Factors prompting augmented reality adoption in sacred places

There is evidence that sacred places across the world are launching augmented reality (AR) applications. This application of AR is somehow prompted by the most recent Covid-19 pandemic where in-person experiences are altered by the virtual. AR, as an innovative technology, augments the physical environment with digitally generated imagery that can generate privileges for tourists in sacred places and become the reason to trigger cultural conflicts and religious controversy. This in-depth interview-based research aims to explore the tourists' views and ideas of applying AR in the Mosque City of Bagerhat of Bangladesh, a UNESCO World Heritage Site in terms of possibilities, cultural conflicts, and religious controversy. Findings show that the application of AR in a sacred place can support tourists in many useful ways, can offer them positive experiences, and help in sustainability concerns of the site. However, the application of AR in a sacred place can be an element of conflicting interests between the religious and general tourists. Adequate attention is thus required from the parties involved in terms of applying AR in the Mosque City of Bagerhat of Bangladesh, a sacred religious site.

COVID-19, climate shocks, and food security linkages: evidence and perceptions from smallholder farming communities in Tanzania

Insights on the indirect effects of the COVID-19 pandemic are critical for designing and implementing policies to alleviate the food security burden it may have caused, and for bolstering rural communities against similar macroeconomic shocks in the future. Yet estimating the causal effects of the pandemic is difficult due to its ubiquitous nature and entanglement with other shocks. In this descriptive study, we combine high-resolution satellite imagery to control for plot-level rainfall with household socio-economic panel data from 2014, 2016, 2019 and 2020, to differentiate the effect of the pandemic from climatic shocks on food security in Morogoro, Tanzania. We find evidence of decreased incomes, increased prices of staple foods, and increased food insecurity in 2020 relative to previous years, and link these changes to the pandemic by asking households about their perceptions of COVID-19. Respondents overwhelmingly attribute economic hardships to the pandemic, with perceived impacts differing by asset level.

Digitalisation and modern imaging technologies in dermatology

Teledermatology is one of the most important developments of digitalisation in dermatology. It has helped to ensure continuity of care during the COVID-19 pandemic. The combination of teledermatology with artificial intelligence can significantly improve medical decision-making. Among imaging modalities, dermoscopy is the most widely used, and its effectiveness can be significantly enhanced when combined with artificial intelligence. Novel techniques that have emerged in recent years include high-frequency ultrasound, optical coherence tomography or multispectral imaging. These are currently used in dermatological research but are expected to gradually become part of daily patient care. The knowledge of digital technologies and new imaging techniques is essential for the modern dermatologist. In the future, it is expected to be an essential part of modern and optimised patient care.

Night-time Human Mobility during Pandemic in the Philippines as Observed by VIIRS Satellite

Recent research has analyzed and studied the growing literature on human mobility during quarantine periods using various methodology and techniques. There are several ways to use light pollution to assess mobility. The data from the VIIRS satellite can be used to quantify light pollution and human mobility in the Philippines during quarantine. The data utilized in this study came from NASA's EOSDIS Worldview website. The number of cases and pixels count increases from early April 2020 to late August 2020. However, the cases increased from February to April 2021. This could be attributed to the active human mobility seen between December 2020 and January 2021. Human interactions have been intense since August 2020, causing an increase in COVID cases that peaked between March and April 2021, before dropping in May 2021. Following the conclusion of this study, light pollution VIIRS satellite pictures can be used to identify possible COVID- 19 cases. There are many more factors and variables to consider when writing a comprehensive paper. With the relaxed quarantine time has been achieved beyond June 2021, additional dates may be explored since there may be a direct relationship between light pollution and COVID-19 instances. © 2022 IEEE.

MNLTour: A Web and Mobile Application for Virtual Tour System of Select Tourist Spots Around Manila Using 360-degree Imagery and Virtual Reality Technology

MNLTour is a virtual tour system for selected tourist spots situated within the city of Manila. It utilizes 360-degree images, 2D images, voice recordings, and virtual reality technology to offer an immersive user experience of the virtual environment. The virtual tour system was developed using the Unity3D software and was then integrated into web and mobile applications accessible through web browsers and android smartphones, respectively. MNLTour aims to promote the wonders of Manila city by showcasing some of its historical tourist spots that have been severely affected by the outbreak of the COVID-19 pandemic. The developed web and mobile applications were tested and later evaluated to assess the overall quality of the software in accordance with ISO 9126 standard. The evaluation statements primarily focus on the aspects of functionality, efficiency, usability, effectiveness, and user satisfaction in using the application. Descriptive statistics was used to analyze and summarize the data gathered from the evaluation respondents. The evaluation of the application in both platforms turned out to have admirable evaluation results;hence, it's safe to say that the developed software has an acceptable overall quality. © 2022 IEEE.

The long wave of COVID-19: a case report using Imagery Rehearsal Therapy for COVID-19-related nightmares after admission to intensive care unit.

Introduction: The COVID-19 pandemic caused several psychological consequences for the general population. In particular, long-term and persistent psychopathological detriments were observed in those who were infected by acute forms of the virus and need specialistic care in the Intensive Care Unit (ICU). Imagery rehearsal therapy (IRT) has shown promising results in managing nightmares of patients with different traumas, but it has never been used with patients admitted to ICUs for severe COVID-19 despite this experience being considered traumatic in the literature. Methods: The purpose of this case study is to describe the application of a four-session IRT for the treatment of COVID-related nightmares in a female patient after admission to the ICU. A 42-year-old Caucasian woman who recovered from a pulmonary rehabilitation program reported shortness of breath, dyspnea, and everyday life difficulties triggered by the long-COVID syndrome. She showed COVID-related nightmares and signs of post-traumatic symptoms (i.e., hyperarousal, nightmares, and avoidance of triggers associated with the traumatic situation). Psychological changes in the aftermath of a trauma, presence, and intensity of daytime sleepiness, dream activity, sleep disturbances, aspects of sleep and dreams, and symptoms of common mental health status are assessed as outcomes at the baseline (during the admission to pneumology rehabilitation) at 1-month (T1) and 3-month follow-up (T2). Follow-up data were collected through an online survey. Results: By using IRT principles and techniques, the patient reported a decrease in the intensity and frequency of bad nightmares, an increase in the quality of sleep, and post-traumatic growth, developing a positive post-discharge. Conclusion: Imagery rehearsal therapy may be effective for COVID-19-related nightmares and in increasing the quality of sleep among patients admitted to the ICU for the treatment of COVID-19. Furthermore, IRT could be useful for its brevity in hospital settings.

Cognitive bias in the context of epidemic

In connection with the scope and duration of the COVID-19 pandemic, the clinical judgement of clinicians and medical practitioners could be influenced such that diagnostic errors (delays and inaccuracies) may ensue. We hereby recall through two clinical scenarios the constant need for practitioners to take a step back in reflecting of the diagnostic process to avoid the <<tunnel effect>> which may result in delaying common and frequent infectious diseases. The flu-like symptoms presented by these patients (fever, myalgia and asthenia...) quickly prompted our emergency room colleagues to suspect SARS-CoV-2 infection. However, further investigations including imagery and blood cultures revealed completely different but common infectious disease conditions, which are potentially fatal.Copyright © 2020 Editions Medecine et Hygiene. All rights reserved.

The Great Indian Water Crisis: Sarnath Banerjee's Graphic Narrative All Quiet in Vikaspuri as an Acerbic Attestation of the Urban Water Crisis in India

Through a detailed analysis of the visual imagery as well as the verbal mode of narration, in Sarnath Banerjee's Graphic narrative All Quiet in Vikaspuri, the study suggests that the water-deprived, post-apocalyptic world that Banerjee reflects, is a spitting image of the Anthropogenic water crisis in India. Drawing theoretical insights from Madhav Gadgil, Ramachandra Guha and Dipesh Chakrabarty, the paper attempts to suggest the "Great Indian Water Crisis" is fueled by "short-termism," increased corporate privatization of water, myopic government development policies and erection of dams and other capitalist structures. The paper also aims to uncover how sociopolitical "slow-violence" is rendered to the natural resources under the garb of "Vikas" (development) and privatization. By contriving the narrative around the quest for the river Saraswati, Banerjee draws attention to the ever-so-real issue of groundwater overextraction in India, leading to its dipping levels and in turn, depletion. Further, the paper argues that "intermediality" of graphic narration abets Banerjee to cater to "the representational challenges" of the Anthropocene.

Investigation of COVID-19 symptoms using deep learning based image enhancement scheme for x-ray medical images

Image enhancement is the inevitable technique for investigating various biological features. The biological image data can be obtained from computer tomography (CT), magnetic resonance imaging (MRI), and X-ray imaging. X-ray imaging is useful for getting the information from lungs and respiratory system. COVID-19 is a life-threatening contiguous disease for the past two years in the world. Patient's chest images playing an important role in the diagnosis of early detection of disease intensity. We propose a generative adversarial network (GAN) method that identifies COVID-19 from medical images and improves diagnostic sensitivity. Here we used virtual colouring methods and a platform for training the images by using a deep parental training method. Similarly, it gives optimal classification results with the help of well-defined image enhancement techniques and image extraction approaches. In our method, the accuracy level lies between 87.8% and 89.6% correspondingly for the dataset and synthetic dataset.

Special Isue: Virtual anatomy, histology and embryology in research and education. (Special Isue: Virtual anatomy, histology and embryology in research and education.)

This issue contains 13 articles on the use of virtual anatomy, histology and embryology in research and education;digital histological morphometry of the human pineal gland in a postmortem study, with endocrine and neurological clinical implications;an international collaborative approach to learning histology using a virtual microscope;delivery anatomy kits to help keep practical veterinary classes during the COVID-19 pandemic;how virtual animal anatomy facilitated a successful transition to online instruction and supported student learning during the coronavirus pandemic;using videos in active learning in veterinary anatomy;dissection videos as a virtual veterinary anatomy peer learning tool at the University of Tehran during the COVID-19 pandemic;a new virtual platform for teaching comparative animal neuroanatomy based on metameric slices of the central nervous system;application of student remote and distance research in neuroanatomy by mapping Dscaml1 expression with a LacZ gene trap in mouse brain;implementing a multi-colour genetic marker analysis technique for embryology education;impact of COVID-19 on student attainment and pedagogical needs when undertaking independent scientific research;extended reality veterinary medicine case studies for diagnostic veterinary imaging instruction and assessing student perceptions and examination performance and students' performance in teaching neuroanatomy using traditional and technology-based methods. 16 proceedings from the Trans-European Pedagogic Anatomy Research Group (TEPARG) Hybrid Meeting entitled "Hybrid Anatomy Education: Barriers and Enablers for Students and Educators" held in Barcelona, Spain, during 5 March 2022, are also included.

Small area population denominators for improved disease surveillance and response.

The Covid-19 pandemic has highlighted the value of strong surveillance systems in supporting our abilities to respond rapidly and effectively in mitigating the impacts of infectious diseases. A cornerstone of such systems is basic subnational scale data on populations and their demographics, which enable the scale of outbreaks to be assessed, risk to specific groups to be determined and appropriate interventions to be designed. Ongoing weaknesses and gaps in such data have however been highlighted by the pandemic. These can include outdated or inaccurate census data and a lack of administrative and registry systems to update numbers, particularly in low and middle income settings. Efforts to design and implement globally consistent geospatial modelling methods for the production of small area demographic data that can be flexibly integrated into health-focussed surveillance and information systems have been made, but these often remain based on outdated population data or uncertain projections. In recent years, efforts have been made to capitalise on advances in computing power, satellite imagery and new forms of digital data to construct methods for estimating small area population distributions across national and regional scales in the absence of full enumeration. These are starting to be used to complement more traditional data collection approaches, especially in the delivery of health interventions, but barriers remain to their widespread adoption and use in disease surveillance and response. Here an overview of these approaches is presented, together with discussion of future directions and needs.

Data-driven techniques for human activity sensing in smart environments

The number of Internet-of-Things (IoT) and edge devices has exploded in the last decade, providing new opportunities to sense and enable many applications to transform everyday people's lives. Wide-scale time series data collected through such devices, coupled with advances in learning technologies, can transform how people interact with their environment. However, as we enter the era of ubiquitous computing, there is a growing need for methods that are easy to use, computationally feasible, and require minimal human supervision to sense human activities by analyzing large-scale data. The goal of this research work is to propose data-driven techniques that focus on human activity sensing at different scales.The first part of the thesis focuses on human activity sensing at building scale for smart indoor environments. Towards that end, this work emphasizes general-purpose human activity sensing using ambient sensors for context-aware computing in smart environments. A deep neural network-based technique for sensing human-environment interaction is proposed and experiments explored interpretability for different ambient sensors and their contribution to model performance to avoid data redundancy. Identifying the challenge of distribution shift in long-term activity sensing, the thesis next focuses on time series partitioning for unlabeled IoT sensor streams, which is an important step toward continuous human activity sensing. This work proposes Cadence, a generalized change point detection technique that detects change points through hypothesis testing by learning a data representation specifically with the segmentation objective. Experiments show that it is sample-efficient, unsupervised, and can robustly detect time-series events across different applications while needing only 9-93 seconds for training.The second part of the thesis focuses on human activity sensing at city scale using large-scale spatio-temporal data. A framework is introduced for sensing urban activity and policy compliance during the COVID-19 crisis using vision and language-based sensing from street view images. Understanding the challenges of street view image usage in urban sensing due to its large scale and distribution variance, a data-driven framework is proposed to evaluate the quality of information in urban scale street view images based on quality attributes capturing spatial, temporal, and content information present in the data. Our experiments show that such framework can be useful for ranking, querying, and improving spatio-temporal data quality and usage in urban computing and activity sensing. We believe such techniques can be useful to model our living patterns by analyzing large-scale data and improve the quality of our life through applications such as home automation, energy optimization, and personalized healthcare. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Modeling of Brain Cortical Activity during Relaxation and Mental Workload Tasks Based on EEG Signal Collection

Coronavirus disease 2019 (COVID-19) has caused everything from daily hassles, relationship issues, and work pressures to health concerns and debilitating phobias. Relaxation techniques are one example of the many methods used to address stress, and they have been investigated for decades. In this study, we aimed to check whether there are differences in the brain cortical activity of participants during relaxation or mental workload tasks, as observed using dense array electroencephalography, and whether these differences can be modeled and then classified using a machine learning classifier. In this study, guided imagery as a relaxation technique was used in a randomized trial design. Two groups of thirty randomly selected participants underwent a guided imagery session;other randomly selected participants performed a mental task. Participants were recruited among male computer science students. During the guided imagery session, the electroencephalographic activity of each student's brain was recorded using a dense array amplifier. This activity was compared with that of a group of another 30 computer science students who performed a mental task. Power activity maps were generated for each participant, and examples are presented and discussed to some extent. These types of maps cannot be easily interpreted by therapists due to their complexity and the fact that they vary over time. However, the recorded signal can be classified using general linear models. The classification results as well as a discussion of prospective applications are presented. © 2023 by the authors.

The YOPP Final Summit: Assessing Past and Forecasting Future Polar Prediction Research

The successes of YOPP from the presentations and keynote presentations included * a better understanding of the impact of key polar measurements (radiosondes and space-based instruments such as microwave radiometers), and recent advancements in the current NWP observing system, achieved through coordinated OSEs in both polar regions (e.g., Sandu et al. 2021);* enhanced understanding of the linkages between Arctic and midlatitude weather (e.g., Day et al. 2019);* advancements in the atmosphere–ocean–sea ice and atmosphere–land–cryosphere coupling in NWP, and in assessing and recognizing the added value of coupling in Earth system models (e.g., Bauer et al. 2016);* deployment of tailored polar observation campaigns to address yet-unresolved polar processes (e.g., Renfrew et al. 2019);* progress in verification and forecasting techniques for sea ice, including a novel headline score (e.g., Goessling and Jung 2018);* advances in process understanding and process-based evaluation with the establishment of the YOPPsiteMIP framework and tools (Svensson 2020);* better understanding of emerging societal and stakeholder needs in the Arctic and Antarctic (e.g., Dawson et al. 2017);and * innovative transdisciplinary methodologies for coproducing salient information services for various user groups (Jeuring and Lamers 2021). The YOPP Final Summit identified a number of areas worthy of prioritized research in the area of environmental prediction and services for the polar regions: * coupled atmosphere, sea ice, and ocean models with an emphasis on advanced parameterizations and enhanced resolution at which critical phenomena start to be resolved (e.g., ocean eddies);* improved definition and representation of stable boundary layer processes, including mixed-phase clouds and aerosols;incorporation of wave–ice–ocean interactions;* radiance assimilation over sea ice, land ice, and ice sheets;understanding of linkages between polar regions and lower latitudes from a prediction perspective;* exploring the limits of predictability of the atmosphere–cryosphere–ocean system;* an examination of the observational representativeness over land, sea ice, and ocean;better representation of the hydrological cycle;and * transdisciplinary work with the social science community around the use of forecasting services and operational decision-making to name but a few. The presentations and discussions at the YOPP Final Summit identified the major legacy elements of YOPP: the YOPPsiteMIP approach to enable easy comparison of collocated multivariate model and observational outputs with the aim of enhancing process understanding, the development of an international and multi-institutional community across many disciplines investigating aspects of polar prediction and services, the YOPP Data Portal3 (https://yopp.met.no/), and the education and training delivered to early-career polar researchers. Next steps Logistical issues, the COVID-19 pandemic, but also new scientific questions (e.g., the value of targeted observations in the Southern Hemisphere), as well as technical issues emerging toward the end of the YOPP Consolidation Phase, resulted in the decision to continue the following three YOPP activities to the end of 2023: (i) YOPP Southern Hemisphere (YOPP-SH);(ii) Model Intercomparison and Improvement Project (MIIP);of which YOPPSiteMIP is a critical element;and (iii) the Societal, Economics and Research Applications (PPP-SERA) Task Team.

Enhancing museums' attractiveness through digitization: An investigation of Italian medium and large-sized museums and cultural institutions

The Covid-19 pandemic put the museums' viability under stress, with national and supranational policies imposing closures and restricting the number of admitted visitors. Digitization enables cultural institutions to overcome such constraints, prompting innovative service delivery models. However, evidence on digitization's implications on organizational attractiveness (OA) is scant. Taking a retrospective approach, the article proposes a parallel mediation analysis to shed some light on the effects of digitization on museums' attractiveness. Findings suggest that digitization enhances OA directly and indirectly, via the delivery of digital services to physical visitors. Furthermore, digitization allows museums to meet the virtual visitors' expectations, enriching the cultural service offering. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Dreaming for the World: A Jungian Study of Dreams During the COVID‐19 Pandemic

This project explores what dreams might reveal about the collective psyche’s response to the COVID‐19 pandemic in its first year, before the development of vaccines. A brief survey, distributed to Jungian colleagues and organizations, and to various social media sites, invited people to submit online a dream related to the COVID‐19 pandemic. Four hundred and thirty‐six dreams were submitted. Forty additional Russian dreams were collected and submitted by Russian colleagues. Using qualitative research methods based on phenomenological hermeneutics, the researchers categorized and counted the range of COVID imagery. In addition, the researchers describe a range of psychic responses to the pandemic, including horror, grief, sickness, social discord, and violence, but also images of healing and transformation, increased sense of community, and spiritual renewal. Several healing nightmares are presented. Healing alchemical and anima/animus imagery is described. Twelve dreams are introduced and presented. It is concluded that the collective psyche, rooted in the Self, is a healing resource for social and cultural trauma. This project supports Beradt’s (1968) inspirational study of dreaming in Nazi Germany, as well as recent studies of COVID‐related dreams and recent publications on the social nature of dreaming.Alternate :Ce projet explore ce que les rêves peuvent révéler en ce qui concerne la réponse de la psyché collective à la pandémie de COVID‐19 dans sa première année, avant le développement des vaccins. Un court questionnaire, distribué à des collègues et des organisations Jungiennes, et à divers sites de réseaux sociaux, invitait les personnes à mettre en ligne un rêve en lien avec la pandémie de COVID‐19. Quatre cent trente‐six rêves ont été mis en ligne. D’autre part quarante rêves ont été collectés et mis en ligne par des collègues Russes. En utilisant les méthodes de recherche qualitative fondées sur l’herméneutique phénoménologique, les chercheurs ont établi des catégories et ont dénombré la variété de l’imagerie liée au COVID. De plus, les chercheurs ont décrit un certain nombre de réponses psychiques à la pandémie, par exemple l’horreur, le chagrin, la maladie, la discorde sociale et la violence, mais également des images de guérison et de transformation, un sentiment accru de communauté, et du renouveau spirituel. Plusieurs cauchemars de guérison sont présentés. L’imagerie de la guérison alchimique et celle liée à l’anima/animus est décrite. Douze rêves sont décrits et présentés. La conclusion apportée est que la psyché collective, enracinée dans le Soi, est une ressource de guérison en ce qui concerne le traumatisme social et culturel. Ce projet soutient l’étude inspirante de Beradt (1968) de rêves dans l’Allemagne Nazie, ainsi que des études récentes de rêves en lien avec la COVID et des publications récentes sur la nature sociale du rêve.Alternate :Dieses Projekt untersucht, was Träume über die Reaktion der kollektiven Psyche auf die COVID‐19‐Pandemie im ersten Jahr vor der Entwicklung von Impfstoffen verraten könnten. Eine kurze Umfrage, die an Jungianische Kollegen und Organisationen sowie an verschiedene Social‐Media‐Sites verteilt wurde, lud Menschen ein, online einen Traum im Zusammenhang mit der COVID‐19‐Pandemie einzureichen. Vierhundertsechsunddreißig Träume wurden eingereicht. Vierzig weitere russische Träume wurden gesammelt und von russischen Kollegen zugesandt. Unter Verwendung qualitativer Forschungsmethoden auf der Grundlage phänomenologischer Hermeneutik kategorisierten und zählten die Forscher die Bandbreite der COVID‐Bilder. Darüber hinaus beschreiben die Forscher eine Reihe psychischer Reaktionen auf die Pandemie, darunter Entsetzen, Trauer, Krankheit, soziale Zwietracht und Gewalt, aber auch Bilder von Heilung und Transformation, gesteigertem Gemeinschaftsgefühl und spiritueller Erneuerung. Mehrere heilende Albträume werden präsentiert. Heilend alchemistische und Anima/Animus‐Bilder werden beschrieben. Zwölf Träume werden vorgestellt und präsentiert. Es wird der Schluß gezogen, daß die im Selbst verwurzelte kollektive Psyche eine heilende Ressource für soziale und kulturelle Traumata darstellt. Dieses Projekt unterstützt Beradts (1968) inspirierende Studie über das Träumen in Nazi‐Deutschland sowie neuere Studien zu COVID‐bezogenen Träumen und neuere Veröffentlichungen über die soziale Natur des Träumens.Alternate :Questo progetto esplora cosa possono rivelare i sogni sulla risposta della psiche collettiva alla pandemia di COVID‐19 nel suo primo anno, prima dello sviluppo dei vaccini. Un breve sondaggio, distribuito a colleghi e organizzazioni junghiane, e a vari siti di social media, ha invitato le persone a presentare online un sogno legato alla pandemia di COVID‐19. Sono stati inviati 436 sogni. Altri quaranta sogni russi sono stati raccolti e inviati da colleghi russi. Usando metodi di ricerca qualitativa basati sull’ermeneutica fenomenologica, i ricercatori hanno categorizzato e contato l’assortimento dell’immaginario relativo al COVID‐19. Inoltre, i ricercatori descrivono una serie di risposte psichiche alla pandemia, incluso orrore, dolore, malattia, tensione sociale e violenza, ma anche immagini di guarigione e trasformazione, maggiore senso di comunità , e rinnovamento spirituale. Vengono presentati diversi incubi che sono stati terapeutici. Vengono descritte la guarigione alchemica e le immagini di anima/animus. Vengono introdotti e presentati dodici sogni. Gli Autori concludono che la psiche collettiva, radicata nel Sé, è una risorsa curativa per il trauma sociale e culturale. Questo progetto supporta lo stimolante studio di Berardt (1968) sui sogni nella Germania nazista, così come studi recenti sui sogni legati al COVID‐19 e con le recenti pubblicazioni sulla natura sociale dei sogni.Alternate :Ð' этом проекте исследуется, что могут рассказать сновидения о реакции коллективной психики на пандемию COVID‐19 в течение первого года, до того, как были разработаны вакцины. Ð' краткой анкете, рассылавшейся юнгианским коллегам и организациям, а также размещенной в социальных сетях, респондентам предлагалось предоставить в электронном виде свои сновидения, связанные с пандемией COVID‐19. Было прислано четыреста тридцать шесть сновидений. Еще сорок сновидений на русском языке было собрано и предоставлено российскими коллегами. Используя качественные методы исследования, основанные на феноменологической герменевтике, исследователи произвели подсчеты и классификацию и получили диапазон образов COVID. Кроме того, исследователи описали целый ряд психологических реакций на пандемию, среди которых ужас, горе, заболевания, социальные разногласия и насилие, но вместе с тем и образы исцеления и трансформации, усиленное чувства общности и духовное обновление. Описывается ряд кошмарных сновиденийс целебным эффектом. Приведены исцеляющие алхимические образы анимы/анимуса. Подробно представлено двенадцать сновидений. Исследователи приходят к заключению, что Ñ€ÐµÑ ÑƒÑ€ÑÐ¾Ð¼ для исцеления социальных и культурных травм является коллективная психика, опирающаяся на Самость. Ð'ыводы проекта подтверждают результаты вдохновляющего исследования Берадта о сновидениях в нацистской Ð"ермании (1968), а также недавних исследований сновидений, связанных с COVID, и публикаций о социальной природе сновидений.Alternate :Este proyecto explora lo que los sueños podrían revelar sobre la respuesta de la psique colectiva a la pandemia de COVID‐19 en su primer año, antes del desarrollo de las vacunas. A través de una breve encuesta, distribuida entre colegas y organizaciones Junguianas, así como en diversas redes sociales, se invitó a la gente a enviar en línea un sueño relacionado con la pandemia de COVID‐19. Se presentaron 436 sueños. Otros cuarenta sueños rusos fueron posteriormente recogidos y enviados por colegas rusos. Utilizando métodos de investigación cualitativa basados en la hermenéutica fenomenológica, los investigadores categorizaron y contaron una gama de imágenes de COVID. Además, los investigadores describen una serie de respuestas psíquicas a la pandemia, que incluyen horror, dolor, enfermedad, discordia social y violencia, pero también imágenes de curación y transformación, aumento del sentido de comunidad y renovación espiritual. Se presentan varias pesadillas curativas. Se describen imágenes alquímicas curativas y de anima/animus. Se introducen y presentan doce sueños. Se concluye que la psique colectiva, enraizada en el Self, es un recurso curativo para el trauma social y cultural. Este proyecto apoya el inspirador estudio de Beradt (1968) sobre los sueños en la Alemania nazi, así como estudios recientes sobre los sueños relacionados con el COVID y con publicaciones recientes sobre la naturaleza social de los sueños.Alternate :为世界做梦:æ–°å† ç–«æƒ…æœŸé—´æ¢¦å¢ƒçš„è£æ ¼å­¦æ´¾ç ”ç©¶è¿™ä¸ªé¡¹ç›®æŽ¢è®¨äº†æ¢¦å¢ƒå¦‚ä½•æ­ç¤ºé›†ä½"心灵对COVID‐19疫情所做出的反应, 这些梦境发生在疫情第一年, åœ¨ç–«è‹—å¼€å‘ä¹‹å‰ã€‚æœ¬ç ”ç©¶å‘è£æ ¼å­¦æ´¾åŒè¡Œå'Œç»„织, 以及通过各种社会åª'ä½"网站分发了一份简短的调查, 邀请人们在线提交与COVID‐19疫情有关的梦。共收集到四百三十六个梦。另外还收集了40个俄罗斯人的梦, å¹¶ç”±ä¿„ç½—æ–¯åŒäº‹æäº¤ã€‚ç ”ç©¶ä½¿ç”¨äº†åŸºäºŽçŽ°è±¡å­¦è¯ é‡Šå­¦çš„å®šæ€§ç ”ç©¶æ–¹æ³•, ç ”ç©¶äººå‘˜å¯¹ä¸Žæ–°å† ç›¸å…³çš„æ„è±¡è¿›è¡Œäº†åˆ†ç±»å'Œç»Ÿè®¡ã€‚此外, ç ”ç©¶äººå‘˜è¿˜æè¿°äº†æ¢¦ä¸­äººä»¬å¯¹ç–«æƒ…åšå‡ºçš„ä¸€ç³»åˆ—å¿ƒç†ååº”, 包括恐怖、悲伤、疾病、社会不å'Œè°å'Œæš´åŠ›, 但也有治愈å'Œè½¬å˜çš„意象、增强的社区感å'Œç²¾ç¥žæ›´æ–°çš„æ„è±¡ã€‚ç ”ç©¶ä»‹ç»äº†å‡ ä¸ªå¸¦æœ‰æ²»æ„ˆæ€§çš„å™©æ¢¦ã€‚æè¿°äº†æ²»æ„ˆæ€§çš„ç‚¼é‡‘æœ¯å'Œé˜¿å°¼çŽ›/阿尼玛斯意象。介绍并展示了12个梦。ç»"论是, æ¤æ ¹äºŽ “自性”的集ä½"心灵是治疗社会å'Œæ–‡åŒ–创伤的一种资源。这个项目的ç»"果支持了Beradt(1968)在纳粹德国的梦境的é¼"èˆžäººå¿ƒçš„ç ”ç©¶ç»"æžœ, ä¹Ÿä¸Žæœ€è¿‘å…³äºŽæ–°å† æ¢¦å¢ƒç ”ç©¶çš„ç»"æžœ, 及最近发表的关于梦境的社会性质的ç»"果一致。

Positive Prospective Mental Imagery Characteristics in Young Adults and Their Associations with Depressive Symptoms.

Background: Positive prospective mental imagery plays an important role in mental well-being, and depressive symptoms have been associated with difficulties in generating positive prospective mental images (PPMIs). We used a mobile app to gather PPMIs generated by young adults during the COVID-19 pandemic and analyzed content, characteristics, and associations with depressive symptoms. Methods: This is a secondary analysis of a randomized controlled trial with 95 healthy young adults allocated into two groups (intervention and control). Participants used the mobile app decreasing mental health symptoms for seven consecutive days. Fifty participants in the intervention group reported PPMIs at least three times per day using a mobile app inducing PPMI generation. We categorized entries into themes and applied moderation models to investigate associations between PPMI characteristics and depressive symptoms. Results: We distinguished 25 PPMI themes. The most frequent were related to consuming food and drinks, watching TV/streaming platforms, and doing sports. Vividness and ease of generation of PPMIs, but not their anticipation, pleasure intensity or number of engagements with the app were associated with fewer depressive symptoms. Conclusions: We identified PPMI themes in young adults and found significant negative associations between depressive symptoms and vividness and generation ease of PPMIs. These results may inform prevention and intervention science, including the design of personalized interventions. We discuss implications for future studies and treatment development for individuals experiencing diminished PPMI. Supplementary Information: The online version contains supplementary material available at 10.1007/s10608-023-10378-5.

An Imagination - Procrastination Link? The Role of Efficacy Beliefs, Visual Imagery, and Affect in Academic Procrastination.

Previous studies have established that there is a relationship between efficacy beliefs and procrastination. Theory and research on motivation suggest that visual imagery (the capacity to create vivid mental images) may be implicated in this relationship and in the general tendency to procrastinate. This study's aim was to build on prior work by examining the role of visual imagery, as well as roles of other specific personal and affective factors, in predicting academic procrastination. Self-efficacy for self regulatory behavior was observed to be the strongest predictor, predicting lower rates of academic procrastination, though this effect was significantly greater for individuals who scored higher on a measure of visual imagery. Visual imagery predicted higher levels of academic procrastination when included in a regression model with other significant factors, though this relationship did not hold for individuals who scored higher on self regulatory self-efficacy, suggesting that this self-belief may shield individuals who would otherwise be disposed to procrastination behavior. Negative affect was observed to predict higher levels of academic procrastination, contrary to a previous finding. This result highlightsthe importance of considering social contextual issues that may influence emotional states, such as those surrounding the Covid-19 epidemic, in studies of procrastination.

Quality Assurance of Chest X-ray Images with a Combination of Deep Learning Methods

Background: Chest X-ray (CXR) imaging is the most common examination;however, no automatic quality assurance (QA) system using deep learning (DL) has been established for CXR. This study aimed to construct a DL-based QA system and assess its usefulness. Method: Datasets were created using over 23,000 images from Chest-14 and clinical images. The QA system consisted of three classification models and one regression model. The classification method was used for the correction of image orientation, left–right reversal, and estimating the patient's position, such as standing, sitting, and lying. The regression method was used for the correction of the image angle. ResNet-50, VGG-16, and the original convolutional neural network (CNN) were compared under five cross-fold evaluations. The overall accuracy of the QA system was tested using clinical images. The mean correction time of the QA system was measured. Result: ResNet-50 demonstrated higher performance in the classification. The original CNN was preferred in the regression. The orientation, angle, and left–right reversal of all images were fully corrected in all images. Moreover, patients' positions were estimated with 96% accuracy. The mean correction time was approximately 0.4 s. Conclusion: The DL-based QA system quickly and accurately corrected CXR images.

Is this the truth? A study of how undergraduates relate to potentially manipulative and misleading online media imagery

This mixed method arts-based study aims to answer the research question: How do undergraduates enrolled in an online course investigating visual culture at a large public Midwestern university relate to possibly manipulative and misleading online media imagery? Before educators can attempt to improve student media literacy, they must first understand how students experience visual media online. A holistic approach where students visualize their relationship with online media, respond to a survey of their attitudes and behaviors concerning online media, and demonstrate their abilities on anassessment of their critical media literacy, provides a rich snapshot of how members of Generation Z or Zoomers relate to online media.My findings reveal that students are extremely susceptible to manipulative or misleading media and that their unwarranted overconfidence may compound that vulnerability. Meanwhile, their art depicted feelings of anxiety, distrust, confusion, and helplessness regarding their relationships with media. With the increasing reliance on online media, exacerbated by the COVID-19 pandemic, it seems as though misinformation online will only continue to proliferate with increasingly dangerous consequences in the real world. As a result, educators, especially art educators, are urged to try to help students develop visual and critical media literacy skills. Recommendations and lesson ideas are provided. (PsycInfo Database Record (c) 2023 APA, all rights reserved)