Search Results (13)

Background/Objectives: There exist several interconnected issues that hinder the development of family medicine in Commonwealth realms such as the United Kingdom, Canada, New Zealand, and Australia. These issues affect both the medical and nursing professions. Family physicians, in most countries including the United Kingdom, are not considered “specialists” and are called “general practitioners” instead. The term GP is an outdated and potentially demeaning term relegated to the early 20th century when they did not receive any more than a few rotations as staff grades before being allowed to run their own community clinic. Registered nurses often cover a minor and subaltern role when working as practice nurses in the UK. They are often replaced by cost-effective, licensed practical nurses in most other English-speaking countries. Nurse practitioners in the UK, though being de facto entirely equal to family physicians in countries like Canada, Australia, New Zealand, and most US states, do not hold a special registration status. Their training is not defined in specific legislation, and they do not function as alternatives to general practitioners in the sense that patient may register with them alone which is often the case in Canada or the USA. Family medicine is, therefore, generally left lacking leadership with members of the medical and nursing professions often struggling for “power” in a way that undermines the foundation of family medicine which is to serve the health needs of a large population ranging from children to seniors. Methods: The purpose of this paper is to describe a solution to management in a Family Medicine Clinic in Calgary, Alberta, Canada. Results: In this model, the physician-nurse team developed a highly trained role of Clinical Nurse Specialist which serves as an overall clinic manager. Conclusions: The implementation of the Clinical Nurse Specialist-led model in family medicine has improved clinic efficiency, patient access, and provider satisfaction. This approach demonstrates a viable framework for enhancing primary care management across Commonwealth realms. Full article

As potato is an important crop, potato disease detection and classification are of key significance in guaranteeing food security and enhancing agricultural production efficiency. Aiming at the problems of tiny spots, blurred disease edges, and susceptibility to noise interference during image acquisition and transmission in potato leaf diseases, we propose a CBSNet-based potato disease recognition method. Firstly, a convolution module called Channel Reconstruction Multi-Scale Convolution (CRMC) is designed to extract the upper and lower features by separating the channel features and applying a more optimized convolution to the upper and lower features, followed by a multi-scale convolution operation to capture the key changes more effectively. Secondly, a new attention mechanism, Spatial Triple Attention (STA), is developed, which first reconstructs the spatial dimensions of the input feature maps, then inputs the reconstructed three types of features into each of the three branches and carries out targeted processing according to the importance of the features, thereby improving the model performance. In addition, the Bat–Lion Algorithm (BLA) is introduced, which combines the Lion algorithm and the bat optimization algorithm and makes the optimization process more adaptive by using the bat algorithm to adjust the gradient direction during the updating process of the Lion algorithm. The BLA not only boosts the model’s ability to recognize potato disease features but also ensures training stability and enhances the model’s robustness in handling noisy images. Experimental results showed that CBSNet achieved an average Accuracy of 92.04% and a Precision of 91.58% on the self-built dataset. It effectively extracts subtle spots and blurry edges of potato leaf diseases, providing strong technical support for disease prevention and control in large-scale potato farming. Full article

This paper reports experimental results concerning the corrosion of 316L austenitic stainless steels produced by ball milling and spark plasma sintering in NaCl electrolyte. Specimens with grain sizes ranging from 0.3 µm to 3 µm, without crystallographic texture, were obtained and compared with a cast that is 110 µm in grain size and an annealed reference. The potentiodynamic experiments showed that the reduction in grain size leads to a degradation of the electrochemical passivation behavior. This detrimental effect can be overcome by appropriate passivation in a HNO₃ concentrated solution before consolidation. The Mott–Schottky measurements showed that the semiconducting properties of the passive layer do not vary significantly on the grain size, especially the donor density, which is responsible for the chemical passivation breakdown by chloride anions. The total electrical resistance of the layer, measured by impedance spectroscopy is always lower than the one of a cast and annealed 316L, but it slightly increases with a reduction in grain size in the ultrafine grain range. This is followed by a slight increase in the thickness of the oxide layer. The effect of chloride ions is very pronounced in terms of passivation breakdown if the powder is not passivated prior to sintering. This leads to the nucleation and growth of subsurface main pits and the formation of secondary satellite pits, especially for the smallest grain sizes. Passivation of the 316L powder before sintering has been found to be an effective way to prevent this phenomenon. Full article

This research aims to investigate how customer relationship management capabilities (CRMCs) improve customer engagement and innovation performance. Customer engagement is also tested as a mediator between CRM capabilities and innovation performance. Furthermore, the distrust moderating role was studied towards the relationship between CRMCs and customer engagement. Data were collected from 491 owner/managers of SMEs working in Saudi Arabia. The findings revealed that CRMCs positively predict customer engagement and innovation performance. Customer engagement directly affects innovation performance and acts as a mediator as well. In addition, the findings proved that distrust moderates on the link between CRMCs and customer engagement. This research adds to the marketing management theory and practices and highlighted the role of CRMCs in achieving innovation performance. It explored, considering the data base collected from SME owners and managers, the mechanism of innovation performance achievement through CRMCs and customer engagement. CRMC improvements allow businesses to have sustainable development and a better integration in the market. Full article

Background: We aimed to propose the apical vertebras distribution modifier to supplement the coronal balance (CB) classification for adult idiopathic scoliosis (AdIS). An algorithm to predict postoperative coronal compensation and avoid postoperative coronal imbalance (CIB) was proposed. Methods: Patients were categorized into CB and CIB groups according to the preoperative coronal balance distance (CBD). The apical vertebras distribution modifier was defined as negative (−) if the centers of the apical vertebras (CoAVs) were on either side of the central sacral vertical line (CSVL) and positive (+) if the CoAVs were on the same side of the CSVL. Results: A total of 80 AdIS patients, with an average age of 25.97 ± 9.20 years, who underwent posterior spinal fusion (PSF) were prospectively recruited. The mean Cobb angle of the main curve was 107.25 ± 21.11 degrees at preoperation. The mean follow-up time was 3.76 ± 1.38 (2–8) years. At postoperation and follow-up, CIB occurred in 7 (70%) and 4 (40%) CB− patients, 23 (50%) and 13 (28.26%) CB+ patients, 6 (60%) and 6 (60%) CIB− patients, and 9 (64.29%) and 10 (71.43%) CIB+ patients. Health-related quality of life (HRQoL) was significantly better in the CIB− group compared with that of the CIB+ group in the dimension of back pain. To avoid postoperative CIB, the correction rate of the main curve (CRMC) should match the compensatory curve for CB−/+ patients; the CRMC should be greater than the compensatory curve for CIB− patients; and the CRMC should be less than the compensatory curve for CIB+ patients, and the inclination of the LIV needs to be reduced. Conclusions: CB+ patients have the least postoperative CIB rate and the best coronal compensatory ability. CIB+ patients are at a high risk of postoperative CIB and have the poorest coronal compensatory capacity in the event of postoperative CIB. The proposed surgical algorithm facilitates the handling of each type of coronal alignment. Full article

We present an analysis of the pseudorapidity $\eta$ and transverse momentum $p_T$ distributions of charged hadrons in $pp$ collisions for the kinematic range of $0<p_T<4$ GeV/c and $\left|\eta \right|<2.4$ at 0.9, 2.36, and 7 TeV. Charged particles are produced in $pp$ collision using several Monte Carlo event generators (Pythia Simple, Vincia, Dire showers, Sibyll2.3d, QGSJETII-04, EPOS-LHC) and compared with CMS data at LHC. It is observed that the Simple parton showers can explain the CMS data very well for $p_T>1$ GeV/c at 0.9 and 2.36 TeV within the experimental errors, while Dire overshoots and Vicia undershoots the data by 50% each. At 7 TeV, the Dire module presents a good prediction, whereas the Simple and Vincia modules underestimate the data within 30% and 50%. Comparing the Simple module of the Pythia model and the predictions of the CRMC models with the experimental data shows that at 0.9 TeV, EPOS-LHC has better results than the others. At 2.36 GeV, the cosmic rays Monte Carlo (CRMC) models have better prediction than the Simple module of Pythia at low $p_T$, while QGSJETII-04 predicts well at high $p_T$. QGSJETII-04 and EPOS-LHC have closer results than the Pythia-Simple and Sibyll2.3d at 7 TeV. In the case of the pseudorapidity distributions, only the Pythia-Simple reproduced the experimental measurements at all energies. The Dire module overestimates, while Vincia underestimates the data in decreasing order of discrepancy (20%, 12%, 5%) with energy. All CRMC models underestimate the data over the entire $\eta$ range at all energies by 20%. The angular ordering of partons and the parton fragmentation could be possible reasons for this deviation. Furthermore, we used the two-component standard distribution to fit the $p_T$ spectra to the experimental data and extracted the effective temperature ($T_{eff}$) and the multiplicity parameter ($N_0$). It is observed that $T_{eff}$ increases with the increase in the center of mass energy. The fit yielded $0.20368\pm 0.01$, $0.22348\pm 0.011$, and $0.24128\pm 0.012$ GeV for 0.9, 2.36, and 7 TeV, respectively. This shows that the system at higher energies freezes out earlier than lower ones because they quickly attain the equilibrium state. Full article

The current study evaluates the influence of the static compaction pressure applied during the casting process on Carbonated Reactive Magnesia Cement-based mortars. For this purpose, mortars, embodying biomass fly ash as filler, were designed and moulded through static compaction pressures of 10, 30, 50, and 70 MPa. The moulded specimens were submitted to an accelerated carbonation curing period of 24 h under controlled conditions. The devised mortars were evaluated through compressive strength tests, and their microstructure was assessed through Mercury Intrusion Porosimetry (MIP), Thermogravimetry and Derivative Thermogravimetry (TG-DTG), and Fourier-transform Infrared Spectroscopy (FTIR) analyses. The results showed that the increment in the static compaction pressure during the specimens’ casting process not only led the mortars to reduce their porosity by up to ~30% and increase their compressive strength by up to ~58% (from 19.8 MPa to 31.2 MPa) but also that such a change seems to hinder the CO₂ diffusion into the specimens’ core, thus resulting in a lower content of carbonated products. In addition, the MIP analyses demonstrated that the static compaction pressure applied in the mortar casting process changes the pores’ characteristics, while TG-DTG and FTIR analyses provided evidence that the devised mortars were carbonated to a certain degree. Therefore, this work demonstrated that Carbonated Reactive Magnesia Cement-based mortars are highly influenced by the static compaction pressure applied during the casting process, at least up to a certain value. Full article

(1) Pions produced in the development of extended atmospheric cosmic ray air showers subsequently decay to muons. The measured yield of those muons is generally underestimated by current phenomenological models and event generators optimized for cosmic ray physics. The importance of those disagreements motivates the feasibility studies for testing these models at the Large Hadron Collider (LHC) energies, at the highest center-of-mass energies achievable in a laboratory. The interaction of a nucleus and a virtual pion created in a charge exchange reaction at the LHC is a similar process to those contributing to the development of air showers in case of cosmic rays. The crucial problem of such an analysis is the selection of charge exchange events with the highest possible efficiency and high purity from proton–proton collisions at the LHC. (2) For this we consider distributions of various measurable quantities given by event generators commonly used in cosmic ray physics. (3) We examine the expected distributions of energy deposited in different calorimeters of an LHC experiment. We consider the geometrical acceptance and energy resolution of the detectors at the Compact Muon Solenoid (CMS) experiment, as an example. We determine a working point cut from the various options for event selection, and compare signal and background predictions using different models for a representative simple observable, such as average transverse momentum or charge particle yield. (4) A set of event selection cuts along these considerations is proposed, with the aim of achieving optimal efficiency and purity. Full article

Colvillea racemosa is a cultivated ornamental plant that is a monotypic genus of Fabaceae. It is native to Madagascar, with limited studies. For the first time, the leaf quality control parameters, the anti-hyperglycemic and anti-inflammatory in vitro activity of Colvillea racemosa ethanol extract (CRE) and its fractions of petroleum ether (CRP), methylene chloride (CRMC), ethyl acetate (CREA), n-butanol (CRB), and methanol (CRME) were evaluated. It exhibited significant inhibition against α-amylase, α-glucosidase and membrane stabilization. CRB was the most active fraction, and in vivo studies revealed that oral treatment with CRB of STZ-induced diabetic rats efficiently lowered blood glucose by 67.78%, reduced serum nitric oxide and lipid peroxide levels by 41.23% and 38.45%, respectively, and increased the GSH level by 90.48%. In addition, compared with the diabetic group, there was a 52.2% decrease in serum VCAM, a 55.5% increase in paraoxonase, an improved lipid profile, and improved liver and kidney functions for a treated diabetic group with CRB. Metabolite profiling of CRB was determined by UPLC-ESI-QTOF-MS and tandem MS/MS. Twenty-three chromatographic peaks were identified, which were classified into phenolic compounds and amino acids. The characterized flavonoids were apigenin and luteolin derivatives. Full article

Mitral valve prolapse (MVP) was first described in the 1960s, and it is usually a benign condition. However, a subtype of patients are known to have a higher incidence of ventricular arrhythmias and sudden cardiac death, the so called “arrhythmic MVP.” In recent years, several studies have been published to identify the most important clinical features to distinguish the benign form from the potentially lethal one in order to personalize patient’s treatment and follow-up. In this review, we specifically focused on red flags for increased arrhythmic risk to whom the cardiologist must be aware of while performing a cardiovascular imaging evaluation in patients with MVP. Full article

The condition of joints in steel truss bridges is critical to railway operational safety. The available methods for the quantitative assessment of different types of joint damage are, however, very limited. This paper numerically investigates the feasibility of using a probabilistic neural network (PNN) and a finite element (FE) model updating technique to assess the condition of joints in steel truss bridges. A two-step identification procedure is developed to achieve damage localization and severity assessment. A series of FE models with single or multiple damages are simulated to generate the training and testing data samples and validate the effectiveness of the proposed approach. The influence of noise on the identification accuracy is also evaluated. The results show that the change rate of modal curvature (CRMC) can be used as a damage-sensitive input of the PNN and the accuracy of preliminary damage localization can exceed 90% when suitable training patterns are utilized. Damaged members can be localized in the correct substructure even with noise contamination. The FE model updating method used can effectively quantify the joint deterioration severity and is robust to noise. Full article

Many coastal communities in the US use base flood elevation (BFE) maps for the 100-year return period, specified on Federal Emergency Management Agency (FEMA) Flood Insurance Rate Maps (FIRMs), to design structures and infrastructure. The FIRMs are increasingly known to have serious problems in accurately specifying the risk coastal communities face, as most recently evidenced during hurricanes Harvey and Irma in 2017 and Florence and Michael in 2018. The FIRM BFE maps also do not include the impact of sea level rise, which clearly needs to be considered in the design of coastal structures over the next several decades given recent National Oceanic and Atmospheric Administration (NOAA) sea level rise (SLR) projections. Here, we generate alternative BFE maps (STORMTOOLS Design Elevation (SDE) maps) for coastal waters of Rhode Island (RI) using surge predictions from tropical and extratropical storms of the coupled surge-wave models from the US Army Corp of Engineers, North Atlantic Comprehensive Coast Study (NACCS). Wave predictions are based on application of a steady state, spectral wave model (STWAVE), while impacts of coastal erosion/accretion and changes of geomorphology are modeled using XBeach. The high-resolution application of XBeach to the southern RI shoreline has dramatically increased the ability to represent the details of dune erosion and overtopping and the associated development of surge channels and over-wash fans and the resulting landward impact on inundation and waves. All methods used were consistent with FEMA guidelines for the study area and used FEMA-approved models. Maps were generated for 0, 2 ft (0.6 m), 5 ft (1.5 m), 7 ft (2.1 m), and 10 ft (3.1 m) of sea level rise, reflecting NOAA high estimates at various times for the study area through 2100. Results of the simulations are shown for both the southern RI shoreline (South Coast) and Narragansett Bay, to facilitate communication of projected BFEs to the general public. The maps are hosted on the STORMTOOLS ESRI Hub to facilitate access to the data. They are also now part of the RI Coastal Resources Management Council (CRMC) risk-based permitting system. The user interface allows access to all supporting data including grade elevation, inundation depth, and wave crest heights as well as corresponding FEMA FIRM BFEs and associated zones. Full article

STORMTOOLS Coastal Environmental Risk Index (CERI) predicts the coastal flooding damage to individual structures using coastal flooding levels, including the effects of sea level rise (SLR), provided in terms of the base flood elevation (BFE), specifications of the structure of interest (type and first floor elevation) and the associated damage functions from the U.S. Army Corp of Engineers (USACE), North Atlantic Coast Comprehensive Study (NACCS). CERI has been applied to selected coastal communities in Rhode Island, including those in Narragansett Bay and along the southern Rhode Island shoreline. Users can access the results of CERI via ArcGIS online at the CERI website. The objective of this effort was to develop, test, distribute, and evaluate a mobile phone application (App) that allows the user to assess the risk from coastal flooding and the associated damage at the individual structure level using the CERI methodology. The App is publicly available and has been developed for both iOS and Android operating systems. Environmental data to support the App, in terms of 100 y flood BFE maps, including the effects of SLR and the selected site grade elevation, are provided in the application by the URI Environmental Data Center (EDC). The user enters the location and type of the structure of interest (residential number of stories, with or without basement, pile supported or commercial building and the first-floor elevation (FFE)) and the desired SLR. The App then calculates the percent structural damage based on the specified environmental conditions and structure specifications. The App can be applied to any structure at any coastal location within the state. The CERI App development project has been guided by an Advisory Board made up of key constituents involved in coastal management and development in the state. The effort included extensive testing of the App by various user groups. The App structure makes it simple and straightforward to transfer to coastal and inland flooded areas in other locations, requiring only the specification of BFEs and grade elevations. Full article