Miracle-dz/UniFAR-FTUs huggingface dataset:
Meibomian gland cyst detection and classification using hyperspectral imaging

Abstract The primary role of the oily secretion (meibum) is to ensure tear film stability and retard evaporation. In addition to these is providing ocular surface lubrication, which is necessary for smooth eyelid movements. When a gland is blocked, it is described as a Meibomian gland cyst (MGC), which can be a meibomian cyst, usually referred to as chalazion (eye bump), or in the case of inflammation, it is considered to be a hordeolum (sty or stye). Topical ophthalmic ointments and eyelid heat massages can treat early diagnosed MGC; otherwise, surgical operation is required. The current techniques of diagnosing MGC are usually uncomfortable or invasive, such as examining the tarsal plate after everting the eyelid or by biopsy procedures. The purpose of this work is to propose a non-invasive MGC evaluation and classification technique using hyperspectral imaging and image processing. The proposed technique was carried out on a single patient (i.e., case study) for a period of 4 months to monitor the MGC evolution until postsurgery-recovery and was compared with a normal eyelid patient. The collected hypercube data were processed using Multivariate Curve Resolution (MCR) and image analysis to classify the MGC severity levels. The proposed work built the threshold of the complete system, where early diagnosis of an MGC is possible before it becomes visible to the eye, hence reducing the treatment duration and avoiding any further complications that require clinical lancing. Also, the system can be used as a postoperative check postsurgery to make sure the eyelid went back to normal.
Environmental Threats over Amazonian Indigenous Lands

This study investigates the main threats related to environmental degradation that affect Amazonian Indigenous Lands (ILs). Through a cluster analysis, we group ILs according to the set of common environmental threats that occur within and outside their limits. The results show that most of the 383 ILs are affected internally by a combination of different environmental threats, namely: deforestation, forest degradation, fires, mining, croplands, pastures, and roads. However, the ILs affected by multiple and relatively severe threats are mainly located in the arc of deforestation and the Roraima state. The threats related to forest loss (deforestation, forest degradation, and fires) are more intense in the ILs’ buffer zones than within, showing that ILs effectively promote environmental preservation. In the cluster analysis, we identified seven clusters that are characterized by common environmental threats within and around their limits, and, based on these results, we have outlined four environmental policy priorities to be strengthened and applied in Amazonian ILs: protecting ILs’ buffer zones; strengthening surveillance actions, and combating illegal deforestation, forest degradation, and mining activities in ILs; preventing and fighting fires; and removing invaders from all ILs in the Amazon. In this study, we warn that the threats presented make the Indigenous peoples in the Amazon more vulnerable. To guarantee indigenous peoples’ rights, illegal actions in these territories and their surroundings must be contained, and quickly.
The Impact of Covid-19 on Millennial Perceptions of Experience Quality and Flow of Experience and Its Influence on Behavior Intention to Revisit a Nature and Rural Destination (Case on Jakarta, Indonesia)

The purpose of this research is to study Quality of Experience and Flow of Experience and their influence on Behavioral Intentions to visit natural and rural destinations for the millennial generation. A total of 156 respondents were assessed and valid for further analysis. The result is that the Quality of Experience determines the satisfaction and behavioral intentions of millennials. Meanwhile, it is recommended that flow of experience be used to influence satisfaction because it has no effect on behavioral intention. The results also show how satisfaction can be a strong mediation of the two independent variables on behavioral intention. This study uses Structural Equation Modeling (SEM) with a Partial Least Square approach using SMARTPLS 3.0. The population of this research is millennials in the Jakarta area and its surroundings. The questionnaire was run while Jakarta was implementing the Health Protocol for distance and movement restrictions to avoid the spread of Covid-19.
Does negative contact undermine attempts to improve intergroup relations? Deepening the understanding of negative contact and its consequences for intergroup contact research and interventions

Intergroup contact is an established pathway to improve intergroup relations. Research has long focused on mainly positive intergroup contact and its capability to improve intergroup relations. Yet, if members of different groups meet, they will not only make positive, but possibly also negative intergroup contact experiences. Recent research considering both positive as well as negative intergroup contact has raised concerns about potentially stronger effects of negative compared to positive contact. These new insights and the increasing awareness of potentially detrimental effects of contact could lead to doubts about whether it is always sensible to bring individuals from different groups together. in everyday settings. We continue by answering calls to increase a more qualitative understanding of what kinds of experiences are seen to be intergroup contact, and where intergroup contact in everyday life is experienced from a lay understanding, with new qualitative data from British White and British Asian individuals. Our results demonstrate that positive as well as negative contact is often rather casual and happens in public spaces and at work. Interventions explicitly addressing these spaces may help to reach more people. We also demonstrate that positive contact is much more frequent than negative contact. This finding is confirmed in the third section, which reviews the relative frequency of positive and negative intergroup contact. Last but not least, we discuss the implications of our review for practitioners and researchers alike.
Highly dispersed sulfur in ordered mesoporous carbon sphere as a composite cathode for rechargeable polymer Li/S battery

A mesoporous carbon sphere with the uniform channels (OMC) is employed as the conductive matrix in the sulfur cathode for the lithium sulfur battery based on all-solid-state PEO(18)Li(CF(3)SO(2))(2)N-10 wt%SiO(2) electrolyte. Cyclic voltammograms (CV) and electrochemical impedance spectrum (EIS) suggest that the electrochemical stability of the S-OMCs is obviously superior to the pristine sulfur cathode. The S-OMCs composite shows excellent cycling performance with a reversible discharge capacity of about 800 mAhg(-1) after 25 cycles. This would be attributed to an appropriate conductive structure in which the active sulfur is highly dispersed in and contacted with the OMCs matrix.
Examining the Dimensions of Organizational Climate on Employee’s creativity in Jordanian Hotels

The objective of this study is to develop and test a conceptual framework which linked the creativity of employees with four organizational climatic factors: the structure, obligation, rewards, and support, as well as the connection between creativity of employees and performance of employees. 432 employees in 18 luxury hotels in Jordan obtained data. The quantitative study is focused on an empirical exploratory factor, a basic linear regression analysis and the validity of the CFA factor solution. Results and recommendations in the study showed that the relationship between employee creativity and employee success affects the creativity of workers through different organizational factors. This study aims to strengthen the organizational environment and results for hotels in the area of hospitality in order to enhance their organizational climate.
Empirical Study on Effects of Self-Correction in Crowdsourced Microtasks

Self-correction for crowdsourced tasks is a two-stage setting that allows a crowd worker to review the task results of other workers; the worker is then given a chance to update their results according to the review.Self-correction was proposed as a complementary approach to statistical algorithms, in which workers independently perform the same task.It can provide higher-quality results with low additional costs. However, thus far, the effects have only been demonstrated in simulations, and empirical evaluations are required.In addition, as self-correction provides feedback to workers, an interesting question arises: whether perceptual learning is observed in self-correction tasks.This paper reports our experimental results on self-corrections with a real-world crowdsourcing service.We found that:(1) Self-correction is effective for making workers reconsider their judgments. (2) Self-correction is effective more if workers are shown the task results of higher-quality workers during the second stage. (3) A perceptual learning effect is observed in some cases. Self-correction can provide feedback that shows workers how to provide high-quality answers in future tasks. (4) A Perceptual learning effect is observed, particularly with workers who moderately change answers in the second stage. This suggests that we can measure the learning potential of workers.These findings imply that requesters/crowdsourcing services can construct a positive loop for improved task results by the self-correction approach.However, (5) no long-term effects of the self-correction task were transferred to other similar tasks in two different settings.
Productivity and Chemical Constituents of some Maize Hybrids as Affected by Foliar Sprinkle Treatments

At Experimental Station Farm, Faculty of Agriculture, Mansoura University, Egypt, throughout 2019 and 2020 years, 2 field experiments were done to study the effect of sprinkle treatments (without, sprinkle with NPK, Zn + Mn + Fe, seaweed extract and combination of NPK + “Zn + Mn + Fe” and seaweed extract) on development, yield and its ingredient and chemical constituents of three maize hybrids (TWC 368, SC 162 and SC168). Every trial was brought in a strip-plot design with 4 duplications. The results appeared that SC 168 hybrid exceeded other researched hybrids (TWC 368 and SC 162) in all studied characters, except plant height and stover yield fed in jointly seasons. Foliar sprinkle maize plants 3 periods with combination of Fert-plus powder at 4 g liter + Zn, Mn and Fe at 3.0 g of each liter + seaweed extract (SWE) at 1.0 g liter water, which topped further foliar sprinkle treatments and formed the highest growth characteristics, yields and its attributes, chemical constituents and uptakes in jointly seasons. It could be decided that sprayed maize SC 168 or SC 162 hybrids with combination of Fert-plus fertilizer at 4 g + micro-elements (Zn, Mn and Fe) at 3.0 g + seaweed extract at 1.0 g liter water in each sprinkle in order to maximize productivity, NPK contents and uptakes underneath the ecological situations of Dakahlia Governorate, Egypt.
The Dynamic Correlation among Financial Leverage, House Price, and Consumer Expenditure in China

With the help of the time-varying parameter vector autoregression with stochastic volatility (TVP-SV-VAR) model and the Bayesian dynamic conditional correlational autoregressive conditional heteroscedasticity (Bayesian DCC-GARCH) model, this study analyzes the interaction mechanism and dynamic correlation among financial leverage, house price, and consumer expenditure (the survey data are collected from China’s National Bureau of Statistics from January 2000 to December 2019; the data on financial leverage and consumer expenditure are from the Wind economic database, and the price of commercial housing was calculated based on the sales volume and area of commercial housing on the official website of China’s National Bureau of Statistics). Empirical results show that an increase in financial leverage significantly increases house prices and reduces consumer expenditure, that a rise in house prices inhibits financial leverage and weakens consumer expenditure, and that an increase in consumer expenditure raises financial leverage and stimulates a rise in house prices. In addition, house price and consumer expenditure are most relevant, followed by financial leverage and consumer expenditure, and then by financial leverage and house price. Therefore, systematic analysis of dynamic correlation among the three variables has important practical significance for formulating appropriate financial policies to stabilize house prices and promote the growth of consumer expenditures. Specially, financial leverage is an important factor to hold back soaring house prices and shrinking consumer expenditure. Therefore, monetary and macroprudential policies should be used to deal with financial leverage variables in order to achieve a balanced and sustainable development of the macroeconomy in China.
The comparison of curcumin and nanocurcumin effects on the expression of E6 and E7 human papilloma virus oncogenes and P53 and pRb factors in HeLa and fibroblast cell lines

Cervical cancer is a common cancer in women around the world. Human papillomavirus infection is main cause of this cancer. Currently treatment methods include chemotherapy, radiation therapy and surgery. These methods usually cause severe reactions and drug resistance in the patients, so finding a safe natural drug for treatment can be very helpful. Curcumin is a compound derived from the root of the Curcuma longa plant and is the active ingredient in a food spice. Various studies have confirmed the anti-cancer, chemoprotective and genes and proteins regulatory effects of this component. Insolubility, low cellular uptake and low bioavailability are common limitations of curcumin use. To overcome these limitations, a nano-formulation of curcumin has been developed in our laboratory. In this study, the effect of nanocurcumin on cellular apoptosis induction of Hela cancer cells was compared with curcumin. It has demonstrated that nanocurcumin function is three time more effective than curcumin in same concentration. This nano-formulation of curcumin in 15µM concentration was able to reduce the expression of E6 and E7 oncogenes, and increase P53 and Rb tumor suppressors in HeLa cancerous cells with p-value = 0.001 − 0.0001, whereas curcumin altered these genes expression in 50µM concentration with p-value = 0.05 − 0.01. Nanocurcumin has no significant effect on the viability of normal fibroblast cells. Therefore, this compound has no effect on normal cells. These findings are consistent with the results of previous studies about nanocurcurcumin in other types of cancer. Therefore, nanocurcumin may be a suitable option to consider for cervical cancer treatment.
An Improved MPPT Method with Dynamic Voltage Error Compensation under Two Varying External Conditions

This paper presents a new maximum power point tracking (MPPT) method which can improve the dynamic tracking ability under two varying external conditions, rapid irradiance variation and grid voltage fluctuation. Different from irradiance variation, the dynamic error of tracking voltage caused by grid voltage fluctuation is usually ignored by MPPT methods. The dynamic error of tracking voltage can make the unexpected power change of photovoltaic system and influence the dynamic MPPT efficiency. According to the different current increment changes under the irradiance variation and the grid voltage fluctuation, the reasons of dynamic voltage errors are analyzed and distinguished. And two corresponding modes of variable step size are designed in the tracking algorithm to regulate the voltage deviation from MPPs. The effectiveness and the improved dynamic tracking performance of the proposed MPPT method are verified by simulation results under the above two varying external conditions.
Uncertainty quantification for the distribution-to-warping function regression method used in distribution reconstruction of missing structural health monitoring data

Data loss is a common problem of structural health monitoring and adversely affects many structural health monitoring applications. Tremendous progress in missing structural health monitoring data imputation has been made in recent years, forming an important part of sensor validation. Most of the imputed data are based on estimates obtained by data-driven statistical or machine learning models; quantifying their estimation uncertainties is significant in terms of being able to perform accuracy assessments and providing more insights into the imputed data. However, this procedure has been surprisingly neglected in the structural health monitoring community. This article focuses on uncertainty quantification for the distribution-to-warping function regression method (an indirect distribution-to-distribution regression method) used in reconstructing distributions of missing data. The distribution-to-warping function regression method belongs to the framework of functional data analysis as both the predictor and response are continuous functions. The challenge of performing uncertainty quantification for the distribution-to-warping function regression method comes not only from the functional nature of warping functions but also from their inherent constraints. To this end, a functional transformation is employed to transform warping functions into a vector space, and the confidence estimation for the regression operator is conducted in the vector space based on functional principal component analysis and bootstrapping. Then, the confidence region of the conditional expectation of missing distribution (caused by data loss) can be further estimated and visualized. In addition, a calibration processing procedure is also considered to obtain improved estimates of the confidence intervals with a better coverage accuracy under the desired probability. Simulation studies are conducted to validate and illustrate the proposed method, and then, it is applied to field strain monitoring data.
Application Research of Big Data Real-time Processing Technology in Smart Grid

Big data is valuable, and big data processing technology can efficiently process massive data and get the value in big data, so the research and application of big data technology become popular nowadays. Smart grid is one of the most potential field for application of big data technology, applying big data technology to smart grid can improve the reliability and economy of smart grid. The operating conditions of power system changes rapidly, therefore, real-time processing technology became the focus of application field. This paper reviewed the data sources, data characteristics and data application scenarios of big data in smart grid, analyzed data processing modes of big data processing technology: batch processing and stream processing, and compared the realization methods of real-time big data processing, summarized the application of big data real-time processing technology in smart grid, and the challenges in the application, and finally, prospected the application of real-time big data processing technology in smart grid.
Estudio comparativo de las fracciones lipídicas de Bactris gasipaes Kunth (chontaduro) obtenidas por extracción soxhlet y por extracción con CO2 supercrítico

The efficiency and composition of lipid extracts of peach palm pulp ( Bactris gasipaes Kunth), harvested in four different locations in the Colombian Pacific region, were evaluated by two different extraction methods. Soxhlet extraction method with hexane as a solvent, and supercritical fluid CO 2 extraction method (SFE CO 2 ) at 26,890 MPa and 330 K were tested. Results showed a higher efficiency for the SFE CO 2 method (4.03-8.28% m/m) as compared to the Soxhlet method (1.5-2.73% m/m) for four ecotypes or crops. Furthermore, the lipids characterization of the different ecotypes, performed by gas chromatography with a flame ionization detector (FID), showed a high content of unsaturated fatty acids, olive oil-like, with 36.23-51.89% m/m oleic acid, 2.38-8.82% m/m linoleic acid, and 0.22-1.58% m/m linolenic acid. The lipid content of peach palm fruit corroborate its potential as a very good source of essential fatty acids.
Oral Sildenafil in the Treatment of Erectile Dysfunction

This chapter summarizes the results of a landmark trial comparing different doses of oral sildenafil versus placebo to treat erectile dysfunction. Patients received either an identical placebo or 25- mg, 50-mg, or 100-mg tablets of sildenafil to be taken approximately one hour before planned sexual activity (but not more than once daily) for 24 weeks. Higher doses of sildenafil resulted in higher mean score for frequency of penetration and maintenance of erection, which were also consistently better than placebo. The most common side effects were headaches, flushing, dyspepsia, rhinitis, and visual disturbances. This study established sildenafil as an effective, reasonably well-tolerated treatment for men with erectile dysfunction of varying etiologies.
Influence of manufacturing parameters on the mechanical properties of nano-reinforced CFRP by carbon nanofibers

One of the most relevant problems of nano-reinforced resins is the uniform dispersion of nanoparticles. This problem is even more relevant when they are involved in the production of laminated composites. In this case, in addition to the agglomeration of nanoparticles, air bubbles are also very frequent during the manufacturing process of laminated composites with nano-reinforced resins. These air bubbles are even more frequent in the manual lay-up process. In this context, this study intends to study some manufacture parameters in order to maximize the mechanical properties. For this purpose, the mixer rotation speed, the dispersion time of the nanoparticles and the vacuum time applied to the system were analyzed in detail. It was found that the mixing time is very dependent on the rotation speed used and there is an ideal vacuum time. A short vacuum time allows air bubbles to exist in the resin, while a long time promotes a decrease in mechanical properties due to the removal of resin in the laminates and, consequently, the fibers are not fully wet.
The Use of Molecular Pathway Inhibitors in the Treatment of Osteosarcoma

Presently, the 5-year survival rate for metastatic osteosarcoma remains low despite advances in chemotherapeutics and neoadjuvant therapy. A majority of the morbidity and nearly all of the mortality in osteosarcoma rely not in the primary disease but in the metastatic disease. The pursuit of novel molecular therapies is attractive due to their targeted abil ity to combat metastasis. Unlike traditional chemotherapy agents, which work by tar - geting rapidly dividing cells, targeted therapies may spare normal cells and decrease the adverse effects of chemotherapy by targeting specific pathways. Here, we discuss key molecular pathways in osteosarcoma and their ability to be modulated for the goal of eradication of primary and metastatic disease. We focus specifically on the aldehyde dehydrogenase (ALDH), epidermal growth factor receptor (EGFR), and insulin-like growth factor-1 receptor (IGF-1R) pathways. pathway, retinoic acid binds to dimers of RXRs and PPARβ/δ to induce the expression of its downstream target genes including PDK-1/Akt. In cells expressing ERα, retinoic acid can bind to dimers of RXRs and ERα as well as induce the expression of c-MYC and cyclin D1. Retinoic acid which extra-nuclearly binds with RARα can also induce the expression of c-MYC and cyclin D1 through the PI3K/Akt signaling pathway.