Miracle-dz/UniFAR-FTUs huggingface dataset:
The honeycomb terrain on the Hellas basin floor, Mars: A case for salt or ice diapirism

We present quantitative plausibility studies of potential formation mechanisms for the “honeycomb” terrain on the northwestern Hellas basin floor. The honeycomb terrain is a unique landscape of ~10.5 × 5 km wide, mostly cell‐shaped depressions that are arranged in a regular, dense pattern covering ~36,000 km2. We argue against the honeycombs being (peri)glacial landforms (till rings, iceberg imprints, and thermokarst) or the result of igneous diapirism, as terrestrial analogs do not reproduce their key characteristics. Fossilized impact melt convection cells also appear to be an unsuitable interpretation, as melt solidification should not permit such structures to be retained. We present arguments in favor of salt or ice diapirism as honeycomb formation models. Honeycomb‐sized diapirs could be formed by a ~2 km thick salt layer (~72,000 km3 for the entire honeycomb terrain), which might have been derived from the highlands north of Hellas Planitia—an area of abundant chloride signatures and intense snowfall according to ancient Mars climate models. Nearby volcanic activity ~3.8 Ga ago potentially enabled recurring phases of (probably salty) meltwater runoff (as indicated by meandering channels) and might therefore have enabled evaporite deposition in the Hellas basin. Being twice as buoyant as salt, water ice would require an only ~1 km thick layer (i.e., ~36,000 km3) to form honeycomb‐sized diapirs, which would be in agreement with a likely ~2 km thick ice stability zone beneath the Hellas basin floor. However, it would remain an open question as to why we find only one such ice diapir landscape on Mars.
Ecología de Macroalgas Marinas Exóticas: aproximación a los factores que regulan la colonización de Caulerpa cylindracea en el Mediterráneo y su interacción con los hábitats bentónicos (praderas de Posidonia Oceanica)

El objetivo general de la tesis doctoral es analizar el establecimiento y ecologia de Caulerpa cylindracea en el Mar Mediterraneo bajo la perspectiva de su potencial colonizador, profundizando en el estudio de la interaccion del alga con las praderas de Posidonia oceanica y en el analisis del papel de la luz como factor determinante en los procesos de invasion del alga en esta region. La tesis esta estructurada en 5 capitulos, precedidos de una introduccion general y concluidos con una discusion general, un apartado de conclusiones y una anexo final. En el capitulo 1 se analiza el establecimiento del alga en aguas de la Region de Murcia, y sirve como marco general para definir la zona donde se llevan a cabo el resto de experimentos desarrollados en la tesis. En este capitulo se identifican los principales habitats invadidos en esta zona, asi como la capacidad de dispersion y colonizacion del alga. En los capitulos 2, 3 y 4 se evalua el papel de la luz como factor determinante en los procesos de colonizacion de alga. El capitulo 2 investiga la respuesta fotosintetica del alga ante un gradiente de profundad y la repercusion de dicha respuesta sobre el metabolismo del carbono. En este capitulo se identifican importantes mecanismos de fotoaclimatacion a nivel fotosintetico y se obtienen evidencias sobre el papel positivo de estos mecanismos sobre la capacidad de alga de desarrollarse en un amplio rango de regimenes luminicos. El capitulo 3 analiza el papel de la luz en la resiliencia de las praderas de Posidonia oceanica a la invasion. Mediante un experimento correlacional en campo se obtienen evidencias de que debajo del dosel vegetal de la angiosperma se registran regimenes luminicos que exceden la capacidad de fotoaclimatacion del alga, lo que se relaciona con un desajuste en la optimizacion en la utilizacion de la luz disponible que determina una reduccion en la capacidad productiva del alga. El capitulo 4 confirma estos resultados mediante un analisis experimental complementario desarrollado en condiciones de mesocosmos y campo. Por ultimo, el capitulo 5 constituye la primera serie temporal larga (ocho anos, 2007-2014) que evalua los fenomenos de interaccion en terminos de abundancia entre Caulerpa cylindracea y Posidonia oeanica. El estudio desarrollado revela que (i) las praderas actuan a modo de barrera ecologica frente a la colonizacion del alga y (ii) que el alga no es capaz de competir negativamente con la angiosperma de manera que no es capaz de generar danos en la pradera, al menos al nivel analizado (nivel poblacional)
SARS-CoV-2 Aerosol and Intranasal Exposure Models in Ferrets

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the worldwide COVID-19 pandemic. Animal models are extremely helpful for testing vaccines and therapeutics and for dissecting the viral and host factors that contribute to disease severity and transmissibility. Here, we report the assessment and comparison of intranasal and small particle (~3 µm) aerosol SARS-CoV-2 exposure in ferrets. The primary endpoints for analysis were clinical signs of disease, recovery of the virus in the upper respiratory tract, and the severity of damage within the respiratory tract. This work demonstrated that ferrets were productively infected with SARS-CoV-2 following either intranasal or small particle aerosol exposure. SARS-CoV-2 infection of ferrets resulted in an asymptomatic disease course following either intranasal or small particle aerosol exposure, with no clinical signs, significant weight loss, or fever. In both aerosol and intranasal ferret models, SARS-CoV-2 replication, viral genomes, and viral antigens were detected within the upper respiratory tract, with little to no viral material detected in the lungs. The ferrets exhibited a specific IgG immune response to the SARS-CoV-2 full spike protein. Mild pathological findings included inflammation, necrosis, and edema within nasal turbinates, which correlated to positive immunohistochemical staining for the SARS-CoV-2 virus. Environmental sampling was performed following intranasal exposure of ferrets, and SARS-CoV-2 genomic material was detected on the feeders and nesting areas from days 2–10 post-exposure. We conclude that both intranasal and small particle aerosol ferret models displayed measurable parameters that could be utilized for future studies, including transmission studies and testing SARS-CoV-2 vaccines and therapeutics.
Stochastic Simulation of Strong‐Motion Records from the 2012 Ahar–Varzaghan Dual Earthquakes, Northwest of Iran

Here, the generalized inversion of S ‐wave amplitude spectra is employed for deriving the site response and S ‐wave attenuation (quality factor) in the northwest region of Iran. A total of 279 strong‐motion accelerograms recorded at distances below 200 km from 41 earthquakes with moment magnitudes ranging from M w 3.8 to 6.5 are used to determine the region‐speciﬁc attenuation model. The site responses have been determined for all 54 stations individually. The bulk of strong‐motion data (i.e., 184 records) comes from the 2012 Ahar–Varzaghan dual earthquakes in northwest Iran and their aftershocks. Also, the modified finite‐fault method, which is able to model nonuniform stress distribution on the fault plane, is employed to investigate the coseismic stress parameter for the first and second Ahar–Varzaghan dual earthquakes by minimizing the difference between the synthesized and observed pseudospectral accelerations for 5% damping. Results denote a concentration of stress drops on the northwestern part of the first event’s fault and on the central and eastern part of the second fault. Stochastic simulations, using the calibrated stress distribution have been performed on a regular grid covering the study area for both rock‐ and soil‐site conditions (in total, 651 points). The results show that the maximum of peak ground accelerations (PGAs) during the Ahar–Varzaghan dual earthquakes for the rock‐site condition reached 557 cm/s/s, and the largest peak ground velocities (PGVs) were estimated around 76 cm/s. In general, comparisons between simulated data and empirical ground‐motion prediction equations (GMPEs) show that the stochastic predictions (PGAs and PGVs) are higher than those predicted by the empirical GMPEs for distances less than 30 km and are smaller for distances more than 30 km. The simulated data are also consistent with the modiﬁed Mercalli intensity observations and show reasonable agreement. This can be considered as another validation of the method.
Revisiting the Subsurface geology of Sabine Peninsula (Melville British Columbia, Canada Island, Western Arctic) through geostatistically-steered data processing and interpretation

The Drake and Hecla gas fields that occur on the Sabine Peninsula of Melville Island are the two largest conventional natural gas fields in Canada and are estimated to contain a combined 8.9 trillion cubic feet of recoverable gas. Modern processing and interpretation methods guided by geostatistical models were applied to more than 3400 line-kilometres of legacy seismic data from onshore Sabine Peninsula. The success of the reprocessing improved the imaging and hence the interpretation of the Devonian through Cretaceous succession. Faults were active repeatedly and control many of the Permian and younger structures. Regional subsurface mapping has identified a number of unconformities and better constrained the relationships between units. The existing discoveries in the region along with the improved understanding of the subsurface lead to the identification of new hydrocarbon plays.
Investigating optimal features in log files for anomaly detection using optimization approach

Logs have been frequently utilised in different software system administration activities. The number of logs has risen dramatically due to the vast scope and complexity of current software systems. A lot of research has been done on log-based anomaly identification using machine learning approach. In this paper, we proposed an optimization approach to select the optimal features from the logs. This will provide the higher classification accuracy on reduced log files. In order to predict the anomalies three phases are used: i) log representation ii) feature selection and iii) Performance evaluation. The efficacy of the proposed model is evaluated using benchmark datasets such as BlueGene/L (BGL), Thunderbird, spirit and hadoop distributed file system (HDFS) in terms of accuracy, converging ability, train and test accuracy, receiver operating characteristic (ROC) measures, precision, recall and F1-score. The results shows that the feature selection on log files outperforms in terms all the evaluation measures.
Beneficial Interactive Effects Provided by an Arbuscular Mycorrhizal Fungi and Yeast on the Growth of Oenothera picensis Established on Cu Mine Tailings

Phytoremediation, an environmentally friendly and sustainable approach for addressing Cu-contaminated environments, remains underutilized in mine tailings. Arbuscular mycorrhizal fungi (AMF) play a vital role in reducing Cu levels in plants through various mechanisms, including glomalin stabilization, immobilization within fungal structures, and enhancing plant tolerance to oxidative stress. Yeasts also contribute to plant growth and metal tolerance by producing phytohormones, solubilizing phosphates, generating exopolysaccharides, and facilitating AMF colonization. This study aimed to assess the impact of AMF and yeast inoculation on the growth and antioxidant response of Oenothera picensis plants growing in Cu mine tailings amended with compost. Plants were either non-inoculated (NY) or inoculated with Meyerozyma guilliermondii (MG), Rhodotorula mucilaginosa (RM), or a combination of both (MIX). Plants were also inoculated with Claroideoglomus claroideum (CC), while others remained non-AMF inoculated (NM). The results indicated significantly higher shoot biomass in the MG-NM treatment, showing a 3.4-fold increase compared to the NY-NM treatment. The MG-CC treatment exhibited the most substantial increase in root biomass, reaching 5-fold that in the NY-NM treatment. Co-inoculation of AMF and yeast influenced antioxidant activity, particularly catalase and ascorbate peroxidase. Furthermore, AMF and yeast inoculation individually led to a 2-fold decrease in total phenols in the roots. Yeast inoculation notably reduced non-enzymatic antioxidant activity in the ABTS and CUPRAC assays. Both AMF and yeast inoculation promoted the production of photosynthetic pigments, further emphasizing their importance in phytoremediation programs for mine tailings.
An Exploration Of How Individuals Living With Diabetes Mellitus Access And Apply Foot Health Education To Prevent Diabetic Foot Complications: A Qualitative Descriptive Study

n Canada, three million persons have Diabetes Mellitus and up to 20% will develop foot ulcers that may lead to amputation if not addressed. Patient foot health education focuses on knowledge, behaviour and daily engagement in prevention activities, yet many lack knowledge and awareness of foot health. The aim of this qualitative study was to explore how individuals living with DM access and apply foot health education to protect their feet from DM related foot complications.
SWOT Matrix Analysis of Gastronomic Features of Fermented Products in Cisambeng Village, Majalengka

This study aims to formulate a digital marketing strategy for fermented products as superior gastronomy in Cisambeng Village, Majalengka Regency. This study uses qualitative research methods with data collection techniques through in-depth interviews, literature studies and documentation studies. The SWOT analysis carried out provides information that fermented food in Majalengka Regency has a great opportunity to be developed into a new food innovation that can build villages in opening job vacancies. SWOT matrix results show that producer of fermented food such as tofu, tempeh, oncom, and dage are experiencing growth, therefore a strength-opportunity strategy can be implemented. This can be achieved by improving the quality of human resources through the recruitment of individuals who are focused on online marketing. Content can be created in the form of videos about the products. The quality of product packaging can be improved to ensure longevity, potentially through the use of vacuum sealing or attractively designed food packages. Existing advertising services owned by social media platforms (online-ads) can be utilized. Consumer reviews can be uploaded on social media to enhance marketing efforts.
Model-Free Predictive Current Control of Five-Phase PMSM Drives

Model predictive control is highly dependent on accurate models and the parameters of electric motor drives. Multiphase permanent magnet synchronous motors (PMSMs) contain nonlinear parameters and mutual cross-coupling dynamics, resulting in challenges in modeling and parameter acquisition. To lessen the parameter dependence of current predictions, a model-free predictive current control (MFPCC) strategy based on an ultra-local model and motor outputs is proposed for five-phase PMSM drives. The ultra-local model is constructed according to the differential equation of current. The inherent relation between the parameters in the predictive current model and the ultra-local model is analyzed in detail. The unknowns of the ultra-local model are estimated using the motor current and voltage at different time instants without requiring motor parameters or observers. Moreover, space vector modulation technology is employed to minimize the voltage tracking error. Finally, simulations and experiments are conducted to verify the effectiveness of the MFPCC with space vector modulation. The results confirm that the proposed method can effectively eliminate the impact of motor parameters and improve steady-state performance. Moreover, this control strategy demonstrates good robustness against load variations.
A Review Study on various Image Security Techniques and Emerging trends for Visual Data Protection

In the rapidly evolving digital age, the proliferation of visual data and images has led to increased concerns about their security and protection. This paper reviews various image security techniques and emerging trends aimed at safeguarding visual data in a digital landscape. The research explores the evolution of image security measures and their adaptation to address contemporary challenges in data protection. This study introduces the stage by elucidating the multifaceted nature of image security, emphasizing its significance in preserving the confidentiality and integrity of visual data. The complex landscape of image security threats is examined, highlighting the challenges faced in safeguarding visual data from various vulnerabilities. This paper delves into the need and significance of image security in the digital age, presenting a compelling case for the adoption of robust security measures. It explores the risks associated with image theft and tampering in the online world and underscores the essential role of image encryption and authentication methods in countering these threats. The study then delves into the realm of encryption techniques, offering insights into both symmetric and asymmetric cryptographic algorithms designed to enhance image security on the internet. The research extends its focus to secure data hiding techniques, such as reversible data hiding in encrypted images, histogram shifting-based data hiding, and high-embedding capacity methods employing optimization algorithms. The paper also explores digital watermarking as a means of image authentication and copyright protection, along with image tamper detection and self-recovery mechanisms in watermarking schemes. Additionally, this review assesses the impact of emerging trends, including machine learning, Blockchain, and AI-based solutions, on the security of visual data, such as deep neural networks, generative adversarial neural networks, and their role in image steganography, forensics, and privacy protection. Consequently, by providing an in-depth analysis of the current state of image security and future directions, this study contributes to the understanding of the critical role played by image security in the digital age and its implications for data protection and privacy.
Re‐examination of the 2003 North American electrical blackout impacts on regional air quality

Aircraft measurements have been utilized to capitalize on the 2003 North American electrical blackout as an unplanned event providing a unique opportunity to assess the impacts of power plants on air quality. Here we adopt a modeling approach using CMAQ with a direct sensitivity technique, DDM‐3D, to quantify how emissions reductions from different sources impacted ozone and particulate matter. Simulated air quality fields were able to reproduce both the regular surface observations and airborne measurements before and during the blackout. Sensitivity results show that blackout‐linked power plant SO2 emissions reductions led to a sulfate concentration reduction of 22% at Selinsgrove, Pennsylvania, while power plant NOx emissions reductions had very limited (∼4%) impacts on O3. These results are lower than the estimates presented in previous studies. Results also suggest that over much of the region, on‐road mobile NOx emissions reductions linked to the blackout had a larger impact on O3.
Multi Polar q-Rung Orthopair Fuzzy Graphs with Some Topological Indices

The importance of symmetry in graph theory has always been significant, but in recent years, it has become much more so in a number of subfields, including but not limited to domination theory, topological indices, Gromov hyperbolic graphs, and the metric dimension of graphs. The purpose of this monograph is to initiate the idea of a multi polar q-rung orthopair fuzzy graphs (m-PqROPFG) as a fusion of multi polar fuzzy graphs and q-rung orthopair fuzzy graphs. Moreover, for a vertex of multi polar q-rung orthopair fuzzy graphs, the degree and total degree of the vertex are defined. Then, some product operations, inclusive of direct, Cartesian, semi strong, strong lexicographic products, and the union of multi polar q-rung orthopair fuzzy graphs (m-PqROPFGs), are obtained. Also, at first we define some degree based fuzzy topological indices of m-PqROPFG. Then, we compute Zareb indices of the first and second kind, Randic indices, and harmonic index of a m-PqROPFG.
DOMR: Toward Deep Open-World Malware Recognition

Deep learning has been widely used for Android malware family recognition, but current deep learning-based approaches make the closed-world assumption that malware families encountered during testing are available at training phase. Unfortunately, this assumption is often violated in practice due to the constant emergence of novel categories and the huge cost of collecting abundant training classes, causing serious failures to the existing approaches. Accordingly, a new problem setting for Android malware family recognition is introduced, i.e., deep open-world malware recognition that poses two critical tasks: 1) Open recognition, aiming to not only classify malware from known families (present in training) but detect malware from unknown families (absent in training); 2) Incremental update, aiming to learn about the detected unknown/new categories without retraining from scratch and catastrophically forgetting the previously learned known/old classes. This paper formalizes the problem and proposes a novel solution called DOMR to address the above two tasks in a unified framework. The core of DOMR is an episode-based representation learning scheme that mimics the open-world setting through episodic training to learn a generalizable representation. The key insight is that the training process following the open-world setting forces the representation to accumulate experience in open recognition, thereby facilitating both the classification of known family instances and the detection of unknown family instances at inference. Given this representation, multiple one-vs-rest classifiers are subsequently built to make the final recognition decision through an aggregative strategy. Comparative experiments show that DOMR outperforms start-of-the-art methods, with macro-averaged F1-scores obtained on two datasets reaching 80.88% and 56.17% in the open case, and 79.34% and 49.55% in the incremental case, respectively. Ablation studies further analyze the effectiveness of DOMR in achieving the open recognition and incremental update goals.