Miracle-dz/UniFAR-FTUs huggingface dataset:
Zinc biofortification through seed nutri-priming using alternative zinc sources and concentration levels in pea and sunflower microgreens

Micronutrient deficiencies caused by malnutrition and hidden hunger are a growing concern worldwide, exacerbated by climate change, COVID-19, and conflicts. A potentially sustainable way to mitigate such challenges is the production of nutrient-dense crops through agronomic biofortification techniques. Among several potential target crops, microgreens are considered suitable for mineral biofortification because of their short growth cycle, high content of nutrients, and low level of anti-nutritional factors. A study was conducted to evaluate the potential of zinc (Zn) biofortification of pea and sunflower microgreens via seed nutri-priming, examining the effect of different Zn sources (Zn sulfate, Zn-EDTA, and Zn oxide nanoparticles) and concentrations (0, 25, 50, 100, and 200 ppm) on microgreen yield components; mineral content; phytochemical constituents such as total chlorophyll, carotenoids, flavonoids, anthocyanin, and total phenolic compounds; antioxidant activity; and antinutrient factors like phytic acid. Treatments were arranged in a completely randomized factorial block design with three replications. Seed soaked in a 200 ppm ZnSO4 solution resulted in higher Zn accumulation in both peas (126.1%) and sunflower microgreens (229.8%). However, an antagonistic effect on the accumulation of other micronutrients (Fe, Mn, and Cu) was seen only in pea microgreens. Even at high concentrations, seed soaking in Zn-EDTA did not effectively accumulate Zn in both microgreens’ species. ZnO increased the chlorophyll, total phenols, and antioxidant activities compared to Zn-EDTA. Seed soaking in ZnSO4 and ZnO solutions at higher concentrations resulted in a lower phytic acid/Zn molar ratio, suggesting the higher bioaccessibility of the biofortified Zn in both pea and sunflower microgreens. These results suggest that seed nutrient priming is feasible for enriching pea and sunflower microgreens with Zn. The most effective Zn source was ZnSO4, followed by ZnO. The optimal concentration of Zn fertilizer solution should be selected based on fertilizer source, target species, and desired Zn-enrichment level.
Asymptotic bounded consensus tracking of double-integrator multi-agent systems with a bounded-jerk target via sampled-data control

This study investigates the asymptotic bounded consensus tracking problems of double-integrator multi-agent systems (MASs) with an asymptotically-unbounded-acceleration and bounded-jerk target via sampled-data control. An improved sampled-data consensus tracking protocol is proposed to guarantee that double-integrator MASs track an asymptotically-unbounded-acceleration and bounded-jerk target available to only a portion of agents. The augmented matrix method and the eigenvalue analysis method are employed for deriving the necessary and sufficient conditions given in the form of the allowable scope of the sampling period. The existence of the non-empty allowable scope of the sampling period theoretically shows the effectiveness of the proposed protocol and comparison simulations numerically illustrate the effectiveness of the proposed protocol.
A position resolution MRPC for muon tomography

Muon tomography is a promising method in the detection and imaging of high Z material. In general, considering the quality of track reconstruction in imaging, a detector of good position resolution, high efficiency and large area is required. This paper presents the design and study of a prototype of position sensitive MRPC with 0.15 mm narrow gas gap and 2.54 mm strip readout. Through a cosmic-ray experiment, the performance of MRPC module is carefully observed and each channel is calibrated. Through an X ray experiment with a narrow slit, the position resolution is studied. The results show that the time resolution of the module can reach 61ps and the spatial resolution can reach 0.36 mm.
Visual Exposes You: Pedestrian Trajectory Prediction Meets Visual Intention

Pedestrian trajectory prediction in multiple scenarios is of immense importance in autonomous driving and disentanglement of human behavior but is limited in catching human intention and initiative. Most previous works tend to predict the trajectory using only 2D coordinates, which generally cause two common problems: a) Overlooking the subjective initiative, including sudden swerve and erratic movement; b) A potential challenge called abnormal collision caused by unlabeled pedestrians on dataset is not being identified and resolved, which would ruin the model prediction. To break those limitations, we introduce visual localization and orientation as Visual Intention Knowledge to help the trajectory prediction, which is learned directly from visual scenarios. It benefits to comprehend human intention and formulates decision-making processes. Moreover, by learning from the visual information and decision-making policy, we construct the Visual Intention Knowledge associated spatio-temporal Transformer (VIKT) to predict human trajectory by combining the intention knowledge with the novel Transformer. Extensive experimental results demonstrate that our VIKT model could achieve competitive performance by the Visual Intention Knowledge through optimizing the model prediction compared with state-of-the-art methods in terms of prediction accuracy on ETH/UCY and SDD benchmarks.
New Insights into the Mesozoic Large‐scale Intra‐plate Magmatism and Mineralization in South China from Seismic Tomography

A great amount of new S‐wave data has been combined to image the mantle structure down to lower mantle depth near the southeastern margin of Eurasia and understand the tectonics in South China since the Mesozoic. Our results reveal a large‐scale structure beneath the South China Sea, with a prominent, broad low‐velocity feature of at least 1500‐km wide in and below the mantle transition zone (MTZ) and a pronounced low‐velocity feature of nearly 500‐km wide in the lowermost mantle. Together these features may represent the head‐and‐tail of an upwelling mantle plume that has interacted with and deformed by the subducting plates in the region. The Andaman–Sumatra plate is seen subducting steeply without stagnation in the MTZ over the large‐scale low‐velocity structure, suggesting that the upwelling mantle may have exerted significant influence on the overlying plate tectonics. Our results suggest a long‐term extensional regime near the southeastern margin of Eurasia, which may help to understand the formation of the large‐scale intra‐plate magmatism and mineralization with accumulation of huge amount of rare metal elements in South China during the Mesozoic, and the continental breakup, the southeastward extrusion of Indochina, and the opening of the South China Sea during the Cenozoic.
The Soul’s Thoughts as Dark Energy

The great mystery concerning our Universe is Dark Energy, which is introduced to explain the acceleration of the expanding galaxies. In the contemporary cosmology, Dark Energy is modeled by a perfect fluid having a very simple equation of state; pressure is proportional to Dark Energy density. The acceleration of the expansion clearly implies the existence of some force that acts to push galaxies apart, and the source of this force is what we have dubbed Dark Energy. However, we have little idea of what the nature of Dark Energy might actually be. None of the four known forces in nature could provide a force to oppose gravity. The main objective of this theory is to derive new equation of state of Dark Energy considering with its Nature. Its Nature has been assumed to be an unknown kind of force generated from our thoughts. First of all, our soul is assumed to be the nature of our thoughts and dreams. More precisely, it has been assumed and described that, respectively, Imaginary fields of the Soul’s thoughts are based on the fact that they are only produced when we are thinking or dreaming about everything and everyone and the main difference between the Imaginary fields of the Soul’s thoughts and the electromagnetic fields. Then it has been explained that a negative mass with negative gravity behavior in the space, like the Soul, produces perpendicular Imaginary fields which provide a force to oppose gravity and accelerate the expansion of the Universe.
Intuitionistic uncertain linguistic aggregation operators and their application to group decision making

An intuitionistic uncertain linguistic number is the generalization of an intuitionistic fuzzy number and an uncertain linguistic number.For the intuitionistic uncertain linguistic information aggregating problems,some operational laws and comparison criteria of the intuitionistic uncertain linguistic numbers are defined and proved.Based on these operational laws,some aggregation operators are proposed, including the intuitionistic uncertain linguistic weighted arithmetic averaging operator(IULWAA), the intuitionistic uncertain linguistic ordered weighted averaging operator(IULOWA) and the intuitionistic uncertain linguistic hybrid averaging operator(IULHA),and the properties of these operators are presented.Based on these operators,an approach for solving multiple attribute group decision making problems is proposed,in which the attribute weights are known and the attribute values take the form of the intuitionistic uncertain linguistic numbers.Finally,an illustrative example shows the effectiveness of the proposed approach.
On the Effect of Electron Temperature Fluctuations on Turbulent Heat Transport in the Edge Plasma of Tokamaks

In this paper we study the impact of electron temperature fluctuations in a two‐dimensional turbulent model. This modification adds a second linear instability, known as sheath‐driven conducting‐wall instability, with respect to the previous isothermal model only driven by the interchange instability. Non‐linear simulations, backed up by the linear analysis, show that the additional mechanism can change drastically the dynamics of turbulence (scales, density‐potential correlation, and statistical momentum). Moreover, its importance relatively to the interchange instability should be more significant in the private flux region than in the main scrape of layer. Its effect on heat transport is also investigated for different regimes of parameters, results show that both instabilities are at play in the heat transport. Finally, the sheath neagtive resistance instability could be responsible for the existence of corrugated heat flux profiles in the scrape‐off layer leading to a multiple decay length. (© 2016 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
New Perspectives in Nonlinearity or What to Do When the Whole is More Than the Sum of Its Parts

This paper presents a theory of algorithms designed to optimize highly interactive systems (multi-diminsional, multi-peak, nonlinear functions). Two applications are discussed: one concerns cognitive systems capable of learning and generalization, and one concerns calculations dealing with the "origin of life" from "organic soups". The algorithms are intrinsically parallel--each function argument processed serves as a carrier for information about a tremendous number of regions (hyperplanes) in the function's domain. Each region is automatically ranked according to the estimated average value of the function over that region, and the rankings are compactly stored in the algorithm's data base (M l-tuples store approximately M-2l/2 rankings). Thus, the algorithm implicitly processes hyperplanes by manipulating function arguments.
A Study on Pulse Wave Signals based on Fibre Bragg Grating Arrays

Pulse wave signals are physiological signals that can be analyzed for obtaining vital parameters such as heart rate, and blood pressure. In this paper, we have utilized widely known fiber Bragg grating (FBG) arrays for acquiring pulse wave signals from the radial artery. Arrays offer various advantages such as multipoint sensing or quasi-distributed sensing, sensing area range, equating spatial orientation (Vertical or Horizontal) effects, and compensating locational effects. After a detailed analysis, the study concluded by reporting a high degree of coherence value (0.859) between signals in the vertical orientation as compared to horizontal orientation.
The Use of Specialized Pro-Resolving Mediators in Biomaterial-Based Immunomodulation

The implantation of a biomaterial will lead to the immediate onset of an acute inflammatory response, which is of key importance in shaping the quality of the repair process. However, the return to homeostasis is critical to prevent a chronic inflammatory response that may impair the healing process. The resolution of the inflammatory response is now recognized as an active and highly regulated process, being described as specialized immunoresolvents that have a fundamental role in the termination of the acute inflammatory response. These mediators collectively coined as specialized pro-resolving mediators (SPMs) are a family of endogenous molecules that include lipoxins (Lx), resolvins (Rv), protectins (PD), maresins (Mar), Cysteinyl-SPMs (Cys-SPMs) and n-3 docosapentaenoic acid-derived SPMs (n-3 DPA-derived SPMs). SPMs have important anti-inflammatory and pro-resolutive actions such as decreasing the recruitment of polymorphonuclear leukocytes (PMNs), inducing the recruitment of anti-inflammatory macrophages, and increasing macrophage clearance of apoptotic cells through a process known as efferocytosis. Over the last years, the trend in biomaterials research has shifted towards the engineering of materials that are able to modulate the inflammatory response and thus stimulate appropriate immune responses, the so-called immunomodulatory biomaterials. These materials should be able to modulate the host immune response with the aim of creating a pro-regenerative microenvironment. In this review, we explore the potential of using of SPMs in the development of new immunomodulatory biomaterials and we propose insights for future research in this field.
Assessing and Improving Provider Knowledge for a Cardiothoracic Intensive Care Unit Electronic Dashboard Initiative

Background: Electronic dashboards measure intensive care unit (ICU) performance by tracking quality indicators, especially pinpointing sub-standard metrics. This helps ICUs scrutinize and change current practices in an effort to improve failing metrics. However, its technological value is lost if end users are unaware of its importance. This results in decreased staff participation, leading to unsuccessful initiation of the dashboard. Therefore, the purpose of this project was to improve cardiothoracic ICU providers’ understanding of electronic dashboards by providing an educational training bundle in preparation for an electronic dashboard initiation. Methods: A Likert survey assessing providers’ knowledge, attitudes, skills, and application of electronic dashboards was conducted. Subsequently, an educational training bundle, consisting of a digital flier and laminated pamphlets, was made available to providers for four months. After bundle review, providers were assessed using the same pre-bundle Likert survey. Results: A comparison of summated scores from pre-bundle (mean = 38.75) and post-bundle surveys (mean = 46.13) yielded an increased summated score overall (mean = 7.38, p ≤ 0.001). Conclusion: An educational bundle improved providers’ understanding and increased their likelihood of using electronic dashboards upon its initiation. Further studies are needed to continue increasing staff participation such as providing specific education to navigate the interface for data retrieval and interpretation.
Sliding Mode-Based Design of Unified Force and Position Control for Series Elastic Actuator

This paper presents unified force and position control based on sliding mode control (SMC) for a series elastic actuator (SEA). Compliant motion of robotic systems is crucial when dealing with unstructured environments as in the case of physical human-robot interaction. Therefore, not only traditional mechanical systems with stiff joints but also mechanically compliant systems such as SEAs have been actively studied. In order to accomplish versatile tasks, the strategy enabling both position control and force control is favorable. In this paper, the controller synthesizing position and force controllers on the basis of SMC for the control problem of SEAs is proposed by extending our previous work. Simulation results demonstrate the feasibility of the proposed method.
Potential of Interleukin (IL)-12 Group as Antivirals: Severe Viral Disease Prevention and Management

The interleukin (IL)-12 family consists of pro- and anti-inflammatory cytokines that are able to signal the activation of host antiviral immunity while preventing over-reactive immune reactions due to active virus replication and viral clearance. Amongst others, IL-12 and IL-23 are produced and released by innate immune cells such as monocytes and macrophages to signal the proliferation of T cells and release of effector cytokines, which subsequently activate host defence against virus infections. Interestingly, the dualities of IL-27 and -35 are evidently shown in the course of virus infections; they regulate the synthesis of cytokines and antiviral molecules, proliferation of T cells, and viral antigen presentation in order to maximize virus clearance by the host immune system. In terms of anti-inflammatory reactions, IL-27 signals the formation of regulatory T cells (Treg) which in turn secrete IL-35 to control the scale of inflammatory response that takes place during virus infections. Given the multitasking of the IL-12 family in regards to the elimination of virus infections, its potential in antiviral therapy is unequivocally important. Thus, this work aims to delve deeper into the antiviral actions of the IL-12 family and their applications in antiviral therapies.
Missing Data Analysis in Traffic Monitoring System Using LSTM

A dependable traffic route optimization system and an accurate traffic simulation model is crucial for effective traffic management system. The creation of a more efficient traffic management system is hampered by the absence of a realistic traffic simulation data. Missing data is one of the fundamental causes of hindrance, because it will certainly result in inaccurate predictions of congestion levels and less effective reconfiguration. Both future traffic data mining and real-time traffic monitoring are impacted by these missing numbers. In this paper we used transfer learning-based algorithm to fill in the gaps of those missing data. This process of data recreation will help the existing traffic management system by improving its accuracy and efficiency which will directly improve the working of traffic simulation models and traffic route optimization systems.
Extended three-dimensional generalized differential quadrature method: The basic equations and thermal vibration analysis of functionally graded fiber orientation rectangular plates

ABSTRACT The present article deals with free vibration of functionally graded fiber orientation rectangular plates considering temperature effect. Three different types of fiber orientation distributions through the thickness of the plate are proposed. The properties of the plate are assumed to be temperature-dependent. Equations of motions are derived based on a three-dimensional theory of elasticity. General differential quadrature method is used to discretize these equations. Effects of temperature, fiber orientation, and boundary conditions besides some geometric parameters are presented. Also, some interesting conclusions are obtained since temperature and functionality of a functionally graded plate have a significant effect on the natural frequency of the plate.
A Climate Science Toolkit for High Impact‐Low Likelihood Climate Risks

An important component of the risks from climate change arises from outcomes that are very unlikely, but whose impacts if they were to occur would be extremely severe. Examples include levels of surface warming, or changes in the water cycle, that are at the extreme of plausible ranges, or crossing of a climate system “tipping point” such as ice sheet or ocean circulation instability. If such changes were to occur their impacts on infrastructure or ecosystems may exceed existing plans for adaptation. The traditional approach of ensemble climate change projections is not well suited to managing these High Impact‐Low Likelihood (HILL) risks, where the objective is to “prepare for the worst” rather than to “plan for what's likely. ” In this paper we draw together a number of ideas from recent literature, to classify four types of HILL climate outcome and to propose the development of a practical “toolkit” of physical climate information that can be used in future to inform HILL risk management. The toolkit consists of several elements that would need to be developed for each plausible HILL climate outcome, then deployed individually to develop targeted HILL risk management approaches for individual sectors. We argue that development of the HILL toolkit should be an important focus for physical climate research over the coming decade, and that the time is right for a focused assessment of HILL risks by the Intergovernmental Panel on Climate Change in its 7th Assessment Cycle.
Configurable NbOx Memristors as Artificial Synapses or Neurons Achieved by Regulating the Forming Compliance Current for the Spiking Neural Network

For the first time, a configurable NbOx memristor is achieved that can be configured as an artificial synapse or neuron after fabrication by controlling the forming compliance current (FCC). When the FCC ≤ 2 mA, the memristors exhibit the resistive‐switching (RS) property, enabling multiple types of synaptic plasticity, including short‐term potentiation, paired‐pulse facilitation, short‐term memory, and long‐term memory. When the FCC ≥ 3 mA, the memristors can be electroformed and exhibit the threshold switching (TS) property with excellent endurance (>1012), thus achieving various biological neuron characteristics, such as threshold‐triggering, strength‐modulation of spike frequency, and leaky integrate‐and‐fire. This enables the successful implementation of a spiking Pavlov's dog that employs the spikes as information carrier by connecting an RS NbOx memristor as artificial synapse and a TS memristor as artificial neuron in series. Furthermore, a fully NbOx memristors‐based single‐layer spiking neural network is simulated. It is first found that, due to the forgetting property of synapse, the recognition accuracy for the Modified National Institute of Standards and Technology handwritten digits is increased from 85.49% to 91.45%. This study provides a solid foundation for the development of neuromorphic machines based on the principles of the human brain.