bluuebunny/crossref_metadata_2025 huggingface dataset:
The response of calcareous nannoplankton to the latest Pliensbachian–early Toarcian environmental changes in the Camino Section (Basque Cantabrian Basin, northern Spain)
Authors: Fraguas Ángela , Gómez Juan José , Goy Antonio , Comas-Rengifo María José
Published: June 2021

Quantitative analysis performed on latest Pliensbachian–early Toarcian calcareous nannofossil assemblages from the Camino section (Basque Cantabrian Basin) allowed their response to the environmental changes recorded during this time interval to be deciphered, characterized by an extinction event. The results were introduced within a principal component analysis and compared with the stable isotope and total organic carbon curves. During the latest Pliensbachian, the Mirabile and the lowermost part of the Semicelatum Ammonite Subzones,
Schizosphaerella
,
Bussonius prinsii
,
Biscutum finchii
,
Calcivascularis jansae
and
Similiscutum avitum
, taxa that probably thrived in rather cold waters, dominated the calcareous nannofossil assemblages. Coinciding with warmer and wetter conditions, which probably led to an increase in surface water fertility, recorded slightly below the extinction boundary, the mesotrophic taxa
B. novum
,
L. hauffii
and
Calyculus
spp. were dominant. Nevertheless,
T. patulus
and
C. jansae
, which became extinct just below the extinction boundary, show preferences for oligotrophic conditions. Salinities similar to those of modern oceans have been inferred around the extinction boundary, considering the coupling between the abundances of
Calyculus
spp. and the species richness together with the absence of black shales. After the extinction boundary, nannofossil assemblages were dominated by the deep-dwelling
C. crassus
and the shallow-dwelling
Lotharingius
species, interpreted as opportunistic taxa. This work confirms that calcareous nannofossils are a really useful tool for palaeoceanographic and palaeoenvironmental reconstructions, especially in terms of climatic changes.
Modeling Complementarity in Behavior Data with Multi-Type Itemset Embedding
Authors: Wang Daheng , Zeng Qingkai , Chawla Nitesh V. , Jiang Meng
Published: June 2021

People are looking for complementary contexts, such as team members of
complementary skills
for project team building and/or reading materials of
complementary knowledge
for effective student learning, to make their behaviors more likely to be successful. Complementarity has been revealed by behavioral sciences as one of the most important factors in decision making. Existing computational models that learn low-dimensional context representations from behavior data have poor scalability and recent network embedding methods only focus on preserving the similarity between the contexts. In this work, we formulate a behavior entry as a set of context items and propose a novel representation learning method,
Multi-type Itemset Embedding
, to learn the context representations preserving the itemset structures. We propose a
measurement of complementarity
between context items in the embedding space. Experiments demonstrate both effectiveness and efficiency of the proposed method over the state-of-the-art methods on behavior prediction and context recommendation. We discover that the complementary contexts and similar contexts are significantly different in human behaviors.
Self-Organization of Cellular Units
Authors: Mitchison Timothy J. , Field Christine M.
Published: June 2021

The purpose of this review is to explore self-organizing mechanisms that pattern microtubules (MTs) and spatially organize animal cell cytoplasm, inspired by recent experiments in frog egg extract. We start by reviewing conceptual distinctions between self-organizing and templating mechanisms for subcellular organization. We then discuss self-organizing mechanisms that generate radial MT arrays and cell centers in the absence of centrosomes. These include autocatalytic MT nucleation, transport of minus ends, and nucleation from organelles such as melanosomes and Golgi vesicles that are also dynein cargoes. We then discuss mechanisms that partition the cytoplasm in syncytia, in which multiple nuclei share a common cytoplasm, starting with cytokinesis, when all metazoan cells are transiently syncytial. The cytoplasm of frog eggs is partitioned prior to cytokinesis by two self-organizing modules, protein regulator of cytokinesis 1 (PRC1)-kinesin family member 4A (KIF4A) and chromosome passenger complex (CPC)-KIF20A. Similar modules may partition longer-lasting syncytia, such as early Drosophila embryos. We end by discussing shared mechanisms and principles for the MT-based self-organization of cellular units.
Understanding the Complex Phage-Host Interactions in Biofilm Communities
Authors: Pires Diana P. , Melo Luís D.R. , Azeredo Joana
Published: June 2021

Bacteriophages and bacterial biofilms are widely present in natural environments, a fact that has accelerated the evolution of phages and their bacterial hosts in these particular niches. Phage-host interactions in biofilm communities are rather complex, where phages are not always merely predators but also can establish symbiotic relationships that induce and strengthen biofilms. In this review we provide an overview of the main features affecting phage-biofilm interactions as well as the currently available methods of studying these interactions. In addition, we address the applications of phages for biofilm control in different contexts.
The Importance of Wafer Edge in Wafer Bonding Technologies and Related Wafer Edge Engineering Methods
Authors: Knechtel Roy , Schwarz Uwe , Dempwolf Sophia , Klingner Holger , Nevin Andy , Lindemann Gunnar , Schikowski Marc
Published: June 2021

Wafer bonding is an important process step in microsystem technologies for processing engineered substrates and for capping. Usually, the work and literature are focused on the bonding of the main wafer area. However, in recent years MEMS technologies have become more complex, with more process steps after wafer bonding. Accordingly, the wafer edge is becoming more and more important, and must be engineered. Methods for realizing this are discussed in this paper.
The Segmentation of Road Scenes Based on Improved ESPNet Model
Authors: Jin Ran , Yu Tongrui , Han Xiaozhen , Liu Yunpeng
Published: June 2021

Image segmentation is an important research in image processing and machine vision in which automated driving can be seen the main application scene of image segmentation algorithms. Due to the many constraints of power supply and communication in in-vehicle systems, the vast majority of current image segmentation algorithms are implemented based on the deep learning model. Despite the ultrahigh segmentation accuracy, the problem of mesh artifacts and segmentation being too severe is obvious, and the high cost, computational, and power consumption devices required are difficult to apply in real-world scenarios. It is the focus of this paper to construct a road scene segmentation model with simple structure and no need of large computing power under the premise of certain accuracy. In this paper, the ESPNet (Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation) model is introduced in detail. On this basis, an improved ESPNet model is proposed based on ESPNet. Firstly, the network structure of the ESPNet model is optimized, and then, the model is optimized by using a small amount of weakly labeled and unlabeled scene sample data. Finally, the new model is applied to video image segmentation based on dash cam. It is verified on Cityscape, PASCAL VOC 2012, and other datasets that the algorithm proposed in this paper is faster, and the amount of parameters required is less than 1% of other algorithms, so it is suitable for mobile terminals.
Tennis Online Teaching Information Platform Based on Android Mobile Intelligent Terminal
Authors: Wang Qingyu
Published: June 2021

With the development of the information age, there is almost one mobile smart device based on android, which is inseparable from mobile smart devices in both learning and life. In order to explore the effects of mobile smart devices on tennis teaching, this article mainly introduces the research on the tennis online teaching information platform based on android mobile smart terminals. This article first uses the android system framework and software architecture to design the technical aspects of the tennis online teaching information platform and then analyzes and improves the functional and nonfunctional requirements of the tennis online teaching information platform and students’ needs for mobile learning. For the design of aspects other than the technology of the online teaching information platform, the control group and the experimental group were designed to carry out teaching experiments, comparing the traditional teaching methods and the teaching methods of the online teaching information platform to bring out different teaching effects to tennis teaching. The results show that online teaching has a better learning effect on tennis skills and tennis theory knowledge, and the academic performance of the traditional teaching method is improved by 20%. In terms of increasing interest in tennis courses, the online teaching information platform has improved 70% of students’ interest.
Hotel Management Evaluation Index System Based on Data Mining and Deep Neural Network
Authors: Chen Peilin
Published: June 2021

In recent years, with the increase in computing power, the sharp drop in costs, and the successful use of data management technology, a large amount of data has been rapidly spread and stored in various fields of the company. How can we passively find active data and form active knowledge from these big data information, know how to use equipment to quickly and accurately obtain high‐quality information, use the obtained information to guide users in decision‐making, and provide more economic and social benefits? This paper focuses on the study of the classifier model based on BP neural network, and the combination of BP neural network model and other optimization algorithms, including genetic algorithm (GA), particle swarm algorithm (PSO), Adaboost algorithm, GA, and PSO have global search performance. It is mostly used to optimize the weight threshold of the network and the number of hidden layer nodes. The Adaboost algorithm builds an enhanced classifier based on the idea of integration. At present, data mining technology has moved from the laboratory research stage to the commercialization stage. The use of widely owned knowledge and information as analysis tools can be used in many fields: such as financial analysis, engineering design, scientific research, management, and production control. At the end of this paper, the improved Adaboost_BP classifier is used, and the result proves that the efficiency of hotel management has increased by at least 75%.
Extraction and Recognition Method of Basketball Players’ Dynamic Human Actions Based on Deep Learning
Authors: Wang Qiulin , Tao Baole , Han Fulei , Wei Wenting
Published: June 2021

The extraction and recognition of human actions has always been a research hotspot in the field of state recognition. It has a wide range of application prospects in many fields. In sports, it can reduce the occurrence of accidental injuries and improve the training level of basketball players. How to extract effective features from the dynamic body movements of basketball players is of great significance. In order to improve the fairness of the basketball game, realize the accurate recognition of the athletes’ movements, and simultaneously improve the level of the athletes and regulate the movements of the athletes during training, this article uses deep learning to extract and recognize the movements of the basketball players. This paper implements human action recognition algorithm based on deep learning. This method automatically extracts image features through convolution kernels, which greatly improves the efficiency compared with traditional manual feature extraction methods. This method uses the deep convolutional neural network VGG model on the TensorFlow platform to extract and recognize human actions. On the Matlab platform, the KTH and Weizmann datasets are preprocessed to obtain the input image set. Then, the preprocessed dataset is used to train the model to obtain the optimal network model and corresponding data by testing the two datasets. Finally, the two datasets are analyzed in detail, and the specific cause of each action confusion is given. Simultaneously, the recognition accuracy and average recognition accuracy rates of each action category are calculated. The experimental results show that the human action recognition algorithm based on deep learning obtains a higher recognition accuracy rate.
Livestock Production Challenges and Improved Forage Production Efforts in the Damot Gale District of Wolaita Zone, Ethiopia
Authors: Mengistu Shimelis , Nurfeta Ajebu , Tolera Adugna , Bezabih Melkamu , Adie Abera , Wolde-meskel Endalkachew , Zenebe Mesfin
Published: June 2021

This study was conducted to identify major livestock production constraints and improved forage production efforts in the Damot Gale district. Four representative kebeles, two associated with our NGO project and two from nonproject outreach activities, were selected. Forty farmers from each kebele were randomly chosen for the purpose of individual interviews using a semistructured questionnaire. Data collected were analyzed using SPSS (version 20) and Excel. The topmost livestock production constraint was feed shortage where a larger proportion of farmers (75.6%) suffered from the problem with higher (

p

 ≤ 0.01) severity in nonproject intervention areas. Of these, 38.6% were challenged for a period of three months while another 61.4% suffered for about four months. Purchasing grass (31.4%) and concentrate (33.5%) and feeding enset (Ensete ventricosum) leaf (21.49%) were the most commonly adopted coping mechanisms to alleviate feed shortages during the dry season, while using purchased grass and enset leaf was the main coping strategy in nonproject intervention (

p

 ≤ 0.01) areas. The majority of households (90.75%) participate in improved forage production regardless of farm size. Desho grass (Pennisetum pedicellatum) (71.38%) and elephant grass (Pennisetum purpureum) (42.63%) are the most common improved forages in both study areas. These forages are produced for the purpose of two or more functions (feed, cash, and preventing erosion) that vary (

p

 ≤ 0.01) among intervention status. Major niche locations adopted for improved forage production include farm land, soil and water conservation structures, and perimeter fencing. Greatest constraints on improved forage production were seed/material shortage followed by land shortage and lack of awareness. Project intervention (

p

 ≤ 0.01), tropical livestock unit (TLU) holding (

p

 ≤ 0.01), and forage seed/planting material access (

p

 < 0.05) were identified as factors (among others) having significant relationship with improved forage development. Strong extension services and efficient input delivery for farmers are vital to support profitable livestock production and resource utilization.
N-Tier Soft Set Data Model: An Approach to Combine the Logicality of SQL and the Flexibility of NoSQL
Authors: Wu Jiang , Ni Du , Xiao Zhi
Published: June 2021

To process a huge amount of data, computing resources need to be organized in clusters that can be scaled out easily. Still, traditional SQL databases built on the relational data model are difficult to be put to use in such clusters, which has motivated the movement named NoSQL. However, NoSQL databases have their limits by using their own data models. In this paper, the original soft set theory is extended, and a new theory system called n-tier soft set is brought up. We systematically constructed its concepts, definitions, and operations, establishing it as a novel soft set algebra. And some features of this algebra display its natural advantages as a data model which could combine the logicality of the SQL model (also known as the relational model) and the flexibility of NoSQL models. This data model provides a unified and normative perspective logic for organizing and manipulating data, combines metadata (semantic) and data to form a self-described structure, and combines index and data to realize fast locating and correlating.
A Study on Gentiana dahurica Fisch Ethanol Extract Alleviating Alcoholic Liver Disease in Mice: A Metabolomic Analysis of the Liver
Authors: Cao Houkang , Guo Yanxiu , Jin Ling
Published: June 2021

We clarified the hepatoprotective effect of Gentiana dahurica Fisch ethanol extract (GDEE) in our previous study, and we further revealed the mechanism with the help of metabolomics technology in this study. The livers from Control group, Alcohol group, and Alcohol + GDEE group were analyzed by metabolomics. The metabolites in the liver were separated by ultra-high-performance liquid chromatography (UHPLC) and were tentatively identified using mass spectrometry (MS)/MS analysis. Differential metabolites were defined with VIP > 1 and

P
<
0.05

. Principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA) were applied to analyze differences among these groups. The results showed that the groups could be clearly distinguished by PCA and OPLS-DA analysis. Alcohol and GDEE could change the overall profile of liver metabolites. Alterations in liver tissues of ALD mice induced by alcohol were mainly involved in the dipeptides, purine and pyrimidine metabolism and glucose and lipid metabolism, which could be partly affected by GDEE. This study revealed that the mechanism of GDEE in alleviating ALD had the characteristics of multitarget and multipathway.
Global Dynamics of Secondary DENV Infection with Diffusion
Authors: Elaiw A. M. , Alofi A. S.
Published: June 2021

During the past eras, many mathematicians have paid their attentions to model the dynamics of dengue virus (DENV) infection but without taking into account the mobility of the cells and DENV particles. In this study, we develop and investigate a partial differential equations (PDEs) model that describes the dynamics of secondary DENV infection taking into account the spatial mobility of DENV particles and cells. The model includes five nonlinear PDEs describing the interaction among the target cells, DENV-infected cells, DENV particles, heterologous antibodies, and homologous antibodies. In the beginning, the well-posedness of solutions, including the existence of global solutions and the boundedness, is justified. We derive three threshold parameters which govern the existence and stability of the four equilibria of the model. We study the global stability of all equilibria based on the construction of suitable Lyapunov functions and usage of Lyapunov–LaSalle’s invariance principle (LLIP). Last, numerical simulations are carried out in order to verify the validity of our theoretical results.
Numerical Simulation of Multiple Explosively Formed Projectile Warhead Forming Characteristics considering Various Materials
Authors: Ma Guangsong , He Guanglin , Liu Yukuan , Zhang Yulong
Published: June 2021

To study the influence of different liner structures and materials (copper, steel, and tungsten) on the forming characteristics of multiple explosively formed projectile (MEFP) with integrated liner and shell designs, three types of liners with different structures were designed. LS‐DYNA was used for numerical simulation, and the results show that the thickness change at the center of the liner has no obvious influence on the shape of the explosively formed projectile (EFP). However, the curvature radius of the liner has a significant influence on the shape of the EFP. When the liner material is copper and the curvature radius of the liner is greater than 8 mm, the EFP shape approximates an ellipsoidal or hemispherical shape and the EFP forming speed is between 1900 m/s and 2400 m/s. When the material of the liner is steel or tungsten and the curvature radius of the liner is thicker than 8 mm, the liner is not able to form projectiles in the shape of a sphere, ellipsoid, or long rod. By comparing the forming speed from 1#EFP to 4#EFP, it can be said that MEFP with integrated liner and shell design displays a certain pressurization effect. Research results show that, for small‐caliber MEFP warheads, subject to the size of the warhead, when the liner is steel or tungsten, the detonation energy generated by the limited charge does not result in the liner forming an effective EFP. However, when the liner material is selected as copper, the EFP forming shape and speed are more appropriate.
Voice Recognition and Inverse Kinematics Control for a Redundant Manipulator Based on a Multilayer Artificial Intelligence Network
Authors: Anh Mai Ngoc , Bien Duong Xuan
Published: June 2021

This study presents the construction of a Vietnamese voice recognition module and inverse kinematics control of a redundant manipulator by using artificial intelligence algorithms. The first deep learning model is built to recognize and convert voice information into input signals of the inverse kinematics problem of a 6-degrees-of-freedom robotic manipulator. The inverse kinematics problem is solved based on the construction and training. The second deep learning model is built using the data determined from the mathematical model of the system’s geometrical structure, the limits of joint variables, and the workspace. The deep learning models are built in the PYTHON language. The efficient operation of the built deep learning networks demonstrates the reliability of the artificial intelligence algorithms and the applicability of the Vietnamese voice recognition module for various tasks.
The Effect of Acceptability and Personality on the Intention to Use Automated Vehicles among Chinese Samples
Authors: Qu Weina , Xu Jing , Ge Yan
Published: June 2021

The development of automated vehicles (AVs) has attracted increasing attention. Understanding public acceptance of AVs and their intention to use them, which are the primary aims of the present study, are especially important considering that increasingly more AVs will be moving on the road in the coming future. A total of 527 participants voluntarily and validly completed a series of questionnaires, including the automated vehicle acceptability scale (AVAS), Big Five Inventory (BFI), and some sociodemographic variables. The results of an internal consistency, reliability, and confirmatory factor analysis (CFA) confirmed the two-factor (contextual acceptability and impaired driving) structure of the AVAS. The Chinese public generally has a positive attitude towards AVs. In addition, our results indicate the possibility of the misuse of AVs. More importantly, the results reveal that contextual acceptability partially mediated the effect of agreeableness on the willingness to drive and the willingness to own AVs and fully mediated its effect on the willingness to rent AVs, while contextual acceptability and interest in impaired driving fully mediated the effect of the openness on the willingness to drive, own, and rent AVs. Manufacturers and retailers in the automotive vehicle industry should provide their customers with comprehensive information regarding the principles and limitations behind the system and the responsibility and obligations of the drivers to avoid misuse. Moreover, providing more targeted services according to customers’ different personality traits might be a useful sales technique.
Swarm Differential Privacy for Purpose-Driven Data-Information-Knowledge-Wisdom Architecture
Authors: Li Yingbo , Duan Yucong , Maamar Zakaria , Che Haoyang , Spulber Anamaria-Beatrice , Fuentes Stelios
Published: June 2021

Privacy protection has recently been in the spotlight of attention to both academia and industry. Society protects individual data privacy through complex legal frameworks. The increasing number of applications of data science and artificial intelligence has resulted in a higher demand for the ubiquitous application of the data. The privacy protection of the broad Data-Information-Knowledge-Wisdom (DIKW) landscape, the next generation of information organization, has taken a secondary role. In this paper, we will explore DIKW architecture through the applications of the popular swarm intelligence and differential privacy. As differential privacy proved to be an effective data privacy approach, we will look at it from a DIKW domain perspective. Swarm intelligence can effectively optimize and reduce the number of items in DIKW used in differential privacy, thus accelerating both the effectiveness and the efficiency of differential privacy for crossing multiple modals of conceptual DIKW. The proposed approach is demonstrated through the application of personalized data that is based on the open-source IRIS dataset. This experiment demonstrates the efficiency of swarm intelligence in reducing computing complexity.
A Recent Advance in the Closure of Skin Wounds on Fragile Skin
Authors: Ko John , Freed Jeffrey S.
Published: June 2021

The delicate nature of the skin in elderly patients poses a difficult challenge to healthcare providers. Emergency departments are frequently presented with traumatic skin tears and soft tissue avulsions in this group of patients. Procedures aimed at closure of these types of wounds often result in worsening of the tears. The DermaClip® skin closure device, which can eliminate the need for anesthesia, addresses these disadvantages and allows for atraumatic, cosmetically satisfactory closure in a rapid and efficient manner, saving time, and costs.
Schisandrin B Attenuates Airway Inflammation by Regulating the NF-κB/Nrf2 Signaling Pathway in Mouse Models of Asthma
Authors: Chen Yaqin , Kong Yu , Wang Qili , Chen Jian , Chen Hua , Xie Huihui , Li Lan
Published: June 2021

Background. Asthma is a complex inflammatory disorder that plagues a large number of people. Schisandrin B is an active ingredient of the traditional Chinese herbal medicine Schisandra with various proven physiological activities such as anti-inflammatory and antioxidant activities. In this study, we explored the anti-inflammatory and antioxidant effects and provided the mechanistic insights into the activity of schisandrin B in a mouse model of ovalbumin- (OVA-) induced allergic asthma. Methods. Male BALB/c mice were sensitized and challenged with OVA to induce asthma and treated with various doses (15 mg/kg, 30 mg/kg, and 60 mg/kg) of SCH to alleviate the features of allergic asthma, airway hyperresponsiveness, inflammatory response, OVA-specific immunoglobulin (Ig)E level, and pathological injury. Results. Schisandrin B significantly attenuated the airway hyperresponsiveness induced by OVA. Moreover, schisandrin B administration suppressed inflammatory responses, reduced the level of IgE, and attenuated pathological injury. Mechanistically, schisandrin B treatment promoted the activation of nuclear erythroid 2-related factor 2 (Nrf2), but suppressed the stimulation of the NF-κB pathway caused by OVA. Conclusion. Taken together, our study suggests that schisandrin B attenuates the features of asthmatic lungs by inhibiting the NF-κB pathway and activating the Nrf2 signaling pathway.
Focused Ultrasound (FUS) for Chronic Pain Management: Approved and Potential Applications
Authors: di Biase Lazzaro , Falato Emma , Caminiti Maria Letizia , Pecoraro Pasquale Maria , Narducci Flavia , Di Lazzaro Vincenzo
Published: June 2021

Chronic pain is one of the leading causes of disability and disease burden worldwide, accounting for a prevalence between 6.9% and 10% in the general population. Pharmacotherapy alone results ineffective in about 70-60% of patients in terms of a satisfactory degree of pain relief. Focused ultrasound is a promising tool for chronic pain management, being approved for thalamotomy in chronic neuropathic pain and for bone metastases-related pain treatment. FUS is a noninvasive technique for neuromodulation and for tissue ablation that can be applied to several tissues. Transcranial FUS (tFUS) can lead to opposite biological effects, depending on stimulation parameters: from reversible neural activity facilitation or suppression (low-intensity, low-frequency ultrasound, LILFUS) to irreversible tissue ablation (high-intensity focused ultrasounds, HIFU). HIFU is approved for thalamotomy in neuropathic pain at the central nervous system level and for the treatment of facet joint osteoarthritis at the peripheral level. Potential applications include HIFU at the spinal cord level for selected cases of refractory chronic neuropathic pain, knee osteoarthritis, sacroiliac joint disease, intervertebral disc nucleolysis, phantom limb, and ablation of peripheral nerves. FUS at nonablative dosage, LILFUS, has potential reversible and tissue-selective effects. FUS applications at nonablative doses currently are at a research stage. The main potential applications include targeted drug and gene delivery through the Blood-Brain Barrier, assessment of pain thresholds and study of pain, and reversible peripheral nerve conduction block. The aim of the present review is to describe the approved and potential applications of the focused ultrasound technology in the field of chronic pain management.
The Challenges Faced by Undergraduate Women during the COVID-19 Pandemic in Saudi Arabia
Authors: Al-Rasheed Amal
Published: June 2021

The latest COVID-19 pandemic is a specific and unusual event. It forced universities to close their doors and move fully to distance education. The sudden shift from traditional education to full distance education created many challenges and difficulties for universities, faculty members, and students. This study aims to investigate the challenges and obstacles faced by undergraduate women in Saudi Arabia universities while using online-only learning during the COVID-19 pandemic outbreak. Moreover, this study provides some recommendations to address these challenges from undergraduate women’s perspectives. The study used a qualitative research methodology to investigate the challenges and difficulties. The participants were undergraduate women selected using random purposive sampling technique from the population of College of Computer and Information Sciences (CCIS) at Princess Nourah Bint Abdulrahman University (PNU), Riyadh, Saudi Arabia. The final sample consisted of 68 undergraduate women who responded to a predesigned open-ended questionnaire that was sent via e-mail to targeted respondents. The data gathered from the questionnaire were analyzed using qualitative content analysis. Results of the research revealed that the most obvious challenges identified by the participants were technical issues, lack of in-person interaction, distractions and time management, lack of a systematic schedule, stress and psychological pressure, missing the traditional university environment, limited availability of digital devices, and lack of access to external learning resources.
Optimized Reconstruction Algorithm Based Analysis of Effects of Exercise Therapy Combined with Celecoxib Capsules on the Rehabilitation of Knee Osteoarthritis Using Computed Tomography Images
Authors: Shi Ying , Yang Yongsheng , Wang Fengjun
Published: June 2021

The aim was to explore the application value of computed tomography (CT) images based on optimized reconstruction algorithm (ORA) in knee osteoarthritis (KOA) and to analyze the rehabilitation effect of exercise therapy combined with celecoxib capsules on KOA. On the basis of iterative reconstruction algorithm, sparse data and compressed sensing (CS) algorithm were introduced in this study for the image reconstruction and were compared with the reconstruction effects of other algorithms. 105 patients with KOA were selected as the subjects investigated, who were treated in the hospital from December 2018 to January 2020. They were divided randomly into group A (exercise therapy), group B (celecoxib capsule therapy), and group C (exercise therapy combined with celecoxib capsules), with 35 patients in each group. All the patients were scanned by CT. Visual analogue score (VAS) method was adopted to compare the pain symptoms of patients in the three groups before and after treatment. The Lysholm knee function score was employed to evaluate the knee function of the patient before and after treatment, and finally the difference in the total effective rate of treatment was compared. The results showed that the reconstruction algorithm in this study had a higher degree of coincidence with the original image, and its root mean square error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) were greatly higher than those of filtered back-projection (FBP) algorithm. There was no huge difference between Lysholm score and VAS in patients of the three groups before treatment (

P
>
0.05

). Besides, Lysholm score in all dimensions and its total score after treatment were higher than those of patients in the three groups before treatment (

P
<
0.05

), and those of patients in group C increased extremely in contrast to group A (

P
<
0.05

). VAS after treatment were all lower in patients of the three groups than those before treatment (

P
<
0.05

), and VAS of patients in group C were sharply lower than those of group A (

P
<
0.05

), but the total effective rate of patients in group C was dramatically higher than the rate of group A (

P
<
0.05

). It indicated that an algorithm with short scanning time and good image quality was established based on iterative reconstruction algorithm. Exercise therapy combined with celecoxib capsules could alleviate the pain symptoms and improve the function of knee joint, which was more advantageous than the simple rehabilitation comprehensive therapy. Therefore, it had higher clinical value for the patients with KOA.
Multivariate Time Series Data Clustering Method Based on Dynamic Time Warping and Affinity Propagation
Authors: Wan Xiaoji , Li Hailin , Zhang Liping , Wu Yenchun Jim
Published: June 2021

In view of the importance of various components and asynchronous shapes of multivariate time series, a clustering method based on dynamic time warping and affinity propagation is proposed. From the two perspectives of the global and local properties information of multivariate time series, the relationship between the data objects is described. It uses dynamic time warping to measure the similarity between original time series data and obtain the similarity between the corresponding components. Moreover, it also uses the affinity propagation to cluster based on the similarity matrices and, respectively, establishes the correlation matrices for various components and the whole information of multivariate time series. In addition, we further put forward the synthetical correlation matrix to better reflect the relationship between multivariate time series data. Again the affinity propagation algorithm is applied to clustering the synthetical correlation matrix, which realizes the clustering analysis of the original multivariate time series data. Numerical experimental results demonstrate that the efficiency of the proposed method is superior to the traditional ones.
Dynamic Allocation Model for Reversible Lanes in the Intelligent Vehicle Infrastructure Cooperative System
Authors: Zhou Guiliang , Mao Lina , Cao Huimin , Hu Pengsen , Bao Xu
Published: June 2021

The real-time dynamic control of reversible lanes is an effective measure to alleviate the traffic congestion caused by the directional imbalance of the traffic flow and improve the utilization rate of urban road resources. This paper proposes a dynamic allocation model for reversible lanes for road sections and intersections in the intelligent vehicle infrastructure cooperative system (IVICS). The dynamic lane allocation model for the road sections is constructed based on the Bureau of Public Road (BPR) function, in which the 24 hours of the day are divided into stages, the traffic volume and road impedance of each stage are obtained, and their product is integrated over time. Finally, the plan with the least delay in each stage is selected as the optimal solution. The dynamic lane control model for intersections is built according to the Highway Capacity Manual 2000 (HCM2000) delay model. With the minimum average delay of vehicles at the intersection as the objective function, the average delay of different lane combinations under different traffic conditions is analyzed to find the optimal combination of reversible lanes and ordinary lanes. The model is verified by case analysis and MATLAB calculations. The results show that the reversible lane dynamic control model can effectively allocate road resources and reduce driving delays.
Association between Human Polyomaviruses and Keratinocyte Carcinomas: A Prospective Cohort Study
Authors: Amorrortu Rossybelle P. , Zhao Yayi , Messina Jane L. , Schell Michael J. , Fenske Neil A. , Cherpelis Basil S. , Sondak Vernon K. , Giuliano Anna R. , Pawlita Michael , McKay-Chopin Sandrine , Gheit Tarik , Waterboer Tim , Tommasino Massimo , Rollison Dana E.
Published: June 2021

Background:

A positive association between Merkel cell polyomavirus (MCPyV) infection and cutaneous squamous cell carcinoma (cuSCC) has been observed in at least one previous case–control study. To evaluate this association in a prospective context, we investigated infections with human polyomaviruses (HPyV), including MCPyV, as predictors of keratinocyte carcinomas, including cuSCC and basal cell carcinoma (BCC), among a cohort of immunocompetent individuals enrolled in the Viruses in Skin Cancer (VIRUSCAN) Study.

Methods:

Associations between markers of baseline HPyV infection (serum antibodies and viral DNA in eyebrow hairs and skin swabs) and incident keratinocyte carcinomas were modeled using Cox proportional hazards regression. Proportions of baseline HPyV infections that were concordant with a subsequent tumor positive for the same HPyV type were assessed.

Results:

No significant associations were observed between baseline markers of MCPyV or other HPyV infections and cuSCC or BCC. Less than 4.5% of baseline MCPyV infections were also detected in subsequently developed keratinocyte carcinoma tumors.

Conclusions:

HPyV infection was not a predictor of keratinocyte carcinoma risk in this prospective cohort.

Impact:

Cancer-associated infections represent attractive targets for cancer prevention; however, HPyV infections have limited potential as novel targets for cuSCC prevention.
Low-Fat Dietary Modification and Risk of Ductal Carcinoma In Situ of the Breast in the Women's Health Initiative Dietary Modification Trial
Authors: Peila Rita , Chlebowski Rowan , Manson JoAnn E. , Crane Tracy E. , Lane Dorothy S. , Saquib Nazmus , Shadyab Aladdin H. , Tabung Fred K. , Barac Ana , Zhang Zhenzhen , Pan Kathy , Wassertheil-Smoller Sylvia , Rohan Thomas E.
Published: June 2021

Background:

Results of observational studies of the association between dietary fat and risk of invasive breast cancer have been inconsistent. In the Women's Health Initiative dietary modification (DM) randomized trial designed to lower fat intake, the intervention was not associated with a statistically significant reduction of overall breast cancer risk. However, the DM association with risk of ductal carcinoma in situ (DCIS) of the breast, a putative breast cancer precursor, has not been reported.

Methods:

A total of 48,835 postmenopausal women, ages 50–79 years at enrollment, with no breast cancer history and ≥32% of total energy intake from fat, were randomly assigned either to a dietary intervention (n = 19,541) designed to reduce total fat intake to 20% of energy and to increase vegetable, fruit, and grain consumption, or to a comparison group (n = 29,294). Cox proportional hazards models were used to estimate HRs and 95% confidence intervals for the association between the intervention and DCIS risk.

Results:

During 18.7 years (median) cumulative follow-up, including intervention (∼8.7 years) and post-intervention phases (∼13.0 years), 817 DCIS cases were ascertained. No evidence of an association between the DM intervention and DCIS risk was observed overall, or by trial phase (intervention and post-intervention). Similarly, no associations were found in subgroups defined by potential risk factors for DCIS.

Conclusions:

DM aiming to reduce fat intake was not associated with altered risk of DCIS.

Impact:

These results do not provide evidence of an association between dietary fat reduction and the risk of DCIS among postmenopausal women.
Memory-like Differentiation Enhances NK Cell Responses to Melanoma
Authors: Marin Nancy D. , Krasnick Bradley A. , Becker-Hapak Michelle , Conant Leah , Goedegebuure Simon P. , Berrien-Elliott Melissa M. , Robbins Keenan J. , Foltz Jennifer A. , Foster Mark , Wong Pamela , Cubitt Celia C. , Tran Jennifer , Wetzel Christopher B. , Jacobs Miriam , Zhou Alice Y. , Russler-Germain David , Marsala Lynne , Schappe Timothy , Fields Ryan C. , Fehniger Todd A.
Published: June 2021

Purpose:

Treatment of advanced melanoma is a clinical challenge. Natural killer (NK) cells are a promising cellular therapy for T cell–refractory cancers, but are frequently deficient or dysfunctional in patients with melanoma. Thus, new strategies are needed to enhance NK-cell antitumor responses. Cytokine-induced memory-like (ML) differentiation overcomes many barriers in the NK-cell therapeutics field, resulting in potent cytotoxicity and enhanced cytokine production against blood cancer targets. However, the preclinical activity of ML NK against solid tumors remains largely undefined.

Experimental Design:

Phenotypic and functional alterations of blood and advanced melanoma infiltrating NK cells were evaluated using mass cytometry. ML NK cells from healthy donors (HD) and patients with advanced melanoma were evaluated for their ability to produce IFNγ and kill melanoma targets in vitro and in vivo using a xenograft model.

Results:

NK cells in advanced melanoma exhibited a decreased cytotoxic potential compared with blood NK cells. ML NK cells differentiated from HD and patients with advanced melanoma displayed enhanced IFNγ production and cytotoxicity against melanoma targets. This included ML differentiation enhancing melanoma patients' NK-cell responses against autologous targets. The ML NK-cell response against melanoma was partially dependent on the NKG2D- and NKp46-activating receptors. Furthermore, in xenograft NSG mouse models, human ML NK cells demonstrated superior control of melanoma, compared with conventional NK cells.

Conclusions:

Blood NK cells from allogeneic HD or patients with advanced melanoma can be differentiated into ML NK cells for use as a novel immunotherapeutic treatment for advanced melanoma, which warrants testing in early-phase clinical trials.
Anagen Effluvium after Therapeutic Scalp Surgery: Unreported Phenomenon
Authors: Contin Leticia Arsie , Santos Leopoldo Duailibe Nogueira , Pereira Ivan José Netto , Rocha Vanessa Barreto
Published: June 2021

Introduction: Many procedures are performed on the scalp, such as excision of pilar and sebaceous cysts, melanocytic nevi, and reduction surgery for scarring alopecia, among others. In hair transplants, telogen effluvium is often reported 3 months after surgery; however, hair loss usually happens much earlier, around second week after the procedure, not compatible with the time required for hair to enter telogen and exogenous phases in normal conditions. Case Reports: We report 3 cases of anagen hair loss 4 weeks after surgeries, with perilesional trichoscopy suggesting anagen effluvium, with typical signs such as black dots and exclamation hairs. Discussion: There are only a few reports about hair loss around operated areas. The cause of this postoperative anagen effluvium is probably a transient ischemia. Conclusion: The practical importance of this phenomenon is to properly orient patients because most of the hair will be lost, since 85% of them are anagens, and also will have spontaneous recovery in the next 3 months.
Proliferative Vascular Smooth Muscle Cells Stimulate Extracellular Matrix Production via Osteopontin/p38 MAPK Signaling Pathway
Authors: Pei Huawei , Zhang Haiyue , Tian Chuan , Sun Xiaogang , Qian Xiangyang , Meng Yanhai , Guo Xiaobo , Chang Qian
Published: June 2021

Introduction: Extracellular matrix disorder and cellular phenotype transformation are the major histopathological features associated with ascending aortic aneurysms. Rare studies have investigated the relationship between cellular phenotype transformation and the abnormalities of the matrix constituents. In this study, we investigated whether the cellular phenotype transformation resulted in the extracellular matrix disorder. Methods: Aortic samples were obtained from 20 patients undergoing operations for ascending aortic aneurysms. Control aortic samples were obtained from 15 patients who underwent coronary artery bypass graft. The protein levels of osteopontin (OPN), collagen, and elastin were examined using Western blot, and quantitative reverse transcriptase-PCR was used to analyze the mRNA expression of collagen and elastin. In vitro experiment, vascular smooth muscle cells (VSMCs) were treated with recombinant human OPN (rh-OPN) or p38 MAPK inhibitor (SB203580) to investigate whether OPN and p38 MAPK regulated the expression of collagen and elastin. Results: The protein level of OPN and collagen III increased in ascending aortic aneurysm samples, compared with controls (p < 0.05). There was no difference in the protein level of elastin between aneurysm tissues and the controls. VSMCs treated with rh-OPN increased the collagen III and elastin protein level and mRNA expression (p < 0.05). Cells treated with SB203580 decreased the collagen III and elastin protein level and mRNA expression (p < 0.05). Furthermore, VSMCs incubated with SB203580 reduced the rh-OPN-induced production of collagen III and elastin (p < 0.05). Conclusion: OPN, the proliferative VSMCs maker, increased the expression of extracellular matrix. OPN/p38 MAPK signaling pathways may protect against ascending aortic aneurysm progression.
Monodactylous Longitudinal Melanonychia: A Sign of Bowen’s Disease in Skin of Color
Authors: Williams Natalie M. , Obayomi Aderonke O. , Diaz-Perez Julio A. , Morrison Brian W.
Published: June 2021

Introduction: Monodactylous longitudinal melanonychia (LM) may represent both benign and malignant dermatologic disorders. However, squamous cell carcinoma in situ (SCCis) is not commonly considered in this setting. Case Presentation: In this report, we present 2 cases of SCCis of the nail matrix in patients with skin of color who presented with monodactylous LM involving the lateral aspect of the nail. Conclusion: These cases suggest that SCCis should be included in the differential diagnosis for monodactylous LM, especially when involving the lateral nail plate in darker skin.
Cancer Antigen 15-3 Serum Level as a Biomarker for Advanced Micropapillary Urothelial Carcinoma of the Bladder: A Case Report
Authors: Takayama Koichiro , Narita Shintaro , Terai Yasushiro , Saito Ryoko , Habuchi Tomonori
Published: June 2021

A 73-year-old woman with no history of disease was referred to our hospital with fatigue and joint pain. Screening blood test showed that her cancer antigen 15-3 (CA 15-3) serum level was elevated to 36.6 U/mL, and a contrast-enhanced computed tomography scan revealed a bladder tumor without metastasis. Cystoscopy showed a papillary and a small kissing tumor, and the histopathological analysis of the bladder tumor obtained by transurethral resection (TUR) showed invasive urothelial carcinoma (UC) with micropapillary variant (pT1). At 4 weeks after TUR, the CA 15-3 serum level was markedly increased to 180.6 U/mL, and radiographic examinations revealed multiple regional and nonregional lymph node metastases. The patient received systemic therapy with gemcitabine and cisplatin. After 3 cycles of chemotherapy, the size of all lymph node metastases reduced by 80% in diameter, and the CA 15-3 serum level decreased from 238.2 to 11.4 U/mL. Immunohistological analysis showed that the bladder tumor was positive for mucin 1, of which CA 15-3 is an epitope. In our patient, changes in the CA 15-3 serum levels were in congruence with the clinical course of advanced micropapillary UC (MPUC). Therefore, the CA 15-3 serum level may be a potentially valuable biomarker for MPUC.