bluuebunny/crossref_metadata_2025_split huggingface dataset:
Acupuncture for insomnia in patients with breast cancer: a single-center, single-blind, randomised, controlled trial protocol
Authors: Ma Tingting , Yin Xiaohui , Yi Runxi , Lu Wei , Zhao Bingcong , Yu Mingwei , Zhang Ganlin , Zhang Qing , Xu Yongmei , Zhang Yi , Pan Yuancan , Yuan Zichun , Li Haiming , Wang Xiaomin 
Published: October 2023

Abstract
Background
Patients with breast cancer have a high incidence of insomnia, which is often accompanied by anxiety, depression, and fatigue. Acupuncture is considered useful for insomnia and emotional disorders and is becoming increasingly acceptable for patients with cancer. However, few studies have been conducted on acupuncture for patients with breast cancer who are suffering from insomnia. This study aims to describe a protocol for an 8-week acupuncture intervention to explore the efficacy and safety of acupuncture therapy using the “regulating spirit and soothing liver” method for treating insomnia patients with breast cancer.
Methods
This study is a single-center, single-blind, randomised, controlled trial. We aim to recruit 70 females, aged 18-60 years, who will be randomly allocated to the intervention (acupuncture) or control (sham acupuncture) groups. The intervention will include an 8-week acupuncture therapy followed by a 3-month follow-up period. The primary outcome is the Pittsburgh Sleep Scale(PSQI) measured every two weeks. Secondary outcomes are the Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ9), and Functional Assessment of Cancer Therapy-Breast Cancer (FACT-B) to assess emotional health and quality of life. We will also record the drug name and quantity given to treat severe insomnia. We also will measure serum 5-hydroxytryptamine(5-HT) concentrations at baseline and again at 4 and 8 weeks. Adverse events will be recorded in detail throughout the trial. Intention-to -treat analyses will be conducted, and the data will be assessed using a global statistical test.
Ethical approval for this trial was granted by the Institutional Ethics Committee of the Beijing Hospital of Traditional Chinese Medicine, Capital Medical University(2022BL02-059-02). Written informed consent was obtained from enrolled patients and will last throughout the trial. The trial results will be disseminated through peer-reviewed publications and conferences.
Discussion
Patients with breast cancer are more likely to experience insomnia, and it may influence the curative effect of their treatments. Undoubtedly, more attention is needed regarding insomnia in these patients; however, there is no established principle or guideline for patients with breast cancer who take multiple different medicines. Therefore, acupuncture may be useful as a less harmful intervention.
Trial registration number ISRCTN12913513, 7 March,2023
Novel Clinical prognostic model to predict survival in hepatocellular carcinoma after LR or LT should be considered including biological characteristics and inflammation score
Authors: Chen Qing , Pan Li-chao , Wang Han-xuan , Zhao Yang , Jia Ya-nan , Wang Jing , Li Xian-liang , Du Guo-Sheng , He Qiang , Lang Ren , Zhou Lin 
Published: October 2023

Abstract

Background:Since prognostic value of neutrophils-to-lymphocytes ratio (NLR) alone in hepatocellular carcinoma (HCC) patients is limited, incorporating tumor biological characteristics may further improve its prognostic ability.Methods:Cox regression analysis was conducted to identify risk factors affecting prognosis of 430 inlcuded HCC patients and the novel NLR (noNLR) model was established by taking correlation coefficient of Cox analysis results as the weight ratio. Then nomogram was used to verify the validity and reliability of this novel model. Patients were divided into high and low noNLR index group with the cutoff value of noNLR calculated by ROC curve. Finally, the predictive value of this novel model in predicting survival benefits was evaluated.Results:The noNLR model was established with independent risk factors for prognosis including NLR, AFP, tumor size and vascular invasion. The AUC of the training (0.7090 vs. 0.7599) and validation (0.6880 vs.0.7594) samples for the nomogram and noNLR models further demostrated the superiority of noNLR model. High noNLR was closely associated with shorter survival time with high recurrence risk and lower 5-year survival rate.Conclusion:noNLR model incorporating tumor biological characteristics can be qualified as a novel model to predict the prognosis of HCC patients after LR or LT.
Asset Pricing and Deep Learning
Authors: Zhang Chen 
Published: October 2023

Abstract
The relentless evolution of machine learning technologies has led to profound advancements across diverse financial disciplines, with asset pricing emerging as a pivotal application. This research ventures into the intricate fusion of advanced deep learning methodologies within the domain of asset pricing, with a particular emphasis on enhancing risk premium measurement to facilitate a deeper understanding of financial phenomena. This study evaluates an array of state-of-the-art deep learning architectures, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformers, and others fortified with memory mechanisms and attention features. All these models are uniformly tested on a consistent set of predictive signals, comprising firm characteristics, systematic risks, and macroeconomic indicators. Empirical evidence gleaned from this study underscores the superior predictive capabilities of these models, with special recognition given to RNNs and Transformers equipped with memory and attention mechanisms. Concurrently, the research emphasizes the substantial economic advantages that investors can reap by deploying deep learning forecasts, thereby attesting to the instrumental role of these technologies in contemporary financial operations. Notwithstanding these technological strides, the study underscores the critical need for integrating domain-specific knowledge and financial theories into the design of these models, hence fostering a harmonious convergence between AI advancements and traditional financial acumen. Further, the research exposes unique challenges that asset return prediction tasks present to deep learning models, particularly the issue of time-varying distribution. This invariably leads to a distribution shift problem, a crucial facet for accurate financial time series prediction. Through rigorous experimentation, the study substantiates the potential of deep learning methodologies in significantly enhancing asset risk premium measurement. With the continual evolution of the deep learning field, such methodologies can consistently broaden our understanding of the underlying economic mechanisms that govern asset pricing. In conclusion, this research not only reasserts the indispensable role of deep learning in the burgeoning field of financial technology but also delineates its superior potential and advantages over traditional machine learning techniques. Such insights illuminate a path for future research, aiming to harness the power of deep learning to foster a comprehensive and nuanced understanding of the complex dynamics that underpin asset pricing.
Deepfake audio detection and justification with Explainable Artificial Intelligence (XAI)
Authors: Govindu Aditi , Kale Preeti , Hullur Aamir , Gurav Atharva , Godse Parth 
Published: October 2023

Abstract
Deepfake audio refers to synthetically generated audio, often used as legal hoaxes to impersonate human voices. This paper generates fake audio from Fake or Real (FoR) dataset using Generative Adversarial Neural Networks (GANs). FoR dataset has the advantage of a diversity of speakers across 195,000 samples. The proposed work analyses the quality of the generated fake data using the Fréchet Audio Distance (FAD) score. FAD evaluation score of 23.814 indicates good quality fake has been produced by the generator. The study further enables glass box analysis of deepfake audio detection through Explainable Artificial Intelligence (XAI) models of LIME, SHAP and GradCAM. This research assists in understanding impact of frequency bands in audio classification based on the quantitative analysis of SHAPLey values and qualitative comparison of explainability masks of LIME and GradCAM. The use of FAD metric provides a quantitative evaluation of generator performance. XAI and FAD metrics help in the development of deepfake audio through GANs with minimal data input. The results of this research are applicable to detection of phishing audio calls and voice impersonation.
Aberrant choroid plexus formation in human cerebral organoids exposed to radiation
Authors: Durante Marco , Bender Tamara , Schickel Esther , Mayer Margot , Debus Jürgen , Grosshans David , Schroeder Insa 
Published: October 2023

Abstract
Brain tumor patients are commonly treated with radiotherapy, but the efficacy of the treatment is limited by its toxicity, particularly the risk of radionecrosis. We used human cerebral organoids to investigate the mechanisms and nature of postirradiation brain image changes commonly linked to necrosis. Irradiation of cerebral organoids lead to increased formation of ZO1+/AQP1+/CLN3+-choroid plexus (CP) structures. Increased CP formation was triggered by radiation via the NOTCH/WNT signaling pathways and associated with delayed growth and neural stem cell differentiation, but not necrosis. The effect was more pronounced in immature than in mature organoids, reflecting the clinically-observed increased radiosensitivity of the pediatric brain. Protons were more effective than X-rays at the same dose, as also observed in clinical treatments. We conclude that radiation-induced brain image-changes can be attributed to aberrant CP formation, providing a new cellular mechanism and strategy for possible countermeasures.
Therapeutic Potential of Salidroside in Diabetic Erectile Dysfunction: Attenuation of Oxidative Stress and Apoptosis via Upregulation of the Nrf2/HO-1 Pathway
Authors: Li Zhenghao , Jia Bin , Guo Zhongkai , Zhang keqin , Li Ziheng , Fu Qiang 
Published: October 2023

Abstract
The primary objective of this research was to delve into the potential therapeutic advantages and intricate molecular mechanisms of salidroside in enhancing erectile function in rats afflicted with DMED, addressing both the animal and cellular dimensions. We utilized Sprague-Dawley (SD) rats to establish DMED models and conduct an in vivo investigation. The DMED rats were treated with varying doses of salidroside and the effects of different doses of Salidroside on DMED were compared. The evaluation of erectile function involved the application of electrical stimulation to the cavernous nerves and the measurement of intracavernous pressure in real time. The penile tissue underwent histological examination and was subsequently analyzed through Western blotting. Hydrogen peroxide (H2O2) was employed in the in vitro trial to induce an oxidative stress condition for the purpose of identifying alterations in cell viability. The CCK8 assay was used to measure the viability of CCSMCs treated with or without salidroside. Flow cytometry was utilized to detect alterations in intracellular reactive oxygen species (ROS). Apoptosis was assessed through Western blotting and TdT-mediated dUTP Nick-End Labeling (Tunel) staining. Ultimately, we found that the Nrf2/HO-1 signaling pathway may be upregulated by Salidroside, leading to the improvement of erectile function in diabetic male rats by alleviating oxidative stress,and reducing apoptosis in the corpus cavernosum tissue.
β-Cyclodextrin modified Nano γ-alumina Synthesized by Co-precipitation Method for Absorption Properties Improvement of Nano Alumina
Authors: Esfanjani Leila , Farhadyar Nazanin , Shahbazi Hamid Reza , Fathi Fereshteh 
Published: October 2023

Abstract
In recent years, an exponential trends in the field of nano absorbents synthesis for water pollution especially heavy metals has been observed. Herein, we report the synthesis of γ-alumina/ β-cyclodextrin nanostructure as heavy metal adsorbent by co-precipitation method and characterization by the Fourier Transmission Infrared (FT-IR) spectroscopy, X- ray powder Diffraction (XRD) and, Scanning Electron Microscope (SEM). The results of XRD and SEM showed nano γ-Al2O3/β-cyclodextrin with 20-30 nm. It has been demonstrated that this nanostructure can be perceived to be potential adsorbent for heavy metal adsorptions.
Benefit analysis of carbon emission reduction in the pilot construction of"zero-waste city " in Chongqing
Authors: Liu YueTing , Zhang Qiang , Xie WenHao , Yuan XiaoHong 
Published: October 2023

Abstract
The construction of "zero-waste city" is an effective program to realize China's reduction of pollution and carbon emissions and promote circular economy. In this paper, the carbon reduction potential of solid waste source reduction and disposal in Chongqing around the implementation of the Zero-waste city policy is calculated based on the emission factor method using the WARM model developed by the EPA. The results show that the carbon emisssion of waste producted of various types of solid waste is mainly concentrated in the field of general industrial solid waste and livestock and poultry manure, and the carbon emisssion reduction in disposal comes from five major types of waste: general industrial solid waste, construction waste, hazardous waste, livestock and poultry manure, and straw. The "Zero-waste city" policy is an effective program to achieve carbon emission reduction in Chongqing, increasing the proportion of recycling and reduce the amount of solid waste to landfill as far as possible is the key to emission reduction in all types of solid waste disposal process. The trend of carbon emission reduction in 2025 is predicted to decrease in both "BAU" and "PLAN" scenarios, which indicates that the upgrading and transformation of local industries and the scaling up of the recycling industry have achieved good carbon emission reduction benefits.
Identifying groundwater recharge potential zone using analytical hierarchy process (AHP) in the semi-arid Shinile watershed, Eastern Ethiopia
Authors: Kassa Asfaw Kebede , Tessema Negash , Habtamu Amensis , Girma Bekele , Adane Zablon 
Published: October 2023

Abstract

Surface and groundwater are priceless resources not consistently concentrated both spatially and temporally. Groundwater is the most valuable resource and dynamic and is not distributed equally. Analytical hierarchy processes (AHP) were used in Shinile Watershed, Eastern Ethiopia to identify high-potential groundwater recharge zones. The amount of groundwater in a particular location depends on topography, lithology, geological structure, depth of weathering, slope, drainage pattern, land use land cover (LULC), and rainfall patterns. Numerous themes are covered in the potentiality mapping according to their relative relevance, including geology, slope gradient, LULC, soil texture, rainfall, lineament density, drainage density, groundwater fluctuation, etc. The weights of various themes have been determined using the AHP method, and then overlay analysis in the geospatial context has been completed. According to the investigation, the groundwater recharge potential zone has five levels: very low, low, moderate, high, and very high. The validation results using existing borehole sites demonstrate that the applied approach produces extremely dense data that can support long-term planning and sustainable groundwater resource utilization in a region with scarce water resources. This study guides effectively incorporating acceptable research findings into national policy and decision-making processes to dramatically improve groundwater supplies' sustainability in the study area.
Molecular Docking Simulations of Protoporphyrin IX, Chlorin e6, and Methylene Blue for Target Proteins of Viruses Causing Skin Lesions: Monkeypox and HSV
Authors: Lara-Vega Israel , Vega-López Armando 
Published: October 2023

Background:
The replication of monkeypox in the skin is critical to understanding its pathogenesis and spread. p37, a highly conserved 37 kDa peripheral membrane protein encoded by the
F13L gene in Orthopoxvitidae is a validated target for anti-poxviral medication like tecovirimat, the
first FDA-approved anti-poxviral drug that was approved in 2018. The detailed recognition mechanism
of tecovirimat on p37 of monkeypox has not been fully clarified. As p37, HSV-1 gD and HSV-2 gD
proteins of HSV are viral envelope glycoproteins identified as ligands for the human nectin-1 as a
functional receptor of permissive cells. The use of non-damaging light for microbial inactivation (MI)
has been documented for different virus like HSV, where photosensitizers (PSs) are used as lightresponsive agents which could generate antiviral responses primarily by oxidation. In addition, some
PSs could elicit antiviral responses in a light-independent way by interacting within the viral-cell
recognition sites.

Objective:
This paper aims to evaluate the formation of complexes between the latest structural data
available on the range of monkeypox and HSV-1/2 envelope proteins with the approved PSs protoporphyrin IX, chlorin e6, and methylene blue.

Methods:
Ligands and receptors preparation, and molecular docking analyses were performed with
Chimera and the Autodock Vina Software. Molecular docking and molecular dynamics simulation
(MD) analyses for a 100 ns trajectory were also performed for the p37 – Methylene blue complex.

Results:
PSs studies were found to form complexes into the patch regions of recognition between
HSV-1/2 gD and human receptors, while MB was found to form a complex with the p37 protein into
de pocket region where tecovirimat acts. MD simulation showed stability in the interaction of MB with
the pocket region of the p37 protein.

Conclusion:
The molecular mechanisms of potential dual antiviral activity for these complexes were
clarified showing that MI with the use of these PSs could be further evaluated for viral skin lesions
produced by monkeypox and HSV.
Current Views About the Link between SARS-CoV-2 and the Liver:
Friends or Foe?
Authors: Lovero Roberto , Charitos Ioannis Alexandros , Topi Skender , Castellaneta Francesca , Cazzolla Angela Pia , Colella Marica 
Published: October 2023

Abstract:
The emergence of the novel coronavirus and the pandemic resulting from its spread
have led to significant negative impacts on health, economy, relationships, and others. Particularly
in the field of hospital care, the need for a greater number of patients has led to a breakdown of
the system. Gastrointestinal manifestations are common in SARS-COV 2 patients, while 10% of
those who are sick exhibit symptoms only from gastrointestinal without any manifestation on the
part of the respiratory tract. The main manifestations are nausea, vomiting, diarrhoea, and anorexia.
It is also interesting to note that biochemical liver disorder is a frequent finding and is associated
with a worse prognosis and higher probability admission to intensive care. It was also
observed that RNA from the virus was found in the stool several days after the tests came back
negative pulmonary secretions, while rectal swab virus detection methods were used with a lower
but comparable sensitivity to that of nasal swabs. Gastrointestinal symptoms in SARS-COV 2
infection are common and their search should be part of the initial diagnosis approach and have a
connection with the gut microbiota dysbiosis and this can lead to an alteration of the gut/liver
axis.
Artificial Intelligence System-based Chatbot as a Hotel Agent
Authors: Ali Javeria , Amjad Ume Aymen , Ansari Wajeeha Iqbal , Hafeez Fareeha 
Published: October 2023

Background:
The idea of being able to communicate with an electronic device in a
similar way as human beings is now the new big thing in the world of Artificial Intelligence. The
fusion of AI and Cloud computing has given rise to a new technology that can understand and
learn conversations in the natural language used by humans. In this Era, where automation is taking over the world, the invention of smart chat-bots has made it possible to imitate humans in
various applications to reduce human effort and thereby perform at maximum efficiency.

Objective:
The objective is to replace a human-constituted assignment with an error-free technology. By using the intent modular concept of dialog flow, the role of the hotel receptionist is eliminated. The purpose of using an API of Google Cloud Platform namely Dialog flow in this project is to conveniently perform NLP (Natural Language Processing) i.e. training a robot to perform according to our instructions and understand the natural language spoken by humans and
the hardware attached to the device enables the listening and speaking of the smart bot.

Methods:
Utilization of Dialog flow Enterprise Edition to make “Hotel Agent” with the use of
intents comprising of a general hotel glossary.

Results:
Dialog flow as a natural language processing recognizer running on the processor Raspberry pie with Python as its constituent language. Finally, it is connected to Google Assistant to
make it publicly available in the execution phase.

Conclusion:
The successful testing of the Artificial Intelligence-based device has ensured that
manpower could be conveniently replaced by Machine Intelligence by using knowledge-based
databases.
Investigation of Quality of Life After Coronary Artery Bypass Surgery: A 10-Year Long-Term Follow-Up Study
Authors: Yildiz Esra , Yildiz Ziya , Dayapoğlu Nuray 
Published: October 2023

Background. Quality of life (QoL) is a multifactorial concept that is used to assess physical and mental health. This cross-sectional study administered the Short Form 36 Health Survey Questionnaire (SF-36) and a sociodemographic datasheet to evaluate the QoL of patients who underwent coronary artery bypass grafting (CABG).
Aim. With this study, we aimed to determine the quality of life of patients who had open heart surgery years later.
Methods. Patients who underwent elective isolated CABG from January to December 2011 in the cardiovascular disease’s clinic of a hospital in Eastern Turkey were recruited, after which data were collected from them via telephone and mail. One patient was contacted by mail, and 32 others were contacted by telephone. The data were examined through the analysis of numbers of percentages, mean values, and standard deviations. The Mann–Whitney U test, Kruskal–Walli’s test, and correlation analysis were also conducted.
Results. Of the patients who underwent surgery, 33 responded to our survey. Their mean age was 69.03±10.91 years. The results showed that gender, marital status, and educational attainment affected the mean SF-36 scores of the participants (p < 0.05) and that the mean QoL score of the patients was low.
Conclusion. Considering the mean age of the respondents, studies that compare such patients with those who did not undergo surgery should be carried out.