Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-Independent Space Partitionings for Summaries

Histograms are a standard tool in data management for describing multidimensional data. It is often convenient or even necessary to define data independent histograms, to partition space in advance without observing the data itself. Specific motivations arise in managing data when it is not suitable to frequently change the boundaries between histogram cells. For example, when the data is subject to many insertions and deletions; when data is distributed across multiple systems; or when producing a privacy-preserving representation of the data. The baseline approach is to consider an equiwidth histogram, i.e., a regular grid over the space. However, this is not optimal for the objective of splitting the multidimensional space into (possibly overlapping) bins, such that each box can be rebuilt using a set of non-overlapping bins with minimal excess (or deficit) of volume. Thus, we investigate how to split the space into bins and identify novel solutions that offer a good balance of desirable properties. As many data processing tools require a dataset as an input, we propose efficient methods how to obtain synthetic point sets that match the histograms over the overlapping bins.
Effect of Single-Layer MoS2 on the Geometry, Electronic Structure, and Reactivity of Transition Metal Nanoparticles

We present results of ab initio density functional theory (DFT) based calculations of the geometry, electronic structure, and reactivity of subnanometer-sized (29-atom) transition metal nanoparticles (NPs) (Cu29, Ag29, and Au29) supported on single-layer MoS2. As compared to its pristine form, defect-laden MoS2 (with a S vacancy row) has relatively larger effect on the above properties of the NPs. The NPs bind more strongly on defect-laden than on pristine MoS2 (in the order Cu29 > Ag29 > Au29), confirming the important role of vacancies in stabilizing the NPs on the support. The presence of vacancies also leads to an increase in charge transfer from the NPs to MoS2 (with the same elemental trend as for their binding energy) and to a shift of the d-band center of the NPs further toward the Fermi level, in turn influencing their propensity toward chemical activity. We examine the adsorption and dissociation of O2 as the prototype reactions and find that there is no barrier for O2 to adsorb on top of an ato.
Understanding Trigger-Action Programs Through Novel Visualizations of Program Differences

Trigger-action programming (if-this-then-that rules) empowers non-technical users to automate services and smart devices. As a user’s set of trigger-action programs evolves, the user must reason about behavior differences between similar programs, such as between an original program and several modification candidates, to select programs that meet their goals. To facilitate this process, we co-designed user interfaces and underlying algorithms to highlight differences between trigger-action programs. Our novel approaches leverage formal methods to efficiently identify and visualize differences in program outcomes or abstract properties. We also implemented a traditional interface that shows only syntax differences in the rules themselves. In a between-subjects online experiment with 107 participants, the novel interfaces better enabled participants to select trigger-action programs matching intended goals in complex, yet realistic, situations that proved very difficult when using traditional interfaces showing syntax differences.
The Role of Fiscal Dependency in Political Development

To the best of our knowledge, the empirical corpus of work on the origins and persistence of democracy has not evaluated the impact of governments' fiscal independence from peoples' taxes on the quality of democracy. Our proxy for fiscal independence is the component 1C titled "government enterprises and investments" taken from the Economic Freedom of the World index. Component 1C measures in a given country the fraction of total investment that is supplied by the government and state-owned enterprises. A higher fraction corresponds to greater fiscal independence. The econometric analysis employing a variety of IV estimators, which includes Lewbel (2012) generated instruments, reveals a conditional negative, robust, and statistically significant effect of fiscal independence on the degree of democracy. The study also unveils a statistically and economically significant impact of fiscal independence on variables inherent to democracy, such as judicial independence and freedom of the press, as well as on human capital, a proximate determinant of democracy. These findings account for the observed heterogeneity in the potentially confounding effects of democratic rule determinants commonly used in the democratization literature. In particular, the study allows for years of education, ethno-linguistic fractionalization, the individualism-collectivism cultural trait, legal origin, risk of expropriation protection, income inequality, geographical characteristics such as latitude and availability of oil reserves, and fixed effects to control for unobserved heterogeneity bias induced by time-invariant variables at the continent level. The evidence uncovered suggests a novel mechanism under-girding the onset, and more crucially, the persistence of democratic rule. The unveiled finding on fiscal dependency is congruous with landmark historical events such as the English Glorious Revolution as well as the tardier emergence of democracy in continental Europe. Similarly, our findings cast light on the modern heterogeneity of democratic outcomes. Specifically, results inform the flourishing Western democracies experience, and the absence or low levels of democracy among countries where governments are owners of revenue-generating companies or recipients of substantial tax revenues paid by private or state-owned corporations. Conspicuous examples of nations, with governments mostly fiscally independent, are Saudi Arabia and Venezuela.
Generating Summaries of Multiple Technical Articles

The research on document summarization has been becoming attractive and important because of the explosive increase of the scientific information. In this paper, we try to develop a system framewo rk that focuses on performing a summarization of multiple papers on a specific domain which is considered more useful for reader to grasp the outline of a research domain.
GIDEON REGALADO ASSESSMENT OF THE PATELLOFEMORAL JOINT IN CHILDREN AND ADOLESCENTS BY KINEMATIC MRI IMAGING AND BY CLINICAL EVALUATION

Due to the complexity of the patellofemoral joint problems in children and adolescents, its diagnosis remains a challenge. The introduction of kinetic MRI (KINE-MRI), however, has made it possible to dynamically investigate the patellofemoral joint. This thesis consists of three studies. The 1st study aims to validate the applicability of KINEMRI in children and adolescents. Of the twenty-nine patients who underwent a KINEMRI scan, nineteen patients had objective unilateral patellar dislocations and ten had signs and symptoms compatible with patellofemoral instability. Ten healthy subjects aged 11-16 years were recruited for comparison. Both knees of the patients were examined and the study’s parameters included the following: 1) bisect offset (BSO) 2) lateral patellar displacement (LPD) 3) patellar tilt angle (PTA) 4) sulcus angle (SA) and 5) Insall–Salvati Index (ISI) at 0, 10, 20 and 30 degrees of flexion. The subjects were divided into three groups: Group 1: knee with patellar dislocation or affected knee (AKG) (n = 29), Group 2: knee without patellar dislocation or unaffected knees (UAKG) (n=26), and Group 3: healthy knees (HKG) (n=19). The study proved that the KINEMRI’s parameters are reproducible in children and adolescents. In the 2nd study, thirtysix patients with primary patellar dislocation were randomized into two groupings: a) conservative treatment group and b) operative treatment group. They were followed up prospectively for 6 years. The study proved that there were fewer re-dislocations and better functioning in the primary operative treatment group (33%) than that of the conservative treatment group (73%). The 3rd study consisted of taking a KINE-MRI measurement of TT-TG distances in adolescents. Thirteen healthy, 11-17-year-old subjects (8 boys and 5 girls) were studied using Tesla 3.0 MRI at 30 to 0 degrees angles. The study proved that the TT-TG distance decreased in greater flexion but increased progressively towards full extension. At 0° of flexion, the mean TT-TG distance was 16.5 mm (SD 4.7) and at 30° of flexion, the mean was 11.2 mm (SD 2.4).
Antagonistic Effects of Vasotocin on Parental Behavior in Convict Cichlids

Antagonistic effects of vasotocin on parental behavior in convict cichlids Sub Title Author 篠塚, 一貴(Shinozuka, Kazutaka) 渡辺, 茂(Watanabe, Shigeru) Publisher Centre for Advanced Research on Logic and Sensibility The Global Centers of Excellence Program, Keio University Publication year 2009 Jtitle CARLS series of advanced study of logic and sensibility Vol.2, (2008. ) ,p.143149 Abstract Notes Part 1: Brain and Evolution Genre Research Paper URL https://koara.lib. keio.ac. jp/xoonips/modules/xoonips/detail.php? koara_id=KO12002001-2009033 1-0143
The Influence of Perceptions of Risks and Benefits on the Continuity of Use of Fintech Services

New technologies have been driving the global financial market, including fintech companies, which provide disruptive financial services in which information technology is the key factor. The objective of this study is to identify which factors most influence intentions to continue using these companies’ products. To achieve this, research by Ryu (2018) was replicated. Our adopted model evaluates the weight of seven factors composing two latent variables – perceived risk and perceived benefit – in the continuity of use of these services. The data collection was performed through an electronic survey, distributed through social networks during May and June of 2019. The main results confirmed seven of the eleven initial hypotheses, highlighting that the perceived benefits, especially the economic ones, were relevant to early adopters and seamless transactions were relevant for late adopters. Surprisingly, perceived risk was not a determinant of continuance intention. One of the contributions of this study is that it indicates some possible demographic and behavioral characteristics of Brazilian fintech consumers, opening up space for a better understanding of the market and service improvements.
Meta-Analysis of the Impact of Adoption of IFRS on Financial Reporting Comparability, Market Liquidity, and Cost of Capital

A large number of empirical studies have addressed the effects of adoption of IFRS, but the results have been mixed. We use a meta-analysis of 55 empirical studies with 1,259 effect sizes to determine the impact of adoption of IFRS on financial reporting comparability, market liquidity, cost of equity and cost of debt. This approach provides an objective view of the empirical results, in contrast to narrative reviews, which offer subjective conclusions. We find that IFRS adoption has increased financial reporting comparability, market liquidity, and reduced cost of equity. For cost of debt, decrease is observed only for voluntary adoption. Our meta-regression analysis shows how the results differ across mandatory and voluntary adoption of IFRS and that the measurement choices, type of control variables, study design, and strength of results explain the variation in the observed effect of adoption of IFRS. We emphasise the importance of these study characteristics and call for further studies using more recent data, on the debt market, and the long-term effect of IFRS adoption. This study should be of interest to regulators and policymakers as they are expected to assess the impacts of adoption of IFRS.
ECONOMIC IMPLICATION OF CLIMATE CHANGE ON FARMING IN KAILAHUN DISTRICT, SIERRA LEONE

This study presents the economic implications of climate change on the farming system in kailahun District of Sierra Leone. The country’s economic and employment mainly depend on agricultural production. This research is to investigate the economic implications of climate change through examining the way climate change affects farmers and finding out the constraints that exacerbates vulnerability of the farming system. The study adopted administration of questionnaires and focus group discussion to present and analyse the information. This study reveals a good scientific understanding of climate change as well as coordinated actions at both the national and global levels. Human activities should be tailored in a more environmental friendly manner in coping with a changing climate as the research reveals the economic impacts on farming in Kailahun District. Poverty, financial insecurity, fall in GDP and change in rainfall pattern are the main factors affect farm products. Less crop yield in 2013 as compared to 2008 accounted for 65%. Fall in GDP’’ accounted for 55% while poverty stand out to be the main constrain that exacerbate climate vulnerability with 41%. Financial insecurity accounted for 22.5% as the main impact of climate change on farming in Kailahun District
Towards Virtualization-Agnostic Latency for Time-Sensitive Applications

As time-sensitive applications are deployed spanning multiple edge clouds, delivering consistent and scalable latency performance across different virtualized hosts becomes increasingly challenging. In contrast to traditional real-time systems requiring deadline guarantees for all jobs, the latency service-level objectives of cloud applications are usually defined in terms of tail latency, i.e., the latency of a certain percentage of the jobs should be below a given threshold. This means that neither dedicating entire physical CPU cores, nor combining virtualization with deadline-based techniques such as compositional real-time scheduling, can meet the needs of these applications in a resource-efficient manner. To address this limitation, and to simplify the management of edge clouds for latency-sensitive applications, we introduce virtualization-agnostic latency (VAL) as an essential property to maintain consistent tail latency assurances across different virtualized hosts. VAL requires that an application experience similar latency distributions on a shared host as on a dedicated one. Towards achieving VAL in edge clouds, this paper presents a virtualization-agnostic scheduling (VAS) framework for time-sensitive applications sharing CPUs with other applications. We show both theoretically and experimentally that VAS can effectively deliver VAL on shared hosts. For periodic and sporadic tasks, we establish theoretical guarantees that VAS can achieve the same task schedule on a shared CPU as on a full CPU dedicated to time-sensitive services. Moreover, this can be achieved by allocating the minimal CPU bandwidth to time-sensitive services, thereby avoiding wasting CPU resources. VAS has been implemented on Xen 4.10. 0. In case studies running time-sensitive workloads on Redis and Spark streaming services, we show that in practice the task schedule on a shared CPU can closely approximate the one on a full CPU.
Supporting Information

Fig. S1. Cumulative mass fraction of ≤20 μm dust (PM20) in two soils from Utah (stars and crosses, respectively, denote soils 00-U36 and 00-U37 in ref. 1) and six soils from across the Sahara (squares, circles, triangles, diamonds, hexagons, and pentagons, respectively, denote soils 1–6 in ref. 2). The thick blue line denotes the log-normal distribution (Eq. 4) with the log-normal parameters D̄s and σs taken as the average of the eight different soils from Table 1. 1. Goldstein H, et al. (2005) Particle-size, CaCO3 , chemical, magnetic, and age data from surficial deposits in and around Canyonlands National Park, Utah. (US Geological Survey). 2. d’Almeida GA, Schutz L (1983) Number, mass and volume distributions of mineral aerosol and soils of the Sahara. J Clim Appl Meteorol 22:233–243.
A Review and Classification of Intrusion Detection System in Data Engineering

— Network revolution is an integral component of connectivity. The network risks have also increased from the latest developments of the internet. The conventional firewall methods are insufficient to survive the modern form of attacks from the internet. An effective intrusion is found to be associated with a machine weakness. Cyber threats are getting increasingly complex and this is making them difficult to track. In the future, that would be a big problem for intelligence forces, such as the security violation of data protection, integrity, and availability. Lots of Intrusion Detection System (IDS) have been proposed which can be generally categorized into Signature-based IDS (SIDS) and Anomaly-based IDS (AIDS) in the literature to protect against ransomware and cyber assaults. In this survey article, it provides a taxonomy of contemporary IDS information research, a thorough analysis of noteworthy recent works, and a summary of the data sets widely utilized for assessment purposes. The research provides a broad range of attacks and methods utilized by attackers to penetrate networks.
Where To Next? A Dynamic Model of User Preferences

We consider the problem of predicting users’ preferences on online platforms. We build on recent findings suggesting that users’ preferences change over time, and that helping users expand their horizons is important in ensuring that they stay engaged. Most existing models of user preferences attempt to capture simultaneous preferences: “Users who like A tend to like B as well”. In this paper, we argue that these models fail to anticipate changing preferences. To overcome this issue, we seek to understand the structure that underlies the evolution of user preferences. To this end, we propose the Preference Transition Model (PTM), a dynamic model for user preferences towards classes of items. The model enables the estimation of transition probabilities between classes of items over time, which can be used to estimate how users’ tastes are expected to evolve based on their past history. We test our model’s predictive performance on a number of different prediction tasks on data from three different domains: music streaming, restaurant recommendations and movie recommendations, and find that it outperforms competing approaches. We then focus on a music application, and inspect the structure learned by our model. We find that the PTM uncovers remarkable regularities in users’ preference trajectories over time. We believe that these findings could inform a new generation of dynamic, diversity-enhancing recommender systems.
A Multiple Models Ensembling Method in TREC Deep Learning

This paper is to describe our participation in the passage ranking tasks of TREC 2020 Depp Learning Track. We take leverage of several pre-trained models, such as BERT, ELECTRA and XLNET, to re-rank passages. Firstly, we use corpus in this track and enhanced next sentence prediction task to pre-treain a new BERT large model. Secondly, we ﬁne-tune the new BERT model as well as ELECTRA, XL-NET and ALBERT with selected triplet data. Then, we ensemble several diﬀerent kind of models to score and rank top-1000 passage. Finally, we select and re-rank top-10 passages in the former step according to the similarity to the top-1 passage to reduce noise.
Size Effects in Nanoparticle Catalysis at Nanoparticle Modified Electrodes: The Interplay of Diffusion and Chemical Reactions

Electron transfer reactions mediated via nanoparticles immobilized on an electrode surface are considered in respect of catalytic processes in which solution phase species are either oxidized or reduced to form products exclusively via electron transfer with negligible reaction at the underlying supporting electrode. Specifically simulation is used to explore the effect of the nanoparticle size for individual nanoparticles as well as ensembles of nanoparticles, and a kinetic diagram is developed. For a single nanoparticle its size controls the rates of diffusion of species to and from the particle so that the relative extent of the catalysis is reduced for larger particles. For an array of nanoparticles the response of the whole is sensitive not only to the particle size but also to the particle coverage since the interparticle distance influences the extent, or otherwise, of the local overlap of the diffusion layers of neighboring particles and hence also the extent of the catalysis. Both particle size a.
Multi-area functional modules mediate feedforward and recurrent processing in visual cortical hierarchy

The visual cortex is organized hierarchically, but extensive recurrent pathways make it challenging to decipher the flow of information with single neuron resolution. Here, we characterize spiking interactions in populations of neurons from six interconnected areas along the visual hierarchy in awake mice. We generated multi-area, directed graphs of neuronal communication and uncovered two spatially-distributed functional modules. One module is positioned to transmit feedforward sensory signals along the hierarchy, while the other receives convergent input and engages in recurrent processing. The modules differ in layer and area distributions, convergence and divergence, and population-level temporal dynamics. These results reveal a neuronal-resolution cortical network topology in which distinct processing modules are interlaced across multiple areas of the cortical hierarchy.
Empirical Study to Explore the Influence of Salesperson’s Customer Orientation on Customer Loyalty

This study tries to examine the influence of salesperson’s customer orientation on Customer Loyalty. Customer orientation is the approach taken by a salesperson to improve customer relationship and increase sales. Many organizations prefer sales orientation as a strategic approach towards increasing sales. Though successful in its objective, sales orientation fails to attract repetitive purchase. It has become a necessity to train frontline employees to better understand the customer needs, keeping in mind the firm’s ultimate objective. This study examines the improvements, customer orientation can bring to increase repurchases thus leading to customer loyalty. The findings suggest that product assortment, long lines of customers, customers’ annual income, and the listening skills of salesperson were the significant antecedents of customer loyalty.
Optical analysis of the action range of glutamate in the neuropil

The wiring scheme of neurons is key to the function of the brain. Neurons are structurally wired by synapses and it is a long-held view that most synapses in the CNS are sufficiently isolated to avoid cross-talk to AMPA receptors of neighboring synapses. Here we report in hippocampal brain slices that quantal glutamate release activated optical reporter proteins >1.5 µm distant to the releasing synapse. 2P-glutamate uncaging was used to quantitatively probe glutamate spread in the neuropil. Releasing ∼35000 molecules of glutamate (∼5 vesicles) at a distance of 500 nm to a spine generated an uncaging EPSC reaching ∼30% of the quantal amplitude at synaptic AMPA-Rs. The same stimulus activated ∼70% of the quantal amplitude at NMDA-Rs and still generated clear current and calcium responses when applied at >= 2 µm remote to the spine. Extracellular spread of glutamate on the sub-micrometer scale appeared cooperative and caused supra-additive activation of AMPA-Rs in a spine. These observations are not predicted by previously used models of glutamate diffusion in the neuropil. An extracellular glutamate scavenger system weakly reduced field potential responses but not the quantal amplitude, indicating that a cross-talk component regularly contributes to synaptic transmission. Our data suggest that slight synaptic crosstalk responses at AMPA receptors of ∼2-4 adjacent synapses may be common (>70 synapses for NMDA receptors). Such broadcasting of synaptic signals to very local neighborhoods could stabilize network learning performance and allow for integration of synaptic activity within the extracellular space.