Miracle-dz/UniFAR-FTUs huggingface dataset:
Microplastic ingestion in Sardinella aurita Valenciennes, 1847 and Lithognathus mormyrus (Linnaeus, 1758) along the Gulf of Bejaia, Algeria

This study reports for the first time, the relationship between microplastic ingestion and biological parameters in Sardinella aurita and Lithognathus mormyrus from the Gulf of Bejaia, Algeria. Gastrointestinal tracts content of 144 fishes belonging to two different habitats (pelagic and demersal) were examined for microplastics contamination. Our results showed that 74.30% of individuals ingested microplastics. The most common colour of plastic particles was blue (49% in S. aurita and 30% in L. mormyrus) and the most of microplastics extracted from gastrointestinal tracts of samples were fibers (71.64%). There was no significant relationship between age and Fulton’s factors of both the species and the quantity of microplastics ingested by them. Keywords: Biological parameters, Fish age, Gastrointestinal tracts, Marine pollution, Plastic particles
Equatorial Pacific Ocean Horizontal Velocity, Divergence, and Upwelling*

Abstract Upper-ocean horizontal velocity and divergence were estimated from shipboard observations taken from 1991 to 1999 in the equatorial Pacific between 170°W and 95°W. Mean transports were estimated for the zonal currents at the mean longitude of the sections, 136°W. Mean meridional currents for the entire longitude range included poleward surface flows reaching −0.09 m s−1 in the south and 0.13 m s−1 in the north as well as equatorward flow within the thermocline reaching 0.05 m s−1 in the south and −0.04 m s−1 in the north near 23°C (85 m). Vertical velocity was diagnosed by integrating horizontal divergence estimated for the entire region down from the surface. Equatorial upwelling velocities peaked at 1.9 (±0.9) × 10−5 m s−1 at 50 m. The upwelling transport in the area bounded by 3.6°S–5.2°N, 170°W–95°W was 62 (±18) × 106 m3 s−1 at 50 m. Strong downwelling was apparent within the North Equatorial Countercurrent. An asymmetry in the meridional flows suggested that on the order of 10 × 106 m3 s−1 o.
Peg-in-hole assembly skill imitation learning method based on ProMPs under task geometric representation

Introduction Behavioral Cloning (BC) is a common imitation learning method which utilizes neural networks to approximate the demonstration action samples for task manipulation skill learning. However, in the real world, the demonstration trajectories from human are often sparse and imperfect, which makes it challenging to comprehensively learn directly from the demonstration action samples. Therefore, in this paper, we proposes a streamlined imitation learning method under the terse geometric representation to take good advantage of the demonstration data, and then realize the manipulation skill learning of assembly tasks. Methods We map the demonstration trajectories into the geometric feature space. Then we align the demonstration trajectories by Dynamic Time Warping (DTW) method to get the unified data sequence so we can segment them into several time stages. The Probability Movement Primitives (ProMPs) of the demonstration trajectories are then extracted, so we can generate a lot of task trajectories to be the global strategy action samples for training the neural networks. Notalby, we regard the current state of the assembly task as the via point of the ProMPs model to get the generated trajectories, while the time point of the via point is calculated according to the probability model of the different time stages. And we get the action of the current state according to the target position of the next time state. Finally, we train the neural network to obtain the global assembly strategy by Behavioral Cloning. Results We applied the proposed method to the peg-in-hole assembly task in the simulation environment based on Pybullet + Gym to test its task skill learning performance. And the learned assembly strategy was also executed on a real robotic platform to verify the feasibility of the method further. Discussion According to the result of the experiment, the proposed method achieves higher success rates compared to traditional imitation learning methods while exhibiting reasonable generalization capabilities. It shows that the ProMPs under geometric representation can help the BC method make better use of the demonstration trajectory and thus better learn the task skills.
Predictor Screening, Calibration, and Observational Constraints in Climate Model Ensembles: An Illustration Using Climate Sensitivity

AbstractClimate projections have been remarkably difficult to constrain by comparing the simulated climatological state from different models with observations, in particular for small ensembles with structurally different models. In this study, the relationship between climate sensitivity and different measures of the present-day climatology is investigated. First, it is shown that 1) a variable proposed earlier that is based on interannual variation of seasonal temperature and 2) the seasonal cycle amplitude are unable to constrain the range of climate sensitivity beyond what was initially covered by the ensemble. Second, it is illustrated how model calibration helps to reveal potentially useful relationships but might also complicate the interpretation of multimodel results. As a consequence, when ensembles are small, when models are neither independently developed nor structurally identical, when observations are likely to have been used in the model development and evaluation process, and when the in.
Design and Analysis of Low Power Hybrid Logic Adder for Signal Processing Applications

- The primary objectives of VLSI design have been to enhance efficiency, reduce power consumption and delay, and minimize area. The current investigation outlines our suggested approach for analyzing a 1-bit hybrid adder compared to different adders concerning power consumption, transistor count, and delay. Recent research introduces a novel method for designing a 1-bit adder utilizing hybrid logic. An evaluation of the circuit’s efficiency has been carried out using the Mentor Graphics tool set. A statistical comparison has been conducted to examine the parameters of the course concerning the parameters of already-present adder circuits. The adder under consideration has been extended to support a width of four bits, thereby enabling an assessment of its potential for scalability. Simulation findings suggest that the proposed architecture demonstrates noteworthy performance enhancements regarding power usage and delay, leading to a comparatively low power delay product. The results obtained from the simulation illustrate that the suggested hybrid adder circuit offers a viable option for the data path structure in contemporary applications that operate at high speeds.
Minimizing the emission of material waste in the production process of batteries

Contemporary societies are strongly dependent existentially and economically on the supply of electricity, both in terms of supplying devices from the power grid, as well as the use of energy storage and constant voltage sources. Electrochemical batteries are commonly used as static energy storage. According to forecasts provided by the Environmental Protection Agency at the global and EU level, in 2025 lead-acid technologies will continue to dominate, with the simultaneous expansion of the lithium-ion battery market. The production, use and handling of used batteries are associated with a number of environmental and social challenges. The way batteries inﬂuence the environment is becoming more and more signiﬁcant, not only in the phase of their use but also in the production phase. The article presents how to effectively reduce the environmental impact of the battery production process by stabilizing it. In the presented example, the proposed changes in the battery assembly process facilitated the minimization of material losses from 0.33% to 0.05%, contributing to the reduction of the negative impact on the environment.
Benthic Diatom Blooms of Blue Haslea spp. in the Mediterranean Sea

Blue Haslea species are marine benthic pennate diatoms able to synthesize a blue-green water-soluble pigment, like marennine produced by H. ostrearia Simonsen. New species of Haslea synthetizing blue pigments were recently described (H. karadagensis, H. nusantara, H. provincialis and H. silbo). Their marennine-like pigments have allelopathic, antioxidative, antiviral and antibacterial properties, which have been demonstrated in laboratory conditions. Marennine is also responsible for the greening of oysters, for example, in the Marennes Oléron area (France), a phenomenon that has economical and patrimonial values. While blue Haslea spp. blooms have been episodically observed in natural environments (e.g., France, Croatia, USA), their dynamics have only been investigated in oyster ponds. This work is the first description of blue Haslea spp. benthic blooms that develop in open environments on the periphyton, covering turf and some macroalgae-like Padina. Different sites were monitored in the Mediterranean Sea (Corsica, France and Croatia) and two different blue Haslea species involved in these blooms were identified: H. ostrearia and H. provincialis. A non-blue Haslea species was also occasionally encountered. The benthic blooms of blue Haslea followed the phytoplankton spring bloom and occurred in shallow calm waters, possibly indicating a prominent role of light to initiate the blooms. In the absence of very strong winds and water currents that can possibly disaggregate the blue biofilm, the end of blooms coincided with the warming of the upper water masses, which might be profitable for other microorganisms and ultimately lead to a shift in the biofilm community.
MicroRNAs as Molecular Biomarkers for the Characterization of Basal-like Breast Tumor Subtype

Breast cancer is a heterogeneous disease highlighted by the presence of multiple tumor variants and the basal-like breast cancer (BLBC) is considered to be the most aggressive variant with limited therapeutics and a poor prognosis. Though the absence of detectable protein and hormonal receptors as biomarkers hinders early detection, the integration of genomic and transcriptomic profiling led to the identification of additional variants in BLBC. The high-throughput analysis of tissue-specific micro-ribonucleic acids (microRNAs/miRNAs) that are deemed to have a significant role in the development of breast cancer also displayed distinct expression profiles in each subtype of breast cancer and thus emerged to be a robust approach for the precise characterization of the BLBC subtypes. The classification schematic of breast cancer is still a fluid entity that continues to evolve alongside technological advancement, and the transcriptomic profiling of tissue-specific microRNAs is projected to aid in the substratification and diagnosis of the BLBC tumor subtype. In this review, we summarize the current knowledge on breast tumor classification, aim to collect comprehensive evidence based on the microRNA expression profiles, and explore their potential as prospective biomarkers of BLBC.
Refinement of Hair Geometry by Strand Integration

Reconstructing 3D hair is challenging due to its complex micro‐scale geometry, and is of essential importance for the efficient creation of high‐fidelity virtual humans. Existing hair capture methods based on multi‐view stereo tend to generate results that are noisy and inaccurate. In this study, we propose a refinement method for hair geometry by incorporating the gradient of strands into the computation of their position. We formulate a gradient integration strategy for hair strands. We evaluate the performance of our method using a synthetic multi‐view dataset containing four hairstyles, and show that our refinement produces more accurate hair geometry. Furthermore, we tested our method with a real image input. Our method produces a plausible result. Our source code is publicly available at https://github.com/elerac/strand_integration.
An Evaluation System of Robotic End-Effectors for Food Handling

Owing to Japan’s aging society and labor shortages, the food and agricultural industries are facing a significant demand for robotic food handling technologies. Considering the large variety of food products, available robotic end-effectors are limited. Our primary goal is to maximize the applicability of existing end-effectors and efficiently develop novel ones, and therefore, it is necessary to categorize food products and end-effectors from the viewpoint of robotic handling and establish their relationships through an effective evaluation approach. This study proposes a system for evaluating robotic end-effectors to identify appropriate ones and develop new ones. The evaluation system consists of food categorization based on food properties related to robotic handling, categorization of robotic end-effectors based on their grasping principles, a robotic system with visual recognition based on Robot Operating System 2 (ROS 2) to conduct handling tests, a scoring system for performance evaluation, and a visualization approach for presenting the results and comparisons. Based on food categorization, 14 real food items and their corresponding samples were chosen for handling tests. Seven robotic end-effectors, both commercialized and under development, were selected for evaluation. Using the proposed evaluation system, we quantitatively compared the performance of different end-effectors in handling different food items. We also observed differences in the handling of real food items and samples. The overall performance of an end-effector can be visualized and quantitatively evaluated to demonstrate its versatility in handling various food items.
"Garugiwa In Line" A Portrait of The Success of Local Wisdom-Based Population Administration Service Innovation in Ende District

This research study aims to see the success of the "Garugiwa In Line" innovation in population administration services. The invention, which adopts the name of the GARUGIWA bird or Arwah Bird, which is an endemic bird that only lives in the Kelimutu mountains in Ende Regency, has recorded various performance achievements in population administration services (Adminduk) for the people of Ende Regency. This research method uses a descriptive qualitative approach. It examines the research focus by measuring government innovation strategies using indicators of integrated services, utilization of cooperation, citizen involvement, and utilization of communication and information technology. The results showed that from the percentage achievement of national service indicators, Disdukcapil Kab. Ende can increase the percentage achievement of service indicators every year. This describes that aspects of local wisdom can be "energy" that contributes to the performance of public services.
Management of oilseed rape to balance root and canopy growth

1 Summary 2 Introduction 2 Materials and Methods 4 Year 1 4 Year 2 5 Weeds and pests 5 Disease control 5 Treatments 6 Results 7 Year 1 7 Year 2 8 Meteorological data 8 Root length density 9 Effects of cultivations on rooting 9 Spring N timing and additional autumn N 10 Low seed rates and delayed sowing 11 Spring growth regulators 13 Yields 14 Discussion 17 Recommendations for further research 18 Acknowledgements 19 References 19 Appendix 20
Cloud-Based Quad Deep Ensemble Framework for the Detection of COVID-19 Omicron and Delta Variants

The mortality rates of patients contracting the Omicron and Delta variants of COVID-19 are very high, and COVID-19 is the worst variant of COVID. Hence, our objective is to detect COVID-19 Omicron and Delta variants from lung CT-scan images. We designed a unique ensemble model that combines the CNN architecture of a deep neural network—Capsule Network (CapsNet)—and pre-trained architectures, i.e., VGG-16, DenseNet-121, and Inception-v3, to produce a reliable and robust model for diagnosing Omicron and Delta variant data. Despite the solo model’s remarkable accuracy, it can often be difficult to accept its results. The ensemble model, on the other hand, operates according to the scientific tenet of combining the majority votes of various models. The adoption of the transfer learning model in our work is to benefit from previously learned parameters and lower data-hunger architecture. Likewise, CapsNet performs consistently regardless of positional changes, size changes, and changes in the orientation of the input image. The proposed ensemble model produced an accuracy of 99.93%, an AUC of 0.999 and a precision of 99.9%. Finally, the framework is deployed in a local cloud web application so that the diagnosis of these particular variants can be accomplished remotely.
Compression Behavior and Textures of Ti57-Nb43 Alloy at High Temperatures

The mechanical behavior, microstructures, as well as the crystallographic textures of the Ti57-Nb43 alloy were investigated on cylindrical specimens compressed at high temperatures, in the range of 700–1000 °C, and strain rates between 0.001 and 1.0 s−1. Hardening, followed by softening behaviors, were observed as a function of strain due to the occurrence of dynamic recrystallization/recovery in hot deformation. The modified five-parameter Voce-type equation described well the stress–strain curves, but, for the present alloy, it was also possible with only four parameters. A new two-variables polynomial function was employed on the four parameters that described well the flow curves as a direct function of temperature and strain rate. It permitted the reduction in the number of parameters and had the predictive capacity for the flow stress at any temperature, strain, and strain rate in the investigated range. The crystallographic textures were similar at all temperatures, with an increase in intensity from 900 °C. The textures could be characterized by a double <100> and <111> fiber and a unique component of (001) <110>, the latter inherited from the initial hot-rolling texture. Viscoplastic polycrystal self-consistent deformation modeling reproduced the measured textures showing that dynamic recrystallization did not alter the development of the deformation texture, only increased its intensity.
Integrating GIS, ECDIS and web-based marine information systems for maritime navigation and coastal protection

SUMMARY Over seventy percent of the Earth’s surface is covered with water upon which world trade, fisheries, marine transportation and costal populations are relying and require safe navigation and environmental protection. This paper summarizes the principal components of a webbased Marine Information System (MIS); the data formats of electronic nautical chart (ENC), Digital Nautical Charts (DNC) and raster nautical chart (RNC) for Electronic Chart Display Information System (ECDIS) and safe navigation; the critical infrastructures under protection by coastal management regimes; the recent advances of acquiring hydrographic data by Light Detection and Ranging (LIDAR) for use in geographic information system (GIS) applications; the reliable sources of ENC, DNC and RNC; and the techniques of converting GIS data to ENC or vice versa to expedite the implementation of a MIS.
Spatial Structure of Class A Tourist Attraction in Chizhou

The tourist attraction is the material carrier of tourism supply. The proper construction of spatial structure of the tourist attraction is of great significance to the development of Chizhou tourism. With the network analysis of geographical mathematics method, the article analyzes the spatial structure of Chizhou tourism. Based on the nearest distance model, connectivity, accessibility and compactness, it analyzes and measures the spatial structure of Chizhou tourism from the perspective of the features of general spatial distribution, and regional spatial distribution structure. The result shows that the spatial distance of class A tourist attraction in Chizhou is small with the aggregation distribution; β index is 1.56, γ index is 0.53, the average pathway length is 3.26, the connectivity in the tourist attractions is low, and the connection of transportation network is weak, the intense transportation network has not come into being, and the integration of tourism resources is low. C of the compactness index is 0.55, the compactness is in medium level, which lays good foundation for tourism transportation construction and improvement of connectivity and accessibility of tourism resources.
Studies on the phytoplankton and the water quality of Malpeque Bay, Prince Edward Island, Canada.

The phytoplankton populations of Malpeque Bay, Prince Edward Island, Canada were studied to determine the role, if any, of the water quality in realtion to the biomass, distribution and size of taxonomic groups. The phytoplankton population density was in the range 10 100 cells l 1 and 153 species were identified. Summer blooms of Tha/assiosira gravida, T. nordenskioldii. Biddulphia pu/Che/fa, B. rhombus, Chae! oceros cons/rictum, Dinophysis caudata and D. norvegica were observed. The salinity, pH and dissolved oxygen analyses showed that the Malpeque Bay waters were of good quality. Regression analysis of the biomass data and the physico-chemical characteristics of the water indicated a positive correlation between the phytoplankton population density and the dissolved oxygen concentration, the temperature of the water, its salinity and its chlorophyll content.
Managing a High Uncertainty Scenario through a Real Option Assessment: Evidence from a Copper Concentrate Trader

Abstract Commodity markets are highly volatile markets where uncertainty management is critical for success. Certain commodities, such as copper concentrates, experience even higher levels of volatility and uncertainty. This is fundamentally due to the absence of a reference market that allows for a transparent price discovery, along with many factors affecting the price and trade of any commodity. Traders also lack the possibility of fully hedging their exposure to copper concentrate prices as there is no derivative market directly available for the commodity. Consequently, this paper analyses the copper concentrate trading business resorting to the Real Options methodology to assess the high volatility and uncertainty which dominates in this area of commodity markets. The results obtained indicate that this method can be applied by copper concentrate traders to separate the price uncertainty from their business operative and financial planning for the future. This provides them with a reliable tool to lower the level of uncertainty affecting their long-term goals, as well as keeping the risk that they are taking under control. It also gives them higher managerial flexibility.