bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the Effectiveness of Different Porous Nanoparticles as Drug Carriers for Retaining the Photostability of Pinosylvin Derivative
Authors: Howaili Fadak , Saadabadi Atefeh , Mäkilä Ermei , Korotkova Ekaterina , Eklund Patrik C. , Salo-Ahen Outi M. H. , Rosenholm Jessica M.
Published: February 2024

Pinosylvin monomethyl ether (PsMME) is a natural compound known for its valuable bioactive properties, including antioxidant and anti-inflammatory effects. However, PsMME’s susceptibility to photodegradation upon exposure to ultraviolet (UV) radiation poses a significant limitation to its applications in the pharmaceutical field. This study, for the first time, introduces a strategy to enhance the photostability of PsMME by employing various nanoformulations. We utilized mesoporous silica nanoparticles (MSNs) coated with polydopamine via a poly(ethylene imine) layer (PDA–PEI–MSNs), thermally carbonized porous silicon nanoparticles (TCPSi), and pure mesoporous polydopamine nanoparticles (MPDA). All these nanocarriers exhibit unique characteristics, including the potential for shielding the drug from UV light, which makes them promising for enhancing the photostability of loaded drugs. Here, these three nanoparticles were synthesized and their morphological and physicochemical properties, including size and ζ-potential, were characterized. They were subsequently loaded with PsMME, and the release profiles and kinetics of all three nanoformulations were determined. To assess their photoprotection ability, we employed gas chromatography with a flame ionization detector (GC-FID) and gas chromatography–mass spectrometry (GC-MS) to assess the recovery percentage of loaded PsMME before and after UV exposure for each nanoformulation. Our findings reveal that MPDA exhibits the highest protection ability, with a remarkable 90% protection against UV light on average. This positions MPDA as an ideal carrier for PsMME, and by extension, potentially for other photolabile drugs as well. As a final confirmation of its suitability as a drug nanocarrier, we conducted cytotoxicity evaluations of PsMME-loaded MPDA, demonstrating dose-dependent drug toxicity for this formulation.
Performance of Full-Component Coal Gasification Fine Slag: High-Value Utilization as Reinforcing Material in Styrene-Butadiene Rubber (ESBR) for Replacing Carbon Black
Authors: Feng Xianggang , Wang Yunpeng , Li Fei , Hao Zhifei , Zhang Yongfeng , Zhang Yinmin
Published: February 2024

Ultrafine, highly active coal gasification slag (HCGS) was produced via a sustainable, green dry-ball-milling method. Coal gasification fine slag (CGS), a potential environmental pollutant, was used as a new source of rubber filler without pre-treatment, enabling waste utilisation. HCGS was added to styrene-butadiene rubber (ESBR) composites, and the effects of HCGS and the filler content on the mechanical and thermal stabilities of SBR were evaluated. The procedure conforms to important green metrics, requiring no solvent or additional reagent, or solvent-assistance for product collection. HCGS reduced the scorch time (t10) and curing time (t90) of the filled ESBR composites relative to those of pure SBR and improved the mechanical parameters. The tensile strength at 50 phr reached 10.91 MPa, and the tear strength at 90 phr reached 64.92 kN/m, corresponding to 9.4- and 3.92-fold increases relative to that of SBR filled with HCGS, respectively. HCGS exerted a reinforcing effect on ESBR, comparable to that of commercial carbon black (CB) N330. HCGS improves the binding between rubber molecules and filler particles and captures the rubber chain, thereby limiting its movement. HCGS is potentially applicable as a CB substitute in the rubber industry, with environmental and economic benefits in the disposal of CGS.
A Novel Fractional Brownian Dynamics Method for Simulating the Dynamics of Confined Bottle-Brush Polymers in Viscoelastic Solution
Authors: Yu Shi , Chu Ruizhi , Wu Guoguang , Meng Xianliang
Published: February 2024

In crowded fluids, polymer segments can exhibit anomalous subdiffusion due to the viscoelasticity of the surrounding environment. Previous single-particle tracking experiments revealed that such anomalous diffusion in complex fluids (e.g., in bacterial cytoplasm) can be described by fractional Brownian motion (fBm). To investigate how the viscoelastic media affects the diffusive behaviors of polymer segments without resolving single crowders, we developed a novel fractional Brownian dynamics method to simulate the dynamics of polymers under confinement. In this work, instead of using Gaussian random numbers (“white Gaussian noise”) to model the Brownian force as in the standard Brownian dynamics simulations, we introduce fractional Gaussian noise (fGn) in our homemade fractional Brownian dynamics simulation code to investigate the anomalous diffusion of polymer segments by using a simple “bottle-brush”-type polymer model. The experimental results of the velocity autocorrelation function and the exponent that characterizes the subdiffusion of the confined polymer segments can be reproduced by this simple polymer model in combination with fractional Gaussian noise (fGn), which mimics the viscoelastic media.
Degradation of Mechanical Properties of Flax/PLA Composites in Hygrothermal Aging Conditions
Authors: Wang Liujiao , Abenojar Juana , Martínez Miguel A. , Santiuste Carlos
Published: February 2024

The main advantage of green composites is their biodegradability, but this biodegradability can also be considered a drawback if the degradation appears during the service life of the component. Therefore, the study of the mechanical behavior of green composites after hygrothermal aging tests is necessary to analyze their degradation process. This study aims to comprehensively analyze the hygrothermal aging behavior and aging mechanism of flax-fiber-reinforced polylactic acid (PLA) biocomposites. The fully biodegradable composites are manufactured by compression molding. In addition, the influence of atmospheric-pressure plasma treatment on the mechanical properties of the biocomposite is studied. Specimens are exposed to water vapor and 40 °C environmental conditions in a stove for up to 42 days. Several specimens of each type are taken out at regular intervals and tested to examine the water absorption, mechanical properties, and thermal characterization. The results show that the stiffness was significantly reduced after 24 h due to matrix degradation, while the strength was reduced only after three weeks.
Activity of a Recombinant Chitinase of the Atta sexdens Ant on Different Forms of Chitin and Its Fungicidal Effect against Lasiodiplodia theobromae
Authors: Correa Katia Celina Santos , Facchinatto William Marcondes , Habitzreuter Filipe Biagioni , Ribeiro Gabriel Henrique , Rodrigues Lucas Gomes , Micocci Kelli Cristina , Campana-Filho Sérgio Paulo , Colnago Luiz Alberto , Souza Dulce Helena Ferreira
Published: February 2024

This study evaluates the activity of a recombinant chitinase from the leaf-cutting ant Atta sexdens (AsChtII-C4B1) against colloidal and solid α- and β-chitin substrates. 1H NMR analyses of the reaction media showed the formation of N-acetylglucosamine (GlcNAc) as the hydrolysis product. Viscometry analyses revealed a reduction in the viscosity of chitin solutions, indicating that the enzyme decreases their molecular masses. Both solid state 13C NMR and XRD analyses showed minor differences in chitin crystallinity pre- and post-reaction, indicative of partial hydrolysis under the studied conditions, resulting in the formation of GlcNAc and a reduction in molecular mass. However, the enzyme was unable to completely degrade the chitin samples, as they retained most of their solid-state structure. It was also observed that the enzyme acts progressively and with a greater activity on α-chitin than on β-chitin. AsChtII-C4B1 significantly changed the hyphae of the phytopathogenic fungus Lasiodiplodia theobromae, hindering its growth in both solid and liquid media and reducing its dry biomass by approximately 61%. The results demonstrate that AsChtII-C4B1 could be applied as an agent for the bioproduction of chitin derivatives and as a potential antifungal agent.
An Ecological Quality Evaluation of Large-Scale Farms Based on an Improved Remote Sensing Ecological Index
Authors: Wang Jun , Jiang Lili , Qi Qingwen , Wang Yongji
Published: February 2024

The ecological quality of large-scale farms is a critical determinant of crop growth. In this paper, an ecological assessment procedure suitable for agricultural regions should be developed based on an improved remote sensing ecological index (IRSEI), which introduces an integrated salinity index (ISI) tailored to the salinized soil characteristics in farming areas and incorporates ecological indices such as the greenness index (NDVI), the humidity index (WET), the dryness index (NDBSI), and the heat index (LST). The results indicate that between 2013 and 2022, the mean IRSEI increasing from 0.500 in 2013 to 0.826 in 2020 before decreasing to 0.646 in 2022. From 2013 to 2022, the area of the farm that experienced slight to significant improvements in ecological quality reached 1419.91 km2, accounting for 71.94% of the total farm area. An analysis of different land cover types revealed that the IRSEI performed more reliably than did the original RSEI method. Correlation analysis based on crop yields showed that the IRSEI method was more strongly correlated with yield than was the RSEI method. Therefore, the proposed IRSEI method offers a rapid and effective new means of monitoring ecological quality for agricultural planting areas characterized by soil salinization, and it is more effective than the traditional RSEI method.
Modelling Vegetation Health and Its Relation to Climate Conditions Using Copernicus Data in the City of Constance
Authors: Khikmah Fithrothul , Sebald Christoph , Metzner Martin , Schwieger Volker
Published: February 2024

Monitoring vegetation health and its response to climate conditions is critical for assessing the impact of climate change on urban environments. While many studies simulate and map the health of vegetation, there seems to be a lack of high-resolution, low-scale data and easy-to-use tools for managers in the municipal administration that they can make use of for decision-making. Data related to climate and vegetation indicators, such as those provided by the C3S Copernicus Data Store (CDS), are mostly available with a coarse resolution but readily available as freely available and open data. This study aims to develop a systematic approach and workflow to provide a simple tool for monitoring vegetation changes and health. We built a toolbox to streamline the geoprocessing workflow. The data derived from CDS included bioclimate indicators such as the annual moisture index and the minimum temperature of the coldest month (BIO06). The biophysical parameters used are leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR). We used a linear regression model to derive equations for downscaled biophysical parameters, applying vegetation indices derived from Sentinel-2, to identify the vegetation health status. We also downscaled the bioclimatic indicators using the digital elevation model (DEM) and Landsat surface temperature derived from Landsat 8 through Bayesian kriging regression. The downscaled indicators serve as a critical input for forest-based classification regression to model climate envelopes to address suitable climate conditions for vegetation growth. The results derived contribute to the overall development of a workflow and tool for and within the CoKLIMAx project to gain and deliver new insights that capture vegetation health by explicitly using data from the CDS with a focus on the City of Constance at Lake Constance in southern Germany. The results shall help gain new insights and improve urban resilient, climate-adaptive planning by providing an intuitive tool for monitoring vegetation health and its response to climate conditions.
Polymer Waveguide Sensor Based on Evanescent Bragg Grating for Lab-on-a-Chip Applications
Authors: Zhang Zhenyu , Abdalwareth Ahmad , Flachenecker Günter , Angelmahr Martin , Schade Wolfgang
Published: February 2024

In this work, an evanescent Bragg grating sensor inscribed in a few-mode planar polymer waveguide was integrated into microchannel structures and characterized by various chemical applications. The planar waveguide and the microchannels consisted of epoxide-based polymers. The Bragg grating structure was postprocessed by using point-by-point direct inscription technology. By monitoring the central wavelength shift of the reflected Bragg signal, the sensor showed a temperature sensitivity of −47.75 pm/K. Moreover, the functionality of the evanescent field-based measurements is demonstrated with two application examples: the refractive index sensing of different aqueous solutions and gas-phase hydrogen concentration detection. For the latter application, the sensor was additionally coated with a functional layer based on palladium nanoparticles. During the refractive index sensing measurement, the sensor achieved a sensitivity of 6.5 nm/RIU from air to 99.9% pure isopropyl alcohol. For the gas-phase hydrogen detection, the coated sensor achieved a reproducible concentration detection up to 4 vol% hydrogen. According to the reported experimental results, the integrated Bragg-grating-based waveguide sensor demonstrates high potential for applications based on the lab-on-a-chip concept.
Towards Learning Discrete Representations via Self-Supervision for Wearables-Based Human Activity Recognition
Authors: Haresamudram Harish , Essa Irfan , Plötz Thomas
Published: February 2024

Human activity recognition (HAR) in wearable and ubiquitous computing typically involves translating sensor readings into feature representations, either derived through dedicated pre-processing procedures or integrated into end-to-end learning approaches. Independent of their origin, for the vast majority of contemporary HAR methods and applications, those feature representations are typically continuous in nature. That has not always been the case. In the early days of HAR, discretization approaches had been explored—primarily motivated by the desire to minimize computational requirements on HAR, but also with a view on applications beyond mere activity classification, such as, for example, activity discovery, fingerprinting, or large-scale search. Those traditional discretization approaches, however, suffer from substantial loss in precision and resolution in the resulting data representations with detrimental effects on downstream analysis tasks. Times have changed, and in this paper, we propose a return to discretized representations. We adopt and apply recent advancements in vector quantization (VQ) to wearables applications, which enables us to directly learn a mapping between short spans of sensor data and a codebook of vectors, where the index comprises the discrete representation, resulting in recognition performance that is at least on par with their contemporary, continuous counterparts—often surpassing them. Therefore, this work presents a proof of concept for demonstrating how effective discrete representations can be derived, enabling applications beyond mere activity classification but also opening up the field to advanced tools for the analysis of symbolic sequences, as they are known, for example, from domains such as natural language processing. Based on an extensive experimental evaluation of a suite of wearable-based benchmark HAR tasks, we demonstrate the potential of our learned discretization scheme and discuss how discretized sensor data analysis can lead to substantial changes in HAR.
A Generative Approach to Person Reidentification
Authors: Asperti Andrea , Fiorilla Salvatore , Orsini Lorenzo
Published: February 2024

Person Re-identification is the task of recognizing comparable subjects across a network of nonoverlapping cameras. This is typically achieved by extracting from the source image a vector of characteristic features of the specific person captured by the camera. Learning a good set of robust, invariant and discriminative features is a complex task, often leveraging contrastive learning. In this article, we explore a different approach, learning the representation of an individual as the conditioning information required to generate images of the specific person starting from random noise. In this way we decouple the identity of the individual from any other information relative to a specific instance (pose, background, etc.), allowing interesting transformations from one identity to another. As generative models, we use the recent diffusion models that have already proven their sensibility to conditioning in many different contexts. The results presented in this article serve as a proof-of-concept. While our current performance on common benchmarks is lower than state-of-the-art techniques, the approach is intriguing and rich of innovative insights, suggesting a wide range of potential improvements along various lines of investigation.
Dense Out-of-Distribution Detection by Robust Learning on Synthetic Negative Data
Authors: Grcić Matej , Bevandić Petra , Kalafatić Zoran , Šegvić Siniša
Published: February 2024

Standard machine learning is unable to accommodate inputs which do not belong to the training distribution. The resulting models often give rise to confident incorrect predictions which may lead to devastating consequences. This problem is especially demanding in the context of dense prediction since input images may be only partially anomalous. Previous work has addressed dense out-of-distribution detection by discriminative training with respect to off-the-shelf negative datasets. However, real negative data may lead to over-optimistic evaluation due to possible overlap with test anomalies. To this end, we extend this approach by generating synthetic negative patches along the border of the inlier manifold. We leverage a jointly trained normalizing flow due to a coverage-oriented learning objective and the capability to generate samples at different resolutions. We detect anomalies according to a principled information-theoretic criterion which can be consistently applied through training and inference. The resulting models set the new state of the art on benchmarks for out-of-distribution detection in road-driving scenes and remote sensing imagery despite minimal computational overhead.
Ebbing Strength, Fading Power: Unveiling the Impact of Persistent Fatigue on Muscle Performance in COVID-19 Survivors
Authors: Kowal Mateusz , Morgiel Ewa , Winiarski Sławomir , Dymarek Robert , Bajer Weronika , Madej Marta , Sebastian Agata , Madziarski Marcin , Wedel Nicole , Proc Krzysztof , Madziarska Katarzyna , Wiland Piotr , Paprocka-Borowicz Małgorzata
Published: February 2024

The total number of confirmed cases of COVID-19 caused by SARS-CoV-2 virus infection is over 621 million. Post-COVID-19 syndrome, also known as long COVID or long-haul COVID, refers to a persistent condition where individuals experience symptoms and health issues after the acute phase of COVID-19. The aim of this study was to assess the strength and fatigue of skeletal muscles in people recovered from COVID-19. A total of 94 individuals took part in this cross-sectional study, with 45 participants (referred to as the Post-COVID Cohort, PCC) and 49 healthy age-matched volunteers (Healthy Control Cohort, HCC). This research article uses the direct dynamometry method to provide a detailed analysis of post-COVID survivors’ strength and power characteristics. The Biodex System 4 Pro was utilized to evaluate muscle strength characteristics during the fatigue test. The fatigue work in extensors and flexors was significantly higher in the PCC. The PCC also showed significantly less power in both extensors and flexors compared to the HCC. In conclusion, this study provides compelling evidence of the impact of post-COVID-19 fatigue on muscle performance, highlighting the importance of considering these effects in the rehabilitation and care of individuals recovering from the virus. PCC achieved lower muscle strength values than HCC.
Research on Classification Algorithm of Silicon Single-Crystal Growth Temperature Gradient Trend Based on Multi-Level Feature Fusion
Authors: Liu Yu-Yu , Mu Ling-Xia , Zhang Peng-Ju , Liu Ding
Published: February 2024

In the process of silicon single-crystal preparation, the timely identification and adjustment of abnormal conditions are crucial. Failure to promptly detect and resolve issues may result in a substandard silicon crystal product quality or even crystal pulling failure. Therefore, the early identification of abnormal furnace conditions is essential for ensuring the preparation of perfect silicon single crystals. Additionally, since the thermal field is the fundamental driving force for stable crystal growth and the primary assurance of crystal quality, this paper proposes a silicon single-crystal growth temperature gradient trend classification algorithm based on multi-level feature fusion. The aim is to accurately identify temperature gradient changes during silicon crystal growth, in order to promptly react to early growth failures and ensure the stable growth of high-quality silicon single crystals to meet industrial production requirements. The algorithm first divides the temperature gradient trend into reasonable categories based on expert knowledge and qualitative analysis methods. Then, it fuses the original features of actual production data, shallow features extracted based on statistical information, and deep features extracted through deep learning. During the fusion process, the algorithm considers the impact of different features on the target variable and calculates mutual information based on the difference between information entropy and conditional entropy, ultimately using mutual information for feature weighting. Subsequently, the fused multi-level feature vectors and their corresponding trend labels are input into a Deep Belief Network (DBN) model to capture process dynamics and classify trend changes. Finally, the experimental results demonstrate that the proposed algorithm can effectively predict the changing trend of thermal field temperature gradients. The introduction of this algorithm will help improve the accuracy of fault trend prediction in silicon single-crystal preparation, thereby minimizing product quality issues and production interruptions caused by abnormal conditions.
Expectations of Egyptian and German Sports Tourists Depending on Destination and Travel Companions
Authors: Tuchel Jacqueline , Hente Luisa , Hodeck Alexander , El Beih Sarah , Zoromba Mohamed
Published: February 2024

The expectations of (sports) tourists are individual and, therefore, particularly diverse. This study investigates the question to which extent expectations differ with regard to various aspects (accommodation, food, activities, meeting new people and fears) according to the destination in the home country or abroad and the travel companion. This study also investigates whether differences can be identified between the two studied countries. A total of 39 people in Egypt and 42 in Germany were asked about their individual and group expectations and fears by using the scenario technique. In small groups, the expectations of travelling with different travel companions (friends, partner and children or grandmother) and to different destinations were discussed to develop concrete wishes and goals. Results show that both the country of origin and the destination, as well as the travel companions, have an influence on expectations.
Structural Response of a Cement Concrete Pavement with a Buffer Layer to Temperature and Moving-Load Effects
Authors: Wang Kun , Li Xiongao , Hu Peng , Fan Liran , Xu Hao , Qu Lu
Published: February 2024

The main issues associated with cement concrete pavements are cracks and broken plates that affect driving comfort and road service life. To ensure sustainable use of the cement concrete, a buffer layer (AC-10) can be introduced between the base and the cement concrete panel. In this study, the interlayer shear test was performed, and the interlayer bonding coefficient under different temperature conditions was determined. The creep test of the buffer layer was also conducted, and the four parameters (E1, E2, η1, and η2) of the Burgers model of the buffer layer were analyzed using regression. According to the parameters obtained from the test, the finite-element model was established, and the moving load was applied to analyze the structural model response under high-, medium-, and low-temperature conditions. The results show that the (1) temperature stress is mainly concentrated in the buffer layer and regions above the structural layer. At low temperatures, the maximum stress at the top of the surface layer is 2.16 MPa, and the vertical strain decreases as a function of depth. (2) Under the combined action of temperature and moving load, the variation ranges of tensile and compressive stresses at the top of the surface layer are the largest; the variation range of the buffer layer and the subsequent structure is small; the maximum warpage deformation of the surface layer is 0.453 mm under high-temperature conditions; and the maximum compression deformation is 0.219 mm under low-temperature conditions. (3) The comprehensive coefficient kc of the fatigue equation was modified, and the comprehensive coefficient kc of the fatigue equation under different vehicle speeds was proposed. This study provides a reference for the sustainable development of cement concrete pavements with buffer layers.
Balancing Sustainability: An Analysis of Habitat for Humanity Affiliates in Mississippi
Authors: Doleac Alex , Langar Sandeep , Sulbaran Tulio
Published: February 2024

Non-profit organizations (NPOs) support economically disadvantaged communities by improving housing conditions and building homes, despite limited resources. With rising housing costs and poverty causing homelessness and poor housing quality, NPOs’ efforts are crucial. However, operating constraints (such as financial, policy, and others), often lead NPOs to prioritize initial costs over sustainability and environmental impacts. Therefore, this research investigated the adoption, implementation, and routinization patterns for sustainability and green efforts in Mississippi (US) by a leading NPO. The research used a two-phased combined design methodology, with the first phase involving explorative design that involved the identification of criteria that led to selecting the affiliates of Habitat for Humanity (HFH) as the unit of analysis. The selected NPO (HFH) had 38 affiliates across Mississippi, US, at the time of the study. The second phase involved a cross-sectional design, with data collected by utilizing a structured telephone survey. All collected data were subjected to descriptive and inferential statistics, and thematic analysis. Twenty-five affiliates (66% response rate) participated in the study, and the results indicate that a small proportion of affiliates were actively adopting sustainability practices for projects constructed, and most were located in the southern part of the state. The research identified factors that lead to the routinization of sustainability practices, the most commonly used third-party benchmarking tools, and perceptions of NPOs towards such tools to evaluate the greenness of residential projects. Some crucial implications were identifying uneven project completion within HFH, limited adoption of green strategies, and perception of green certification as non-vital.
Assessing the Ecological Cost of Material Flow in China’s Waste Paper Recycling System
Authors: Dai Tiejun
Published: February 2024

This article introduces the concept of ecological costs associated with the waste paper recycling system. The costs associated with this process include resource consumption, waste emissions, ecological damage, and production processes. To analyze the ecological costs of deviations from the baseline material flow in a waste paper recycling system, a benchmark material flow diagram is constructed using the material flow analysis method. The diagram illustrates a fully closed one-way material flow of the recycling system, which is highly abstracted and simplified. The study analyzed the ecological costs of the benchmark material flow and the impact of deviations from it. The results suggest that the circulation of materials within and between processes increases the ecological cost of the waste paper recycling system. Furthermore, the release of materials from a process into the environment also contributes to its ecological impact. However, the introduction of external materials into the recycling system can reduce its ecological impact, particularly if these materials are recycled resources. The study emphasizes the significance of considering ecological costs in waste paper recycling systems to minimize their environmental impact.
Life Cycle Assessment in Higher Education: Design and Implementation of a Teaching Sequence Activity
Authors: Navajas Alberto , Echarri Itsaso , Gandía Luis M. , Pozuelo Jorge , Cascarosa Esther
Published: February 2024

The latest studies show that to achieve the Sustainable Development Goals on education, there must be a focus on adequately training higher education students. In this work, we present a study about the Life Cycle Analysis of knowledge of products and processes of engineering students. This aspect is very relevant in engineering education since it has direct implications on sustainability. The first step was to identify what the learning problems were, and taking them into account, a specific teaching sequence was designed and implemented over three academic years. Two activities, on an increasing level of complexity, of the application of Life Cycle Assessment are shown in this paper. The first one is the Life Cycle Analysis comparison between two steel and polypropylene pieces. The second one is the Life Cycle Analysis comparison between three different ends of life of a polypropylene piece: mechanical recycling, incineration, and landfill. Data on the evolution of students’ marks while solving a “one step more difficult project” throughout these courses have been collected. The results show a generalized learning by the students about Life Cycle Analysis.
Spatiotemporal Patterns and Drivers of Trade-Offs and Synergy in the Beijing–Tianjin Sand Source Control Project: A Bayesian Belief Network-Based Analysis
Authors: Li Jiahao , Cui Ming , Cai Qi , Liu Yuguo , Bo Wenjing
Published: February 2024

Understanding the interactions between ecosystem services is the foundation for optimizing ecosystem management and improving human well-being. However, studies on the driving mechanism of ecosystem service relationship formation in arid and semiarid climates are scarce. The Beijing–Tianjin Sand Source Control Project (BTSSCP) has been underway for more than 20 years (2001–2022), and a comprehensive scientific assessment of the effects of its implementation is important for managing ecosystems more efficiently. Taking the BTSSCP region as a study area, four ecosystem services (water conservation (WC), soil conservation (SC), wind erosion control (WEC), and net primary productivity (NPP)) were quantified and mapped in 2000, 2010, and 2020. In this study, a Bayesian belief network (BBN) model was used to analyze ecological processes and determine the relationship between the potential influencing factors and ecosystem services. A sensitivity analysis identified the key factors affecting ecosystem service supply on the basis of a Bayesian belief network simulation. The results showed an increasing trend for four ecosystem services over the past 20 years. Regarding spatial distribution, WC, SC, and NPP exhibited an overall “high in the east and low in the west” pattern, while the spatial distribution of WEC was more dispersed. The intensity of the trade-offs among WC, SC, and NPP has increased, while that of the trade-offs between the rest of the variables has decreased in the BTSSCP over the past 20 years. The results of the Bayesian network modeling indicated that precipitation, NDVI, land use, and temperature were the major variables influencing the strength of ecosystem service trade-offs. The conditional probabilities of the key variables in different states showed that the Sunit Left Banner, Sunit Right Banner, and other areas of control of the desertification of arid grassland had a high probability of trade-offs in WC_SC and SC_NPP. However, the probability of a trade-off between WEC and NPP was higher in the southeastern part of the Yanshan Hills Mountain Water Source Reserve than in the other regions; thus, it should be prioritized as an area for ecological restoration in future planning. This paper provides a scientific reference for the effective protection of ecosystems and the formulation of sustainable policies.
Cosmic Ray Anisotropy and Spectra as Probes for Nearby Sources
Authors: Li Aifeng , Liu Wei , Guo Yiqing
Published: February 2024

Cosmic ray (CR) spectra and anisotropy are closely related to the distribution of CR sources, making them valuable probes for studying nearby sources. There are 12 nearby sources located within 1 kpc of the solar system, and which ones are the optimal candidates? In this work, we have selected the Geminga, Monogem, Vela, Loop I, and Cygnus SNR sources as the focus of our research, aiming to identify the optimal candidate by investigating their contribution to the energy spectra and anisotropy using the Spatially Dependent Propagation (SDP) model. Additionally, the anisotropic diffusion effect of the local regular magnetic field (LRMF) on CR particles is also considered in the SDP model. Our previous work only provided 1D anisotropy along the right ascension; this current work will further present 2D anisotropy maps along the right ascension and declination. When the injection power of different nearby sources is roughly equal, the results show that the Geminga, Momogem, and Loop I SNR sources contribute significantly to the nuclear energy spectra. Under the isotropic diffusion without considering the LRMF, the 2D anisotropy maps indicate that the phase points to the nearby source below 100 TeV. We further adjust the injection power of the Monogem SNR source in accordance with the spin-down energy of the Geminga and Monogem pulsars, and find that the contribution of the corrected Monogem SNR can be disregarded. Because the Loop I SNR source is located in the direction of the Galactic Center (GC), it cannot contribute to the excess of CRs in the anti-GC direction. Under anisotorpic diffusion with the consideration of the LRMF, the 2D anisotropy maps show that only the Geminga SNR can match the anisotropy measurement, while the other sources cannot. Finally, we conclude that the Geminga SNR source is the optimal nearby source.
Analysis of Mixing Efficiency in a Stirred Reactor Using Computational Fluid Dynamics
Authors: Ramírez-López Adan
Published: February 2024

Lead recycling is very important for reducing environmental pollution risks and damages. Liquid lead is recovered from exhaust batteries inside stirred batch reactors; the process requires melting to be cleaned. Nevertheless, it is necessary to establish parameters for evaluating mixing to improve the efficiency of the industrial practices. Computational fluid dynamics (CFD) has become a powerful tool to analyze industrial processes for reducing operating costs, avoiding potential damages, and improving the equipment’s performance. Thus, the present work is focused on simulating the fluid hydrodynamics inside a lead-stirred reactor monitoring the distribution of an injected tracer in order to find the best injection point. Then, different injected points are placed on a control plane for evaluation; these are evaluated one by one by monitoring the tracer concentration at a group of points inside the batch. The analyzed reactor is a symmetrical, vertical batch reactor with two geometrical sections: one cylindrical body and a semi-spherical bottom. Here, one impeller with four flat blades in a shaft is used for lead stirring. The tracer concentration on the monitoring points is measured and averaged for evaluating the efficiency inside the tank reactor. Hydrodynamics theory and a comparison between the concentration profiles and distribution of tracer curves are used to demonstrate both methods’ similarities. Then, the invariability of the tracer concentration on the monitoring points is adopted as the main parameter to evaluate the mixing, and the best injection point is found as a function of the shortest mixing time. Additionally, the influence of the impeller rotation speed is analyzed as an additional control parameter to improve industrial practices.
OLEDs on Down-Converting Fabric by Using a High Scalable Planarization Process and a Transparent Polymeric Electrode
Authors: Prontera Carmela Tania , Pugliese Marco , Mariano Fabrizio , Taurino Daniela , Giannuzzi Roberto , Primiceri Vitantonio , Esposito Marco , Andretta Antonio , Gigli Giuseppe , Maiorano Vincenzo
Published: February 2024

Textile-based electronics represents a key technology for the development of wearable devices. Light-emitting textiles based on OLED architecture are particularly promising due to their intrinsic flexibility and possibility to be fabricated on large areas using scalable processes. Fabric planarization is one of the most critical issues in their fabrication. Here we report a fast, simple, and industrially scalable planarization method based on the transfer of surface morphological properties from silicon to fabric. A liquid resin is used as a planarization layer, and by exploiting the low roughness of a ‘guide substrate’ it is possible to replicate the smooth and uniform surface from the silicon to the planarization layer. The result is a fabric with a flat and homogeneous polymer layer on its surface, suitable for OLED fabrication. In particular, the effect of resin viscosity on the surface morphology was evaluated to obtain the best planarization layer. The best device shows high luminance and current efficiency values, even after 1000 bending cycles. We also explored the possibility of tuning the color emitted by the device by using a fluorescent fabric as a down-converting layer. Thanks to this approach, it is in principle possible to achieve white emission from a very simple device architecture.
Immunological Cross-Reactivity and Preclinical Assessment of a Colombian Anticoral Antivenom against the Venoms of Three Micrurus Species
Authors: Rodríguez-Vargas Ariadna , Franco-Vásquez Adrián Marcelo , Triana-Cerón Miguel , Alam-Rojas Shaha Noor , Escobar-Wilches Derly C. , Corzo Gerardo , Lazcano-Pérez Fernando , Arreguín-Espinosa Roberto , Ruiz-Gómez Francisco
Published: February 2024

Snakebite accident treatment requires the administration of antivenoms that provide efficacy and effectiveness against several snake venoms of the same genus or family. The low number of immunogenic components in venom mixtures that allow the production of antivenoms consequently gives them partial neutralization and a suboptimal pharmacological response. This study evaluates the immunorecognition and neutralizing efficacy of the polyvalent anticoral antivenom from the Instituto Nacional de Salud (INS) of Colombia against the heterologous endemic venoms of Micrurus medemi, and M. sangilensis, and M. helleri by assessing immunoreactivity through affinity chromatography, ELISA, Western blot, and neutralization capability. Immunorecognition towards the venoms of M. medemi and M. sangilensis showed values of 62% and 68% of the protein composition according to the immunoaffinity matrix, respectively. The analysis by Western blot depicted the highest recognition patterns for M. medemi, followed by M. sangilensis, and finally by M. helleri. These findings suggest that the venom compositions are closely related and exhibit similar recognition by the antivenom. According to enzyme immunoassays, M. helleri requires a higher amount of antivenom to achieve recognition than the others. Besides reinforcing the evaluation of INS antivenom capability, this work recommends the use of M. helleri in the production of Colombian antisera.
Adsorption of Zearalenone by Aureobasidium pullulans Autolyzed Biomass Preparation and Its Detoxification Properties in Cultures of Saccharomyces cerevisiae Yeast
Authors: Bzducha-Wróbel Anna , Janowicz Monika , Bryła Marcin , Grzesiuk Iga
Published: February 2024

Different preventive strategies are needed to minimize the intake risks of mycotoxins, including zearalenone (ZEN). The aim of this study was to determine the ZEN adsorption ability of an autolyzed biomass preparation of polymorphic yeast Aureobasidium pullulans A.p.-3. The evaluation of the antitoxic properties of the preparation was also performed in relation to Saccharomyces cerevisiae yeast (ATCC 2366, ATCC 7090 and ATCC 9763) used as a model cell exposed to a toxic ZEN dose. The preparation at a dose of 5 mg/mL showed the adsorption of ZEN present in model systems at concentrations between 1 μg/mL to 100 μg/mL. The highest degree of adsorption was established for ZEN concentrations of 1 μg/mL and 5 μg/mL, becoming limited at higher doses of the toxin. Based on the Langmuir model of adsorption isotherms, the predicted maximum ZEN adsorption was approx. 190 µg/mL, regardless of pH. The growth of three strains of S. cerevisiae yeast cells in the medium with ZEN at concentrations within the range of 1.56 μg/mL–100 μg/mL was analyzed to determine the minimum inhibitory concentration. The growth of all tested strains was especially limited by high doses of ZEN, i.e., 50 and 100 μg/mL. The protective effect of the tested preparation was noted in relation to yeast cells exposed to toxic 100 μg/mL ZEN doses. The highest yeast cell growth (app. 36% percentage) was noted for a S. cerevisiae ATCC 9763 strain compared to the medium with ZEN but without preparation. More detailed tests determining the antitoxic mechanisms of the A. pullulans preparation are planned in the future, including cell culture bioassays and animal digestive tract models.
Effects of OnabotulinumtoxinA on Allodynia and Interictal Burden of Patients with Chronic Migraine
Authors: Argyriou Andreas A. , Dermitzakis Emmanouil V. , Rikos Dimitrios , Xiromerisiou Georgia , Soldatos Panagiotis , Litsardopoulos Pantelis , Vikelis Michail
Published: February 2024

Background: We primarily aimed to ascertain whether treatment with OnabotulinumtoxinA (BoNTA) might influence the extent of the interictal burden and cutaneous allodynia in patients with chronic migraine (CM). Methods: Seventy CM patients, who received three consecutive cycles of BoNTA, were studied. The interictal burden was assessed with the Migraine Interictal Burden Scale (MIBS-4), while cutaneous allodynia was examined with the Allodynia Symptom Checklist (ASC-12) together with PI-NRS VAS to obtain hair brushing scores, and then these were compared from baseline (T0) to the last efficacy evaluation follow-up (T1). Efficacy outcomes, mostly mean headache days (MHD) and “Headache Impact Test” scores, were also assessed between T0 and T1. Results: BONTA improved the interictal burden, with a decrease in MIBS-4 scoring by an average of −7 at T1, compared to baseline (p < 0.001). The percentage of patients with a moderate/severe interictal burden was substantially decreased. Likewise, BoNTA reduced the extent of cutaneous allodynia, with a significant reduction in both the ASC-12 (1 vs. 6; p < 0.001) and PI-NRS VAS (1 vs. 5; p < 0.001) to hair brushing median scores at T1, compared to baseline. Reduced MHD rates were significantly associated with a smaller interictal burden at T1. The efficacy of BoNTA, with a significant reduction in MHD and HIT-6 scores at T1 compared to T0, was re-confirmed. Conclusions: BoNTA resulted in a statistically significant reduction in the interictal burden and also improved cutaneous allodynia. The reduction in ictal burden was associated with the down-scaling of the interictal burden. Hence, BoNTA improved the full spectrum of migraine impairment by diminishing the clinical expression of central sensitization.
Impact of Delta SARS-CoV-2 Infection on Glucose Metabolism: Insights on Host Metabolism and Virus Crosstalk in a Feline Model
Authors: Rochowski Matthew T. , Jayathilake Kaushalya , Balcerak John-Michael , Selvan Miruthula Tamil , Gunasekara Sachithra , Miller Craig , Rudd Jennifer M. , Lacombe Véronique A.
Published: February 2024

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causes enhanced mortality in people with metabolic and cardiovascular diseases. Other highly infectious RNA viruses have demonstrated dependence on glucose transport and utilization, so we hypothesized that SARS-CoV-2 infection could lead to alterations in cellular and whole-body glucose metabolism. Twenty-four healthy domestic cats were intratracheally inoculated with B.1.617.2 (delta) SARS-CoV-2 and samples were collected at 4- and 12-days post-inoculation (dpi). Blood glucose and circulating cortisol concentrations were elevated at 4 and 12 dpi. Serum insulin concentration was statistically significantly decreased, while angiotensin 2 concentration was elevated at 12 dpi. SARS-CoV-2 RNA was detected in the pancreas and skeletal muscle at low levels; however, no change in the number of insulin-producing cells or proinflammatory cytokines was observed in the pancreas of infected cats through 12 dpi. SARS-CoV-2 infection statistically significantly increased GLUT protein expression in both the heart and lungs, correlating with increased AMPK expression. In brief, SARS-CoV-2 increased blood glucose concentration and cardio-pulmonary GLUT expression through an AMPK-dependent mechanism, without affecting the pancreas, suggesting that SARS-CoV-2 induces the reprogramming of host glucose metabolism. A better understanding of host cell metabolism and virus crosstalk could lead to the discovery of novel metabolic therapeutic targets for patients affected by COVID-19.
SIV Infection Is Associated with Transient Acute-Phase Steatosis in Hepatocytes In Vivo
Authors: Derby Nina , Biswas Sreya , Yusova Sofiya , Luevano-Santos Cristina , Pacheco Maria Cristina , Meyer Kimberly A. , Johnson Brooke I. , Fischer Miranda , Fancher Katherine A. , Fisher Cole , Abraham Yohannes M. , McMahon Conor J. , Lutz Savannah S. , Smedley Jeremy V. , Burwitz Benjamin J. , Sodora Donald L.
Published: February 2024

Metabolic-dysfunction-associated fatty liver disease (MAFLD) is a major cause of morbidity and mortality in HIV-infected individuals, even those receiving optimal antiretroviral therapy. Here, we utilized the SIV rhesus macaque model and advanced laparoscopic techniques for longitudinal collection of liver tissue to elucidate the timing of pathologic changes. The livers of both SIV-infected (N = 9) and SIV-naïve uninfected (N = 8) macaques were biopsied and evaluated at four time points (weeks −4, 2, 6, and 16–20 post-infection) and at necropsy (week 32). SIV DNA within the macaques’ livers varied by over 4 logs at necropsy, and liver SIV DNA significantly correlated with SIV RNA in the plasma throughout the study. Acute phase liver pathology (2 weeks post-infection) was characterized by evidence for fat accumulation (microvesicular steatosis), a transient elevation in both AST and cholesterol levels within the serum, and increased hepatic expression of the PPARA gene associated with cholesterol metabolism and beta oxidation. By contrast, the chronic phase of the SIV infection (32 weeks post-infection) was associated with sinusoidal dilatation, while steatosis resolved and concentrations of AST and cholesterol remained similar to those in uninfected macaques. These findings suggest differential liver pathologies associated with the acute and chronic phases of infection and the possibility that therapeutic interventions targeting metabolic function may benefit liver health in people newly diagnosed with HIV.