bluuebunny/crossref_metadata_2025 huggingface dataset:
Compressed sensing with continuous parametric reconstruction
Authors: Andras Imrich , Michaeli Linus , Saliga Jan
Published: September 2020

This work presents a novel unconventional method of signal reconstruction after compressive sensing. Instead of usual matrices, continuous models are used to describe both the sampling process and acquired signal. Reconstruction is performed by finding suitable values of model parameters in order to obtain the most probable fit. A continuous approach allows more precise modelling of physical sampling circuitry and signal reconstruction at arbitrary sampling rate. Application of this method is demonstrated using a wireless sensor network used for freshwater quality monitoring. Results show that the proposed method is more robust and offers stable performance when the samples are noisy or otherwise distorted.
A hybrid method of genetic algorithm and support vector machine for intrusion detection
Authors: Tally Mushtaq Talb , Amintoosi Haleh
Published: September 2020

With the development of web applications nowadays, intrusions represent a crucial aspect in terms of violating the security policies. Intrusions can be defined as a specific change in the normal behavior of the network operations that intended to violate the security policies of a particular network and affect its performance. Recently, several researchers have examined the capabilities of machine learning techniques in terms of detecting intrusions. One of the important issues behind using the machine learning techniques lies on employing proper set of features. Since the literature has shown diversity of feature types, there is a vital demand to apply a feature selection approach in order to identify the most appropriate features for intrusion detection. This study aims to propose a hybrid method of Genetic Algorithm and Support Vector Machine. GA has been as a feature selection in order to select the best features, while SVM has been used as a classification method to categorize the behavior into normal and intrusion based on the selected features from GA. A benchmark dataset of intrusions (NSS-KDD) has been in the experiment. In addition, the proposed method has been compared with the traditional SVM. Results showed that GA has significantly improved the SVM classification by achieving 0.927 of f-measure.
Electroencephalography Might Improve Diagnosis of Acute Stroke and Large Vessel Occlusion
Authors: Erani Fareshte , Zolotova Nadezhda , Vanderschelden Benjamin , Khoshab Nima , Sarian Hagop , Nazarzai Laila , Wu Jennifer , Chakravarthy Bharath , Hoonpongsimanont Wirachin , Yu Wengui , Shahbaba Babak , Srinivasan Ramesh , Cramer Steven C.
Published: September 2020

Background and Purpose:

Clinical methods have incomplete diagnostic value for early diagnosis of acute stroke and large vessel occlusion (LVO). Electroencephalography is rapidly sensitive to brain ischemia. This study examined the diagnostic utility of electroencephalography for acute stroke/transient ischemic attack (TIA) and for LVO.

Methods:

Patients (n=100) with suspected acute stroke in an emergency department underwent clinical exam then electroencephalography using a dry-electrode system. Four models classified patients, first as acute stroke/TIA or not, then as acute stroke with LVO or not: (1) clinical data, (2) electroencephalography data, (3) clinical+electroencephalography data using logistic regression, and (4) clinical+electroencephalography data using a deep learning neural network. Each model used a training set of 60 randomly selected patients, then was validated in an independent cohort of 40 new patients.

Results:

Of 100 patients, 63 had a stroke (43 ischemic/7 hemorrhagic) or TIA (13). For classifying patients as stroke/TIA or not, the clinical data model had area under the curve=62.3, whereas clinical+electroencephalography using deep learning neural network model had area under the curve=87.8. Results were comparable for classifying patients as stroke with LVO or not.

Conclusions:

Adding electroencephalography data to clinical measures improves diagnosis of acute stroke/TIA and of acute stroke with LVO. Rapid acquisition of dry-lead electroencephalography is feasible in the emergency department and merits prehospital evaluation.
Young Women Had More Strokes Than Young Men in a Large, United States Claims Sample
Authors: Leppert Michelle H. , Ho P. Michael , Burke James , Madsen Tracy E. , Kleindorfer Dawn , Sillau Stefan , Daugherty Stacie , Bradley Cathy J. , Poisson Sharon N.
Published: September 2020

Background and Purpose:

Cardiovascular risk factors, which are overall more prevalent in men, are considered the major risk factors for strokes among young adults. However, recent European data found the incidence of strokes to be higher in young women. Using a large US claims sample, we examined sex differences in the index stroke rate of young adults.

Methods:

We performed a retrospective cohort study of enrollees in a 10% random sample of PharMetrics, a nationally representative claims database of insured Americans from 2001 to 2014. Outcomes were index ischemic stroke events, based on inpatient admissions using
International Classification of Diseases-Ninth Revision
codes. The index stroke rate was estimated from Poisson rate models with time varying covariates for 2-year periods, stratified by sex and age groups.

Results:

We identified 20 554 index strokes (50.4% women; mean age 63) including 5198 in young adults ages 15 to 54. There was no difference by sex in the index stroke rate in the extremes of age groups 15 to 24 and ≥75 years old. However, in the 25 to 34 and 35 to 44 year age groups, more women had strokes than men (incidence rate ratio: men:women, 0.70 [95% CI, 0.57–0.86]; 0.87 [95% CI, 0.78–0.98], respectively). In contrast, in the 45 to 54, 55 to 64, and 65 to 74 year age groups, more men had strokes (incidence rate ratio, 1.25 [95% CI, 1.16–1.33]; 1.41 [95% CI, 1.18–1.34]; 1.18 [95% CI, 1.12–125], respectively).

Conclusions:

More young women than men have strokes, suggesting possible importance of sex-mediated etiologies of stroke. Understanding these drivers is critical to stroke treatment and prevention efforts in young adults.
The Impact of No-Loan Program Participation on the Likelihood of Graduate School Enrollment Among Low-Income, First-Generation Students
Authors: Ortagus Justin C. , Kramer Dennis A.
Published: September 2020

Previous research shows that low-income and first-generation college students are less likely to obtain the benefits associated with attending graduate school. No-loan programs, which typically administer financial aid through institutional grants, are designed to improve access and success among students from low-income backgrounds, but we know very little about the influence of no-loan programs after students enroll and eventually graduate from college. This study examines the impact of no-loan program participation on graduate school enrollment by leveraging a novel institutional dataset and applying regression discontinuity, difference-in-differences, and propensity score weighting approaches. Results indicate that no-loan program participation has a positive and relatively consistent impact on graduate school enrollment among low-income and first-generation students.
Graphical Data Sets as Compositional Structure: Sonification of Color Graphs in RGB for Clarinet and Piano
Authors: Metcalf Thomas
Published: September 2020

This article follows the methodology behind the composition of the author's piece RGB (2019) for clarinet and piano, a sonification of four color graphs generated from Jackson Pollock's Out of the Web (1949). The article demonstrates the process of “mapping” data to sound while creating allowances for compositional intuition. In this way, the author hopes to demonstrate the usefulness and flexibility of composing with this approach, as well as its future implications and potential improvements, while acknowledging that this is a specific example of such an approach rather than an all-encompassing taxonomy for any visual input.
Assessing Goodness-of-Fit in Marked Point Process Models of Neural Population Coding via Time and Rate Rescaling
Authors: Yousefi Ali , Amidi Yalda , Nazari Behzad , Eden Uri. T.
Published: September 2020

Marked point process models have recently been used to capture the coding properties of neural populations from multiunit electrophysiological recordings without spike sorting. These clusterless models have been shown in some instances to better describe the firing properties of neural populations than collections of receptive field models for sorted neurons and to lead to better decoding results. To assess their quality, we previously proposed a goodness-of-fit technique for marked point process models based on time rescaling, which for a correct model produces a set of uniform samples over a random region of space. However, assessing uniformity over such a region can be challenging, especially in high dimensions. Here, we propose a set of new transformations in both time and the space of spike waveform features, which generate events that are uniformly distributed in the new mark and time spaces. These transformations are scalable to multidimensional mark spaces and provide uniformly distributed samples in hypercubes, which are well suited for uniformity tests. We discuss the properties of these transformations and demonstrate aspects of model fit captured by each transformation. We also compare multiple uniformity tests to determine their power to identify lack-of-fit in the rescaled data. We demonstrate an application of these transformations and uniformity tests in a simulation study. Proofs for each transformation are provided in the appendix.
Wheeleriola perplexa gen. et sp. nov., the first member of Catotrichinae (Diptera: Cecidomyiidae) found in New Zealand
Authors: JASCHHOF MATHIAS , JASCHHOF CATRIN
Published: September 2020

Catotrichinae, a small, relict subfamily of the Cecidomyiidae, are of peculiar interest to the phylogeny of gall midges. Three genera and eight species of extant catotrichines were previously known to science, all found in the Holarctic region and Australia. Here, the first New Zealand member of this group is described and named Wheeleriola perplexa, new genus, new species. The adult morphology of Wheeleriola is characterized by two peculiarities: the vestiture on the male flagellomeres shows beginnings of girdle formation, and the medial veins are largely reduced. Both conditions challenge the hypothesis of Catotrichinae being the earliest branching lineage of the cecidomyiid clade, which is explained and discussed.
Cryptographic Merkle-Damgard Hash Construction: MD5 Vulnerabilities
Authors: Sharma Arvind K. , Mittal S. K.
Published: September 2020

Cryptography is a branch of Computer-Science which fully devotes towards further enhancements or innovations of various applications concern to information security i.e., to manage Confidentiality/ Integrity of resources. Confidentiality of resources most probably look after by ‘Encryption–Decryption’
techniques like ‘DES,’ ‘AES,’ ‘Blowfish,’ ‘Two-Fish,’ etc., were as ‘Integrity’ managed by Hash Functions, which have a distinct paramount significance in Network-Security/Computer- Security/Internet-Security. Both the ‘Integrity’
of data and ‘Authenticity’ of resource proved with the help of digest generated by the Hash algorithm. There are several hash algorithms available to provide distinct security, depends on how hard is to break it and pre-defined resource utilization (time/space). Some well-known
names are MD4, MD5, SHA, JH, Skein, Grøstl, Blake, Hamsi, Fugue, Crush, Whirlpool, Tav, etc. In this article, we are focusing on vulnerabilities in the Merkle- Damgard scheme for constructing Hash-Functions with suitable implementation of MD5.
Comparison of Different Edge Detection Techniques to Improve Quality of Medical Images
Authors: Chhabra Mohit , Kumar Rajneesh
Published: September 2020

In modern era the major challenge will betodetect diseases from Medical Images. To curb this challenge, different efficient image feature extraction techniques was required in medical fields. Today Medical field industry today deals with millions of images of different disease of brain
heart, lungs. So in this paper, we had presented a comparison among different feature extraction technique like Canny, Laplacian of Gaussian, Sobel, Prewit on large number of images of lung disease. The objective of our research work was to find best extraction techniques based on various
image quality parameters such as Mean absolute error (MAE), Root mean square error (RMSE), mean square error (MSE), Signal to noise ratio (SNR).
Asynchronous Media Access Control Protocols and Cross Layer Optimizations for Wireless Sensor Networks: An Energy Efficient Perspective
Authors: Guleria Kalpna , Prasad Devendra , Lilhore Umesh Kumar , Simaiya Sarita
Published: September 2020

In the recent past, the wireless technology has grown at a very rapid pace and it has brought a revolution in the field of communication. WSNs are of great importance in building the smart devices and intelligent applications such as smart homes, military surveillance applications, target tracking and structural health monitoring etc. One of the major hardware limitations is limited energy of sensor nodes which has motivated researchers to emphasize on energy efficient communication and this in turn has given a lot of stimulus for the research of energy efficient protocols for MAC and network layer. Further, the cross-layer optimizations have a major impact on network performance metrics like increased energy efficiency, enhanced reliability, reduced delay and increased security as well. In this paper, various energy efficient asynchronous MAC, MIMO-MAC layer routing protocols, analysis, cross layer optimization have been discussed.
A Hybrid Tumour Detection and Classification Based on Machine Learning
Authors: Lilhore Umesh Kumar , Simaiya Sarita , Prasad Devendra , Guleria Kalpna
Published: September 2020

Every excess tissue or impaired production of brain tissue in the human embryo is known as something of a tumor. Inside the brain, there may have been a tumor or any other orifice. Recognition of tumors and proper treatment at all times are still a difficult challenge. MRI devices are
used mostly for the identification of specific tumors. MRI technologies are most often used for either the identification of specific tumors. Use artificial intelligence, medical diagnosis by imaging and machine learning is considered one of the many important issues for systems. Brain tumor
evaluation generally requires greater accuracy, although small differences in assessment may turn to hazards. Because of this, the segmentation of both the tumor is a serious medical obstacle. Here proposed work introduces a hybrid machine learning-based tumor detection system (HMLBTD) for
MR frames. The Fuzzy C-Means and K-Means Clustering Composite Clustering methodology have been used by the proposed HMLBTD frameworks and subsequently improved the classification of SVM and classification of normal and abnormal tumors. Across clustering, throughout order to achieve statistically
valid performance, HMLBTD incorporates Fuzzy C-Means hybrid versions to achieve precision and K-means through segmentation. Throughout the second clustering step, HMLBTD employs Enhanced SVM (and use the ADA-boost framework with SVM) As well as the suggested HMLBTD strategy and also the proposed
solution being implemented by utilizing different performance descriptive statistics using the MATLAB framework. An experimental study demonstrates that HMLBTD’s novel approach delivers higher yields than those of the traditional methods.
Dynamic Hybrid Secured Environment (DHSE) to Provide Confidentiality in Cloud Computing Environment
Authors: Garg Deepak , Rani Shalli
Published: September 2020

With help of internet technology today people can process, store and share data easily moreover, cloud computing model has provided various application services to users such as storage because cloud provide pay as you go environment. Storage helps data owner to share their data among
users or employees of organization. But there is a need for data owners to provide flexible access control such that unauthorized users cannot have access to the data and confidentiality can be maintained. In addition, there is a need that only encrypted data is shared over the cloud. Encryption
schemes have a major role in security domain of cloud computing model. In this article, DHSE scheme which is a hybrid technique and uses AES, ABE and IBE for key and data encryption is proposed. Furthermore, to validate and to do the security investigation of our plan we have verified our
results using AVISPA tools.
Internet of Things Based Video Surveillance Systems for Security Applications
Authors: Ghosh Gopal , Kavita  , Sood Monica , Verma Sahil
Published: September 2020

The principle point of this paper is to talk about the Video surveillance system plays major role in the security applications now a days. The need for surveillance systems are increasing drastically. Internet of things makes Video surveillance more effective. Internet of Things is an interrelated communication network for several systems and having the ability to transfer the information through the network without human or computer interaction. This paper reviews the network traffic due to Video surveillance and its management with Software Defined Networking. This paper also reviews the applications of Internet of things in Video surveillance system.
Invasive Ductal Carcinoma Detection in Histopathology Images Using Machine Learning Techniques Without Deploying Feature Extraction
Authors: Gupta Isha , Gupta Sheifali , Singh Swati
Published: September 2020

Breast cancer is one of the common malignant diseases in female all over the world. Microscopic investigation of tissues in breast is essential for analysis of breast cancer. For detection of breast cancer, pathologist uses various magnificent stages for obtaining accurate diagnosis
of biopsy images which is time consuming. Development in digital imaging techniques has helped in assessment of pathology images using machine learning and computerized methods which could computerize a few of the pathology stages in the diagnosis of breast cancer. This kind of automation
can be helpful in achieving quick and exact results reducing the observers’ inconsistency, thus increasing the accuracy. In this work, a new method is proposed to categorize breast cancer histopathology images. The objective is to evaluate the robustness and accuracy of a classification
system based on machine learning, to automatically identify invasive tumor on digitized images without extracting the features. Here, a new method is presented that employs machine learning classifiers for classification of invasive tumor on whole slide images. The accuracy of different classifiers
varies from 80% to 85%, leaving scope for improvement. The aim is to gather different researchers in both machine learning and medical field to proceed toward this Computer Aided Diagnosis (CAD) system for classification of invasive ductal carcinoma (IDC).
Current Approaches to Advanced Research in Data Science at International Top League Universities
Authors: Hashim Wahidah , Prathees A/L Jayaretnam , Othman Marini , Maseleno Andino
Published: September 2020

Data Science also known as Analytics, has a high demand in the industries right now, where professionals who are well trained in this field are being recruited by many large companies. Before the existence of data science, companies and industries search for software engineers and data
analysis to sort IT related problems. However, as the internet start to being used by most of the people in the world, data keep on pouring in a large volume and velocity, software engineers and data analysis could not handle it anymore. Analyzing the tremendous size of data is called Big
Data Analytics. Corporate companies have already started to realize that data scientists are the right person to tackle Big Data related problems. Low supply of data scientist has hiked in the salary of the data scientist, as the pay for a data scientist many more time higher compare to other
IT related professionals. Knowledge in data science can solve any data related problems in this world. Data scientist are not only recruited by tech-giants like Google and Amazon, medium organizations also started to understand the importance of data science and they too recruit data scientist
for their company. In this paper, we will explore on the requirement and knowledges of data science that can be covered in UNITEN’s computer science syllabus.
Engineering ofωTransaminase for Effective Production of Chiral Amines
Authors: Mirzaei Mitra , Berglund Per
Published: September 2020

ωTransaminases are pyridoxal-5-phosphat (PLP) dependent enzymes having the ability to catalyze the transference of an amino group to a keto compound. These enzymes are used for production of chiral amines which are important building blocks in pharmaceutical industry. There is often a need to improve enzyme properties such as enzyme stability, enzyme specificity and to decrease substrate-product inhibition. Here, protein engineering was applied to improve the enzyme activity of the enzyme fromChromobacterium violaceumRational-design and site-directed mutagenesis were applied on position of (W60) in the active site of the enzyme. Different mutated enzyme variants such as W60H, W60F and W60Y were made. Also, the enantiopreference of the wild type enzyme was reversed to produce (R)-chiral amines. For this aim, a screening assay was followed by semi-rational approach and saturation mutagenesis in the active site of the enzyme. Creating the mutated enzyme libraries resulted to obtaining two enzyme variants. Their properties were low enantiopreference towards formations of (R)-enantiopreference and low specific constant ratio between fast and slow enantiomers (Evalue around one).
Binary Genetic Algorithm (BGA): A Hybrid Approach for Efficient Web Document Categorization
Authors: Bhavana  , Raheja Neeraj
Published: September 2020

Textual data on the web is growing at an exponential rate and millions of categories of data are available on web. In this big data environment, finding accurate information from these millions of categories is a challenging task. Web document categorization helps in classifying the
web pages in to one or more predefined categories. This paper proposed hybrid Text document categorization approach. In this paper document categorization approach is improved by feature extraction and selection approach since filtering for relevant features is done twice. Here Deep Belief
Network (DBN) is used for feature extraction i.e., DBN-FE, Binary Genetic Approach is used for Feature Selection i.e., BGA-FS and three different classifiers are used for evaluation of result of proposed categorization scheme. BGA Model gives the promising result for proposed approach in comparison
to other approaches.
CROSSINN: A Field Experiment to Study the Three-Dimensional Flow Structure in the Inn Valley, Austria
Authors: Adler Bianca , Gohm Alexander , Kalthoff Norbert , Babić Nevio , Corsmeier Ulrich , Lehner Manuela , Rotach Mathias W. , Haid Maren , Markmann Piet , Gast Eckhard , Tsaknakis George , Georgoussis George
Published: September 2020

While the exchange of mass, momentum, moisture, and energy over horizontally homogeneous, flat terrain is mostly driven by vertical turbulent mixing, thermally and dynamically driven mesoscale flows substantially contribute to the Earth–atmosphere exchange in the atmospheric boundary layer over mountainous terrain (MoBL). The interaction of these processes acting on multiple scales leads to a large spatial variability in the MoBL, whose observational detection requires comprehensive instrumentation and a sophisticated measurement strategy. We designed a field campaign that targets the three-dimensional flow structure and its impact on the MoBL in a major Alpine valley. Taking advantage of an existing network of surface flux towers and remote sensing instrumentation in the Inn Valley, Austria, we added a set of ground-based remote sensing instruments, consisting of Doppler lidars, a ceilometer, a Raman lidar, and a microwave radiometer, and performed radio soundings and aircraft measurements. The objective of the Cross-Valley Flow in the Inn Valley Investigated by Dual-Doppler Lidar Measurements (CROSSINN) experiment is to determine the mean and turbulent characteristics of the flow in the MoBL under different synoptic conditions and to provide an intensive dataset for the future validation of mesoscale and large-eddy simulations. A particular challenge is capturing the two-dimensional kinematic flow in a vertical plane across the whole valley using coplanar synchronized Doppler lidar scans, which allows the detection of cross-valley circulation cells. This article outlines the scientific objectives, instrument setup, measurement strategy, and available data; summarizes the synoptic conditions during the measurement period of 2.5 months; and presents first results.
Large-Scale Analysis of Global Gridded Precipitation and Temperature Datasets for Climate Change Impact Studies
Authors: Tarek Mostafa , Brissette François P. , Arsenault Richard
Published: September 2020

Currently, there are a large number of diverse climate datasets in existence, which differ, sometimes greatly, in terms of their data sources, quality control schemes, estimation procedures, and spatial and temporal resolutions. Choosing an appropriate dataset for a given application is therefore not a simple task. This study compares nine global/near-global precipitation datasets and three global temperature datasets over 3138 North American catchments. The chosen datasets all meet the minimum requirement of having at least 30 years of available data, so they could all potentially be used as reference datasets for climate change impact studies. The precipitation datasets include two gauged-only products (GPCC and CPC-Unified), two satellite products corrected using ground-based observations (CHIRPS V2.0 and PERSIANN-CDR V1R1), four reanalysis products (NCEP CFSR, JRA55, ERA-Interim, and ERA5), and one merged product (MSWEP V1.2). The temperature datasets include one gauge-based (CPC-Unified) and two reanalysis (ERA-Interim and ERA5) products. High-resolution gauge-based gridded precipitation and temperature datasets were combined as the reference dataset for this intercomparison study. To assess dataset performance, all combinations were used as inputs to a lumped hydrological model. The results showed that all temperature datasets performed similarly, albeit with the CPC performance being systematically inferior to that of the other three. Significant differences in performance were, however, observed between the precipitation datasets. The MSWEP dataset performed best, followed by the gauge-based, reanalysis, and satellite datasets categories. Results also showed that gauge-based datasets should be preferred in regions with good weather network density, but CHIRPS and ERA5 would be good alternatives in data-sparse regions.
Science, Catholicism, and the French (Latin) Pattern of Secularization. The Case of Argentina (1820–1958)
Authors: de Asúa Miguel
Published: September 2020

This article considers the relationships between science and religion (Catholicism) in Argentina from 1820 to mid-20th century as a case of what David Martin has characterized as the French (Latin) pattern of secularization. It examines the role of science and scientific discourse in three episodes in which secularizing measures were discussed and in two cases applied by the state: restrictions to the activities of the regular clergy in 1822; legislation transferring church functions to the state and establishing of non-confessional elementary education in the 1880s; and the attempts in the 1910s at transforming Catholic centers of cult into secular shrines and investing secular images with sacred meanings. The analysis confirms the widely held view that science as such was not the engine of secularization and suggests that it was the pattern of secularization which shaped the relationships between science and religion in a given society.
Assessment of Knowledge, Attitude and Practice of Adverse Drug Reaction Reporting Among Healthcare Professionals working in Primary, Secondary and Tertiary Healthcare Facilities in Ekiti State, South-West Nigeria
Authors: Adegbuyi Theophilus A. , Fadare Joseph O. , Araromi Ebisola J. , Sijuade Abayomi O. , Bankole Iyanu , Fasuba Ilesanmi K. , Alabi Rachel A.
Published: September 2020

Background:

Adverse drug reactions (ADRs) constitute a significant global healthcare challenge associated with increased morbidity, mortality and healthcare costs; however, there are concerns that ADRs are grossly under-reported by different categories of healthcare professionals (HCPs) in many countries. The main objective of this study was to assess the knowledge, attitude and practice of ADR reporting of HCPs working at the primary, secondary and tertiary levels of care in Ekiti State, Nigeria.

Methodology:

This was a self-administered questionnaire-based study conducted among HCPs working in Ekiti State, South-west Nigeria. The questionnaire which was adapted from ones used in similar studies was reviewed for content validity by experts in the field. Healthcare professionals (medical doctors, pharmacists, nurses, community health extension workers, and other allied HCPs) working in the 3 tiers of healthcare participated in the study. The questionnaire consisted of sections on the demographics of respondents, their knowledge, attitude and practice of ADR reporting. Data analysis was done using SPSS (version 25) employing t test, ANOVA and chi-square as appropriate with P-value < .05 accepted as being statistically significant.

Results:

Three hundred HCPs comprising of nurses (112; 37.3%), physicians (75; 25.0%), pharmacists (53; 17.7%), community health extension workers (40; 13.3%) and others (20; 6.7%) completed the questionnaire with 166 (55.3%) of them working in tertiary healthcare facilities. Male respondents (6.3 ± 1.7; P = .003), pharmacists (7.0 ± 1.6; P < .0001), HCPs and those from tertiary centers (6.2 ± 1.7; P = .028) had higher knowledge scores. While 228 (76%) respondents had observed incidents of ADR during their professional practice, only 75 (25%) have ever reported it. Only 113 (37.7%) of respondents had seen the adverse drug reaction reporting form with only 53 (17.7%) ever using it. The reporting methods preferred by respondents were through email/internet (102; 34.0%), phone/SMS (78; 26.0%) and using the hard copy of the forms (95; 31.7%). The attitude of respondents towards ADR reporting was mainly positive.

Conclusion:

There was significant variation in the knowledge of different categories of HCPs and facility levels about ADR reporting. Encouragingly, the overall attitude of respondents towards ADR reporting was positive. Based on the above, strategies are needed to build capacity of HCPs in the area of on adverse drug reaction and its’ reporting.
Organization Development Values From a Future-Oriented Perspective: An International Delphi Study
Authors: Yoon Hyung Joon , Farley Sasha B. , Padilla Cesar
Published: September 2020

This study sought to identify Organization Development (OD) values to guide OD practitioners using a future-oriented perspective to differentiate OD from related fields. Employing six guiding principles, a Delphi study with three rounds was conducted with 42 international OD practitioners and researchers who practice in 58 countries collectively. As a result, this study identified nine OD values ( awareness of self and system, continuous learning and innovation, integrity, courageous leadership, trust and respect, diversity, collaborative engagement, strategic practicality, and client growth and development) along with 71 corresponding behavioral indicators. This article compares the identified values with OD values featured in the existing literature, adding temporal external validity and highlighting the consistency of OD values over time. Also discussed are the implications of this research for OD practitioners, the OD field, OD researchers, and other groups.
Randomized Trial of 2 Self-Titrated Oral Appliances for Airway Management
Authors: Schneiderman E. , Schramm P. , Hui J. , Wilson P. D. , Moura P. , German Z. , McCann A. , Newton M.
Published: September 2020

The effectiveness and predictability of 2 different oral appliance (OA) designs to reduce the respiratory event index (REI) in moderate and severe obstructive sleep apnea (OSA) patients requires elucidation. The primary aim of the trial was to determine if 2 widely used midline-traction and bilateral-thrust OA designs differ in effectiveness to reduce the REI within a single test population categorized by OSA severity. Moderate and severe adult OSA patients, who were previously prescribed continuous positive airway pressure therapy (CPAP) but were dissatisfied with it ( n = 56), were studied by home-polygraphy in a randomized crossover trial using either midline-traction with restricted mouth opening (MR) or bilateral thrust with opening permitted (BP) design OAs. OAs were used nightly for 4 wk (T2) followed by a 1-wk washout period, then 4 wk (T4) using the alternate OA. REI and oxygen saturation (SaO2) were primary outcomes, while predictability and efficacy comparison of the 2 OAs were secondary outcomes. Thirty-six participants had used MR and BP OAs during both 4-wk study legs. Twenty (55.6%) MR OA-using participants, 25 (69.4%) BP OA-using participants, and 16 (44.4%) participants using both OAs had significant REI reductions. Overall baseline (T0) median REI (interquartile range) of 33.7 (20.7–54.9) was reduced to 18.0 (8.5–19.4) at T2 and to 12.5 (8.2–15.9) at T4 ( P < 0.001). Comparison of the 2 sequence groups’ (MR-BP and BP-MR) REI showed the median differences between T0 and T2 and T4 were highly significant ( P < 0.001). Regression analysis predicted about half of all users will have REIs between 8 and 16 after 2 mo. Baseline overjet measures >2.9 mm predicted greater OA advancement at T4. Mean and minimum SaO2 did not change significantly from T0 to T2 or T4. MR and BP OA designs similarly attenuated REI in moderate and severe OSA individuals who completed the 8-wk study protocol with greater REI reduction in those with severe OSA (ClinicalTrials.gov NCT03219034).
Western Colonialism and World Society in National Education Systems: Global Trends in the Use of High-Stakes Exams at Early Ages, 1960 to 2010
Authors: Furuta Jared
Published: September 2020

National high-stakes exams are a fundamental structural feature of education systems around the world. Despite their importance in shaping educational stratification, little is known about the social processes that influence how and why national high-stakes exams are used at early ages on a global basis. I argue that global trends in the use of primary-level high-stakes exams during the postwar period are shaped by competing international and historical pressures. On one hand, Western colonialism instigated path-dependent processes that led former French and British colonies to continue to use high-stakes exams at the primary level, even after gaining independence. On the other hand, a worldwide cultural shift toward universalistic conceptions of education as a human right has led other countries to abandon high-stakes exams at early ages. Drawing on a newly constructed panel data set of 138 countries from 1960 to 2010, I show that national high-stakes exams have declined over time at early ages of schooling. Evidence from a series of panel regression models supports arguments about the importance of Western colonialism and universalistic conceptions of education in world society in shaping the use of high-stakes exams at the primary level.
The Impact of the Media and Environmental Pollution on the Economy and Health Using a Modified Meta 2-Stage EBM Malmquist Model
Authors: Li Ying , Chiu Yung-ho , Liu Yabin , Lin Tai-Yu , Chang Tzu-Han
Published: September 2020

China’s pursuit of economic growth, rapid industrialization, and urbanization over the past few decades has resulted in high energy consumption, which in turn has caused serious environmental pollution problems, such as CO2 and PM2.5 emissions, the long-term exposure to which can seriously affect resident health. To resolve these air pollution problems, the Chinese government has put in place several policies to reduce air and environmental pollution. Past studies on energy and environmental efficiency have been mostly static, have ignored the dynamic changes over time and regional differences, and have rarely considered human health factors. Therefore, this study employed a modified meta 2-stage Epsilon-Based Measure (EBM) Malmquist model to explore the relationships between the economy, energy, the environment, health and media, and the regional differences in 31 Chinese cities from 2014 to 2016. It was found that (1) Haikou and Lhasa’s efficiencies were 1 and were the best in all 3 years, and Shijiazhuang, Jinan and Shenyang’s were the most improved; (2) there was a gap between the eastern, central and western technological frontiers, with Chengdu, Hohhot, Chongqing, and Nanchang having technological gap ratios below 0.70 in the western and central Chinese regions, and Haikou, Guangzhou, and Shanghai in eastern China having technological gap ratios above 0.90 in all 3 years; and (3) the variations in the health treatment stage were greater than in the production stage, indicating that technological changes and efficiency improvements in the health treatment stages in each city were not stable.
From Black Power to Broken Windows: Liberal Philanthropy and the Carceral State
Authors: Collings-Wells Sam
Published: September 2020

During the 1960s, the Ford Foundation was one of the largest philanthropic organizations in the United States. This article examines the shifting strategies which Ford deployed in an attempt to tackle urban disorder in U.S. cities between 1965 and 1982. From 1966 to 1969, Ford engaged in a series of experimental projects which sought to dampen unrest through “community action” and grassroots mobilization, many of which required working with Black Power organizations. Yet, after this generated considerable political controversy, the foundation shifted toward funding liberal police reform, establishing the Police Foundation in 1970, a Washington-based organization whose research provided the intellectual underpinning for “Broken Windows” policing. Studying the Ford Foundation’s programming during this period can illuminate the understudied contribution of liberal philanthropy to the rise of the carceral state, as well as the connections between the grassroots antipoverty efforts of the 1960s and the punitive turn of the 1970s.
Proficiency and Giftedness: The Role of Language Comprehension in Gifted Identification and Achievement
Authors: Hamilton Rashea , Long Daniel , McCoach D. Betsy , Hemmler Vonna , Siegle Del , Newton Sarah D. , Gubbins E. Jean , Callahan Carolyn M.
Published: September 2020

English learners (ELs) are the fastest growing population of students in the United States and currently represent nearly 10% of public school enrollment; however, they also constitute less than 3% of gifted program enrollment in these schools. Although an increasing number of studies explore this underrepresentation, research that specifically examines the role of language proficiency in gifted identification is limited. This study explored the role of several factors on ELs’ time to reclassification (the point at which students are considered to have reached language proficiency and are no longer classified as ELs) and, in turn, being identified for gifted services. The findings suggested notable demographic and socioeconomic influences on the time to reclassification of ELs. Students who were reclassified earlier tended to be enrolled in schools with more gifted students and had a greater probability of being identified as gifted.
Exploring Family Service Providers Perceptions of Working with Recoupled Parents in Stepfamilies
Authors: Cann-Milland Sonia , Mornane Angela , Southcott Jane
Published: September 2020

We explore the perception of family service providers’ opinions and personal experiences working with recoupled parents in stepfamily forms. We examined service providers’ specific knowledge, attitudes, and practical responses to working with stepfamily forms that functions very differently to nuclear family forms. We interviewed four family service providers who work with individuals, couples, and families from a multiplicity of diverse family forms. Four main themes came out of the data collected: challenges family service providers identified when working with stepfamilies; complex relationship connections in stepfamilies; working within the boundaries and limitations of legislation and policies relating to both families in general and stepfamilies; and understanding and working within the parameters of how the family functions as a stepfamily. Our research demonstrates the importance of family service providers having a platform to discuss issues impacting family service providers working relevantly and effectively with stepfamilies.
‘My wife is my doctor at home’: A qualitative study exploring the challenges of home-based palliative care in a resource-poor setting
Authors: Salifu Yakubu , Almack Kathryn , Caswell Glenys
Published: September 2020

Background:

Family caregiving is common globally, but when a family member needs palliative and end-of-life care, this requires knowledge and expertise in dealing with symptoms, medication, and treatment side effects. Caring for a family member with advanced prostate cancer in the home presents practical and emotional challenges, especially in resource-poor contexts, where there are increasing palliative cases without adequate palliative care institutions.

Aim:

The study explored palliative and end-of-life care experiences of family caregivers and patients living at home in a resource-poor context in Ghana.

Design:

This is a qualitative study using thematic analysis of face-to-face interviews at two-time points.

Participants:

Men living with advanced prostate cancer ( n = 23), family caregivers ( n = 23), healthcare professionals ( n = 12).

Findings:

Men with advanced prostate cancer face complex issues, including lack of access to professional care and a lack of resources for homecare. Family caregivers do not have easy access to professional support; they often have limited knowledge of disease progression. Patients have inadequate access to medication and other practical resources for homecare. Caregivers may be overburdened and perform the role of the patient’s ‘doctor’ at home-assessing patient’s symptoms, administering drugs, and providing hands-on care.

Conclusion:

Home-based care is promoted as an ideal and cost-effective model of care, particularly in Westernised palliative care models. However, in resource-poor contexts, there are significant challenges associated with the implementation of this model. This study revealed the scale of challenges family caregivers, who lack basic training on aspects of caring, face in providing home care unsupported by healthcare professionals.
Cell-derived decellularized extracellular matrix scaffolds for articular cartilage repair
Authors: Zhu Wenrun , Cao Lu , Song Chunfeng , Pang Zhiying , Jiang Haochen , Guo Changan
Published: September 2020

Articular cartilage repair remains a great clinical challenge. Tissue engineering approaches based on decellularized extracellular matrix (dECM) scaffolds show promise for facilitating articular cartilage repair. Traditional regenerative approaches currently used in clinical practice, such as microfracture, mosaicplasty, and autologous chondrocyte implantation, can improve cartilage repair and show therapeutic effect to some degree; however, the long-term curative effect is suboptimal. As dECM prepared by proper decellularization procedures is a biodegradable material, which provides space for regeneration tissue growth, possesses low immunogenicity, and retains most of its bioactive molecules that maintain tissue homeostasis and facilitate tissue repair, dECM scaffolds may provide a biomimetic microenvironment promoting cell attachment, proliferation, and chondrogenic differentiation. Currently, cell-derived dECM scaffolds have become a research hotspot in the field of cartilage tissue engineering, as ECM derived from cells cultured in vitro has many advantages compared with native cartilage ECM. This review describes cell types used to secrete ECM, methods of inducing cells to secrete cartilage-like ECM and decellularization methods to prepare cell-derived dECM. The potential mechanism of dECM scaffolds on cartilage repair, methods for improving the mechanical strength of cell-derived dECM scaffolds, and future perspectives on cell-derived dECM scaffolds are also discussed in this review.
Massive intra-abdominal recurrence after robotic-assisted radical cystectomy: A case report and critical appraisal of literature
Authors: Chiancone Francesco , Fabiano Marco , Califano Alfonso , Langella Nunzio Alberto , Pucci Luigi , Franzese Dario , Izzo Alessandro , Perdonà Sisto , Fedelini Paolo
Published: September 2020

Introduction:

Over the years, the robotic surgery is gaining increasing importance in the treatment of bladder cancer. Some doubts remain about the oncological safety of robotic approach and alerts have been raised about the occurrence of atypical recurrences, including peritoneal carcinomatosis and port-site metastasis.

Case presentation:

The patient referred to our Emergency Department because of acute confusional state probably due to severe anemia and sepsis. A left nephroureterectomy, left hemicolectomy with end colostomy and the surgical excision of the huge mass was performed through a xipho-pubic incision associated to another left peri-stomal incision. The histological specimen analysis showed a high-grade sarcoma, not otherwise specified (sarcoma, NOS-type), measuring 29 cm × 8 cm × 5 cm in diameters. The left kidney and ureter were not infiltrated by the neoplasm while serosa membranes and muscular layers of left colon were infiltrated by the mass. The patient died because of a cardiac arrest 4 days after surgery.

Discussion:

RARC is a safe and feasible alternative to open radical cystectomy (ORC) with satisfactory operative time, little blood loss, and low transfusion rates. Despite this, RARC is associated with a low, but not neglectable, risk of atypical metastases like peritoneal implants and port-site metastasis. Although a small amount (7%) of RARC were performed in non-urothelial variants of bladder cancer, the sarcomatoid one can be related to a greater risk of atypical recurrence and special precaution should be taken to reduce potential causes of tumor seeding.
Youth Weigh In: Views on Advanced Neurotechnology for Drug-Resistant Epilepsy
Authors: Udwadia Farhad R. , McDonald Patrick J. , Connolly Mary B. , Hrincu Viorica , Illes Judy
Published: September 2020

Background:

Epilepsy affects over 500,000 children in North America of whom 30% have drug-resistant epilepsy. Advancements with neurotechnologies show promising benefits, but the perceptions of these procedures by youth is unknown.

Methods:

We conducted semistructured interviews with 10 youth in British Columbia, Canada who underwent procedures for drug-resistant epilepsy involving different forms of neurotechnology (subdural grids, vagus nerve stimulation, responsive neurostimulation). Interviews were analyzed using the constant comparative qualitative method.

Results:

Four major thematic categories emerged from the interviews. Treatment values, impact of the disorder, personal context, and impact of neurotechnology.

Conclusions:

Besides the predictable goal of seizure reduction, a desire for autonomy and the importance of trust in the medical team emerged as dominant values within the 4 thematic categories that were explicit to the use of new neurotechnologies for the management of drug-resistant epilepsy.