Miracle-dz/UniFAR-FTUs huggingface dataset:
AVO analysis of 3-D seismic data at G-field, Norway

The Amplitude variation with offset (AVO) analysis looks at how the amplitude of reflection events, such as those at the top of reservoir intervals, change with varying offset or reflection angle. By modelling these effects for different reservoir fluids via fluid substitution, effects of production can be recognised within the seismic data. Amplitude differences viewed between survey vintages can also highlight the movement of fluid contacts and changing fluid compositions throughout the reservoir. AVO analysis was performed on the three wells; well A, B and C. The analysis involves in creating a synthetic model to infer the amplitude responses observed at a particular reservoir horizon. Four types of fluid model substitution were created; pure brine, pure oil, pure gas and brine mix (70% Brine, 20% Gas and 10% Oil). Prominent amplitude changes which correspond primarily to the production effects can be seen in the Tarbert reservoir
Self-Rotation of Electrothermally Responsive Liquid Crystal Elastomer-Based Turntable in Steady-State Circuits

Self-excited motions, characterized by their ability to harness energy from a consistent environment and self-regulate, exhibit significant potential in micro-devices, autonomous robotics, sensor technology, and energy generation. This study introduces an innovative turntable system based on an electrothermally responsive liquid crystal elastomer (LCE). This system facilitates self-rotation within a steady-state circuit. Employing an electrothermal LCE model, we have modeled and numerically analyzed the nonlinear dynamics of an LCE-rope within steady-state circuits, utilizing the four-order Runge–Kutta method for calculations. The numerical results reveal the emergence of two distinct motion patterns in the turntable system under steady-state conditions: a self-rotation pattern and a static pattern. The self-rotation is initiated when the system’s absorbed energy surpasses the energy lost due to damping effects. Furthermore, this paper delves into the critical conditions necessary for initiating self-rotation and examines the influence of various key dimensionless parameters on the system’s rotation amplitude and frequency. These parameters include gravitational acceleration, the initial position of the mass ball, elastic stiffness of the LCE and spring, limiting temperature, heating zone angle, thermal shrinkage coefficient, and damping factor. Our computational findings establish that these parameters exert a modulatory impact on the rotation amplitude and period. This research enhances the understanding of self-excited motions and offers promising avenues for applications in energy harvesting, monitoring, soft robotics, medical devices, and micro- and nano-devices.
Authorship Verification in software engineering education

The prevalence of academic misconduct, specifically contract cheating, is a rising concern in higher education institutions globally. Among the recent advancements, Generative Artificial Intelligence (genAI) has exacerbated the situation by offering authentically generated writings, making detection through traditional plagiarism tools ineffective. This paper explores the development and application of students' academic writing profiles, using a combination of word embedding (Word2Vec) and stylistic feature extraction techniques. By leveraging a Siamese neural network, our method focuses on recognising distinctive writing styles, a concept rooted in Authorship Verification (AV). Our approach's efficacy evaluates favourably against other AV methods and is tested against AI-generated texts deliberately designed to mimic student writing. The study emphasises the importance of understanding individual academic writing styles to identify outsourcing or AI-generated work effectively.
Model-based Approach to Small Area Estimation of Disability counts and rates using Data from the 2006 Participation and Activity Limitation Survey

This paper presents the small area model considered to produce estimates of the number of persons with disabilities and disability rates for health regions and selected municipalities using the 2006 Participation and activity limitation survey data. The paper describes the transformations applied to direct estimators and to the variances associated with these estimators in order to meet certain fundamental criteria. The log linear unmatched model to which the hierarchical Bayes (HB) approach was applied by relying on the Gibbs sampling method and the results from the latter model are presented. Lastly, the paper presents the data sampling methodology used to ensure that the final statistics take into account province level results.
GIS AND PALEONTOLOGY OF DHOK BUN AMEER KHATOON FOSSIL SITE, PAKISTAN

This paper deals with Geographic Information System (GIS) and paleontology of newly discovered fossil site (32 o 47' 26.4" N 72° 55' 35.7" E). GIS analyses are essential to study the fossil deposits for reconstructing the taphonomic history. The recent discovery of fossils from Dhok Bun Ameer Khatoon (DBAK), Chakwal district, Pakistan, provides an opportunity of GIS analysis in paleontology with emphasis on the distribution of Giraffokeryx species.
Influence of Suction History on Hydraulic and Stress-Strain Behavior of Unsaturated Soils

Abstract An experimental study was performed to investigate the effects of suction history on the hydraulic and stress-strain behavior of unsaturated soils. Test results show that, even if the same path of net stress and suction was followed during triaxial shearing, the stress-strain and strength behavior are different between specimens experiencing different suction histories. When the maximum suction experienced in the past was less than the residual suction, the specimen that experienced higher past suction produced higher shear strength. This is because the specimen was subjected to a higher suction, i.e., a higher average skeleton stress, and thus became overconsolidated. In contrast, when the maximum suction experienced in the past was higher than the residual suction, the specimen that experienced higher past suction produced lower shear strength. This is because, in this particular case, the high suction induced structural damage in the specimen, which impacts the stress-strain behavior during su.
A Multidisciplinary approach to Tsunami Risk Management: A proposal for a framework based on a case study of Iquique

In this multidisciplinary project a proposal for a framework for tsunami risk management in Chile, has been developed. This was done using Iquique in the north of Chile as a case study. Solutions for improvement of current practice have been searched within specific activity areas of hazard management: prediction, mitigation and response. Prediction concerns the available intelligence on the chance of occurrence and the related force of the tsunami event. For this, earthquake (and resulting tsunami) scenarios have been defined and modeled with NeoWave in order to establish probable boundary conditions for the rest of the research. A scenario based on the conditions described by [Chlieh et al., 2011b], with a Mw. 8.8, turned out to have the worst results (runup of 12m max, inundation of almost 10m max, and arrival time less than 12 min). Based on these results estimations have been made of the number of people at risk and economic damage. The number of people at risk was derived from zonal data from [SINTIA, 2010] and resulted in at least 12,500 people living in inundated areas. Direct economic damage was derived using fragility curves [Mas et al., 2012b] and building value estimations [Blong, 2001], and resulted in 14:90M damage in an Iquique downtown area and 142M damage in the Zofri shopping mall area. For mitigation of tsunami effects, prevention of the tsunami event (e.g. by means of breakwaters) has not been taken into account. Focus has been on city evacuation, possible slope failures of infrastructure, and possibilities of vertical evacuation. For city evacuation remarkable differences between inundation maps from SHOA, ONEMI, the Municipality of Iquique, and our model results were indicated, from which the cause is not clear. An optimistic calculation on evacuation possibilities of the Zofri shopping mall has shown that only 6,000 people (from 10,000 people present during peak hour) could escape. A slope failure analysis of the main exit from the Zofri area and the highway A16 has indicated that both slopes are instable. Additional geo analyses pointed out that safety zones in higher grounds are stable, that there's a lack of knowledge on liquefaction of quaywalls (which could be troublesome for port evacuation routes), and that scouring of sidewalks is likely (however it will not occur during evacuation). An initial analysis on high buildings in Iquique resulted in 56 buildings that have been examined for vertical evacuation and two areas that lack any possibilities for vertical evacuation (Zofri and the port). An hydraulic load analysis has been done, based on both NeoWave model results and analytical approach. After a comparative stability analysis with available criteria for seismic loads, 21 buildings in Iquique were marked as suitable for vertical evacuation.
Influence of Accelerometer Sensor Position for Measurement of Lateral Acceleration of Delivery Van for Cargo Securement

The use of sensors in monitoring lateral accelerations in delivery van transport focuses on measuring lateral accelerations on routes with roundabouts and curves to increase road safety. Using microelectromechanical system (MEMS) sensors, it measures the lateral accelerations acting on the vehicle and the load being transported during the test drives to study vehicle dynamics of delivery van for cargo securing, which is essential to the decision of where accelerometer sensors should be placed when monitoring accelerations or performing cargo securing tests. Using an accelerometer and position tracking, accelerations can be detected when traversing curves and roundabouts at selected locations on the vehicle and load. Manual labeling of acceleration events has been used to identify different lateral acceleration events and regression analysis to determine the relationship between lateral accelerations at different sensor positions. The level of acceleration on the roof of the vehicle was found to be like that occurring on a lashed load with limited movements. If we compare the mean values of the lateral accelerations of the individual events between the sensors, the sensor on the side of the vehicle body at the height of the sensor on the load had approximately 5% lower mean values than the sensor on the roof. The sensor on the load measured approximately 5% higher mean values than the sensor on the roof. Hence, the mean lateral accelerations of the individual events for the sensor on the load are 10% higher than for the sensor at the same height on the vehicle body. The values of the mean lateral accelerations of the delivery van from the sensor on the roof of the vehicle are closer to the values of the accelerations of the sensor on the load than to the values of the sensor on the body of the vehicle at the same height.
Mmp12 Is Translationally Regulated in Macrophages during the Course of Inflammation

Despite the importance of rapid adaptive responses in the course of inflammation and the notion that post-transcriptional regulation plays an important role herein, relevant translational alterations, especially during the resolution phase, remain largely elusive. In the present study, we analyzed translational changes in inflammatory bone marrow-derived macrophages upon resolution-promoting efferocytosis. Total RNA-sequencing confirmed that apoptotic cell phagocytosis induced a pro-resolution signature in LPS/IFNγ-stimulated macrophages (Mϕ). While inflammation-dependent transcriptional changes were relatively small between efferocytic and non-efferocytic Mϕ; considerable differences were observed at the level of de novo synthesized proteins. Interestingly, translationally regulated targets in response to inflammatory stimuli were mostly downregulated, with only minimal impact of efferocytosis. Amongst these targets, pro-resolving matrix metallopeptidase 12 (Mmp12) was identified as a translationally repressed candidate during early inflammation that recovered during the resolution phase. Functionally, reduced MMP12 production enhanced matrix-dependent migration of Mϕ. Conclusively, translational control of MMP12 emerged as an efficient strategy to alter the migratory properties of Mϕ throughout the inflammatory response, enabling Mϕ migration within the early inflammatory phase while restricting migration during the resolution phase.
BoucaNet: A CNN-Transformer for Smoke Recognition on Remote Sensing Satellite Images

Fire accidents cause alarming damage. They result in the loss of human lives, damage to property, and significant financial losses. Early fire ignition detection systems, particularly smoke detection systems, play a crucial role in enabling effective firefighting efforts. In this paper, a novel DL (Deep Learning) method, namely BoucaNet, is introduced for recognizing smoke on satellite images while addressing the associated challenging limitations. BoucaNet combines the strengths of the deep CNN EfficientNet v2 and the vision transformer EfficientFormer v2 for identifying smoke, cloud, haze, dust, land, and seaside classes. Extensive results demonstrate that BoucaNet achieved high performance, with an accuracy of 93.67%, an F1-score of 93.64%, and an inference time of 0.16 seconds compared with baseline methods. BoucaNet also showed a robust ability to overcome challenges, including complex backgrounds; detecting small smoke zones; handling varying smoke features such as size, shape, and color; and handling visual similarities between smoke, clouds, dust, and haze.
Governing Through Gridlock: Bill Composition under Divided Government

Abstract What is the effect of divided government on issue attention in state legislatures? Much of the research on divided government examines how it affects the enactment of significant legislation but does not consider other effects on legislative behavior. In this article, I propose a new theory of the relationship between divided government and legislative activity. Regardless of partisan control, reelection-minded legislators face pressure to deliver benefits to voters, yet divided government can make substantive policy change difficult. As a result of these competing pressures, under divided government legislators increasingly turn their focus to bills that benefit their local constituents, which are seen as easier to enact and allow them to engage in advertising, credit claiming, and position taking. Consistent with this theory, I find that under divided government, legislators introduce bills at the same rate, but the type of legislation introduced shifts away from statewide policy changes and towards district-specific legislation.
Characterizations of novel broad-spectrum lytic bacteriophages Sfin-2 and Sfin-6 infecting MDR Shigella spp. with their application on raw chicken to reduce the Shigella load

The evidence and prevalence of multidrug-resistant (MDR) Shigella spp. poses a serious global threat to public health and the economy. Food- or water-borne MDR Shigella spp. demands an alternate strategy to counteract this threat. In this regard, phage therapy has garnered great interest from medical practitioners and researchers as a potential way to combat MDR pathogens. In this observation, we isolated Shigella phages from environmental water samples and tested against various clinically isolated MDR Shigella spp. In this study, we have defined the isolation and detailed physical and genomic characterizations of two phages Sfin-2 and Sfin-6 from environmental water samples. The phages exhibited potent lytic activity against Shigella flexneri, Shigella dysenteriae, and Shigella sonnei. They showed absorption within 5–10 min, a burst size ranging from ~74 to 265 PFU/cell, and a latent period of 5–20 min. The phages were stable at a broad pH range and survived an hour at 50°C. The purified phages Sfin-2 and Sfin-6 belong to the Siphoviridae family with an isometric head (64.90 ± 2.04 nm and 62.42 ± 4.04 nm, respectively) and a non-contractile tail (145 ± 8.5 nm and 148.47 ± 14.5 nm, respectively). The in silico analysis concluded that the size of the genomic DNA of the Sfin-2 phage is 50,390 bp with a GC content of 44.90%, while the genome size of the Sfin-6 phage is 50,523 bp with a GC content of 48.30%. A total of 85 and 83 putative open reading frames (ORFs) were predicted in the Sfin-2 and Sfin-6 phages, respectively. Furthermore, a comparative genomic and phylogenetic analysis revealed that both phages represented different isolates and novel members of the T1-like phages. Sfin-2 and Sfin-6 phages, either individually or in a cocktail form, showed a significant reduction in the viable Shigella count on raw chicken samples after 72 h of incubation. Therefore, these results indicate that these phages might have a potential role in therapeutic approaches designed for shigellosis patients as well as in the biological control of MDR Shigella spp. in the poultry or food industry during the course of meat storage.
“Low-risk groups” deserve more attention than “high-risk groups” in imported COVID-19 cases

Objective To estimate the optimal quarantine period for inbound travelers and identify key risk factors to provide scientific reference for emerging infectious diseases. Methods A parametric survival analysis model was used to calculate the time interval between entry and first positive nucleic acid test of imported cases in Guangzhou, to identify the influencing factors. And the COVID-19 epidemic risk prediction model based on multiple risk factors among inbound travelers was constructed. Results The approximate 95th percentile of the time interval was 14 days. Multivariate analysis found that the mean time interval for inbound travelers in entry/exit high-risk occupations was 29% shorter (OR 0.29, 95% CI 0.18–0.46, p < 0.0001) than that of low-risk occupations, those from Africa were 37% shorter (OR 0.37, 95% CI 0.17–0.78, p = 0.01) than those from Asia, those who were fully vaccinated were 1.88 times higher (OR 1.88, 95% CI 1.13–3.12, p = 0.01) than that of those who were unvaccinated, and those in other VOC periods were lower than in the Delta period. Decision tree analysis showed that a combined entry/exit low-risk occupation group with Delta period could create a high indigenous epidemic risk by 0.24. Conclusion Different strata of imported cases can result in varying degrees of risk of indigenous outbreaks. “low-risk groups” with entry/exit low-risk occupations, fully vaccinated, or from Asia deserve more attention than “high-risk groups. ”
Pedestrian velocity obstacles: Pedestrian simulation through reasoning in velocity space

SEAN CURTIS: Pedestrian Velocity Obstacles: Pedestrian Simulation through Reasoning in Velocity Space (Under the direction of Dinesh Manocha) We live in a populous world. Furthermore, as social animals, we participate in activities which draw us together into shared spaces – office buildings, city sidewalks, parks, events (e.g., religious, sporting, or political), etc. Models that can predict how crowds of humans behave in such settings would be valuable in allowing us to analyze the designs for novel environments and anticipate issues with space utility and safety. They would also better enable robots to safely work in a common environment with humans. Furthermore, credible simulation of crowds of humans would allow us to populate virtual worlds, helping to increase the immersive properties of virtual reality or entertainment applications. We propose a new model for pedestrian crowd simulation: Pedestrian Velocity Obstacles (PedVO). PedVO is based on Optimal Reciprocal Collision Avoidance (ORCA), a local navigation algorithm for computing optimal feasible velocities which simultaneously avoid collisions while still allowing the agents to progress toward their individual goals. PedVO extends ORCA by introducing new models of pedestrian behavior and relationships in conjunction with a modified geometric optimization planning technique to efficiently simulate agents with improved human-like behaviors. PedVO introduces asymmetric relationships between agents through two complementary techniques: Composite Agents and Right of Way. The former exploits the underlying collision avoidance mechanism to encode abstract factors and the latter modifies the optimization algorithm’s constraint definition to enforce asymmetric coordination. PedVO further changes the optimization algorithm to more fully encode the agent’s knowledge of its environment, allowing the agent to make more intelligent decisions, leading to a better utilization of space and improved flow. PedVO incorporates a new model, which works in conjunction with the local planning algorithm, to introduce a ubiquitous density-sensitive behavior observed in human crowds – the so-called “fundamental diagram. ” We
Comparing Effects of Aggregation Methods on Statistical and Spatial Properties of Simulated Spatial Data

Spatial data aggregation is widely practiced for "scaling-up" environmental analyses and modeling from local to regional or global scales. Despite acknowledgments of the general effects of aggregation, there is a lack of systematic comparison between aggregation methods. The study evaluated three methods - averaging, central-pixel resampling, and median using simulated images. Both the averaging and median methods can retain the mean and median values, respectively, but alter significantly the standard deviation. The central-pixel method alters both statistics. The statistical changes can be modified by the presence of spatial autocorrelation for a11 three methods. Spatially, the averaging method can reveal underlying spatial patterns at scales within the spatial autocorrelation ranges. The median method produces almost identical results because of the similarities between the averaged and median values of the simulated data. To a limited extent, the central-pixel method retains contrast and spatial patterns of the original images. At scales coarser than the autocorrelation range, the averaged and median images become homogeneous and do not difler significantly between these scales. The central-pixel method can induce severe spatially biased errors at coarse scales. Understanding these trends can help select appropriate aggregation methods and aggregation levels for particular -- applications.