Using Adaptive Interaction to Simplify Caregiver’s Communication with People with Dementia Who Cannot Speak

Caregivers find it difficult to interact with people with dementia who have lost the capacity for speech. Adaptive Interaction is a simplified approach that uses the nonverbal fundamentals of communication to connect with people who can no longer speak. Here we present Adaptive Interaction as a method for equipping caregivers with these nonverbal skills to increase communication with the people they care for. Six caregivers were each paired with one individual with dementia and trained in Adaptive Interaction. After receiving training in Adaptive Interaction, caregivers identified more communicative behaviours in their interactions partners and engaged in more frequent positive social behaviours and meaningful actions during interactions. These findings suggest that it is possible to equip staff to use simplified communication based on nonverbal fundamentals to connect with people with dementia who can no longer speak.

Personally Tailored Survival Prediction of Patients With Follicular Lymphoma Using Machine Learning Transcriptome-Based Models

Follicular Lymphoma (FL) has a 10-year mortality rate of 20%, and this is mostly related to lymphoma progression and transformation to higher grades. In the era of personalized medicine it has become increasingly important to provide patients with an optimal prediction about their expected outcomes. The objective of this work was to apply machine learning (ML) tools on gene expression data in order to create individualized predictions about survival in patients with FL. Using data from two different studies, we were able to create a model which achieved good prediction accuracies in both cohorts (c-indexes of 0.793 and 0.662 in the training and test sets). Integration of this model with m7-FLIPI and age rendered high prediction accuracies in the test set (cox c-index 0.79), and a simplified approach identified 4 groups with remarkably different outcomes in terms of survival. Importantly, one of the groups comprised 27.35% of patients and had a median survival of 4.64 years. In summary, we have created a gene expression-based individualized predictor of overall survival in FL that can improve the predictions of the m7-FLIPI score.

Pre-Operative Point-of-Care Assessment of Left Ventricular Diastolic Dysfunction, an Observational Study

Background Left ventricular (LV) diastolic dysfunction is an acknowledged peri-operative risk factor that should be identified before surgery. This study aimed to evaluate a simplified echocardiographic method using e’ and E/e’ for identification and grading of diastolic dysfunction pre-operatively. Methods 96 ambulatory surgical patients were consecutively included to this prospective observational study. Pre-operative transthoracic echocardiography was conducted prior to surgery, and diagnosis of LV diastolic dysfunction was established by comprehensive and simplified assessment, and the results were compared. The accuracy of e’-velocities in order to discriminate patients with diastolic dysfunction was established by calculating accuracy, efficiency, positive (PPV) and negative predictive (NPV) values, and area under the receiver operating characteristic curve (AUROC). Results Comprehensive assessment established diastolic dysfunction in 77% (74/96) of patients. Of these, 22/74 was categorized as mild dysfunction, 43/74 as moderate dysfunction and 9/74 as severe dysfunction. Using the simplified method with e’ and E/e’, diastolic dysfunction was established in 70.8% (68/96) of patients. Of these, 8/68 was categorized as mild dysfunction, 36/68 as moderate dysfunction and 24/68 as severe dysfunction. To discriminate diastolic dysfunction of any grade, e’-velocities (mean<9 cm s−1) had an AUROC of 0.901 (95%CI 0.840-0.962), with a PPV of 55.2%, a NPV of 90.9% and a test efficiency of 0.78. Conclusions The results of this study indicate that a simplified approach with tissue Doppler e’-velocities may be used to rule out patients with diastolic dysfunction pre-operatively, but together with E/e’ ratio the severity of diastolic dysfunction may be overestimated. Trial registration: Clinicaltrials.gov, Identifier: NCT 03349593. Date of registration 2017-11-21. https://clinicaltrials.gov.

Social emotional ability development (SEAD): An integrated model of practical emotion-based competencies

Social emotional abilities (i.e., specific skills), defined as the set of cognitive abilities, emotion-based knowledge, and behavioral competencies (i.e., skill levels) that facilitate adaptively employing prosocial processes and behaviors (i.e., “actions”), such as emotional regulation and sympathetic and empathetic response behaviors, is contemporarily modeled and measured as emotional intelligence. This conceptualization can be problematic, however, as the two concepts are not the same and traditional methods of measuring emotional intelligence can have limited practical utility. The social emotional ability development (SEAD) theoretical model introduced in this treatise represents a pragmatic and simplified approach to the development of social emotional ability and competency as abstracted from constructs of emotional intelligence, social intelligence, and sociocultural learning theory. Further, the SEAD model reaches beyond the individual as the unit of analysis to explore, conceptualize, differentiate, investigate, and define the hierarchal, bi-directional, and contextual nature of the dimensions of social emotional ability within close relationships. Implications for how the SEAD model can be used by researchers, practitioners, educators, individuals, families, and couples across a broad spectrum of domains and interventions are discussed.

Less Is More: Audience Cognition of Comic Simplification in the Characters of Peking Opera

A simplified approach was used to determine if “Less is More” is still a trend in comics’ Peking opera characters. There were 225 website volunteers who took part in the study. Via a questionnaire survey and analysis, this study explored the feasibility of “simplification” in comedy. The results indicate that the proposed “simplifying” approach can be applied to the creation of dramatic characters, but the scale of simplification must be adjusted flexibly to suit different subjects. For audiences, there is not much recognition and sympathy for the works that are simplified in the extreme and the current symbolization. The simplification used in this study is merely the first step in testing the usefulness of simplification as an approach. It is used as a means of understanding the cognition of the audience to accept the simple features of Peking opera characters. In subsequent studies, the proposed “simplified” approach is necessary to adapt and improve with a view to practical application. It also requires an in-depth analysis of the cognitive differences of the different participants according to the cognitive and communication theories of artistic creation.

A Mass Balance Approach in Sediment Budgeting of Large Alluvial Rivers with special emphasis on the Brahmaputra in Assam

Morphology of an alluvial river channel is the consequence of erosion, sediment transport and sedimentation in a river. Sediment budget accounts for the sources, sinks and redistribution pathways of sediments, solutes and nutrients in a unit region over unit time. Human activities are the most important factors that affect the variation in the pattern of river sediment load. This paper discusses sediment budget of a few large rivers by review of literature and estimation of sediment budget of Brahmaputra River in Assam using mass balance approach. An attempt has also been made to discuss human and climatic impact on sediment load of major rivers of the world. Total sediment load in the Brahmaputra River at downstream location (India-Bangladesh border) was estimated to be 814×106 t/year. Considering 10% of sediment load of the Brahmaputra as bed load, suspended sediment load at downstream was estimated to be 733×106 t/year. Tributaries, bank erosion and scouring of river bed were found to contribute 52%, 27% and 21% respectively to sediment load of Brahmaputra at downstream locations. In spite of limitations of the dependable data, future complexity due to climate change impact and hydropower dam initiative in upstream of the River, the study is a simplified approach in sediment budgeting of the Brahmaputra.

Face Mask Detection Using Machine Learning

COVID-19 epidemic has affected our daily life disturbing the world trade and transport. Wearing a face mask has become a new necessity for safety. In the near future, many institutions will ask the customers to wear masks to avail of their services. Therefore, face mask detection has become a necessity to help society. This paper presents a simplified approach to achieve this purpose using some packages like TensorFlow, Keras, OpenCV and Scikit-Learn. This method detects the face from the image in frame and then identifies if it has worn a mask or not. As in a surveillance task, it can also detect a face along with a mask in movement through image processing. The method attains accuracy up to 93% and 91.2% respectively on two datasets. We explore optimized values of parameters using the Sequential CNN (Convolutional Neural Network) model to detect the presence of masks correctly. Keywords: Face Mask Detection, Convolutional Neural Network, TensorFlow, Keras, Image Processing

Method versatility in RNA extraction-free PCR detection of SARS-CoV-2 in saliva samples

Early in the pandemic, a simple, open-source, RNA extraction-free RT-qPCR protocol for SARS-CoV-2 detection in saliva was developed and made widely available. This simplified approach (SalivaDirect) requires only sample treatment with proteinase K prior to PCR testing. However, feedback from clinical laboratories highlighted a need for a flexible workflow that can be seamlessly integrated into their current health and safety requirements for the receiving and handling of potentially infectious samples. To address these varying needs, we explored additional pre-PCR workflows. We built upon the original SalivaDirect workflow to include an initial incubation step (95°C for 30 minutes, 95°C for 5 minutes or 65°C for 15 minutes) with or without addition of proteinase K. The limit of detection for the workflows tested did not significantly differ from that of the original SalivaDirect workflow. When tested on de-identified saliva samples from confirmed COVID-19 individuals, these workflows also produced comparable virus detection and assay sensitivities, as determined by RT-qPCR analysis. Exclusion of proteinase K did not negatively affect the sensitivity of the assay. The addition of multiple heat pretreatment options to the SalivaDirect protocol increases the accessibility of this cost-effective SARS-CoV-2 test as it gives diagnostic laboratories the flexibility to implement the workflow which best suits their safety protocols.