Miracle-dz/UniFAR-FTUs huggingface dataset:
Market Structure, Financial Intermediation and Riskiness of Banks: Evidence from Asia Pacific

From a sample of commercial banks in Asia Pacific over the 1994-2009 period, this study highlights that banks in less competitive markets exhibit lower loan growth and higher instability. Such instability is further followed by a decline in deposit growth, suggesting that Asian banks are also subject to indirect market discipline mechanisms through bank market structure. This study therefore sheds light on the importance of enhancing bank competition to overcome bank risk and strengthen financial intermediation. This study also advocates greater reliance on market discipline to promote bank stability.
Using two dyes to observe the competition of Ca2+ trapping mechanisms and their effect on intracellular Ca2+ signals

The specificity and universality of intracellular signals rely on the variety of spatio-temporal patterns that the concentration can display. liberation through inositol 1,4,5-trisphosphate receptors () is key for this variety. In this paper, we study how the competition between buffers of different kinetics affects signals that involve release through . The study also provides insight into the underlying spatial distribution of the channels that participate in the signals. Previous works on the effects of buffers have drawn conclusions ‘indirectly’ by observing the -bound dye distributions in the presence of varying concentrations of exogenous buffers and using simulations to interpret the results. In this paper, we make visible the invisible by observing the signals simultaneously with two dyes, and , each of which plays the role of a slow or fast buffer, respectively. Our observations obtained for different concentrations of highlight the dual role that fast buffers exert on the dynamics, either reducing the intracluster channel coupling or preventing channel inhibition and allowing the occurrence of relatively long cycles of release. Our experiments also show that signals with relatively high release rates remain localized in the presence of large concentrations, while the mean speed of the elicited waves increases. We interpret this as a consequence of the more effective uncoupling between clusters as the slow dye concentration increases. Combining the analysis of the experiments with numerical simulations, we also conclude that release not only occurs within the close vicinity of the centers of the clearly identifiable release sites ( clusters) but there are also functional in between them.
Delivering CRISPR: a review of the challenges and approaches

Abstract Gene therapy has long held promise to correct a variety of human diseases and defects. Discovery of the Clustered Regularly-Interspaced Short Palindromic Repeats (CRISPR), the mechanism of the CRISPR-based prokaryotic adaptive immune system (CRISPR-associated system, Cas), and its repurposing into a potent gene editing tool has revolutionized the field of molecular biology and generated excitement for new and improved gene therapies. Additionally, the simplicity and flexibility of the CRISPR/Cas9 site-specific nuclease system has led to its widespread use in many biological research areas including development of model cell lines, discovering mechanisms of disease, identifying disease targets, development of transgene animals and plants, and transcriptional modulation. In this review, we present the brief history and basic mechanisms of the CRISPR/Cas9 system and its predecessors (ZFNs and TALENs), lessons learned from past human gene therapy efforts, and recent modifications of CRISPR/Cas9 to provide functions beyond gene editing. We introduce several factors that influence CRISPR/Cas9 efficacy which must be addressed before effective in vivo human gene therapy can be realized. The focus then turns to the most difficult barrier to potential in vivo use of CRISPR/Cas9, delivery. We detail the various cargos and delivery vehicles reported for CRISPR/Cas9, including physical delivery methods (e.g. microinjection; electroporation), viral delivery methods (e.g. adeno-associated virus (AAV); full-sized adenovirus and lentivirus), and non-viral delivery methods (e.g. liposomes; polyplexes; gold particles), and discuss their relative merits. We also examine several technologies that, while not currently reported for CRISPR/Cas9 delivery, appear to have promise in this field. The therapeutic potential of CRISPR/Cas9 is vast and will only increase as the technology and its delivery improves.
An exploration of the lived experience of professional grief among occupational therapists working in palliative care settings

BACKGROUND/AIM Occupational therapists who work in palliative care are frequently exposed to the experience of death and dying. Previous occupational therapy research has offered insight into factors that influence feelings relating to death and dying and associated coping strategies. However, existing literature is dated and has not specifically examined the concept of grief. This study addresses this gap in knowledge by exploring the lived experience of professional grief among occupational therapists working in palliative care settings. METHODS Semi-structured interviews were conducted with six Australian palliative care occupational therapists. The data were collected and analysed using an interpretive phenomenological approach. RESULTS Four interrelated themes were identified as core to the lived experience of professional grief among participants. These included; 'knowledge of self', 'giving permission for connections and feelings', 'filtering experience' and 'being present at work and at home'. CONCLUSION Considered in combination, these themes offer a guide for therapists to explore their own experience of and responses to professional grief and, in doing so, foster the development of personalised management strategies.
Cell-Free Protein Synthesis From Fast-Growing Vibrio natriegens

Vibrio natriegens constitutes one of the fastest-growing nonpathogenic bacteria and a potential novel workhorse for many biotechnological applications. Here, we report the development of a Vibrio-based cell-free protein synthesis system (CFPS). Specifically, up to 0.4 g L-1 eGFP could be successfully synthesized in small-scale batch reactions using cell-free extract obtained from fast-growing V. natriegens cultures. Versatile CFPS system characterization attained by combining the analyses of key metabolites for translation and ribosomes revealed limitations regarding rRNA stability and critical substrate consumption (e.g., amino acids). Alternatively, rRNA showed increased stability by inducing Mg2+homeostasis in the reaction. Although the enormous translation capacity of the CFPS system based on the available ribosome concentration could not yet be fully exploited, its potential was successfully demonstrated by activating an endogenous transcription unit with V. natriegensRNA polymerase (RNAP) for protein expression. This allowed the use of in vitro screening for promoter strength, a critical factor for efficient gene expression in vitro and in vivo. Three different promoters were tested and output signals corresponded well with the expected affinity for V. natriegens RNAP. This established CFPS toolbox may provide a foundation to establish V. natriegens as a valuable platform in biotechnology as well as synthetic biology.
Abstract Meaning Representation for Paraphrase Detection

Abstract Meaning Representation (AMR) parsing aims at abstracting away from the syntactic realization of a sentence, and denote only its meaning in a canonical form. As such, it is ideal for paraphrase detection, a problem in which one is required to specify whether two sentences have the same meaning. We show that naïve use of AMR in paraphrase detection is not necessarily useful, and turn to describe a technique based on latent semantic analysis in combination with AMR parsing that significantly advances state-of-the-art results in paraphrase detection for the Microsoft Research Paraphrase Corpus. Our best results in the transductive setting are 86.6% for accuracy and 90.0% for F_1 measure.
Semantic search extension based on polish wordnet relations in business document exploration

This paper addresses the problem of building a specialized semantic search engine for documents collected in small or medium-sized enterprises. It presents the results of a project that brought together computer scientists and entrepreneurs for the purpose of providing a common perspective regarding the implementation in company practice of a search engine based on the Polish version of Word-Net semantic relations. The core functionality of the search engine module is provided along with a discussion on how to arrange semantic similarity structures so as to ensure the efficient generation of relevant search engine results. Some patterns and similarity coefficients for hyperonymy, hyponymy, holonymy and meronymy relations are presented and analyzed for the purpose of producing relationship structures. Finally, the architecture of the system that can be implemented in a company is outlined.
Tracking interval changes of pulmonary nodules using a sequence of three-dimensional thoracic images

We are developing a computerized approach to characterize pulmonary nodules through quantitative analysis between sequential 3-D thoracic images. In this approach the registration procedure of sequential 3-D pulmonary images consisted of two transformation steps: the rigid transformation step between two sequential 3-D thoracic CT images and the affine transformation step between two sequential region-of-interest (ROI) images including the pulmonary nodule. In both transformation step, the normalized mutual information was used as a voxel-based similarity measure. After the registration procedure, the 3-D pulmonary nodule image was segmented from the ROI image by a deformable surface method. The curvatures of each voxel in the nodule were computed directly from the gray-level 3-D image. Through curvatures a local description of the lesion was obtained by using shape index, curvedness, and CT value. Based on this local description of the nodule, the evolution of geometrical parameters was tracked through the time interval. Additionally, to characterize globally the evolution of the local description, the shape and the curvedness spectra were introduced. The interval changes of the lesion were traced in the feature spaces. The application results of our method to the sequence of 3-D thoracic images demonstrated that the interval changes of pulmonary nodules could be made visible. © (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Conservation of the RB1 gene in human and primates

Mutations in the RB1 gene are associated with retinoblastoma, which has served as an important model for understanding hereditary predisposition to cancer. Despite the great scrutiny that RB1 has enjoyed as the prototypical tumor suppressor gene, it has never been the object of a comprehensive survey of sequence variation in diverse human populations and primates. Therefore, we analyzed the coding (2,787 bp) and adjacent intronic and untranslated (7,313 bp) sequences of RB1 in 137 individuals from a wide range of ethnicities, including 19 Asian Indian hereditary retinoblastoma cases, and five primate species. Aside from nine apparently disease‐associated mutations, 52 variants were identified. They included six singleton, coding variants that comprised five amino acid replacements and one silent site. Nucleotide diversity of the coding region (π=0.0763±1.35 × 10−4) was 52 times lower than that of the noncoding regions (π=3.93±5.26 × 10−4), indicative of significant sequence conservation. The occurrence of purifying selection was corroborated by phylogeny‐based maximum likelihood analysis of the RB1 sequences of human and five primates, which yielded an estimated ratio of replacement to silent substitutions (ω) of 0.095 across all lineages. RB1 displayed extensive linkage disequilibrium over 174 kb, and only four unique recombination events, two in Africa and one each in Europe and Southwest Asia, were observed. Using a parsimony approach, 15 haplotypes could be inferred. Ten were found in Africa, though only 12.4% of the 274 chromosomes screened were of African origin. In non‐Africans, a single haplotype accounted for from 63 to 84% of all chromosomes, most likely the consequence of natural selection and a significant bottleneck in effective population size during the colonization of the non‐African continents. Hum Mutat 25:396–409, 2005. © 2005 Wiley‐Liss, Inc.
A Comparison of Composite Reliability Estimators

Coefficient omega and alpha are both measures of the composite reliability for a set of items. Unlike coefficient alpha, coefficient omega remains unbiased with congeneric items with uncorrelated errors. Despite this ability, coefficient omega is not as widely used and cited in the literature as coefficient alpha. Reasons for coefficient omega’s underutilization include a limited knowledge of its statistical properties. However, consistent efforts to understand the statistical properties of coefficient omega can help improve its utilization in research efforts. Here, six approaches for estimating confidence intervals for coefficient omega with unidimensional congeneric items were evaluated through a Monte Carlo simulation. The evaluations were made through simulation conditions that mimic realistic conditions that investigators are likely to face in applied work, including items that are not normally distributed and small sample size(s). Overall, the normal theory bootstrap confidence interval had the best performance across all simulation conditions that included sample sizes less than 100. However, most methods had sound coverage with sample sizes of 100 or more.
Optimization of a Dual-Band Wireless Power and Data Telemetry System Using Genetic Algorithm

Inductively coupled coils are commonly used in implanted biomedical electronic devices for wireless power and data transmission. The design challenges include high power transmission efficiency, high data rate, and overall low power operation. This article uses genetic algorithm for the optimization which has the advantages of global optimization, capability of handling multiple targets, and providing multiple solutions. —Shuenn-Yuh Lee, National Cheng Kung University
#NonDicevoSulSerio at SemEval-2018 Task 3: Exploiting Emojis and Affective Content for Irony Detection in English Tweets

This paper describes the participation of the #NonDicevoSulSerio team at SemEval2018-Task3, which focused on Irony Detection in English Tweets and was articulated in two tasks addressing the identification of irony at different levels of granularity. We participated in both tasks proposed: Task A is a classical binary classification task to determine whether a tweet is ironic or not, while Task B is a multiclass classification task devoted to distinguish different types of irony, where systems have to predict one out of four labels describing verbal irony by clash, other verbal irony, situational irony, and non-irony. We addressed both tasks by proposing a model built upon a well-engineered features set involving both syntactic and lexical features, and a wide range of affective-based features, covering different facets of sentiment and emotions. The use of new features for taking advantage of the affective information conveyed by emojis has been analyzed. On this line, we also tried to exploit the possible incongruity between sentiment expressed in the text and in the emojis included in a tweet. We used a Support Vector Machine classifier, and obtained promising results. We also carried on experiments in an unconstrained setting.
Music Genre Classification With Neural Networks: An Examination Of Several Impactful Variables

There have been several attempts to classify music with content-based machine learning approaches. Most of these projects followed a similar procedure with a Deep Belief Network. In this project, we examined the performance of convolutional neural networks (CNN) and recurrent neural networks (RNN) as well as other components of a classification architecture, such as the choice of dataset, pre-processing techniques, and the sample size. Under a controlled environment, we discovered that the most successful architecture was a Melspectrogram combined with a CNN. Although our results fell behind the state-of-the-art performance, we outperform other music classification studies that use a CNN by a large margin. By performing binary classification, we also discovered individuality across genres that caused inconsistent performance.
Cognitive behavior therapy for older adults with insomnia and depression: a randomized controlled trial in community mental health services

Study Objectives To investigate whether cognitive behavior therapy was effective for older adults with comorbid insomnia and depression in a community mental health setting, and explore whether an advanced form of cognitive behavior therapy for insomnia produced better outcomes compared to a standard form of cognitive behavior therapy for insomnia. Methods An 8-week randomized controlled clinical trial was conducted within community mental health services, Victoria, Australia. Seventy-two older adults (56% female, M age 75 ± 7 years) with diagnosed comorbid insomnia and depression participated. Three conditions were tested using a group therapy format: cognitive behavior therapy for insomnia (CBT-I, standard), cognitive behavior therapy for insomnia plus positive mood strategies (CBT-I+, advanced), psychoeducation control group (PCG, control). The primary outcomes were insomnia severity (Insomnia Severity Index) and depression severity (Geriatric Depression Scale). Primary and secondary measures were collected at pre (week 0), post (week 8), and follow-up (week 20). Results CBT-I and CBT-I+ both generated significantly greater reductions in insomnia and depression severity compared to PCG from pre to post (p < .001), which were maintained at follow-up. Although the differences between outcomes of the two treatment conditions were not statistically significant, the study was not sufficiently powered to detect either superiority of one treatment or equivalence of the two treatment conditions. Conclusion CBT-I and CBT-I+ were both effective at reducing insomnia and depression severity for older adults. Mental health services that deliver treatment for comorbid insomnia with cognitive behavior therapy may improve recovery outcomes for older adults with depression. Trial Registration: Australian and New Zealand Clinical Trials Registry (ANZCTR); URL: https://www.anzctr. org.au; Trial ID: ACTRN12615000067572; Date Registered: December 12, 2014.
The Role of Micro‐Ribonucleic Acids in Legumes with a Focus on Abiotic Stress Response

Legumes are special group of N‐fixing plants that are an essential component of cropping system and important source of food and feed for human and animal consumption. Like other crops, the productivity of legumes is threatened by environmental stresses caused due to global climate change. Abiotic stress tolerance is complex trait involving a suite of genes, the expression of which is controlled by transcription factors including gene and/or polypeptide sequences. Recently, micro‐ribonucleic acids (miRNAs) have been increasingly recognized for their role in regulating the synthesis of polypeptides from different messenger ribonucleic acids (mRNAs) including those that act as transcription factors. This review summarizes the current knowledge on the role of different miRNAs in response to main abiotic stresses in legumes. We found consistent as well as conflicting results within and between different legume species. This highlights that we have barely scratched the surface and very comprehensive and targeted experiments will be required in future to underpin the role of miRNAs in controlling the expression of important genes associated with abiotic stress tolerances.
Nethammer: Inducing Rowhammer Faults through Network Requests

In this paper, we present Nethammer, a remote Rowhammer attack without a single attacker-controlled line of code on the targeted system, i.e., not even JavaScript. Nethammer works on commodity consumer-grade systems that either are protected with quality-of-service techniques like Intel CAT or that use uncached memory, flush instructions, or non-temporal instructions while handling network requests (e.g., for interaction with the network device). We demonstrate that the frequency of the cache misses is in all three cases high enough to induce bit flips. Our evaluation showed that depending on the location, the bit flip compromises either the security and integrity of the system and the data of its users, or it can leave persistent damage on the system, i.e., persistent denial of service. We invalidate threat models of Rowhammer defenses building upon the assumption of a local attacker. Consequently, we show that most state-of-the-art defenses do not affect our attack. In particular, we demonstrate that target-row-refresh (TRR) implemented in DDR4 has no aggravating effect on local or remote Rowhammer attacks.
Overlapping Community Detection by Node-Weighting

Community detection is an important task with great practical value for understanding the structure and function of complex networks. However, in many social networks, a node may belong to more than one community. Thus, the detection of overlapping community is more significant. The local expansion algorithm using seeds to find overlapping communities is becoming increasingly popular, but how to choose suitable seeds and expand the local communities effectively is still a great challenge. In this paper, we propose a new overlapping community detection algorithm based on node-weighting (OCDNW). The main idea of the algorithm is to find a good seed and then greedily expand it based on an improved community quality metric. Finally it optimizes the community structure to ensure the quality of community partitioning. Experimental results on synthetic and real world networks prove that the proposed algorithm can detect overlapping communities successfully and outperform other state-of-the-art methods.
Scalable Wide and Deep Learning for Computer Assisted Coding

In recent years the use of electronic medical records has accelerated resulting in large volumes of medical data when a patient visits a healthcare facility. As a first step towards reimbursement healthcare institutions need to associate ICD-10 billing codes to these documents. This is done by trained clinical coders who may use a computer assisted solution for shortlisting of codes. In this work, we present our work to build a machine learning based scalable system for predicting ICD-10 codes from electronic medical records. We address data imbalance issues by implementing two system architectures using convolutional neural networks and logistic regression models. We illustrate the pros and cons of those system designs and show that the best performance can be achieved by leveraging the advantages of both using a system combination approach.