Miracle-dz/UniFAR-FTUs huggingface dataset:
Introduction of PBL in the First Year of Traditional Medical Introduction of PBL in the First Year of Traditional Medical Curriculum Curriculum

Purpose : Problem-Based Learning (PBL) is one of the more prominent student-centred approaches introduced in medical education to enhance the effectiveness of traditional lectures that have not always succeeded in preparing medical students for problem-solving in clinical settings. We conducted a study that introduced a short PBL case in a traditional curriculum of ﬁ rst-year medical students and investigated students ’ overall experience. Method : Participants were ﬁ rst-year medical students of a 6-year undergraduate medical programme (MD6) with varying levels of prior exposure to PBL, ranging from none to minor or some experience. All participants completed a questionnaire on their experience following completion of the PBL tutorial. Qualitative analysis of student comments allowed us to gain valuable insights, while quantitative analysis of their responses enabled us to assess their satisfaction with PBL in comparison to traditional lecture-based learning. Results : Analysis of the questionnaires revealed an overwhelmingly positive response from students towards the PBL approach, indicating a strong desire for more PBL-styled classes throughout their medical studies. Discussion : We have shown that the introduction of PBL in the ﬁ rst year of studies of a traditional lecture-based medical curriculum was well received by students, with the majority of them reporting that PBL was more interesting and more engaging than traditional lecture based learning.
Detecting the human ﬁngerprint in the summer 2022 western–central European soil drought

In the 2022 summer, western–central Europe and several other regions in the northern extratropics experienced substantial soil moisture deﬁcits in the wake of precipitation shortages and elevated temperatures. Much of Europe has not witnessed a more severe soil drought since at least the mid-20th century, raising the question whether this is a manifestation of our warming climate. Here, we employ a well-established statistical approach to attribute the low 2022 summer soil moisture to human-induced climate change using observation-driven soil moisture estimates and climate models. We ﬁnd that in western–central Europe, a June–August root zone soil moisture drought such as in 2022 is expected to occur once in 20 years in the present climate but would have occurred only about once per century during preindustrial times. The entire northern extratropics show an even stronger global warming imprint with a 20-fold soil drought probability increase or higher, but we note that the underlying uncertainty is large. Reasons are manifold but include the lack of direct soil moisture observations at the required spatiotemporal scales, the limitations of remotely sensed estimates, and the resulting need to
A STUDY ON MEASURING E-SERVICE QUALITY OF ONLINE E – PHARMACY.

There is growth of E-pharmacy/Online medicine post covid. The purpose of the study is to examine E-service quality of E-pharmacy and give appropriate suggestions to improve the overall E-service quality of E-pharmacy. Parametric t-test is applied to evaluate significant gap analysis of various dimensions of E-service quality. It is seen that customers are satisfied towards Application Design, Reliability, Responsiveness and Information of the portal and customers are not satisfied towards security dimensions of the portal. Further studies can be conducted by building a Structural equation model to evaluate impact of E-service quality on customers satisfaction and customers loyalty.
: Improving the

—Microstrip patch antennas are attractive for communication applications due to their small size, low cost, and easy fabrication. Regardless of the diverse usage of these antennas, their bandwidth and efficiency are still limited and need to be improved. Therefore, this paper aims to enhance the bandwidth and efficiency of a microstrip antenna by inserting a slot into various patch designs. Flame Retardant (FR4) material is used in the dielectric substrate and the antenna is fed by a microstrip line. Virtually, the antenna performance is attempted to be optimized through empirical investigations of feedline lengths, slot sizes and positions, and ground plane dimensions and locations. To achieve the results, the High Frequency Structure Simulator (HFSS) is used, and the paper concludes by showing that the antenna performance is enhanced by the slot, and the return loss is significantly reduced when the ground plane is moved to the front surface of the antenna.
Steelpan-specific pitch detection: a dataset and deep learning model

The steelpan is a pitched percussion instrument that although generally known by listeners is typically not included in music instrument audio datasets. This means that it is usually underrepresented when training existing data-driven deep learning models for fundamental frequency estimation. Furthermore, the steelpan has complex acoustic properties that make fundamental frequency estimation challenging when using deep learning models for general fundamental frequency estimation that are trained to work with any music instrument. Fundamental frequency estimation or pitch detection is a core task in music information retrieval and it is interesting to explore methods that are tailored to specific instruments and whether they can out-perform more general methods. To address this, we present SASS-E, the Steelpan Analysis Sample Set for Evaluation that can be used to train steel-pan specific pitch detection algorithms as well as propose a custom-trained deep learning model for steelpan fundamental frequency estimation. This model outperforms general state-of-the-art methods such as PYIN and CREPE on steelpan audio - even while having significantly fewer parameters and operating on a shorter analysis window. This reduces minimum system latency, allowing for deployment to a real-time system that can be used in live music contexts.
An experimental Investigation for the Effect of the V-cut Baffles in a Grooved Cavity

: - V cut baffles are being used inside a cavity in the current study to speed up heat transfer. To conduct testing, rectangular cavity ducts were manufactured and used. For heat flux (4800, 8000 W/m 2 ), constant heat flux was applied to the cavity's bottom wall. Experiments were conducted on a slew of variables, including Reynolds number, cutting height, and heat flux. Cutting height of 5, 10, and 15 centimeters is maintained, as is the Reynolds number (16000-5000). Using a 15-cm V-cutting baffle at Re=13000 and a heat flux of (4800 W/m 2 ) increases the Nusselt number by 87.1 percent when compared to the straight baffle while using a 5-cm V-cutting baffle at Re=5000 and a heat flux of (q=4800 W/m 2 ) in a cavity increases the Nusselt number by (5.4 percent) when compared to the straight baffle. Baffle height of 10cm at Re=5000 and heat flux (q=4800 W/m 2 ) did not result in any improvement. Another interesting finding is the increase in Nusselt number when using a V-cutting baffle with a heat flux of (q=8000W/m2) and cutting height of 15 cm, and Re=5000, as compared to a straight baffle, which has a heat flux of (q=5000 W/m 2 ). The average Nusselt number (q=8000W/m 2 ) can be predicted using empirical correlation.
Cloud-Native Database Systems and Unikernels: Reimagining OS Abstractions for Modern Hardware

This paper explores the intersection of operating systems and data-base systems, focusing on the potential of specialized kernels for cloud-native database systems. Although the idea of custom, DBMS-optimized OS kernels is old, it is largely unrealized due to the demands of hardware compatibility and the reluctance of users to install specialized operating systems. However, the cloud and the database-as-a-service model make custom OS kernels realistic for the first time. Among specialized OS kernel architectures, uniker-nels stand out for relying on a single address space, eliminating the need for costly process isolation that is provided by general-purpose operating systems. They offer benefits such as the elimination of system call overhead, direct access to hardware, and reduced complexity. Beyond these immediate advantages, unikernels offer a unique opportunity: the possibility to revisit dated POSIX APIs. By allowing direct interaction with modern hardware primitives, unikernels pave the way for the development of novel abstractions that are not confined to the limitations of older APIs, opening doors to a new era of co-designed, high-performance cloud-native data processing systems and OS kernels.
The Electrosteel: An Electronic Instrument Inspired by the Pedal Steel Guitar

The Electrosteel is a new electronic instrument inspired by the user interface of the pedal steel guitar (PSG). The Elec-trosteel uses the interface concepts of the PSG (a bar in the left hand, plucked strings for the right hand, foot pedals, knee levers, etc) as a control paradigm for digital synthesis. The instrument allows performers with skill on the PSG to expand their sonic range, and creates a powerful new multi-dimensional way to control synthesis. This paper describes the development of the instrument and its custom embedded synthesis engine, with a focus on the design challenges posed by mapping an existing performer interface to a new instrument.
Information bottleneck learns dominant transfer operator eigenfunctions in dynamical systems

A common task across the physical sciences is that of model reduction: given a high-dimensional and complex description of a full system, how does one reduce it to a small number of important collective variables? Here we investigate model reduction for dynamical systems using the information bottleneck framework. We show that the optimal compression of a system’s state is achieved by encoding spectral properties of its transfer operator. After demonstrating this in analytically-tractable examples, we show our findings hold also in variational compression schemes using experimental fluids data. These results shed light into the latent variables in certain neural network architectures, and show the practical utility of information-based loss functions.
NO2 climatology in the northern subtropical region: diurnal, seasonal and interannual variability [Discussion paper]

Daily NO2 vertical column density (VCD) has been routinely measured by zenith sky spectroscopy at the subtropical station of Izã na (28 N, 16 W) since 1993 in the framework of the Network for the Detection of Atmospheric Composition Change (NDACC). Based on 14 years of data the first low latitude NO2 VCD climatology has been established and the main characteristics from short timescales of one day to interannual variability are presented. Instrumental descriptions and different sources of errors are described in detail. The observed diurnal cycle follows that expected by gas-phase NO x chemistry, as can be shown by the good agreement with a vertically integrated chemical box model, and is modulated by solar radiation. The seasonal evolution departs from the phase of the hours of daylight, indicating the signature of upper stratospheric temperature changes. From the data record (1993–2006) no significant long-term trends in NO2 VCD can be inferred. Comparison of the groundbased data sets with nadir-viewing satellite spectrometers shows excellent agreement for SCIAMACHY with differences between both datasets of 1.1%. GOME displays unrealistic features with the largest discrepancies during summer. The ground-based data are compared with long-term output of the SLIMCAT 3-D chemical transport model (CTM). The basic model, forced by ECMWF (ERA-40) analyses, captures the observed NO 2 annual cycle but significantly underestimates the spring/summer maximum (by 12% at sunset and up to 25% at sunrise). In a model run which uses assimilation of satellite CH 4 profiles to constrain the model long-lived tracers the agreement is significantly improved. This improvement in modelled column NO 2 is due to better Correspondence to: M. Gil (gilm@inta.es) modelled NOy profiles and points to transport errors in the ECMWF ERA-40 reanalyses.
MIMIR: Modelling user Intentions with Markov chains for Intention Recommendations

Despite detection tools and the automation of cybersecurity, analysts are more in-demand than ever. They have to perform complex security investigations in order to find and qualify threats. It is necessary to speed up and ease security tasks in order to reduce the effects of analysts shortages. Recommender systems are widely used in the task of helping users find their way in enormous amount of heterogeneous data for example in online marketplaces. That situation is similar to the one face by analysts. We thus offer to design a recommender system for incident response. By recognizing 7 relevant user intentions throughout the investigation process, we propose MIMIR, that provides relevant recommendations for the analyst’s next actions based on their most probable objectives. We evaluate MIMIR in different ways, using 4 experiments and 5 datasets. The results show the validity of the model as well as the relevance of recommendations, which is a first step towards recommendations based on user intention recognition in the field of incident response.
Antiandrogen Flutamide-Induced Restoration of miR-449 Expression Mitigates Functional Biomarkers Associated with Ovarian Cancer Risk

Background: The involvement of the androgen and androgen receptor (AR) pathway in the development of epithelial ovarian cancer is increasingly recognized. However, the specific mechanisms by which anti-androgen agents, such as flutamide, may prevent ovarian cancer and their efficacy remain unknown. We examined the effects of flutamide on the miRNA expression profile found in women at high risk (HR) for ovarian cancer. Methods: Ovarian and tubal tissues, free from ovarian, tubal, peritoneal cancers, and serous tubal intraepithelial carcinoma (STIC), were collected from untreated and flutamide-treated HR women. Low-risk (LR) women served as controls. Transcriptomic miRNA sequencing was performed on these 3 sample cohorts. The miRNAs that showed the most notable differential expression were subjected to functional assays in primary ovarian epithelial cells and ovarian cancer cells. Results: Flutamide treatment demonstrated a normalization effect on diminished miRNA levels in HR tissues compared to LR tissues. Particularly, the miR-449 family was significantly upregulated in HR ovarian tissues following flutamide treatment, reaching levels comparable to those in LR tissues. MiR-449a and miR-449b-5p, members of the miR-449 family, were computationally predicted to target the mRNAs of AR and colony-stimulating factor 1 receptor (CSF1R, also known as c-fms), both of which are known contributors to ovarian cancer progression, with emerging evidence also supporting their roles in ovarian cancer initiation. These findings were experimentally validated in primary ovarian epithelial cells and ovarian cancer cell lines (SKOV3 and Hey): flutamide treatment resulted in elevated levels of miR-449a and miR-449b-5p, and introducing mimics of these miRNAs reduced the mRNA and protein levels of CSF1R and AR. Furthermore, introducing miR-449a and miR-449b-5p mimics showed inhibitory effects on the migration and proliferation of ovarian cancer cells. Conclusion: Flutamide treatment restored the reduced expression of miR-449a and miR-449b-5p in HR tissues, thereby decreasing the expression of CSF1R and AR, functional biomarkers associated with an increased risk of ovarian cancer. In addition to the known direct binding of flutamide to the AR, we found that flutamide also suppresses AR expression via miR-449a and miR-449b-5p upregulation, revealing a novel dual-inhibitory mechanism on the AR pathway. Taken together, our study highlights mechanisms supporting the chemopreventive potential of flutamide in ovarian cancer, particularly in HR patients with reduced miR-449 expression.
Evaluation of methodologies for risk assessment of combined toxic actions of chemical substances and establishment of PBTK/TD models for pesticides

The risk assessment of pesticide residues in food is based on toxicological evaluation of the single compounds and no internationally accepted procedure exists for evaluation of cumulative exposure to multiple residues of pesticides in crops, except for a few groups of pesticides sharing a group ADI. However, several attempts have been suggested during the last decade. This paper gives an overview of the various approaches. It is of paramount importance to consider whether there will be either no interaction or interaction between the compounds in the mixture. When there are no interactions several approaches are available for the risk assessment of mixtures of pesticides. However, no single simple approach is available to judge upon potential interactions at the low doses that humans are exposed to from pesticide residues in food. In these cases, PBTK models could be useful as tools to assess combined tissue doses and to help predict potential interactions including thresholds for such effects. This would improve the quality of the risk assessment. 2009 Elsevier Inc. All rights reserved.
Interaction of the Cyprus/Tethys slab with the mantle transition zone beneath Anatolia

This work has been supported by the UK Natural Environment Research Council under grant NE/I028017/1. Seismic equipment was provided by the NERC Geophysical Equipment Facility (SEIS-UK) under loan 947. Additional funds were provided by the Bogazici University Scientific Research Projects (BAP) under grant 6922 and the Turkish State Planning Organization (DTP) under the TAM project number 2007K120610. G.T. was supported by the Leeds-York Doctoral Training Partnership (SPHERES) of the Natural Environment Research Council (NERC), UK (NE/L002574/1).
Smoking-Related Disease Impact in the Eastern Mediterranean Region: A Comprehensive Assessment Using Global Burden of Disease Data.

BACKGROUND Smoking remains a significant risk factor for numerous health issues, including lung cancer, chronic obstructive pulmonary disease, ischemic heart disease, stroke, and respiratory infections. This study investigates the burden of tobacco-related diseases in the Middle East and North Africa (MENA) region. METHODS Utilizing the GBD data, we examined the risk of smoking and second-hand smoke exposure and their related causes of death and disability in the 22 MENA countries. Smoking prevalence and disease burden data were analyzed with estimates reported as age-standardized rates. RESULTS Tobacco abuse accounted for 14.5% of all deaths and 23.2% of deaths tied to known risk factors, with an age-standardized death rate of 110.8 per 100,000. Cardiovascular diseases were the primary cause of smoking-related deaths and DALYs, representing 53.4% of all deaths and 50.3% of all DALYs. This was followed by neoplasms (24.6% of all deaths and 20.3% of all DALYs), chronic respiratory diseases(12.4% of all deaths and 11.9% of all DALYs), and respiratory infections and tuberculosis(4% of all deaths and 3.4% of all DALYs). Second-hand smoking caused 20.5% of tobacco-related deaths and 21.5% of tobacco-related DALYs, disproportionately affecting younger individuals. An increasing disease burden was observed in Lebanon, Turkey, Syria, Tunisia, UAE, and Libya, and declining rates were most evident in Oman and Qatar. CONCLUSION Our study emphasizes the impact of smoking on cardiovascular disease, the primary cause of smoking-related mortality and morbidity in the MENA region. Our findings highlight the urgent need for effective tobacco control policies and interventions.
Migrating attributes tied to the EPA river reache file to the national hydrography dataset

In cooperation with several federal and state agencies, the Information Center for the Environment (ICE) at the University of California Davis is analyzing the ability to cross-reference information linked to California's hydrography dataset (a modified form of the U.S. Environmental Protection Agency's River Reach File) to the new National Hydrography Dataset. California's Reach File contains a critical but non-standard foreign key that is essential to many research applications. Additionally, ICE plans to test, verify, and recommend enhancements to cross-referencing methods to improve the transfer of reach-code information from earlier hydrography datasets in California to the NHD.
Associations of prenatal one-carbon metabolism nutrients and metals with epigenetic aging biomarkers at birth and in childhood in a US cohort

Epigenetic gestational age acceleration (EGAA) at birth and epigenetic age acceleration (EAA) in childhood may be biomarkers of the intrauterine environment. We investigated the extent to which first-trimester folate, B12, 5 essential, and 7 non-essential metals in maternal circulation are associated with EGAA and EAA in early life. Bohlin EGAA and Horvath pan-tissue and skin and blood EAA were calculated using DNA methylation measured in cord blood (N=351) and mid-childhood blood (N=326; median age = 7.7 years) in the Project Viva pre-birth cohort. A one standard deviation increase in individual essential metals (copper, manganese, and zinc) was associated with 0.94-1.2 weeks lower Horvath EAA at birth, and patterns of exposures identified by exploratory factor analysis suggested that a common source of essential metals was associated with Horvath EAA. We also observed evidence nonlinear associations of zinc with Bohlin EGAA, magnesium and lead with Horvath EAA, and cesium with skin and blood EAA at birth. Overall, associations at birth did not persist in mid-childhood; however, arsenic was associated with greater EAA at birth and in childhood. Prenatal metals, including essential metals and arsenic, are associated with epigenetic aging in early life, which might be associated with future health.
Early Visual Cortices Reveal Interrelated Item and Category Representations in Aging

Neural dedifferentiation, the finding that neural representations tend to be less distinct in older adults compared with younger adults, has been associated with age-related declines in memory performance. Most studies assessing the relation between memory and neural dedifferentiation have evaluated how age impacts the distinctiveness of neural representations for different visual categories (e.g., scenes and objects). However, how age impacts the quality of neural representations at the level of individual items is still an open question. Here, we present data from an age-comparative fMRI study that aimed to understand how the distinctiveness of neural representations for individual stimuli differs between younger and older adults and relates to memory outcomes. Pattern similarity searchlight analyses yielded indicators of neural dedifferentiation at the level of individual items as well as at the category level in posterior occipital cortices. We asked whether age differences in neural distinctiveness at each representational level were associated with inter- and/or intraindividual variability in memory performance. While age-related dedifferentiation at both the item and category level related to between-person differences in memory, neural distinctiveness at the category level also tracked within-person variability in memory performance. Concurrently, neural distinctiveness at the item level was strongly associated with neural distinctiveness at the category level both within and across participants, elucidating a potential representational mechanism linking item- and category-level distinctiveness. In sum, we provide evidence that age-related neural dedifferentiation co-exists across multiple representational levels and is related to memory performance.