Feasibility of waste-derived hydroxyapatite mixed with ultra high molecular weight polyethylene composites for fused deposition modeling process

In this study, feasibility of waste-derived hydroxyapatite (HAp) reinforced UHMWPE composites for Fused Deposition Modeling (FDM) process was investigated. Compared to the commercial HAp, derived from natural resources such as corals, fish bone and eggshells have been converted into HAp and show the similarity with the commercial HAp. Ca/P ratio was so important to human body because Ca influence growth of human bones and P play a role in immune system activation. This research has used waste eggshell has been used to synthesize HAp by using hydrothermal synthesis. The Ca/P ratio was investigated by using SEM/EDS and XRD test. By using these test, it revealed Ca/P ratio of waste-derived HAp has shown 1.69 approximately with the standard Ca/P ratio (1.67). HAp/UHMWPE composites formulation samples were prepared by mixed between HAp and UHMWPE using Brabender Mixer. HAp/UHMWPE composite formulation samples were characterized by their weight percentage. The feasibility of each HAp/UHMWPE composite samples has been studied by their morphology, thermal and rheology properties by using SEM/EDS, TGA/DSC and Rheology test. Formulation sample U50H50 with 50 wt.% of HAp has shown the homogenous mixture, 1.69 Ca/P ratio, lowest melting point and good pseudo-plastic behavior compared to other formulation samples. Therefore, this formulation samples has been used in single screw extruder to fabricate diameter size of 1.75+0.05 mm filament wire for FDM process. DOE has been developed by using Taguchi method with the parameter controlled were die temperature and screw frequency. The optimum parameter setting to produce the diameter of 1.75+0.05 mm filament wire was successfully found at screw frequency of 2.5 Hz and die temperature of 190 ºC. The characteristic of the FDM process shows the samples with optimum dimensional accuracy and relative density was found at 245 ºC of temperature nozzle and 130 ºC of temperature platform. This result shown Hap/UHMWPE composite has potential to become material filament wire feedstock for FDM process

With No Deliberate Speed: The Segregation of Roma Children in Europe

In this study, by taking the advantage of both inorganic ZnO nanoparticles and the organic material chitosan as a composite seed layer, we have fabricated well-aligned ZnO nanorods on a gold-coated glass substrate using the hydrothermal growth method. The ZnO nanoparticles were characterized by the Raman spectroscopic techniques, which showed the nanocrystalline phase of the ZnO nanoparticles. Different composites of ZnO nanoparticles and chitosan were prepared and used as a seed layer for the fabrication of well-aligned ZnO nanorods. Field emission scanning electron microscopy, energy dispersive X-ray, high-resolution transmission electron microscopy, X-ray diffraction, and infrared reflection absorption spectroscopic techniques were utilized for the structural characterization of the ZnO nanoparticles/chitosan seed layer-coated ZnO nanorods on a gold-coated glass substrate. This study has shown that the ZnO nanorods are well-aligned, uniform, and dense, exhibit the wurtzite hexagonal structure, and are perpendicularly oriented to the substrate. Moreover, the ZnO nanorods are only composed of Zn and O atoms. An optical study was also carried out for the ZnO nanoparticles/chitosan seed layer-coated ZnO nanorods, and the obtained results have shown that the fabricated ZnO nanorods exhibit good crystal quality. This study has provided a cheap fabrication method for the controlled morphology and good alignment of ZnO nanorods, which is of high demand for enhancing the working performance of optoelectronic devices

Bayesian inference of the evolution of a phenotype distribution on a phylogenetic tree

The distribution of a phenotype on a phylogenetic tree is often a quantity of interest. Many phenotypes have imperfect heritability, so that a measurement of the phenotype for an individual can be thought of as a single realisation from the phenotype distribution of that individual. If all individuals in a phylogeny had the same phenotype distribution, measured phenotypes would be randomly distributed on the tree leaves. This is however often not the case, implying that the phenotype distribution evolves over time. Here we propose a new model based on this principle of evolving phenotype distribution on the branches of a phylogeny, which is different from ancestral state reconstruction where the phenotype itself is assumed to evolve. We develop an efficient Bayesian inference method to estimate the parameters of our model and to test the evidence for changes in the phenotype distribution. We use multiple simulated datasets to show that our algorithm has good sensitivity and specificity properties. Since our method identifies branches on the tree on which the phenotype distribution has changed, it is able to break down a tree into components for which this distribution is unique and constant. We present two applications of our method, one investigating the association between HIV genetic variation and human leukocyte antigen, and the other studying host range distribution in a lineage of Salmonella enterica, and we discuss many other potential applications. All the methods described in this paper are implemented in a software package called TreeBreaker which is freely available for download at https://github.com/ansariazim/TreeBreaker

Agent-based Learning of Materials Datasets from Scientific Literature

Advancements in machine learning and artificial intelligence are transforming materials discovery. Yet, the availability of structured experimental data remains a bottleneck. The vast corpus of scientific literature presents a valuable and rich resource of such data. However, manual dataset creation from these resources is challenging due to issues in maintaining quality and consistency, scalability limitations, and the risk of human error and bias. Therefore, in this work, we develop a chemist AI agent, powered by large language models (LLMs), to overcome these challenges by autonomously creating structured datasets from natural language text, ranging from sentences and paragraphs to extensive scientific research articles. Our chemist AI agent, Eunomia, can plan and execute actions by leveraging the existing knowledge from decades of scientific research articles, scientists, the Internet and other tools altogether. We benchmark the performance of our approach in three different information extraction tasks with various levels of complexity, including solid-state impurity doping, metal-organic framework (MOF) chemical formula, and property relations. Our results demonstrate that our zero-shot agent, with the appropriate tools, is capable of attaining performance that is either superior or comparable to the state-of-the-art fine-tuned materials information extraction methods. This approach simplifies compilation of machine learning-ready datasets for various materials discovery applications, and significantly ease the accessibility of advanced natural language processing tools for novice users in natural language. The methodology in this work is developed as an open-source software on https://github.com/AI4ChemS/Eunomia

The continuum relationship of aesthetic and social space in the dhikr performativity of the Sambas Malay in West Kalimantan

Studies on performative issues in ritual practices often detach social practices from performative studies, emphasizing aesthetic elements instead. This separation creates a divide between aesthetic and social practices. This study seeks to describe dhikr practices that reinforce performative aspects by examining the continuum between aesthetic and social spaces. It highlights the importance of the reciprocal relationship between these two domains, which ultimately redefines the spaces where aesthetic and social practices are performed. The research employs a methodology centered on observations and interviews with informants, categorized by their use of traditional or contemporary songs in performing dhikr. Data analysis was conducted both on-site and off-site. On-site analysis involved recording local terms and describing them within their cultural context. Additionally, transcription was undertaken to convert sounds, movements, and voices into written form. Off-site analysis included verifying data completeness, classifying data based on research needs, reducing irrelevant data, coding the remaining data, and organizing it into themes before presenting it systematically. The findings reveal three key processes within the continuum. First, the configuration of traditional and contemporary songs illustrates a linear progression that reflects the formation of Sambas Malay culture. Second, the configuration of songs and cultural construction is mediated through both cultural and structural platforms. Third, this continuum extends to the internal experiences of dhikr practitioners, serving as a reflective process of their practices. The study’s results have significant implications for understanding dhikr practices, demonstrating that they are not solely religious in nature. It also opens new avenues for research, particularly exploring the political dimensions of dhikr practices and their relationship to power dynamics within the Sambas Malay community

HUKM SHAR‘Ī AND THE RECIPROCAL IDENTIFICATION BETWEEN ITS DEFINITION AND SUBJECT MATTER: THE MISSING LINK

When the nature of a particular notion is sought to be known, one often resorts to look for its definition, and that definition, by its nature, often identifies the subject matter. Conversely, the definition sought for identifying the subject matter could not have been articulated before investigating the nature of the notion and designating its subject matter. This logical link of reciprocal identification between the definition of ḥukm and its subject matter is assumed missing. In order for it to be recovered, this paper investigates the nature of ḥukm shar‘ī from both the perspective of its definition and that of its subject matter. From both perspectives, that is, that of the definition of ḥukm and its subject matter, the nature of ḥukm will be investigated through the presentation of the different views of the subject matter of dispute. This is to be followed by a critical analysis of that which searches for the truly distinctive character that provides the subject matter of dispute with its significance so that it can be used in selecting the appropriate view of the disputing views or, if not, searching for it elsewhere. The distinctive character of ḥukm is thought to be embedded in legitimacy to which bindingness is tied, and therefore the definition suggested by theologians which identifies ḥukm with the communication of the ḥukm-giver is thought to be the appropriate definition. The definitio

AI-Driven High-Precision Model for Blockage Detection in Urban Wastewater Systems

In artificial intelligence (AI), computer vision consists of intelligent models to interpret and recognize the visual world, similar to human vision. This technology relies on a synergy of extensive data and human expertise, meticulously structured to yield accurate results. Tackling the intricate task of locating and resolving blockages within sewer systems is a significant challenge due to their diverse nature and lack of robust technique. This research utilizes the previously introduced “S-BIRD” dataset, a collection of frames depicting sewer blockages, as the foundational training data for a deep neural network model. To enhance the model’s performance and attain optimal results, transfer learning and fine-tuning techniques are strategically implemented on the YOLOv5 architecture, using the corresponding dataset. The outcomes of the trained model exhibit a remarkable accuracy rate in sewer blockage detection, thereby boosting the reliability and efficacy of the associated robotic framework for proficient removal of various blockages. Particularly noteworthy is the achieved mean average precision (mAP) score of 96.30% at a confidence threshold of 0.5, maintaining a consistently high-performance level of 79.20% across Intersection over Union (IoU) thresholds ranging from 0.5 to 0.95. It is expected that this work contributes to advancing the applications of AI-driven solutions for modern urban sanitation systems

PRESENTING A NEW LAMINATION METHOD FOR THE ELASTIC ANALYSIS OF MULTILAYER CYLINDRICAL SHELLS

ABSTRACT In this article, by using the lamination theory, three hypothetical equations with unknown coefficients have been considered for the modeling of the displacement behavior of each layer of a shell in the cylindrical coordinate system, which completely satisfy the natural and geometrical boundary conditions. In this article, complete continuity has been assumed between the layers of a multilayer shell at their common boundaries, and this continuity is modeled by considering the same behavioral equations at the interface of two adjacent layers. By using the first law of thermodynamics to obtain the total potential energy of the layers, and by taking the derivative of this total energy equation with respect to the unknown coefficients of displacement equations and solving the resulting system, these coefficients are determined. It is obvious that, by knowing a shell's displacement equations, the other quantities needed for the analysis of the shell can be calculated as well

A systematic review of dietary, nutritional, and physical activity interventions for the prevention of prostate cancer progression and mortality

PURPOSE: Given the long-term, although potentially fatal, nature of prostate cancer, there is increasing observational evidence for the reduction in disease progression and mortality through changes in lifestyle factors. METHODS: We systematically reviewed dietary, nutritional, and physical activity randomized interventions aimed at modifying prostate cancer progression and disease-specific mortality, including a detailed assessment of risk of bias and methodological quality. RESULTS: Forty-four randomized controlled trials of lifestyle interventions, with prostate cancer progression or mortality outcomes, were identified. Substantial heterogeneity of the data prevented a meta-analysis. The included trials involved 3,418 prostate cancer patients, median 64 men per trial, from 13 countries. A trial of a nutritional supplement of pomegranate seed, green tea, broccoli, and turmeric; a trial comparing flaxseed, low-fat diet, flaxseed, and low-fat diet versus usual diet; and a trial supplementing soy, lycopene, selenium, and coenzyme Q10, all demonstrated beneficial effects. These trials were also assessed as having low risk of bias and high methodological quality (as were seven other trials with no evidence of benefit). The remaining trials were either underpowered, at high or unclear risk of bias, inadequately reported, of short duration or measured surrogate outcomes of unproven relationship to mortality or disease progression, which precluded any benefits reported being reliable. CONCLUSION: Large, well-designed randomized trials with clinical endpoints are recommended for lifestyle modification interventions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10552-015-0659-4) contains supplementary material, which is available to authorized users