bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of VMD-LSTM in Water Quality Prediction
Authors: Tao Dongqing , Yang Yun , Cai Zhi , Duan Junlong , Lan Hao 
Published: May 2023

Abstract
Water is an indispensable prerequisite and essential factor for human life and social development. Change in water quality is closely related to water pollution. Water quality prediction is the basic work to control water environmental pollution. Therefore, the establishment of effective models is of great value to social economy, environmental protection and human health. This paper aims at the problem that the prediction error of relative maximum and relative minimum values of Long Short-Term Memory (LSTM) in dealing with time series is large, combined with the advantages of Variational Mode Decomposition(VMD) to extract signal fluctuation characteristics and reduce noise interference, Taking the Dissolved oxygen(DO) and the Total phosphorus(TP) as the main research objects, A combined model based on VMD-LSTM is proposed. The three indexes of Mean Absolute Error(MAE), Root Mean Square Error(RMSE) and Mean Absolute Percentage Error(MAPE) were used to judge. Experiments show that the VMD-LSTM model has improved all indicators compared with the LSTM model. DO prediction results respectively reduced by 38.8%, 41.4% and 44.4%, TP prediction results respectively reduced by 30.4%, 34.4% and 32.2%, the validity of the model is verified.
Graph-Clustering Anonymity Privacy Protection Algorithm With Fused Distance-Attributes
Authors: Wang Zhenxin , Liu Tao , Wang Yujie , Bao Xianglin , Xu Xiaofeng , Huang Xiangxiang , Cheng Bin 
Published: May 2023

Abstract
Clustering anonymity is a common social network data privacy protection scheme, which is based on graph-clustering. Many existing graph clustering methods mainly focus on the relationship between the structure and attributes of nodes, and the difference between them due to the metric usually causes the problem of poor clustering results. To address the shortcomings in the above graph-clustering methods, a graph-clustering anonymity method implemented with fused distance-attributes (GCA-DA) is proposed. Firstly, the algorithm quantifies the distance and attribute similarity between nodes separately and balances the metric differences between them to calculate the integrated similarity. Then all the nodes in the graph are clustered into clusters according to the integrated similarity between two nodes, each of which contains no fewer than k nodes. Finally, all the clusters are anonymized. In this method, the attribute generalization for every cluster can prevent attacks by the background knowledge of structure and attributes. In addition, the attributes are divided into numerical and non-numerical attributes to measure them separately, therefore can maintain the usability of the data better. Experiment results demonstrate the effectiveness in improving the quality of clustering and reducing information loss.
Index Correlation Analysis in Water Quality Monitoring Big Data
Authors: Li Hao , Yu Ziwen , Song Lingyu , Chen Xia , Tan WenWu , Li Peilun , Zhang Jianjun , Xiao Ke , Wang Li , Lin Haijun 
Published: May 2023

Abstract
Among the water quality indicators, permanganate and turbidity are important indicators to reflect the pollution status of water bodies. In order to study the correlation between the two, the water quality monitoring data of relevant water areas were obtained by designing a web crawler, and the water quality monitoring data set was constructed. After the data was cleaned, the correlation analysis was carried out. The experimental results show that there is a big difference in the correlation coefficient between the two indicators at different periods of the same monitoring point. The correlation between the two indicators in the abundant-water season is greater than that in the flat-water season, and the correlation between them in the flat-water season is greater than that in the poor-water season. Among them, there was a high positive correlation between the two indicators during the abundant-water season, and there is little correlation between them during the poor-water season.
A Multi-Objective Cloud Workflow Scheduling Strategy Based on the Modified HEFT Algorithm
Authors: Wang Heng , Deng Jianguang 
Published: May 2023

Abstract
Aiming at the issues of poor system resource utilization and the challenge of ensuring the quality of service (QoS) in scientific workflow scheduling in the current cloud computing environment. By combining the existing IaaS cloud resource model with the scientific workflow task model, the article proposed a cloud workflow scheduling model framework. Firstly, proposed multi-objective QoS constraints based on the execution time and costs in scientific workflow scheduling. Then, modified the HEFT algorithm which was a typical scientific workflow scheduling algorithm. Based on the modified HEFT algorithm makes full use of the idle time of resources and maximizes the multi-objective QoS requirements of users. The comparative experiments show that the scheduling strategy of the modified HEFT algorithm can effectively optimize the costs and execution time of scientific workflow scheduling and achieve higher system resource utilization.
Differential-Linear Cryptanalsis on SIMECK32/64 and SIMON32/64
Authors: Zhang Feng , Li Feng , Zhang Wenzheng 
Published: May 2023

Abstract
In this paper, we give differential-linear cryptanalysis of SIMON, which is a family of lightweight block ciphers published by the National Security Agency, and SIMECK, which is a family of lightweight block ciphers proposed by Yang et al. Firstly, all input difference and output masks with one active bit are traversed to obtain a 9-round SIMON32/64 differential-linear distinguisher and a 10-round SIMECK32/64 differential-linear distinguisher. Then, a 12-round SIMON32/64 differential-linear distinguisher with bias 2−12.69 and a 13-round SIMECK32/64 differential-linear distinguisher with bias 2−14.03 can be obtained by searching one round of differential characteristics forward and two rounds of linear approximations backward. The dynamic key guessing technique proposed by Wang et al. has excellent advantages in the SIMON-like cipher key recovery process. Therefore, we have applied it to differential-linear cryptanalysis. Then, the 12-round SIMON32/64 differential-linear distinguisher is extended forward by four rounds and backward by four rounds to attack the 20-round SIMON32/64 with time complexity 255.68 and data complexity 228. And the 13-round SIMECk32/64 differential-linear distinguisher is extended forward by four rounds and backward by four rounds to attack the 21-round SIMECK32/64 with time complexity 250.67 and data complexity 230. These are the best differential-linear cryptanalysis results for SIMON32/64 and SIMECK32/64 in the open literature.
Design of a composite collimator for the hard X-ray camera in HL-2M tokamak
Authors: Chen Hao , Zhao Chaoyang , Wang Zhonghai , Li Lingli , Zhou Yanhan , Zhang Jie , Xu Hongbing , Cheng Shikui , Zhu Yuxuan , Zhang Yipo 
Published: May 2023

Abstract
A new hard X-ray (HXR) camera is being designed for the
HuanLiu-2M (HL-2M) tokamak to measure the spatial-temporal evolution
of the fast electrons in the energy range of 20–200 keV during
radio frequency (RF) drive or heating experiments. The new camera
integrates 63 channels of independent detectors consisting of 63
lutetium yttrium oxyorthosilicate scintillators (LYSO) coupled to
silicon photomultipliers (SiPMs). A composite collimator (pinhole +
collimating tube) is designed for the HXR camera to arrange the 63
channels in a compact space and reduce background rays. This paper
introduces the design of composite collimator and the calculation of
geometric parameters of the pinhole and collimating tube. The
geometric factor uniformity (GFU) and effective count
rate (ECR) of the composite collimator were evaluated by
Geant4 simulation for different pinhole inner wall thicknesses
T
1. The results show that when the energy is 200 keV,
GFU increases and ECR increases and then
decreases when reducing T
1. The optimal T
1 is 2 mm, and
the resulting GFU is 0.83 and ECR is 78.2%
for 200 keV.
Free radical scavenging effects of grapefruit essential oil nanoemulsion stabilized with carrageenan and its cytotoxicity assay on HeLa cell line
Authors: Watcharin Waralee , Gupta Suman , Saning Amonrada , Laodheerasiri Sireerat , Chuenchom Laemthong 
Published: May 2023

Abstract
Grapefruit peel essential oil exhibited antioxidant and antibacterial activities attributed to their phenolic and flavonoid compounds. In this study, nanoemulsion of grapefruit peel essential oil and carrageenan was investigated for their antioxidant properties. The oil in water (o/w) emulsion was formulated with 0.5% and 1.0% (w/v) grapefruit peel essential oil and carrageenan. Carrageenan was utilised as an encapsulating agent to decrease volatility of essential oil and increase its stability. The resulting nanoemulsion was characterised using transmission electron microscopes (TEM), ultraviolet–visible (UV–vis) spectrophotometry and Fourier-transform infrared spectroscopy (FTIR). Nanoemulsion formulated with 0.5% grapefruit peel essential oil exhibited strong radical scavenging 2,2-diphenyl-1-picrylhydrazyl (DPPH) effects showing the highest half maximal effective concentration value (EC50) at 83.4 ± 1.4 mg l−1 and revealed the highest total phenolic content (80.1 ± 11.8 mg GAE/g) in comparison with 1.0% grapefruit peel essential oil-nanoemulsion and free grapefruit peel essential oil (2.0% w/v). The cytotoxicity of nanoemulsion prepared from grapefruit peel essential oil against HeLa cells also exhibited higher than 90% of cell viability, which was not affected by the formulation of nanoemulsion. The incorporation of grapefruit peel essential oil into nanoemulsion improved its stability while retaining its bioactivity and non-toxicity.
Stretchable kirigami-inspired conductive polymers for strain sensors applications
Authors: Abbasipour Mina , Kateb Pierre , Cicoira Fabio , Pasini Damiano 
Published: May 2023

Abstract
Kirigami metamaterials can be exploited in stretchable electronics owing to their architecture, which can be leveraged to amplify stretchability, bendability and deformability. Herein, we report a stretchable kirigami-structured poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS)/polydimethylsiloxane (PDMS) polymer composite. The electromechanical response and mechanical behavior of kirigami PEDOT:PSS-coated PDMS and polymer composite specimens were investigated and compared with their non-kirigami counterparts. The kirigami structure exhibited improved electromechanical properties owing to its characteristic architecture. This study illustrates the application of a kirigami polymer composite as a strain sensor for human motion detection.
Temperature-induced hysteresis in amplification and attenuation of surface-plasmon-polariton waves
Authors: Mackay Tom G , Son Tran Vinh , Haché Alain , Lakhtakia Akhlesh 
Published: May 2023

Abstract
The propagation of surface-plasmon-polariton (SPP) waves at the planar interface of a metal and a dielectric material was investigated for a dielectric material with strongly temperature-dependent constitutive properties. The metal was silver and the dielectric material was vanadium multioxide impregnated with a combination of active dyes. Depending upon the volume fraction of vanadium multioxide, either attenuation or amplification of the SPP waves may be achieved; the degree of attenuation or amplification is strongly dependent on both the temperature and whether the temperature is increasing or decreasing. At intermediate volume fractions of vanadium multioxide, for a fixed temperature, a SPP wave may experience attenuation if the temperature is increasing but experience amplification if the temperature is decreasing.
Climate concern elasticity of carbon footprint
Authors: Leferink Enar Kornelius , Heinonen Jukka , Ala-Mantila Sanna , Árnadóttir Áróra 
Published: May 2023

Abstract
The income elasticity of carbon footprint is a summary variable often used to describe the relationship between income and carbon footprints. Previous studies primarily calculate this elasticity using emissions intensities per monetary unit. However, this study is based on a survey conducted in Nordic countries which allows us to directly calculate carbon footprints from responses about quantity and types of activities instead of from spending. As a result, we curtail an inbuilt relationship between income and carbon footprints. As a result, our method produces an income elasticity estimate that is approximately one-fourth of the highest estimates that exist, and 30% lower than the smallest current estimate. Furthermore, we introduce a new summary variable called the climate concern elasticity of carbon footprint. This variable provides a simple method to analyze the relationship between pro-climate attitudes, pro-climate behavior, and carbon footprints. This new parameter can serve as a framework that identifies key areas where the investigation of the relationship between people’s climate concern and their carbon footprint may be most useful. This framework and improved knowledge of income elasticities can guide policymakers and future research and provide new methods to estimate carbon footprint distributions.
Robotic in situ bioprinting for cartilage tissue engineering
Authors: Wang Yaxin , Pereira Rúben F , Peach Chris , Huang Boyang , Vyas Cian , Bartolo Paulo 
Published: May 2023

Abstract
Articular cartilage damage caused by trauma or degenerative pathologies such as osteoarthritis can result in significant pain, mobility issues, and disability. Current surgical treatments have a limited capacity for efficacious cartilage repair, and long-term patient outcomes are not satisfying. Three-dimensional bioprinting has been used to fabricate biochemical and biophysical environments that aim to recapitulate the native microenvironment and promote tissue regeneration. However, conventional in vitro bioprinting has limitations due to the challenges associated with the fabrication and implantation of bioprinted constructs and their integration with the native cartilage tissue. In situ bioprinting is a novel strategy to directly deliver bioinks to the desired anatomical site and has the potential to overcome major shortcomings associated with conventional bioprinting. In this review, we focus on the new frontier of robotic-assisted in situ bioprinting surgical systems for cartilage regeneration. We outline existing clinical approaches and the utilization of robotic-assisted surgical systems. Handheld and robotic-assisted in situ bioprinting techniques including minimally invasive and non-invasive approaches are defined and presented. Finally, we discuss the challenges and potential future perspectives of in situ bioprinting for cartilage applications.
Strain localization in wearable integrated electronics using dot pattern
Authors: Hajizadeh Pouria , Naserifar Naser 
Published: May 2023

Abstract
Sensors and actuators can now achieve high levels of stretchability and functionality owning to the recent development of stretchable electronics. One main factor in creating high-performance stretchable electronics that can be adequately transferred to curved surfaces, such as human skin, is the conformal design of the island-bridge model. In island-bridge models, interconnect conductors (bridges) are the most vulnerable. Thus, it is necessary to preserve the durability and functionality of interconnect conductors under high strains. In this study, by transferring dots to the main substrate, the interconnect conductors can be protected. This causes the strain to become localized in the region between the two neighboring islands. This region is known as safe region. In the safe region, the strains bypass the other side of the stretchable electronic from the upper and lower parts. This objective was achieved using the experimental tensile test and finite element analysis. These results displayed a 4% − 9% reduction in the average strain of safe region while applying 10% − 30% strain. The design parameters were optimized with energy release rate measurement. Additionally, the interconnect conductors’ path in the safe region was optimized improving this value to at least 50% below its applied strain. This design made the stretchable electronic significantly durable while maintaining its functionality.
Shape sensing of optical fiber Bragg gratings based on deep learning
Authors: Manavi Roodsari Samaneh , Huck-Horvath Antal , Freund Sara , Zam Azhar , Rauter Georg , Schade Wolfgang , Cattin Philippe C 
Published: May 2023

Abstract
Continuum robots in robot-assisted minimally invasive surgeries provide adequate access to target anatomies that are not directly reachable through small incisions. Achieving precise and reliable shape estimation of such snake-like manipulators necessitates an accurate navigation system, that requires no line-of-sight and is immune to electromagnetic noise. Fiber Bragg grating (FBG) shape sensing, particularly eccentric FBG (eFBG), is a promising and cost-effective solution for this task. However, in eFBG sensors, the spectral intensity of the Bragg wavelengths that carries the strain information can be affected by undesired bending-induced phenomena, making standard characterization techniques less suitable for these sensors. We showed in our previous work that a deep learning model has the potential to extract the strain information from the eFBG sensor’s spectrum and accurately predict its shape. In this paper, we conducted a more thorough investigation to find a suitable architectural design of the deep learning model to further increase shape prediction accuracy. We used the Hyperband algorithm to search for optimal hyperparameters in two steps. First, we limited the search space to layer settings of the network, from which, the best-performing configuration was selected. Then, we modified the search space for tuning the training and loss calculation hyperparameters. We also analyzed various data transformations on the network’s input and output variables, as data rescaling can directly influence the model’s performance. Additionally, we performed discriminative training using the Siamese network architecture that employs two convolutional neural networks (CNN) with identical parameters to learn similarity metrics between the spectra of similar target values. The best-performing network architecture among all evaluated configurations can predict the shape of a 30 cm long sensor with a median tip error of 3.11 mm in a curvature range of 1.4 m−1 to 35.3 m−1.
Low-dimensional optoelectronic synaptic devices for neuromorphic vision sensors
Authors: Lv Chengzhai , Zhang Fanqing , Li Chunyang , Li Zhongyi , Zhao Jing 
Published: May 2023

Abstract
Neuromorphic systems represent a promising avenue for the development of the next generation of artificial intelligence hardware. Machine vision, one of the cores in artificial intelligence, requires system-level support with low power consumption, low latency, and parallel computing. Neuromorphic vision sensors provide an efficient solution for machine vision by simulating the structure and function of the biological retina. Optoelectronic synapses, which use light as the main means to achieve the dual functions of photosensitivity and synapse, are the basic units of the neuromorphic vision sensor. Therefore, it is necessary to develop various optoelectronic synaptic devices to expand the application scenarios of neuromorphic vision systems. This review compares the structure and function for both biological and artificial retina systems, and introduces various optoelectronic synaptic devices based on low-dimensional materials and working mechanisms. In addition, advanced applications of optoelectronic synapses as neuromorphic vision sensors are comprehensively summarized. Finally, the challenges and prospects in this field are briefly discussed.
Parenteral medication considerations for the ketogenic diet
Authors: Abu-Sawwa Renad , Busque Katherine , Cokley Jon 
Published: May 2023

Abstract

Purpose
This initiative conducted a needs assessment regarding the extent of potential risk for accidental carbohydrate exposure in patients on the ketogenic diet in acute care settings at 2 academic medical centers.

Summary
Medications used in the emergency department, intensive care unit, or operating room can contain carbohydrates or be diluted in carbohydrate-containing fluids. Use of these medications can shift patients on the ketogenic diet out of ketosis, causing breakthrough seizures. Despite standard clinical practices, there are no consensus guidelines to date for the logistical management of these patients during hospital admissions. This lack of standardized management increases the risk for parenteral medication errors during transitions within the healthcare system. A review of the literature demonstrates increased medication safety errors compounded by this lack of systemwide endeavors. Initiatives enhancing provider education and quality improvement safety measures have been reported; however, the extent of the potential risk with regard to medication formulation has not been assessed. Fifty medications were evaluated for their potential risk for carbohydrate exposure in a real-world quality improvement needs assessment conducted at 2 academic medical centers.

Conclusion
Because of increased exposure to carbohydrate-containing medications and medication safety errors, the authors recommend developing institutional protocols, an order set in the electronic medical record, and a multidisciplinary approach for patients on the ketogenic diet. Further research is warranted to assess the impact of these quality improvement measures on safety and clinical outcomes and to justify the development and implementation of consensus guidelines in centers of excellence that serve these patients.
Developmental dynamics of crassulacean acid metabolism (CAM) in Opuntia ficus-indica
Authors: Niechayev Nicholas A , Mayer Jesse A , Cushman John C 
Published: May 2023

Abstract

Background and Aims
The relative contributions of C3 photosynthesis and crassulacean acid metabolism (CAM) during the earliest stages of development were investigated to assess how much each might contribute to cactus pear (Opuntia ficus-indica) productivity.

Methods
The developmental progression of C3 photosynthesis and CAM was assessed in seedlings and daughter cladodes of mature plants by titratable acidity, δ13C isotopic values and diel gas exchange measurements.

Key Results
Nocturnal acidification was observed in seedling cladodes and cotyledons at the earliest stages of development and became highly significant by 75 days of development. Seedling cotyledons showed mean δ13C values of −21.4 and −17.1 ‰ at 30 and 100 days of age, respectively. Seedling cladodes showed mean δ13C values of −19.4 and −14.5 ‰ at 30 and 100 days of age, respectively. These values are typical of CAM plants. Net CO2 assimilation was negative, then occurred in both the day and the night, with nighttime fixation becoming predominant once the primary cladode reached 5 cm in size. Emergent daughter cladodes growing on mature plants showed nocturnal titratable acidity at the earliest stages of development, which became significant when daughter cladodes were &gt;2.5–5 cm in height. Emergent daughter cladodes showed mean δ13C values of −14.5 to −15.6 ‰, typical of CAM plants. CO2 assimilation studies revealed that net CO2 uptake was negative in daughter cladodes &lt;12 cm in length, but then exhibited net positive CO2 assimilation in both the day and the night, with net nocturnal CO2 assimilation predominating once the daughter cladode grew larger.

Conclusions
Developing O. ficus-indica primary and daughter cladodes begin as respiring sink tissues that transition directly to performing CAM once net positive CO2 fixation is observed. Overall, these results demonstrate that CAM is the primary form of photosynthetic carbon assimilation for O. ficus-indica even at the earliest stages of seedling or daughter cladode development.