Dynamic Fitness Research Articles

Wield the Power of Omni-channel Retailing Strategy: a Capability and Supply Chain Resilience Perspective

ABSTRACT Omni-channel strategy can be a powerful mechanism through which successful implementing organisations achieve higher levels of resilience to better survive disruptions. However, such potential benefits have been overlooked in existing literature with limited discussions on how omni-channel strategy can be exploited for uncertain business environments. We conduct an in-depth case study on a leading UK-based fashion retailer, Next , to explore the role of omni-channel strategy in helping organisations respond to the challenging retail landscape. Our results reveal that Next ’s ability to achieve vitality even during the COVID-19 pandemic is largely attributed to its well-executed omni-channel strategy, which enhances its supply chain resilience (SCRES) by maintaining a dynamic fit between the internal information processing capacity and the changing information processing needs induced by external conditions. Our study contributes to the omni-channel and SCRES literature and provides practical insights on how omni-channel strategy can be wielded for both stable and turbulent environments.

Exploring associations between physical fitness tests and a law enforcement specific Physical Ability Test using principal components analysis

ABSTRACT The purpose of this study was to determine relationships between components of physical fitness on performance in an occupation-specific physical ability test (PAT) for state patrol officers (women, n = 19; men, n = 256) using archived data. Physical fitness was assessed by 2.4 km run time (2.4 R), body fat % (BF), 1 min sit-up (SU), 1-min push-up (PU), the vertical jump (VJ), and the sit-and-reach test (SR). Principal components analysis (PCA) of the entire sample revealed that dynamic fitness (DF), related 2.4 R, SU, PU, VJ, & BF, explained 49% of variance in performance in the PAT. Lower back and hamstring flexibility explained a further 18% of variance. Law-enforcement agencies using a standard job-specific test to screen the occupational fitness of its members may use fitness tests to make fitness recommendations. Officers should prioritize developing aerobic fitness, muscular endurance, lower-body power, and flexibility to help meet the demands of occupational performance.

Regression and validation studies of the spread of novel COVID-19 in Iraq using mathematical and dynamic neural networks models: A case of the first six months of 2020

The dramatic spread of COVID-19 has put the entire world at risk. In this work, the spread of COVID-19 in Iraq has been studied. Due to the increase in the number of positive cases and deaths with this disease, huge pressure acts on the economy and world professionals worldwide. Therefore, building mathematical models to predict the growth of this serious disease is extremely useful. It helps to predict the future numbers of cases in Iraq. Therefore, dynamic neural networks and curve fitting techniques have been developed to construct such a model. Data from the World Health Organization (WHO) are used as a source for mathematical model construction. The period between 25, February to 18, June 2020 was used for regression, validation, and model construction of Dynamic Neural Networks (DNN). Nine samples (19 – 27 June 2020) were used for predicting the future infected and death cases. Descriptive statistical studies showed that the standard deviation varies sharply on June as compared with earlier months of 2020. Three mathematical models are proposed. Linear, polynomials (2nd, 3rd, and 4th orders), and exponential models are used to correlate confirmed infected cases (CIC) and confirmed death cases (CDC) that represent the dependent variables as function of time (independent variable). Nonlinear regression based on least-square method is used to estimate the coefficients of models. Exponential models were the most significant with 0.9964 and 0.9974 correlation coefficients for CIC and CDC, respectively. Validation analysis showed a significant deviation between real and predicted cases using exponential models. However, DNN models showed better response than exponential models. This is evidenced by objective and subjective comparisons. Finally, the CIC and CDC may be increased with time to approach 50000 and 2000 respectively at the end of June 2020.

Using evolutionary functional–structural plant modelling to understand the effect of climate change on plant communities

AbstractThe ‘holy grail’ of trait-based ecology is to predict the fitness of a species in a particular environment based on its functional traits, which has become all the more relevant in the light of global change. However, current ecological models are ill-equipped for this job: they rely on statistical methods and current observations rather than the mechanisms that determine how functional traits interact with the environment to determine plant fitness, meaning that they are unable to predict ecological responses to novel conditions. Here, I advocate the use of a 3D mechanistic modelling approach called functional–structural plant (FSP) modelling in combination with evolutionary modelling to explore climate change responses in natural plant communities. Gaining a mechanistic understanding of how trait–environment interactions drive natural selection in novel environments requires consideration of individual plants with multidimensional phenotypes in dynamic environments that include abiotic gradients and biotic interactions, and their combined effect on the different vital rates that determine plant fitness. Evolutionary FSP modelling explicitly simulates the trait–environment interactions that drive eco-evolutionary dynamics from individual to community scales and allows for efficient navigation of the large, complex and dynamic fitness landscapes that emerge from considering multidimensional plants in multidimensional environments. Using evolutionary FSP modelling as a tool to study climate change responses of plant communities can further our understanding of the mechanistic basis of these responses, and in particular, the role of local adaptation, phenotypic plasticity and gene flow.

Dynamic trial fitting of the cup in press-fit total hip arthroplasty, a feasibility study

Trial fitting of the cup during total hip arthroplasty (THA) is done by trial cups, which do not resemble the real press-fit obtained by the definitive implant. Our goal is to judge feasibility of the X-pander® in clinical practice ; a device developed to mimic the real press-fit obtained by the definitive cup, to ensure satisfactory press-fit. In this feasibility study 45 experienced orthopaedic surgeons from 7 European countries filled in a structured survey after 78 primary THA and 31 revision surgeries, using the X-pander instead of traditional trial cups. Primary outcomes were decision change concerning cup size or further reaming and increased confidence regarding cup insertion and size. Additionally, potential association between the primary outcomes and procedure (primary or revi- sion), bone quality and experience of the surgeon were evaluated. In 33.3% of the primary and 32.2% of the revision cases the X-pander measurement changed the deci- sion and further reaming or change of cup size was decided. In 61.5% and 58.1% of respectively the primary and revision THAs the X-pander was judged to give fairly to much more reliable information than traditional trial cups. The X-pander could lead to less additional screw fixation, as stated in 37.2% of the primary and 25.8% of the revision cases and to better cup insertion in respectively 50.0% and 51.6%. This study validates that the X-pander may be a suitable option for accurate sizing and assessment of the reamed acetabulum and could replace traditional trial cups in THA.

Analysis and design of fringe phase control system for scanning beam interference lithography

Scanning beam interference lithography (SBIL) is an advanced technology developed for manufacturing large-area diffraction grating at a nanometer-scale phase accuracy. To withstand environmental disturbances and maintain the interference fringes still relative to the substrate, SBIL requires high-precision phase control. We proposed a fringe phase control system with homodyne detection for SBIL. First, a homodyne detector is employed to achieve high-precision phase measurement, while ensuring the simplicity of the optics and high laser utilization. The time-varying nonlinear error in the measurement results is corrected by a dynamic ellipse fitting method. To reduce the latency effect, a lead controller is designed using the root locus method based on the model identification result. The lead controller considerably increases the control bandwidth while ensuring a sufficient phase margin, which further suppresses disturbances and stabilizes the interference fringes to within ∼1 / 60 of the fringe period. Wide-range phase tracking for perpendicular scanning with high accuracy is also verified through an experiment.

Development of Prototype Low-Cost QTSS™ Wearable Flexible More Enviro-Friendly Pressure, Shear, and Friction Sensors for Dynamic Prosthetic Fit Monitoring.

There is a current healthcare need for improved prosthetic socket fit provision for the masses using low-cost and simple to manufacture sensors that can measure pressure, shear, and friction. There is also a need to address society’s increasing concerns regarding the environmental impact of electronics and IoT devices. Prototype thin, low-cost, and low-weight pressure, shear, and loss of friction sensors have been developed and assembled for trans-femoral amputees. These flexible and conformable sensors are simple to manufacture and utilize more enviro-friendly novel magnetite-based QTSS™ (Quantum Technology Supersensor™) quantum materials. They have undergone some initial tests on flat and curved surfaces in a pilot amputee trial, which are presented in this paper. These initial findings indicate that the prototype pressure sensor strip is capable of measuring pressure both on flat and curved socket surfaces in a pilot amputee trial. They have also demonstrated that the prototype shear sensor can indicate increasing shear forces, the resultant direction of the shear forces, and loss of friction/slippage events. Further testing, amputee trials, and ongoing optimization is continuing as part of the SocketSense project to assist prosthetic comfort and fit.

Technical and tactical diagnosis model of table tennis matches based on BP neural network

BackgroundThe technical and tactical diagnosis of table tennis is extremely important in the preparation for competition which is complicated by an apparent nonlinear relationship between athletes’ performance and their sports quality. The neural network model provides a high nonlinear dynamic processing ability and fitting accuracy that may assist in the diagnosis of table tennis players’ technical and tactical skill. The main purpose of this study was to establish a technical and tactical diagnosis model of table tennis matches based on a neural network to analyze the influence of athletes’ techniques and tactics on the competition results.MethodsA three-layer Back Propagation (BP) neural network model for table tennis match diagnosis were established. A Double Three-Phase evaluation method produced 30 indices that were closely related to winning table tennis matches. A data sample of 100 table tennis matches was used to establish the diagnostic model (n = 70) and evaluate the predictive ability of the model (n = 30).ResultsThe technical and tactical diagnosis model of table tennis matches based on BP neural network had a high-level of prediction accuracy (up to 99.997%) and highly efficient in fitting (R2 = 0.99). Specifically, the technical and tactical diagnosis results indicated that the scoring rate of the fourth stroke of Harimoto had the greatest influence on the winning probability.ConclusionThe technical and tactical diagnosis model of table tennis matches based on BP neural network was highly accurate and efficiently fit. It appears that the use of the model can calculate athletes’ technical and tactical indices and their influence on the probability of winning table tennis matches. This, in turn, can provide a valuable tool for formulating player’s targeted training plans.

An Adaptive Cuckoo Search-Based Optimization Model for Addressing Cyber-Physical Security Problems

One of the key challenges in cyber-physical systems (CPS) is the dynamic fitting of data sources under multivariate or mixture distribution models to determine abnormalities. Equations of the models have been statistically characterized as nonlinear and non-Gaussian ones, where data have high variations between normal and suspicious data distributions. To address nonlinear equations of these distributions, a cuckoo search algorithm is employed. In this paper, the cuckoo search algorithm is effectively improved with a novel strategy, known as a convergence speed strategy, to accelerate the convergence speed in the direction of the optimal solution for achieving better outcomes in a small number of iterations when solving systems of nonlinear equations. The proposed algorithm is named an improved cuckoo search algorithm (ICSA), which accelerates the convergence speed by improving the fitness values of function evaluations compared to the existing algorithms. To assess the efficacy of ICSA, 34 common nonlinear equations that fit the nature of cybersecurity models are adopted to show if ICSA can reach better outcomes with high convergence speed or not. ICSA has been compared with several well-known, well-established optimization algorithms, such as the slime mould optimizer, salp swarm, cuckoo search, marine predators, bat, and flower pollination algorithms. Experimental outcomes have revealed that ICSA is superior to the other in terms of the convergence speed and final accuracy, and this makes a promising alternative to the existing algorithm.

In Situ Bio-Methanation Modelling of a Randomly Packed Gas Stirred Tank Reactor (GSTR)

In situ Bio-Methanation (BM) is a recently developed biogas upgrading technique which finds application also in the Power to Gas (P2G) field. In this study a novel configuration of BM digester, the randomly packed Gas Stirred Tank Reactor (GSTR), was modelled. A 49 L reactor, in thermophilic conditions (55 °C) and at atmospheric pressure, was filled up with random packing on which the microbial populations could adhere. The feedstock used was Second Cheese Whey (SCW), liquid waste of cheese factories, rich in lactose (38 g/L), and its flowrate was chosen to obtain a Hydraulic Retention Time (HRT) of 30 days. The process was analyzed for different hydrogen inlet flowrates of 10 mL/min and 50 mL/min. The produced biogas was also recirculated in the reactor in order to transfer, into the liquid phase, as much hydrogen as possible. The model parameters were estimated by means of stationary state information of the reactor working without hydrogen injection, while a dynamical fitting was necessary to evaluate the value of the hydrogen mass transfer coefficient during BM. The model well described the reactor behavior and, by means of a dimensionless analysis in which the numbers of Stanton (St) and β were defined, it was found out that the mass transfer coefficient is the limiting step of the process.

Distributed 3-D Path Planning for Multi-UAVs with Full Area Surveillance Based on Particle Swarm Optimization

Collision-free distributed path planning for the swarm of unmanned aerial vehicles (UAVs) in a stochastic and dynamic environment is an emerging and challenging subject for research in the field of a communication system. Monitoring the methods and approaches for multi-UAVs with full area surveillance is needed in both military and civilian applications, in order to protect human beings and infrastructure, as well as their social security. To perform the path planning for multiple unmanned aerial vehicles, we propose a trajectory planner based on Particle Swarm Optimization (PSO) algorithm to derive a distributed full coverage optimal path planning, and a trajectory planner is developed using a dynamic fitness function. In this paper, to obtain dynamic fitness, we implemented the PSO algorithm independently in each UAV, by maximizing the fitness function and minimizing the cost function. Simulation results show that the proposed distributed path planning algorithm generates feasible optimal trajectories and update maps for the swarm of UAVs to surveil the entire area of interest.

Estimation of COVID-19 outbreak size in Harbin, China.

Since the first level response to public health emergencies was launched on January 25, 2020, in Heilongjiang province, China, the outbreak of COVID-19 seems to be under control. However, an outbreak of COVID-19 caused by imported cases developed in Harbin during April 2020. A mathematical model is established to investigate the transmission of COVID-19 in Harbin. Based on the dynamical analysis and data fitting, the research investigates the outbreak of COVID-19 in Harbin and estimates the outbreak size of COVID-19 in Harbin. The outbreak size estimated of COVID-19 in Harbin reaches 174, where 54% of infected cases were identified while 46% of infected cases were not found out. We should maintain vigilance against unfound infected people. Our findings suggest that the effective reproduction number decreased drastically in contrast with the value of 3.6 on April 9; after that the effective interventions were implemented by the Heilongjiang province government. Finally, the effective reproduction number arrived at the value of 0.04 which is immensely below the threshold value 1, which means that the Heilongjiang province government got the outbreak of COVID-19 in Harbin under control.

Application of piggy-back lens in the correction of severe keratoconus: A case study.

This is a case study on the application of a piggy-back lens in the correction of severe keratoconus. From the results of general eye examination, refractive state examination, and corneal morphology examination on the patient, it was determined that corneal protrusion and deformation of the right eye were obvious. The right eye was corrected using a piggy-back lens and the left eye with a rigid gas-permeable contact lens (RGPCL) alone. The right-eye lens fit well and the lens coverage was good. Both the static and dynamic fit results for the left-eye lens were good. After wearing the glasses for one month, the patient attended a review and stated that the lenses were comfortable to wear. The patient's vision was good after wearing the lenses. No obvious congestion was found in the conjunctiva under a slit lamp. The effects on both eyes of wearing RGPCLs were favorable. The corneal curvature reduced and the corneal thickness only changed to a small degree. For keratoconus patients, application of a piggy-back lens can improve corrected visual acuity, comfort levels, and safety, prolong the wearing time, and enhance the effect of orthokeratology.

Dynamic simulation and parameter fitting method of cometary dust based on machine learning

Dynamic simulation and parameter fitting method of cometary dust based on machine learning

Optimal Job Scheduling With Resource Packing for Heterogeneous Servers

Jobs in modern computing clusters have highly diverse processing duration and heterogeneous resource requirements. In this paper, we consider the problem of job scheduling for a computing cluster comprised of multiple servers with heterogeneous computation resources, while taking the different resource demands of the jobs into account. Our focus is to achieve a low overall job response time for the system (which is also referred to as the job flowtime) while providing fairness between small and large jobs. Since the job flowtime minimization problem under multiple (even homogeneous) servers are known to be NP-hard, we propose an approximation algorithm to tackle the original online scheduling problem by adopting the recently-proposed notion of fractional job flowtime as a surrogate objective for minimization. For the general online job arrival case with multi-dimensional resource requirements, we apply Online Convex Optimization (OCO) techniques to design the corresponding scheduling algorithm with performance guarantees. In the single-dimensional resource setting, we show that the dynamic fit of the online version of our approximate algorithm grows only sublinearly with respect to time and derive a bound for its dynamic regret when comparing to its offline counterpart. While the baseline version of our proposed scheduling algorithm assumes the possibilities of job preemption and job migration across different servers, we show that the extent of job preemption and migration can be well controlled by augmenting the objective function with the corresponding switching costs.

In-situ Cu-doped carbon-supported catalysts applied for high-salinity polycarbonate plant wastewater treatment and a coupling application

• Cu and N doped biochar (Cu@NBC) was fabricated from the waste adsorbent. • The Cu@NBC/PDS system equipped with resistance to anions in high-salinity wastewater. • Cu@NBC can be uniformly deposited onto the PSF membrane. • Cu@NBC/PSF membrane exhibited instantaneous catalytic performance. • Electron-transfer process can inactivate bacteria to relieve membrane fouling. Organic pollutants decomposition in high-salinity wastewater is still a challenge for environmental restoration due to the inhibitory effects results from the consumption of radicals by anions. Herein, we demonstrated a non-radical oxidation process via the peroxydisulfate (PDS) activation rather than photocatalysis by the Cu 2+ adsorbed adsorbent-based nitrogen doped biochar (Cu@NBC) for efficiently decontaminating polycarbonate plant wastewater (PCW). After the pyrolysis, the Cu 2+ in the waste biosorbent were reduced to Cu 2 O, and the N-doping improved the fixation of Cu and the formation of Cu 2 O. Through both dynamic fitting and characterization analysis, the critical role of Cu 2 O in PDS activation rather than photocatalysis was revealed for the first time. Different from always reported 1 O 2 dominated non-radical process, an electron-transfer mechanism involving surface metastable species was proved to play a key role in the Cu@NBC/PDS system. Benefit from the electron-transfer process, the Cu@NBC/PDS system equipped with high resistance to the anions in high-salinity wastewater. The results indicated that BPA as well as chemical oxygen demand (COD) could be effective removal within 90 min. We further deposited the activator on an ultrafiltration membrane and exhibited a rapid oxidation of BPA as the wastewater passed through the filter, and the composite membrane can effectively inactivate bacteria, which will provide a safety strategy for mitigation of membrane fouling.

Precise Dynamical Masses and Orbital Fits for β Pic b and β Pic c

Abstract We present a comprehensive orbital analysis to the exoplanets β Pictoris b and c that resolves previously reported tensions between the dynamical and evolutionary mass constraints on β Pic b. We use the Markov Chain Monte Carlo orbit code orvara to fit 15 years of radial velocities and relative astrometry (including recent GRAVITY measurements), absolute astrometry from Hipparcos and Gaia, and a single relative radial velocity measurement between β Pic A and b. We measure model-independent masses of M Jup for β Pic b and 8.3 ± 1.0 M Jup for β Pic c. These masses are robust to modest changes to the input data selection. We find a well-constrained eccentricity of 0.119 ± 0.008 for β Pic b, and an eccentricity of for β Pic c, with the two orbital planes aligned to within ∼05. Both planets’ masses are within ∼1σ of the predictions of hot-start evolutionary models and exclude cold starts. We validate our approach on N-body synthetic data integrated using REBOUND. We show that orvara can account for three-body effects in the β Pic system down to a level ∼5 times smaller than the GRAVITY uncertainties. Systematics in the masses and orbital parameters from orvara’s approximate treatment of multiplanet orbits are a factor of ∼5 smaller than the uncertainties we derive here. Future GRAVITY observations will improve the constraints on β Pic c’s mass and (especially) eccentricity, but improved constraints on the mass of β Pic b will likely require years of additional radial velocity monitoring and improved precision from future Gaia data releases.

Ways to win: strategic choices, institutions and performance in sub-Saharan Africa

PurposeThe purpose of this study is to analyse the effects of market-based and nonmarket-based strategies on firm performance in African countries. This study also investigates host country institutions' effect on the relationship between firm strategies and performance in these countries.Design/methodology/approachData of 1,276 firms in five African countries were obtained from two different sources: The World Bank Enterprise Database and The Global Competitiveness Report. Two-stage least squares regression was applied.FindingsBoth market-based strategies and corporate political activity (CPA)improve firm performance in the African countries included in the analysis. Institutional development also has a direct positive impact on firm performance. However, the effect of CPA weakens as the host country shifts towards more efficient, market-oriented institutions. Furthermore, the results show that local African firms benefit more from institutional development than foreign firms.Originality/valueThe paper confirms and extends our understanding of the dynamic fit between institutions and strategy by highlighting the moderating role of institutional development on CPA and market-based strategies in enhancing firm performance.

Preparation and characterization of 96-well microplates coated with molecularly imprinted polymer for determination and biosimilarity assessment of recombinant human erythropoietin

Synthesis and applications of molecularly imprinted polymers (MIP) are rapidly growing. In this study, a biomimetic MIP was prepared through silanes polymerization on the surface of 96-well microplates using recombinant human erythropoietin-alfa (rhEPO) as a template molecule. The rhEPO was immobilized onto the plate surface using bi-functional cross-linker and a thin imprinted layer following sol-gel procedure was constructed. After template extraction, uniform three-dimensional cavities compatible with the configuration of rhEPO were obtained. The rhEPO-MIP preparation was optimized using 2-level factorial design and response surface design where polymerization time and interactions between the different variable were found to be the most significant factors. Size-exclusion chromatography (SEC) was used to monitor the stability of the rhEPO under the investigated polymerization conditions. Determination of rhEPO using the MIP microplate showed good dynamic response fitting to the 4 PL regression model (0.9962) over a concentration range of 10.00 - 100.00 ng mL−1. Adsorption of rhEPO onto MIP followed the Langmuir isotherm model (r = 0.9957, χ2 =0.02786) with pseudo-second-order kinetics (r = 0.9984). The surface of the rhEPO-MIP was characterized using scanning electron microscopy (SEM) while step-by-step surface modification was tracked using Fourier transform infrared (FTIR) spectroscopy. The rhEPO-MIP was able to distinguish between the rhEPO-alfa template and modified rhEPO molecules; rhEPO-beta, hyperglycosylated and pegylated forms (imprinting factors < 2) and in the commonly used formulation additive human serum albumin (HSA) (R% = 113.96 -95.22%). The rhEPO-MIP was applied to compare the receptor-binding pattern to rhEPO and its biosimilars / structural analogues. The results were cross-validated using the conventional assay protocol (RP-HPLC and ELISA) and an acceptable correlation was observed with RP-HPLC (maximum deviation is 7.78%). This work confirmed the applicability of rhEPO-MIP with its unique binding features for batch release, stability and biosimilarity assessment as well as subsequent evaluation of batch-to-batch consistency during bioproduction of target analytes.

Cancer Cell Fitness Is Dynamic.

Several phenotypes that impact the capacity of cancer cells to survive and proliferate are dynamic. Here we used the number of cells in colonies as an assessment of fitness and devised a novel method called Dynamic Fitness Analysis (DynaFit) to measure the dynamics in fitness over the course of colony formation. DynaFit is based on the variance in growth rate of a population of founder cells compared with the variance in growth rate of colonies with different sizes. DynaFit revealed that cell fitness in cancer cell lines, primary cancer cells, and fibroblasts under unhindered growth conditions is dynamic. Key cellular mechanisms such as ERK signaling and cell-cycle synchronization differed significantly among cells in colonies after 2 to 4 generations and became indistinguishable from randomly sampled cells regarding these features. In the presence of cytotoxic agents, colonies reduced their variance in growth rate when compared with their founder cell, indicating a dynamic nature in the capacity to survive and proliferate in the presence of a drug. This finding was supported by measurable differences in DNA damage and induction of senescence among cells of colonies. The presence of epigenetic modulators during the formation of colonies stabilized their fitness for at least four generations. Collectively, these results support the understanding that cancer cell fitness is dynamic and its modulation is a fundamental aspect to be considered in comprehending cancer cell biology and its response to therapeutic interventions. SIGNIFICANCE: Cancer cell fitness is dynamic over the course of the formation of colonies. This dynamic behavior is mediated by asymmetric mitosis, ERK activity, cell-cycle duration, and DNA repair capacity in the absence or presence of a drug.