Natural bone constitutes a complex and organized structure of organic and inorganic components with limited ability to regenerate and restore injured tissues, especially in large bone defects. To improve the reconstruction of the damaged bones, tissue engineering has been introduced as a promising alternative approach to the conventional therapeutic methods including surgical interventions using allograft and autograft implants. Bioengineered composite scaffolds consisting of multifunctional biomaterials in combination with the cells and bioactive therapeutic agents have great promise for bone repair and regeneration. Cellulose and its derivatives are renewable and biodegradable natural polymers that have shown promising potential in bone tissue engineering applications. Cellulose-based scaffolds possess numerous advantages attributed to their excellent properties of non-toxicity, biocompatibility, biodegradability, availability through renewable resources, and the low cost of preparation and processing. Furthermore, cellulose and its derivatives have been extensively used for delivering growth factors and antibiotics directly to the site of the impaired bone tissue to promote tissue repair. This review focuses on the various classifications of cellulose-based composite scaffolds utilized in localized bone drug delivery systems and bone regeneration, including cellulose-organic composites, cellulose-inorganic composites, cellulose-organic/inorganic composites. We will also highlight the physicochemical, mechanical, and biological properties of the different cellulose-based scaffolds for bone tissue engineering applications.
On the northern coast of British Columbia, Canada, we used the infaunal invertebrate community (meiofauna) of the Cassiar Cannery mudflat to assess responses to different severities of a mechanical disturbance. Overall, the infaunal community was effective in identifying if a disturbance had occurred, regardless of disturbance severity. However, considerable overlap was observed between infaunal communities in disturbed and reference habitat. Variation between disturbed and reference habitats was primarily the result of differences in the relative abundances of five taxa (Oligochaeta, Nematoda, Nippoleucon hinumensis, Capitella species complex, and Macoma balthica). Conversely, the infaunal community was not an effective tool in differentiating between disturbance severities, likely because of the subtle differences observed between infaunal successional stages. We also assessed how increasing misalignment of spatial resolution between sampling and disturbance scales influenced analytical findings. As misalignment between the scale of disturbance and investigation increased, Type I and Type II errors became more common in our analyses. Our findings indicate that intertidal infaunal communities can be effectively used to study the influence of disturbances upon an ecological system. However, care must be taken to ensure the proper sampling scheme is used, one that overlaps with the scale of disturbance. These findings expand our understanding of how communities respond to disturbance and will be of interest to anyone attempting to study, detect, or mediate anthropogenic and natural disturbances.
Background The primary aim of this study was to determine the influence of task constraints, from an ecological perspective, on goal kicking performance in Australian football. The secondary aim was to compare the applicability of three analysis techniques; logistic regression, a rule induction approach and conditional inference trees to achieve the primary aim. In this study, an ecological perspective has been applied to explore the impact of task constraints on shots on goal in the Australian Football League, such as shot type, field location and pressure. Analytical techniques can increase the understanding of competition environments and the influence of constraints on skilled events. Differing analytical techniques can produce varying outputs styles which can impact the applicability of the technique. Logistic regression, Classification Based on Associations rules and conditional inference trees were conducted to determine constraint interaction and their influence on goal kicking, with both the accuracy and applicability of each approach assessed. Results Each analysis technique had similar accuracy, ranging between 63.5% and 65.4%. For general play shots, the type of pressure and location particularly affected the likelihood of a shot being successful. Location was also a major influence on goal kicking performance from set shots. Conclusions When different analytical methods display similar performance on a given problem, those should be prioritised which show the highest interpretability and an ability to guide decision-making in a manner similar to what is currently observed in the organisation.
Seeking to obtain a competitive advantage and manage the risk of injury, team sport organisations are investing in tracking systems that can quantify training and competition characteristics. It is expected that such information can support objective decision-making for the prescription and manipulation of training load. This narrative review aims to summarise, and critically evaluate, different tracking systems and their use within team sports. The selection of systems should be dependent upon the context of the sport and needs careful consideration by practitioners. The selection of metrics requires a critical process to be able to describe, plan, monitor and evaluate training and competition characteristics of each sport. An emerging consideration for tracking systems data is the selection of suitable time analysis, such as temporal durations, peak demands or time series segmentation, whose best use depends on the temporal characteristics of the sport. Finally, examples of characteristics and the application of tracking data across seven popular team sports are presented. Practitioners working in specific team sports are advised to follow a critical thinking process, with a healthy dose of scepticism and awareness of appropriate theoretical frameworks, where possible, when creating new or selecting an existing metric to profile team sport athletes.
The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.
Authentication plays a critical role in the security of quantum key distribution (QKD) protocols. We propose using Polynomial Hash and its variants for authentication of variable length messages in QKD protocols. Since universal hashing is used not only for authentication in QKD but also in other steps in QKD like error correction and privacy amplification, and also in several other areas of quantum cryptography, Polynomial Hash and its variants as the most efficient universal hash function families can be used in these important steps and areas, as well. We introduce and analyze several efficient variants of Polynomial Hash and, using deep results from number theory, prove that each variant gives an ε-almost-Δ-universal family of hash functions. We also give a general method for transforming any such family to an ε-almost-strongly universal family of hash functions. The latter families can then, among other applications, be used in the Wegman–Carter MAC construction which has been shown to provide a universally composable authentication method in QKD protocols. As Polynomial Hash has found many applications, our constructions and results are potentially of interest in various areas.
Complex systems are open systems consisting of many components that can interact among themselves and the environment. New forms of behaviours and patterns often emerge as a result. There is a growing recognition that most sporting environments are complex adaptive systems. This acknowledgement extends to sports injury and is reflected in the individual responses of athletes to both injury and rehabilitation protocols. Consequently, practitioners involved in return to sport decision making (RTS) are encouraged to view return to sport decisions through the complex systems lens to improve decision-making in rehabilitation. It is important to clarify the characteristics of this theoretical framework and provide concrete examples to which practitioners can easily relate. This review builds on previous literature by providing an overview of the hallmark features of complex systems and their relevance to RTS research and daily practice. An example of how characteristics of complex systems are exhibited is provided through a case of anterior cruciate ligament injury rehabilitation. Alternative forms of scientific inquiry, such as the use of computational and simulation-based techniques, are also discussed—to move the complex systems approach from the theoretical to the practical level.
The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.
Background Osteoarthritis (OA) is a chronic, progressive condition that can be effectively managed via conservative treatments including exercise, weight management and education. Offering these treatments contemporaneously and digitally may increase adherence and engagement due to the flexibility and cost-effectiveness of digital program delivery. The objective of this review was to summarise the characteristics of current digital self-management interventions for individuals with OA and synthesise adherence and attrition outcomes. Methods Electronic databases were searched for randomised controlled trials utilising digital self-management interventions in individuals with OA. Two reviewers independently screened the search results and extracted data relating to study characteristics, intervention characteristics, and adherence and dropout rates. Results Eleven studies were included in this review. Intervention length ranged from 6 weeks to 9 months. All interventions were designed for individuals with OA and mostwere multi-component and were constructed around physical activity. The reporting of intervention adherence varied greatly between studies and limited the ability to form conclusions regarding the impact of intervention characteristics. However, of the seven studies that quantified adherence, six reported adherence > 70%. Seven of the included studies reported attrition rates < 20%, with contact and support from researchers not appearing to influence adherence or attrition. Conclusions Holistic digital interventions designed for a targeted condition are a promising approach for promoting high adherence and reducing attrition. Future studies should explore how adherence of digital interventions compares to face-to-face interventions and determine potential influencers of adherence.
Background Martial arts training has shown positive impacts on balance and physiological measurements. Further investigation of the contents and feasibility of an effective therapeutic assessment of martial arts is needed in older adults, mainly for future applications and real-world implementation. Methods Sixteen older adults (8 male, 8 female, age 59–90 years), with or without chronic conditions, participated in a preliminary study using 5-weeks of karate training and a triple baseline control procedure. Group and single subject data analyses were conducted for dynamic balance, Timed Up and Go (TUG), hand grip, ankle plantarflexion force, and spinal cord excitability (via the soleus H-reflex) pre- and post-training. Results On average, participants completed a total of 2437 steps, 1762 turns, 3585 stance changes, 2047 punches, 2757 blocks, and 1253 strikes. Karate training improved dynamic balance performance such that the group average time was reduced (time to target (−13.6%, p = 0.020) and time to center (−8.3%, p = 0.010)). TUG was unchanged when considering the entire group ( p = 0.779), but six participants displayed significant changes. Left handgrip (7.9%, p = 0.037), and plantarflexion force in the right (28.8%, p = 0.045) and left leg (13.3%, p = 0.024) increased for the group. Spinal cord excitability remained unchanged in group data analysis but 5 individuals had modulated H max /M max ratios. Conclusion 5-weeks of karate training delivered in a fashion to mimic generally accessible community-level programs improved balance and strength in older adults. Whole-body movement embodied in karate training enhanced neuromuscular function and postural control. We met the overriding goal of this preliminary study to emphasize and assess feasibility and safety for the generalizability of martial arts interventions to real-world communities to impact health outcomes. Further quantitative work should explore threshold dose and development of martial arts training interventions as potential “exercise is medicine” functional fitness for older adults.
Return-to-sport (RTS) decisions are critical to clinical sports medicine and are often characterised by uncertainties, such as re-injury risk, time pressure induced by competition schedule and social stress from coaches, families and supporters. RTS decisions have implications not only for the health and performance of an athlete, but also the sports organisation. RTS decision-making is a complex process, which relies on evaluating multiple biopsychosocial factors, and is influenced by contextual factors. In this narrative review, we outline how RTS decision-making of clinicians could be evaluated from a decision analysis perspective. To begin with, the RTS decision could be explained as a sequence of steps, with a decision basis as the core component. We first elucidate the methodological considerations in gathering information from RTS tests. Second, we identify how decision-making frameworks have evolved and adapt decision-making theories to the RTS context. Third, we discuss the preferences and perspectives of the athlete, performance coach and manager. We conclude by proposing a framework for clinicians to improve the quality of RTS decisions and make recommendations for daily practice and research.
Background Patients use medical cannabis for a wide array of illnesses and symptoms, and many substitute cannabis for pharmaceuticals. This substitution often occurs without physician oversight, raising patient safety concerns. We aimed to characterize substitution and doctor-patient communication patterns in Canada, where there is a mature market and national regulatory system for medical cannabis. Methods We conducted an anonymous, cross-sectional online survey in May 2021 for seven days with adult Canadian federally-authorized medical cannabis patients ( N = 2697) registered with two global cannabis companies to evaluate patient perceptions of Primary Care Provider (PCP) knowledge of medical cannabis and communication regarding medical cannabis with PCPs, including PCP authorization of licensure and substitution of cannabis for other medications. Results Most participants (62.7%, n = 1390) obtained medical cannabis authorization from their PCP. Of those who spoke with their PCP about medical cannabis (82.2%, n = 2217), 38.6% ( n = 857) reported that their PCP had “very good” or “excellent” knowledge of medical cannabis and, on average, were moderately confident in their PCP’s ability to integrate medical cannabis into treatment. Participants generally reported higher ratings for secondary care providers, with 82.8% ( n = 808) of participants rating their secondary care provider’s knowledge about medical cannabis as “very good” or “excellent.” Overall, 47.1% ( n = 1269) of participants reported substituting cannabis for pharmaceuticals or other substances (e.g., alcohol, tobacco/nicotine). Of these, 31.3% ( n = 397) reported a delay in informing their PCP of up to 6 months or more, and 34.8% ( n = 441) reported that their PCP was still not aware of their substitution. Older, female participants had higher odds of disclosing cannabis substitution to their PCPs. Conclusion Most of the surveyed Canadian medical cannabis patients considered their PCPs knowledgeable about cannabis and were confident in their PCPs’ ability to integrate cannabis into treatment plans. However, many surveyed patients substituted cannabis for other medications without consulting their PCPs. These results suggest a lack of integration between mainstream healthcare and medical cannabis that may be improved through physician education and clinical experience.
Recent studies report doubling numbers of deaths due to dementia. With such an escalating mortality rate related to cognitive decline diseases, like dementia, timely information on contributing factors and knowledge discovery from evidence-based repositories is warranted. A large amount of scholarly knowledge extracted from research findings on dementia can be understood only using human intelligence for arriving at quality inferences. Due to the unstructured data presented in such a massive dataset of scientific articles available online, gaining insights from the knowledge hidden in the literature is complex and time-consuming. Hence, there is a need for developing a knowledge management model to create, query and maintain a knowledge repository of key elements and their relationships extracted from scholarly articles in a structured manner. In this paper, an innovative knowledge discovery computing model to process key findings from unstructured data from scholarly articles by using the design science research (DSR) methodology is proposed. The solution caters to a novel composition of the cognitive script of crucial knowledge related to dementia and its subsequent transformation from unstructured into a structured format using graph-based next-generation infrastructures. The computing model contains three phases to assist the research community to have a better understanding of the related knowledge in the existing unstructured research articles: (i) article collection and construction of cognitive script, (ii) generation of Cypher statements (a knowledge graph query language) and (iii) creation of graph-based repository and visualization. The performance of the computing model is demonstrated by visualizing the outcome of various search criteria in the form of nodes and their relationships. Our results also demonstrate the effectiveness of visual query and navigation highlighting its usability.
Adoption of IoT technology without considering its security implications may expose network systems to a variety of security breaches. In network systems, IoT edge devices are a major source of security risks. Implementing cryptographic algorithms on most IoT edge devices can be difficult due to their limited resources. As a result, compact implementations of these algorithms on these devices are required. Because the field multiplication operation is at the heart of most cryptographic algorithms, its implementation will have a significant impact on the entire cryptographic algorithm implementation. As a result, in this paper, we propose a small hardware accelerator for performing field multiplication on edge devices. The hardware accelerator is primarily composed of a processor array with a regular structure and local interconnection among its processing elements. The main advantage of the proposed hardware structure is the ability to manage its area, delay, and consumed energy by choosing the appropriate word size l. We implemented the proposed structure using ASIC technology and the obtained results attain average savings in the area of 95.9%. Also, we obtained significant average savings in energy of 63.2%. The acquired results reveal that the offered hardware accelerator is appropriate for usage in resource-constrained IoT edge devices.
A set D of vertices of a graph G=(V,E) is irredundant if each non-isolated vertex of G[D] has a neighbour in V−D that is not adjacent to any other vertex in D. The upper irredundance number IR(G) is the largest cardinality of an irredundant set of G; an IR(G)-set is an irredundant set of cardinality IR(G). The IR-graph of G has the IR(G)-sets as vertex set, and sets D and D′ are adjacent if and only if D′ can be obtained from D by exchanging a single vertex of D for an adjacent vertex in D′. An IR-tree is an IR-graph that is a tree. We characterize IR-trees of diameter 3 by showing that these graphs are precisely the double stars S(2n,2n), i.e., trees obtained by joining the central vertices of two disjoint stars K1,2n.
This paper documents home Internet access, types of Internet access, connection speeds, and prices for basic home Internet in tribal areas of the United States. We find that the share of households with Internet access is 21 percentage points lower in tribal areas than in neighboring non-tribal areas. When compared to these non-tribal areas, download speeds, whether measured using fixed or mobile broadband networks, are approximately 75% slower in tribal areas, while the lowest price for basic Internet services in tribal areas is 11% higher. Regression techniques reveal that traditional cost factors such as terrain and population density fully explain the price gap but account for only a fraction of the tribal differences in Internet access and connection speeds. Income differences are strong predictors of Internet access but do not affect connection speeds. A sizable amount of the variation in the access and home connection gap between tribal and non-tribal is left unexplained. We conclude with a discussion of how federal broadband programs have penetrated Indian Country, how tribal-specific factors are related to the variation in Internet access within Indian Country, and the potential policy implications of our findings.
Background Health risks associated with drug use are concentrated amongst structurally vulnerable people who use illegal drugs (PWUD). We described how Canadian policy actors view structural vulnerability in relation to harm reduction and policymaking for illegal drugs, and what solutions they suggest to reduce structural vulnerability for PWUD. Methods The Canadian Harm Reduction Policy Project is a mixed-method, multiple case study. The qualitative component included 73 semi-structured interviews conducted with harm reduction policy actors across Canada's 13 provinces and territories between November 2016 and December 2017. Interviews explored perspectives on harm reduction and illegal drug policies and the conditions that facilitate or constrain policy change. Our sub-analysis utilized a two-step inductive analytic process. First, we identified transcript segments that discussed structural vulnerability or analogous terms. Second, we conducted latent content analysis on the identified excerpts to generate main findings. Results The central role of structural vulnerability (including poverty, unstable/lack of housing, racialization) in driving harm for PWUD was acknowledged by participants in all provinces and territories. Criminalization, in particular, was seen as a major contributor to structural vulnerability by justifying formal and informal sanctions against drug use and, by extension, PWUD. Many participants expressed that their personal understanding of harm reduction included addressing the structural conditions facing PWUD, yet identified that formal government harm reduction policies focused solely on drug use rather than structural factors. Participants identified several potential policy solutions to intervene on structural vulnerability including decriminalization, safer supply, and enacting policies encompassing all health and social sectors. Conclusions Structural vulnerability is salient within Canadian policy actors’ discourses; however, formal government policies are seen as falling short of addressing the structural conditions of PWUD. Decriminalization and safer supply have the potential to mitigate immediate structural vulnerability of PWUD while policies evolve to advance social, economic, and cultural equity.
Numerical simulations of thermo-solutal Marangoni convection in a floating half SiGe zone with radiation effects under zero gravity have been carried out. In this system, thermal and solutal Marangoni flows develop along the melt free surface either in the same direction or opposite directions depending on the directions of thermal and solutal gradients. In present model of a half SiGe zone, the ambient temperature is kept constant. Radiation due to heat loss and heat gain is considered as the dominant heat transfer mechanism from the ambience. Transition mode maps, based on concentration distribution with respect to Marangoni ratio (Rσ=MaC/MaT) and ambient temperature (Ta), have been developed to investigate the effect of radiation at unequal or equal (MaC, MaT) values. The maps reveal the main concentration structures and potential transitions at various Ta values. The opposite thermo-solutal Marangoni flows give rise to more complex structures than those of the same-direction flows. Both heat loss and heat gain may alter or destabilize the concentration distribution in the melt. However, to some extent, heat loss in the opposite-direction flow case provides a stabilizing effect on the azimuthal wave pattern at a lower or higher Rσ value.
Adolescence is a stage of development unique to the human life course, during which key social, physical, and cognitive milestones are reached. Nonetheless, both the experience of adolescence and the role(s) of adolescents in the past have received little scholarly attention. Here we combine a broad interpretative framework for adolescence among prehistoric hunter-gatherers with direct bioarchaeological (burial) data to examine the lives of teenagers in the European Mid-Upper Paleolithic or Gravettian (∼35–25,000 years ago). Comparisons of the burial practices of individuals of different age classes (infant, child, adolescent, adult), as well as between adolescents who died at different ages, reveal some patterns related to adolescence in these communities, including 1) fewer distinctions based on sex among adolescents compared to adults; 2) differences between the sexes in age-at-death within our ‘adolescent’ age class—with females disproportionally dying later—potentially indicating high risks associated with first pregnancy; 3) distinctions in grave goods and diet among adolescents of different ages-at-death which we tentatively interpret as providing an emic perspective on the beginning of adolescence as defined by Pleistocene hunter-gatherers. Nonetheless, our analysis supports long-standing models of a distinct, continent-wide European Mid-Upper Paleolithic funerary tradition, with the burial data expressing social cohesion, rather than social distinctions, between age classes.
In this paper, a novel asynchronous sliding mode-based learning control is proposed for a class of discrete-time semi-Markov jump systems, in which the probability density function of sojourn-time is dependent on two consecutive modes. The asynchronous switching characteristic is employed for the nonsynchronization between the controller and the jump modes. Based on the discrete-time semi-Markov kernel and multiple-Lyapunov functions, sufficient conditions are provided to guarantee the σ-error mean-square stability of the sliding mode dynamics. Furthermore, a recursive sliding mode learning controller is designed such that the sliding modes can be driven onto the designed sliding surface and the chattering caused by the asynchronous switching and mode jump can be effectively suppressed. Finally, numerical simulations on the continuous stirred tank reactor system are given to demonstrate the effectiveness and potential of the proposed techniques.
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