Search Results (1,073)

Fixed external louvers are widely used to improve the environmental performance of glass curtain wall office buildings, yet existing studies more often report preferred solutions than transferable decision ranges for early-stage design. This study develops interval-based design rules for a standard-floor prototype of a point-supported glass curtain wall office building in Tianjin, a representative cold-climate city in China. A seven-variable design space integrating spatial-scale and shading variables was evaluated for 3000 Latin hypercube samples in a Rhino–Grasshopper–Honeybee workflow linked to Radiance and EnergyPlus, using Tianjin’s typical meteorological year data and GB 55015—2021-based office schedules, including an occupant density of 10 m²/person and occupied heating/cooling setpoints of 20/26 °C. Raw-sample statistics, Bootstrap-based stability testing, and surrogate-model-assisted continuous-response analysis were used to identify dominant variables, single-objective preferred intervals, and a neutral equal-weight baseline compromise zone. Under a neutral equal-weight baseline adopted for early-stage comparison, the compromise interval is concentrated around 20–25°, with 15–30° as a practical starting range, while alternative weighting scenarios show directional shifts toward the prioritized objective. Full article

Nosema ceranae is a common and highly contagious fungal pathogen that primarily infects the gut of adult honeybees, causing nosemosis. As a chronic disease of the digestive system, it poses a global threat to honeybee health and colony sustainability. This study aimed to investigate the inhibitory effects of different concentrations of Scutellaria baicalensis aqueous extract on N. ceranae in the intestines of infected Apis cerana through feeding experiments. In addition, the therapeutic efficacy of its major active component, baicalin, was evaluated, and its potential molecular mechanisms of action were explored. The results showed that, compared with the control group, administration of S. baicalensis aqueous extract at concentrations of 1 mg/mL, 5 mg/mL, and 10 mg/mL significantly reduced midgut spore loads (p < 0.05). Further experiments showed that a 0.5 mg/mL baicalin sucrose solution, prepared with 0.5% (v/v) DMSO as co-solvent, exhibited optimal solubility and significantly inhibited the proliferation of spores in the honeybee midgut. Transcriptomic analysis of A. cerana revealed varying numbers of significantly differentially expressed genes among the baicalin-treated (HG) group, the co-solvent control (DMSO) group, and the blank control (C) group. Four candidate DEGs associated with the effects of baicalin were further identified, namely LOC108003965, LOC108000905, LOC107996681, and CYP4G11. Gene Ontology enrichment analysis showed that, in the comparison between the HG group and the C group, these DEGs were significantly enriched in six functional categories: iron ion binding, phosphoric ester hydrolase activity, heme binding, tetrapyrrole binding, hydrolase activity (acting on ester bonds), and oxidoreductase activity (acting on paired donors, with incorporation or reduction of molecular oxygen). Collectively, these results demonstrate that S. baicalensis aqueous extract effectively inhibits the proliferation of N. ceranae within the host, and its active component, baicalin, exhibits a similar inhibitory effect. The present study proposes a novel strategy in which baicalin may enhance host endogenous chitinase-related activity to target and disrupt the spore wall, offering a new perspective for the prevention and control of honeybee nosemosis. Full article

Ascosphaera apis is a fungal pathogen of honeybee larvae and the primary cause of chalkbrood disease, which weakens bee colonies, impairing their ability to function effectively and making them more susceptible to other pathogens and environmental stressors. This study aimed to develop and validate an in-house matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) spectral library for A. apis. A new MALDI-TOF MS library was constructed using reference Ascosphaera species and validated through whole-genome-based confirmation of 31 clinical isolates of A. apis. Three different protein extraction methods were tested and compared: liquid cultivation, formic acid–ethanol extraction and extended direct transfer. Our findings demonstrate that MALDI-TOF MS is a rapid and reliable tool for identifying A. apis under the tested laboratory conditions and within the analyzed strain set, with no misidentifications observed for the liquid cultivation and formic acid–ethanol extraction methods. The extended direct mycelium transfer method was slightly less effective but still showed a high sensitivity of 83.9%. This study provides a foundation for improving diagnostic approaches in the management of honeybee fungal diseases. Full article

Emerging evidence indicates that non-coding RNAs (ncRNAs) play important regulatory roles in honeybee social behavior and development. However, the regulatory roles of ncRNAs in honeybees remain largely elusive. To systematically identify ncRNAs associated with queen-regulated ovary activation, we conducted whole-transcriptome sequencing on the heads of Apis mellifera workers from queenright and queenless colonies. Subsequent bioinformatics analyses were conducted to profile differentially expressed (DE) RNAs and construct potential regulatory networks. High-quality sequencing data provided a foundation for subsequent analyses. This transcriptome data yielded 3968 lncRNA transcripts, comprising 3146 known and 822 novel candidates, all of which exhibited typical structural features of lncRNAs. Comparative expression analyses revealed that 246 lncRNAs, 1439 mRNAs, and 10 miRNAs were differentially expressed. Comprehensive functional analyses indicated that the identified DElncRNAs potentially regulate sensory perception-related target mRNAs via cis-regulation, and coordinate metabolic and proteostatic reprogramming via trans-regulation to support the transition to reproductive activation in workers. Furthermore, a competing endogenous RNA network was constructed which integrated 74 DElncRNAs, 5 DEmiRNAs, and 36 DEmRNAs to predict their potential post-transcriptional interactions. Our findings highlight a comprehensive analysis of ncRNAs and mRNAs in worker heads, providing a foundation for functional validation of their roles in honeybee ovary development. Full article

Botanical insecticides containing a mixture of plant essential oils (EOs) are considered suitable for the management of houseflies (M. domestica). The adulticidal efficacies of single EOs and mixtures of EOs, including lemongrass (C. citratus), star anise (I. verum), nutmeg (M. fragrans), and their components (geranial, trans-anethole, and α-pinene), against houseflies were determined in comparison to 2% (w/v) α-cypermethrin as the positive control and distilled water as the negative control. The mixture of star anise EO (1%) + geranial (1%) was the most effective adulticide, superseding single EOs, other combinations of EOs, and its active component, α-cypermethrin, and distilled water. This mixture was highly synergistic and was found to be over 74% more toxic than all single EOs and almost 2.6 times more toxic than α-cypermethrin. Furthermore, the tested EOs did not cause mortality in guppies (P. reticulata) or earthworms (E. fetida), and caused a maximum of 48% mortality in honeybees (A. mellifera) at 24 h; by contrast, α-cypermethrin led to 100% mortality in honeybees within 0.5 h and in guppies and earthworms within 24 h, although it had low toxicity toward houseflies. Thus, a mixture of star anise EO + geranial is a promising source of EO-derived insecticides for housefly control that is also safe for important non-target species. Full article

Varroa destructor (Bee mite) and Deformed Wing Virus are primary causes of honeybee colony collapse. This study developed an automated AI-based vision inspection system for detecting bee mites and deformed bees using the YOLO algorithm. The system integrates an RGB camera, a beecomb rotation motor, and an image transmission module to enable automated dual-sided image acquisition of the beecomb. The image characteristics of normal bees, bee mites, and deformed bees were analyzed, and YOLO-based object detection models were developed to classify them. Six YOLO models—based on YOLOv8 and YOLOv11 architectures across three model sizes (nano, small, and large)—were evaluated on 405 test images (6441 objects). The proposed system reduced the inspection time from 240 s required for manual method to 20 s per beecomb, achieving 12-fold efficiency improvement. Comparative analysis showed model-task specialization: YOLOv8l excelled in detecting small bee mites (F1: 92.5%, mAP[0.5]: 92.1%), while YOLOv11s achieved the highest performance for morphologically diverse deformed bees (F1: 95.1%). Error analysis indicated that detection performance was influenced by morphological characteristics. Deformed bee detection errors correlated with overlap in wing-to-body ratio: DB Type II exhibited 18.6% miss rate, while DB Type III achieved perfect detection. In bee mite detection, a sensitivity–specificity trade-off was observed: YOLOv11l had the lowest false negatives (2.5%) but highest false positives, while YOLOv8l demonstrated superior discrimination. These results demonstrate the practical potential of the proposed system for field deployment in apiaries, supporting early pest diagnosis and improved colony health management. The model-task specialization framework provides guidance for architecture selection based on object characteristics. Future work will focus on multi-location validation and real-time monitoring integration. Full article

Beekeeping is a profitable and mind-relaxing practice; however, monitoring beehives poses significant challenges, such as consuming time and potentially disturbing hive equilibrium, which may lead to colony collapse. Developing precision beekeeping (PB) systems is crucial to assist beekeepers in decision-making, automate redundant hive maintenance, and enhance the security and comfort of bee life. This review systematically explores research on PB systems, based on a keyword-driven search of Scopus and Web of Science databases, yielding 46 relevant publications. The analysis highlights a notable increase in research activity in the field since 2016. The integration of advanced technologies, including machine learning, cloud computing, IoT, and scenario-based communication methods, has proven instrumental in predicting hive states such as queen status, enemy attacks, readiness for harvest, swarming events, and population decline. Commonly measured parameters include hive weight, temperature, and relative humidity, with various sensors employed to ensure precision while minimizing bee disturbance. Additionally, bee traffic monitoring has emerged as a critical approach to assessing hive health. Most studies focus on honeybees rather than stingless bees and, in the context of enemy identification, Varroa destructor is the primary target. This review underscores the potential of novel technologies to revolutionize apiculture and enhance hive management practices. Full article

Despite the undisputable ecosystem importance of honeybees, human activities have a substantial impact on their health. Since foraging is directly linked to a wide range of crops and bee-attracting flowers, plant protection products are at the forefront of chemical scrutiny, along with contamination of pollen, nectar, beehive components and water by other xenobiotics. In this study, a non-targeted Liquid Chromatography-High-Resolution Mass Spectrometry (LC-HRMS) screening was applied to 25 honeybee samples collected after reported death incidents in Greece. This approach led to the tentative annotation of over 50 compounds across various chemical classes, including pesticides, PFAS candidates not included in the EFSA “PFAS-4”, pharmaceuticals, antibiotics, industrial chemicals, and natural product constituents. In parallel, targeted pesticide residue analysis using liquid and gas chromatography coupled to tandem mass spectrometry (LC-MS/MS and GC-MS/MS) was performed, covering more than 250 active substances and providing direct quantitative results, revealing 11 active substances in concentrations ranging from <limit of quantification (LOQ) to 0.95 mg/kg, overlapping substantially with the HRMS detection. Overall, this study does not allow concrete causal attribution of mortality to specific chemicals; however, it documents complex co-occurrence patterns (pesticides together with other xenobiotics and plant bioactives), not excluding sublethal and mixture-toxicity effects. Quantified pesticide concentrations were below acute LD50-based thresholds, yet selected samples combined neonicotinoid/pyrethroid/fungicide signatures and other contaminants, supporting the need for mixture-toxicity frameworks and effect-based follow-ups. Full article

Propolis produced by honeybees, Apis mellifera, has been valued since ancient times as a remedy for different ailments for its broad medicinal properties. This wide range of biological activities may arise from the production of distinct propolis types within the hive, each serving specific functions and containing unique molecular compositions. In this study, we investigated the effects of four propolis types—masonry, sealing, brood-protection, and intruder-neutralizing—on hydrogen peroxide (H₂O₂)-induced oxidative injury in human skeletal muscle cells. Among these, only brood-protection propolis significantly prevented the H₂O₂-induced loss of cell viability. Bio-guided fractionation of this active propolis identified five major compounds: benzyl caffeate (BC), caffeic acid phenethyl ester (CAPE), cinnamyl caffeate (CC), prenyl caffeate (PC), and (E)-3-methyl-3-butenyl caffeate (MBC), all displaying stronger cytoprotective effects than their ferulate equivalents. We finally demonstrated that propolis extract and its active compounds reduced lipid peroxidation in post-mortem minced mouse skeletal muscle and compared their efficacy to other natural compounds. Chemical analysis of resins from neighboring flora suggested that black poplar (Populus nigra) buds are the primary botanical source of these caffeate derivatives. Collectively, these results highlight the functional diversity of hive propolis and its potential applications in food preservation as well as in complementary and preventive medicine. Full article

During the adaptive reuse of industrial heritage buildings, existing opening systems and envelope performance often pose major constraints. These restrictions make it difficult for the building to meet the requirements of the updated indoor environment, resulting in insufficient daylight and increased energy consumption. Therefore, optimizing lighting and energy performance has become the primary goal of the retrofit design. However, with limited interventions, the retrofit of heritage buildings to achieve significant overall performance improvement is still a challenge. From a sustainability perspective, improving daylight utilization and reducing energy demand are essential strategies for achieving low-carbon and resource-efficient building retrofit. This study proposes a grid-based parametric multi-objective optimization approach to optimize the window openings of the building envelope. The approach defines the position, size and material properties of the roof and facade openings as design variables. Implemented via the Honeybee and Octopus platforms, it integrates a genetic algorithm with EnergyPlus and Radiance simulations to co-optimize daylight performance, circadian frequency, and energy use intensity. Taking a single-story typical industrial heritage building in China’s cold climate zone as a case study, it is shown that coordinated multi-objective constraints significantly improve the overall performance across various evaluation metrics. The optimization results also provide interpretable window configuration strategies and recommended parameter ranges, which fully consider the climate adaptability of the surrounding environment. These findings offer useful guidance for sustainable retrofit design decision-making in similar single-story industrial heritage buildings. Full article

Adequate pollination of pollinator-dependent crops relies on the abundance and diversity of pollinators, and any temporal mismatch can lead to decreased productivity. Induced off-season flowering is widely used to anticipate the blooming time and to have a favorable market to generate greater economic income. However, the relationship between off-season flowering, effective pollination, and crop yield remains poorly understood. In this study, we compared pollinator and yield metrics of mango among its natural and off-season flowering across two years. We found that the composition, richness, and abundance of their effective pollinators varied across flowering seasons. Remarkably, blowflies were the floral visitors that deposited the highest number of pollen grains per visit and were the most important pollinators during the off-season, while honeybees and stingless bees were more important in the natural season. Mango yield was more positively related to the abundance of wild pollinators in both seasons than to honeybees. However, in both flowering seasons, mango trees suffered from pollen limitation and had a high incidence of malformed fruits. These findings highlight the important role of wild pollinators in maintaining and improving the mango yield and quality, mainly during the induced flowering season, improving the income to mango producers and increasing food security. Full article

While the gut microbiota of pollen-carrying bees (e.g., honeybees and bumblebees) has been well studied, the gut microbiota of vespine wasps remains poorly understood. Unlike pollen-carrying bees, which primarily consume pollen and nectar, vespine wasp larvae mainly feed on insects, suggesting that their gut bacterial communities may be different. Therefore, this study aimed to reveal the differences in larval gut bacterial communities between pollen-carrying bees and vespine wasps. Using datasets obtained from our own samplings and public resources released by other researchers, we compared the diversity and composition of larval gut bacterial communities between vespine wasps and pollen-carrying bees. Alpha diversity and beta diversity of bacterial communities were measured. Results showed that vespine wasp larvae harbored distinct gut bacterial communities from those of pollen-carrying bees, dominated by Leuconostoc, Hafnia-Obesumbacterium and Lactobacillus. Significant differences in bacterial composition were observed at both the community level and the dominant taxa level between pollen-carrying bee larvae and vespine wasp larvae. Moreover, significant differences were also found among larval gut bacteria of vespine wasps. These findings provide insights into the bacterial composition of aculeate wasps with different dietary habits. Full article

As the predominant native pollinator across Asia, Apis cerana is essential for the maintenance of biodiversity and agricultural productivity. The gut microbiota of honeybees plays a central role in host nutrition, detoxification, and immune function. p-Coumaric acid, a widespread phenolic acid enriched in pollen and nectar, has been reported to promote honeybee health by prolonging lifespan and increasing the expression of detoxification-related genes, hence improving tolerance to pesticides. Its influence on gut microbial communities, however, remains insufficiently characterized in A. cerana. This study evaluated the effects of dietary p-coumaric acid on survival, sucrose solution consumption, and gut microbiome composition in A. cerana workers using absolute quantification sequencing. Bees were provided sucrose solutions containing p-coumaric acid at concentrations of 41.0, 82.0, and 164.0 mg/L for durations of 5 and 10 days. The results indicated no effect on survival but revealed time-dependent changes in sucrose solution consumption. p-Coumaric acid exposure altered the abundance of non-core bacterial taxa, including Bombella and Apilactobacillus, whereas the core gut microbiota (Lactobacillus, Gilliamella, Snodgrassella, Apibacter, and Bifidobacterium) remained stable. These results suggest that p-coumaric acid modulates sucrose solution consumption and selectively influences non-core gut bacteria without disrupting survival or core microbiota stability, underscoring its role in regulating host–microbe interactions in honeybees. Full article

The digital and green transitions in the AEC sector require rapid, data-driven workflows to redefine sustainability through real-time performance evaluation. However, the high computational cost of traditional energy simulations often lacks evidence-based feedback during early-stage design. This study introduces a surrogate machine learning framework (S-TCML) designed to bypass traditional energy simulation by providing an instantaneous assessment of thermal comfort. Using a parametric Grasshopper–Honeybee environment, a dataset of 3072 configurations was generated for an office room in Cairo, Egypt. Six machine learning algorithms were benchmarked, with Gradient Boosting and Random Forest demonstrating superior performance in capturing non-linear thermal physics. Validation against the EnergyPlus engine confirmed that S-TCML models deliver predictions in milliseconds—a 99.9% reduction in computational time. The Gradient Boosting model achieved exceptional accuracy with an R² of 0.999 and RMSE of 0.013 for PMV and an R² of 0.995 and RMSE of 0.46% for PPD prediction. Feature importance analysis proved that a tree-based ML model can capture the underlying physical relationship between variables. To bridge the feedback gap, a web-based graphical user interface (GUI) was developed to facilitate proactive design exploration. This framework supports sustainable decision-making and design efficiency, offering scalable, user-friendly tools that protect occupant health and ensure thermal resilience in hot–arid environments. Full article

A simple, fast, and cost-effective organic solvent-based protocol was developed for DNA extraction from deer antlers and prepared trophy skulls, eliminating the need for commercial kits or cryogenic grinding. The method combines bead-based mechanical homogenization with a 4 h enzymatic digestion in EDTA buffer containing N-lauryl sarcosine and Proteinase K, followed by phenol–chloroform–isoamyl alcohol purification and centrifugal filtration. DNA quality and quantity were evaluated using agarose gel electrophoresis, Qubit fluorometry, and Nanodrop spectrophotometry. The protocol was tested on 60 samples, comprising 30 antlers and 30 pedicle parts from prepared trophy skulls of roe deer (Capreolus capreolus), fallow deer (Dama dama), and red deer (Cervus elaphus). To assess suitability for downstream applications, species-specific microsatellite markers were amplified using multiplex PCR, successfully generating complete genotypes from all 60 samples. These results, along with a demonstrated case study, confirm that the developed protocol provides high-quality DNA suitable for molecular genetic investigations, enabling reliable genotyping from small amounts of both antler and processed trophy materials in forensic and conservation contexts. Full article