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Despite advances in scaling up new vaccines in low- and middle-income countries, the global number of unvaccinated children has remained high over the past decade. We used 2000–2019 household survey data from 154 surveys representing 89 low- and middle-income countries to assess within-country, economic-related inequality in the prevalence of one-year-old children with zero doses of diphtheria–tetanus–pertussis (DTP) vaccine. Zero-dose DTP prevalence data were disaggregated by household wealth quintile. Difference, ratio, slope index of inequality, concentration index, and excess change measures were calculated to assess the latest situation and change over time, by country income grouping for 17 countries with high zero-dose DTP numbers and prevalence. Across 89 countries, the median prevalence of zero-dose DTP was 7.6%. Within-country inequalities mostly favored the richest quintile, with 19 of 89 countries reporting a rich–poor gap of ≥20.0 percentage points. Low-income countries had higher inequality than lower–middle-income countries and upper–middle-income countries (difference between the median prevalence in the poorest and richest quintiles: 14.4, 8.9, and 2.7 percentage points, respectively). Zero-dose DTP prevalence among the poorest households of low-income countries declined between 2000 and 2009 and between 2010 and 2019, yet economic-related inequality remained high in many countries. Widespread economic-related inequalities in zero-dose DTP prevalence are particularly pronounced in low-income countries and have remained high over the previous decade.

This paper presents an overview of various sensorless control methods, with a focus on dual three-phase permanent magnet synchronous machines (DTP-PMSM). Owing to the important role that DTP-PMSMs play in motion-control applications in industry, most academic researchers and industry activists seek to reduce costs and size while increasing the capability and efficiency of motion applications. This has led to an increase in the number of publications about multiphase machines in recent years. The purpose of this article is to review the most important sensorless control techniques, which are divided into two main categories, namely saliency-based control method for low-speed range and model-based control method for high-speed range. Both methods are subdivided into other categories, with a focus on DTP-PMSMs. The methods are compared with each other for the purpose of selecting the most suitable control technique for implementation in applications such as ship propulsion, wind turbines, and aerospace.

In the last few decades, nose-to-brain delivery has been investigated as an alternative route to deliver molecules to the Central Nervous System (CNS), bypassing the Blood-Brain Barrier. The use of nanotechnological carriers to promote drug transfer via this route has been widely explored. The exact mechanisms of transport remain unclear because different pathways (systemic or axonal) may be involved. Despite the large number of studies in this field, various aspects still need to be addressed. For example, what physicochemical properties should a suitable carrier possess in order to achieve this goal? To determine the correlation between carrier features (eg, particle size and surface charge) and drug targeting efficiency percentage (DTE%) and direct transport percentage (DTP%), correlation studies were performed using machine learning. Detailed analysis of the literature from 2010 to 2021 was performed on Pubmed in order to build \"NANOSE\" database. Regression analyses have been applied to exploit machine-learning technology. A total of 64 research articles were considered for building the NANOSE database (102 formulations). Particle-based formulations were characterized by an average size between 150-200 nm and presented a negative zeta potential (ZP) from -10 to -25 mV. The most general-purpose model for the regression of DTP/DTE values is represented by Decision Tree regression, followed by K-Nearest Neighbors Regressor (KNeighbor regression). A literature review revealed that nose-to-brain delivery has been widely investigated in neurodegenerative diseases. Correlation studies between the physicochemical properties of nanosystems (mean size and ZP) and DTE/DTP parameters suggest that ZP may be more significant than particle size for DTP/DTE predictability.

The recently emerged SARS-CoV-2 causing the ongoing COVID-19 pandemic is particularly virulent in the elderly while children are largely spared. Here, we explored the potential role of cross-reactive immunity acquired from pediatric vaccinations and exposure to common human pathogens in the protection and pathology of COVID-19. To that end, we sought for peptide matches to SARS-CoV-2 (identity ≥ 80%, in at least eight residues) in the proteomes of 25 human pathogens and in vaccine antigens, and subsequently predicted their T and B cell reactivity to identify potential cross-reactive epitopes. We found that viruses subject to pediatric vaccinations do not contain cross-reactive epitopes with SARS-CoV-2, precluding that they can provide any general protection against COVID-19. Likewise, common viruses including rhinovirus, respiratory syncytial virus, influenza virus, and several herpesviruses are also poor or null sources of cross-reactive immunity to SARS-CoV-2, discarding that immunological memory against these viruses can have any general protective or pathological role in COVID-19. In contrast, we found combination vaccines for treating diphtheria, tetanus, and pertussis infectious diseases (DTP vaccine) to be significant sources of potential cross-reactive immunity to SARS-CoV-2. DTP cross-reactive epitopes with SARS-CoV-2 include numerous CD8 and CD4 T cell epitopes with broad population protection coverage and potentially neutralizing B cell epitopes in SARS-CoV-2 Spike protein. Worldwide, children receive several DTP vaccinations, including three-four doses the first year of life and one at 4-6 years of age. Moreover, a low antigenic Tdap dose is also given at ages 9-14. Thereby, children may well be protected from SARS-CoV-2 through cross-reactive immunity elicited by DTP vaccinations, supporting testing in the general population to prevent COVID-19.

Process algebra can be considered one of the most practical formal methods for modeling Smart IoT Systems in Digital Twin, since each IoT device in the systems can be considered as a process. Further, some of the algebras are applied to predict the behavior of the systems. For example, PALOMA (Process Algebra for Located Markovian Agents) and PACSR (Probabilistic Algebra of Communicating Shared Resources) process algebras are designed to predict the behavior of IoT Systems with probability on choice operations. However, there is a lack of analytical methods in the algebras to predict the nondeterministic behavior of the systems. Further, there is no control mechanism to handle undesirable nondeterministic behavior of the systems. In order to overcome these limitations, this paper proposes a new process algebra, called dTP-Calculus, which can be used (1) to specify the nondeterministic behavior of the systems with static probability, (2) verify the safety and security requirements of the nondeterministic behavior with probability requirements, and (3) control undesirable nondeterministic behavior with dynamic probability. To demonstrate the feasibility and practicality of the approach, the SAVE (Specification, Analysis, Verification, Evaluation) tool has been developed on the ADOxx Meta-Modeling Platform and applied to a SEMS (Smart Emergency Medical Service) example. In addition, a miniature digital twin system for the SEMS example was constructed and applied to the SAVE tool as a proof of concept for Digital Twin. It shows that the approach with dTP-Calculus on the tool can be very efficient and effective for Smart IoT Systems in Digital Twin.

PurposeDrawing on the dual process model of ideology and prejudice, the purpose of this paper is to examine whether, how and when a supervisor's Machiavellianism leads to subordinates' perceptions of abusive supervision. In doing so, the authors also explore the mediating role of the supervisor's competitive world views and the moderating role of subordinates' performance on this relationship.Design/methodology/approachThe theoretical model was tested using three sources of data from supervisors, their subordinates and the organization. Hierarchical linear model analysis was run on supervisor and subordinate dyadic data for testing whether subordinates' performance moderated the mediated relationships or not.FindingsThe results suggest that the supervisors' competitive worldviews explain the positive link between their Machiavellianism and subordinates' perceptions of abusive supervision. The results highlight that the mediation effect of supervisors' competitive worldviews on the link between their Machiavellianism and their subordinates' perceptions of abusive supervision is more pronounced when subordinates' performance is low than when it is high.Research limitations/implicationsThis research contributes to the authors’ knowledge of the link between supervisors' Machiavellianism and abusive supervision, and how the toxic influence of their Machiavellianism is mediated by supervisors' competitive worldviews.Originality/valueThe study contributes to the literature on abusive supervision and personality by studying the role of personality as an antecedent of abusive supervision. Further, this study used subordinates' performance as a contextual variable for understanding abusive supervision.

The long-term impact of the COVID-19 pandemic on routine childhood vaccination remains unclear. We aimed to determine whether parents with children born both before and after the pandemic changed their vaccination decisions with regard to Measles-Mumps-Rubella (MMR) and Diphtheria-Tetanus-Pertussis (DTP)-containing vaccines. This self-controlled, matched cross-sectional study compared parental attitudes and behaviors towards childhood vaccination before and after the COVID-19 pandemic in the United Kingdom (UK) and Israel. We included 777 parents in the UK and 1270 in Israel, each with children born both before and after the pandemic. In the UK, Penta/hexavalent coverage declined from 96.5 % in children born pre-pandemic to 94.7 % in those born after and MMR from 97.3 % to 93.6 %, with 5.1 % of parents reporting vaccinating their child before but not after the pandemic for at least one vaccine. In Israel, pentavalent coverage decreased from 95.3 % in children born pre-pandemic to 93.1 % in those born after and MMR from 94.3 % to 91.6 %; 6.6 % reported a change towards non-vaccination for at least one vaccine. Reasons for non vaccination were similar across both countries and did not change after the pandemic. Refusal because of concern for side effects was the main refusal reason in both settings (cited by 83 % and 65 % of refusers pre-pandemic in the UK and Israel respectively, vs 92 and 63 % after). Across both countries, some minority groups were more likely to reduce vaccination. Over a third (37 %, 95 % CI 35–39) of participants reported less trust in vaccines after the pandemic compared to before. These findings suggest that the pandemic's impact on routine immunization is sustained and not context-specific. Interventions to restore trust and reduce concerns surrounding vaccines may help prevent persistent declines, maintain herd immunity, and ensure children remain protected post-pandemic. •Reported MMR/DTP vaccine coverage decreased by >3.5 % post COVID-19 among parents who vaccinated their children pre-pandemic.•Fear of side effects was the most common for vaccine refusal reason before and after the pandemic in Israel and the UK•The reasons for non-vaccination have not changed, but the phenomenon has amplified.•Over a third of parents reported less trust in vaccines after the pandemic compared to before.

Process algebra is one of the most suitable formal methods to model smart IoT systems for smart cities. Each IoT in the systems can be modeled as a process in algebra. In addition, the nondeterministic behavior of the systems can be predicted by defining probabilities on the choice operations in some algebra, such as PALOMA and PACSR. However, there are no practical mechanisms in algebra either to measure or control uncertainty caused by the nondeterministic behavior in terms of satisfiability of the system requirements. In our previous research, to overcome the limitation, a new process algebra called dTP-Calculus was presented to verify probabilistically the safety and security requirements of smart IoT systems: the nondeterministic behavior of the systems was defined and controlled by the static and dynamic probabilities. However, the approach required a strong assumption to handle the unsatisfied probabilistic requirements: enforcing an optimally arbitrary level of high-performance probability from the continuous range of the probability domain. In the paper, the assumption from the previous research is eliminated by defining the levels of probability from the discrete domain based on the notion of Permissible Process and System Equivalences so that satisfiability is incrementally enforced by both Permissible Process Enhancement in the process level and Permissible System Enhancement in the system level. In this way, the unsatisfied probabilistic requirements can be incrementally enforced with better-performing probabilities in the discrete steps until the final decision for satisfiability can be made. The SAVE tool suite has been developed on the ADOxx meta-modeling platform to demonstrate the effectiveness of the approach with a smart EMS (emergency medical service) system example, which is one of the most practical examples for smart cities. SAVE showed that the approach is very applicable to specify, analyze, verify, and especially, predict and control uncertainty or risks caused by the nondeterministic behavior of smart IoT systems. The approach based on dTP-Calculus and SAVE may be considered one of the most suitable formal methods and tools to model smart IoT systems for smart cities.

Drug-tolerant persister (DTP) cells are a subpopulation of cancer cells capable of surviving therapeutic stress through reversible, non-genetic adaptations. These cells contribute to minimal residual disease and eventual tumor relapse. Understanding the mechanisms that govern the entry into and exit from the DTP state—such as epigenetic remodeling, metabolic rewiring, and transcriptional plasticity—reveals actionable vulnerabilities. This article reviews the biological basis of DTP reversibility, outlines the major challenges in targeting these cells, and proposes innovative therapeutic strategies including epigenetic inhibitors, metabolic disruptors, and adaptive dosing regimens. We also highlight the importance of biomarker development and dynamic monitoring. Targeting DTP cells at their reversible stage may prevent permanent resistance, offering a promising avenue to improve treatment durability and patient outcomes in cancer therapy.

We reviewed Corynebacterium spp. infection cases reported in South Africa during 2015-2023. We analyzed 84 isolates from 83 patients with C. diphtheriae, as well as 1 C. belfantii and 3 C. ulcerans isolates. Among C. diphtheriae cases, we observed respiratory diphtheria (26/83 patients [31%]), endocarditis (14/83 [17%]), cutaneous diphtheria (22/83 [27%]), nonspecific respiratory illnesses (5/83 [6%]), and asymptomatic carriage (16/83 [19%]). The median patient age was 19 (range 0-88) years. Diphtheria-tetanus-pertussis vaccination was incomplete for 26% (5/19) or unknown for 68% (13/19) of children 0-9 years of age. C. diphtheriae was intermediately resistant to penicillin (82/84 [98%] isolates; MIC 0.5 μg/mL) but susceptible to erythromycin (83/84 [99%] isolates; MIC 0.25 μg/mL). Eighteen unique sequence types were identified, corroborating C. diphtheriae heterogeneity. Toxin-producing strains were detected among cutaneous and respiratory diphtheria cases, indicating all forms of disease require monitoring and prompt public health action to curb transmission.