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Background: As utilization of individual antenatal care (I-ANC) has increased throughout sub-Saharan Africa, questions have arisen about whether individual versus group-based care might yield better outcomes. We implemented a trial of group-based antenatal care (G-ANC) to determine its impact on birth preparedness and complication readiness (BPCR) among pregnant women in Ghana. Methods: We conducted a cluster randomized controlled trial comparing G-ANC to routine antenatal care in 14 health facilities in the Eastern Region of Ghana. We recruited women in their first trimester to participate in eight two-hour interactive group sessions throughout their pregnancies. Meetings were facilitated by midwives trained in G-ANC methods, and clinical assessments were conducted in addition to group discussions and activities. Data were collected at five timepoints, and results are presented comparing baseline (T0) to 34 weeks' gestation to 3 weeks post-delivery (T1) for danger sign recognition, an 11-point additive scale of BPCR, as well as individual items comprising the scale. Results: 1285 participants completed T0 and T1 assessments (N = 668 I-ANC, N = 617, G-ANC). At T1, G-ANC participants were able to identify significantly more pregnancy danger signs than I-ANC participants (mean increase from 1.8 to 3.4 in G-ANC vs. 1.7 to 2.2 in I-ANC, p < 0.0001). Overall BPCR scores were significantly greater in the G-ANC group than the I-ANC group. The elements of BPCR that showed the greatest increases included arranging for emergency transport (I-ANC increased from 1.5 to 11.5% vs. G-ANC increasing from 2 to 41% (p < 0.0001)) and saving money for transportation (19–32% in the I-ANC group vs. 19–73% in the G-ANC group (p < 0.0001)). Identifying someone to accompany the woman to the facility rose from 1 to 3% in the I-ANC group vs. 2–20% in the G-ANC group (p < 0.001). Conclusions: G-ANC significantly increased BPCR among women in rural Eastern Region of Ghana when compared to routine antenatal care. Given the success of this intervention, future efforts that prioritize the implementation of G-ANC are warranted. Trial registration: ClinicalTrials.gov Identifier: NCT04033003 (25/07/2019). Protocol available: Protocol Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9508671/. [ABSTRACT FROM AUTHOR]

This review focuses on the definitions, modalities, applications, and performance of various aspects of digital twins (DTs) in the context of transmission and industrial machinery. In this regard, the context around Industry 4.0 and even aspirations for Industry 5.0 are discussed. The many definitions and interpretations of DTs in this domain are first summarized. Subsequently, their adoption and performance levels for rotating and industrial machineries for manufacturing and lifetime performance are observed, along with the type of validations that are available. A significant focus on integrating fundamental operations of the system and scenarios over the lifetime, with sensors and advanced machine or deep learning, along with other statistical or data-driven methods are highlighted. This review summarizes how individual aspects around DTs are extremely helpful for lifetime design, manufacturing, or decision making even when a DT can remain incomplete or limited. [ABSTRACT FROM AUTHOR]

Background: Although the majority of Ghanaian women receive antenatal care (ANC), many exhibit low health literacy by misinterpreting and incorrectly operationalizing ANC messages, leading to poor maternal and newborn health outcomes. Prior research in low-resource settings has found group antenatal care (G-ANC) feasible for women and providers. This study aims to determine the effect of G-ANC on increasing maternal health literacy. We hypothesized that pregnant women randomized into G-ANC would exhibit a greater increase in maternal health literacy than women in routine, individual ANC. Methods: A 5-year cluster randomized controlled trial was conducted in 14 rural and peri-urban health facilities in the Eastern Region of Ghana. Facilities were paired based on patient volume and average gestational age at ANC enrollment and then randomized into intervention (G-ANC) vs. control (routine, individual ANC); 1761 pregnant women were recruited. Data collection occurred at baseline (T0) and post-birth (T2) using the Maternal Health Literacy scale, a 12-item composite scale to assess maternal health literacy. Logistic regression compared changes in health literacy from T0 to T2. Results: Overall, women in both the intervention and control groups improved their health literacy scores over time (p < 0.0001). Women in the intervention group scored significantly higher on 3 individual items and on overall composite scores (p < 0.0001) and were more likely to attend 8 or more ANC visits. Conclusion: While health literacy scores improved for all women attending ANC, women randomized into G-ANC exhibited greater improvement in overall health literacy post-birth compared to those receiving routine individual care. Life-saving information provided during ANC must be presented in an understandable format to prevent women and newborns from dying of preventable causes. Trial Registry: Ethical approval for the study was obtained from the Institutional Review Boards of the University of Michigan (HUM#00161464) and the Ghana Health Service (GHS-ERC: 016/04/19). [ABSTRACT FROM AUTHOR]

In this study, we introduce and investigate a new class of split inverse problems, comprising a multidimensional parameter of evolution, which we call the multidimensional split variational inequality problem with multiple output sets. To demonstrate its applicability, we formulate the equilibrium flow of multidimensional traffic network models for an arbitrary number of locations. We define a multidimensional split Wardrop condition with multiple output sets and establish its equivalence with the formulated equilibrium flow of multidimensional traffic network models. We then establish the existence and uniqueness of equilibria for our proposed model. In addition, we propose a method for solving the introduced problem. We then validate our results using some numerical experiments. [ABSTRACT FROM AUTHOR]

Our body is comprised of trillions of bacteria, virus, fungi etc. The term "microbiome" refers to them all together. In contrast to human health, some of the bacteria are linked to illnesses that are critical to the immune system, heart, and weight. In fact, most of the microbes in our intestines are found in a pocket of our large intestine called the caecum. They are referred to as a gut microbiome. In fact, there are more bacterial cells in our body that are human cells. Thereare roughly 40 trillion of bacterial cells in our body while the number of human cells are nearly 30 trillion. The gut microbiome refers to all of the microbes present in our intestine, which acts as another organ to live with microbes with millions of years. In the present review the the composition of gut microbiome and their function towards human health is discussed. Microbes have played a very important role in human body. From birth and throughout life, the gut microbiota influences the body by regulating the immune system, central nervous system, and other physiological processes as well as food digestion. The gut microbiota and its benefits for human health are the main topics of this review. [ABSTRACT FROM AUTHOR]

Microorganisms create biofilms, which are surface adherent community structures. These biofilms are essential to the infection process mediated by microbes. Antibiotic resistance is another thing that biofilm spreads, which is a big worry these days. Diverse bacteria use diverse mechanisms to create biofilms, and these mechanisms often depend on the environment in which they grow as well as strainspecific characteristics. Many chemical compounds are discovered to be useful in investigating the biofilm management method. The usefulness of nanoparticles in preventing biofilm-mediated disease is the subject of the current review. Using nanoscale particles to fight microbial biofilm is one possible way to treat these persistent diseases. Recently, antibacterial agents have been delivered employing innovative nanotechnology-based antimicrobial activity in order to destroy planktonic bacteria and their biofilm structures. In the sphere of medicine, this technique is now considered developing. Antimicrobial-loaded nanoparticles alone or in combination with other materials could increase the bacterial activity of nanomaterials to prevent the formation of biofilms. These particles are reactive substances that readily penetrate the matrix, serving as a barrier to numerous antibodies. One type of nanoparticle, called AgNPs, exhibited antibacterial action by rupturing the integrity of the bacterial cell membrane, which resulted in the release of cellular content and eventual death. Additionally, polymeric-based formulations like hydrogel, polymeric microspheres, nanospheres, and smart olimer, as well as lipid-based nanoparticles like liposomes and solid lipid nanoparticles, have been used in the biofilm treatment. Additionally, research is ongoing with various metals like copper, zinc, and their oxides. Here, we talked about the safety issues and the promise of metal oxide nanoparticles. The pathogens are effectively killed by NPs without endangering other cells or having any negative effects on living cells. [ABSTRACT FROM AUTHOR]

Background: Healthy Lifetime, a theoretically driven, personalized health coaching program delivered electronically, including face-to-face videoconferencing, was developed to intervene in early aging to stave off functional decline and minimize the onset/exacerbation of chronic conditions. Objective: To determine the efficacy of a theoretically driven, personalized health coaching program in participants 50 years and older with one or more chronic conditions using a randomized, controlled, pragmatic clinical trial methodology. Methods: Participants were randomly assigned to the HL (n = 59) or a usual care (n = 63) group. The HL group received health coaching from a trained nurse over eight weeks. Outcomes were measured at baseline, eight weeks, and 20 weeks (after the 12-week no-treatment phase). Regression modeling with fixed-effect repeated measures was used to account for the longitudinal data collection. Results: For the HL group, health habits increased at 8 weeks (3.1 units; SE = 1.0; p =.0005; effect size =.15). This difference was sustained at 20 weeks (2.4 units, SE = 0.2; p =.0005). Independent self-care agency improved at 8 weeks in individuals with high blood pressure (13.5 units; SE = 4.37; p =.0023; effect size =.3). However, that difference was not sustained at 20 weeks (p =.47). No significant improvements were shown in the usual care group at 8 weeks or 20 weeks. Conclusions: HL participants significantly improved their health habits at 8 weeks and sustained this improvement at week 20 (after a 12-week no-treatment phase) vs. the usual care group. Changing health habits alone has been shown to reduce all-cause morbidity and mortality in chronic disease. The high-functioning, community-dwelling older adults with chronic diseases we studied is an important target population for primary care practices to intervene early in aging to stave off the complications of chronic disease and functional decline. Trial registration: ClinicalTrials.gov (record NCT05070923, 07/10/2021). [ABSTRACT FROM AUTHOR]

There are a large number of time domain, frequency domain and time-frequency signal processing methods available for univariate feature extraction. However, there is no consensus in SHM on which feature, or feature sets, are best suited for the identification, localisation and prognosis of damage. This paper attempts to address this problem by providing a comprehensive benchmark of feature selection & reduction methods applied to an extensive set of univariate features. These univariate features are extracted using multiple statistical, temporal and spectral methods from the benchmark S101 and Z24 bridge datasets. These datasets contain labelled accelerometer recordings from full scale bridges as they are progressively subjected to multiple damage scenarios. To identify the minimal set of features that best distinguishes between the multiple damage states, a supervised machine learning approach is used in combination with multiple feature selection methods. The ability of these reduced feature sets to distinguish between damage states is benchmarked using the prediction performance of the classification models, with the training and test sets obtained through stratified k-fold cross validation. The results obtained show that reduced sets of univariate features, extracted from a single accelerometer sensor, are capable of accurately distinguishing between multiple classes of healthy and damaged states. This work provides a benchmark for SHM practitioners and researchers alike for the choice, comparison and validation of feature extraction and feature selection methods across a wide range of systems. [ABSTRACT FROM AUTHOR]

Peatlands store up to 2320 Mt of carbon (C) on only ~20% of the land area in Ireland; however, approximately 90% of this area has been drained and is emitting up to 10 Mt C per year. Gross primary productivity (GPP) is a one of the key components of the peatland carbon cycle, and detailed knowledge of the spatial and temporal extent of GPP under changing management practices is imperative to improve our predictions of peatland ecology and biogeochemistry. This research assesses the relationship between remote sensing and ground-based estimates of GPP for a near-natural peatland in Ireland using eddy covariance (EC) techniques and high-resolution Sen-tinel 2A satellite imagery. Hybrid models were developed using multiple linear regression along with six widely used conventional indices and a light use efficiency model. Estimates of GPP using NDVI, EVI, and NDWI2 hybrid models performed well using literature-based light use efficiency parameters and showed a significant correlation from 89 to 96% with EC-derived GPP. This study also reports additional site-specific light use efficiency parameters for dry and hydrologically normal years on the basis of light response curve methods (LRC). Overall, this research has demonstrated the potential of combining EC techniques with satellite-derived models to better understand and monitor key drivers and patterns of GPP for raised bog ecosystems under different climate scenarios and has also provided light use efficiency parameters values for dry and wetter conditions that can be used for the estimation of GPP using LUE models across various site and scales. [ABSTRACT FROM AUTHOR]

Background: The cornerstone of management of phyllodes tumor is surgery. No standard of care exists regarding adjuvant therapy; however, local recurrence is a predominant pattern of failure. The aims of this study were to evaluate the clinical characteristics and treatment patterns of phyllodes tumor and to compare local recurrence and disease-free survival rates of patients with borderline and malignant phyllodes tumor treated with or without adjuvant radiotherapy. Materials and Methods: We analyzed the demographic data, treatment details, and recurrence patterns of all patients with nonmetastatic phyllodes tumors of the breast (n = 34) treated with a multimodality approach who presented to our institute from January 2015 to December 2020. Results: The median age at presentation was 41.2 years, and the median tumor size was 12.5 cm. All patients underwent definitive surgical procedures in the form of wide local excision or mastectomy. No recurrence was noted in the patients with a benign histology. After a median follow-up period of 38 months, the local recurrence rate was 27% for the patients with borderline and malignant histology treated with adjuvant radiotherapy (n = 11) versus 47% for those (n = 17) who did not receive adjuvant radiotherapy. The 3-year local recurrence-free survival rate was 72% in the adjuvant radiotherapy group, versus 51% in the surgery only group. Conclusion: The results of the current study confirm the excellent prognosis of patients with benign phyllodes tumor undergoing surgery alone. Local recurrence was the predominant mode of failure in the patients with borderline and malignant histology. Locoregional control was improved with the addition of postoperative radiotherapy in the patients with borderline and malignant histology irrespective of margin status. [ABSTRACT FROM AUTHOR]

Many authors have reported the use of deep learning techniques to model wind power forecasts. For shorter-term prediction horizons, the training and deployment of such models is hindered by their computational cost. Neuromorphic computing provides a new paradigm to overcome this barrier through the development of devices suited for applications where latency and low-energy consumption play a key role, as is the case in real-time short-term wind power forecasting. The use of biologically inspired algorithms adapted to the architecture of neuromorphic devices, such as spiking neural networks, is essential to maximize their potential. In this paper, we propose a short-term wind power forecasting model based on spiking neural networks adapted to the computational abilities of Loihi, a neuromorphic device developed by Intel. A case study is presented with real wind power generation data from Ireland to evaluate the ability of the proposed approach, reaching a normalised mean absolute error of 2.84 percent for one-step-ahead wind power forecasts. The study illustrates the plausibility of the development of neuromorphic devices aligned with the specific demands of the wind energy sector. [ABSTRACT FROM AUTHOR]

This article reports the fluorometric detection of toxic hexavalent chromium Cr (VI)) in wastewater and Cr (VI) contaminated living cells using in-situ grown carbon quantum dots into the goethite (α-FeOOH) nano-matrix. The synthesized nano-hybrid shows enormous potential in determining the chromium contamination levels in various types of water samples. This selective fluorometric probe is enormously sensitive (LOD 81 nM) toward hexavalent chromium, which makes it a dedicated chromium sensor. Moreover, the sensing mechanism has been assessed using Stern–Volmer's equation and fluorescence lifetime experiments showing the simultaneous occurrence of photoinduced electron transfer and the inner filter effect. This chromium sensor has also been employed to assess the contamination level in real-life industrial wastewater. The performance of this probe in a real-life wastewater sample is quite commendable. Further, this biocompatible fluorometric probe has been used to demonstrate the in-vitro sensing of Cr (VI) in HeLa cells. The rapid detection mechanism of hexavalent chromium in living cells has been validated using theoretical docking simulations. Henceforth, this fluorometric sensor material could open new avenues not only in wastewater monitoring but also in biomedical applications. [ABSTRACT FROM AUTHOR]

Methane (CH4), a potent greenhouse gas, traps heat in the atmosphere and significantly contributes to global warming. Atmospheric CH4 comes from various natural and anthropogenic sources. CH4 emissions from the decomposition of organic material by bacteria in natural wetlands, other land types, agriculture, and waste management constitute the major component of global emissions. Although there is no clear evidence that CH4 emissions from wetlands and other natural sources have increased substantially in the last decade, uncertainties remain regarding sources and their spatial extent causing discrepancies between emission estimates from inventories/models and estimates inferred by an ensemble of atmospheric inversions. Here we show that satellite-based CH4 total column measurements along with surface albedo from Sentinel-5 Precursor (S-5p) show unique sensitivity to certain land types. Consequently, the areal extent of six land types (marsh, swamp, forest, grassland, cropland, and barren-land) could be identified with high overall accuracy by analysing S-5p data over Canada utilising our classification-segmentation algorithm. Monthly and yearly inventory maps were created, which can be used to validate or complement global models where data from other sources are missing and may help in further constraining the methane budget. [ABSTRACT FROM AUTHOR]

Recently, the structural information about non-coking and coking coal has attracted pronounced interest for sustainable utilization of poor coking coal in different industries specifically for steel industry like Tata Steel. In the present work, demineralization techniques via acid treatment (HCl-HF) are effective to remove mineral phase from coal. The difference in carbon chemistry of non-coking (CDPCI), weakly coking (Curragh SS), and prime coking coals (Illawarra and Jamadoba) has been studying through advanced characterization methods like petrography, TGA-DTG, FTIR spectroscopy, X-ray diffraction, Raman, 13C solid-state NMR, FESEM, and TEM. These advanced characterization techniques offer comparative structural information of different coal through the distribution of individual coal maceral and mineral grains with their rank (petrographic study), functional group study along aliphatic-aromatic structural relationship measurement (FTIR), crystalline/graphitic nature of carbon (XRD & Raman) with oxygenated carbon skeletal structural information (Solid State 13C NMR), aromatic-aliphatic cross-linking behavior (FESEM) and their orientation toward lattice fringe structure (TEM). [ABSTRACT FROM AUTHOR]

The properties of rotating neutron stars are investigated using eight equations of state (EOSs). We also study the relations between various observables corresponding to different angular velocities for all those EOSs. All of these EoSs lead to non-rotating compact stars with maximum masses between 1.8 to 2.25 M ⊙ . We calculate the moment of inertia and studied its variation with mass and the relation between central energy density and angular momentum. We compare our results with the observational findings from the most massive pulsar PSR J0740+6620 and the heaviest secondary component in the black hole—neutron star merger GW190814. It is noted that the secondary compact object of GW190814 having mass ∼ 2.6 M ⊙ might be explained as a rapidly rotating neutron star (NS) with frequency larger than 1000 Hz. [ABSTRACT FROM AUTHOR]

Purpose: We describe the development and the psychometric properties of an instrument to assess self-perceived EOL care competencies for healthcare professionals: The End-of-Life Care Questionnaire (EOL-Q). Methods: The EOL-Q consists of 28 questions assessing knowledge, attitudes and behaviors with subscale items addressing seven domains of care: decision-making, communication, continuity of care, emotional support for patients/families, symptom management, spiritual support for patients/families, and support for clinicians. The EOL-Q was used to assess competencies of 1,197 healthcare professionals from multiple work units at a large medical center. Cronbach's alpha coefficients were calculated for the survey and subscales. A factor analysis was also conducted. Results: Internal consistency reliability was for was high for the total scale (0.93) and for the subscales addressing knowledge, behaviors, decision-making, communication, emotional support and symptom management (0.84-0.92); and moderate (>0.68) for the attitudes and continuity of care subscales. The factor analysis demonstrated robust consolidation of the communication and continuity of care subscales (eigenvalue 9.47), decision-making subscale (eigenvalue 3.38), symptom management subscale (eigenvalue 1.51), and emotional and spiritual support subscales (eigenvalue 1.13). Conclusion: Analysis of the psychometric properties of the EOL-Q care across settings supports its reliability and validity as a measure of self-perceived EOL care competencies in the domains of communication and continuity of care, decision-making, symptom management, and emotional and spiritual support. The EOL-Q displays promise as a tool for use in a variety of educational, research, and program development initiatives in EOL care. [ABSTRACT FROM AUTHOR]

Structural damage in a bridge is defined as a significant deviation in the structural response from its standard operating conditions, not explainable by variations in external environmental and operational effects. However, environmental effects such as temperature fluctuations can cause significant seasonal variations in the structural response of a bridge and can mask its changes due to structural damage. This poses a challenge for structural health monitoring of bridges where reliable diagnosis of damage or deterioration is often related to isolation of the responses. To address it, a statistical damage-detection methodology is introduced where strain data are modelled using a dynamic harmonic regression time-series model. Prediction intervals of multi-step ahead forecasts from the dynamic harmonic regression model are then used as statistical control limits within which the observed phenomenon should fall under standard operating conditions. This single recursive structural health monitoring framework for automatic fitting and multi-step ahead forecasting of 1-min interval time-series strain data includes recorded temperature values and diurnal trends as regressors in the model to account for environmental variations. The potential of this method as a robust automatic structural health monitoring strategy is demonstrated on strain data sampled at 1-min interval from a full-scale damaged pre-stressed concrete bridge – before, during and after repair. The proposed method can capture both sudden and daily changes in structural response due to temperature effects, and a rolling multi-step ahead interval forecast was able to identify damage on back-cast data transitioning from a healthy state to a damaged state. [ABSTRACT FROM AUTHOR]

A 28‐year hydrological record on four intermittent wetlands (turloughs) in a hydraulically linked karst area in the west of Ireland was used to assess ecohydrological metrics for different vegetation communities. A methodology using a combination of continuous water level monitoring and high resolution topographic surveying was used to develop a detailed hydrological model of the karst network, from which water levels at any point within the turloughs can be defined at any time during the 28‐year period (1989 to 2017). The flood conditions experienced across the spatial distributions for different vegetation communities (as mapped by a field survey) have then been collated and presented as statistical distributions for flood duration, flood depth, flood frequency and mean temperature/global radiation at the time of year in spring when the flood waters start to recede. Analysis of these four turloughs has revealed distinct differences between vegetation communities, from Eleocharis acicularis communities at the turlough base typically experiencing 6 to 7 months of inundation per year compared to the limestone pavement community at the top fringes of the turloughs only flooded from 1 to 2 months per year. An approach that used Sentinel‐2 satellite data to provide an assessment of whether there have been changes in the spatial distribution of the communities is also presented. Such metrics can be evaluated alongside other variables such as water quality (particularly nutrients), soil type and land‐use, in order to understand the habitat requirements for such plant communities and their associated ecological systems. [ABSTRACT FROM AUTHOR]

There has been a recent surge of research interest in quantifying the health and environmental impacts of increased cycling in urban environments. Although there is general agreement that the benefits of increased cycling outweigh the risks, most of the methodologies developed have had limited value for evaluating real-world transport policies. This is because they are based on hypothetical scenarios where increased cycling takes place but give no consideration to the courses of action which may help policymakers to achieve the scenarios. A useful extension to these methodologies would be one which allowed a user to find the optimal infrastructure design and/or policies which would maximize total societal benefit, taking into account the health and environmental impacts of cycling. In this study, a Network Design Problem is formulated for systematically designing cycling network layouts in order to maximize the net benefits to the network users and society. The problem is formulated as a mathematical program with equilibrium constraints (MPEC) and a solution approach based on a genetic algorithm (GA) is provided to solve the problem. The problem formulation and solution algorithm are tested using a numerical example. The GA algorithm was shown to efficiently converge to an optimal or near-optimal solution for the cycle network design. The proposed optimization framework may be adopted by transport authorities and/or urban planners as a decision support tool to help them to systematically identify the best design for a cycle network which balances the benefits and risks to all stakeholders. [ABSTRACT FROM AUTHOR]

In this paper, we have considered a two-fluid model assuming that the pulsars are made of ordinary matter admixed with dark matter. Contribution of dark matter comes from the fitting of the rotation curves of the SPARC sample of galaxies (de León in Gen Relativ Gravit 25:1123, 1993). For this, we have investigated the dark matter based on the singular isothermal sphere (SIS) dark matter density profile in the galactic halo region. Considering this two-fluid model, we have studied the physical features of the pulsars present in different galaxy in details. Here, we compute the probable radii, compactness (u) and surface red-shift ( Z s ) of the four pulsars namely : PSR J1748-2021B in NGC 6440B galaxy, PSR J1911-5958A in NGC 6752 galaxy, PSR B1802-07 in NGC 6539 galaxy and PSR J1750-37A in NGC 6441 galaxy. [ABSTRACT FROM AUTHOR]

Background: The Institute of Medicine identifies that quality palliative/end-of-life (EOL) care should be provided to patients with serious, life-limiting illnesses and their families by competently prepared health professionals. Purpose: This study assessed perceived concerns of health professionals pertaining to the delivery of palliative/EOL care in the hospital setting. The specific aim was to determine thematic concerns in the delivery of palliative/EOL care which emerged from respondents' impressions of a memorable palliative/EOL patient experience. Methods: Interdisciplinary health professionals at a large academic health system in the Midwest were surveyed to reflect upon a memorable palliative/EOL life care patient situation (positive or negative). A Thematic Analysis approach was used to code qualitative responses to 4 open-ended questions and then extract themes and subthemes from the coded data. Results: Concerns identified by participants (N = 425) emerged around 7 themes including communication (97%), decision-making/care planning (75%), education needs (60%), EOL care (48%), ethics (24%), satisfaction with care (9%), and spiritual/cultural sensitivity (6%). Conclusion: Challenges exist in the delivery of quality palliative/EOL care in the hospital setting which may be addressed through educational initiatives that focus on recognition of cultural influences on care preferences, improving communication between patients/families and providers, education about the differences between palliative and EOL care, and increased competency of health providers in having EOL/goals-of-care discussions. Health professionals must recognize the benefit of collaborative palliative care in order to meet patient and family needs holistically and comprehensively. [ABSTRACT FROM AUTHOR]

Cycling as a mode of transport avoids the negative external costs of driving such as air pollution, carbon dioxide emissions and noise and can also reduce the public health costs associated with physical inactivity. However, increased cycling may also have disadvantages such as increased exposure to air pollution and risk of traffic collisions. A number of studies have developed methods to quantify these health and environmental impacts and have shown that the overall impact of increased cycling is positive. However, while minimising travel costs is traditionally the main objective of transport planners, these studies have not included travel cost impacts in their analyses. In this study, the impacts of a modal shift towards cycling are quantified, taking into account health, environmental and travel cost impacts. It was found that the health and environmental impacts of increased cycling in Dublin, Ireland, would be strongly positive, mainly due to the health benefits of physical activity. When travel costs are also included in the analysis, the central estimate of net impact remains positive but the uncertainty increases considerably. This underscores the importance of the transport and health sectors working together to maximise the social welfare resulting from transport projects. [ABSTRACT FROM AUTHOR]

Background: In the United States, most deaths occur in hospitals, with approximately 25% of hospitalized patients having palliative care needs. Therefore, the provision of good end-of-life (EOL) care to these patients is a priority. However, research assessing staff preparedness for the provision of EOL care to hospitalized patients is lacking. Objective: To assess health-care professionals’ self-perceived competencies regarding the provision of EOL care in hospitalized patients. Methods: Descriptive study of self-perceived EOL care competencies among health-care professionals. The study instrument (End-of-Life Questionnaire) contains 28 questions assessing knowledge, attitudes, and behaviors related to the provision of EOL care. Health-care professionals (nursing, medicine, social work, psychology, physical, occupational and respiratory therapist, and spiritual care) at a large academic medical center participated in the study. Means were calculated for each item, and comparisons of mean scores were conducted via t tests. Analysis of variance was used to identify differences among groups. Results: A total of 1197 questionnaires was completed. The greatest self-perceived competency was in providing emotional support for patients/families, and the least self-perceived competency was in providing continuity of care. When compared to nurses, physicians had higher scores on EOL care attitudes, behaviors, and communication. Physicians and nurses had higher scores on most subscales than other health-care providers. Conclusions: Differences in self-perceived EOL care competencies were identified among disciplines, particularly between physicians and nurses. The results provide evidence for assessing health-care providers to identify their specific training needs before implementing educational programs on EOL care. [ABSTRACT FROM AUTHOR]

Abstract: Underwater inspections stand to gain from using stereo imaging systems to collect three‐dimensional measurements. Although many stereo‐matching algorithms have been devised to solve the correspondence problem, that is, find the same points in multiple images, these algorithms often perform poorly when applied to images of underwater scenes due to the poor visibility and the complex underwater light field. This article presents a new stereo‐matching algorithm, called PaLPaBEL (Pyramidal Loopy Propagated BELief) that is designed to operate on challenging imagery. At its core, PaLPaBEL is a semiglobal method based on a loopy belief propagation message passing algorithm applied on a Markov random field. A pyramidal scheme is adopted that enables wide disparity ranges and high‐resolution images to be handled efficiently. For performance evaluation, PaLPaBEL is applied to underwater stereo images captured under various visibility conditions in a laboratory setting, and to synthetic imagery created in a virtual underwater environment. The technique is also demonstrated on stereo images obtained from a real‐world inspection. The successful results indicate that PaLPaBEL is well suited for underwater application and has value as a tool for the cost‐effective inspection of marine structures. [ABSTRACT FROM AUTHOR]

The transportation sector is the greatest contributor to air pollution. With the booming demand for transportation, reducing the pollution has become one of the main concerns of researchers. EPA emission standards are designed to protect air quality and human health. Diesel Euro 5 NOxhas become a matter of disquiet since it has been found that NOxemissions are significantly exceeding the standard limit. This paper presents a study to estimate the disparity in real-world NOxemission levels resulted from all diesel Euro 5 passenger cars (PC) and light commercial vehicles (LCV) that are present in Ireland. NOxemission levels calculated based on laboratory test results, on-road measurements and the COPERT 4 model were compared. Additionally, NOxemission levels from the defective Volkswagen models have been calculated to quantify the effect of the Volkswagen scandal on Ireland. Impacts of excess NOxemissions on health and cost have also been presented. [ABSTRACT FROM PUBLISHER]

Image processing-based methods, capable of detecting and quantifying cracks, surface defects or recovering 3D shape information are increasingly being recognised as a valuable tool for inspecting underwater structures. It is of great practical importance for inspectors to know the effectiveness of such techniques when applied in conditions. This paper considers an underwater environment characterised by poor visibility chiefly governed by the lighting and turbidity levels, along with a range of geometry and damage conditions of calibrated specimens. The paper addresses the relationship between underwater visibility and the performance of image-based methods through the development and calibration of a first open-source underwater lighting and turbidity image repository (ULTIR). ULTIR contains a large collection of images of submerged specimens that have been photographed under controlled lighting and turbidity levels featuring various forms of geometry and damage. ULTIR aims to facilitate inspectors when rationalising the use of image processing methods as part of an underwater inspection campaign and to enable researchers to efficiently evaluate the performance of image-based methods under realistic operating conditions. Stakeholders in underwater infrastructure can benefit through this first large, standardised, well-annotated, and freely available database of images and associated metadata. [ABSTRACT FROM AUTHOR]

Background: Educating nurses about palliative and end-of-life (EOL) care is a high priority in health care settings. The purpose of this study was to assess nurses' perceived competency regarding the provision of palliative and EOL care to hospitalized patients. Method: This study surveyed nurses from 25 pediatric and adult acute and intensive care units (ICU; N = 583) Quantitative data analysis was descriptive and correlational. Qualitative data analysis identified themes of participant concerns. Results: Data analysis revealed that perceived competency in palliative and EOL care is significantly higher in the ICU nurses (p < .0001). Mean scores were significantly higher when nurses had more than 10 years of experience (p < .0001). Open-ended responses indicated concerns regarding improved communication behaviors, decision making, and facilitation of continuity of care. Conclusion: The results provide guidance for development of palliative and EOL care nursing education programs tailored to address specific unit needs according to staff characteristics, patient population focus of care, and acuity level of care. [ABSTRACT FROM AUTHOR]

Daly's Bridge is a historic steel suspension footbridge in Ireland, known locally as the 'Shaky Bridge' for its noticeable movement under pedestrian loading. Although there is concern regarding the performance of the structure, testing or modelling has not been carried out to date and inadequate information exists in relation to carrying out such analyses. In this paper, Daly's Bridge is instrumented and tested for the first time and a model of the bridge is established and improved in the process. Apart from ambient vibration, excitation from traversing pedestrians and cyclists is considered. Video analysis of dynamic deflection, a wavelet-packet-based technique using acceleration responses and dynamic measurements from a cheap smartphone accelerometer application are used to identify and compare the natural frequency of the bridge. The work contributes to the evidence base of full-scale measurements from instrumenting and analysing responses of aging pedestrian bridges, highlighting the complexity, challenges, opportunities and limitations related to the varied levels of information available from disparate sources. The study also highlights the need to investigate to what extent cheap sensors can be successfully used as compared to their more expensive and sophisticated counterparts. [ABSTRACT FROM AUTHOR]

Multifocal osteosarcoma (MFOS), osteosarcoma involving multiple sites, is a rare variant of osteosarcoma. When the lesions appear within 6 months of initial presentation of the tumor, it is known as synchronous MFOS. Synchronous MFOS has an incidence of 1%-3% only. Moreover, the histological variant of small cell osteosarcoma is even rarer. A case of 14-year-old male with synchronous MFOS of small cell type involving frontal and mandibular bone simultaneously is being reported here. It poses a dilemma to both the clinician and the pathologist to diagnose whether it represents multiple primary tumor or metastatic disease. [ABSTRACT FROM AUTHOR]

Several chemotherapeutic agents applied to human beings for past few decades for different ailments, have been found to possess potent antitubercular activity. Two such agents, methdilazine (Md) and promethazine (Pz) were used to select mycobacterial mutants resistant to themselves at different levels and tested to determine if such mutants simultaneously developed cross-resistance to known antitubercular drugs. Mutants were produced by application of a heavy inoculum on Lowenstein-Jensen medium containing Md (or Pz) at concentrations higher than their respective minimum inhibitory concentrations (MICs). These were then tested to find out if such mutants have changed their resistogramme pattern with respect to the test antitubercular agents. Certain first-step Md-mutants became simultaneously resistant to ethambutol and pyrazinamide; while the step-2 Md-mutants revealed further increase in resistance to these agents along with resistance to isoniazid, rifampicin and streptomycin as well. In the study with Pz it was noted that many mutants showed distinctly higher levels of resistance to all the test drugs, particularly to isoniazid, pyrazinamide and streptomycin. The levels of MIC were distinctly high in many mutants. These observations on cross-resistances seem to be best explained on the basis of a reduction in cell-membrane permeability acting in a non-specific manner. The role of such a cross-resistance may possibly be accounting for an overall increase in the MICs of many drugs against several groups of microorganisms including Mycobacterium tuberculosis and other species of Mycobacterium during the last five decades. [ABSTRACT FROM AUTHOR]

The process of Nuclei detection in high-grade breast cancer images is quite challenging in the case of image processing techniques due to certain heterogeneous characteristics of cancer nuclei such as enlarged and irregularly shaped nuclei, highly coarse chromatin marginalized to the nuclei periphery and visible nucleoli. Recent reviews state that existing techniques show appreciable segmentation accuracy on breast histopathology images whose nuclei are dispersed and regular in texture and shape; however, typical cancer nuclei are often clustered and have irregular texture and shape properties. This paper proposes a novel segmentation algorithm for detecting individual nuclei from Hematoxylin and Eosin (H&E) stained breast histopathology images. This detection framework estimates a nuclei saliency map using tensor voting followed by boundary extraction of the nuclei on the saliency map using a Loopy Back Propagation (LBP) algorithm on a Markov Random Field (MRF). The method was tested on both whole-slide images and frames of breast cancer histopathology images. Experimental results demonstrate high segmentation performance with efficient precision, recall and dice-coefficient rates, upon testing high-grade breast cancer images containing several thousand nuclei. In addition to the optimal performance on the highly complex images presented in this paper, this method also gave appreciable results in comparison with two recently published methods—Wienert et al. (2012) and Veta et al. (2013), which were tested using their own datasets. [ABSTRACT FROM AUTHOR]

Several chemotherapeutic agents applied to human beings for past few decades for different ailments, have been found to possess potent antitubercular activity. Two such agents, methdilazine (Md) and promethazine (Pz) were used to select mycobacterial mutants resistant to themselves at different levels and tested to determine if such mutants simultaneously developed cross-resistance to known antitubercular drugs. Mutants were produced by application of a heavy inoculum on Lowenstein-Jensen medium containing Md (or Pz) at concentrations higher than their respective minimum inhibitory concentrations (MICs). These were then tested to find out if such mutants have changed their resistogramme pattern with respect to the test antitubercular agents. Certain first-step Md-mutants became simultaneously resistant to ethambutol and pyrazinamide; while the step-2 Md-mutants revealed further increase in resistance to these agents along with resistance to isoniazid, rifampicin and streptomycin as well. In the study with Pz it was noted that many mutants showed distinctly higher levels of resistance to all the test drugs, particularly to isoniazid, pyrazinamide and streptomycin. The levels of MIC were distinctly high in many mutants. These observations on cross-resistances seem to be best explained on the basis of a reduction in cell-membrane permeability acting in a non-specific manner. The role of such a cross-resistance may possibly be accounting for an overall increase in the MICs of many drugs against several groups of microorganisms including Mycobacterium tuberculosis and other species of Mycobacterium during the last five decades. [ABSTRACT FROM AUTHOR]

Background: Free radicals are known to cause severe damage to most of the biomolecules in the human system and are responsible for various illnesses including neurodegenerative, cardiovascular and autoimmune disorders. Antioxidants can reduce effects of free radicals and are given to patients suffering from such diseases. There are certain natural antioxidants like flavonoids which possess free radical scavenging activities. The flavonoid quercetin is one such compound among naturally occurring antioxidants. The present study has been designed to determine the antioxidant activity in the synthetic antidepressant drug imipramine which is structurally similar to quercetin. Method: Specific standard procedures like ferric ion reducing capacity by FRAP assay, phosphomolybdenum assay and cupric ion reducing (CUPRAC) assay were carried out keeping ascorbic acid as the known standard. Results: Ferric ion reducing property of imipramine by FRAP assay revealed that reducing power of imipramine augmented with increasing amounts of the drug. In the phosphomolybdenum assay antioxidant capacity of imipramine increased in a dose dependent manner. In both these studies imipramine showed greater antioxidant action than ascorbic acid. In CUPRAC assay as the amount of imipramine was increased there was a definite elevation in antioxidant activity; however, it was comparatively less active than ascorbic acid. Conclusion: The highly potent antioxidant property in the antidepressant synthetic compound imipramine may be recognized by physicians involved in treatment of psychosis since patients receiving this drug regularly will certainly be in an advantageous position. The parent structure of imipramine can be modified further to potentiate antioxidant property of the drug. [ABSTRACT FROM AUTHOR]

Roadside safety barriers designs are tested with passenger cars in Europe using standard EN1317 in which the impact angle for normal, high and very high containment level tests is 20°. In comparison to EN1317, the US standard MASH has higher impact angles for cars and pickups (25°) and different vehicle masses. Studies in Europe (RISER) and the US have shown values for the 90th percentile impact angle of 30°–34°. Thus, the limited evidence available suggests that the 20° angle applied in EN 1317 may be too low. The first goal of this paper is to use the US NCHRP database (Project NCHRP 17–22) to assess the distribution of impact angle and collision speed in recent ROR accidents. Second, based on the findings of the statistical analysis and on analysis of impact angles and speeds in the literature, an LS-DYNA finite element analysis was carried out to evaluate the normal containment level of concrete barriers in non-standard collisions. The FE model was validated against a crash test of a portable concrete barrier carried out at the UK Transport Research Laboratory (TRL). The accident data analysis for run-off road accidents indicates that a substantial proportion of accidents have an impact angle in excess of 20°. The baseline LS-DYNA model showed good comparison with experimental acceleration severity index (ASI) data and the parametric analysis indicates a very significant influence of impact angle on ASI. Accordingly, a review of European run-off road accidents and the configuration of EN 1317 should be performed. [ABSTRACT FROM AUTHOR]

Lathyrus sativus L. (Grass pea) is the source for cheap and nutritious food choice in drought and famine susceptible zones in greater part of North India and Africa. The non-protein amino acid β-N-oxalyl-L-α,β-diaminopropionic acid (β-ODAP) has been known for decades for its potent neurotoxic effect, causing irreversible neurodegenerative disease “neurolathyrism”, present in both seed and leaf of Lathyrus sativus L. and other species in varying proportions. It is crucial to establish a rapid as well as reliable detection methodology for β-ODAP content in various Lathyrus plants. Currently available HPLC based methods involve multi-step derivatization of the sample. To overcome this, we have developed β-ODAP analysis method by HPLC without any prior derivatization. This method is statistically significant in the range of 2 to 100μg/ml and exhibited linear response with r2 > 0.99. Limit of detection and quantitation of the later method was determined to be 5.56 μg/ml and 16.86 μg/ml, respectively. In addition to this, a TLC based method has also been developed. The limit of detection of β-ODAP is 0.6μg and for its substrate, L-1,2-diaminopropionic acid is 5μg. Both HPLC and TLC methods were validated by conducting in-vitro bioconversion test to detect the presence of biocatalyst in plant extract. This method is economical, rapid and simple. [ABSTRACT FROM AUTHOR]

In the past several years, active travel (walking and cycling) has increasingly been recognized as an effective means of improving public health by increasing physical activity and by avoiding the negative externalities of motorized transport. The impacts of increased active travel on mortality and morbidity rates have been quantified through a range of methodologies. In this study, the existing publications in this field of research have been reviewed to compare and contrast the methodologies adapted and to identify the key considerations and the best practices. The publications were classified in terms of the health summary outcomes and exposure variables considered, the model structures used in the studies and the impact of these choices on the results. Increased physical activity was identified as the most important determinant of the health impacts of active travel but different ways of quantifying these health impacts can lead to substantial differences in the scale of the impact. Further research is required into the relationship between increased physical activity and health effects in order to reach consensus on the most reliable modelling approach for this important determinant of benefits. Critical discussions on other exposure variables have also been provided to ascertain best practices. Additionally, a logical flow of the modelling processes (and their variations) has also been illustrated which can be followed for developing future studies into the health impacts of active travel. [ABSTRACT FROM AUTHOR]

This paper evaluates the potential of gabions as roadside safety barriers. Gabions have the capacity to blend into natural landscape, suggesting that they could be used as a safety barrier for low-volume road in scenic environments. In fact, gabions have already been used for this purpose in Nepal, but the impact response was not evaluated. This paper reports on numerical and experimental investigations performed on a new gabion barrier prototype. To assess the potential use as a roadside barrier, the optimal gabion unit size and mass were investigated using multibody analysis and four sets of 1:4 scaled crash tests were carried out to study the local vehicle–barrier interaction. The barrier prototype was then finalised and subjected to a TB31 crash test according to the European EN1317 standard for N1 safety barriers. The test resulted in a failure due to the rollover of the vehicle and tearing of the gabion mesh yielding a large working width. It was found that although the system potentially has the necessary mass to contain a vehicle, the barrier front face does not have the necessary stiffness and strength to contain the gabion stone filling and hence redirect the vehicle. In the EN1317 test, the gabion barrier acted as a ramp for the impacting vehicle, causing rollover. [ABSTRACT FROM PUBLISHER]

Non-recurrent congestion or incidents are detrimental to the operability and efficiency of busy urban transport networks. There exist multiple automatic incident detection algorithms (AIDAs) to remotely detect the occurrence of an incident in highway or freeway scenarios; however, very little research has been performed to automatically detect incidents in signalized urban arterials. This limited research attention has mostly been focused on developing new urban arterial specific algorithms, rather than identifying alternative methods to synthesize existing freeway-based algorithms for urban conditions. The main hindrance to such synthesis is that the traffic patterns on the signalized urban arterials are significantly different from the same on highways/freeways due to the presence of traffic intersections. This article introduces a new strategy of customizing the existing AIDAs (freeway based or otherwise) to significantly improve their adaptability to signalized urban arterial transport networks. The new strategy focuses on preprocessing the traffic information before being used as input to a freeway/highway-based AIDA to lessen the effect of traffic signals and to imitate the input patterns in highway/freeway-based incident conditions. The effectiveness of this new strategy has been established with the help of four existing AIDAs. The proposed strategy is a simple solution to implement existing algorithms to signalized urban networks without any further instrumentation or operational cost. [ABSTRACT FROM AUTHOR]

Imaging-based damage detection techniques are increasingly being utilized alongside traditional visual inspection methods to provide owners/operators of infrastructure with an efficient source of quantitative information for ensuring their continued safe and economic operation. However, there exists scope for significant development of improved damage detection algorithms that can characterize features of interest in challenging scenes with credibility. This article presents a new regionally enhanced multiphase segmentation (REMPS) technique that is designed to detect a broad range of damage forms on the surface of civil infrastructure. The technique is successfully applied to a corroding infrastructure component in a harbour facility. REMPS integrates spatial and pixel relationships to identify, classify, and quantify the area of damaged regions to a high degree of accuracy. The image of interest is preprocessed through a contrast enhancement and color reduction scheme. Features in the image are then identified using a Sobel edge detector, followed by subsequent classification using a clustering-based filtering technique. Finally, support vector machines are used to classify pixels which are locally supplemented onto damaged regions to improve their size and shape characteristics. The performance of REMPS in different color spaces is investigated for best detection on the basis of receiver operating characteristics curves. The superiority of REMPS over existing segmentation approaches is demonstrated, in particular when considering high dynamic range imagery. It is shown that REMPS easily extends beyond the application presented and may be considered an effective and versatile standalone segmentation technique. [ABSTRACT FROM AUTHOR]

In this article the multibody simulation software package MADYMO for analysing and optimizing occupant safety design was used to model crash tests for Normal Containment barriers in accordance with EN 1317. The verification process was carried out by simulating a TB31 and a TB32 crash test performed on vertical portable concrete barriers and by comparing the numerical results to those obtained experimentally. The same modelling approach was applied to both tests to evaluate the predictive capacity of the modelling at two different impact speeds. A sensitivity analysis of the vehicle stiffness was also carried out. The capacity to predict all of the principal EN1317 criteria was assessed for the first time: the acceleration severity index, the theoretical head impact velocity, the barrier working width and the vehicle exit box. Results showed a maximum error of 6% for the acceleration severity index and 21% for theoretical head impact velocity for the numerical simulation in comparison to the recorded data. The exit box position was predicted with a maximum error of 4°. For the working width, a large percentage difference was observed for test TB31 due to the small absolute value of the barrier deflection but the results were well within the limit value from the standard for both tests. The sensitivity analysis showed the robustness of the modelling with respect to contact stiffness increase of ±20% and ±40%. This is the first multibody model of portable concrete barriers that can reproduce not only the acceleration severity index but all the test criteria of EN 1317 and is therefore a valuable tool for new product development and for injury biomechanics research. [ABSTRACT FROM PUBLISHER]

Gabions are stone-filled wire containers which are frequently used as retaining walls. However, due to their high mass, relatively low cost and visual appeal, a row of single gabion blocks, joined at the ends, has the potential to be used as a roadside impact absorption device where traditional steel or concrete devices may not be suitable. To evaluate such application, the shear and bending deformation of gabions under vehicle impact need to be investigated. In this paper, the shear response of a single gabion block is analytically modelled and a gabion beam multibody model is developed using a discretisation method to capture the deformability of the gabion structure. The material properties of the gabion beam are adopted from experimental values available in the literature and the modelling is statically validated over athree-point bending testand adistributed loading test. The results show that the discretised multibody modelling can be effectively used to describe the static deformation behaviour of gabion blocks. [ABSTRACT FROM AUTHOR]

Climate change is a prevalent issue facing the world today. Unexpected increase in rainfall intensity and events is one of the major signatures of climate change. Rainfall influences traffic conditions and, in turn, traffic volume in urban arterials. For improved traffic management under adverse weather conditions, it is important to develop a traffic prediction algorithm considering the effect of rainfall. This inclusion is not intuitive as the effect is not immediate, and the influence of rainfall on traffic volume is often unrecognizable in a direct correlation analysis between the two time-series data sets; it can only be observed at certain frequency levels. Accordingly, it is useful to employ a multiresolution prediction framework to develop a weather adaptive traffic forecasting algorithm. Discrete wavelet transform (DWT) is a well-known multiresolution data analysis methodology. However, DWT imparts time variance in the transformed signal and makes it unsuitable for further time-series analysis. Therefore, the stationary form of DWT known as stationary wavelet transform (SWT) has been used in this paper to develop a neurowavelet prediction algorithm to forecast hourly traffic flow considering the effect of rainfall. The proposed prediction algorithm has been evaluated at two urban arterial locations in Dublin, Ireland. This paper shows that the rainfall data successfully augments the traffic flow data as an exogenous variable in periods of inclement weather, resulting in accurate predictions of future traffic flow at the two chosen locations. The forecasts from the neurowavelet model outperform the forecasts from the standard artificial neural network (ANN) model. [ABSTRACT FROM PUBLISHER]