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.

In the present study, piecewise integrated composite (PIC) bumper beam for passenger cars was proposed and design optimisation process for composite bumper beam against IIHS test was carried out with the help of machine learning. Several elements in IIHS bumper FE model have been assigned to be references, in order to collect training data which, allow the machine learning model to study the method of predicting loading types of each finite element. 2-D and 3-D implementations were provided by machine learning models, which determined stacking sequences of each finite element in PIC bumper beam. It was found that the PIC bumper beam, which was designed by machine learning model has direct impact on reducing the possibility of failure as well as increasing bending strength effectively than conventional composite bumper beam. Moreover, 3-D implementation produced better results compared with 2-D implementation since it was preferable to choose loading type information which was achieved from surroundings when the target elements were located either at corner or junction of planes instead of using information came from the same plane of target.

Integrated assessment modelling (IAM) has been successfully used in the development of international agreements to reduce transboundary pollution in Europe, based on the GAINS model of IIASA. At a national level in the UK a similar approach has been taken with the UK Integrated Assessment Model, UKIAM, superimposing pollution abatement measures and behavioural change on energy projections designed to meet targets set for reduction of greenhouse gas emissions, and allowing for natural and imported contributions from other countries and shipping. This paper describes how UKIAM has been used in development of proposed targets for reduction of fine particulate PM2.5 in the Environment Act, exploring scenarios encompassing different levels of ambition up to 2050 with associated health and other environmental benefits. There are two PM2.5 targets, an annual mean concentration target setting a maximum concentration to be reached by a future year, and a population exposure reduction target with benefits for health across the whole population. The work goes further, to also demonstrate links to social deprivation. There is a strong connection between climate measures aimed at reducing net GHG emissions to zero by 2050 and future air quality, which may be positive or negative, as illustrated by sectoral studies for road transport where electrification of the fleet needs to match the evolution of energy production, and for domestic heating where use of wood for heating is an air quality issue. UKIAM has been validated against air pollution measurements and other modelling, but there are many uncertainties including future energy projections. New work is beginning to link UKIAM directly with the TIMES model addressing future energy projections, to explore different uptake scenarios for hydrogen production and use with respect to air quality.

Soil erosion is one of the most important environmental problems which can have various negative consequences, such as land degradation affecting the sustainable development and the agricultural production, especially for developing countries like Tunisia. Moreover, soil erosion is a major problem around the world because of its effects on soil fertility by nutriment loss and siltation in water bodies. Apart from this, soil erosion by water is the most serious type of land loss in several regions both locally and globally. This study evaluated regional soil erosion risk through the derivation of appropriate factors, using the Revised Universal Soil Loss Equation (RUSLE), which was applied to establish a soil erosion risk map of the whole Tunisian territory and to identify the vulnerable areas of the country. RUSLE model take into account all the factors playing a major role in erosion processes, namely the erodibility of soils, topography, land use, rainfall erosivity and anti-erosion farming practices. The equation is thus implemented under Geographic Information System (GIS) “Arc GIS Desktop”. The results indicated that Tunisia has a serious risk of soil water erosion, showing that 6.43% of the total area of the country is affected by a very high soil loss rate estimated at more than 30 t/ha/year and 4.20% are affected by high mean annual soil loss ranging from 20 to 30 t/ha/year. The most eroded areas were identified in west southern, central and western parts of the country. The spatial erosion map can be used as a decision support document to guide decision-makers towards better land management and provide the opportunity to develop management strategies for soil erosion prevention and control in the global scale of Tunisia.

The ecotoxic effect of glyphosate, a commonly used Parthenium control herbicide, was evaluated in laboratory on biological and fitness attributes of Zygogramma bicolorata. Bioassay of glyphosate was carried within a minimum range of field recommended dose. Indirect exposure experiment reveals that glyphosate caused maximum mortality of 3^rd larval instars, extends the development stages of larvae, pre pupation and pupation. Significant negative effect was observed on sex ratio, fecundity, egg viability and on other fitness attributes. The study demonstrated the non-compatibility of glyphosate and unsafe with Zygogramma bicolorata. The study concludes that owing to acute toxicity of glyphosate at recommended field dose may be used in combination with Z. bicolorata for successful control of Parthenium weed, but needs to be evaluated under natural field conditions.

As a fundamental optical approach to interferometry, Sagnac interference has been widely used for reflection manipulation, precision measurements, and spectral engineering in optical systems. Compared to other interferometry configurations, it offers attractive advantages by yielding a reduced system complexity without the need for phase control between different pathways, thus offering a high degree of stability against external disturbance and a low wavelength dependence. The advance of integration fabrication techniques has enabled chip-scale Sagnac interferometers with greatly reduced footprint and improved scalability compared to more conventional approaches implemented by spatial light or optical fiber devices. This facilitates a variety of integrated photonic devices with bidirectional light propagation, showing new features and capabilities compared to unidirectional-light-propagation devices such as Mach-Zehnder interferometers (MZIs) and ring resonators (RRs). Here, we present our latest results for functional integrated photonic devices based on Sagnac interference. We outline the theory of integrated Sagnac interference devices with comparisons to other integrated photonic building blocks such as MZIs, RRs, photonic crystal cavities, and Bragg gratings. We present our latest results for Sagnac interference devices realized in integrated photonic chips, including reflection mirrors, optical gyroscopes, basic filters, wavelength (de)interleavers, and optical analogues of quantum physics.

Background: The importance of community health psychology in providing complex bio-psycho-social care is well-documented. We present a mixed-method study monitoring the efficacy of health psychology services in the Public Health Focused Model Program for Primary Care Development (2012-2017) in four disadvantaged micro-regions in North-East Hungary. Methods: Study 1 assessed the availability of the services using a sample of 17003 respondents. Study 2 applied a follow-up design to measure the efficacy of the health psychology services in a sample of 132 clients. In Study 3, we conducted focus group interviews to assess clients’ lived experiences. Results: More mental health issues and higher education predicted a higher probability of service use. Follow-up showed that individual and group-based psychological interventions resulted in lower depression and (marginally) higher well-being. Thematic analysis of the focus group interviews indicated that participants deemed topics like psychoeducation, a greater acceptance of psychological support, and heightened awareness of individual and community support important. Conclusions: The results of the monitoring studies demonstrate the important role health psychology services can play in primary health care in disadvantaged regions. Community health psychology can improve well-being, reduce inequality, support the population’s health awareness, and address unmet social needs in disadvantaged regions in Hungary.

Optical microcombs represent a new paradigm for generating laser frequency combs based on compact chip-scale devices, which have underpinned many modern technological advances for both fundamental science and industrial applications. Along with the surge in activity related to optical micro-combs in the past decade, their applications have also experienced rapid progress ‒ not only in traditional fields such as frequency synthesis, signal processing, and optical communications, but also in new interdisciplinary fields spanning the frontiers of light detection and ranging (LiDAR), astronomical detection, neuromorphic computing, and quantum optics. This paper reviews the applications of optical microcombs. First, an overview of the devices and methods for generating optical microcombs is provided, which are categorized into material platforms, device architectures, soliton classes, and driving mechanisms. Second, the broad applications of optical microcombs are systematically reviewed, which are categorized into microwave photonics, optical communications, precision measurements, neuromorphic computing, and quantum optics. Finally, the current challenges and future perspectives are discussed.

As a derivative of graphene, graphene oxide (GO) was initially developed by chemists to emulate some of the key properties of graphene, but it was soon recognized as a unique material in its own right, addressing an application space that is not accessible to chemical vapor deposition based materials. Over the past decade, GO has emerged as a new frontier material with tremendous advances in its material fabrication and quality control over its properties. These in turn have led to rapid progress in GO based photonics, electronics, and optoelectronics concepts and devices, evoking new science and paving the way for many technological breakthroughs with exceptional performance. Here, we review the unique fundamental characteristics of GO, its thin film fabrication methods, patterning techniques, and mechanisms for tuning its material properties. This latter capability in particular has enabled novel advanced functional photonic, electronic, and optoelectronic devices. Understanding these insights is essential for designing and tailoring GO properties for state-of-the-art applications including solar energy harvesting, energy storage, medical diagnosis, image displays, and optical communications. We conclude by discussing the open challenges and exciting opportunities of this field, together with future prospects for major technological advancements and breakthroughs.

Apicomplexan infections, such as giardiasis and cryptosporidiosis, negatively impact a considerable proportion of human and commercial livestock populations. Despite this, the molecular mecha-nisms of disease, particularly the effect on the body beyond the gastrointestinal tract, are still poorly understood. To highlight host-parasite-microbiome biochemical interactions, we utilised integrated metabolomics-16S rRNA genomics and metabolomics-proteomics approaches in a C57BL/6J mouse model of giardiasis and compared these to Cryptosporidium and uropathogenic Escherichia coli (UPEC) infections. Comprehensive samples (faeces, blood, liver, and luminal contents from duo-denum, jejunum, ileum, caecum and colon) were collected 10 days post infection and subjected to proteome and metabolome analysis by liquid and gas chromatographic mass-spectrometry, re-spectively. Microbial populations in faeces and luminal washes were examined using 16S rRNA metagenomics. Proteome-metabolome analyses indicated that 12 and 16 key pathways were sig-nificantly altered in the gut and liver, respectively, during giardiasis with respect to other infections. Energy pathways including glycolysis and supporting pathways of glyoxylate and dicarboxylate metabolism, and redox pathway of glutathione metabolism, were upregulated in small intestinal luminal contents and the liver during giardiasis. Metabolomics-16S rRNA genetics integration in-dicated that populations of three bacterial families –Autopobiaceae (Up), Desulfovibrionaceae (Up) and Akkermanasiaceae (Down) – were most significantly affected across the gut during giardiasis, causing upregulated glycolysis and short-chained fatty acid (SCFA) metabolism. In particular, the perturbed Akkermanasiaceae population seemed to cause oxidative stress responses along the gut-liver axis. Overall, the systems biology approach applied in this study highlighted that the effects of host-parasite-microbiome biochemical interactions extended beyond the gut ecosystem to the gut-liver axis. These findings form the first steps in a comprehensive comparison to ascertain the major molecular and biochemical contributors of host-parasite interactions and contribute towards the development of biomarker discovery and precision health solutions for apicomplexan infections.

In electric circuits, energy is delivered by electromagnetic fields through the space, as suggested by Kraus and Carver. They provide insights by showing electric/magnetic fields and Poynting vector directions around a DC circuit. In this work, the energy flow mechanism by Kraus and Carver is further studied theoretically for arbitrary terminal potentials of a DC power source.

In this paper, we consider a reconfigurable intelligent surface (RIS)-assisted integrated satellite-high altitude platform-terrestrial networks (IS-HAP-TNs) that can improve network performance by exploiting HAP's stability and RIS's reflection. Specifically, the reflector RIS is installed on the side of HAP to reflect signals from the multiple ground user equipments (UEs) to the satellite. To aim at maximising system sum rate, we jointly optimize the transmit beamforming matrix at the ground UEs and RIS phase shift matrix. Due to the limitation of the unit modulus of the RIS reflective elements constraint, the combinatorial optimization problem is difficult to tackle it effectively by traditional solving methods. Based on this, this paper studies deep reinforcement learning (DRL) algorithm to achieve online decision making for this joint optimization problem. In addition, it is verified through simulation experiments that the proposed DRL algorithm outperforms the standard scheme in terms of system performance and execution time, and higher computing speed, making real-time decision making truly feasible。

An upsurge in global population over the years and rapid urbanization have accelerated huge dependence on petroleum-derived fuels and consequent environment concerns owing to green-house gas emissions in the atmosphere. An integrated biorefinery uses lignocellulosic feedstock as raw material for the production of renewable biofuels, and other fine chemicals. The sustain-able bio-economy and the biorefinery industry would benefit greatly from the effective use of lignocellulosic biomass obtained from agricultural feedstocks to replace petrochemical products. Lignin, cellulose, hemicellulose, and other extractives, which are essential components of ligno-cellulosic biomass, must be separated or upgraded into useful forms in order to fully realize the potential of biorefinery. The development of low-cost and green pretreatment technologies with effective biomass deconstruction potential is imperative for an efficient bioprocess. The abun-dance of microorganisms along with their continuous production of various degradative en-zymes makes them suited for the environmentally friendly bioconversion of agro-industrial wastes into viable bioproducts. The present review highlights the concept of biorefinery, ligno-cellulosic biomass and its valorization by green pretreatment strategies into biofuels and other biochemicals. The major barriers and challenges in bioconversion technologies, environmental sustainability of the bioproducts and promising solutions to alleviate those bottlenecks are also summarized.

Community-based case managers in health have been compared to glue which holds the dynamic needs of clients to a disjointed range of health and social services. However, case manager roles are difficult to understand due to poorly defined roles, confusing terminology, and low visibility in New Zealand. This review aims to map the landscape of case management work to advance workforce planning by clarifying the jobs, roles, and relationships of case managers in Aotearoa New Zealand (NZ). Our scoping and mapping review includes peer-reviewed articles, grey literature sources, and interview data from 15 case managers. Data was charted iteratively until convergent patterns emerged and distinctive roles identified. A rich and diverse body of literature describing and evaluating case management work in NZ (n=148) is uncovered with at least 38 different job titles recorded. 18 distinctive roles are further analysed with sufficient data to explore the research question. Social ecology maps highlight diverse interprofessional and intersectoral relationships. Significant innovation and adaptations are evident in this field, particularly in the last five years. Case managers also known as health navigators, play a pivotal but often undervalued role in NZ health care, through their interprofessional and intersectoral relationships. Their work is often unrecognised which impedes workforce development and the promotion of person-centred and integrated health care.

Over 130 countries have committed to reaching net-zero CO2 or GHG emissions by 2050, yet this ambition is rarely underpinned by robust policies. By applying a detailed integrated assessment modelling approach for Brazil, we assess, for the first time, the extent to which the existing and planned local policies could put Brazil on the path to its net zero pledge. This includes quantifying the role of nature-based solutions, such as protection and restoration, and engineered solutions, such as bioenergy with carbon capture and storage (BECCS). We show protection is the single most important climate mitigation measure at relatively low costs, whereas relying heavily on engineered solutions would jeopardise Brazil’s chances of achieving its net zero pledge. We also show that the mismatch between Brazil's short- and long-term climate targets reflects current weak environmental governance. Our analysis reinforces the urgent need for Brazil to eliminate illegal deforestation and go beyond to help fight climate change whilst curbing biodiversity loss.

Enhanced supercontinuum generation (SCG) is experimentally demonstrated in integrated silicon nitride (Si₃N₄) waveguides incorporating highly nonlinear graphene oxide (GO) in the form of two-dimensional (2D) films. On-chip integration of the 2D GO films with precise control of their thickness is realized by using a transfer-free and layer-by-layer coating method. The control of the film length and coating position is achieved via window opening in the upper silica cladding of the photonic integrated chips. Detailed SCG measurements are performed using the fabricated devices with different waveguide geometries and GO film thicknesses, and the results are compared with devices without GO. Significantly improved spectral broadening of ultrashort optical pulses with ultrahigh peaks powers exceeding 1000 W is observed for the hybrid devices, achieving up to 2.4 times improvement in the spectral bandwidth relative to devices without GO. Theoretical analyses for the influence of GO film thickness, coating length, coating position, and waveguide geometry are also provided by fitting the experimental results with theory, showing that there is still significant room for further improvement. This work opens up a promising new avenue towards improving the SCG performance of photonic integrated devices by incorporating functional 2D materials.

Social network analysis (SNA) is an effective method for characterizing networks from various specific perspectives. Global trade contracted sharply in 2020 owing to the COVID-19 pandemic, and growth is expected to be lower than the pre-pandemic trends. This study takes countries worldwide as the primary unit of analysis and uses different procedures of social network analysis (SNA), including network density, centrality, and core-periphery structure, and applies them to the field of trade in electronic integrated circuit products (ICPT). In addition to static and descriptive analysis, this study also uses of tools such as Ucinet 6.732 for visual analysis, visual analysis, and more convenient and precise display of the network structure of ICPT. The important countries play a central role in determining the overall structural features. The core-periphery structure in the network from both spatial and temporal perspectives, data on electronic integrated circuit products for the period 2015-2021 were used in SNA. This study found that the ICPT network became denser from 2015 to 2021 but declined and picked up in 2018 and 2020. Moreover, the core-peripheral structure exists in the ICPT network. The main core network countries are Taiwan, Hong Kong, Singapore, mainland China, Malaysia, Japan, the Philippines, Thailand, Vietnam, and other Asian countries, including the United States and Germany.

Relatives play an important role in mental health service users’ care. Interventions directed either at service users or their relatives may influence the other person as well. The project Activa’t per la salut mental (Get active for mental health) consisted of a series of four interventions addressed at people diagnosed with mental disorders and their relatives to help them in their recovery process, increasing their agency and quality of life. The objective of the present study is to evaluate the interaction of the participation of service users on their relatives’ outcomes and vice versa. The impact of the project was evaluated within an RCT. The treatment group had access to all the circuit interventions while the control group received treatment as usual and could only access one of the interventions. All participants were evaluated at baseline, six months, and twelve months after the end of the first intervention. Service users were evaluated with the Stages of recovery questionnaire, and relatives with the Family Burden Interview Schedule II and the Duke-UNC-11 questionnaires. The interaction between service users and their relatives was analysed by means of correlational analyses within the intervention group. Service users baseline characteristics influenced in the level of participation of relatives and vice versa. The results also indicated an interaction between service users’ recovery score changes on the change of care burden of relatives. Service users’ participation levels interacted with the decrease of relatives’ burden. These results can be extremely helpful in fostering interactive benefits in future projects addressing the wellbeing of mental health service users and their relatives. Future studies could use specific designs to explore the directionality of the causality of these effects.

This paper develops a two-layer optimization approach that provides energy-optimal control for vehicles and traffic signal controllers. The optimizer in the first layer computes the traffic signal timings to minimize the total energy consumption levels of approaching vehicles from upstream traffic. The traffic signal optimization can be easily implemented in real-time signal controllers, and it overcomes the issues in the traditional Webster’s method of overestimating the cycle length when the traffic volume-to-capacity ratio exceeds 50 percent. The second layer optimizer is the vehicle speed controller, which calculates the optimal vehicle brake and throttle levels to minimize the energy consumption of individual vehicles. The A-star dynamic programming is used to solve the formulated optimization problem in the second layer to expedite the computation speed so that the optimal vehicle trajectories can be computed in real-time and can be easily implemented in simulation software for testing. The proposed integrated controller is first tested on an isolated signalized intersection, and then an arterial network with multiple intersections to investigate the performance of the proposed controller under various traffic demand levels. The test results demonstrate that the proposed integrated controller can greatly improve energy efficiency with fuel savings up to 17.7%, at the same time enhancing traffic mobility by up to 47.18% reduction in traffic delay and up to 24.84% reduction in vehicle stops.

The simultaneous advances in artificial neural networks and photonic integration technologies have spurred extensive research in optical computing and optical neural networks (ONNs). The potential to simultaneously exploit multiple physical dimensions of time, wavelength and space give ONNs the ability to achieve computing operations with high parallelism and large-data throughput. Different photonic multiplexing techniques based on these multiple degrees of freedom have enabled ONNs with large-scale interconnectivity and linear computing functions. Here, we review the recent advances of ONNs based on different approaches to photonic multiplexing, and present our outlook on key technologies needed to further advance these photonic multiplexing/hybrid-multiplexing techniques of ONNs.

The development of synthetic biology has enabled us to make massive progress on biotechnology and to approach research questions from a brand new perspective. In particular, the design and study of gene regulatory networks in vitro, in vivo and in silico, have played an increasingly indispensable role in understanding and controlling biological phenomena. Among them, it is of great interest to understand how associative learning is formed at the molecular circuit level. Noticeably, mathematical models have been increasingly used to predict the behaviors of molecular circuits. The Fernando’s model, which is thought to be one of the first works in this line of research using the Hill equation, attempted to design a synthetic circuit that mimics Hebbian learning in the neural network architecture. In this article, we carry out in-depth computational analysis of the model and demonstrate that the reinforcement effect can be achieved by choosing the proper parameter values. We also construct a novel circuit that can demonstrate forced dissociation, which was not observed in the Fernando’s model. Our work can be readily used as reference for synthetic biologists who consider implementing the circuits of this kind in biological systems.

We experimentally investigate power-sensitive photo-thermal tuning (PTT) of two-dimensional (2D) graphene oxide (GO) films coated on integrated optical waveguides. We measure the light power thresholds for reversible and permanent GO reduction in silicon nitride (SiN) waveguides integrated with 1 and 2 layers of GO. Raman spectra at different positions of a hybrid waveguide with permanently reduced GO are characterized, verifying the inhomogeneous GO reduction along the direction of light propagation through the waveguide. The differences between the PTT induced by a continuous-wave laser and a pulsed laser are also compared, confirming that the PTT mainly depend on the average input power. These results reveal interesting features for 2D GO films coated on integrated optical waveguides, which are of fundamental importance for the control and engineering of GO’s properties in hybrid integrated photonic devices.

In recent years, Malaysia has faced environmental challenges caused by municipal solid waste, especially household waste, during the Covid-19 pandemic. Among all the household waste, plastic and paper are the most prominent waste that causes environmental hazards. Several recycling associations in Malaysia have carried out their practices for better waste sustainability and management to curb the increasing amount of household waste. However, the effectiveness is still vague in achieving smart and effective household waste management. Therefore, this paper aims to investigate Malaysia’s household waste management, mainly in three significant municipalities in Malaysia for Kuala Lumpur, Penang and Melaka, in becoming a resilient and sustainable city by addressing two main research questions 1) What are the key factors for ensuring the more success move for future household waste management in cities? and 2) How will the 3 municipalities address their waste issues based on the key factors from RQ1, respectively? This paper reviewed 13 waste management articles and explores the potential of the four factors of waste management from the perspective of technology and data, economy, social and governance. The discussed factors and models contributed to an integrated future-proofing framework that focuses on smart waste tracking, an gamified awareness education, and strict policies to control waste management are the way forward for the future of smart cities household waste management.

Following the development and dissemination of new climate-smart agricultural technologies to farmers globally, there has been an increase in the number of socio-economic studies on the adoption of climate-smart integrated pests’ management (CS-IPM) technologies over the years. In this study, we review empirical evidence on adoption determinants of CS-IPM technologies and identify possible science-policy interfaces. Generally, our review shows that socioeconomic and institutional factors are influential in shaping CS-IPM adoption decisions of farmers. More specifically, income was found to positively influence the adoption of CS-IPM technologies while land size owned influences CS-IPM adoption negatively. Registered land tenure (registered secure rights) positively influences CS-IPM technologies’ adoption, implying that efficient land markets that enable competitive and fair distribution and access to land, more so by the vulnerable but efficient smallholder producers do indeed increase the adoption of CS-IPMs technologies. Social capital, achieved via farmers’ organizations is also central in fostering CS-IPM technologies’ adoption, just as markets reforms that minimize market failures regarding access to credit, labor, and agricultural information, which could indirectly hinder farmers’ use of CS-IPM practices. Functional extension systems that improve farmers’ awareness of CS-IPM do also improve CS-IPM technologies’ adoption. However, the adoption of CS-IPM technologies in Ghana and Benin is slow-paced because of factors like lack of access to farm inputs that facilitate uptake of these technologies, lack of credit facilities, and limited extension services among others. Interestingly, our review confirms that CS-IPM technologies do indeed reduce and minimize the intensity of pesticide usage and foster ecosystem (environmental and human) health. Therefore, this review unearths strategic determinants of CS-IPM adoption and makes fundamental guidance around climate-smart innovations transfer and environmental policies that should be prioritized to curb environmental pollution and ensure agricultural ecosystems’ sustainability.

The easternmost Mediterranean is a distinct transition zone from the ocean to the continent located at the junction between the largest Earth's lithospheric segments: Eurasian and African. The methodology of paleomagnetic mapping of such transition zones is based on integrating the mapping techniques for both continental and oceanic platforms: paleomagnetic reconstructions, results of radiometric dating of magnetized rocks, tectonic-structural reconstructions, biogeography, and utilization of the results of various geophysical surveys. The geodynamic-paleomagnetic mapping makes it possible to reveal the multilevel structural heterogeneity and display complex elements of the geodynamics of different ages inherent in this transition zone. Northern Israel is obviously the most complex area in the easternmost Mediterranean. For the combined paleomagnetic mapping, well-studied paleomagnetically and radiometrically areas were selected: (1) the Carmel area, (2) the Atlit area (internal part of the Carmel area), (3) the Sea of Galilee with the adjoining zones (primarily, the Kinnarot Valley), and (4) the area of the Hula Basin with adjacent areas of the Golan Plateau, Hermon Mt., and Galilea uplift. The constructed paleomagnetic profiles for the Carmel area (on the top of the accumulative surface of the Lower Cretaceous traps), and the Kinnarot Valley – Sea of Galilee – Hula Basin, evidently indicate the complex history of the paleogeodynamic evolution of the region. These studies demonstrate the effectiveness of paleomagnetic mapping integrated with paleomagnetic profiling, crossing these geologically complex areas.

Previous studies reported the physical, transcriptomics and metabolomics changes in in-vitro acute heat stressed bovine granulosa cells. Granulosa cells exhibited transient proliferation senescence, oxidative stress, increased rate of apoptosis, and decline in steroidogenic activity. This study performs joint integration and network analysis of metabolomics and transcriptomics data to further narrow down and elucidate the role of differentially expressed genes, important metab-olites and relevant cellular and metabolic pathways in acute heat-stressed granulosa cells. Among significant (Raw P-value <0.05) metabolic pathways where metabolites and genes did converge, this study found Vitamin B6 metabolism, Glycine, serine and threonine metabolism, Phenylalanine metabo-lism, Arginine biosynthesis, Tryptophan metabolism, Arginine and proline metabolism, Histidine metabolism, and Glyoxylate and dicarboxylate metabolism. Important significant convergent bio-logical pathways included, ABC transporters and Protein digestion and absorption, while func-tional signaling pathways included cAMP, mTOR, and AMPK signaling pathways together with Ovarian steroidogenesis pathway. Among caner pathways, the most important pathway was Central carbon metabolism in cancer. Through multiple analysis query, Progesterone, Serotonin, citric acid, Pyridoxal, L-Lysine, Succinic acid, L-Glutamine, L-Leucine, L-Threonine, L-Tyrosine, Vitamin B6, Choline, and CYP1B1, MAOB, VEGFA, WNT11, AOX1, ADCY2, ICAM1, PYGM, SLC2A4, SLC16A3, HSD11B2 and NOS2 appeared to be important enriched metabolites and genes, respectively. These genes, metabolites, metabolic, cellular and cell signaling pathways com-prehensively elucidate the mechanisms underlying the intricate fight between death and survival in acute heat-stressed bovine granulosa cells, and essentially help further our understanding and future quest of research in this direction.

Recently, hybrid logic circuits based on magnetic tunnel junctions (MTJs) have been widely investigated to realize zero standby power. However, such hybrid CMOS/MTJ logic circuits suffer from a severe sensing reliability due to the limited tunnel magnetoresistance ratio (TMR≤150%) of the MTJ and the large process variation in the deep sub-micrometer technology node. In this paper, a novel differential sensing amplifier (DSA) is proposed, in which two PMOS transistors are added to connect the discharging branches and evaluation branches. Owing to the positive feedback realized by these two added PMOS transistors, it can achieve a large sensing margin. By using an industrial CMOS 40 nm design kit and a physics-based MTJ compact model, hybrid CMOS/MTJ simulations have been performed to demonstrate its functionality and evaluate its performance. Simulation results show that it can achieve a smaller sensing error rate of 9% in comparison with the previously proposed DSAs with the TMR ratio of 100% and process variation of 10%, while maintaining almost the same sensing delay of 74.5 ps and sensing energy of 1.92 fJ/bit.

We experimentally demonstrate enhanced self-phase modulation (SPM) in silicon nitride (Si₃N₄) waveguides integrated with 2D graphene oxide (GO) films. GO films are integrated onto Si₃N₄ waveguides using a solution-based, transfer-free coating method that enables precise control of the film thickness. Detailed SPM measurements are carried out using both picosecond and femtosecond optical pulses. Owing to the high Kerr nonlinearity of GO, the hybrid waveguides show significantly improved spectral broadening compared to the uncoated waveguide, achieving a broadening factor of up to ~3.4 for a device with 2 layers of GO. By fitting the experimental results with theory, we obtain an improvement in the waveguide nonlinear parameter by a factor of up to 18.4 and a Kerr coefficient (n₂) of GO that is about 5 orders of magnitude higher than Si₃N₄. Finally, we provide a theoretical analysis for the influence of GO film length, coating position, and its saturable absorption on the SPM performance. These results verify the effectiveness of on-chip integrating 2D GO films to enhance the nonlinear optical performance of Si₃N₄ devices.

Competing and complementary models of resting-state brain dynamics contribute to our phenomenological and mechanistic understanding of whole-brain coordination and communication, and provide potential evidence for differential brain functioning associated with normal and pathological behavior. These neuroscientific theories stem from the perspectives of physics, engineering, mathematics, and psychology and create a complicated landscape of domain-specific terminology and meaning, which, when used outside of that domain, may lead to incorrect assumptions and conclusions within the neuroscience community. Here we review and clarify the key concepts of Connectivity, Computation, Criticality, and Coherence — the 4C’s — and outline a potential role for metastability as a common denominator across these propositions. We analyze and synthesize whole-brain neuroimaging research, examined through functional magnetic imaging (fMRI), to demonstrate that complexity science offers a principled and integrated approach to describe, and potentially understand, macroscale spontaneous brain functioning.

Nuclear fission technologies have the potential to play a significant role in the energy mix of a net-zero and sustainable society. However, to achieve the sustainability goal two significant challenges remain: efficient and sustainable fuel usage and the minimisation of long term nuclear waste. Civil nuclear molten salt systems and technologies offer the opportunity to address both, delivering future reactors at scale for efficient and effective power production and nuclear waste burnup. Potentially, both objectives could be fulfilled in one reactor system, which could significantly improve sustainability indices. In addition, demand driven development of a significantly reduced fuel cycle with enhanced proliferation resistance offers further potential for improvement. To achieve these goals, a transformative approach for salt clean-up during molten salt reactor operation is proposed in this work, by concentrating on the detection and removal of key neutron poisoning elements which prevent the reactor from long-term operation. This work also demonstrates the importance of the effective integration of physics, reactor design and chemistry when systems modelling in achieving these system development goals.

The building sector of most tropical countries still use predominantly primary biomass as the principal fuel. This has adverse effects like CO2 emission and deforestation and is associated with issues like poverty, ill-health, and low standard of living. Therefore, energy policies try to improve on the efficiency of firewood and charcoal end-use technologies, to palliate the negative effects. In this research, the global change assessment model (GCAM) is used, to investigate the impact of efficiency improvement on the energy consumption pattern of the building sector of developing countries. The aim of the study is to provide empirical data that would better inform policymakers on the effects of modernizing these primary fuels. The study developed three scenarios with different levels of efficiency improvements. The results show that efficiency improvement rather increases primary biomass consumption and CO2 emission. However, there is a fall in the consumption of traditional biomass in the second half of the modelling period. The increase in biomass-based fuels consumption was seen to be linked to their affordability. Therefore, policymakers need not only elaborate policies that improve biomass efficiency, but also introduce and motivate other clean cooking fuels like butane, biogas, and electricity.

With the rapid surge in technological advancements, an equal amount of investment in technology-embedded teaching has become vital to pace up with the ongoing educational needs. Distance education has evolved from the era of postal services to the use of ICT tools in current times. With the aid of globally updated content across the board, technology usage ensures all students receive equal attention without any discrimination. Importantly, web-based teaching allows all kind of students to learn at their own pace, without the fear of being judged, including professionals who can learn remotely without disturbing their job schedules. Having web-based content allows low-cost and robust implementation of the content upgradation. An improved, yet effective, version of the education using such tools is Hybrid Learning (HL). This learning mode aims to provide luxurious reinforcement to its legitimate candidates while maintaining the quality standards of various elements. Incorporated with both traditional and distance learning methods, along with exploiting social media tools for increased comfort level and peer-to-peer collaboration, HL ultimately facilitates the end user and educational setup. The structure of such a hybrid model is realized by delivering the study material via a learning management system (LMS) designed in compliance with quality standards, which is one of the fundamental tackling techniques for controlling quality constraints. In this paper, we present the recently piloted project by COMSATS University Islamabad (previously known as COMSATS Institute of Information Technology) which is driven by technology-embedded teaching model. This model is an amalgam of the traditional class room model with the aid of state-of-the-art online learning technologies. The students are enrolled as full-time students, with all the courses in traditional classroom mode, except one course offered as hybrid course. This globally adapted model helps the students to benefit from both face-to-face learning as well as gaining hands-on experience on technology-enriched education model providing flexibility of timings, learning pace, and boundaries. Our HL model is equipped with two major synchronous and asynchronous blocks. The synchronous block delivers real-time live interaction scenarios using discussion boards, thereby providing a face-to-face environment. Interactions via social network has witnessed equally surging improvement in the output performance. The asynchronous block refers to the lecture videos, slides and handouts, prepared by imminent professors, available 24/7 for students. To ensure quality output, our HL model follows the course learning outcomes (CLOs), and program learning outcomes (PLOs) as per international standards. As a proof of concept, we have deployed a mechanism at the end of each semester to verify the effectiveness of our model. This mechanism fundamentally surveys the satisfaction levels of all the students enrolled in the HL courses. With the surveys already conducted, a significant level of satisfaction has been noted. Extensive results from these surveys are presented in the paper to further validate the efficiency and robustness of our proposed HL model.

Human activities mostly impact the trend and direction of surface water, groundwater, and other river basin resources in the watershed in Africa. Human activities influence river flows and the water quality at both highlands and lowlands. A watershed is indeed a conserved area of land that collects rain and snow and empties or penetrates into ground water sources. The act of managing the activities around the watershed is the Integrated Watershed Management while considering the social, economic, and environmental issues, as well as community interests to manage water resources sustainably. These watersheds, river basins, and groundwater resources provide important services for communities and biodiversity. This paper reveals that the best way to protect groundwater resources is on a watershed basis using IWM. This technique enables us to handle a variety of concerns and objectives while also allowing us to plan in a complicated and uncertain environment. IWM involves cooperation and participation from a wide range of community interests and water users, including municipalities, companies, people, agencies, and landowners, for stakeholders' input to be successful. All of the strategies and plans are produced concerning one another, as well as the overall conditions of the watershed, local land uses, and specific issues.

Ordinary computing machines prohibit self-reference because it leads to logical inconsistencies and undecidability. In contrast, the human mind can understand self-referential statements without necessitating physically impossible brain states. Why can the brain make sense of self-reference? Here, we address this question by defining the Strange Loop Model, which features causal feedback between two brain modules, and circumvents the paradoxes of self-reference and negation by unfolding the inconsistency in time. We also argue that the metastable dynamics of the brain inhibit and terminate unhalting inferences. Finally, we show that the representation of logical inconsistencies in the Strange Loop Model leads to causal incongruence between brain subsystems in Integrated Information Theory.

The total lipid and protein content of the invasive caprellid amphipod Caprella scaura, from the biofouling communities of fish farm cages in the Pagasitikos Gulf were analyzed and compared among seasons. Proteins were the most abundant component (48.5 – 49.3%). Lipid content was relatively lower, with a wider range (6.7 – 34%) and showed a distinct seasonal fluctuation with high values in the winter population and a gradual decrease in spring and summer, with the lowest values in Autumn. Composition of the fatty acids profile was consistent among the seasons, with palmitic (16:0), Oleic (18:1n-9), Eicosapentanoic (20:5n-3)(EPA) and Docosahexanoic acid (22:6n-3 )(DHA) being the most abundant fatty acids. The presence of high levels of EPA and DHA fatty acids makes the species a potential candidate for use of these organisms in aquaculture.

A convolutional neural network (CNN) is sometimes understood as a black box in the sense that while it can approximate any function, studying its structure will not give us any insights into the nature of the function being approximated. In other terms, the discriminative ability does not reveal much about the latent representation of a network. This research aims to establish a framework for interpreting the CNNs by profiling them in terms of interpretable visual concepts and verifying them by means of Integrated Gradient. We also ask the question, "Do different input classes have a relationship or are they unrelated?" For instance, could there be an overlapping set of highly active neurons to identify different classes? Could there be a set of neurons that are useful for one input class whereas misleading for a different one? Intuition answers these questions positively, implying the existence of a structured set of neurons inclined to a particular class. Knowing this structure has significant values; it provides a principled way for identifying redundancies across the classes. Here the interpretability profiling has been done by evaluating the correspondence between individual hidden neurons and a set of human-understandable visual semantic concepts. We also propose an integrated gradient-based class-specific relevance mapping approach that takes the spatial position of the region of interest in the input image. Our relevance score verifies the interpretability scores in terms of neurons tuned to a particular concept/class. Further, we perform network ablation and measure the performance of the network based on our approach.

With compact footprint, low energy consumption, high scalability, and mass producibility, chip-scale integrated devices are an indispensable part of modern technological change and development. Recent advances in two-dimensional (2D) layered materials with their unique structures and distinctive properties have motivated their on-chip integration, yielding a variety of functional devices with superior performance and new features. To realize integrated devices incorporating 2D materials, it requires a diverse range of device fabrication techniques, which are of fundamental importance to achieve good performance and high reproducibility. This paper reviews the state-of-art fabrication techniques for the on-chip integration of 2D materials. First, an overview of the material properties and on-chip applications of 2D materials is provided. Second, different approaches used for integrating 2D materials on chips are comprehensively reviewed, which are categorized into material synthesis, on-chip transfer, film patterning, and property tuning / modification. Third, the methods for integrating 2D van der Waals heterostructures are also discussed and summarized. Finally, the current challenges and future perspectives are highlighted.

A developed six-port reflectometry (SPR) system was integrated to measure the relative permittivity of tumor and normal breast tissue for medical diagnostic purpose. In order to obtain an accurate and precise measurement, the calibration process was done to the SPR using the well-known three-standard technique. Next, the studied dielectric probe was connected to the calibrated measurement-port of the SPR. The open end of the probe aperture was dibbed into the normal and tumor synthetic breast tissue samples to measure the synthetic breast tissues dielectric constant, ɛrʹ, and loss factor, ɛrʺ in the frequency range of 1.5 GHz to 3.3 GHz. Finally, the comparative studies were conducted between commercial VNA with Keysight 85070E dielectric probe and the studied SPR-probe system based on the measured magnitude of the reflection coefficient, phase shift, dielectric constant, and loss factor of the synthetic breast samples. The maximum absolute errors of the measured reflection coefficient magnitude, phase shift, dielectric constant, and loss factor were found to be 0.01, 1.07°, 1.12, and 0.75, respectively. It was ascertained that the predicted dielectric constant, ɛrʹ, is able to differentiate between normal, (ɛrʹ &lt; 50) and tumor, (ɛrʹ &gt; 50) breast tissues.

Integrated photovoltaic-fuel cell (IPVFC) systems, amongst other integrated energy generation methodologies are renewable and clean energy technologies that have received diverse research and development attentions over the last few decades due to their potential applications in a hydrogen economy. This article systematically updates the state-of-the-art of IPVFC systems and provides critical insights into the research and development gaps needed to be filled/addressed to advance these systems towards full commercialisation. The design methodologies, renewable energy-based microgrid and off-grid applications, energy management strategies, optimisations and the prospects as self-sustaining power source were covered. IPVFC systems could play an important role in the upcoming hydrogen economy since they depend on solar hydrogen which has almost zero emissions during operation. Highlighted herein are the progresses as well as the technical challenges requiring research efforts to solve to realise numerous potential applications of IPVFC systems such as in unmanned aerial vehicles, hybrid electric vehicles, agricultural applications, telecommunications, desalination, synthesis of ammonia, boats, buildings, and distributed microgrid applications.

As Solar Photovoltaics in buildings reaches maturity, grid integration and economic yield are topics of greater interest. The traditional design of photovoltaic installations has considered the optimal orientation of photovoltaic modules to be that which yields the maximum annual energy production. The influence of the consumption patterns and the hourly-variable electricity prices implies that this traditional optimal design might not be the most profitable. Using a full-year dataset for a residential installation, alternative installations using canopies and modules attached to the façades are simulated. Simulating the energy balances for different annual consumptions, it is found that the canopy and façade installations offer better self-consumption of the PV produced energy, reflected in a 9% higher self-consumption degree using modules on façades and a 5% using canopies. The economic evaluation under the new electricity tariffs in Spain shows a better profit for PV self-consumption, reducing by more than 2 years the time of return on investment. The analysis of different alternatives for an industrial PV has allowed us to identify several benefits for these orientations, such as an increase in annual energy production of up to 59% over the optimal-producing orientation, that are confirmed after several months of operation.

High efficacy LED lamps combined with adaptive lighting control and greenhouse integrated photovoltaics (PV) could enable the concept of year-round cultivation and become a feasible option even in the harsh climate of the Nordic countries. Meteorological satellite data of this region was analyzed in a parametric study to evaluate the potential of these technologies. The generated maps showed monthly average temperatures fluctuating from -20°C to 20°C throughout the year. The natural photoperiod and light intensity also changed drastically, resulting in monthly average daily light integral (DLI) levels ranging from 45-50 mol·m-2·d-1 in summer and contrasting with 0-5 mol·m-2·d-1 during winter. To compensate, growth room cultivation independent from outdoor conditions could be used in winter. Depending on the efficacy of the lamps, the electricity required for sole-source lighting at 300 µmol·m-2·s-1 for 16 hours would be between 1.4 and 2.4 kWh·m-2·d-1. Greenhouses with supplementary lighting could help start the cultivation earlier in spring and extend it further into autumn. The energy required for lighting highly depends on several factors such as the natural light transmittance, the light threshold settings and the lighting control protocol, resulting in electric demands between 0.6 and 2.4 kWh·m-2·d-1. Integrating PV on the roof or wall structures of the greenhouse could offset some of this electricity, with specific energy yields ranging from 400 to 1120 kWh·kWp-2·yr-1 depending on the region and system design.

A method for calibrating models of agricultural production and resource use presented by Howitt [1] for policy analysis is proposed to leverage multidisciplinary agricultural research at the National Center for Alluvial Aquifer Research (NCAAR). An illustrative example for Sunflower County, MS is presented to show how plot-level research can be extended to draw systemic region or basin wide implications. A hypothetical improvement in yields for dryland soybean varieties is incorporated to the model and shown to have a positive impact on aquifer outcomes and producer profits. The example illustrates that a change in one practice-crop combination can have system-wide impacts as evidenced by the change in acreages for all crops and practices.

A single farmed fish species assimilates about 20% of the nutrients in the supplied diet. This study evaluated if the culture of complementary ecological-function species can recover nutrients dispersed into the water and transform them into high-valued biomass. A completely randomized experiment was designed with three treatments and four replications of each production system: monoculture of lambari (Astyanax lacustris); integrated aquaculture of lambari and Amazon river prawn (Macrobrachium amazonicum); and integrated aquaculture of lambari, Amazon river prawn, and curimbatá (Prochilodus lineatus). Fingerlings of lambari (0.8 ± 0.8 g) were stocked in twelve earthen-ponds (0.015 ha) at the density of 50 fish m^-2. Eight ponds, were stocked with juveniles of Amazon river prawn (1.1 ± 0.2 g) at the density of 25 prawn m⁻². Four of these eight ponds were stocked with curimbatá fingerlings (0.2 ± 0.1 g) at a density of 13 fish m^-². Only lambari was fed twice a day with an extruded commercial diet. The experiment lasted 60 days when lambari attained commercial size. The inclusion of prawn increased the total species yield from 1.8 to 2.4 t ha^-1 cycle^-1 and reduced the feed conversion ratio (FCR) from 2.5 to 1.8. The inclusion of prawn and curimbatá increased the total yield to 3.2 t ha^-1 cycle^-1 and reduced the FCR to 1.4. Therefore, the integrated culture of lambari, prawn, and curimbatá improves the use of space, water, feed, and benthic species can recover the large quantity of nutrients accumulated in the bottom of lambari pond production, converting them into high-nutritional and monetary-valued biomass.

Multichannel EEGs were obtained from healthy participants in the eyes-closed no-task condition (where the alpha component is typically abolished). EEG dynamics in the two conditions were quantified with two related binary Lempel-Ziv measures of the first principal component and with three measures of integrated information including the more recently proposed integrated synergy. Both integrated information and integrated synergy with model order p=1 had greater values in the eyes closed condition. If the model order of integrated synergy was determined with the Bayesian Information Criterion, this pattern was reversed, and in common with other measures, integrated synergy was greater in the eyes open condition. Eyes open versus eyes closed separation was quantified by calculation of the between-condition effect size. Lempel-Ziv complexity of the first principal component showed greater separation than the measures of integrated information. The performance of the integrated information measures investigated here when distinguishing between indisputably different physiological states encourages caution when advocating for their use as measures of consciousness.

Research Infrastructures (RIs) are essential to achieve excellence in innovative scientific research. However, because of limited land availability and specific geological requirements, evaluating the viability of a site for a new RI can be a challenging task. Stringent safety construction requirements include developing site-specific architectural and geoengineering solutions, minimizing construction disturbances, and reinforcing rock and soil in a timely fashion. For successful development of the RIs in China, such as the Daya Bay Neutrino Laboratory (DBNL), and the China Spallation Neutron Source (CSNS), an integrated approach of joint geophysical methods including the electrical resistivity tomography (ERT), controlled-source audio-frequency magneto telluric (CSAMT)), gravity and seismic refraction methods, and geological mapping and surveys were carried out. Geophysical parameters, such as electrical resistivity, density, and seismic velocity show inverse proportion to the degree of rock fracturing or weathering. The results show that the low values of geophysical parameters suggest the weathered/fractured rock, while high values reveal the fresh bedrock. The Engineering Geological Suitability Index (EGSI) value can represent the individual EGSI values at a constant and summed over varying depths. EGSI methodology is an improvement on the existing siting process, and has been applied this to CSNS. Our integrated approach provides clearer insight of the subsurface for site suitability of RIs in challenging engineering geological conditions, and removes any ambiguity caused by a single geophysical parameter. The obtained geological knowledge of the area not only provides engineers with much-needed information about the construction conditions of a potential site, but also gives scientists the opportunity to explore the local geology. In this study, we demonstrate our innovative approach for siting RIs, as demonstrated by the synthetic evaluation of the site location and utilization for two established RIs (DBNL and CSNS).

This paper discusses the use of a participatory approach to assess the level of understanding of the Water-Energy-Climate Change nexus in South Africa. The aim is to facilitate the development of well-coordinated, systematic, and holistic strategies for efficient management of the nexus and its implications in the country. The assessment was guided by the broader Integrated Water Resource Management framework, which promotes a participatory approach in the administration of water resources. The paper argues that despite the reasonable level of understanding of WECC, there is still a lack of integrated policy development and planning among key stakeholders. This is exacerbated by limited coordination and consultation among these stakeholders, particularly policymakers. This necessitates the urgent adoption of holistic and systems thinking approaches, and the promotion of collaboration among different stakeholders mandated to manage WECC sectors. Until such approaches are adopted, the WECC nexus will continue to impede the country’s socio-economic development and environmental wellbeing.

Introduction: Due to COVID-19 pandemic, performance of many program has been declined and Tuberculosis (TB) program is not an exception. TB case detection and notification has been recognized as one of worst hit area. The objective of this study was to explore the TB notification status of India during this pandemic and explore options to mitigate the issue. Methods: A secondary data analysis was performed on open source TB notification database of India. Relevant literature review was done to find out remedies based on the different initiative taken by different states of India. Results: In 2020, total TB notification decreased in all the states in comparison to 2019. The percentage of loss in the country was 34%. Private TB notification also decreased in 2020 in all the states except in Jharkhand. The percentage of loss in private TB notification in the country was 35%. Notification started declining in the month of February 2020 and it was lowest in the month of April-2020. The trend of notification began to improve since May 2020 when the States started taking innovative initiatives like Integrated TB Covid Case Search. Conclusion: Due to the ongoing COVID-19 pandemic the notifications of TB cases declined noticeably which has a serious implication in terms of silent spread within household and community. But the picture can be improved with integrated approach for TB-COVID case finding and management.

Negative feedback to the back gate of MOS devices available in FD-SOI technologies can be used to improve linearity of operational amplifiers. Two operational amplifiers designed and fabricated in a 22nm FD-SOI technology illustrate this technique, its advantages and limitations.

We demonstrate a compact 4x4 wavelength selective switch with 50 % fewer electrical pads as compared with our previous generation. We report loss and crosstalk for different paths of the switch. We measure median loss of 5.32 dB and worst case crosstalk of -35 dB. The microring resonators tune by more than one free spectral range, which is an improvement over our previous generation of switches. This switch can support 8 channels at 400 GHz spacing. We conclude that it is not possible to drive both microring resonators with the same voltage and separate control is required because of fabrication variation of the current technology.

In this paper, we review devices used in silicon photonic switches. Devices in switches are divided into active and passive devices. Active devices consist of microring resonator, contra directional couplers, mach zhender switches. Passive devices consist of waveguide crossings and arrayed waveguide gratings. We also list the state of the art in devices in a comparison table.

We report a micro-ring resonator with adiabatic bends, non contact waveguide heaters and small bend radius. The ring has the lowest reported off resonance loss and can support 8 wavelength division multiplexed channels at 200 GHz spacing. We measure 0.49 nm/mW tuning efficiency and 0.085 dB off resonance loss.

Susceptibility to economically-important diseases of grapes is critical to the evaluation of germplasm recommended for commercial production and for development of sustainable production systems. In 2018-2019, nine cold-hardy grape cultivars including ‘Brianna’, ‘Crimson Pearl’, ‘Itasca’, ‘Louise Swenson’, ‘Marechal Foch’, ‘Marquette’ ‘Petite Pearl’, ‘St. Pepin’, and ‘Verona’ were evaluated on non-treated vines for susceptibility to downy mildew, powdery mildew, black rot, anthracnose, Phomopsis leaf spot and fruit rot, and Botrytis bunch rot. No cultivars were consistently disease-free, and all exhibited some degree of black rot and powdery mildew infection. Relative susceptibility to disease was not consistent across both years, but ‘Brianna’ had greater incidence of black rot and ‘Louise Swenson’ showed lower incidence of powdery mildew in both years. The relatively new cultivars ‘Crimson Pearl’ and ‘Verona’ exhibited comparatively moderate disease susceptibility overall. Growers typically manage diseases with fungicides on commercial farms, so cultivar susceptibility is just one component of a sustainable pest management and production system.

We present a simulation library in Python 3 called Lumos. Different optimization routines areimplemented using multiple instruments. Automated measurements are implemented in this librarywhich lead to faster measurements as compared to manual sweeps. We elaborate on the experimentalmethods and also example usage is mentioned.

The article is focused on detailed framework process for hierarchized construction of periodic freight train paths (PFTPs) – allocation of pre-arranged railway capacity to freight rail operators. The framework process considers fluctuations in demand for capacity from freight rail opera-tors, so the quality of a freight train path is related with its construction priority. Introduced framework process aims to offer freight rail operators attractive train paths, with low number of scheduled stops, and this way enhance competitiveness and decrease energy consumption of freight railway as a factor for sustainable development. The proposed generic process is in-tended for all time horizons of capacity allocation. Correctness of the framework process is tested on the example of mainline Prague – Dresden, in the context of prospective (denser) mod-el passenger timetable.

In mountain communities like Sebei, Uganda, that are highly vulnerable to emerging and reemerging infectious diseases, community-based surveillance plays an important role in the monitoring of public health hazards. In this survey, we explored capacities of Village Health Teams (VHTs) in Sebei communities of Mount Elgon in undertaking surveillance tasks for emerging and reemerging infectious diseases in the context of a changing climate. We used participatory epidemiology techniques to elucidate VHTs’ perceptions on climate change and public health and assess their capacities in conducting surveillance for emerging and reemerging infectious diseases. Overall, VHTs perceived climate change to be occurring with wider impacts on public health. However, they have inadequate capacities in collecting sur-veillance data. The VHTs lack transport to navigate through their communities and have in-sufficient capacities in using mobile phones for sending alerts. They do not engage in reporting other hazards related with the environment, wildlife and domestic livestock that would ac-celerate infectious disease outbreaks. Records are not maintained for disease surveillance ac-tivities and the abilities of VHTs to analyze data are also limited. However, VHTs have access to platforms that can enable them to disseminate public health information. The VHTs thus need to be retooled to conduct their work effectively and efficiently through equipping them with adequate logistics and knowledge on collecting, storing, analyzing, and relaying data, which will improve infectious disease response and mitigation efforts.

One of the important research directions in the field of photovoltaics is integration with construction. The integration of solar cell systems with a building can reduce installation costs and help optimize the used space. One of the interesting types of cells is dye-sensitized solar cells. In addition to their interesting properties, they also have aesthetic value. In the classic arrangement, they are constructed using glass with a transparent conductive layer (TCL). This article describes replacing a classic glass counter electrode with an electrode based on a ceramic tile and nickel foil. This solution makes it possible to expand their construction applications. The advantage of this solution is full integration with construction while simultaneously generating electricity. A dye-sensitized solar cell was built layer-by-layer on ceramic tile and nickel foil. An atomization method was used to deposit fluorine-doped tin oxide, and then a screen printing method was used to deposit a platinum layer. The electrical parameters of the manufactured DSSCs with and without a counter electrode tile were characterized by measuring their current-voltage characteristics under standard AM 1.5 radiation. A dye-sensitized solar cell integrated with ceramic tiles and nickel foil was produced and displayed an efficiency of over 4%.

The concerning worldwide increase of obesity and chronic metabolic diseases such as T2D, dyslipidemia, and cardiovascular disease motivates further investigations into preventive and alternative therapeutic approaches. Over the past decade, there is growing evidence that the formation and activation of thermogenic adipocytes (brown and beige) may serve as therapy to treat obesity and its associated diseases owing to its capacity to increase energy expenditure and to modulate circulating lipids and glucose levels. Thus, understanding the molecular mechanism of brown and beige adipocytes formation and activation will facilitate the development of strategies to combat metabolic disorders. Here, we provide a comprehensive overview of pathways and players involved in the development of brown and beige fat as well as the role of thermogenic adipocytes in energy homeostasis and metabolism. Also, we discuss the alterations in brown and beige adipose tissue function during obesity and, explore the therapeutic potential of thermogenic activation to treat metabolic syndrome.

Zimbabwe has ambitious and laudable GHG mitigation targets. Compared to a coal based future emissions reductions by 33% per capita by 2030 are targeted, by implementing a set of identified nationally determined contributions (NDCs). If historical climate conditions continue, it can do this at low or negative cost. However, anticipated conditions may not continue, and of the planned emissions reductions in the NDCs, 88% would come from the expansion of hydropower, which is driven by rainfall. If climate change causes the extreme droughts witnessed in recent years to become more frequent, embarking on Zimbabwe’s NDC future (underpinned by its official system development plan) may be expensive and further cripple the economy. Note that the economy is already being strangled by constrained power supplies due to unusually dry conditions in the Zambezi river basin. If the NDC Future is pursued, but the climate becomes drier, proactive efforts might be made to overcome the power shortages. However, this may result in a rapid ramp up of greenhouse gas emissions if the country turns to coal to reinforce its system and increase its resilience against hydropower vulnerability and the costs that would otherwise ensue. If the country were to keep its NDC investments and supplement them with more aggressive deployment of clean adaptation options, strongly positive outcomes appear possible. Specifically, this would require increased deployment of renewable energy technologies, a restructured power market, and deep increases in energy efficiency investments. In so doing, the country would not only exceed its NDC targets, but also reduce costs in a manner that is climate resilient. This would not remove the country's need for hydropower and some level of coal reliance. However, it will introduce requirements to ensure flexibility in both hydropower and coal power production. For hydropower, power stations will need to provide and be recompensed for providing ‘balancing services’, that is, storing water and producing electricity when the wind is not blowing, nor sun shining. In order to ensure continuous output from mines, it may require intelligent stockpiling combined with dynamic forecasting. This would apply not only to production in Zimbabwe, but potentially for neighboring countries. Doing so would allow predictable mining activities, but allow electricity systems to absorb low cost, low carbon hydropower at high rainfall periods. To make the NDCs resilient via clean adaptation, strong institutional restructuring is required. However, internalizing those costs and moving to advanced market structures and business cases may strain the capacity of current institutions.

Silicon-based photonic integrated circuit (PIC) is a research focus in producing high-density photonics. One of the potential applications of silicon PIC is the sensing and measurement system. In this work, we use the one-dimensional photonic crystal (1D-PhC) cavity design which and utilize it at the PIC level design. The 1D PhC design used as the compact model has the same characteristics as experimentally demonstrated in previous works. The compact model is made from the S-parameter extraction of the 1D-PhC device which is done by using Lumerical FDTD software. The PIC design integrates the 1D-PhC device as a sensing component with a PN-phase shifter (PN-PS) to function as a refractive index (RI) sensor calibration or tuning circuit. A custom design of PN-PS device is used by simulating and extracting the bias voltage-effective index (bias-Neff) data by using Lumerical DEVICE and MODE into the circuit simulator. The circuit-level simulation is done by using Lumerical Interconnect software. Finally, we show the GDSII layout design of the 1D-PhC based photonic sensor calibration circuit with an analysis of generic silicon PIC design rules. The designed PIC is applicable for the bio-sensing applications and photonic SOC component. This work also shows the promise of PIC design approach for further PIC development.

We propose and theoretically investigate integrated photonic filters based on coupled Sagnac loop reflectors (SLRs) formed by a self-coupled wire waveguide. By tailoring coherent mode interference in the device, three different filter functions are achieved, including Fano-like resonances, wavelength interleaving, and varied resonance mode splitting. For each function, the impact of device structural parameters is analyzed to facilitate optimized performance. Our results theoretically verify the proposed device as a compact multi-functional integrated photonic filter for flexible spectral shaping.

The World Health Organization has developed the Integrated Care of Older People (ICOPE) strategy, a program based on the measurement of intrinsic capacity (IC) as “the composite of all physical and mental attributes on which an individual can draw”. Multicomponent interventions appear to be the more effective approach to enhance IC and to prevent frailty and dependence, being adapted physical activity is the preventive intervention that has shown more evidence in the treatment of frailty and risk of falls. The present study aims to describe the development of a multi-domain group-based intervention addressed to frail older people living in the community aimed to improve and/or maintain intrinsic capacity by means of promoting physical activity, healthy nutrition, and psychological wellbeing in frail older people. We used the GUIDED checklist to describe the development process of AMICOPE (Aptitude Multi-domain group-based intervention to improve and/or maintain IC in frail Older PEople). The intervention was built upon the ICOPE framework and it is described with Template for Intervention Description and Replication (TIDieR) guidelines and it includes dietary advice, cognitive stimulation strategies, medication review, goal setting, and activities to strengthen social support and manage depressive symptoms, as well as strength, balance and flexibility exercise using the Vivifrail program. The study represents the first stage of the UK Medical Research Council framework for developing and evaluating a complex intervention. The next step should be carrying out a feasibility study for the AMICOPE intervention, and in a later stage, assessing the effectiveness in a randomized controlled trial.

The exponential growth of population and the consistent food demand has compelled humanity to seek alternatives to traditional farming and innovative technologies to increase production. Exploring offshore for natural resources and alleviating pressure on land has been an ongoing research field, especially in the energy and aquaculture sector. However, the idea of floating farming is still in its infancy and requires significant innovations. The work presented here shed further light on this area by proposing a comprehensive model of ‘Integrated, multicultural, Multileveled Floating Farm (MFF).’ Various aspects of planning, design, constructions and operations of such MFF are discussed. An integrated waste management system is proposed to improve sustainability. The conceptual design and associated financial analysis demonstrated that such integration of various modes of farming could be profitable and sustainable at the same time. The cost estimation and profit analysis are presented in the context of Singapore, and a conservative approach is followed for the calculation. However, the model can easily be extended for application in other countries.

This topical review describes the results of recent research into and development of silicon nitride, a ceramic material with unique properties. The outcome of this ongoing research strongly encourages the use of monolithic silicon nitride and coatings as contemporary and future biomaterial for a variety of medical applications. Crystallographic structure, synthesis and processing of monolithic structures and coatings, and examples of their medical applications are covered that relate to spinal, orthopedic and dental implants, bone grafts and scaffolds, platforms for intelligent synthetic neural circuits, antibacterial and antiviral particles and coatings, optical biosensors, and nano-photonic waveguides for sophisticated medical diagnostic devices. The examples provided show convincingly that silicon nitride is destined to become a leader to replace titanium and other entrenched biomaterials in many fields of medicine.

Species distribution models have become tools of great importance in ecology since the advanced knowledge of suitable habitat of species is needed in the process of the world's biodiversity conservation. Models that use presence-only data are of great interests and are widely used in ecology due to their easy access. However, these models do not estimate accurately the true spatial species distribution based solely on presence-only data since they do not account for biases induced by the sampling techniques used and imperfect detection. To address this gap, Hierarchical integrated models have been recently introduced. Through this study, we assessed the relative performance of these new SDMs models using simulated data. The performance of the models was tested by comparing the estimates of parameters of the distribution models they provide with parameters used to simulate the distribution of the virtual species. The best model was the one whose estimates were close to the true distribution parameters of the virtual species. Results showed that analyzing Presence-only data in conjunction with Point-counts data through the Dorazio's Hierarchical model produced estimates of the coecients of the species intensity models with high precision and less bias while the Koshkina integrated model showed poor performance. Site-occupancy data, being not informative of species abundance, did not allow reducing biases in Presence-only data. The Dorazio's Hierarchical model produced estimates with high precision even with low detection probability. We have also found that the species rarity tends to in ate the variability of the models' estimates making modelling abundant species to be more accurate than modelling less abundant species. Hence, to model the species distribution with high precision based on Presence-only data, additional Point-counts data are required to account for sampling bias and imperfect detection.

Advanced image processing will be crucial for emerging technologies such as autonomous driving, where the requirement to quickly recognize and classify objects under rapidly changing, poor visibility environments in real time will be needed. Photonic technologies will be key for next-generation signal and information processing, due to their wide bandwidths of 10’s of Terahertz and versatility. Here, we demonstrate broadband real time analog image and video processing with an ultrahigh bandwidth photonic processor that is highly versatile and reconfigurable. It is capable of massively parallel processing over 10,000 video signals simultaneously in real time, performing key functions needed for object recognition, such as edge enhancement and detection. Our system, based on a soliton crystal Kerr optical micro-comb with a 49GHz spacing with >90 wavelengths in the C-band, is highly versatile, performing different functions without changing the physical hardware. These results highlight the potential for photonic processing based on Kerr microcombs for chip-scale fully programmable high-speed real time video processing for next generation technologies.

We present theoretical designs of high performance optical filters in integrated silicon photonic nanowire resonators. We use mode interference in formed by zig-zag waveguide coupled Sagnac loop reflectors (ZWC-SLRs), tailored to achieve diverse filtering functions with good performance. These include compact bandpass filters with improved roll-off, optical analogues of Fano resonances with ultrahigh spectral extinction ratios (ERs) and slope rates, and resonance mode splitting with high ERs and low free spectral ranges. The analysis verifies the feasibility of multi-functional integrated photonic filters based on ZWC-SLR resonators for flexible spectral engineering in diverse applications.

The efficiency of microbial inactivation in water is highly dependent on the type of treatment technology used as well as the characteristics of the water to be treated. Wastewater from poultry slaughterhouses carries a significant number of microorganisms posing threat to humans and the environment in general. Therefore, the treatment of poultry slaughterhouse wastewater requires the use of appropriate purification systems with high removal efficiency for microbial agents. In this study, the performance of an integrated treatment plant with electrolysis, ultrafiltration, and ultraviolet radiation as the principal treatment units is investigated in terms of microbial inactivation from poultry slaughterhouse wastewater. In this case, Total microbial number, Total coliform bacteria, Thermo-tolerant coliform bacteria, Pathogenic flora, including Salmonella coliphages, Spores of sulfite-reducing clostridia, Pseudomonas aeruginosa, and Staphylococcus aureus Enterococcus were studied. About 63.95% to 99.83% of the microbes were removed by the EC treatment unit, as well as 99.86% to 100% removal efficiency was achieved after the combined treatment. However, the Pseudomonas aeruginosa was the only microbial agent detected in the final effluent after the combined treatment. The phenomenon suggests that an upgrade to the treatment plant may be required to achieve 100% removal assurance for Pseudomonas aeruginosa.

The efficiency of microbial inactivation in water is highly dependent on the type of treatment technology used as well as the characteristics of the water to be treated. Wastewater from poultry slaughterhouses carries a significant number of microorganisms posing threat to humans and the environment in general. Therefore, the treatment of poultry slaughterhouse wastewater requires the use of appropriate purification systems with high removal efficiency for microbial agents. In this study, the performance of an integrated treatment plant with electrolysis, ultrafiltration, and ultraviolet radiation as the principal treatment units is investigated in terms of microbial inactivation from poultry slaughterhouse wastewater. In this case, Total microbial number, Total coliform bacteria, Thermo-tolerant coliform bacteria, Pathogenic flora, including Salmonella coliphages, Spores of sulfite-reducing clostridia, Pseudomonas aeruginosa, and Staphylococcus aureus Enterococcus were studied. About 63.95% to 99.83% of the microbes were removed by the EC treatment unit, as well as 99.86% to 100% removal efficiency was achieved after the combined treatment. However, the Pseudomonas aeruginosa was the only microbial agent detected in the final effluent after the combined treatment. The phenomenon suggests that an upgrade to the treatment plant may be required to achieve 100% removal assurance for Pseudomonas aeruginosa.

Plant diseases cause losses of approximately 16% globally. Thus, management measures must be implemented to mitigate losses and guarantee food production. In addition to traditional management measures, resistance induction and biological control have gained ground in agriculture due to their enormous potential. Endophytic fungi colonize plant tissues internally and have the potential to act as biological control agents, as elicitors in the process of resistance induction and in attenuating abiotic stresses. In this review, we list the action of this group of microorganisms as potential agents which can act in controlling plant diseases and describe several examples in which endophytes were able to reduce the damage caused by pathogens and adverse conditions. This is due to their arsenal of molecules generated during the interaction by which they form a kind of biological shield in the plant. Studies on these microorganisms have grown due to the existing diversity and the multiple benefits they can offer. Finally, considering that endophytic fungi can be an important tool in managing diseases due to the large amount of biologically active substances produced, bioprospecting this class of microorganisms is tending to increase and generate valuable products.

The primary cilium plays a pivotal role during embryonic development of vertebrates. It acts as a somatic signaling hub for specific pathways, such as sonic hedgehog signaling. In humans, mutations in genes that cause dysregulation of ciliogenesis or ciliary function lead to severe developmental disorders called ciliopathies. Beyond its obvious role in early morphogenesis, growing evidence points towards an essential function of the primary cilium in neural circuit formation in the central nervous system. However, very little is known about a potential role in the formation of the peripheral nervous system. Here, we investigated the presence of the primary cilium in neural crest cells and their derivatives in the trunk of the developing chicken embryo in vivo. We found that neural crest cells, sensory neurons, and boundary cap cells all bear a primary cilium during key stages of early peripheral nervous system formation. Moreover, we described differences in the ciliation of neuronal cultures of different populations from the peripheral and central nervous system. Our results offer a framework for further in vivo and in vitro investigations on specific roles that the primary cilium might play during peripheral nervous system formation.

We report an all-optical radio-frequency (RF) spectrum analyzer with a bandwidth greater than 5 terahertz (THz), based on a 50-cm long spiral waveguide in a CMOS-compatible high-index doped silica platform. By carefully mapping out the dispersion profile of the waveguides for different thicknesses, we identify the optimal design to achieve near zero dispersion in the C-band. To demonstrate the capability of the RF spectrum analyzer, we measure the optical output of a femtosecond fiber laser with an ultrafast optical RF spectrum in the terahertz regime.

Statistical management policy and system plays significant role in development of any nation as it guides the planner to analyze the gaps, design programs and allocate budget in efficient manner. Globally, design and usage of statistical management system varies relying on country specific ability and resources availability. Government of Nepal has been managing database in individual as well as thematic manner. Policy wise, thematic database is in operation based on Statistics Act 1958 and individual database is in operation based on Birth, Death and Other Personal Related Events Registration Act 1976. Though civil registration related policies have been either updated or newly formed, sectoral statistic management related policy has not been updated since its first promulgation period (1958). With no policy supporting the consolidated statistical management system, government as well as non-government agencies has been investing millions of dollars annually to collect, compile and analyze individual related data and fulfill their respective objectives. It has forced the government services and performance to be paper-based, time-consuming and tedious thus creating dis-trust among citizen each passing day. Though, formulation of legal instrument promoted digital movement and mandated shift towards e-government modality, the process has been low. Theoretically, Technology Acceptance Model (TAM) state the need of having advanced and efficient technology to be in place in current setting to improve governance, efficiency, accountability, transparency and trust. Also, the same theory state the requirement of strong willingness and motivation from the users (government, non-government and citizen) to adopt the technology based policy and system. As the integrated statistical management policy emphasizes on technology-based system or digital system, the perspectives of Technology Acceptance Model also termed as Information System Theory aid in understanding the context, conceptualizing and addressing the needs with an establishment and implementation of digital system or technology based system. This policy paper applied the Technology Acceptance Model (TAP) to examine the underlying opportunities and challenges associated with an integrated statistical management policy. With existing gaps in existing policy, system and practice alongside an overview of opportunities and challenges, this paper recommends the need of stand-alone integrated statistical management policy to consolidate sectoral as well as civil related information through single system based on recommended policy.

An exploding demand for processing capabilities related to the emergence of the IoT, AI and big data, has led to the quest for increasingly efficient ways to expeditiously process the rapidly increasing amount of data. These ways include different approaches like improved devices capable of going further in the more Moore path, but also new devices and architectures capable of going beyond Moore and getting more than Moore. Among the solutions being proposed, Stochastic Computing has positioned itself as a very reasonable alternative for low-power, low-area, low-speed, and adjustable precision calculations; four key-points beneficial to edge computing. On the other hand, chaotic circuits and systems appear to be an attractive solution for (low-power, green) secure data transmission in the frame of edge computing and IoT in general. Classical implementations of this class of circuits require intensive and precise calculations. This paper discusses the use of the SC framework for the implementation of nonlinear systems, showing that it can provide results comparable to those of classical integration, with much simpler hardware, paving the way for relevant applications.

Community radios play a paramount role in the development of the community. Community radio stations have been highly engaged in addressing social, economic, cultural, educational, health, environmental, sanitation, and disaster issues effectively and strategically using local languages in context. Community radios are also used to express, and share indigenous views, thoughts, ideas, problems, and perspectives of local people. The purpose of this analysis is to explore the role of community radio for integrated and sustainable development in Ethiopia. It used a systematic narrative review. Nine research works and five assessments report were selected purposively and analyzed in a quantitative approach. Currently, in Ethiopia, there are 50 community radio stations that received broadcast licenses from Ethiopian Broadcast Authority with four types of licensing and broadcasting in 29 local languages. Community radio helps the community to identify their common goals, create holistic plans, monitor the progress of their developmental activities, and guide on sustainable development. It contributes to integrated and sustainable development in a collaborative and creative process that cultivates the social, economic, and political conditions needed for the community to succeed which aimed to improve and sustain the livelihoods of the community. However, the media can’t achieve its target goal to support the development activities and bring holistic development of the community. As a result; this review paper focuses on reviewing how Ethiopians use community radios for holistic development. And it suggested the way how we can use community radios for the prospective holistic development in Ethiopia.

With the development of energy internet, integrated energy system can effectively reduce carbon emissions and improve the utilization of renewable energy. In this paper, a low-carbon optimal scheduling model of integrated energy system considering heat loss of heat network pipeline is proposed. Based on the study of concentrating solar power (CSP) plant and heat storage tank (HS), an optimal scheduling model is established, which takes system operation cost, environmental pollution and penalty cost of abandoning wind and solar energy as objectives. Through the analysis of example results, it is proved that the model proposed in this paper can achieve the goal of reliable, low-carbon and economic operation of the system. At the same time, it shows that CSP unit can reduce the operation cost of system and increase energy coupling and utilization.

We theoretically investigate advanced multi-functional integrated photonic filters formed by three waveguide coupled Sagnac loop reflectors (3WC-SLRs). By tailoring the coherent mode interference, the spectral response of the 3WC-SLR resonators is engineered to achieve diverse filtering functions with high performance. These include optical analogues of Fano resonances that yield ultrahigh spectral extinction ratios (ERs) and slope rates, resonance mode splitting with high ERs and low free spectral ranges, and classical Butterworth, Bessel, Chebyshev, and elliptic filters. A detailed analysis of the impact of the structural parameters and fabrication tolerances is provided to facilitate device design and optimization. The requirements for practical applications are also considered. These results theoretically verify the effectiveness of using 3WC-SLR resonators as multi-functional integrated photonic filters for flexible spectral engineering in diverse applications.

We review recent work on broadband RF channelizers based on integrated optical frequency Kerr micro-combs combined with passive micro-ring resonator filters, with microcombs having channel spacings of 200GHz and 49GHz. This approach to realizing RF channelizers offers reduced complexity, size, and potential cost for a wide range of applications to microwave signal detection.

We theoretically investigate and optimize four-wave mixing (FWM) in silicon nitride (SiN) waveguides integrated with two-dimensional (2D) layered graphene oxide (GO) films. Based on extensive previous measurements of the material parameters of the GO films, we perform detailed analysis for the influence of device parameters including waveguide geometry, GO film thickness, length, and coating position on the FWM conversion efficiency (CE) and conversion bandwidth (CB). The influence of dispersion and photo-thermal changes in the GO films is also discussed. Owing to the strong mode overlap between the SiN waveguides and the highly nonlinear GO films, FWM in the hybrid waveguides can be significantly enhanced. We obtain good agreement with previous experimental results and show that by optimizing the device parameters to balance the trade-off between Kerr nonlinearity and loss, the FWM CE can be improved by as much as ~20.7 dB and the FWM CB can be increased by ~4.4 folds, relative to the uncoated waveguides. These results highlight the significantly enhanced FWM performance that can be achieved in SiN waveguides by integrating 2D layered GO films.

The dynamics involving market competition and the challenges of dealing with empowered customers, means that creating and delivering relevant customer experience (CX) of service, is as important as creating product or services. Several studies have treated customer experience as though a front-desk, sales-point affair with the customer in the retailing environment, negating the critical role of organization-wide efforts in the overall customer experience management sequence. This review, however, adopts customer-centricity, as a theoretical lens to underscore the [re]configuration of organizational-level factors that are critical to adopting a high customer-experienced centred organization. Based on the review, we highlight conditions for adopting high customer experience management organization: (1) developing an integrated CX strategy, (2) CX-based knowledge management, (3) organizational re-design that supports CX-management, (4) top management commitment, (5) integrated CX IT systems, and (6) CX-oriented HR policies. These practices are only necessary conditions, but not sufficient, for creating, delivering, relevant and sustainable customer experience. However, more robust empirical studies are needed to advance the application of organization-wide customer experience management, which vary across industry, products/services, and sector.

In this work, meshless methods are applied for the solution of two-dimensional steady-state heat conduction problems with nonlocal multi-point boundary conditions (NMBC). These meshless procedures are based on multiquadric radial basis function (MQ RBF) and its modified version (i.e. integrated MQ RBF). The proposed meshless methods which were recently published in \cite{Reutskiy2016} is compared with standard collocation method (i.e. Kansa's method). Three different sorts of solution domain are considered in which Dirichlet boundary condition is specified on some part of the boundary and is related to the unknown function values at a discrete set of interior points. The influence of NMBC on the accuracy and condition number of the system matrix associated to the proposed methods is investigated. The sensitivity of the shape parameter is also analyzed in the proposed methods. Performance of the proposed approaches in terms of accuracy and efficiency is confirmed on the benchmark problems.

Tomato (Solanum lycopersicum L.) is a valuable horticultural crop grown and consumed worldwide. Optimum production is hindered by several factors of which Verticillium dahliae, the cause of Verticillium wilt, is one of the major biological constraints in temperate production regions. V. dahliae is difficult to manage because it is a vascular pathogen, has a broad host range and worldwide distribution, and can persist in soil for years. Understanding the pathogen virulence and genetic diversity, host resistance, and plant-pathogen interactions can ultimately inform the development of integrated strategies to manage the disease. In recent years, considerable research has focused on providing new insight into these processes as well as the development and integration of environment-friendly management approaches. In this review, we discuss and summarize the recent findings on the race and population structure of V. dahliae; pathogenicity factors; host genes, proteins, and enzymes involved in defense; the emergent management strategies, and recent approaches to managing Verticillium wilt in tomatoes.

With superior optical properties, high flexibility in engineering its material properties, and strong capability for large-scale on-chip integration, graphene oxide (GO) is an attractive solution for on-chip integration of two-dimensional (2D) materials to implement functional integrated photonic devices capable of new features. Over the past decade, integrated GO photonics, representing an innovative merging of integrated photonic devices and thin GO films, has experienced significant development, leading to a surge in many applications covering almost every field of optical sciences. This paper reviews the recent advances in this emerging field, providing an overview of the optical properties of GO as well as methods for the on-chip integration of GO. The main achievements made in GO hybrid integrated photonic devices for diverse applications are summarized. The open challenges as well as the potential for future improvement are also discussed.

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of simulation and statistical results of EO with other optimization techniques showed that EO is more effective and superior.

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus 13 voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ 14 constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources 15 on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar 16 PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed 17 using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of 18 simulation and statistical results of EO with other optimization techniques showed that EO is more effective 19 and superior.

Lemongrass (Cymbopogon flexuosus) is an aromatic perennial grass grown extensively for its essential oil. Lemongrass oil is chiefly a mixture of various cyclic and acyclic bioactive monoterpenes. We reviewed lemongrass oil and its biosynthesis in the present chapter along with its biochemical composition. Furthermore, we attempted to explore both the possible routes for essential oil biosynthesis in lemongrass, i.e. mevalonate and non-mevalonate pathways and how these pathways interwind with each other. Lemongrass oil has high commercial potential in medicinal, cosmetic, food and energy industries. Regarding the pharmacological properties, a wide array of biological activities has been observed in lemongrass oil such as antimicrobial, insecticidal, analgesic and anti-cancer properties as well as its efficacy as insect-repellent. The later sections were dedicated for the analysis of insecticidal property of the lemongrass oil and the mechanism working behind this phenomenon where it was observed that in addition to synergistic effects, various components of lemongrass oil can also induce specific neurotoxic and cytotoxic responses in the insects.

The deep Cretaceous tight sandstone in Kuqa Depression of Tarim foreland basin is an ultra-low porosity and ultra-deep gas-bearing reservoir, which is characterized by small pores, fine throats, and poor connectivity. The wireline logging responses are so complex, and especially, it is difficult to identify fluid types from resistivity logs. Based on acoustic, density, and neutron logs response differences in gas and water layers, effective fluid sensitivity factors are constructed for gas layer identification. From conventional logs, acoustic-neutron porosity difference, density-neutron porosity difference, and triple-porosity ratio are all sensitive parameters to the gas layer. From the NMR logging response mechanism, the density and NMR porosity difference, and T2 geometric mean of the movable fluid are also two sensitive parameters to the gas layer. Based on these parameters, a series of fluid typing charts are constructed and their adaptabilities are analyzed and compared. By contrast, NMR log interpretation is better, and triple-porosity comprehensive method from conventional logs is also effective when NMR logging is not available. Finally, the comprehensive fluid typing strategy by combining some methods for ultra-low porosity tight sandstone is summarized and optimized. This study is another alternative for fluid identification using non-electrical logs.

We theoretically investigate integrated photonic resonators formed by two mutually coupled Sagnac loop reflectors (MC-SLRs). Mode interference in the MC-SLR resonators is tailored to achieve versatile filter shapes with high performance, which enable flexible spectral engineering for diverse applications. By adjusting the reflectivity of the Sagnac loop reflectors (SLRs) as well as the coupling strength between different SLRs, we achieve optical analogues of Fano resonance with ultrahigh spectral slope rates, wavelength interleaving / non-blocking switching functions with significantly enhanced filtering flatness, and compact bandpass filters with improved roll-off. In our designs the requirements for practical applications are considered, together with detailed analyses of the impact of structural parameters and fabrication tolerances. These results highlight the strong potential of MC-SLR resonators as advanced multi-functional integrated photonic filters for flexible spectral engineering in optical communications systems.

Long-Term Potentiation(LTP) and Long-Term Depression(LTD) are two major forms of synaptic plasticity, which are also two well-know functional and unit activities involved in high advanced central neural system(CNS) activities, like memory. But we still know little about how the advanced CNS activities are organized in the brain and in the level of organism. Based on the current understanding and experimental evidence of neurology, we propose the term “Information Circulation” to summarize the current understandings for advanced CNS activities, and we define it as separately input neural signals finally converge in different levels of CNS and interact with each other, then neural information are circulated and processed in different levels of CNS to give out orders for next body actions. This review provides a detailed description for the functional organizations of advanced CNS activities in the term of Information Circulation. This article outlines the receiving of outside stimulation and transmission of neural information, especially transmission and procession of visual bioelectrical signals, then we described neural circuits of Information Circulation in advanced CNS activities, the corresponding specificity and dynamic properties of neural circuits, different sensation linkages, and neural synchronization for information circulation to produce consciousness in CNS. In conclusion, Information Circulation is defined as an important signature involved in advanced CNS activities.

Despite the productivity, achieving long-term sustainability and maintaining plant biodiversity become the pivotal goals in orchard floor management, especially along tree rows. Thus, the paradigm of eradicating weeds in the tree row using chemical herbicide or repeated soil tillage needs to be substituted with more sustainable alternatives. This study was conducted in two commercial apple and peach orchards in Marche region (Italy). Two integrated mechanical approaches, integrated mowing (mower + brush or disc) and integrated tillage (blade weeder + integrated mowing), were compared with standard herbicide system in a 2-years trial. Weed species abundance, soil coverage rate, and weed biomass productions, including gas exchange parameters, tree growth, fruit yield and quality were measured. Both integrated practices had significant effects on the number of weed species, total vegetation coverage, and dry weed biomass production. No significant differences were found in terms of tree gas exchange parameters, growth and fruit yield. However, a few fruit quality parameters such as fruit firmness, solid soluble content and dry matter content responded positively to the integrated practices. These results suggest that the integrated mechanical approaches of weed management increased orchard biodiversity, and they had no adverse effects on tree growth, fruit yield, and quality.

This paper presents a compact on-chip antenna architecture for 5G body centric networks (BCNs) applications. A dual meander line (DML) integrated antenna consists of two stacked layers of two turns of meander lines and a ground metal layer. The DML structure decreases the resonant frequency, increases tuning bands and broadens the operating bandwidth to be a suitable choice for high data rate biomedical applications. The antenna’s performance is evaluated in both scenarios inside and outside the human body. The proposed antenna is fabricated using UMC180 nm CMOS technology with a total area of 1150µm×200µm, and operates at bands 22 GHz, 34 GHz, 44 GHz and 58 GHz with an operating bandwidth up to 2 GHz at impedance bandwidth ≤ 7.5 dB (VSWR≤2.5). The proposed antenna is simulated using high frequency structure simulator (HFSS) and shows good agreement between measured and simulated results.

The integrated stress response (ISR) is an adaptational signaling pathway that is induced in response to different stimuli, such as accumulation of unfolded and misfolded protein, hypoxia, amino acid deprivation, viral infection and ultraviolet light. It has been known that viral infection can activate ISR, but the role of ISR during viral infection is still unclear. In some cases, ISR is a protective mechanism of host cell against infection with virus whilst ISR may be hijacked by viruses for facilitating its replication. In this review, we highlighted recent advances on induction of ISR upon viral infection and the downstream responses involved such as autophagy, apoptosis, formation of stress granules and innate immunity response. We then discussed the molecular mechanism of ISR regulating viral replication and how viruses antagonize this cellular stress response resulting from ISR.

Introduction Older people with complex, chronic conditions often receive insufficient or inefficient care provision. And few instruments are able to measure their perception on care provision. The "User Reported Measure of Care Coordination" instrument has been satisfactorily used to evaluate chronic care provision and integration. The aim of this study is to validate this instrument into Spanish. Methods The questionnaire was adapted and validate in two phases: translation and cultural adaptation of the questionnaire, and psychometric property measurement. Study population were chronic care conditions patients. Results A total of 332 participants completed test re-test as part of the questionnaire validation process. The final version of the questionnaire had 6 domains: Health and Well-being (D1), Health day to day (D2), Social Services (D3), Planned Care (D4), Urgent Care (D5) and Hospital Care (D6). Cronbach's alpha for the overall questionnaire was 0.86, indicating good internal consistency. When analysing each domain, only Planned Care (D4) and Urgent Care (D5) had Cronbach’s Alphas slightly lower than 0.7, although this could be related to the low number of items in each domain. A good temporal stability was observed for the distinct subscales and items, with intraclass correlation coefficients varying from 0.412 to 0.929 (p < 0.05). Conclusion The adapted version of the “User Reported Measure of Care Coordination” into Spanish proved to be a practical tool for use in our daily practice and an efficient instrument for assessment of care coordination in chronic, complex conditions in older people across services and levels of care.

The advance of the medical field in the 21st century has influenced the development of many innovations, including in medical education. PBL (problem-based learning) is one of the pedagogical approaches that has been studying and implementing worldwide to attract medical students’ attention with their learning style and learning environment. China is the most significant “receiver” country of foreign students in Asia, and clinical medicine is one of the most chosen majors for undergraduate. In China, PBL has been implementing in some schools, but mostly with the local students and only a few implementations to the international students. International medical students in China faced a variety of challenges during their studies. In this review paper, we give the solution to adapt to the challenges by focusing on the implementation the integrated organ/system curriculum/syllabus with the PBL method to the school system with the support of the school stakeholders and students’ role.

Vertical-channel organic dual-gate/base transistors would be highly interesting since vertical organic transistors are the fastest organic transistors demonstrated today. However, incorporating a dual gate/base structure into an ultra-short channel vertical architecture represents a substantial challenge. Here, we successfully realize a new device concept of vertical organic permeable dual-base transistors (OPDBTs), where either of both base electrodes can be used to change the on-currents and tune the threshold voltages. The optimized devices yield a high on-current density of 1.54 A cm^-2 and a large current gain of 9.2×10⁵, corresponding to a high transmission value of 99.998%. The detailed operation mechanisms are investigated by calibrated TCAD simulations with the Poole-Frenkel mobility model, Gaussian density of states and tunneling model. Finally, high-performance logic circuits, e.g. inverter, NAND/AND computation functions are demonstrated with one single OPDBT operating at supply voltages of < 2.0 V. We believe that OPDBTs offer a compact and technologically simple hardware platform with excellent application potential for vertical-channel organic transistors in complex logic circuits.

Layered two-dimensional (2D) GO films are integrated with silicon-on-insulator (SOI) nanowire waveguides to experimentally demonstrate an enhanced Kerr nonlinearity, observed through self-phase modulation (SPM). The GO films are integrated with SOI nanowires using a large-area, transfer-free, layer-by-layer coating method that yields precise control of the film thickness. The film placement and coating length are controlled by opening windows in the silica cladding of the SOI nanowires. Owing to the strong mode overlap between the SOI nanowires and the highly nonlinear GO films, the Kerr nonlinearity of the hybrid waveguides is significantly enhanced. Detailed SPM measurements using picosecond optical pulses show significant spectral broadening enhancement for SOI nanowires coated with 2.2-mm-long films of 1−3 layers of GO, and 0.4-mm-long films with 5−20 layers of GO. By fitting the experimental results with theory, the dependence of GO’s n₂ on layer number and pulse energy is obtained, showing interesting physical insights and trends of the layered GO films from 2D monolayers to quasi bulk-like behavior. Finally, we show that by coating SOI nanowires with GO films the effective nonlinear parameter of SOI nanowires is increased 16 fold, with the effective nonlinear figure of merit (FOM) increasing by about 20 times to FOM > 5. These results reveal the strong potential of using layered GO films to improve the Kerr nonlinear optical performance of silicon photonic devices.

We report a broadband radio frequency (RF) channelizer with up to 92 channels using a coherent microcomb source. A soliton crystal microcomb, generated by a 49 GHz micro-ring resonator (MRR), is used as a multi-wavelength source. Due to its ultra-low comb spacing, up to 92 wavelengths are available in the C band, yielding a broad operation bandwidth. Another high-Q MRR is employed as a passive optical periodic filter to slice the RF spectrum with a high resolution of 121.4 MHz. We experimentally achieve an instantaneous RF operation bandwidth of 8.08 GHz and verify RF channelization up to 17.55 GHz via thermal tuning. Our approach is a significant step towards the monolithically integrated photonic RF receivers with reduced complexity, size, and unprecedented performance, which is important for wide RF applications ranging from broadband analog signal processing to digital-compatible signal detection.

Integrated information theory (IIT) was initially proposed to describe human consciousness in terms of intrinsic-causal brain network structures. This theory could potentially be used for conceptualising complex living systems. In a previous study, we analysed collective behaviour in {\it Plecoglossus altivelis}. We found that IIT 3.0 exhibits qualitative discontinuity between three and four schools of fish in terms of $\Phi$ values (i.e., group integrity). Other measures, such as mutual information, did not show such characteristics. In this study, we follow up on our previous findings and introduce two new factors. First, we define the global parameter settings to determine a different kind of group integrity. Second, we set several timescales (from $\Delta t =5/120$ s to $\Delta t =120/120$ s). The results showed that we succeeded in classifying fish school according to their group size in terms of the degree of group integrity, despite the small group size. The concrete classification includes the followership for a two-fish school, fission--fusion for a three-fish school, emergence of leadership for a four-fish school, and emergence of Boid-like behaviour for a five-fish school. These minute classifications have never been revealed before. Finally, we discuss one of the longstanding paradoxes in collective behaviour, known as the heap paradox, for which two tentative answers could be provided through our IIT analysis.

Layered two-dimensional (2D) graphene oxide (GO) films are integrated with micro-ring resonators (MRRs) to experimentally demonstrate enhanced nonlinear optics in the form of four-wave mixing (FWM). Both uniformly coated and patterned GO films are integrated on CMOS-compatible doped silica MRRs using a large-area, transfer-free, layer-by-layer GO coating method together with photolithography and lift-off processes, yielding precise control of the film thickness, placement, and coating length. The high Kerr nonlinearity and low loss of the GO films combined with the strong light-matter interaction within the MRRs results in a significant improvement in the FWM efficiency in the hybrid MRRs. Detailed FWM measurements are performed at different pump powers and resonant wavelengths for the uniformly coated MRRs with 1−5 layers of GO as well as the patterned devices with 10−50 layers of GO. The experimental results show good agreement with theory, achieving up to ~7.6-dB enhancement in the FWM conversion efficiency (CE) for an MRR uniformly coated with 1 layer of GO and ~10.3-dB for a patterned device with 50 layers of GO. By fitting the measured CE as a function of pump power for devices with different numbers of GO layers, we also extract the dependence of GO’s third-order nonlinearity on layer number and pump power, revealing interesting physical insights about the evolution of the layered GO films from 2D monolayers to quasi bulk-like behavior. These results confirm the high nonlinear optical performance of integrated photonic resonators incorporated with 2D layered GO films.

Visual-inertial integrated navigation system (VINS) has been extensively studied over the past decades to provide accurate and low-cost positioning solutions for autonomous systems. Satisfactory performance can be obtained in an ideal scenario with sufficient and static environment features. However, there are usually numerous dynamic objects in deep urban areas, and these moving objects can severely distort the feature tracking process which is fatal to the feature-based VINS. The well-known method mitigates the effects of dynamic objects is to detect the vehicles using deep neural networks and remove the features belongs to the surrounding vehicle. However, excessive exclusion of features can severely distort the geometry of feature distribution, leading to limited visual measurements. Instead of directly eliminating the features from dynamic objects, this paper proposes to adopt the visual measurement model based on the quality of feature tracking to improve the performance of VINS. Firstly, a self-tuning covariance estimation approach is proposed to model the uncertainty of each feature measurements by integrating two parts: 1) the geometry of feature distribution (GFD), 2) the quality of feature tracking. Secondly, an adaptive M-estimator is proposed to correct the measurement residual model to further mitigate the impacts of outlier measurements, such as the dynamic features. Different from the conventional M-estimator, the proposed method effectively alleviates the reliance of excessive parameterization of M-estimator. Experiments are conducted in a typical urban area of Hong Kong with numerous dynamic objects, and the results show that the proposed method could effectively mitigate the effects of dynamic objects and improved accuracy of VINS is obtained when compared with the conventional method.

Desalination accounts for 1% of the total global water consumption and is an energy-intensive process, with the majority of operational expenses attributed to energy consumption. Moreover, at present, a significant portion of the power comes from traditional fossil fuel-fired power plants and the greenhouse gas emissions associated with power production along with concentrated brine discharge from the process, pose a severe threat to the environment. Due to the dramatic impact of climate change, there is a major opportunity to develop sustainable desalination processes to combat the issues of brine discharge, greenhouse gas emissions along with a reduction in energy consumption per unit of freshwater produced. Nanotechnology can play a vital role to achieve specific energy consumption reduction as nanofluids application increases the overall heat transfer coefficient enabling the production of more water for the same size desalination plant. Furthermore, concentrated brine discharge harms the marine ecosystems, and hence, this problem must also be solved to support the objective of sustainable desalination. Several studies have been carried out in the past several years in the field of nanotechnology applications for desalination, brine treatment and the role of renewable energy in desalination. This paper aims to review the major advances in this field of nanotechnology for desalination. Furthermore, a hypothesis for developing an integrated solar thermal and nanofluid sustainable desalination system, based on the cyclic economy model is proposed.