bluuebunny/crossref_metadata_2025 huggingface dataset:
Quality of Life Outcomes in Patients With Sinonasal Malignancy After Definitive Treatment
Authors: Philips Ramez , Agarwal Aarti , Chitguppi Chandala , Swendseid Brian , Graf Alexander , Murphy Kira , Jangro William , Rhodes Lora , Toskala Elina , Luginbuhl Adam , Curry Joseph , Nyquist Gurston , Rosen Marc , Johnson Jennifer , Rabinowitz Mindy
Published: December 2020

Objectives/Hypothesis

To describe multidimensional quality of life (QOL) outcomes in patients with sinonasal malignancies (SNM). To elucidate factors predicting worse QOL in this population.

Study Design

Retrospective chart review at tertiary institution.

Methods

A retrospective chart review on patients treated for SNM from 2006 to 2019 at a tertiary medical center was conducted. QOL outcomes were measured using the Hospital Anxiety and Depression Scale (HADS) and the Functional Assessment Cancer Therapy – Nasopharynx (FACT‐NP) score. A stepwise multiple linear regression analysis was conducted to assess factors predicting worse QOL.

Results

Eighty‐one patients met inclusion criteria. Twelve (14.8%) patients had a subscale score >11 for anxiety (HADS‐A) or depression (HADS‐D) indicating significant anxiety or depression, at a median of 24 (8–68.5) months post treatment. The median FACT‐NP total score was 136 (110–152). On multivariable analysis, advanced T classification, single status, and worse social support survey score were significant predictors of worse HADS score. Worse social support survey score was a significant predictor of worse total FACT‐NP score.

Conclusion

After adjusting for confounders, at a median of 24 months after completion of definitive therapy for SNM, advanced T classification and single relationship status were found to be significant predictors of anxiety and depression (based on HADS). A worse social support survey score was associated with worse anxiety, depression, and QOL (based on HADS and FACT‐NP). Identifying these factors early may help to guide treatment and psychiatric referral to at‐risk individuals after the treatment of SNM.

Level of Evidence

3 Laryngoscope, 131:E2212–E2221, 2021
Barbed Reposition Pharyngoplasty versus Expansion Sphincter Pharyngoplasty: A Meta‐Analysis
Authors: Neruntarat Chairat , Khuancharee Kitsarawut , Saengthong Petcharat
Published: December 2020

Objective

This study was to compare barbed reposition pharyngoplasty (BRP) and expansion sphincter pharyngoplasty (ESP) in the treatment of obstructive sleep apnea (OSA).

Methods

Relevant 907 articles were searched from various databases until August 2020, including PubMed, MEDLINE, EMBASE, Cochrane Library, Web of Science and Scopus, and reference lists.

Results

Four studies with a total of 208 participants were included. The mean reduction of apnea‐hypopnea index (AHI) in the BRP group was 74.03% and the mean reduction of AHI in the ESP group was 60.17%. The mean success rate in the BRP group and the ESP group was 84.96% and 79.87%, respectively. The mean difference (MD) of the change in AHI between groups was not significantly different (MD = −1.24 event/hr, 95% CI [−11.86, 9.36], P = .82). There was no significant difference in postoperative AHI, postoperative Epworth Sleepiness Scale, pain, hospital stay, time to oral diet, and the change in oxygen desaturation index in both groups whereas the analgesic requirement was lower in the BRP group. Operative time was lower in the BRP group (MD = 21.72 minutes, 95% CI [18.85, 24.60], P < .0001).

Conclusion

The outcomes in both procedures are comparable in the improvement of OSA with palatal collapse. BRP is superior to ESP in term of surgical time. However, randomized clinical controlled trials with multicenter cooperation and long‐term follow‐up are essential to further demonstrate the efficacy of these procedures. Laryngoscope, 131:1420–1428, 2021
The setup and relaxation of spring upwelling in a deep, rotationally influenced lake
Authors: Roberts Derek C. , Egan Galen C. , Forrest Alexander L. , Largier John L. , Bombardelli Fabian A. , Laval Bernard E. , Monismith Stephen G. , Schladow Geoffrey
Published: December 2020

Strong and sustained winds can drive dramatic hydrodynamic responses in density‐stratified lakes, with the associated transport and mixing impacting water quality, ecosystem function, and the stratification itself. Analytical expressions offer insight into the dynamics of stratified lakes during severe wind events. However, it can be difficult to predict the aggregate response of a natural system to the superposition of hydrodynamic phenomena in the presence of complex bathymetry and when forced by variable wind patterns. Using an array of current, temperature, and water quality measurements at the upwind shore, we detail the hydrodynamic response of deep, rotationally influenced Lake Tahoe to three strong wind events during late spring. Sustained southwesterly winds in excess of 10 m s−1 drove upwelling at the upwind shore (characteristic of non‐rotational upwelling setup), with upward excursions of deep water exceeding 70 m for the strongest event. Hypolimnetic water, with elevated concentrations of chlorophyll a and nitrate, was advected toward the nearshore, but this water rapidly returned to depth with the relaxation of upwelling after the winds subsided. The relaxation of upwelling exhibited rotational influence, highlighted by an along‐shore, cyclonic front characteristic of a Kelvin wave‐driven coastal jet, with velocities exceeding 25 cm s−1. The rotational front also produced downwelling to 100 m, transporting dissolved oxygen to depth. More complex internal wave features followed the passage of these powerful internal waves. Results emphasize the complexity of these superimposed hydrodynamic phenomena in natural systems, providing a conceptual reference for the role upwelling events may play in lake ecosystems.
Circulation of an atypical hepatitis C virus (HCV) strain at a dialysis unit in northeast India
Authors: Kalita Deepjyoti , Deka Sangeeta , Chamuah Kailash
Published: December 2020

Patients undergoing hemodialysis are at an increased risk of hepatitis C virus (HCV) infection. The implementation of standard infection control measures can substantially decrease the risk of infections and other nosocomial infections. To study the HCV infection rates and genotypes in maintenance hemodialysis subjects in a dialysis unit. A total of 196 maintenance hemodialysis subjects were tested for HCV RNA for one year at a tertiary care teaching hospital in northeast India continuously. Genotyping was performed using direct sequencing (Sanger sequencing) of the 5′UTR‐core region. The HCV infection rate was 26.0%. On phylogenetic analysis, 29 sequences clustered around genotype 3 and subtype 3f were observed. High sequence similarities (75–100% homology) were observed among the isolated sequences. High molecular similarities in the isolates from the same dialysis unit with a high infection rate (26.0%) over a relatively short period of study (10 months) indicated an ongoing nosocomial transmission. Nosocomial transmission by subtype 3f is rare, and it has not been reported in dialysis cases previously. The strain is most likely evolving from common strains such as 3b or 3i and may spread due to migration or movement of people. Urgent implementation of adequate infection control measures is required.
Lipid metabolism in cancer progression and therapeutic strategies
Authors: Fu Yan , Zou Tiantian , Shen Xiaotian , Nelson Peter J. , Li Jiahui , Wu Chao , Yang Jimeng , Zheng Yan , Bruns Christiane , Zhao Yue , Qin Lunxiu , Dong Qiongzhu
Published: December 2020

Dysregulated lipid metabolism represents an important metabolic alteration in cancer. Fatty acids, cholesterol, and phospholipid are the three most prevalent lipids that act as energy producers, signaling molecules, and source material for the biogenesis of cell membranes. The enhanced synthesis, storage, and uptake of lipids contribute to cancer progression. The rewiring of lipid metabolism in cancer has been linked to the activation of oncogenic signaling pathways and cross talk with the tumor microenvironment. The resulting activity favors the survival and proliferation of tumor cells in the harsh conditions within the tumor. Lipid metabolism also plays a vital role in tumor immunogenicity via effects on the function of the noncancer cells within the tumor microenvironment, especially immune‐associated cells. Targeting altered lipid metabolism pathways has shown potential as a promising anticancer therapy. Here, we review recent evidence implicating the contribution of lipid metabolic reprogramming in cancer to cancer progression, and discuss the molecular mechanisms underlying lipid metabolism rewiring in cancer, and potential therapeutic strategies directed toward lipid metabolism in cancer. This review sheds new light to fully understanding of the role of lipid metabolic reprogramming in the context of cancer and provides valuable clues on therapeutic strategies targeting lipid metabolism in cancer.
Numerical appraisal under the influence of the time dependent Maxwell fluid flow over a stretching sheet
Authors: Ali Khan Kashif , Seadawy Aly R. , Jhangeer Adil
Published: December 2020

In this article, the study is to explore the series solution of magnetohydrodynamics, first‐order chemically reacting Maxwell fluid past a stretching sheet concentrated in a porous medium along with Soret and Dufour effects. The resemblance transformation is applied to convert the said time‐dependent phenomena into a family of ordinary differential equations. Then, elucidated by an analytic‐numeric approach named as homotopy analysis method (HAM) where numerical simulation is carried out carefully by a powerful software MATHEMATICA. Furthermore, the impact of disparate physical factors on the profiles of the flow model is presented vividly. The locus of the study is on the strength of the solution technique, so the error graphs disclose the fact that as the number of iterations enhanced, square residual profiles declines to 0 more sharply.
Prescribing of menopausal hormone therapy in Germany: Current status and changes between 2004 and 2016
Authors: Heinig Miriam , Braitmaier Malte , Haug Ulrike
Published: December 2020

Background

Prescribing of menopausal hormone therapy (MHT) declined drastically after publication of the Women's Health Initiative's (WHI) findings in 2002, but studies on longer‐term trends and details of use are scarce.

Methods

We used the German Pharmacoepidemiological Research Database (GePaRD) containing health insurance claims data from ~25 million persons. Using data from 2004–2016, we conducted cross‐sectional analyses to determine the prevalence of MHT use overall and by type and route of administration in women aged 45–75. In longitudinal analyses, we assessed MHT use over 5 years and compared the patterns between different time periods.

Results

From 2004 to 2016, prevalence of systemic MHT prescriptions decreased by >60% in women aged 55–65 and by >50% in women aged 50 and 70 years old. Prevalence declined for most types and routes of administration at all ages (−16% to −79%) with some exceptions, for example, local MHT (vaginal estrogen). Among 50‐year‐old women in 2012, 6% were already prescribed systemic MHT at age 49 and of the remaining women, 16% were newly prescribed systemic MHT before age 55. At all ages, the cumulative dose of systemic MHT prescribed over 5 years was lower in the period 2012–2016 compared to 2005–2009 (−6% to −46%).

Conclusions

For most types of MHT and all age groups, prevalence declined considerably between 2004 and 2016 in Germany. The cumulative dose per MHT user also decreased, suggesting a trend towards a shorter duration of use.
The effectiveness and safety ofTripterygium wilfordiiglycosides combined with disease‐modifying anti‐rheumatic drugs in the treatment of rheumatoid arthritis: A systematic review and meta‐analysis of 40 randomized controlled trials
Authors: Zheng Wenhao , Mei Yifan , Chen Chunhui , Cai Leyi , Chen Hua
Published: December 2020

Objective

This systematic review and meta‐analysis were performed to investigate the efficacy and safety ofTripterygium wilfordiiglycosides (TG) for rheumatoid arthritis (RA) from the current literature.

Methods

An electronic search was conducted in eight databases (PubMed, EMBASE, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure, Chinese Biomedical Literature Database, Chinese VIP Database, and Wanfang Database) from inception until September 2020. Randomized controlled trials (RCTs) with risk of bias (RoB) score ≥ 4 according to the Cochrane RoB tool were included for the analyses. The primary outcome measures were duration of morning stiffness (DMS), tender joint count (TJC), swollen joint count (SJC), visual analog score (VAS), C‐reactive protein (CRP), erythrocyte sedimentation rate (ESR), and rheumatoid factor (RF). The secondary outcome measures were the total clinical effective rate and adverse events. All the analyses were used by the random effects models. The meta‐analysis was performed using RevMan 5.3 and STATA 14.0.

Results

A total of 40 RCTs with 3092 patients met our inclusion criteria. This meta‐analysis showed that TG plus DMARDs for RA could decrease the DMS (p< .001), TJC (p< .001), SJC (p< .001), VAS (p< .001), serum CRP (p< .001), ESR (p< .001), and RF (p< .001) and improve total effective rate (p< .001). In addition, TG was generally safe and well tolerated in RA patients.

Conclusion

Despite the limitations, the present evidence supports, at least to an extent, that TG can be recommended for routine use for RA patients. More large multicenter and high‐quality RCTs are required for further research.
The impact of impurities on the mechanical properties of recycled polyethylene
Authors: Thoden van Velzen Eggo Ulphard , Chu Sharon , Alvarado Chacon Fresia , Brouwer Marieke T. , Molenveld Karin
Published: December 2020

The mechanical properties of mechanically recycled polyethylene (rPE) were studied in relation to the composition of the feedstock. This composition varied in six steps from only bottle bodies from a single type of high‐density polyethylene (HDPE) to the complete composition of an industrially sorted polyethylene (PE) product, including other packaging components, other PE‐based packages, sorting faults and residual waste. The rPE with the highest impact resistance was made from the single‐grade bottle bodies. The addition of bodies made from other types of PE already reduced the impact resistance with 11%. All the other stepwise additions of packaging components and faultily sorted objects caused the impact resistance to decrease further. Conversely, the elongation at break grew with the stepwise addition of these packaging components and faultily sorted objects. From the used methods, the best analysis method to accurately determine the polymeric composition of the rPE was found to be near‐infrared‐assisted flake analysis. This method can not only be used to determine the polymeric composition, but due to the strong correlation with the impact resistance, it is also a valuable indicator for the expected mechanical properties of rPE.
On the adsorption affinity of graphene and white graphene sheets by dioxin‐like pollutants
Authors: Alvarado Raúl , Ramos‐Berdullas Nicolás , Mandado Marcos
Published: December 2020

The affinity of graphene and white graphene sheets by dioxin‐like pollutants was compared by means of high‐level quantum chemical calculations. 2,3,7,8‐tetrachloro‐p‐dibenzodioxin (TCDD) and 2,3,7,8‐tetrachlorodibenzofuran (TCDF) were chosen as prototypes of dioxin‐like pollutants with high toxicological activity. Large interaction energies were obtained both in graphene and white graphene surfaces, contrary to other previous works using the graphene surface only. The interactions clearly differed in the relative weight of inductive and dispersion forces, being the former more important in white graphene. Leaving thermal effects out, the stacking adsorption was energetically favored over the perpendicular in graphene whereas no difference was found in white graphene. Due to the low water solubility of dioxin‐like pollutants very small differences were obtained between gas phase and solution adsorption enthalpies. Including thermal effects, perpendicular adsorption was found to be both energetically and entropically favored over stacking at 298 K. The adsorption free energies reflected a larger affinity by white graphene than graphene by around 2–5 kcal·mol−1. Therefore, boron nitride 2D surfaces are expected to perform better than carbon 2D surfaces as adsorbents for dioxin‐like pollutants in line with recent experimental works on water contaminants.
Warming rather than elevated CO2 shifts the rhizobacterial community composition in four maize‐growing soils
Authors: Fang Rui , Yu Zhenhua , Li Yansheng , Xie Zhihuang , Wang Guanghua , Liu Xiaobing , Liu Junjie , Liu Judong , Herbert Stephen J. , Jin Jian
Published: December 2020

Climate change may fundamentally affect the microorganisms in the rhizosphere that drive soil C and nutrient cycles. This study aimed to clarify the response of rhizobacterial community to warming and elevated CO2 (eCO2) in typical maize (Zea mays L.)‐growing soils. Under climate change, the shift of rhizobacterial community composition was assumed to be different among soils, which would be associated with the C sequestration and stability in soils. Using open‐top chambers to mimic climate warming and eCO2, we examined the taxonomic composition of bacterial communities in the rhizosphere of maize grown in four farming soils (Acrisol, Fluvisol, Kastanozem, and Phaeozem). Warming decreased the richness of the rhizobacterial community by 3.8% across the soils, but eCO2 did not significantly alter community richness. The shift in bacterial community composition was greater under warming than under eCO2, and the shift was different among soils. The abundance of Streptomyces and Gaiella significantly increased in Phaeozem and Acrisol in response to warming but not in Fluvisol or Kastanozem. Sphingomonas was suppressed in Phaeozem under warming, whereas Sphingomonas, Shinella, and Rhodospirillaceae_norank were enriched in the other three soils. Soil chemical characteristics including nitrate, Olsen P, available K, and soil organic C (SOC) were significantly associated with a number of dominant operational taxonomic units. These results indicate that the effect of warming on bacterial community composition in the rhizosphere of maize may be stronger than the effect of eCO2. Climate change led to various changes in the rhizobacterial community composition among soils that might be associated with the quality of SOC and nutrient status in different soils.
Cross-matching of allogeneic mesenchymal stromal cells eliminates recipient immune targeting
Authors: Rowland Aileen L. , Miller Donald , Berglund Alix , Schnabel Lauren V. , Levine Gwendolyn J. , Antczak Douglas F. , Watts Ashlee E.
Published: December 2020

Allogeneic mesenchymal stromal cells (MSCs) have been used clinically for decades, without cross-matching, on the assumption that they are immune-privileged. In the equine model, we demonstrate innate and adaptive immune responses after repeated intra-articular injection with major histocompatibility complex (MHC) mismatched allogeneic MSCs, but not MHC matched allogeneic or autologous MSCs. We document increased peri-articular edema and synovial effusion, increased synovial cytokine and chemokine concentrations, and development of donor-specific antibodies in mismatched recipients compared with recipients receiving matched allogeneic or autologous MSCs. Importantly, in matched allogeneic and autologous recipients, but not mismatched allogeneic recipients, there was increased stromal derived factor-1 along with increased MSC concentrations in synovial fluid. Until immune recognition of MSCs can be avoided, repeated clinical use of MSCs should be limited to autologous or cross-matched allogeneic MSCs. When non–cross-matched allogeneic MSCs are used in single MSC dose applications, presensitization against donor MHC should be assessed.
Analysis of the Explosive Properties of Tetrasulfur Tetranitride, S4N4
Authors: Koch Ernst‐Christian , Sućeska Muhamed
Published: December 2020

The explosive properties of tetrasulfur tetranitride, S4N4, are reviewed and analysed. S4N4 is an explosive compound with an impact sensitivity comparable to pentaerythritol tetranitrate (PETN) (Ei=4 J) but a friction sensitivity equal or even lower than lead azide (F=0.1–1 N). S4N4 has primary explosive properties. It has a working capacity greater than silver azide, AgN3, and is capable to initiate TNT. S4N4 shows an unusual non‐linear density/detonation velocity relationship which is due to different stability regimes of sulfur species present in the Chapman Jouguet zone. S4N4 is stable, non‐ageing, non‐toxic, insoluble in water and hence an interesting candidate for future lead tricinate replacement.
Childhood disadvantage and adolescent socioemotional wellbeing as predictors of future parenting behaviour
Authors: McAnally H.M. , Iosua E. , Sligo J.L. , Belsky J. , Spry E. , Letcher P. , Macdonald J.A. , Thomson K.C. , Olsson C.A. , Williams S. , McGee R. , Bolton A.E. , Hancox R.J.
Published: December 2020

Introduction

In extending work on early life antecedents of parenting, we investigate associations between childhood family history of disadvantage, adolescent socioemotional wellbeing, and age at first parenthood and subsequent parenting behaviour.

Methods

Parent‐child interactions were recorded when participants in the longitudinal Dunedin Multidisciplinary Health and Development Study (New Zealand) had a three‐year‐old child. Data were available for 358 mothers and 321 fathers, aged between 17.7 and 41.5 at the time of their child's birth. Associations between parenting and antecedent data on socioeconomic disadvantage, adolescent wellbeing and mental health, as well as current adult mental health and age at parenting, were tested for using structural equation modelling.

Results

Family disadvantage in childhood and lower adolescent wellbeing was associated with less positive future parenting, but only adult (not adolescent) anxiety/depression symptoms were directly associated with parenting behaviour. Childhood family disadvantage was associated with further disadvantage across the life course that included less positive parenting of the next generation. In contrast, socioemotional wellbeing during adolescence and later age of onset of parenting were associated with more positive parenting.

Conclusions

Reducing childhood disadvantage and improving socioemotional wellbeing during childhood and adolescence is likely to have intergenerational benefits through better parenting of the next generation.
Investigation of the Interaction Between Magnetosheath Reconnection and Magnetopause Reconnection Driven by Oblique Interplanetary Tangential Discontinuity Using Three‐Dimensional Global Hybrid Simulation
Authors: Guo Zhifang , Lin Yu , Wang Xueyi
Published: December 2020

Magnetosheath reconnection due to the interaction of an interplanetary directional discontinuity with the bow shock and Earth's magnetosphere under an initially northward interplanetary magnetic field (IMF) has been investigated in previous simulations (e.g., Guo et al., 2018, https://doi.org/10.1029/2018ja025679). Under an initially southward IMF, the magnetosheath reconnection could interact with reconnection at the magnetopause. In this study, using three‐dimensional (3D) global‐scale hybrid simulations, we present cases with incoming tangential discontinuities (TDs) in an initially southward IMF, which possess various magnetic field rotation angles (ΔΦ) and half‐width (w), to study the effects of pre‐existing magnetopause reconnection on the formation of magnetosheath flux ropes, as well as the subsequent interaction between the magnetopause reconnection and magnetosheath reconnection, with downstreams of both Quasi‐perpendicular (Q‐) and Quasi‐parallel (Q‐||) shock examined. The initial IMF is assumed to be oblique, with a finite Bx and Bz, similar to that in Guo et al. (2018), https://doi.org/10.1029/2018ja025679 but with a southward Bz < 0. Compared with the cases with an initially northward IMF, magnetopause reconnection weakens the compression processes of the TD and leads to less frequent reconnection in the magnetosheath. The existence and the structure of magnetosheath reconnection are found to strongly depend on the parameters w and of the TD. When interacting with the magnetopause reconnection, the magnetosheath flux ropes can re‐reconnect with the geomagnetic dipole field lines, forming new structures of magnetopause flux ropes. The resulting evolution of flux rope configuration is illustrated.
Interaction of Oppositely Traveling Medium‐Scale Traveling Ionospheric Disturbances Observed in Low Latitudes During Geomagnetically Quiet Nighttime
Authors: Wu Kun , Xu Jiyao , Wang Wenbin , Sun Longchang , Yuan Wei
Published: December 2020

In this study, an unusual event of medium‐scale traveling ionospheric disturbances (MSTIDs) that propagated in opposite directions was observed by multi‐instruments (all‐sky imager, global positioning system (GPS), and digisonde) in low latitudes during geomagnetically quiet nighttime. These MSTIDs had wavefronts aligned from northwest to southeast. One MSTID propagated southwestward and another propagated northeastward. They encountered and interacted with each other. Some MSTIDs structures merged into one and disappeared after the interaction. Furthermore, an eastward moving plasma bubble also encountered the MSTIDs and then gradually dissipated during the propagation process. The MSTIDs traveling in opposite directions should be related to ionospheric plasma motion and their trigger mechanisms. The interactive process of MSTIDS involved in plasma drifts and polarization electric fields. Meanwhile, the interaction with an ionospheric irregularity structure can change some of the MSTID characteristics.
Direct and Indirect Pathways of Convected Water Masses and Their impacts on the Overturning Dynamics of the Labrador Sea
Authors: Georgiou Sotiria , Ypma Stefanie L. , Brüggemann Nils , Sayol Juan‐Manuel , van der Boog Carine G. , Spence Paul , Pietrzak Julie D. , Katsman Caroline A.
Published: December 2020

The dense waters formed by wintertime convection in the Labrador Sea play a key role in setting the properties of the deep Atlantic Ocean. To understand how variability in their production might affect the Atlantic Meridional Overturning Circulation (AMOC) variability, it is essential to determine pathways and associated timescales of their export. In this study, we analyze the trajectories of Argo floats and of Lagrangian particles launched at 53°N in the boundary current and traced backward in time in a high‐resolution model, to identify and quantify the importance of upstream pathways. We find that 85% of the transport carried by the particles at 53°N originates from Cape Farewell, and it is split between a direct route that follows the boundary current and an indirect route involving boundary‐interior exchanges. Although both routes contribute roughly equally to the maximum overturning, the indirect route governs its signal in denser layers. This indirect route has two branches: part of the convected water is exported rapidly on the Labrador side of the basin and part follows a longer route toward Greenland and is then carried with the boundary current. Export timescales of these two branches typically differ by 2.5 years. This study thus shows that boundary‐interior exchanges are important for the pathways and the properties of water masses arriving at 53°N. It reveals a complex three‐dimensional view of the convected water export, with implications for the arrival time of signals of variability therein at 53°N and thus for our understanding of the AMOC.
Construction of defect-engineered three-dimensionally ordered macroporous WO3 for efficient photocatalytic water oxidation reaction
Authors: Wang Yating , Peng Chaosheng , Jiang Tao , Zhang Jing , Jiang Zheng , Li Xingang
Published: December 2020

We report defect-engineered 3DOM WO3 photonic crystals featuring abundant oxygen vacancies, excellent charge transport properties and remarkable photocatalytic performance.
User Authentication: A Three Level Password Authentication Mechanism
Authors: Mishra Gouri Sankar , Mishra Pradeep Kumar , Nand Parma , Astya Rani , Amrita
Published: December 2020

User authentication is one of the cutting edge research to provide access to legitimate uses. A number of mechanisms like biometric, image based, graphical based have been implemented. In this research work a three level password authentication is proposed and reported experimental results. From the result analysis it is found that the three level authentication provides reliable security level in comparison to the existing mechanisms.
IoMT: A Review of Pacemaker Vulnerabilities and Security Strategy
Authors: Puat Haidhar Athir Mohd , Rahman Nor Azlina Abd
Published: December 2020

Internet of Medical Things or IoMT is known as the most wanted technology in the healthcare sector. Almost 420 million connected device have been deployed globally to all healthcare facilities and with around 70 million more devices expected to be deployment by early of 2020 [4]. This types of technology and connection of medical devices to healthcare IT framework is not only beneficial to the patients but facilitates the structure of the traditional healthcare system of delivery information from department to department in healthcare environment. As a result to this budget for healthcare management and handling can be reduce and use for better improvement. However, with the advantages of IoMT, all the security behind every IoMT devices need to be considered. This paper is reviewing on several IoMT devices such as smart pen, implantable cardiac devices (pacemaker), wireless vital monitors and several other devices in terms of its functionality and vulnerabilities that might expose the devices to the attacker. More detail discussion is focusing into Pacemaker which is one of the IoMT devices. Several security strategy and solutions to minimize the vulnerabilities of IoMT devices are also being discussed.
Plant Leaf Disease Classification and Detection System Using Machine Learning
Authors: Geetha G. , Samundeswari S. , Saranya G. , Meenakshi K. , Nithya M.
Published: December 2020

In a developing country like India agriculture plays a noteworthy role. Agricultural intervention in the livelihood of rural India indulges by about 58%. Among the agricultural products, tomato is one of the most used crops. Thus, preventing significant loss in quantity and yield of tomato is majorly dependent on recognition and classification of diseases a tomato plant might possess. Latest and fostering technologies like Image processing is used to rectify such issues using different types of techniques and algorithms. Initially, the leaves of a tomato plant get affected, when plant develops a particular type of disease. In this project, four consecutive stages are used to discover the type of disease. The four stages include pre-processing, leaf segmentation, feature extraction and classification. To remove the noise we are doing the pre-processing and to part the affected or damages area of the leaf, image segmentation is used. The k-nearest neighbors (KNN) algorithm, which is a guided, supervised and advance machine learning algorithm, is implemented to find solutions for both the problems related to classification and regression. During the terminal stage, user is recommended with the treatment. Mostly live plants are adversely affected by the diseases. This paper imparts representation of leaf disease detection employing image processing that can identify drawbacks in tomato plant from images, based on color, bound and texture to give the brisk and reliable results to the farmer.
Named Entity Recognition in English Text
Authors: Jain Rachna , Sharma Abhishek , Mishra Gouri Sankar , Nand Parma , Chakraborty Sudeshna
Published: December 2020

Natural Language processing has been one of the challenging field of computational linguistics. Language processing occurs in several steps in which Named Entity Recognition is one of the prominent phase. NER frameworks have been contemplated and created generally for a considerable length of time, however precise frameworks utilizing profound neural systems (NN) have just been presented over the most recent couple of years. We present a far reaching review of profound neural system models for NER, and balance them with past ways to deal with NER dependent on highlight designing and other regulated or semi-administered learning calculations.
Image Captioning Using Deep Convolutional Neural Networks (CNNs)
Authors: Geetha G. , Kirthigadevi T. , Ponsam G.Godwin , Karthik T. , Safa M.
Published: December 2020

Earth is challenging to label satellite image clips with atmospheric conditions and various classes of land cover and land use. We proposed an algorithms to help the global community for a better understanding that where, how, and why deforestation take place all over the world. Upcoming development in satellite imaging technology have set grow to new opportunities for more precise investigation of both broad and minute changes occurring on Earth, including deforestation. Since 40 years, almost a fifth of the Amazon rain forest has been cut down. To estimate and analysis the forest this application is developed. Satellite images are trained on deep convolutional neural networks (CNNs) to learn image features and used multiple classification frameworks including gate recurrent unit label captioning and sparse_cross_entropy to predict multiclass, multi-label images. By fine-tuning an architecture consisting of the encoder of pre-trained VGG-19 parameters trained on ImageNet data together with the GRU decoder.
A Survey on Image Segmentation Using Deep Learning
Authors: Mary S. Prince , Ankayarkanni  , Nandini Usha , Sathyabama  , Aravindhan S.
Published: December 2020

Image segmentation is a critical process in computer vision. It involves dividing a visible input into segments to simplify image analysis. Segments represent objects or parts of objects and comprise sets of super-pixels. Image segmentation sorts pixels into larger components, eliminating the need to believe individual pixels as units of observation. Brain tumour segmentation is a crucial task in medical image segmentation. Early diagnosis of brain tumours plays a crucial role in improving treatment possibilities and increases the survival rate of the patients. Manual segmentation of the brain tumours for cancer diagnosis, from great deal of MRI images generated in clinical routine, may be a difficult and time-consuming task. There is a requirement for automatic brain tumour image segmentation. The method is proposed to segment normal tissues like substantial alba, grey matter, spinal fluid, and abnormal tissue like tumour part from a resonance Imaging (MRI) automatically. The system also uses to segment the tumour cells along the morphological filtering are going to be wont to remove background noises for smoothening of region. The project results will be presented as segmented tissues and classification using, Convolutional Neural Network (CNN) classifier.
A Customized Data Recovery Tool
Authors: Angamutu Kausalyani A/P , Rahman Nor Azlina Abd , Suki Nik Nurul Ain Nik
Published: December 2020

Data recovery is the process of salvaging deleted, formatted, corrupted, damaged or inaccessible data from the storage media as it cannot be accessed through normal way. There are two types of data recovery which is physical recovery and logical recovery. Physical recovery needs special equipment to repair the damaged parts of storage device like scratched plates, stalled spindle, fried chip, etc. and this process need to be undertaken in clean and controlled environment to extract data from storage device. Logical recovery is a software-based solution that recovers data from storage device which faced logical error in operating system or accidental user deletion. This paper will discuss on logical recovery and it is divided into few sections which is public awareness on data recovery, literature review on existing data recovery tool, analysis on user requirements for data recovery tool, proposed data recovery tool functionality and proposed data recovery tool framework.
A Review on IoMT device Vulnerabilities and Countermeasures
Authors: Jegatheswaran Reshiwaran A/L , Sakira Isaac Joshua , Rahman Nor Azlina Abd
Published: December 2020

According to a report by Allied Market Research they have said that by 2021 the IOMT would most likely reach about $136.8 billion worldwide [12]. This indicates that sooner almost all medical Centre would implement IOMT devices in their Centre and also in their patients’ body to get better result. Having a good growth on this it may indicate on the development of medical. It also proves on the movement from traditional medical to technology era medical whereby for checkups patients does not need to turn up as the device of IOMT would present the data. IOMT devices would allow the Medical Centre to cut cost on certain equipment as they could be done by using small IOMT device. This device is designed to generate data and provide indication for the users. IoMT also saves on the patients waiting time since analysis and prescription can be done on the go and there is no need for queuing up at medical facilities. Appointments can also be scheduled remotely depending on availability of the medical personnel. Because of the dependence on the internet for the transfer and storage or medical data, there is a big risk regarding data privacy and security. The aim of this research is to explore the vulnerabilities associated with IoMT devices that focusing on Mobile Cardiac Telemetry and Respiro Smart Inhaler system and suggest suitable protection mechanisms against the possible attacks to the IoMT devices.
Performance Evaluation of Analytics Models for Trends Analysis of News
Authors: Heng Lau Yee , Logeswaran Rajasvaran , Marikannan Booma Poolan
Published: December 2020

Microblogging services, especially Twitter, allow the user to share their most recent thoughts, feelings or news freely and almost immediately. Hence, the number of news tweets generated by the news media is increasing exponentially. Mining the valuable data from the large volume of tweets can help increase the revenue of organisations by allowing them to engage with the public faster and better by responding to the latest topics of interest. In this work, mining the hot keywords and being able in classifying the news tweets, trending topic and keywords in the news tweets. Both supervised and unsupervised machine learning models are used. Several machine learning algorithms are being used to compare the accuracy in classifying the tweets.
Performing Experimentation with Physics Model to Predict Statistical Weather Condition
Authors: Jayanthiladevi A. , Nagaraju V. , Devi L. , Padmavathi N. , Sailaja P. , Minu M.S , Tapas Bapu B R
Published: December 2020

Ice in wind turbines may cause a tremendous reduction in energy conservation. As, ice over turbines are not considered to be a traditional weather prediction data, prediction towards power can leads to higher error. This work anticipates a statistical approach dependent on Niave bayes regression to identify production loss has to be analyzed. It measures input of regional weather condition and various other conditions, and identify power production loss for 48 hours to enhance prediction of next generation energy loss. This can be trained with various prediction measurements and drastically enhances other conventional approaches for longer period. It may diminish absolute production error by ∼100kW and it computes its skill with other models. Prediction of weather data is considered to be one of the effectual data for diverse statistical prediction and some calculations are not so absolute. This method can be computational less cost and may be trained again for next prediction.
MathFun: A Mobile App For Dyscalculia Children
Authors: Rohizan Rizawati , Soon Lim Hean , Mubin Siti Azreena
Published: December 2020

Learning disability can vary from dyslexia (reading), dyscalculia (math) and dysgraphia (writing) where it focuses on certain learning disability that is being faced by the children. Dyscalculia is one of the common learning disabilities where in this category children are lack in ability of studying the math. However, with the enhancement of technologies, variety of application can be created in aiding the children learning process such as mobile learning by using mobile app. This paper focuses on the findings from the result of the MathFun app on the effectiveness towards enhancing the learning process for the learning disability children. MathFun is a mobile app created by following the Calculic Model approach for Malaysia Dyscalculia children. Usability was performed in order to assess the usability and verifying the effectiveness of MathFun. This study involved 3 teachers and three children. Descriptive analysis was performed from the collected data. Based on the outcome, it’s shows that the MathFun app able to help and improve the learning and has the potential to be use in the classrooms.
Coordinate Access System for Live Video Acquisition
Authors: Annapurna B. , Rama Reddy T , Raghavendran Ch. V. , Singh Raushan Kumar , Prasad Vedurai Veera
Published: December 2020

Biometric systems are the most advanced access technology developed so far in the 21st century. It does not even require to carry key cards or passwords in mind. Today most of the commercial and private entries are protected by biometric recognition systems like fingerprint scans facial recognition, retina scans, voice matching, etc. Even our phones, laptops, and daily access devices are equipped with biometric systems. In banks, the PCs are secured by the combination of passwords and fingerprint scans. Biometric scans are considered the most secure access technology so far. Our paper is to examine whether they are secure? Should we rely on them with our hard-earned money and social identity? Is there any way we can use these services without actually compromising our data and security? Our observation is on our digital identity. Promoting digitization in every department brings our topic in the picture. All our information is saved in our phones, our daily routine, whom we talk, what we purchase, whom we chat, where we travel, etc. Almost every smartphone has biometric fingerprint locks which means our phones have our fingerprint scans in database and with internet blend it’s tethered worldwide. Our fingerprints are connected to our bank accounts, PAN Cards, Passport, and SIM Cards using Aadhar Cards. If someone has our fingerprint they can easily reach our Aadhar Card and through that to all our personal information. Most of the phone companies are Chinese, Korean, German, and American. As per their country policies, they must share their data with the governing authorities. We aim to create a security system without actually using the biometric scans. The system is an advancement of the biometric system but with better accuracy and intelligence. We interface image acquisition tools to live track the red color things. The web camera or inbuilt system lens can be used as the acquisition system. When the red color object is moved in front of the lens it shows the corresponding coordinate of the object shown. We use these x and y coordinate of the objects as the authentication points. If the correct value grant access is 120 ⩽ x ⩽ 122 means the system grants permission only if the value of x=120,121 or 122 is obtained. Now, this is tricky. Even if you know the correct value also, it is very difficult to bring the correct point. Think about if you don’t know the point and it is also possible to make it much difficult by adding y coordinate so if the desired point is x=10, y=12 (10, 12) it is way more difficult. Each point is a possible password candidate and the screen of any device have megapixels where 1 Megapixel=106 pixels. Each pixel is a possible key or password entry. It can keep all our information safe and secure. We use a microcontroller and motor driver connected gate to demonstrate the result.
An Effectual Data Management Over Healthcare Systems for Improving Privacy in Iot Environment
Authors: Prasad K. Krishna , Aithal P. S. , Jayanthiladevi A.
Published: December 2020

The advancements in hardware and networking technology are merged with Internet of Things (IoT) which provides flexibility for monitoring the health condition of individuals. This is a smart environment that includes city, homes, and agriculture; as well, it recently includes healthcare systems for disease prediction and for medical advices. To improve the ability of IoT with healthcare system, the layers of data transmission has to be analyzed. This is to validate the faster response of physicians during the time of communication and lower latency. Moreover, this technology encounters various challenges in providing privacy towards the users and to address this privacy issue to certain extent. In the initial stage, the technology runs with a lesser privacy. Hence, this work deals with the modeling of e-healthcare framework that deals with preserving electronic medical records and attempts to eliminate privacy issue. However, the experimentation is done with MATLAB environment that concentrates on the metrics like response time and delay. The anticipated model provides better outcome in contrary to other models. The outcomes of this work are effectual while offering privacy with standardized network factors.
An Experimental Study on Partial Replacement of Cement and Fine Aggregate with Industrial Waste in Concrete Paver Blocks
Authors: Venkateswara Rao J , Rajesh S , Shankar Gopi
Published: December 2020

The present experimental investigation reports the relative results of flexural and compressive strength of conventional uni-paver concrete blocks of M-40 grade with the paver blocks produced by the combined partial replacement of the cement and fine aggregate with fly ash and pond ash respectively. Incorporation of these industrial products resulted in the saving of cement subsequently an overall saving of about 10% in the economy per each paver block production, while not compromising with its performance in respect to its strength aspect. The paver block considered in this experimental work is of zig- zag shape specimen of size 201 mm × 100 mm × 80 mm. Initially, fine aggregate and cement were replaced in percentages of 5, 10, 15 and 20 separately with pond ash and fly ash respectively. Later on, both fine aggregate and cement were replaced and the performance of paver block is evaluated in terms of its mechanical properties.