This paper investigates an Energy Neutral System using Micro Energy Harvesters for a Health Monitoring Wireless Sensor Node (HM-WSN). We have implemented HM-WSN consisting of a solar cell energy harvester, a Power Management Unit (PMU) and the ucontroller, sensor and transmitter acting as load. A battery extender and a switching logic circuit for sensor node is designed to evaluate the efficiency of the proposed system. The HM-WSN senses body temperature with improvement in lifetime of coincell. The HM-WSN is built using commercially available off the shelf (COTS components and consumes 47.2uW for data being updated every 134s. It can be operated for approximately 1.32 years only on a coincell. Furthermore, the HM-WSN can be operated with solar energy at 200lux, achieving 96.36 years with a combination of a coincell with an additional capacitor of 2.2mF. It attains 4.07 years to 16.87 years lifetime with the load capacitor varying from 1mF to 1.5mF at 350lux lighting condition. With the same ambient condition and a 2mF load capacitor, HM-WSN attains complete energy autonomy.

Genetic transformation is a critical tool for gene manipulation and functional analyses in plants, enabling the exploration of key phenotypes and agronomic traits at the genetic level. While dicotyledonous plants offer various tissues for in vitro culture and transformation, monocotyledonous plants, such as rice, have limited options. This study presents an efficient method for genetically transforming rice (Oryza sativa L.) using seed-derived embryogenic calli as explants. Two target genes were utilized to assess regeneration efficiency: green fluorescent protein (eGFP) and the apple FLOWERING LOCUS T (FT)-like gene (MdFT1). Antisense MdFT1 was cloned into a vector controlled by the rice α-amylase 3D (Ramy3D) promoter, while eGFP was fused to Cas9 under the Ubi promoter. These vectors were introduced separately into rice embryogenic calli from two Korean cultivars using Agrobacterium-mediated transformation. Transgenic seedlings were successfully regenerated via hygromycin selection using an in vitro cultivation system. PCR confirmed stable transgene integration in the transgenic calli and their progeny. Fluorescence microscopy revealed eGFP expression, and antisense MdFT1-expressing lines exhibited notable phenotypic changes, including variations in plant height and grain quality. This study demonstrated the effective use of seed-derived embryogenic calli for rice transformation, offering a promising approach for developing transgenic plants in monocot species.

Current agriculture intensifies crop cultivation to meet food demand, leading to unsustainable use of chemical fertilizers. This study investigates a few physiological and agronomic responses of common wheat following the inoculation with plant growth-promoting bacteria to reduce nitrogen inputs. A field trial was conducted in 2022-23, in Legnago (Verona, Italy) on Triticum aestivum var. LG-Auriga comparing full (180 kg ha-1) and reduced (130 kg ha-1) N doses, both with and without foliar application at end tillering of the N-fixing bacterium Methylobacterium symbioticum. Biofertilization did not improve shoot growth, while it seldom increased root length density in the arable layer. It delayed leaf senescence, prolonged photosynthetic activity, amplified stomatal conductance and PSII efficiency under reduced N dose. Appreciable ACC-deaminase activity of such bacterium disclosed augmented nitrogen retrieval and reduced ethylene production, explaining ameliorated stay-green. Yield and testing weight were unaffected by biofertilization, while both glutenin-to-gliadin and HMW-to-LMW ratios increased together with dough tenacity. It is concluded that Methylobacterium symbioticum can amplify nitrogen metabolism at reduced nitrogen dose, offering a viable approach to reduce chemical fertilization under suboptimal growing conditions for achieving a more sustainable agriculture. Further research over multiple growing seasons and soil types is necessary to corroborate these preliminary observations.

In the frame of our diversity-oriented research on multitarget small molecule anticancer agents, utilizing convergent synthetic sequences terminated by Sonogashira coupling reactions, a preliminary selection of representative alkyne-tethered vindoline hybrids was synthesized. The novel hybrids with additional pharmacophoric fragments of well-documented anticancer agents, including FDA-approved tyrosine-kinase inhibitors (imatinib and erlotinib) or ferrocene or chalcone units, were evaluated for their antiproliferative activity on malignant cell lines MDA-MB-231 (triple negative breast cancer), A2780 (ovarian cancer), HeLa (human cervical cancer) and SH-SY5Y (neuroblastoma) as well as human embryonal lung fibroblast MRC-5 served as reference non-malignant cell line for the assessment of the therapeutic window of the tested hybrids. The biological assays identified a trimethoxyphenyl-containing chalcone-vindoline hybrid (36) as a promising lead compound exhibiting submicromolar activity on A2780 cells with a marked therapeutic window. These results suggest that ovarian cancer might be considered as a prioritized target of treatment with 36.

This paper presents the work done to transition the lab scale synthesis (1 g) to a large scale (400 g) synthesis of the 3-5-diamino-1H-Pyrazole Disperazol; a new pharmaceutical for treatment of antibiotic resistant Pseudomonas aeruginosa biofilm infections. The potentially hazardous diazotisation step in the lab scale synthesis was transformed to a safe and easy to handle flow chemistry step. Additionally, the paper presents an OSHA recommended safety assessment of the active compound E, performed by Fauske and Associates, LLC.

Titanium alloys belong to the metal biomaterials that are one of the most widely used in medicine. In recent years, in order to reduce the use of vanadium, Ti6Al4V alloy is increasingly replaced by Ti6Al7Nb alloy. In addition, to ensure the best possible biocompatibility, its surface is subjected to appropriate modifications, for example, anodic oxidation. Despite the extensive use of anodic oxidation of titanium implants in orthopedics, there are few works focused on a detailed analysis of the chemical composition of the surface layers. In addition, the effect of treatments before anodic oxidation on the properties of the produced layer has not been analyzed. Thus, the purpose of this study was to analyze in detail the chemical composition of the passive layer of Ti6Al7Nb alloy obtained by anodic oxidation preceded by sandblasting. Moreover, the physicochemical properties of the analyzed surface affecting biocompatibility were determined. For this purpose, surface observation, wettability and roughness tests, microhardness tests, electrochemical tests and phase composition analysis were carried out. In addition, the preclinical suitability, of the surface modified in this way, was evaluated by cytotoxicity tests.

Background: Endometriosis is a female chronic inflammatory disease in which endometrial tissue develops outside the uterine cavity. It is a complex pathology, that significantly contributes to morbidity in premenopausal women, leading to chronic pain, infertility, and subfertility negatively impacting the physical, and emotional well-being and overall quality of life. The public health burden of endometriosis remains elusive and challenging to determine, and this uncertainty can lead to inadequate healthcare services and treatments. Objective: To estimate the incidence and prevalence of endometriosis in Italy using the hospital discharge records database. Population-based retrospective study. Nationwide between 2011 and 2020. Methods: From the National Hospital Discharge Database were selected all admissions with a diagnosis of endometriosis (ICD-9-CM, codes 617.x), supported by the presence of a procedure code of laparoscopy or any other surgical procedure allowing direct visualisation of the lesions. Main outcomes measures Incidence and prevalence of endometriosis were estimated for the entire 2010-2020 period and by individual year, analysing the time trend and variability in different geographical areas of Italy. Results: A total of 134,667,646 women aged 15–50 years with one or more hospitalisations for endometriosis in all Italian hospitals. The incidence of endometriosis in Italy during this period was 0.839 per 1000 women (CI95% 0.834-0.844), exhibiting a statistically significant decreasing trend over the years. A discernible north-south gradient was observed, with higher rates documented in the northern regions. The prevalence rate stood at 14.0 per 1000 during the same period, and a similar north-south geographical gradient was identifiable in the prevalence rates as well. Conclusions: The utilization of national-level hospital data enables the generation of incidence and prevalence data for endometriosis without variations in methods and definitions, facilitating the evaluation of temporal trends and regional comparisons. Understanding and quantifying this phenomenon is essential for appropriate healthcare planning in various Italian regions.

Introduction: The emergency of the SARS-CoV-2 virus spread and its subsequent global pan-demic have raised significant concerns regarding its impact on pregnancy outcomes. This review aims to summarize the emerging data on the risk of preterm delivery in pregnant women infected with SARS-CoV-2. Materials and Methods: A systematic search was conducted from March 2020 to December 2023 using PubMed, following PRISMA guidelines. Studies correlating maternal COVID-19 infection with preterm birth were included. Results: Thirteen studies were analyzed, indicating a higher incidence of preterm birth in SARS-CoV-2 positive pregnant women compared to controls. The average incidence rate of pre-term birth in infected patients was 18.5%, with a median of 12.75%, while non infected women showed an average incidence of preterm birth of 10% with a median of 8.2%. Discussion: Studies suggest an association between SARS-CoV-2 infection during pregnancy and increased risk of preterm birth and cesarean section. Severity of symptoms and underlying comorbidities further elevate this risk. Notably, infections during the third trimester pose the highest risk of preterm birth. Conclusion: Preventing SARS-CoV-2 infection during pregnancy is crucial to mitigate adverse obstetric outcomes. Close monitoring and tailored interventions for infected pregnant women, particularly those in later trimesters and with comorbidities, are imperative to reduce the risk of preterm birth and improve maternal-fetal outcomes.

(1) Background: Sarcopenia, a condition characterized by a decrease in muscle mass and strength, is very common in patients with obesity and can be aggravated by bariatric surgery, potentially compromising the clinical results of surgery. There is increasing interest in pa-tient-reported outcome measures (PROMs) to assess results in other health variables that may be especially important for individual patients. The role of exercise in enhancing health-related quality of life (HRQoL) after surgery remains underexplored. This study investigated the impact of exercise on HRQoL in bariatric sarcopenic patients via the Sarcopenia Quality of Life (SarQoL) questionnaire. (2) Method: Candidates for surgery took part in the EXPOBAR program and were randomized into experimental and control groups. The intervention lasted 16 weeks, starting one month after surgery, and included combined aerobic and resistance exercise. Outcomes, including body composition and physical fitness parameters, were measured before and after the intervention. All participants underwent gastric bypass surgery (RYGB). (3) Results: The baseline characteristics of the participants were not significantly different between the two groups. All patients met the criteria for moderate/severe obesity and the EASO/ESPEN criteria for sarcopenia, namely, reduced muscle strength assessed by grip strength and reduced muscle mass assessed by the ASMM score/weight. After completing the study protocol, patients in both groups had increased HRQoL, but the increase was significantly greater in the intervention group than in the control group. (4) Conclusion: Our findings suggest that exercise plays a crucial role in improving both physical and psychological well-being in postbariatric patients, highlighting the need to integrate structured exercise programs in post-surgery care. This study was prospectively registered at Clinicaltrials.gov (NCT03497546).

This study delves into the intricate interplay of economic growth components, specifically focusing on Consumption and investment in Saudi Arabia from 2000 to 2022. Employing vector error correction models and cointegration techniques, we analyze the short- and long-term dynamics within the relationship of Consumption, investment, and economic growth. Granger causality analysis is also used to discern these pivotal variables' causal connections. Our empirical analysis reveals a persistent long-term cointegration relationship among the variables, underscoring the enduring nature of their interdependency. Furthermore, our findings highlight Consumption and investment's statistically significant positive impact on economic growth. Notably, the short-term analysis unveils a stable model characterized by an annual adjustment to equilibrium of 100%.Moreover, the Granger causality study demonstrates unidirectional causal linkages between Consumption, investment, and economic growth. These findings hold substantial implications for policy formulation in Saudi Arabia. Policymakers must grasp the ramifications of burgeoning prosperity and evolving private consumption patterns on future environmental outcomes. Achieving sustainable long-term results necessitates equal emphasis on bolstering private Consumption and fostering other facets of economic growth.

Road safety and the effectiveness of the transportation system as a whole are significantly impacted by driver comfort. Road surface quality can play a significant part in the driver’s comfort experienced on roads in any country. This study employs a Random Forest technique to examine the association between road roughness and drivers' comfort during long-distance driving. Using Random Forest, a dependable machine learning technique that can handle big datasets and detect nonlinear correlations, this work aims to shed light on the complex dynamics between road conditions and driver’s comfort. 1,048,576 rows of data from MIRANDA, an application developed at the University of Gustave Eiffel, were used in this study as part of the data collected from a probe vehicle. The data collected includes an International Roughness Index (IRI). The IRI thresholds offer a simple method for assessing driver comfort and road irregularity. While highlighting how uneven and uncomfortable the road is, the research's findings (Road Roughness: SD – 0.73; Driver's Comfort: - Mean, 10.01, SD – 0.64) also contribute to the standardization of road condition evaluation and maintenance communication. This finding is anticipated to aid in the development of strategies for improving the welfare of long-haul drivers and fixing road infrastructure to comply with standard road index, ultimately leading to the creation of more efficient and sustainable transportation systems.

The aim of this study is to analyze the characteristics of drought such as intensity, cumulative curves and trends, based on SPEI (Standardized Precipitation Evapotranspiration Index) at 8 stations in Korea from 1981 to 2010. The traditional SPEI is based on Thornthwaite equation for estimating evapotranspiration; SPEI_th. However, a standard of agricultural water management in Korea suggests FAO Penman-Monteith equation; SPEI_pm. In this study, we analyzed the intensity and trends of drought using SPEI_th and SPEI_pm, respectively, and analyzed the relationship between them. Both of central and southern region, the SPEIs were below -1.0 (moderated drought) for the periods May-August in the representative drought year such as 1988, 2001, and 2008-09. The frequency of drought was higher in southern region than central region. In addition, SPEI_pm showed slightly more intensive drought rather than SPEI_th except for Chuncheon and Gwangju. In 5 stations except for Cheoncheon, Gwangju and Jinju, the cumulative probability that SPEI_pm is below -1.5 was significantly increased from 1981-1995 to 1996-2010. As the results of drought trends, the increasing trend of SPEIs was shown on fall season, and the cumulative probability that SPEI_pm is below -1.5 was also significantly increased.

The field of epigenetics, which explores how heritable traits or stable alterations of cell functions occur without changes to the DNA sequence and how environmental factors affect gene expression, is rapidly advancing. Epigenetics plays a critical role in memory formation, learning, and cognitive functioning, effectively bridging genetics with environmental influence. Maternal behavior in rats, for instance, can modify the stress response of their offspring through epigenetic mechanisms such as histone acetylation and DNA methylation. Understanding neurodegenerative diseases like Parkinson's disease (PD) depends on comprehending the mechanisms of epigenetic regulation. Epigenetic modifications, which alter proteins and DNA structure without changing the DNA sequence, can activate or suppress gene expression, assisting organisms in adapting to environmental changes. These modifications may influence genes involved in inflammation, synaptic plasticity, and neuroprotection, potentially contributing to cognitive deficits in PD patients. MicroRNAs (miRNAs), histone modifications, and DNA methylation are the epigenetic mechanisms that significantly influence cell differentiation and maintain normal cellular activity. Understanding the intricate molecular processes of epigenetics could lead to more targeted and effective therapies. Despite numerous findings on how epigenetics affects cognitive alterations in PD patients, only some studies coordinate and integrate these results. Here, we summarize recent findings on how epigenetic changes impact gene expression linked to cognitive impairments in PD.

The main goal of our scientific study is to determine the particular characteristics of the endo-scopic image of the otorhinolaryngologic pathology of nasopharynx, which is called chronic rhinosinusitis in association with gastroesophageal acid reflux disease. Background/Objectives: to identify a specific features in the endoscopic picture of chronic rhinosinusitis associated with acid gastroesophageal reflux disease symptoms. Methods: there were selected 521 adult patients, from this sample as a main group we have selected only 95 patients with the highest scores on the Reflux Symptom Index (RSI) (>20) and Reflux Symptom Score-12 (RSS-12) (>130) questionnaires. As a control group we have selected 41 adult patients only with chronic rhinosinusitis and 10 healthy patients. Results: there were significant changes in the nasopharyngeal mucosa. In-creased vascularity of the nasopharyngeal mucosa was noted in 91 patients (95,7%). Hypertrophy of the nasopharyngeal mucosa was found in 83 patients (87,4%). In 77 (81,1%) patients, mucus was found in the nasopharynx with different characteristics of color and consistency, and no mucus or other secretions were found in the middle nasal passages in these patients. In 62 pa-tients (65,3%) asymmetric hypertrophy of the mucosa of the oropharynx was noted. Conclusions: the presence of specific features of the endoscopic picture of the nose and nasopharynx of pa-tients with chronic rhinosinusitis associated with gastroesophageal disease symptoms and pro-posed a method for assessing the degree of influence of gastroesophageal reflux disease on the mucosal layer of the nose and nasopharynx. The possible influence of symptoms of gas-tro-oesophageal reflux disease on the course and severity of clinical manifestations of exacerba-tions of chronic rhinosinusitis needs further investigation.

This study delves into the dynamics of 'Variations' and 'Claims' within construction projects, specifically under the FIDIC-Red Book 1999 framework. The study aims to identify, categorize, and devise mitigation strategies for key types of variations and claims aligning with the FIDIC conditions of contract. The research is drawing on inputs from construction industry professionals including contract administrators and project managers, focusing on the MENA region. This choice is driven by the region's extensive adoption of FIDIC standards and its rapidly growing construction sector. Data collection encompassed a questionnaire distributed to 80 industry experts predominantly through interviews that focused on countries like Saudi Arabia, UAE, Kuwait, and Egypt. These locations were chosen to reflect diverse construction practices and the involvement of international firms. Utilizing SPSS-V.25 for statistical analysis, the study uncovers the most prevalent and impactful causes of variations and claims, highlighting the critical need for managerial intervention. A key feature is the integration of scientometric analysis for a quantitative finding. A significant addition to the methodology is the implementation of a k-means clustering analysis. The survey had high internal consistency with a Cronbach's alpha of 0.97, and respondents reported frequent and significant claims like delayed drawings, ambiguous documents, and client changes. The results showed that effective claims management requires clear communication and balanced contracts, while poor design and contract documentation cause variations and claims. Spearman's correlation showed strong positive relationships between certain claim types and causes, emphasizing the importance of dealing with these factors to reduce claims. Most respondents said the survey could predict and reduce claims.

Medical waste management is crucial issues for keeping our life safe and safety. Without effective measures for waste management, we cannot keep ourselves safe from different types of contagious diseases; viruses, bacteria. Knowledge sharing assists healthcare staff in identifying and mitigating hazards on appropriate handling, segregation and disposal medical waste. The aim of the study is to identify a multifaceted analysis of knowledge sharing, training, communication and attitudes for effective medical waste management. This study selected 153 medical workers randomly, including nurses, lab technologists, and cleaners, from hospitals, diagnostic centers, and clinics in the northern part of Bangladesh. The study design of this research is mixed-methods. This research adopts a survey and interview as a research strategy. The samples are collected randomly. SPSS software packages, MS Excel Office, and PLS-SEM are used to analyze data. Most of the respondents always share their knowledge face-to-face according to the findings. The result also shows that there are positive relationship between sources of knowledge (p: 0.046), awareness and knowledge (p: 0.049), attitudes of waste management (p: 0.025) and effective medical waste management. However, there are no relationships between communication and collaboration (p: 0.943), the practice of waste management (p: 0.155), supervision and staff monitoring (p: 0.527), training and education (p: 0.656) and effective medical waste management. Its focus on the northern part of Bangladesh introduces regional specificity, potentially limiting the applicability of results to other regions. The knowledge-sharing practices for waste management among medical staff are examined within this research, along with the relationship between attitude, awareness, and knowledge, staff supervision and monitoring, practice, training, and education and effective medical waste management that have not been studied before home and abroad. This analysis highlights the critical need for an integrated approach to medical waste management, emphasizing the importance of continuous education, open communication, and cultivating a culture that prioritizes environmental sustainability. The insights from this study offer practical recommendations for healthcare institutions to improve their medical waste management practices, ultimately leading to enhanced health outcomes and better environmental protection.

This study focuses on enhancing controllable fibrin-based hydrogels for tissue engineering, addressing existing weaknesses. By integrating a novel copolymer, we improve the foundation for cell-based angiogenesis with adaptable structural features. Tissue engineering often faces challenges like waste disposal and nutrient supply beyond the 200 µm diffusion limit. Angiogenesis breaks through this limitation, allowing the construction of larger constructs. Our innovative scaffold combination significantly boosts angiogenesis, resulting in longer branches and more capillary network junctions. The copolymer attached to fibrin fibers enables precise adjustment of hydrogel mechanical-dynamic properties for specific applications. Our material proves effective for angiogenesis, even under suppression factors like suramin. In our study, we prepared fibrin-based hydrogels with and without the copolymer PVP12400-co-GMA10mol%. Using a co-culture system of human umbilical vein endothelial cells (HUVEC) and mesenchymal stem cells (MSC), we analyzed angiogenetic behavior on and within the modified hydrogels. Capillary-like structures were reproducibly formed on different surfaces, demonstrating the general feasibility of three-dimensional endothelial cell networks in fibrin-based hydrogels. This highlights the biomaterial's suitability for in vitro pre-vascularization of biohybrid implants.

(1) Background: LUS has emerged as a simple, rapid and non-invasive method for the dynamic assessment of pulmonary congestion, a major prognostic factor and a therapeutic target in AHF. (2) Methods: In the single-center prospective observational study, 42 patients hospitalized for AHF in the post-emergency polyvalent medicine department of CHU Grenoble were successively included between May 2021 and July 2022. Clinical examination, LUS and electrolyte panel results were collected daily. Vital status was assessed 30 days after the last LUS. The primary endpoint was the evolution of the number of B-lines according to the dose of diuretic administered ; (3) Results: We performed 188 LUS. Our patients were elderly (85.8 [SD 8.1]) and comorbid. The median number of B-lines decreased from 17 at admission to 7 in the middle of the hospital stay, then stagnated until discharge. Simultaneously, the median dose of diuretics, initially stable at a maximum of 40 mg/d IV, decreased to 20mg/d IV by the end of hospital stay. Patients with CKD had a higher mean number of B-lines at entry (24.2 [SD 11.6]) compared to those without CKD (8.2 [SD 8.8]). However, the evolution of B-lines number was independent of creatinine levels. 30-day all-causes mortality was significantly related to the number of B-lines at discharge (15.2 [SD 10.1] in deceased patients versus 3.9 [SD 5.4] in living patients, p

This paper focuses on the role of the most common mineralogical techniques applied to the identification of the different statuary qualities in white, grey and black Göktepe marble. For this purpose, a Roman case of sculpture marble collection from the rural villa of Valdetorres de Jarama (central Iberia), of the 4th century AD, is presented. The mythological statuary, combining white, grey and black marbles, are one of the most outstanding marble collections in Aphrodisian style found in Hispania. The analytical results (Petrography, Cathodoluminescence, C and O isotopes, and Sr and Mn concentration) support the identification of two varieties of “black” Göktepe, traditionally named as bigio morato and bigo antico, as well as the best statuary quality on white Göktepe. In addition, the analytical identification of other Asiatic marbles in Valdetorres collection, a white coarse-grained originally from the quarries of Aphrodisias city and one small piece identified as Carian red from Iasos, corroborates the already suggested strong connection existing between artists and the stone material they chose for their works. Finally, it is noteworthy the identification carried out on the marble of the bases that served as seats for the sculptures, as it is a white marble of lower quality whose analytical characteristics are consistent with the Microasiatic marble of Denizli. The use of these exotic and exceptional raw materials confirms the taste for luxury and decorative richness in Late Antique Hispanic rural villae and contributes to a better understanding of the distribution of Aphrodisian productions in the Western Roman provinces.

Lead optimization in drug discovery is a crucial phase where initial hits are refined into compounds with improved pharmacological properties. While traditional methods rely on manual experimentation and modifications, AI-driven techniques have revolutionized this process by leveraging big data and predictive modeling. This review explores how AI-driven approaches accelerate lead optimization, showcasing examples like deep neural networks and reinforcement learning. Integration of multi-omic data and experimental validation further enhances AI-driven strategies. The future lies in refining these AI methods, democratizing tools, and interdisciplinary collaboration to streamline drug discovery and address medical needs efficiently.

Abstract: Conventional antibiotic and multidrug treatments become less and less effective and a discovery of new effective and safe antibacterial agents got a global priority. The returning to the natural antibacterial product is relatively new current trend. Terrestrial biota is a rich source of biologically active substances whose antibacterial potential was not fully utilized. Aim of this review is to present the current state-of-the art of terrestrial biota-derived antibacterial agents and inspired by nature treatments. It is a summary of the most important sources and new identified or modified antibacterial agents and treatments during the last 5 years. It focuses on the significance of plants- animals- and bacteria-derived biologically active agents as powerful alternatives to antibiotics as well as on the advantages of utilizing natural antibacterial molecules alone or in combinations with antibiotics. The main conclusion is that the terrestrial biota derived antibacterial products and substances open variety of new ways to modern improved therapeutic strategies. New terrestrial sources of known antibacterial agents and new antibacterial agents from terrestrial biota were discovered during the last 5 years, which are under investigation together with some long ago known but now surviving their renaissance for the development of new medical treatments. Use of natural antibacterial peptides as well as combinational therapy by commercial antibiotics and natural products outlines as the most promising for treating of bacterial infections. In vivo testing and clinical trials are necessary to reach clinical application.

Background: Despite a range of available treatments, there is a remaining unmet need for patients with severe post-partum hemorrhage (sPPH). Objective: This manuscript evaluated efficacy and safety of recombinant activated factor VIIa (rFVIIa) in sPPH management. Methods: An open-label, multi-center, randomized controlled trial (RCT; NCT00370877) and four observational studies (OS; OS-1 [NCT04723979], OS-2, OS-3 and OS-4) were analyzed regarding efficacy (need for subsequent invasive procedures, including uterine compression sutures, uterine or iliac artery ligation, arterial embolization or hysterectomy) and safety (incidence of thromboembolic events [TE] and maternal mortality) of rFVIIa for sPPH. The RCT, and OS-1 and OS-2, included a control group of women who did not receive rFVIIa (with propensity score-matching used in OS-1 and OS-2), whereas OS-3 and OS-4 provided descriptive data for rFVIIa exposed women only. Results: A total of 446 women exposed to rFVIIa and 1,717 non-exposed controls were included. In the RCT, fewer rFVIIa exposed women (50% [21/42]) had an invasive procedure versus non-exposed women (91% [38/42]; odds ratio 0.11, 95% confidence interval 0.03–0.35). In OS-1, more rFVIIa exposed women (58% [22/38]) had an invasive procedure versus non-exposed women (35% [13.3/38]; odds ratio 2.46, 95% confidence interval 1.06–5.99). In OS-2, 17% (3/18) of rFVIIa exposed women and 32% (5.6/17.8) of non-exposed women had an invasive procedure (odds ratio 0.33, 95% confidence interval 0.03–1.75). Across all included women, TEs occurred in 1.5% (0.2% arterial and 1.2% venous) of rFVIIa exposed women and 1.6% (0.2% arterial and 1.4% venous) of non-exposed women with available data. Conclusions: The positive treatment effect of rFVIIa in the RCT was not confirmed in the OS. However, the safety analysis did not show any increased incidence of TEs with rFVIIa treatment.

Bioimpedance analysis (BIA) is a validated non-invasive technique already proven to be useful for the diagnosis, prognosis, and management of body fluids in subjects with heart failure (HF) and chronic kidney disease (CKD). Although BIA has been widely employed for research purposes, its clinical application is still not fully widespread. The aim of this review is to provide a comprehensive overview of the state of art of BIA utilization by analysing the clinical benefits, limitations, and the potential future developments in this clinically unexplored field.

Detecting volatile organic compounds (VOCs) emitted from different plant species and their or-gans can provide valuable information about plant health and environmental factors that affect them. For example, limonene emission can be a biomarker to monitor plant health and detect stress. Traditional methods for VOC detection encounter challenges, prompting the proposal of novel approaches. In this study, we proposed integrating electrospinning, molecular imprinting, and conductive nanofibers to fabricate limonene sensors. In detail, polyvinylpyrrolidone (PVP) and polyacrylic acid (PAA) served here as fiber and cavity formers, respectively, with multi-walled carbon nanotubes (MWCNT) enhancing conductivity. We developed one-step monolithic molecularly imprinted fibers, where S(-)-limonene was the target molecule using electrospinning technique. The functional cavities were fixed using UV curing method, followed by a target mol-ecule washing. This procedure enabled the creation of recognition sites for limonene within the nanofiber matrix, enhancing sensor performance and streamlining manufacturing. Humidity was crucial for sensor working, with optimal conditions at about 50% RH. The sensors rapidly re-sponded to S(-)-limonene, reaching a plateau within 200 seconds. Enhancing fiber density im-proved sensor performance, resulting in a lower limit of detection (LOD) of 137 ppb. However, excessive fiber density decreased accessibility to active sites, thus reducing sensitivity. Remarka-bly, the thinnest mat on the fibrous sensors created provided the highest selectivity to limonene (Selectivity Index: 72%) compared to other VOCs, such as EtOH (used as a solvent in nanofiber development), aromatic compounds (toluene), and two other monoterpenes (α-pinene and linalo-ol) with similar structure. These findings underscored the potential of the proposed integrated approach for selective VOC detection in applications such as precision agriculture and environ-mental monitoring.

Background: The rise of new SARS-CoV-2 mutations brought challenges and progress in the global fight against COVID-19. Mutations in spike and accessory genes affect transmission, vaccine efficacy, treatments, testing, and public health strategies. Monitoring emerging variants is crucial to halt virus spread. Methods: 44 nasopharyngeal/oropharyngeal swabs from Kenyan patients were sequenced with the Illumina platform. Galaxy's bioinformatic tools were used for genomic analysis. SARS-CoV-2 genome classification was done using PANGOLIN and mutation annotation with the COVID-19 Annotator tool. Results: The study showed 5 clades to be circulating in the region. 38(86%) were BA.1.1; 2(5%) were BA.1.1.1; 1(2%) was BA.1; 1(2%) was BA.1.14 and 2(5%) were AY.46. These clades had a cumulative of 173 mutations among them with 50 novel mutations. Forty-eight of these novel mutations occurred in a low frequency of 2.3% of the sequences tested while the other two, S:R214R, and NSP2:A555A, were for 43.2% and 18.2% of the cases respectively. Conclusions: The high-frequency novel mutations were synonymous mutations, a phenomenon that was previously viewed as phenotypically silent but recent studies indicate they can affect viral fitness with potential functional associations. These findings add to the understanding of the SARS-CoV-2 virus future evolutionary and immunological dynamics in the region

This study outlines a 3-step production process for Ti-TiC Metal Matrix Composite (MMC) employing powder Mechanical Blending, Laser Powder Bed Fusion (LPBF), and a heat treatment. A TiC fraction of more than 20 vol% was formed in-situ through the reaction of titanium with carbon during the LPBF process. The manufactured MMC pieces showed a record stiffness and fracture strain combination. The LPBF energy density impacted strongly porosity type. The as-built microstructure displayed an homogeneous distribution of sub-stoichiometric TiC dendrites which were fully converted into equiaxed TiC grains during the heat treatment. The TiC C/Ti ratio was found to be close to 0.5, resulting in an effective reinforcement content nearly twice the one expected for stoichiometric TiC, leading to stronger reinforcement. The mechanical analysis revealed a Young’s modulus of up to 149 GPa and an ultimate tensile strength of up to 770 MPa, indicating a 27% and 34% improvement, respectively, compared to commercially pure Titanium produced by LPBF and heat treated in the same conditions. A fracture strain of up to 2.8% was achieved. The combination of in-situ formation of defect-free TiC reinforcement and subsequent heat treatment enables to reach an exceptional ductility, considering the 20 vol% reinforcement content.

This work aimed to develop an anionic cellulose nanofiber (CNF) bio-adsorbent from palm date tree waste and to investigate its removal efficiency against cationic methylene blue dye from contaminated water. Palm date pulp was first prepared from palm date leaves through acid hydrolysis using H2SO4, followed by hydrolysis in a basic medium using KOH, in which the process completely removed the components of hemicellulose, lignin, and silica. To obtain anionic CNF, the resulting pulp was further treated with H2SO4, followed by centrifugation. Biogel formation of the CNF suspension was promoted by sonication, where its removal efficiency of methylene blue dye was studied as a function of dye concentration, temperature, contact time, and pH value. Two equilibrium models, the Langmuir and Freundlich models were employed, and the Langmuir model was found to be consistent with the experimental data. The highest removal efficiency was obtained at 60oC and was 5mg/gm. Furthermore, several kinetic models were used to gain insight into the adsorption mechanism. The pseudo-second-order model provided an accurate description of the adsorption process, while the Elovich equation suggested a chemical reaction between methylene blue dye and CNF. The study’s findings were in agreement with the pseudo-second-order model, indicating general chemical reactions. The study indicates that CNF adsorbents derived from renewable natural waste sources such as palm date leaves can be effective in removing cationic contaminants such as methylene blue dye.

Myelolipoma is a benign, typically inert neoplasm of uncertain aetiology that is rarely reported in cats. Although commonly asymptomatic, in some cases, myelolipomas can cause abdominal discomfort or present with rupture and haemorrhage. Here, we describe a rare case of a splenic myelolipoma in a Domestic Long Hair cat in which, after extensive diagnostic investigations, clinical signs of hyporexia and weight loss were attributable to the presence of an intra-abdominal mass. The patient was treated by splenectomy and unexpectedly died during the post-operative period. Although splenectomy appears to be a sensible intervention in symptomatic patients, the optimal management of splenic myelolipomas in cats remains unknown. The risk-benefit ratio of surgical management needs to be carefully considered, and therapeutic intervention should be tailored individually to each patient.

Advances in early detection of Breast cancer and treatment improvements have significant-ly increased survival rates. Traditional screening methods, including mammography, MRI, ultrasound, and biopsies, while effective, often come with high costs and risks. Recently, thermal imaging has gained attention due to its minimal risks compared to mammography, although it is not widely adopted as a primary detection tool since it depends on identifying skin temperature changes and lesions. The advent of machine learning (ML) and deep learning (DL) has enhanced the effectiveness of breast cancer detection and diagnosis using this technology. In this study a novel methodology for developing an interpretable computer-aided diagnosis (CAD) system for breast cancer detection, leveraging explaina-ble Artificial Intelligence (XAI) throughout its various phases. To achieve these goals, we proposed a new multi-objective optimization approach named Hybrid Particle Swarm Optimization algorithm (HPSO) and Hybrid spider Monkey Optimization algorithm (HSMO). These algorithms simultaneously combine the continuous and binary representations of PSO and SMO to effectively manage trade-offs between Accuracy, feature selection and hyperparameter tuning. We evaluate several CAD models and investigate the impact of handcrafted methods such as Local Binary Patterns (LBP), Histogram of Oriented Gradients (HOG), Gabor filters, and edge detection. We further shedding light on the effect of feature selection and optimization on feature attribution and model decision-making processes using the SHapley Additive exPlanations (SHAP) framework, with a particular emphasis on cancer classification using the DMR-IR dataset. The results of our experiments demonstrate in all trials that the performance of the model is improved. Also with HSMO our models achieved a high accuracy of 98.27% and F1- score of 98.15% while selecting only 25.78% of the HOG features. This approach not only boosts the performance of CAD models but also ensures comprehensive interpretability. This method emerges as a promising and transparent tool for early breast cancer diagnosis.

The success of near-infrared spectroscopy (NIRS) analysis hinges on the precision and robustness of the calibration model. Shallow learning (SL) algorithms like partial least squares discriminant analysis (PLS-DA) often fall short in capturing interrelationships between adjacent spectral variables, and the analysis results are easily affected by spectral noise, which dramatically limits the breadth and depth application of NIRS. Deep learning (DL) methods, with their capacity to discern intricate features from limited samples, are progressively integrated into NIRS. In this paper, two discriminant analysis problems including wheat kernels and Yali pears were used as examples, and several representative calibration models to research the robustness and effectiveness of the model. Additionally, this article proposed a near-infrared calibration model, which is based on gramian angular difference field and coordinate attention convolutional neural networks (G-CACNN). The research results show that, compared with SL, spectral preprocessing has a smaller impact on the analysis accuracy of consensus learning (CL) and DL, and the latter has the highest analysis accuracy in the modeling results of using the original spectrum. The accuracy of G-CACNN in two discrimination tasks is 98.48% and 99.39%, respectively. Finally, This research compared the performance of various models under noise to evaluate the robustness and noise resistance of the proposed method.

This study presents the first genome assembly of the freshwater saprobe fungus Neonectria lugdunensis and a comprehensive phylogenomics analysis of the Nectriaceae family, examining genomic traits according to fungal lifestyles. The Nectriaceae family, one of the largest in Hypocreales, includes fungi with significant ecological roles and economic importance as plant pathogens, endophytes, and saprobes. The phylogenomics analysis identified 2684 single-copy orthologs, providing a robust evolutionary framework for the Nectriaceae family. We analyzed the genomic characteristics of 17 Nectriaceae genomes, focusing on their carbohydrate-active enzymes (CAZymes), biosynthetic gene clusters (BGCs), and adaptations to environmental temperatures. Our results highlight the adaptation mechanisms of N. lugdunensis, emphasizing its capabilities for plant-litter degradation and enzyme activity in varying temperatures. Comparative genomics of different Nectriaceae lifestyles revealed significant differences in genome size, gene content, repetitive elements, and secondary metabolite production. Endophytes exhibited larger genomes, more effector proteins, and BGCs, while plant pathogens had higher thermo-adapted protein counts, suggesting greater resilience to global warming. In contrast, the freshwater saprobe shows less adaptation to warmer temperatures and is important for conservation goals. This study underscores the importance of understanding fungal genomic adaptations to predict ecosystem impacts and conservation targets in the face of climate change.

The joint extraction of entities and relations is a critical task in information extraction, and its performance directly affects the performance of downstream tasks. However, existing joint extraction models based on deep learning exhibit weak processing capabilities for the phenomenon of multiple pronunciations of one character and multiple characters of one pronunciation when processing Chinese texts, resulting in performance loss. To address these issues, this paper introduces part-of-speech (POS) and pinyin features to aid the model in learning semantic features that are more contextually appropriate. A Chinese Joint Entity and Relation Extraction Model based on Progressive Contrastive Learning and Heterogeneous Feature Fusion is proposed (CJE-PCHF). During model training, an interactive fusion network based on progressive contrastive learning is employed to learn the dependencies between pinyin, POS, and semantic features. This guides the model in heterogeneous feature fusion, capturing higher-order semantic associations between heterogeneous features. On the commonly used DuIE evaluation dataset for joint extraction, this model achieved a significant improvement, with the F1 score increasing by 5.4% compared to the benchmark model CasRel.

Yoga promotes acceptance, compassion, physicality, active postures, mental and emotional awareness, and spiritual benefits. It involves breath techniques, postures, and body locks, maintaining balance and strength. It's based on ethical principles. Beyond simple performance, swimming is a catalyst for overall well-being. Complementarily, yoga serves as an invaluable adjunct for swimmers, enhancing flexibility, strength, and body awareness - a triad essential to aquatic excellence. The confluence of yoga and swimming, particularly through the practice of aqua yoga asanas, presents a new paradigm for both athletes and non-performers alike. Athletes who embrace the harmonious fusion of swimming and yoga unearth the potential for achieving not just athletic mastery but also a more balanced and fulfilling lifestyle. This blend provides a route not only to enhance performance in the water but also to elevate the overall quality of life. We examined the feasibility of incorporating yoga and swimming practice into Romanian subjects' lifestyles, designing a factor analysis in SmartPLS software, based on an online survey. The study assesses the participants' knowledge of yoga's theory and philosophy, as well as their perceptions of the swimming practice's benefits for social and health issues. According to our study, Romanian participants practice yoga and swimming as often as possible to reduce stress, improve concentration for work-related tasks, and improve joint elasticity, balance, and muscular tone. Thus, Yoga and swimming are substitutes for other approaches in prevention and therapy.

Selenium nanoparticles (SeNPs) can mitigate cadmium (Cd2+) toxicity in crop cultivation and aquaculture. This study investigates the impact of SeNPs on Cd-induced toxicity in Chlamydomonas reinhardtii, a model organism, aiming to mitigate Cd damage in crops. SeNPs were synthesized using sodium carboxymethyl cellulose (CMC) as a dispersant and vitamin C to reduce H2SeO3. Characterization by transmission electron microscopy (TEM) and nanoparticle granulator revealed uniform, stable spherical SeNPs. Cd2+ and SeNPs of varying concentrations were introduced into culture media of wild type (CC125mt+) and cell wall defect type (CC400mt+) Chlamydomonas reinhardtii. Growth curves, photosynthetic pigment content, enzyme activities (T-SOD and CAT), MDA content, and ROS levels were assessed. Fluorescence induction kinetics, QA oxidation kinetics, and Cd2+ content in cells were measured to evaluate SeNPs' effect on Cd toxicity. Results showed SeNPs exacerbated Cd2+ toxicity in CC125mt+ by inhibiting growth and increasing catalase activity, indicating enhanced oxidative damage. SeNPs intensified PSII damage by Cd2+ and increased intracellular Cd2+ content, possibly exacerbating toxicity. SeNPs had no effect on Cd2+ toxicity in CC400mt+. Overall, SeNPs exacerbated Cd2+ toxicity in wild type CC125mt+ but not in cell wall defective CC400mt+. These findings caution against indiscriminate use of nano-selenium to mitigate Cd damage, stressing the importance of careful target selection, dosage, and range considerations.

A high-gain broadband circularly polarized crossed dipole antenna is designed. This antenna utilizes two pairs of cross dipoles and a pair of phase delay lines to form circularly polarized radiation. Open-circuit stubs are loaded on the four arms of these two pairs of cross dipoles to introduce new circularly polarized resonating frequency. A rectangular ring patch is introduced directly below the cross dipoles to form the third circularly polarized resonating frequency, thereby broadening the axial ratio bandwidth of the antenna. In addition, metal posts are loaded at the four right angles of the rectangular ring patch to increase the antenna gain. Measurement results show that the antenna achieves a 3dB axial ratio bandwidth of 29.2% (1.9 GHz-2.55 GHz) and maintains a gain of 7.5 dB within the passband, exhibiting good circularly polarized radiation performance.

With LiDAR (Light Detection and Ranging) time series being used for various applications, optimal realisation of a common geodetic datum over many epochs is a highly important prerequisite with direct impact on accuracy and reliability of derived measures. In our work, we develop and define several approaches to the adjustment of multi-temporal LiDAR data in a given software framework. These approaches ranging from pragmatic to more rigorous solutions are applied to an 8 year time series with 21 individual epochs. The analysis of the respective results suggests that a sequence of bi-temporal adjustments brings the best results while being more flexible and computationally viable than the most extensive approach of using all epochs in one single multi-temporal adjustment. With a combination of sparse control patches measured in the field and one selected reference block, we obtain relative datum discrepancies in the range of 1-2 cm for the complete time series. Based on our findings, we formulate design criteria for setting up and adjusting future time series with the proposed method.

Edvard Munch, a founder of Expressionism was pre-occupied with depicting his subjective experience and the most prolific painter of self-portraits since Rembrandt. Based on evidence that faces and self-related images are more salient than other objects it is plausible that self-portraits, in which the subject and object are the same, reflect the artist’s state of mind. Although he suffered from a variety of physical and psychological illness Munch was not diagnosed with any specificity in his lifetime. Posthumous diagnoses include schizophrenia, anxiety, bipolar and other disorders. Recent research has revealed altered visual perception in such patients. The present study empirically analysed three stylistic elements of Munch’s painted self-portraits and portraits: contrast, colour and fractal dimension and his painted productivity, to determine if variations correlate with critical life events and if so whether they indicate states of mind. It found significant increases in contrast and colour brightness and persistent high complexity during critical periods supporting the conclusion that Munch is diagnostically best described as suffering from early onset schizophrenia and comorbid social anxiety disorder.

Many have speculated that events of personal and financial loss in Rembrandt’s life caused depression and that this is revealed by examination of his self-portraits particularly those painted in old age. Some report detecting various physiological diseases associated with aging, including vision impairment, which may have affected his mood and work. Aging and neurodegenerative disease which often accompanies it, are both associated with depression. Recent advances in imaging and computer technology make it possible to empirically examine changes in artistic style which can contribute to understanding artists’ physical and mental health. In the current study changes in contrast, colour and fractal dimension were measured in the entire corpus of Rembrandt’s painted self-portraits and portraits to determine whether changes in style indicate depression or disease. Productivity was also examined as an indirect indicator. Given the high salience attributed to self-images, it also examined whether differences in style could be detected between self-portraits and portraits of related and unrelated others. The results indicate that it is unlikely that Rembrandt suffered from unipolar or bipolar depression, age-related cognitive decline, or neurodegenerative disease. The data are consistent with someone experiencing episodes of low mood consistent with normal grieving and adversity followed by resilient recovery. There is evidence of a gradient in saliency and complexity between self-portraits and related and unrelated portraits, of a less formal style in portraits of related others and of a ‘late’ style identified by leading art historians consistent with macular degeneration. The results are also consistent with an association of aesthetic preference with mid-level fractal values tending towards the Golden Mean long associated with beauty in nature and in art.

Aimed to obtain purple garlic varieties, 360 bolting bulbs from the Protected Geographical Indication (PGI) “Las Pedroñeras” were selected for their size, and the presence of abundant external scales. After a further selection, 243 out of the 360 bulbs were discarded due to undesired characteristics, as light purple color, high number of small cloves, cloves affected by Fusarium spp. and mites, among other. It was stablished that each bulb would give rise to a family. Thus, 117 families were planted under a random design during season 2021-2022. Either physiological, morphological and phenological traits were assessed for each family, and the affectations by pest and pathogens were also controlled. After the assessment of this trial, 103 out 117 families remained in the program, and were used for the establishment of a second trial the next season. Unlike the first trial, after the evaluations only 23 families remained in the program. There was observed a high variability for most of traits, with a great influence of families. The phenotypic behavior of families was significative influenced by environment, highlighting the need of their assessment under different environmental conditions. The high variability registered for the target sample, opens the possibility to select new garlic varieties from this PGI.

Nowadays, considering the growing tendency of companies towards e-commerce as well as green production, and dual-channel green supply chain management has become particularly important. This paper investigates pricing decisions within a dual-channel green supply chain framework while considering the capital constraints faced by risk-averse manufacturer. Simultaneously, the impact of the degree of risk aversion, consumer green preferences, and channel preferences on the optimal decision-making process of green supply chain members is analyzed. We address the issue of financial constraints faced by manufacturer through bank loans and trade credit financing and compare the two cases. Our findings illustrate that trade credit financing outperforms bank loan financing in the dual-channel green supply chain. Moreover, pricing decisions under different models are influenced by consumer preferences and risk aversion. Specifically, the greenness of the product, wholesale price, and sale price exhibit negative correlations with manufacturers' risk aversion but positive correlations with consumer preferences.

Mushroom cultivation vastly improves the yield of mushrooms under optimized, controlled conditions, but may be susceptible to opportunistic colonization by pest species that can establish themselves, as well as the pathogens and pests they may transmit. Here we describe our investigation into the bacterial communities of adult Lycoriella ingenua (Diptera: Sciaridae) and Megaselia halterata (Diptera: Phoridae) collected from button mushroom (Agaricus bisporus) production houses in Pennsylvania. We collected adult flies and sequenced the hypervariable v4 region of the bacterial 16S rRNA using the Illumina MiSeq. The most abundant bacterial genus detected in both species was Wolbachia, but phylogenetic analysis revealed that the infections are from different clades. Future studies include the characterization of Wolbachia infections on fly behavior and biology, comparison of microbial diversity of fly species colonizing wild mushrooms, and other microbiota that may contribute to the success of certain pest fly species.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Prenylated flavonoids of Humulus lupulus L. have gained attention for their potential health benefits. In this study, Amber ALE and Russian Imperial Stout beers were prepared. In order to increase the content of prenylated flavonoids in beer, there was added ethanol extract of Polaris hops, they were dry hopping with Polaris hops or pure xanthohumol was added. In unfiltered beers, the highest total content of polyphenols (3.60 ± 0.32 g/L gallic acid) was determined on the eighth day of fermentation and maturation in Amber ALE beer without the addition of extract. The highest total antioxidant capacity was determined in Russian Imperial Stout beer with the addition of xanthohumol on the eighth day of fermentation and maturation (0.675 ± 0.008 mmol/L Trolox). This type of beer also had a high antioxidant efficiency (85.96 - 88.00%). Xanthohumol (2.05 mg/L) and isoxanthohumol (2.819 mg/L) were detectable only until the thirteenth day of fermentation and beer maturation. Therefore, the beers were filtered, and the ethanol extract of the Polaris was added to them for 24 hours. This procedure was used to prepare a functional beer of the Amber ALE type (15.210 ± 0.053 mg xanthohumol in 1 L and 0.922 ± 0.077 mg isoxanthohumol in 1 L) and a functional beer of the Russian Imperial Stout type (32.375 ± 0.032 mg xanthohumol in 1 L and 1.877 ± 0.043 mg isoxanthohumol in 1 L).

Laser-targeted weeding methods further enhance the sustainable development of green agriculture, with one key technology being the improvement of weed localization accuracy. Here, we propose an improved YOLOv8 instance segmentation based on bidirectional feature fusion and deformable convolution (BFFDC-YOLOv8-seg) to address the challenges of insufficient weed localization accuracy in complex environments with resource-limited laser weeding devices. Initially, by training on extensive datasets of plant images, the most appropriate model scale and training weights are determined, facilitating the development of a lightweight network. Subsequently, the introduction of the Bidirectional Feature Pyramid Network (BiFPN) during feature fusion effectively prevents the omission of weeds. Lastly, the use of Dynamic Snake Convolution (DSConv) to replace some convolutional kernels enhances flexibility, benefiting the segmentation of weeds with elongated stems and irregular edges. Experimental results indicate that the BFFDC-YOLOv8-seg model achieves a 4.9% increase in precision, an 8.1% increase in recall rate, and a 2.8% increase in mAP50 value to 98.8% on a vegetable weed dataset compared to the original model. It also shows improved mAP50 over other typical segmentation models such as Mask R-CNN, YOLOv5-seg, and YOLOv7-seg by 10.8%, 13.4%, and 1.8%, respectively. Furthermore, the model achieves a detection speed of 24.8 FPS on the Jetson Orin nano standalone device, with a model size of 6.8MB that balances between size and accuracy. The model meets the requirements for real-time precise weed segmentation, suitable for complex vegetable field environments and resource-limited laser weeding devices.

Nowadays, microfluidics has become an anarchist interdisciplinary topic with considerable attention in a wide range of biotechnology applications. In this research work, numerical investigation of microfluidic micro-mixer is carried out using hybrid actuation approach with different micropillar shapes and gaps. For this purpose, COMSOL Multiphysics is used with three different physics such as thermoviscous acoustic to solve acoustic governing equations, laminar physics is used to solve fluid flow governing equations and diluted transport species is used to solve mixing governing equations. The simulations were carried out with flow velocity of 200 µm/s at both inlets with an oscillation frequency of 15kHz. The outcomes were in the form of acoustic characteristics such as acoustic pressure, acoustic velocity, acoustic streaming and mixing index. The results revealed that the inclusion of micropillars enhanced the mixing performance and strength of acoustic field resulting in improvement of mixing performance compared to the case without micropillars. In addition, it was also investigated that blade shape micropillars with 0.150 mm gaps deliver best results compared to the other cases with maximum and minimum values of the mixing index 0.95 and 0.72 respectively. The obtained results can be extremely helpful for design and modifications of hybrid microfluidics micro-mixer.

Infection with the malaria parasite Plasmodium, remains a major cause of illness and death world-wide. The development of evasion strategies by the parasite from host immunity and its adaptability to antimalarial drugs has raised the urgency for developing new strategies to combat this disease. One promising avenue is targeting telomeres – sequences found at chromosome termini– and telomerase – the enzyme that catalysis synthesis of telomeres using an intrinsic RNA template. As telomeres shorten critically, cells undergo replicative senescence or apoptosis. Plasmodium, lacking telomerase activity in its human stages, exploits alternative mechanisms, accelerating telomere shortening, aging, and immune evasion. Chemical telomerase inhibitors show promise as antimalarials. In this review, we examine the potential of targeting this system in malaria therapy, with telomerase inhibitors offering a novel approach. A systematic search on PubMed using Boolean techniques identified 246 relevant articles from 1985 to March 31, 2024. After filtering, 43 articles met inclusion criteria, supplemented by snowball sampling. The telomerase inhibitor drug strategy is widely applicable against cancer. However, given the drugability of telomerase and the absolute requirement for active telomere maintenance in the vast majority of parasites including plasmodium, telomerase and telomere maintenance could well represent the Achilles heel of the parasite

Background: People with Down syndrome (DS) have a trisomy of chromosome 21 and marked deficits in verbal memory but relatively preserved visuospatial perception. Verbal memories are related to semantic knowledge. Little is known about the organization of semantic knowledge in people with DS, which was the aim of this study. Aims: The extent of false memory in people with DS was examined. Possible differences in the number of false memories induced by nominal and verbal themes were examined. Methods and Procedures: In the study phase, ten word lists with semantically related associates were presented. In the recognition phase, participants made judgments on whether each word had been represented previously as semantically related lures, old words, and semantically unrelated new words. Outcomes and Results: Differences in the processing of nominal and verbal theme-related lures were observed among people with DS. When processing nominal theme-related lures, people with DS showed delayed false positives. When processing verbal theme-related lures, people with DS showed no differences compared to controls. Similar patterns have been observed in people with DS when processing nominal theme-related associates and verbal theme-related associates. People with DS have delayed recognition of associates. When processing unrelated words, they showed significantly higher false positives than controls for both nominal and verbal eliciting themes. Further analyses of the themes revealed differences in false positives across syntactic categories among groups. Conclusions and Implications: People with DS showed a delayed recognition of associates and deviance in recognizing unrelated words in the nominal and verbal theme categories. People with DS were delayed in terms of nouns, but deviated with verbs in associated and unrelated words. Additionally, people with DS showed distinct patterns in processing five nominal lures and three verbal lures, suggesting that they formed false memories differently based on distinct syntactic categories. Thus, it was concluded that people with DS develop a deviant semantic structure. Category-based interventions for people with DS should be implemented in order to improve their semantic knowledge through lexical connections.

This study uses a mass-spring-damping system to simulate the repeated strain of liquefaction cyclic triaxial tests. The two results are compared in this paper to understand the feasibility of the mass-spring-damping system developed in this paper and the feasibility of future research on this related topic and development potential. The main factors affecting this mode's repeated strain are the spring coefficient k and the external force Q0. The spring coefficient has an inverse relationship but does not increase in multiples. The external force has a direct proportional relationship but does not increase the result- a non-multiple increase. When the pore water pressure of the liquefied cyclic triaxial test specimen rises, it will cause the specimen to liquefy, decreasing effective stress, shear modulus G, and damping ratio D, causing an increase in strain. The shear modulus and damping ratio are related to the spring coefficients k and c. Both are variables that change with time. This article takes an original thin-tube specimen at point A in the Yunlin area in Taiwan as a testing example. Through Mathematica software, it can be obtained that the mass m=1kg, the spring coefficient k=244e-0.1t kgf/cm, and the damping coefficient c=0.739e-0.257t kgf-s/cm and external force Q0=10.1sin2πt kg; Finally, this study selected the original thin-tube specimens from four locations in the Yunlin area, and simulated the repeated strain amount of the cyclic triaxial test specimens through a spring-damping system. The results show that the spring-damping system is feasible for simulated cyclic triaxial tests because the model is simple and the parameters are easy to understand and obtain, which also shows the extensibility of this model. Preliminary results of the research show that this model can further simulate the repeated strain obtained by cyclic triaxial tests without considering the increased trend in pore water pressure and the decrease in effective stress during cyclic loading.

The paper presents an error model of a measurement chain containing link performing discrete wavelet transform algorithm which is most often the last stage of measurement signal processing. The goal is to determine the uncertainty budget of the input quantities of the wavelet transform algorithm. The error model takes into account parts of analog, analog-to-digital and digital processing, describing the properties of subsequent fragments of the chain using their transmittance and processing functions. The proposed model enables the description of both deterministic and non-deterministic properties of signal errors. The proposed model was validated using an example measurement chain created for this purpose.

Hybrid materials are a recent addition in the field of Restorative Dentistry for computer-assisted design/ computer-assisted manufacturing (CAD/CAM) indirect restorations. The long–term clinical success of modern dental restorative materials follows a multifactorial pattern. Among the characteristics, affecting the longevity of a restoration, mechanical properties and physicο – chemical interactions are of utmost importance. While numerous researchers constantly evaluate the mechanical properties, the biological background of resin–based CAD/CAM biomaterials is scarcely investigated and, therefore, less described in the literature. This review aims to analyze the biofilm formation on the surfaces of novel hybrid, resin–based CAD/CAM materials and evaluate the methodological protocols followed to assess microbial growth. It is demonstrated that the surface structure, the composition and the finishing and polishing procedures on the surface of a dental restorative material influence the initial bacterial adhesion; however most studies focus on in vitro protocols, whereas in vivo and/or in situ research of microbiomics in CAD/CAM restorative materials is lacking, obstructing in that manner the accurate understanding of the bioadhesion phenomenon in the oral cavity.

Optical backbone networks constitute the fundamental infrastructure employed today by network operators to deliver services to users. As network capacity is a key factor influencing optical network performance, it is important to understand how topological and physical properties impact its behavior and to have the capability to estimate its value. In this context, we propose here a method to evaluate the network capacity that relies on the optical reach to account for physical layer aspects, in conjunction with constrained routing techniques for traffic routing. As this type of routing can lead to traffic blocking, particularly due to the limitation on the number of wavelengths per fiber, we also propose a fiber assignment algorithm designed to deal with this problem. We apply this method to a set of randomly generated networks using a modified Waxman model, and for a network with 60 nodes, in a scenario without blocking, we obtain capacities of about 2.5 Pbit/s for a symbol rate of 64 Gbaud and about 5 Pbit/s for a symbol rate of 128 Gbaud. Remarkably, this duplication in the total network capacity is achieved by an increase in the total fiber length of only about 51%.

Aerial image classification has become popular and has attracted extensive research efforts in recent decades. The main challenge lies in its very high spatial resolution but relatively insufficient spectral information. To this end, spatial-spectral feature extraction is a popular strategy for classification. However, parameter determination for that feature extraction is usually time-consuming and depends excessively on experience. In this paper, an automatic spatial feature extraction approach based on image raster and segmental vector data cross-analysis is proposed for the classification of very high spatial resolution (VHSR) aerial imagery. First, multi-resolution segmentation is used to generate strongly homogeneous image objects and extract corresponding vectors. Then, to automatically explore the region of a ground target, two rules, which are derived from Tobler’s First Law of Geography (TFL) and a topological relationship of vector data, are integrated to constrain the extension of a region around a central object. Third, the shape and size of the extended region are described. A final classification map is achieved through a supervised classifier using shape, size, and spectral features. Experiments on three real aerial images of VHSR (0.1 to 0.32 m) are done to evaluate effectiveness and robustness of the proposed approach. Comparisons to state-of-the-art methods demonstrate the superiority of the proposed method in VHSR image classification.

In multi-objective optimization problems, the optimization target is to obtain a set of non-dominated solutions. Comparing solution sets is crucial in evaluating the performances of different optimization algorithms. The use of performance indicators is common in comparing those sets and, subsequently, optimization algorithms. A good solution set must be close to the Pareto-optimal front, well-distributed, maximally extended and fully filled. Therefore, an effective performance indicator must encompass these features as a whole and must be Pareto dominance compliant. Unfortunately, some of the known indicators often fail to properly reflect the quality of a solution set or cost a lot to compute. This paper demonstrates that the Degree of Approximation (DOA) quality indicator, is a weakly Pareto compliant unary indicator that gives a good estimation of the match between the approximated front and the Pareto-optimal front. Moreover, DOA computation is easy and fast.

As the natural resources are getting exhausted, the concept of sustainable development of region has received increasing attentions, especially for resource-dependent cities. In this paper an innovative method that emergy analysis and IPAT (Human Impact Population Affluence Technology) model were combined in order to analyze the quantitative relationship of economic growth and energy consumption and further to evaluate its overall sustainability level. Taiyuan, a traditional, resource-dependent city in China, is selected as the case study region. The main results show that total emergy of Taiyuan increased from 9.023× 1023 sej in 2007 to 9.116× 1023sej in 2014, with 38% reduction on non-renewable emergy and 125% growth on imported emergy. Regional emergy money ratio (RMB) was reduced by 48% from 5.31× 1013sej/$ in 2007 to 2.74× 1013sej/$ in 2014, indicating that the increasing speed of consuming resources and energy was faster than the increase of GDP, and that Taiyuan’s money purchasing power declined. The lower emergy sustainability index (ESI) indicates that Taiyuan was explored and produced large quantities of mineral resources, which puts more stress on the environment as a consequence, and that this is not sustainable in the long run. The IPAT analysis demonstrates that Taiyuan sticks to the efforts of energy conservation and environmental protection, in order to promote regional sustainable development, it is necessary to take an integrated effort. Policy insights suggest that resourceful regions should improve include energy and resource efficiency, optimizing energy and resourceful structure.

Metal-reinforced polymethyl-methacrylate (PMMA) is considered the gold standard material for immediate loading on dental implants. However, mechanical problems under loading cycles can occur, such as fractures. To overcome these drawbacks, a novel polymer-based material has been proposed. The aim of the present in vitro comparative research is to validate a novel composite polymer developed to replace metal-reinforced PMMA interim restoration due to its advantages of good mechanical proprieties, easier manufacturing, and handling. Ten interim restorations were CAD/CAM designed and fabricated (five in the composite "ONLY" group, and five in the metal-reinforced PMMA group). All the samples were screwed into the prototype models, simulating a complete edentulous mandible rehabilitated with six straight implants. Outcome measures were breakpoint (load, N) and displacement (mm) thought a static, compression test and material behavior under dynamic cyclic test method (fatigue test). A total of twenty samples were tested. Ten samples were used for each test (10 for static and 10 for dynamic), five samples were used in each group (test and control). All the specimens completed the mechanical tests, as planned. There was no statistically significant difference between groups for all, breakpoint, displacement and fatigue tests. Breakpoint in the test group was 1953.19 ± 543.73 N, while, it was 2031.10 ± 716.68 N in the control group, with no statistically significant difference (P=0.775). The displacement was 1.89 ± 0.34 mm in the test group and 1.98 ± 0.75 mm in the control group, again, with no statistically significant difference (P=0.763). Under dynamic cyclic test method, in the control group the mean load was 2504.6 ± 972.15 N, while, in the test group the mean load was 3382 ± 578.5 N. The difference between group was 877.4 ± 579.3 N (p value=0.121). With the limitation of this in vitro study, the novel composite polymer can be used to immediately load dental implants. Further clinical researches are needed to confirm this preliminary results.

In arid and semi-arid regions like Tunisia, irrigation water is typically saline, posing a soil and crop salinization risk and yield reduction. This research aims to study the combined effects of soil matric and osmotic potential stresses on tomato root water uptake. Plants were grown in pot and field experiments in loamy-clay soils and were irrigated with three different irrigation water qualities: 0, 3.5, and 7 dS/m. The Hydrus-1D model was used to simulate the combined dynamics of subsurface soil water and salts. Successful calibration and validation of the model against measured water and salt profiles enabled the examination of the combined effects of osmotic and matric potential stresses on root water uptake. Relative yields, indirectly estimated from actual and potential transpiration, indicated that the multiplicative stress response model effectively simulated measured yields and the impact of saline water irrigation on crop yields. The gradual salinization of the root zone further evidenced this effect. The scenario considering a temperature increase of 2°C had no significant impact on crop yields in the pot and field experiments.

Glycerol represents a useful functional component of heat-transfer fluids. Glycerol is known to be triboelectrically active. We report how the flow of glycerol, stopped in a cylindrical coiled pipe, influences horseradish peroxidase (HRP) enzyme. Namely, glycerol flow was pumped through the coil and then stopped. After that, we incubated the 0.1 µM solution of HRP near the side of the coil, and then adsorbed HRP onto mica. This operation markedly increased the HRP aggregation on mica in comparison with the control sample. We explain this phenomenon by the influence of triboelectrically induced electromagnetic fields. Our results can be useful in the development of flow-based systems for biosensors and bioreactors.

To date, the development of unmanned technologies using autonomous underwater vehicles (AUV) has become an urgent demand for solving the problem of inspection of industrial sub-sea structures. A key issue here is precise localization of AUVs relative to underwater objects. However, the well-known challenges of recognizing and coordinating underwater objects (impossibility to use GPS, undercurrents, etc.) do not allow high-precision navigation if based solely on a standard suite of AUV navigation tools (sonars, etc.). An alternative is a technology of processing of optical images that, at short distances, can provide higher accuracy of AUV navigation compared to a technology of acoustic measurement processing. In this study, in the context of the problem of subsea production system inspection, we propose a method to recognize underwater objects and provide coordinate reference of AUV to them, based on stereo-image processing. Its distinctive features are the use of a non-standard technique for generating a geometric model of an object from its views (foreshortening) taken from positions of a pre-made overview trajectory, the use of various characteristic geometric elements when recognizing objects, and the original algorithms for comparing visual data of the inspection trajectory with an a priori model of the object.

The extensive utilization of drones has led to numerous scenarios that encompass both advantageous and perilous outcomes. By using deep learning techniques, it is aimed to reduce the dangerous effects of drone use through early detection of drones.The state of the art of the study is evaluation of deep learning approaches such as pre trained YOLOv8 drone detection for security issues. In this study, dataset collected by Mehdi Özel for a UAV competition are sourced from GitHub. These images are labeled using Roboflow, and the model is trained on Google Colab. To enhance model performance, dataset augmentation techniques including rotation and blurring are implemented. Following these steps, a significant precision value of 0.946, a notable recall value of 0.9605 and a considerable precision-recall curve value of 0.978 are achieved, surpassing many popular models such as Mask CNN, CNN, and YOLOv5.

Nucleation is a fundamental and general process at the initial stage of first order phase transition. Although various models based on the classical nucleation theory (CNT) have been proposed to explain the energetics and kinetics of nucleation, detailed understanding on nanoscales are still required. Here we focus on homogeneous bubble nucleation, in which evaluation of the size dependence of bubble free energy is the key issue. We propose application of a formula in stochastic thermodynamics, the Jarzynski’s equality, for data analysis of molecular dynamics (MD) simulation to evaluate the free energy of bubble nucleation. As a test case, we performed a series of MD simulations with Lennard-Jones (LJ) fluid system. By applying an external spherical force field to equilibrated LJ liquid, we evaluated the free energy change during bubble growth as the Jarzynski’s ensemble average of required works. A fairly smooth free energy curve was obtained as a function of bubble radius in metastable liquid of mildly negative pressure conditions.

This study examines geothermal energy extraction potential from the basement rock within the Denver-Julesburg (DJ) Basin, focusing on flow performance and heat extraction efficiency of different geothermal well configurations. It specifically compares U-Shaped, V-Shaped, Inclined V-Shaped, and Pipe-in-Pipe configurations against Enhanced Geothermal Systems (EGS) setups. Through numerical modeling, we evaluated the thermal behavior of these systems under various operational scenarios and fracture conditions. Results suggest that while closed-loop systems offer moderate temperature increases, EGS configurations show substantial potential for high-temperature extraction. This underscores the importance of evaluating well configurations in complex geological settings like the DJ Basin. The insights from this study aid in strategic geothermal energy planning and development, marking significant advancements in geothermal technology and setting a foundation for future explorations and optimizations.

The Asian clam Corbicula fluminea is a native aquatic species in Eastern Asia and Africa but has become one of the most ecologically and economically harmful invasive species in aquatic ecosystems in Europe, North America, South America. Due to their natural characteristics as a hermaphroditic species with high fecundity and dispersal capacity, Asian clams are extremely difficult to eradicate once they have infiltrated a waterbody. This is an emerging issue for states in the Northeastern United States as Asian clams expand their range farther North due to climate change. There has been extensive research conducted to develop chemical treatments to reactively control invasive mollusc populations and proactively prevent their further spread. However, treatments are mostly targeted toward biofouling bivalves in industrial settings. A comprehensive review of Asian clam chemical treatments used in open water systems was performed to evaluate molluscicides and identify toxicity ranges of emerging treatments that maximize Asian clam mortality and minimize negative impact to water quality and non-target species. The potential chemical applications in Asian clam control and management are summarized in this report to assist resource managers and practitioners on invasive Asian clam management.

In this study, global response analysis was performed to explore the mechanism of action of Usnic acid and its synergy with Norfloxacin, a well-known quinolone antibiotic to which MRSA clinical isolates showed resistance (MIC, 500 µg/mL). Microdilution assay, growth kinetics, microscopic analysis, and cell-based assays consistently showed that Usnic acid possess strong anti-staphylococcal activity (MIC, 7.8 µg/ml), causes cell leakage, modulates efflux pump activity, and synergizes with Norfloxacin against multi-drug resistant clinical isolate MRSA 2071. Whole cell proteome profiling using gel-free based nano-LC-ESI-QTOF-MS/MS revealed several proteins whose expression was significantly modulated by Usnic acid and Norfloxacin alone or in combination. Usnic acid downregulated the abundance of RNA polymerase subunits (RpoB, RpoC), carbamoyl phosphate synthase large subunit (PyrAB), chaperone (GroEL), and adenylosuccinate synthetase (PurA). Interestingly, proteins found to be upregulated in the presence of Usnic acid and Norfloxacin included oxidative stress-related proteins such as peroxidase (Tpx), alkyl hydroperoxide reductase (AphC), and general stress protein (UspA). This study clearly showed that Usnic acid affects numerous cellular targets and can potentiate the action of Norfloxacin. Furthermore, an in-vivo study emphasized the use of Usnic acid to develop as a safe phytopharmaceutical to repurpose old antibiotics through combination therapy against MRSA infections.

Strip steel surface defect recognition research has important research significance in industrial production. Aiming at the problems of defect feature extraction difficulty, slow detection speed and insufficient dataset, YOLOv5 is improved on the basis of YOLOv5, and YOLO-LFPD (Lightweight fine particle detection) model is proposed. By introducing the RepVGG (Re-param VGG) module, the robustness of the model to the surface defect features of strip steel is enhanced, and the expressive ability of the model is improved. FasterNet is used to replace the backbone network, which ensures the accuracy and accelerates the inference speed, making the model more suitable for real-time monitoring. The use of pruning, GA genetic algorithm with OTA loss function method further reduces the model size while better learning the strip steel defect feature information, thus improving the generalisation ability and accuracy of the model. The experimental results show that the introduction of the RepVGG module and the use of FasterNet can well improve the model performance, with a reduction of 48% in the number of parameters, a reduction of 13% in the number of GFLOPs, an inference time of 77% of the original, and an optimal accuracy compared with the network models in recent years. The experimental results on the NEU-DET dataset show that the accuracy of YOLO-LFPD is improved by 3% to 81.2%, which is better than other models, and provides new ideas and references for the lightweight strip steel surface defect detection scenarios and application deployment.

Graph Neural Networks (GNNs) are powerful models capable of managing intricate connections in non-Euclidean data, such as social networks, physical systems, chemical structures, and communication networks. Despite their effectiveness, the large-scale and complex nature of graph data demands substantial computational resources and high performance during both training and inference stages, presenting significant challenges, particularly in the context of embedded systems. Recent studies on GNNs have investigated both software and hardware solutions to enhance computational efficiency. Earlier studies on Deep Neural Networks (DNNs) have indicated that methods like reconfigurable hardware and quantization are beneficial in addressing these issues. Unlike DNN research, studies on efficient computational methods for GNNs are less developed and require more exploration. This survey reviews the latest developments in quantization and FPGA-based acceleration for GNNs, showcasing the capabilities of reconfigurable systems (often FPGAs) to offer customized solutions in environments marked by significant sparsity and the necessity for dynamic load management. It also emphasizes the role of quantization in reducing both computational and memory demands through the use of fixed-point arithmetic and streamlined vector formats. This paper concentrates on low-power, resource-limited devices over general hardware accelerators and reviews research applicable to embedded systems. Additionally, it provides a detailed discussion of potential research gaps, foundational knowledge, obstacles, and prospective future directions.

Despite the effectiveness of insulin injections in managing hyperglycemia in Type 1 Diabetes, they fall short in addressing autoimmunity and regenerating damaged islets. This review aims to explore the potential of various treatment modalities for T1DM, including mesenchymal stem cells (MSCs), MSC-derived exosomes, gene therapy, islet allotransplantation, and pancreatic islet cell transplantation. Results: MSCs demonstrate efficacy in T1DM treatment through immunomodulation and tissue regeneration, although further research is warranted to optimize their therapeutic potential. Gene therapy presents a promising approach despite challenges such as donor shortage and immune rejection. Pancreatic islet cell transplantation emerges as a viable option, albeit with associated risks including graft rejection and the need for immunosuppression. Teplizumab, an FDA-approved humanized monoclonal antibody, revolutionizes the treatment landscape of Type 1 Diabetes by significantly delaying its onset, offering a paradigm shift since the discovery of insulin Conclusion: Ongoing studies and technological advancements in T1DM management offer a promising outlook for improved treatments and possibly even eradication on a global scale. MSCs, MSC-derived exosomes, gene therapy, and pancreatic islet transplantation hold considerable potential.

The digital transformation in Industry 4.0 has revolutionized quality control paradigms, integrating advanced technologies such as augmented reality, deep learning, and computer vision systems into a new era called "Quality 4.0". This study systematically reviews how these technologies are shaping new practices in continuous quality supervision and improvement, adapting to increasingly automated and connected production environments. Through a comprehensive analysis of the literature, practical applications in various industrial sectors, from manufacturing and agriculture to the production of sweets and snacks, are highlighted. Additionally, the conceptual and detailed design of a quality control system using artificial intelligence tools is presented, focusing on the inspection of dimensions, color, weight, and labeling of MDF boxes. The proposed system demonstrates an effective integration of sensors, high-definition cameras, and deep learning algorithms, validated through tests with boxes of different sizes. The results suggest that the adoption of these technologies not only improves the accuracy and efficiency of inspections but is also essential to maintaining high-quality standards in a dynamic and competitive industrial environment.

This paper presents a wideband dual-polarized dipole antenna structure operating at 1.7-3.8 GHz (76.4%). For a traditional 4G dipole antenna which covers the band 1.71 GHz- 2.69 GHz, it’s difficult to maintain the satisfactory impedance matching and normal stable radiation patterns within the 5G sub-6 GHz band 3.3-3.8 GHz, which mainly due to the fixed antenna height is no longer a quarter-wavelength. To solve this, a connected-ring-shaped metasurface structure is proposed and deployed to operate as an artificial magnetic conductor (AMC). As a result, stable antenna radiation patterns are obtained within the whole band 1.7-3.8 GHz. For verification, this wideband dipole antenna using AMC is implemented and tested. The measured results show that the proposed antenna has an impedance bandwidth of 80.7% (1.7-4.0 GHz). It has an average measured in-band realized gain of 7.0±1.0 dBi and a stable 70∘±5∘ half power beam width (HPBW) within the 4G/5G-sub 6GHz bands 1710-2690 MHz and 3300-3800 MHz.

This bibliometric analysis delves into the realm of botanical gardens through the process of mapping literature and discerning research frontiers, underlying themes, and interconnections within the extant body of knowledge. The study uses a dataset of 1340 publications and employs methodologies such as authors' keywords co-occurrence data to examine the discipline's trends, patterns, and knowledge gaps. The study finds significant growth in literature from 1960 to 2023, emphasizing botanical gardens, conservation, taxonomy, biodiversity, ex-situ conservation, and diversity. Key influencers such as Sanja Kovačić, Elaissi, and Chemli have steered research directions towards ex-situ conservation and essential oils, reflecting the field's interdisciplinary nature. The study shows global institutional variation, with entities like the Chinese Academy of Sciences, the Royal Botanic Gardens UK, and the New York Botanical Garden US leading the discourse. Thematic analyses have identified core themes and emerging research topics, with ecological restoration, essential oils, invasive species, and climate change mirroring the field's expanding scope. The consistent prevalence of themes such as 'botanical gardens' and 'conservation' over time underscores their enduring significance. Emerging topics like climate change and biodiversity are gaining prominence, signaling a shift in research priorities. The expanding array of subjects, including 'invasive species' and 'genetic diversity,' indicates an amplified scope and growing complexity in botanical garden research. This study aims to bridge a crucial gap by outlining the developmental trajectory of botanical gardens and offering guidance for future research directions. Diverse research domains within botanical garden studies, including biodiversity, essential oils, taxonomy, and ex-situ conservation, present extensive avenues for exploration. Future research endeavors should delve into these impactful themes to better understand botanical ecosystems and their conservation. The study emphasizes the importance of nurturing interdisciplinary collaborations and multidisciplinary projects, advocating for a comprehensive and collaborative approach to future research in botanical garden studies.

The paper presents a proposal for an in-house mathematical model of a liquid flat-plate solar collector. The proposed model is a one-dimensional distributed parameter model enabling simulations of the collector operation under arbitrarily variable boundary conditions. The model is based on the solution of energy balance equations for all components of the collector. The formulated differential equations are solved iteratively using an implicit difference scheme. In order to obtain a stable numerical solution, it is necessary to use appropriate steps of the time and spatial division. These were found by comparing the results obtained from the model with the results of the analytical solution available in the literature for the transient state, which constitutes the novelty of the present study. The accuracy of the results obtained from the model was verified experimentally by comparing the measured and the calculated history of the fluid temperature at the outlet of the collector. The calculation of the collector time constant is proposed in the paper as an example of the model practical application. The results of the time constant calculation were compared with the values obtained experimentally on the test stand. This is another novelty of the presented research. The analysed collector instantaneous efficiency was then calculated for selected outdoor conditions. The presented mathematical model can also be used to verify the correctness of the collector operation. Comparing, on an ongoing basis, the measured and the calculated values of the fluid temperature at the collector outlet, conclusions can be drawn about the process of solar glass fouling or glycol gelling. The model's simplicity and the low computational demands enable such comparisons in an online mode.

This research investigates the application of Fused Filament Fabrication (FFF) in producing WC-10Co hardmetals, focusing binder formulations and understanding its influence on extrusion force and the influence of printing variables on green density of the samples. By examining the interplay between different binder compositions and backbone contents, the study aims to enhance the mechanical properties of the sintered parts while reducing defects inherent in the printing process. Evidence suggested that formulated feedstocks influenced the hardness of the sintered hardmetal, not due to microstructural changes but to macrostructural responses like macro defects introduced during printing, debinding and sintering of the samples. The results demonstrate the critical role of PP-MA content in improving part density and sintered hardness, suggesting the need for specific thermal debinding protocols tailored to each feedstock. The study provides insights into the formulation of feedstocks for hardmetal FFF, proposing a path toward refining manufacturing processes for better quality and performance of 3D printed hardmetal components.

This study aimed to develop a laboratory-scale direct air capture unit for evaluating and comparing amine-based adsorbents under temperature vacuum swing adsorption conditions. The experimental campaign conducted with the direct air capture unit allowed for the determination of equilibrium loading, CO2 uptake capacity, and other main performance parameters of the investigated adsorbent Lewatit VP OC 1065®. The investigations also helped to understand the co-adsorption of both CO2 and H2O on the tested material, which is crucial for improving temperature vacuum swing adsorption processes. This was achieved by obtaining pure component isotherms for CO2 and H2O as well as three different co-adsorption isotherm models from literature. It was found that the weighted average dual-site Toth model emerged as the most accurate and reliable model for simulating this co-adsorption behavior. Its predictions closely align with experimental data, particularly in capturing the adsorption equilibrium at various temperatures. It was also observed that this lab-scale unit offers advantages over thermogravimetric analysis when conducting adsorption experiments on the chosen amine. The final aim of this study is to provide a pathway to develop devices for testing and developing efficient and cost-effective adsorbents for direct air capture.

Plants support numerous microorganisms within their tissues and the rhizosphere, and these microorganisms, known as the microbiota, can influence plant growth and health. Up to 40% of a plant's photosynthetic metabolism may be invested in the rhizosphere. The microbiota is considered an extra genome that can be modulated to meet plant needs. Researchers have identified a set of genes from these microorganisms, known as the microbiome, which can be manipulated to enhance plant growth and health, improve nutrient absorption, reduce the need for chemical fertilizers, increase resistance to pathogens and pests, and increase stress tolerance. In particular, fungi exhibit large genetic and metabolic diversity and are often used to promote plant growth. For example, the fungus Purpureocillum lilacinum has been employed primarily as a biocontrol agent to manage nematodes, but some studies have suggested that it may also promote plant growth by increasing the efficiency of the plant to absorb nutrients from the soil and provide phytohormones to plants. Therefore, the current review aims to summarize the existing literature on the use of this fungus in agriculture as nematodes control and discuss its potential as a plant growth promoter.

Exploring for green and affordable protection of perishable fruit like cherry tomato is of significance. Here the protective efficacy and its underpinnings of coating with oleaster gum, alone or incorporated with cuminal, on cherry tomatoes stored at ambient temperature were investigated. The composite coating of oleaster gum with 0.1% cuminal reduced decay, respiration rate, weight loss, and softening of the fruit and decelerated their decreases of total soluble solids, titratable acidity, and soluble proteins, and therefore maintained their marketability. Furthermore, it reduced the accumulation of O•− 2and H2O2 in fruit, and mitigated cell membrane lipid oxidation and permeabilization, thereby retarding their senescence. Instrumentally, it elevated the activities of superoxide dismutase, catalase, peroxidase, and ascorbate peroxidase and the levels of ascorbic acid and glutathione. This potentiation of the fruit antioxidant system makes the composite coating a promising approach to keeping the postharvest quality of perishable fruit.

The impact of the agriculture net carbon effect is crucial for climate change mitigation, yet research on this topic in China is currently insufficient. In this study, the carbon balance ratio (CBR) is used to characterise the net carbon effect of agriculture, and the spatial Durbin model and threshold regression model were used to empirically analyse the CBR with a sample of 30 provincial-level regions in China from 2004 to 2019. The aim was to investigate the mechanism of the influence of the land management scale (SCALE) of farming on the CBR. The results of the study indicate that national farming generally has a net sink effect, with large changes in interannual fluctuations; the expansion of SCALE has an obvious role in increasing sinks and reducing emissions, and has a positive spatial spillover effect on CBR, with significant spatial heterogeneity. Furthermore, as the SCALE expands, the direction of the influence of rural residents’ income and education level on CBR changes in the opposite direction, showing a significant non-linear relationship characteristic. However, in most areas, the SCALE threshold has not yet been reached, suggesting that the improvement in education levels can still offset the negative impact of economic income growth in the short term. The study recommends paying attention to the role of farmers’ human capital, changing production methods, and implementing carbon peaking and carbon neutrality goals to enhance the net sink effect of the farming industry, which would be achieved by increasing land management scale.

This study presents an innovative approach for the utilization of industrial by-products and municipal waste in the production of sustainable and environmentally friendly cement mortar. We explored stabilized stainless-steel reduced slag (SSRS) and polyethylene (PE) plastic waste as partial replacements for aggregates. Various engineering properties of the resulting cement mortar specimens, including slump, slump flow, compressive strength, flexural strength, tensile strength, water absorption, and ultrasonic pulse velocity (UPV), were investigated through comprehensive experimental tests. The influence of different water-cement (w/c) ratios and substitution amounts on the engineering properties of the cement mortar samples was thoroughly examined. The findings revealed that an increase in PE substitution adversely affected the overall workability of the cement mortar mixtures, whereas an increase in SSRS amount contributed to enhanced workability. As for the hardened properties, a consistent trend was observed for both cases, with higher w/c ratios and substitution amounts leading to reduced mechanical properties. Water absorption and UPV test results validated the increased formation of porosity with higher w/c ratios and substitution amounts. This study proposes a promising method to effectively repurpose industrial by-products and municipal wastes, transforming them into sustainable construction and building materials. Additionally, a comparative analysis of transportation costs and carbon footprint emissions between SSRS-cement mortar and PE-cement mortar was conducted to assess their environmental impact and sustainability. Generally, higher w/c ratios and replacement levels corresponded to reduced carbon footprint. The geographical location of the source of SSRS and PE remains a challenge and studies to overcome this challenge must be further explored.

The application of artificial intelligence to point-of-care testing (POCT) disease detection has become a hot research field, in which breath detection which detects the patient's exhaled VOCs combined with sensor arrays of Convolutional Neural Network (CNN) algorithms as a new lung cancer detection is attracting more researchers' attention. However, due to low accuracy, high complexity computation and large number of parameters make the CNN algorithms difficult transplant to the embedded system of POCT devices. A lightweight neural network (LTNet) in this work is proposed to deal with this problem, and meanwhile, achieve high-precision classification of acetone and ethanol gases, which are respiratory markers for lung cancer patients. Compared to currently popular lightweight CNN models such as EfficientNet, LTNet has fewer parameters (32K) and its training weight size is only 0.155 MB. LTNet achieved an overall classification accuracy of 99.06% and 99.14% in the own mixed gas dataset and the University of California (UCI) dataset, which are both higher than that of the five existing models’, and it also offers the shortest training (844.38s and 584.67s) and inference time (23s and 14s) in the same validation set. Compared to the existing CNN models, LTNet is more suitable for resource-limited POCT devices.

A total of 473 metabolites were identified from 4 sour cherry genotypes using UPLC-TOF-MS. Untargeted metabolomics revealed the dominant chemical groups present in sour cherries. PCA showed that the diversity in sour-cherry metabolites was due to the genotype differences indicating iditol, malic acid, chlorobenzene, 2-mercaptobenzothiazole, and pyroglutamic acid as the predominant contributors. The variable importance in the projection (VIP > 1.0) in partial least-squares–discriminant analysis described 20 biomarker metabolites, representing the cherry metabolome profiles. A heatmap of Pearson’s correlation analysis between the 20 biomarker metabolites and antioxidant activities identified seven antioxidant determinants that displayed the highest correlations with different types of antioxidant activities. This study of correlating metabolomics and antioxidant activities elucidated that the higher nutritional value and biological functions of select sour cherry genotypes can be useful for the development of nutraceutical and functional foods.

An extensive thermodynamic study of N-methylformamide (CAS RN: 123-39-7) and N,N-dimethylformamide (CAS RN: 68-12-2), is presented in this work. The liquid heat capacities of N-methylformamide were measured by Tian–Calvet calorimetry in the temperature interval (250 – 300) K. The vapor pressures for N-methylformamide and N,N-dimethylformamide were measured using static method in the temperature range 238 K to 308 K. The ideal-gas thermo-dynamic properties were calculated using a combination of the density functional theory (DFT) and statistical thermodynamics. A consistent thermodynamic description was developed using the method of simultaneous correlation, where the experimental and selected titerature data for vapor pressures, vaporization enthalpies, and liquid phase heat capacities and calculated ide-al-gas heat capacities are treated together to ensure overall thermodynamic consistency of the results. Resulting vapor pressure equation is valid from the triple point to the normal boiling point temperature.

The effective Supervisory Control and Data Acquisition (SCADA) system can improve the reliability, safety and economic benefits of microgrid operation. In this research, the lower central controller and upper WEB monitoring system are connected by the SCADA system which is as the hub of microgrid intelligent monitoring platform. This system contains a set of specific functions programmed by Java as a middleware which can provide control and communication between the central controller and the upper monitoring system. The system realizes the real-time data acquisition and storage, the control instructions parsing and transmitting, the microgrid security and stability, the load balancing and resource recovery of the microgrid. All that functions have been tested and verified in the actual operation.

In order to overcome the limitation of the traditional adaptive Unscented Kalman Filtering (UKF) algorithm in noise covariance estimation for statement and measurement, we propose a hybrid adaptive UKF algorithm based on combining Maximum a posteriori (MAP) criterion and Maximum likelihood (ML) criterion, in this paper. First, to prevent the actual noise covariance deviating from the true value which can lead to the state estimation error and arouse the filtering divergence, a real-time covariance matrices estimation algorithm based on hybrid MAP and ML is proposed for obtaining the statement and measurement noises covariance, respectively; and then, a balance equation the two kinds of covariance matrix is structured in this proposed to minimize the statement estimation error. Compared with the UFK based MAP and based ML, the proposed algorithm provides better convergence and stability.

Aluminum wire is a common material for wire bonding due to its resistance to oxidation and low price. It does not melt when becoming a free air ball (FAB) during the electronic flame-off (EFO) process with wettability, and is applied by wedge bonding. This study used 20μm Zn-Coated Al-0.5wt.%Si (ZAS) wires to improve the FAB shape after the EFO process, while maintaining stability of the mechanical properties, including the interface bonding strength and hardness. In order to test circuit stability after ball bonding, the current-tensile test was performed. During the experiment, it was found that 80nm ZAS with wire bonding has lower resistance and higher fusing current. For the bias tensile test, the thicker Zn film diffused into the Al-Si matrix easily, after which the strength was reduced. The ball-bond interfaces had no change in their condition before and after the bias. Accordingly, ZAS could be a promising candidate for ball bonding in the future.

The main objective of this work is the assessment of the annual number of hospital admissions for respiratory disease (HARD) due to the exposure to in-healable particulate matter (PM10), within the greater Athens area (GAA), Greece. Towards this aim, the time series of the particulate matter with aerodynamic diameter less than 10μm (PM10) recorded in six monitoring stations located in the GAA, for a 13-year period 2001-2013, is used. Initially, a descriptive statistical treatment of PM10 concentrations took place. Furthermore, the AirQ2.2.3 software developed by the WHO was used to evaluate adverse health effects by PM10 in the GAA during the examined period. The results show that, during the examined period PM10 concentrations present a significant decreasing trend. Also, the mean annual HARD cases per 100,000 inhabitants ranged between 20 (suburban location) and 40 (city centre location). Approximately 70% of the annual HARD cases are due to city centre residents. In all examined locations, a declining trend in the annual number of HARD cases is appeared. Moreover, a strong relation between the annual number of HARD cases and the annual number of days exceeding the European Union daily PM10 threshold value was found.

In this article we compute many topological indices for the family of Möbius ladder. At first we give general closed form of M-polynomial of this family and recover many degree based topological indices out of it. We also compute Zagreb indices and Zagreb polynomials of this family.

In this paper we report a new development on the numerical model for aluminum-steam combustion. This model is based on diffusion flame of continuum regime and the thermal equilibrium between the particle and the flow field, which can be used to calculate the aluminum particle combustion model for two phase calculation conditions. The model prediction is in good agreement with the experimental data. A new type of vortex combustor was proposed for the combustion of aluminum and steam, and the mathematical model of the two phase reacting flow with in this combustor was established. The turbulence effects are modeled using the Reynolds Stress Model (RSM) with Linear Pressure-Strain approach, and the Eddy-Dissipation model is used to simulate the gas phase combustion. Aluminum particles are injected into the vortex combustor and form a swirling flow around the chamber and their trajectories are traced using the Discrete Phase Model (DPM). The simulation results show that the vortex combustor can achieve high efficient combustion of aluminum and steam. The influencing factors, such as the eccentric distance of the inlet of aluminum particles, particle size and steam inlet diameter, etc., are studied. The work described in this paper represents an attempt to the design of a vortex combustor in order to increase aluminum combustion efficiency.

In this work model of mirror elements equilibrium of the micromechanical components is developed, the behavior analysis of the mirror element of micromechanical mirrors in case changing of control voltages of electrostatic actuators is carried out, an expression for determining the maximum value of deflection voltage at which the snap-down effect will take the following form is obtained in case of the influence of the coefficient of the electrostatic rigidity of electrostatic actuators. The developed equilibrium model of mirror elements and the obtained results of modeling can be used at design of micromechanical mirrors with internal suspensions.

A novel scaffold design has been created to enhance tissue engineering and regenerative medicine by optimizing the controlled, prolonged release of hepatocyte growth factor (HGF), a powerful chemoattractant for endogenous mesenchymal stem cells. We present a new stacked scaffold that is made up of three different fibrin gel layers, each of which has HGF integrated into the matrix. The design attempts to preserve HGF's regenerative properties for long periods of time, which is necessary for complex tissue regeneration. These multi-layered fibrin gels have been mechanically evaluated using rheometry, and their degradation behavior has been studied using D-Dimer ELISA. Understanding the kinetics of HGF release from this novel scaffold configuration is essential for understanding HGF's long-term sustained bioactivity. A range of cell-based tests were carried out to verify the functionality of HGF following extended incorporation. These tests included 2-photon microscopy using phalloidin staining to examine cellular morphology, SEM analysis for scaffold-cell interactions, and scratch and scatter assays to assess migration and motility. The analyses show that the novel stacking scaffold promotes vital cellular processes for tissue regeneration in addition to supporting HGF's bioactivity. This scaffold design was developed for in situ tissue engineering. Using the body as a bioreactor, the scaffold should recruit mesenchymal stem cells from their niche thus combining the regenerative abilities of HGF and MSCs to promote tissue remodeling and wound repair.

This aim of this study was to investigate the relationships between lifestyle factors, insulin resistance, and male fertility in 73 men with and without insulin resistance. The participants were divided based on insulin resistance status. Their physical activity, diet, perceived stress, sleep quality, libido level, and the duration of sexual abstinence were assessed on the basis of a number of parameters, including indices proposed by the authors. The results highlighted associations between a number of parameters, i.e., micronutrient and vitamin intake, diet quality, body composition, insulin resistance, and the duration of sexual abstinence, and semen quality, as measured by sperm motility. Significantly, the presence or absence of insulin resistance was linked to male fertility. A multivariate model was developed, incorporating parameters such as the Matsuda index, vitamin intake, and sexual abstinence duration, to predict motility scores. The study underscores the negative impact of modern civilization’s lifestyle choices on male fertility. Notably, vitamin and mineral consumption, especially from antioxidant-rich diets like the Mediterranean diet, emerged as key modifiable factors affecting fertility. Routine diagnostics for insulin resistance in fertility-related interventions is recommended. The study also highlights the importance of considering sexual abstinence duration during semen collection for accurate diagnostic results. Future research should focus on validating the proposed multivariate model and exploring the effects of lifestyle modifications, particularly vitamin supplementation, on fertility outcomes in men, especially in the context of insulin resistance.

"Suero costeño" a type of sour cream, is a traditional dairy product made mainly in the Colombian Caribbean region and has a variety of uses. The objective was to characterize the physicochemical and rheological properties of “suero costeño” produced in department of Córdoba-Colombia. Samples of " suero costeño " were obtained from local producers, characterized physicochemically (protein, fat, crude fiber, moisture, ash, carbohydrates, chlorides, pH and acidity), and rheologically (stationary tests), adjusting their behavior to the power-law model. The results show great variability in the physicochemical characteristics of the “suero costeño” made by the different artisanal producers, classifying it as a full-fat sour cream or light sour cream, and values of protein, pH and acidity similar to similar traditional dairy products from other countries, such as Reindeer sour cream and Curd or cottage cheese. “Suero costeño” can be classified as a pseudoplastic fluid and depending on the raw materials used and the production process, some present thixotropy, which may be the product of interactions between proteins and fats, which cause changes in the internal structure. Due to this great variability in its physicochemical and rheological characteristics, it is necessary to standardize the process of producing to improve the marketing of this Colombian culinary product.

The increase in the rate and prevalence of diseases associated with the localized and general loss of bone mass calls for an investigation into therapeutic alternatives that largely involve the de-velopment of new biomaterials and cell therapy, converting tissue bioengineering into a prom-ising option. An experimental model of a critical mandibular lesion in rats has been used to study bone re-generation by treating the ostectomy with the biomaterials Evolution® and Gen-Os® (OsteoBiol®, Italy) combined, or not, with dental pulp stem cells (DP-MSC). The results obtained through the Micro-CT and histological study reveal the almost complete re-covery of the lesion in the group with DP-MSC. These results are supported by increases in endoglin, TGF-β, protocollagen I, parathormone, and calcitonin, generating an environment of bone generation and development when combining Evolution® and Gen-Os® (OsteoBiol®, Italy) with DP-MSC. These promising results confirm the transcendental role of DP-MSC in combina-tion with osteogenic biomaterials for bone regeneration, and warrant further studies, including its assessment in clinical trials.

The invasion of ship domain stands out as a significant factor contributing to the risk of collisions during vessel navigation. However, there is a lack of research on the mechanisms underlying collision risks specifically related to merchant and fishing vessels in coastal waters. This study proposes an assessment method for collision risks between merchant and fishing vessels in coastal waters and validated through a comparative analysis through visualization. First of all, the operational status of fishing vessels is identified. Collaboratively working fishing vessels are treated as a unified entity, expanding their ship domain during operation to assess collision risks. Secondly, to quantify the collision risk between ships, a collision risk index (CRI) is proposed and visualized based on the severity of collision risk. Finally, taking the high risk area of merchant and fishing vessels collision in the Minjiang River Estuary as an example, this paper conduct the analysis involves classifying ship collision scenarios, extracting risk data under different collision scenarios, and visually analyzing areas prone to danger. The results indicate that this method effectively evaluates the severity of collision risk, and the identified high-risk areas resulting from the analysis is verified by accidents occurred in the recent three years.

Mobile health technologies enable continuous, quantitative assessment of mobility and gait in real-world environments, facilitating early diagnosis of gait disorders, disease progression monitoring, and prediction of adverse events like falls. Traditionally, mobile gait assessment predominantly relied on body-fixed sensors positioned at the feet or lower trunk. Here, we investigate the potential of an algorithm utilizing an ear-worn motion sensor for spatiotemporal segmentation of gait patterns. We collected 3D acceleration profiles from the ear-worn sensor during varied walking speeds in 53 healthy adults. Temporal convolutional networks were trained to detect stepping sequences and predict spatial relations between steps. The resulting algorithm, mEar, accurately detects initial and final ground contacts (F1 score of 99% and 91%, respectively). It enables determination of temporal and spatial gait cycle characteristics (among others stride time and stride length) with good to excellent validity at a precision sufficient to monitor clinically relevant changes in walking speed, stride-to-stride variability, and side asymmetry. This study highlights the ear as a viable site for monitoring gait and proposes its potential integration with in-ear vital sign monitoring. Such integration offers a practical approach to comprehensive health monitoring and telemedical applications, by integrating multiple sensors in a single anatomical location.

This study offers an analysis of existing research on sustainability and its link to accounting and management control in the port sector. The existing studies do not provide a comprehensive discussion of management accounting and control tools in this context, despite recognizing the relevance of the issue. The Scoping Review was used as a methodological basis, with reference to the framework of Arksey and O’Malley [1], with the aim of mapping the literature on the role of ac-counting and management control, as well as their relationship with the Triple Bottom Line associated with the various levels of sustainability in this sector. The results point to a diversity of tools used essentially in developed countries, where the interest in efficiency, sustainability and strategic alignment stands out.

For very first time, we report the synthesis of 8-(2-methoxyphenyl)-6-methyl-2-(1-methyl-1H-benzo[d]imidazol-2-yl)quinoline 1. This was achieved in several steps, including usage of Suzuki reaction for functionalization of 2-(1H-benzo[d]imidazol-2-yl)quinoline moiety. The new compound exhibits blue fluorescence. Its structure was confirmed with 1D- and 2D-NMR spectroscopy, IR-spectroscopy, high-resolution mass spectrometry and X-ray analysis.

Polymeric Intraocular lenses (IOLs) are vital for restoring vision following cataract surgery and for correcting refractive errors. Despite technological and medical advancements, challenges persist in achieving optimal vision and preventing complications. Surface modifications aim to mitigate the risk of posterior capsule opacification (PCO), while pre-operative measurements aid in selecting suitable IOLs. However, individualized solutions are lacking and there is a clear demand for the development of fully customised IOL surfaces. We employ laser micromachining technology for precise modifications via ablation on PMMA and Acrylic IOLs, using femtosecond (fs), nanosecond (ns), and diode continuous wave (CW) lasers, at wavelengths ranging from near-ultraviolet to infrared. Characterization reveals controlled ablation patterning, achieving feature sizes from as small as 400 nm to several micrometers. Regular and confocal Micro-Raman spectroscopy revealed alterations of the IOL materials' structural integrity for some pattering cases, thus affecting the optical properties, while these can be minimised by proper selection of micromachining conditions. The results suggest the feasibility of accurate IOL patterning, which could offer personalized vision correction solutions, based on relevant corneal wavefront data, thus surpassing standard lenses, marking a significant advancement in cataract surgery outcomes.

For the first time to optimize the creation of new neuroprotective agents based on bioflavonoids, we applied information technologies - docking analysis to calculate the binding of candidate molecules to the pharmacological target protein transthyretin, as well as the program of virtual screening of NO scavengers. As a result of this approach, the substance catechin was isolated from candidate molecules - quercetin, catechin, Epicatechin gallate, Epicatechin, Procyanidin B1, Procyanidin B2, Procyanidin B3, Catechin-3-gallate according to docking analysis. As a result of virtual screening, catechin was identified as a potential NO scavenger (55.15% prediction). The results of the prediction were confirmed by in vitro experiments. Course administration of catechin to animals with experimental multiple sclerosis (MS) against the background of methylprednisolone administration completely eliminated lethal cases, reduced the number of diseased animals by 20%, as well as prevented the development of severe neurological symptoms by 20% (compared to the methylprednisolone group) and by 60% compared to the control group. Course administration of catechin with methylprednisolone leads to decrease of neurodegradation markers in the cytosol of rats with EAE: NSE by 37%, and S-100 - by 54.8%. The combined administration of methylprednisolone significantly exceeds the combination of methylprednisolone with the reference drug mexidol by the degree of NSE reduction. The obtained results indicate a significant neuroprotective effect of ocular combinations of methylprednisolone and catechin. The above-mentioned confirms the correctness of bioflavonoid selection with the help of virtual screening program.

When profit-driven renewal is difficult to implement, many historic districts are “frozen protected” in China. In the social context of “building cities for the people” in recent years, the public value-oriented renewal of urban historic areas plays an important role in the transformation of cities. This study investigates the strategies of historic district regeneration in China by integrating spatial form, urban governance, and public value. We propose a novel framework to analyze the regeneration of historic districts, using Taiyuan Bell Tower Street as a case study. The framework distinguishes between two dimensions: spatial and economic-social. In the spatial dimension, we focus on the transformation of spatial form to regenerate public value, emphasizing the attribute of "publicness" as central to urban regeneration efforts. This involves a tiered approach of excavating and upgrading historic districts at macro, meso, and micro levels. In the economic-social dimension, we explore urban governance to strengthen public value, involving government, market, and societal actors in a collaborative renewal process. The analysis highlights that a public value-oriented approach to heritage regeneration offers greater sustainability and could serve as a model for other cities seeking similar outcomes.

Lane detection is a foundational technology for autonomous driving systems. It involves identifying the boundaries of lanes on the road and ensuring the vehicle stays within these boundaries. Accurate lane detection is crucial for safety, navigation and traffic management. This paper presents an artificial intelligent based autonomous road lane detection and navigation system for vehicles. The system can detect and analyze road lanes accurately and efficiently in real-time, with frame rates of up to 17 FPS. By utilizing image processing techniques, the system can identify the location and boundaries of road lanes and obstacles on the road and provide accurate and reliable navigation guidance to the driver. The system is integrated with sensors and actuators to provide comprehensive autonomous navigation. The efficiency of the proposed system is demonstrated using accuracy of lane detection on straight and curve lanes covering frames per second and motor of the speed as parameters for assessment. Results show that the proposed system detects lane as entire lane detection, partial lane detection and no detection status on different settings.

Whey protein was pretreated with multi-frequency ultrasound in mono, dual, and tri-frequency modes. The effect of multi-frequency ultrasound pretreatment on the hardness, chemical forces, and microstructure of acid-induced whey protein gel was investigated. Whey protein gels pretreated with dual and tri-frequency ultrasound showed higher hardness (p3.35 mm) in those samples were resisted to gastric digestion. Moreover, the tri-frequency ultrasound pretreatment of whey protein gel released the least free amino group during gastric digestion. In contrast, whey protein gel with the mono-frequency ultrasound pretreatment released the highest amount of free amino acid group during intestinal digestion. Findings from this study suggested that gel hardness and network density could modulate the digestion behaviors of protein gels.

MicroRNAs are small non-coding RNAs, which contribute to the regulation of many physiolog-ical and pathological processes. Conventionally, miRNAs perform their activity in the cyto-plasm, where they regulate gene expression by interacting in a sequence-specific manner with mature messenger RNAs. Recent studies point to the presence of mature miRNAs in the nucleus. This review summarizes current findings regarding the molecular activities of nuclear miRNAs. These molecules can regulate gene expression at the transcriptional level by directly binding DNA on the promoter or the enhancer of regulated genes. MiRNAs recruit to these regions dif-ferent protein complexes, resulting both in activation or repression of transcription, through a number of molecular mechanisms. Haematopoiesis is presented as a paradigmatic biological process whereby nuclear miRNAs possess a relevant regulatory role. Nuclear miRNAs may af-fect gene expression also acting on nuclear mRNA processing and on the biogenesis of miRNA themselves by regulating pri-miRNA maturation. Overall, nuclear miRNAs are biologically ac-tive molecules that can be critical for the fine tuning of gene expression and deserve further studies in a number of physiological and pathological conditions