Miracle-dz/UniFAR-FTUs huggingface dataset:
Privacy Profiles and Amplification by Subsampling

Differential privacy provides a robust quantifiable methodology to measure and control the privacy leakage of data analysis algorithms.A fundamental insight is that by forcing algorithms to be randomized, their privacy leakage can be characterized by measuring the dissimilarity between output distributions produced by applying the algorithm to pairs datasets differing in one individual.After the introduction of differential privacy, several variants of the original definition have been proposed by changing the measure of dissimilarity between distributions, including concentrated, zero-concentrated and R{\'e}nyi differential privacy. The first contribution of this paper is to introduce the notion of privacy profile of a mechanism.This profile captures all valid $(\varepsilon,\delta)$ differential privacy parameters satisfied by a given mechanism, and contrasts with the usual approach of providing guarantees in terms of a single point in this curve.We show that knowledge of this curve is equivalent to knowledge of the privacy guarantees with respect to the alternative definitions listed above.This sheds further light into the connections between different privacy definitions, and suggests that these should be considered alternative but otherwise equivalent points of view. The second contribution of this paper is to apply the privacy profiles machinery to study the so-called ``privacy amplification by subsampling'' principle, which ensures that a differentially private mechanism run on a random subsample of a population provides higher privacy guarantees than when run on the entire population.Several instances of this principle have been studied for different random subsampling methods, each with an ad-hoc analysis. In this paper we set out to study this phenomenon in detail with the aim to provide a general method capable of recovering prior analyses in a streamlined fashion.Our method makes extensive use of coupling argument, and introduces a new tool to analyse differential privacy for mixture distributions.
Correlation between portal vein diameter and craniocaudal length of the spleen

Abstract Objective: To determine the correlation between portal vein diameter and spleen size (craniocaudal). Methodology: The study was conducted at the University Ultrasound Clinic, The University of Lahore, Lahore Pakistan from 1st January to 1st July 2013. All the individuals who referred for abdominal sonographic examination, including male, female, older and younger were conveniently included in the study, voluntarily, irrespective of the disease state. Ultrasonographic measurements of the caudocranial length of the spleen and portal vein were carried out on all of the one thousand subjects. The subject position for spleen was supine or right posterior oblique during suspended inspiration and right anterior oblique position for portal vein diameter with quiet respiration. The correlation between the splenic length and portal vein diameter was evaluated. Result: A total of 1000 subjects; 36.9% females and 63.1% males aged from 4 to 79 years. The mean splenic length was 10.29 ± 1.89 cm. The mean portal vein diameter was 10.27 ± 1.78 mm. A statistically significant correlation was found between the spleen size and portal vein diameter; the Pearson correlation was significant at the 0.01 level. Conclusion: Portal vein diameter is directly correlated to splenic caudocranial length. A regression formula was developed to measure the splenic length from the calculation of portal vein diameter.
PETSc: An Advanced Math and Computing Framework for Rapidly Developing Parallel Smart Grid Applications

Developing parallel (scalable) software for smart grid applications is a challenging task entailing considerable time and effort. This paper introduces the open source highperformance library PETSc (Portable Extensible Toolkit for Scientific computation) as a potential math and computing framework for rapid development of parallel smart grid applications. PETSc has been tested on a gamut of scientific applications on single-core machines to supercomputers, has highly optimized implementations, and includes a wide array of tested numerical solvers. We provide an overview of PETSc’s mathematical and computing capabilities and discuss a few emerging power system applications that can be developed by using PETSc.
MICROMYCETES IN INDUSTRIAL AND HOUSEHOLD DUST: PECU LIARITIES, EFFECT ON MANUFACTURING AND PEOPLE’S SAFETY

Taking into account that dust is an aggressive env iro ment factor which often determines the success of food-stuff production, the durability of technologi cal equipment and people’s safety, dust from 8 grou ps of premises of different purposes was collected and compared. O ne hundred test portions were taken and investigate d from 28 premises of different purposes. The humidity of dus t, the variety of inorganic and organic substances, du t elemental composition, its contamination with propagules and myotoxins were determined, the micromycetes detecte d in dust were isolated and identified. The major part of iso lates detected in dust were ascribed to the micromy cetes of Penicillium genus, which due to their biological peculiarities are able to spread rapidly and release toxic metab oli es into the environment: The degree of spreading of fungi of Aspergillus genus was somewhat lower. Some of the toxins mentioned which are synthesized and released into the environment (aflatoxins, ochratoxins, patulin) can be controlled.
Histogram-based Feature Extraction for GPS Trajectory Clustering

Clustering trajectories from GPS data is a crucial task for developing applications in intelligent transportation systems. Most existing approaches perform clustering on raw data consisting of series of GPS positions of moving objects over time. Such approaches are not suitable for classifying moving behaviours of vehicles, e.g., how to distinguish between a trajectory of a taxi and a trajectory of a private car. In this paper, we focus on the problem of clustering trajectories of vehicles having the same moving behaviours. Our approach is based on histogram-based feature extraction to model moving behaviours of objects and utilizes traditional clustering algorithms to group trajectories. We perform experiments on real datasets and obtain better results than existing approaches.
A Longitudinal View of Netflix: Content Delivery over IPv6 and Content Cache Deployments

We present an active measurement test (netflix) that downloads content from the Netflix content delivery network. The test measures latency and achievable throughput as key performance indicators when downloading the content from Netflix. We deployed the test on ~100 SamKnows probes connected to dual-stacked networks representing 74 different origin ASes. Using a ~2.75 year-long (Jul 2016–Apr 2019) dataset, we observe Netflix Open Connect Appliance (OCA) infrastructure to be highly available, although some vantage points experience low success rates connecting over IPv6. We witness that clients prefer connecting to Netflix OCAs over IPv6, although the preference over IPv6 tends to drop over certain peak hours during the day. The TCP connect times toward the OCAs have reduced by ~40% and the achievable throughput has increased by 20% over the measurement duration. We also provision scamper right after the netflix test to capture the forwarding path toward the Netflix OCAs. We observe that the Netflix OCA caches deployed inside the ISP are reachable within six IP hops and can reduce IP path lengths by 40% over IPv4 and by half over IPv6. Consequently, TCP connect times are reduced by 64% over both address families. The achieved throughput can~ also increase by a factor of three when such ISP caches are used to stream content. This is the first study to measure Netflix content delivery from residential networks, since the inception of the Netflix CDN infrastructure in 2011. To encourage reproducibility of our work, an anonymized version of the entire longitudinal dataset is publicly released.
SOLAR ENERGY TECHNOLOGIES, ENERGY-POVERTY NEXUS AND PUTTING THE LAST FIRST

DOI URL: https://doi.org/10.36713/epra3012 This paper reviews how renewable energy applications in rural areas could reduce poverty, create income generating enterprises, and improve overall well-being of communities. In addition to highlighting a wide range of cases from developing countries, the research also points out to multifarious applications of solar energy technologies for rural development. The conventional myths that the poor cannot afford nor manage smart technologies are not true, as evidenced in the cases presented in this paper. Another objective of this paper is to highlight and emphasise the role of institutions, both formal and informal, with their nested partnerships in supporting, promoting and enhancing the use renewable energy technology-based solutions in rural communities of developing and emerging (BRICs) economies.
SPOTTED OWL Strix occidentalis

Three subspecies are recognized: Mexican Spotted Owl (Strix occidentalis lucida), California Spotted Owl (S. occidentalis occidentalis), and Northern Spotted Owl (S. occidentalis caurina) (Dawson et al. 1986; Wilcove 1987). Starch-gel electrophoresis was unable to detect variation between S. occidentalis occidentalis and S. occidentalis caurina; however, S. occidentalis lucida did show variation, suggesting the possibility of two distinct species (Barrowclough and Gutierrez 1990). In addition, two separate evolutionary histories have been demonstrated by the major allelic frequency difference between occidentalis/caurina and lucida (Barrowclough and Gutierrez 1990).
Big Data Analysis on Montane Geography and Urban Development in Nepal

The Hindu Kush Himalayan (HKH) region is home to about 210 million people and is undergoing rapid urban sprawl. This study analyzed the correlation between the urban settlement and montane geography with ArcGIS and regression models. This study discovered that 81% of urban settlements are on valley floors (gradient < 3°) than slopes. Slope gradient (p-value = 0.0036) and soil type are correlated with urban intensity, but slope aspect is not. In terms of soil type, Cambisols, especially Eutric and Ferralic Cambisols are more suitable for urban settlements than other soils. This quantitative study on the urbanization process in Nepal will help to inform area-specific land use and urban planning policies, assist hazard vulnerability assessment and management, and offer basic urbanization data necessary to other environmental studies.
Construction of ANFIS Model Based on LM-Test for Forecasting of Chili Price Data in Semarang

The research aim is constructing Adaptive Neuro-Fuzzy Inference System (ANFIS) model for forecasting time series data. The ANFIS model is constructed and applied to chili price data in Semarang. The daily data are written during December 2018 to May 2019. The input selection in ANFIS is done by using the Lagrange Multiplier (LM) test. The lag-1 with 2 membership functions is selected as optimal input. The performance of prediction based on in-sample data is measured by the values of mean absolute percentage error (MAPE) and root mean squares error (RMSE). The values of MAPE and RMSE are 2.9% and 939.8 respectively.
KORGAN: An Efficient PKI Architecture Based on PBFT Through Dynamic Threshold Signatures

During the past decade, several misbehaving certificate authorities (CAs) have issued fraudulent TLS certificates allowing man-in-the-middle (MITM) kinds of attacks that result in serious security incidents. In order to avoid such incidents, Yakubov et al. ((2018) A blockchain-based PKI management framework. NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, Taipei, Taiwan, April, pp. 16. IEEE) recently proposed a new public key infrastructure (PKI) architecture where CAs issue, revoke and validate X.509 certificates on a public blockchain. However, in their proposal TLS clients are subject to MITM kinds of attacks, and certificate transparency is not fully provided. In this paper, we eliminate the issues of the Yakubov et al.’s scheme and propose a new PKI architecture based on permissioned blockchain with PBFT consensus mechanism where the consensus nodes utilize a dynamic threshold signature scheme to generate signed blocks. In this way, the trust to the intermediary entities can be completely eliminated during certificate validation. Our scheme enjoys the dynamic property of the threshold signature because TLS clients do not have to change the verification key even if the validator set is dynamic. We implement our proposal on private Ethereum network to demonstrate the experimental results. The results show that our proposal has negligible overhead during TLS handshake. The certificate validation duration is less than the duration in the conventional PKI and Yakubov et al.’s scheme.
Isolation and detection of CAMv5S promoter and cry gene from the genetically modified cotton varieties

• Received: 12 July 2015 • Revised: 15 September 2015 • Accepted: 05 October 2015 • Published: 04 January 2016 • ABSTRACT Cotton (Gossypium arboretum) plays an important role in the day and daily life of humans. The production of cotton has been affected by various number of insect pest causes a serious infestation and infection which leads to vast damage to the cotton and its producers. In this study, the pre hybrid varieties such as MECH-184 and RCH 2 have been taken which was compared with a non Bt cotton variety (as a control) were studied for the presence of CaMV 35S promoter and cry genes. This has been studied using the PCR and lateral flow methods. From the results, these hybrid varieties have contained both the CaMV 35S promoter and cry genes.
On the construction of the european sentiment indicator

Economic sentiment surveys are carried out by all European Union member states and are often seen as early indicators for future economic developments. Based on these surveys, the European Commission constructs an aggregate European Economic Sentiment Indicator (ESI). This paper compares the ESI with more sophisticated aggregation schemes based on statistical methods: dynamic factor analysis and partial least squares. The indicator based on partial least squares clearly outperforms the other two indicators in terms of comovement with economic activity. In terms of forecast ability, the ESI, constructed in a rather ad hoc way, can compete with the other indicators.
What Were the Odds? Estimating the Market's Probability of Uncertain Events

An event study generates only a lower bound on the full effect of an event unless researchers know the probability that investors assigned to the event before it occurred. We develop two model-free methods for recovering the market’s priced-in probability of events. These methods require running event studies in financial options to complement the standard event study in stock prices. Validating both approaches, we estimate that the 2016 U.S. election outcome had a 12% chance of occurring. This probability is consistent with contemporary polling, bookmaker, and prediction market estimates. Demonstrating the usefulness of our approaches, we show that many OPEC meetings’ outcomes were well-anticipated. OPEC retained substantial influence on world oil prices even as the U.S. increased oil production.
It's A Hard NACHT Life: Understanding How NLRP12 Ticks

The protein NODlike receptor pyrin domain containing 12 (NLRP12) comes from a family of protein receptors with a wide range of functions including fertility as well as anti-inflammatory properties. The biological role of NLRP12 is poorly understood: research on the mechanisms behind its function and/or activation remains contradictory between different cell models. Current research suggests its involvement in a multi-protein complex named the inflammasome. The alternative hypothesis that has also been proposed is that NLRP12 is not a part of the inflammasome, rather it negatively regulates a transcription factor known as NF-κB down stream of Toll-like receptors. NLRP12 is important because if it is mutated, research has found it can cause severe inflammation in the colon (colitis) and even lead to certain types of colorectal cancer. Other experiments have shown that NLRP12 is also responsible for causing a wide range of autoimmune diseases in humans. Thus, if we can control NLRP12, we might be able to provide better treatments for these debilitating diseases. I propose that by performing a yeast-2hybrid screen, that I can find new proteins that can unveil NLRP12’s function(s). My research has identified three ubiquitin associated proteins that interact with NLRP12; including: CUL3, RNF2, and COPS5 proteins. The functions of all three of these proteins lead me to believe NLRP12 may participate in a ubiquitin pathway to regulate inflammation. In addition, I found NLRP12 also interacted with IFIT1, which is known to interfere with virus infection and is also associated with ubiquitination. This new information could help provide details to unveiling how NLRP12 functions in relation to different proteins it interacts with in vivo.
A Critical Review on the Rise of Social Enterprise as a Foundation of Motivation and Innovation in Entrepreneurship

This paper examines the emergence of social enterprise in modern business world and argues that conventional entrepreneurship in open market system, capitalism and laissez faire is retreating and giving way to more socially anchored entrepreneurship. This paper addresses the question on the dynamic impacts of social enterprise on the trajectory of motivation, innovation and sustainability entrepreneurship in modern business world. This paper maintains that social enterprise is a growing and unstopable phenomenon and could assume the central role of entrepreneurship in future.
Fundamental Driven Liquidity Traps: A Unified Theory of the Great Depression and the Great Recession

This paper integrates the New Keynesian literature on the liquidity trap to offer a unified theory of the Great Recession and the Great Depression in the United States. We first give an overview of fast moving forces that can lead to a liquidity trap, such as a banking crisis and debt deleveraging shocks and then turn to long acting forces such as the aging of the population and a rise in inequality. These latter forces are often associated with the idea of secular stagnation. We then analyze a number of monetary and fiscal policy interventions within the standard New Keynesian model as well as in a model in which there is a permanent trap. The paper closes by applying the theory to understand the onset and recovery from the U.S. Great Depression and addressing key questions related to the U.S. Great Recession. — Preliminary, First Draft, Comments Welcome, please address to Gauti_Eggertsson@brown.edu —-
The Effect of Customer Relationship Management Practices on Airline Customer Loyalty

Customer satisfaction and loyalty are important concerns for travel providers and have a significant role in maximizing their sales. Therefore, adopting the activities of customer relationship management could help them building strong relationships with customers. This study explores the opinions of EgyptAir passengers on customer relationship management activities adopted by the company and how this affects their satisfaction and loyalty. A questionnaire was used for data collection and structural equation modelling was employed for rigorous findings. Findings revealed a positive significant effect of shared values, bonding, commitment, trust, tangibility, and handling customer conflicts on passenger satisfaction and loyalty.
Cardiopulmonary bypass induced inflammation: pathophysiology and treatment

The severity of the systemic inflammatory response syndrome may vary widely,ranging from being barely detectable to multiple organ dysfunction syndrome.While researching the development of the CPB-induced acute phase reaction,its pathogenesis gradually discovered and some new pharmacological,technical,surgical strategies are used in clinical practive in order to find the most possible method to prevent and cure it.
The role of the Regional Innovation System approach in contemporary regional policy: is it still relevant in a globalised world?

The Regional Innovation System (RIS) approach has had a significant impact on the design and implementation of regional innovation policies. However, is the regional level still a relevant scale of policy making in a globalised world and can the RIS approach still produce important insights on how to promote regional socio-economic development? This working paper is a pre-print version of a forthcoming chapter in the book ‘Regions and innovation policies in Europe: learning from the margins’, edited by Manuel Gonzalez-Lopez and Bjørn T. Asheim (2021), Edward Elgar, Cheltenham.
Analysis of Routine and Integrative Data from Clostridioides difficile Infection Diagnosis and the Consequent Observations

Clostridioides difficileInfection (CDI) is an acute disease that needs a fast proper treatment. Unfortunately, the diagnosis, and above all the understanding of the results, remain arduous.This study analyzed routine and integrative results of all fecal samples from patients over time. Our aim was to understand the dynamics of CDI infection and the meaning of “difficult to interpret” results, to make physicians better understand the various tools they can use.We evaluated routine results obtained from 815 diarrheal stools with Enzyme Immunoassay (EIA) that detectsC. difficileGlutamate Dehydrogenase (GDH) antigen and toxin B. We also reanalyzed a part of samples using integrative tests: a Real-time polymerase chain reaction (RT-PCR) forC. difficiletoxin B gene (tcdB) and the automated immunoassay VIDASC. difficilesystem for GDH and toxins A/B.EIA GDH positivity increased through multiple testing over time, with aPvalue <0.001, depicting a sort of bacterial growth curve. Eighty-five percent of GDH positive/toxin B negative,i.e., discrepant, samples PCR weretcdBpositive, 61.5% of discrepanttcdBpositive samples were VIDAS toxins A/B positive, and 44.4% of GDH EIA negative stools were VIDAS GDH positive.The results confirmed the low sensitivity of the EIA system forC. difficileGDH and toxins, questioned the use of the latter for concluding any CDI diagnostic algorithm, and led us to indicate the algorithm beginning with tcdB molecular research, and continuing in positive cases with VIDAS CD GDH method, as the most effective for CDI.
Privacy Amplification of Iterative Algorithms via Contraction Coefficients

We investigate the framework of privacy amplification by iteration, recently proposed by Feldman et al., from an information-theoretic lens. We demonstrate that differential privacy guarantees of iterative mappings can be determined by a direct application of contraction coefficients derived from strong data processing inequalities for f-divergences. In particular, by generalizing the Dobrushin’s contraction coefficient for total variation distance to an f-divergence known as Eγ-divergence, we derive tighter bounds on the differential privacy parameters of the projected noisy stochastic gradient descent algorithm with hidden intermediate updates.
International Trade , Spillovers and Regional Income Disparity

To explain China’s regional income disparity, heterogeneous production functions for different regions have been introduced recently. This study extends this contribution by developing a multi-regional model, based on China’s 2002 updated interregional input-output table. It is found that interregional trade and regional income disparities are partly explained by a region’s position in the global supply chain. Typically, the South Coast and East Coast regions locate in the top tier of the hierarchy while the Central, Northwest and Southwest regions represent the lower end. Moreover, it is shown by a scenario analysis that regional disparity will persist, but may be alleviated in the short run by Regional Development Programs.