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Purpose: Pulsed electrical field (PEF) ablation is an energy-based technique used to treat a range of cancers by irreversible electroporation (IRE). Our objective was to use computational and plant-based models to characterize the electric field distribution and ablation zones induced with a commercial 8-needle array-based applicator intended for treatment of skin cancer when high-frequency IRE (H-FIRE) pulses are applied. Electric field characterisation of this device was not previously assessed. Methods: Vegetable experimental were conducted using parallel plate electrodes to obtain the lethal threshold for H-FIRE pulses. Then a 3D computational model of the applicator was built mimicking the experimental conditions. The computational ablation zones were validated with the experiments for different voltage levels ranging from 220 to 525 V. Results: A threshold of 453 V/cm was estimated for H-FIRE pulses, which was used to predict computationally the ablation zones. It was found that the model showed a low prediction error, ranging from 2% for the minor diameter to 4.5% for the depth compared with experiments. Voltages higher than 370 V created an ablation volume with a rectangular prism shape determined by the positions of the needles, whereas lower voltages provoked the appearance of untreated areas (gaps). Conclusions: Our computer model predicts reasonably well the ablation zone induced by H-FIRE pulses, suggesting that a sufficiently large voltage must be applied to avoid the appearance of gaps. The validated model with vegetable experiments could serve as the basis for future computer studies to predict the behaviour of this device on heterogeneous tissues. [ABSTRACT FROM AUTHOR]

When state armed forces engage in violence against civilians during civil wars, why do some citizens continue to support the government? I argue that individuals' support for the state in such contexts is shaped by the interplay between their perceptions of violence, governance and ideology. Drawing on research concerning motivated reasoning, I suggest that ideological similarity with and effective governance from the state can alleviate the negative effect of military violence against civilians on support for the state and, conversely, augment the positive effect of insurgent abuse on attitudes toward the government. Analysis of seven years of surveys fielded by the Latin American Public Opinion Project in Colombia between 2005 and 2011 suggests that individuals' responses to victimization by the state's armed forces depend on whether the individuals are ideologically aligned with the state. More specifically, among people who have an ideology similar to that of the president, military victimization has a less negative effect on support for the armed forces and for the national government. There is also mixed evidence that the quality of state governance, particularly the provision of security from crime, shapes the ways people respond to victimization. While existing studies primarily focus on the effects of either violence or governance on attitudes toward the state, these findings indicate that a more complete theory of why people support governments which engage in violence against civilians requires an understanding of not only violence but also of governance and ideology. [ABSTRACT FROM AUTHOR]

Introduction: Fruits are vital for promoting human health, as well as providing nutrients and other compounds linked to protection against many different diseases. Loengo (Anisophyllea boehmii Engl.) produces an edible stone fruit, plum-shaped (drupe), dark blue and maroon or carmine in the ripening stage, which is generally, consumed fresh in the production areas. Characterization of this fruit will contribute to estimate its nutritional and pharmaceutical potential impact. The present work aimed at the physic-chemical, nutritional and antioxidant activity characterization of loengo fruit. Methods: Soluble solid contents (SSC) in the pulp were assessed in juice, at room temperature. Total protein was determined using the Dumas method. In what concerns the mineral composition were determined by ICP-OES. Organic acids identification and quantification was accomplished using a high-performance liquid chromatography (HPLC) system. The total polyphenol contents (TPC) were determined in 96-well microplate assays. Antioxidant activity were determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and the ferric reducing antioxidant power (FRAP) assay. Results and discussion: Composition, in terms of fresh matter is as follows: pulp soluble sugar content (refractometer) is 19.5% ± 0.02%, and pulp titratable acidity 1.2% ± 0.1% expressed in citric acid; total protein content is 7.4% ± 0.02%, 8.0% ± 0.1%, 16.9% ± 0.2%, for the peel, pulp and seed, respectively. In what concerns the mineral composition, the results obtained show that it is a good source of minerals, mainly potassium and phosphorus, but also calcium, sulfur, and magnesium, with the pulp richer in potassium, the seed in phosphorus, and the peel in calcium. As expected, the pulp showed the highest total soluble sugar content, whereas the seed had the lowest. The main sugars found in the pulp were glucose and fructose. In the peel citric acid was the main organic acid found, together with malic, oxalic, and ascorbic acids. Most antioxidant activity was found in the seed. The results of this work provide important basic information to recommend the consumption of this fruit for its sweet taste, chemical and nutritional composition, and, most of all, for its richness in total phenolic compounds for it potential to formulate nutraceutical foods. [ABSTRACT FROM AUTHOR]

Purpose: Long COVID (LC) is an ongoing public health crisis due to the persistent and debilitating symptoms that many individuals develop after surviving an acute SARS-CoV-2 infection. Neurocognitive impairments associated with LC are prevalent and difficult to treat. This study describes the clinical characteristics and outcomes from a cohort of patients with LC and examines how cognitive dysfunction is related to various other health domains such as function, neuropsychiatric issues, and quality of life. Methods: Retrospective cross-sectional analyses were conducted using self-reported data collected by online survey: demographic information, questions about symptoms, perceived deficits, functional limitations, and other measures of well-being from various standardized instruments. The relationship between cognitive dysfunction and these variables was assessed by Spearman correlations and chi-square tests. Results: The sample included 427 subjects: 29.7% male, median 45 (14–89) years old. Based on normative cutoff, a large majority (72.4%) presented with cognitive dysfunction, which was significantly associated to fatigue (P <.001), disability (P <.001), reduced employment (P <.001), and difficulty in usual activities (P <.001). Conclusions: These findings align with and expand on previous studies investigating the negative impact of LC. Impaired cognition seems linked to adverse effects and daily functioning but causality cannot be determined without further research. Ongoing efforts are needed for identifying feasible and effective treatment options that may improve management of this complex condition. [ABSTRACT FROM AUTHOR]

The concept of green scheduling, which deals with the environmental impact of the scheduling process, is becoming increasingly important due to growing environmental concerns. Most green scheduling problem variants focus on modelling the energy consumption during the execution of the schedule. However, the dynamic unrelated machines environment is rarely considered, mainly because it is difficult to manually design simple heuristics, called dispatching rules (DRs), which are suitable for solving dynamic, non-standard scheduling problems. Using hyperheuristics, especially genetic programming (GP), alleviates the problem since it enables the automatic design of new DRs. In this study, we apply GP to automatically design DRs for solving the green scheduling problem in the unrelated machines environment under dynamic conditions. The total energy consumed during the system execution is optimised along with two standard scheduling criteria. The three most commonly investigated green scheduling problem variants from the literature are selected, and GP is adapted to generate appropriate DRs for each. The experiments show that GP-generated DRs efficiently solve the problem under dynamic conditions, providing a trade-off between optimising standard and energy-related criteria. [ABSTRACT FROM AUTHOR]