bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Sensory Characteristics of the Soybean Spreads Enhanced with Vegetables and Spices
Authors: Kostyra Eliza , Gawlińska Klaudia , Żakowska-Biemans Sylwia , Piotrowska Anna , Gantner Magdalena , Kulik Klaudia , Świąder Katarzyna
Published: January 2024

Transitioning to a plant-based diet presents a number of complex ethical, environmental, and health-related considerations. This trend is not only reshaping consumer diets, but also steering the food industry towards the development of new plant-based products. The primary aim of this study was to examine and identify the sensory similarities and differences in soybean spreads consisting of vegetable purées—specifically, beetroot, pumpkin, broccoli, and carrot—with the addition of spices such as marjoram and cumin. The sensory assessment was conducted using the Quantitative Descriptive Analysis (QDA). Twenty-three descriptors were selected and defined following the profiling procedure. The sensory properties of soy-based spreads have been significantly altered by the addition of vegetable purées and spices. Adding vegetable purées reduced the intensity of soybean odour and flavour, lowered fatty notes, and resulted in a less dense texture, while enhancing vegetable odour and flavour. This also improved the moisture content and overall sensory quality of the spreads. Although spices did not notably enhance these sensory attributes, soy-based vegetable spreads remain an attractive option for unique vegetarian finger foods and lunch dishes, catering to diverse consumer preferences. The addition of vegetable purées and spices to spreads creates opportunities for innovative and flavourful plant-based options.
System-Level Assessment of Massive Multiple-Input–Multiple-Output and Reconfigurable Intelligent Surfaces in Centralized Radio Access Network and IoT Scenarios in Sub-6 GHz, mm-Wave, and THz Bands
Authors: Pavia João Pedro , Velez Vasco , Souto Nuno , Silva Mário Marques da , Correia Américo
Published: January 2024

In this article, we investigate in different scenarios the feasibility of using massive multiple-input–multiple-output (mMIMO) with reconfigurable intelligent surfaces (RISs) to increase the throughput and coverage with high energy efficiency, considering sub-6 GHz, mmWave, and THz bands. With that objective, a centralized radio access network (C-RAN) suitable for beyond fifth-generation (B5G) systems is considered, where we integrate the base stations (BSs) with multiple RISs and IoT devices or user equipment. RISs with a large number of quasi-passive reflecting elements constitute a low-cost approach capable of shaping radio wave propagation and improving wireless connectivity. We consider a scenario where multiple RISs are combined with mMIMO in the uplink in order to provide connectivity to a smart city (with thousands of active low-power IoT devices), wirelessly, in the 3.6 GHz and 28 GHz bands. We also address a scenario where RISs are adopted with mMIMO in the downlink so as to offer connectivity to a stadium with a pitch, (and thousands of active users’ equipment) in the 28 GHz band. Finally, we also studied the connectivity at 100 GHz of a factory in which several RIS panels, replacing most of the BSs equipped with mMIMO, assure improved throughput and coverage. We concluded that RISs are capable of improving the performance in any of these analyzed scenarios at the different frequency bands, justifying that they are a key enabling technology for 6G.
Old Landslide Detection Using Optical Remote Sensing Images Based on Improved YOLOv8
Authors: Li Yunlong , Ding Mingtao , Zhang Qian , Luo Zhihui , Huang Wubiao , Zhang Cancan , Jiang Hui
Published: January 2024

The reactivation of old landslides can be triggered by heavy destructive earthquakes, heavy rainfall, and ongoing human activities, thereby resulting in the occurrence of secondary landslides. However, most existing models are designed for detecting nascent landslides and there are few algorithms for old landslide detection. In this paper, we introduce a novel landslide detection model known as YOLOv8-CW, built upon the YOLOv8 (You Only Look Once) architecture, to tackle the formidable challenge of identifying old landslides. We replace the Complete-IoU loss function in the original model with the Wise-IoU loss function to mitigate the impact of low-quality samples on model training and improve detection recall rate. We integrate a CBAM (Convolutional Block Attention Module) attention mechanism into our model to enhance detection accuracy. By focusing on the southwest river basin of the Sichuan–Tibet area, we collect 558 optical remote sensing images of old landslides in three channels from Google Earth and establish a dataset specifically for old landslide detection. Compared to the original model, our proposed YOLOv8-CW model achieves an increase in detection accuracy of 10.9%, recall rate of 6%, and F1 score from 0.66 to 0.74, respectively. These results demonstrate that our improved model exhibits excellent performance in detecting old landslides within the Sichuan–Tibet area.
Cluster-Centered Visualization Techniques for Fuzzy Clustering Results to Judge Single Clusters
Authors: Vahldiek Kai , Klawonn Frank
Published: January 2024

Fuzzy clustering, as a powerful method for pattern recognition and data analysis, often produces complex results that require careful examination of individual clusters. In this paper, advanced visualization techniques are presented that aim to facilitate the analysis of fuzzy clustering results by focusing on the evaluation and interpretation of individual clusters. The presented approach is based on the development of cluster-centric visualization techniques that consider the inherent uncertainty of fuzzy clustering results. The novelty is an assessment of individual clusters with the proposed visualizations. In general, three cluster-centered visualization techniques are presented. These approaches are intended not only to illustrate the overall structure of the fuzzy clustering results but also to enable detailed individual cluster analysis. The performance of the presented visualization techniques is demonstrated by their application to real data sets from different areas. The results show that the techniques provide an effective way to judge individual clusters in fuzzy clustering results for complex data structures.
Computational Fluid Dynamic Simulation of Fabric Cooling in a Stenter Machine
Authors: Erdoğan Ahmet , Sığırcı Muhammet Tibet
Published: January 2024

Stenter machines are used to remove moisture from fabrics produced in the textile industry. Following the drying process, the cooling process, which is applied to fabrics using injector channels, is conducted in the last section of a stenter machine, preventing fabrics from expanding and the degradation of their quality. The present study mainly aimed to investigate the fabric-cooling process in a stenter machine used actively in a textile company. First, industrial data were obtained with some experiments, and computational fluid dynamics (CFD) simulations were then conducted by validating the industrial data. All CFD models were simulated using ANSYS Fluent commercial CFD software. A total of four parameters, including two geometric and two operating parameters, were considered in order to investigate their effects on the fabric-cooling performance of the stenter machine. While the geometric parameters were the porosity (β) and injector angle (α), the operating parameters were the velocity of the airflow that cools the fabrics and fabric velocity, representing the movement of the fabric. As outputs of CFD simulations, fabric surface temperature values, the distributions of fabric surface temperatures, and some streamlines were illustrated. Although low values of porosity (β1 = 0.05) and injector angle (α1 = 0°) provided better performance, airflow velocity could be increased one or two times for the range of these constant parameters.
Enhanced Student Admission Procedures at Universities Using Data Mining and Machine Learning Techniques
Authors: Assiri Basem , Bashraheel Mohammed , Alsuri Ala
Published: January 2024

The progress of technology has played a crucial role in enhancing various fields such as education. Universities in Saudi Arabia offer free education to students and follow specific admission policies. These policies usually focus on features and scores such as the high school grade point average, general aptitude test, and achievement test. The main issue with current admission policies is that they do not fit with all majors, which results in high rates of failure, dropouts, and transfer. Another issue is that all mentioned features and scores are cumulatively calculated, which obscures some details. Therefore, this study aims to explore admission criteria used in Saudi Arabian universities and the factors that influence students’ choice of major. First, using data mining techniques, the research analyzes the relationships and similarities between the university’s grade point average and the other student admission features. The study proposes a new Jaccard model that includes modified Jaccard and approximated modified Jaccard techniques to match the specifications of students’ data records. It also uses data distribution analysis and correlation coefficient analysis to understand the relationships between admission features and student performance. The investigation shows that relationships vary from one major to another. Such variations emphasize the weakness of the generalization of the current procedures since they are not applicable to all majors. Additionally, the analysis highlights the importance of hidden details such as high school course grades. Second, this study employs machine learning models to incorporate additional features, such as high school course grades, to find suitable majors for students. The K-nearest neighbor, decision tree, and support vector machine algorithms were used to classify students into appropriate majors. This process significantly improves the enrolment of students in majors that align with their skills and interests. The results of the experimental simulation indicate that the K-nearest neighbor algorithm achieves the highest accuracy rate of 100%, while the decision tree algorithm’s accuracy rate is 81% and the support vector machine algorithm’s accuracy rate is 75%. This encourages the idea of using machine learning models to find a suitable major for applicants.
Development of Virtual Sensor Based on LSTM-Autoencoder to Detect Faults in Supply Chilled Water Temperature Sensor
Authors: Jin San , Jang Ahmin , Lee Donghoon , Kim Sungjin , Shin Minjae , Do Sung Lok
Published: January 2024

Supply chilled water temperature (SCWT) is an important variable for the efficient and stable operation of heating, ventilation, and air conditioning (HVAC) systems. A precisely measured value ensured by the continuous reliability of the temperature sensor is essential for optimal control of an HVAC system because temperature sensor faults can affect the chiller operation and waste energy. Therefore, temperature sensor fault-detection strategies are imperative for maintaining a comfortable indoor thermal environment and ensuring the efficient and stable operation of HVAC systems. This study proposes a fault-detection method for an SCWT sensor using a virtual sensor based on a long short-term memory-autoencoder. The fault-detection performance is evaluated considering a case study under various sensor fault scenarios to evaluate changes in indoor thermal comfort and energy consumption after correcting sensor faults detected by the virtual sensor. The results verify excellent fault-detection performance in various fault scenarios (F-1 scores ranging from 0.9350 to 1.000). After correcting the SCWT fault, indoor thermal comfort is steadily maintained without additional energy consumption (indoor set-point temperature unmet hour reduced by a maximum of 105.7 hours, and energy consumption decreased by up to 1.8%).
Analysis of Stochastic Properties of MEMS Accelerometers and Gyroscopes Used in the Miniature Flight Data Recorder
Authors: Rzucidło Paweł , Kopecki Grzegorz , Szczerba Piotr , Szwed Piotr
Published: January 2024

MEMS (micro-electro-mechanical system) gyroscopes and accelerometers are used in several applications. They are very popular due to their small size, low price, and accessibility. The design of MEMS accelerometers enables the measurement of vibrations, with frequencies from tenths of hertz to even 1 kHz. MEMS gyroscopes can be applied to measure angular rates, and indirectly also angular oscillations with frequencies similar to accelerometers. Despite significant stochastic errors, MEMS sensors are used not only in popular domestic appliances (e.g., smartphones) but also in safety-critical units, such as aeronautical attitude and heading reference systems (AHRSs). In engineering, methods of stochastic properties analysis are important tools for sensor selection, verification, and the design of measurement algorithms. In this article, three methods used for the analysis of stochastic properties of sensors are presented and comparative analyses are shown. The applied measurement frequencies (1 kHz) were much higher than those typically found in MEMS sensor applications. Additionally, an exemplary analysis of temperature drift frequency, as well as the possibility for the synthesis of complementary filter parameters with the use of the described methods, is shown. Assessment of the stochastic properties of MEMS accelerometers and gyroscopes was performed under both constant and variable temperature conditions (during warm-up after switching on) with the use of classic methods, such as power spectral density (PSD) and Allan variance (AV), as well as the less known but very promising generalized method of wavelet moments (GMWM).
A Simulation and Experiment of the Flow Fluctuation Characteristics of a Fertilizer Distribution Apparatus with a Screw from the Perspective of the Force Chain
Authors: Zhang Mengqiang , Niu Hao , Han Yuchen , Zhi Yi , Yuan Tianhao , Zhang Hong , He Yichuan , Tang Zhihui , Lan Haipeng
Published: January 2024

To investigate the causes of flow fluctuations in a worm-type distributor during the fertilization process, this study employed the discrete element method to simulate the fertilization process. The analysis focused on the influences of force chain evolution on particle flow fluctuations and the effects of the rotational speed. The results indicate that the flow fluctuations in the worm-type distributor are not solely attributed to its helical structure but are closely associated with the evolution of force chains within the particle systems. Furthermore, a one-to-one correspondence between the flow fluctuations and force-chain evolution exists. The rotational speed was found to exert significant influences on the axial and circumferential distributions of the force chains. As the rotational speed increases, the coefficient of variation (CV) of the axial distribution of the force chains gradually decreases. Meanwhile, the uniformity index (UI) of the circumferential distribution of the force chains initially increases and then decreases. In the context of a worm-type distributor, the axial distribution of force chains emerges as the dominant influencing factor for flow fluctuations. For the specific worm-type distributor model chosen in this study, the minimum flow fluctuations were observed at a rotational speed of 80 rpm. These research findings offer valuable insights into understanding the flow fluctuations of worm-type distributors and provide references for further exploration in this field.
Effect of Y2O3-Al2O3 Additives on the Microstructure and Electrical Properties Evolution of Si3N4 Ceramics
Authors: Hou Dong , Han Yu , Nie Jingkai , Zhang Yiming , Chen Leng
Published: January 2024

Si3N4 ceramic materials have great potential in the field of insulation in SF6 gas ultra-high-voltage transmission and transformation equipment due to their excellent insulation performance and thermal stability. In this paper, Y2O3-Al2O3 was used as a sintering aid to prepare high-density (>99%) Si3N4 ceramics through two-step pressureless liquid-phase sintering, and the mechanism of the influence of Y2O3-Al2O3 addition on the microstructure and electrical properties of Si3N4 ceramics was studied. The results showed that increasing the sintering aid content could increase the grain size of Si3N4 ceramics, while increasing the Y2O3 ratio could refine the grain size. When Y2O3-Al2O3 addition was 8% and the ratio was 5:3, the room temperature volume resistivity of Si3N4 ceramics was the highest, 7.33 × 1014 Ω·m, and the volume resistivity was the most stable when the sintering aid content was 12%. The internal carrier migration type of Si3N4 ceramics was mainly ion conduction, mainly along the grain boundaries. The temperature stability of the resistivity of Si3N4 ceramics could be improved by doping with Y3+ functional ions to reduce the potential barrier conductivity level and refine the grain size to improve the conduction path. The dielectric constant and dielectric loss of Si3N4 ceramics were mainly affected by interface polarization. They gradually increased with the increase in sintering aid addition. Temperature had little effect on dielectric constant and dielectric loss in the range of 20–80 °C.
Approach of Dynamic Tracking and Counting for Obscured Citrus in Smart Orchard Based on Machine Vision
Authors: Feng Yuliang , Ma Wei , Tan Yu , Yan Hao , Qian Jianping , Tian Zhiwei , Gao Ang
Published: January 2024

The approach of dynamic tracking and counting for obscured citrus based on machine vision is a key element to realizing orchard yield measurement and smart orchard production management. In this study, focusing on citrus images and dynamic videos in a modern planting mode, we proposed the citrus detection and dynamic counting method based on the lightweight target detection network YOLOv7-tiny, Kalman filter tracking, and the Hungarian algorithm. The YOLOv7-tiny model was used to detect the citrus in the video, and the Kalman filter algorithm was used for the predictive tracking of the detected fruits. In order to realize optimal matching, the Hungarian algorithm was improved in terms of Euclidean distance and overlap matching and the two stages life filter was added; finally, the drawing lines counting strategy was proposed. ln this study, the detection performance, tracking performance, and counting effect of the algorithms are tested respectively; the results showed that the average detection accuracy of the YOLOv7-tiny model reached 97.23%, the detection accuracy in orchard dynamic detection reached 95.12%, the multi-target tracking accuracy and the precision of the improved dynamic counting algorithm reached 67.14% and 74.65% respectively, which were higher than those of the pre-improvement algorithm, and the average counting accuracy of the improved algorithm reached 81.02%. The method was proposed to effectively help fruit farmers grasp the number of citruses and provide a technical reference for the study of yield measurement in modernized citrus orchards and a scientific decision-making basis for the intelligent management of orchards.
Usage of a Sensory-Motor Intervention System for Understanding the Adaptive Behavior of Insects
Authors: Shigaki Shunsuke , Ando Noriyasu
Published: January 2024

Despite their diminutive neural systems, insects exhibit sophisticated adaptive behaviors in diverse environments. An insect receives various environmental stimuli through its sensory organs and selectively and rapidly integrates them to produce an adaptive motor output. Living organisms commonly have this sensory-motor integration, and attempts have been made for many years to elucidate this mechanism biologically and reconstruct it through engineering. In this review, we provide an overview of the biological analyses of the adaptive capacity of insects and introduce a framework of engineering tools to intervene in insect sensory and behavioral processes. The manifestation of adaptive insect behavior is intricately linked to dynamic environmental interactions, underscoring the significance of experiments maintaining this relationship. An experimental setup incorporating engineering techniques can manipulate the sensory stimuli and motor output of insects while maintaining this relationship. It can contribute to obtaining data that could not be obtained in experiments conducted under controlled environments. Moreover, it may be possible to analyze an insect’s adaptive capacity limits by varying the degree of sensory and motor intervention. Currently, experimental setups based on the framework of engineering tools only measure behavior; therefore, it is not possible to investigate how sensory stimuli are processed in the central nervous system. The anticipated future developments, including the integration of calcium imaging and electrophysiology, hold promise for a more profound understanding of the adaptive prowess of insects.
Investigating Models for the Transcription of Mathematical Formulas in Images
Authors: Feichter Christian , Schlippe Tim
Published: January 2024

The automated transcription of mathematical formulas represents a complex challenge that is of great importance for digital processing and comprehensibility of mathematical content. Consequently, our goal was to analyze state-of-the-art approaches for the transcription of printed mathematical formulas on images into spoken English text. We focused on two approaches: (1) The combination of mathematical expression recognition (MER) models and natural language processing (NLP) models to convert formula images first into LaTeX code and then into text, and (2) the direct conversion of formula images into text using vision-language (VL) models. Since no dataset with printed mathematical formulas and corresponding English transcriptions existed, we created a new dataset, Formula2Text, for fine-tuning and evaluating our systems. Our best system for (1) combines the MER model LaTeX-OCR and the NLP model BART-Base, achieving a translation error rate of 36.14% compared with our reference transcriptions. In the task of converting LaTeX code to text, BART-Base, T5-Base, and FLAN-T5-Base even outperformed ChatGPT, GPT-3.5 Turbo, and GPT-4. For (2), the best VL model, TrOCR, achieves a translation error rate of 42.09%. This demonstrates that VL models, predominantly employed for classical image captioning tasks, possess significant potential for the transcription of mathematical formulas in images.
Recycling 3D Printed Concrete Waste for Normal Strength Concrete Production
Authors: Mengistu Girum Mindaye , Nemes Rita
Published: January 2024

As the use of 3D-printed concrete becomes more prevalent, the need for effective recycling methods becomes paramount. This study addresses this concern by exploring the repurposing of 3D-printed concrete waste as an aggregate in normal-strength concrete for C30/37 and C40/50 classes, covering both fine and coarse aggregates in its particle size distribution. The extent of recycled aggregate (RA) replacement was determined through sieve analysis. A two-stage investigation assessed the compressive strength performance of the concrete specimens. The initial stage produced reference specimens with no replacement, representing conventional concrete. In the second stage, variable specimens incorporated 50% and 67% recycled aggregate (RA) from 3D-printed concrete waste. Results revealed that in C40/50, both the 50% and 67% replacements consistently exhibited a higher strength than 0%. In C30/37, the 50% replacement displayed decreased strength compared to the 0% and 67%, while the 67% replacement consistently showed superior strength. Adjusting the water content impacted strength; at 67%, slight variations occurred, while at 50%, extra water led to a significant decrease. An overarching discovery is that the efficacy of the 67% replacement level holds regardless of the concrete strength class.
Analysis of Precipitation and Drought in the Main Southeastern Iberian River Headwaters (1952–2021)
Authors: Estrela María José , Corell David , Miró Juan Javier , Niclós Raquel
Published: January 2024

This study evaluated the long-term changes in precipitation patterns and drought conditions in one of the key recharge areas of the hydrological system of southern and southeastern Spain, namely, the Sierra de Cazorla y Segura, which contains the headwater sectors of the catchment basins of two important rivers, namely, the Guadalquivir and the Segura. The research covered a period of 70 years (1952–2021) and undertook an exhaustive analysis of data from 348 pluviometric stations. The most relevant results are as follows: (1) most areas experienced a decrease in the precipitation volume and number of rainy days during the study period; (2) summer and winter showed the most significant decreases; (3) weak and moderate precipitation (<40 mm/d) showed significant decreases in both volume and frequency, while heavy precipitation (≥40 mm/d) showed the opposite behavior; (4) the durations of dry periods increased, while the durations of wet periods decreased in most areas; and (5) the SPEI showed an increase under drought conditions. This research underscores the need for water resource management and resilience strategies with interdisciplinary relevance in the face of changing hydrological patterns.
Quantifying Contributions of Factors and Their Interactions to Aerosol Acidity with a Multiple-Linear-Regression-Based Framework: A Case Study in the Pearl River Delta, China
Authors: Ling Hong , Deng Mingqi , Zhang Qi , Xu Lei , Su Shuzhen , Li Xihua , Yang Liming , Mao Jingying , Jia Shiguo
Published: January 2024

This study presents an approach using multiple linear regression to quantify the impact of meteorological parameters and chemical species on aerosol pH variance in an urban setting in the Pearl River Delta, China. Additionally, it assesses the contributions of interactions among these factors to the variance in pH. The analysis successfully explains over 96% of the pH variance, attributing 85.8% to the original variables and 6.7% to bivariate interactions, with further contributions of 2.3% and 1.0% from trivariate and quadrivariate interactions, respectively. Our results highlight that meteorological factors, particularly temperature and humidity, are more influential than chemical components in affecting aerosol pH variance. Temperature alone accounts for 37.3% of the variance, while humidity contributes approximately 20%. On the chemical front, sulfate and ammonium are the most significant contributors, adding 14.3% and 9.1% to the pH variance, respectively. In the realm of bivariate interactions, the interplay between meteorological parameters and chemical components, especially the TNO3–RH pair, is exceptionally impactful, constituting 58.1% of the total contribution from interactions. In summary, this study illuminates the factors affecting aerosol pH variance and their interplay, suggesting the integration of statistical methods with thermodynamic models for enhanced understanding of aerosol acidity dynamics in the future.
Proteomic and Metabolomic Analysis of the Quercus ilex–Phytophthora cinnamomi Pathosystem Reveals a Population-Specific Response, Independent of Co-Occurrence of Drought
Authors: Hernández-Lao Tamara , Tienda-Parrilla Marta , Labella-Ortega Mónica , Guerrero-Sánchez Victor M. , Rey María-Dolores , Jorrín-Novo Jesús V. , Castillejo-Sánchez María Ángeles
Published: January 2024

Holm oak (Quercus ilex) is considered to be one of the major structural elements of Mediterranean forests and the agrosilvopastoral Spanish “dehesa”, making it an outstanding example of ecological and socioeconomic sustainability in forest ecosystems. The exotic Phytophthora cinnamomi is one of the most aggressive pathogens of woody species and, together with drought, is considered to be one of the main drivers of holm oak decline. The effect of and response to P. cinnamomi inoculation were studied in the offspring of mother trees from two Andalusian populations, Cordoba and Huelva. At the two locations, acorns collected from both symptomatic (damaged) and asymptomatic (apparently healthy) trees were sampled. Damage symptoms, mortality, and chlorophyll fluorescence were evaluated in seedlings inoculated under humid and drought conditions. The effect and response depended on the population and were more apparent in Huelva than in Cordoba. An integrated proteomic and metabolomic analysis revealed the involvement of different metabolic pathways in response to the pathogen in both populations, including amino acid metabolism pathways in Huelva, and terpenoid and flavonoid biosynthesis in Cordoba. However, no differential response was observed between seedlings inoculated under humid and drought conditions. A protective mechanism of the photosynthetic apparatus was activated in response to defective photosynthetic activity in inoculated plants, which seemed to be more efficient in the Cordoba population. In addition, enzymes and metabolites of the phenylpropanoid and flavonoid biosynthesis pathways may have conferred higher resistance in the Cordoba population. Some enzymes are proposed as markers of resilience, among which glyoxalase I, glutathione reductase, thioredoxin reductase, and cinnamyl alcohol dehydrogenase are candidates.
Therapeutic Potential of Cannabinoid Profiles Identified in Cannabis L. Crops in Peru
Authors: Wong-Salgado Pedro , Soares Fabiano , Moya-Salazar Jeel , Ramírez-Méndez José F. , Moya-Salazar Marcia M. , Apesteguía Alfonso , Castro Americo
Published: January 2024

Cannabis is a plant that is cultivated worldwide, and its use is internationally regulated, but some countries have been regulating its medicinal, social, and industrial uses. This plant must have arrived in Peru during the Spanish conquest and remains widely cultivated illicitly or informally to this day. However, new regulations are currently being proposed to allow its legal commercialization for medicinal purposes. Cannabis contains specific metabolites known as cannabinoids, some of which have clinically demonstrated therapeutic effects. It is now possible to quantitatively measure the presence of these cannabinoids in dried inflorescences, thus allowing for description of the chemical profile or “chemotype” of cannabinoids in each sample. This study analyzed the chemotypes of eight samples of dried inflorescences from cannabis cultivars in four different regions of Peru, and based on the significant variation in the cannabinoid profiles, we suggest their therapeutic potential. The most important medical areas in which they could be used include the following: they can help manage chronic pain, they have antiemetic, anti-inflammatory, and antipruritic properties, are beneficial in treating duodenal ulcers, can be used in bronchodilators, in muscle relaxants, and in treating refractory epilepsy, have anxiolytic properties, reduce sebum, are effective on Methicillin-resistant Staphylococcus aureus, are proapoptotic in breast cancer, can be used to treat addiction and psychosis, and are effective on MRSA, in controlling psoriasis, and in treating glioblastoma, according to the properties of their concentrations of cannabidiol, cannabigerol, and Δ9-tetrahydrocannabinol, as reviewed in the literature. On the other hand, having obtained concentrations of THC, we were able to suggest the psychotropic capacity of said samples, one of which even fits within the legal category of “non-psychoactive cannabis” according to Peruvian regulations.
Surgical Treatment of Paediatric Thalamic Gliomas—Single-Centre Experience
Authors: Krahulik David , Blazek Filip , Halaj Matej , Hrabalek Lumir , Stepanova Eva , Pavelka Zdenek , Rohanova Marie
Published: January 2024

The surgical treatment of paediatric thalamic gliomas has been burdened with high morbidity, and these lesions were often considered inoperable. With new approaches and intraoperative technologies, we can remove tumours once deemed inoperable. In our single centre, we have operated on 11 paediatric patients over the course of 8 years. We have performed eight GTR resections and three intended subtotal resections. The postoperative neurological deficit ranged from mild to very severe for motor weakness and none to severe for aphasia after surgery, with all of the patients improving at 3-month follow-up. Radicality in the surgical approach to thalamic gliomas in children has shown significant benefits when compared to more conservative approaches. For children with LGGs, extensive surgical resection is associated with improved prognosis and longer progression-free survival. However, it does not yield the same proportional benefit for HGGs due to its aggressive nature and worse outlook.
Promoting Physical and Mental Health among Children and Adolescents via Gamification—A Conceptual Systematic Review
Authors: Gkintoni Evgenia , Vantaraki Fedra , Skoulidi Charitini , Anastassopoulos Panagiotis , Vantarakis Apostolos
Published: January 2024

The rapid growth in digital technology usage among children and adolescents has highlighted the need for novel approaches to promote their physical and mental health. This paper investigates the viability of gamification—the application of game mechanics to non-gaming contexts—as a potent instrument for health promotion and mental health support. This conceptual systematic review seeks to examine the various published articles promoting children and adolescents’ physical and mental health through gamified techniques. These interventions can provide an interactive and engaging platform for encouraging physical activity, promoting healthy nutrition, enhancing emotional regulation, and promoting mental health. The significance of this topic stems from the pervasive use of electronic games, beginning at a young age, which makes them popular educational tools. For the review to be systematic and reproducible, the PsycINFO, Scopus, PubMed, and Elsevier databases were searched and the PRISMA method was utilized for the analysis. After analyzing the research data, empirical studies assessing the use of gamification in promoting adolescents’ physical and mental health are discussed. In conclusion, gamification has demonstrated promise for promoting children’s and adolescents’ physical and mental health. It improves motivation, commitment, and adherence to healthy behaviors. However, additional research is required to evaluate gamification interventions’ long-term effectiveness and sustainability in promoting health behaviors among this population.
Solidification Behavior of Heavy Metal Pb2+ for Spontaneous Combustion Coal Gangue-Based Geopolymers
Authors: Liu Fang , Tang Ran , Wang Baomin , Yan Jifei
Published: January 2024

Spontaneous combustion coal gangue (SCCG) is considered to be an aluminosilicate-based solid waste containing various toxic ions. The alkali-activation method for this material can not only fully use its potential hydration activity but also solidify the hazardous components to some extent. Through introducing additional Pb2+, the solidification behavior of heavy metal Pb2+ for an SCCG-based geopolymer was studied in the present paper. The solidification efficiencies were evaluated by Pb2+ leaching rates under neutral and acidic conditions, while its mechanism was explained by the methods of XRD, TG, FT-IR, SEM, and MIP. The results show that the Pb2+ solidification efficiency increases along with the curing age, and acidic rather than neutral conditions lead to a more intensive solidification capacity. Judging by the permissive maximum value of 5 mg/L, the Pb2+ original concentrations under neutral and acidic circumstances should be lower at 2.0 wt.% and 3.0 wt.%, respectively. The Pb2+ absorption is dominated by the physical process, due to the formation of no new hydration products. However, the Pb2+ addition would interrupt the reconstruction of the Si-Al network structure, slowing the accumulation of N-A-S-H gel and the densifying of the matrix. When the Pb2+ concentration grows, the sizes of hydration productions shrink continuously, more defects appear in the microstructure of the geopolymer, and the pore structure deteriorates rapidly, all of which accelerate the diffusion of toxic ions to the external condition.
Research on Energy Consumption Prediction Models for High-Rise Hotels in Guangzhou, Based on Different Machine Learning Algorithms
Authors: Zhang Jin , Yuan Chuyan , Yang Junyi , Zhao Lihua
Published: January 2024

With the advancement of information technology, energy consumption prediction models are widely used for various types of buildings (office, residential, and commercial buildings) as guidance during the design and management stages. This article will establish an efficient building energy consumption prediction model for hotel buildings. To achieve this, we collected 78 architectural drawings of high-rise hotel buildings to establish 6 kinds of typical energy consumption models in 2 standard floor layouts and 3 public area levels. Then, on this basis, we used the total energy consumption calculated by EnergyPlus as an indicator to conduct sensitivity analysis on geometric feature parameters, internal heat source parameters, and thermal parameters, respectively. Finally, we generated a building database with 5000 samples through the R programming language to calculate and verify the energy consumption. As a result, it was proved that the energy consumption of hotel buildings can be predicted accurately, and that quadratic polynomial regression, with the best accuracy and stability, is the most suitable optimization model for hotel energy consumption prediction in Guangzhou. These conclusions provide a good theoretical basis for the analysis, prediction, and optimization of energy consumption in high-rise hotel buildings in the future.
Research on the Impact of Air Temperature and Wind Speed on Ventilation in University Dormitories under Different Wind Directions (Northeast China)
Authors: Cheng Yanzhe , Yang Mingxin , Xie Songgao , Liu Jiaqi , Zheng Sheng
Published: January 2024

This study employs computational fluid dynamics to analyze the natural ventilation conditions of university student dormitories in the northeastern region of China under various outdoor wind directions, wind speeds, and temperature conditions. By separately simulating room natural ventilation efficiency under four different outdoor wind speeds (1.5 m/s, 3.3 m/s, 5.4 m/s and 7.9 m/s) at different outdoor temperatures (−10 °C, 0 °C, 10 °C and 20 ℃), curves of indoor pollutant removal rates (VOA-Time) are established for different wind directions. The study also determines the minimum ventilation time required for rooms under different environmental conditions (TVOA=70%). The data indicate that, despite the promotion of ventilation efficiency with increasing wind speed or indoor-outdoor temperature difference, the wind direction determines the extent to which these factors enhance room ventilation efficiency. Furthermore, there are corresponding mathematical relationships between TVOA=70%, outdoor temperature, wind speed, and different wind directions, allowing for predictions related to the rate of indoor carbon dioxide change. The research findings will assist students in formulating more effective ventilation strategies under complex outdoor environmental conditions.
Characterization and Analysis of Iron Ore Tailings Sediments and Their Possible Applications in Earthen Construction
Authors: Bessa Sofia , Duarte Marlo , Lage Gabriela , Mendonça Isabela , Galery Roberto , Lago Rochel , Texeira Ana Paula , Lameiras Fernando , Aguilar Maria Teresa
Published: January 2024

Mineral extraction is of ultimate importance for the economies of different countries, and Brazil is one of the world’s leading producers of iron ores. Unfortunately, dams are still the main problem, mainly in Minas Gerais, especially after the Fundão Dam rupture in 2015. Additionally, there is still a massive presence of buildings built on earth throughout the Minas Gerais mining region, built from the 18th century to today. Investigating the potential of iron ore tailings (IOT) to be incorporated into traditional earthen construction techniques in regions affected by dam ruptures presents a relevant and innovative research approach. In addition, the local reuse of these sediments should be the priority. Thus, the main objective of this work was to collect, characterize, and analyze the possibilities of the application of these tailings to produce rammed earth (RE). A complete characterization analysis was performed on the samples collected at three points. To analyze the soil-IOT compatibility, representative mixtures of RE were produced, and the specific mass, compaction, and compressive strength were performed. It was observed that the IOT samples have a high silica content and that the mixtures of IOT–soil, even without cement, reached the compressive strength values of the international standards, or even above them.
Natural Ventilation Potential of Residential Buildings in China Considering the Combined Effect of Indoor and Outdoor Air Pollution
Authors: Lin Bo , Xie Changhong , Chen Yan , Xu Xu
Published: January 2024

With its rapid economic development, China has had to confront the serious issues of high energy consumption and air pollution. Natural ventilation is regarded as an effective method to reduce building energy consumption, but it is largely influenced by indoor and outdoor air pollution. However, most of the previous studies estimating natural ventilation potential (NVP) in China do not consider air pollution. This research estimated the NVP for residential buildings in major cities from four climate regions in China (Guangzhou, Chengdu, Shanghai, Beijing, and Shenyang) while considering the combined effect of indoor and outdoor air pollution. We compared the yearly NVP in three different scenarios, namely without considering air pollution, only considering outdoor air pollution, and considering both outdoor and indoor air pollution. The results show that Guangzhou had the highest yearly NVP, followed by Shanghai, Beijing, Shenyang, and Chengdu. The impact of air pollution could reduce the annual NVP in China by 78–95%. In addition, the main factors causing a low NVP differed between the four cities. The key factors for Chengdu and Guangzhou were natural ventilation flow rate and indoor air pollution, respectively. Beijing and Shenyang were mostly influenced by outdoor air pollution. Shanghai had two main factors with similar influence degrees, namely outdoor air pollution and indoor air pollution. The findings of this study will guide architects and policymakers in better forming natural ventilation strategies.
The Intersection of Collegiate Gothic Architecture and Missionary Education: A Case Study of Anderson Hall at Soochow University
Authors: Chen Xi , He Jiabao , Wang Shiruo
Published: January 2024

This research delves into the influence of Collegiate Gothic style on modern Chinese Christian universities, with a specific focus on Soochow University’s Anderson Hall. Originating from the medieval universities of Oxford and Cambridge, the Collegiate Gothic style underwent a historical trajectory that saw its migration to the United States in the late 19th century. With Western colonization in China, Collegiate Gothic emerged as a tangible expression of Christian missions within Chinese academic institutions. Methodologically, this study employs historical analysis and empirical research to scrutinize factors influencing the choice of Collegiate Gothic style for Anderson Hall, revealing collaborations between Western architects and Chinese artisans. The analysis emphasizes the style’s impact on visual aesthetics and functionality within Anderson Hall. In conclusion, despite China’s disapproval of colonial history, the preservation of Anderson Hall testifies to its adaptability amidst sociocultural changes, serving as a silent witness to transformative moments in Chinese history and architectural technology. This paper underscores the complex interplay of influences on architectural style, particularly the significant role of missionary activities in the style, reflecting religious dissemination and the transmission of cultural values and aesthetic ideals.
Nanocomposite PVDF/TiO2 Photocatalytic Membranes for Micropollutant Removal in Secondary Effluent
Authors: Aldana Juan C. , Pedrosa Marta , Silva Adrián M. T. , Faria Joaquim L. , Acero Juan L. , Álvarez Pedro M.
Published: January 2024

In this study, a mixed-matrix method was used to prepare PVDF polymeric membranes with different amounts of TiO2 P25 photocatalyst embedded, which were employed in filtration processes in the presence of UV radiation (LED, peak emission at 375 nm) to eliminate two aqueous micropollutants (MPs) used as model compounds (venlafaxine and metoprolol). The obtained membranes were characterized to gain insights into their texture, morphology, composition, and other catalyst-related properties that could affect the photocatalytic filtration process. For that purpose, N2 adsorption–desorption, contact angle, SEM-EDX, thermal analysis, FTIR, XPS, UV-vis DRS, and PL spectroscopy were used. Filtration tests were carried out in continuous mode using a dead-end filtration cell to evaluate the performance of the prepared membranes in removing the selected MPs. Experiments were performed both in ultrapure water and a secondary effluent from a municipal wastewater treatment plant. It was found that the synthesized membranes could effectively remove the target MPs in ultrapure water, achieving up to 99% elimination. Such process performance decreased drastically in the secondary effluent with removals below 35%. Carbonate/bicarbonate ions in the secondary effluent were identified as the main scavenging substances. Thus, after the partial removal of carbonate/bicarbonate ions from the secondary effluent, the removal of MPs achieved was above 60%.
Preparation of Viable Human Neurites for Neurobiological and Neurodegeneration Studies
Authors: Brüll Markus , Geese Nils , Celardo Ivana , Laumann Michael , Leist Marcel
Published: January 2024

Few models allow the study of neurite damage in the human central nervous system. We used here dopaminergic LUHMES neurons to establish a culture system that allows for (i) the observation of highly enriched neurites, (ii) the preparation of the neurite fraction for biochemical studies, and (iii) the measurement of neurite markers and metabolites after axotomy. LUHMES-based spheroids, plated in culture dishes, extended neurites of several thousand µm length, while all somata remained aggregated. These cultures allowed an easy microscopic observation of live or fixed neurites. Neurite-only cultures (NOC) were produced by cutting out the still-aggregated somata. The potential application of such cultures was exemplified by determinations of their protein and RNA contents. For instance, the mitochondrial TOM20 protein was highly abundant, while nuclear histone H3 was absent. Similarly, mitochondrial-encoded RNAs were found at relatively high levels, while the mRNA for a histone or the neuronal nuclear marker NeuN (RBFOX3) were relatively depleted in NOC. Another potential use of NOC is the study of neurite degeneration. For this purpose, an algorithm to quantify neurite integrity was developed. Using this tool, we found that the addition of nicotinamide drastically reduced neurite degeneration. Also, the chelation of Ca2+ in NOC delayed the degeneration, while inhibitors of calpains had no effect. Thus, NOC proved to be suitable for biochemical analysis and for studying degeneration processes after a defined cut injury.