Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting egregious responses in neural sequence-to-sequence models

In this work, we attempt to answer a critical question: whether there exists some input sequence that will cause a well-trained discrete-space neural network sequence-to-sequence (seq2seq) model to generate egregious outputs (aggressive, malicious, attacking, etc.). And if such inputs exist, how to find them efficiently. We adopt an empirical methodology, in which we first create lists of egregious output sequences, and then design a discrete optimization algorithm to find input sequences that will cause the model to generate them. Moreover, the optimization algorithm is enhanced for large vocabulary search and constrained to search for input sequences that are likely to be input by real-world users. In our experiments, we apply this approach to dialogue response generation models trained on three real-world dialogue data-sets: Ubuntu, Switchboard and OpenSubtitles, testing whether the model can generate malicious responses. We demonstrate that given the trigger inputs our algorithm finds, a significant number of malicious sentences are assigned large probability by the model, which reveals an undesirable consequence of standard seq2seq training.
Antibody-Neutralized Reovirus Is Effective in Oncolytic Virotherapy

Oncolytic viruses are thought to lose antitumor efficacy when bound to neutralizing antibodies. However, monocytes can internalize antibody-neutralized virus and transfer infectious virus to tumor cells, killing them. Thus, antibodies could be exploited for oncolytic virus therapy. Immunotherapy is showing promise for otherwise incurable cancers. Oncolytic viruses (OVs), developed as direct cytotoxic agents, mediate their antitumor effects via activation of the immune system. However, OVs also stimulate antiviral immune responses, including the induction of OV-neutralizing antibodies. Current dogma suggests that the presence of preexisting antiviral neutralizing antibodies in patients, or their development during viral therapy, is a barrier to systemic OV delivery, rendering repeat systemic treatments ineffective. However, we have found that human monocytes loaded with preformed reovirus–antibody complexes, in which the reovirus is fully neutralized, deliver functional replicative reovirus to tumor cells, resulting in tumor cell infection and lysis. This delivery mechanism is mediated, at least in part, by antibody receptors (in particular FcγRIII) that mediate uptake and internalization of the reovirus/antibody complexes by the monocytes. This finding has implications for oncolytic virotherapy and for the design of clinical OV treatment strategies. Cancer Immunol Res; 6(10); 1161–73. ©2018 AACR.
Loei Fabric Weaving Pattern Recognition Using Deep Neural Network

The Thai traditional woven fabrics are handicraft products indicate the flourish of Thai national culture and creativity of the nation. Many provinces have a long history of their own patterns on hand-woven fabric weaving style. One of the well-known provinces is Loei. Several villages produce their own unique styles in the woven pattern: Tai Loei, Tai Dam, or Tai Lue. Local people are able to recognize and distinguish the difference between these fabric groups but it is not easy for people from other areas, especially tourists to discriminate them. Moreover, the most complicated one is to train a machine to tell the difference between these fabric patterns. The issues about machine to classify the identity of something used to be the difficult problem in the area of pattern recognition and image classification. But the advancement in the popular algorithms of Deep Neural Network on image recognition opens the new opportunity to accomplish these problems with the greatly improved result. In this paper, we proposed to apply the Deep Neural Network techniques to solve Thai Loei woven fabric pattern recognition problem. For helping the machine to recognize the local weaving style and for the tourist to understand the exclusive on each local tradition.
Impact of Risk-Related Disclosure on the Risk-Taking Behavior of Commercial Banks in Pakistan

INTRODUCTION Mamoona Naz1 Huma Ayub2 1 Student, Department of Business Administration, Fatima Jinnah Women University, Rawalpindi, Pakistan. mamoona08@gmail.com 2 Assistant Professor, Department of Business Administration, Fatima Jinnah Women University, Rawalpindi, Pakistan. Bank supervisors have embraced the concept of market discipline as a supportive tool to their supervisory and regulatory measures; for monitoring risk in individual banks and in the banking system as whole (Benink & Wihlborg, 2002). Adequate risk disclosures are essential for this concept to work. The financial crisis of 2007 and its worldwide consequences also raised questions about the awareness of risks financial intermediaries remain exposed to, and the techniques and procedures they have in place to manage such risks (Krugman, 2009). In light of this Basel Committee for Banking Supervision (BCBS) devised risk disclosure requirements in Basel-II under Pillar-3 of market discipline to ensures adequate risk disclosures on the part of commercial banks, assisting shareholders and other stakeholders in decision-making (Hakenes & Schnabel, 2011). These requirements are imposed to deter agency conflict and information asymmetry ultimately eliminating moral hazard incentives (Baumann & Nier, 2004; Benink & Wihlborg, 2002; Ghosh & Das, 2005; Jeitschko & Jeung, 2005). For evaluation of the disclosure levels, the literature demonstrates the use of disclosure
Unusual BK polyomavirus‐associated urologic malignancies in renal transplant recipients: Report of two cases and review of the literature

Renal transplant recipients are at increased risk of developing urologic malignancies, some of which are associated with prolonged BK virus infection. We report two cases of BK virus‐associated carcinoma with variant morphological patterns (clear cell adenocarcinoma of the bladder and micropapillary urothelial carcinoma of the pelvicaliceal system) arising in the urinary tract of renal transplant recipients. In both cases, the diagnosis was initially established on cytologic specimens: on urine cytology in one patient and on fine needle aspiration of an inguinal lymph node in the other patient. The unusual cytologic features of both cases (multiple morphologies in one patient and micropapillary pattern in the other), co‐occurrence of decoy cells in the urine of one patient and the occurrence of these tumors in renal transplant recipients raised the possibility of BK polyomavirus‐associated malignancy and led to confirmatory SV40 immunostains that were positive. These cases expand the morphologic variants of BK virus‐associated urologic malignancies diagnosed in solid organ transplant patients. While differentiating BK virus‐infected cells from malignant cells in urine cytology specimens is a diagnostic challenge, greater awareness of their possible co‐existence is vital, as this could be the only chance for an early diagnosis.
Hearing Loss and Verbal Memory Assessment Among Older Adults

Objective: Research has found that adults with hearing loss perform worse on cognitive testing than adults without hearing loss; however, heavy emphasis on tests involving auditory stimuli may overdiagnose cognitive impairment among individuals with hearing loss. This study compared visual- and auditory-verbal memory tests among adults with and without hearing loss. Method: Forty-one adults with hearing loss (HL) and 41 age-matched adults with normal hearing (NH) completed a neuropsychological battery that included auditory and visual versions of the Hopkins Verbal Learning Testing-Revised (HVLT-R). A natural auditory condition presented HVLT-R stimuli at normal speaking volume. A crossed auditory condition presented HVLT-R stimuli to individuals with hearing loss with amplified acoustic intensity and to individuals with normal hearing under hearing loss simulation. Results: Mixed-model ANOVA indicated significant group (HL vs. NH) by condition (visual, natural auditory, crossed auditory) interactions for HVLT-R performance, with large effect sizes. The HL group performed significantly worse than the NH group on the natural auditory version; however, the NH group performed significantly worse than the HL group on the crossed condition. The groups were equivalent on the visual condition and all other cognitive tests, showing small effect sizes. Moreover, for the HL group, visual HVLT-R correlated with other cognitive tests whereas auditory versions did not. Conclusion: Cognitively intact older adults with hearing loss appeared impaired on auditory-verbal memory assessment under typical administration conditions. Visual assessment of verbal memory showed evidence of superior validity and is a viable alternative method to assess memory function especially in older populations.
Baculovirus-Induced Fast-Acting Innate Immunity Kills Liver-Stage Plasmodium

Baculovirus (BV), an enveloped insect virus with a circular dsDNA genome, possesses unique characteristics that induce strong innate immune responses in mammalian cells. In this study, we show that BV administration in BALB/c mice not only provides complete protection against a subsequent Plasmodium berghei sporozoite infection for up to 7 d after the injection but also eliminates existing liver-stage parasites completely. The elimination of sporozoites by BV was superior to that by primaquine, and this effect occurred in a TLR9-independent manner. At 6 h after BV administration, IFN-α and IFN-γ were robustly produced in the serum, and RNA transcripts of IFN-stimulated genes were markedly upregulated in the liver compared with control mice. The in vivo passive transfer of serum after BV administration effectively eliminated liver-stage parasites, and IFN-α neutralization abolished this effect, indicating that the BV liver-stage parasite-killing mechanism is downstream of the type I IFN signaling pathway. These findings provide evidence that BV-induced, fast-acting innate immunity completely kills liver-stage parasites and, thus, may lead to new malaria drug and vaccine strategies.
Fast Vehicle Detection Using a Disparity Projection Method

The stereo vision could obtain the 3-D coordinate of the detected object by computing the disparity of the corresponding image points. However, on account of the time complexity and the low robustness of the image matching algorithm, it is seldom used in large-scale scene. This paper puts forward a new vehicle detection method, which simplifies the massive Fourier transformation in the image matching process. The method converts the 2-D Fourier transformation to 1-D with the dimensionality reduction of reused Fourier transformation. Meanwhile, 1-D Fourier transformation of the fast image matching model is also derived. The coarse-to-fine pyramid search strategy is used according to the gradient information of each depth map adaptively. The adjacent area of the same depth is obtained with a larger matching weight which improves the matching accuracy and robustness. The model can be used in the fitting and projection transformation of road plane after background extraction. Thus reduce the complexity of vehicle segmentation and enhance the robustness of vehicle detection. The experimental results show the method can effectively achieve the large-scale and real-time detection. It is adaptive to various illumination changes and impervious to shadow and occlusion.
An Optimal Pricing Scheme for the Energy-Efficient Mobile Edge Computation Offloading With OFDMA

The mobile edge computation offloading (MECO) system has emerged as a promising technology to address several problematic issues in cloud computing such as data throughput, capacity, and security. In this letter, we consider a single-cloud-multi-user MECO system with orthogonal frequency-division multiple access and propose an optimal pricing scheme to consider each mobile user’s (MU) need for resources. The proposed model was formulated as a single-leader-multi-user Stackelberg game model, and the Stackelberg equilibrium was provided to optimize the utility of the MUs and the edge cloud. Here, the utility of the MU implies the energy efficiency and payment for using the computation capacity of the edge cloud, and the utility of the edge cloud implies the revenue for serving computation offloading. The optimal strategies of the MUs are uniquely given by closed-form expressions, and that of the edge cloud is given by gradient descent methods. Some numerical examples are provided to verify our approach.
Isolated and Ensemble Audio Preprocessing Methods for Detecting Adversarial Examples against Automatic Speech Recognition

An adversarial attack is an exploitative process in which minute alterations are made to natural inputs, causing the inputs to be misclassified by neural models. In the field of speech recognition, this has become an issue of increasing significance. Although adversarial attacks were originally introduced in computer vision, they have since infiltrated the realm of speech recognition. In 2017, a genetic attack was shown to be quite potent against the Speech Commands Model. Limited-vocabulary speech classifiers, such as the Speech Commands Model, are used in a variety of applications, particularly in telephony; as such, adversarial examples produced by this attack pose as a major security threat. This paper explores various methods of detecting these adversarial examples with combinations of audio preprocessing. One particular combined defense incorporating compressions, speech coding, filtering, and audio panning was shown to be quite effective against the attack on the Speech Commands Model, detecting audio adversarial examples with 93.5% precision and 91.2% recall.
Barrier-Certified Adaptive Reinforcement Learning With Applications to Brushbot Navigation

This paper presents a safe learning framework that employs an adaptive model learning algorithm together with barrier certificates for systems with possibly nonstationary agent dynamics. To extract the dynamic structure of the model, we use a sparse optimization technique. We use the learned model in combination with control barrier certificates that constrain policies (feedback controllers) in order to maintain safety, which refers to avoiding particular undesirable regions of the state space. Under certain conditions, recovery of safety in the sense of Lyapunov stability after violations of safety due to the nonstationarity is guaranteed. In addition, we reformulate an action-value function approximation to make any kernel-based nonlinear function estimation method applicable to our adaptive learning framework. Lastly, solutions to the barrier-certified policy optimization are guaranteed to be globally optimal, ensuring the greedy policy improvement under mild conditions. The resulting framework is validated via simulations of a quadrotor, which has previously been used under stationarity assumptions in the safe learnings literature, and is then tested on a real robot, the brushbot, whose dynamics is unknown, highly complex, and nonstationary.
What you see depends on what you hear: temporal averaging and crossmodal integration

In our multisensory world, we often rely more on auditory information than on visual input for temporal processing. One typical demonstration of this is that the rate of auditory flutter assimilates the rate of concurrent visual flicker. To date, however, this auditory dominance effect has largely been studied using regular auditory rhythms. It thus remains unclear whether irregular rhythms would have a similar impact on visual temporal processing; what information is extracted from the auditory sequence that comes to influence visual timing; and how the auditory and visual temporal rates are integrated together in quantitative terms. We investigated these questions by assessing, and modeling, the influence of a task-irrelevant auditory sequence on the type of ‘Ternus apparent motion’: group motion versus element motion. The type of motion seen critically depends on the time interval between the two Ternus display frames. We found that an irrelevant auditory sequence preceding the Ternus display modulates the visual interval, making observers perceive either more group motion or more element motion. This biasing effect manifests whether the auditory sequence is regular or irregular, and it is based on a summary statistic extracted from the sequential intervals: their geometric mean. However, the audiovisual interaction depends on the discrepancy between the mean auditory and visual intervals: if it becomes too large, no interaction occurs – which can be quantitatively described by a partial Bayesian integration model. Overall, our findings reveal a crossmodal perceptual averaging principle that may underlie complex audiovisual interactions in many everyday dynamic situations. Public Significance Statement The present study shows that auditory rhythms, regardless of their regularity, can influence the way in which the visual system times (subsequently presented) events, thereby altering dynamic visual (motion) perception. This audiovisual temporal interaction is based on a summary statistic derived from the auditory sequence: the geometric mean interval, which is then combined with the visual interval in a process of partial Bayesian integration (where integration is unlikely to occur if the discrepancy between the auditory and visual intervals is too large). We propose that this crossmodal perceptual averaging principle underlies complex audiovisual interactions in many everyday dynamic perception scenarios. Author Note This study was supported by grants from the Natural Science Foundation of China (31200760, 61621136008, 61527804), German DFG project SH166 3/1 and “projektbezogener Wissenschaftleraustausch” (proWA). The data, and the source code of statistical analysis and modeling are available at https://github.com/msenselab/temporal_averaging. Part of the study has been presented as a talk in 17th International Multisensory Research Forum (IMRF, June 2016, Suzhou, China).
Scalar Diversity, Negative Strengthening, and Adjectival Semantics

Previous research has demonstrated great variability in the rates of scalar inferences across different triggers (Doran et al., 2009; van Tiel et al., 2016). In the current study, we show that variation is more systematic than previously thought. In particular, we present experimental evidence suggesting that endorsements of scalar implicatures (i) are anti-correlated with the degree of negative strengthening of the stronger scale-mate (e.g., whether John is not stunning is interpreted as conveying that John is rather ugly) and (ii) are affected by the scale structure and the underlying scalar semantics of gradable adjectives (in particular boundedness, polarity, and adjectival extremeness). Overall, our research suggests that scale structure should be taken into account in theories of implicature.
Rabbit Microbiota Changes Throughout the Intestinal Tract

To gain insight into the importance of carefully selecting the sampling area for intestinal microbiota studies, cecal and fecal microbial communities of Caldes meat rabbit were characterized. The animals involved in the study were divided in two groups according to the feed intake level they received during the fattening period; ad libitum (n = 10) or restricted to 75% of ad libitum intake (n = 11). Cecum and internal hard feces were sampled from sacrificed animals. Assessment of bacterial and archaeal populations was performed by means of Illumina sequencing of 16S rRNA gene amplicons in a MiSeq platform. A total of 596 operational taxonomic units (OTUs) were detected using QIIME software. Taxonomic assignment revealed that microbial diversity was dominated by phyla Firmicutes (76.42%), Tenericutes (7.83%), and Bacteroidetes (7.42%); kingdom Archaea was presented at low percentage (0.61%). No significant differences were detected between sampling origins in microbial diversity or richness assessed using two alpha-diversity indexes: Shannon and the observed number of OTUs. However, the analysis of variance at genus level revealed a higher presence of genera Clostridium, Anaerofustis, Blautia, Akkermansia, rc4-4, and Bacteroides in cecal samples. By contrast, genera Oscillospira and Coprococcus were found to be overrepresented in feces, suggesting that bacterial species of these genera would act as fermenters at the end of feed digestion process. At the lowest taxonomic level, 83 and 97 OTUs in feces and cecum, respectively, were differentially represented. Multivariate statistical assessment revealed that sparse partial least squares discriminant analysis (sPLS-DA) was the best approach for this purpose. Interestingly, the majority of the most discriminative OTUs selected by sPLS-DA were found to be differentially represented between sampling origins in univariate analysis. Our study provides evidence that the choice of intestinal sampling area is relevant due to important differences in some taxa’s relative abundance that have been revealed between rabbits’ cecal and fecal microbiota. An appropriate sampling intestinal area should be chosen in each microbiota assessment.
Reduced language processing automaticity induces weaker emotions in bilinguals regardless of learning context.

While the evidence for impoverished emotional reactions of bilinguals in their weaker second language (L2) accumulates, the underlying mechanisms of this effect remain poorly understood. Here, we investigate how unbalanced bilinguals' language-specific emotions vary depending on differences in language processing automaticity versus in language learning and use contexts. We analyzed behavioral emotional reactions in a hypothetical decision-making task with low emotional appeal, the Asian disease problem (Study 1) and pupil and valence responses to authentic narrative video advertising with high emotional appeal (Study 2). Both studies replicated the L2 emotion disadvantage. In decision-making, L2 reactions paralleled first language reactions under perceptual load. During the L2 narrative, the pupil dilated less because of reduced lexical access automaticity rather than in response to language-context factors. The findings suggest that bilinguals have language-independent emotional representations. Yet, they process emotional information conveyed in L2 less automatically, which triggers weaker emotional reactions. (PsycINFO Database Record
Okul Öncesi Öğretmenliği ve Çocuk Gelişimi Öğrencilerinin Üstbiliş Düzeylerinin ve Yaşam Doyumlarının İncelenmesi

Bu arastirmanin temel amaci, okul oncesi ogretmenligi ve cocuk gelisimi bolumu ogrencilerinin ustbilis duzeyleri ve yasam doyumu duzeylerini incelemektir. Iliskisel tarama modelindeki bu arastirmanin calisma grubunu 2017-2018 egitim ogretim yilinda Istanbul ilindeki 2 vakif universitesinin okul oncesi ogretmenligi lisans programinda ve cocuk gelisimi on lisans programinda ogrenim gormekte olan 167 ogrenci olusturmustur. Arastirmada veri toplama araci olarak Kisisel Bilgi Formu, Ustbilis Olcegi-30 ve Yasam Doyumu Olcegi kullanilmistir. Arastirma verileri SPSS 20 programi kullanilarak analiz edilmistir. Arastirma sonucunda, okul oncesi ogretmenligi ve cocuk gelisimi bolumu ogrencilerinin ustbilis duzeyleri ve yasam doyumu duzeyleri arasinda anlamli iliski oldugu saptanmistir. Okul oncesi ogretmenligi ve cocuk gelisimi ogrencilerinin ustbilis duzeylerinin universite turu ve bolumune, sinif duzeyine gore anlamli duzeyde farklilasmazken; yasa, kardes sayisina, okul oncesi ogretmenligi/cocuk gelisimi bolumunu secme nedenine ve algilanan ebeveyn tutumuna gore anlamli duzeyde farklilastigi saptanmistir. Okul oncesi ogretmenligi ve cocuk gelisimi ogrencilerinin yasam doyumlarinin universite turu ve bolumune, yasa ve kardes sayisina gore anlamli duzeyde farklilasmazken; sinif duzeyine, okul oncesi ogretmenligi/cocuk gelisimi bolumunu secme nedenine ve algilanan ebeveyn tutumuna gore anlamli duzeyde farklilastigi saptanmistir.