Similar Packages Research Articles

Implementation of the Package of Essential Non-Communicable (PEN) Disease Interventions in Low-Resource Settings: A Systematic Review

Background: To deal with the rising prevalence and death rate of non-communicable diseases, the WHO designed a package of essential interventions for non-communicable diseases for low- and middle-income countries. This review aimed to identify the barriers and facilitators of the implementation of this program. Methods: The electronic databases of PubMed, Scopus, Web of Science, Cochrane Library, and Scientific Information Database (SID) were searched for papers without a time limit at the end of Dec 2020. Only English and Persian languages were considered. The PRISMA guideline was consulted. Results: Overall, 15 articles were selected for the final analysis out of 404 initially retrieved ones, based on inclusion/exclusion criteria and quality assessment. Thirteen articles had good quality, while 2 articles were of fair quality. Studies were published during 2014-2020. Thematic analysis was used to make sense of papers so that barriers and facilitators were categorized within 2 main themes and 7 sub-themes. Certain organizational factors including human resources, service delivery, structure, leadership/governance, data and information, resources, and financing were identified as barriers and facilitators. Knowledge and culture, and economic and social factors were identified as contextual factors. Conclusion: By considering the factors identified in this study, policymakers and health system managers can be more successful in implementing this WHO PEN and similar packages.

What could improve surgical data system at health facilities with high surgical volume in Ethiopia?

BackgroundThe effective management of surgical and anesthesia care relies on quality data and its readily availability for both patient-centered decision-making and facility-level improvement efforts. Recognizing this critical need, the Strengthening Systems for Improved Surgical Outcomes (SSISO) project addressed surgical care data management and information use practices across 23 health facilities from October 2019 to September 2022. This study aimed to evaluate the effectiveness of SSISO interventions in enhancing practices related to surgical data capture, reporting, analysis, and visualization.MethodsThis study employed a mixed method, pre- post intervention evaluation design to assess changes in data management and utilization practices at intervention facilities. The intervention packages included capacity building trainings, monthly mentorship visits facilitated by a hub-and-spoke approach, provision of data capture tools, and reinforcement of performance review teams. Data collection occurred at baseline (February – April 2020) and endline (April – June 2022). The evaluation focused on the availability and appropriate use of data capture tools, as well as changes in performance review practices. Appropriate use of registers was defined as filling all the necessary data onto the registers, and this was verified by completeness of selected key data elements in the registers.ResultsThe proportion of health facilities with Operation Room (OR) scheduling, referral, and surgical site infection registers significantly increased by 34.8%, 56.5% and 87%, respectively, at project endline compared to baseline. Availability of OR and Anesthesia registers remained high throughout the project, at 91.3% and 95.6%, respectively. Furthermore, the appropriate use of these registers improved, with statistically significant increases observed for OR scheduling registers (34.8% increase). Increases were also noted for OR register (9.5% increase) and anesthesia register (4.5% increase), although not statistically significant. Assessing the prior three months reports, the report submissions to the Ministry of Health/Regional Health Bureau (MOH/RHB) rose from 85 to 100%, reflecting complete reporting at endline period. Additionally, the proportion of surgical teams analyzing and displaying data for informed decision-making significantly increased from 30.4% at baseline to 60.8% at endline period.ConclusionThe implemented interventions positively impacted surgical data management and utilization practice at intervention facilities. These positive changes were likely attributable to capacity building trainings and regular mentorship visits via hub-and-spoke approach. Hence, we recommend further investigation into the effectiveness of similar intervention packages in improving surgical data management, data analysis and visualization practices in low- and middle-income country settings.

Interactive and educational simulation tool for permanent magnet synchronous machines

PurposeThis paper aims to present an interactive design and simulation tool for permanent magnet synchronous machines based on the finite-element-method. The tool is intended for education and research on electrical machines.Design/methodology/approachA coupling between the software MATLAB and finite element method magnetics is used. Several functionalities are included as modular scripts and represented in the form of a graphical user interface. Included are fully parametrized motor models, automatic winding generations and the evaluation of torque waveforms, core losses and speed-torque-diagrams. A survey was conducted to determine how the motivation of students concerning the covered topics is influenced by using the tool.FindingsDue to its simplicity and the intuitive visualization of the results, the tool provides direct access to the topic of electrical machines without having to deal with separate scripts. The modular structure of the software allows simple extensions with new functions. Because students can directly contribute to the tool with their own work, their motivation for using and extending it increases.Originality/valueThe presented tool offers more functionalities compared to similar free software packages, e.g. the calculation of core losses and speed-torque diagrams. Also, it is designed in such a way that it can be easily understood and extended by students.

Quality of Environmental Impact Assessment Reports for Lodge Developments in Protected Areas: The Okavango Delta Case, Botswana

This paper evaluates the quality of environmental impact assessment (EIA) reports for lodge developments in Botswana’s Okavango Delta, which is a wetland of international importance and forms part of a transboundary conservation area and world heritage site. A quality review of 31 EIA reports, approved between 2013 and 2021, was conducted by applying a context specific EIA report quality review package. The review package consists of four review areas with seventeen categories and 64 sub-categories, adapted from similar international packages to address the specific legal requirements for EIA in Botswana as well as best practice. Results show that the overall quality of the reports are poor, with 71% graded as ‘unsatisfactory’. In general, descriptive areas of the EIA reports fared better, while the performance of the more analytical areas was ‘poor’. Key areas of weakness include - the identification of impacts; prediction and assessment of impact magnitude; as well as identifying alternatives and mitigation measures. Overall results suggest that currently EIA report content is insufficient to inform decision-making towards sustainable tourism development in the Okavango Delta. It is recommended that areas of weakness can be addressed by providing clear strategic direction; developing a central data management system; setting norms and standards for tourism development as well as building capacity and awareness of key stakeholders. This will ensure that EIA remains a tool of choice for decision making and avoid becoming a mere ‘red-tape’/administrative process aimed at securing development approvals.

Conversation and the evolution of metacognition

Abstract While the term “metacognition” is sometimes used to refer to any form of thinking about thinking, in cognitive psychology, it is typically reserved for thinking about one’s own thinking, as opposed to thinking about others’ thinking. How metacognition in this more specific sense relates to other-directed mindreading is one of the main theoretical issues debated in the literature. This article considers the idea that we make use of the same or a largely similar package of resources in conceptually interpreting our own mind as we do in interpreting others’. I assume that a capacity for other-directed mindreading is minimally shared with our great-ape relatives, but I argue that the architecture of this system had to be substantially modified before it could efficiently and adaptively be turned inwards on one’s own mind. I contend that an important piece of the overall evolutionary explanation here likely concerns selection pressures arising from the domain of conversational interaction. Specifically, drawing on work carried out in the human interaction studies tradition (e.g., conversation analysis), I argue that the smooth to-and-fro of conversational interaction can be seen to heavily depend on metacommunicative capacities, which, in turn, are underpinned by metacognitive capacities. I conclude with a thumbnail sketch of an evolutionary account of the emergence of these metacognitive capacities in the human line. Their appearance and spread – whether via genes, cultural learning, or more likely, some combination of the two – helps to explain the transition from great-ape communication to human conversation.

Estimating the Cost of Strauss Pile Retaining Wall Works Using the Cost Significant Method

Cost estimation is an important element in a project. In the early stages of a project, information for estimates tends to be less accurate. Therefore, a cost estimation model is needed that can explain most of the projects based on the lack of information. The estimation method used is the Cost Significant Model. The aim is to determine the accuracy of the Strauss Mast Retaining Wall Work cost estimation model against the actual project cost. Data was collected using the sampling method, and 5 (five) similar project packages were obtained from 2019-2021. Produce 2 (two) Significant Cost Items that have cumulative costs (80%), namely Strauss Pile Work (X3) of 32% and Pile Work (X4) of 48%. Then it is analyzed to produce a regression equation formula using the SPSS application, and the equation is Y = 5696.59+5.270 X3-1,389X4 with a Cost Model Factor of 1.11. Estimated accuracy ranges from -7.3% to +8.4%. With an average of +0%. The accuracy rate is in class 1 of the International AACE classification, which has a lower limit of -3% to -10% and an upper limit of +3% to 15%. The estimation model is feasible to use to check the bid estimate.

Serial image interpretation tasks improve accuracy and increase confidence in Level 1 echocardiography reporting: a pilot study

BackgroundFocused echocardiography is increasingly used in acute and emergency care, with point-of-care ultrasound integrated into several specialist training curricula (e.g. Emergency Medicine, Cardiology, Critical Care). Multiple accreditation pathways support development of this skill but there is scant empirical evidence to inform selection of teaching methods, accreditation requirements or quality assurance of education in focussed echocardiography. It has also been noted that access to in-person teaching can be a barrier to completing accreditation programmes, and that this may affect learners disproportionately depending on the location or nature of their institution. The purpose of the study was to determine whether serial image interpretation tasks as a distinct learning tool improved novice echocardiographers’ ability to accurately identify potentially life-threatening pathology from focused scans. We also aimed to describe the relationship between accuracy of reporting and participants’ confidence in those reports, and to assess users’ satisfaction with a learning pathway that could potentially be delivered remotely.Methods27 participants from a variety of healthcare roles completed a program of remote lectures and 2 in-person study days. During the program they undertook 4 ‘packets’ of 10 focused echocardiography reporting tasks (total = 40) based on images from a standardised dataset. Participants were randomized to view the scans in varying orders. Reporting accuracy was compared with consensus reports from a panel of expert echocardiographers, and participants self-reported confidence in their image interpretation and their satisfaction with the learning experience.ResultsThere was a stepwise improvement in reporting accuracy with each set of images reported, from an average reporting score of 66% for the 1st packet to 78% for the 4th packet. Participants felt more confident in identifying common life-threatening pathologies as they reported more echocardiograms. The correlation between report accuracy and confidence in the report was weak and did not increase during the study (rs = 0.394 for the 1st packet, rs = 0.321 for the 4th packet). Attrition during the study related primarily to logistical issues. There were high levels of satisfaction amongst participants, with most reporting that they would use and / or recommend a similar teaching package to colleagues.ConclusionsHealthcare professionals undertaking remote training with recorded lectures, followed by multiple reporting tasks were capable of interpreting focused echocardiograms. Reporting accuracy and confidence in identifying life-threatening pathology increased with the number of scans interpreted. The correlation between accuracy and confidence for any given report was weak (and this relationship should be explored further given the potential safety considerations). All components of this package could be delivered via distance learning to enhance the flexibility of echocardiography education.

The CIMS (Cyanobacterial ITS motif slicer) for molecular systematics

The 16S-23S rRNA Internal Transcribed Spacer (ITS) is a commonly employed taxonomic marker in cyanobacterial systematics. Due to numerous challenges in articulating phylogenetic relationships within this ubiquitous, ancient lineage, a polyphasic approach including 16S rRNA sequence data, ecology, morphology, and ITS secondary structure analysis has become the standard. In particular, the ITS motifs are being utilized in the erection of novel and cryptic taxa. However, this is challenging as researchers must manually mine and parse sequence data to visually find and identify ITS structures. This painstaking process deters researchers from using ITS motifs, may lead to inconsistencies, and is a rather dry, tedious enterprise. Thus, we present a simple, user-friendly web-based application for help in finding and preparing the most common cyanobacterial motifs (e.g., the Box-B, D1-D1´, tRNAs, etc.). After extensive testing, we note that the most common motifs are recovered at ca. 97%. These motifs can then be easily exported into Mfold or other similar folding packages. We hope that this will both provide a valuable tool for researchers but will also facilitate new discoveries and allow for greater consistency in publishing ITS comparisons. The tool can be accessed at www.phylo.dev.

Internet of medical things for VTE patients in ICU: A self-attention mechanism-based energy-efficient risk identification scheduling algorithm

The explosive growth of medical data has dramatically increased the demand for computing power, resulting in insufficient spectrum resources and communication overload. Hospitals need to invest much money to expand computing resources. Various diseases require varying degrees of multi-sensor and continuous monitoring. Take venous thromboembolism (VTE) patients in the intensive care unit (ICU) as an example, enlargement of the right heart, widening of the pulmonary artery, and abnormal results of myocardial enzyme examination maybe lead to sudden death within a short time in the ICU inpatient ward. Steady and dynamic health monitoring is essential. Patients’ immediate risk perception can significantly improve medical efficiency and reduce adverse consequences. How to provide a more efficient and secure full-time monitoring scheme, dynamically adjust the workload, and allocate computing tasks and requests reasonably is a practical problem to be solved urgently. First, this paper defines a task similarity to measure the similarity between different task packages and determine the priority of tasks to avoid forwarding highly similar task packages and reduce energy consumption. Second, the edge gateway caching mechanism with a self-attention mechanism is constructed, which changes the centralized scheduling mode of traditional cloud computing, devolves the coordination function to the edge, and divides the network into multiple local sub-networks. The central node of the sub-network determines the scheduling scheme. The experimental results show that the system can ensure the quality of service and use the edge’s limited computing resources, effectively shield the inefficient data transmission requirements, reduce the use cost and medical quality, and has a specific theoretical and practical value.

Hub-driven policy packages as a basis for e-waste reform: rationales and a case study

ABSTRACT Extended Producer Responsibility (EPR) principles have emerged as the template for e-waste policies, centered on establishing regulated collection and recycling channels. Originating in the global North, these policies are increasingly adopted in the global South where e-waste is primarily ‘managed’ by the informal sector, centered in spatially defined hubs. These formal systems fail to achieve collection quotas, while further marginalizing informal recyclers by delegitimizing their access to e-waste. We suggest an alternative hub-centered approach to e-waste reform based on eight years of research and advocacy within the Israel-West Bank e-waste system. We offer several converging rationales for centralizing hubs in e-waste policies and a case study demonstrating an integrated hub-driven package of business, enforcement, and cleanup measures. While the unique complexities of the Israeli-Palestinian case offer an exceptional window into the dynamics of a hub-driven approach, similar packages might shape e-waste policy reform throughout the global South.

Logitr: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness-to-Pay Space Utility Parameterizations

This paper introduces the logitr R package for fast maximum likelihood estimation of multinomial logit and mixed logit models with unobserved heterogeneity across individuals, which is modeled by allowing parameters to vary randomly over individuals according to a chosen distribution. The package is faster than other similar packages such as mlogit, gmnl, mixl, and apollo, and it supports utility models specified with

Effectiveness of intervention package on knowledge and attitude regarding functional needs and quality of life of elderly patients with psychiatric illness, among nursing interns.

To develop and assess the effectiveness of the intervention package on knowledge and attitude regarding meeting the functional needs and improving the quality of life of elderly patients with psychiatric illness, among nursing interns. The study was carried out among 60 nursing interns of a tertiary government mental health setting. After the pretest, the educational intervention package on functional needs and quality of life of elderly patients with psychiatric illness was administered to the study group in four sessions. Posttest data collection was performed using the same questionnaires after 2 weeks after the last session. There was a statistically significant improvement in the knowledge and attitude of nursing students following the sessions of the intervention package. Pretest data showed that there is a positive correlation between the knowledge and attitude of study subjects. Overall knowledge has significantly improved after attending the intervention program (Z = 6.701, P < 0.001). Moreover, the overall attitude level has significantly improved after attending the intervention program (Z = 6.741, P < 0.001). The educational intervention package on functional needs and quality of life of elderly patients with psychiatric illness was effective in improving the knowledge and attitude regarding functional needs and quality of life of elderly patients with psychiatric illness, among nursing interns. Similar packages may be incorporated into the nursing curriculum in training future nurses for their better practice in this area.

Using Large Peer-Teaching Groups to Learn Construction Management Software Packages

ABSTRACT Two large peer-teaching groups were developed in a construction management course in order to self-learn and then subsequently teach two separate construction management software packages. One half of the class was asked to learn and teach Microsoft Project and the other was asked to learn and teach Primavera P6, which are very similar scheduling packages. Milestone deliverables were due throughout the semester, with a final presentation near the end of the 16-week semester. This intervention took place a total of five times and one addition control semester in which the instructor taught both packages in a traditional manner for comparison. Within each peer-teaching group, the teams were asked to nominate a leader and co-leader, who would be responsible for assigning responsibilities to the team and to facilitate learning. This methodology allowed for two layers of peer-teaching; one within the peer-teaching group, and the other from the peer-teaching group to the remaining students. The intervention was validated through in-course questionnaires, and homework, quiz, and exam grade comparisons from the student-led lecture versus the instructor-led lecture. The surveys indicated a preference to the peer-teaching and student-led learning, over instructor-led learning. The grade comparison demonstrated an average 13.2 percentage point improvement.

Supplementary Learning Resource Package in Science 10 Physics

Physics is a difficult subject for the vast majority of Filipino students to learn. It is also a challenge for educators worldwide to create learning media that makes it easier to explain the material especially in learning fields that require a reasonably high level of understanding, such as Physics. The use of high-quality instructional materials facilitates and improves the teaching and learning process. This study aimed to develop and evaluate a supplementary learning resource package in Physics for Grade 10 Science. Descriptive method of research was used in this research. The respondents of the study were the thirty science teachers and fifteen science experts who evaluated the materials based on the set standards. The study showed that the supplementary learning resource package is acceptable for use by teachers and students for independent learning particularly in the new normal education. It is recommended that the supplementary learning resource package be further validated in order to provide more effective instructional materials to both learners and teachers, and that other science teachers be encouraged by their school heads to develop similar learning packages.

Skill of Medium-Range Forecast Models Using the Same Initial Conditions

Abstract In the Different Models, Same Initial Conditions (DIMOSIC) project, forecasts from different global medium-range forecast models have been created based on the same initial conditions. The dataset consists of 10-day deterministic forecasts from seven models and includes 122 forecast dates spanning one calendar year. All forecasts are initialized from the same ECMWF operational analyses to minimize the differences due to initialization. The models are run at or near their respective operational resolutions to explore similarities and differences between operational global forecast models. The main aims of this study are 1) to evaluate the forecast skill and how it depends on model formulation, 2) to assess systematic differences and errors at short lead times, 3) to compare multimodel ensemble spread to model uncertainty schemes, and 4) to identify models that generate similar solutions. Our results show that all models in this study are capable of producing high-quality forecasts given a high-quality analysis. But at the same time, we find a large variety in model biases, both in terms of temperature errors and precipitation. We are able to identify models whose forecasts are more similar to each other than they are to those of other systems, due to the use of similar model physics packages. However, in terms of multimodel ensemble spread, our results also demonstrate that forecast sensitivities to different model formulations still are substantial. We therefore believe that the diversity in model design that stems from parallel development efforts at global modeling centers around the world remains valuable for future progress in the numerical weather prediction community.

Genotype calling and haplotype inference from low coverage sequence data in heterozygous plant genome using HetMap.

This study developed a new genotyping method that can accurately infer heterozygous genotype information from the complex plant genome sequence data, which helped discover new alleles in the association studies. Many software packages and pipelines had been developed to handle the sequence data of the model species. However, Genotyping from complex heterozygous plant genome needs further improvement on the previous methods. Here we present a new pipeline available at https://github.com/Ncgrhg/HetMapv1 ) for variant calling and missing genotype imputation from low coverage sequence data for heterozygous plant genomes. To check the performance of the HetMap on the real sequence data, HetMap was applied to both the F1 hybrid rice population, which consists of 1495 samples and the wild rice population with 446 samples. The high coverage sequence data of four hybrid rice accessions and two wild rice accessions, which were also included in low coverage sequence data, were used to validate the accuracy of genotype inference. The validation results showed that HetMap archieved significant improvement in heterozygous genotype inference accuracy (13.65% for hybrid rice, 26.05% for wild rice) and total accuracy compared with similar software packages. The application of the new genotype with the genome-wide association study also showed improvement of association power in wild rice awn length phenotype. It could archive high genotype inference accuracy in low sequence coverage in a small population with both the natural and constructed recombination population. HetMap provided a powerful tool for the heterozygous plant genome sequence data analysis, which may help to discover new phenotype regions for the plant species with the complex heterozygous genome.

Impact of Assessment as Learning on Attitudes towards Mathematics of Senior High School Students in Ahanta West and Mpohor Districts

Students’ attitude towards learning of mathematics has been of interest to both mathematics educators and other stakeholders. This is because students’ achievement and attitude have been described to like the siemese twin; almost impossible to separate. The concerns have been on how to improve students’ attitude towards mathematics. The study examined the impact of assessment as learning on attitudes on mathematics among Senior High School students in Ahanta West and Mpohor Districts. Quasi-experimental pre-test/ post-test control group design was adopted for the study. Multi-stage sampling techniques were applied to generate a sample of 81 participants comprising 32 in the experimental group and 49 in the control group. A questionnaire was mainly used for the data collection. A questionnaire on attitudes was administered students to determine classes with no significant difference in attitudes towards Mathematics. Then a training package with assessment as learning and a similar package with the traditional assessment methods were administered to the Experimental group and control group respectively. Finally, post intervention questionnaire on attitudes were administered to both groups. The results revealed SHS students in the experimental group have positive attitudes towards mathematics than those in the control group. Also gender has no significant effect on attitude towards mathematics in the face of assessment as learning.

The Effects of a Health Literacy Training Intervention on Self-Care Behaviors and Treatment Adherence in Patients with Ischemic Heart Diseases

Objectives: This study examined the effect of a health literacy training intervention on self-care behaviors and treatment adherence in patients with ischemic heart disease (IHD). Methods: A quasi-experimental study was conducted in 2020, on 50 patients with IHD referred to a medical center in Kashan, Iran. The patients were assigned to a control group (n=25) and an intervention (n=25) group via a block randomization method. The intervention group received a health literacy training intervention, while the control group did not. The "Adherence to Treatment Questionnaire" and the "Self-Care Behavior Questionnaire" were used to gather the data at the start and the end of the study. Results: The mean baseline self-care behaviors in the intervention and the control groups were 61.56±10.99 and 56.25±8.42 (p=0.061) out of 100, which then changed to 85.24±4.06 and 53.01±4.86 (p<0.001). Also, the mean baseline treatment adherence in the intervention and the control groups were 84.77±29.19 and 84.40±13.89 (p=0.315) out of 200, which then changed to 179.08±8.59 and 95.76±9.24 (p<0.001). Conclusion: The health literacy training intervention could improve self-care behaviors and treatment adherence in patients with IHD. Nurses and the medical team are recommended to implement similar packages to improve the health literacy of patients with IHD. Keywords: Health literacy, Patients education, Ischemic heart disease, Self-care behaviors, Treatment adherence

Enabling Product Recognition and Tracking Based on Text Detection for Mobile Augmented Reality

We propose a system that supports real-time product recognition and tracking based on text detection for mobile augmented reality. To accurately distinguish products with visually similar packages, we develop a method that recognizes product names by utilizing the characteristics of texts printed on the product packages. It first filters out irrelevant products and effectively ranks candidate products through an inverted index search. We significantly reduce processing overhead by selectively performing product name recognition. In addition, we present an optical-flow-based method that enables efficient and responsive product tracking. Our evaluation shows that the proposed system achieves significantly better product recognition accuracy (80%) compared to alternative solutions, Vuforia (55.4%) and MobileNetV2 (69.6%). We also show that it achieves reasonable tracking accuracy and processing latency to support quality mobile AR experiences.

Phone App to Perform Quality Control of Pesticide Spray Applications in Field Crops

It has been recognized for decades that low and inconsistent spray coverages of pesticide applications represent a major challenge to successful and sustainable crop protection. Deployment of water-sensitive spray cards combined with image analysis can provide valuable and quantitative insight into spray coverage. Herein we provide description of a novel and freely available smartphone app, “Smart Spray”, for both iOS and Android smart devices (iOS and Google app stores). More specifically, we provide a theoretical description of spray coverage, and we describe how Smart Spray and similar image-processing software packages can be used as decision support tools and quality control for pesticide spray applications. Performance assessment of the underlying pixel classification algorithm is presented, and we detail practical recommendations on how to use Smart Spray to maximize accuracy and consistency of spray coverage predictions. Smart Spray was developed as part of ongoing efforts to: (1) maximize the performance of pesticide sprays, (2) minimize pest-induced yield loss and to potentially reduce the amount of pesticide used, (2) reduce the risk of target pests developing pesticide resistance, (3) reduce the risk of spray drift, and (4) optimize spray application costs by introducing a quality control.