bluuebunny/crossref_metadata_2025 huggingface dataset:
Retrospective Comparative Study of Clinical Outcomes and Cost-Effectiveness with Bone Substitutes on Volar Locking Plate Fixation of Unstable Distal Radial Fractures in the Elderly
Authors: MORI Yusuke , TAKEGAMI Yasuhiko , TOKUTAKE Katsuhiro , OKA Yoshiharu , IMAGAMA Shiro
Published: February 2023

Background: This multicenter retrospective study aimed to compare clinical outcomes and cost-effectiveness with bone substitutes on volar locking plate (VLP) fixation of unstable distal radial fractures (DRF) in the elderly.

Methods: The data of 1,980 patients of ≥65 years of age who underwent surgery for the DRF with a VLP in 2015–2019 were extracted from a database (named TRON). Patients lost to follow-up or who received autologous bone grafting were excluded. The patients (n = 1,735) were divided into the VLP fixation alone (Group VLA) and VLP fixation with bone substitutes (Group VLS). Propensity score matching of background characteristics (ratio, 4:1) was performed. The modified Mayo wrist scores (MMWS) were evaluated as clinical outcomes. The implant failure rate, bone union rate, volar tilt (VT), radial inclination (RI), ulnar variance (UV) and distal dorsal cortical distance (DDD) were evaluated as radiologic parameters. We also compared the initial surgery cost and total cost for each group.

Results: After matching, the backgrounds of Groups VLA (n = 388) and VLS (n = 97) were not significantly different. The MMWS values of the groups were not significantly different. Radiographic evaluation revealed no implant failure in either group. Bone union was confirmed in all patients in both groups. The VT, RI, UV and DDD values of the groups were not significantly different. The initial surgery cost and total cost in the VLS group were significantly higher than those in the VLA group ($3,515 vs. $3,068, p < 0.001).

Conclusions: In patients of ≥65 years of age with DRF, the clinical and radiological outcomes of VLP fixation with bone substitutes did not differ from those of VLP fixation alone, yet the additional use of bone augmentation was associated with higher medical costs. The indications for bone substitutes should be more strictly considered in the elderly with DRF.

Level of Evidence: Level IV (Therapeutic)
Modified Thompson–Littler Method for Chronic Instability of the Proximal Interphalangeal Joint: A Report of Two Cases
Authors: MATSUO Tomoki , SUZUKI Taku , KIMURA Hiroo , IWAMOTO Takuji
Published: February 2023

A 40-year-old patient and a 45-year-old patient presented with chronic dorsal and lateral subluxation of the proximal interphalangeal (PIP) joint of the little finger and underwent surgeries. Through a dorsal approach, the ulnar lateral band was transected and transferred to the radial side through the volar side of the PIP joint. The transferred lateral band and the remnant of the radial collateral ligament were secured with an anchor on the radial side of the proximal phalanx. Satisfactory results were obtained without the loss of flexion and recurrence of subluxation of the finger. This method enabled the correction of both dorsal and lateral instability of the PIP joint through a dorsal incision. The modified Thompson–Littler technique was useful for chronic instability of the PIP joint.–

Level of Evidence: Level V (Therapeutic)
Combining the Projective Consciousness Model and Virtual Humans for Immersive Psychological Research: A Proof-of-concept Simulating a ToM Assessment
Authors: Rudrauf D. , Sergeant-Perhtuis G. , Tisserand Y. , Monnor T. , De Gevigney V. , Belli O.
Published: February 2023

Relating explicit psychological mechanisms and observable behaviours is a central aim of psychological and behavioural science. One of the challenges is to understand and model the role of consciousness and, in particular, its subjective perspective as an internal level of representation (including for social cognition) in the governance of behaviour. Toward this aim, we implemented the principles of the Projective Consciousness Model (PCM) into artificial agents embodied as virtual humans, extending a previous implementation of the model. Our goal was to offer a proof-of-concept, based purely on simulations, as a basis for a future methodological framework. Its overarching aim is to be able to assess hidden psychological parameters in human participants, based on a model relevant to consciousness research, in the context of experiments in virtual reality. As an illustration of the approach, we focused on simulating the role of Theory of Mind (ToM) in the choice of strategic behaviours of approach and avoidance to optimise the satisfaction of agents’ preferences. We designed a main experiment in a virtual environment that could be used with real humans, allowing us to classify behaviours as a function of order of ToM, up to the second order. We show that agents using the PCM demonstrated expected behaviours with consistent parameters of ToM in this experiment. We also show that the agents could be used to estimate correctly each other’s order of ToM. Furthermore, in a supplementary experiment, we demonstrated how the agents could simultaneously estimate order of ToM and preferences attributed to others to optimize behavioural outcomes. Future studies will empirically assess and fine tune the framework with real humans in virtual reality experiments.
Development of a Benchmark Odia Handwritten Character Database for an Efficient Offline Handwritten Character Recognition with a Chronological Survey
Authors: Dey Raghunath , Balabantaray Rakesh Chandra
Published: February 2023

A good benchmark dataset is a primary requirement in the offline handwritten character recognition (HCR) process. Only three handwritten numerals and alphabet datasets from Odia are publicly accessible for study, although many writers have used several datasets in their experiments. In this article, two tasks are done to address this issue. Those are the following: First, an extensive survey focused on various datasets is provided with the methodologies used in chronological order. The second factor is a solution to the lack of publicly available handwritten characters and numeral datasets. A new dataset of handwritten Odia characters with numerals has been developed. Anyone can access this dataset by sending an email to the authors of the article. This dataset was created with the help of 150 volunteers of various age groups, races, and qualifications. Some homogeneous experiments are conducted using deep learning models to evaluate the consistency of the dataset. One heterogeneous trial has also been performed to estimate the complexities of the characters present in the dataset by comparing them with the existing benchmark datasets.
A Survey on Multi-modal Summarization
Authors: Jangra Anubhav , Mukherjee Sourajit , Jatowt Adam , Saha Sriparna , Hasanuzzaman Mohammad
Published: February 2023

The new era of technology has brought us to the point where it is convenient for people to share their opinions over an abundance of platforms. These platforms have a provision for the users to express themselves in multiple forms of representations, including text, images, videos, and audio. This, however, makes it difficult for users to obtain all the key information about a topic, making the task of automatic multi-modal summarization (MMS) essential. In this article, we present a comprehensive survey of the existing research in the area of MMS, covering various modalities such as text, image, audio, and video. Apart from highlighting the different evaluation metrics and datasets used for the MMS task, our work also discusses the current challenges and future directions in this field.
Group-Based Personalized News Recommendation with Long- and Short-Term Fine-Grained Matching
Authors: Xu Hongyan , Peng Qiyao , Liu Hongtao , Sun Yueheng , Wang Wenjun
Published: February 2023

Personalized news recommendation aims to help users find news content they prefer, which has attracted increasing attention recently. There are two core issues in news recommendation: learning news representation and matching candidate news with user interests. In this context, “candidate” indicates potential for interest. Due to the superior ability to understand natural language demonstrated by Pretrained Language Models (PLMs), recent works utilize PLMs (e.g., BERT) to strengthen news modeling, obtaining more accurate user interest matching and achieving notable improvement in news recommendation. However, the existing PLM-based methods are usually incapable of fully exploring the fine-grained (i.e., word-level) relatedness between user behaviors and candidate news due to the heavy computational cost brought by PLMs. In this article, we propose a group-based personalized news recommendation method with long- and short-term matching mechanisms between users and candidate news based on PLMs to learn fine-grained matching efficiently and effectively. In our approach, we design to group user historical clicked news into chunks with quite shorter news sequences according to their clicked timestamps, which could alleviate the computation issues of PLMs. PLMs are applied in each group jointly with the candidate news to capture their word-level interaction, and global group-level matching is learned across different groups. In addition, the group-based mechanism could be naturally adapted for long- and short-term user representation learning, in which we build users’ long preferences from the representations of all groups and treat the last group as short interests, respectively. Finally, we employ a gate network to dynamically unify the group-level, long- and short-term representations, yielding comprehensive user-news matching effectively. Extensive experiments are conducted on two real-world datasets. The results show that our proposed method achieves superior performance in news recommendations.
Parsing-Conditioned Anime Translation: A New Dataset and Method
Authors: Li Zhansheng , Xu Yangyang , Zhao Nanxuan , Zhou Yang , Liu Yongtuo , Lin Dahua , He Shengfeng
Published: February 2023

Anime is an abstract art form that is substantially different from the human portrait, leading to a challenging misaligned image translation problem that is beyond the capability of existing methods. This can be boiled down to a highly ambiguous unconstrained translation between two domains. To this end, we design a new anime translation framework by deriving the prior knowledge of a pre-trained StyleGAN model. We introduce disentangled encoders to separately embed structure and appearance information into the same latent code, governed by four tailored losses. Moreover, we develop a FaceBank aggregation method that leverages the generated data of the StyleGAN, anchoring the prediction to produce in-domain animes. To empower our model and promote the research of anime translation, we propose the first anime portrait parsing dataset,
Danbooru-Parsing
, containing 4,921 densely labeled images across 17 classes. This dataset connects the face semantics with appearances, enabling our new constrained translation setting. We further show the editability of our results, and extend our method to manga images, by generating the first manga parsing pseudo data. Extensive experiments demonstrate the values of our new dataset and method, resulting in the first feasible solution on anime translation.
Co-Electrodeposited Pi-MnO2-rGO as an Efficient Electrode for the Selective Oxidation of Piperonyl Alcohol
Authors: Rodrigues Roopa Margaret , Thadathil Ditto Abraham , Shanker G. , Sirimahachai Uraiwan , Varghese Anitha , Hegde Gurumurthy
Published: February 2023

Pi-MnO2-rGO-CFP electrode was developed through a concurrent deposition of Pi-MnO2 and reduced graphene oxide (rGO) on carbon fiber paper (CFP). Cyclic voltammetry (CV) and electrochemical impedance studies (EIS) were applied for the electrochemical characterization of the electrode. The electro catalytic activity of the modified electrode was improved by the increased synergistic characteristics of the CFP and electrochemically deposited rGO-Pi-MnO2 composite. The performance of the modified electrode was remarkable due to its lowest charge transfer resistance (R
ct), and highest surface area offering more active sites and quicker electron transport kinetics. X-ray diffraction spectroscopy (XRD), Raman spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and optical profilometry (OP) were employed to study the physicochemical properties. Furthermore, the modified electrode was availed to oxidize piperonyl alcohol mediated by 4-acetamido-2,2,6,6-tetramethylpiperidine-1-oxyl (4-acetamido TEMPO or 4-ACT). The product obtained was purified and characterized by 1HNMR. The turnover frequency of 4-ACT was studied at different concentrations of the reactant, and the reaction parameters were also optimized using statistical tool design of experiment. This methodology is demonstrated to be economical, environmentally benign, and highly efficient in obtaining piperonal as it is carried out under milder reaction conditions.
Mechanism of Metallic Uranium and Bimetallic U-Ga, U-Cd Alloys Electrodeposition in Molten LiCl–KCl–CsCl Eutectic
Authors: Novoselova Alena , Smolenski Valeri , Volkovich Vladimir A. , Ryzhov Alexander A. , Yan Yongde , Xue Yun , Ma Fuqiu , Chukin Andrey V.
Published: February 2023

Speciation and behavior of uranium (III) chloride in the ternary low melting LiCl–KCl–CsCl eutectic was studied by electrochemistry and spectroscopy techniques. Cathodic reduction of U(III) ions on inert (tungsten) and reactive (gallium, cadmium) electrodes was investigated at 623–923 K using cyclic and square wave voltammetry. The potential scan rate was changed from 0.075 to 0.5 V s−1 in all experiments. It was established that the electrochemical reduction process on the inert electrode was irreversible, proceeded in one stage, and was controlled by the charge transfer. Formation of uranium alloys with gallium and cadmium was studied using active liquid Ga and Cd electrodes. Reduction of uranium ions of the reactive electrodes proceeded with considerable depolarization. The effect of current density on the composition of the cathodic product was considered. Conditions for the electrochemical production of alloys of a given composition were determined.
Microstructure and Physical Properties of (Eu, Ni) Co-Doped BiFeO3 Materials
Authors: Thang Dao Viet , Hung Nguyen Manh , Khang Nguyen Cao , Oanh Le Thi Mai , Nguyen Van Quang , Van Minh Nguyen
Published: February 2023

BiFeO3 (BFO) and Bi1-x
Eu
x
Fe0.975Ni0.025O3 (x = 0, 0.025, 0.05, 0.075, 0.10) materials were synthesized by sol-gel method. The structural, optical, ferromagnetic, and ferroelectric properties of all samples were systematically investigated using different techniques. Analysis results of XRD showed that all samples were crystallized in the rhombohedral structure with R
3C space group. The crystal lattice parameters were a = 5.563 Å, c = 13.833 Å and crystal size is L
XRD = 519 Å for BiFeO3 materials whereas the a, c, and L
XRD of (Eu, Ni) co-doped samples decreased with Eu concentration. Raman scattering spectra were used for confirming the substitution of Eu3+ ions into Bi-sites. Fluorescence spectra showed the enhancement of characteristic emission peaks with Eu concentration. The BFO exhibited weak ferroelectric behavior with a maximum polarization of P
s = 12.698 μC cm−2, remnant polarization of P
r = 7.351 μC cm−2. Ferroelectric properties of the (Eu, Ni) co-doped samples were significantly enhanced. The BFO material exhibited a weak ferromagnetic behavior with saturation magnetization of M
s = 0.036 emu g−1, remnant magnetization of M
r = 0.004 emu g−1. The ferromagnetic properties of sample were also improved with presence of (Eu, Ni) dopants. The origin of the improvement in ferromagnetism, ferroelectricity, and fluorescence were also thoroughly discussed.
11β-HSD1 determines the extent of muscle atrophy in a model of acute exacerbation of COPD
Authors: Webster Justine M. , Waaijenberg Kelsy , van de Worp Wouter R. P. H. , Kelders Marco C. J. M. , Lambrichts Sara , Martin Claire , Verhaegen Frank , Van der Heyden Brent , Smith Charlotte , Lavery Gareth G. , Schols Annemie M. W. J. , Hardy Rowan S. , Langen Ramon C. J.
Published: February 2023

Muscle atrophy is an extrapulmonary complication of acute exacerbations (AE) in chronic obstructive pulmonary disease (COPD). The endogenous production and therapeutic application of glucocorticoids (GCs) have been implicated as drivers of muscle loss in AE-COPD. The enzyme 11 β-hydroxysteroid dehydrogenase 1 (11β-HSD1) activates GCs and contributes toward GC-induced muscle wasting. To explore the potential of 11βHSD1 inhibition to prevent muscle wasting here, the objective of this study was to ascertain the contribution of endogenous GC activation and amplification by 11βHSD1 in skeletal muscle wasting during AE-COPD. Emphysema was induced by intratracheal (IT) instillation of elastase to model COPD in WT and 11βHSD1/KO mice, followed by vehicle or IT-LPS administration to mimic AE. µCT scans were obtained prior and at study endpoint 48 h following IT-LPS, to assess emphysema development and muscle mass changes, respectively. Plasma cytokine and GC profiles were determined by ELISA. In vitro, myonuclear accretion and cellular response to plasma and GCs were determined in C2C12 and human primary myotubes. Muscle wasting was exacerbated in LPS-11βHSD1/KO animals compared with WT controls. RT-qPCR and western blot analysis showed elevated catabolic and suppressed anabolic pathways in muscle of LPS-11βHSD1/KO animals relative to WTs. Plasma corticosterone levels were higher in LPS-11βHSD1/KO animals, whereas C2C12 myotubes treated with LPS-11βHSD1/KO plasma or exogenous GCs displayed reduced myonuclear accretion relative to WT counterparts. This study reveals that 11β-HSD1 inhibition aggravates muscle wasting in a model of AE-COPD, suggesting that therapeutic inhibition of 11β-HSD1 may not be appropriate to prevent muscle wasting in this setting.
A proteomics approach to identify COPD-related changes in lung fibroblasts
Authors: Bekker Nicolaas J. , van Pijkeren Alienke , Wolters Justina C. , Sánchez Brotons Alejandro , Guryev Victor , Woldhuis Roy R. , Bischoff Rainer , Alkema Wynand , Horvatovich Peter , van Nijnatten Johannes L. L. , van den Berge Maarten , Timens Wim , Brandsma Corry-Anke
Published: February 2023

Lung fibroblasts are implicated in abnormal tissue repair in chronic obstructive pulmonary disease (COPD). The exact mechanisms are unknown and comprehensive analysis comparing COPD- and control fibroblasts is lacking. The aim of this study is to gain insight into the role of lung fibroblasts in COPD pathology using unbiased proteomic and transcriptomic analysis. Protein and RNA were isolated from cultured parenchymal lung fibroblasts of 17 patients with stage IV COPD and 16 non-COPD controls. Proteins were analyzed using LC-MS/MS and RNA through RNA sequencing. Differential protein and gene expression in COPD was assessed via linear regression, followed by pathway enrichment, correlation analysis, and immunohistological staining in lung tissue. Proteomic and transcriptomic data were compared to investigate the overlap and correlation between both levels of data. We identified 40 differentially expressed (DE) proteins and zero DE genes between COPD and control fibroblasts. The most significant DE proteins were HNRNPA2B1 and FHL1. Thirteen of the 40 proteins were previously associated with COPD, including FHL1 and GSTP1. Six of the 40 proteins were related to telomere maintenance pathways, and were positively correlated with the senescence marker LMNB1. No significant correlation between gene and protein expression was observed for the 40 proteins. We hereby describe 40 DE proteins in COPD fibroblasts including previously described COPD proteins (FHL1, GSTP1) and new COPD research targets like HNRNPA2B1. Lack of overlap and correlation between gene and protein data supports the use of unbiased proteomics analysis and indicates that different types of information are generated with both methods.
A Pressure‐Sinkage Model for Deep‐Sea Sediments Based on Variable‐Order Fractional Derivatives
Authors: Wei Dingbang , Cao Huade , Xia Jianxin
Published: February 2023

In order to better describe the pressure‐sinkage process of deep‐sea surface sediments, this article proposes a new four‐element model. First, the pressure‐sinkage process was divided into four components according to the change in the deep‐sea sediment sinkage rate, and the time‐dependent mechanical property of deep‐sea sediments was described. Then, a new four‐element pressure‐sinkage model was established by introducing variable‐order fractional derivatives into the modelling idea of classic element combination to describe the full pressure‐sinkage regions of deep‐sea sediments. Furthermore, by comparing with the experimental results from other literature, the proposed model was verified to predict the pressure‐sinkage process of deep‐sea sediments under static and dynamic loads. Finally, through a sensitivity analysis of model parameters, the effects of ground pressure and time on the law and mechanism of deep‐sea sediment pressure sinkage were revealed. Results indicate that the deep‐sea sediment pressure‐sinkage process has obvious nonlinear characteristics and that the sinkage depth increases directly with ground‐specific pressure and time. Through comparative analysis of both experimental and predicted results, the proposed pressure‐sinkage constitutive model can describe the stress‐strain of the full stages. Thus, the variable order model represents an effective method to predict the pressure‐sinkage process of deep‐sea sediments.
[Retracted] Resveratrol Suppresses Bupivacaine‐Induced Spinal Neurotoxicity in Rats by Inhibiting Endoplasmic Reticulum Stress via SIRT1 Modulation
Authors: Luo Yunpeng , Zhao Yang , Lai Jian , Wei Liling , Zhou Gang , Yu Yue , Liu Jingchen
Published: February 2023

Bupivacaine (BUP) may cause neurotoxic effects after spinal anesthesia. Resveratrol (RSV), a natural agonist of Silent information regulator 1 (SIRT1), protects various tissues and organs from damage by regulating endoplasmic reticulum (ER) stress. The aim of this study is to explore whether RSV could alleviate the neurotoxicity induced by bupivacaine via regulating ER stress. We established a model of bupivacaine‐induced spinal neurotoxicity in rats using intrathecal injection of 5% bupivacaine. The protective effect of RSV was evaluated by injecting intrathecally with 30 μg/μL RSV in total of 10 μL per day for 4 consecutive days. On day 3 after bupivacaine administration, tail‐flick latency (TFL) tests and the Basso, Beattie, and Bresnahan (BBB) locomotor scores were assessed to neurological function, and the lumbar enlargement of the spinal cord was obtained. H&E and Nissl staining were used to evaluate the histomorphological changes and the number of survival neurons. TUNEL staining was conducted to determine apoptotic cells. The expression of proteins was detected by IHC, immunofluorescence, and western blot. The mRNA level of SIRT1 was determined by RT‐PCR. Bupivacaine caused spinal cord neurotoxicity by inducing cell apoptosis and triggering ER stress. RSV treatment promoted the recovery of neurological dysfunction after bupivacaine administration by suppressing neuronal apoptosis and ER stress. Furthermore, RSV upregulated SIRT1 expression and inhibited PERK signaling pathway activation. In summary, resveratrol suppresses bupivacaine‐induced spinal neurotoxicity in rats by inhibiting endoplasmic reticulum stress via SIRT1 modulation.
Severe Malaria in an Adult Patient from Low-Endemic Area in Flores Island, East Nusa Tenggara
Authors: Teressa Maria , Purnama Asep , Henrina Joshua , Wiraatmadja Agustinus , Boro Angela M. B. , L. Sam Candida I. , Dedang Tersila A. D. , Cahyadi Alius
Published: February 2023

Malaria is an infection caused by protozoa of the genus Plasmodium, commonly found in tropical and subtropical regions worldwide. Plasmodium falciparum causes the most severe form of the disease and may progress to life-threatening manifestations. This case describes a 26-year-old man who suffered cerebral malaria with multiple organ dysfunction and successfully recovered despite poor initial prognosis. Negligent and late diagnosis of malaria leads to severe complications and a worse prognosis. This case emphasizes despite living in a low-endemic malaria area, physicians should remain meticulous and consider malaria as differential diagnosis even after initially presenting with nonspecific symptoms. Consequently, malarial screening should be performed to modify the risk of mortality. Furthermore, close monitoring and early administration of intravenous artesunate are also particularly critical.
Obstacle Boundary Point and Expected Velocity‐Based Flocking of Multiagents with Obstacle Avoidance
Authors: Wu Jianhui , Ji Yuanfa , Sun Xiyan , Liang Weibin
Published: February 2023

Obstacle avoidance is a key technology of multiagents flocking control. However, most existing research studies assume that the agent can obtain global information about obstacles and have specific constraints on the shape and boundary of obstacles, which easily limit their practical applications. To relax these constraints, we assume that the agent can only perceive the position of obstacle boundary points within its sensing radius and propose an obstacle boundary point and an expected velocity‐based flocking algorithm of multiagents with obstacle avoidance. In this algorithm, the attraction/repulsion potential is designed to avoid collisions between agents and between the agent and obstacle boundary points, the expected velocity is designed to tow the agent to move along the boundary of obstacles, and the virtual leader is designed to lead all agents to realize the group objective. Finally, the sufficient conditions that the agent does not collide are demonstrated, and the performance of the proposed algorithm is further verified through simulations.
[Retracted] Ant Colony Optimization‐Enabled CNN Deep Learning Technique for Accurate Detection of Cervical Cancer
Authors: Kavitha R. , Jothi D. Kiruba , Saravanan K. , Swain Mahendra Pratap , Gonzáles José Luis Arias , Bhardwaj Rakhi Joshi , Adomako Elijah
Published: February 2023

Cancer is characterized by abnormal cell growth and proliferation, which are both diagnostic indicators of the disease. When cancerous cells enter one organ, there is a risk that they may spread to adjacent tissues and eventually to other organs. Cancer of the cervix of the uterus often initially manifests itself in the uterine cervix, which is located at the very bottom of the uterus. Both the growth and death of cervical cells are characteristic features of this condition. False‐negative results provide a significant moral dilemma since they may cause women to get an incorrect diagnosis of cancer, which in turn can result in the woman’s premature death from the disease. False‐positive results do not raise any significant ethical concerns; but they do require a patient to go through an expensive and time‐consuming treatment process, and they also cause the patient to experience tension and anxiety that is not warranted. In order to detect cervical cancer in its earliest stages in women, a screening procedure known as a Pap test is often performed. This article describes a technique for improving images using Brightness Preserving Dynamic Fuzzy Histogram Equalization. To individual components and find the right area of interest, the fuzzy c‐means approach is applied. The images are segmented using the fuzzy c‐means method to find the right area of interest. The feature selection algorithm is the ACO algorithm. Following that, categorization is carried out utilizing the CNN, MLP, and ANN algorithms.
[Retracted] Individualized Management of Quality of Care in Orthopedic Nurses Based on Sensitive Indicators
Authors: Zhang Weiling , Huang Xiaomin , Huang Tianwen
Published: February 2023

Background. Sensitive indicators of nursing quality focus on the core elements of nursing quality management. Nursing‐sensitive quality indicators will play an increasingly important role in the macro and micro management of nursing quality in my country. Objective. This study were aimed at formulating the sensitive index management of orthopedic nursing quality based on individual nurses for improvement of the quality of orthopedic nursing. Methods. Based on the previous literature, the existing challenges in the early application of the orthopedic nursing quality evaluation index were summarized. Moreover, the management system of the orthopedic nursing quality‐sensitive index based on individual nurses was devised and implemented, including monitoring the structure and result indices of individual nurses on duty and sampling the process indicators of patients managed by individual nurses. At the quarter‐end, the data analysis was performed and fed back to determine the key points of the changes in the quality of specialized nursing affecting the individual, and the PDCA method was utilized for persistent improvement. The changes of sensitive indices of orthopedic nursing quality before (July‐December 2018) and 6 months after implementation (July‐December 2019) were compared. Results. There were significant differences in other indices (accuracy of limb blood circulation assessment/accuracy of pain assessment/postural care pass rate/accuracy of rehabilitation behavioral training/satisfaction of discharged patients) (P < 0.05). Conclusion. The formulation of an individual‐based orthopedic nursing quality‐sensitive index management system modifies the traditional quality management model, improves the specialized nursing level, contributes to the accurate core competence training of specialized nursing, and improves the quality of specialized nursing of individual nurses. Consequently, there is an overall improvement in the specialized nursing quality of the department, and fine management is attained.
Synergistic Antibacterial Effect of Ethyl Acetate Fraction of Vernonia amygdalina Delile Leaves with Tetracycline against Clinical Isolate Methicillin-Resistant Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa
Authors: Satria Denny , Harahap Urip , Dalimunthe Aminah , Septama Abdi Wira , Hertiani Triani , Nasri Nasri
Published: February 2023

Multidrug-resistant bacteria have raised global concern about the inability to fight deadly infectious diseases. Methicillin-resistant Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa are the most common resistant bacteria that are causing hospital infections. The present study was undertaken to investigate the synergistic antibacterial effect of the ethyl acetate fraction of Vernonia amygdalina Delile leaves (EAFVA) with tetracycline against the clinical isolates MRSA and P. aeruginosa. Microdilution was used to establish the minimum inhibitory concentration (MIC). A checkerboard assay was conducted for the interaction effect. Bacteriolysis, staphyloxanthin, and a swarming motility assay were also investigated. EAFVA exhibited antibacterial activity against MRSA and P. aeruginosa with a MIC value of 125 μg/mL. Tetracycline showed antibacterial activity against MRSA and P. aeruginosa with MIC values of 15.62 and 31.25 μg/mL, respectively. The interaction between EAFVA and tetracycline showed a synergistic effect against MRSA and P. aeruginosa with a Fractional Inhibitory Concentration Index (FICI) of 0.375 and 0.31, respectively. The combination of EAFVA and tetracycline induced the alteration of MRSA and P. aeruginosa, leading to cell death. Moreover, EAFVA also inhibited the quorum sensing system in MRSA and P. aeruginosa. The results revealed that EAFVA enhanced the antibacterial activity of tetracycline against MRSA and P. aeruginosa. This extract also regulated the quorum sensing system in the tested bacteria.
Modeling the Training Iteration Time for Heterogeneous Distributed Deep Learning Systems
Authors: Zeng Yifu , Chen Bowei , Pan Pulin , Li Kenli , Chen Guo
Published: February 2023

Distributed deep learning systems effectively respond to the increasing demand for large‐scale data processing in recent years. However, the significant investment in building distributed learning systems with powerful computing nodes places a huge financial burden on developers and researchers. It will be good to predict the precise benefit, i.e., how many times of speedup it can get compared with training on single machine (or a few), before actually building such big learning systems. To address this problem, this paper presents a novel performance model on training iteration time for heterogeneous distributed deep learning systems based on the characteristics of the parameter server (PS) system with bulk synchronous parallel (BSP) synchronization style. The accuracy of our performance model is demonstrated by comparing real measurement results on TensorFlow when training different neural networks with various kinds of hardware testbeds: the prediction accuracy is higher than 90% in most cases.
Research on Electricity Market Trading Mechanism Considering Peak‐to‐Valley Ratio and Multitime Coupling
Authors: Wang Rongmao , Li Qingchun , Zhang Jian , Zhang Ye , Xu Xilin , Zhang Kai
Published: February 2023

With the development of the economy and society, electricity demand is increasing. However, there are some problems on the power grid side, such as the excess capacity of power installed, abandoned power of renewable energy, low overall utilization rate, and high pressure of stable operation. The problem stems from the inconsistency between the peak of electricity production and consumption and the lack of obvious power price signals. In this article, the market development objectives are combined with the time‐divided transaction, and two objectives of market development are proposed: (1) Reduce the peak‐valley difference of power supply and demand; (2) Expand the peak‐valley price difference in the market. Combined with the physical properties of the power market, a multiperiod coupling trading mechanism is designed. The results show that the speculative and profit‐seeking behavior of power producers will be stopped under the proposed trading mode, the potential of users for peak‐valley filling will be effectively developed, the peak‐valley gap of the power system can be controlled within a reasonable range, and the peak‐valley gap of power trading can be further amplified.
Geomechanical Characteristics and Stimulation of Dibei Deep Tight Sandstone Reservoirs in the Kuqa Depression of Tarim Basin
Authors: Xu Ke , Yang Haijun , Zhang Hui , Wang Zhimin , Fang Lu , Yin Guoqing , Wang Haiying
Published: February 2023

Facing the problem of increased production of deep tight gas reservoirs, this study takes the Dibei gas reservoir in Tarim Basin as an example, carries out geomechanical research, and reveals the rock mechanical properties, in situ stress, and fracture characteristics of the tight reservoir. From the perspective of the in situ stress field and the effectiveness of fractures, the study reveals their impacts on reservoir quality, wellbore stability, and fracturing networks. The results show that the in situ stress and the effectiveness of fracture mechanics under its control have obvious control over the production capacity in the Dibei gas reservoir. The positions and intervals with low in situ stress, high fracture density, and fracture effectiveness are often favorable parts. A directional well has the dual advantages of overcoming reservoir heterogeneity and safety and stability. Understanding the geomechanical characteristics can quantitatively optimize the best wellbore trajectory, reduce the difficulty of fracturing from the source of well location deployment, improve the efficiency of hydraulic fracturing, and then realize the stimulation of gas reservoirs. In addition, the favorable borehole trajectory considers both the sweet spot penetration and borehole wall stability, which will reduce the difficulty of fracturing and is conducive to the efficient stimulation of tight gas reservoirs. Geomechanics research has built an integrated bridge between geology and engineering, which plays a significant role in increasing gas production.
Jordan–Schur Algorithms for Computing the Matrix Exponential
Authors: Petkov Petko H.
Published: February 2023

In this paper, two new versions of the Schur algorithm for computing the matrix exponential of an n × n complex matrix A are presented. Instead of the Schur form, these algorithms use the Jordan–Schur form of A. The Jordan–Schur form is found by less computation and it is determined more reliable than the reduction to Jordan form since it is obtained using only unitary similarity transformations. In contrast to the known methods, the diagonal blocks of the matrix exponential are obtained by using finite Taylor series. This improves the accuracy and avoids the decisions made about the termination of the series expansion. The off‐diagonal blocks of the exponential are determined by modifications of the Schur–Parlett or Schur–Fréchet method, which takes advantage of the Jordan–Schur form of the matrix. The numerical features of the new algorithms are discussed, revealing their advantages and disadvantages in comparison with the other methods for computing the matrix exponential. Computational experiments show that using the new algorithms, the matrix exponential is determined in certain cases with higher accuracy than some widely used methods, however, at the price of an increase in the computational cost which is of order n4. It is shown that the Jordan–Schur algorithms for computing the matrix exponential are appropriate for matrices with multiple eigenvalues and are especially efficient in cases of large Weyr characteristics.
Effects of Personality Traits and Mentalization on Workplace Bullying Experiences among Intensive Care Unit Nurses
Authors: Jang Sun Joo , Kim Eunhye , Lee Haeyoung
Published: February 2023

Aim. This study aimed to investigate the effects of intensive care unit nurses’ personality traits and mentalization on workplace bullying after controlling for organizational culture. Background. Nurses’ personality traits and mentalization may significantly influence workplace bullying. Methods. This cross-sectional study collected data from 416 nurses using an online survey in July 2022. Major variables were evaluated using the Pathological Narcissism Inventory, Perfectionistic Self-Presentation and Psychological Distress Scale, Short Dark Triad, Mentalization Scale, Positive Nursing Organizational Culture Measurement Tool, and the Negative Acts Questionnaire-Revised. . A multiple regression analysis was performed. Results. Narcissistic vulnerability, mentalization, and perfectionistic self-presentation significantly influence workplace bullying (victim aspect). Dark personality, mentalization, and perfectionistic self-presentation significantly influence workplace bullying (perpetrator aspect). Conclusions. Individual nurses could become either victims of bullying or perpetrators according to their personality traits. Therefore, it is necessary to determine their personality traits, so that they do not become influencing factors in workplace bullying. Implications for Nursing Management. Efforts at a nursing organization level are crucial to understand nurses’ personality traits, enhance their mentalization, minimize the manifestations of the negative aspects of their traits, and positively affect the prevention and alleviation of workplace bullying.
Extracellular Vesicles Derived from Three-Dimensional-Cultured Human Umbilical Cord Blood Mesenchymal Stem Cells Prevent Inflammation and Dedifferentiation in Pancreatic Islets
Authors: Lee Eunwon , Ha Seungyeon , Kim Gyuri , Kim Jae Hyeon , Jin Sang-Man
Published: February 2023

It is unclear whether extracellular vesicles (EVs) from mesenchymal stem cells (MSCs) have a direct protective effect on pancreatic islets. In addition, whether culturing MSCs in three dimensions (3D) instead of a monolayer (2D) can induce changes in the cargo of EVs that facilitate the polarization of macrophages into an M2 phenotype has not been investigated. We sought to determine whether EVs from MSCs cultured in 3D can prevent inflammation and dedifferentiation in pancreatic islets and, if so, whether the protective effect is superior to that of EVs from 2D MSCs. Human umbilical cord blood- (hUCB-) MSCs cultured in 3D were optimized according to cell density, exposure to hypoxia, and cytokine treatment based on the ability of the hUCB-MSC-derived EVs to induce the M2 polarization of macrophages. Islets isolated from human islet amyloid polypeptide (hIAPP) heterozygote transgenic mice were cultured in serum-deprived conditions with hUCB-MSC-derived EVs. EVs derived from 3D hUCB-MSCs had more abundant microRNAs involved in M2 polarization of macrophages and had an enhanced M2 polarization ability on macrophages, which was optimized when the 3D culture condition was

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cells per spheroid without preconditioning with hypoxia and cytokine exposure. When islets isolated from hIAPP heterozygote transgenic mice were cultured in serum-deprived conditions with hUCB-MSC-derived EVs, the EVs derived from 3D hUCB-MSCs suppressed the expression of proinflammatory cytokines and caspase-1 in pancreatic islets and increased the proportion of M2-polarized islet-resident macrophages. They improved glucose-stimulated insulin secretion, reduced the expression of Oct4 and NGN3, and induced the expression of Pdx1 and FoxO1. The greater suppression of IL-1β, NLRP3 inflammasome, caspase-1, and Oct4 and induction of Pdx1 and FoxO1 were found in islets cultured with the EVs derived from 3D hUCB-MSCs. In conclusion, EVs derived from 3D hUCB-MSCs optimized for M2 polarization attenuated nonspecific inflammation and preserved β-cell identity of pancreatic islets.
Effect and Mechanism of Traditional Chinese Medicine Exercise Therapy on Stroke Recovery
Authors: Guo Cunxiao , Wang Yuanwang , Wang Shuang , Zhang Shouyao , Tai Xiantao
Published: February 2023

Stroke is currently the second largest contributor to disability‐adjusted life years (DALYs) in developing countries, and it is the third largest contributor to DALYs in developed countries. It requires a large number of resources from the health care system every year, which places a great burden on society, families, and individuals. The treatment of traditional Chinese medicine exercise therapy (TCMET) during stroke recovery has become a hot topic of current research due to its few adverse events and high efficiency. This article sorts out the latest progress of TCMET on the recovery of stroke through the review method and explores its role and mechanism based on existing clinical and experimental studies. TCMET treatment of stroke recovery mainly includes Tai Chi, Baduanjin, Daoyin, Yi Jin Jing, five‐fowl play, and six‐character tips, which can effectively improve motor function, balance and coordination ability, cognitive dysfunction, nerve function, depression or emotional state, daily living ability, and so on after stroke. The mechanisms of stroke treated by TCMET are discussed, and deficiencies in the literature are discussed and analyzed. It is hoped that some guiding suggestions will be provided for future clinical treatment and experimental studies.
Application of Media Integration in the Construction of Scientific and Technological Innovation Ecological Chain
Authors: Liu Jingjing
Published: February 2023

With the recent international economic and social changes, the development of innovation theories, the changes in the global industrial structure, and the transformation of old and new kinetic energy, many countries have advanced from innovation paradigm 1.0 to 3.0, integrating a variety of disciplines and theories, and using this concept to enhance their innovation capabilities. In such an environment, how to combine scientific and technological innovation with ecological environment construction, practice the integration and symbiosis of ecology and innovation, and promote the development of green innovation is the current focus of academic research. The scientific and technological innovation ecological chain is an organizational model that realizes the goal of scientific and technological innovation and the value-added spiral through the orderly connection and synergistic interaction between the main bodies or elements of innovation, such as basic research, technical research, achievement transformation, talent support, and technological finance. This paper takes Shanxi Province’s scientific and technological innovation ecological chain as a typical example, collects relevant text data through web crawler technology, then deconstructs the system of scientific and technological innovation ecological chain based on media integration, understands the composition of its main chain, supporting chain, and the interaction between the chains mechanism, and finally puts forward policy suggestions for the deepening of the future regional scientific and technological innovation ecological chain.
Black Rice Anthocyanidins Regulates Gut Microbiota and Alleviates Related Symptoms through PI3K/AKT Pathway in Type 2 Diabetic Rats
Authors: Zhang Xuejing , Sun Mubai , Li Da , Miao Xinyu , Hua Mei , Sun Ruiyue , Su Ying , Chi Yanping , Wang Jinghui , Niu Honghong
Published: February 2023

Black rice anthocyanins (BRAs) have extremely high nutritional value and health care effects. This study investigated the intervention effect of BRAs on type 2 diabetes mellitus (T2DM) and the regulation effect on intestinal microbiota imbalance in T2DM rats. This study established successfully a T2DM model in a high-fat and high-glucose diet combined with streptozotocin (STZ). BRAs intervention reduced significantly the fasting blood glucose level of T2DM rats, improved the glucose tolerance of rats, reduced the blood lipid level and inflammation state, and repaired liver, oxidative stress, and other injuries. In addition, BRAs’s intervention enhanced the expression of phosphoinositol 3-kinase (PI3K)/protein kinase B (AKT), activated the expression of adenosine 5’-monophosphate-activated protein kinase(AMPK), and the downstream acetyl-CoA carboxylase (ACC) and carnitine palmitoyl transferase (CPT1) in the liver. 16S rRNA sequencing showed that BRAs significantly decreased the abundances of Bifidobacterium and Clostridiaceae_Clostridium, and promoted the abundances of Akkermansia and Lactobacillus. Accelerate the recovery of gut microbiota diversity. BRAs play an antidiabetic role by regulating the PI3K/AKT signaling pathway and intestinal microbiota in T2MD rats.
Emerging Highly Pathogenic Avian Influenza (H5N8) Virus in Podiceps nigricollis in Northwest China in 2021
Authors: He Zhen , Jin Tiezhi , Wu Weikang , Zhao Zhe , Lu Zhenhua , Song Shuxuan , Liu Kun , Shao Zhongjun
Published: February 2023

Three highly pathogenic avian influenza (H5N8) viruses were detected in the migratory bird Podiceps nigricollis in Northwest China in June 2021. Phylogenetic analysis indicated that these H5N8 isolates belonged to clade 2.3.4.4b, which were highly homologous to strains isolated in China and South Korea. In this study, H5N8 virus infection in Podiceps nigricollis was detected using Oxford Nanopore Technologies sequencing technology and caused pathological changes in multiple organs.
Antioxidant Compounds in the Treatment of Alzheimer’s Disease: Natural, Hybrid, and Synthetic Products
Authors: Hatami Maryam , Mortazavi Mojtaba , Baseri Zahra , Khani Batool , Rahimi Mehdi , Babaei Sahar
Published: February 2023

Alzheimer’s disease (AD) which is associated with cognitive dysfunction and memory lapse has become a health concern. Various targets and pathways have been involved in AD’s progress, such as deficit of acetylcholine (ACh), oxidative stress, inflammation, β‐amyloid (Aβ) deposits, and biometal dyshomeostasis. Multiple pieces of evidence indicate that stress oxidative participation in an early stage of AD and the generated ROS could enable neurodegenerative disease leading to neuronal cell death. Hence, antioxidant therapies are applied in treating AD as a beneficial strategy. This review refers to the development and use of antioxidant compounds based on natural products, hybrid designs, and synthetic compounds. The results of using these antioxidant compounds were discussed with the given examples, and future directions for the development of antioxidants were evaluated.