Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous Identification and Optimal Tracking Control of Unknown Continuous Time Nonlinear System With Actuator Constraints Using Critic-Only Integral Reinforcement Learning

In order to obviate the requirement of drift dynamics in adaptive dynamic programming (ADP), integral reinforcement learning (IRL) has been proposed as an alternate formulation of Bellman equation.However control coupling dynamics is still needed to obtain closed form expression of optimal control effort. In addition to this, initial stabilizing controller and two sets of neural networks (NN) (known as Actor-Critic) are required to implement IRL scheme. In this paper, a stabilizing term in the critic update law is leveraged to avoid the requirement of an initial stabilizing controller in IRL framework to solve optimal tracking problem with actuator constraints. With such a term, only one NN is needed to generate optimal control policies in IRL framework. This critic network is coupled with an experience replay (ER) enhanced identifier to obviate the necessity of control coupling dynamics in IRL algorithm. The weights of both identifier and critic NNs are simultaneously updated and it is shown that the ER-enhanced identifier is able to handle parametric variations better than without ER enhancement. The most salient feature of the novel update law is its variable learning rate, which scales the pace of learning based on instantaneous Hamilton-Jacobi-Bellman (HJB) error. Variable learning rate in critic NN coupled with ER technique in identifier NN help in achieving tighter residual set for state error and error in NN weights as shown in uniform ultimate boundedness (UUB) stability proof. The simulation results validate the presented "identifier-critic" NN on a nonlinear system.
Integrated pest management in forestry: Some difficulties in pursuing the holy-grail

As Australian forests become more intensively managed, there is increasing interest in the development of integrated pest management (IPM) strategies for the control of forest pests. IPM, in the strict sense, is a research model which uses tools such as economic injury levels (EIL's), growth impact models and pest population monitoring to help coordinate the application and timing of pest control techniques. Because of economic and practical constraints (such as effective monitoring, determination of EIL's and low operating budgets), I argue that IPM may be an inappropriate model upon which to base research priorities. As an alternative, I remind both researchers and forest managers that many pest control techniques, such as biological control and silvicultural management, can be used effectively outside an IPM framework. Because forest managers ultimately dictate the level of support which is given to forest health management, it should be at the corporate level, rather than the research level, that the decision as to which pest management model to be followed is made.
Predictive Guardbanding: Program-Driven Timing Margin Reduction for GPUs

The energy efficiency of GPU architectures has emerged as an essential aspect of computer system design. In this article, we explore the energy benefits of reducing the GPU chip’s voltage to the safe limit, i.e., <inline-formula> <tex-math notation="LaTeX">$V_{\min }$ </tex-math></inline-formula> point, using predictive software techniques. We perform such a study on several commercial off-the-shelf GPU cards. We find that there exists about 20% voltage guardband on those GPUs spanning two architectural generations, which, if “eliminated” entirely, can result in up to 25% energy savings on one of the studied GPU cards. Our measurement results unveil a program dependent <inline-formula> <tex-math notation="LaTeX">$V_{\min }$ </tex-math></inline-formula> behavior across the studied applications, and the exact improvement magnitude depends on the program’s available guardband. We make fundamental observations about the program-dependent <inline-formula> <tex-math notation="LaTeX">$V_{\min }$ </tex-math></inline-formula> behavior. We experimentally determine that the voltage noise has a more substantial impact on <inline-formula> <tex-math notation="LaTeX">$V_{\min }$ </tex-math></inline-formula> compared to the process and temperature variation, and the activities during the kernel execution cause large voltage droops. From these findings, we show how to use kernels’ microarchitectural performance counters to predict its <inline-formula> <tex-math notation="LaTeX">$V_{\min }$ </tex-math></inline-formula> value accurately. The average and maximum prediction errors are 0.5% and 3%, respectively. The accurate <inline-formula> <tex-math notation="LaTeX">$V_{\min }$ </tex-math></inline-formula> prediction opens up new possibilities of a cross-layer dynamic guardbanding scheme for GPUs, in which software predicts and manages the voltage guardband, while the functional correctness is ensured by a hardware safety net mechanism.
Increasing the Yield of Lactuca sativa, L. in Glass Greenhouses through Illumination Spectral Filtering and Development of an Optical Thin Film Filter

With the increase in world population, the continued advances in modern greenhouse agriculture and plant growth practices are expected to help overcome the global problem of future food shortages. The next generation greenhouse design practices will need to address a range of issues, ranging from energy and land use efficiency to providing plant-optimized growth techniques. In this paper, we focus on investigating the optimum irradiation spectra matched to the lettuce species (Lactuca sativa, L.), commonly grown in greenhouse environments, in order to develop low-emissivity glass panes that maximize the biomass productivity of glass greenhouses. This low-emissivity glass passes the solar spectral components needed for crop growth, while rejecting other unwanted radiations. This could potentially lead to significant energy savings and other beneficial effects related to greenhouse climate control, in a range of climates. The experimental results show that substantial biomass productivity improvements in lettuce (up to approximately 14.7%) can be attained by using spectrally optimized illumination, instead of white light illumination. This optimized wavelength is then demonstrated as being used to develop an advanced metal-dielectric thin-film filter that produces the optimized illumination spectrum when exposed to sunlight.
A Novel Data-Driven Magnetic Resonance Spectroscopy Signal Analysis Framework to Quantify Metabolite Concentration

Developing tools for precise quantification of brain metabolites using magnetic resonance spectroscopy (MRS) is an active area of research with broad application in non-invasive neurodegenerative disease studies. The tools are mainly developed based on black box (data-driven), or basis sets approaches. In this study, we offer a multi-stage framework that integrates data-driven and basis sets methods. We first use truncated Hankel singular value decomposition (HSVD) to decompose free induction decay (FID) signals into single tone FIDs, as the data-driven stage. Subsequently, single tone FIDs are clustered into basis sets while using initialized K-means with prior knowledge of the metabolites, as the basis set stage. The generated basis sets are fitted with the magnetic resonance (MR) spectra while using a linear constrained least square, and then the metabolite concentration is calculated. Prior to using our proposed multi-stage approach, a sequence of preprocessing blocks: water peak removal, phase correction, and baseline correction (developed in house) are used.
Crystal structure and Hirshfeld surface analysis of 4,4′-(propane-1,3-diyl)bis(4H-1,2,4-triazol-1-ium) pentafluoridooxidovanadate(V)

In the structure of the title salt, second-order Jahn–Teller distortion of the coordination octahedra around V ions is reflected by coexistence of short V—O bonds and trans-positioned long V—F bonds, with four equatorial V—F distances being intermediate in magnitude. Hydrogen bonding of the anions is restricted to F-atom acceptors only, with particularly strong N–H⋯F interactions [N⋯F = 2.5072 (15) Å] established by axial and cis-positioned equatorial F atoms.
Comparing model-based control methods for simultaneous stiffness and position control of inflatable soft robots

Inflatable robots are naturally lightweight and compliant, which may make them well suited for operating in unstructured environments or in close proximity to people. The inflatable joints used in this article consist of a strong fabric exterior that constrains two opposing compliant air bladders that generate torque (unlike McKibben actuators where pressure changes cause translation). This antagonistic structure allows the simultaneous control of position and stiffness. However, dynamic models of soft robots that allow variable stiffness control have not been well developed. In this work, a model that includes stiffness as a state variable is developed and validated. Using the stiffness model, a sliding mode controller and model predictive controller are developed to control stiffness and position simultaneously. For sliding mode control (SMC), the joint stiffness was controlled to within 0.07 Nm/rad of a 45 Nm/rad command. For model predictive control (MPC) the joint stiffness was controlled to within 0.045 Nm/rad of the same stiffness command. Both SMC and MPC were able to control to within 0.5° of a desired position at steady state. Stiffness control was extended to a multiple-degree-of-freedom soft robot using MPC. Controlling stiffness of a 4-DOF arm reduced the end-effector deflection by approximately 50% (from 17.9 to 12.2cm) with a 4 lb (1.8 kg) step input applied at the end effector when higher joint stiffness (40 Nm/rad) was used compared with low stiffness (30 Nm/rad). This work shows that the derived stiffness model can enable effective position and stiffness control.
Online Password Guessability via Multi-Dimensional Rank Estimation

Human-chosen passwords are the a dominant form of authentication systems. Passwords strength estimators are used to help users avoid picking weak passwords by predicting how many attempts a password cracker would need until it finds a given password. In this paper we propose a novel password strength estimator, called PESrank, which accurately models the behavior of a powerful password cracker. PESrank calculates the rank of a given password in an optimal descending order of likelihood. PESrank estimates a given password's rank in fractions of a second---without actually enumerating the passwords---so it is practical for online use. It also has a training time that is drastically shorter than previous methods. Moreover, PESrank is efficiently tweakable to allow model personalization in fractions of a second, without the need to retrain the model; and it is explainable: it is able to provide information on why the password has its calculated rank, and gives the user insight on how to pick a better password. Our idea is to cast the question of password rank estimation in a probabilistic framework used in side-channel cryptanalysis. We view each password as a point in a $d$-dimensional search space, and learn the probability distribution of each dimension separately. The dimensions represent the base word, plus a dimension for each possible transformation such as adding a suffix or using a capitalization pattern. Using this model, password strength estimation is analogous to side-channel rank estimation. We implemented PERrank in Python and conducted an extensive evaluation study of it. We also integrated it into the registration page of a course at our university. Even with a model based on 905 million passwords, the response time was well under 1 second, with up to a 1-bit accuracy margin between the upper bound and the lower bound on the rank.
A review of manufacturing systems for introducing collaborative robots

—Industry 4.0 highlights a new industrial revolution for the manufacturing system. This work aims to provide a review of different types of manufacturing systems and present motivations of introducing collaborative robots into manufacturing. We start with a discussion about the existing research of human-robot collaboration as well as its perception and control strategies. Then, we give a review of the current applications of swarm robots in manufacturing. Finally, we propose some insights for future directions of human-robot society.
Analysis of supply response of black tiger shrimp production using Nerlove model

Article history: Received April 1 2020 Received in revised format April 1 2020 Accepted April 27 2020 Available online April 27 2020 This study aims to analyze the effect of black tiger shrimp price and other factors on the shrimp area in the Mekong Delta using the supply response function based on the Nerlovian partial adjustment model. Using quarterly panel data collected from four provinces (Ca Mau, Bac Lieu, Soc Trang, and Kien Giang) for the period of 2014 to 2017, the estimates in the supply response are obtained from Fixed-Effects (FE) method. Results indicate that the adaptive expectation hypothesis to the simple Cobweb model is likely to best fit the data. The estimates of the supply response model show that information used for expected price formation quickly responded in making a decision of black tiger shrimp production. In both the short run and long run, the expected price has a significant effect in directing black tiger shrimp farmers to formulate the supply response decision. The acreage response elasticity is more elastic. by the authors; licensee Growing Science, Canada 20 © 20
Regulation of T cell receptor (TCR)‐β locus allelic exclusion and initiation of TCR‐α locus rearrangement in immature thymocytes by signaling through the CD3 complex

During thymocyte differentiation, the T cell receptor (TCR)‐β genes are rearranged before the TCR‐α genes. Immature CD4−8− double‐negative thymocytes with a productive rearrangement of the TCR‐β locus are selected to continue maturation to the CD4+8+ double‐positive stage, driven by signals through the pre‐TCR. The signals through the pre‐TCR can be synchronized by injection of mice with anti‐CD3ϵ monoclonal antibody. Using this approach, we demonstrated coordinated induction of a triad of responses in immature thymocytes: arrest of V to DJ rearrangement in the TCR‐β locus, transient down‐regulation of rearrangement‐activating gene (RAG)‐1 and RAG‐2 transcripts, and initiation of germ‐line transcription of the TCR‐α locus. These results suggest that the transition from TCR‐β to TCR‐α locus rearrangement is controlled by signal transduction through the pre‐TCR.
Organic Manure Amended with Phosphate Solubilizing Bacteria on Soil Phosphorous Availability

Purpose : Combine use of phosphate solubilizing microorganisms and organic manure has greater agronomic utility as it could improve phosphorous (P) utilization efficiency through conversion of insoluble P to accessible forms. Therefore, the present study was conducted to assess the effect of different organic manures (poultry manure, goat manure and cow dung) with phosphate solubilizing microorganism on phosphorous availability. Research Method : The phosphate solubilizing bacterial (PSB) strain employed in this study was isolated from soil samples collected from agricultural lands in Matara District of Sothern Sri Lanka. The strain was identified as Enterobacter cancerogenous. Eight treatment combinations each replicated three times were used in the study. Findings : P availability of organic manure amended soils was progressively increased irrespectively the inoculation of PSB strain. The bulk of the increment occurred during the first 2 to 3 weeks of the incubation followed by slight reductions at the later stages. P availability of the soil amended with organic manures was significantly (P ≤ 0.05) higher than that of the control. Furthermore, the specified were much higher when PSB was inoculated to the soil amended with organic manures. PSB inoculants were used with poultry manure showed the highest P availability. Originality / Value : The availability of soil phosphorous is enhanced by combine use of organic manures and PSB inoculants; the practice is suggested to be employed in integrated nutrient management strategies.
Transcriptional responses of Solanum nigrum to methyl jasmonate and competition: a glasshouse and field study

Summary 1Field studies are needed to understand how plants respond to environmental stresses. However, transcriptional responses of plants interacting with biotic stressors, such as herbivores or competitors, have been measured primarily in controlled environments. Using oligonucleotide microarrays (with 60 and 568 genes), we determined how accurately glasshouse (GH) studies of transcriptional responses to methyl jasmonate (MeJA) elicitation and competition reflect the responses of Solanum nigrum L. plants grown under field conditions. We used MeJA to elicit herbivore resistance in a standardized manner. 2In field-grown plants (experiment I), 13 genes (from the 60-gene microarray) involved in defence and primary metabolism were significantly up- or downregulated by MeJA elicitation, which also increased the activity of trypsin proteinase inhibitors. 3We also grew S. nigrum with competitors in GH (experiment IIa) and field mesocosms (experiment IIb), and used the 60-gene microarray to examine the MeJA-elicited transcriptional changes. Both GH- and field-grown plants consistently regulated genes involved in oxylipin signalling and primary metabolism. However, the larger number of downregulated genes in GH-grown compared with field-grown plants suggests that field-grown plants are less sensitive to MeJA elicitation, probably because they are exposed to more abiotic stresses. 4The 60-gene microarray did not reveal any effects of competition, but the analysis with the 568-gene array identified many genes, some of which are involved in stress-signalling pathways and significantly altered only in plants grown with competitors. These alterations were associated with a significant decrease in fitness (number of fruits). 5We conclude that microarrays can be used successfully to monitor the gene expression of plants growing in natural environments, and we identify key genes that are regulated in plants interacting with competitors and herbivores. Whether these transcriptional responses mature into phenotypic changes should be determined by additional phenotypic analysis.
COVID-19 and Kawasaki Like Disease: The Known-Known, the Unknown-Known and the Unknown-Unknown

In the end of April nearly 100 cases of children aged between 6 month and 9 years with Kawasaki like disease have been reported (mostly in Europe) probably linked to COVID-19. We aim to sum up the known data about this new entity based on published data (in a case report, a serie of 8 cases and in newspapers and society statement) and using our knowledge of classical Kawasaki disease. It seems to be a post infectious disease with an onset between 2-4 weeks after the infection, probably in genetically predisposed children aged between 6 month to 17 years. A very rough estimation of incidence based on data from Bergamo, Italy, and New York State and a lot assumption is between 0.011% (95% CI:0.009-0.014%) - 0.31% (95% CI: 0.2-0.47%) of infected children. Clinical signs overlaps with Kawasaki disease in some children, but another feature is prominent gastrointestinal manifestations. For the 9 detailed patients most had incomplete presentation for Kawasaki disease (with a mean 1.7 (+/-1.2) criteria per patient for the 5 non fever criterion) and only one had a classical form. In some cases, presentation is closer to toxic shock syndrome or isolated myocarditis. Persistent fever seems to be constant and biological exploration are consistent with inflammation (elevated CRP, ferritin and D-Dimers). Management is described as supportive and children seem to improve rapidly, but can require cardiac or respiratory support. To date there is one death. Paediatricians and general practitioners need to be aware of these possible evolution following COVID-19 infection. However it seems to be rare and children are probably still spared from most morbidities and mortality linked to COVID-19 infection . There are need of published detailed cohorts to better delineate these entities.
A comparative study of fleece growth in Tasmanian Fine Merino and Wiltshire Horn ewes

1. From repeated fibre samplings and several skin biopsies on six Tasmanian Fine Merinos and eight Wiltshire Horn adult ewes variations in fibre diameter, fibre growth rate, and fibre regeneration or shedding frequency were measured over a period of 15 months. Slight differences were present in the treatment of the two breeds, but from the combined evidence of the live weights and fibre diameters maintained, it was concluded that these were negligible, that both breeds were under closely comparable conditions, and that their performance was at a moderately high and typical level for each breed. 2. In the Merinos fibre diameter (ca. 20 µ) fluctuated little during the period of observation, whereas in the Wiltshires it varied over a wide range from less than 40µ in winter to more than 80µ in summer. There were negligible differences between the three body regions, back, side, and belly, in the Merinos, but in the Wiltshires the belly grew markedly coarser fibres than the other two regions. 3. The fibre growth rate in the Merinos did not vary greatly from 7 to 8 mm. per 28 days throughout the period of observation or between the body regions. In the Wiltshires, fibre growth rate showed extreme variations from a minimum of about 3 mm. during the winter to a maximum of about 12 mm. per 28 days at the end of summer, with significant differences between the three body regions. However, in spite of these differences in the mode of growth, the total length of fibre grown per annum at the midside was approximately the same (10 cm.). Thus, were it not for fibre shedding, the Wiltshire Horn breed would grow a short-wool fleece.
Modelling of nutrient impacts in Port Phillip Bay : a semi-enclosed marine Australian ecosystem

This paper overviews the ecosystem model developed for the Port Phillip Bay Environmental Study. The model simulates the cycling of N, P and Si in the water-column, epibenthos and sediments, and is driven by a physical transport model. The integrated model is forced by exchanges with Bass Strait and by nutrient inputs from the Western Treatment Plant, rivers, and the atmosphere. The model has been calibrated and tested by using data from process studies, flux measurements and spatial surveys at a range of scales. It provides a picture of nitrogen cycling through the water and sediments on bay-wide annual scales, which emphasizes the role of denitrification. It also reproduces well the observed spatial and temporal variation under varying nutrient load regimes, and provides insights into the factors controlling regional phytoplankton blooms, including the interaction of nitrogen and silica in the western bay. The model is used to investigate the bay’s responses to changed nutrient loads, changes in sediment biogeochemistry, and marine pest invasion. The bay’s assimilative capacity for nitrogen is largely controlled by its sediment denitrification capacity. If nitrogen loads approach the limits of this capacity, a rapid onset of eutrophication is predicted.