Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing the hate and counter speech accounts on Twitter

The online hate speech is proliferating with several organization and countries implementing laws to ban such harmful speech. While these restrictions might reduce the amount of such hateful content, it does so by restricting freedom of speech. Thus, an promising alternative supported by several organizations is to counter such hate speech with more speech. In this paper, We analyze hate speech and the corresponding counters (aka counterspeech) on Twitter. We perform several lexical, linguistic and psycholinguistic analysis on these user accounts and obverse that counter speakers employ several strategies depending on the target community. The hateful accounts express more negative sentiments and are more profane. We also find that the hate tweets by verified accounts have much more virality as compared to a tweet by a non-verified account. While the hate users seem to use words more about envy, hate, negative emotion, swearing terms, ugliness, the counter users use more words related to government, law, leader. We also build a supervised model for classifying the hateful and counterspeech accounts on Twitter and obtain an F-score of 0.77. We also make our dataset public to help advance the research on hate speech.
Particulate Air Pollution, Blood Mitochondrial DNA Copy Number, and Telomere Length in Mothers in the First Trimester of Pregnancy: Effects on Fetal Growth

Growing evidences have shown that particulate matter (PM) exposures during pregnancy are associated with impaired fetal development and adverse birth outcomes, possibly as a result of an exaggerated systemic oxidative stress and inflammation. Telomere length (TL) is strongly linked to biological age and is impacted by oxidative stress. We hypothesized that PM exposure during different time windows in the first trimester of pregnancy influences both mitochondrial DNA copy number (mtDNAcn), an established biomarker for oxidative stress, and TL. Maternal blood TL and mtDNAcn were analysed in 199 healthy pregnant women recruited at the 11th week of pregnancy by quantitative polymerase chain reaction. We also examined whether maternal mtDNAcn and TL were associated with fetal growth outcomes measured at the end of the first trimester of pregnancy (fetal heart rate, FHR; crown-rump length, CRL; and nuchal translucency, NT) and at delivery (birth weight, length, head circumference). The possible modifying effect of prepregnancy maternal body mass index was evaluated. PM10 exposure during the first pregnancy trimester was associated with an increased maternal mtDNAcn and a reduced TL. As regards ultrasound fetal outcomes, both FHR and CRL were positively associated with PM2.5, whereas the association with FHR was confirmed only when examining PM10 exposure. PM10 was also associated with a reduced birth weight. While no association was found between mtDNAcn and CRL, we found a negative relationship between mtDNAcn and fetal CRL only in overweight women, whereas normal-weight women exhibited a positive, albeit nonsignificant, association. As abnormalities of growth in utero have been associated with postnatal childhood and adulthood onset diseases and as PM is a widespread pollutant relevant to the large majority of the human population and obesity a rising risk factor, our results, if confirmed in a larger population, might represent an important contribution towards the development of more targeted public health strategies.
Anonymous Communication via Anonymous Identity-Based Encryption and Its Application in IoT

Under the environment of the big data, the correlation between the data makes people have a greater demand for privacy. Moreover, the world has become more diversified and democratic than ever before. Freedom of speech is considered to be very important; thus, anonymity is also a very important security demand. The research of our paper proposes a scheme which can ensure both the privacy and the anonymity of a communication system, that is, the protection of message privacy while ensuring the users’ anonymity. It is based on anonymous identity-based encryption (IBE), by which the users’ metadata are protected. We implement our scheme in JAVA with Java pairing-based cryptography library (JPBC); the experiment shows that our scheme has significant advantage in efficiency compared with other anonymous communication system. Internet-of-Things (IoT) involves many devices, and privacy of devices is very significant. Anonymous communication system provides a secure environment without leaking metadata, which has many application scenarios in IoT.
Modulation of Innate Immunity by G-CSF and Inflammatory Response by LBPK95A Improves the Outcome of Sepsis in a Rat Model

Introduction Sepsis is the primary cause of death from infection. We wanted to improve the outcome of sepsis by stimulating innate immunity in combination with modulating the severity of inflammatory responses in rats. Method Sepsis was induced by the injection of feces suspension (control). A 5-day course of G-CSF treatment was given before the septic insult (G-CSF). The inflammatory response was decreased using various doses of the LPS-blocking peptide LBPK95A (5 mg/kg = 100% Combi group, 0.5 mg/kg = 10% Combi group, and 0.05 mg/kg = 1% Combi group). Survival rates were observed. Bacterial clearance, neutrophil infiltration, tissue damage, and the induction of hepatic and systemic inflammatory responses were determined 2 h and 12 h after the septic insult. Results High-dose LBPK95A (100% Combi) reduced the survival rate to 10%, whereas low-dose LBPK95A (10% and 1% Combi) increased the survival rates to 50% and 80%, respectively. The survival rates inversely correlated with multiorgan damage as indicated by the serum levels of ALT and urea. G-CSF treatment increased the white blood cell counts, hepatic neutrophil infiltration, and bacterial clearance in the liver, lung, and blood. The blockade of the LPS-LBP interaction decreased neutrophil infiltration, led to increased white blood cell count, and decreased hepatic neutrophil infiltration, irrespective of dose. However, bacterial clearance improved in the 1% and 10% Combi groups but worsened in the 100% Combi group. G-CSF increased TNF-α and IL-6 levels. Irrespective of dose, the blockade of the LPS-LBP interaction was associated with low systemic cytokine levels and delayed increases in hepatic TNF-α and IL-6 mRNA expression. The delayed increase in cytokines was associated with the phosphorylation of STAT3 and AKT. Conclusion Our results revealed that increasing innate immunity by G-CSF pretreatment and decreasing inflammatory responses using LBPK95A improved the survival rates in a rat sepsis model and could be a novel strategy to treat sepsis.
Fabrication and Packaging of CMUT Using Low Temperature Co-Fired Ceramic

This paper presents fabrication and packaging of a capacitive micromachined ultrasonic transducer (CMUT) using anodically bondable low temperature co-fired ceramic (LTCC). Anodic bonding of LTCC with Au vias-silicon on insulator (SOI) has been used to fabricate CMUTs with different membrane radii, 24 µm, 25 µm, 36 µm, 40 µm and 60 µm. Bottom electrodes were directly patterned on remained vias after wet etching of LTCC vias. CMUT cavities and Au bumps were micromachined on the Si part of the SOI wafer. This high conductive Si was also used as top electrode. Electrical connections between the top and bottom of the CMUT were achieved by Au-Au bonding of wet etched LTCC vias and bumps during anodic bonding. Three key parameters, infrared images, complex admittance plots, and static membrane displacement, were used to evaluate bonding success. CMUTs with a membrane thickness of 2.6 µm were fabricated for experimental analyses. A novel CMUT-IC packaging process has been described following the fabrication process. This process enables indirect packaging of the CMUT and integrated circuit (IC) using a lateral side via of LTCC. Lateral side vias were obtained by micromachining of fabricated CMUTs and used to drive CMUTs elements. Connection electrodes are patterned on LTCC side via and a catheter was assembled at the backside of the CMUT. The IC was mounted on the bonding pad on the catheter by a flip-chip bonding process. Bonding performance was evaluated by measurement of bond resistance between pads on the IC and catheter. This study demonstrates that the LTCC and LTCC side vias scheme can be a potential approach for high density CMUT array fabrication and indirect integration of CMUT-IC for miniature size packaging, which eliminates problems related with direct integration.
How do we use in vitro models to understand epileptiform and ictal activity? A report of the TASK1‐WG4 group of the ILAE/AES Joint Translational Task Force

In vitro brain tissue preparations allow the convenient and affordable study of brain networks and have allowed us to garner molecular, cellular, and electrophysiologic insights into brain function with a detail not achievable in vivo. Preparations from both rodent and human postsurgical tissue have been utilized to generate in vitro electrical activity similar to electrographic activity seen in patients with epilepsy. A great deal of knowledge about how brain networks generate various forms of epileptiform activity has been gained, but due to the multiple in vitro models and manipulations used, there is a need for a standardization across studies. Here, we describe epileptiform patterns generated using in vitro brain preparations, focusing on issues and best practices pertaining to recording, reporting, and interpretation of the electrophysiologic patterns observed. We also discuss criteria for defining in vitro seizure‐like patterns (i.e., ictal) and interictal discharges. Unifying terminologies and definitions are proposed. We suggest a set of best practices for reporting in vitro studies to favor both efficient across‐lab comparisons and translation to in vivo models and human studies.
Immunogenicity evaluation of plasmids encoding Brucella melitensis Omp25 and Omp31 antigens in BALB/c mice

Objective(s): Vaccination is one of the most effective means to protect humans and animals against brucellosis. Live attenuated Brucella vaccines are considered effective in animals but they may be potentially infectious to humans, so it is vital to improve the immunoprotective effects and safety of vaccines against Brucella. This study was designed to evaluate the immunogenicity of DNA vaccines encoding B. melitensis outer membrane proteins (Omp25 and Omp31) against B. melitensis Rev1 in a mouse model. Materials and Methods: For this propose, Omp25 and Omp31 genes were cloned (individually and together) into the eukaryotic expression vector pcDNA3.1/Hygro (+). Expressions of recombinant plasmids were confirmed by SDS-PAGE and Western blot analysis. Six groups of BALB/c mice (seven mice per group) were intramuscularly injected with three recombinant constructs, native pcDNA3.1/Hygro (+) and phosphate-buffered saline (PBS) as controls and subcutaneous injection of attenuated live vaccine Rev1. Results: Results indicated that DNA vaccine immunized BALB/c mice had a dominant immunoglobulin G response and elicited a T-cell-proliferative response and induced significant levels of interferon gamma (INF-γ) compared to the control groups. Conclusion: Collectively, these finding suggested that the pcDNA3.1/Hygro DNA vaccines encoding Omp25 and Omp31 genes and divalent plasmid were able to induce both humoral and cellular immunity, and had the potential to be a vaccine candidate for prevention of B. melitensis infections.
Meta-Transfer Learning for Few-Shot Learning

Meta-learning has been proposed as a framework to address the challenging few-shot learning setting. The key idea is to leverage a large number of similar few-shot tasks in order to learn how to adapt a base-learner to a new task for which only a few labeled samples are available. As deep neural networks (DNNs) tend to overfit using a few samples only, meta-learning typically uses shallow neural networks (SNNs), thus limiting its effectiveness. In this paper we propose a novel few-shot learning method called meta-transfer learning (MTL) which learns to adapt a deep NN for few shot learning tasks. Specifically, "meta" refers to training multiple tasks, and "transfer" is achieved by learning scaling and shifting functions of DNN weights for each task. In addition, we introduce the hard task (HT) meta-batch scheme as an effective learning curriculum for MTL. We conduct experiments using (5-class, 1-shot) and (5-class, 5-shot) recognition tasks on two challenging few-shot learning benchmarks: miniImageNet and Fewshot-CIFAR100. Extensive comparisons to related works validate that our meta-transfer learning approach trained with the proposed HT meta-batch scheme achieves top performance. An ablation study also shows that both components contribute to fast convergence and high accuracy.
An Optically Induced Dielectrophoresis (ODEP)-Based Microfluidic System for the Isolation of High-Purity CD45neg/EpCAMneg Cells from the Blood Samples of Cancer Patients—Demonstration and Initial Exploration of the Clinical Significance of These Cells

Circulating tumour cells (CTCs) in blood circulation play an important role in cancer metastasis. CTCs are generally defined as the cells in circulating blood expressing the surface antigen EpCAM (epithelial cell adhesion molecule). Nevertheless, CTCs with a highly metastatic nature might undergo an epithelial-to-mesenchymal transition (EMT), after which their EpCAM expression is downregulated. In current CTC-related studies, however, these clinically important CTCs with high relevance to cancer metastasis could be missed due to the use of the conventional CTC isolation methodologies. To precisely explore the clinical significance of these cells (i.e., CD45neg/EpCAMneg cells), the high-purity isolation of these cells from blood samples is required. To achieve this isolation, the integration of fluorescence microscopic imaging and optically induced dielectrophoresis (ODEP)-based cell manipulation in a microfluidic system was proposed. In this study, an ODEP microfluidic system was developed. The optimal ODEP operating conditions and the performance of live CD45neg/EpCAMneg cell isolation were evaluated. The results demonstrated that the proposed system was capable of isolating live CD45neg/EpCAMneg cells with a purity as high as 100%, which is greater than the purity attainable using the existing techniques for similar tasks. As a demonstration case, the cancer-related gene expression of CD45neg/EpCAMneg cells isolated from the blood samples of healthy donors and cancer patients was successfully compared. The initial results indicate that the CD45neg/EpCAMneg nucleated cell population in the blood samples of cancer patients might contain cancer-related cells, particularly EMT-transformed CTCs, as suggested by the high detection rate of vimentin gene expression. Overall, this study presents an ODEP microfluidic system capable of simply and effectively isolating a specific, rare cell species from a cell mixture.
Monitoring Protein Secretion in Streptomyces Using Fluorescent Proteins

Fluorescent proteins are a major cell biology tool to analyze protein sub-cellular topology. Here we have applied this technology to study protein secretion in the Gram-positive bacterium Streptomyces lividans TK24, a widely used host for heterologous protein secretion biotechnology. Green and monomeric red fluorescent proteins were fused behind Sec (SPSec) or Tat (SPTat) signal peptides to direct them through the respective export pathway. Significant secretion of fluorescent eGFP and mRFP was observed exclusively through the Tat and Sec pathways, respectively. Plasmid over-expression was compared to a chromosomally integrated spSec-mRFP gene to allow monitoring secretion under high and low level synthesis in various media. Fluorimetric detection of SPSec-mRFP recorded folded states, while immuno-staining detected even non-folded topological intermediates. Secretion of SPSec-mRFP is unexpectedly complex, is regulated independently of cell growth phase and is influenced by the growth regime. At low level synthesis, highly efficient secretion occurs until it is turned off and secretory preforms accumulate. At high level synthesis, the secretory pathway overflows and proteins are driven to folding and subsequent degradation. High-level synthesis of heterologous secretory proteins, whether secretion competent or not, has a drastic effect on the endogenous secretome, depending on their secretion efficiency. These findings lay the foundations of dissecting how protein targeting and secretion are regulated by the interplay between the metabolome, secretion factors and stress responses in the S. lividans model.
A Converse Bound for Cache-Aided Interference Networks

In this paper, an interference network with arbitrary number of transmitters and receivers is studied, where each transmitter is equipped with a finite size cache. We obtain an information-theoretic lower bound on both the peak normalized delivery time (NDT), and the expected NDT of cache-aided interference networks with uniform content popularity. For the peak NDT, we show that our lower bound is strictly tighter than the bound in the literature for small cache sizes. Moreover, we show that the feasibility region on the expected NDT is bigger than that of the peak NDT.
Verifying Fairness Properties via Concentration

As machine learning systems are increasingly used to make real world legal and financial decisions, it is of paramount importance that we develop algorithms to verify that these systems do not discriminate against minorities. We design a scalable algorithm for verifying fairness specifications. Our algorithm obtains strong correctness guarantees based on adaptive concentration inequalities; such inequalities enable our algorithm to adaptively take samples until it has enough data to make a decision. We implement our algorithm in a tool called VeriFair, and show that it scales to large machine learning models, including a deep recurrent neural network that is more than five orders of magnitude larger than the largest previously-verified neural network. While our technique only gives probabilistic guarantees due to the use of random samples, we show that we can choose the probability of error to be extremely small.
Adenosine Actions on Oligodendroglia and Myelination in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is the most commonly diagnosed neurodevelopmental disorder. Independent of neuronal dysfunction, ASD and its associated comorbidities have been linked to hypomyelination and oligodendroglial dysfunction. Additionally, the neuromodulator adenosine has been shown to affect certain ASD comorbidities and symptoms, such as epilepsy, impairment of cognitive function, and anxiety. Adenosine is both directly and indirectly responsible for regulating the development of oligodendroglia and myelination through its interaction with, and modulation of, several neurotransmitters, including glutamate, dopamine, and serotonin. In this review, we will focus on the recent discoveries in adenosine interaction with physiological and pathophysiological activities of oligodendroglia and myelination, as well as ASD-related aspects of adenosine actions on neuroprotection and neuroinflammation. Moreover, we will discuss the potential therapeutic value and clinical approaches of adenosine manipulation against hypomyelination in ASD.
Conflict Detection and Logical Complexity

Empirical evidence for the capacity to detect conflict between biased reasoning and normative principles has led to the proposal that reasoners have an intuitive grasp of some basic logical principles. In two studies, we investigate the boundary conditions of these logical intuitions by manipulating the logical complexity of problems where logical validity and conclusion believability conflict or not. Results pointed to evidence for successful conflict detection on the basic Modus Ponens (MP) inference, but also showed evidence for such a phenomenon on the more complex Modus Tollens (MT) inference. This suggests that both the MP and the MT inferences are simple enough for reasoners to have an intuitive grasp of their logical structure. The boundaries of logical intuition might thus reside in problems of greater complexity than these inferences. We also observed that on the invalid Affirmation of the Consequent (AC) and Denial of the Antecedent (DA) inferences, participants showed higher accuracy on the inference that was expected to be more complex (DA), and no evidence for successful conflict detection was found on these forms. Implications for the logical intuition framework are discussed.
Distribution of Paraoxonase-1 (PON-1) and Lipoprotein Phospholipase A2 (Lp-PLA2) across Lipoprotein Subclasses in Subjects with Type 2 Diabetes

Paraoxonase-1 (PON1) and lipoprotein phospholipase A2 (Lp-PLA2) may exert an important protective role by preventing the oxidative transformation of high- and low-density lipoproteins (HDL and LDL, respectively). The activity of both enzymes is influenced by lipidome and proteome of the lipoprotein carriers. T2DM typically presents significant changes in the molecular composition of the lipoprotein subclasses. Thus, it becomes relevant to understand the interaction of PON1 and Lp-PLA2 with the subspecies of HDL, LDL, and other lipoproteins in T2DM. Serum levels of PON1-arylesterase and PON1-lactonase and Lp-PLA2 activities and lipoprotein subclasses were measured in 202 nondiabetic subjects (controls) and 92 T2DM outpatients. Arylesterase, but not lactonase or Lp-PLA2 activities, was inversely associated with TD2M after adjusting for potential confounding factors such as age, sex, smoking, body mass index, hypertension, and lipoprotein subclasses (odds ratio = 3.389, 95% confidence interval 1.069–14.756). Marked difference between controls and T2DM subjects emerged from the analyses of the associations of the three enzyme activities and lipoprotein subclasses. Arylesterase was independently related with large HDL-C and small intermediate-density lipoprotein cholesterol (IDL-C) in controls while, along with lactonase, it was related with small low-density lipoprotein cholesterol LDL-C, all IDL-C subspecies, and very low-density lipoprotein cholesterol (VLDL-C) in T2DM (p < 0.05 for all). Concerning Lp-PLA2, there were significant relationships with small LDL-C, large IDL-C, and VLDL-C only among T2DM subjects. Our study showed that T2DM subjects have lower levels of PON1-arylesterase compared to controls and that T2DM occurrence may coincide with a shift of PON1 and Lp-PLA2 towards the more proatherogenic lipoprotein subclasses. The possibility of a link between the two observed phenomena requires further investigations.