Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Assembling Modular Networks for Interpretable Multi-Hop Reasoning

Multi-hop QA requires a model to connect multiple pieces of evidence scattered in a long context to answer the question. The recently proposed HotpotQA (Yang et al., 2018) dataset is comprised of questions embodying four different multi-hop reasoning paradigms (two bridge entity setups, checking multiple properties, and comparing two entities), making it challenging for a single neural network to handle all four. In this work, we present an interpretable, controller-based Self-Assembling Neural Modular Network (Hu et al., 2017, 2018) for multi-hop reasoning, where we design four novel modules (Find, Relocate, Compare, NoOp) to perform unique types of language reasoning. Based on a question, our layout controller RNN dynamically infers a series of reasoning modules to construct the entire network. Empirically, we show that our dynamic, multi-hop modular network achieves significant improvements over the static, single-hop baseline (on both regular and adversarial evaluation). We further demonstrate the interpretability of our model via three analyses. First, the controller can softly decompose the multi-hop question into multiple single-hop sub-questions to promote compositional reasoning behavior of the main network. Second, the controller can predict layouts that conform to the layouts designed by human experts. Finally, the intermediate module can infer the entity that connects two distantly-located supporting facts by addressing the sub-question from the controller.
What can computational models learn from human selective attention? A review from an audiovisual crossmodal perspective

Selective attention plays an essential role in information acquisition and utilizationfrom the environment. In the past 50 years, research on selective attention has beena central topic in cognitive science. Compared with unimodal studies, crossmodalstudies are more complex but necessary to solve real-world challenges in both humanexperiments and computational modeling. Although an increasing number of findingson crossmodal selective attention have shed light on humans’ behavioral patterns andneural underpinnings, a much better understanding is still necessary to yield the samebenefit for intelligent computational agents. This article reviews studies of selectiveattention in unimodal visual and auditory and crossmodal audiovisual setups from themultidisciplinary perspectives of psychology and cognitive neuroscience, and evaluatesdifferent ways to simulate analogous mechanisms in computational models and robotics.We discuss the gaps between these fields in this interdisciplinary review and provideinsights about how to use psychological findings and theories in artificial intelligence fromdifferent perspectives.
Efficiently Breaking the Curse of Horizon: Double Reinforcement Learning in Infinite-Horizon Processes

Oﬀ-policy evaluation (OPE) in reinforcement learning is notoriously diﬃcult in long-and inﬁnite-horizon settings due to diminishing overlap between behavior and target policies. In this paper, we study the role of Markovian, time-invariant, and ergodic structure in eﬃcient OPE. We ﬁrst derive the eﬃciency limits for OPE when one assumes each of these structures. This precisely characterizes the curse of horizon: in time-variant processes, OPE is only feasible in the near-on-policy setting, where behavior and target policies are suﬃciently similar. But, in ergodic time-invariant Markov decision processes, our bounds show that truly-oﬀ-policy evaluation is feasible, even with only just one dependent trajectory, and provide the limits of how well we could hope to do. We develop a new estimator based on Double Reinforcement Learning (DRL) that leverages this structure for OPE. Our DRL estimator simultaneously uses estimated stationary density ratios and q -functions and remains eﬃcient when both are estimated at slow, nonparametric rates and remains consistent when either is estimated consistently. We investigate these properties and the performance beneﬁts of leveraging the problem structure for more eﬃcient OPE.
SuPer: A Surgical Perception Framework for Endoscopic Tissue Manipulation With Surgical Robotics

Traditional control and task automation have been successfully demonstrated in a variety of structured, controlled environments through the use of highly specialized modeled robotic systems in conjunction with multiple sensors. However, the application of autonomy in endoscopic surgery is very challenging, particularly in soft tissue work, due to the lack of high-quality images and the unpredictable, constantly deforming environment. In this letter, we propose a novel surgical perception framework, SuPer, for surgical robotic control. This framework continuously collects 3D geometric information that allows for mapping a deformable surgical field while tracking rigid instruments within the field. To achieve this, a model-based tracker is employed to localize the surgical tool with a kinematic prior in conjunction with a model-free tracker to reconstruct the deformable environment and provide an estimated point cloud as a mapping of the environment. The proposed framework was implemented on the da Vinci Surgical System in real-time with an end-effector controller where the target configurations are set and regulated through the framework. Our proposed framework successfully completed soft tissue manipulation tasks with high accuracy. The demonstration of this novel framework is promising for the future of surgical autonomy. In addition, we provide our dataset for further surgical research. **Website: https://www.sites. google.com/ucsd.edu/super-framework.
Phase Collaborative Network for Two-Phase Medical Image Segmentation

In real-world practice, medical images acquired in different phases possess complementary information, {\em e.g.}, radiologists often refer to both arterial and venous scans in order to make the diagnosis. However, in medical image analysis, fusing prediction from two phases is often difficult, because (i) there is a domain gap between two phases, and (ii) the semantic labels are not pixel-wise corresponded even for images scanned from the same patient. This paper studies organ segmentation in two-phase CT scans. We propose Phase Collaborative Network (PCN), an end-to-end framework that contains both generative and discriminative modules. PCN can be mathematically explained to formulate phase-to-phase and data-to-label relations jointly. Experiments are performed on a two-phase CT dataset, on which PCN outperforms the baselines working with one-phase data by a large margin, and we empirically verify that the gain comes from inter-phase collaboration. Besides, PCN transfers well to two public single-phase datasets, demonstrating its potential applications.
Learning Alignment for Multimodal Emotion Recognition from Speech

Speech emotion recognition is a challenging problem because human convey emotions in subtle and complex ways. For emotion recognition on human speech, one can either extract emotion related features from audio signals or employ speech recognition techniques to generate text from speech and then apply natural language processing to analyze the sentiment. Further, emotion recognition will be beneficial from using audio-textual multimodal information, it is not trivial to build a system to learn from multimodality. One can build models for two input sources separately and combine them in a decision level, but this method ignores the interaction between speech and text in the temporal domain. In this paper, we propose to use an attention mechanism to learn the alignment between speech frames and text words, aiming to produce more accurate multimodal feature representations. The aligned multimodal features are fed into a sequential model for emotion recognition. We evaluate the approach on the IEMOCAP dataset and the experimental results show the proposed approach achieves the state-of-the-art performance on the dataset.
The contribution of endothelin-1 in colorectal cancer & the efficacy of the novel endothelin receptor antagonist ZD4054

The overall aims of this thesis are: to determine the cellular response to ET-1 and effects of receptor antagonism on proliferation, migration and contraction of colonic fibroblasts and cancer cell lines. At the molecular level to identify novel genes that are regulated by ET-1 and whether antagonists including ZD4054 have potentially beneficial effects by blocking expression of these genes. Finally to determine ET-1 binding distribution by autoradiography in patient tumour sections and delineate binding characteristics of ET-1 and its receptor antagonists (Bmax, Kd and IC50). To investigate ET-1 and its antagonistic effects at the cellular level, colorectal cancer cell lines and colonic fibroblasts (isolated from patient colorectal cancer specimens) were studied. They were incubated with ET-1 with/without BQ123, zibotentan (ETAR antagonists) and/or BQ788 (ETBR antagonist). Growth was measured by methylene blue uptake; migration by scratch wound assay and contraction in collagen gels. To identify novel key genes regulated by ET-1, Illumina micro-arrays determined differential gene expression post-ET-1 stimulation of 3 colorectal cancer cell lines and the 4 human colonic fibroblast strains. To confirm expression of genes of interest, we examined time point induction mRNA levels (conventional RT-PCR; quantitative real-time RT-PCR). ETA (Zibotentan, BQ123) and ETB (BQ788) antagonistic effects were measured at the mRNA and protein levels (Immunoblotting). Silencing (SiRNA) was also used to confirm receptor involvement in regulation of these key genes. ET-1 receptor distribution and binding characteristics (Kd; Bmax) were determined using in vitro autoradiography on patient sections, tissue homogenates, CRC cell lines and colonic fibroblasts. Effects of the ETAR specific antagonist zibotentan (ZD4054) on ET-1 receptor binding (IC50) were evaluated against laboratory-standard compounds. Immunohistochemistry (IHC) was used to identify stromal structures and receptor distribution (vascular CD31; Thy-1 fibroblasts; collagen type XI; ETA and ETB). Study was awarded ethical approval, REC No. 08/H0720/162, University College London Hospitals
Carer Engagement in the Home-Care Provision Industry

Employee engagement is a concept that can have huge positive bearings on organisational outcomes (Buckingham and Coffman, 1999), specifically in the health industry (Pelzang, 2010; Lee, Lee and Kang 2012). This research will examine the key influencers of engagement for carers in the home-care sector in East Clare. The home-care sector is going to become an increasingly important one in the years ahead, given Ireland’s ageing population. The industry is beginning to be opened up to tender and is currently unregulated (Home and Community Care Ireland, 2014). However, there appears to be very little Irish research done in this area despite it being of such critical social and economic importance both to the individual being cared for and society as a whole. Therefore, it is worthy of more examination. The impetus for the research arose through the researcher working in a large home care provider in Dublin for one day a week for six months. This prompted a curiosity about how the ad-hoc working hours impacted on carer engagement levels. The methodology used in this research was structured, face-to-face interviews with five carers which was the most appropriate way to gain a comprehensive insight into the area. The interviews were structured around a questionnaire amended from Tellis-Neyak (2007) and allowed the research to generate the “why” of the responses for better understanding (Saunders, Lewis and Thornhill, 2009). The research found that the carers interviewed display what appears to be a uniquely high level of engagement, to the extent that the main source of job stress is that they can’t do more for their clients. Pay appears not to be a significant factor in determining engagement levels. There is a very hands-off style of management resulting in a high level of employee discretion. There is little or no formal recognition of the outstanding work that is done by carers on a daily basis. The findings are of enormous value as the job of a carer is truly unique and needs to be recognised and valued by their employers and society.
Reversing Threat to Safety: Incongruence of Facial Emotions and Instructed Threat Modulates Conscious Perception but Not Physiological Responding

Facial expressions inform about other peoples’ emotion and motivation and thus are central for social communication. However, the meaning of facial expressions may change depending on what we have learned about the related consequences. For instance, a smile might easily become threatening when displayed by a person who is known to be dangerous. The present study examined the malleability of emotional facial valence by means of social learning. To this end, facial expressions served as cues for verbally instructed threat-of-shock or safety (e.g., “happy faces cue shocks”). Moreover, reversal instructions tested the flexibility of threat/safety associations (e.g., “now happy faces cue safety”). Throughout the experiment, happy, neutral, and angry facial expressions were presented and auditory startle probes elicited defensive reflex activity. Results show that self-reported ratings and physiological reactions to threat/safety cues dissociate. Regarding threat and valence ratings, happy facial expressions tended to be more resistant becoming a threat cue, and angry faces remain threatening even when instructed as safety cue. For physiological response systems, however, we observed threat-potentiated startle reflex and enhanced skin conductance responses for threat compared to safety cues regardless of whether threat was cued by happy or angry faces. Thus, the incongruity of visual and verbal threat/safety information modulates conscious perception, but not the activation of physiological response systems. These results show that verbal instructions can readily overwrite the intrinsic meaning of facial emotions, with clear benefits for social communication as learning and anticipation of threat and safety readjusted to accurately track environmental changes.
Incorporating Statistical Test and Machine Intelligence Into Strain Typing of Staphylococcus haemolyticus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

Staphylococcus haemolyticus is one of the most significant coagulase-negative staphylococci, and it often causes severe infections. Rapid strain typing of pathogenic S. haemolyticus is indispensable in modern public health infectious disease control, facilitating the identification of the origin of infections to prevent further infectious outbreak. Rapid identification enables the effective control of pathogenic infections, which is tremendously beneficial to critically ill patients. However, the existing strain typing methods, such as multi-locus sequencing, are of relatively high cost and comparatively time-consuming. A practical method for the rapid strain typing of pathogens, suitable for routine use in clinics and hospitals, is still not available. Matrix-assisted laser desorption ionization-time of flight mass spectrometry combined with machine learning approaches is a promising method to carry out rapid strain typing. In this study, we developed a statistical test-based method to determine the reference spectrum when dealing with alignment of mass spectra datasets, and constructed machine learning-based classifiers for categorizing different strains of S. haemolyticus. The area under the receiver operating characteristic curve and accuracy of multi-class predictions were 0.848 and 0.866, respectively. Additionally, we employed a variety of statistical tests and feature-selection strategies to identify the discriminative peaks that can substantially contribute to strain typing. This study not only incorporates statistical test-based methods to manage the alignment of mass spectra datasets but also provides a practical means to accomplish rapid strain typing of S. haemolyticus.
Determination of nucleotide and enzyme degradation in haddock (Melanogrammus aeglefinus) and herring (Clupea harengus) after high pressure processing

Background The degradation of nucleotides and their enzymes had been widely used to evaluate fish freshness. Immediately after fish death, adenosine triphosphate (ATP) degrades into inosine-5-monophosphate (IMP) via adenosine-5-diphosphate (ADP) and adenosine-5-monophosphate (AMP). IMP degradation continues to produce inosine (ino) and hypoxanthine (Hx) and further deteriorates the fish by producing xanthine and uric acid. The dephosphorylation of IMP to Ino is carried out by the enzyme 5′-nucleotidase (5′-NT), whereas the degradation of Ino to Hx is carried out by the enzyme nucleoside phosphorylase (NP). This study assesses the application of high pressure processing (HPP) in two species of fishes; haddock (Melanogrammus aeglefinus) and herring (Clupea harengus) as a means to extend the shelf-life by slowing down the rate of nucleotides degradation. Methods Haddock (Melanogrammus aeglefinus) and herring (Clupea harengus) fillets were subjected to HPP at 200, 250 and 300 MPa for 1 and 3 min before being stored for 14 days. In addition, 5′-NT and NP enzyme activities were determined on both fish species that were subjected to 100–600 MPa for 1 and 3 min. Results Adenosine triphosphate, ADP and AMP in both haddock and herring were lower at higher pressure levels. Inosine (Ino) increased (p < 0.05) after treatment at higher pressures in both species. Hx in herring decreased significantly (p < 0.05) at higher pressures but not in haddock. K values are the ratio of Ino and Hx to all nucleotides. K values in haddock were not significantly (p > 0.05) affected by the pressure treatment. H values are ratio of Hx to the sum of IMP, Ino and Hx. H values in haddock were significantly decreased (p < 0.05) with increasing pressure level. F values are ratio of IMP to the sum of IMP, Ino and Hx. F values showed no significant effects (p > 0.05) after pressure treatment. Furthermore, K values in control herring were significantly higher (p < 0.05) than those of the pressure-treated samples. H values in herring decreased significantly (p < 0.05) with increasing pressure level. F values in herring showed no significant effects (p > 0.05) after pressure treatment. Pressure treatment brought a significant decrease (p < 0.05) in protein content in both haddock and herring. 5′-NT activity was 20–35 fold higher compared to NP activity in haddock and 15–44 fold higher than NP activity in herring. 5′-NT and NP activities decreased significantly with increasing pressure level in both species. Discussion High pressure processing effectively slows down the conversion of Ino to Hx, delaying the undesirable flavour that develops in spoiling fish. The autolytic conversion of IMP to Ino by endogenous 5′-NT predominates in the earliest stages of storage is an autolytic process. However, both bacterial and endogenous NP enzymes are probably responsible for the gradual accumulation of Hx in fish. K values are recommended as a useful measurement of fish freshness.
The effect of cardiac rehabilitation at 4 weeks postoperatively on quality of life in patients treated with totally thoracoscopic ablation

There is a lack of evidence on the effect of exercise-based cardiac rehabilitation (EBCR) in patients treated with total thoracoscopic ablation (TTA) for atrial fibrillation (AF). Our study investigated the efficacy and safety of postoperative exercise intervention in patients recovering from TTA. Twenty-four patients participated in the study, and were divided into the two groups, exercise group (EG) (n=12) and control group (n= 12). Patients in EG performed the exercise intervention including the aerobic and resistance exercise program twice a week for 8 weeks, which was used as a hospital-based cardiac rehabilitation for the out-patient. A cardiopulmonary exercise test was administered to evaluate aerobic exercise capacity, and qualitative aspect of patient’s life was assessed using the Short Form 36 questionnaires to compare pre and postoperative wellness of patient’s life. Although there was an increase of VO2peak (peak oxygen uptake) after exercise intervention, no significant improvement was found (P=0.055). Two of 4 physical health scores (role-physical, P=0.013 and general health, P=0.05) and three of four mental health scores (vitality, P=0.027, social function, P=0.016, and mental health, P=0.003) were significantly improved after 8 weeks of EBCR. Each summarized scale in the physical (P=0.022) and mental (P= 0.004) survey section was also significantly improved in postoperative assessment compared to the preoperative one. In this context, we concluded that EBCR initiated at the time point of 4th week after TTA operation can guarantee the secure postoperative physical activity, and the 8 weeks of EBCR can effectively improve the quality of life in AF Patients.
Genome-wide miRNA profiling and pivotal roles of miRs 125a-5p and 17-92 cluster in human neutrophil maturation and differentiation of acute myeloid leukemia cells

MicroRNAs (miRNAs, miRs) are short non-coding post-transcriptional regulators of gene expression in normal physiology and disease. Acute myeloid leukemia is characterized by accumulation of malignantly transformed immature myeloid precursors, and differentiation therapy, used to overcome this differentiation blockage, has become a successful therapeutic option. The human HL-60 acute leukemia cell line serves as a cell culture model for granulocytic maturation, and dimethyl sulfoxide (DMSO) incubation leads to its differentiation towards neutrophil-like cells, as assessed by biochemical, functional and morphological parameters. DMSO-induced HL-60 cell differentiation constitutes an excellent model to examine molecular processes that turn a proliferating immortal leukemic cell line into mature non-proliferating and apoptosis-prone neutrophil-like end cells. By performing genome-wide miRNA profiling and functional assays, we have identified a signature of 86 differentially expressed canonical miRNAs (51 upregulated; 35 downregulated) during DMSO-induced granulocytic differentiation of HL-60 cells. Quantitative real-time PCR was used to validate miRNA expression. Among these differentially expressed canonical miRNAs, we found miR-125a-5p upregulation and miR-17-92 cluster downregulation acted as major regulators of granulocytic differentiation in HL-60 cells. Enforced expression of miR-125a-5p promoted granulocytic differentiation in HL-60 cells, whereas miR-17-92 ectopic expression inhibited DMSO-induced HL-60 granulocytic differentiation. Ectopic expression of miR-125a-5p also promoted granulocytic differentiation in human acute promyelocytic leukemia NB4 cells, as well as in naïve human primary CD34+-hematopoietic progenitor/stem cells. These findings provide novel molecular insights into the identification of miRNAs regulating granulocytic differentiation of human leukemia cells and normal CD34+-hematopoietic progenitor/stem cells, and may assist in the development of novel miRNA-targeted therapies for leukemia.