bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved Deep Q-network for Mobile Charging Sequence Scheduling with the Minimal Mobile Charger Energy Capacity in Wireless Rechargeable Sensor Network
Authors: Jiang Chengpeng , Chen Wencong , Li Jinglin , Wang Jing , Wang Ziyang , Xiao Wendong 
Published: February 2023

Abstract
Wireless rechargeable sensor network (WRSN) is a new type of wireless sensor networks (WSNs) with rechargeable sensor nodes, which provides a feasible way to overcome the energy constraint prob- lem in WSN. Mobile charging is promising for WRSN by charging sensors using the mobile charger (MC), usually via wireless energy transfer (WET). However, it is challenging to maintain the network working sustainably under the limited capacity of the MC, and most existing works assume that the capacity of MC is infinite or with a very large value, which may be impossible in many real applica- tions. This paper will study the mobile charging sequence scheduling problem to maintain the network working sustainably and minimize the energy capacity of the MC (CSSEC). Specifically, the problem of minimizing the energy capacity of MC is coupled with mobile charging sequence scheduling, and the charging sequence will directly affect the energy cost of MC during a charging tour. Therefore, we propose an improved deep Q-network for CSSEC (IDQN-CSSEC) to address this issue. It employs the MC as the agent to explore the WRSN, and determines a charging policy for MC based on the charging demand of sensors, which selects the next sensor for charging. IDQN-CSSEC uses the Q learning and deep Q-network (DQN) comprehensively, which trains the Q table of the Q learning and the networks of DQN in the early stage of the training, and updates them simultaneously. The action determined by Q learning is selected with a greater probability, which decreases as the iteration step increases. Simu- lation experiments verify that the charging policy determined by IDQN-CSSEC can make the network work sustainably with the minimal energy cost of the MC by comparing it with the baseline methods.
Differences in Word Choice between Male and Female Translators: Analyzing Persian Translations of “A Man Called Ove”
Authors: Alipour Roya 
Published: February 2023

Abstract
The present study concentrates on answering the question of whether there are unintentional differences between genders in the translation of emotive and non-emotive texts, resulting in female translators preferring more expressive words when translating emotive texts in comparison to their male counterparts. The works of four translators, two males and two females, who had translated Fredrik Backman’s novel: A Man Called Ove, from English into Persian were used as samples of the study. To answer the research question, qualitative method was used, and the data were collected by analyzing some words, phrases and sentences as the bases for analysis. It was concluded that although there were obvious differences in word choice in translations, no specific pattern was found that showed gender might affect translation of emotive and non-emotive texts.
On the calculation of phonetic feature vectors and division of Min Chinese
Authors: Song Jiali , Zheng Wei 
Published: February 2023

Abstract
The affinity between dialects is reflected in the phonetic similarity. Using the vector space model of Python language, the dialect phonetic features can be transformed into the vector data format, and then the cosine similarity formula is used to compare and analyze. Assign values to the intimacy and estrangement of 19 dialect points in Min Chinese, and visualize the intimacy and estrangement in complex dialect areas. Finally, the calculated result matrix is compared with the results of traditional manual statistical research to show the rationality and accuracy of the econometric analysis method.
Rethinking of Rural Land Consolidation Model from A Village Scale of Mountainous Areas : Insight on Factor Integration
Authors: Lan ZHAO , Yanlin HAN , ZHANG Linlin , Lei HUANG , DENG Xiyue 
Published: February 2023

Abstract
How to effectively promote the development and transformation of mountainous agriculture is the key to cracking the bottleneck of China's rural development. Land consolidation has always been one of the main means to achieve it. Based on the rural factor resources, land resources, labor resources, agricultural industrial resources and ecological landscape resources, this paper selects a typical mountain village—Qianlong Village of Guanyin Town in Huaying City as a research area. Through field investigation and face-to-face interviews, on the basis of the division of "production-living-ecology" space, combined with the industrial development orientation and the integration characteristics of various factors, the land consolidation planning model based on factor integration is constructed. Evaluation system of rural resources integration effect is built based on the matter-element extension evaluation model. The evaluation results show that land consolidation has performed excellently for industrial factors and ecological landscape resources, land resources and rural labor resources, indicating that land consolidation is effective in promoting rural industrial economic development and improving rural landscape functions. In the short-term, the effects of land use structure adjustment and rural labor integration cannot be fully realized. This practice provides a case and a useful reference on how land consolidation can promote the transformation of rural economic development through factor integration.
Triplex PCR Amplification of Different Melting Profile Amplicons for Simultaneous Detection of HCV, HBV, and HIV-1 Genomes in a Single Tube
Authors: Nemr Waleed Abdelgaber , Radwan Nashwa Kamal 
Published: February 2023

Abstract
Background
Hepatitis C Virus (HCV), Hepatitis B Virus (HBV), and Human Immunodeficiency Virus 1 (HIV-1) are epidemic blood-borne viruses, pose threats to human health and cause economic losses to nations for combating their infection transmission. However, the diagnostic methodologies which depend on the detection of viral nucleic acid are much expensive but more accurate than immunological testing.
Methods
This study approaches a lower cost triplex PCR method for simultaneous detection of the nucleic acids (genomes) of the three mentioned viruses. This PCR targets amplification of a short conserved region, having distinguishable melting profile and electrophoretic molecular weight, inside each viral genome. Therefore, this diagnostic method will be applicable with both conventional PCR (combined with electrophoresis) and real time PCR facilities. Many in silico investigations have been conducted to prove the capability of the approached PCR to detect variants of each virus. Then, Egyptian isolates of each virus have been subjected for the laboratory application of the given protocol.
Results
The results revealed good sensitivity for detecting and discriminating low copies of each type of viral particles.
Conclusions
The given protocol presents a sensitive PCR diagnostic test, with less time and cost those are ordinary needed for detecting three types of viruses. This will be a good substitutive system for the mistakable immunological-based tests.
The effects of estrus cycle on the expression of ovarian biological clock-related genes of Xiang pigs
Authors: Tang Liang-Ting , Huang Shihui , Niu Xi , Li Sheng , Wang Jiafu , Ran Xue-Qin , Tang Liang-Ting 
Published: February 2023

Abstract
The biological clock has been studied to play a critical role in the reproductive system of various living organisms like swine. To examine the effects of estrus cycle on the expression of ovarian biological clock-related gene in Xiang pig, in this study, we analyzed the expression and alternative splicing of biological clock-related genes in ovary during estrus and diestrus periods. In total, we detected 90 clock-related genes expressed in the ovaries of the Xiang pigs and found 33 clock-related genes differentially expressed between estrous and diestrous stages. We identified 44 differential splicing events from the transcripts of 34 biological clock-related genes. Furthermore, we also found 20 genes including the core clock components, arntl and cry1 were differentially regulated only at AS level and 14 genes, including per1 and clock, were differentially regulated at both expression and AS levels. We also proved that the core clock genes per1, cry1, clock and arntl and the clock-related genes, ppp1cb and ntrk1 were rhythmically expressed in Xiang pig ovaries by RT-qPCR experiments. The results demonstrated that the biological clock in the ovaries of Xiang pigs might play an important role in regulating the ovarian physiological functions by the transcriptional and post-transcriptional regulation.
Normal integral bases of Lehmer's cyclic quintic fields
Authors: Aoki Miho , Hashimoto Yu 
Published: February 2023

Abstract
Let Kn be a tamely ramified cyclic quintic field generated by a root of Emma Lehmer's parametric polynomial. We give all normal integral bases for Kn only by the roots of the polynomial, which is a generalization of the work of Lehmer in the case that n4+5n3+15n2+25n+25 is prime number, and Spearman-Willliams in the case that n4+5n3+15n2+25n+25 is square-free.
Mathematics Subject Classification (2010) Primary 11R04 · 11R20, Secondary 11C08 · 11L05 · 11R80
Fashion Intelligence in the Metaverse: Promise and Future Prospects
Authors: Mu Xiangyu , Zhang Haijun , Shi Jianyang , Hou Jie , Ma Jianghong , Yang Yimin 
Published: February 2023

Abstract
With the development of artificial intelligence (AI) and the constraints on offline activities imposed due to the sudden outbreak of the COVID epidemic, the Metaverse has recently attracted significant research attention from both academia and industrial practitioners. Fashion, as an expression of a consumer’s aesthetics and personality, has enormous economic potential in both the real world and the Metaverse. In this research, we provide a comprehensive survey of two of the most important components of fashion in the Metaverse: virtual digital humans, and tasks related to fashion items. We survey state-of-the-art articles from 2007 to the present and provide a new taxonomy of extant research topics based on these articles. We also highlight the applications of these topics in the Metaverse from the perspectives of designers and consumers. Finally, we describe possible scenes involving fashion in the Metaverse. The current challenges and open issues related to the fashion industry in the Metaverse are also discussed in order to provide guidance for fashion practitioners, and to shed some light on the future development of fashion AI in the Metaverse.
Cuproptosis-related genes to establish prognostic model and predict the immunotherapy response in cervical cancer
Authors: Xue Xinzi , Zhao Yue , Zhang Dan , Xu Danying , Huang Long , Wang Xia 
Published: February 2023

Abstract
Background
Cuproptosis is a new type of cell death recently discovered. Some studies have found that cuproptosis- related lncRNA is related to the prognosis of cervical cancer. However, there are few studies on the relationship between cuproptosis-related genes and immune infiltration and prognosis of cervical cancer. The objective of this study was to investigate the prognosis of cervical cancer and cuproptosis-related genes and the response to immunotherapy.
Methods
The clinical data of cervical cancer patients were downloaded from TCGA database, and randomly divided into training group and validation group. The cuproptosis -related genes was screened out by univariate Cox, Lasso-Cox and multivariate Cox analysis, and the risk model was constructed. The OS of two subgroups and the whole cohort were analyzed by Kaplan-Meier curve, and the prognostic value of the model was verified by ROC curve and PCA. The independent prognostic value of clinical features and risk score was analyzed by univariate and multivariate analysis. Then, the gene ontology (GO), Kyoto Gene and Genome Encyclopedia of Genes and Genomes (KEGG) were analyzed to illustrate the difference genes of the biological characteristics of the two risk groups, and the drug sensitivity between the two subgroups was also analyzed.
Results
We constructed five genes related to the death of copper (FDX1, ARF1, APP, HSF1, MT1A). From the survival curve of risk score, whether it is training group, validation group or overall OS, the total survival time of low-risk group is far longer than that of high winds and obstacles, and it has a good prognosis (P < 0.001). In addition, by univariate and multivariate Cox analysis, risk score and T (tumor size) were independent prognostic factors (P < 0.001). According to the receiver operating characteristic curve (ROC) and PCA, the prognosis model of this study can achieve high accuracy, with the area under the curve (AUC) of 1 year, 3 years and 5 years being 0.751, 0.736 and 0.748 respectively. We also use classification ROC analysis to evaluate the sensitivity and specificity of risk score and other clinical features such as age, grade and stage. The results of enrichment analysis showed that extracellular matrix, extracellular structure and external packaging structure were closely related to genes. We also found that the sensitivity of 24 drugs is closely related to the risk score, which can provide accurate therapeutic drugs for different groups of patients in time.
Conclusion
Our study established a prognostic risk model composed of 5-cuproptosis related genes, and proved that the model has obvious relationship with the prognosis of patients, which can accurately predict the overall survival of patients. And patients with low risk score are more likely to benefit from immunotherapy and the enrichment of immune cells is higher.
Long-term functional outcomes and multidisciplinary management after Duhamel pull-through for total colonic aganglionosis- 20-year experience in a tertiary surgical centre
Authors: Bhandarkar Kailas , Giuliani Stefano , Cross Kate , De Coppi Paolo , Blackburn Simon , Curry Joe 
Published: February 2023

Abstract
Purpose Management of patients with total colonic aganglionosis (TCA) is challenging for paediatric surgeons. The purpose of this study was to review our institution’s 20-year experience regarding long-term outcomes in these patients.
Methods Retrospective review was conducted for patients diagnosed with TCA. Data was collected on demographics, clinical presentation, complications, need for additional surgery and long-term effects on bowel function.
Results Out of 202 patients with Hirschsprung’s disease (HSCR), 13 were diagnosed with TCA (6.4 %). Clinical presentation was variable - 11 presented in neonatal period and 2 in infancy. Ileorectal Duhamel pull-through was performed in all patients. Median follow up was 13 years. 11 are toilet trained, of whom 5 are fully continent. 6 continue to have problems with bowel continence or constipation. 1 developed recurrent episode of Hirschsprung’s associated enterocolitis (HAEC). 2 patients had stoma re-established. Patients experiencing difficulties in bowel function are jointly managed by a multidisciplinary team consisting of surgeons, gastroenterologists, paediatric psychologists, and clinical nurse specialists.
Conclusions TCA can be associated with significant long-term morbidity. Nearly half of the patients have ongoing problems with bowel continence requiring a permanent stoma in some. Diligent follow-up coupled with multidisciplinary team input has helped manage these patients in our institution.
Design, Modeling, and Analysis of Memory Allocation Policies for Rack-Scale Memory Disaggregation
Authors: Puri Amit , Jose John , Venkatesh Tamarapalli 
Published: February 2023

Abstract
Memory disaggregation architecture is an emerging alternative to the traditional server architecture to address the issue of memory under-utilization in data centers. Memory disaggregation offers a large pool of remote memory connected via high-speed network fabric, thereby allows independent upgrade of memory components. Disaggregated design gives better adaptability of servers to the ever-increasing memory requirement from applications, such as HPC workload, video and big data analytics. However, disaggregrated memory architectures cause significantly large memory access latency due to the limited speed of interconnects currently used. In this paper, we propose a rack-scale disaggregated memory architecture and discuss the various software/hardware design aspects for such an architecture. We analyze the remote memory access latency in this architecture and observe that a significant part of the latency arises out of not only the interconnect, but also due to the contention at the queues of remote memory. To address this issue, we propose two-phase memory allocation policies for disaggregated memory environments that could significantly reduce the average memory access latency, compared to the conventional policies. We built a simulator that uses a trace-based front-end module and a cycle-accurate memory simulator to evaluate the memory access latency in a disaggregated memory system. We conduct experiments with different allocation policies across various benchmarks, representing applications with diverse memory access patterns. Our study shows encouraging results toward adoption of rack-scale memory disaggregation with acceptable memory latency, that could further be reduced with other system-level optimizations.
Assessment of lateral depths and irrigation water levels on yield, yield parameters and biyoethanol content in sweet sorghum
Authors: Polat Begum , Buyuktas Dursun , Karaca Cihan , Aydinsakir Koksal , Erkan Selime Benemir , Turhan Irfan , Bastug Ruhi 
Published: February 2023

Abstract
In this study, it was aimed to evaluate the effects of different lateral depths and irrigation treatments on the bioethanol yield and yield components of the sweet sorghum (Sorghum bicolor L.) in the subsurface drip irrigation method. The experiment was carried out in three replications in a randomized block trial design in 2020 and 2021 in Antalya, Turkey. In irrigation treatments, three different irrigation water levels in which 100%, 66% and 33% of the amount were applied as irrigation water (I1, I2, I3, respectively), when the cumulative reference crop evapotranspiration reached 25±5 mm and lateral depth combinations in which the laterals were placed at two different depths, 25 cm and 50 cm (D1 and D2, respectively) were used. At the end of both years, a statistical difference (p<0.01) was determined between the mean yield components (forage, hay, juice and sugar yield) of different irrigation water levels. As the applied irrigation water level increased, the yield components also increased. While the interaction of lateral depth and irrigation water level affected forage and hay yield in the second year, sugar and juice yield values in the first year. In this study, it was determined that the difference in the effects of the interaction between the years was due to the irregular temperature increases in the second year climate, and the lateral depth of 50 cm was more suitable in drier conditions. At the end of two years, the bioethanol yields and evapotranspiration (ET) obtained in D1 treatments at different irrigation levels varied between 440-2962 L ha-1 and 105.1-473.0 mm, respectively, while it varied between 440-3222 L ha-1 and 105.1-473.0 mm in D2 treatments, respectively. The highest bioethanol yield in the first year was obtained from D1I1, D2I2, D2I1 treatments, while in the second year, from D2I1 was obtained. Considering the I1 treatments, more evapotranspiration was realized in the D1 despite the same amount of irrigation water applied in both years. In addition, when the applications that were irrigated at the same amount at 25 and 50 cm lateral depths in both years were compared, it was determined that water productivity (WP) and irrigation water efficiency (IWP) values obtained at 50 cm lateral depth were higher, except for I3. In this study, it was determined that a lateral depth of 50 cm was more suitable for maximum bioethanol yield, especially in warmer climatic conditions. At the same time, I1 and I2 irrigation levels have been suggested, depending on climatic conditions.
An Efficient Stock Price Prediction Mechanism Using Multivariate Sequential LSTM Autoencoder
Authors: G Rubell Marion Lincy , Selby Nevin , Taparia Aditya 
Published: February 2023

Abstract
In this research, a method is proposed for predicting stock prices using deep learning techniques, specifically the Multivariate Sequential Long Short-Term Memory Autoencoder. This variant of the LSTM neural network model is designed to handle multivariate time series data. This model is able to capture dependencies between variables using the LSTM component, while the autoencoder component is used to learn a useful representation of the data in an unsupervised manner, which can improve the accuracy of stock price predictions. Its sequential structure also allows it to capture temporal dependencies in the data, making it well-suited for time series prediction tasks. The goal of this research is to help investors maximize returns through the identification of stock price trends. This paper also discusses the literature on various time series prediction models and describes the implementation and comparison of several techniques, including Univariate Sequential LSTM (USLSTM), Univariate Sequential LSTM Autoencoder (USLSTMA), Gated Recurrent Unit (GRU), Random Forest, and Generative Adversarial Networks (GAN). These models are compared with the proposed variants of Multivariate Sequential LSTM (MSLSTM), Multivariate Sequential LSTM Autoencoder (MSLSTMA) for market price prediction. In the experiments performed with real stock market data, the MSLSTMA model outperformed all other models in predicting the stock prices.