Targeted next-generation sequencing (NGS) technology detects specific mutations that can provide treatment opportunities for colorectal cancer (CRC) patients. We included 145 CRC patients who underwent surgery. We analyzed the mutation frequencies of common actionable genes and their association with clinicopathological characteristics and oncologic outcomes using targeted NGS. Approximately 97.9% (142) of patients showed somatic mutations. Frequent mutations were observed in TP53 (70%), KRAS (49%), and APC (47%). TP53 mutations were significantly linked to higher overall stage (p=0.038) and lower disease-free survival (DFS) (p=0.039). ATM mutation was significantly associated with higher tumor stage (p=0.012) and shorter overall survival (OS) (p=0.041). Stage 3 and 4 patients with ATM mutations (p=0.023) had shorter OS, and FBXW7 mutation was significantly associated with shorter DFS (p=0.002). In multivariate Cox regression analysis, ATM mutation was an independent biomarker for poor prognosis of OS (p=0.022). TP53 and FBXW7 mutations are independent biomarkers for poor prognosis of DFS (p=0.042 and 0.030, respectively). A comprehensive analysis of the molecular markers for CRC can provide insights into the mechanisms underlying disease progression and help optimize a personalized therapy.

We present a method to improve the reconstruction and generation performance of variational autoencoder (VAE) by injecting an adversarial learning. On the other hand, instead of comparing the reconstructed with the original data to calculate the reconstruction loss, we use a consistency principle for deep features. The training process of the VAE is then divided into two steps, training the encoder and then training the decoder. By using this two-step learning process, our method can be more widely used in applications other than image processing. While training the encoder, the label information is integrated to better structure the latent space in a supervised way. The adversarial constraints allow the decoder to generate data with better authenticity and more realistic than the conventional VAE. We present experimental results to show that our method gives better performance than the original VAE.

High frequency knowledge of the spatio-temporal distribution of the Downwelling Surface Shortwave Flux (DSSF) and its diffuse fraction (fd) at the surface is nowadays essential for understanding climate processes at the surface-atmosphere interface, plant photosynthesis and carbon cycle, and for the solar energy sector. The EUMETSAT Satellite Application Facility for Land Surface Analysis operationally delivers estimation of the MDSSFTD (Downwelling Surface Short-wave radiation Fluxes – Total and Diffuse fraction) product with an operational status since the year 2019. The method for the retrieval was presented in the companion paper [40]. The part 2 now focuses on the evaluation of the MDSSFTD algorithm and presents the comparison of the corresponding outputs, i.e. total DSSF and diffuse fraction (fd) components, against in-situ measurements acquired at four BSRN stations over a seven-month period. The validation is performed on an instantaneous basis. We show that the satellite estimates of DSSF and fd meet the target requirements defined by the user community for all-sky (clear and cloudy) conditions. For DSSF, the requirements are 20Wm^-2 for DSSF<200Wm^-2, and 10% for DSSF>=200Wm^-2. The MBE and rMBE compared to the ground measurements are 3.618Wm^-2 and 0.252%, respectively. For fd, the requirements are 0.1 for fd<0.5, and 20% for fd>=0.5. The MBE and rMBE compared to the ground measurements are -0.044 and -17.699%, respectively. The study also provides a separate analysis of the product performances for clear sky and cloudy sky conditions. The importance of representing the cloud-aerosol radiative coupling in the MDSSFTD method is discussed. Finally, it is concluded that the quality of the Aerosol Optical Depth (AOD) forecasts currently available is enough accurate to obtain reliable diffuse solar flux estimates. This quality of AOD forecasts was still a limitation a few years ago.

Computational Fluid Dynamics (CFD) simulations, based on Reynolds Averaged Navier Stokes (RANS) models, are a useful tool for a wide range of coastal and offshore applications, providing a high fidelity representation of the underlying hydrodynamic processes. Generating input waves in the CFD simulation is performed by a numerical wavemaker (NWM), with a variety of different NWM methods existing for this task. While NWMs, based on impulse source methods, have been widely applied for wave generation in depth averaged, shallow water models, they have not seen the same level of adoption in the more general RANS based CFD simulations, due to difficulties in relating the required impulse source function to the resulting free surface elevation for non-shallow water cases. This paper presents an implementation of an impulse source wavemaker, which is able to self-calibrate the impulse source function to produce a desired wave series in deep or shallow water at a specific point in time and space. Example applications are presented, for a numerical wave tank (NWT), based on the opensource CFD software OpenFOAM, for wave packets in deep and shallow water, highlighting the correct calibration of phase and amplitude. Also, the suitability for cases requiring very low reflection from NWT boundaries is demonstrated. Possible issues in the use of the method are discussed and guidance for good application is given.

Computational Fluid Dynamics (CFD) is utilized to study entropy generation for the rarefied steady state laminar 2-D flow of air-Al2O3 nanofluid in square cavity equipped with two solid fins at the hot wall. Such flows are of great importance in industrial applications, such cooling of the electronic equipment’s and nuclear reactors. In the current study, effects of Knudsen number (Kn), Rayleigh number (Ra) and the nano solid particles volume fraction (ϕ) on the entropy generation are investigated. The values of parameters considered in this work are as follows: 0≤Kn≤0.1, 〖10〗^3≤Ra≤〖10〗^6,0≤ϕ≤0.2. Length of the fins (LF) is considered to be fixed and equals to 0.5 m, whereas the location of the fins with respect to the lower wall (HF) is set to 0.25 and 0.75 m. Simulations demonstrate that there is an inverse direct effect of Kn on the entropy generation. Moreover, it is found that when Ra is less than 104, the entropy generation, due to the flow, increases as ϕ increases. In addition, the entropy generation due to the flow will decrease at Ra greater than 104 as ϕ increases. Moreover, the entropy generation due to heat will increase as both the ϕ and Ra increase. In addition, a correlation model of the total entropy generation as a function of all of the investigated parameters in this study is proposed. Finally, an optimization technique is adapted to find out the conditions at which the total entropy generation is minimized

Decarbonization of air mobility requires the decarbonization of its energy. While biofuels will play an important role, other low carbon energy carriers based on electricity are considered: battery electrification, liquid hydrogen (LH₂) or eFuel, a hydrogen-based energy carrier. Each energy carrier has its own conversion steps and losses and its own integration effects with the aircraft. These combinations lead to different energy requirements and must be understood to compare their cost and CO₂ emissions. Since they are all electricity-based, this study compares these energy carriers using the well to rotor methodology when applied to a standard Vertical Take-Off and Landing (VTOL) air mobility mission. This novel approach allows one to understand that the choice of the energy carrier dictates the propulsive system architecture, leading to integration effects with the aircraft which can significantly change the energy required, from 400 to 2665 kWh for the same mission. These deviations lead significant differences in CO₂ emissions and costs. Battery electrification is impacted by the battery manufacturing but has the lowest electricity consumption. It is an optimum solution but only until the battery weight can be lifted. In all scenarios eFuel is more efficient than LH₂. We conclude that carrying the most efficient molecule in an aircraft pays the extra energy cost spent on the ground. Finally, we found that for each of these energy carriers, it is the electricity carbon intensity and price which will dictate the cost and CO₂ emissions of an air mobility mission.

Three different populations of sulfated polysaccharides can be found in the cell wall of the red alga Botryocladia occidentalis. In a previous work, the structures of the two more sulfated polysaccharides were revised. In this work, NMR-based structural analysis was performed on the least sulfated polysaccharide and its chemically modified derivatives. Results have revealed the presence of both 4-linked α- and 3-linked β-galactose units having the following chemical features: more than half of the total galactose units are not sulfated, the α-units occur primarily as 3,6-anhydro-galactose units either 2-O-methylated or 2-O-sulfated, and the β-galactose units can be 4-O-sulfated or 2,4-O-disulfated. SPR-based results indicated weaker binding of the least sulfated galactan to thrombin, factor Xa, and antithrombin, but stronger binding to heparin cofactor II than unfractionated heparin. This report together with our previous publication completes the structural characterization of the three polysaccharides found in the cell wall of the red alga B. occidentalis and correlates the impact of their composing chemical groups with the levels of interaction with the blood co-factors.

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

The effects of co-addition CeO2 and SiC particles on the morphology, surface cracks, microstructure, precipitated phases and wear property of plasma beam spraying Fe55-based coatings on 1025 steel were investigated by optical microscopy (OM), scanning electron microscopy (SEM), energy-dispersive X-ray spectrometer (EDS), ultra-deep field microscope and wet sand rubber wheel friction tester, respectively. The results showed that the dendrite exhibited a directional growth pattern perpendicular to the substrate and the transitional states of microstructure with the co-addition CeO2 and SiC particles. With addition of CeO2 or SiC affected the flowability of molten steel at macro level, leading to a reduction in the liquid phase diffusion coefficient DL of Cr and C and resulted in a decrease in the G/R ratio. The dendrites changed into equiaxed grains. The main phase composition of Fe55 welding layer is Cr7C3, γ-Fe. The grain boundaries consisted mainly of a reticular eutectic structure. The worn-out uniformly surface of the Fe55+1.5 wt% SiC+0.01wt% CeO2 with Ra was 0.28 μm was smoother than that of other samples. The sub-wear mechanisms during the friction process were microploughing and microcutting. The hardness and toughness of Fe55+1.5 wt% SiC+0.01wt% CeO2 were well-matched, avoiding excessive microcutting and microplastic deformation.

A new copper(I) complex, [Cu2(L)2dppm](PF6)2 (1) [L = 3-(2-Pyridyl)-5,6-diphenyl-1,2,4-triazine and dppm: Bis(diphenylphosphino)methane] was prepared and characterized by IR, 1H-NMR, 31P-NMR spectroscopy, elemental and thermogravimetric analysis, and single-crystal X-ray diffraction technique. Complex 1 is a dinuclear compound, showing that L and dppm act as tridentate and bidentate chelating ligands, respectively. The two Cu(I) atoms exhibit a distorted tetrahedral coordination sphere embedded in N3P environments. The supramolecular interactions in the solid-state structure are characterized by C−H···N, C−H···F, C-H···π and π···π intermolecular interactions that were analyzed by inspection of the Hirshfeld surface and fingerprint plots. Additionally, the complex was studied experimentally in solution by UV–Vis spectroscopy and cyclic voltammetry; also, theoretical studies with Time-Dependent Density Functional Theory (TD-DFT) were performed. Moreover, the optical and electrochemical properties have been studied, focusing on the band gap. Compound 1 has been used as a co-sensitizer in a dye-sensitized solar cell, showing good activity.

The major challenge for membrane distillation (MD) is membrane wetting resistance induced by pollutants in the feed solution. The proposed solution for this issue was to fabricate membranes with hydrophobic properties. Hydrophobic electrospun Poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) nanofibers membranes were produced for brine treatment using the direct contact membrane distillation (DCMD) technique. These nanofibers membranes were prepared from three different polymeric solution compositions to study the effect of solvent composition in the electrospinning process. Further, the effect of the polymer concentration was investigated by preparing polymeric solutions with three different polymer percentages: 6, 8, and 10%. All nanofibers membranes obtained from electrospinning were post-treated at varying temperatures. The effects of thickness, porosity, pore size, and LEP were studied. The hydrophobicity was determined by contact angle measurements, which were investigated by optical contact angle goniometry. The crystallinity and thermal properties were studied by DCS and XRD, while the functional groups were studied by FTIR. The morphological study was performed by AMF and described the roughness of nanofibers membranes. Finally, all nanofibers membranes have enough of a hydrophobic nature to be used in DCMD. PVDF membrane filter disc and all nanofibers membranes were applied in DCMD to treat brine water. The resulting water flux and permeate water quality were compared, and it was discovered that all produced nanofibers membranes showed good behavior with varying water flux, but the salt rejection was greater than 90%. A membrane prepared from DMF/acetone 5-5 with 10% PVDF-HFP provided perfect performance, with an average water flux of 44 kg.m-2.h-1 and salt rejection of 99.8%.

Coronavirus disease 2019 (COVID-19) is a potentially serious acute respiratory infection caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Since the World Health Organization (WHO) declared COVID-19 a global pandemic, the virus has spread to more than 200 countries with more than 500 million cases and more than 6 million deaths reported globally. It has long been known that viral respiratory tract infections predispose patients to bacterial infections and that these co-infections often have an unfavourable clinical outcome. Moreover, nosocomial infections, also known as health care-associated infections (HAIs), are those infections that are absent at the time of admission and acquired after hospitalization. However, the impact of coinfections or secondary infections on the progression of COVID-19 disease and its lethal outcome is still debated. The aim of this review was to assess the literature on the incidence of bacterial co-infections and superinfections in patients with COVID-19. The review also highlights the importance of the rational use of antibiotics in patients with COVID-19 and the need to implement antimicrobial stewardship principles to prevent the transmission of drug-resistant organisms in healthcare settings. Finally, alternative antimicrobial agents to counter the emergence of multidrug-resistant bacteria causing healthcare-associated infections in COVID-19 patients will also be discussed.

The reliability of Underwater Wireless Sensor Networks (UWSNs) is measured in terms of energy consumption (EC), end-to-end delay(E2E) and packet delivery ratio (PDR). The adverse effects of channel may cause data loss. Reducing delay up to possible extend improves the reliability of the network, also increasing the number of nodes in a particular network increase reliability. Besides, increasing the number of nodes improve reliability but also increase power consumption. In order to overcome these shortcomings, the two routing protocols are proposed in this paper, namely Delay and Reliability Aware Routing (DRAR) protocol and Cooperative Delay and Reliability Aware Routing (Co-DRAR) protocol for UWSNs. In DRAR protocol, network is divided into two equal regions where two sink nodes(SNs) are positioned at upper region of the network and two SNs are placed at the mid region of the network. The protocol choose the relay node based on residual energy (RE), distance and Bit Error Rate (BER). These parameters protect the data packets from corruption and also provide stable path (where nodes remain active for longer period and do not die quickly). The protocol uses single link and may get worse sometimes while changing channel circumstances. To address this problem, cooperative routing scheme is added to DRAR protocol in order to developed its enhanced version known as Co-DRAR protocol. The protocol works by allowing the destination to receive multiple copies of data packets in order to decide the quality of packets. The proposed protocols DRAR and Co-DRAR perform routing irrespective to geographical position of sensors nodes conversely to the some of conventional routing protocols that's way our propose protocol better perform than the well-known protocol i.e. Depth base routing (DBR) in terms of EC, E2E, PDR, dead nodes, packet drop ratio and number of alive nodes (ANs).

The management of urban water has evolved from single-function systems to more sustainable designs promoting society and nature as inputs to engineer novel infrastructure. In transdisciplinary research, co-design refers to a design thinking strategy in which people jointly frame a problem-solution. This article presents a conceptual framework to assess a case study focusing on the process of co-design and implementation of green infrastructure as a prototype for stormwater management. The evaluation is carried out from a self-reflective post-implementation perspective. Research activities are translated into the framework to evaluate conditions shaping the trajectory of the prototype. As a result, key aspects driving the research regarding levels of stakeholder participation and dimensions of power are identified. Planning resilient co-design strategies to retrofit urban spaces is necessary to avoid unintended consequences, especially at the initial experimental stages. This study aims to contribute to the continuous improvement of pilot strategies in urban spaces by providing a framework for a structured evaluation of research experiences.

Background. To improve maternal and child health, it is essential to adhere to health-promoting and preventive measures. However, reliable information as well as effective tools are not easy to identify in this field. Our cross-sectional study investigated the needs and expectations of expectant and new mothers and fathers -primary users of an app supporting the first 1000 days of life. Methods. Between May and August 2022, we recruited expectant and new parents by administering a 71-item 5-point Likert scale questionnaire related to content, functionalities, and technical features of a hypothetical app. We stratified responses by sociodemographic characteristics and then performed ward hierarchical clustering. Results. The 94 women and 69 men involved in our study generally agreed with the proposed content, but expressed low interest in certain app functionalities, especially those related to interaction mechanism and interactivity. Women were generally more demanding than men, and family income declined as the needs and expectations increased. Conclusions. Our findings, resulting from the engagement of end-users, may be useful for designers and technology providers to implement mHealth solutions that, in addition to conveying reliable information, are tailored to the needs and preferences of end-users in the first 1000 days of life.

Pharmaceutically active compounds and organic pollutants are becoming a major environmental dispute possessing serious threat to the water bodies and terrestrial ecosystem. Microorganisms are capable of the self-purification process, and hence the microbial degradation is considered a lucrative method to counteract the therapeutic and recalcitrant pollutants. Pharmaceutical toxicants in aquatic system can be treated by conventional wastewater treatment, but slow sludge settling, presence of mixture of pharmaceuticals and recalcitrant compounds often pose a potential ecological risk. Some microbial strains are very effective in reducing the chemical oxygen demand (COD), biological oxygen demand (BOD), total dissolved solids (TDS), and turbidity in pharmaceutical industrial wastewater treatment. The natural microbial community has a significant role in the ecological processes of pharmaceutical and organic compounds, including non-steroidal anti-inflammatory drugs, analgesics, blood lipid regulators and other micropollutants. Specific bacterial isolates can act as biodegraders, and fungal treatment could offer protection to the ecosystem. These microorganisms use the pollutants as their sole carbon source and transform the contaminants by co-metabolic pathways. Natural attenuation by native microorganisms, biostimulation and bioaugmentation are the processes employed to degrade the target contaminant. Microorganisms may also be genetically engineered to improve the neutralization efficiency, which would assist in the mineralization of the pollutants. Thus, employing microorganisms to detoxify the pollutants probably enhances the sustainable potential biodegradability, improves water quality standards and ensures eco-friendly alternative bioremediation strategy.

In the next decade, further digitalisation of the entire wind energy project lifecycle is expected to be a major driver for reducing project costs and risks. In this paper, a literature review on the challenges related to implementation of digitalisation in the wind energy industry is first carried out, showing that there is a strong need for new solutions that enable co-innovation within and between organisations. Therefore, a new collaboration method called the WeDoWind Ecosystem is developed and demonstrated. The method is centred around specific "challenges", which are defined by "challenge providers" within a topical "space" and made available to participants via a digital platform. The data required in order to solve a particular "challenge" is provided by the "challenge providers" under the confidentiality conditions they specify. The method is demonstrated via a case study, the EDP Wind Turbine Fault Detection Challenge. Six submitted solutions using diverse approaches are evaluated. Two of the methods perform significantly better than EDP’s existing method in terms of Total Prediction Costs (saving up to €120,000). The WeDoWind Ecosystem is found to be a promising solution for enabling co-innovation in wind energy, providing a number of tangible benefits for both challenge and solution providers.

There are two contrary opinions regarding the risk if mainland China (MC) moves away from its zero-COVID policy. Some experts think the risk shall be much lower than influenza as per MC’s own COVID-19 case fatality rate (CFR), while some other experts think the risk shall be much higher than influenza as per the COVID-19 CFRs of other regions. We elucidate here that this and multiple other striking differences in the CFR between various scenarios all support and substantially resulted from the view that good IDM is highly powerful to mitigate COVID-19, where IDM (isolation-disinfection-maintenance) means isolation of COVID-19 cases from other people, disinfection of their living environments, and health maintenance (e.g., rest, nutrition, breathing). The high effect of good IDM is also supported by the theoretic functions of IDM in minimizing co-infections and maintaining body functions, and the fact that all the 505 COVID-19 deaths reported in MC in 2022 before May 5 died directly of severe underlying diseases with COVID-19. Although it is tough for people in poverty to obtain good IDM, good IDM can be feasible at home for the most mild cases and in hospitals for the most severe cases. Therefore, good IDM can be crucial to mitigating COVID-19 worldwide. It also suggests that the risk for China to end its zero-COVID policy depends on China’s control policies or measures. Based on the effect of IDM, the cautious co-existence policy was proposed for COVID-19 control. This policy could reduce the whole death toll in MC because good IDM is non-specific and can reduce deaths of various other diseases. The cautious co-existence policy (non-specific) and the vaccination policy (specific) aid each other to mitigate COVID-19, and they cannot replace each other. Those who are qualified in health for vaccination should be vaccinated against COVID-19 timely.

The purpose of this study was to identify the factors that affect the mortality among adult HIV/TB co-infected patients and to see the nutritional difference among mortality in residence level. Retrospective cohort studies of 417 patients which fulfill our criteria were included. Multilevel logistic regression models were used. MLwiN and SPSS software are used to estimate the parameter. The variance of the random factor in the empty model was significant which indicates that there were residential differences in TB-HIV co-infected mortality and it shows multilevel analysis was an appropriate approach for further analysis. The prevalence of HIV/TB co-infected patients' death was 12.9% in study time. Functional status, age of patients, WHO clinical stages, nutritional status, CD4 counts, regimen, and BMI were found to be significant determinants of HIV/TB co-infected mortality. In our study, patients with the bedridden category of functional status, the fourth stages of WHO clinical stages (stage IV), patients with higher age, patients whose treatments were second-line regimen and low CD4 cell counts were more at risk of death. The study also revealed that; poor nutritional status increased the risk of mortality among HIV/TB co-infected patients and it varies among the residence of the patients (rural area were more at risk).

Threats emerging from microplastics pollution in the marine environment have received much global attention. This review assessed sources, fate, and impacts of microplastics in marine ecosystems and identified gaps. Most studies document ubiquity of microplastics and associated environmental effects. Effects include impacts to marine ecosystems, risks to biodiversity, and threats to human health. Microplastic leakage into marine ecosystems arises from plastic waste mismanagement and a lack of effective mitigative strategies. This review identified a scarcity of microplastics mitigation strategies across different stakeholders. Lack of community involvement in microplastic monitoring or ecosystem conservation exists due to limited existence of stakeholder co-management initiatives. Although some management strategies exist for controlling the effects of microplastics (often implemented by local and global environmental groups); a standardized management strategy to mitigate microplastics in coastal areas is urgently required. There is a need to identify focal causes of microplastic pollution in the marine environment through further environmental research. This would extend to creating more effective policies as well as harmonized and extended efforts of educational campaigns and incentives for counteraction and plastic waste reduction, while mandating stringent penalties for polluting the marine environment. This will help reduce microplastic leakage into the environment.

It was recently demonstrated that a co-planar capacitive sensor could be applied to the evaluation of materials without the disadvantages associated with the other techniques. This technique effectively detects changes in the dielectric properties of the materials due to, for instance, imperfections or variations in the internal structure, by moving a set of simple electrodes on the surface of the specimen. An AC voltage is applied to one or more electrodes and signals are detected by others. This is a promising inspection method for imaging the interior structure of the numerous materials, without the necessity to be in contact with the surface of the sample. In this paper, Finite Element (FE) modelling was employed to simulate the electric field distribution from a co-planar capacitive sensor and the way it interacts with a non-conducting sample. Physical experiments with a prototype capacitive sensor were also performed on a Plexiglas sample with sub-surface defects, to assess the imaging performance of the sensor. A good qualitative agreement was observed between the numerical simulation and experimental result.

Currently, one of the biggest issues when developing an ODS alloy is the competition established between the different oxide precursors during the precipitation of oxides which nature depends on their chemical composition. In the presence of various precursors, usually the one with the highest affinity to oxygen leads to the absence of the other oxides. In this work, a new process to equilibrate the local concentration of species and to decrease the competition among them is explained. A unique compound, containing the diverse oxide precursors as one complex oxide, is introduced in a prealloyed 14Cr Steel powder via mechanical alloying. Thus, generating environments enriched in Y, Ti and Zr which, after consolidation, refine the oxides precipitation improving the thermal stability of the alloy. SPS were used as consolidation technique to guarantee shorter sintering times and to maintain the nanostructure obtained. Mechanical properties were tested by tensile tests and Vickers microhardness.

Background: Co-infections of SARS-CoV-2 with respiratory viruses, bacteria and fungi have been reported to cause a wide range of illness. Objectives: We asses s the prevalence of co-infection of SARS-CoV-2 with seasonal respiratory viruses, document the respiratory viruses detected among individuals tested for SARS-CoV-2, and describe characteristics of individuals with respiratory virus co-infection detected. Methods: Specimens included in this study were submitted as part of routine clinical testing to Public Health Ontario Laboratory from individuals requiring testing for SARS-CoV-2 and/or seasonal respiratory viruses. Results: Co-infection was detected in a smaller proportion (2.5%) of individuals with laboratory confirmed SARS-CoV-2 than those with seasonal respiratory viruses (4.3%); this difference was not significant. Individuals with any respiratory virus co-infection were more likely to be younger than 65 years of age and male than those with single infection. Those with SARS-CoV-2 co-infection manifested mostly mild respiratory symptoms. Conclusions: Findings of this study may not support routine testing for seasonal respiratory viruses among all individuals tested for SARS-CoV-2, as they were rare during the study period nor associated with severe disease. However, testing for seasonal respiratory viruses should be performed in severely ill individuals, in which detection of other viruses may assist with patient management.

The complex interplay among pathogens, host factors, and the integrity and composition of the endogenous microbiome determine the course and outcome of gastrointestinal infections. The model organism Yersinia entercolitica (Ye) is one of the five top frequent causes of bacterial gastroenteritis based on the Epidemiological Bulletin of the Robert Koch Institute (RKI) published on September 10, 2020. A fundamental challenge in predicting the course of an infection is to understand whether co-infection with two Yersinia strains differing only in their capacity to resist killing by the host immune system may decrease the overall virulence by competitive exclusion or increase it by acting cooperatively. Herein, we study the primary interactions among Ye, the host immune system and the microbiota, and their influence on Yersinia population dynamics. The employed model considers two host compartments, the intestinal mucosa and lumen, commensal bacteria, the co-existence of wild-type and mutant Yersinia strains, as well the host immune responses. We determine four possible equilibria: the disease-free, wild-type-free, mutant-free, and co-existence of wild-type and mutant equilibrium. We also calculate the reproduction number for each strain as a threshold parameter to determine if the population may either be eradicated or persist within the host. We conclude that the infection should disappear if the reproduction numbers for each strain fall below one, and the commensal bacteria’s growth rate exceeds the pathogens’ growth rates. These findings will help inform public health control strategies. The supplement includes MATLAB source script, Maple workbook, and figures.

MicroRNAs are used as biomarkers for classification of cancer subtypes since certain miRNAs are differentially expressed in normal and patient samples. Moreover, miRNAs target mRNAs and can heavily influence Gene Expressions. Thus, deregulation of miRNAs is linked to various disorders. Thus, miRNAs can be used for prognosis and developing personalized health solutions for patients. Given the importance of miRNAs, there has been substantial work done in the field. In this paper, recent works in the field of using miRNAs expressions of patients were considered. A total of 20 papers were surveyed which utilized feature selection ensembles, fuzzy logic as well as deep learning. 10 papers have been reported which offer insight into how miRNAs can be utilized for subtype-specific or generalized cancer diagnosis.

Abstract The COVID-19 pandemic has tremendously affected the African continent and the rest of the world. Most businesses have closed and a lot of people have lost their jobs. The aviation industry has been shaken to the core with airlines losing millions of dollars and flights being cancelled. The tourism industry has consequently been affected due to restricted travel of tourists, impacting wildlife conservation and livelihoods. Schools, colleges and universities have been closed. The virus has infected millions of people and hundreds of thousands of people have died globally putting strain on health systems especially those of hard hit countries. Various countries all over the world have put measures to control the spread of the virus through lockdowns and social distancing policies. The reduced economic activities and mobility of people has resulted in improved air quality, cleaner water and beaches in some countries. However there are also negative impacts such as challenges in waste management, increased pharmaceutical and household waste and discovery of the corona virus in wastewater, a potential threat to public health. A considerable amount of research has been done on the socio-economic impacts of COVID-19 in Africa but there is still limited research on its impact on the environment. This paper serves to highlight the observed and potential environmental impacts of COVID-19 in Africa.

Hydrogen is useful as a fuel and could be produced by a variety of means. One approach uses artificial photosynthesis where energy from sunlight powers the splitting of water into hydrogen and oxygen. But, biological methods for producing hydrogen has emerged strongly over the past decades. In particular, specific microorganisms could use different substrates to produce hydrogen at differing yields. Such fundamental discoveries with industrial applications thus motivated the use of metabolic engineering approaches and methodologies in enhancing biological hydrogen production through a series of enzyme over-expression, pathway debottlenecking, and gene deletion. However, such approaches heavily rely on the selection of an appropriate microbial chassis for biohydrogen production. With the proper strain in hand, use of alternative substrates may engender greater hydrogen productivities. But learning from the bioprocessing field, co-culture of two compatible microorganisms have been sought after for improving biohydrogen production. In addition, thermophilic microbes may also be useful candidates for exploiting hydrogen production from composting. Future outlook in the field looks into filling our gaps in understanding of the metabolic network that feeds into hydrogen production in different organisms. But, more importantly, problems such as reduced growth rate in engineered microbes point to fundamental issues with using genetically engineered microorganisms for improved biohydrogen production, to which clever bioprocess engineering may yield solutions.

Biofilm-mediated infection is a major cause of bone prosthesis failure. The lack of molecules able to act in biofilms has driven research aimed at identifying new anti-biofilm agents via chemical screens. However, to be able to accommodate a large number of compounds, the testing conditions of these screenings end up being typically far from the clinical scenario. In this study, we assess the potential applicability of three anti-biofilm compounds (based on natural compounds) as part of implanted medical devices by testing them on in vitro systems that more faithfully resemble the clinical scenario. To that end, we used a competition model based on the co-culture of SaOS-2 mammalian cells and Staphylococcus aureus (collection and clinical strains) on a titanium surface. Additionally, we studied whether these derivatives of natural compounds enhance the previously proven protective effect of pre-incubating the titanium surface with SaOS-2 cells. Out of the three tested leads, one showed the highest potential, and can be regarded as a promising agent for incorporation into bone implants. This study emphasizes and demonstrates the importance of using meaningful experimental models, where potential antimicrobials ought to be tested for protection of biomaterials in translational applications.

In the present paper, Co-B/SiC composite coatings were obtained via electrodeposition from colloidal suspensions with different concentrations of SiC particles and subsequent heat treatments at 350 °C. The composition, morphology and structure of the Co-B/SiC composite coatings were analyzed using glow discharge spectrometry (GDS), scanning electron microscopy (SEM) coupled with energy-dispersive spectroscopy (EDS) and X-ray diffraction (XRD). Hardness and tribological properties were also studied. The results showed that an increase in the SiC concentration in the colloidal suspensions resulted in both an increase in the SiC content and a decrease in the B content in the obtained Co-B/SiC coatings. The Co-B/SiC coatings were adherent, glossy and soft and exhibited a homogeneous composition in all thicknesses. By contrast, an increase in the SiC particle content of the Co-B/SiC composite coating from 0 to 2.56 at.% SiC reduced the hardness of the film from 680 to 360 HV and decreased the wear volume values from 1180 to 23 mm³ N^-1 m^-1, respectively (that is, the wear resistance increased). Moreover, when the Co-B/SiC coatings with SiC content ranging from 0 to 2.56 at.% SiC were subjected to a heat treatment process, the obtained coating hardness values were in the range of 1200 to 1500 HV and the wear volume values were in the range of 382 to 19 mm³ N^-1 m^-1.

Renewable sources and electric distribution network can produce or make available a surplus of electric and thermal energies. The Intermediate Temperature Solid Oxide Electrolyzer (IT-SOE) fed by CO2-steam mixtures can store these electric and thermal energies producing CO-H2 mixtures with high conversion efficiency. Inside the IT-SOE, the CO2-steam mixtures are converted to CO-H2 mixtures and O2 through the cathode and anode electrochemical reactions and reverse water gas shift chemical reaction. In this article an IT-SOE stack fed by different types of steam mixtures was tested at different operating temperatures and the stack polarization and electric power curves were detected experimentally. At the highest hydrogen production operating temperature of the stack fed by steam mixtures, the experimental polarization and electric power curves of the stack fed by steam and CO2-steam mixtures were compared. A simulation model of the IT-SOE system (stack and furnace) fed by CO2-steam mixtures was formulated ad hoc and implemented in a Matlab environment and experimentally validated. At the highest hydrogen production stack operating temperature, the IT-SOE system thermal equilibrium current was evaluated through the simulation model. Moreover, the influence of this current on the IT-SOE system efficiency and the CO-H2 mixture degree of purity was highlighted.

The aim of this study was synthesize and evaluate the effects of Poly (D, L-Lactide-co-glycolide) (PLGA) Nanoparticles (NPs) of metformin (PLGA+ Met) on inflammation, and bone loss in a ligature-induced periodontitis rat model. The prepared NPs were characterized by mean diameter, size particle, polydispensity index and encapsulation efficiency by Atomic force microscopy (AFM). Male albino Wistar rats were randomly divided into four groups of 20 rats in each group, and given the following treatments for 10 days to evaluate in vivo activity: (1) Sham: no ligature + water; (2) Positive control: ligature + water (with Periodontal disease and Diabetes); (3) ligature + PLGA+ 10 mg/kg Met (With Periodontal disease and Diabetes); and (4) ligature + PLGA+ 100 mg/kg Met (with Periodontal disease and Diabetes). Water or PLGA + Met was administered orally by gavage. Maxillae were fixed and scanned using Micro-computed Tomography (μCT) to quantify linear of bone loss. Histopathological characteristics were assessed through immunohistochemical staining for Osteocalcin, Cathepsyn K, RANKL/RANK/OPG pathway. IL-1β and TNF-α from gingival tissues were analysed by Elisa immunoassay. Quantitative RT-PCR reaction was used to evaluate gene expression of AMPK, NF-κB p-65, Hmgb1 and TAK-1 from gingival tissues. Statistical analysis was performed using one-way ANOVA at 5% significance. The mean diameter of MET-loaded PLGA nanoparticles was in a range of 457.1 ± 48.9 nm with a polydispersity index of 0.285, zeta potential: 8.16 ± 1.1 mV and entrapment efficiency (EE) was 70%. The results suggest that the addition of MET in the core slightly affected the particle sizes. Treatment with PLGA+ 10 mg/kg Met showed low inflammatory cells, decreased bone loss and integrity cement and levels of IL-1β, and TNF-α (p < 0.05) were significantly reduced. Additionally, weak staining was shown by RANKL, Cathepsyn K, OPG, and osteocalcin. Radiographically, linear measurements showed a statistically significant reduction in bone loss after treatment with PLGA+ 10 mg/kg Met compared to the positive control (p < 0.05). RT-PCR showed increased AMPK expression (p < 0.05) and decreased expression of NF-κB P65, HMGB1 and TAK-1 after PLGA+ 10 mg/kg Met (p < 0.05). The PLGA nanoparticle + 10 mg/kg Met decreased glucose levels and also decreased the inflammatory response, and bone loss in ligature-induced periodontitis in rats.

Logistics Engineering has transcended over the decades into an approach for competitive benefits in organisational performance and logistics efficiency. Most industries are recognising that significant savings are available to companies that are able to ordinate and improve within their logistics operations. Companies today face great challenges because the successful supply of many products and services needs to the effective integration of logistics activities across a prolongation supply chain and an increasing geographical separation. Moreover, logistics integration approach involves both internal integration for an ordinated, unified process as well as relationships to react flexibly, changeability, and responsibility to customer's demands. In this study, by using of Fuzzy Vikor (F-Vikor), the best combination of RIR was selected and RIR Locating was done. The main aim of this paper is survey and design of the integrated operational logistics network (IOLN) and also, a proposed IOLN to integration of the Iran Khodro Co Supply Network.

Biocompatible and biodegradable poly(butylene succinate-co-adipate) (PBSA)/hexadecylamine-modified PPZn (m-PPZn) nanocomposites were prepared using a melt mixing process. Experimental results of wide-angle X-ray diffraction and transmission electron microscopy revealed that the stacking layers of the m-PPZn were partially intercalated and partially exfoliated into the PBSA polymer matrix. The isothermal crystallization kinetics of PBSA/m-PPZn nanocomposites were studied at the temperature range of 62−70 °C and the half-time for crystallization of 3 wt % PBSA/m-PPZn nanocomposite was reduced by 27−35% compared with that of pure PBSA. This finding suggests that the incorporation of m-PPZn might cause the heterogeneous nucleation and the subsequent crystallization growth, which enhances the isothermal crystallization rate of PBSA/m-PPZn nanocomposite. The biodegradation rates of PBSA using Lipase from Pseudomonas sp. increase as the contents of m-PPZn increase. The degradation behavior of the neat PBSA investigated using the change of weight-average molecular weight belongs to exo-type hydrolysis activity. It is necessary to point out that the change of degree of crystallinity and degradation rate are almost linearly proportional to the loading of hexadecylamine-modified PPZn. This finding would provide an important information for the manufacturing biodegradable PBSA nanocomposites.

The purpose of the present study was to investigate the effects of psychological pressure on corticospinal excitability, the spinal reflex, lower limb muscular activity, and reaction times during a task involving dominant leg movements. Ten healthy participants performed a simple reaction time task by raising the heel of their dominant foot from a switch. After 20 practice trials, participants performed 20 non-pressure and 20 pressure trials in a counterbalanced order. Stress responses were successfully induced, as indexed by significant increases in state anxiety, mental effort, and heart rates under pressure. Significant increases in motor evoked potential (MEP) amplitude of the tibialis anterior muscle (TA) occurred under pressure. In terms of task-related EMG amplitude, the co-contraction rate between the soleus (SOL) and TA muscles significantly increased along with SOL and TA EMG amplitudes under pressure. Hoffmann reflexes for SOL and reaction times did not change under pressure. These results indicate that corticospinal excitability and leg muscle-related EMG activity increase homogeneously during lower limb movements that are performed under psychological pressure.

This paper provides an exhaustive narrative review of third-generation antipsychotics (TGAs), focusing on aripiprazole, cariprazine, brexpiprazole, and lurasidone for managing substance-induced psychosis. It includes a comprehensive literature review to evaluate the efficacy and tolerability of these medications. The paper emphasizes the distinct challenges in treating substance-induced psychosis, which is a psychiatric condition triggered by the misuse or withdrawal of various substances, leading to symptoms like hallucinations and delusions, and is distinct from primary psychotic disorders. It underscores the potential of TGAs in addressing both psychotic symptoms and substance-related issues, while highlighting the need for more research on long-term effects and advocating for an integrated approach combining pharmacological and psychological interventions

This review delves into the critical role of automation and sensor technologies in optimizing parameters for thermal treatments within electricity power generation. The demand for efficient and sustainable power generation has led to a significant reliance on thermal treatments in power plants. However, ensuring precise control over these treatments remains challenging, necessitating the integration of advanced automation and sensor systems. This paper evaluates the pivotal aspects of automation, emphasizing its capacity to streamline operations, enhance safety, and optimize energy efficiency in thermal treatment processes. Additionally, it highlights the indispensable role of sensors in monitoring and regulating crucial parameters such as temperature, pressure, and flow rates. These sensors enable real-time data acquisition, facilitating immediate adjustments to maintain optimal operating conditions and prevent system failures. It explores the recent technological advancements, including machine learning algorithms and IoT integration, which have revolutionized automation and sensor capabilities in thermal treatment control. Incorporating these innovations has significantly improved the precision and adaptability of control systems, resulting in heightened performance and reduced environmental impact. This review underscores the imperative nature of automation and sensor technologies in thermal treatments for electricity power generation, emphasizing their pivotal role in enhancing operational efficiency, ensuring reliability, and advancing sustainability in power generation processes.

Stalk rot caused by Fusarium fungi is one of the most widespread and devastating diseases of maize, and the introduction of resistant genotypes is one of the most effective strategies for controlling the disease. Breeding genotypes with genetically determined resistance will also allow less use of crop protection products. The aim of the research was to identify molecular markers and associated candidate genes determining maize plant resistance to Fusarium stalk rot. The plant material for the study consisted of 122 maize hybrids, which were sown in plots of 10 m2, in a complete randomized block design, in three repetitions, at two locations (Smolice: 51 42’ 58.904’’ N, 17 13’ 29.13’’ E and Kobierzyce: 50 58’ 19.411’’ N, 16 55’ 47.323’’ E). The analyzed genotypes were simultaneously subjected to next-generation sequencing using the Illumina platform. The results of the observation of the degree of infection and sequencing were used for association mapping, which ultimately resulted in the selection of 10 molecular markers important at both places. Among the identified markers, two SNP markers that are located inside candidate genes play an important role. Marker 4772836 is located inside the serine/threonine-protein kinase bsk3 gene, while marker 4765764 is located inside the histidine kinase 1 gene. Both genes can be associated with plant resistance to Fusarium stalk rot, and these genes can also be used in breeding programs to select resistant varieties.

In the realm of artificial intelligence (AI), generative systems, most notably Midjourney, have tremendous power to generate creative images of buildings and sites of Islamic architectural heritage through text-to-image generation based on the internet. The AI-generated representations have significant potential for architects, specialists, and common users. However, the system has considerable limitations when generating images for some buildings and sites where the representations appear too far from their original represented structures. This research article attempts to answer the question: What are the limitations of using the AI system of Midjourney in producing images similar to the original buildings and sites of the Islamic architectural heritage? The research employs prompt engineering techniques based on historical sources as inputs to examine the accuracy of the output of the AI-generated images of selected examples of structures of the Islamic tradition. It compares the output with the original look by employing direct observation and critical analysis of human intelligence (HI). It categorizes these limitations into four groups: (1) limits of the prompt, (2) limits of fame, (3) limits of regionality and historical styles, and (4) limits of architectural elements and details. It concludes that while Midjourney has great capability to represent high-end AI-generated images inspired by the Islamic tradition, it currently falls short of presenting the actual appearance of some of their original structures.

This research presents a comprehensive computational analysis of the two-phase flow dynamics within a three-dimensional porous transport layer (PTL) in a proton exchange membrane (PEM) electrolyzer. Employing advanced computational fluid dynamics (CFD) and a volume of fluid (VOF) approach, the study utilizes the finite-volume method to model a time-dependent, isothermal process within a laminar flow regime. Notably, the study treats oxygen as the dispersed phase and water as the continuous phase within the system. Investigations on the anode side uncovered the formation of gas bubbles on the electrode's surface subsequent to the electrochemical reaction. The simulation, spanning 5 seconds with 0.25-second intervals, highlights the critical role of the time interval between the initiation and 2 seconds in achieving pressure and velocity equilibrium within the PTL. The initial 0.75 seconds witnessed a peak in oxygen concentration, followed by its movement across the PTL, exhibiting a transition from regions of lower to higher concentration, consistent with known physical behaviour. Remarkably, the model recorded the highest pressure of 3.5 Pa at 0.25 s. Furthermore, the study observed an incremental pressure drop from 0.25 s to 0.5 s and 1 s, approximately amounting to 28.5% and 20%, respectively, ultimately leading to a uniform pressure distribution within the model. Over time, the pressure drop intensified across the entire model due to the evolving nature of the oxygen gas. These findings provide valuable insights into the complex dynamics of two-phase flow processes within PEM electrolyzers, contributing to the advancement of sustainable energy technologies.

Tunable circular devices made of liquid crystals or other materials, like lenses, axicons or phase plates are often constrained by limitations in size, tunability, power and other parameters. These constrains restrict their use and limit their applicability. In this review, a thorough study of the use of light orbital angular momentum in LC devices manufacturing is presented. Twisted light amazingly fosters the simultaneous optimization of most critical parameters. Experimental demonstrations of unmatched performance of tunable LC lenses, axicons and other elements, in magnitudes such as lens diameter (> 1”), power and tunability (> ±6 diopters), fill factor (> 98%) and time response have been achieved by reversible vortex generation created by azimuthal phase delay. This phase delay can be eventually removed within the optical system, so that the lens performance is not affected.

Lithium-ion batteries (LIBs) have become indispensable energy storage devices for various applications, ranging from portable electronics to electric vehicles and renewable energy systems. The performance and reliability of LIBs depend on several key components, including the electrodes, separators, and electrolytes. Among these, the choice of binder materials for the electrodes plays a critical role in determining the overall performance and durability of LIBs. This review introduces polymer binders that have been traditionally used in the cathode, anode, and separator materials of LIBs. Furthermore, it explores the problems identified in traditional polymer binders and examines the research trends in next-generation polymer binder materials for lithium-ion battery as alternatives.

Higher concentrations of greenhouse gases resulting from anthropogenic actions associated with energy generation are one of the causes of climate change. In view of this, several efforts have been undertaken in the search for more sustainable alternatives, and photovoltaic (PV) technology has stood out among the different possibilities. However, PV generation is highly sensitive to future climate variability, which is a source of uncertainty that can complicate energy planning and compromise the viability of systems. This theme has received attention from the academic community, but some challenges to map and identify relevant literature have been encountered. Therefore, this study was conducted to analyze and identify relevant aspects of international scientific production on the impacts of climate change on the potential of photovoltaic production, CC-PVP, through bibliometric techniques. For this, 3900 articles from the Web of Science and Scopus databases, published between 1960 and 2021, were retrieved and analyzed through a bibliometric approach, using the SciMAT tool. Among the results obtained, it is worth pointing out that the CC-PVP research field (i) has moderate maturity, (ii) is concentrated in the areas of energy, fuels and technology, as well as environmental sciences and meteorology, (iii) has the most studied themes currently related to energy and the forecasting of photovoltaic energy production and electric energy consumption in the world, especially when considering climate change, and (iv) is more researched by Chinese, North Americans and Australians.

The valley pseudospin properties of electrons in two–dimensional hexagonal materials result in lots of fascinating physical phenomena, which opens up the new field of valleytronics. The valley-contrasting physics aims at distinguishing the valley degree of freedom based on valley–dependent effects. Here, we theoretically demonstrate that both of the valley–selective high harmonic generation and valley–selective electronic excitation can be achieved by using an orthogonal two–color (OTC) laser field in gapped graphene. It is shown that the asymmetry degrees of harmonic yields in the plateaus, cutoff energies of generated harmonics and electron populations from two different valleys can be precisely controlled by the relative phase of the OTC laser field. Thus the selectivity of the dominant valley for the harmonic radiation and electronic polarization can be switched by adjusting the relative phase of the OTC laser field. Our work offers an all–optical route to produce the valley–resolved high harmonic emissions and manipulate the ultrafast valley polarization on a femtosecond timescale in condensed matter.

Two monophyletic Daphnia species (Daphnia magna and D. similis) were exposed to a sub-lethal concentration of Pb (50 µg/L) for nine generations under two food regimes (usual and restricted) and analysed for acetylcholinesterase (AChE) activity, hatching delay and lifespan, and Net Reproductive Rate (R0) at subcellular, individual and population levels, respectively. At the sixth generation, Pb acclimated neonates were moved to a clean media for three more generations to check for recovery. D. magna showed no Pb effect on Net Reproductive Rate (R0). However, Pb stimulated reproduction, reduced lifespan and decreased AChE activity. Hatching delay and lifespan did not improve during the recovery process, indicating genetic adaptation. Food restriction reduced R0, lifespan, delayed hatching, and increased AChE activity; opposite outcomes were shown for D. similis. Full recovery shown by R0 suggests a physiological acclimation of D. similis. Under food restriction, the animals exhibited a reduction of R0 and lifespan, delayed hatching and increased AChE activity; however, with no Pb effect. The recovery process under food restriction showed that D. similis might not cope with Pb exposure, indicating failed recovery. Such outcomes indicate that a model species' sensitivity may not represent another's sensitivity.

Current sources play an essential role in tissue excitation used in bioelectrical impedance spectroscopy. Most investigations use Howland current sources that, despite their practicality and simplified implementation, have operating frequency limitations and dependence on the load impedance due to theirs narrow output impedance, specially at higher frequencies. The objective of this work is to propose model for a robust current-controlled sinusoidal oscillator. The oscillator is based on fully analog electronics, which enables controlling oscillation phase and amplitude by using a voltage reference. The mathematical model is based on Pyragas control application to the classical harmonic oscillator. From the modelling process, it was build an oscillator topology based on second-generation current carriers and on transconductance amplifiers. The reference signal (Fsync) was a sinusoidal voltage source having a frequency of 1MHz and an amplitude of 1Vpp. The oscillator output current synchronized the oscillations’ phase and amplitude with Fsync, regardless of their magnitude before the control signal acted in the circuit at t≈13.5μs. SPICE simulations using ideal components have confirmed the successful operation of the proposed oscillator. This type of oscillator can be implemented in SOIC, then allowing oscillation control interface with logic circuits.

Integer is either a composite number or a prime number. Therefore, detecting composite numbers is important for solving prime numbers. The study of prime numbers, apart from satisfying human curiosity, can be very important. In this article, the order of composite numbers has been detected. And explained with a simple method and a simple function. And, a method has been developed in which all composite numbers and therefore prime numbers can be determined by using the specified methods, functions and formulas.

The article is devoted to issues related to the propagation and transformation of vortexes in the optical range of frequency. Within the framework of the traditional and modified model of slowly varying envelope approximation (SVEA), the process of converting vortex beams of the optical domain into vortex beams of the terahertz radio range based on nonlinear generation of a difference frequency in a medium with a second-order susceptibility is considered. The modified SVEA splits a slowly varying amplitude into two factors, which makes it possible to more accurately describe the three-wave mixing process. The theoretical substantiation of the rule of vortex beams topological charges conversion is given – the topological charge of the output radio-vortex beam is equal to the difference between the topological charges of the input optical vortex beams. A numerical simulation model of the processes under consideration has been implemented and analyzed.

This work addresses the problem of sampling from Gaussian probability distributions by means of uniform samples obtained deterministically and directly from space-filling curves (SFCs), a purely topological concept. To that end, the well-known inverse cumulative distribution function method is used, with the help of the probit function,which is the inverse of the cumulative distribution function of the standard normal distribution. Mainly due to the central limit theorem, the Gaussian distribution plays a fundamental role in probability theory and related areas, and that is why it has been chosen to be studied in the present paper. Numerical distributions (histograms) obtained with the proposed method, and in several levels of granularity, are compared to the theoretical normal PDF, along with other already established sampling methods, all using the cited probit function. Final results are validated with the Kullback-Leibler and two other divergence measures, and it will be possible to draw conclusions about the adequacy of the presented paradigm. As is amply known, the generation of uniform random numbers is a deterministic simulation of randomness using numerical operations. That said, sequences resulting from this kind of procedure are not truly random. Even so, and to be coherent with the literature, the expression ”random number” will be used along the text to mean ”pseudo-random number”.

The nationwide lockdown imposed to control the spread of novel coronavirus induced dramatic alterations in different sectors of the Nepalese governance, including Solid Waste Management (SWM) practices. The study identifies SW collection gaps in seven major cities of Nepal and highlights the municipal and public households on SW management practices before and during the lockdown to emphasize the linkage between COVID-19 and SWM. It includes information on solid waste status, collection frequency and coverage, workers safety practices, types of vehicles operated for collection and alternative methods adopted by households to manage SW during the lockdown. For this, 1329 households survey and key informant interviews were conducted in seven cities of Nepal during the lockdown. It was found that although the coverage of the collection service was similar during the pandemic, there was a drastic decrease in the collection frequency leading to a collection gap of around 570 tons/day. More than 50% of the surveyed households adopted no proper alternative measures as they claimed that they stored solid waste with proper management so that municipal authorities can take it. The study reveals poor occupational health and safety practices among the solid waste workers due to the unavailability of safety gears and equipment despite being aware of the modes of transmission of the virus. The pandemic exacerbated the challenges of smooth SWM as it is an essential and needy service. This study highlights the need for a timely strategic management framework to be developed by the government to continue the smooth SWM practices during the lockdown.

In this research first, a sequence of properties called delta is assigned to each prime number and then examined. Deltas are only dependent on the distribution of prime numbers, so the results obtained for the delta distribution can be considered as a proxy for the distribution of prime numbers. The first observation was that these properties are not unique and different prime numbers may have the same value of delta of a given order. It was found that a small number of deltas cover a large portion of prime numbers, so by recognizing repetitive deltas, the next prime numbers can be predicted with a certain probability, but the most important observation of this study is the normal distribution of deltas. This research has not tried to justify the obtained observations and instead of answering the questions, it seeks to ask the right question.

Paraphrase generation is an important yet challenging task in NLP. Neural network-based approaches have achieved remarkable success in sequence-to-sequence(seq2seq) learning. Previous paraphrase generation work generally ignores syntactic information regardless of its availability, with the assumption that neural nets could learn such linguistic knowledge implicitly. In this work we make an endeavor to probe into the efficacy of explicit syntactic information for the task of paraphrase generation. Syntactic information can appear in the form of dependency trees which could be easily acquired from off-the-shelf syntactic parsers. Such tree structures could be conveniently encoded via graph convolutional networks(GCNs) to obtain more meaningful sentence representations, which could improve generated paraphrases. Through extensive experiments on four paraphrase datasets with different sizes and genres, we demonstrate the utility of syntactic information in neural paraphrase generation under the framework of seq2seq modeling. Specifically, our GCN-enhanced models consistently outperform their syntax-agnostic counterparts in multiple evaluation metrics.

This work investigated the effects of manufacturing variations including coil resistance, initial pod mass, and e-liquid color on coil lifetime and aerosol generation of Vuse ALTO pods. Random samples of pods were used until failure (where e-liquid was consumed, and coil resistance increased to high value indicating a coil break). Initial coil resistance, initial pod mass, and e-liquid net mass ranged between 0.89 to 1.14 [], 6.48 to 6.61 [g], and 1.88 to 2.00 [g] respectively. Coil lifetime with light color e-liquid was (mean) = 149, (standard deviation) = 10.7 puffs while pods with dark color e-liquid was = 185, = 22.7 puffs with a difference of ~36 puffs (p &lt;0.001). Total mass of e-liquid consumed until coil failure was = 1.93, = 0.035 [g]. TPM yield per puff of all test pods for the first session (brand new pods) was = 0.0123, = 0.0003 [g]. During usage, TPM yield per puff of pods with light color e-liquid was relatively steady while it was continuously decreasing for pods with dark e-liquid. Coil lifetime and TPM yield per puff were not correlated with either variation in initial coil resistance or variation in initial pod mass. The absence of e-liquid in the pod is an important factor in causing coil failure. Small bits of the degraded coil could be potentially introduced to the aerosol. There is a potential correlation of e-liquid color with both coil lifetime and TPM yield per puff. Change of e-liquid color might have been a result of oxidation which changed some nicotine into nicotyrine.

The excellent properties of nanomaterials have been confirmed in many fields, but the effects on plants are still unclear. In this study, we have found that bismuth vanadium promoted the growth of taproots and the development of lateral roots, increased the roots activity by regulating the expression of polyamine or hormone-related genes and reducing the accumulation of reactive oxygen species in Arabisdopsis thaliana. Meantime, BV had higher antimicrobial effect than that of graphene oxide (GO). These results showed us a new perspective possibility of nanomaterials assisting the development of plants and crops, which is expected to become one of the ways to solve the problem of controlling and promoting the development of plants and crops.

Machine learning research has been able to solve problems in multiple aspects. An open area of research is machine learning for solving optimisation problems. An optimisation problem can be solved using a metaheuristic algorithm, which is able to find a solution in a reasonable amount of time. However, there is a problem, the time required to find an appropriate metaheuristic algorithm, that would have the convenient configurations to solve a set of optimisation problems properly. A solution approach is shown here, using a proposal that automatically creates metaheuristic algorithms aided by a reinforced learning approach. Based on the experiments performed, the approach succeeded in creating a metaheuristic algorithm that managed to solve a large number of different continuous domain optimisation problems. This work's implications are immediate because they describe a basis for the generation of metaheuristic algorithms in real-time.

Climate justice as a commons is conceived as the intertemporal climate equity and equal- ity exchange amongst generations. Sustainability, intended as the interplay amongst the economy, the society, the environment, and the governance, is essential to forge the climate justice theoretical framework. On this base, the study attempts to model intertemporal choice amongst generations in these four domains, making use of an over- lapping generations (OLG) model. The proxies detected are GDP growth (economy), environmental quality (environment), and labor growth, and environmental investment (society) as assumptions. The governance dimension is captured by the di¤erence in wealth between young and old generations. The work aims at replying to the follow- ing research question: Which are the conditions for sustainable development such that climate justice holds? The intra-intergenerational exchange is de…ned in two periods, while the individual provides their preferred economic and environmental choice mix as consumption-saving. This study shows that sustainable growth is achievable only with increased young e¤ort and less leisure and consumption.

This letter introduces a frequency response characteristic (FRC) curve and its application in high renewable power systems. In addition, the letter presents a method for fast frequency response assessment and frequency nadir prediction without performing dynamic simulations using detailed models. The proposed FRC curve and fast frequency response assessment method are useful for operators to understand frequency response performance of high renewable systems in real time.

This work probes the combined effects of magnetic field and viscous dissipation on heat field and examine the second law analysis (entropy generation) in an electrically conducting fluid under the effect of wall mass transfer over continuous stretched non-isothermal surface with variable viscosity. The viscosity of the fluid is assumed to be an inverse linear function of temperature. The governing equation for the problem are changed to dimensionless ordinary differential equations by using similarity transformation and solved numerically by using Rung Kutta and Shooting technique. Velocity, concentration and temperature distribution are obtained and used to compute the entropy generation and the Bejan number in the flow field. The effect of variable viscosity, Schmidt number, Hartman and Reynolds number on the velocity, concentration, temperature, entropy generation and Bejan number are studied and discussed.

Metasurfaces of gold (Au) nanoparticles on a SiO2-Si substrate were fabricated for the enhancement of second harmonic generation (SHG) using electron beam lithography and lift-off. Triangular Au nanoprisms which are non-centro-symmetric and support the second- order non-linearity were examined for SHG. The thickness of the SiO2 spacer is shown to be an efficient parameter to spectrally tune to maximise SHG. Electrical field enhancement at the fundamental wavelength was shown to define the intensity of the second harmonics. Numerical modeling of light enhancement was verified by experimental measurements of SHG and reflectivity spectra at the normal incidence. At the plasmonic resonance, SHG is enhanced up to ∼3.5×103 times for the optimised conditions.

Following an updated outlook of global energy production and utilization, we show through selected examples from both developing and developed countries how distributed generation from renewable energy sources, and from solar energy in particular, is the key solution to ending energy poverty across the world. Guidelines aimed at policy makers suggest a systems view of energy that will be instrumental in guiding the transition from fossil fuels to combustion-free renewable energy for all energy end uses.

1) Background: One of the most common cancer that affects men worldwide and North American men is prostate cancer. Gleason score is a pathological grading system to examine the potential aggressiveness of the disease in the prostate tissue. The advancement in computing and next-generation sequencing technology now allow us to study the genomic profiles of patients in association with their different Gleason score more accurately and effectively. 2) Methods: In this study, we used a novel machine learning method to analyze gene expression of prostate tumors with different Gleason scores, and identify potential genetic biomarkers for each Gleason group. We obtained a publicly-available RNA-Seq dataset of a cohort of 104 prostate cancer patients from the National Center for Biotechnology Information’s (NCBI) Gene Expression Omnibus (GEO) repository, and categorized patients based on their Gleason scores to create a hierarchy of disease progression. A hierarchical model with standard classifiers in different Gleason groups, also known as nodes, was developed to identify and predict nodes based on their mRNA or gene expression. In each node, patient samples were analyzed via class imbalance and hybrid feature selection techniques to build the prediction model. The outcome from analysis of each node is a set of genes that can differentiate each Gleason group from the remaining groups. To validate the proposed method, the set of identified genes are used to classify a second dataset of 499 prostate cancer patients collected from cBioportal [1]. 3) Results: The overall accuracy of applying this novel method to the first dataset was 93.3%, and further validated to 87% accuracy using the second dataset. This method also identified genes that were not previously reported as potential biomarkers for specific Gleason groups. In particular, PIAS3 was identified as a potential biomarker for Gleason score 4+3=7, and UBE2V2 for Gleason score 6. 4) Insight: Previous reports show that the genes predicted by this newly proposed method strongly correlate with prostate cancer development and progression. Furthermore, pathway analysis shows that both PIAS3 and UBE2V2 share similar protein interaction pathways, the JAK/STAT signaling process.

In the recent past, there has been a rise in Prostate Cancer (PCa) in Asia, particularly India. Although systematic reviews on PCa have dealt on the genetics, genomics and the environmental influence in causal of PCa, no predictive analytics in comparing the PCa from Caucasian, American to Asian population was attempted. In this review article, we have attempted to elaborate this aspect of PCa and deliberated on challenges related to next generation sequencing methods of PCa’s manifestation when compared to the west.

While laminar flow heat transfer and mixing in microfluidic geometries has been investigated experimentally, as has the effect of geometry-induced turbulence in microfluidic flow (it is well documented that turbulence increases convective heat transfer in macrofluidic flow), little literature exists investigating the effect of electrokinetically-induced turbulence on heat transfer at the micro scale. Using recently observed experimental data, this work employed computational fluid dynamics coupled with electromagnetic simulations to determine if electrokinetically-forced, low-Reynolds number turbulence could be observed in a rectangular microchannel with using Newtonian fluids. Analysis of the results was done via comparison to the experimental criteria defined for turbulent flow. This work shows that, even with a simplified simulation setup, computational fluid dynamics (CFD) software can produce results comparable to experimental observations of low-Reynolds turbulence in microchannels using Newtonian fluids. In addition to comparing simulated velocities and turbulent energies to experimental data this work also presents initial data on the effects of electrokinetic forcing on microfluidic flow based on entropy generation rates.

B chromosomes (Bs) were discovered a century ago, and since then most studies have focused on describing their distribution and abundance using traditional cytogenetics. Only recently have attempts been made to understand their structure and evolution at the level of DNA sequence. Many questions regarding the origin, structure, function and evolution of B chromosomes remain unanswered. Here we identify B chromosome sequences from several species of cichlid fish from Lake Malawi by examining the ratios of DNA sequence coverage in individuals with and without B chromosomes. We examine the efficiency of this method, and compare results using both Illumina and PacBio sequence data. The B chromosome sequences detected in 13 individuals from 7 species were compared to assess the rates of sequence replacement. B-specific sequence common to at least 12 of the 13 datasets are identified as the “Core” B chromosome. The location of B sequence homologs throughout the genome provides further support for theories of B chromosome evolution. Finally, we identified candidate genes located on the B chromosome which may regulate the segregation and maintenance of the B chromosome.

Rhizosphere microbiomes which have been implicated to enhance plant growth and yield are modulated or influenced by a couple of environmental factors such as soil type, plant cultivar, climate change and anthropogenic activities. In particular, anthropogenic activity such as the use of nitrogen-based chemical fertilizers is associated with environmental destruction and this call for a more ecofriendly strategy to increase nitrogen level of agricultural land. This feat is attainable by harnessing nitrogen-fixing endophytic and free-living rhizobacteria. Rhizobium, Pseudomonas, Azospirillum and Bacillus have been found to have positive impacts on crops by enhancing both above and belowground biomass and could therefore play positive roles in achieving sustainable agriculture. Thus, it is needful to study these rhizosphere microbiomes with more sophisticated culture-independent technologies such as next generation sequencing (NGS) with the prospect of discovering novel bacteria with plant growth promoting traits. This review is therefore aimed at discussing factors that can modulate rhizosphere microbiomes with focus on the contributions of nitrogen fixing bacteria towards sustainable agricultural development and the techniques that can be used for their study.

A turbomachinery is essential part in the power generation cycle. But, it is main noise source to annoy workers and users and to make environmental problem. Thus it is important to reduce this noise for operating the power generation cycle. This noise is created by flow instability on rotor blade trailing edge. An airfoil that becomes a section of a rotor blade of a rotating machine is manufactured as a blunt trailing edge (TE) with a round or flatback shape rather than the ideal sharp TE shape for the purposes of producibility and durability. This increases the tonal noise and flow-induced vibration at low frequency owing to vortex shedding behind TE when compared with a sharp TE. In order to overcome this problem, this study investigates the oblique TE shape using numerical simulation. In order to do so, the flow was simulated using large eddy simulation (LES) and the noise was analysed by acoustic analogy coupled with LES result. Once the simulation results were verified using the flatback airfoil measurements of Sandia National Laboratories, numerical prediction was performed for airfoils modified to have oblique trailing edge angles of 60°, 45°, and 30° to analyse the flow and noise characteristics. From the simulation results for an airfoil having an oblique TE, it could be seen that the vortex shedding frequency moves in accordance with the oblique angle and that the vortex shedding noise characteristics change according to this angle when compared to the flatback TE airfoil. Therefore, it is considered that modifying the flatback TE airfoil to have an appropriate oblique angle can reduce noise and change the tonal frequency to a bandwidth that is suitable for mechanical systems.

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

In this study, we investigated the features of co-infection with SARS-CoV-2 and nonpathogenic strain LEV8 of coxsackievirus A7 or enterovirus A71 for Vero E6 cells and Syrian hamsters. The investigation of co-infection with SARS-СoV-2 and LEV-8 or EV-A71 in the cell model was shown that a competitive inhibitory effect for these viruses were especially significant against SARS-CoV-2. Pre-infection with enteroviruses in animals caused more than a 100-fold decrease in the levels of SARS-CoV-2 virus replication in the respiratory tracts and more rapid clearance of the lower respiratory tract from infectious SARS-CoV-2. Co-infection with SARS-CoV-2 and LEV-8 or EV-A71 also reduced the severity of clinical manifestations of the SARS-CoV-2 infection for animals. Additionally, the histological data illustrated that co-infection with nonpathogenic coxsackievirus decreased the level of pathological changes by SARS-CoV-2 in the lungs. Research into the chemokine/cytokine profile demonstrated that the studied enteroviruses efficiently triggered this part of antiviral immune response, which can be associated with significant inhibition of SARS-CoV-2 infection. These results demonstrate that there exists a strong viral interference between the studied nonpathogenic strain of coxsackievirus A7 or enteroviruses A71 and SARS-CoV-2 pathogenic for humans in vitro and in vivo.

Environment pollution is the major problem for all the sectors. In environment pollution there are different types of pollution is included such as air pollution, water pollution, soil pollution etc. In these types of pollution most of it is air pollution. There are many reasons for pollution of air. Human advance in science but one of the major draw backs of science is the pollution of air rapidly. Air pollution is injurious to health. Every year a large number of people died for the effects of air pollution. It can be improved in many ways among these ways technology upgradation plays a major role here. There are various method that prevent air pollution. Many researchers tried and is trying to prevent the air pollution in many ways. In this review paper I summarise the existing research on different ways for preventing air pollution in addition I will discuss the gaps and future aspect on this topic.

In this paper, the integrated performance of a modular biomass boiler with an existing industrial Rankine steam heat and power cycle and a supplementary supercritical-CO2 (sCO2) Brayton cycle is analyzed. The aim is to leverage the high efficiency supplementary sCO2 cycle to increase net generation and energy efficiency from the existing biomass boiler. Two sCO2 heater configurations situated within the flue gas flow path are investigated, namely a single convective-dominant heater, and a dual heater configuration with a radiative and a convective heater. A quasi-steady-state 1D model was developed to simulate the integrated cycle, including detailed component characteristics for the Rankine and Brayton cycles. The model solves the mass, energy, momentum, and species balance equations. The system is analyzed for three cases: (i) the existing Rankine cycle without the sCO2 integration, (ii) with the single convective-dominant sCO2 heater configuration, and (iii) the dual sCO2 heater configuration. The results show the required rate of overfiring for the sCO2 configurations, with a 15.3% increase in fuel flowrate resulting in an additional 21.2% in net power output. The model quantifies the impact of the sCO2 heaters, with reduced heat uptakes for downstream boiler heat exchangers. Furnace water wall heat uptake increased due to overfiring, offsetting the reduced heat uptakes at downstream evaporative heat exchangers. The dual configuration has more impact on Rankine cycle operation due to the radiative sCO2 heater placement in front of the second superheater, absorbing some of the direct radiation from the furnace.

The last decade has witnessed rapid development of immersive virtual reality (IVR) and its application in various contexts. However, its application in supporting real-time virtual collaboration has been quite rare due to technical barriers and the lack of validated design principles. To address this research gap, this study designed and developed an IVR space to enable multi-user synchronous co-located collaboration. An evaluation study (N = 95) was conducted to explore its useful design considerations and the influencing factors for collaboration experience. The IVR space was enabled by the simultaneous localization and mapping (SLAM)-based inside-out tracking technique and was informed by four essential design considerations for promoting effective collaboration in IVR, namely, the role script, learning task, collaboration mechanism, and communication design. The study results revealed that students in general were satisfied with their collaboration experience in IVR, with social presence and collaboration competency as significant predictors of collective efficacy and social experience. Based on both quantitative and qualitative results, this study proposes four validated principles for designing effective IVR spaces to support synchronous co-located collaboration.

Sexual selection involving female choice or female preference (‘inter-sexual’ selection) or male-male competition (‘intra-sexual’ selection) is one of the key mechanisms for evolutionary diversification and speciation. In particular, sexual selection is recently suggested to be an important mode to drive the evolution of “novel” phenotype (i. e. “evolutionary novelty”). Despite extensive studies performed on sexually selected traits or male-specific ornaments (or weapon-like structures) with respect to their evolutionary origin and history and fitness benefits, relatively little is known about the molecular genetic mechanisms underlying their developmental process. However, with advances of genomic technologies (including whole transcriptome analysis using Next Generation Sequencing [NGS] techniques; RNA-Seq), progresses have been made to unveil the genetic background underpinning diverse sexually selected traits in different animal taxa. In the present review, we compile empirical data on the genes, genetic mechanisms or regulatory pathways underlying various sexually selected traits to explore whether the “common” genetic architectures shape the development and evolution of those traits across evolutionarily distant animal lineages. We show that the recruitment of pre-existing genetic network for a new purpose (i.e. gene network “co-option”) is rather widespread in the development and evolution of sexually selected traits, indicating that particular genes or gene-sets are repeatedly involved in different sexually selected traits. Information of genes or genetic mechanisms regulating the development of sexually selected traits would be an essential piece to complete a whole picture of the origin and evolution of sexually selected traits.

Sorghum has become increasingly popular for diverse applications, including food, feed, and bioenergy. The present study aimed to perform a bibliometric and content analysis on sorghum research in the industrial-agricultural sector to evaluate global research patterns, emerging topics, and future trends. The bibliometric analysis of the Scopus bibliographic metadata was done using Bibliometrix and Vosviewer. The results of this investigation show the descriptive analysis underscored fluctuation in research output and citation impact over the years. The identified four patterns through co-occurrence analysis encompassed central themes of sorghum research, including genetic expression and plant stress cluster, cereal crop and yield cluster, biomass and microbial bioprocessing, and metabolism and antioxidant cluster. The thematic map portrays a comprehensive view of cereal crops and yields, biomass and microbial bioprocessing, metabolism and antioxidant research, environmental remediation and sustainable agriculture practices, and the declining theme of starch. The findings provide valuable insights into the global pattern of sorghum research and emerging trends, thus directing future multidisciplinary research efforts for enhanced knowledge and sustainable practices in the industrial-agricultural sector.

Cobalt-doped alumina catalysts were prepared by different methods, applying either the conventional wet impregnation (WI) and/or the advanced spray impregnation (SI), and evaluated as novel oxidation catalysts for CO and MeOH oxidation. The spray impregnation technique aims towards the synthesis of core-shell catalytic nanostructures to secure chemical/thermal stability of the active sites on the catalyst carrier. The catalysts were further promoted with low Pd content (0.5 wt.%) applying either incipient wetness impregnation (DI) or spray impregnation. The results revealed the superior performance of spray impregnated catalysts (Co/γ-Al2O3-SI) for both reactions. The deposition of Co oxide on the outer surface of the alumina particle (SEM images) and the availability of the active Co phase, resulted in the enhancement of Co/γ-Al2O3 catalysts oxidation activity. Pd incorporation increased catalysts reducibility (TPR-H2) and improved the catalysts performance for both reactions. However, Pd incorporation method affected the catalytic performance; as with the SI method the active phase of Co3O4 was probably covered from PdO and was not available for the oxidation reactions. On the contrary, the incorporation of Pd with the DI method resulted in better dispersion of PdO all over the Co/Al catalyst surface, maintaining available Co active sites and better Pd-Co interaction. MeOH desorption studies revealed the methanol oxidation mechanism; Co/Al catalysts promote partial oxidation of MeOH to formaldehyde (HCHO) and dehydration to dimethyl ether (DME), while Pd-based Co/Al catalysts enhance the complete oxidation of methanol to CO2 and H2O.

Scenario analysis is a widely employed method for addressing uncertainties when assessing the physical and socio-economic impacts if climate change. Global scenarios have been extensively used in this context. However, these scenarios are in most cases not suitable for supporting local analyses. On the other hand, locally developed scenarios may lack the global context, thus having limited comparability with or transferability to other locations. The Shared Socioeconomic Pathways, which have been primarily developed for climate impact research, provide the possibility to extend the existing global narratives and adapt them to local characteristics in order to develop locally relevant scenarios. Here, we propose a methodological framework for producing harmonized scenarios across different case studies. This framework was developed in the EVOKED project and combines elements of top-down and bottom-up approaches to develop local scenarios for five regions in northern Europe. We employ the SSP as boundary conditions and, in cooperation with stakeholders from these five regions, develop local scenarios for a range of SSP. The developed sets of scenarios are consistently informed by global developments and are therefore comparable with other downscaled scenarios developed in different regions. At the same time, they have been based on local participatory processes, thus being locally credible and relevant to the needs of stakeholders. The local scenarios constitute a climate service per se as they can raise stakeholder awareness of the processes that will drive risk, exposure, and adaptive capacity in the future and inform discussions on mitigation strategies and adaptation pathways.

There is a growing notion that biomass are the best resource to replace the declining fossil fuels, yet both share the long lived human threat: toxic combustion emissions. Among the toxic combustion products is carbon monoxide (CO) that not only causes acute but also chronic ailments. This brief review discusses the solid fuel processing technologies from combustion, thermochemical and biochemical processing to kinetics and thermodynamics including the mechanism for release of CO. It further expounds on the burden that CO has caused England and Wales in the last 25 years. The main gist are the systems that have been developed to minimize human exposure to CO including cooking, heating, catalytic and detection systems. Finally, alternative technologies are discussed that work by changing the chemical nature of solid fuels as a way to minimize CO emissions.

Intramuscular fat content (IFC) and meat color are vital indicators affecting pork quality. A significant positive correlation between IFC and redness meat color (a* value) indicates that these two traits are likely to be regulated by shared molecular pathways. To identify candidate genes, hub genes, and signaling pathways that regulate these two traits, we measured the IFC and a* value in 147 hybrid pigs and selected individuls with extreme phenotypes for transcriptome analysis. The results revealed 485 and 394 overlapping differentially expressed genes (DEGs) using DESeq2, limma, and edgeR packages affecting IFC and a* value, respectively. Weighted gene co-expression network analysis (WGCNA) identified four modules significantly correlated with IFC and a* value. Moreover, we integrated functional enrichment analysis results based on DEGs, GSEA, and WGCNA conditions to identify candidate genes, and identified 47 and 53 candidate genes affecting IFC and a* value, respectively. The protein-protein interaction (PPI) network analysis of candidate genes showed that 6 and 14 hub genes affecting IFC and a* value, respectively. These genes mainly participated in various pathways related to lipid metabolism and redox reactions. Notably, four crucial hub genes (MYC, SOX9, CEBPB, and PPAGRC1A) were shared for these two traits. After functional annotation of these four hub genes, we hypothesized that the SOX9/CEBPB/PPARGC1A axis could co-regulate lipid metabolism and myoglobin redox response. Further research on these hub genes, especially the SOX9/CEBPB/PPARGC1A axis, will help to understand the molecular mechanism of the co-regulation of IFC and a* value, which will provide the theoretical basis for improving pork quality.

CO2, CH4 and CO are the most critical atmospheric gases in terms of their impact on the radiative system, air quality and health. This work provides information on the direction of source areas and potential sources of emissions and shows many aspects of these gases by a statistical analysis using bivariate polar diagrams and local weather conditions (e.g., temperature, wind speed and wind direction) recorded at the Lamto station (LTO, 6°31N and 5°02W) in Côte d’Ivoire over the 2014-2018 period. The results show that the main regions contributing to the high concentrations of CH4 (> 1925 ppb) and CO2 (> 420 ppm) in the GSS, GSP, PSS and PSP seasons are the North and Northwest sectors of Lamto. In these directions, CH4 and CO2 concentrations are associated with wind speeds less than 6 m.s-1, due to the influences of local sources as emissions resulting from the degradation of organic matter submerged during the impoundment of the Taabo dam, and/nor human activities linked to the practice of intensive agriculture. In addition, the high concentrations of CO (> 350 ppb) are observed in GSS in the North, North-West, North-East and East sectors for wind speeds less than or equal to 9 m.s-1, due to the influences of both local and distant sources. The correlation coefficients between CH4 and CO, and between CH4 and CO2 are positive and significant in all sectors. However, those calculated between CO2 and CO have showed both low and high values in all seasons.

Bacteremia and fungemia are significant causes of morbidity and mortality which frequently occur as co-infections with viral respiratory infections including SARS-CoV-2. It was aimed to evaluate the microorganisms isolated from blood cultures of SARS-CoV-2 positive and negative patients and investigate their antimicrobial resistance patterns. A retrospective analysis was performed with the total number of 22,944 blood cultures sent to the laboratory between November 2020 and December 2021. Blood cultures were performed on the BD Bactec automated system. Identification was performed using conventional methods, VITEK-2 and MALDI-TOF MS. Antibacterial/antifungal susceptibility tests were performed according to EUCAST/CLSI recommendations. SARS-CoV-2 tests were performed with RT-PCR. It was detected 1,630 culture positivity belonging to 652 patients. Totally 633 of 652 patients were tested for SARS-CoV-2; 118 (18.6%) were positive and 515 (81.3%) were negative. The bacteria and fungi isolated at the high-est rate in SARS-CoV-2 positive patients were methicillin-resistant coagulase negative staphylococci (MR-CoNS) (21.5%), Escherichia coli (12.4%), Klebsiella pneumoniae (12.4%), Candida albicans (1.65%) and Candida glabrata complex (1.65%); while in negative patients, E. coli (21.3%), MR-CoNS (13.5%), K. pneumoniae (12.05%), C. albicans (2.1%), Candida parapsilosis (1.1%) and Candida tropicalis (0.9%). The fact that the most common isolate was MR-CoNS in SARS-CoV-2 positive patients (p = 0.028); the detection of Acinetobacter baumannii was more frequent (p = 0.001) and the isolation of carbapenem-resistant K. pneumoniae was at a higher rate than in SARS-CoV-2 negative patients; also, the increase in multidrug-resistant strains indicate that healthcare-associated infec-tions should not be disregarded while focusing on the outbreak.

Vasculogenic mimicry (VM), a process in which aggressive cancer cells form tube-like structures, plays a crucial role in providing nutrients and escape routes. Highly plastic tumor cells, such as those with triple-negative breast cancer (TNBC) phenotype, can develop VM. However, little is known about the interplay between cellular components of the tumor microenvironment upon TNBC cells VM-capacity. In this study, we analyzed the ability of endothelial and stromal cells to induce VM when interacting with TNBC cells, and analyzed the involvement of the FGFR/PI3K/Akt pathway in this process. VM was corroborated using fluorescently‐labeled TNBC cells. Only endothelial cells triggered VM formation, suggesting a predominant role of paracrine/ juxtacrine factors from an endothelial origin in VM development. By immunocytochemistry, qPCR and secretome analyses, we determined increased expression of proangiogenic factors as well as stemness markers in VM-forming cancer cells. Similarly, endothelial cells primed by TNBC cells showed upregulation of proangiogenic molecules, including FGF, VEGFA, and several inflammatory cytokines. The endothelium-dependent TNBC-VM formation was prevented by AZD4547 or LY294002, strongly suggesting the involvement of the FGFR/PI3K/Akt axis in this process. Given that VM is associated with poor clinical prognosis, targeting FGFR/PI3K/Akt pharmacologically may hold promise for treating and preventing VM in TNBC tumors.

Cells are influenced by several biomechanical aspects of their microenvironment, such as substrate geometry. According to the literature, substrate geometry influences the behavior of muscle cells; in particular, the curvature feature improves cell proliferation. However, the effect of the substrate geometry on the myogenic differentiation process is not clear and needs to be further investigated. Here, we show that the 3D co-printing technique allows the realization of substrates. To test the influence of the co-printing technique on cellular behavior we realized linear polycaprolactone substrates with channels in which a fibrinogen-based hydrogel loaded with C2C12 cells was deposited. Cell viability and differentiation were investigated up to 21 days in culture. The results suggest that this technology significantly improves the differentiation at 14 days. Therefore, we investigate the substrate geometry influence by comparing three different co-printed geometries – linear, circular, and hybrid structures (linear and circular features combined). Based on our results, all structures exhibit optimal cell viability (&gt; 94%) but the linear pattern allows to increase the in-vitro cell differentiation, in particular after 14 days of culture. This study proposes an endorsed approach for creating artificial muscles for future skeletal muscle tissue engineering applications.

Wild artisanal cultures, such as SCOBY-based membranes (Symbiotic Culture of Bacteria and Yeasts) and water kefir grains (WKG), are complex consortia of microorganisms comprising yeasts, lactic and acetic acid bacteria, with a large strains’ diversity and abundance. The fermented products (FPs) obtained by the microbiome’s contribution can be included into functional products due to their metabiotics (pre-, pro-, post-, and paraprobiotics) as a result of the complex and synergistic association as well as due to the metabolic functionality. In this study, both consortia of SCOBY and WKG were involved in the co-fermentation of a new formulated substrate, that was further analysed aiming at increasing of the postbiotic composition of the FPs. Plackett-Burman (PB) and Response Surface Methodology (RSM) techniques were used for the experimental designs to select and optimize the most important parameters that influence the freeze-dried starter cultures of SCOBY and WKG activity as a multiple inoculum. The tea concentration (1-3%), sugar concentration (5-10%), raisins concentration (3-6%), SCOBY lyophilized culture concentration (0.2-0.5%), WKG lyophilized culture concentration (0.2-0.5%), and fermentation time (5-7 days), were considered the independent variables for mathematical analysis and fermentation conditions’ optimization. The pH, total acidity (TA), antioxidant activity (DPPH), and antimicrobial activity against Escherichia coli ATCC 25922, Bacillus subtilis MIUG B1, Staphylococcus aureus ATCC 25923, and Aspergillus niger MIUG M5 were evaluated as responses. The rich postbiotic bioactive composition of the FP obtained in optimized biotechnological conditions highlighted the usefulness of the artisanal co-cultures, through their symbiotic metabolic interactions for the improvement of bioactive potential.

Heavy metal contamination is listed among the most alarming threats to the environment and human health. The detrimental effects of heavy metals in the natural environment span from a reduction of biodiversity to toxic effects on marine life - through microplastic born heavy metals -, to impairment of microbial activity in the soil, and to detrimental effects on animal reproduction. A host of different chemical and biological technologies have been proposed to alleviate environmental contamination by heavy metals. Relatively less attention has been paid to the microbial precipitation of heavy metals, as a side mechanism of the most general process of microbially induced calcite precipitation (MICP). This process is currently receiving a great deal of interest from both a theoretical and practical standpoint, because of its possible practical applications in concrete healing and soil consolidation, and its importance in the more general framework of microbial induced mineral precipitation. In this study, we analyse the ability of the marine bacteria Vibrio harveyi in co-precipitating CaCO3 minerals, together with Cd, Cr, Pb, and Zn added in form of nitrates, from solutions containing CaCl2. The precipitated carbonatic minerals were a function of the different heavy metals present in the solution. The process of co-precipitation appears to be rather effective and fast, as the concentrations of the 4 heavy metals were reduced in 2 days by 97.2%, on average, in the solutions.

When present in specific amounts in the air, the colorless, odorless, and tasteless gases monoxide and carbon dioxide may either replace oxygen in red blood cells (CO) or increase the respiratory rate causing cardiac arrhythmias (CO2), leading to death. Commercial sensors take around 8 h to detect levels of CO (50 PPM), causing moderate poisoning. SnO2 presents controlled interactions with the atmosphere using conductance and vacancy adjustments to capture electrical properties. However, the selectivity of gas detection by SnO2 can still be improved, thus also increasing the application possibilities. The present study aimed to optimize the sensing of CO and CO2 in SnO2 using palladium functionalization. The vapor-liquid-solid method synthesized a network of SnO2 nanobelts decorated with palladium nanoparticles. The sensitivity of the sensors for CO and CO2 were evaluated, characterizing parameters such as response time, a wide range of CO and CO2 concentrations, and temperature. In the seventh measurement cycle, the sensor response for different concentrations of gases in consecutive cycles showed a sensitivity of up to 125% for CO in 60 s. Furthermore, we observed increased sensor sensitivity with material doping with nanoparticles from 130 ppm to 1360 ppm in 30 seconds to CO. Conclusion: The results provide a better understanding of the sensitivity of SnO2 in palladium-decorated nanoparticles, offering insights for detecting low CO concentrations quickly. The behavior of these doped nanosensors showed us the importance of considering them as a practical possibility for detecting these gases of importance to human health.

Dyadic data which is also called co-occurrence data (COD) contains co-occurrences of objects. Searching for statistical models to represent dyadic data is necessary. Fortunately, finite mixture model is a solid statistical model to learn and make inference on dyadic data because mixture model is built smoothly and reliably by expectation maximization (EM) algorithm which is suitable to inherent spareness of dyadic data. This research summarizes mixture models for dyadic data. When each co-occurrence in dyadic data is associated with a value, there are many unaccomplished values because a lot of co-occurrences are inexistent. In this research, these unaccomplished values are estimated as mean (expectation) of random variable given partial probabilistic distributions inside dyadic mixture model.

It is common knowledge that increasing CO₂ concentration plays a major role in enhancement of the greenhouse effect and contributes to global warming. The purpose of this study is to complement the conventional and established theory that increased CO₂ concentration due to human emissions causes an increase of temperature, by considering the reverse causality. Since increased temperature causes an increase in CO₂ concentration, the relationship of atmospheric CO₂ and temperature may qualify as belonging to the category of “hen-or-egg” problems, where it is not always clear which of two interrelated events is the cause and which the effect. We examine the relationship of global temperature and atmospheric carbon dioxide concentration at the monthly time step, covering the time interval 1980–2019, in which reliable instrumental measurements are available. While both causality directions exist, the results of our study support the hypothesis that the dominant direction is T → CO₂. Changes in CO₂ follow changes in T by about six months on a monthly scale, or about one year on an annual scale. We attempt to interpret this mechanism by involving biochemical reactions, as at higher temperatures soil respiration, and hence CO₂ emission, are increasing.

The current global COVID-19 pandemic is compounding on populations susceptible to tropical illnesses like dengue in different developing countries like Bangladesh. The growing concern is that Bangladesh is a dengue-endemic zone and the peak transmission occurs in the monsoon season (June to October). In the most recent monsoon, a total of 354 dengue cases have been confirmed until 27^th July 2020, data-driven from only 41 hospitals alone. A fifty-three-year-old male patient was found to be co-infected with COVID-19 and dengue fever. Concerns arise as hospitals are increasingly denying to admit the patients. Moreover, reports of the false-positive results in dengue screening tests recorded in different countries further exacerbate the issue. These conditions could postpone the early diagnosis of COVID-19 cases and aggravate the situation. In addition, the overwhelming wave of the dengue cases would be a challenge for the vulnerable health care system of the country which is already under strain due to the COVID-19 pandemic. Failure to establish and implement proper policies might lead to the dengue outbreak with the burdens of the concurrent COVID pandemic, resulting in the collapse of the health and social system, as well as the economic growth of the country.

Information theory provides robust measures of multivariable interdependence, but classically does little to characterize the multivariable relationships it detects. The Partial Information Decomposition (PID) characterizes the mutual information between variables by decomposing it into unique, redundant, and synergistic components. This has been usefully applied, particularly in neuroscience, but there is currently no generally accepted method for its computation. Independently, the Information Delta framework characterizes non-pairwise dependencies in genetic datasets. This framework has developed an intuitive geometric interpretation for how discrete functions encode information, but lacks some important generalizations. This paper shows that the PID and Delta frameworks are largely equivalent. We equate their key expressions, allowing for results in one framework to apply towards open questions in the other. For example, we find that the approach of Bertschinger et al. is useful for the open Information Delta question of how to deal with linkage disequilibrium. We also show how PID solutions can be mapped onto the space of delta measures. Using Bertschinger et al. as an example solution, we identify a specific plane in delta-space on which this approach’s optimization is constrained, and compute it for all possible three-variable discrete functions of a three-letter alphabet. This yields a clear geometric picture of how a given solution decomposes information

Within the past several decades, the emergence of new viral diseases with more severe health complications and mortality, primarily in older adults with comorbidities, is evidence of an age-dependent, compromised bodily response to abrupt stress with concomitant reduced immunity. The emergence of new infectious coronaviruses such as SARS-CoV-2 has resulted in the coronavirus disease 2019 (COVID-19). The result is increased morbidity and mortality in persons with underlying chronic diseases and among those with compromised defense mechanisms, regardless of age and among older adults who are more likely to fit these categories. COVID-19 appears to be primarily an upper respiratory disease. While SARS-CoV-2 is highly virulent, there is variability in the severity of the disease and its complications in humans. Severe pneumonia, acute respiratory distress syndrome (ARDS), lung fibrosis, cardiac t complication, acute kidney injury, hospitalization, and high mortality have been reported in older adults with COVID-19, that result from pathogen-host interactions. Here, we review potential interactions of the coronavirus and host cellular responses in relation to hallmarks of aging including genomic instability, telomere attrition, impaired autophagy, mitochondrial dysfunction, innate immunosenescence, inflammation and inflammasomes, adaptive immunosenescence, and epigenetic alterations, that likely contribute to the increased pathophysiological responses to SARS-CoV-2 among older adults.

Objective: Taiwan Government’s organizations have endeavored to promote the applications of big data and open data. The “My Health Bank” is one of the measures promoted by the National Health Administration, Ministry of Health and Welfare. This study proposes the perspective of the “value co-creation” with the attempt to extend the concept of service ecosystem and apply it on the platform of My Health Bank to examine whether people (patients, families, and caregivers) can promote their health literacy? Method: This cross-sectional study, with people that have registered at “My Health Bank” as subjects. Complying with the inclusion criteria, 401 questionnaires were delivered, with 391 valid ones, excluding those incompletely and inaccurately filled. Result: That the affecting factors of the co-creation of values: age, education level, annual income, and platform operation show to be significant ( p＜0.05); and gender, occupation, and resource exchange do not reach the significant level (p＞0.1). Conclusion: We found My Health Bank changed the inertia of “value creation” in the traditional medical value, it allows the traditional medical and healthcare industry to expose to the impacts of the mega trend of the internet, the transformation of the platform in a necessary trend.

In the recent decade, Building Information Modelling (BIM) has widely been adopted in the Architecture, Engineering and Construction (AEC) industry and completely upended the way we build. While BIM continues gain momentum in the industry, it has also attracted increasing attentions from researchers. However, most of the current study focuses on reviewing BIM for management, BIM for green building, BIM for infrastructure and BIM for Facilities Management (FM). There are few studies about Global BIM review and to discuss their complex inter-connections. In this study, we adopted a scientometric analysis method to review global BIM research from 2004-2019. A total of 1455 scholarly bibliographic records obtained from Web of Science Core Collection databased were established for the analysis. This study has identified the top productive and influential researchers, research institutes, regions/countries, subject categories and journals in the BIM field. In addition, 11 clusters of Global BIM research were also identified including construction project, green BIM, construction safety planning, automated IFC-based workflow and so on. Authors distinguished 11 clusters of global BIM research into 3 stages, namely formulating stage, accelerating stage and transforming stage. Furthermore, authors reviewed the BIM policy of Singapore and observed there is a co-production relationship between evolution of BIM policy and global BIM research. These findings provide valuable information for researchers, practitioners and policy makers by visualizing the current progress in the research field of BIM and highlighting future research needs.

Magneto-optic surface plasmon resonance (MOSPR) based sensors are highly attractive as next generation biosensors. However, these sensors suffer from oxidation leading to degradation of performance, reproducibility of the sensor surface because of the difficulty of removing adsorbed materials, and degradation of sensor surface during surface cleaning, and these limit their applications. In this paper, I propose MOSPR-based biosensors with 0 to 15 nm thick inert polycarbonate laminate plastic as a protective layer and theoretically demonstrate the practicability of our approach in water-medium for three different probing samples: ethanol, propanol, and pentanol. I also investigate microstructure and magnetic properties. The chemical composition and layered information of the sensor are investigated using X-ray reflectivity and X-ray diffraction analyses and these show distinct fcc-Au (111) phases, as dominated by the higher density of conduction electrons in Au as compared to Co. The magnetic characterization measured with the in-plane magnetic field to the sensor surface for both the as-deposited and annealed multilayers showed isotropic easy axis magnetization parallel to the multilayer interface at a saturating magnetic field of <100 Oe. The sensor showed a maximum sensitivity of 5.5 × 10⁴%/RIU for water-ethanol media and the highest detection level of 2.5 × 10⁻⁸ for water-pentanol media as the protective layer is increased from 0 to 15 nm.c

Nowadays, we live in a world in which people are facing with a lot of data that should be stored or displayed. One of the key methods to control and manage this data refers to grouping and classifying them in clusters. Today, clustering has a critical role in information retrieval methods for organizing large collections inside a few significant clusters. One of the main motivations for the use of clustering is to determine and reveal the hidden and inherent structure of a set of data. Ensemble clustering algorithms combine multiple clustering algorithms to finally reach an overall clustering system. Ensemble clustering methods by lack of information fusing utilize several primary partitions of data to find better ways. Since various clustering algorithms look at the different data points, they can produce various partitions from such data. It is possible to create a partition with high performance by combining the partitions obtained from different algorithms, even if the clusters to be very dense from each other. Most studies in this area have examined all the initial clusters. In this study, a new method is used in which the most sustainable clusters are utilized instead of all primary produced clusters. Consensus function based on co-association matrixes used to select more stable clusters. The most stable clusters selection method is done by cluster stability criterion based on F-measure. Optimization functions are used to optimize the obtained final clusters. The genetic algorithm is the optimizer used in this article to find the ultimate clusters participated in a consensus. Experimental results on several datasets show that the output of proposed method is various clusters with high stability.

Direct georeferencing of airborne pushbroom scanner data usually suffers from the limited precision of navigation sensors onboard of the aircraft. The bundle adjustment of images and orientation parameters, used to perform geocorrection of frame images during the post-processing phase, cannot be used for pushbroom cameras without difficulties: it relies on matching corresponding points between scan lines, which is not feasible in the absence of sufficient overlap and texture information. We address this georeferencing problem by equipping our aircraft with both a frame camera and a pushbroom scanner: the frame images and the navigation parameters measured by a couple GPS/Inertial Measurement Unit (IMU) are input to a bundle adjustment algorithm; the output orientation parameters are used to project the scan lines on a Digital Elevation Model (DEM) and on an orthophoto generated during the bundle adjustement step; using the image feature matching algorithm Speeded Up Robust Features (SURF), corresponding points between the image formed by the projected scan lines and the orthophoto are matched, and through a least-squares method, the boresight between the two cameras is estimated and included in the calculation of the projection; finally, using Particle Image Velocimetry (PIV) on the gradient image, the projection is deformed into a final image that fits the geometry of the orthophoto. We apply this algorithm to five test acquisitions over Lake Geneva region (Switzerland) and Lake Baikal region (Russia). The results are quantified in terms of Root Mean Square Error (RMSE) between matching points of the RGB orthophoto and the pushbroom projection. From a first projection where the Interior Orientation Parameters (IOP) are known with limited precision and the RMSE goes up to 41 pixels, our geocorrection estimates IOP, boresight and Exterior Orientation Parameters (EOP) and produces a new projection which RMSE with the reference orthophoto is around two pixels.

Various renewable energy sources such as wind power and photovoltaic (PV) have been increasingly integrated into the power system through power electronic converters in recent years. However, power electronic converter-driven stability issues under specific circumstances, for instance, modal resonances might deteriorate the dynamic performance of the power systems or even threaten the overall stability. In this paper, the integration impact of a hybrid renewable energy source (HRES) system on modal interaction and converter-driven stability is investigated in an IEEE 16-machine 68-bus power system. Firstly, an HRES system is introduced, which consists of full converter-based wind power generation (FCWG) and full converter-based photovoltaic generation (FCPV). The equivalent dynamic models of FCWG and FCPV are then established, followed by the linearized state-space modeling. On this basis, converter-driven stability analyses are performed to reveal the modal resonance mechanisms of the interconnected power systems and the modal interaction phenomenon. Additionally, time-domain simulations are conducted to verify effectiveness of dynamic models and support the converter-driven stability analysis results. To avoid detrimental modal resonances, an optimization strategy is further proposed by retuning the controller parameters of the HRES system. The overall results demonstrate the modal interaction effect between external AC power system and the HRES system and its various impacts on converter-driven stability.

Electrical energy demand increase does evolve rapidly due to several socioeconomic factors such as industrialization, population growth, urbanization and of course the evolution of modern technologies in this 4th industrial revolution era. Such rapid increase in energy demand introduces a huge challenge in power system. Such has paved way for network operators to seek for alternative energy resources other than the conventional fossil fuel system. Hence, the penetration of renewable energy into the electricity supply mix has evolved rapidly in the past three decades. However, the grid system has to be well planned ahead to accommodate such increase in energy demand in the long run. Transmission Network Expansion Planning (TNEP) is a well ordered and profitable expansion of power facilities that meets the expected electric energy demand with an allowable degree of reliability. This paper proposes a TNEP model that minimises the network reinforcements, operational costs and costs of renewable energy penetrations, while satisfying the increase in demand. The problem is formulated as a mixed integer linear programming (MILP) problem. The developed model has been tested in several IEEE test systems in multi-period scenarios. The paper also carried out a detailed derivation of the new non-negative variables in terms of the power flow magnitudes, the bus voltage phase angles and the lines’ phase angles for proper mixed integer variables’ decomposition techniques. Moreover, this paper tends to provide additional recommendation in terms of which particular year (within 20 years of planning period) can the network operators install new line(s), new corridor(s) and/or additional generation capacity to the respective existing power networks. Such is achieved by running incremental periods simulations from base year through the planning horizon. The results show the efficacy of the developed model in solving the TNEP problem with a reduced and acceptable computation time even for large power grid system.

Neurological involvement following COronaVIrus Disease 19 (COVID-19) is thought to have a neuroinflammatory etiology. Co-ultraPEALut (an antiinflammatory molecule) and luteolin (an antioxidant) yielded promising results as neuroinflammation antagonists. This study aimed at describing cognitive impairment in post-COVID patient treated with co-ultraPEALut. Montreal Cognitive Assessment (MoCA), Prospective-Retrospective Memory Questionnaire (PRMQ), Fatigue Severity Scale (FSS) and a subjective evaluation were administered at baseline and after 10 months. Co-ultraPEALut-treated patients were retrospectively compared with controls. 26 co-ultraPEALut-treated patients showed significant improvement in PRMQ (T0: 51.94±10.55, T1: 39.67±13.02, p

Selection of the most suitable material is one of the key decisions to be taken at the design stage of a manufacturing process. Traditional approaches as Ashby maps based on material properties are widely used in the industry. However, in the production of multimaterial components, the criteria for the selection can include antagonistic approaches. The aim of this work is the implementation of a methodology based on the results of process simulations for several materials and classify them by applying an advanced data analytics method based on Machine Learning (ML), in this case the Support Vector Regression (SVR) and Multi-Criteria Decision Making (MCDM) methodolo-gies, in this case Multi-criteria Optimization and Compromise Solution (VIKOR) combined with Entropy weighting methods. In order to do this, a Finite Element Model (FEM) has been built to evaluate the extrusion force and the die wear in a multi-material co-extrusion process of bimetallic Ti6Al4V-AZ31B billets. After applying SVR and VIKOR combined with Entropy weighting methodologies, a comparison has been established based on the material selection and complexity of the methodology used, resulting that material chosen in both methodologies is very similar and MCDM method is easier to implement because there is no need of evaluate the error of the pre-diction model and the time for data preprocessing is less than the time needed in SVR.

When it comes to financial transactions and counterfeit detection systems, banknote classification is crucial. In this paper, we propose an approach for the classification of Kazakhstan banknote images integrating Learning Vector Quantization (LVQ) with Statistical Texture Feature Extraction using the Gray Level Co-occurrence matrix (GLCM). Our methodology demonstrates effectiveness in accurately classifying banknote images, as evidenced by experimental results. The comprehensive testing scenarios show promising outcomes, with the combination of GLCM and Color Histogram under the LVQ algorithm achieving a high accuracy of 94.87 percent at distance 1 and 90°. These findings indicate the robustness and practical viability of the proposed method for authenticating banknotes.

This study aimed to investigate the coloring ingredient potential of liver homogenates that form Zn-protoporphyrin (ZnPP), a natural red pigment, after anaerobic incubation. The liver homogenates were used to develop nitrite-free sterile pork liver pâtés. These liver homogenates can be applied in the formulation of pâtés directly or as a centrifuged insoluble fraction that is highly concentrated in ZnPP. Both the whole homogenate and its insoluble fraction were adjusted to pH 7.5 before their use in the formulation of pâtés with and without antioxidant (0.5% ascorbate plus 0.1% tocopherol) addition. Pâtés formulated with the whole homogenate showed color and texture characteristics similar to those of the positive control with nitrite. However, high levels of the insoluble fraction also led to pâtés with improved color characteristics but with a two-fold softened texture. Therefore, the form and amount of ZnPP added played a role in the final appearance of the product. The ZnPP pigment was more stable than heme was in the sterilization treatment, and antioxidant addition proved to be unnecessary. The ZnPP-rich ingredients allowed for the preparation of nitrite-free cooked liver pâtés with a stable red color and could be potentially applied in other uncured cooked meat products.

Monometallic (Ni, Co, Cu) and bimetallic (Ni-Co, Ni-Cu) 10-20 wt. % metal containing catalysts supported on fly ash zeolite were prepared by post-synthesis impregnation method. The catalysts were characterized by X-ray powder diffraction, N2 physisorption, XPS and H2-TPR methods. Finely dispersed metal oxides and mixed oxides were detected after the decomposition of impregnating salt on the relevant zeolite support. By reduction intermetallic, NiCo and NiCu phases were identified in the bimetallic catalysts. Hydrogeoxygenation of lignocellulosic biomass-derived levulinic acid to γ-valerolactone (GVL) was studied. Bimetallic, 10 wt. % Ni, 10 wt. % Cu or Co containing fly ash zeolite catalyst showed higher catalytic activity than monometallic ones. Their selectivity to GVL reached 70-85 % at 100 % conversion. The reaction proceeds through formation of 4-hydroxy pentanoic acid, as the only intermediate compound.