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Cultural industries constitute a crucial part of the sustainable economy. In accordance with the principles of socialist public ownership nations, the economic benefits of cultural industries should be ultimately transformed into more significant social benefits. Guided by the policies and requirements of the
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Cultural industries constitute a crucial part of the sustainable economy. In accordance with the principles of socialist public ownership nations, the economic benefits of cultural industries should be ultimately transformed into more significant social benefits. Guided by the policies and requirements of the Chinese government concerning the social benefits of cultural industries, this paper innovatively integrates Data Envelopment Analysis (DEA) and Tobit models to empirically analyze the social benefits and their influencing factors within China’s cultural industries. The findings indicate that the social benefits of China’s cultural industries are currently in a state of diminishing returns to scale, with fiscal support and educational levels significantly enhancing the industry’s social benefits. This paper recommends that policymakers aiming to convert the economic benefits of cultural industries into social benefits more systematically and effectively should focus on enhancing the quality of industry outputs.
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To achieve sustainable development goals and meet the demand for clean and efficient energy utilization, it is imperative to advance the penetration of renewable energy in various sectors. Energy storage systems can mitigate the intermittent issues of renewable energy and enhance the efficiency
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To achieve sustainable development goals and meet the demand for clean and efficient energy utilization, it is imperative to advance the penetration of renewable energy in various sectors. Energy storage systems can mitigate the intermittent issues of renewable energy and enhance the efficiency and economic viability of existing energy facilities. Among various energy storage technologies, thermocline heat storage (THS) has garnered widespread attention from researchers due to its stability and economic advantages. Currently, there are only a few review articles focusing on THS, and there is a gap in the literature regarding the optimization design of THS systems. Therefore, this paper provides a comprehensive review of the recent research progress in THS, elucidating its principles, thermal storage materials, applications, and optimization designs. The novelty of this work lies in the detailed classification and analysis of various optimization designs for THS, including tank shape, aspect ratio, inlet/outlet configuration, thermal energy storage materials arrangement, operating strategies, and numerical model optimization approaches. The limitations of existing research are also identified, and future perspectives are proposed, aiming to provide recommendations for THS research and contribute to the development and promotion of THS technology.
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Lattice structures have become an innovative solution for the improvement of part design, as they are able to substitute solid regions, maintain mechanical capabilities, and reduce material usage; however, dimensional quality control of these geometries is challenging. X-ray computed tomography (XCT) is the
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Lattice structures have become an innovative solution for the improvement of part design, as they are able to substitute solid regions, maintain mechanical capabilities, and reduce material usage; however, dimensional quality control of these geometries is challenging. X-ray computed tomography (XCT) is the most suitable non-destructive metrological technique as it is capable of characterizing internal features and hidden elements. Uncertainty estimation of XCT is still in development, and studies typically use high-resolution calibrated devices such as focal variation microscopes (FVMs) as a reference, focusing on certain parts of the lattice but not the whole structure. In this paper, an estimation of the accuracy of XCT evaluation of a complete lattice structure in comparison to a higher-resolution reference device (FVM) is presented. Experimental measurements are taken on ad hoc designed test objects manufactured in polyamide 12 (PA12) using selective laser sintering (SLS), optimized for the evaluation on both instruments using different cubic-based lattice typologies. The results confirm higher precision on XCT evaluation in both qualitative and quantitative analysis. Even with a lower resolution, XCT is able to characterize details of the surface such as re-entrant features; as well, standard deviations and uncertainties in strut diameter evaluation remain more stable in all cells in XCT, identifying on the other hand reconstruction problems on FVM measurements. Moreover, it is shown that, using XCT, no additional evaluation errors were found in inner cells, suggesting that the measurement of external elements could be representative of the whole structure for metrological purposes.
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Effective emission control technologies and eco-friendly propulsion systems have been developed to decrease exhaust particle emissions. However, more work must be conducted on non-exhaust traffic-related sources such as tyre wear. The advent of automated vehicles (AVs) enables researchers and automotive manufacturers to consider
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Effective emission control technologies and eco-friendly propulsion systems have been developed to decrease exhaust particle emissions. However, more work must be conducted on non-exhaust traffic-related sources such as tyre wear. The advent of automated vehicles (AVs) enables researchers and automotive manufacturers to consider ways to further decrease tyre wear, as vehicles will be controlled by the system rather than by the driver. In this direction, this work presents the formulation of an optimal control problem for the trajectory optimisation of automated articulated vehicles for tyre wear minimisation. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one to minimise tyre wear in fixed time cases. Specific boundaries and constraints are applied to the problem to ensure the vehicle’s stability and the feasibility of the solution. According to the results, a small increase in the journey time leads to a significant decrease in the mass loss due to tyre wear. The employment of articulated vehicles with low powertrain capabilities leads to greater tyre wear, while excessive increases in powertrain capabilities are not required. The conclusions pave the way for AV researchers and manufacturers to consider tyre wear in their control modules and come closer to the zero-emission goal.
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The accurate prediction of heavy precipitation in convective environments is crucial because such events, often occurring in Italy during the summer and fall seasons, can be a threat for people and properties. In this paper, we analyse the impact of satellite-derived surface-rainfall-rate data
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The accurate prediction of heavy precipitation in convective environments is crucial because such events, often occurring in Italy during the summer and fall seasons, can be a threat for people and properties. In this paper, we analyse the impact of satellite-derived surface-rainfall-rate data assimilation on the Weather Research and Forecasting (WRF) model’s precipitation prediction, considering 15 days in summer 2022 and 17 days in fall 2022, where moderate to intense precipitation was observed over Italy. A 3DVar realised at CNR-ISAC (National Research Council of Italy, Institute of Atmospheric Sciences and Climate) is used to assimilate two different satellite-derived rain rate products, both exploiting geostationary (GEO), infrared (IR), and low-Earth-orbit (LEO) microwave (MW) measurements: One is based on an artificial neural network (NN), and the other one is the operational P-IN-SEVIRI-PMW product (H60), delivered in near-real time by the EUMETSAT HSAF (Satellite Application Facility in Support of Operational Hydrology and Water Management). The forecast is verified in two periods: the hours from 1 to 4 (1–4 h phase) and the hours from 3 to 6 (3–6 h phase) after the assimilation. The results show that the rain rate assimilation improves the precipitation forecast in both seasons and for both forecast phases, even if the improvement in the 3–6 h phase is found mainly in summer. The assimilation of H60 produces a high number of false alarms, which has a negative impact on the forecast, especially for intense events (30 mm/3 h). The assimilation of the NN rain rate gives more balanced predictions, improving the control forecast without significantly increasing false alarms.
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A bacterium was isolated and identified from the secretion of a rhesus monkey with endometritis. The morphological results showed that the strain exhibited round, convex, gray-white colonies with smooth surfaces and diameters ranging from 1 to 2 mm when cultured on Columbia blood
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A bacterium was isolated and identified from the secretion of a rhesus monkey with endometritis. The morphological results showed that the strain exhibited round, convex, gray-white colonies with smooth surfaces and diameters ranging from 1 to 2 mm when cultured on Columbia blood agar at 37 °C for 24 h; on salmonella–shigella agar (S.S.) at 37 °C for 24 h, the colonies appeared round, flat, and translucent. Gram staining showed negative results with blunt ends and non-spore-forming characteristics. Molecular biology results showed that the 16S rRNA sequence of the strain revealed over 96.9% similarity with published sequences of M. morganii from different sources in the NCBI GenBank database. Morphological and molecular biology analysis confirmed that the strain (RM2023) isolated from cervical secretions of rhesus monkey was M. morganii. Drug sensitivity testing demonstrated that the isolated strain (RM2023) was sensitive to ceftriaxone, amikacin, gentamicin, cefazolin, cefuroxime, ceftazidime, levofloxacin, cotrimoxazole, norfloxacin, and tetracycline; moderately sensitive to ampicillin; and resistant to penicillin, vancomycin, ciprofloxacin, and clindamycin. The research findings provide valuable insights for disease prevention in rhesus monkeys and contribute to molecular epidemiological studies.
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This research, focusing on the environmental impact of tire and brake disc pad wear, constitutes a significant area of transport-related studies. These two key vehicle components are not only the most frequently worn but also generate micro- and nano-pollutants (i.e., rubber, metal [...] Read more.
This research, focusing on the environmental impact of tire and brake disc pad wear, constitutes a significant area of transport-related studies. These two key vehicle components are not only the most frequently worn but also generate micro- and nano-pollutants (i.e., rubber, metal oxides) that potentially harm the environment. Over half of the globally produced natural and synthetic rubbers, which amounted to about 30 million tons in 2022, are used for tire production. This work focuses on the study of roadside snow, sand, and standing water deposits from various locations in the urban agglomeration (Poznań, Poland) during the winter season, determining their qualitative composition and the quantitative content of pollutants originating from tire abrasion. In addition, the method of washing nano- and micro-rubber particles and their full characteristics was also presented. Fourier-transform infrared (FT-IR) and nuclear magnetic resonance (NMR) spectroscopic studies, optical and scanning electron microscopy (SEM-EDS), particle size studies using a dynamic light scattering (DLS) particle analyzer, and thermogravimetric analysis (TGA) were conducted for a detailed characterization of the pollutants in the environment. The conducted particle separation methods allowed for the extraction of a fraction mainly containing gum residues with particle sizes less than 2 µm. The results of these tests make it possible to estimate the level of contamination with rubber and metal residues during the abrasion of tires, pads, and brake discs while driving, which is crucial for understanding the impact of vehicle part exploitation on the environment.Full article
The potential outcomes framework serves as a fundamental tool for quantifying causal effects. The average dose–response function (also called the effect curve) is typically of interest when dealing with a continuous treatment variable (exposure). The focus of this work
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The potential outcomes framework serves as a fundamental tool for quantifying causal effects. The average dose–response function (also called the effect curve) is typically of interest when dealing with a continuous treatment variable (exposure). The focus of this work is to determine the impact of an extreme level of treatment, potentially beyond the range of observed values—that is, estimating for very large t. Our approach is grounded in the field of statistics known as extreme value theory. We outline key assumptions for the identifiability of the extreme treatment effect. Additionally, we present a novel and consistent estimation procedure that can potentially reduce the dimension of the confounders to at most 3. This is a significant result since typically, the estimation of is very challenging due to high-dimensional confounders. In practical applications, our framework proves valuable when assessing the effects of scenarios such as drug overdoses, extreme river discharges, or extremely high temperatures on a variable of interest.
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by
Muhammad Asif, Hafiz Ahmad Iqrash Qureshi, Saba Mazhar Seyal, Muhammad Aslam, Muhammad Tauseef Sultan, Maysaa Elmahi Abd Elwahab, Piotr Matłosz and Justyna Wyszyńska
J. Clin. Med.2024, 13(10), 2944; https://doi.org/10.3390/jcm13102944 (registering DOI) - 16 May 2024
Obesity is currently considered a public health problem in both developed and developing countries. Gender- and age-specific body mass index (BMI) growth standards or references are particularly effective in monitoring the global obesity pandemic. This study aimed to report disparities in age-, gender-
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Obesity is currently considered a public health problem in both developed and developing countries. Gender- and age-specific body mass index (BMI) growth standards or references are particularly effective in monitoring the global obesity pandemic. This study aimed to report disparities in age-, gender- and ethnic-specific statistical estimates of overweight and obesity for 2–18 years aged Pakistani children and adolescents using the World Health Organization (WHO), the Center for Disease Control (CDC) 2000 references, the International Obesity Task Force (IOTF) and Pakistani references for BMI. Methods: The study used secondary data of 10,668 pediatric population, aged 2–18 years. Demographic information like age (years), gender, city and anthropometric examinations, i.e., height (cm) and weight (kg) were used in this study. The recommended age- and gender-specific BMI cut-offs of the WHO, CDC 2000 and the IOTF references were used to classify the children sampled as overweight and obese. For the Pakistani reference, overweight and obesity were defined as BMI-for-age ≥ 85th percentile and BMI-for-age ≥ 95th percentile, respectively. Cohen’s κ statistic was used to assess the agreement between the international references and local study population references in the classification of overweight/obesity. Results: The statistical estimates (%) of the participants for overweight and obesity varied according to the reference used: WHO (7.4% and 2.2%), CDC (4.9% and 2.1%), IOTF (5.2% and 2.0%) and Pakistan (8.8% and 6.0%), respectively; suggesting higher levels of overweight and obesity prevalence when local study references are used. The Kappa statistic shows a moderate to excellent agreement (κ ≥ 0.6) among three international references when classifying child overweight and obesity and poor agreement between local references and the WHO (0.45, 0.52), CDC (0.25, 0.50) and IOTF references (0.16, 0.31), for overweight and obesity, respectively. Conclusions: The results of the study showed a visible difference in the estimates of excess body weight after applying the WHO, CDC, IOTF and local BMI references to the study population. Based on the disparity results and poor agreement between international references and the local study reference, this study recommends using local BMI references in identifying children with overweight and obesity.
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The escalating demand for enhanced therapeutic efficacy and reduced adverse effects in the pharmaceutical domain has catalyzed a new frontier of innovation and research in the field of pharmacy: novel drug delivery systems. These systems are designed to address the limitations of conventional
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The escalating demand for enhanced therapeutic efficacy and reduced adverse effects in the pharmaceutical domain has catalyzed a new frontier of innovation and research in the field of pharmacy: novel drug delivery systems. These systems are designed to address the limitations of conventional drug administration, such as abbreviated half-life, inadequate targeting, low solubility, and bioavailability. As the disciplines of pharmacy, materials science, and biomedicine continue to advance and converge, the development of efficient and safe drug delivery systems, including biopharmaceutical formulations, has garnered significant attention both domestically and internationally. This article presents an overview of the latest advancements in drug delivery systems, categorized into four primary areas: carrier-based and coupling-based targeted drug delivery systems, intelligent drug delivery systems, and drug delivery devices, based on their main objectives and methodologies. Additionally, it critically analyzes the technological bottlenecks, current research challenges, and future trends in the application of novel drug delivery systems.
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Understanding the nuanced interplay between plant polyphenols and starch could have significant implications. For example, it could lead to the development of tailor-made starches for specific applications, from bakinag and brewing to pharmaceuticals and bioplastics. In addition, this knowledge could contribute to the
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Understanding the nuanced interplay between plant polyphenols and starch could have significant implications. For example, it could lead to the development of tailor-made starches for specific applications, from bakinag and brewing to pharmaceuticals and bioplastics. In addition, this knowledge could contribute to the formulation of functional foods with lower glycemic indexes or improved nutrient delivery. Variations in the complexes can be attributed to differences in molecular weight, structure, and even the content of the polyphenols. In addition, the unique structural characteristics of starches, such as amylose/amylopectin ratio and crystalline density, also contribute to the observed effects. Processing conditions and methods will always alter the formation of complexes. As the type of starch/polyphenol can have a significant impact on the formation of the complex, the selection of suitable botanical sources of starch/polyphenols has become a focus. Spectroscopy coupled with chemometrics is a convenient and accurate method for rapidly identifying starches/polyphenols and screening for the desired botanical source. Understanding these relationships is crucial for optimizing starch-based systems in various applications, from food technology to pharmaceutical formulations.
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Eelgrass meadows have attracted much attention not only for their ability to maintain marine ecosystems as feeding grounds for marine organisms but also for their potential to store atmospheric and dissolved CO2 as blue carbon. This study comprehensively evaluated the bacterial and
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Eelgrass meadows have attracted much attention not only for their ability to maintain marine ecosystems as feeding grounds for marine organisms but also for their potential to store atmospheric and dissolved CO2 as blue carbon. This study comprehensively evaluated the bacterial and chemical data obtained from eelgrass sediments of different scales along the Japanese coast to investigate the effect on the acclimatization of eelgrass. Regardless of the eelgrass habitat, approximately 1% Anaerolineales, Babeliales, Cytophagales, and Phycisphaerales was present in the bottom sediment. Sulfate-reducing bacteria (SRB) were present at 3.69% in eelgrass sediment compared to 1.70% in bare sediment. Sulfur-oxidizing bacteria (SOB) were present at 2.81% and 1.10% in the eelgrass and bare sediment, respectively. Bacterial composition analysis and linear discriminant analysis revealed that SOB detoxified H2S in the eelgrass meadows and that the larger-scale eelgrass meadows had a higher diversity of SOB. Our result indicated that there were regional differences in the system that detoxifies H2S in eelgrass meadows, either microbial oxidation mediated by SOB or O2 permeation via the physical diffusion of benthos. However, since bacterial flora and phylogenetic analyses cannot show bias and/or causality due to PCR, future kinetic studies on microbial metabolism are expected.
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Urethane acrylate (UA) was synthesized from various di-polyols, such as poly(tetrahydrofuran) (PTMG, Mn = 1000), poly(ethylene glycol) (PEG, Mn = 1000), and poly(propylene glycol) (PPG, Mn = 1000), for use as a polymer binder for paint. Polymethyl methacrylate (PMMA) and UA were blended
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Urethane acrylate (UA) was synthesized from various di-polyols, such as poly(tetrahydrofuran) (PTMG, Mn = 1000), poly(ethylene glycol) (PEG, Mn = 1000), and poly(propylene glycol) (PPG, Mn = 1000), for use as a polymer binder for paint. Polymethyl methacrylate (PMMA) and UA were blended to form an acrylic resin with high transmittance and stress-strain curve. When PMMA was blended with UA, a network structure was formed due to physical entanglement between the two polymers, increasing the mechanical properties. UA was synthesized by forming a prepolymer using di-polyol and hexamethylene diisocyanate, which were chain structure monomers, and capping them with 2-hydroxyethyl methacrylate to provide an acryl group. Fourier transform infrared spectroscopy was used to observe the changes in functional groups, and gel permeation chromatography was used to confirm that the three series showed similar molecular weight and PDI values. The yellowing phenomenon that appears mainly in the curing reaction of the polymer binder was solved, and the mechanical properties according to the effects of the polyol used in the main chain were compared. The content of the blended UA was quantified using ultravioletvisible spectroscopy at a wavelength of 370 nm based on 5, 10, 15, and 20 wt%, and the shear strength and tensile strength were evaluated using specimens in a suitable mode. The ratio for producing the polymer binder was optimized. The mechanical properties of the polymer binder with 5–10 wt% UA were improved in all series.
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Photodynamic therapy (PDT) shows promise in tumor treatment, particularly when combined with nanotechnology. This study examines the impact of deep learning, particularly the Cellpose algorithm, on the comprehension of cancer cell responses to PDT. The Cellpose algorithm enables robust morphological analysis of cancer
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Photodynamic therapy (PDT) shows promise in tumor treatment, particularly when combined with nanotechnology. This study examines the impact of deep learning, particularly the Cellpose algorithm, on the comprehension of cancer cell responses to PDT. The Cellpose algorithm enables robust morphological analysis of cancer cells, while logistic growth modelling predicts cellular behavior post-PDT. Rigorous model validation ensures the accuracy of the findings. Cellpose demonstrates significant morphological changes after PDT, affecting cellular proliferation and survival. The reliability of the findings is confirmed by model validation. This deep learning tool enhances our understanding of cancer cell dynamics after PDT. Advanced analytical techniques, such as morphological analysis and growth modeling, provide insights into the effects of PDT on hepatocellular carcinoma (HCC) cells, which could potentially improve cancer treatment efficacy. In summary, the research examines the role of deep learning in optimizing PDT parameters to personalize oncology treatment and improve efficacy.
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The subcellular location of a protein provides valuable insights to bioinformaticians in terms of drug designs and discovery, genomics, and various other aspects of medical research. Experimental methods for protein subcellular localization determination are time-consuming and expensive, whereas computational methods, if accurate, would
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The subcellular location of a protein provides valuable insights to bioinformaticians in terms of drug designs and discovery, genomics, and various other aspects of medical research. Experimental methods for protein subcellular localization determination are time-consuming and expensive, whereas computational methods, if accurate, would represent a much more efficient alternative. This article introduces an ab initio protein subcellular localization predictor based on an ensemble of Deep N-to-1 Convolutional Neural Networks. Our predictor is trained and tested on strict redundancy-reduced datasets and achieves 63% accuracy for the diverse number of classes. This predictor is a step towards bridging the gap between a protein sequence and the protein’s function. It can potentially provide information about protein–protein interaction to facilitate drug design and processes like vaccine production that are essential to disease prevention.
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The Industrial Metrology Business Unit of Nikon Corporation, on behalf of ScottishPower Renewables and Maritime Archaeology (MA), Southampton, UK, has employed X-ray CT (computed tomography) to visualise the internal structure of an anchor found in the North Sea. The non-destructive method of internal
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The Industrial Metrology Business Unit of Nikon Corporation, on behalf of ScottishPower Renewables and Maritime Archaeology (MA), Southampton, UK, has employed X-ray CT (computed tomography) to visualise the internal structure of an anchor found in the North Sea. The non-destructive method of internal inspection and measurement has helped to determine approximately when it was made. The results indicate that the artefact, initially thought to be potentially Roman, is probably more recent, likely dating to between the late 16th and early 17th centuries CE. This paper presents the discovery, recovery, analysis and interpretation of a significant find from a UK offshore wind farm and underscores the valuable role that non-destructive X-ray CT played in the investigation.
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Macular edema (ME) remains a primary cause of visual deterioration in uveitis. Visual acuity (VA) can often be maintained using corticosteroid depot systems. This study evaluated the efficacy of a fluocinolone acetonide (FAc) intravitreal implant (ILUVIEN®) in treating non-infectious uveitis using
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Macular edema (ME) remains a primary cause of visual deterioration in uveitis. Visual acuity (VA) can often be maintained using corticosteroid depot systems. This study evaluated the efficacy of a fluocinolone acetonide (FAc) intravitreal implant (ILUVIEN®) in treating non-infectious uveitis using real-world data. This retrospective analysis included 135 eyes subdivided into responders and non-responders. Central retinal thickness (CRT), VA, and intraocular pressure (IOP) were followed over time. A significant decrease in CRT and an increase in VA were observed in all eyes throughout the follow-up period (p < 0.01). An IOP increase (p = 0.028) necessitated treatment in 43% of eyes by Month 6. Non-responders were older (p = 0.004) and had been treated with more dexamethasone (DEX) implants (p = 0.04); 89.3% had a defect in the external limiting membrane (ELM) and inner/outer segment (IS/OS) zone (p < 0.001). Immunomodulatory therapy had no impact on treatment response. Pars plana vitrectomy (PPV) patients had a mean CRT reduction of 47.55 µm and a reduced effect by Month 24 (p = 0.046) versus non-PPV patients. We conclude that the FAc implant achieves long-term control of CRT and improves VA. Increases in IOP were manageable. Eyes with a previous PPV showed milder results. Data showed a correlation between older age, a damaged ELM and IS/OS zone, frequent DEX inserts, and poorer outcome measures.
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This review highlights the role of postbiotics, which may provide an underappreciated avenue doe promising therapeutic alternatives. The discovery of natural compounds obtained from microorganisms needs to be investigated in the future in terms of their effects on various metabolic disorders and molecular
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This review highlights the role of postbiotics, which may provide an underappreciated avenue doe promising therapeutic alternatives. The discovery of natural compounds obtained from microorganisms needs to be investigated in the future in terms of their effects on various metabolic disorders and molecular pathways, as well as modulation of the immune system and intestinal microbiota in children and adults. However, further studies and efforts are needed to evaluate and describe new postbiotics. This review provides available knowledge that may assist future research in identifying new postbiotics and uncovering additional mechanisms to combat metabolic diseases.
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Thermal comfort and daylighting are vital components of dormitory environments. However, enhancing indoor lighting conditions may lead to increased annual energy consumption and decreased thermal comfort. Therefore, it is crucial to identify methods to reduce buildings’ energy costs while maintaining occupants’ thermal comfort
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Thermal comfort and daylighting are vital components of dormitory environments. However, enhancing indoor lighting conditions may lead to increased annual energy consumption and decreased thermal comfort. Therefore, it is crucial to identify methods to reduce buildings’ energy costs while maintaining occupants’ thermal comfort and daylighting. Taking the dormitory building of Songyuan No. 2 at Shandong Jianzhu University of Architecture, which is located in a cold region, as an example, a field measurement analysis was conducted on the recessed balconies within the dormitory. The measured data were analyzed and utilized to simulate the annual energy consumption, thermal comfort predicted mean vote (PMV), and useful daylight illuminance (UDI) values of the dormitory units using the Grasshopper platform with the Ladybug and Honeybee plugins. The different depths of the balconies and window-to-wall ratios have a significant impact on the indoor physical environment and energy consumption, leading to the design of independent variables and the construction of a simplified parametric model. The simulation results underwent multi-objective optimization using genetic algorithm theory through the Octopus platform, resulting in a Pareto optimal solution set. Comparisons between the final-generation data and simulations of the original Song II dormitory unit indicate potential energy savings of up to 2.5%, with a 25% improvement in indoor thermal comfort satisfaction. Although there was no significant improvement in the UDI value, all the solution sets meet the minimum requirement of 300 lux specified by relevant regulations, according to the simulated average illuminance levels on the indoor work plane. Finally, the 60 optimal solution sets were further screened, filtering out sets deviating excessively from certain objectives, to identify 6 optimal solutions that are more balanced and exhibit a higher overall optimization rate. These findings offer detailed data references to assist in the design of dormitory buildings in cold regions.
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Breast cancer, when advancing to a metastatic stage, involves the liver, impacting over 50% of cases and significantly diminishing survival rates. Presently, a lack of tailored therapeutic protocols for breast cancer liver metastasis (BCLM) underscores the need for a deeper understanding of molecular
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Breast cancer, when advancing to a metastatic stage, involves the liver, impacting over 50% of cases and significantly diminishing survival rates. Presently, a lack of tailored therapeutic protocols for breast cancer liver metastasis (BCLM) underscores the need for a deeper understanding of molecular patterns governing this complication. Therefore, by analyzing differentially expressed genes (DEGs) between primary breast tumors and BCLM lesions, we aimed to shed light on the diversities of this process. This research investigated breast cancer liver metastasis relapse by employing a comprehensive approach that integrated data filtering, gene ontology and KEGG pathway analysis, overall survival analysis, identification of the alteration in the DEGs, visualization of the protein–protein interaction network, Signor 2.0, identification of positively correlated genes, immune cell infiltration analysis, genetic alternation analysis, copy number variant analysis, gene-to-mRNA interaction, transcription factor analysis, molecular docking, and identification of potential treatment targets. This study’s integrative approach unveiled metabolic reprogramming, suggesting altered PCK1 and LPL expression as key in breast cancer metastasis recurrence.
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Barred galaxies often develop a box/peanut pseudobulge, but they can also host a nearly spherical classical bulge, which is known to gain rotation due to the bar. We aim to explore how the presence of gas impacts the rotation of classical bulges. We
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Barred galaxies often develop a box/peanut pseudobulge, but they can also host a nearly spherical classical bulge, which is known to gain rotation due to the bar. We aim to explore how the presence of gas impacts the rotation of classical bulges. We carried out a comprehensive set of hydrodynamical N-body simulations with different combinations of bulge masses and gas fractions. In these models, both massive bulges and high gas content tend to inhibit the formation of strong bars. For low-mass bulges, the resulting bar is stronger in cases of low gas content. In the stronger bar models, bulges acquire more angular momentum and thus display considerable rotational velocity. Such bulges also develop anisotropic velocity dispersions and become triaxial in shape. We found that the rotation of the bulge becomes less pronounced as the gas fraction is increased from 0 to 30%. These results indicate that the gas content has a significant effect on the dynamics of the classical bulge, because it influences bar strength. Particularly in the case of the low-mass bulges (10% bulge mass fraction), all of the measured rotational and structural properties of the classical bulge depend strongly and systematically on the gas content of the galaxy.
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Neem leaves have long been used in traditional medicine for promoting longevity. However, the precise mechanisms underlying their anti-aging effects remain elusive. In this study, we investigated the impact of neem leaf extract (NLE) extracted from a 50% ethanol solution on the chronological
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Neem leaves have long been used in traditional medicine for promoting longevity. However, the precise mechanisms underlying their anti-aging effects remain elusive. In this study, we investigated the impact of neem leaf extract (NLE) extracted from a 50% ethanol solution on the chronological lifespan of Saccharomyces cerevisiae, revealing an extension in lifespan, heightened oxidative stress resistance, and a reduction in reactive oxygen species. To discern the active compounds in NLE, LC/MS and the GNPS platform were employed. The majority of identified active compounds were found to be flavonoids. Subsequently, compound-target pharmacological networks were constructed using the STP and STITCH platforms for both S. cerevisiae and Homo sapiens. GOMF and KEGG enrichment analyses of the predicted targets revealed that “oxidoreductase activity” was among the top enriched terms in both yeast and human cells. These suggested a potential regulation of oxidative stress response (OSR) by NLE. RNA-seq analysis of NLE-treated yeast corroborated the anti-oxidative effect, with “oxidoreductase activity” and “oxidation-reduction process” ranking high in enriched GO terms. Notably, CTT1, encoding catalase, emerged as the most significantly up-regulated gene within the “oxidoreductase activity” cluster. In a ctt1 null mutant, the enhanced oxidative stress resistance and extended lifespan induced by NLE were nullified. For human cells, NLE pretreatment demonstrated a decrease in reactive oxygen species levels and senescence-associated β-galactosidase activity in HeLa cells, indicative of anti-aging and anti-oxidative effects. This study unveils the anti-aging and anti-oxidative properties of NLE while delving into their mechanisms, providing novel insights for pharmacological interventions in aging using phytochemicals.
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The rapid development of miniaturized, high-frequency, and highly integrated microelectronic devices has brought about critical issues in electromagnetic compatibility and thermal management. In recent years, there has been significant interest in lightweight polymer-based composites that offer both electromagnetic interference (EMI) shielding and thermal
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The rapid development of miniaturized, high-frequency, and highly integrated microelectronic devices has brought about critical issues in electromagnetic compatibility and thermal management. In recent years, there has been significant interest in lightweight polymer-based composites that offer both electromagnetic interference (EMI) shielding and thermal conductivity. One promising approach involves constructing three-dimensional (3D) interconnection networks using functional fillers in the polymer matrix. These networks have been proven effective in enhancing the thermal and electrical conductivity of the composites. This mini-review focuses on the preparation and properties of 3D network-reinforced polymer composites, specifically those incorporating metal, carbon, ceramic, and hybrid networks. By comparing the effects of different filler types and distribution on the composite materials, the advantages of 3D interconnected conductive networks in polymer composites are highlighted. Additionally, this review addresses the challenges faced in the field of multifunctional thermal management and electromagnetic protection materials and provides insights into future development trends and application prospects of 3D structured composites.
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