Conventional Analysis Methods Research Articles

Examining the educational experiences of Behvarzes from the insufficient participation of some people in preventive measures against the COVID-19 pandemic: a lesson for the future

BackgroundThis study aims to explore the experiences of Behvarzes regarding the reasons behind the insufficient participation of some individuals with the preventive protocols established during the COVID-19 pandemic.MethodsA qualitative study was conducted from July 2021 to December 2022 using the conventional content analysis method. Purposive sampling was employed to select 14 Behvarzes working in villages covered by Kashan University of Medical Sciences. Data were collected through semi-structured in-depth individual interviews and analyzed using conventional content analysis.ResultsThe study identified seven subcategories which were grouped into two main categories of reasons for inadequate compliance with health protocols by some individuals. These include: (1) Intentional non-compliance with preventive protocols, with the following subcategories: perceived obligation and adherence to social customs, denial of risk, belief in external health locus of control, and fear and distrust of prevention and treatment methods. (2) Unintentional non-compliance with preventive protocols, with the following subcategories: insufficient or contradictory information, negligence, and inevitability.ConclusionThe findings suggest that ensuring compliance with health guidelines is not a one-size-fits-all approach. providing empowerment and obstacle removal solutions to those forced to violate preventive protocols for various reasons are all critical components of successful interventions. Also, cultural familiarity can aid in the design of appropriate interventions to address these challenges.

High-Speed Imaging and Quantitative Analysis of Non-Equilibrium Stochastic Processes Using Atomic-Resolution Electron Microscopy

Abstract Chemical phenomena are inherently complex and stochastic, making them difficult to fully understand using conventional ensemble-averaged analytical methods. These methods primarily capture long-lived species and common structural features, limiting the study of transient intermediates and minute structural characteristics. In contrast, single-molecule time-resolved analysis using advanced microscopy techniques, particularly transmission electron microscopy (TEM), offers high spatial and temporal resolution to observe the nonequilibrium dynamics of molecules and their assemblies. This account discusses the authors’ research on developing TEM techniques to visualize intricate and transient interactions within molecular systems, enhancing the understanding of chemical phenomena at atomic and molecular levels.

Perceived vulnerability related to health in cancer post-treated adolescent in Iran: a content analysis

BackgroundThe prevalence of cancer is increasing, which significantly impacts the health and various aspects of the lives of cancer-post-treated adolescents. Adolescents with cancer have many negative consequences, including increased vulnerability. Therefore, this study aimed to explore the perceived vulnerability of cancer-post-treated adolescents using a deep examination of experiences and perceptions of participants.MethodsThis study was conducted on 18 participants, who were selected based on purposive sampling in 2023 using a qualitative method through a content analysis approach in Iran. A face-to-face and semi-structured individual interview was used to collect data. Inclusion criteria were children aged 11–19 years, with no history of diseases except cancer, at least one year passed since their last treatment and were aware of their disease. Inclusion criteria for other participants were Parents of childhood cancer survivors whose child is under 19 years old. Health care providers that had at least one year of experience working with and caring for pediatric cancer survivors. The research objective, participation principle, and interview recording were explained to the participants before the interview started. The criteria of credibility, dependability, confirmability and transferability were included to support the trustworthiness of data. The data was analyzed using the conventional qualitative content analysis method and MAXQDA10 software was used for data management.ResultsThe participants included 12 cancer-post-treated adolescents, two parents, two nurses, one doctor, and one cancer charity representative. The data analysis identified three categories: “Confusion in early adolescence”, “Psychological turmoil of disease”, and “Physical burden of the disease”. Finally, the latent content was formulated in to a “Perceived vulnerability” overarching theme.ConclusionIdentifying the patient’s perceptions and beliefs is one of the current health problems to improve the quality of life and facilitate the optimal transition from adolescence to adulthood and adult care. Health professionals have an opportunity to address factors that increase survivors’ sense of vulnerability to health problems by correcting knowledge gaps.

Advancing predictive maintenance: a deep learning approach to sensor and event-log data fusion

Purpose This study aims to introduce an innovative approach to predictive maintenance by integrating time-series sensor data with event logs, leveraging the synergistic potential of deep learning models. The primary goal is to enhance the accuracy of equipment failure predictions, thereby minimizing operational downtime. Design/methodology/approach The methodology uses a dual-model architecture, combining the patch time series transformer (PatchTST) model for analyzing time-series sensor data and bidirectional encoder representations from transformers for processing textual event log data. Two distinct fusion strategies, namely, early and late fusion, are explored to integrate these data sources effectively. The early fusion approach merges data at the initial stages of processing, while late fusion combines model outputs toward the end. This research conducts thorough experiments using real-world data from wind turbines to validate the approach. Findings The results demonstrate a significant improvement in fault prediction accuracy, with early fusion strategies outperforming traditional methods by 2.6% to 16.9%. Late fusion strategies, while more stable, underscore the benefit of integrating diverse data types for predictive maintenance. The study provides empirical evidence of the superiority of the fusion-based methodology over singular data source approaches. Originality/value This research is distinguished by its novel fusion-based approach to predictive maintenance, marking a departure from conventional single-source data analysis methods. By incorporating both time-series sensor data and textual event logs, the study unveils a comprehensive and effective strategy for fault prediction, paving the way for future advancements in the field.

Advancing predictive maintenance: a deep learning approach to sensor and event-log data fusion

Purpose This study aims to introduce an innovative approach to predictive maintenance by integrating time-series sensor data with event logs, leveraging the synergistic potential of deep learning models. The primary goal is to enhance the accuracy of equipment failure predictions, thereby minimizing operational downtime. Design/methodology/approach The methodology uses a dual-model architecture, combining the patch time series transformer (PatchTST) model for analyzing time-series sensor data and bidirectional encoder representations from transformers for processing textual event log data. Two distinct fusion strategies, namely, early and late fusion, are explored to integrate these data sources effectively. The early fusion approach merges data at the initial stages of processing, while late fusion combines model outputs toward the end. This research conducts thorough experiments using real-world data from wind turbines to validate the approach. Findings The results demonstrate a significant improvement in fault prediction accuracy, with early fusion strategies outperforming traditional methods by 2.6% to 16.9%. Late fusion strategies, while more stable, underscore the benefit of integrating diverse data types for predictive maintenance. The study provides empirical evidence of the superiority of the fusion-based methodology over singular data source approaches. Originality/value This research is distinguished by its novel fusion-based approach to predictive maintenance, marking a departure from conventional single-source data analysis methods. By incorporating both time-series sensor data and textual event logs, the study unveils a comprehensive and effective strategy for fault prediction, paving the way for future advancements in the field.

IMAX FRET (Information Maximized FRET) for Multipoint Single-Molecule Structural Analysis.

Understanding the structure of biomolecules is vital for deciphering their roles in biological systems. Single-molecule techniques have emerged as alternatives to conventional ensemble structure analysis methods for uncovering new biology in molecular dynamics and interaction studies, yet only limited structural information could be obtained experimentally. Here, we address this challenge by introducing iMAX FRET, a one-pot method that allows ab initio 3D profiling of individual molecules using two-color FRET measurements. Through the stochastic exchange of fluorescent weak binders, iMAX FRET simultaneously assesses multiple distances on a biomolecule within a few minutes, which can then be used to reconstruct the coordinates of up to four points in each molecule, allowing structure-based inference. We demonstrate the 3D reconstruction of DNA nanostructures, protein quaternary structures, and conformational changes in proteins. With iMAX FRET, we provide a powerful approach to advance the understanding of biomolecular structure by expanding conventional FRET analysis to three dimensions.

Quantification of cooking oil fumes using non-catalytic transesterification: A reliable method for indoor air quality assessment

Cooking oil fumes (COFs), which are aerosols formed via the interaction of water and oil (triglycerides, TGs), contribute to the incidence of lung cancer. Control of indoor COF concentrations has not yet been established, as reliable methods for quantifying COFs have not been developed. This study aimed to quantify COFs based on the derivatization of TGs via a non-catalytic transesterification reaction. Our investigation into the thermolytic behaviors of oil confirmed that COFs generated at ≤ 200 °C primarily consisted of oil and water vapor. Alkali-catalyzed transesterification is commonly used for the derivatization of TGs. However, it is sensitive to impurities such as free fatty acids and water, leading to side reactions. Furthermore, this reaction requires additional purification steps to separate the catalyst and has long reaction times (≥120 min). In contrast, non-catalytic transesterification is not sensitive to impurities and can achieve a conversion yield of over 97 wt% within 1 min. The conversion yield of non-catalytic transesterification was higher than that of the alkali-catalyzed method, indicating that non-catalytic transesterification could be a more reliable method for quantifying COFs. Additionally, the concentration of COFs determined using non-catalytic derivatization was higher than that obtained using the conventional aerosol analysis method (PM gravimetric method). This approach addresses a critical gap in current practices, offering a valuable tool for assessing and regulating COF levels in indoor spaces. Consequently, this contributes to broader efforts aimed at mitigating potential adverse health effects associated with exposure to COFs.

Highly Sensitive Two-dimensional Profiling of N-linked Glycans by Hydrophilic Interaction Liquid Chromatography and Dual Stacking Capillary Gel Electrophoresis

BackgroundN-Glycosylation is one of the most important post-translational modifications in proteins. As the N-glycan profiles in biological samples are diverse and change according to the pathological condition, various profiling methods have been developed, such as liquid chromatography (LC), capillary electrophoresis (CE), and mass spectrometry. However, conventional analytical methods have limitations in sensitivity and/or resolution, hindering the discovery of minor but specific N-glycans that are important both in the basic glycobiology research and in the medical application as biomarkers. Therefore, a highly sensitive and high-resolution N-glycan profiling method is required. ResultsIn this study, we developed a novel two-dimensional (2D) separation system, which couples hydrophilic interaction liquid chromatography (HILIC) with capillary gel electrophoresis (CGE) via large-volume dual preconcentration by isotachophoresis and stacking (LDIS). Owing to the efficient preconcentration efficiency of LDIS, limit of detection reached 12 pM (60 amol, S/N = 3) with good calibration curve linearity (R2 > 0.999) in the 2D analysis of maltoheptaose. Finally, 2D profiling of N-linked glycans obtained from standard glycoproteins and cell lysates were demonstrated. High-resolution 2D profiles were successfully obtained by data alignment using triple internal standards. N-glycans were well distributed on the HILIC/CGE 2D plane based on the glycan size, number of sialic acids, linkage type, and so on. As a result, specific minor glycans were successfully identified in HepG2 and HeLa cell lysates. Significance and NoveltyIn conclusion, the HILIC/CGE 2D analysis method showed sufficient sensitivity and resolution for identifying minor but specific N-glycans from complicated cellular samples, indicating the potential as a next-generation N-glycomics tool. Our novel approach for coupling LC and CE can also dramatically improve the sensitivity in other separation modes, which can be a new standard of 2D bioanalysis applicable not only to glycans, but also to other diverse biomolecules such as metabolites, proteins, and nucleic acids.

The Story of Staying Out of The Normal Routine Life in Adolescent Mothers in Marginal Areas in Urmia through the Lenz of Conventional Content Analysis Approach

Background: Adolescent pregnancy is a main health concern in relation to adolescent mothers and their neonates especially in deprived areas Aim: This study aimed to explore the experiences of adolescent mothers who live in deprived marginal areas in Urmia in Iran Methods: This qualitative study was conducted in 2022–2023 using the conventional content analysis approach. Participants were eighteen adolescent mothers purposefully selected from healthcare centers in marginal areas in Urmia. Data were gathered via semi-structured interviews and were analyzed by the conventional content analysis method proposed by Graneheim and Lundman Findings: ‘‘Staying out of the life normal routine’ was the main theme consisted of four categories ‘forced early marriage', 'experience of abuse', 'learned helplessness', and 'impulses of hope under the shadow of motherhood' and five sub-categories role conflict, lifelong regret, attachment, reviving the lost self-value and the delight of family establishment Conclusion: Based on the results of the study health care providers, especially midwives, will be oriented to deal with adolescent mothers to help them to have successful transition to motherhood.

Robust Methods for Assessing the Characteristics of Locomotor Activity Based on Markerless Video Capture Data

Introduction. Analysis of locomotor activity is essential in a number of biomedical and pharmacological research designs, as well as environmental monitoring. The movement trajectories of biological objects can be represented by time series exhibiting a complex multicomponent structure and non-stationary dynamics, thus limiting the effectiveness of conventional correlation and spectral time series analysis methods. Recordings obtained using markerless technologies are typically characterized by enhanced noise levels, including both instrumental noise and anomalous errors associated with false estimates of the location of the points of interest, as well as gaps in the trajectories, promoting an urgent need in the development of robust methods to assess the characteristics of locomotor activity.Aim. Development of robust methods for assessing the characteristics of locomotor activity capable of efficient processing of noisy recordings obtained by markerless video-based motion capture systems.Materials and methods. In order to assess the characteristics of locomotor activity, the relative movements of body parts of laboratory animals were analyzed using the stability metrics of the mutual dynamics of their trajectories, their relative delays, as well as the relative duration of the recording fragments when relatively stable mutual dynamics could be observed. The local maxima of the cross-correlation function of two body fragments, the minima of the standard deviation of the difference between their Hilbert phases, as well as their relative delays, were used as the metrics of mutual dynamics.Results. The considered phase metrics were shown to explicitly reflect changes in locomotor activity, while the assessment of time delays using phase metric was shown to be prone to periodic error. The above limitation could be largely overcome using the correlation metrics, assuming that phase and correlation metrics could be combined.Conclusion. The proposed robust methods provide stable estimates of the characteristics of locomotor activity based on markerless video capture recordings, altogether increasing the efficiency of diagnostic procedures and assessment of the therapeutic effect during rehabilitation.

A smartphone-based electrochemical sensing platform for the portable and simultaneous determination of flavonoids in Citri Reticulatae Pericarpium

BackgroundThe efficient and timely determination of polymethoxylated flavones (PMFs, primarily nobiletin and tangeretin) and flavanone glycosides (primarily hesperidin) in Citri Reticulatae Pericarpium (CRP) is of paramount importance for the production of CRP and the evaluation of its efficacy. Conventional analytical methods including chromatography-based approaches commonly provide high sensitivity and selectivity, but require bulky equipment and complicated procedures performed by professional technicians and are thus inconvenient in practical applications. Therefore, there is a clear need for portable and miniaturized sensing platforms that can rapidly and simultaneously detect PMFs and hesperidin in CRP product. ResultsA state-of-the-art three-dimensional porous graphene electrode was first fabricated by direct laser scribing of a poly(ether-ether-ketone) (PEEK) film for electrocatalysis of nobiletin, tangeretin and hesperidin. Kinetic analysis was conducted to investigate the reaction mechanisms of these three flavonoids at such prepared PEEK-laser induced graphene (PEEK-LIG) electrodes. Since the as-prepared PEEK-LIG electrodes exhibited high electrocatalytic efficiency towards these three flavonoids, a portable electrochemical sensing platform assembled with a smartphone, a miniatured electrochemical workstation, and an integrated PEEK-LIG microchip was developed. Consequently, the developed portable electrochemical sensing platforms exhibited great sensitivity and low detection limits for both PMFs and hesperidin. More importantly, tests conducted on real CRP extract samples demonstrated that the developed portable electrochemical sensing platform exhibited high validity, high reliability, as well as excellent reproducibility. SignificanceThis is the inaugural report on the portable and simultaneous determination of PMFs and hesperidin in the pericarp of Citrus Reticulata, which may be utilized for differentiating CRP products. Furthermore, the portable and powerful electrochemical sensing platforms developed could also potentially be applied for a wide range of analytes, thanks to their simple and rapid fabrication and determination processes.

The Open SprayBot: A high-throughput paper spray mass spectrometry platform for disease screening

Newborn disease screening increases survival, improves quality of life and reduces treatment costs for healthcare systems. Mass spectrometry (MS) is an effective method for metabolic screening. However, conventional analytical methods require biofluid handling and cooling conditions during transport, making the logistics difficult and expensive, especially for remote regions. ’Paper-spray’ (PS) ionization generates a charged solvent spray from samples deposited on paper strips. Therefore, samples can be applied on a suitable matrix and shipped as dried spots to diagnostic laboratories with standard postal or messenger services. We built a robotic platform, the ’Open SprayBot’, to automatically analyze paper-deposited samples via PS-MS and increase the sample throughput. The system is operated via RUMBA32 and Arduino Mega boards. A commercial syringe pump and power supply provide solvent application and electrical current required for PS-MS. The usability of the Open SprayBot was demonstrated by quantifying palmitoyl-l-carnitine, a common biomarker in newborn screening.

Quantification of membrane fluidity in bacteria using TIR-FCS

Plasma membrane fluidity is an important phenotypic feature that regulates the diffusion, function, and folding of transmembrane and membrane-associated proteins. In bacterial cells, variations in membrane fluidity are known to affect respiration, transport, and antibiotic resistance. Membrane fluidity must therefore be tightly regulated to adapt to environmental variations and stresses such as temperature fluctuations or osmotic shocks. Quantitative investigation of bacterial membrane fluidity has been, however, limited due to the lack of available tools, primarily due to the small size and membrane curvature of bacteria that preclude most conventional analysis methods used in eukaryotes. Here, we develop an assay based on total internal reflection-fluorescence correlation spectroscopy (TIR-FCS) to directly measure membrane fluidity in live bacteria via the diffusivity of fluorescent membrane markers. With simulations validated by experiments, we could determine how the small size, high curvature, and geometry of bacteria affect diffusion measurements and correct subsequent measurements for unbiased diffusion coefficient estimation. We used this assay to quantify the fluidity of the cytoplasmic membranes of the Gram-positive bacteria Bacillus subtilis (rod-shaped) and Staphylococcus aureus (coccus) at high (37°C) and low (20°C) temperatures in a steady state and in response to a cold shock, caused by a shift from high to low temperature. The steady-state fluidity was lower at 20°C than at 37°C, yet differed between B. subtilis and S. aureus at 37°C. Upon cold shock, the membrane fluidity decreased further below the steady-state fluidity at 20°C and recovered within 30 min in both bacterial species. Our minimally invasive assay opens up exciting perspectives for the study of a wide range of phenomena affecting the bacterial membrane, from disruption by chemicals or antibiotics to viral infection or change in nutrient availability.

Rapid Measurement of Antioxidant Properties of Dendrobium officinale Using Near-Infrared Spectroscopy and Chemometrics.

Dendrobium officinale (D. officinale), often used as a dual-use plant with herbal medicine and food applications, has attracted considerable attention for health-benefiting components and wide economic value. The antioxidant ability of D. officinale is of great significance to ensure its health care value and safeguard consumers' interests. However, the common analytical methods for evaluating the antioxidant ability of D. officinale are time-consuming, laborious, and costly. In this study, near-infrared (NIR) spectroscopy and chemometrics were employed to establish a rapid and accurate method for the determination of 2,2'-azinobis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) scavenging capacity, 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging capacity, and ferric reducing antioxidant power (FRAP) in D. officinale. The quantitative models were developed based on the partial least squares (PLS) algorithm. Two wavelength selection methods, namely the genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) method, were used for model optimization. The CARS-PLS models exhibited superior predictive performance compared to other PLS models. The root mean square errors of cross-validation (RMSECVs) for ABTS, FRAP, and DPPH were 0.44%, 2.64 μmol/L, and 2.06%, respectively. The results demonstrated the potential application of NIR spectroscopy combined with the CARS-PLS model for the rapid prediction of antioxidant activity in D. officinale. This method can serve as an alternative to conventional analytical methods for efficiently quantifying the antioxidant properties in D. officinale.

Transition experiences of patients with post stroke dysphagia and family caregivers: A longitudinal, qualitative study.

Stroke patients with dysphagia and family caregivers will experience multiple transitions during the whole process of the disease and various nursing needs will be generated. There is a lack of knowledge about their experiences at different transition stages. Thus, we aimed to explore the transition experiences of patients with post stroke dysphagia and family caregivers from admission to discharge home. A semi-structured interview based on Meleis's transition theory was used during hospitalization and telephone follow-up interviews were conducted in the first, third, and sixth month after the diagnosis of dysphagia. Interview transcripts were analyzed using the conventional content analysis method. A total of 17 participants enrolled in the first face-to-face interview, 16 participants took part in the first month's telephone follow-up interview, 14 participants in the third month, and 12 participants in the sixth month. The transition experiences of patients with post stroke dysphagia and family caregivers could be summarized into three themes: (1)transition from onset to admission; (2)transition from discharge to other rehabilitation institutions; and (3)transition from discharge to home. Each theme had identified interrelated subthemes. The experiences of patients with post stroke dysphagia and family caregivers during transition are a dynamic process with enormous challenges in each phase. Collaboration with health care professionals, follow-up support after discharge, and available community and social support should be integrated into transitional nursing to help patients facilitate their transition.

Identification of key genes and pathways in duck fatty liver syndrome using gene set enrichment analysis

High-laying ducks are often fed high-energy, nutritious feeds to maintain high productivity, which predisposes them to lipid metabolism disorders and the development of fatty liver syndrome (FLS), which seriously affects production performance and has a substantial economic impact on the poultry industry. Therefore, it is necessary to elucidate the mechanisms underlying the development of fatty liver syndrome. In this study, seven Shan Partridge ducks, each with fatty liver syndrome and normal laying ducks, were selected, and Hematoxylin Eosin staining (HE staining), Masson staining, and transcriptome sequencing were performed on liver tissue. In addition to exploring key genes and pathways using conventional analysis methods, we constructed the first Kyoto Encyclopedia of Genes and Genomes (KEGG) database-based predefined gene set containing 12,764 pathways and 16,836 genes and further performed gene set enrichment analysis (GSEA) on the liver transcriptome data. Finally, key nodes and biological processes were identified via the protein-protein interaction (PPI) network. The results showed that the liver in the FL group exhibited steatosis and fibrosis, and a total of 3,663 genes with upregulated expression versus 2,296 downregulated genes were screened by conventional analysis. GSEA analysis and PPI network analysis revealed that the liver in the FL group exhibited disruption of the mitochondrial electron transport chain, leading to decreased oxidative phosphorylation and the secretion of excessive proinflammatory factors amid the continuous accumulation of lipids. Under continuous chronic inflammation, cell cycle arrest triggers apoptosis, while fibrosis becomes more severe, and procarcinogenic genes are activated, leading to the continuous development and deterioration of the liver. In conclusion, the predefined gene set constructed in this study can be used for GSEA, and the identified hub genes provide useful reference data and a solid foundation for the study of the genetic regulatory mechanism of fatty liver syndrome in ducks.

Care Bermuda, families of the patients with chronic mental disorders in Iran surrounded by psychosocial problems and needs: a qualitative study

Background: A mental disorder is characterized by a clinically significant impairment of cognition, emotion regulation, or behavior. As a result of the shift in care from medical centers and hospitals to home care, we now see a change in the treatment of patients with chronic mental disorders. Consequently, families have become the main support system in the progressive care of these patients, leading to psychological and social problems. The current qualitative study investigated the social and psychological health needs and problems of family caregivers of patients with chronic mental disorders in Iran’s cultural and social context. Methods: This was a content analysis qualitative study. The study was conducted in three psychiatric hospitals in Farabi, Noor, Modares. Purposive sampling was done and continued until data saturation. Semi-structured, face-to-face, and individual interviews were conducted with 49 participants (15 family caregivers of patients with CMD and 34 members of the mental health care team). Data analysis was done using the conventional content analysis method. Results: Eight hundred seventy-five primary codes were obtained, which were classified into 10 subcategories and 3 main categories of ʻhealth challenges of caregiverʼ, ʻconfused concept of careʼ and “the need for a coherent support system. Conclusion: In Iranian society, after the patient is discharged from the hospital or care center, family members will change their role to the most important caregivers of these patients. The psychological and social health of these caregivers is destroyed because of the problems they have in providing care for their patients and their needs, which are not met.

Building functional networks for complex response analysis in systems of coupled nonlinear oscillators

Some aspects of engineering dynamics, such as nonlinearities and transient motion of many interconnected parts, remain difficult to handle today. To comply with increasing demands on resilience and safety, the dynamics of large machines need to be better understood. Complex network methods, already present in many scientific disciplines, provide a tool set complementary to conventional methods of system analysis. This work aims at providing a new, function-based view on mechanical systems by generating functional networks. To this end, a network algorithm is applied to sets of cyclically coupled Duffing oscillators as a common example of a complex nonlinear mechanical system. In the functional network, each node represents an oscillator while the direction of the network edges represents a functional coupling. Results show that the network method is capable of identifying dynamical transitions and synchronization between components, as well as determining the number of different states present within a system. Additionally, the time evolution of the component interactions, especially in response to a disturbance, is studied via a sliding-window approach. The results of this analysis might hopefully open new ways for a more efficient system analysis through optional sensor placement, and for effective countermeasures against unwanted dynamics through improved analysis of transient dynamics.

The experiences of patients with COVID-19 and their relatives from receiving professional home care nursing: a qualitative content analysis

BackgroundTo overcome of patients with COVID-19 over the capacity of hospitals and mild to moderate severity of the disease in most cases, the World Health Organization and the Centers for Disease Control and Prevention in the United States, recommend home care for these patients. Receiving care at home will face challenges that can be context-based, especially in crises like the Coronavirus pandemic. The present study aimed to describe the experiences of patients with COVID-19 and their relatives from receiving professional home care nursing.MethodsThis study was conducted using a qualitative content analysis method. Nine participants with COVID-19 who were receiving home care nursing in Semnan participated in this study. The purposive sampling method was used. Sampling continued until no new categories appeared, meaning the category’s theoretical saturation. Deep and semi-structured interviews were used to collect data based on the research question. Data was analyzed using the conventional content analysis method using Graneheim and Lundman’s approach.ResultsAfter analyzing the interviews and comparing codes based on similarities and differences, three main themes, 11 categories, and 30 subcategories were identified. The main themes included “The value of home care” (personalization of care, being economical, providing intellectual security, and reducing the concern of family), “Comprehensive care” (professional commitment, empathy, mastery in care, and patronage), and “Care challenges” (cultural barriers, inadequate services, and lack of information about costs and conditions).ConclusionThe patients with COVID-19 who received professional nursing care at home mentioned some challenges, such as the caregiver not being of the same sex as the patient, delay in receiving the service, the inadequacy of the centers, the limitation of the right to choose the care provider, and insufficient information about the cost of services received before receiving each care.

Ion-selective paper-based chromogenic strip and electrochemical sensor for the detection of ammonium ions

The fraudulent practice of adding ammonium salts to milk in order to enhance the nitrogen content has serious health implications including renal failure. Ammonium ion detection has been targeted through the conventional analytical methods however, lack of portability and complex operation limits their use for field applications. In this scenario, paper-based test strips and electrochemical sensors can provide strategies for point-of-test applications. Here, an ion-selective paper-based chromogenic strip and an electrochemical sensor has been developed for detection and quantification of ammonium ions. The developed paper-based chromogenic strip showed detection limit of 0.008 % (w/v) for ammonium ions, whereas, electrochemical sensor showed an LOD of 0.0062 ± 0.0023 % (w/v) with a sensitivity of 1.6 × 10−5 A.% −1.mm−2. The developed paper-based chromogenic strip and electrochemical sensor can be employed by regulatory bodies and dairy industries to ensure the safety and quality of milk.