bluuebunny/crossref_metadata_2025 huggingface dataset:
Unconventional superconductivity from weak coupling
Authors: Dürrnagel Matteo , Beyer Jacob , Thomale Ronny , Schwemmer Tilman
Published: July 2022

We develop a joint formalism and numerical framework for analyzing the superconducting instability of metals from a weak coupling perspective. This encompasses the Kohn–Luttinger formulation of weak coupling renormalization group for superconductivity as well as the random phase approximation imposed on the diagrammatic expansion of the two-particle Green’s function. The central quantity to resolve is the effective interaction in the Cooper channel, for which we develop an optimized numerical framework. Our code is capable of treating generic multi-orbital models in two as well as three spatial dimensions and, in particular, arbitrary avenues of spin-orbit coupling.

Graphic abstract
The same, but different, but still the same: structural and dynamical differences of neutrophil elastase and cathepsin G
Authors: Schuhmann Fabian , Tan Xiangyin , Gerhards Luca , Bordallo Heloisa N. , Solov’yov Ilia A.
Published: July 2022

Although the general mechanism for serine protease catalysis is well established, some questions still remain. For instance, the two enzymes, neutrophil elastase and cathepsin G, have a lot of structural resemblances. However, elastase degrades virulence factors, while cathepsin G does not. This paper studies both enzymes computationally to probe for their conformational differences. In the process, a methodology is established to not only quantify similarities between the protein trajectories describing proteins’ temporal evolution but also account for a varying number of amino acid residues comprising each structure. Our results indicate slight differences in the behavior of the active sites of neutrophil elastase and cathepsin G in the solvent. These subtle changes could indicate differences in the general behavior responsible for the different specificity of the two enzymes.

Graphical abstract
Quantum optimal control in quantum technologies. Strategic report on current status, visions and goals for research in Europe
Authors: Koch Christiane P. , Boscain Ugo , Calarco Tommaso , Dirr Gunther , Filipp Stefan , Glaser Steffen J. , Kosloff Ronnie , Montangero Simone , Schulte-Herbrüggen Thomas , Sugny Dominique , Wilhelm Frank K.
Published: July 2022

Quantum optimal control, a toolbox for devising and implementing the shapes of external fields that accomplish given tasks in the operation of a quantum device in the best way possible, has evolved into one of the cornerstones for enabling quantum technologies. The last few years have seen a rapid evolution and expansion of the field. We review here recent progress in our understanding of the controllability of open quantum systems and in the development and application of quantum control techniques to quantum technologies. We also address key challenges and sketch a roadmap for future developments.
The modified KdV equation for a nonlinear evolution problem with perturbation technique
Authors: Asghar Saleem , Haider Jamil Abbas , Muhammad Noor
Published: July 2022

This paper examines nonlinear partial differential equation (PDE) solutions. Scientists and engineers have struggled to solve nonlinear differential equations. Nonlinear equations arrive in nearly all problems in nature. There are no well-established techniques for solving all nonlinear equations, and efforts have been made to enhance approaches for a specific class of problems. Keeping this in mind, we shall investigate the perturbation method’s efficiency in solving nonlinear PDEs. Several techniques work well for diverse issues. We recognize that there may be several solutions to a given nonlinear issue. Methods include homotropy analysis, tangent hyperbolic function, factorization and trial function. However, some of these strategies do not cover all nonlinear issue solutions. In this paper, we use the perturbation technique to solve the zeroth-order Airy equation and also find the Bessel function in the first-order nonhomogeneous differential equation by using self-similar solutions that appears in modified Korteweg–de Vries (KdV) equation. This approach will be used for nonlinear equations in physics and applied mathematics.
Growth and application of MoSe2 in solar cells
Authors: Yuan Jintao , Ai Zikang , Yu Meng , Huang Ruiming , Cheng Qijin
Published: July 2022

MoSe2 from monolayer to bulk phase can realize the transition from a direct bandgap semiconductor to an indirect bandgap semiconductor. Its bandgap varies between 1.1 and 1.55 eV, which matches the solar spectral range, so Si-based heterojunction solar cells with MoSe2 as an active layer have great significance in the development of low-cost, high-efficiency and high-flexibility photovoltaic devices. In this work, MoSe2 thin films were synthesized by chemical vapor deposition using MoO3 and Se powders as precursor sources. The effects of different process parameters (Se source temperature, Mo source temperature, growth time, carrier gas flow rate and hydrogen ratio) on the synthesis of MoSe2 thin films were systematically investigated. The optimized experimental parameters were determined as follows: the molybdenum source temperature of 800[Formula: see text], the selenium source 20 cm away from molybdenum source, the growth time of 10 min, the carrier gas flow rate of 60 sccm, the hydrogen ratio of 10%. Then MoSe2/Si heterojunction solar cells were constructed via wet chemical transfer. The open-circuit voltage, short-circuit current density, filling factor and photovoltaic conversion efficiency of the fabricated solar cells were 0.19 V, 5.71 mA/cm2, 30.47% and 0.33%, respectively. Main factors affecting the photovoltaic performance of the MoSe2/Si solar cells have also been discussed. This work is very helpful for the development of MoSe2 material and relevant application in the field of solar cells.
Adaptive event-triggered group consensus of multi-agent systems under stochastic sampling
Authors: Li Hongjie , Zhao Ruirui , Peng Xinhai
Published: July 2022

This paper investigates group consensus for linear multi-agent systems with nonidentical dynamics. A novel adaptive event-triggered communication scheme is presented by using the stochastic sampling information, the event-triggered matrices and time-varying event-triggered parameters are introduced into event-triggered condition, where event-triggered parameters can be adjusted with the system dynamics evolving. The group consensus protocol is designed based on the neighboring agents information at event-triggered instants, then a new stochastic sampled-data dependent error model is constructed, some group consensus criteria in mean-square can be derived and the feedback matrices can also be obtained. Finally, two numerical examples are provided to illustrate the validity of the theoretical results.
Visual Saliency Modeling with Deep Learning: A Comprehensive Review
Authors: Abraham Shilpa Elsa , Kovoor Binsu C.
Published: July 2022

Visual saliency models mimic the human visual system to gaze towards fixed pixel positions and capture the most conspicuous regions in the scene. They have proved their efficacy in several computer vision applications. This paper provides a comprehensive review of the recent advances in eye fixation prediction and salient object detection, harnessing deep learning. It also provides an overview on multi-modal saliency prediction that considers audio in dynamic scenes. The underlying network structure and loss function for each model are explored to realise how saliency models work. The survey also investigates the inclusion of specific low-level priors in deep learning-based saliency models. The public datasets and evaluation metrics are succinctly introduced. The paper also makes a discussion on the key issues in saliency modeling along with some open problems and growing research directions in the field.
A simple concept with minimum steps for solving the transportation problem to obtain the lowest shipping cost
Authors: Sangeetha V. , Thirusangu K. , Elumalai P.
Published: July 2022

Transportation problem has been employed in different range of operations amd the optimization of such problem is significant in many areas. A simple penalty and rapid process is used in this paper in order to obtain the lowest shipping cost for the transportation problems. A new method is proposed to extract the optimal solution of transportation problem. First, we solve a transportation problem employing a new way, and we compare this new proposed method solution to the VAM and MODI methods. Following that, we obtain that the transportation solution of the proposed method is equal to the MODI solution. This result demonstrates that by utilizing the novel proposed strategy, we can identify the straight optimal solution to the majority of transportation problems. Finally, the solution process is mathematically presented.
Accelerating Attention Mechanism on FPGAs based on Efficient Reconfigurable Systolic Array
Authors: Ye Wenhua , Zhou Xu , Zhou Joey , Chen Cen , Li Kenli
Published: July 2022

Transformer model architectures have recently received great interest in natural language, machine translation, and computer vision, where attention mechanisms are their building blocks. However, the attention mechanism is expensive because of its intensive matrix computations and complicated data flow. The existing hardware architecture has some disadvantages for the computing structure of attention, such as inflexibility and low efficiency. Most of the existing papers accelerate attention by reducing the amount of computation through various pruning algorithms, which will affect the results to a certain extent with different sparsity. This paper proposes the hardware accelerator for the
multi-head attention (MHA)
on
field-programmable gate arrays (FPGAs)
with reconfigurable architecture, efficient systolic array, and hardware-friendly radix-2 softmax. We propose a novel method called
Four inputs Processing Element (FPE)
to double the computation rate of the
data-aware systolic array (SA)
and make it efficient and load balance. Especially, the computation framework is well designed to ensure the utilization of SA efficiently. Our design is evaluated on a Xilinx Alveo U250 card, and the proposed architecture achieves 51.3×, 17.3× improvement in latency, and 54.4×, 17.9× energy savings compared to CPU and GPU.
Temporal Robustness of Temporal Logic Specifications: Analysis and Control Design
Authors: Rodionova Alena , Lindemann Lars , Morari Manfred , Pappas George
Published: July 2022

We study the temporal robustness of temporal logic specifications and show how to design temporally robust control laws for time-critical control systems. This topic is of particular interest in connected systems and interleaving processes such as multi-robot and human-robot systems where uncertainty in the behavior of individual agents and humans can induce timing uncertainty. Despite the importance of time-critical systems, temporal robustness of temporal logic specifications has not been studied, especially from a control design point of view. We define synchronous and asynchronous temporal robustness and show that these notions quantify the robustness with respect to synchronous and asynchronous time shifts in the predicates of the temporal logic specification. It is further shown that the synchronous temporal robustness upper bounds the asynchronous temporal robustness. We then study the control design problem in which we aim to design a control law that maximizes the temporal robustness of a dynamical system. Our solution consists of a Mixed-Integer Linear Programming (MILP) encoding that can be used to obtain a sequence of optimal control inputs. While asynchronous temporal robustness is arguably more nuanced than synchronous temporal robustness, we show that control design using synchronous temporal robustness is computationally more efficient. This tradeoff can be exploited by the designer depending on the particular application at hand. We conclude the article with a variety of case studies.
Electrodeposition of Hydroxyapatite Coating on Ti6Al4V Alloy: Mechanistic Investigation of the Substrate Crystallographic Texture Effect
Authors: Amirnejad Mohabbat , Rajabi Mohammad , Jamaati Roohollah
Published: July 2022

Hydroxyapatite (HAp) coating electrodeposition was performed on three orthogonal surfaces of duplex-annealed Ti6Al4V alloy. This approach made it possible to investigate the effect of substrate crystallographic texture on hydroxyapatite coating properties exclusively from its microstructure. The coating characteristics were evaluated by scanning electron microscopy, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), laser surface profilometry, and potentiodynamic polarization test. The results showed that the presence of

10

1
¯

0

low-surface energy planes leads to smaller HAp deposits of 39 ± 4 μm due to the higher nucleation rate during electrodeposition. The highest surface roughness value of 75 ± 1 μm, as well as the lowest degree of crystallinity, equal to 23.5%, belonged to the surface in which

0001

and

11

2
¯

0

planes of high-surface energy placed in parallel to the surface. The electrochemical test results showed that the protective efficiency of HAp coatings was the highest for the surface with

10

1
¯

0

planes in parallel. This was attributed to the increased thickness and the low porosity content of the coating.
Design of Neodymium Vanadate Nanoparticles Decorated on Carbon–Boron Core-Shell Microspheres Matrix: An Electrochemical Detection of Nilutamide
Authors: Balasubramanian Sriram , Baby Jeena N. , Hsu Yung-Fu , Wang Sea-Fue , George Mary
Published: July 2022

The risk of pharmaceutical contamination is a growing ecological issue that affects every region of the globe. Continuous enhancement in the intake and negligent domestic ejection of these cytostatic agents are the main grounds for the occurrence of active residual metabolites in various aquatic environments. Electrochemical sensors are a capable substitute for other conventional analytical methods for monitoring toxic drug pollutants due to their beneficial features. Thus, the purpose of this work is to demonstrate an energy-efficient fabrication of neodymium vanadate integrated with boron-doped carbon (NdVO4/B–C) hybrid composite for the selective electrochemical determination of nilutamide (NT– anti-androgen drug). The choice of neodymium among rare earth metals has a significant impact on the electrochemical redox processes. In addition, rapid electron mobility for well-separated peaks and defined current potentials implies an improved active surface area in NdVO4. Therefore, the incorporation of B–C displays substantial enhancement in electronic conductivity, identifying the nanocomposite as a remarkable detecting candidate. The presence of multiple oxidation states of rare earth vanadate embedded on boron-doped activated carbon results in high synergistic interactions and advanced matrix structures that facilitate superlative electrocatalytic characteristics including the minimal Rct value (81.32 Ω.cm2), wide linear-range responses (0.001–344 μM), low limit of detection (0.0002 μM), high sensitivity (5.56 μA·μM−1·cm−2), good stabilities (operational stability = 3000 s and storage stability = 20 days), and excellent selectivity (with an excess concentration of 12 interfering compounds). It is noteworthy that the NdVO4/B–C modified electrode provides an outstanding recovery range (±99.91%–99.94%) for real sample analysis, thus marking it to be a competitive sensor option for commercial usage.
Passive Sweat-Based Pruritic Cytokine Detection and Monitoring System
Authors: Upasham Sayali , Rice Paul , Shahub Sarah , Dhamu Vikram Narayanan , Prasad Shalini
Published: July 2022

Interleukin-31 has been reported to be involved with chronic skin conditions like atopic dermatitis (AD). This work focuses on the development of a portable IL-31 detection system that works with passive sweat over the physiologically relevant range-150–620 pg ml−1. Four simulated flaring profiles were used to benchmark the IL-31 rise and fall detection capabilities of the sensor. These temporal profiles were generated according to the SCORAD range for severity of AD and were spanned across different dosing regimens. The sensing platform displays good sensitivity with a limit of detection of 50 pg ml−1 and dynamic range of 50–750 pg ml−1 for the flaring profiles in synthetic and human sweat, and with coupled portable electronics. Furthermore, in order to create a robust and predictive system, a machine learning algorithm was incorporated to create a flare prediction system. This algorithm shows high accuracy for the test data sets and provides the proof-of-concept for the use of ml coupled electrochemical systems for chronic diseases like AD.
Dietary fat composition shapes bile acid metabolism and severity of liver injury in a pig model of pediatric NAFLD
Authors: Manjarín Rodrigo , Dillard Kayla , Coffin Morgan , Hernandez Gabriella V. , Smith Victoria A. , Noland-Lidell Trista , Gehani Tanvi R. , Smart Hayden J. , Wheeler Kevin , Sprayberry Kimberly A. , Edwards Mark S. , Fanter Rob K. , Glanz Hunter , Immoos Chad , Santiago-Rodriguez Tasha M. , Blank Jason M. , Burrin Douglas G. , Piccolo Brian D. , Abo-Ismail Mohammed , La Frano Michael R. , Maj Magdalena
Published: July 2022

Bile acid homeostasis and signaling is disrupted in NAFLD and may play a central role in the development of the disease. However, there are no studies addressing the impact of diet on bile acid metabolism in patients with NAFLD. In juvenile Iberian pigs, we show that fatty acid composition in high-fat high-fructose diets affects BA levels in liver, plasma, and colon but these changes were not associated with the severity of the disease.
Transcriptomic responses are sex-dependent in the skeletal muscle and liver in offspring of obese mice
Authors: Kelly Amy C. , J. Rosario Fredrick , Chan Jeannie , Cox Laura A. , Powell Theresa L. , Jansson Thomas
Published: July 2022

Transcriptomic data support that fetuses of obese mothers modulate metabolism in both muscle and liver. These changes were strikingly sexually dimorphic in agreement with published findings that male offspring of obese dams exhibit pronounced metabolic disease earlier. In both males and females, the transcriptomic responses in the fetus were different than those at 3 mo, implicating adaptive mechanisms throughout adulthood.
Symbolic cues enhance express visuomotor responses in human arm muscles at the motor planning rather than the visuospatial processing stage
Authors: Contemori Samuele , Loeb Gerald E. , Corneil Brian D. , Wallis Guy , Carroll Timothy J.
Published: July 2022

Express arm muscle responses to suddenly appearing visual targets for reaching rapid have been attributed to the tecto-reticulo-spinal pathway in humans. We demonstrate that symbolic cues before target presentation can modulate such express arm muscle responses compatibly with the biomechanics of the cued reaching direction and the cue validity. This implies cortically mediated modulation of one or more sensorimotor transformation nodes of the subcortical express pathway.
More comprehensive proprioceptive stimulation of the hand amplifies its cortical processing
Authors: Hakonen Maria , Nurmi Timo , Vallinoja Jaakko , Jaatela Julia , Piitulainen Harri
Published: July 2022

Corticokinematic coherence (CKC) can be used to study cortical proprioceptive processing and localize proprioceptive hand representation. Our results indicate that proprioceptive stimulation delivered simultaneously at the same frequency to fingers (D2–D4) maximizes CKC strength allowing robust and fast localization of the human hand region in the sensorimotor cortex using MEG.
Asymmetrical transfer of adaptation between reaching and tracking: implications for feedforward and feedback processes
Authors: Coudiere Adrien , Fernandez Enzo , de Rugy Aymar , Danion Frederic R.
Published: July 2022

Reaching and manual tracking are thought to rely differently on feedforward and feedback processes. Here, we show that although nearly complete transfer of visuomotor adaptation occurs from reaching to tracking, only minimal transfer is found from tracking to reaching. Even though the update of feedforward processes (key for reaching) proved directly useful to feedback processes (key for tracking), the strong asymmetrical transfer suggests that feedback control can be updated independently from feedforward adaptation.
The Study of Estimation of Landfill Capacity through Dynamic System Approach
Authors: Warlina Lina , Listyarini Sri
Published: July 2022

In line with the increase in population, the production of waste will also grow every year. Unfortunately, the land used for final waste disposal (landfill) is extremely limited, especially in developing countries. This study aimed to predict landfill capacity in accommodating waste from the community based on daily waste input using a dynamic system and to provide alternative policies on landfill waste management. The analyzed data consisted of primary and secondary data, whereas the simulations applied system dynamic approach using Vensim software. The simulation results indicate that the waste production will reach 36,861,653 tons in 2030 if nothing is done. Assuming that all waste from the surrounding communities is accumulated in one landfill, Bantargebang landfill can only accommodate until 2022. To be able to use Bantargebang landfill up to 2030, the waste production must be reduced by 50% for organic waste and 50% for inorganic waste. From the analysis, it is proven that composting reduces a greater amount of waste than other waste reduction methods, namely recycling or reusing, by the same percentage. Waste sorting is therefore highly recommended to be done by the community in every household as a basis to facilitate further handling. The community can play an active role in reducing waste, e.g., by composting organic waste and recycling or reusing inorganic waste. Furthermore, regulations should be made that can give punishment to households that do not carry out segregation. Reliable infrastructure for waste management needs to be facilitated, and counseling/training/outreach on waste sorting to the community must also be provided at the district level.
Restoration Design of Chu Architecture: Zhanghua Tower Based on VR Technology
Authors: He Fan
Published: July 2022

The restoration design of Chinese traditional ancient buildings by VR technology can help to form a new media of ancient building culture and promote the process of digital protection in buildings. Studying the restoration design of Chinese traditional ancient buildings under VR technology can effectively protect the ancient building culture. This paper analyzes the unique design style of Chu architecture and integrates it into VR architecture restoration design. By taking the Zhanghua tower, a representative building in Chu, as an example, this paper expounds on the realization process of restoration design of ancient buildings in Chu. In addition, through 3 ds max and Unity3D platform, the plane shape description, virtual model construction, virtual model optimization, and virtual scene construction are completed, and the virtual space experience of Chu architecture is realized by using Virtools software.
Deep Learning-Based Natural Language Processing Methods for Sentiment Analysis in Social Networks
Authors: Li Yan
Published: July 2022

This paper presents an in-depth study of the sentiment of social network communication through a deep learning-based natural language processing approach and designs a corresponding model to be applied in the actual social process. Specifically, the network can dynamically select the most important word in the current state according to the information available and achieve the accurate recognition of the dynamically changing important content in a sentence. Based on this, the semantic understanding of the whole sentence is achieved through a continuous cycle of the process. In addition, considering that the semantic representation of natural language is highly dependent on contextual information, the lack of contextual information will lead to the ambiguity and inaccuracy of semantic representation. In this paper, we study the sentiment analysis algorithms in social networks at two levels, unimodal and multimodal, and construct a text sentiment analysis model and a picture-text multimodal sentiment analysis model in social networks, respectively. By comparing the experiments with the existing models on several datasets, the accuracy of the two models exceeded the benchmark models by 4.45% and 5.2%, respectively, which verified the effectiveness of the two models. The feasibility of applying the optimized convolutional neural network recurrent optimization network to social network sentiment analysis is verified by practically applying the optimized convolutional neural network recurrent optimization network to single task and multitask and comparing other existing deep learning classifiers.
Application of Multipopulation Genetic Algorithm in Industrial Special Clothing Design
Authors: Zhang Xianglei , Yang Cuiyu
Published: July 2022

Industrial special clothing refers to the clothing worn by employees of industrial enterprises and departments in order to dress uniformly, facilitate work, or protect their bodies from external injuries. They have the common characteristics of practicality and identification. This kind of clothing includes many styles, such as uniforms, shirts, jackets, overalls, skirts, aprons, and headscarves, which are also applicable in different fields. For example, the clothing for high-temperature operation requires high temperature resistance and comfort, while the clothing for high-altitude operation requires high clothing strength and can play a protective role. General interactive genetic algorithm only supports single user evaluation. The results can only reflect the preferences of a single user. The product designed by interactive genetic algorithm needs to meet the needs of as many users as possible, and a multiuser interactive genetic algorithm suitable for population design is proposed. The detailed design of three main modules of the algorithm, namely, population initialization module, single population module, and multipopulation module, is given. Finally, the algorithm and the general single user interactive genetic algorithm are applied to the garment design system for comparative experiments. The effectiveness of the algorithm in group design is verified.
AIOps Architecture in Data Center Site Infrastructure Monitoring
Authors: Dong Wei
Published: July 2022

AIOps (artificial intelligence for IT operations) has been growing rapidly in recent years. However, it can be seen that the vast majority of AIOps applications are implemented in the IT domain. In contrast, there are few applications in the data center infrastructure domain. Many real-world practices show that a working architecture or algorithm cannot be directly replicated from other domains due to completely different business scenarios and different data characteristics. In this paper, an AIOps architecture for the data center infrastructure monitoring domain is presented. A proven working architecture is given in terms of core modules, such as technical architecture, machine learning algorithms, big data, and business applications, and details are designed in practice. This paper focuses on the technical part and not on each part of the architecture work. In other words, NFRs (nonfunctional requirements), such as performance, availability, manageability, and security, will not be discussed in this paper.
Triad1 Promotes the Inflammatory Response and Neuronal Apoptosis to Aggravate Acute Spinal Cord Injury in Rats
Authors: Shen Xiang , Zhang Yang , Zhu Hengjie , Sun Yinming , Wang Wenqiang , Zhou Zheng , Li Chengcun
Published: July 2022

Objective. Spinal cord injury (SCI) is one of the most devastating central injuries, resulting in serious locomotor deficits. Triad1 is known to play an important role in SCI, but its effects on the inflammatory response and physiological behavior have not been thoroughly studied. This study is aimed at examining the effects of Triad1 on the inflammatory response and neuronal injury in acute SCI in rats. Methods. Twenty-four male Sprague–Dawley (SD) rats were randomly divided into a control group, SCI group, sh-NC group, and Triad1 knockout group (sh-Triad1). The Basso Beattie Bresnahan locomotor rating scale was utilized for the assessment of the motor ability of rats. Hematoxylin and eosin (H&E), Luxol fast blue (LFB), and TUNEL staining were used to assess the pathological injury, demyelination, and neuronal apoptosis, respectively. ELISA was used to detect the levels of IL-1β, IL-10, and TNF-α, and qRT-PCR was used to examine the expression level of Triad1. Furthermore, the protein levels of Triad1, Bax, Bcl-2, and cleaved caspase-3 were determined using western blotting. Results. The Triad1 expression level was upregulated in damaged spinal cord tissue. Knockdown of Triad1 improved motor function and reduced SCI as well as apoptosis of spinal cord neurons. In addition, the knockdown of Triad1 inhibited the inflammatory response caused by SCI. Conclusion. Knockdown of Triad1 can reduce SCI in rats with acute SCI by inhibiting the inflammatory response and apoptosis.
Analysis of the Effect of Laparoscopic Cholecystectomy for Acute Cholecystitis after Percutaneous Transhepatic Gallbladder Puncture and Drainage
Authors: Yang Jia-Peng , Tian Zhong
Published: July 2022

Objective. To assess the effect of laparoscopic cholecystectomy for acute cholecystitis after percutaneous transhepatic gallbladder drainage (PTGBD). Methods. A total of 70 patients with acute cholecystitis diagnosed and treated in our hospital between April 2020 and November 2021 were recruited and assigned to receive either conventional treatment (conventional group) or PTGBD plus laparoscopic cholecystectomy (experimental group) according to the order of admission (with January 2021 as the cut-off time point), with 35 cases in each group. Outcome measures included treatment outcomes, surgical indices, and postoperative recovery. Results. Patients in the experimental group showed significantly less intraoperative hemorrhage volume and shorter operative time, time-lapse before passing gas, and hospital stay (83.15 ± 31.17, 32.54 ± 12.61, 23.02 ± 4.61, 7.98 ± 3.24) versus those in the conventional group (120.56 ± 30.55, 61.01 ± 15.54, 28.15 ± 5.91, 11.95 ± 4.15) (

P
<
0.05

). The incidence of conversion to open surgery and postoperative drainage in the experimental group was significantly lower (2.86%, 5.71%) than that of the conventional group (25.71%, 45.71%) (

P
<
0.05

). The differences in the postoperative body temperature of the two groups did not come up to statistical standard (

P
>
0.05

). The experimental group had faster body temperature recovery and leukocyte recovery and better leukocyte levels (1.25 ± 0.56, 2.36 ± 0.48, 7.92 ± 1.36) than the conventional group (3.11 ± 1.05, 5.41 ± 0.63, 10.52 ± 2.78) (

P
<
0.05

). There was 1 (2.86%) case of pneumothorax and 1 (2.86%) case of intestinal bleeding in the experimental group, and there were 2 (5.71%) cases of biliary leakage, 3 (8.57%) cases of pneumothorax, 4 (11.43%) cases of intestinal bleeding, 5.71% cases of incisional infection, 1 (2.86%) case of respiratory failure, and 1 (2.86%) case of liver damage in the conventional group. The experimental group showed a significantly lower incidence of complications (5.71%) versus the conventional group (37.14%) (

P
<
0.05

). Conclusion. PTGBD plus laparoscopic cholecystectomy for acute cholecystitis effectively improves surgical safety, promotes patients' postoperative recovery, and reduces the incidence of conversion to open surgery and postoperative complications with a high safety profile. Further trials are, however, required prior to clinical promotion.
Mechanical Performance Test and Numerical Simulation Analysis of Building Steel Plate and Concrete Composite Structure
Authors: Liu Qian
Published: July 2022

The study aims to continuously improve the level of the construction industry, such as the improvement of construction capacity and efficiency and reduction of the project cost and construction period, and find a specific way to improve the development of the construction industry. First, the study analyzes the research status of mechanical properties of horizontal joints, vertical joints, and the overall structure of worldwide prefabricated buildings. Next, the built-in steel fabricated concrete shear wall model is established. Moreover, the quasi-static experimental analysis is conducted on the joints of the fabricated shear wall with built-in section steel. The finite element software is used to analyze the numerical simulation test of the new built-in shear wall. According to the relevant test parameters, the finite element model is constructed, and the parameters are set. Finally, the shear wall model is established and tested by a simulation experiment, and the simulation results are compared with the numerical simulation results. The final results show that the proposed connection mode of the reinforced skeleton and new fabricated joints improves the stability of prefabricated buildings. The use of the quasi-static test to test the relevant performance parameters has a short calculation time, high efficiency, and high parameter optimization accuracy. It can better simulate the actual working conditions and the actual stress-strain and damage failure conditions. Moreover, the conclusion is drawn that the shear wall structure with steel plate concrete has good ductility and deformation capacity. The study has a certain reference significance for the construction optimization of steel plate concrete prefabricated buildings and related research in the future.
[Retracted] Synthesis and Evaluation of Finasteride‐Loaded HPMC‐Based Nanogels for Transdermal Delivery: A Versatile Nanoscopic Platform
Authors: Ahmad Aousaf , Ahmad Mahmood , Minhas Muhammad Usman , Sarfraz Muhammad , Sohail Muhammad , Khan Kifayat Ullah , Tanveer Sana , Ijaz Shakeel
Published: July 2022

Herein, we report nanogels comprising diverse feed ratio of polymer hydroxypropyl methylcellulose (HPMC), monomer acrylic acid (AA), and cross‐linker methylene bisacrylamide (MBA) fabricated for transdermal delivery of finasteride (FIN). Free radical solution polymerization method with subsequent condensation was employed for the synthesis using ammonium per sulfate (APS) and sodium hydrogen sulfite (SHS) as initiators. Carbopol‐940 gel (CG) was formulated as assisting platform to deliver FIN nanogels transdermally. Developed formulations were evaluated by several in vitro, ex vivo, and in vivo parameters such as particle size and charge distribution analysis, Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), X‐ray diffractogram (XRD), rheological testing, in vitro swelling and drug release, and ex vivo skin permeation, irritation, and toxicity assessment. The results endorsed the nanogel formation (117.3 ± 29.113 nm), and the impact of synthesizing method was signified by high yield of nanogels (≈91%). Efficient response for in vitro swelling and FIN release was revealed at pH 5.5 and 7.4. Skin irritation and toxicity assessment ensured the biocompatibility of prepared nanocomposites. On the basis of the results obtained, it can be concluded that the developed nanogels were stable with excellent drug permeation profile across skin.
Cultural and Creative Product Design and Image Recognition Based on the Convolutional Neural Network Model
Authors: Han Sangyun , Shi Zhifang , Shi Yongkang
Published: July 2022

The development in technology has resulted in the utilization of artificial intelligence systems in various fields. In this research, we are going to study cultural and creative product design and image recognition based on a convolutional neural network (CNN) model. A convolutional neural network is referred to as a type of artificial neural network (ANN) that is used to analyze visual images. Our proposed system deploys a convolutional neural network model for image recognition in the field of cultural and creative product design. Cultural and creative products are becoming more popular these days. The cultural and creative products are referred to as innovative products or innovative new product design which makes use of the cultural symbols and other cultural factors in their design. In simple words, it is the integration of culture and creativity in a new product design. The main aspect of cultural creative products is the incorporation of cultural features into a new product, thus obtaining a creative- and culture-based product. The study results have proved that CNN has provided an accuracy of 87%.
Anti‐Metalloprotease P‐I Single‐Domain Antibodies: Tools for Next‐Generation Snakebite Antivenoms
Authors: Silva Marcela C. S. , Pereira Soraya S. , Gouveia Marilia P. , Luiz Marcos B. , Sousa Rosa M. O. , Kayano Anderson M. , Francisco Aleff F. , Prado Nidiane D. R. , Dill Leandro S. M. , Fontes Marcos R. M. , Zanchi Fernando B. , Stabeli Rodrigo G. , Soares Andreimar M. , Zuliani Juliana P. , Fernandes Carla F. C.
Published: July 2022

In order to address the global antivenom crisis, novel antivenoms need to present high therapeutic efficacy, broad neutralization ability against systemic and local damage, sufficient safety, and cost‐effectiveness. Due to biological characteristics of camelid single‐domain antibodies (VHH) such as high affinity, their ability to penetrate dense tissues, and facility for genetic manipulation, their application in antivenoms has expanded considerably. VHHs that are active against the metalloprotease BjussuMP‐II from the snake Bothrops jararacussu were selected. After isolation of BjussuMP‐II, a camelid was immunized with the purified toxin in order to construct the recombinant phage library. Following a round of biopanning, 52% of the selected clones were able to recognize BjussuMP‐II in an ELISA assay. After sequencing, seven sequence profiles were identified. One selected clone (VHH61) showed cross‐reactivity to B. brazili venom, but did not recognize the Crotalus and Lachesis genera, indicating specificity for the Bothrops genus. Through in vitro tests, the capacity to neutralize the toxicity triggered by BjussuMP‐II was observed. Circular dichroism spectroscopy indicated a robust secondary structure for VHH61, and the calculated melting temperature (TM) for the clone was 56.4°C. In silico analysis, through molecular docking of anti‐BjussuMP‐II VHHs with metalloprotease, revealed their potential interaction with amino acids present in regions critical for the toxin’s conformation and stability. The findings suggest that anti‐BjussuMP‐II VHHs may be beneficial in the development of next‐generation antivenoms.
Qige Huxin Formula Attenuates Isoprenaline-Induced Cardiac Fibrosis in Mice via Modulating Gut Microbiota and Protecting Intestinal Integrity
Authors: Shi Lipeng , Du Xuqin , Zuo Biao , Hu Jinyuan , Cao Wenfu
Published: July 2022

Background. The composition and metabolic activities of gut microbiota are strongly interconnected with cardiac fibrosis (CF) and heart failure (HF). Qige Huxin formula (QHF), a traditional Chinese medicine (TCM) formulation originating from a classical Fangji Huangqi decoction, has been widely used to clinically treat HF for decades. However, it is still unclear whether QHF alleviates CF by modulating gut microbiota and intestinal integrity. Purpose. This study aimed to investigate the cardioprotective effects of QHF in isoprenaline-induced CF through modulating gut microbiota and intestinal integrity. Methods. Fifty mice were randomly divided into five groups after one week of acclimatization feeding: control group, model group, 2.56 g/kg/d group (low-dose QHF), 5.12 g/kg/d group (high-dose QHF), and meto group (15 mg/kg/d). The CF model was established by subcutaneously injecting the mice with isoprenaline (10 mg/kg/d for 14 days), followed by QHF treatment. The heart volume, cardiac weight index (CWI), serum myocardial enzymes, serum inflammatory cytokines, serum lipopolysaccharide, histopathology of the heart and colon tissues, ZO-1, and occludin of colon tissues were then measured. Fecal samples from mice were analyzed using 16S rRNA sequencing. Results. QHF treatment significantly reduced heart volume, CWI, and serum CK and CK-MB levels, attenuated cardiac histopathological alterations, and alleviated CF. QHF treatment also downregulated TNF-α, IL-1β, and IL-6 in serum. Moreover, QHF treatment decreased the serum level of lipopolysaccharide and maintained intestinal integrity by upregulating ZO-1 and occludin. The 16S rRNA microbiota analysis revealed that QHF treatment increased the relative abundance of Marvinbryantia and Phascolarctobacterium. Conclusions. QHF treatment exerts cardioprotective effects through modulating gut microbiota, protecting intestinal integrity, and alleviating inflammation. This study shows that gut microbiota may enhance heart-gut interaction.
Research on Improving the Accuracy of Ideological and Political Education in Colleges under Artificial Intelligence Technology in the Era of Big Data
Authors: Sun Yifei , Zheng Huilin
Published: July 2022

The construction of the index system is incomplete in the accuracy evaluation of ideological and political work in Colleges and universities, which leads to the poor effect of the accuracy evaluation of ideological and political work in Colleges and universities. Therefore, this paper proposes to introduce artificial intelligence big data technology to improve the accuracy of ideological and political work in Colleges and universities. Analyze and improve the starring participants in ideological and political work in Colleges and universities, determine the basic principles to improve the accuracy of ideological and political work in Colleges and universities, determine the importance indicators of ideological and political teachers’ teaching, students’ classroom learning, after-school practice, and school ideological and political work, and divide them into primary indicators and secondary indicators. The naive Bayesian model is used to decompose the accuracy indicators of ideological and political work in Colleges and universities, build the accuracy evaluation model of ideological and political work in Colleges and universities, and realize the research on improving the accuracy of ideological and political work in Colleges and universities. The experimental results show that this method can effectively improve the integrity of the accuracy evaluation index of ideological and political work in Colleges and universities and improve the accuracy evaluation effect of ideological and political work in Colleges and universities.
Prediction of Employment Index for College Students by Deep Neural Network
Authors: Wu Dan
Published: July 2022

With the acceleration of popularization of higher education in China and the intensification of employment difficulties for college graduates, the employment field has gradually widened, the number of entrepreneurs has gradually increased, and the regional differences are obvious. The employment difficulty of college graduates has aroused wide-spread concern in the society. Therefore, the convolution neural network (CNN) is used to establish a prediction and evaluation model for the employment development trend of college graduates in this paper. The feasibility and practicability are proved by a case, which is of great significance for the government and colleges to provide decision-making support and suggestions to solve the problem of difficult employment.
Product Shape Design Scheme Evaluation Method Based on Spatial Data Mining
Authors: Wei Qian
Published: July 2022

The stage of product modeling design implies a lot of complex tacit knowledge, which is the embodiment of the design concept centered on product modeling design and is also the hot spot and difficulty of modern design theory and method research. Aiming at the evaluation and decision of product modeling design scheme, a decision-making method of approaching ideal solution ranking based on grey relational analysis was proposed, which realized the convergence of tacit knowledge. The empty association rule is an important knowledge content of spatial data mining. A fuzzy genetic algorithm can solve the characteristics of random and nonlinear problems and solve the data mining problems of spatial association rules. The fuzzy genetic algorithm of discrete crossover probability and mutation probability is applied to data mining of spatial association rules in a spatial database, the coding method of the fuzzy genetic algorithm and the construction of fitness function are discussed, and the process of mining spatial association rules is given. The results show that the method of mining s association rules with the fuzzy genetic algorithm is feasible and has higher mining efficiency. This paper discusses the construction method of designing a decision support database based on linear regression and neural network and then proposes a decision method combining TOPSIS and grey relational analysis, which comprehensively considers the position and shape of the scheme data curve.
Correlation between the Dissemination of Classic English Literary Works and Cultural Cognition in the New Media Era
Authors: Guo Weiwei
Published: July 2022

With the continuous development of new media technology, the spiritual needs of the masses have been greatly satisfied and the aesthetic ability has also been significantly improved compared with the past. From the current point of view, “literary works,” as the spiritual food of contemporary people, are promoting social spirit. The use of natural language processing and knowledge graph technology can improve cultural cognition to promote the dissemination and development of classic English literature, which has become a necessary means of dissemination of classic English literature. Most of the existing classic English literary works are appreciated based on modern literature datasets. Nowadays, with the continuous development of new media technology, there are fewer studies on the dissemination and cultural cognition of classic English literary works. This makes it impossible for readers to obtain cultural cognition from classic English literary works, making it difficult for the dissemination and development of classic English literary works. In view of the above problems, using natural language processing and knowledge graph technology, taking Shakespeare's play “Hamlet” represented by classic English literary works as an example, the research on the construction method of knowledge graph is carried out and the cultural characteristics in literary works are extracted and analyzed. In parsing, a bidirectional gated recurrent unit network model based on hybrid character embedding is proposed. Based on n-gram embedding, by combining pretraining embedding and radical embedding, it can fully consider the rich semantic information in English literature works to extract. Feature: in terms of named entity recognition, based on the existing iterative atrous convolutional network model, an iterative atrous convolutional network model is proposed. To get the best sequence label and get the last labeled entity information, in terms of knowledge graph construction and visual query, a workflow method for building knowledge graph from unstructured text is proposed and a flask-based knowledge graph visual query system is designed, which applies the best model of the above two tasks. We decode the complete “Hamlet” text, extract entities and their semantic links as nodes and relationships in the knowledge graph, store knowledge through the graph database, and finally form a visual query system that combines the front and back end.