Stages Of Process Research Articles

Interoceptive signals shape the earliest markers and neural pathway to awareness at the visual threshold

Variations in interoceptive signals from the baroreceptors (BRs) across the cardiac and respiratory cycle can modulate cortical excitability and so affect awareness. It remains debated at what stages of processing they affect awareness-related event-related potentials (ERPs) in different sensory modalities. We investigated the influence of the cardiac (systole/diastole) and the respiratory (inhalation/exhalation) phase on awareness-related ERPs. Subjects discriminated visual threshold stimuli while their electroencephalogram, electrocardiogram, and respiration were simultaneously recorded. We compared ERPs and their intracranial generators for stimuli classified correctly with and without awareness as a function of the cardiac and respiratory phase. Cyclic variations of interoceptive signals from the BRs modulated both the earliest electrophysiological markers and the trajectory of brain activity when subjects became aware of the stimuli: an early sensory component (P1) was the earliest marker of awareness for low (diastole/inhalation) and a perceptual component (visual awareness negativity) for high (systole/exhalation) BR activity, indicating that BR signals interfere with the sensory processing of the visual input. Likewise, activity spread from the primary visceral cortex (posterior insula) to posterior parietal cortices during high and from associative interoceptive centers (anterior insula) to the prefrontal cortex during low BR activity. Consciousness is thereby resolved in cognitive/associative regions when BR is low and in perceptual centers when it is high. Our results suggest that cyclic fluctuations of BR signaling affect both the earliest markers of awareness and the brain processes underlying conscious awareness.

Improvements in Precision of Relative Binding Free Energy Calculations Afforded by the Alchemical Enhanced Sampling (ACES) Approach.

Accurate in silico predictions of how strongly small molecules bind to proteins, such as those afforded by relative binding free energy (RBFE) calculations, can greatly increase the efficiency of the hit-to-lead and lead optimization stages of the drug discovery process. The success of such calculations, however, relies heavily on their precision. Here, we show that a recently developed alchemical enhanced sampling (ACES) approach can consistently improve the precision of RBFE calculations on a large and diverse set of proteins and small molecule ligands. The addition of ACES to conventional RBFE calculations lowered the average hysteresis by over 35% (0.3-0.4 kcal/mol) and the average replicate spread by over 25% (0.2-0.3 kcal/mol) across a set of 10 protein targets and 213 small molecules while maintaining similar or improved accuracy. We show in atomic detail how ACES improved convergence of several representative RBFE calculations through enhancing the sampling of important slowly transitioning ligand degrees of freedom.

Bilateral connections from the amygdala to extrastriate visual cortex in the marmoset monkey.

It is known that the primate amygdala forms projections to many areas of the ipsilateral cortex, but the extent to which it forms connections with the contralateral visual cortex remains less understood. Based on retrograde tracer injections in marmoset monkeys, we report that the amygdala forms widespread projections to the ipsilateral extrastriate cortex, including V1 and areas in both the dorsal (MT, V4T, V3a, 19M, and PG/PFG) and the ventral (VLP and TEO) streams. In addition, contralateral projections were found to target each of the extrastriate areas, but not V1. In both hemispheres, the tracer-labeled neurons were exclusively located in the basolateral nuclear complex. The number of labeled neurons in the contralateral amygdala was small relative to the ipsilateral connection (1.2% to 5.8%). The percentage of contralateral connections increased progressively with hierarchical level. An injection in the corpus callosum demonstrated that at least some of the amygdalo-cortical connections cross through this fiber tract, in addition to the previously documented path through the anterior commissure. Our results expand knowledge of the amygdalofugal projections to the extrastriate cortex, while also revealing pathways through which visual stimuli conveying affective content can directly influence early stages of neural processing in the contralateral visual field.

Understanding medical students' transition to and development in clerkship education: a qualitative study using grounded theory.

Medical students perceive the transition to clerkship education as stressful and challenging and view themselves as novices during their rotation in clerkship education. The developmental perspective is thus important because the transition to clerkship supports rather than hinders growth. Accordingly, this study examines medical students' transition to clerkship and their developmental features. In-depth interviews were conducted with 18 medical students or graduates who had completed clerkships as medical students. Based on Straussian grounded theory, the collected data were analyzed in terms of the differences between pre- and post-clerkship education. Our data analysis revealed five stages of the transition process: "anticipation and anxiety," "reality check," "seeking solutions," "practical application," and "transition and stability." The core category, that is, "growing up from being students to being student doctors," was driven by patients who perceived the participants as student doctors. Meanwhile, the participants recognized that having a solution that is agreed upon by colleagues was more important than knowing the correct answer. The participants undergoing the transition to clerkship showed developmental features divided into three categories: personal, social, and professional. Specifically, they attempted to balance clerkship and life through personal development, learned to navigate around the hospital and reduced tension through social development, and developed clinical competencies focused on efficiency through professional development. This study explores the process of students' transition to clerkship education and the developmental features that emerge during this period. The students were motivated by patients who perceived them as student doctors. Through the transition, they maintained a work-life balance and adapted to hospitals but developed an overly doctor-centered attitude by cultivating clinical competencies with a focus on efficiency. To develop them into medical professionals, it is essential to assist their transition and cultivate a patient-centered attitude.

A Hybrid Prototype Method Combining Physical Models and Generative Artificial Intelligence to Support Creativity in Conceptual Design

Conceptual design is an essential stage in the design process, and its ultimate success largely depends on designers’ creativity. Both physical and digital prototypes are commonly adopted by designers to support ideation and creativity, providing intuitive perception and rapid iteration, respectively. In recent advancements, large-scale generation models are able to offer data-enabled creativity support by generating high-quality solutions comparable to human designers. This opens up an imaginary space for designers and brings new possibilities for design tools. In this study, we proposed a hybrid prototype method that synergistically combines physical models and generative artificial intelligence (AI) in the conceptual design stage. Correspondingly, we developed a hybrid prototype system to implement the proposed method. We conducted a comparative user study with 45 designers who completed a design task using the physical prototype method, standalone generative AI, and the hybrid prototype method, respectively. Our results verified the effectiveness of the hybrid prototype method and investigated its mechanism in supporting creativity. Finally, we discussed the application value and optimisation space of the hybrid prototype method.

From innovation to stability: Evaluating the ripple influence of digital payment systems and capital adequacy ratio on a bank’s Z-score

This study investigated the influence of digital payment systems on banks’ stability by exploring their effect on the Z-score of the Jordanian banking sector during the period from 2004 until 2022. It specifically focused on liquidity risks generated from e-payment transactions and how sufficient capital adequacy ratios enhance banking sector stability over both short-term and long-term periods by standing against sudden volatilities yielded from large amounts of transactions executed through digital payment systems. To achieve this objective, the study utilizes time series dual regression analyses of vector autoregression and vector error correction models on E-views 12 to cover the time variation influences of digital payment on the banking sector Z-score. The regression results indicate varied effects between the benefits and risks of digital payment systems on a bank’s Z-score that influence the immediate sector’s stability, indicating that while digital payment systems can initially hold liquidity risks, leading to short-term instability; the strategic implementation of robust capital adequacy ratio stands as a protective buffer by fostering long-term banking sector resilience. The results also suggest future predictions and insights for financial sector legislators and regulators emphasizing the need for monitoring strategies that stimulate continuous innovations in the digital payment infrastructure while constantly ensuring the stability and resilience of the banking sector. Thus, prudent liquidity management and the reinforcement of capital buffers are encouraged to pilot the dual challenges and opportunities that appeared at the stages of the digital payment process, ultimately guiding the sector toward continuous growth and sustainability. AcknowledgmentThe author is grateful to the Middle East University, Amman, Jordan for the financial support granted to cover the publication fee of this research.

水射流技术在农业领域的应用研究现状

Water jet technology, as a non-contact cutting and crushing technique, is commonly used in industries such as cleaning, rust removal, cutting, drilling, and mining. It enables a green and environmentally friendly production process by avoiding environmental pollution, heat generation, blade replacement, and sharpening issues. Cutting, cleaning, and crushing techniques are widely applied in various stages of agricultural production, but mostly through contact-based methods. The application of non-contact water jet technology in the agricultural field is still in its infancy. This paper summarized the current application status and research progress of water jet technology in different operational stages of agriculture, including sowing, management, field harvesting, and post-harvest processing. The specific requirements of key parameters for different operational objects and stages were analysed. Furthermore, the challenges encountered in the application of water jet technology in agriculture and provides prospects for future research directions were discussed. The review is intended to provide references for the promotion and green sustainable development of water jet technology in the agricultural field.

Intimal Macrovascular Pericytes: Their Role in Vascular Biology and Atherogenesis.

Atherosclerosis remains a major challenge to global healthcare despite decades of research and constant trials of novel therapeutic approaches. One feature that makes atherosclerosis treatment so elusive is an insufficient understanding of its origins and the early stages of the pathological process, which limits our means of effective prevention of the disease. Macrovascular pericytes are cells with distinct shapes that are located in the arterial wall of larger vessels and are in many aspects similar to microvascular pericytes that maintain the functionality of small vessels and capillaries. This cell type combines the residual contractile function of smooth muscle cells with a distinct stellar shape that allows these cells to make numerous contacts between themselves and the adjacent endothelial layer. Moreover, pericytes can take part in the immune defense and are able to take up lipids in the course of atherosclerotic lesion development. In growing atherosclerotic plaques, the morphology and function of pericytes change dramatically due to phagocytic and synthetic phenotypes that are actively involved in lipid accumulation and extracellular matrix synthesis. In this review, we summarize our knowledge of this less-studied cell type and its role in atherosclerosis.

Phytochemical Profiling of Wastes from the Processing of Shea Butter (Vitellaria paradoxa) and Pharmacological Potentials within the Paradigm of Circular Bioeconomy: Emphasizing Antioxidant and Antidiabetic Applications

Shea butter is a natural fat that is extracted from the kernels of the shea butter tree, and it is widely used in food preparation, cosmetics, and therapeutic practices. Shea trees are prevalent across Africa, and the traditional extraction methods produce significant wastes. However, there is dearth of information on the phytochemical profiling of these wastes and their potential biomedical values. Thus, this study conducted a thorough phytochemical investigation of the shea butter wastes from different processing stages, including brown and black shea cakes (SNC1 and SNC2), shea nut shells (SNS), and shea nut wastewater (SNWW). By using gas chromatography-mass spectrometry (GC-MS), the bioactive chemicals in these wastes were identified and quantified. Furthermore, the antioxidant and anti-diabetic activities of the wastes were investigated for their potential pharmacological applications. The maximum antioxidant activities obtained at 60 mg/ml revealed DPPH radical scavenging of 62.34% for SNC1, ferric reducing power of 68.13% for SNC2, H2O2 radical scavenging of 38.46% for SNS, and nitric oxide scavenging of 35.13% for SNWW indicating their potentials in combating oxidative stress. Additionally, the promising anti-diabetic activity, with alpha-amylase inhibition reaching 84.74% for SNS at 60 mg/ml highlights their potential in diabetes management. This study provides a holistic understanding of shea butter wastes, unraveling their chemical complexity and exploring their pharmacological potentials. It not only expands our knowledge of shea butter wastes, but also unlocks new avenues for utilization of the wastes in various industries, thereby contributing to waste management and sustainable exploitation of shea resources.

An Underwater Image Enhancement Method Based on Multi-scale Layer Decomposition And Fusion

High-quality underwater images can intuitively reflect the most realistic underwater conditions, guiding for underwater environmental monitoring and resource exploration strongly. But when factors like light absorption affect underwater optical imaging, it has been found that poor visibility and blurred texture details occur in acquired images, posing challenges for the identification and detection of underwater targets. To obtain natural images, an enhancement algorithm is proposed based on multi-scale layer decomposition and fusion. The algorithm employs different strategies to recover image attenuation information from both local and global perspectives, generating two complementary preprocessed fusion inputs. For fusion input 1, operations are conducted in the RGB color space. Initially, the mean proportion of each color channel is used to identify the attenuated color channel. Then, a local compensation strategy is adaptively applied to restore the pixel intensity of the attenuated color channel. Finally, a statistical color correction method is used to eliminate color cast in the image. Fusion input 2 involves two processing stages. In the Lab color space, the algorithm uses the grayscale information to reduce the deviation in the mean values of channels a and b globally. The local mean information of the component L enhances detail textures. In the RGB color space, linear stretching is applied to correct color deviations. To fuse the structural features of two complementary preprocessed inputs and avoid interference between signals from different layers, the color channels of fused input image are first decomposed into muti-scale structural layers based on structural priors. Then, the image enhancement is achieved through layer-by-layer fusion of the corresponding color channels of the two inputs. By testing and analyzing with the, it was found that the proposed method can improve the clarity of attenuated images in various underwater scenarios of UIEBD and RUIE datasets effectively, enhancing image detail and texture richness, increases contrast, and achieving natural and comfortable visual quality. Compared with the quantitative metrics of 14 other algorithms, the proposed algorithm shows an average score improvement of 10.14, 90.48, and 2.06, respectively, in metrics AG (average gradient), EI (edge intensity), and NIQE (natural image quality evaluator). In the RUIE dataset, it shows an average score improvement of 10.21, 94.76, and 1.86, respectively.

The transformative impact of large language models on medical writing and publishing: current applications, challenges and future directions.

Large language models (LLMs) are rapidly transforming medical writing and publishing. This review article focuses on experimental evidence to provide a comprehensive overview of the current applications, challenges, and future implications of LLMs in various stages of academic research and publishing process. Global surveys reveal a high prevalence of LLM usage in scientific writing, with both potential benefits and challenges associated with its adoption. LLMs have been successfully applied in literature search, research design, writing assistance, quality assessment, citation generation, and data analysis. LLMs have also been used in peer review and publication processes, including manuscript screening, generating review comments, and identifying potential biases. To ensure the integrity and quality of scholarly work in the era of LLM-assisted research, responsible artificial intelligence (AI) use is crucial. Researchers should prioritize verifying the accuracy and reliability of AI-generated content, maintain transparency in the use of LLMs, and develop collaborative human-AI workflows. Reviewers should focus on higher-order reviewing skills and be aware of the potential use of LLMs in manuscripts. Editorial offices should develop clear policies and guidelines on AI use and foster open dialogue within the academic community. Future directions include addressing the limitations and biases of current LLMs, exploring innovative applications, and continuously updating policies and practices in response to technological advancements. Collaborative efforts among stakeholders are necessary to harness the transformative potential of LLMs while maintaining the integrity of medical writing and publishing.

A Modified of Fourth-Order Partial Differential Equations Model Based on Isophote Direction to Noise Image Removal

Image denoising is one of the initial stages of image processing. Many models based on the diffusion method have been used to smooth the image. One of the problems, we face in the model based on the diffusion method is its possible loss of edges. The diffusion force is known to be more effective in areas of high frequency. So This paper suggests combining the direction of isophote and fourth-order partial differential equations to reduce the problem of loss edges and preserve important details of the image. The direction of the isophote can regulate the direction of diffusion. Thus, we have a proposed model that can remove the noise in the area while preserving the important edges and details of the image. We have proven the efficiency and superiority of the proposed model by applying it to a set of images and solving it numerically using the finite difference method (FDM).

Ensuring the legal interests of a person in pre-trial criminal proceedings

In the science of the criminal process, there is no unified vision of the essence of a person’s legitimate interests and guarantees of their provision at the stage of pre-trial investigation. Ensuring a legitimate interest at the stage of pre-trial criminal proceedings is not supported by the performance of duties by other participants. An effective guarantee of the realization of a person’s legitimate interests in pre-trial criminal proceedings should be the real possibility of going to court to challenge the decisions, actions or inaction of law enforcement agencies. The presence of such a legal possibility should stimulate law enforcement agencies to take active actions aimed at satisfying legitimate interests. The criminal procedural law must provide for a mechanism to protect the legal interests of a person, both those that directly follow from the criminal procedural norms and those that are not provided for by the criminal procedural law, but are consistent with the spirit and principles of criminal justice. It can be argued that the legitimate interests of a person in pre-trial criminal proceedings are general legal and not prohibited aspirations of a person. Ensuring the legal interests of a person at the pre-trial stage of the criminal process should be ensured by a general obligation (general obligation) to take active actions by state bodies aimed at ensuring legal interests. The guarantee of the realization of the legal interests of a person in pre-trial criminal proceedings is the legal regulation in the criminal procedural law of the procedure for judicial appeal of decisions, actions or inaction of law enforcement bodies (including pre-trial investigation bodies) that prevent the realization of general legal aspirations of a person at the pre-trial stage of criminal proceedings. The need for regulatory regulation of the procedure for judicial protection of legitimate interests is determined by their legal nature, which provides for regularities in the actions of the participants of criminal proceedings of an undefined nature.

Consecutive diagnosis of nanosecond pulsed discharge in a coaxial electrode configuration using a quadruple emICCD camera system

Abstract Understanding the rapid dynamics of the primary streamer is crucial for comprehending the nanosecond pulsed discharge process. To reveal the fast primary streamer process, this study introduces a newly developed quadruple emICCD camera system capable of capturing a sequence of four discharge images in single pulse, coupled with self-customized software for data analysis. A nanosecond pulse power with its FWHM of 10.5 ns was applied to a coaxial reactor, focusing on the dynamics of the primary streamer. Our research clarifies the spatiotemporal variations of the primary streamer’s properties and examines their relation with inner electrode diameter (i.d. 0.2–2.0 mm). Results showed that in a pulse-powered coaxial electrode, there are three stages in the primary streamer process and that i.d. serves as an important factor influencing the formation and propagation of streamers. Interestingly, we found that streamer head velocity, streamer width, and streamer area for individual streamers remain constant prior to streamer channels reaching the outer electrode. Furthermore, we also observed an initial increase followed by a decrease in both streamer head velocity and streamer width with increasing i.d values. This study sheds light on the fundamental properties of the primary streamer during nanosecond pulsed discharge, contributing valuable insights for future plasma applications.

Effects of air damping on quality factors of different probes in tapping mode atomic force microscopy

Abstract The AFM probe in tapping mode is a continuous process of energy dissipation, from moving away from to intermittent contact with the sample surfaces. At present, studies regarding the energy dissipation mechanism of this continuous process have only been reported sporadically, and there are no systematic explanations or experimental verifications of the energy dissipation mechanism in each stage of the continuous process. The quality factors can be used to characterize the energy dissipation in TM-AFM systems. In this study, the vibration model of the microcantilever beam was established, coupling the vibration and damping effects of the microcantilever beam. The quality factor of the vibrating microcantilever beam under damping was derived, and the air viscous damping when the probe is away from the sample and the air squeeze film damping when the probe is close to the sample were calculated. In addition, the mechanism of the damping effects of different shapes of probes at different tip–sample distances was analyzed. The accuracy of the theoretical simplified model was verified using both experimental and simulation methods. A clearer understanding of the kinetic characteristics and damping mechanism of the TM-AFM was achieved by examining the air damping dissipation mechanism of AFM probes in the tapping mode, which was very important for improving both the quality factor and the imaging quality of the TM-AFM system. This study’s research findings also provided theoretical references and experimental methods for the future study of the energy dissipation mechanism of micro-nano-electromechanical systems.

A review of conditions influencing fate of Shiga toxin-producing Escherichia coli O157:H7 in leafy greens.

The accuracy of predictive microbial models used in quantitative microbial risk assessment (QMRA) relies on the relevancy of conditions influencing growth or inactivation. The continued use of log-linear models in studies remains widespread, despite evidence that they fail to accurately account for biphasic kinetics or include parameters to account for the effect of environmental conditions within the model equation. Although many experimental studies detail conditions of interest, studies that do not do so lead to uncertainty in QMRA modeling because the applicability of the predictive microbial models to the conditions in the risk scenarios is questionable or must be extrapolated. The current study systematically reviewed 65 articles that provided quantitative data and documented the conditions influencing the inactivation or growth of Shiga toxin-producing Escherichia coli (STEC) O157:H7 in leafy greens. The conditions were identified and categorized as environmental, biological, chemical, and/or processing. Our study found that temperature (n=37 studies) and sanitizing and washing procedures (n=12 studies) were the most studied conditions in the farm-to-table continuum of leafy greens. In addition, relative humidity was also established to affect growth and inactivation in more than one stage in the continuum. This study proposes the evaluation of the interactive effects of multiple conditions in processing and storage stages from controlled experiments as they relate to the fate of STEC O157:H7 in leafy greens for future quantitative analysis.

632. CAN CARDIOPULMONARY EXERCISE TESTING PREDICT NEOADJUVANT CHEMOTHERAPY TOXICITY IN OESOPHAGEAL ADENOCARCINOMA PATIENTS?

Abstract Background Cardiopulmonary exercise testing (CPET) is a method of assessing cardiopulmonary fitness. In the context of surgery, it is used to risk-stratify patients, allowing targeted prehabilitation to optimise comorbidities and fitness prior to surgery, and triage patients to the appropriate level of care after the operation. Various CPET-derived variables have been shown to be associated with short- and long-term outcomes after various surgery. In patients post-oesophagectomy, these variables are predictive of long-term survival. This study aimed to assess the use of this tool to predict neoadjuvant chemotherapy (NAC) related complications in patients receiving neoadjuvant FLOT prior to oesophagectomy. Methods All patients who underwent routine CPET during the staging process prior to NAC with FLOT and oesophagectomy in a single high-volume centre between September 2018 and January 2023 were included. Data were extracted from the unit’s contemporaneously maintained database. The Mann-Whitney U test was used to compare CPET variables in patients who completed NAC with FLOT fully versus those who did not finish NAC with FLOT due to acute chemotherapy toxicities. Results There were 129 patients who received neoadjuvant FLOT and had routine CPET performed during the defined study period. Six of those patients (4.7%) did not complete neoadjuvant chemotherapy due to acute chemotherapy toxicities but progressed to surgery. The median anaerobic threshold, VO2 peak, and VE/VCO2 among those who completed NAC were 14.2 ml/kg/min, 20.3 ml/kg/min, and 28, respectively, compared to 13.4 ml/kg/min, 19.7 ml/kg/min, and 31 in those who did not complete NAC (p=0.595, p=0.695, and p=0.160, respectively). Conclusion Although patients who received all four cycles of NAC with FLOT prior to oesophagectomy demonstrated CPET values indicating better base-line fitness than those who had to discontinue NAC due to acute chemotherapy toxicity, these differences did not reach the level of statistical significance. This study, therefore, did not demonstrate any predictive value of CPET in assessing the risk of incomplete NAC treatment prior to oesophagectomy.

Identifying liver cancer cells using cascaded convolutional neural network and gray level co-occurrence matrix techniques

<p>Liver cancer has a high mortality rate, especially in South Asia, East Asia, and Sub-Saharan Africa. Efforts to reduce these rates focus on detecting liver cancer at all stages. Early detection allows more treatment options, though symptoms may not always be apparent. The staging process evaluates tumor size, location, lymph node involvement, and spread to other organs. Our research used the CLD staging system, assessing tumor size (C), lymph nodes (L), and distant invasion (D). We applied a deep learning approach with a cascaded convolutional neural network (CNN) and gray level co-occurrence matrix (GLCM)-based texture features to distinguish benign from malignant tumors. The method validated with the cancer imaging archive (TCIA) dataset, demonstrating superior accuracy compared to existing techniques.</p>

457. EVALUATING THE ACCURACY OF CLINICAL SIEWERT CLASSIFICATION, A RETROSPECTIVE REVIEW OF 807 PATIENTS

Abstract Background Adenocarcinoma of the gastro-esophageal junction (GEJ) is increasingly common in Western societies. GEJ tumours are typically categorized using the Siewert classification, which divides the tumours in to 3 types based on location relative to the GEJ. Studies have shown that there is improved survival with a proximal surgical resection such as esophagectomy for type 1 tumours while type 3 tumours have improved survival when managed as other gastric cancers with a total or extended total gastrectomy. This requires accurate clinical classification. This study aims to evaluate the accuracy of commonly used staging modalities in the clinical classification of GEJ tumours. Methods A review of 807 consecutive patients undergoing curative resection for GEJ cancer was performed. Patient data was obtained from a prospectively maintained database between February 2010 and April 2023. Siewert type was established clinically as part of the staging process. The standard staging modalities used for every patient included computerized tomography (CT) and endoscopy, with most patients also undergoing positron emission tomography (PET). Endoscopic ultra-sonography (EUS) and staging laparoscopy was also used selectively. Accuracy was determined by comparing clinical classification to pathological classification following surgery. Results 807 patients were included [319 type 1, 401 type 2, 87 type 3]. Clinical classification was the same as pathological classification in 59.5% of cases [69.6% for type 1, 48.6% for type 2, 71.3% for type 3 (p<0.001). The use of different staging modalities for each sub-type is presented in table 1. For patients that underwent EUS, Siewert type was accurate in 59.4% of cases overall. The failure rate for EUS was 2.9%. For patients undergoing staging laparoscopy Siewert type was accurate in 69.3% and for patients that underwent PET, EUS and staging lap the accuracy was 74.4%. Conclusion Accurately determining Siewert type clinically is challenging. This is particularly relevant for type 2 tumours which had the least accurate comparison of clinical to pathological type. The use of additional modalities including EUS, and staging laparoscopy improves accuracy but may not be feasible in all patients.

Systematic Configurator for Complexity Management in Manufacturing Systems

Complexity management in manufacturing systems is crucial for the economic growth of countries, as efficient management can significantly improve business performance and ensure competitiveness in globalized markets. This research aims to develop a complexity management configurator that identifies critical effects, proposes solution strategies, and optimizes processes through a Lean Production and Industry 4.0 approach. To this end, its systematic design integrates the key stages of management: planning, organization, management and control. The research was structured as an applied study, implementing three main panels: general information, application of a diagnostic tool at each stage of the administrative process, and results focused on measuring the complexity and implementation of advanced technological solutions. The tool enables manufacturing companies not only to diagnose sources of complexity, but also to optimize their operations by adopting Lean methodologies and Industry 4.0 technologies. The findings show how the integration of these strategies contributes to reducing both static and dynamic complexity, resulting in greater operational efficiency and improved performance in an increasingly competitive industrial environment. In conclusion, the proposed configurator is positioned as a key tool to improve the competitiveness and sustainability of manufacturing companies by offering a comprehensive approach to complexity management that is tailored to the demands of modern industry.