Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Probiotic Bacillus clausii on Production Parameters and Intestinal Histomorphology of Meat-Type Chicken

This study aimed to evaluate the effect of probiotic Bacillus clausii on performance parameters, the histomorphological architecture of the intestine, and its economic importance in broilers. For this purpose, 120 days old broiler chicks were randomly assigned to 4 groups comprised of group A (Control), group B (4×10 6 spore @0.01 ml/L), group C (8×10 6 spore@0.02 ml/L) and group D (12×10 6 spore@0.03 ml/L). Each group consisted of 3 replicates (n=10/replicate). The results revealed that water-supplemented B. clausii had no effect on daily feed intake in broiler chicks. However, higher (p<0.05) weight gain and improved FCR were found with the highest level of supplementation (0.03ml/L) of B. clausii . Histo- morphological results showed increased villus height, villus height: crypt depth, and villus surface area. Moreover, the supplementation of 12×10 6 spore@0.03 ml/L also increased (p<0.05) the net profit due to increased production. In conclusion, the use of water-based supplemented B. clausii (12×10 6 spore@0.03 ml/L) has a positive impact on production parameters and intestinal health in meat-type chicken.
Independent Control over Passbands in Highly Selective and Compact Triple-band Bandpass Filter Based on Substrate Integrated Waveguide

|This paper proposes a method of independent control over each passband in a high performance triple bandpass (cid:12)lter, which is an essential requirement in the (cid:12)eld of microwave communication systems. Individual techniques are presented here to control the excited modes that are responsible for the generation of triple passbands based on substrate integrated waveguide loaded with semi-circular mushroom resonators. Initially, a circular substrate integrated waveguide (CSIW) loaded with two cascaded semi-circular mushroom resonators (ScMRs) with distinct modi(cid:12)cations and orientations in the schematic is employed to generate three passbands. The fundamental mode and next higher order mode of the entire resonator structure are utilized to generate three passbands, and distinct techniques of mode perturbations and variation in coupling strength are introduced to independently control the excited modes. Subsequently, the methods established to control the excited modes are employed to independently control the center frequencies (CFs) of three passbands. All those methods established to control the CFs of the three passbands are veri(cid:12)ed with experimental results which show good agreement with the simulated ones.
Ball tracking and trajectory prediction system for tennis robots

Recently, as the service robot market has grown, robots have emerged in various fields such as industry, service, and sports. In the field of sports, robots that can play with humans have been developed. We proposed a novel vision system for measuring the trajectory of a tennis ball and predicting its bound position, which can be utilized in the development of tennis robots. In this paper, we introduce a ball detection algorithm using an artificial neural network and a ball trajectory prediction algorithm using stereo vision. Our approach involved the use of a net vision system and a robot vision system to accurately detect and track the ball as it moves across the court. By combining these two systems, we were able to predict the trajectory and bound position of the tennis ball with high accuracy. As a result, the accuracy of the neural network for ball detection in actual tennis images reaches 81.4%. The ball trajectory prediction error in Gazebo simulation is 29.6 cm in the x-axis, 7.2 cm in the y-axis, and 11.7 cm in the z-axis on average.
Astrometric VLBI Observations of the Galactic LPVs, Miras, and OH/IR stars

Abstract Studies of Galactic LPVs based on astrometric VLBI are presented. We use a VLBI array, “VERA”, to measure parallaxes and calibrate the K-band period luminosity relation (PLR) of the Galactic Miras. Since the PLR offers a distance indicator, its calibration is crucial to reveal their spatial distribution. Parallaxes of dozens of LPVs are presented. For the longer period stars, the mass-loss is high and the stars are obscured and recognized as OH/IR stars. We estimated mid-infrared absolute magnitudes of dozens of OH/IR stars and found that they show a loose concentration around −14 mag at λ of 11.6 μm, indicating an existence of PLR for OH/IR stars. Astrometry of OH/IR stars will also help us to study non-steady spiral arms as proposed from the latest simulation study of the galactic dynamics. We will start astrometric VLBI observation of two OH/IR stars NSV25875 and OH127.8+0.0 at 43 GHz with VERA.
Phytochemical study and evaluation of the antiulcer effect of aqueous and hydroethanolic extracts of the recipe for the leaves of Eriosema erici-rosenii re fr. and Neoboutonia melleri müll. arg. prain in mice

This work aimed to justify the traditional use of the recipe based on Eriosema erici and Neoboutonia mülleri in the treatment of gastric ulcers. The ulcer was induced by the HCl/ethanol mixture. To elucidate the antiulcer mechanism; the effect of the aqueous (300 and 600 mg/kg) and hydroethanolic (300 and 600 mg/kg) extracts was evaluated on lipid peroxidation, the production of antioxidant enzymes, the release of nitric oxide. At the doses used, the extracts of the recipe significantly reduced gastric lesions. In addition, they showed an antioxidant effect not only by inhibiting the ferric reducing power but also by opposing lipid peroxidation and improving the expression of antioxidant factors by increasing the production of catalase (CAT), glutathiones (GSH; GPx), super oxide dismutase (SOD). This coupled with a nitrogen effect. The phytochemical screening revealed the presence of flavonoids, tannins, terpernoids which could justify the antiulcer and antioxidative effect observed.
Black Hole Universe and Hubble’s Law

Within the framework of the black-hole model of the Universe, I gave the dependence of the redshift of light reaching the Earth versus the distance of the galaxy that is the source of this light. The linear fragment of the graph of this relationship corresponds with Hubble’s observations. The non-linear part represents a sharp increase of the redshift.
Below‐cloud scavenging of fine and coarse aerosol particles by rain: The role of raindrop size

Below‐cloud aerosol scavenging is an important process to remove particles from the atmosphere. In this study, both precipitation (measured with a laser disdrometer registering drops between 0.125 and 8 mm) and atmospheric aerosol particles (measured with a Passive Cavity Aerosol Spectrometer Probe registering aerosol sizes between 0.1 and 24 µm) have been sampled on a 1 min basis. Based on 6 months of outdoor measurements in León (northwest Iberian Peninsula), the scavenging coefficients were calculated for the aerosol particles measured, with a mean value of 2.6 × 10−5 ± 6.0 × 10−5 s−1 for the fine mode and 5.8 × 10−5 ± 9.6 × 10−5 s−1 for the coarse mode in 54 rain events. Likewise, the particle concentration decreased during rain by 10%, and by 18% between the time before and after the rain. In the Greenfield Gap (sizes between 0.3 and 1 µm) the scavenging is less effective, mainly between 0.6 and 1 µm, than with smaller particles. The number of drops between 0.75 and 3 mm shows statistically significant (p < 0.05) negative correlations with the number of particles between 0.16 and 1.76 µm, thus illustrating the potential of those raindrops to favour the scavenging of particles of that size. In addition, there were statistically significant negative correlations between the total volume removed by falling drops (mm3/m3) and the variation of the number of particles in channels with diameters between 0.12 and 0.19 µm.
Sound-Based Real-Time Scrap Falling State Monitoring in the Shearing Process of Wide Heavy Plate Mill

The scrap falling state in the shearing process of a Wide Heavy Plate Mill depends on manual monitoring and judgment. The steel plate can only move forward after the scrap falls, otherwise, the equipment will be damaged. An experienced operator can use the sound they hear to estimate the falling state. To automatically recognize sound events, a scheme of sound data acquisition processing and recognition for monitoring the scrap state of the shearing process is proposed in this article. First, a pickup is installed at the monitoring point of the crop shear to collect the sound. Afterward, the sound data is processed and finally fed into the model for recognition. Since many sound segments in the field are not related to key actions, an endpoint detection technique based on a short-term energy threshold and the variable window length strategy is applied in the data processing section to obtain the sound segments to be identified. The Log-Mel spectrogram feature of the sound segment is then extracted. After a data filling to ensure a uniform data shape, the feature map is fed into a lightweight deep convolution neural network called MobileNetV2 to quickly identify sound events. For the shearing process events, the model recognition accuracy can reach 95% of the ${F}1$ score in a realistic noise environment and we can identify the scrap falling 0.3 s after the action starts. Finally, the model was applied to the UrbanSound8K dataset and achieved 95% recognition accuracy, validating the performance of the method.
Toward Zero-Energy Devices: Waveform Design for Low-Power Receivers

The use of a low-power wake-up receiver (WUR) can significantly reduce the device’s energy consumption. To incorporate such WURs into existing communication systems, the waveform design needs to facilitate simple detection yet be compatible with the orthogonal frequency division multiplexing (OFDM) transmission. In this letter, we propose a novel phase design for the wake-up signal (WUS) so that the time-domain distortion of the WUS can be minimized. A majorization-minimization (MM) method is proposed to address the waveform design problem. Simulations show that the proposed scheme can achieve a near-optimal detection performance under different system parameters.
Evaluation of Color Changes in Resin Infiltrated White Spot Lesion after Exposure to Different Colored Oral Rinses

This study aimed to compare the colour changes of resin-infiltrated white spot lesions after exposure to artificial saliva and oral rinses (Oral-B Pro-Expert, Listerine and Colgate Plax) at different time intervals (24 h, 72 h and 7 d). The premolar teeth were selected and sectioned into two halves. The artificial white spot lesions were created and resin-infiltration procedure was performed to seal the pores. The specimens immersed in the control subgroup showed an insignificant colour change (∆E) after 72 h. While significant differences in colour change among the experimental groups across time intervals (p<0.001), oral rinse groups (p<0.001), and the interaction between timeline and groups (p<0.001). All resin-infiltrated specimens showed colour differences after immersion in oral rinses with visually perceptible change. Although, Colgate Plax and Oral B oral rinses demonstrated the highest and lowest colour change, respectively in the initial 24 h. However, at 72 h and 7 d time-points, Listerine oral rinse demonstrated the highest colour change, while the lowest values were observed in Oral-B oral rinse. The use of Listerine should therefore be cautiously advised in resin-infiltrated cavities.
Learning Structured Relation Embeddings for Fine-Grained Fashion Attribute Recognition

Fashion attribute recognition is a not-new topic, but rather a core task in understanding fashion from the perspective of computer vision. This article proposes a structured relation-aware network (sRA-Net), which exploits multiple hidden relations in fashion images to enrich and achieve accurate attribute representations to boost the performance of fashion attribute recognition. Specifically, it deconstructs the features of a clothing fashion item into three levels, including low-level attribute-related image region information, mid-level attribute dependency information, and high-level clothing look information. To learn these multi-relational embeddings, we present three relation-aware attention mechanisms. The attribute attention mechanism describes the relationship among different attribute vectors through self-attention and uses the attention map to update the attribute embedding. Then, the spatial attention mechanism associates the attribute with the image features and enhances the attribute embedding by leveraging the attribute-related image region. Finally, the channel attention mechanism selects attribute-related image feature channels to obtain a more fine-grained attribute embedding. Furthermore, we introduce structure-aware embedding to constrain attribute recognition in images from a global perspective by identifying the inner structure of the clothing. Without bells and whistles, sRA-Net outperforms all state-of-the-art attribute recognition methods on two mainstream fashion attribute datasets, namely the DeepFashion-C dataset and iFashion-Attribute dataset, with over 1%-3% improvement.
INFLUENCER CHARACTERISTICS IN SOCIAL MEDIA INFLUENCER MARKETING: A SYSTEMATIC LITERATURE REVIEW

In light of rising interest in research on influencer marketing, this paper aims to analyse the impact of influencer characteristics on consumer behaviour. The study was based on a systematic analysis of 127 peer-reviewed articles published or accepted from 2000 to 2021. The paper included 52 influencer characteristics classified into four categories: psychological, social, behavioural and demographic characteristics. The findings show that influencers’ psychological characteristics, such as trustworthiness, expertise, and attractiveness, have been over-studied. However, research gaps exist in the area of influencers’ social characteristics, such as envy and betrayal, as well as behavioural characteristics, such as facial expression, body language, speaking speed and sharing secrets. In addition, there is also a lack of research on the importance of demographic characteristics such as gender, age and ethnicity.
Advances in Novel Tumor Therapeutics Based on Nanomaterial Technologies

Cancer is the leading cause of death in the world, throughout the global researches of cancer treatment, people have a deeper understanding of cancer, and the treatment methods are constantly breakthrough. Conventional surgery, chemotherapy and radiotherapy have serious adverse effects and patients' quality of life is not significantly improved. Now, photodynamic therapy, photothermal therapy andthermodynamic therapy based on nanotechnology and materials technology are booming, and the development of these novel cancer therapies and their combination therapies brings more possibilities for cancer treatment. This review summarizes the research progress of novel cancer therapies based on nano and material technology from the aspects of mechanism of action and therapeutic methods, hoping to provide reference for their clinical application.
An Optimization‐Based Approach for Source Term Estimations of Atmospheric Releases

This article highlights an optimization‐based approach to estimate the main characteristics (i.e., location and intensity) that describe the source of a release of a hazardous material (e.g., a chemical or biological agent) in the atmosphere. The method, which uses, as input data, concentration measurements provided by a network of sensors (and some additional meteorological data), is first formalized in the general framework of parametric source term estimation inverse problems. Some simple and new geometric interpretations of the method are proposed. Next, it is shown that the approach can also provide a realistic understanding of the uncertainties in the estimation of the characteristics of the source. Then, a strategy for an optimal deployment of mobile sensors in hazardous materials operations is proposed. To conclude, the source estimation approach and the network design strategy are evaluated with data from a wind tunnel experiment conducted at the Environmental Flow Research Center at the University of Surrey, UK.
Cultural Application of Accounting and Economic Systems: An Islamic Perspective

The spirit of Islamic economics has recently developed in Indonesia, which is the context of this study evaluating the culture of using conventional accounting and economic systems. The objective of this study is to determine how the Islamic economy applies mainstream accounting and financial systems culturally. Our study explored the applicability of standard accounting and economic systems from an Islamic perspective. Initially, we gathered data on accounting information systems and Islamic Sharia from journals, conferences, books, and other relevant sources. Then, we used a comprehensive evaluation and interpretation coding system to acquire pertinent information to answer the project's concerns. We scoured Google Books, Taylor & Francis, Sage Publications, Elsevier, and other domestic scientific publications for information on the assessment and interpretation coding factors. The Islamic Sharia economic system is a system or mechanism that is regulated according to Islamic Sharia law, for example, in regulating business activities, classifying data, summarizing data, preparing reports, and analyzing finances and businesses using principles and rules that are derived from the Qur'an, hadith, and the understanding of scholars in order to realize a just and equitable society.
The Planck-Balance—using a fixed value of the Planck constant to calibrate E1/E2-weights

A balance is proposed, which allows the calibration of weights in a continuous range from 1 mg to 1 kg using a fixed value of the Planck constant, h. This so-called Planck-Balance (PB) uses the physical approach of Kibble balances that allow the Planck constant to be derived from the mass. Using the PB no calibrated mass standards are required during weighing processes any longer, because all measurements are traceable via the electrical quantities to the Planck constant, and to the meter and the second. This allows a new approach of balance types after the expected redefinition of the SI-units by the end of 2018. In contrast to many scientific oriented developments, the PB is focused on robust and daily use. Therefore, two balances will be developed, PB2 and PB1, which will allow relative measurement uncertainties comparable to the accuracies of class E2 and E1 weights, respectively, as specified in OIML R 111-1. The balances will be developed in a cooperation of the Physikalisch-Technische Bundesanstalt (PTB) and the Technische Universität Ilmenau in a project funded by the German Federal Ministry of Education and Research.
Electromagnetic Fields in Reverberant Environments

The phenomenon of resonating electromagnetic (EM) fields has been commonly and successfully exploited in reverberation chambers (RC) for the purpose of electromagnetic compatibility (EMC) testing, as well as modeling multipath environments. Although largely successful, the currently used statistical models allow for a certain degree of freedom, especially with regard to defining the extreme field strengths, which are also the main cause of electromagnetic interference (EMI). Furthermore, some actual multipath, enclosed environments such as airplane fuselages, ships, or even building interiors, can unintentionally possess the ability to create enough strong reflections so that the resulting resonating EM field within them resembles the field inside a dedicated RC. The initial step made in this thesis focuses on introducing REs as environments sharing multiple aspects of EM field shaping with RCs. The results indicate a possible similarity to a referential RC analyzed alongside. Furthermore, due to the difficulty of collecting large amounts of data and parameter isolation in the REs, two dedicated chambers: a classical RC and the vibrating intrinsic reverberation chamber (VIRC), have been analyzed as candidates allowing to simulate an RE in laboratory conditions. The search of maximum field strengths in REs has been performed by exploiting the capability of the VIRC to efficiently generate large amounts of independent samples. Performing very long measurements in the VIRC allows to obtain the desired results with very high repeatability, while giving space for parameter isolation. The measurement results obtained outside the laboratory conditions allowed to formulate a method of performing on-site emissions testing. Although performed in imperfect REs, a modified RC standard technique has been successfully applied, concluding that such an approach is possible and recommended. The final topic of the thesis discusses a creation of a simplified macro-parameter model of field coupling to cables when neither the exact cable geometry, nor the coupling field is known. Instead of focusing on precision, this investigation aims at finding any similarities, possibly allowing to avoid the difficulties related to the very sensitive description of a non-uniform transmission line, exploiting the mixed randomness of the line geometry and the multipath field excitation.
Diagnosis of Hepatitis Using Supervised Learning Algorithm

Hepatitis is the most serious disease in developing countries. Therefore, early diagnosis is very important to obstacle the effect that can happen as a consequence of this disease. In this case, deep learning can solve the issue at an early stage. An innovative deep learning-based technique to identify hepatitis is presented in this study. In this study 45 layers, convolutional neural network (CNN) architecture connected with three fully connected layers is used in the proposed architecture. The two classes of collected hepatitis datasets are then used to train the suggested CNN model. The model achieved 0.934 classification accuracy. The proposed model was compared to the state of the art at the time. The outcome presented implies that the model's performance is remarkable.
Enlargement of filtration on Poisson space: a Malliavin calculus approach

Abstract Being inspired by the work of Imkeller et al., who first developed a measured-valued version of Malliavin calculus to study the enlargement of filtration by an ‘exogenous’ random variable on the Wiener space, in this article we consider the enlargement of filtration on the Poisson space. We construct a measure-valued Malliavin calculus on the Poisson space with the Malliavin type calculus defined by Mensi and Privault. Without resorting to the traditional Jacod’s condition nor its local version, the measure-valued Poisson Malliavin calculus can be applied to compute the ‘information drift’. Our result applies for a general -integrable ‘exogenous’ random variable, while previous works require a more restrictive Malliavin differentiability. Finally, we illustrate a concrete application of our results with an example from Mensi and Privault.