bluuebunny/crossref_metadata_2025_split huggingface dataset:
Long-term fertilization and manuring effects on the nexus between sulphur distribution and SOC in an Inceptisol over five decades under a finger millet-maize cropping system
Authors: B Gokila , G Manimaran , D Jayanthi , K Sivakumar , G Sridevi , S Thenmozhi , M Elayarajan , A Renukadevi , R Sudha , P Balasubramanian 
Published: December 2023

Abstract

Our investigation revealed that alterations in sulphur (S) pools are predominantly governed by soil organic carbon (SOC), soil nitrogen (N), microbial biomass, and soil enzyme activities in sandy clay loam soil. We employed ten sets of nutrient management techniques, ranging from suboptimal (50% RDF) to super-optimal doses (150% RDF), including NPK + Zn, NP, N alone, S-free NPK fertilizers, NPK + FYM, and control treatments, to examine the interrelation of S with SOC characteristics. Fourier-transform infrared (FT-IR) spectroscopy was utilized to analyze the functional groups present in SOC characterization across four treatments: 100% NPK, 150% NPK, NPK + FYM, and control plots samples. Principal component analysis (PCA) was then applied to assess 29 minimal datasets, aiming to pinpoint specific soil characteristics influencing S transformation. In an Inceptisol, the application of fertilizers (100% RDF) in conjunction with 10 t ha− 1 of FYM resulted in an escalation of S pools from the surface to the subsurface stratum (OS > HSS > SO42−- S > WSS), along with an increase in soil N and SOC. FT-IR spectroscopy identified cellulose and thiocyanate functional groups in all four plots, with a pronounced presence of carbohydrate - protein polyphenol, sulfoxide (S = O), and nitrate groups specifically observed in the INM plot. The PCA findings indicated that the primary factors influencing soil quality and crop productivity (r2 of 0.69) are SOC, SMBC, SMBN, SMBS, and the enzyme activity of URE, DHA, and AS. According to the study, the combined application of fertilizer and FYM (10 t ha− 1) together exert a positive impact on sulfur transformation, SOC accumulation, and maize yield in sandy clay loam soil.
3D-DenseUNet: A New Model for BrainSegmentation in Magnetic Resonance Images
Authors: Khaled Afifa , Mubarak Ahmed , He Kun 
Published: December 2023

Abstract
Recent deep learning models have attracted substantial attention in infant brainanalysis. These models have performed state-of-the-art performance, such as semisupervised techniques (e.g., Temporal Ensembling, mean teacher). However, thesemodels depend on an encoder-decoder structure with stacked local operators togather long-range information, and the local operators limit the efficiency and effectiveness. Besides, the MRI data contain different tissue properties (T P s) suchas T1 and T2. One major limitation of these models is that they use both dataas inputs to the segment process, i.e., the models are trained on the dataset once,and it requires much computational and memory requirements during inference. In this work, we address the above limitations by designing a new deep-learningmodel, called 3D-DenseUNet, which works as adaptable global aggregation blocksin down-sampling to solve the issue of spatial information loss. The self-attentionmodule connects the down-sampling blocks to up-sampling blocks, and integrates the feature maps in three dimensions of spatial and channel, effectively improvingthe representation potential and discriminating ability of the model. Additionally,we propose a new method called Two Independent Teachers (2IT), that summarizes the model weights instead of label predictions. Each teacher model is trainedon different types of brain data, T1 and T2, respectively. Then, a fuse model isadded to improve test accuracy and enable training with fewer parameters andlabels compared to the Temporal Ensembling method without modifying the network architecture. Empirical results demonstrate the effectiveness of the proposedmethod. The code is publicly available at: https://github.com/AfifaKhaled/Two-Independent-Teachers-are-Better-Role-Model
Analysis of cytokine profiles in pediatric fulminant myocarditis and acute myocarditis multicenter study
Authors: Nomura Yoji , Suzuki Takanori , Kunida Katsuyuki , Uchida Hidetoshi , Ito Ryoichi , Oshima Yasunori , Kito Machiko , Imai Yuki , Kawai Satoru , Kozawa Kei , Saito Kazuyoshi , Hata Tadayoshi , Yoshimoto Junichiro , Yoshikawa Tetsushi , Yasuda Kazushi 
Published: December 2023

Abstract
Introduction: Acute myocarditis (AM) is an inflammatory disease of the heart muscle that can progress to fulminant myocarditis (FM), a severe and life-threatening condition. The cytokine profile of myocarditis in children, especially in relation to fulminant myocarditis, is not well understood. This study aims to evaluate the cytokine profiles of acute and fulminant myocarditis in children.
Method: Pediatric patients diagnosed with myocarditis were included in the study. Cytokine levels were measured using a multiplexed fluorescent bead-based immunoassay. Statistical analysis was performed to compare patient characteristics and cytokine levels between FM, AM, and healthy control (HC) groups. Principal component analysis (PCA) was applied to cytokine groups that were independent among the FM, AM, and HC groups.
Result: The study included twenty-two patients with FM and fourteen with AM patients. We identified 4 cytokines that were significantly higher in the FM group compared to the AM group: IL1-RA (p=0.002), IL-8 (p=0.005), IL-10 (p=0.011), and IL-15 (p=0.005). IL-4 was significantly higher in the AM group compared to FM and HC groups (p=0.006, and 0.0015). PDGF-AA, and VEGF-A were significantly lower in the FM group than in the AM group (p=0.013, and <0.001). Similar results were obtained in PCA.
Conclusion: Cytokine profiles might be used to differentiate pediatric FM from AM, stratify severity, and predict prognosis. The targeted therapy that works individual cytokines might provide a potential treatment for reducing the onset of the FM and calming the condition, and further studies are needed.
Wastewater treatment using microalgal–bacterial consortia in the photo-activated sludge process
Authors: Rada-Ariza A. , Lopez-Vazquez C. , Van der Steen N. P. , Lens P. N. L. 
Published: December 2023

Abstract
Nitrogen-rich wastewaters (10–400 mg N/L) are produced by municipal, industrial and agricultural wastes, including effluents from anaerobic treatment processes. These represent a risk to the environment due to the high nutrient concentrations (nitrogen and phosphorous), which can cause eutrophication of water bodies, deteriorating the quality of the ecosystems. As a solution, the nitrogen removal capacity of a novel bio-treatment system, the photo-activated sludge (PAS), composed of microalgae and bacteria consortia can be applied. Photobioreactors used for the simultaneous cultivation of microalgae and bacteria under sequencing batch conditions showed that microalgal–bacterial consortia can remove ammonium 50% faster than solely microalgal consortia. The increase in ammonium removal rates is due to the action of nitrifying bacteria, supplied with oxygen produced by the algae. The microalgal–bacterial system offers the possibility of reducing the hydraulic retention time, which can decrease the large area requirements often demanded by algal systems. The SRT is the main parameter to control the efficiency of the technology. The control of the suspended solids concentration, by adjusting the SRT, influences the light penetration within the reactor, which can limit or enhance the oxygen production of the algae. The photo-activated sludge system using microalgal–bacterial consortia is a sustainable treatment option for ammonium-rich wastewaters, providing clean effluents and opening reuse options for the biomass.
Processes and biorefinery approach for enhanced algal bioproduct recovery in the form of lipid and UV protectant
Authors: Chandra Rashmi , Hooshmand Masoomeh 
Published: December 2023

Abstract
This chapter discusses various methodologies for lipid extraction, including solvent extraction, enzymatic treatment, ultrasonic aided extraction, and supercritical carbon dioxide extraction, underscoring the need for further research and optimization for large-scale applications. The chapter further explores the potential symbiotic relationship between algal fuel production and waste treatment. This strategy effectively utilizes microalgae's natural ability to thrive in adverse conditions and sequester CO2 and other pollutants. This approach can simultaneously reduce the environmental footprint while generating valuable biomass for biodiesel production. Another noteworthy point the chapter brings forward is the ability of microalgae to produce valuable compounds under environmental stress, particularly UV radiation. The UV-absorbing compounds such as mycosporine-like amino acids (MAAs) and scytonemin, present substantial potential for use in the cosmetic and pharmaceutical sectors due to their potent UV absorption and photoprotective properties.
Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic
Authors: Baz Lomba Jose Antonio , Pires João , Myrmel Mette , Arnø Jorunn Karterud , Madslien Elisabeth Henie , Langlete Petter , Amato Ettore , Hyllestad Susanne 
Published: December 2023

Abstract

The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1–2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.
Integrating wastewater reuse into water management schemes of Caribbean SIDS: A Trinidad and Tobago case study
Authors: Roopnarine Ronald , Baird Kervelle , Hosein Mikella , Jackson Renee , Salim Shehnaaz , Cephas Anisha , Daley Oral , Gangapersad Samantha , Govia Sara-Jade , Cashman Adrian , Crichlow Akil , Pinongcos Federick 
Published: December 2023

Abstract

Integrating Wastewater Reuse (WWRU) into national Water Management Schemes (WMS) is crucial as Small Island Developing States (SIDS) attempt to cope with water resource constraints in a changing climate. In 2022, the Global Environment Facility Caribbean Regional Fund (GEF CReW+) on Wastewater Management, the Ministry of Public Utilities (MPU), Trinidad and Tobago and the Trinidad and Tobago Bureau of Standards (TTBS) spearheaded the development of a national voluntary standard for treated wastewater reuse focused on agricultural and landscaping uses. During the process, the MPU conducted a Knowledge, Attitudes and Practices (KAP) and Willingness to Pay (WTP) assessment to inform the standard and subsequent implementation. Results indicated `good' knowledge on wastewater and WWRU (59.3%), however attitudes and practices were considered `poor'. Inferential Statistics performed on numerically coded survey response data revealed no statistically significant relation with the demographic factors assessed; 84.1% of respondents were willing to use treated wastewater with health concerns identified as the main barrier; 27.3% of respondents were willing to pay the same price as conventional water, while 31.2% were willing to pay 25 -50% less. This assessment can inform the implementation and pricing process and provide valuable insights to increase the uptake of WWRU in the region.
Edible Oils and Development of New Products: Sensory, Microbiological, and
Cytotoxic Aspects
Authors: do Espírito Santo de Jesus Fabiane , de Jesus Freitas Tayane , Bispo Alana Moreira , de Matos Santos Lívia , Braga Alves Agnes Sophia , Aparecida Souza Machado Bruna , Ferreira Ribeiro Camila Duarte 
Published: December 2023

Abstract:
Edible oils offer several health benefits. Their inclusion in food products can improve the nutritional
profile while reducing saturated and trans fats. This research aimed to evaluate the sensory, microbiological, and
cytotoxic characteristics of edible oils and analyze how these characteristics behave when oils are added to food
products. A comprehensive search of scientific articles was conducted in the databases and virtual libraries
DOAJ, IOP Science, MDPI, Scopus, SpringerLink, Taylor & Francis Online, and Wiley Online Library, using a
time frame from 2000 to 2023. Fish oils and oil blends were widely used in these studies. The analyzed studies
demonstrated satisfactory results regarding flavor, appearance, and overall acceptance of edible oils. Low microbial
growth was also found, and no toxicity was reported in the studies. Among the 70 studies reviewed, a
substantial majority (76%) introduced edible oils into food formulations, focusing on dairy, baked, and confectionery
products. Most of the studies that applied oils in foods showed no significant difference (p > 0.05) in
attributes such as color, texture, aroma, and overall acceptance compared to products without oil addition (control).
Encapsulation techniques for oils and the incorporation of flavorings were identified as effective strategies
for seamlessly integrating edible oils into food products. Considering the importance of the characteristics of
edible oils, this study can encourage, and support researchers interested in exploring this field and developing
innovative oil-based food products.
Therapeutic Potential of Targeting Transforming Growth Factor-beta
(TGF-β) and Programmed Death-ligand 1 (PD-L1) in Pancreatic Cancer
Authors: Pourali Ghazaleh , Zafari Nima , Velayati Mahla , Mehrabadi Shima , Maftooh Mina , Hassanian Seyed Mahdi , Ghayour Mobarhan Majid , Ferns Gordon A. , Avan Amir , Khazaei Majid 
Published: December 2023

Abstract:
Pancreatic cancer (PC) is one the most lethal malignancies worldwide affecting around
half a million individuals each year. The treatment of PC is relatively difficult due to the difficulty
in making an early diagnosis. Transforming growth factor-beta (TGF-β) is a multifunctional factor
acting as both a tumor promoter in early cancer stages and a tumor suppressor in advanced disease.
Programmed death-ligand 1 (PD-L1) is a ligand of programmed death-1 (PD-1), an immune
checkpoint receptor, allowing tumor cells to avoid elimination by immune cells. Recently, targeting
the TGF-β signaling and PD-L1 pathways has emerged as a strategy for cancer therapy. In this
review, we have summarized the current knowledge regarding these pathways and their contribution
to tumor development with a focus on PC. Moreover, we have reviewed the role of TGF-β
and PD-L1 blockade in the treatment of various cancer types, including PC, and discussed the clinical
trials evaluating TGF-β and PD-L1 antagonists in PC patients.
Recent Progress and Challenges in Clinical Translation of Nanomedicines
in Diagnosis and Treatment of Lung Cancer
Authors: Yadav Bhavna , Chauhan Mahima , Singh Rahul Pratap , Sonali  , Shekhar Saurabh 
Published: December 2023

Abstract:
Lung cancer is one of the leading causes of death across the world. There are numerous
challenges in the early diagnosis and effective treatment of lung cancer, including developing multidrug
resistance. However, the diagnosis of lung cancer could be minimally invasive or non-invasive.
Nowadays, nanomedicines offer solutions to several emerging challenges in drug delivery research
areas. It has the potential to enhance the therapeutic efficacy of biologically and chemically
active agents at the site of action. This approach can also be employed in molecular and cellular
imaging, precise and early detection, screening, and targeting drugs for lung cancer treatment. A
proper understanding of the disease and timely diagnosis using strategically designed effective
nanocarriers can be a promising approach to effectively managing cancer. The present review explores
issues related to lung cancer chemotherapy and the promises and hurdles of newer approaches
like nanomedicine. The article also summarizes the preclinical studies on diagnosis and
treatment, pitfalls, and challenges in the clinical translation of nanomedicines for lung cancer therapy.
Development and Validation of an Analytical RP-HPLC Method for Simultaneous Estimation of Losartan and its Active Metabolite (EXP-3174) in Isolated Perfused Rat Liver
Authors: Toolabi Mahsa , Ramezankhani Reyhaneh , Rahbar Nadereh , Dibaei Maryam , Foroumadi Alireza , Lavasani Hoda , Kazemi Vida , Rouini Mohammadreza 
Published: December 2023

Background:
The liver perfusion method is frequently used in drug pharmacokinetic
studies and the various effects of drugs on liver tissue. The aim of this study was to establish and
validate an analytical method using high-performance liquid chromatography to determine the simultaneous
concentration of losartan and its active metabolite, EXP-3174, in an isolated perfused rat
liver study.

Method:
An HPLC system with isocratic mode was used. Various chromatographic parameters
were adjusted to develop and validate a method for determination of losartan and its active metabolite
in liver perfusion media.

Results:
In this study, losartan and its active metabolite, EXP-3174, were separated using a C18 stationary
phase, a mobile phase consisting of acetonitrile: phosphate buffer at a flow rate of
1 mL.min-1, and UV detection at 254 nm. Retention times for losartan and the metabolite were 10
and 16 minutes, respectively. Linearity from 25-250 ng.ml-1 was validated with acceptable accuracy
and precision. The LOD and LOQ for losartan were 7.0 and 21.1 ng.ml-1, respectively. The LOD
and LOQ for metabolite were 7.4 and 22.4 ng.ml-1, respectively. ChromGate® software was used to
acquire and process the data.

Conclusions:
The optimized and validated technique was effectively used to analyze losartan and
its active metabolite in isolated perfused rat liver.
The Role of Polar Optical Modes in Wide Bandgap Semiconductor Quantum Structures
Authors: Stavrou V.N. , Tsoulos I.G. , Mastorakis N.E. 
Published: December 2023

:
In this paper, the interface polariton (IP), the confined (CF) modes in nanostructures
made with wide bandgap semiconductors, as well as their contributions to the carrier scattering
mechanism have been investigated. An asymmetric quantum well (AQW) made with
ZnSe/CdSe/ZnS has been studied. More specifically, the dielectric continuum (DC) model has
been employed to describe both the IP and the CF modes. Additionally, the Fermi golden rule
has been used to estimate the electron transition rate within the asymmetric structure. Our numerical results show that the scattering rate for an electron which is localized at the bottom of
the first subband above the well and drops within the quantum well, is characterized by regular
peaks with an almost linear increase as the size of the QW increases. The emerge peaks are related to two different physical characteristics of the AQW system. These peaks are related to
electron resonances and the threshold phonon emission (both CF and IP) called phonon resonances. The scattering rate of an electron which is localized at the bottom of the second subband
above the well and makes transitions to all possible states within the quantum well gives only
rise to phonon resonances. The research highlights the importance of the CF and IP modes on
transition rates and their dependence on both the size of the quantum well and the asymmetry of
the barrier materials.

:
PACS: 68.65.Fg, 74.25.Kc, 63.22.−m, 63.22.+m
Optimized Hybrid Deep Learning for Real-Time Pandemic Data Forecasting: Long and Short-Term Perspectives
Authors: Dash Sujata , Giri Sourav Kumar , Pani Subhendu Kumar , Mallik Saurav , Wang Mingqiang , Qin Hong 
Published: December 2023

Background:
With new variants of COVID-19 causing challenges, we need to focus on
integrating multiple deep-learning frameworks to develop intelligent healthcare systems for early detection
and diagnosis.

Objective:
This article suggests three hybrid deep learning models, namely CNN-LSTM, CNN-Bi-
LSTM, and CNN-GRU, to address the pressing need for an intelligent healthcare system. These
models are designed to capture spatial and temporal patterns in COVID-19 data, thereby improving
the accuracy and timeliness of predictions. An output forecasting framework integrates these models,
and an optimization algorithm automatically selects the hyperparameters for the 13 baselines and the
three proposed hybrid models.

Methods:
Real-time time series data from the five most affected countries were used to test the effectiveness
of the proposed models. Baseline models were compared, and optimization algorithms were
employed to improve forecasting capabilities.

Results:
CNN-GRU and CNN-LSTM are the top short- and long-term forecasting models. CNNGRU
had the best performance with the lowest SMAPE and MAPE values for long-term forecasting
in India at 3.07% and 3.17%, respectively, and impressive results for short-term forecasting with
SMAPE and MAPE values of 1.46% and 1.47%.

Conclusion:
Hybrid deep learning models, like CNN-GRU, can aid in early COVID-19 assessment
and diagnosis. They detect patterns in data for effective governmental strategies and forecasting. This
helps manage and mitigate the pandemic faster and more accurately.
Recent Patents on Block Particle Collision Performance Test Bench
Authors: Sun Bowen , Xing Bangsheng , Yang Daolong 
Published: December 2023

Background:
China is rich in mineral resources with a complete range of types. Currently,
163 kinds of minerals have been found, and 149 kinds of minerals with Proven reserves,
including 7 kinds of energy minerals, 54 kinds of metal minerals, and 86 kinds of non-metallic
minerals. Ore particles can undergo various collisions during mining and transportation.

Objective:
Because particle collision behavior can greatly affect particle size and particle properties
during the final application, it can also lead to the generation of a large amount of dust during
processing and transportation, seriously affecting environmental quality. Therefore, exploring the
collision performance of particle collisions is very important.

Method:
This test bench can compensate for the shortcomings of existing particle collision measurement
technologies, by measuring the motion trajectory after collision between particles, as well
as the collision force between particles and metal plates, as well as the motion trajectory after collision.

Results:
The test bench has the advantages of a simple structure, a small footprint, diverse functions,
and stable operation.

Conclusion:
This test bench can be used for measuring the collision force and post-collision motion
trajectory of block particles and has broad practicality and strong innovation.