bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficacy of bilateral lower limb training over unilateral to re-educate balance and walking in post stroke survivors: a protocol for randomized clinical trial
Authors: Harjpal Pallavi , Qureshi Mohd Irshad , Kovela Rakesh Krishna 
Published: May 2021

Abstract
Background: Stroke is the leading cause of global morbidity and a major contributor to disability. According to the National Stroke Association, as many as 9 out of 10 stroke survivors have some degree of paralysis immediately after the stroke. Aim is to evaluate the level to which the bilateral lower limb training compared to unilateral alone, reinforces the lower limb functional recovery in the subjects with sub-acute stroke.Methods: The participants (n=40) with subacute stroke will be included in assessor blinded, randomized clinical trial. Participants will be categorized into 2 groups after performing baseline assessments and equal randomization. The participants in Group A will receive only training to the affected side, and those in the Group B will receive bilateral training. We will be evaluating the improvement in lower limb function by balance and walking along with gait parameters.Discussion: Findings of the study will provide further insight into the effectiveness of bilateral training over unilateral in post stroke survivors. If this study is proved to be effective it will improve the balance and gait impairments in post stroke patients.The clinical trial registry-India(CTRI) registration number for this trial is CTRI/2021/05/033621.
Understanding the benefits and burdens associated with a Malaria Human Infection Study in Kenya: Experiences of study volunteers and other stakeholders
Authors: Chi Primus Che , Owino Esther Awuor , Jao Irene , Olewe Fredrick , Ogutu Bernhards , Bejon Philip , Kapulu Melissa , Kamuya Dorcas , Marsh Vicki 
Published: May 2021

Abstract
Background Human infection studies that involve deliberately infecting healthy volunteers with a pathogen raise important ethical issues, including the need to ensure that benefits and burdens are understood and appropriately accounted for. Building on earlier work, we embedded social science research within an ongoing malaria human infection study in coastal Kenya to understand the study benefits and burdens experienced by study stakeholders in this low-resource setting and assess the wider implications for future research planning and policy. Methods Data were collected using qualitative research methods, including in-depth interviews (44), focus group discussions (10) and non-participation observation. Study participants were purposively selected (key informant or maximal diversity sampling), including volunteers in the human infection study, study staff, community representatives and local administrative authorities. Data were collected during and up to 18 months following study residency, from sites in Coastal and Western Kenya. Voice recordings of interviews and discussions were transcribed, translated and analysed using Framework Analysis, combining data- and theory-driven perspectives. Findings Physical, psychological, economic and social forms of benefits and burdens were experienced across study stages. Important benefits for volunteers included the study compensation, access to health checks, good residential living conditions, new learning opportunities, developing friendships and satisfaction at contributing towards a new malaria vaccine. Burdens primarily affected study volunteers, including experiences of discomfort and ill-health; fear and anxiety around aspects of the trial process, particularly deliberate infection and the implications of prolonged residency; anxieties about early residency exit and interpersonal conflict. These issues had important implications for volunteers’ families, study staff and the research institution’s reputation more widely. Conclusion Developing ethically and scientifically strong HIS relies on grounded accounts of volunteers, study staff and the wider community, understood in the socioeconomic, political and cultural context where studies are implemented. Recognition of the diverse, and sometimes perverse, nature of potential benefits and burdens in a given context, and who this might implicate, is critical to this process. Prior and on-going stakeholder engagement is core to developing these insights, which can be importantly expanded and underlined through embedded forms of social science research.
Representation of Rossby wave propagation and its effect on the teleconnection between the Indian summer monsoon and extratropical rainfall in the Met Office Unified Model
Authors: Tang Xinxin , Li Jianping , Zhang Huqiang , Zhao Sen 
Published: May 2021

Abstract
Compared with Global Atmosphere 6 (GA6) of the UK Met Office Unified Model (UM), the dry bias over the Indian monsoon region in Global Atmosphere 7 (GA7) is significantly reduced. However, the physical processes controlling how this reduced dry bias in India influences rainfall teleconnections in the extratropics remain unclear. Thus, in this study, we use Rossby wave tracing in a horizontally nonuniform background flow to investigate how the improved simulation of monsoon rainfall in GA7 compared with GA6 affects extratropical rainfall teleconnections. We find that wave rays emanating from the upper troposphere in the Indian monsoon region first propagate westward, then divide into the Northern Hemisphere (NH) subtropical westerlies over Asia and the Southern Hemisphere (SH) subtropical westerlies. The wave ray trajectories in GA7 in years of strong Indian summer monsoon rainfall (ISMR) are closer to observations than those in GA6. We also find that the upper tropospheric meridional winds over the South Asian monsoon region and western Tibetan Plateau are much better simulated in GA7 than in GA6 owning to the improvement of ISMR and South Asian High (SAH), which leads to a more realistic simulation of the wave rays in GA7. The better simulated circulation teleconnections in GA7 then modulate the vertical motion and moisture transport, and hence affect extratropical rainfall anomalies in the NH and SH. This paper provides new insights for the assessment of tropical–extratropical teleconnections in models.
An Ensemble Hybrid forecasting Model for Annual Runoff Based on Sample Entropy, Secondary Decomposition, and Long Short-Term Memory Neural Network
Authors: Wang Wenchuan , Du Yu-jin , Chau Kwok-wing , Xu Dong-mei , Liu Chang-jun , Ma Qiang 
Published: May 2021

Abstract
Accurate and consistent annual runoff prediction in regions is a hot topic in the management, optimization, and monitoring of water resources. A novel prediction model (ESMD-SE-WPD-LSTM) is presented in this study. Firstly, the extreme-point symmetric mode decomposition (ESMD) is used to produce several intrinsic mode functions (IMF) and a residual (Res) by decomposing the original runoff series. Secondly, the sample entropy (SE) method is employed to measure the complexity of each IMF. Thirdly, we adopt wavelet packet decomposition (WPD) to further decompose the IMF with the maximum SE into several appropriate components and detailed components. Then the LSTM model, a deep learning algorithm based recurrent approach, is employed to predict all components obtained in the previous step. Finally, the forecasting results of all components are aggregated to generate the final prediction. The proposed model, which is applied to five annual series from different areas in China, is evaluated based on four quantitative indexes (R, NSEC, MAPE and RMSE). The results indicate that the ESMD-SE-WPD-LSTM outperforms other benchmark models in terms of four quantitative indexes. Hence the proposed model can provide higher accuracy and consistency for annual runoff prediction, making it an efficient instrument for scientific management and planning of water resources.
Experimental demonstration of NO reduction and ammonia slip for diesel engine SCR system
Authors: Yue Guangzhao , Qiu Tao , Lei Yan 
Published: May 2021

Abstract
This paper aims to investigate the characteristics of selective catalytic reduction(SCR) in a V2O5-WO3/TiO2 catalyst by studying the key parameter, and obtain the control method of NH3 injection under sample test bench. Four parameters are defined and adopted to represent the NO-NH3 reaction characteristics. The effect of NH3/NO ratio(NSR), catalyst temperature and NH3 injection period on NO conversion efficiency and NH3 slip was investigated. The correlation between NH3 slip and ammonia saturation storage level was studied. The experimental results show that the ammonia saturation storage level has great effects on NO reduction and NH3 slip. The NO conversion efficiency and NH3 slip strongly depends on the ammonia saturation storage level. Under such condition, the NO conversion efficiency is best when the ammonia saturation storage level is 68.2%~73%, until the value reach to 75% before the NH3 slip. Pulse injection can improve the NO conversion efficiency and NH3 slip. The period of pulse injection has few influence on the mean value of NO at the outlet, however, it affects the peak value of NO and NH3 slip. Using varied period pulse injection can further improve NO conversion efficiency and restrain NH3 slip. The outlet NO is able to be reduced by adopting suitable NH3 pulse injection interval.
Efficient Prediction of Bridge Conditions using Modified Convolutional Neural Network
Authors: Kumar Amit , Singla Sandeep , Kumar Ajay , Bansal Aarti , Kaur Avneet 
Published: May 2021

Abstract
Artificial Intelligence (AI) technology has proved itself as a proficient substitute for classical techniques of modeling. AI is a branch of computer science with the help of which machines and software with intelligence similar to humans can be developed. Many problems related to structural as well as civil engineering are exaggerated with uncertainties that are difficult to be solved using traditional techniques. AI proves advantageous in solving these complex problems. Presently, a comprehensive model based on the Convolutional Neural Network technique of Artificial Intelligence is developed. This model is advantageous in accurately predicting the structure of a bridge without the need for actual testing. The firefly algorithm is used as a technique for accurate feature selection. The database is taken from national bridge inventory (NBI) using internet sources. Different performance measures like accuracy, recall, precision, and F1 score are considered for accurate prediction of the bridge structure and also provide advantages in actual monitoring and controlling of bridges. The proposed CNN model is used to measure these parameters and to provide a comparison with the standard CNN model. The proposed model provides a considerable amount of accuracy (97.49 %) as compared to accuracy value (85 %) using the standard CNN model.
Matrix condition mitigates the effects of habitat fragmentation on species extinction risk
Authors: Ramírez-Delgado Juan , Marco Moreno Di , Watson James , Johnson Chris , Rondinini Carlo , Llano Xavier Corredor , Arias Miguel , Venter Oscar 
Published: May 2021

Abstract
Habitat loss is the leading cause of global biodiversity decline, but the influence of human pressure within the matrix surrounding habitat fragments remains poorly understood. Here we measure the relationship between fragmentation, matrix condition (measured as the extent of high human footprint levels), and the change in extinction risk of 4,327 terrestrial mammals. We find that the matrix condition and the fragmentation of habitat are strongly associated with changes in species extinction risk. Importantly, we discover that fragmentation is a stronger predictor of risk than species life-history traits, habitat loss, and habitat amount. Moreover, the importance of fragmentation increases with an increasing deterioration of the matrix condition, highlighting the critical influence matrix quality plays on the effects of fragmentation. These findings suggest that restoration measures in habitat matrices may be an important conservation action for mitigating the effects of fragmentation relative to extinction risk of terrestrial mammals.
Singular Integral Equations in Scattering of Planar Dielectric Waveguide Eigenwaves by the System of Graphene Strips at THz
Authors: Kaliberda Mstislav E. , Lytvynenko Leonid M. , Pogarsky Sergey A. 
Published: May 2021

Abstract
We consider the scattering of the H-polarized eigenwaves of a planar dielectric waveguide by a coplanar system of graphene strips in the THz range. The strips are placed along the centerline of the waveguide. Our treatment is based on the singular integral equations with the Nystrom-type discretization algorithm. Dependences of the scattering characteristics, near and far fields are studied. Frequency scanning radiation pattern are presented. Maximum of the radiated power is observed near the plasmon resonances. The resonant frequency and main lobe level can be controlled by variation of the chemical potential. Applied optimization procedure allows to obtain the radiation pattern with the side-lobe level less than -20 dB. The presented results can be used in designing of graphene leaky-wave antennas.
Fatigue Design Curves for Laser-Metal-Deposited Type 420 Stainless Steel and Effect of an Interval during Deposition Process
Authors: Uematsu Yoshihiko , Sasaki Ryosuke , Kakiuchi Toshifumi , Yamamoto Seiei , Zensho Akihiro , Sano Ri-ichiro 
Published: May 2021

Abstract
Fully-reversed axial loading fatigue tests were conducted using type 420J1 martensitic stainless steel. The specimens were additively manufactured by a laser metal deposition (LMD) process. The results were compared with conventionally-manufactured (CMed) type 420J2 stainless steel. According to the axial loading fatigue test results, the fatigue strengths of the laser-metal-deposited (LMDed) specimens were nearly comparable to those of the CMed specimens. Fractographic analyses revealed that process-induced defects were hardly seen at the fatigue crack initiation sites of the LMDed specimens. It indicates that defect-free deposition was possible by the LMD process. On the other hand, when the LMD specimens experienced intervals during deposition processes, local softening occurred due to the tempering of the building plate. Fatigue tests revealed that the interval during LMD process had detrimental effect on the fatigue strengths due to the local softening. The upper and lower bounds of S-N curves were proposed as fatigue design curves for the samples with and without the interval during LMD process.
Life Cycle Assessment of Irish District Heating Systems: A Comparison of Waste Heat Pump, Biomass-Based and Conventional Gas Boiler
Authors: Mahon Conall , Mediboyina Maneesh Kumar , Gartland Donna , Murphy Fionnuala 
Published: May 2021

Abstract
This paper presents a life cycle assessment (LCA) of heat supply scenarios for the replacement of fossil-based energy systems through a case study focusing on an existing gas-fired boiler supplying heat for buildings located in Tallaght, Ireland. The three replacement systems considered are a waste heat fed heat pump district heating system (WHP-DH), a biomass CHP plant district heating system (BCHP-DH), and an individual gas boiler system (GB). The study found that both DH systems have lower environmental impact than the GB, with the BCHP-DH being superior to WHP-DH. However, using 2030 electricity data showed almost similar overall impacts for both the DH systems. Human toxicity potential (HTP) was highest among all impact categories studied and was due to the large additional infrastructure requirement for all three systems. Whereas the other impacts; Global warming (GWP), Fossil fuel depletion (FFD) and Eutrophication (EP), were due to involving usage of natural gas and electricity in use phase. The BCHP-DH showed reduced greenhouse gas (GHG) emissions by 45% and FFD by 73% compared to the GB system. Using 2030 electricity data, the WHP-DH decreased GHG emissions by 42% and FFD by 47%. Further, replacing biomethane with the natural gas in the DH systems decreased GWP by at least 11.4%. The present study concludes that the environmental benefit of a DH system is largely dependent on the carbon intensity of the electricity it uses, thus recommending the DH systems for large scale retrofitting schemes in Ireland to reach Europe’s 2030 GHG reduction targets.
Developing a theory-based behavior change intervention to improve the prescription of surgical prophylaxis
Authors: Lohiniva Anna-Leena , Heweidy Iman , Abdu Samiha , Omar Abouelata , Ackley Caroline , Samir Shady , Talaat Maha 
Published: May 2021

Abstract
Background: Antimicrobial resistance (AMR) is increasingly pervasive due to multiple, complex prescribing and consuming behaviours. Accordingly, behaviour change is an important component of response to AMR. Little is known about the best approaches to change antibiotic use practices and behaviours. Aim: This project aims to develop a context-specific behaviour change strategy focusing on promoting appropriate prescription practices following the World Health Organization recommendations for surgical prophylaxis. in an orthopaedic surgery unit in Egypt. Methods: The project included a formative qualitative research study was based on the Theoretical Domains Framework (TDF) and an intervention that was developed to following the Behaviour Change Wheel (BCW) in a knowledge co-production workshop that ensured that the theory based intervention was a culturally acceptable, practical and implementable intervention. Results: The prescription of surgical prophylaxis was influenced by five TDF domains including, knowledge, belief in consequences (mistrust towards infection prevention and control measures), environmental factors (lack of prescription guidelines) , professional role and reinforcement (a lack of appropriate follow up actions influenced prescription of surgical prophylaxis). The appropriate set of behaviour change functions of BCW and related activities to improve the current practices included education, enablement, persuasion, environmental restructuring and restriction. Conclusions: The study showed that a theory based and context specific intervention can be created by using the TDF and BCW together with knowledge-co creation to improve the prescription of surgical prophylaxis in and Egyptian orthopaedic unit. The intervention need to piloted and scaled up.
Analysis and Research on Blasting Network Delay of Deep-Buried Diversion Tunnel Crossing Fault Zone Based on EP-CEEMDAN-INHT
Authors: Wu Jing , Wu Li , Sun Miao , Lu Ya-ni , Han Yan-hua 
Published: May 2021

Abstract
The Empirical Mode Decomposition (EMD) of blasting seismic wave monitoring signal with noise can get IMFs with serious mode confusion and divergent end points. The Hilbert transform is constrained by the Bedrosian theorem, when it dealing with such IMFs will get negative instantaneous frequency, which leads to serious error in the identification of non-electric millisecond detonator initiation delay. EP-CEEMDAN-INHT is proposed and applied to the delay analysis of blasting network of deep buried diversion tunnel crossing fault zone. Comparing EP-CEEMDAN-INHT with EMD-HHT, it is found that EP-CEEMDAN-INHT can clearly display the time-frequency information contained in the measured blasting vibration signal, and EMD mode confusion and endpoint effect are well suppressed. The actual millisecond time interval obtained by EP-CEEMDAN-INHT can judge whether the detonator is in normal service. At the same time, the blasting millisecond interval with the best damping effect is 54.51ms to 59.75ms, which can realize the optimization of blasting network and has important practical significance for blasting safety control.
Study on the Dynamic Responses of Tunnel Linings with Small Net Distance Under Bias Pressures Caused by Blasting
Authors: Zhang Yabin , Fei Yang , Linyan Huang 
Published: May 2021

Abstract
The mutual influence of the parallel excavation of the tunnel can not be ignored. The control of the distance between the faces of the two tunnels is also a difficult point in the construction process. Taking the Nanshan Tunnel of Tieben Expressway in Liaoning Province as the background, the blasting simulation research was carried out under the conditions of different distances between the tunnel faces. Firstly, based on the field test data, the blasting conditions under different tunnel faces were simulated by numerical simulation. The research shows that: (1) The velocity effect of the preceding hole on the subsequent hole is embodied as: the smaller the distance between the face of the tunnel, the more obvious the velocity effect of the subsequent hole; the velocity effect of the subsequent hole on the preceding hole is mainly reflected in the change of the velocity propagation process; (2) The influence of the leading hole on the displacement of the trailing hole is mainly reflected in the following: the greater the distance between the tunnel faces, the later the peak appears, and the smaller the displacement peak; the influence of the trailing hole on the displacement of the leading hole is mainly reflected in the following: the greater the distance between the tunnel faces, the smaller the peak displacement.
Genetic Algorithm-based Task Allocation in Multiple Modes of Human-Robot Collaboration Systems with Two Cobots
Authors: Liau Yee Yeng , RYU Kwangyeol 
Published: May 2021

Abstract
In this paper, we introduce a human-robot collaboration (HRC) mold assembly cell to cope with small-volume mold production and reduce the risk of musculoskeletal disorders (MSDs) on a human worker during manual mold assembly operation. Besides, the wide variety of types and weights of the mold components motivated us to design an HRC system that consists of two robots. Therefore, we propose two collaboration modes for HRC systems using two robots and develop a task-allocation model to demonstrate the application of these collaboration modes in the mold assembly. The task-allocation model assigns a task based on the task characteristics and capability of agents in the collaboration cell. First, we decompose the assembly operation into functional actions to analyze the characteristics of tasks. Then, we obtain the agent assignment preference based on task characteristics and capability of agents using the analytic network process. Finally, we apply the genetic algorithm in the final task allocation to minimize assembly time, use of a less capable agent, and ergonomic risk. This paper contributes to expanding the HRC system with two robots in the mold assembly to allow the execution of a greater diversity of tasks and improve the assembly time and MSD risk level for the human worker.