Variations, effectiveness and its associated factors of a nationwide web-based hypertension management training project in China: insights from a government-led campaign for 1.2 million lay health workers

OBJECTIVES To evaluate the effectiveness of a large-scale,web-based,in-service hypertension management training project among lay health workers(LHWs)at primary care health(PHC)settings in China,and to examine the factors contributing to the of effectiveness.variations METHODS We used data from a web-based national hypertension management training project implemented in 2018,it was designed to facilitate LHWs to learn,understand,and apply the relevant knowledge and skills in hypertension management through providing training courses by use of the web-based platform with unified standards.All LHWs were required to parti-cipate in the exams before and after training to acquire scores for the use of evaluating their performance of hypertension man-agement knowledge.We first used descriptive analysis to present the variations of effectiveness in hypertension management knowledge among LHWs by important subgroups.Afterwards,we used multilevel logistic regression to examine the individual regional factors contributing to the variations and quantify the magnitude of how these factors affected training effectiveness.and RESULTS There were 1,208,610 LHWs who completed training and were certificated.Nationally,the scores of LHWs in-creased significantly from 62.87±21.14 out of 100 in the pre-test to 88.30±11.31 in the post-test by 25.43(95%confidence interval[CI]:25.40-25.47).Training contents involved in antihypertensive medication showed the lowest score(54.36)in the pre-test and soared the most after training,up to 84.22 by 54.94%.Individual factors associated with disparities in the knowledge of hyperten-sion management decreased substantially after training,which included sex,age,education,practice type,professional level,and hierarchy of working institutions.Geographical variations were shown at the provincial level,with the majority of them being ex-by factors at the regional level.plained CONCLUSIONS Accessible web-based training modality,government efforts,accompanied with experiences derived from the training,could be generalized to other low-and middle-income countries in facilitating the hypertension management capacity of LHWs.Localization and evaluation is warranted on the way to its further application.

Unveiling health rights:A call to action for sex workers'HIV care in the Philippines

We are writing in response to the article titled“Addressing the needs and rights of sex workers for HIV healthcare services in the Philippines”[1].The article calls for attention on the significant challenges faced by sex workers in the Philippines in accessing HIV healthcare.We appreciate the article’s effort to examine these issues in depth.We would like to present a constant flow of thoughts in this letter while highlighting the positive aspects,potential obstacles,and additional points that contribute to this ongoing discussion.

Assessment of Knowledge, Attitude and Practices among Healthcare Workers in a Tertiary Care Hospital on Needle Stick Injury

Purpose: Needle-stick injury (NSI) is one of the most potential occupational hazards for healthcare workers because of the transmission of blood-borne pathogens. As per recent data, around 30 lakh healthcare workers sustain Needle stick injuries each year. This study was conducted to assess healthcare workers’ knowledge, attitude and practices regarding needle stick injury. Materials & Methods: A cross-sectional study was conducted in a Tertiary Care Hospital over the period of 3 months. The study population consisted of Intern Doctors, Post Graduate resident Doctors, Staff Nurses, laboratory technicians of Government Medical College and New Civil Hospital, Surat (n = 300). The data were collected using a self-administered questionnaire via the means of Google Forms. Questionnaire was made with prior review literature. The data obtained were entered and analysed in Microsoft Excel. Results: The prevalence of NSI in our study was 46%, with a higher prevalence among the PG residents (72%). Overall scores regarding knowledge and attitude were better in PG residents (knowledge score > 7 in 71% and Attitude Score > 7 in 68% of PG Residents). Even though the PG residents scored highest in the knowledge category, the majority of them suffered needle stick injuries as a result of poor practice scores. Among those who had NSI (n = 139/300), 70% of study participants had superficial injuries, only 9% reported the incident, 18% got medical attention within 2 hours of the incident, and 7% followed up to recheck their viral markers status. Most incidents of NSI were due to hypodermic needles while recapping needles. Conclusion: Exposure to needle stick injuries and their underreporting remains a common problem. It is imperative that healthcare workers receive regular training on the proper handling of sharp objects. We can also draw the conclusion that preventing NSIs requires putting knowledge into practice.

Construction Activity Analysis of Workers Based on Human Posture Estimation Information

Identifying workers’construction activities or behaviors can enable managers to better monitor labor efficiency and construction progress.However,current activity analysis methods for construction workers rely solely on manual observations and recordings,which consumes considerable time and has high labor costs.Researchers have focused on monitoring on-site construction activities of workers.However,when multiple workers are working together,current research cannot accu rately and automatically identify the construction activity.This research proposes a deep learning framework for the automated analysis of the construction activities of multiple workers.In this framework,multiple deep neural network models are designed and used to complete worker key point extraction,worker tracking,and worker construction activity analysis.The designed framework was tested at an actual construction site,and activity recognition for multiple workers was performed,indicating the feasibility of the framework for the automated monitoring of work efficiency.

Pattern of Eye Diseases among Tea Workers

Background: Bangladesh’s tea industry is essential to the country’s economic expansion. Since tea workers in Bangladesh are marginalized within our community, they have limited access to comprehensive eye care services. Productivity and well-being are cornerstones of comprehensive health care strategy. Ocular disorders are influenced by life expectancy, sociodemographic status, and the epidemiological transition. In this context, the state of ocular health and the many eye illnesses remain to be significantly addressed. Purpose: To evaluate the pattern of eye diseases among tea workers in a tea estate of Bangladesh. Methods: This cross-sectional observational study was carried out in Halda Valley Tea Estate, Nazirhat, Fatickchari, Chattogram, Bangladesh, under the supervision of the Department of Community Ophthalmology, BSMMU, following ethical clearance and approval by the IRB board of BSMMU. With informed written consent and approval from the authority of the tea estate, a total of 110 tea workers were recruited. Socio-demographic characteristics, ocular findings, and patterns of eye diseases were determined and recorded. Results: The mean age of the study participants was 39.60 ± 11.63 years. The maximum (58.1%) study participants were 31 - 50 years old, female (64.5%), illiterate (82.7%), and tribal (71.8%) indigenes. Eye diseases were found in 94.5% of workers. Presbyopia (28.2%), cataracts (27.3%), and refractive error (26.4%) were the most common. Tea workers with eye diseases were significantly older than those who did not have any eye diseases (40.20 ± 11.57 vs. 29.17 ± 7.31 years, p Conclusion: A significant number of tea workers had eye diseases, of which presbyopia, cataracts, and refractive error were the most common.

Collaborative positioning for swarms:A brief survey of vision,LiDAR and wireless sensors based methods

As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.

Prevalence of Gender-Based Violence among Sex Workers in Bangui, Central African Republic (CAR)

Background: Violence against women has become an international public health and human rights issue in recent decades. The violence suffered by sex workers is of little interest for research, yet it constitutes a major health and safety problem. We propose to assess the extent of the phenomenon of gender-based violence (GBV) among sex workers (SWs) in the city of Bangui in the CAR. Methodology: This is a descriptive cross-sectional epidemiological study covering the period from July to October 2021 carried out among SWs in Bangui, the capital of the CAR. Given that the SWs association had only 159 members in Bangui, an exhaustive sampling was retained. Were included in the study, any SW present during the data collection period and having given their written consent. The parameters studied were socio-demographic characteristics: age, sex, residence, level of education, marital status, and characteristics linked to violence: the notion of violence during their professional activity, the type of violence, the declaration and the declaration if necessary, the response and management of this violence. The data collected was analyzed using Epi info version 7 software. Results: Of the 159 SWs that counted the association, 108 had been included. The average age was 27.0 years with extremes of 14 and 46 years. The age groups of 25 to 34 years were the most represented (43.5%). Fifty-six SWs (51.9%) had reached the secondary level. Unemployed SWs were in the majority at 74.1%;Sixty-six (66) SWs in our sample (61.1%) had already been victims of violence during the exercise of their activity Sexual violence was the most represented (28.5%) followed by verbal violence (22.4%). Sixty-eight (62.9%) wanted to stop the professional activity of SWs and 93.1% would accept another income-generating activity in place of sex work. Conclusion: It is necessary to supervise SWs and protect them within the framework of respect for human rights, rather than criminalizing them and the exploiters flouting their human dignity and putting their lives in danger. .

Adaptive H_(∞)Filtering Algorithm for Train Positioning Based on Prior Combination Constraints

To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

An improved particle filter indoor fusion positioning approach based on Wi-Fi/PDR/geomagnetic field

The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning(PDR)and geomagnetic technology have the problems of large initial position error,low sensor accuracy,and geomagnetic mismatch.In this study,a novel indoor fusion positioning approach based on the improved particle filter algorithm by geomagnetic iterative matching is proposed,where Wi-Fi,PDR,and geomagnetic signals are integrated to improve indoor positioning performances.One important contribution is that geomagnetic iterative matching is firstly proposed based on the particle filter algorithm.During the positioning process,an iterative window and a constraint window are introduced to limit the particle generation range and the geomagnetic matching range respectively.The position is corrected several times based on geomagnetic iterative matching in the location correction stage when the pedestrian movement is detected,which made up for the shortage of only one time of geomagnetic correction in the existing particle filter algorithm.In addition,this study also proposes a real-time step detection algorithm based on multi-threshold constraints to judge whether pedestrians are moving,which satisfies the real-time requirement of our fusion positioning approach.Through experimental verification,the average positioning accuracy of the proposed approach reaches 1.59 m,which improves 33.2%compared with the existing particle filter fusion positioning algorithms.

Synthetic Aperture Positioning: A Review

Obtaining precise position of interested emitters passively has wide applications in both civilian and military fields.Different from traditional parameter measurement and direct position determination(DPD)method,recently a new passive localization method based on synthetic aper-ture technique,named synthetic aperture positioning(SAP),has been proposed.The method com-pensates for the nonlinear phase produced by relative motion between the moving platform and the emitter,achieving coherent summation of intercepted signals.The SAP can obtain high-resolution and high-precision localization results at a low signal-to-noise ratio.This paper summarizes the research progress of SAP,including localization principles,spaceborne applications,and application scope analysis.Besides,the possible future outlook of SAP is considered.

Wireless Positioning:Technologies,Applications,Challenges,and Future Development Trends

The development of the fifth-generation(5G)mobile communication systems has entered the commercialization stage.5G has a high data rate,low latency,and high reliability that can meet the basic demands of most industries and daily life,such as the Internet of Things(IoT),intelligent transportation systems,positioning,and navigation.The continuous progress and development of society have aroused wide concern.Positioning accuracy is the core demand for the applications,especially in complex environments such as airports,warehouses,supermarkets,and basements.However,many factors also affect the accuracy of positioning in those environments,for example,multipath effects,non-line-of-sight,and clock synchronization errors.This paper provides a comprehensive review of the existing works about positioning for the future wireless network and discusses its key techniques and algorithms,as well as the current development and future directions.We first outline the current traditional positioning technologies and algorithms,which are discussed and analyzed with the relevant literature.In addition,we also discuss application scenarios for wireless localization.By comparing different positioning systems,the challenges and future development directions of existing wireless positioning systems are prospected.

Epidemiological Profile of Men Who Have Sex with Men: First Data about Male Sex Workers in Central African Republic (CAR)

Objectives: Sex work is not well documented among African men. The aim of this study was to describe the epidemiological profile of men who have sex with men (MSM) and eventually to determine the proportion of sex workers (SW) among them, as well as the proportion of MSM who have been victims of gender-based violence (GBV). Material and Methods: A cross-sectional study coordinated by the Direction de la Médecine du Travail was carried out at the headquarters of the association ALTERNATIVES in Bangui Bangui from July 1 to October 31, 2021. Consenting MSM present during the study period were systematically included. Sociodemographic variables, those relating to the future vision of the activity and to GBV were collected and analyzed using Epi-Info version 7 software. Results: Forty MSM with an average age of 23 years and mainly secondary education (75.0%) were included. The vast majority of MSM were unemployed (85.0%). 45.0% had been victims of GBV and wanted to stop working as an MSM (47.5%), and almost 2/3 (65.0%) would accept another income-generating activity in exchange for the MSM. Violence was sexual (32.5%), economic (22.5%), physical (20.0%), verbal (12.5%) and psychological (12.5%). Conclusion: The MSM were mainly young, poorly educated, unemployed, and almost half were victims of GBV. The desire to change MSM activity to another income-generating activity alongside that of MSM shows that many of them are SW, workers in the informal sector. This must be taken into account in prevention activities, even if the data needs to be confirmed on a much larger sample.

Hybrid pedestrian positioning system using wearable inertial sensors and ultrasonic ranging

Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.

Study on Influencing Factors of Mental Health of Mobile Young White-Collar Workers in China

Mobile young white-collar workers not only have the characteristics of mobile young people,but also have the characteristics of general white-collar workers.Under the influence of both,their mental health may be suffering from“double disadvantage”.So,based on an ecological model of the stress process,this paper tries to use the data of the questionnaire on the mental health of mobile young white-collar workers in Zhejiang Province to explore the influence of some factors in the middle workplace and residence place on the mental health of micro individuals.The results show that:(1)The working environment with high control and low freedom and the workplace discrimination against the mobile status will have a negative impact on the mental health of mobile young white-collar workers;(2)Financial anxiety in daily life will lead to a decline in the mental health level of mobile young white-collar workers;(3)Good organizational support and neighborhood social relations can significantly relieve life pressure,so as to effectively improve the mental health of mobile young white-collar workers.It can be seen that we also need to pay more attention to the mental health of mobile young white-collar workers in order to improve their situation.

A Combined Antenna Array Deployment with High Positioning Accuracy and Low Angular Measurement Error

In this paper,an antenna array composed of circular array and orthogonal linear array is proposed by using the design of long and short baseline“orthogonal linear array”and the circular array ambiguity resolution design of multi-group baseline clustering.The effectiveness of the antenna array in this paper is verified by sufficient simulation and experiment.After the system deviation correction work,it is found that in the L/S/C/X frequency bands,the ambiguity resolution probability is high,and the phase difference system error between each channel is basically the same.The angle measurement error is less than 0.5°,and the positioning error is less than 2.5 km.Notably,as the center frequency increases,calibration consistency improves,and the calibration frequency points become applicable over a wider frequency range.At a center frequency of 11.5 GHz,the calibration frequency point bandwidth extends to 1200 MHz.This combined antenna array deployment holds significant promise for a wide range of applications in contemporary wireless communication systems.

Accurate Source-Receiver Positioning Method for a High-Resolution Deep-Towed Multichannel Seismic Exploration System

The near-seabed multichannel seismic exploration systems have yielded remarkable successes in marine geological disaster assessment,marine gas hydrate investigation,and deep-sea mineral exploration owing to their high vertical and horizontal resolution.However,the quality of deep-towed seismic imaging hinges on accurate source-receiver positioning information.In light of existing technical problems,we propose a novel array geometry inversion method tailored for high-resolution deep-towed multichannel seismic exploration systems.This method is independent of the attitude and depth sensors along a deep-towed seismic streamer,accounting for variations in seawater velocity and seabed slope angle.Our approach decomposes the towed line array into multiline segments and characterizes its geometric shape using the line segment distance and pitch angle.Introducing optimization parameters for seawater velocity and seabed slope angle,we establish an objective function based on the model,yielding results that align with objective reality.Employing the particle swarm optimization algorithm enables synchronous acquisition of optimized inversion results for array geometry and seawater velocity.Experimental validation using theoretical models and practical data verifies that our approach effectively enhances source and receiver positioning inversion accuracy.The algorithm exhibits robust stability and reliability,addressing uncertainties in seismic traveltime picking and complex seabed topography conditions.

An improved positioning model of deep-seafloor datum point at large incidence angle

The inhomogeneous sound speed in seawater causes refraction of sound waves,and the elimination of the refraction effect is essential to the accuracy of underwater acoustic positioning.The raytracing method is an indispensable tool for effectively handling problems.However,this method has a conflict between localization accuracy and computational quantity.The equivalent sound speed profile(ESSP)method uses a simple sound speed profile(SSP)instead of the actual complex SSP,which can improve positioning precision but with residual error.The residual error is especially non-negligible in deep water and at large beam incidence angles.By analyzing the residual error of the ESSP method through a simulation,an empirical formula of error is presented.The data collected in the sailing circle mode(large incidence angle)of the South China Sea are used for verification.The experiments show that compared to the ESSP method,the improved algorithm has higher positioning precision and is more efficient than the ray-tracing method.

WiFi Indoor Positioning and Tracking Algorithm Based on Compressive Sensing and Sage-Husa Adaptive Kalman Filter

Aiming at the problem that the positioning accuracy of WiFi indoor positioning technology based on location fingerprint has not reached the requirements of practical application, a WiFi indoor positioning and tracking algorithm combining adaptive affine propagation (AAPC), compressed sensing (CS) and Kalman filter is proposed. In the off-line phase, AAPC algorithm is used to generate clustering fingerprints with optimal clustering effect performance;In the online phase, CS and nearest neighbor algorithm are used for position estimation;Finally, the Kalman filter and physical constraints are combined to perform positioning and tracking. By collecting a large number of real experimental data, it is proved that the developed algorithm has higher positioning accuracy and more accurate trajectory tracking effect.

Labor Motivation and Its Influence on Workers’Productivity-A Secondary Publication

The productivity of an institution is achieved,in large part,by creating a harmonious environment that reflects the satisfaction,empowerment,and collaborative spirit of each employee.From this perspective,management will consider upgrades using all tactics that allow for the achievement of these goals,including direct effort and the involvement of all stakeholders.The objective of this study was to examine the relationship between work motivation and the productivity of workers in the communal board of the Barrio Sur corregimiento in the province of Colón.Using the questionnaire as an instrument,as well as the descriptive method,allowed for the report and evaluation of the characteristics of the workers,indicating interpersonal deficits and distancing in the motivations that drive administrative action.By incorporating different approaches previously analyzed and developed by different authors familiar with the subject,it was possible to achieve substantial results,such as the need to implement administrative strategies that harmoniously incorporate workers,showing that,despite motivation problems,the work environment where one works is very important in the performance of their duties.Managing to motivate the direct participation of the workers selected as part of the sample,who showed full satisfaction with the results framed within the framework of individual improvement and,above all,the commitment to the institution to improve its work.