Miracle-dz/UniFAR-FTUs huggingface dataset:
Preclinical and Clinical Medical Students’ Perception of the Learning Environment: A Reference to the Forensic Medicine and Clinical Toxicology Course

Purpose: Understanding learning environments is vital for developing curricula. This study aims to evaluate medical students’ achievements and perception of learning environments considering the Forensic Medicine and Clinical Toxicology course as an analog for the curricular transition process. Methods: A cross-sectional study was conducted among undergraduate medical students at the Faculty of Medicine, Tanta University, from August 2020 to October 2021. Using the Dundee Ready Education Environment Measure (DREEM) questionnaire, the perception of 621 students (of which 307 were enrolled in the integrated curriculum and 314 in the traditional curriculum) were compared. Furthermore, the appropriate tests of significance and correlations were used to compare students’ perception according to their enrollment, age, gender, and previous year grade point average. Results: The mean overall DREEM score was 121.04 ± 22.35, implying a more positive than negative learning environment, that is, a more positive learning perception, with students’ perceptions of teachers moving in the right direction, students’ academic self-perceptions getting more on the positive side, more positive attitudes regarding student’s perceptions of the learning environment, and not-too-bad student’s social self-perception. Medical students enrolled in the integrated curriculum showed higher DREEM scores, with significantly better learning and academic self-perceptions (p < 0.05). Knowledgeable, qualified faculties are the most significant characteristic feature in both systems. A significant number of students achieved excellent grades in the integrated curriculum (n = 740 out of 1076, 68.8%) than in the traditional one (n = 470 out of 961, 48.9%) (p < 0.0001). Conclusion: This study revealed a smooth, successful transition from the traditional to integrated curriculum among Egyptian medical students. The main areas for improvements are focusing on factual teaching, implementing student-centered teaching activities, promoting students’ memorizing, and engaging students in activities that may help them enjoy learning. these changes in the different learning phases. Therefore, and because of the critical medicolegal importance of the Forensic Medicine and Clinical Toxicology course, our study aims to evaluate medical students’ perception of learning environments wherein the course is delivered in two different learning contexts (traditional subject-based curriculum versus the integrated system-based curriculum). Moreover, this study aims to compare students’ achievements in the MBBCH program—where the course is taught in clinical phases—with the integrated MSBP-CB program—where the same course is delivered in basic phases.
Sulfide minerals from the Horoman peridotite, Hokkaido, Japan.

Ni-bearing minerals such as pentlandite, heazlewoodite, unknown sulfide minerals X, Y and Z are found in the Horoman peridotite, Hokkaido, Japan. Cu-rich mineral of talnakhite, bornite and native copper also occurs associating with Ni-bearing minerals. Pentlandite has the compositional range from 4.276 to 5.238 in atomic ratio of Fe (total atoms=17) changing coexisting minerals. Unknown sulfide mineral X has composition with Cu: 0.010∼0.144, Fe: 5.573∼6.044: Ni: 2.800∼3.392, Co: 0.047∼0.109, S: 7.884∼8.109 in atomic ratio (total atoms=17) and its ideal formula is (Fe, Cu)6Ni3S8. The compositional range of unknown sulfide mineral Y is Cu: 0.573∼1.003, Fe: 5.783∼6.154: Ni: 1.875∼2.392, Co: 0.012∼0.036, S: 7.953∼8.099 in atomic ratio (total atoms=17), and most copper rich end corresponds to CuFe6Ni2S8. Unknown sulfide mineral Z has ideal formula of Cu2Fe5Ni2S8. Pentlandite and unknown sulfide mineral X occur as primary minerals in the peridotite. Talnakhite and bornite are also found and has their ideal compositions.
Sensitivity of regional climatic simulation over Southeastern South America to SST specification during austral summer

The impact of the sea‐surface temperature (SST) specification over the South Atlantic Ocean on the interannual variability of the simulated precipitation and air temperature over Southeastern South America (SESA) was studied during ten austral summers, from 1989 to 1998, using the Regional Climate Model version 3 (RegCM3), driven by the National Centers for Environmental Prediction (NCEP) reanalysis. The analyses were performed by comparing simulations forced with: (1) monthly observed SST (OSST); (2) SST composed by the persistence of November SST anomalies superimposed on the climatological observed cycle (persisted SST‐PSST). The results show that, over the continental SESA, the PSST impact is low on the simulated seasonal precipitation and air temperature climatologies. Furthermore, the interannual seasonal anomalies in this area do not change sign as a function of the prescribed SST. This is very important since it shows that, on a seasonal timescale, the use of PSST over the subtropical South Atlantic does not introduce additional error source in the regional model simulations over the continental SESA. Over the Atlantic Ocean, mainly in the region where the South Atlantic Convergence Zone (SACZ) acts, the simulations presented a direct response as a function of the SST, i.e. if the PSST is warmer (colder) than the OSST, the seasonal precipitation increases (decreases).
Privacy Strategies for Conversational AI and their Influence on Users' Perceptions and Decision-Making

Conversational AI (CAI) systems are on the rise and have been widely adopted in homes, cars and public spaces. Yet, people report privacy concerns and mistrust in these systems. Current data protection regulations ask providers to communicate data practices transparently and provide users with options to control their data. However, even if users are given control, their decisions can be subject to heuristics and biases leaving people frustrated and regretful. Based on the idea of conversational privacy and debiasing, we design three privacy strategies for CAI that allow people to have their data deleted while at the same time promoting rational decision-making. We conduct a user study to test our strategies in two widespread scenarios using a text-based CAI system and evaluate their impact on peoples’ privacy perception, usability and attitude-behaviour alignment. We find that our strategies can significantly change people’s behaviour, but do not influence peoples’ privacy perception. Finally, we discuss evaluation metrics and future research directions to investigate privacy controls in Conversational AI systems.
Rare Category Analysis for Complex Data: A Review

Despite the sheer volume of data being collected, it is often the rare categories that are of the most important in many high impact domains, ranging from financial fraud detection in online transaction networks to emerging trend detection in social networks, from spam image detection in social media to rare disease diagnosis in the medical decision support system. The unique challenges of rare category analysis include: (1) the highly skewed class distribution; (2) the non-separability nature of the rare categories from the majority classes; (3) the data and task heterogeneity; (4) the time-evolving property of the input data sources. This survey aims to provide a concise review of the state-of-the-art techniques on complex rare category analysis, where the majority classes have a smooth distribution while the minority classes exhibit the compactness property in the feature space or subspace. Rare category analysis aims to identify, characterize, represent and interpret the anomalies that not only show statistical significance but also exhibit interesting patterns (e.g, compactness, high-order structures, shown in a burst, etc.). More specifically, we start with the introduction, problem definition, and unique challenges of complex rare category analysis, then present a comprehensive review of recent advances that are designed for this problem setting, from rare category exploration without any label information to the exposition step that characterizes rare examples with a compact representation, from representing rare patterns in a salient embedding space to interpreting the prediction results and providing relevant clues for the end-users’ interpretation; finally, we discuss the potential problems and shed light on the future directions of complex rare category analysis.
"It doesn't just feel like something a lawyer slapped together." Mental-Model-Based Privacy Policy for Third-Party Applications on Facebook

Users are often unaware of the information that applications collect and are surprised by unexpected data collection and sharing practices. With numerous third-party applications on Facebook potentially accessing the personal information of billions of users, it is essential to understand users’ mental models of data sharing to help them make informed decisions. To achieve this, we conducted semi-structured interviews using drawings and think-aloud protocol with 32 participants. Our participants had misconceptions regarding third-party applications’ data sharing practices with varied mental models. Based on these findings, we created mental model-based privacy policy design that prompts users to consider a specific scenario and provides information to help them understand their misconceptions. To evaluate our designs, we then conducted an online study with 26 participants over Amazon Mechanical Turk (MTurk). Our results showed that using mental models helped users comprehend the message in the privacy policy, connect them to the design, and grabbed their attention. Finally, we offer recommendations for future research regarding the usage of mental models in designs to combat users’ misconceptions with an effortless depiction of privacy policy.
Exploring Pedagogies & Strategies for Integrating Adaptive Learning Platforms: A Case Study of a High School in Hong Kong

This paper explores the pedagogical approaches teachers employ and the strategies that school leaders implement to promote the use of an Adaptive Learning Platform (ALP) in a high school in Hong Kong. It assesses how such an AI-powered platform can support teachers in enhancing student engagement and learning outcomes. The study employs a case study methodology to identify the factors influencing the incorporation of ALP. Qualitative data were collected through teacher interviews, and an in-depth analysis was carried out to identify effective pedagogies and strategies for implementing adaptive learning. The findings of this study underscore the significance of supportive school leadership that encourages teachers to embrace ALP as a tool for promoting student learning. Additionally, effective implementation of ALP necessitates a shift in pedagogical practices from traditional teacher-centred approaches to more student-centred strategies. The study concludes that the integration of ALP into teaching practices can boost student engagement and elevate the quality of learning outcomes. In summary, this research contributes to understanding the successful implementation of ALP in high schools, emphasising the critical roles of school leadership support and the adoption of student-centred pedagogies. The findings provide valuable insights for educators, administrators, and policymakers interested in utilising ALP to improve student learning outcomes.
Are You Anonymous? Inferring Personal Information from Nonverbal Behavior Data Tracked in Immersive Virtual Reality

The growing adoption of virtual reality (VR) technology has raised concerns regarding individuals’ privacy. We explored people’s ability to infer personal information about others from representations of nonverbal behavior data tracked in VR. We conducted a within-subject experiment with 53 participants to explore if they could guess personal information from gestures, spatial behavior, and a combination of both represented through neutral avatars in VR. We found that participants could not guess better than random for most features, except for age and native English speaker status. Furthermore, there were almost no differences between the various types of behavior, except for native English speaker status. We discuss how our results contradict previous research on people’s identification from nonverbal behavior. Our study is the first to address people’s ability to infer other people’s information from nonverbal behavior in VR.
“It's not that I want to see the student's bedroom...”: Instructor Perceptions of e-Proctoring Software

The COVID-19 pandemic motivated higher education institutions to adopt the use of e-proctoring software as a means to maintain academic integrity. This study explores the tension between student privacy and academic integrity from instructors’ perspective. Through semi-structured qualitative interviews with 19 university instructors, our findings delineate the competing factors influencing instructors’ adoption or avoidance of e-proctored assessments: academic integrity, the online remote format, logistical considerations such as class size, departmental policies, and privacy considerations. We analysed instructors’ specific privacy attitudes towards e-proctoring, and perspectives regarding student privacy and institutional data protection practices. Lastly, we evaluated instructors’ appraisals on the efficacy of e-proctoring software. E-proctoring was presented to instructors as the straightforward solution, but we found instructors’ experiences to be complex, leading them to exhibit conflicted views on whether e-proctoring accomplished its goals. Most instructors deprioritized privacy considerations when deciding whether to adopt e-proctoring but viewed academic integrity as the topmost inviolable priority. Overall, we provide insight into a detailed landscape showcasing the complexities of managing privacy and competing priorities within higher education from the instructors’ perspective.
Lithosphere folding: Primary response to compression? (from central Asia to Paris basin)

We examine the role of lithosphere folding in the large‐scale evolution of the continental lithosphere. Analysis of the record of recent vertical motions and the geometry of basin deflection for a number of sites in Europe and worldwide suggests that lithospheric folding is a primary response of the lithosphere to recently induced compressional stress fields. Despite the widespread opinion, folding can persist during long periods of time independently of the presence of many inhomogeneities such as crustal faults and inherited weakness zones. The characteristic wavelengths of folding are determined by the presence of young lithosphere in large parts of Europe and central Asia and by the geometries of the sediment bodies acting as a load on the lithosphere in basins. The proximity of these sites to the areas of active tectonic compression suggests that the technically induced horizontal stresses are responsible for the large‐scale warping of the lithosphere. Wavelengths and persistence of folding are controlled by many factors such as rheology, faulting, time after the end of the major tectonic compression, nonlinear effects, and initial geometry of the folded area. In particular, the persistence of periodical undulations in central Australia (700 Myr since onset of folding) or in the Paris basin (60 Myr) long after the end of the initial intensive tectonic compression requires a very strong rheology compatible with the effective elastic thickness values of about 100 km in the first case and 50–60 km in the second case.
Direct Rhenium-Osmium age of the Oxfordian-Kimmeridgian boundary, Staffin bay, Isle of Skye, U.K., and the Late Jurassic time scale

Ar39 Ar age for the basal Berriasian suggest that the duration of the Kimmeridgian and Tithonian were nominally ~650 k.y. shorter than previously determined. The Re-Os data for the Staffin black shale indicates that the seawater Os isotope composition at the Oxfordian/Kimmeridgian boundary was radiogenic ( 187 Os/ 188 Os = 0.53), similar to that for the Early Tithonian, but much higher than the Late Callovian ( 187 Os/ 188 Os = 0.27). These Os isotope compositions suggest that the rate of continental weathering had increased from the Callovian to Kimmeridgian/Tithonian.
Humidity variability revealed by a sounding array and its implications for cloud representation in GCMs

Subgrid‐scale humidity variability is critical for statistical cloud schemes. The Atmospheric Radiation Measurement (ARM) sounding array, covering a comparable size to a grid box of current global climate models (GCMs), provides estimates of subgrid‐scale humidity variability. Using radiosonde measurements from ARM sounding arrays, humidity variabilities at a tropical and a midlatitude site are analyzed. Normalized moisture variance is small in the lower troposphere but tends to be large in the middle troposphere. Moisture variability dominates relative humidity (RH) variability at the tropical site, but the contribution by temperature variability cannot be ignored at the midlatitude site. Based on the analysis, a simple linear relationship between RH variance and mean is proposed. Cloud schemes assuming Gaussian distributions give comparable cloudiness as those assuming a beta distribution considering both moisture variance and skewness. A probability distribution function scheme assuming a Gaussian distribution of RH has more flexibility than a RH threshold scheme, which tends to overestimate cloudiness in the moist boundary layer over the tropics. Supersaturation with respect to ice needs to be allowed in the upper troposphere over the tropics to reduce the persistent overestimated cloudiness there. Similar comparison results are found from analysis of cloud resolving model simulations. The study suggests that measurements from sounding arrays would be valuable for statistical cloud scheme evaluation and development.
Safety and efficacy of doxycycline in the treatment of rosacea

: Rosacea is a common, chronic, skin condition characterized by recurrent episodes of facial flushing, transient or persistent erythema, papules, pustules, and telangiectasias, in a symmetrical facial distribution. The etiology of rosacea remains unknown and this condition represents a therapeutic challenge because of its chronic nature, progression, potential for disfigurement and psychological impact. Although there is no curative therapy for rosacea, the most widely used systemic agents are oral tetracycline derivatives, including tetracycline, doxycycline, and minocycline. This article reviews the available evidence for the use of doxycycline, a second-generation tetracycline, in the treatment or rosacea.
VARIABILITY IN THE CHEMICAL COMPOSITION OF IN SITU SUBGLACIAL MELTWATERS

Meltwaters collected from boreholes drilled to the base of the Haut Glacier d'Arolla, Switzerland have chemical compositions that can be classified into three main groups. The first group is dilute, whereas the second group is similar to, though generally less concentrated in major ions, than contemporaneous bulk glacial runoff. The third group is more concentrated than any observed bulk runoff, including periods of flow recession. Waters of the first group are believed to represent supraglacial meltwater and ice melted during drilling. Limited solutes may be derived from interactions with debris in the borehole. The spatial pattern of borehole water levels and borehole water column stratification, combined with the chemical composition of the different groups, suggest that the second group represent samples of subglacial waters that exchange with channel water on a diurnal basis, and that the third group represent samples of water draining through a ‘distributed’ subglacial hydraulic system. High NO−3 concentrations in the third group suggest that snowmelt may provide a significant proportion of the waters and that the residence time of the waters at the bed in this particular section of the distributed system is of the order of a few months. The high NO−3 concentrations also suggest that some snowmelt is routed along different subglacial flowpaths to those used by icemelt. The average SO2−4: (HCO−3 + SO2−4) ratio of the third group of meltwaters is 0.3, suggesting that sulphide oxidation and carbonate dissolution (which gives rise to a ratio of 0.5) cannot provide all the HCO−3 to solution. Hence, carbonate hydrolysis may be occurring before sulphide oxidation, or there may be subglacial sources of CO2, perhaps arising from microbial oxidation of organic C in bedrock, air bubbles in glacier ice or pockets of air trapped in subglacial cavities. The channel marginal zone is identified as an area that may influence the composition of bulk meltwater during periods of recession flow and low diurnal discharge regimes. © 1997 by John Wiley & Sons, Ltd.
A surrogate non-intrusive reduced order model of quasi-geostrophic turbulence dynamics based on a combination of LSTM and different approaches of DMD

Mathematical modeling is applied to study phenomena and system behavior.In various engineering fields, many physical phenomena are illustrated using a set of differential equations.In many real-world applications, the mathematical models are very complex, and numerical simulations in high-dimensional systems are challenging.Examples of these problems are large-scale physical problems such as geophysical, which have high temporal and spatial variations.In these problems, model order reduction is a useful method for achieving an appropriate approximation because it can significantly decrease computational costs.Deep learning has recently been used to explore information from data and make predictions.There are several methods for dimensionality reduction.In this paper, we combine the dynamic mode decomposition (DMD) and the long short-term memory (LSTM) network.This is because LSTM can predict nonlinear systems and time series data.We use LSTM and DMD to predict nonlinear systems and reduce dimensions, respectively.Four common DMD schemes have been applied for dimensionality reduction.The common geophysical dataset has been used to evaluate the performance of the proposed method.Finally, we compare the variations of the modal coefficients which are obtained from snapshots projection and the reduced-order model.These results show the high accuracy of our proposed method.One of the things that is important is the time complexity of algorithm implementation.The time complexity of the proposed method is 10 times faster when 15 modes are used for modeling than when all features are used.