bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advancing Cognitive Radio in 5G Networks: A Survey of Flexible and Reconfigurable Antenna Technologies
Authors: C Anjani , Muduli Arjuna 
Published: February 2024

Abstract:
Nowadays, the communication industry is looking for a cognitive radio platform that can be
used to handle multiple frequency bands, utilize various transmission protocols and be reconfigurable. For
spectrum allocation, two methodologies have been adopted for CR between users who are licensed (PU)
and those who are not (SU). They are spectrum overlay and spectrum underlay. Secondary users need to
operate below the principal users' noise level therefore, significant restrictions resisted on the strength of
their transmission in spectrum underlay methodology. Spectrum underlay is a type of underlay that is used
in the construction of the unoccupied section of the spectrum searched by CR in the spectrum overlay process. A reconfigurable antenna is needed on RF front-end side of CR, which will a range of completely to
span a vast array of frequencies specified sub-bands of frequency, and this is often a major design challenge. An antenna with a flexible monopole for Ultra-wideband equipment competent to function between
the frequency range of 3.1 GHz to 10.6 GHz. Designs of reconfigurable antennas reported in the literature
are mostly observed to be capable of manual tuning or switching between two or a few frequency bands.
Hence, the requirement of new designs of integrated UWB and reconfigurable narrowband antennas that
operate from 2 GHz and up to 12 GHz frequency range with a high degree of automated tunability or
switching facility into different narrow bands would have a strong application potential for CRs.
Performance Analysis of Multiple Interference Suppression of One Small Four Elements Array Antenna used in Satellite Navigation System
Authors: Hao Ronghua , Zhao Xiaobo 
Published: February 2024

background:
The anti-interference requirements of miniaturized satellite navigation arrays is increasing, the anti-interference ability reducing of small aperture arrays caused by large mutual coupling, large main lobe width, may be solved through adopting quad-arrays antenna.

objective:
Research of multiple interference suppression method is the aim of the paper, and it makes the research of small four element satellite navigation array antenna

method:
In the paper, it focuses on the structural design of low coupling polarized array antennas, and makes analysis of mutual coupling between array elements, the compensation technology based on auxiliary sources is proposed.

result:
Experimental analysis of antenna narrowband interference suppression are made. Relevant anti-interference results on four element antenna are also obtained. The anti-interference ability of four element antenna is summarized.

conclusion:
The anti-interference ability of four element antenna is analyzed and summarized in the paper, related results show that small four element satellite navigation array antenna can be used in the multiple interference suppression, in the satelliate navigation system.
An Approach to Forecast Quality of Water Effectively Using Machine Learning Algorithms
Authors: Nambiar P.V. Manjusha , Urkude Giridhar 
Published: February 2024

Background:
The quality of water directly or indirectly impacts the health and environmental
well-being. Data about water quality can be evaluated using a Water Quality Index (WQI).
Computing WQI is a quick and affordable technique to accurately summarise the quality of water.

Objective:
The objective of this study is to find strategies for data preparation to categorize a dataset
on the water quality in two remote Indian villages in different geographic locations, to predict the quality
of water, and to identify low-quality water before it is made accessible for human consumption.

Methods:
To accomplish this task, four water quality features Nitrate, pH, Residual Chlorine,
and Total Dissolved Solids which are crucial for human consumption, are considered to dictate the
quality of water. Methods used in handling these features include five steps that are data preprocessing
with min-max normalization, finding WQI, using feature correlation to identify parameter
importance with WQI, application of supervised machine learning regression models such as
Random Forest (RF), Multiple Linear Regression (MLR), Gradient Boosting (GB) and Support
Vector Machine (SVM) for WQI prediction. Then, a variety of machine learning classification
models, including K-Nearest Neighbour (KNN), Support Vector Classifier (SVC), and Multi-layer
Perceptron (MLP), are ensembled with Logistic Regression (LR), acting as a meta learner, to create
a stack ensemble model classifier to predict the Water Quality Class (WQC) more accurately.

Results:
The examination of the testing model revealed that RF regression and MLR algorithms
performed best in predicting the WQI with mean absolute error (MAE) of 0.003 and 0.001 respectively.
Mean square error (MSE), root mean square error (RMSE), R squared (R2), and Explained
Variance Score (EVS) findings are 0.002,0.005,0.988 and 0.998 respectively with RF
while 0.001,0.031,0.999 and 0.999 respectively with MLR. Meanwhile, for predicting WQC, the
stack model classifier showed the best performance with an Accuracy of 0.936, F1 score of 0.93,
and Matthews Correlation Coefficient (MCC) of 0.893 for the dataset of Lalpura and Accuracy
of 0.991, F1 Score of 0.991 and MCC of 0.981 respectively for the dataset of Heingang.

Conclusion:
This study explores a method for predicting water quality that combines easy and
feasible water quality measurements with machine learning. The stack model classifier performed
best for multiclass classification, according to this study. To ensure that the highest quality
of water is given throughout the year, information from this study will motivate researchers to
look into the underlying root causes of the quality variations.
Distributed Dynamic State Estimation of Power Systems Considering Dynamic State Constraints based on Phasor Measurements Units
Authors: Juan Li , Jia-ming Wang , Yun-long Jiang , Xiong Yang , Mao-lin Zhu , Hao Liu 
Published: February 2024

Background:
Dynamic state estimation can provide detailed information about power
systems. However, there is no clear, dynamic equation for the state transition of bus voltages in
power systems. Currently, smoothing methods based on historical data are commonly used, but
they cannot ensure accurate state prediction in power systems with a large amount of renewable
energy. Moreover, the fast sampling rate of phasor measurement units generates a vast amount of
real-time data for the dispatch center, making it challenging for centralized state estimation to
meet real-time demands.

Objective:
This paper proposes a distributed power system state estimation considering dynamic
state constraints to address the above issues.

Methods:
By incorporating the constraints between the dynamic states of the system dynamic
components and the bus voltage phasors, the state transition equations for bus voltage phasors are
constructed based on the predicted dynamic states and the nodal injection power equations. This
allows taking the dynamic model constraints into account when predicting bus voltage phasors.
Then, based on the principle of hierarchical coordination and distributed state estimation, the
method of estimation-coordination-correction is adopted to acquire system state information
quickly and accurately.

method:
By incorporating the constraints between the dynamic states of the system dynamic components and the bus voltage phasors, the state transition equations for bus voltage phasors are constructed based on the predicted dynamic states and the nodal injection power equations. This allows taking the dynamic model constraints into account when predicting bus voltage phasors. Then, based on the principle of hierarchical coordination and distributed state estimation, the method of estimation-coordination-correction is adopted to acquire system state information quickly and accurately.

Results:
Furthermore, an IEEE 9-bus system and an IEEE 39-bus system are used to validate the
proposed method. The proposed method is compared with other algorithms to prove its superiority.

result:
Furthermore, an IEEE 9-bus system and an IEEE 39-bus system are used to validate the proposed method. And the proposed method is compared with other algorithms to prove its superiority.

Conclusion:
The simulation results show that the proposed method can effectively improve the
accuracy of the state estimation results of power systems under dynamic conditions.

conclusion:
The simulation results show that the proposed method can effectively improve the accuracy of the state estimation results of power systems under dynamic conditions.

other:
None
Prevalent Oral Drug Delivery System for Dental Care
Authors: Frank Amanda , Singh Komal , Singh Preet Amol , Bajwa Neha 
Published: February 2024

Abstract:
Oral drug delivery systems, including fluoride supplements, constitute one of the most
prevalent routes for the administration of medications, playing a crucial role in the treatment and
prevention of various diseases, including dental caries. Fluorides, employed as a preventive and
control measure against dental caries, are available in two primary forms: Systemic fluorides and
topical fluorides. Topical fluorides are found in toothpaste, varnish, gels, mouth rinses, and washes,
while systemic fluorides are administered via lozenges, tablets, and liquid formulations.

:
This literature work focuses on the specific challenges associated with fluoride supplement formulations
and aims to shed light on potential setbacks. Among these challenges, poor patient
compliance, especially in pediatric populations, and the associated risk of underdosing or overdosing,
leading to fluorosis, stand out as significant concerns. If left unaddressed, these issues
could compromise the efficacy of one of the most effective caries prevention methods available.

:
The primary objective of this study is to explore advancements in fluoride supplement formulations,
with a particular emphasis on addressing the identified challenges, especially for pediatric
and geriatric patients. By devising improved formulations tailored to the unique needs of these
populations, we aim to mitigate compliance issues and minimize the associated risk factors,
thereby strengthening the effectiveness of dental caries prevention strategies. This research endeavors
to contribute valuable insights to the field of oral healthcare and pharmaceutical development,
ultimately promoting better oral health outcomes for individuals of all ages.
Enhancing Image Captioning Using Deep Convolutional Generative
Adversarial Networks
Authors: Jaiswal Tarun , Pandey Manju , Tripathi Priyanka 
Published: February 2024

Introduction::
Introduction: Image caption generation has long been a fundamental challenge in the
area of computer vision (CV) and natural language processing (NLP). In this research, we present
an innovative approach that harnesses the power of Deep Convolutional Generative Adversarial
Networks (DCGAN) and adversarial training to revolutionize the generation of natural
and contextually relevant image captions.

Method::
Our method significantly improves the
fluency, coherence, and contextual relevance of generated captions and showcases the effectiveness
of RL reward-based fine-tuning. Through a comprehensive evaluation of COCO datasets,
our model demonstrates superior performance over baseline and state-of-the-art methods.
On the COCO dataset, our model outperforms current state-of-the-art (SOTA) models
across all metrics, achieving BLEU-4 (0.327), METEOR (0.249), Rough (0.525) and CIDEr
(1.155) scores.

Result::
The integration of DCGAN and adversarial training opens new possibilities
in image captioning, with applications spanning from automated content generation to enhanced
accessibility solutions.

Conclusion::
This research paves the way for more intelligent
and context-aware image understanding systems, promising exciting future exploration and innovation
prospects.
Effectiveness of Telemedicine for Musculoskeletal Disorders: Umbrella Review
Authors: Bargeri Silvia , Castellini Greta , Vitale Jacopo Antonino , Guida Stefania , Banfi Giuseppe , Gianola Silvia , Pennestrì Federico 
Published: February 2024

Background
Several systematic reviews (SRs) assessing the use of telemedicine for musculoskeletal conditions have been published in recent years. However, the landscape of evidence on multiple clinical outcomes remains unclear.

Objective
We aimed to summarize the available evidence from SRs on telemedicine for musculoskeletal disorders.

Methods
We conducted an umbrella review of SRs with and without meta-analysis by searching PubMed and EMBASE up to July 25, 2022, for SRs of randomized controlled trials assessing telemedicine. We collected any kind of patient-reported outcome measures (PROMs), patient-reported experience measures (PREMs), and objective measures, including direct and indirect costs. We assessed the methodological quality with the AMSTAR 2 tool (A Measurement Tool to Assess systematic Reviews 2). Findings were reported qualitatively.

Results
Overall, 35 SRs published between 2015 and 2022 were included. Most reviews (n=24, 69%) were rated as critically low quality by AMSTAR 2. The majority of reviews assessed “telerehabilitation” (n=29) in patients with osteoarthritis (n=13) using PROMs (n=142 outcomes mapped with n=60 meta-analyses). A substantive body of evidence from meta-analyses found telemedicine to be beneficial or equal in terms of PROMs compared to conventional care (n=57 meta-analyses). Meta-analyses showed no differences between groups in PREMs (n=4), while objectives measures (ie, “physical function”) were mainly in favor of telemedicine or showed no difference (9/13). All SRs showed notably lower costs for telemedicine compared to in-person visits.

Conclusions
Telemedicine can provide more accessible health care with noninferior results for various clinical outcomes in comparison with conventional care. The assessment of telemedicine is largely represented by PROMs, with some gaps for PREMs, objective measures, and costs.

Trial Registration
PROSPERO CRD42022347366; https://osf.io/pxedm/
Combining top-down and bottom-up approaches to evaluate recent trends and seasonal patterns in U.K. N2O emissions
Authors: Saboya Eric , Manning Alistair J. , Levy Peter , Stanley Kieran M , Pitt Joseph , Young Dickon , Say Daniel , grant Aoife , Arnold Tim , Rennick Chris , Tomlinson Samuel , Carnell Edward , Artioli Yuri , Stavert Ann R , Spain T Gerard , O´Doherty Simon , Rigby Matthew , Ganesan Anita L 
Published: February 2024

Atmospheric trace gas measurements can be used to independently assess
national greenhouse gas inventories through inverse modelling. Here,
atmospheric nitrous oxide (NO) measurements made in the
United Kingdom (U.K.) and Republic of Ireland are used to derive monthly
NO emissions for 2013-2022 using two different inverse
methods. We find mean U.K. emissions of 90.5±23.0 (1σ)
and 111.7±32.1 (1σ) Gg NO
yr for 2013-2022, and corresponding trends of
-0.68±0.48 (1σ) Gg NO
yr and -2.10±0.72 (1σ) Gg
NO yr, respectively for the two
inverse methods. The U.K. National Atmospheric Emissions Inventory
(NAEI) reported mean NO emissions of 73.9 Gg
NO yr across this period, which is
14-33% smaller than the emissions derived from atmospheric data. We
infer a pronounced seasonal cycle in NO emissions, with
a peak occurring in the spring and a second smaller peak in the late
summer for certain years. The springtime peak has a long seasonal
decline that contrasts with the sharp rise and fall of
NO emissions estimated from the bottom-up U.K.
Emissions Model (UKEM). Bayesian inference is used to minimize the
seasonal cycle mismatch between the average top-down (atmospheric
data-based) and bottom-up (process model and inventory-based) seasonal
emissions at a sub-sector level. Increasing agricultural manure
management and decreasing synthetic fertilizer NO
emissions reduces some of the discrepancy between the average top-down
and bottom-up seasonal cycles. Other possibilities could also explain
these discrepancies, such as missing emissions from NH
deposition, but these require further investigation.
Soluble ST2 as a possible biomarker for inflammation in patients with acute heart failure
Authors: Lai Jiacheng , Huang Chongjian , Li Bin , Han Yongsheng 
Published: February 2024

Aim
The aim of this study was to explore the relationship between peripheral circulating serum soluble suppression of tumorigenicity-2 (sST2) levels and inflammatory biomarkers in patients with acute heart failure (AHF).

Methods
One hundred and eleven consecutive AHF patients with NYHA class II-IV were enrolled, and peripheral blood was collected within 24 h of admission for the detection of NT-ProBNP, sST2, hypersensitive troponin I, cytokines, precalcitoninogen, C-reactive protein, in addition to routine standard of care blood tests.

Results
The median sST2 of 111 patients was 47.50 ng/ml (24.25–86.15 IQR), of whom 43 patients (38.7%) had sST2 35 ng/ml or less; linear correlation analysis showed that serum sST2 correlated with NT-ProBNP (r
2 = 0.32), NEU% (r
2 = 0.41), NLR (r
2 = 0.36), CRP (r
2 = 0.50), IL-18 (r
2 = 0.43) (P < 0.001), and correlated with Hs-cTnI (r
2 = 0.19), NUE (r
2 = 0.25), LYM (r
2 = -0.23), IL-2RA (r
2 = 0.29) (P < 0.05). Multiple linear regression analysis depicted that CRP (β = 0.318), IL-18 (β = 0.368), NEU% (β = 0.346), NLR (β = −0.304), and NT-ProBNP (β = 0.324) significantly correlated with sST2 values, respectively (P < 0.05). ST2 levels have a linear association with length of hospitalization.

Conclusion
Peripheral blood inflammatory markers (CRP, IL-18, NEU%, NLR) in patients with AHF had a close relationship with sST2 levels, and the mechanism of action of sST2 may be related to the inflammatory response.
Prognostic role of coronary artery ectasia in patients with nonobstructive coronary artery disease
Authors: Gurgoglione Filippo Luca , Benatti Giorgio , Vignali Luigi , Tadonio Iacopo , Magnani Giulia , Denegri Andrea , Lazzeroni Davide , Tuttolomondo Domenico , De Gregorio Mattia , Indrigo Elia , Signoretta Gianluca , Abbati Vittoria , Nicolini Francesco , Ardissino Diego , Solinas Emilia , Niccoli Giampaolo 
Published: February 2024

Aims
Coronary artery ectasia (CAE) has been linked to the occurrence of adverse events in patients with ischemia/angina and no obstructive coronary arteries (INOCA/ANOCA), while the relationship between CAE and myocardial infarction with nonobstructive coronary arteries (MINOCA) has been poorly investigated. In our study we aimed at assessing differences in clinical, angiographic and prognostic features among patients with CAE and MINOCA vs. INOCA/ANOCA presentation.

Methods
Patients with angiographic evidence of CAE were enrolled at the University Hospital of Parma and divided into MINOCA vs. INOCA/ANOCA presentation. Clinical and quantitative angiographic information was recorded and the incidence of major adverse cardiovascular events (MACE) was assessed at follow-up.

Results
We enrolled a total of 97 patients: 49 (50.5%) with MINOCA and 48 (49.5%) with INOCA/ANOCA presentation. The presentation with MINOCA was associated with a higher frequency of inflammatory diseases (P = 0.041), multivessel CAE (P = 0.030) and thrombolysis in myocardial infarction (TIMI) flow < 3 (P = 0.013). At a median follow-up of 38 months, patients with MINOCA had a significantly higher incidence of MACE compared with those with INOCA/ANOCA [8 (16.3%) vs. 2 (4.2%), P = 0.045], mainly driven by a higher rate of nonfatal MI [5 (10.2%) vs. 0 (0.0%), P = 0.023]. At multivariate Cox regression analysis, the presentation with MINOCA (P = 0.039) and the presence of TIMI flow <3 (P = 0.037) were independent predictors of MACE at follow-up.

Conclusion
Among a cohort of patients with CAE and nonobstructive coronary artery disease, the presentation with MINOCA predicted a worse outcome.
MANAJEMEN LABA PADA PERUSAHAAN SEKTOR MAKANAN DAN MINUMAN
Authors: Pratiwi Devica , Shelyna Livianti  , Fendy Sunjaya  , Wendy Salim Saputra  , Gladhistani Renata  
Published: February 2024

Perusahaan melakukan manajemen laba untuk memperoleh keuntungan bagi perusahaan atau manajemen perusahaan. Beberapa faktor yang mempengaruhi pihak manajemen untuk melakukan manajemen laba, seperti profitabilitas, tanggung jawab sosial perusahaan (CSR) dan ukuran perusahaan. Penelitian ini berfokus pada perusahaan makanan dan minuman yang terdaftar di Bursa Efek Indonesia tahun 2018-2020. Terdapat 13 perusahaan yang dipilih dengan metode purposive sampling selama periode pengamatan selama 3 tahun. Hasil penelitian menunjukkan bahwa semua data observasi yang dikumpulkan dan lolos uji asumsi klasik. Hasil uji F menunjukkan bahwa penelitian layak dengan nilai t sebesar 0,036. Hasil uji t menunjukkan bahwa profitabilitas (0,719) dan CSR (0,148) tidak berpengaruh terhadap manajemen laba, sehingga hipotesis pertama dan kedua ditolak. Sedangkan ukuran perusahaan (0,004) memiliki pengaruh negatif terhadap manajemen laba dan berarti hipotesis ketiga diterima. Kesimpulan dari penelitian ini adalah ukuran perusahaan berpengaruh negatif terhadap manajemen laba, sedangkan profitabilitas dan CSR tidak berpengaruh terhadap manajemen laba.

Companies carry out earnings management to gain profits for the company or company management. Several factors influence management to manage earnings, such as profitability, corporate social responsibility (CSR) and company size. This research focuses on food and beverage companies listed on the Indonesia Stock Exchange in 2018-2020. There were 13 companies selected by purposive sampling method during the 3 year observation period. The results showed that all observational data were collected and passed the classical assumption test. The results of the F test show that the research is feasible with a t value of 0.036. The results of the t test show that profitability (0.719) and CSR (0.148) have no effect on earnings management, so the first and second hypotheses are rejected. Meanwhile, firm size (0.004) has a negative effect on earnings management and means that the third hypothesis is accepted. The conclusion of this study is that company size has a negative effect on earnings management, while profitability and CSR have no effect on earnings management.
ANALISIS EFEKTIVITAS PENYEWAAN MOBIL TERHADAP PERUSAHAAN STARTUP
Authors: Indrajaya Fransiskus Dion 
Published: February 2024

The development of companies in Indonesia is happening a lot after the Covid-19 pandemic began to subside. Many business people who have started to open their companies which are commonly referred to as startup companies have started to appear in Indonesia. Startup companies are start-up companies that have recently been operating and are in the development stage. This company usually starts with ordinary capital, therefore, the owner of the company will suppress capital. One way is to use a car rental service for the company's mobility needs. This is done to avoid car maintenance costs and car taxes. In order for car rental services to be in demand, car rental service companies must balance the quality of the vehicles being rented as well as the driver services provided as well as affordable prices. In terms of vehicles, the vehicles for rent are in good condition and clean. Meanwhile, in terms of the services of the drivers being rented, the drivers must have good driving skills and have a good nature and be friendly to users of car rental services. Therefore, the effectiveness of using this car rental service must also be maintained properly so that it can be more attractive to business people who are starting to build their startup company.
Keywords: startup, vehicle, driver, effectiveness