Cognitive Aid for Anesthetic Preparation in An Emergency Situation: A Simulation-Based Study

When anesthesia checklists and preparations are performed urgently, omissions may occur and be deleterious to the patient. The aim of this study was to evaluate in simulation the interest of a cognitive aid to effectively prepare an anesthetic room for an emergency. In a prospective single-center simulation-based study, 32 anesthesia residents had to prepare an anesthetic room in an emergency scenario, without cognitive aid in the first phase. Three months later (phase 2), they were randomly assigned to receive a cognitive aid (aid group) or no additional aid (control) and were involved in the same scenario. The primary outcome was the validation rate of each essential item in the first 5 min in phase 2. Eight items were significantly more frequently completed in the first 5 min in the aid group in phase 2 (vs. phase 1), compared with two only in the control group. However, there were no significant differences in the overall number of completed items between the two groups, as both groups completed significantly more items in phase 2, either in the first 5 min (19 (14–23) vs. 13 (9–15) in phase 1 for all residents, p < 0.001) or without time limit. Preparation times were reduced in phase 2 in both groups. In conclusion, the use of a cognitive aid allowed anesthesia residents to complete some safety items of a simulated urgent anesthesia preparation more frequently. In addition, despite daily clinical experience, a single simulation session improved anesthesia preparation and reduced the preparation time with or without cognitive aid.

MARS: a tool for haplotype-resolved population-based structural variation detection

Motivation: Linked-reads enables genome-wide phased diploid assemblies. These haplotype-resolved assemblies allow us to genotype structural variants (SVs) with a high sensitivity and be able to further phase them. Yet, existing SV callers are designed for haploid genome assemblies only, and there is no tool to call SV from a large population of diploid assemblies which can define and refine SVs from a global view. Results: We introduce MARS (Multiple Alignment-based Refinement of Svs) in linked-reads for the detection of the most common SV types - indels from diploid genome assemblies of a large population. We evaluated SVs from MARS based on Mendelian law of inheritance and PacBio HiFi reads and it achieved a high validation rate around 73%-87% for indels that we have selected from 34 assembled samples.

ANALISIS RASIO KEUANGAN UNTUK MEMPREDIKSI FINANCIAL DISTRESS PERUSAHAAN MANUFAKTUR DI BEI

ABSTRACT This study aims to examine the prediction of the company's financial difficulties using the Altman Z-score 1968 model and the effect of financial ratios including working capital to total assets, retained earnings to total assets, earnings before interest and tax to total assets, market value equity to book value. of total liabilities, and sales to total assets on financial distress. The sample used in this study is a manufacturing company listed on the Indonesia Stock Exchange (BEI) 2015-2019. Sampling in this study using purposive sampling method and obtained 64 companies. The results showed that the variables Working Capital to Total Assets (X1), Retained Earnings to Total Assets (X2), Earnings Before Interest and Tax to Total Assets (X3), Market Value Equity To Book Value of Total Liabilities (X4), and Sales to Total Assets (X5) has a positive effect on financial distress, and the most significant effect on financial distress is the variable Retained Earnings to Total Assets. From the results of SPSS 17.0 processing, the equation Z = -1,813 + 1,216 X1 + 1,837 X2 + 0.122 X3 + 0.070 X4 + 0.506 X5 is produced. Meanwhile, the discriminant model that was formed had a high enough validation rate, namely 97.6%. Keywords: Financial ratio analysis; Financial distress; Altman Z-score

Pharmaceutical Product Liability, Litigation Regimes, and the Propensity to Patent: An Empirical Firm-Level Investigation

Do different pharmaceutical product liability regimes in different countries induce propensity to patent? We exploit the variation in pharmaceutical liability and litigation rules across firms in the pharmaceutical industry and countries to explain the firm-level propensity to patent. Drawing on a large dataset from European Patent Office (EPO) covering over 9,950 pharmaceutical patents from 63 countries over the period 1991–2015, we compute the conditional probabilities of individual pharmaceutical firms to acquire a valid-based patent on the validation outcomes and examine whether different liability regimes encourage or deter firm-level propensity to patent. Our empirical strategy addresses firm-level idiosyncrasies, country-level unobserved effects, and common technology shocks that potentially invoke omitted variable bias in the effects of liability regimes on the propensity to patent. Our investigation reveals that liability regimes combined with damage caps, broad statutory excuses, and reversed burden of proof have a strong positive effect on the firm-level patent stock and a negative effect upon EPO patent validation rate. The evidence suggests that not all liability rules and related litigation procedures are created equal. Firms are systematically more likely to hold (firm-level patent stock) valid patents at the EPO when the liability and litigation rules are not complex and when the damage cap, broad statutory excuses, and reversed burden of proof are introduced.

Using open-source high resolution remote sensing data to determine the access to buildings in the context of passenger transport

&lt;p&gt;Routing on a road network requires geographical points on the road network that correspond best to the addresses of the given origin and destination, here called snapping points. The technique to determine such snapping points is also called offline map matching. Conventional routing machines use the shortest perpendicular distance from a building&amp;#8217;s centroid to the road network for this purpose. However, in some cases, this technique leads to suboptimal results when the access to a building is not reachable from the road segment with the shortest perpendicular distance. We used open-source data &amp;#8212; multispectral images, OpenStreetMap data, Light Detection and Ranging (LiDAR) data &amp;#8212; to perform a cost-distance analysis and determined the most likely access to buildings. Therefore, we assumed that the path to the building shows less vegetation cover, minimal slope of the terrain and avoids building footprints. Our results are validated based on a predetermined Ideal Snapping Area for different weightings of the parameters vegetation, slope und building footprints. We also compared our results with a conventional routing machine (Open Source Route Machine - ) that uses the perpendicular distance. The validation-rate of our approach is up to 90%, depending on the weighting of chosen parameters, whereas the conventional routing machine shows a validation-rate of 81%. The optimized snapping points can be used to determine enhanced stop locations in passenger transport to improve services such as door-to-door transportation (e.g. demand-responsive transport).&lt;/p&gt;

PENGEMBANGAN BAHAN AJAR TEMATIK BERBASIS SAINS TEKNOLOGI MASYARAKAT (STM) UNTUK MENINGKATKAN KOMPETENSI SISWA DI SDN 1 ALUE DUA

This development research aims to produce thematic teaching materials that are feasible and effective to use as additional teaching materials besides textbooks on the theme of living things and the environment. The research was conducted at SDN 1 Alue Dua Langsa. The research sample was students of class V B SDN 1 Alue Dua. The method in this research is the method of research and development (Research and Development) with the Three D (3D) development model. The results of increasing student competence in the form of cognitive abilities using pre-experimental methods with One Group Pretest-Postest Design. The results showed that the additional thematic teaching materials in the form of modules based on Community Science Technology (STM) were declared valid by experts / experts with a validation rate of 84%. Furthermore, there was an increase in students' cognitive abilities which could be seen from the post-test average score increased to 70.5 from the pretest score of 39.27 and the N-Gain score on the high criteria, namely 71.28. So it can be concluded that thematic teaching materials in the form of STM-based modules are feasible to use and have a significant effect on improving the competence of students' cognitive abilities. Abstrak Penelitian pengembangan ini bertujuan untuk menghasilkan bahan ajar tematik yang layak dan efektif digunakan sebagai bahan ajar tambahan selain buku paket pada tema makhluk hidup dan lingkungan. Penelitian dilakukan di SDN 1 Alue Dua Kota langsa dengan sampel penelitian adalah siswa kelas V B SDN 1 Alue Dua. Metode dalam penelitian ini adalah metode penelitian dan pengembangan (Researchand Development) dengan model pengembangan Three D (3D). Hasil peningkatan kompetensi siswa berupa kemampuan kognitif menggunakan metode pre-experimental dengan One Group Pretest-Postest Design. Hasil penelitian menunjukkan bahwa bahan ajar tematik tambahan berupa modul berbasis Sains Teknologi Masyarakat (STM) dinyatakan valid oleh ahli/pakar dengan tingkat validasi sebesar 84%. Selanjutnya terdapat peningkatan kemampuan kognitif siswa yang dapat dilihat dari skor rata rata postes meningkat menjadi 70,5 dari skor pretes 39,27 dan skor N-Gain pada kriteria tinggi yaitu 71,28. Sehingga dapat disimpulkan bahwa bahan ajar tematik berupa modul berbasis STM layak digunakan dan berpengaruh signifikan terhadap peningkatan kompetensi kemampuan kognitif siswa di SDN 1 Alue Dua. Kata Kunci: Bahan ajar, Tematik, Sains Teknologi Masyarakat, Kompetensi

Integrative analysis of structural variations using short-reads and linked-reads yields highly specific and sensitive predictions

Genetic diseases are driven by aberrations of the human genome. Identification of such aberrations including structural variations (SVs) is key to our understanding. Conventional short-reads whole genome sequencing (cWGS) can identify SVs to base-pair resolution, but utilizes only short-range information and suffers from high false discovery rate (FDR). Linked-reads sequencing (10XWGS) utilizes long-range information by linkage of short-reads originating from the same large DNA molecule. This can mitigate alignment-based artefacts especially in repetitive regions and should enable better prediction of SVs. However, an unbiased evaluation of this technology is not available. In this study, we performed a comprehensive analysis of different types and sizes of SVs predicted by both the technologies and validated with an independent PCR based approach. The SVs commonly identified by both the technologies were highly specific, while validation rate dropped for uncommon events. A particularly high FDR was observed for SVs only found by 10XWGS. To improve FDR and sensitivity, statistical models for both the technologies were trained. Using our approach, we characterized SVs from the MCF7 cell line and a primary breast cancer tumor with high precision. This approach improves SV prediction and can therefore help in understanding the underlying genetics in various diseases.

DeepMosaic: Control-independent mosaic single nucleotide variant detection using deep convolutional neural networks

Introductory paragraphMosaic variants (MVs) reflect mutagenic processes during embryonic development1 and environmental exposure2, accumulate with aging, and underlie diseases such as cancer and autism3. The detection of MVs has been computationally challenging due to sparse representation in non-clonally expanded tissues. While heuristic filters and tools trained on clonally expanded MVs with high allelic fractions are proposed, they showed relatively lower sensitivity and more false discoveries4–9. Here we present DeepMosaic, combining an image-based visualization module for single nucleotide MVs, and a convolutional neural networks-based classification module for control-independent MV detection. DeepMosaic achieved a higher accuracy compared with existing methods on biological and simulated sequencing data, with a 96.34% (158/164) experimental validation rate. Of 932 mosaic variants detected by DeepMosaic in 16 whole genome sequenced samples, 21.89-58.58% (204/932-546/932) MVs were overlooked by other methods. Thus, DeepMosaic represents a highly accurate MV classifier that can be implemented as an alternative or complement to existing methods.

DEVELOPMENT OF 3-DIMENSIONAL SNAKE AND LADDER GAME: IMPLEMENTATION WITH SECOND GRADE STUDENTS OF SDN 37 PEKANBARU

This study aims to test the feasibility of a three-dimensional snake and ladder game to reflect the thematic learning material from theme 6 subthemes 2 about taking care of animals around me. This study was conducted in June 2020 in one of second grade parent house of SD N 37 Pekanbaru. This research is motivated by the lack of learning media that can be used to primary school students. The learning outside learning hours is important for students to be able to have leraning activities, working together in groups, respecting friends' opinions and interacting. The 3D snake and ladder game is an interesting game. The development of 3D snake and ladder game is carried out according to the Research and Development (R&D) method according to the procedure of ADDIE development models. The feasibility test of 3D snake and ladder game product had validation rate of 87.5% from the media expert in the "very acceptable" category and 92.5% from the content expert in the "very acceptable" category. Student responses to the snake and ladder game developed as a whole scored 95.97% in the "excellent" category.

Somatic mutations in Parkinson disease are enriched in synaptic and neuronal processes

The role of somatic mutations in complex diseases, including neurodevelopmental and neurodegenerative disorders, is becoming increasingly clear. To explore their relevance in sporadic Parkinson disease, we performed whole-exome sequencing in blood and four brain regions of ten patients. We identified 59 candidate somatic single nucleotide variants (sSNVs) through sensitive calling and extensive filtering. We validated 27 of them with amplicon-based deep sequencing, with a 70% validation rate for the highest-confidence variants. Most of the sSNVs were exclusively called in blood but were also found in the brain tissues with the ultra-deep amplicon sequencing, demonstrating the strength of multi-tissue sampling designs. We could confirm between 0 and 6 sSNVs per patient and generally those with a shorter lifespan carried more variants. Remarkably, the validated sSNVs are enriched in genes with synaptic functions that are co-expressed with genes previously associated with Parkinson disease.