Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of developing countries ’ innovation policies on firms ’ decisions to invest in R &

Using data on Ecuadorian firms for the period 2009-2011 and by employing inverse probability weighting, this paper compares the impact of two developing countries’ policy instruments that may induce firms to invest in R&D activities. The first is public procurement which has recently been viewed as an important tool when encouraging innovation. The second is innovation support programs which are intended to increase firms’ technological capabilities. Results indicate that public procurement does not induce firms to invest in R&D activities, even for the largest contracts. However, participating in innovation support programs does so. Furthermore, the combination of both policy instruments does not produce a significant effect on firms’ decisions to invest in R&D.
DangZero: Efficient Use-After-Free Detection via Direct Page Table Access

Use-after-free vulnerabilities remain difficult to detect and mitigate, making them a popular source of exploitation. Existing solutions incur impractical performance/memory overhead, require specialized hardware, and/or guarantee only protection, but not detection. In this paper, we propose DangZero, a new solution to detect use-after-free vulnerabilities as they occur. DangZero builds on a traditional page protection and aliasing scheme, where objects are made inaccessible after a free, and subsequent accesses are immediately detected. In contrast to prior solutions using alias-based detection, DangZero relies on direct page table access in ring 0 to provide a much more efficient implementation. The key idea is that, by giving the program's allocator direct access to the page tables, we can efficiently manage and invalidate vulnerable objects. To safely implement this, we build upon a unikernel-like design, where virtualization provides ring-0 (guest-mode) access, isolation, as well as compatibility with existing Linux programs. Moreover, we show direct page table access serves as an efficient building block for garbage collection-style alias reclaiming. Doing so provides the ability to safely reuse freed areas and address the scalability issues plaguing state-of-the-art alias-based solutions. Our experimental results confirm that DangZero provides accurate detection guarantees with significantly lower overhead than competing state-of-the-art solutions (e.g., 18% saturated throughput degradation on long-running programs such as the Nginx web server).
A Run a Day Won't Keep the Hacker Away: Inference Attacks on Endpoint Privacy Zones in Fitness Tracking Social Networks

Fitness tracking social networks such as Strava allow users to record sports activities and share them publicly. Sharing encourages peer interaction but also constitutes a risk, because an activity's start or finish may inadvertently reveal privacy-sensitive locations such as a home or workplace. To mitigate this risk, networks introduced endpoint privacy zones (EPZs), which hide track portions around protected locations. In this paper, we show that EPZ implementations of major services remain vulnerable to inference attacks that significantly reduce the effective anonymity provided by the EPZ, and even reveal the protected location. Our attack leverages distance information leaked in activity metadata, street grid data, and the locations of the entry points into the EPZ. This yields a constrained search space where we use regression analysis to predict protected locations. Our evaluation on 1.4 million Strava activities shows that our attack discovers the protected location for up to 85% of EPZs. Larger EPZs reduce the performance of our attack, while geographically dispersed activities in sparser street grids yield better performance. We propose six countermeasures, that, however, come with a usability trade-off, and responsibly disclosed our findings and countermeasures to the major networks.
I'm SPARTACUS, No, I'm SPARTACUS: Proactively Protecting Users from Phishing by Intentionally Triggering Cloaking Behavior

Phishing is a ubiquitous and increasingly sophisticated online threat. To evade mitigations, phishers try to "cloak" malicious content from defenders to delay their appearance on blacklists, while still presenting the phishing payload to victims. This cat-and-mouse game is variable and fast-moving, with many distinct cloaking methods---we construct a dataset identifying 2,933 real-world phishing kits that implement cloaking mechanisms. These kits use information from the host, browser, and HTTP request to classify traffic as either anti-phishing entity or potential victim and change their behavior accordingly. In this work we present SPARTACUS, a technique that subverts the phishing status quo by disguising user traffic as anti-phishing entities. These intentional false positives trigger cloaking behavior in phishing kits, thus hiding the malicious payload and protecting the user without disrupting benign sites. To evaluate the effectiveness of this approach, we deployed SPARTACUS as a browser extension from November 2020 to July 2021. During that time, SPARTACUS browsers visited 160,728 reported phishing URLs in the wild. Of these, SPARTACUS protected against 132,274 sites (82.3%). The phishing kits which showed malicious content to SPARTACUS typically did so due to ineffective cloaking---the majority (98.4%) of the remainder were detected by conventional anti-phishing systems such as Google Safe Browsing or VirusTotal, and would be blacklisted regardless. We further evaluate SPARTACUS against benign websites sampled from the Alexa Top One Million List for impacts on latency, accessibility, layout, and CPU overhead, finding minimal performance penalties and no loss in functionality.
Stacked Denoising and Stacked Convolutional Autoencoders. An Evaluation of Transformation Robustness for Spatial Data Representations

Making sense of visual data in raw pixel representation is a difficult task in machine learning because of the complex ways underlying factors interact to create images. Applying two methods for representation learning, the stacked convolutional autoencoder (SCA) and the stacked denoising autoencoder (SDA), however, image data can be encoded to new representations. After training both methods on digit (MNIST) and data from laser welding videos, the image features produced by SCA improve on their SDA counterparts in two desirable properties. Firstly, SCA yield image features that are more useful for a specific purpose, namely the image classification with a subsequent SVM classifier. Secondly, SCA features exhibit a higher degree of invariance to input transformations than those representations generated by an SDA. The superior performance of SCA over SDA image representations is likely a consequence of SCA preserving and exploiting the spatial structure of the input data, while also coming with pooling layers which by design lead to a degree of invariance.
Energy Efficient Resource Allocation in Heterogenous Software Defined Network : A Reverse Combinatorial

In this paper, resource allocation for energy efficiency in heterogeneous Software Defined Network (SDN) with multiple network service providers (NSPs) is studied. The considered problem is modeled as a reverse combinatorial auction game, which takes different quality of service (QoS) requirements into account. The heterogeneous network selection associated with power allocation problem is optimized by maximizing the energy efficiency of data transmission. By exploiting the properties of fractional programming, the resulting non-convex Winner Determination Problem (WDP) is transformed into an equivalent subtractive convex optimization problem. The proposed reverse combinatorial auction game is proved to be strategy-proof with low computing complexity. Simulation results illustrate that with SDN controller, the proposed iterative ascending price algorithm converges in a small number of iterations and demonstrates the trade-off between energy efficiency and heterogeneous QoS requirement, especially ensures high fairness among different network service providers.
Fabrication of single phase super paramagnetic iron oxide nanoparticles from waste soil of factory

The application of Iron (III) oxide nanoparticles in biology and medicine is much more than the other magnetic nanoparticles. Biocompatibility with human body, stability and ease of production caused the wide range of its development. Single-phase iron (III) oxide nanoparticles were synthesis by use of factory waste soil instead of feedstock with low temperature wet chemical cleaving oxygen method. With respect to the precursor material that is factory waste soil (feedstock), it is cost-effective economically and also is innovative. In this synthesis method, single-phase iron(III) oxide were obtained by acid digestion of waste soil. The nanoparticles were analyzed by: Fourier Transform Infrared spectroscopy (FTIR), X-Ray Diffraction (XRD) that the crystallite size of nanoparticles calculated by XRD peaks and Debye-Scherrer formula and obtained 11 nm. Transmission Electron Microscope (TEM) images showed the spherical shape of nanoparticles with average size of 10 nm. Vibrating sample magnetometery (VSM) analysis was applied to determine the magnetic saturation and the size of nanoparticles was estimated 9 nm from this analysis. Fourier Transform Infrared spectroscopy gently shows the atomic bond between iron and oxygen (FeO) in nanoparticles. The results of X-ray Diffraction show that the sample was synthesized are cubic Spinel single-phase.
Succinct Zero Knowledge for Floating Point Computations

We study the problem of constructing succinct zero knowledge proof systems for floating point computations. The standard approach to handle floating point computations requires conversion to binary circuits, following the IEEE-754 floating point standard. This approach incurs a poly(w) overhead in prover efficiency for computations with w-bit precision, resulting in very high prover runtimes -- already the key bottleneck in the design of succinct arguments. We make the following contributions: -We propose a new model for verifying floating point computations that guarantees approximate correctness w.r. t. a relative error bound. This model is inspired by numerical analysis, and is very meaningful for applications such as machine learning and scientific computing. -Using this model, we present a general method for constructing succinct zero-knowledge proofs for floating point computations starting from existing public-coin "commit-and-prove'' systems. For computations with w-bit precision, our approach incurs only a log(w) overhead in prover running time. Our compiler nearly preserves (up to a factor of 2) the communication complexity of the underlying protocol, and requires sub-linear verification time. The resulting proof can be made non-interactive in the random oracle model. Concretely, our scheme is ~57x faster than the method following IEEE standard exactly [35] for 32-bit floating point computations. Central to our main result, and of independent interest, is a new batch range proof system in standard prime order groups that does not rely on bit decomposition.
16 Magnetic Nanoparticles : Its Effect on Cellular Behaviour and Potential Applications

With the advancement of nanotechnology and the development of molecular medicine, molecular and imaging becomes one of the most popular researches in the latest medicine. Molecular imaging can be defined as the imaging of targeted molecules non-invasively and repetitively in living organisms and cellular imaging can be defined similarly as the imaging of cells or cellular process non-invasively and repetitively in living organisms. At present, the common imaging tools for clinical study include ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI). However, MRI is superior to CT for its better in soft tissue contrast, more sensitive in pathology detection, and lack of ionization irradiation.
1 Using synchronous fluorescence to investigate 2 compounds and interactions influencing foam 3 characteristics in sparkling wines 4

The appearance of bubbles and foam can influence the likeability of a wine even before its 17 consumption. Since foams are essential to visual and taste attributes of sparkling wines, it is of great importance 18 to understand which compounds affect bubbles and foam characteristics. The aim of this work was to investigate 19 the effect of interactions among proteins, amino acids, and phenols on the characteristics of foam in sparkling 20 wines by using synchronous fluorescence spectroscopy techniques. Results has shown that several compounds 21 present in sparkling wines influence foam quality differently, and importantly, highlighted how the interaction 22 of those compounds might result in different effects on foam parameters. Amongst the results, mannoproteins 23 were found to be most likely to promote foam and collar stability, while phenols were likely to increase the ratio 24 of small bubbles and collar height in the foam matrix. In summary, this work contributes to a better 25 understanding of the effect of wine compounds on foam quality as well as the effect of the interactions between 26 those compounds. 27
SIMILIARITY MEASURES FOR DEPTH ESTIMATIO

This paper deals with similarity measures for stereoscopic depth estimation. These measures are used for matching of image pairs, which is the first step of the estimation process. We analyze influence of these similarity measures on performance of depth estimation basing on some of commonly known measures and compare the results with some novel proposals. The performance is judged by increase of quality of view synthesis, which is the main aim of this paper. Experimental results over variety of moving material demonstrate that considerable gain can be attained without any modifications to estimation core and with tuning of matching stage only. Finally, some guidelines on design of well performing similarity measures are given. For the sake of paper, the whole work is described in context of belief-propagation algorithm, but in general, the results and conclusions apply for many other state-of-the art optimization techniques.
Comparative Studies on Chemical Composition , Phenolic Compounds and Antioxidant Activities of Brown and White Perilla ( Perilla frutescens ) Seeds

Chemical composition, phenolic compounds and antioxidant activities of brown perilla and white perilla seeds were comparatively studied. Brown perilla seed had higher protein, fat, ash and crude fiber contents than those of white perilla seed (p<0.05). Additionally, brown perilla seed contained greater contents of Ca, Mg, and P than those of white perilla seed (p<0.05). However, no difference in Fe content was found in both seeds (p>0.05). Brown perilla seed was rich in polyunsaturated fatty acid, in particular γ-linolenic acid and α-linolenic acid. The most abundant of β-carotene and α-tocopherol was found in brown perilla seed. Higher total phenolic, total flavonoid, and total flavonol contents together with higher 2, 2-diphenyl-1-picrylhydrazyl (DPPH) and 2, 2’-azino-bis(3-ethylbenzthiazoline6-sulphonic acid) (ABTS)-radical scavenging activities as well as a greater reducing capacity were observed in brown perilla seed extract (p<0.05). Therefore, brown perilla seed can be a good source of both macroand micro-nutrients with phytochemical antioxidant activity.
on Coping Style , Social Support and Psychological Health Among Undergraduate Nursing Students

The purpose of this study was to compare coping style, social support and psychological health of nursing students during mid period of clinical practice in Wuhan and Peking, China and determine the relationship of copying styles, the social support and the mental health among undergraduate nursing students by Folkman and Lazarus’s Coping Style, Perceived Social Support Scale (PSSS) and SCL-90 questionnaire. The result was that (1) tring to find a solution to the problem was the first coping style; (2) no significant difference of coping styles between Wuhan and Peking (p >0.05), significant differences of family support and total social support (P<0.01) and other support (P<0.05). No significant difference was present in friend support (p>0.05), differences on mean score of SCL-90, as well as depression, anxiety, phobia, schizophrenia factor and hostility factor score; (3)negative correlations were found between mature coping style and SCL-90 total score (r = -0.54, p < 0.05), while positive correlations related to immature coping style (r =0.28, p < 0.01) and total score of SCL-90, no relation between mixed coping and total score of SCL-90 (r =0.17, p>0.05), SCL-90 total score had a negative correlation to family support, friend support, other support and total score of perceived social support (r =-0.292, -0.287,-0.290,-0.416, p < 0.01). Mature coping style is related to higher psychological health. The family support, social support and mental health level of undergraduate nursing students in Peking are higher than in Wuhan. The higher social support perceived by undergraduate nursing students, the better mental health they reported.
The Limits of Meritocracy, WP/18/231, November 2018

We show that too much meritocracy, modeled as accuracy of performance ranking in contests, can be a bad thing: in contests with homogeneous agents, it reduces output and is Pareto inefficient. In contests with sufficiently heterogeneous agents, discouragement and complacency effects further reduce the benefits of meritocracy. Perfect meritocracy may be optimal only for intermediate levels of heterogeneity. JEL Classification Numbers: D22, D47, D61, D63, L23
Uncovering Intent based Leak of Sensitive Data in Android Framework

To prevent unauthorized apps from retrieving the sensitive data, Android framework enforces a permission based access control. However, it has long been known that, to bypass the access control, unauthorized apps can intercept the Intent objects which are sent by authorized apps and carry the retrieved sensitive data. We find that there is a new (previously unknown) attack surface in Android framework that can be exploited by unauthorized apps to violate the access control. Specifically, we discover that part of Intent objects that are sent by Android framework and carry sensitive data can be received by unauthorized apps, resulting in the leak of sensitive data. In this paper, we conduct the first systematic investigation on the new attack surface namely the Intent based leak of sensitive data in Android framework. To automatically uncover such kind of vulnerability in Android framework, we design and develop a new tool named LeakDetector, which finds the Intent objects sent by Android framework that can be received by unauthorized apps and carry the sensitive data. Applying LeakDetector to 10 commercial Android systems, we find that it can effectively uncover the Intent based leak of sensitive data in Android framework. Specifically, we discover 36 exploitable cases of such kind of data leak, which can be abused by unauthorized apps to steal the sensitive data, violating the access control. At the time of writing, 16 of them have been confirmed by Google, Samsung, and Xiaomi, and we received bug bounty rewards from these mobile vendors.
Poster: Insights into Global Deployment of RPKI Validation

IP prefix hijacks, due to malicious attacks or benign misconfigurations, pose a threat to the Internet's stability and security. RPKI was designed to enable networks to block prefix hijacks by enforcing Route Origin Validation (ROV). In this work we evaluate the effectiveness of the global ROV deployment in blocking prefix hijacks. We perform control-plane and data-plane experiments and provide an in-depth analysis of the collected results. Our analysis is based on new methodologies we developed that allow more accurate identification of ROV enforcing ASes. Our analysis shows that the current ROV enforcement rate is significantly higher than found in previous studies: in contrast to 0.6% in a study from 2021, in our work we find that 37.8% enforce ROV. Our results indicate that ROV has finally gained traction and offers substantial protection against prefix hijacks.
Resource Misallocation and Productivity: Evidence from Mexico, WP/18/112, May 2018

This paper explores the role for specific structural distortions in explaining Mexico’s weak productivity growth through the resource misallocation channel. It makes two contributions. First, we validate the approach of measuring misallocation indirectly as in Hsieh and Klenow (2009) by illustrating a close correlation between misallocation and per capita incomes across Mexican states. Second, we exploit the large variation in resource misallocation within industries and across states together with unusually rich data at the firm, local, and industry level to shed light on its determinants. We identify several well-defined distortions that have a statistically and economically meaningful effect on productivity via resource misallocation. JEL Classification Numbers: D24, O12, O47
Anticoccidial properties of micronized curcumin against Eimeria tenella in experimentally infected broiler chickens ـــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ

In this study, the anticoccidial properties of micronized curcumin against Eimeria tenella in a comparison with the ordinary one were investigated. The experiment was conducted using 105 broiler chicks, divided into four groups; micronized curcumin (A), curcumin (B), infected untreated (C) and uninfected untreated (D). Group A and B were treated for seven successive days with micronized curcumin (with sodium alginate) and curcumin suspended in corn oil respectively. All Chicks were infected orally with E. tenella at the 22th days of age except the control negative one. Depending on the anticoccidial indices (relative weight gain, survival rate, lesion value and oocyst value), the micronized curcum in treated group showed a higher protection than curcumin treated. As anti-oxidant, both of curcumin treated groups revealed a significant increase in glutathione (GSH), superoxide dismutase (SOD) and catalase comparing with the control infected untreated group at p ≤ 0.05. In addition, significant decrease of malondialdehyde (MDA) concentration of treated groups comparing with infected untreated group was recorded (p≤0.05). Since curcumin had anti-inflammatory properties, TNFα and IL 10 βR were significantly decreased in curcumin treated in a comparison with the infected untreated groups at p ≤ 0.05. In conclusion, the micronized curcumin has a marked role in restricting the adverse effect of E. tenella infection in broiler chickens better than curcumin alone.