Accurate determination of the number and location of immature small yellow peaches is crucial for bagging, thinning, and estimating yield in modern orchards. However, traditional methods have faced challenges in accurately distinguishing immature yellow peaches due to their resemblance to leaves and susceptibility to variations in shooting angles and distance. To address these issues, we proposed an improved target-detection model (EMA-YOLO) based on YOLOv8. Firstly, the sample space was enhanced algorithmically to improve the diversity of samples. Secondly, an EMA attention-mechanism module was introduced to encode global information; this module could further aggregate pixel-level features through dimensional interaction and strengthen small-target-detection capability by incorporating a 160 × 160 detection head. Finally, EIoU was utilized as a loss function to reduce the incidence of missed detections and false detections of the target small yellow peaches under the condition of high density of yellow peaches. Experimental results show that compared with the original YOLOv8n model, the EMA-YOLO model improves mAP by 4.2%, Furthermore, compared with SDD, Objectbox, YOLOv5n, and YOLOv7n, this model’s mAP was improved by 30.1%, 14.2%,15.6%, and 7.2%, respectively. In addition, the EMA-YOLO model achieved good results under different conditions of illumination and shooting distance and significantly reduced the number of missed detections. Therefore, this method can provide technical support for smart management of yellow-peach orchards. Full article

Momordica charantia, commonly known as bitter melon, is a fruiting plant that has been used for several diseases including infectious diseases. In this study, we report the antibacterial, antifungal, and antiviral activity of different bitter melon fruit parts originating from India and Saudi Arabia. The in vitro experiments are supported by the molecular docking of karavilosides to verify their role in the bioactivity. The antimicrobial assays revealed activity against Candida albicans, Escherichia coli, and Staphylococcus aureus. The extracts exhibited the potent inhibition of HIV-I reverse transcriptase, with an IC50 of 0.125 mg/mL observed for the pith extract originating from Saudi Arabia and the standard drug doxorubicin. The molecular docking of karavilosides exhibited a significant affinity to reverse transcriptase comparable to Rilpivirine and higher than that of doxorubicin. These outcomes encourage the precious bioactive components of the seed and pith of the Saudi bitter melon fruits to be further studied for isolation and structure elucidation. Full article

Coronary artery disease (CAD) and hypertension significantly contribute to cardiovascular morbidity and mortality. MicroRNAs (miRNAs) have recently emerged as promising biomarkers and therapeutic targets for these conditions. This systematic review conducts a thorough analysis of the literature, with a specific focus on investigating miRNA expression patterns in patients with CAD and hypertension. This review encompasses an unspecified number of eligible studies that employed a variety of patient demographics and research methodologies, resulting in diverse miRNA expression profiles. This review highlights the complex involvement of miRNAs in CAD and hypertension and the potential for advances in diagnostic and therapeutic strategies. Future research endeavors are imperative to validate these findings and elucidate the precise roles of miRNAs in disease progression, offering promising avenues for innovative diagnostic tools and targeted interventions. Full article

The power sector is one of the major CO₂-emitting industries in China. It is also the first key emissions control industry included in China’s national carbon trading market established in 2021. Therefore, based on the data of 30 provinces and cities in China from 2015 to 2022, this study analyzes the impact of the national carbon market policy on the carbon emissions of the power industry based on the generalized Difference-in-Difference (DID) model. Based on the method of text analysis, this paper constructs the carbon market policy intensity index of each region and incorporates it into the DID model. Empirical analysis finds that the national carbon market policy can significantly inhibit the carbon emissions of the power industry. However, the heterogeneity analysis of 30 provinces and cities shows that the national carbon market policy has a significant impact on the regions that already have a carbon pilot, but not on the non-pilot regions. Therefore, this paper demonstrates the effectiveness of the national carbon market policy in the power industry emissions control, and also exposes the heterogeneity between regions, providing an important empirical basis for the inclusion of other energy-intensive industries. Full article

Conjugated linoleic acid (CLA) is a class of naturally occurring octadecadienoic acid in humans and animals and is a general term for a group of conformational and positional isomers of linoleic acid. In order to obtain the development of excellent lactic acid strains with a high production of conjugated linoleic acid, 32 strains with a possible CLA conversion ability were obtained by initial screening using UV spectrophotometry, and then the strains were re-screened by gas chromatography, and finally, the strain with the highest CLA content was obtained. The strains were optimized for cultivation by changing the amount of substrate addition, inoculum amount, and fermentation time. The results showed that the yield of the experimentally optimized strain for the conversion of conjugated linoleic acid could reach 94.68 ± 3.57 μg/mL, which was 74.4% higher than the initial yield of 54.28 ± 2.12 μg/mL of the strain. The results of this study can provide some basis for the application of conjugated linoleic acid production by Lactobacillus paracasei in the fermentation of lactic acid bacteria. Full article

Arrhythmic risk stratification in patients with Lamin A/C gene (LMNA)-related cardiomyopathy influences clinical decisions. An implantable cardioverter defibrillator (ICD) should be considered in patients with an estimated 5-year risk of malignant ventricular arrhythmia (MVA) of ≥10%. The risk prediction score for MVA includes non-missense LMNA mutations, despite their role as an established risk factor for sudden cardiac death (SCD) has been questioned in several studies. The purpose of this study is to investigate cardiac features and find gene–phenotype correlations that would contribute to the evidence on the prognostic implications of non-missense vs. missense mutations in a cohort of LMNA mutant patients. An observational, prospective study was conducted in which 54 patients positive for a Lamin A/C mutation were enrolled, and 20 probands (37%) were included. The median age at first clinical manifestation was 41 (IQR 19) years. The median follow-up was 8 years (IQR 8). The type of LMNA gene mutation was distributed as follows: missense in 26 patients (48%), non-frameshift insertions in 16 (30%), frameshift deletions in 5 (9%), and nonsense in 7 (13%). Among the missense mutation carriers, two (8%) died and four (15%) were admitted onto the heart transplant list or underwent transplantation, with a major adverse cardiovascular event (MACE) rate of 35%. No statistically significant differences in MACE prevalence were identified according to the missense and non-missense mutation groups (p value = 0.847). Our data shift the spotlight on this considerable topic and could suggest that some missense mutations may deserve attention regarding SCD risk stratification in real-world clinical settings. Full article

Acute ischemic stroke (AIS) and traumatic brain injury (TBI) are two severe neurological events, both being major causes of death and prolonged impairment. Their incidence continues to rise due to the global increase in the number of people at risk, representing a significant burden on those remaining impaired, their families, and society. These molecular and cellular mechanisms of both stroke and TBI present similarities that can be targeted by treatments with a multimodal mode of action, such as traditional Chinese medicine. Therefore, we performed a detailed review of the preclinical and clinical development of MLC901 (NeuroAiD^TMII), a natural multi-herbal formulation targeting several biological pathways at the origin of the clinical deficits. The endogenous neurobiological processes of self-repair initiated by the brain in response to the onset of brain injury are often insufficient to achieve complete recovery of impaired functions. This review of MLC901 and its parent formulation MLC601 confirms that it amplifies the natural self-repair process of brain tissue after AIS or TBI. Following AIS and TBI where "time is brain", many patients enter the post-acute phase with their functions still impaired, a period when "the brain needs time to repair itself". The treatment goal must be to accelerate recovery as much as possible. MLC901/601 demonstrated a significant reduction by 18 months of recovery time compared to a placebo, indicating strong potential for facilitating the improvement of health outcomes and the more efficient use of healthcare resources. Full article

Particleboards have gained attention in the global market. Understanding their physical–mechanical behavior in the current technological context is essential due to adhesive polymerization, which depends on variables such as pressing time and temperature. Today, the use of nanoparticles has become a plausible option for improving the properties of polymers used in wood-based composites. This study evaluates the influences of the addition of non-commercial 0.5% aluminum oxide (Al₂O₃) and aluminum oxide copper (CuO) nanoparticles using a greener route with a lower environmental impact obtaining a urea-formaldehyde (UF)-based polymeric adhesive to manufacture particle composites of Eucalyptus urophylla var. grandis wood. Regarding characterizations, the resin properties analyzed were viscosity, gel time, and pH, as well as panel properties, including density, moisture content, thickness swelling, modulus of elasticity, modulus of rupture, and thermal conductivity. The results were compared with scientific publications and standards. The addition of nanoparticles interfered with viscosity, and all treatments indicated a basic pH. It was not possible to determine the gel time after 10 min. Nanoparticles added to the polymers in the internal layer did not cause an improvement in the swelling properties in terms of thickness, with no significant statistical difference for density and moisture content. The increase from 150 °C to 180 °C may have caused an improvement in all physical–mechanical properties, indicating that the higher temperature positively influenced the polymerization of the formaldehyde-based adhesive. Therefore, the additions of both nanoparticles (0.5% in each condition) led to a limitation in the material influence with respect to physical–mechanical performance. Full article

This paper presents an eye image segmentation-based computer-aided system for automatic diagnosis of ocular myasthenia gravis (OMG), called OMGMed. It provides great potential to effectively liberate the diagnostic efficiency of expert doctors (the scarce resources) and reduces the cost of healthcare treatment for diagnosed patients, making it possible to disseminate high-quality myasthenia gravis healthcare to under-developed areas. The system is composed of data pre-processing, indicator calculation, and automatic OMG scoring. Building upon this framework, an empirical study on the eye segmentation algorithm is conducted. It further optimizes the algorithm from the perspectives of “network structure” and “loss function”, and experimentally verifies the effectiveness of the hybrid loss function. The results show that the combination of “nnUNet” network structure and “Cross-Entropy + Iou + Boundary” hybrid loss function can achieve the best segmentation performance, and its MIOU on the public and private myasthenia gravis datasets reaches 82.1% and 83.7%, respectively. The research has been used in expert centers. The pilot study demonstrates that our research on eye image segmentation for OMG diagnosis is very helpful in improving the healthcare quality of expert doctors. We believe that this work can serve as an important reference for the development of a similar auxiliary diagnosis system and contribute to the healthy development of proactive healthcare services. Full article

In this research, bio-based films were developed using polyelectrolyte complexes derived from chitosan and gelatin for packaging fish oil. To further enhance the antioxidant functionality, the films were enriched with gallic acid and orange essential oils, either individually or in combination. Initially, the films were characterized for their physico-chemical, optical, surface, and barrier properties. Subsequently, the phenolic compounds and antioxidant capacity of the films were assessed. Finally, the films were tested as antioxidant cover lids for packaging fish oil, which was then stored at ambient temperature for 30 days, with periodical monitoring of oil oxidation parameters. This study revealed that the inclusion of gallic acid-induced possible crosslinking effects, as evidenced by changes in moisture content, solubility, and liquid absorption. Additionally, shifts in the FTIR spectral bands suggested the binding of gallic acid and/or phenols in orange essential oils to CSGEL polymer chains, with noticeable alterations in film coloration. Notably, films containing gallic acid exhibited enhanced UV barrier properties crucial for preserving UV-degradable food compounds. Moreover, formulations with gallic acid demonstrated decreased water vapor permeability, while samples containing orange essential oils had lower CO₂ permeability levels. Importantly, formulations containing both gallic acid and essential oils showed a synergistic effect and a significant antioxidant capacity, with remarkable DPPH inhibition rates of up to 88%. During the 30-day storage period, fish oil experienced progressive oxidation, as indicated by an increase in the K232 value in control samples. However, films incorporating gallic acid or orange essential oils as active antioxidants, even used as indirect food contact, effectively delayed the oxidation, highlighting their protective benefits. This study underscores the potential of sustainable bio-based films as natural antioxidant packaging for edible fish oil or fresh fish, offering a promising tool for enhancing food preservation while reducing its waste. Full article

In South Korea, the proportion of adults experiencing severe loneliness has been increasing rapidly. Accordingly, this study examines the elements of loneliness experienced by Korean adults and investigates their structural relevance using concept mapping. Korean adults (47) were recruited for individual in-depth interviews based on their scores on the UCLA Loneliness Scale. The interviews yielded 80 unique statements, which were then evaluated using multidimensional scaling and a hierarchical cluster analysis. A cluster map of loneliness was derived, with three clusters: (1) emotional distress due to the actual or anticipated absence of connection in relationships, (2) emotional distance from oneself or from others in a relationship, and (3) powerlessness and emptiness due to being directionless. Two dimensions distinguished these clusters: the lack of a sense of connection or self-assurance, and an inward or outward focus. These findings reveal that loneliness encompasses more than unmet relational needs; it also involves self-attentional focus, indicating a need to reconceptualize the notion of loneliness. The study’s implications extend to counseling theory and practices by highlighting the importance of addressing both relational connections and self-perceptions in interventions for loneliness. By expanding the understanding of loneliness through empirical data, this research provides a more comprehensive framework for addressing loneliness. Full article

In this work, an artificial neural network (ANN)-based model is proposed to describe the input–output relationships in a Limaçon-To-Circular (L2C) gas expander with an inlet valve. The L2C gas expander is a type of energy converter that has great potential to be used in organic Rankine cycle (ORC)-based small-scale power plants. The proposed model predicts the different performance indices of a limaçon gas expander for different input pressures, rotor velocities, and valve cutoff angles. A network model is constructed and optimized for different model parameters to achieve the best prediction performance compared to the classic mathematical model of the system. An overall normalized mean square error of 0.0014, coefficient of determination ($R^2$) of 0.98, and mean average error of 0.0114 are reported. This implies that the surrogate model can effectively mimic the actual model with high precision. The model performance is also compared to a linear interpolation (LI) method. It is found that the proposed ANN model predictions are about 96.53% accurate for a given error threshold, compared to about 91.46% accuracy of the LI method. Thus the proposed model can effectively predict different output parameters of a limaçon gas expander such as energy, filling factor, isentropic efficiency, and mass flow for different operating conditions. Of note, the model is only trained by a set of input and target values; thus, the performance of the model is not affected by the internal complex mathematical models of the overall valved-expander system. This neural network-based approach is highly suitable for optimization, as the alternative iterative analysis of the complex analytical model is time-consuming and requires higher computational resources. A similar modeling approach with some modifications could also be utilized to design controllers for these types of systems that are difficult to model mathematically. Full article

Triboelectric nanogenerators (TENGs) are devices that efficiently transform mechanical energy into electrical energy by utilizing the triboelectric effect and electrostatic induction. Embroidery triboelectric nanogenerators (ETENGs) offer a distinct prospect to incorporate energy harvesting capabilities into textile-based products. This research work introduces an embroidered triboelectric nanogenerator that is made using polyester and nylon 66 yarn. The ETENG is developed by using different embroidery parameters and its characteristics are obtained using a specialized tapping and friction device. Nine ETENGs were made, each with different stitch lengths and line spacings for the polyester yarn. Friction and tapping tests were performed to assess the electrical outputs, which included measurements of short circuit current, open circuit voltage, and capacitor charging. One sample wearable embroidered energy harvester collected 307.5 μJ (24.8 V) of energy under a 1.5 Hz sliding motion over 300 s and 72 μJ (12 V) of energy through human walking over 120 s. Another ETENG sample generated 4.5 μJ (3 V) into a 1 μF capacitor using a tapping device with a 2 Hz frequency and a 50 mm separation distance over a duration of 520 s. Measurement of the current was also performed at different pressures to check the effect of pressure and validate the different options of the triboelectric/electrostatic characterization device. In summary, this research explains the influence of embroidery parameters on the performance of ETENG (Embroidery Triboelectric Nanogenerator) and provides valuable information for energy harvesting applications. Full article

Urban space’s physical and environmental characteristics impact urban public safety. Specifically, many areas in the older urban core are morphologically unsafe. The historic city’s resilience to natural disasters and emergency phenomena often surpasses expectations thanks to settlement principles, post-disaster transformations, and redundancies that enhance the performance of the historic built environment. Yet, the necessity to introduce new qualities to reclaim urban heritages scattered throughout the territory, often abandoned or sparsely populated, underscores the need for maintenance and management measures to boost safety and resilience. This study aims to identify technological components in urban space that influence the safety of places and define a design method for safety planning in historic urban settings. Urban safety interventions encompass various technological aspects in conjunction with the widespread distribution of equipment, adaptation of public and private facilities, and networked infrastructure and services. This paper delineates the elements that converge in the technological design of an appropriate historic town center to address potential emergencies. It presents the initial findings of studies conducted on a minor center with a strong historical value. This document aims to be useful for administrations of smaller municipalities, as the proposed method can be replicated in similar contexts. Full article

Recently, several studies have argued about the interactions of the real economy and financial system, as well as the importance of financial cycles in business cycle fluctuations. To date, there exists near consensus among central bankers, economists, and other scholars that the financial cycle is an important source of business cycle fluctuations. This has raised the question of whether monetary policy should respond to financial instability and/or imbalances. As a result, we asked the following questions: Should monetary policy lean against the wind by targeting the aggregate financial cycle in South Africa? And what is the role of monetary policy in minimizing financial imbalances and instabilities in South Africa? The present article aims to provide answers to the above-mentioned question. Through the adoption of a multiple-equation generalized method of moments and structural vector autoregressive approaches, this article simultaneously estimates and compares both the finance-augmented and the conventional Taylor rules. It is shown that the South African Reserve Bank has considered developments in the aggregate financial cycle in setting its policy rate. Overall, there is clear evidence to conclude that the South African Reserve Bank can lean against the wind by targeting the aggregate financial cycle, but only as a genuine augmentation not as a fully flagged objective. This article adds new evidence to the South African literature on the prevailing debate of whether monetary policy should respond to developments in the financial system. Full article

The purpose of this article is to navigate the intricate balance between innovation and sustainability, pinpointing facilitating factors for their harmonious coexistence. It aims to guide firms toward a future where innovation drives progress while safeguarding the planet’s and its inhabitants’ well-being. Synthesizing the existing research, this study explores the impacts of various factors on sustainable innovation performance. The results highlight the positive associations of leadership roles, dynamic capabilities, stakeholder engagement, and social and environmental aspects with the firm’s innovation, providing insights for fostering sustainable innovation practices. This study proposes a framework that illustrates how factors impacting sustainable innovation intersect with theories studied in this article, such as the triple bottom line (TBL) and sustainability development theory (SDT). A systematic literature review (SLR) methodology is adopted to synthesize the knowledge and validate the research outcome to reach a conclusion. It will be beneficial to include sustainability both as a critical strategy for any firm’s growth and as a key part of the academic curriculum to create knowledge that will develop responsible leaders for a sustainable world. Future studies may utilize quantitative methods, like surveys, to empirically validate outcomes, offering numerical insights into factors influencing sustainable innovation within firms and enriching understanding of their impact and relationships. Full article

The development of the textile industry has negative effects on the natural environment. Cotton cultivation, dyeing fabrics, washing, and finishing require a lot of water and energy and use many chemicals. One of the most dangerous pollutants generated by the textile industry is dyes. Most of them are characterized by a complex chemical structure and an unfavorable impact on the environment. Especially azo dyes, whose decomposition by bacteria may lead to the formation of carcinogenic aromatic amines and raise a lot of concern. Using the metabolic potential of microorganisms that biodegrade dyes seems to be a promising solution for their elimination from contaminated environments. The development of omics sciences such as genomics, transcriptomics, proteomics, and metabolomics has allowed for a comprehensive approach to the processes occurring in cells. Especially multi-omics, which combines data from different biomolecular levels, providing an integrative understanding of the whole biodegradation process. Thanks to this, it is possible to elucidate the molecular basis of the mechanisms of dye biodegradation and to develop effective methods of bioremediation of dye-contaminated environments. Full article

Wild-caught fish from coral reefs, one of the most threatened ecosystems on the planet, continue to supply the marine aquarium trade. Despite customs and veterinary checks during imports, comprehensive data on this global industry remain scarce. This study provides consolidated data on the largest import market by value, the European Union (EU): a 24-million-euro annual trade value, detailing the main exporting and importing countries, as well as the species and families of the 26 million specimens imported between 2014 and 2021. A watchlist alert system based on the number of specimens traded, import trends, and vulnerability index according to FishBase and the IUCN Red List conservation status is presented, providing key information on which species should require closer scrutiny by authorities. While the European TRAde Control and Expert System (TRACES) electronically monitors the movement of live animals to respond quickly to biosecurity risks, one-third of marine ornamental fish imported lack species-level information. With minor adjustments, TRACES holds the potential to significantly enhance data granularity and the monitoring of wildlife trade, with marine ornamental fish being an interesting case study to validate this approach. Full article

The SARS-CoV-2 infection has been associated with important mortality, particularly in immunocompromised patients, including solid organ transplant (SOT) recipients. Remdesivir (RDV) is an antiviral drug that has proven to be effective in reducing the replication of the virus in host cells, by which it may reduce the progression of symptoms and, consequently, the length of hospital stay and mortality. Randomized controlled trials have evaluated its use in the general population but never in SOT recipients. For the first time in this review, the safety and efficacy of RDV is evaluated in this specific population. The literature research was conducted using PubMed/MEDLINE and Scopus databases from 1 January 2020 to 24 November 2023, and 23 studies were analyzed. Although no clinical studies specifically evaluating this population have been conducted yet, RDV is likely safe for SOT patients when compared to the general population, so prescribers should consider utilizing RDV in SOT patients who are at high risk for progression to severe COVID-19. Future research will allow for the confirmation of the observed results and the acquisition of broader and clearer data regarding the safety and efficacy of the drug in this specific setting. Full article

The grooming behavior of honeybees serves as a crucial auto-protective mechanism against Varroa mite infestations. Compared to Apis mellifera, Apis cerana demonstrates more effective grooming behavior in removing Varroa mites from the bodies of infested bees. However, the underlying mechanisms regulating grooming behavior remain elusive. In this study, we evaluated the efficacy of the auto-grooming behavior between A. cerana and A. mellifera and employed RNA-sequencing technology to identify differentially expressed genes (DEGs) in bee brains with varying degrees of grooming behavior intensity. We observed that A. cerana exhibited a higher frequency of mite removal between day 5 and day 15 compared to A. mellifera, with day-9 bees showing the highest frequency of mite removal in A. cerana. RNA-sequencing results revealed the differential expression of the HTR2A and SLC17A8 genes in A. cerana and the CCKAR and TpnC47D genes in A. mellifera. Subsequent homology analysis identified the HTR2A gene and SLC17A8 gene of A. cerana as homologous to the HTR2A gene and SLC17A7 gene of A. mellifera. These DEGs are annotated in the neuroactive ligand–receptor interaction pathway, the glutamatergic synaptic pathway, and the calcium signaling pathway. Moreover, CCKAR, TpnC47D, HTR2A, and SLC17A7 may be closely related to the auto-grooming behavior of A. mellifera, conferring resistance against Varroa infestation. Our results further explain the relationship between honeybee grooming behavior and brain function at the molecular level and provide a reference basis for further studies of the mechanism of honeybee grooming behavior. Full article

Evaluation of the 3D bone morphology of the glenohumeral joint is necessary for pre-surgical planning. Zero echo time (ZTE) magnetic resonance imaging (MRI) provides excellent bone contrast and can potentially be used in the place of computed tomography. Segmentation of the shoulder anatomy, particularly the humeral head and the acetabulum, is needed for the detailed assessment of each anatomy and for pre-surgical preparation. In this study, we compared the performance of two popular deep learning models based on Google’s DeepLab and U-Net to perform automated segmentation on ZTE MRI of human shoulders. Axial ZTE images of normal shoulders (n = 31) acquired at 3-Tesla were annotated for training with DeepLab and 2D U-Net, and the trained model was validated with testing data (n = 13). While both models showed visually satisfactory results for segmenting the humeral bone, U-Net slightly over-estimated while DeepLab under-estimated the segmented area compared to the ground truth. Testing accuracy quantified by Dice score was significantly higher (p < 0.05) for U-Net (88%) than DeepLab (81%) for the humeral segmentation. We have also implemented the U-Net model onto an MRI console for push-button DL segmentation processing. Although this is an early work with limitations, our approach has the potential to improve shoulder MR evaluation hindered by manual post-processing and may provide clinical benefit for quickly visualizing bones of the glenohumeral joint. Full article