Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Multi-modal Representations of Narrative Multimedia: a Case Study of Webtoons

This study aims to learn task-agnostic representations of narrative multimedia. The existing studies focused on only stories in the narrative multimedia without considering their physical features. We propose a method for incorporating multi-modal features of the narrative multimedia into a unified vector representation. For narrative features, we embed character networks as with the existing studies. Textual features can be represented using the LSTM (Long-Short Term Memory) autoencoder. We apply the convolutional autoencoder to visual features. The convolutional autoencoder also can be used for the spectrograms of audible features. To combine these features, we propose two methods: early fusion and late fusion. The early fusion method composes representations of features on each scene. Then, we learn representations of a narrative work by predicting time-sequential changes in the features. The late fusion method concatenates feature vectors that are trained for allover the narrative work. Finally, we apply the proposed methods on webtoons (i.e., comics that are serially published through the web). The proposed methods have been evaluated by applying the vector representations to predicting the preferences of users for the webtoons.
Role of Space Weather in Determining the State of the Ionosphere

The influence of space weather on the state of the ionosphere is most pronounced during disturbances. In the present paper, this effect is estimated from changes of the total electron content TEC and the critical frequency foF2. For the study, March 2012 was selected, which includes two periods: March 7-17 and March 21-31. The first period includes four strong magnetic storms and is well documented in the literature in terms of the behavior of solar and geomagnetic parameters. The second period is characterized by an increase in TEC over almost the entire period. Latitudinal variations of TEC in the range 30° - 80° N near the meridian of 15° E and their correlation coefficients with solar and geomagnetic parameters are obtained. Using vertical sounding data (foF2) for four European stations near the selected meridian, the latitudinal dependence of the equivalent slab thickness of the ionosphere was constructed over the entire range. This dependence made it possible to obtain the latitudinal response of the frequency foF2 on disturbances and to reveal features such as the transition from the zone of negative disturbances at high latitudes to positive disturbances at low latitudes in the first period, daily excess over the median in the second period. This response was compared with frequency behavior for the International Reference Ionosphere model IRI. It was shown that the IRI model does not adequately reflect the variation of foF2 during disturbances, however, an assessment of the latitudinal dependence of the accuracy of the model, when compared with the median, showed that the model provides results for the high-latitude region at level of the middle-latitude values with a decrease in accuracy with decreasing latitude.
Orally Administered Antibiotics Vancomycin and Ampicillin Cause Cognitive Impairment With Gut Dysbiosis in Mice With Transient Global Forebrain Ischemia

Gut microbiota is closely associated with the occurrence of neuropsychiatric disorders. Antibiotics are frequently used to prevent pathogen infection in patients with brain ischemia. To understand the impact of prophylactic antibiotic treatment for patients with brain ischemia, we examined the effects of orally administered vancomycin and ampicillin on cognitive function and gut microbiota composition in mice with transient global forebrain ischemia (tIsc). tIsc operation and orally gavaged vancomycin mildly and moderately caused cognitive impairment, respectively. However, the exposure of mice with tIsc to vancomycin or ampicillin severely impaired cognitive function in the Y-maze, novel object recognition, and Banes maze tasks. Furthermore, their treatments induced NF-κB activation as well as active microglia (NF-κB+/Iba1+ and LPS+/Iba1+ cells) and apoptotic (caspase 3+/NeuN+) cell population in the hippocampus, whereas the brain-derived neurotrophic factor (BDNF)+/NeuN+ cell populations decreased. These treatments also caused colitis and gut dysbiosis. They increased the population of Proteobacteria including Enterobacter xiangfangenesis. Orally delivered fecal transplantation of vancomycin-treated mice with or without tIsc and oral gavage of Enterobacter xiangfangenesis also significantly deteriorated the cognitive impairment and colitis in transplanted mice with tIsc. These findings suggest that oral administration of antibiotics can deteriorate cognitive impairment with gut dysbiosis in patients with brain ischemia.
Mapping Study on Constraint Consistency Checking in Distributed Enterprise Systems

Constraint consistency errors in distributed systems can lead to fatal consequences when left unobserved and undetected. The primary goal of quality engineers should be to avoid system inconsistencies in general. However, it is typically a much more straight forward process in monolith-like systems with one codebase than in distributed solutions where heterogeneity occurs across modules. In this paper, we raise the research question of what is the existing state-of-the-art and research literature practice when it comes to consistency checking in distributed systems. We conducted a systematic search for existing work and assess the evidence to categorize the approaches and to identify used techniques. Identified works offer interesting directions and achievements. Often the works share tool prototypes and instruments to build on the top of when performing further research in this direction and we share them in this paper. Finally, we discuss open challenges and gaps in this field to promote the interest of the research audience.
On Matching Log Analysis to Source Code: A Systematic Mapping Study

Logging is a vital part of the software development process. Developers use program logging to monitor program execution and identify errors and anomalies. These errors may also cause uncaught exceptions and generate stack traces that help identify the point of error. Both of these sources contain information that can be matched to points in the source code, but manual log analysis is challenging for large systems that create large volumes of logs and have large codebases. In this paper, we contribute a systematic mapping study to determine the state-of-the-art tools and methods used to perform automatic log analysis and stack trace analysis and match the extracted information back to the program's source code. We analyzed 16 publications that address this issue, summarizing their strategies and goals, and we identified open research directions from this body of work.
Failure Prediction by Utilizing Log Analysis: A Systematic Mapping Study

In modern computing, log files provide a wealth of information regarding the past of a system, including the system failures and security breaches that cost companies and developers a fortune in both time and money. While this information can be used to attempt to recover from a problem, such an approach merely mitigates the damage that has already been done. Detecting problems, however, is not the only information that can be gathered from log files. It is common knowledge that segments of log files, if analyzed correctly, can yield a good idea of what the system is likely going to do next in real-time, allowing a system to take corrective action before any negative actions occur. In this paper, the authors put forth a systematic map of this field of log prediction, screening several hundred papers and finally narrowing down the field to approximately 30 relevant papers. These papers, when broken down, give a good idea of the state of the art, methodologies employed, and future challenges that still must be overcome. Findings and conclusions of this study can be applied to a variety of software systems and components, including classical software systems, as well as software parts of control, or the Internet of Things (IoT) systems.
Testing the Process Dissociation Procedure by Behavioral and Neuroimaging Data: The Establishment of the Mutually Exclusive Theory and the Improved PDP

The process dissociation procedure (PDP) of implicit sequence learning states that the correct inclusion-task response contains the incorrect exclusion-task response. However, there has been no research to test the hypothesis. The current study used a single variable (Stimulus Onset Asynchrony SOA: 850 ms vs. 1350 ms) between-subjects design, with pre-task resting-state fMRI, to test and improve the classical PDP to the mutually exclusive theory (MET). (1) Behavioral data and neuroimaging data demonstrated that the classical PDP has not been validated. In the SOA = 850 ms group, the correct inclusion-task response was at chance, but the incorrect exclusion-task response occurred greater than chance. In the SOA = 850 ms group, the two responses were not correlated, but in the SOA = 1,350 ms group and putting the two groups together, the two responses were in contrast to each other. In each group, brain areas whose amplitude of low frequency fluctuations (ALFFs) in the resting-state related to the two responses were either completely different or opposite to one another. However, the results were perfectly consistent with the MET proposed by the present study which suggests that the correct inclusion-task response is equal to the correct exclusion-task response is equal to C + A1, and the incorrect exclusion-task response is equal to A2. C denotes the controlled response and A1 and A2 denote two different automatic responses. (2) The improved PDP was proposed to categorize the 12 kinds of triplets as delineating four knowledge types, namely non-acquisition of knowledge, uncontrollable knowledge, half-controllable knowledge, and controllable knowledge with the MET. ALFFs in the resting-state could predict the four knowledge types of the improved PDP among two groups. The participants’ control of the four knowledge types (degree of consciousness) gradually improved. Correspondingly, the brain areas in the resting-state positively related to the four knowledge types, gradually changed from the sensory and motor network to the somatic sensorimotor network, and then to the implicit learning network, and then to the consciousness network. The brain areas in the resting-state negatively related to the four knowledge types gradually changed from the consciousness network to the sensory and motor network. As SOA increased, the brain areas associated with almost all the four knowledge types changed. (3) The inhomogeneous hypothesis of the MET is best suited to interpret behavioral and neuroimaging data; it states that the same components among the four knowledge types are not homogeneous, and the same knowledge types are not homogeneous between the two SOA groups.
PerfNet: Platform-Aware Performance Modeling for Deep Neural Networks

The technology of deep learning has grown rapidly and been widely used in the industry. In addition to the accuracy of the deep learning (DL) models, system developers are also interested in comprehending their performance aspects to make sure that the hardware design and the systems deployed to meet the application demands. However, developing a performance model to serve the aforementioned purpose needs to take many issues into account, e.g. the DL model, the runtime software, and the system architecture, which is quite complex. In this work, we propose a multi-layer regression network, called PerfNet, to predict the performance of DL models on heterogeneous systems. To train the PerfNet, we develop a tool to collect the performance features and characteristics of DL models on a set of heterogeneous systems, including key hyper-parameters such as loss functions, network shapes, and dataset size, as well as the hardware specifications. Our experiments show that the results of our approach are more accurate than previously published methods. In the case of VGG16 on GTX1080Ti, PerfNet yields a mean absolute percentage error of 20%, while the referenced work constantly overestimates with errors larger than 200%.
Metal Poisoning in Fish

INTRODUCTION. INTRODUCTION. CHEMICAL AND PHYSICAL PROPERTIES OF ELEMENTS CONSIDERED. TERMINOLOGY OF METAL POISONING. SUMMARY. REFERENCES. SELENIUM. INTRODUCTION. ENVIRONMENTAL EXPOSURES. GENERAL TOXICOLOGY. REPRODUCTIVE TOXICITY. ACCUMULATION. BIOLOGICAL EFFECTS. Hematology. Histopathology. Other Alterations. SUMMARY. REFERENCES. ARSENIC. INTRODUCTION. ENVIRONMENTAL EXPOSURES. TOXICITY. ACCUMULATION AND RETENTION. HISTOPATHOLOGY. Arsenic-Inclusions. Necrotic and Fibrous Bodies. Hemosiderin Granules. Myelin Figures. SUMMARY. REFERENCES. LEAD. INTRODUCTION. ENVIRONMENTAL EXPOSURES. TOXICITY. ACCUMULATION AND DISTRIBUTION. BIOLOGICAL EFFECTS. Hematological Alterations. Respiratory Changes. Neuronal and Muscular Abnormalities. Behavioral Changes. Additional Effects. SUMMARY. REFERENCES. ZINC. INTRODUCTION. ENVIRONMENTAL EXPOSURES. TOXICITY. In Vivo Studies. In Vitro Studies. ACCUMULATION AND DISTRIBUTION. RETENTION. BIOLOGICAL EFFECTS. Behavioral Changes. Physiological Alterations. Histopathology. Enzymatic Alterations. Protective Mechanisms. SUMMARY. REFERENCES. CADMIUM. INTRODUCTION. ENVIRONMENTAL EXPOSURES. TOXICITY. ACCUMULATION AND TISSUE DISTRIBUTION. ELIMINATION. BIOLOGICAL EFFECTS. Vertebral Alterations. Respiratory Changes. Histopathology. Reproductive Effects. Hematology. Plasma Changes. Enzymatic Effects. Protective Mechanisms. SUMMARY. REFERENCES. COPPER. INTRODUCTION. TOXICITY. ACCUMULATION. BIOLOGICAL EFFECTS. Histopathology. Hematology. Behavior. Physiology. Reproduction. SUMMARY. REFERENCES. MERCURY. INTRODUCTION. ENVIRONMENTAL EXPOSURES. Methylation. Contamination Sites. TOXICITY. General Information. Reproductive Toxicity. ACCUMULATION AND RETENTION. Mucous Production. Demethylation. Temperature. Exposure Level and Time. Source. Chemical Form. Life Stage. BIOLOGICAL EFFECTS. Histopathology. Hematology. Behavior. SUMMARY. REFERENCES. INTERACTIONS. INTRODUCTION. EVALUATION OF THE TOXICITY OF A MIXTURE. TOXICITY OF SPECIFIC MIXTURES OF ELEMENTS. Copper and Zinc. Copper and Mercury. Copper and Methylmercury. Copper, Zinc, and Nickel. Selenium and Mercury. ACCUMULATION OF ELEMENTS FROM MIXTURES. Copper, Zinc, Mercury, Iron, and Manganese. Selenium and Mercury. Selenium, Mercury, Zinc, and Iron. SUMMARY. REFERENCES. APPENDIX I: EPA WATER QUALITY CRITERIA SUMMARY FOR PRIORITY POLLUTANTS. INDEX
Introduction to Coordination Chemistry

Preface Preamble 1 The Central Atom 1.1 Key Concepts in Coordination Chemistry 1.2 A Who's Who of Metal Ions 1.3 Metals in Molecules 1.4 The Road Ahead Concept Keys Further Reading 2 Ligands 2.1 Membership: Being a Ligand 2.2 Monodentate Ligands - The Simple Type 2.3 Greed is Good - Polydentate Ligands 2.4 Polynucleating Species - Molecular Bigamists 2.5 A Separate Race - Organometallic Species Concept Keys Further Reading 3 Complexes 3.1 The Central Metal Ion 3.2 Metal-Ligand Marriage 3.3 Holding On - The Nature of Bonding in Metal Complexes 3.4 Coupling - Polymetallic Complexes 3.5 Making Choices 3.6 Complexation Consequences Concept Keys Further Reading 4 Shape 4.1 Getting in Shape 4.2 Forms of Complex Life 4.3 Influencing Shape 4.4 Isomerism - Real 3D Effects 4.5 Sophisticated Shapes 4.6 Defining Shape Concept Keys Further Reading 5 Stability 5.1 The Makings of a Stable Relationship 5.2 Complexation - Will it Last? 5.3 Reactions Concept Keys Further Reading 6 Synthesis 6.1 Molecular Creation - Ways to Make Complexes 6.2 Core Metal Chemistry - Periodic Table Influences 6.3 Reactions Involving the Coordination Shell 6.4 Reactions Involving the Metal Oxidation State 6.5 Reactions Involving Coordinated 6.6 Organometallic Synthesis Concept Keys Further Reading 7 Properties 7.1 Finding Ways to Make Complexes Talk - Investigative Methods 7.2 Getting Physical - Methods and Outcomes 7.3 Probing the Life of Complexes - Using Physical Methods Concept Keys Further Reading 8 A Complex Life 8.1 Life's a Metal Ion 8.2 Metalloproteins and Metalloenzymes 8.3 Doing What Comes Unnaturally 8.4 A Laboratory-free Approach - In Silico Prediction Concept Keys Further Reading 9 Complexes and Commerce 9.1 Kill or Cure? - Complexes as Drugs 9.2 How Much? - Analysing with Complexes 9.3 Profiting from Complexation 9.4 Being Green 9.5 Complex Futures Concept Keys Further Reading Appendix One Nomenclature Appendix Two Molecular Symmetry: The Point Group Index
Early Screening and Risk Factors of Autism Spectrum Disorder in a Large Cohort of Chinese Patients With Prader-Willi Syndrome

Previous studies regarding the prevalence of Autism Spectrum Disorder (ASD) in patients with Prader-Willi Syndrome (PWS) have implicated heterogenous findings. Additionally, the early screening of ASD high-risk population for ASD and identifying ASD risk factors in PWS patients have not been explored. This study included 218 Chinese PWS patients aged 3 months to 18 years old. 78% of subjects were identified as high risk for ASD by ASQ-3 Communication domain score for those younger than 3 years of age and 84% of subjects were classified as high risk for ASD by the GARS-3 for those aged 3 years and older. Among PWS clinical measurements, under-height (P = 0.0186), overweight (P = 0.0248), and obstructive sleep apnea (P = 0.0259) were each significantly correlated with ASD risk. These risk factors and their internal relationship with ASD or ASD traits warrant further studies.
Evaluation of Quality and Acceptability of Snack (Kokoro) Produced From Synthetic Provitamin A Maize (Zea mays) Genotypes

Kokoro from provitamin A (PVA) maize genotypes, produced through conventional breeding, was studied to improve the indigenous white maize-based snack deficient in provitamin A carotenoid commonly consumed in South-western Nigeria. The chemical composition, carotenoid retention, and acceptability of Kokoro from three PVA maize genotypes and one landrace yellow maize variety (control) were estimated. Chemical composition showed significant differences (p < 0.05) in parameters with high crude fat content (23.21–32.11%). The sensory evaluation result revealed that Kokoro from DT STR SYN2-Y (control) was the most acceptable, while among the PVA Kokoro, PVA SYN HGBC1 was acceptable. The pre-processing for the estimated carotenoids (μg g−1); lutein, zeaxanthin, total β-carotene, and PVA in maize genotypes ranged from 10.38 to 12.87, 6.03 to 10.97, 3.83 to 6.18, and 5.96 to 8.43, while after processing to Kokoro, total β-carotene ranged from 1.47 to 3.10 μg g−1 and total PVA content 2.43–4.00 μg g−1. The carotenoid retention in Kokoro from PVA maize genotypes ranged from zeaxanthin 5.89–8.39%; lutein 2.74–4.45%; total β-carotene 38.24–66.14%, and total PVA 37.98–67.05%. Degradation of carotenoid was observed due to the unit operations in the processing method that led to the exposure of the food matrix to direct sunlight, heat, light, metals, and oxygen resulting in the formation of cis-isomers and loss of provitamin A quantity. The maize genotype PVASYNHGBC0 had the highest PVA value and carotenoid retention after processing. The study observed that PVA retention of Kokoro was genotype-dependent, and genotype PVASYNHGBC0 (Provitamin A maize HGA cycle zero) retained the highest carotenoid content. Also, PVASYNHGBC0 (for all the servings' size; 100 and 150 g) in all age groups had the highest percentage contribution of vitamin A to the recommended daily allowance. However, further improvement in the carotenoid content of maize genotypes is needed to enable the production of nutritious Kokoro with higher vitamin A percentage contribution and retinol equivalent.
Free Rather Than Total Iron Content Is Critically Linked to the Fur Physiology in Shewanella oneidensis

Ferric uptake regulator (Fur) is a transcriptional regulator playing a central role in iron homeostasis of many bacteria, and Fur inactivation commonly results in pleiotropic phenotypes. In Shewanella oneidensis, a representative of dissimilatory metal-reducing γ-proteobacteria capable of respiring a variety of chemicals as electron acceptors (EAs), Fur loss substantially impairs respiration. However, to date the mechanism underlying the physiological phenomenon remains obscure. This investigation reveals that Fur loss compromises activity of iron proteins requiring biosynthetic processes for their iron cofactors, heme in particular. We then show that S. oneidensis Fur is critical for maintaining heme homeostasis by affecting both its biosynthesis and decomposition of the molecule. Intriguingly, the abundance of iron-containing proteins controlled by H2O2-responding regulator OxyR increases in the fur mutant because the Fur loss activates OxyR. By comparing suppression of membrane-impermeable, membrane-permeable, and intracellular-only iron chelators on heme deficiency and elevated H2O2 resistance, our data suggest that the elevation of the free iron content by the Fur loss is likely to be the predominant factor for the Fur physiology. Overall, these results provide circumstantial evidence that Fur inactivation disturbs bacterial iron homeostasis by altering transcription of its regulon members, through which many physiological processes, such as respiration and oxidative stress response, are transformed.
Emerging Roles of Exosomes in T1DM

Type 1 diabetes mellitus (T1DM) is a complex autoimmune disorder that mainly affects children and adolescents. The elevated blood glucose level of patients with T1DM results from absolute insulin deficiency and leads to hyperglycemia and the development of life-threatening diabetic complications. Although great efforts have been made to elucidate the pathogenesis of this disease, the precise underlying mechanisms are still obscure. Emerging evidence indicates that small extracellular vesicles, namely, exosomes, take part in intercellular communication and regulate interorgan crosstalk. More importantly, many findings suggest that exosomes and their cargo are associated with the development of T1DM. Therefore, a deeper understanding of exosomes is beneficial for further elucidating the pathogenic process of T1DM. Exosomes are promising biomarkers for evaluating the risk of developingty T1DM, monitoring the disease state and predicting related complications because their number and composition can reflect the status of their parent cells. Additionally, since exosomes are natural carriers of functional proteins, RNA and DNA, they can be used as therapeutic tools to deliver these molecules and drugs. In this review, we briefly introduce the current understanding of exosomes. Next, we focus on the relationship between exosomes and T1DM from three perspectives, i.e., the pathogenic role of exosomes in T1DM, exosomes as novel biomarkers of T1DM and exosomes as therapeutic tools for T1DM.