Miracle-dz/UniFAR-FTUs huggingface dataset:
Early super-spreader events are a likely determinant of novel SARS-CoV-2 variant predominance

The emergence of multiple new SARS-CoV-2 variants, characterized to varying degrees by increased infectivity, higher virulence and evasion of vaccine and infection-induced immunologic memory, has hampered international efforts to contain the virus. While it is generally believed that these variants first develop in single individuals with poor immunologic control of the virus, the factors governing variant predominance in the population remain poorly characterized. Here we present a mathematical framework for variant emergence accounting for the highly variable number of people secondarily infected by individuals with SARS-CoV-2 infection. Our simulations suggest that threatening new variants probably develop within infected people fairly commonly, but that most die out and do not achieve permanence in the population. Variants that predominate are more likely to be associated with higher infectiousness, but also the occurrence of a super-spreader event soon after introduction into the population.
Comparison in safety of chemotherapy protocols for blood cancers: toxicity of H-CVAD versus GELA/BURKIMAB/PETHEMA LAL

Background and objective The Hyper-CVAD/Methotrexate-Cytarabine (H-CVAD/MTX-AraC) chemotherapy protocol has been one of the standard treatments for blood cancers, such as Mantle cell lymphoma (MCL), Burkitt’s lymphoma (BL) and B-cell and T-cell acute lymphoblastic leukaemia (ALL). Due to high toxicity, it has been progressively replaced with new specific regimens with a better safety profile (GELA protocol for MCL, BURKIMAB for BL and PETHEMA for B-cell and T-cell ALL). The objective of this study is to analyse the toxicity and infectious complications of these therapeutic regimens, as well as the event free survival (EFS). Patients and methods This is a retrospective and descriptive observational study of 81 patients, comparing 42 patients treated with H-CVAD/MTX-AraC (group A) versus 39 patients treated with GELA/BURKIMAB/PETHEMA (group B). Results All patients in group A developed pancytopenia, but in group B 74.4% neutropenia, 51.3% thrombocytopenia and 69.2% anaemia. The total number of infections in group A was higher than in group B: 154 versus 48, 3.67 versus 1.23 per patient and 0.59 versus 0.25 per cycle. Likewise, febrile neutropenia happened: 106 versus 21 cases, 2.52 versus 0.52 per patient and 0.41 versus 0.11 per cycle. EVS is higher in group B: 33% versus 79% (2-year), and 24% versus 69% (5-year). Conclusions Current therapeutic protocols have shown higher EFS due to better safety profile, with less haematological, neurological and haemorrhagic toxicity, as well as lower rates of infectious complications.
Adaptive Bagging Methods for Classification of Data Streams with Concept Drift

: Data streams represent a continuous stream of data, in many forms, coming from different sources. Streams are often dynamic and its underlying structure usually changes over time. When solving predictive tasks on the streaming data, traditional models, trained on historical data, may become invalid, when such change occurs. Therefore, adaptive models, equipped with mechanisms to reflect the changes in the data, are suitable to solve these tasks. Adaptive ensemble models represent a popular group of such methods used in classification tasks on data streams. In this paper, we designed and implemented the modifications of the adaptive bagging methods, which utilizes internal class-weighting schemes for the model adaptation. Implemented models were evaluated on two simulated real-world data streams and compared with base classifiers and other adaptive methods. In addition to the performance evaluation, we also analyzed other models' characteristics, such as the duration of model update and memory requirements.
insulated-gate bipolar transistors (RB-IGBTs) [9-11] also promote the proliferation of CSI

1Abstract—This paper proposes a split-capacitor four-wire current source inverter, which is the dual of the split-capacitor four-wire voltage source inverter. Since the midpoint of the dc link is tied to the neutral point of ac filter capacitors, the common mode voltage (CMV) is reduced significantly. Consequently, the leakage current issue is effectively addressed. The proposed circuit is cost-effective as no extra switch is added. This paper firstly establishes the equivalent common-mode circuit of the proposed inverter. And the impact of the neutral line inductance on CMV is also analyzed. Then, a specific modulation is introduced to balance the dc-link voltages/currents. To achieve good input/output performance, a nonlinear control method is developed based on time-domain models. Finally, all the proposed methods and related theoretical analysis are verified by simulations and experimental results.
Very Short Primer on Blockchain Technology for Database Researchers

Blockchain is an emerging technology, considered increasingly often beyond the cryptocurrency world for business-to-business use-cases. In contrast to public blockchains such as Bitcoin, that are open systems in which anyone can participate, in business-to-business scenarios the membership of the service is controlled (permissioned blockchain). This permits the use of Byzantine fault tolerant (BFT) consensus protocols at the core of the service to establish a total order of transactions, instead of the more expensive Proof-of-Work-based consensus protocols. Permissioned blockchains typically set out to solve problems in the space where databases have traditionally resided, with the main difference being that the former decentralizes trust. There are numerous research proposals in the intersection of databases and blockchains. Sadly, there are still many misconceptions about this technology which leads to confusion in the community. The main goal of this primer is to give an overview of the relevant topics and provide pointers for further reading.
Automated seismic-to-well ties using dynamic time warping

The quality of seismic-to-well tie is commonly quantified using the classical Pearson’s correlation coefficient. However the seismic wavelet is time-variant, well logging and upscaling is only approximate, and the correlation coefficient does not follow this nonlinear behavior. We introduce the Dynamic Time Warping (DTW) to automate the tying process, accounting for frequency and time variance. The Dynamic Time Warping method can follow the nonlinear behavior better than the commonly used correlation coefficient. Furthermore, the quality of the similarity value does not depend on the selected correlating window. We compare the developed method with the manual seismic-to-well tie in a benchmark case study.
Meisyarah Dwiastuti Indonesian-English Neural Machine Translation

In this thesis, we conduct a study on neural machine translation (NMT) for an under-studied language, Indonesian, specifically for English-Indonesian (EN-ID) and Indonesian-English (ID-EN) in a low-resource domain, TED talks. Our goal is to implement domain adaptation methods to improve the low-resource EN-ID and ID-EN NMT systems. First, we implement model fine-tuning method for EN-ID and ID-EN NMT systems by leveraging a large parallel corpus containing movie subtitles. Our analysis shows the benefit of this method for the improvement of both systems. Second, we improve our ID-EN NMT system by leveraging English monolingual corpora through back-translation. Our back-translation experiments focus on how to incorporate the back-translated monolingual corpora to the training set, in which we investigate various existing training regimes and introduce a novel 4-way-concat training regime. We also analyze the effect of finetuning our back-translation models with different scenarios. Experimental results show that our method of implementing back-translation followed by model finetuning makes an improvement in our ID-EN NMT systems by around 1.5 BLEU point over a system without back-translation. Our ID-EN NMT systems show a comparable performance with Google Translate on WIT3 TED Talks tst2015-6 and tst2017plus test sets.
SEGMENTATION AND IDENTIFICATION OF MRI BRAIN SEGMENT IN DIGITAL IMAGE

: Brain image segmentation is important in the area of clinical diagnosis. MRI Brain image segmentation is time consuming and there is always a chance of occurrence of error when the segmentation is done manually. It is always possible to detect the infected tissues easily in the current medical field. However, the accuracy and the characteristics of abnormalities of the tissues are not precise. In the past, many researchers have identified the drawbacks of manual segmentation and hence proposed the semiautomatic and fully automatic segmentation methods in the field of medical imaging. The amount of precision about the detection of defective tissues leads to acceptance of a particular image segmentation method. In this article three segmentation methods are hybridized to get the optimum extraction of the region of interest (ROI) in brain MRI image. Further, the region properties of segment is extracted and stored as knowledgebase. The proposed algorithm integrates multiple segmentation methods and identifies the Brain Outer layer in MRI image. This identification aids medical experts for optimum diagnosis of defective tissues in the brain.
Convolutional neural networks model compression based on feature selection for image classiﬁcation

: Deep convolutional neural networks (CNN) feature extractor (CNN--FE) has been widely applied in many applications and achieved great success. However, evaluating shows that the CNN--FE holds abundant parameters which largely limits its applications on memory-limited platforms, such as smartphones. This study makes an effort to trim the well-known CNN--FEs, AlexNet, to reduce its parameters meanwhile the image classiﬁcation performance almost remains unchanged. This task is considered as a CNN--FE model compression problem. Through carefully analyzing the parameter distribution of AlexNet, we ﬁnd about 99% of parameters are in its fully connected layer but the deep features are redundant for image classiﬁcation tasks with small number of categories. Moreover, we propose to convert the CNN--FE model compression problem into a feature selection problem. Speciﬁcally, a feature selection method, which is based on mutual information and a novel criterion related to the classiﬁcation accuracy and the compression ratio, has been proposed. Image classiﬁcation experiments on a public scene categories database and our self-built wireless capsule endoscope (WCE) bubble dataset show that our proposed CNN--FE model compression method reduces more than 83% size of the AlexNet while almost maintaining the classiﬁcation accuracy.
The State of the Art of Barriers to Exclusive Breastfeeding among Working Mothers in Developing Countries

According to the WHO, the global standard for infant nutrition is exclusive breastfeeding (EBF). However, the level of EBF has been identified to remain low in developing countries. This is quite ironical as one could expect that breastfeeding mothers in developing countries will find EBF attractive as a better alternative to infant food considering the high level of food insecurity in the region. Adopting a qualitative approach, this paper dived into the literature and identified key factors which act as impediments to EBF among working mothers in this region - insufficient breastfeeding breaks in the workplace, lack of breastfeeding spaces and short maternity leaves, birth by caesarean section, poor lactation, poor maternal health, and poor spousal and societal support.
U-Pb zircon dates for the Granite Mountain batholith, Burgess Creek stock, and Sheridan Creek stock, Gibraltar Mine area, south-central British Columbia

The Granite Mountain batholith (Late Triassic), host to the Gibraltar porphyry Cu-Mo deposit, is east of the Fraser River between Williams Lake and Quesnel. Previously considered part of Cache Creek terrane, the batholith is in a panel of Quesnel terrane rocks that is faulted against Cache Creek terrane to the east and south, as established by mapping carried out in 2013 and 2014. Samples collected during this mapping, dated using the U-Pb zircon chemical abrasion thermal ionization mass spectrometry method (CA-TIMS), provide crystallization ages for the batholith and two adjacent plutonic units. Three samples from the Granite Mountain batholith yield Late Triassic dates of 217.15 ±0.37 Ma (Granite Mountain phase leucocratic tonalite), 215.71 ±0.36 Ma (Mine phase tonalite), and 214.98 ±0.38 Ma (quartz-plagioclase porphyry dike cutting Mine phase tonalite). The Burgess Creek stock, on the northeast margin of the Granite Mountain batholith, provides dates of 222.71 ±0.39 Ma (tonalite) and 221.25 ±0.39 Ma (quartz diorite), demonstrating that it is also Late Triassic, but several million years older than the Granite Mountain batholith. Tonalite from the Sheridan Creek stock, south of the Granite Mountain batholith, returns an Early Cretaceous date of 108.57 ±0.18 Ma. The Sheridan Creek contains a foliation with the same orientation and characteristics as a prominent foliation in the southern part of the Granite Mountain batholith, demonstrating that deformation of both is mid-Cretaceous or younger.
CrowdGO: Machine learning and semantic similarity guided consensus Gene Ontology annotation

Background Characterising gene function for the ever-increasing number and diversity of species with annotated genomes relies almost entirely on computational prediction methods. These software are also numerous and diverse, each with different strengths and weaknesses as revealed through community benchmarking efforts. Meta-predictors that assess consensus and conflict from individual algorithms should deliver enhanced functional annotations. Results To exploit the benefits of meta-approaches, we developed CrowdGO, an open-source consensus-based Gene Ontology (GO) term meta-predictor that employs machine learning models with GO term semantic similarities and information contents. By re-evaluating each gene-term annotation, a consensus dataset is produced with high-scoring confident annotations and low-scoring rejected annotations. Applying CrowdGO to results from a deep learning-based, a sequence similarity-based, and two protein domain-based methods, delivers consensus annotations with improved precision and recall. Furthermore, using standard evaluation measures CrowdGO performance matches that of the community’s best performing individual methods. Conclusion CrowdGO offers a model-informed approach to leverage strengths of individual predictors and produce comprehensive and accurate gene functional annotations. Availability and Implementation CrowdGO is implemented in Python3, and is freely available from https://gitlab.com/mreijnders/CrowdGO, with a Snakemake workflow and pre-trained models.
Cerebral biodistribution and real-time particle tracking in vivo of ultrabright fluorescent PLGA nano-carriers

Nanoparticles hold great promise as drug carriers for the central nervous system (CNS), however, knowledge about their biodistribution within the CNS remains fragmentary. To overcome this, we used poly(lactic-co-glycolic acid) (PLGA), a biodegradable polymer approved for the use in humans, to prepare nanocarriers and loaded them with bulky fluorophores. Thereby, we increased single particle fluorescence by up to 55-fold as compared to quantum dots. As a consequence, 70 nm PLGA nanocarriers were visualized by intravital real-time 2-photon microscopy, demonstrating that coating with pluronic F-68 (PF-68) significantly increased the circulation time of PLGA nanoparticles in the blood and facilitated their uptake by cerebral endothelial cells in mice. Using a novel in vivo imaging protocol we unambiguously distinguished, by confocal microscopy, nanoparticles’ fluorescence from tissue auto-fluorescence and demonstrated how PF-68 coated PLGA NPs were taken up into late endothelial lysosomes within 1 hour. In summary, by increasing the brightness of clinically approved PLGA nanocarriers to a level which allowed in vivo detection, we were able to demonstrate that PF-68 shifts the uptake of individual particles from macrophages towards endothelial cells. Our novel technological approach significantly improves the ability to evaluate tissue targeting of nanoscale drugdelivery systems in living organisms, thereby remarkably reducing the gap between their development and clinical translation.
Live-cell single-molecule tracking highlights requirements for stable Smc5/6 chromatin association in vivo

The essential Smc5/6 complex is required in response to replication stress and is best known for ensuring the fidelity of homologous recombination. Using single-molecule tracking in live fission yeast to investigate Smc5/6 chromatin association, we show that Smc5/6 is chromatin associated in unchallenged cells and this depends on the non-SMC protein Nse6. We define a minimum of two Nse6-dependent sub-pathways, one of which requires the BRCT-domain protein Brc1. Using defined mutants in genes encoding the core Smc5/6 complex subunits we show that the Nse3 double-stranded DNA binding activity and the arginine fingers of the two Smc5/6 ATPase binding sites are critical for chromatin association. Interestingly, disrupting the ssDNA binding activity at the hinge region does not prevent chromatin association but leads to elevated levels of gross chromosomal rearrangements during replication restart. This is consistent with a downstream function for ssDNA binding in regulating homologous recombination.
Stereoselective Synthesis of β-Amino Ketones: A Three-Component Mannich-Type Reaction of Aromatic Aldehydes, Anilines, and Cyclohexanone Using Amberlyst-15

Abstract A three-component Mannich-type reaction of aromatic aldehydes, anilines, and cyclohexanone in the presence of Amberlyst-15 affords the corresponding β-amino ketones in good yields at room temperature. The conversion is highly diastereoselective, favoring the formation of anti-isomers.
Ab initio study of nitrogen-multisubstituted neutral and positively charged C20 fullerene

Ab initio investigation of structural and electronic properties of Nitrogen doped fullerenes, obtained from C20 by replacing up to 10 C atoms with N atoms, are studied by means of first principals density functional theory calculations using numerical orbitals as basis sets. We have obtained the ground state structures for C20−nNn for n=1-10. While substituting nitrogen atoms, we cannot substitute more than 9 nitrogen atoms. Nitrogen doping in C20 shows a significant change in density of states. For a better comparison with experimental measurements, we have also considered some positively charged ions and report the differences between properties of these ions and the corresponding neutral molecules.
Nitrate-nitrogen removal with small-scale reverse osmosis, electrodialysis and ion-exchange units in rural areas

The nitrate-nitrogen concentration in water supplied to clinics in Limpopo Province is too high to be fit for human consumption (35 to 75 mg/l NO 3 -N). Therefore, small-scale technologies (reverse osmosis, ion-exchange and electrodialysis) were evaluated for nitrate-nitrogen removal to make the water potable (< 10 mg/l NO3-N). It was found that the reverse osmosis process should function well for nitrate-nitrogen removal. Nitrate-nitrogen could be reduced from a concentration of 35 to 43 mg/l in 1 case to a concentration of between 1.4 and 5.5 mg/l in the treated water. In another case it could be reduced from 54 to 72 mg/l to 12 to 17 mg/l in the treated water. The water was also effectively desalinated. The ionexchange process could also reduce the nitrate-nitrogen concentration to less than 10 mg/l in the treated water. However, the water could not be efficiently desalinated and the process should function better when the level of total dissolved solids in the feed is not very high. The electrodialysis process should also function well for nitrate-nitrogen and salinity removal. However, the electrodialysis process is more complicated to operate. The reverse osmosis and ion-exchange processes are therefore suggested for nitrate-nitrogen removal at clinics. Capital costs for small-scale reverse osmosis and ion-exchange units are estimated at ZAR7 000 and ZAR10 000, respectively. Operational costs for reverse osmosis and ion-exchange are estimated at ZAR3.16/m 3 and ZAR3.60/m 3 of treated water, respectively.
Ionic and carbonaceous compositions of PM 10 , PM 2.5 and PM 1.0 at Gosan ABC Superstation and their ratios as source signature

Abstract. PM1.0, PM2.5, and PM10 were sampled at Gosan ABC Superstation on Jeju Island from August 2007 to September 2008. The carbonaceous aerosols were quantified with the thermal/optical reflectance (TOR) method, which produced five organic carbon (OC) fractions, OC1, OC2, OC3, OC4, and pyrolyzed organic carbon (OP), and three elemental carbon (EC) fractions, EC1, EC2, and EC3. The mean mass concentrations of PM1.0, PM2.5, and PM10 were 13.7 μg m−3, 17.2 μg m−3, and 28.4 μg m−3, respectively. The averaged mass fractions of OC and EC were 23.0% and 10.4% for PM1.0, 22.9% and 9.8% for PM2.5, and 16.4% and 6.0% for PM10. Among the OC and EC sub-components, OC2 and EC2+3 were enriched in the fine mode, but OC3 and OC4 in the coarse mode. The filter-based PM1.0 EC agreed well with black carbon (BC) measured by an Aethalometer, and PM10 EC was higher than BC, implying less light absorption by larger particles. EC was well correlated with sulfate, resulting in good relationships of sulfate with both aerosol scattering coefficient measured by Nephelometer and BC concentration. Our measurements of EC confirmed the definition of EC1 as char-EC emitted from smoldering combustion and EC2+3 as soot-EC generated from higher-temperature combustion such as motor vehicle exhaust and coal combustion (Han et al., 2010). In particular, EC1 was strongly correlated with potassium, a traditional biomass burning indicator, except during the summer, when the ratio of EC1 to EC2+3 was the lowest. We also found the ratios of major chemical species to be a useful tool to constrain the main sources of aerosols, by which the five air masses were well distinguished: Siberia, Beijing, Shanghai, Yellow Sea, and East Sea types. Except Siberian air, the continental background of the study region, Beijing plumes showed the highest EC1 (and OP) to sulfate ratio, which implies that this air mass had the highest net warming by aerosols of the four air masses. Shanghai-type air, which was heavily influenced by southern China, showed the highest sulfate enhancement. The highest EC2+3/EC1 ratio was found in aged East Sea air, demonstrating a significant influence of motor vehicle emissions from South Korea and Japan and less influence from industrial regions of China. The high ratio results from the longer residence time and less sensitivity to wet scavenging of EC2+3 compared to EC1, indicating that soot-EC could have greater consequence in regional-scale warming.
Symmetrical 1,3-Dialkylimidazolium Based Ionic Liquid Crystals

The synthesis and characterization for a series of symmetrical 1,3-dialkylimidazolium salts with different chain lengths and counter anions together with their 1-alkylimidazole precursors are described. Liquid crystal (LC) properties of these salts are studied. Images under polarizing optical microscopy show focal conic texture together with homeotropic domains. A smectic A mesophase, typical for rod-like imidazolium salts, is assigned. Studies from powder X-ray diffraction suggest a lamellar structure with noninterdigitated monolayer arrangement for the LC salts in the mesophase. In addition, a short note on the structure and property relationship for rod-like, disc- or fan-like, and dendritic shaped imidazolium ionic liquid crystals (ImILCs) forming smectic, columnar, and cubic phase is briefly summarized. A comparison of minimum alkyl chain length needed for 1-alkyl-3-methyl and symmetrical 1,3-dialkyl ImILCs to exhibit LC behavior is addressed.