Miracle-dz/UniFAR-FTUs huggingface dataset:
Input–output organization of the mouse claustrum

Progress in determining the precise organization and function of the claustrum (CLA) has been hindered by the difficulty in reliably targeting these neurons. To overcome this, we used a projection‐based targeting strategy to selectively label CLA principal neurons. Combined with adeno‐associated virus (AAV) and monosynaptic rabies tracing techniques, we systematically examined the pre‐synaptic input and axonal output of this structure. We found that CLA neurons projecting to retrosplenial cortex (RSP) collateralize extensively to innervate a variety of higher‐order cortical regions. No subcortical labeling was found, with the exception of sparse terminals in the basolateral amygdala (BLA). This pattern of output was similar to cingulate‐ and visual cortex‐projecting CLA neurons, suggesting a common targeting scheme among these projection‐defined populations. Rabies virus tracing directly demonstrated widespread synaptic inputs to RSP‐projecting CLA neurons from both cortical and subcortical areas. The strongest inputs arose from classically defined limbic regions, including medial prefrontal cortex, anterior cingulate, BLA, ventral hippocampus, and neuromodulatory systems such as the dorsal raphe and cholinergic basal forebrain. These results suggest that the CLA may integrate information related to the emotional salience of stimuli and may globally modulate cortical state by broadcasting its output uniformly across a variety of higher cognitive centers.
Neural network approach to classifying alarming student responses to online assessment

Automated scoring engines are increasingly being used to score the free-form text responses that students give to questions. Such engines are not designed to appropriately deal with responses that a human reader would find alarming such as those that indicate an intention to self-harm or harm others, responses that allude to drug abuse or sexual abuse or any response that would elicit concern for the student writing the response. Our neural network models have been designed to help identify these anomalous responses from a large collection of typical responses that students give. The responses identified by the neural network can be assessed for urgency, severity, and validity more quickly by a team of reviewers than otherwise possible. Given the anomalous nature of these types of responses, our goal is to maximize the chance of flagging these responses for review given the constraint that only a fixed percentage of responses can viably be assessed by a team of reviewers.
Learning to Detect Fake Face Images in the Wild

Although Generative Adversarial Network (GAN) can be used to generate the realistic image, improper use of these technologies brings hidden concerns. For example, GAN can be used to generate a tampered video for specific people and inappropriate events, creating images that are detrimental to a particular person, and may even affect that personal safety. In this paper, we will develop a deep forgery discriminator (DeepFD) to efficiently and effectively detect the computer-generated images. Directly learning a binary classifier is relatively tricky since it is hard to find the common discriminative features for judging the fake images generated from different GANs. To address this shortcoming, we adopt contrastive loss in seeking the typical features of the synthesized images generated by different GANs and follow by concatenating a classifier to detect such computer-generated images. Experimental results demonstrate that the proposed DeepFD successfully detected 94.7% fake images generated by several state-of-the-art GANs.
Factors associated with knowledge and awareness of HIV/AIDS among married women in Bangladesh: evidence from a nationally representative survey

ABSTRACT Women in Bangladesh share a greater risk of Human Immunodeficiency Virus (HIV)/Acquired Immune Deficiency Syndrome (AIDS) infection compared to men. Levels of knowledge and awareness largely contribute to the prevalence of the HIV epidemic and its consequences. So, it is required to conduct studies based on most recent data to explore the determinants of HIV awareness. Therefore, we aimed to find the awareness level and factors influencing HIV related awareness among the married women in Bangladesh. We used data from 2014 Bangladesh Demographic and Health Survey (BDHS). About two-third of total respondents who heard about the HIV/AIDS were selected and interviewed successfully (n = 12,593) about 11 basic questions related to individual’s awareness. A score of the respondent’s knowledge and awareness was determined based on these questions. We used logistic regression models for analysing the data. We found about 62% of the respondents had an adequate knowledge and consciousness about the HIV/AIDS. Respondents’ education status, mass-media access, place of living, and working status played significant role on the awareness. As expected, respondents with higher education were more aware than those with no education (odds ratio (OR) = 3.56, 95% confidence interval (CI): 2.99–4.23). Moreover, respondents who had access to the mass media were more likely to be aware compared to those who did not have the access (OR = 1.14, 95% CI: 1.04–1.26). Although a sizeable proportion of women had an adequate knowledge and awareness regarding the HIV/AIDS, we recommend implementing educational programmes related to HIV/AIDS in the curriculum to ensure a standard level of awareness throughout the nation. Since the respondents from rural areas scored significantly lower than the urban areas, awareness through mass media, particularly in rural areas, is of prime concern for raising awareness.
19F MRI of the Lungs Using Inert Fluorinated Gases: Challenges and New Developments

Fluorine‐19 (19F) MRI using inhaled inert fluorinated gases is an emerging technique that can provide functional images of the lungs. Inert fluorinated gases are nontoxic, abundant, relatively inexpensive, and the technique can be performed on any MRI scanner with broadband multinuclear imaging capabilities. Pulmonary 19F MRI has been performed in animals, healthy human volunteers, and in patients with lung disease. In this review, the technical requirements of 19F MRI are discussed, along with various imaging approaches used to optimize the image quality. Lung imaging is typically performed in humans using a gas mixture containing 79% perfluoropropane (PFP) or sulphur hexafluoride (SF6) and 21% oxygen. In lung diseases, such as asthma, chronic obstructive pulmonary disease (COPD), and cystic fibrosis (CF), ventilation defects are apparent in regions that the inhaled gas cannot access. 19F lung images are typically acquired in a single breath‐hold, or in a time‐resolved, multiple breath fashion. The former provides measurements of the ventilation defect percent (VDP), while the latter provides measurements of gas replacement (ie, fractional ventilation). Finally, preliminary comparisons with other functional lung imaging techniques are discussed, such as Fourier decomposition MRI and hyperpolarized gas MRI. Overall, functional 19F lung MRI is expected to complement existing proton‐based structural imaging techniques, and the combination of structural and functional lung MRI will provide useful outcome measures in the future management of pulmonary diseases in the clinic.
The problem solver and the artisan designer: strategies for utilizing design idea archives

This paper presents the results of an extensive qualitative study investigating how professional designers utilize personal idea archives. While we know that designers archive creative ideas in different formats and on different platforms, we know little about if and how designers utilize these idea archives in their daily practice. Through a series of interviews (n=20) and walkthroughs of design idea archives, we identified two archetypal strategies. The Problem Solver is concerned with the task at hand, keeps relevant ideas around, and discards them when the ideas have served their purpose. On the other hand, The Artisan Designer systematically archives potentially useful ideas in carefully selected formats and continues developing ideas over extended time spans. We conclude with a discussion about how these different strategies might be supported by technological archiving tools.
Adversarial Training in Affective Computing and Sentiment Analysis: Recent Advances and Perspectives

Over the past few years, adversarial training has become an extremely active research topic and has been successfully applied to various Artificial Intelligence (AI) domains. As a potentially crucial technique for the development of the next generation of emotional AI systems, we herein provide a comprehensive overview of the application of adversarial training to affective computing and sentiment analysis. Various representative adversarial training algorithms are explained and discussed accordingly, aimed at tackling diverse challenges associated with emotional AI systems. Further, we highlight a range of potential future research directions. We expect that this overview will help facilitate the development of adversarial training for affective computing and sentiment analysis in both the academic and industrial communities.
Exploring relationships between museum artefacts through spatial interaction

We propose a novel approach, which involves visitors physically manipulating visual representations of artefacts and scanning with their mobile phone different groups or sequences of items in order to reveal digital information about their relationships. To explore this interaction mechanism we collaborated with a museum to develop an interactive paper map, on which visitors can place tangible representations of artefacts and scan the resulting arrangements. Based on an in-situ study of its use, we reveal that museum visitors engaged in different strategies for exploration of relationships between artefacts in the museum collection (inspection, strategic and experimental configuration), and for social collaboration (sharing the interaction space, adopting interaction roles and sharing a reaction to the "reveal"). We discuss how future interactive installations can accommodate these behaviours.
The Role of CXCR3 and Its Chemokine Ligands in Skin Disease and Cancer

Chemokines and their receptors play an important role in the recruitment, activation and differentiation of immune cells. The chemokine receptor, CXCR3, and its ligands, CXCL9, CXCL10, and CXCL11 are key immune chemoattractants during interferon-induced inflammatory responses. Inflammation of the skin resulting from infections or autoimmune disease drives expression of CXCL9/10/11 and the subsequent recruitment of effector, CXCR3+ T cells from the circulation. The relative contributions of the different CXCR3 chemokines and the three variant isoforms of CXCR3 (CXCR3A, CXCR3B, CXCR3alt) to the inflammatory process in human skin requires further investigation. In skin cancers, the CXCR3 receptor can play a dual role whereby expression on tumor cells can lead to cancer metastasis to systemic sites while receptor expression on immune cells can frequently promote anti-tumor immune responses. This review will discuss the biology of CXCR3 and its associated ligands with particular emphasis on the skin during inflammation and carcinogenesis.
Metabolomics-Driven Elucidation of Cellular Nitrate Tolerance Reveals Ascorbic Acid Prevents Nitroglycerin-Induced Inactivation of Xanthine Oxidase

Glyceryl trinitrate (GTN) has found widespread use for the treatment of angina pectoris, a pathological condition manifested by chest pain resulting from insufficient blood supply to the heart. Metabolic conversion of GTN, a nitric oxide (NO) pro-drug, into NO induces vasodilation and improves blood flow. Patients develop tolerance to GTN after several weeks of continuous use, limiting the potential for long-term therapy. The mechanistic cause of nitrate tolerance is relatively unknown. We developed a cell culture model of nitrate tolerance that utilizes stable isotopes to measure metabolism of 15N3-GTN into 15N-nitrite. We performed global metabolomics to identify the mechanism of GTN-induced nitrate tolerance and to elucidate the protective role of vitamin C (ascorbic acid). Metabolomics analyses revealed that GTN impaired purine metabolism and depleted intracellular ATP and GTP. GTN inactivated xanthine oxidase (XO), an enzyme that is critical for the metabolic bioactivation of GTN into NO. Ascorbic acid prevented inactivation of XO, resulting in increased NO production from GTN. Our studies suggest that ascorbic acid has the ability to prevent nitrate tolerance by protecting XO, but not aldehyde dehydrogenase (another GTN bioactivating enzyme), from GTN-induced inactivation. Our findings provide a mechanistic explanation for the previously observed beneficial effects of ascorbic acid in nitrate therapy.
Panobinostat mediated cell death: a novel therapeutic approach for osteosarcoma

Osteosarcoma is an aggressive cancer with a poor long term prognosis. Neo-adjuvant poly-chemotherapy followed by surgical resection remains the standard treatment, which is restricted by multi-drug resistance. If first-line therapy fails, disease control and patient survival rate drop dramatically. We aimed to identify alternative apoptotic mechanisms induced by the histone deacetylase inhibitor panobinostat in osteosarcoma cells. Saos-2, MG63 and U2-OS osteosarcoma cell lines, the immortalized human osteoblast line hFOB and the mouse embryo osteoblasts (MC3T3-E1) were treated with panobinostat. Real time viability and FACS confirmed the cytotoxicity of panobinostat. Cell stress/death related factors were analysed by RT-qPCR and western blot. Cell morphology was assessed by electron microscopy. 10 nM panobinostat caused cell viability arrest and death in all osteosarcoma and osteoblast cells. P21 up-regulation was observed in osteosarcoma cells, while over-expression of p73 was restricted to Saos-2 (TP53−/−). Survivin and Bcl-2 were suppressed by panobinostat. Endoplasmic reticulum (ER) stress markers BiP, CHOP, ATF4 and ATF6 were induced in osteosarcoma cells. The un-spliced Xbp was no further detectable after treatment. Autophagy players Beclin1, Map1LC3B and UVRAG transcripts over-expressed after 6 hours. Protein levels of Beclin1, Map1LC3B and p62 were up-regulated at 72 hours. DRAM1 was stable. Electron micrographs revealed the fragmentation and the disappearance of the ER and the statistically significant increase of autophagosome vesiculation after treatment. Panobinostat showed a synergistic suppression of survival and promotion of cell death in osteosarcoma cells. Panobinostat offers new perspectives for the treatment of osteosarcoma and other malignant bone tumours.
Application of Machine Learning in Wireless Networks: Key Techniques and Open Issues

As a key technique for enabling artificial intelligence, machine learning (ML) is capable of solving complex problems without explicit programming. Motivated by its successful applications to many practical tasks like image recognition, both industry and the research community have advocated the applications of ML in wireless communication. This paper comprehensively surveys the recent advances of the applications of ML in wireless communication, which are classified as: resource management in the MAC layer, networking and mobility management in the network layer, and localization in the application layer. The applications in resource management further include power control, spectrum management, backhaul management, cache management, and beamformer design and computation resource management, while ML-based networking focuses on the applications in clustering, base station switching control, user association, and routing. Moreover, literatures in each aspect is organized according to the adopted ML techniques. In addition, several conditions for applying ML to wireless communication are identified to help readers decide whether to use ML and which kind of ML techniques to use. Traditional approaches are also summarized together with their performance comparison with ML-based approaches, based on which the motivations of surveyed literatures to adopt ML are clarified. Given the extensiveness of the research area, challenges and unresolved issues are presented to facilitate future studies. Specifically, ML-based network slicing, infrastructure update to support ML-based paradigms, open data sets and platforms for researchers, theoretical guidance for ML implementation, and so on are discussed.
Detecting Hate Speech and Offensive Language on Twitter using Machine Learning: An N-gram and TFIDF based Approach

Toxic online content has become a major issue in today's world due to an exponential increase in the use of internet by people of different cultures and educational background. Differentiating hate speech and offensive language is a key challenge in automatic detection of toxic text content. In this paper, we propose an approach to automatically classify tweets on Twitter into three classes: hateful, offensive and clean. Using Twitter dataset, we perform experiments considering n-grams as features and passing their term frequency-inverse document frequency (TFIDF) values to multiple machine learning models. We perform comparative analysis of the models considering several values of n in n-grams and TFIDF normalization methods. After tuning the model giving the best results, we achieve 95.6% accuracy upon evaluating it on test data. We also create a module which serves as an intermediate between user and Twitter.
Coadministration of Chemokine Receptor Antagonists with Morphine Potentiates Morphine’s Analgesic Effect on Incisional Pain in Rats

Crossdesensitization between opioid and chemokine receptors and involvement of chemokines in pain modulation are well established. We investigated if coadministration of chemokine receptor antagonists (CRAs) with morphine would enhance the analgesic potency of morphine on incisional pain in rats. Animals underwent incisional surgery on the left hind paw and pain responses were evaluated using von Frey filaments at various time points postsurgery between 15 and 360 minutes and daily between 24 and 72 hours. Dose-response curves for morphine, maraviroc (a CCR5 antagonist), and AMD3100 (a CXCR4 antagonist) alone were established. While morphine significantly reduced pain in a time- and dose-dependent manner, maraviroc and AMD3100 had no effect by themselves. Coadministration of either maraviroc or AMD3100 with morphine significantly increased morphine’s analgesic effect on incisional pain, shifting the dose-response curve to the left 2.3- and 1.8-fold, respectively. Coadministration of both CRAs with morphine significantly shifted further the morphine dose-response curve to the left 3.3-fold. The effect of treatments on mRNA levels in the draining popliteal lymph node for a panel of chemokines and cytokines showed that message for many of these mediators was upregulated by the incision, and the combination of morphine with the CRAs markedly downregulated them. The data show that combining morphine with CRAs potentiates morphine’s analgesic effect on incisional pain. Thus, the same analgesic effect of morphine alone can be achieved with lower doses of morphine when combined with CRAs. Using morphine in lower doses could reduce unwanted side effects and possibly block development of tolerance and dependence.
A53T Mutant Alpha-Synuclein Induces Tau-Dependent Postsynaptic Impairment Independently of Neurodegenerative Changes

Abnormalities in α-synuclein are implicated in the pathogenesis of Parkinson's disease (PD). Because α-synuclein is highly concentrated within presynaptic terminals, presynaptic dysfunction has been proposed as a potential pathogenic mechanism. Here, we report novel, tau-dependent, postsynaptic deficits caused by A53T mutant α-synuclein, which is linked to familial PD. We analyzed synaptic activity in hippocampal slices and cultured hippocampal neurons from transgenic mice of either sex expressing human WT, A53T, and A30P α-synuclein. Increased α-synuclein expression leads to decreased spontaneous synaptic vesicle release regardless of genotype. However, only those neurons expressing A53T α-synuclein exhibit postsynaptic dysfunction, including decreased miniature postsynaptic current amplitude and decreased AMPA to NMDA receptor current ratio. We also found that long-term potentiation and spatial learning were impaired by A53T α-synuclein expression. Mechanistically, postsynaptic dysfunction requires glycogen synthase kinase 3β-mediated tau phosphorylation, tau mislocalization to dendritic spines, and calcineurin-dependent AMPA receptor internalization. Previous studies reveal that human A53T α-synuclein has a high aggregation potential, which may explain the mutation's unique capacity to induce postsynaptic deficits. However, patients with sporadic PD with severe tau pathology are also more likely to have early onset cognitive decline. Our results here show a novel, functional role for tau: mediating the effects of α-synuclein on postsynaptic signaling. Therefore, the unraveled tau-mediated signaling cascade may contribute to the pathogenesis of dementia in A53T α-synuclein-linked familial PD cases, as well as some subgroups of PD cases with extensive tau pathology. SIGNIFICANCE STATEMENT Here, we report mutation-specific postsynaptic deficits that are caused by A53T mutant α-synuclein, which is linked to familial Parkinson's disease (PD). The overexpression of WT, A53T, or A30P human α-synuclein leads to decreased spontaneous synaptic vesicle release. However, only those neurons expressing A53T α-synuclein exhibit tau phosphorylation-dependent postsynaptic dysfunction, which is characterized by decreased miniature postsynaptic current amplitude and decreased AMPA to NMDA receptor current ratio. The mutation-specific postsynaptic effects caused by human A53T α-synuclein will help us better understand the neurobiological basis of this specific form of familial PD. The differential effects of exogenous human WT, A53T, A30P, and E46K α-synuclein on glutamatergic synaptic responses will help to explain the clinical heterogeneity of sporadic and familial PD.