bluuebunny/crossref_metadata_2025_split huggingface dataset:
Matrix Approach to Accelerate Spin‐Up of CLM5
Authors: Liao Cuijuan , Lu Xingjie , Huang Yuanyuan , Tao Feng , Lawrence David M. , Koven Charles D. , Oleson Keith W. , Wieder William R. , Kluzek Erik , Huang Xiaomeng , Luo Yiqi 
Published: August 2023

AbstractNumerical models have been developed to investigate and understand responses of biogeochemical cycle to global changes. Steady state, when a system is in dynamic equilibrium, is generally required to initialize these model simulations. However, the spin‐up process that is used to achieve steady state pose a great burden to computational resources, limiting the efficiency of global modeling analysis on biogeochemical cycles. This study introduces a new Semi‐Analytical Spin‐Up (SASU) to tackle this grand challenge. We applied SASU to Community Land Model version 5 and examined its computational efficiency and accuracy. At the Brazil site, SASU is computationally 7 times more efficient than (or saved up to 86% computational cost in comparison with) the traditional native dynamics (ND) spin‐up to reach the same steady state. Globally, SASU is computationally 8 times more efficient than the accelerated decomposition spin‐up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin‐up on site and globally in comparison with other spin‐up methods. It is generalizable to wide biogeochemical models and thus makes computationally costly studies (e.g., parameter perturbation ensemble analysis and data assimilation) possible for a better understanding of biogeochemical cycle under climate change.
Collective magnetic Higgs excitation in a pyrochlore ruthenate
Authors: Wulferding Dirk , Kim Junkyoung , Kim Mi Kyung , Yang Yang , Lee Jae Hyuck , Song Dongjoon , Oh Dongjin , Kim Heung-Sik , Chern Li Ern , Kim Yong Baek , Noh Minji , Choi Hyunyong , Choi Sungkyun , Perkins Natalia B. , Kim Changyoung , Park Seung Ryong 
Published: August 2023

AbstractThe emergence of scalar Higgs-type amplitude modes in systems where symmetry is spontaneously broken has been a highly successful, paradigmatic description of phase transitions, with implications ranging from high-energy particle physics to low-energy condensed matter systems. Here, we uncover two successive high temperature phase transitions in the pyrochlore magnet Nd2Ru2O7 at TN = 147 K and T* = 97 K, that lead to giant phonon instabilities and culminate in the emergence of a highly coherent excitation. This coherent excitation, distinct from other phonons and from conventional magnetic modes, stabilizes at a low energy of 3 meV. We assign it to a collective Higgs-type amplitude mode, that involves bond energy modulations of the Ru4 tetrahedra. Its striking two-fold symmetry, incompatible with the underlying crystal structure, highlights the possibility of multiple entangled broken symmetries.
A model framework to communicate the risks associated with aflatoxins
Authors: Bhardwaj Kiran , Meneely Julie P. , Haughey Simon A. , Dean Moira , Wall Patrick , Petchkongkaew Awanwee , Baker Bob , Zhang Guangtao , Elliott Christopher T. 
Published: August 2023

AbstractRisk communication is defined as the interactive exchange of information and opinions concerning risk, risk-related factors and risk perceptions amongst all the stakeholders of food safety throughout the risk analysis process. The interactive exchange of information occurs at three different levels i.e. informed level, dialogue level and engagement level. For an effective food safety risk communication (FSRC), it is important that the information should adhere to the core principles of risk communication which are transparency, openness, responsiveness and timeliness. Communication of a food safety risk within all the components of risk communication strategy constitutes a complex network of information flow that can be better understood with the help of a framework. Therefore, a model framework to communicate the risks associated with aflatoxins (AFs) dietary intake has been developed with the aim of (a) creating general awareness amongst public and (b) involving industry stakeholders in the prevention and control of risk. The framework has been motivated by the learnings and best practices outlined in the identified technical guidance documents for risk communication. Risk assessors, risk managers, industry stakeholders and general public have been identified as the major stakeholders for the present framework. Amongst them, industry stakeholders and general public has been selected as the major target audience for risk managers. Moreover, population residing in low- and middle-income countries (LMIC) has been identified as the main target group to reach.
How level of understanding and type of used sources relate to adherence to COVID-19 public health measures in Canada
Authors: Courdi Clémentine , Ramazan Ali Sahar , Pelletier-Dumas Mathieu , Stolle Dietlind , Dorfman Anna , Lina Jean-Marc , Lacourse Éric , de la Sablonnière Roxane 
Published: August 2023

AbstractPrevious studies have highlighted the importance of promoting health literacy and minimizing misinformation to encourage higher adherence to key public health measures during the COVID-19 pandemic. This study explores how one’s self-reported understanding of information and types of sources used to get information regarding COVID-19 can hinder adherence to public health measures implemented by the Canadian government. Data was collected following a longitudinal design of 11 time points for April 2020 to April 2021. The sub-sample used for this study included 2659 Canadians who completed the survey for at least four time points. Using Latent Class Growth Analysis, we modelled typical trajectories of adherence to three key public health measures: staying home, social distancing and mask wearing. Overall, a lower level of understanding was associated with lower adherence trajectories to public health measures, and vice-versa. Adjusted odds ratio (AOR) showed that the higher the level of understanding, the higher were the chances of following a high adherence trajectory. The type of used sources also showed a significant statistical association with adherence trajectories for social distancing and staying home (AOR: between 1.1 and 3.4). These results are discussed considering future policy implications.
Degradation and energy performance evaluation of mono-crystalline photovoltaic modules in Egypt
Authors: Atia Doaa M. , Hassan Amal A. , El-Madany Hanaa T. , Eliwa Aref Y. , Zahran Mohamed B. 
Published: August 2023

AbstractDegradation reduces the capability of solar photovoltaic (PV) production over time. Studies on PV module degradation are typically based on time-consuming and labor-intensive accelerated or field experiments. Understanding the modes and methodologies of degradation is critical to certifying PV module lifetimes of 25 years. Both technological and environmental conditions affect the PV module degradation rate. This paper investigates the degradation of 24 mono-crystalline silicon PV modules mounted on the rooftop of Egypt's electronics research institute (ERI) after 25 years of outdoor operation. Degradation rates were determined using the module's performance ratio, temperature losses, and energy yield. Visual inspection, I–V characteristic measurement, and degradation rate have all been calculated as part of the PV evaluation process. The results demonstrate that the modules' maximum power ($${P}_{max}$$

P

max

) has decreased in an average manner by 23.3% over time. The degradation rates of short-circuit current ($${I}_{sc}$$

I

sc

) and maximum current ($${I}_{m}$$

I
m

) are 12.16% and 7.2%, respectively. The open-circuit voltage ($${V}_{oc}$$

V

oc

), maximum voltage ($${V}_{m}$$

V
m

), and fill factor ($$FF$$

FF

) degradation rates are 2.28%, 12.16%, and 15.3%, respectively. The overall performance ratio obtained for the PV system is 85.9%. After a long time of operation in outdoor conditions, the single diode model's five parameters are used for parameter identification of each module to study the effect of aging on PV module performance.
Comparisons of the prediction models for undiagnosed diabetes between machine learning versus traditional statistical methods
Authors: Choi Seong Gyu , Oh Minsuk , Park Dong–Hyuk , Lee Byeongchan , Lee Yong-ho , Jee Sun Ha , Jeon Justin Y. 
Published: August 2023

AbstractWe compared the prediction performance of machine learning-based undiagnosed diabetes prediction models with that of traditional statistics-based prediction models. We used the 2014–2020 Korean National Health and Nutrition Examination Survey (KNHANES) (N = 32,827). The KNHANES 2014–2018 data were used as training and internal validation sets and the 2019–2020 data as external validation sets. The receiver operating characteristic curve area under the curve (AUC) was used to compare the prediction performance of the machine learning-based and the traditional statistics-based prediction models. Using sex, age, resting heart rate, and waist circumference as features, the machine learning-based model showed a higher AUC (0.788 vs. 0.740) than that of the traditional statistical-based prediction model. Using sex, age, waist circumference, family history of diabetes, hypertension, alcohol consumption, and smoking status as features, the machine learning-based prediction model showed a higher AUC (0.802 vs. 0.759) than the traditional statistical-based prediction model. The machine learning-based prediction model using features for maximum prediction performance showed a higher AUC (0.819 vs. 0.765) than the traditional statistical-based prediction model. Machine learning-based prediction models using anthropometric and lifestyle measurements may outperform the traditional statistics-based prediction models in predicting undiagnosed diabetes.
Characterizing the circadian connectome of Ocimum tenuiflorum using an integrated network theoretic framework
Authors: Singh Vikram , Singh Vikram 
Published: August 2023

AbstractAcross the three domains of life, circadian clock is known to regulate vital physiological processes, like, growth, development, defence etc. by anticipating environmental cues. In this work, we report an integrated network theoretic methodology comprising of random walk with restart and graphlet degree vectors to characterize genome wide core circadian clock and clock associated raw candidate proteins in a plant for which protein interaction information is available. As a case study, we have implemented this framework in Ocimum tenuiflorum (Tulsi); one of the most valuable medicinal plants that has been utilized since ancient times in the management of a large number of diseases. For that, 24 core clock (CC) proteins were mined in 56 template plant genomes to build their hidden Markov models (HMMs). These HMMs were then used to identify 24 core clock proteins in O. tenuiflorum. The local topology of the interologous Tulsi protein interaction network was explored to predict the CC associated raw candidate proteins. Statistical and biological significance of the raw candidates was determined using permutation and enrichment tests. A total of 66 putative CC associated proteins were identified and their functional annotation was performed.
A cluster-based trusted routing method using fire hawk optimizer (FHO) in wireless sensor networks (WSNs)
Authors: Hosseinzadeh Mehdi , Yoo Joon , Ali Saqib , Lansky Jan , Mildeova Stanislava , Yousefpoor Mohammad Sadegh , Ahmed Omed Hassan , Rahmani Amir Masoud , Tightiz Lilia 
Published: August 2023

AbstractToday, wireless sensor networks (WSNs) are growing rapidly and provide a lot of comfort to human life. Due to the use of WSNs in various areas, like health care and battlefield, security is an important concern in the data transfer procedure to prevent data manipulation. Trust management is an affective scheme to solve these problems by building trust relationships between sensor nodes. In this paper, a cluster-based trusted routing technique using fire hawk optimizer called CTRF is presented to improve network security by considering the limited energy of nodes in WSNs. It includes a weighted trust mechanism (WTM) designed based on interactive behavior between sensor nodes. The main feature of this trust mechanism is to consider the exponential coefficients for the trust parameters, namely weighted reception rate, weighted redundancy rate, and energy state so that the trust level of sensor nodes is exponentially reduced or increased based on their hostile or friendly behaviors. Moreover, the proposed approach creates a fire hawk optimizer-based clustering mechanism to select cluster heads from a candidate set, which includes sensor nodes whose remaining energy and trust levels are greater than the average remaining energy and the average trust level of all network nodes, respectively. In this clustering method, a new cost function is proposed based on four objectives, including cluster head location, cluster head energy, distance from the cluster head to the base station, and cluster size. Finally, CTRF decides on inter-cluster routing paths through a trusted routing algorithm and uses these routes to transmit data from cluster heads to the base station. In the route construction process, CTRF regards various parameters such as energy of the route, quality of the route, reliability of the route, and number of hops. CTRF runs on the network simulator version 2 (NS2), and its performance is compared with other secure routing approaches with regard to energy, throughput, packet loss rate, latency, detection ratio, and accuracy. This evaluation proves the superior and successful performance of CTRF compared to other methods.
Blood glucose variance measured by continuous glucose monitors across the menstrual cycle
Authors: Lin Georgianna , Siddiqui Rumsha , Lin Zixiong , Blodgett Joanna M. , Patel Shwetak N. , Truong Khai N. , Mariakakis Alex 
Published: August 2023

AbstractPast studies on how blood glucose levels vary across the menstrual cycle have largely shown inconsistent results based on limited blood draws. In this study, 49 individuals wore a Dexcom G6 continuous glucose monitor and a Fitbit Sense smartwatch while measuring their menstrual hormones and self-reporting characteristics of their menstrual cycles daily. The average duration of participation was 79.3 ± 21.2 days, leading to a total of 149 cycles and 554 phases in our dataset. We use periodic restricted cubic splines to evaluate the relationship between blood glucose and the menstrual cycle, after which we assess phase-based changes in daily median glucose level and associated physiological parameters using mixed-effects models. Results indicate that daily median glucose levels increase and decrease in a biphasic pattern, with maximum levels occurring during the luteal phase and minimum levels occurring during the late-follicular phase. These trends are robust to adjustments for participant characteristics (e.g., age, BMI, weight) and self-reported menstrual experiences (e.g., food cravings, bloating, fatigue). We identify negative associations between each of daily estrogen level, step count, and low degrees of fatigue with higher median glucose levels. Conversely, we find positive associations between higher food cravings and higher median glucose levels. This study suggests that blood glucose could be an important parameter for understanding menstrual health, prompting further investigation into how the menstrual cycle influences glucose fluctuation.
Space-based gravitational wave signal detection and extraction with deep neural network
Authors: Zhao Tianyu , Lyu Ruoxi , Wang He , Cao Zhoujian , Ren Zhixiang 
Published: August 2023

AbstractSpace-based gravitational wave (GW) detectors will be able to observe signals from sources that are otherwise nearly impossible from current ground-based detection. Consequently, the well established signal detection method, matched filtering, will require a complex template bank, leading to a computational cost that is too expensive in practice. Here, we develop a high-accuracy GW signal detection and extraction method for all space-based GW sources. As a proof of concept, we show that a science-driven and uniform multi-stage self-attention-based deep neural network can identify synthetic signals that are submerged in Gaussian noise. Our method exhibits a detection rate exceeding 99% in identifying signals from various sources, with the signal-to-noise ratio at 50, at a false alarm rate of 1%. while obtaining at least 95% similarity compared with target signals. We further demonstrate the interpretability and strong generalization behavior for several extended scenarios.
Increasing Pediatric Hearing Aid Use: Considerations for Clinical Practice
Authors: Muñoz Karen , Markle Kali , San Miguel Guadalupe G. , Twohig Michael P. 
Published: August 2023

Purpose:
Hearing aid use can be variable for young children, and inconsistent wear time can undermine spoken language development. This study explored the effectiveness of hearing aid data logging (DL) awareness and coaching sessions on increasing hours of hearing aid use. We also collected qualitative data on challenges participants experienced managing hearing aid use.

Method:
We used a single-subject design that included three conditions, during a 6-week period, in the same order for each participant. Condition A was baseline, Condition B was DL monitoring alone, and Condition C was remote coaching calls plus DL monitoring.

Results:
Hours of hearing aid use increased for each child from baseline to the end of the study, ranging from 1.19 to 4.4 hr. Mothers reported that the coaching calls were beneficial and helped them identify and problem-solve issues.

Conclusions:
Parents were able to increase hours of hearing aid use with DL awareness and coaching support. Tele-audiology offers an opportunity to provide parents with more frequent support that can be individualized based on their situation, challenges, and family needs.
Introduction: An International Perspective on Clinical Research in Speech-Language Pathology Cleft Care
Authors: Louw Brenda 
Published: August 2023

Purpose:
International cleft care can be viewed from the perspective of reviewing and closely examining clinical research conducted by speech-language pathologists in countries around the globe that may contribute to evidence-based practices in our own settings. Clinical research is aimed at bridging the gap between research and clinical practice by maximizing the relevance and application of research for practice. It is informed by current needs and barriers to practice and addresses the evaluation of the methods of assessment and intervention with clinicians as the primary audience. The aim of this forum is to share research conducted in clinical settings around the globe and to facilitate a broader reach and greater clinical impact to encourage clinicians' implementation of the research-generated solutions.

Conclusion:
Authors from Brazil, United Kingdom and Ireland, and Sweden exchange their expertise, passion, and research findings on cleft lip and/or palate (CL/P) to provide a broad view on clinical research internationally. The approaches and strategies shared may be applied to evidence-based practice in the United States to support quality service delivery when addressing the needs of individuals with CL/P.
Conservation Biology of Endangered Wild Walnut in Tianshan Valley, Xinjiang
Authors: Tan Yangyi 
Published: August 2023

Wild walnut belongs to the walnut family in Tianshan Valley of Xinjiang. Tertiary tree species in Central Asia and endangered plant under state protection. Its main distribution areas are as far as the Western Tianshan Mountains and Pamir-Alai Mountains of the former Soviet Union, and it is only distributed in Dekuztala County of Xinjiang, China. It is of great scientific value to study the origin and evolution of cultivated walnut, paleofloristic changes, paleogeography, Tertiary and Quaternary climatic changes. Due to the narrow distribution of wild walnut in Xinjiang, harsh desert conditions, climate change, human disturbance, habitat fragmentation and other factors, wild walnut in Xinjiang is facing the risk of extinction, and it is urgent to carry out research on conservation biology and conservation genetics.
In this paper, floristic, community and plant population research and analysis methods were adopted [1][6]. In this paper, the floristic composition, plant ecological type structure, plant climate and soil water characteristics of wild walnut community, age structure of wild walnut population, fluctuation cycle and evolution trend of population age composition, population growth characteristics, phenotypic plasticity of seeds and compound leaves, and biomass allocation were analyzed comprehensively in Xinjiang Nature Reserve. And put forward scientific protection countermeasures.
Neuroendokrines Karzinom der Gallenblase als seltene Ursache
für Meläna und Hämatemesis beim Hund
Authors: Krämer Anna Lena , Seehusen Frauke , Nolff Mirja Christine 
Published: August 2023

ZusammenfassungEin 9-jähriger männlicher Malinois wurde zur weiteren Evaluation
akuter Meläna und Hämatemesis sowie seit einem Monat anhaltenden
Gewichtsverlusts vorgestellt. Klinisch präsentierte sich der Patient von
geringgradig reduziertem Allgemeinbefinden. Die Blutuntersuchung ergab eine
geringgradige nicht-regenerative Anämie sowie eine geringgradige
Alaninaminotransferase (ALT)-Erhöhung. Ultrasonographisch bestand der
Verdacht auf eine frühe Mukozele. Die medikamentöse Therapie mit
Gastroprotektiva führte nicht zur klinischen Besserung und der Hund
entwickelte eine progressive Anämie. Die Gastroduodenoskopie verlief
ohne besonderen Befund. Aufgrund anhaltender Symptomatik wurde eine explorative
Laparotomie durchgeführt. Dabei wurde eine ulzerierte blutende Masse am
Gallenblasenhals detektiert. Die histopathologische Untersuchung ergab ein
neuroendokrines Karzinom. Hinweise auf eine Mukozele fanden sich
histopathologisch nicht. Meläna und Hämatemesis waren
postoperativ nicht mehr nachweisbar und 13 Monate nach Cholezystektomie war der
Hund weiterhin klinisch symptomfrei. Neuroendokrine Karzinome der Gallenblase
sollten als seltene Ursachen für Meläna und Hämatemesis
beim Hund betrachtet werden.