bluuebunny/crossref_metadata_2025_split huggingface dataset:
Numerical Modeling of Downstream Scour in Circular Culverts: Impact of Inlet Blockages and Variable Flow Conditions
Authors: Ahmed Kaywan Othman , Kavianpour Mohammad Reza , Amini Ata , Aminpour Younes 
Published: April 2024

Abstract
Accurate estimation of scour depth downstream of culvert outlets is essential for culvert design integrity. Inadequate designs can result in structural failures, leading to increased costs for maintenance and rehabilitation. This research evaluates the efficacy of numerical models in predicting scour depth and its location downstream of circular culverts under variable flow conditions. Two hydrographs were created for unsteady flow, featuring nine different flow discharges, while steady flow conditions were analysed at flow rates of 14 l/s and 22 l/s. The study investigated circular culverts with inlet blockages of 0%, 15%, and 30%, comparing outcomes with predictions from the Flow-3D software by using renormalization group (RNG) turbulence model. Extensive experimental data on circular culverts were utilized, with simulations performed using commercial software. This involved analysing the scour’s downstream profile, its maximum depth, and location, and comparing these metrics with actual observed data. Results showed that numerical model predictions closely matched the experimental data, although the simulated scour was generally less than what was observed for both steady and unsteady flows. While blockage rates notably impacted the scour patterns in unsteady flow scenarios, escalating blockage percentages did not uniformly translate into proportional increases in scour depth within steady flow environments.
Generative Deep Belief Differential Lotka Volterra-Based Data Transmission in Wsn for Real-Time Health Care Monitoring
Authors: Sachin B M , Sarvagya Mrinal 
Published: April 2024

Abstract
Wireless Sensor Networks (WSNs) have considerable awareness owing to their extensive scope of applications, to name a few being, natural disaster prohibition, health care monitoring video surveillance and so on. Moreover, the energy consumed during communication is a substantial quantity of energy loss and the routing protocol is the most suitable means to address this issue by fine-tuning weights to conserve the energy. Therefore the main issue experienced by WSN is the routing and data transmission and hence distinct points of reference need to be addressed when designing the routing protocol for real time healthcare monitoring. Motivated by these issues, in this work a method called, Probabilistic Generative Deep Belief and Differential Game Lotka Volterra (PGDB-DGLV) based data transmission in WSN for real-time health care monitoring is proposed. The PGDB-DGLV method is split into two sections, namely, optimal route discovery and robust data transmission. To measure route stability Balanced Centrality and Probabilistic Generative Deep Belief Network algorithm is designed. In the proposed model, a fine-tuned adjacency matrix employing the Stable Balanced Centrality function is defined to determine the next hop based on certain parameters like, hop count, residual energy and link quality. These parameters are salient assessments in adjacent node selections with which routing can be performed. Also, the initialization of the adjacency matrix and its corresponding fine-tuning is performed via the Probabilistic Generative Deep Belief Network. Second, to minimize the transmission speed and therefore reduce packet loss significantly, two kinds of game models, i.e., cooperative and cooperative models are constructed. Finally, the Lotka Volterra function is applied to ensure robust data transmission. At last, the performance of the proposed PGDB-DGLV method is evaluated using different evaluation metrics they are energy consumption, throughput transmission speed and packet loss rate. Finally, the evaluated results are compared with the prevailing data transmission methods. Among these methods, the proposed PGDB-DGLV method has achieved a better transmission speed with minimum energy consumption and maximum throughput considerably.
A Bayesian Network Approach to Hybrid Threat
Modelling
Authors: Vonk Maarten , Sweijs Tim , Minicozzi Raffaele 
Published: April 2024

Abstract
Western governments have adopted an assortment of counter-hybrid threat measures to defend against hostile actions below the conventional military threshold. The impact of these measures is unclear because of the ambiguity of hybrid threats, their cross-domain nature, and uncertainty about how countermeasures shape adversarial behaviour. This paper presents a model to simulate the impact of countermeasures on hybrid threat behaviour through a Bayesian Network approach - a probabilistic modelling technique. The model balances the costs of countermeasures, their ability to dissuade the adversary from executing hybrid threats, and their potential to mitigate the impact of hybrid threats. We run 1000 variants of a semi-synthetic scenario simulating the strategic interaction between attacking agent A and defending agent B over a cyber attack on critical infrastructure to explore the effectiveness of a set of five different counter-hybrid threat measures. Counter-hybrid measures range from strengthening resilience and denial of the adversary's ability to execute a hybrid threat to dissuasion through the threat of punishment. Our analysis primarily evaluates the overarching characteristics of counter-hybrid threat measures This approach allows us to generalize the effectiveness of these measures, rather than attributing results to measures individually. In addition, we discuss policy relevance and outline future research avenues.
The impact of climate risks on the cost of capital of oil and gas companies
Authors: Bettega Leonardo de Carvalho Bastos , Goncalves Edson Daniel Lopes , de Souza Rafael Martins 
Published: April 2024

Abstract
In a context of energy transition and decarbonization, companies operating in the oil and gas sector may be more exposed to climate risks, both physical and transition related. This greater exposure may reflect in a higher cost of capital, given the risk of stranded assets, stigmatization of the sector and reduced funding. This paper seeks to study this hypothesis, applying econometric models to analyze whether climate risk, represented here by a Carbon Intensity metric (scope 1 and scope 2 greenhouse gas emissions per US$ of revenue), has a significant effect on the systematic risk coefficient (beta) of these companies. The results show that Carbon Intensity has a statistically significant positive effect on beta, contributing to the argument that greater climate risk can increase companies' systematic risk. According to the most robust model (Model 1), a 100% increase in Carbon Intensity generates a corresponding rise of 0.0608 in beta, everything else kept constant - an increase of 7.25% in relation to the average beta of the sample.
Epigenetic Impact of Curcumin and Thymoquinone on Cancer Therapeutics
Authors: Kumar Vikas , Kesharwani Roohi , Patel Dilip K , Verma Amita , Mehanna Mohamed Gamil , Mohammad Ayman , Bawadood Azizah Salim , Alabassi Fahad A. , Anwar Firoz 
Published: April 2024

Abstract:
Today, one of the most prevalent reasons for death among people is carcinoma.
Because it is still on the increase throughout the world, there is a critical need for in-
-depth research on the pathogenic mechanisms behind the disease as well as for efficient
treatment. In the field of epigenetics, gene expression alterations that are inherited but
not DNA sequence changes are investigated. Three key epigenetic changes, histone modifications,
DNA methylation and non-coding RNA (ncRNA) expression, are principally
responsible for the initiation and progression of different tumors. These changes are interconnected
and constitute many epigenetic changes. A form of polyphenolic chemical
obtained from plants called curcumin has great bioactivity against several diseases, specifically
cancer. A naturally occurring substance called thymoquinone is well-known for
its anticancer properties. Thymoquinone affects cancer cells through a variety of methods,
according to preclinical studies. We retrieved information from popular databases,
including PubMed, Google Scholar, and CNKI, to summarize current advancements in
the efficiency of curcumin against cancer and its epigenetic regulation in terms of DNA
methylation, histone modifications, and miRNA expression. The present investigation offers
thorough insights into the molecular processes, based on epigenetic control, that underlie
the clinical use of curcumin and thymoquinone in cancerous cells.
Genes Selectively Expressed in Rat Organs
Authors: Li Dan , Wan Xulian , Yun Yu , Li Yongkun , Duan Weigang 
Published: April 2024

Background:
Understanding organic functions at a molecular level is important for scientists
to unveil the disease mechanism and to develop diagnostic or therapeutic methods.

Aim:
The present study tried to find genes selectively expressed in 11 rat organs, including the adrenal
gland, brain, colon, duodenum, heart, ileum, kidney, liver, lung, spleen, and stomach.

Materials and Methods:
Three normal male Sprague-Dawley (SD) rats were anesthetized, their organs
mentioned above were harvested, and RNA in the fresh organs was extracted. Purified RNA
was reversely transcribed and sequenced using the Solexa high-throughput sequencing technique.
The abundance of a gene was measured by the expected value of fragments per kilobase of transcript
sequence per million base pairs sequenced (FPKM). Genes in organs with the highest expression
level were sought out and compared with their median value in organs. If a gene in the highest
expressed organ was significantly different (p < 0.05) from that in the medianly expressed organ,
accompanied by q value < 0.05, and accounted for more than 70% of the total abundance, the gene
was assumed as the selective gene in the organ.

Results & Discussion:
The Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology
(GO) pathways were enriched by the highest expressed genes. Based on the criterion, 1,406 selective
genes were screened out, 1,283 of which were described in the gene bank and 123 of which
were waiting to be described. KEGG and GO pathways in the organs were partly confirmed by the
known understandings and a good portion of the pathways needed further investigation.

Conclusion:
The novel selective genes and organic functional pathways are useful for scientists to
unveil the mechanisms of the organs at the molecular level, and the selective genes’ products are
candidate disease markers for organs.
Mono-canalicular Lacrimal Stent Intubation for Congenital Nasolacrimal Duct Obstruction Treatment
Authors: Abushnein Ali Nema , Yasir Muthanna Basheer , Yosif Wissam 
Published: April 2024

Background

Epiphora, marked by tear overflow at the eyelid margin, is a prevalent condition in ophthalmology, affecting over 20% of infants. The causes involve hypersecretion due to anterior segment diseases or compromised lacrimal drainage systems. While
congenital nasolacrimal duct obstruction (CNLDO)
in children often resolves spontaneously, persistent cases may necessitate surgical intervention. The management, which includes probing, stent insertion, and dacryocystorhinostomy, remains challenging due to the miniaturized and variable anatomy of the lacrimal pathways.

Objective and Aims

This study aims to investigate the efficacy of mono-canalicular Lacrijet stent insertion in managing
congenital nasolacrimal duct obstruction (CNLDO)
in pediatric patients, particularly those aged over 24 months. It focuses on assessing success rates in cases with prior probing or no previous probing. The study aims to contribute valuable insights to the existing literature on the effectiveness of Lacrijet intubation as a management option for CNLDO.

Patients and Methods
A prospective observational study following 25 pediatric patients diagnosed with epiphora in an ophthalmology hospital. The procedure included using mono-canalicular Lacrijet intubation. Patients were followed for 180 days post-operatively via subjective and objective measures. Independent and paired t-tests were used for numerical variables. Chi-square was applied to check the significant association of variables with outcome. A p-value less than or equal to 5% is considered significant.

Results
More than half of the sample was 3-6 years of age (56%), males (52%), and had previous probing attempts (56%). Seven (28%) patients were relieved from symptoms within less than 5 days, 12 (48%) recovered within 5-9 days, and 2 (8%) patients were symptom-free after 10 days. The success rate was 84%. Only 4 patients (16%) had unsuccessful outcomes. There was no significant difference in outcome regarding patients’ age, gender, affected eye, previous probing, and site of intubation.

Conclusions and Recommendations
Mono-canalicular Lacrijet stent insertion appears as a simple, safe, and reliable outpatient procedure for treating CNLDO in children. Age and prior failed probing did not significantly impact success rates. Early and detailed assessments are recommended for children with epiphora, with consideration for mono-canalicular stenting. Future research could compare outcomes between probing and intubation as initial treatments for pediatric epiphora.
Optimizing Neuroprotective Nano-structured Lipid Carriers for Transdermal Delivery through Artificial Neural Network
Authors: Dalwadi Saloni , Thakkar Vaishali , Prajapati Bhupendra 
Published: April 2024

Background:
Dementia associated with Alzheimer’s disease (AD) is a neurological disorder.
AD is a progressive neurodegenerative condition that predominantly impacts the elderly population,
although it can also manifest in younger people through the impairment of cognitive functions,
such as memory, cognition, and behaviour. Donepezil HCl and Memantine HCl are encapsulated
in Nanostructured Lipid Carriers (NLCs) to prolong systemic circulation and minimize the systemic
side effects.

Objective:
This work explores the use of data mining tools to optimize the formulation of NLCs
comprising of Donepezil HCl and Memantine HCl for transdermal drug delivery. Neuroprotective
drugs and excipients are utilized for protecting the nervous system against damage or degeneration.

Methods:
The NLCs were formulated using a high-speed homogenization technique followed by ultrasonication.
NLCs were optimized using Box Behnken Design (BBD) in Design Expert Software
and artificial neural network (ANN) in IBM SPSS statistics. The independent variables included the
ratio of solid lipid to liquid lipid, the percentage of surfactant, and the revolutions per minute (RPM)
of the high-speed homogenizer.

Results:
The NLCs that were formulated had a mean particle size ranging from 67.0±0.45 to
142.4±0.52 nm. Both drugs have a %EE range over 75%, and Zeta potential was determined to be -
26±0.36 mV. CryoSEM was used to do the structural study. The permeation study showed the prolonged
release of the formulation.

Conclusion:
The results indicate that NLCs have the potential to be a carrier for transporting medications
to deeper layers of the skin and reaching systemic circulation, making them a suitable formulation
for the management of Dementia. Both ANN and BBD techniques are effective tools for systematically
developing and optimizing NLC formulation.
Consumer Perspectives for a Future Mobile App to Document Real-World Listening Difficulties: Qualitative Study
Authors: Galvin Karyn , Tomlin Dani , Timmer Barbra H B , McNeice Zoe , Mount Nicole , Gray Kathleen , Short Camille E 
Published: April 2024

Background
By enabling individuals with hearing loss to collect their own hearing data in their personal real-world settings, there is scope to improve clinical care, empower consumers, and support shared clinical decision-making and problem-solving. Clinician support for this approach has been established in a separate study.

Objective
This study aims to explore, for consumers with hearing loss, their (1) experiences of listening difficulties, to identify the data an app could usefully collect; (2) preferences regarding the features of mobile apps in general; and (3) opinions on the potential value and desirable features of a yet-to-be designed app for documenting listening difficulties in real-world settings.

Methods
A total of 3 focus groups involved 27 adults who self-reported hearing loss. Most were fitted with hearing devices. A facilitator used a topic guide to generate discussion, which was video- and audio-recorded. Verbatim transcriptions were analyzed using inductive content analysis.

Results
Consumers supported the concept of a mobile app that would facilitate the documenting of listening difficulties in real-world settings important to the individual. Consumers shared valuable insights about their listening difficulties, which will help determine the data that should be collected through an app designed to document these challenges. This information included early indicators of hearing loss (eg, mishearing, difficulty communicating in groups and on the phone, and speaking overly loudly) and prompts to seek hearing devices (eg, spousal pressure and the advice or example provided by others, and needing to rely on lipreading or to constantly request others to repeat themselves). It also included the well-known factors that influence listening difficulties (eg, reverberation, background noise, group conversations) and the impacts and consequences of their difficulties (eg, negative impacts on relationships and employment, social isolation and withdrawal, and negative emotions). Consumers desired a visual-based app that provided options for how data could be collected and how the user could enter data into an app, and which enabled data sharing with a clinician.

Conclusions
These findings provide directions for the future co-design and piloting of a prototype mobile app to provide data that are useful for increasing self-awareness of listening difficulties and can be shared with a clinician.
Characterizing the Adoption and Experiences of Users of Artificial Intelligence–Generated Health Information in the United States: Cross-Sectional Questionnaire Study
Authors: Ayo-Ajibola Oluwatobiloba , Davis Ryan J , Lin Matthew E , Riddell Jeffrey , Kravitz Richard L 
Published: April 2024

Background
OpenAI’s ChatGPT is a source of advanced online health information (OHI) that may be integrated into individuals’ health information-seeking routines. However, concerns have been raised about its factual accuracy and impact on health outcomes. To forecast implications for medical practice and public health, more information is needed on who uses the tool, how often, and for what.

Objective
This study aims to characterize the reasons for and types of ChatGPT OHI use and describe the users most likely to engage with the platform.

Methods
In this cross-sectional survey, patients received invitations to participate via the ResearchMatch platform, a nonprofit affiliate of the National Institutes of Health. A web-based survey measured demographic characteristics, use of ChatGPT and other sources of OHI, experience characterization, and resultant health behaviors. Descriptive statistics were used to summarize the data. Both 2-tailed t tests and Pearson chi-square tests were used to compare users of ChatGPT OHI to nonusers.

Results
Of 2406 respondents, 21.5% (n=517) respondents reported using ChatGPT for OHI. ChatGPT users were younger than nonusers (32.8 vs 39.1 years, P<.001) with lower advanced degree attainment (BA or higher; 49.9% vs 67%, P<.001) and greater use of transient health care (ED and urgent care; P<.001). ChatGPT users were more avid consumers of general non-ChatGPT OHI (percentage of weekly or greater OHI seeking frequency in past 6 months, 28.2% vs 22.8%, P<.001). Around 39.3% (n=206) respondents endorsed using the platform for OHI 2-3 times weekly or more, and most sought the tool to determine if a consultation was required (47.4%, n=245) or to explore alternative treatment (46.2%, n=239). Use characterization was favorable as many believed ChatGPT to be just as or more useful than other OHIs (87.7%, n=429) and their doctor (81%, n=407). About one-third of respondents requested a referral (35.6%, n=184) or changed medications (31%, n=160) based on the information received from ChatGPT. As many users reported skepticism regarding the ChatGPT output (67.9%, n=336), most turned to their physicians (67.5%, n=349).

Conclusions
This study underscores the significant role of AI-generated OHI in shaping health-seeking behaviors and the potential evolution of patient-provider interactions. Given the proclivity of these users to enact health behavior changes based on AI-generated content, there is an opportunity for physicians to guide ChatGPT OHI users on an informed and examined use of the technology.
Withania somnifera: A potential rejuvenator of medicinal system for healthcare
Authors: Sharma Vibhuti , Sehgal Rutika , Gupta Reena 
Published: April 2024

Medicinal herbs have been used since the time of the Vedas. The plants have therapeutic qualities in every part. Secondary metabolites of extensive variety are present in medicinal plants and are utilised in the production of medications as well as in the treatment of many different ailments. Withania somnifera is a medicinal plant, have various properties. 'Ashwagandha' is the popular name of Withania somnifera. It is offered as churna, a finely sieved powder that can be combined with ghee, water or honey. It has memory-enhancing, anti-oxidant, anti-stress, anti-venom, anti-inflammatory and anti-tumor effects. It is employed to treat a variety of clinical problems. In addition to being used as a suppressant in HIV/AIDS patients, Withania somnifera is used to treat ulcers, emaciation, colds, coughs, diabetes, conjunctivitis, insomnia, senile dementia, epilepsy, leprosy, Parkinson's disease, nervous disorders, rheumatism, arthritis, intestinal infections, bronchitis and asthma. The review article concentrates on the Withania somnifera plant's different pharmacological qualities.
Keywords: Withania somnifera, Ayurveda, Anti-oxidant, Anti-inflammatory, Anti-tumour
Investigating the Lid Effect in the Generation of Ocean Island Basalts
Authors: Jiang Shihao , Hawkins Rhys , Hoggard Mark James , Davies D. Rhodri , Campbell Ian H 
Published: April 2024

Ocean Island Basalts (OIBs) are generated by mantle plumes, with their
geochemistry controlled by a combination of source composition,
temperature, and thickness of overlying lithosphere. For example, OIBs
erupting onto thicker, older oceanic lithosphere are expected to exhibit
signatures indicative of higher average melting pressures. Here, we
quantitatively investigate this relationship using a global dataset of
Neogene and younger OIB compositions. Local lithospheric thicknesses are
estimated using theoretical plate-cooling models and Bayes factors are
applied to identify trends. Our findings provide compelling evidence for
a correlation between OIB geochemistry and lithospheric thickness, with
some variables SiO,
AlO, FeO, Lu, Yb and
λ) showing linear trends that can be attributed to
increasing average melting pressure, whereas others (λ
and λ, CaO) require a bi-linear fit with a change in
gradient at ~55 km. Observed variations in highly
incompatible elements are consistent with melt fractions that decrease
with increasing lithospheric thickness, as expected. Nevertheless, at
thicknesses beyond ~55 km, the implied melt fraction
does not decrease as rapidly as suggested by theoretical expectations.
This observation is robust across different lithospheric thickness
estimates, including those derived from seismic constraints. We
interpret this result as weak plumes failing to effectively thin
overlying lithosphere and/or producing insufficient melt to erupt at the
surface, in combination with a ‘memory effect’ of incomplete
homogenisation of melts during their ascent. This view is supported by
independent estimates of plume buoyancy flux, indicating that OIB
magmatism on older lithosphere may be biased towards hotter plumes.