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Previous research indicates that vitamin D and omega-3 co-supplementation may benefit overall health, but current evidence regarding its effects on lipid profile remains unclear. The present systematic review and meta-analysis aimed to examine the effects of vitamin D and omega-3 co-supplementation on lipid profile (total cholesterol [TC], low-density lipoprotein [LDL], triglyceride [TG] and high-density lipoprotein [HDL]) in adults.

In this systematic review and meta-analysis, relevant studies were obtained by searching the PubMed, Scopus and Web of Science databases (from inception to January 2022). Weighted mean differences and 95% confidence intervals were estimated via a random-effects model. Heterogeneity, sensitivity analysis and publication bias were reported using standard methods.

Pooled analysis of six randomized controlled trials (RCTs) revealed that vitamin D and omega-3 co-supplementation yielded significant reductions in TG (p = 0.631). A pooled analysis of five trials indicated a significant association between omega-3 and vitamin D treatment and reductions in TC (p = 0.001) and LDL (p = 0.001). Although, pooled analyses of omega-3 and vitamin D did not significantly affect HDL.

The findings suggest that vitamin D and omega-3 co-supplementation lowers TG, TC and LDL in adults. Future, large-scale, RCTs on various populations are needed to elucidate further beneficial effects of vitamin D and omega-3 co-supplementation on lipid profile and establish guidelines for clinical practice.

The study showcases the social impact (online attention) of funded research compared to nonfunded for the BRICS nations. The key themes achieving online attention across the funded and nonfunded publications have also been identified.

A total of 1,507,931 articles published across the BRICS nations for a period of three (03) years were downloaded from the Clarivate Analytics' InCites database of Web of Science (WoS). “Funding Acknowledgement Analysis (FAA)” was used to identify the funded and nonfunded publications. The altmetric score of the top highly cited (1%) publications was gauged from the largest altmetric data provider, “Altmetric.com”, using the DOI of each publication. One-way ANOVA test was used to know the impact of funding on the mentions (altmetrics) across different data sources covered by Altmetric.com. The highly predominant keywords (hotspots) have been mapped using bibliometric software, “VOSviewer”.

The mentions across all the altmetric sources for funded research are higher compared to nonfunded research for all nations. It indicates the altmetric advantage for funded research, as funded publications are more discussed, tweeted, shared and have more readers and citations; thus, acquiring more social impact/online attention compared to nonfunded publications. The difference in means for funded and nonfunded publications varies across various altmetric sources and nations. Further, the authors’ keyword analysis reveals the prominence of the respective nation names in publications of the BRICS.

The study showcases the utility of indexing the funding information and whether research funding increases social impact return (online attention). It presents altmetrics as an important impact assessment and evaluation framework indicator, adding one more dimension to the research performance. The linking of funding information with the altmetric score can be used to assess the online attention and multi-flavoured impact of a particular funding programme and source/agency of a nation so that necessary strategies would be framed to improve the reach and impact of funded research. It identifies countries that achieve significant online attention for their funded publications compared to nonfunded ones, along with the key themes that can be utilised to frame research and investment plans.

The study represents the social impact of funded research compared to nonfunded across the BRICS nations.

The purpose of this paper is to design and manufacture an intelligent 3D printed sensor to monitor the re-occurrence of diaphragmatic hernia (DH; after surgery) in bovines as an Internet of Things (IOT)-based solution.

The approach used in this study is based on a bibliographic analysis for the re-occurrence of DH in the bovine after surgery. Using SolidWorks and ANSYS, the computer-aided design model of the implant was 3D printed based on literature and discussions on surgical techniques with a veterinarian. To ensure the error-proof design, load test and strain–stress rate analyses with boundary distortion have been carried out for the implant sub-assembly.

An innovative IOT-based additive manufacturing solution has been presented for the construction of a mesh-type sensor (for the health monitoring of bovine after surgery).

An innovative mesh-type sensor has been fabricated by integration of metal and polymer 3D printing (comprising 17–4 precipitate hardened stainless steel and polyvinylidene fluoride-hydroxyapatite-chitosan) without sacrificing strength and specific absorption ratio value.

Digital transformation affected modern society influencing how businesses cooperate and produce value. In this context, Artificial Intelligence plays a critical role. This study aims to explore the role of Artificial Intelligence in organisational positioning within the market, influencing firms' competitiveness. In this vein, this research seeks to respond to the following research question: How does AI impact the competitive advantage of healthcare organizations?.

To tackle the research question, an explorative analysis using the case study method to investigate an international healthcare center in Dubai was conducted. Nine semi-structured interviews were conducted with the head and the members of the robotic surgery team in CMC Dubai to thoroughly understand what the components of the robotic approach are and how the arrangement before the introduction of this innovative technique while shedding light on the added value and the advantages of adopting such technique on both patient safety and patient satisfaction. Additionally, archival data and online documentation (e.g. industry reports, newspaper articles and internal documents) were analyzed to obtain data triangulation.

The results highlight three primary outcomes influenced by implementing AI in organizational processes: clinical, financial and technological outcomes. The study will offer interesting non-studied insights about the implementation of Artificial Intelligence tools in the healthcare sector and specifically robotic surgeries, and to which extent this will contribute and represent a competitive advantage. Results will hopefully insert a brick in the wall of the impact of AI tools on the quality and the results of surgical operations while emphasizing the benefits of integrating AI in surgical practice.

This study offers interesting theoretical and practical implications. It opens a new perspective to understand and manage AI tools in service. This research is not without limits providing valuable insights for future research.

The purpose of this review paper is to address the substantial challenges of the outdated exoskeletons used for rehabilitation and further study the current advancements in this field. The shortcomings and technological developments in sensing the input signals to enable the desired motions, actuation, control and training methods are explained for further improvements in exoskeleton research.

Search platforms such as Web of Science, IEEE, Scopus and PubMed were used to collect the literature. The total number of recent articles referred to in this review paper with relevant keywords is filtered to 143.

Exoskeletons are getting smarter often with the integration of various modern tools to enhance the effectiveness of rehabilitation. The recent applications of bio signal sensing for rehabilitation to perform user-desired actions promote the development of independent exoskeleton systems. The modern concepts of artificial intelligence and machine learning enable the implementation of brain–computer interfacing (BCI) and hybrid BCIs in exoskeletons. Likewise, novel actuation techniques are necessary to overcome the significant challenges seen in conventional exoskeletons, such as the high-power requirements, poor back drivability, bulkiness and low energy efficiency. Implementation of suitable controller algorithms facilitates the instantaneous correction of actuation signals for all joints to obtain the desired motion. Furthermore, applying the traditional rehabilitation training methods is monotonous and exhausting for the user and the trainer. The incorporation of games, virtual reality (VR) and augmented reality (AR) technologies in exoskeletons has made rehabilitation training far more effective in recent times. The combination of electroencephalogram and electromyography-based hybrid BCI is desirable for signal sensing and controlling the exoskeletons based on user intentions. The challenges faced with actuation can be resolved by developing advanced power sources with minimal size and weight, easy portability, lower cost and good energy storage capacity. Implementation of novel smart materials enables a colossal scope for actuation in future exoskeleton developments. Improved versions of sliding mode control reported in the literature are suitable for robust control of nonlinear exoskeleton models. Optimizing the controller parameters with the help of evolutionary algorithms is also an effective method for exoskeleton control. The experiments using VR/AR and games for rehabilitation training yielded promising results as the performance of patients improved substantially.

Robotic exoskeleton-based rehabilitation will help to reduce the fatigue of physiotherapists. Repeated and intention-based exercise will improve the recovery of the affected part at a faster pace. Improved rehabilitation training methods like VR/AR-based technologies help in motivating the subject.

The paper describes the recent methods for signal sensing, actuation, control and rehabilitation training approaches used in developing exoskeletons. All these areas are key elements in an exoskeleton where the review papers are published very limitedly. Therefore, this paper will stand as a guide for the researchers working in this domain.

The authors determine how the scheduling and sequencing of surgeries by surgeons impacts the rate of post-surgical complications and patient length-of-stay in the hospital.

Leveraging a dataset of 29,169 surgeries performed by 111 surgeons from a large hospital network in Ontario, Canada, the authors perform a matched case-control regression analysis. The empirical findings are contextualized by interviews with surgeons from the authors’ dataset.

Surgical complications and longer hospital stays are more likely to occur in technically complex surgeries that follow a similarly complex surgery. The increased complication risk and length-of-hospital-stay is not mitigated by scheduling greater slack time between surgeries nor is it isolated to a few problematic surgery types, surgeons, surgical team configurations or temporal factors such as the timing of surgery within an operating day.

There are four major limitations: (1) the inability to access data that reveals the cognition behind the behavior of the task performer and then directly links this behavior to quality outcomes; (2) the authors’ definition of task complexity may be too simplistic; (3) the authors’ analysis is predicated on the fact that surgeons in the study are independent contractors with hospital privileges and are responsible for scheduling the patients they operate on rather than outsourcing this responsibility to a scheduler (i.e. either a software system or an administrative professional); (4) although the empirical strategy attempts to control for confounding factors and selection bias in the estimate of the treatment effects, the authors cannot rule out that an unobserved confounder may be driving the results.

The study demonstrates that the scheduling and sequencing of patients can affect service quality outcomes (i.e. post-surgical complications) and investigates the effect that two operational levers have on performance. In particular, the authors find that introducing additional slack time between surgeries does not reduce the odds of back-to-back complications. This result runs counter to the traditional operations management perspective, which suggests scheduling more slack time between tasks may prevent or mitigate issues as they arise. However, the authors do find evidence suggesting that the risk of back-to-back complications may be reduced when surgical pairings are less complex and when the method involved in performing consecutive surgeries varies. Thus, interspersing procedures of different complexity levels may help to prevent poor quality outcomes.

The authors empirically connect choices made in scheduling work that varies in task complexity and to patient-centric health outcomes. The results have implications for achieving high-quality outcomes in settings where professionals deliver a variety of technically complex services.

This paper aims to present a kinematics analysis method and statics based control of the continuum robot with mortise and tenon joints to achieve better control performance of the robot.

The kinematics model is derived by the geometric analysis method under the piecewise constant curvature assumption, and the workspace and dexterity of the proposed robot are analyzed to optimize its structure parameters. Moreover, the statics model is established by the principle of virtual work, which is used to analyze the mapping relationship between the bending deformation and the applied forces/torques. To improve the control accuracy of the robot, a model-based controller is put forward.

Results of the experiments verify the feasibility of the proposed continuum structure and the correctness of the established model and the control method. The force deviation between the theoretical value and the actual value is relatively small, and the mean value of the deviation between the driving forces is only 0.46 N, which verify the established statics model and the controller.

The proposed model and motion controller can realize its accurate bending control with a few deviations, which can be used as the reference for the motion planning and dynamic model of the continuum robot.