bluuebunny/crossref_metadata_2025 huggingface dataset:
Validity of Two Awake Wear-Time Classification Algorithms for activPAL in Youth, Adults, and Older Adults
Authors: Carlson Jordan A. , Tuz-Zahra Fatima , Bellettiere John , Ridgers Nicola D. , Steel Chelsea , Bejarano Carolina , LaCroix Andrea Z. , Rosenberg Dori E. , Greenwood-Hickman Mikael Anne , Jankowska Marta M. , Natarajan Loki
Published: April 2021

Background: The authors assessed agreement between participant diaries and two automated algorithms applied to activPAL (PAL Technologies Ltd, Glasgow, United Kingdom) data for classifying awake wear time in three age groups. Methods: Study 1 involved 20 youth and 23 adults who, by protocol, removed the activPAL occasionally to create nonwear periods. Study 2 involved 744 older adults who wore the activPAL continuously. Both studies involved multiple assessment days. In-bed, out-of-bed, and nonwear times were recorded in the participant diaries. The CREA (in PAL processing suite) and ProcessingPAL (secondary application) algorithms estimated out-of-bed wear time. Second- and day-level agreement between the algorithms and diary was investigated, as were associations of sedentary variables with self-rated health. Results: The overall accuracy for classifying out-of-bed wear time as compared with the diary was 89.7% (Study 1) to 95% (Study 2) for CREA and 89.4% (Study 1) to 93% (Study 2) for ProcessingPAL. Over 90% of the nonwear time occurring in nonwear periods >165 min was detected by both algorithms, while <11% occurring in periods ≤165 min was detected. For the daily variables, the mean absolute errors for each algorithm were generally within 0–15% of the diary mean. Most Spearman correlations were very large (≥.81). The mean absolute errors and correlations were less favorable for days on which any nonwear time had occurred. The associations between sedentary variables and self-rated health were similar across processing methods. Conclusion: The automated awake wear-time classification algorithms performed similarly to the diary information on days without short (≤2.5–2.75 hr) nonwear periods. Because both diary and algorithm data can have inaccuracies, best practices likely involve integrating diary and algorithm output.
Comparing Counts of Park Users With a Wearable Video Device and an Unmanned Aerial System
Authors: Suminski Richard R. , Dominick Gregory M. , Saponaro Matthew
Published: April 2021

Evidence suggests that video captured with a wearable video device (WVD) may augment or supplant traditional methods for assessing park use. Unmanned aerial systems (UASs) are used to assess human activity, but research employing them for park assessments is sparse. Therefore, this study compared park user counts between a WVD and UAS. A diverse set of 33 amenities (e.g., playground) in three parks were videoed simultaneously by one researcher wearing a WVD and another operating the UAS. Assessments were done at 12 p.m. and 7 p.m. on weekends, with one park evaluated on two occasions 7 days apart. Two investigators independently reviewed videos and reached consensus on the counts of individuals at each amenity. Intraclass correlation coefficients (ICCs) were used to determine intra- and interrater reliabilities. A total of 404 (M = 4.7; SD = 9.6) and 389 (M = 4.5; SD = 9.0) individuals were counted in the UAS and WVD videos, respectively. Absolute agreement was 86% (74/86) and 100% when no individuals were using the amenity. Whether using all 86 videos or only videos having people (48 videos), ICCs indicated excellent reliability (ICC = .99; p < .001). The totals seen for the repeated measures were UAS = 146 and WVD = 136 for Day 1 and UAS = 169 and WVD = 161 for Day 2. Intrarater reliability was excellent for the UAS (ICC = .92; p < .001) and good for the WVD (ICC = .89; p < .001). Disagreement was mainly due to obstructions—people behind or under structures. This study provides support for the use of UASs for counting park users and future research examining the potential benefits of video analysis for assessing park use.
Senior Physical Education Teacher Education Majors’ Reflections on Teaching at a Youth Development Center
Authors: Dixon Cory E. , Hastie Peter A. , Russell Jared A.
Published: April 2021

Purpose: Acknowledging the growing ethnic and cultural gap in diverse teacher and student populations, this study examined the pedagogical experiences of undergraduate physical education teacher education seniors following a teaching experience at a youth development center. Method: A phenomenological case study approach was employed in which preservice teachers taught and participated in over 45 secondary physical education lessons. The primary data sources were reflective journals and semistructured interviews. Results: Two major themes were constructed that describe the journeys of the physical education teacher education seniors teaching at both the youth development center field experience and in their internship placements the following semester. Initially, the preservice teachers experienced nervousness, uncertainty, and concern but, across time, experienced a degree of change and growth that saw them becoming particularly aware of and appreciating the personal biographies of their students. Discussion: The extent to which the physical education teacher education seniors’ experiences at the youth development center were transferred into their internships is discussed in addition to implications for introducing culturally relevant pedagogies in nontraditional settings.
Ethical controversy swirls around shark fossil from Mexico
Authors: Ortega Rodrigo Pérez
Published: April 2021

Paleontologists raise questions of access to exquisite specimen.
In Vitro
Activity of Oxazolidinone against Nontuberculous Mycobacteria, Including Macrolide-Resistant Clinical Isolates
Authors: Kim Dae Hun , Kim Su-Young , Koh Won-Jung , Jhun Byung Woo
Published: April 2021

We evaluated the
in vitro
activities of oxazolidinone antibiotics, including linezolid, sutezolid, and delpazolid, against clinical nontuberculous mycobacteria (NTM) isolates. Regardless of macrolide resistance, for
Mycobacterium avium
,
Mycobacterium intracellulare
, and
Mycobacterium kansasii
, sutezolid showed the lowest MIC and minimal bactericidal concentration (MBC) values among oxazolidinone antibiotics.
Calprotectin-Mediated Zinc Chelation Inhibits Pseudomonas aeruginosa Protease Activity in Cystic Fibrosis Sputum
Authors: Vermilyea Danielle M. , Crocker Alex W. , Gifford Alex H. , Hogan Deborah A.
Published: April 2021

The factors that contribute to worse outcomes in individuals with cystic fibrosis (CF) with chronicPseudomonas aeruginosainfections are not well understood. Therefore, there is a need to understand environmental factors within the CF airway that contribute toP. aeruginosacolonization and infection.
Serratia marcescens RamA Expression Is under PhoP-Dependent Control and Modulates Lipid A-Related Gene Transcription and Antibiotic Resistance Phenotypes
Authors: Mariscotti Javier F. , García Véscovi Eleonora
Published: April 2021

We demonstrate that in
S. marcescens
, the transcriptional regulator RamA is autoregulated and also controlled by the PhoP/PhoQ signal transduction system. We have shown that PhoP is able to directly and specifically bind to
ramA
,
mgtE1
,
mgtE2
,
lpxO1
, and
lpxO2
promoter regions.
Velopharyngeal dysfunction following botulinum toxin type A injection to the lateral pterygoid muscles for recurrent jaw dislocation
Authors: Kanbour Abdullah , Hurrell Michael James Leslie , Ricciardo Peter
Published: April 2021

Complications related to lateral pterygoid muscle (LPM) botulinum toxin A (BtA) injection for recurrent temporomandibular joint dislocation are uncommon. No cases of velopharyngeal dysfunction (VPD) following LPM BtA injection have been reported to date. This report details the perioperative and follow-up findings for a patient developing VPD following LPM BtA injection.
Oligosecretory multiple myeloma: a devastating presentation of a difficult diagnosis
Authors: Roque Ricardo , Machado Laura , Flor Duarte , Cunha Francisca
Published: April 2021

A 57-year-old man with lumbar pain and fever was diagnosed with spondylodiscitis. Afterward, he acquired full paraplegia. Image studies showed a mass extending from D9 to the vertebral canal, plus numerous adjacent osteolytic lesions. Serum immunoelectrophoresis was normal, bone marrow had 0.5% of monoclonal plasmocytes, but D9’s biopsy found a plasmacytoma. Despite bone marrow aspiration results, skeleton osteolytic lesions made multiple myeloma (MM) a more plausible diagnosis, later confirmed by the biopsy. The absence of classical MM findings, alongside a medullary compression syndrome, suggested an oligosecretory MM, which was proved by an altered FLC essay. This delayed diagnosis, with multiple diagnostic misguiding leads, also presents rare IgA and lambda chains production and normal levels of uninvolved immunoglobulins. Oligosecretory MM can lead to an inaccurate and delayed diagnosis, with devastating consequences to patient’s morbidity and mortality. Therefore, FLC essay is essential in early assessment of potential MM patients.
Emphysematous endometritis in stage III endometrial cancer
Authors: Al Sbihi Ali , Manasrah Nouraldeen , Alqasem Sarah , Abudalou Mohammad
Published: April 2021

We report a case of emphysematous endometritis in a 65-year-old patient who has stage III, high-grade, poorly differentiated endometrial cancer; she was on chemotherapy. The patient developed pyogenic emphysematous endometritis complicated by hypovolemic shock and sepsis. She was admitted to the intensive care unit for treatment with vasopressors and antibiotics. The shock was successfully managed and her hospital course was otherwise unremarkable.
Chest wall tuberculosis in children: a mimicker of bone tumour
Authors: Balasubramaniyan Muthuvel , Verma Sanjay , Dhawan Sumeet Rajendra , saxena Akshay Kumar
Published: April 2021

Osteoarticular tuberculosis of flat bones of the chest wall such as sternum, scapula and rib is extremely rare in children. Because of its atypical clinical presentation mimicking malignant bone tumours, diagnosis remains a challenge. Histological and microbiological diagnosis remains confirmatory. Antitubercular therapy is the cornerstone in management.
Effect of aerobic exercise training on asthma control in postmenopausal women (the ATOM-study): protocol for an outcome assessor, randomised controlled trial
Authors: Hansen Erik Sören Halvard , Hostrup Morten , Rasmusen Hanne Kruuse , Hellsten Ylva , Backer Vibeke
Published: April 2021

Introduction

Late-onset asthma in postmenopausal women is characterised by poor disease control with daily symptoms and reduced quality of life despite treatment with inhaled antiasthma therapies. These patients represent a phenotype that is characterised by low eosinophilic airway inflammation, severe symptoms, moderate obesity and poor response to inhaled antiasthma therapies, which highlights the need of identification of alternative treatment strategies. Thus, this study aims to evaluate if regular high-intensity aerobic exercise improves symptom control in postmenopausal women with asthma.

Methods and analysis

This is an ongoing randomised controlled trial planning to enrol 40 postmenopausal women with late-onset asthma. Participants are randomised 1:1 either to supervised exercise training (spinning) three times per week for 12 weeks or to usual care. The primary outcome is change from baseline to follow-up in the Asthma Control Questionnaire. Secondary outcomes are changes in markers of systemic inflammation, airway inflammation, body composition and right ventricular function of the heart.

Ethics and dissemination

The study is approved by the Ethics Committee in the Capital Region of Denmark nr. H-18028966 and the Danish Data Protection Agency nr. VD-2019–59. The methods used in the study are well known and have a low risk with a chance of substantial improvement in disease control in this patient group. Results are planned to be published in an international peer-reviewed medical journal regardless of outcome.

Trial registration number

NCT03747211.
Is greater patient involvement associated with higher satisfaction? Experimental evidence from a vignette survey
Authors: Birkeland Søren , Bismark Marie , Barry Michael John , Möller Sören
Published: April 2021

Background

Patient-centredness is an essential quality parameter of modern healthcare. Accordingly, involving patients in decisions about care is required by international laws and an increasing number of medical codes and standards. These directives are based on ethical principles of autonomy. Still, there is limited empirical knowledge about the influence of patient involvement on satisfaction with care.

Objective

In a large national vignette survey, we aimed to empirically test healthcare users’ satisfaction with healthcare given different degrees of patient involvement, choices made and outcomes.

Methods

A web-based cross-sectional survey distributed to a randomised sample of men in Denmark aged 45–70 years. Case vignettes used prostate-specific antigen (PSA) screening for early detection of prostate cancer as a clinical model. Using a 5-point Likert scale, we measured respondents’ satisfaction with care in scenarios which differed in the amount of patient involvement (ranging from no involvement, through involvement with neutral or nudged information, to shared decision-making), the decision made (PSA test or no PSA test) and clinical outcomes (no cancer detected, detection of treatable cancer and detection of non-treatable cancer).

Results

Participating healthcare users tended to be more satisfied with healthcare in scenarios illustrating greater levels of patient involvement. Participants were positive towards nudging in favour of the intervention but patient involvement through shared decision-making obtained the highest satisfaction ratings (Likert rating 3.81 without any involvement vs 4.07 for shared decision-making, p<0.001). Greater involvement also had an ameliorating effect on satisfaction if a non-treatable cancer was later diagnosed.

Conclusion

Our study provides empirical support for the hypothesis that greater patient involvement in healthcare decision-making improves satisfaction with care irrespective of decisions made and clinical outcomes. Overall satisfaction with the care illustrated was highest when decisions were reached through shared decision-making.
Mapping palliative care provision in European prisons: an EAPC Task Force Survey
Authors: Turner Mary , Chassagne Aline , Capelas Manuel Luis , Chambaere Kenneth , Panozzo Stacey , Teves Carla Marinho , Riegler Edith
Published: April 2021

Objectives

Prison populations around the world are ageing and numbers are rising, leading to greater demand for palliative care for prisoners approaching the end of life. This paper reports a survey that was undertaken by the European Association for Palliative Care Task Force on mapping palliative care provision for prisoners in Europe. The Task Force was established to begin to address the gap in research knowledge by exploring prison systems and care provision across different countries.

Methods

The survey, developed by the Task Force Steering Committee, consisted of 40 questions in six sections. It was completed through online searches; only data that were publicly available on the internet were included. Numerical data were analysed using descriptive statistics, and thematic comparisons were made of free-text data.

Findings

The survey was completed for eight countries: Australia, Belgium, Czech Republic, England and Wales, France, Portugal, Scotland and Slovakia. Three main findings are reported here: healthcare and palliative care provision in prisons, deaths in custody and compassionate release. Despite increasing numbers of older prisoners, relatively few prisons provide inpatient care, and only one country has any prisons that provide dedicated palliative care services. Early release on compassionate grounds is extremely rare in most countries.

Conclusion

For the principle of equivalence to be adhered to, facilities for sick and dying prisoners need to be improved, or many more people need to be released on compassionate grounds at the end of life. This mapping study has identified key issues in relation to palliative care in prison and provides the basis for further international research.
A Strong Convergence Theorem for Solving the Split Equality Fixed Point Problem
Authors: Zhou Xueling , Li Meixia , Che Haitao
Published: April 2021

In this paper, we study the split equality fixed point problem and propose a new iterative algorithm with a self-adaptive stepsize that does not need the prior information of the operator norms and is calculated easily. The L-Lipschitz and quasi-pseudo-contractive mappings are chosen as the operators in the algorithm since they have a wider range of applications. Moreover, we prove that the sequence generated by the algorithm strongly converges to the solution of the problem. Finally, we check the feasibility and effectiveness of the algorithm by comparing with other algorithms.
Background mode selection during asymptotic-de Sitter inflation
Authors: Ziyaee A. R. , Mohsenzadeh M. , Yusofi E.
Published: April 2021

For the first time, we choose non-flat vacuum mode for background spacetime based on the minimum number of created particles during early non-de Sitter inflation. In conventional methods for calculating the number of created particles, the flat background is selected automatically and causes a negative number problem for created particles during asymptotic-de Sitter inflation. In a covariant approach to curved spacetime, both real and background spacetimes should be selected, curved and consequently the relation for particle creation should be modify. As an interesting finding from this research, flat space does not include minimum number of particles and there are some asymptotic de Sitter spacetimes with fewer number. Therefore, in the generalized formula for particle creation, we choose a non-flat background containing the minimum number of created particles.
Hecke operators on Hilbert–Siegel theta series
Authors: Fretwell Dan , Walling Lynne
Published: April 2021

We consider the action of Hecke-type operators on Hilbert–Siegel theta series attached to lattices of even rank. We show that the average Hilbert–Siegel theta series are eigenforms for these operators, and we explicitly compute the eigenvalues.
Towards the Sato–Tate groups of trinomial hyperelliptic curves
Authors: Emory Melissa , Goodson Heidi , Peyrot Alexandre
Published: April 2021

We consider the identity component of the Sato–Tate group of the Jacobian of curves of the form [Formula: see text] where [Formula: see text] is the genus of the curve and [Formula: see text] is constant.

We approach this problem in three ways. First we use a theorem of Kani-Rosen to determine the splitting of Jacobians for [Formula: see text] curves of genus 4 and 5 and prove what the identity component of the Sato–Tate group is in each case. We then determine the splitting of Jacobians of higher genus [Formula: see text] curves by finding maps to lower genus curves and then computing pullbacks of differential 1-forms. In using this method, we are able to relate the Jacobians of curves of the form [Formula: see text], [Formula: see text] and [Formula: see text]. Finally, we develop a new method for computing the identity component of the Sato–Tate groups of the Jacobians of the three families of curves. We use this method to compute many explicit examples, and find surprising patterns in the shapes of the identity components [Formula: see text] for these families of curves.
Assessment of Machine Learning-Based Audiovisual Quality Predictors
Authors: K. Mythili , Narwaria Manish
Published: April 2021

Quality assessment of audiovisual (AV) signals is important from the perspective of system design, optimization, and management of a modern multimedia communication system. However, automatic prediction of AV quality via the use of computational models remains challenging. In this context,
machine learning (ML)
appears to be an attractive alternative to the traditional approaches. This is especially when such assessment needs to be made in no-reference (i.e., the original signal is unavailable) fashion. While development of ML-based quality predictors is desirable, we argue that proper assessment and validation of such predictors is also crucial before they can be deployed in practice. To this end, we raise some fundamental questions about the current approach of ML-based model development for AV quality assessment and signal processing for multimedia communication in general. We also identify specific limitations associated with the current validation strategy which have implications on analysis and comparison of ML-based quality predictors. These include a lack of consideration of: (a) data uncertainty, (b) domain knowledge, (c) explicit learning ability of the trained model, and (d) interpretability of the resultant model. Therefore, the primary goal of this article is to shed some light into mentioned factors. Our analysis and proposed recommendations are of particular importance in the light of significant interests in ML methods for multimedia signal processing (specifically in cases where human-labeled data is used), and a lack of discussion of mentioned issues in existing literature.
Characterizing Student Engagement Moods for Dropout Prediction in Question Pool Websites
Authors: Hadi Mogavi Reza , Ma Xiaojuan , Hui Pan
Published: April 2021

Problem-Based Learning (PBL) is a popular approach to instruction that supports students to get hands-on training by solving problems. Question Pool websites (QPs) such as LeetCode, Code Chef, and Math Playground help PBL by supplying authentic, diverse, and contextualized questions to students. Nonetheless, empirical findings suggest that 40% to 80% of students registered in QPs drop out in less than two months. This research is the first attempt to understand and predict student dropouts from QPs via exploiting students' engagement moods. Adopting a data-driven approach, we identify five different engagement moods for QP students, which are namely challenge-seeker, subject-seeker, interest-seeker, joy-seeker, and non-seeker. We find that students have collective preferences for answering questions in each engagement mood, and deviation from those preferences increases their probability of dropping out significantly. Last but not least, this paper contributes by introducing a new hybrid machine learning model (we call Dropout-Plus) for predicting student dropouts in QPs. The test results on a popular QP in China, with nearly 10K students, show that Dropout-Plus can exceed the rival algorithms' dropout prediction performance in terms of accuracy, F1-measure, and AUC. We wrap up our work by giving some design suggestions to QP managers and online learning professionals to reduce their student dropouts.
Crowdsourcing and Evaluating Concept-driven Explanations of Machine Learning Models
Authors: Mishra Swati , Rzeszotarski Jeffrey M.
Published: April 2021

An important challenge in building explainable artificially intelligent (AI) systems is designing interpretable explanations. AI models often use low-level data features which may be hard for humans to interpret. Recent research suggests that situating machine decisions in abstract, human understandable concepts can help. However, it is challenging to determine the right level of conceptual mapping. In this research, we explore granularity (of data features) and context (of data instances) as dimensions underpinning conceptual mappings. Based on these measures, we explore strategies for designing explanations in classification models. We introduce an end-to-end concept elicitation pipeline that supports gathering high-level concepts for a given data set. Through crowd-sourced experiments, we examine how providing conceptual information shapes the effectiveness of explanations, finding that a balance between coarse and fine-grained explanations help users better estimate model predictions. We organize our findings into systematic themes that can inform design considerations for future systems.
IRF
Authors: Alkan Öznur , Mattetti Massimiliano , Daly Elizabeth M. , Botea Adi , Vejsbjerg Inge , Knijnenburg Bart
Published: April 2021

Recommender systems are used with increasing frequency in a wide variety of domains ranging from e- commerce to tourism, healthcare and online learning. However, the interaction with these systems generally tends to be limited to shallow feedback, such as providing ratings or filtering. Allowing users to interact with the recommender systems in a conversational environment brings opportunities in which the preferences can effectively be elicited from the users while the users can feel more in control of the whole process. However, when the existing non-interactive recommender systems are considered, it may not be easy to build an interactive layer directly on top of them. This is because there is already a great deal of modelling and work invested in the underlying algorithm and the system itself. Enabling interaction could mean rebuilding the whole solution from scratch, as the current design may not be able to consume preferences and information learnt from the user interaction online. In this paper, we propose the Interactive Recommender Framework, which converts non-interactive recommender solutions to conversational recommenders. We demonstrate how Interactive Recommender Framework can successfully enable interactivity on top of non-interactive recommender systems by integrating it into two different recommender algorithms from literature, and validate our solution through offline simulation experiments and online user studies.
Assessment of Cinnamomum tamala (Tejpat) Plantation in Community Forests: A Case Study from Tanahun District
Authors: Khanal S. , Tiwari B. K. , Gautam L.
Published: April 2021

Cinnamomum tamala is the major NTFPS cultivated commercially in major parts of Nepal. A research was conducted on the plantation of C. tamala in three research sites, Malayang community forest (CF), Saldada CF, and Banaskhadi CF, of Tanahun district for calculating the survival rate, mortality rate, and overall plant growth performance. Simple stratified random sampling methods were used; height and mean breast diameter (DBH) were measured, and a prestructured questionnaire was used for collecting the data and information from the research sites; also, secondary data from AFO, Tanahun, were used for the analysis of data. The first-year survival rate was the highest (62%) at Saldada CF and lowest at Banaskhadi CF (35%); however, the second-year survival rate was the highest at Saldada CF at 50%. Mean height : DBH (cm) of the plant was the highest at Saldada CF (126 cm) and lowest at Banaskhadi (25 cm). The Pearson correlation analysis at α = 0.05 was conducted to test the association between mean height and DBH (cm) of C. tamala which was r = 0.93, df = 12,

p
<
0.001

, r = 0.30, df = 11,

p
<
0.001

, and r = 0.88, df = 11,

p
<
0.001

, respectively, of Saldada CF, Banaskhadi CF, and Malayang CF. The mean height and mean breast diameter (DBH) (cm) of C. tamala were highly correlated in Saldada CF with the highest second-year survival rate. As C. tamala grows well in acidic soil, pH of all the three research sites was basic, more than 7.5; however, Saldada CF had the highest growth rate than others because the organic matter content was the highest (3.4).
General Minimum Lower-Order Confounding Designs with Multi-Block Variables
Authors: Zhao Yuna
Published: April 2021

Blocking the inhomogeneous units of experiments into groups is an efficient way to reduce the influence of systematic sources on the estimations of treatment effects. In practice, there are two types of blocking problems. One considers only a single block variable and the other considers multi-block variables. The present paper considers the blocking problem of multi-block variables. Theoretical results and systematical construction methods of optimal blocked

2

n
−
m

designs with

N
/
4

+
1
≤
n
≤

5
N
/

16

are developed under the prevalent general minimum lower-order confounding (GMC) criterion, where

N
=

2

n
−
m

.
A Review of Antenna Array Technologies for Point-to-Point and Point-to-Multipoint Wireless Communications at Millimeter-Wave Frequencies
Authors: Federico G. , Caratelli D. , Theis G. , Smolders A. B.
Published: April 2021

With the introduction of 5G communication systems operating in the mm-wave frequency range, new opportunities in terms of multimedia services and applications will become available. For this to happen, several technical challenges from an antenna standpoint need to be addressed. The achievements of high-gain characteristics and agile beamforming with wide-scan capabilities are the main targets of the ongoing research on mm-wave antenna arrays. In this paper, an up-to-date overview of antenna array technology for wireless communications at mm-wave frequencies is given. Particular focus is put on the review of the state-of-the art and most advanced antenna array concepts for point-to-point and point-to-multipoint radio links at said frequencies. Various figures of merit are assessed for a comprehensive analysis and bench marking of the technical solutions investigated in the presented survey.
An Integrated Multicriteria Decision-Making Approach to Evaluate Traveler Modes’ Priority: An Application to Peshawar, Pakistan
Authors: Farooq Asim , Stoilova Svetla , Ahmad Firoz , Alam M. , Nassar Hassan , Qaiser Tanveer , Iqbal Kamran , Qadir Abdul , Ahmad Mahmood
Published: April 2021

The transport planning is essential to meeting passengers’ needs for fast, safe, and reliable transport. The research goals of this study are to determine the most suitable mode of transport between predetermined alternatives according the criteria related to the transport planning. The research method combines GIS analysis, SWOT analysis, BEM method, and PROMETHEE II method in an integrated approach for decision-making. The methodology is applied to the city of Peshawar city. It includes six steps. First, a passenger questionnaire is used to establish passenger preferences when making a trip in the city. Secondly, alternative modes of urban transportation are defined. In the case of Peshawar, the following alternatives are considered: a new BRT service, BRT with five additional stops, old bus service, wagon, carpooling, and Careem/Uber. Thirdly, there is GIS analysis to investigate the stops of the BRT alternative transportation. GIS and satellite analysis have been completed for each stop. Fourthly, criteria for the assessment of urban transport modes are determined based on SWOT analysis. A total of twenty four subcriteria are proposed. Fifthly, the best-worst method (BWM) which is based on linear programming method is applied to determine the weightings that should be given to the main criteria and subcriteria. Sixthly, alternative modes of transportation are ranked by applying preference ranking organization method for enrichment evaluations’ (PROMETHEE II) method. The results show that the main important criteria greater than 5% are small movement interval: S4 (6%), security: S7 (13%), reliability: S8 (8%), accessibility:O1 (15%), possibility of special services: O2 (5%), possibility of including insurance in the travel tariff: O3 (8%), possibility of the modernization of the infrastructure: O4 (7%), and environmental pollution: T3 (5%). The implications of this study propose a BRT service with five additional stops is the best urban transport plan for Peshawar. The originality of this research consists in integration of a strategic planning technique SWOT analysis, GIS analysis, and multicriteria analysis in complete methodology to evaluate traveler’s modes priority. The methodology used in this research can be applied to evaluate different transport alternatives for transport networks worldwide.
Real-Time Heart Arrhythmia Detection Using Apache Spark Structured Streaming
Authors: Ilbeigipour Sadegh , Albadvi Amir , Akhondzadeh Noughabi Elham
Published: April 2021

One of the major causes of death in the world is cardiac arrhythmias. In the field of healthcare, physicians use the patient’s electrocardiogram (ECG) records to detect arrhythmias, which indicate the electrical activity of the patient’s heart. The problem is that the symptoms do not always appear and the physician may be mistaken in the diagnosis. Therefore, patients need continuous monitoring through real-time ECG analysis to detect arrhythmias in a timely manner and prevent an eventual incident that threatens the patient’s life. In this research, we used the Structured Streaming module built top on the open-source Apache Spark platform for the first time to implement a machine learning pipeline for real-time cardiac arrhythmias detection and evaluate the impact of using this new module on classification performance metrics and the rate of delay in arrhythmia detection. The ECG data collected from the MIT/BIH database for the detection of three class labels: normal beats, RBBB, and atrial fibrillation arrhythmias. We also developed three decision trees, random forest, and logistic regression multiclass classifiers for data classification where the random forest classifier showed better performance in classification than the other two classifiers. The results show previous results in performance metrics of the classification model and a significant decrease in pipeline runtime by using more class labels compared to previous studies.
Enhanced Squeezing and Entanglement in Nondegenerate Three-Level Laser Coupled to Squeezed Vacuum Reservoir
Authors: Mosisa Ebisa
Published: April 2021

Squeezing and entanglement of a two-mode cascade laser, produced by a three-level atom which is initially prepared by a coherent superposition of the top and bottom levels then injected into a cavity coupled to a two-mode squeezed vacuum reservoir is discussed. I obtain stochastic differential equations associated with the normal ordering using the pertinent master equation. Making use of the solutions of the resulting differential equations, we determined the mean photon number for the cavity mode and their correlation, EPR variables, smallest eigenvalue of the symplectic matrix, intensity difference fluctuation, and photon number correlation. It is found that the squeezed vacuum reservoir increases the degree of the statistical and nonclassical features of light produced by the system. Furthermore, using the criteria developed by logarithm negativity and Hillery-Zubairy criteria, the quantum entanglement of the cavity mode is quantified. It is found that the degree of the entanglement for the system under consideration increases with the squeezing parameter of the squeezed vacuum reservoir.
Mixed-Integer Linear Programming Model by Linear Approximation for a Strike Package-to-Target Assignment Problem
Authors: Kim Heungseob
Published: April 2021

This study deals with an aircraft-to-target assignment (ATA) problem considering the modern air operation environment, such as the strike package concept, multiple targets for a sortie, and the strike packages’ survivability. For the ATA problem, this study introduces a novel mathematical model in which a heterogeneous vehicle routing problem (HVRP) and a weapon-to-target assignment (WTA) problem are conceptually integrated. The HVRP generates the flight routes for strike packages because this study confirms that the survivability of a strike package depends on the path, and the WTA problem evaluates the likelihood of successful target destruction of assigned weapons. Although the first version of the model is developed as a mixed-integer nonlinear programming (MINLP) model, this study attempts to convert it to a mixed-integer linear programming (MILP) model using the logarithmic transformation and piecewise linear approximation methods. For an ATA problem, this activity could provide an opportunity to use the excellent existing algorithms for searching the optimal solution of LP models. To maximize the operational effectiveness, the MILP model simultaneously determines the following for each strike package: (a) composition type, (b) targets, (c) flight route, (d) types, and (e) quantity of weapons for each target.
Rare Histological Variants of Liver Cancer and Their Management: A Single-Institution Experience
Authors: Swed Brandon , Gandarilla Omar , Chiu Kenrry , Halazun Karim H. , Samstein Benjamin , Yantiss Rhonda , Brar Gagandeep
Published: April 2021

Primary liver malignancies, including hepatocellular carcinoma (HCC) and cholangiocarcinoma, are a major cause of cancer-related morbidity and mortality worldwide. There are several histologically and biologically distinct subtypes of liver cancer that have previously been reported. However, literature regarding the nonsurgical management of these patients upon disease recurrence remains limited. These variants include combined HCC-cholangiocarcinoma (cHCC-CC), Epstein–Barr virus- (EBV-) associated carcinoma, undifferentiated carcinoma, and clear cell or thyroid-like variants of HCC. Here, we aim to highlight the pathologic features, clinical course, and outcomes of five patients with these unusual hepatic tumors and explain the rationale behind the choice of their systemic therapies upon disease recurrence. All patients underwent surgical resection as the standard of care for localized disease, and upon relapse, they were treated with either chemotherapy, targeted therapy, immunotherapy, or active surveillance based on the clinical context and tumor histology. These rare variants are important to recognize as they have prognostic and therapeutic implications, and there are currently insufficient data in the literature to guide further therapy.
Three-Dimensional Autonomous Obstacle Avoidance Algorithm for UAV Based on Circular Arc Trajectory
Authors: Guo Jiandong , Liang Chenyu , Wang Kang , Sang Biao , Wu Yulin
Published: April 2021

This paper proposes an innovative and efficient three-dimensional (3D) autonomous obstacle algorithm for unmanned aerial vehicles (UAVs) which works by generating circular arc trajectories to avoid obstacles. Firstly, information on irregular obstacles is obtained by an onboard detection system; this information is then transformed into standard convex bodies, which are used to generate circular arc avoidance trajectories, and the obstacle avoidance problem is turned into a trajectory tracking strategy. Then, on the basis of the geometric relationship between a UAV and obstacle modeling, the working mechanism of the avoidance algorithm is developed. The rules of obstacle detection, avoidance direction, and the criterion of avoidance success are defined for different obstacle types. Finally, numerical simulations of different obstacle scenarios show that the proposed algorithm can avoid static and dynamic obstacles effectively and can implement obstacle avoidance missions for UAVs well.
Performance Analysis of UAV‐Assisted Wireless Powered Sensor Network over Shadowed κ − μ Fading Channels
Authors: Milovanovic Ivan , Stefanovic Caslav
Published: April 2021

In this work, we analyze performances of the unmanned aerial vehicle‐ (UAV‐) assisted wireless powered sensor communication, where sensor transmission ability is supported by the UAV. Harvested energy from the UAV‐broadcasted signal is further used at the sensor nodes for uplink information transmission to the UAV, over assumed shadowed κ − μ fading channels. Here, we observe a general scenario in which due to the flight conditions of the UAV, the channel’s content include the LOS components affected by the shadowing effect, modeled by the general shadowed κ − μ channel model, which can be reduced to other well‐known channel models as its special cases. We derive closed‐form expressions for the outage probability (OP) of such wireless sensor network (WSN) operating in shadowed κ − μ fading environments. Further, we analyze the optimization of time allocation to minimize OP subjected to UAV’s energy constraints. The impact of channel parameters on observed performance measures is analyzed, and obtained results are numerically validated.
Measurement Method of Distributed Nodes in Wireless Sensor Networks Based on Multiple Attributes
Authors: Zheng Bing , Yang Jing
Published: April 2021

Wireless sensor network (WSN) is usually organized in a particular area for achieving some specific tasks and functions. It has broad application prospects in military, environmental monitoring, disaster relief, and other many commercial areas. Measuring the significance of distributed nodes is the foundation of many applications of WSN. Therefore, this paper studies the distributed node measurement methods and approaches based on multiple attributes in wireless sensor networks to improve the accuracy of distributed node importance measurement. The entropy weight TOPSIS method is used to calculate the importance index of distributed nodes of degree centrality, eigenvector centrality, compactness centrality, betweenness centrality, K-kernel decomposition centrality, and aggregation coefficient; the PR value of each node is given by combining the PageRank algorithm; and then, the parameters α and β are introduced to calculate the comprehensive importance measurement results of each node, to finally obtain the importance measurement results of each node dynamically through the improved node deletion method. The experimental results of the research show that the proposed method can accurately measure the importance of distributed nodes in wireless sensor networks, and the accuracy is as high as 98%.
Preparation of Gelatin/Polycaprolactone Electrospun Fibers Loaded with Cis-Platinum and Their Potential Application for the Treatment of Prostate Cancer
Authors: Jin Yang , Sun Peng , Wu Tong , Wang Jin , Huang Xiaoyu , Zuo Shishuai , Cui Zilian , Chen Ji , Li Lianjun , Suo Ning , Jin Xunbo , Zhang Dong
Published: April 2021

Although the development of nanomaterials for cancer therapy has received much attention in recent years, prostate cancer still remains one of the most troubling cancers in males. In this work, biomimetic polycaprolactone (PCL)/gelatin (GT)/cis-platinum (CDDP) (PG@CDDP) fibrous films were developed via electrospinning technology. The microstructure and chemical properties of PG@CDDP fibers are investigated. It is found that the microscopic morphology and diameter of PG@CDDP fibers are changed compared to those of the PG fibers. The Fourier transform-infrared spectroscopy and wide-angle X-ray diffraction demonstrate that CDDP is successfully incorporated into the fibers. The human prostate cancer cells in vitro to electrospun films (PG and PG@CDDP) were evaluated based on initial cell response and cell viability. The density, elongation, and viability of adhered cancer cells significantly reduce with an increased concentration of CDDP in PG fibers. Thus, the developed PG@CDDP fiber matrix has great potential as candidate scaffolds for the treatment of prostate cancer.
PBRM1 Deficiency Confers Synthetic Lethality to DNA Repair Inhibitors in Cancer
Authors: Chabanon Roman M. , Morel Daphné , Eychenne Thomas , Colmet-Daage Léo , Bajrami Ilirjana , Dorvault Nicolas , Garrido Marlène , Meisenberg Cornelia , Lamb Andrew , Ngo Carine , Hopkins Suzanna R. , Roumeliotis Theodoros I. , Jouny Samuel , Hénon Clémence , Kawai-Kawachi Asuka , Astier Clémence , Konde Asha , Del Nery Elaine , Massard Christophe , Pettitt Stephen J. , Margueron Raphaël , Choudhary Jyoti S. , Almouzni Geneviève , Soria Jean-Charles , Deutsch Eric , Downs Jessica A. , Lord Christopher J. , Postel-Vinay Sophie
Published: April 2021

Inactivation of Polybromo 1 (PBRM1), a specific subunit of the PBAF chromatin remodeling complex, occurs frequently in cancer, including 40% of clear cell renal cell carcinomas (ccRCC). To identify novel therapeutic approaches to targeting PBRM1-defective cancers, we used a series of orthogonal functional genomic screens that identified PARP and ATR inhibitors as being synthetic lethal with PBRM1 deficiency. The PBRM1/PARP inhibitor synthetic lethality was recapitulated using several clinical PARP inhibitors in a series of in vitro model systems and in vivo in a xenograft model of ccRCC. In the absence of exogenous DNA damage, PBRM1-defective cells exhibited elevated levels of replication stress, micronuclei, and R-loops. PARP inhibitor exposure exacerbated these phenotypes. Quantitative mass spectrometry revealed that multiple R-loop processing factors were downregulated in PBRM1-defective tumor cells. Exogenous expression of the R-loop resolution enzyme RNase H1 reversed the sensitivity of PBRM1-deficient cells to PARP inhibitors, suggesting that excessive levels of R-loops could be a cause of this synthetic lethality. PARP and ATR inhibitors also induced cyclic GMP-AMP synthase/stimulator of interferon genes (cGAS/STING) innate immune signaling in PBRM1-defective tumor cells. Overall, these findings provide the preclinical basis for using PARP inhibitors in PBRM1-defective cancers.

Significance:

This study demonstrates that PARP and ATR inhibitors are synthetic lethal with the loss of PBRM1, a PBAF-specific subunit, thus providing the rationale for assessing these inhibitors in patients with PBRM1-defective cancer.
Remote Cardiac Safety Monitoring through the Lens of the FDA Biomarker Qualification Evidentiary Criteria Framework: A Case Study Analysis
Authors: Izmailova Elena S. , Wood William A. , Liu Qi , Zipunnikov Vadim , Bloomfield Daniel , Homsy Jason , Hoffmann Steven C. , Wagner John A. , Menetski Joseph P.
Published: April 2021

Clinical safety findings remain one of the reasons for attrition of drug candidates during clinical development. Cardiovascular liabilities are not consistently detected in early-stage clinical trials and often become apparent when drugs are administered chronically for extended periods of time. Vital sign data collection outside of the clinic offers an opportunity for deeper physiological characterization of drug candidates and earlier safety signal detection. A working group representing expertise from biopharmaceutical and technology sectors, US Food and Drug Administration (FDA) public-private partnerships, academia, and regulators discussed and presented a remote cardiac monitoring case study at the FNIH Biomarkers Consortium Remote Digital Monitoring for Medical Product Development workshop to examine applicability of the biomarker qualification evidentiary framework by the FDA. This use case examined the components of the framework, including the statement of need, the context of use, the state of the evidence, and the benefit/risk profile. Examination of results from 2 clinical trials deploying 510(k)-cleared devices for remote cardiac data collection demonstrated the need for analytical and clinical validity irrespectively of the regulatory status of a device of interest, emphasizing the importance of data collection method assessment in the context of intended use. Additionally, collection of large amounts of ambulatory data also highlighted the need for new statistical methods and contextual information to enable data interpretation. A wider adoption of this approach for drug development purposes will require collaborations across industry, academia, and regulatory agencies to establish methodologies and supportive data sets to enable data interpretation and decision-making.