bluuebunny/crossref_metadata_2025 huggingface dataset:
Husbandry Conditions and Welfare State of Pet Chinchillas (Chinchilla lanigera) and Caretakers’ Perceptions of Stress and Emotional Closeness to Their Animals
Authors: Gilhofer Elisabeth M. , Hebesberger Denise V. , Waiblinger Susanne , Künzel Frank , Rouha-Mülleder Cornelia , Mariti Chiara , Windschnurer Ines
Published: November 2024

For pet chinchillas, limited data are available on husbandry and the human–animal relationship despite their impact on health, behavior, and welfare. We conducted an online survey with pet chinchilla caretakers (n = 336), targeting husbandry practices, health, behavioral indicators of welfare, and human–chinchilla relationships. We further investigated associations between caretakers’ perceptions of stress in their chinchillas and emotional closeness to their animals. Basic needs such as keeping with conspecifics, constant access to water and hay, or offering dust baths were mostly fulfilled. Potential welfare issues included individual keeping (14.3%), undersized cages/enclosures (reported by 27.6% of the Austrian respondents), and suffering from a disease (14.7%). Behavioral indicators of good welfare, such as playing and cuddling with conspecifics, were observed several times per day by 40.9% and 87.9% of the respondents, respectively. Repetitive and unwanted behaviors were less common (fur biting, for instance, occurred ‘never’ in 82.9%). Caretakers rated their animals as generally more stressed if the animal was ill and more often showed fearful behavior toward them. Caretakers feeling closer to their animals spent more time engaging with them. Correct identification of this kind of association could be used as guidance for recommendations to improve chinchilla welfare at home and in the veterinary setting.
A Five-Bundle Intervention to Improve Blood Culture Use in a Tertiary Hospital in Romania
Authors: Popa Alina-Ioana , Tălăpan Daniela , Popescu Gabriel-Adrian
Published: November 2024

Objectives: The aims of this study were to evaluate the efficacy of a five-bundle intervention and to decrease the number of cases in which only one set of blood cultures is collected prior to starting antimicrobials. Methods: The study group consisted of the two hospital wards that have the highest collection rate (120 blood cultures/1000 patient days and 121.4 blood cultures/1000 patient days, respectively), and the control group consisted of the other three adult wards. The collection protocol was changed, and a bundle of five measures was introduced: one-on-one discussions with the nurses, 2% chlorhexidine in 70% alcohol for disinfection, ensuring the use of sterile gloves, sterile wipes, a checklist for the materials needed, and a copy of the collection protocol. The impact of these changes was followed over a 5-month period. Results: Prior to the intervention, the contamination rate was higher in the control group (6.5%) versus the study group (4%), p = 0.00578. The before–after analysis revealed a significantly reduced contamination rate in the control group (4.6% vs. 6.5% p = 0.0099), but it was above the one obtained in the study group (3.1% vs. 4%, p = 0.1635). The number of infectious episodes in which one blood culture set was collected decreased significantly in the study group (77/311 vs. 139/456, p = 0.041). Conclusions: The intervention decreased the contamination rate and the number of infectious episodes in which one blood culture set is collected.
Optimization of Rotary Drilling Rig Mast Structure Based on Multi-Dimensional Improved Salp Swarm Algorithm
Authors: Yang Heng , Ren Yuhang , Xu Gening
Published: November 2024

The mast is a critical component of rotary drilling rigs, which has a cross-section consisting of a rectangular shape formed by two web plates and two flange plates. Structural optimization of the mast is necessary to address the issue of excessive weight. The shortcomings of the traditional structural optimization algorithms are summarized as follows: the optimized steel plate thickness is a non-integer, where rounding upwards may increase the cost to a certain extent, but it can ensure the safety of the structure; rounding downwards its load carrying capacity may not satisfy the requirements, and thus a novel Salp Swarm Algorithm is proposed to solve the optimization problem. First, this study improves the initialization and update strategy in the traditional Salp Swarm Algorithm. In order to obtain a solution for engineering, an innovative multi-dimensional running comparison is carried out. Secondly, the optimization model of rotary drilling rigs is established based on the division of the working conditions. The objective function of the optimization model is to minimize the weight of the mast while considering the constraints of strength, stiffness, stability, and welding process. Finally, the proposed optimization algorithm and the established optimization model are applied to optimize the design of the mast for a rotary drilling rig. The empirical results demonstrate that the weight of the mast has been reduced by 20%. In addition, the Improved Salp Swarm Algorithm exhibits higher solution quality, faster iteration capability, and extreme stability in optimizing welded box sections compared to the conventional algorithm. The example shows that the Improved Salp Swarm Algorithm is applicable to the optimization problem of box sections.
Towards Real-Time Integrated Water Vapor Estimates with Triple-Frequency Galileo Observations and CNES Products
Authors: Abdelazeem Mohamed
Published: November 2024

Integrated water vapor (IWV) is a crucial parameter for tropospheric sounding and weather prediction applications. IWV is essentially calculated using observations from global navigation satellite systems (GNSS). Presently, the Galileo satellite system is further developed, including more visible satellites that transmit multi-frequency signals. This study aims to evaluate the accuracy of real-time IWV estimated from a triple-frequency Galileo-only precise point positioning (PPP) processing model utilizing E1, E5a, E5b, and E5 observations, which is not addressed by the previous studies. For this purpose, Galileo datasets from 10 global reference stations spanning various 4-week periods in the winter, spring, summer, and fall seasons are acquired. To process the acquired datasets, dual- and triple-frequency ionosphere-free PPP solutions are used, including E1E5a PPP, E1E5aE5b PPP, and E1E5E5b PPP solutions. The publicly available real-time products from the Centre National d’Etudes Spatiales (CNES) are utilized. The real-time IWV values are computed and then validated with the European Centre for Medium-Range Weather Forecasting (ECMWF) reanalysis products (ERA5) counterparts. The findings demonstrate that the root mean square error (RMSE) of the estimated IWV is less than 3.15 kg/m2 with respect to the ECMWF ERA5 counterparts. Furthermore, the E1E5aE5b PPP and E1E5E5b PPP models enhance the IWV’s accuracy by about 11% and 16%, respectively, compared with the E1E5a PPP model.
Can the Artificial Release of Fluorinated Gases Offset Global Cooling Due to Supervolcanic Eruptions?
Authors: Xu Yangyang , Ribar Nathanael P. , Sachnik Jeffrey , Schade Gunnar W. , Lockley Andrew John , Zhang Yi Ge , Yu Pengfei , Hu Jianxin , Velders Guus J. M.
Published: November 2024

Large volcanic eruptions, such as the prehistoric Yellowstone eruption, induce abrupt global cooling—by some estimates at a rate of ~1 °C/year, lasting for more than a decade. An abrupt global cooling of several °C—even if only lasting a few years—would present immediate, drastic stress on biodiversity and food production. This cooling poses a global catastrophic risk to human society beyond the immediate and direct impact of eruptions. Using a simple climate model, this paper discusses the possibility of counteracting large volcanic cooling with the intentional release of greenhouse gases. Longer-lived compounds (e.g., CO2 and CH4) are unsuitable for this purpose, but selected fluorinated gases (F-gases), either individually or in combinations, could be released at gigaton scale to offset large volcanic cooling substantially. We identify candidate F-gases (e.g., C4F6 and CH3F) and derive radiative and chemical properties of ‘ideal’ compounds matching specific cooling events. Geophysical constraints on manufacturing and stockpiling due to mineral availability are considered, alongside technical and economic implications based on present-day market assumptions. The effects and uncertainty due to atmospheric chemistry related to aerosol injection, F-gases release, and solar dimming are discussed in the context of large volcanic perturbation. The caveats and future steps using more complex chemistry–climate models are discussed. Despite the speculative nature of the magnitude and composition of F-gases, our conceptual analysis has implications for testing the possibility of mitigating certain global catastrophic cooling risks (e.g., nuclear winter, asteroid impact, and glacier transition) via intentional intervention.
Challenges and Potentials: Environmental Assessment of Particulate Matter in Spaces Under Highway Viaducts
Authors: Chen Zeyin , Li Siying , Liu Chao
Published: November 2024

Under-viaduct space (UVS) is becoming an important solution to urban mobility problems, and the construction and use of high-density city center highways and elevated bridges are increasing, which has a negative impact on the UVS. Air pollution is a problem in these spaces, but research on air pollution in UVSs is lacking. To further study air pollution in UVS, this study selected a case area of a UVS in central Shanghai and investigated the spatiotemporal distribution patterns of air pollution and the influencing factors. We found that air pollution in the UVS is significantly higher than the background levels, and the higher the background levels, the greater the difference between the pollution of the UVS and the background. In terms of the impact factor, air pollution is highly correlated with the built environment and traffic flow. The research provides evidence of the exposure to air pollution in under viaducts spaces in the microenvironment.
Varying Performance of Low-Cost Sensors During Seasonal Smog Events in Moravian-Silesian Region
Authors: Nevrlý Václav , Dostál Michal , Bitala Petr , Klečka Vít , Sléžka Jiří , Polách Pavel , Nevrlá Katarína , Barabášová Melánie , Langová Růžena , Bernatíková Šárka , Martiníková Barbora , Vašinek Michal , Nevrlý Adam , Lazecký Milan , Suchánek Jan , Chaloupecká Hana , Kiča David , Wild Jan
Published: November 2024

Air pollution monitoring in industrial regions like Moravia-Silesia faces challenges due to complex environmental conditions. Low-cost sensors offer a promising, cost-effective alternative for supplementing data from regulatory-grade air quality monitoring stations. This study evaluates the accuracy and reliability of a prototype node containing low-cost sensors for carbon monoxide (CO) and particulate matter (PM), specifically tailored for the local conditions of the Moravian-Silesian Region during winter and spring periods. An analysis of the reference data observed during the winter evaluation period showed a strong positive correlation between PM, CO, and NO2 concentrations, attributable to common pollution sources under low ambient temperature conditions and increased local heating activity. The Sensirion SPS30 sensor exhibited high linearity during the winter period but showed a systematic positive bias in PM10 readings during Polish smog episodes, likely due to fine particles from domestic heating. Conversely, during Saharan dust storm episodes, the sensor showed a negative bias, underestimating PM10 levels due to the prevalence of coarse particles. Calibration adjustments, based on the PM1/PM10 ratio derived from Alphasense OPC-N3 data, were initially explored to reduce these biases. For the first time, this study quantifies the influence of particle size distribution on the SPS30 sensor’s response during smog episodes of varying origin, under the given local and seasonal conditions. In addition to sensor evaluation, we analyzed the potential use of data from the Copernicus Atmospheric Monitoring Service (CAMS) as an alternative to increasing sensor complexity. Our findings suggest that, with appropriate calibration, selected low-cost sensors can provide reliable data for monitoring air pollution episodes in the Moravian-Silesian Region and may also be used for future adjustments of CAMS model predictions.
Modeling the Spatial Flows of Nitrogen: The Case of Xiamen
Authors: Li Yanmin , Zhang Tianqi , Wang Shihang , Shen Yu-Sheng , Cui Shenghui
Published: November 2024

Rapid city expansion and intensive human activities have remarkably affected nitrogen flow, leading to increasingly intricate spatial heterogeneity of nitrogen flow. Focused on the temporal characteristics of nitrogen flow at certain city scales, the existing research has missed comprehensive grid-scale spatial models for nitrogen flow. To address this gap, this study develops a comprehensive spatial model for nitrogen flow by incorporating both natural and anthropic processes. Taking Xiamen as its research case, this study utilizes grid technology and spatial analysis to build a detailed spatial model for nitrogen flow at the grid scale. The results of spatial characteristics of Xiamen in 2015 revealed that hotspots of nitrogen input were primarily located in the surrounding areas outside and east of Xiamen, with the maximum nitrogen input reaching 20.07 × 104 kg/ha. However, the hotspots of nitrogen load in the atmosphere were concentrated in the urban center (i.e., Xiamen Island) and the nearby sea areas. The maximum nitrogen outputs can reach 18.32 × 104 kg/ha, which is 18 times the total nitrogen output to the water environment. Additionally, it was found that a significant gradient correlation exists between nitrogen flow and population density. These findings provide support for low-nitrogen spatial planning and emission reduction policymaking.
MiRNA Profiling of Areca Nut-Induced Carcinogenesis in Head and Neck Cancer
Authors: Huang Hung-Han , Chang Joseph T. , You Guo-Rung , Fu Yu-Fang , Shen Eric Yi-Liang , Huang Yi-Fang , Shen Chia-Rui , Cheng Ann-Joy
Published: November 2024

Background: While miRNAs are increasingly recognized for their role in tumorigenesis, their involvement in head and neck cancer (HNC) remains insufficiently explored. Additionally, the carcinogenic mechanisms of areca nut, a major habitual carcinogen in Southeast Asia, are not well understood. Methods and results: This study adopts a systematic approach to identify miRNA profiles associated with areca nut-induced HNC. Using miRNA microarray analysis, we identified 292 miRNAs dysregulated in areca nut-treated HNC cells, with 136 upregulated and 156 downregulated. Bioinformatic analysis of the TCGA-HNSC dataset uncovered a set of 692 miRNAs relevant to HNC development, comprising 449 overexpressed and 243 underexpressed in tumor tissues. Integrating these datasets, we defined a signature of 84 miRNAs, including 39 oncogenic miRNAs (OncomiRs) and 45 tumor-suppressive miRNAs (TsmiRs), highlighting their pivotal role in areca nut-induced carcinogenesis. MultiMiR analysis identified 740 genes cross-regulated by eight hub TsmiRs, significantly impacting key cancer-related pathways (p53, PI3K-AKT, MAPK, and Ras) and critical oncogenic processes. Moreover, we validated miR-499a-5p as a vital regulator, demonstrating its ability to mitigate areca nut-induced cancer progression by reducing cell migration, invasion, and chemoresistance. Conclusions: Thus, this miRNA signature addresses a crucial gap in understanding the molecular underpinnings of areca nut-induced carcinogenesis and offers a promising platform for clinical applications in risk assessment, diagnosis, and prognosis of areca nut-associated malignancies.
Progress in Precision Medicine for Head and Neck Cancer
Authors: Vakili Sanaz , Behrooz Amir Barzegar , Whichelo Rachel , Fernandes Alexandra , Emwas Abdul-Hamid , Jaremko Mariusz , Markowski Jarosław , Los Marek J. , Ghavami Saeid , Vitorino Rui
Published: November 2024

This paper presents a comprehensive comparative analysis of biomarkers for head and neck cancer (HNC), a prevalent but molecularly diverse malignancy. We detail the roles of key proteins and genes in tumourigenesis and progression, emphasizing their diagnostic, prognostic, and therapeutic relevance. Our bioinformatic validation reveals crucial genes such as AURKA, HMGA2, MMP1, PLAU, and SERPINE1, along with microRNAs (miRNA), linked to HNC progression. OncomiRs, including hsa-miR-21-5p, hsa-miR-31-5p, hsa-miR-221-3p, hsa-miR-222-3p, hsa-miR-196a-5p, and hsa-miR-200c-3p, drive tumourigenesis, while tumour-suppressive miRNAs like hsa-miR-375 and hsa-miR-145-5p inhibit it. Notably, hsa-miR-155-3p correlates with survival outcomes in addition to the genes RAI14, S1PR5, OSBPL10, and METTL6, highlighting its prognostic potential. Future directions should focus on leveraging precision medicine, novel therapeutics, and AI integration to advance personalized treatment strategies to optimize patient outcomes in HNC care.
Untreated Vestibular Schwannoma: Analysis of the Determinants of Growth
Authors: Yang Cheng , Alvarado Daniel , Ravindran Pawan Kishore , Keizer Max E. , Hovinga Koos , Broen Martinus P. G. , Kunst Henricus (Dirk) P. M. , Temel Yasin
Published: November 2024

The growth rate of sporadic VS varies considerably, posing challenges for consistent clinical management. This systematic review examines data on factors associated with VS growth, following a protocol registered in the PROSPERO database. The analysis reveals that key predictors of tumor growth include tumor location, initial size, and specific clinical symptoms such as hearing loss and imbalance. Additionally, several studies suggest that growth observed within the first year may serve as an indicator of subsequent progression, enabling the earlier identification of high-risk cases. Emerging factors such as the posture swing test and MRI signal intensity have also been identified as novel predictors that could further refine growth assessments. Our meta-analysis confirms that tumor location, initial size, cystic components, and vestibular symptoms are closely linked to the likelihood of VS growth. This review provides valuable guidance for clinicians in identifying patients who may require closer monitoring or early intervention. By integrating these predictive factors into clinical practice, this review supports more personalized treatment and contributes to the development of more accurate prognostic models for managing untreated sporadic VS.
The Immunomodulatory Effect of Different FLT3 Inhibitors on Dendritic Cells
Authors: Schlaweck Sebastian , Radcke Alea , Kampmann Sascha , Becker Benjamin V. , Brossart Peter , Heine Annkristin
Published: November 2024

Background: FMS-like tyrosine kinase 3 (FLT3) mutations or internal tandem duplication occur in 30% of acute myeloid leukemia (AML) cases. In these cases, FLT3 inhibitors (FLT3i) are approved for induction treatment and relapse. Allogeneic hematopoietic stem cell transplantation (alloHSCT) remains the recommended post-induction therapy for suitable patients. However, the role of FLT3i therapy after alloHSCT remains unclear. Therefore, we investigated the three currently available FLT3i, gilteritinib, midostaurin, and quizartinib, in terms of their immunosuppressive effect on dendritic cells (DCs). DCs are professional antigen-presenting cells inducing T-cell responses to infectious stimuli. Highly activated DCs can also cause complications after alloHSCT, such as triggering Graft versus Host disease, a serious and potentially life-threatening complication after alloHSCT. Methods: To study the immunomodulatory effects on DCs, we differentiated murine and human DCs in the presence of FLT3i and performed immunophenotyping by flow cytometry and cytokine measurements and investigated gene and protein expression. Results: We detected a dose-dependent immunosuppressive effect of midostaurin, which decreased the expression of costimulatory markers like CD86, and found a reduced secretion of pro-inflammatory cytokines such as IL-12, TNFα, and IL-6. Mechanistically, we show that midostaurin inhibits TLR and TNF signaling and NFκB, PI3K, and MAPK pathways. The immunosuppressive effect of gilteritinib was less pronounced, while quizartinib did not show truncation of relevant signaling pathways. Conclusions: Our results suggest different immunosuppressive effects of these three FLT3i and may, therefore, provide an additional rationale for optimal maintenance therapy after alloHSCT of FLT3-positive AML patients to prevent infectious complications and GvHD mediated by DCs.
Estimation of the Partial Discharge Inception Voltage of Electrical Asset Components at Variable Environmental Pressure: A Modelling Approach
Authors: Myneni Sukesh Babu , Montanari Gian Carlo
Published: November 2024

Since partial discharges, PD, are a major accelerated degradation mechanism of organic electrical insulation systems, measuring partial discharge inception voltage, PDIV, of electrical asset components in aviation and aerospace is a fundamental tool to cope with life, safety, and reliability requirements. Partial discharge phenomenology and inception voltage depend on pressure, specifically, PDIV decreases with pressure. To avoid PD inception during aircraft or aerospace vehicle operation, the value of PDIV must be known at any pressure that electrical asset components will experience. However, a lack of experimental facilities adequate to test PD on real-size asset components might prevent from having PD-related information at pressures lower (or higher) than standard atmospheric pressure, SAP. This paper presents a heuristic approach, based on physics-derived PD field inception models, that allows the estimation of PDIV at low pressure to be carried out based on measurements made at SAP, when the typology of the defect causing partial discharge is known (from SAP PD measurements), but the precise type, size, and location of the PD-generating defect is unknown. It is shown that PDIV estimates obtained by the proposed models for internal and surface discharges are in good agreement with measured values in a range from SAP to 0.05 bar, testing simple insulation geometries but also real asset components, such as motors.
Optimizing Alkaline Water Electrolysis: A Dual-Model Approach for Enhanced Hydrogen Production Efficiency
Authors: Luo Simin , Zhang Tengfei , Xu Hongning , Zhang Jie , Zhao Haichao , Yun Jimmy , Zhao Hong
Published: November 2024

This study develops a semi-empirical model of an alkaline water electrolyzer (AWE) based on thermodynamic and electrochemical principles to investigate cell voltage behavior during electrolysis. By importing polarization curve test data under specific operational conditions, eight undefined parameters are precisely fitted, demonstrating the model’s high accuracy in describing the voltage characteristics of alkaline electrolyzers. Additionally, an AWE system model is introduced to examine the influence of various operational parameters on system efficiency. This innovative approach not only provides detailed insights into the operational dynamics of AWE systems but also offers a valuable tool for optimizing performance and enhancing efficiency, advancing the understanding and optimization of AWE technologies.
LiDAR-Based Modeling of Individual Tree Height to Crown Base in Picea crassifolia Kom. in Northern China: Comparing Bayesian, Gaussian Process, and Random Forest Approaches
Authors: Yang Zhaohui , Yang Hao , Zhou Zeyu , Wan Xiangxing , Zhang Huiru , Duan Guangshuang
Published: November 2024

This study compared hierarchical Bayesian, mixed-effects Gaussian process regression, and random forest models for predicting height to crown base (HCB) in Qinghai spruce (Picea crassifolia Kom.) forests using LiDAR-derived data. Both modeling approaches were applied to a dataset of 510 trees from 16 plots in northern China. The models incorporated tree-level variables (height, diameter at breast height, crown projection area) and plot-level spatial competition indices. Model performance was evaluated using leave-one-plot-out cross-validation. The Gaussian mixed-effects process model (with an RMSE of 1.59 and MAE of 1.25) slightly outperformed the hierarchical Bayesian model and the random forest model. Both models identified LiDAR-derived tree height, DBH, and LiDAR-derived crown projection area as primary factors influencing HCB. The spatial competition index (SCI) emerged as the most effective random effect, with the lowest AIC and BIC values, highlighting the importance of local competition dynamics in HCB formation. Uncertainty analysis revealed consistent patterns across the predicted values, with an average relative uncertainty of 33.89% for the Gaussian process model. These findings provide valuable insights for forest management and suggest that incorporating spatial competition indices can enhance HCB predictions.
Dynamic Wood Consumption Forecast in Germany from 2020 to 2050
Authors: Wang Ruisheng , Haller Peer
Published: November 2024

Against the backdrop of pressing environmental challenges such as global warming, nations are intensifying efforts to reduce energy consumption and emissions in the future. The carbon-neutral attribute of wood is being reassessed, signaling a potential shift in consumption patterns. This study aims to forecast wood consumption in Germany from 2020 to 2050 and evaluate the ability of domestic forests to meet demand. Employing a material flow analysis approach and considering recent data alongside Germany’s Climate Action 2050 goals, consumption projections were made for sectors such as building, paper, energy, furniture, and packaging. Results indicate a significant surge in wood consumption, particularly in the scenario with a high residential renovation rate, necessitating substantial wood imports to fulfill demand. Energy and building emerge as pivotal sectors for reducing wood consumption. This research fills a gap in prospective prediction on wood consumption, which is essential for aligning strategies with environmental objectives.
A Secure Auditable Remote Registry Pattern for IoT Systems
Authors: Maña Antonio , Jaime Francisco J. , Gutiérrez Lucía
Published: November 2024

In software engineering, pattern papers serve the purpose of providing a description of a generalized, reusable solution to recurring design problems, based on practical experience and established best practices. This paper presents an architectural pattern for a Secure Auditable Registry service based on Message-Oriented Middleware to be used in large-scale IoT systems that must provide auditing capabilities to external entities. To prepare the pattern, the direct experience in applying the pattern solution in an industry-funded R&D project has been a key aspect because it has allowed us to gain a deep understanding of the problem and the solution, and it has contributed to the correctness and real-world applicability of the pattern as described. To further improve the quality of the paper, we have followed the commonly accepted practices in pattern development (including peer reviews) to ensure that the core aspects of the solution are correctly represented and that the description allows it to be applicable to similar problems in other domains, such as healthcare, autonomous devices, banking, food tracing or manufacturing to name a few. The work done in applying this pattern confirms that it solves a recurring problem for IoT systems, but also that it can be adopted in other domains, providing an effective solution in order to achieve enhancement of the auditability capabilities of the target systems. This pattern will be part of a pattern language (i.e., a family of related patterns) that we are developing for transitioning from legacy systems to IoT with an emphasis on security.
Molecular and Functional Assessment of TSC1 and TSC2 in Individuals with Tuberous Sclerosis Complex
Authors: Dufner-Almeida Luiz Gustavo , Cardozo Laís F. M. , Schwind Mariana R. , Carvalho Danielly , Almeida Juliana Paula G. , Cappellano Andrea Maria , Alegria Thiago G. P. , Nanhoe Santoesha , Nellist Mark , Passos-Bueno Maria Rita , Chiavegatto Silvana , Silva Nasjla S. , Rosemberg Sérgio , Pereira Ana Paula A. , Antoniuk Sérgio Antônio , Haddad Luciana A.
Published: November 2024

Tuberous sclerosis complex (TSC) is an autosomal dominant neurodevelopmental disorder and multisystem disease caused by pathogenic DNA alterations in the TSC1 and TSC2 tumor suppressor genes. A molecular genetic diagnosis of TSC confirms the clinical diagnosis, facilitating the implementation of appropriate care and surveillance. TSC1 and TSC2 encode the core components of the TSC1/2 complex (TSC1/2), a negative regulator of the mechanistic target of rapamycin (MTOR) complex 1 (TORC1). Functional analysis of the effects of TSC1 and TSC2 variants on TORC1 activity can help establish variant pathogenicity. We searched for pathogenic alterations to TSC1 and TSC2 in DNA isolated from 116 individuals with a definite clinical diagnosis of TSC. Missense variants and in-frame deletions were functionally assessed. Pathogenic DNA alterations were identified in 106 cases (91%); 18 (17%) in TSC1 and 88 (83%) in TSC2. Of these, 35 were novel. Disruption of TSC1/2 activity was demonstrated for seven TSC2 variants. Molecular diagnostics confirms the clinical diagnosis of TSC in a large proportion of cases. Functional assessment can help establish variant pathogenicity and is a useful adjunct to DNA analysis.
Volatile Organic Compound (VOC) Contamination in Hotel Rooms: A Pilot Study to Understand Sources and Health Risks
Authors: Nored Adam , Fu Xianqiang , Qi Rui , Batbaatar Namuun , Jia Chunrong
Published: November 2024

The COVID-19 pandemic drove the use of cleaning products, causing organic solvent contamination in hospitality environments. This pilot study investigated the presence and concentrations of volatile organic compounds (VOCs) in selected hotels in four different US cities with varying star ratings at the end of the pandemic period. Targeting 139 VOCs, 57 were detected across eight groups: alcohols, halocarbons, aromatics, alkanes, terpenes, carbonyls, ethers, and esters, in the indoor air. Alcohols were the most prevalent, especially in lower-rated hotels, suggesting higher use of cleaning supplies. Elevated levels of aromatics were detected in hotels rated under three stars, with a notable disparity compared to higher-rated hotels. Additionally, alkanes and terpenes such as n-tetradecane and d-limonene were consistently detected. Health risk assessment showed concentrations of all VOCs remained below their health criteria for customers. The cumulative cancer risk was 2.25 × 10−6 for hotel workers from chronic occupational exposure to eight carcinogenic VOCs, representing 1/3 of the lifetime risk from these chemicals in the ambient air. Cancer risks from individual VOCs ranged from 0.001 × 10−6 to 1.07 × 10−6, with chloroform accounting for nearly half of the cumulative risk. The findings underscore the need for careful selection and use of furnishings and cleaning supplies and for effective indoor air pollution control and management in hotel indoor environments.
The Tax Incidence and Tax Pass-Through of Smokeless Tobacco in the US
Authors: He Yanyun , Yang Qian , Shang Ce
Published: November 2024

Background: States adopt different tax bases for smokeless tobacco (SLT), making tax incidence on SLT not directly comparable across states. In addition, how taxes are passed through to SLT prices among states that impose specific taxes, and whether the pass-through rates for SLT are affected by the uptake and evolution of e-cigarettes, is unknown. Objective: This study will calculate the tax incidence on SLT and investigate how SLT taxes are passed to prices at the 25th, 50th, and 75th percentile levels, as well as whether these pass-through rates vary by e-cigarette uptake and evolution. Methods: We regressed SLT prices on specific taxes using ordinary least square regressions while controlling for state-, year-, and quarter-fixed effects. We then tested the difference in tax pass-through rates by different periods. Findings: The average tax incidence on chewing tobacco, moist snuff, dry snuff, and snus was 22%, 22%, 23%, and 20%, respectively. For moist snuff, taxes were fully passed to prices at the 25th and 50th percentiles (rate = 1.01, p < 0.001) and overly passed to prices at the 75th percentile (rate = 1.25, p < 0.001). The e-cigarette uptake and evolution significantly raised taxes by 13 cents and 14 cents per ounce, respectively, for moist snuff at the 75th percentile prices (p < 0.05). Conclusions: If harm is considered a criterion for taxing tobacco products, the tax incidence on SLT could be further increased. Considering that lower-priced SLT have lower tax pass-through rates, price promotion restrictions and minimum pricing laws may be needed to increase the cost of lower-priced products. Additionally, we observed that tobacco companies tended to increase tax pass-through for premium SLT products as e-cigarettes gained popularity, which may indicate a strategic response to shifting consumer preferences.
Comprehensive Review and Future Research Directions on ICT Standardisation
Authors: Mahdi Mohammed Najah , Walshe Ray , Farrell Sharon , Pandit Harshvardhan J.
Published: November 2024

Standardisation has become imperative to retaining order and development in modern society. The simplest actions, such as train timings and the width of the railroad, would be very difficult to achieve without Standardisation. Standardisation also solves problems, such as the use of mobile devices, which requires travel abroad when out of range. We perform a large-scale quantitative analysis for papers dealing with (1) standards and (2) Information and communications technology (ICT) data in three important databases, namely Web of Science, IEEE Explore, and ACM digital library, in this paper. These three databases presented 216 articles that were divided into five categories: standard-related review and survey studies, information management across hardware and software standards, energy management standards, machine learning model classification performance, privacy-aware software system standards, and health information and communications technology standards. This paper discusses how Standardisation facilitates the planning of the entire research and innovation process by encouraging discussions regarding the specific outputs the research aims to achieve. The paper further illustrates that references related to standardisation within the call topics act as a crucial motivating factor in the decision to adopt standardisation. In conclusion, our contribution provides a better understanding of standards in peer-reviewed publications and an essential foundation for future research. In addition, we demonstrate that standards play an important role in innovation.
Quantum Marine Predator Algorithm: A Quantum Leap in Photovoltaic Efficiency Under Dynamic Conditions
Authors: Fergani Okba , Himeur Yassine , Mechgoug Raihane , Atalla Shadi , Mansoor Wathiq , Tkouti Nacira
Published: November 2024

The Quantum Marine Predator Algorithm (QMPA) presents a groundbreaking solution to the inherent limitations of conventional Maximum Power Point Tracking (MPPT) techniques in photovoltaic systems. These limitations, such as sluggish response times and inadequate adaptability to environmental fluctuations, are particularly pronounced in regions with challenging weather patterns like Sunderland. QMPA emerges as a formidable contender by seamlessly integrating the sophisticated hunting tactics of marine predators with the principles of quantum mechanics. This amalgamation not only enhances operational efficiency but also addresses the need for real-time adaptability. One of the most striking advantages of QMPA is its remarkable improvement in response time and adaptability. Compared to traditional MPPT methods, which often struggle to keep pace with rapidly changing environmental factors, QMPA demonstrates a significant reduction in response time, resulting in up to a 30% increase in efficiency under fluctuating irradiance conditions for a resistive load of 100 Ω. These findings are derived from extensive experimentation using NASA’s worldwide power prediction data. Through a detailed comparative analysis with existing MPPT methodologies, QMPA consistently outperforms its counterparts, exhibiting superior operational efficiency and stability across varying environmental scenarios. By substantiating its claims with concrete data and measurable improvements, this research transcends generic assertions and establishes QMPA as a tangible advancement in MPPT technology.
Consumer Satisfaction Benchmarking Analysis Using Group Decision Support System (GDSS) PROMETHEE Methodology in a GIS Environment
Authors: Saridou Anastasia S. , Vavatsikos Athanasios P.
Published: November 2024

In today’s competitive environment, multi-branch companies allocate their stores with the aim of expanding their territorial coverage to attract new customers and increase their market share. Consumer satisfaction surveys either produce global performance results or they are not able to differentiate consumer perceptions using location analytics. This research develops a novel framework to assist multi-branch companies in mapping the consumer satisfaction performance of their stores, expanding conventional customer relationship management to the spatial context. The framework developed proposes a decision model that combines the Group Decision Support extension of the PROMETHEE and CRITIC methods in a GIS environment to generate satisfaction performance mappings. The developed decision-making framework converts consumer responses into satisfaction performance maps, allowing the company’s stores and their competitors to be evaluated. Moreover, it provides insight into the potential opportunities and threats for each store. The performance of the proposed framework is highlighted through a case study involving a multi-branch coffeehouse company in a Greek city. Finally, a tool developed to assist the computational part of the framework is presented.
Functional Analysis of CPSF30 in Nilaparvata lugens Using RNA Interference Reveals Its Essential Role in Development and Survival
Authors: Jing Shengli , Yang Jing , Liu Yali , Wang Feifei , Zheng Fang , Ren Aobo , Yu Bingbing , Zhao Yue , Jia Bing , Chen Ruixian , Yu Bin , Liu Qingsong , Xu Jingang
Published: November 2024

The brown planthopper (Nilaparvata lugens) is a major pest threatening global rice production, significantly reducing yields annually. As N. lugens increasingly develops resistance to conventional control methods, such as chemical pesticides, there is an urgent need for innovative and sustainable pest management strategies. Cleavage and Polyadenylation Specificity Factor 30 (CPSF30) is a key protein involved in mRNA 3′ end processing, yet its function in N. lugens remains poorly understood. This study aims to elucidate the role of CPSF30 in the growth and development of N. lugens and evaluate its potential as a target for RNA interference (RNAi)-based pest control strategies. We cloned and characterized the cDNA sequence of NlCPSF30, which encodes a protein of 341 amino acids containing five CCCH zinc-finger domains and two CCHC zinc-knuckle domains. Sequence alignment revealed that NlCPSF30 is highly conserved among insect species, particularly in the zinc-finger domains essential for RNA binding and processing. Phylogenetic analysis showed that NlCPSF30 is closely related to CPSF30 proteins from other hemipteran species. Expression analysis indicated that NlCPSF30 is most highly expressed in the fat body and during the adult stage, with significantly higher expression in females than in males. RNAi-mediated silencing of NlCPSF30 in third-instar nymphs resulted in severe phenotypic abnormalities, including disrupted molting and increased mortality following injection of double-stranded RNA (dsRNA) targeting NlCPSF30. Moreover, it influenced the expression of genes associated with hormone regulation, namely NlHry, NlE93, and NlKr-h1. These results suggest that NlCPSF30 is integral to critical physiological processes, with its disruption leading to increased mortality. Our findings identify NlCPSF30 as an essential gene for N. lugens’ survival and a promising target for RNAi-based pest management strategies. This study provides a valuable molecular target and theoretical insights for developing RNAi-based control methods against N. lugens.
Identification of Land and Potential Production of Willow Biomass Crops Using a Multi-Criteria Land Suitability Assessment
Authors: Hossain Md Sahadat , Volk Timothy A.
Published: November 2024

The New York State (NYS) Climate Act aims for net-zero emissions across all economic sectors by 2050, with renewable biofuels playing a key role in this transition. Approximately half of the biomass required for these biofuels is expected to come from purpose-grown sources like willow. To address this demand, we assessed land availability and biomass production potential for willow using a GIS-based fuzzy logic Land Suitability Assessment (LSA) model under three land scenarios: (1) including all cropland, (2) excluding conventional crops, and (3) excluding any cropland. Our findings show that NYS has the potential for between 1.07 and 1.59 million ha for willow cultivation, capable of producing 14.0 to 20.6 million dry Mg of biomass annually. Grassland/pasture accounts for 32–51%, and herbaceous cover for 32–48% of the potential areas. Between 33% and 53% of the area identified was in parcels that were 2–20 ha in size. These results highlight the considerable potential for purpose-grown biomass in NYS, supporting the state’s decarbonization goals and renewable energy transition.
Molecular Evolution and Adaptation Strategies in Marine Ciliates: An Inspiration for Cold-Adapted Enzyme Engineering and Drug Binding Analysis
Authors: Pucciarelli Sandra , Mozzicafreddo Matteo , Vassallo Alberto , Piersanti Angela , Miceli Cristina
Published: November 2024

In the present review, we summarize genome mining of genomic data obtained from the psychrophilic Antarctic marine ciliate Euplotes focardii and its evolutionary-close mesophilic cosmopolitan counterpart E. crassus. This analysis highlights adaptation strategies that are unique to the Antarctic ciliate, including antioxidant gene duplication and distinctive substitutions that may play roles in increased drug binding affinity and enzyme reaction rate in cold environments. Enzymes from psychrophiles are usually characterized by high activities and reaction rates at low temperatures compared with their counterparts from mesophiles and thermophiles. As a rule, catalyst cold activity derives from an increased structural flexibility that may lead to protein denaturation in response to temperature fluctuation. Molecular thermolability has been a major drawback of using macromolecules from psychrophiles in industrial applications. Here, we report a case study in which the role of peculiar amino acid substitution in cold adaptation is demonstrated by site-directed mutagenesis. Combined with a rational design approach, these substitutions can be used for site-directed mutagenesis to obtain cold-active catalysts that are structurally stable. Furthermore, molecular docking analysis of β-tubulin isotypes extrapolated from E. focardii and E. crassus genomes allowed us to obtain additional insight on the taxol binding site and drug affinity. E. focardii genome mining and the comparison with the mesophilic sibling counterpart can be used as an inspiration for molecular engineering for medical and industrial applications.
Efficient Simultaneous Isolation of Pinostrobin and Panduratin A from Boesenbergia rotunda Using Centrifugal Partition Chromatography
Authors: Eiamart Wanna , Wittayalertpanya Supeecha , Tadtong Sarin , Samee Weerasak
Published: November 2024

The bioactive flavonoids pinostrobin (PN) and panduratin A (PA) from Boesenbergia rotunda are essential for research and therapeutic applications. This study introduces an innovative method utilizing ultrasound-assisted extraction with n-hexane pre-treatment, followed by one-step centrifugal partition chromatography (CPC) purification. Extraction efficiency was evaluated using ultra high-performance liquid chromatography (UHPLC), and the isolated compounds were characterized through 1H-NMR and liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS), adhering to AOAC validation guidelines. Optimal extraction conditions comprised a particle size of 125 μm, a solid-to-liquid ratio of 1:30 g/mL, and a 10 min extraction time, yielding a crude extract of 6.96 ± 0.07%. Using an n-hexane/MeOH/water (5/3.4/1.6, v/v) solvent system in ascending mode, PN (2.16 mg, 98.78% purity) and PA (0.4 mg, 99.69% purity) were isolated from 67 mg of crude extract within 30 min. This streamlined approach enhances purification efficiency, allowing for faster extraction and higher purity, making it a suitable method for commercial applications.
Azobenzene as an Effective Ligand in Europium Chemistry—A Synthetic and Theoretical Study
Authors: Allis Damian G. , Torvisco Ana , Webb Cody C. , Gillett-Kunnath Miriam M. , Ruhlandt-Senge Karin
Published: November 2024

The preparation and characterization of two novel europium–azobenzene complexes that demonstrate the effectiveness of this ligand for stabilizing reactive, redox-active metals are reported. With the family of rare earth metals receiving attention due to their potential as catalysts, critical components in electronic devices, and, more recently, in biomedical applications, a detailed understanding of factors contributing to their coordination chemistry is of great importance for customizing their stability and reactivity. This study introduces azobenzene as an effective nonprotic ligand system that provides novel insights into rare earth metal coordination preferences, including factors contributing to the coordinative saturation of the large, divalent europium centers. The two compounds demonstrate the impact of the solvent donors (tetrahydrofuran (THF) and dimethoxyethane (DME)) on the overall coordination chemistry of the target compounds. Apart from the side-on coordination of the doubly-reduced azobenzene and the anticipated N-N bond elongation due to decreased bond order, the two compounds demonstrate the propensity of the europium centers towards limited metal-π interactions. The target compounds are available by direct metallation in a straightforward manner with good yields and purity. The compounds demonstrate the utility of the azobenzene ligands, which may function as singly- or doubly-reduced entities in conjunction with redox-active metals. An initial exploration into the computational modeling of these and similar complexes for subsequent property prediction and optimization is performed through a methodological survey of structure reproduction using density functional theory.