bluuebunny/crossref_metadata_2025 huggingface dataset:
Enzymatic Assembly of Chitosan-Based Network Polysaccharides and Their Encapsulation and Release of Fluorescent Dye
Authors: Totani Masayasu , Nakamichi Aina , Kadokawa Jun-ichi
Published: April 2024

We prepared network polysaccharide nanoscopic hydrogels by crosslinking water-soluble chitosan (WSCS) with a carboxylate-terminated maltooligosaccharide crosslinker via condensation. In this study, the enzymatic elongation of amylose chains on chitosan-based network polysaccharides by glucan phosphorylase (GP) catalysis was performed to obtain assembly materials. Maltoheptaose (Glc7) primers for GP-catalyzed enzymatic polymerization were first introduced into WSCS by reductive amination. Crosslinking of the product with the above-mentioned crosslinker by condensation was then performed to produce Glc7-modified network polysaccharides. The GP-catalyzed enzymatic polymerization of the α-d-glucose 1-phosphate monomer from the Glc7 primers on the network polysaccharides was conducted, where the elongated amylose chains formed double helices. Enzymatic disintegration of the resulting network polysaccharide assembly successfully occurred by α-amylase-catalyzed hydrolysis of the double helical amyloses. The encapsulation and release of a fluorescent dye, Rhodamine B, using the CS-based network polysaccharides were also achieved by means of the above two enzymatic approaches.
Sarcopenia Identification Using Alternative Vertebral Landmarks in Individuals with Lung Cancer
Authors: Byrne Cecily A. , Fantuzzi Giamila , Stephan Jeremy T. , Kim Sage , Oddo Vanessa M. , Koh Timothy J. , Gomez Sandra L.
Published: April 2024

(1) Background: Sarcopenia, or low skeletal mass index (SMI), contributes to higher lung cancer mortality. The SMI at third lumbar vertebrae (L3) is the reference standard for body composition analysis. However, there is a need to explore the validity of alternative landmarks in this population. We compared the agreement of sarcopenia identification at the first lumbar (L1) and second lumbar (L2) to L3 in non-Hispanic Black (NHB) and White (NHW) individuals with lung cancer. (2) Methods: This retrospective, cross-sectional study included 214 NHB and NHW adults with lung cancer. CT scans were analyzed to calculate the SMI at L1, L2, and L3. T-tests, chi-square, Pearson’s correlation, Cohen’s kappa, sensitivity, and specificity analysis were used. (3) Results: Subjects presented with a mean age of 68.4 ± 9.9 years and BMI of 26.3 ± 6.0 kg/m2. Sarcopenia prevalence varied from 19.6% at L1 to 39.7% at L3. Cohen’s kappa coefficient was 0.46 for L1 and 0.64 for L2, indicating weak and moderate agreement for the identification of sarcopenia compared to L3. (4) Conclusions: Sarcopenia prevalence varied greatly depending on the vertebral landmark used for assessment. Using L2 or L1 alone resulted in a 16.8% and 23.8% misclassification of sarcopenia in this cohort of individuals with lung cancer.
Carbon Nanodisks Decorated with Guanidinylated Hyperbranched Polyethyleneimine Derivatives as Efficient Antibacterial Agents
Authors: Lyra Kyriaki-Marina , Tournis Ioannis , Subrati Mohammed , Spyrou Konstantinos , Papavasiliou Aggeliki , Athanasekou Chrysoula , Papageorgiou Sergios , Sakellis Elias , Karakassides Michael A. , Sideratou Zili
Published: April 2024

Non-toxic carbon-based hybrid nanomaterials based on carbon nanodisks were synthesized and assessed as novel antibacterial agents. Specifically, acid-treated carbon nanodisks (oxCNDs), as a safe alternative material to graphene oxide, interacted through covalent and non-covalent bonding with guanidinylated hyperbranched polyethyleneimine derivatives (GPEI5K and GPEI25K), affording the oxCNDs@GPEI5K and oxCNDs@GPEI25K hybrids. Their physico-chemical characterization confirmed the successful and homogenous attachment of GPEIs on the surface of oxCNDs, which, due to the presence of guanidinium groups, offered them improved aqueous stability. Moreover, the antibacterial activity of oxCNDs@GPEIs was evaluated against Gram-negative E. coli and Gram-positive S. aureus bacteria. It was found that both hybrids exhibited enhanced antibacterial activity, with oxCNDs@GPEI5K being more active than oxCNDs@GPEI25K. Their MIC and MBC values were found to be much lower than those of oxCNDs, revealing that the GPEI attachment endowed the hybrids with enhanced antibacterial properties. These improved properties were attributed to the polycationic character of the oxCNDs@GPEIs, which enables effective interaction with the bacterial cytoplasmic membrane and cell walls, leading to cell envelope damage, and eventually cell lysis. Finally, oxCNDs@GPEIs showed minimal cytotoxicity on mammalian cells, indicating that these hybrid nanomaterials have great potential to be used as safe and efficient antibacterial agents.
Non-Volatile Memory Based on ZnO Thin-Film Transistor with Self-Assembled Au Nanocrystals
Authors: Xie Hui , Wu Hao , Liu Chang
Published: April 2024

Non-volatile memory based on thin-film transistor is crucial for system-on-panel and flexible electronic systems. Achieving high-performance and reliable thin-film transistor (TFT) memory still remains challenging. Here, for the first time, we present a ZnO TFT memory utilizing self-assembled Au nanocrystals with a low thermal budget, exhibiting excellent memory performance, including a program/erase window of 9.8 V, 29% charge loss extrapolated to 10 years, and remarkable endurance characteristics. Moreover, the memory exhibits favorable on-state characteristics with mobility, subthreshold swing, and current on–off ratio of 17.6 cm2V−1s−1, 0.71 V/dec, and 107, respectively. Our study shows that the fabricated TFT memory has great potential for practical applications.
Elastic Liposomes Containing Calcium/Magnesium Ferrite Nanoparticles Coupled with Gold Nanorods for Application in Photothermal Therapy
Authors: Pacheco Ana Rita F. , Barros Ana Margarida , Amorim Carlos O. , Amaral Vítor S. , Coutinho Paulo J. G. , Rodrigues Ana Rita O. , Castanheira Elisabete M. S.
Published: April 2024

This work reports on the design, development, and characterization of novel magneto-plasmonic elastic liposomes (MPELs) of DPPC:SP80 (85:15) containing Mg0.75Ca0.25Fe2O4 nanoparticles coupled with gold nanorods, for topical application of photothermal therapy (PTT). Both magnetic and plasmonic components were characterized regarding their structural, morphological, magnetic and photothermal properties. The magnetic nanoparticles display a cubic shape and a size (major axis) of 37 ± 3 nm, while the longitudinal and transverse sizes of the nanorods are 46 ± 7 nm and 12 ± 1.6 nm, respectively. A new methodology was employed to couple the magnetic and plasmonic nanostructures, using cysteine as bridge. The potential for photothermia was evaluated for the magnetic nanoparticles, gold nanorods and the coupled magnetic/plasmonic nanoparticles, which demonstrated a maximum temperature variation of 28.9 °C, 33.6 °C and 37.2 °C, respectively, during a 30 min NIR-laser irradiation of 1 mg/mL dispersions. Using fluorescence anisotropy studies, a phase transition temperature (Tm) of 35 °C was estimated for MPELs, which ensures an enhanced fluidity crucial for effective crossing of the skin layers. The photothermal potential of this novel nanostructure corresponds to a specific absorption rate (SAR) of 616.9 W/g and a maximum temperature increase of 33.5 °C. These findings point to the development of thermoelastic nanocarriers with suitable features to act as photothermal hyperthermia agents.
Energy Efficiency Analysis of a Deformable Wave Energy Converter Using Fully Coupled Dynamic Simulations
Authors: Luo Chen , Huang Luofeng
Published: April 2024

Deformable wave energy converters have significant potential for application as flexible material that can mitigate structural issues, while how to design the dimensions and choose an optimal deployment location remain unclear. In this paper, fully coupled computational fluid dynamics and computational solid mechanics were used to simulate the dynamic interactions between ocean waves and a deformable wave energy converter. The simulation results showed that the relative length to wave, deployment depth and aspect ratio of the device have significant effects on the energy conversion efficiency. By calculating the energy captured per unit width of the device, the energy efficiency was found to be up to 138%. The optimal energy conversion efficiencies were achieved when the structure length was 0.25, 0.5 or 0.75 of the dominating wavelength and submerged at a corresponding suitable depth. The aspect ratio and maximum stress inside the wave energy converter showed a nonlinear trend, with potential optimal points revealed. The simulation approach and results support the future design and optimisation of flexiable wave energy converters or other marine structures with notable deformations.
Micro–Nanoplastics as Potential Carriers of Dioxins and Toxoplasma gondii in Patients with Carotid Atheromas
Authors: Di Guardo Giovanni
Published: April 2024

A recent major study has shown that there is an increased risk of myocardial infarction, stroke and lethal outcomes in patients affected by carotid atheromas that contain micro-nanoplastics (MNPs) compared to subjects that do not have MNPs in their lesions [...]
Evaluating the Impact of Practical Training: A Study on Satisfaction and Drug Knowledge among Pharmacy Students
Authors: Wakui Nobuyuki , Shirozu Shunsuke , Machida Yoshiaki
Published: April 2024

Practical training stands as a crucial component in shaping pharmacy students, bridging the gap between classroom-based theoretical knowledge and its application in real-world contexts. This study investigates the correlation between the satisfaction levels experienced during practical training and the acquisition of knowledge, particularly focusing on drug names. Drawing from the National DataBase (NDB) open data provided by Japan’s Ministry of Health, Labour and Welfare, a survey centered on the top 100 dispensed drugs was crafted. A correlation analysis was conducted between the satisfaction scores gathered from students and their depth of knowledge on drug names. Intriguingly, despite observing a significantly high satisfaction level during the practical training, there was no marked correlation between this satisfaction and the proficiency in recalling drug names after the training. Furthermore, the volume of daily prescriptions handled did not significantly impact this knowledge. The findings underscore the notion that high satisfaction during training does not necessarily guarantee a thorough understanding of the subject matter. This sheds light on the importance of not solely relying on satisfaction metrics in training programs and ensuring a holistic, in-depth educational approach.
Effects of Squeezing on the Power Broadening and Shifts of Micromaser Lineshapes
Authors: Hernández-Sánchez Leonardi , Ramos-Prieto Irán , Soto-Eguibar Francisco , Moya-Cessa Héctor Manuel
Published: April 2024

AC Stark shifts have an impact on the dynamics of atoms interacting with a near-resonant quantized single-mode cavity field, which is relevant to a single atom micromaser. In this study, we demonstrate that, when the field is in a squeezed coherent state, atomic lineshapes are highly sensitive to the squeezing parameter. Furthermore, we show that, when considering a superposition of squeezed coherent states with equal amplitude, the displacement of the transition lines depends significantly, not only on the squeezing parameter, but also on its sign.
Structural, Mechanical, and Optoelectronic Properties of CH3NH3PbI3 as a Photoactive Layer in Perovskite Solar Cell
Authors: Rugut Elkana K. , Maluta Nnditshedzeni E. , Maphanga Regina R. , Mapasha Refilwe E. , Kirui Joseph K.
Published: April 2024

The structural, electronic, mechanical, and optical properties of pseudo-cubic CH3NH3PbI3 perovskite have been studied within the framework of density functional theory, in line with solar cell applications. The computed values of lattice and elastic constants concurred with the available theoretical and experimental data. This compound has a semi-conducting behavior, with a direct band gap of about 1.49 eV. Note that the solar radiation spectrum has a maximum energy intensity value of approximately 1.50 eV. Thus, semiconductors with such gaps are preferred for photovoltaic applications. Its elastic parameters reveal that it is a ductile material that is mechanically stable. Optical descriptors such as refractive index, reflectivity, extinction, energy loss, and absorption have been explored with the aim of establishing the optical features of the material. Our findings demonstrate that this perovskite is suitable for solar cell applications based on the size and nature of the band gap, as also supported by the obtained upper limit value of simulated power conversion efficiency via the spectroscopic limited maximum efficiency mathematical model.
Thermally-Activated Shape Memory Behavior of Biodegradable Blends Based on Plasticized PLA and Thermoplastic Starch
Authors: Sessini Valentina , Salaris Valentina , Oliver-Cuenca Victor , Tercjak Agnieszka , Fiori Stefano , López Daniel , Kenny José M. , Peponi Laura
Published: April 2024

Biodegradable blends based on plasticized poly(lactic acid) PLA and thermoplastic starch (TPS) have been obtained. The influence of the PLA plasticizer as a compatibility agent has been studied by using two different plasticizers such as neat oligomeric lactic acid (OLA) and functionalized with maleic acid (mOLA). In particular, the morphological, thermal, and mechanical properties have been studied as well as the shape memory ability of the melt-processed materials. Therefore, the influence of the interaction between different plasticizers and the PLA matrix as well as the compatibility between the two polymeric phases on the thermally-activated shape memory properties have been studied. It is very interesting to use the same additive able to act as both plasticizer and compatibilizer, decreasing the glass transition temperature of PLA to a temperature close to the physiological one, obtaining a material suitable for potential biomedical applications. In particular, we obtain that OLA-plasticized blend (oPLA/TPS) show very good thermally-activated capability at 45 °C and 50% deformation, while the blend obtained by using maleic OLA (moPLA/TPS) did not show shape memory behavior at 45 °C and 50% deformation. This fact is due to their morphological changes and the loss of two well-distinguished phases, one acting as fixed phase and the other one acting as switching phase to typically obtain shape memory response. Therefore, the thermally-activated shape memory results show that it is very important to make a balance between plasticizer and compatibilizer, considering the need of two well-established phases to obtain shape memory response.
Decision Intelligence-Based Predictive Modelling of Hard Rock Pillar Stability Using K-Nearest Neighbour Coupled with Grey Wolf Optimization Algorithm
Authors: Kamran Muhammad , Chaudhry Waseem , Taiwo Blessing Olamide , Hosseini Shahab , Rehman Hafeezur
Published: April 2024

Pillar stability is of paramount importance in ensuring the safety of underground rock engineering structures. The stability of pillars directly influences the structural integrity of the mine and mitigates the risk of collapses or accidents. Therefore, assessing pillar stability is crucial for safe, productive, reliable, and profitable underground mining engineering processes. This study developed the application of decision intelligence-based predictive modelling of hard rock pillar stability in underground engineering structures using K-Nearest Neighbour coupled with the grey wolf optimization algorithm (KNN-GWO). Initially, a substantial dataset consisting of 236 different pillar cases was collected from seven underground hard rock mining engineering projects. This dataset was gathered by considering five significant input variables, namely pillar width, pillar height, pillar width/height ratio, uniaxial compressive strength, and average pillar stress. Secondly, the original hard rock pillar stability level has been classified into three types: failed, unstable, and stable, based on the pillar’s instability mechanism and failure process. Thirdly, several visual relationships were established in order to ascertain the correlation between input variables and the corresponding pillar stability level. Fourthly, the entire pillar database was randomly divided into a training dataset and testing dataset with a 70:30 sampling method. Moreover, the (KNN-GWO) model was developed to predict the stability of pillars in hard rock mining. Lastly, the performance of the suggested predictive model was evaluated using accuracy, precision, recall, F1-score, and a confusion matrix. The findings of the proposed model offer a superior benchmark for accurately predicting the stability of hard rock pillars. Therefore, it is recommended to employ decision intelligence models in mining engineering in order to effectively prioritise safety measures and improve the efficiency of operational processes, risk management, and decision-making related to underground engineering structures.
Nitrogen Fixation via Plasma-Assisted Processes: Mechanisms, Applications, and Comparative Analysis—A Comprehensive Review
Authors: Klimek Angelique , Piercey Davin G.
Published: April 2024

Nitrogen fixation, the conversion of atmospheric nitrogen into biologically useful compounds, is crucial for sustaining biological processes and industrial productivity. Recent advances have explored plasma-assisted processes as an innovative approach to facilitate nitrogen fixation. This review offers a comprehensive summary of the development, current state of the art, and potential future applications of plasma-based nitrogen fixation. The analysis encompasses fundamental principles, mechanisms, advantages, challenges, and prospects associated with plasma-induced nitrogen fixation.
Implementations of Digital Transformation and Digital Twins: Exploring the Factory of the Future
Authors: Rahmani Ramin , Jesus Cristiano , Lopes Sérgio I.
Published: April 2024

In the era of rapid technological advancement and evolving industrial landscapes, embracing the concept of the factory of the future (FoF) is crucial for companies seeking to optimize efficiency, enhance productivity, and stay sustainable. This case study explores the concept of the FoF and its role in driving the energy transition and digital transformation within the automotive sector. By embracing advancements in technology and innovation, these factories aim to establish a smart, sustainable, inclusive, and resilient growth framework. The shift towards hybrid and electric vehicles necessitates significant adjustments in vehicle components and production processes. To achieve this, the adoption of lighter materials becomes imperative, and new technologies such as additive manufacturing (AM) and artificial intelligence (AI) are being adopted, facilitating enhanced efficiency and innovation within the factory environment. An important aspect of this paradigm involves the development and utilization of a modular, affordable, safe human–robot interaction and highly performant intelligent robot. The introduction of this intelligent robot aims to foster a higher degree of automation and efficiency through collaborative human–robot environments on the factory floor and production lines, specifically tailored to the automotive sector. By combining the strengths of human and robotic capabilities, the future factory aims to revolutionize manufacturing processes, ultimately driving the automotive industry towards a more sustainable and technologically advanced future. This study explores the implementation of automation and the initial strides toward transitioning from Industry 4.0 to 5.0, focusing on three recognized, large, and automotive companies operating in the north of Portugal.
Simulation and Control Strategies for Longitudinal Propagation of Acid Fracture in a Low-Permeability Reservoir Containing Bottom Water
Authors: Li Song , Fan Yu , Guo Yujie , Wang Yang , He Tingting , Zhang Hua , Ye Jiexiao , Chen Weihua , Zhang Xi
Published: April 2024

The reservoir in the Anyue gas field, located in the Sichuan basin of China, belongs to the second member of the Dengying formation and has distinctive geological features. It is characterized by strong heterogeneity, low porosity, low permeability, and locally developed natural fractures. The reservoir space consists primarily of corrosion holes, natural fractures, and similar voids. Moreover, the lower reservoir exhibits high water saturation and a homogeneous bottom-water interface. Since it is a carbonate-based hydrocarbon reservoir with low porosity and permeability, deep acid fracturing has proven to be an efficient method for enhancing individual well production. However, the reconstruction of the second member of the Dengying formation reservoir poses significant challenges. The reservoir contains high-angle natural fractures, small vertical stress differences, and is located in close proximity to the gas–water interface. As a result, it becomes difficult to control the height of the acid break. Improper acid break treatment may easily result in water production affecting gas well production. To explore ways to control the longitudinal extension of acid fractures, 3D numerical models focusing on the initiation and expansion of acid fractures have been developed. This model takes into account geological and engineering factors such as stress differences, acid fracture displacements and scales, and their effects on the longitudinal extension of acid fractures. It was revealed that the pressure difference is the main controlling factor for the acid fracture height, followed by the reservoir thickness, the interlayer thickness, and the viscosity of the working fluid. Technical countermeasures for controlled fracture and high-acid fracturing tailored to different reservoir characteristics have been proposed, and design parameters for controlled fracture and high-acid fracturing can be optimized. By effectively controlling the vertical extension of the acid fracture, it is possible to maximize production from a single well while avoiding interference from the lower water layer. This study provides theoretical guidance for the application of deep-acid-fracturing techniques in low-permeability bottom-water gas reservoirs.
A Deep Learning Approach Based on Novel Multi-Feature Fusion for Power Load Prediction
Authors: Xiao Ling , An Ruofan , Zhang Xue
Published: April 2024

Adequate power load data are the basis for establishing an efficient and accurate forecasting model, which plays a crucial role in ensuring the reliable operation and effective management of a power system. However, the large-scale integration of renewable energy into the power grid has led to instabilities in power systems, and the load characteristics tend to be complex and diversified. Aiming at this problem, this paper proposes a short-term power load transfer forecasting method. To fully exploit the complex features present in the data, an online feature-extraction-based deep learning model is developed. This approach aims to extract the frequency-division features of the original power load on different time scales while reducing the feature redundancy. To solve the prediction challenges caused by insufficient historical power load data, the source domain model parameters are transferred to the target domain model utilizing Kendall’s correlation coefficient and the Bayesian optimization algorithm. To verify the prediction performance of the model, experiments are conducted on multiple datasets with different features. The simulation results show that the proposed model is robust and effective in load forecasting with limited data. Furthermore, if real-time data of new energy power systems can be acquired and utilized to update and correct the model in future research, this will help to adapt and integrate new energy sources and optimize energy management.
Development and Process Optimization of a Steamed Fish Paste Cake Prototype for Room Temperature Distribution
Authors: Lee Jin-Hwa , Kang Sang In , Mansoor Sana , Lee Inhwan , Kim Do Youb , Kim Ye Youl , Park Yongjoon , Sohn Jae-Hak , Bashir Khawaja Muhammad Imran , Choi Jae-Suk
Published: April 2024

Surimi-based products typically demand cold storage and a cold chain distribution system, which not only affects their physical properties and flavor but also escalates production costs. In this study, we introduced a novel high-temperature and high-pressure retort processing method to enable room temperature storage and distribution of a surimi-based product, a fish paste cake. Our optimization efforts focused on refining the processing conditions for the fish paste cake. This included incorporating transglutaminase, sugar additives, natural herbal or seaweed extracts, and optimizing retort processing conditions to enhance textural properties, minimize browning and off flavor, and extend the shelf-life of the product. Our results demonstrated that the addition of 0.3% ACTIVA TG-K, 1.0% trehalose, and 0.5% sea tangle extract during the production process significantly enhanced the gel strength, minimized browning, and improved the overall flavor of the fish paste cake prototype. Importantly, the developed prototype exhibited favorable biochemical, textual, nutritional, and sensory properties, extending the shelf-life up to 160 days without compromising physical, chemical, or sensory attributes. In addition, the developed prototype exhibited improved elasticity, compared to control groups. The innovative process not only facilitates room temperature storage and distribution of surimi-based products but also holds potential for generating additional profits.
Research on the Analysis of and Countermeasures for the Eutrophication of Water Bodies: Waihu Reservoir as a Case Study
Authors: Qi Yiting , Cao Xin , Cao Ruisi , Cao Mingjie , Yan Ailan , Li Erpeng , Xu Dong
Published: April 2024

Water quality deterioration and eutrophication have become a global concern, while reservoir pollution caused by multiple factors has led to frequent algal blooms, posing a serious threat to rural drinking water security and urban water supply. The purpose of this paper is to analyze the current water quality of Waihu Reservoir and use the single index method, the weighted comprehensive scoring method, and the nutrient level index method (TLI) to evaluate eutrophication. On this basis, the pollution sources of the reservoir are comprehensively analyzed and discussed, and effective control strategies are proposed. The evaluation results indicate that the reservoir is of moderate eutrophication type. Therefore, reducing the input of nutrients such as nitrogen and phosphorus in water is the main goal of alleviating exogenous pollution. The combination of engineering intervention and ecological restoration strategies to remove nutrients from the aquatic environment is an effective strategy to manage endogenous pollution. From the point of view of the source of pollution, this study provides an in-depth analysis of exogenous and endogenous pollution, respectively, and the proposed treatment is instructive for the control and routine management of eutrophication in the Waihu Reservoir, as well as for the management of similar problems in different reservoirs.
Diesel Adulteration Detection with a Machine Learning-Enhanced Laser Sensor Approach
Authors: Mourched Bachar , AlZoubi Tariq , Vrtagic Sabahudin
Published: April 2024

This paper introduces a novel and cost-effective method for detecting adulterated diesel, specifically targeting contamination with kerosene, by leveraging machine learning and the refractive index values of mixed diesel samples. It proposes a laser-based sensor, employing COMSOL simulations for synthetic data generation to facilitate machine learning training. This innovative approach not only streamlines the detection process by eliminating the need for expensive equipment and specialized personnel but also enables on-site testing without extensive sample preparation. The sensor’s design, utilizing light refraction and reflection principles, allows for the accurate measurement of diesel adulteration levels. Validation results showcase the machine learning models’ high precision in predicting adulteration percentages, as evidenced by an R-squared value of 0.999 and a mean absolute error of 0.074. This research signifies a leap in sensor technology, offering a practical solution for rapid diesel adulteration detection, especially in developing countries, by minimizing reliance on advanced laboratory analyses. The sensor’s design aligns with the requirements for low-cost IoT technology, presenting a versatile tool for various applications.
Mind the Psychedelic Hype: Characterizing the Risks and Benefits of Psychedelics for Depression
Authors: Meling Daniel , Ehrenkranz Rebecca , Nayak Sandeep M. , Aicher Helena D. , Funk Xaver , van Elk Michiel , Graziosi Marianna , Bauer Prisca R. , Scheidegger Milan , Yaden David B.
Published: April 2024

Rationale: Psychedelic research re-emerged from a period of suppression into the so-called psychedelic renaissance. In parallel, most media reporting has shifted from the overstatement of the risks of psychedelics to overly positive hype. As the empirical evidence is more equivocal than frequently portrayed, the conclusions about the effectiveness of psychedelics should be considered preliminary. Poor science communication about psychedelics’ therapeutic potential may lead potential participants or patients to feel misled and policy decisions to be misinformed. An evidence-informed characterization of their risks and benefits is needed. Objectives: This article assesses the state of psychedelic research for treating depression and the effect sizes of psychedelics on therapeutic outcomes, the risk of bias, and the prevalence of adverse effects. We review research on the risks and benefits of psychedelics and discuss how the following depression treatments have shown decreasing effect sizes over time: (1) cognitive behavioral therapy, (2) mindfulness interventions, (3) selective serotonin reuptake inhibitors, and (4) ketamine. We speculate that a similar trend may occur for psychedelic treatments. Results and conclusions: It is likely that larger and better-controlled psychedelic trials will demonstrate smaller effect sizes that are more comparable to other conventional and emerging treatments for mood disorders. Clear science communication is critical for setting public expectations and psychedelic policy. With this evidence-based assessment, we aim to cut through the misinformation about the benefits, risks, and future prospects of psychedelic treatments.
Synodality and Its Implications for Catholic Schools: An Exploratory Study of System Leaders in Western Canadian Catholic Schools
Authors: Hoven Matt , Pagnotta-Kowalczyk Eugenia , Sarnecki Dean
Published: April 2024

Pope Francis’s dream for a synodal Church has implications for Catholic schools globally, but what exactly are these consequences? This paper explores Francis’s vision in the context of Canadian Catholic schools in Alberta, Saskatchewan, and the Northwest Territories (NWT), where these schools are fully-funded by the government and enroll nearly a quarter million students. Ten exploratory interviews with chief superintendents from these schools—which formed the basis of a larger study—were analyzed to understand potential connections to Francis’s vision and his four commitments to synodality: focusing on relationships, a culture of encounter, the essentials of the Christian faith, and local decision-making. The pope differentiates synodality from democratic forms of leadership and demands a communal form of listening and discerning God’s Spirit. While the superintendents’ style of leadership appeared to mirror synodality in many ways, predominant issues remain to be explored: an emphasis on relationships upends the status quo and gives new directions for the schools; encountering others will inevitably demand prophetic leadership by the system leaders; leading with the essentials of faith will not please everyone in Catholic schooling; and shared authority among the superintendents, bishops, and trustees requires further dialogue.
Development and Application of a High-Precision Portable Digital Compass System for Improving Combined Navigation Performance
Authors: Zhang Songhao , Cui Min , Zhang Peng
Published: April 2024

There are not many high-precision, portable digital compass solutions available right now that can enhance combined navigation systems’ overall functionality. Additionally, there is a dearth of writing about these products. This is why a tunnel magnetoresistance (TMR) sensor-based high-precision portable digital compass system is designed. First, the least-squares method is used to compensate for compass inaccuracy once the ellipsoid fitting method has corrected manufacturing and installation errors in the digital compass system. Second, the digital compass’s direction angle data is utilized to offset the combined navigation system’s mistake. The final objective is to create a high-performing portable TMR digital compass system that will enhance the accuracy and stability of the combined navigation system (abbreviated as CNS). According to the experimental results, the digital compass’s azimuth accuracy was 4.1824° before error compensation and 0.4580° after it was applied. The combined navigation system’s path is now more accurate overall and is closer to the reference route than it was before the digital compass was added. Furthermore, compared to the combined navigation route without the digital compass, the combined navigation route with the digital compass included is more stable while traveling through the tunnel. It is evident that the digital compass system’s design can raise the integrated navigation system’s accuracy and stability. The integrated navigation system’s overall performance may be somewhat enhanced by this approach.
Effects of Marquandomyces marquandii SGSF043 on Maize Growth Promotion and Soil Enzyme Activity
Authors: Zheng Xu , Zhang Bo , Shi Feng , Chen Yuanlong , Zhao Xiumei
Published: April 2024

In order to further clarify the growth-promoting effect of the non-core Metarhizium sp. Marquandomyces marquandii on plants, M. marquandii SGSF043, which was obtained via pre-screening in the laboratory, was selected as a test strain and the seed soaking method was adopted. The effects of a fermentation broth obtained from this strain on the seed germination, seedling growth, and rhizosphere soil enzyme activity of maize were studied. The results were as follows: In seed germination tests, M. marquandii SGSF043 fermentation liquid had a certain inhibitory effect on corn seed germination, and the germination rate was only 15%. When the fermentation solution was diluted 10 times, the germination rate reached 97%. After the germination test, the growth of maize plumules was promoted in the groups treated with 10-times and 1000-times dilutions. In the field community experiment, based on the comprehensive evaluation of seedling biomass indicators, the solution diluted 100 times had the best growth-promoting effect. The aboveground fresh weight was increased by 127.13% compared with the control group. The results show that M. marquandii SGSF043 has the potential to promote the growth of maize and improve the soil environment, which provides a theoretical basis for the research on and the application of M. marquandii in farmland.
Learning with Errors: A Lattice-Based Keystone of Post-Quantum Cryptography
Authors: Sabani Maria E. , Savvas Ilias K. , Garani Georgia
Published: April 2024

The swift advancement of quantum computing devices holds the potential to create robust machines that can tackle an extensive array of issues beyond the scope of conventional computers. Consequently, quantum computing machines create new risks at a velocity and scale never seen before, especially with regard to encryption. Lattice-based cryptography is regarded as post-quantum cryptography’s future and a competitor to a quantum computer attack. Thus, there are several advantages to lattice-based cryptographic protocols, including security, effectiveness, reduced energy usage and speed. In this work, we study the learning with errors (LWE) problem and the cryptosystems that are based on the LWE problem and, in addition, we present a new efficient variant of LWE cryptographic scheme.
Rectal Spacer Reduces Gastrointestinal Side Effects of Radiation Post Radical Prostatectomy
Authors: Hong Anne , Bolton Damien , Pham Trung , Angus David , Pan David , Joon Daryl Lim , Tan Alwin , McMillan Kevin , Chan Yee , Manohar Paul , Thomas Joe , Ho Huong , Orio Peter , Holt Emily , Cokelek Margaret , Lawrentschuk Nathan , Foroudi Farshad , Chao Michael
Published: April 2024

Objectives: Our objective was to assess the rate of complications and gastrointestinal adverse effects of rectal spacer insertion for salvage post prostatectomy radiation therapy. Methods: A retrospective observational study was performed. Between September 2018 and March 2022, 64 post-radical prostatectomy patients who were planned for salvage radiation therapy received a rectal spacer. The selected patients were those who had nerve-sparing prostatectomy with intrafascial or interfascial dissections (where Denonvillier’s fascia is retained). Radiation dose to the rectal wall and gastrointestinal symptoms were assessed. Symptoms were graded using the National Cancer Center Institute Common Terminology Criteria for Adverse Events v4.0 grading scheme. A total of 39 patients had pre-spacer planning computer tomography (CT) scans, and the rectal dose before and after the spacer insertion was calculated. Comparisons were made using the Student’s t-test, with a p-value < 0.05 representing statistical significance. Finally, clinicians were surveyed to rate the ease of the procedure using a 5-point Likert scale of 1 to 5 (1: very difficult, 2: difficult, 3: moderate, 4: easy, 5: very easy). Results: A total of 64 patients successfully underwent rectal spacer insertion. The mean age was 64.4 years (standard deviation: 5.7 years). After a median of 14 months’ (range 6 to 35) follow up, acute grade 1 and above gastrointestinal (GI) toxicities were seen in 28% of patients (grade 2 in 1.5%), and late grade 1 and above GI toxicities were seen in 12% of patients (grade 2 in 1.5%). Amongst the 39 patients with pre-spacer planning CT images, the volume of the rectum receiving 60%, 70%, 80%, 90%, and 100% of the prescribed radiation dose was reduced by 25.9%, 34.2%, 35.4%, 43.7%, and 61.7%, respectively. All dose reductions were statistically significant. The procedure was rated as “easy” or “very easy” to perform in 56% of cases. Conclusions: The insertion of a rectal spacer in selected patients undergoing PPRT is feasible and safe and significantly improves rectal wall radiation dosimetry in salvage post prostatectomy radiation therapy. It was accomplished in >95% of patients, increasing vesico-rectal separation from ‘immediate vicinity’ to 11 mm without any post-operative complications in experienced hands. In addition, it achieved significant reduction in rectal radiation doses, leading to low rates of acute and late grade 2 toxicity.
Revolutionizing Coffee Farming: A Mobile App with GPS-Enabled Reporting for Rapid and Accurate On-Site Detection of Coffee Leaf Diseases Using Integrated Deep Learning
Authors: Hitimana Eric , Kuradusenge Martin , Sinayobye Omar Janvier , Ufitinema Chrysostome , Mukamugema Jane , Murangira Theoneste , Masabo Emmanuel , Rwibasira Peter , Ingabire Diane Aimee , Niyonzima Simplice , Bajpai Gaurav , Mvuyekure Simon Martin , Ngabonziza Jackson
Published: April 2024

Coffee leaf diseases are a significant challenge for coffee cultivation. They can reduce yields, impact bean quality, and necessitate costly disease management efforts. Manual monitoring is labor-intensive and time-consuming. This research introduces a pioneering mobile application equipped with global positioning system (GPS)-enabled reporting capabilities for on-site coffee leaf disease detection. The application integrates advanced deep learning (DL) techniques to empower farmers and agronomists with a rapid and accurate tool for identifying and managing coffee plant health. Leveraging the ubiquity of mobile devices, the app enables users to capture high-resolution images of coffee leaves directly in the field. These images are then processed in real-time using a pre-trained DL model optimized for efficient disease classification. Five models, Xception, ResNet50, Inception-v3, VGG16, and DenseNet, were experimented with on the dataset. All models showed promising performance; however, DenseNet proved to have high scores on all four-leaf classes with a training accuracy of 99.57%. The inclusion of GPS functionality allows precise geotagging of each captured image, providing valuable location-specific information. Through extensive experimentation and validation, the app demonstrates impressive accuracy rates in disease classification. The results indicate the potential of this technology to revolutionize coffee farming practices, leading to improved crop yield and overall plant health.
Advanced Prussian Blue Cathodes for Rechargeable Li-Ion Batteries
Authors: Wu Shun-Ji , Li Wen-Hsien , Batsaikhan Erdembayalag , Ma Ma-Hsuan , Yang Chun-Chuen
Published: April 2024

Taking advantage of fact that the surface electrons of metallic nanoparticles (NPs) can be effectively released even at a low voltage bias, we demonstrate an improvement in the electrochemical performance of nanosized Prussian Blue (PB)-based secondary batteries through the incorporation of bare Ag or Ni NPs in the vicinity of the working PB NPs. It is found that the capacity for electrochemical energy storage of the 17 nm PB-based battery is significantly higher than the capacity of 10 nm PB-based, 35 nm PB-based or 46 nm PB-based batteries. There is a critical PB size for the highest electrochemical energy storage efficiency. The full specific capacity CF of the 17 nm PB-based battery stabilized to 62 mAh/g after 130 charge–discharge cycles at a working current of IW = 0.03 mA. The addition of 14 mass percent of Ag NPs in the vicinity of the PB NPs gave rise to a 32% increase in the stabilized CF. A 42% increase in the stabilized CF could be obtained with the addition of 14 mass percent of Ag NPs on the working electrode of the 35 nm PB-based battery. An enhancement in CF was also found for electrodes incorporating bare Ni NPs but the effect was smaller.
Raman Spectra of Blood Serum as Holistic Biomarker for Differential Auxiliary Diagnoses of Attention Deficit and Hyperactivity Disorder (ADHD) in Adults
Authors: Dogan Gizem Yavuz , Halimoglu Gokhan , Kaplanoglu Dilara , Aksoy Umut Mert , Kandeger Ali , Yavuz Elif , Kartal Sehban , Fausto Rui , Ildiz Gulce Ogruc
Published: April 2024

Attention deficit and hyperactivity disorder (ADHD) is a prevalent neurodevelopmental condition, impacting approximately 10% of children globally. A significant proportion, around 30–50%, of those diagnosed during childhood continue to manifest ADHD symptoms into adulthood, with 2–5% of adults experiencing the condition. The existing diagnostic framework for ADHD relies on clinical assessments and interviews conducted by healthcare professionals. This diagnostic process is complicated by the disorder’s overlap in symptoms and frequent comorbidities with other neurodevelopmental conditions, particularly bipolar disorder during its manic phase, adding complexity to achieving accurate and timely diagnoses. Despite extensive efforts to identify reliable biomarkers that could enhance the clinical diagnosis, this objective remains elusive. In this study, Raman spectroscopy, combined with multivariate statistical methods, was employed to construct a model based on the analysis of blood serum samples. The developed partial least-squares discriminant analysis (PLS-DA) model demonstrated an ability to differentiate between individuals with ADHD, healthy individuals, and those diagnosed with bipolar disorder in the manic phase, with a total accuracy of 97.4%. The innovative approach in this model involves utilizing the entire Raman spectrum, within the 450–1720 cm−1 range, as a comprehensive representation of the biochemical blood serum setting, thus serving as a holistic spectroscopic biomarker. This method circumvents the necessity to pinpoint specific chemical substances associated with the disorders, eliminating the reliance on specific molecular biomarkers. Moreover, the developed model relies on a sensitive and reliable technique that is cost-effective and rapid, presenting itself as a promising complementary diagnostic tool for clinical settings. The potential for Raman spectroscopy to contribute to the diagnostic process suggests a step forward in addressing the challenges associated with accurately identifying and distinguishing ADHD from other related conditions.
Towards a Sustainable Mining: Reuse of Slate Stone Cutting Sludges for New Geopolymer Binders
Authors: Carrillo Beltrán Raúl , Picazo Camilo Elena , Perea Toledo Griselda , Corpas Iglesias Francisco Antonio
Published: April 2024

In recent years, the mining industry of slate stone in Spain, from Castille and Leon, has grown significantly due to construction and building sector demands. The continuous accumulation of cutting sludges in ponds from mining and processing operations brings associated environmental problems if the cutting sludges are not properly treated. A potential environmental mitigation measure is the valorization of cutting sludges for the development of new binder materials through geopolymerization. Therefore, this research focused its attention on studying the feasibility of slate stone cutting sludges as a source of aluminosilicates for geopolymer conformation. For this experiment, the mining raw material was analyzed through a typical characterization test campaign in order to validate its feasibility as a source of aluminosilicates for geopolymerization. Subsequently, geopolymers were prepared with slate stone cutting sludges and a 12 M concentration using different Na2SiO3/NaOH ratios (5, 2.5, 1.6, 1.25, and 1). Geopolymer samples were tested, and their physical and mechanical characteristics were evaluated. The test results show that an alkali activator with a 2.5 ratio led to better mechanical and physical properties, with a 7-day compressive strength value of 27.23 MPa. Therefore, this research aims to demonstrate that slate stone cutting sludge could constitute a sustainable binder material for construction purposes.
Towards Sustainable Material: Optimizing Geopolymer Mortar Formulations for 3D Printing: A Life Cycle Assessment Approach
Authors: Roux Charlotte , Archez Julien , Le Gall Corentin , Saadé Myriam , Féraille Adélaïde , Caron Jean-François
Published: April 2024

Geopolymer-based concretes have been elaborated among others for their potential to lower the environmental impact of the construction sector. The rheology and workability of fresh geopolymers make them suitable for new applications such as 3D printing. In this paper, we aim to develop a potassium silicate- and metakaolin-based geopolymer mortar with sand and local earth additions suited for 3D printing and an environmental assessment framework for this material. The methodology aims at the optimization of both the granular skeleton and the geopolymer matrix for the development of a low-environmental-impact material suited for 3D printing. Using this approach, various metakaolin/earth geopolymer mortars are explored from a mechanical and environmental point of view. The environmental assessment of the lab-scale process shows an improvement for the climate change category but a degradation of other indicators, compared to Portland-cement-based concrete. Several promising options exist to further optimize the process and decrease its environmental impacts. This constitutes the main research perspective of this work.