Smart Learning Environment (SLE) in the Fourth Industrial Revolution (IR 4.0)

This paper is attempted to examine the explanatory approach in dealing with SLE by advancing online learning sources. The systematic approach of searching for the relevant articles on SLE in IR 4.0 has been widely identified through two electronic databases, Scopus and Web of Sciences. Through adopting such digitally systematic search program, identification was made on the various elements in terms of online learning resources (OLR). This attempts to propose the SLE framework model with an innovative approach in enhancing the learning through incorporating IR 4.0 platform to utilize the variety of information sources together with knowledge attribution in the higher education (HE). The contribution provides theoretical framework with the guideline of well-adapted performance in the educational activities as the new normal trend. In achieving this attainment, the readiness of both instruction facilities and accessibility procedure is significantly the main basis in ensuring the process flow in enlarging the digital learning.

Motor Point Heatmap of the Calf

Background: Contractions of muscles in the calf induced by neuromuscular electrical stimulation (NMES) may prevent venous thromboembolism. However, compliance to NMES-treatment is limited by the use of suboptimal stimulation points which may cause discomfort. Knowledge of where one is most likely to find muscle motor points (MP) could improve NMES comfort and compliance.Aims: To anatomically map the MPs of the calf as well as to calculate the probability of finding a MP in different areas of the calf. Material and Methods: On 30 healthy participants (mean age 37 years) anatomical landmarks on the lower limbs were defined. The location of the four most responsive MPs on respectively the medial and lateral calf muscle bellies were determined in relation to these anatomical landmarks using a MP search pen and a pre-set MP search program with 3 Hz continuous stimulation. The anatomy of the calves was normalized and subdivided into a matrix of 48 (6x8) smaller areas (3x3cm), from upper medial to lower lateral, in order to calculate the probability of finding a MP in one of these areas. The probability of finding a MP was then calculated for each area and presented with a 95% confidence interval.Results: The MP heat map displayed a higher concentration of MPs proximally and centrally on the calf. However, there were wide inter-individual differences in the location of the MPs. The highest probability of finding a MP was in area 4, located proximally and medially, and in area 29, located centrally and around the maximum circumference, both with 50% probability (95% CI: 0.31-0.69). The second highest probability of finding MPs was in areas 9, 10, 16, proximally and medially, all with 47% probability (95% CI: 0.28-0.66). These areas 4, 9, 10, 16 and 29 exhibited significantly higher probability of finding motor points than all areas with a mean probability of 27% and lower (p<0.05) The lateral and distal outskirts exhibited almost zero probability of finding MPs. Conclusions: This MP heat map of the calf could be used to expedite electrode placement and to improve compliance in order to receive consistent and enhanced results of NMES treatments.

Fair and Effective Policing for Neighborhood Safety: Understanding and Overcoming Selection Biases

An accurate crime prediction and risk estimation can help improve the efficiency and effectiveness of policing activities. However, reports have revealed that biases like racial prejudice could exist in policing enforcement, and trained predictors may inherit them. In this work, we study the possible reasons and countermeasures to this problem, using records from the New York frisk and search program (NYCSF) as the dataset. Concretely, we provide analysis on the possible origin of this phenomenon from the perspective of risk discrepancy, and study it with the scope of selection bias. Motivated by theories in causal inference, we propose a re-weighting approach based on propensity score to balance the data distribution, with respect to the identified treatment: search action. Naively applying existing re-weighting approaches in causal inference is not suitable as the weight is passively estimated from observational data. Inspired by adversarial learning techniques, we formulate the predictor training and re-weighting as a min-max game, so that the re-weighting scale can be automatically learned. Specifically, the proposed approach aims to train a model that: 1) able to balance the data distribution in the searched and un-searched groups; 2) remain discriminative between treatment interventions. Extensive evaluations on real-world dataset are conducted, and results validate the effectiveness of the proposed framework.

P068 Abstract tin soldiers Global FOP patient search

While looking for one, you may find another: Tin Soldiers and the search for undiagnosed individuals with Fibrodysplasia Ossificans Progressiva (FOP) Background FOP is an ultra-rare condition where heterozygous, gain-of-function missense mutations in the ACVR1 gene result in progressive heterotopic bone formation in ligaments, tendons and muscles and result in severe disability.1 FOP has an estimated incidence of 0.6–1.3 per million individuals 2,3 suggesting that currently there are ∼8000 patients living with FOP worldwide, however only about 900 patients are currently diagnosed worldwide The diagnosis is made clinically by identification of typical malformations of the great toes as well as inflammatory swellings (flare-ups) that result in progressive and episodic ossification of soft connective tissues, often triggered by trauma.4 Muscle biopsies, though contraindicated, are frequently performed mistakenly during the course of diagnosis, as FOP is not a well-known condition. There is an urgent need to identify individuals with FOP across the globe in order to avoid harmful biopsies and to provide a pathway to care for patients with FOP. Tin Soldiers is a global FOP patient search program utilizing multimedia campaigns aimed at educating and bringing attention to FOP, to find individuals across the globe and to connect them to pathways of care. The mission is to identify every person with FOP who is currently undiagnosed, as well as to deliver education and support to those living with a diagnosis, but not connected to support networks. Once found, all people living with FOP are connected to pathways to care. The aim is to describe the Tin Soldiers global FOP patient search program approach and report early results of the program. Methods Tin Soldiers creates multimedia campaigns to create awareness and to educate medical professionals, healthcare workers, general public and local communities on FOP. At the heart of the communication program is story-telling of people living with FOP, from a feature-length documentary to public service announcements, animated short films and an 8-part Global Master Series—all designed to bring attention to FOP in order to find patients and provide a pathway to diagnosis and care. Importantly diagnosis is not the end of the journey, it’s just the beginning. Results Since official operations commenced in March 2020, Tin Soldiers has trained 535 medical professionals; established an African Clinicians Council of 10 doctors with the intention of mentoring others across the continent; increased the number of African patients with a diagnosis from 25 patients in December 2020–32 in April 2021. Connected previously diagnosed (but not connected) patients to a robust support network and held the first African FOP Family Gathering with clinicians from both South Africa and Nigeria. On the journey, patients with other conditions have been discovered including Juvenile Idiopathic Arthritis (JIA), Progressive Osseus Heteroplasia (POH) and Multiple Osteochondromas (MO). These patients have been diagnosed and connected to both medical care and patient support. Another important outcome is the continued education of doctors globally with the uptake of the CME Master Series in Russia and planned rollouts in Algeria, Nigeria, Kenya, Namibia, Sweden (in partnership with the national patient organization) and Brazil (under the First Lady’s patronage). Conclusion Tin Soldiers offers an innovative model of patient identification, diagnosis, support and education at all levels of care, using the power of story-telling and multi-media marketing. Such a model could be considered for raising the profile of other musculoskeletal or rare conditions and connecting patients to a functioning pathway to care.

Identification of BvgA-Dependent and BvgA-Independent Small RNAs (sRNAs) in Bordetella pertussis Using the Prokaryotic sRNA Prediction Toolkit ANNOgesic

Noncoding small RNAs (sRNAs) are crucial for posttranscriptional regulation of gene expression in all organisms and are known to be involved in the regulation of bacterial virulence. We have investigated the presence of sRNAs in the obligate human pathogen B. pertussis , using transcriptome sequencing (RNA-seq) and the recently developed prokaryotic sRNA search program ANNOgesic.

In Silico identification of a common mobile element insertion in exon 4 of RP1

Mobile element insertions (MEIs) typically exceed the read lengths of short-read sequencing technologies and are therefore frequently missed. Recently, a founder Alu insertion in exon 4 of RP1 has been detected in Japanese patients with macular dystrophy by PCR and gel electrophoresis. We aimed to develop a grep search program for the detection of the Alu insertion in exon 4 of RP1 using unprocessed short reads. Among 494 unrelated Korean patients with inherited eye diseases, 273 patients with specific retinal phenotypes who were previously genotyped by targeted panel or whole exome sequencing were selected. Five probands had a single heterozygous truncating RP1 variant, and one of their unaffected parents also carry this variant. To find a hidden genetic variant, whole genome sequencing was performed in two patients, and it revealed AluY c.4052_4053ins328/p.(Tyr1352Alafs*9) insertion in RP1 exon 4. This AluY insertion was additionally identified in other 3 families, which was confirmed by PCR and gel electrophoresis. We developed simplified grep search program to detect this AluY insertion in RP1 exon 4. The simple grep search revealed a median variant allele frequency of 0.282 (interquartile range, 0.232–0.383), with no false-positive results using 120 control samples. The MEI in RP1 exon 4 was a common founder mutation in Korean, occurring in 1.8% of our cohort. The RP1-Alu grep program efficiently detected the AluY insertion, without the preprocessing of raw data or complex installation processes.

Automated Assignment of Proteoform Classification Levels

Proteoform identification is required to fully understand the biological diversity present in a sample. However, these identifications are often ambiguous because of the challenges in analyzing full length proteins by mass spectrometry. A five-level proteoform classification system was recently developed to delineate the ambiguity of proteoform identifications and to allow for comparisons across software platforms and acquisition methods. Widespread adoption of this system requires software tools to provide classification of the proteoform identifications. We describe here implementation of the five-level classification system in the software program MetaMorpheus, which provides both bottom-up and top-down identifications. Additionally, we developed a stand-alone program called ProteoformClassifier that allows users to classify proteoform results from any search program, provided that the program writes output that includes the information necessary to evaluate proteoform ambiguity. This stand-alone program includes a small test file and database to evaluate if a given program provides sufficient information to evaluate ambiguity. If the program does not, then ProteoformClassifier provides meaningful feedback to assist developers with implementing the classification system. We tested currently available top-down software programs and found that none of them other than MetaMorpheus provided sufficient information regarding identification ambiguity to permit classification.

Estimation of the numerical efficiency of global optimization methods

Currently, test problems are used to test the effectiveness of new global optimization methods. In this article, we analyze test global optimization problems to test the numerical efficiency of methods for their solution. At present, about 200 test problems of unconditional optimization and more than 1000 problems of conditional optimization have been developed. We can find these test problems on the Internet. However, most of these test problems are not informative for testing the effectiveness of global optimization methods. The solution of test problems of conditional optimization, as a rule, has trivial solutions. This allows the parameters of the algorithms to be tuned before these solutions are obtained. In test problems of conditional optimization, the accuracy of the fulfillment of constraints is important. Often, small errors in the constraints lead to a significant change in the value of an objective function. Construction of a new package of test problems to test the numerical efficiency of global optimization methods and compare the exact quadratic regularization method with existing methods.The author suggests limiting oneself to test problems of unconstrained optimization with unknown solutions. A package of test problems of unconstrained optimization is pro-posed, which includes known test problems with unknown solutions and modifications of some test problems proposed by the author. We also propose to include in this package J. Nie polynomial functions with unknown solutions. This package of test problems will simplify the verification of the numerical effectiveness of methods. The more effective methods will be those that provide the best solutions. The paper compares existing global optimization methods with the exact quadratic regularization method proposed by the author. This method has shown the best results in solving most of the test problems. This paper presents some of the results of the author's numerical experiments. In particular, the best solutions were obtained for test problems with unknown solutions. This method allows solving multimodal problems of large dimensions and only a local search program is required for its implementation.