Identifying and resolving conflict in mobile application features through contradictory feedback analysis.

As mobile applications proliferate and user feedback becomes abundant, the task of identifying and resolving conflicts among application features is crucial for delivering satisfactory user experiences. This research, motivated to align application development with user preferences, introduces a novel methodology that leverages advanced Natural Language Processing techniques. The paper showcases the use of sentiment analysis using RoBERTa, topic modeling with Non-negative matrix factorization (NMF), and semantic similarity measures from Sentence-BERT. These techniques enable the identification of contradictory sentiments, the discovery of latent topics representing application features, and the clustering of related feedback instances. The approach detects conflicts by analyzing sentiment distributions within semantically similar clusters, further enhanced by incorporating antonym detection and negation handling. It employs majority voting, weighted ranking based on rating scores, and frequency analysis of feature mentions to resolve conflicts, providing actionable insights for prioritizing requirements. Comprehensive evaluations on large-scale iOS App Store and Google Play Store datasets demonstrate the approach's effectiveness, outperforming baseline methods and existing techniques. The research improves mobile application development and user experiences by aligning features with user preferences and providing interpretable conflict resolution strategies, thereby introducing a novel approach to the field of mobile application development.

Deviation parameters of intraoral scanning with and without artificial markers versus conventional impression of total, partial and congenital nasal defects: A pilot non-randomized clinical trial.

PURPOSE: This pilot clinical trial aimed to investigate accuracy of intra-oral scanning (IOS) with and without artificial reference markers in capturing total, subtotal and congenital nasal defects. BASIC PROCEDURES: Thirteen patients with 3 types of nasal defects were selected and digitally scanned using an IOS with (ScM) and without artificial markers (Sc). Patients were grouped as follows; Group T (total nasal defect), Group P (partial/subtotal nasal defect), Group C (congenital defect). Silicone impressions of the defects were made and poured to get a model that was scanned using a Desktop scanner (Imp). The standard tessellation language (STL) files obtained from IOS were registered and compared to each other using a processing software. RMS, positive and negative average values were used to report deviations between the scans. Kruskal Wallis test was used to study the effect of defect type, while Friedmann was used to study the effect of impression technique. Results were considered significant at P≤.05. MAIN FINDINGS: All deviation values showed statistically significant differences among the 3 studied nasal defects and among the 3 investigated impression techniques. The smallest deviation values were recorded in Sc-ScM of congenital defects (RMS= 0.13±0.04, +average=0.08±0.01, -average=-0.09±0.02), while the largest deviation values were recorded in IMP-Sc in the total defects (RMS= 0.38±0.05, +average=0.29±0.04, -average=-0.29±0.04). CONCLUSIONS: Within the limitations of this study, it was concluded that the nasal defect type and the use of artificial markers during scanning affect the deviation parameters of the obtained scan. The combined effect of the studied parameters calls for the use of markers in when scanning total nasal defects.

Passively sensing smartphone use in teens with rates of use by sex and across operating systems.

Youth screen media activity is a growing concern, though few studies include objective usage data. Through the longitudinal, U.S.-based Adolescent Brain Cognitive Development (ABCD) Study, youth (mage = 14; n = 1415) self-reported their typical smartphone use and passively recorded three weeks of smartphone use via the ABCD-specific Effortless Assessment Research System (EARS) application. Here we describe and validate passively-sensed smartphone keyboard and app use measures, provide code to harmonize measures across operating systems, and describe trends in adolescent smartphone use. Keyboard and app-use measures were reliable and positively correlated with one another (r = 0.33) and with self-reported use (rs = 0.21-0.35). Participants recorded a mean of 5 h of daily smartphone use, which is two more hours than they self-reported. Further, females logged more smartphone use than males. Smartphone use was recorded at all hours, peaking on average from 8 to 10 PM and lowest from 3 to 5 AM. Social media and texting apps comprised nearly half of all use. Data are openly available to approved investigators ( https://nda.nih.gov/abcd/ ). Information herein can inform use of the ABCD dataset to longitudinally study health and neurodevelopmental correlates of adolescent smartphone use.

Therapeutic effect of long-acting muscarinic antagonist for treating uncontrolled asthma assessed using impulse oscillometry.

BACKGROUND: In recent years, the incorporation of LAMAs into asthma therapy has been expected to enhance symptom control. However, a significant number of patients with asthma continue to experience poorly managed symptoms. There have been limited investigations on LAMA-induced airway alterations in asthma treatment employing IOS. In this study, we administered a LAMA to patients with poorly controlled asthma, evaluated clinical responses and respiratory function, and investigated airway changes facilitated by LAMA treatments using the IOS. METHODS: Of a total of 1282 consecutive patients with asthma, 118 exhibited uncontrolled symptoms. Among them, 42 switched their treatment to high-dose fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) (ICS/LABA/LAMA). The patients were then assessed using AHQ-33 or LCQ and ACT. Spirometry parameters (such as FEV1 or MMEF) and IOS parameters (such as R20 or AX) were measured and compared before and after exacerbations and the addition of LAMA. RESULTS: Of the 42 patients, 17 who switched to FF/UMEC/VI caused by dyspnea exhibited decreased pulmonary function between period 1 and baseline, followed by an increase in pulmonary function between baseline and period 2. Significant differences were observed in IOS parameters such as R20, R5-R20, Fres, or AX between period 1 and baseline as well as between baseline and period 2. Among the patients who switched to inhaler due to cough, 25 were classified as responders (n = 17) and nonresponders (n = 8) based on treatment outcomes. Among nonresponders, there were no significant differences in spirometry parameters such as FEV1 or PEF and IOS parameters such as R20 or AX between period 1 and baseline. However, among responders, significant differences were observed in all IOS parameters, though not in most spirometry parameters, between period 1 and baseline. Furthermore, significant differences were noted between baseline and period 2 in terms of FEV1, %MMEF, %PEF, and all IOS parameters. CONCLUSION: ICS/LABA/LAMA demonstrates superiority over ICS/LABA in improving symptoms and lung function, which is primarily attributed to the addition of LAMA. Additionally, IOS revealed the effectiveness of LAMA across all airway segments, particularly in the periphery. Hence, LAMA can be effective against various asthma phenotypes characterized by airway inflammation, even in real-world cases.

Investigating Indian oil sardine aggregation events in coastal waters of the southeastern Arabian sea.

The southwest coast of India experiences frequent Indian oil sardine (IOS) nearshore aggregation events, especially in the coastal waters off Kerala. These ephemeral dense IOS aggregation events are known as "Sardine Run". To investigate the reason and provide a scientific basis for these sporadic events, satellite/model-derived physical, meteorological, and biological parameters were analysed. Sea Surface Temperature during a majority of events was in the range of 26-29 °C, agreeing with the reported temperature conditions for IOS in the Arabian Sea. Additionally, a marginal lowering of SST as an effect of precipitation before most of the events might have attracted IOS towards the near-coastal waters in addition to the phytoplankton diet availability, resulting in the aggregation event. However, different scenarios also depicted coastal warming and probable hypoxic conditions in degrading IOS habitat and resulting in beach aggregation events. During most of the IOS aggregation events, the wind and surface current direction was alongshore/coastward, which complemented the propagation of live IOS shoals towards the beach.

Automatic removal of soft tissue from 3D dental photo scans; an important step in automating future forensic odontology identification.

The potential of intraoral 3D photo scans in forensic odontology identification remains largely unexplored, even though the high degree of detail could allow automated comparison of ante mortem and post mortem dentitions. Differences in soft tissue conditions between ante- and post mortem intraoral 3D photo scans may cause ambiguous variation, burdening the potential automation of the matching process and underlining the need for limiting inclusion of soft tissue in dental comparison. The soft tissue removal must be able to handle dental arches with missing teeth, and intraoral 3D photo scans not originating from plaster models. To address these challenges, we have developed the grid-cutting method. The method is customisable, allowing fine-grained analysis using a small grid size and adaptation of how much of the soft tissues are excluded from the cropped dental scan. When tested on 66 dental scans, the grid-cutting method was able to limit the amount of soft tissue without removing any teeth in 63/66 dental scans. The remaining 3 dental scans had partly erupted third molars (wisdom teeth) which were removed by the grid-cutting method. Overall, the grid-cutting method represents an important step towards automating the matching process in forensic odontology identification using intraoral 3D photo scans.

Impact of Scanbody Geometry and CAD Software on Determining 3D Implant Position.

The implementation of CAD software in the digital production of implant prosthetics stands as a pivotal aspect of clinical dentistry, necessitating high precision in the alignment of implant scanbodies. This study investigates the influence of scanbody geometry and the method of superimposing in CAD software when determining 3D implant position. A standardized titanium model with three bone-level implants was digitized to create reference STL files, and 10 intraoral scans were performed on Medentika and NT-Trading scanbodies. To determine implant position, the generated STL files were imported into the Exocad CAD software and superimposed-automatically and manually-with the scanbody geometries stored within the software's shape library. Position accuracy was determined by a comparison of the 3D-defined scanbody points from the STL matching files with those from the reference STL files. The R statistical software was used for the evaluation of the data. In addition, mixed linear models and a significance level of 0.05 were applied to calculate the p-values. The manual overlay method was significantly more accurate than the automatic overlays for both scanbody types. The Medentika scanbodies showed slightly superior precision compared to the NT-Trading scanbodies. Both scanbody geometry and the type of alignment in the CAD software significantly affect digital workflow accuracy. Manual verification and adjustment of the automatic alignment process are essential for precise implant positioning.

Forensic analysis of iOS binary cookie files.

iPhone operating system (iOS) devices utilize binary cookies as a data storage tool, encoding user-specific information within an often-neglected element of smartphone analysis. This binary format contains details such as cookie flags, expiration, and creation dates, domain, and value of the cookie. These data are invaluable for forensic investigations. This study presents a comprehensive methodology to decode and extract valuable data from these files, enhancing the ability to recover user activity information from iOS devices. This paper provides an in-depth forensic investigation into the structure and function of iOS binary cookie files. Our proposed forensic technique includes a combination of reverse engineering and custom-built Python scripts to decode the binary structure. The results of our research demonstrate that these cookie files can reveal an array of important digital traces, including user preferences, visited websites, and timestamps of online activities. It concludes that the forensic analysis of iOS binary cookie files can be a tool for forensic investigators and cybersecurity professionals. In the rapidly evolving domain of digital forensics, this research contributes to our understanding of less-explored data sources within iOS devices and their potential value in investigative contexts.

Intrinsic signal optoretinography of dark adaptation abnormality due to rod photoreceptor degeneration.

This research aims to investigate the potential of using intrinsic optical signal (IOS) optoretinography (ORG) to objectively detect dark adaptation (DA) abnormalities related to rod photoreceptor degeneration. Functional optical coherence tomography (OCT) was employed in both wild-type (WT) and retinal degeneration 10 (rd10) mice to conduct this assessment. Dynamic OCT measurements captured the changes in retinal thickness and reflectance from light-to-dark transition. Comparative analysis revealed significant IOS alterations within the outer retina. Specifically, a reduction in thickness from external limiting membrane (ELM) peak to retinal pigment epithelium (RPE) peak was observed (WT: 1.13 ± 0.69 µm, 30 min DA; rd10: 2.64 ± 0.86 µm, 30 min DA), as well as a decrease in the intensity of the inner segment ellipsoid zone (EZ) in 30 min DA compared to light adaptation (LA). The reduction of relative EZ intensity was notable in rd10 after 5 min DA and in WT after 15 min DA, with a distinguishable difference between rd10 and WT after 10 min DA. Furthermore, our findings indicated a significant decrease in the relative intensity of the hypo-reflective band between EZ and RPE in rd10 retinas during DA, which primarily corresponds to the outer segment (OS) region. In conclusion, the observed DA-IOS abnormalities, including changes in ELM-RPE thickness, EZ, and OS intensity, hold promise as differentiators between WT and rd10 mice before noticeable morphological abnormalities occur. These findings suggest the potential of this non-invasive imaging technique for the early detection of dysfunction in retinal photoreceptors.

Ayudando a la toma de decisiones en el diagnóstico, tratamiento y seguimiento de úlceras de etiología vascular mediante el empleo de una aplicación móvil / A mobile decision support system for diagnosis, treatment and follow-up of vascular ulcers

Introducción y objetivo: los sistemas de ayuda a la decisión médica (SADM) son sistemas computacionales que utilizan dispositivos inteligentes, lo que facilita el diagnóstico y el tratamiento de múltiples patologías, transformando la atención sanitaria en un sistema dinámico y de precisión. Las úlceras de etiología vascular representan un importante problema de salud que suponen un gran consumo de recursos. La transformación digital puede mejorarla calidad de los diagnósticos, de los tratamientos y de los seguimiento de los pacientes, mejorando la eficacia y la eficiencia de la asistencia sanitaria. El objetivo es desarrollar una aplicación móvil que facilite el diagnóstico y el tratamiento de úlceras de etiología vascular. Métodos: para desarrollar este SADM se elaboraron algoritmos para los diagnósticos y los tratamientos capaces de generar una respuesta correcta, guiando al usuario hacia un diagnóstico más probable o a la aplicación del tratamiento específico. En Android se empleó el entorno de programación Android Studio y el lenguaje de programación JAVA, y para el desarrollo en iOS se empleó XCode y el lenguaje de programación Swift. El diagnóstico de úlceras de etiología vascular incluye: úlcera neuropática, isquémica, neuroisquémica, venosa o flebostática, úlceramixta y úlcera hipertensiva o de Martorell. Resultados: UlcerAPP es visual e intuitiva. Orientará en el diagnóstico en respuesta a los algoritmos desarrollados. Además, podrá accederse al tratamiento específico de cada una de ellas. Incluirá recomendaciones de seguimiento y criterios de derivación. Conclusiones: UlcerAPP es un proyecto desarrollado para mejorar el manejo clínico de las úlceras en el entorno de la Atención Primaria y potenciar el conocimiento de la patología vascular y del tratamiento de las úlceras de dicha etiología. (AU)

Introduction and objective: decision support systems (DSS) are computer systems that use computer devicesor smartphones, facilitating the diagnosis and properly treatment of multiple pathologies, transforming healthcare into a dynamic, preventive and precision system. Vascular ulcers represent an important health problem, witha great consumption of resources. Digital transformation can improve the quality of diagnoses, treatments andpatient follow-up, and therefore improve the effectiveness and efficiency of healthcare. This paper aims to develop UlcerApp, a totally new mobile DSS for vascular ulcers management, which facilitates the diagnosis, treatment andmonitoring of ulcers of vascular etiology, in the primary health care. Methods: for achieving the main purpose of this research work, a decision algorithm will be developed and implemented by an Android (Android Studio- JAVA) and iOS (XCode- Switf ) mobile applications. Results: the App developed which implements the algorithms UlcerApp is capable of diagnose 6 kind of vascularulcers: neuropathic, ischemic, neuroischemic, venous ulcer, mixed ulcer and hypertensive or Martorell ulcer. UlcerAPP is a visual and intuitive application that will guide the user to correct diagnosis. After them, users will be able to access the specific treatment. It will include follow-up recommendations as well as referral criteria. Conclusions: UlcerAPP is a project developed to improve the clinical management of vascular ulcers in the primary health care, enhance knowledge of vascular pathology and treatment of ulcers of said etiology. (AU)

Depth of reading within the gingival sulcus of seven intraoral scanners: an in vitro study.

AIM: The present in vitro study aimed to evaluate the depth of reading of intraoral scanners (IOSs) within the gingival sulcus. MATERIALS AND METHODS: A knife-edge preparation for a full crown was performed on a Frasaco model. The gingival sulcus of the scanned model was modified using a dedicated software program (Model Creator, exocad DentalCAD 2.4 Plovdiv) by setting the apical width (AW), coronal width (CW), and gingival sulcus depth (D). Two dental models with different gingival sulcus depths (1 or 2 mm) were printed using the digital light processing (DLP) technique. Each model was scanned 10 times. Seven different IOSs were used: Emerald, Trios 3, Carestream 3600, Dental Wings DWIO, CondorScan, True Definition Scanner (TDS), and Cerec Omnicam. Measurements of D values were performed using 3Shape 3D viewer software. The normality of the data distribution was evaluated using the Shapiro-Wilk test (P < 0.05). The nonparametric Levene's test was used to check for homoscedasticity. The data were statistically analyzed using the Kruskal-Wallis test (α = 0.05) and the Nemenyi test. RESULTS: All IOSs were able to read within the 1-mm-deep gingival sulcus, albeit with some statistically significant differences (P < 0.001). TDS and Trios 3 were able to read within the 2-mm-deep gingival sulcus (P < 0.001). CONCLUSIONS: The depth of reading of different IOSs can vary significantly. In the model with a 2-mm gingival sulcus, even in the absence of oral fluids, the depth of reading was incomplete, suggesting that deep preparations into the gingival sulcus are difficult to detect with IOSs.

Beyond forced exhalation: impulse oscillometry as a promising tool for bronchial hyperresponsiveness evaluation.

Introduction: The multiple forced expiratory maneuvers that must be performed during methacholine test require a high degree of collaboration and can lead to fatigue. However, impulse oscillometry (IOS) is a noninvasive test, quick and easy to perform, that does not require effort-dependent maneuvers.Objectives: The primary endpoint was to evaluate the relationship between IOS and spirometry during the methacholine test. The secondary endpoint was to study the predictive value of baseline IOS in the development of bronchial hyperreactivity.Methods: Observational, prospective, cross-sectional study, with recruitment of consecutive patients from the pulmonology department with clinical suspicion of bronchial asthma with negative bronchodilator test and normal FeNO.Results: Twenty-five patients were included, with a mean age of 49 ± 18 years. Thirteen patients (52%) had a positive methacholine test. The correlation between IOS indices and FEV1 was significant (p < 0.05) in all cases. The indices with the highest predictive power were R5-20 and AX. The optimal cutoff points were an increase of greater than 32.96% in R5, greater than 120.83% for X5, an increase of 30.30 [kPa l-1s-1] in R5-20, and an increase of 1.01 [kPa l-1] for AX. Baseline oscillometry demonstrated a strong predictive value in the development of bronchial hyperreactivity, with a sensitivity of 61.5% and a specificity of 91.7%, using the cut-off point of 160.0% for R5.Conclusions: IOS may be a valuable alternative to forced spirometry in detecting bronchial hyperreactivity during the methacholine test, showing a good correlation between both tests.

Performance of the caries diagnosis feature of intraoral scanners and near-infrared imaging technology-A narrative review.

PURPOSE: To describe and discuss the benefits and drawbacks of various dental caries diagnostic techniques, including the use of intraoral scanners for caries diagnosis based on near-infrared imaging (NIR) technology. MATERIAL AND METHODS: A MEDLINE search from 1980-2023 focused on dental caries diagnostic techniques, emphasizing intraoral scanners using NIR technology. Alternative caries detection methods were also evaluated for their advantages and limitations, enabling a comparison with NIR. The review included traditional caries tools, the latest detection methods, and NIR's role in intraoral scanners, drawing from case reports and both in vivo and in vitro studies. Keywords like "caries detection," "intraoral scanners," and "Near Infrared Imaging (NIRI)" guided the search. After screening titles and abstracts for relevance, full texts with valuable insights were thoroughly analyzed. The data was grouped into three: traditional diagnostics, advanced digital methods, and intraoral scanner-based detection. RESULTS: This comprehensive narrative review described and discussed the current state of dental caries diagnostic methods, given the insufficient number of clinical investigations suitable for a systematic review. Traditional caries diagnosis techniques have shown variable accuracy dependent on a dentist's experience and the potential over-removal of healthy tooth structures. Intraoral scanners have emerged as a novel caries detection method, because of their integration of NIR technology. Various studies have confirmed the efficacy of NIR in detecting interproximal caries and in the early diagnosis of non-cavitated caries. Specifically, intraoral scanners have demonstrated promising results, proving comparable to established diagnostic methods like bitewing radiography. Nevertheless, while the integration of NIR into intraoral scanners seems promising, the technology still faces challenges, notably its accuracy in detecting secondary and subgingival cavities. However, with anticipated integrations of AI, NIR in intraoral scanners could revolutionize early caries detection. CONCLUSIONS: Intraoral scanners with NIR technology offer non-destructive imaging, real-time lesion visuals, and enhanced patient communication. Although comparable to bitewing radiography in some studies, a universally accepted diagnostic tool is lacking. Future research should compare them with existing methods, focusing on clinical outcomes, cost-effectiveness, and patient acceptance.

ESMira: A decentralized open-source application for collecting experience sampling data.

This paper introduces ESMira, a server and mobile app (Android, iOS) developed for research projects using experience sampling method (ESM) designs. ESMira offers a very simple setup process and ease of use, while being free, decentralized, and open-source (source code is available on GitHub). The ongoing development of ESMira started in early 2019, with a focus on scientific requirements (e.g., informed consent, ethical considerations), data security (e.g., encryption), and data anonymity (e.g., completely anonymous data workflow). ESMira sets itself apart from other platforms by both being free of charge and providing study administrators with full control over study data without the need for specific technological skills (e.g., programming). This means that study administrators can have ESMira running on their own webspace without needing much technical knowledge, allowing them to remain independent from any third-party service. Furthermore, ESMira offers an extensive list of features (e.g., an anonymous built-in chat to contact participants; a reward system that allows participant incentivization without breaching anonymity; live graphical feedback for participants) and can deal with complex study designs (e.g., nested time-based sampling). In this paper, we illustrate the basic structure of ESMira, explain how to set up a new server and create studies, and introduce the platform's basic functionalities.

A Primer on the Role of iPhone Apps in Medical and Radiology Education and How to Develop Them.

Among the numerous innovations implemented in medical education since the beginning of the 21st century, small-group learning experiences have worked well for modern students and the application of computer technology provided access to thousands of lectures, images, and slides via the internet. This has helped to build an electronic foundation on which further educational adaptations have arisen in the current era, coupled with the altered communications landscape represented by Apple's introduction of the iPhone and Google's subsequent entrance onto the playing field. With the advent of smartphone applications (apps), education has taken on an even more personalized approach. Data show that the use of educational apps has been embraced by today's nursing and medical students, notably including radiology students. We survey recent research on the use and desirability of medical apps and offer practical tips for those ready to embark on developing medical, particularly radiology, educational apps including how to assess and hone them for optimal use.

Technology Trends for Massive MIMO towards 6G.

At the dawn of the next-generation wireless systems and networks, massive multiple-input multiple-output (MIMO) in combination with leading-edge technologies, methodologies, and architectures are poised to be a cornerstone technology. Capitalizing on its successful integration and scalability within 5G and beyond, massive MIMO has proven its merits and adaptability. Notably, a series of evolutionary advancements and revolutionary trends have begun to materialize in recent years, envisioned to redefine the landscape of future 6G wireless systems and networks. In particular, the capabilities and performance of future massive MIMO systems will be amplified through the incorporation of cutting-edge technologies, structures, and strategies. These include intelligent omni-surfaces (IOSs)/intelligent reflecting surfaces (IRSs), artificial intelligence (AI), Terahertz (THz) communications, and cell-free architectures. In addition, an array of diverse applications built on the foundation of massive MIMO will continue to proliferate and thrive. These encompass wireless localization and sensing, vehicular communications, non-terrestrial communications, remote sensing, and inter-planetary communications, among others.

Short-term effect of particulate matter on lung function and impulse oscillometry system (IOS) parameters of chronic obstructive pulmonary disease (COPD) in Beijing, China.

OBJECTIVE: This study aimed to evaluate the associations between particulate matter (PM), lung function and Impulse Oscillometry System (IOS) parameters in chronic obstructive pulmonary disease (COPD) patients and identity effects between different regions in Beijing, China. METHODS: In this retrospective study, we recruited 1348 outpatients who visited hospitals between January 2016 and December 2019. Ambient air pollutant data were obtained from the central monitoring stations nearest the participants' residential addresses. We analyzed the effect of particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) exposure on lung function and IOS parameters using a multiple linear regression model, adjusting for sex, smoking history, education level, age, body mass index (BMI), mean temperature, and relative humidity . RESULTS: The results showed a relationship between PM2.5, lung function and IOS parameters. An increase of 10 µg/m3 in PM2.5 was associated with a decline of 2.083% (95% CI: -3.047 to - 1.103) in forced expiratory volume in one second /predict (FEV1%pred), a decline of 193 ml/s (95% CI: -258 to - 43) in peak expiratory flow (PEF), a decline of 0.932% (95% CI: -1.518 to - 0.342) in maximal mid-expiratory flow (MMEF); an increase of 0.732 Hz (95% CI: 0.313 to 1.148) in resonant frequency (Fres), an increase of 36 kpa/(ml/s) (95% CI: 14 to 57) in impedance at 5 Hz (Z5) and an increase of 31 kpa/(ml/s) (95% CI: 2 to 54) in respiratory impedance at 5 Hz (R5). Compared to patients in the central district, those in the southern district had lower FEV1/FVC, FEV1%pred, PEF, FEF75%, MMEF, X5, and higher Fres, Z5 and R5 (p < 0.05). CONCLUSION: Short-term exposure to PM2.5 was associated with reductions in lung function indices and an increase in IOS results in patients with COPD. The heavier the PM2.5, the more severe of COPD.

CardinalKit: open-source standards-based, interoperable mobile development platform to help translate the promise of digital health.

Smartphone devices capable of monitoring users' health, physiology, activity, and environment revolutionize care delivery, medical research, and remote patient monitoring. Such devices, laden with clinical-grade sensors and cloud connectivity, allow clinicians, researchers, and patients to monitor health longitudinally, passively, and persistently, shifting the paradigm of care and research from low-resolution, intermittent, and discrete to one of persistent, continuous, and high resolution. The collection, transmission, and storage of sensitive health data using mobile devices presents unique challenges that serve as significant barriers to entry for care providers and researchers alike. Compliance with standards like HIPAA and GDPR requires unique skills and practices. These requirements make off-the-shelf technologies insufficient for use in the digital health space. As a result, budget, timeline, talent, and resource constraints are the largest barriers to new digital technologies. The CardinalKit platform is an open-source project addressing these challenges by focusing on reducing these barriers and accelerating the innovation, adoption, and use of digital health technologies. CardinalKit provides a mobile template application and web dashboard to enable an interoperable foundation for developing digital health applications. We demonstrate the applicability of CardinalKit to a wide variety of digital health applications across 18 innovative digital health prototypes.

COVID-19 advising application development for Apple devices (iOS).

One of humanity's most devastating health crises was COVID-19. Billions of people suffered during this pandemic. In comparison with previous global pandemics that have been faced by the world before, societies were more accurate with the technical support system during this natural disaster. The intersection of data from healthcare units and the analysis of this data into various sophisticated systems were critical factors. Different healthcare units have taken special consideration to advance technical inputs to fight against such situations. The field of natural language processing (NLP) has dramatically supported this. Despite the primitive methods for monitoring the bio-metric factors of a person, the use of cognitive science has emerged as one of the most critical features during this pandemic era. One of the essential features is the potential to understand the data based on various texts and user inputs. The deployment of various NLP systems is one of the most challenging factors in handling the bulk amount of data flowing from multiple sources. This study focused on developing a powerful application to advise patients suffering from ailments related to COVID-19. The use of NLP refers to facilitating a user to identify the present critical situation and make necessary decisions while getting infected. This article also summarises the challenges associated with NLP and its usage for future NLP-based applications focusing on healthcare units. There are a couple of applications that reside for android-based systems as well as web-based chat-bot systems. In terms of security and safety, application development for iOS is more advanced. This study also explains the block meant of an application for advising COVID-19 infection. A natural language processing powered application for an iOS operating system is indeed one of its kind, which will help people who need to advise proper guidance. The article also portrays NLP-based application development for healthcare problems associated with personal reporting systems.

Non-Invasive Disease Specific Biomarker Detection Using Infrared Spectroscopy: A Review.

Many life-threatening diseases remain obscure in their early disease stages. Symptoms appear only at the advanced stage when the survival rate is poor. A non-invasive diagnostic tool may be able to identify disease even at the asymptotic stage and save lives. Volatile metabolites-based diagnostics hold a lot of promise to fulfil this demand. Many experimental techniques are being developed to establish a reliable non-invasive diagnostic tool; however, none of them are yet able to fulfil clinicians' demands. Infrared spectroscopy-based gaseous biofluid analysis demonstrated promising results to fulfil clinicians' expectations. The recent development of the standard operating procedure (SOP), sample measurement, and data analysis techniques for infrared spectroscopy are summarized in this review article. It has also outlined the applicability of infrared spectroscopy to identify the specific biomarkers for diseases such as diabetes, acute gastritis caused by bacterial infection, cerebral palsy, and prostate cancer.