Miracle-dz/UniFAR-FTUs huggingface dataset:
Does gamified interaction build a strong consumer-brand connection? A study of mobile applications

In recent times gamification has increasingly been used by brands through smartphones to interact effectively with their consumers. The core assumption for creating gamified environment is that it will develop engagement with the consumer and motivate them to use their product or services. However, beyond this assumption, there is dearth empirical evidence regarding how much effective these gamified features are in engaging consumers. Therefore, this research analyses the relationship between flow, brand engagement, self-brand connection and brand usage intent among consumers (N = 360)of two gamified mobile applications. The findings show that the multidimensional construct flow formed by five dimensions i.e. challenge, feedback, autonomy, immersion, and interaction positively associates with cognitive brand engagement and emotional brand engagement. Additionally, both these forms of brand engagement further strengthen consumers’ brand connection and motivate them for further use. These results imply that gamified environment can augment consumer engagement with brand and further increase usage intention. Therefore, gamification can be an effective technique in brand management and brand managers can use it to strengthen relationship with consumers and increasing possibility of using their brands.
An Overdispersed Black-Box Variational Bayesian–Kalman Filter with Inaccurate Noise Second-Order Statistics

Aimed at the problems in which the performance of filters derived from a hypothetical model will decline or the cost of time of the filters derived from a posterior model will increase when prior knowledge and second-order statistics of noise are uncertain, a new filter is proposed. In this paper, a Bayesian robust Kalman filter based on posterior noise statistics (KFPNS) is derived, and the recursive equations of this filter are very similar to that of the classical algorithm. Note that the posterior noise distributions are approximated by overdispersed black-box variational inference (O-BBVI). More precisely, we introduce an overdispersed distribution to push more probability density to the tails of variational distribution and incorporated the idea of importance sampling into two strategies of control variates and Rao–Blackwellization in order to reduce the variance of estimators. As a result, the convergence process will speed up. From the simulations, we can observe that the proposed filter has good performance for the model with uncertain noise. Moreover, we verify the proposed algorithm by using a practical multiple-input multiple-output (MIMO) radar system.
A fast LP‐based solution to the production planning problem with capacity constraints including setup considerations

Purpose – Resource capacity and product changeovers must be both considered in the preparation of a realistic production plan. The purpose of this paper is to present a heuristic for enforcing resource availability and the accompanying changeover realities into a continuous‐variable linear programming formulation that would otherwise require a mixed‐integer model. The results from both approaches are compared in terms of objective function values and computational requirements; the effectiveness of the heuristic approach is demonstrated.Design/methodology/approach – A case study search was conducted to identify relevant data sets that could be used to exercise the optimization and heuristic models. The case studies found in the literature were too small and simple compared to the problem complexity desired. The authors developed a case study based on the development of a production plan for a typical flashlight. It includes two end‐products that differ in their bills of materials and process requirements.
Computational Evaluation of the Steady and Pulsed Jet Effects on the Performance of a Circulation Control Wing Section

Circulation Control Wing (CCW) technology is a very effective way of achieving very high lift coefficients needed by aircraft during take-off and landing. This technology can also be used to directly control the flow field over the wing. Compared to a conventional high-lift system, a Circulation Control Wing (CCW) can generate the required values of lift coefficient C(sub L,max) during take-off/landing with fewer or no moving parts and much less complexity. Earlier designs of CCW configurations used airfoils with a large radius rounded trailing edge to maximize the lift benefit. However, these designs also produced very high drag. These high drag levels associated with the blunt, large radius trailing edge can be prohibitive under cruise conditions when Circulation Control is no longer necessary. To overcome this difficulty, an advanced CCW section, i.e., a circulation hinged flap was developed to replace the original rounded trailing edge CC airfoil. This concept developed by Englar is shown. The upper surface of the CCW flap is a large-radius arc surface, but the lower surface of the flap is flat. The flap could be deflected from 0 degrees to 90 degrees. When an aircraft takes-off or lands, the flap is deflected as in a conventional high lift system. Then this large radius on the upper surface produces a large jet turning angle, leading to high lift. When the aircraft is in cruise, the flap is retracted and a conventional sharp trailing edge shape results, greatly reducing the drag. This kind of flap does have some moving elements that increase the weight and complexity over an earlier CCW design. But overall, the hinged flap design still maintains most of the Circulation Control high lift advantages, while greatly reducing the drag in cruising condition associated with the rounded trailing edge CCW design. In the present work, an unsteady three-dimensional Navier-Stokes analysis procedure has been developed and applied to this advanced CCW configuration. The solver can be used in both a 2-D and a 3-D mode, and can thus model airfoils as well as finite wings. The jet slot location, slot height, and the flap angle can all be varied easily and individually in the grid generator and the flow solver. Steady jets, pulsed jets, the leading edge and trailing edge blowing can all be studied with this solver.
Dither Signals and Their Effect on Quantization Noise

In this paper, the conditions a dither signal must meet so that the quantizer noise can be considered independent of the signal are derived for a quantizer having a finite number of levels. An infinite class of dither signals which satisfy these conditions is given. It is seen that the most useful member of this class is one whose probability density function is uniformly distributed over a quantizing interval. It is also shown that a necessary and sufficient condition for the noise n(t) to be independent of the signal x(t) is that a measurable quantity, called the "D" factor, be zero.
Drain Spacing Effects on Water Table Control and Cane Sugar Yields

An experiment was conducted in Southern Louisiana during 1980 through 1990 to determine soil and crop response to subsurface drainage. Three subsurface drain spacings, 14, 28, and 42 m, were tested on Jeanerette silty clay loam soil. The 14 and 28 m spacings were most effective in controlling the water table: average annual SEW30 values were 46 and 122 cm-d, respectively. Average annual SEW30 value for the 42 m spacing was 242 cm-d while that from the nondrained check was 642 cm-d. Sugarcane responded favorably to subsurface drainage. Average annual sugar yields were 6041 kg/ha from the 14 m spacing, 6029 kg/ha from the 28 m spacing, 5788 kg/ha from the 42 m spacing, and 4990 kg/ha from the check. Yields among the three drained treatments were not significantly different, but yields from the drained treatments were significantly greater than those from the nondrained check. The value of the average sugar yield increases from both the 28 m and the 42 m spacings more than justified the cost of installing subsurface drainage systems. The drainage costs included 10% interest and a 10-year amortization period. Since there was no statistically significant crop yield advantage to subsurface drains spaced closer than 42 m, the drain spacing recommended for draining Jeanerette silty clay loam soil in Louisiana is 42 m.
Extending the Mathews stability graph for open–stope design

Abstract The Mathews method of predicting open-stope stability was first proposed in 1980. The initial stability graph was based on a limited number of case studies, primarily from deep, North American, steeply dipping open stopes in strong rocks of medium to good quality. Since then new data have been added by various practitioners to modify, update and validate the method and support its use as a preliminary open-stope design tool. The original Mathews method has been extended with use of a significantly increased database of mining case histories. The format of the Mathews stability graph has been changed to reflect the broader range of stope geometries and rock mass conditions now captured within the database. The extended database now contains in excess of 400 case histories. Logistic regression has been performed on this larger database to delineate and optimize placement of the stability zones statistically. Isoprobability contours have been generated for all stability outcomes. The advantage of the logistic regression lies in its ability to minimize the uncertainties reflected in the method through the use of maximum likelihood estimates. The risks associated with use of the Mathews method can now be quantified and the true statistical significance of the stability zones understood.
Assessment of Heat Strain Among Workers in Steel Industry a Study

The impact of Heat on workers Health in the steel industry has been examined in the present study. The main objective of the present study were to examine the effect of Heat stress on workers employed in steel plant by measuring physiological reactions of workers such as pulse rate and core body temperature and comparing the results with exposure limits recommended by ACGIH & other professional bodies. Secondary objective was to determine an association between air temperature at workplace & rise in core body temperature of workers during work. Out of 140 employees exposed to heat hazard, 101 employees are examined in this study. Study was done in important production units in steel plant having heat hazards such as Blast furnace Cast House, Steel Melting shop, Energy optimizing furnace, Ladle refining furnace, continuous casting machine and Rolling mills; reheating furnaces, roll table, cooling bed area. Workers were interviewed, examined & information was collected through questionnaire. Workers were not using Heat resistant coat or cool coats for thermal comforts. The maximum core body temperature after work was found 39.3 0 C (Mean; 38.52 & S.D; 0.7). The maximum pulse rate of workers after work was found 120 beats/minute (Mean; 94.96 beats/minute, S.D; 13.11). The study indicate core body temperature of workers was found more than permissible exposure limit prescribed by ACGIH. This indicate the heat strain sustained by workers is significant whereas the pulse rate and Blood pressure was found normal & not exceeded the limits. In this study, correlation between air temperature at workplace & core body temperature rise was found significant. (r= 0.55, P = < 0.01)
A coarse‐refine segmentation network for COVID‐19 CT images

Abstract The rapid spread of the novel coronavirus disease 2019 (COVID‐19) causes a significant impact on public health. It is critical to diagnose COVID‐19 patients so that they can receive reasonable treatments quickly. The doctors can obtain a precise estimate of the infection's progression and decide more effective treatment options by segmenting the CT images of COVID‐19 patients. However, it is challenging to segment infected regions in CT slices because the infected regions are multi‐scale, and the boundary is not clear due to the low contrast between the infected area and the normal area. In this paper, a coarse‐refine segmentation network is proposed to address these challenges. The coarse‐refine architecture and hybrid loss is used to guide the model to predict the delicate structures with clear boundaries to address the problem of unclear boundaries. The atrous spatial pyramid pooling module in the network is added to improve the performance in detecting infected regions with different scales. Experimental results show that the model in the segmentation of COVID‐19 CT images outperforms other familiar medical segmentation models, enabling the doctor to get a more accurate estimate on the progression of the infection and thus can provide more reasonable treatment options.
Optimization of Biostimulants Application for Phenology and Quality of Oats

: In modern agriculture the use of biostimulants not only reduces the cost of production but also increase yield and quality of crops without harming environment. The response of fodder oat to biostimulants was evaluated in a pot experiment using four biostimulants at different concentrations i.e Moringa leaf extract at ratio of 1:10, 1:20, 1:30, 1:40, 1:50, Sea weed extract at 1%, 2%, 3%, 4%, 5%, Thiourea at 100 ppm, 200 ppm, chitosan 100 ppm was comparatively better in performance with 964.98 g yield per pot and 9.35% CP. It is concluded from our study that biostimulants improve fodder oat yield and quality.
Dual-Wavelength Fluorescence Monitoring of Photodynamic Therapy: From Analytical Models to Clinical Studies

Simple Summary Fluorescence imaging is an efficient tool in monitoring photodynamic therapy procedures allowing us to track accumulation and photobleaching of a photosensitizer (PS). Chlorin-based PSs feature high absorption in the red and blue bands of visible spectrum. Due to spectral dispersion of light penetration depth in biotissues, fluorescence signals registered upon excitation by red or blue light are formed in different measurement volumes. We present analytical and numerical models of dual-wavelength fluorescence imaging for evaluation of PS localization depth in the cases of topical administration and intravenous injection. The results of analytical and numerical simulations are in good agreement with the phantom experiments, and are translated to the in vivo imaging, which allows to interpret experimental observations in animal trials, human volunteers, and clinical studies. The proposed approach allows us to noninvasively estimate typical accumulation depths of PS localization which are consistent with the morphologically expected values. Abstract Fluorescence imaging modalities are currently a routine tool for the assessment of marker distribution within biological tissues, including monitoring of fluorescent photosensitizers (PSs) in photodynamic therapy (PDT). Conventional fluorescence imaging techniques provide en-face two-dimensional images, while depth-resolved techniques require complicated tomographic modalities. In this paper, we report on a cost-effective approach for the estimation of fluorophore localization depth based on dual-wavelength probing. Owing to significant difference in optical properties of superficial biotissues for red and blue ranges of optical spectra, simultaneous detection of fluorescence excited at different wavelengths provides complementary information from different measurement volumes. Here, we report analytical and numerical models of the dual-wavelength fluorescence imaging of PS-containing biotissues considering topical and intravenous PS administration, and demonstrate the feasibility of this approach for evaluation of the PS localization depth based on the fluorescence signal ratio. The results of analytical and numerical simulations, as well as phantom experiments, were translated to the in vivo imaging to interpret experimental observations in animal experiments, human volunteers, and clinical studies. The proposed approach allowed us to estimate typical accumulation depths of PS localization which are consistent with the morphologically expected values for both topical PS administration and intravenous injection.
Machine-learning-guided library design cycle for directed evolution of enzymes: the effects of training data composition on sequence space exploration

Machine learning (ML) is becoming an attractive tool in mutagenesis-based protein engineering because of its ability to design a variant library containing proteins with a desired function. However, it remains unclear how ML guides directed evolution in sequence space depending on the composition of training data. Here, we present a ML-guided directed evolution study of an enzyme to investigate the effects of a known “highly positive” variant (i.e., variant known to have high enzyme activity) in training data. We performed two separate series of ML-guided directed evolution of Sortase A with and without a known highly positive variant called 5M in training data. In each series, two rounds of ML were conducted: variants predicted by the first round were experimentally evaluated, and used as additional training data for the second-round prediction. The improvements in enzyme activity were comparable between the two series, both achieving enzyme activity 2.2–2.5 times higher than 5M. Intriguingly, the sequences of the improved variants were largely different between the two series, indicating that ML guided the directed evolution to the distinct regions of sequence space depending on the presence/absence of the highly positive variant in the training data. This suggests that the sequence diversity of improved variants can be expanded not only by conventional ML using the whole training data, but also by ML using a subset of the training data even when it lacks highly positive variants. In summary, this study demonstrates the importance of regulating the composition of training data in ML-guided directed evolution.
Dietary behaviour and anthropometric parameters across the spectrum of pregnant and lactating mother, infant, young children, adolescent girls and reproductive age group females: An assessment of undernutrition among KOL tribe

Introduction: The Kol is an ancient tribal community, who resides in the backward Bundelkhand and Baghelkhand regions bordering UP and MP. Reports claim the high level of exploitation and marginalisation of them by feudal landed landlords. Due to the dearth of studies on Kol community their plight hasn't been addressed effectively so far. Thus, this study was undertaken to assess the dietary behaviour and anthropometric parameters across the spectrum of Maternal, Lactating, Infant, Young Children, Adolescent girls, and reproductive-age women (MIYC-AR) of Kol Community. Methodology: It was a descriptive observational cross-sectional study, conducted over a period of 6 months; in hard to reach area of Manikpur block, Mangawa, in Chitrakoot district. Pregnant, lactating mothers, infant, young children, adolescent and reproductive age females who were found eligible, were included in the study. A total of 180 participants (30 from each group) were recruited by non-probability purposive sampling. A structured questionnaire was used to collect information regarding Iron folic acid and calcium intake, frequency of major meals and snacks, feeding history of infant and young child. Weight, height, head circumference and mid upper arm circumference were noted and the participants were classified accordingly. Statistical analysis was done using STATA version 13 software. Results: Only 36% and 30% of the pregnant and lactating mother, respectively, consumed IFA and calcium. The mean diet diversity score was inadequate for all the groups. Maximum among adolescents (70%) and half of the reproductive age group female (50%) were underweight. More than half of the infants (57%) were found to be malnourished on MUAC measurement, while the similar proportion among young children were found to be normal (p < 0.001). Half of the young children had timely initiation of complimentary feeding. But, none among young children received Vitamin A syrup. Conclusion: Significant higher prevalence of malnutrition was found among infants, adolescents, and reproductive age group females. Strengthening the public distribution system and rigorous supplementary nutrition services through ICDS are the priority intervention needed to address the poor nutritional status of tribe.
A Study on Work Environment, Work-life Balance and Burnout among Health Workers in Bangalore during COVID-19 Era

Recent outbreak of the global pandemic due to COVID-19 has led to a public health emergency, threatened human life and, created a worldwide economic challenge. Doctors, nurses and, health care workers from public and private sectors responded quickly to tackle the health crisis with stretched resources, shortage of personal protective equipment (PPE), and limited infrastructures. Physical exhaustion due to heavy workload, fear of getting infected, feeling powerless to handle a dying patient’s condition and, lack of protective gears and infrastructures have created a situation of tremendous mental stress and high burnout among them. This empirical study investigated the sources of supportsthe workplace and family and their impacts on the work-life balance based on a survey using pre-established constructs measured on the Likert scale on the healthcare professionals in Bangalore during November-December 2020. The result indicated that workplace settings have a significant impact on work-life balance (WLB). Unmarried women found to balance the work with less burnout and health workers at higher positions were supported in a better manner by the hospital management.
Capacitance computation for CPW discontinuities with finite metallization thickness by hybrid finite-element method

A variational equation is derived for the capacitances of coplanar waveguide (CPW) structures with finite metallization thickness. The equation is expressed in terms of the static potential in the slot region and is solved by applying the hybrid finite-element method (FEM). In the case of small metallization thickness, it is reduced to a perturbation formula for the incremental capacitances. Numerical results for the equivalent capacitances of various discontinuities with finite metallization thickness are presented and compared with measured data. The reasonable agreement between the measured data and the theoretical results validates the present approach. Being simple and computationally efficient, the method is suitable for dealing with extensive CPW discontinuity problems where the metallization thickness is not negligible.
AN OPTIMIZATION TECHNIQUE FOR RADIAL COMPRESSOR IMPELLERS

A software tool has been created to aid in automated impeller design within an integrated design system for radial flow impellers. The design tool takes the results from the 1D preliminary design process and uses these to define a parameterized blade geometry, which incorporates features that are required for low mechanical stresses and simple manufacturing. This geometry is then adjusted to minimize a global objective function using a throughflow computation. The adjustment is based on selection with a breeder genetic algorithm. The initial population includes “elite” designs from a database of earlier well-proven experience, and the final design is honed to perfection with a hill-climbing method. With the help of a suitable global objective function incorporating mechanical and aerodynamic criteria, and taking into account wide experience with the design of impellers, the tool provides a fast screening of various design possibilities to produce a geometrical input for more advanced computational fluid dynamic and mechanical analysis. This is demonstrated through the redesign of an impeller previously designed by conventional methods. Comparisons of the results of the CFD analysis of the new impeller with that of the earlier design demonstrate that the tool can rapidly produce nearly optimal designs as an excellent basis for further refinement by the more complex analysis methods.Copyright © 2008 by ASME