bluuebunny/crossref_metadata_2025 huggingface dataset:
Long-term treatment outcomes from the perspective of a patient with unilateral cleft lip and palate
Authors: Fowler Peter , Ardouin Kenny , Haworth Jennifer , Snape Leslie
Published: December 2021

The management of patients with orofacial cleft (OFC) often extends from diagnosis or birth well into adulthood and requires many different specialists within multidisciplinary teams (MDT). The aims of treatment are to restore form and function relating to hearing, speech, occlusion and facial aesthetics. People with OFCs that include the lip, alveolus and palate (cleft lip and palate (CLP)) require several different staged and coordinated surgical and non-surgical interventions, and the treatment pathway is associated with a heavy burden of care. Due to the extensive nature of the interaction with these patients, MDT members have opportunities to provide enhanced patient-centred care and support. This case report provides an overview of the current knowledge of the aetiology of OFC and the management of these patients. It provides a unique perspective from one of the coauthors who has a unilateral CLP (UCLP) and reports on his treatment experiences and long-term treatment outcomes. By having a better understanding of the impact of UCLP and treatment provided, MDT members can not only provide improved clinical treatment but also offer improved patient experiences for those with craniofacial anomalies, in particular, an increased awareness of the psychosocial challenges, they endure throughout their treatment pathway and beyond.
Extensive subcutaneous emphysema from scalp to lower limbs in a 44-year old
Authors: Sokhal Balamrit Singh , Prasanna Kumar Menon Sowmya , Panesar Harrypal , Rajagopalan Sriram
Published: December 2021

A 44-year-old man was admitted after being found suspended by his ankles from a bridge for 5 days. The events leading to it was not clearly known initially. On examination, the patient was hypotensive and hypothermic, airway was oedematous and both lower limbs were mottled with dusky feet. Both foot pulses were impalpable, with prolonged capillary refill time and sensation barely present. Doppler signals were not heard in the feet, but groin pulses and popliteal signals were present. On CT, the patient had bilateral pneumothoraxes, extensive subcutaneous emphysema throughout the body from the subcutaneous tissue of the scalp to both lower limbs and pneumomediastinum and pneumoperitoneum. CT angiogram showed opacification up to proximal crural vessels and absence beyond. After multispeciality input and optimisation of his physiology, he underwent bilateral below knee amputations as they were non-salvageable.
Hierarchy of qualities in global health partnerships: a path towards equity and sustainability
Authors: Schriger Simone H , Binagwaho Agnes , Keetile Moses , Kerry Vanessa , Mubiligi Joel M , Ramogola-Masire Doreen , Roland Michelle , Barg Frances K , Cancedda Corrado
Published: December 2021

Despite the exponential growth of global health partnerships (GHPs) over the past 20 years, evidence for their effectiveness remains limited. Furthermore, many partnerships are dysfunctional as a result of inequitable partnership benefits, low trust and accountability and poor evaluation and quality improvement practices. In this article, we describe a theoretical model for partnerships developed by seven global health experts. Through semistructured interviews and an open-coding approach to data analysis, we identify 12 GHP pillars spanning across three interconnected partnership levels and inspired by Maslow’s hierarchy of needs. The transactional pillars are governance, resources and expertise, power management, transparency and accountability, data and evidence and respect and curiosity. The collaborative pillars (which build on the transactional pillars) are shared vision, relationship building, deep understanding and trust. The transformational pillars (which build on the collaborative pillars and allow partnerships to achieve their full potential) are equity and sustainability. The theoretical model described in this article is complemented by real-life examples, which outline both the cost incurred when GHPs fail to live up to these pillars and the benefits gained when GHPs uphold them. We also provide lessons learnt and best practices that GHPs should adopt to further increase their strength and improve their effectiveness in the future. To continue improving health outcomes and reducing health inequities globally, we need GHPs that are transformational, not just rhetorically but de facto. These actualised partnerships should serve as a catalyst for the greater societal good and not simply as a platform to accrue and exchange organisational benefits.
Using geospatial models to map zero-dose children: factors associated with zero-dose vaccination status before and after a mass measles and rubella vaccination campaign in Southern province, Zambia
Authors: Arambepola Rohan , Yang Yangyupei , Hutchinson Kyle , Mwansa Francis Dien , Doherty Julie Ann , Bwalya Frazer , Ndubani Phillimon , Musukwa Gloria , Moss William John , Wesolowski Amy , Mutembo Simon
Published: December 2021

Introduction

Despite gains in global coverage of childhood vaccines, many children remain undervaccinated. Although mass vaccination campaigns are commonly conducted to reach these children their effectiveness is unclear. We evaluated the effectiveness of a mass vaccination campaign in reaching zero-dose children.

Methods

We conducted a prospective study in 10 health centre catchment areas in Southern province, Zambia in November 2020. About 2 months before a national mass measles and rubella vaccination campaign conducted by the Ministry of Health, we used aerial satellite maps to identify built structures. These structures were visited and diphtheria-tetanus-pertussis (DTP) and measles zero-dose children were identified (children who had not received any DTP or measles-containing vaccines, respectively). After the campaign, households where measles zero-dose children were previously identified were targeted for mop-up vaccination and to assess if these children were vaccinated during the campaign. A Bayesian geospatial model was used to identify factors associated with zero-dose status and measles zero-dose children being reached during the campaign. We also produced fine-scale zero-dose prevalence maps and identified optimal locations for additional vaccination sites.

Results

Before the vaccination campaign, 17.3% of children under 9 months were DTP zero-dose and 4.3% of children 9–60 months were measles zero-dose. Of the 461 measles zero-dose children identified before the vaccination campaign, 338 (73.3%) were vaccinated during the campaign and 118 (25.6%) were reached by a targeted mop-up activity. The presence of other children in the household, younger age, greater travel time to health facilities and living between health facility catchment areas were associated with zero-dose status. Mapping zero-dose prevalence revealed substantial heterogeneity within and between catchment areas. Several potential locations were identified for additional vaccination sites.

Conclusion

Fine-scale variation in zero-dose prevalence and the impact of accessibility to healthcare facilities on vaccination coverage were identified. Geospatial modelling can aid targeted vaccination activities.
Investigation of the chemical ordering and thermal properties of the Rh–Ag–Au nanoalloys
Authors: Yildirim Huseyin
Published: December 2021

In this paper, the melting behaviors of Rh–Ag–Au nanoalloys are investigated with MD simulation. For Rh–Ag–Au nanoalloys, icosahedron structure was considered. The local optimizations of Rh–Ag–Au nanoalloys were carried out with the BH algorithm. The interatomic interactions were modeled with the Gupta potential. The local optimization results of Rh–Ag–Au nanoalloys show that Au and Ag atoms prefer to locate on the surface, and Rh atoms prefer to locate in the inner shells. The bond order parameter result is compatible with the excess energy analysis. It is noted that structures with more Ag–Au bonds are more energetically stable. Caloric curve, heat capacity, Lindemann index, and RMSD methods were used for estimating the melting temperatures of Rh–Ag–Au nanoalloys. According to the simulation results, melting temperatures depend on the composition. Also, it is discovered that nanoalloys are generally melting in two stages. Surface melting of the third shell is occupied by Ag and Au atoms, and then homogeneous melting of the inner shells is occupied by Rh atoms. It is found that the difference between surface melting temperatures and homogeneous melting temperatures in Ag-poor compositions is more significant than that of Ag-rich nanoalloys. In addition, the melting temperatures of the nanoalloys are found to be increased as the size of nanoalloys increases.
18β-Glycyrrhetinic Acid Inhibits TGF-β-Induced Epithelial-to-Mesenchymal Transition and Metastasis of Hepatocellular Carcinoma by Targeting STAT3
Authors: Jie Mo , Zhang Zhao-Qi , Deng Ning , Liu Qiu-Meng , Wang Chao , Ge Qian-Yun , Du Peng-Chen , Song Sha-Sha , Zhang Xue-Wu , Long-Xin  , Liang Hui-Fang , Chu Liang , Zhang Lei , Chen Xiao-Ping , Chen Jin , Dong Han-Hua , Zhang Bi-Xiang
Published: December 2021

18[Formula: see text]-glycyrrhetinic acid (GA) is the active ingredient of the traditional Chinese medicinal herb Glycyrrhizae radix et rhizoma. We previously demonstrated that GA inhibited tumor growth in hepatocellular carcinoma (HCC). However, the effect of GA on transforming growth factor-[Formula: see text] (TGF-[Formula: see text]-induced epithelial-mesenchymal transition (EMT) and metastasis were still unclear. In this study, in vitro transwell assays and immunofluorescence (IF) demonstrated that GA inhibited TGF-[Formula: see text]-induced migration, invasion and EMT of HCC cells. However, it had little effect on the inhibition of proliferation by TGF-[Formula: see text]. Moreover, we confirmed that GA suppressed the metastasis of HCC cells in vivousing an ectopic lung metastasis model. Furthermore, we found that GA inhibited TGF-[Formula: see text]-induced EMT mainly by reducing the phosphorylation of signal transducer and activator of transcription 3 (STAT3), which played an essential role in TGF-[Formula: see text]-induced EMT and cell mobility. Mechanistically, GA inhibited the phosphorylation of STAT3 by increasing the expression of Src homology 2 domain-containing protein tyrosine phosphatases 1 and 2 (SHP1 and SHP2). Therefore, we concluded that GA inhibited TGF-[Formula: see text]-induced EMT and metastasis via the SHP1&SHP2/STAT3/Snail pathway. Our data provide an attractive therapeutic target for future multimodal management of HCC.
Casimir effect with one large extra dimension
Authors: Erdas Andrea
Published: December 2021

In this work, I study the Casimir effect of a massive complex scalar field in the presence of one large compactified extra dimension. I investigate the case of a scalar field confined between two parallel plates in the macroscopic three dimensions, and examine the cases of Dirichlet and mixed (Dirichlet–Neumann) boundary conditions on the plates. The case of Neumann boundary conditions is uninteresting, since it yields the same result as the case of Dirichlet boundary conditions. The scalar field also permeates a fourth compactified dimension of a size that could be comparable to the distance between the plates. This investigation is carried out using the [Formula: see text]-function regularization technique that allows me to obtain exact expressions for the Casimir energy and pressure. I discover that when the compactified length of the extra dimension is similar to the plate distance, or slightly larger, the Casimir energy and pressure become significantly different than their standard three-dimensional values, for either Dirichlet or mixed boundary conditions. Therefore, the Casimir effect of a quantum field that permeates a compactified fourth dimension could be used as an effective tool to explore the existence of large compactified extra dimensions.
Control Algorithm of Permanent Magnet Direct Drive Belt Conveyor System for Mining Based on Reduced Order Model
Authors: Liu Jiehui , Qin Hao , Wang Guimei , Zhao Haichao
Published: December 2021

Over the decades, permanent magnet synchronous motor (PMSM) has been widely used in coal mine production. In this paper, an optimized neural network predictive controller (NNPC) of permanent magnet direct drive belt conveyor system (BCS) for mining based on reduced order model (ROM) is established. First, in order to establish the full order model of the permanent magnet direct drive BCS, CEMA is used for dynamic analysis, and the dynamic equation of the permanent magnet direct drive BCS is established. Second, the Proper Orthogonal Decomposition (POD) method is used to reduce the order in this paper. Finally, the NNPC of permanent magnet direct drive BCS based on the ROM is proposed. The simulation result shows that the order of BCS model is effectively reduced by the POD method. The NNPC based on the ROM has a good performance in the control of permanent magnet direct drive BCS, and the error between of the full order model and the ROM is 0.19[Formula: see text]m/s.
On the Bogolyubov endomorphisms of the renormalized square of white noise algebra
Authors: Rebei Habib , Wannes Slaheddine
Published: December 2021

We introduce the quadratic analogue of the Bogolyubov endomorphisms of the canonical commutation relations (CCR) associated with the re-normalized square of white noise algebra (RSWN-algebra). We focus on the structure of a subclass of these endomorphisms: each of them is uniquely determined by a quadruple [Formula: see text], where [Formula: see text] are linear transformations from a test-function space [Formula: see text] into itself, while [Formula: see text] is anti-linear on [Formula: see text] and [Formula: see text] is real. Precisely, we prove that [Formula: see text] and [Formula: see text] are uniquely determined by two arbitrary complex-valued Borel functions of modulus [Formula: see text] and two maps of [Formula: see text], into itself. Under some additional analytic conditions on [Formula: see text] and [Formula: see text], we discover that we have only two equivalent classes of Bogolyubov endomorphisms, one of them corresponds to the case [Formula: see text] and the other corresponds to the case [Formula: see text]. Finally, we close the paper by building some examples in one and multi-dimensional cases.
Analytical Solution for Vibrations of a Modified Timoshenko Beam on Visco-Pasternak Foundation Under Arbitrary Excitations
Authors: Yu Haitao , Chen Xizhuo , Li Pan
Published: December 2021

An analytical solution is derived for dynamic response of a modified Timoshenko beam with an infinite length resting on visco-Pasternak foundation subjected to arbitrary excitations. The modified Timoshenko beam model is employed to further consider the rotary inertia caused by the shear deformation of a beam, which is usually neglected by the traditional Timoshenko beam model. By using Fourier and Laplace transforms, the governing equations of motion are transformed from partial differential forms into algebraic forms in the Laplace domain. The analytical solution is then converted into the time domain by applying inverse transforms and convolution theorem. Some widely used loading cases, including moving line loads for nondestructive testing, travelling loads for seismic wave passage, and impulsive load for impact vibration, are also discussed in this paper. The proposed generic solutions are verified by comparing their degraded results to the known solutions in other literature. Several examples are performed to further investigate the differences of the beam responses obtained from the modified and the traditional Timoshenko beam models. Results show that the modified Timoshenko beam simulates the beam responses more accurately than the traditional model, especially under the dynamic loads with a high frequency. The analytical solutions proposed in this paper can be conveniently used for design and applied as an effective tool for practitioners.
Invertible matrices over a class of semirings
Authors: Dolžan David
Published: December 2021

We characterize the invertible matrices over a class of semirings such that the set of additively invertible elements is equal to the set of nilpotent elements. We achieve this by studying the liftings of the orthogonal sums of elements that are “almost idempotent” to those that are idempotent. Finally, we show an application of the obtained results to calculate the diameter of the commuting graph of the group of invertible matrices over the semirings in question.
Surface Plasmonic Lasing in Micro-Nanostructures of Silicon Excited by using Pulsed Infrared Lasers
Authors: Huang Wei-Qi , Wang Zi-Lin , Chen Cui-Fen , Wang Ke , Peng Hong-Yan , Li Xin , Wang An-Chen , Huang Zhong-Mei , Liu Shi-Rong
Published: December 2021

Surface plasmon is a possible candidate to break the diffraction limit and open the door for developing nanolasers on silicon chips. A new step in this development involves the choice of the structures and compositions for better surface plasmonic emission. The micro-nanostructures were fabricated by using a nanosecond pulsed laser on silicon surface, in which the surface plasmonic emission is stronger. The group of emission peaks with multiple-longitudinal-mode occurs in the optical gain curve. Interestingly, the quantum energy of surface plasmon with 140[Formula: see text]meV has been measured at first, which is related to the peak interval (about 62[Formula: see text]nm) of longitudinal modes in the surface plasmonic lasing spectra. The surface plasmonic lasing near 865[Formula: see text]nm was observed in the Purcell cavity with Si–Cr–Si layers excited by using pulsed lasers at 1064[Formula: see text]nm. Surface plasmonic structure induced with photons was observed by using the reflection Talbot effect image, in which the mechanism of the surface plasmonic lasing can be explored. The physical model of the surface plasmonic laser has been built on the energy levels of the micro-nanostructures of Si.
HOW THE EXCHANGE RATE REGIME AFFECTS ADJUSTMENT TO LARGE OIL PRICE SWINGS IN OIL EXPORTING COUNTRIES
Authors: Almozaini Majed S.
Published: December 2021

The aim of this study is to analyze how oil price shocks affect the economic growth of floating exchange rate regimes and fixed exchange rate regimes in oil-exporting countries with a ratio of oil exports to total exports exceeding 70%. Also, this study seeks to determine what monetary and fiscal policies both regimes apply in order to curb business cycles and reduce inflationary and recessionary gaps. The analytical study uses panel data for the period from 1991 to 2019, covering 24 oil-exporting countries, from the World Economic Outlook (WEO) database and World Bank. The econometric model is estimated by applying a panel VECM to examine the short- and long-term interdependencies in the macroeconomic variables. The results demonstrate that when there is a negative shock to the oil price, the exchange rate of the floating exchange rate regimes depreciates, money supply increases, and government spending decreases. In contrast, the exchange rate of the fixed exchange rate regimes fluctuates slightly; the money supply slightly decreases in the near, medium, and long term; and government spending decreases.
Handwriting-Assistant
Authors: Bu Yanling , Xie Lei , Yin Yafeng , Wang Chuyu , Ning Jingyi , Cao Jiannong , Lu Sanglu
Published: December 2021

Pen-based handwriting has become one of the major human-computer interaction methods. Traditional approaches either require writing on the specific supporting device like the touch screen, or limit the way of using the pen to pure rotation or translation. In this paper, we propose Handwriting-Assistant, to capture the free handwriting of ordinary pens on regular planes with mm-level accuracy. By attaching the inertial measurement unit (IMU) to the pen tail, we can infer the handwriting on the notebook, blackboard or other planes. Particularly, we build a generalized writing model to correlate the rotation and translation of IMU with the tip displacement comprehensively, thereby we can infer the tip trace accurately. Further, to display the effective handwriting during the continuous writing process, we leverage the principal component analysis (PCA) based method to detect the candidate writing plane, and then exploit the distance variation of each segment relative to the plane to distinguish on-plane strokes. Moreover, our solution can apply to other rigid bodies, enabling smart devices embedded with IMUs to act as handwriting tools. Experiment results show that our approach can capture the handwriting with high accuracy, e.g., the average tracking error is 1.84mm for letters with the size of about 2cmx1cm, and the average character recognition rate of recovered single letters achieves 98.2% accuracy of the ground-truth recorded by touch screen.
KATN
Authors: You Xuanke , Zhang Lan , Yu Haikuo , Yuan Mu , Li Xiang-Yang
Published: December 2021

Leveraging sensor data of mobile devices and wearables, activity detection is a critical task in various intelligent systems. Most recent work train deep models to improve the accuracy of recognizing specific human activities, which, however, rely on specially collected and accurately labeled sensor data. It is labor-intensive and time-consuming to collect and label large-scale sensor data that cover various people, mobile devices, and environments. In production scenarios, on the one hand, the lack of accurately labeled sensor data poses significant challenges to the detection of key activities; on the other hand, massive continuously generated sensor data attached with inexact information is severely underutilized. For example, in an on-demand food delivery system, detecting the key activity that the rider gets off his/her motorcycle to hand food over to the customer is essential for predicting the exact delivery time. Nevertheless, the system has only the raw sensor data and the clicking "finish delivery" events, which are highly relevant to the key activity but very inexact, since different riders may click "finish delivery" at any time in the last-mile delivery. Without exact labels of key activities, in this work, we propose a system, named KATN, to detect the exact regions of key activities based on inexact supervised learning. We design a novel siamese key activity attention network (SAN) to learn both discriminative and detailed sequential features of the key activity under the supervision of inexact labels. By interpreting the behaviors of SAN, an exact time estimation method is devised. We also provide a personal adaptation mechanism to cope with diverse habits of users. Extensive experiments on both public datasets and data from a real-world food delivery system testify the significant advantages of our design. Furthermore, based on KATN, we propose a novel user-friendly annotation mechanism to facilitate the annotation of large-scale sensor data for a wide range of applications.
Thru-the-wall Eavesdropping on Loudspeakers via RFID by Capturing Sub-mm Level Vibration
Authors: Wang Chuyu , Xie Lei , Lin Yuancan , Wang Wei , Chen Yingying , Bu Yanling , Zhang Kai , Lu Sanglu
Published: December 2021

The unprecedented success of speech recognition methods has stimulated the wide usage of intelligent audio systems, which provides new attack opportunities for stealing the user privacy through eavesdropping on the loudspeakers. Effective eavesdropping methods employ a high-speed camera, relying on LOS to measure object vibrations, or utilize WiFi MIMO antenna array, requiring to eavesdrop in quiet environments. In this paper, we explore the possibility of eavesdropping on the loudspeaker based on COTS RFID tags, which are prevalently deployed in many corners of our daily lives. We propose Tag-Bug that focuses on the human voice with complex frequency bands and performs the thru-the-wall eavesdropping on the loudspeaker by capturing sub-mm level vibration. Tag-Bug extracts sound characteristics through two means: (1) Vibration effect, where a tag directly vibrates caused by sounds; (2) Reflection effect, where a tag does not vibrate but senses the reflection signals from nearby vibrating objects. To amplify the influence of vibration signals, we design a new signal feature referred as Modulated Signal Difference (MSD) to reconstruct the sound from RF-signals. To improve the quality of the reconstructed sound for human voice recognition, we apply a Conditional Generative Adversarial Network (CGAN) to recover the full-frequency band from the partial-frequency band of the reconstructed sound. Extensive experiments on the USRP platform show that Tag-Bug can successfully capture the monotone sound when the loudness is larger than 60dB. Tag-Bug can efficiently recognize the numbers of human voice with 95.3%, 85.3% and 87.5% precision in the free-space eavesdropping, thru-the-brick-wall eavesdropping and thru-the-insulating-glass eavesdropping, respectively. Tag-Bug can also accurately recognize the letters with 87% precision in the free-space eavesdropping.
Mover
Authors: Lyu Wenjun , Wang Guang , Yang Yu , Zhang Desheng
Published: December 2021

Human mobility models typically produce mobility data to capture human mobility patterns individually or collectively based on real-world observations or assumptions, which are essential for many use cases in research and practice, e.g., mobile networking, autonomous driving, urban planning, and epidemic control. However, most existing mobility models suffer from practical issues like unknown accuracy and uncertain parameters in new use cases because they are normally designed and verified based on a particular use case (e.g., mobile phones, taxis, or mobile payments). This causes significant challenges for researchers when they try to select a representative human mobility model with appropriate parameters for new use cases. In this paper, we introduce a MObility VERification framework called MOVER to systematically measure the performance of a set of representative mobility models including both theoretical and empirical models based on a diverse set of use cases with various measures. Based on a taxonomy built upon spatial granularity and temporal continuity, we selected four representative mobility use cases (e.g., the vehicle tracking system, the camera-based system, the mobile payment system, and the cellular network system) to verify the generalizability of the state-of-the-art human mobility models. MOVER methodically characterizes the accuracy of five different mobility models in these four use cases based on a comprehensive set of mobility measures and provide two key lessons learned: (i) For the collective level measures, the finer spatial granularity of the user cases, the better generalization of the theoretical models; (ii) For the individual-level measures, the lower periodic temporal continuity of the user cases, the theoretical models typically generalize better than the empirical models. The verification results can help the research community to select appropriate mobility models and parameters in different use cases.
Uterine Fibroids: Hiding in Plain Sight
Authors: Stewart Elizabeth A. , Nowak Romana A.
Published: December 2021

Uterine fibroids (leiomyomas) are present in >75% of women and can cause serious morbidity. They are by far the leading cause of hysterectomy. Fibroids are a complex mixture of cells that include fibroblasts and smooth muscle cells. Rich in extracellular matrix, they typically arise through somatic mutations, most commonly MED12. Their lack of growth inhibition and their ability to have facets of malignancy yet be histologically and biologically benign provide opportunities to explore basic processes. To date, the mechanisms responsible for growth and development of leiomyomas are an enigma. This review provides an overview of current understanding and future directions for clinical and basic research of fibroids.
From “Hunger Hormone” to “It’s Complicated”: Ghrelin Beyond Feeding Control
Authors: Deschaine Sara L. , Leggio Lorenzo
Published: December 2021

Discovered as a peptide involved in releasing growth hormone, ghrelin was initially characterized as the “hunger hormone.” However, emerging research indicates that ghrelin appears to play an important part in relaying information regarding nutrient availability and value and adjusting physiological and motivational processes accordingly. These functions make ghrelin an interesting therapeutic candidate for metabolic and neuropsychiatric diseases involving disrupted nutrition that can further potentiate the rewarding effect of maladaptive behaviors.
Rock Mechanical Properties and Breakdown Pressure of High-Temperature and High-Pressure Reservoirs in the Southern Margin of Junggar Basin
Authors: Kong Mingwei , Zhang Zhaopeng , Zhao Chunyan , Chen Huasheng , Ma Xinfang , Zou Yushi
Published: December 2021

The mechanical properties of the high-temperature and high-pressure reservoirs in the southern margin of Junggar Basin have not been clearly understood, which correspondingly results in uncertainties when predicting the breakdown pressure. To address this issue, firstly, rock mechanical experiments under high temperature, high confining pressure, and high pore pressure were carried out. Secondly, empirical formulas related to the transformation of dynamic and static mechanical parameters in the regional strata were proposed. Finally, the existing prediction model for the formation breakdown pressure was improved by taking the wellbore seepage and thermal stress into consideration. Results show that under the reservoir condition of high temperature and high pressure, the rock sample tends to form closed shear cracks. High temperature causes thermal damages and the reduction of the compressive strength and elastic modulus, while the combined effects of high confining pressure and pore pressure enhance the compressive strength and plasticity of the rock sample simultaneously. Based on the correlation analysis, it is found that the static elastic modulus is linearly related to the dynamic value, while static Poisson’s ratio is a quadratic function of the dynamic value. These fitting functions can be used to obtain the profiles of static elastic modulus and Poisson’s ratio based on their dynamic values from the logging interpretation. Besides, the improved prediction model for the rock breakdown pressure can yield more accurate results indicated by the error less than 2%. Therefore, the proposed breakdown pressure prediction model in this study can provide theoretical guidance in the selection of fracturing truck groups and the design of the pumping schedule for high-temperature and high-pressure reservoirs.
Agent‐Oriented Software Engineering Methodologies: Analysis and Future Directions
Authors: Abdalla Reem , Mishra Alok
Published: December 2021

The Internet of Things (IoT) facilitates in building cyber‐physical systems, which are significant for Industry 4.0. Agent‐based computing represents effective modeling, programming, and simulation paradigm to develop IoT systems. Agent concepts, techniques, methods, and tools are being used in evolving IoT systems. Over the last years, in particular, there has been an increasing number of agent approaches proposed along with an ever‐growing interest in their various implementations. Yet a comprehensive and full‐fledged agent approach for developing related projects is still lacking despite the presence of agent‐oriented software engineering (AOSE) methodologies. One of the moves towards compensating for this issue is to compile various available methodologies, ones that are comparable to the evolution of the unified modeling language (UML) in the domain of object‐oriented analysis and design. These have become de facto standards in software development. In line with this objective, the present research attempts to comprehend the relationship among seven main AOSE methodologies. More specifically, we intend to assess and compare these seven approaches by conducting a feature analysis through examining the advantages and limitations of each competing process, structural analysis, and a case study evaluation method. This effort is made to address the significant characteristics of AOSE approaches. The main objective of this study is to conduct a comprehensive analysis of selected AOSE methodologies and provide a proposal of a draft unified approach that drives strengths (best) of these methodologies towards advancement in this area.
Computer Network Dynamic Balance Flow Distribution Based on Closed-Loop Particle Swarm Feedback Model
Authors: Zhou Wei
Published: December 2021

Based on the closed-loop particle swarm feedback model, this paper proposes a graphical method to analyze the stability of the computer network dynamic balance system. First, based on the second-order time delay system model of congestion control, the stability of the system is described by characteristic pseudopolynomials. Secondly, based on the inverse line, the stability of the system is verified by graphical analysis methods, and the PID controller parameter range that guarantees the stability of the system is obtained, and the relationship between the controller proportional gain boundary and the network characteristic parameters is analyzed. Then, based on the analysis of the basic particle swarm optimization algorithm, the particle swarm evolution formula is divided into two parts, its own factors and social factors, and the influence of each part on the evolution speed and position of the particle swarm is analyzed, and an improved particle swarm is proposed. Finally, according to the above analysis, we find the corresponding equation from the appropriate solution in turn, thereby designing a class of particle swarm optimization algorithm with fewer intermediate variables. In view of the system involved in the classical PID control parameter tuning method, the improved particle swarm algorithm is applied to the parameter tuning and optimization of the PID controller. During the experiment, the improved PSO-PID controller optimization algorithm was used in the random early detection algorithm of active queue management, the process of the improved algorithm was researched and designed, and the relevant performance of the improved algorithm was verified through simulation experiments.
Outcomes of Early versus Late Endotracheal Intubation in Patients with Initial Non-Shockable Rhythm Cardiopulmonary Arrest in the Emergency Department
Authors: Daorattanachai Kiattichai , Srivilaithon Winchana , Phakawan Vitchapon , Imsuwan Intanon
Published: December 2021

Background. Sudden cardiac arrest is a critical condition in the emergency department (ED). Currently, there is no considerable evidence supporting the best time to complete advanced airway management (AAM) with endotracheal intubation in cardiac arrest patients presented with initial non-shockable cardiac rhythm. Objectives. To compare survival to hospital discharge and discharge with favorable neurological outcome between the ED cardiac arrest patients who have received AAM with endotracheal intubation within 2 minutes (early AAM group) and those over 2 minutes (late AAM group) after the start of chest compression in ED. Methods. We conducted a retrospective cohort study involving the ED cardiac arrest patients who presented with initial non-shockable rhythm in ED. Multivariable logistic regression analysis was used to evaluate the independent effect of early AAM on outcomes. The outcomes included the survival to hospital discharge and discharge with favorable neurological outcome. Results. There were 416 eligible participants: 209 in the early AAM group and 207 participants in the late AAM group. The early AAM group showed higher survival to hospital discharge compared with the late AAM group, but no statistically significant difference (adjusted odds ratio (aOR): 1.28, 95% confidence interval (CI): 0.59 -2.76,

p
=
0.524

). Discharge with favorable neurological outcome is also higher in the early AAM group (aOR: 1.68, 95% CI, 0.52 -5.45,

p
=
0.387

). Conclusion. This study did not demonstrate a significant improvement of survival to hospital discharge and discharge with favorable neurological outcome in the ED cardiac arrest patients with initial non-shockable cardiac arrest who underwent early AAM within two minutes. More research is needed on the timing of AAM and on airway management strategies to improve survival.
[Retracted] Analgesic Effects of Different κ‐Receptor Agonists Used in Daytime Laparoscopic Cholecystectomy
Authors: Zhou Wanjun , Wang Jiawu , Hu Chengyun , Dai Feibiao , Zhang Zhetao , Li Chuanyao , Tang Chaoliang , Xie Yanhu
Published: December 2021

Background. Comparing the effect of two different κ‐receptor agonists, nalbuphine and oxycodone, and regular morphine in patients for prophylactic analgesia of acute pain after daytime laparoscopic cholecystectomy. Methods. One hundred and twenty‐four patients undergoing laparoscopic cholecystectomy were randomly allocated to receive nalbuphine (group N), oxycodone (group O), and morphine (group M). The three groups were all given intravenous injection (iv.) of 0.15 mg/kg injection before incision and 0.05 mg/kg injection at the end of pneumoperitoneum. The Visual Analogue Scale (VAS) scores (incision, visceral, and shoulder) and Ramsay sedation scores at 1, 2, 4, 8, 12, 16, 20, and 24 hours after surgery, the time of extubation, the incidence of postoperative adverse events, the satisfaction of pain treatment, and the duration of stay after surgery were all recorded. Results. Compared with group M, the VAS scores of visceral pain at rest decreased in group N and group O at 1‐8 h after surgery (P < 0.05). The VAS scores of visceral pain at movement in group N decreased longer than those in group O (P < 0.05). Compared with that of group M, the postoperative time in Ramsay sedation score of group O increased longer than that of group N (P < 0.05). Compared with group N, patients had worse sleep quality in group O, longer length of stay in group M, and lower satisfaction in both groups. Conclusion. Compared with morphine, prophylactic use of the κ‐receptor agonists, nalbuphine and oxycodone, during laparoscopic cholecystectomy can reduce postoperative visceral pain. Furthermore, the nalbuphine group had fewer adverse reactions, better analgesia, and better satisfaction.
Artificial Intelligence Algorithm-Based Lumbar and Spinal MRI for Evaluation of Efficacy of Chinkuei Shin Chewan Decoction on Lumbar Spinal Stenosis
Authors: Zhu Yuefeng , Wu Tao , Wang Wenhao , Cai Chengchen , Zhu Bin , Lin Weilong , Xu Hao , Liang Qianqian , Wang Yongjun
Published: December 2021

The study aimed to explore the application value of lumbar Magnetic Resonance Imaging (MRI) images processed by artificial intelligence algorithms in evaluating the efficacy of chinkuei shin chewan decoction (a traditional Chinese medicine to nourish the kidney) in the treatment of lumbar spinal stenosis (LSS). Specifically, 110 LSS patients admitted to the hospital were selected as the research subjects. They were randomly divided into the control group (n = 55) and experimental group (n = 55) according to different treatment methods. The control group was treated with traditional medicine, and the experimental group additionally took chinkuei shin chewan decoction on its basis. Based on the traditional U-net algorithm, a U-net registration algorithm based on artificial intelligence was designed by introducing the information entropy theory, and the algorithm was applied to the lumbar MRI image evaluation of LSS patients. Compared with the traditional U-net algorithm, the artificial intelligence-based U-net registration algorithm had a decreased noise level

P
<
0.05

, the Jaccard (J) value (0.84) and the Dice value (0.93) increased significantly versus the traditional algorithm (J = 0.63, Dice = 0.81), and the characteristics of the image were more accurate. Before treatment, the Oswestry Disability Index (ODI) scores of the experimental group and the control group were 44.32 ± 6.45 and 43.32 ± 5.45, respectively. After treatment, the ODI scores of the two groups were 10.21 ± 5.05 and 17.09 ± 5.23, respectively. Both showed significant improvement, while the improvement of the experimental group was more obvious than that of the control group

P
<
0.05

. The overall effective rates of the two groups of patients were 96.44% and 82.47%, respectively, and the experimental group was significantly higher than the control group

P
<
0.05

. Under the U-net registration algorithm based on artificial intelligence, the diagnostic accuracy of lumbar MRI in the experimental group was 94.45%, significantly higher than 67.5% before the introduction of the algorithm

P
<
0.05

. In conclusion, chinkuei shin chewan decoction are effective for the treatment of LSS, and lumbar MRI based on the artificial intelligence U-net registration algorithm can evaluate the efficacy of LSS well and is worthy of promotion.
Evaluation Model of Power Operation and Maintenance Based on Text Emotion Analysis
Authors: Wan Wei , Liu Yuanlong , Han Xingwang , Wang Huijian
Published: December 2021

The application of data mining technology in power field mainly focuses on the application of power defect text and dispatching text. However, the power operation and maintenance data contains a lot of information about power equipment suppliers. Taking the operation and maintenance text involving power equipment suppliers as an example, this paper summarizes the theme of operation and maintenance text and studies the evaluation model of power equipment suppliers. The next sentence prediction analysis model of single round dialogue text based on transformer bidirectional encoder prediction and cosine similarity weighting is proposed, which can effectively divide the topic of dialogue text. Aiming at the semantic richness and complexity of power operation and maintenance text, a supplier evaluation model based on text emotion analysis is proposed. Based on the expansion of the entries and attributes of the existing power ontology dictionary, the dialogue emotion analysis rules are established to realize the normal evaluation of power equipment suppliers.
Simultaneous Determination of Ten Bioactive Components from Shenling Baizhu San in Rat Plasma by UHPLC-MS/MS: Application to a Comparative Pharmacokinetic Study in Normal and Two Models of Ulcerative Colitis Rats
Authors: Xu Xia , Wang Weiwei , Chen Yaxi , Zhang Qiyun , Li Bingtao , Zhong Yiwen , Tu Yu , Zhang Wentong , Xu Guoliang , Jiang Li
Published: December 2021

Shenling Baizhu San, a traditional formula, has a long history of treating spleen asthenic diarrhea by invigorating the spleen and dispelling dampness in China. A rapid and accurate UHPLC-MS/MS method was developed and fully validated for the simultaneous determination of ten active constituents in rat plasma: panaxadiol, ginsenoside Rg1, atractylenolide I, atractylenolide III, pachymic acid, neferine, nuciferine, diosgenin, platycodin D, and isoliquiritigenin. The plasma samples were pretreated by the protein precipitation method with acetonitrile. The analytes and puerarin (internal standard) were determined with high selectivity and sensitivity (LLOQ, 0.31–0.68 ng·mL−1) within 10 minutes. The validation parameters, including intra-/interday precisions, accuracy, recovery, matrix effect, and stability, were within acceptable ranges. The validated method was successfully applied to the pharmacokinetics study of ten components in normal and two rat models of ulcerative colitis (i.e., spleen deficiency with dampness retention-ulcerative colitis (SDDR-UC) rats and pure-ulcerative colitis (P-UC) rats). The pharmacokinetic parameters were significantly different among the three groups of rats. Overall, the absorption of the components was shown as follows: normal group > SDDR-UC group > P-UC group. The study could provide a scientific basis for further studies on pharmacokinetics and clinical differential application of SDDR-UC and P-UC patients.
Research Trends, Hot Spots, and Prospects for Traditional Chinese Medicine in the Field of Ischemia-Reperfusion Injury
Authors: Sun Yu , Cai Yuan , Xiao Man , Hu Ming-hai , Shao Guo-qiang , Liu Hui , Shen Bing-bing , Li Peng-hui , Peng Yan-mei
Published: December 2021

Ischemia-reperfusion (I/R) injury is one of the most common phenomena in ischemic disease or processes that causes progressive disability or even death. It has a major impact on global public health. Traditional Chinese medicine (TCM) has a long history of application in ischemic diseases and has significant clinical effect. Numerous studies have shown that the formulas or single herbs in TCM have specific roles in regulating oxidative stress, anti-inflammatory, inhibiting cell apoptosis, etc., in I/R injury. We used bibliometrics to quantitatively analyze the global output of publications on TCM in the field of I/R injury published in the period 2001–2021 to identify research hotspots and prospects. We included 446 related documents published in the Web of Science during 2001–2021. Visualization analysis revealed that the number of publications related to TCM in the field of I/R injury has increased year by year, reaching a peak in 2020. China is the country with the largest number of publications. Keywords and literature analyses demonstrated that neuroregeneration is likely one of the research hotspots and future directions of research in the field. Taken together, our findings suggest that although the inherent limitations of bibliometrics may affect the accuracy of the literature-based prediction of research hotspots, the results obtained from the included publications can provide a reference for the study of TCM in the field of I/R injury.
Classical and Bayesian Estimation of the Inverse Weibull Distribution: Using Progressive Type‐I Censoring Scheme
Authors: Algarni Ali , Elgarhy Mohammed , M Almarashi Abdullah , Fayomi Aisha , R El-Saeed Ahmed
Published: December 2021

The challenge of estimating the parameters for the inverse Weibull (IW) distribution employing progressive censoring Type‐I (PCTI) will be addressed in this study using Bayesian and non‐Bayesian procedures. To address the issue of censoring time selection, qauntiles from the IW lifetime distribution will be implemented as censoring time points for PCTI. Focusing on the censoring schemes, maximum likelihood estimators (MLEs) and asymptotic confidence intervals (ACI) for unknown parameters are constructed. Under the squared error (SEr) loss function, Bayes estimates (BEs) and concomitant maximum posterior density credible interval estimations are also produced. The BEs are assessed using two methods: Lindley’s approximation (LiA) technique and the Metropolis‐Hasting (MH) algorithm utilizing Markov Chain Monte Carlo (MCMC). The theoretical implications of MLEs and BEs for specified schemes of PCTI samples are shown via a simulation study to compare the performance of the different suggested estimators. Finally, application of two real data sets will be employed.
New Media Advertising Communication Analysis Model Based on Extension Neural Network
Authors: Zhang Zhe
Published: December 2021

In order to improve the effect of new media advertising communication analysis, this paper combines the scalable neural network to construct the new media advertising communication analysis model. Moreover, this paper analyzes in detail the basic theories of fuzzy neural network and extension evaluation, the structure design and learning algorithm, and classification of fuzzy neural network. In particular, this paper summarizes the optimization algorithms and methods of neural network structure. In addition, this paper improves the algorithm to meet the needs of new media advertising data analysis and builds an intelligent system framework. The experimental verification shows that the new media advertising communication analysis model based on the extension neural network proposed in this paper meets the new media advertising communication analysis effect.