Miracle-dz/UniFAR-FTUs huggingface dataset:
Ensemble dressing for hydrological applications

This manuscript presents a simple yet effective method to account for uncertainty in hydrologic ensemble forecasting applications. Most operational hydrological ensemble forecasting systems only account for uncertainty in future climate (e.g. precipitation) forcings, ignoring other sources of uncertainty (e.g. model error). The result can be under‐dispersive and overconfident forecasts. Ensemble dressing is a form of statistical post‐processing to include information about the uncertainty of individual ensemble members. First, the historical simulations can be corrected to remove systematic biases. Next, the simulated and observed flow data are transformed to ensure that model residuals can be fitted to a distribution (e.g. normal); this study uses a 2‐parameter log‐sinh transformation. Model residuals in transformed space determine the width of the error distribution. Ensemble forecasts are then generated and transformed. Each ensemble is dressed with the error distribution, the results are untransformed, and finally, a probabilistic forecast is derived from the collective distribution of the dressed ensembles. The method is applied to 128 catchments in southeast Australia, demonstrating that the raw ensemble can be made reliable through the use of this dressing method. Copyright © 2012 John Wiley & Sons, Ltd.
Facilitating Active Collaborative Learning in Medical Education; a Literature Review of Peer Instruction Method

Abstract The call for educational reform by the Carnegie Foundation for the Advancement of Teaching marked a pivotal juncture in the trajectory of medical education in the United States. The call underscored the imperative for educational restructuring to equip forthcoming physicians with the requisite skills to engage in lifelong learning. Among the several active teaching methods is the Peer Instruction (PI), a brainchild of Eric Mazur, empowering students to steer their own education and wield knowledge adeptly into real-world scenarios. In this review paper, we delve into the core elements of PI which involves the combination of four dynamic pedagogical approaches which are: Just-in-Time Teaching, ConcepTest, Audience Response System, and Think-Pair-Share technique. PIs effectiveness notwithstanding, it is not exempt from limitations such as its flexible implementation, lengthy time, the level of expertise required for instructional design, among others. While Peer Instruction has become increasingly popular among educators across other disciplines, with proven educational benefits with positive outcomes, PIs footprint in gradate and postgraduate medical education remains inchoate, evidenced by a paucity of scholarly references. This underscores a crucial gap - despite its proven potency in fueling engagement and learning, PI still lacks formal recognition and acknowledgement as a distinct instructional method in medical education. Within these boundaries, the promise of heightened education and amplified engagement beckons further exploration of PI as a medical educational model, warranting more consideration and research.
Multimodal deep learning for chronic kidney disease prediction: leveraging feature selection algorithms and ensemble models

ABSTRACT This research presents an advanced approach to enhance disease diagnosis using imbalanced medical datasets. Feature selection techniques, LASSO and Relief, are applied to identify relevant features from the UCI dataset and missing values are handled appropriately. To address the class imbalance, SMOTEENN is used, creating a new combined dataset with selected features. Three deep learning models, FNNs, LSTMs, and GBMs, are employed and trained on the combined dataset, achieving remarkable accuracy (1.0). Evaluating the models on LASSO and Relief datasets independently, FNN/MLP obtains perfect accuracy, GBM performs well (0.9888 on LASSO and 1.0 on Relief), and LSTM shows good results (0.9663 on LASSO and 1.0 on Relief). This study demonstrates the effectiveness of combining LASSO and Relief for feature selection and highlights the impact of SMOTEENN on model performance. The achieved accuracy with all models on the combined dataset showcases deep learning's potential for accurate disease diagnosis even with imbalanced data, offering promising insights for robust medical diagnosis systems.
On the nonseasonal variations in sea level along the west coast of North America

Spectra of monthly sea level anomalies are investigated for the frequency range between 0 and 6 cycles per year. It is found that most of the power is concentrated at low frequencies. There is a good coherence between anomalies of sea level and atmospheric pressure at almost all frequencies, indicating a fast response between these variables. The coherence between anomalies of sea level and sea surface temperature is moderate to poor depending upon the particular environment of the tide gage station. There is some coherence between anomalies of sea level and the south component of the geostrophic wind, owing to the influence of the Coriolis force. In river mouths the anomalies in sea level largely reflect the anomalies in river discharge. A fairly successful estimate of the sea level anomaly of the present month can be made from the present anomalies of atmospheric pressure and sea surface temperature. Statistical prediction of sea level anomalies is less successful.
Planificar un currículum o un programa formativo

Un curriculum o un programa de formacion, sea cual sea la etapa del continuum de la educacion medica en la que se inscriba, no es simplemente el contenido del mismo o el listado de las materias y asignaturas que lo componen, o sus cargas lectivas y su ordenacion por periodos lectivos ni la simple norma que pueda aparecer en un documento oficial. Actualmente, el concepto de curriculum incluye otros muchos aspectos que han de tenerse en cuenta en su planificacion. Asi, habra de considerarse las estrategias educativas a utilizar , los contenidos, los objetivos del programa y los resultados del aprendizaje, las experiencias educativas, el entorno educativo, la evaluacion, los estilos y ritmos de aprendizaje y la programacion de tareas. Este articulo es una introduccion a los principios basicos de la planificacion curricular, ofreciendo una vision general de las principales etapas a seguir en dicho proceso, en el bien entendido de que cada una de ellas requiere un mayor desarrollo y profundidad.
A Low-Power 256-Element Ka-Band CMOS Phased-Array Receiver With On-Chip Distributed Radiation Sensors for Small Satellite Constellations

This article presents a low-power 256-element $Ka$ -band CMOS phased-array receiver utilizing ON-chip distributed radiation sensors for the low Earth orbit (LEO) small satellite communication system. Since the available solar cell area limits the power generation of the small LEO satellites, a distributed current-sharing common-gate (CG) low noise amplifier (LNA) and a voltage-tuning variable gain amplifier (VGA) are introduced to reduce power consumption. After utilizing the proposed technique, the power consumption of the beamformer is 2.95 mW/element. Moreover, the proposed voltage-tuning VGA is configured to utilize both upper and lower transistors for gain contributions to save power. The ON-chip distributed radiation sensors are presented to eliminate the non-uniform radiation influence and realize 0.22-dB/Mrad gain degradation performance. The proposed receiver achieves −20-dBm single-element IIP3 with a 3.6-dB noise figure. The occupied ON-chip area for a single element is only 0.24 mm2. DVB-S2X standard modulated signals of up to 256 amplitude and phase-shift keying (APSK) can be supported in the over-the-air (OTA) measurement. The receiver achieves −31.3-dB EVM and 24-Gb/s link speed under 1.5-GBaud dual-linear polarization signals. The measured 256-element beam pattern can cover radiated angle from −50° to +50° with lower than −9-dBc sidelobe level. Thanks to the proposed low-power distributed current-sharing CG LNA and ON-chip radiation sensors, a low-power radiation-hardened phased-array receiver can be achieved for the small LEO satellites.
Late Quaternary evolution of Lake Urana, New South Wales, Australia

Lake Urana is a well-preserved relict lake in the semi-arid Riverine Plain of southeastern Australia. A compound lunette at its eastern shoreline consists of a quartz-sand-dominated unit (Bimbadeen Formation), thermoluminescence (TL) dated at 30 ka to 12 ka, and a clay and sand facies unit (Coonong Formation), dated at 55 ka to 35 ka. The intervening period indicates a phase of periodically exposed lake floor and soil formation. The older wet phase conforms well with similar environments recorded from the same period at Lake Mungo. However, the return to high water levels from 30 ka to 12 ka departs sharply from the generally accepted palaeoclimatic model from Australia, which demands severe glacial maximum desiccation and widespread construction of clay lunettes. Although hydrological budgets calculated for Lake Urana and nearby Lake Cullivel require high glacial maximum water levels they do not support higher precipitation.
Some Paleopathological Cases from a Medieval Necropolis of Drustar (Silistra), Bulgaria (Investigation of the Postcranial Skeletons)

Drustar was a medieval town in Northeastern Bulgaria. It was the most important fortress in the Lower Danube. The bone material was excavated from a necropolis situated near to the north wall of the fortress. The burials were dated in 9th – 15th century AD. The study included postcranial skeletons of 147 individuals (42 children and 105 adults). There were observed traces of pathological changes in the different bones of the postcranial skeleton, such as fractures, osteoarthritis, spina bifida, etc. The degenerative disorders of the joints were most often occurred. The results obtained suggest that living conditions were not very favourable for the medieval population of Drustar. DOI: 10.5901/mjss.2013. v4n11p603
Modelling and simulation of virtual Mars scene

There is a limited cognition on human beings comprehend the universe. Aiming at the impending need of mars exploration in the near future, starting from the mars three-dimensional (3D) model, the mars texture which based on several reality pictures was drew and the Bump mapping technique was managed to enhance the realistic rendering. In order to improve the simulation fidelity, the composing of mars atmospheric was discussed and the reason caused atmospheric scattering was investigated, the scattering algorithm was studied and calculated as well. The reasons why "Red storm" that frequently appeared on mars were particularized, these factors inevitable brought on another celestial body appearance. To conquer this problem, two methods which depended on different position of view point (universe point and terrestrial point) were proposed: in previous way, the 3D model was divided into different meshes to simulate the storm effect and the formula algorithm that mesh could rotate with any axis was educed. From a certain extent the model guaranteed rendering result when looked at the mars (with "Red storm") in universe; in latter way, 3D mars terrain scene was build up according to the mars pictures downloaded on "Google Mars", particle system used to simulated the storm effect, then the Billboard technique was managed to finish the color emendation and rendering compensation. At the end, the star field simulation based on multiple texture blending was given. The result of experiment showed that these methods had not only given a substantial increase in fidelity, but also guaranteed real-time rendering. It can be widely used in simulation of space battlefield and exploration tasks.
Relationship between maternal and infant serum vitamin D levels in Jos, Plateau State, Nigeria: a cross-sectional study

Introduction there is growing interest in the link between maternal and infant vitamin D (VD) levels. Breast milk transmission and the fact that the mother and her child may share risk factors for VD, such as exposure to sunlight, diet, and sociocultural influences may impact VD status, the magnitude of which is largely unknown in our topical low-middle income setting. We assessed the connection between maternal and infant VD status including their correlates. Methods this cross-sectional study investigated 95 maternal-infant pairs in Jos. Mothers were interviewed using a questionnaire. Blood sampling and analysis of serum total 25 hydroxy VD were performed using the chemiluminescent immunoassay method. Maternal and infant VD levels were classified as VD deficient (VDD), VD insufficient (VDI), and VD sufficient (VDS). The mean maternal and infant VD were compared, and the Spearman correlation between them was assessed, a stepwise linear regression was also performed with infant vitamin D as a dependent variable. For all statistical analysis, p<0.05 was considered significant. Results the median maternal and infant VD was 29.68 ng/ml and 29.41 ng/ml, respectively. The mean infant VD (32.19 ± 10.61 ng/ml) was comparable to maternal VD (31.12 ± 12.94 ng/ml) (p=0.483), with a Spearman correlation coefficient of 0.3 (p=0.037). Maternal vitamin D (beta=0.539, duration of exclusive breastfeeding (beta=-3.490), and infant age (beta=1.655) were found to be significant independent predictors of infant vitamin. Conclusion beyond neonatal age, a significant positive relationship between maternal and infants´ VD levels exists and suggests that family-focused vitamin D intervention might be an effective public health approach in the tropical city of Jos.
A Calculation of Ocean Heat Storage and Effective Ocean Surface Layer Depths for the Northern Hemisphere

Abstract In the hierarchy of simple ocean formulations available for coupling to atmospheric GCMs, a scheme whereby ocean surface-layer depths vary geographically and seasonally is deemed better than a fixed depth layer at all locations and seasons, but still is less sophisticated than dynamic ocean models. Yet such simple ocean formulations are useful for basic sensitivity studies. Here, a calculation of varying surface layer depths is done by first performing an ocean heat storage calculation using gridded, long-term mean mixed-layer depths and sea surface temperatures with a parameterized temperature structure beneath the mixed layer derived from weather ship data. Heat storage values in the midlatitudes are larger in the Atlantic than in the Pacific, which is in qualitative agreement with the weather ship data. Variants of the basic calculation show that neither mixed layer data nor SST data alone are sufficient to compute heat storage adequately. Using the results from the parameterized heat storage .
The Use of Artificial Intelligence to Promote Autonomous Pronunciation Learning: Segmental and Suprasegmental Features Perspective

The study aimed at investigating the effects of autonomous pronunciation learning using AI as well as the experiences of autonomous pronunciation learning using AI by higher level students. Explanatory sequential mixed-method research using both quantitative and qualitative methods was employed within thirty-two students from Universitas PGRI Semarang's first-year students serving as the sample. Assessments, interviews, and an evaluation of instructional materials were used as the instruments. Through pre- and post-testing, quantitative analysis was used to evaluate the students’ pronunciation proficiency. Quantitative data analysis was done using SPSS. However, a qualitative analysis was used to review the interview. To bolster the findings of the tests, it was descriptively examined. After the treatments using an AI based application named ELSA, there was a significant correlation between the use of AI and autonomous pronunciation learning. However, ELSA has certain shortcomings. It appears to be primarily concerned with segmental than suprasegmental features. Only intonation is available from among all the features offered to practice suprasegmental features. While students found it difficult to emphasize words, there is no other practice for suprasegmental qualities. In reality, the ELSA website states that its curriculum covers core English skills such as word stress, intonation, rhythm, listening, and conversation. As a result, the ELSA creator may take this criticism into consideration as they continue to improve their product. It implies that the creator is responsive to the concerns or suggestions of their customers or users, which can contribute to the ongoing development and success of the product.
A Survey of EEG and Machine Learning-Based Methods for Neural Rehabilitation

One approach to therapy and training for the restoration of damaged muscles and motor systems is rehabilitation. EEG-assisted Brain-Computer Interface (BCI) may assist in restoring or enhancing ‘lost motor abilities in the brain. Assisted by brain activity, BCI offers simple-to-use technology aids and robotic prosthetics. This systematic literature review aims to explore the latest developments in BCI and motor control for rehabilitation. Additionally, we have explored typical EEG apparatuses that are available for BCI-driven rehabilitative purposes. Furthermore, a comparison of significant studies in rehabilitation assessment using machine learning techniques has been summarized. The results of this study may influence policymakers’ decisions regarding the use of EEG equipment, particularly wireless devices, to implement BCI technology. Moreover, the literature review results offer suggestions for further study and new research areas. We plan to identify the additional characteristics of each EEG equipment and determine which one is most suited for each industry by measuring the user experience based on various devices in future research.
A single layered broadband circularly polarized MIMO antenna based on metasurface with aperture CPW feed

ABSTRACT In this paper, a single-layered broadband circularly polarized MIMO antenna is presented for a 5 GHz wireless local area network (WLAN). The Metasurface is designed with an array of patches and these patches are excited by four uniform aperture CPW feed MIMO antennas. The stubs are added across the aperture and central patches at respective apertures are increased to achieve broad bandwidth. Truncated corner square patches are used for the metasurface to achieve circular polarization (CP). The CP MIMO antenna has achieved an impedance bandwidth of 33% (4.35 GHz-6.08 GHz), a 3 dB axial ratio (AR) bandwidth of 11.95% (5.18 GHz-5.8 GHz) and a gain of 8dBi.
RRS Discovery Cruise 248, 07 Jul-10 Aug 2000. A multidisciplinary study of the environment and ecology of deep-water coral ecosystems and associated seabed facies and features (The Darwin Mounds, Porcupine Bank and Porcupine Seabight)

RRS Discovery Cruise 248 aimed to carry out a multidisciplinary study of the environment and ecology of deep-water coral ecosystems and associated seabed features in the northeast Atlantic. The study was primarily focused on the Darwin Mounds area, northern Rockall Trough (59° 49’N, 07° 22’W), but also examined a number of sites in the Porcupine Seabight area. The cruise was divided into two legs (Govan-Stornoway, 8 Jul-21 Jul 2000; Stornoway-Southampton, 22 Jul-10 Aug 2000). Leg 1 focused on the ecology of the Darwin Mounds area, with seabed photographic surveys (SOC SHRIMP system), coring (Box and Multiple cores) and trawling (Agassiz) forming the main activities. Leg 2 began with detailed geological investigations of the Darwin Mounds area, concentrating on piston coring and sidescan sonar surveys. Leg 2 concluded with combined ecological and geological studies of carbonate mound sites on the Porcupine Bank and in the Porcupine Seabight. Observations in the Darwin Mounds area confirmed the common occurrence of deep-water corals on these Mounds. The mounds themselves do not appear to be carbonate formations but may be better characterised as sand volcanoes. Numerous xenophyophores were observed in association with the mounds; however, no live specimens were recovered in any of the samples collected. Sidescan sonar images and seabed photography both suggested that the Darwin Mounds area had been subject to considerable commercial trawling with resultant apparent damage to the deep-water coral ecosystems. The various operations undertaken in the Porcupine Seabight area were also successful in imaging giant carbonate mounds and their associated coral communities with both sidescan sonar and seabed photography, and in recovering biological sample material from these areas. In common with the Darwin Mounds area, the observations made suggested that deep-water fishing impacts on coral ecosystems were also evident in this region.
Mechanisms and Application of Gas-Based Anticancer Therapies

Cancer is still one of the major factors threatening public health, with morbidity and mortality rates at the forefront of the world. Clinical drawbacks, such as high toxicity and side effects of drug therapy, and easy recurrence after surgery affect its therapeutic effect. Gas signaling molecules are essential in maintaining biological homeostasis and physiological functions as specific chemical substances for biological information transfer. In recent years, the physiological regulatory functions of gas molecules in the cancer process have been gradually revealed and have shown broad application prospects in tumor therapy. In this paper, standard gas therapies are classified and introduced. Taking H2, CO2, NO, CO, H2S, and SO2 gases as examples, the research progress and application of gas therapies in malignant tumors are mainly introduced in terms of biological characteristics, anticancer mechanisms, and treatment strategies. Finally, the problems and prospects for developing gases as anticancer drugs are outlined.
An Integrated Approach to Optimal Merging Sequence Generation and Trajectory Planning of Connected Automated Vehicles for Freeway On-Ramp Merging Sections

Intensive interactions among vehicles at freeway on-ramp merging areas lead to congestion and accidents. The emergence of connected automated vehicles (CAVs) has shown great potential to improve this issue. In this paper, a mixed integer nonlinear programming (MINLP) model is proposed and solved for the task of a cooperative merging of two traffic streams at a freeway on-ramp merging section. The proposed model simultaneously optimizes multiple vehicles’ trajectories and their merging sequence to improve traffic efficiency and ensure safety. Unlike conventional treatments, which match one mainline facilitating vehicle with one merging vehicle, the proposed model determines the optimal number of facilitating vehicles and which mainline vehicles should serve as the facilitating vehicles to cooperatively minimize disruption from ramps. The safety and feasibility of the planned vehicle trajectories are guaranteed at any time. We propose an integrated solution algorithm that incorporates an iterative linear programming method into a novel search process based on a necessary condition for optimality that we identify and prove. The algorithm is highly efficient because it enjoys a significantly reduced search space. The proposed approach, consisting of the MINLP model and the solution algorithm, is evaluated under different traffic demands and mainline-ramp demand ratios and real vehicle arrival patterns from the NGSIM dataset. The performance of the proposed method outperforms benchmark CAV control algorithms, and the computational efficiency is promising for real-time automated merging tasks.