Miracle-dz/UniFAR-FTUs huggingface dataset:
OPTIMIZATION OF PROCESS PARAMETERS USING DIFFERENT STATISTICAL DESIGNS

Industries expect optimal solutions for the problems with a few experiments to reduce the cost and time of the experimentation. Many statistical methods are introduced to fulfil the demands of the industries. In the present study, three statistical methods namely Taguchi’s design of experiments, central composite designs (CCD) and balanced incomplete block design (BIBD) are considered. The adequacy of these methods is examined considering the test data of tensile shear strength of resistance spot welding for galvanized steel. Since the data is insufficient for the test runs demanded by the statistical methods, an empirical relation is developed from the test data using the response surface methodology (RSM). From the developed empirical relation, the necessary data is generated for CCD and BIBD. Empirical relations are also developed from the data of the test runs in CCD and BIBD. The optimal process parameters are identified from these methods and verified with the test data. The best method is identified based on the number of experiments and the adequacy in estimating the performance indicator for the identified optimal input variables. The maximum tensile shear strength estimated for the optimal input variables using Taguchi approach is close to the test results. Estimates from CCD and BIBD are slightly low to that of test results.
Human Fall Detection by FMCW Radar Based on Time-Varying Range-Doppler Features

 Abstract — The existing two-dimensional micro-Doppler features extraction ignores the correlation information between the spatial and temporal dimension features. For the range-Doppler map, the time dimension is introduced, and a frequency modulation continuous wave (FMCW) radar human fall detection algorithm based on time-varying range-Doppler features is proposed. Firstly, the range-Doppler sequence maps are generated from the echo signals of the continuous motion of the human body collected by the radar. Then the three-dimensional data cube composed of multiple frames of range-Doppler maps is input into the three-dimensional Convolutional Neural Network (3D CNN). The spatial and temporal features of time-varying range-Doppler are extracted by the convolution layer and pool layer at the same time. Finally, the extracted spatial and temporal features are input into the fully connected layer for classification. The experimental results show that the proposed fall detection algorithm has a detection accuracy of 95.66%.
Desorption Isotherms of Dioscorea Schimperiana (Hairy Yam): An Experimental and Modeling Approach

:- Several scientific types of research have already been carried out on yam tuber varieties of the Dioscorea family such as Dioscorea Retundata, and Dioscorea Alata. We can mention among others: the determination of sorption isotherms, their isosteric heat, and the drying kinetics. Dioscorea Schimperiana is also a tuber belonging to the same family and is currently a very popular foodstuff in the West Cameroon region. This plant, considered a nutritional element, also has several therapeutic virtues. However, the lack of knowledge of some of its thermophysical properties, especially the water content at equilibrium, is a hindrance to its optimal use. The present study, therefore, focuses on the determination of desorption isotherms, which could be useful for the modeling of a suitable dryer for the drying of Dioscorea Schimperiana. These desorption isotherms are obtained by the static gravimetric method, in the range of relative humidity from 11 to 97% and temperatures of 30°C, 40°C, and 50°C. The Henderson, Harkings and Jura, Halsey, modified Oswin, and GAB models were used for smoothing the experimental points. The isotherms obtained are of type II and characterized by a sigmoidal shape. The best fits were obtained for the GAB and Henderson equations. These data obtained by the GAB and Henderson models are of great use as it allows us to model the isosteric heat of desorption of Dioscorea Schimperiana.
Have difficulty standing up? soft exosuitsare here to help!

robotics is a novel disruptive technology that is revolutionizing the fields of robotics. Innovative use of compliant materials by researchers has elevated soft robotics over contemporary technologies. The Computational Sensing and Smart Machines (CSSM) laboratory of the Department of Mechanical Engineering, University of Moratuwa, has been taking strides in the development of soft robotics, ranging from actuators, sensors, and applications.
Plant attributes interact with fungal pathogens and nitrogen addition to drive soil enzymatic activities and their temporal variation

Nitrogen enrichment can alter soil communities and their functioning directly, via changes in nutrient availability and stoichiometry, or indirectly, by changing plant communities or higher trophic levels. In addition, soil biota and their associated functions may show strong temporal changes in their response to environmental changes, yet most current studies have only focused on one of these potential drivers or have measured soil functioning only once during the peak growing season. Therefore, we know little about the relative importance of the different mechanisms by which nitrogen enrichment affects soil communities, functioning and temporal stability. In a large grassland experiment manipulating nitrogen enrichment, plant species richness, functional composition and foliar pathogen presence, we measured activities of two enzymes, β-glucosidase and acid phosphatase, as indicators of soil functioning. We did so across different seasons and years to assess their temporal dynamics and how consistently they responded to multiple drivers. Nitrogen addition was the most important driver of β-glucosidase activity, and it increased β-glucosidase activity over time. However, interactions between plant attributes and fungicide application were the main drivers of acid phosphatase activity. The temporal stability of soil enzyme activity was differently affected by two facets of plant diversity (species richness [+] and functional diversity [-]), with nitrogen and fungicide addition dampening these effects. Synthesis: Fungicide effects, and their interactions with plant diversity, show the importance of foliar pathogens not only for above-but also for belowground processes, and highlight the possibility that these plant enemies are major modulators in the relationships between plant diversity and ecosystem functioning. We also show the need to consider temporal dynamics in belowground processes to better understand the responses of ecosystem functioning to environmental changes such as nutrient enrichment.
PF131010 Ciechanow fireball - the body possible related to Near Earth Asteroids 2010 TB54 and 2010 SX11

On 2010 October 13, the Apollo type 20-meter asteroid 2010 TB54 passed within 6.1 lunar distances from the Earth. On the same date, but 11.4 hours earlier, exactly at 02:52:32 UT, the sky over central Poland was illuminated by -8.6 magnitude PF131010 Ciechanow fireball. The trajectory and orbit of the fireball was computed using multi-station data of Polish Fireball Network (PFN). The results indicate that the orbit of the meteoroid which caused the PF131010 fireball is similar to the orbit of 2010 TB54 asteroid and both bodies may be related. Moreover, two days before appearance of Ciechanow fireball another small asteroid denoted as 2010 SX11 passed close to the Earth-Moon system. Its orbit is even more similar to the orbit of Ciechanow fireball parent body than in case of 2010 TB54. The PF131010 Ciechanow entered Earth's atmosphere with the velocity of 12.9 +\- 0.2 km/s and started to shine at height of 82.5 +\- 0.3 km. Clear deceleration started after first three seconds of flight, and the terminal velocity of the meteor was only 5.8 +\- 0.2 km/s at height of 29.3 +\- 0.1 km. Such a low value of terminal velocity indicates that fragments with total mass of around 2 kg could survive the atmospheric passage and cause fall of the meteorites. The predicted area of possible meteorite impact is computed and it is located near Grabowo village south of Ostroleka city.
Perceptual analysis of distance sampling and transmittance estimation techniques in biomedical volume visualization

: In volumetric path tracer, distance sampling and transmittance estimation techniques play a vital role in producing high-quality final rendered images. Previously, these techniques were implemented for production volume rendering, and were analyzed for faster convergence. In this article, we have augmented additional transmittance estimators including ratio tracking, residual ratio tracking and unbiased ray marcher in a GPU-based volumetric path tracer (Exposure Render) for biomedical datasets. We have also analyzed distance sampling methods and transmittance estimators perceptually using CIEDE2000 and Structural Similarity Index (SSIM). It was found that ratio and residual ratio tracking estimators performed close to each other and were better than unbiased ray marching perceptually. In addition, ray marching was observed to be better than delta tracking for distance sampling. We also validated these results by conducting a user study where different users were shown rendered images using varied distance samplers and transmittance estimators. Although, as expected, datasets had an impact on the rendering result for each technique, the perceptual differences did exist between distance samplers and transmittance estimators. As a major contribution of this work, we have found that distance sampling and transmittance estimation techniques have a crucial role for biomedical visualization due to having a direct impact on the final rendered image which is used in the diagnosis and prognosis of disease.
Nonstationarity and Structural Breaks in Economic Time Series: Asymptotic Theory and Monte Carlo Simulations

Testing for unit roots: principles and procedures. Part one: Tests for unit roots against fixed trend-stationary alternatives. Part two: Tests for unit roots against non-fixed trend-staionary alternatives. 2. Specification and analysis of test regressions for unit root tests against breaking trend-stationary. 3. Asymptotic and finite sample behaviour of statistics from unit root test regressions when the alternative is a breaking trend-stationary model. 4. An empirical application.
One-to-Many and Many-to-One Dialogue Learning via Sentence Semantic Segmentation Guided Conditional Variational Auto-Encoder

Due to the complex mapping relations, one-to-001 many and many-to-one phenomena are huge 002 challenges for open-domain dialogue genera-003 tion task, which tend to make dialogue mod-004 els generate irrelevant, incoherent or non-005 diverse responses. Most existing methods 006 avoid learning such phenomena through intro-007 ducing the external information, reconstruct-008 ing the optimization function or manipulating 009 data samples. However, avoiding confronting 010 such challenges ignores valuable information 011 in these responses, and the dialogue mod-012 els cannot learn the nature of such phenom-013 ena. In this paper, we propose a Sentence Se-014 mantic Segmentation guided Conditional Vari-015 ational Auto-Encoder (SegCVAE) to directly 016 learn one-to-many and many-to-one responses. 017 SegCVAE uses prominent semantics to replace 018 the original semantics to learn the distribution 019 of latent variables, which avoids the gap be-020 tween latent variables and the context, thus en-021 suring the relevance and coherence of the gen-022 erated responses. Furthermore, SegCVAE can 023 segment multiple prominent semantics to en-024 sure the diversity of generated responses. To 025 evaluate the model, we ﬁrst deﬁne two new 026 tasks named one-to-many dialogue learning 027 task and many-to-one dialogue learning task. 028 And then provide two new dialogue datasets 029 named One-to-Many and Many-to-One, which 030 are extracted from the well-established dataset. 031 Finally, we also propose the evaluation strate-032 gies based on some commonly-used metrics. 033 The experiment results show that our model 034 achieve better performance than the baseline 035 models in addressing these two new tasks. 036
The weighed average geodetic of distributions of probabilities in the statistical physics

The results received in works [Centsov N.N. [N.N. Chentsov], Statistical decision rules and optimal inference, 1982 Amer. Math. Soc. (Translated from Russian); Morozova, E. A. , Chentsov, N. N. Natural geometry of families of probability laws. 1991 Probability theory, 8, 133--265, 270--274, 276 (in Russian)] for statistical distributions at studying algebra of decision rules and natural geometry generated by her, are applied to estimations of the nonequilibrium statistical operator and superstatistics. Expressions for the nonequilibrium statistical operator and superstatistics are received as special cases of the weighed average geodetic of distributions of probabilities.
FACTORS AFFECTING INTERACTIONS BETWEEN TOURISTS 

Tourism includes the relations between people from different cultures and this also allows cross-cultural interaction and contact. Intercultural interaction also includes the interactions between tourists from different cultures and nations. In the tourism industry, the interaction between tourists constitutes another dimension of social interaction. Cross-cultural interaction generally includes interactions between people who have cultural characteristics different from each other regarding perception, expectations, values, worldview, rules of behaviour and form of communication, and come from different two cultures. This can lead to positive and negative interactions between tourists. From this perspective, other tourists can have positive and negative effects on a tourist's experience. However, in the literature, the studies on other tourists and interactions between tourists have been very limitedly. Therefore, this study aims to reveal factors affecting tourist-to-tourist (t2t) interactions. In the study, it was carried out semistructured interviews with thirty-three international tourists visiting Istanbul. It was used the triangulation technique to provide the reliability and validity of the study. Accordingly, focus group interviews were held with 7 tourist guides. As a result of the research, it was found that some cultural, personal and situational factors affect the interactions between tourists.
Adiabatic regularization for gauge fields and the conformal anomaly

We construct the adiabatic regularization method for a $U(1)$ gauge field in a conformally flat spacetime by quantizing in the canonical formalism the gauge fixed $U(1)$ theory with mass terms for the gauge fields and the ghost fields. We show that the adiabatic expansion for the mode functions and the adiabatic vacuum can be defined in a similar way using WKB-type solutions as the scalar fields. As an application of the adiabatic method, we compute the trace of the energy momentum tensor and reproduces the known result for the conformal anomaly obtained by the other regularization methods. The availability of the adiabatic expansion scheme for gauge field allows one to study the renormalization of the de-Sitter space maximal superconformal Yang-Mills theory using the adiabatic regularization method.
Journal Pre-proof Self-medication among pregnant women in Ghana: A systematic review and meta-analysis

Background: Despite the associated health risks of self-medication during pregnancy, recent evidence suggests that the phenomena persist in most countries. However, self-medication during pregnancy in Ghana is poorly understood due to the lack of a comprehensive review study. Objectives: We sought to review existing literature on the prevalence of self-medication, drugs used in self-medication, diseases associated with self-medication, and why pregnant women in Ghana self-medicate. Methods: A comprehensive search was conducted in PubMed, Science Direct, African Journal Online (AJOL), Google Scholar, and the websites of Ghanaian universities to identify studies that were published until February 2022. We performed this review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A random-effects meta-analysis was done in StatsDirect statistical software and OpenMeta [Analyst] to estimate the prevalence of self-medication during pregnancy and was reported in a forest plot. Simple charts and tables were used to summarize evidence on drugs used in self-medication, diseases associated with selfmedication, and reasons for self-medication. Results: Six (6) studies met our inclusion criteria and the pooled prevalence of self-medication during pregnancy was 65.4% (95% CI = 58.2%-72.6%; I 2 = 88.32%; p < 0.001). Common drugs used for self-medication included analgesics (48.1%) and herbal drugs (45.9%). Headache and lower abdominal pain were the most common conditions for which pregnant women self-medicated. The main reasons for self-medication were the perceived unserious nature of diseases, previous experience with drugs, and easy access to over-the-counter drugs. Conclusions: Self-medication among pregnant women in Ghana is substantially high. Measures need to be implemented to reduce the high prevalence of self-medication during pregnancy to achieve sustainable development goals on maternal health in Ghana. A limitation of this study was the small number of included studies, which calls for more studies on self-medication during pregnancy in Ghana.
Diversification and niche evolution in the brown alga Dictyota (Dictyotales, Phaeophyceae).

The brown alga Dictyota has a global distribution and is well sampled, making it a prime model for inferring diversification in relation to sea surface temperature (SST). This study aims to characterize diversification patterns and the evolution of the macroecological niche by combining climatic data with molecular phylogenetics. Evolutionarily significant units (ESU’s) are delineated with the psb A gene under the neighbor-joining criterion. A six-locus dataset is used to estimate the phylogeny, then diversification statistics are calculated by means of the statistical platform R. SST data obtained through satellite imagery are used to estimate the ancestral character state and perform species distribution modeling (SDM) under the principle of maximum entropy. Predicted niche occupancy, ancestral climatic tolerances, and niche similarity metrics were computed by integrating the time calibrated phylogeny with the SDM output, while disparity is calculated by combining the phylogeny with raw SST data. Results indicate a basal ancestor that inhabited a southern warm temperate region approximately 70 Ma, and gave rise to 85 species in 5 related genera (predominantly the Dictyota genus), fairly evenly split between northern temperate, tropical and southern temperate regions. A density dependent model best fits the phylogeny, with diversification bursts between 40 and 15 Ma and lineage accumulation higher than expected by chance. Significant phylogenetic signal is detected in the Dictyota genus for SST maximum, mean, and minimum, though non Dictyota genera register signal only for SST range. In addition, multiple instances of divergent evolution and high within subclade disparity were detected. The results show diversification rates that are closely but not completely correlated with SST variables, indicating that other abiotic and biotic processes likely played a role in promoting Dictyota diversity.
Lightweight Neural Architecture Search with Parameter Remapping and Knowledge Distillation

Designing diverse neural architectures taking into account resource constraints or datasets is one of the main challenges in Neural Architecture Search (NAS). However, existing sample-based or one-shot NAS approaches require excessive time or computational cost to be used in multiple practical scenarios. Recently, to alleviate such issues, zero-shot NAS methods that are efficient proxies have been proposed, yet their performance is rather poor due to the strong assumption that they predict the final performance of a given architecture with random initialization. In this work, we propose a novel NAS based on block-wise parameter remapping (PR) and knowledge distillation (KD), which shows high predictive performance while being fast and lightweight enough to be used iteratively to support multiple real-world scenarios. PR significantly shortens training steps and accordingly we can reduce the required time/data for KD to work as an accurate proxy to just few batches, which is largely practical in real-world. In the experiments, we validate the proposed method for its accuracy estimation performance on CIFAR-10 from the MobileNetV3 search space. It outperforms all relevant baselines in terms of performance estimation with only 20 batches.
Target Enclosing and Coverage Control for Quadrotors with Constraints and Time-Varying Delays: A Neural Adaptive Fault-Tolerant Formation Control Approach

This paper investigates the problem of formation fault-tolerant control of multiple quadrotors (QRs) for a mobile sensing oriented application. The QRs subject to faults, input saturation and time-varying delays can be controlled to perform a target-enclosing and covering task while guaranteeing the state constraints will not be exceeded. A distributed formation control scheme is proposed, using a radial basis function neural network (RBFNN)-based time-delay position controller and an adaptive fault-tolerant attitude controller. The Lyapunov–Krasovskii approach is used to analyze the time-varying delay. Barrier Lyapunov function is deployed to handle the prescribed constraints, and an auxiliary system combined with a command filter is designed to resolve the saturation problem. An RBFNN and adaptive estimators are deployed to provide estimates of disturbances, fault signals and uncertainties. It is proven that all the closed-loop signals are bounded under the proposed protocol, while the prescribed constraints will not be violated, which enhances the flight safety and QR formation’s applicability. Comparative simulations based on application scenarios further verify the effectiveness of the proposed method.
Title: Auxin and pectin remodeling interplay during rootlet emergence in white 1 2

Secondary root emergence is a crucial trait that shapes the plant’s underground system. Virtually every 38 developmental step of root primordium morphogenesis is controlled by auxin. However, how the 39 hormone controls cell separation in primordium-overlaying tissues through wall loosening is poorly 40 understood. Here, we took advantage of white lupin and its spectacular cluster root development to 41 assess the contribution of auxin to this process. We show that auxin’s positive role on rootlet 42 emergence is associated with an upregulation of cell wall pectin modifying and degrading genes. 43 Downregulation of a pectinolytic enzyme gene expressed in cells surrounding the primordium resulted 44 in delayed emergence. Pectins were demethylesterified in the emergence zone and auxin treatment 45 further enhanced this effect. Additionally, we report specific rhamnogalacturonan-I modifications during 46 cortical cell separation. In conclusion, we propose a model in which auxin has a dual role during rootlet 47 emergence: Firstly, through active pectin demethylesterification and secondly by regulating the 48 expression of cell wall remodeling enzymes. carbohydrate metabolic process, lyase and polygalacturonase activities. This suggests a prominent action of auxin on quick but transient