Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance analysis of optimization algorithms for convolutional neural network-based handwritten digit recognition

Handwritten digit recognition has been widely researched by the recognition society during the last decades. Deep convolutional neural networks (CNN) have been exploited to propose efficient handwritten digit recognition approaches. However, the CNN model may need an optimization algorithm to achieve satisfactory performance. In this work, a performance evaluation of seven optimization methods applied in a straightforward CNN architecture is presented. The inspected algorithms are stochastic gradient descent (SGD), adaptive gradient (AdaGrad), adaptive delta (AdaDelta), adaptive moment estimation (ADAM), maximum adaptive moment estimation (AdaMax), nesterov-accelerated adaptive moment estimation (Nadam), and root mean square propagation (RMSprop). Experimental results carried out on MNIST and EMNIST digit datasets have shown the superior performance of RMSprop and Adam algorithms over the peer methods, respectively.
Three‐dimensional VP and VP/VS structure of the upper crust in the Erzincan basin (eastern Turkey)

[1] Using aftershocks of the 13 March 1992 Erzincan earthquake (Ms = 6.8) three dimensional VP and VP/VS velocity structure of the Erzincan basin and its surroundings were modeled by local earthquake tomography. Travel times of body waves, belonging to 1025 selected high-quality events recorded by 58 temporary stations, were inverted iteratively and simultaneously by using the SIMUL2000 algorithm. Synthetic and resolution tests were performed to analyze the sensitivity of tomographic results and model parameterization. The resulting 3-D VP and VP/VS tomographic images show velocity anomalies related to geologic and tectonic structures beneath the Erzincan basin. While low VP anomalies down to 2–3 km depths are associated to thick Neogene sediments deposited in the Erzincan basin, high VP anomalies indicate bed rocks and intrusive magmatic rocks beneath the mountain ranges. VP/VS anomalies are an important indicator of local tectonic structures, and the physical, mechanical, and compositional variations in the rocks. The low VP/VS anomalies (≤1.7) observed at shallow depths (0–4 km) track the main fault systems and thus the weakness zones in the basin. The high VP/VS anomalies (≥1.9) located between 4 and 6 km depth in the southeast of the Erzincan basin may correspond to fluid saturation, high pore pressure, and carbonate content in the rock matrix. The high VP/VS ratios play an important role for increasing seismicity in this area because of the fluid saturation and the high pore pressure. Finally, on the basis of the 3-D tomographic images, basement of the Erzincan basin deepens down to about 10 km depth and possesses an irregular and asymmetric shape. The thick and unconsolidated sedimentary layer increases seismic risk to Erzincan and other cities located on the basin as it magnifies ground motion caused by large earthquakes.
Construction of a Viscoelastic Model of Human Cancellous Bone in Alveolar Bone Based on Bone Mineral Density Distribution

Orthodontic treatment was accompanied by the remodeling of cancellous bone in alveolar bone (CBAB), which manifested as the increase or decrease in bone mineral density (BMD). BMD is closely related to the mechanical properties of the alveolar bone. Therefore, the aim of this study was to quantify the effect of BMD on its viscoelastic behavior and to assess orthodontic forces at different BMDs. A total of nine CBAB samples were cut from the cervical, middle, and apical regions of the right mandible between canine, premolars, and molars. After scanning with micro-computed tomography (micro-CT). The BMD of samples was measured and dynamic mechanical analysis (DMA) was performed. Based on the fourth-order generalized Maxwell model, a viscoelastic constitutive model characterizing the BMD variation was constructed. The BMD exhibited variations within different regions of the CBAB. The storage modulus is positively correlated with BMD, and the loss modulus is negatively correlated with BMD.
Population and Demographic Trends of Ferruginous Pygmy-owls in Northern

3 INTRODUCTION . 4 STUDY AREA . 5 METHODS . 5 DESIGN. 5 Trends in abundance. 5 Trends in territory occupancy and demographic parameters . 6 OWL SURVEYS . 6 ENVIRONMENTAL MEASUREMENTS . 7 ANALYSES. 8 Parameter estimation . 8 Modeling . 8 RESULTS . 9 ABUNDANCE . 9 Effort and detections . 9 Trends in abundance. 9 OCCUPANCY . 10 Effort and detections . 10 Trends in occupancy. 10 DEMOGRAPHIC PARAMETERS. 10 Effort and detections . 10 Trends in demographic parameters . 11 RAINFALL . 11 Historical trends . 11 Pygmy-owls and rainfall . 11 DISCUSSION. 12 TRENDS IN ABUNDANCE AND OCCUPANCY. 12 TRENDS IN DEMOGRAPHIC PARAMETERS. 14 RAINFALL . 14 RECOVERY IMPLICATIONS. 15 ACKNOWLEDGEMENTS. 16 LITERATURE CITED . 18
Holocene climate variability in tropical South America : case history from a high-mountain wet zone in NW Colombia based on palynology and X-ray microfluorescence

Sediments deposited in a high-altitude wet zone of the NW Andes of Colombia have been studied in order to reconstruct climatic variations in the tropics during the Holocene (the last 11'500 years). Sediments were studied by palynology and X-ray microfluorescence which can be used as proxies for temperature and rainfall and have a decadal to yearly time resolution. Results demonstrate that the Holocene record in NW Colombia is marked by rapid and very significant changes in temperature and precipitations. Temperatures may have varied (up or down) of a few degrees centigrade over less than a century. Rainfall data and regional comparisons show that the climate mechanisms that have influenced NW Colombia during the Holocene are both Pacific and Atlantic-driven. Rainfall proxies show the influence of both the El Nino Southern Oscillation (ENSO) in the Pacific and the Inter Tropical Convergence Zone (ITCZ) in the Atlantic.
Alginate encapsulation for bupivacaine delivery and mesenchymal stromal cell immunomodulatory cotherapy

Purpose Mesenchymal stromal cells (MSCs) are used to treat various inflammatory conditions. In parallel, to mitigate pain associated with inflammation, analgesics or opioids are prescribed, often with significant side effects. Local anesthetics (LAs) offer a promising alternative to these medications. However, their short duration and negative effects on anti-inflammatory MSCs have limited their therapeutic effectiveness. To mitigate these negative effects and to move toward developing a cotherapy, we engineered a sustained release bupivacaine alginate-liposomal construct that enables up to 4 days of LA release. By encapsulating MSC in alginate (eMSC), we demonstrate that we can further increase drug concentration to clinically relevant levels, without compromising eMSC viability or anti-inflammatory function. Materials and methods MSCs were freely cultured or encapsulated in alginate microspheres ± TNFα/IFN-γ and were left untreated or dosed with bolus, liposomal, or construct bupivacaine. After 24, 48, and 96 hours, the profiles were assessed to quantify secretory function associated with LA–MSC interactions. To approximate LA exposure over time, a MATLAB model was generated. Results eMSCs secrete similar levels of IL-6 and prostaglandin E2 (PGE2) regardless of LA modality, whereas free MSCs secrete larger amounts of IL-6 and lower amounts of anti-inflammatory PGE2. Modeling the system indicated that higher doses of LA can be used in conjunction with eMSC while retaining eMSC viability and function. In general, eMSC treated with higher doses of LA secreted similar or higher levels of immunomodulatory cytokines. Conclusion eMSCs, but not free MSC, are protected from LA, regardless of LA modality. Increasing the LA concentration may promote longer and stronger pain mitigation while the protected eMSCs secrete similar, if not higher, immunomodulatory cytokine levels. Therefore, we have developed an approach, using eMSC and the LA construct that can potentially be used to reduce pain as well as improve MSC anti-inflammatory function.
Evaluating the potential of multi-temporal Sentinel-1 and Sentinel-2 data for regional mapping of olive trees

ABSTRACT Olives are a crucial economic crop in Mediterranean countries. Detailed spatial information on the distribution and condition of crops at regional and national scales is essential to ensure the continuity of crop quality and yield efficiency. However, most earlier studies on olive tree mapping focused mainly on small parcels using single-sensor, very high resolution (VHR) data, which is time-consuming, expensive and cannot feasibly be scaled up to a larger area. Therefore, we evaluated the performance of Sentinel-1 and Sentinel-2 data fusion for the regional mapping of olive trees for the first time, using the Izmir Province of Türkiye, an ancient olive-growing region, as a case study. Three different monthly composite images reflecting the different phenological stages of olive trees were selected to separate olive trees from other land cover types. Seven land-cover classes, including olives, were mapped separately using a random forest classifier for each year between 2017 and 2021. The results were assessed using the k-fold cross-validation method, and the final olive tree map of Izmir was produced by combining the olive tree distribution over two consecutive years. District-level areas covered by olive trees were calculated and validated using official statistics from the Turkish Statistical Institute (TUIK). The K-fold cross-validation accuracy varied from 94% to 95% between 2017 and 2021, and the final olive map achieved 98% overall accuracy with 93% producer accuracy for the olive class. The district-level olive area was strongly related to the TUIK statistics (R2 = 0.60, NRMSE = 0.64). This study used Sentinel data and Google Earth Engine (GEE) to produce a regional-scale olive distribution map that can be scaled up to the entire country and replicated elsewhere. This map can, therefore, be used as a foundation for other scientific studies on olive trees, particularly for the development of effective management practices.
SATELLITE MONITORING OF HYDROLOGIC TRANSFORMATIONS IN SOUTHERN EGYPT

Human actions are altering the hydrologic regimes of many regions. Where these transformations are occurring over broad spatial scales, satellite remote sensing may provide the only effective means to monitor their extent and impacts. Over the past decade, two processes (irrigation, and the overflow from high water levels on the Lake Nasser reservoir) have introduced large quantities of water into the previously hyper-arid Toshka region of southern Egypt. We have developed an automated, satellite-based system for monitoring the expansion and contraction of a series of vast new lakes that formed as a result of floodwater diversion beginning in September 1998. Analysis of 166 satellite images shows that the surface area of the six lakes rose to 1740 km 2
The role of format familiarity and word frequency in Chinese reading

For Chinese readers, reading from left to right is the norm, while reading from right to left is unfamiliar. This study comprises two experiments investigating how format familiarity and word frequency affect reading by Chinese people. Experiment 1 examines the roles of format familiarity (reading from left to right is the familiar Chinese format, and reading from right to left is the unfamiliar Chinese format) and word frequency in vocabulary recognition. Forty students read the same Chinese sentences from left to right and from right to left. Target words were divided into high and low frequency words. In Experiment 2, participants engaged in right-to-left reading training for 10 days to test whether their right-to-left reading performance could be improved. The study yields several main findings. First, format familiarity affects vocabulary recognition. Participants reading from left to right had shorter fixation times, higher skipping rates, and viewing positions closer to word center. Second, word frequency affects vocabulary recognition in Chinese reading. Third, right-to-left reading training could improve reading performance. In the early indexes, the interaction effect of format familiarity and word frequency was significant. There was also a significant word-frequency effect from left to right but not from right to left. Therefore, word segmentation and vocabulary recognition may be sequential in Chinese reading.
sub-arc mantle of Kohistan (Pakistan) Geological evidence and modeling of melt migration by porosity waves in the

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Technology Adaptation and CEO Characteristics: Enhancing Competitive Advantage in Indonesia’s MSME of F&B in the Jabodetabek Region

The food and beverage (F&B) industry significantly impacts Indonesia's economy, playing a crucial role in economic growth and welfare. Micro, small, and medium-sized enterprises (MSMEs) in the F&B sector, particularly in the Jabodetabek region, are essential contributors to Indonesia's global standing. This study explores the relationship between technology adaptation, CEO characteristics, and competitive advantage in Jabodetabek's F&B MSMEs. Challenges faced by these enterprises, such as limited resources and human capital, underscore the need for effective technology adoption and strong leadership. The research aims to enrich the literature on this subject and provide insights for policymakers to enhance MSME competitiveness.
Temporal and spatial variability in sea-ice carbon:nitrogen ratios on Canadian Arctic shelves

To enhance the accuracy of carbon cycling models as applied to sea ice in the changing Arctic, we analyzed a large data set of particulate organic carbon (POC) and nitrogen (PON) measurements in first-year bottom sea ice (n = 257) from two Arctic shelves, the Canadian Arctic Archipelago and Beaufort Sea shelf, including dark winter and spring seasonal measurements. Wide ranges of sea-ice POC:PON ratios were observed during both the dark winter (12–46 mol:mol) and spring (3–24 mol:mol) periods. Sea-ice POC:PON ratios and chlorophyll a concentrations were significantly higher in the Archipelago versus the Beaufort Sea shelf (p < 0.01), yet there was a highly significant relationship between sea-ice POC and PON during spring for both shelves (r2 = 0.94). POC:PON ratios were not consistent over the range of measured POC and PON concentrations, justifying the use of a power function model to best describe the relationship between POC and PON. Distinct relationships between POC:PON ratios and chlorophyll-based biomass were observed for the dark winter and the spring: dark winter sea-ice POC:PON ratios decreased with increasing sea-ice biomass whereas spring POC:PON ratios increased with increasing sea-ice biomass. The transition from the dark period to the spring growth period in first-year sea ice represented a distinct stoichiometric shift in POC:PON ratios. Our results demonstrate that the Redfield ratio has limited applicability over the four-order of magnitude range of biomass concentrations observed in first-year sea ice on Arctic shelves. This study emphasizes the need for variable POC:PON stoichiometry in sea-ice biogeochemical models and budget estimates, in particular at high biomass concentrations and when considering seasonality outside of the spring period in first year ice. The use of a power function model for POC:PON relationships in sea ice is also recommended to better constrain carbon estimates in biogeochemical sea-ice models.
Attention-Based Methods for Emotion Categorization From Partially Covered Faces

Emotions are considered to convey much meaning in communication. Hence, artificial methods for emotion categorization are being developed to meet the increasing demand to introduce intelligent systems, such as robots, into shared workspaces. Deep learning algorithms have demonstrated limited competency in categorizing images from posed datasets with the main features of the face being visible. However, the use of sunglasses and face masks are common in our daily lives, especially with the outbreak of communicable diseases such as the recent coronavirus. Anecdotally, partial coverings of the face reduce the effectiveness of human communication, so would this have hampering effects on computer vision, and if so, would different emotion categories be affected equally? Here, we analyze the performance of emotion classification systems when faces are partially covered with simulated sunglasses and face masks. Deep neural networks consider all pixels in an image as equally important unlike the neuroscientific findings on how humans recognize emotions. Hence, we propose a method that considers different constituent parts (e.g. mouth, eyes, and jaw) separately, giving more attention to relevant (uncovered) regions of the face. The method is compared with three standard, partial coverings-based and attention-based methods. We found that face coverings worsen emotion categorization by up to 74% for the state-of-the-art methods, whereby emotion categories are affected differently by different coverings, e.g. clear mouth coverings have little effect on categorizing happiness, but sadness is affected badly. The proposed method (on average 60.43%) has significantly improved the performance over the standard deep learning ($< $ 46% on average), partial coverings-based ($< $ 47% on average), as well as the attention-based ($< $ 51% on average) methods for both the CK+, KDEF, and RAF-DB datasets when faces were partially covered with sunglasses or different face masks.
Complexities of Authentic Assessment Implementation in English Learning at Rural Areas-Based High Schools

This research aimed to examine the level of the implementation of authentic assessment by high school English teachers in a rural area of Siak district, Riau Province, Indonesia, and to explore their perception regarding authentic assessment. This research used a mixed method in which both quantitative and qualitative data were collected and analyzed. The research samples were 39 high school English teachers in the Siak region. The research instrument used is a questionnaire comprising 38 closed and three open questions, distributed online via Google Forms. The questionnaire was designed using Likert Scale with options ranging from 1-5 (very poor to very good) Data were also collected using semi-structured interviews to enrich data from the Google Form. This study found that the total average score of quantitative data is 4.1, classified as good. That means the implementation of authentic assessment by English teachers is at a good level. Then from the qualitative data analysis, it appeared that most teachers have a positive perception of authentic assessment as a tool for monitoring and evaluating student learning outcomes. However, there are still some problems faced by the teachers in implementing this assessment, such as the lack of time allotment for the English subject at school and the complexity of the assessment procedures. This implies that some policies are required to make the authentic assessment work well at school levels so teachers can benefit from the assessment for improving English learning at schools.
FRC-GIF: Frame Ranking-Based Personalized Artistic Media Generation Method for Resource Constrained Devices

—Generating video highlights in the form of animated graphics interchange formats (GIFs) has significantly simplified the process of video browsing. Animated GIFs have paved the way for applications concerning streaming platforms and emerging technologies. Existing studies have led to large computational complexity without considering user personalization. This paper proposes lightweight method to attract users and increase views of videos through personalized artistic media, i.e., static thumbnails and animated GIF generation. The proposed method analyzes lightweight thumbnail containers (LTC) using the computational resources of the client device to recognize personalized events from feature-length sports videos. Next, the thumbnails are then ranked through the frame rank pooling method for their selection. Subsequently, the proposed method processes small video segments rather than considering the whole video for generating artistic media. This makes our approach more computationally efficient compared to existing methods that use the entire video data; thus, the proposed method complies with sustainable development goals. Furthermore, the proposed method retrieves and uses thumbnail containers and video segments, which reduces the required transmission bandwidth as well as the amount of locally stored data. Experiments reveal that the computational complexity of our method is 3.73 times lower than that of the state-of-the-art method.
Observation-based gridded runoff estimates for Europe (E-RUNversion 1.1)

Abstract. River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first assemble an unprecedented collection of river flow observations, combining information from three distinct databases. Observed monthly runoff rates are subsequently tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 12) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950–December 2015) on a 0.5° × 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring. The newly derived data are made publicly available at doi:10.1594/PANGAEA.861371 .
Smart Composite Booms for Solar Sails

Composite booms for solar sails have been prototyped by using innovative smart materials. Shape memory polymer composites (SMPCs) have been manufactured by interposing SMP layers between carbon-fiber-reinforced (CFR) plies. A polyimide membrane has been embedded into the CFR-SMPC frame of the sail during lamination. The sail’s size has been limited to 250 × 250 mm2 to allow its testing on Earth. The feasibility of large sail deployments has been shown by prototyping small CFR-SMPC elements to insert only in the folding zones. Numerical simulation by finite element modeling allowed for predicting the presence of wrinkles close to the frame’s vertexes in the cases of large sails under solar radiation pressures. Nevertheless, the frame’s configuration, with SMPC booms at all the edges of the sail membrane, seems to be suitable for drag sails instead of propulsion. On-Earth recovery tests have been performed on 180° folded sails by using flexible heaters. After an initial induction time, the maximum rate was reached with a following drop. In the case of two heaters per folding zone, the angular recovery rate reached the maximum value of about 30 deg/s at the power of 34 W, and full recovery was made in 20 s.