Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship Between Laboratory Findings and Mortality in COVID-19 Patients Requiring Intensive Care

Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shows a wide clinical manifestation from asymptomatic infection to life-threatening respiratory failure. This study aimed to determine the relationship between the survival and demographic data, comorbidity status, and laboratory parameters of coronavirus disease 2019 (COVID-19) patients requiring intensive care. Material and methods: We retrospectively analyzed 236 patients requiring intensive care whose diagnosis was confirmed by the SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) test. The patients were divided into two groups in terms of survival. Demographic data; procalcitonin and C-reactive protein (CRP) levels; leukocyte, lymphocyte, and neutrophil counts in hemogram and neutrophil-to-lymphocyte ratio (NLR) levels; and lower respiratory and blood cultures were examined, and the relationships between these parameters and survival were evaluated with hypothesis testing. Results: In the study, 156 (66.1%) males and 80 (33.9%) females, a total of 236 patients, were included. Sixty-seven (28.3%) surviving patients were determined as Group 1, and 169 (71.7%) deceased patients were determined as Group 2. A statistically significant difference was found between the groups in terms of mean age (p<0.001) and gender distribution (p=0.011). In laboratory parameters, a significant difference was observed between the groups in lymphocyte count (p=0.001), NLR (p<0.001), and procalcitonin levels (p<0.001). Although leukocyte (p=0.075), neutrophil (p=0.031), and CRP (p=0.112) levels were higher in Group 2, there was no statistical difference. Mortality was found to be higher in patients with comorbidity (p=0.012) or co-infection (p=0.002). Conclusion: High levels of neutrophil count, NLR, and procalcitonin; low lymphocyte count; the presence of comorbidity; and secondary bacterial infection were found to be associated with mortality in COVID-19 patients in the intensive care unit.
Multi-scale Gaussian Segmentation via Graph Cuts

Towards the improvement of image segmentation performance, a new improved segmentation method is proposed which combines the use of multi-scale information. The multi-scale information of an image, generated by a linear Gaussian smoothing function through an interactive scheme that provides different levels of image cues which help to capture the abundant content of the image. However, Gaussian smoothing cannot generate an optimum solution to the specific scale level. According to the boundaries sensibility to scale, a convergence constraint based on the significant scale level of the segmented regions is constructed. The experimental results show that this method has superior advantages in performance and towards noise images.
Fuzzy models of rough mathematics

The study shows that the introduced known formal description of rough sets can be interpreted in terms of fuzzy sets. This makes it possible to solve many problems of rough mathematics by the developed apparatus of fuzzy mathematics. The authors suggest a way of describing rough numbers with the help of membership functions of fuzzy numbers. The study specifies the chosen type of membership functions and the method of calculating their parameters. The algebra of fuzzy numbers is adapted to perform operations with numbers that are described roughly. The obtained elements are formulae for calculating the expected values and variations of rough numbers. These correlations are simplified for the most realistic special cases. A possibility is considered for solving roughly given optimization problems. A procedure is described for reducing an optimization problem with rough parameters to a usual problem of mathematical programming. An example is given on solving a linear programming problem whose parameters are determined roughly. The rough problem parameters are described with functions of an (L-R) type. It is suggested that the problem should be solved on the basis of the introduced complex criterion. The numerical value of the criterion takes into account the extent of closeness of the obtained result to the modal solution as well as the level of compactness of the membership function of the resulting value of the objective function.
A Review of Skin Cancer Detection: Traditional and Deep Learning-Based Techniques

One of the most serious types of cancer is skin cancer. The rising number of skin cancer cases, high mortality rate, and high cost of medical treatment necessitate early detection of its symptoms. Skin cancer is detected and differentiated from melanoma using lesion criteria such as symmetry, color, size, and shape. Given the significance of these challenges, researchers have developed a variety of early-detection approaches for skin cancer. This paper comprehensively reviews classical and deep-learning techniques for detecting early skin cancer. The performance of these techniques is evaluated based on various metrics, and the datasets used for training and testing are analyzed. Studies using techniques such as clinical examination, dermoscopy, and histopathology are identified, and the architecture of the deep neural networks used for skin cancer detection is analyzed. A comprehensive comparison of classical and deep-learning techniques for skin cancer detection is provided in this review paper.
Temperature Dependence of the Thermo-Optic Coefficient of SiO2 Glass

This paper presents a thorough analysis on the temperature dependence of the thermo-optic coefficient, dn/dT, of four bulk annealed pure-silica glass samples (type I—natural quartz: Infrasil 301; type II—quartz crystal powder: Heraeus Homosil; type III—synthetic vitreous silica: Corning 7980 and Suprasil 3001) from room temperature down to 0 K. The three/four term temperature dependent Sellmeier equations and respective coefficients were considered, which results from fitting to the raw data obtained by Leviton et al. The thermo-optic coefficient was extrapolated down to zero Kelvin. We have obtained dn/dT values ranging from 8.16 × 10−6 up to 8.53 × 10−6 for the four samples at 293 K and for a wavelength of 1.55 μm. For the Corning 7980 SiO2 glass, the thermo-optic coefficient decreases monotonically, from 8.74 × 10−6 down to 8.16 × 10−6, from the visible range up to the third telecommunication window, being almost constant above 1.3 μm. The Ghosh’s model was revisited, and it was concluded that the thermal expansion coefficient only accounts for about 2% of the thermo-optic coefficient, and we have obtained an expression for the temperature behavior of the silica excitonic bandgap. Wemple’s model was also analyzed where we have also considered the material dispersion in order to determine the coefficients and respective temperature dependences. The limitations of this model were also discussed.
Stratification Breakdown in Antarctic Coastal Polynyas, Part I: Influence of Physical Factors on the Destratification Timescale

This study examines the process of water-column stratification breakdown in Antarctic coastal polynyas adjacent to an ice shelf with a cavity underneath. This first part of a two-part sequence seeks to quantify the influence of offshore katabatic winds, alongshore winds, air temperature, and initial ambient stratification on the timescales of polynya destratification through combining process-oriented numerical simulations and analytical scaling. In particular, the often-neglected influence of wind-driven circulation on the lateral transport of the water formed at the polynya surface — which we call Polynya Source Water (PSW) — is systematically examined here. First, an ice-shelf/sea-ice/ocean coupled numerical model is adapted to simulate the process of PSW formation in polynyas of various configurations. The simulations highlight that i) before reaching the bottom, majority of the PSW is actually carried away from the polynya by katabatic wind-induced offshore outflow, diminishing water-column mixing in the polynya and intrusion of the PSW into the neighboring ice shelf cavity, and ii) alongshore coastal easterly winds, through inducing onshore Ekman transport, reduce offshore loss of the PSW and enhance polynya mixing and PSW intrusion into the cavity. Second, an analytical scaling of the destratification timescale is derived based on fundamental physical principles to quantitatively synthesize the influence of the physical factors, which is then verified by independent numerical sensitivity simulations. This work provides insights into the mechanisms that drive temporal and cross-polynya variations in stratification and PSW formation in Antarctic coastal polynyas, and establishes a framework for studying differences among the polynyas in the ocean.
Microwave emission power exceeding 10 μW in spin torque vortex oscillator

We fabricated vortex-type spin-torque oscillators (STOs) with optimized structures to enhance the microwave emission power. Inserting a thin Co70Fe30 layer between the MgO tunnel barrier and Fe-B free layer of the STOs resulted in the magnetoresistance ratio up to 190% with a resistance area (RA) value of 4.1 Ω μm2, which contributed to a large enhancement of the emission power. The optimized STO exhibited the emission power of 10.1 μW, which is the highest power from a single STO reported to date, with excellent frequency stability (fSTO/Δf = 2000 with the timing jitter of 12 ps). The results suggest that the vortex-STOs are promising candidates for next generation microwave generators.
Impact of deoxygenation and warming on global marine species in the 21st century

Abstract. Ocean temperature and dissolved oxygen shape marine habitats in an interplay with species' physiological characteristics. Therefore, the observed and projected warming and deoxygenation of the world's oceans in the 21st century may strongly affect species' habitats. Here, we implement an extended version of the Aerobic Growth Index (AGI), which quantifies whether a viable population of a species can be sustained in a particular location. We assess the impact of projected deoxygenation and warming on the contemporary habitat of 47 representative marine species covering the epipelagic, mesopelagic, and demersal realms. AGI is calculated for these species for the historical period and into the 21st century using bias-corrected environmental data from six comprehensive Earth system models. While habitat viability decreases nearly everywhere with global warming, the impact of this decrease is strongly species dependent. Most species lose less than 5 % of their contemporary habitat volume at 2 ∘C of global warming relative to preindustrial levels, although some individual species are projected to incur losses 2–3 times greater than that. We find that the in-habitat spatiotemporal variability of O2 and temperature (and hence AGI) provides a quantifiable measure of a species' vulnerability to change. In the event of potential large habitat losses (over 5 %), species vulnerability is the most important indicator. Vulnerability is more critical than changes in habitat viability, temperature, or pO2 levels. Loss of contemporary habitat is for most epipelagic species driven by the warming of ocean water and is therefore elevated with increased levels of global warming. In the mesopelagic and demersal realms, habitat loss is also affected by pO2 decrease for some species. Our analysis is constrained by the uncertainties involved in species-specific critical thresholds, which we quantify; by data limitations on 3D species distributions; and by high uncertainty in model O2 projections in equatorial regions. A focus on these topics in future research will strengthen our confidence in assessing climate-change-driven losses of contemporary habitats across the global oceans.
CMB Power Spectrum Results from the South Pole Telescope

The South Pole Telescope (SPT) is a 10-meter telescope designed to survey the millimeter-wave sky. The telescope and its 960-element bolometric camera were successfully installed at the South Pole in 2007. Since then, the SPT has imaged 2200 square degrees of the sky with low noise and arcminute resolution. We report on the CMB power spectrum results from SPT. In conjunction with data from the WMAP satellite, the new SPT data leads to a 6 sigma detection of gravitational lensing in the CMB. The SPT+WMAP data also improve constraints on the shape of the primordial power spectrum with implications for inflationary models. Finally, the SPT+WMAP data yield measurements of the primordial helium abundance and the number of relativistic particle species in the early Universe.
Numerical Investigation on Lift Force Generation Mechanism of Clap and Fling Motion Using Unstructured ALE Method

To study the lift generation mechanism and energy expenditure of clap and fling motion for insect flight, an unstructured mesh finite volume ALE method is developed. To solve mesh deformation problems during clap and fling motion, we adopt two mesh modification techniques. A 2D elliptical wing model is used to validate our solver by comparing the solutions to the already published numerical and experimental results. We analyzed the lift generation mechanism of clap and fling motion. The paper also released the comparison of Cl and energy expenditure between the single wing hovering motion and clap & fling. Conclusions have been made: the wake capture and delayed stall contribute to the lift generation while the rapid pitch mechanism decreases the lift. Clap and fling motion generate less lift but consume less energy, which means that it can generate more lift as consuming the same energy compared to single hovering motion by quantitative analysis.
Synergistic Effects of Rhizobacteria and Salicylic Acid on Maize Salt-Stress Tolerance

Maize (Zea mays L.) is a salt-sensitive plant that experiences stunted growth and development during early seedling stages under salt stress. Salicylic acid (SA) is a major growth hormone that has been observed to induce resistance in plants against different abiotic stresses. Furthermore, plant growth-promoting rhizobacteria (PGPR) have shown considerable potential in conferring salinity tolerance to crops via facilitating growth promotion, yield improvement, and regulation of various physiological processes. In this regard, combined application of PGPR and SA can have wide applicability in supporting plant growth under salt stress. We investigated the impact of salinity on the growth and yield attributes of maize and explored the combined role of PGPR and SA in mitigating the effect of salt stress. Three different levels of salinity were developed (original, 4 and 8 dS m−1) in pots using NaCl. Maize seeds were inoculated with salt-tolerant Pseudomonas aeruginosa strain, whereas foliar application of SA was given at the three-leaf stage. We observed that salinity stress adversely affected maize growth, yield, and physiological attributes compared to the control. However, both individual and combined applications of PGPR and SA alleviated the negative effects of salinity and improved all the measured plant attributes. The response of PGPR + SA was significant in enhancing the shoot and root dry weights (41 and 56%), relative water contents (32%), chlorophyll a and b contents (25 and 27%), and grain yield (41%) of maize under higher salinity level (i.e., 8 dS m−1) as compared to untreated unstressed control. Moreover, significant alterations in ascorbate peroxidase (53%), catalase (47%), superoxide dismutase (21%), MDA contents (40%), Na+ (25%), and K+ (30%) concentration of leaves were pragmatic under combined application of PGPR and SA. We concluded that integration of PGPR and SA can efficiently induce salinity tolerance and improve plant growth under stressed conditions.
Optimization Method for Stereo Matching Based on Minimum Spanning Tree

This paper describes the application of minimum spanning tree algorithm in process of stereo matching and optimization of depth map. A stereo matching method for the real-time application scene of binocular vision is proposed, which the stereo matching is completed under the sample of the image and reduced the image size by the minimum spanning tree of original image. On the one side, the method reduces the amount of the image under the sample, and then uses the minimum spanning tree to form the relationship between the original image and the lower sample image. On the other side, the lower sampling image uses the minimum spanning tree to the cost aggregation, so that the cost aggregation can through the local limit. This method can generate global disparity map without mismatched black voids, and it also has a good effect on optimizing depth map obtained by other methods.
Decision Statistics for Incoherent Signal Detection in Multi-Element Antenna Arrays

We present a detailed study of the characteristics of the exact decision statistic for the optimal incoherent signal detection in a multielement antenna array. The exact decision statistic is derived from a rigorous expression for the likelihood ratio in the case where the useful-signal amplitudes at the antenna-array elements are identical, whereas the phases are random. The analysis is carried out in the space of the variables which are observed at the outputs of the incoherent matched filters performing the initial signal processing at each antenna-array element. Variation in the signal-to-noise ratio is shown to deform the boundary of partitioning of the multidimensional observation space, which results in a variation in the threshold values of the exact decision statistic when the Neyman–Pearson criterion is used. The characteristics of the exact decision statistic and various approximate decision statistics are compared in detail. For the antenna arrays with a large number of elements, the influence of the used decision statistic on the target-missing probability is shown to become rather significant. A new combined decision statistic with the characteristics that are close to those of the exact decision statistic is introduced for a wide signal-to-noise ratio range.
Degradation and Bone-Contact Biocompatibility of Two Drillable Magnesium Phosphate Bone Cements in an In Vivo Rabbit Bone Defect Model

The use of bone-cement-enforced osteosynthesis is a growing topic in trauma surgery. In this context, drillability is a desirable feature for cements that can improve fracture stability, which most of the available cement systems lack. Therefore, in this study, we evaluated a resorbable and drillable magnesium-phosphate (MgP)-based cement paste considering degradation behavior and biocompatibility in vivo. Two different magnesium-phosphate-based cement (MPC) pastes with different amounts of phytic acid (IP 6) as setting retarder (MPC 22.5 and MPC 25) were implanted in an orthotopic defect model of the lateral femoral condyle of New Zealand white rabbits for 6 weeks. After explantation, their resorption behavior and material characteristics were evaluated by means of X-ray diffraction (XRD), porosimetry measurement, histological staining, peripheral quantitative computed tomography (pQCT), cone-beam computed tomography (CBCT) and biomechanical load-to-failure tests. Both cement pastes displayed comparable results in mechanical strength and resorption kinetics. Bone-contact biocompatibility was excellent without any signs of inflammation. Initial resorption and bone remodeling could be observed. MPC pastes with IP 6 as setting retardant have the potential to be a valuable alternative in distinct fracture patterns. Drillability, promising resorption potential and high mechanical strength confirm their suitability for use in clinical routine.
Awareness and knowledge of the effects of smoking on oral health, and smoking cessation motivation among high school students in Jakarta

Introduction: The number of adolescent smokers is rising in Indonesia. Awareness and knowledge about the nega­ tive effects of smoking could prevent adolescents from smoking. Motivation to stop smoking might predict the likeli­ hood of smoking cessation. Objectives: The aim of this study was to discover the level of Jakarta adolescents’ awareness and knowledge of the effects of smoking on oral health, and smoking cessation motivation. Material and methods: An online questionnaire­based cross­sectional study was conducted in Jakarta using convenient sampling methods among 552 high school students. The relationship between the variables was inves­ tigated using simple logistic regression and Spearman’s rho correlation. Results: Most of the participants ( n = 493, 89.3%) were aware that smoking jeopardizes oral health. About 324 (65.72%) participants had little knowledge about the specific effects of smoking on oral health. Female partici­ pants, never smoking participants, smoking for a short period, or those having the intention to quit smoking were all more likely to be aware than their counterparts. With respect to knowledge, participants who never smoked displayed higher knowledge levels than their peers. The level of smoking cessation motivation was insufficient, with 22 (43.1%) respondents reporting the motivation to quit. No statistically significant difference was found between motivation scores with awareness and knowledge. There were linear correlations between the motivation scores and cessation duration, smoking period, and the intention to quit smoking. Conclusions: Incorporating oral health education in smoking prevention program among adolescents is recom­ mended. However, more tailored approach is required to help this group of population, who already is nicotine­ addicted, to stop smoking.
Teachers’ Instrumentation of a Collaborative Dynamic Geometry Environment

We draw on the theory of instrumental genesis (RABARDEL; BEGUIN, 2005) and the notion of co-action (HEGEDUS; MORENO-ARMELLA, 2010) to understand how teachers’ instrumentation of dynamic geometry environment (DGE) and how this instrumentation shapes their geometric knowledge. In small groups, six middle and high school mathematics teachers engaged in solving open-ended geometric problems in an online dynamic geometry environment for 15 weeks. Our analysis of their interactions indicates that the co-action between the teachers and the environment helped them appropriate the dragging feature of DGE, which shaped their understanding of geometrical relations, particularly dependencies. Designing tasks that support teachers’ effective appropriation of DGEs requires special attention to the co-active nature of DGEs. This study provides insights into aspects of learners’ collaborative interaction with certain technologies.
Tear Cytokine Levels in Sicca Syndrome-Related Dry Eye: A Meta-Analysis

Sjogren’s syndrome (SS) is an autoimmune disease that affects exocrine glands, mainly salivary and lacrimal glands. Several studies have investigated cytokine profiles in tears in order to understand the pathogenesis of SS and find additional diagnostic markers. This systematic review and meta-analysis aimed to analyze cytokines in tears of SS patients. A systematic literature search of the Cochrane, Medline via PubMed, Scopus, and Web of Science databases was conducted using key terms related to “Sjögren’s syndrome” and “tears” combined with “biomarker”, “cytokines”, “interleukin”, and “chemokines”, following PRISMA guidelines. Article selection was subjected to certain eligibility criteria. A total of 17 articles (from 1998 and 2022) were selected for the quantitative and qualitative analysis. When compared to controls, concentrations of IFN-γ, TNF-α, IL-1α, IL-1 Ra, IL-4, IL-6, IL-8, IL-10, IL-17, IL-21 and IL-22 were consistently higher; however, IL-23 was significantly lower in patients with SS compared to the controls. Tear levels of some cytokines were significantly elevated among SS groups compared to control groups. Therefore, these cytokines could be potential biomarkers of SS. However, standardization of sample collection and analytical methods is necessary in order to translate these findings into clinical practice.