Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration Agricultural Knowledge and Internet of Things for Multi-Agent Deficit Irrigation Control

Technology related to the Internet of Things and Big Data is developing rapidly, favoring agricultural management and cultivation. External environmental parameters affect crop growth. Irrigation operations involve multi-conditional decisions. Artificial intelligence and image processing technology are used to control watering, process environmental data, and use the processed data are then used to train models to predict soil moisture. The results thus obtained are used to divide soil into that with high, normal, and low moistures. A camera commonly used to capture images of soil, which are imported into a convolutional neural network for feature extraction. Next, the category of soil is predicted following deep learning. The results of the two predictions are sent to a fuzzy control system and the soil moisture interval is defined based on the category of crop that is being planted in it. The rule base is constructed using the defined parameters, and determines the judgment rule from the agricultural professional, And external conditions lead to the fuzzy controller. Defuzzified results are imported into controlled a control device. This work uses the IoT to serialize information from the fields in a farm and uses artificial intelligence techniques to analyze the state of plants. Image recognition technology is to provide more precise and comprehensive control to improve the accuracy of irrigation.
Anti-Confusing: Region-Aware Network for Human Pose Estimation

In this work, we propose a novel framework named Region-Aware Network (RANet), which learns the ability of anti-confusing in case of heavy occlusion, nearby person and symmetric appearance, for human pose estimation. Specifically, the proposed method addresses three key aspects, i.e., data augmentation, feature learning and prediction fusion, respectively. First, we propose Parsing-based Data Augmentation (PDA) to generate abundant data that synthesizes confusing textures. Second, we not only propose a Feature Pyramid Stem (FPS) to learn stronger low-level features in lower stage; but also incorporate an Effective Region Extraction (ERE) module to excavate better target-specific features. Third, we introduce Cascade Voting Fusion (CVF) to explicitly exclude the inferior predictions and fuse the rest effective predictions for the final pose estimation. Extensive experimental results on two popular benchmarks, i.e. MPII and LSP, demonstrate the effectiveness of our method against the state-of-the-art competitors. Especially on easily-confusable joints, our method makes significant improvement.
Changes in the 1963–2013 shallow ground thermal regime in Russian permafrost regions

Spatial variability and temporal trends of the shallow ground thermal regime and permafrost active-layer thickness (ALT) were estimated over 1963–2013 using daily soil temperature data available from stations of the Russian Hydrometeorological Service. Correlation analysis was used to evaluate the role of changing climatic conditions on the ground thermal regime. ALT data collected by the Circumpolar Active Layer Monitoring program in Russia were used to expand the geography of ALT observations over 1999–2013, and to identify ‘hot spots’ of soil temperature and ALT change. Results indicate that a substantially higher rate of change in the thermal regime of permafrost-affected soils prevailed during 1999–2013, relative to the last fifty years. Results indicate that the thermal regime of the upper permafrost in western Russia is strongly associated with air temperature, with much weaker relationships in central and eastern Russia. The thermal regime of permafrost-affected soils shows stronger dependence on climatic conditions over the last fifteen years relative to the historical 50-year period. Geostatistical analysis revealed that the cities of Norilsk and Susuman are hot spots of permafrost degradation. Of six settlements selected for detailed analysis in various parts of the permafrost regions, all but one (Chukotka), show substantial changes in the shallow ground thermal regime. Northern locations in the continuous permafrost region show thickening of the active layer, while those farther south experienced development of residual thaw layers above the permafrost and decreases in the duration of the freezing period.
Automated analysis of Gaze Patterns for Autism Screening- Density Approach

“Visual scanning reflects a model of the world that exists inside the brain of each individual” – by Moshe Eizenman. Advancements in eye-tracking technology have led to some wide-ranging applications in fields of medical research, gaming, automation, Human- Computer Interaction(HCI) and many more. This paper presents an automated study of gaze patterns as an investigating tool to distinguish autism spectrum disorder from typical development. Gaze abnormality can be used to study the model of the world perceived by people with autism that is quite different from normal people.
Social pedagogy as a model to provide support for siblings of children with intellectual disabilities

The experiences of non-disabled children growing up with a sibling with an intellectual disability vary considerably, with reported impact ranging from increased mental health problems through evaluations of life enhancement. However, there is evidence that the net impact is neutral to positive, which was supported by the findings of this report of a service evaluation survey. The value of providing support to those young siblings is however clear. An established method of support is within a group of peers who also have a sibling with an intellectual disability, though no specific method for running this type of group has yet been fully explored. This article reports the views of 39 children taking part in such a group, analysing their perspective through a proposed model for the operation of sibling groups: social pedagogy. It was found that the closer the group’s activities were to social pedagogy, the more supported the children and young people felt.
Design of Efficient Quantum-Dot Cellular Automata (QCA) MAC Unit

QCA technology has considerable advantages in comparison with Complementary Metal Oxide Semiconductor (CMOS) technology, such as extremely low power dissipation, high operating frequency, and a small size and can operate at one Terahertz. The Multiply -Accumulator (MAC) unit is considered as one of the essential operation in Digital Signal Processing (DSP). In the real-time DSP systems, several applications like speech processing, video coding and digital filtering etc, require MAC operations. However, the power dissipation and area are the most significant aspects in these systems. In this paper, low power MAC Unit based on QCA technology is designed. QCADesigner ver 2.0. 3 is used to validate the accuracy of the proposed circuit. The power dissipation is estimated using QCAPro tool. The total power consumed by this unit is 4.03 mW. It is found that proposed design is better than other designs based on classical technology. As the works in the field of QCA logic signal processing has started to progress, the suggested contribution will give rise to a new thread of research in the field of real time signal processing.
The clade vertebrata: spines and routing in ad hoc networks

This work proposes a self-organizing, dynamic infrastructure called a spine for efficient routing in ad hoc networks. We present a scalable framework for routing that encompasses a range of knowledge at each spine node, and identify the trade-offs involved for routing at different points in this range. Our routing algorithm requires only partial topology information at each spine node, consisting of the spine structure, dependants of each spine node, propagation of long-lived links, and snooped routing information from ongoing flows. Through worst-case theoretical bounds and simulation of typical scenarios, we show that the spine-based routing with only partial topology information provides good routes at low overhead.
A Statistically Principled and Computationally Efficient Approach to Speech Enhancement using Variational Autoencoders

Recent studies have explored the use of deep generative models of speech spectra based of variational autoencoders (VAEs), combined with unsupervised noise models, to perform speech enhancement. These studies developed iterative algorithms involving either Gibbs sampling or gradient descent at each step, making them computationally expensive. This paper proposes a variational inference method to iteratively estimate the power spectrogram of the clean speech. Our main contribution is the analytical derivation of the variational steps in which the en-coder of the pre-learned VAE can be used to estimate the varia-tional approximation of the true posterior distribution, using the very same assumption made to train VAEs. Experiments show that the proposed method produces results on par with the afore-mentioned iterative methods using sampling, while decreasing the computational cost by a factor 36 to reach a given performance .
THE EVOLUTION OF SELF‐FERTILIZATION AND INBREEDING DEPRESSION IN PLANTS. I. GENETIC MODELS

The amounts of inbreeding depression upon selfing and of heterosis upon outcrossing determine the strength of selection on the selfing rate in a population when this evolves polygenically by small steps. Genetic models are constructed which allow inbreeding depression to change with the mean selfing rate in a population by incorporating both mutation to recessive and partially dominant lethal and sublethal alleles at many loci and mutation in quantitative characters under stabilizing selection. The models help to explain observations of high inbreeding depression (> 50%) upon selfing in primarily outcrossing populations, as well as considerable heterosis upon outcrossing in primarily selfing populations. Predominant selfing and predominant outcrossing are found to be alternative stable states of the mating system in most plant populations. Which of these stable states a species approaches depends on the history of its population structure and the magnitude of effect of genes influencing the selfing rate.
Imitation learning for agile autonomous driving

We present an end-to-end imitation learning system for agile, off-road autonomous driving using only low-cost on-board sensors. By imitating a model predictive controller equipped with advanced sensors, we train a deep neural network control policy to map raw, high-dimensional observations to continuous steering and throttle commands. Compared with recent approaches to similar tasks, our method requires neither state estimation nor on-the-fly planning to navigate the vehicle. Our approach relies on, and experimentally validates, recent imitation learning theory. Empirically, we show that policies trained with online imitation learning overcome well-known challenges related to covariate shift and generalize better than policies trained with batch imitation learning. Built on these insights, our autonomous driving system demonstrates successful high-speed off-road driving, matching the state-of-the-art performance.
Bacopa monniera Attenuates Scopolamine-Induced Impairment of Spatial Memory in Mice

Scopolamine, an anticholinergic, is an attractive amnesic agent for discerning the action of candidate antiamnesic drugs. Bacopa monniera Linn (Syn. Brahmi) is one such antiamnesic agent that is frequently used in the ancient Indian medical system. We have earlier reported the reversal of diazepam-induced amnesia with B. monniera. In this study we wanted to test if scopolamine-induced impairment of spatial memory can also be ameliorated by B. monniera using water maze mouse model. The objective of study was to study the effect of B. monniera on scopolamine-induced amnesia. We employed Morris water maze scale to test the amnesic effect of scopolamine and its reversal by B. monniera. Rotarod test was conducted to screen muscle coordination activity of mice. Scopolamine significantly impaired the acquisition and retrieval of memory producing both anterograde and retrograde amnesia. Bacopa monniera extract was able to reverse both anterograde and retrograde amnesia. We propose that B. monniera's effects on cholinergic system may be helpful for developing alternative therapeutic approaches for the treatment of Alzheimer's disease.
Towards Model-Driven Application Security across Clouds

In this paper we present a security meta-model for describing security requirements of cloud applications as well as a platform architecture to drive perimeter security and continuous risk assessment tools and processes supporting application deployments across regions and clouds. We demonstrate a case study of a geo-distributed cloud deployment with a specifically configured intrusion detection solution to handle DDoS attacks via cloud resource elasticity actions.
An entropy based approach for direction-of-arrival estimation in Gaussian and non-Gaussian correlated noise

In this paper, we present an entropy based approach for DOA estimation in Gaussian and non-Gaussian environments. The DOA estimates are obtained by minimizing an entropy measure of the array data in the noise subspace. We show that the entropy approach leads to the MAP algorithm under the Gaussian assumption. Under the non-Gaussian assumption, we apply the varimax norm as an information measure. An intuitive consistency analysis is also performed. Computer simulations are used to demonstrate the effectiveness of the proposed approach.
Janus Kinase 2-dependent Activation of p38 Mitogen-activated Protein Kinase by Growth Hormone

We demonstrate here that p38 mitogen-activated protein (MAP) kinase is activated in response to cellular stimulation by human GH (hGH) in Chinese hamster ovary cells stably transfected with GH receptor cDNA. This activation requires the proline-rich box 1 region of the GH receptor required for JAK2 association and is prevented by pretreatment of cells with the JAK2-specific inhibitor AG490. ATF-2 is both phosphorylated and transcriptionally activated by hGH, and its transcriptional activation also requires the proline-rich box 1 region of the GH receptor. Expression of wild type JAK2 can further enhance hGH-induced ATF-2-, CHOP-, and Elk-1-mediated transcriptional activation, whereas pretreatment with AG490 is inhibitory. Use of either specific pharmacological inhibitors or transient transfection of cells with p38α MAP kinase cDNA or a dominant negative variant demonstrated that hGH-stimulated transcriptional activation of ATF-2 and CHOP, but not Elk-1, is regulated by p38 MAP kinase. Both the p38 MAP kinase and p44/42 MAP kinase are critical for hGH-stimulated mitogenesis, whereas only p38 MAP kinase is required for hGH-induced actin cytoskeletal re-organization. p38 MAP kinase is therefore an important regulator in coordinating the pleiotropic effects of GH.
Secure QR-Code Based Message Sharing System Using Cryptography and Steganography

Many cryptographic techniques are available for serving the purpose of information security over the web, servers and local systems. However, there is always demand of more security which may not be meet by such cryptographic algorithms alone because of known security attacks and mathematical complexity. Thus visualizing the strategic combination of cryptography and steganography techniques can provide a higher level of security. Quick Response (QR) codes are used extensively due to their beneficial characteristics. It includes robustness, readability, error correction capability, large data capacity than traditional barcodes etc. Thus, in this work, we propose a 3-layered architecture for securing message sharing mechanism by using QR code image in one layer. This architecture utilizes the empirical and strategic use of cryptography and steganography techniques. The proposed system provides the higher level of security on the basis of quantitative and qualitative results. Also, we evaluate our system against the performance evaluation criteria discussed in the paper.
The Ethics of Record Destruction

This paper attempts to analyze an unnamed charity’s journey for increased transparency and governance. Several potential misstep scenarios are discussed. The names of parties and organizations involved have been changed. The literature review overviews complexities associated with accounting/ organizational performance situations and introduce an ethical model for possible outcome determination and other discussion based considerations. This study articulates the evolution of ethics at both the unnamed charity and with its external and internal stakeholders and presents questions regarding the contextual approach of management, external auditors, and internal parties.
Mechanical Strain Measurements Using Semiconductor Piezoresistive Material

In this article, the design of a MEMS-based strain sensor has been introduced. This design has high sensitivity, low power consumption compared with the commercially available thin-foil strain gauges, and high absolute resolution. All of these are at high signal stability over a wide temperature range. The piezoresistivity theory, the microfabrication process flow and the finite element simulation have been introduced to provide guidelines for the sensor design process
Modulations of Heart Rate, ECG, and Cardio-Respiratory Coupling Observed in Polysomnography

The cardiac component of cardio-respiratory polysomnography is covered by ECG and heart rate recordings. However, their evaluation is often underrepresented in summarizing reports. As complements to EEG, EOG, and EMG, these signals provide diagnostic information for autonomic nervous activity during sleep. This review presents major methodological developments in sleep research regarding heart rate, ECG, and cardio-respiratory couplings in a chronological (historical) sequence. It presents physiological and pathophysiological insights related to sleep medicine obtained by new technical developments. Recorded nocturnal ECG facilitates conventional heart rate variability (HRV) analysis, studies of cyclical variations of heart rate, and analysis of ECG waveform. In healthy adults, the autonomous nervous system is regulated in totally different ways during wakefulness, slow-wave sleep, and REM sleep. Analysis of beat-to-beat heart-rate variations with statistical methods enables us to estimate sleep stages based on the differences in autonomic nervous system regulation. Furthermore, up to some degree, it is possible to track transitions from wakefulness to sleep by analysis of heart-rate variations. ECG and heart rate analysis allow assessment of selected sleep disorders as well. Sleep disordered breathing can be detected reliably by studying cyclical variation of heart rate combined with respiration-modulated changes in ECG morphology (amplitude of R wave and T wave).
Design Presentation and Induced-Stress Study of a 6-axis Single-Mass Piezoelectric IMU

This paper explores steps towards induced stress enhancement of a new improved design of a 6-axis single-mass piezoelectric motion sensor. The detailed numerical analysis was based on a previously developed and validated finite element model for the new design. The experimental data, reported in literature for a design with a similar geometry, has been used in the validation. Using the same dimensions' range, we detail the new improved design geometry. The analysis of the induced stress in response to x, y and z-accelerations shows that the new design offers better performances. In response to x-axis and z-axis accelerations, evaluated induced stress values are 2 and 2.5 orders of magnitude higher than those measured on the reported design, respectively.
Neuron-based heredity and human evolution

It is widely recognized that human evolution has been driven by two systems of heredity: one DNA-based and the other based on the transmission of behaviorally acquired information via nervous system functions. The genetic system is ancient, going back to the appearance of life on Earth. It is responsible for the evolutionary processes described by Darwin. By comparison, the nervous system is relatively newly minted and in its highest form, responsible for ideation and mind-to-mind transmission of information. Here the informational capabilities and functions of the two systems are compared. While employing quite different mechanisms for encoding, storing and transmission of information, both systems perform these generic hereditary functions. Three additional features of neuron-based heredity in humans are identified: the ability to transfer hereditary information to other members of their population, not just progeny; a selection process for the information being transferred; and a profoundly shorter time span for creation and dissemination of survival-enhancing information in a population. The mechanisms underlying neuron-based heredity involve hippocampal neurogenesis and memory and learning processes modifying and creating new neural assemblages changing brain structure and functions. A fundamental process in rewiring brain circuitry is through increased neural activity (use) strengthening and increasing the number of synaptic connections. Decreased activity in circuitry (disuse) leads to loss of synapses. Use and disuse modifying an organ to bring about new modes of living, habits and functions are processes in line with Neolamarckian concepts of evolution (Packard, 1901). Evidence is presented of bipartite evolutionary processes—Darwinian and Neolamarckian—driving human descent from a common ancestor shared with the great apes.
Unconstrained and Constrained Model Predictive Control for a Modified Quadruple Tank System

In this paper, an implementation of Model Predictive Control (MPC) for a Modified Quadruple Tank System (MQTS) is addressed. The MQTS system is a multi-input-multi-output (MIMO) system and has complicated variables interactions. The aim of this work is to demonstrate the implementation of MPC, including the derivations of unconstrained and constrained MPC equations for the particular system. Besides that, we want to evaluate the performance of the MPCs in terms of the behaviour of the system and to verify should the realisations are physically feasible. For the purpose of the study, a linear discrete-time state space model is employed. The model is from an existing dynamics of the system which comprises deterministic and stochastic components. As for the controller, the MPC consists of a state estimator and a constrained regulator. A Kalman filter is incorporated to estimate the current state from the filtered part while the predictions part is used by the constrained regulator, which is an Optimal Control Problem (OCP) to predict the future output trajectory. The objective of the OCP consists of a tracking error term that penalizes deviations of the predicted outputs from the setpoint and a regularization term that penalizes the changes in the inputs (manipulated variables). The resulting OCP is represented as a Quadratic Programming (QP) is solved and the performance of MPC is demonstrated through simulations using MATLAB.
Detecting semantics-preserving XML schema mappings based on annotations to OWL ontology

We consider the problem of deciding whether there exists a semantics-preserving mapping between two XML schemas or parts of schemas specified by tree patterns [1]. To define the semantics of XML data we interpret its schema in an OWL ontology [4] through a semantic annotation. The annotation is used to derive complex XML-to-OWL mappings, which are next used to reason about semantic relations (subsumption) between annotated schemas. Using operations on mappings [3] (inversion and composition) we can derive a semantic XML-to-XML mapping preserving semantics of transformed data. We propose an algorithm for deriving XML-to-OWL mappings based on annotation, and an algorithm for reasoning about semantic relationships (subsumption and equivalence) between (sub)schemas defined by tree patterns.