Special Case Research Articles

Predictive modeling of flow characteristics in supersonic separators using machine learning

In the pursuit of cleaner energy sources, pre-processing fuel streams is crucial before distribution. Challenges arise during this process, leading to operational issues and diminished transmission efficiency. Among different technologies, supersonic separators are the ones that separate undesired components from the main gas stream more effectively. Precise forecasting of nozzle flow rate and shockwave location at a low cost can markedly enhance the efficiency of manufacturing and rating. In this research, the one-dimensional method has been developed to solve flow equations simultaneously by implementing equations of state. CFD has been used for the verification of the developed model, and the effect of different equations of state is investigated. Results show that the one-dimensional model significantly reduces the calculation time. Different EOSs result in up to 2.0 % and 3.5 % variation in the prediction of shock location and the mass flow rate, respectively.A machine learning methodology is employed to predict the location of shockwaves and the choked flow rate at an even lower cost. A dataset of 160 entries, generated using Peng Robinson's EOS, serves as the basis for this analysis. Prediction tasks are executed using Random Forest, k-nearest Neighbors, and Multilayer Perceptron models. While all three models demonstrate proficiency in data interpolation with R2 scores up to 0.9962 and 0.9951 for the shockwave location and mass flow rate, respectively, discerning their performance in extrapolation appears contingent on the specific case. In the case of extrapolation, Multilayer Perceptron and k-Nearest Neighbors show better match to one-dimensional results.

Feasibility of Cryobiopsy Specimen Retrieval Through Standard Guide Sheath for Peripheral Pulmonary Lesions Without Bronchoscope Removal.

Transbronchial cryobiopsy is a promising technique for biopsy of peripheral pulmonary lesions (PPL). However, cryobiopsy specimen retrieval can pose problems due to the risk of bleeding during the blind period when the bronchoscope and cryoprobe are removed en bloc. Artificial airways and prophylactic balloon placement are risk-reducing measures, but the latter is challenging in upper lobe PPL. Specimen retrieval through standard guide sheath (GS) system without the need for bronchoscope removal may now be feasible with the ultrathin cryoprobe. Retrospective review of radial endobronchial ultrasound (rEBUS)-guided transbronchial cryobiopsy for PPL cases in which cryobiopsy specimen was retrieved through the GS over a 6-month period. Twenty patients were included with an overall median age of 66.50 (IQR: 53.0 to 76.7). The median procedural time was 30 (IQR: 25.0 to 33.7) minutes. Median target size was 3.20 (IQR: 2.17 to 4.84)cm with 85% of lesions demonstrated "within" rEBUS orientation. Overall technical feasibility was 85% with median cryoactivation of 4.0 (IQR: 3.0 to 4.0) seconds. No specimen was retrieved in 3 patients. The diagnostic yield for forceps and cryobiopsy was 70% and 60%, respectively, and the combined diagnostic yield was 85% (P<0.01 vs. forceps biopsy). Median aggregate size for forceps and cryobiopsy was 8.0 (IQR: 5.3 to 10.0) and 4.5 (IQR: 2.3 to 7.0)mm respectively (P<0.01). No pneumothorax was reported and mild self-limiting bleeding was encountered in 30% of cases. Retrieval of cryoprobe through standard GS appears to be a safe and feasible method that can simplify the transbronchial cryobiopsy procedure and complement forceps biopsy in specific cases.

Science, health and the military dictatorship in Brazil: the Integrated Endemic Disease Program (PIDE) of CNPq (1973-1987)

This article analyzes the Integrated Endemic Disease Program (PIDE), which was established in 1973 by the National Council for Scientific and Technological Development CNPq, financed by the Brazilian Funding Authority for Studies and Projects FINEP. The program was established to finance research on diseases considered strategic to the economic development plans of the military regime (1964-1985). Acknowledged to be a landmark program in the history of Brazilian parasitology, PIDE was set up during a period when the dictatorship was both violently repressing scholars and investing heavily in science and technology (S&T). The article examines the context in which the program was implemented and analyzes what it signified for planners in the S&T field and for the scientists who coordinated it. The contention is that PIDE was an example of how the scientific community managed to use financial and institutional resources available under the S&T policy in the 1970s to advance research on parasitic diseases and update its agenda. This analysis contributes to recent historiography that, based on specific historical cases, reflects on the paradoxical nature of a regime that, in its authoritarian modernization project, simultaneously persecuted scientists and supported science.

Best practices for your confirmatory factor analysis: A JASP and lavaan tutorial.

Confirmatory factor analysis (CFA) is a fundamental method for evaluating the internal structural validity of measurement instruments. In most CFA applications, the measurement model serves as a means to an end rather than an end in itself. To select the appropriate model, prior validity evidence is crucial, and items are typically assessed on an ordinal scale, which has been used in the applied social sciences. However, textbooks on structural equation modeling (SEM) often overlook this specific case, focusing on applications estimable using maximum likelihood (ML) instead. Unfortunately, several popular commercial SEM software packages lack suitable solutions for handling this 'typical CFA', leading to confusion and suboptimal decision-making when conducting CFA in this context. This article conceptually contributes to this ongoing discussion by presenting a set of guidelines for conducting a typical CFA, drawing from recent empirical research. We provide a practical contribution by introducing and developing a tutorial example within the JASP and lavaansoftware platforms. Supplementary materials such as videos, files, and scripts are freely available.

Intervention Programs Focusing on Social Cognition in Schizophrenia

Social cognitive functions make it possible to correctly recognize and interpret the emotions and mental states of others in the social environment, to understand their intentions correctly and to react accordingly. Therefore, these functions arecritical for healthy social interactions and professional success in human life. Social cognitive functions are impaired in many psychiatric and neurological diseases and this impairment negatively affects almost all areas of patients' lives, albeit in different dimensions. According to research findings revealing the relationship between social cognition and social functioning, social cognition should be one of the treatment targets for many diseases. Recently, there has been increasing interest in interventions that target the improvement of these functions. In this article, these training programs, research findings and assessment tools used in these studies are discussed in the specific case of schizophrenia.

Statistical Modeling of Football Players’ Transfer Fees Worldwide

Professional football clubs invest vast amounts of money in the recruitment of players. This article presents the latest advances in statistical modeling of the factors that market actors take into consideration to determine the transfer prices of professional football players. It extends to a global scale the econometric approach previously developed by the authors to evaluate the transfer prices of players under contract with clubs from the five major European leagues. The statistical technique used to build the model is multiple linear regression (MLR), with fees paid by clubs as an independent variable. The sample comprises over 8000 transactions of players transferred for money from clubs worldwide during the period stretching from July 2014 to March 2024. This paper shows that a statistical model can explain up to 85% of the differences in the transfer fees paid for players. Despite the specific cases and other possible distortions mentioned in the discussion, the use of a statistical model to determine player transfer prices is thus highly relevant on a global scale.

Real-world evaluation of multimodal treatment practice in older oesophageal cancer patients

Abstract OBJECTIVES Elderly-specific data for multimodal treatment of oesophageal cancer (EC) is lacking. This study aimed to evaluate the safety and efficacy of multimodal treatment in older EC patients and to compare the impact of neoadjuvant chemotherapy (NCT) and neoadjuvant chemoradiotherapy (NCRT). METHODS Patients diagnosed with oesophageal squamous cell carcinoma or adenocarcinoma who received NCT/NCRT were identified in the National Cancer Database (NCDB, 2004–2015). First, we compared baseline and post-treatment characteristics between younger (&amp;lt;70 years) and older patients (≥70 years). Logistic regression was used to investigate risk factors of postoperative mortality. Second, we evaluated the effect of neoadjuvant chemotherapy on postoperative mortality and overall survival in the older cohort. Inverse probability of treatment weights (IPTW) and multivariable analyses were used to compensate for differences in baseline covariates. RESULTS We first compared outcomes of neoadjuvant therapy plus oesophagectomy in 14778 eligible EC patients. The older group experienced higher rates of postoperative mortality at 30 days (5.8%) and 90 days (13.5%) compared to younger patients. Postoperative mortality was significantly related to the Charlson-Deyo score and treatment-related factors including NAT type and minimally invasive technique. Second, among the 3,141 older patients (with a median follow-up of 57.8 months and 2029 deaths), those receiving NCT obtained significantly lower postoperative mortality and improved overall survival compared with NCRT (IPTW-Adjusted P = 0.05; HR, 0.85; 95% Cl, 0.72–0.99). CONCLUSIONS Neoadjuvant therapy plus oesophagectomy carries increased short-term mortality risk in older EC patients. NCT in older EC patients showed lower postoperative mortality but no statistically significant differences in overall survival with a point estimate favoring NCT compared to the NCRT group, making NCT a potential option for consideration in specific cases.

Way forward in improving Rhinoplasty Outcomes.

Rhinoplasty is an elective surgical procedure required by the patient to attain an aesthetic and functional improvement of the nose. The degree of expectancy of the patient - and the surgeon - to the outcome of rhinoplasty is usually high, and any result under perfection may be seen as a failure. Consistently achieving good results in rhinoplasty requires thorough attention from the surgeon to every step of the rhinoplasty process. Fully understanding of patient's desires, careful preoperative evaluation of the face and proper selection of patients is crucial towards improving rhinoplasty outcomes. Furthermore, an individually tailored surgical planning according to the unique features of the specific case, preferring remodeling over resection surgical techniques and reinforcing nasal framework support and careful surgical execution will likely ensure a satisfactory and long-lasting surgical outcome of rhinoplasty. Rhinoplasty requires a lifelong dedication of the surgeon for providing the best outcomes to the patients that trust their noses to his or her surgical skills. The rhinoplasty surgeon has been labeled the "eternal student" and this should reflect the delicacy and the humbleness of the rhinoplasty surgeon.

A versatile knee exoskeleton mitigates quadriceps fatigue in lifting, lowering, and carrying tasks.

The quadriceps are particularly susceptible to fatigue during repetitive lifting, lowering, and carrying (LLC), affecting worker performance, posture, and ultimately lower-back injury risk. Although robotic exoskeletons have been developed and optimized for specific use cases like lifting-lowering, their controllers lack the versatility or customizability to target critical muscles across many fatiguing tasks. Here, we present a task-adaptive knee exoskeleton controller that automatically modulates virtual springs, dampers, and gravity and inertia compensation to assist squatting, level walking, and ramp and stairs ascent/descent. Unlike end-to-end neural networks, the controller is composed of predictable, bounded components with interpretable parameters that are amenable to data-driven optimization for biomimetic assistance and subsequent application-specific tuning, for example, maximizing quadriceps assistance over multiterrain LLC. When deployed on a backdrivable knee exoskeleton, the assistance torques holistically reduced quadriceps effort across multiterrain LLC tasks (significantly except for level walking) in 10 human users without user-specific calibration. The exoskeleton also significantly improved fatigue-induced deficits in time-based performance and posture during repetitive lifting-lowering. Last, the system facilitated seamless task transitions and garnered a high effectiveness rating postfatigue over a multiterrain circuit. These findings indicate that this versatile control framework can target critical muscles across multiple tasks, specifically mitigating quadriceps fatigue and its deleterious effects.

A front-fixing numerical method for a fluvio-deltaic sedimentation process with thespace fractional derivative and variable sediment flux

This paper centers around a space-fractional mathematical model for a fluvio-deltaic sedimentation process which involves a space-fractional derivative (Caputo derivative) and time dependent variable sediment flux to investigates the movement of shoreline in a sedimentary ocean basin. This model is a specific case of a basic shoreline model and analogous to a Stefan problem. The numerical solution to the problem is acquired by employing a front-fixing explicit finite difference method. The consistency, stability and convergence of the numerical scheme are theoretically analyzed. The effects of variable sediment flux on the movement of shoreline position and the height of sediments are also assessed for different cases.

Halogen Bonding on Water─A Drop in the Ocean?

Halogen bonding is a valuable interaction in drug design, offering an unconventional way to influence affinity and selectivity by leveraging the halogen atoms' ability to form directional bonds. The present study evaluates halogen-water interactions within protein binding sites, demonstrating that targeting a water molecule via halogen bonding can in specific cases contribute beneficially to ligand binding. In solving and examining the crystal structure of 2-cyclopentyl-7-iodo-1H-indole-3-carbonitrile bound to DYRK1a kinase, we identified a notable iodine-water interaction, where water accepts a halogen bond with good geometric and energetic features. This starting point triggered further investigations into the prevalence of such interactions across various halogen-bearing ligands (chlorine, bromine, iodine) in the PDB. Using QM calculations (MP2/TZVPP), we highlight the versatility and potential benefits of such halogen-water interactions, particularly when the water molecule is a stable part of the binding site's structured environment. While the interaction energies with water are lower compared to other typical halogen bond acceptors, we deem this different binding strength essential for reducing desolvation costs. We suggest that "interstitial" water molecules, as stable parts of the binding site engaging in multiple strong interactions, could be prime targets for halogen bonding. Further systematic studies, combining high-resolution crystal structures and quantum chemistry, are required to scrutinize whether halogen bonding on water is more than a "drop in the ocean".

The effect of common ownership among supply chain parties on decision-making and surplus with manufacturer encroachment

In the financial economics field, several studies assess the effect of common ownership on the economic consequence, decision-making of firms, and social performance. In this situation, based on recent supply chain practices and manufacturer encroachment, we examine the effect of common ownership on supply chain parties composed of a retailer and a manufacturer and social performance. From our model analysis, we demonstrate that manufacturer encroachment improves the retailer’s profit under specific economic environments, while generally, manufacturer encroachment harms the retailer’s profit because the manufacturer obtains market share through a direct channel. Additionally, we demonstrate that increasing common ownership improves total surplus in a specific case. Therefore, our analysis does not only propose the positive effects of common ownership among all vertical supply chain parties for supply chain coordination, as opposed to what is indicated by the real world, but also implies that society should accommodate common ownership among supply chain parties in specific economic environments from the perspective of total surplus.

Climbing university rankings under resources constraints: a combined approach integrating DEA and directed Louvain community detection

AbstractOver recent years, scholarly interest in universities’ allocation and effective utilisation of financial resources has been growing. When used efficiently, financial resources may improve universities’ quality of research and teaching, and therefore their positions in world university rankings. However, despite the relevance of financial efficiency to university placement in academic rankings, universities’ total available financial resources appear much more significant. In the present study, we propose an innovative methodology to determine realistic ranking targets for individual universities, based on their available financial resources. In particular, we combine data envelopment analysis, as developed by Banker et al. (Manag Sci 30(9):1078–1092, 1984), and a directed Louvain community detection algorithm to examine 318 universities across five countries, considering their ARWU scores alongside key financial indicators (i.e., long-term physical capital, total operating revenues). We identify clusters of universities with similar financial profiles and corresponding ARWU scores, as well as universities that have optimised their use of financial resources, representing benchmarks for similar universities to emulate. The approach is subsequently applied to Italian universities, as a specific national case. The findings may be useful for policy makers and university managers seeking reliable strategies for climbing academic rankings, particularly in countries with limited public investment in higher education.

A Case Report of Critical Aortic Stenosis Diagnosed Utilizing Non-Imaging Continuous Wave Doppler Probe

Abstract Background Aortic Stenosis (AS) is the most commonly acquired valvular pathology in the western world. AS severity is typically evaluated with Doppler echocardiography. Evaluation of aortic gradients using standard Doppler echocardiography from the apical window may underestimate the true gradient due to misalignment of blood flow to the ultrasound beam and is often better evaluated from other imaging windows using a Non-imaging Continuous-Wave Doppler (NI-CWD) probe. Herein, we describe a unique case of aortic stenosis being underestimated by dynamic acoustic shadowing from the apical window rather than beam misalignment. Case Summary The patient is a Hispanic 31-year-old male with a congenital bicuspid aortic valve who underwent a balloon aortic valvuloplasty at age 13. At age 31 the patient underwent a repeat transthoracic echocardiogram (TTE) that was largely unchanged from his prior TTE from 15 years prior. Notably on this TTE, there was acoustic shadowing of color Doppler in the distal left ventricular outflow tract and aortic valve during systole. While gradients only suggested moderate aortic stenosis, the degree of left ventricular hypertrophy was suspicious for more severe aortic stenosis. Only by using the NI-CWD probe at the right sternal border were we able to identify very-severe aortic stenosis with a peak velocity of 6.5 m/s and a mean gradient of 100 mmHg. Discussion In our specific case, dynamic acoustic shadowing of the aortic valve from the apical window obscured both imaging and Doppler signals. This acoustic shadowing was not present from the right sternal border with the NI-CWD probe, leading to an over 100% increase in aortic valve peak velocity and proper correction of AS severity. This allowed for expedited care and underscores the importance of such techniques.

Alternative treatment methods for bovine mastitis: prospects and limitations (review)

Mastitis remains the most common problem of dairy industry despite the preventive measures and treatment schemes being developed. Antibacterial drugs remain first line agents for therapy of the mammary gland inflammatory diseases in animals. Taking into account the risks associated with antibiotic therapy, such as decreased drug effectiveness due to occurrence of bacterial resistant strains, food safety issues, environmental impact and restrictions on the use of antibacterial drugs in veterinary medicine, an increasing number of scientific studies are addressing new therapeutic agents that can serve as an alternative to conventional therapy. The aim of this review is to give an idea of currently available literature data on alternative methods for the prevention and treatment of mastitis in cattle that are not associated with antibiotics. In general, a significant number of in vitro studies aimed at finding new effective and safe drugs are yielding promising results. This review describes the following alternative remedies: probiotics, bacteriocins, bacteriophages, phage enzymes (endolysins), nanoparticles, plant extracts, essential oils and immunobiological agents (vaccines). Understanding the mechanisms of their action will allow recommending the best treatment option for mastitis in each specific case. These treatment methods can potentially reduce use of antibiotics and increase animal productivity, however more in vivo studies are needed to prove the effectiveness of antibiotics used directly in the conditions of farm settings.

The Application and Significance of Autonomous Driving Technology in Industrial Production

In this study, we first gave an overview of autonomous driving technology and focused on its application in industrial production. By analyzing the types and characteristics of autonomous driving technology, we introduced key types such as unmanned vehicles, automated robots, and drones in detail. Subsequently, this paper selected three specific application cases of logistics transportation, warehouse management, and production process automation to deeply analyze the actual application effects of autonomous driving technology in industrial production. In addition, this paper also explores the significance of autonomous driving technology in the industrial production process and its impact on industrial production efficiency and cost. The study found that the application of autonomous driving technology can not only improve production efficiency, but also significantly reduce operating costs. Through this study, we hope to provide theoretical guidance and practical reference for the application of autonomous driving technology in the field of industrial production in my country.

Life cycle assessment based optimization of scenarios of reusable glass bottles using context-specific key parameters

Reusable glass bottles are experiencing a resurgence, driven notably by societal concerns and regulations. While single-use glass bottles generally have higher environmental footprint compared to plastic bottles, reusable systems could reduce both impacts related to single-use (e.g., climate change, energy consumption) and plastics (e.g., microplastic pollution). The environmental benefits of reusable bottles can vary across systems and this can be overlooked by stakeholders who rely on generic results for communication and a limited number of parameters to design their systems. This study addresses this gap by developing a systematic analysis of the variability of life cycle assessment results, within the specific case study of a new beverage. As a result, a list of key parameters to consider for the specific case study is set, enabling to propose targeted mitigation strategies. The commonly used generic key parameters are complemented with context-specific key parameters, empowering stakeholders to develop efficient systems and communicate their environmental performance accurately. Different configurations are likely to be influenced by other key parameters, and require specific mitigation strategies. In this perspective, stakeholders need assistance in: (1) designing context-specific strategies, and (2) translating – complex and plural – life cycle assessment results into actionable decisions.

The Governance of Territorial Networks of Organisations: Case of the Tangier-Tetouan-Al Hoceima Region

This work focuses on the governance of territorial networks of organizations in the Tangier-Tetouan-Al Hoceima region in Morocco. By examining this specific case, we seek to understand how regional governance structures influence collaboration and coordination between organizations operating in this territory. To understand this subject in depth, it is crucial to look at the governance of territorial networks of organizations, drawing inspiration from both international experiences and the specificities of the Moroccan context. Our research is based on a descriptive literature review beginning by defining the foundations of the governance of territorial networks, including the conceptualization of the term, their typological diversity, and their different forms. Then, by examining international experiences in governance, through the study of cases such as that of France, Italy, the Basque Countries, and the German model. Finally, by tracing the history of the development of territorial networks of organizations in Morocco, while highlighting the needs, trends, and potential of each of the entities making up the clusters.

The Diagnostic Performance of Large Language Models and General Radiologists in Thoracic Radiology Cases: A Comparative Study.

To investigate and compare the diagnostic performance of 10 different large language models (LLMs) and 2 board-certified general radiologists in thoracic radiology cases published by The Society of Thoracic Radiology. We collected publicly available 124 "Case of the Month" from the Society of Thoracic Radiology website between March 2012 and December 2023. Medical history and imaging findings were input into LLMs for diagnosis and differential diagnosis, while radiologists independently visually provided their assessments. Cases were categorized anatomically (parenchyma, airways, mediastinum-pleura-chest wall, and vascular) and further classified as specific or nonspecific for radiologic diagnosis. Diagnostic accuracy and differential diagnosis scores (DDxScore) were analyzed using the χ2, Kruskal-Wallis, Wilcoxon, McNemar, and Mann-Whitney U tests. Among the 124 cases, Claude 3 Opus showed the highest diagnostic accuracy (70.29%), followed by ChatGPT 4/Google Gemini 1.5 Pro (59.75%), Meta Llama 3 70b (57.3%), ChatGPT 3.5 (53.2%), outperforming radiologists (52.4% and 41.1%) and other LLMs (P<0.05). Claude 3 Opus DDxScore was significantly better than other LLMs and radiologists, except ChatGPT 3.5 (P<0.05). All LLMs and radiologists showed greater accuracy in specific cases (P<0.05), with no DDxScore difference for Perplexity and Google Bard based on specificity (P>0.05). There were no significant differences between LLMs and radiologists in the diagnostic accuracy of anatomic subgroups (P>0.05), except for Meta Llama 3 70b in the vascular cases (P=0.040). Claude 3 Opus outperformed other LLMs and radiologists in text-based thoracic radiology cases. LLMs hold great promise for clinical decision systems under proper medical supervision.

Optimizing cryopreservation strategies for scalable cell therapies: A comprehensive review with insights from iPSC-derived therapies.

Off-the-shelf cell therapies hold significant curative potential for conditions, such as Parkinson's disease and heart failure. However, these therapies face unique cryopreservation challenges, especially when novel routes of administration, such as intracerebral or epicardial injection, require cryopreservation media that are safe for direct post-thaw administration. Current practices often involve post-thaw washing to remove dimethyl sulfoxide (Me2SO), a cytotoxic cryoprotective agent, which complicates the development and clinical translation of off-the-shelf therapies. To overcome these obstacles, there is a critical need to explore Me2SO-free cryopreservation methods. While such methods typically yield suboptimal post-thaw viability with conventional slow-freeze protocols, optimizing freezing profiles offers a promising strategy to enhance their performance. This comprehensive review examines the latest advancements in cryopreservation techniques across various cell therapy platforms, with a specific case study of iPSC-derived therapies used to illustrate the scalability challenges. By identifying key thermodynamic and biochemical phenomena that occur during freezing, this review aims to identify cell-type independent approaches to improve the efficiency and efficacy of cryopreservation strategies, thereby supporting the widespread adoption and clinical success of off-the-shelf cell therapies.