Miracle-dz/UniFAR-FTUs huggingface dataset:
Static and Dynamic Community Detection Methods That Optimize a Specific Objective Function: A Survey and Experimental Evaluation

Most current survey papers classify community detection methods into broad categories and do not draw clear boundaries between the specific techniques employed by these methods. We survey in this paper all fine-grained community detection categories, the clustering methods that fall under these categories, and the techniques employed by these methods for optimizing each objective function. We provide methodology-based taxonomies that classify static and dynamic community detection methods into hierarchically nested, fine-grained, and specific classes. We classify the methods into the objective function they optimize. Each objective function class is classified into clustering categories. Each category is further classified into clustering methods. Methods are further classified into sub-methods and so on. Thus, the lowest subclass in a hierarchy is a fine-grained and specific method. For each method, we survey the different techniques in literature employed by the method. We empirically and experimentally compare and rank the different methods that fall under each clustering category. We also empirically and experimentally compare and rank the different categories that optimize a same objective function. In summary, the block-based, top-down divisive-based, random walk-based, and matrix eigenvector-based methods achieved good results. Finally, we provide fitness metrics for each objective function.
Comparison of the Effectiveness of Different Barrier Enclosure Techniques in Protection of Healthcare Workers During Tracheal Intubation and Extubation

Supplemental Digital Content is available in the text. The coronavirus disease 2019 (COVID-19; SARS-CoV-2) pandemic has created serious challenges to anesthesiologists. As hospitalized patients’ respiratory function deteriorates, many will require endotracheal intubation. Airway management of infected patients risks aerosolization of viral-loaded droplets that pose serious hazards to the anesthesiologist and all health care personnel present. The addition of an enclosure barrier during airway management minimizes the hazard by entrapping the droplets and possibly the aerosols within an enclosed space adding additional protection for health care workers. The aim of this study was to compare the effectiveness of different barrier enclosure techniques during tracheal intubation and extubation.
A Super-Learner Ensemble of Deep Networks for Vehicle-Type Classification

Automatic vehicle-type classification plays an imperative role in the development of efficient Intelligent Transportation Systems (ITS). In this paper, a super-learner ensemble is proposed for the vehicle-type classification problem. A densely connected single-split super learner is utilized to exploit the strengths and diminish the weaknesses of the individual base learners ResNet50, Xception, and DenseNet. The super learner aims to learn fusion weights in a data-adaptive manner to obtain the optimal combination of the base learners. The proposed method is simple, robust, and enhances the discrimination capabilities among the similarly-looking classes without requiring any hand-crafted features or logical reasoning. The proposed method is evaluated using two of the most challenging publicly available traffic surveillance datasets: the MIOvision Traffic Camera Dataset (MIO-TCD) and the Beijing Institute of Technology’s (BIT) vehicle classification dataset. Three variants of the super learner ensemble: RXD-CV-CW, RXD-CV-CW-NCW and Augmented-RXD, were examined on the MIO-TCD dataset with variations in applying class weights and data augmentation during training. RXD-CV-CW-NCW and Augmented-RXD share the third place among the published state-of-the-art methods reported in the MIO-TCD classification challenge. Augmented-RXD generalizes to the classes in common between the two datasets without degrading its performance on the MIO-TCD dataset. Both variants achieved an overall accuracy of 97.94%, and a Cohen Kappa score of 96.78%. In addition, the super-learner variants that we trained on the BIT-Vehicle dataset images achieved overall accuracies of up to 97.62%.
5′ modifications to CRISPR–Cas9 gRNA can change the dynamics and size of R-loops and inhibit DNA cleavage

Abstract A key aim in exploiting CRISPR–Cas is gRNA engineering to introduce additional functionalities, ranging from individual nucleotide changes that increase efficiency of on-target binding to the inclusion of larger functional RNA aptamers or ribonucleoproteins (RNPs). Cas9–gRNA interactions are crucial for complex assembly, but several distinct regions of the gRNA are amenable to modification. We used in vitro ensemble and single-molecule assays to assess the impact of gRNA structural alterations on RNP complex formation, R-loop dynamics, and endonuclease activity. Our results indicate that RNP formation was unaffected by any of our modifications. R-loop formation and DNA cleavage activity were also essentially unaffected by modification of the Upper Stem, first Hairpin and 3′ end. In contrast, we found that 5′ additions of only two or three nucleotides could reduce R-loop formation and cleavage activity of the RuvC domain relative to a single nucleotide addition. Such modifications are a common by-product of in vitro transcribed gRNA. We also observed that addition of a 20 nt RNA hairpin to the 5′ end of a gRNA still supported RNP formation but produced a stable ∼9 bp R-loop that could not activate DNA cleavage. Consideration of these observations will assist in successful gRNA design.
Artificial Intelligence based analysis of fundus images of retina to screen for diabetic retinopathy and cataract: A pilot study in North India

- Introduction: Fundus examination is the first and foremost step in the diagnosis of vision conditions like diabetic retinopathy, cataract, corneal opacity and vitreous infection. But the fundus examination requires considerable experience and is subject to human errors. Artificial intelligence (AI) based analysis of fundus images of retina can be an answer to this problem. AI can be used even in the remotest areas where expert ophthalmologists are not available. Sevamob provides artificial intelligence enabled healthcare platform to organizations. It uses deep learning for image recognition, machine learning for triaging and computer vision for object counting. AI models of various medical conditions are first trained in the software from anonymized image data procured from various sources. To determine the accuracy of AI based point-of-care screening solution for fundus images of retina, an android smartphone / tablet with Sevamob app and a low end fundus camera were used. The system was operated by a nurse or a technician with minimal training Methods: Fundus images of retina from clinically suspected diabetic retinopathy ,cataract, corneal opacity, vitreous infection and membrane hemorrhage were included in the study. Results:
Analysis of Technological and Consumption Quality of Offal and Offal Products Obtained from Pulawska and Polish Landrace Pigs

Simple Summary In many countries, offal is an important culinary and technological raw material used for the production of offal dishes and products. Given the growing popularity of such products, as well as insufficient knowledge about the technological and nutritional value of offal, it is important to determine the properties of some pork offal and offal products. The study material consisted of 100 fattening pigs: 50 Pulawska pigs and 50 Polish Landrace pigs. The offal components (tongue, heart, lungs, liver, kidneys) were analysed for physical traits, basic chemical composition and energy value. Offal products (pate, liver sausage, brawn) were made from the offal and their physical, chemical and organoleptic parameters were evaluated. The results, obtained in our study, indicate a high technological and consumption quality of offal from Pulawska and Polish Landrace pigs. The organoleptic quality of the evaluated offal products was higher for Pulawska than Polish Landrace pigs, in particular with regard to aroma and flavour. We suggest that our study could influence consumer awareness of the consumption of pork offal and offal preparations while increasing the use for production of the Pulawska breed, and thus, other native breed characteristic of many other countries of the world. Abstract The aim of the study was to determine technological and consumption quality of some offal components obtained from Pulawska and Polish Landrace fattening pigs, and to analyse the eating quality of the offal products. The study material consisted of 100 fattening pigs: Pulawska (PUL) and 50 Polish Landrace (PL) pigs. The offal components were analysed for physical traits, chemical composition and energy value. Offal products were made from the offal and their physical, chemical and organoleptic parameters were evaluated. Our study showed that breed had a significant effect (p ≤ 0.05) on pH45 of the tongue, heart (PUL > PL), lungs and kidneys (PUL < PL), and on the fat content of the tongue, heart (PUL > PL), liver and kidneys (PUL < PL). A highly significant effect of breed (p ≤ 0.01) was observed for protein content of the lungs, liver (PUL < PL) and kidneys (PUL > PL), for collagen content of the kidneys (PUL < PL) and liver (PUL < PL), and for energy value (p ≤ 0.01) of the heart (PUL > PL) and liver (PUL < PL). Moreover, our results indicate that the organoleptic quality of the evaluated offal products was higher for Pulawska than Polish Landrace pigs, in particular with regard to consistency (p < 0.05) and flavour (p < 0.01) of the liver sausage.
The influence of nitrogen fertilisation on quantities and proportions of different protein types in wheat flour

The flours of 13 wheat varieties grown at different levels of nitrogen fertilisation were characterised by the quantitative determination of flour protein groups and gluten protein types using a combined extraction/HPLC procedure. The results demonstrate that the quantities of albumins and globulins were scarcely influenced by different nitrogen fertilisation, whereas those of gluten proteins (gliadins, glutenins) were strongly influenced. The effect on gliadins was more pronounced than on glutenins, as well as the effect on major protein types (α-gliadins, γ-gliadins, LMW subunits of glutenin) in comparison with minor types (ω-gliadins, HMW subunits of glutenin). The proportions of hydrophilic proteins (ω-gliadins, HMW subunits of glutenin) were increased by high levels of nitrogen and those of hydrophobic proteins (γ-gliadin, LMW subunits of glutenin) were decreased. The degree of the effects on both quantities and proportions of flour protein groups and gluten protein types was strongly dependent on the variety. © 1998 SCI.
Analysis of real-time particulate matter (PM2.5) concentrations in Washington, DC, using generalized additive models (GAMs)

The objective of this paper is to report the results of a generalized additive model used to predict local particulate matter concentrations at a Washington, DC Department of Energy and Environment (DOEE) federal regulatory monitoring station. While the DOEE uses state-of-the-art federal equivalent method (FEM) equipment to demonstrate compliance with the clean air act for regulatory purposes, these measurements reflect regional, not neighborhood air quality. A GW student-led living lab project—Fresh Air DC—has been testing uRAD INDUSTRIAL low-cost air quality sensors that can be used to collect air quality data at the neighborhood level using LoRaWAN based smart city technology. Because low-cost sensors often lack the accuracy and sensitivity of FEM equipment, research indicates that low-cost sensor (LCS) monitoring networks require post- processing and data modelling in order to apply findings to educational and policy goals. Although LCS data processing has been conducted using linear and nonlinear models, nonlinear models tend to have a greater ability to capture the nuanced relationships between air pollutants and meteorological influences. In this paper, we post-process uRAD PM 2.5 sensor data using DOEE FEM equipment as a reference instrument in the development of three models to adjust uRAD data to the DOEE FEM data—ordinary least squares linear regression, generalized linear models (GLMs), and generalized additive models (GAMs). Our model includes meteorological variables such as temperature, humidity, and wind speed. Our statistical models for post-processing are evaluated on the basis of deviance and Akaike Information Criterion (AIC). We expect that the GLM and GAM will be useful for capturing nonlinear relationships between the PM2.5 measurements and meteorological variables.
MILP-Based Differential Cryptanalysis on Round-Reduced Midori64

Mixed integer linear programming (MILP) model was presented by Sun <italic>et al.</italic> at Asiacrypt 2014 to search for differential characteristics of block ciphers. Based on this model, it is easy to assess block ciphers against differential attack. In this paper, the MILP model is improved to search for differential trails of Midori64 which is a family of lightweight block ciphers provided by Banik <italic>et al.</italic> at Asiacrypt 2015. We find the best 5-round differential characteristics of Midori64 with MILP-based model, and the probabilities are <inline-formula> <tex-math notation="LaTeX">$2^{-52}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$2^{-58}$ </tex-math></inline-formula> respectively. Based on these distinguishers, we give key recovery attacks on the 11-round reduced Midori64 with data complexities of <inline-formula> <tex-math notation="LaTeX">$2^{55.6}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$2^{61.2}$ </tex-math></inline-formula>, and time complexities of <inline-formula> <tex-math notation="LaTeX">$2^{109.35}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$2^{100.26}$ </tex-math></inline-formula>.
A Bibliography of the Invasive Alga Sargassum muticum (Yendo) Fensholt (Fucales; Sargassaceae)

A compilation of approximately three hundred publications concerning the brown alga Sargassum mulicum (Yendo) Fensholt is given. This seaweed has attracted considerable attention amongst the phycological fraternity, because of recent large-scale changes in its geographical distribution and feared consequences of the alga's presence in invaded habitats.
Placental Myeloid Cells Protect against Zika Virus Vertical Transmission in a Rag1-Deficient Mouse Model

Key Points Maternal myeloid cells are recruited to the placenta during ZIKV infection. Maternal but not fetal myeloid cells inhibit vertical transmission of ZIKV. Myeloid cells do not contribute to maintenance of the placental barrier. The ability of Zika virus (ZIKV) to cross the placenta and infect the fetus is a key mechanism by which ZIKV causes microcephaly. How the virus crosses the placenta and the role of the immune response in this process remain unclear. In the current study, we examined how ZIKV infection affected innate immune cells within the placenta and fetus and whether these cells influenced virus vertical transmission (VTx). We found myeloid cells were elevated in the placenta of pregnant ZIKV-infected Rag1−/− mice treated with an anti-IFNAR Ab, primarily at the end of pregnancy as well as transiently in the fetus several days before birth. These cells, which included maternal monocyte/macrophages, neutrophils, and fetal myeloid cells contained viral RNA and infectious virus, suggesting they may be infected and contributing to viral replication and VTx. However, depletion of monocyte/macrophage myeloid cells from the dam during ZIKV infection resulted in increased ZIKV infection in the fetus. Myeloid cells in the fetus were not depleted in this experiment, likely because of an inability of liposome particles containing the cytotoxic drug to cross the placenta. Thus, the increased virus infection in the fetus was not the result of an impaired fetal myeloid response or breakdown of the placental barrier. Collectively, these data suggest that monocyte/macrophage myeloid cells in the placenta play a significant role in inhibiting ZIKV VTx to the fetus, possibly through phagocytosis of virus or virus-infected cells.
An Interactive Image Editing System Using an Uncertainty-Based Confirmation Strategy

We propose an interactive image editing system that has a confirmation dialogue strategy using an entropy-based uncertainty calculation on its generated images with Deep Convolutional Generative Adversarial Networks (DCGAN). DCGAN is an image generative model that learns an image manifold of a given dataset and enables continuous change of an image. Our proposed image editing system combines DCGAN with a natural language interface that accepts image editing requests in natural language. Although such a system is helpful for human users, it often faces uncertain requests to generate acceptable images. A promising approach to solve this problem is introducing a dialogue process that shows multiple candidates and confirms the user’s intention. However, confirming every editing request creates redundant dialogues. To achieve more efficient dialogues, we propose an entropy-based dialogue strategy that decides when the system should confirm, and enables effective image editing through a dialogue that reduces redundant confirmations. We conducted image editing dialogue experiments using an avatar face illustration dataset for editing by natural language requests. Through quantitative and qualitative analysis, our results show that our entropy-based confirmation strategy achieved an effective dialogue by generating images desired by users.
Radiocarbon dating and microarchaeology untangle the history of Jerusalem's Temple Mount: A view from Wilson's Arch

Radiocarbon dating is rarely applied in Classical and Post-Classical periods in the Eastern Mediterranean, as it is not considered precise enough to solve specific chronological questions, often causing the attribution of historic monuments to be based on circumstantial evidence. This research, applied in Jerusalem, presents a novel approach to solve this problem. Integrating fieldwork, stratigraphy, and microarchaeology analyses with intense radiocarbon dating of charred remains in building materials beneath Wilson's Arch, we absolutely dated monumental structures to very narrow windows of time–even to specific rulers. Wilson’s Arch was initiated by Herod the Great and enlarged during the Roman Procurators, such as Pontius Pilatus, in a range of 70 years, rather than 700 years, as previously discussed by scholars. The theater-like structure is dated to the days of Emperor Hadrian and left unfinished before 132–136 AD. Through this approach, it is possible to solve archaeological riddles in intensely urban environments in the historical periods.
The use of alkaline EDTA solution improves heat-induced epitope retrieval for immunohistochemical localization of MIB-1 antigen

This study was carried out to show whether the removal of tissue-bound calcium ions during a heat-induced epitope retrieval (HIER) procedure improved immunohistochemical staining of the tissues. In addition, the proteolytic susceptibilities of the fixed tissues before and after various epitope retrieval procedures were also evaluated. Immuno-histochemical staining for MIB-1 antigen from paraffin-embedded cases of tonsillitis, gastric adenocarcinomas, and breast carcinomas was performed following heat-treatments for 1, 2, 3, and 5 min in the presence of various buffers such as 0.01 M citrate buffer (pH 6.0), 0.1 M Tris-HCI buffer (pH 8.0), and 1 mM EDTA-NaOH solution (pH 8.0), each of which has different calcium chelating capabilities. In addition, the immuno-histochemical staining was performed following 0.05% and 0.1% trypsinizations of the tissues before and after the epitope retrieval. The trypsin-treated tissues were also analyzed with sodium dodecylsulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The immunohistochemical staining of MIB-1 was most prominent when 1 mM EDTA solution (pH 8.0) was employed during HIER. Although trypsin digestion of the tissues before and after HIER generally increased the staining intensity, the cellular morphology of the background was poorly preserved. In addition, no significant differences were observed with gel electrophoresis of the trypsin digested tissues prepared in the various epitope retrieval solutions. Taken together, it can be suggested that the EDTA solution is more effective than other buffers in exposing epitopes presumably by removing tissue-bound calcium ions. Also, an additional trypsin treatment is not necessary even before and after the HIER as long as the EDTA solution is used.
Empirical Study about Class Change Proneness Prediction using Software Metrics and Code Smells

: During the lifecycle of software, maintenance has been considered one of the most complex and costly phases in terms of resources and costs. In addition, software evolves in response to the needs and demands of the ever-changing world and thus becomes increasingly complex. In this scenario, an approach that has been widely used to rationalize resources and costs during the evolution of object-oriented software is to predict change-prone classes. A change-prone class may indicate a part of poor quality of software that needs to be refactored. Recently, some strategies for predicting change-prone classes, which are based on the use of software metrics and code smells, have been proposed. In this paper, we present an empirical study on the performance of 8 machine learning techniques used to predict classes prone to change. Three different training scenarios were investigated: object-oriented metrics, code smells, and object-oriented metrics and code smells combined. To perform the experiments, we built a data set containing eight object-oriented metrics and 32 types of code smells, which were extracted from the source code of a web application that was developed between 2013 and 2018 over eight releases. The machine learning algorithms that presented the best results were: RF, LGBM, and LR. The training scenario that presented the best results was the combination of code smells and object-oriented metrics.
Sugar Preferences and Digestion by Cape White-Eyes, Zosterops virens, Fed Artificial Fruit Diets

Sugar preferences and digestion of sugars in artificial fruit of different sugar types and concentrations were investigated in a South African facultative frugivore, the Cape white-eye (Zosterops virens). We studied sugar preferences, daily food and energy intake, and digestive efficiencies and transit times with birds that were fed artificial fruit diets comprising 6.6, 12.4 and 22% glucose and sucrose, respectively. Digestive transit rates of birds fed artificial fruit diets were faster for glucose compared with sucrose diets, irrespective of concentration. Birds showed increased food intake with decreasing glucose concentration, but showed no significant differences in these intake amounts with differing sucrose concentrations. Apparent assimilation efficiencies were lower than most nectar studies, and were generally higher for glucose fruit (79.3–85.6%) compared with sucrose fruit (69.0–78.4%). In choice tests, birds preferred sucrose over glucose of equivalent weight, irrespective of concentration. It appears likely that the Cape white-eye has high levels of sucrase activity, although further study is needed to verify this.