Miracle-dz/UniFAR-FTUs huggingface dataset:
Posterior Capsule Opacification (PCO) Cases at Lamongan Eye Clinic: Two Years of Retrospective Data

Introduction: Posterior capsular opacity (PCO) is the most common complication of cataract surgery. PCO is caused by the lens epithelial cells (LEC), which then proliferate in the capsular bag after surgery. Several complications can occur, such as increased intraocular pressure (IOP), cystoid macular edema (CME), retinal hemorrhage, retinal detachment, and implanted lens (IOL) damage. Capsule Nd:YAG laser is currently the standard procedure for treating PCO, with a success rate of 95%. Purpose: This study aimed to provide an overview of PCO incidence and the success rate of PCO handling in the eye clinic. Methods: This study was a retrospective observational study. Data was taken from medical records of patients diagnosed with PCO who came to the Lamongan Eye Clinic for two years (May 2018 to April 2020). Data regarding the profile of the subject was analyzed descriptively. The data distribution was tested using the Kolmogorov-Smirnov test. Results: From May 2018 to April 2020, 134 patients with PCO came to the Lamongan Eye Clinic. Mean pre-laser best-corrected visual acuity (BCVA) was 0.76 ± 0.44 (logMAR), post-laser was 0.40 ± 0.40 (logMAR). There was a significant difference in the mean refraction correction of the PCO patients before and after Nd:YAG laser capsulotomy, whereas the mean BCVA after undergoing YAG laser was higher than before. Mean pre-laser IOP was 15.00 ± 3.55 mmHg and post-laser was 14.20 ± 3.27 mmHg. The mean post-laser IOP was lower than the pre-laser IOP. The Nd:YAG laser capsulotomy significantly affected IOP. Conclusions: There is a statistically significant improvement in BCVA before and after capsulotomy. Capsulotomy had a significant effect on improving BCVA up to 7%; however, had no effect on IOP.
Initiation of Tomato Fruit Ripening with Copper

A vacuum infiltration technique that allowed precise control of both infiltration rate and amount of solution administered to whole tomato (Lycopersicon esculentum) fruit was developed. Controlled volumes of 5 mm solutions of CuSO4, Cu(NO3)2, HgCl2, CaSO4, KNO3, (NH4)2C2O4, Na2HPO4, citrate and 1 mm EDTA or EGTA were infiltrated into intact, mature-green tomato fruit and evaluated with regard to their effect on the pattern of tomato ripening. Copper significantly accelerated lycopene accumulation and influenced both the timing and magnitude of climacteric ethylene production. Infiltration with HgCl2 elicited similar effects as copper, but severe phytotoxicity was observed. In contrast, CaSO4, KNO3, and chelators had no significant effect on the pattern of ripening. Copper initiated wound ethylene production in the ripening mutant rin that reached up to 50% of the wound levels observed in normal fruit, but rin was not induced to ripen.
Strategic HRM and Firm Performance: Mediating Role of Knowledge Management Capacity and Innovation Performance

The purpose of the current study is to investigate the linkage between strategic HRM (SHRM) and firm performance through knowledge management capability and innovation performance. Primary data were gathered from 624 employees working in 252 Indian firms. Using Model 6 of PROCESS macro, a serial mediation model was estimated to analyse the proposed relationships between SHRM, knowledge management capability, innovation performance and firm performance. The study has revealed that the use of SHRM practices which include selection, training, appraisal, rewards and empowerment results in enhanced knowledge management capability, improved innovation performance and heightened firm performance. Further, the results establish that knowledge management capability and innovation performance act as sequential mediators in linking SHRM to firm performance.
Observer-based integrated event–triggered sliding mode control for Internet of vehicles with communication constraints

This paper investigates the co-design problem of the integrated event-triggering (IET) scheme and integral sliding mode control (ISMC) for the non-linear Internet of vehicles (IoVs) with communication constraints. The main goal is to improve the tracking performance and increase the bandwidth utilization of vehicular ad hoc networks (VANETs) with various external disturbances. First, a non-linear IoV dynamic model is established by considering the disturbance from the preceding vehicle, internal and external resistance, and uncertainty of the engine time constant. Second, an IET transmission mechanism based on both absolute and relative restriction conditions of sampled-data error is proposed to reduce unnecessary data transmissions among vehicles. Third, co-design IET mechanisms and ISMC controller based on estimated H∞ observer are designed, which can obtain the disturbance attenuation and asymptotic stability, and the result is complemented by additional conditions established for guaranteeing string stability. Finally, extensive simulations are conducted to verify the theoretical analysis and prove the effectiveness and superiority of the proposed method.
Effect of Leaves on Carbohydrate Content and Movement of 14C-Assimilate in Plum Cuttings1

The top leaf of fresh softwood cuttings of ‘Marianna 2624’ plum (Prunus cerasifera × Prunus munsoniana) was exposed to 14CO2 and the effect of leaf area and indolebutyric acid (IBA) on rooting and distribution of 14c was assessed. IBA enhanced the rooting of cuttings with 1/2 or 3 leaves, whereas leafless cuttings failed to root regardless of treatment. Most of the 14C remained in the upper portion of the stem adjacent to the treated leaf; the mid-stem segment acquired about 40% of the activity. Little radioactivity reached the base of fresh cuttings, but upon rooting it accumulated 4 times the percentage of 14c found in comparable non-rooting bases. In all cuttings the incorporation of 14C into starch was much greater in the mid-stem than in the base. As much as 75% of the radioactivity in rooted bases was recovered in a residue remaining after ethanol soluble substances and starch were removed. The level of starch declined continually in the base but decreased in the mid-stem only at the end of the study. The concentration of sugars in both segments was relatively constant while that of sorbitol declined markedly and was hardly detectable in rooted bases. The largest loss of carbohydrates occurred in the bases treated with IBA. The similarity in levels and trends of carbohydrate utlization in the bases of cuttings with or without leaves indicated that in this cultivar the stimulatory effect of leaves on rooting is not associated with their being a source of carbohydrates.
State Space Modeling of an Offshore Wind Power Plant With an MMC-HVDC Connection for an Eigenvalue-Based Stability Analysis

Large offshore wind power plants (OWPPs) installed far from the coastline are emerging to benefit from the strong and steady wind resources available at these locations. The high-voltage direct-current (HVDC) transmission system based on the modular multilevel converter (MMC) is the most appropriate solution to transmit the produced energy to the onshore grid, in a way that a complex power-electronic-based electrical system is formed at the OWPP. Undesired interactions can occur between the MMC-based HVDC station, the several wind-turbine (WT) converters, and the passive elements of the offshore grid. To guarantee a safe and reliable operation of the OWPP, a small-signal analysis must be performed in advance to predict possible unstable situations and their root causes, in a way as to take corrective measures to avoid them. In this paper, a state-space model of an OWPP is developed adopting a recently proposed model in multiple $dq$ frames of the MMC, which considers the internal dynamics of the converter. With the developed model, an eigenvalue-based stability assessment is carried out, where participation factors are calculated to identify the main contributors to the unstable modes that appear as a consequence of undesired low-frequency interactions at the offshore grid. As far as the authors know, an eigenvalue-based stability assessment of an OWPP with an MMC-HVDC connection is a topic rarely or never explored in the literature before since a detailed time-invariant state-space model of the MMC was not available until recently. Thus, the eigenvalue-based stability study is the main contribution of this paper. The developed model can easily be extended to more complex OWPPs with different configurations in future works. Another contribution of this paper is the proposal of an adaptation to the MMC’s grid-following state-space model so that the converter’s dynamics in grid-forming mode can be represented. Finally, various studies are presented to prove that the adopted MMC’s approximated model is accurate enough for small-signal stability analyses.
The Anomaly of Leading Indicator

The counter cyclical strategy used to deal with the Covid-19 pandemic is through fiscal policy, government expenditure by refocusing on the health sector and economic recovery. This policy is not only carried out in Indonesia but in other affected countries. In general, government expenditure has made positive impact on GDP, but during the COVID-19 pandemic this affect became negative. Using data from 137 countries, government health expenditure has a negative impact on GDP. If government expenditure policies continue to focus on health care, it will have an impact on other sectors, ultimately negative economic growth. In addition to refocusing on health expenditure, there are also assistance programs for affected communities. Higher aid should affect the GDP, but there is no difference in GDP growth between the two groups of countries based on the percentage of income support. Government expenditure policies in each country certainly aim to maintain the stability of the country, but the policy objectives should be allocated not only curatively but also preventively by taking into account the long-term impact post covid-19 Era.
Effects of Pruning on Penetration of Photosynthetically Active Radiation and Leaf Physiology in Apples Trees1

Several summer pruning treatments were applied in August to ‘Stayman’/Malling Merton (MM) 111 apple (Malus domestica Borkh.) trees measuring 4m high and 5m wide to examine the resulting changes in light climate. Diffuse photosynthetically active radiation (PAR) increased immediately by about 1/5 on the periphery and 1/10 within the canopy from 2 types of summer pruning. These changes in PAR had no effect on net photosynthetic (Pn) potential, dark respiration (Rd), or specific leaf weight (SLW) determined 21 and 54 days after pruning. One method of summer pruning reduced penetration of PAR into inner canopy positions the year following treatment.
Quantitative Analysis of the Derailment Characteristics of Loaded and Empty Unit Trains

Operation of unit trains has grown substantially over the past half century owing to their ability to provide economic and efficient transportation of bulk products. Although various aspects of train safety have been studied, there has been limited research examining the effect of train loading conditions on derailment occurrence, cause and severity. An algorithm was developed to identify derailments of loaded and empty unit trains on mainlines and sidings recorded in the Federal Railroad Administration database. A dataset of these accidents for the 15-year period of 2001–2015 was developed and analyzed. The frequency of derailments for both loaded and empty unit trains declined by more than 50%. The average number of cars derailed per accident fluctuated for both loading conditions, but showed no particular trend. Approximately five times more loaded unit train derailments were recorded in the database than empty unit trains, but in the absence of specific unit train traffic data, inferences about rates are not possible. Loaded unit trains were more than four times heavier than empty unit trains and loaded train derailments tended to involve more cars than empty trains. The distribution of derailment causes differed for loaded and empty unit trains. Loaded trains most frequently derailed because of broken rails and welds, while the leading cause of empty train derailments was obstructions, in particular severe weather. Over 90% of the derailments of loaded and empty unit trains considered in this study occurred on mainline tracks, and the distribution of causes differed between mainline and siding tracks.
Reduction in the Migration Activity of Microglia Treated with Silica-Coated Magnetic Nanoparticles and their Recovery Using Citrate

Nanoparticles have garnered significant interest in neurological research in recent years owing to their efficient penetration of the blood–brain barrier (BBB). However, significant concerns are associated with their harmful effects, including those related to the immune response mediated by microglia, the resident immune cells in the brain, which are exposed to nanoparticles. We analysed the cytotoxic effects of silica-coated magnetic nanoparticles containing rhodamine B isothiocyanate dye [MNPs@SiO2(RITC)] in a BV2 microglial cell line using systems toxicological analysis. We performed the invasion assay and the exocytosis assay and transcriptomics, proteomics, metabolomics, and integrated triple-omics analysis, generating a single network using a machine learning algorithm. The results highlight alteration in the mechanisms of the nanotoxic effects of nanoparticles using integrated omics analysis.
Sympatric soil biota mitigate a warmer‐drier climate for Bouteloua gracilis

Climate change is altering temperature and precipitation, resulting in widespread plant mortality and shifts in plant distributions. Plants growing in soil types with low water holding capacity may experience intensified effects of reduced water availability as a result of climate change. Furthermore, complex biotic interactions between plants and soil organisms may mitigate or exacerbate the effects of climate change. This 3‐year field experiment observed the performance of Bouteloua gracilis ecotypes that were transplanted across an environmental gradient with either sympatric soil from the seed source location or allopatric soil from the location that plants were transplanted into. We also inoculated plants with either sympatric or allopatric soil biotic communities to test: (1) how changes in climate alone influence plant growth, (2) how soil types interact with climate to influence plant growth, and (3) the role of soil biota in mitigating plant migration to novel environments. As expected, plants moved to cooler‐wetter sites exhibited enhanced growth; however, plants moved to warmer‐drier sites responded variably depending on the provenance of their soil and inoculum. Soil and inoculum provenance had little influence on the performance of plants moved to cooler‐wetter sites, but at warmer‐drier sites they were important predictors of plant biomass, seed set, and specific leaf area. Specifically, transplants inoculated with their sympatric soil biota and grown in their sympatric soil were as large as or larger than reference plants grown at the seed source locations; however, individuals inoculated with allopatric soil biota were smaller than reference site individuals at warmer, drier sites. These findings demonstrate complicated plant responses to various aspects of environmental novelty where communities of soil organisms may help ameliorate stress. The belowground microbiome of plants should be considered to predict the responses of vegetation more accurately to climate change.
Hyperspectral Image Classification Model Using Squeeze and Excitation Network with Deep Learning

In the domain of remote sensing, the classification of hyperspectral image (HSI) has become a popular topic. In general, the complicated features of hyperspectral data cause the precise classification difficult for standard machine learning approaches. Deep learning-based HSI classification has lately received a lot of interest in the field of remote sensing and has shown promising results. As opposed to conventional hand-crafted feature-based classification approaches, deep learning can automatically learn complicated features of HSIs with a greater number of hierarchical layers. Because HSI's data structure is complicated, applying deep learning to it is difficult. The primary objective of this research is to propose a deep feature extraction model for HSI classification. Deep networks can extricate features of spatial and spectral from HSI data simultaneously, which is advantageous for increasing the performances of the proposed system. The squeeze and excitation (SE) network is combined with convolutional neural networks (SE-CNN) in this work to increase its performance in extracting features and classifying HSI. The squeeze and excitation block is designed to improve the representation quality of a CNN. Three benchmark datasets are utilized in the experiment to evaluate the proposed model: Pavia Centre, Pavia University, and Salinas. The proposed model's performance is validated by a performance comparison with current deep transfer learning approaches such as VGG-16, Inception-v3, and ResNet-50. In terms of accuracy on each class of datasets and overall accuracy, the proposed SE-CNN model outperforms the compared models. The proposed model achieved an overall accuracy of 96.05% for Pavia University, 98.94% for Pavia Centre dataset, and 96.33% for Salinas dataset.
The use of three-factor model to make financial portfolio and help clients’ decisions

minimizing the risks involved in investing and also increasing the chance of making profits are the most essential two factors in investment. In order to make profits and reduce risks, more and more people tend to find professional managers to make financial portfolios since they are the ones who understand clients’ financial needs and suggest the best and unique investment strategies. During the calculation, we choose the three-factor model over CAPM. The traditional asset pricing model, known formally as the CAPM uses only one variable to describe the returns of a portfolio or stock with the returns of the market as a whole. In addition, generally speaking, the Fama-French Three-Factor Model provides a much better explanation for cross-sectional variations in stock returns in a number of countries. Our paper discusses the advantages and disadvantages of three-factor models compared to CAPM, and the use of three-factor model.
Genetic Diversity of North American Strawberry Cultivars

Pedigrees of 134 North American strawberry (Fragaria × ananassa Duch.) cultivars introduced since 1960 were used to calculate 1) the genetic contribution of founding clones to these cultivars; 2) genetic relatedness among these cultivars; and 3) inbreeding coefficients of these cultivars. Fifty-three founding clones accounted for the pedigrees of these cultivars, with a mean genetic contribution ranging from <0.1% to 11%. Cultivars were clustered according to the genetic contribution into groups strongly related to geographic region of origin. Cultivars developed in California plus those derived in large part from California germplasm were a distinct cluster. The remaining cultivars divided strongly into two geographical divisions, with cultivars of a western or northern origin primarily in the first division, and cultivars of a southern or eastern origin primarily in the 2nd division. Cluster groups within each division also were related to the region of origin of cultivars. Cultivars also were clustered on the basis of Wright’s coefficient of relationship, a measure of genetic relatedness. Cluster groups from this analysis were strongly related to region of origin of cultivars, and were similar in content to groups based on genetic contributions. Inbreeding coefficients ranged from 0.0 to 0.875, but were <0.5 for all cultivars developed from cross-fertilization. Inbreeding coefficients were related partly to region of origin of the cultivars, but this relationship was probably an indirect result of unequal numbers of generations of controlled hybridization from common ancestors. For example, cultivars developed in California, which resulted from more generations of hybridization, generally had higher inbreeding coefficients. Strategies are suggested for maintaining and increasing genetic diversity of North American breeding populations.
Fluid Balance and Carbohydrate Intake of Elite Female Soccer Players during Training and Competition

This study examined sweat rate, sweat sodium concentration [Na+], and ad-libitum carbohydrate and fluid intakes in elite female soccer players during training (n = 19) and a match (n = 8); eight completed both for comparisons. Body mass (kg) was obtained before and after exercise to calculate sweat rate. The sweat [Na+] was determined from absorbent patches on the thigh or back. Sweat rate, percentage body mass change, and sweat [Na+] for 19 players during training were 0.47 ± 0.19 L·h−1, +0.19 ± 0.65%, and 28 ± 10 mmol·L−1, respectively. Sweat rate was higher during a match (0.98 ± 0.34 L·h−1) versus training (0.49 ± 0.26 L·h−1, p = 0.007). Body mass losses were greater post-match (−1.12 ± 0.86%) than training (+0.29 ± 0.34%, p = 0.003). Sweat [Na+] was similar for training (29 ± 9 mmol·L−1) and a match (35 ± 9 mmol·L−1) (p = 0.215). There were no differences in match versus training carbohydrate intakes (2.0 ± 2.3 g·h−1, 0.9 ± 1.5 g·h−1, respectively, p = 0.219) or fluid intakes (0.71 ± 0.30 L·h−1, 0.53 ± 0.21 L·h−1, respectively, p = 0.114). In conclusion, female soccer players’ sweat rates were higher during a match than during training, and carbohydrate intakes were below recommendations for matches and training.
A Smoothing Projected Levenberg-Marquardt Type Algorithm for Solving Constrained Equations

In this article, we consider the problem of finding a solution of a nonsmooth constrained (and not necessarily square) system of equations. We first reformulate the original problem as an equivalent system of equations with nonnegative constraints, and then present a smoothing projected Levenberg-Marquardt type algorithm to solve the reformulated system, which solves a strictly convex quadratic program at each iteration. We show that this algorithm not only converges globally, but also converges locally superlinearly under an error bound assumption that is much weaker than the standard nonsingularity condition. Some numerical results for the presented algorithm indicate that the algorithm works quite well in practice.
It’s COVID-19 chaos! Is the temporary restriction on short selling in Thailand effective?

Abstract This paper evaluates the effectiveness of the COVID-19 temporarily led restriction on short selling by the Stock Exchange of Thailand (SET). We investigate the causal effect of short selling restriction on return, volatility and market quality from 2 September 2019 to 30 September 2020. Exploiting this short selling restriction as a natural experiment, we conduct difference-in-difference analyses and find that the uptick restriction on short selling worsens market quality with higher spread, lower market depth, and order imbalance. In addition, we find an increase in volatility during the restriction and a negative return surrounding the announcement date. This implies that the restriction increases the trading costs and price impact and fails to tame the volatile market and reduce returns.