For W-band long-range mm-wave wireless transmission systems, nonlinearity issues resulting from photoelectric devices, optical fiber, and wireless power amplifiers can be handled by deep learning equalization algorithms. Besides, the PS technique is considered an effective measure to further increase the capacity of the modulation-constraint channel. However, since the proba-bilistic distribution of m-QAM varies with the amplitude, there have been difficulties in learning valuable information from the minority class. This limits the gain of nonlinear equalization. To overcome the imbalanced machine learning problem, we propose a novel two-lane DNN (TLD) equalizer with the random over-sampling (ROS) technique in this paper. The combination of PS at the transmitter and ROS at the receiver improves the overall performance of the W-band wireless transmission system, and our 4.6-km ROF delivery experiment verifies its effectiveness for the W-band mm-wave PS-16QAM system. Based on our proposed equalization scheme, we realize single-channel 10-Gbaud W-band PS-16QAM wireless transmission over 100 m optical fiber link and 4.6-km wireless air-free distance. The results show that compared with the typical TLD without ROS, the TLD-ROS can improve the receiver sensitivity by 1dB. Furthermore, a reduction of 45.6% in complexity is realized, and training samples can be reduced by 15.5%. Considering the actual wireless physical layer with its requirements, there is much to be gained from the joint use of deep learning and balanced data pre-processing techniques.

The purpose of this study is to develop and evaluate a self-microemulsifying drug delivery system (SMEDDS) to improve the oral absorption of poorly water-soluble Olaparib. Through the solubility test of Olaparib in various oils, surfactants and co-surfactants, pharmaceutical excipients for use in SMEDDS manufacturing were selected. Self-emulsifying regions were identified by mixing the selected materials at various ratios, and a pseudoternary phase diagram was constructed by synthesizing these results. Various physicochemical properties of microemulsion incorporating Olaparib were confirmed by investigating the particle morphology, particle size, zeta potential, drug content and stability. In addition, the improved dissolution and oral absorption of Olaparib were also confirmed through a dissolution test and a pharmacokinetic study. An optimal microemulsion was generated in the formulation of Capmul MCM EP/NF 10%, Labrasol 80% and PEG 400 10%. Fabricated nano-sized microemulsions were well-dispersed in aqueous solutions, and it was also confirmed that it was maintained well without any problems of either physical or chemical stability. The 5 min initial dissolution of Olaparib in fabricated formulations was improved by 10.6 times (pH1.2), 14.8 times (pH6.8) and 14.8 times (distilled water) compared to the values of Olaparib powder. The dissolution at 120min was 45.4±4.0%(pH1.2), 53.5±1.1% (pH6.8) and 58.1±1.00% (distilled water) in Olaparib powder but has been significantly improved by 1.7 times (74.8±1.9%), 1.6 times (84.2±0.3%) and 1.5 times (81.2±0.7%) in SMEDDS. Associated with the high dissolutions of Olaparib in fabricated microemulsions, the pharmacokinetic parameters were also greatly improved. The Cmax and AUCinf of Olaparib in the prepared microemulsion were increased 4.2- and 3.2-fold, respectively, compared to powder. Taken together with the results mentioned above, the microemulsion system could be an effective tool as an oral delivery formulation for Olaparib. Additionally, our results demonstrate that the SMEDDS systems comprising Capmul MCM, Labrasol and PEG 400 could be a useful option for improvement of several other poorly water-soluble drugs with physico-chemical properties similar to Olaparib.

Background: Endocrine conditions that impact women define polycystic ovary syndrome. Previous studies have demonstrated a connection between PCOS and insulin intolerance, oxidative stress, and immune system dysfunction. Additionally, some reports have indicated that propolis has antioxidant properties and that chitosan nanoparticles have beneficial effects on the reproductive system. The goal of the present study is to compare metformin (Met) to chitosan-propolis nanoparticles and explain how they protect against a rat PCOS model caused by estradiol valerate (EV). (as a control treatment). Methods: In order to cause PCOS in rodents, a single subcutaneous injection of estradiol valerate was used, followed by a 42-day oral administration of 500 mg/kg of chitosan-propolis nanoparticles. Four sets of rats were created: the control, PCOS, metformin (PCOS and 150 mg/kg metformin), and chitosan-propolis nanoparticle (PCOS and 500 mg/kg chitosan-propolis nanoparticle) groups. The histopathological examination of the ovaries and measurement of serum ferctors were performed on all of the animals. Estradiol valerate caused PCOS, but chitosan-propolis nanoparticle therapy reversed it. Results: After chitosan-propolis nanoparticle intervention, the body weight and ovarian morphology had improved, and the serum biochemical parameters, including esretogen, progestron, vitamin D, calcium, and the insulin resistance index, had been corrected. These EV-induced changes include decreased SOD activity, elevated MDA levels, and evidence that oxidative stress was increased by EV when chitosan-propolis nanoparticle/Met were administered for 42 straight days. Additionally, certain relative mRNA transcripts, including those for the MCP, IL18, and CRP genes, were markedly upregulated in EV-treated animals. These findings unequivocally demonstrate the beneficial effects of chitosan-propolis nanoparticles/Met in inflammatory disorders. Conclustion: Together, the study's end findings, which are presented here, are consistent with the hypothesis that chitosan-propolis nanoparticle/Met offered protective activity against the harmful effects of EV. Although ameliorative effects may have been implicated, the primary pathway or pathways still need to be clarified.

Sensors and actuators are fundamental units in Cyber-Physical and Internet of Things systems. Because they are included in a variety of systems, using many technologies, it is very useful to characterize their functions abstractly by describing them as Abstract Entity Patterns (AEPs), that are patterns that describe abstract conceptual entities. For concreteness, we study them here in the context of autonomous cars. An autonomous car is a complex system because, in ad-dition to its own complex design, it interacts with other vehicles and with the surrounding in-frastructure. To handle these functions, it must incorporate various technologies from different sources. An autonomous car is an example of a Cyber-Physical System, where some of its func-tions are performed by Internet of Things units. Sensors are extensively used in autonomous cars to measure physical quantities; actuators are commanded by controllers to perform appro-priate physical actions. From AEPs we can derive concrete patterns, a structure combining re-lated AEPs is an Entity Solution Frame (ESF). Both sensors and actuators are susceptible to mali-cious attacks due to the large attack surface of the system where they are used. Our work is in-tended to make autonomous cars more secure, which also increases their safety. Our final objec-tive is to build a Security Solution Frame for sensors and actuators of autonomous cars that will facilitate their secure design. A Security Solution Frame is a solution structure that groups to-gether and organizes related security patterns. This article is the first stage of a secure unit that can be used to design not only secure autonomous cars but also any system where sensors and actuators are used. This paper concentrates on AEPs and ESFs for sensors and actuators; that is, on the functional aspects of these devices.

To prolong the fatigue life of a product handled by machine, parametric accelerated life testing (ALT) is mentioned as an organized technique to pinpoint design flaws and minimize fatigue-connected failures. It requires (1) an ALT procedure, (2) fatigue model, (3) parametric ALTs with adjustment, and (4) an approximate of whether present product complete the BX life. The use of a quantum-transported time-to-failure archetype and a sample size are advised. The improvements in the reliability of a refrigerator ice-maker, comprising an auger motor with bearing, were utilized as a case investigation. In the 1st ALT, a steel rolling bearing cracked due to repeated loads under cold circumstances (below −20 C) in the freezer compartment. The bearing was altered by adjusting the matter from AISI 52100 alloy steel with 1.30-1.60% chromium to lubricated sliding bearing with sintered and hardened steel (FLC 4608-110HT) because of its high fatigue strength at lower temperatures. In the 2nd ALT, a helix made of polycarbonates (PCs) fractured. As an adjustment, a reinforced rib of the helix was thickened. As no troubles in the 3rd ALT occur, the lifetime of an ice-maker was proved to be B1 life 10 years.

Animal models of diseases in particular, the mice, are considered to be the cornerstone for translational research in immunology. The aim of the present study is to model the geometry and analyze the network structure of murine lymphatic system (LS). The algorithm for building the graph model of the LS makes use of anatomical data. To identify the edge directions of the graph model, a mass balance approach to lymph dynamics based on Hagen-Poiseuille equation is applied. It is the first study in which a geometric model of the murine LS has been developed and characterized in terms of its structural organization and the lymph transfer function. Our study meets the demand for quantitative mechanistic approaches in the growing field of immunoengineering to utilize or exploit the lymphatic system for immunotherapy.

Cempo Ireng (Oryza sativa L. var. Cempo Ireng) is one of the black rice variety in Indonesia that consumed as functional food, not as a staple food because of the black rice contains anthocyanin pigment which has beneficial to human health. High concentration of anthocyanin reaching 393.93 ppm cause black color in the pericarp layer of Cempo Ireng which make this variety as an antioxidant source, low glycemic index, and free of gluten, leading to have higher price in the rice market. However, most of the farmers are not cultivate Cempo Ireng due to the longer vegetative phase up to 150 days compared to the white rice varieties which only takes 90 days, the taller phenotype of Cempo Ireng cause problems in cultivation, and also the purple color of Cempo Ireng attract birds and earhead bug (Leptocorisa oratorius) to feed on black rice caryopsis that cause severe yield loss. Transgenic methods, mutation technique, intensification systems, and physical treatment have been applied in Cempo Ireng to overcome those lack characteristics. In the future, Cempo Ireng also has a big potential to become a parent in cross breeding program because of the positive characters. The aim of this review is to describe the potential of Cempo Ireng in rice breeding program for improving food sustainability.

Considering the actual world economical trends, one of the most important questions is now and in the future: how to reduce power consumption of electronic systems. Since the invention of computers, the electrical energy consumption step by step increased. Now when not only computers, but electric vehicles, robots, automation, and unmanned aerial vehicles play a very important role of our life, the main problem of system designers is how to reduce energy consumption in these systems. But also the existing already working systems must be revised in order to decrease their electric power consumption. The importance of this subject (energy control) shows that a huge number of research publications and survey papers deal with it. Just focusing on the last one or two years (2021 and 2022) the search hit 221000 titles (103000 hits only in 2022). Analyzing all the research areas is almost impossible, but focusing on some important research subjects, where one of the main topic is “energy saving methods” can give an overview about the subject. The paper focuses on the area of industrial robotic systems, electric vehicles, and embedded systems.

Others have proposed that living systems are characterized by the possession of a kind of information unique to them. This information, variously called semantic, symbolic, or coding information conveys meaning from senders to recipients, most commonly among genome and other cellular components, different cells, organisms, etc., enabling all biological functions. Unlike other kinds of information, it is only indirectly quantifiable and does not increase by copying. Here, the term system information is used to encompass the entire package of coding information enabling all organisms of a species to complete their life cycles through possession of its copy (Crkvenjakov and Heng 2021). System information grows in a nonreductive evolution only during speciation proper by the acquisition of novel functions by daughter species. Contemporary science agrees that species are units of evolution but has failed to recognize and parse the importance of phases of speciation and stasis for evolution. Confinement of system information change to speciation only explains for the first time why there are species and why their number increases nearly exponentially throughout evolution. More importantly, here we define that evolution as a process operating on a planetary scale, while chance based, is non-random mathematically since it obeys the Laws of Information which dictate the behavior of System information in organisms. Growth and persistence of system information on the non-degenerative portion of Tree of Life follow the law of conservation, which states that its growth is as parsimonious (minimal) as possible and the persistence of parental system information the maximal possible in each unit speciation step. This formulation is a restatement of Loewnstain's (1999) principle of information economy and our lock-in law (Crkvenjakov and Drmanac 2007). The principle holds that since, on chance assumption, the system information change cost is directly proportional to time, more costly pathways of achieving the same new functional goal will be, almost without exception, competed out by the less costly ones. As a corollary of the conservation law, the speciation law states that speciation follows the most economical way of growth of system information while conserving the existing one, which is horizontal information transfer by molecular sex (uptake of exogenous nucleic acid into the progeny genome) by exchange among two parents from maximally possible divergent lineages. The speciation law dictates that molecular sex mode be used since it is the most parsimonious one. The molecular sex cost in information bits is zero to the recipient, which is not the case with the generally accepted mode of vertical accumulation of information bits in a population gene pool within a lineage.

Background: Current drug for the treatment of endometriosis is not able of completely cure and significant side effects hinder the continuation of treatment. So, the search for new drug candidates is necessary, and the use of plants extracts is highlighted. Babassu oil and copaiba oilresin have several therapeutic properties. We investigated the in vitro effects of two nanoemulsions containing babassu oil (Orbignya speciosa) (SNEDDS-18) and/or copaiba oilresin (Copaifera langsdorffii) (SNEDDS-18/COPA) on cultured human eutopic endometrium stromal cells from endometrial biopsies of patients without (CESC) and with (EuESC) endometriosis, and human stromal cells from biopsies of endometriotic lesions (EctESC). Methods: CESC, EuESC and EctESC were established and treated with SNEDDS-18 and SNEDDS-18/COPA to evaluate its effects on cytotoxicity, cell morphology, proliferation, and signaling pathways. Results: After 48 hours incubation with SNEDDS-18 and SNEDDS-18/COPA, cell viability and proliferation were inhibited, especially in EctESC. The lowest concentration of both nanoemulsions reduced cell viability and proliferation and breakdown the cytoskeleton in EctESCs. After 24h treatment it was observed a decrease in IL-1, TNF-α, and MCP-1, and an increase in IL-10 production. Conclusions: Both nanoemulsions can affect the endometriotic stromal cell behaviors, thus revealing two potential candidates for new phytotherapeutic agents on the management of endometriosis.

Anthocyanins are among the best-known phenolic compounds and possess remarkable biological activities, including antioxidant, anti-inflammatory, anticancer, and antidiabetic effects. Despite their therapeutic benefits, they are not widely used as health-promoting agents due to their insta-bility, low absorption, and thus, low bioavailability and rapid metabolism in the human body. Recent research suggests that the application of nanotechnology could increase their solubility and/or bioavailability, and thus, their biological potential. Therefore, in this review, we decided to provide, for the first time, a comprehensive overview of in vitro and in vivo studies on nanocarriers used as delivery systems of anthocyanins, and their aglycones, i.e., anthocyanidins alone or com-bined with conventional drugs to the treatment or management of chronic diseases.

Many spatial decision support systems suffer from user adoption issues in practice due to lack of trust, technical expertise, and resources. Automated machine learning has recently allowed non-experts to explore and apply machine learning models in the industry without requiring abundant expert knowledge and resources. This paper reviews recent literature from 136 papers, and proposes a general framework for integrating spatial decision support systems with automated machine learning to lower major user adoption barriers. Challenges of data quality, model interpretability, and practical usefulness were discussed as general considerations for system implementation. Research opportunities related to spatially explicit models in AutoML, and resource-aware, collaborative/connected, and human-centered systems were also discussed to address these challenges. This paper argues that integrating spatial decision support systems with automated machine learning can not only encourage user adoption, but also mutually benefit research in both fields — bridging human-related and technical advancements for fostering future developments in spatial decision support systems and automated machine learning.

Since the 1990s, mobile telecommunication networks have gradually become denser around the world. Nowadays, large parts of their backhaul network consist of commercial microwave links (CMLs). Since CML signals are attenuated by rainfall the exploitation of records of this attenua-tion for precipitation monitoring purposes is an innovative and inexpensive solution. Performance data from mobile operators' networks is crucial for the implementation of this technology. And, moreover for near real-time quantification. To meet this requirement, a real-time system for col-lecting and storing CML power levels from the cellular phone operator "Telecel Faso" in Burkina Faso was implemented. This new acquisition system, which uses the Simple Network Manage-ment Protocol (SNMP) can simultaneously record the transmitted and received power levels from all the CML to which it has access, with a time resolution of one minute. Installed at “Laboratoire des Matériaux et Environnement de l’Université Joseph KI-ZERBO (Burkina Faso)”, this acquisi-tion system is dynamic and has gradually grown from eight to more than 1000 radio links Tele-cel Faso CML links between 2019 and 2021. The system covers the capital Ouagadougou and the main cities of Burkina Faso (Bobo Dioulasso, Ouahigouya, Koudougou and Kaya) as well as the axes connecting Ouagadougou to these cities.

It is a truism that whole energy system models underpin the development of policies for energy system decarbonisation. But recent reviews have thrown doubt on the appropriateness of such models for addressing the multiple goals for future energy systems, in the face of emergent real-world complexity and the evolution of stakeholder’s priorities. Without an understanding of the changing priorities of policy makers and expectations of stakeholders for future systems, system objectives and constraints are likely to be ill-defined, and there is a risk that models may be inadvertently instrumentalised. Adopting a system architecture perspective, the authors have undertaken a three-year programme of research to explore strategies for decarbonising heat in the UK, with interaction with and elicitation of needs from stakeholders at its heart. This paper presents the procedure, methods, and results of an exercise in which experts from stakeholder organisations across the energy system were interviewed. Analysis of interview data reveals two broad approaches to heat decarbonisation which can be broadly defined as either adaptive or transformative. Specific insights gained from these interviews enabled our modelling teams to refocus their work for exploration with a wider circle of stakeholders. Results suggests that this iterative approach to formalising model-policy interaction could improve the transparency and legitimacy of modelling and enhance its impact on policy making.

According to the World Food Programme (WFP), the projected increase in the human population stands at 2 billion people by 2050. At the same time, world food production is witnessing a declining trend over recent years, and 690 million (8.9%) of the world's population are already in severe starvation. Climate variability and climate change impacts on food security are very eminent today. For this reason, this study explored the real effects of climate variability and change on food security in Africa by applying the system Generalized Method of Moments (GMM) and the Panel Corrected Standard Errors (PCSEs) estimators on data from 2001–2018 for 38 selected African countries. The findings reveal that higher amounts of precipitation positively influence food security along two dimensions (food availability and utilization). Hotter temperatures negatively impact food availability and utilization. However, it aids food accessibility in Africa. Similarly, carbon dioxide emissions improve food availability and are harmful to food accessibility and food utilization in Africa. Consequently, the effects of climate variability and change on food security in Africa are undesirable, thereby putting the continent at risk of food insecurity over the long run. Given these findings, the study made appropriate recommendations for policy change to address the negative effects of climate variability and change on food security in Africa.

Forest road pavement needs an evaluation methodology based on a comprehensive assessment of road conditions. This research was conducted to evaluate the performance of a method for rating the surface condition of forest roads and eventually to adapt the method to the situation prevailing in a forest road network. The rating method selected as the basis for this experiment was the pavement condition index (PCI) developed by the U.S. Army Corps of Engineers. A 53 km of forest roads were selected contained the most influential factors and conditions variability. Eventually, 201 road segments were delineated between 150-300 m in length. Within the given segments, sample plots were set 20 m in length consecutively. It was concluded that the panel scores for distress and surface condition of sample unit and section differed from forest road pavement condition index (FRPCI) and PCI. Linear regression was used to derive equations between distress and PCI score to determine effective FRPCI parameters that provide a numerical rating for the condition of road segments within the road network, where 0 worlds are the worst possible condition, and 100 is the best possible condition best. Also, regression analysis showed the FRPCI model with a 0.87 correlation for the total of the road is a performance index used for the first time in forest roads. This study showed a range of FRPCI from 7.8 to 96.3, different from PCI and URCI ratings (0.85-45 and 1.2-53). The FRPCI index helps forest managers in road maintenance, harvesting, and planning to use road information.

This study quantified effluents generated during processing in three industry types, estimated the energy potential from the quantified effluents in form of biogas generation, and determined the economic viability of the biogas recovered. Data were procured from relevant scientific publications to quantify the effluents generated from the production processes in the industry types examined using industrial process calculations. The effluent data generated was used on the 2-module biogas energy recovery model to estimate the bioenergy recovery potential within it. Economic and financial analysis was based on cash flow comparison of all costs and benefits resulting from its activities. The effluents generated average daily biogas of 2559 Nm³/gVS, having a daily potential combined heat and power of 0.52 GWh and 0.11 GWh respectively. The Life Cycle Analysis and cost-benefit analysis show the quantity of avoided emissions from using the effluents to generate heat and power for processes, and also the profitability of the approach. Conclusively, the study shows the use of biomass effluents to generate biogas for CHP is a viable one based on the technologies of a reciprocating engine, gas turbine, microturbine, and fuel cell. However, it is recommended that the theoretical estimation be validated using a field-scale project.

In several mammalian species including humans, complex stimulation patterns such as cognitive challenge and physical exercise lead to improvements in organ function, organism health and performance, as well as possibly longer lifespans. The hypothesis is presented here that activity-dependent transcriptional programs, induced by these environmental stimuli, temporarily and lightly de-differentiate somatic cells such as neurons and muscle cells into a state that resembles functionally younger cells to allow cellular remodeling and adaptation of the organism to environmental change. This cellular adaptation program targets several process classes that are heavily implicated in aging, such as mitochondrial metabolism, cell-cell communication, intracellular signaling and epigenetic information processing and leads to functional improvements in these areas. I reverse engineer these activity-dependent gene programs, identify critical molecular nexus points such as CREB, MEF2 and cFos and speculate as to how one might leverage them to prevent and attenuate human aging-related decline of body function, enhance human performance and restore more youthful levels of function and morphology. The findings presented here can serve as a basis for the study and development of effective longevity efforts as the underlying gene programs could be used as markers for treatment success and as targets for therapy development.

The role of agroforestry systems in providing ecosystem services is very crucial. The most significant increase in carbon (C) storage is often achieved by moving from lower biomass land-use systems to tree-based systems like agroforestry (AF). However, estimation of carbon stocks in indigenous agroforestry systems of South-eastern Rift- valley landscapes, Ethiopia the data are scarce. The study was aimed to investigate the biomass, biomass carbon (BC), and soil organic carbon (SOC) stock of Enset based, Enset-Coffee based, and Coffee-Fruit tree-Enset based agroforestry systems. Comparison of SOC stock of agroforestry systems against their adjacent monocropping farms was also investigated. The study was conducted in three selected sites of the Dilla Zuria district of Gedeo zone. Twenty farms (total of 60) representative of each AF system were randomly selected, inventoried and biomass C stocks estimated. Ten adjacent mono-cropping farms which were related to each AF system were selected in a purposive manner for comparison of SOC stock. Inventory and soil sampling were employed in the 10×10 m farm plot. The mean aboveground biomass ranged from 81.1 t ha-1 to 255.9 t ha-1 and for belowground biomass from 26.9 t ha-1 to 72.2 t ha-1. The highest C stock was found in Coffee-Fruit tree-Enset based (233.3±81.0 t ha-1), and the lowest was in Coffee-Enset based agroforestry system (190.1±29.8 t ha-1). The result showed that SOC stocks were not statistically significant between the three AF systems, although they showed a significant difference in their BC stock. The AF systems' C stocks are substantially higher than those reported for tropical forests and other AF systems. The SOC of AF systems was significantly higher than the ones for the adjacent monocropped farms. Therefore, it is possible to deduce that AF systems are storing significant amount of C and contributing to climate change mitigation.

This article introduces new method using ANN to control SVC in order to correct the source power factor of low voltage network. Two ANN approaches are investigated to design accurate and fast power factor correction (PFC) controller. First approach uses simple ANN (SANNA). Second approach uses cascaded ANN (CANNA). ANN regression, performance and the calculated error for both approaches are investigated to select between the two approaches. CANNA is selected as a better solution and it used to build the ANN PFFC controller using database, generated by MATLAB-Simulink, for standard three low voltage levels (240V, 220V and 110V). Nine test cases are carried out to validate the performance of proposed ANN PFC controller with a network has variable loads and low power factor (0.6 approximately). In order to extend the use of the controller to other voltage levels not included in the training process of the cascaded ANN, only the SVC is resized. Another nine cases are carried out with the same loads using the same ANN controller, as it is, to test its performance with the extended voltage level range (415V, 230V and 120V). The results show accurate and fast response in all test cases.

Due to the shortage of agricultural labor forces and rapid aging of farmers, the utilization of tractors is becoming popular and essential in Korea. Tractors can be classified into two types, a walking tractor called as a power tiller and a riding tractor. In this study, agricultural tractors including walking and riding types were categorized into 4 levels by rated output power. And diesel emission inventory of tractors was established and analyzed using 2011 and 2019 survey data in Korea. Emission inventory including CO, NOx, SOx, TSP(PM10), PM2.5, VOCs and NH3 were established using Tier 3 methodology. The total amount of emission using agricultural tractors was decreased about 13% from 2011 to 2019. The number of walking tractors were decreased by about 19% in 8 years, on the other hand that of riding tractors were increased by about 12%. However, the emission reduction is about 48% for walking tractors and the emission increment is about 5% for riding tractors. Thus, the total emission from agricultural tractors was decreased by about 16% in those periods. It is due to the decrease of 21% and 15% in the hours of use of walking and riding tractors, respectively, in 2019. Walking tractors mainly emit air pollutants from spraying and transporting. Riding tractors mainly 61% of total air pollutants emits from soil preparation and transporting operations. Geographic information system (GIS) was used to spatially assign air pollutants variables into 17 provinces and metropolitan cities in Korea. High emission generating regions and changes of emissions during 8 years were clearly seen in GIS analysis. High air pollutant emitting regions are mainly located in the western and southern regions of Korea, which have plenty of arable areas compared to other regions in Korea.

The movement direction of propagating convective systems originating from both inland and offshore over the north coast of West Java in Indonesia is determined primarily by the prevailing wind. However, the role of a land-sea contrast and a rugged topography over southern West Java is also expected to affect propagating convective systems by increasing land-sea breezes and enhancing upward motion. These hypotheses are tested using a weather prediction model incorporating convection (up to 3 km height) to simulate the heavy rainfall event during 26–29 January associated with the 2002 Jakarta flood. First, we addressed the influence of land-sea contrast and topography on the local circulation, particularly in the area surrounding Jakarta, by replacing the inland topography over western Indonesia (96°–119°E, 17°S–0°) with a water body with an altitude of 0 m. We then compared the results of model simulations with and without topography. The results show that the main role of the topography here is enhancing the upward motion and generating a deep convective cloud in response to the land-based convective system during 26–27 January 2002, which then continuously and rapidly propagates offshore due to the cold pool mechanism. Furthermore, the land-sea contrast has a significant role in increasing sea breeze under the rapidness of the landward propagation system during 28–29 January 2002, which was strengthened by the gravity waves and resulted in early morning convection over coastal regions.

Tephra plumes can cause a significant hazard for surrounding towns, infrastructure, and air traffic. The current work presents the use of a small and compact X-band Multi-Parameter (X-MP) radar for the remote tephra detection and tracking of two eruptive events at Merapi Volcano, Indonesia, in May and June 2018. Tephra detection was done by analysing the multiple parameters of radar: copolar correlation and reflectivity intensity. These parameters were used to cancel unwanted clutter and retrieve tephra properties, which are grain size and concentration. Real-time spatial and temporal forecasting of tephra dispersal was performed by applying an advection scheme (nowcasting) in the manner of Ensemble Prediction System (EPS). Cross-validation was done using field-survey data, radar observations, and Himawari-8 imagery. The nowcasting model computed both the displacement and growth and decaying rate of the plume based on the temporal changes in two-dimensional movement and tephra concentration, respectively. Our results with ground-based data, where the radar-based estimated grain size distribution fell within the range of in-situ data. The uncertainty of real-time forecasted tephra plume depends on the initial condition, which affects the growth-and decaying rate estimation. The EPS improves the predictability rate by reducing the number of missed and false forecasted events. Our findings and the method presented here are suitable for early warning of tephra fall hazard at the local scale.

The article presents development of the more electric turbofan engine in distributed architecture with a design thrust in the range from 3 to 7.5 and from 7.5 to 30 kN for small and medium-sized unmanned aerial vehicles. The engine subsystems are considered as separate smart modules with a built-in control system, exchanging data via a digital channel with the central engine control and diagnostics unit. The key smart engine units are combined in the following subsystems: starter and turbine generators, oil pumps, actuator of guide vanes, fuel pumps, fuel metering unit, control and diagnostic unit. All pumps and guide vane actuator are electrically driven. Control and monitoring signals are transmitted via a digital bus. Functional and reliability analysis, technical configuration design of each subsystem are presented. Based on analysis of the architecture of distributed control system for gearbox-free more electric engine, different configurations of described subsystems are proposed.

The contamination on the insulators may increase its surface conductivity and, as a consequence, electrical discharges occur more frequently, which can lead to interruptions in the power supply. To maintain reliability in the electrical distribution power system, components that have lost their insulating properties must be replaced. Identifying the components that need maintenance, is a difficult task as there are several levels of contamination that are hardly noticed during inspections. To improve the quality of inspections, this paper proposes to use the k-nearest neighbours (k-NN) to classify the levels of insulator contamination, based on the image of insulators at various levels of contamination simulated in the laboratory. Using computer vision features such as mean, variance, asymmetry, kurtosis, energy, and entropy are used for training the k-NN. To assess the robustness of the proposed approach, statistical analysis and a comparative assessment with well-consolidated algorithms such as decision tree, ensemble subspace, and support vector machine models are presented. The k-NN showed results of up to 85.17 % accuracy using the k-fold cross-validation method, with an average accuracy higher than 82 % for multi-classification of the contamination of the insulators, being superior to the compared models.

Urban Tree Canopy (UTC) greatly enhances the livability of cities by reducing urban heat buildup, mitigating stormwater runoff, and filtering airborne particulates, among other ecological services. These benefits, combined with the relative ease of measuring tree cover from aerial imagery, have led many cities to adopt management strategies based on UTC goals. In this study, we conducted canopy analyses for the 300 largest cities in Florida to assess the impacts of development practices, urban forest ordinances, and hurricanes on tree cover. Within the cities sampled, UTC canopy ranged from 5.9% to 68.7% with a median canopy coverage of 32.3% Our results indicate that the peak gust speeds recorded during past hurricanes events were a significant predictor of canopy coverage (P-value = <0.001) across the sampled cities. As peak gust speeds increased from 152 km/h (i.e., a lower-intensity Category 1 storm) to 225 km/h (lower-intensity Category 4 and the maximum gusts captured in our data), predicted canopy in developed urban areas decreased by 7.7%. Beyond the impacts of hurricanes and tropical storms, we found that historic landcover and two out of eight urban forest ordinances were significant predictors of existing canopy coverage (P-landcover <0.001; P-tree preservation ordinance = 0.02, P-heritage tree ordinance = 0.03). Results indicate that local policies and tree protections can protect or enhance urban tree canopy, even in the face of rapid development and periodic natural disturbances.

Evidence on adult mammalian neurogenesis and scarce studies with human brains led to the idea that adult human neurogenesis occurs in the subgranular zone (SGZ) of the dentate gyrus and in the subventricular zone (SVZ). However, findings published from 2018 rekindled controversies on adult human SGZ neurogenesis. We systematically reviewed studies published during the first decade of characterization of adult human neurogenesis (1994–2004) – when the two-neurogenic-niche concept in humans was consolidated – and compared with further studies. The synthesis of both periods is that adult human neurogenesis occurs in an intensity ranging from practically zero to a level comparable to adult mammalian neurogenesis in general, which is the prevailing conclusion. Nonetheless, Bernier and colleagues showed in 2000 intriguing indications of adult human neurogenesis in a broad area including the limbic system. Likewise, we later showed evidence that limbic and hypothalamic structures surrounding the circumventricular organs form a continuous zone expressing neurogenesis markers encompassing the SGZ and SVZ. The conclusion is that publications from 2018 on adult human neurogenesis did not bring novel findings on location of neurogenic niches. Rather, we expect that the search of neurogenesis beyond the canonical adult mammalian neurogenic niches will confirm our indications that adult human neurogenesis is orchestrated in a broad brain area. We predict that this approach may, for example, clarify that human hippocampal neurogenesis occurs mostly in the CA1-subiculum zone and that the previously identified human rostral migratory stream arising from the SVZ is indeed the column of the fornix expressing neurogenesis markers.

Clustered regularly interspaced short palindromic repeats or CRISPR, one of the major technological tools from nature's toolbox, has revolutionized the scientific world with its potential use in humans and plants. CRISPR Cas9 was first known as an adaptive immune system of bacteria. It is a system that cleaves foreign DNA. It has been exploited to be used as a genome editing tool for correcting genetic diseases in humans, for plants to create stress-resistant plants, and for a variety of different purposes. This review provides a basic overview of its applications in different areas of biological research. It has immense potential for a variety of researches, but it's still a mystery for science. It feels like scientists just know a tip of an iceberg.

Here we are concerning with two problems of a coupled system of random and stochastic nonlinear differential equations with two coupled systems of nonlinear nonlocal random and stochastic integral conditions. The existence of solutions will be studied. The sufficient condition for the uniqueness of the solution will be given. The continuous dependence of the unique solution on the nonlocal conditions will be proved.

Integration of battery energy storage in photovoltaic (PV) systems can reduce the electricity costs and provide desirable flexibility and reliability to these systems decreasing renewable energy fluctuations. This paper presents a review of the PV-battery application in Brazil, highlighting the challenges and prospects based on the state-of-art. A PV-battery systems description is presented in this work, as well as the most applied battery technology and its comparison. The paper also describes the set of applications such as voltage and frequency regulation, renewable energy integration, power quality, etc. In the Brazilian scenario, there are applications of PV-battery systems, most of them part of research and development projects (R&amp;D’s), and some real cases are shown, including its goals, applied equipment, operation modes, strategies, and perspectives. Additionally, this work evaluates the Brazilian scenario regarding the energy storage systems implementation challenges, such as regulatory barriers, business models, and opportunities for R&amp;D in the energy market. In conclusion, it is need develop proper regulatory models to expand PV-battery systems and make them visible to the agents in the electricity sector.

Computer systems are involved in many critical human applications today, so that a small error can lead to serious and dangerous problems. These errors can be from an error in the incorrect design of the user interface to an error in the program code. The success of a software product depends on several factors. Given that different organizations and institutions use software products, the need to have a quality and desirable Software according to the goals and needs of the organization makes measuring the quality of software products. an important issue for most organizations and institutions, To be sure of having the right software. It is necessary to use a standard quality model to examine the features and sub-features for a detailed and principled study in the quality discussion. In this study, the quality of Word software was measured by Adaptive Neural Fuzzy Inference System. In recent years, powerful systems called fuzzy inference systems on The basis of adaptive neural network (ANFIS) has been used in various sciences. Using the power of neural network training and the linguistic advantage of fuzzy systems, these types of systems have been able to realize the advantages of the two in terms of analyzing very powerful complex processes. Considering the importance of software quality and to have a good and usable software in terms of quality and measuring the quality of software during the study. It was applied at different levels to make the result of measuring the quality of Word software more accurate and closer to reality. In this research, the quality of the software product is measured based on the adaptive neural-fuzzy inference system in ISO standard. According to the results obtained in this study, it is understood that quality is a continuous and hierarchical concept and the quality of each part of the software at any stage of production can lead to high quality products.

Protein phosphatase 2A (PP2A) is a ubiquitous serine/threonine phosphatase implicated in a wide variety of regulatory cellular functions. PP2A is abundant in the mammalian nervous system and dysregulation of its cellular functions are associated with myriad neurodegenerative disorders. Additionally, PP2A has oncologic implications, recently garnering attention and emerging as a therapeutic target because of the antitumor effects of a potent PP2A inhibitor, LB100. LB100 abrogation of PP2A is believed to exert its inhibitory effects on tumor progression through cellular chemo- and radio-sensitization to adjuvant agents. An updated and unifying review of PP2A biology and inhibition with LB100 as a therapeutic strategy for targeting cancers of the nervous system is needed, as other reviews have mainly covered broader applications of LB100. In this review, we discuss the role of PP2A in normal cells and tumor cells of the nervous system. Further, we summarize current evidence regarding the therapeutic potential of LB100 for treating solid tumors of the nervous system.

With the development of designing and manufacturing level for micro-electromechanical system (MEMS) gyroscopes, the control circuit system becomes a key point to determine their internal performances. Nevertheless, phase delay of electron components may result in some serious hazards. This paper describes a real-time circuit phase delay correction system for MEMS vibratory gyroscopes. A detailed theoretical analysis is provided to clarify the influences of circuit phase delay on the in-phase and quadrature (IQ) coupling characteristics and zero rate output (ZRO) utilizing force-to-rebalance (FTR) closed-loop detection and quadrature correction system. By deducing the relationship between amplitude-frequency, phase-frequency of MEMS gyroscope and the phase relationship of the whole control loop, a real-time correction system is proposed to automatically adjust the phase reference value of phase-locked loop (PLL) and thus compensate for the real-time circuit phase delay. The experimental results show that the correction system can accurately measure and compensate the circuit phase delay in real time. Furthermore, the unwanted IQ coupling can be eliminated and the ZRO is decreased by 755% to 0.095°/s. This correction system realizes a small angle random walk of 0.978°/√h, and a low bias instability of 9.458°/h together with a scale factor nonlinearity of 255 ppm at room temperature. Besides, the thermal drift of ZRO is reduced to 0.0034°/s/°C at a temperature range from -20°C to 70°C.

We work with reference to a well-known semiclassical model, in which quantum degrees of freedom interact with classical ones. We show that, in the classical limit, it is possible to represent classical results (e.g., classical chaos) by means a pure-state density matrix.

Dermal interstitial fluid (ISF) is a novel source of biomarkers that can be considered as an alternative to blood sampling for disease diagnosis and treatment. Nevertheless, in vivo extraction and analysis of ISF are challenging. On the other hand, microneedle (MN) technology can address most of the challenges associated with dermal ISF extraction and is well-suited for long-term, continuous ISF monitoring as well as in situ detection. In this review, we first briefly summarise the different dermal ISF collection methods and compare them with MN methods. Next, we elaborate on the design considerations and biocompatibility of MNs. Subsequently, the fabrication technologies of various MNs used for dermal ISF extraction, including solid MNs, hollow MNs, porous MNs and hydrogel MNs, are thoroughly explained. In addition, different sensing mechanisms of ISF detection will be discussed in detail. Subsequently, we identify the challenges and propose the possible solutions associated with ISF extraction. A detailed investigation is provided for the transport and sampling mechanism of ISF in vivo. Also, the current in vitro skin model integrated with the MN arrays will be discussed. Finally, future directions to develop a point-of-care (POC) device to sample ISF are proposed.

Multiple sclerosis (MS) is a chronic inflammatory neurodegenerative autoimmune disease characterized by aberrant infiltration of immune cells into the central nervous system (CNS) and by the loss of myelin. Sclerotic lesions and various inhibitory factors hamper remyelination processes within the CNS. MS patients typically experience gradual cognitive and physical disabilities as the disease progresses. The etiology of MS is still unclear and emerging evidence suggests that microbiome composition could play a much more significant role in disease pathogenesis than was initially thought. Initially believed to be isolated to the gut microenvironment, we now know that the microbiome plays a much broader role in various tissues and is essential in the development of the immune system. Here, we present some of the unexpected roles that the microbiome plays in MS and discuss approaches for the development of next-generation treatment strategies.

Machine Learning (ML) and Artificial Intelligence(AI) have revolutionized almost all fields that are linked to the acquisition of intelligent behavior in the real world. It is an attractive alternative for a researcher of artificial intelligence. Contrary to rule-based programming, ML is an algorithmic approach in which learning comes from existing data. The more data we have these computer systems look at, we say we’re ‘training’ the computer system, and as the computers begin to identify patterns in the data, identify abnormalities in the data from these abnormalities we improve the system architect according to the requirement. This article introduces the use of comprehensive concepts of machine learning, in general, particular, and their potential applications in communications. Furthermore, the current state and futuristic potentials of enabling universal communication with implications of machine learning methods have been explained. In this review paper, we offer a comprehensive talk on distinctive methods/techniques of information analytics, artificial intelligence (AI), and machine learning (ML) moved forward the contact aware communication system.

In spite of unique structural, spectroscopic and redox properties, the synthetic variants of the planar, antiaromatic hexaphyrin (1.0.1.0.1.0) derivatives 2, has been limited due to the low yields and difficulty in access to the starting material. A chemical modification of the meso-substituents could be good alternative overcoming the synthetic barrier. Herein, we report a regio-selective nucleophilic aromatic substitution (SNAr) of meso-pentafluorophenyl group in rosarrin 2 with catechol. The reaction afforded benzodioxane fused rosarrin 3 as single product with high yield. The intrinsic antiaromatic character of the starting rosarrin 2 retained throughout the reactions. Clean, two electron reduction was achieved by treatment of 3 with SnCl2•2H2O affording 26pi-electron aromatic rosarrin 4. The synthesized compounds exhibited noticeable changes in photophysical and redox properties compared with starting rosarrin 2. .

Wireless Sensor Networks (WSN) is the network of the resource-constrained network which forms the foundation of the Internet of Things (IoT). The Routing Protocol for Low-power and Lossy Networks (RPL) is responsible for generating and managing data routing paths. Nodes implementing RPL uses the mechanics of Objective Function (OF) to select the preferred next-hop node – parent node, and optimal routing path to the destination node. If routing decisions are not efficiently made, this results in increased collision domain, leading to packet losses and packet retransmission which impairs the network operational lifetime. In this study, we present the Contiki Operating System (OS), a state-of-the-art OS for IoTs, ContikiRPL; Contiki variant of RPL. We investigated the performance of RPL with respect to its two OFs; Objective Function Zero (OF0) and the Minimum Rank with Hysteresis Objective Function (MRHOF). The performance of these OFs was evaluated on the following metrics; Packet Delivery Ratio (PDR), Power consumption, and network latency. The result shows that MRHOF outperformed OF0 on all metrics with an overall average PDR of 91.5%, a latency of 44ms, and power consumption of 1.72mW across all nodes. This results in optimal network performance with improved network operational lifetime.

At present, the drilling rig for deep seabed shallow strata is widely used in the exploration of ocean cobalt-rich crust resources and other fields, which not only can obtain solid core samples at a specific station, but the operation process is relatively safe. This paper mainly presents the structure and mechanism of mobile drilling rig in acquiring the seafloor cores (up to 1.5 m long). Based on the function of the AMESim software, the hydraulic propulsion system model of mobile drilling rig is established, which is the basis and core part of the mobile drilling rig. Moreover, the control methods of closed-loop and PID are respectively used to control the hydraulic propulsion system for simulation analysis. Through the comparison of simulation results, it is found that the PID control method is more convincing in verifying the design rationality of hydraulic propulsion system. In the simulation of the PID-controlled hydraulic propulsion system, the co-simulation technology of AMESim and Matlab/Simulink not only establishes the hydraulic model and control model, but also determines the relevant simulation parameters, which is helpful to improve the system simulation efficiency. In its verification deployment in the South China Sea, the mobile drilling rig has been operated for many times at different depths, and some cores have been successfully obtained. Furthermore, the mobile drilling rig has been used during the 55th Voyage of China Oceanic Scientific Expedition supported by China Ocean Mineral Resources R&D Association. Several sites were explored and a large number of cobalt-rich crust cores were obtained. The powerful theory and sea trails are provided to support for the further research on survey of the abyssal resource.

: A strong financialtransaction is an important factor in organizational triumph and sustainability, and it is elucidated in the revised student handbook of the University that can be found on page 96 rules 1 to 5. This study assessed the registered students organizations' profile in terms of its type, registration, years of establishment, functions, and designations of student leaders and advisers. The financial practices or internal control system manages their organizational finances and the problems encountered by the student organizations and eventually proposed a manual of operation for students and youth organization's internal control system. This research used the descriptive design with the aid of questionnaire; data gathering through quota sampling from 57 student leaders and advisers of different student organizations of NEUST. Findings showed that most organizations had their constitution and by-laws but kept only as files and renewal requirements. Some provisions were not known to the officers, mostly were registered more than five years in operation; however, in terms of functions of officers and advisers, the results showed that some functions were not done by the officers who supposed to do it like the auditors who serve as treasurers also, the PRO as the record keeper and the presidents who handled finances and collections and as well as disbursements of funds. Generally, the organizations' financial activities were deemed to be "good", especially budgeting and cash receipt, due to the implementation of "no collection and no tuition fee policy". The researchers concluded that the absence of the proper internal control systems and manual of operation and lack of proper transfer of financial records from the previous sets of officers were the serious problems that should be addressed. Moreover, the student organizations' internal control system could still be improved if there is proper training and supervision in accounting operation.

Due to the tremendous progress in the automotive industry, the growth of the urban population, the number of vehicles is increasing and this creates parking challenges. Intelligent parking management systems offer an optimal solution for finding empty parking space so that drivers can quickly find their car parking space. To solve these problems, it is necessary to design an intelligent parking system, in addition to providing comfort to drivers, which is also economically viable. This paper proposes an intelligent multi-storey car parking system with the help of RFID technology and examining user preferences that can effectively solve car parking problems. The proposed method is a multi-objective decision-making method to reduce the problem of car parking, which is called MODM-RPCP. Therefore, the proposed MODM-RPCP method can allocate the best space for their stopping place by using the decision-making system and based on the priorities considered by the users. The simulation results show that the MODM-RPCP reduces the average booking time more than 19.2% and 27.1%, and decreases the response time of central parking management server more than 20.1% and 29.78% compared to MOGWOLA and ODPP approaches.

This paper presents a new analytical method for obtaining new deformations compatibility equations or, new Saint-Venant’s identities, into the relative coordinate system with projected deformations by applying the hypothesis of the lineal shell theory in general flexion state. The method proposed generalizes the compatibility conditions established by A.L. Goldenveizer for the shell theory. On the other hand, the new equations include the deformations compatibility equations by other authors: Flügge, Saint-Venant, Love-Kirchhoff, Timoshenko, Goldenveizer, and Reissner-Mindlin. The results showed an increase of knowledge in general shell theory, and provide inverse and semi-inverse solutions, whose systems solution correspond to the hyper-statics degrees of the physical model, and not to their degrees of freedom.

This paper proposes a mathematical model to simulate Day-ahead markets of large-scale multi-energy systems with high share of renewable energy. Furthermore, it analyses the importance of including unit commitment when performing such analysis. The results of the case study, which is performed for the North Sea region, show the influence of massive renewable penetration in the energy sector and increasing electrification of the district heating sector towards 2050, and how this impacts the role of other energy sources such as thermal and hydro. The penetration of wind and solar is likely to challenge the need for balancing in the system as well as the profitability of thermal units. The degree of influence of the unit commitment approach is found to be dependent on the configuration of the energy system. Overall, including unit commitment constraints with integer variables leads to more realistic behaviour of the units, at the cost of increasing considerably the computational time. Relaxing integer variables reduces significantly the computational time, without highly compromising the accuracy of the results. The proposed model, together with the insights from the study case, can be specially useful for system operators for optimal operational planning.

There is a marked momentum towards the use of clean hydrogen energy as an alternative for fossil fuels. Renewable energies such as solar and wind are being used to generate hydrogen from the water hydrolysis process. Indeed, this approach stores renewable energies in the form of combustible hydrogen for other energy uses. The other alternative that could be economically more cost-effective at the current technology stage is to explore the natural “Hydrogen System” where the natural hydrogen is generated and accumulated within the earth system, the same that stands for a “Petroleum System”. The Discovery of a large accumulation of relatively pure natural hydrogen (H2) in Mali has triggered the opportunity of searching for natural hydrogen accumulations in other countries. The generation of hydrogen from a circular depression in Mali and some other countries is linked to the presence of geologically very old iron-rich basement rocks. Solid-liquid redox reactions between iron-rich minerals and groundwater that split water are a possible source of H2 in deep basement rocks. It is believed that the hydrogen degassing may be detected by surface topographic circular to sub-circular shallow depressions. Chemical processes such as dissolution by hydrogen are considered to play the main role in the formation of the circular depressions through preferential vertical hydrogen migration channel. Archean iron-rich Yilgarn Craton that covers a vast area of Western Australia (WA) contains abundant iron-rich mafic-ultramafic rocks. The craton reveals many surficial circular depressions visible through satellite images. The area has abundant fault systems and is blanketed with Eocene sedimentary rocks containing high-quality reservoir rocks. All these characteristics seem to provide most of the required elements, such as hydrogen source, migration pathway, and reservoir rock for a “Hydrogen System” in this area.

In this paper, we study the Parisian time of a reflected Brownian motion with drift on a finite collection of rays. We derive the Laplace transform of the Parisian time using a recursive method, and provide an exact simulation algorithm to sample from the distribution of the Parisian time. The paper is motivated by the settlement delay in the real-time gross settlement (RTGS) system. Both the central bank and the participating banks in the system are concerned about the liquidity risk, and are interested in the first time that the duration of settlement delay exceeds a predefined limit, we reduce this problem to the calculation of the Parisian time. The Parisian time is also crucial in the pricing of Parisian type options; to this end, we will compare our results with the existing literature.

The work safety standardization of enterprises based on the traditional work safety theory has played a significant role in reducing the number of accidents and improving work safety to some extent in China. However, some problems are coming with the work safety standardization of enterprises developing constantly in China. On the one hand, it is not combined with the actual situation of the enterprise, lacking pertinence and specificity, these defects resulted that it is not integrated with original safety production management system of enterprise and make it difficult to carry out. On the other hand, there is a lack of systematic management methods for the work safety management system of enterprise, most of enterprises only pay attention to the inspection result rather than the process control. This means after the check of the government, many enterprises will relax to carry out the system. This paper puts forward a new method for optimizing the standardization management mode of work safety based on the Viable System Model(VSM), which can solve the defects of work safety standardization of enterprises management system. An optimization model of work safety standardization based on VSM was construct for explaining the process optimization and control of work safety standardization management. It can improve the connectivity between the enterprise and the government. The conclusion of this paper can provide reference for achieving the development and optimization of work safety standardization of enterprises in China.

This paper reports on the changing dynamics of a small town’s social-ecological system (SES) concerning oil and gas industry boom-bust economic cycles and both the vulnerability and resilience of the town over the past 30 years. With the goal to understand how resource-based single industry impact social-ecological systems, we developed indicators of human and environmental well-being and assessed them. Seven indicators include labor force distribution, education, oil price, household income, water quality, air quality, and land cover land use. Over this period, Drayton Valley, Canada quadrupled in size, with more than 20% of the population working in the oil and gas sector. Median income rose to 42% above the national average despite the population lagging national benchmarks for educational attainment. There have also been dramatic fluctuations in levels of fluoride, phosphorus, and other chemicals in water quality samples, implying a correlation with fossil fuel extractive activities over this period. Land cover land use change analysis shows a decreased area of water bodies, wetland, and forests, and increased built capital and agricultural land. While economic boom cycles have led to cash inflows, an exclusive focus on the benefits of the oil and gas industry may leave those dependent on the industry vulnerable to social and environmental risk factors during bust cycles that are beyond their control in the everchanging global oil economy. This phenomenon which has been referred to as the “resource curse” suggests the need to anticipate cyclical (or more sustained) periods of low levels of oil and gas production. These results suggest that single boom-bust economies impact every aspect of social-ecological systems. Therefore, a sustainable development plan that comprehensively considers not only economic growth, but also diversification, environment protection, and strategic land use planning is indispensable to ensure the long-term development of communities that depend upon extractive industries.

Establishing an accurate mathematical model is the foundation of simulating the motion of marine vehicles and structures, and it is the basis of modeling-based control design. System identification from observed input-output data is a practical and powerful method. However, for modeling objects with different characteristics and known information, a single modeling framework can hardly meet the requirements of model establishment. Moreover, there are some challenges in system identification, such as parameter drift and overfitting. In this work, three robust methods are proposed for generating ocean hydrodynamic models based on Bayesian regression. Two Bayesian techniques, semi-conjugate linear regression and noisy input Gaussian process regression, are used for parametric and nonparametric gray-box modeling and black-box modeling. The experimental free-running tests of the KVLCC2 ship model and a multi-freedom wave energy converter (WEC) are used to validate the proposed Bayesian models. The results demonstrate that the proposed schemes for system identification of the ship and WEC have good generalization ability and robustness. Finally, the developed modeling methods are evaluated considering the aspects required conditions, operating characteristics and prediction accuracy.

The information on the land use and soil conservation practice based on year 2006, 2010 and 2014, hence offering an opportunity to model the impacts of land use change on erosion, deposition and surface water runoff. Limitation in the use of hydrological models had been their inability to handle the large amount of input data that describe the heterogeneity of the natural system. In this study, a procedure that takes into account soil conservation practice based on the land use change, the response of soil erosion and sediment export from the George Town Conurbation catchment area, and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion areas of rural and urban planning proposes. Average annual sediment yield and data on a grid basis estimated using Universal Soil Loss Equation (USLE) and an emerging technology represented by Geographic Information System (GIS) used as a tool to produce a map for erosion rate. The changing of the land use from forest to agriculture and then to an urban area is a challenging task to research on land use demand for population, and environmental impact assessment is important for the planning of natural resources management, allowing research the modification of land use properly and implement more sustainable for long term management strategies. The challenge is to formulate strategies that would promote an integrated approach to the land use planning at an appropriate level as to address the issues that arose. Modelling for creating urban growth boundary for the George Town Conurbation must have to be controlled surface runoff and soil loss and sediment export from land use of the George Town Conurbation catchment.

Although the failure of antibiotic treatment is normally attributed to resistance, tolerance and persistence display a significant role in the lack of response to antibiotics. Due to the fact that several nosocomial pathogens show a high level of tolerance and/or resistance to chlorhexidine, in this study we analyzed the molecular mechanisms associated with chlorhexidine adaptation in two clinical strains of Klebsiella pneumoniae by phenotypic and transcriptomic studies. These two strains belong to ST258-KPC3 (high-risk clone carrying β-lactamase KPC3) and ST846-OXA48 (low-risk clone carrying β-lactamase OXA48). Our results showed that K. pneumoniae ST258-KPC3CA and ST846-OXA48CA strains exhibited a different behavior under CHLX pressure, adapting to this biocide through resistance and tolerance mechanisms, respectively. Furthermore, the appearance of cross-resistance to colistin was observed in the ST846-OXA48CA strain (tolerant to CHLX), using the broth microdilution method. Interestingly, this ST846-OXA48CA isolate contained a plasmid that encodes a novel type II toxin/antitoxin (TA) system, PemK/PemI. We characterized this PemK/PemI TA system by cloning both genes into the IPTG-inducible pCA24N plasmid, and found their role in persistence and biofilm formation. Accordingly, the ST846-OXA48CA strain showed a persistence biphasic curve in the presence of a chlorhexidine-imipenem combination, and these results were confirmed by the enzymatic assay (WST-1).

Dysregulation of the angiotensin-II Type-I receptor (AT1R) and its pathway was reported to associate with poor-prognosis in several malignancies, including colorectal-cancer (CRC). We have explored the therapeutic-potential of targeting AT1R using valsartan, and its pharmacological-interaction with Fluorouracil (5-FU) in CRC. Anti-proliferative function was evaluated in 2-/3-dimensional cells and in vivo models. Anti-proliferative, anti-migratory, apoptotic function and effect on cell-cycle was assessed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), wound-healing test, and Fluorescence-activated cell sorting (FACS), respectively, while gene-expression was determined at mRNA/protein levels. By histogical analysis and measuring of oxidative/antioxidant markers, we evaluated the anti-inflammatory properties of valsartan. Valsartan suppressed cell-growth and impacted the anti-tumor-activities of 5-FU by apoptosis-induction. Valsartan inhibited the cells migration by perturbation of Matrix metalloproteinase (MMP1). Furthermore, valsartan inhibited tumor-growth and metastasis, and this was more notable in valsartan/5-FU combination-treated-group. The mechanism was plausible to be via the induction of Reactive-oxygen-species (ROS) and down-regulation of Superoxide-dismutase (SOD), thiol/catalase (CAT) as well as Vascular endothelial growth factor (VEGF) and Transforming growth factor beta (TGF-β). Valsartan may protect cells against intestinal fibrosis by modulation of pro-fibrotic and pro-inflammatory components include fibronectin, Interleukin) IL-1β (, Tumor necrosis factor alpha) TNF-α (, Interferon gamma) INF-γ (, and Monocyte Chemotactic Protein 1 (MCP-1). Our findings demonstrated that targeting the AT1R receptor may inhibit tumor-growth and ameliorate fibrosis and inflammation associated with CRC via modulation of AT1 and TGF-β pathways.

In this study, a three-dimensional bioelectrochemical reactor system (3D-BERs) with granular activated carbon (GAC) epitomizes a novel treatment technology for treating nitrate-polluted water. The conventional denitrification process faces many challenges, including the huge demand for organic carbon, long-term accumulation of intermediate products, and the adaptation period. Results shown that under the optimal conditions of the COD/NO3--N ratio was 1.5, the denitrification efficiency reached 98.62%, when compared to 81.12% at COD/ NO3--N ratio of 3.5, and the initial pH of 7.5 ± 0.5, NO3--N was entirely removed at 2.2 h without accumulation of nitrite. The high initial ratio of NO2--N/NO3--N is mainly to accelerate the denitrification rate by accelerating the reduction of nitrite. Denitrification process followed by zero-order kinetics linear model for at different concentrations of inlet NO3--N, and achieved higher denitrification rate at greater inlet NO3--N concentration. High-throughput sequencing shows that the community structure and relative abundance of bacteria changed significantly, especially at the genes and the phyla level in immobilized GAC particles. Microbial composition enhanced the removal of nitrogen at the inner surface (IS) and bottom surface (BS) of immobilized GAC carriers. Therefore, this system is expected to be a more efficient and useful supplement or a cost-effective alternative compared to the traditional low carbon to nitrogen wastewater treatment system.

The landscape of centralized cloud computing is now changing to distributed and decentralized clouds with promising impacts on energy consumption, resource availability, resilience, and customer experience. This research highlights the impacts of emerging IT trends, namely, 5G wireless technology, blockchain, and industrial Artificial Intelligence (AI) in development and realization of the next generation of cloud computing. Integration of these technologies in cyber-physical system and cloud manufacturing paradigms is explained and a unified edge-fog-cloud architecture is proposed for successful implementation in manufacturing systems.

Smoking is a risk factor for respiratory infections and there is reasonable concern that it may affect COVID-19 susceptibility and severity. Recent studies have focused on the interaction between smoking (and nicotine) and ACE2 expression, suggesting that ACE2 up-regulation could contribute to enhanced viral cell entry. However, case series have shown that there is an unexpectedly low prevalence of smoking among hospitalized COVID-19 cases. Since early April, we were the first to hypothesize that dysfunction of the nicotinic cholinergic system (NCS) may be implicated in the pathophysiology of severe COVID-19. We recently reported that many of the clinical manifestations of severe COVID-19 could be explained by dysregulation of the NCS. In this study, we present an amino acid sequence in the receptor binding domain of the SARS-CoV-2 Spike glycoprotein which is homologous to a sequence of a snake venom toxin. We present the 3D structural location of this “toxin-like” sequence on the Spike Glycoprotein. These findings suggest that SARS-CoV-2 could potentially interact with acetylcholine receptors causing dysregulation of the NCS and the cholinergic anti-inflammatory pathway.

The state of community lock-down due to COVID-19 pandemic caused restricted movements of people. There are existing evidence of the negative impact of quarantine and isolation to the mental health of a person in different contexts. A scoping review of literature using Google Scholar was conducted to discover records about the public mental health while in a community quarantine due to COVID-19 pandemic. A methodological approach suggested by Arksey and O’Malley was utilized. It comprised (a) identifying the research questions, (b) identifying relevant literatures, (c) selecting literature, (d) charting the extracted data, and (e) summarizing, analyzing, and reporting the results. As of April 17, 2020, there were only 4 original articles found that discuss psychosocial aspect of the COVID-19 crisis. After an online survey, they present evidence that (1) there is an outward change in the people’s behavior toward self-care during the pandemic and (2) trusting the community governing bodies can minimize the level of anxiety and stress. Other literatures found are original articles in preprint (n=8), letters, commentaries, editorial (n=6), review paper (n=4), and WHO guideline (n=1). It is evident that the psychosocial aspect of COVID-19 crisis needs more attention from the scholars and a large research gap can be lessened trough expansion of online platforms.

Objective: On March 11, 2020 the WHO declared that COVID-19 is pandemic. Among the risk factors for many infectious diseases, a role of the ABO blood group system is reported in the literature. We argue whether it is necessary to investigate the relationship between ABO blood groups and susceptibility to SARS-CoV-2 infection and if we should consider some blood groups as potential risk factors for COVID-19. Results: Based on the scientific evidence reported in this letter, we believe that further studies are needed to investigate how the ABO polymorphism influences the host susceptibility, individual response and clinical risk for SARS-CoV-2 infection.

The interaction between endocannabinoid (eCB) system with in key brain structures such as hippocampus, amygdala and prefrontal cortex and sleep deprivation (SD)-induced psychosis has been less studied. The present hypothesis revolves around the question whether altered chemical dynamics within the eCB system with the resultant impact on cannabinoid receptors in key cortical hubs would impact SD-induced psychosis-like symptoms. Having this investigated research is expected to pave the path towards identifying newer drug targets namely for schizophrenia.

Market-orientation is widely applied to understand the expected interaction of smallholder farmers with input and output markets. Commonly used interchangeably with market participation, it is fast becoming a key milestone for attaining smallholder commercialization. This study introduces the term into the disaster resilience, seed systems and livelihoods context. Using a mixed methods approach, 120 smallholder farmers in a drought-affected district of South Africa were sampled, and information collected for analysis. The result shows that most of the farmers rely on purchased seeds and fertilizers for crop production, and on average sold 62% of their farm produce. A market orientation index (MOI) of 55% was estimated, showing that the farmers were market oriented. The farm size, quantities of seeds and fertilizer purchased, value of crop produced, amount received from crop sales, distance to markets and access to credit were found significant in determining their market orientation. Policy interventions were made to improve access to irrigation, seed varieties and extension delivery in the area. The finding has implications for development efforts at rebuilding after a natural disaster, as well as sourcing food aid from local smallholder farmers by humanitarian actors.

Humanity’s social and economic development has been challenged by a range of adversities over the millennia that have caused widespread and unimaginable suffering. At the same time, these challenges have forced humans to evolve more wisely, overcoming adversity through creativity and leading to advancements in science and technology, medicine, ethics and legal systems, and socio-political systems. The dynamics of risks and opportunities caused by COVID-19, in the built, cyber, social and economic environments, present opportunities for deepening our understanding of resilient and sustainable development and infrastructure. This article reflects on five lessons that COVID-19 is teaching us about what it means to develop sustainably through the lens of transportation: (1) sustainable development planning and analytical frameworks must be comprehensive, for long-term sustainability; (2) multi-modal transportation is a superior vision for sustainable development than any one particular mode; (3) tele-activities are part of an effective infrastructure sustainability strategy; (4) economic capital is critically important to sustainable development even when it is not a critical existential threat, and, (5) effective social capital is essential in global disaster resistance and recovery, and can and must be leveraged between fast-moving and slow-moving disasters. Resilient and sustainable infrastructure will continue to be critical to addressing evolving natural and man-made hazards in the 21^st Century.

3M syndrome is a rare disorder that involves the gene CUL7. CUL7 modulates odour detection, conditions the olfactory response (OR) and plays a role in olfactory system development. Despite this involvement, there are no direct studies on olfactory functional effects in 3M syndrome. The purpose of the present work was to analyse the cortical OR, through chemosensory event-related potentials (CSERP) and power spectra calculated by electroencephalogram (EEG) signals recorded in 3M infants: two twins (3M-N) and an additional subject (3M-O). The results suggest that olfactory processing is diversified. Comparison of N1 and LPC components indicated substantial differences in 3M syndrome that may be a consequence of a modified olfactory processing pattern. Moreover, the presence of delta rhythms in 3M-O and 3M-N clearly indicates their involvement with OR, since the delta rhythm is closely connected to chemosensory perception, in particular to olfactory perception.

In this paper, we study the existence of the random -pullback attractor of a non-autonomous local modified stochastic Swift-Hohenberg equation with multiplicative noise in stratonovich sense. It is shown that a random -pullback attractor exists in when its external force has exponential growth. Due to the stochastic term, the estimate are delicate, we overcome this difficulty by using the Ornstein-Uhlenbeck(O-U) transformation and its properties.

In order to increase the number of tourism in ecotourism, enhance the ecotourism attractions. It is essential to construct the ecotourism service system for the Penghu National Scenic Area because the ecology system is sensitive and frangible. This study adopts the Fuzzy Delphi method and Analytic Hierarchy Process (AHP) to establish an index framework of ecotourism service system of Penghu National Scenic Area. The results indicated that there are 4 dimensions which include 21 factors service attributes are identified as the service system for traveling. The findings are concluded as follows:(1)the security management capability is the main principle for ecotourism service system;(2)the ecological diversity is fundamental for the marine environment and the core resource for ecotourism;(3)the transportation capacity and environmental quality need to improve; (4)the marine environmental resources is the most important item for sound ecotourism development; (5)the enhancement of the operation willingness of local communities can promote ecotourism development;(6)the natural resources should be protected to provide an ideal recreational environment for ecotourism;(7)the development of ecotourism needs to support local conservation to achieve sustainability. The perspectives of sustainability and service system are involved to support the value of this study, which can continuously sustain Penghu archipelago.

As entrepreneurial interest is believed to represent a causal factor increasing entrepreneurship, research has begun to explore how family systems affect youth entrepreneurial interests. In the present study, we attempt to identify different types of family influence on the entrepreneurial interests of young people. A questionnaire was used to obtain data from 1,633 Spanish youths, who were 15 to 18 years old, and another questionnaire was used to obtain data from 839 parents. Principal Component Analysis identified unique family types and revealed that they have differential associations to entrepreneurial interest among youths. These findings reaffirm the influence of family on the entrepreneurial ecosystem and the promotion of an entrepreneurial family cuture. This study further suggests that early attention should focus on the detection of entrepreneurial interest among youths so that actions can be implemented in the families of low-interest youths to incentivize an entrepreneurial family culture.

It is proposed that both human creativity and human consciousness are (unintended) consequences of the human brain’s extraordinary energy efficiency. The topics of creativity and consciousness are treated separately, though have a common sub-structure. It is argued that creativity arises from a synergy between two cognitive modes of the human brain (which broadly coincide with Kahneman’s Systems 1 and 2). In the first, available energy is spread across a relatively large network of neurons. As such, the amount of energy per active neuron is so small that the operation of such neurons is susceptible to thermal (ultimately quantum decoherent) noise. In the second, available energy is focussed on a small enough subset of neurons to guarantee a deterministic operation. An illustration of how this synergy can lead to creativity with implications for computing in silicon are discussed. Starting with a discussion of the concept of free will, the notion of consciousness is defined in terms of an awareness of what are perceived to be nearby counterfactual worlds in state space. It is argued that such awareness arises from an interplay between our memories on the one hand, and quantum physical mechanisms (where, unlike in classical physics, nearby counterfactual worlds play an indispensable dynamical role) in the ion channels of neural networks. As with the brain’s susceptibility to noise, it is argued that in situations where quantum physics plays a role in the brain, it does so for reasons of energy efficiency. As an illustration of this definition of consciousness, a novel proposal is outlined as to why quantum entanglement appears so counter-intuitive.

In power systems, flow allocation (FA) methods allow to allocate usage and costs of the transmission grid to each single market participant. Based on predefined assumptions, the power flow is split into isolated generator specific or producer specific sub-flows. Two prominent FA methods, Marginal Participation (MP) and Equivalent Bilateral Exchanges (EBE), build upon the linearized power flow and thus on the Power Transfer Distribution Factors (PTDF). Despite their intuitive and computationally efficient concept, they are restricted to networks with \emph{passive} transmission elements only. As soon as a significant number of \emph{controllable} transmission elements, such as High-voltage direct current (HVDC) lines, operate in the system, they loose their applicability. This work reformulates the two methods in terms of Virtual Injection Patters (VIP) which allows to efficiently introduce a shift parameter $q$, tuning contributions of net sources and net sinks in the network. Major properties and differences of the methods are pointed out. Finally, it is shown how the MA and EBE algorithm can be applied to generic meshed AC-DC electricity grids: Introducing a \emph{pseudo-impedance} which reflects the operational state of controllable elements, allows to extend the PTDF matrix under the assumption of knowing the current system's flow. Basic properties from graph theory are used for solving the pseudo-impedance dependent on the position in the network. This directly enables \emph{e.g.} HVDC lines to be considered in the MP and EBE algorithm. The extended methods are applied to a low-carbon European network model (PyPSA-EUR) with a spatial resolution of N=181 and an 18\% transmission expansion. The allocations of VIP and MP, show that countries with high wind potentials profit most from the transmission grid expansion. Based on the average usage of transmission system expansion a method of distributing operational and capital expenditures is proposed. Further it is shown, how injections from renewable resources strongly drive country-to-country allocations and thus cross-border electricity flows.

Being a chilling-sensitive staple crop, rice (Oryza sativa L.) is vulnerable to climate change. The competence of rice to withstand chilling stress should, therefore, be enhanced through technological tools. The present study employed chemical intervention like application of sodium nitroprusside (SNP) as nitric oxide (NO) donor and elucidated the underlying molecular mechanisms of NO-mediated chilling tolerance in rice. At germination stage, germination indicators were interrupted by chilling stress (5.0 ± 1.0°C for 8 h day‒1), while pretreatment with 100 μM SNP markedly improved the indicators. At seedling stage (14-day-old), chilling stress caused stunted growth with visible toxicity along with alteration of biochemical markers, for example, increase in oxidative stress markers (superoxide, hydrogen peroxide, and malondialdehyde) and osmolytes (total soluble sugar; proline and soluble protein content, SPC), and decrease in chlorophyll (Chl), relative water content (RWC), and antioxidants. However, NO application attenuated toxicity symptoms with improving growth performance which might be attributed to enhanced activities of antioxidants, mineral contents, Chl, RWC and SPC. Furthermore, principal component analysis indicated that water imbalance and increased oxidative damage were the main contributors to chilling injury, whereas NO-mediated mineral homeostasis and antioxidant defense were the critical determinants for chilling tolerance in rice. Collectively, our findings revealed that NO protects against chilling stress through valorizing cellular defense mechanisms, suggesting that exogenous application of NO could be a potential tool to evolve cold tolerance as well as climate resilience in rice.

Integrated Model of Distributed Systems is used for modeling and verification. In formalism, the distributed system is modeled as a collection of server states and agent messages. The evolution of the system takes the form of actions that transform the global system configuration (states and messages) into a new configuration. Formalism is used in the Dedan verification environment for finding different kinds of deadlocks: communication deadlocks in the server view and resource deadlocks in the agent view. For other purposes, a conversion has been developed to equivalent models: to Petri nets for structural analysis and do Distributed Autonomous and Asynchronous Automata (DA3) for easy graphical modeling in terms of system components. In addition, it is possible to simulate a verified system on distributed components in DA3. The automata have two forms: Server-DA3 (S-DA3) for the server view and Agent-DA3 (A-DA3) for the agent view. DA3 formalism is compared to other concepts of distributed automata known from the literature.

The brain, rather than being homogeneous, displays an almost infinite topological genus, because is punctured with a very high number of topological vortexes, i.e., .e., nesting, non-concentric brain signal cycles resulting from inhibitory neurons devoid of excitatory oscillations. Starting from this observation, we show that the occurrence of topological vortexes is constrained by random walks taking place during self-organized brain activity. We introduce a visual model, based on the Pascal’s triangle and linear and nonlinear arithmetic octahedrons, that describes three-dimensional random walks of excitatory spike activity propagating throughout the brain tissue. In case of nonlinear 3D paths, the trajectories in brains crossed by spiking oscillations can be depicted as the operation of filling the numbers of the octahedrons in the form of “islands of numbers”: this leads to excitatory neuronal assemblies, spaced out by empty area of inhibitory neuronal assemblies. These procedures allow us to describe the topology of a brain of infinite genus, to assess inhibitory neurons in terms of Betti numbers, and to highlight how non-linear random walks cause spike diffusion in neural tissues when tiny groups of excitatory neurons start to fire.

Stable isotope concentrations in the soil, rain and ground water have been used to trace the water extraction zones of plants in different environments. The need to identify the plant water use by plants in afforestation programs to control desertification increases the importance of sap water partitioning of plants in sand dune areas. However, the introduction of new plant covers exerts pressure on the water resources and can affect the local soil water conditions. In this study, we analyzed the isotope concentrations in rain, soil, sap, and ground water after the summer of 2010. Two experimental plots established in the Hailiutu catchment (Shaanxi province, northwest China) were selected to gather the water samples between September and October 2010. One plot is dominated by Salix bushes (Salix psammophila C. Wang \& Chang Y. Yang) and the other by the tree species Willow (Salix matsudana Koidz.). The total precipitation at the experimental site was 401 mm/yr during 2010, while 88.7 mm was collected in total for the period September to October. Willow trees transpired 12.82 kg/d being almost three times larger than Salix shrubs (4.57 kg/d). Despite the transpiration rates of both plant species and the few rain events in the region, the soil water beneath the plant covers is not depleted. Stable isotope signature of soil water beneath both covers shows the fractionation front in Salix at 20 cm depth and at Willow at 40 cm depth. However, soil water signature is closer to the groundwater than the collected rain water.

There are four subtypes of adenosine receptors (ARs), named A1, A2A, A2B and A3, all of which are G protein-coupled receptors. The A2BAR, coupled to both Gαi and Gαq G proteins, is one of the several G-protein-coupled receptors that are expressed in a significantly higher level in some cancer tissues in comparison to adjacent normal tissues. There is growing evidence that the A2BAR plays an important role in tumor cell proliferation, angiogenesis, metastasis, and immune suppression. Thus, A2BAR antagonists are potentially novel attractive anticancer agents. Several antagonists targeting at the A2BAR are currently in clinical trials for various types of cancers. In this review, we first describe the signaling, agonists, and antagonists of the A2BAR. We further discuss the role of the A2BAR in the progression of various types cancers, and the rationale of using A2BAR antagonists in cancer therapy

The existence of a common ancestor to all living organisms in Earth is a necessary corollary of Darwin idea of common ancestry. The Last Universal Common Ancestor (LUCA) has been normally considered as the ancestor of cellular organisms that originated the three domains of life: Bacteria, Archaea and Eukarya. Recent studies about the nature of LUCA indicate that this first organism should present hundreds of genes and a complex metabolism. Trying to bring another of Darwin ideas into the origins of life discussion, we went back into the prebiotic chemistry trying to understand how LUCA could be originated under gradualist assumptions. Along this line of reasoning, it became clear to us that the definition of another ancestral should be of particular relevance to the understanding about the emergence of biological systems. Together with the view of biology as a language for chemical translation, on which proteins are encoded into nucleic acids polymers, we glimpse a point in the deep past on which this Translation mechanism could have taken place. Thus, we propose the emergence of this process shared by all biological systems as a point of interest and propose the existence of this pre-cellular entity named FUCA, as the First Universal Common Ancestor. FUCA was born in the very instant on which RNA-world replicators started to be capable to catalyze the bonding of amino acids into oligopeptides. FUCA has been considered mature when the translation system apparatus has been assembled together with the establishment of a primeval, possibly error-prone genetic code. This is FUCA, the earliest ancestor of LUCA’s lineage.

Despite considerable progress in the diagnosis of various diseases, an ideal, simple tool for diagnosing patients with respiratory tract infections has not yet been invented. Many simple diagnostic tests are widely available to most doctors, provided they are aware of the prevalence of primary immunodeficiency. Other, more accurate studies are available only to immunologists. The aim of the study was to investigate the occurrence of dependence between selected physical parameters of serum such as: electrical conductivity, electrical permeability, dielectric loss factor, and selected parameters of the immune system. In addition, we have also included the ionogram (Na, K, Cl, Ca, Mg) and glucose concentration. As a result of research, the statistically significant, but very weak correlations between impedance magnitude |Z| and platelet counts (PLT), mean platelet volume (MPV) and chloride ions (Cl-) were found. The statistically significant differences according |Z| between children with and without deficiency in parameters of the immune system were noticed. Values of |Z| are higher in the case of children without deficiency in parameters of the immune system. The method of impedance measurements presented in our work is significantly easier then biosensors presented by other scientists. Taking into account our results, it can be stated that this method is promising for fast and easy detection of immunological disorders.

Rapid technological advancements in information communication technologies have enabled water resource data collection at greater spatial and temporal scale. However, this water data is often limited to the purposes of its primary collection, and limits decisions made by stakeholders towards sustainable urban water management. This empirically focused research paper examines how water practitioners involved in strategic planning can capture additional values from integrating different water data. Furthermore, the perception of 22 urban water practitioners across Australia are presented, regarding the importance of and difficulty in using water data for strategic planning, and the necessary steps for achieving integrated water management practices. Interviewees perception revealed gaps in available water resource data (i.e. water quality, ground water, stormwater, and urban water use), and limitations of industry guidelines for operating within existing governance frameworks. Overall, the research highlights the Australian urban water sector’s perception of water data’s crucial role in representing stakeholders interest; however, changes made in water data’s collection are required for an integrated water management approach. Implications for future open water data standard are discussed.

The complexity of Mixed-Integer Linear Programs (MILPs) increases with the number of nodes in energy system models. An increasing complexity constitutes a high computational load that can limit the scale of the energy system model. Especially in microgrid optimisation problems with multiple buildings and energy systems with a number of rival supply, distribution and storage technologies, methods are sought to reduce this complexity. In this paper, we present a new 2-Level Approach to MILP energy system models that determine the system design through a combination of continuous and discrete decisions. On the first level, data reduction methods are used to determine the discrete design decisions in a simplified solution space. Those decisions are then fixed, and on the second level the full dataset is used to extract the exact scaling of the chosen technologies. The performance of the new 2-Level Approach is evaluated for a case study of an urban energy system with six buildings and an island system based on a high share of renewable energy technologies. The results of the studies show a high accuracy with respect to the total annual costs, chosen system structure, installed capacities and peak load with the 2-Level Approach compared to the results of a single level optimization. The computational load is thereby reduced by more than one order of magnitude, while a significantly higher accuracy is reached in comparison to the common time series aggregation approach.

In the neuroscience research field, specific for medical imaging analysis, how to mining more latent medical information from big medical data is significant for us to find the solution of diseases. In this review, we focus on neuroimaging data that is functional Magnetic Resonance Imaging (fMRI) which non-invasive techniques, it already becomes popular tools in the clinical neuroscience and functional cognitive science research. After we get fMRI data, we actually have various software and computer programming that including open source and commercial, it's very hard to choose the best software to analyze data. What's worse, it would cause final result imbalance and unstable when we combine more than software together, so that's why we want to make a pipeline to analyze data. On the other hand, with the growing of machine learning, Python has already become one of very hot and popular computer programming. In addition, it is an open source and dynamic computer programming, the communities, libraries and contributors fast increase in the recent year. Through this review, we hope that can make neuroimaging data analysis more easy, stable and uniform base the one platform system.

Bioelectrochemical systems (BES) encompass a group of biobased technologies capable of directly converting organic matter into electricity. In these systems, which are derived from conventional electrochemical systems, the ion exchange membrane represents a key element because of its influence on the economic feasibility and on the performance of BES. This study examines the impact of long-term operation of a BES on the mechanical, chemical and electrochemical properties of five different kind of cation exchange membranes (Nafion-117, CMI-7001, Zirfon UTP 500, FKE and FKB) through several techniques: (i) scanning electron microscopy (SEM) and atomic force microscopy (AFM) to assess the changes on the membranes surface, (ii) thermogravimetric analysis (TGA) to evaluate the structural stability of the membranes, and (iii) ion exchange capacity (IEC) to monitor any change in their electrochemical properties. Results confirmed that there is not an ideal membrane for BES. While Nafion and CMI-7000 exhibited the strongest chemical structure, they also underwent the highest fouling as revealed by a fast increase in surface roughness.

The effect of prostaglandin E1 (PGE1) encapsulated in nanoparticles (Nano PGE1) on motor dysfunction and muscle atrophy induced by sciatic nerve injury (SNI) was investigated in rats, and was compared with PGE1 encapsulated in lipid microspheres (Lipo PGE1) or PGE1 clathrated in cyclodextrin (PGE1-CD). The hind limb muscle weight ratio decreased until 2 weeks after SNI. All 3 PGE1 formulations significantly improved SNI-induced motor dysfunction. Nano PGE1 significantly promoted recovery from muscle atrophy at 2 and 3 weeks after SNI. Lipo PGE1 was also effective, but multiple doses were required. Compared with the SNI control group, the Nano PGE1 group showed upregulation of vascular endothelial growth factor (VEGF) and agrin expression in the injured sciatic nerve and atrophic muscles. Nano PGE1 accumulated prominently at the site of nerve injury and persisted for longer than Lipo PGE1 or PGE1-CD. Expression of all EP receptors was detected in the normal sciatic nerve, and EP2 expression increased after SNI. Finally, Nano PGE1 promoted ERK1/2 and Akt phosphorylation. These findings suggest that PGE1 released from nanoparticles accumulates at sites of nerve injury and increases VEGF production by augmenting ERK1/2 phosphorylation via EP receptor signaling, thus promoting tissue repair and regeneration.

Tree condition, pruning and orchard management practices within intensive horticultural tree crop systems can be determined via measurements of tree structure. Multi-spectral imagery acquired from an unmanned aerial system (UAS) has been demonstrated as an accurate and efficient platform for measuring various tree structural attributes, but research in complex horticultural environments has been limited. This research established a methodology for accurately estimating tree crown height, extent, plant projective cover (PPC) and condition of avocado tree crops, from a UAS platform. Individual tree crowns were delineated using object-based image analysis. In comparison to field measured canopy heights, an image-derived canopy height model provided a coefficient of determination (R2) of 0.65 and relative root mean squared error of 6%. Tree crown length perpendicular to the hedgerow was accurately mapped. PPC was measured using spectral and textural image information and produced an R2 value of 0.62 against field data. A random forest classifier was applied to assign tree condition into four categories in accordance with industry standards, producing out-of-bag accuracies >96%. Our results demonstrate the potential of UAS-based mapping for the provision of information to support the horticulture industry and facilitate orchard-based assessment and management.

BACKGROUND G6PD deficiency is an inherited an X-linked recessive condition leading to insufficient levels of glucose-6-phosphate dehydrogenase, thus causing hemolytic anaemia under certain conditions. METHODS Our study is explorative for cases admitted to Jordan University Hospital. The studied parameters include demographics, clinical manifestations, biochemical markers including Hb level, WBC count, liver enzymes, and blood grouping. RESULTS Most of the patients were admitted to the emergency unit (53.13%). Individuals who were Rh-positive represented 57.81%, while patients of AB blood group accounted for 75%. The mean values were 4.81 years (age), 29.06 hours (time-to-hospital admission), 38.10 degree Celsius (temperature), 6.11 gm/dl (Hb), 13242.19 (WBC count), 343.20 U/L (S. ALP), and 50.98 IU/L (S. ALT). There was no significant difference between males and females or between favism-induced versus drug-induced hemolytic episodes. AB and Rh positive blood groups are of protective effect in relation to liver enzymes. Patients who were admitted to the hospital within 24 hours from having clinical manifestations had a better prognosis. CONCLUSION This study is the first inferential research on G6PD deficiency from the Middle East to explore cases from one of the largest healthcare centres in Jordan. The role of blood grouping should be investigated prospectively.

The identification of linear dynamic systems with static nonlinearities in the delta domain has been presented in this paper applying a firefly based hybrid meta-heuristic algorithm integrating Firefly algorithm (FA) and Gray wolf optimizer (GWO). FA diversifies the search space globally while GWO intensifies the solutions through its local search abilities. A test system with continuous polynomial nonlinearities has been considered for hammerstein and wiener system identification in continuous, discrete and delta domain. Delta operator modelling unifies system identification of continuous-time systems with discrete domain at higher sampling frequency. Pseudo random binary sequence, contaminated with white noise, has been taken up as the input signal to estimate the unknown model parameters as well as static nonlinear coefficients. The hybrid algorithm not only outperforms the parent heuristics of which they are constituted but also proves better as compared to some standard and latest heuristic approaches reported in the literature.

Studies on N balance due to N inputs and outputs and soil N retention to measure cropping system performance and environmental sustainability are limited due to the complexity of measurements of some parameters. We measured N balance based on N inputs and outputs and soil N retention under dryland agroecosystem affected by cropping system and N fertilization from 2007 to 2011 in the northern Great Plains, USA. Cropping systems were conventional tillage barley (Hordeum vulgaris L.)-fallow (CTB-F), no-tillage barley-fallow (NTB-F), no-tillage barley-pea (Pisum sativum L.) (NTB-P), and no-tillage continuous barley (NTCB). Nitrogen rates to barley were 0, 40, 80, and 120 kg N ha-1. Total N input due to N fertilization, pea N fixation, soil N mineralization, atmospheric N deposition, nonsymbiotic N fixation, and crop seed N and total N output due to grain N removal, denitrification, volatilization, N leaching, gaseous N (NOx) emissions, surface runoff, and plant senescence were 28 to 37% greater with NTB-P and NTCB than CTB-F and NTB-F. Total N input and output also increased with increased N rate. Nitrogen sequestration rate at 0 to 10 cm averaged 22 kg N ha-1 yr-1 for all treatments. Nitrogen deficit ranged from 5 to 16 kg N ha-1 yr-1, with greater deficits for CTB-F and NTB-P and higher N rates. Because of increased grain N removal and reduced N loss to the environment and N fertilizer requirement, NTB-P with 40 kg N ha-1 can enhance agronomic performance and environmental sustainability while reducing N inputs compared to other management practices.

In this paper we propose a novel theoretical framework, which was previously developed for major depression and bipolar disorder, namely the compensatory immune-regulatory reflex system (CIRS), as applied to the neuro-immune pathophysiology of schizophrenia and its phenotypes, including first episode psychosis (FEP), acute relapses, chronic and treatment resistant schizophrenia (TRS), comorbid depression, and deficit schizophrenia. These schizophrenia phenotypes and manifestations are accompanied by increased production of positive acute phase proteins, including haptoglobin and α2-macroglobulin, complement factors, and macrophagic M1 (IL-1β, IL-6 and TNF-α), T helper (Th)-1 (interferon-γ and IL-2R), Th-2 (IL-4, IL-5), Th-17 (IL-17) and T regulatory (Treg; IL-10 and transforming growth factor (TGF)-β1) cytokines, cytokine-induced activation of the tryptophan catabolite (TRYCAT) pathway as well as chemokines, including CCL-11 (eotaxin), CCL-2, CCL-3 and CXCL-8. While the immune profiles in the different schizophrenia phenotypes indicate activation of the immune-inflammatory response system (IRS), there are simultaneous signs of CIRS activation, including increased levels of the IL-1 receptor antagonist (sIL-1RA), sIL-2R and tumor necrosis factor-a receptors, Th-2 and Treg phenotypes with increased IL-4 and IL-10 production, and increased levels of TRYCATs and haptoglobin, α2-macroglobulin and other acute phase reactants, which have immune-regulatory and anti-inflammatory effects. Signs of activated IRS and CIRS pathways are also detected in TRS, chronic and deficit schizophrenia indicating that these conditions are accompanied by a new homeostatic setpoint between upregulated IRS and CIRS components. In FEP, increased baseline CIRS activity is a protective factor which may predict favorable clinical outcomes. Moreover, impairments in the CIRS are associated with deficit schizophrenia and greater impairments in semantic and episodic memory. It is concluded that CIRS plays a key role in the pathophysiology of schizophrenia by negatively regulating the primary IRS and contributing to recovery from the acute phase of illness. Components of the CIRS may offer promising therapeutic targets for schizophrenia.

The conversion of C1 gas feedstock, such as carbon monoxide (CO), into useful platform chemicals has attracted considerable interest in industrial biotechnology. One conversion method is electrode-based electron transfer to microorganisms using bioelectrochemical systems (BESs). In this BES system, acetate is the predominant component of various volatile fatty acids (VFAs). To appropriately separate and concentrate the produced acetate, a BES type electrodialysis cell with an anion exchange membrane was constructed and evaluated under various operational conditions, such as the applied external current. The higher acetate flux of 23.9 mmol/m2∙hr was observed under -15 mA current in an electrodialysis-based bioelectrochemical system. In addition, the initial acetate concentration affects the separation efficiency and transportation rate. The maximum flux appeared at 48.6 mmol/m2∙hr when the acetate concentration was 100mM, whereas the effect of the initial pH of the anolyte was negligible. The acetate flux was 14.9 mmol/m2∙hr when actual fermentation broth from BES based CO fermentation, was used as a catholyte. A comparison of the synthetic medium with the actual fermentation medium suggests that unknown substances and metabolites in the actual medium interfere with electrodialysis in the BES. These results provide information on the separation and optimal concentration for VFAs produced by C1 gas fermentation through electrodialysis, and a combination of a BES and electrodialysis.

The origination of most free-living animal species is predictable. ‘Light’ order production in the trophic levels below is the key. Absent from the abiotic environment (pre-primary level) and prokaryotes, ‘light’ order consists of differences in species composition between highly-developed, species-packed communities in which extinction may be the precursor to speciation, particularly ecologically comparable tropical continental lowland ones of Africa, Australia, India, and South America. Based on but not itself of matter and non-burnable, its nil waste heat content ‘compensates’ for burned-up food energy. Where the amounts of it on infra-apical trophic levels form an inverted pyramid like waste heat’s, occupancy of trophic levels from primary to apical is predictable (variation and selection assumed). Terminal non-inversion predicts post-apical vacancy. Examined communities were from grasslands (grasses, large grazing mammals, large carnivores), and woodlands (woody plants, butterflies, insect-eating birds, raptorial birds). Linnaeus’s binomial classificational system turned out to be unexpectedly rich in new content. A new object of study, the neoLinnaean, is recognised and a new process, the neoLyellian, advanced to explain it. Relations to Darwin’s and Lyell’s non-predictive theories of change, to ecology and evolution, to thermodynamics, statistical mechanics and quantum mechanics, and to neurology are discussed.

Declining water supply is the main cause of rising water fee for agricultural use. Moreover, in non-technical irrigation, poor irrigation infrastructure exacerbates water scarcity. Thus, the purpose of this study is to identify farmer willingness to pay for non-technical irrigation and its determinants. Structured questionnaire was used to collect data from 100 farmers. Contingent valuation method was employed to elicit farmer WTP and multiple linear regression was used to find its determinants. The result shows that farmer average WTP is Rp 3,055,168 /ha/year. It accounts for 20 percent of total farmer revenue and almost 20 times fee for technical irrigation. Economic and technical variables are the significant determinants of WTP while social variables seem insignificant to WTP. This result indicates high economic value of water, and to improve irrigation management we recommend establishing irrigation infrastructure gradually by mobilizing farmer resources (capital and management) and strengthening WUA.

Climate change and global warming are becoming important problems around the globe. To prevent these environmental problems, many countries try to reduce the emissions of greenhouse gases (GHG) and manage the consumption of energy. In Korea, Korea Electric Power Corporation (KEPCO) has introduced Smart Grid (SG) technologies to its branch office in 2014. This was the first demonstration of smart grid on a building called Smart Grid Station. This paper treats the achievements of the Smart Grid Station (SGS) by its early target in three aspects. The things are peak reduction, power consumption reduction and electricity fee saving. The authors analyzed the achievements by comparing the data of 2015 with the data of 2014. Through the evaluation, the authors studied the case, proved the advantages of SGS, and suggested the requirements to improve and the direction to go of the system.

Filamentous fungi such as Aspergillus spp. are opportunistic pathogens, which cause highly invasive infections, especially in immunocompromised individuals. Control of such fungal pathogens is increasingly problematic due to the small number of effective drugs available for treatment. Moreover, the increased incidence of fungal resistance to antifungal agents makes this problem a global human health issue. The cell wall integrity system of fungi is the target of antimycotic drugs echinocandins, such as caspofungin (CAS). However, echinocandins cannot completely inhibit the growth of filamentous fungal pathogens, which results in survival/escape of fungi during treatment. Chemosensitization was developed as an alternative intervention strategy, where co-application of CAS with the intervention catalyst octyl gallate (OG; chemosensitizer) greatly enhanced CAS efficacy, thus achieved ≥ 99.9% elimination of filamentous fungi in vitro. Based on hypersensitive responses of Aspergillus antioxidant mutants to OG, it is hypothesized that, besides destabilizing cell wall integrity, the redox-active characteristic of OG may further debilitate fungal antioxidant system.

The main purpose of this paper is to present a system to detect extrusion failures in Fused Deposition Modelling (FDM) 3D printers by sensing that the filament is moving forward properly. After several years using these kind of machines, authors detected that there is not any system to detect the main problem in FDM machines. Authors thought in different sensors and used the Weighted Objectives Method, one of the most common evaluation methods, for comparing design concepts based on an overall value per design concept. Taking into account the obtained scores of each specification, the best choice for this work is the optical encoder. Once the sensor is chosen, it is necessary to design de part where it will be installed without interfering with the normal function of the machine. To do it, photogrammetry scanning methodology was employed. The developed device perfectly detects the advance of the filament without affecting the normal operation of the machine. Also, it is achieved the primary objective of the system, avoiding loss of material, energy and mechanical wear, keeping the premise of making a low-cost product that does not significantly increase the cost of the machine. This development has made it possible to use the printer with remains coil filament, which were not spent because they were not sufficient to complete an impression and also printing models in two colours with only one extruder.

Grading of rice grains has gain attentions due its requirement of quality assessment during import or export. Rice grain quality depends on milling operation, where rice hull is removed with a huller system followed by whitening operation. In such process, adjustment of rollers, control, and operation is important in terms of quality of milled rice. Especially, the basmati rice needed more quality assurance as it is not parboiled rice and exported globally with a high product value. In this present work, the basic problem of quality assessment in rice industry is addressed with digital image processing based technique. Machine vision and digital image processing provide an alternative with the automated, nondestructive, cost-effective, and fast approach as compared with traditional method which is done manually by human inspectors. A model of quality grade testing and identification is built based on morphological features using digital image processing and knowledge based adaptive neuro-fuzzy inference system (ANFIS). The qualities of rice kernels are determined with the help of shape descriptors and geometric features using the sample images of milled rice. The adopted technique has been tested on a sufficient number of training images of basmati rice grain. The proposed method gives a promising result in an evaluation of rice quality with 100% classification accuracy for broken and whole grain. The milling efficiency is also assessed using the ratio between head rice and broken rice percentage and it is 77.27% for the test sample. The overall results of the adopted methodology are promising in terms of classification accuracy and efficiency.

The physical and economic sustainability of using Built Environment Wind Turbine (BEWT) systems depends on the wind resource potential of the candidate site. Therefore, it is crucial to carry out a wind resource assessment prior to deployment of the BEWT. The assessment results can be used as a referral tool for predicting the performance and lifespan of the BEWT in the given built environment. To date, there is limited research output on BEWTs in South Africa with available literature showing a bias towards utility-scale or conventional ground based wind energy systems. This study aimed to assess wind power generation potential of BEWT systems in Fort Beaufort using the Weibull distribution function. The results show that Fort Beaufort wind patterns can be classified as fairly good and that BEWTs can best be deployed at 15m for a fairer power output as roof height wind speeds require BEWT of very low cut-in speed of at most1.2ms⁻¹.

The tumor microenvironment is known to have increased levels of cytokines and metabolites, such as glutamate, due to their release from the surrounding cells. A normal cell around the tumor that responds to the inflammatory environment is likely to be subsequently altered. We will discuss how these abnormalities will support tumor survival via the actions of gap junctions (GJs) and hemichannels (HCs) which are composed of hexamer of connexin 43 (Cx43) protein. In particular, we will discuss how GJ intercellular communication (GJIC) in glioma cells, the primary brain tumor, is a regulatory factor and its attenuation leads to tumor invasion. In contrast, the astrocytes, which are normal cells around the glioma, are "hijacked" by tumor cells, either by receiving the transmission of malignant substances from the cancer cells via GJIC, or perhaps via astrocytic HC activity through the paracrine signaling which enable the delivery of these substances to the distal astrocytes. This astrocytic signaling would promote tumor expansion in the brain. In addition, brain metastasis from peripheral tissues has also been known to be facilitated by GJs formed between cerebral vascular endothelial cells and cancer cells. Astrocytes and microglia are generally thought to eliminate cancer cells at the blood brain barrier. In contrast, some reports suggest they facilitate tumor progression as tumor cells take advantage of the normal functions of astrocytes that support the survival of the neurons by exchanging nutrients and metabolites. In summary, GJIC is essential for the normal physiological function of growth and allowing the diffusion of physiological substances. Therefore, whether GJIC is cancer promoting or suppressing may be dependent by what permeates through GJs, when it is active, and to which cells. The nature of GJs, which has been ambiguous in brain tumor progression, will need to be re-visited and understood together with new findings on Cx proteins and HC activities.

Constructed rapid infiltration system (CRI) is a new type of sewage biofilm treatment technology, but due to its anaerobic zone lacks of the carbon sources and the condition for nitrate retention, its nitrogen removal perfomance is very poor; However, shortcut nitrification-denitrification process presents distinctive advantages, as it saves oxygen, requires less organic matter and needs less time for denitrification compared to conventional nitrogen removal method. Thus, if the shortcut nitrification-denitrification process could be applied to CRI system properly, the simpler, more economic and efficient nitrogen removal method will be obtained. But, as its reaction process shows that the first and the most important step of achieving shortcut nitrification-denitrification is to achieve shortcut nitrification. Thus, in this study, we explored the feasibility to achieve shortcut nitrification, which produces nitrite as the dominant nitrogen species in effluent, by addition of potassium chlorate (KClO₃) to the influent. In an experimental CRI model system, the effects on nitrogen removal, nitrate inhibition and nitrite accumulation were studied, and the advantages of achieving shortcut nitrification-denitrification were also analysed. The results showed that shortcut nitrification was successfully achieved and maintained in a CRI system by adding 5 mM KClO₃ to the influent at a constant pH of 8.4. Under these conditions nitrite accumulation rate was increased, while a lower concentration of 3 mM KClO₃ had no obvious effect. The addition of 5 mM KClO₃ in influent presumably allowed sufficient activity of ammonia-oxidizing bacteria (AOB) but inhibited nitrite-oxidizing bacteria (NOB) strongly enough to result in a maximum nitrite accumulation rate of up to over 80%. As a result, nitrite became the dominant nitrogen product in the effluent. Moreover, if the shortcut denitrification will be achieved in the subsequent research, it could save 60.27 mg carbon source (CH₃OH) consumption when treatment of per liter sewage in CRI system compared with full denitrification process.

Multi-cameras system is widely applied in 3D computer vision especially when multiple cameras are distributed on both sides of the measured object. The calibration methods of multi-cameras system are critical to the accuracy of vision measurement and the key is to find an appropriate calibration target. In this paper, a high-precision camera calibration method for multi-cameras system based on transparent glass checkerboard and ray tracing is described, which is used to calibrate multiple cameras distributed on both sides of the glass checkerboard. Firstly, the intrinsic parameters of each camera is obtained by Zhang’s calibration method. Then, multiple cameras capture several images from the front and back of the glass checkerboard with different orientations, and all images contain distinct grid corners. As the cameras on one side are not affected by the refraction of glass checkerboard, extrinsic parameters can be directly calculated. However, the cameras on another side are influenced by the refraction of glass checkerboard, and the direct use of projection model will produce calibration error. A multi-cameras calibration method using refractive projection model and ray tracing is developed to eliminate this error. Furthermore, both synthetic and real data are employed to validate the proposed approach. The experimental results of refractive calibration show that the error of the 3D reconstruction is smaller than 0.2 mm, the relative errors of both rotation and translation are less than 0.014%, and the mean and standard deviation of reprojection error of 4-cameras system are 0.00007 and 0.4543 pixel. The proposed method is flexible, high accurate, and simple to carry out.

Emergency control load-shedding is a key solution to prevent blackouts in the power system. This paper proposed a new model of emergency controls load shedding based on the fast identification of the unstable state of the power system. K-means clustering algorithm divided the instability mode into the clusters. The results of analysis of this cluster were used as the basis for classification control. Building load shedding strategies is consisted of the pre-designed rules based on AHP algorithm. When the recognition of the power system “instability” is detected, the signal of load shedding control is triggered immediately, therefore the decision time is greatly shortened comparing to the traditional methods. The effectiveness of the proposed method was tested on the IEEE 39-bus to overcome the limitations of the last traditional methods.

At present, medical institutes generally use EMR to record patient's condition, including diagnostic information, procedures performed and treatment results. EMR has been recognized as a valuable resource for large scale analysis. However, EMR has the characteristics of diversity, incompleteness, redundancy and privacy, which make it difficult to carry out data mining and analysis directly. Therefore, it is necessary to preprocess the source data in order to improve data quality and improve the data mining results. Different types of data require different processing technologies. Most structured data commonly needs classic preprocessing technologies, including data cleansing, data integration, data transformation and data reduction. For semi-structured or unstructured data, such as medical text, containing more health information, it requires more complex and challenging processing methods. The task of information extraction for medical texts mainly includes NER (Named Entity Recognition) and RE (Relation Extraction). In this paper, we introduce the process of EMR processing, including data collection, data preprocessing, data mining, evaluation and knowledge application, analyze the current status of the key technologies, such as data preprocessing and data mining, and provide an overview of the application domains and prospects of EMR mining technologies. Finally, we summarize the existing problems in the research of EMR mining, and review the development trends.

To help reduce the impact of geohazards, an innovative landslide early-warning technology based on an energy demodulation-based fiber optic sensing (FOS-LW for short) technology, is introduced in this paper. FOS-LW measures the energy change in a sensing fiber at the segment of micro-bending, which can be caused by landslide movements, and automatically raises an alarm as soon as the measured signal intensity in the fiber reaches a pre-set threshold. Based on the sensing of micro-bending losses in the fiber optics, a two-event sensing algorithm has been developed for the landslide early-warning. The feasibility of the FOS-LW technology is verified through laboratory simulation and field tests. The result shows that FOS-LW has some unique features such as the graded alarm, real-time responses, remote monitoring, low cost and passive optical network, and can be applied in the early-warning of landslides.

Anomaly detection plays a significant role in helping gas turbines run reliably and economically. Considering collective anomalous data and both sensitivity and robustness of the anomaly detection model, a sequential symbolic anomaly detection method is proposed and applied to the gas turbine fuel system. A structural Finite State Machine is to evaluate posterior probabilities of observing symbolic sequences and most probable state sequences they may locate. Hence an estimating based model and a decoding based model are used to identify anomalies in two different ways. Experimental results indicates that these two models have both ideal performance overall, and estimating based model has a strong ability in robustness, while decoding based model has a strong ability in accuracy, particularly in a certain range of length of sequence. Therefore, the proposed method can well facilitate existing symbolic dynamic analysis based anomaly detection methods especially in gas turbine domain.

Off-grid electrification planning increasingly recognizes the importance of productive use of electricity (PUE) to promote community value creation and (financial) project sustainability. To ensure a sustainable and efficient integration in the community and energy system, PUE assets must carefully be evaluated to match both the community needs and the residential electricity demand patterns. We propose a novel methodology interlinking qualitative interviews, statistical analysis, and energy system modelling to optimize decision-making for PUE integration in off-grid energy systems in rural Madagascar by aligning relevant PUE effectively with anticipated residential electricity demand patterns based on socio-economic determinants of the community. We find that a possible contribution of the PUE to reducing the electricity costs depends signifi-cantly on three factors: 1. the residential electricity consumption patterns that are influenced by the socio-economic composition of the community, 2. the degree of flexibility of i) PUE assets and ii) operational preferences of the PUE user, and 3. the capacity of community members to finance and operate PUE assets. Our study demonstrates that significant cost reductions for PUE-integrated off-grid energy systems can be achieved by applying our proposed methodology. When matching PUE and residential consumption patterns, the integration of PUE assets in residential community energy system can reduce the financial risk of operators, provided the PUE enterprise operates reliably and sustainably. We highlight that the consideration of local value chains and co-creation approaches are essential to ensure the energy system is addressing the community’s needs, creates value for the community, enhances the project´s financial sustainability, and is achieving the overall objectives of decentralized energy system planning.

Incorporating knowledge graphs as auxiliary information to enhance recommendation systems can improve the representations learning of users and items. Recommendation methods based on knowledge graph can introduce user-item interaction learning into the item graph, focusing only on learning the node vector representations within a single graph; alternatively, they can treat user-item interactions and item graphs as two separate graphs and learn from each graph individually. Learning from two graphs has natural advantages in exploring original information and interaction information, but faces two main challenges: 1) in complex graph connection scenarios, how to adequately mine the self-information of each graph, and 2) how to merge interaction information from the two graphs while ensuring that user-item interaction information predominates. Existing methods do not thoroughly explore the simultaneous mining of self-information from both graphs and effective interaction information, leading to the loss of valuable insights. Considering the success of contrastive learning in mining self-information and auxiliary information, this paper proposes a dual-graph contrastive learning recommendation method based on knowledge graphs (KGDC) to explore a more accurate representations of users and items in recommendation systems based on external knowledge graphs. In the learning process within the self-graph, KGDC has strengthened and represented the information of different connecting edges in both graphs, and extracted the existing information more fully. In interactive information learning, KGDC reinforces the interaction relationship between users and items in the external knowledge graph, realizing the leading role of the main task. We have conducted a series of experiments on three standard datasets, and the results show that the proposed method can achieve better results.