Impact of QR-Codes as a Disruptive Technology During the Covid-19 Contagion

Introduction In the world economy, QR codes became very popular, and their prominence is expanding rapidly. The QR-codes look a bit like barcodes, but are made up of square patterns. As businesses are increasingly embracing these technologies, QR codes are becoming more popular, QR code readers are being integrated into smartphones. Apple released iOS 11 to search QR codes using the smartphone camera back in 2017 which is now a game-changing marketing strategy for businesses and retailers. Objective: The objective of the paper is to conduct an extensive theoretical review on the growth of QR codes in the digital era and QR codes' reach as contactless payment solutions. Methodology: A bibliometric review by refereeing quality articles published in highly ranked journal. Conclusion: When the QR code reader was integrated into the new Android smartphone camera, it proved to be a key differentiator.  Following the global COVID-19 contagion, there has been a nudge for contactless activities and remote resource allocation, such as online work, payments and online classes among others. QR-codes have seen a spectacular increase in usage across all aspects of life

MOCF: A Multi-Objective Clustering Framework using an Improved Particle Swarm Optimization Algorithm

Traditional clustering algorithms, such as K-Means, perform clustering with a single goal in mind. However, in many real-world applications, multiple objective functions must be considered at the same time. Furthermore, traditional clustering algorithms have drawbacks such as centroid selection, local optimal, and convergence. Particle Swarm Optimization (PSO)-based clustering approaches were developed to address these shortcomings. Animals and their social Behaviour, particularly bird flocking and fish schooling, inspire PSO. This paper proposes the Multi-Objective Clustering Framework (MOCF), an improved PSO-based framework. As an algorithm, a Particle Swarm Optimization (PSO) based Multi-Objective Clustering (PSO-MOC) is proposed. It significantly improves clustering efficiency. The proposed framework's performance is evaluated using a variety of real-world datasets. To test the performance of the proposed algorithm, a prototype application was built using the Python data science platform. The empirical results showed that multi-objective clustering outperformed its single-objective counterparts

Arabidopsis mRNA polyadenylation machinery: comprehensive analysis of protein-protein interactions and gene expression profiling

BACKGROUND: The polyadenylation of mRNA is one of the critical processing steps during expression of almost all eukaryotic genes. It is tightly integrated with transcription, particularly its termination, as well as other RNA processing events, i.e. capping and splicing. The poly(A) tail protects the mRNA from unregulated degradation, and it is required for nuclear export and translation initiation. In recent years, it has been demonstrated that the polyadenylation process is also involved in the regulation of gene expression. The polyadenylation process requires two components, the cis-elements on the mRNA and a group of protein factors that recognize the cis-elements and produce the poly(A) tail. Here we report a comprehensive pairwise protein-protein interaction mapping and gene expression profiling of the mRNA polyadenylation protein machinery in Arabidopsis. RESULTS: By protein sequence homology search using human and yeast polyadenylation factors, we identified 28 proteins that may be components of Arabidopsis polyadenylation machinery. To elucidate the protein network and their functions, we first tested their protein-protein interaction profiles. Out of 320 pair-wise protein-protein interaction assays done using the yeast two-hybrid system, 56 (approximately 17%) showed positive interactions. 15 of these interactions were further tested, and all were confirmed by co-immunoprecipitation and/or in vitro co-purification. These interactions organize into three distinct hubs involving the Arabidopsis polyadenylation factors. These hubs are centered around AtCPSF100, AtCLPS, and AtFIPS. The first two are similar to complexes seen in mammals, while the third one stands out as unique to plants. When comparing the gene expression profiles extracted from publicly available microarray datasets, some of the polyadenylation related genes showed tissue-specific expression, suggestive of potential different polyadenylation complex configurations. CONCLUSION: An extensive protein network was revealed for plant polyadenylation machinery, in which all predicted proteins were found to be connecting to the complex. The gene expression profiles are indicative that specialized sub-complexes may be formed to carry out targeted processing of mRNA in different developmental stages and tissue types. These results offer a roadmap for further functional characterizations of the protein factors, and for building models when testing the genetic contributions of these genes in plant growth and development

Non-contact tests for identifying people at risk of primary angle closure glaucoma

BACKGROUND: Primary angle closure glaucoma (PACG) accounts for 50% of glaucoma blindness worldwide. More than three-quarters of individuals with PACG reside in Asia. In these populations, PACG often develops insidiously leading to chronically raised intraocular pressure and optic nerve damage, which is often asymptomatic. Non-contact tests to identify people at risk of angle closure are relatively quick and can be carried out by appropriately trained healthcare professionals or technicians as a triage test. If the test is positive, the person will be referred for further specialist assessment. OBJECTIVES: To determine the diagnostic accuracy of non-contact tests (limbal anterior chamber depth (LACD) (van Herick test); oblique flashlight test; scanning peripheral anterior chamber depth analyser (SPAC), Scheimpflug photography; anterior segment optical coherence tomography (AS-OCT), for identifying people with an occludable angle. SEARCH METHODS: We searched the following bibliographic databases 3 October 2019: CENTRAL; MEDLINE; Embase; BIOSIS; OpenGrey; ARIF and clinical trials registries. The searches were limited to remove case reports. There were no date or language restrictions in the searches. SELECTION CRITERIA: We included prospective and retrospective cross-sectional, cohort and case-control studies conducted in any setting that evaluated the accuracy of one or more index tests for identifying people with an occludable angle compared to a gonioscopic reference standard. DATA COLLECTION AND ANALYSIS: Two review authors independently performed data extraction and quality assessment using QUADAS2 for each study. For each test, 2 x 2 tables were constructed and sensitivity and specificity were calculated. When four or more studies provided data at fixed thresholds for each test, we fitted a bivariate model using the METADAS macro in SAS to calculate pooled point estimates for sensitivity and specificity. For comparisons between index tests and subgroups, we performed a likelihood ratio test comparing the model with and without the covariate. MAIN RESULTS: We included 47 studies involving 26,151 participants and analysing data from 23,440. Most studies were conducted in Asia (36, 76.6%). Twenty-seven studies assessed AS-OCT (analysing 15,580 participants), 17 studies LACD (7385 participants), nine studies Scheimpflug photography (1616 participants), six studies SPAC (5239 participants) and five studies evaluated the oblique flashlight test (998 participants). Regarding study quality, 36 of the included studies (76.6%) were judged to have a high risk of bias in at least one domain.The use of a case-control design (13 studies) or inappropriate exclusions (6 studies) raised patient selection concerns in 40.4% of studies and concerns in the index test domain in 59.6% of studies were due to lack of masking or post-hoc determination of optimal thresholds. Among studies that did not use a case-control design, 16 studies (20,599 participants) were conducted in a primary care/community setting and 18 studies (2590 participants) in secondary care settings, of which 15 investigated LACD. Summary estimates were calculated for commonly reported parameters and thresholds for each test; LACD ≤ 25% (16 studies, 7540 eyes): sensitivity 0.83 (95% confidence interval (CI) 0.74, 0.90), specificity 0.88 (95% CI 0.84, 0.92) (moderate-certainty); flashlight (grade1) (5 studies, 1188 eyes): sensitivity 0.51 (95% CI 0.25, 0.76), specificity 0.92 (95% CI 0.70, 0.98) (low-certainty); SPAC (≤ 5 and/or S or P) (4 studies, 4677 eyes): sensitivity 0.83 (95% CI 0.70, 0.91), specificity 0.78 (95% CI 0.70, 0.83) (moderate-certainty); Scheimpflug photography (central ACD) (9 studies, 1698 eyes): sensitivity 0.92 (95% CI 0.84, 0.96), specificity 0.86 (95% CI 0.76, 0.93) (moderate-certainty); AS-OCT (subjective opinion of occludability) (13 studies, 9242 eyes): sensitivity 0.85 (95% CI 0.76, 0.91); specificity 0.71 (95% CI 0.62, 0.78) (moderate-certainty). For comparisons of sensitivity and specificity between index tests we used LACD (≤ 25%) as the reference category. The flashlight test (grade 1 threshold) showed a statistically significant lower sensitivity than LACD (≤ 25%), whereas AS-OCT (subjective judgement) had a statistically significant lower specificity. There were no statistically significant differences for the other index test comparisons. A subgroup analysis was conducted for LACD (≤ 25%), comparing community (7 studies, 14.4% prevalence) vs secondary care (7 studies, 42% prevalence) settings. We found no evidence of a statistically significant difference in test performance according to setting. Performing LACD on 1000 people at risk of angle closure with a prevalence of occludable angles of 10%, LACD would miss about 17 cases out of the 100 with occludable angles and incorrectly classify 108 out of 900 without angle closure. AUTHORS' CONCLUSIONS: The finding that LACD performed as well as index tests that use sophisticated imaging technologies, confirms the potential for this test for case-detection of occludable angles in high-risk populations. However, methodological issues across studies may have led to our estimates of test accuracy being higher than would be expected in standard clinical practice. There is still a need for high-quality studies to evaluate the performance of non-invasive tests for angle assessment in both community-based and secondary care settings

An Architecture for Crowd Density Estimation in Heterogenous Opportunistic Environment

[ES] Esta tesis presenta un nuevo modelo llamado "Modelo dinámico de interacción social y multitud urbana (DUCSIM)", que tiene como objetivo calcular la densidad de multitudes y descifrar las redes sociales en entornos oportunistas. Con la creciente similitud de los dispositivos electrónicos conectados a Internet y la influencia generalizada de las redes sociales en línea, se ha creado un enorme rastro digital. Las huellas digitales basadas en la movilidad humana y el mayor uso de sistemas de comunicación inalámbrica como 3G, 4G y 5G forman una rica base de datos que puede analiarse. Estas huellas digitales ofrecen una forma única de modelar los patrones de multitud dentro de diferentes contextos, como asambleas espontáneas en espacios públicos y escenarios planificados, como en el caso de los megaeventos. El estudio se centra en el desafío de las reuniones multitudinarias oportunistas, donde las personas se congregan por diferentes motivos sin planificación; manifiestan sus movimientos de forma dinámica e inesperada. El análisis del comportamiento humano en las ciudades modernas y desarrolladas requiere que estas reuniones se produzcan en centros comerciales, cruces de carreteras y flash mobs. El análisis macroscópico de la densidad de multitudes basado en datos de las torres de telefonía móvil sirve como primera etapa para delinear el marco DUCSIM. Se adopta el método Median-of-Median (M-o-M) para mayor solidez, ya que este análisis implica umbrales de conteo bruto de multitudes diario y semanal. Las densidades de multitud se clasifican en cuartiles para mostrar distintos grados de distribución de la multitud. A través del análisis macroscópico, el marco avanza hacia el análisis de movilidad acumulativa de multitudes. La dinámica del movimiento de multitudes se mide cambiando las señales de las torres de telefonía movil y formulando un mapa de densidad de multitudes para pronosticar sus movimientos posteriores. Examina el microanálisis del movimiento individual y las relaciones interpersonales a menor escala. Incluye asignar personas a torres de telefonía móvil y formar gráficos de interacción social que infieren y actualizan las relaciones sociales. La parte más importante de DUCSIM radica en su capacidad de aprender y adaptarse dinámicamente para crear un modelo de representación novedoso que se adapte al patrón recién detectado. Esta flexibilidad ayuda a garantizar la relevancia del marco, que debe actualizarse continuamente. El modelado predictivo personalizado se combina con datos históricos que engloban la tesis. El marco utiliza densidades de multitudes anteriores y datos de movimiento para descubrir tendencias y predecir dinámicas de multitudes futuras, mejorando así la eficiencia de la planificación urbana, la respuesta a emergencias o las ciudades inteligentes. El marco DUCSIM proporciona un método integral, flexible y de previsión para comprender y controlar los fenómenos de aglomeración urbana. Una forma moderna de análisis de datos que involucra varias fuentes de datos, respaldada por matemáticas rigurosas, hace que este método sea único para los estudios urbanos. Además, da impulso al ámbito académico y proporciona recomendaciones prácticas sobre la aplicación de esta metodología en la gestión y planificación de las ciudades modernas.[CA] Aquesta tesi presenta un nou model anomenat "Dynamic Urban Crowd and Social Interaction Model (DUCSIM)", que té com a objectiu calcular la densitat de multituds i desxifrar xarxes socials en entorns oportunistes. Amb la creixent comú d'aparells electrònics enllaçats a Internet i la influència generalitzada de les xarxes socials en línia, s'ha creat un enorme rastre digital. Les traces digitals basades en la mobilitat humana i l'augment de l'ús de sistemes de comunicació sense fils com 3G, 4G i 5G formen una base de dades rica per ser analitzada. Aquestes traces digitals ofereixen una manera única de modelar els patrons de multituds en diferents contextos, com ara assemblees espontànies en espais públics i escenaris planificats, com en el cas dels megaesdeveniments. L'estudi se centra en el repte de les reunions multitudinàries oportunistes, on la gent es congrega per diferents motius sense planificació; manifesten els seus moviments de manera dinàmica i inesperada. L'anàlisi del comportament humà a les ciutats modernes i desenvolupades requereix que aquestes reunions es produeixin en centres comercials, cruïlles de carreteres i flash mobs. L'anàlisi macroscòpic de la densitat de multituds basada en dades de les torres de telefonía mòbil serveix com a primera etapa per descriure el marc DUCSIM. El mètode M-o-M s'adopta per a la robustesa, ja que aquesta anàlisi implica umbrals de recompte de multituds diaris i setmanals. Les densitats de multitud es classifiquen en quartils per mostrar diferents graus de distribució de multitud. Mitjançant l'anàlisi macroscòpic, el marc avança cap a l'anàlisi de la mobilitat acumulat de multituds. La dinàmica del moviment de la multitud es mesura canviant els senyals de les torres de telefonía mòbil i formulant un mapa de densitat de la multitud per preveure els seus moviments posteriors. Examina el microanàlisi del moviment individual i les relacions interpersonals a menor escala. Inclou assignar persones a torres de telefonía mòbil i formar gràfics d'interacció social que dedueixin i actualitzin les relacions socials. La part més important de DUCSIM està en la seua capacitat per aprendre i adaptar-se de manera dinàmica per crear un model de representació nou que s'adapte al patró recentment detectat. Aquesta flexibilitat ajuda a garantir la rellevància del marc, que s'ha d'actualitzar contínuament. El modelatge predictiu personalitzat es combina amb les dades històriques que engloben la tesi. El marc utilitza dades de moviment i densitats de multitud anteriors per descobrir tendències i predir les properes dinàmiques de multituds, millorant així l'eficiència de la planificació urbana, la resposta d'emergència o les ciutats intel·ligents. El marc DUCSIM proporciona un mètode complet, flexible i de previsió per entendre i controlar els fenòmens d'aglomeracions urbanes. Una forma moderna d'anàlisi de dades que inclou diverses fonts de dades, amb el suport de matemàtiques rigoroses, fa que aquest mètode sigui únic per als estudis urbans. A més, dóna un impuls a l'àmbit acadèmic i ofereix recomanacions pràctiques sobre l'aplicació d'aquesta metodologia en la gestió i planificació de la ciutat moderna.[EN] This thesis presents a new framework called the "Dynamic Urban Crowd and Social Interaction Model (DUCSIM)," which is aimed at calculating crowd density and deciphering social networks in opportunistic environments. With the growing commonality of internet-linked electronic gadgets and the widespread influence of online social networks, an enormous digital trail has been created. The digital traces based on human mobility and the increased usage of wireless communication systems such as 3G, 4G, and 5G form a rich database to be analyzed. These digital traces offer a unique way of modelling the crowd patterns within different contexts, like spontaneous assemblies in public spaces and planned scenarios, as in the case of mega-events. The study focuses on the challenge of opportunistic crowd gatherings, where people congregate for different reasons without planning; they manifest their motions dynamically and unexpectedly. The analysis of human behaviour in modern, developed cities requires that these gatherings occur in malls, road junctions, and flash mobs. Macroscopic crowd density analysis based on data from MOBILE towers serves as the first stage in outlining the DUCSIM framework. The Median-of-Median (M-o-M) method is adopted for robustness as this analysis involves daily and weekly raw crowd count thresholds. Crowd densities are ranked in quartiles to show varying degrees of crowd distribution. Through the macroscopic analysis, the framework progresses to cumulative crowd mobility analysis. Crowd movement dynamics are measured by changing signals from MOBILE towers and formulating a crowd's density map to forecast its subsequent motions. It examines the micro-analysis of individual movement and interpersonal relations on a smaller scale. It includes assigning people to MOBILE towers and forming social interaction graphs that infer and update social relationships. The most important part of DUCSIM lies in its ability to dynamically learn and adapt to create a novel representation model to suit the newly detected pattern. This flexibility helps to ensure the relevancy of the framework, which must be continually updated. Custom predictive modelling combines with historical data that encompasses the thesis. The framework uses previous crowd densities and movement data to discover trends and predict upcoming crowd dynamics, thus improving urban planning efficiency, emergency response, or smart cities. The DUCSIM framework provides a comprehensive, flexible and forecasting method of understanding and controlling urban crowd phenomena. A modern form of data analysis involving several data sources, supported by rigorous mathematics, makes this method unique for urban studies. Moreover, it gives impetus to the academic sphere and provides practical recommendations concerning the application of this methodology within modern city management and planning.Addepalli, L. (2024). An Architecture for Crowd Density Estimation in Heterogenous Opportunistic Environment [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/20474

RECAST: Telling Apart Social and Random Relationships in Dynamic Networks

International audienceWhen constructing a social network from interactions among people (e.g., phone calls, encounters), a crucial task is to define the threshold that separates social from random (or casual) relationships. The ability to accurately identify social relationships becomes essential to applications that rely on a precise description of human routines, such as recommendation systems, forwarding strategies and opportunistic dissemination protocols. We thus propose a strategy to analyze users' interactions in dynamic networks where entities act according to their interests and activity dynamics. Our strategy, named \textit{\classifierE (\classifier)}, allows classifying users interactions, separating random ties from social ones. To that end, \classifier observes how the real system differs from an equivalent one where entities' decisions are completely random. We evaluate the effectiveness of the \classifier classification on five real-world user contact datasets collected in diverse networking contexts. Our analysis unveils significant differences among the dynamics of users' wireless interactions in the datasets, which we leverage to unveil the impact of social ties on opportunistic routing. We show that, for such specific purpose, the relationships inferred by \classifier are more relevant than, e.g., self-declared friendships on Facebook

Arabidopsis mRNA polyadenylation machinery: comprehensive analysis of protein-protein interactions and gene expression profiling

<p>Abstract</p> <p>Background</p> <p>The polyadenylation of mRNA is one of the critical processing steps during expression of almost all eukaryotic genes. It is tightly integrated with transcription, particularly its termination, as well as other RNA processing events, i.e. capping and splicing. The poly(A) tail protects the mRNA from unregulated degradation, and it is required for nuclear export and translation initiation. In recent years, it has been demonstrated that the polyadenylation process is also involved in the regulation of gene expression. The polyadenylation process requires two components, the <it>cis</it>-elements on the mRNA and a group of protein factors that recognize the <it>cis</it>-elements and produce the poly(A) tail. Here we report a comprehensive pairwise protein-protein interaction mapping and gene expression profiling of the mRNA polyadenylation protein machinery in Arabidopsis.</p> <p>Results</p> <p>By protein sequence homology search using human and yeast polyadenylation factors, we identified 28 proteins that may be components of Arabidopsis polyadenylation machinery. To elucidate the protein network and their functions, we first tested their protein-protein interaction profiles. Out of 320 pair-wise protein-protein interaction assays done using the yeast two-hybrid system, 56 (~17%) showed positive interactions. 15 of these interactions were further tested, and all were confirmed by co-immunoprecipitation and/or in vitro co-purification. These interactions organize into three distinct hubs involving the Arabidopsis polyadenylation factors. These hubs are centered around AtCPSF100, AtCLPS, and AtFIPS. The first two are similar to complexes seen in mammals, while the third one stands out as unique to plants. When comparing the gene expression profiles extracted from publicly available microarray datasets, some of the polyadenylation related genes showed tissue-specific expression, suggestive of potential different polyadenylation complex configurations.</p> <p>Conclusion</p> <p>An extensive protein network was revealed for plant polyadenylation machinery, in which all predicted proteins were found to be connecting to the complex. The gene expression profiles are indicative that specialized sub-complexes may be formed to carry out targeted processing of mRNA in different developmental stages and tissue types. These results offer a roadmap for further functional characterizations of the protein factors, and for building models when testing the genetic contributions of these genes in plant growth and development.</p

Arabidopsis mRNA polyadenylation machinery: comprehensive analysis of protein-protein interactions and gene expression profiling

BACKGROUND: The polyadenylation of mRNA is one of the critical processing steps during expression of almost all eukaryotic genes. It is tightly integrated with transcription, particularly its termination, as well as other RNA processing events, i.e. capping and splicing. The poly(A) tail protects the mRNA from unregulated degradation, and it is required for nuclear export and translation initiation. In recent years, it has been demonstrated that the polyadenylation process is also involved in the regulation of gene expression. The polyadenylation process requires two components, the cis-elements on the mRNA and a group of protein factors that recognize the cis-elements and produce the poly(A) tail. Here we report a comprehensive pairwise protein-protein interaction mapping and gene expression profiling of the mRNA polyadenylation protein machinery in Arabidopsis. RESULTS: By protein sequence homology search using human and yeast polyadenylation factors, we identified 28 proteins that may be components of Arabidopsis polyadenylation machinery. To elucidate the protein network and their functions, we first tested their protein-protein interaction profiles. Out of 320 pair-wise protein-protein interaction assays done using the yeast two-hybrid system, 56 (approximately 17%) showed positive interactions. 15 of these interactions were further tested, and all were confirmed by co-immunoprecipitation and/or in vitro co-purification. These interactions organize into three distinct hubs involving the Arabidopsis polyadenylation factors. These hubs are centered around AtCPSF100, AtCLPS, and AtFIPS. The first two are similar to complexes seen in mammals, while the third one stands out as unique to plants. When comparing the gene expression profiles extracted from publicly available microarray datasets, some of the polyadenylation related genes showed tissue-specific expression, suggestive of potential different polyadenylation complex configurations. CONCLUSION: An extensive protein network was revealed for plant polyadenylation machinery, in which all predicted proteins were found to be connecting to the complex. The gene expression profiles are indicative that specialized sub-complexes may be formed to carry out targeted processing of mRNA in different developmental stages and tissue types. These results offer a roadmap for further functional characterizations of the protein factors, and for building models when testing the genetic contributions of these genes in plant growth and development

Normalized expression data for the NASC Arabidopsis biotic stress series (Additional file ) were extracted and plotted as shown

The legends indicate the correspondence between the plots and the respective Arabidopsis gene identification designation. The numerical key for each array experiment is given along the X-axis. While the full list of the agents can be found in Additional file , here is a brief list: 1–16, control and infection; 17–22, control and infection; 23–36, control and elicitors treatment; 37–52, dark and different light treatment.<p><b>Copyright information:</b></p><p>Taken from "Arabidopsis mRNA polyadenylation machinery: comprehensive analysis of protein-protein interactions and gene expression profiling"</p><p>http://www.biomedcentral.com/1471-2164/9/220</p><p>BMC Genomics 2008;9():220-220.</p><p>Published online 14 May 2008</p><p>PMCID:PMC2391170.</p><p></p