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PloS One 2024Refugees and their healthcare providers face numerous challenges in receiving and providing maternal and newborn care. Research exploring how these challenges are...
INTRODUCTION
Refugees and their healthcare providers face numerous challenges in receiving and providing maternal and newborn care. Research exploring how these challenges are related to adverse perinatal and maternal outcomes is scarce. Therefore, this study aims to identify suboptimal factors in maternal and newborn care for asylum-seeking and refugee women and assess to what extent these factors may contribute to adverse pregnancy outcomes in the Netherlands.
METHODS
We conducted a retrospective analysis of national perinatal audit data from 2017 to 2019. Our analysis encompassed cases with adverse perinatal and maternal outcomes in women with a refugee background (n = 53). Suboptimal factors in care were identified and categorized according to Binder et al.'s Three Delays Model, and the extent to which they contributed to the adverse outcome was evaluated.
RESULTS
We identified 29 suboptimal factors, of which seven were related to care-seeking, six to the accessibility of services, and 16 to the quality of care. All 53 cases contained suboptimal factors, and in 67.9% of cases, at least one of these factors most likely or probably contributed to the adverse perinatal or maternal outcome.
CONCLUSION
The number of suboptimal factors identified in this study and the extent to which they contributed to adverse perinatal and maternal outcomes among refugee women is alarming. The wide range of suboptimal factors identified provides considerable scope for improvement of maternal and newborn care for refugee populations. These findings also highlight the importance of including refugee women in perinatal audits as it is essential for healthcare providers to better understand the factors associated with adverse outcomes to improve the quality of care. Adjustments to improve care for refugees could include culturally sensitive education for healthcare providers, increased workforce diversity, minimizing the relocation of asylum seekers, and permanent reimbursement of professional interpreter costs.
Topics: Humans; Refugees; Female; Netherlands; Pregnancy; Infant, Newborn; Adult; Retrospective Studies; Perinatal Care; Pregnancy Outcome; Health Services Accessibility; Quality of Health Care; Young Adult; Patient Acceptance of Health Care
PubMed: 38935661
DOI: 10.1371/journal.pone.0305764 -
Indian Journal of Public Health Oct 2023Cancer incidence rates are rising at an alarming rate in India and are expected to rise by 12% in the next 5 years. Hence, a thorough knowledge of the existing scope of...
BACKGROUND
Cancer incidence rates are rising at an alarming rate in India and are expected to rise by 12% in the next 5 years. Hence, a thorough knowledge of the existing scope of the cancer problem is required to provide an approach for analyzing and regulating the impact of cancer across the country.
OBJECTIVES
This study aimed to determine whether the cancer incidence rates of all the states and union territories across the six geographical regions of India are statistically different from each other or not and also to identify the highly cancer-affected states.
MATERIALS AND METHODS
The data have been obtained from the website www.indiastat.com from 2009 to 2020. The one-way analysis of variance, followed by Tukey's test and t-test, is used for the statistical evaluation.
RESULTS
The multiple comparison tests revealed that the difference between the cancer incidence rates is significant in all the states and union territories in every region of India. The highly affected states in the six geographical regions of India are Uttar Pradesh (UP), Tamil Nadu, Bihar, Maharashtra, Assam, and Madhya Pradesh. The most highly affected state among them is UP. These states contributed to nearly half of India's cancer burden in 2020.
CONCLUSION
This study offers significant information on the current status of cancer incidence rates in India for 12 years. As India is observing an increase in cancer incidence, therefore, additional efforts are required to strengthen cancer prevention and control strategies, particularly in India's most cancer-affected states.
Topics: India; Humans; Incidence; Neoplasms
PubMed: 38934824
DOI: 10.4103/ijph.ijph_1587_22 -
MSystems Jun 2024The alarming rise of antibiotic-resistant bacterial infections is driving efforts to develop alternatives to conventional antibiotics. In this context, antimicrobial...
UNLABELLED
The alarming rise of antibiotic-resistant bacterial infections is driving efforts to develop alternatives to conventional antibiotics. In this context, antimicrobial peptides (AMPs) have emerged as promising candidates for their ability to target a broad range of microorganisms. However, the development of AMPs with optimal potency, selectivity, and/or stability profiles remains a challenge. To address it, computational tools for predicting AMP properties and designing novel peptides have gained increasing attention. PyAMPA is a novel platform for AMP discovery. It consists of five modules, namely AMPScreen, AMPValidate, AMPSolve, AMPMutate, and AMPOptimize, that allow high-throughput proteome inspection, candidate screening, and optimization through point-mutation and genetic algorithms. The platform also offers additional tools for predicting and evaluating AMP properties, including antimicrobial and cytotoxic activity, and peptide half-life. By providing innovative and accessible inroads into AMP motifs in proteomes, PyAMPA will enable advances in AMP development and potential translation into clinically useful molecules. PyAMPA is available at: https://github.com/SysBioUAB/PyAMPA.
IMPORTANCE
This paper introduces PyAMPA, a new bioinformatics platform designed for the discovery and optimization of antimicrobial peptides (AMPs). It addresses the urgent need for new antimicrobials due to the rise of antibiotic-resistant infections. PyAMPA, with its five predictive modules -AMPScreen, AMPValidate, AMPSolve, AMPMutate and AMPOptimize, enables high-throughput screening of proteomes to identify potential AMP motifs and optimize them for clinical use. Its unique approach, combining prediction, design, and optimization tools, makes PyAMPA a robust solution for developing new AMP-based therapies, offering a significant advance in combatting antibiotic resistance.
PubMed: 38934543
DOI: 10.1128/msystems.01358-23 -
Sensors (Basel, Switzerland) Jun 2024In recent years, with the rapid development of deep learning and its outstanding capabilities in target detection, innovative methods have been introduced for infrared... (Review)
Review
In recent years, with the rapid development of deep learning and its outstanding capabilities in target detection, innovative methods have been introduced for infrared dim small target detection. This review comprehensively summarizes public datasets, the latest networks, and evaluation metrics for infrared dim small target detection. This review mainly focuses on deep learning methods from the past three years and categorizes them based on the six key issues in this field: (1) enhancing the representation capability of small targets; (2) improving the accuracy of bounding box regression; (3) resolving the issue of target information loss in the deep network; (4) balancing missed detections and false alarms; (5) adapting for complex backgrounds; (6) lightweight design and deployment issues of the network. Additionally, this review summarizes twelve public datasets for infrared dim small targets and evaluation metrics used for detection and quantitatively compares the performance of the latest networks. Finally, this review provides insights into the future directions of this field. In conclusion, this review aims to assist researchers in gaining a comprehensive understanding of the latest developments in infrared dim small target detection networks.
PubMed: 38931669
DOI: 10.3390/s24123885 -
Sensors (Basel, Switzerland) Jun 2024The high-altitude real-time inspection of unmanned aerial vehicles (UAVs) has always been a very challenging task. Because high-altitude inspections are susceptible to...
The high-altitude real-time inspection of unmanned aerial vehicles (UAVs) has always been a very challenging task. Because high-altitude inspections are susceptible to interference from different weather conditions, interference from communication signals and a larger field of view result in a smaller object area to be identified. We adopted a method that combines a UAV system scheduling platform with artificial intelligence object detection to implement the UAV automatic inspection technology. We trained the YOLOv5s model on five different categories of vehicle data sets, in which mAP50 and mAP50-95 reached 93.2% and 71.7%, respectively. The YOLOv5s model size is only 13.76 MB, and the detection speed of a single inspection photo reaches 11.26 ms. It is a relatively lightweight model and is suitable for deployment on edge devices for real-time detection. In the original DeepStream framework, we set up the http communication protocol to start quickly to enable different users to call and use it at the same time. In addition, asynchronous sending of alarm frame interception function was added and the auxiliary services were set up to quickly resume video streaming after interruption. We deployed the trained YOLOv5s model on the improved DeepStream framework to implement automatic UAV inspection.
PubMed: 38931645
DOI: 10.3390/s24123862 -
Sensors (Basel, Switzerland) Jun 2024Rapid advancements in connected and autonomous vehicles (CAVs) are fueled by breakthroughs in machine learning, yet they encounter significant risks from adversarial...
Rapid advancements in connected and autonomous vehicles (CAVs) are fueled by breakthroughs in machine learning, yet they encounter significant risks from adversarial attacks. This study explores the vulnerabilities of machine learning-based intrusion detection systems (IDSs) within in-vehicle networks (IVNs) to adversarial attacks, shifting focus from the common research on manipulating CAV perception models. Considering the relatively simple nature of IVN data, we assess the susceptibility of IVN-based IDSs to manipulation-a crucial examination, as adversarial attacks typically exploit complexity. We propose an adversarial attack method using a substitute IDS trained with data from the onboard diagnostic port. In conducting these attacks under black-box conditions while adhering to realistic IVN traffic constraints, our method seeks to deceive the IDS into misclassifying both normal-to-malicious and malicious-to-normal cases. Evaluations on two IDS models-a baseline IDS and a state-of-the-art model, MTH-IDS-demonstrated substantial vulnerability, decreasing the F1 scores from 95% to 38% and from 97% to 79%, respectively. Notably, inducing false alarms proved particularly effective as an adversarial strategy, undermining user trust in the defense mechanism. Despite the simplicity of IVN-based IDSs, our findings reveal critical vulnerabilities that could threaten vehicle safety and necessitate careful consideration in the development of IVN-based IDSs and in formulating responses to the IDSs' alarms.
PubMed: 38931632
DOI: 10.3390/s24123848 -
Sensors (Basel, Switzerland) Jun 2024To achieve large-scale development of triboelectric nanogenerators (TENGs) for water wave energy harvesting and powering the colossal sensors widely distributed in the...
To achieve large-scale development of triboelectric nanogenerators (TENGs) for water wave energy harvesting and powering the colossal sensors widely distributed in the ocean, facile and scalable TENGs with high output are urgently required. Here, an elastic self-recovering hybrid nanogenerator (ES-HNG) is proposed for water wave energy harvesting and marine environmental monitoring. The elastic skeletal support of the ES-HNG is manufactured using three-dimensional (3D) printing technology, which is more conducive to the large-scale integration of the ES-HNG. Moreover, the combination of a TENG and an electromagnetic generator (EMG) optimizes the utilization of device space, leading to enhanced energy harvesting efficiency. Experimental results demonstrate that the TENG achieves a peak power output of 42.68 mW, and the EMG reaches a peak power output of 4.40 mW. Furthermore, various marine environment monitoring sensors, such as a self-powered wireless meteorological monitoring system, a wireless alarm system, and a water quality monitoring pen, have been successfully powered by the sophisticated ES-HNG. This work introduces an ES-HNG for water wave energy harvesting, which demonstrates potential in marine environment monitoring and offers a new solution for the sustainable development of the marine internet of things.
PubMed: 38931554
DOI: 10.3390/s24123770 -
Sensors (Basel, Switzerland) Jun 2024This paper addresses the problem of removing 3D effects as one of the most challenging problems related to 2D electrical resistivity tomography (ERT) monitoring of...
This paper addresses the problem of removing 3D effects as one of the most challenging problems related to 2D electrical resistivity tomography (ERT) monitoring of embankment structures. When processing 2D ERT monitoring data measured along linear profiles, it is fundamental to estimate and correct the distortions introduced by the non-uniform 3D geometry of the embankment. Here, I adopt an iterative 3D correction plus 2D inversion procedure to correct the 3D effects and I test the validity of the proposed algorithm using both synthetic and real data. The modelled embankment is inspired by a critical section of the Parma River levee in Colorno (PR), Italy, where a permanent ERT monitoring system has been in operation since November 2018. For each model of the embankment, reference synthetic data were produced in Res2dmod and Res3dmod for the corresponding 2D and 3D models. Using the reference synthetic data, reference 3D effects were calculated to be compared with 3D effects estimated by the proposed algorithm at each iteration. The results of the synthetic tests showed that even in the absence of a priori information, the proposed algorithm for correcting 3D effects converges rapidly to ideal corrections. Having validated the proposed algorithm through synthetic tests, the method was applied to the ERT monitoring data in the study site to remove 3D effects. Two real datasets from the study site, taken after dry and rainy periods, are discussed here. The results showed that 3D effects cause about ±50% changes in the inverted resistivity images for both periods. This is a critical artifact considering that the final objective of ERT monitoring data for such studies is to produce water content maps to be integrated in alarm systems for hydrogeological risk mitigation. The proposed algorithm to remove 3D effects is thus a rapid and validated solution to satisfy near-real-time data processing and to produce reliable results.
PubMed: 38931543
DOI: 10.3390/s24123759 -
Molecules (Basel, Switzerland) Jun 2024Organic phosphoester (OPE) antioxidants are currently required due to their contribution to enhancing the quality of polymers, including polypropylene (PP). In this...
Organic phosphoester (OPE) antioxidants are currently required due to their contribution to enhancing the quality of polymers, including polypropylene (PP). In this research, an integral methodology is presented for the efficient extraction of bis(2,4-dicumylphenyl) pentaerythritol diphosphite from industrial wastewater. Upon employing the solid-phase extraction (SPE) technique, the recovered compound is subjected to a comprehensive analysis of the recovered compound using high-performance liquid chromatography (HPLC), mass spectrometry (MS), thermal analysis (TGA), Fourier transforms infrared spectroscopy (FTIR), and differential scanning calorimetry (DSC). Subsequently, purified Bis(2,4-dicumylphenyl) pentaerythritol diphosphite was evaluated as a thermo-oxidative stabilizer after incorporation into PP resins. The relative standard deviation (RSD), Error (Er), linearity (R), and percentage (%) recovery were less than 2.6, 2.5, more significant than 0.9995, and greater than 96%, respectively, for the inter-day and intra-day tests of the chromatographic method and the SPE. Except for chloroform, which was necessary due to the solubility properties of the investigated analyte, the use of environmentally friendly solvents, such as methanol and acetonitrile, was considered during the development of this research. The OPE extracted from industrial wastewater was characterized by FTIR, UV-Vis, DSC, TGA, and MS, allowing the elucidation of the structure of Bis(2,4-dicumylphenyl) pentaerythritol diphosphite (BDPD). The recovered OPE was mixed with PP resins, allowing it to improve its thermal properties and minimize its thermo-oxidative degradation. Organophosphorus flame retardant (OPE)' concentration in wastewater is alarming, ranging from 1179.0 to 4709.6 mg L. These exceed toxicity thresholds for aquatic organisms, emphasizing global environmental risks. Using a validated solid-phase extraction (SPE) technique with over 94% recovery, the study addresses concerns by removing organic contaminants and supporting circular economy principles. The high economic and environmental significance of recovering BDPD underscores the need for urgent global attention and intervention.
PubMed: 38930844
DOI: 10.3390/molecules29122780 -
Micromachines May 2024Lidar has the advantages of high accuracy, high resolution, and is not affected by sunlight. It has been widely used in many fields, such as autonomous driving, remote...
Lidar has the advantages of high accuracy, high resolution, and is not affected by sunlight. It has been widely used in many fields, such as autonomous driving, remote sensing detection, and intelligent robots. However, the current lidar detection system belongs to weak signal detection and generally uses avalanche photoelectric detector units as detectors. Limited by the current technology, the photosensitive surface is small, the receiving field of view is limited, and it is easy to cause false alarms due to background light. This paper proposes a method based on a combination of image-side telecentric lenses, microlens arrays, and interference filters. The small-area element detector achieves the high-concentration reception of echo beams in a large field of view while overcoming the interference of ambient background light. The image-side telecentric lens realizes that the center lines of the echo beams at different angles are parallel to the central axis, and the focus points converge on the same focal plane. The microlens array collimates the converged light beams one by one into parallel light beams. Finally, a high-quality aspherical focusing lens is used to focus the light on the small-area element detector to achieve high-concentration light reception over a large field of view. The system achieves a receiving field of view greater than 40° for a photosensitive surface detector with a diameter of 75 μm and is resistant to background light interference.
PubMed: 38930682
DOI: 10.3390/mi15060712