bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Students Performance using Machine learning
Authors: Dhilipan J. , Vijayalakshmi N. , Suriya S. , Christopher Arockiya
Published: February 2021

An enormous measure of computerized information is being produced over a wide assortment in the field of data mining strategies. The creation of student achievement prediction models to predict student performance in academic institutions is a key area of the development of Education Data Mining. A prediction system has been proposed by using their 10th, 12th and previous semester marks. The study is evaluated using Binomial logical regression, Decision tree, and Entropy and KNN classifier. In order to attain their higher score, this framework would assist the student to recognize their final grade and improve their academic conduct.
Fault Diagnosis and Asset Management of Power Transformer Using Adaptive Boost Machine Learning Algorithm
Authors: Balaraman Sujatha , Madavan R. , Vedhanayaki S. , Saroja S. , Srinivasan M. , Stonier Albert Alexander
Published: February 2021

Dissolved Gas Analysis (DGA) data of liquid insulation used to find the incipient faults such as partial discharge, thermal faults of various temperatures, discharge of high and low energy faults, combination of electrical and thermal faults in transformers. The conventional approaches of DGA namely Gas Ratio method, Duval triangle method and the Neural Network seems to be time consuming and sometimes yield erroneous results. In this paper, Adaptive BOOST machine learning algorithm is proposed, which is effective in classifying the transformer incipient faults. The results of proposed algorithm is compared with the results of different other machine learning algorithms such as K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Decision Tree, Ensembler algorithm for the same set of transformers data. From the comparison, it is evident that ADABOOST machine learning algorithm performs well.
Mitigation and analysis of sub synchronous resonance for DFIG based wind farm using STATCOM controller
Authors: Arockiaraj S. , Karunakaran S. , Tamilarasu P.
Published: February 2021

Large-scale integration in transmission networks has led to several challenges; one of which is the need for increased transmission capacity to transport a bulk amount of power without affecting the voltage. In case of transmitting power to large distances series compensation is used along with Doubly-Fed Induction Generator (DFIG) wind turbine and it is simulated using MATLAB Simulink and the results obtained are validated. DFIG wind turbine is operated at normal operating state. Due to series compensation Sub Synchronous Resonance (SSR) occurs which is quite harmful to the wind generator because of the frequency variation, the gear mechanics of the generator gets damaged. When a larger disturbance occurred in any part of the study system at any bus bar, the effect of SSR would be more harmful. The effect of SSR depends on the compensation percentage we used for series compensation. SSR can be mitigated by using Flexible AC transmission System (FACTS) devices such as STATCOM, SVC, and SSSC. We use STATCOM because of its high stability margin, low switching loss and variable voltage rating. Whenever disturbance occurs in the transmission line then STATCOM comes into action by supplying reactive power and absorbing real power thus maintaining the system stability. The STATCOM controller gives pulse to the STATCOM for respective action such as real power absorption or reactive power injection. Thus the Wind turbine is protected and system stability is maintained.
Review on different control techniques for induction motor drive in electric vehicle
Authors: Marulasiddappa H B , Pushparajesh V
Published: February 2021

Now a day Electric vehicles (EV) are called future vehicles in place of internal combustion engines because of their working with pollution free and more efficient. This paper reviews various control strategies of induction motor drives (IMD) for EV applications. Efficiency and performance are the major considerations in selecting control algorithms for induction motor drives. Basically there are scalar control and vector control methods for IMDs. Scalar control technique has drawback of low performance. Conventional direct torque control (DTC) technique is one of the most preferable control technique for controlling torque and flux independently. But due the lower switching frequency in direct torque control leads to more flux ripple and torque ripples and it leads lower performance of induction motor drives.
Development of Optimal Day-Ahead Electricity Pricing Scheme using Real Coded Genetic Algorithm under Demand Response Environment
Authors: Krishna Paramathma M. , Devaraj D. , Agneshidhayaselvi V. , Karuppasamypandian M.
Published: February 2021

Real-time pricing in a Smart Grid scenario allows consumers to move their time-insensitive loads to off-peak hours and maintains the power balance between the demand side and supply side. This scheme has a strong impact on customer behaviour, network operations, and overall control of the power grids. In this proposed work, Real coded Genetic Algorithm (RGA) is used to develop a Day Ahead Real-Time electricity-Pricing (DARTP) model. The established scheme maximizes the benefit of the energy provider without reducing the minimum daily consumption rate, the consumer response to the reported electricity prices, and the constraints of distribution networks. The RGA results demonstrate that the calculated optimal prices bring higher benefits for consumers and energy providers than the posting of market prices directly to consumers on the day ahead. The proposed setup is tested with a 32-node distribution bus system. Simulation results reveal that the deployed methodology will help the participants to shift the peak load time to base load time by receiving optimal DARTP, thereby reducing excessive consumption made during the instance of peak load. The obtained DARTP will be sent to the consumers through the deployment of an Advanced Metering System.
Online estimation of control parameters of FACTS devices for ATC enhancement using artificial neural network
Authors: Karuppasamy Pandiyan M , Agnes Idhayaselvi V , Danalakshmi D , Sheela A
Published: February 2021

The deregulated electricity sector needs an improvement in the Available Transfer Capability (ATC) towards the maintenance of power network at balanced condition and to utilize the system in effective manner. Independent System Operator (ISO) maintains the ancillary services by ensuring the reliability of the power system. One of the major functions of ancillary service provider is to maintain the voltage and power flow at stable level. To improve the ATC, both the line power flow and bus voltage profile have to be modified and it is taken care by the ISO. The major limiting criterion for ATC is bus voltage profile. It is well known that the device Thyristor Controlled Series Compensation TCSC which is one of the Flexible AC Transmission System (FACTS) devices can modify the line flow by adjusting the line reactance and Static VAR compensator (SVC) can improve the bus voltage profile by injecting reactive power to the bus. In this research, an Artificial Neural Network (ANN) based estimation of control parameter of FACTS devices such as TCSC and SVC for ATC enhancement is used. The proposed approach uses two different ANN network to find the different TCSC and SVC control parameters to improve the ATC values without violating its voltage constraints for real time transactions. The ANN algorithms such as Radial Basis Function (RBF) as well as Back Propagation Algorithm (BPA) were used to find the TCSC and SVC Parameters and the results are compared. The proposed methods are demonstrated through Reliability Test System (RTS) of IEEE 24 bus. The simulation output represents the suitability of the anticipated method for Real Time estimation of FACTS devices control parameter settings for ATC Enhancement.
Optimization of processing conditions on mechanical properties of Polypropylene nanocomposite reinforced with Gigantochloa Scortechinii via ANOVA
Authors: Khamis S Z , Mamat O , Othman M H
Published: February 2021

Defining the level and value of the appropriate parameters is very significant in seeing the quality in mechanical properties of the injection molding products, particularly affecting the advanced material such as nanocomposites. Consequently, this study was aimed to optimize the processing conditions to the mechanical properties of the sample in nanocomposite polypropylene reinforced with Gigantochloa Scortechinii fiber. The tests to be tested were flexural strength, shrinkage and warpage, and the factor chosen were melting temperature, filling time, packing pressure and screw speed. The bamboo fiber types Gigantochloa Scortechinii in form nano powder, and preheat at 120˚C after alkaline treatment, and so blended with polypropylene, Maleic anhydride, and cloisite 20A using two step of twin-screw extruder brabender. According the result from ANOVA, the flexural strength and shrinkage for 0wt% and 3wt% of Gigantochloa Scortechinii fiber, the most influence parameter is filling time, while the melt temperature for 6wt% of gigantochlia scortechinii fiber. For the result of warpage, for 0wt% and 3wt% of fiber Gigantochloa Scortechinii, the melting temperature is the highest factor prevailing warpage. Whereas for 6wt% of the fiber Gigantochloa Scortechinii, the packing pressure and screw speed are the highest factor. The conclusions of this study will be invaluable for quality dominance and benchmarking for future researchers.
A review on bonding of Polyamide reinforced carbon fibre via additive manufacturing
Authors: Naima Khalid Nisa , Afiqah Mohd Radzuan Nabilah , Bakar Sulong Abu , Mohd Foudzi Farhana
Published: February 2021

Continuous carbon fibre offers a huge potential which is a lightweight, high strength, low density, a low coefficient of thermal expansion, and high thermal conductivity and stiffness. In addition, polyamide-6 (PA6) has good mechanical and physical properties thus, it makes PA6 as effectiveness between matrix and reinforcement of continuous carbon fibre. 3D printing as a cost effective in additive manufacturing was covered in a complex part building using CAD software based on CAD model makes fisible finish the elements. The main objectives of this paper are to review on interlayer bonding of polyamide reinforced carbon fibre by using 3D printing method on their mechanical properties. This paper scope was a review on the bonding of polymeric composites which is polyamide reinforced carbon fibre as the material used and their printing parameter which is important for their orientation during printing. The printing parameter in 3D printing was set to vary the quality and mechanical behavior of the sample. The sample was reviewed on their bead orientation consist of 0°, 45°, and 90° directional angle of the sample in form of their bonding. Mechanical properties of the samples were tests using tensile test and resulted at 0° it achieves higher tensile strength and modulus when tensile loading direction is parallel to deposition direction. At 90° direction, the fibre was perpendicular with the tensile loading direction and resulted in a decreased tensile property.
A review on the prospect of wind power as an alternative source of energy in Malaysia
Authors: Ashwindran S N , Azizuddin A A , Oumer A N , Sulaiman M Z
Published: February 2021

Fossil fuels has dictated the energy sector for several decades, rising as the primary and prominent source of energy production for various sector of industries namely electricity (power), transportation, manufacturing and others. However, extensive usage of fossil fuels majorly contributed to pollution issues and degradation of the environment. Hence, governments and research agencies are providing supports and resources to facilitate the growth of renewable energy sector (RES). This manuscript provides a brief view of the challenges of wind renewable energy sector in Malaysia relative to geographical wind condition, government policies and challenges in initiation of wind technologies and global perspective of green energy in terms of RER. It is found that data presented by previous researchers on wind speed data are considered unreliable to be utilized for WT power density assessment and design. Notably, wind speed in Malaysia is seasonal based and highly inconsistent. The wind flow pattern and intensity experience by Malaysia are merely an aftereffect of weather change in neighbouring regions. Nevertheless, it is found that selected regions of east-coast peninsular Malaysia and selected region of Sabah and Sarawak is potential for harvesting wind power due to substantial and adequate wind pattern behavior during monsoon season. Therefore, it is evident that geographical wind condition of Malaysia is appropriate for wind power devices as a form of RER in green energy sector of Malaysia. However, it is also found that fundamental design modification is required on conventional design of WT in terms of blade morphology and configuration in order to adapt to unsteady monsoon wind speed pattern.
Optimization of laser melting parameter to enhanced surface properties in hot press forming die
Authors: Norhafzan B , Aqida S N , Khairil C M
Published: February 2021

This paper presents laser melting process with various parameter to enhanced surface properties of AISI H13 tool steel. The design of experiment (DOE) optimisation was conducted to obtain significant model using regression analysis. DOE were analysed using response surface method (RSM) with Box-Behnken design approach. Design Expert 7 software was used to design parameter of laser melting process. The laser melting processes was conducted using Nd:YAG laser system with pulsed mode at a constant average power of 100 W, overlapping rate of 30 to 50%, peak power of 1700 to 2500 W and pulse repetition frequency (PRF) of 50 to 70 Hz respectively. The responses were characterised for sub-surface hardness, melt depth and surface roughness. The results show that optimum parameter of 2500 W peak power, 60 Hz PRF and 30% overlapping rate produced highest surface hardness of 793.7 HV0.1 with 0.21 mm melted depth and 3.89 µm surface roughness from experimental data. This finding was important to enhance properties of AISI H13 tool steel for hot press forming die using laser process.
Effect of thread profile variation on pullout and bending strength of a pedicle screw
Authors: Daud Rosdi , Kae W Y , Mas Ayu H , Shah A
Published: February 2021

Pedicle screw is an important instrument in treatment of spinal degeneration or disease. However, the pedicle screw failure still occurs due to the screw loosening, fracture and pullout. There are few factors that affected the pedicle screw performance as reported by previous research but still lacking study related to the pedicle screw thread profile. Thus, the aim of this research is to investigate the effect of variation of thread pitch on the pullout and bending strength of pedicle screw. The research is carried out by constructing 3D pedicle screw models (model 1-6), importing the models into ANSYS, meshing and post processing analysis. The equivalent or Von-Mises stress used to compare the bending and pullout performance of the pedicle screws. Based on the obtained finite element analysis result, the single thread pedicle screw (model 3) has the optimum performance in bending while the model 4 is the optimum in pullout performance. While, for the dual threaded pedicle screw, the model 6 which has coarse thread pitch at screw tip is better than model 5 (fine thread). Thus, it can be conclude that both the single and dual threaded pedicle screw with coarse thread pitch has lower maximum equivalent stress than fine thread pitch, which is means it has better bending and pullout performance.
A review on 3D printed polymer-based composite for thermal applications
Authors: Halim N A , Mogan J , Sandanamsamy L , Harun W S W , Kadirgama K , Ramasamy D , Tarlochan F
Published: February 2021

Recently, 3D printing techniques for the polymer-based part has become popular in the industry and academic area. Fused deposition modelling (FDM) is one of the most popular methods among 3D printing techniques because of its low cost, ability to fabricate objects with complex structures and geometries, specific functions, ease in processing, safety, reliability, and availability of various thermoplastic materials. This technique’s application is widespread on the electronic application, medical application, and rapid tooling applications. This paper aims to review fused deposition modelling (FDM) 3D printed polymer-based composite techniques for thermal management applications. This paper will provide an overview of fused deposition modelling (FDM) techniques in 3D printing, conducting polymer base and conducting nanofiller additive material used, and current trend research in this area.
New Determination Method of Two Bioactive Saponins in Lysimachia capillipes Hemsl. by Quantitative Analysis of Multi-Components by Single-Marker
Authors: Zhang Xiaoyong , Chen Xuezhao , Jin Juan , Gong Minghua , He Qiang , Li Shouxin , Tian Jinkui
Published: February 2021

Capilliposide B (CPS-B) and Capilliposide C (CPS-C), as the key components in Lysimachia capillipes Hemsl., increasingly aroused the interest and research concern of many researchers due to the good bioactivities. Nowadays, the reference standards of CPS-B and CPS-C yield were very limited. Due to the deficit of reference standards, the determination could be difficult to carry out, and the quality control and evaluation would be restrained afterwards. To solve this urgent problem, a quantitative analysis of multi-components by single-marker (QAMS) method was proposed and established based on high-performance liquid-chromatography tandem evaporative light-scattering detector. In this QAMS method, the content of the two bioactive components could be calculated by buddlejasaponin IV, which is applied as an external standard and readily obtained. And the methodological experiments were evaluated and indicated accuracy, stability and feasibility of this QAMS method. Therefore, in this study, this built method would properly meet the requirement of determination of CPS-B, CPS-C and quality control of the L. capillipes Hemsl. plant.
Diagnostic Value of 16S Ribosomal RNA Gene Polymerase Chain Reaction/Sanger Sequencing in Clinical Practice
Authors: Fida Madiha , Khalil Sarwat , Abu Saleh Omar , Challener Douglas W , Sohail Muhammad Rizwan , Yang Joshua N , Pritt Bobbi S , Schuetz Audrey N , Patel Robin
Published: February 2021

Background

Accurate microbiologic diagnosis is important for appropriate management of infectious diseases. Sequencing-based molecular diagnostics are increasingly used for precision diagnosis of infections. However, their clinical utility is unclear.

Methods

We conducted a retrospective analysis of specimens that underwent 16S ribosomal RNA (rRNA) gene polymerase chain reaction (PCR) followed by Sanger sequencing at our institution from April 2017 through March 2019.

Results

A total of 566 specimens obtained from 460 patients were studied. Patients were considered clinically infected or noninfected based on final diagnosis and management. In 17% of patients, 16S rRNA PCR/sequencing was positive and in 5% of patients, this test led to an impact on clinical care. In comparison, bacterial cultures were positive in 21% of patients. Specimens with a positive Gram stain had 12 times greater odds of having a positive molecular result than those with a negative Gram stain (95% confidence interval for odds ratio, 5.2–31.4). Overall, PCR positivity was higher in cardiovascular specimens (37%) obtained from clinically infected patients, with bacterial cultures being more likely to be positive for musculoskeletal specimens (P < .001). 16S rRNA PCR/sequencing identified a probable pathogen in 10% culture-negative specimens.

Conclusion

16S rRNA PCR/sequencing can play a role in the diagnostic evaluation of patients with culture-negative infections, especially those with cardiovascular infections.
The European Perspective and History on Biosimilars for the Treatment of Inflammatory Bowel Diseases
Authors: Solitano Virginia , D’Amico Ferdinando , Da Rio Leonardo , Peyrin-Biroulet Laurent , Danese Silvio
Published: February 2021

With the expiration of biologics’ patents, biosimilars entered the market as a promising opportunity to reduce health-care costs in the field of inflammatory bowel diseases. Although biosimilars were initially poorly accepted, the growing evidence about their efficacy and safety has changed this situation, resulting in their widespread use. However, there is still an unmet need of improving patients’ education about biosimilars to minimize nocebo responses and to accept nonmedical switching. Looking to the future, the use of recently authorized adalimumab biosimilars and the first attempts of adopting different strategies of switching (eg, cross-, multiple-) will fill some residual knowledge gaps.
Impact of the introduction of an enhanced recovery pathway in esophageal cancer surgery: a cohort study and propensity score matching analysis
Authors: Moons J , Depypere L , Lerut T , van Achterberg T , Coosemans W , Van Veer H , Mandeville Y , Nafteux P
Published: February 2021

Enhanced recovery pathways (ERP) have the potential to improve clinical outcomes. Aim of this study was to determine the impact of ERP on perioperative results as compared with traditional care (TC) after esophagectomy. In this study, two cohorts were compared. Cohort 1 represented 296 patients to whom TC was provided. Cohort 2 consisted of 200 unselected ERP patients. Primary endpoints were postoperative complications. Secondary endpoints were the length of stay and 30-day readmission rates. To confirm the possible impact of ERP, a propensity matched analysis (1:1) was conducted. A significant decrease in complications was found in ERP patients, especially for pneumonia and respiratory failure requiring reintubation (39% in TC and 14% in ERP; P<0.0001 and 17% vs. 12%; P<0.0001, respectively) and postoperative blood transfusion (26.7%–11%; P<0.0001). Furthermore, median length of stay was also significantly shorter: 13 days (interquartile range [IQR] 10–23) in TC compared with 10 days (IQR 8–14) in ERP patients (P<0.0001). The 30-day readmission rate (5.4% in TC and 9% in ERP; P=0.121) and in-hospital mortality rate (4.4% in TC and 2.5% in ERP; P=0.270) were not significantly affected. A propensity score matching confirmed a significant impact on pneumonia (P=0.0001), anastomotic leak (P=0.047), several infectious complications (P=0.01–0.034), blood transfusion (P=0.001), Comprehensive Complications Index (P=0.01), and length of stay (P=0.0001). We conclude that ERP for esophagectomy is associated with significantly fewer postoperative complications and blood transfusions, which results in a significant decrease of length of stay without affecting readmission and mortality rates.
Impact of winter holiday and government responses on mortality in Europe during the first wave of the COVID-19 pandemic
Authors: Björk Jonas , Mattisson Kristoffer , Ahlbom Anders
Published: February 2021

Background

This aggregated population study investigated the impact of the seemingly quasi-randomly assigned school winter holiday in weeks 6–10 (February to early March) on excess mortality in 219 European regions (11 countries) during the COVID-19 pandemic in the spring 2020. A secondary aim was to evaluate the impact of government responses to the early inflow of infected cases.

Methods

Data on government responses weeks 8–14 were obtained from the Oxford COVID-19 Government Response Tracker. Regional data on total all-cause mortality during weeks 14–23 in 2020 were retrieved from Eurostat and national statistical agencies and compared with the average mortality during same period 2015–2019. Variance-weighted least square regression was used with mortality difference as dependent variable with adjustment for country, population density and age distribution.

Results

Being a region with winter holiday exclusively in week 9 was in the adjusted analysis associated with 16 weekly excess deaths [95% confidence interval (CI) 13–20] per million inhabitants during weeks 14–23, which corresponds to 38% of the excess mortality in these regions. A more stringent response implemented in week 11, corresponding to 10 additional units on the 0–100 ordinal scale, was associated with 20 fewer weekly deaths (95% CI 18–22) per million inhabitants.

Conclusions

Winter holiday in week 9 was an amplifying event that contributed importantly to the excess mortality observed in the study regions during the spring 2020. Timely government responses to the resulting early inflow of cases reduced the excess in mortality.
Creating and Validating a DNA Methylation-Based Proxy for Interleukin-6
Authors: Stevenson Anna J , Gadd Danni A , Hillary Robert F , McCartney Daniel L , Campbell Archie , Walker Rosie M , Evans Kathryn L , Harris Sarah E , Spires-Jones Tara L , McRae Allan F , Visscher Peter M , McIntosh Andrew M , Deary Ian J , Marioni Riccardo E
Published: February 2021

Background

Studies evaluating the relationship between chronic inflammation and cognitive functioning have produced heterogeneous results. A potential reason for this is the variability of inflammatory mediators which could lead to misclassifications of individuals’ persisting levels of inflammation. DNA methylation (DNAm) has shown utility in indexing environmental exposures and could be leveraged to provide proxy signatures of chronic inflammation.

Method

We conducted an elastic net regression of interleukin-6 (IL-6) in a cohort of 875 older adults (Lothian Birth Cohort 1936; mean age: 70 years) to develop a DNAm-based predictor. The predictor was tested in an independent cohort (Generation Scotland; N = 7028 [417 with measured IL-6], mean age: 51 years).

Results

A weighted score from 35 CpG sites optimally predicted IL-6 in the independent test set (Generation Scotland; R2 = 4.4%, p = 2.1 × 10−5). In the independent test cohort, both measured IL-6 and the DNAm proxy increased with age (serum IL-6: n = 417, β = 0.02, SE = 0.004, p = 1.3 × 10−7; DNAm IL-6 score: N = 7028, β = 0.02, SE = 0.0009, p < 2 × 10−16). Serum IL-6 did not associate with cognitive ability (n = 417, β = −0.06, SE = 0.05, p = .19); however, an inverse association was identified between the DNAm score and cognitive functioning (N = 7028, β = −0.16, SE = 0.02, pFDR < 2 × 10−16).

Conclusions

These results suggest methylation-based predictors can be used as proxies for inflammatory markers, potentially allowing for further insight into the relationship between inflammation and pertinent health outcomes.
Optimism and Longevity Beyond Age 85
Authors: Jacobs Jeremy M , Maaravi Yoram , Stessman Jochanan
Published: February 2021

Background

Optimism is associated with health benefits and improved survival among adults older than 65 years. Whether or not optimism beyond age 85 continues to confer survival benefits is poorly documented. We examine the hypothesis that being optimistic at ages 85 and 90 is associated with improved survival.

Method

The Jerusalem Longitudinal Study (1990–2020) assessed comorbidity, depression, cognition, social and functional status, and 5-year mortality among a representative community sample, born during 1920–1921, at age 85 (n = 1096) and age 90 (n = 533). Overall optimism (Op-Total) was measured using a validated 7-item score from the Scale of Subjective Wellbeing for Older Persons. The 4 questions concerning positive future expectations (Op-Future) and 3 questions concerning positive experiences (Op-Happy) were also analyzed separately. We determined unadjusted mortality hazards ratios and also adjusted for gender, financial difficulty, marital status, educational status, activities of daily living dependence, physical activity, diabetes mellitus, hypertension, ischemic heart disease, cognitive impairment, and depression.

Results

Between ages 85–90 and 90–95 years, 33.2% (364/1096) and 44.3% (236/533) people died, respectively. All mean optimism scores declined from age 85 to 90, with males significantly more optimistic than females throughout. All measures of optimism (Op-Total, Op-Future, and Op-Happy) at ages 85 and 90 were significantly associated with improved 5-year survival from age 85 to 90 and 90 to 95, respectively, in both unadjusted and adjusted models. Findings remained unchanged after separately excluding depressed subjects, cognitively impaired subjects, and subjects dying within 6 months from baseline.

Conclusions

These finding support the hypothesis that being optimistic continues to confer a survival benefit irrespective of advancing age.
Job Strain and Trajectories of Cognitive Change Before and After Retirement
Authors: Nilsen Charlotta , Nelson Monica E , Andel Ross , Crowe Michael , Finkel Deborah , Pedersen Nancy L
Published: February 2021

Objectives

We examined associations between job strain and trajectories of change in cognitive functioning (general cognitive ability plus verbal, spatial, memory, and speed domains) before and after retirement.

Methods

Data on indicators of job strain, retirement age, and cognitive factors were available from 307 members of the Swedish Adoption/Twin Study of Aging. Participants were followed up for up to 27 years (mean = 15.4, SD = 8.5).

Results

In growth curve analyses controlling for age, sex, education, depressive symptoms, cardiovascular health, and twinness, greater job strain was associated with general cognitive ability (estimate = −1.33, p = .002), worse memory (estimate = −1.22, p = .007), speed (estimate = −1.11, p = .012), and spatial ability (estimate = −0.96, p = .043) at retirement. Greater job strain was also associated with less improvement in general cognitive ability before retirement and a somewhat slower decline after retirement. The sex-stratified analyses showed that the smaller gains of general cognitive ability before retirement (estimate = −1.09, p = .005) were only observed in women. Domain-specific analyses revealed that greater job strain was associated with less improvement in spatial (estimate = −1.35, p = .010) and verbal (estimate = −0.64, p = .047) ability before retirement in women and a slower decline in memory after retirement in women (estimate = 0.85, p = .008) and men (estimate = 1.12, p = .013). Neither preretirement nor postretirement speed was affected significantly by job strain.

Discussion

Greater job strain may have a negative influence on overall cognitive functioning prior to and at retirement, while interrupting exposure to job strain (postretirement) may slow the rate of cognitive aging. Reducing the level of stress at work should be seen as a potential target for intervention to improve cognitive aging outcomes.
Post hocpatient satisfaction with the choice of valve prosthesis for aortic valve replacement: results of a single-centre survey
Authors: Bryssinck Laure , De Vlieger Siel , François Katrien , Bové Thierry
Published: February 2021

OBJECTIVES

Our goal was to examine post hoc patient satisfaction and the decision-making process of choosing a prosthesis for aortic valve replacement (AVR).

METHODS

We surveyed 113 patients who were operated on for AVR at 60–70 years of age, including 74 patients with a mechanical valve (MECH) and 39 with a bioprosthesis (BIO). The study focused on quality of life and the decision pathway in relation to prosthesis choice and valve-related complications. Decisional conflict was defined as the post hoc uncertainty perceived by patients regarding their choice of prosthesis.

RESULTS

The survey was performed at a median of 5.2 (3.2–8.1) years after the AVR. Patients with a biological valve were older (BIO: 68.4 years [66.2–69.4] vs MECH: 63.9 [61.9–66.7]; P < 0.001). Global post hoc satisfaction with prosthesis choice was high in both groups (MECH: 95.9%; BIO: 100%), and 85.1% (MECH) and 92.3% (BIO) of them would repeat their choice. Conflict about their decision was equal (MECH: 30.3%; BIO: 32.6%) for different reasons: MECH patients experienced more anticoagulation-related inconvenience (25.9% vs 0%), fear of bleeding (31.1% vs 0%) and prosthesis noise (26.2% vs 0%), whereas more BIO patients feared prosthesis failure (39.7% vs 17.4%) or reoperation (43.5% vs 18.1%). Active involvement in the decision (odds ratio 0.37, 95% confidence interval 0.16–0.85; P = 0.029) and adequate information about the prosthesis (odds ratio 0.34, 95% confidence interval 0.14–0.86; P = 0.020) decreased the risk of conflict about the decision.

CONCLUSIONS

Although 30% of the responders showed a decisional conflict related to prosthesis-specific interferences, global patient satisfaction with the prosthesis choice for AVR is excellent. Increasing the patient’s involvement in the prosthesis choice through shared accountability and improved information is recommended to decrease the choice-related uncertainty.
Air filtration improvement of konjac glucomannan-based aerogel air filters through physical structure design
Authors: Qian Hong , Fang Ying , Wu Kao , Wang Hao , Li Bin , Jiang Fatang
Published: February 2021

This study presents two methods to improve the air filtration performance of konjac glucomannan (KGM)-based aerogel air filters through physical structure design by changing the pore-size distribution and the surface area, using an air purifier. Results indicated that KGM-based aerogels had a comparable filtration effect with the commercial air filter with a longer purification time. This purification time could be shortened by over 50%, by changing the pore-size distribution from large size to small size or increase the surface area with the fold structure. This should boost the development of polysaccharide-based aerogel used as the air filter.
Distributed information-theoretic clustering
Authors: Pichler Georg , Piantanida Pablo , Matz Gerald
Published: February 2021

We study a novel multi-terminal source coding setup motivated by the biclustering problem. Two separate encoders observe two i.i.d. sequences $X^n$ and $Y^n$, respectively. The goal is to find rate-limited encodings $f(x^n)$ and $g(z^n)$ that maximize the mutual information $\textrm{I}(\,{f(X^n)};{g(Y^n)})/n$. We discuss connections of this problem with hypothesis testing against independence, pattern recognition and the information bottleneck method. Improving previous cardinality bounds for the inner and outer bounds allows us to thoroughly study the special case of a binary symmetric source and to quantify the gap between the inner and the outer bound in this special case. Furthermore, we investigate a multiple description (MD) extension of the CEO problem with mutual information constraint. Surprisingly, this MD-CEO problem permits a tight single-letter characterization of the achievable region.
Controllability of non-linear fractional-order systems with damping behaviour and multiple delays
Authors: Arthi G , Suganya K
Published: February 2021

A controllability analysis of both linear and non-linear fractional-order systems with damping behaviour and multiple delays is studied. We derived the controllability result for damped system with multi-term fractional order and multiple delays by introducing some lemmas with the help of Laplace transform properties and Mittag–Leffler function. Further, some new sufficient conditions ensuring controllability for a class of non-linear multi-term fractional-order damped systems with multiple delays are established by utilizing fractional Caputo derivatives and Schauder’s fixed point theorem. Moreover, as applications that demonstrate the proposed results, two examples are presented.
Effectiveness of vancomycin plus cloxacillin compared with vancomycin, cloxacillin and daptomycin single therapies in the treatment of methicillin-resistant and methicillin-susceptible Staphylococcus aureus in a rabbit model of experimental endocarditis
Authors: Castañeda Ximena , García-De-la-Mària Cristina , Gasch Oriol , Pericàs Juan M , Soy Dolors , Cañas-Pacheco Maria-Alejandra , Falces Carlos , García-González Javier , Hernández-Meneses Marta , Vidal Bàrbara , Almela Manel , Quintana Eduard , Tolosana Jose M , Fuster David , Llopis Jaume , Dahl Anders , Moreno Asuncion , Marco Francesc , Miró Jose M ,   the Hospital Clínic Endocarditis Study Group, Miró Jose M , Hernández-Meneses Marta , Ambrosioni Juan , Dahl Anders , Téllez Adrian , Pericàs Juan M , Moreno Asuncion , García de la Mària Cristina , Cañas Maria Alexandra , García-González Javier , Almela Manel , Casals Climent , Morales Francisco-Javier , Marco Francesc , Vila Jordi , Quintana Eduard , Sandoval Elena , Paré Juan C , Falces Carlos , Pereda Daniel , Cartañá Ramon , Ninot Salvador , Azqueta Manel , Sitges Marta , Vidal Barbara , Andrea Rut , Pomar José L , Castella Manuel , Tolosana José M , Ortiz José , Fita Guillermina , Rovira Irene , Perissinotti Andrés , Fuster David , Ramírez Jose , Soy Dolors , Castro Pedro , Llopis Jaume
Published: February 2021

Objectives

To investigate if the addition of cloxacillin to vancomycin enhances the activity of both monotherapies for treating MSSA and MRSA experimental endocarditis (EE) in rabbits.

Methods

Vancomycin plus cloxacillin was compared with the respective monotherapies and daptomycin. In vitro time–kill studies were performed using standard (105 cfu) and high (108 cfu) inocula of five MRSA, one glycopeptide-intermediate (GISA) and five MSSA strains. One MSSA (MSSA-678) and one MRSA (MRSA-277) strain were selected to be used in the in vivo model. A human-like pharmacokinetics model was applied and the equivalents of cloxacillin 2 g/4 h IV and daptomycin 6 mg/kg/day IV were administered. To optimize vancomycin activity, dosage was adjusted to achieve an AUC/MIC ≥400.

Results

Daptomycin sterilized significantly more vegetations than cloxacillin (13/13, 100% versus 9/15, 60%; P = 0.02) and showed a trend of better activity than vancomycin (10/14, 71%; P = 0.09) and vancomycin plus cloxacillin (10/14, 71%; P = 0.09) against MSSA-678. Addition of cloxacillin to vancomycin (13/15, 87%) was significantly more effective than vancomycin (8/16, 50%; P = 0.05) and showed similar activity to daptomycin (13/18, 72%; P = 0.6) against MRSA-277. In all treatment arms, the bacterial isolates recovered from vegetations were re-tested and showed the same daptomycin susceptibility as the original strains.

Conclusions

Vancomycin plus cloxacillin proved synergistic and bactericidal activity against MRSA. Daptomycin was the most efficacious option against MSSA and similar to vancomycin plus cloxacillin against MRSA. In settings with high MRSA prevalence, vancomycin plus cloxacillin might be a good alternative for empirical therapy of S. aureus IE.
Electronic phenotyping of health outcomes of interest using a linked claims-electronic health record database: Findings from a machine learning pilot project
Authors: Gibson Teresa B , Nguyen Michael D , Burrell Timothy , Yoon Frank , Wong Jenna , Dharmarajan Sai , Ouellet-Hellstrom Rita , Hua Wei , Ma Yong , Baro Elande , Bloemers Sarah , Pack Cory , Kennedy Adee , Toh Sengwee , Ball Robert
Published: February 2021

Objective

Claims-based algorithms are used in the Food and Drug Administration Sentinel Active Risk Identification and Analysis System to identify occurrences of health outcomes of interest (HOIs) for medical product safety assessment. This project aimed to apply machine learning classification techniques to demonstrate the feasibility of developing a claims-based algorithm to predict an HOI in structured electronic health record (EHR) data.

Materials and Methods

We used the 2015-2019 IBM MarketScan Explorys Claims-EMR Data Set, linking administrative claims and EHR data at the patient level. We focused on a single HOI, rhabdomyolysis, defined by EHR laboratory test results. Using claims-based predictors, we applied machine learning techniques to predict the HOI: logistic regression, LASSO (least absolute shrinkage and selection operator), random forests, support vector machines, artificial neural nets, and an ensemble method (Super Learner).

Results

The study cohort included 32 956 patients and 39 499 encounters. Model performance (positive predictive value [PPV], sensitivity, specificity, area under the receiver-operating characteristic curve) varied considerably across techniques. The area under the receiver-operating characteristic curve exceeded 0.80 in most model variations.

Discussion

For the main Food and Drug Administration use case of assessing risk of rhabdomyolysis after drug use, a model with a high PPV is typically preferred. The Super Learner ensemble model without adjustment for class imbalance achieved a PPV of 75.6%, substantially better than a previously used human expert-developed model (PPV = 44.0%).

Conclusions

It is feasible to use machine learning methods to predict an EHR-derived HOI with claims-based predictors. Modeling strategies can be adapted for intended uses, including surveillance, identification of cases for chart review, and outcomes research.
A patient-centered digital scribe for automatic medical documentation
Authors: Wang Jesse , Lavender Marc , Hoque Ehsan , Brophy Patrick , Kautz Henry
Published: February 2021

Objective

We developed a digital scribe for automatic medical documentation by utilizing elements of patient-centered communication. Excessive time spent on medical documentation may contribute to physician burnout. Patient-centered communication may improve patient satisfaction, reduce malpractice rates, and decrease diagnostic testing expenses. We demonstrate that patient-centered communication may allow providers to simultaneously talk to patients and efficiently document relevant information.

Materials and Methods

We utilized two elements of patient-centered communication to document patient history. One element was summarizing, which involved providers recapping information to confirm an accurate understanding of the patient. Another element was signposting, which involved providers using transition questions and statements to guide the conversation. We also utilized text classification to allow providers to simultaneously perform and document the physical exam. We conducted a proof-of-concept study by simulating patient encounters with two medical students.

Results

For history sections, the digital scribe was about 2.7 times faster than both typing and dictation. For physical exam sections, the digital scribe was about 2.17 times faster than typing and about 3.12 times faster than dictation. Results also suggested that providers required minimal training to use the digital scribe, and that they improved at using the system to document history sections.

Conclusion

Compared to typing and dictation, a patient-centered digital scribe may facilitate effective patient communication. It may also be more reliable compared to previous approaches that solely use machine learning. We conclude that a patient-centered digital scribe may be an effective tool for automatic medical documentation.
Determining the range of validity of quasar X-ray and UV flux measurements for constraining cosmological model parameters
Authors: Khadka Narayan , Ratra Bharat
Published: February 2021

We use six different cosmological models to study the recently released compilation of X-ray and UV flux measurements of 2038 quasars (QSOs) which span the redshift range 0.009 ≤ z ≤ 7.5413. We find, for the full QSO data set, that the parameters of the X-ray and UV luminosities LX−LUV relation used to standardize these QSOs depend on the cosmological model used to determine these parameters, i.e. it appears that the full QSO data set includes QSOs that are not standardized and so cannot be used for the purpose of constraining cosmological parameters. Subsets of the QSO data, restricted to redshifts z ≲ 1.5–1.7 obey the LX−LUV relation in a cosmological-model-independent manner, and so can be used to constrain cosmological parameters. The cosmological constraints from these lower z, smaller QSO data subsets are mostly consistent with, but significantly weaker than, those that follow from baryon acoustic oscillation and Hubble parameter measurements.
Tumor metabolism and neurocognition in CNS lymphoma
Authors: Geng Huimin , Tsang Mazie , Subbaraj Lakshmipriya , Cleveland Joseph , Chen Lingjing , Lu Ming , Sharma Jigyasa , Vigneron Daniel B , Kurhanewicz John , LaFontaine Marisa , Luks Tracy , Barshop Bruce A , Gangoiti Jon , Villanueva-Meyer Javier E , Rubenstein James L
Published: February 2021

Background

The mechanistic basis for neurocognitive deficits in central nervous system (CNS) lymphoma and other brain tumors is incompletely understood. We tested the hypothesis that tumor metabolism impairs neurotransmitter pathways and neurocognitive function.

Methods

We performed serial cerebrospinal fluid (CSF) metabolomic analyses using liquid chromatography-electrospray tandem mass spectrometry to evaluate changes in the tumor microenvironment in 14 patients with recurrent CNS lymphoma, focusing on 18 metabolites involved in neurotransmission and bioenergetics. These were paired with serial mini-mental state examination (MMSE) and MRI studies for tumor volumetric analyses. Patients were analyzed in the setting of the phase I trial of lenalidomide/rituximab. Associations were assessed by Pearson and Spearman correlation coefficient. Generalized estimating equation (GEE) models were also established, adjusting for within-subject repeated measures.

Results

Of 18 metabolites, elevated CSF lactate correlated most strongly with lower MMSE score (P < 8E-8, ρ = −0.67). High lactate was associated with lower gamma-aminobutyric acid (GABA), higher glutamate/GABA ratio, and dopamine. Conversely, high succinate correlated with higher MMSE scores. Serial analysis demonstrated a reproducible, time-dependent, reciprocal correlation between changes in lactate and GABA concentrations. While high lactate and low GABA correlated with tumor contrast-enhancing volume, they correlated more significantly with lower MMSE scores than tumor volumes.

Conclusions

We provide evidence that lactate production and Warburg metabolism may impact neurotransmitter dysregulation and neurocognition in CNS lymphomas. We identify novel metabolomic biomarkers that may be applied in future studies of neurocognition in CNS lymphomas. Elucidation of mechanistic interactions between lymphoma metabolism, neurotransmitter imbalance, and neurocognition may promote interventions that preserve cognitive function.