Miracle-dz/UniFAR-FTUs huggingface dataset:
Esc 2 and Sgs 1 Act in Functionally Distinct Branches of the Homologous Recombination Repair Pathway in Saccharomyces cerevisiae

Esc2 is a member of the RENi family of SUMO-like domain proteins and is implicated in gene silencing in Saccharomyces cerevisiae. Here, we identify a dual role for Esc2 during S-phase in mediating both intra-S-phase DNA damage checkpoint signaling and preventing the accumulation of Rad51-dependent homologous recombination repair (HRR) intermediates. These roles are qualitatively similar to those of Sgs1, the yeast ortholog of the human Bloom’s syndrome protein, BLM. However, whereas mutation of either ESC2 or SGS1 leads to the accumulation of unprocessed HRR intermediates in the presence of MMS, the accumulation of these structures in esc2 (but not sgs1) mutants is entirely dependent on Mph1, a protein that shows structural similarity to the Fanconi anemia group M protein (FANCM). In the absence of both Esc2 and Sgs1, the intra-S-phase DNA damage checkpoint response is compromised after exposure to MMS, and sgs1esc2 cells attempt to undergo mitosis with unprocessed HRR intermediates. We propose a model whereby Esc2 acts in an Mph1-dependent process, separately from Sgs1, to influence the repair/tolerance of MMS-induced lesions during S-phase.
DEPARTMENT OF ECONOMICS DISCUSSION PAPER SERIES Banking inefficiency in Central and Eastern European countries under a quadratic Loss function

This paper employs a specification of a quadratic loss function based on forwardlooking rational expectations to model the underlying dynamics of efficiency scores in the banking industry of eleven Central and Eastern European countries over the period 1998-2005. Results show that there is considerable variation in the adjustment speed to the long run equilibrium across banking systems and over time, while it also appears that the recent accession to the EU has not led to the expected increase in the speed of adjustment to the long run equilibrium. Moreover, banks’ ownership structure appears to assert an influence on the speed at which credit institutions correct their past-period inefficiency. JEL Classification: D24; G21; L25
Deep Structured Learning for Visual Relationship Detection

In the research area of computer vision and artificial intelligence, learning the relationships of objects is an important way to deeply understand images. Most of recent works detect visual relationship by learning objects and predicates respectively in feature level, but the dependencies between objects and predicates have not been fully considered. In this paper, we introduce deep structured learning for visual relationship detection. Specifically, we propose a deep structured model, which learns relationship by using feature-level prediction and label-level prediction to improve learning ability of only using feature-level predication. The feature-level prediction learns relationship by discriminative features, and the label-level prediction learns relationships by capturing dependencies between objects and predicates based on the learnt relationship of feature level. Additionally, we use structured SVM (SSVM) loss function as our optimization goal, and decompose this goal into the subject, predicate, and object optimizations which become more simple and more independent. Our experiments on the Visual Relationship Detection (VRD) dataset and the large-scale Visual Genome (VG) dataset validate the effectiveness of our method, which outperforms state-of-the-art methods.
How blockchain technology can change medicine

ABSTRACT Although the best-known use of blockchain technology (BCT) is in the field of economics and cryptocurrencies in general, its usefulness is extending to other fields, including the biomedical field. The purpose of this article is to clarify the role that BCT can play in the field of medicine. We have performed a narrative review of the literature on BCT in general and on medicine in particular. The great advantage of BCT in the health arena is that it allows development of a stable and secure data set with which users can interact through transactions of various types. This environment allows the entry and operation of clinical data without compromising other sensitive data. Another important advantage of BCT is that the entire network is decentralized and is maintained by the users themselves; thus, there is no need to rely on organizations for storage. The Blockchain code is open source and can be used, modified and revised by its users. BCT literature is scarce so far. This article describes the basics of this technology and summarizes the various aspects in which BCT could change the paradigm of current medicine. The great potential of BCT, as well as its many applications in the field of health sciences, encompasses the fields of legal medicine, research, electronic medical records, medical data analysis (big data), teaching and the regulation of payment for medical services. If technological advances continue along these lines, it could bring about a revolution in medicine as we know it.
Plasma natriuretic peptide levels and the risk of cardiovascular events and death.

BACKGROUND The natriuretic peptides are counterregulatory hormones involved in volume homeostasis and cardiovascular remodeling. The prognostic significance of plasma natriuretic peptide levels in apparently asymptomatic persons has not been established. METHODS We prospectively studied 3346 persons without heart failure. Using proportional-hazards regression, we examined the relations of plasma B-type natriuretic peptide and N-terminal pro-atrial natriuretic peptide to the risk of death from any cause, a first major cardiovascular event, heart failure, atrial fibrillation, stroke or transient ischemic attack, and coronary heart disease. RESULTS During a mean follow-up of 5.2 years, 119 participants died and 79 had a first cardiovascular event. After adjustment for cardiovascular risk factors, each increment of 1 SD in log B-type natriuretic peptide levels was associated with a 27 percent increase in the risk of death (P=0.009), a 28 percent increase in the risk of a first cardiovascular event (P=0.03), a 77 percent increase in the risk of heart failure (P<0.001), a 66 percent increase in the risk of atrial fibrillation (P<0.001), and a 53 percent increase in the risk of stroke or transient ischemic attack (P=0.002). Peptide levels were not significantly associated with the risk of coronary heart disease events. B-type natriuretic peptide values above the 80th percentile (20.0 pg per milliliter for men and 23.3 pg per milliliter for women) were associated with multivariable-adjusted hazard ratios of 1.62 for death (P=0.02), 1.76 for a first major cardiovascular event (P=0.03), 1.91 for atrial fibrillation (P=0.02), 1.99 for stroke or transient ischemic attack (P=0.02), and 3.07 for heart failure (P=0.002). Similar results were obtained for N-terminal pro-atrial natriuretic peptide. CONCLUSIONS In this community-based sample, plasma natriuretic peptide levels predicted the risk of death and cardiovascular events after adjustment for traditional risk factors. Excess risk was apparent at natriuretic peptide levels well below current thresholds used to diagnose heart failure.
A &Apos;Reciprocal Dumping&Apos; Model of International Trade

This paper develops a model in which the rivalry of oligopolistic firms serves as an independent cause of international trade. The model shows how such rivalry naturally gives rise to "dumping" of output in foreign markets, and shows that such dumping can be "reciprocal" -- that is, there may be two-way trade in the same product. Reciprocal dumpingis shown to be possible for fairly general specification of firm behaviour.The welfare effects of this seemingly pointless trade are ambiguous. On one hand, resources are wasted in the cross-handling of goods; on the other hand, increased competition reduces monopoly distortions. Surprisingly,in the case of free entry and Cournot behaviour reciprocal dumping is unanibiuously beneficial.
A novel approach for estimating Truck Factors

Truck Factor (TF) is a metric proposed by the agile community as a tool to identify concentration of knowledge in software development environments. It states the minimal number of developers that have to be hit by a truck (or quit) before a project is incapacitated. In other words, TF helps to measure how prepared is a project to deal with developer turnover. Despite its clear relevance, few studies explore this metric. Altogether there is no consensus about how to calculate it, and no supporting evidence backing estimates for systems in the wild. To mitigate both issues, we propose a novel (and automated) approach for estimating TF-values, which we execute against a corpus of 133 popular project in GitHub. We later survey developers as a means to assess the reliability of our results. Among others, we find that the majority of our target systems (65%) have TF ≤ 2. Surveying developers from 67 target systems provides confidence towards our estimates; in 84% of the valid answers we collect, developers agree or partially agree that the TF's authors are the main authors of their systems; in 53% we receive a positive or partially positive answer regarding our estimated truck factors.
A Compact Ultra-Wideband Multibeam Antenna System

A compact UWB (6–18 GHz) multibeam antenna system is proposed. Design procedures comprising of ridged coaxial waveguide, radome with lens properties, and biconical antenna are presented. A novel UWB feed network consisting of a ridged coaxial waveguide with eight inputs has been designed and optimized to achieve minimum reflections as well as desired radiation pattern over the frequency range of operation. The radiating element is a biconical antenna, redesigned and optimized to meet the requirements for radiation characteristics. Another notable improvement made by our design is to employ a radome, which not only enhances the mechanical stability of the biconical antenna and protects the structure, but also it acts as a lens that improves the directivity of the radiating element. Extensive optimization procedures have been applied to all parts of the antenna system to achieve the desired performance. The whole system has been simulated using HFSS full-wave simulator. The measurement results of the fabricated system are in good agreement with simulations.
Locality Preserving Projection Based on F-norm

Locality preserving projection (LPP) is a well-known method for dimensionality reduction in which the neighborhood graph structure of data is preserved. Traditional LPP employ squared F-norm for distance measurement. This may exaggerate more distance errors, and result in a model being sensitive to outliers. In order to deal with this issue, we propose two novel F-norm-based models, termed as F-LPP and F-2DLPP, which are developed for vector-based and matrix-based data, respectively. In F-LPP and F-2DLPP, the distance of data projected to a low dimensional space is measured by F-norm. Thus it is anticipated that both methods can reduce the influence of outliers. To solve the F-norm-based models, we propose an iterative optimization algorithm, and give the convergence analysis of algorithm. The experimental results on three public databases have demonstrated the effectiveness of our proposed methods.
Changes in the structure and prediction of earnings in Chinese state enterprises during the economic reform

The question of payment and its determination has in China exposed tensions between socially embedded values and the functional requirements for modernization. These can be expressed respectively in terms of a traditional model, which predicts that earnings will be higher for people who are older, loyal to their unit and male, and a reform model, which predicts that earnings will be higher for people who have formal qualifications, have relevant training, hold positions of greater responsibility and are performing well and/or belong to a successful enterprise. The postulates of these two models, and the extent to which their relevance has changed with China's economic reform, are examined in the light of data on 144 job-holders in six Beijing state-owned enterprises, collected at two points in time, namely October 1985 and March 1990. The results indicate that in 1985 factors identified by the traditional model, especially age, were the most important predictors of earnings. By 1990 some movement towards .
Creating a Toxic Neighborhood in Los Angeles County

The city of Commerce, a largely industrial and Latino city east of Los Angeles, contains a disproportionately high concentration of manufacturers that emit toxic chemicals. The coincidence of a minority population and toxic sites is a classic example of environmental inequity. The authors seek to understand why industry located in this community. A historical investigation of the development of a hazardous community suggests that demographics alone are not responsible for the concentration of manufacturing in Commerce. The zoning decisions of the Los Angeles County Regional Planning Commission in the 1920s and 1930s set the pattern of industrialization in Commerce.
Depression and immunity: a meta-analytic review.

A meta-analysis indicated that clinical depression was associated with several large alterations in cellular immunity. Analyzing only methodologically sound studies, reliable immune alterations included lowered proliferative response of lymphocytes to mitogens (effect size rs = .24-.45), lowered natural killer cell activity (r = .28), and alterations in numbers of several white blood cell populations (rs = .11-.77). Immune alterations were greater in both older and hospitalized samples. There was also evidence of a linear relation between intensity of depressive affect and indicators of cellular immunity. Estimates of sample sizes needed to detect reliable effects for each immune outcome are provided. How neuroendocrine mechanisms or health practices might link depression to immunity is discussed, and design features needed to better understand these pathways are specified.
Identifying the Influential Bloggers: A modular approach based on Sentiment Analysis

The social web provides an easy and quick medium for public communication and online social interactions. In the web log, short as a blog, the bloggers share their views in the form of creating and commenting on blog posts. The bloggers who influence other users in a blogging community are known as the influential bloggers. Identification of such influential bloggers has vast applications in advertising, online marketing and e-commerce. This paper investigates the problem of identifying influential bloggers and presents a model which consists of two modules: Activity and Recognition. The activity module takes into account a blogger's activity and recognition module measures a blogger's influence in his/her social community. The integration of activity and recognition modules identifies the active as well as influential bloggers. The proposed model, MIBSA (Model to find Influential Bloggers using Sentiment Analysis), takes into account the existing and novel features of sentiment expressed in content generated by a blogger. The model is evaluated against the existing standard models using the real world blogging data. The results confirm that sentiment expressed in blog content plays an important role in measuring a blogger's influence and should be considered as a feature for finding the top influential bloggers in the blogosphere.
Evidence-Based Education : Case Study of Educational Data Acquisition and Reuse

There must be as many concrete indicators as possible in education, which will become signposts. People will not be confident about their learning and will become confused with tenuous instruction. It is necessary to clarify what they can do and what kinds of abilities they can improve. This paper describes a case of evidence-based education that acquires educational data from students’ study activities and not only uses the data to enable instructors to check the students’ levels of understanding but also improve their levels of performance. Our previous research called discussion mining was specifically used to collect various data on meetings (statements and their relationships, presentation materials such as slides, audio and video, and participants’ evaluations of statements). This paper focuses on student presentations and discussions in laboratory seminars that are closely related to their research activities in writing their theses. We propose a system that supports tasks to be achieved in research activities and a machine-learning method to make the system sustainable for long-term operation by automatically extracting essential tasks. We conducted participant-based experiments that involved students and computer-simulation-based experiments to evaluate how efficiently our proposed machine-learning method updated the task extraction model. We confirmed from the participantbased experiments that informing responsible students of tasks that were automatically extracted on the system we developed improved their awareness of the tasks. Here, we also explain improvements in extraction accuracy and reductions in labeling costs with our method and how we confirmed its effectiveness through computer simulations.
Organization and remodeling of the olivocerebellar climbing fiber projection

Climbing fibers, terminal portions of the axons of inferior olive neurons, form strong synaptic connections to Purkinje cells in an exclusive one-to-one relationship. This projection is established during development by drastic reshaping in each climbing fiber and in overall axonal arborization. Early climbing fibers form loose ‘creeper’-type terminal arbors that seem to make weak contact with many Purkinje cells in the first postnatal week. The terminal arbor then becomes focused on a single Purkinje cell with the aggregation of swellings (‘transitional’ type), and eventually tightly surrounds the Purkinje cell soma (‘nest’ type) in the second postnatal week. The terminal arbor is then displaced upward to the stem of the apical dendrite of the Purkinje cell (‘capuchon’ or ‘hood’) and eventually to the proximal portion of the dendritic tree (mature climbing fiber). Single-axon morphology in rats has shown that olivocerebellar axons in the creeper stage branch more frequently and have many more climbing fibers than those in adults. The climbing fibers that originate from an axon are largely organized into microzones as in adults. Concomitant with this remodeling of climbing fibers, the number of climbing fibers per olivocerebellar axon is significantly decreased by the putative retraction of climbing fibers during development from the creeper to nest stage. Due to additional retraction after the nest stage, an olivocerebellar axon in an adult has about seven climbing fibers. The above morphological remodeling and retraction during development can be closely compared to the changes in climbing fiber-Purkinje cell synaptic interaction observed in rats and mice. Generation and aggregation of the swellings in the terminal arbor between the creeper and nest stages are correlated with maturation of the synaptic connection. The decrease in climbing fibers in the same and following periods is correlated with the elimination of overabundant synapses to establish one-to-one connections.
The Carbon Neutral Public Sector

Abstract This paper argues for research into the effectiveness of government strategies for a ‘carbon neutral public sector’. We review initiatives in three OECD countries: New Zealand, Australia and the UK. In all jurisdictions, government agencies have consistently stressed ‘leading by example’ as a rationale for adoption. ‘Direct mandate’ by the Prime Minister (NZ); ‘organic development’ from wider central government sustainability initiatives (UK); and a more ‘laissez faire’ approach by Australian Federal and State Governments, were identified as the general pathways leading to implementation. Our assessment indicates: a lack of understanding of the implementation process for carbon neutrality; a need to identify and critically examine the ‘offset threshold’ at which mitigation efforts cease and offsetting is adopted; an absence of any evaluation of the ‘leading by example’ rationale; a lack of inter-country comparisons; a gap in understanding the relationship with economic and social aspects of sustainability; and a need to evaluate the utility of core government departments as the focus of carbon accounting. We urge colleagues to consider research in this area with a view to contributing to the interdisciplinary solutions which we believe are required.
Purchasing Power Parity-evidence from a new panel test

This paper uses a recently suggested test for unit roots in panels of time series data (Maddala and Wu, Oxford Bulletin of Economics and Statistics, 61, 631-52, 1999) to consider the Purchasing Power Parity hypothesis. The major innovation of this test is that it allows both the testing of unit root null, using the ADF test, and the stationarity null, using the KPSS test. It is found that the results are inconsistent, suggesting that either alternative hypotheses to a unit root may need to be considered or that panel based testing in this particular context may be of limited value.
A Combined Process of Liftoff and Printing for the Fabrication of Scalable Inkjet Printed Microstructures on a Flexible Substrate

In this paper, a combined process of liftoff and printing (CPLoP) techniques is introduced to realize size-scalable printed silver microstructures with line widths ranging from 5 to 70 μm and resistivities of ~9.8 μΩ · cm on a flexible polyimide substrate via thermal sintering at 300 °C for 30 min. In addition, a printed interdigitated capacitor with an electrode line width and spacing of 10 μm and a printed spiral square inductor with a 10-μm line width and 5-μm spacing in an area of 1 mm2 have been successfully demonstrated with an area capacitance and inductance of 0.43 pF/mm2 at 10 KHz and 1.054 μH/mm2 up to 100 KHz, respectively, which are the orders of magnitude performance improvement in comparison with the contemporary inkjet-printed capacitors and inductors. Owing to the significant reduction of energy demand in processing tools and waste generation in processing materials, the results have revealed that the CPLoP process can facilitate the advancement of printing manufacture technology for microelectronics applications.
Computer-aided scheme for functional index computation of left ventricle in cardiac CTA: segmentation and partitioning of left ventricle

Cardiac functional indices, such as ejection fraction and regional wall motion/ thickening, are commonly used for assessing the contractility and functionality of the heart in clinical practice. An important step for computer-aided determination of functional indices is the automated segmentation of the heart from computed tomography angiography (CTA) and the partitioning of the left ventricle into 16 segments. We develop a fully automatic scheme which not only segments the whole heart from cardiac CTA images, but also partitions the left ventricle, including the blood pool and myocardium, into 16 segments of bull’s eye plot. The segmentation is based on image registration and atlas propagation techniques, whereas the bull’s eye plot is first obtained through atlas propagation and then further improved to correct inconsistency across different subjects, uneven size for each segment and “zig-zag” edges between them. In this preliminary study, a cohort of ten clinical CTA data was employed to compute and evaluate the regional functional indices as well as the global indices.