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Impact of COVID-19 on the prevalence of multi-drug-resistant bacteria: a literature review and meta-analysis
No full textThe COVID-19 pandemic affected the global healthcare delivery system, raising concerns about its influence on antimicrobial resistance (AMR). This systematic review and meta-analysis assessed the impact of the COVID-19 pandemic on the prevalence of MDR bacteria in different healthcare environments. A systematic search was carried out in PubMed-MEDLINE, Embase, Web of Science, BIOSIS, Scopus, and Google Scholar for articles published from December 2019 to January 2024. After screening 77 full-text studies, 28 studies were included in the analysis. The inclusion criteria included original human studies presenting MDR bacteria incidence before and during/after COVID-19 with reference to Carbapenem-resistant Acinetobacter baumannii, Carbapenem-resistant Enterobacteriaceae, Vancomycin Resistant Enterococci, Carbapenem-Resistant Pseudomonas aeruginosa, Methicillin-resistant Staphylococcus aureus, and Extended-Spectrum Beta-Lactamase-producing Enterobacteriaceae. The overall odds ratio (OR = 0.91, 95% CI: 0.70-1.17) indicates no significant change in the prevalence of multidrug-resistant (MDR) bacterial infection between the pre-COVID-19 and the COVID-19 period. There was no significant change in the prevalence of MRSA, ESBL, and VRE pre- and post-COVID. However, there was a significant reduction in the prevalence of CR-Ab, CRE, and CRPA pre- and during/after-COVID-19. MDR prevalence was significantly increased in Asia (18%) while it decreased slightly in North America (10.3%), showing variations in antibiotic use. The findings show that COVID-19 has different effects on the prevalence of MDR bacteria across geographical regions and healthcare facilities. [Abstract copyright: © 2025. The Author(s), under exclusive licence to Springer Nature Switzerland AG.
Our common journey towards a sustainable existence
Full text linkUnless global businesses are sustainable and take sustainable actions in all they do, the planet Earth will die and go into oblivion, that’s my own personal conviction. This I believe will not be in the interest of anyone. This timely journal of ours, the Journal of Sustainable Business aims to encourage global scholars in the field of sustainability and all it encompasses that are based up and down this planet to engage and publish their good quality research studies that would ensure the survival of this precious creation of God called the Earth
Academic support as a ‘third space’: a team’s reflection on post-pandemic practice
Full text linkThis paper describes and reflects upon the re-organisation of academic support across a department of architecture, art and design within a British post-92 university drawing on the concept of ‘third space’ in relation to student success. Both the department and the institution are committed to social justice, widening participation and academic success. With the introduction of online support during the pandemic and a new team of colleagues, an opportunity arose to revise how academic support was delivered to undergraduate students. For this team, which includes academic mentors and an academic manager, the COVID-19 pandemic brought challenges that impacted our historical delivery of academic support, requiring us to redefine our service to students and colleagues in the light of student success and inspired by the concept of the ‘third space’. This paper reflects upon the changes we made, as a case study, with reference to quantitative data, students’ feedback and Whitchurch’s (2009) framework of knowledges, legitimacies and relationships for blended professionals
Changes in cardiorespiratory fitness following exercise training prescribed relative to traditional intensity anchors and physiological thresholds: a systematic review with meta-analysis of individual participant data
No full textBackground
It is unknown whether there are differences in maximal oxygen uptake (O2max) response when prescribing intensity relative to traditional (TRAD) anchors or to physiological thresholds (THR).
Objectives
The present meta-analysis sought to compare: (a) mean change in O2max, (b) proportion of individuals increasing O2max beyond a minimum important difference (MID) and (c) response variability in O2max between TRAD and THR.
Methods
Electronic databases were searched, yielding data for 1544 individuals from 42 studies. Two datasets were created, comprising studies with a control group (‘controlled’ studies), and without a control group (‘non-controlled’ studies). A Bayesian approach with multi-level distributional models was used to separately analyse O2max change scores from the two datasets and inferences were made using Bayes factors (BF). The MID was predefined as one metabolic equivalent (MET; 3.5 mL kg−1 min−1).
Results
In controlled studies, mean O2max change was greater in the THR group compa
Heroes, villains and naked nations: micro-solidarity and grounded nationalism in times of crisis
Full text linkFiguratively speaking, the COVID-19 pandemic (2019–22) stripped nations naked, exposing the bare structure of how nationalism, as the driving force behind the nation-states, operates on the ground. Based on a survey conducted in April 2021 in five countries (Sweden, Serbia, Germany, Ireland and England), we thematically analyze two open-ended questions on who should be remembered as the heroes and villains of the pandemic, demonstrating that people’s perception of COVID-19 is shaped and reimagined through the category of their own nation-state. Two main arguments are put forward: (1) the vast majority of answers show that heroes and villains are found in small group encounters; (2) yet in-group micro-solidarity is referential to the existing organizational and ideological power of the nation-state. We utilize the notion of “naked nations” to show that, in times of crisis, people’s selfhood is profoundly grounded in micro-solidarity encounters that are tightly linked to nation-states
AOBL‑IPACO: a novel and optimized algorithm to mitigate losses in electrical grid systems
Full text linkThis paper shows the framework for solving the economic optimization problem in electrical grid system using Advanced Oppositional Based Learning (AOBL) technique with Invasive Plant Ant Colony Optimization (IPACO) algorithm. The work focuses on application of newly developed algorithm called Advance Oppositional Invasive Plant Ant Colony Optimization (AOIPACO) to solve the various constraints of single objective problem. The artificial algorithm leads to direction of exploration for new space of ant colonies with process of threats elimination from native candidates in energy management. During simulation process, the proposed algorithm reduces the power loss along with improvement of cost factor and computational time. The proposed AOIPACO approach is implemented on standard IEEE-5, 13 and 40 bus systems and generates optimal results as compared to other conventional techniques while solving the complex problem of optimization. Further, this meta heuristic technique help to improve the quality of power market system with minimum computation error at fast convergence rate
Blockchain and FL-based secure architecture for enhanced external Intrusion detection in smart farming
Full text linkSmart farming influences advanced technologies to optimize agricultural procedures, yet it meets significant cybersecurity challenges, particularly in External Intrusion Detection (EID). This article proposes a novel architecture combining Blockchain Technology and Federated Learning (FL) to reinforce the security of Smart Farming Systems (SMS) against external threats. The integration of Blockchain ensures data authentication and transparent data storage, while FL enables collaborative model training without compromising data privacy. Our architecture employs Ensemble Learning (EL) for the Local Model at the Ensemble Layer to train each Smart Land's data and offers privacy-prevented security. These devices utilize FL techniques to collaboratively train intrusion detection models while preserving the confidentiality of sensitive data. The Aggregated Model completes data aggregation at the Authentication Layer, and the PoAh Consensus Algorithm is leveraged for smart land's data authentication. The IoT Sensor device's identical information of smart lands is stored at the Macro Base Stations (MBSs). After downloading the aggregated values of the aggregated model, the local model transfers the smart lands information to the Cloud layer for decision making and decentralized storage. The validation outcomes of the proposed architecture demonstrate excellent performance, with an average processing time of 3.663 secs and 0.9956 accuracy for Smart Land compared to existing frameworks
Balancing institutional, social and cognitive factors: human resources professionals' involvement in executive remuneration governance
Full text linkThis paper investigates qualitatively the involvement of Human Resources (HR) professionals in executive remuneration governance within large UK public companies and similar organisations, considering the complex interplay of institutional, social and cognitive factors that influence executive pay decisions. Through interviews with senior HR professionals and focus groups involving mid-ranking HR professionals, the study identifies key themes, challenges and opportunities faced by HR in navigating the executive remuneration landscape. The study contributes to a more nuanced understanding of the sociological and psychological dimensions of executive pay governance. The findings highlight the practical implications for HR professionals, emphasising the need for active engagement with diverse stakeholder groups, fostering a culture of openness and transparency to ensure that executive pay practices and associated processes align with organisational values and societal expectations, while underscoring the value of learning from diverse perspectives and practices
Two plus four equals three - iron(II)/iron(IV) comproportionation as an additional pathway for iron(IV)-oxido reactions
No full textIron enzymes are ubiquitous in nature. In particular, enzymes with iron−oxygen cofactors as active sites perform a vast variety of reactions. Both iron(III)-hydroxido and iron(IV)-oxido species have been observed to play a catalytically active role. In order to complement biochemical investigations, a large variety of synthetic compounds using these motifs were synthesized in past decades to study and understand their inherent reactivity. One such synthetic model complex is [FeIV(O)(Py5Me2)]2+, (Py5Me2 = 2,6-bis(1,1-bis(2-pyridyl)ethyl)pyridine, henceforth labelled L1), which was used as a model complex for epigenetically relevant iron(II)/α-ketoglutarate-dependent ten-eleven translocation 5-methylcytosine dioxygenases (TET). Additionally, [FeIII(OH)(Py5(OH)2)]2+ (Py5(OH)2 =pyridine-2,6-diylbis [di(pyridin-2-yl)methanol, henceforth labelled L2) was tested as alipoxygenase model. We have complemented the available complexes of these related pentapyridyl complexes to include all oxidation states II−IV and performed detailed spectroscopic and spectrometric investigations. We found that iron(II) and iron(IV)-oxido compounds (cross-)comproportionate readily to form iron(III)-hydroxido species, which represents a major side reaction for model complex investigations. We also investigated the oxidative reactivity of a new iron(IV)-oxido complex
Weaponized IoT: a comprehensive comparative forensic analysis of Hacker Raspberry Pi and PC Kali Linux machine
Full text linkThe proliferation of Internet of Things (IoT) devices presents significant challenges for cybersecurity and digital forensics, particularly as these devices have become increasingly weaponised for malicious activities. This research focuses on the forensic analysis capabilities of Raspberry Pi devices configured with Kali Linux, comparing their forensic capabilities to conventional PC-based forensic investigations. The study identifies key gaps in existing IoT forensic methodologies, including limited tool compatibility, constrained data retention, and difficulties in live memory analysis due to architectural differences. The research employs a testbed-based approach to simulate cyberattacks on both platforms, capturing and analysing forensic artefacts such as system logs, memory dumps, and network traffic. The research findings reveal that while traditional PCs offer extensive forensic capabilities due to superior storage, tool support, and system logging, Raspberry Pi devices present significant forensic challenges, primarily due to their ARM architecture and limited forensic readiness. The study emphasises the need for specialised forensic tools tailored to IoT environments and suggests best practices to enhance forensic investigation capabilities in weaponised IoT scenarios. This research contributes to the field by bridging the gap between theoretical frameworks and real-world forensic investigations, offering insights into the evolving landscape of IoT forensics and its implications for digital evidence collection, analysis, and forensic readiness