Miracle-dz/UniFAR-FTUs huggingface dataset:
Interobserver Reliability of Tear Break-Up Time Examination Using “Smart Eye Camera” in Indonesian Remote Area

Introduction Dry eye disease (DED) is a multifactorial disease of tears and ocular surface that results in symptoms of discomfort, visual disturbance, and tear film instability leading to decrease of vision, productivity and quality of life, and blindness. DED diagnosis remains difficult and underdiagnosed regarding inconsistency between subjective symptoms and clinical findings. Tear break-up time (TBUT) is an objective indicator of tear film stability in diagnostic DED. A novel smartphone attachment, namely SEC (smart eye camera), could mimic conventional slit lamp to assess TBUT and beneficial in facilitating DED diagnosis. Reliability between a non and an ophthalmologist in TBUT assessment and DED diagnosis is observed in this study. Purpose To determine interobserver reliability of TBUT measurement for diagnosing DED using SEC. Design This a cross-sectional analytic study involving 99 participants (198 eyes) aged 40 years who visited Pratama Gema Santi Hospital, Nusa Penida, from September 2nd to 4th, 2022, with consecutive sampling technique. Methods Fluoresceined eyes were filmed using the SEC device and apps, continued by masked ophthalmologist and resident assessing TBUT based on the video. The primary outcome is interobserver reliability for TBUT measurement and DED diagnosis. Results The mean age of participants was 55.22±9.78 years, 48.5% male and 51.5% female. The reliability of interobserver in assessing DED based on TBUT test is 0.78 (95% CI=0.31–1.26, P-value=0.001), and interobserver reliability in diagnosing DED based on OSDI and TBUT showed good agreement (weighted kappa=0.71). Good interobserver reliability underscores that non-ophthalmologists can diagnose DED based on TBUT video using SEC. Conclusion SEC video has good interobserver reliability to assess TBUT for DED diagnosis. SEC can be used as one of the methods in assessing DED in limited health care facilities. The high reliability of interobserver assessment indicates that DED diagnosis using video taken with SEC may be useful for telemedicine evaluation in remote areas.
Exploring Mangifera indica (Anacardiaceae) leaf and bark methanol extracts as potential adjuvant therapy in the management of multidrug-resistant Staphylococcus aureus

Background: After several decades of antibiotic use, pathogenic bacteria have reached alarming levels of resistance. Staphylococcus aureus is the most common cause of nosocomial infections, and treatment is difficult owing to the advent of multidrug-resistant (MDR) strains. This motivates the search for more potent drugs. Foremost, adjuvant compounds that increase the effectiveness of conventional antibiotics are also being researched extensively. The current study examined the anti-staphylococcal and antibiotic-resistance reversal effects of the methanol extracts of Mangifera indica (leaves and bark). Methods: Botanicals were tested alone, in the presence of reserpine (efflux pump inhibitor), and in association with commonly prescribed antibiotics, using a 96-well broth microdilution method against a panel of seventeen MDR strains and clinical isolates of S. aureus, including methicillin-resistant strains (MRSA). The ability of the leaf extract to inhibit H+-ATPase-mediated proton pumping was determined by controlling the acidification of the bacterial solution, whereas the influence on bacterial kinetic growth was determined by measuring absorbance (OD600 nm) after exposure to various concentrations of the test extract. Results: M. indica leaf and bark extracts exhibited exceptional anti-staphylococcal capabilities, inhibiting 100% of the S. aureus strains tested. The minimal inhibitory concentrations (MICs) recorded varied from 256 to 2048 µg/mL; the effects were bactericidal (MBC/MIC ≤ 4) in most cases. The bark extract demonstrated an outstanding potential to improve the efficacy of conventional antibiotics. The activity of chloramphenicol, doxycycline, tetracycline, levofloxacin, and ampicillin was enhanced against 100% of studied MDR S. aureus in association with the bark extract at sub-inhibitory concentrations of MIC/2 and MIC/4. The leaf extract of M. indica induced a concentration-dependent inhibition of S. aureus MRSA4 growth over 20 hours of exposure at 0.5×MIC, MIC, and 2×MIC. The latent phase has been extended up to 6 hours after treatment with the extract. Similarly, M. indica leaf extract significantly reduced the acidity of the bacterial solution in a concentration-dependent manner, indicating a possible target of its antibacterial effect. Conclusion: The present study revealed the remarkable activity of M. indica leaf and bark extracts against MDR strains and clinical isolates of S. aureus, including MRSA. The bark extract might be used as an adjuvant to antibiotic therapy, as indicated by its notable potentiation activity when combined with conventional antibiotics. Keywords: Antibacterial activity; Mangifera indica; multidrug resistance; potentiation; Staphylococcus aureus.
The structure and evolution of vortex lines in supercell thunderstorms

Vortex lines have been analyzed relatively infrequently within the severe storms community, and when they have been shown, often they only are presented schematically within conceptual models (e.g., to illustrate the vorticity tilting process responsible for midlevel mesocyclogenesis). We recently have been looking at vortex lines in observed and simulated supercell thunderstorms. Is there anything that can be gleaned about the processes associated with the amplification of low-level rotation from examining vortex lines? In our oral presentation, we focus on the vortex line “arches” that emanate from the low-level mesocyclones of supercells (both tornadic and nontornadic). The oral presentation summarizes the idealized simulation and observational findings presented in recent articles by Straka et al. (2007) and Markowski et al. (2008). Also discussed in the oral presentation is the kinematic and probable dynamic similarity of the vortex line arches observed in supercells to those observed in larger-scale convective systems in conjunction with line-end vortices. Moreover, we present some speculations about why tornadogenesis is favored in supercell environments that have high relative humidity in the boundary layer and strong low-level shear. Given the time constraints, our oral presentation does include a discussion of the evolution of vortex lines that precedes the development of vortex line arches. The discussion is presented below instead.
Functional regression analysis and variable selection for motion data

Modern technology offers us highly evolved data collection devices. They allow us to observe data densely over continua such as time, distance, space and so on. The observations are normally assumed to follow certain continuous and smooth underline functions of the continua. Thus the analysis must consider two important properties of functional data: infinite dimension and the smoothness. Traditional multivariate data analysis normally works with low dimension and independent data. Therefore, we need to develop new methodology to conduct functional data analysis. In this thesis, we first study the linear relationship between a scalar variable and a group of functional variables using three different discrete methods. We combine this linear relationship with the idea from least angle regression to propose a new variable selection method, named as functional LARS. It is designed for functional linear regression with scalar response and a group of mixture of functional and scalar variables. We also propose two new stopping rules for the algorithm, since the conventional stopping rules may fail for functional data. The algorithm can be used when there are more variables than samples. The performance of the algorithm and the stopping rules is compared with existed algorithms by comprehensive simulation studies. The proposed algorithm is applied to analyse motion data including scalar response, more than 200 scalar covariates and 500 functional covariates. Models with or without functional variables are compared. We have achieved very accurate results for this complex data particularly the models including functional covariates. The research in functional variable selection is limited due to its complexity and onerous computational burdens. We have demonstrated that the proposed functional LARS is a very efficient method and can cope with functional data very large dimension. The methodology and the idea have the potential to be used to address other challenging problems in functional data analysis.
Enhanced Cell Wall and Cell Membrane Activity Promotes Heat Adaptation of Enterococcus faecium

Enterococcus faecium (E. faecium) is widely used in foods and is known as a probiotic to treat or prevent diarrhea in pets and livestock. However, the poor resistance of E. faecium to high temperature processing procedures limits its use. Strain domestication is a low-cost and effective method to obtain high-temperature-resistant strains. In this study, heat treatment was performed from 45 °C to 70 °C and the temperature was gradually increased by 5 °C every 3 days. After domestication, the survival rates of the high temperature adaptation strain RS047-wl under 65 °C water bath for 40 min was 11.5 times higher than WT RS047. Moreover, the saturated fatty acid (SFA) contents in cell membrane and the cell volume significantly increased in the RS047-wl. The combined transcriptomic, metabolomic, and proteomics analysis results showed a significant enhancement of cell wall and membrane synthesis ability in the RS047-wl. In conclusion, one of the main factors contributing to the improved high temperature resistance of RS047-wl was its enhanced ability to synthesize cell wall and membrane, which helped maintain normal cell morphology. Developing a high-temperature-resistant strain and understanding its mechanism enables it to adapt to high temperatures. This lays the groundwork for its future development and application.
Utilisation of new media in communicating insecurity in Southeast Nigeria

This paper aims to describe how in recent times, the issue of insecurity in the southeast of Nigeria is alarming. People are no longer safe as they have become targets for the perpetrators of insecurity within the region. In all of these cases, people must be fully aware of the level of insecurity in a specific location in order to determine the next course of action. In order to achieve this, this study examined the use of new media to communicate insecurity in Southeast Nigeria. The study was founded on the premise of technological determinism. In this research, a survey research approach was used. Using the Wimmer and Dominick sample size calculator, a sample of 384 was generated from the study's population of 22,012,828. A questionnaire was utilised as a data collection tool. Meanwhile, the multistage sampling procedure was used. Data was analysed with the use of descriptive statistics and pie chart. The finding showed that 51.0% of respondents had been exposed to insecurity messages via new media to a very large extent. It was also revealed that on an average of 74.8% (N=367), new media has been used in communicating insecurity among residents in southeastern Nigeria to a very large extent. It was recommended that new media users should be sensitized on the need to use the platform appropriately or with a sense of responsibility instead of using it to fuel more security problems within the southeastern region of Nigeria.
Spectrally-Efficient Modulation on Conjugate-Reciprocal Zeros (SE-MOCZ) for Non-Coherent Short Packet Communications

This paper proposes a non-coherent communication scheme for short packet communications (SPCs), called spectrally-efficient modulation on conjugate reciprocal zeros (SE-MOCZ). The proposed SE-MOCZ scheme is realized by combining the recently-proposed MOCZ and faster-than-Nyquist (FTN) signaling. Specifically, the pulses carrying the polynomial coefficients of MOCZ are accelerated beyond the Nyquist limit to enhance the spectral efficiency. The spectral efficiency enhancement, however, comes at the expense of inter-polynomial-coefficient interference (IPCI), which increases the number of received complex zeros in the $z$ -domain of the polynomial representing the received signal. We design a partial-complex-zeros-removal filter at the receiver to partially remove the pre-defined zeros due to the FTN signaling. Furthermore, we also optimize the radius of the transmit complex zeros in SE-MOCZ to improve the bit error rate (BER) performance. We propose a maximum likelihood (ML) detector for the proposed SE-MOCZ scheme. To strike a balance between the BER performance and computational complexity, we adopt a root-finding minimum distance (RFMD)-based detector. Simulation results clearly show the performance advantage of the proposed SE-MOCZ when compared to MOCZ for a wide range of operating parameters.
Optimal Multi-Attribute Auctions Based on Multi-Scale Loss Network

There is a strong demand for multi-attribute auctions in real-world scenarios for non-price attributes that allow participants to express their preferences and the item’s value. However, this also makes it difficult to perform calculations with incomplete information, as a single attribute—price—no longer determines the revenue. At the same time, the mechanism must satisfy individual rationality (IR) and incentive compatibility (IC). This paper proposes an innovative dual network to solve these problems. A shared MLP module is constructed to extract bidder features, and multiple-scale loss is used to determine network status and update. The method was tested on real and extended cases, showing that the approach effectively improves the auctioneer’s revenue without compromising the bidder.
An EMF Observer for PMSM Sensorless Drives Adaptive to Stator Resistance and Rotor Flux Linkage

The electromotive force (EMF) observer-based sensorless algorithms are sensitive to temperature rise because it requires the stator resistance (<inline-formula> <tex-math notation="LaTeX">$R_{s}$ </tex-math></inline-formula>) or the rotor flux linkage (<inline-formula> <tex-math notation="LaTeX">$\psi _{r}$ </tex-math></inline-formula>). The temperature measuring of an operating motor can be difficult, therefore, adaptive sensorless algorithms with online <inline-formula> <tex-math notation="LaTeX">$R_{s}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\psi _{r}$ </tex-math></inline-formula> estimation are appreciated. However, existing methods require extra signal injections, transient operations or estimate <inline-formula> <tex-math notation="LaTeX">$R_{s}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\psi _{r}$ </tex-math></inline-formula> one at a time to overcome the rank-deficient problem. In this paper, an adaptive EMF observer which is able to estimate both <inline-formula> <tex-math notation="LaTeX">$R_{s}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\psi _{r}$ </tex-math></inline-formula> simultaneously without requiring any signal injections or transient operations is proposed. The method exploits the harmonic back EMFs (HBEMF) to serve as a novel reference model and regulates the <inline-formula> <tex-math notation="LaTeX">$R_{s}$ </tex-math></inline-formula> value in the EMF observer accordingly. The rank deficient problem is solved with the extra information provided by the HBEMFs. To make use of the HBEMFs, a parameter insensitive extraction method and an algorithm to calculate the rotor position from them are proposed. With the proposed reference model, an adaptive scheme to regulate <inline-formula> <tex-math notation="LaTeX">$R_{s}$ </tex-math></inline-formula> is proposed. To obtain the rotor flux linkage, a <inline-formula> <tex-math notation="LaTeX">$\psi _{r}$ </tex-math></inline-formula> estimator is also developed. The effectiveness of these proposed methods is verified with experiments and simulations.
Biomechanical Analysis of Muscle Fatigue and Ground Reaction Force for the Development of Outdoor Walking Shoes

Objective: The purpose of this study was to analyze and compare different kinds of outdoor walking shoes in terms of muscle fatigue and ground reaction force on walking, and to provide foundational data for developing and choosing outdoor walking shoes that fit the users. Method: The study subjects were 30 healthy men. The experiment was conducted by using outdoor walking shoes with different inner and outer harnesses of the midsole, and shapes of the outsole. For data collection, electromyography was used to measure the muscle fatigue of the anterior tibial muscle and gastrocnemii, which contribute to the dorsiflexion and plantarflexion of the ankle joint, and the biceps muscle of the thigh and lateral great muscles, which contribute to the flexion and extension of the knee joint. A GRF measurement device was used to measure the X , Y , and Z axes. Results: In the type A outdoor walking shoes, regarding the hardness of the midsole, the inner part was soft, while the outer part was hard. The vertical ground reaction force was the lowest, which means least impact while walking and light load to the knees and ankles. The type C outdoor walking shoes were intended to provide a good feel in wearing the shoes. The tibialis anterior, biceps femoris, and gastrocnemii indicate low fatigue, which means that during a long-distance walk, it will minimize the fatigue in the muscles of the lower limbs. Conclusion: To sum up the study results, the different types of outdoor walking shoes indicate their unique characteristics in the biomechanical comparison and analysis. However, the difference was not statistically significant. Thus, a systematic and constant follow-up research should be conducted to cope with expanding market for outdoor walking shoes. Lastly, this study is expected to present foundational data and directions for developing outdoor walking shoes.
Robotic Surgery: A Comprehensive Review of the Literature and Current Trends

Robotic surgery (RS) is an evolution of minimally invasive surgery that combines medical science, robotics, and engineering. The first robots approved by the Food and Drug Administration (FDA) were the Da Vinci Surgical System and the ZEUS Robotic Surgical System, which have been improving over time. Through the decades, the equipment applied to RS had undergone a wide transformation as a response to the development of new techniques and facilities for the assembly and implementation of the own. RS has revolutionized the field of urology, enabling surgeons to perform complex procedures with greater precision and accuracy, and many other surgical specialties such as gynecology, general surgery, otolaryngology, cardiothoracic surgery, and neurosurgery. Several benefits, such as a better approach to the surgical site, a three-dimensional image that improves depth perception, and smaller scars, enhance range of motion, allowing the surgeon to conduct more complicated surgical operations, and reduced postoperative complications have made robotic-assisted surgery an increasingly popular approach. However, some points like the cost of surgical procedures, equipment-instrument, and maintenance are important aspects to consider. Machine learning will likely have a role to play in surgical training shortly through "automated performance metrics," where algorithms observe and "learn" individual surgeons’ techniques, assess performance, and anticipate surgical outcomes with the potential to individualize surgical training and aid decision-making in real time.
Do the Dragons Move Together; Co-integrated and Causality Study Among Chinese Bourses-A Curious Case of Hang Seng and Shanghai Stock Exchange

Hang Seng (HSI) and Shanghai (SSE) are the two pillars of Chinese dominance for the past 25–30 years among the global bourses. However, both the indices have very little in common, as far as ingredients are concerned. Mutual Stock Connect in 2014 has opened the doors from both the sides for the investors, raising a question on the co-integration once again. On one hand, Hang Seng attracted foreign investors (both retail and Institutional) and on the other hand Shanghai focussed more on domestic funds that are stickier in nature. This study inspects the chances and the intensity of the Causal relationship between these two dragon indices. The time period is for two and a half decades and the tools that are used include Johansen Co-integration Test and Bivariate Granger Causality. The test finds medium to strong relative dependency and reciprocity despite very few stocks being common. It also finds Shanghai (SSE) as the lead or the driver index, and Hang Seng (HSI) as the driven index. Even the model of two indices is different as well (HSI follows Moving Averages and SSE follows ARMA). In efficient markets, this kind of secular movement is quite evident in nature, and thus the study confirms that Chinese capital markets are proven to be tending towards the efficient side.
THE FOURIER TRANSFORM BASED DESCRIPTOR FOR VISUAL OBJECT CLASSIFICATION

Most of the state-of-arts visual object classification methods use image representations such as bag of words (BoW) or Fisher vector (FV) models, which are built depend on encoding local features. In that context, local patches sampled from images are represented by different shape and texture descriptors such as SIFT, LBP, SURF, etc. In this study, we define a new descriptor depend on weighted histograms of phase angles of local 2-D discrete Fourier transform (FT). We make comparison with the classification accuracies achieved by using the proposed descriptor to the ones obtained by other commonly used descriptors on Caltech 4, Caltech-101, Coil-100 and PASCAL VOC 2007 data sets. Experimental results show that our proposed descriptor provides good accuracies (the best results on Caltech-4 and Coil-100, and the second best result on Caltech-101 and PASCAL VOC 2007 datasets) reporting that FT based local descriptor obtain major belongings of images that are valuable for visual object classification. The combination of image representations resulting from FT descriptor with the representations is achieved by other descriptors, results even get better put forwarding that tested descriptors encode different supplementary knowledge.