Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Spray Dried Spirulina Protein-Berry Pomace Polyphenol Particles to Attenuate Pollution-Induced Skin Damage: A Convergent Food-Beauty Approach

Spray drying (SD) microencapsulation of phytochemicals from berry pomaces with Spirulina protein (SP) was incorporated into a cosmeceutical topical formulation to mitigate pollution skin damage. Initially, microparticles produced with SP and polyphenols recovered from fruit pomaces (elderberry SP-EB and muscadine grape SP-MG) were characterized regarding physicochemical and phytochemical content (polyphenol load, carotenoid and phycocyanin contents and antioxidant activity). SP had low total phenolic content (7.43 ± 0.23 mg GAE/g DW), but complexation with elderberry or muscadine grape pomaces polyphenols led to a substantial increase (27.63 ± 1.15 SP-EB and 111.0 ± 2.6 mg GAE/g DW SP-MG). SP-MG particles had higher anthocyanin (26.87 ± 1.25 mg/g) and proanthocyanidin (9.02 ± 0.74 mg/g) contents compared to SP-EB particles. SP-MG were prioritized to prepare a topical gel to attenuate skin oxinflammatory markers and prevent skin barrier disruption using ex vivo human biopsies exposed to diesel engine exhaust (DEE). The immunofluorescence results showed increased oxidative protein damage and inflammation associated with impaired skin barrier function after DEE exposure while topical application of gel formulated with SP-MG mitigated these effects. Overall, this study demonstrated that protein-polyphenol complexation is a synergistic strategy to stabilize and deliver residual fruit/algae phytoactives into cosmeceutical products for skin health applications.
Modeling saline fluid flow through subglacial ice-walled channels and the impact of density on fluid flux

Subglacial hydrological systems have impacts on ice dynamics, as well as, nutrient and sediment transport. There has been extensive effort to understand the dynamics of subglacial drainage through numerical modeling. These models, however, have focused on freshwater in warm ice and neglected the consideration of fluid chemistry such as salts. Saline fluid can exist in cold-based glacier systems where freshwater cannot and understanding the routing of saline fluid is important for understanding geochemical and microbiological processes in these saline cryospheric habitats. A better characterization of 5 such terrestrial environments may provide insight to analogous systems on other planetary bodies. We present a model of channelized drainage from a hypersaline subglacial lake and highlight the impact of salinity on melt rates in an ice-walled channel. The model results show that channel walls grow more quickly when fluid contains higher salt concentrations which lead to higher discharge rates. We show this is due to a higher density fluid moving through a gravitational potential. This model provides a framework to assess the impact of fluid chemistry and properties on the spatial and temporal variation of 10 fluid flux.
Wideband Signal Based Near-Field Electromagnetic Ranging for Indoor Localizatio

The near-field electromagnetic ranging (NFER) technology exploits the near-field phase behavior of low frequency signals to measure the distance and can provide better ranging performance than the high frequency signal based methods in the cluttered environments. However, the currently existing NFER system uses the mono-frequency signals and can not obtain same ranging accuracy at different distances. In addition, low signal-to-noise ratio (SNR) seriously impacts the ranging accuracy. In this paper, we proposed a wideband signal based NFER system to improve the ranging performance. Instead of the mono-frequency signals, the proposed wideband system transmits the wideband signals. We use frequency domain phase measurement (FDPM) to detect the phase difference between received electric field signal and magnetic field signal. Then the least squares method is used to estimate the distance. Simulation results show that the proposed wideband NFER system can improve the ranging performance at low SNR environment and within a wide range of distances. Keywordsnear-field electromagnetic ranging; wideband signal; frequency domain phase measurement; phase difference; least squares
Investigating How Achievement Goals Influence Student Behavior in Computer Based Learning

: This study uses a mixed methods approach to explore relationships between goal achievement orientation and changes in student achievement, behavior, and affect while using Betty’s Brain. Qualitative coding was applied to student interviews to identify either performance or mastery goal approaches applied during their interaction with the game. A combination of quantitative methods were used to determine the influence and strength of goal orientations on student outcomes and interviews were thematically examined for patterns across student experiences. Findings from this study imply that students who communicate a goal approach (either performance approach or mastery approach) are more likely to experience confusion and engage in review-related behaviors such as reading informational resources and noting the accuracy of their responses.
Glacial isostatic adjustment strain rate - stress paradox in the Western Alps, impact on active faults and seismicity

In regions formerly glaciated during the Last Glacial Maximum (LGM), Glacial Isostatic Adjustment (GIA) explains most of the measured uplift and deformation rates. GIA is also proposed as a key process contributing to fault activity and seismicity shortly after the LGM and potentially up to present-day. Here, we study the impact of GIA on present-day fault activity and seismicity in the Western Alps. We show that, in the upper crust, GIA induces horizontal compressive stress perturbations associated with horizontal extension rates. The latter agree with the observed geodetic strain rates and with the 10 seismicity deformation patterns. Yet, in nearly all cases, the GIA stress perturbations tend either to inhibit fault slip, or to promote fault slip with the wrong mechanism compared to the seismicity deformation style. Thus, although GIA from the LGM explains a major part of the geodetic strain rates, it does not drive nor promote the observed seismicity (which must be driven by other processes). This apparent strain rate - stress paradox results from the gradual diminution over time of the finite shortening induced in the upper crust by the LGM icecap. A direct corollary of our results is that seismicity and seismic hazard 15 studies in the Western Alps cannot directly integrate geodetic velocities and strain rates, but instead require detailed modeling of the GIA transient impact.
Comments on wavefield propagation using Reverse-time and Downward continuation

Each iteration a of Full-waveform inversion requires the migration of the difference between the real data and the new data created from an updated model. The migration process has typically used the Reverse-time algorithm, though alternative algorithms are now being used. The reflectivity estimate from a migration may use a cross-correlation with forward modelled data and will contains artifacts that have a very low frequency and bias the reflectivity. The cause of these low frequency artifacts is identified and evaluated using Reverse-time and Downward-continuation wavefield propagation of energy using a wavelet on a one dimensional model. The model contains varying velocities that produce multiples that are displayed with a two dimensional array in space and time. The wavefields are propagated using finite difference and phase-shift algorithms, with various initial and boundary conditions. The resulting cross-correlations are then processed to evaluate their potential for representing the reflectivity of the model.
An Investigation on the Relationship between Personality Traits and Grit Levels among Pre-Service English Language Teachers

: Grit has been a renowned construct in the fields of education (Duckworth & Quinn, 2009) and profession (Baum & Locke, 2004). Similarly, personality traits have also been long acknowledged by different researchers as a determiner of one‟s likelihood to succeed too. It is depicted as an internal characteristic noted for its relative stability, consistency, and longevity (APA). As they are equal key determiners, it is intriguing to know whether there is a relationship between these two. The current study aims to realize this among pre-service English language teachers as respondents. Big Five Personality Traits Scale and Short-Grit Scale were utilized in gathering the necessary data for such, while a Personal Information Section was provided to identify the demographics of the respondents. Sequentially, it was revealed that there is indeed a statistically significant relationship between the personality traits of the respondents, such as conscientiousness and openness, and their grit levels.
Improvement of information system of cargo transportation routing management

The architecture of the information system is proposed in this article, which consists of two subsystems: management of cargo transportation and information flows with centralized management. The tasks and requirements for modern information systems of transport logistics has been analyzed. The task is to find the optimal route plan according to a given criterion for vehicles planning on a directed graph with irregular edge weights, considering the implementation of the delivery concept “right on time”. To consider daily, weekly, and seasonal fluctuations in traffic intensity, the concept of a time layer of the model is introduced. An algorithm for solving the problem of transport routing with load capacity restrictions is developed based on modifying the algorithm of ant colonies.
Principal Component Analysis Technique for Finding the Best Applicant for a Job: Case Study at Cihan University-Erbil

—This paper focuses on the use of principal component analysis (PCA) technique in choosing the best applicant for a job in Cihan University-Erbil. Cihan University has a panel of judges (University staff) to help in choosing the applicants for a job by evaluating or rating each one on different scale of preference and different type of characteristics. This process usually creates complicated multivariate data structure, which consists of 25 applicants for a job rated by a panel of judges on 17 characteristics (25 rows, applicants, and 17 columns, characteristics). PCA plays a crucial role in conducting impactful research as it offers a potent technique for analyzing multivariate data. Researchers can utilize this method to extract valuable information that aids decision-makers in problem-solving. To ensure the appropriateness of data for PCA, certain testing procedures are necessary. In this study, two tests, namely, the Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett’s test of sphericity, were performed, and their significance is vital. The findings indicate that the data employed in this research are suitable for PCA. Scoring and ranking procedures as extra tools were used to see that applicant No. (1) Is the first accepted for a job, applicant No. (17) Is the second, applicant No. (12) Is the third, and so on.
Improving multi-object re-identification at night with GAN data augmentation

This study concentrates on a camera-based traffic sensor that measures bicycle, vehicle and pedestrian trips called FlowCube ™ . To achieve multi-object tracking, FlowCube uses a model chain consisting of object detection, local tracking, trip filtering and re-identification (re-id). Whereas FlowCube’s performance is fit-for-purpose during the daytime, it degrades in more challenging nighttime conditions. With that, this study is aimed at improving FlowCube’s nighttime re-id performance. The hypothesis is that the poor nighttime re-id performance is due to a lack of nighttime re-id training data. So, in this paper a Generative Adverserial Network based data augmentation with alpha blending is proposed to enrich FlowCube’s re-id training data with synthetic nighttime imagery. The findings show that this method improves FlowCube’s mean re-id F1 scores and reduces the variance between results across multiple training runs, both for nighttime and general re-id. The same improvement can be expected for other camera-based traffic sensors which use multi-object tracking with re-identification.
Approximate Multiplier based on Low power and reduced latency with Modified LSB design

The devised approximation multiplier can adapt the precision and processing power needed formul triplication sat run-time based on the needs of the user. To decrease error distance, we also suggest a straight forward error compensation circuit. There are two types of approximate multi pliers. Dynamic voltages caling can be used for the first kind, which controls the timing route of the multiplier. If the voltage is lower, the critical path will take longer to complete. As a result, when the time path is violated, errors occurs and approximated results are produced. These cond types involves redesigning precise multiplier circuits like the Wallace Tree Multiplier and Dadda Tree Multiplier in order to change the functional behaviors of multipliers. Most of the earlier research on rebuilding multipliers suggested erroneous m-n compressors, which have m inputs and producen outputs. It dynamically reduces the area covered under the multiplier LSB which enables the MSB in accurate manner and LSB in approximate manner. This convolution al system approach is regarded to sequential cover up more than 32 bit multiplier. Since the accompanied circuit reduce then tire area by10times lesser than original multiplier, this conventional unit is regarded as abled circuit in the segment. Since the process of compressing partial products absorbed the majority of the multiplier energy and resulted in a consider able route delay, these incorrect compressors were utilized to compress the partial products within multiplication. These functionality are over come through our experimental setup.
Medical Insurance Premium Prediction Using Regression Models

: Medical insurance premium prediction is an important area of research that aims to accurately estimate the cost of healthcare for individuals based on their medical history and other relevant factors. In this study, It is considered the performance of four different machine learning models for medical insurance premium prediction: linear regression, ridge regression, support vector machine (SVM), and random forest regression. The usage of a dataset of medical insurance claims and demographic information to train and evaluate the models. The data was preprocessed and feature engineered to ensure optimal model performance. We used mean squared error (MSE) and R-squared as evaluation metrics to compare the performance of the different models. Our results showed that all four models were able to predict medical insurance premiums with reasonable accuracy. However, SVM and random forest regression outperformed linear and ridge regression in terms of MSE and R-squared. SVM had the lowest MSE of 3122.55 and R-squared of 0.854, while random forest regression had an MSE of 3423.32 and the highest R-squared of 0.887. Overall, The study highlights the potential of machine learning models for medical insurance premium prediction. SVM and random forest regression are promising techniques that can accurately estimate medical insurance premiums based on a range of factors. These models can provide valuable insights for healthcare providers and policy makers to improve the cost-effectiveness and quality of healthcare services.
Sample Moments and Weak Convergence to Multivariate Stochastic Power Integrals

This work considers sample moments arising from least squares, least absolute deviation, and extremum estimators of linear and nonlinear multivariate systems with I(1) regressors. The sample moments are shown to converge weakly to multivariate stochastic power integrals, and these results can be considered as a multivariate generalization of the univariate results reported earlier.
Molecular dynamics modeling of mechanical loss in amorphous tantala and titania-doped tantala

The mechanical loss (Q−1) intrinsic to amorphous oxides is the limiting factor for sensitive, high-precision gravitational wave detectors and optical devices. Recent experimental work suggests that doping amorphous tantala with titania reduces Q−1, however the physical processes underlying this reduction are unknown. Here we calculate Q−1 for pure and titania-doped tantala using numerical methods combined with molecular dynamics simulations that have atomic levels of resolution. Our results match experimental trends that titania doping decreases the magnitude of the low-temperature loss peak characteristic of these materials, with 62% titanium cation doping minimizing Q−1 at low temperature. We provide a microscopic explanation for this reduced loss by examining how doping affects the potential energy landscape, strain coupling constant, relaxation time, and other properties of the amorphous materials within the framework of the double well potential model. Analyzing configurational changes provides the first atomic description of the transitions driving mechanical loss at various temperatures in these oxides. These results identify the important parameters contributing to Q−1 that are most affected by doping and provide guidance for how to screen for optimal doping combinations to minimize loss in other materials. PACS numbers: 63.50. Lm,62.20. D,62.20. Qp
Role of N2-Fixing Plant Growth-Promoting Rhizobacteria in Some Selected Vegetables

Due to the increase in food-borne diseases, especially in recent years, consumers' orientation to healthy products and their emphasis on consumption force producers to environmentally friendly products. Nitrogen is the most widely used plant nutrient in the world. Nitrogen, a very expensive input due to its excessive use, pollutes the environment and causes nitrate accumulation in plants. Therefore, vegetable growers strive to replace chemical fertilizers such as nitrogen with environmentally friendly and cost-effective sources. PGPRs stand out in this regard and at the same time, their potential in environmentally and consumer-friendly vegetable production needs to be revealed. In this study, the importance and potential role of N2-fixing PGPR are discussed for the improvement of yield and yield components in environment-friendly vegetable production for healthy human nutrition.
Laser Slowing of CaF Molecules and Progress Towards a Dual-MOT for Li and CaF

Diatomic molecules are considered good candidates for the study of strongly correlated systems and precision measurement searches due to their combination of complex internal states and strong long-range interactions. Cooling molecules down to ultracold temperatures is often a necessary step for fully utilizing the power of the molecule. This requires a trap for molecules and the ability to cool molecules to the mK regime and below. A magnetooptical trap (MOT) is a good tool for achieving mK temperatures. However, extra care is needed for molecules to form the necessary quasi-closed cycling transitions due to molecule’s complicated energy structure. In our work with CaF, we use two repump lasers to block vibrational leakage and selection rules for the rotational degree of freedom to achieve about 10 photon cycles. The two-stage buffer gas beam source is a general method to generate a cold and slow beam of molecules with a forward velocity of about 50 m/s. The compatibility of the buffergas source with a MOT is studied and we confirm that such beams can be nicely compatible with MOTs using various atomic species. In order to load molecules into a MOT from even such a slow beam, additional slowing is required due to the low capture velocity of a molecular MOT (< 10 m/s). We apply a frequency-broadened “white-light” slowing on CaF from a two-stage source, demonstrating slowing of CaF below 10 m/s. An ACMOT, which provides active remixing of dark substates, is also developed and Li atoms are slowed and trapped. These are crucial ingredients for iii co-trapping CaF molecules and Li atoms and study their collisional properties, which would lead to sympathetic cooling of molecules down to ultracold temperatures. The achievement of slowing and development of this system allowed for the detailed study of the CaF laser cooling system, as well as physical processes involved with AC MOTs and the proposed MOT for CaF. Crucial knowledge of this archetypal system provides significant progress toward manipulation and control of molecules similar to what has been achieved with atoms and what is necessary for searches for new physics with ultracold molecules.
Color Barcodes from Debut to Present: A Broad Survey on the State of the Art

Efficiently transferring information, which is of major importance for almost all engineering systems, requires a data representative appropriate to maintain the density and consistency of the information dispatched. As such a machine-readable representation of data, barcodes are one of the most recognized and powerful instruments of the purpose in every domain. Likewise, from the perspective of engineering, colors are excellent sources of information exchange, since the transmission of color connotes the conveyance of its entire scalar attributes in the same spatial channel component. Exerting colors on barcodes as an effective way of bursting the data conveyance capacity has been an active area of research for over 50 years. Significant progress has been achieved through efforts in this regard. It is also envisagable that the evident evolution in related technologies exoterically empowers the enhancement of color barcode capabilities as capacity and reliability, thereby further encouraging prospected research in this direction. Herein, a comprehensive survey of the studies on this main area of interest is presented. To help better acquainted with the field, also a taxonomy of the peculiar interference sources and distortion effects is provided, besides, the 3D barcoding process itself and the research areas are described. Most of the relevant works from debut to the present are broadly examined. Rather than presenting a timeline, studies that pertain to similar issues are addressed together. Amongst those related, premising or pivotal ones are preferably cited as far as feasible. Moreover, all perused works are analyzed by the research areas and the results are presented. Also, the issues relatively more prominent as affecting the performance of the whole process are specified. In the conclusion, some of the research subjects that appear open, scarce, or require further elaboration were remarked on as well. It is anticipated this study to contribute to the efforts toward leveraging color in barcodes.