Miracle-dz/UniFAR-FTUs huggingface dataset:
International Trade Price Index: A Leading Indicator for Indonesia's Inflation?

As one of essential indicators in economy, inflation rate can be determined by several factors. One of these factors is price index other than CPI, representing price change, other at consumer level. Many studies have examined the effect of price indices such as Producer Price Index (PPI) and Wholesale Price Index (WPI) on inflation, including in Indonesia. However, in an open economy, the level of openness, which can be approximated by International Trade Price Index (IHPI), may also influence changes in inflation. In Indonesia, no studies still examine the nexus between ITPI and inflationThis study aims to examine the effect of price indices variables other than at consumer level, particularly ITPI, on inflation and whether we can use it as one of the leading indicators of inflation in Indonesia. The analysis results of the ARDL-ECM model show that all price indices variables simultaneously influence inflation. However, the effect of each variable partially on inflation in the short and long run varies. The speed of adjustment to return to equilibrium is 4.67% per month after the shock happened. Nevertheless, the effect of ITPI on inflation is insignificant, both in the short and long run. Thus, we can conclude that ITPI is not yet able to be a leading indicator of inflation in Indonesia. However, the result of this study must be carefully concluded since the use of time series analysis depends on the lag length and the number of observations included.
PERFORMANCE OF NITROGEN-USE EFFICIENT NERICA4 RICE LINES IN INDONESIAN RAIN-FED ECOSYSTEMS

Rice absorbs only 30-40% of N fertilizer application. Therefore, one of the solutions is using a variety of rice that absorbs N more efficiently. This experiment is aimed at determining the yield parameters, NUE performance, and nitrous oxide flux of NERICA4 transgenic lines and NERICA4-wild-type in rain-fed agro-ecosystems at different doses of N fertilizer during a confined field trial. The experiment was conducted in Central Java, Indonesia, during the 2017/2018 rainy season. The experiment used a factorial randomized block design with four replications. Three transgenic lines of NERICA4 (NUE2, NUE9, NUE12) and NERICA4-WT were used as the main plot and N fertilizer rates (60, 120, and 180 kg N/ha) were used as the subplot. The results showed that an increase in the N fertilizer rate generally improved the plant height and the tiller number of NERICA4-NUE lines. The tiller numbers of NERICA4-NUE lines were higher than NERICA4-WT on high N dosages. There was a strong correlation between the N uptake and the grain yield. The analysis showed that all NERICA4-NUE lines use N more efficiently than NERICA4-WT, significantly at 60 kg N/ha with higher total grain than NERICA4-WT. NERICA4-NUE9 tended to emit lower nitrous oxide flux than other NERICA4-NUE and NERICA4-WT.
Observations on the Magnetic Disconnections of a Magnetic Cloud from the Sun through Magnetic Reconnection

Most coronal mass ejections (CMEs) originally exhibit closed magnetic flux rope (MFR) structures near the Sun. Moreover, the amount of magnetic field magnitude in the heliosphere can continually increase when CMEs propagate from the Sun to interplanetary space. To solve the problem of increased magnetic field magnitude, the closed field lines of MFRs should be opened and disconnected through magnetic reconnections. Here, we report a magnetic cloud (MC) associated with a magnetic reconnection exhaust measured by Wind over the period of 2001 October 31 to November 1. Observations of unidirectional suprathermal electron strahls revealed that part of the field lines before the rear boundary of the MC was opened. The magnetic reconnection event was disconnecting the opened field lines of the MC by merging with open field lines after the MC. These observations indicated that MFRs could be opened or disconnected in no particular order.
Tracking of manoeuvring targets using fuzzy information fusion filter

ABSTRACT The paper discusses the tracking of a manoeuvring target using fuzzy information fusion filters (FIFFs), based on bearing only measurements received from multiple sensors. While a number of tracking filters including the Kalman filters have been proposed and demonstrated successfully for tracking, the information filter has been reported to be capable of estimating the state of a target even without an initial estimate. However, the estimate is often seen to diverge after a short period. A FIFF has been shown to track small manoeuvres in target following a constant velocity model but is not effective when the target switches to a coordinated turn model. In this paper, the idea of using the FIFF for tracking manoeuvring target is proposed and demonstrated. The filter uses only the bearing measurements in tracking the target and also for detecting the manoeuvre. Using an adaptive turn rate model, the turning rate of the moving target is estimated from the range rate. Here, the range rate is also computed directly from bearing measurements. The detection of the onset of manoeuvre is on the basis of consistent change in the turning rate of the target. A number of different scenarios involving manoeuvring targets are given to demonstrate the efficacy of this approach.
Automated Segmentation of Individual Tree Structures Using Deep Learning over LiDAR Point Cloud Data

Deep learning techniques have been widely applied to classify tree species and segment tree structures. However, most recent studies have focused on the canopy and trunk segmentation, neglecting the branch segmentation. In this study, we proposed a new approach involving the use of the PointNet++ model for segmenting the canopy, trunk, and branches of trees. We introduced a preprocessing method for training LiDAR point cloud data specific to trees and identified an optimal learning environment for the PointNet++ model. We created two learning environments with varying numbers of representative points (between 2048 and 8192) for the PointNet++ model. To validate the performance of our approach, we empirically evaluated the model using LiDAR point cloud data obtained from 435 tree samples scanned by terrestrial LiDAR. These tree samples comprised Korean red pine, Korean pine, and Japanese larch species. When segmenting the canopy, trunk, and branches using the PointNet++ model, we found that resampling 25,000–30,000 points was suitable. The best performance was achieved when the number of representative points was set to 4096.
TREE SPECIES RECOGNITION AT STANDS SCALE: VALIDITY TEST OF MULTI-TEXTURE EXTRACTED FROM MULTISEASONAL UAV-BASED IMAGERY

In order to evaluate the effectiveness of multi-type texture features of images of four seasons in pure stand tree species recognition, this research applied 5-band RedEdge-MX sensor to collect remote sensing data of four seasons and extracted eight texture features, including mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment and correlation, from 20 spectral bands. Maximum likelihood classification and random forest were adopted for the determination of the best window for texture extraction which resulted in the construction of optimal texture feature set in tree species recognition. Then, the performance of these texture feature sets along with their combinations in tree species recognition was analyzed. Experimental findings showed that the eight texture features of four seasonal data performed well in the recognition of pure stand tree species. Texture feature mean presented the highest performance (with overall accuracy of 88.8559%) and worst variance (84.8180%). The combination of eight texture features further improved the recognition accuracy of tree species (92.0599%) compared with single texture features. The recognition accuracy of tree species could be further improved by combining eight texture features with spectral band and digital surface model (92.7002%). Research showed that the application of multi-type texture features in typical seasons of spring, summer, autumn and winter fully captured the differences of various tree species in different bands and seasons, which could be applied to the effectively identify pure stand tree species
Vortex-ring-induced stratified mixing: mixing model

The study of vortex-ring-induced mixing has been significant for understanding stratified turbulent mixing in the absence of a mean flow. Renewed interest in this topic has prompted the development of a one-dimensional model for the evolution of a stratified system in the context of isolated mixing events. This model is compared to numerical simulations and physical experiments of vortex rings interacting with a stratification. Qualitative agreement between the evolution of the density profiles is observed, along with close quantitative agreement of the mixing efficiency. This model highlights the key dynamical features of such isolated mixing events.
Frequency of Acute Kidney Injury with Hypoxic Ischemic Encephalopathy Staging in Neonates with Perinatal Asphyxia: An Observational Study (Descriptive Case Series)

Perinatal asphyxia affects almost all the organs in neonates, kidneys being one of commonly affected organs. Early recognition of disturbances in renal function is important for early intervention to prevent irreversible damage to kidneys. Objective: In this study we observed the frequency of acute kidney injury (AKI) in neonates with clinical staging of hypoxemic ischemic encephalopathy (HIE) in neonates with perinatal asphyxia. Methodology: An overall number of 145 term neonates with perinatal asphyxia admitted at nursery of Liaquat University Hospital, Hyderabad from February-2019 to july-2019 were included in this study. Urine output was monitored from day one and serum creatinine was sent on third day of life. Serum creatinine was sent early of those neonates having low urine output. Results: The average birth weight was 2.72±2.67 kg. There were 106 (73.1%) males and 39 (26.9%) females. Most neonates were born via simple vaginal delivery 100 (68.97%) and few via caesarian section 45 (31.03%). Out of 145 neonates 38 (26.21%) were in stage I, 95 (65.52%) in stage II and 12 (8.28%) in stage III HIE. Frequency of AKI in neonates with perinatal asphyxia was 55 (37.93%). Incidence of AKI was significantly high in stage II 45(81.8%) as compare to stage I 0(0%) and stage III 10(18.2%) (p=0.0005). Conclusion: AKI is a common complication of perinatal asphyxia. Further multicenter based and studies on large scale need to be done to identify the inter-relationship between maternal factors and perinatal asphyxia associated AKI to prevent neonatal morbidity and mortality. Keywords: Acute kidney injury, perinatal asphyxia, hypoxic ischemic encephalopathy.
Impact of Negative Discrete Emotion on Subjective Career Success with Mediation Role of Proactive Career Behavior

This study aims to investigate how (ANG) affects the (SCS), using the framework of affective event theory. Furthermore, the study seeks to shed light on the specific ways in which different aspects of (ANG) impact "(SCS)". by exploring the potential mediating role of (PCB). The study's primary objective is to provide light on how people might lessen (ANG's) deleterious effects on their (SCS) by investigating these pathways. Data from 415 individuals with jobs in the service industry in Pakistan was used to conduct statistical tests using a method called "structural equation modelling" (SEM). The study's results show that (ANG) significantly affects many facets of (SCS). Specifically, the findings show a negative direct effect of ANG on SCS, while also revealing a positive association between ANG & (PCB). Moreover, the research shows that PCB mediates the connection between ANG and SCS. Future studies should investigate the function of negative emotions and PCB, and SEFF as mediators of the SCS to fully comprehend its significance for both workers and employers. This problem may be alleviated and biases avoided by using an externally derived scale for a number of constructs.
A testable theory for high-Tc superconductivity in cuprates

A number of theories for the superconductivity in cuprates, have been proposed in the more than 30 years that have elapsed since its discovery. A common feature of these theories is the small number, or even the absence, of quantitative predictions that could be compared to a vast number of experimental data, which are, conversely, available. Such theories are, consequently non-testable. We describe the foundations and a number of applications of a theory describing High-Tc Superconductivity in cuprates, which we proposed recently, that besides being testable, has proven to meet successfully the tests to which it has been submitted so far.
Effect of Electronic Word of Mouth, Perceived Service Quality and Perceived Usefulness on Alibaba's Customer Commitment

Consumer behavior to do online shopping is growing with technological advances. To meet consumer needs for online shopping various e-commerce began to develop. Alibaba is one of the e-commerce services in the world that has emerged in the current digital era that provides various attractive offers and attractive sales products. Alibaba can be reached anywhere and anytime. This study aims to determine how the influence of electronic word of mouth, perceived service quality and perceived usefulness on Alibaba's customer commitment. The population used in this study were Alibaba users. This study used 100 respondents as the research sample. The data will be analyzed using multiple linear regression analysis techniques. The results show that electronic word of mouth, perceived service quality and price perception can have a significant effect on Alibaba's customer commitment.
Convergence dans le domaine complexe des séries de fonctions propres

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Adhesion factors and antimicrobial resistance of Escherichia coli strains associated with colibacillosis in piglets in Colombia

Background and Aims: The pathogenicity of Escherichia coli is determined by the presence of genes that mediate virulence factors such as adherence capacity and toxin production. This research aimed to identify the adhesion factors and antibiotic resistance capacity of E. coli strains associated with diarrhea in piglets in Colombia. Materials and Methods: Presumptive E. coli strains were isolated from the rectal swabs of piglets in swine farms between 4 and 40 days of age with evidence of diarrhea. Presumptive E. coli strains were tested for antibiotic resistance. The hemolytic capacity of presumptive E. coli strains was measured and molecularly identified. Strains confirmed as hemolytic E. coli was evaluated for the presence of five adhesion factors (F4, F5, F6, F18, and F41) and resistance to 11 antibiotics. Results: Fifty-two putative E. coli strains were isolated, six of which showed a hemolytic capacity. The hemolytic strains were molecularly identified as E. coli. Adhesive fimbriae were found in five of six β-hemolytic E. coli isolates. Combinations of the adhesion factors F6–F18 and F6–F41 were linked to antibiotic resistance capacity. Conclusion: The phenomenon of E. coli strains resistant to multiple antibiotics on pig farms represents a constant risk factor for public health and pig production.
Beamforming Network for 5G Applications

This paper is devoted to the design, analysis, and implementation of switched beamforming network operating at 5.2 GHz for 5G applications. It is intended to launch four beams. The Butler matrix feeding network is presented to electronically switch the beam in the desired direction. This work achieves a good approach to alleviate the problem of cross-over implementation and fabrication. A Four-element array of printed antennas is designed and fabricated. The network and array are implemented on Rogers RT/duroid 5880 substrate with a relative permittivity of 2.2 and a thickness of 1.04 mm. The different scattering parameters are simulated using both ADS and CST which conduct good agreement between the simulated and measured results.
Anthocyanins in Mulberry Leaves (Morus rubra L.) Ethanol Extract as the Inhibitor for the Growth of Candida albicans

Infections caused by Candida albicans are generally common in the vaginal mucosa or called Vulvovaginal Candidiasis. Herbal medicine is proven to be an alternative to treat vaginal candidiasis. Mulberry leaves have many chemical compounds, one of which is anthocyanins. Anthocyanins have pharmacological benefits and biological activity that can protect against human pathogenic bacteria. This study aims to observe the effect of anthocyanin compounds extracted from mulberry leaves (Morus Rubra L) on the growth of Candida albicans. Identification of compounds on mulberry leaves used the TLC spectrophotodensitometry on silica gel 60 F254. TLC plates were washed with methanol and activated at 110 degrees C for 30 minutes. The plates were eluted in a chamber that had been saturated with the mobile phase of n-butanol:glacial acetic acid:water (4:1:2) and transferred using a CMAG TLC densitometer with a spectrum in the wavelength range of 200-700 nm. Design study is experimental study with a short Post-Test Only Control Group. This study was conducted at the Pharmaceutical Biology Laboratory of PGRI Adi Buana University and the Laboratory of Professor Nidhom Foundation. The results showed that there was a content of anthocyanin compounds in mulberry leaves with antifungal function against Candida albicans.
Understanding the Mechanisms of Radiation Belt Dropouts Observed by Van Allen Probes

To achieve a better understanding of the dominant loss mechanisms for the rapid dropouts of radiation belt electrons, three distinct radiation belt dropout events observed by Van Allen Probes are comprehensively investigated. For each event, observations of the pitch angle distribution of electron fluxes and electromagnetic ion cyclotron (EMIC) waves are analyzed to determine the effects of atmospheric precipitation loss due to pitch angle scattering induced by EMIC waves. Last closed drift shells (LCDS) and magnetopause standoff position are obtained to evaluate the effects of magnetopause shadowing loss. Evolution of electron phase space density (PSD) versus L* profiles and the μ and K (first and second adiabatic invariants) dependence of the electron PSD drops are calculated to further analyze the dominant loss mechanisms at different L*. Our findings suggest that these radiation belt dropouts can be classified into distinct classes in terms of dominant loss mechanisms: magnetopause shadowing dominant, EMIC wave scattering dominant, and combination of both mechanisms. Different from previous understanding, our results show that magnetopause shadowing can deplete electrons at L* < 4, while EMIC waves can efficiently scatter electrons at L* > 4. Compared to the magnetopause standoff position, it is more reliable to use LCDS to evaluate the impact of magnetopause shadowing. The evolution of electron PSD versus L* profile and the μ, K dependence of electron PSD drops can provide critical and credible clues regarding the mechanisms responsible for electron losses at different L* over the outer radiation belt.
Pranayama Breathing Detection with Deep Learning Pranayama Breathing Detection with Deep Learning

Yoga, a complementary health approach, according to a 2017 National Health Interview Survey by the Center for Disease Control and Prevention (CDC), is a choice of around 14.3% adults in the US. Kapalbhati pranayama, a yoga practice of alternating fast exhales and longer passive inhales, is understood to improve our health. Incorrect and irregular practices, however, can cause injuries and adverse effects. To avoid these undesired effects, it is essential to maintain a pace fit for the practitioner. In the absence of any tools to observe a pace of practice, this work develops a deep learning method that listens to a person’s breathing sound and outputs the pace/counts of kapalbhati breathings in real-time. Our deep learning model, based on our own accuracy definition, is 93% accurate. The model, when packaged as an application, can be used by practitioners with a plan/prescription to observe and adjust their pace and counts per session. In this paper, we elaborately discuss the data collection, cleaning, labeling, deep learning architecture and training, challenges in development, and quantitative evaluation of our results. We plan to release our code publicly along with an application that the public can use. We would like to caution that this work aims to provide an example tool for maximizing benefits and minimizing the adverse effects and injuries from kapalbhati practice, but not to promote yoga practice.
Relationship Between Customer Expectations and Financial Performance of Food Industry Businesses in a Customer Satisfaction Model

Research on customer satisfaction in repeat purchases shows that the relationship between customer expectations and customer satisfaction can be inverse to what is commonly reported. This also has an impact on the nancial performance of an enterprise, which is therefore directly in uenced by customer expectations. The goal of this paper is to determine whether customer satisfaction affects customer expectations and whether these expectations have a direct impact on the nancial performance of an enterprise. The variables representing factors of customer satisfaction, including customer expectations, are measured using a customer survey. Business nancial performance (BFP) was measured using the ROA, ROE, and Asset Turnover indicators. The model was created using Structural Equation Modelling. The research con rmed a positive direct effect of customer expectations on BFP (speci cally ROA). Customer satisfaction impacted nancial performance indirectly via customer expectations in two years. This suggests that the in uence of customer expectations on BFP is long-term in nature, although this effect is rather weak. As customers make repeat purchases, customer expectations change. These changes re ect relationships primarily with customer satisfaction and loyalty and BFP. Customer satisfaction is shown to in uence customer expectations, which in turn in uence BFP. Therefore, it is advisable to focus on (raising) customer expectations in repeat purchases if the businesses want to achieve higher nancial performance.