Search Results (7,442)

The increasing costs of traditional protein sources, such as soybean meal (SBM), have prompted interest in alternative feeds for ruminants. Non-protein nitrogen (NPN) sources, like urea, offer a cost-effective alternative by enabling rumen microorganisms to convert NPN into microbial protein, which is crucial for ruminant nutrition. However, the rapid hydrolysis of urea in the rumen can result in excessive ammonia (NH₃) production and potential toxicity. Slow-release urea (SRU) has been developed to mitigate these issues by gradually releasing nitrogen, thereby improving nutrient utilization and reducing NH₃ toxicity risks. This review explores SRU’s development, types, mechanisms, and benefits, highlighting its potential to enhance ruminal fermentation, microbial protein synthesis, and overall feed efficiency. SRU formulations include polymer-coated urea, lipid-coated urea, calcium-urea, starea, and zeolite-impregnated urea, each designed to control nitrogen release and minimize adverse effects. Studies have demonstrated that SRU can improve microbial nitrogen efficiency and reduce nitrogen losses, although results regarding feed intake, digestibility, and milk yield are mixed. These discrepancies indicate that factors such as SRU type, diet formulation, and animal breed may influence outcomes. Continued research is essential to optimize SRU applications, aiming to enhance ruminant production, economic viability, and environmental stewardship. Full article

We report a case of a 16-year-old girl presenting to our clinic with decreased visual acuity and increased intraocular pressure in both eyes. The ophthalmological examination revealed best-corrected visual acuity (BCVA) of 0.3 in the right eye (R.E.) and 0.4 in the left eye (L.E.) and intraocular pressure (IOP) of 46 mmHg in the R.E. and 42 mmHg in the L.E., with a 360° closed angle on gonioscopy, pupillary block due to bulging, a hyper-spherical lens and high corneal thickness, without ectopia lentis or cataract. The eyes responded poorly to pharmacological mydriasis; therefore, the lens equator could not be visualised. The patient had a history of pulmonary stenosis, short stature and no significant cognitive deficits. These elements point to the diagnosis of Weill–Marchesani syndrome, and the ophthalmological management was surgical, including lens extraction and the installation of a capsular tension ring, an intraocular lens and a Shunt ExPress implantation. Evolution was favourable, with improved BCVA of 0.7 in the R.E. and 0.63 in the L.E. and IOP of 14 mmHg in the R.E. and 13 mmHg in the L.E., without topical or systemic treatment at the 6-month follow-up. Weill–Marchesani syndrome has a complex presentation, with ophthalmological, musculoskeletal, cardiac and psychiatric manifestations. Usually, this leads to a need for a multidisciplinary approach. The ophthalmologic symptoms are often the cause of presentation to a specialist, and glaucoma is the most threatening of the ocular pathologies, with possible evolution into irreversible blindness; therefore, prompt surgery and careful follow-up become key components of the treatment plan. As a take-home message, we encourage a high degree of suspicion of Weill–Marchesani syndrome in such cases. Full article

In the process of shield tunneling, the cutter will inevitably be worn and damaged and will need to be replaced frequently. The low efficiency and high safety risk of traditional manual cutter change have prompted robotic cutter change to become the mainstream trend of current research. However, it is difficult to realize mechanical automation disassembly due to the existence of many fragmented parts and complex disassembly steps in the traditional cutter system. Therefore, this paper proposes an eccentric integrated cutter system, which greatly simplifies the disassembly process while retaining the excellent fastening structure of the traditional cutter system. The evaluation system of the cutter system was established through the analytic hierarchy process, and it was verified that the eccentric integrated cutter system has obvious superiority in realizing automated disassembly and assembly and, at the same time, that it has good structural strength. Finally, vibration experiments were carried out based on shield construction conditions. The experimental results show that after 14 h of continuous vibration, the residual preload ratio of the integrated cutter sample stabilized at more than 90%, which indicates good anti-loosening performance. Full article

Background: Lameness in cattle negatively affects welfare and productivity. Early identification of lameness allows for prompt treatment, and mobility scoring allows for herd-level prevalence data to be monitored. The reliability of a four-point mobility scoring system was investigated when used by beef farmers and veterinary surgeons. Methods: An online questionnaire that contained forty video clips of beef cattle was created for mobility scoring performed by farmers and vets. Results: The Fleiss kappa coefficient for inter-observer agreement across all 81 respondents and all videos was 0.34, which showed fair agreement. Beef farmers generally had lower agreement than vets (0.29 vs. 0.38). Vets had significantly higher inter-observer reliability compared to beef farmers (p = 0.035). Overall, Cohen’s kappa coefficient for intra-observer agreement across all respondents varied from 0.085 (slight agreement) to 0.871 (almost perfect agreement). Limitations: The survey was only available online, which may have limited distribution and engagement. The recruitment of participants was not specific to differing levels of previous experience in mobility scoring. The mobility scoring was not performed in person, which could be more reflective of clinical application. Conclusions: The application of a four-point mobility scoring system for beef cattle had fair inter-observer reliability and a wide range of intra-observer reliability, but this is poorer than previously reported. This presents a challenge for the identification of lame beef cattle at both the individual and herd levels. Full article

Chiari malformation type 1 (CM1) is a structural defect that involves the herniation of the cerebellar tonsils through the foramen magnum, causing mild to severe neurological symptoms. Little is known about the molecular and developmental mechanisms leading to its pathogenesis, prompting current efforts to elucidate genetic drivers. Inherited genetic disorders are reported in 2–3% of CM1 patients; however, CM1, including familial forms, is predominantly non-syndromic. Recent work has focused on identifying CM1-asscoiated variants through the study of both familial cases and de novo mutations using exome sequencing. This article aims to review the current understanding of the genetics of CM1. We discuss three broad classes of CM1 based on anatomy and link them with genetic lesions, including posterior fossa-linked, macrocephaly-linked, and connective tissue disorder-linked CM1. Although the genetics of CM1 are only beginning to be understood, we anticipate that additional studies with diverse patient populations, tissue types, and profiling technologies will reveal new insights in the coming years. Full article

Raman spectroscopy is a technique which involves quantitative and qualitative molecular analysis based on the interaction between incident light and isolation of scattered wavelengths in generating a molecular fingerprint. It has a broad array of potential scientific applications, encompassing areas as diverse as food science and forensics. However, it may also be highly useful in clinical oncology. A recent focus of research in oncology has been in achieving the individualisation of care. Two important strategies to achieve a so-called “precision oncology” approach may include the detection of circulating tumour DNA (ctDNA) in more objectively evaluating treatment response and guiding de-escalation and intensification approaches in systemic therapy and therapeutic drug monitoring (TDM). Therapeutic drug monitoring involves the quantitation of plasma drug levels in order to tailor medication dosing in optimizing outcomes. The existing approaches to characterize small molecules, such as fluorescence-based and chromatographic strategies, may be limited by high costs, long turnaround times, and bulky equipment. Surface-enhanced Raman spectroscopy (SERS) may be deployed by utilizing a handheld device, with the potential for point of care, rapid turnaround, low-cost assessment of clinically relevant parameters, and prompt implementation of attendant changes in treatment. Although there is a growing body of data supporting the implementation of TDM and evaluation of ctDNA in achieving precision medicine, the uptake of such approaches remains relatively limited outside of clinical trials. As stated, the nature of existing analytical methodologies may prove to be a significant barrier to the routine clinic-based implementation of such approaches. Therefore, we provide the existing evidence for SERS in alleviating these barriers. We also provide insights into how SERS could contribute to clinical oncology. Full article

All 32 Brazilian species of Parodia Speg (Cactaceae) occurring in Rio Grande do Sul State are considered threatened, according to the IUCN criteria. Until 2021, Parodia rechensis (CR) was known by only two small populations. However, a new population with over 400 individuals was discovered in 2021, prompting the study of its reproductive biology as a way to promote its conservation. Anthesis, breeding system, and natural pollination were studied in the field. The breeding system was studied by applying controlled pollination treatments to plants excluded from pollinators (bagged). Germination features were studied at the Seed Bank of the Porto Alegre Botanical Garden under controlled temperatures (20, 25, and 30 °C). The anthesis is diurnal and lasts for up to four days. The flowers offer pollen as the sole resource to the pollinators. The study species is unable to set fruit and seed without the agency of pollinators and has self-incompatible (unable to set fruit and seeds when pollinated with pollen of the same individual) characteristics that can considerably restrict its reproduction. Native bees of Halictidae and Apidae (Hymenoptera) are the main pollinators, with a smaller contribution of Melyridae (Coleoptera) and Syrphidae (Diptera). Natural fruit set is moderate (≤64%, per individual), but the species presents vegetative growth, producing several branches from the mother plant. Seeds showed the optimum germination rate at 20 °C and an inhibition of 75% in germinability at 30 °C. Our findings suggest the need to manage the species’ habitat to guarantee the permanency of the plants and healthy populations of pollinators as well. Our findings raise concerns about the germination and establishment of new individuals in the context of rising temperatures caused by climate change. Suggestions for the possible management of the extant populations are made. Full article

As an essential thrombolytic agent, the tissue plasminogen activator receives increasing attention due to its longer half-life, lower immunogenicity, and easier administration, which are superior to other thrombolytic agents. In this study, the isolated and purified plasminogen activator from the sandworm (Perinereis aibuhitensis) was expressed in E. coli (Escherichia coli) to investigate its potential for simplifying the development process. The sandworm plasminogen activator was previously successfully cloned and expressed in E. coli with low yield and activity in the culture supernatant. This low yield and activity prompted us to optimize its DNA sequence. Furthermore, to raise the efficiency in the separation of the target protein, the protein’s solubility was enhanced by fusing it with maltose-binding protein (MBP) tags. Eventually, the fibrinolytic activity was successfully restored after digestion with tobacco etch virus (TEV) protease. This study provides an innovative method of efficiently expressing and purifying plasminogen activators from sandworm in E. coli and broadens its applications in therapeutic treatment of cardiovascular diseases, including thrombosis, stroke, and coronary atherosclerotic heart disease. Full article

This article proposes an underappreciated value for traditional natural theology and its familiar arguments for the existence of God, without endorsing the soundness or the rational cogency of these arguments. Famously, Aquinas and Kant represent two extremes, with Aquinas endorsing some natural theology arguments for God’s existence and Kant opposing such arguments. This article recommends a moderating approach, on the grounds that while Aquinas is unduly optimistic here by the epistemic standards of many inquirers, Kant is too pessimistic regarding the heuristic value of the relevant natural theology arguments. The neglected heuristic value of these arguments, according to this article, is in their prompting in unique ways some challenging and fruitful questions for inquiry about God. The disputed natural theology arguments have not achieved anything near a consensus on their soundness or rational cogency, but they still can have significant heuristic value aside from their soundness or rational cogency. This article identifies the relevant fruitful questions and their theoretical importance for human inquiry about God. Ultimately, a heuristic interrogative approach to familiar arguments of natural theology gives these arguments a new role with resilient heuristic value for inquiry about God, even if they do not justify the belief that God exists. Such moderation, this article contends, is rationally defensible with regard to these arguments. Full article

This study investigates the integration of generative AI in higher education and the development of the SPARRO framework, a structured approach to improving human–AI interaction in academic settings. This ethnographic study explores the integration of generative AI in healthcare and nursing education, detailing the development of the SPARRO framework based on observations of student and faculty interactions with AI tools across five courses. The study identifies key challenges such as AI hallucination, mistrust of AI-generated summaries, and the difficulty in formulating effective prompts. The SPARRO framework addresses these challenges, offering a step-by-step guide for planning, prompt design, reviewing, and refining AI outputs. While the framework shows promise in improving AI integration, future research is needed to validate its applicability across other academic disciplines and assess its long-term impact on critical thinking and academic integrity. This study contributes to the growing body of research on AI in education, offering practical solutions for ethically and effectively integrating AI tools in academic settings. Full article

Research has demonstrated that engagement in any learning environment improves learning and may even boost performance. Consequently, numerous scholars have examined various approaches to raising student engagement in learning. Gamification is one such approach because it is thought to increase motivation and reduce cognitive load to ultimately improve learning outcomes. However, some studies have called into question its benefits, prompting more research to be conducted to properly understand the phenomenon. Hence, the study examined gamification’s influence on motivation and cognitive load for enhancing learning engagement. The study was underpinned by the integration of the Attention, Relevance, Confidence, and Satisfaction (ARCS) model, self-determination theory (SDT), and cognitive load theory (CLT) in developing a conceptual framework. A sample of 407 university students who participated in five gamified courses were involved in the study. The data collected through a questionnaire were analyzed using SmartPLS structural equation modeling software. According to the study’s findings, both motivation and cognitive load influence engagement in learning, with cognitive load being the stronger influence. The study contributes to our knowledge by elucidating the relationship between gamification and students’ cognitive load and motivation to learn, as well as how these elements ultimately engage students in the learning process. Full article

This study introduces a novel architecture for value, preference, and boundary alignment in large language models (LLMs) and generative AI systems, accompanied by an experimental implementation. It addresses the limitations in AI model trustworthiness stemming from insufficient comprehension of personal context, preferences, and cultural diversity, which can lead to biases and safety risks. Using an inductive, qualitative research approach, we propose a framework for personalizing AI models to improve model alignment through additional context and boundaries set by users. Our framework incorporates user-friendly tools for identification, annotation, and simulation across diverse contexts, utilizing prompt-driven semantic segmentation and automatic labeling. It aims to streamline scenario generation and personalization processes while providing accessible annotation tools. The study examines various components of this framework, including user interfaces, underlying tools, and system mechanics. We present a pilot study that demonstrates the framework’s ability to reduce the complexity of value elicitation and personalization in LLMs. Our experimental setup involves a prototype implementation of key framework modules, including a value elicitation interface and a fine-tuning mechanism for language models. The primary goal is to create a token-based system that allows users to easily impart their values and preferences to AI systems, enhancing model personalization and alignment. This research contributes to the democratization of AI model fine-tuning and dataset generation, advancing efforts in AI value alignment. By focusing on practical implementation and user interaction, our study bridges the gap between theoretical alignment approaches and real-world applications in AI systems. Full article

Climate change significantly impacts transportation infrastructure, particularly asphalt pavements. Similarly, the heat absorption of paved surfaces, especially conventional black pavements, significantly intensifies the urban microclimate. Paved surfaces, including asphalt pavements, account for over 30% of the covered surfaces and are vulnerable to rising temperatures, which cause not only pavement distress, such as rutting and cracking, but also urban heat islands (UHI). Sustainable pavement solutions, specifically colored pavements, have been investigated for their potential to mitigate these effects. This review presents an extensive overview of current pavement technologies, emphasizing conventional asphalt’s economic, environmental, and functional characteristics. A discussion of the benefits and challenges of colored pavements is also provided, including their ability to reduce UHI, enhance safety, and contribute to sustainable urban growth. This paper discusses advancements in pavement material science, the use of recycled materials, and the application of reflective coatings, providing insights into sustainable infrastructure development. Transitioning from conventional black pavements to sustainable colored alternatives is not merely a matter of material choice but a strategic transition toward resilient urban planning. Increasing demand for environmentally friendly infrastructure could prompt the construction industry to adopt colored pavements as a tool to promote environmental stewardship. Full article

Pneumonia is an inflammation of lung tissue caused by various infectious microorganisms and noninfectious factors. It affects people of all ages, but vulnerable age groups are more susceptible. Imaging techniques, such as chest X-rays (CXRs), are crucial in early detection and prompt action. CXRs for this condition are characterized by radiopaque appearances or sometimes a consolidation in the affected part of the lung caused by inflammatory secretions that replace the air in the infected alveoli. Accurate early detection of pneumonia is essential to avoid its potentially fatal consequences, particularly in children and the elderly. This paper proposes an enhanced framework based on convolutional neural network (CNN) architecture, specifically utilizing a transfer-learning-based architecture (MobileNet V1), which has outperformed recent models. The proposed framework is improved using a hybrid method combining the operation of two optimization algorithms: the dung beetle optimizer (DBO), which enhances exploration by mimicking dung beetles’ navigational strategies, and Fick’s law algorithm (FLA), which improves exploitation by guiding solutions toward optimal areas. This hybrid optimization effectively balances exploration and exploitation, significantly enhancing model performance. The model was trained on 7750 chest X-ray images. The framework can distinguish between healthy and pneumonia, achieving an accuracy of 98.19 ± 0.94% and a sensitivity of 98 ± 0.99%. The results are promising, indicating that this new framework could be used for the early detection of pneumonia with a low cost and high accuracy, especially in remote areas that lack expertise in radiology, thus reducing the mortality rate caused by pneumonia. Full article

Hypokalemia is a common laboratory finding in hospitalized patients, typically resulting from insufficient potassium intake, renal or gastrointestinal losses, or intracellular shifts. While the underlying cause is often easily identifiable, certain cases present diagnostic challenges, and if left unrecognized, the consequences can be life-threatening. We report a rare and atypical case of severe symptomatic hypokalemia as the initial presentation of newly diagnosed Graves’ disease. The condition was caused by thyrotoxic periodic paralysis, a rare but serious complication of thyrotoxicosis, predominantly seen in East Asian populations. This disorder is characterized by episodes of acute, reversible muscle weakness associated with transient hypokalemia, which increases the risk of falls and traumatic injuries. The prompt identification of the etiology in such cases is critical for preventing recurrence and avoiding potentially fatal complications. Full article