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Reconfigurable intelligent surfaces (RISs) are anticipated to constitute a critical component of forthcoming communication networks due to their ability to establish controllable wireless environments. Furthermore, RIS can be leveraged to solve infeasible localization problems. This paper presents a novel adoption of the geometric dilution of precision (GDoP) analysis in the design of non-line of sight (NLoS) single anchor millimetre wave (mmWave) large RIS-aided localization in the near-field. Considering downlink transmission, the time difference of arrival (TDoA) is used to estimate the positioning by extracting the signal contribution of each RIS tile. Considering the enriched time of arrival (ToA) measurements provided by RIS, the RIS tiles involved in TDoA-based estimation should be selected properly. Therefore, the GDoP adopted in this context is to select RIS tile combinations that achieve minimum GDoP values. It has been shown via numerical simulation that the proposed design of the RIS-aided localization outperforms other state-of-the-art techniques that adopt the signal-to-noise ratio (SNR) for the selection of the RIS tiles. It is demonstrated that the proposed scheme can provide sufficient localization accuracy involving only 10% of RIS tiles, whereas the SNR method requires about (70–80) % of the tiles to approximately achieve the same accuracy. [ABSTRACT FROM AUTHOR]

This research introduces innovative approaches to enhance intrusion detection systems (IDSs) by addressing critical challenges in existing methods. Various machine-learning techniques, including nature-inspired metaheuristics, Bayesian algorithms, and swarm intelligence, have been proposed in the past for attribute selection and IDS performance improvement. However, these methods have often fallen short in terms of detection accuracy, detection rate, precision, and F-score. To tackle these issues, the paper presents a novel hybrid feature selection approach combining the Bat metaheuristic algorithm with the Residue Number System (RNS). Initially, the Bat algorithm is utilized to partition training data and eliminate irrelevant attributes. Recognizing the Bat algorithm's slower training and testing times, RNS is incorporated to enhance processing speed. Additionally, principal component analysis (PCA) is employed for feature extraction. In a second phase, RNS is excluded for feature selection, allowing the Bat algorithm to perform this task while PCA handles feature extraction. Subsequently, classification is conducted using naive bayes, and k-Nearest Neighbors. Experimental results demonstrate the remarkable effectiveness of combining RNS with the Bat algorithm, achieving outstanding detection rates, accuracy, and F-scores. Notably, the fusion approach doubles processing speed. The findings are further validated through benchmarking against existing intrusion detection methods, establishing their competitiveness. [ABSTRACT FROM AUTHOR]

The class imbalance problem, in which the distribution of different classes in training data is unequal or skewed, is a prevailing problem. This can lead to classifier algorithms being biased, negatively impacting the performance of the minority class. In this paper, we addressed the class imbalance problem in datasets for aspect-based sentiment classification. Aspect-based Sentiment Classification (AbSC) is a type of fine-grained sentiment analysis in which sentiments about particular aspects of an entity are extracted. In this work, we addressed the issue of class imbalance by creating synthetic data. For synthetic data generation, two techniques have been proposed: paraphrasing using the PEGASUS fine-tuned model and backtranslation using the M2M100 neural machine translation model. We compared these techniques with two other class balancing techniques, such as weighted oversampling and cross-entropy loss with class weight. An extensive experimental study has been conducted on three benchmark datasets for restaurant reviews: SemEval-2014, SemEval-2015, and SemEval-2016. We applied these methods to the BERT-based deep learning model for aspect-based sentiment classification and studied the effect of balancing the data on the performance of these models. Our proposed balancing technique, using synthetic data, yielded better results than the other two existing methods for dealing with multi-class imbalance. [ABSTRACT FROM AUTHOR]

Patients previously examined for cancer with a negative result may present in general practice with ongoing or new symptoms or signs suggestive of cancer. This paper explores the potential existence of a relatively safe period for cancer occurrence after receiving negative examination results for specific types of cancer, including lung (CT thorax), upper gastrointestinal (gastroscopy), colorectal (colonoscopy), bladder (cystoscopy), and breast (clinical mammography). Register-based time-to-event analyses. Denmark. All 3.3 million citizens aged 30–85 years who on January first, 2017, had not previously been diagnosed with the specific type of cancer were categorized based on the time since their most recent examination. Using 1-year follow-up, we calculated the age- and sex-adjusted hazard ratios of being diagnosed with the related cancer, with non-examined individuals as reference. Negative examination results were defined as the absence of a cancer diagnosis within 6 months following the examination. Previous negative examination results were common, also among those diagnosed with cancer during follow-up. For 10 years after a negative colonoscopy the risk of diagnosing a colorectal cancer was nearly halved. However, already 1 year after a clinical mammography and 2 years after a CT thorax the risk of diagnosing the related cancers was significantly higher among those with a previous negative result compared to non-examined individuals. This study did not identify a post-examination period in which the cancer risk, compared to non-examined individuals, was sufficiently low to confidently rule out any of the investigated cancers. What should one expect when considering re-examining a patient with a negative result of a previous examination for cancer? We found that previous negative examination results are common in the general population and among those subsequently diagnosed with cancer. We did not find a safe period after any of the examinations in which a negative result alone could safely rule out the presence of cancer. [ABSTRACT FROM AUTHOR]

In this paper, we will conclude the results of Bufeng-1 (BF-1) A/B data processing, calibration workflow, and validation of the calibrated sea surface winds, land surface soil moisture, and sea surface height measurements. Since 2019, the BF-1 mission has operated in-orbit for over 4 years. The Earth reflected delay Doppler maps (DDMs) are continuously collected to perform global sea surface and land observations. At the same time, the intermediate frequency (IF) raw data are also obtained for 12 seconds every pass in diagnostic mode. To begin with, a brief description of the spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) technique will be provided in the introduction. Next, we will present the overview of Chinese BF-1 mission and the data specifications used in our research. In the next section, the BF-1 mission-related spaceborne power calibration and validation are presented to show the support to power DDM observable production for sea surface and land surface applications. Then, the status of Chinese Beidou System (BDS) Equivalent Isotropic Radiated Power (EIRP) acquisition programme is then introduced. Furthermore, the latest sea surface height (SSH) measurements results including two modes (group delay and carrier phase) and wind speed derivation based on machine learning (ML) method will be spatial-temporal aligned and validated with auxiliary datasets including Denmark Technology University (DTU) mean sea surface (MSS) products and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis. The previous published results of sea surface winds retrieval under Hurricane conditions and soil moisture retrieval are also reviewed for the BF-1 mission applications. Finally, the conclusion of BF-1 derived results will be discussed to draw out ongoing/future works. [ABSTRACT FROM AUTHOR]

The accurate three-dimensional wind field obtained from a Doppler lidar not only helps to comprehend the refined structure of complex airflow but also provides important and valuable solutions for many fields. However, the underlying homogeneity assumption of the typical wind retrieval methods, such as Doppler Beam Swinging (DBS) and Velocity Azimuth Display (VAD) based on a single-lidar, will introduce the measurement uncertainty in complex terrain. In this paper, a new design of a wind measurement campaign involving seven lidars was carried out, which contained the three-lidar-based Virtual Tower (VT) using a time-space synchronization technique and four single-lidars with different elevation angles. This study investigates the performance of VT and VAD measurements under various conditions and evaluates the sensitivity of wind measurement uncertainty of VAD to the horizontal spatial- and probe volume-average effects associated with elevation angles of the laser beam. The inter-comparison results between VT and four VADs show consistent trends with small relative errors under neutral atmospheric conditions with weak wind velocity. Under convective or high Turbulence Intensity (TI) conditions, the relative errors between VT and VAD become larger and more fluctuant. Moreover, it is found that the measurement uncertainty of VAD increases at a given elevation angle with the increasing measurement heights, which is caused by the horizontal homogeneity associated with the conical scanning area. Additionally, the simulated and measured results of four VADs indicate that a larger elevation angle corresponds to a lower measurement uncertainty for a given height. [ABSTRACT FROM AUTHOR]

This paper contrasts predicted X-band sea surface backscattering from slick-free and oil-covered sea surfaces with actual measurements acquired by the X-band satellite TerraSAR-X and COSMO-SkyMed Synthetic Aperture Radar (SAR) missions. Two SAR scenes were acquired with a temporal difference of about 36 minutes, under similar met-ocean conditions, during the North Sea's Gannet Alpha oil spill accident. The normalized radar cross section of the slick-free sea surface is predicted using the Advanced Integral Equation Model (AIEM) while the backscatter from the oiled sea surface is predicted by the AIEM augmented with the Model of Local Balance (MLB) to include the damping effect of oil slicks. Experimental results show that X-band co-polarized numerical predictions agree reasonably well with both TSX and CSK actual measurements collected over slick-free sea surfaces. When dealing with oil-covered sea surfaces, the predicted backscattering reasonably agrees with TSX measurements, while it overestimates the CSK ones. This is likely due to the different spreading conditions of the oil imaged by the two satellite missions. [ABSTRACT FROM AUTHOR]

Landslides are destructive geohazards to people and infrastructure, resulting in hundreds of deaths and billions of dollars of damage every year. Therefore, mapping the rate of deformation of such geohazards and understanding their mechanics is of paramount importance to mitigate the resulting impacts and properly manage the associated risks. In this paper, the main outcomes relevant to the joint European Space Agency (ESA) and the Chinese Ministry of Science and Technology (MOST) Dragon-5 initiative cooperation project ID 59,339 "Earth observation for seismic hazard assessment and landslide early warning system" are reported. The primary goals of the project are to further develop advanced SAR/InSAR and optical techniques to investigate seismic hazards and risks, detect potential landslides in wide regions, and demonstrate EO-based landslide early warning system over selected landslides. This work only focuses on the landslide hazard content of the project, and thus, in order to achieve these objectives, the following tasks were developed up to now: a) a procedure for phase unwrapping errors and tropospheric delay correction; b) an improvement of a cross-platform SAR offset tracking method for the retrieval of long-term ground displacements; c) the application of polarimetric SAR interferometry (PolInSAR) to increase the number and quality of monitoring points in landslide-prone areas; d) the semiautomatic mapping and preliminary classification of active displacement areas on wide regions; e) the modeling and identification of landslides in order to identify triggering factors or predict future displacements; and f) the application of an InSAR-based landslide early warning system on a selected site. The achieved results, which mainly focus on specific sensitive regions, provide essential assets for planning present and future scientific activities devoted to identifying, mapping, characterizing, monitoring and predicting landslides, as well as for the implementation of early warning systems. [ABSTRACT FROM AUTHOR]

Polarimetric calibration is essential for the pre-processing of Polarimetric Synthetic Aperture Radar (PolSAR) data because it effectively mitigates polarimetric distortions in the measured PolSAR data. Traditional methods of polarimetric calibration employ man-made calibrators that offer high accuracy. However, the frequency of calibration is often limited due to the labor-intensive and time-consuming nature of deploying such calibrators. Some polarimetric calibration methods based on distributed targets in nature enable more frequent calibration. Nevertheless, these methods are constrained by the availability of specific distributed targets with known polarimetric properties for estimating parameters related to co-polarization channel imbalance (co-pol-imba) parameters. If distributed targets are not appropriately selected or suitable targets are absent within the image scene, the accuracy of calibration will be compromised. To address this challenge, this paper introduces the idea of cross-calibration, which uses calibrated PolSAR data to determine the real polarimetric property of distributed targets and cross-estimates co-pol-imba parameters for uncalibrated PolSAR data. Furthermore, considering the disparities in imaging geometry between calibrated and uncalibrated PolSAR data, the Cross-Co-Polarization Ratio (CCPR) coefficients are proposed to select stable distributed targets in both the calibrated PolSAR data and the uncalibrated PolSAR data. This approach not only takes into account the impact of co-pol-imba on feature extraction but can also be applied in a broader range of scenes. The real data experiments on the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data show that the estimated results of the cross-calibration method for co-pol-imba are comparable to the polarimetric calibration method based on man-made calibrators, with an amplitude difference of 0.17 dB and a phase difference of 0.69°. [ABSTRACT FROM AUTHOR]

The Greenhouse Gas Monitoring Instrument (GMI) onboard the Chinese hyperspectral satellite GF5–02 can provide abundant observations of global atmospheric CO2, which plays an important role in climate research. CO2 retrieval precision is the key to determining the application value of the GMI. To reduce the influence of atmospheric scattering on retrieval, we combined the Directional Polarimetric Camera (DPC) data on the same satellite to improve the anti-interference ability of GMI CO2 retrieval and ensure its retrieval precision. To realize the reliability and feasibility of the collaborative use of the GMI and DPC, this paper designs the pointing registration method of the GMI based on coastline observations, the spatial resolution matching method and the collaborative cloud screening method of the GMI and DPC observations. Combined with the DPC, which supplied the spectral data and aerosol product, the retrieval ability of the coupled bidirectional reflectance distribution function CO2 retrieval (CBCR) method developed for GMI CO2 retrieval was improved, with the retrieval efficiency of CO2 products increasing by 27%, and the CO2 retrieval precision increasing from 3.3 ppm to 2.7 ppm. Moreover, collaborative use not only guaranteed the GMI's ability to detect global and area CO2 concentration distribution characteristics, such as significant concentration differences between the Northern and Southern Hemispheres in winter and high CO2 concentrations in urban agglomeration areas caused by human activities, but also extended the GMI's potential for monitoring anomalous events, such as the Tonga volcanic eruption. [ABSTRACT FROM AUTHOR]

Remote sensing, particularly satellite-based, can play a valuable role in monitoring areas prone to geohazards. The high spatial and temporal coverage provided by satellite data can be used to reconstruct past events and continuously monitor sensitive areas for potential hazards. This paper presents a range of techniques and methods that were applied for in-depth analysis and utilization of Earth observation data, with a particular emphasis on: (1) detecting mining subsidence, where a novel approach is proposed by combining an improved U-Net model and Interferometry Synthetic Aperture Radar (InSAR) technology. The results showed that the Efficient Channel Attention (ECA) U-Net model performed better than the U-Net (baseline) model in terms of Mean Intersection over Union (MIoU) and Intersection over Union (IoU) indicators; (2) monitoring water conservancy and hydropower engineering. The Xiaolangdi multipurpose dam complex was monitored using Small BAsline Subsets (SBAS) InSAR method on Sentinel-1 time series data and four small regions with high deformation rates were identified on the slope of the reservoir bank on the north side. The dam body also showed obvious deformation with a velocity exceeding 60 mm/a; (3) the evaluation of the potential of InSAR results to integrate monitoring and warning systems for valuable heritage and architectural preservation. The overall outcome of these methods showed that the use of Artificial Intelligence (AI) techniques in combination with InSAR data leads to more efficient analysis and interpretation, resulting in improved accuracy and prompt identification of potential hazards; and (4) finally, this study also presents a method for detecting landslides in mountainous regions, using optical imagery. The new temporal landslide detection method is evaluated over a 7-year analysis period and unlike conventional bi-temporal change detection methods, this approach does not depend on any prior-knowledge and can potentially detect landslides over extended periods of time such as decades. [ABSTRACT FROM AUTHOR]

Optical and Synthetic Aperture Radar (SAR) remote sensing has a long history of use and reached a good level of maturity in archaeological and cultural heritage applications, yet further advances are viable through the exploitation of novel sensor data and imaging modes, big data and high-performance computing, advanced and automated analysis methods. This paper showcases the main research avenues in this field, with a focus on archaeological prospection and heritage site protection. Six demonstration use-cases with a wealth of heritage asset types (e.g. excavated and still buried archaeological features, standing monuments, natural reserves, burial mounds, paleo-channels) and respective scientific research objectives are presented: the Ostia-Portus area and the wider Province of Rome (Italy), the city of Wuhan and the Jiuzhaigou National Park (China), and the Siberian "Valley of the Kings" (Russia). Input data encompass both archive and newly tasked medium to very high-resolution imagery acquired over the last decade from satellite (e.g. Copernicus Sentinels and ESA Third Party Missions) and aerial (e.g. Unmanned Aerial Vehicles, UAV) platforms, as well as field-based evidence and ground truth, auxiliary topographic data, Digital Elevation Models (DEM), and monitoring data from geodetic campaigns and networks. The novel results achieved for the use-cases contribute to the discussion on the advantages and limitations of optical and SAR-based archaeological and heritage applications aimed to detect buried and sub-surface archaeological assets across rural and semi-vegetated landscapes, identify threats to cultural heritage assets due to ground instability and urban development in large metropolises, and monitor post-disaster impacts in natural reserves. [ABSTRACT FROM AUTHOR]

This paper provides a political economy analysis of the bilateral trade relations and patterns of exchange that existed between Iran and Sub-Saharan Africa (SSA) from 1962 to 2021. The paper contributes to the growing literature on Iran–Africa relations by empirically delineating not just the changes, but also the continuities between Iran and its African trading partners before and after the Iranian Revolution. It also adds nuance to the broader scholarship on South–South cooperation by showing the disparity between the rhetoric of South–South solidarity and reciprocity between Iran and SSA, on one side, and their low and fluctuating trade volumes, on the other. These volumes resulted from historical inertia or path dependency and structural factors, including trade complementarities and geopolitical conditions, more than demographic, cultural, or religious realities. They were also shaped by the agency and decision-making of Iranian and African leaders and officials regarding the extent to economically engage with each other. [ABSTRACT FROM AUTHOR]

This paper seeks to understand the socio-political dimension of the political changes in Assam vis-a-vis "regionalism" and its contestations. The Changing contours of regionalism in Assam reflect its distinct character marked by the simultaneous articulation of regional, sub-regional and national identity in a complex socio-ethnic and historical context. The recent political trajectory of Assam bears testimony to the dual challenges facing the forces of regionalism; the presence of sub-regional ethnic identity articulation and the appropriation of regional space and issues by the national parties. Further, the shifting allegiance of ethnic identity-based parties to the national parties is critical to understand the dynamics of regionalism in Assam. Socio-political developments subsequent to the rise of BJP post-2014 provide an interesting landscape to comprehend the complexities inherent in understanding regionalism in contemporary Assam. On a contextual note, the paper also locates the question of regionalism in the ongoing debates of NRC and CAA. [ABSTRACT FROM AUTHOR]

Polymers, with various advantages including lightweight, low cost, flexibility and ease of processing, are popular choices for thermal management in flexible electronics, photovoltaics, fuel cells, etc. In this perspective, we review the recent progress of developing uniaxial thermally conductive polymers and three-dimensional polymers with high thermal conductivity, discuss new opportunities in applying machine learning methods to search for thermally conductive polymers, and finally point out current key challenges and future directions in simulations and experimental measurements. The useful insights in this perspective can guide the rational design of thermally conductive polymers for advanced thermal management. This paper delineates the advantages and recent progress of pristine polymers with high thermal conductivity and provides significant insights on future directions in the simulations and experimental measurements of thermally conductive pristine polymers. [ABSTRACT FROM AUTHOR]

Carbon nanofibers (CNFs) and graphene nanosheets (GNs) are introduced to obtain nano-sized TiC particles in a novel additive manufactured Ni-Co-based superalloy. The double strengthening effects of reaction-induced TiC and remaining CNFs/GNs are conceptualized in the present paper. The CNFs and GNs act as heterogeneous nucleation sites for the formation of uniformly distributed TiC nanoparticles, which inhibits the crack and homogenize the microstructure. Interestingly, the existence of remaining GNs/CNFs is revealed via 3D atom-by-atom tomographic reconstruction technology for the first time. This unique combination of nanoparticles and residual CNFs/GNs nanofillers has great potential to develop superalloys with excellent properties. The formation of nano-sized dispersion TiC particles is induced by the introduction of carbon nanofibers and graphene nanosheets in additive manufactured superalloy, which inhibits the crack and homogenizes the microstructure. [ABSTRACT FROM AUTHOR]

Diagnostics are an essential, undervalued part of the health-care system. For many diseases, molecular diagnostics are the gold standard, but are not easy to implement in Low- and Middle-Income Countries (LMIC). Sample-to-result (S2R) platforms combining all procedures in a closed system could offer a solution. In this paper, we investigated their suitability for implementation in LMIC. A scorecard was used to evaluate different platforms on a range of parameters. Most platforms scored fairly on the platform itself, ease-of-use and test consumables; however, shortcomings were identified in cost, distribution and test panels tailored to LMIC needs. The diagnostic coverage for common infectious diseases was found to have a wider coverage in high-income countries (HIC) than LMIC. A literature study showed that in LMIC, these platforms are mainly used as diagnostic tools or evaluation of diagnostic performance, with a minority assessing the operational characteristics or the clinical utility. In this narrative review, we identified various points for adaptation of S2R platforms to LMIC conditions. For S2R platforms to be suitable for implementation in LMIC some modifications by the manufacturers could be considered. Furthermore, strengthening health systems and digitalization are vital; as are smaller, cheaper, faster, and sustainable technologies. [ABSTRACT FROM AUTHOR]

The identification of early-stage colorectal cancers (CRC) and the resection of pre-cancerous neoplastic lesions through colonoscopy allows to decrease both CRC incidence and mortality. However, colonoscopy miss rates up to 26% for adenomas and 9% for advanced adenomas have been reported. In recent years, artificial intelligence (AI) systems have been emerging as easy-to-use tools, potentially lowering the risk of missing lesions. This review paper focuses on GI Genius device (Medtronic Co. Minneapolis, MN, U.S.A.) a computer-assisted tool designed to assist endoscopists during standard white-light colonoscopies in detecting mucosal lesions. Randomized controlled trials (RCTs) suggest that GI Genius is a safe and effective tool for improving adenoma detection, especially in CRC screening and surveillance colonoscopies. However, its impact seems to be less significant among experienced endoscopists and in real-world clinical scenarios compared to the controlled conditions of RCTs. Furthermore, it appears that GI Genius mainly enhances the detection of non-advanced, small polyps, but does not significantly impact the identification of advanced and difficult-to-detect adenoma. When using GI Genius, no complications were documented. Only a small number of studies reported an increased in withdrawal time or the removal of non-neoplastic lesions. [ABSTRACT FROM AUTHOR]

This paper considers what we know about the potential for disinformation in hydrological data when used for the evaluation of hydrological models. This will generally arise from epistemic uncertainties associated with hydrological observations, particularly from nonstationary or extrapolated rating curves for discharges, and poor rainfall and snowmelt information when interpolated over basin areas. Approaches based on information theory are not well suited to consideration of such epistemic uncertainties in model evaluation and an alternative approach based on setting limits of acceptability independent of any model runs is suggested. This allows for both the rejection of all models tried, and for acceptability of models across different model structures and parameter sets. The paper concludes with some suggestions for future research on defining disinformative data for both point and spatial observables, studying model failures, and defining new observations with a view to having the greatest impact on reducing model uncertainties. [ABSTRACT FROM AUTHOR]

The growing Internet of Things (IoT) landscape requires robust security; traditional rule-based systems are insufficient, driving the integration of machine learning (ML) for effective intrusion detection. This paper provides an inclusive overview of research efforts focused on harnessing ML methodologies to fortify intrusion detection within IoT. Tailored feature extraction techniques are pivotal for achieving high detection accuracy while minimizing false positives. The study employs the IoT23 dataset from Kaggle and incorporates four optimization algorithms – Particle Swarm Optimizer, Whale-Pearson optimization algorithm, Harris-Hawks Optimizer, and Support Vector Machine with Particle Swarm optimization algorithm (SVM-PSO) – for feature extraction and selection. A comparison with ML algorithms such as logistic regression, decision tree and naïve Bayes classifier highlights Harris-Hawks Optimizer as the most effective. Furthermore, ensemble methods, particularly the fusion of random forest with HHO optimization, yield an impressive accuracy of 99.97%, surpassing AdaBoost and XGBoost approaches. This paper underscores the application of diverse ensemble learning techniques to enhance intrusion detection precision and efficiency within the intricate IoT landscape, effectively tackling the challenges posed by its complex and ever-changing nature. [ABSTRACT FROM AUTHOR]

The burden of malnutrition experienced globally, coupled with the increasing rate of micronutrient deficiencies, compromises the health and well-being of women during their reproductive years. Obesity places young South African women at particular risk during pregnancy, and increases obesity risk for their offspring. To address these risks, the Bukhali trial is being implemented in Soweto, South Africa with 18–28-year-old women, as part of the Healthy Lifestyle Trajectory Initiative. A dietitian is part of the Bukhali intervention team (community health workers) to provide nutritional support for overweight/obese trial participants, making use of the International Federation of Gynaecology and Obstetrics (FIGO) Nutrition Checklist. This paper reflects on the experiences and lessons learned by the Bukhali dietitian, including the use of the FIGO Nutrition Checklist and Healthy Conversation Skills to facilitate conversations about making healthy dietary behaviour changes. Identified challenges that influence nutrition and behaviour are discussed, including lack of food affordability, cultural and social influences on healthy food choices, unsupportive environments and food insecurity. Strategies to optimise this nutritional support are also mentioned. The Bukhali trial is showing that introducing additional nutrition support by a dietitian for at-risk participants has the potential to encourage young women to prioritise nutrition and health, even in the midst of contextual challenges to both nutrition and health. [ABSTRACT FROM AUTHOR]

The paper examines the rhetorical imagination of the Catholic speaker in public discourse on the basis of the parliamentary discourses of Pope Benedict XVI. According to this researcher, Pope Benedict XVI's rhetorical model in the speeches is an extended version of Michael J. Hostetler's critical distance model supported by the translation idea of Jurgen Habermas. This conclusion is reached by analysis of the constituent elements of the arguments in three parliamentary speeches given by Pope Benedict XVI. James B. Freeman's updated version of Stephen Toulmin's argumentation model is used to discern the constituent element of the argument. [ABSTRACT FROM AUTHOR]

Conversations regarding moral values are increasingly becoming a pivotal dimension of public discourse. This paper presents a new approach to unacceptable discourse. Drawing on René Girard's cultural anthropology and Luciano Elizalde's dissent management theory, this work develops a scale of situations of dissent, such as controversy, polemic and public discourse scandal. It offers a detailed study of the polemic raised by the book Marry Him and Be Submissive, a process of dissent which was generated in Spain in November 2013 on the occasion of the publication of this Italian bestseller and lasted until January 2014. The book was written by the Italian journalist Costanza Miriano and translated and edited by the Archdiocese of Granada. The case study uses a triangular approach to discourse analysis, which aims to comprehend the enunciator's legitimacy and social positioning, the communication context in which the debate takes place, and the characteristics of the public discourse. A central element regards how reactions are organized around the signifier 'submissive' and the different frames of interpretation assigned to this word, in what will be called 'feminist' and 'post-feminist' paradigms. Mechanisms of dissent and consensus are explained, and takeaways and actors' strategies are discussed. [ABSTRACT FROM AUTHOR]

Castanopsis orthacantha Franch. 1899 is one representative tree species distributed in the evergreen broad-leaved forests of southwestern China. This species is an important source of timber for manufacturing furniture, floors, and paper. It also plays a significant role in maintaining ecological balance and stability. To help with the genetic diversity assessment of C. orthacantha, we sequenced and assembled the first complete chloroplast genome. The length of the chloroplast genome was 160,588 bp, with a typical quadripartite structure (GenBank accession no. OR900101). The large single-copy (LSC), small single-copy (SSC), and two inverted repeats (IRs) were 90,237 bp, 18,953 bp, and 25,699 bp in length, respectively. We annotated one hundred and thirty genes across the chloroplast genome, including 86 protein-coding genes (79 are unique), 37 tRNA genes (29 are unique), and eight rRNA genes (four are unique). Seventeen genes had one intron, and four were detected with two introns. The maximum likelihood phylogeny suggested that C. orthacantha, C. lamontii, C. sclerophylla, and C. hainanensis formed a clade with a high bootstrap value. This newly sequenced chloroplast genome assembly will aid in the population genetic and phylogenetic studies of Castanopsis species in the future. [ABSTRACT FROM AUTHOR]

We examine private supplementary tutoring within the context of Finnish general upper secondary education. Specifically, we focus on profit-driven private preparatory course providers who cater to individual students and their families, aiming to improve applicants' prospects of gaining access to higher education. We examine this during a time when a recent education policy reform has renewed seeking admission to higher education in Finland, consequently impacting the private supplementary tutoring market associated with it. We draw on Bourdieu's concepts of field, capital, and habitus as a starting point for discussing the complex dynamics between public and private actors in the field of Finnish general upper secondary education and the role of economic capital. The ethnographic data analyzed for this paper consist of field notes and interviews (n = 58) from three general upper secondary schools, produced in 2019-2020. The study aims to investigate the negotiations between the public and private spheres of education within the everyday practices of Finnish public upper secondary education during an educational policy reform. We conclude that the fields of public and private education are not separate but rather intertwined, and they can become blurred in the everyday life of schools through both temporal and spatial overlaps. [ABSTRACT FROM AUTHOR]

This paper introduces the Special Issue 'Minorities and Grain Trade in Early Modern Europe'. While an area's traditional supply circuits benefitted from satisfactory harvests and a stable food demand, minorities' contribution became crucial during crisis. Due to their commercial networks, facilities, and capital, minorities and their agents were able to cope with market disruption, especially when inflation and the reconfiguration of supply areas rendered 'traditional' grain merchants unable to face the emergency. The papers included in the Special Issue focus on the geographical and financial scope of legal grain-trading minorities' businesses and their degree of specialisation and analyse how political authorities' reliance on minorities to face food scarcity not only represented an economic opportunity for minorities but also contributed to shaping their relationship with public authorities. [ABSTRACT FROM AUTHOR]

Next point-of-interest (POI) recommendation has been applied by many internet companies to enhance the user travel experience. Recent research advocates deep-learning methods to model long-term check-in sequences and mine mobility patterns of people to improve recommendation performance. Existing approaches model general user preferences based on historical check-ins and can be termed as preference pattern models. The preference pattern is different from the intention pattern, in that it does not emphasize the user mobility pattern of revisiting POIs, which is a common behavior and kind of intention for users. An effective module is needed to predict when and where users will repeat visits. In this paper, we propose a Spatio-Temporal Intention Learning Self-Attention Network (STILSAN) for next POI recommendation. STILSAN employs a preference-intention module to capture the user's long-term preference and recognizes the user's intention to revisit some specific POIs at a specific time. Meanwhile, we design a spatial encoder module as a pretrained model for learning POI spatial feature by simulating the spatial clustering phenomenon and the spatial proximity of the POIs. Experiments are conducted on two real-world check-in datasets. The experimental results demonstrate that all the proposed modules can effectively improve recommendation accuracy and STILSAN yields outstanding improvements over the state-of-the-art models. [ABSTRACT FROM AUTHOR]

Spatial equity in access to urban services is a significant element of sustainable urban planning. To date, a service-based index is used to measure service attractiveness, considering attractiveness as a static concept. While from the user side view, service attractiveness is a dynamic concept related to the variation of different opportunities of users to use the services and capacities. In this paper, a user-based method for measuring service attractiveness is proposed. In this approach, the attractiveness of service for a user is modeled as a function of the user's Travel Times (TT), Free Times (FTs), park size and relative positions of the user, local demanding population, and service. Then, the inequity of attractiveness of services for different users has been examined using three inequity indices including the Duration of Use (DU), Frequency of Visit (FV), and the Chance of Space Choice (CSC). The proposed method is applied to urban regional parks of Tehran municipality. Traffic Analysis Zones (TAZs) and regional parks are respectively regarded as the users and services. In addition to considering inequity of access to the first closest park, the additional cost of accessing to the other two closest parks is also considered. Results show that the proposed method leads to the exploration of the existing inequities of DU, FV, and CSC among residents in local scales, whereas in the service-based method, all users of a service are highlighted with a single value of attractiveness. Comparison of the user-based and service-based attractiveness indices show significant differences. As an example, user-based attractiveness values of about 14% and 20% of TAZs are respectively 5 and 3 square meters more than that of the service-based attractiveness index. However, the service-based method is suitable for regional-scale comparison of the inequities. Therefore, the proposed index can complement the service-based index for inequity mapping and management in varying scales. [ABSTRACT FROM AUTHOR]

Remote sensing provides us with an approach for the rapid identification and monitoring of spatiotemporal changes in the urban ecological environment at different scales. This study aimed to construct a remote sensing assessment index for urban ecological livability with continuous fine spatiotemporal resolution data from Landsat and MODIS to overcome the dilemma of single image-based, single-factor analysis, due to the limitations of atmospheric conditions or the revisit period of satellite platforms. The proposed Ecological Livability Index (ELI) covers five primary ecological indicators – greenness, temperature, dryness, water-wetness, and atmospheric turbidity – which are geometrically aggregated by non-equal weights based on an entropy method. Considering multisource time-series data of each indicator, the ELI can quickly and comprehensively reflect the characteristics of the Ecological Livability Quality (ELQ) and is also comparable at different time scales. Based on the proposed ELI, the urban ecological livability in the central urban area of Wuhan, China, from 2002 to 2017, in the different seasons was analyzed every 5 years. The ELQ of Wuhan was found to be generally at the medium level (ELI ≈0.6) and showed an initial trend of degradation but then improved. Moreover, the ecological livability in spring and autumn and near rivers and lakes was found to be better, whereas urban expansion has led to the outward ecological degradation of Wuhan, but urban afforestation has enhanced the environment. In general, this paper demonstrates that the ELI has an exemplary embodiment in urban ecological research, which will support urban ecological protection planning and construction. [ABSTRACT FROM AUTHOR]

The suffix "washing" refers to the practice of portraying controversial actions in a positive light by leveraging progressive principles, often used by economic corporations, organizations, political parties, or governments. This paper introduces and develops the term "studentwashing" to define the deliberate effort to present Israeli territorial development as an attractive, youthful, and unique experience. This portrayal aims to engage larger segments of society in the national geopolitical project while normalizing its settler-colonial aspects as a means to ensure its continuation. While the constant development of new territorial settlements is dependent either on the right-wing religious sector or on the "quality-of-life" settlers, studentwashing is reserved for areas that are not ideological enough for the first nor sufficiently attractive to the latter. Analyzing "student villages" in the Negev, this paper depicts a new territorial strategy meant to enhance the state's spatial control over the predominantly Arab periphery inside official Israeli borders. Accordingly, this paper offers a new perspective on Israel's territorial strategies and enhances the general study of geopolitical and geo-economic spatial development. [ABSTRACT FROM AUTHOR]

This paper provides an analysis of the historical trajectory of Turkish geographical practice over the past four decades, situated within the broader socio-political landscape of the country. The transmission of the modern geographical tradition from continental Europe to Turkey during the interwar period established the discipline as a holistic science of the human-environment relationship. Although this understanding started to change after the 1968 events, the 1980 Turkish military coup abruptly disrupted innovative endeavors in the discipline, prompting a resurgence of regionally focused synthesis within geography. This insular approach prevailed for several decades but began to evolve in response to the internationalization trends that emerged in the 2000s, with deliberate steps taken toward fostering innovation. Despite institutional damage resulting from the political developments following the 2016 military coup attempt, the discipline maintained its commitment to innovation. This paper critically examines the divergent responses of Turkish geography and its practitioners to the 1980 military coup and the 2016 coup attempt, highlighting the significant influence of globalization. [ABSTRACT FROM AUTHOR]

Notwithstanding India's public stand professing its respect of the sovereignty principle, the imperatives of competitive international relations have necessitated the use of force against its neighbors, thereby undermining their sovereignty. This use of force has been manifested through conventional wars as well as through the sub-conventional use of force such as surgical strikes. This paper examines how India has sought to toe a fine line between pursuing its national interest through the application of military power while being mindful of the broader normative frameworks influencing state behavior since 1947. In doing so, it engages with the interplay of the material and the ideational. Given the time span of the study, it also seeks to shine light on the elements of continuity and change that mark its application of military power through the prism of the sovereignty principle. Furthermore, the paper also pays attention to the recent surgical strikes, features that mark them as being different from previous such actions performed by India, and what this means for India's understanding of the sovereignty principle. [ABSTRACT FROM AUTHOR]

The role of cartography in environmentally-sustainable development is twofold: first, useful and usable maps enable sense making and decision making about environmental processes, impacts, and protections; second, maps themselves, as digital tools, can be more energy efficient in minimizing our impact on the environment. In this paper, we elevate this energy awareness as a key design consideration for maps and introduce a novel conceptual framework for considering the carbon footprint of the content, form, and use of maps. We first systematically investigate how specific map design decisions impact the energy consumption of digital devices. We then discuss the possible ways that digital maps can be greener, outlining a series of 'big questions' about the content, form, and use context of maps needing future research to realize greener maps. Finally, we assert that green cartography requires not only novel techniques to design green maps but also greater attention to shaping individual, organizational, and social attitudes towards environmentally-friendly maps. [ABSTRACT FROM AUTHOR]

The rapid development of digital finance has transformed traditional financial institutions. We investigate the effect and economic consequences of bank digital transformation on corporate financial constraints using data from China. The results show that bank digital transformation alleviates corporate financial constraints by decreasing information search, processing, and verification costs. Furthermore, the effect of bank digital transformation on corporate financial constraints is more pronounced for firms with higher contract intensity, more intangible assets, and poorer external information environment. We also find that bank digital transformation alleviates corporate financial constraints by increasing debt financing. In addition, we show that digital transformation promotes lending by big banks, resulting in the crowding-out effect. Finally, we find that bank digital transformation promotes the flow of credit resources to non-zombie firms, which effectively improves credit allocation efficiency. This paper extends research on digital finance and new structural finance from the perspective of bank digital transformation. [ABSTRACT FROM AUTHOR]

This paper examines the influence of enterprise digital transformation on safety production performance. Our results indicate that digital transformation significantly improves the safety performance of China's listed enterprises. Furthermore, a series of cross-sectional analyses confirm that the effect of digital transformation on safety production performance is more prominent not only in regions with higher levels of marketisation and stronger enforcement of safety production systems but also in markets with higher competition and stronger supervision. Moreover, the proposed effect is also more significant in corporations with higher capital intensity and lower financing constraints. The mechanism tests reveal that digital transformation improves the quality of internal control and optimises corporate innovation, thereby improving the safety production performance. Our findings highlight the impact of digital technology application on enterprise production safety performance, serving as a valuable reference for promoting the development and implementation of digital technologies in the field of production safety. [ABSTRACT FROM AUTHOR]

Despite agriculture being the largest employer of young people, South Africa faces a youth unemployment crisis. The youth are increasingly disinterested in agriculture and often view it as a last resort in the absence of alternative employment opportunities. This paper explores strategies to change these negative perceptions and attract young people to agriculture. Drawing on twenty-two studies conducted over the past decade, national grade 12 statistics, University enrolments, yearbook reviews, and twenty job advertisements, I identify five key areas for intervention. First, the youth interested in agripreneurship need support to access financial and physical resources. They also need training offered jointly by tertiary institutions and the government. Second, agricultural education in primary and secondary schools will likely attract and retain youths to agriculture. Third, we need to reform the education system at all levels to ensure holistic student development opportunities, including the technical and soft skills required by agricultural sector employers. Fourth, our marketing strategies need reform; collaboration with the media is necessary to increase awareness and change youths' perceptions about agriculture and agricultural careers. Five, we need to strengthen the role of agricultural associations to bridge the gap between the agricultural sector and secondary and tertiary education institutions. [ABSTRACT FROM AUTHOR]

Human capital development is considered the primary source of knowledge and skills in the innovation process. Despite this, there is evidence of a lack of technical and managerial knowledge among emerging sugarcane farmers who are beneficiaries of South Africa's land reform programme, thus, limiting their full potential in terms of innovation and productivity which is detrimental to their competitiveness. This paper employs the Crépon, Duguet, and Mairesse (CDM) approach, correcting for endogeneity problems, to estimate the causal impact of on-the-job training expenditure, used as a proxy for human capital development, on innovation, and innovation on farm productivity. It is based on a case study of 35 emerging sugarcane farmers in the KwaZulu-Natal north coast, South Africa. The results from the CDM model confirm the causal relationships between human capital (on-the-job training) and the innovation behaviour of the farmers, which positively impact the farm's productivity. This result underscores the relevance of human capital development in boosting innovation and productivity in the agricultural sector. [ABSTRACT FROM AUTHOR]

Many vascular disorders arise as a result of dysfunctional smooth muscle cells. Tissue engineering strategies have evolved as key approaches to generate functional vascular smooth muscle cells for use in cell-based precision and personalized regenerative medicine approaches. This article highlights some of the challenges that exist in the field and presents some of the prospects for translating research advancements into therapeutic modalities. The article emphasizes the need for better developing synergetic intracellular and extracellular cues in the processes to generate functional vascular smooth muscle cells from different stem cell sources for use in tissue engineering strategies. This paper explores the potential of engineering smooth muscle tissues to treat vascular diseases, focusing on challenges like sourcing the right cells and creating supportive environments for cell growth. It highlights advances in materials that mimic the body's conditions and the use of 3D fabrication methods for creating complex structures. Additionally, it discusses the significance of mitochondrial function in blood vessel muscle cells. The research emphasizes interdisciplinary efforts and personalized treatments as key to developing effective therapies. The goal is to engineer lab-grown tissues that can repair or replace damaged blood vessels, offering hope for addressing major health challenges associated with vascular diseases. [ABSTRACT FROM AUTHOR]

In India, the incidence of mucormycosis reached high levels during 2021–2022, coinciding with the COVID-19 pandemic. In response to this, we established a multicentric ambispective cohort of patients hospitalised with mucormycosis across India. In this paper, we report their baseline profile, clinical characteristics and outcomes at discharge. Patients hospitalized for mucormycosis during March–July 2021 were included. Mucormycosis was diagnosed based on mycological confirmation on direct microscopy (KOH/Calcofluor white stain), culture, histopathology, or supportive evidence from endoscopy or imaging. After consent, trained data collectors used medical records and telephonic interviews to capture data in a pre-tested structured questionnaire. At baseline, we recruited 686 patients from 26 study hospitals, of whom 72.3% were males, 78% had a prior history of diabetes, 53.2% had a history of corticosteroid treatment, and 80% were associated with COVID-19. Pain, numbness or swelling of the face were the commonest symptoms (73.3%). Liposomal Amphotericin B was the commonest drug formulation used (67.1%), and endoscopic sinus surgery was the most common surgical procedure (73.6%). At discharge, the disease was stable in 43.3%, in regression for 29.9% but 9.6% died during hospitalization. Among survivors, commonly reported disabilities included facial disfigurement (18.4%) and difficulties in chewing/swallowing (17.8%). Though the risk of mortality was only 1 in 10, the disability due to the disease was very high. This cohort study could enhance our understanding of the disease's clinical progression and help frame standard treatment guidelines. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is a prevalent tumour with high morbidity rates worldwide, and its incidence among younger populations is rising. Early diagnosis of CRC can help control the associated mortality. Fungi are common microorganisms in nature. Recent studies have shown that fungi may have a similar association with tumours as bacteria do. As an increasing number of tumour-associated fungi are discovered, this provides new ideas for the diagnosis and prognosis of tumours. The relationship between fungi and colorectal tumours has also been recently identified by scientists. Therefore, this paper describes the limitations and prospects of the application of fungi in diagnosing CRC and predicting CRC prognosis. [ABSTRACT FROM AUTHOR]

Aphasia is a communication disorder resulting from stroke and/or neurodegenerative conditions which involve the left cerebral hemisphere. It is a debilitating disorder affecting a person's ability to speak, understand, read, and write. Its impact on daily life necessitates therapeutic strategies to aid patients with aphasia. In this special report, the authors speculate whether current pharmacotherapeutic strategies are effective in treating aphasia. The authors look at aphasia caused by different conditions and how this could impact therapy before providing the reader with their expert perspectives. The aim of this paper is for the reader to gain a clearer understanding of the efficacy of the current pharmacotherapeutic treatment paradigms as well as potential future developments. The exploration of pharmacotherapy for aphasia in vascular brain disorders and neurodegenerative diseases has received much attention in recent years with various therapeutic strategies having been put forward. In terms of whether pharmacotherapy is effective for the treatment of aphasia, there is still no clear-cut answer. Further research is needed with more studies requiring a greater emphasis on language and communication deficits. Biomarkers may also help clinicians provide their patients with a more personalized treatment plan. [ABSTRACT FROM AUTHOR]

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Thin-film-transistor-liquid crystal displays (TFT-LCDs) still dominate most of the display markets due to a big leap in image quality while keeping low cost and superior reliability, and its evolution is continuing to compete with emerging emissive displays. In this paper, recent progress in liquid crystal technologies mainly focusing on fringe-field switching (FFS) and polymer-stabilized vertical alignment (PS-VA) modes and materials for improving electro-optic performances is reviewed. [ABSTRACT FROM AUTHOR]

Piezoelectric semiconductors (PSs) have widespread applications in semiconductor devices due to the coexistence of piezoelectricity and semiconducting properties. It is very important to conduct a theoretical analysis of PS structures. However, the present of nonlinearity in the partial differential equations (PDEs) that describe those multi-field coupling mechanical behaviors of PSs poses a significant mathematical challenge when studying these PS structures. In this paper, we present a novel approach based on machine learning for solving multi-field coupling problems in PS structures. A physics-informed neural networks (PINNs) is constructed for predicting the multi-field coupling behaviors of PS rods with extensional deformation. By utilizing the proposed PINNs, we evaluate the multi-field coupling responses of a ZnO rod under static and dynamic axial forces. Numerical results demonstrate that the proposed PINNs exhibit high accuracy in solving both static and dynamic problems associated with PS structures. It provides an effective approach to predicting the nonlinear multi-field coupling phenomena in PS structures. [ABSTRACT FROM AUTHOR]

Cynanchum otophyllum Schneid is an important medicinal plant in China. In this paper, the chloroplast genome of C. otophyllum was sequenced based on high-throughput technology, and the chloroplast genome structure characteristics and phylogenetic relationship of C. otophyllum were analyzed. The results showed the complete plastome genome size of C. otophyllumis 160,874bp, including one small single copy (SSC, 19,851bp) and one large single copy (LSC, 92,009bp) regions isolated by a pair of inverted repeat regions (IRs, 24,507bp). The whole plastome genome including 84 protein encoding genes, 8 rRNA and 37 tRNA. Based on the phylogenetic topologies, C. otophyllum shows close association with additional Gomphocarpus and Asclepias genus. This study contributes to an enhanced understanding of the genetic information of C. otophyllum and provides a theoretical basis for the development of molecular markers and phylogeographic of the species, as well as for constructing the phylogenetic tree of Asclepiadaceae. [ABSTRACT FROM AUTHOR]

In this paper, we consider an uplink non-orthogonal multiple access (NOMA) for energy harvesting at the base station or access point in the wireless system. By exploiting energy enough, a base station or access point can serve many users at the downlink. The fixed power allocation factors are adopted, and the power splitting energy harvesting protocol brings many benefits to both the uplink and downlink of a wireless system. The closed-form expressions of outage probability are investigated and examined in a group of two users. Moreover, the optimal outage probability for two users is shown numerically. Finally, Monte Carlo simulations are presented to further support the validity of our framework and findings. [ABSTRACT FROM AUTHOR]

In software testing, the quality of the test suite plays a very important role for not only the effectiveness of the testing but also the quality assurance of software. Mutation testing is considered as the usable, automatic and very effective technique in detecting mistakes of the set of test cases such as missing test cases, redundant test cases··· However, when using the mutation testing technique in practice, the generation of a large number of mutants has led to very high computational costs. This raises the question of whether we can reliably and accurately predict this mutation score without running mutants or not. If we can do this, it will save a lot of time and effort but still ensure the effectiveness of mutation testing. In this paper, we propose the approach using machine learning to perform mutation score cross-prediction for software which are new and completely different from the software used to generate test data (mutants) in model training and testing. The experimental results have shown that our proposed approach has achieved the positive results and is highly feasible. Thus, we believe that the approach can be applied to significantly reduce the cost of mutation testing. [ABSTRACT FROM AUTHOR]

Multicast services provide an efficient way of conserving resources and reducing network traffic for multicast senders. However, ensuring security, particularly source authentication, is crucial for applications such as online news, IPTV, video streaming, and stock quote distribution. Previous research efforts have attempted to provide source authentication for multicast applications, but they often struggle to handle the dynamic nature of multicast mobile receivers and multi-domain networks. This paper provides an analysis of research conducted over 22 years on source authentication mechanisms with non-repudiation. Most of these mechanisms fail to address the dynamic nature of mobile users and multi-domain networks. To address this issue, a new multicast source authentication scheme for multi-domain Software Defined Mobile Networks (SDMN) is proposed. This approach uses the global view of the controller in SDMN to operate in dynamic environments, provide non-repudiation, and tolerate packet loss. Simulation results indicate that the proposed mechanism uses resources efficiently, reduces communication and delay overhead, and performs well in multi-domain and dynamic networks. [ABSTRACT FROM AUTHOR]

\nHighlightsIn order to investigate the micro-mechanisms of adhesive failure at the asphalt-aggregate interface under freeze-thaw cycling, this study presents a novel model for freeze-thaw cycling of asphalt mixtures constructed using molecular dynamics. The model is employed to explore the micro-mechanisms of adhesive failure between asphalt and aggregate surfaces under freeze-thaw cycling conditions. Utilising the four-component model of asphalt, asphalt molecules were constructed, with silicon dioxide and calcium carbonate chosen to represent acidic and alkaline aggregates, respectively. Subsequently, an asphalt-aggregate-water freeze-thaw cycling model was developed. Building upon this foundation, the variations in interface interactions between asphalt and the two types of minerals were analysed under the same freeze-thaw cycling conditions but differing freeze-thaw cycle counts. This analysis was conducted through the examination of Radial Distribution Function (RDF), water molecule coordination numbers, and hydrogen bond quantities at the interfaces between asphalt and the two mineral types. The research findings indicate that acidic aggregates exhibit a greater affinity for water molecules compared to alkaline aggregates. Hydrogen bond interactions exist between aggregates and water molecules, with the hydrogen bond energy being greater than the interactions between asphalt molecules and aggregate surfaces. The cohesive energy decreases with an increasing number of freeze-thaw cycles, leading to a gradual reduction in asphalt viscosity and facilitating the detachment of asphalt from the aggregate surface. Consequently, acidic aggregates tend to absorb water molecules more readily, and water can lower the viscosity of asphalt molecules, ultimately resulting in the macroscopic delamination of asphalt from the aggregate surface. These research outcomes provide valuable theoretical guidance for a deeper exploration of the adhesive failure mechanisms in asphalt-aggregate interactions. This paper proposes a new calculation model for asphalt mixture adhesion failure.The hydrogen bonding between water molecules and aggregates is greater than that between asphalt and aggregates.Freezing and thawing cycles will reduce the cohesive energy density of asphalt and reduce the adhesion between asphalt and aggregate.This paper proposes a new calculation model for asphalt mixture adhesion failure.The hydrogen bonding between water molecules and aggregates is greater than that between asphalt and aggregates.Freezing and thawing cycles will reduce the cohesive energy density of asphalt and reduce the adhesion between asphalt and aggregate. [ABSTRACT FROM AUTHOR]