabilization of monoclinic ZrO2 and an increase in their defectiveness. In this case, the position of the Fermi level changes abruptly, and the energy gap decreases. It has been established that not only for pure systems, including those doped with Y2O3, the main contribution to the formation of the conduction band is made by the p-states of electrons. An analysis of the mechanism of water adsorption on the surface of t-ZrO2 (101) and t-YSZ (101) showed that H2O on unstabilized t-ZrO2 (101) is adsorbed dissociatively with an energy of -1.22 eV, as well as by the method of molecular chemisorption with an energy of -0.69 eV and the formation of a hydrogen bond with a bond length of 1.01 Å. In the case of t-YSZ (101), water is molecularly adsorbed onto the surface with an energy of -1.84 eV. Dissociative adsorption of water occurs at an energy of -1.23 eV, near the yttrium atom.

The paper presents the measured values of tensile forces acting on transmission idlers in the upper and lower run of a conveyor belt placed on a laboratory machine designed at the Department of Machine and Industrial Design, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava). The tensile forces detected by two strain gauge load cells and recorded using DEWESoft software were used to calculate the friction coefficient which acts on the surface of the driving drum casing and the conveyor belt. The friction coefficient at the slip point, or during the slippage of the conveyor belt on the rubber or steel casing of the driving drum was determined for two states of the surfaces which are in contact. Experimental measurements on a laboratory machine determined four values of friction coefficients, for two types of drum surfaces and for two states of contact surfaces, which were compared with the recommended standard values. The measured values reached higher values in comparison with the values given by the CSN standards. The highest deviation of 273.3% is achieved using a steel wet surface, and the lowest deviation of 106.3% is achieved when using a rubber dry lining for the driving drum casing. On the presented laboratory machine, it is possible to measure tensile forces for different speeds of movement, different belt angles on the driving drum, various types of belt surfaces, different types of drum casing linings and different sizes of tension forces for the endless loop of the conveyor belt. For these characteristics of the conveyor belt, the magnitude of the friction coefficient, acting between the belt and the drum surfaces, can be determined.

Base on building information modeling(BIM) plus with Robotic process automation (RPA) technology is rapid development in smart building operations and maintenance (O&M). RPA is a workflow-based automated execution tool that is particularly well suited for replacing manual execution of simple and repetitive tasks using computer systems. The use of RPA technology can saves man-hours and increases productivity, which is important for the automation of building operations and maintenance operations.. The BIM technology, as an advanced technology in the construction industry, it can provide new ideas and methods for building operation and maintenance based on its visualization characteristics. That’s integrating RPA with BIM technology which will enhance the digitalization and virtualization of smart building operation and management. In this article will first introduce the features of RPA and BIM technology and then discuss the technical roadmap for remote automated operation and maintenance of smart building equipment room to implemention a low-cost and high efficient building equipment room operation and maintenance solution.

Climate change causes weather extremes to rise in frequency and severity, which could have detrimental effects on human life, property and livelihood activity. There is significant uncertainty about the influences of anthropogenic climate change on the occurrence and severity of small-scale, sudden onset weather phenomena such as hailstorms and subsequent loss and damage. Yet, several studies indicate that there is an apparent stable connection between hailstorm activity and hailstorm damage. Severe hailstorm events are observed in Bangladesh in recent years, which are, in fact, rapid-onset disasters but low exposure in terms of giving government response and media consideration. Hence this study examines potential impacts and management strategies for loss and damage resulting from hailstorm events among smallholder farmers in Kurigram District's Phulbari Upazila of Bangladesh. Firstly, the direct and long term economic and non-economic loss and damage caused by the hailstorm on human well-beings and livelihoods were assessed. Then, the study evaluated the current adaptation, coping, management and response strategies at the institutional and community level in the context of such extreme events. Finally, a regulatory framework and implementation approaches had suggested achieving the country's resilience against disaster and climate change-induced loss and damage. Participatory Vulnerability Analysis, Key Informant Interviews and Sample Surveys accumulated the primary data for the study. In addition, secondary data were collected through analysis of literature, published and unpublished scientific articles and media reports, etc. This research outcome will help countries develop a guideline to address climate change and disaster-related loss and damage.

We introduce a new class of Vertex Operator Algebras Y+ and their duals, which generalize the standard W-algebras WN of type sl(N). These algebras can be defined in terms of junctions of boundary conditions and interfaces in the GL-twisted N = 4 Super Yang Mills gauge theory. The aim of these technical calculations is to find the relation of these ortho-symplectic Y-algebras to truncations of even W\infinity.

Recent developments in optical biosensors based on integrated photonic devices are reviewed with a special emphasis on silicon-on-insulator ring resonator. The review is mainly devoted to the following aspects: (1) Principles of sensing mechanism, (2) sensor design, (3) biofunctionalization procedures for specific molecule detection and (4) measurement set-ups and advances in chip-integration. The inherent challenges of implementing photonics-based biosensors to meet specific requirements of applications in medicine, food analysis, and environmental monitoring are discussed.

Various type of soils have been identified based on their electrical and magnetic properties, especially with regards to peat soils. Peat soils are commonly considered as partly decomposed vegetation. In this study, electrical and magnetic properties have been used in K-means clustering to identify layers of peat soils. K-means clustering is a partitioning method that treats observations in the data. Data cores were obtained at every centimeter and examined for their electrical conductivity (σ) and magnetic susceptibility (χ_m) properties. A 291 cm core was obtained at Tegal Arum Village in South Kalimantan, Indonesia. The K-means clustering results indicate two different layers at 148 cm, and this is supported by loss on ignition (LOI) measurements. In the first layers, a 87.65% LOI was found associated with peat soils (above 248 cm). Whereas, in the second layers, there was a 26.11% LOI associated with mineral soils (below 248 cm). The results of this study using K-means clustering can be used to delineate soil layers.

Wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal, and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modelling and control become challenging problems. On one hand, high-fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behaviour. Therefore, the development of modelling and control for wind turbine systems should consider these complexity aspects. On the other hand, these control solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The main point of this paper is thus to provide two practical examples of development of robust control strategies when applied to a simulated wind turbine plant. Experiments with the wind turbine simulator and the Monte–Carlo tools represent the instruments for assessing the robustness and reliability aspects of the developed control methodologies when the model-reality mismatch and measurement errors are also considered. Advantages and drawbacks of these regulation methods are also highlighted with respect to different control strategies via proper performance metrics.

Cement production requires a significant amount of energy and natural resources, severely impacting the environment due to harmful gas emissions. Coal Bottom Ash (CBA) and Coal Boiler Slag (CBS), byproducts of coal-fired power plants, have pozzolanic properties. CBA and CBS can be mechanically ground to obtain Ground Coal Bottom Ash (GCBA) or Ground Coal Bottom Slag (GCBS), which can potentially replace cement in concrete, reducing waste in landfills, benefit the economy, preserving natural resources, and reducing health hazards. This study was performed to determine the optimum amount of GCBA and GCBS that can replace cement in concrete. The fresh, mechanical, and durability properties of the concrete containing GCBA were compared to a control mix consisting of 100% Portland cement. The optimum amount of cement replaced with GCBA and GCBS was 10% and 5%, respectively, based on compressive strength. The GCBA-based concrete's tensile strength, modulus of elasticity, and durability properties were better than the control. The compressive strength of the GCBA and GCBS-based mortars increased with an increase in fineness. GCBA and GCBS fineness should be within the limit recommended in the ASTM C618 standard to enhance concrete or mortar properties.

International basins are divided into sub-basins that are managed at the national and local levels, within the territory of each country, before reaching the level of international concern. The management of international basins could be developed using an integrated water management, based on multi-level governance model in which many actors are involved, from local to international scale. However, in the La Plata River Basin this model is not working, even with international agreements such as the La Plata Basin Treaty, which was signed in 1969. The understanding of political interests behind the law helps to explain its inefficiency. Therefore, considering the lack of a systemic view in an international watershed, it could be possible to have accumulating effects caused by the transformations of watercourses in the sub-basins. Then, the 2014 water crisis in the State of São Paulo, Brazil, is an example of the possible consequences arising from the lack of an integrated water management in the La Plata River Basin. Finally, this article demonstrates that the only way to have water resources utilization efficiency in an international basin is considering it as an integrated ecosystem, in order that any local problem may affect the whole basin.

African swine fever (ASF) is a notifiable viral disease of domestic and wild suids. Despite intensive re-search efforts, the pathogenesis of the disease is still far from being understood. Analysis of biomarkers in different body fluids may supplement traditional pathogenesis studies. As reliable protocols are often es-tablished in laboratories with lower biosafety, reliable inactivation of samples is crucial. The objective of this study was to find a procedure that inactivates the virus while preserving the biomarkers for down-stream analyses. To this means, three different inactivation protocols were employed, namely Tergitol-type NP-40 (NP-40) and polyoxyethylene-p-t-octylphenol (Triton X-100), respectively, and one with 95 °C heating. It could be demonstrated that all samples treated with 0.5% (v/v) concentration of both deter-gents showed absence of virus infectivity. The same was true for heated samples. However, heated serum was not suitable for analyses. Next, the treatment impact on biomarker readouts was assessed. While all protocols had an impact on the detection of biomarkers, correlation was retained. Especially NP-40 could be the desired detergent for more accurate measurements while achieving efficient virus inactivation. Based on these studies, samples can be reliably inactivated for most biomarker analyses and thus broader interdisciplinary cooperation is possible.

Objectives: The study aimed to uncover the percentages of battered women in Jordan, its causes, forms, and relationship to several social factors. Methodology: The study was conducted on a random, targeted sample of (1308) women based on social sample survey method and electronic questionnaire tool for data collection, the Descriptive statistical method and chi-square test were used to examine statistically significant differences. Results: The study found that the percentage of battered women reached 17.1% during Corona pandemic in 2020, and the increase in men's violence against women during this period of was in large and medium degrees according to the sample. Husbands were the most practicing violence against their wives at 37.5%, followed by fathers against daughters at 28.6%, and brothers against sisters at 26.8%. The causes of male violence are due to social factors represented by male domination culture, interference by family and relatives, and economic factors represented by the high cost of living, low household income and poverty. The most common forms of violence are verbal, physical, and psychological. The study found that women in southern Jordan, who are poorer and less educated, and who live in a large family, are the most abused. The study recommended activating family and community service and reform offices, solving problems of deteriorating economic situation and individual poverty, and enlightening community awareness of the dangers of domestic violence.

The investigation of the electromagnetic properties of biological particles in microfluidic platforms may enable wireless monitoring and interaction with functional activity of microorganisms. Of high relevance is the membrane potential as it is one of the most important parameters of living cells. In particular, the complex mechanisms of the cell’s membrane potential are comparable to the dynamics of bacteria membranes, providing a simplified platform for advancing the current techniques and knowledge of general bio-particle dynamics. In this work, we provide a theoretical analysis and experimental results on the microwave detection of bacteria on a microfluidic-based framework for sensing the membrane potential of bacteria. The results enable to further advance the state-of-the-art of electromagnetic bacteria sensing and microfluidic control, and their implication for measuring and interacting with the cell and its membrane potentials, which is of great importance for developing new biotechnological engineered systems and solutions.

In this paper a full state feedback control of a double inverted pendulum on a cart (DIPC) are designed and compared. Modeling is based on Euler-Lagrange equations derived by specifying a Lagrangian, difference between kinetic and potential energy of the DIPC system. A full state feedback control with H infinity and H 2 is addressed. Two approaches are tested: open loop impulse response and a double inverted pendulum on a cart with full state feedback H infinity and H 2 controllers. Simulations reveal superior performance of the double inverted pendulum on a cart with full state feedback H infinity controller.

In addition to the traditional QoS metrics of delay, delay jitter, and packet loss probability (PLP), Quality of Experience (QoE) is now widely accepted as a numerical proxy for actual user experience. The literature has reported many mathematical mappings between QoE and QoS. These QoS parameters are measured by the network providers using sampling. There are some papers studying sampling errors in QoS measurements; however there is no account of propagation of these sampling errors to QoE evaluation. In this paper, we used industrially acquired measurements of PLP and jitter to evaluate the sampling errors and correlation in measurements. Focussing on Video-on-demand (VoD) applications, we use subjective testing and regression to map QoE metrics onto PLP and jitter. The resulting mathematical functions of QoE and theory of error propagation was used to evaluate the propagated error in QoE, and this error was represented as confidence interval. Using the guidelines of UK government for sampling, our results indicate that confidence intervals around estimated QoE in a busy hour can be between MOS=1 to MOS=5 at targeted operating point of QoS parameters. These results are a new perspective on QoE evaluation, and are of great significance to all organisations that need to estimate the QoE VoD applications precisely.

Starting from Thomas Friedrich’s work “Weak Spin(9) structures on 16-dimensional Riemannian manifolds”, we review several interactions between Spin(9) and geometries related to octonions. Several topics are discussed in this respect: explicit descriptions of the Spin(9) canonical 8-form and its analogies with quaternionic geometry, the role of Spin(9) both in the classical problems of vector fields on spheres and in the geometry of the octonionic Hopf fibration. Next, we deal with locally conformally parallel Spin(9) manifolds in the framework of intrinsic torsion. Finally, we discuss applications of Clifford systems and Clifford structures to Cayley-Rosenfeld planes and to three series of Grassmannians.

Four methods in two different families have been constructed to derive the exact solutions to Benjamin-Bona-Mahony equation in two space dimensions. Simply defined hyperbolic tangent, hyperbolic secant and hyperbolic cosecant ansatzes and the expansion method based on the Sine-Gordon equation in two dimensions are directly substituted into the governing ODE reduced from the two dimensional BBM equation. Classical algebraic method is used to find the relations among the target parameters representing the nonzero coefficients in the predicted solutions and the wave transform parameters. Some complex and real solutions have been constructed in explicit forms.

This paper generalizes the actuator disc theory to the application of crosswind kite power systems. For simplicity, it is assumed that the kite sweeps an annulus in the air, perpendicular to the wind direction (i.e. straight downwind configuration with tether parallel to the wind). It is further assumed that the wind flow has a uniform distribution. Expressions for power harvested by the kite is obtained, where the effect of the kite on slowing down the wind (i.e. the induction factor) is taken into account. It is shown that although the induction factor may be small for a crosswind kite (of the order of a few percentage points), neglecting it in calculations may result in noticeable overestimation of the amount of power harvestable by a crosswind kite system.

This is a quantitative research based on secondary sources of data. The study examines the influence of Chief Executive Officer’s (CEO) compensation on a firm's performance. The objectives of the study were to determine if CEO compensation and firm size do significantly influence a firm’s performance. In other to elicit information to examine the relationship between the variables, the convenience sampling technique, with the combination of both the cross-sectional and time-series data (panel data) were used since they provide greater precision and guard against having an illusory sample. 10 banks quoted on the Nigerian Stock Exchange were sampled for easy accessibility of data. The least square regression technique was used to test the hypotheses of the study. Two hypotheses were tested using panel least square (EViews 8) and from the research work, we summarize the following results; there is a significant relationship between CEO compensation and firm performance in the Nigerian banking industry. In addition, firm size does significantly influence firm performance in the Nigerian banking industry. The study recommends that there should be proper compensation review as this will increase the productivity of the executives. Since increased pay is necessary for the efficiency of the workers, it is advised to ensure a considerable pay as this will ensure for efficiency in the organization. In addition, since the core goal of setting up any business is to make a profit, business organisations should sort out ways at maximising profit and this could include cutting down expenses such as cutting down excessive employees’ pay (CEOs pay especially) and setting apposite pay package for employees. Therefore, policymakers (board of directors) should make an effort to align CEO’s paywith the firm’s capability to pay.

Radical reactions in water or aqueous media are important for organic synthesis, realizing high yielding processes under non-toxic and environmentally friendly conditions. This overview includes (i) a general introduction to organic chemistry in water and aqueous media, (ii) synthetic approaches in-, on- and with-water as well as in heterogeneous phase, (iii) reaction of carbon-centered radicals with water (or deuterium oxide) activated through coordination with various Lewis acids, (iv) photocatalysis in water and aqueous media, and (v) synthetic applications bioinspired from naturally occurring processes. A wide range of chemical processes and synthetic strategies under different experimental conditions have been reviewed that lead to important functional group translocation and transformation reactions, leading to the preparation of complex molecules. These results reveal how water as a solvent/medium/reagent in radical chemistry has matured over the last two decades and how further discoveries are foreseen to come in the near future.

This study presents a detailed assessment on the impact of the Brazilian legal framework related to the access and benefit sharing provisions of the UN Convention on Biological Diversity. The research is based on a comprehensive dataset that was systematically collected over several years, directly from the official government bodies responsible for its implementation. The aim of the study is to contribute to a fact-based discussion on the effectiveness of national ABS laws, focusing on the Brazilian legal framework, first established in the year 2000 and revised in 2015, as a case example. This study balances the costs and benefits of the Brazilian ABS system and assesses the regulatory challenges it poses to individuals, companies, and institutions that perform research, share knowledge, develop, manufacture or market products derived from Brazilian biodiversity. The study indicates that, after over 22 years of operation, the regulatory challenges are still real and relevant, and that the significant volume of data collected from users on access, prior commercialization and shipment of genetic materials abroad was never systematically assessed by the agencies in charge. Besides, it shows that the costs incurred by the government in managing the policy itself have been higher than the economic benefits it has made possible, and that the institutional mechanisms in place since 2015 have not been able to allocate the monetary benefits contributed by users to the National Benefit Sharing Fund to any projects aimed at developing sustainable uses or preserving Brazilian biodiversity.

Gene expression variations of plant leaf are investigated by irradiating seed and leaf with oxygen or air plasmas. Enhancement of leaf growth is induced by oxygen plasma irradiation on seeds, which is supported by increased gene expression for protein synthesis, oxidative-reduction reactions and decreased gene expression concerning DNA methylation and histone modification. Suppression of leaf growth is observed by the oxygen plasma, which would be owing to increased gene expression concerning heat shock protein and redox reaction, and decreased expression of photosynthesis and glycoprotein. Also, gene expression variation due to air plasma irradiation is almost same as that of oxygen plasma. Active oxygen species are major factors in both oxygen and air plasmas for the variation of gene expressions in plant.

It is crucial to forecast the water demand accurately for supplying water efficiently and stably in a water supply system. In particular, accurately forecasting short-term water demand helps in saving energy and reducing operating costs. With the introduction of the Smart Water Grid (SWG) in a water supply system, the amount of water consumption is obtained in real time through an advanced metering infrastructure (AMI) sensor, which can be used for forecasting the short-term water demand. The models widely used for water demand forecasting include the autoregressive integrated moving average, radial basis function-artificial neural network, quantitative multi-model predictor plus, and long short-term memory. However, there is a lack of research on assessing the performance of models and forecasting the short-term water demand by applying the data on the amount of water consumption by purpose and the pipe diameter of an end-use level of the SWG demonstration plant in each demand forecasting model. Therefore, in this study, the short-term water demand was forecasted for each model using the data collected from the AMI, and the performance of each model was assessed. The Smart Water Grid Research Group installed ultrasonic-wave-type AMI sensors in the block 112 located in YeongJong Island, Incheon, and the actual data used for operating the SWG demonstration plant were adopted. The performance of the model was assessed by using the residual, root mean square error (RMSE), normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency (NSE), and Pearson correlation coefficient (PCC) as indices. The water demand forecast was slightly underestimated in models that employed the assessment results based on the RMSE and NRMSE. Furthermore, the forecasting accuracy was low for the NSE due to a large number of negative values; the correlation between the observed and forecasted values of the PCC was not high, and it was difficult to forecast the peak amount of water consumption. Therefore, as the short-term water demand forecasting models using only time and the amount of water consumption have limitations in reflecting the characteristics of consumers, a water supply system can be managed more precisely if other factors (weather, customer behavior, etc.) influencing the water demand are applied.

This paper deals with a non-standard finite difference scheme defined on a quasi-uniform mesh for approximate solutions of the Magneto-Hydro Dynamics (MHD) boundary layer flow of an incompressible fluid past a flat plate for a wide range of the magnetic parameter. We show how to improve the obtained numerical results via a mesh refinement and a Richardson extrapolation. The obtained numerical results are favourably compared with those available in the literature.

In 2010, Parties to the Convention on Biological Diversity (CBD) adopted the Strategic Plan for Biodiversity 2011–2020 to address the loss and degradation of nature. Subsequently, most biodiversity indicators continued to decline. Nevertheless, conservation actions can make a positive difference for biodiversity. The emerging Post-2020 Global Biodiversity Framework has potential to catalyze efforts to ‘bend the curve’ of biodiversity loss. Thus, the inclusion of a goal on species, articulated as Goal B in the Zero Draft of the Post-2020 Framework, is essential. However, as currently formulated, this goal is inadequate for preventing extinctions, and reversing population declines; both of which are required to achieve the CBD’s 2030 mission. We contend it is unacceptable that Goal B could be met while most threatened species deteriorated in status and many avoidable species extinctions occurred. We examine the limitations of the current wording and propose an articulation with robust scientific basis. A goal for species that strives to end extinctions and recover populations of all species that have experienced population declines, and especially those at risk of extinction, would help to align actors towards the transformative actions and interventions needed for humans to live in harmony with nature.

Publicly-funded scientists have a responsibility to engage with the public on scientific information, but are lacking a standardized framework and assessment strategy to do it well. The PEPS (Public Engagement Practices for Scientists) Method is an outcomes-centered framework employing standardized pedagogical methods with quantifiable outcomes. This approach reveals that scientists often have unrealistic expectations for achieving affective learning outcomes (i.e. changing views from anti- to pro-vaccine) by solely cognitive learning strategies (i.e. supplying data). The PEPS Method can serve as a roadmap for standardized science communication assessments, complementing existing science communication training programs for the next generation of scientists.

Since the Sustainable Development Goals (SDGs) came into effect, both UNESCO and other international organisations recommend empowering youth to implement the SDGs in universities. Getting started with the SDGs at university level is of special relevance in pre-service teacher training since future teachers are powerful agents of change in the lives of young people. Future teachers need to acquire competencies in sustainability to be able to promote meaningful changes in sustainable behaviour. To that end, holistic approaches to facilitate their acquirement need to be developed. The aim of this study is to explore which teaching methodologies are suitable for the development of competencies in sustainability in Higher Education (HE) and how to empower students to take a leading role in implementing the SDGs in universities. The participants in the study are a group of 23 students in pre-service teacher training. The experimental educational model used for the development of sustainable competencies consists of a methodological sequence of Project-Oriented Learning (POL) and a Cross-disciplinary Workshop on Sustainable Food. This study provides evidence that a holistic approach is appropriate for developing sustainable competencies and contributes to empowering students to implement SDG 12 at their university.

Human-Computer Interaction, including technology-aided instruction, is beginning to focus on virtual reality (VR) technology due to its ability to support immersive learning, teaching through simulation, and gamification of learning. These systems can deliver high-level multisensory learning experiences that are important in the teaching of many subjects, especially those involving abstract concepts or requiring spatial skills, such as organic chemistry. Haptic experiences with VR, however, remain a challenge. In addition, development have focused on general entertainment/gaming; VR systems in chemistry implement simulations of the chemistry laboratory and other advanced systems whereas those that support safe, game-like, immersive and multisensory learning of organic chemistry with haptics at pre-university education levels are scarce. We developed the VR Multisensory Classroom (VRMC) as an immersive learning environment within a VR head-mounted display, where learners employ hand movements to build hydrocarbon molecules and experience haptic feedback through gloves with built-in sensors and hand-tracking with the Leap Motion system. We report here the evaluation of the first prototype by learners from diverse backgrounds who reported on the ability of the VRMC to support high engagement, motivation, interest and organic chemistry learning as well as diverse learning styles. The VRMC is a novel VR classroom that supports immersive learning in molecular organic chemistry with haptics for multisensory learning.

This article presents a description of a new method for solving the factorization problem, based on the gradient descent algorithm. This approach demonstrates significant improvements in efficiency compared to traditional methods proposed in previous research. This article describes a new method for solving the factorization problem, based on the gradient descent algorithm, and demonstrates the transition from algebraic methods to approaches based on functional analysis. The proposed approach not only improves the efficiency of solving the problem but also allows the application of computational algorithms of functional analysis, opening new possibilities for research and optimization.

Droplet-based microfluidics has revolutionized numerous fields such as biomedical research, pharmaceuticals, drug discovery, food engineering, flow chemistry, and cosmetics. This paper presents a comprehensive study focusing on the detection and characterization of droplets with volumes in the nanoliter range. Leveraging the precise control of minute liquid volumes, we introduced a novel spectroscopic On-Chip microsensor equipped with integrated microfluidic channels for droplet generation, characterization, and sensing, simultaneously. The microsensor, designed with Interdigitated-Ring-Shaped Electrodes (IRSE) and seamlessly integrated with microfluidic channels, offers enhanced capacitance and impedance signal amplitudes, reproducibility, and reliability in droplet analysis. We were able to make analyses of droplets length in the range 1.0-6.0 mm, velocity 0.66-2.51 mm/s, droplet volume 1.07nL-113.46nL. Experimental results demonstrated that the microsensor's has a great performance in terms of droplet size, velocity, and length, with a significant signal amplitude of capacitance and impedance, and real-time detection capabilities, thereby highlighting its potential for facilitating microcapsule reactions and enabling on-site real-time detection for chemical and biosensor analyses on-chip.

A stable driver state is essential in the process of manually transition control, which inevitably occurs in Level 3 automated driving situations. To this end, this paper proposed a CNN algorithm-based driver state monitoring system that uses multi-sensor data such as driver's face image, biometric information, and vehicle behavior information as input. This system calculates the probability of drowsiness for each of the four time periods using a convolutional neural network (CNN) based on ToF camera-based eye blinking, ECG information (pulse rate) embedded in the steering wheel, and vehicle information (steering angle data). In order to build a reliable and high-quality training dataset (Ground Truth) for the CNN algorithm, a baseline was established by matching the driver's face image with the electrocardiogram (ECG) and electroencephalogram (EEG) changes in the drowsy and normal states. In a simulation test of the proposed CNN algorithm using more than 20,000 driver image data acquired using a driving simulator, the TNR was 94.8% and the accuracy was 94.2%. Our proposed method is expected to minimize human errors that may occur when switching control by monitoring inappropriate driver state (drowsiness) in real time.

Since its inception in the late 2000s, blockchain has emerged as a powerful tool for creating trust without intermediaries to incentivize global communities for working for a common goal, such as the improvement of its very ecosystem, its applications and community adoption. While first blockchains were mainly devised for confirming transactions of their innate cryptocurrencies like Bitcoin, smart-contract blockchains like Ethereum can interface with the real-world through so-called “oracles”, which feed trustful off-chain information. This paper introduces digital twins of physical objects and processes as computational oracles to effectively unleash the tremendous opportunity offered by blockchain to the realm of fundamental science, research and technology development (RTD). The crowdsourcing concept is illustrated with the example of centrifugal flow control in microfluidic “Lab-on-a-Disc” (LoaD) systems.

Background: Antiplatelet medications such as aspirin and clopidogrel are used following thrombotic stroke or transient ischemic attack (TIA) to prevent a recurrent stroke. However, the antiplatelet treatments fail frequently, and patients experience recurrent stroke. One approach to lower the rates of recurrence, may be the individualized antiplatelet therapies (antiplatelet therapy modification (ATM)) based on the results of platelet function analysis (PFA). This review was undertaken to gather and analyse the evidence about the effectiveness of such approaches. Methods: We searched Medline, CINAHL, Embase, Web of Science and Cochrane databases to 7 January 2020. Results: Two observational studies involving 1136 patients were included. The overall effects of PFA-based ATM on recurrent strokes (OR 1.05; 95% CI 0.69 to 1.58), any bleeding risk (OR 1.39; 95% CI 0.92 to 2.10) or death hazard from any cause (OR 1.19; 95% CI 0.62 to 2.29) were not significantly different from the standard antiplatelet therapy without ATM. Conclusions: The two studies showed opposite effects of PFA-guided ATM on the recurrent strokes in aspirin non-responders, leading to an insignificant difference in the subgroup meta-analysis (OR 1.59; 95% CI 0.07 to 33.77), while the rates of any bleeding events (OR 1.04; 95% CI 0.49 to 2.17) or death from any cause (OR 1.17; 95% CI 0.41 to 3.35) were not significantly different between aspirin non-responders with ATM and those without ATM. There is a need for large randomized controlled trials which account for potential confounders such as ischemic stroke subtypes, technical variations in the testing protocols, patient adherence to therapy, and pharmacogenetic differences.

The ongoing revolution in Deep Learning is redefining the nature of computing that is driven by the increasing amount of pattern classification and cognitive tasks. Specialized digital hardware for deep learning still holds its predominance due to the flexibility offered by the software implementation and maturity of algorithms. However, it is being increasingly desired that cognitive computing occurs at the edge, i.e. on hand-held devices that are energy constrained, which is energy prohibitive when employing digital von Neumann architectures. Recent explorations in digital neuromorphic hardware have shown promise, but offer low neurosynaptic density needed for scaling to applications such as intelligent cognitive assistants (ICA). Large-scale integration of nanoscale emerging memory devices with Complementary Metal Oxide Semiconductor (CMOS) mixed-signal integrated circuits can herald a new generation of Neuromorphic computers that will transcend the von Neumann bottleneck for cognitive computing tasks. Such hybrid Neuromorphic System-on-a-chip (NeuSoC) architectures promise machine learning capability at chip-scale form factor, and several orders of magnitude improvement in energy efficiency. Practical demonstration of such architectures has been limited as performance of emerging memory devices falls short of the expected behavior from the idealized memristor-based analog synapses, or weights, and novel machine learning algorithms are needed to take advantage of the device behavior. In this work, we review the challenges involved and present a pathway to realize ultra-low-power mixed-signal NeuSoC, from device arrays and circuits to spike-based deep learning algorithms, with ‘brain-like’ energy-efficiency.

Cardiovascular Diseases (CVDs) are still menacing and killing adults worldwide, notwithstanding the tremendous effort, to decrease their related mortality and morbidity. Lately, a growing body of evidences indicated that inflammation plays a pivotal role in the pathogenesis and complications of CVDs. A receptor of the immunoglobulin superfamily, triggering receptor expressed on myeloid cells -1 (TREM-1) was shown to induce and to amplify the inflammation in both acute and chronic diseases pathogenesis and progression and hence it is one of the important factors that complicates CVDs. Thus, studies endeavored to investigate the role played by TREM-1 in CVDs with respect to their etiologies, complications and possible therapeutics. We examined here, for the first time, the most relevant studies regarding TREM-1 involvement in CVDs. We summarized the finding after critically analyzing them and made some suggestions for furtherance of the investigations with the aim to utilize TREM-1 and its pathways for diagnostic, management and prognosis of CVDs. Overall, TREM-1 was found to be involved in the pathogenesis of acute and chronic cardiovascular conditions like Acute myocardial infraction (AMI) and atherosclerosis as well. Although most therapeutic approaches are yet to be elucidated, present research outcome displays a promising future to utilize TREM-1 pathway as potential target to understand and manage CVDs.

Magnetic nanoparticles are met across many biological species ranging from magnetosensitive bacteria, fishes, bees, bats, rats, birds, to humans. They can be both of biogenetic origin and due to environmental contamination, being either in paramagnetic or ferromagnetic state. The energy of such naturally occurring single-domain magnetic nanoparticles can reach up to 10-20 room k_BT in the magnetic field of the Earth, which naturally led to supposition that they can serve as sensory elements in various animals. This work explores within a stochastic modeling framework a fascinating hypothesis of magnetosensitive ion channels with magnetic nanoparticles serving as sensory elements, especially, how realistic it is given a highly dissipative viscoelastic interior of living cells and typical sizes of nanoparticles possibly involved.

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

In this work, the author employs the quantum hydrodynamic formalism to achieve the geometrization of spacetime for describing the gravitational interaction within the framework of quantum theory. This approach allows for the development of an equation of gravity that is mathematically connected to the fermion and boson fields. This achievement is accomplished by incorporating two fundamental principles: covariance of the quantum field equations and the principle of least action. By considering these principles, a theory is established that enables the calculation of gravitational corrections to Quantum Electrodynamics, and potentially, to the standard model of particle physics as well. The theory also provides an explanation for two phenomena: the existence of a cosmological pressure density similar to quintessence, that is compatible with the small value of the observed cosmological constant, and the breaking of matter-antimatter symmetry at high energies offering insights into why there is an imbalance between the two in the early universe. In the cosmological modeling of the theory, there exists a proposal to account for the formation of supermassive black holes that are accompanied by their own surrounding galaxies, without relying on the process of mass accretion. The model, in accordance with recent observations conducted by the James Webb Space Telescope, supports the notion that galactic configurations were established relatively early in the history of the universe, shortly after the occurrence of the Big Bang.

Illicit drug consumption is posing critical concerns in our society causing health issues, crime-related activities, and the disruption of border trade. The smuggling of illicit drugs urges the development of new tools for rapid on-site identification in cargos. Current methods used by law enforcement officers rely on presumptive color tests and portable spectroscopic techniques. However, these methods sometimes exhibit inaccurate results due to commonly used cutting agents, the colorful nature of the sample or because the drugs are smuggled (hidden or mixed) in common goods. Interestingly, electrochemical sensors can deal with these specific problems. Herein, an electrochemical device is presented that uses affordable screen-printed electrodes for the electrochemical profiling of illicit drugs by square-wave voltammetry (SWV). The identification of the illicit compound is based on the oxidation potential of the analyte. Hence, a library of electrochemical profiles is built upon the analysis of illicit drugs and common cutting agents. This library allows the design of a tailor-made script that enables the identification of each drug through a user-friendly interface (laptop or mobile phone). Importantly, the electrochemical test is compared by analyzing 48 confiscated samples with other portable devices based on Raman and FTIR spectroscopy as well as a laboratory standard method (i.e. gas chromatography – mass spectrometry). Overall, the electrochemical results obtained through the analysis of different samples from confiscated cargos at an end-user site, present a promising alternative to current methods, offering low-cost and rapid testing in the field.

Until recently, the classic approach to mineral exploration studies is to bring the field samples/drill cores collected during field studies to the laboratory followed by laborious analysis procedures to generate the analytical data. This is very expensive, time consuming and difficult for exploring vast areas. But rapid technological advances in field portable analytical instruments such as portable ultraviolet–visible and near-infrared spectrophotometers, gamma ray spectrometer, pXRF, pXRD, pLIBS, and µRaman spectrometer have changed this scenario completely and increased their on-site applications in mineral exploration studies. These instruments are currently providing direct, rapid, on-site, real-time, non-destructive, cost-effective identification, and determination of target elements, indicator minerals and pathfinder elements in rock, soil, and sediment samples. These portable analytical instruments are currently helping to obtain accurate chemical and mineralogical information directly in field with minimal or no sample preparation, and providing decision-making support during field work as well as during drilling operations in several successful mineral exploration programs. In this article, the developments in these portable devices, and their contributions in the platinum group elements (PGE), rare earth elements (REE), gold, base metals, and lithium exploration studies both on land and on ocean bed have been summarized with examples.

Cooperation is widely recognized to be challenging for the well-balanced development of human societies. The emergence of cooperation in populations has been largely studied in the context of the Prisoner's Dilemma game, where temptation to defect and fear to be betrayed by others often activate defective strategies. In this paper we analyze the decision making mechanisms fostering cooperation in the two-strategy Stag-Hunt and Chicken games, which include the mixed strategy Nash equilibrium, describing partially cooperative behavior. We find the conditions for which cooperation is asymptotically stable in both full and partial cases, and we show that the partially cooperative steady state is also globally stable in the simplex. Furthermore, we show that the last can be more rewarding than the first, thus making the mixed strategy effective, although people cooperate at a lower level with respect to the maximum allowed, as it is reasonably expected in real situations. Our findings highlight the importance of Stag-Hunt and Chicken games in understanding the emergence of cooperation in social networks.

Homochirality is an obvious feature of life on Earth. On the other hand, extraterrestrial samples contain largely racemic compounds. The same is true for any common organic synthesis. Therefore, it has been a perplexing puzzle for decades how these racemates could have formed enantiomerically enriched fractions as a basis for the origin of homochiral life forms. Numerous hypotheses have been put forward as to how preferentially homochiral molecules could have formed and accumulated on Earth. In this article, it is shown that homochirality of the abiotic organic pool at the time of formation of the first self-replicating molecules is not necessary and not even probable. It is proposed to abandon the notion of a molecular ensemble and to focus on the level of individual molecules. Although the formation of the first self-replicating, most likely homochiral molecule is a seemingly improbable event, on a closer look, it is almost inevitable that homochiral molecules have formed simply on a statistical basis. In this case, the non-selective leap to homochirality would be one of the first steps in chemical evolution directly out of a racemic “ocean”. Moreover, most studies focus on the chirality of the primordial monomers with respect to an asymmetric carbon atom. However, any polymer with a minimal size that allows folding to a secondary structure, would spontaneously lead to asymmetric higher structures (conformations). Most of the functions of these polymers would be influenced by this inherently asymmetric folding. To summarize, simple and universal mechanisms may have led to homochiral self-replicating systems in the context of chemical evolution. A homochiral monomer pool is deemed unnecessary and probably never existed on primordial Earth.

Construction Design Management (DM) involves the coordination of design process and activity to ensure quality project design, yet it involves many challenges. This work reports on a collaborative Knowledge Transfer Project (KTP) that tackled several challenges faced by construction design management practitioners. Employing a design science research methodology (DSRM), qualitative analysis of semi-structured interviews with purposively identified design managers first uncovered real world concerns around design coordination, and designer performance monitoring. Then to address these concerns, a web-based design management prototype dashboard was developed which uses typical project data to aid the management of design coordination activity and facilitate design management task prioritization and reporting functionalities. By digitalizing selected design management processes to improve efficiency, and productivity, the visual reporting capability of the dashboard enables design production to be monitored at project and portfolio levels; trends in designer performance to be assessed and focus to be retained on technical queries (TQs) and requests for information (RFIs). By reporting on the development of this web-based Design Management prototype dashboard and illustrating how it can enhance design management productivity in construction firms, this work also provides further evidence of how employing a design science research methodology in construction can produce practical solutions that address real world construction concerns.

The various methods used to choose the profile shift coefficients, primarily the so-called equalizations, were based on assumed advantages without physical evidence proving them. In this paper a new calculation method is presented for determining profile shift coefficient. The procedure gives the pair of values ​​of the profile shift coefficients, in which case, under the given load, the resulting bending stress will be of the lowest possible value.

The research is focusing on analyzing the concentrations of particulate matter (PM) next to a highly congested road section, with 39,900 as a maximum number of vehicles per 24 h, in the vicinity of Timisoara, Romania. Concentrations have been measured in multiple episodes using two different measurement methods, gravimetric and dynamic light scattering, showing a disperse range of PM concentrations. Presence of metal particles in the samples have been analyzed using an electron microscope. Additionally, impact on human health is described by evaluating results for inhalable, thoracic, and alveolar sized particles.

Loss of photoreceptors in retinal degenerative diseases also impacts the inner retina: bipolar cell dendrites retract, neurons rewire and protein expression changes. ON-bipolar cells represent an attractive target for optogenetic vision restoration. However, above-described maladaptations may negatively impact the quality of restored vision. To investigate this question, we employed human post-mortem retinas and transgenic rd1_Opto-mGluR6 mice expressing the optogenetic construct Opto-mGluR6 in ON-bipolar cells and carrying the retinal degeneration rd1 mutation. We found significant changes in delayed rectifier potassium channel expression in ON-bipolar cells of degenerative retinas. In particular, we found an increase in Kv1.3 expression already in early stages of degeneration. Immunohistochemistry localized Kv1.3 channels specifically to OBC axons. In whole-cell patch-clamp experiments, ON-bipolar cells in the degenerated murine retina were less responsive, which could be reversed by application of the specific Kv1.3 antagonist Psora-4. Notably, Kv1.3 block significantly increased the amplitude and kinetics of Opto-mGluR6-mediated light responses in ON-bipolar cells of the blind retina and increased the signal-to-noise ratio of light-triggered responses in retinal ganglion cells. We propose that reduction of Kv1.3 activity in the degenerated retina, either by pharmacological block or by KCNA3 gene silencing, could improve the quality of restored vision.

In this work we identify combinations of technological activities that signal the presence local capabilities in a country to successfully export a product. We use country-level patent and trade data to generate a multi-layer network, and we apply maximization of entropy to generate synthetic data to effectively divide signal from noise. We show that in several sectors the signal far exceed the noise. Our exercise provides robust evidence of the presence of synergies between technologies to explain trade performances in specific markets. This can be highly useful for policy makers, to inform industrial and innovation policies.

Covariant integral quantization with rotational symmetry SO(3) is established for the quantum motion on this group manifold, or, alternatively, for Gabor signal analysis on this group. We revisit the action of the related (non-unitary) Weyl-Gabor operator on the Hilbert space of square integrable functions on SO(3) and disclose a set of various properties. By selecting weight functions on the corresponding discrete-continuous phase space, one derives related coherent states and Wigner transform.

Liquid manipulation by photoisomerization attracts recent attentions as a new active droplet control method for micro-chemical analysis. Such a non-inverse manipulation can be realized by a use of solution liquid of surfactant that exhibits the \emph{cis}-\emph{trans} isomerization triggered by light irradiation with a specific wavelength such as ultraviolet light. Since the isomerization is accompanied by changes in fluid properties, a light irradiation on one of liquid-air interfaces of a liquid column in a tube would generate differences in the wettability accompanied between the both sides of the finite liquid column. Although this technique has been demonstrated experimentally by Muto et al. (\emph{Euro.~Phys.~J.~Special Topics}, {\bf 226}, 2016, 1199--1205), its dynamics and developments of each isomer distribution are not understood. In order to reveal the liquid-column migration phenomenon, we have performed numerical simulations of air-liquid two-phase flows and its scalar transport of the isomer, using the Volume-of-Fluid method in conjunction with the Continuum-Surface-Force model and Continuous-Species-Transfer method. We validated present results by comparison with experimental result in terms of the migration distance of the liquid column. We confirmed a termination of the liquid-column migration occurs when the \emph{cis} isomer distribution reaches the non-irradiated region. The migration speed was less dependent on the liquid-column length and was proportional to the tube diameter.

The oil and gas industry faces increasing pressure to remove people from dangerous offshore environments. Robots present a cost-effective and safe method for inspection, repair and maintenance of topside and marine offshore infrastructure. In this work, we introduce a new immobile multi-sensing robot, the Limpet, which is designed to be low-cost and highly manufacturable, and thus can be deployed in huge collectives for monitoring offshore platforms. The Limpet can be considered an instrument, where in abstract terms, an instrument is a device that transforms a physical variable of interest (measurand) into a form that is suitable for recording (measurement). The Limpet is designed to be part of the ORCA (Offshore Robotics for Certification of Assets) Hub System, which consists of the offshore assets and all the robots (UAVs, drones, mobile legged robots etc.) interacting with them. The Limpet comprises the sensing aspect of the ORCA Hub System. We integrated the Limpet with Robot Operating System (ROS), which allows it to interact with other robots in the ORCA Hub System. In this work, we demonstrate how the Limpet can be used to achieve real-time condition monitoring for offshore structures, by combining remote sensing with signal processing techniques. We show an example of this approach for monitoring offshore wind turbines. We demonstrate the use of four different communication systems (WiFi, serial, LoRa and optical communication) for the condition monitoring process. By processing the sensor data on-board, we reduce the information density of our transmissions, which allows us to substitute short-range high-bandwidth communication systems with low-bandwidth long-range communication systems. We train our classifier offline and transfer its parameters to the Limpet for online classification, where it makes an autonomous decision based on the condition of the monitored structure.