Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning to Disentangle Interleaved Conversational Threads with a Siamese Hierarchical Network and Similarity Ranking

An enormous amount of conversation occurs online every day, such as on chat platforms where multiple conversations may take place concurrently. Interleaved conversations lead to difficulties in not only following discussions but also retrieving relevant information from simultaneous messages. Conversation disentanglement aims to separate intermingled messages into detached conversations. In this paper, we propose to leverage representation learning for conversation disentanglement. A Siamese hierarchical convolutional neural network (SHCNN), which integrates local and more global representations of a message, is first presented to estimate the conversation-level similarity between closely posted messages. With the estimated similarity scores, our algorithm for conversation identification by similarity ranking (CISIR) then derives conversations based on high-confidence message pairs and pairwise redundancy. Experiments were conducted with four publicly available datasets of conversations from Reddit and IRC channels. The experimental results show that our approach significantly outperforms comparative baselines in both pairwise similarity estimation and conversation disentanglement.
Artificial light at night prolongs juvenile development time in the black field cricket, Teleogryllus commodus

A growing body of evidence exists to support a detrimental effect of the presence of artificial light at night (ALAN) on life-history and fitness traits. However, few studies simultaneously investigate multiple traits and the life stages at which changes manifest. We experimentally manipulated ALAN intensities, within those found in the natural environment, to explore the consequences for growth, survival, and reproductive success of the field cricket, Teleogryllus commodus. We reared crickets from egg to adult under a daily light-cycle consisting of 12 hr bright daylight (2,600 lx) followed by either 12 hr darkness (0 lx) or dim-light environments (1, 10, or 100 lx). We found egg hatch, adult survival, and reproductive measures were largely comparable for all treatments. However, juvenile development time (number of days from egg to adult) was on average 10 days (14%) longer and adults were also larger when crickets were exposed to any light at night (1, 10, or 100 lx). Our data demonstrate that chronic lifetime exposure to ALAN can modulate the timing of life-history events and may disrupt phenology to a similar extent as other abiotic factors.
Human Salivary Acidic Proline-Rich Proteins (APRP-1/2) In Adult Patients With Dental Caries

Background: Acidic proline-rich proteins (APRPs) are manifested in human saliva in various phenotypes and represent its important component. The unique structure of their two isoforms. APRP-1/2 as well as their coupling to hydroxyapatite and formation of the acquired enamel pellicle are well known. Nevertheless, role of APRP-1/2 in adult patients with dental caries still remains unclear. The aim of this study was to analyze the levels of APRP-1/2 in saliva of adult patients with dental caries. Patients and Methods: The studies were conducted on 106 adult patients which were qualified to individual groups on grounds of dental examination and calculation of DMFT index. Group 1 (control) included 18 caries-free patients (DMFT=0). Group 2 included 20 persons (DMFT=2.3 Â± 1.0) with very low intensity of caries. Group 3 included 20 patients (DMFT=6.2 Â± 1.3) with low intensity of caries. Group 4 comprised 24 patients (DMFT=10.9 Â± 1.8) with moderate intensity of caries. Group 5 included 24 patients (DMFT=19.5 Â± 3.5) with high intensity of dental caries. Concentrations of APRP-1/2 in saliva were estimated using PRH2 ELISA kit (MyBioSource). Results: In persons of group 1 (control) concentration of APRP-1/2 averaged at 15.2 Â± 2.6 ng/ml. This concentration did not statistically differ from results obtained in patients of groups 2. On the other hand in patients of groups 3, 4 and 5 mean values of APRP-1/2 concentrations amounted respectively to: 18.6 Â± 3.2 ng/ml, 35.4 Â± 4.6 ng/ml and 39.8 Â± 5.1 ng/ml. The obtained values of APRP-1/2 were significantly higher than results obtained in group 1 (p 0.05; test for two independent proportions). Conclusions: High levels of APRP-1/2 in saliva of adult patients may be involved in intensification of the caries process.
Bioactivities of Phenolics by Focusing on Suppression of Chronic Diseases: A Review

Phenolics, which are secondary metabolites of plants, exhibit remarkable bioactivities. In this contribution, we have focused on their protective effect against chronic diseases rather than their antioxidant activities, which have been widely discussed in the literature. A large body of epidemiological studies has proven the bioactivities of phenolics in both standard compounds and natural extracts: namely, anticancer, anti-inflammatory, and antibacterial activities as well as reducing diabetes, cardiovascular disease, and neurodegenerative disease. Phenolics also display anti-analgesic, anti-allergic, and anti-Alzheimer’s properties. Thus, this review provides crucial information for better understanding the bioactivities of phenolics in foods and fills a gap in the existing collective and overall knowledge in the field.
Mutational spectrum of acute myeloid leukemia patients with double CEBPA mutations based on next-generation sequencing and its prognostic significance

The aim of this study was to profile the spectrum of genetic mutations in acute myeloid leukemia (AML) patients co-occurring with CEBPA double mutation (CEBPAdm). Between January 1, 2012, and June 30, 2017, 553 consecutive patients with de novo AML were screened for CEBPA mutations. Out of these, 81 patients classified as CEBPAdm were analyzed further by a sensitive next-generation sequencing assay for mutations in 112 candidate genes. Within the CEBPA gene itself, we found 164 mutations. The most common mutated sites were c. 936_937insGAG (n = 11/164, 6.71%) and c. 939_940insAAG (n = 11/164, 6.71%), followed by c.68dupC (n = 10/164, 6.10%). The most common co-occurring mutations were found in the CSF3R (n = 16/81, 19.75%), WT1 (n = 15/81, 18.52%), and GATA2 (n = 13/81, 16.05%) genes. Patients with CSF3R mutations had an inferior four-year relapse-free survival (RFS) than those with the wild-type gene (15.3% versus 46.8%, respectively; P = 0.021). Patients with WT1 mutations had an inferior five-year RFS compared with those without such mutations (0% versus 26.6%, respectively, P = 0.003). However, GATA2, CSF3R, WT1 mutations had no significant influence on the overall survival. There were some differences in the location of mutational hotspots within the CEBPA gene, as well as hotspots of other co-occurring genetic mutations, between AML patients from Chinese and Caucasian populations. Some co-occurring mutations may be potential candidates for refining the prognoses of AML patients with CEBPAdm in the Chinese population.
Nuclear localization of the CK 2 α-subunit correlates with poor prognosis in clear cell renal cell carcinoma

Protein kinase CK2α, one of the two catalytic isoforms of the protein kinase CK2 has been shown to contribute to tumor development, tumor proliferation and suppression of apoptosis in various malignancies. We conducted this study to investigate CK2 expression in different subtypes of Renal Cell Carcinoma (RCC) and in the benign oncocytoma. qRT-PCR, immunohistochemistry and Western blot analyses revealed that CK2α expression was significantly increased at the mRNA and protein levels in clear cell RCC (ccRCC). Also the kinase activity of CK2 was significantly increased in ccRCC compared to normal renal cortex. Nuclear protein expression of CK2α correlated in univariate analysis with poor Progression Free Survival (HR = 8.11, p = 0.016). Functional analyses (cell proliferation assay) revealed an inhibitory effect of Caki-2 cell growth following CK2 inhibition with CX-4945. Our results suggest that CK2α promotes migration and invasion of ccRCC and therefore could serve as a novel prognostic biomarker and molecular therapeutic target in this type of cancer.
Target Foresight Based Attention for Neural Machine Translation

In neural machine translation, an attention model is used to identify the aligned source words for a target word (target foresight word) in order to select translation context, but it does not make use of any information of this target foresight word at all. Previous work proposed an approach to improve the attention model by explicitly accessing this target foresight word and demonstrated the substantial gains in alignment task. However, this approach is useless in machine translation task on which the target foresight word is unavailable. In this paper, we propose a new attention model enhanced by the implicit information of target foresight word oriented to both alignment and translation tasks. Empirical experiments on Chinese-to-English and Japanese-to-English datasets show that the proposed attention model delivers significant improvements in terms of both alignment error rate and BLEU.
Thrombectomy 24 hours after stroke: beyond DAWN

Background and purpose The results of the DAWN trial support the benefit of thrombectomy in patients with anterior circulation large vessel occlusion (LVO) acute stroke presenting within 6–24 hours from time last known well (TLKW). We sought to evaluate the characteristics and outcomes of patients who met DAWN criteria but underwent thrombectomy beyond 24 hours of TLKW. Methods A retrospective review of endovascular thrombectomy databases at three comprehensive stroke centers was performed to identify all patients who received thrombectomy beyond 24 hours of TLKW and otherwise met the DAWN criteria. Baseline characteristics, efficacy, and safety outcomes were compared with patients in the DAWN trial intervention arm. Results Twenty-one patients met the inclusion criteria. Rates of successful reperfusion (mTICI2b–3: 81% vs 84%, P=0.72), 90-day functional independence (modified Rankin Scale score 0–2, 43% vs 48%, P=0.68), and symptomatic intracranial hemorrhage (5% vs 6%, P=0.87) were comparable across the two groups. Conclusion Thrombectomy appears to be safe and feasible in patients with acute ischemic stroke due to LVO meeting all DAWN trial criteria but treated beyond 24 hours of TLKW with outcomes comparable to patients in the DAWN trial intervention arm. Further studies are warranted to validate these findings.
A System for Efficient High-Recall Retrieval

The goal of high-recall information retrieval (HRIR) is to find all or nearly all relevant documents for a search topic. In this paper, we present the design of our system that affords efficient high-recall retrieval. HRIR systems commonly rely on iterative relevance feedback. Our system uses a state-of-the-art implementation of continuous active learning (CAL), and is designed to allow other feedback systems to be attached with little work. Our system allows users to judge documents as fast as possible with no perceptible interface lag. We also support the integration of a search engine for users who would like to interactively search and judge documents. In addition to detailing the design of our system, we report on user feedback collected as part of a 50 participants user study. While we have found that users find the most relevant documents when we restrict user interaction, a majority of participants prefer having flexibility in user interaction. Our work has implications on how to build effective assessment systems and what features of the system are believed to be useful by users.
Managing Persistent Objects with a Unified Access Framework in Persistent Memory

Research on SCM tends to follow the conventional path: using part of persistent memory as persistent heap to recover data sets after power failure; and using part of persistent memory as persistent storage to save files abstracted by files systems. However, file abstraction causes a big performance gap between persistent heap and persistent storage. persistent data objects in persistent heap is difficult for reuse and management because of these objects losing their address meaningfulness while process is over. We propose a unified access framework to manage persistent objects in persistent heap, which provides a unified access manner for persistent objects both in persistence (storage) and in temporary (memory), not requiring serializing and de-serializing operations for file abstraction. Persistent objects are organized according to application data structures in temporary, and independently exist out of process in persistence, even the process is over. Compared to PMFS, PXFS, NV-Heap, PMSE can get 1.8X, 1.1X, 44% performance gains respectively under the workloads with mixed data sets (50% of reads, 50% of writes).
Nivolumab for the treatment of colorectal cancer

ABSTRACT Introduction: Despite a variety of therapies for advanced metastatic colorectal cancer being available, the outcomes in this malignancy remain suboptimal. Immunotherapy has been slow to impact the management of this patient group. Checkpoint inhibitors, such as nivolumab, have had disappointing results when used broadly. However, for the subset of patients with microsatellite unstable colorectal cancer, the use of checkpoint inhibitors such as nivolumab appears to be transformative, and will provide a new therapeutic option for patient with advanced disease. Areas covered: Nivolumab gained regulatory approval for the treatment of dMMR/MSI-H metastatic colorectal cancer in mid 2017. The current review will summarize the clinical evidence of checkpoint inhibitors in metastatic colorectal cancer, with a focus on nivolumab. Expert commentary: For patients with dMMR/MSI-H mCRC, the use of nivolumab has now been shown to have objective and sustained clinical responses in a pivotal phase II trial. While additional data are limited, the therapeutic role for augmenting an immune response in metastatic colorectal cancer is likely to continue to expand. Further combination trials of nivolumab with immunologic and non-immunologic agents are ongoing.
Higher-Order Syntactic Attention Network for Longer Sentence Compression

A sentence compression method using LSTM can generate fluent compressed sentences. However, the performance of this method is significantly degraded when compressing longer sentences since it does not explicitly handle syntactic features. To solve this problem, we propose a higher-order syntactic attention network (HiSAN) that can handle higher-order dependency features as an attention distribution on LSTM hidden states. Furthermore, to avoid the influence of incorrect parse results, we trained HiSAN by maximizing jointly the probability of a correct output with the attention distribution. Experimental results on Google sentence compression dataset showed that our method achieved the best performance on F1 as well as ROUGE-1,2 and L scores, 83.2, 82.9, 75.8 and 82.7, respectively. In human evaluation, our methods also outperformed baseline methods in both readability and informativeness.
Optimal human functioning around the world: A new index of eudaimonic well‐being in 166 nations

As more and more people realize that wealth fails to fully capture the essence of human well-being, interest in non-monetary measures of well-being has intensified. Eudaimonic well-being (EWB; i.e., optimal psychosocial functioning) is a largely overlooked aspect of national well-being that has never been examined at the global level. This study uses data from nearly 1,800,000 respondents recruited probabilistically from 166 countries between the years of 2005 and 2017 to construct an index of EWB. EWB demonstrates moderate positive associations with other quality-of-life indicators (i.e., national life satisfaction, national prosperity, overall quality of life, and gross domestic product), indicating that it captures information not reflected by them. The distribution of EWB at national, regional, and global levels, as well as its global trend, is explored. The study also examines the relationships between EWB and a number of theoretically related individual- and country-level variables. Presented are also the results of multilevel modelling including a wide range of predictors.
Humor Recognition Using Deep Learning

Humor is an essential but most fascinating element in personal communication. How to build computational models to discover the structures of humor, recognize humor and even generate humor remains a challenge and there have been yet few attempts on it. In this paper, we construct and collect four datasets with distinct joke types in both English and Chinese and conduct learning experiments on humor recognition. We implement a Convolutional Neural Network (CNN) with extensive filter size, number and Highway Networks to increase the depth of networks. Results show that our model outperforms in recognition of different types of humor with benchmarks collected in both English and Chinese languages on accuracy, precision, and recall in comparison to previous works.
Africa infrastructure country diagnostic : roads in Sub-Saharan Africa

A road network providing adequate connectivity across national territory is typically one of the most costly items of infrastructure that any country requires. It is also the one that has typically weighed most heavily on the national budget-with a strong character for public good-that has traditionally limited the scope for cost recovery. This review of the state of road networks in Sub-Saharan Africa provides a snapshot of the current state of evolution of the sector. The snapshot encompasses the maturity of the institutional framework, the adequacy of public finance, and the performance of networks. It focuses on exploring the interconnections between these three aspects, and in particular the extent to which institutional reform has contributed to improving sectoral finances and ultimately network condition. The study is organized as follows. Chapter two presents the overall anatomy of the Sub-Saharan African road network, comparing its basic attributes to road networks found in other developing regions. Chapter three describes the evolution of institutional reform in the sector and classifies countries according to the quality of these frameworks. Chapter four analyzes road sector expenditure trends relative to theoretical norms, and tries to explain differences in expenditure across countries using the typology described above. Chapter five focuses on road network condition, and uses the same typology to understand differences in country performance. Chapter six concludes.
Decision Making for Management of Periimplant Diseases

Introduction: Nonsurgical and surgical management of periimplant mucositis and periimplantitis have shown promising results in arresting periimplant marginal bone loss (MBL) and preventing implant loss. However, management of periimplant diseases still remains unpredictable for full reconstruction of lost tissues and completely arrests disease progression. The present study proposes a decision tree that compiles both clinical and radiographic presentation of failing implants to aid in the decision making for their management. Materials and Methods: An extensive literature review was performed using 3 electronic databases (PubMed, Ovid MEDLINE, and Cochrane Central) on the most recent treatment modalities for the management of periimplant diseases. Discussion: Evidence-based treatment suggestions were primarily derived from periimplant defect morphology, presence, and severity of periimplant MBL. More evidence is required supporting soft-tissue augmentation for the treatment of periimplant diseases. Conclusion: Management of periimplant diseases can include lasers, mechanical instrumentation, chemical detoxification, and antimicrobial agents for nonsurgical approaches. On the other hand, removal of failing implants, resective surgery, guided bone regeneration, and soft-tissue grafting are presented as valid options for the surgical treatment of periimplantitis.
A Phylogenomic and Molecular Markers Based Analysis of the Class Acidimicrobiia

Recent metagenomic surveys of microbial community suggested that species associated with the class Acidimicrobiia are abundant in diverse aquatic environments such as acidic mine water, waste water sludge, freshwater, or marine habitats, but very few species have been cultivated and characterized. The current taxonomic framework of Acidimicrobiia is solely based on 16S rRNA sequence analysis of few cultivable representatives, and no molecular, biochemical, or physiological characteristics are known that can distinguish species of this class from the other bacteria. This study reports the phylogenomic analysis for 20 sequenced members of this class and reveals another three major lineages in addition to the two recognized families. Comparative analysis of the sequenced Acidimicrobiia species identified 15 conserved signature indels (CSIs) in widely distributed proteins and 26 conserved signature proteins (CSPs) that are either specific to this class as a whole or to its major lineages. This study represents the most comprehensive phylogenetic analysis of the class Acidimicrobiia and the identified CSIs and CSPs provide useful molecular markers for the identification and delineation of species belonging to this class or its subgroups.
Color image segmentation with bounded generalized Gaussian mixture model and feature selection

We present a novel method for color image segmentation based on an unsupervised learning model and feature selection. Our focus here is to develop an expectation maximization algorithm based on a mixture of bounded generalized Gaussian model combined with a feature selection mechanism. The developed statistical model offers more flexibility in data modeling than the Gaussian distribution and the feature selection mechanism aims at eliminating irrelevant features and then improving the segmentation performances. Obtained results performed on a large dataset of real world color images confirm the effectiveness of the proposed approach.
The Equilibrium Assignment of Narcissistic CEOs to Firms

Firms may rationally select CEOs whose level of narcissism is compatible with their circumstances. We model the firm-CEO matching process in which narcissistic CEOs are matched to firms characterized by their shareholders’ risk aversion. This leads us to predict that (i) contemporaneous (future) CEO narcissism is increasing (decreasing) in the compensation package; (ii) CEO narcissism is decreasing in shareholder risk aversion and (iii) CEO narcissism is increasing in CEO narcissism mean reversion. We test our predictions on a 10-year sample of S&P 500 CEOs, using a time-varying measure of CEO narcissism. Our empirical results provide preliminary support for all our predictions.