Miracle-dz/UniFAR-FTUs huggingface dataset:
The Tasseled Cap de-mystified

The fundamental concepts on which the Tasseled Cap transformations of MSS and TM data are based - particularly the identification of inherent data structures - are explained and discussed. Emphasis on the structures present in data from any given sensor, which are themselves the expression of physical characteristics of scene classes, provides a number of advantages, including (a) reduction in data volume with minimal information loss; (b) spectral features which can be applied, without re-definition or adjustment, to any data set for a given sensor; (c) spectral features which can be directly associated with important physical parameters; and (d) easier integration of data from multiple sensors.
A mixed finite element formulation for elastoplasticity

The present article, provides a novel mixed finite element formulation for elastoplasticity which is suitable for the discretization of thin‐walled structures using highly anisotropic volume elements. We present a thermodynamically consistent framework for the modeling of elastoplastic stress response, where dissipative effects are considered through a dissipation function instead of explicit flow rules. Along these lines, a mixed incremental principle, in which stresses are included as independent unknowns, is derived. We propose to employ tangential‐displacement normal‐normal‐stress (TDNNS) elements for a Galerkin discretization of the underlying variational problem. These elements were originally developed for linear elasticity, where it could be shown that they do not suffer from shear locking if the element's aspect ratio deteriorates. Excellent computational performance and accuracy of the proposed method are demonstrated in several benchmark problems.
Machine Learning Based Lens-Free Shadow Imaging Technique for Field-Portable Cytometry

The lens-free shadow imaging technique (LSIT) is a well-established technique for the characterization of microparticles and biological cells. Due to its simplicity and cost-effectiveness, various low-cost solutions have been developed, such as automatic analysis of complete blood count (CBC), cell viability, 2D cell morphology, 3D cell tomography, etc. The developed auto characterization algorithm so far for this custom-developed LSIT cytometer was based on the handcrafted features of the cell diffraction patterns from the LSIT cytometer, that were determined from our empirical findings on thousands of samples of individual cell types, which limit the system in terms of induction of a new cell type for auto classification or characterization. Further, its performance suffers from poor image (cell diffraction pattern) signatures due to their small signal or background noise. In this work, we address these issues by leveraging the artificial intelligence-powered auto signal enhancing scheme such as denoising autoencoder and adaptive cell characterization technique based on the transfer of learning in deep neural networks. The performance of our proposed method shows an increase in accuracy >98% along with the signal enhancement of >5 dB for most of the cell types, such as red blood cell (RBC) and white blood cell (WBC). Furthermore, the model is adaptive to learn new type of samples within a few learning iterations and able to successfully classify the newly introduced sample along with the existing other sample types.
Direct Drive Volume Control Electro-hydraulic System

The principle and characteristics of direct drive hydraulic system were introduced.For the direct drive hydraulic system,AC servo motor is used to drive bi-direction pump,the pump and actuator(hydraulic cylinder or hydraulic motor) build up a closed circuit,and there is no direction valves,speed control valves and relief valves in the hydraulic circuit.The system can implement the control of direction change,speed and pressure limit of actuators through adjusting the direction,speed,torque and variable torque limit of motor.If the actuator needs to work,motor runs,else,the motor stops.Therefore there is no restriction losses and idle running losses in this system.The biggest advantages of the system is energy-saving.
Adaptasi individual dan kolektif: Respons masyarakat Indonesia menghadapi pandemi COVID-19

The COVID-19 pandemic has given an impact on various aspects of human life forcing humans to adapt to the existing condition. This study aimed to explore the adaptation process toward the COVID-19 pandemic in Indonesia. The research method applied was quantitative-descriptive. A total of 544 Indonesian citizens filled out an online social perception toward risk and spread of COVID-19 scale through a google form. The results focused on the adaptive response of the community consisting of both perceptions and behaviors. This study found that the adaptation of the society to deal with COVID-19 did not only occur at the individual level but also at the collective level. At the individual level, there were two kinds of psychological adaptation found namely active and passive. At the collective level, this study suggested that collective coping is an important form of social-psychological adaptation in which solidarity is the essence of the process.
Clinical and Molecular Relationships between COVID-19 and Feline Infectious Peritonitis (FIP)

The emergence of severe acute respiratory syndrome 2 (SARS-CoV-2) has led the medical and scientific community to address questions surrounding the pathogenesis and clinical presentation of COVID-19; however, relevant clinical models outside of humans are still lacking. In felines, a ubiquitous coronavirus, described as feline coronavirus (FCoV), can present as feline infectious peritonitis (FIP)—a leading cause of mortality in young cats that is characterized as a severe, systemic inflammation. The diverse extrapulmonary signs of FIP and rapidly progressive disease course, coupled with a closely related etiologic agent, present a degree of overlap with COVID-19. This paper will explore the molecular and clinical relationships between FIP and COVID-19. While key differences between the two syndromes exist, these similarities support further examination of feline coronaviruses as a naturally occurring clinical model for coronavirus disease in humans.
Mutational characteristics of young and elderly gastric cancer: a comparative study.

Background Young gastric cancer (YGC) has been indicated as having a worse prognosis than in elderly gastric cancer (EGC). It has been reported that YGC and EGC patients show different genomic profiles; however, there has been no comparative study conducted to reveal their mutational characteristics. Methods Firstly, we divided and analyzed the mutational landscape and 50 cancer-related genes characters of YGC (n=18) and EGC (n=18) patients from The Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD). A total of 8 gastric cancer samples including 4 YGC and 4 EGC patients were collected to detect 50 cancer-related genes by multiplex polymerase chain reaction (PCR) next generation sequencing. The R/maftools package was used to describe the mutational characteristics. Results Our results showed that the EGC group harbored more mutations than the YGC group. In 50 cancer-related genes in our cohort, the YGC group tended to be different from the EGC group using multiplex PCR next generation sequencing. In the YGC group, candidate mutations were identified within the following genes: IDH2, PDGFRA, KRAS, FLT3, FGFR2, and FGFR3. The YGC group showed less tumor mutational burden (TMB) level then EGC. Conclusions The YGC group tended to be more sensitive to molecularly targeted therapy because of it having more somatic mutations in 50 cancer-related genes using targeted next-generation sequencing.
Discrepancies in Antimicrobial Susceptibility between the JP2 and the Non-JP2 Genotype of Aggregatibacter actinomycetemcomitans

The Aggregatibacter actinomycetemcomitans JP2 genotype is associated with high leukotoxin production and severe (aggressive) periodontitis. The aim of this study was to compare the antimicrobial susceptibility of JP2 and non-JP2 genotype strains. Minimal inhibitory concentrations (MICs) of 11 antimicrobials were determined for 160 A. actinomycetemcomitans of serotype a, b, or c, mostly isolated in Sweden or Ghana. MIC distributions for benzylpenicillin and fusidic acid revealed a more susceptible subpopulation for 38 serotype b strains, including the 32 of the JP2 genotype, with a benzylpenicillin MIC range of 0.125–0.5 mg/L. In contrast, benzylpenicillin MIC ≤ 16 mg/L was the estimated 99.5% epidemiological cutoff (ECOFF) of all strains. Beta-lactamase production was not detected. The fusidic acid MIC distribution of 11 strains of Aggregatibacter aphrophilus agreed with that found in non-JP2 strains. Cefotaxime, meropenem, levofloxacin, and trimethoprim–sulfamethoxazole MICs were all ≤0.25 mg/L, while MIC90 values for amoxicillin, azithromycin and tetracycline were 1 mg/L. Metronidazole MICs varied between 0.5 and >256 mg/L. The discrepant findings indicate that A. actinomycetemcomitans may be divided into two separate wild types, with a suggested intrinsic reduced susceptibility for benzylpenicillin in the majority of non-JP2 genotype strains. Possible implications for the treatment of A. actinomycetemcomitans infections are discussed.
A Web-Based, Time-Use App To Assess Children’s Movement Behaviors: Validation Study of My E-Diary for Activities and Lifestyle (MEDAL)

Background Existing modes of collecting self-reported 24-hour movement information from children, including digital assessments, have not been demonstrated to be of acceptable validity when compared to objective measurements. My E-Diary for Activities and Lifestyle (MEDAL) is an interactive web-based diary developed to collect time-use information from children aged 10 years and older. Objective This study evaluated the validity of MEDAL for assessing children’s movement behaviors by comparing self-reported and accelerometer-measured time spent in movement behavior among children in Singapore aged 10-11 years. Methods Funding for this study was obtained in October 2017, and data were collected between April and August 2020. Participants recorded their daily activities using MEDAL over 2 specified weekdays and 2 weekend days and wore an Actigraph accelerometer on their nondominant wrist throughout the study to objectively assess movement behaviors. Spearman correlation coefficient and intraclass correlation coefficient (ICC) were used to compare the accelerometer measurements and self-reports for each movement behavior. Bland-Altman plots were generated to investigate trends of bias in the self-reports. Results Among the participants aged 10-11 years (29/49, 59% boys), we observed that children reported lower light physical activity (LPA) and higher moderate-to-vigorous physical activity (MVPA), inactivity, and night sleep than that measured by the accelerometer. There was a moderate-to-strong correlation between self-reported and accelerometer-measured MVPA (r=0.37; 95% CI 0.20-0.54), inactivity (r=0.36; 95% CI 0.18-0.54), and night sleep (r=0.58; 95% CI 0.43-0.74); the correlation for LPA was poor (r=0.19; 95% CI 0.02-0.36). Agreement was poor for all behaviors (MVPA: ICC=0.24, 95% CI 0.07-0.40; LPA: ICC=0.19, 95% CI 0.01-0.36; inactivity: ICC=0.29, 95% CI 0.11-0.44; night sleep: ICC=0.45, 95% CI 0.29-0.58). There was stronger correlation and agreement on weekdays for inactivity and night sleep; conversely, there was stronger correlation and agreement for MVPA and LPA on weekend days. Finally, based on Bland-Altman plots, we observed that with increasing MVPA, children tended to report higher MVPA than that measured by the accelerometer. There were no clear trends for the other behaviors. Conclusions MEDAL may be used to assess the movement behaviors of children. Based on self-reports, the children are able to estimate their time spent in MVPA, inactivity, and night sleep although actual time spent in these behaviors may differ from accelerometer-derived estimates; self-reported LPA warrant cautious interpretation. Observable differences in reporting accuracy exist between weekdays and weekend days.
Multi‐scale, multivariate community models improve designation of biodiversity hotspots in the Sunda Islands

Species occur in sympatric assemblages, bound together by ecological relationships and interspecific interactions. Borneo and Sumatra host some of the richest assemblages of biota worldwide. The region, however, faces the highest global deforestation rates, which seriously threaten its unique biodiversity. We used a large camera trap dataset that recorded data for 70 terrestrial species of mammals and birds, to explore the drivers of regional species richness patterns. Using a multi‐scale, multivariate modelling framework which quantified the main environmental factors associated with patterns of biodiversity, while simultaneously assessing individual relationships of each species, we determined the ecological drivers of sampled biodiversity, and their contributions to community assemblages. We then mapped predicted species richness, evaluated the effectiveness of protected areas in securing biodiversity hotspots, performed gap analysis to highlight biodiverse areas lacking protection and compared our predictions with species richness maps produced by using IUCN range layers. Finally, we investigated the performance of each species as an indicator of sampled biodiversity. We demonstrate that biodiversity in Borneo and Sumatra is primarily affected by gradients of ecological and anthropogenic factors, and only marginally by topographic and spatial factors. In both islands, species are primarily associated with elevational gradients in vegetation and climate, leading to altitudinal zonation in niche separation as a major factor characterizing the islands' biodiversity. Species richness was highest in north‐eastern Borneo and in western Sumatra. We found that most predicted biodiversity hotspots are not formally protected in either island; only 9.2 and 18.2% of the modelled species richness occurred within protected areas in Borneo and Sumatra, respectively. We highlighted that our prediction for Borneo performed better than, and differed drastically from, the IUCN species richness layer, while for Sumatra our modelled species richness layer and the IUCN one were similar, and both showed low predictive power. Our analysis suggests that common and generalist carnivores are the most effective indicators of sampled biodiversity and have high potential as focal, umbrella or indicator species to assist multi‐species vertebrate conservation planning. Understanding existing drivers and patterns of biodiversity is critical to support the development of effective community conservation strategies in this rapidly changing region.
Influential Factors and Personalized Prediction Model of Acute Pain Trajectories after Surgery for Renal Cell Carcinoma

Background: Renal cell carcinoma (RCC) is the most common neoplasm in kidneys, and surgical resection remains the mainstay treatment. Few studies have investigated how the postoperative pain changes over time and what has affected its trajectory. This study aimed to characterize the variations in postoperative pain over time and investigate associated factors after RCC surgery. Methods: This retrospective study was conducted in a single medical center in Taiwan, where maximal pain scores in a numeric rating scale were recorded daily in the first five postoperative days (PODs) after RCC surgery. Latent curve models were developed, using two latent variables, intercept and slope, which represented the baseline pain and rate of pain resolution. These models explain the variations in postoperative pain scores over time. A predictive model for postoperative pain trajectories was also constructed. Results: There were 861 patients with 3850 pain observations included in the analysis. Latent curve analysis identified that female patients and those with advanced cancer (stage III and IV) tended to have increased baseline pain scores (p = 0.028 and 0.012, respectively). Furthermore, patients over 60 years, without PCA use (both p < 0.001), and with more surgical blood loss (p = 0.001) tended to have slower pain resolution. The final predictive model fit the collected data acceptably (RMSEA = 0.06, CFI = 0.95). Conclusion: Latent curve analysis identified influential factors of acute pain trajectories after RCC surgery. This study may also help elucidate the complex relationships between the variations in pain intensity over time and their determinants, and guide personalized pain management after surgery for RCC.
Urinary hsv2-miR-H9 to hsa-miR-3659 ratio is an effective marker for discriminating prostate cancer from benign prostate hyperplasia in patients within the prostate-specific antigen grey zone

Purpose Tumor microRNAs (miRNAs) are released to biofluids directly or indirectly. Although urinary miRNAs are promising non-invasive biomarkers for the diagnosis of prostate cancer (PCa), their clinical application is challenging for technical reasons. We examined the efficacy of urinary hsv2-miR-H9 to hsa-miR-3659 ratio as a non-invasive diagnostic biomarker of PCa. Materials and Methods The expression of urinary miRNAs was quantified by real-time PCR in 116 samples from 53 patients with benign prostatic hyperplasia (BPH) and 63 patients with PCa. The miRNA expression ratio was calculated using an upregulated miRNA (hsv2-miR-H9) as the numerator and a downregulated miRNA (hsa-miR-3659) as the denominator. Results The urinary miR-H9 to miR-3659 ratio was significantly higher in PCa than in BPH controls (p<0.001). The diagnostic accuracy of the urinary miRNA expression ratio was comparable with that of prostate-specific antigen (PSA) (receiver operating characteristic [ROC] curve comparison, p=0.287). The area under the curve for urinary miRNA expression ratio was 0.862 and that for PSA was 0.642 in the “PSA gray zone” (3–10 ng/mL) (ROC curve comparison, p=0.034). The use of the urinary miRNA expression ratio would have prevented 70.6% of unnecessary prostate biopsies; however, 28.6% of PCa cases could be missed in patients within the PSA gray zone. Conclusions The expression ratio of urinary miR-H9 to miR-3659 could be a relevant non-invasive biomarker for PCa diagnosis, particularly for patients within the PSA gray zone.
Applying the biopsychosocial model to unpack a psychosocial support intervention designed to improve antiretroviral treatment outcomes for adolescents in South Africa

Adolescents (10 to 19 years) living with HIV (ALHIV) experience disproportionately poor adherence to antiretroviral treatment (ART) compared to other age groups. Several barriers, including psychosocial challenges, contribute to this observation. Psychosocial support (PSS) interventions show promising results as a strategy to deal with the biological and psychosocial challenges faced by ALHIV. However, there is dearth of information on how psychosocial support interventions designed to improve treatment adherence and retention in care among ALHIV are effective. In this commentary, we used the biopsychosocial model to formulate hypotheses on how the components of a PSS intervention could improve adherence and retention in ART care. Psychological wellbeing, coping strategies, social support, self-efficacy, and disclosure are key components in the intervention designed to improve ART adherence and retention in care. The management of ALHIV for improved ART adherence and retention requires recognising and addressing the complex biological, psychological and social issues peculiar to them.
Hearing Like a Musician: Integrating Sensory Perception of Self into a Social Theory of Self-Reflexivity

In Mead’s philosophy, we develop and present ourselves in anticipation of an audience, taking the role of other to “see” ourselves as we will be seen. But what we see when we take the position of other is not in fact what the other sees of ourselves. It is only the visible side of our experience that the other can grasp, leaving hidden our interior experiences. This article speaks to this conundrum left by Mead’s writing, presenting the training of musicians as a strategic site for showing why we need to go beyond Mead in social psychology, adding what Merleau-Ponty shows us of how we work on the invisible side of our experience. This research examines how classical music teachers work with students to deliberately transform their inner experience of their sound to align their self-perception with how others perceive them.
Antebellum America for German Immigrants: Thérèse Robinson von Jacob and Talvi‘s The Exiles (1853)

ABSTRACT The career of German writer Talvi (Thérèse Albertine Luise von Jacob Robinson [1797–1870]) illustrates her strong engagement with the intellectual and elite literary scenes of nineteenth-century Europe and America. This essay reviews her family background and early literary activities in Europe, while noting her extraordinary career as a language scholar, novelist, poet, translator, ethnologist and historian. Written during a period before the development of strong immigration laws in the United States, her complex novel Die Auswanderer (1852)– published in English translation as The Exiles (1853) – voices concerns relevant to both immigrants and American citizens alike, while providing strong views on issues such as slavery, immigration, cultural variation across American states and comparative national identities. The Exiles stands out as both an important early immigration novel and a notable example of German perspectives on the antebellum American social scene.
Dynamics of Pinus wood prices for different timber assortments: comparison of stochastic processes

Understanding the dynamics of market prices for Pinus wood is a prerequisite for strategic decisions concerning forest investment plans since, in terms of the market, the exogenous risk to a project depends on timber assortments. The stochastic process that represents the best way of pricing the underlying asset therefore needs to be known. This study set out to compare Fractional Brownian Motion and Geometric Brownian Motion, through econometric tests, to understand the stochastic model that best represents the price behaviour of Pinus wood from planted forests in the state of Santa Catarina, Brazil, for the pricing of the underlying asset and valuation of the real options intrinsic to forest investment projects. The time series of prices, for the period from June 2017 to July 2019, relate to three assortments of Pinus wood used for multiple products. The recommended econometric tests to analyse the time series were for normality of the data, trend, autocorrelation, stationarity and fractional differential estimation. The time series were then modelled by means of stochastic processes in line with the econometric tests. The time series showed normal behaviour and indicated the presence of a positive trend and non-stationarity in the data. In addition, a true long memory was found in all series. Fractional Brownian Motion proved to be the most suitable stochastic process for modelling the prices of three forest timber assortments, given the non-stationary characteristics and true long memory of the time series for Pinus wood prices.