Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved operational stability of polyfluorene-based organic light-emitting diodes with plasma-treated indium–tin–oxide anodes

We report the influence of various surface treatments of indium–tin–oxide (ITO) anodes on the operational stability of high-efficiency (up to 8.2 lm/W) green-emitting polymer light-emitting diodes (PLEDs), employing a doped poly(3,4-ethylene dioxythiophene), hole transport layer, a polyfluorene based emissive layer, and Ca–Al cathodes. The anodes were modified by physical (oxygen-plasma), chemical (aquaregia), and combined treatments. Oxygen plasma improves the stability under constant current with respect to all other anodes, with half-brightness (100 cd/m2) lifetimes two to five times longer than for untreated samples, and 1000 times longer than for aquaregia samples. We derive two major indications for optimization of PLEDs. First, thermal management of the diode is of the uppermost importance and there is significant scope for improvement. Second, the ITO anode and in general the electrical properties of the hole-injecting contact are crucial to device operation, even in the presence of a hole transpo.
Efficient covid19 disease diagnosis based on cough signal processing and supervised machine learning

The spread of the coronavirus has claimed the lives of millions worldwide, which led to the emergence of an economic and health crisis at the global level, which prompted many researchers to submit proposals for early diagnosis of the coronavirus to limit its spread. In this work, we propose an automated system to detect COVID-19 based on the cough as one of the most important infection indicators. Several studies have shown that coughing accounts for 65% of the total symptoms of infection. The proposed system is mainly based on three main steps: first, cough signal detection and segmentation;second, cough signal extraction;and third, three techniques of supervised machine learning-based classification: Support Vector Machine (SVM), K-Nearest Neighbours (KNN), and Decision Tree (DT). Our proposed system showed high performance through good accuracy values, where the best accuracy for classifying female coughs was 99.6% using KNN and 88% for males using SVM. © 2022 by the Authors.
Error covariance estimation methods based on analysis residuals: theoretical foundation and convergence properties derived from simplified observation networks

We examine the theoretical foundation of the method to estimate error covariances based on analysis residuals in observation space, also known as the Desroziers method. Our analysis also includes a method based on a posteriori diagnostics of variational analysis schemes. A mathematical analysis of convergence is carried out with a simplified regular observation network, where we identify stable and unstable fixed‐point solutions, examine their rate of convergence and the conditions for convergence to the truth and compare it with maximum‐likelihood estimation. It is shown that the estimation of variance parameters converges to the truth if the error correlation is specified correctly. The convergence is much faster with the analysis increment method than with the method designed for variational analysis schemes. We also propose a combination of the Desroziers scheme and the maximum‐likelihood estimation method that could be used to estimate the spatial correlation length‐scale of observation errors. The estimation of both full observation and background‐error covariances matrices derived entirely from observation‐based residuals does not change the gain matrix, but the estimation of either one matrices is well‐defined. An analysis of the estimation of the full observation error covariance matrix using a regular observation network reveals that if all eigenvalues of the prescribed background‐error covariance are smaller than their corresponding innovation covariance eigenvalue, then the estimated error covariance converges to the truth but only if the prescribed background error is correctly specified. In the case where some eigenvalues of the background‐error covariance greatly exceed those of the innovation covariance, the convergent observation‐error matrix may become rank‐deficient. Its inverse does not exist.
Stabilization of Copper-Based Biochips with Alumina for Biosensing Application

Surface plasmon resonance devices typically rely on the use of gold-coated surfaces, but the use of more abundant metals is desirable for the long-term development of plasmonic biochips. As a substitute for gold, thin copper films have been deposited on glass coverslips by thermal evaporation. As expected, these films immersed in a water solution initially exhibit an intense plasmonic resonance comparable to gold. However, without protection, an angle-resolved optical analysis shows a rapid degradation of the copper, characterized by a continuous angular shift of the plasmonic resonance curve. We show that copper films protected with a thin layer of aluminum oxide of a few nanometers can limit the oxidation rate for a sufficient time to perform some standard measurements. As the process is simple and compatible with the current biochip production technique, such an approach could pave the way for the production of alternative and more sustainable biochips.
Bioprinting on Organ-on-Chip: Development and Applications

Organs-on-chips (OoCs) are microfluidic devices that contain bioengineered tissues or parts of natural tissues or organs and can mimic the crucial structures and functions of living organisms. They are designed to control and maintain the cell- and tissue-specific microenvironment while also providing detailed feedback about the activities that are taking place. Bioprinting is an emerging technology for constructing artificial tissues or organ constructs by combining state-of-the-art 3D printing methods with biomaterials. The utilization of 3D bioprinting and cells patterning in OoC technologies reinforces the creation of more complex structures that can imitate the functions of a living organism in a more precise way. Here, we summarize the current 3D bioprinting techniques and we focus on the advantages of 3D bioprinting compared to traditional cell seeding in addition to the methods, materials, and applications of 3D bioprinting in the development of OoC microsystems.
Efficient Multipath Selection for IoT Video Transmission

In IoT video applications, such as public transportation and traffic monitoring, video is often transmitted over a multi-hop wireless network and has stringent Quality of Service requirements. While multipath routing has been proposed as an effective strategy for supporting this demand, it should select paths that meet the requirements of the driving video application in a timely manner. In this paper, we introduce FITPATH, an efficient and adaptable path selection scheme for multipath routing that can accommodate scenarios where multiple video sources can simultaneously transmit heterogeneous video flows, i.e., flows of different bitrates. FITPATH uses a novel heuristic-based iterative optimization approach that estimates the conditions of the underlying network in real time while accounting for the different bitrate requirements of the application video flows. We show FITPATH outperforms various existing path selection mechanisms both in terms of user QoE and network performance. We also evaluate FITPATH’s convergence to demonstrate that it can be used in practice to quickly generate solutions with adequate video quality while incrementally improving QoE as the algorithm iterates.
PERBANDINGAN METODE WATERFALL DAN RAD (RAPID APPLICATION DEVELOPMENT) PADA PENGEMBANGAN SISTEM INFORMASI

- The development of software systems is always faced with the choice of a very diverse system development methodology, this raises doubts for developers, because if one chooses the methodology it can affect the success or failure of developing this system. The research used by the author is using data from previous studies, reviewing journals, and making comparisons, in other words the author uses descriptive methods. Based on the research, it was found that the waterfall method is not suitable for high development models because the stages cannot be repeated, are expensive and the processing time is carried out in stages, while the Rapid application development (RAD) method is suitable for large projects because it uses an iterative method and can save money. cost
Exploring the Relevance between Gut Microbiota-Metabolites Profile and Chronic Kidney Disease with Distinct Pathogenic Factor

Gut dysbiosis-altered metabolite association exhibits specific and convincing utility to differentiate CKD associated with distinct pathogenic factor. These results present the validity of pathogenesis-associated markers across healthy participants and high-risk population toward the early screening, prevention, diagnosis, or personalized treatment of CKD. ABSTRACT The intimate correlation of chronic kidney disease (CKD) with structural alteration in gut microbiota or metabolite profile has been documented in a growing body of studies. Nevertheless, a paucity of demonstrated knowledge regarding the impact and underlying mechanism of gut microbiota or metabolite on occurrence or progression of CKD is unclarified thus far. In this study, a liquid chromatography coupled-mass spectrometry and long-read sequencing were applied to identify gut metabolites and microbiome with statistically-discriminative abundance in diabetic CKD patients (n = 39), hypertensive CKD patients (n = 26), or CKD patients without comorbidity (n = 40) compared to those of healthy participants (n = 60). The association between CKD-related species and metabolite was evaluated by using zero-inflated negative binomial (ZINB) regression. The predictive utility of identified operational taxonomic units (OTUs), metabolite, or species-metabolite association toward the diagnosis of incident chronic kidney disease with distinct pathogenic factor was assessed using the random forest regression model and the receiver operating characteristic (ROC) curve. The results of statistical analyses indicated alterations in the relative abundances of 26 OTUs and 41 metabolites that were specifically relevant to each CKD-patient group. The random forest regression model with only species, metabolites, or its association differentially distinguished the hypertensive, diabetic CKD patients, or enrolled CKD patients without comorbidity from the healthy participants. IMPORTANCE Gut dysbiosis-altered metabolite association exhibits specific and convincing utility to differentiate CKD associated with distinct pathogenic factor. These results present the validity of pathogenesis-associated markers across healthy participants and high-risk population toward the early screening, prevention, diagnosis, or personalized treatment of CKD.
Characterization of multiple Si∕SiO2 interfaces in silicon-on-insulator materials via second-harmonic generation

Charge generation, transport, and recombination processes in UNIBOND® silicon-on-insulator wafers are studied via an optical second-harmonic generation (SHG) technique. The electric fields at the interfaces vary with time due to charge trapping. The presence of a thin native oxide layer on the top Si film contributes significantly to the SH intensity due to the strong time-dependent electric field generated by electrons transported to the surface. For the thick buried oxide, the electric field is primarily due to carrier trapping at the interface, and it varies with time weakly. The SHG signals depend strongly on the externally applied electric field, which can differentiate the contribution of each interface to the total SH signal.
Nucleo-Cytoplasmic Transport of ZIKV Non-Structural 3 Protein Is Mediated by Importin-α/β and Exportin CRM-1

Flaviviruses have a cytoplasmic replication cycle, but recent evidence indicates that nuclear elements play a role in their viral replication. Viral proteins, such as NS5 and C, are imported into the nucleus, and blocking their import prevents replication. ABSTRACT Flaviviruses have a cytoplasmic replicative cycle, and crucial events, such as genome translation and replication, occur in the endoplasmic reticulum. However, some viral proteins, such as C, NS1, and NS5 from Zika virus (ZIKV) containing nuclear localization signals (NLSs) and nuclear export signals (NESs), are also located in the nucleus of Vero cells. The NS2A, NS3, and NS4A proteins from dengue virus (DENV) have also been reported to be in the nucleus of A549 cells, and our group recently reported that the NS3 protein is also located in the nucleus of Huh7 and C636 cells during DENV infection. However, the NS3 protease-helicase from ZIKV locates in the perinuclear region of infected cells and alters the morphology of the nuclear lamina, a component of the nuclear envelope. Furthermore, ZIKV NS3 has been reported to accumulate on the concave face of altered kidney-shaped nuclei and may be responsible for modifying other elements of the nuclear envelope. However, nuclear localization of NS3 from ZIKV has not been substantially investigated in human host cells. Our group has recently reported that DENV and ZIKV NS3 alter the nuclear pore complex (NPC) by cleaving some nucleoporins. Here, we demonstrate the presence of ZIKV NS3 in the nucleus of Huh7 cells early in infection and in the cytoplasm at later times postinfection. In addition, we found that ZIKV NS3 contains an NLS and a putative NES and uses the classic import (importin-α/β) and export pathway via CRM-1 to be transported between the cytoplasm and the nucleus. IMPORTANCE Flaviviruses have a cytoplasmic replication cycle, but recent evidence indicates that nuclear elements play a role in their viral replication. Viral proteins, such as NS5 and C, are imported into the nucleus, and blocking their import prevents replication. Because of the importance of the nucleus in viral replication and the role of NS3 in the modification of nuclear components, we investigated whether NS3 can be localized in the nucleus during ZIKV infection. We found that NS3 is imported into the nucleus via the importin pathway and exported to the cytoplasm via CRM-1. The significance of viral protein nuclear import and export and its relationship with infection establishment is highlighted, emphasizing the development of new host-directed antiviral therapeutic strategies.
Functional Amyloids in Pseudomonas aeruginosa Are Essential for the Proteome Modulation That Leads to Pathoadaptation in Pulmonary Niches

Pseudomonas aeruginosa is inextricably linked with chronic lung infections. In this study, the well-conserved Fap operon was found to be essential for pathoadaptation in pulmonary infection in a rat lung model. ABSTRACT Persistence and survival of Pseudomonas aeruginosa in chronic lung infections is closely linked to the biofilm lifestyle. One biofilm component, functional amyloid of P. aeruginosa (Fap), imparts structural adaptations for biofilms; however, the role of Fap in pathogenesis is still unclear. Conservation of the fap operon encoding Fap and P. aeruginosa being an opportunistic pathogen of lung infections prompted us to explore its role in lung infection. We found that Fap is essential for establishment of lung infection in rats, as its genetic exclusion led to mild focal infection with quick resolution. Moreover, without an underlying cystic fibrosis (CF) genetic disorder, overexpression of Fap reproduced the CF pathotype. The molecular basis of Fap-mediated pulmonary adaptation was explored through surface-associated proteomics in vitro. Differential proteomics positively associated Fap expression with activation of known proteins related to pulmonary pathoadaptation, attachment, and biofilm fitness. The aggregative bacterial phenotype in the pulmonary niche correlated with Fap-influenced activation of biofilm sustainability regulators and stress response regulators that favored persistence-mediated establishment of pulmonary infection. Fap overexpression upregulated proteins that are abundant in the proteome of P. aeruginosa in colonizing CF lungs. Planktonic lifestyle, defects in anaerobic pathway, and neutrophilic evasion were key factors in the absence of Fap that impaired establishment of infection. We concluded that Fap is essential for cellular equilibration to establish pulmonary infection. Amyloid-induced bacterial aggregation subverted the immune response, leading to chronic infection by collaterally damaging tissue and reinforcing bacterial persistence. IMPORTANCE Pseudomonas aeruginosa is inextricably linked with chronic lung infections. In this study, the well-conserved Fap operon was found to be essential for pathoadaptation in pulmonary infection in a rat lung model. Moreover, the presence of Fap increased pathogenesis and biofilm sustainability by modulating bacterial physiology. Hence, a pathoadaptive role of Fap in pulmonary infections can be exploited for clinical application by targeting amyloids. Furthermore, genetic conservation and extracellular exposure of Fap make it a commendable target for such interventions.
Spore-Forming Clostridium (Clostridioides) difficile in Wastewater Treatment Plants in Western Australia

Clostridium difficile infection (CDI) is a leading cause of antimicrobial-associated diarrhea in health care facilities. Extended hospital stays and recurrences increase the cost of treatment and morbidity and mortality. ABSTRACT There is growing evidence that shows Clostridium (Clostridioides) difficile is a pathogen of One Health importance with a complex dissemination pathway involving animals, humans, and the environment. Thus, environmental discharge and agricultural recycling of human and animal waste have been suspected as factors behind the dissemination of Clostridium difficile in the community. Here, the presence of C. difficile in 12 wastewater treatment plants (WWTPs) in Western Australia was investigated. Overall, C. difficile was found in 90.5% (114/126) of raw sewage influent, 48.1% (50/104) of treated effluent, 40% (2/5) of reclaimed irrigation water, 100% (38/38) of untreated biosolids, 95.2% (20/21) of anaerobically digested biosolids, and 72.7% (8/11) of lime-amended biosolids. Over half of the isolates (55.3% [157/284]) were toxigenic, and 97 C. difficile ribotypes (RTs) were identified, with RT014/020 the most common (14.8% [42/284]). Thirteen C. difficile isolates with the toxin gene profile A+ B+ CDT+ (positive for genes coding for toxins A and B and the binary C. difficile transferase toxin [CDT]) were found, including the hypervirulent RT078 strain. Resistance to the antimicrobials fidaxomicin, vancomycin, metronidazole, rifaximin, amoxicillin-clavulanate, meropenem, and moxifloxacin was uncommon; however, resistance to clindamycin, erythromycin, and tetracycline was relatively frequent at 56.7% (161/284), 14.4% (41/284), and 13.7% (39/284), respectively. This study revealed that toxigenic C. difficile was commonly encountered in WWTPs and being released into the environment. This raises concern about the possible spillover of C. difficile into animal and/or human populations via land receiving the treated waste. In Western Australia, stringent measures are in place to mitigate the health and environmental risk of recycling human waste; however, further studies are needed to elucidate the public health significance of C. difficile surviving the treatment processes at WWTPs. IMPORTANCE Clostridium difficile infection (CDI) is a leading cause of antimicrobial-associated diarrhea in health care facilities. Extended hospital stays and recurrences increase the cost of treatment and morbidity and mortality. Community-associated CDI (CA-CDI) cases, with no history of antimicrobial use or exposure to health care settings, are increasing. The isolation of clinically important C. difficile strains from animals, rivers, soil, meat, vegetables, compost, treated wastewater, and biosolids has been reported. The objective of this study was to characterize C. difficile in wastewater treatment plants (WWTPs) in Australia. We found that C. difficile can survive the treatment processes of WWTPs, and toxigenic C. difficile was being released into the environment, becoming a potential source/reservoir for CA-CDI.
Host Genetics and Environment Shape the Composition of the Gastrointestinal Microbiome in Nonhuman Primates

Our data point to the degree to which host genetics can influence GI microbiome composition and suggest, within primate species, that individual host genetics is unlikely to significantly alter the microbiome. These data are important for the development of therapeutics aimed at altering the microbiome within populations of genetically disparate members of primate species. ABSTRACT The bacterial component of the gastrointestinal tract microbiome is comprised of hundreds of species, the majority of which live in symbiosis with the host. The bacterial microbiome is influenced by host diet and disease history, and host genetics may additionally play a role. To understand the degree to which host genetics shapes the gastrointestinal tract microbiome, we studied fecal microbiomes in 4 species of nonhuman primates (NHPs) held in separate facilities but fed the same base diet. These animals include Chlorocebus pygerythrus, Chlorocebus sabaeus, Macaca mulatta, and Macaca nemestrina. We also followed gastrointestinal tract microbiome composition in 20 Macaca mulatta (rhesus macaques [RMs]) as they transitioned from an outdoor to indoor environment and compared 6 Chlorocebus pygerythrus monkeys that made the outdoor to indoor transition to their 9 captive-born offspring. We found that genetics can influence microbiome composition, with animals of different genera (Chlorocebus versus Macaca) having significantly different gastrointestinal (GI) microbiomes despite controlled diets. Animals within the same genera have more similar microbiomes, although still significantly different, and animals within the same species have even more similar compositions that are not significantly different. Significant differences were also not observed between wild-born and captive-born Chlorocebus pygerythrus, while there were significant changes in RMs as they transitioned into captivity. Together, these results suggest that the effects of captivity have a larger impact on the microbiome than other factors we examined within a single NHP species, although host genetics does significantly influence microbiome composition between NHP genera and species. IMPORTANCE Our data point to the degree to which host genetics can influence GI microbiome composition and suggest, within primate species, that individual host genetics is unlikely to significantly alter the microbiome. These data are important for the development of therapeutics aimed at altering the microbiome within populations of genetically disparate members of primate species.
Algorithmisches Investment. Zum Einsatz von Künstlicher Intelligenz und Big Data in Finanzorganisationen

Zusammenfassung Quantitative Hedge-Fonds, kurz Quants, nutzen heute zunehmend digitale Künstliche Intelligenz- und Big-Data-Technologien, um ihre Marktanalyse und ihr Portfoliomanagement zu optimieren. Quants stehen damit exemplarisch für einen gesellschaftlichen Trend, Entscheidungsprozesse zunehmend digitalen Algorithmen zu überantworten. Zugleich zeigt die fortschreitende Algorithmisierung in und durch Quants, dass Digitalisierungsprozesse in hohem Maße in und durch Organisationen vorangetrieben werden. Die Algorithmisierung des Finanzsystems wird sowohl durch organisationale Strukturen und Prozesse geprägt wie auch umgekehrt Algorithmen die organisationale Informationsverarbeitung- und Wissensgenerierung verändern. Algorithmisches Investment durch Quant-Hedge-Fonds verdeutlicht, dass Digitalisierungsprozesse der Gesellschaft in ihrer organisationalen Verfasstheit verstanden werden müssen.