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Biodiversity credits are more problematic than carbon credits

Bayesian predictive system for assessing the damage intensity of residential masonry buildings under the impact of continuous ground deformation

AbstractThe paper introduces a method for predicting damage intensity in masonry residential buildings situated in mining areas, focusing on the impact of large-scale continuous ground deformation. The research utilizes in situ data collected in a database, encompassing structural and material features, as well as information on maintenance quality and building durability. In addition to this information, the database collected data on the intensity of continuous deformation of the mining area at the location of the building, as well as the range and intensity of damage identified in buildings. The information included in the database was the result of many years of observations of buildings during the disclosure of impacts from mining exploitation and was based on: the results of in-situ building inventory, analysis of available building documentation and information provided by mining companies. The archived data were categorized variables labeled. The transformation of the data to a labeled value was dictated directly by the assumptions of the GOBNILP algorithm. Ultimately, a predictive model, represented by an optimal Bayesian network structure, is established. The optimisation of the network structure is achieved through the adaptation of the GOBNILP Bayesian network learning algorithm from data. This optimisation process is executed through the Gurobi Optimizer. It is worth noting that this interdisciplinary approach represents one of the first applications of such a methodology in the field of civil and environmental engineering. The results obtained can therefore be of significant value given the fact that the methodology of detecting the structure of Bayesian networks from data is still developing intensively in other scientific fields. In the course of the analyses, metric scores are examined, and various network structures are assessed based on their complexity. Great values of classification accuracies over 91% were obtained. This meticulous evaluation allows for the selection of the optimal Bayesian network that best generalises the knowledge acquired during the learning process. The paper also demonstrates the potential application of the obtained model in diagnosing damage causes and predicting future occurrences, highlighting the versatility of the proposed approach for addressing issues in the field.

Deep learning-integrated MRI brain tumor analysis: feature extraction, segmentation, and Survival Prediction using Replicator and volumetric networks

Evaluation of LLMs accuracy and consistency in the registered dietitian exam through prompt engineering and knowledge retrieval

To ensure trust, AI weather-forecast models still need training in physics

Author Correction: Pathophysiology of high fat diet induced obesity: impact of probiotic banana juice on obesity associated complications and hepatosteatosis

Machine learning algorithms for predicting delayed hyponatremia after transsphenoidal surgery for patients with pituitary adenoma

Magnetic nano-sized solid acid catalyst bearing sulfonic acid groups for biodiesel synthesis and oxidation of sulfides

‘One of the last taboos’: breaking the stigma of substance-use disorders in academia

The lightweight design of steel pistons for diesel engines based on thermo-mechanical characteristics

Uncovering genetic determinants of antioxidant properties in Thai landrace rice through genome-wide association analysis

The trill of the chase: recording birdsong in Ireland’s disappearing wilderness

Denture care attitudes, hygiene levels and oral mucosal lesions in complete denture wearers from a single-institution cross‐sectional study

Incidence and risk factors of postoperative delirium in elderly surgical patients 2023

Coupling mechanisms of plasmon resonance and Bi3+ emission in YAG: Bi, Ce, Yb epitaxial films at low temperatures

Fancy birds decorate nests with a natural pattern: snakeskin

An exploratory study on the perception of the over-the-top (OTT) industry among film and media production major university students: Utilizing the Q methodology

This study investigates the perceptions of university students majoring in film and media production (FMP) regarding the over-the-top (OTT) industry. We used the Q methodology to achieve this study’s purpose, with 33 Q sets and 22 university students majoring in FMP. The study revealed three perception structures of FMP major university students regarding the OTT industry. Type 1 considered the diversity and accessibility of OTT to be important from the consumer’s perspective, and Type 2 emphasized the importance of improving the quality of content from the producer’s perspective. Even though Type 3 considered the OTT industry an excellent platform, they tended to think of movies in theaters as the final destination. Based on the study’s results, all types thought that the growth and development of the OTT industry would continue. However, the study demonstrated that they need perceptions from a macroscopic viewpoint in areas related to OTT industry technology, education, and systems.

FBP1 controls liver cancer evolution from senescent MASH hepatocytes

Canine urothelial cell model to study intracellular bacterial community development by uropathogenic Escherichia coli

Urinary tract infections (UTIs) are among the most common bacterial infections of both dogs and humans, with most caused by uropathogenic Escherichia coli (UPEC). Recurrent UPEC infections are a major concern in the treatment and management of UTIs in both species. In humans, the ability of UPECs to form intracellular bacterial communities (IBCs) within urothelial cells has been implicated in recurrent UTIs. However, the role of IBCs has not been explored in the pathogenesis of canine recurrent UTIs. In this study, we identified IBCs in both urine and bladder tissue from dogs with UPEC associated UTIs. In addition, we showed that UPECs derived from canine UTIs form IBCs within primary canine urothelial cells. As in human UTIs, formation of IBCs by canine UPECs correlated with the presence of the fimH gene as those isolates lacking the fimH gene formed fewer IBCs in canine urothelial cells then those harboring the fimH gene. Additionally, UPEC strains from clinical cases classified as recurrent UTIs had higher rates of IBC formation than UPEC strains from non-recurrent UTIs. These IBCs were tolerant to treatment with enrofloxacin, cefpodoxime and doxycycline at 150, 50 and 50 μg/mL respectively, which are representative of the concentrations achieved in canine urine after standard dosing. This is consistent with the clinical perspective that current UTIs are a common condition of dogs and are difficult to manage through antimicrobial treatment. Additionally, the dog could prove to be a powerful model of IBC formation as they are natural models of UPEC-causing UTIs and have similar pathophysiology of IBC formation.

Experiences of fasting during Ramadan in British Muslims: Psychological, social and health behaviours

Ramadan is a month-long religious festival observed by Muslim worldwide, characterised by intermittent fasting. This qualitative study addressed the need to understand how fasting is experienced by Muslims residing in Western cultures, aiming to inform policies that create a more supportive environment. Practicing Muslims, both men and women, were recruited in the North of England in the United Kingdom (UK). Data were collected by individual interviews (N = 7) and focus group discussion (N = 4) and then analysed using Social Ecological Theory as a framework. Fasting was managed at the individual level through instrumental food choice and eating practices, and by adapting sleep routines. Disrupted sleep routines posed a challenge for those who had to adhere to Western working schedules, leading to perceived detriments to cognitive function and mood. The sense of belonging associated with Ramadan was seen as a motivating factor for fasting. Breaking the fast (Iftar) was marked by social activity and the availability of traditional fried foods. Participants identified the wider Western culture and environment as challenging for those who are fasting. These findings imply a need for policies that enable flexible working practices for Muslims during Ramadan.