DeepSig: Deep learning improves signal peptide detection in proteins

Motivation: The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Results: Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. Availability and implementation: DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website

One-Stop Dispensing:Hospital Costs and Patient Perspectives on Self-Management of Medication

(1) Objective: To assess hospital medication costs and staff time between One-Stop Dispensing (OSD) and the Traditional Medication System (TMS), and to evaluate patient perspectives on OSD. (2) Methods: The study was conducted at Hvidovre Hospital, University of Copenhagen, Denmark in an elective gastric surgery and acute orthopedic surgery department. This study consists of three sub-studies including adult patients able to self-manage medication. In Sub-study 1, staff time used to dispense and administer medication in TMS was assessed. Medication cost and OSD staff time were collected in Sub-study 2, while patient perspectives were assessed in Sub-study 3. Medication costs with two days of discharge medication were compared between measured OSD cost and simulated TMS cost for the same patients. Measured staff time in OSD was compared to simulated staff time in TMS for the same patients. Patient satisfaction related to OSD was evaluated by a questionnaire based on a five-point Likert scale (‘very poor’ (1) to ‘very good’ (5)). (3) Results: In total, 78 elective and 70 acute OSD patients were included. Overall, there was no significant difference between OSD and TMS in medication cost per patient ($2.03 [95% CI −0.57–4.63]) (p = 0.131). Compared with TMS, OSD significantly reduced staff time by an average of 12 min (p ≤ 0.001) per patient per hospitalization. The patients’ satisfaction for OSD was high with an average score of 4.5 ± 0.7. (4) Conclusion: There were no differences in medication costs, but staff time was significantly lower in OSD and patients were overall satisfied with OSD

Towards a hybrid testing process unifying exploratory testing and scripted testing

CONTEXT Given the current state of the art in research, practitioners are faced with the challenge of choosing scripted testing (ST) or exploratory testing (ET). OBJECTIVE This study aims at systematically incorporating strengths of ET and ST in a hybrid testing process to overcome the weaknesses of each. METHOD We utilized systematic review and practitioner interviews to identify strengths and weaknesses of ET and ST. Strengths of ET were mapped to weaknesses of ST and vice versa. Noblit and Hare's lines-ofargument method was used for data analysis. The results of the mapping were used as input to codesign a hybrid process with experienced practitioners. RESULTS We found a clear need to create a hybrid process as follows: (i) both ST and ET provide strengths and weaknesses, and these depend on some particular conditions, which prevents preference of one approach to another; and (ii) the mapping showed that it is possible to address the weaknesses in one process by the strengths of the other in a hybrid form. With the input from literature and industry experts, a flexible and iterative hybrid process was designed. CONCLUSIONS Practitioners can clearly benefit from using a hybrid process given the mapping of advantages and disadvantage

Audio-Visual Feedback for Self-monitoring Posture in Ballet Training

An application for ballet training is presented that monitors the posture position (straightness of the spine and rotation of the pelvis) deviation from the ideal position in real-time. The human skeletal data is acquired through a Microsoft Kinect v2. The movement of the student is mirrored through an abstract skeletal figure and instructions are provided through a virtual teacher. Posture deviation is measured in the following way: Torso misalignment is calculated by comparing hip center joint, shoulder center joint and neck joint position with an ideal posture position retrieved in an initial calibration procedure. Pelvis deviation is expressed as the xz-rotation of the hip-center joint. The posture deviation is sonified via a varying cut-off frequency of a high-pass filter applied to floating water sound. The posture deviation is visualized via a curve and a rigged skeleton in which the misaligned torso parts are color-coded. In an experiment with 9-12 year-old dance students from a ballet school, comparing the audio-visual feedback modality with no feedback leads to an increase in posture accuracy (p < 0.001, Cohen's d = 1.047). Reaction card feedback and expert interviews indicate that the feedback is considered fun and useful for training independently from the teacher

Satisfaction Measurement of Publics with Bicycle Path

Import 05/08/2014Má bakalářská práce se zabývá problematikou měření spokojenosti veřejnosti s cyklostezkami. Cílem mé bakalářské práce bylo zjistit a následně vyhodnotit spokojenost veřejnosti s cyklistickými trasami v Ostravě a okolí. Výzkum byl proveden pomocí dotazníkového šetření. V závěru mé bakalářské práce jsou navrhnuty návrhy a doporučení pro zvýšení spokojenosti veřejnosti s cyklistickými trasami.My thesis deals with the satisfaction measurement of publics with bicycle path. The goal of my thesis was to find and evaluate satisfaction measurement of publics with bicycle path in Ostrava and around. Research was performed through questionnaire survey. In the end my thesis are designed proposals and recommendations to improve satisfaction of publics with bicycle path.116 - Katedra marketingu a obchoduvelmi dobř