bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blockchain based Multi-signature Smart Contract Electronic Seal Orienting Mobile IoT Terminals
Authors: Liu Chunyan , Feng Tao 
Published: October 2023

Abstract
The surging interest in digitalization has revitalized research for digital business model. Mobile Internet of Things (IoT) terminals will reach billions and become an important infrastructure for a digital and intelligent society. In the digital business model of IoT terminals, the electronic seal of commercial contracts are especially investigated to provide same level security as guaranteed by the traditional seal. However, the existing electronic seal is only applicable to the centralized network applications, which severely rely on the certificate authority. In this paper, we propose a blockchain based multi-signature smart contract electronic seal. The key of our design is to deploy a smart contract of business parties on Ethereum for secure electronic seal orienting mobile IoT terminals. Unlike traditional seal, this electronic seal is verified and managed collectively by all mining nodes. Combining it with the optimization in terms of a multi-signature algorithm encoded in smart contract, our design achieves complete digital contract function in all business participants of terminals. As an example, we show an implementation of Goerli testnet of the Ethereum network with the smart contract deployment. The security analysis and evaluation demonstrate that our design is secure of its multi-signature and can be used in practice.
Biomolecular condensates form spatially inhomogeneous network fluids
Authors: Pappu Rohit , Dar Furqan , Cohen Samuel , Mitrea Diana , Philips Aaron , Nagy Gergely , Leite Wellington , Stanley Christopher , Choi Jeon-Mo , Kriwacki Richard 
Published: October 2023

Abstract
The functions of biomolecular condensates are thought to be influenced by their material properties, and these are in turn determined by the multiscale structural features within condensates. However, structural characterizations of condensates are challenging, and hence rarely reported. Here, we deploy a combination of small angle neutron scattering, fluorescence recovery after photobleaching, and bespoke coarse-grained molecular dynamics simulations to provide structural descriptions of model condensates that mimic nucleolar granular components (GCs). We show that facsimiles of GCs are network fluids featuring spatial inhomogeneities across hierarchies of length scales that reflect the contributions of distinct protein and peptide domains. The network-like inhomogeneous organization is characterized by a coexistence of liquid- and gas-like macromolecular densities that engenders bimodality of internal molecular dynamics. These insights, extracted from a combination of approaches, suggest that condensates formed by multivalent proteins share features with network fluids formed by associative systems such as patchy or hairy colloids.
Dynamic behaviour and formation mechanism of shear band during high speed cutting Inconel 718
Authors: Hao Zhaopeng , Wang Xindi , Fan YiHang 
Published: October 2023

Abstract
Abastract

In this paper, the shear zone storage energy model and strain gradient theory were compiled into a subroutine for secondary development to implement multi-scale finite element simulations. The shear zone storage energy was analyzed based on the variation of stress, temperature, and overall dislocation density. The plastic deformation behavior occurred in cutting was analyzed by combining microscopic and macroscopic based on the change of storage energy in the shear zone. The dynamic recrystallization and periodic fracture theories were also correlated with the variation of shear zone storage energy to investigate the mechanism of adiabatic shear zone formation in depth. It was found that the overall dislocation density, stress and shear zone storage energy change in the same trend, and the temperature and shear zone storage energy change in the opposite trend. The proliferation and annihilation of dislocations affect the change of storage energy. The storage energy reaches a peak of 9.6704 KJ when the overall dislocation density increases to a critical value of 7.7664×109, during which the stress gradually increases to 1.920×109Mpa. The local interaction between geometric dislocations and grain boundaries will contribute to the increase of stored dislocations due to local work hardening, which causes spontaneous deformation instability and thus the gradual formation of deformation zones. When the shear zone temperature reaches a peak of 886°C, the stress gradually decreases to 6.27×108Mpa. The aggravation of the stress concentration phenomenon caused the workpiece to release a large amount of heat energy because it could not bear the excessive strain, and the resulting thermal softening effect caused the hardness to decrease. At the same time, dislocations accumulate and new dislocation sources in the vicinity were activated, which caused the overall dislocation density to start decreasing and the material to undergo local shear instability, thus leading to dynamic recrystallization and the formation of a phase transition zone at high temperature. The storage energy decreases to a trough value of 3.1555 KJ when the overall dislocation density decreases to 2.5342×109. Dynamic recrystallization happens at different stages due to the change of storage energy, and the rate of storage energy change will affect the nucleation rate of dynamic recrystallization and thus the rate of adiabatic shear zone formation.
Pten and P-4e-bp1 Might be Associated with Postoperative Recurrence of Rectal Cancer Patients Undergoing Concurrent Radiochemotherapy
Authors: Zhang Heng , Li Xiaofan , Sun Wanjun , Qin Haoren , Li Haipeng , Yan Hao , Wang Huaqing , Zhang Xipeng , Zhang Shiwu , Wang Hui 
Published: October 2023

Abstract
Background
Local recurrence after surgery and radiochemotherapy seriously affects the prognosis of locally advanced rectal cancer (LARC) patients. Studies on molecular markers related to the radiochemotherapy sensitivity of cancers have been widely carried out, which might provide valued information for clinicians to carry out individual treatment.
Aim
To find potential biomarkers of tumors for predicting postoperative recurrence.
Methods
In this study, LARC patients undergoing surgery and concurrent radiochemotherapy were enrolled. We focused on clinicopathological factors and PTEN, SIRT1, p-4E-BP1, and pS6 protein expression assessed by immunohistochemistry in 73 rectal cancer patients with local recurrence and 76 patients without local recurrence.
Results
The expression of PTEN was higher, while the expression of p-4E-BP1 was lower in patients without local recurrence than in patients with local recurrence. Moreover, TNM stage, lymphatic vessel invasion (LVI), PTEN and p-4E-BP1 might be independent risk factors for local recurrence after LARC surgery combined with concurrent radiochemotherapy.
Conclusions
This study suggests that PTEN and p-4E-BP1 might be potential biomarkers for prognostic prediction and therapeutic targets for LARC.
Transcutaneous carbon dioxide improves joint inflammation and articular cartilage degeneration in rat osteoarthritis models
Authors: Li Changxin , Moriyama Hideki , Inoue Shota , Hatakeyama Junpei , Takamura Daisuke , Jiang Hanlin , Sakai Yoshitada , Akisue Toshihiro 
Published: October 2023

Abstract
Background
As global aging increases, and with life expectancy increases, both osteoarthritis (OA) prevalence and incidence is expected to rise. Transcutaneous carbon dioxide (CO2) therapy has been shown to promote muscle regeneration, healing of fractures, strengthening of athletic endurance, recovery from peripheral nerve damage, and cancer. However, its effect on symptom modification and inflammation in OA is largely unknown. The objective of this study was to examine whether CO2 therapy could slow progression of OA and relieve OA-related inflammation in a chemically or surgically induced model in rats.
Question/purposes
Using chemically and surgically induced models of OA, we sought to clarify whether transcutaneous carbon dioxide therapy improves OA-related inflammation and suppresses degeneration of articular cartilage.
Methods
OA model was induced by intra-articular injection of monosodium iodoacetate (MIA) and surgically induced by destabilization of the medial meniscus (DMM) in the knee joint. The pathogenesis period of MIA was set at 2 weeks, and that of DMM at 4 weeks. After the creation of the osteoarthritis model, either CO2 therapy or sham intervention was applied daily for 20 minutes, and treatment was applied at 2 weeks. At the end of the intervention period, behavioral assessments were completed and then knee joints were harvested. Non-demineralized frozen sections were prepared and samples were examined histologically.
Results
Assessments of knee joint diameter showed that knee swelling in the DMM model improved significantly after 2 weeks of CO2 therapy compared to the control group. The histomorphometric evaluation showed a significant increase in chondrocyte density in the CO2 group compared to the MIA and DMM groups. Furthermore, the number of matrix metalloproteinases 13, a disintegrin and metalloproteinase with thrombospondin motifs 5, proinflammatory cytokines tumor necrosis factor-α, interleukin (IL)-1β, and IL-6 positive cells decreased in the CO2 group, while the number of aggrecan and type II collagen positive cells increased.
Conclusions
Our results clearly demonstrate that transcutaneous CO2 therapy improves OA-related inflammation and suppresses degeneration of articular cartilage.
Clinical Relevance
Transcutaneous application of CO2 may have therapeutic potential for improving articular inflammation and degeneration of articular cartilage in OA patients.
Integrative Metabolomics, Genomics, and Transcriptomics Analysis Unravels Anti-Cancer Potential of Secondary Metabolites in Dillenia Suffruticosa
Authors: Ahmad Norhayati , Ali Sabri Mohd. , Kaewnarin Khwanta , Lim Abner , Hong Jing Han , Ng Cedric , Hamdani Nur Izzah Amal Afiqah , Zaini Nurul Hazlina , Ruslan Mohammad Amiruddin , Soon Boon Yu , Ibrahim Nor Sarah Irdina , Liu Wei , Chung Odelia Yuan Xuan , Lim Boon Yee , Chan Jason Yongsheng , Taha Hussein , Teh Bin Tean 
Published: October 2023

Abstract

The genus Dillenia, native to Southeast Asia and the Indian Ocean islands tropics, lacks genomic information despite its wide-ranging medicinal and ornamental applications. This study presents a comprehensive genomics, transcriptomics and metabolomics profiling of Dillenia suffruticosa which is widely used in the local populace and highly regenerative in secondary forests of Brunei Darussalam. The assembled genome spans a size of 596 Mb (N50: 20.8 Mb) with 30,490 genes. Multi-omics profiling revealed metabolites were discovered in D. suffruticosa, including phenolics, alkaloids, flavonoids, and terpenoids, alongside their biosynthetic pathways. Additionally, the study examined the cytotoxic effects of D. suffruticosa extracts on ten types of cancer cell lines. The findings indicate that extracts derived from the root organ, which contains higher levels of terpenoids trigger cancer cell death through the NF-kB pathway. In conclusion, this study enriches the chemogenomic and plant metabolites understanding of D. suffruticosa for pharmacological applications in a multidisciplinary approach.
The assessment of Noise Immunity in Domino Employing Silicon Nano Materials
Authors: Garg Sandeep , Gupta Tarun Kumar , Pandey Amit Kumar , Pandey Digvijay , Rajput Prince 
Published: October 2023

Abstract
This article describes a novel Low Voltage Noise Immune Domino Logic (LVNIDL), which can be used to create CMOS domino using Si Nanomaterials. In 32 nm nano size silicon CMOS technology, wide fan-in input domino OR gate have been proposed and have already undergone HSPICE simulation. For the transient analysis of domino gates in the simulation, a D.C supply voltage of 0.9V and a frequency of 100 MHz are utilised. The proposed technique consumes 76.07% less power than the preceding conditional stacked keeper domino logic. Furthermore, when compared to the existing CPVT technique, the designed LVNIDL technique reduces maximum delay by 56.25%. The LVNIDL technique boosts the power delay product by up to 88.54% and the EDP by up to 95.31% when compared to earlier domino. In terms of unity noise gain, the LVNIDL technique outperforms the earlier domino by 1.09 to 1.47 times.
SHDC: An Smart Hybrid Data Compression Method in WBANs
Authors: HajilooVakil Mahdieh , Shirmohammadi Zahra 
Published: October 2023

Abstract
The Wireless Body Area Networks (WBANs) are a set of sensors on the human s body that are designed in very small sizes. These sensors are faced with the exchange of a huge amount of data, which causes them to run out of energy consumption. One of the most effective methods to save the sensors' energy is the use of data compression. However the problem of compression methods in WBANs is inadequate for compressing large amounts of duplicate data. In this regard, a new method called Smart Hybrid Data Compression (SHDC) is presented. SHDC method use Recurrent Neural Network (RNN) and Run Length Encoding (RLE) which involves four key steps: 1-create and fit the LSTM network, 2-prediction, 3-calculate error and 4-compressed by lossless procedure. The presented method has a very good performance in energy consumption, data volume reduction by removing unimportant and repetitive data in the exchange of information between sensors and sink, high accuracy in data prediction and achieving a high compression rate due to low error. The SHDC method is implemented on the data set received from body sensors including blood pressure systolic, blood pressure diastolic, heart rate, respiration and SPO2. In the last step the differences between predictions and original signals are coded by four lossless coding: RLE, Huffman, Limpel Ziv Welch (LZW) and Arithmetic. Three measurements of Compression Ratio (CR), Energy Remaining (ER) and Root Mean Square Error (RMSE) after data compression have been measured. Our results compared with state-of-art lossless coding methods. Results show the SHDC method with RNN and RLE has the highest energy saving on average of 98% by maintaining the appropriate compression ratio.
Dynamic analysis of resistance in Colombian elite Hevea brasiliensis genotypes as a breeding strategy for enhancing South American leaf blight management under disease non-escape conditions in the Amazon region
Authors: Galindo-Rodríguez Lyda Constanza , Sterling Armando , Muñoz-Ramirez Herminton , Martínez-Moyano Edgar , Fonseca-Restrepo Jesica Andrea , Loaiza-Molina Luis Carlos 
Published: October 2023

Abstract
South American Leaf Blight (SALB) stands as the primary limitation to the establishment of new rubber (Hevea brasiliensis) crops in Latin America. This study aimed to assess the temporal dynamics of resistance to SALB in 99 elite Colombian genotypes and the IAN 873 cultivar (control) of H. brasiliensis in small-scale clone trials conducted under conditions with a high disease prevalence in the northwestern Colombian Amazon. Resistance monitoring was carried out on a monthly basis and analyzed over five climatic periods. Three variables were recorded: attack severity (AT, ranging from 0 to 4), reaction type (TR, ranging from 1 to 6) and stromal density (ST, ranging from 0 to 4). The maximum scores for TR and ST were used to classify the level of resistance of the genotypes. Highly significant differences in the mean values of AT, TR and ST among the genotypes, across the periods, and in the interaction between genotype and period were found. Over time, an increase in symptoms (AT) and signs (TR and ST) of SALB was observed. During the rainy periods, SALB intensity was highest, resulting in a leaf area affected ranging from 16–30%. Eight genotypes exhibited partial resistance (PR) (TR < 5 and ST < 2), while 16 genotypes demonstrated complete resistance (CR) (TR < 3 and ST = 0), and 76 genotypes were highly susceptible (HS) (TR > 5 or ST > 2). The temporal analysis early on identified 23 Colombian superior genotypes with varying degrees of SALB resistance, which can be a valuable breeding resource for improving SALB management in the Colombian Amazon region.
Real space iterative reconstruction for vector tomography (RESIRE-V)
Authors: Pham Minh , Osher Stanley , Miao Jianwei , Rana Arjun , Lu Xinyuan 
Published: October 2023

Abstract

Tomography has had an important impact on the physical, biological, and medical sciences. To date, most tomographic applications have been focused on 3D scalar reconstructions. However, in some crucial applications, vector tomography is required to reconstruct 3D vector fields such as the electric and magnetic fields. Over the years, several vector tomography methods have been developed. Here, we present the mathematical foundation and algorithmic implementation of REal Space Iterative REconstruction for Vector tomography, termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates between the projections and a 3D reconstruction. Each iteration consists of a forward step using the Radon transform and a backward step using its transpose, then updates the object via gradient descent. Incorporating with a 3D support constraint, the algorithm iteratively minimizes an error metric, defined as the difference between the measured and calculated projections. The algorithm can also be used to refine the tilt angles and further improve the 3D reconstruction. To validate RESIRE-V, we first apply it to a simulated data set of the 3D magnetization vector field, consisting of two orthogonal tilt series, each with a missing wedge. Our quantitative analysis shows that the three components of the reconstructed magnetization vector field agree well with the ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D magnetization vector field of a ferromagnetic meta-lattice consisting of three tilt series. Our 3D vector reconstruction reveals the existence of topological magnetic defects with positive and negative charges. We expect that RESIRE-V can be incorporated into different imaging modalities as a general vector tomography method.To make the algorithm accessible to a broad user community,, we have made our RESIRE-V MATLAB source codes and the data freely available at https://github.com/minhpham0309/RESIRE-V.
Integrated bioinformatic analysis of the shared mechanisms in endochondral ossification Between ossification of the ligamentum flavum (OLF) and ankylosing spondylitis (AS)
Authors: Yishan Liu , Li Yang , Liu Yixuan , Gao Zhongya , Zhang Jianjun , Qiu Youcai , Wang Can , Lu Xuhua , Yang Jiandong 
Published: October 2023

Abstract
Ossification of the ligamentum flavum (OLF) and ankylosing spondylitis (AS) are complex maladies characterized by the progressive process of endochondral ossification. This study aims to elucidate shared biomarkers related to ectopic ossification and the potential molecular regulatory mechanism. Microarray and RNA-seq datasets, obtained from the Gene Expression Omnibus (GEO) database, were utilized to discern differentially expressed genes (DEGs) in the OLF and AS datasets. Weighted gene co-expression network analysis (WGCNA) was conducted to identify co-expression modules associated with OLF and AS. Furthermore, the central hub genes were thoughtfully selected through the application of the least absolute shrinkage and selection operator (LASSO) regression, and three pivotal hub genes (MAB21L2, MEGF10, ISLR) were screened. Among these, ROC analysis demonstrated the exceptional diagnostic potential of MAB21L2. Finally, an examination of immune infiltration patterns unveiled activated CD8 T cells as shared differential immune infiltrating cells, significantly linked to MAB21L2 in both pathogeneses. This study represents the first instance of identifying MAB21L2 as a prospective diagnostic marker for patients contending with OLF complicated by AS. Results suggest a plausible association with the extracellular matrix (ECM)-receptor interaction in both pathogeneses, thereby offering valuable insights into the pathogenesis of spinal ligament ossification and unveiling promising therapeutic targets.
Developing a critical care visualization touch panel system to support rapid and accurate data interpretation
Authors: Kamio Tadashi 
Published: October 2023

Abstract

Purpose Critical care patients require constant monitoring of their vital signs and test results; however, gathering these data can be challenging. However, studies have indicated that visualization dashboards can enhance situational awareness by streamlining data collection, reducing difficulties, and minimizing errors. Therefore, we developed a bedside display that enables rapid and accurate access to the information required for critical care. Methods Only critical care data from the existing system were extracted and reconfigured onto a bedside display to avoid costly and time-consuming electronic health records (EHR) transitions. Results Real-time bedside display has four major benefits: improved data reliability during rounds, earlier accessibility for surgeons, quicker recognition of patient condition changes by nurses, and transition from paper to digital data collection and monitoring in the Intensive care unit (ICU). Conclusion Our approach to reuse EHR data to support critical care management offers a new perspective that may be replicated in other facilities.
Determination of Meaningful Block Sizes for Rock Fall Modelling
Authors: Illeditsch Mariella , Preh Alexander 
Published: October 2023

Abstract
The determination of the so-called design block is one of the central elements of the Austrian Guideline for rock fall protection ONR 24810. It is specified as a certain percentile (P95-P98, depending on event frequency) of a recorded block size distribution (BSD). BSDs may be determined from the detachment area (IBSD) and/or from the deposition area (RBSD). Deposition areas, if available, are generally accessible and measurable without technical aids. However, most measuring methods are subjective, uncertain, not verifiable, or inaccurate. Also, rock fall blocks are often fragmented due to the preceding fall process. The IBSD is (also) required for meaningful rock fall modelling. The statistical method seems the most efficient and cost-effective method to determine IBSDs with many blocks within the full range of block sizes. In current literature, joint properties are often described by the lognormal and exponential distribution functions. Today, we can model Synthetic Rock Masses (SRM) based on Discrete Fracture Networks (DFN). DFNs statistically describe the geometric properties of the joint sets. This way, we can carry out exact rock mass block surveys and determine IBSDs. We asked whether IBSDs derived from SRM models can be described by probability distribution functions and if yes, how well. We fitted various distribution functions to three determined IBSDs of different lithologies. We compared their correlations using the KS test and the MSE method. We show that the generalized exponential distribution function best describes IBSDs across various lithologies, when compared to 78 other distribution functions. This could allow for more certain, accurate, verifiable, holistic, and objective results. Further investigations are required.