Conventional Analysis Methods Research Articles

The barriers and challenges of using health information technology in medication administration process for pediatrics and neonates: A qualitative study.

Children and neonates are more susceptible to diseases and are a vulnerable group in medication administration (MA). Nurses interact directly with patients, ensuring safety and preventing unintended outcomes. Health Information Technology (HIT) has transformed health care, aiding nurses in decision-making and treatment responses. Despite its benefits, technology presents challenges that must be overcome to facilitate the nursing practice. Therefore, the present study aimed to explore the barriers to HIT use in the process of MA in children and neonates in a developing country. Semi-structured face-to-face interviews were conducted with 22 health care professionals across seven pediatric and neonatal settings. Also, observations were made of these settings for 3 weeks. A qualitative analysis was performed using the conventional content analysis method, recommended by Colaizzi's seven-step approach. The results showed that the most significant barriers to adopting technology in MA process could be classified into two main categories: "inappropriate management approaches" with two sub-categories ("Managers' reluctance to adopt new technology", "lack of adequate budget for hardware resources"), and "resistance to change" with two sub-categories ("A desire to use conventional (traditional) approaches in care","cultural issues and impracticality of providing some specialized technology services"). The findings revealed MA process complexities, which have been insufficiently examined in the current literature. We have highlighted the need for improved "effectiveness of HIT systems in administering medication processes, budget for hardware resources, and managers" interest in using new technology. The present findings can guide the development of more effective and user-friendly HIT systems in pediatric and neonatal care settings.

Computer Simulation for Effective Pharmaceutical Kinetics and Dynamics: A Review.

Computer-based modelling and simulation are developing as effective tools for supplementing biological data processing and interpretation. It helps to accelerate the creation of dosage forms at a lower cost and with the less human effort required to conduct the work. This paper aims to provide a comprehensive description of the different computer simulation models for various drugs along with their outcomes. The data used are taken from different sources, including review papers from Science Direct, Elsevier, NCBI, and Web of Science from 1995-2020. Keywords like - pharmacokinetic, pharmacodynamics, computer simulation, whole-cell model, and cell simulation, were used for the search process. The use of computer simulation helps speed up the creation of new dosage forms at a lower cost and less human effort required to complete the work. It is also widely used as a technique for researching the structure and dynamics of lipids and proteins found in membranes. It also facilitates both the diagnosis and prevention of illness. Conventional data analysis methods cannot assess and comprehend the huge amount, size, and complexity of data collected by in vitro, in vivo</i>, and ex vivo</i> experiments. As a result, numerous in silico</i> computational e-resources, databases, and simulation software are employed to determine pharmacokinetic (PK) and pharmacodynamic (PD) parameters for illness management. These techniques aid in the provision of multiscale representations of biological processes, beginning with proteins and genes and progressing through cells, isolated tissues and organs, and the whole organism.

Investigating the Possibility of Nurse Prescribing Training Development in Nursing Education System in Iran

PurposeEnough medical knowledge and skills are fundamentals for nurse prescribing authority development. This study will explore the potential for developing nurse prescribing training in Iran, where nurses currently lack prescribing authority despite their strong academic nursing education. MethodsThis is a study with two phases. At first, in a conventional qualitative content analysis method, with purposive and snowball sampling, from June 2021 to March 2023, 20 participants, including 16 nurses in different clinical, managerial, educational, and policy-making settings, three physicians, and one clinical pharmacist were interviewed. Unstructured interviews were conducted face-to-face or virtually due to COVID-19. Qualitative content analysis Elo and Kyngäs 2008 was used for data analysis. In the second comparative analysis phase, four masters of science and one doctor of nursing curricula were analyzed in the existence of the nurse prescribing prerequisite courses and these five curricula and two potential masters of science in community health and critical care nursing curricula were compared with John Hopkins University curricula. ResultsIn the qualitative phase, two themes emerged: nursing education challenges and the potential for nurse prescribing training development. These were further broken down into four subthemes: inadequate nurses' knowledge in prerequisite nurse prescribing courses, unprepared educational infrastructure, treatment sector potentials, and educational potentials, with a total of 12 concepts identified. During the comparative phase, it was found that none of the nursing curricula had adequate prerequisite courses for nurse prescribing. However, the Community Health and Critical Care nursing curricula showed potential for developing nurse prescribing training. ConclusionsIn the nursing education system, there are some challenges and potentials for prescribing training, and the community health and critical care nursing curricula have the potential capacity to prepare the graduated nurses to prescribe. It needs educational and managerial policies. More developmental research and pilot studies are recommended.

Challenges and Barriers to Commercialization of Health Sciences Research Results: A Qualitative Study

Background: In today's world, due to intense competition and the rapid pace of production, exploiting knowledge and converting it into economic returns has become a critical management issue for academics and capital owners. Commercialization activities can impact the educational and research programs of universities, potentially leading to resistance against them. Objectives: The current study was conducted to identify the challenges of the commercialization process in health science research. Methods: This qualitative study was conducted between June and December 2022 in Tehran province, Iran. Data were collected using semi-structured interviews with 22 key individuals, including university management and technology experts, as well as CEOs and experts from knowledge-based companies, selected through purposive sampling. The interview guide was designed based on four in-depth interviews, theoretical foundations, and comparative study findings. The obtained data were analyzed using the conventional content analysis method in MAXQDA 10 software. Results: The challenges of the commercialization process for health sciences research results were categorized into six main themes and 16 sub-themes. The main themes identified in this study were rules and regulations, societal culture, university management and infrastructure, human resources, financial systems, and organizational cooperation with industry. Conclusions: Policymakers, especially senior health managers, can create a suitable platform for the optimal use of resources and the expansion of targeted relationships between universities and industries by incorporating economic insight into academic services. By compiling relevant laws and guidelines, optimizing resource management, achieving financial independence for universities, and increasing the productivity of health research, the high costs associated with the commercialization of academic research projects can be reduced.

Inline Raman Spectroscopy Provides Versatile Molecular Monitoring for Platelet Extracellular Vesicle Purification with Anion-Exchange Chromatography.

Extracellular vesicles (EVs) are relatively recently discovered biological nanoparticles that mediate intercellular communication. The development of new methods for the isolation and characterization of EVs is crucial to support further studies on these small and structurally heterogenous vesicles. New scalable production methods are also needed to meet the needs of future therapeutic applications. A reliable inline detection method for the EV manufacturing process is needed to ensure reproducibility and to identify any possible variations in real time. Here, we demonstrate the use of an inline Raman detector in conjunction with anion exchange chromatography for the isolation of EVs from human platelets. Anion-exchange chromatography can be easily coupled with multiple inline detectors and provides an alternative to size-based methods for separating EVs from similar-sized impurities, such as lipoprotein particles. Raman spectroscopy enabled us to identify functional groups in EV samples and trace EVs and impurities in different stages of the process. Our results show a notable separation of impurities from the EVs during anion-exchange chromatography and demonstrate the power of inline Raman spectroscopy. Compared to conventional EV analysis methods, the inline Raman approach does not require hands-on work and can provide detailed, real-time information about the sample and the purification process.

Above the roads: Unleashing unmanned aerial vehicles and image processing for traffic analysis

Road traffic surveillance using unmanned aerial vehicles is a practice that can be found especially in the field of intelligent vehicle management, which is still in the early stages of research and application. This paper presents three methods of analyzing traffic data. One method is a conventional one, based on Doppler radar detection and the other two methods analyze images captured by unmanned aerial vehicles, being based on deep learning techniques. After acquiring the images, they went through a complex processing process to eliminate noise and improve the clarity of the image, then the identification of the vehicles was done by recognizing moving objects and highlighting them either through a bounding box or through labelling. The quality of images obtained from unmanned aerial vehicles is similar to the quality of images obtained from fixed surveillance cameras. The comparative analysis of the results obtained through image processing, together with those obtained through a conventional method of traffic analysis, the Doppler radar, highlighted the fact that video detection used in intelligent vehicle management is a method that both researchers and local authorities can rely on the performance of traffic studies or the analysis of traffic incidents and accidents.

Nursing educators' experiences of cultural competence in the nursing education program: A qualitative descriptive study

BackgroundTo meet the population's increasing diversity and the health system's needs, it is necessary to prepare nursing schools to produce culturally qualified students. PurposeThis study aimed to extract the experiences of nursing educators about the cultural competence of nursing students. MethodIn this qualitative descriptive study, data were collected through in-depth, semi-structured interviews with 15 nursing educators affiliated with three medical sciences universities in southeastern Iran. Purposive data sampling and analysis were performed using Graneheim and Lundman's conventional content analysis methods. ResultsOne main theme, 5 categories, and 18 subcategories were extracted. The main theme was “cultural equality, the essence of care and education”. Categories included “Toward culturally-based caring and education”, “Charter of cultural rights”, “The need for cultural competence facilitators”, “Cultural exposure”, and “Modifying the curriculum policies”. ConclusionThis study shows that nursing educators strive to take into account students' cultural competence, even though cultural competence is not explicitly integrated into nursing curricula. The acquisition of cultural competence requires multifaceted changes in education, in clinical centers, and in the creation of cultural infrastructure.

2D/3D hierarchical porous structure of mNPC/SMOH@C to construct an electrochemical sensor for the simultaneous determination of p-acetylaminophenol and p-aminophenol

BackgroundAs persistent organic pollutants (POPs), the accumulation of p-acetylaminophenol (PAT) and p-aminophenol (PAP) in water can seriously damage the health of plants and animals, ultimately leading to threats to human health and safety. Electrochemical sensors have the advantages of being fast, inexpensive, and accurate compared to the complex, expensive, and cumbersome conventional analytical methods. In this study, we designed and synthesized composites with two-dimensional/three-dimensional (2D/3D) porous structures to construct an efficient electrochemical platform for the simultaneous detection of PAT and PAP. ResultsIn this work, a novel 3D foamy birnessite Na0.55Mn2O4·1.5H2O@C (SMOH@C) was synthesized, which was composited with 2D ordered mesoporous nanosheets (mNPC) to construct electrochemical sensors detecting PAT and PAP simultaneously. The prepared 2D/3D porous structure of mNPC/SMOH@C increased the exposure of active sites due to its large specific surface area. The introduction of a 3D carbon skeleton altered the charge transfer rate of SMOH@C, and the rich pore structure and oxygen-rich vacancies created favorable conditions for the diffusion and adsorption of PAP and PAT, which enabled the sensitive detection of PAT and PAP. The constructed mNPC/SMOH@C electrochemical sensor could simultaneously detect PAT (1 × 10−7 - 1 × 10−4 M) and PAP (5 × 10−8 - 1 × 10−4 M) with detection limits of 20.4 nM and 30.1 nM, respectively. The sensor has good repeatability (RSD <4 %) and reproducibility (RSD <4 %), and satisfactory recoveries (96.7–102.8 %) were obtained in the analysis of natural water samples. SignificanceIn this paper, for the first time, we present the synthesis of 3D foam birnessite and its composite with mNPC for the electrochemical simultaneous detection of PAT and PAP. Our proposed strategy for fabricating 2D/3D porous composites lays the foundation for the design and synthesis of other porous materials. In addition, this study provides new ideas for developing efficient and practical electrochemical sensors for detecting pollutants in aquatic environments.

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.

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-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.

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.

A Deep Learning Approach for Intrusion Detection Systems –A Review

Throughout the past decade, the researchers have developed many a number of intrusion detection systems. Some of these were developed to work on host based and some were network-based intrusion detection systems. The presented systems are combination of HIDS/NIDS and signature/anomaly based, or hybrid systems. The intrusion detection system is an intelligence system known as computational intelligence. The main goal of computational intelligence is to provide solutions to complex real-world problems. An effective IDS must use more than standard mathematical techniques and conventional analysis methods combined with soft computing techniques to synergistically create a more robust IDS. In this paper, we review three important areas of research that have significant implication for proposed framework. First, we review existing shallow learning intrusion detection systems both in machine and deep learning. In the second section, we review existing hybrid intrusion detection systems. Finally, we provide some findings and analysis of the literature studies.

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.

High-speed imaging and quantitative analysis of nonequilibrium 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, offers high spatial and temporal resolution to observe the nonequilibrium dynamics of molecules and their assemblies. This account discusses the authors’ research on developing transmission electron microscopy techniques to visualize intricate and transient interactions within molecular systems, enhancing the understanding of chemical phenomena at atomic and molecular levels.

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

PurposeThis 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/approachThe 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.FindingsThe 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/valueThis 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.

Simple Method to Assess Foam Structure and Stability using Hydrophobin and BSA as Model Systems.

The properties and arrangement of surface-active molecules at air-water interfaces influence foam stability and bubble shape. Such multiscale-relationships necessitate a well-conducted analysis of mesoscopic foam properties. We introduce a novel automated and precise method to characterize bubble growth, size distribution and shape based on image analysis and using the machine learning algorithm Cellpose. Studying the temporal evolution of bubble size and shape facilitates conclusions on foam stability. The addition of two sets of masks, for tiny bubbles and large bubbles, provides for a high precision of analysis. A python script for analysis of the evolution of bubble diameter, circularity and dispersity is provided in the Supporting Information. Using foams stabilized by bovine serum albumin (BSA), hydrophobin (HP), and blends thereof, we show how this technique can be used to precisely characterize foam structures. Foams stabilized by HP show a significantly increased foam stability and rounder bubble shape than BSA-stabilized foams. These differences are induced by the different molecular structure of the two proteins. Our study shows that the proposed method provides an efficient way to analyze relevant foam properties in detail and at low cost, with higher precision than conventional methods of image analysis.

Thermal response tests on boreholes in multi-layered ground with geothermal gradient

The design of ground source heat pump systems requires knowledge of the properties of the ground and boreholes, which are often measured through thermal response tests (TRTs). Conventional TRT analysis methods apply for uniform ground properties and undisturbed ground temperature. These assumptions become less valid for deeper boreholes, which penetrate more ground layers while the geothermal gradient becomes more important. In multi-layered ground without a geothermal gradient, conventional methods estimate the effective ground thermal conductivity kgr near the thickness-weighted average, but a geothermal gradient adds complications. In the present study simulated TRTs with quasi-steady-state and fully transient models demonstrate that the required test duration for conventional methods may become impractically large as the borehole depth increases. In general, this occurs when the dimensionless parameter |qratio| approaches 1 or less. This parameter represents the ratio of the externally imposed heat injection/extraction rate to the natural heat rate associated with the geothermal gradient. In these cases, the conventional methods do not estimate the thickness-weighted average value of kgr. On the other hand, a fully transient multi-layered ground model can determine the thickness-weighted average value of kgr. This model requires measured fluid vertical temperature profiles to estimate individual layer values of kgr within reasonable uncertainties.

The story of staying out of normal routine life in adolescent mothers in marginal areas in Urmia through the Lenz of conventional content analysis approach

BackgroundAdolescent pregnancy is a main health concern in relation to adolescent mothers and their neonates especially in deprived areas. AimThis study aimed to explore the experiences of adolescent mothers who live in deprived marginal areas in Urmia in Iran. MethodsThis 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. ConclusionBased 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.