bluuebunny/crossref_metadata_2025 huggingface dataset:
Cholesterol Conjugates of Small Interfering RNA: Linkers and Patterns of Modification
Authors: Chernikov Ivan V. , Ponomareva Ul’yana A. , Meschaninova Mariya I. , Bachkova Irina K. , Vlassov Valentin V. , Zenkova Marina A. , Chernolovskaya Elena L.
Published: February 2024

Cholesterol siRNA conjugates attract attention because they allow the delivery of siRNA into cells without the use of transfection agents. In this study, we compared the efficacy and duration of silencing induced by cholesterol conjugates of selectively and totally modified siRNAs and their heteroduplexes of the same sequence and explored the impact of linker length between the 3′ end of the sense strand of siRNA and cholesterol on the silencing activity of “light” and “heavy” modified siRNAs. All 3′-cholesterol conjugates were equally active under transfection, but the conjugate with a C3 linker was less active than those with longer linkers (C8 and C15) in a carrier-free mode. At the same time, they were significantly inferior in activity to the 5′-cholesterol conjugate. Shortening the sense strand carrying cholesterol by two nucleotides from the 3′-end did not have a significant effect on the activity of the conjugate. Replacing the antisense strand or both strands with fully modified ones had a significant effect on silencing as well as improving the duration in transfection-mediated and carrier-free modes. A significant 78% suppression of MDR1 gene expression in KB-8-5 xenograft tumors developed in mice promises an advantage from the use of fully modified siRNA cholesterol conjugates in combination chemotherapy.
Synthesis and Properties of Novel Alkyl-Substituted Hexaazacyclophanes and Their Diradical Dications
Authors: Li Shunjie , Chen Jian
Published: February 2024

Radicals based on arylamine cyclophanes can be used as functional materials and show application potential in fields such as synthetic chemistry, molecular electronic components, organic light-emitting diodes, and catalytic chemistry. Using a Buchwald–Hartwig palladium-catalyzed aryl halide amination method, we synthesized a series of neutral hexaazacyclophane compounds 1–3 with different substituents in the meta–meta–meta positions of the phenyl rings. Three characteristic high-spin hexaazacyclophane diradical dications were obtained by two-electron oxidation using AgSbF6: 12·+•2[SbF6]−, 22·+•2[SbF6]−, and 32·+•2[SbF6]−. The electronic structures and physical properties of these compounds were then investigated by 1H and 13C nuclear magnetic resonance spectroscopy, cyclic voltammetry, electron paramagnetic resonance spectroscopy, superconducting quantum interferometry, ultraviolet–visible spectroscopy, and density functional theory calculations. The findings provide new ideas for designing radical species with novel physical properties and electronic structures. Importantly, the obtained radical species are not sensitive to air, making them valuable functional materials for practical applications.
Advancements and Prospects in Perovskite Solar Cells: From Hybrid to All-Inorganic Materials
Authors: Maziviero Fernando Velcic , Melo Dulce M. A. , Medeiros Rodolfo L. B. A. , Oliveira Ângelo A. S. , Macedo Heloísa P. , Braga Renata M. , Morgado Edisson
Published: February 2024

Hybrid perovskites, materials composed of metals and organic substances in their structure, have emerged as potential materials for the new generation of photovoltaic cells due to a unique combination of optical, excitonic and electrical properties. Inspired by sensitization techniques on TiO2 substrates (DSSC), CH3NH3PbBr3 and CH3NH3PbI3 perovskites were studied as a light-absorbing layer as well as an electron–hole pair generator. Photovoltaic cells based on per-ovskites have electron and hole transport layers (ETL and HTL, respectively), separated by an ac-tive layer composed of perovskite itself. Major advances subsequently came in the preparation methods of these devices and the development of different architectures, which resulted in an efficiency exceeding 23% in less than 10 years. Problems with stability are the main barrier to the large-scale production of hybrid perovskites. Partially or fully inorganic perovskites appear promising to circumvent the instability problem, among which the black perovskite phase CsPbI3 (α-CsPbI3) can be highlighted. In more advanced studies, a partial or total substitution of Pb by Ge, Sn, Sb, Bi, Cu or Ti is proposed to mitigate potential toxicity problems and maintain device efficiency.
Dual-Band All-Optical Logic Gates by Coherent Absorption in an Amorphous Silicon Graphene Metasurface
Authors: Chen Yixiao , Shen Chongyang , Li Qingyuan , Li Jianyao , Deng Xiaoxu
Published: February 2024

The dual-band polarization-independent all-optical logic gate by coherent absorption effect in an amorphous silicon (a-Si) graphene metasurface is investigated theoretically and numerically. Taking the substrate effect into consideration, the coherent perfect absorption condition of the a-Si graphene metasurface is derived on the basis of the Cartesian multipole method. The coherent nearly perfect absorption of the a-Si graphene metasurface is realized by the interference of multipole moments and the interband transition of monolayer graphene, achieving peak values of 91% and 92% at 894.5 nm and 991.5 nm, respectively. The polarization independence of the coherent absorption is revealed due to the center symmetry of the structure of the a-Si graphene metasurface. The dual-band polarization-independent all-optical XOR and OR logic gates are implemented at 894.5 nm and 991.5 nm by the a-Si graphene metasurface based on the coherent nearly perfect absorption, which has the opportunity to be utilized in all-optical computing, all-optical data processing, and future all-optical networks.
School Nutrition Personnel Perceptions of School Salad Bars before and after COVID-19
Authors: Garr Katlyn , Mendoza Ashley , Mazzeo Suzanne E. , Raynor Hollie A. , de Jonge Lilian , Tatum Kristina L. , Moore Bonnie , Bean Melanie K.
Published: February 2024

Many schools have salad bars as a means to increase students’ fruit and vegetable intake. School nutrition programs experienced drastic changes to the school food environment due to COVID-19. The aim of the current study was to understand cafeteria personnel’s experiences related to salad bar implementation before the COVID-19 pandemic and in the current school environment to inform efforts to enhance salad bar sustainability. Seven elementary schools (N = 30 personnel) installed salad bars prior to COVID-19; three of these schools (n = 13 personnel) re-opened salad bars after COVID-19. Cafeteria personnel completed surveys assessing their experiences with salad bars at both time points. Satisfaction with salad bar implementation and training was high pre- and post-COVID-19. Most agreed that salad bars increased students’ fruit and vegetable intake, yet had concerns about cleanliness and waste. Perceived job difficulty increased post-COVID-19 (p = 0.01), and satisfaction with student salad bar training decreased (p = 0.001). Additional staff support and greater student training were needed post-COVID-19. Overall, salad bars were viewed favorably; however, more challenges and lower satisfaction were reported following COVID-19. Increasing support for cafeteria personnel is needed for salad bar sustainability and improving the school food environment.
Low Iodine Nutrition Knowledge in Chinese Breastfeeding Women despite Adequate Iodine Status
Authors: Liu Shuchang , Sharp Andrew , Lane Steven , Villanueva Elmer V. , Lu Zhiliang , Ma Zheng Feei
Published: February 2024

There has been a scarcity of evidence about iodine nutrition knowledge among women during pregnancy and lactation. The aim of this study was to determine women’s iodine knowledge and the relationship between knowledge and iodine status during pregnancy and lactation. Women were recruited from a hospital in the western part of China in the third trimester of pregnancy and followed until the end of the first week of lactation. The women’s iodine status was measured by their urinary iodine concentration (UIC) and an iodine-specific, validated food frequency questionnaire (FFQ). Iodine nutrition knowledge was assessed using an iodine nutrition knowledge questionnaire. A total of 200 women (mean age of 29.0 ± 4.2 years) completed the whole study. The majority of the women did not consume enough iodine during both pregnancy and lactation (231.89 vs. 237.26 µg/day). The overall mean iodine knowledge scores in our sample of women during pregnancy and lactation were 4.77 and 4.87, indicating low iodine knowledge. The use of iodized salt and a higher education level were significantly associated with an increased iodine knowledge score. In conclusion, this study reported poor iodine nutrition knowledge in women, highlighting a public health concern. Therefore, the iodine knowledge of women should be improved, possibly via maternal health campaigns to avoid the consequences of iodine deficiency disorders in newborns.
A Deep Sequencing Strategy for Investigation of Virus Variants within African Swine Fever Virus-Infected Pigs
Authors: Johnston Camille Melissa , Olesen Ann Sofie , Lohse Louise , le Maire Madsen Agnete , Bøtner Anette , Belsham Graham J. , Rasmussen Thomas Bruun
Published: February 2024

African swine fever virus (ASFV) is the causative agent of African swine fever, an economically important disease of pigs, often with a high case fatality rate. ASFV has demonstrated low genetic diversity among isolates collected within Eurasia. To explore the influence of viral variants on clinical outcomes and infection dynamics in pigs experimentally infected with ASFV, we have designed a deep sequencing strategy. The variant analysis revealed unique SNPs at <10% frequency in several infected pigs as well as some SNPs that were found in more than one pig. In addition, a deletion of 10,487 bp (resulting in the complete loss of 21 genes) was present at a nearly 100% frequency in the ASFV DNA from one pig at position 6362-16849. This deletion was also found to be present at low levels in the virus inoculum and in two other infected pigs. The current methodology can be used for the currently circulating Eurasian ASFVs and also adapted to other ASFV strains and genotypes. Comprehensive deep sequencing is critical for following ASFV molecular evolution, especially for the identification of modifications that affect virus virulence.
Hedgehog Pathway Inhibition by Novel Small Molecules Impairs Melanoma Cell Migration and Invasion under Hypoxia
Authors: Falsini Alessandro , Giuntini Gaia , Mori Mattia , Ghirga Francesca , Quaglio Deborah , Cucinotta Antonino , Coppola Federica , Filippi Irene , Naldini Antonella , Botta Bruno , Carraro Fabio
Published: February 2024

Melanoma is the principal cause of death in skin cancer due to its ability to invade and cause metastasis. Hypoxia, which characterises the tumour microenvironment (TME), plays an important role in melanoma development, as cancer cells can adapt and acquire a more aggressive phenotype. Carbonic anhydrases (CA) activity, involved in pH regulation, is related to melanoma cell migration and invasion. Furthermore, the Hedgehog (Hh) pathway, already known for its role in physiological processes, is a pivotal character in cancer cell growth and can represent a promising pharmacological target. In this study, we targeted Hh pathway components with cyclopamine, glabrescione B and C22 in order to observe their effect on carbonic anhydrase XII (CAXII) expression especially under hypoxia. We then performed a migration and invasion assay on two melanoma cell lines (SK-MEL-28 and A375) where Smoothened, the upstream protein involved in Hh regulation, and GLI1, the main transcription factor that determines Hh pathway activation, were chemically inhibited. Data suggest the existence of a relationship between CAXII, hypoxia and the Hedgehog pathway demonstrating that the chemical inhibition of the Hh pathway and CAXII reduction resulted in melanoma migration and invasion impairment especially under hypoxia. As in recent years drug resistance to small molecules has arisen, the development of new chemical compounds is crucial. The multitarget Hh inhibitor C22 proved to be effective without signs of cytotoxicity and, for this reason, it can represent a promising compound for future studies, with the aim to reach a better melanoma disease management.
Morpho-Anatomical Modulation of Seminal Roots in Response to Water Deficit in Durum Wheat (Triticum turgidum var. durum)
Authors: Felouah Oum Cheikh , Ammad Faiza , Adda Ahmed , Bouzid Assia , Gharnaout Mohammed Lotfi , Evon Philippe , Merah Othmane
Published: February 2024

The productivity of durum wheat in Mediterranean regions is greatly reduced by water deficits that vary in intensity and time of occurrence. The development of more tolerant cultivars is the main solution for fighting these stresses, but this requires prior study of their mechanisms. The involvement of the root system in drought avoidance is of major importance. It is in this context that the present work attempts to establish the impact of morpho-anatomical remodeling of seminal roots on dehydration avoidance at the javelina stage in five durum wheat genotypes grown under three water regimes, 100%, 60% and 30% of field capacity (FC). In the last two treatments, which were applied by stopping irrigation, moisture was concentrated mainly in the depths of the substrate cylinders and was accompanied by greater root elongation compared with the control. The elongation reached rates of 20 and 22% in the ACSAD 1231 genotype and 12 and 13% in the Waha genotype, in the 60% FC and 30% FC treatments respectively. The seminal roots anatomy was also modified by water deficit in all genotypes but to different degrees. The diameter of vessels in the late metaxylem vessels was reduced, reaching 17.3 and 48.2% in the Waha genotype in the 60% FC and 30% FC treatments, respectively. The water deficit also increased the number of vessels in the early metaxylem, while reducing the diameter of its conducting vessels. ACSAD 1361 and Langlois genotypes stood out with the highest rates of diameter reduction. The morpho-anatomical transformations of the roots contributed effectively to the plants’ absorption of water and, consequently, to the maintenance of a fairly high relative water content, approaching 80%.
Sustainable Composites: Analysis of Filler–Rubber Interaction in Natural Rubber–Styrene–Butadiene Rubber/Polyurethane Composites Using the Lorenz–Park Method and Scanning Electron Microscopy
Authors: De Carvalho Arthur Pimentel , Dos Santos Harison Franca , Ribeiro Gabriel Deltrejo , Hiranobe Carlos Toshiyuki , Goveia Danielle , Gennaro Elmer Mateus , Paim Leonardo Lataro , Dos Santos Renivaldo José
Published: February 2024

This study examined micronized polyurethane residues as a reinforcing filler in elastomeric composites made from natural rubber (NR) and styrene–butadiene rubber (SBR). Due to growing environmental concerns, this research aimed to find sustainable alternatives to synthetic materials. The results indicated that adding micronized polyurethane improved the mechanical properties of the composites, reinforcing the polymer matrix and increasing the cross-link density as a barrier against solvents. The composites met the requirements for industrial applications, though; at 40 phr of polyurethane filler, material deformation was reduced, indicating saturation. FTIR analysis confirmed the homogeneity of the materials without chemical reactions, while electron microscopy revealed an increase in the number of particles and irregularities with the filler. The composite with 10 phr showed a lower volume loss in abrasion resistance, meeting the standards for soles. The composite with 30 phr of polyurethane achieved the best results without the filler’s saturation and met the footwear industry’s requirements. The results show the potential for sustainable practices in industry using this elastomeric blend.
The Influence of TiO2–Lignin Hybrid Fillers in Low-Density Polyethylene Composites on Photocatalytic Performance and UV-Barrier Properties
Authors: Jędrzejczak Patryk , Cegłowski Michał , Bula Karol , Klapiszewski Łukasz
Published: February 2024

The main objective of this study was to discover new packaging materials that could integrate one of the most expected properties, such as UV protection, with a self-cleaning ability defined as photocatalytic performance. Accordingly, new hybrid additives were used to transform LDPE films into materials with complex performance properties. In this study, titanium dioxide–lignin (TL) hybrid systems with a weight ratio of inorganic to organic precursors of 5-1, 1-1, and 1-5 were prepared using a mechanical method. The obtained materials and pristine components were characterized using measurement techniques and research methods, such as Fourier-transform infrared spectroscopy (FTIR), thermal stability analysis (TGA/DTG), measurement of the electrokinetic potential as a function of pH, scanning electron microscopy (SEM), and particle size distribution measurement. It was found that hydrogen bonds were formed between the organic and inorganic components, based on which the obtained systems were classified as class I hybrid materials. In the next step, inorganic–organic hybrid systems and pristine components were used as fillers for a low-density polyethylene (LDPE) composite, 5 and 10% by weight, in order to determine their impact on parameters such as tensile elongation at break. Polymer composites containing titanium dioxide in their matrix were then subjected to a test of photocatalytic properties, based on which it was found that all materials with TiO2 in their structure exhibit photocatalytic properties, whereby the best results were obtained for samples containing the TiO2–lignin hybrid system (1-1). The mechanical tests showed that the thin sheet films had a strong anisotropy due to chill-roll extrusion, ranging from 1.98 to 3.32. UV–Vis spectroscopy revealed four times higher light absorption for composites in which lignin was present than for pure LDPE, in the 250–450 nm range. On the other hand, the temperature at 5% and 30% weight loss revealed by TGA testing increased the highest performance for LDPE/TiO2 materials (by 20.4 °C and 8.7 °C, respectively).
Development of a Machine Learning Model to Predict the Color of Extruded Thermoplastic Resins
Authors: Neo Puay Keong , Leong Yew Wei , Soon Moi Fuai , Goh Qing Sheng , Thumsorn Supaphorn , Ito Hiroshi
Published: February 2024

The conventional method for the color-matching process involves the compounding of polymers with pigments and then preparing plaques by using injection molding before measuring the color by an offline spectrophotometer. If the color fails to meet the L*, a*, and b* standards, the color-matching process must be repeated. In this study, the aim is to develop a machine learning model that is capable of predicting offline color using data from inline color measurements, thereby significantly reducing the time that is required for the color-matching process. The inline color data were measured using an inline process spectrophotometer, while the offline color data were measured using a bench-top spectrophotometer. The results showed that the Bagging with Decision Tree Regression and Random Forest Regression can predict the offline color data with aggregated color differences (dE) of 10.87 and 10.75. Compared to other machine learning methods, Bagging with Decision Tree Regression and Random Forest Regression excel due to their robustness, ability to handle nonlinear relationships, and provision of insights into feature importance. This study offers valuable guidance for achieving Bagging with Decision Tree Regression and Random Forest Regression to correlate inline and offline color data, potentially reducing time and material waste in color matching. Furthermore, it facilitates timely corrections in the event of color discrepancies being observed via inline measurements.
Improving Unsupervised Object-Based Change Detection via Hierarchical Multi-Scale Binary Partition Tree Segmentation: A Case Study in the Yellow River Source Region
Authors: Du Yihong , He Xiaoming , Chen Liujia , Wang Duo , Jiao Weili , Liu Yongkun , He Guojin , Long Tengfei
Published: February 2024

Change detection in remote sensing enables identifying alterations in surface characteristics over time, underpinning diverse applications. However, conventional pixel-based algorithms encounter constraints in terms of accuracy when applied to medium- and high-resolution remote sensing images. Although object-oriented methods offer a step forward, they frequently grapple with missing small objects or handling complex features effectively. To bridge these gaps, this paper proposes an unsupervised object-oriented change detection approach empowered by hierarchical multi-scale segmentation for generating binary ecosystem change maps. This approach meticulously segments images into optimal sizes and leverages multidimensional features to adapt the Iteratively Reweighted Multivariate Alteration Detection (IRMAD) algorithm for GaoFen WFV data. We rigorously evaluated its performance in the Yellow River Source Region, a critical ecosystem conservation zone. The results unveil three key strengths: (1) the approach achieved excellent object-level change detection results, making it particularly suited for identifying changes in subtle features; (2) while simply increasing object features did not lead to a linear accuracy gain, optimized feature space construction effectively mitigated dimensionality issues; and (3) the scalability of our approach is underscored by its success in mapping the entire Yellow River Source Region, achieving an overall accuracy of 90.09% and F-score of 0.8844. Furthermore, our analysis reveals that from 2015 to 2022, changed ecosystems comprised approximately 1.42% of the total area, providing valuable insights into regional ecosystem dynamics.
Quasi-Dense Matching for Oblique Stereo Images through Semantic Segmentation and Local Feature Enhancement
Authors: Yao Guobiao , Zhang Jin , Zhu Fengqi , Gong Jianya , Jin Fengxiang , Fu Qingqing , Ren Xiaofang
Published: February 2024

This paper proposes a quasi-dense feature matching algorithm that combines image semantic segmentation and local feature enhancement networks to address the problem of the poor matching of image features because of complex distortions, considerable occlusions, and a lack of texture on large oblique stereo images. First, a small amount of typical complex scene data are used to train the VGG16-UNet, followed by completing the semantic segmentation of multiplanar scenes across large oblique images. Subsequently, the prediction results of the segmentation are subjected to local adaptive optimization to obtain high-precision semantic segmentation results for each planar scene. Afterward, the LoFTR (Local Feature Matching with Transformers) strategy is used for scene matching, enabling enhanced matching for regions with poor local texture in the corresponding planes. The proposed method was tested on low-altitude large baseline stereo images of complex scenes and compared with five classical matching methods. Results reveal that the proposed method exhibits considerable advantages in terms of the number of correct matches, correct rate of matches, matching accuracy, and spatial distribution of corresponding points. Moreover, it is well-suitable for quasi-dense matching tasks of large baseline stereo images in complex scenes with considerable viewpoint variations.
Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST)
Authors: Šafran Valentino , Lin Simon , Nateqi Jama , Martin Alistair G. , Smrke Urška , Ariöz Umut , Plohl Nejc , Rojc Matej , Bēma Dina , Chávez Marcela , Horvat Matej , Mlakar Izidor
Published: February 2024

The importance and value of real-world data in healthcare cannot be overstated because it offers a valuable source of insights into patient experiences. Traditional patient-reported experience and outcomes measures (PREMs/PROMs) often fall short in addressing the complexities of these experiences due to subjectivity and their inability to precisely target the questions asked. In contrast, diary recordings offer a promising solution. They can provide a comprehensive picture of psychological well-being, encompassing both psychological and physiological symptoms. This study explores how using advanced digital technologies, i.e., automatic speech recognition and natural language processing, can efficiently capture patient insights in oncology settings. We introduce the MRAST framework, a simplified way to collect, structure, and understand patient data using questionnaires and diary recordings. The framework was validated in a prospective study with 81 colorectal and 85 breast cancer survivors, of whom 37 were male and 129 were female. Overall, the patients evaluated the solution as well made; they found it easy to use and integrate into their daily routine. The majority (75.3%) of the cancer survivors participating in the study were willing to engage in health monitoring activities using digital wearable devices daily for an extended period. Throughout the study, there was a noticeable increase in the number of participants who perceived the system as having excellent usability. Despite some negative feedback, 44.44% of patients still rated the app’s usability as above satisfactory (i.e., 7.9 on 1–10 scale) and the experience with diary recording as above satisfactory (i.e., 7.0 on 1–10 scale). Overall, these findings also underscore the significance of user testing and continuous improvement in enhancing the usability and user acceptance of solutions like the MRAST framework. Overall, the automated extraction of information from diaries represents a pivotal step toward a more patient-centered approach, where healthcare decisions are based on real-world experiences and tailored to individual needs. The potential usefulness of such data is enormous, as it enables better measurement of everyday experiences and opens new avenues for patient-centered care.
Intelligent Path Planning with an Improved Sparrow Search Algorithm for Workshop UAV Inspection
Authors: Zhang Jinwei , Zhu Xijing , Li Jing
Published: February 2024

Intelligent workshop UAV inspection path planning is a typical indoor UAV path planning technology. The UAV can conduct intelligent inspection on each work area of the workshop to solve or provide timely feedback on problems in the work area. The sparrow search algorithm (SSA), as a novel swarm intelligence optimization algorithm, has been proven to have good optimization performance. However, the reduction in the SSA’s search capability in the middle or late stage of iterations reduces population diversity, leading to shortcomings of the algorithm, including low convergence speed, low solution accuracy and an increased risk of falling into local optima. To overcome these difficulties, an improved sparrow search algorithm (namely the chaotic mapping–firefly sparrow search algorithm (CFSSA)) is proposed by integrating chaotic cube mapping initialization, firefly algorithm disturbance search and tent chaos mapping perturbation search. First, chaotic cube mapping was used to initialize the population to improve the distribution quality and diversity of the population. Then, after the sparrow search, the firefly algorithm disturbance and tent chaos mapping perturbation were employed to update the positions of all individuals in the population to enable a full search of the algorithm in the solution space. This technique can effectively avoid falling into local optima and improve the convergence speed and solution accuracy. The simulation results showed that, compared with the traditional intelligent bionic algorithms, the optimized algorithm provided a greatly improved convergence capability. The feasibility of the proposed algorithm was validated with a final simulation test. Compared with other SSA optimization algorithms, the results show that the CFSSA has the best efficiency. In an inspection path planning problem, the CFSSA has its advantages and applicability and is an applicable algorithm compared to SSA optimization algorithms.
Missing Data Imputation Method Combining Random Forest and Generative Adversarial Imputation Network
Authors: Ou Hongsen , Yao Yunan , He Yi
Published: February 2024

(1) Background: In order to solve the problem of missing time-series data due to the influence of the acquisition system or external factors, a missing time-series data interpolation method based on random forest and a generative adversarial interpolation network is proposed. (2) Methods: First, the position of the missing part of the data is calibrated, and the trained random forest algorithm is used for the first data interpolation. The output value of the random forest algorithm is used as the input value of the generative adversarial interpolation network, and the generative adversarial interpolation network is used to calibrate the position. The data are interpolated for the second time, and the advantages of the two algorithms are combined to make the interpolation result closer to the true value. (3) Results: The filling effect of the algorithm is tested on a certain bearing data set, and the root mean square error (RMSE) is used to evaluate the interpolation results. The results show that the RMSE of the interpolation results based on the random forest and generative adversarial interpolation network algorithms in the case of single-segment and multi-segment missing data is only 0.0157, 0.0386, and 0.0527, which is better than the random forest algorithm, generative adversarial interpolation network algorithm, and K-nearest neighbor algorithm. (4) Conclusions: The proposed algorithm performs well in each data set and provides a reference method in the field of data filling.
Identification of Illegal Dumping and Community Views in Informal Settlements, Cape Town: South Africa
Authors: Jakeni Yamkela , Maphanga Thabang , Madonsela Benett Siyabonga , Malakane Karabo Concelia
Published: February 2024

Municipalities face the greatest difficulty in implementing an efficient and effective waste collection system, especially in informal settlements with limited spatial planning. Illegal dumping is exacerbated by the proliferation of informal settlements and the lack of adequate waste management services provided by municipalities. A geographic information system (GIS) provides decision makers with a framework for analyzing and simulating a wide variety of spatial problems, including waste management issues. The purpose of this study is to map areas susceptible to illegal dumping and to determine why the community dumps there. The data were collected qualitatively via a questionnaire using a purposeful sampling technique, and SPSS 28.0 was used to analyze the data. The accessibility of streets and the availability of vacant land affected the location and concentration of illegal dumping in the test area. The lands within a buffer zone of 250 to 500 m of populated areas are the most vulnerable. The majority of residents have individual garbage receptacles, while a minority of 43.18% do not. A total of 52 dumpsites were identified inside the red zone of the model, suggesting a strong likelihood of illegal dumping activities. Hence, the community continues to have difficulties in effectively managing garbage disposal, compelling them to resort to alternative methods of waste disposal.
Evaluation of Rheological Properties of Polymer-Modified Asphalt Binders and Mastics with Organic Additive—Imidazoline
Authors: Mielczarek Marta , Fornalczyk Sylwia , Słowik Mieczysław
Published: February 2024

The article presents the results of testing the asphalt binder modified with SBS copolymer (5%) and its mixture with mineral fillers called asphalt mastics. The aim of the research and analysis was to check the possibility of using an organic additive in the form of imidazolines and to assess their impact on the viscoelastic properties of the obtained asphalt mastics. The main advantage of using imidazoline is the increased resistance of asphalt mixtures to low-temperature cracking at the top of the road route and reducing its maintenance costs. Based on the examination of the adhesion of the binder with the addition of various imidazolines to the aggregate, a selection was made from six analyzed subtypes. One of them was selected for further research. The tests were carried out in a dynamic shear rheometer in a wide temperature range from −36 °C to 82 °C, determining the most important parameters of the tested materials, i.e., dynamic shear modulus (|G*|), phase angle (δ) and the non-recoverable creep compliance (Jnr). The test results and their analysis confirmed the beneficial effect of imidazoline on the viscoelastic properties of mastics in the low-temperature range, even at the lowest content of 0.2%. Based on the results of the determination of Jnr and |G*|/sinδ in the range of high operating temperatures, no significant deterioration in permanent deformation parameters was observed. Moreover, the use of imidazoline reduces technological temperatures during the production of HMA used in the pavement and, therefore, reduces CO2 emissions into the atmosphere.
A Dual-Channel Cooperative Strategy between Recyclers and E-Tailers for the Offline and Online Recycling of Waste Electronics
Authors: Wei Hairui , Wang Xiaoyang , Yang Tingshu
Published: February 2024

A Stackelberg game model was formulated for dual recycling channels for a supply chain with a recycler and an e-tailer, who recycle and resell waste electronics. A reverse solution was adopted to find the optimal recycling prices, the optimal selling prices, and the supply chain’s overall profits for cooperative and non-cooperative models. The profits gained in the cooperative model were greater. We proposed a revenue-sharing contract to investigate the profit distribution. Finally, we validated the effectiveness of the cooperative recycling model through numerical simulations, calculated the revenue-sharing factors, and analyzed the effects of these factors on the decisions of the recycler and the e-tailer. By comparing the dual-channel non-cooperative recycling model based on online and offline recycling by the recycler to the dual-channel cooperative recycling model based on offline recycling by the recycler and online recycling by the e-tailer, as well as examining the results in relation to the contracts, we found that the recycler and the e-tailer should cooperate in recycling electronics to maximize the supply chain’s overall profits. However, the e-tailer will see reduced profits and may be less willing to cooperate, so it is necessary to formulate a revenue-sharing contract. The revenue-sharing factors in the contract must be set within a reasonable range; otherwise, either party could see reduced profits and renounce cooperation, even if the supply chain’s overall profit is maximized. The recycler is the more critical party for achieving cooperation. In this paper, we research the cooperative strategy between recyclers and e-tailers that is conducive for expanding the market scale of waste electronics recycling and improving the profits of both parties, while promoting the sustainable development of the supply chain.
Sustainable Production of Ultrathin Ge Freestanding Membranes
Authors: Hanuš Tadeáš , Ilahi Bouraoui , Cho Jinyoun , Dessein Kristof , Boucherif Abderraouf
Published: February 2024

Germanium (Ge) is a critical material for applications in space solar cells, integrated photonics, infrared imaging, sensing, and photodetectors. However, the corresponding cost and limited availability hinder its potential for widespread applications. However, using Ge freestanding membranes (FSMs) allows for a significant reduction in the material consumption during device fabrication while offering additional advantages such as lightweight and flexible form factor for novel applications. In this work, we present the Ge FSM production process involving sequential porous Ge (PGe) structure formation, Ge membrane epitaxial growth, detachment, substrate cleaning, and subsequent reuse. This process enables the fabrication of multiple high-quality monocrystalline Ge FSMs from the same substrate through efficient substrate reuse at a 100 mm wafer scale by a simple and low-cost chemical cleaning process. A uniform, high-quality PGe layer is produced on the entire recovered substrate. By circumventing the use of conventional high-cost chemical–mechanical polishing or even substantial chemical wet-etching, and by using an optimized PGe structure with reduced thickness, the developed process allows for both cost and an environmental impact reduction in Ge FSMs production, lowering the amount of Ge used per membrane fabrication. Moreover, this process employs large-scale compatible techniques paving the way for the sustainable production of group IV FSMs for next-generation flexible optoelectronics.
Direct Detection of Dark Matter: A Critical Review
Authors: Misiaszek Marcin , Rossi Nicola
Published: February 2024

The nature of dark matter in the Universe is one of the hardest unsolved problems in modern physics. Indeed, on one hand, the overwhelming indirect evidence from astrophysics seems to leave no doubt about its existence; on the other hand, direct search experiments, especially those conducted with low-background detectors in underground laboratories all over the world, seem to deliver only null results with a few debated exceptions. Furthermore, the lack of predicted candidates on the LHC energy scale has made this dichotomy even more puzzling. We will recall the most important phases of this novel branch of experimental astro-particle physics, analyzing the interconnections among the main projects involved in this challenging quest, and we will draw conclusions slightly different from how the problem is commonly understood.
A Simple Model of the Energy Threshold for Snowball Chambers
Authors: Szydagis Matthew , Levy Cecilia , Bolotnikov Aleksey E. , Diwan Milind V. , Homenides George J. , Kamaha Alvine C. , Martin Joshua , Rosero Richard , Yeh Minfang
Published: February 2024

Cloud and bubble chambers have historically been used for particle detection, capitalizing on supersaturation and superheating, respectively. Here, we present new results from a prototype snowball chamber, in which an incoming particle triggers the crystallization of a purified, supercooled liquid. We demonstrate, for the first time, simulation agreement with our first results from 5 years ago: the higher temperature of the freezing of water and significantly shorter time spent supercooled compared to the control in the presence of a Cf-252 fission neutron source. This is accomplished by combining Geant4 modeling of neutron interactions with the Seitz nucleation model used in superheated bubble chambers, including those seeking dark matter. We explore the possible implications of using this new technology for GeV-scale WIMP searches, especially in terms of spin-dependent proton coupling, and report the first supercooling of WbLS (water-based liquid scintillator).
Low-Flow Identification in Flood Frequency Analysis: A Case Study for Eastern Australia
Authors: Rima Laura , Haddad Khaled , Rahman Ataur
Published: February 2024

Design flood estimation is an essential step in many water engineering design tasks such as the planning and design of infrastructure to reduce flood damage. Flood frequency analysis (FFA) is widely used in estimating design floods when the at-site flood data length is adequate. One of the problems in FFA with an annual maxima (AM) modeling approach is deciding how to handle smaller discharge values (outliers) in the selected AM flood series at a given station. The objective of this paper is to explore how the practice of censoring (which involves adjusting for smaller discharge values in FFA) affects flood quantile estimates in FFA. In this regard, two commonly used probability distributions, log-Pearson type 3 (LP3) and generalized extreme value distribution (GEV), are used. The multiple Grubbs and Beck (MGB) test is used to identify low-flow outliers in the selected AM flood series at 582 Australian stream gauging stations. It is found that censoring is required for 71% of the selected stations in using the MGB test with the LP3 distribution. The differences in flood quantile estimates between LP3 (with MGB test and censoring) and GEV distribution (without censoring) increase as the return period reduces. A modest correlation is found (for South Australian catchments) between censoring and the selected catchment characteristics (correlation coefficient: 0.43), with statistically significant associations for the mean annual rainfall and catchment shape factor. The findings of this study will be useful to practicing hydrologists in Australia and other countries to estimate design floods using AM flood data by FFA. Moreover, it may assist in updating Australian Rainfall and Runoff (national guide).
Optimization of H2 Supply to the Refuelling Infrastructure for Long-Haul Trucks: Centralized versus Local H2 Production, and Using Transportation by Tanker Truck or Pipeline
Authors: Mahbub Nafisa , Ribberink Hajo
Published: February 2024

In a simulation study, it was investigated how the costs of supplying H2 for the refuelling of long-haul trucks along highways in Canada can be minimized by optimizing the design of the refuelling infrastructure. Scenarios using local or centralized blue H2 production were evaluated using two different modes of H2 transportation (liquid H2 tanker trucks and pipelines). For each scenario, the average H2 supply costs were determined considering H2 production costs from facilities of different sizes and transportation costs for H2 that was not produced locally. Average H2 supply costs were 2.83 CAD/kg H2 for the scenario with local H2 production at each refuelling site, 3.22–3.27 CAD/kg H2 for scenarios using centralized H2 production and tanker truck transportation, and 2.92–2.96 CAD/kg H2 for centralized H2 production scenarios with pipeline transportation. Optimized scenarios using the cheaper transportation option (tanker truck or pipeline) for each highway segment had average H2 supply costs (2.82–2.88 CAD/kg H2) similar to those of using only local H2 production, with slightly lower costs for the scenario using the largest H2 production volumes. Follow-on research is recommended to include the impact of CO2 transportation (from blue H2 production) on the design of an optimum supply infrastructure.
Assessing the uptake of incentivised physical health checks for people with serious mental illness: a cohort study in primary care
Authors: Matias Maria Ana , Jacobs Rowena , Aragón María José , Fernandes Luis , Gutacker Nils , Siddiqi Najma , Kasteridis Panagiotis
Published: February 2024

Background

People with serious mental illness are more likely to experience physical illnesses. The onset of many of these illnesses can be prevented if detected early. Physical health screening for people with serious mental illness is incentivised in primary care in England through the Quality and Outcomes Framework (QOF). GPs are paid to conduct annual physical health checks on patients with serious mental illness, including checks of body mass index (BMI), cholesterol, and alcohol consumption.

Aim

To assess the impact of removing and reintroducing QOF financial incentives on uptake of three physical health checks (BMI, cholesterol, and alcohol consumption) for patients with serious mental illness.

Design and setting

Cohort study using UK primary care data from the Clinical Practice Research Datalink between April 2011 and March 2020.

Method

A difference-in-difference analysis was employed to compare differences in the uptake of physical health checks before and after the intervention, accounting for relevant observed and unobserved confounders.

Results

An immediate change was found in uptake after physical health checks were removed from, and after they were added back to, the QOF list. For BMI, cholesterol, and alcohol checks, the overall impact of removal was a reduction in uptake of 14.3, 6.8, and 11.9 percentage points, respectively. The reintroduction of BMI screening in the QOF increased the uptake by 10.2 percentage points.

Conclusion

This analysis supports the hypothesis that QOF incentives lead to better uptake of physical health checks.
Bioinformatics – Supporting modern life science research, applications, and challenges
Authors: Singh Sarvendra Vikram
Published: February 2024

Bioinformatics is an interdisciplinary field that develops methods, software tools for understanding biological data and aims to investigate questions about biological composition, structure, function, and evolution of molecules, cells, tissues, and organisms using mathematics, informatics, statistics, and computer science. As we are moving towards the era of cutting-edge technologies there will be a lot of data to store, process and analyze.  It offers analysis software for data studies and comparisons and provides tools for modeling, visualizing, exploring and interpreting data. It includes analysis, structural and functional characterization of biomolecules leading to the development of Genomics, Proteomics, Transcriptomics, and Metabolomics, etc. Drug discovery and development tools, supported by recent advancements in machine learning and cloud computing should shorten the time to find and produce an efficient drug compound with fewer side effects and more results emerge as a branch called Chemo-informatics. Personalized medicine where bioinformatics can help a lot to make drug molecules based on the genetic makeup of individuals for better outcomes is a prime area of research and need of the society at present. The major futures challenge of the scientific community is to create an in-vitro model of whole-cell or organism and further simulating a whole cell or an organism by applying in-silico approaches. To achieve that, reliable tools that utilize those technologies need to be developed and tested. Bioinformatics reduces the search space/size of the problem by thousand times. The main goal is to convert a multitude of complex data into useful information and knowledge. As a consequence of understanding such data, one can basically engineer longer life for society.
Design and mechanic analysis of asphalt pavements with subgrade reinforced using the AEMC software
Authors: De Mello Pablo , Simões Gabriel Bueno Brandão , Gidrão Gustavo de Miranda Saleme , Bosse Rúbia Mara , Kempka Mariane , Silvestro Laura
Published: February 2024

The Construction industry is one of the major contributors to waste generation in various aspects of its production chain. Construction and Demolition Waste (CDW) stand out, generated by the lack of reuse and inadequate disposal, as well as a lack of knowledge about the potential uses of this material. Thus, this article presents a methodology for the use and design of asphalt pavement layers that use CDW as coarse aggregate and/or infrastructure layer. In this context, a mechanical analysis of the material used as a subgrade reinforcement in asphalt pavements for roads is carried out. In this sense, the study promoted the California Bearing Ratio (CBR) test of recycled aggregate, and subsequently, empirical design was performed using the DNIT method and mechanistic structural evaluation using the MeDiNa AEMC. The results of stresses, strains, and displacements reveal that the material can partially replace the simple granular gravel (BGS) as a sub-base material, contributing positively to the structural performance of the road infrastructure. It should be noted that this is a preliminary study, but the use of the material may be of interest in the short and medium term, significantly contributing to another way of useful and conscious disposal, bringing sustainability to the Construction industry.