bluuebunny/crossref_metadata_2025_split huggingface dataset:
Examination of genetic clones of Myrtus communis as potential sources of organic agricultural pest control agents
Authors: Quinn Elazar , Ben-Simchon Eyal , Gorelick Jonathan , Oka Yuji , Frenkel Omer , Sionov Edward , Kostyukovsky Moshe , Dudai Nativ , Shimshoni Jakob , Zilkah Shmuel , Cohen Menashe , Rapaport Aviv , Shelef Oren 
Published: August 2023

Abstract
Myrtus communis is a Mediterranean shrub cultivated in Israel for traditional, ceremonial use only, with more than 98% of the crop biomass, equivalent to 26–27 tons per ha per annum, considered agricultural waste. Therefore, potentially profitable use for this excess is being highly sought. As Myrtus is also known for its unique terpene and terpenoid content, this work evaluated the impact of essential oil (EO) extracted from several M. communis cultivars on storage insects, nematodes, fungi, and pathogens. In addition, the allelopathic effect of M. communis litter on the germination success of wheat seeds was evaluated. The EO extracts demonstrated an insecticidal effect on several storage insects in fumigation experiments, and a potentially inhibiting effect on wheat development in allelopathy experiments. No significant impact of M. communis EOs on the examined fungi, pathogens, and nematodes was recorded. Additional uses of the M. communis biomass suggest supplying additional income to the farmer through the circular agriculture approach. In addition, the use of this local crop can contribute to sustainable intensification by increasing farming efficiency, nature-based substitutes for chemical pesticides, and possibly the future design of agriculture through the integration of Myrtus in monoculture crops.
The Role of Micromobility in Mobility as a Service in Future Cities
Authors: Saryazdi Ali Haji Gholam , Faraji Seyed J. , Gharamaleki A.Y. Faramarz , Arman Mohadese 
Published: August 2023

Abstract
With urbanization expansion, transportation, and traffic and pollution in cities have increased, which has necessitated the need for a more sustainable urban transportation system. Micro-mobility programs have been proposed worldwide. Despite various previous literature, a comprehensive conceptualization has not been accomplished. Therefore, with a qualitative Meta-Synthesis; we re-introduce and define this style of transportation and answer questions about the criteria for determining micro-mobility, types of micro-mobility, its applications in cities, and its advantages and disadvantages, its main role in urban transportation in future cities and the current market, and its future forecast. The results showed that there is no specific and comprehensive definition to explain micro-mobility and its determining indicators are different and their value is changing according to technological changes. micro-mobility plays a unique role in future cities under the livable city concept with a predicted exponential usage growth, as it has a complementary role to public transportation.
Enhancing the conventional culture: The evaluation of several culture media and growth conditions improve the isolation of ruminal bacteria
Authors: Botero-Rute Lina Marcela , Caro-Quintero Alejandro , Acosta-González Alejandro 
Published: August 2023

Abstract

The rumen microbiota is crucial in cattle digestion, but its low cultivability makes it difficult to study its ecological function and biotechnological potential. To improve the recovery of ruminal microorganisms, this study combined the evaluation of several cultivation parameters with metabarcoding analysis. The parameters tested were culture media (CAN, ER, GC, GOOD, KNT, KYO, NYO, TRB), rumen fluid dilution (10-2, 10-6, and 10-12), and incubation time (3 and 7 days). The bacterial populations were determined through Illumina sequencing of 16S rRNA from three biological replicates of each treatment. Results showed that the culture media did not recover all rumen populations and altered the dominant phyla's relative abundance. In the rumen, Bacteroidetes and Firmicutes had a relative abundance of 75 % and 15 %, respectively, but in the culture media, it was 15 % and 60 %. The PCoA analysis showed that dilution had a significant impact on population composition, with 10-2and 10-6populations clustering together while 10-12populations were more distant. Incubation time had no impact on populations diversity. After comparing PCoA distances, two media (CAN, KNT) were selected based on their ability to recover similar populations to the rumen. 64 cultures were obtained and 54 were identified through 16s rRNA gene sequencing. The metataxonomic analysis showed that CAN media had reproducibility over time, while KNT showed enrichment of different taxa due to the use of rumen fluid as a substrate.
Developing Questions to Assess and Measure Patients’ Perceived Survival Benefit from Adjuvant Endocrine Therapy in Breast Cancer: A Mixed Methods Pilot Study
Authors: Tawfik Bernard , Jacobson Kendal , Brown-Glaberman Ursa , Kosich Mikaela , Horn M. Lee , Nemunaitis Jacklyn , Dayao Zoneddy , Pankratz V. Shane , Sussman Andrew L. , Guest Dolores 
Published: August 2023

Abstract
Purpose
This mixed methods study developed multiple question types to understand and measure women’s perceived benefit from adjuvant endocrine therapy. We hypothesis that patients do not understand this benefit and sought to develop the questions needed to test this hypothesis and obtain initial patient estimates.
Methods
From 8/2022 to 3/2023, qualitative interviews focused on assessing and modifying 9 initial varied question types asking about the overall survival (OS) benefit from adjuvant endocrine therapy. Subsequent focus groups modified and selected the optimal questions. Patients’ self-assessment of their OS benefit was compared to their individualized PREDICT model results.
Results
Fifty-three patients completed the survey; 42% Hispanic, 30% rural, and 47% with income <$39,999 per year. Patients reported adequate health care literacy (61.5%) and average confidence about treatment and medication decisions 49.4 (95% CI 24.4–59.5). From the original 9 questions, 3 modified questions were ultimately found to capture patients’ perception of this OS benefit, focusing on graphical and prose styles. Patients estimated an OS benefit of 42% compared to 4.4% calculated from the PREDICT model (p < 0.001).
Conclusion
In this group with considerable representation from ethnic minority, rural and low-income patients, qualitative data showed that more than one modality of question type was needed to clearly capture patients’ understanding of treatment benefit. Women with breast cancer significantly overestimated their 10-year OS benefit from adjuvant endocrine therapy compared to the PREDICT model.
Novel oxadiazole functionalized pyridopyrimidine derivatives; their anticancer activity and Molecular docking studies
Authors: Dasari Raghu , Gali Srinivas , korra Rajashekar , Vaddiraju Namrata 
Published: August 2023

Abstract

A series of novel oxadiazole functionalized pyridopyrimidine derivatives prepared starting from 6-methyl/ethyl-2-oxo-4-(trifluoromethyl)-1,2-dihydropyridine-3-carbonitrile 1. These compound 1 on reaction with sulphuric acid and obtained compound 2, further compound 2 on reaction with chloroacetamide followed by reaction with EMME coupling and further cyclization to obtain compound 5. Compound 5 on reaction with hydrazide hydrate and obtained hydrazide derivatives 6. Compound 6 on reaction with diverse substituted aromatic acids to get oxadiazole derivatives 7a-l. All the final compounds 7a-l evaluated for anti cancer activity against four human cancer cell lines such as HeLa - Cervical cancer (CCL-2); COLO 205- Colon cancer (CCL-222); HepG2- Liver cancer (HB-8065); MCF7 - Breast cancer (HTB-22) and promising compounds 7d and 7k have been identified and evaluated for molecular docking interactions.
The Global Stability Of Fractional Epidemiological Model With n Strain "AllCoronavirus Mutations"
Authors: Ahmed KAJOUNI , KHADIJA CHANNAN , hilal khalid 
Published: August 2023

Abstract
In this work, we have constructed a new system of differential equations which mathematically models infectious diseases with several mutations. (such as covid 19 disease and their mutations). Therefore, we are interested in studying the asymptotic stability of our new system.
Domain of Attraction of the Time to Extinction For a Class of Subcritical Bisexual Galton-Watson Branching Processes
Authors: Martín-González Ehyter Matías , Galván-Galván Carlos , Calvo-Martínez Eduardo 
Published: August 2023

Abstract
We show that the time to extinction of a subcritical Bisexual Galton-Watson Branching Process (BGWBP for short) with mating function depending on the previous generation, is the discretization of a random variable whose distribution function belongs to the Gumbel maximal domain of attraction. This implies that the distribution of the aforementioned time to extinction can be well approximated using classical Extreme Value Theory, for instance, the Peaks Over Threshold method. We provide several numerical examples of this approximation.
Optimizing Left Ventricular Assist Device Therapy: A Machine Learning Approach for Predicting Cardiac Output
Authors: Belkacem Marwen , Jemili Farah , Ellouze Omar , Kissi Asma El , Kamel Ferid 
Published: August 2023

Abstract
Heart failure (HF) is a significant concern worldwide, with left ventricular assist devices (LVADs) providing effective mechanical circulatory support for end-stage HF patients. However, the static nature of current LVAD pumping rates poses challenges in adapting to patients' physiological needs. To address this limitation, we propose a novel approach utilizing Multi-Layer Perceptron (MLPRegressor), a machine learning algorithm, to predict cardiac output (CO) accurately and adaptively adjust LVAD speed based on non-invasive physiological data. Our approach includes data preprocessing, feature engineering, and model evaluation. Our study demonstrates the superior performance of MLPRegressor over other machine learning models, with a Root mean squared error (RMSE) of 0.652 L/min and an R-squared score of 0.786. Personalized LVAD treatment based on predicted CO has the potential to improve patient outcomes and reduce complications associated with static pumping rates. Future research should explore additional physiological parameters, validation on larger datasets, and real-time monitoring for dynamic LVAD control in clinical settings. The integration of ML in cardiac care holds promise for enhancing heart failure management and patient care.
Dynamic multilayer functional connectivity detects preclinical and clinical Alzheimer’s disease
Authors: Canal-Garcia Anna , Veréb Dániel , Mijalkov Mite , Westman Eric , Volpe Giovanni , Pereira Joana B. 
Published: August 2023

Abstract

Background Increasing evidence suggests that patients with Alzheimer's disease (AD) present alterations in functional connectivity but previous results have not always been consistent. One of the reasons that may account for this inconsistency is the lack of consideration of temporal dynamics. To address this limitation, here we studied the dynamic modular organization on resting-state functional MRI (rs-fMRI) across different stages of AD using a novel multilayer brain network approach. Methods Participants from preclinical and clinical AD stages were included. Temporal multilayer networks were used to assess time-varying modular organization. Logistic regression models were employed for disease stage discrimination, and partial least squares analyses examined associations between dynamic measures with cognition and pathology. Results Temporal multilayer functional measures distinguished all groups, particularly preclinical stages, overcoming the discriminatory power of risk factors such as age, sex, and APOE 𝜀4 carriership. Dynamic functional measures exhibited strong associations with cognition as well as amyloid and tau pathology. Conclusions Dynamic multilayer functional connectivity shows promise as a functional imaging biomarker for both early and late stage AD diagnosis.
Laparoscopic-assisted Altemeier surgery for total rectal prolapse: a case report
Authors: Chen Shiwei , Chen Xiangwen , Yang Tao , Cao Qiurui , Gan Guolian 
Published: August 2023

Abstract
Background Surgery is the predominant method of treating total rectal prolapse. The transabdominal approach has the advantage of reducing recurrence rates compared to the transperineal approach. However, the former is complicated and is mostly applied to patients with prolapse accompanied by constipation. Therefore, Laparoscopic-assisted Altemeier surgery might be a novel option for patient with total rectal prolapse.Case report A 40-year-old man who repeatedly suffered rectal prolapse after defecation for 3 years, was diagnosed with total rectal prolapse based on physical examination and MRI, and the prolapse was about 10 cm. We performed laparoscopic-assisted Altemeier surgery. Postoperatively, the patient achieved an excellent recovery and was out on day 7.Conclusion This procedure ensures that the prolapsed bowel is completely removed and the pelvic floor elevation is assessed, which reduces the chances of recurrence. In addition, the risks, invasiveness and longer duration of more complex laparoscopic procedures are avoided.
Application of Artificial Intelligence in Poultry Farming - Advancing Efficiency in Poultry Farming By Automating The Egg Counting Using Computer Vision System
Authors: Vinod Anoopa , Mohanty Deba Chandan , John Aishwarya , Depuru Bharani Kumar 
Published: August 2023

Abstract
Counting eggs may seem like a simple task, but for poultry farms, it is a vital process that directly impacts productivity, inventory control, and overall output quality. However, the conventional manual counting methods are laborious, time-consuming, and prone to human errors. This research presents a ground-breaking computer imaging system designed to automate egg detection and counting, utilizing the remarkable potential of Computer Vision and Artificial Intelligence (AI) techniques.
The primary objective is to develop a robust and reliable system capable of real-time identification and enumeration of eggs within poultry houses. Strategically positioned cameras capture images, providing a unique perspective into the poultry environment. State-of-the-art computer vision algorithms, including advanced object detection methods like Faster Regions with Convolutional Neural Networks (Faster R-CNN) or You Only Look Once (YOLO), accurately identify eggs within the images using cutting-edge deep learning models.
By integrating AI techniques, the system enhances accuracy and reliability, while continuously learning from vast amounts of data. This transformative automation eliminates labour-intensive manual counting, offering a dependable, efficient, and cost-effective solution while reducing both time and labour requirements and minimizing human errors.
Moreover, the automated system enables real-time data collection, facilitating data-driven decision-making in the poultry industry. Through the integration of cutting-edge computer vision algorithms and AI techniques, the system provides an accurate, efficient, and reliable solution to optimize production processes, enhance inventory control, and ensure high-quality outputs. This work contributes to the ongoing technological advancements in the poultry industry, ultimately improving productivity, and sustainability, and enabling data-driven decision-making.
The Sexual and Reproductive Health Covariates of Early Menarche Among Adolescent Girls
Authors: Ibitoye Mobolaji , Sandfort Theo G. M. , Bingenheimer Jeffrey B. , Sommer Marni 
Published: August 2023

Abstract

Introduction
Research suggests that girls who reach menarche at an early age are at greater risk for negative sexual and reproductive health (SRH) outcomes than their later-maturing counterparts, but very little research has examined this issue in sub-Saharan Africa, especially in West Africa. The goal of the current study was to determine whether early menarche was associated with any SRH outcomes in a sample of Ghanaian girls.
Methods
The study data were drawn from the baseline assessment of a longitudinal study involving two age cohorts (13–14 and 18–19 years) of 700 adolescent girls from Ghana. Logistic regressions were used to assess the association between early menarche (before age 13) and seven SRH outcomes (adolescent sexual activity, early sexual initiation, inconsistent condom use, transactional sex, sexual violence, multiple sexual partners and adolescent pregnancy).
Results
Early menarche was significantly associated with adolescent sexual activity (odds ratio [OR] = 6.4; 95% confidence interval [CI] 2.1–19.7), and sexual violence (OR = 3.2; 95% CI 1.6–6.2) in the younger cohort and early sexual initiation (OR = 3.2; 95% CI 1.19–8.61) and multiple sexual partners (OR = 3.7; 95% CI 1.39–9.87) in the older cohort. Early menarche was also associated with transactional sex and teen pregnancy in the full sample.
Conclusions
These findings suggest the need for special attention to the needs of early-maturing girls in SRH programming. Interventions are needed to delay adolescent sexual activity in girls with early menarche. Efforts to prevent sexual violence among adolescent girls in Ghana may benefit from targeting and addressing the specific needs of early-maturing girls.
Superradiant and subradiant states in lifetime-limited organic molecules through laser-induced tuning
Authors: Lange Christian , Hood Jonathan , Daggett Emma , Walther Valentin , Huang Libai 
Published: August 2023

Abstract
An array of radiatively coupled emitters is an exciting new platform for generating, storing, and manipulating quantum light. However, the simultaneous positioning and tuning of multiple lifetime-limited emitters into resonance remains a significant challenge. Here we report the creation of superradiant and subradiant entangled states in pairs of lifetime-limited and sub-wavelength spaced organic molecules by permanently shifting them into resonance with laser-induced tuning. The molecules are embedded as defects in an organic nanocrystal. The pump light redistributes charges in the nanocrystal and dramatically increases the likelihood of resonant molecules. The frequency spectra, lifetimes, and second-order correlation agree with a simple quantum model. This scalable tuning approach with organic molecules provides a pathway for observing collective quantum phenomena in sub-wavelength arrays of quantum emitters.
Macroscopic Length Scale of Water Super-Transport in Single Ultralong Carbon Nanotube
Authors: Sun Silei , Shen Boyuan , Gao Jun , Zhu Zhenxing , Wei Fei 
Published: August 2023

Abstract
The emergent nanofluidics promotes the exploration of the special hydrodynamics of fluid transport in a nano-sized flow domain1–3. Water, the most common fluid in the nature and human society, will form the ordered structures4–7 by reducing the hydrogen bonding and transport ultra-fast in carbon nanotubes8–16. However, such behaviors have only been reported in the tubes with nano- or micro-meter lengths far away from what can be considered as the macroscopic scales. Here we establish a mass spectroscopy system to detect the super-transport of water and heavy water in individual ultralong carbon nanotubes with an enhancement ratio ε over 106, two orders of magnitude higher than previous results. It indicates that the physics behind water super-transport is still efficient in a macroscopic length scale, where the effects of entrance/exit losses, surface energies, and temperature on the water super-transport can also be evaluated. Such a long transport system will reduce the contribution of entrance/exit effect to the total pressure drop to approach the intrinsic slippage resistance. This work not only extends the super-transport property of nanofluidics into macroscopic length scale, but also provide new hope to detect the intrinsic ultra-low friction on solid-liquid interface for a lossless mass transport in macroscopic applications.
Stochastic Optimal Harmonic Suppression with Permissible Photovoltaic Penetration Level for Grid-Linked Systems using Monte Carlo-Based Hybrid NSGA2-MOPSO
Authors: Abubakar Ali , Borkor Reindorf Nartey , Amoako-Yirenkyi Peter 
Published: August 2023

Abstract
Integrating a high Penetration level of Solar Photovoltaic (SPV) power in the electricity grid could enhance the system’s sustainability, reliability, and affordability. Nevertheless, at higher Penetrations, the intermittency, non-dispatchable nature of the SPV generation, and the extensive utilization of inverter-based interfaces generate excessive harmonic distortions that damage power system devices and interrupt the smooth operation of the power system. Thus, the severity of the harmonic distortion impacts varies as a function of the degree of the SPV Penetration level in the grid-connected system. Though the problem is highly nonlinear stochastic programming with multiple conflicting power quality criteria, no existing study holistically captures the randomness, the contradictory nature of the objectives, and the grid’s technical limitations simultaneously. This study proposes a novel Monte-Carlo-based Hybrid multi-objective methodology to scale up the Photovoltaic Penetration level with a minimum Total Harmonic Distortion (THD) for multilevel SPV inverters in grid-connected systems without violating the system’s standard operational limitations. Six state-of-the-art Multi-Objective Evolutionary algorithms were implemented and compared using hypervolume indica- tor, execution time, and parametric statistical analysis to obtain a quality solution. The results showed that the Hybrid NSGAII-MOPSO outflanked the rest in terms of convergence, diversity, and execution time. It could be inferred that even under variable weather conditions, this harmonic suppression design approach could accurately optimize the SPV Penetration level and mitigate the THD without degrading the grid’s standard operational constraints. In comparison, the stochastic design technique creates a far more reliable SPV grid-connected system than the deterministic approach.
Mitigating Imported Fuel Dependency in Agricultural Production: Case study of an island nation's vulnerability to global catastrophic risks
Authors: Boyd Matt , Ragnarsson Sam , Terry Simon , Payne Ben , Wilson Nick 
Published: August 2023

Abstract
A major global catastrophe could disrupt trade in liquid fuels. Countries dependent on imported oil products might struggle to sustain industrial agriculture. Island nations importing 100% of refined fuels are particularly vulnerable. Our case study of New Zealand aimed to estimate the agricultural land area and biofuel volumes needed to feed the national population in the absence of trade. Results showed that stored diesel would quickly be exhausted with ordinary use (weeks), and even with strict rationing (months). To preserve fuel, we found that farming wheat (requiring as little as 5.3 million liters (L) of diesel per annum), was more fuel-efficient than potatoes (11.7) or dairy (38.7), to feed the national population under a climate-as-usual scenario. The wheat would require 24% of currently grain-cropped land. Under climate conditions adverse to agriculture in a worst case (severe nuclear winter) scenario, fuel requirements increased for wheat, potatoes, and dairy milk, to as much as 14.3, 34.5 and 107.6 million L per annum respectively. If growing wheat, then canola crop as feedstock for the required biofuel would occupy 1–3% of all currently grain-farmed land. Investment in canola biodiesel or renewable diesel refineries could ensure supply for the bare minimum agricultural liquid fuel needs. Expansion in refining and canola cropping before a catastrophe as a resilience measure might be encouraged through market mechanisms, direct government investment, or a combination of these. Logistics of scale-up post-catastrophe should also be analyzed. Biodiesel produced would help the nation meet its emissions reduction targets in normal times.