bluuebunny/crossref_metadata_2025_split huggingface dataset:
Catalytic Oxidation of CO over Nanocrystalline La1–xCexNiO3 Perovskite‐Type Oxides
Authors: Amini Sajjad , Meshkani Fereshteh , Rezaei Mehran 
Published: August 2019

AbstractNanocrystalline La1–xCexNiO3 (x = 0.1, 0.3, 0.5, 0.7, 0.9) perovskite‐type oxide catalysts prepared by the Pechini method were employed in catalytic CO oxidation and the effect of substitution of La by Ce on CO conversion was evaluated. The results indicated the remarkable effect of La substitution with Ce on the catalytic performance at low temperatures. The reaction temperature had a significant influence on the stability of the catalysts. The La0.1Ce0.9NiO3 sample exhibited the highest activity among the prepared catalysts in CO oxidation reaction. In addition, the influence of different parameters including pretreatment condition, feed ratio, and gas hourly space velocity (GHSV) on the catalytic performance was examined. The optimum catalyst proved high stability under severe reaction conditions in the presence of water vapor and CO2 in the feed stream.
Influence of the Feeding Rate on the Transient Behavior of a Biomass Combustor
Authors: Pérez-Orozco Raquel , Patiño David , Porteiro Jacobo , Cid Natalia , Regueiro Araceli 
Published: August 2019

AbstractMonitored variables in biomass combustion devices, such as emissions or temperature, are usually characterized by their averaged values over the entire process, although they tend to present a pulsating behavior. This assumption induces instantaneous errors when experimental data are used in numerical simulation. The interest in obtaining high‐quality experimental information for a proper model validation leads to find an alternative to describe them and to discern which operating variables are the main ones responsible for those fluctuations. The application of frequency‐domain tools, such as coherence, is proposed as a useful solution for determining if the emission and temperature profiles are intrinsically related to any known periodical signal, such as the feeding cycle.
Chemometric approach to estimate kinetic properties of paclitaxel prodrugs and their substructures for solubility prediction through molecular modelling and simulation studies
Authors: Munjal Nupur S. , Shukla Rohit , Singh Tiratha Raj 
Published: August 2019

AbstractPaclitaxel drug is administered in the treatment of ovarian and breast cancer and also in Kaposi sarcoma. In spite of being nanomolar active, use of this drug is confined because of its low aqueous solubility, hence many prodrugs for increasing paclitaxel's solubility were formed, but the formation process was not rational. In the current study, quantitative structure property relationship (QSPR) models were formed for the solubility prediction of paclitaxel prodrugs. Structures of all molecules were optimized at the parameterization method 6 (PM6) and Austin Model 1 (AM1) levels, after which Dragon‐based 5250 descriptors and quasi‐mixture descriptors were calculated. Independent descriptors were selected in multiple steps, and QSPR models having 12 and 10 descriptors with R2 and Q2 values of 0.78 and 0.60 and 0.80 and 0.69 for AM1‐ and PM6‐optimized geometry datasets, respectively, were formed. Also, for substituent group dataset, QSPR models with 8 and 9 descriptors having R2 and Q2 values of 0.82 and 0.76 and 0.93 and 0.83 were determined for AM1‐ and PM6‐optimized geometry datasets, respectively. Quasi‐mixture descriptors, which were calculated for substituent group datasets, gave the QSPR model with R2 and Q2 values of 0.70 and 0.58 and 0.69 and 0.52 respectively for AM1‐ and PM6‐optimized geometries. After the models' development, the substituent group dataset was employed for the formation of docking and molecular dynamics simulation–based models for the metabolic study with CYP1A2 enzyme. It is anticipated that the proposed QSPR models will serve as a base for the designing of new paclitaxel prodrugs with improved aqueous solubility.
Effects of cancer history on functional age and mortality
Authors: Blair Cindy K. , Jacobs David R. , Demark‐Wahnefried Wendy , Cohen Harvey J. , Morey Miriam C. , Robien Kim , Lazovich DeAnn 
Published: August 2019

BackgroundCancer, its treatment, and associated adverse effects may accelerate the functional aging of cancer survivors. In the current study, the authors used geriatric assessment (GA) to compare the functional age of long‐term cancer survivors with that of similarly aged women without a cancer history, and to examine whether functional age influences all‐cause mortality differently between these 2 groups.MethodsParticipants included 1723 cancer survivors and 11,145 age‐matched, cancer‐free women enrolled in the Iowa Women's Health Study in 1986 who completed the 2004 questionnaire (at ages 73‐88 years). GA domain deficits included ≥2 physical function limitations, ≥2 comorbidities, poor general health, poor mental health, and underweight. The risk of all‐cause mortality was estimated for deficits in each GA domain between 4 groups based on the cross‐classification of the presence and/or absence of cancer history and GA domain deficit (the referent group was cancer‐free women without a GA deficit).ResultsBoth cancer history and GA domain deficits significantly predicted 10‐year mortality for all GA domains. Cancer survivors without deficits had a 1.3‐fold to 1.4‐fold risk of mortality, similar to the 1.1‐fold to 1.7‐fold risk noted among cancer‐free women with deficits (all P < .05). Cancer survivors with deficits were found to have the highest mortality risk for 4 of 5 domains (hazard ratio range, 1.6‐2.0). Mortality risk increased with the increasing number of GA deficits, which was greater in cancer survivors compared with cancer‐free women.ConclusionsEven without GA deficits, cancer survivors appear to have an excess risk of death compared with women without cancer, and these deficits add to mortality risk. Interventions are needed to maintain or improve functional/physiological capacity as women age, especially in cancer survivors.
Transgenic Tumor Models for Evaluating CAR T‐Cell Immunotherapies
Authors: Aranda Fernando , Barajas Miguel , Huarte Eduardo 
Published: August 2019

AbstractChimeric antigen receptor (CAR) T‐cell therapy against tumor antigens involves a recombinant immunoreceptor that combines an antibody‐derived targeting fragment with signaling domains capable of activating T cells and fusion of this receptor domain to a costimulatory domain (typically CD28 or 4‐1BB). Clinical trials of CAR T‐cell therapeutics targeting CD19 antigens for relapsed or refractory B‐cell malignancies have shown unparalleled results and consequently have recently been approved by the U.S. Food and Drug Administration. However, the lack of efficacy beyond B‐cell malignancies, the emergence of resistance to CAR T‐cell therapy due to loss of the antigenic epitope, and severe cases of cytokine release syndrome and neurotoxicity necessitate further preclinical studies. As it is very complicated to develop a single animal model that would replicate the complexity of the clinical scenario, this article focuses on transgenic models used to study human tumor‐associated antigens in an immunocompetent model. © 2019 by John Wiley & Sons, Inc.
Oral health among children attending an oncology clinic in Trinidad
Authors: Kowlessar Anne , Naidu Rahul , Ramroop Visha , Nurse Janelle , Dookie Kavita , Bodkyn Curt , Lalchandani Sanjay 
Published: August 2019

AbstractObjectivesLittle is known about the oral health of paediatric oncology patients in the Caribbean. Poor oral health can complicate oncology treatment, negatively affecting a child's health. In children undergoing chemotherapy or bone marrow transplant, odontogenic infections can progress to life‐threatening sepsis. The aim of this study is to investigate the oral health among children attending an oncology clinic in Trinidad.Material and MethodsSample population included paediatric oncology patients attending a children's hospital in Trinidad. Subsequent to obtaining informed consent, a 14‐item questionnaire was administered to parents/caregivers. An intra‐oral examination was undertaken by two dentists to assess soft tissues, gingival health, and dentition status, using visual examination only.ResultsSeventy‐one children and their caregivers participated in the study. The children consisted of both patients warded or attending as outpatients; 53.5% of patients were male and the mean age 6.64 (SD 3.33) years with a range of 1 to 15 years. Gingivitis and mucositis were present among 41.3% and 3% of patients, respectively. The prevalence of visible dental caries was 54.3%. Caries experience (dmft) was 2.28 (SD 3.63), and for those children with some caries experience (dmft > 0), this was 5.59 (SD 3.72). The majority (62.5%) had never visited a dentist. The most common dental treatment needs were dental prophylaxis (98.4%) and restorative treatment (50.8%). Acute lymphocytic leukaemia (39.1%) was the most common malignancy among this sample, and patients were at varying stages of cancer treatment.ConclusionsOral health among this sample of paediatric oncology patients was generally poor, with untreated caries being common, and the majority of children not having had any previous dental care. Preventive dental care for these patients should include oral hygiene instruction, dietary advice, topical fluoride application along with management of carious lesions, and odontogenic infections. This preliminary study highlights the need for closer collaboration between general dental practitioners, paediatric dentists, and paediatric oncology physicians, in caring for these patients.
Neutral zone recording in computer‐guided implant prosthesis: A new digital neuromuscular approach
Authors: Frascaria Massimo , Pietropaoli Davide , Casinelli Matteo , Cattaneo Ruggero , Ortu Eleonora , Monaco Annalisa 
Published: August 2019

AbstractBackgroundNeutral zone (NZ) is a specific area in the oral cavity where muscular opposite forces are null. NZ represents the ideal zone for prosthesis placement. In this study, we compared digital implant planning using conventional technique and using NZ registration through piezography.MethodsSixty‐tree implants were digitally planned. Angular deviation differences between traditional planned and NZ‐planned implants were calculated. In addition, interferences with soft tissues (i.e., tongue and cheeks) were evaluated.ResultsWe observed a significant difference between traditional technique and piezographic approach in terms of implants angulation (p = .003), independent of site. A 4.7% of the planned abutments with traditional technique were placed outside the NZ, causing conflict with soft tissues in the digital model.ConclusionsCompared with traditional technique, piezography allows a significantly different exploitation of the nonconflict area, which potentially translates into better management of soft tissues and improved functionality of the implants.
Secure data transfer aware grouping technique for cloud‐assisted Internet of things applications
Authors: Raheema Alaa Q. , Tarish Hiba A. 
Published: August 2019

SummaryTask clustering process in distributed systems is used to improve the performance of executing workflow applications. In cloud‐assisted Internet of things (CIoT) framework, performing efficient task clustering is highly challenging because of the dynamic nature of cloud, availability of various billing models, and billing granularity options. This work aims at reducing the security overhead among the dependent tasks by using data transfer aware grouping technique (DTAGT), which takes into consideration the amount of data transferred among dependent tasks to obtain a cluster that reduces the security overhead in the network by optimizing the data transfer rate. Collecting the data in a CIoT environment is difficult, and the redundancy among the data from the sensors tends to decrease the lifetime of the network and also increases the latency has been resolved using proposed DTAGT. The overall objective of the proposed grouping algorithm is to reduce the total completion time and cost of executing workflow application with high reliability in CIoT platform. The proposed system is implemented, and the result analysis shows DTWCT (Dual‐tree complex wavelet transform) outperforms the other related works.
Hash‐balanced binary tree–based public auditing in vehicular edge computing and networks
Authors: Liu Mingxi , Fan Kuan , Kumar Neeraj , He Debiao , Shi Wenbo 
Published: August 2019

SummaryIn recent years, cloud storage technology is developed maturely, so data owners could deposit data to relieve the storage pressure. In vehicular communication networks, vehicles tend to use low‐latency networks to transfer the valid road information and vehicle information generated by smart sensors in real time. Vehicular edge computing (VEC) networks satisfy the low‐latency requirements of the vehicular communication networks. However, vehicles have no space to store a copy of the data locally like using a local storage service. Vehicles, as users of cloud storage, pay attention to the integrity of the data especially. Unfortunately, many existing auditing schemes for integrity are not fully applicable to the VEC paradigm, because of significant differences in security assumptions. In this paper, a dynamic public audit protocol is proposed to the VEC paradigm. First, a new threat model is defined to formalize noncollusive and collusive attacks according to VEC servers and cloud server providers. Second, we propose a novel auditing protocol based on hash‐balanced binary tree (HBBT) and describe the auditing process and dynamic operations. Third, security analysis and experimental analysis are completed to demonstrate the safety and effectiveness of the proposed scheme.
Fault diagnosis in wireless sensor network using clonal selection principle and probabilistic neural network approach
Authors: Mohapatra Santoshinee , Khilar Pabitra M. , Swain Rakesh R. 
Published: August 2019

SummaryThe fault diagnosis in wireless sensor networks is one of the most important topics in the recent years of research work. The problem of fault diagnosis in wireless sensor network can be resembled with artificial immune system in many different ways. In this paper, a detection algorithm has been proposed to identify faulty sensor nodes using clonal selection principle of artificial immune system, and then the faults are classified into permanent, intermittent, and transient fault using the probabilistic neural network approach. After the actual fault status is detected, the faulty nodes are isolated in the isolation phase. The performance metrics such as detection accuracy, false alarm rate, false‐positive rate, fault classification accuracy, false classification rate, diagnosis latency, and energy consumption are used to evaluate the performance of the proposed algorithm. The simulation results show that the proposed algorithm gives superior results as compared with existing algorithms in terms of the performance metrics. The fault classification performance is measured by fault classification accuracy and false classification rate. It has also seen that the proposed algorithm provides less diagnosis latency and consumes less energy than that of the existing algorithms proposed by Mohapatra et al, Panda et al, and Elhadef et al for wireless sensor network.
Rolling window regression of δ13C and δ18O values in carbonate sediments: Implications for source and diagenesis
Authors: Oehlert Amanda M. , Swart Peter K. 
Published: August 2019

AbstractDiagenetic alteration can produce, modify or erase significant biogeochemical information recorded in carbon and oxygen (δ13C and δ18O) values of marine carbonates throughout geological time. Understanding the type and extent of alteration experienced by a carbonate deposit can improve sedimentological and geochemical interpretations of events in Earth history. In this study, we present a new application of a statistical approach to aid in the identification and interpretation of sedimentological surfaces in a shallow marine carbonate sequence using a rolling window regression (RWR) analysis. RWR analysis evaluates the degree of covariation between two records and how it changes through time. Geological application of this statistical technique permits a new perspective on the fine scale variability in carbon and oxygen isotope records and the processes that generate them and provides a complementary tool for sedimentological interpretations. In this study, we apply RWR to δ13C and δ18O values from the Clino drilled into the western margin of Great Bahama Bank, a core that has been extensively altered by diagenetic processes, within the vadose, phreatic and marine burial zones. This core penetrates ~676 m of shallow marine to deeper slope deposits and contains a variety of both sedimentological and diagenetic events, including facies transitions, subaerial exposure surfaces, marine hardgrounds, firmgrounds and periods of reduced sedimentation rate. Using more than 1,200 analyses of paired δ13C and δ18O values, we have applied a RWR analysis to evaluate how the correlation between these two proxies changes at scales of 10, 30 and 100 m. The results of this study highlight the dynamic evolution of correlations between δ13C and δ18O values within diagenetic zones and in association with diagenetic surfaces and provide context for interpreting covariance in δ13C and δ18O values from the geological record.
Eating disorder recovery in men: A pilot study
Authors: Bardone‐Cone Anna M. , Johnson Shelby , Raney Thomas J. , Zucker Nancy , Watson Hunna J. , Bulik Cynthia M. 
Published: August 2019

AbstractObjectiveThis pilot study examined the validity of a comprehensive definition of recovery (physical, behavioral, and cognitive recovery indices) for the first time in men.MethodMen with an eating disorder history were recruited from former patients at eating disorder centers, university campuses, and fitness centers/gyms. At baseline and a 12‐month follow‐up, data were collected via online surveys, diagnostic interviews, and measured weight and height from men with an eating disorder history (n = 36) and men with no eating disorder history (n = 27).ResultsOf the men with an eating disorder history, 15 met criteria for an eating disorder, 7 met criteria for partial recovery, and 5 for full recovery. Men who met criteria for full recovery did not differ significantly from men with no eating disorder history and had significantly lower levels of broad eating pathology, thinness and restricting expectancies, body shame, difficulties in stopping thoughts about body, food, or exercise, and male body attitudes related to muscularity and body fat than men with an eating disorder. Men meeting criteria for full recovery had higher levels of body acceptance and intuitive eating than men who met criteria for partial recovery or an eating disorder. In terms of predictive validity, of those fully recovered at baseline, 60% also met full recovery criteria at follow‐up.DiscussionPreliminary findings suggest that a comprehensive definition of recovery applies to men. Although research with larger samples is needed, this research provides some optimism for the potential of recovery in men.
State‐space modeling reveals habitat perception of a small terrestrial mammal in a fragmented landscape
Authors: Gardiner Riana , Hamer Rowena , Leos‐Barajas Vianey , Peñaherrera‐Palma Cesar , Jones Menna E. , Johnson Chris 
Published: August 2019

Abstract

Habitat loss is a major cause of species loss and is expected to increase. Loss of habitat is often associated with fragmentation of remaining habitat. Whether species can persist in fragmented landscapes may depend on their movement behavior, which determines their capability to respond flexibility to changes in habitat structure and spatial distribution of patches.

Movement is frequently generalized to describe a total area used, or segmented to highlight resource use, often overlooking finer‐scale individual behaviors. We applied hidden Markov models (HMM) to movement data from 26 eastern bettongs (Bettongia gaimardi) in fragmented landscapes. HMMs are able to identify distinct behavior states associated with different movement patterns and discover how these behaviors are associated with habitat features.

Three distinct behavior states were identified and interpreted as denning, foraging, and fast‐traveling. The probability of occurrence of each state, and of transitions between them, was predicted by variation in tree‐canopy cover and understorey vegetation density. Denning was associated with woodland with low canopy cover but high vegetation density, foraging with high canopy cover but low vegetation density, and fast‐traveling with low canopy cover and low vegetation density.

Bettongs did move outside woodland patches, often fast‐traveling through pasture and using smaller stands of trees as stepping stones between neighboring patches. Males were more likely to fast‐travel and venture outside woodlands patches, while females concentrated their movement within woodland patches.

Synthesis and applications: Our work demonstrates the value of using animal movement to understand how animals respond to variation in habitat structure, including fragmentation. Analysis using HMMs was able to characterize distinct habitat types needed for foraging and denning, and identify landscape features that facilitate movement between patches. Future work should extend the use of individual movement analyses to guide management of fragmented habitat in ways that support persistence of species potentially threatened by habitat loss.
Effectiveness of biosurfactant for the removal of trihalomethanes by biotrickling filter
Authors: Mezgebe Bineyam , Sorial George , Wendell David , Sahle‐Demessie E. 
Published: August 2019

In this study, the biodegradation of a mixture of two trihalomethane (THM) compounds, chloroform (CF) and dichlorobromomethane (DCBM), was evaluated using two laboratory‐scale biotrickling filters (BTFs). The two BTFs, hereby designated as “BTF‐A” and “BTF‐B,” were run parallel and used ethanol as co‐metabolite at different loading rates (LRs), and a lipopeptide‐type biosurfactant that was generated by the gram‐positive bacteria, Surfactin, respectively. The results using BTF‐A showed that adding ethanol at a higher rate of 4.59 g/(m3 h) resulted in removal efficiencies of 85% and 87% for CF and DCBM, respectively. Conversely, for the same LR, the use of Surfactin without ethanol (BTF‐B) showed comparable removal efficiencies of 85% and 80% for CF and DCBM, respectively. The maximum rate constant for CF and DCBM for the BTF‐A was 0.00203 s−1 and 0.0022 s−1, respectively. For the same THMs LR, similar reaction rate constants resulted for the BTF‐B. Further studies were conducted to investigate and understand the microbial diversity within both BTFs. The result indicated that for BTF with co‐metabolite, Fusarium sp. was the most dominant fungi over 98% followed by F. Solani with less than 2%. F. oxysporum and Fusarium sp. were instead the dominant fungi for the BTF with Surfactin. Before introducing the Surfactin into the BTF, the batch experiment was conducted to evaluate the effectiveness of synthetic surfactant as compared to a biosurfactant (Surfactin). In this regard, vials with Surfactin showed better performance than vials with Tomadol 25‐7 (synthetic surfactant).