bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robotic Transanal Surgery for Rectal Cancer
Authors: Marks John H. , Perez Rafael E. , Salem Jean F. 
Published: September 2021

AbstractRobotic transanal surgery is the culmination of major developments in rectal cancer management and minimally invasive surgery. It is the result of continuous efforts to tackle the challenges inherent to rectal cancer surgery. This latest technology holds great promise and excitement for the care of the rectal cancer patient. In this article, we will describe the evolution of transanal rectal cancer surgery and describe how the convergence of transanal transabdominal, transanal endoscopic microsurgery, transanal minimally invasive surgery (TAMIS), transanal total mesorectal excision (taTME), and the different robotic platforms have culminated in the development of single port robotic transanal minimally invasive surgery (SP rTAMIS) and single port robotic transanal total mesorectal excision (SP rtaTME). We will describe the indications, technical aspects, outcomes, benefits, and limitations of the SP rTAMIS and SP rtaTME.
Complicated Intubations are Associated with Bronchopulmonary Dysplasia in Very Low Birth Weight Infants
Authors: Glenn Tara , Fischer Linnea , Markowski Ashley , Carr Cara Beth , Malay Sindhoosha , Hibbs Anna Maria 
Published: September 2021

Objective This study aimed to evaluate the association between desaturation <60% (severe desaturation) during intubation and a total number of intubation attempts in the first week of life in very low birth weight (VLBW) infants with adverse long-term outcomes including bronchopulmonary dysplasia (BPD) and severe periventricular/intraventricular hemorrhage grade 3 or 4 (PIVH).
Study Design A retrospective chart review was performed on VLBW infants intubated in the neonatal intensive care unit during the first week of life between January 2017 and July 2020. Descriptive tables were generated for two outcomes including BPD and PIVH. Multivariable logistic regression was performed for each outcome including significant predictors that differed between groups with a p-value of <0.2.
Results A total of 146 patients were included. Patients with BPD or PIVH had a lower gestational age, and patients with BPD had a lower BW. Patients with BPD had a greater number of intubation attempts in the first week of life (4 vs. 3, p < 0.001). In multivariable logistic regression controlling for confounding variables, the odds developing BPD were higher for patients with increased cumulative number of intubation attempts in the first week of life (odds ratio [OR]: 1.29, 95% confidence interval [CI]: 1.03–1.62, p = 0.029). Post hoc analyses revealed increased odds of developing BPD with increased number of intubation encounters in the first week of life (OR: 2.20, 95% CI: 1.04–4.82, p = 0.043). In this post hoc analysis including intubation encounters in the model; desaturation <60% during intubation in the first week of life was associated with increased odds of developing BPD (OR: 2.35, 95% CI: 1.02–5.63, p = 0.048).
Conclusion The odds of developing BPD for VLBW infants were higher with increased intubation attempts and intubation encounters. In a post hoc analysis, the odds of developing BPD were also higher with desaturation during intubation. Further research is needed to determine mechanisms of the relationship between complicated intubations and the development of BPD.
Key Points
Transient liquid phase bonding of ZK60 magnesium alloy using graphene nanoplatelets
Authors: Nadeem Irfan , Aslam Ahmed , Mahmood Sultan , Shahzad Muhammad , Tauqir Anjum , Subhani Tayyab 
Published: September 2021

Transient liquid phase bonding of ZK60 magnesium alloy was performed by incorporating aluminium foil as an interlayer, unaided and in combination with graphene nanoplatelets. The solitary incorporation of aluminium foil increased the shear strength of magnesium alloy in comparison to the addition of graphene nanoplatelets with aluminium foil. The fractured surfaces revealed a mixed-mode fracture while the hardness profile across the interface showed the increase in hardness in the bonded region, which was due to the formation of Al12Mg17 intermetallic. GRAPHICAL ABSTRACT
Effect of pulsed electric field on diabetes-induced glycated enzyme, oxidative stress, and inflammatory markers in vitro and in vivo
Authors: Rezaeinezhad A , Eslami P , Afrasiabpour Gh , Mirmiranpour H , Ghomi H 
Published: September 2021

Abstract
This study focused on the effect of pulsed electric field (PEF) on the modification of superoxide dismutase (SOD) to recover its activity (in vitro) and thereby reverse oxidative stress in diabetic mice (in vivo). The result of the in vitro assay demonstrated that PEF could modify the glycated SOD structure through a change in the electrostatic environment of the protein. This modification leads to an 83% and 31% increase in the enzymatic activity of in vitro and in vivo assays, respectively. The in vivo assessment results show a decrease in oxidative stress biomarker indices, advanced glycation end products content, and inflammatory cytokines concentrations. However, the change in blood glucose level is not significant. According to the results, PEF would be effective in diabetes therapy and could be employed as a complementary method.
Training of quantized deep neural networks using a magnetic tunnel junction-based synapse
Authors: Greenberg-Toledo Tzofnat , Perach Ben , Hubara Itay , Soudry Daniel , Kvatinsky Shahar 
Published: September 2021

Abstract
Quantized neural networks (QNNs) are being actively researched as a solution for the computational complexity and memory intensity of deep neural networks. This has sparked efforts to develop algorithms that support both inference and training with quantized weight and activation values, without sacrificing accuracy. A recent example is the GXNOR framework for stochastic training of ternary and binary neural networks (TNNs and BNNs, respectively). In this paper, we show how magnetic tunnel junction (MTJ) devices can be used to support QNN training. We introduce a novel hardware synapse circuit that uses the MTJ stochastic behaviour to support the quantize update. The proposed circuit enables processing near memory (PNM) of QNN training, which subsequently reduces data movement. We simulated MTJ-based stochastic training of a TNN over the MNIST, SVHN, and CIFAR10 datasets and achieved an accuracy of

98.61
%

,

93.99
%

and

83.02
%

, respectively (less than

1
%

degradation compared to the GXNOR algorithm). We evaluated the synapse array performance potential and showed that the proposed synapse circuit can train TNNs in situ, with

18.3

T
O
P
s

W

for feedforward and

3

T
O
P
s

W

for weight update.
Effect of non-uniform efficiency on higher-order cumulants in heavy-ion collisions *
Authors: Si Fan , Zhang Yifei , Luo Xiaofeng 
Published: September 2021

Abstract
We perform a systematic study on the effect of non-uniform track efficiency correction in higher-order cumulant analysis in heavy-ion collisions. Through analytical derivation, we find that the true values of cumulants can be successfully reproduced by the efficiency correction with an average of the realistic detector efficiency for particles with the same charges within each single phase space. The theoretical conclusions are supported by a toy model simulation by tuning the non-uniformity of the efficiency employed in the track-by-track efficiency correction method. The valid averaged efficiency is found to suppress the statistical uncertainties of the reproduced cumulants dramatically. Thus, usage of the averaged efficiency requires a careful study of phase space dependence. This study is important for carrying out precision measurements of higher-order cumulants in heavy-ion collision experiments at present and in future.
A remotely controlled Marangoni surfer
Authors: Timm Mitchel L. , Jafari Kang Saeed , Rothstein Jonathan P. , Masoud Hassan 
Published: September 2021

Abstract
Inspired by creatures that have naturally mastered locomotion on the air–water interface, we developed and built a self-powered, remotely controlled surfing robot capable of traversing this boundary by harnessing surface tension modification for both propulsion and steering through a controlled release of isopropyl alcohol. In this process, we devised and implemented novel release valve and steering mechanisms culminating in a surfer with distinct capabilities. Our robot measures about 110 mm in length and can travel as fast as 0.8 body length per second. Interestingly, we found that the linear speed of the robot follows a 1/3 power law with the release rate of the propellant. Additional maneuverability tests also revealed that the robot is able to withstand 20 mm s−2 in centripetal acceleration while turning. Here, we thoroughly discuss the design, development, performance, overall capabilities, and ultimate limitations of our robotic surfer.
Cleaner air reveals growing influence of climate on dissolved organic carbon trends in northern headwaters
Authors: de Wit Heleen A , Stoddard John L , Monteith Donald T , Sample James E , Austnes Kari , Couture Suzanne , Fölster Jens , Higgins Scott N , Houle Daniel , Hruška Jakub , Krám Pavel , Kopáček Jiří , Paterson Andrew M , Valinia Salar , Van Dam Herman , Vuorenmaa Jussi , Evans Chris D 
Published: September 2021

Abstract
Surface water browning, the result of increasing concentrations of dissolved organic matter (DOM), has been widespread in northern ecosystems in recent decades. Here, we assess a database of 426 undisturbed headwater lakes and streams in Europe and North America for evidence of trends in DOM between 1990 and 2016. We describe contrasting changes in DOM trends in Europe (decelerating) and North America (accelerating), which are consistent with organic matter solubility responses to declines in sulfate deposition. While earlier trends (1990–2004) were almost entirely related to changes in atmospheric chemistry, climatic and chemical drivers were equally important in explaining recent DOM trends (2002–2016). We estimate that riverine DOM export from northern ecosystems increased by 27% during the study period. Increased summer precipitation strengthened upward dissolved organic carbon trends while warming apparently damped browning. Our results suggest strong but changing influences of air quality and climate on the terrestrial carbon cycle, and on the magnitude of carbon export from land to water.
Updated respiration routines alter spatio-temporal patterns of carbon cycling in a global land surface model
Authors: Butler Ethan E , Wythers Kirk R , Flores-Moreno Habacuc , Chen Ming , Datta Abhirup , Ricciuto Daniel M , Atkin Owen K , Kattge Jens , Thornton Peter E , Banerjee Arindam , Reich Peter B 
Published: September 2021

Abstract
We updated the routines used to estimate leaf maintenance respiration (MR) in the Energy Land Model (ELM) using a comprehensive global respiration data base. The updated algorithm includes a temperature acclimating base rate, an updated instantaneous temperature response, and new plant functional type specific parameters. The updated MR algorithm resulted in a very large increase in global MR of 16.1 Pg (38%), but the signal was not geographically uniform. The increase was concentrated in the tropics and humid warm-temperate forests. The increase in MR led to large but proportionally smaller decreases in global net primary production (19%) and in average global leaf area index (15%). The effect on global gross primary production (GPP) was a more modest 5.7 Pg (4%). A detailed site level analysis also demonstrated a wide range of effects the updated algorithm can have on the seasonal cycle of GPP. Output from the updated and old models did not differ markedly in how closely they matched a suite of benchmarks. Given the substantial impact on the land surface carbon cycle, a neutral influence on model benchmarks, and better alignment with empirical evidence, an MR algorithm similar to the one presented here should be adopted into ELM.
Removal of Hexavalent Chromium using Iron Nanoparticles Prepared using Date Seed Extract
Authors: Habib F , Shanableh A , Bhattacharjee S 
Published: September 2021

Abstract
Removal of hexavalent chromium from contaminated water systems is critical due to their high toxicity to aquatic and human health. Iron based nanoparticles (FeNPs) have emerged as promising materials for chromium removal. However, greener alternatives to the chemical synthesis routes of FeNPs are highly desirable while retaining their remediation ability. In this study we evaluate the removal efficiency of chromium using iron nanoparticles synthesized using aqueous extracts of date tree seeds (ds-FeNPs). Characterization of ds-FeNPs reveal the presence of 20-100 nm spherical nanoparticles containing Fe, C, O and S elements. Batch experiments demonstrated that the removal efficiency increased with increase in nanoparticles dose for a fixed chromium concentration (from 18 to 98% at nanoparticles dose of 166 to 1000 mg/L), whereas an opposite trend was observed for varying chromium concentrations at fixed nanoparticles dose. Removal efficiency was also probed at different initial pH levels and results indicate complete removal of chromium in acidic pH (100% at pH 3) whereas basic pH hindered chromium removal.
Research on the Courtyard Mosque Soundscape- A Case Study in the Huajue Alley Mosque
Authors: Shan H , Liang Y 
Published: September 2021

Abstract
The mosque is one of the representative Islamic buildings. The unique sound of imam calling and Muslim chanting endows the mosque with the unique spirit of place. Soundscape examining the symbiotic relationship between humans and the environment from the perspective of multidisciplinary integration, realize the evaluation of the adaptability, matching and harmony among sound, architecture and environment from the perspective of human experience. In order to realize the characteristic integration of the modern life and the traditional human settlement space in the new era, to protect and inherit the unique role and charm of the sound elements in the environment, this article starts from the perspective of the soundscape, taking the acoustic environment in the national-protecting Mosque in Huajue Alley as the representative of the research object, combining objective measurement and subjective evaluation methods, a meticulous study has been carried out on the current acoustic environment of the Mosque in Huajue Alley and its main influencing factors. The results of the study highlight the importance of sound elements to the courtyard mosque architecture itself and to the daily life of Muslim communities. It also provides meaningful exploration and practice for enriching the construction of the soundscape theory system.
Undesirable Substances Reduction in Solid Fuel Recovered from Municipal Solid Waste of Russia
Authors: Mikhailova N V , Yasinskaya A V 
Published: September 2021

Abstract
There has been substantiated the approach to high quality SRF production from MSW based on the analysis of waste chemical and morphological composition. The method involves analysis of undesirable elements content in MSW morphological components and targeted removal of the components that are predominant carriers of the undesirable elements. The morphological components to be removed has been identified, the physical attributes of their distinction from target fuel components have been chosen, the methods of separation and related equipment have been proposed. The application of the proposed combination of methods to the MSW of Russia has been modelled with a favourable outcome on all relevant heavy metals and chlorine.
Smart-IoT Platform to Monitor Microclimate Conditions in Tropical Regions
Authors: Gonzalez CJ , Espinosa A. , Ponte D. , Gibeaux S. 
Published: September 2021

Abstract
Precision farming has a large scale of applications including wireless sensor networks to monitor the crop yields. For example, Raspberry pi board enables the possibility to integrate the agriculture system with online servers as well as an efficient sensor method for monitoring agricultural parameters. The occidental region of Panama is an agro-based economy; for instance, precision farming can help the farmers use modernization techniques which improve primitive methods, still used in developing countries. However, commercial solutions of sensors are very expensive for farmers, making it impossible for small producers to implement this type of system. The purpose of this research is to present an updated comprehensive systematic literature in the field of IoT smart agriculture, showing a prototype of an IoT device and the monitoring system platform. The developed framework allows the control from a remote location and it can be implemented in grain stores, agricultural fields, and farming households.
Data-driven sustainable ship design using Axiomatic Design and Bayesian Network Model
Authors: Fardelas G , Kim S G 
Published: September 2021

Abstract
Environmental sustainability, as well as social and economic well-being, must be considered in every stage of a product lifecycle, from conceptual design to its retirement. Even though this sustainability-centric approach represents a critical driver for innovation, it also increases the design complexity. Nowadays, the maritime transport accounts for a large share of transport demand, and the importance of sustainable ship design is increasingly growing, not only for ethical and legislative but also for competitive reasons. The design of a sustainable ship considering all those aspects is a complex process in this regard. One way to manage the complexity is to identify and avoid the functional couplings at the early stage of the design process. This paper presents the conceptual design of a merchant ship's conventional propulsion system with a view to the Axiomatic Design framework and known sustainable engineering principles. We also explore the Bayesian machine learning interface to propose a data-driven method for calculating the probability of achieving specific sustainability-related functional requirements. Data-driven Bayesian reasoning can also be used to select the best design parameter among the proposed alternatives as well as to identify hidden design couplings that have not identified by the designers in the conceptual design stage.
Decision support systems in building construction – an Axiomatic Design approach
Authors: Marcher Carmen , Rauch Erwin , Giusti Andrea , Matt Dominik T 
Published: September 2021

Abstract
The introduction of Industry 4.0 leads to new decision-making scenarios in the construction industry. The construction sector still hesitates to adopt emerging technologies and many construction companies require support in the field of digitalisation and automation of processes. One way to support this sector is the use of decision support systems that perform a careful assessment of the feasibility for replacing traditional systems with automated ones. However, the design and the development of decision support systems is a complex and time-consuming task. In this work we apply Axiomatic Design to define design guidelines for the development of decision support systems in construction equipment selection. The needs of the construction industry for decision support in these scenarios are derived from existing literature in the field of construction and the key characteristic of decision-theoretic expert systems. These needs are analysed and translated into functional requirements. Then, through a mapping and decomposition process, the design solutions for the development of a decision support system are deduced. Functional requirements and design solutions are transformed into design guidelines that support the systematic development and implementation of decision support systems for the construction phase of a building.
Identifying Poor Designs with Conflicts in Design Parameters
Authors: Iino Kenji , Nakao Masayuki 
Published: September 2021

Abstract
Mechanical design is an act of defining machines that produce values to people, however, a poor design sometimes causes mechanisms to fail. Such failures can lead to harms to people, the environment, or both and in the worst case, it can even cause people’s death. Axiomatic design is a design tool that helps the designer come up with more stable and robust designs by pointing out troubling elements in a design by identifying interference among parts. Taking a design through axiomatic analysis only at an abstract level, however, can miss finding interferences within. A product, through its lifetime, can also experience disturbances that the designer overlooked at the time of design. This paper discusses a trouble that arose with bicycles with a new safety feature of locking the front wheel when parked. The locking mechanism faced an unexpected part failure that caused the handle to lock while riding. Another topic is an inherent interference that existed from the very beginning of a design that the designers could not identify probably due to the extreme complexity of the system, the Fukushima Nuclear Power Plant-1, Unit-1. Analysis for evaluating how well a design will meet its functional requirement without trouble should go into the detail level, especially for all modes of operation, to avoid oversight of hard-to-find interferences and conflicts. This paper also suggests carrying out design analysis after production if phenomena, unexpected or unforeseen at the time of design, arise after a product is placed into service.
Using axiomatic design principles for the development of a device to measure the positioning error of an industrial robot
Authors: Cosmin Răzvan , Stavarache  , Ermolai Vasile , Irimia Alexandru , Etcu Mihaela 
Published: September 2021

Abstract
Robots are part of the integrated production process, being widely used in manufacturing processes, including the positioning of parts. One of the factors that influences the accuracy of the products to be machined is related to the errors of positioning the workpiece at each stage of manufacture. To determine the amplitude and the medium value of the positioning error, we used axiomatic design to develop a device capable of measuring positioning errors. The result was a constructive solution for a device capable of taking the positioning data of the end of the robot arm along three axes of a spatial coordinate system. In this way, data are recorded using dial comparators positioned on existing channels in the three walls corresponding to the corner of a cube-shaped box. Statistical processing of measurement results should provide information on the positioning accuracy of a workpiece by an industrial robot.
Design of Neural Networks
Authors: Mantri Pam , Thomas John 
Published: September 2021

Abstract
Artificial Neural Networks (ANN) and Deep Learning (DL) are used to solve complex problems including image recognition, speech recognition and have applications in new technologies for autonomous driving, facial recognition, detecting cancers from imaging samples among others. Various design considerations are involved in the design, training, and testing of Artificial Neural Networks (ANN). These include the design of the input/output layer, the structure and number of hidden layers, the data/data-structures of variables, the transformative functions embedded in the network, the optimizers being considered, the learning rate and its systematic adjustment, the prudent usage of dropout, the parallelism-related batch-size, the number of epochs, the adaptive logic for systematically changing the network for better fit, etc. While all these methods and techniques are sensible and relevant, there lacks an overarching framework for the needed design. This paper considers the design of an ANN from an Axiomatic Design (AD) perspective that parallels the biological inspiration for ANN’s in the first place, i.e., the brain. The axiomatic design approach is used for explicating and extricating the form, function, and adaptive evolution of the underlying network.