bluuebunny/crossref_metadata_2025 huggingface dataset:
Corrosion Resistant Superhydrophobic Aluminum Alloy: A Review
Authors: Panda Bijayani
Published: January 2021

Aluminum alloys are widely used in aerospace and space applications due to their high strength to weight ratio. The most prevalent method to prevent corrosion of aluminum alloys is anodic oxidation or anodization treatment. The anodized layer is porous and hence there are chances of penetration of moisture and corrosion of underlying substrate underneath the anodized layer. Surface modification of the aluminum alloy by superhydrophobic coating is a very attractive method to improve the corrosion resistance of aluminum alloys. The inspiration for the fabrication of superhydrophobic coatings is obtained from various examples in nature such as strider’s legs and lotus leaf. The fabrication of superhydrophobic coatings involves two important steps; generation of a rough surface and deposition of low surface energy material. The present paper reviews the various researches undertaken for the production of superhydrophobic surfaces on aluminum and aluminum alloys. Finally, the scope of future research activities in the fabrication of superhydrophobic coatings has been discussed in the paper.
Schematic review of plasma arc oxidation process for Mg Alloy Bio Implants
Authors: Jadhav Priya , Bongale Arunkumar , Kumar Satish
Published: January 2021

The biomaterials are having diverse applications in temporary implants. The implant performance and compatibility inside the human body element are enormous factors of research. The implant material requires excellent mechanical properties that can endure corrosion, higher stress, load-bearing capacity. The compatibility with local tissues of the human body is a crucial point of tolerance. This article is based on a review of papers in the area of Magnesium alloy bioimplants. The purpose of the review is to understand different methods and recent developments for Mg alloy material in the domain. Different methods for producing coatings and the effect of the addition of nanoparticles are discussed.
An Insight: Machining of Titanium Alloys & Associated Tool Wear
Authors: Sisodiya Mangal Singh , Bajpai Vivek
Published: January 2021

Titanium alloy has some important applications in the aerospace industries along with other sectors, but its machinability efficiently is still a topic of intent research. Several factors work together to hinder its effective machining by various cutting tools. Although work has been done to some extent by some well cutting tools such as carbide tools however, very little work has been stated and established by using CBN tools or cryogenically treated CBN tools. The review has been done elaboratively to bring out various aspects of titanium alloy and its machining by various conventional cutting tools along with the CBN cutting tool.
Influence of deposition parameters on Tribological Performance of HVOF Coating: A review
Authors: Vats Alok , Kumar Arun , Patnaik Amar , Meena M L
Published: January 2021

Any mechanical component stationary or in relative motion is exposed to severe surface phenomena like corrosion, wear, abrasion etc. To address these issues various surface treatment processes are in industrial practice. In recent times, coatings techniques have been identified as cost effective alternative to other surface modification techniques. Thermal spray technique proves to be the prominent method to among a large variety of processes available. HVOF method owing to its capability to provide wear and corrosion resistant coatings with characteristics like high hardness, adhesion, density (porosity <1%) is widely accepted across industries. Process parameters seems to have significant influence on coating properties like porosity level, oxide content, micro hardness and tribological performance of coating. This paper intends to investigate the effect of above mentioned process deposition parameters on physical, mechanical, wear, erosion and corrosion properties of coating.
Development of an Internet of Things (IoT) based Lockout/Tagout (LOTO) device for Accident Prevention in Manufacturing Industries
Authors: Kumar S , Tauseef S M
Published: January 2021

Despite all the technological advances, safety remains the biggest challenge in Industries. Each year, thousands of electrocutions and hundreds of machinery-related accidental deaths are happening. A number of these accidents involve inadequate, unauthorised or improper use of hazardous energy control procedures, also known as lockout/tagout (LOTO) procedures. Although the organizations like Occupational Safety and Health Administration (OSHA), USA, The National Institute for Occupational Safety and Health (NIOSH) and others have defined a very detailed LOTO procedure, however, these LOTO procedures have many manual activities. With the emergence of IoT (Internet of Things) these manual activities can be combined with automated activities thereby enhancing safety. IoT based devices can be implemented to ensure authorized access to hazardous areas around operating machinery, improve documentation and monitoring of service during repair and/or maintenance that requires shutdown of the machinery, and prevent unexpected, unauthorised start up, or movement during maintenance of machinery or related activities. Acknowledging the importance of IoT enabled safety devices NIOSH is also exploring the possibility of implementing IoT based technologies to provide intelligent machine monitoring as part of a comprehensive LOTO program. This paper presents the development of an IoT based LOTO device, its implementation and effectiveness in improving safety and accident prevention. It is found that the IoT based LOTO device is effective in accident prevention (from 47 to 0 incidents) and its performance (from 697 to 349 Seconds) is reliable.
Fracture analysis of edge cracked FGM plate under compressive load along crack
Authors: Mishra Kundan , Lal Achchhe , Sutaria B. M.
Published: January 2021

Fracture analysis of FGM plate with edge crack under compressive point load along crack is carried out by using extended finite element method (XFEM). In this present work a FGM plate where material properties vary along width with edge crack is considered for the study. The mathematical formulation is carried out in MATLAB and the stress distribution and mixed mode stress intensity factors (SIFs) are obtained for different position of point load. The validation study is carried out for developed MATLAB code with previously published research paper and then fracture analysis of FGM plate with crack under compressive point load along crack is investigated. The present study is carried out to understand the fracture resistance of edge crack FGM plate when the action of load is along crack.
Numerical study of heat transfer enhancement through a circular tube fitted with and without rectangular cut twisted tape insert
Authors: Hakim M U , Hridoy M W , Islam M I , Rayhan M S
Published: January 2021

Numerical simulations have been carried out to investigate the heat transfer enhancement in a tube fitted with a rectangular cut twisted tape insert and compare the data with a smooth tube. For this purpose, CFD (Computational Fluid Dynamics) was utilized to simulate the three-dimensional model with appropriate boundary conditions. The numerical results show that the flow field can be adjusted and the thickness of boundary layer can be decreased by inserting the rectangular cut twisted tape insert so that the heat transfer can be enhanced in the tube. Water was used as the working fluid. The results obtained show an increase in Nusselt number as a result of increasing heat transfer rate for the tube provided with rectangular cut twisted tapes than the plain tube. The pressure drop across the tube wall for twisted tape with the rectangular cut is higher than the plain tube. This increase in the rate of heat transfer is due to the introduction of secondary swirl flow (due to twisted tape) along with the primary flow.
An Experimental Study on Machining of AISI H - 13 Steel Using Dimple-Textured and Non-Textured Tungsten Carbide Cutting Tools
Authors: Vignesh G. , Barik Debabrata , Aravind S. , Ragupathi P. , Arun M.
Published: January 2021

Fabrication of micro-dimples at the rack surface closer to the cutting region of the tungsten carbide tool will induce the tribological modifications at the tribo-contact surfaces. The motive of this work is to find the influence of micro-dimples fabricated on the cutting tools during turning operations. Linear arrays of dimple-textures with various geometrical aspects (dimple diameter and depth) and area density ratio were prepared using laser marking technique. The influence of surface-texture pattern is experimentally analysed through dry machining of AISI H – 13 steel using a dimple-textured tungsten carbide cutting tool. The responses of cutting temperature and cutting force generated during the turning operation were analysed. It shows improvement in machinability in terms of wear rate reduction in dimple-textured tools. Optimizing the dimension of micro-dimples (diameter of 90µm, depth of 60µm) results in a 10% reduction in tool wear rate.
Dissimilar Metal Welds used in AUSC Power Plant, Fabrication and Structural Integrity Issues
Authors: Singh Sanjay , Singh Alok Bihari , Kumar Manoj , Meena M L , Dangayach G S
Published: January 2021

In the current era, the Advanced Ultra Super-Critical (AUSC) plants have been used to substantially increased efficiency with environmental protection. AUSC components boiler header, re-heater and super-heater tube etc. are fabricated by using advanced materials to join by the welding process. Any failure of the power plant can lead to grave consequences, not only of substantial financial losses but additionally immensely treasured and irreparable human life loss. In this review, the dissimilar metal welds (DMWs) have many issues such as metallurgical issue, cracking, carbon migration, welding electrode selection, creep properties, suitable welding process and structure integrity issues which enhanced the failure of weldments. The results of our review showed that DMWs of AUSC power plant are joined by activated flux Tungsten Inert Gas (A-TIG) and Pulse A-TIG process to increase the productivity and cut the significant fraction of cost. However, A-TIG process with Post Weld Heat Treatment (PWHT) improved the mechanical properties and high-temperature creep resistance properties of DMWs. This state of the art is encouraged the researchers about the enormous future scope.
Optimization of FGM Composition for Better Environment Material
Authors: Gautam Mrinal , Chaturvedi Manish
Published: January 2021

In functionally graded heat-resisting material, the volume fraction of constituents varies functionally and continuously, and these are examined for high temperature engineering applications. By the spatial distribution of the volume fraction the thermal behaviour of FGMs is strongly influenced. Thus, the determination of volume fraction distribution becomes a critical part in the FGM design for a given loading condition and specification. In present work, averaging estimation approach viz, modified rule of mixture is considered. The present work is concerned with the Optimization of FGM Composition for better environment material. The investigation is carried out for uniform heating condition through the plate thickness. Classical laminate theory is used to determine residual stress. The code is developed on MATLAB for constrained minimization and the MATLAB function ‘fmincon’ is employed. The comparative study of three different thermal loading is presented. The effectiveness of residual stress minimization is explored for various boundary conditions.
Study & Analysis of Tire Wear Characteristics of TATA LPO 1618
Authors: Gohane Gaurav , Indurkar Anmol , Chimurkar Palash , Patle Sandip , Nagina Suraj Kumar , Tirpude Swapnil , Bawane Ujwal
Published: January 2021

The tires are a key sub-system of vehicles that have a big responsibility in comfort, fuel consumption and traffic safety. As we know that current tires are just passive rubber elements which do not contribute actively to improve the driving experience or the vehicle safety. During the driving of vehicle, we get few and unsatisfied information from tires. Therefore, this is the main reason to develop an intelligent tire, which could provide useful information to other systems and become an active safety system. In the Tata (LPO 1618) Vehicle an experimental tire strain-based system is used to measure tire tread deformation by means of various aids. Tests under different working conditions such as vertical load or slip angle considering a certain camber angle have been carried out using an indoor tire test (Slightly). By this project and research work, we are trying to introduce an automated tire monitoring and inflation system, which can ensure adequate tire pressure to better accommodate handling requirements. In this paper the numerical method for introducing the prediction tire where account has been introduced to reduce break down time.
Increase productivity of vertical roller mill using seven QC tools
Authors: Pareek Praveen , Sankhla Dr. Vijayendra Singh
Published: January 2021

Cement sector in india is enjoyign success and capacity enhancement due to the rapidly growing demand in various sectors but at the same time a threat is approaching to cement industry that its input cost is increasing day by day like power cost, fuel cost, raw material cost. Also cement is a highly energy consuming industry. Hence in order to survive and sustain in the market its profitability need to be enhanced by increasing productivity and reducing power consumption. High productivity and low power costs can be achieved by increasing output, lowering breakdowns and optimizing the grinding process which eats almost 60% of power cost. In recent years vertical roller mill (VRM) has proved to be a popular choice for finished cement grinding due to low power consumption but it is also very sensitive to vibrations and can deteriorate productivity if process optimization is varied slightly. Objective of this research paper is process optimization of Vertical roller mill, improvement in productivity and reduction in vibration breakdowns using seven QC tools. The research explains complete process of identifying possible causes and final root causes, finding possible solutions and implementing them in order to increase the output of vertical roller mill. This study can benefit the organizations using VRM and are not able to utilize its full productivity due to some bottlenecks or constraints.
Computational Study of Small Vanadium and Chromium Oxide Clusters: Effect of Hydrogenation
Authors: Chahal Ankur , Abbas Haider
Published: January 2021

In the present work we report the effect of hydrogenation on small vanadium oxide (V2O4, V2O6and V4O10) and chromium oxide (Cr2O4, Cr2O6andCr4O10) clusters, within the framework of density functional theory. Comparison between dehydrogenated and hydrogenated cluster suggests that hydrogenation of these clusters changes the HOMO-LUMO position and their gap. A considerable enhancement in dipole moment is also observed. It is found that hydrogenation enhances the occupancy of the metal in these clusters and therefore, the metallicity increases. The observed mechanism of charge transfer due to hydrogenation is in good agreement with the reported experimental and theoretical results.
Study the reduction of mill scale with lean grade coal through RI-RDI
Authors: Shekhawat Deepika , Kukshal Vikas , Banerjee M K , Patnaik Amar
Published: January 2021

In the present study, efforts have been made to assess and study the reduction of mill scale in the presence of single gaseous reductant (i.e. CO gas) in RI-RDI (reducibility index (RI) and reduction degradation index) equipment. While conducting this study optimal process parameters like reduction temperature, mill scale size, reduction time and mill scale to coal ratio were analysed. An exceptional experimental profile is maintained inside the furnace to attain the optimum metallization. The mill scales are reduced inside the furnace and the extent of reduction is evaluated from the weight loss. Post conducting reduction in the RI-RDI test apparatus, the reduced mill scale is characterized for the microstructural and morphological studies using SEM, EDS, XRD. The most optimum results of the reduction were attained in RI-RDI apparatus giving iron content of (metallization) 89.15 % at the reduction temperature of 1050°C for 240 mins holding time. During the entire study on RI-RDI apparatus, flow rate of CO is maintained at 4.5 LPM (litres per minute) and N2at 10.5 LPM. Finally, the degree of metallisation in the sample as well as the product material is calculated by using the chemical analysis process (dichromate and ferric chloride method). The characterization of produced iron powder was done by chemical analysis, XRD, and FE-SEM. The FE-SEM results confirm the presence of resultant pore characteristics. It is observed that mill scale can be significantly reduced to metallic iron by utilizing lean grade coal.
A Short Review on Polymer, Metal and Ceramic Based Implant Materials
Authors: Shekhawat Deepika , Singh Amit , Bhardwaj Ashray , Patnaik Amar
Published: January 2021

The present work focuses on the evaluation of polymer, metal and ceramic based biomaterials with particular emphasis on success rate of these materials till date along with the merits and demerits of these material system. Currently, the search for the materials with improved performance is on rise for biomedical (mainly total hip replacement, THR) applications owing to increase in the number of orthopedic patients worldwide. The clinicians utilized polymer and metal-based implants in ancient times to heal and treat the bone imperfections as well as fractures. The next generation materials required an update on properties, cell material interactions, repair and regeneration, that can only be acquired from recent knowledge related to materials. The commonly employed polymers (natural based polymers, proteins or polysaccharides; and synthetic polymers, poly (lactic acid), poly (glycolic acid), poly (ε-caprolactone), poly(3-hydroxybutyrate) (PHB)) and metals (SS, Mg-alloy, Ti-alloys, Co-alloy, silver, and nickel-titanium alloys) failed to fulfill the long-term durability and lacked in generating adequate bonding with the bones. It is intended that the facts and details abridged in this review article ought to be a beneficial tool in the development of progressively eminent implant materials like ceramic based materials against premature failure, cyclic stress generation, wear, corrosion fatigue, implant loosening and ultimate fracture.
1-D/2-D/3-D Hopfield Associative Memories
Authors: Garimella Rama Murthy , Singh Aman , Jyothi Prasanna GC , Jagannadan Manasa , Vankam Vidya Sree , Bairaju Maha Lakshmi
Published: January 2021

In this research paper storage as well as retrieval of 1-D/2-D/3-D information using Hopfield type Associative Memories (AMs) is discussed. Various Artificial Neural Networks(ANN) architectures are proposed. Also, implementational issues associated with those Associative Memories are discussed. Cascade connection of AM and Convolutional Neural Network is proposed for noise immunity.
Prediction of Learner’s Performance in Adaptive E-Learning System using Learning Analytics
Authors: Sweta Soni , Mahato Shalini , Pathak Laxmi Kumari
Published: January 2021

The main objective of Learning Analytics is to collect, interpret and investigate the information for setting proper co-relation to improve the students’ learning experiences. As the popularity and demand of learning analytics are on rise, higher education is continuously moving from offline to online E-Learning Educational System. It has been further promoted on account of COVID-19. Learning pedagogies, evaluation measures and feedback measures have also been changed accordingly. The aim of this paper is to discuss the efficacy of learning analytics in online educational system using e-learning platform. R programming language with GGPLOT2 is used as Visualization tool to focus on gain insights of adaptation of learning analytics. The results show the better computational performance in terms of predicting students to improve their learning achievements and mitigating risk of failures.
Bernoulli Vacation Scheduling (BVS) Model for Energy efficient intrusion detection in WSN
Authors: Kalnoor Gauri , GowriShankar S
Published: January 2021

Cutting-edge wireless sensor networks, security is the most important challenge that has to be considered. Most of the applications of WSN are vulnerable to attacks, as they are deployed in any kind of environment. So, the intrusion detection system is the second line of defense for WSN. The intruder should be detected in WSN more efficiently. We introduce the Bernoulli scheduling rule such that several trials are performed to get the detection of an intruder to be successful once. Since the sensor nodes are always active for detecting an intruder, the energy consumption becomes high. To reduce the consumption of energy, sleep/wakeup, also called small interval vacations are used for the sensors which are almost considered to be like the mechanism of fluid queues. In our proposed work, the vacations are introduced so that the energy used is minimized whenever the sensor is not required to be active. Thus, in our proposed work, since WSN is vulnerable to many harmful attacks, the Bernoulli scheduling rule is applied and the sensor nodes have a vacation state whenever the sensor need not be active, to save the energy consumed. The probability of detecting an intruder is calculated and performance is compared. We have applied a fluid queuing model for the vacations of small intervals in the sensor nodes to minimize the energy consumption and the obtained result is compared with the energy consumed when the vacations are not applied. Thus, the results are simulated for both energy consumed and the number of success rates of detection of an intruder, most importantly the comparison is analyzed with the past work of wsn.
Optimizing process of Healthcare Assistance at Road Side using Particle Swarm optimization and Person Accident Behaviour
Authors: Khan Amreen , Raghuwanshi M.M. , Borkar Prashant
Published: January 2021

In the worldwide road accidents are very common and happened throughout the day. It is not restricted to time, density of population, geographical location, tropical geography, etc. Due to rapid increase in population and many other factors like driving and safety rules, driving pattern, etc., the worldwide rate of roadside accidents are also increasing. The African countries is having highest road accident inhabitants along with highest number of fatalities, whereas the Asian countries are the second rank in the world incurred rate of accidents with more fatalities during the road accidents. Hence, In order to handle these road accidents the major concern is to provide quick and fast emergency and health-care services like deployment of quick response team(QrT), first-aid, immediate hospitalization, and various assistance services that helps in reducing the fatalities during the road accidents. Now there is a need to develop effective and less parameterized approach which will helps in reducing the road accidents and provide quick response assistance to the needy. In order to develop the effective and comprehensive solution to the above mentioned problem, optimization is the key ingredient, which results in the evolvement of one of the most popular and effective algorithm called particle swarm optimization. In this paper we are going to evaluate, analyse and simulate particle swarm optimization (PSO) algorithm in order to design and develop novel solution to the above mentioned problem based on accident pattern and the behaviour of a person who met with the road accident.
Sentiment analysis on micro-blog data using machine learning techniques - A Review
Authors: Kalaivani M S , Jayalakshmi S
Published: January 2021

The user generated content in social networks, websites, ratings and reviews about product, people, places have become very beneficial for various fields to improve its growth. Sentiment analysis, which studies user generated content and find the correct sentiment polarity. Data collection, feature extraction, sentiment classification and decision making are the steps involved in this process. Machine Learning and Deep learning Methods are used to predict the sentiments. Large Input dataset from websites or microblog is taken as input and processed. There are some challenges in identifying accurate decisions. This Review Paper focus on recent studies about learning models such as Support vector Machines, Maximum Entropy, deep learning models and various methods which are used in solving sentiment classification, product review analysis, Text Processing and visual analysis etc.
RETRACTED: Medicine Distribution Robot and Human Less Intervention for Covid-19 Affected People (AKM MED ASSISTIVE BOT)
Authors: Murugan Kalpana , Ali Khan Md Arbas , Kylash MR , Muralidharan M
Published: January 2021

Social robots and administration robots with social insights are beginning to coordinate into our regular day to day activities. Managing health care needs of the patients collaborate with person-centered healthcare. Untimed medications to patients can cause serious health issues for the patients in hospitals and in old age nursing homes. The proposed work is intended to assist these patients with providing or recommending the necessary medication in the correct order at the specific times of the day without the actual need of a human nurse. This is incredibly tricky for the old patient who have issues in monitoring their medication at regular intervals. Thus, to avoid this, we have developed this medication robot. Which is a semi-autonomous microcontroller based programmable robot that works on the ‘line following robot’ concept, which can remind the patients, to consume their pills at regular intervals in a day. After successful intake of pills, the status of the medication is consequently sent to the patient’s relative through an SMS.
Rapid microwave-assisted biosynthesis of chitooligosaccharide coated silver nanoparticles: assessments of antimicrobial activity for paediatric pulp therapy
Authors: Rajasekaran Subhathira , Rao Sneha S , Dalavi Pandurang Appana , Prabhu Ashwini , Anil Sukumaran , Venkatesan Jayachandran , Bhat Sham S
Published: January 2021

Silver nanoparticles (AgNPs) have gained much attention in the treatment of dental caries due to their excellent antimicrobial activities. In this study, we have biosynthesised chitooligosaccharide coated silver nanoparticles (COS-AgNPs) using a rapid microwave-assisted method. The physical and chemical characterisations of biosynthesised COS-AgNPs were investigated using UV–visible spectroscopy (UV–vis), dynamic light scattering (DLS), Fourier transform infrared spectroscopy (FTIR), X-Ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM) and transmission electron microscopy (TEM) equipped with selected area electron diffraction (SAED). Further, the developed COS-AgNPs were assessed for antimicrobial activity on Streptococcus mutans. From the DLS analysis, the average particle size of the COS-AgNPs was found to be ∼32 nm. The morphologies of the COS-AgNPs were monodisperse and spherical in shape. XRD peaks are coherent with the standard peaks of AgNPs. Antimicrobial activity of COS-AgNPs showed a significant zone of inhibition due to the synergistic effect of COS-AgNPs. Furthermore, the antibacterial potential of developed COS-AgNPs-Ca(OH)2 paste was checked against Streptococcus mutans, Staphylococcus aureus, and Enterococcus faecalis. COS-AgNPs based composite paste showed better inhibition zone against the tested microbes. Hence, COS-AgNPs and COS-AgNPs-Ca(OH)2 based paste materials will be promising biomaterials for pulp therapy in paediatric dentistry.
Fibre-coupled, multiplexed methane detection using range-resolved interferometry
Authors: Bremner J A A , Kissinger T , Hodgkinson J , Tatam R P
Published: January 2021

We describe the first use of range-resolved interferometric signal processing for measurement of spectral transmission. This was applied to gas sensing using tunable diode laser spectroscopy, allowing the simultaneous and independent measurement of methane concentrations in multiple gas cells. The system uses a single injection-current modulated diode laser and a single photodetector. For three gas cells, we show the ability of the system to measure methane at noise equivalent concentrations of less than 200 ppm for a 0.5 s measurement period and a potential noise equivalent concentration (1σ) of <20 ppm with 150 s averaging time. We further show that cross-talk between cells is below the experimental uncertainty for the system.
Defect inspection technologies for additive manufacturing
Authors: Chen Yao , Peng Xing , Kong Lingbao , Dong Guangxi , Remani Afaf , Leach Richard
Published: January 2021

Additive manufacturing (AM) technology is considered one of the most promising manufacturing technologies in the aerospace and defense industries. However, AM components are known to have various internal defects, such as powder agglomeration, balling, porosity, internal cracks and thermal/internal stress, which can significantly affect the quality, mechanical properties and safety of final parts. Therefore, defect inspection methods are important for reducing manufactured defects and improving the surface quality and mechanical properties of AM components. This paper describes defect inspection technologies and their applications in AM processes. The architecture of defects in AM processes is reviewed. Traditional defect detection technology and the surface defect detection methods based on deep learning are summarized, and future aspects are suggested.
Transverse vibration of tapered nanobeam with elastic supports
Authors: Hossain Mainul , Lellep Jaan
Published: January 2021

A tapered nanobeam is modelled by Euler–Bernoulli beam theory and nonlocal theory of elasticity. A solution technique based on homotopy perturbation method is proposed to analyse the dynamic behavior of the tapered nanobeam. Beam becomes tapered along the width exponentially. The effects of flexible and rigid supports on the vibration of tapered nanobeam are analysed. Influences of tapered ratio and nonlocal parameter on the shape mode of deflection are also scrutinized. Homotopy perturbation method shows its effectiveness in this analysis. The results reveal that the effects of nonlocal parameter and tapered ratio are significant for the dynamic behavior of tapered nanobeam.
Kissing number in non-Euclidean spaces of constant sectional curvature
Authors: Dostert Maria , Kolpakov Alexander
Published: January 2021

This paper provides upper and lower bounds on the kissing number of congruent radius

r
>
0

r > 0

spheres in hyperbolic

H

n

\mathbb {H}^n

and spherical

S

n

\mathbb {S}^n

spaces, for

n
≥
2

n\geq 2

. For that purpose, the kissing number is replaced by the kissing function

κ
H

(
n
,
r
)

\kappa _H(n, r)

, resp.

κ
S

(
n
,
r
)

\kappa _S(n, r)

, which depends on the dimension

n
n

and the radius

r
r

.

After we obtain some theoretical upper and lower bounds for

κ
H

(
n
,
r
)

\kappa _H(n, r)

, we study their asymptotic behaviour and show, in particular, that
<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="kappa Subscript upper H Baseline left-parenthesis n comma r right-parenthesis tilde left-parenthesis n minus 1 right-parenthesis dot d Subscript n minus 1 Baseline dot upper B left-parenthesis StartFraction n minus 1 Over 2 EndFraction comma one half right-parenthesis dot e Superscript left-parenthesis n minus 1 right-parenthesis r">

κ
H

(
n
,
r
)
∼
(
n
−
1
)
⋅

d

n
−
1

⋅
B
(

n
−
1

2

,

1
2

)
⋅

e

(
n
−
1
)
r

\kappa _H(n,r) \sim (n-1) \cdot d_{n-1} \cdot B(\frac {n-1}{2}, \frac {1}{2}) \cdot e^{(n-1) r}

, where

d
n

d_n

is the sphere packing density in

R

n

\mathbb {R}^n

, and

B
B

is the beta-function. Then we produce numeric upper bounds by solving a suitable semidefinite program, as well as lower bounds coming from concrete spherical codes. A similar approach allows us to locate the values of

κ
S

(
n
,
r
)

\kappa _S(n, r)

, for

n
=
3
,

4

n= 3,\, 4

, over subintervals in

[
0
,
π
]

[0, \pi ]

with relatively high accuracy.
Joint Associations of Multiple Dietary Components With Cardiovascular Disease Risk: A Machine-Learning Approach
Authors: Zhao Yi , Naumova Elena N , Bobb Jennifer F , Claus Henn Birgit , Singh Gitanjali M
Published: January 2021

The human diet consists of a complex mixture of components. To realistically assess dietary impacts on health, new statistical tools that can better address nonlinear, collinear, and interactive relationships are necessary. Using data from 1,928 healthy participants in the Coronary Artery Risk Development in Young Adults (CARDIA) cohort (1985–2006), we explored the association between 12 dietary factors and 10-year predicted risk of atherosclerotic cardiovascular disease (ASCVD) using an innovative approach, Bayesian kernel machine regression (BKMR). Employing BKMR, we found that among women, unprocessed red meat was most strongly related to the outcome: An interquartile range increase in unprocessed red meat consumption was associated with a 0.07-unit (95% credible interval: 0.01, 0.13) increase in ASCVD risk when intakes of other dietary components were fixed at their median values (similar results were obtained when other components were fixed at their 25th and 75th percentile values). Among men, fruits had the strongest association: An interquartile range increase in fruit consumption was associated with −0.09-unit (95% credible interval (CrI): −0.16, −0.02), −0.10-unit (95% CrI: −0.16, −0.03), and −0.11-unit (95% CrI: −0.18, −0.04) lower ASCVD risk when other dietary components were fixed at their 25th, 50th (median), and 75th percentile values, respectively. Using BKMR to explore the complex structure of the total diet, we found distinct sex-specific diet-ASCVD relationships and synergistic interaction between whole grain and fruit consumption.
Characterizing the Chemical Profile of Incidental Ultrafine Particles for Toxicity Assessment Using an Aerosol Concentrator
Authors: Viana M , Salmatonidis A , Bezantakos S , Ribalta C , Moreno N , Córdoba P , Cassee F R , Boere J , Fraga S , Teixeira J P , Bessa M J , Monfort E
Published: January 2021

Incidental ultrafine particles (UFPs) constitute a key pollutant in industrial workplaces. However, characterizing their chemical properties for exposure and toxicity assessments still remains a challenge. In this work, the performance of an aerosol concentrator (Versatile Aerosol Concentration Enrichment System, VACES) was assessed to simultaneously sample UFPs on filter substrates (for chemical analysis) and as liquid suspensions (for toxicity assessment), in a high UFP concentration scenario. An industrial case study was selected where metal-containing UFPs were emitted during thermal spraying of ceramic coatings. Results evidenced the comparability of the VACES system with online monitors in terms of UFP particle mass (for concentrations up to 95 µg UFP/m3) and between filters and liquid suspensions, in terms of particle composition (for concentrations up to 1000 µg/m3). This supports the applicability of this tool for UFP collection in view of chemical and toxicological characterization for incidental UFPs. In the industrial setting evaluated, results showed that the spraying temperature was a driver of fractionation of metals between UF (<0.2 µm) and fine (0.2–2.5 µm) particles. Potentially health hazardous metals (Ni, Cr) were enriched in UFPs and depleted in the fine particle fraction. Metals vaporized at high temperatures and concentrated in the UF fraction through nucleation processes. Results evidenced the need to understand incidental particle formation mechanisms due to their direct implications on particle composition and, thus, exposure. It is advisable that personal exposure and subsequent risk assessments in occupational settings should include dedicated metrics to monitor UFPs (especially, incidental).
Intraspecific trait variation in plants: a renewed focus on its role in ecological processes
Authors: Westerband A C , Funk J L , Barton K E
Published: January 2021

Background

Investigating the causes and consequences of intraspecific trait variation (ITV) in plants is not novel, as it has long been recognized that such variation shapes biotic and abiotic interactions. While evolutionary and population biology have extensively investigated ITV, only in the last 10 years has interest in ITV surged within community and comparative ecology.

Scope

Despite this recent interest, still lacking are thorough descriptions of ITV’s extent, the spatial and temporal structure of ITV, and stronger connections between ITV and community and ecosystem properties. Our primary aim in this review is to synthesize the recent literature and ask: (1) How extensive is intraspecific variation in traits across scales, and what underlying mechanisms drive this variation? (2) How does this variation impact higher-order ecological processes (e.g. population dynamics, community assembly, invasion, ecosystem productivity)? (3) What are the consequences of ignoring ITV and how can these be mitigated? and (4) What are the most pressing research questions, and how can current practices be modified to suit our research needs? Our secondary aim is to target diverse and underrepresented traits and plant organs, including anatomy, wood, roots, hydraulics, reproduction and secondary chemistry. In addressing these aims, we showcase papers from the Special Issue.

Conclusions

Plant ITV plays a key role in determining individual and population performance, species interactions, community structure and assembly, and ecosystem properties. Its extent varies widely across species, traits and environments, and it remains difficult to develop a predictive model for ITV that is broadly applicable. Systematically characterizing the sources (e.g. ontogeny, population differences) of ITV will be a vital step forward towards identifying generalities and the underlying mechanisms that shape ITV. While the use of species means to link traits to higher-order processes may be appropriate in many cases, such approaches can obscure potentially meaningful variation. We urge the reporting of individual replicates and population means in online data repositories, a greater consideration of the mechanisms that enhance and constrain ITV’s extent, and studies that span sub-disciplines.
Laser and Light-Based Device Education in a Plastic Surgery Residency Program: A Continuing Medical Education Overview
Authors: Wamsley Christine E , Hoopman John , Kenkel Jeffrey M
Published: January 2021

The increasing prevalence of laser use, particularly in plastic surgery, demands education of both practitioners and trainees to ensure efficacy and patient safety. The purpose of this continuing medical education module is to provide the learner with a detailed outline for laser training education for plastic surgery trainees. In this overview, a discussion of the characteristics of light, an introduction to fundamental laser principles, a comparison of lasers and pulsed light systems, and examples of several therapeutic applications for light-based devices in the clinical setting will be presented. Additionally, the 5 parameters necessary for operation of light-based devices, as well as the importance of laser safety education, will be reviewed. We hope this continuing medical education will provide both practicing plastic surgeons and trainees with the proper education on the lasers and pulsed light devices they will use in their clinical practices.
Generating property-matched decoy molecules using deep learning
Authors: Imrie Fergus , Bradley Anthony R , Deane Charlotte M
Published: January 2021

Motivation

An essential step in the development of virtual screening methods is the use of established sets of actives and decoys for benchmarking and training. However, the decoy molecules in commonly used sets are biased meaning that methods often exploit these biases to separate actives and decoys, and do not necessarily learn to perform molecular recognition. This fundamental issue prevents generalization and hinders virtual screening method development.

Results

We have developed a deep learning method (DeepCoy) that generates decoys to a user’s preferred specification in order to remove such biases or construct sets with a defined bias. We validated DeepCoy using two established benchmarks, DUD-E and DEKOIS 2.0. For all 102 DUD-E targets and 80 of the 81 DEKOIS 2.0 targets, our generated decoy molecules more closely matched the active molecules’ physicochemical properties while introducing no discernible additional risk of false negatives. The DeepCoy decoys improved the Deviation from Optimal Embedding (DOE) score by an average of 81% and 66%, respectively, decreasing from 0.166 to 0.032 for DUD-E and from 0.109 to 0.038 for DEKOIS 2.0. Further, the generated decoys are harder to distinguish than the original decoy molecules via docking with Autodock Vina, with virtual screening performance falling from an AUC ROC of 0.70 to 0.63.

Availability and implementation

The code is available at https://github.com/oxpig/DeepCoy. Generated molecules can be downloaded from http://opig.stats.ox.ac.uk/resources.

Supplementary information

Supplementary data are available at Bioinformatics online.
Comment on: Phase I/II study of adding intraperitoneal paclitaxel in patients with pancreatic cancer and peritoneal metastasis
Authors: Rau Kun-Ming , Chang Chao-Sung , Pei Sung-Nan , Hsieh Meng-Che , Tsai Yu-Fen , Chiu Chong-Chi
Published: January 2021

Our submission is the Correspondence to the text with the title of “Phase I/II study of adding intraperitoneal paclitaxel in patients with pancreatic cancer and peritoneal metastasis”. It was published in Br J Surg 2020; 107: 1811–1817.
Coronavirus Disease 2019 Symptoms and Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Positivity in a Large Survey of First Responders and Healthcare Personnel, May–July 2020
Authors: Akinbami Lara J , Petersen Lyle R , Sami Samira , Vuong Nga , Lukacs Susan L , Mackey Lisa , Atas Jenny , LaFleur Bonnie J
Published: January 2021

A severe acute respiratory syndrome coronavirus 2 serosurvey among first responder/healthcare personnel showed that loss of taste/smell was most predictive of seropositivity; percent seropositivity increased with number of coronavirus disease 2019 symptoms. However, 22.9% with 9 symptoms were seronegative, and 8.3% with no symptoms were seropositive. These findings demonstrate limitations of symptom-based surveillance and importance of testing.
Immunodeficiency and Cancer in 3.5 Million People Living With Human Immunodeficiency Virus (HIV): The South African HIV Cancer Match Study
Authors: Ruffieux Yann , Muchengeti Mazvita , Egger Matthias , Efthimiou Orestis , Bartels Lina , Olago Victor , Davidović Maša , Dhokotera Tafadzwa , Bohlius Julia , Singh Elvira , Rohner Eliane
Published: January 2021

Background

We analyzed associations between immunodeficiency and cancer incidence in a nationwide cohort of people living with human immunodeficiency virus (HIV; PLWH) in South Africa.

Methods

We used data from the South African HIV Cancer Match Study built on HIV-related laboratory measurements from the National Health Laboratory Services and cancer records from the National Cancer Registry. We evaluated associations between time-updated CD4 cell count and cancer incidence rates using Cox proportional hazards models. We reported adjusted hazard ratios (aHRs) over a grid of CD4 values and estimated the aHR per 100 CD4 cells/µL decrease.

Results

Of 3 532 266 PLWH, 15 078 developed cancer. The most common cancers were cervical cancer (4150 cases), Kaposi sarcoma (2262 cases), and non-Hodgkin lymphoma (1060 cases). The association between lower CD4 cell count and higher cancer incidence rates was strongest for conjunctival cancer (aHR per 100 CD4 cells/µL decrease: 1.46; 95% confidence interval [CI], 1.38–1.54), Kaposi sarcoma (aHR, 1.23; 95% CI, 1.20–1.26), and non-Hodgkin lymphoma (aHR, 1.18; 95% CI, 1.14–1.22). Among infection-unrelated cancers, lower CD4 cell counts were associated with higher incidence rates of esophageal cancer (aHR, 1.06; 95% CI, 1.00–1.11) but not breast, lung, or prostate cancer.

Conclusions

Lower CD4 cell counts were associated with an increased risk of developing various infection-related cancers among PLWH. Reducing HIV-induced immunodeficiency may be a potent cancer-prevention strategy among PLWH in sub-Saharan Africa, a region heavily burdened by cancers attributable to infections.
Exercise training in patients after kidney transplantation
Authors: De Smet Stefan , Van Craenenbroeck Amaryllis H.
Published: January 2021

Kidney transplantation is the treatment of choice for patients with end-stage renal disease. Next to the risk of allograft failure, major obstacles for disease-free survival after kidney transplantation include a higher incidence of cancer, infection and cardiovascular events. Risk factors for adverse clinical outcomes include pre-existent comorbidities, the introduction of an immunodeficient status and (lack of) lifestyle changes after transplantation. Indeed, physical inactivity and poor physical fitness are important targets to address in order to improve clinical outcomes after kidney transplantation. This review summarizes the current evidence on exercise training after kidney transplantation, derived from randomized controlled trials. As much as possible, results are discussed in the perspective of the Standardized Outcomes in Nephrology-Transplantation core outcomes, which were recently described as critically important outcome domains for trials in kidney transplant recipients.
bc-GenExMiner 4.5: new mining module computes breast cancer differential gene expression analyses
Authors: Jézéquel Pascal , Gouraud Wilfried , Ben Azzouz Fadoua , Guérin-Charbonnel Catherine , Juin Philippe P , Lasla Hamza , Campone Mario
Published: January 2021

‘Breast cancer gene-expression miner’ (bc-GenExMiner) is a breast cancer–associated web portal (http://bcgenex.ico.unicancer.fr). Here, we describe the development of a new statistical mining module, which permits several differential gene expression analyses, i.e. ‘Expression’ module. Sixty-two breast cancer cohorts and one healthy breast cohort with their corresponding clinicopathological information are included in bc-GenExMiner v4.5 version. Analyses are based on microarray or RNAseq transcriptomic data. Thirty-nine differential gene expression analyses, grouped into 13 categories, according to clinicopathological and molecular characteristics (‘Targeted’ and ‘Exhaustive’) and gene expression (‘Customized’), have been developed. Output results are visualized in four forms of plots. This new statistical mining module offers, among other things, the possibility to compare gene expression in healthy (cancer-free), tumour-adjacent and tumour tissues at once and in three triple-negative breast cancer subtypes (i.e. C1: molecular apocrine tumours; C2: basal-like tumours infiltrated by immune suppressive cells and C3: basal-like tumours triggering an ineffective immune response). Several validation tests showed that bioinformatics process did not alter the pathobiological information contained in the source data. In this work, we developed and demonstrated that bc-GenExMiner ‘Expression’ module can be used for exploratory and validation purposes.

Database URL: http://bcgenex.ico.unicancer.fr