Miracle-dz/UniFAR-FTUs huggingface dataset:
FEA-based tracking control of flexible body switching dynamic structure

Abstract In dynamically switched systems with unknown switching signal, the control system is conventionally designed based on the worst switching scenario to ensure system stability. Such conservative design demands excessive control effort in less critical switching configurations. In the case of continuum mechanics systems, such excessive control inputs result in increased structural deformations and resultant modeling uncertainties. These deformations alter differential equations of motion which cripple the task of control. In this paper, a new approach for tracking control of uncertain continuum mechanics multivariable systems undergoing switching dynamics and unknown time delay has been proposed. Control algorithm is constructed based on the mathematical rigid model of the plant and a Common Lyapunov Function (CLF) is proposed upon sliding hyperplane regarding all switching configurations. Considering the model-based nature of sliding mode control (SMC) and inevitable uncertainties induced from modeling simplifications of continuum system or parameter evaluation errors, Finite Element Analysis (FEA) is utilized to approximate total model uncertainties. To obtain robust stability, instead of conventional switching functions in the construction of control law, the control inputs are selected such that system dynamics reside within stability bounds which are calculated based on the Lyapunov asymptotic stability criterion. Therefore, the unwanted chattering issue caused by continuous switching is not observed in control input signals. Eventually, the accuracy of the proposed method has been verified through the student version of ANSYS® mechanical APDL-based simulations and its effectiveness has been demonstrated in multiple operating conditions.
The Global Amylase Research Trend in Food Science Technology: A Data-Driven Analysis

ABSTRACT Amylase (E.C.3.2.1.1) is one of the most important enzymes, of great significance for biotechnology. With the increasing number of studies of amylases, it is urgent to comprehensively gasp the future research trend of amylase, which promotes research and applications of amylase. Besides, the understand the past, present and future of amylase research helps scientists to further pursuit frontier of amylase research in global scale. Therefore, we used data-driven analysis method to present the hot points and further trends of amylase, which obtains data from Web of Science database. We comparatively analyzed the research hot points of amylases from several scales: Publication trends, Disciplinary trends, Interdisciplinary research tendency, and Collaborations trends. The results show that the research of amylase has good continuity on research contents, containing applications of amylases, the catalytic models of amylases, and the amylase-related nutrition and metabolism. Amylase research in terms of “Nutrition & dietetics” and “Agriculture” fields may be the further new disciplinary trends. Additionally, the intensive collaboration of amylases focuses on structural function, chemical, and physical properties of amylase.
Automation of the Peak Fitting Method in Bone FTIR Microspectroscopy Spectrum Analysis: Human and Mice Bone Study

FTIR microspectroscopy (FTIRM) is a commonly used nondestructive method to characterise thin bone sections. However, spectrum analysis methods are often highly sensitive to small variations (e.g., boundary limits), thus implying a time-consuming and redundant analysis process. To solve this issue, software has been developed based on several algorithms to automate the analysis. Furthermore, a rigorous framework has been established concerning the peak fitting method to obtain the systematic best potential solution. Validation of the automatic method has been performed by comparison with the manual method. Results and validation proved the reliability of the automatic process. The developed algorithms provide the means necessary to fully compare the results between bone FTIRM studies and between different laboratories.
Speckle tracking ultrasonography as a new tool to assess diaphragmatic function: a feasibility study

A reliable method of measuring diaphragmatic function at the bedside is still lacking. Widely used two-dimensional (2D) ultrasonographic measurements, such as diaphragm excursion, diaphragm thickness, and fractional thickening (FT) have failed to show clear correlations with diaphragmatic function. A reason for this is that 2D ultrasonographic measurements, like FT, are merely able to measure the deformation of muscular diaphragmatic tissue in the transverse direction, while longitudinal measurements in the direction of contracting muscle fibres are not possible. Speckle tracking ultrasonography, which is widely used in cardiac imaging, overcomes this disadvantage and allows observations of movement in the direction of the contracting muscle fibres, approximating muscle deformation and the deformation velocity. Several studies have evaluated speckle tracking as a promising method to assess diaphragm contractility in healthy subjects. This technical note demonstrates the feasibility of speckle tracking ultrasonography of the diaphragm in a group of 20 patients after an aortocoronary bypass graft procedure. The results presented herein suggest that speckle tracking ultrasonography is able to depict alterations in diaphragmatic function after surgery better than 2D ultrasonographic measurements.
Almost second-order uniformly convergent numerical method for singularly perturbed convection–diffusion–reaction equations with delay

This paper deals with the numerical treatment of time-dependent singularly perturbed convection–diffusion–reaction equations with delay. In the considered equations, the highest order derivative term is multiplied by a perturbation parameter, ε taking arbitrary value in the interval . For small ε, the solution of the equations exhibits a boundary layer on the right side of the spatial domain. The considered equations contain a small delay on the convection and reaction terms of the spatial variable. The terms involving the delay are approximated using the Taylor series approximation. The resulting singularly perturbed parabolic convection–diffusion–reaction equations are treated using the Crank Nicolson method in time derivative discretization and the mid-point upwind finite difference method on piecewise uniform Shishkin mesh for the space variable derivative discretization. The stability and the uniform convergence of the scheme are investigated well. The proposed scheme gives almost first-order convergence in the spatial direction. The Richardson extrapolation technique is applied to accelerate the rate of convergence of the scheme in the spatial direction to order almost two. To validate the applicability of the scheme, numerical examples are presented and solved for different values of the perturbation parameter and delay parameter.
‘Trying to make it matter’: The challenges of assimilating a resettlement culture into a ‘local’ prison

As part of the Transforming Rehabilitation reforms, 70 ‘local’ prisons in England and Wales were re-designated as resettlement prisons, in order to provide additional through-the-gate support to individuals serving short sentences. Drawing on staff and prisoner interviews in one case study resettlement prison, this article considers what challenges were involved with implementing a resettlement culture in a local prison. Findings first outline factors inhibiting the resettlement status of the prison; these include a tension between attempts to implement a more expansive resettlement remit into the prison, while also fulfilling more long-standing core institutional duties; the size and churn of the prison population; wide-scale apathy caused by change fatigue; and government austerity policies which caused significant difficulties in the day-to-day staffing of the prison. This article then turns to practitioner responses to the re-designation, finding that practitioners interpreted resettlement in two limited ways: top-down managerial attempts to instil a wider resettlement culture into the prison, and resistance from prison officers who felt unwilling or unable to expand their roles beyond custodial and security concerns. This article concludes by outlining how this set of inter-related barriers frustrated staff and prisoners alike, eroding a sense of hope and purpose and impeding true cultural change.
Investigating the alignment to mathematical modelling of teacher-created mathematical modelling activities available online

ABSTRACT Mathematical modelling has garnered national and international interest due to its importance. Mathematical modelling can develop students’ mathematical understandings, teamwork and communication practices. The ability for teachers to select appropriate mathematical modelling tasks is important to ensure the benefits listed for students are realized. The purpose of this study was to investigate the alignment to mathematical modelling of teacher-created curricular resources available through the Teachers Pay Teachers (TPT) website. The TPT website, where teachers can buy and sell resources, is used by millions of teachers each year. Through this research, we sought to investigate if the curricula that resulted in searches for mathematical modelling are aligned to mathematical modelling. We found that about 6% of the curricula resources in our searches could be considered mathematical modelling. These curricular resources are described. We also categorized the curricular resources from the searches, that were not coded as mathematical modelling. This provides insights into teachers’ misconceptions of mathematical modelling. Implications for teachers and researchers for issues to be considered as the prevalence of online resources increases are discussed.
Influence of Environmental Noise on Quality Control of HVAC Devices Based on Convolutional Neural Network

Testing the quality of manufactured products based on their sound expression is becoming popular nowadays. To maintain low production costs, the testing is processed at the end of the assembly line. Such measurements are affected considerably by the factory noise even though they are performed in anechoic chambers. Before designing the quality control algorithm based on a convolutional neural network, we do not know the influence of the factory noise on the success rate of the algorithm that can potentially be obtained. Therefore, this contribution addresses this problem. The experiments were undertaken on a synthetic dataset of heat, ventilation, and air-conditioning devices. The results show that classification accuracy of the decision-making algorithm declines more rapidly at a high level of environmental noise.
Recent Advances of Nanoremediation Technologies for Soil and Groundwater Remediation: A Review

Nanotechnology has been widely used in many fields including in soil and groundwater remediation. Nanoremediation has emerged as an effective, rapid, and efficient technology for soil and groundwater contaminated with petroleum pollutants and heavy metals. This review provides an overview of the application of nanomaterials for environmental cleanup, such as soil and groundwater remediation. Four types of nanomaterials, namely nanoscale zero-valent iron (nZVI), carbon nanotubes (CNTs), and metallic and magnetic nanoparticles (MNPs), are presented and discussed. In addition, the potential environmental risks of the nanomaterial application in soil remediation are highlighted. Moreover, this review provides insight into the combination of nanoremediation with other remediation technologies. The study demonstrates that nZVI had been widely studied for high-efficiency environmental remediation due to its high reactivity and excellent contaminant immobilization capability. CNTs have received more attention for remediation of organic and inorganic contaminants because of their unique adsorption characteristics. Environmental remediations using metal and MNPs are also favorable due to their facile magnetic separation and unique metal-ion adsorption. The modified nZVI showed less toxicity towards soil bacteria than bare nZVI; thus, modifying or coating nZVI could reduce its ecotoxicity. The combination of nanoremediation with other remediation technology is shown to be a valuable soil remediation technique as the synergetic effects may increase the sustainability of the applied process towards green technology for soil remediation.
Rate‐dependent fracture modeling of bituminous media using nonlinear viscoelastic cohesive zone with Gaussian damage function

Cracking of bituminous materials is one of the main distresses that results in roadway failure. As bituminous media are highly rate‐dependent at intermediate temperatures due to the viscoelastic nature of the binding materials, cracking is also highly rate‐dependent viscoelastic. This presents a clear need to address the phenomenon in the modeling‐analysis process for a more accurate design of mixtures and pavements. This study proposes an advanced computational modeling method to predict complex rate‐dependent cracking in bituminous materials and pavements. In particular, we explored an extrinsic nonlinear viscoelastic cohesive zone (NVCZ) integrated with Gaussian damage evolution. To examine the modeling method and its validity, two modeling efforts in multiple length scales were made: mm‐scale material‐level modeling and cm‐m scale hierarchical modeling that linked the mixture with pavement structure. The NVCZ modeling with Gaussian damage evolution successfully predicted material cracking and damage at different loading rates by using a single set of fracture parameters. This implies that the complex cracking behavior of bituminous materials can be characterized by material‐specific fracture parameters that can be identified by a simple fracture test. The pavement modeling through a parametric analysis demonstrated the sensitivity and capability of the modeling to effectively capture the interrelated influence of several core design variables, such as traffic, material properties, and layer configurations, all of which affect pavement responses and damage evolution. The computational modeling presented in this study has the scientific rigor to predict nonlinear rate‐dependent viscoelastic fracture of bituminous materials and pavements with a good modeling efficiency by significantly reducing laboratory tests.
Performance Evaluation of Selenite (SeO32−) Reduction by Enterococcus spp.

Lactic acid bacteria (LAB) such as Enterococcus spp. have an advantage over several bacteria because of their ability to easily adapt to extreme conditions which include high temperatures, highly acidic or alkaline conditions and toxic metals. Although many microorganisms have been shown to reduce selenite (SeO32−) to elemental selenium (Se0), not much work has been done on the combined effect of Enterococcus spp. In this study, aerobic batch reduction of different selenite concentrations (1, 3 and 5 mM) was conducted using Enterococcus hermanniensis sp. and Enterococcus gallinarum sp. (3.5 h, 35 ± 2 °C, starting pH > 8.5). Results from the experiments showed that the average reductions rates were 0.608, 1.921 and 3.238 mmol·(L·h)−1, for the 1, 3 and 5 mM SeO32− concentrations respectively. In addition, more selenite was reduced for the 5 mM concentration compared to the 1 and 3 mM concentrations albeit constant biomass being used for all experiments. Other parameters which were monitored were the glucose consumption rate, protein variation, pH and ORP (oxidation reduction potential). TEM analysis was also conducted and it showed the location of electron-dense selenium nanoparticles (SeNPs). From the results obtained in this study, the authors concluded that Enterococcus species’s high adaptability makes it suitable for rapid selenium reduction and biosynthesis of elemental selenium.
A review on the design and development of photocatalyst synthesis and application in microfluidic reactors: challenges and opportunities

Abstract Microfluidics is an emerging branch of science that has significant applications in various fields. In this review paper, after a brief introduction to the concept of photocatalysis, nanoparticle preparation methods and film formation techniques have been studied. Nanoparticle synthesis in microfluidic systems and microreactor types for on-chip photocatalyst synthesis and challenges of nanoparticles handling in microsystems have been reviewed. To resolve particle polydispersity and microchannel clogging, a good suggestion can be the use of droplet-based microreactors. The configurative designs for the microfluidic reactor with immobilized photocatalysts, their applications, and their challenges have been comprehensively addressed. The three main challenges ahead the immobilized photocatalytic microfluidic reactors are optimal light distribution, prevention of the recombination of photogenerated electrons and holes, and improved mass transfer. Internal light-emitting diodes with a waveguide can resolve the number one challenge of photocatalysis application in optofluidic reactors, that is, light distribution.
Imaging subsurface orebodies with airborne electromagnetic data using a recurrent neural network

Conventional interpretation of airborne electromagnetic data has been conducted by solving the inverse problem. However, with recent advances in machine learning (ML) techniques, a one-dimensional (1D) deep neural network inversion that predicts a 1D resistivity model using multi-frequency vertical magnetic fields and sensor height information at one location has been applied. Nevertheless, bacause the final interpretation of this 1D approach relies on connecting 1D resistivity models, 1D ML interpretation has low accuracy for the estimation of an isolated anomaly, as in conventional 1D inversion. Thus, we propose a two-dimensional (2D) interpretation technique that can overcome the limitations of 1D interpretation, and consider spatial continuity by using a recurrent neural network (RNN). We generated various 2D resistivity models, calculated the ratio of primary and induced secondary magnetic fields of vertical direction in ppm scale using vertical magnetic dipole source, and then trained the RNN using the resistivity models and the corresponding electromagnetic (EM) responses. To verify the validity of 2D RNN inversion, we applied the trained RNN to synthetic and field data. Through application of the field data, we demonstrated that the design of the training dataset is crucial to improve prediction performance in a 2D RNN inversion. In addition, we investigated changes in the RNN inversion results of field data dependent on the data preprocessing. We demonstrated that using two types of data, logarithmic transformed data and linear scale data, which having different patterns of input information can enhance the prediction performance of the EM inversion results.
Hydrothermal synthesis of copper (II) and Nickel (II) nano complexes with unsymmetric tetradentate Schiff base ligand. New precursors for preparation of copper (II) and nickel (II) oxides nano-particles

Two new nano particles of copper (II) and nickel (II) complexes, [Cu(cd5Clsalen)] (1) and [Ni(cd5Clsalen)] (2) with unsymmetrical tetradentate Schiff base ligand cd5Clsalen={methyl-2-[N-[2-(2-hydroxy-5-choloro-2phenyl) methylidynetrilo]ethyl}amino-1-cyclopentenedithiocarboxylate, were synthesized by hydrothermal method. These compounds were characterized by a variety of physic-chemical techniques via. scanning electron microscopy (SEM), X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (IR) and elemental analysis. The complexes (in bulk) have a NNOS coordination sphere, with the two nitrogens coordinated in a cis configuration. The coordination around nickel center is essentially square-planar with a small tetrahedral distortion and the geometry around the copper center is square planar. Nano-particles of Copper (II) and Nickel (II) oxides have been prepared by calcination of two different Copper (II) and Nickel (II) complexes at 450 oC that were characterized by scanning electron microscopy (SEM), X-ray powder diffraction (XRD) and IR spectroscopy. The average size of the particles was estimated from the Sherrer formula. This study demonstrates the Schiff base complexes may be suitable precursors for the preparation of nanoscale materials with different and interesting morphologies.
The local implications of a macrostrategy on the villagers and the environment

Nature subcontracted mankind for temporary management stipulating a rigor that does not disregard the smallest details because this is where the difference between perfection and riskiness lies, which inevitably leads to disasters. It establishes binding general rules and local imperatives to be fulfilled otherwise it takes back the reins. For this reason, anthropic macrostrategies must frame their priorities and objectives according to a sustainable social-ecosystem. Here, we evaluate the environmental effect of the triggered landuse change of the metropolis-portuary-industrial park of Tangier (Strait of Gibraltar) on ecosystem services (i.e. vegetation and water) and anticipate their interactions with indigenous villagers. We established a multifactorial analysis including long-term (1985-2021) land-use dynamic assessment, 16-years pixel-based Mann-Kendall phenological trend, EPM soil erosion modelling and assessment of the total volumes of the detached soil, and an NDVI/NDWI monthly drought monitoring. Later, we compared these outcomes with a social survey with 171 households to analyze their living conditions, and their environmental perception and attitude. We have observed that anthropogenic intervention is the precursor of erosion which is likely to worsen natural weaknesses, which are already at the origin of a massive potential loss of soil estimated at 1.2 kg/m²/year. We correlated the negative phenological trend with the lane of the roads and infrastructure and we observed that severe drought episodes are long, frequent and at short intra and interannual intervals. We found a statistically significant association between the low level of education and the rural seclusion with the environmental degradation and the unavailability of water which can evoke serious risks. We anticipate the urgent need for an inclusive reform that implements a behavioral culture, encourages education, and creates social facilitation to build an upward spiral that produces better conditions and more opportunities for the rural society. Broadly, Managers should integrate scientific instructions to master the details and continuously improve macrostrategies to achieve integral and lasting success.
Electrocatalytic Activities towards the Electrochemical Oxidation of Formic Acid and Oxygen Reduction Reactions over Bimetallic, Trimetallic and Core–Shell-Structured Pd-Based Materials

The structural design of nanosized electrocatalysts is extremely important for cathodic oxygen reduction reactions (ORR) and anodic oxidation reactions in small organic compounds in direct fuel cells. While Pt is still the most commonly used electrode material for ORR, the Pd electrocatalyst is a promising alternative to Pt, because it exhibits much higher electrocatalytic activity towards formic acid electrooxidation, and the electrocatalytic activity of ORR on the Pd electrode is the higher than that of all other precious metals, except for Pt. In addition, the mass activity of Pt in a core–shell structure for ORR can be improved significantly by using Pd and Pd-based materials as core materials. Herein, we review various nanoscale Pd-based bimetallic, trimetallic and core–shell electrocatalysts for formic acid oxidation and ORR of polymer electrolyte fuel cells (PEFCs). This review paper is separated into two major topics: the electrocatalytic activity towards formic acid oxidation over various Pd-based electrocatalysts, and the activity of ORR on Pd-based materials and Pd core–Pt shell structures.