This paper outlines the evolution of a learning technology interface from a Beta version to launch with educators and its alignment to pedagogical theory, designed to maximise collaboration between teacher and student. It explores how the “co-creation” of curricula via textual sources that underpin teaching and learning can be enhanced through interactive e-books and outlines the challenges involved in this praxis. With a number of stakeholders involved in the live use of the platform (including teachers, students, HE educators, course instructors, curriculum designers and software developers), iterative feedback loops informed real-time design improvements to both the interface and the-ory. This collaboration utilised a design-based research (DBR) approach (Wang and Hannafin, 2005), which is outlined here as explanation of how the tool developed and how iterative feedback helped to reconsider the challenges educators face in implementing pedagogical innovation across differing contexts. We propose how speculative design (Lukens and DiSalvo, 2012) and Activity Theory (Engeström, 1987) workshops can methodologically enhance the planning and evaluation phases inherent to DBR approaches, which involve students to prepare for educators’ innovation. Finally, we conclude with how educators can utilise these design principles using stratified approaches to help prepare organisational approaches for innovation.

Industrial Control Systems (ICS) are integral to managing and optimizing processes in various industries, including manufacturing, power generation, and more. However, the scarcity of widely adopted ICS datasets hampers research efforts in areas like optimization and security. This scarcity arises due to the substantial cost and technical expertise required to create physical ICS environments. In response to these challenges, this paper presents a groundbreaking approach to generating synthetic ICS data through a data-driven ICS network simulation. We circumvent the need for expensive hardware by recreating the entire ICS environment in software. Moreover, rather than manually replicating the control logic of ICS components, we leverage existing data to autonomously generate control logic. The core of our method involves the stochastic setting of setpoints, which introduces randomness into the generated data. Setpoints serve as target values for controlling the operation of the ICS process. This approach enables us to augment existing ICS datasets and cater to the data requirements of machine learning-based ICS intrusion detection systems and other data-driven applications. Our simulated ICS environment employs virtualized containers to mimic the behavior of real-world PLCs and SCADA systems, while control logic is deduced from publicly available ICS datasets. Setpoints are generated probabilistically to ensure data diversity. Experimental results validate the fidelity of our synthetic data, emphasizing its ability to closely replicate temporal and statistical characteristics of real-world ICS networks. In conclusion, this innovative data-driven ICS network simulation offers a cost-effective and scalable solution for generating synthetic ICS data. It empowers researchers in the field of ICS optimization and security with diverse, realistic datasets, furthering advancements in this critical domain. Future work may involve refining the simulation model and exploring additional applications for synthetic ICS data.

Natural Gas (NG) processing is a prominent industrial separation process. Among the available techniques, the innovative membrane process shows potential for efficient removal of impurities, including carbon dioxide (CO₂). This study focuses on utilizing breakthroughs in membrane separation to drive sustainable CO₂ extraction from natural gas. Through comprehensive research and analysis, we explore the effectiveness and feasibility of membrane-based systems in removing CO₂ impurities from NG, thus promoting greener and more sustainable industrial practices. Our findings underscore the transformative nature of membrane separation technology, presenting new possibilities for a more environmentally-friendly and sustainable approach to CO₂ extraction from natural gas.Natural Gas (NG) processing utilizes various techniques for impurity removal, with the membrane process emerging as a promising option for efficient carbon dioxide (CO₂) extraction. This research proposes the integration of a simple mathematical model into ASPEN HYSYS to design a membrane system for CO₂/CH₄ separation. The study also investigates parameter sensitivities by altering operating conditions, such as feed composition and pressure, as well as membrane properties, including selectivity. By analyzing these variables, we aim to optimize the performance and efficiency of the membrane system, facilitating the sustainable extraction of CO₂ from NG. The findings contribute to advancing the design and operation of membrane-based processes for CO₂ separation, paving the way for greener and more sustainable industrial practices. In addition, this study explores various configurations for optimizing the design of the membrane system, including single-stage with and without recycling as well as double-stage configurations. The investigation demonstrates that methane recovery can be enhanced through the recycling of the permeate stream and by implementing a double stage membrane system. These findings highlight the potential for improving the efficiency and performance of the membrane system, enabling higher methane recovery rates. By considering different configurations, this research contributes to the development of more effective and sustainable CO₂ extraction processes from natural gas.

African swine fever virus (ASFV) is the causative agent of African swine fever, an economically important disease of pigs, often with a high case fatality rate. ASFV has demonstrated low genetic diversity among isolates collected within Eurasia. To explore the influence of viral variants on clinical outcomes and infection-dynamics in pigs experimentally infected with ASFV, we have designed a deep sequencing strategy. Variant analysis revealed 3 distinct SNPs present in the virus inoculum (at 2.4%, 0.7%, and 13% frequency, respectively) that were maintained within all infected pigs (1-6 % frequency, and the latter at 16-21%). Several pigs displayed other unique SNPs at <10% frequency. In addition, a deletion of 10487 bp (resulting in the complete loss of 21 genes) was present at nearly 100% frequency in the ASFV DNA from one pig at position 6362-16849. This deletion was also found to be present at low levels in the virus inoculum and in two other infected pigs. The current methodology can be used for the currently circulating Eurasian ASFVs and also adapted to other ASFV strains and genotypes. Comprehensive deep sequencing is critical for following ASFV molecular evolution, especially for identification of modifications that affect virus virulence.

Background: Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease of unknown origin, with a median survival time of ~3 years after diagnosis without anti-fibrotic therapy. It is characterized by progressive fibrosis indicated by increased collagen deposition and high numbers of fibroblasts in the lung. It was demonstrated that CCL18 induces collagen and αSMA synthesis in fibroblasts. We aimed to identify the CCL18 receptor responsible for its pro-fibrotic activities. Methods: We used a random phage display library to screen for potential CCL18-binding peptides, demonstrated its expression in human lungs and fibroblast lines by PCR and immunostaining and verified its function in cell lines. Results: We identified CCR6 (CD196) as a CCL18 receptor and found its expression in fibrotic lung tissue and on lung fibroblast lines derived from fibrotic lungs but it is almost absent in control lines and tissue. CCL18 induces receptor-internalization in a CCR6-overexpressing cell line. CCR6 blockade in primary human lung fibroblasts reduces CCL18-induced FGF2 release as well as collagen-1 and αSMA expression. Knock-down of CCR6 in a mouse fibroblast cell line abolishes the induction of collagen and -smooth muscle actin expression. Conclusion: Our data indicate that CCL18 triggers pro-fibrotic processes via CCR6, highlighting its role in fibrogenesis.

We report recent enhancements of the online atomic database at the Ohio State University, NORAD-Atomic-Data, that provides various parameters for radiative and collisional atomic processes dominant in astrophysical plasma. NORAD stands for Nahar Osu RADiative. The database belongs to the data sources, especially for the latest works, of the international collaborations of the Opacity Project and the Iron Project. The contents of the database are calculated values for energies, oscillator strengths, radiative decay rates, lifetimes, cross sections for photoionization, electron-ion recombination cross sections and recombination rate coefficients. We have recently expanded NORAD-Atomic-Data with several enhancements over those reported earlier. They are as follows. i) We continue to add energy levels, transition parameters, cross sections for atoms and ions with their publications. ii) Recently added radiative atomic data contains significant amount of transition data for photo-absorption spectral features corresponding to x-ray resonance fluorescence effect, prominent wavelength regions of bio-signature elements, such as phosphorus ions, and emission bumps of heavy elements, such as of lanthanides, that may be created in a kilonova event. We are including iii) collisional data for electron-impact-excitation, iv) experimental data for energies and oscillator strengths for line formation, v) experimental cross sections for photoionization that can be applied for benchmarking and other applications, and vi) introduction of a web-based interactive feature to calculate spectral line ratios at various plasma temperature and density diagnostics, starting with our recently published data for P II. We presented summary description of theoretical backgrounds for the computed data in the earlier paper. With introduction of experimental results, we present summary description of measurement of high resolution photoionization cross sections at Advanced Light Source of LBNL synchrotron set-up and briefly discuss other set-ups. These additions should make NORAD-Atomic-Data more versatile for various applications. For brevity, we provide information on the extensions and avoid repetition of data description of the original paper.

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.

As the international community attaches importance to environmental and climate issues, carbon dioxide emissions in various countries have been subject to constraints and limits. Carbon trading market, as a market tool to reduce greenhouse gas emissions, has gone through a development process from a pilot carbon market to a national carbon market in China. At present, the industries included in the national carbon market are mainly the electric power industry, and the carbon emissions of the electric power industry account for about 40% of the national carbon emissions. According to the construction history of foreign carbon markets, China's future carbon quota allocation will gradually transition from free allocation to auction allocation,the auction mechanism will bring a heavy economic burden to the electric power industry, especially the thermal power generation industry. Therefore, this study takes Guangdong Province as an example to optimize the power generation mix with the objective of minimizing the total economic cost after the innovative introduction of the carbon quota auction mechanism and constructs an optimization model of the power generation mix based on the auction ratio by comprehensively applying the system dynamics model and the multi-objective linear programming model and systematically researches the power generation structure under different auction ratios with the time scale of months and quantitatively evaluates the economic inputs needed to reduce the greenhouse gas emissions.The results of the study show that after comprehensively comparing the total economic cost, renewable energy development and carbon emissions, it is the most scientific and reasonable to set the auction ratio of carbon allowances at 20%, which achieves the best level of economic and environmental benefits.

Marine lipids are recognized for their health promoting features, mainly for being the primary sources of omega-3 fatty acids, and therefore critical for human nutrition in an age when the global supply for these nutrients is experiencing an unprecedent pressure due to an ever-increasing demand. The seafood industry originates a considerable yield of co-products worldwide that, while already explored for other purposes, remain mostly undervalued as sustainable sources of healthy lipids, often being explored for low value oil production. These co-products are especially appealing as lipid sources since, besides the well-known nutritional upside of marine animal fat, particularly rich in omega-3 polyunsaturated fatty acids (PUFAs), they have also interesting bioactive properties, which may garner them further interest, not only as food, but also for other high-end applications. Besides the added value that these co-products may represent as valuable lipid sources, there is also the obvious ecological upside of reducing seafood industry waste. In this sense, repurposing these bioresources will contribute to a more sustainable use of marine animal food, reducing the strain on already heavily depleted seafood stocks. Therefore, untapping the potential of marine animal co-products as valuable lipid sources aligns with both health and environmental goals by guaranteeing additional sources of healthy lipids and promoting more eco-conscious practices.

While machine learning (ML) has been quite successful in the field of structural health monitoring (SHM), its practical implementation has been limited. This is because ML model training requires data containing a variety of distinct damaged instances captured from a real structure and the experimental generation of such data is challenging. One way to tackle this issue is by generating training data through numerical simulations. However, simulated data cannot capture the bias and variance of experimental uncertainty. To overcome this problem, this work proposes a deep learning-based domain transformation method for transforming simulated data to the experimental domain. Use of this technique has been demonstrated for debonding location and size prediction of stiffened panels using a vibration-based method. The results are satisfactory for both, debonding location and size prediction. This domain transformation method can be used in any field where experimental data for training machine learning models is scarce.

Co-delivery of antigens and adjuvants to the same antigen presenting cells (APCs) can significantly improve the efficacy and safety profiles of vaccines. Here, we report amine-grafted silica nanoparticles (A-SNPs) as a tunable vaccine co-delivery platform for TLR7/8 agonists along with the recombinant influenza antigen hemagglutinin H7 (H7) to APCs. A-SNPs of two different sizes (50 and 200 nm) were prepared and coated with INI-4001 at different coating densities, followed by co-adsorption of H7. Both INI-4001 and H7 showed > 90% adsorption to the tested A-SNP formulations. TNF-α and IFN-α cytokine release by human peripheral blood mononuclear cells as well as TNF-α, IL-6, and IL-12 release by mouse bone marrow-derived dendritic cells revealed that the potency of the INI-4001-adsorbed A-SNPs (INI-4001/A-SNP) formulations can be improved relative to aqueous formulation control. This improved potency was dependent on particle size and ligand coating density. In addition, slow-release profiles of INI-4001 were measured from INI-4001/A-SNP formulations in plasma with 30-50% INI-4001 released after 7 days. In vivo murine immunization studies demonstrated significantly improved H7-specific humoral and Th1/Th17-polarized T cell immune responses with no observed adverse reactions. Low-density 50 nm INI-4001/A-SNP elicited significantly higher IFN-γ and IL-17 induction over that of the H7 antigen only group and INI-4001 aqueous formulation controls. In summary, this work introduces an effective and biocompatible SNP-based co-delivery platform that enhances the immunogenicity of TLR7/8 agonist-adjuvanted subunit influenza vaccines.

During the COVID-19 pandemic, the circulation of non–SARS-CoV-2 respiratory viruses changed throughout the world. This study aimed to analyze the effect of respiratory syncytial virus (RSV), metapneumovirus (MPV), rhinovirus (RV), and parainfluenza (PIV)-3 single infection, dual co-infection, and viral load on cytokine and chemokine expression in 300 Mexican patients with ARIs negative for SARS-CoV-2. Molecular detection and viral load were performed by RT-qPCR. Cytokine and chemokine expression was determined in samples positive for single RSV, MPV, RV, or PIV-3 infection, and in the most frequent dual co-infections, by a cytokine panel using a magnetic-bead-based multiplex immunoassay. Of the patients positive for viral infection, 91.7% had a single infection and 8.3% had dual co-infections. In this study, RSV was the respiratory virus with the highest prevalence, and the most common dual co-infection was RV+RSV. On the other hand, RV infections had the highest viral loads compared to the other viruses detected. FGF basic, MIP-1α IL-8, IP-10, MCP-1, IFN-γ, and RANTES showed differential expression between single infections and dual co-infections compared to healthy patients. We report, for the first time, the circulation of non-SARS-CoV-2 viruses in the south of Mexico and the cytokine and chemokine profiles associated with these viruses.

Ti-aluminosilicate gels were used as supports for immobilization of Fe, Co and Ni oxides (5%) by impregnation, and synthesis of efficient photocatalysts in degradation of β-lactam antibiotic from water. Titanium oxide (1 and 2%) was incorporated into zeolite network by modifying the gel during the zeolitation process. The formation of the zeolite Y structure and its microporous structure were evidenced by X-ray diffraction and N2 physisorption. The structure, composition, reduction and optical properties were studied by X-ray difraction, H2-TPR, XPS, Raman, photoluminiscence and UV-Vis spectroscopy. The obtained results indicated a zeolite Y structure for all photocatalysts with tetra-coordinate Ti4+ sites. The immobilized metals from group VIII are both in the form of metal oxides such as Fe2O3, Fe3O4, CoO, Co3O4 , NiO and also in the me-tallic state (Fe0, Co0, and Ni0). A red shift of the absorption edge was observed in UV-Vis spectra of photocatalysts upon addition of Fe, Co or Ni species. The photocatalytic performances were evaluated in degradation of cefuroxime from water under visible light irradiation. The best results were obtained for iron immobilized photocatalysts. Scavenger experiments explained the photocatalytic results and their mechanisms. A different contribution of the active species to the photocatalytic reactions was evidenced.

Delivery systems of the biologically active substance such as proanthocyanidins (PCAN) produced through the electrospinning method were designed using a blend of poly(L-lactide-co-glycolide) and poly[(R,S)-3-hydroxybutyrate]. The research involved the structural and thermal characteristics of the developed electrospun three-dimensional fiber matrix, as well as hydrolytic degradation tests performed on them. Additionally, the release profile of PCAN from the electrospun nonwoven was determined using UV–VIS spectroscopy. Approximately 30% of PCAN was released from the tested electrospun nonwoven during the initial 15-20 days of incubation. The chemical structure of water-soluble oligomers that were formed after the hydrolytic degradation of the developed delivery system was identified through electrospray ionization mass spectrometry. Oligomers of lactic acid and OLAGA oligocopolyester, as well as oligo-3-hydroxybutyrate terminated with hydroxyl and carboxyl end groups, were recognized as degradation products released into the water during the incubation time. It was also demonstrated that variations in the degradation rate of individual mat components influenced the degradation pattern, and the number of formed oligomers. The obtained results suggest that the incorporation of proanthocyanidins into the system slowed down the hydrolytic degradation process of the poly(L-lactide-co-glycolide)/poly[(R,S)-3-hydroxybutyrate] three-dimensional fiber matrix. In addition, in vitro cytotoxicity and antimicrobial studies advocate the use of PCAN for biomedical applications with promising antimicrobial activity.

The SARS-CoV-2 have caused a devastating pandemic of all times in the recent human history. However, there is a serious paucity in high quality data on aggravating factors and mechanisms of co-infection. This study aimed to identify the trending patterns of bacterial co-infections and types and associated outcomes in three phases of the pandemic. Using quality hospital data, we have investigated the SARS-CoV-2 fatality rates, profiles, and types of bacterial co-infections before, during, and after COVID-19 vaccinations. Out of 389 isolates used in different aspects, 298 was examined before and during the pandemic (n=149 before, n=149 during), death rates were 32% during compared to only 7.4% before pandemic with significant association (P value = 0.000000075). Death rate was 34% in co-infected (n = 170) compared to non-co-infected patients (n = 128) indicating a highly significant value (P value = 0.00000000000088). However, analysis of patients without other respiratory problems (n=28) indicated that among the remaining 270 patients, death was 30% in co-infected patients (n=150) and only 0.8% in non-coinfected (n=120) with high significant P value= 0.00000000076. The trending patterns of co-infections before, during, and after vaccinations showed a significant decline in Staphylococcus aureus with concomitant peaks in Gram-negatives in totals of (n= 149 before/n= 149 during): Klebsiella pneumonia (n = 11/49 before/during; E. coli n=10/24, A. baumannii n=8/25, and Ps. Aeruginosa n= 5/16, and S. aureus 13/1. Nevertheless, in post vaccination phase, (n= 91) gender-specific co-infections were examined for potential differences in susceptibility. Methicillin resistant S. aureus (MRSA) dominated both genders followed by E. coli in males and females with the latter gender showing higher rates of isolations in both species. Klebsiella pneumoniae declined to third place mostly in male patients. The drastic decline in K. pneumoniae and Gram-negatives post-vaccination strongly imply a potential co-protection in vaccines. Future analysis would gain more insights into molecular mimicry.

This paper presents a novel cheminformatics approach for the design and synthesis of hydroxyapatite/collagen nanocomposites, which have potential biomedical applications in tissue engineering, drug delivery, orthopedic and dental implants. The nanocomposites are synthesized by the co-precipitation method with different ratios of hydroxyapatite and collagen, and their mechanical, biological, and degradation properties are analyzed using various experimental and computational techniques, such as attenuated total reflection Fourier-transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, scanning electron microscopy with energy-dispersive X-ray spectroscopy, and molecular simulation. The antimicrobial activity of the nanocomposites is evaluated in vitro against several bacterial and fungal strains, demonstrating their medical potential. Additionally, in silico analyses are performed to predict the absorption, distribution, metabolism, and excretion properties and the bioavailability of the collagen samples. This work opens new avenues for the development of novel biomaterials using cheminformatics tools and methods, which can facilitate the optimization of the design and synthesis parameters, as well as the prediction of the biological outcomes. Future research directions include the investigation of the biocompatibility and bioactivity of the nanocomposites in vivo, as well as the exploration of other applications and functionalities of these nanocomposites.

: The primary objective of this study was to investigate the association of certain genetic alterations and intraoperative fluorescent activity of 5-aminolevulinic acid (ALA) in brain metastasis (BM) of lung adenocarcinoma. A retrospective cohort study was conducted among 72 patients who underwent surgical resection of BM from lung adenocarcinoma at our institute for 5 years. Cancer cell infiltration was estimated by the intraoperative fluorescent activity of 5-ALA, and genetic alterations were analyzed by next-generation sequencing (NGS). The sensitivity and specificity for detecting cancer cell infiltration using 5-ALA were 87.5% and 96.4%, respectively. Genes associated with cell cycle regulation (p = 0.003) and cell proliferation (p = 0.044) were significantly associated with positive fluorescence activity of 5-ALA in the adjacent brain tissue. Genetic alterations in cell cycle regulation and cell proliferation were also associated with shorter recurrence-free survival (p = 0.013 and p = 0.042, respectively) and overall survival (p = 0.026 and p = 0.042, respectively) in the multivariate analysis. The results suggest that genetic alterations in cell cycle regulation and cell proliferation are associated with positive fluorescence activity of 5-ALA in the adjacent infiltrative brain tissue and influence the clinical outcome of BM of lung adenocarcinoma.

In this article, we review about the nature of Kerr Blackhole, Kerr metric and express kerr metric in Boyer-Lindquist co-ordinates.

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.

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.

Sarcomas are a heterogenous group of tumours that commonly carry poor prognosis with limited therapeutic options. Adolescents and young adults (AYA) with sarcoma are a unique and under-studied patient population that have only achieved modest survival gains compared to other groups. We present our institutional experience of AYA with sarcoma who underwent comprehensive molecular profiling (CMP) using either large-panel targeted DNA sequencing or whole genome and transcriptome sequencing and evaluated the feasibility and clinical impact of this approach. Genomic variants detected were determined to be clinically relevant and actionable following the Molecular Tumour Board evaluation. Clinicians provided feedback regarding the utility of testing three months after reporting. Twenty-five patients who were recruited for CMP are included in this analysis. The median time from consent to final molecular report was 45 days (interquartile range 37-57). Potentially actionable variants were detected for 14 patients (56%) and new treatment recommendations were identified for 12 patients (48%). Pathogenic germline variants were identified in three patients (12%), and one patient had a change of diagnosis. Implementation for CMP for AYA with sarcoma is clinically valuable, feasible and should be increasingly integrated into routine clinical practice as technologies and turnaround times continue to improve.

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.

Robots in space are necessarily extremely light and lack structural stiffness resulting in natural frequencies of resonance so low as to reside inside the attitude controller’s bandwidth. A variety of input trajectories can be used to drive a controller’s attempt to ameliorate the control-structural interactions where feedback is provided by low-quality, noisy sensors. Traditionally, step functions are used as the ideal input trajectory. However, step functions are not ideal in many applications, as they are discontinuous. Alternative input trajectories are explored in this manuscript and applied to an example system that includes a flexible appendage attached to a rigid main body. The main body is controlled by a reaction wheel. The equations of motion of the flexible appendage, rigid body, and reaction wheel are derived. A feedback controller is developed to account for the rigid body modes. Additional filters are added to compensate for the system’s flexible modes. Sinusoidal trajectories are autonomously generated to feed the controller. Whiplash compensation is additionally implemented for comparison. The control method without random errors with the smallest error is the sinusoidal trajectory method, which showed a 97.39% improvement when compared to the baseline response when step trajectories were commanded, while the sinusoidal method was inferior to traditional step trajectories when sensor noise and random errors were present.

We have investigated the canine of olive flounder in terms of the nonlinear optical signals of two-photon excitation autofluorescence (2PEF) and second harmonic generation (SHG), whereby two kinds of nonlinear microscope images of the canine were obtained using ~140 femtosecond pulses. For increasing excitation power of laser pulses, a photobleaching effect was found to be significant in the red and green ranges of autofluorescence, where a double-exponential decay of the intensity occurs within hundreds of second due to collagen fluorophores in the canine. In the blue range of autofluorescence, the photobleaching is suppressed due to an energy conversion of the incident laser pulse to SHG signal. As a result, the signal in blue range remains constant for long term exposure to laser. We have also found that the SHG intensity depends on the orienta-tion of linearly polarized excitation, and the optical anisotropy of SHG can be attributed to the collagen alignment of canines.

Modern electrical power systems integrate renewable generation, with solar generation being one of the pioneers worldwide. In Latin America, the greatest potential and development of solar generation is found in Chile through the National Electric System. However, its energy matrix faces a crisis of drought and reduction of emissions that limits hydroelectric generation and involves the definitive withdrawal of coal generation. The dispatch of these plants is carried out by the system operator, who uses a simplified mechanism, called “economic merit list” and which does not reflect the real costs of the plants to the damage of the operating and marginal cost of the system. This inefficient dispatch scheme fails to optimize the availability of stored gas and its use over time. Therefore, a real-time redispatch model is proposed that minimizes the operation cost function of the power plants, integrating the variable generation cost as a polynomial function of the net specific fuel consumption, adding gas volume stock restrictions and water reservoirs. In addition, the redispatch model uses an innovative "maximum dispatch power" restriction, which depends on the demand associated with the automatic load disconnection scheme due to low frequency. Finally, by testing real simulation cases, the redispatch model manages to optimize the operation and dispatch costs of power plants, allowing the technical barriers of the market to be broken down with the aim of integrating ancillary services in the short term, using the power reserves in primary (PFC), secondary (SCF), and tertiary (TCF) frequency control.

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.

We present a summary of the main results within the Scale Invariant Vacuum (SIV) paradigm based on the Weyl Integrable Geometry (WIG) as an extension to the standard Einstein General Relativity (EGR). After a brief review of the mathematical framework, where we also highlight the connection between the weak-field SIV equations and the notion of un-proper time parametrization within the reparametrization paradigm, we continue with the main results related to early Universe; that is, applications to inflation, Big Bang Nucleosynthesis, and the growth of the density fluctuations within the SIV. In the late time Universe the applications of the SIV paradigm are related to scale-invariant dynamics of galaxies, MOND, dark matter, and the dwarf spheroidals where one can find MOND to be a peculiar case of the SIV theory. Finally, within the recent time epoch, we highlight that some of the change in the length-of-the-day (LOD), about 0.92 cm/yr, can be accounted for by SIV effects in the Earth-Moon system.

It is argued that all physical knowledge ultimately stems from observation and that the simplest possible observation is that an event has happened at a certain space-time location . Considering historic experiments, which had been groundbreaking in the evolution of our modern ideas of matter on the atomic, nuclear and elementary particle scales, it is shown that such experiments produce as outputs macroscopically observable events which represent binary decisions with regard to simple alternatives and which accumulate in the course of time into spatio-temporal patterns whose forms allow decisions to be taken concerning conceivable alternatives of explanation. Working towards elucidating the physical and information-theoretic characteristics of those elementary pieces of information we arrive at the conclusion that - unlike the events of relativity which are mere 4-tuples of spacetime coordinates - the events of observation are pieces of information endowed with the properties of physical action, spacetime extension, and Lorentz invariance. Another important aspect is that such events are produced at the expense of irreversibly dissipating energy which can be stated in Landauer diction in the form that more energy needs to be spent in the erasure of events than had previously been invested in their initiation.

Ultralight power generation equipment has high requirements for the power density, continuous operation, and transient stability of the whole machine, and there is a direct conflict between high power density design and substantial stability control in the power unit design. In order to meet the power density requirements of ultra-light power stations, three main problems need to be solved, namely engine speed oscillation and flameout in the process of load power mutation, matching of the generator and engine torque, and stabilizing the voltage waveform of the AC output end. In this paper, we proposed an exquisite control strategy for ultralight power generation systems in engines, generators, and inverters. The effectiveness and practicability of the proposed strategy are verified by both simulation and experiment. The results show that the proposed control strategy can effectively solve the instability problem of the ultralights generator set and improve the stability of the system, where the response recovery can be achieved within 0.9 seconds under the condition of total load increase or decrease, and the mismatching degree of the generator following the engine is reduced by 90%. The strategy could also guarantee long-term stable operation with high-quality electrical energy output.

Contemporary diagnostic practice in psychiatry relies on the tick-box approach of diagnostic manuals. In light of the obvious limitations of diagnostic systems, narrative formulations, whether in the form of biological, psychodynamic or behavioural cognitive ones, have been proposed. Their approach, which can be caricatured as one of drawing arrows, enriches our clinical tools and practice but in their explicitly theoretical orientation, as well as expanding the field of discovery, they also constrain it. In two previous papers I summarized the resulting limitations, with specific reference to the patient’s experience and proposed further enriching clinical perspicacity by attending to images and parataxis. The specific intent of attending to the patient’s experiences through a process that explicitly eschews narrativization, but allows clinical phenomena to “hang loose”, is to facilitate a process of clinical discovery and healing through practices of co-production between patient and clinician. In the present paper, I expand the range of phenomena that may assist in this co-production through adding attention to dreams to that of images and parataxis. In particular, I turn to the work of the Italian novelist Guido Morselli. Morselli agrues that the self is created through bundling experiences together through acts of “will” in order to establish our personal narrative. In doing so, however, the “will” forbids access to phenomena that do not fit the dominant narrative. Experience is therefore impoverished. Dream consciousness is a type of consciousness not harnessed by the constraints of narrativity. It allows a slipping of the narrative vigilance which bundles phenomena together to create a coherent narrative and thus offers a richer menu of potential experiences, including “bizarre” images that can serve to challenge our usual self-narrative and offer a new perspective on ourselves.

We introduce the Transformation Flower Approach (TFA), a Theory of Change that attends to multiple value creation and institutional change as a dual design challenge. We highlight how the TFA integrates social scientific theories and models relevant for transformative change (in particular focusing on pathways, leverage points, governance, power, and values) and demonstrate its practical value by an application to the ongoing transformation of the Dutch food system. By providing a holistic, transdisciplinary and practically relevant approach that aims to support new social contract formation, the TFA goes beyond other transformative change approaches. Based on the notion of pathways, it offers a toolbox that aids in working towards desired futures, involving both incumbents and challengers in an effort to harness untapped yet proximal potentials in a forward-looking way. By embracing an innovation approach, it not only promises to circumvent resistance to change, but also serves as a step-by-step approach to identify options for multiple value creation and effective cooperation. We demonstrate the analytical and practical value of the TFA by discussing action perspectives at various levels and scales in the context of the Dutch food system transition, including (1) area-oriented approaches, (2) acceleration agendas for specific transformation pathways, and (3) actor-specific transformation flowers. In developing these, we emphasize the importance of interdependencies between leverage points. Our approach helps to identify opportunities to link transformative options (the what), actors (the who) and levers (the how) in dynamic interaction to embark on transformative pathways.

Background: With continuous advances in next-generation sequencing (NGS), novel hepadnaviruses have been discovered in many species over the last 10 years. Methods: In this study, the cloud search and analysis of NGS data published in Nature by Edgar et al. was used as a basis to re-mine and reanalyze public NGS data for new hepadnaviruses. Results: Ultimately, at least 41 new species of hepadnaviruses were identified, including hepadnaviruses from the model animals hamster and mouse, frog hepadnavirus with pan-species infectivity, and diverse African cichlid hepadnaviruses that circulate within populations. Conclusions: The discovery of the new species of hepadnaviruses not only provides new clues for the study of the origin and evolution of hepadnaviruses, but also can be used to construct new hepadnavirus animal infection models, which will be helpful for the research of eradicative drugs for hepatitis B virus (HBV).

Air pollution has been a major environmental issue worldwide from the last few decades. It is a man-made issue that has a serious harmful impact on the environment and the health of humans. There are different sources of emission, but industrial processes and motor vehicles contribute to a chief part of air pollution. It has acute as well as chronic effects on the health of humans and affects different organs. It is thought the main environmental risk factor in the incidence and progression of several diseases such as lung cancer, asthma, Alzheimer's and Parkinson's diseases. Long-term exposure to air pollution has different toxicological impacts on humans such as respiratory and cardiovascular diseases, neuropsychiatric complications, eye irritation and skin diseases. As per the study by the World Health Organization (WHO), nitrogen oxides (NOx), carbon monoxide (CO), ozone (O₃), sulfur dioxide (SO₂), volatile organic compounds (VOCs) and heavy metals are the major air contaminants. These pollutants are different in their properties, composition and time of disintegration. The aim of this study is to review the different sources, types, impacts, challenges and mitigation of air pollution in detail.

This study investigates the effect of Re addition on the microstructure evolution and oxidation resistance of Co-Cr-Ta-Ti-C alloys. The alloys tested in this study consist of a Co-rich matrix with mixed HCP and FCC phases, together with TaTiC2 and Ti-based carbides. The addition of Re promotes the precipitation and growth of a CoCr-rich σ phase. Differential thermal analysis (DTA) showed that the melting temperatures did not change drastically up to 10 at% Re addition, whereas 15 at% Re addition significantly increased the melting temperature of the alloys. Oxidation tests in air at 1200°C showed that excessive Re content could lead to deterioration in oxidation resistance, mainly due to the accelerated formation of volatile Re oxides.

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.

The Semiconductor and Liquid Assisted Photothermal Effect (SLAPE)” concept was employed for the first time in this study to generate electricity from sunlight. In SLAPE process, a semiconducting material is immersed completely in a stable organic solvent to capture the complete sunlight reaching the earth surface and to turn it into the heat-energy that can be eventually converted into electricity by using Organic Rankine Cycle (ORC) with the help of a heat engine and electric generator. In this investigation, the SLAPE solar panels were fabricated with two top and bottom chambers separated by thin thermally conducting metal sheet (Cu or Al). Multi-crystalline silicon photovoltaic cells (SPVCs) in conjunction with -butyrolactone were employed to capture the sunlight, and a low-boiling point dichloromethane (DCM) solvent was employed as a working fluid to capture the in situ generated heat energy from sunlight. Upon exposure to the natural sunlight, the 21 numbers of SPVCs together with about 2 litres -butyrolactone containing one square meter area SLAPE solar panel has generated about 17 V when integrated with a laboratory model reciprocally moved steam engine and a custom-made electric generator, whereas, a commercial SPVC solar panel with 21 number SPVCs generate a maximum voltage of 11 V. The theoretical background governing the SLAPE solar panels, the necessity for their invention and the proof of concept of SLAPE solar panels have been thoroughly presented and discussed and established in this article.

The paper presents a thorough examination of the burgeoning field of utilizing manufacturing waste for sustainable energy generation, aligning with the global imperative for resource efficiency and clean energy solutions. With the manufacturing sector being a significant contributor to waste generation, this study explores innovative approaches to transform waste materials into valuable resources, thereby mitigating environmental impacts and contributing to a circular economy. This work critically reviews current trends, emphasizing technological advancements, policy interventions, and market dynamics shaping the manufacturing waste utilization landscape. Noteworthy developments, such as advanced sorting technologies and the integration of digital solutions, are discussed in detail, showcasing their role in enhancing the efficiency of waste management processes. The study outlines future trends in the field, anticipating a shift towards closed-loop systems guided by circular economy principles. This comprehensive review aims to contribute to the discourse on sustainable waste management and energy generation by providing a holistic perspective on the field's current state and offering insights into the future trajectories that will propel manufacturing waste toward a more sustainable and circular future. The synthesis of technological innovation, collaborative efforts, and evolving regulatory frameworks presents a compelling case for the continued exploration of manufacturing waste as a valuable resource in the pursuit of a more sustainable and energy-efficient world.

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.

To protect power lines, distance relays are used which can rely on a modified distance resistance. But usually the operating range of these relays changes as the network conditions change (network topology, load value, output value, etc.) and leads to false trips, By using methods that can process information and recognize patterns, for example, the use of micro and intelligent processor algorithms can use the new relays with high precision and thus provide adequate protection. In this study, a distance relay was modeled using a neural network, and it was observed that the neural relay had higher accuracy than the conventional relay. In addition to detecting the fault and its location, type and phase of the fault, three-stage simultaneous protection can be performed. As a result, the number of linear relays can be reduced by using relays based on neural technologies. An MLP (multilayer perceptron) neural network is used to model a sequence of distances.

A bridged 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) derivative (PN-DOPO) in combination with aluminum phosphates coated sepiolite (Sep@AlPO4) was used to improve the flame retardancy, thermal stability and mechanical properties of poly (ethylene oxide) (PEO)/poly (butylene adipate-co-terephthalate) (PBAT) blends. The synergistic effects of PN-DOPO and Sep@AlPO4 on the fire resistance, thermal decomposition behavior and mechanical properties of PEO/PBAT composites were investigated systematically. The results indicated that 5 wt % Sep@AlPO4 combined with 10 wt% PN-DOPO into PEO/PBAT achieved a V-1 rating in UL-94 test and the LOI value increased to 23.7%, meanwhile, the peak-heat release rate (p-HRR), av-HRR and total heat release (THR) values of PEO/PBAT/PN10%/Sep5% composites decreased by 35.6%, 11.0% and 23.0% compared with those of PEO/PBAT, respectively. The thermogravimetric analysis (TGA) results confirmed that PN-DOPO/Sep@AlPO4 could enhance the initial thermal stability and char yield of PEO/PBAT matrix, and TGA/Fourier transform infrared spectrometry (TGA-FTIR) results revealed that the composites exhibited the absorption peaks of phosphorous-containing groups and an increase in gas-phase volatiles during the thermal decomposition process. The digital photographs and morphological structures of char residues demonstrated that PN-DOPO and Sep@AlPO4 mixtures benefited to the formation of a more continuous and dense carbon layer on the composites surface during combustion. Rheological behavior revealed that a higher storage modulus, loss modulus and complex viscosity of PEO/PBAT/PN-DOPO/Sep@AlPO4 composites could also promote the cross-linking structure during burning. Furthermore, the PEO/PBAT/PN-DOPO/Sep@AlPO4 composites exhibited excellent mechanical properties in terms of elongation at break and flexural performance than the PEO/PBAT system. All the results demonstrated that PEO/PBAT system modified by the combination of PN-DOPO and Sep@AlPO4 not only exhibited excellent synergistic effect on the flame retardance, but also had good improvement on thermal stability and mechanical properties, indicating the potential application in areas requiring fire safety.

Alkali-activated materials, sometimes called geopolymers, can be used as alternative cementitious materials to conventional Portland cement. There is a significant current interest in these materials due to their low CO2 footprint. Typical applications of alkali-activated materials are within civil engineering, however, potential applications as well cementing material within oil & gas are also being studied with emerging interest. This paper presents a systematic study of compressive strength development from 1 to 28 days for metakaolin-based alkali-activated cement. The results show that compressive strength is highly dependent upon the initial Si/Al ratio in the mix design, as well as the concentration of the activator solution. Furthermore, due to the relatively low initial reactivity of the used metakaolin material, different types of co-binders were included in the slurry composition to improve early strength development. The two different co-binders tested were another, more reactive metakaolin material and Blast Furnace Slag (GGBFS). It was found that both these co-binders performed as intended, by ensuring early strength development via precipitation of K-A-S-H and C-A-S-H gels, respectively, and also by enabling subsequent strength development due to improved dissolution of the low-reactive metakaolin.

This review focuses on the Just Energy Transition (JET) policies of the BRICS member countries, with the aim of finding lessons and possible adoption of some of the key energy policy aspects utilized in other countries for benchmarking for the South African context. Considerations of the present stage of JET in South Africa and the energy-source mix supporting the electricity sector, cognisant of the lifespan and condition of power plants. Analysis of the energy mix revealed that all nations were energy dependent on electricity which was produced by predominantly fossil fuelled power plants with high GHG (concentrating on high CO2 emissions). It was concluded that some of the learnings and lessons learnt from the BRICS countries might be incorporated into a South African energy plan for the transition with options and guidance for formulation of policies. This study will attract responsible environmentally conscious audience that has a commitment and drive to combat global warming and curbing climate change.

Human keratinocytes and melanoma can stick together to form clusters after eight days in co-culture. As in dynamic system concepts, one can consider cluster formation as the system attractor, cell seeding as the initial condition, and density change over time as a path within the basin of attraction. Herein, Cellular Automata, which is a class of Agent-Based Models, and Boolean Networks are discrete modeling methods used in population dynamics such that running the dynamics of cellular automata backward reveals an underlying network in terms of basin of attraction, also known as global dynamics. Thus, we hypothesize that one can estimate the local dynamic of an agent-based model from the basin of attraction of a boolean network. Here, we propose an approach to estimating these agent-based model rules, which consists of comparing the density states within each state transition and reaching a consensus among state transitions belonging to a basin of attraction of a boolean network. The objectives of this study are: (1) to infer a boolean network from the co-culture growth curve; (2) to estimate the rules of agent-based models; and (3) to implement spatial dynamics simulations. The binarization of the growth curve shows high population density after four days; the estimated agent-based model rules were compatible with cell proliferation and migration in agreement with literature, so we had to propose individual rules for survival and death. Spatial dynamics shows that (1) keratinocytes exhibit a higher density in neighborhoods where melanoma is present; (2) the chance of keratinocyte migration increases until the fourth day, then decreases, and the probability of survival increases substantially after four days; and (3) cells with low proliferation capacity die and free space for those with high ones. Our approach suggests that the attractor state of cell co-culture is induced mainly by an increase in keratinocyte migration and survival. Our approach has the potential to offer valuable clues about microenvironmental interactions or configurations that drive population dynamics.

In this paper, we propose a method for the generation of simulation test scenarios for autonomous driving. Based on the requirements of standard regulatory test scenarios, we can generate virtual simulation scenarios and functional scenario libraries for autonomous driving, which can be used for simulation verification of different ADAS functions. Firstly, the design operation domain (ODD) of the functional scenario is selected and the weight values of the ODD elements taken are calculated; then a combination test algorithm based on parameter weights is improved to generate autonomous driving virtual simulation test cases for the ODD elements, which can effectively reduce the number of generated test cases compared with the traditional combination test algorithm; then the traffic participant elements under each test case are Then, the values of the subelements under the traffic participant element in each test case are sampled and clustered to obtain hazard specific scenarios. Finally, the specific scenarios are applied to the automatic emergency braking (AEB) system on the model-in-the-loop (MIL) testbed to verify the effectiveness of this scenario generation method.

The study aims to analyze the characteristic parameters of rooftop photovoltaic (PV) power generation on industrial plant buildings in the Ningxia region of China, in order to evaluate the impact of passive design characteristic parameters on the benefits of PV power generation and determine the degree of impact of different passive design characteristic parameters. The methodology involves analyzing the characteristics of existing industrial plant buildings in Ningxia, China, and conducting a series of regional studies on the parameters of plant PV power generation influencing factors. The simulation results revealed that five features, including roof form, PV panel laying pattern, PV panel laying area, azimuth angle, and PV module material, have a significant impact on PV power generation benefits of industrial plant buildings.The study further uses MATLAB 2022b to build a backpropagation neural network model with 5 neurons in the implicit layer to predict the PV power generation benefits. The model calculates the whole-life cycle power generation benefits and the whole-life cycle reduction of carbon emissions as output data. Finally, the Mean Impact Value (MIV) method is employed to select the feature parameter values one by one within their range, and the passive design feature parameters that have the greatest influence on the prediction results are identified as the PV panel laying method, the PV panel tilt angle, and the PV material parameters, respectively.

As renewable energy generation prediction systems have been introduced into the energy trading market, accurate prediction of solar photovoltaic (PV) energy generation has become a crucial challenge for ensuring stable trade of variable energy. Therefore, it is essential to quantitatively investigate and analyze current prediction technology and develop more advanced prediction systems. In this study, three models for predicting PV energy generation were investigated. Multiple regression, random forest, and gradient boosting machine (GBM) models were con-structed for 15 utility-scale power plants throughout South Korea. Model performance was evaluated in terms of root mean square error (RMSE) and mean absolute error (MAE). The multiple regression-based model had an RMSE of 12.00% and MAE of 9.06%. The random forest model had an RMSE of 11.69% and MAE of 8.61%. The GBM model had an RMSE of 11.34% and MAE of 8.18%, indicating its superior accuracy among the three models in predicting PV energy generation. These findings provide valuable insights that may contribute to the development of advanced PV energy generation models and their application in grid operations.

The devastating effects of COVID-19 permeates virtually all aspects of life across geographic boundaries. As the lockdown is eased, and reinstated, across many parts of the world, attention is now shifting towards how to navigate the ‘now normal’ rather than the ‘next normal,’ of doing business with a view to achieving sustainable development. This study highlights some of the challenges and opportunities for micro, small, and medium enterprises (MSMEs) in times of crisis such as COVID-19. Conceptual by orientation, the study provides a broad overview of trends in crises times, drawing upon a range of qualitative accounts. The overarching message is the current direction of travel for MSMEs in sustaining their bottom-line, not after the crisis, but at this particular moment in time. The study highlights some implications for ‘pivoting,’ in order to cushion the impact of the pandemic on efforts to capacitate MSMEs in leveraging value co-creation with the consumers. The implications of the here and now are discussed.

This comprehensive review explores the principles, applications, and future directions of human-powered energy generation technologies. It begins by providing a detailed examination of viable human energy sources, elucidating the physical principles behind various energy harvesting devices. The review then compiles and assesses existing products in the field of human power generation, while also outlining the opportunities and challenges it presents. Finally, an innovative concept of an eco-village system is introduced to demonstrate a future potential application scenario for human-generated electricity. It outlines two developmental stages for this system and underscores its significance in the construction of the harmonious and sustainable communities. This forward-thinking approach could pave the way for broader discussions on sustainable living and eco-friendly energy generation in a world increasingly focused on environmental concerns and social stability.

Lentil (Lens culinaris Medik.) is an essential legume crop providing healthy and nutritious food for people in low- to middle-income countries, worldwide. Lentil roots support symbiotic interactions with soil rhizobia species fostering nitrogen fixation; however, assemblage and diversity of the complete microbial rhizosphere community and the effect of seed genotype and origin remains largely unexplored. In this study we examined with metagenomic analysis, the effects of seed origin on the rhizosphere’s communities in samples of the famous Greek lentil landrace Eglouvis derived from different local farmers and farming systems including a Gene Bank sample, in comparison to a commercial variety. The landrace exhibited higher rhizosphere microbiome diversity compared to the commercial variety for all indexes. A core microbiome comprised of 158 taxa was present in all samples, while higher number of unique bacterial taxa was recorded in the landrace samples compared to the commercial cultivar. Noteworthy, landrace samples originated from organic farming had more than double unique taxa compared to conventional counterparts. The study revealed higher diversity of N2 fixers and archaea, Crenarchaeota and Thaumarchaeota, in landrace samples and particularly in those derived from organic farming, underpinning the distinct recruiting efficiency of beneficial soil microbes by the landrace.

A novel approach was developed that combined LP-based row generation with optimization-based sorting to tackle computational challenges posed by budget allocation problems with combinatorial constraints. The proposed approach dynamically generated constraints using row generation and prioritized them using optimization-based sorting to ensure a high-quality solution. Computational experiments and case studies revealed that as the problem size increased, the proposed approach outperformed simplex solutions in terms of solution search time. Specifically, for a problem with 50 projects (N = 50) and 2,251,799,813,685,250 constraints, the proposed approach found a solution in just 1.4 seconds, while LP failed due to the problem size. The proposed approach demonstrated enhanced computational efficiency and solution quality compared to traditional LP methods.

The (benzylthio)acetic acid (HBTA) and some aminopyrimidines, namely 2-aminopyrimidine (2-AP), 5-aminopyrimidine (5-AP), 2-amino-4,6-dimethylpyrimidine (2-A-4,6-DMP) and 2,4,6-triaminopyrimidine (2,4,6-TAP), were successfully embodied as structural units into the construction of a total of four novel supramolecular organic frameworks. The received crystalline solids were inspected by single crystal X-ray diffraction (SC XRD) in order to obtain insight into the structural and supramolecular facets. The SOFs deriving from 2-AP, 5-AP as well as 2-A-4,6-DMP crystallize in the form of true co-crystals (1-3), while the one originating from 2,4,6-TAP crystallizes as salt solvate (4). The SC XRD results indicated the different contents of structural residues present in the asymmetric units of the crystals 1-4 despite the using the same molar ratio of molecular co-formers in each case. The molecular structures of co-crystals 1-3 consist of either one neutral residue of each starting components (1 and 3) or a half nonionized residue of aminopyrimidine ingredient and one neutral residue of acidic specie (2). The asymmetric unit of salt solvate 4 is composed of two ionized residues of each co-former (two 2,4,6-TAP+ cations and two BTA- anions) and one MeOH solvent molecule. The most extensive H-bonding network is observed in the crystal structure of salt solvate 4. The relevant molecular ingredients in co-crystals 1-3 are mainly hold together by the neutral Ocarboxylic–H···Npyrimidine and Namine–H···Ocarboxylic H-bonds. In the case of aggregate 4, the corresponding ionic residues are predominantly sustained by the charged-assisted Npyrimidinium–H···Ocarboxylate and Namine–H···Ocarboxylate hydrogen interactions. The MeOH solvent incorporated into the crystal lattice of adduct 4 is also involved in H-bonding by simultaneously serving as the single donor in OMeOH–H···S and the single acceptor in Namine–H···OMeOH H-bonds afforded the structural diversity within the 2,4,6-TAP+ cations and BTA- anions. Other weaker sets of additional non-covalent contacts existing in the crystal structures of analyzed conglomerates are involved in the self-assembly, stabilization and expansion of total supramolecular organic frameworks. The fact of the formation of non-covalent bonded supramolecular organic frameworks in question is also reflected in corresponding results obtained through elemental analysis (EA), Fourier transform infrared spectroscopy (FT−IR) and thermal analysis (TG/DSC).

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.

Multiphoton microscopy (MPM) is a cutting-edge nonlinear microscopy technique known for its exceptional capabilities in imaging dense tissues, making it an ideal tool for exploring human kidney tissue. This study delves into the application of MPM in evaluating renal cell tumors and characterizing tumor capsules. MPM encompasses two core methods: two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG). It leverages femtosecond lasers to provide deep tissue imaging while minimizing phototoxicity, making it well-suited for live tissue analysis. The study analyzed 100 formalin-fixed paraffin-embedded (FFPE) kidney tissue samples, ensuring compliance with ethical standards. Using a Ti:Sapphire laser for femtosecond pulses and a variety of optical components and filters, the researchers captured TPEF and SHG signals, facilitating image analysis. Normal kidney tissue exhibited distinctive structures like glomeruli and tubules under MPM. Renal cell carcinoma (ccRCC) displayed unique TPEF patterns with eccentrically located nuclei and indistinct cytoplasmic membranes. Papillary RCC (pRCC) exhibited a papillary pattern with dark nuclei, while chromophobe RCC (chRCC) showcased distinct features like thick cell membranes, strong TPEF signal in nuclei, and granular cytoplasm. Renal oncocytoma (RO) presented strong TPEF signals in cuboidal cells with microcyst-like arrangements. Overall, MPM proved invaluable in assessing human kidney tissue, offering distinct TPEF patterns for different renal cell tumor types. This non-invasive technique has the potential to enhance pathological examinations and advance our understanding of complex biological processes, ultimately contributing to improved diagnostics and treatment strategies for renal diseases.

We discuss a formalism which allows for the calculation of a higher harmonic current response to an applied electric field for disordered superconducting systems described on the basis of tight-binding models. The theory is based on an expansion of the density matrix in powers of the field amplitudes where we solve the equation of motion for the individual components. This allows the evaluation of higher order response functions on significantly larger lattices than one can achieve with a previously used approach, which is based on a direct temporal integration of the equation of motion for the complete density matrix. In case of small lattices, where both methods can be applied by including also the contribution of collective modes, we demonstrate the agreement of the corresponding results.

Soiling accumulated on a photovoltaic (PV) module can significantly reduce the transmittance of the cover glass, resulting in power losses and consequent economic losses. Natural atmospheric parameters influence the accumulation of soiling at the various geographic locations. In this paper, the approaches and outcomes of the research studies on either indoor (simulator-based) or outdoor (field-based) PV soiling have been thoroughly reviewed. Different parameters depicted for the power loss of PV modules are analyzed individually and presented. Moreover, this study delves into a detailed examination of the key factors influencing dust depositions on PV modules in various geographical regions, with a particular focus on their relationship with climatic conditions. This way, probable future research directions to quantify soiling losses are identified. In addition, different loss prevention and mitigation techniques are also reviewed. This makes it possible to highlight effective strategies and pinpoint potential future research lines in these areas.

The increase in carbon dioxide emissions has a significant impact on human society and the global environment. As the most abundant and cheap C1 resource, the conversion and utilization of carbon dioxide has received extensive attention from researchers. In many methods of carbon dioxide conversion and utilization, the reverse water gas conversion reaction is considered to be one of the most effective ways. In this paper, the research progress of reverse water gas conversion reaction in recent years is introduced.

In recent years, the genesis of natural gas and the definition of major gas source rocks in the Baiyun Sag of the Pearl River Mouth Basin have attracted extensive attention from scholars. There is still considerable controversy over the genesis and the main gas source rocks of natural gas. In this study, the chemical kinetics method of natural gas generation and carbon isotope fractionation was used to study the generation history and isotope evolution history of Paleogene natural gas in the Y5 well area located on the north slope of Baiyun Sag. And other geochemical discriminant methods were applied simultaneously to determine the type and source rocks of natural gas. The results show that the natural gas in the Y5 well area on the northern slope of Baiyun Sag is mainly kerogen degradation gas, mixed with a small amount of oil cracking gas. The mixture of kerogen degradation gas and a small amount of crude oil cracking gas caused the inversion of the carbon isotope sequence of ethane and propane. The natural gas in the Y5 well area mainly comes from delta–shallow lacustrine facies source rock. The high–quality reservoirs in the shallower strata accumulate natural gas generated in the early stage, and the tight reservoirs in the deeper strata mainly accumulate natural gas generated in the late stage.

Zambia recently experienced extended hours of load shedding due to reduced hydroelectricity generation attributed to poor rainfall patterns. The inability to meet energy demand has influenced the government to consider alternative energy sources. This study aims to assess the economic feasibility of the eight sites using a 25-turbine layout for a 4 MW generic wind turbine at 130m hub height. An economic evaluation mathematical model was developed to analyze the economic feasibility using net present value, simple payback period, internal rate of return, and levelized cost of electricity (LCOE). The study shows that the Lusaka wind farm was the most economical with 386 GWh energy yield analysis (EYA), wind speed of 8 m/s, NPV of 316 million dollars, SPP of 2.9 years, IRR of 82%, and LCOE of $0.182/ kWh. The results also show that the other seven sites are economically feasible, with Petauke being the lowest. The study's economic sensitivity analysis conducted by varying the average electricity tariff shows that Lusaka was the most financially viable site. Therefore, policymakers should develop cost-reflective feed-in tariff (FiT) schemes and power purchase agreements for the country to have cost-reflective electricity tariffs that will motivate independent power producers to invest in Zambia.

The optimal regime of three-photon resonant excitation of a helium atom by a femtosecond ul-traviolet (UV) pulse was discovered and numerically studied, at which the maximum power of the third harmonic of the UV field is achieved in the spectrum of dipole acceleration (the second time derivative of the induced dipole moment) of the atom. It is shown that the optimal frequency of the UV field nearly coincides with the frequency of the three-photon transition 1s2 – 1s2p, taking into account its shift as a result of the dynamic Stark effect, and the intensity of the UV field is dictated by the condition of maximizing the product of the populations of the 1s2 and 1s2p states, averaged over the time interval during which the UV field is non-zero. For the considered UV field durations, from 10 to 100 cycles of the carrier frequency (from units to tens of femtoseconds), the optimal intensity lies in the range from 10^14 W/cm^2 to several units of 10^14 W/cm^2. It is shown that with an optimal choice of the frequency and intensity of the UV field, the dynamics of excitation of bound and continuum states, as well as the shape of the time envelope of the dipole acceleration of the atom, weakly depend on the duration of the UV field envelope; only their time scale changes significantly. In addition, under the optimal conditions the average power of the third harmonic signal in the dipole acceleration spectrum is practically independent of the duration of the UV field envelope.

In South Korea, demolition waste (DW) management has become increasingly significant owing to the rising number of old buildings. Effective DW management requires an efficient approach that accurately quantifies and predicts the generation of DW (DWG) of various types, which necessitates access to the required information or technology capable of achieving this. Hence, we developed an artificial intelligence-based model that predicts the generation of ten DW types, specifically from buildings in redevelopment areas. We used an artificial neural network algorithm with < 10 neurons in the hidden layer to derive individual input variables and optimal hyperparameters for each DW type. All DWG prediction models achieved an average validation and test prediction performance (R²) of 0.970 and 0.952, respectively, with their ratios of percent deviation ≥ 2.5, ver-ifying them as excellent models. Moreover, a Shapley additive explanations analysis revealed that DWG was most impacted by the floor area for all the DW types, with a positive correlation with DWG. Conversely, other factors showed either a positive or negative correlation with DWG de-pending on the DW type. The study findings will enable demolition companies and local gov-ernments in making informed decisions for efficient DW management and resource allocation by accurately predicting the generation of various types of DW.

As one of the important components of underwater propulsion systems, water lubricated bearings are often failure due to mechanical wearing and vibrating, especially under high loads and prolonged friction. In this paper, a dual-network co-crosslinking strategy based on HNBR is proposed, in which the epoxy network connects with the rubber network through Epoxidized Eommia ulmoides gum. The damping, tribological and mechanical properties of the prepared composite are systematically investigated. The results show that this material has excellent friction and vibration damping properties, with a water-lubricated coefficient of friction as low as 0.022 and a wear resistance as high as 3.87 × 10-6mm3/Nm. Preparing HNBR-based composite by dual network co-crosslinked is proved being a feasible solution to improve the reliability and service life of water-lubricated bearings.

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.

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.

Understanding microbial composition in upper respiratory infections (URIs) is critical for effective diagnosis and treatment. Precision Metagenomic next-generation sequencing p(mNGS) can provide a comprehensive yet clinically relevant profile of respiratory infection. The hybridization capture-based targeted sequencing generated a precision metagenomics profile of 29 patients with acute URIs. Nasopharyngeal samples were collected from the subjects suspected of respiratory infection, and p(mNGS) was performed using the Illumina®/IDbyDNA Respiratory Pathogen ID/AMR Panel (RPIP). The dataset obtained from the mNGS analysis contains a wealth of information on the composition of acute URI microbiota, including the relative abundance of known pathogens and potential clinical implications. The dataset represents a valuable resource for future research endeavors in respiratory medicine, infectious disease epidemiology, and therapeutic interventions. In addition, the dataset offers significant potential for reuse and integration with other omics datasets. The comprehensive nature of the mNGS data allows the exploration of associations between the respiratory microbiota and host factors such as clinical outcomes, immune responses, or genetic predisposition. Combining this dataset with other relevant datasets, such as transcriptomics or metabolomics, could provide a deeper understanding of the complex interactions between the microbiota and the host in acute URIs.

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.

We report a diode pumped solid state (DPSS) laser used for intracavity pump-enhanced difference frequency generation (DFG) to create a 3.5 micron laser. Using a 50 mm-long periodically poled lithium niobate (PPLN) crystal inside the cavity of an Nd:YVO4 solid state laser at 1064 nm with 4.5 W pump power at 808 nm, and a 310 mW C-band signal at 1529 nm, up to 31 mW of mid-infrared output power at 3499 nm is obtained. The cavity requires no active stabilization and/or locking, and the entire cavity is &lt;8 cm in length. The obtained output power corresponds to a black box efficiency of 2.20 %W-1, which is the highest value reported to date for continuous wave DFG based on a bulk nonlinear optical crystal with no active stabilization. Potential future applications in free space optical communication are discussed as well.

This research, which focuses on wave energy generating technology, suggests a brand-new oscillating float-type wave energy conversion system that is appropriate for the offshore wave environment. To accurately model the device, a three-dimensional viscous numerical pool is created based on STAR-CCM+. The array-type power generation device is numerically simulated using theoretical analysis and numerical simulation, and the wave energy power generation device is arranged as double floats in the front and rear rows, representing triangular array type and rectangular array type, respectively. The triangular array type is a superior layout and can make greater use of marine resources, according to this paper's analysis of the hydrodynamic and power generation impacts of the three array types. The findings are meant to serve as a guide for engineering practice.

Remote distributed generation control and demand response is nowadays a basic need, especially for the Distributed Network Operators (DNOs). The integration of Renewable Energy Sources (RES) with stochastic production characteristics into the grid in conjunction with the newly appeared stochastic demand consumers (i.e., electric vehicles) hardens the ef-forts of the DNOs to keep the grid’s operation within safe limits and prevent cascading black-outs while staying in compliance with the SAIDI and SAIFI indices during maintenance and re-pair operations. Taking also under consideration the aging of the existing grid infrastructure, making it year by year more prone to failure, it is yet of great significance for the DNOs to have access to real-time feedback from grid’s infrastructure, fast, with low-cost upgrade interventions, easily deployed on the field and with fast response potential, in order to be able to perform real-time grid management (RTGM). In this article, we describe the architecture, development and deployment of a hybrid real-time control system of distributed generation (DG) units, which has the potential to be applied easily to DNO’s substations, RES plants and consumers (i.e. electric vehicles’ charging stations), that combines a low-cost minimum intervention into the electricity grid and its components and eliminates all communication interoperability problems between the different vendors’ installed electrical equipment.

Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent Based Models and Simulation consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Agents generate large volumes of data over time and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents’ perspectives on key events by providing natural language narratives. However, these narratives need to be factual, transparent, and reproducible. To this end, we present a structured narrative prompt for sending queries to LLMs. Chi-square tests and Fisher’s Exact tests are applied to assess statistically significant difference in sentiment scores of the narrative messages between simulation generated narratives, ChatGPT-generated narratives, and real tweets. The narrative prompt structure effectively yields narratives with the desired components from ChatGPT. This structure is expected to be extensible across LLMs. In 14 out of 44 categories, ChatGPT generated narratives which has sentiment scores that were not discernibly different, in terms of statistical significance (alpha level of 0.05), from the sentiment expressed in real tweets. Three outcomes are provided: (1) a list of benefits and challenges for LLMs in narrative generation; (2) a structured prompt for requesting narratives of a LLM based on simulated agents’ information; and (3) an assessment of statistical significance in the sentiment prevalence of the generated narratives compared to real tweets. This indicates significant promise in the utilization of LLMs for helping to connect simulated agent’s experiences with real people.

The aim of this article is to review hydrogen combustion applications within the energy transition framework. Hydrogen blends are also included, from the well known hydrogen enriched natural gas (HENG) to the hydrogen and ammonia blends whose chemical kinetics is still not clearly defined. Hydrogen and hydrogen blends combustion characteristics will be firstly summarized, in terms of standard properties like the laminar flame speed and the adiabatic flame temperature, but also evidencing the critical role of hydrogen preferential diffusion in burning rate enhancement and the drastic reduction in radiative emission with respect to natural gas flames. Then, combustion applications in both thermo-electric power generation (based on internal combustion engines, i.e., gas turbines and piston engines) and hard-to-abate industry (requiring high temperature kilns and furnaces) sectors will be considered, highlighting the main issues due to hydrogen addition related to safety, pollutant emissions, and potentially negative effects on industrial products (e.g., glass, cement and ceramic).

Functional dependence of the axial zero-field splitting parameter D with respect to a properly chosen geometrical parameter (Dstr) in metal complexes is termed the Magnetostructural D-Correlation. In mononuclear hexacoordinate Ni(II) complexes with the ground electronic term 3B1g (3A2g in the regular octahedron) it proceeds along two intercepting straight lines allowing to predict the sign and magnitude of the D-parameter by knowing the X-ray structure alone; Dstr is constructed from the metal-ligand bond lengths. In hexacoordinate Co(II) complexes it is applicable only in the segment of the compressed bipyramid where the ground electronic term 4B1g is orbitally non-degenerate so that the spin Hamiltonian formalism holds true. The D vs Dstr correlation is strongly non-linear and it is represented by a set of decreasing exponentials. In tetracoordinate Co(II) complexes, on the contrary, the angular distortion from the regular tetrahedron is crucial so that the appropriate structural parameter Dstr is constructed of bond angles. All of these empirical correlations originate in the electronic structure of metal complexes that can be modelled by the generalized crystal-field theory. As the barrier to spin reversal in the single-molecule magnets is proportional to the D-value, for a rational tuning and/or prediction of the single-molecule magnetic behavior knowledge/prediction of the D-parameter is beneficial. In this review, we present the statistical processing of an extensive set of structural and magnetic data of Co(II) and Ni(II) complexes, which were published over the past 15 years. Magnetostructural D-correlations defined for this data set are reviewed in detail.

This paper investigates the polarization and heat generation characteristics of batteries under different ambient temperatures and discharge rates by means of using a coupled electric-thermal model. The study found that the largest percentage of polarization is ohmic polarization, followed by concentration polarization and electrochemical polarization. The values of the three types of polarization are generally small and stable under normal-temperature environments and low-discharge rates. However, they increase significantly in low-temperature environments and high-discharge rates and continue to rise during the discharge process. Additionally, ohmic heat generation and polarization generation also increase significantly under these conditions. Reversible entropy heat is less sensitive to ambient temperature but increases significantly with the increase of the discharge rate. Ohmic heat generation and polarization heat generation contribute to the total heat generation of the battery at any ambient temperature, while reversible entropy heat only contributes to the total heat generation of the battery at the end of discharge.

Thermally-assisted-occupation density functional theory (TAO-DFT) has been an efficient electronic structure method for studying the ground-state properties of large electronic systems with multi-reference character over the past few years. To explore the time-dependent (TD) properties of electronic systems (e.g., subject to an intense laser pulse), in this work, we propose a real-time (RT) extension of TAO-DFT, denoted as RT-TAO-DFT. Besides, we employ RT-TAO-DFT to study the high-order harmonic generation (HHG) spectra and related TD properties of molecular hydrogen H2 at the equilibrium and stretched geometries, aligned along the polarization of an intense linearly polarized laser pulse. The TD properties obtained with RT-TAO-DFT are compared with those obtained with the widely used time-dependent Kohn-Sham (TDKS) method. In addition, issues related to the possible spin-symmetry breaking effects in the TD properties are discussed.

Upper mesophilic temperature acclimation of halophilic, hydrogen-producing bacteria from salt fields was investigated in this study, along with the changes in microbial abundance during an-aerobic digestion (AD) process. Genomic approaches such as PCR-denaturing gradient gel elec-trophoresis (DGGE) and next-generation sequencing (NGS) were performed to profile the mi-crobial communities. During AD, there was a significant abundance of Halanaerobacter lacunarum at 48°C followed by the increase in hydrogen yield, signifying potential contribution from the halophile in the hydrogen production. A decrease in the dominance of H. lacunarum and Halan-aerobium fermentans at 42°C, likely due to an increase in other bacterial species, was noted but their dominance significantly increased at temperatures of 45°C and 48°C. This investigation provides valuable insights in highlighting the potential of Halanaerobium sp. and the other halo-philic bacteria to adapt under upper mesophilic temperature conditions and synthesizing hy-drogen. The findings in the present study also underscore the importance of optimizing temper-ature and pH conditions to maximize hydrogen yield during high-salt anaerobic digestion.

Generative artificial intelligence (AI), in particular large language models such as ChatGPT have reached public consciousness with a wide-ranging discussion of their capabilities and suitability for various professions. Following the printing press and internet, generative AI language models are the third transformative technological invention with truly cross-sectoral impact on knowledge transmission. While the printing press allowed for the transmission of knowledge that is independent of the physical presence of the knowledge holder with publishers acting as gatekeepers, the internet added levels of democratization allowing anyone to publish, along with global immediacy. The development of social media resulted in an increased fragmentation and tribalization of on-line communities on their ways of knowing, resulting in alternative truths propagated in echo chambers. It is against this background that generative AI language models have entered public consciousness. Using strategic foresight methodology, this paper will examine the polemic proposition that the age of generative AI will emerge as an age of public ignorance.

We present results of the detected voltage distribution of a quantum random number generator based on the photonic integration of semiconductor laser, delay interferometer and photodetector. We find that the integrated system behaves as expected for random number generation from gain-switched laser sources. The biggest advantage is that only electrical connections are needed to operate the system without the need for tricky and expensive optical alignment to external circuitry. We supply results showing that random bit stream created from the random numbers passes the NISTS statistical test suite tests; thus demonstrating the feasibility to generate random number via quantum means at gigabit/s rates from a single photonic integrated circuit. The results are backed by numerical simulations.

One of the rapidly developing research areas in the power system is the integration of distributed generation (DG) with the distribution system. The size and location of DG sources had a considerable impact on power system networks. Artificial intelligence (AI) techniques can be used to address multidimensional problems relating to DG size and location in distribution systems. Heuristic optimization offers a reliable and effective method for solving complicated real-world problems. This work focuses on a hybrid approach that combines the two heuristic optimization methods i.e., Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) for the optimal siting and sizing of DG in distribution systems. This hybrid approach combines ideas from GA and PSO and generates individuals in a new generation using both PSO mechanisms and the procedures found in GA. An extensive performance analysis of the IEEE 14 busbar standard test system is conducted to demonstrate the viability of the suggested methodologies. In the designated locations, DG is placed, and the outcomes have been verified. The results indicated that the right placement of DG injection enhances the voltage profile and lowers the distributed system’s power losses. These techniques offer unique methods for determining the location of the DG unit, demonstrating the potential of such a computational techniques to reduce computing time and complexity while simultaneously reducing human errors associated with hit-and-trail methods.

In recent years, frequent occurrences of low temperature disasters due to global climate change have significantly impacted the normal growth of crops. Research has indicated that inorganic selenium (which is more toxic) can not only enhance the effects of low temperature stress but also increase selenium content on plants; however, there is a scarcity of studies investigating the impacts of organic selenium and nano-selenium on crops. In order to investigate whether organic selenium and nano-selenium can enhance low-temperature tolerance and increase selenium content in pak choi (Brassica chinensis var. pekinensis. cv. ‘Suzhouqing’), different concentrations (0, 5, 10, 20 mg L-1) of exogenous selenium were applied in this experiment to assess their effects on plant growth, nutritional quality and antioxidant properties. RNA-Seq technology was used to sequence the transcriptome of the leaves. Based on the transcriptome data, a Weighted Gene Co-expression Network Analysis (WGCNA) was employed to construct a network that associates with physiological traits related to stress resistance. Two highly correlated gene co-expression modules were identified, and within them, nine hub genes associated with endocytosis, antioxidant stress, absorption, transport, and metabolism of selenium were discovered. The results indicated that the beneficial effects on yield and total selenium content under low temperature were attributed to (1) protection of photosynthetic pigments for enhancing photosynthetic capacity by the up-regulation of LHca2, LHcb1, LHca1, LHcb4 in KEGG pathway: photosynthesis-antenna proteins; (2) activation of antioxidant system for efficient ROS homeostasis such as SOD, POD and CAT by the genes such as Superoxide dismutase, Monodehydroascorbate and (3) selenium absorption by endocytosis, seleninum transportation by ABC transporter gene family and selenium metabolism related genes such as Cysteine synthase, Glutaredoxin. These findings provide a foundation for further investigation into the molecular mechanisms underlying the effects of organic selenium and nano-selenium on cyanochloride production at low temperatures.

Collaborative robots have experienced low acceptance in applications, especially in industry. 1 This fact has attracted the attention of researchers and practitioners, who point to different causes 2 for this low acceptance. One of the main reasons is the difficulty in converging on suitable methods 3 for modeling collaborative interactions between robots and their surrounding context during the 4 requirements phase. These interactions must be elicited and modeled during requirements modeling 5 to maximize value creation through collaboration and must be formally verified, taking into account 6 the risks of human-robot interaction. However, such modeling is often not present in collaborative 7 robot design, and the choice of an appropriate approach remains an open problem. In this paper, 8 this problem is addressed from a requirements engineering perspective, a goal-oriented model and 9 a service-based approach supported by an additional verification method based on Petri nets is 10 proposed. A case study based on collaborative robots used in a hospital environment is presented.

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.

Combining wind and solar photovoltaic (PV) generation can provide complementary renewable power production, but depends on correlated resources. This study analyzed 10 years of wind data from Naama, Algeria to evaluate the potential for evening wind generation to offset the loss of solar at sunset. Average wind speeds showed a distinct increase during evening hours, coinciding with the decrease in solar irradiance. Wind turbine simulations using a 1.5 MW turbine and the wind data showed sufficient resources for profitable power production after sunset. Statistical analyses confirmed significantly higher wind speeds and simulated power output in evening vs daylight periods (p&lt;0.05). The Pearson correlation coefficient between evening wind speeds and decreasing solar irradiance was 0.63, supporting a strong positive relationship. These findings indicate Naama has adequate wind resources to deploy economically viable wind power capacity that can complement existing solar infrastructure and provide renewable electricity after dark , .

The effective treatment of human immunodeficiency virus (HIV), also known as acquired immunodeficiency syndrome (AIDS), has transformed a highly lethal disease into a chronic and manageable condition. However, better methods need to be developed for eliminating the virus from reservoirs, enhancing patient access and adherence to therapy, and improving treatment in the long term to reduce adverse effects. From the perspective of drug discovery, one promising strategy is the development of anti-HIV prodrugs. This approach aims to enhance the efficacy and safety of treatment, promoting the development of more appropriate and convenient systems for patients. In this review, we discussed the use of the prodrug approach for HIV antiviral agents and emphasized nucleoside reverse transcriptase inhibitors. We comprehensively described various strategies that are used to enhance factors such as water solubility, bioavailability, pharmacokinetic parameters, permeability across biological membranes, chemical stability, drug delivery to specific sites/organs, and tolerability. These strategies might help researchers conduct better studies in this field. We also reported successful examples from the primary therapeutic classes while discussing the advantages and limitations. In this review, we highlighted the key trends in the application of the prodrug approach for treating HIV/AIDS..

Disorder of S-adenosylhomocysteine hydrolase (AHCY) activity leads to the potentially lethal rare disease AHCY deficiency, first described in 2004 by Baric and co-workers [1]. In order to shed new light on molecular aspects of the disease, in particular changes at transcriptome level, we enabled knock-down of AHCY expression in model systems such as the colon cancer cell line SW480 to simulate the environment occurring in AHCY deficiency patients. Further, we per-formed deep sequencing of mRNA, followed by differential expression and molecular pathway analysis. Fifteen differentially expressed networks were identified, and interestingly, we found a predicted effect of AHCY down-regulation on the expression of the Lymphoidphoid enhanc-er-binding factor 1 (LEF1) gene, indicating changes in the TCF4/LEF1 complex. LEF1, a member of the T-cell Factor (TCF)/LEF1 family of high-mobility group transcription factors, is a down-stream mediator of the Wnt/β-catenin signaling pathway [2]. LEF1 is essential in stem cell maintenance, and especially in its role in epithelial-mesenchymal transition (EMT). Western blot analysis of LEF1 protein expression confirmed our transcriptomic data predictions and revealed significantly increased LEF1 protein in AHCY- deficient cells, providing a novel link between AHCY and cancer cell phenotype.

this paper we present approaches for generating random numbers along with potential applications. Rather than trying to provide extensive coverage of several techniques or algorithms that have appeared in the scientific literature, we focus on some representative approaches presenting their workings and properties in detail. Our goal is to delineate their strengths and weaknesses as well as their potential application domains so as the reader can judge what would be the best approach for the application in hand, possibly a combination of the available approaches. For instance, a physical source of randomness can be used for the initial seed, then suitable preprocessing can enhance its randomness and then the output of the preprocessing can feed different types of generators, e.g. a linear congruential generator, a cryptographically secure one and one based on the combination of one way hash functions and shared key cryptoalgorithms in various modes of operation. Then, if desired, the outputs of the different generators can be combined giving the final random sequence. Moreover, we present a set of practical randomness tests which can be applied on the outputs of random number generators in order to assess their randomness characteristics. In order to demonstrate the importance of unpredictable random sequences, we present an application of cryptographically secure generators in domains where unpredictability is one of the major requirements, i.e. eLotteries and cryptographic key generation.

K-Rb-83Kr based atomic co-magnetometer for measuring moving MEGs is theoretically studied in this paper. Parameters such as the spin exchange rates, the spin dephasing rates and the polarization of the nuclear spins are studied to configure the co-magnetometer. Results show that the nuclear spin could generate around 700 nT magnetic field under which the nuclear spin could compensate wide range of magnetic fields. We also showed the hybrid optical pumping vapor cell fabrication process in this paper. Alkali metals were mixed in a glove box and then was connected to the alkali vapor cell fabrication system. The vapor cell fabrication process is illustrated in this paper.

A comparative study of the physicochemical properties of natural bentonite clays of Pogodayevо (Republic of Kazakhstan, mod.1) and Dash-Salakhli (Republic of Azerbaijan, mod.2) deposits and modification of the bentonite clay with polyhydroxocations of iron (III) and aluminium (III). It-wasestablished that the modification of natural bentonitesusing polyhydroxocations of iron (III) and aluminium(III) by the method of "co-precipitation" leads to a change in their chemical composition, structural and sorption properties. The results showed that hydroxy-aluminum cations ([Al3O4(OH)24(H2O)12]7+) and poly-hydroxyl-Fe or polyoxo-Fe were intercalated into clay layers, which led to an increase in the values of d001 and specific surface areas compared to those of the original bentonite, from 37 to 120 for the Pogodaevo bentonite and from 51 to 172 respectively for bentonite from the Dash-Salakhli deposit. It is shown that modified sorbents based on natural bentonite are finely porous objects with a predominance of pores of 1.5−6.0 nm in size. As a result, there is a significant increase in the specific surface area of sorbents. Modification of bentonite with polyhydroxocations of iron (III) and aluminium (III) by the "co-precipitation" method also leads to an increase in the sorption capacity of the sorbents obtained with respect to nickel (II) cations. Modified bentonites were used for the adsorption of Ni (II) ions from the model solution. Ni (II) was absorbed in a neutral pH solution. The study of equilibrium adsorption showed that the data are in good agreement with the Langmuir isotherm model. The maximum adsorption capacity of the Ni (II) monolayer obtained from the Langmuir equation was 25.0 mg/g (mod. 1_Al_5-c), 18.2 mg/g (mod. 2_Al_5-c) for Al-bentonite and 16.7 mg/g (mod. 1_Fe_5-c), 10.1 (mod. 2_Fe_5-c) for Fe-bentonite. The kinetics of adsorption is considered. The high content of Al-OH anion exchange centresin them determines the higher sorption activity of Al-modified bentonites.

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.

This study explores the potential of data science software solutions like Customer Relationship Management Software (CRM) for increasing the revenue generation of businesses. We focused on those businesses in Accommodation and Food Service sector across the European Union (EU). The investigation is contextualized within the rising trend of data-driven decision making, examining the potential correlation between data science application and business revenue. Employing a comprehensive evaluation of Eurostat datasets from 2014 to 2021, we used both univariate and multivariate analyses, we assessed e-commerce sales data across countries, focusing on the usage of big data and CRM tools. Big data utilization showed a clear, positive relationship with enhanced e-commerce sales. However, CRM tools exhibited a dualistic impact: while their use in marketing showed no significant effect on sales, their application in non-marketing functions had a negative correlation. These findings underscore the potential role of CRM and data science solutions in enhancing business performance in the EU's Accommodation and Food Service industry.

The possibility of deep radiochemical purification of Li2CO3 has been examined in the frame of the purification program of AMoRE collaboration. In this experiment, commercial Li2CO3 was converted into LiNO3. Co-precipitation with inorganic salt-based carriers followed by membrane filtration and sorption using MDM inorganic sorbent methods were tested for the removal of alkaline-earth and transition metals, potassium, magnesium, aluminum, uranium, thorium, and radium. The calcium molybdate-based carrier was the most efficient for removing Th, U, and K. Subsequently, the radium, calcium, and barium contaminations were removed with MDM sorbent. After the impurities’ removal, the final Li2CO3 product was synthesized with NH4HCO3 sludge. The separation factors were derived by means of ICP-MS and HPGe analyses of the initial material, intermediate and final products. The study showed the optimum conditions of co-precipitation and sorption to reach a high yield and radiopurity of lithium carbonate used for low radioactive background experiments.

The inaugural AIDS Program in Brazil was established in São Paulo in 1983, with the Instituto Adolfo Lutz appointed for laboratory assistance. Subsequently, research on HIV infections and HIV/HTLV (HIV/HTLV-1 and HIV/HTLV-2) co-infections were conducted. This narrative review focuses on studies from the Immunology Department (1983–2017) that significantly influenced AIDS diagnosis or provided epidemiological data such as prevalence rates, sex, age, and risk factors. Ten studies, encompassing over 8,000 individuals, are discussed. During 1983–1985, nearly all AIDS cases were attributed to homosexual/bisexual men aged 31 years old. Subsequently, heterosexual men and women emerged as risk groups owing to intravenous drug use (IDU) and/or unprotected sexual intercourse with AIDS patients or multiple partners per year. From 1985 onwards, vertical transmission led to child infections. HIV/HTLV co-infection rates decreased over time, initially associated with male IDU, and in the 2010s, with females, IDU, and individuals aged &gt;40 years. Trends in HIV and HIV/HTLV co-infections among younger men and women (&lt;30 years of age) were observed from 2015–2017. The changing characteristics and risk groups for HIV and HIV/HTLV co-infections over the years underscore the necessity for ongoing public policies to prevent retrovirus transmission, particularly among adolescents and young adults.

Homologous recombination deficiency (HRD) has become an important prognostic and predictive biomarker for patients with high-grade serous ovarian cancer who may benefit from poly-ADP ribose polymerase inhibitors (PARPi) and platinum-based therapies. HRD testing provides relevant information to personalize patients’ treatment options, and it has been progressively incorporated in diagnostic laboratories. In this study, we evaluated the feasibility of in-house HRD testing deployable in a diagnostic clinical setting, comparing results from two commercially available next-generation sequencing (NGS)-based tumor tests (SOPHiA DDMTM HRD Solution and AmoyDx HRD Focus Panel) with the reference assay from Myriad MyChoice CDx. A total of 85 ovarian cancer samples were subjected to HRD testing. An overall strong correlation was observed across the three assays evaluated, regardless of the different underlying methods employed to assess genomic instability, with the highest pairwise correlation between Myriad and SOPHiA (R=0.87, p-value=3.39x10-19). The comparison of the assigned HRD status to the reference Myriad’s test revealed a positive predictive value (PPV) and negative predictive value (NPV) of 90.9% and 96.3% for SOPHiA’s test, while AmoyDx’s test achieved 75% PPV and 100% NPV. This is the largest HRD testing evaluation using different methodologies and provides a clear picture of the robustness of NGS-based tests currently offered in the market. Our data show that the implementation of in-house HRD testing in diagnostic laboratories is technically feasible and it can be reliably performed with commercial assays. Also, the turnaround time is compatible with clinical needs, being an ideal alternative to offer to a broader number of patients, while still maintaining high-quality standards at more accessible price tiers.

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.

The introduction of digitization has changed all spheres of business on a global level, including geospatial data. In the Republic of Serbia, the process on this topic should begin with the introduction of the terms ePlan and eSpace. The general goal of the paper implies the construction and implementation of the ePlan as a future part of the eSpace for digital management of geospatial data, by creating co-creating value. For this purpose, the authors conducted research in which representatives of local self-governments and holders of public authority participated, by means of structured online research. The focus was on the digitization of urban and planning documents and the establishment a central database of spatial and planning documents in electronic format, and its further distribution through the one system. In that way, easy access to digital plan data expands the user community, and enables communication with different stakeholder groups. Ac-cording to the results of the research, the authors point out that it is necessary to form a new model for managing geospatial data through a eSpace system. This is achieved by shifting the focus from urban and spatial planning to other databases and their registers that are related to geospatial data. The goal of the paper indicates that it is necessary to raise the awareness of society, to introduce the concept of value co-creation, because conditions are created for the implementation of all measures aimed at digitization and management of electronic services in sustainable project society, at all countries.

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 2022-2023 influenza season in Romania was characterized by high pediatric hospitalization rates, predominated by influenza A subtypes H1N1 and H3N2. Lowered population immunity to influenza after the SARS-CoV-2 pandemic and subsequent stoppage of influenza circulation, particularly in children who had limited pre-pandemic exposures, influenced hospitalization among children immunosuppressed, and patients with concurrent medical conditions who are at increased risk for developing severe forms of influenza. This study focused on the characteristics of influenza issues among paediatric patients, as well as the relationship between different influenza virus types and viral and bacterial coinfections and illness severity in the 2022-2023 season after the SARS-CoV-2 pandemic. We conducted a retrospective clinical analysis on 301 cases of influenza in pediatric inpatients (age ≤ 18 years), hospitalized at the National Institute of Infectious Diseases "Prof. Dr. Matei Balș" IX Pediatric Infectious Diseases Clinical Section between October 2022 and February 2023. The most significant age group was 57.8% representing children between one to four years old and female. The average clinical forms were found in 61.7%, whereas severe versions represented 18.2% of cases. Most of the complications were respiratory (acute interstitial pneumonia, 76.1%), hematological (72.1%), represented by intra-infectious and deficiency anemia, leukopenia, thrombocytopenia), 33.6% were digestive, such as diarrheal disease, liver cytolysis syndrome, and the acute dehydration syndrome associated with electrolyte imbalance (71.4%). Severe complications were associated with a risk of unfavorable evolution: acute respiratory failure and neurological complications (convulsions, encephalitis). No deaths were reported. We noticed that the flu season 2022-2023 was characterized by the association of co-infections (viral, bacterial, fungal and parasitic) more frequent than in previous years (26.2% vs. 16%), which evolved more severely, with prolonged hospitalization and more complications (p<0.05), and time of use of oxygen therapy was statistically significant (p > 0.05); influenza vaccination in this group was zero. In conclusion, coinfections with respiratory viruses increase the severity of the pediatric population's immunity to influenza, especially among young children who are more vulnerable to developing a serious illness. All people above the age of six months should get vaccinated against influenza to prevent the illness and its severe complications.

Background: Identifying genetic mutations that lead to spermatogenic impairment is essential for offering patients informed genetic counseling and preventing the transmission of genetic defects to their offspring, often through the use of advanced reproductive technologies. Objectives: The purpose of this study was to identify potential single nucleotide polymorphisms (SNPs) associated with male infertility. Methods and Materials: Genetic variants that may cause infertility are identified by combining targeted next generation sequencing (NGS) panel and whole exome sequencing (WES). The validation step of Sanger sequencing adds confidence to the identified variants. Results: Our analysis revealed five distinct affected genes covering seven SNPs: based on targeted NGS panel and WES data, namely SPATA16 (rs16846616, 1515442, 1515441), CFTR (rs213950), KIF6 (rs2273063), STPG2 (r2903150) and DRC7 (rs3809611). Infertile men have a higher mutation rate than fertile men, especially those with azoospermia. Discussion and Conclusions: These findings strongly support the hypothesis that dysfunction of microtubule-related and spermatogenesis-specific genes contributes to idiopathic male infertility. The SPATA16, CFTR, KIF6, STPG2 and DRC7 mutations are associated with male infertility, specifically azoospermia, further examination of this genetic function is required.

Primary central nervous system and brain tumors are one of the global burdens that are continuously increasing in cases and requiring more treatment options. Surgery has been the leading treatment option for tumors, however, the localization of the tumor and its infiltrating nature make this option challenging. DNA microarray expression profiles of different CNS tumors provide insight into potential biomarkers for identifying different tumor types and subtypes. Here, we utilized the differentially expressed genes common in four expression profiles, GSE66354, GSE68848, GSE74195, and GSE43290 to reconstruct the gene co-expression network. In this study, we were able to identify preserved cluster genes, hub genes, co-regulating transcription factors, miRNA families, and candidate repurposed drugs. Fourteen identified hub genes, which were, CACNA1A, DNM1, GABRA1, GRIA2, MAPT, SLC17A7, SNAP25, SNAP91, STXBP1, SYT1, COL1A1, COL6A2, FBN2, and FN1 appeared to play a role in tumor progression and may serve as drug targets. We also reported the DEGs in each tumor type, which were ATRT, EPN, PA, MED, PNET, MEN, ACM, ODG, and GBM. Five identified miRNA families, which were, let-7 family, mir-124 family, mir-1 family, mir-103 family, and mir-27 family described in the literature to have tumor-suppressing characteristics. Drug-gene and drug-transcription factor network revealed 32 candidate repurposed drugs and 13 were validated through connectivity map analysis. Here, two main repurposed drugs fit the regulatory requirement for gene interaction, these were, quercetin and vorinostat. Future validation in experimental studies may utilize the future use of the candidate repurposed drugs. Our study provides insights into drug repurposing prospects and understanding tumor expressions.

University-Business partnership for collaborative curriculum design, development and delivery is possibly the less explored dimension of University Business Collaboration (UBC). Even if some models for curricular design and development might be available, scarce information exists on how the partnership is constructed, the new curricula are designed, developed and how they are implemented. This article intends to present and discuss the experience obtained during a three-year European funded Project, namely Think4Jobs. This project exemplifies the significance and benefits of UBC in the design, development and delivery of curricula that meet the evolving demands of the labour market while promoting Critical Thinking (CT) as a foundational 21st century skill to contribute to graduates' employability. Think4Jobs project brought together a multidisciplinary team of researchers and business organisations from five European countries (Germany, Greece, Lithuania, Portugal and Romania) with interests in promoting and developing CT and mitigating eventual competence gaps. The project's success was attributed to key practices, including defining a common conceptualization of CT, employing participatory co-design, and providing common training for university and business partners. Clear objectives, explicit roles, effective communication, and ongoing evaluation further enhanced the collaboration. Experiential learning, real-work problems, and case studies reinforced the curricula, bridging the gap between academia and the labour market. By embracing these insights, future UBC initiatives can empower graduates with the necessary skills to stand out in an ever-changing labour market, contributing to enhanced education and successful careers.

This paper presents a design and performance analysis of a 10-element 5G massive MIMO antenna array for sub-6GHz mobile handsets, specifically for LTE bands 42 (3400-3600 MHz), 43 (3600-3800 MHz), 48/49 (3550-3700 MHz) applications. The proposed antenna array consists of 10 closely spaced linearly polarized inverted-F antennas with a compact size of 20 × 9 mm2 of a single element. The proposed antenna array provides high gain, high efficiency, and low correlation between the antenna elements, which results in improved channel capacity, increased data rate, and enhanced signal quality. The performance of the antenna array is evaluated in terms of the radiation pattern, gain, efficiency, and correlation coefficient. The simulation and measured results show that the proposed antenna array achieves an approximate peak gain of 3.1 dBi at the resonance frequency, a total efficiency of 65 %, and a low correlation coefficient of 0.06 between the antenna elements. Therefore, the proposed 5G massive MIMO antenna array is a promising candidate for sub-6 GHz mobile handsets, particularly for LTE bands 42/43/48/49 applications.

In the present study, we implemented species distribution models (SDMs) to determine the potential invasive distribution range of a cichlid fish, Nile tilapia, Oreochromis niloticus, in a very sensitive inland water system in the southeastern Arabian Peninsula where it is now established and spreading. By using the “Biomod2” package, and the latest CMIP6 climate data, four single species distribution models and EM were built, and the results were evaluated by operating characteristic (ROC) and the true skill statistic (TSS). Based on the relative importance of climate factor analysis the mean diurnal range and precipitation seasonality were useful predictors of habitat suitability for O. niloticus. The response curve analysis indicated that the presence probability of O. niloticus decreased with increasing mean diurnal range and decreasing precipitation seasonality. The suitable distribution ranges for O. niloticus in the studied area were mainly distributed in the northeast of this region. The ensemble model results specified a significant impact of climate change on O. niloticus distribution, so highly suitable areas for this species will be reduced, while areas with low to moderate suitability increase slightly or remain unchanged. Based on the available data, Nile tilapia fulfills all four criteria to be considered as an invasive species: colonization in a new area, direct or indirect impacts of anthropological activity on its distribution range, geographical discontinuity between its native area (Africa) and the Arabian Peninsula (remote dispersal), and finally, its successful breeding in situ without human assistance resulting establishment of this biopollutant. Species distribution modeling provides insights into the factors that can reduce the risks and negative impacts of this biological pollutant on aquatic ecosystems of the southeastern Arabian Peninsula which harbors about 22 recognized fish species in 16 genera, 10 families, seven orders, and a class including 20 natives (seven endemic) species.