Miracle-dz/UniFAR-FTUs huggingface dataset:
UPGRADVISOR: Early Adopting Dependency Updates Using Hybrid Program Analysis and Hardware Tracing

Applications often have fast-paced release schedules, but adoption of software dependency updates can lag by years, leaving applications susceptible to security risks and unexpected breakage. To address this problem, we present U PGRADVISOR , a system that reduces developer effort in evaluating dependency updates and can, in many cases, automatically determine which updates are backward-compatible versus API-breaking. U PGRADVISOR introduces a novel co-designed static analysis and dynamic tracing mechanism to gauge the scope and effect of dependency updates on an application. Static analysis prunes changes irrelevant to an application and clusters relevant ones into targets . Dynamic tracing needs to focus only on whether targets affect an application, making it fast and accurate. U PGRADVISOR handles dynamic interpreted languages and introduces call graph over-approximation to account for their lack of type information and selective hardware tracing to capture program execution while ignoring interpreter machinery. We have implemented U PGRADVISOR for Python and evaluated it on 172 dependency updates previously blocked from being adopted in widely-used open-source software, including Django , aws-cli , tfx , and Celery . U PGRADVISOR automatically determined that 56% of dependencies were safe to update and reduced by more than an order of magnitude the number of code changes that needed to be considered by dynamic tracing. Evaluating U PGRADVISOR ’s tracer in a production-like environment incurred only 3% overhead on average, making it fast enough to deploy in practice. We submitted safe updates that were previously blocked as pull requests for nine projects, and their developers have already merged most of them. Abstract The version of U PGRADVISOR used to perform the experiments described in the paper may be downloaded from figshare.com. Theartifactcontainsthecodeforthepackagesur-vey, the static analyzer, and the hardware tracer. It also contains scripts to compile the tracer, run the experiments described in the paper, and produce most of the figures. For the most up to We provide the analyzer pre-installed in a docker container. The tracer requires a bare-metal machine. It directly employs a tracing capability found in Intel 5th generation CPUs (Broadwell) and above. Installing the tracer software requires root access to the OS. This artifact will run on a i7-10700 CPU workstation with 16GB RAM. A slower machine may result in reduced performance. We set up the docker container on the tracer machine and encourage you to do the same.
Edinburgh Research Explorer Eager Markov

We consider inﬁnite-state discrete Markov chains which are eager : the probability of avoiding a deﬁned set of ﬁnal states for more than n steps is bounded by some exponentially decreasing function f ( n ) . We prove that eager Markov chains include those induced by Probabilistic Lossy Channel Systems, Probabilistic Vector Addition Systems with States, and Noisy Turing Machines, and that the bounding function f ( n ) can be effectively constructed for them. Furthermore, we study the problem of computing the expected reward (or cost) of runs until reaching the ﬁnal states, where rewards are assigned to individual runs by computable reward functions. For eager Markov chains, an effective path exploration scheme, based on forward reachability analysis, can be used to approximate the expected reward up-to an arbitrarily small error.
ArchiCap – A tool for capability-based IT architecture exploration ArchiCap – A tool for capability-based IT architecture exploration

IT architects often face a high uncertainty and a lack of methodical support when it comes to architectural decisions in emerging IT environments. Here, a capability-based approach can help to ensure business-orientation and strategic alignment. However, in practice it turns out to be difficult to identify relevant capabilities and adequate architectural possibilities. The prototype presented in this proposal constitutes a web-based software tool to support the exploration of capabilities and link them to architectural decisions. For this, the software allows (i) the definition of environmental setups for certain application areas (e
MacaquesMotif Between Humans and Rhesus Conserved MHC Class I Peptide Binding

Since the onset of the HIV pandemic, the use of nonhuman primate models of infection has increasingly become important. An excellent model to study HIV infection and immunological responses, in particular cell-mediated immune responses, is SIV infection of rhesus macaques. CTL epitopes have been mapped using SIV-infected rhesus macaques, but, to date, a peptide binding motif has been described for only one rhesus class I MHC molecule, Mamu-A*01. Herein, we have established peptide-live cell binding assays for four rhesus MHC class I molecules: Mamu-A*11, -B*03, -B*04, and -B*17. Using such assays, peptide binding motifs have been established for all four of these rhesus MHC class I molecules. With respect to the nature and spacing of crucial anchor positions, the motifs deﬁned for Mamu-B*04 and -B*17 present unique features not previously observed for other primate species. The motifs identiﬁed for Mamu-A*11 and -B*03 are very similar to the peptide binding motifs previously described for human HLA-B*44 and -B*27, respectively. Accordingly, naturally processed peptides derived from HLA-B*44 and HLA-B*27 speciﬁcally bind Mamu-A*11 and Mamu-B*03, respectively, indicating that conserved MHC class I binding capabilities exist between rhesus macaques and humans. The deﬁnition of four rhesus MHC class I-speciﬁc motifs expands our ability to accurately detect and quantitate immune responses to MHC class I-restricted epitopes in rhesus macaques and to rationally design peptide epitope-based model vaccine constructs destined for use in nonhuman primates. The Journal of Immunology, 2000, 164: 283–291.
The role of social media as a voluntary intellectual capital disclosure in universities: Evidence from Indonesia

Purpose: This research explains the influence of social media as a tool for the voluntary disclosure of intellectual capital on university performance. Design/methodology: All universities in Indonesia were analyzed based on the observation of their social media accounts such as Facebook, Instagram, Twitter, and YouTube channels after which they were correlated with the university performance. Findings: The results showed that social media can be used as voluntary disclosure of intellectual capital. This was indicated by the positive correlation between the popularity of the universities on social media and their relational capital and institutional performance. However, no impact was found on the number of students but a significant difference was recorded in the use of social media between public and private universities in Indonesia. Research limitations/implications: The data were obtained only from one country and this means there is a need to analyze several other countries with different social media platforms in the future. Practical implications: From a strategic management perspective, this is an opportunity for universities to manage social media effectively in order to increase the popularity of their cyberspace and institutional performance. It is recommended that universities have a special role in managing their social media content in order to be able to develop and manage digital communications effectively as a strategy to improve the performance of institutions. Social implications: Social media plays a vital role in improving an organization's performance and providing adequate information to stakeholders. This is important because the existence of intangible assets is critical to the survival of a business. Originality/value: This research empirically examines the impact of using social media on public-sector organizations (universities) with a specific focus on its application as a voluntary disclosure tool of intellectual capital.
Transcription activation is enhanced by multivalent interactions independent of liquid-liquid phase separation

Transcription factors (TFs) consist of a DNA binding and an activation domain (AD) that are considered to be independent and exchangeable modules. However, recent studies conclude that also the physico-chemical properties of the AD can control TF assembly at chromatin via driving a phase separation into “transcriptional condensates”. Here, we dissected the mechanism of transcription activation at a reporter gene array with real-time single-cell fluorescence microscopy readouts. Our comparison of different synthetic TFs reveals that the phase separation propensity of the AD correlates with high transcription activation capacity by increasing binding site occupancy, residence time and the recruitment of co-activators. However, we find that the actual formation of phase separated TF liquid-like droplets has a neutral or inhibitory effect on transcription induction. Thus, our study suggests that the ability of a TF to phase separate reflects the functionally important property of the AD to establish multivalent interactions but does not by itself enhance transcription. rTetR-VPR fusions that induce both transcription and high enrichments levels of BRD4 H3K27ac. rTetR-VP16 fusion displayed moderate but robust activation at very low dCas9 BLInCR H3K27ac
Edinburgh Research Explorer Do Be Do Be Do

We explore the design and implementation of Frank, a strict functional programming language with a bidirectional effect type sys-tem designed from the ground up around a novel variant of Plotkin and Pretnar’s effect handler abstraction. Effect handlers provide an abstraction for modular effectful programming: a handler acts as an interpreter for a collection of commands whose interfaces are statically tracked by the type system. However, Frank eliminates the need for an additional effect handling construct by generalising the basic mechanism of functional abstraction itself. A function is simply the special case of a Frank operator that interprets no commands. Moreover, Frank’s operators can be multihandlers which simultaneously interpret commands from several sources at once, without disturbing the direct style of functional programming with values. Effect typing in Frank employs a novel form of effect polymorphism which avoid mentioning effect variables in source code. This is achieved by propagating an ambient ability inwards, rather than accumulating unions of potential effects outwards. We introduce Frank by example, and then give a formal account of the Frank type system and its semantics. We introduce Core Frank by elaborating Frank operators into functions, case expressions, and unary handlers, and then give a sound small-step operational semantics for Core Frank. Programming with effects and handlers is in its infancy. We contribute an exploration of future possibilities, particularly in combination with other forms of rich type system.
Dynamic detection method for falling ears of maize harvester based on improved YOLO-V4

: Traditional maize ear harvesters mainly rely on manual identification of fallen maize ears, which cannot realize real-time detection of ear falling. The improved You Only Look Once-V4 (YOLO-V4) algorithm is combined with the channel pruning algorithm to detect the dropped ears of maize harvesters. K -means clustering algorithm is used to obtain a prior box matching the size of the dropped ears, which improves the Intersection Over Union (IOU). Compare the effect of different activation functions on the accuracy of the YOLO-V4 model, and use the Mish activation function as the activation function of this model. Improve the calculation of the regression positioning loss function, and use the CEIOU loss function to balance the accuracy of each category. Use improved Adam optimization function and multi-stage learning optimization technology to improve the accuracy of the YOLO-V4 model. The channel pruning algorithm is used to compress the model and distillation technology is used in the fine-tuning of the model. The final model size was only 10.77% before compression, and the test set mean Average Precision (mAP) was 93.14%. The detection speed was 112 fps, which can meet the need for real-time detection of maize harvester ears in the field. This study can provide technical reference for the detection of the ear loss rate of intelligent maize harvesters.
Economic cycles and self-employment: Synthetic Cohort Analysis for Greater Santiago*

Economic cycles affect both unemployment and the composition of employment, which can have an impact on the well-being of individuals if these changes in composition are involuntary or involve a decrease in the quality of employment. In this article, we study the relationship between economic cycles and self-employment, distinguishing between employers and own-account workers, through a synthetic cohort methodology using data for Chile. The results suggest that the proportion of employers is procyclical and that of own-account workers is countercyclical. This suggests that own-account employment is a refuge in times of crisis from the shortage of wage-based employment. This highlights the importance of designing public policies that would improve the conditions of self-employed workers.
Optimization of fiber-orientation distribution in fiber-reinforced composite injection molding by Taguchi, back propagation neural network, and genetic algorithm–particle swarm optimization

Fiber orientation induced by injection molding of short-fiber-reinforced composites causes anisotropy in material properties and produces warping. Fiber-orientation distribution is very important to research for mold design and quality to produce sound molded parts. In this study, three kinds of methods are used to solve the optimization problem. Fiber-orientation distribution is described by fiber-orientation tensor variation. The objective function is a minimum problem of the fiber-orientation tensor variation. Parameters such as fiber content, fiber aspect ratio, melting temperature, injection pressure, holding pressure, and filling time are considered as design variables. Based on orthogonal experiment design, Moldflow software is used in the fiber-reinforced acrylonitrile butadiene styrene composite injection molding. The effects of process parameters for the plastic part are studied using the signal-to-noise ratio. The most important design parameter influencing fiber-orientation tensor variation is determined by finite element analysis results based on the analysis of variance. The optimization model is established on the basis of the back propagation neural network. The Taguchi, the particle swarm optimization, and genetic algorithm–particle swarm optimization hybrid algorithm are used to find the minimum fiber-orientation tensor variation value. Results show that the quality index of the fiber-orientation tensor variation in the part is improved.
Why Discard if You can Recycle?: A Recycling Max Pooling Module for 3D Point Cloud Analysis

In recent years, most 3D point cloud analysis models have focused on developing either new network architectures or more efficient modules for aggregating point features from a local neighborhood. Regardless of the network architecture or the methodology used for improved feature learning, these models share one thing, which is the use of max-pooling in the end to obtain permutation invariant features. We first show that this traditional approach causes only a fraction of 3D points contribute to the permutation-invariant features, and discards the rest of the points. In order to address this issue and improve the performance of any baseline 3D point classification or segmentation model, we propose a new module, referred to as the Recycling Max-Pooling (RMP) module, to recycle and utilize the features of some of the discarded points. We incorporate a refinement loss that uses the recycled features to refine the prediction loss obtained from the features kept by traditional max-pooling. To the best of our knowledge, this is the first work that explores recycling of still useful points that are traditionally discarded by max-pooling. We demonstrate the effectiveness of the proposed RMP module by incorporating it into several milestone baselines and state-of-the-art networks for point cloud classification and indoor semantic segmentation tasks. We show that RPM, without any bells and whistles, consistently improves the performance of all the tested networks by using the same base network implementation and hyper-parameters. The code is provided in the supplementary material.
Fusing Sentinel-2 and Landsat 8 Satellite Images Using a Model-Based Method

: The Copernicus Sentinel-2 (S2) constellation comprises of two satellites in a sun-synchronous orbit. The S2 sensors have three spatial resolutions: 10, 20, and 60 m. The Landsat 8 (L8) satellite has sensors that provide seasonal coverage at spatial resolutions of 15, 30, and 60 m. Many remote sensing applications require the spatial resolutions of all data to be at the highest resolution possible, i.e., 10 m for S2. To address this demand, researchers have proposed various methods that exploit the spectral and spatial correlations within multispectral data to sharpen the S2 bands to 10 m. In this study, we combined S2 and L8 data. An S2 sharpening method called Sentinel-2 Sharpening (S2Sharp) was modiﬁed to include the 30 m and 15 m spectral bands from L8 and to sharpen all bands (S2 and L8) to the highest resolution of the data, which was 10 m. The method was evaluated using both real and simulated data.
How Good Is Aesthetic Ability of a Fashion Model?

We introduce A100 (Aesthetic 100) to assess the aesthetic ability of the fashion compatibility models. To date, it is the first work to address the AI model's aesthetic ability with detailed characterization based on the professional fashion domain knowledge. A100 has several desirable characteristics: 1. Completeness. It covers all types of standards in the fashion aesthetic system through two tests, namely LAT (Liberalism Aesthetic Test) and AAT (Academicism Aesthetic Test); 2. Reliability. It is training data agnostic and consistent with major indicators. It provides a fair and objective judgment for model comparison. 3. Explainability. Better than all previous indicators, the A100 further identifies essential characteristics of fashion aesthetics, thus showing the model's performance on more fine-grained dimensions, such as Color, Balance, Material, etc. Experimental results prove the advance of the A100 in the aforementioned aspects. All data can be found at https://github.com/AemikaChow/AiDLab-fAshIon-Data.
Monetary Policy Under Labor Market Power

IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management. ABSTRACT: Using the near universe of online vacancy postings in the U.S., we study the interaction between labor market power and monetary policy. We show empirically that labor market power amplifies the labor demand effects of monetary policy, while not disproportionately affecting wage growth. A search and matching model in which firms can attract workers by either offering higher wages or posting more vacancies can rationalize these findings. We also find that vacancy postings that do not require a college degree or technology skills are more responsive to monetary policy, especially when firms have labor market power. Our results help explain the “wageless” recovery after the 2008 financial crisis and the flattening of the wage Phillips curve, especially for the low-skilled, who saw stagnant wages but a robust decline in unemployment.
Systematic Reviews and Meta- and Pooled Analyses Urinary Cadmium Concentration and Risk of Breast Cancer: A Systematic Review and Dose-Response Meta-Analysis

Cadmium is a toxic and persistent heavy metal with estrogenic activities. We conducted a systematic review and meta-analysis of cohort, case-control, and cross-sectional studies of the association between urinary cadmium concentration, a biomarker of cadmium exposure, and breast cancer risk. Studies were identified by searching PubMed and Embase (to March 15, 2015) and by reviewing the reference lists of pertinent articles. Study-specific risk estimates were combined by using a random-effects model. We identified 2 cohort studies (with 67 breast cancer deaths) and 5 case-control studies and 1 cross-sectional study (with 1,416 cases and 5,083 controls) on urinary cadmium concentration in relation to breast cancer risk. The studies were published during the past 10 years (2006 – 2015). There was no consistent association between urinary cadmium and breast cancer mortality in the cohort studies. In case-control and cross-sectional studies, the pooled odds ratios were 2.24 (95% confidence interval: 1.50, 3.34; I 2 = 63.4%) for the highest versus lowest categoryof cadmium concentration and 1.66 (95% confidence interval: 1.23, 2.25) for each 0.5-µg/g creatinine increase of cadmium concentration. This meta-analysis suggests that a high cadmium exposure may be a risk factor for breast cancer, but large prospective studies are needed to confirm this finding.
Performance evaluation of the Philips Vereos PET/CT System according to the NEMA NU2-2012 standard

Aim: The aim of this study is to evaluate the physical performance of the Philips Vereos whole-body PET/CT system according to the NEMA NU2-2012 standard and to compare it to other state-of-the-art PET/CT systems. Methods: Spatial resolution, sensitivity, count-rate performance, count rate accuracy and image quality were assessed. Specifically, spatial resolution was measured using an 18F point-source. System sensitivity was calculated from acquisitions of an 18F line-source inside Al-tubes with varying thickness. Count rate performance and count rate accuracy assessment was based on measurements of an 18F line-source inside a 20 cm diameter polyethylene cylinder. PET image quality was assessed using a NEMA IQ phantom. All measurements were performed according to the predefined and implemented NEMA NU2-2012 acquisition protocols at a clinical installation of a Philips Vereos PET/CT system. Evaluation was performed using the software provided by the vendor. Results: Average (radial and tangential) transvers spatial resolution was 4.2 mm, 4.5 mm and 5.5 mm FWHM for 1 cm, 10 cm and 20 cm radial offset from the center of the field-of-view (FOV), respectively. Axial spatial resolution varied between 4.2 mm and 4.6 mm FWHM depending on the radial source position. The average sensitivity was 5.2 cps/kBq. A peak NEC of 153.4 kcps was measured at an activity concentration of 54.9 kBq/mL. The scatter fraction at peak NEC was 33.9% and the maximum count rate error at and below NEC peak was 6.8%. Contrast recovery coefficients varied form 54.3% (10 mm sphere) to 83.9% (22 mm) for the hot spheres, and between 81.4% (28 mm) and 87% (37 mm) for the cold spheres for a given sphere to background ratio of 4:1. Conclusion: The overall performance characteristics of the Vereos PET/CT system are comparable to state-of-the-art whole-body PET/CT systems with the exception of the peak NEC occurring at a higher activity concentration, thus, indicating the ability of the Vereos system to cover a wider range of activities.