bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial distribution pattern of dominant tree species in different disturbance plots in the Changbai Mountain
Authors: Zhang Mengtao , Zhang Yuyuan , Kang Xingang 
Published: January 2022

Abstract
The effects of disturbance on spatial patterns and species interactions provide critical information on community structure and species coexistence. Two standard plots of 1-ha were set, one of them was a sample plot with retrograde succession after disturbance, and the other one was undisturbed. Spatial indices and Spatial patterns statistics were used to analyze the spatial pattern and inter-specific correlation of main tree species in two plots. Our results showed that the diameter distributions of different species have reverse J-shape, unimodal and bimodal distribution in the disturbed plot, while bell-shaped curves were observed in the undisturbed plot. The distributions of tree species were mainly random through the uniform angle indices, but the results of univariate pair correlation function g(r) for most standing trees showed clustered patterns in almost all scales. Some similar results of the classification of Wiegand scheme of species association consistent with the consequences of the bivariate pair correlation. The mark variograms showed positive autocorrelation at a coarse scale. The current study may aid in efforts of forest management planning and ecosystem services. Meanwhile, different research methods of spatial distribution also help to improve the accuracy of spatial distribution and the interspecific association of tree species.
Deep Learning-Based Fully Automatic Segmentation of the Maxillary Sinus on Cone-Beam Computed Tomographic Images
Authors: Choi Han Seung , Jeon Kug Jin , Kim Young Hyun , Ha Eun-Gyu , Lee Chena , Han Sang-Sun 
Published: January 2022

Abstract
This study proposes a deep learning-based method for fully automatic segmentation of the maxillary sinus, including clear or hazy states, on cone-beam computed tomographic (CBCT) images. The model, which consisted of a U-Net architecture with post-processing, was developed using 19,350 CBCT images from 90 maxillary sinuses (34 clear sinuses, 56 hazy sinuses). Post-processing was performed to improve the accuracy of the prediction results of U-Net. Model performance was evaluated compared to manual labeling by an oral radiologist. The artificial intelligence (AI) prediction results before post-processing were DSC of 0.9071 ± 0.1842, HD of 2.6207 ± 4.9279 in clear sinuses and DSC of 0.9107 ± 0.1988, HD of 2.7812 ± 4.2835 in hazy sinuses. After post-processing, the results all improved (DSC: 0.9072 ± 0.1842, HD: 2.4057 ± 2.4496 in clear sinuses and DSC: 0.9123 ± 0.1977, HD: 1.9158 ± 2.0887 in hazy sinuses). The proposed deep learning model showed good performance for clear and hazy maxillary sinus segmentation with minimal time and effort, and the post-processing method improved the accuracy of automatic segmentation.
Centralized Fusion Robust Steady-state Estimator for Networked Uncertain System With Coloured Noises, One-step Random Delay and Packet Dropouts
Authors: Liu Wenqiang , Li Shuang , Tao Guili 
Published: January 2022

Abstract
This study is aimed to address the centralized fusion (CF) robust estimation problems for a class of multisensor networked systems with mixed uncertainties, which include coloured noises, same multiplicative noises in system parameter matrices, additive white noise, uncertain noise variances, as well as the one-step random delay and packet dropouts (PD). To deal with this kind of systems, one-step random delay and inconsecutive packet dropouts are described by two Bernoulli distributed random variables. By using the augmentation, de-randomization and fictitious noise techniques, the original system has transformed into an augment model with only uncertain noise variances. In the light of the minimax robust estimation principle, based on the worst-case CF system with conservative upper bounds of uncertain noise variances, the robust CF steady-state Kalman estimators (predictor, filter, and smoother) are presented. By providing a novel approach, consist of non-negative definite matrix method and Lyapunov equation approach, prove the robustness of the CF estimator. Finally, a UPS simulation example illustrates the effectiveness of the proposed CF estimation algorithms.
Fruit Recognition Method for a Harvesting Robot with RGB-D Cameras
Authors: Yoshida Takeshi , Kawahara Takuya , Fukao Takanori 
Published: January 2022

Abstract
In this study, we present a recognition method for a fruit-harvesting robot to automate the harvesting of pears and apples on joint V-shaped trellis. It is necessary to recognize the three-dimensional position of the harvesting target for harvesting by the fruit-harvesting robot to insert its end-effector. However, the RGB-D (red, green, blue and depth) camera on the harvesting robot has a problem in that the point cloud obtained in outdoor environments can be inaccurate. Therefore, in this study, we propose an effective method for the harvesting robot to recognize fruits using not only three-dimensional information obtained from the RGB-D camera but also two-dimensional images and information from the camera. Furthermore, we report a method for determining the ripeness of pears using the information on fruit detection. Through experiments, we confirmed that the proposed method satisfies the accuracy required for a harvesting robot to continuously harvest fruits.
A Multifunctional Composite Hydrogel as an Intrinsic and Extrinsic Coregulator for Enhanced Therapeutic Efficacy for Psoriasis
Authors: Xu Jiangmei , Chen Hao , Chu Zhaoyou , Li Zhu , Chen Benjin , Sun Jianan , Lai Wei , Ma Yan , He Yulong , Qian Haisheng , Wang Fei , Xu Yunshen 
Published: January 2022

Abstract
Background
Psoriasis is a chronic relapsing immunological skin disease characterized by multiple cross-talk inflammatory circuits which are relevantly associated with abnormal cross-reactivity between immune cells and keratinocytes (KCs). It may be inadequate to eradicate complicated pathogenesis only via single-mode therapy. To provide optimal combinatory therapeutics, a nanocomposite-based hydrogel was constructed by loading methotrexate (MTX) into ZnO/Ag to realize synergistic multiple target therapy of psoriasis.
Results
In this composite hydrogel, ZnO hybrid mesoporous microspheres were utilized both as drug carriers and ROS-scavenging nanoparticles. A proper amount of Ag nanoparticle-anchored ZnO nanoparticles (ZnO/Ag) was functionalized with inherent immunoregulatory property. The experiments showed that ZnO/Ag nanoparticles could exhibit a self-therapeutic effect that was attributed to reducing innate cytokine profiles by inactivating p65 in proinflammatory macrophages and abrogating secretion of adaptive cytokines in KCs by downregulating ROS-mediated STAT3-cyclin D1 signaling. A preferable antipsoriatic efficacy was achieved via topical administration of this hydrogel on the IMQ-induced psoriasis mice model, demonstrating the superior transdermal delivery and synergistic enhancement of therapeutic efficacy caused by intrinsic nanoparticles and extrinsic MTX.
Conclusion
this composite hydrogel could serve as a multifunctional, nonirritating, noninvasive and effective transcutaneous nanoagent against psoriasis.
Predicting Calmness, Anxiety, and Depression using Wearable Sensors
Authors: Borthakur Rajlakshmi , Sharma Natwar , Pattanaik Priya 
Published: January 2022

Abstract
One of the main reasons for the high prevalence of mental disorders is that there is no technology to aid diagnosis or to report on recovery factors like effect of therapeutic interventions and medicines. To enable faster access to screening and to measure recovery, we propose a wearables-based framework for the automatic prediction of the states of anxiety, depression and calmness in individuals. The framework called H2SEC is based on the integrated measurements of Habituation, Hypoactivity, Synchronization, Experience and Calmness (H2SEC) through a unified framework. The framework also enables the tracking of these states in realtime, showing transition from one state of consciousness to another.

To build and validate the H2SEC framework, we collected Electrodermal Activity (EDA) and Blood Volume Pulse (BVP) data, sampled at 100 Hz using a wearable device from 61 Neutral, 60 Depressed and 110 subjects with Anxiety, while they performed the experimental task. By tracking the timeseries data in centiseconds, we identified segments of time in the subjects’ data where their per-minute state of Sympathetic Nervous System (SNS) was lower compared to the previous minutes. Within these segments called Sympathetic Transition Points (STPs), we calculated scores related to the H2SEC parameters of Habituation, Hypoactivity, Synchronization, Experience and Calmness and compared them against similar scores from non-STP segments. We thus arrived at the physiological coordinates of the Neutral, Anxiety, and Depression groups, apart from identifying the intrinsic nature of calmness in each group.

We implemented multi-output, multi-label machine learning (ML) algorithms to predict mental states(Neutral, Anxiety, and Depression) along with the nature of calmness (Calm, Approaching Calmness, and Not Calm) in each subject. We report 100% F1, along with 100% Precision and Recall in identifying both the states. Our methodology is the state-of-the-art in terms of mental health monitoring, and to the best of our knowledge we are the first to report on mental health disorders (anxiety and depression) and recovery mechanism (calmness) using an integrated methodology.
A Liquid-pressure-adaptive Superhydrophobic Surface
Authors: Deng Xu , Tan Yao , Yang Jinlong , Li Yong , Li Xiaomei , Wu Qiao , Yu Fanfei , Cui Jiaxi , Chen Longquan , Wang Dehui , Fan Yue 
Published: January 2022

Abstract
The dynamic application environments of superhydrophobic surfaces, such as in the manufacturing, chemical, and garment industries, require the fast adaptiveness of the surfaces to their surroundings. Despite the progress in materials and structural design of superhydrophobic surfaces, simultaneously achieving high superhydrophobic stability and low adhesion by traditional design is still challenging. Here, we demonstrate a liquid-pressure-adaptive superhydrophobic surface with self-adjustable solid-liquid stability and adhesion when reacting to the dynamic environmental requirements. To understand the underlying adaptive processes, we imaged the liquid impalement dynamics in three dimensions by confocal microscope and measured the stability and superhydrophobicity in varied systems. We envision our design strategy of liquid-pressure-adaptive superhydrophobic surfaces with dynamic anti-infiltration capability could guide the development of stable superhydrophobicity under complex wetting conditions.
Combined Hormone Receptor and Human Epidermal Growth Factor Receptor-2 Expression Reflects Inter-and Intra-tumor Heterogeneity in Hormone Receptor-positive/human Epidermal Growth Factor Receptor-2-positive Breast Cancer
Authors: Yuan Peng , Ju Jie , Du Feng , Gao Song-Lin , Si Yi-Ran , Hu Nan-Lin , Liu Dong-Xu , Wang Xue , Yue Jian , Zheng Fang-Chao , Kang Yi-Kun , Yang Zi-Xuan , Ma Fei , Xu Bing-He 
Published: January 2022

Abstract
BackgroundHormone receptor-positive and human epidermal growth factor receptor-2-positive (HR+/HER2+) breast cancer comprise approximately 5-10% of all invasive breast cancers. However, the lack of knowledge regarding the complexity of tumor heterogeneity in HR+/HER2+ disease remains a barrier to more accurate therapies. This study aimed to describe the tumor heterogeneity of HR+/HER2+ breast cancer and to establish a novel indicator to identify the HER2-enriched-like subtype in patients with HR+/HER2+ breast cancer.MethodsFirst, a comprehensive analysis was performed on HR+/HER2+ breast cancer samples from the TCGA (n=141) and METABRIC (n=104) databases. We determined the distribution of PAM50 intrinsic subtypes within the two cohorts and compared the somatic mutational profile and RNA expression features between HER2-enriched and non-HER2-enriched subtypes. We then performed multiplex immunofluorescence to evaluate HER2 and estrogen receptor (ER) expression simultaneously in the third cohort, enrolling 43 cases of early HR+/HER2+ breast cancer from Cancer Hospital, Chinese Academy of Medical Sciences (CAMS). ResultsAll four main intrinsic subtypes were identified in HR+/HER2+ breast cancer, of which the luminal-B subtype was the most common, followed by the HER2-enriched and luminal-A subtypes. Significantly increased TP53 and ERBB3 and decreased PIK3CA somatic mutation frequency were observed in the HER2-enriched subtype compared with the non-HER2-enriched subtype. In addition, the HER2-enriched subtype was characterized by significantly higher ERBB2 and lower ESR1 expression. We then constructed a marker termed rH/E to reflect the relative expression of ERBB2 to ESR1 in each patient. rH/E discriminates the HER2-enriched subtype from the non-HER2 subtypes better than the expression of ERBB2 or ESR1 alone. In the CAMS cohort, we observed four subtypes of tumor cells: ER+/HER2-, ER+/HER2+, ER-/HER2+, and ER-/HER2-. Tumor cell diversity was common, with 86% of patients having all four subtypes of tumor cells. Moreover, rH/E showed a significant prognostic association in the CAMS cohort. ConclusionsThis study furthers our understanding of the complexity of tumor heterogeneity in HR+/HER2+breast cancer, and suggests that the combined analysis of ERBB2 and ESR1 expression may contribute to identifying patients with specific subtypes in this population.
Nanotechnology Strategy as Antibacterial: a Primer for the Notice.
Authors: Ibisanmi Tope Abraham 
Published: January 2022

Abstract
Background: Multidrug-resistant (MDR) bacteria cause a serious threat to any or all fields of bioscience because it may result in treatment failure which might have severe consequences, especially in case of critical patients. The development of a new antibacterial agents cropped up to be a complex process. One of the most important aspect of modern field research is nanotechnology, it deals with synthesis, design and manipulation of particles structures ranging from approximately 1-100nm.Main body: Nanoparticles (NPs) have big selection of applications in areas like health care, cosmetics, food and feed, environmental health e.t.c. Nanoparticles matrix properties and constituent materials can be used to categorized them into inorganic and organic nanosystems. Techniques use within the synthesis of NPs includes; chemical, physical, chemistry, and biological ways. every methodology has its advantages and disadvantages with common issues of value, quantifiability and uniform particle size. celebrated life scientist Sir Alexander Fleming aforesaid that “There is perhaps no therapy drug to that in appropriate circumstances the bacteria can't react by in a way deed fastness.” thus, there's high chance that the organism can also become resistance to freshly developed medication at later stage, additional these medications are highly expensive.Conclusions: To this end NPs are considered to be good antibacterial agents and may overcome the barrier of MDR owing to their multifunctional mechanisms to intervene normal cell functionality, ability to anchor to the bacterial cell wall and subsequently penetrate it, thereby causing structural changes in the cell membrane permeability leading to cell death.
How is People's Awareness of “Biodiversity” Measured ?Using Sentiment Analysis and LDA Topic Modeling in the Twitter Discourse Space from 2010 to 2020
Authors: Ohtani Shimon 
Published: January 2022

Abstract
The importance of biodiversity conservation is gradually being recognized worldwide, and 2020 was the final year of the Aichi Biodiversity Targets formulated at the 10th Conference of the Parties to the Convention on Biological Diversity (COP10) in 2010. Unfortunately, the majority of the targets were assessed as unachievable. While it is essential to measure public awareness of biodiversity when setting the post-2020 targets, it is also a difficult task to propose a method to do so. This study provides a diachronic exploration of the discourse on “biodiversity” from 2010 to 2020, using Twitter posts, in combination with sentiment analysis and topic modeling, which are commonly used in data science. Through the aggregation and comparison of n-grams, the visualization of eight types of emotional tendencies using the NRC emotion lexicon, the construction of topic models using Latent Dirichlet allocation (LDA), and the qualitative analysis of tweet texts based on these models, I was able to classify and analyze unstructured tweets in a meaningful way. The results revealed the evolution of words used with “biodiversity” on Twitter over the past decade, the emotional tendencies behind the contexts in which “biodiversity” has been used, and the approximate content of tweet texts that have constituted topics with distinctive characteristics. While the search for people's awareness through SNS analysis still has many limitations, it is undeniable that important suggestions can be obtained. In order to further refine the research method, it will be essential to improve the skills of analysts and accumulate research examples as well as to advance data science.
Describing long-term opioid use utilizing Nordic Prescription Registers – A Norwegian example
Authors: Hamina Aleksi , Hjellvik Vidar , Handal Marte , Odsbu Ingvild , Clausen Thomas , Skurtveit Svetlana 
Published: January 2022

Abstract
Previous studies have defined long-term opioid use in varying ways, decreasing comparability, reproducibility, and clinical applicability of the research. Based on recommendations from recent systematic reviews, we aimed to develop methodology to estimate the prevalence of use persisting more than three months utilizing one of the Nordic prescription registers. We used the Norwegian Prescription Register (NorPD) to extract data on all opioid dispensations between January 1st, 2004, and October 31st, 2019. New users of opioids (washout 365 days) were defined as long-term users if they filled two criteria: 1) they had ≥2 dispensations of opioids, 91-180 days apart; 2) days 0-90 included ≥90 dispensed administration units (e.g., tablets) of opioids. Overall, there were 2,543,224 new users of opioids during the study period. Of these, 354,666 (13.9%) filled the criteria for long-term opioid use at least once. Compared to those who did not fill the criteria (short-term users), long-term users were older, more likely women, and used tramadol, oxycodone, and buprenorphine more frequently as their first opioid. In conclusion, we found that 1/7 of opioid users continued use longer than 3 months. Future outcome research should identify the clinically most important dose requirements for long-term opioid use criteria.
The multiple uses of water derived from managed aquifer recharge systems in Kenya and India
Authors: Parker A. H. , Nyangoka J. , Rodrigues I. , Yadav B. , Le Corre K. S. , Campo P. , Quinn R. 
Published: January 2022

Abstract‘Multiple-use services’ (MUS) takes into account the fact that households use water for both domestic and for productive uses. This paper is the first to determine how managed aquifer recharge (MAR) systems are a form of MUS. Two cases were studied in India and in Kenya. In the Kenyan case, sand dams are the form of MAR, and in India check dams and infiltration ponds of various scales are used. Through observations, interviews, and water quality data, it is possible to describe how the communities access the water from these infrastructures in multiple ways for different uses, according to their water needs and the characteristics of the different access points. MAR involves harvesting rainwater and retaining run-off water into the dry season thus increasing the amount of available water and enabling diversification of water uses. It should therefore be considered as an option by water managers aiming to develop water resources meeting both the domestic and productive needs of communities.
Therapeutic Application of Microsponges-based Drug Delivery Systems
Authors: Rahman Mahfoozur , Almalki Waleed H. , Panda Sunil K. , Das Aman K. , Alghamdi Saad , Soni Kriti , Hafeez Abdul , Handa Mayank , Beg Sarwar , Rahman Ziyaur 
Published: January 2022

Abstract:
Microsponges delivery systems (MDS) are highly porous, cross-linked polymeric systems that activate
due to temperature, pH, or when rubbed. MDS offer a wide range of advantages, like controlled drug release,
site-specific action, stability over a broad range of pH, less irritation, cost-effectiveness, and improved
patient compliance. They can be transformed into various dosage forms like creams, gels, and lotions. MDS are
suitable for the treatment of topical disorders like acne, psoriasis, dandruff, eczema, scleroderma, hair loss, skin
cancer, and other dreadful diseases. The applications of MDS in drug delivery are not limited to topical drug
delivery but are also explored for oral, parenteral, and pulmonary drug deliveries. Microsponges have been
studied for colon targeting of drugs and genes. Additionally, MDS have several applications such as sunscreen,
cosmetics, and over-the-counter (OTC) products. Furthermore, MDS do not actuate any irritation, genotoxicity,
immunogenicity, or cytotoxicity. Therefore, this review extensively highlights microsponges, their advantages,
key factors affecting their characteristics, their therapeutic applications in topical disorders and in cancer, their
use as cosmetics, as well as recent advances in MDS and the associated challenges.
Adipose Tissue-Mesenchymal Stem Cells Caused to Change the
Methylation Status of hTERT Gene Promoter CpG Islands of Molt-4
Leukemia Cells as Cell-based Therapy
Authors: Fathi Ezzatollah , Montazersaheb Soheila , Vandghanooni Somayeh , Farahzadi Raheleh , Vietor Ilja 
Published: January 2022

Background:
DNA methylation was considered as prognostic information in
some hematological malignancies. Previous studies have reported the in vitro and in
vivo biology role of mesenchymal stem cells (MSCs) on leukemic cells. The aim of this
study was to investigate the effect of MSCs on the promoter methylation status of
hTERT as a catalytic subunit of telomerase enzyme.

Methods:
In the experimental study, the Molt-4 leukemic cells were co-cultured with
MSCs for 7 days. At the end of the co-culture period, the Molt-4 cells were collected,
DNA and protein were extracted. Then methylation specific-PCR and western blotting
were done for evaluating the hTERT gene promoter methylation status and cyclin D1
and hTERT protein expression, respectively. In the following, the flow cytometry was
done for cell cycle distribution assay.

Results:
It was found that MSCs resulted in a significant decrease in the cyclin D1 and
hTERT protein expression levels. Also, MSCs caused changes in the methylation status
of the CpG islands in the hTERT gene promoter region. The following results showed
that MSCs caused a significant increase in the number of cells at G0/G1 phase and
arrest the G0/G1 phase as well as decrease in the cell proliferation of Molt-4 cells.

Conclusion:
It is concluded that co-culture of MSCs with Molt-4 cells could be involved
in changing the methylation status of hTERT gene promoter, cell cycle and hTERT
protein expression; it could be potentially beneficial for further investigations regarding
the cell transplantation and cell-based therapy.