Search Results (432)

This study investigates the effectiveness of passive design in low-rise residential buildings located in arid desert climates, using the Dubai Solar Decathlon Middle East (SDME) competition as a case study. This full-scale experiment offers a unique opportunity to evaluate design solutions under controlled, realistic conditions; prescriptive, modeled performance; and monitored performance assessments. The prescriptive assessment reviews geometry, orientation, envelope thermal properties, and shading. Most houses adopt compact forms, with envelope-to-volume and envelope-to-floor area ratios averaging 1 and 3.7, respectively, and window-to-wall ratios of approximately 17%, favoring north-facing openings to optimize daylight while reducing heat gain. Shading is strategically applied, horizontal on south façades and vertical on east and west. The thermal properties significantly exceed the local code requirements, with wall performance up to 80% better than that mandated. The modeled assessment uses Building Energy Models (BEMs) to simulate the impact of prescriptive measures on energy performance. Three variations are applied: assigning minimum local code requirements to all the houses to isolate the geometry (baseline); removing shading; and applying actual envelope properties. Geometry alone accounts for up to 60% of the variation in cooling intensity; shading reduces loads by 6.5%, and enhanced envelopes lower demand by 14%. The monitored assessment uses contest-period data. Indoor temperatures remain stable (22–25 °C) despite outdoor fluctuations. Energy use confirms that houses with good designs and airtightness have lower cooling loads. Airtightness varies widely (avg. 14.5 m³/h/m²), with some well-designed houses underperforming due to construction flaws. These findings highlight the critical role of passive design as the first layer for improving the energy performance of the built environment and advancing toward net-zero targets, specifically in arid desert climates. Full article

Foraging behavior in hens is an important indicator of animal welfare. It involves both the search for food and exploration of the environment, which provides necessary enrichment. In addition, it has been inversely linked to damaging behaviors such as severe feather pecking. Conventional studies rely on manual observation to investigate foraging location, duration, timing, and frequency. However, this approach is labor-intensive, time-consuming, and subject to human bias. Our study developed computer vision-based methods to automatically detect foraging hens in a cage-free research environment and compared their performance. A cage-free room was divided into four pens, two larger pens measuring 2.9 m × 2.3 m with 30 hens each and two smaller pens measuring 2.3 m × 1.8 m with 18 hens each. Cameras were positioned vertically, 2.75 m above the floor, recording the videos at 15 frames per second. Out of 4886 images, 70% were used for model training, 20% for validation, and 10% for testing. We trained multiple You Only Look Once (YOLO) object detection models from YOLOv9, YOLOv10, and YOLO11 series for 100 epochs each. All the models achieved precision, recall, and mean average precision at 0.5 intersection over union (mAP@0.5) above 75%. YOLOv9c achieved the highest precision (83.9%), YOLO11x achieved the highest recall (86.7%), and YOLO11m achieved the highest mAP@0.5 (89.5%). These results demonstrate the use of computer vision to automatically detect complex poultry behavior, such as foraging, making it more efficient. Full article

Successful dental implant therapy relies on accurate planning and placement, e.g., through static, computer-aided implant surgery using CAD/CAM-fabricated surgical guides. This study examined production methods’ influence on surgical guide sleeve housing geometry. A model with two edentulous spaces was digitized using intraoral scanning and CBCT, and two virtually positioned implants were planned. Ten guides per group were produced using milling (MCX5), DLP printing (ASIGA and SHERA), and SLA printing (FORM), printing with 50 µm and 100 µm layers each. Each guide (n = 70) was then digitized using an industrial scanner before and after sterilization. Superimposition of the actual guide data with the reference data allowed for evaluation of deviations at the drill sleeve housing along the x-, y-, z-, and dxyz-axes. Descriptive and statistical evaluation was performed (significance level: p ≤ 0.0125). Significant differences existed among the production methods: Milling and SLA showed higher deviations than the DLP group (p < 0.001). Milled guides post-sterilization showed the highest deviations (0.352 ± 0.08 mm), while one DLP printer at 50 μm layer thickness showed lowest deviations (0.091 ± 0.04 mm). The layer thickness was insignificant, whereas sterilization increased deviation (p < 0.001). DLP produced the most precise implant surgical guides. All 3D printers were suitable for fabricating clinically acceptable surgical guides. Full article

This paper investigates the cultural landscapes established by nineteenth-century German immigrants in South Australia and the southern Riverina of New South Wales, with particular attention to settlement patterns, architectural traditions and toponymic transformation. German immigration to Australia, though numerically modest compared to the Americas, significantly shaped local communities, especially due to religious cohesion among Lutheran migrants. These settlers established distinct, enduring rural enclaves characterized by linguistic, religious and architectural continuity. The paper examines three manifestations of these cultural landscapes. A rich toponymic landscape was created by imposing on natural landscape features and newly founded settlements the names of the communities from which the German settlers originated. It discusses the erosion of German toponyms under wartime nationalist pressures, the subsequent partial reinstatement and the implications for cultural memory. The study traces the second manifestation of a cultural landscapes in the form of nucleated villages such as Hahndorf, Bethanien and Lobethal, which often followed the Hufendorf or Straßendorf layout, integrating Silesian land-use principles into the Australian context. Intensification of land use through housing subdivisions in two communities as well as agricultural intensification through broad acre farming has led to the fragmentation (town) and obliteration (rural) of the uniquely German form of land use. The final focus is the material expression of cultural identity through architecture, particularly the use of traditional Fachwerk (half-timbered) construction and adaptations such as pug-and-pine walling suited to local materials and climate. The paper examines domestic forms, including the distinctive black kitchen, and highlights how environmental and functional adaptation reshaped German building traditions in the antipodes. Despite a conservation movement and despite considerable documentation research in the late twentieth century, the paper shows that most German rural structures remain unlisted and vulnerable. Heritage neglect, rural depopulation, economic rationalization, lack of commercial relevance and local government policy have accelerated the decline of many of these vernacular buildings. The study concludes by problematizing the sustainability of conserving German Australian rural heritage in the face of regulatory, economic and demographic pressures. With its layering of intangible (toponymic), structural (buildings) and land use (cadastral) features, the examination of the cultural landscape established by nineteenth-century German immigrants adds to the body of literature on immigrant communities, settler colonialism and landscape research. Full article

The impacts of renovation actions on pre- and post-retrofitting building performances are complex to analyse, particularly small and potentially self-actuated actions, such as adding insulation layers to a cold roof slab or changing doors. These interventions are widespread in small residential houses and cases where the owners are the residents. However, a large research gap currently remains regarding the impact of sustainable solutions on building performance. This study aims to address this issue by proposing a methodology based on commercial cloud monitoring solutions and middleware development that analyses and reports on the impact of such solutions to end users, allowing for an analysis of real variations in air temperature levels. The methodology is applied to two single/double-family residential houses, acting as demo cases for verification, across a multi-year time horizon. In both cases, measurements were conducted before and after typical limited renovation actions. Alongside the proposed methodology, descriptions of the smart solutions’ requirements are provided. The results mainly focus on temperature variations. Finally, the impact of the solutions on energy consumption was analysed for one of the buildings, and feedback was briefly provided by the users. Full article

Background: Reliable and non-invasive methods for assessing welfare in poultry are essential for improving evidence-based welfare monitoring and advancing management practices in commercial production systems. The iris-to-pupil (IP) ratio, previously validated by our group in primates and cattle, reflects autonomic nervous system balance and may serve as a physiological indicator of stress in laying hens. This study evaluated the utility of the IP ratio under field conditions across diverse commercial layer housing systems. Materials and Methods: In total, 296 laying hens (Lohmann Brown, n = 269; White Leghorn, n = 27) were studied across four locations in Canada housed under different systems: Guelph (indoor; pen), Spring Island (outdoor and scratch; organic), Ottawa (outdoor, indoor and scratch; free-range), and Toronto (outdoor and hobby; free-range). High-resolution photographs of the eye were taken under ambient lighting. Light intensity was measured using the light meter app. The IP ratio was calculated using NIH ImageJ software (Version 1.54p). Statistical analysis included one-way ANOVA and linear regression using GraphPad Prism (Version 5). Results: Birds housed outdoors had the highest IP ratios, followed by those in scratch systems, while indoor and pen-housed birds had the lowest IP ratios (p < 0.001). Subgroup analyses of birds in Ottawa and Spring Island farms confirmed significantly higher IP ratios in outdoor environments compared to indoor and scratch systems (p < 0.001). The IP ratio correlated weakly with ambient light intensity (r² = 0.25) and age (r² = 0.05), indicating minimal influence of these variables. Although White Leghorn hens showed lower IP ratios than Lohmann Browns, this difference was confounded by housing type; all White Leghorns were housed in pens. Thus, housing system but not breed was the primary driver of IP variation. Conclusions: The IP ratio is a robust, non-invasive physiological marker of welfare assessment in laying hens, sensitive to housing environment but minimally influenced by light or age. Its potential for integration with digital imaging technologies supports its use in scalable welfare assessment protocols. Full article

Environmental air anomaly detection is crucial for ensuring the healthy growth of livestock in smart pig farming systems. This study focuses on four key environmental variables within pig housing: temperature, relative humidity, carbon dioxide concentration, and ammonia concentration. Based on these variables, it proposes a novel encoder–decoder architecture for anomaly detection based on continuous-time models. The proposed framework consists of two embedding layers: an encoder module built around a continuous-time neural network, and a decoder composed of multilayer perceptrons. The model is trained in a self-supervised manner and optimized using a reconstruction-based loss function. Extensive experiments are conducted on a multivariate multi-sequence dataset collected from real-world pig farming environments. Experimental results show that the proposed architecture significantly outperforms existing transformer-based methods, achieving 92.39% accuracy, 92.08% precision, 85.84% recall, and an F₁ score of 88.19%. These findings highlight the practical value of accurate anomaly detection in smart farming systems; timely identification of environmental irregularities enables proactive intervention, reduces animal stress, minimizes disease risk, and ultimately improves the sustainability and productivity of livestock operations. Full article

We consider light, high-absorbance, low-reflectance, electrically large layered sheet structures composed of thin carbon nanotube films. Such structures can be utilized in electromagnetic absorption and shielding applications in the X-band. They are of increasing interest in sensor-enabling technologies, stealth systems, and EMI shielding of electronic components. Especially in aerospace, this is crucial, as sensors are integral to aerospace engineering, enhancing the safety, efficiency, and performance of aircraft and spacecraft. To that end, sheets with carbon nanotube films embedded in a glass fiber polymer matrix are fabricated. The films have a thickness of around 70 μm. As shown, they cause a significant attenuation of the electromagnetic field. For shielding applications, a single-film sheet structure with total thickness of 1.65 mm presents an attenuation of around 25 dB in the transmission coefficient, while the attenuation can reach 37 dB for a two-film sheet structure with thickness of 1.8 mm. Shielding effectiveness performance is found to be greater than 35 dB for the two-film sheet structure. For applications requiring both high shielding and absorption, a two-layered structure with a thickness of 4.65 mm has been designed. The absorption, represented by the Loss Factor, is calculated to achieve values greater than 90%. The simulation results show good agreement with the measured data. The findings demonstrate a promising structure for materials suitable for sensor housings and smart electromagnetic environments where the suppression of electromagnetic interference is critical. In conclusion, the addition of carbon nanotube films, even at micrometer thicknesses, within a glass fiber polymer matrix significantly enhances both electromagnetic shielding and absorption performance. Full article

Rooster behavior and activity are critical for egg fertility and hatchability in broiler and layer breeder houses. Desirable roosters are expected to have good leg health, reach sexual maturity, be productive, and show less aggression toward females during mating. However, not all roosters are desirable, and low-productive roosters should be removed and replaced. The objectives of this study were to apply an object detection model based on deep learning to identify hens and roosters based on phenotypic characteristics, such as comb size and body size, in a cage-free (CF) environment, and to compare the performance metrics among the applied models. Six roosters were mixed with 200 Lohmann LSL Lite hens during the pre-peak phase in a CF research facility and were marked with different identifications. Deep learning methods, such as You Only Look Once (YOLO) models, were innovated and trained (based on a comb size of up to 2500 images) for the identification of male and female chickens based on comb size and body features. The performance matrices of the YOLOv5u and YOLOv11 models, including precision, recall, mean average precision (mAP), and F1 score, were statistically compared for hen and rooster detection using a one-way ANOVA test at a significance level of p < 0.05. For rooster detection based on comb size, YOLOv5lu, and YOLOv11x variants performed the best among the five variants of each model, with YOLOv5lu achieving a precision of 87.7%, recall of 56.3%, and mAP@0.50 of 60.1%, while YOLOv11x achieved a precision of 86.7%, recall of 65.3%, and mAP@0.50 of 61%. For rooster detection based on body size, YOLOv5xu, and YOLOv11m outperformed other variants, with YOLOv5xu achieving a precision of 88.9%, recall of 77.7%, and mAP@0.50 of 82.3%, while YOLOv11m achieved a precision of 89.0%, recall of 78.8%, and mAP@0.50 of 82.6%. This study provides a reference for automatic rooster monitoring based on comb and body size and offers further opportunities for tracking the activities of roosters in a poultry breeder farm for performance evaluation and genetic selection in the future. Full article

This study investigates the development and sensing profile of synthetic melanin nanoparticle-coated electrodes for the electrochemical detection of heavy metals, including lead (Pb), cadmium (Cd), cobalt (Co), zinc (Zn), nickel (Ni), and iron (Fe). Synthetic melanin films were prepared in situ by the deacetylation of diacetoxy indole (DAI) to dihydroxy indole (DHI), followed by the deposition of DHI monomers onto indium tin oxide (ITO) and glassy carbon electrodes (GCE) using cyclic voltammetry (CV), forming a thin layer of synthetic melanin film. The deposition process was characterized by electrochemical quartz crystal microbalance (EQCM) in combination with linear sweep voltammetry (LSV) and amperometry to determine the mass and thickness of the deposited film. Surface morphology and elemental composition were examined using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). In contrast, Fourier-transform infrared (FTIR) and UV–Vis spectroscopy confirmed the melanin’s chemical structure and its polyphenolic functional groups. Differential pulse voltammetry (DPV) and amperometry were employed to evaluate the melanin films’ electrochemical activity and sensitivity for detecting heavy metal ions. Reproducibility and repeatability were rigorously assessed, showing consistent electrochemical performance across multiple electrodes and trials. A comparative analysis of ITO, GCE, and graphite electrodes was conducted to identify the most suitable substrate for melanin film preparation, focusing on stability, electrochemical response, and metal ion sensing efficiency. Finally, the applicability of melanin-coated electrodes was tested on in-house heavy metal water samples, exploring their potential for practical environmental monitoring of toxic heavy metals. The findings highlight synthetic melanin-coated electrodes as a promising platform for sensitive and reliable detection of iron with a sensitivity of 106 nA/ppm and a limit of quantification as low as 1 ppm. Full article

Ambrosia beetles have evolved specialized structures termed “mycangia”, which house and transport symbiotic microbes. Microbial partners include at least one obligate mutualistic filamentous fungus used as food for larvae and adults, and potentially secondary filamentous fungi, yeasts, and bacteria. Beetles in the genus Xyleborus possess paired pre-oral mycangial structures located within the head on either side of the mouth parts. Mycangia develop in pupae, with newly emerged adults acquiring partners from the environment. However, information concerning the cellular structure and function of Xyleborus mycangia remains limited. We show that in X. affinis, mycangia are lined with a layer of striated dense material, enclosing layers of insect epithelial cells, with diverse spine-like structures. Larger (5–10 μm) projections were concentrated within and near the entrance of mycangia, with smaller filaments (4–8 μm) within the mycangia itself. Rows of “eyelash” structures lined the inside of mycangia, with fungal cells free-floating or in close association with these projections. Serial sections revealed mandibular articulations, and mandibular, pharyngeal, and labial muscles, along with the mycangial entry/exit channel. Sheets of comb-like spines at the mycangial entrance and opposite the mycangia attached to the roof of the labrum or epipharynx may serve as an interlocking mechanism for opening/closing the mycangia and guiding fungal cells into entry/exit channels. Additionally, mandibular fibra (muscle tissue) potentially enervating and affecting the mechanism of mycangial functioning were noted. These data add crucial mechanistic detail to the model of pre-oral mycangia in Xyleborus beetles, their cellular structures, and how they house and dispense microbial symbionts. Full article

Studies of positional (=locomotor and postural) behavior are central to understanding how animals interact with the challenges imposed by their environment and are crucial for conservation management. The present study investigates, for the first time, the positional behavior and substrate use of the endangered southern pygmy slow loris Xanthonycticebus pygmaeus. Despite their very specialized morphology and ecology, the positional behavior of lorises is understudied. Behavioral data were collected using 30-s scan instant sampling on seven captive animals housed in a large, enriched enclosure of the Poznań Nowe Zoo (Poland) during February–June 2013. Pygmy slow lorises were almost exclusively arboreal and most activities occurred on multiple substrates (82.93%). Small (57.91%) and large (28.28%) substrates were extensively used. Horizontal (42.11%) and oblique (38.47%) substrates dominated. Clamber (39.39%), quadrupedalism (33.77%), and vertical climb (17.62%) were the main locomotor modes. Standing was the dominant posture (47.23%), followed by hanging (27.32%) and clinging (11.31%). Our results concur with the limited observations available on other lorisines; pygmy slow lorises employed a diverse and flexible positional repertoire as an adaptation to the exploitation of the continuous forest layers with intertwined small substrates of various inclinations. Consequently, protecting and managing these habitats, supported by ex situ reintroduction programs, can effectively contribute to the conservation of the species’ populations. Full article

Accurately determining HER2 status is essential for breast cancer treatment. We developed an AI-integrated in-house application for automated Dual bright-field (BF) in situ hybridization (ISH) analysis on whole slide images (WSIs), although optimal scanning conditions remain unclear. We evaluated scanners and optimized scanning protocols for clinical application. Ten de-identified invasive breast carcinoma cases, with HER2 immunohistochemistry and FISH results, were analyzed using three scanners and six scanning protocols. WSIs scanned by Scanner ‘A’ have 0.12 µm/pixel with 0.95 NA (A1) and 1.2 NA (A2); Scanner ‘B’ have 0.08 µm/pixel (B1); 0.17 µm/pixel (B2); and 0.17 µm/pixel with extended focus (1.4 µm step size and three layers) (B3); Scanner ‘C’ has 0.26 µm/pixel (C1) resolution. Results showed scanning protocols A1, A2, B2, and B3 yielded HER2 gene amplification status and ASCO/CAP ISH group results consistent with manual FISH as the ground truth. However, protocol C demonstrated poor concordance due to nuclei detection failure in six cases. The AI-integrated application achieved the best performance using scanning protocols with optimized resolutions of 0.12 µm/pixel and 0.17 µm/pixel with extended focus. This study highlights the importance of scanner selection in AI-based HER2 assessment and demonstrates that optimized scanning parameters enhance the accuracy and reliability of automated Dual BF ISH analysis. Full article

This study examines the climate adaptability of traditional Hani ‘Mushroom Houses’ located in the rice terrace region of Honghe Hani Autonomous Prefecture, Yunnan, China. By analyzing 30 years of meteorological data, the study identifies the local climatic characteristics of high temperatures, high humidity, and significant diurnal temperature variations. The thermal comfort voting method was used to establish a quantitative relationship between the Physiological Equivalent Temperature (PET) index and residents’ subjective thermal perceptions, thereby assessing seasonal variations in thermal comfort. Field measurements of indoor and outdoor temperature, humidity, and wind speed were conducted in May and December 2023 to evaluate thermal interactions between rooms. This study demonstrated: (1) the critical roles of building orientation (e.g., northwest-facing design), functional layout (e.g., multi-story zoning), and structural forms (e.g., thick walls, thatched roofs) in regulating temperature and humidity. (2) Confirmed that Hani ‘Mushroom Houses’ stabilize indoor environments through passive strategies, including material selection (wood, rammed earth), natural ventilation (cross-draft design), and spatial organization (climate-buffering storage layers). (3) Provided empirical evidence for optimizing traditional dwellings (e.g., enhanced insulation, ventilation improvements) and advancing sustainable practices in similar climatic regions. Full article

We present the performance and application of a commercial off-the-shelf Si PIN diode (Hamamatsu S14605) as a charged particle detector in a compact ion beam system (IBS) capable of generating D–D and p–B fusion charged particles. This detector is inexpensive, widely available, and operates in photoconductive mode under a reverse bias voltage of 12 V, supplied by an A23 battery. A charge-sensitive preamplifier (CSP) is mounted on the backside of the detector’s four-layer PCB and powered by two ±3 V lithium batteries (A123). Both the detector and CSP are housed together on the vacuum side of the IBS, facing the fusion target. The system employs a CF-2.75-flanged DB-9 connector feedthrough to supply the signal, bias voltage, and rail voltages. To mitigate the high sensitivity of the detector to optical light, a thin aluminum foil assembly is used to block optical emissions from the ion beam and target. Charged particles generate step responses at the preamplifier output, with pulse rise times in the order of 0.2 to 0.3 µs. These signals are recorded using a custom-built data acquisition unit, which features an optical fiber data link to ensure the electrical isolation of the detector electronics. Subsequent digital signal processing is employed to optimally shape the pulses using a CR-RCⁿ filter to produce Gaussian-shaped signals, enabling the accurate extraction of energy information. Performance results indicate that the detector’s baseline RMS ripple noise can be as low as 0.24 mV. Under actual laboratory conditions, the estimated signal-to-noise ratios (S/N) for charged particles from D–D fusion—protons, tritons, and helions—are approximately 225, 75, and 41, respectively. Full article