"Advancing the implementation of innovative analytical technologies in pharmaceutical manufacturing-Some regulatory considerations".

Analytical technologies and methods play a pivotal role in attribute understanding and control which are essential to the rapidly evolving field of pharmaceutical development and manufacturing. These technologies are advancing quickly, where innovations often involve both new scientific approaches and novel applications of established techniques. In many cases, the lack of harmonized global regulatory expectations presents challenges for the adoption of advanced technologies.

An automatic approach to detect skin cancer utilizing active infrared thermography.

Skin cancer is a growing global concern, with cases steadily rising. Typically, malignant moles are identified through visual inspection, using dermatoscopy and patient history. Active thermography has emerged as an effective method to distinguish between malignant and benign lesions.

Piece by piece-a computer-aided method for virtual re-association of commingled fragmented remains.

Unlabelled: Air crashes or explosions with numerous victims may result in thousands of fragmented human remains that present a massive challenge for disaster victim identification teams. Genetic identification may present important financial and technical limits, and the physical re-association of fractured bones by forensic anthropologists may require a time-consuming phase of cleaning and drying. A virtual re-association (VRA) of fragmented human remains using postmortem computed tomography (CT)-scan images could enhance the identification process and reduce the number of genetic analyses required.

Feasibility Study on the Use of Infrared Cameras for Skin Cancer Detection under a Proposed Data Degradation Model.

Infrared thermography is considered a useful technique for diagnosing several skin pathologies but it has not been widely adopted mainly due to its high cost. Here, we investigate the feasibility of using low-cost infrared cameras with microbolometer technology for detecting skin cancer. For this purpose, we collected infrared data from volunteer subjects using a high-cost/high-quality infrared camera.

Recovering the activity parameters of an active fluid confined in a sphere.

The properties of an active fluid, for example, a bacterial bath or a collection of microtubules and molecular motors, can be accessed through the dynamics of passive particle probes. Here, in the perspective of analyzing experimental situations of confinement in droplets, we consider the kinematics of a negatively buoyant probe particle in an active fluid, both confined within a spherical domain. The active bath generates a fluctuating flow that pushes the particle with a velocity that is modeled as a colored stochastic noise, characterized by two parameters, the intensity and memory time of the active flow.

Enhancing the Efficiency of a Cybersecurity Operations Center Using Biomimetic Algorithms Empowered by Deep Q-Learning.

In the complex and dynamic landscape of cyber threats, organizations require sophisticated strategies for managing Cybersecurity Operations Centers and deploying Security Information and Event Management systems. Our study enhances these strategies by integrating the precision of well-known biomimetic optimization algorithms-namely Particle Swarm Optimization, the Bat Algorithm, the Gray Wolf Optimizer, and the Orca Predator Algorithm-with the adaptability of Deep Q-Learning, a reinforcement learning technique that leverages deep neural networks to teach algorithms optimal actions through trial and error in complex environments. This hybrid methodology targets the efficient allocation and deployment of network intrusion detection sensors while balancing cost-effectiveness with essential network security imperatives.

Accumulation and depletion of E. coli in surfaces mediated by curvature.

Can topography be used to control bacteria accumulation? We address this question in the model system of smooth-swimming and run-and-tumble Escherichia coli swimming near a sinusoidal surface, and show that the accumulation of bacteria is determined by the characteristic curvature of the surface. For low curvatures, cells swim along the surface due to steric alignment and are ejected from the surface when they reach the peak of the sinusoid. Increasing curvature enhances this effect and reduces the density of bacteria in the curved surface.

Kinetic Theory of Motility Induced Phase Separation for Active Brownian Particles.

When two active Brownian particles collide, they slide along each other until they can continue their free motion. For persistence lengths much larger than the particle diameter, the directors do not change, but the collision can be modeled as producing a net displacement on the particles compared to their free motion in the absence of the encounter. With these elements, a Boltzmann-Enskog-like kinetic theory is built.

A Novel Approach to Combinatorial Problems: Binary Growth Optimizer Algorithm.

The set-covering problem aims to find the smallest possible set of subsets that cover all the elements of a larger set. The difficulty of solving the set-covering problem increases as the number of elements and sets grows, making it a complex problem for which traditional integer programming solutions may become inefficient in real-life instances. Given this complexity, various metaheuristics have been successfully applied to solve the set-covering problem and related issues.

The role and limitations of electronic medical records versus patient interviews for determining symptoms of, underlying comorbidities of, and medication use by patients with COVID-19.

Electronic medical records (EMRs) are important for rapidly compiling information to determine disease characteristics (eg, symptoms) and risk factors (eg, underlying comorbidities, medications) for disease-related outcomes. To assess EMR data accuracy, agreement between EMR abstractions and patient interviews was evaluated. Symptoms, medical history, and medication use among patients with COVID-19 collected from EMRs and patient interviews were compared using overall agreement (ie, same answer in EMR and interview), reported agreement (yes answer in both EMR and interview among those who reported yes in either), and κ statistics.

Enhanced recovery after cardiac surgery: A literature review.

Enhanced recovery after cardiac surgery (ERACS) represents a constellation of evidence-based peri-operative methods aimed to reduce the physiological and psychological stress patients experience after cardiac surgery, with the primary objective of providing an expedited recovery to pre-operative functional status. The method involves pre-operative, intra-operative, and post-operative interventions as well as direct patient engagement to be successful. Numerous publications in regard to the benefits of enhanced recovery have been presented, including decreased post-operative complications, shortened length of stay, decreased overall healthcare costs, and higher patient satisfaction.

Selenized non-Saccharomyces yeasts and their potential use in fish feed.

Selenium (Se) is a vital trace element, essential for growth and other biological functions in fish. Its significance lies in its role as a fundamental component of selenoproteins, which are crucial for optimal functioning of the organism. The inclusion of Se in the diets of farmed animals, including fish, has proved invaluable in mitigating the challenges arising from elemental deficiencies experienced in captivity conditions due to limitations in the content of fishmeal.

Development of a protocol for standardized use of a water-soluble contrast agent with polyethylene glycol in post-mortem CT angiography.

Computed tomography angiography (PMCTA) is increasingly used in postmortem cases. Standardized validated protocols permit to compare different PMCTA images and make it more easily to defend a case in court. In addition to the well-known technique by Grabherr et al.

Management of coagulopathy among patients with cirrhosis undergoing upper endoscopy and paracentesis: Persistent gaps and areas of consensus in a multispecialty Delphi.

Patients with cirrhosis have abnormal coagulation indices such as a high international normalized ratio and low platelet count, but these do not correlate well with periprocedural bleeding risk. We sought to develop a consensus among the multiple stakeholders in cirrhosis care to inform process measures that can help improve the quality of the periprocedural management of coagulopathy in cirrhosis. We identified candidate process measures for periprocedural coagulopathy management in multiple contexts relating to the performance of paracentesis and upper endoscopy.

Prenatal exposure to environmental toxins and comprehensive dental findings in a population cohort of children.

Environmental toxins are known to have many impacts on growth and development in humans, starting in utero. Alterations in amelogenesis, caused by chemical and physical trauma that occur during the antenatal, perinatal and postnatal time periods, may result in developmental defects in deciduous and permanent tooth enamel, as demonstrated in animal studies. These defects can be clinically visible and result in a variety of morphological and functional problems in the dentition.

Upper Extremity Trauma in Costa Rica - Evaluating Epidemiology and Identifying Opportunities.

Background: Traffic accidents and musculoskeletal injuries represent a major cause of morbidity and mortality in Costa Rica. To inform capacity building efforts, we conducted a survey study of hand and upper extremity (UE) fellowship-trained surgeons in Costa Rica to evaluate the epidemiology, complications, and challenges in care of UE trauma.

Methods: Aiming to capture all hand and UE trained surgeons in Costa Rica, we compiled a list of nine surgeons and sent a survey in Spanish using Qualtrics.

Skin Cancer Detection and Classification Using Neural Network Algorithms: A Systematic Review.

In recent years, there has been growing interest in the use of computer-assisted technology for early detection of skin cancer through the analysis of dermatoscopic images. However, the accuracy illustrated behind the state-of-the-art approaches depends on several factors, such as the quality of the images and the interpretation of the results by medical experts. This systematic review aims to critically assess the efficacy and challenges of this research field in order to explain the usability and limitations and highlight potential future lines of work for the scientific and clinical community.

Challenging the Limits of Binarization: A New Scheme Selection Policy Using Reinforcement Learning Techniques for Binary Combinatorial Problem Solving.

In this study, we introduce an innovative policy in the field of reinforcement learning, specifically designed as an action selection mechanism, and applied herein as a selector for binarization schemes. These schemes enable continuous metaheuristics to be applied to binary problems, thereby paving new paths in combinatorial optimization. To evaluate its efficacy, we implemented this policy within our BSS framework, which integrates a variety of reinforcement learning and metaheuristic techniques.

Autonomous Parameter Balance in Population-Based Approaches: A Self-Adaptive Learning-Based Strategy.

Population-based metaheuristics can be seen as a set of agents that smartly explore the space of solutions of a given optimization problem. These agents are commonly governed by movement operators that decide how the exploration is driven. Although metaheuristics have successfully been used for more than 20 years, performing rapid and high-quality parameter control is still a main concern.

Feature Selection Problem and Metaheuristics: A Systematic Literature Review about Its Formulation, Evaluation and Applications.

Feature selection is becoming a relevant problem within the field of machine learning. The feature selection problem focuses on the selection of the small, necessary, and sufficient subset of features that represent the general set of features, eliminating redundant and irrelevant information. Given the importance of the topic, in recent years there has been a boom in the study of the problem, generating a large number of related investigations.

Dynamic Population on Bio-Inspired Algorithms Using Machine Learning for Global Optimization.

In the optimization field, the ability to efficiently tackle complex and high-dimensional problems remains a persistent challenge. Metaheuristic algorithms, with a particular emphasis on their autonomous variants, are emerging as promising tools to overcome this challenge. The term "autonomous" refers to these variants' ability to dynamically adjust certain parameters based on their own outcomes, without external intervention.

Psychometric analysis of the revised CompLEC test to measure reading speed and reading comprehension in university students.

Background: At university level, reading comprehension is one of the most important linguistic competences in the professional training of students because it is an instrument that enables the acquisition and production of scientific knowledge. Likewise, at this level of education, speed reading becomes a technique that allows to make the most of the time devoted to reading and to develop the ability to concentrate. However, there are not many instruments in the scientific literature that measure these two variables; therefore, the objective of this study was: To determine the psychometric properties of the revised compLEC test to measure reading comprehension and speed in university students.