A systemic and synthetic review of the anatomy of the temporomandibular joint in magnetic resonance imaging was developed for its evaluation. The temporomandibular joint is an anatomical structure composed of bones, muscles, ligaments and an articular disc that allows important physiological movements, such as mandibular opening, closing, protrusion, retrusion and lateralization. Magnetic resonance imaging is an imaging technique that does not use ionizing radiation and is more specific for the evaluation and interpretation of soft tissues, due to its high resolution, so it has an important role in the diagnosis of various maxillofacial pathologies, which is why the dentist should have knowledge of the structures and functions of the temporomandibular joint through magnetic resonance imaging. The review demonstrates the importance of magnetic resonance imaging in the study of the anatomy of the temporomandibular joint, in addition to mentioning the advantages provided by this imaging technique such as its good detail of the soft tissues in its different sequences and the non-use of ionizing radiation to obtain its images.

Outsourcing logistics operations is a common trend as businesses prioritize core activities. Establishing a sustainable partnership between businesses and logistics service providers requires a systematic approach. This study is needed to develop a more effective and adaptive framework for logistics service provider selection by integrating diverse criteria and decision-making methodologies, ultimately enhancing the precision and sustainability of procurement processes. This study advocate for leveraging industry-based knowledge in procurement, emphasizing the need to define decision-making elements. The research analyzes nearly 300 logistics procurement projects, using a neural network-based methodology to propose a model that aids businesses in identifying optimal criteria for evaluating logistics service providers based on extensive industry knowledge. The goal of this study is to develop and test a practical model that would support businesses in choosing most suitable criteria for selection of logistics service providers based on cumulative market patterns. The results of this study are as follows. It introduces novel elements by gathering and systematizing unique market data using developed data processing methodology. It innovatively classifies decision-making elements, allocating them into distinct groups for use as features in a neural network. The study further contributes by developing and training a predictive model based on a prepared dataset, addressing pre-defined goals, expectations related to green logistics, and specific requirements in the tendering process for selecting logistics service providers. Study is concluded by summarizing suggestions for future research in area of adopting neural networks for selection of logistics service providers.

Analysing external factors with a design-thinking approach is crucial for adaptation, identifying opportunities, and mitigating risks in native digital enterprises. This research introduces a framework rooted in design principles and future scenarios for external analysis, with the aim of meeting current market needs. The study employs a mixed qualitative-quantitative research approach, incorporating methods such as literature review, workshops, and surveys. These methods enable the collection and analysis of both qualitative and quantitative data, providing a comprehensive and accurate understanding of the research topic by using it in a DNVB case study. Developing a conceptual framework using a design-thinking approach which we call ASPECT contributes to a comprehensive interpretation of complexity, intertwining collective and individual factors. This reduces the risk of overlooking essential elements when making strategic decisions in ambiguous, uncertain, and volatile contexts. This method contrasts with traditional external analysis frameworks like CAME, Pestle, and SWOT. The document aims to contribute to the literature by exploring new models of external analysis based on the design process. This framework combines the conventional stages of a design thinking process with methodologies for future scenarios to identify relevant external factors for organizations. It provides an innovative conceptual framework for creating new business models and growth strategies for digital enterprises.

Three-dimensionally cross-linked polymer nanocomposite networks coated nano sand light-weight proppants (LWPs) were successfully prepared via ball-milling the macro sand and subsequently modifying the resultant nano sand with sequential polymer nanocomposite coating. The modified nano sand proppants had good sphericity and roundness. Thermal analyses showed that the samples can withstand up to 411 ℃. Moreover, the proppant samples’ specific gravity (S.G.) was 1.02–1.10 g/cm³ with excellent water dispersibility. Therefore, cross-linked polymer nanocomposite networks coated nano sand particles can act as potential candidates as water-carrying proppants for hydraulic fracturing operations.

Fungi can be used to remove or degrade polluting compounds through a mycoremediation process. Sometimes even more efficiently than prokaryotes, they can therefore be used to combat pollution from non-biodegradable polymers. Cellulose acetate is a commonly used material in the manufacture of cigarette butts, so when discarded, it generates pollution. The fungus Pleurotus ostreatus has the ability to degrade cellulose acetate through the enzymes it secretes. The enzyme hydrolyzes the acetyl group of cellulose acetate, while cellulolytic enzymes degrade the cellulose backbone into sugars, polysaccharides, or cellobiose. In addition to cellulose acetate, this fungus is capable of degrading other conventionally non-biodegradable polymers, so it has the potential to be used to reduce pollution. Large-scale cultivation of the fungus has proven to be more economically viable than conventional methods for treating non-biodegradable polymers, which is an additional advantage.