bluuebunny/crossref_metadata_2025 huggingface dataset:
Are the Player Selection Process and Performance Influenced by Relative Age Effect in Elite Women’s Handball?
Authors: la Rubia Alfonso , Lorenzo-Calvo Jorge , Rivilla-García Jesús , Marquina Moisés
Published: November 2021

The relative age effect (RAE) is a phenomenon present in team sports, but it does not influence each gender to the same extent. This study aimed to examine the RAE and its relation to performance in international women's handball competitions (2017/18 World Championships). The sample was composed of 1,096 female players distributed into three categories: youth or under 18 (n = 369); junior or under 20 (n = 328) and senior (n = 399). The teams were divided into four groups based on their final position (medalist, quarter-finalist, eight-finalist and bottom-eight teams). The birthdate distribution (trimesters and semesters) was analysed according to the competition category and the playing position. Differences between the expected and observed birthdate distribution were checked using the chi-square statistical test followed by the calculation of the odds ratio. The results revealed, by trimester, the presence of the RAE in the youth (x2(7) = 87.22; p < 0.001) and junior (x2 (7) = 33.12; p < 0.001) categories, with no impact on senior (p > 0.05). The effect size was relatively strong in the youth category (Vc = 0.48). By semester, the prevalence of the RAE was also found in the senior category (p < 0.05). According to the playing position, the RAE was especially detected in ‘goalkeeper’ (p < 0.01) and ‘centre-back’ (p < 0.05) positions, both in U-18 and U-20 categories. Surprisingly, this effect also appeared in the ‘back’ players in the senior category (p < 0.05). A prevalence of the RAE was identified in teams with a higher final position, but interestingly had a greater impact in the quarter-finalist teams (p < 0.001) than in the medalist teams (p < 0.01). The findings demonstrated that the RAE tends to decrease as the chronological age of players increases, demonstrating a strong presence according to collective performance in international women’s handball.
Exploration of the Age-Category Soccer Performance Effects During Ball Possession Small-Sided Games
Authors: André Nunes Nuno , Gonçalves Bruno , SJ Fenner Jonathan , Owen Adam , Travassos Bruno
Published: November 2021

Small-sided games have been adopted as an integral part of soccer training, however, the use of task constraints by the coach and the action capabilities of both players and teams require further investigation. The aim of this investigation was to explore the age-category effects (under-11: U11, under-15: U15 and under-23: U23) on external training workloads (total distance covered, distance covered while walking, running and sprinting, number of sprints and maximum sprint speed), internal training load metrics (rate of perceived exertion, RPE) and tactical individual actions (passing number with dominant and non-dominant foot, and max passing speed) during 4 vs. 4 ball possession small-sided game constrained within three different playing areas (small: 20 x 15 m, medium: 25 x 20 m, and large: 30 x 25 m). Results revealed substantial differences (all p < .001) for each specific playing area observed across many of the external workload measures. For every area analysed, U23 players covered more distance walking, whereas U11 and U15 players covered more distances at higher intensities. Additionally, significant differences were found for the RPE (small playing area: p = .001; large playing area: p < .001) with U23 and U15 players showing higher scores compared with U11 ones. It can be concluded that a 4 vs. 4 ball possession small-sided game can provide different performance related stimuli to players, depending on age category and the playing surface area. Therefore, coaches and individuals involved with training and development of soccer players across all age groups should be aware of the key variables highlighted in this study before planning training drills.
Robust decentralized controller design in time domain: Equivalent subsystem approach
Authors: Veselý Vojtech
Published: November 2021

In this paper, the original method to design of PID robust decentralized controller is obtained for linear time-invariant large-scale uncertain system. The controller design procedure performs on the subsystem level such that the closed-loop stability and performance of complex system in the frame of the designer chosen controller design procedure ( H
2
, L
2 -gain, pole placement,...) is guaranteed. The proposed method is implemented in two steps. In the first step, the required dynamic properties of the subsystems are determined so as to ensure the stability of complex system. In the second step, on the subsystem level a decentralized controller design is provided using any suitable design procedure for each subsystem.
On possible energy savings with transmission supported via feedback channel in CubeSat transceiver
Authors: Farkaš Peter , Rakús Martin
Published: November 2021

Recently a transmission technique, which can save energy thanks to supportive transmission in the feedback channel, was presented for transmitted information with different probability distributions. The basic assumption for its practical exploitation is that a node collecting information has enough energy - much more than the supported node. So far, in the published theoretical analysis it was assumed that the node does not consume energy for receiving the supporting sequence or that the amount of this energy is negligible comparing to energy needed for transmission. This paper makes the analyses more exact and practically oriented. Particularly, it estimates possible energy savings by incorporating the energy expenditures for receiving the supporting sequence in scenarios with Poisson distributed payload messages. The data from a real transceiver for CubeSat are used for obtaining the numerical results in these estimations.
Intelligent reflected surfaces assisted code domain non-orthogonal multiple access scheme
Authors: Shukla Aasheesh
Published: November 2021

The propagation medium plays a crucial role in any wireless communication networks, the channel between the transmitter and the receiver, deteriorate the quality of the received signal due to the uncontrollable interactions such as scattering, reflection, and refraction in the channel with the surrounding objects. To overcome this challenge, the recent advent of recongurable intelligent surfaces can be helpful, in which the network operators can control the radio waves,eg, the phase, amplitude, frequency, and even polarization, of the impinging signals without the need of complex decoding, encoding, and radio frequency processing operations. On the other hand, few research papers reported an efficient code domain non orthogonal multiple access (NOMA) such as Interleave division multiple access (IDMA) system for wireless information transfer. Persuaded by the capability of this arising RIS technology, the present article is aimed to provide the modified framework of IDMA (code-domain NOMA) communication system based on RIS technology. Simulation results demonstrate that the proposed system achieves better SNR performance than the conventional IDMA framework.
SNR improvement based on piecewise linear interpolation
Authors: Xu Pengfei , Jia Yinjie
Published: November 2021

Interpolation improves the resolution of the curve. Based on the stationary characteristics of the signal and the non-stationary characteristics of the noise, the theoretical proof indicates that the piecewise linear interpolation can improve the signal-to-noise ratio, which is further confirmed by simulation results.
Bioimpedance to assess the body composition of high-performance karate athletes: applications, advantages and perspectives
Authors: Rossi Luciana
Published: November 2021

Karate, a millennial martial art, was recently inserted among traditional Olympic combat sports for the Olympic Games in Japan. The aim of the present study is to determine, through bioimpedance analysis, the body composition of high-performance athletes participating in the São Paulo Olympic Karate Project. Participants were 22 athletes of both sexes, average age of 23.6 (6.0) years old, body mass of 66.6 (13.5) kg and fat percentage of 16.6 (5.5)%. Bioimpedance test indicated significant differences between sexes related to sexual dysmorphia, which had an impact on bioelectrical variables. Through comparative evaluation between male and female athletes, this study contributes to body composition analysis, indicating that, in the future, related bioimpedance tests should be used beyond their classical application, including phase angle, muscle function and other attributes.
Analysis of β-agonists in different biological matrices by liquid chromatography–tandem mass spectrometry
Authors: Śniegocki Tomasz , Sell Bartosz , Posyniak Andrzej
Published: November 2021

Introduction

Wide use is made of β-agonists in therapy due to their smooth muscle–relaxant properties. They also have a side effect of increasing muscle mass. Besides improving oxygen utilisation as bronchodilators, β-agonists increase protein synthesis and promote fat burning. The growth- and performance-enhancing effects are often exploited in illegal use. The guiding objective of this study was to develop a procedure for the determination of β-agonists by a single method in different types of matrices.

Material and Methods

Five grams of homogenised samples were subjected to enzymatic hydrolysis with β-glucuronidase in ammonium acetate, pH 5.2. Purification was performed by solid phase extraction. Analytes were eluted with 10% acetic acid in methanol. The eluted β-agonists were analysed by high-performance liquid chromatography–tandem mass spectrometry.

Results

Validation results met the requirement of the confirmation criteria according to European Commission Decision 2002/657/EC in terms of apparent recoveries (93.2–112.0%), repeatability (3.1–7.1%) and intra-laboratory reproducibility (4.1–8.2%).

Conclusion

The method can be successfully applied in the detection and determination of clenbuterol, salbutamol, mabuterol, mapenterol, terbutaline, brombuterol, zilpaterol, isoxsuprine and ractopamine in feed, drinking water, urine, muscle, lung and liver matrices.
The protective action of piperlongumine against mycobacterial pulmonary tuberculosis in its mitigation of inflammation and macrophage infiltration in male BALB/c mice
Authors: Lu Nihong , Yang Yongrui , Li Xiaofei , Li Jie , Cheng Jie , Lv Zhengxuan , Du Yingrong
Published: November 2021

Introduction

Piperlongumine (PL) is a bioactive alkaloid and medicinal compound of piperamide isolated from the long pepper (Piper longum Linn). It has demonstrated bactericidal action against Mycobacterium tuberculosis (MTB), the cause of pulmonary tuberculosis; nevertheless, immunomodulatory activity had not been identified for it in MTB-triggered granulomatous inflammation. This study investigated if piperlongumine could inhibit such inflammation.

Material and Methods

Mycobacterium tuberculosis strain H37Rv was subjected to a broth microdilution assay. Piperlongumine at 5, 15, and 25 μg/mL, 0.2% dimethyl sulphoxide as control or 4 μM of dexamethasone were tested in vitro on MH-S murine alveolar macrophages. BALB/c mice were orally administered PL at 50, 100 and 150 mg/kg b.w. after trehalose-6,6-dimycolate (TDM) stimulation. Chemokine and cytokine concentrations were determined in lung supernatants. Flow cytometry and Western blot analysis were performed to determine phosphorylated spleen tyrosine kinase (Syk), c-Jun N-terminal kinase (JNK) and extracellular signal-regulated kinase (ERK) pathways.

Results

Piperlongumine inhibited inflammatory mediators and adherence of lymphocyte function-associated antigen 1 to MH-S cells following TDM activation. It also improved macrophage clearance of MTB. In TDM-stimulated MH-S cells, PL significantly influenced the macrophage inducible Ca2+-dependent lectin receptor (Mincle)-Syk-ERK signalling pathway. Oral dosing of PL effectively suppressed the development of pulmonary granulomas and inflammatory reactions in the TDM-elicited mouse granuloma model.

Conclusion

PL as an inhibitor of MTB-triggered granulomatous inflammation may be an effective complementary treatment for mycobacterial infection.
“Just” Algorithms: Justification (Beyond Explanation) of Automated Decisions Under the General Data Protection Regulation
Authors: Malgieri Gianclaudio
Published: November 2021

This paper argues that if we want a sustainable environment of desirable AI systems, we should aim not only at transparent, explainable, fair, lawful, and accountable algorithms, but we also should seek for “just” algorithms, that is, automated decision-making systems that include all the above-mentioned qualities (transparency, explainability, fairness, lawfulness, and accountability). This is possible through a practical “justification” statement and process (eventually derived from algorithmic impact assessment) through which the data controller proves, in practical ways, why the AI system is not unfair, not discriminatory, not obscure, not unlawful, etc. In other words, this justification (eventually derived from data protection impact assessment on the AI system) proves the legality of the system with respect to all data protection principles (fairness, lawfulness, transparency, purpose limitation, data minimisation, accuracy, storage limitation, integrity, and accountability). All these principles are necessary components of a broader concept of just algorithmic decision-making and is already required by the GDPR, in particular considering: the data protection principles (Article 5), the need to enable (meaningful) contestations of automated decisions (Article 22) and the need to assess the AI system necessity, proportionality and legality under the Data Protection Impact Assessment model framework. (Article 35).
The Moral and Legal Status of Artificial Intelligence (Present Dilemmas and Future Challenges)
Authors: Milinkovic Igor
Published: November 2021

The rapid development of artificial intelligence (AI) systems raises dilemmas regarding their moral and legal status. Can artificial intelligence possess moral status (significance)? And under what conditions? Can one speak of the dignity of artificial intelligence as the basis of its moral status? According to some authors, if there are entities who have the capacities on which the dignity of human beings is based, they would also possess intrinsic dignity. If dignity is not an exclusive feature of human beings, such status also could be recognised by artificial intelligence entities. The first part of the paper deals with the problem of moral status of artificial intelligence and the conditions that must be fulfilled for such a status to be recognised. A precondition for the existence of moral status of artificial intelligence is its ability to make autonomous decisions. This part of the paper considers whether developing autonomous AI is justified, or, as some authors suggest, the creation of AI agents capable of autonomous action should be avoided. The recognition of the moral status of artificial intelligence would reflect on its legal status. The second part of the paper deals with the question of justifiability of ascribing legal personhood to the AI agents. Under what conditions would recognition of legal personhood by the artificial intelligence be justified and should its legal subjectivity be recognised in full scope or only partially (by ascribing to the AI agents a “halfway-status,” as some authors suggest)? The current state of the legal regulation of artificial intelligence will be observed as well.
Added value of sites suitable for sustainable office development
Authors: Kupec Josef
Published: November 2021

Valuations of real estate are widely used for various purposes and it relied always upon the financial and other markets. Valuation methodology is based on the operation of the free market economy and the real estate properties. The issue of certified properties is relatively new in the field of real estate valuation and is not sufficiently explored. Certified buildings are preferred by major corporate tenants with international field of activity who often have ethical rules for sustainable development. Therefore, certified properties are attractive to international commercial real estate investors who have higher purchasing power and are willing to pay a higher purchase price. Sustainable property certification is an element affecting the market value of the property. The purpose of this presented research is to quantify the impact of property certification on the value of office properties in Prague and subsequently to determine the impact of sustainability certificates on the market value of the land by using basic valuation techniques. The outcome of the project could be used by real estate valuation experts as a guideline to consider the future project certification and its impact on the land market value.
Personal information inference from voice recordings: User awareness and privacy concerns
Authors: Kröger Jacob Leon , Gellrich Leon , Pape Sebastian , Brause Saba Rebecca , Ullrich Stefan
Published: November 2021

Through voice characteristics and manner of expression, even seemingly benign voice recordings can reveal sensitive attributes about a recorded speaker (e. g., geographical origin, health status, personality). We conducted a nationally representative survey in the UK (n = 683, 18–69 years) to investigate people’s awareness about the inferential power of voice and speech analysis. Our results show that – while awareness levels vary between different categories of inferred information – there is generally low awareness across all participant demographics, even among participants with professional experience in computer science, data mining, and IT security. For instance, only 18.7% of participants are at least somewhat aware that physical and mental health information can be inferred from voice recordings. Many participants have rarely (28.4%) or never (42.5%) even thought about the possibility of personal information being inferred from speech data. After a short educational video on the topic, participants express only moderate privacy concern. However, based on an analysis of open text responses, unconcerned reactions seem to be largely explained by knowledge gaps about possible data misuses. Watching the educational video lowered participants’ intention to use voice-enabled devices. In discussing the regulatory implications of our findings, we challenge the notion of “informed consent” to data processing. We also argue that inferences about individuals need to be legally recognized as personal data and protected accordingly.
(∈, δ)-Indistinguishable Mixing for Cryptocurrencies
Authors: Liang Mingyu , Karantaidou Ioanna , Baldimtsi Foteini , Gordon S. Dov , Varia Mayank
Published: November 2021

We propose a new theoretical approach for building anonymous mixing mechanisms for cryptocurrencies. Rather than requiring a fully uniform permutation during mixing, we relax the requirement, insisting only that neighboring permutations are similarly likely. This is defined formally by borrowing from the definition of differential privacy. This relaxed privacy definition allows us to greatly reduce the amount of interaction and computation in the mixing protocol. Our construction achievesO(n·polylog(n)) computation time for mixingnaddresses, whereas all other mixing schemes requireO(n2) total computation across all parties. Additionally, we support a smooth tolerance of fail-stop adversaries and do not require any trusted setup. We analyze the security of our generic protocol under the UC framework, and under a stand-alone, game-based definition. We finally describe an instantiation using ring signatures and confidential transactions.
How Can and Would People Protect From Online Tracking?
Authors: Mehrnezhad Maryam , Coopamootoo Kovila , Toreini Ehsan
Published: November 2021

Online tracking is complex and users find it challenging to protect themselves from it. While the academic community has extensively studied systems and users for tracking practices, the link between the data protection regulations, websites’ practices of presenting privacy-enhancing technologies (PETs), and how users learn about PETs and practice them is not clear. This paper takes a multidimensional approach to find such a link. We conduct a study to evaluate the 100 top EU websites, where we find that information about PETs is provided far beyond the cookie notice. We also find that opting-out from privacy settings is not as easy as opting-in and becomes even more difficult (if not impossible) when the user decides to opt-out of previously accepted privacy settings. In addition, we conduct an online survey with 614 participants across three countries (UK, France, Germany) to gain a broad understanding of users’ tracking protection practices. We find that users mostly learn about PETs for tracking protection via their own research or with the help of family and friends. We find a disparity between what websites offer as tracking protection and the ways individuals report to do so. Observing such a disparity sheds light on why current policies and practices are ineffective in supporting the use of PETs by users.
Towards Improving Code Stylometry Analysis in Underground Forums
Authors: Tereszkowski-Kaminski Michal , Pastrana Sergio , Blasco Jorge , Suarez-Tangil Guillermo
Published: November 2021

Code Stylometry has emerged as a powerful mechanism to identify programmers. While there have been significant advances in the field, existing mechanisms underperform in challenging domains. One such domain is studying the provenance of code shared in underground forums, where code posts tend to have small or incomplete source code fragments. This paper proposes a method designed to deal with the idiosyncrasies of code snippets shared in these forums. Our system fuses a forum-specific learning pipeline with Conformal Prediction to generate predictions with precise confidence levels as a novelty. We see that identifying unreliable code snippets is paramount to generate high-accuracy predictions, and this is a task where traditional learning settings fail. Overall, our method performs as twice as well as the state-of-the-art in a constrained setting with a large number of authors (i.e., 100). When dealing with a smaller number of authors (i.e., 20), it performs at high accuracy (89%). We also evaluate our work on an open-world assumption and see that our method is more effective at retaining samples.
Ulixes: Facial Recognition Privacy with Adversarial Machine Learning
Authors: Cilloni Thomas , Wang Wei , Walter Charles , Fleming Charles
Published: November 2021

Facial recognition tools are becoming exceptionally accurate in identifying people from images. However, this comes at the cost of privacy for users of online services with photo management (e.g. social media platforms). Particularly troubling is the ability to leverage unsupervised learning to recognize faces even when the user has not labeled their images. In this paper we propose Ulixes, a strategy to generate visually non-invasive facial noise masks that yield adversarial examples, preventing the formation of identifiable user clusters in the embedding space of facial encoders. This is applicable even when a user is unmasked and labeled images are available online. We demonstrate the effectiveness of Ulixes by showing that various classification and clustering methods cannot reliably label the adversarial examples we generate. We also study the effects of Ulixes in various black-box settings and compare it to the current state of the art in adversarial machine learning. Finally, we challenge the effectiveness of Ulixes against adversarially trained models and show that it is robust to countermeasures.
User Perceptions of Gmail’s Confidential Mode
Authors: Qahtani Elham Al , Javed Yousra , Shehab Mohamed
Published: November 2021

Gmail’s confidential mode enables a user to send confidential emails and control access to their content through setting an expiration time and passcode, pre-expiry access revocation, and prevention of email forwarding, downloading, and printing. This paper aims to understand user perceptions and motivations for using Gmail’s confidential mode (GCM). Our structured interviews with 19 Gmail users at UNC Charlotte show that users utilize this mode to share their private documents with recipients and perceive that this mode encrypts their emails and attachments. The most commonly used feature of this mode is the default time expiration of one week, and the least used feature is the pre-expiry access revocation. Our analysis suggests several design improvements.
Making the Most of Parallel Composition in Differential Privacy
Authors: Smith Josh , Asghar Hassan Jameel , Gioiosa Gianpaolo , Mrabet Sirine , Gaspers Serge , Tyler Paul
Published: November 2021

We show that the ‘optimal’ use of the parallel composition theorem corresponds to finding the size of the largest subset of queries that ‘overlap’ on the data domain, a quantity we call themaximum overlapof the queries. It has previously been shown that a certain instance of this problem, formulated in terms of determining the sensitivity of the queries, is NP-hard, but also that it is possible to use graph-theoretic algorithms, such as finding the maximum clique, to approximate query sensitivity. In this paper, we consider a significant generalization of the aforementioned instance which encompasses both a wider range of differentially private mechanisms and a broader class of queries. We show that for a particular class of predicate queries, determining if they are disjoint can be done in time polynomial in the number of attributes. For this class, we show that the maximum overlap problem remains NP-hard as a function of the number of queries. However, we show that efficient approximate solutions exist by relating maximum overlap to the clique and chromatic numbers of a certain graph determined by the queries. The link to chromatic number allows us to use more efficient approximate algorithms, which cannot be done for the clique number as it may underestimate the privacy budget. Our approach is defined in the general setting off-differential privacy, which subsumes standard pure differential privacy and Gaussian differential privacy. We prove the parallel composition theorem forf-differential privacy. We evaluate our approach on synthetic and real-world data sets of queries. We show that the approach can scale to large domain sizes (up to 1020000), and that its application can reduce the noise added to query answers by up to 60%.
Proof-of-Vax: Studying User Preferences and Perception of Covid Vaccination Certificates
Authors: Kowalewski Marvin , Herbert Franziska , Schnitzler Theodor , Dürmuth Markus
Published: November 2021

Digital tools play an important role in fighting the current global COVID-19 pandemic. We conducted a representative online study in Germany on a sample of 599 participants to evaluate the user perception of vaccination certificates. We investigated five different variants of vaccination certificates based on deployed and planned designs in a between-group design, including paper-based and app-based variants. Our main results show that the willingness to use and adopt vaccination certificates is generally high. Overall, paper-based vaccination certificates were favored over app-based solutions. The willingness to use digital apps decreased significantly by a higher disposition to privacy and increased by higher worries about the pandemic and acceptance of the coronavirus vaccination. Vaccination certificates resemble an interesting use case for studying privacy perceptions for health-related data. We hope that our work will educate the currently ongoing design of vaccination certificates, give us deeper insights into the privacy of health-related data and apps, and prepare us for future potential applications of vaccination certificates and health apps in general.
Circuit-PSI With Linear Complexity via Relaxed Batch OPPRF
Authors: Chandran Nishanth , Gupta Divya , Shah Akash
Published: November 2021

In 2-party Circuit-based Private Set Intersection (Circuit-PSI), P
0 and P
1 hold sets S0 and S1 respectively and wish to securely compute a function f over the set S0 ∩ S1 (e.g., cardinality, sum over associated attributes, or threshold intersection). Following a long line of work, Pinkas et al. (PSTY, Eurocrypt 2019) showed how to construct a concretely efficient Circuit-PSI protocol with linear communication complexity. However, their protocol requires super-linear computation.

In this work, we construct concretely efficient Circuit-PSI protocols with linear computational and communication cost. Further, our protocols are more performant than the state-of-the-art, PSTY – we are ≈ 2.3× more communication efficient and are up to 2.8× faster. We obtain our improvements through a new primitive called Relaxed Batch Oblivious Programmable Pseudorandom Functions (RB-OPPRF) that can be seen as a strict generalization of Batch OPPRFs that were used in PSTY. This primitive could be of independent interest.
Polymath: Low-Latency MPC via Secure Polynomial Evaluations and Its Applications
Authors: Lu Donghang , Yu Albert , Kate Aniket , Maji Hemanta
Published: November 2021

While the practicality of secure multi-party computation (MPC) has been extensively analyzed and improved over the past decade, we are hitting the limits of efficiency with the traditional approaches of representing the computed functionalities as generic arithmetic or Boolean circuits. This work follows the design principle of identifying and constructing fast and provably-secure MPC protocols to evaluate useful high-level algebraic abstractions; thus, improving the efficiency of all applications relying on them. We present Polymath, a constant-round secure computation protocol suite for the secure evaluation of (multi-variate) polynomials of scalars and matrices, functionalities essential to numerous data-processing applications. Using precise natural precomputation and high-degree of parallelism prevalent in the modern computing environments, Polymath can make latency of secure polynomial evaluations of scalars and matrices independent of polynomial degree and matrix dimensions.

We implement our protocols over the HoneyBadgerMPC library and apply it to two prominent secure computation tasks: privacy-preserving evaluation of decision trees and privacy-preserving evaluation of Markov processes. For the decision tree evaluation problem, we demonstrate the feasibility of evaluating high-depth decision tree models in a generaln-party setting. For the Markov process application, we demonstrate that Poly-math can compute large powers of transition matrices with better online time and less communication.
If You Like Me, Please Don’t “Like” Me: Inferring Vendor Bitcoin Addresses From Positive Reviews
Authors: Schäfer Jochen , Müller Christian , Armknecht Frederik
Published: November 2021

Bitcoin and similar cryptocurrencies are becoming increasingly popular as a payment method in both legitimate and illegitimate online markets. Such markets usually deploy a review system that allows users to rate their purchases and help others to determine reliable vendors. Consequently, vendors are interested into accumulating as many positive reviews (likes) as possible and to make these public. However, we present an attack that exploits these publicly available information to identify cryptocurrency addresses potentially belonging to vendors. In its basic variant, it focuses on vendors that reuse their addresses. We also show an extended variant that copes with the case that addresses are used only once. We demonstrate the applicability of the attack by modeling Bitcoin transactions based on vendor reviews of two separate darknet markets and retrieve matching transactions from the blockchain. By doing so, we can identify Bitcoin addresses likely belonging to darknet market vendors.
Polaris: Transparent Succinct Zero-Knowledge Arguments for R1CS with Efficient Verifier
Authors: Fu Shihui , Gong Guang
Published: November 2021

We present a new zero-knowledge succinct argument of knowledge (zkSNARK) scheme for Rank-1 Constraint Satisfaction (RICS), a widely deployed NP-complete language that generalizes arithmetic circuit satisfiability. By instantiating with different commitment schemes, we obtain several zkSNARKs where the verifier’s costs and the proof size range fromO(log2N) toO(N)O\left( {\sqrt N } \right)depending on the underlying polynomial commitment schemes when applied to anN-gate arithmetic circuit. All these schemes do not require a trusted setup. It is plausibly post-quantum secure when instantiated with a secure collision-resistant hash function. We report on experiments for evaluating the performance of our proposed system. For instance, for verifying a SHA-256 preimage (less than 23k AND gates) in zero-knowledge with 128 bits security, the proof size is less than 150kB and the verification time is less than 11ms, both competitive to existing systems.
SoK: Cryptographic Confidentiality of Data on Mobile Devices
Authors: Zinkus Maximilian , Jois Tushar M. , Green Matthew
Published: November 2021

Mobile devices have become an indispensable component of modern life. Their high storage capacity gives these devices the capability to store vast amounts of sensitive personal data, which makes them a high-value target: these devices are routinely stolen by criminals for data theft, and are increasingly viewed by law enforcement agencies as a valuable source of forensic data. Over the past several years, providers have deployed a number of advanced cryptographic features intended to protect data on mobile devices, even in the strong setting where an attacker has physical access to a device. Many of these techniques draw from the research literature, but have been adapted to this entirely new problem setting.

This involves a number of novel challenges, which are incompletely addressed in the literature. In this work, we outline those challenges, and systematize the known approaches to securing user data against extraction attacks. Our work proposes a methodology that researchers can use to analyze cryptographic data confidentiality for mobile devices. We evaluate the existing literature for securing devices against data extraction adversaries with powerful capabilities including access to devices and to the cloud services they rely on. We then analyze existing mobile device confidentiality measures to identify research areas that have not received proper attention from the community and represent opportunities for future research.
The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites
Authors: Namara Moses , Sloan Henry , Knijnenburg Bart P.
Published: November 2021

Research finds that the users of Social Networking Sites (SNSs) often fail to comprehensively engage with the plethora of available privacy features— arguably due to their sheer number and the fact that they are often hidden from sight. As different users are likely interested in engaging with different subsets of privacy features, an SNS could improve privacy management practices by adapting its interface in a way that proactively assists, guides, or prompts users to engage with the subset of privacy features they are most likely to benefit from. Whereas recent work presents algorithmic implementations of such privacy adaptation methods, this study investigates the optimal user interface mechanism to present such adaptations. In particular, we tested three proposed“adaptation methods”(automation, suggestions, highlights) in an online between-subjects user experiment in which 406 participants used a carefully controlled SNS prototype. We systematically evaluate the effect of these adaptation methods on participants’ engagement with the privacy features, their tendency to set stricter settings (protection), and their subjective evaluation of the assigned adaptation method. We find that theautomationof privacy features afforded users the most privacy protection, while giving privacysuggestionscaused the highest level of engagement with the features and the highest subjective ratings (as long as awkward suggestions are avoided). We discuss the practical implications of these findings in the effectiveness of adaptations improving user awareness of, and engagement with, privacy features on social media.
Vibro piles performance prediction using result of CPT
Authors: Więcławski Paweł
Published: November 2021

Vibro piles belong to the group of full displacement piles with an expanded base, characterised by a very high load capacity, especially in non-cohesive soils. The problem is to adopt a reliable method for the determination of full load–settlement (Q–s) curve. A frequent difficulty is the determination of the load capacity limit based on the static load test because the course of the load–settlement curve is of a linear nature. This publication presents the empirical method. It allows direct prediction of a full axially loaded pile settlement curve based on the values of qc cone resistance obtained in cone penetration test (CPT). The advantage offered by this procedure is the accuracy of the obtained limit values in relation to the actual load-bearing capacity as compared to other methods based on soil parameters obtained in in situ testing. An additional advantage is the Q–s characteristics, which enable designing for intermediate values, allowing for the criterion of minimal or equal settlements. The shape of analytical curves was compared with static pile load test (SPLT) curves. This comparison showed large convergences between the analytical and measured curves.
Exploring Perceptions of Religion and Science among Turkish Academics
Authors: Sevinç Kenan , Coleman Thomas J. , Farias Miguel
Published: November 2021

The religiosity of academics has been studied for over a decade. With few exceptions, this research has been conducted on American “elite” scientists, and data from non-Western countries is lacking. Drawing from psychological and sociological literature, the present exploratory study investigates the religiosity of Turkish academics (N = 361) and their perceptions on the relationship between religion and science, and associated variables such as interpretation of the Quran, and belief in evolution and creationism. Moreover, we address criticism directed at previous research by probing for different God concepts among believing academics. Although cultural differences can be identified, the results generally support the idea that academics are less religious with 54% identifying as “less religious” or “not religious,” compared to 24.2% self-identifying as “religious” or “extremely religious.”
Reconciling the Irreconcilable: A Property Rights Approach to Resolving the Animal Rights Debate
Authors: Cesario Anthony J.
Published: November 2021

Libertarianism is understood to be a “deontological theory of law” that purportedly applies exclusively to humans. According to some libertarians, however, “one of the greatest weaknesses of libertarian theory” is that there are no provisions outlawing the abuse and torture of animals even though this seems to be one of “the most heinous acts it is possible to do”. Moreover, a few of these libertarians go even further and claim that this legal philosophy of non-aggression should actually be extended to include other animals. The purpose of this paper is to reconcile this seemingly irreconcilable situation by arguing that it is a “continuum problem” and offering a principled, libertarian compromise that resolves the animal rights debate using the non-aggression principle (NAP) and private property rights.
Rejoinder to Huemer on Animal Rights
Authors: Block Walter E.
Published: November 2021

Heumer and I debate animal rights, utilitarianism, libertarianism, morality and philosophy. We agree that suffering is a problem, and diverge, widely, on how to deal with it. I maintain that this author’s reputation as a libertarian, let alone an intellectual leader of this movement, is problematic. Why? That is because libertarianism, properly understood, is a theory of intra-human rights; this philosophy says nothing about right from an extra-human perspective, Heumer to the contrary notwithstanding. That is to say, he is improperly importing into the freedom philosophy considerations extraneous to it.
Development of Reliable Models of Signal-Controlled Intersections
Authors: Glushkov Alexandr , Shepelev Vladimir
Published: November 2021

The paper considers an approach to building various mathematical models for homogeneous groups of intersections manifested through the use of clustering methods. This is because of a significant spread in their traffic capacity, as well as the influence of several random factors. The initial data on the traffic flow of many intersections was obtained from real-time recorders of the convolutional neural network. As a result of the analysis, we revealed statistically significant differences between the groups of intersections and compiled their linear regression models as a basis for the subsequent formation of generic management decisions. To demonstrate visually the influence of random factors on the traffic capacity of intersections, we built distribution fields based on the fuzzy logic methods for one of the clusters consisting of 14 homogeneous intersections. Modeling was based on the Gaussian type of membership functions as it most fully reflects the random nature of the pedestrian flow and its discontinuity.
Real-Time Lane Line Tracking Algorithm to Mini Vehicles
Authors: Suto Jozsef
Published: November 2021

Autonomous navigation is important not only in autonomous cars but also in other transportation systems. In many applications, an autonomous vehicle has to follow the curvature of a real or artificial road or in other words lane lines. In those application, the key is the lane detection. In this paper, we present a real-time lane line tracking algorithm mainly designed to mini vehicles with relatively low computation capacity and single camera sensor. The proposed algorithm exploits computer vision techniques in combination with digital filtering. To demonstrate the performance of the method, experiments are conducted in an indoor, self-made test track where the effect of several external influencing factors can be observed. Experimental results show that the proposed algorithm works well independently of shadows, bends, reflection and lighting changes.
Aviation Profiling Method Based on Deep Learning Technology for Emotion Recognition by Speech Signal
Authors: Koshekov К.Т. , Savostin А.А. , Seidakhmetov B.K. , Anayatova R.K. , Fedorov I.O.
Published: November 2021

This paper proposes a method of automatic speaker-independent recognition of human psycho-emotional states by analyzing the speech signal based on Deep Learning technology to solve the problems of aviation profiling. For this purpose, an algorithm to classify seven human psycho-emotional states, including anger, joy, fear, surprise, disgust, sadness, and neutral state was developed. The algorithm is based on the use of Mel-frequency cepstral coefficients and Mel spectrograms as informative features of speech signals audio recordings. These informative features are used to train two deep convolutional neural networks on the generated dataset. The developed classifier testing on a delayed verification dataset showed that the metric for the multiclass fraction of correct answers’ accuracy is 0.93. The solution proposed in the paper can be in demand in human-machine interfaces creation, medicine, marketing, and in the field of air transportation.
PEMODELAN ALIRAN AIRTANAH UNTUK SISTEM MANJEMEN DAN PEMBANGUNAN DI KAWASAN PERKOTAAN KABUPATEN MAJENE, PROVINSI SULAWESI BARAT
Authors: Marwadi Aji
Published: November 2021

Model air tanah yang digambarkan komputer merupakan sebuah representasi dari keadaan sebenarnya yang mewakilinya di lapangan, sehingga dapat berfungsi sebagai monitoring dan perkiraan suatu sistem aliran air tanah di masa depan. Tujuan dari penelitian ini adalah pemodelan aliran air tanah yang dapat mewakili kondisi sebenarnya yang terjadi di kawasan perkotaan Kabupaten Majene. Pemodelan dilakukan dengan cara numerik menggunakan Visual Modflow. Data masukan yang dibutuhkan adalah : korelasi data logbor/geolistrik, batas (boundary) lokasi penelitian yang akan dimodelkan yaitu river boundary, pengukuran serta pengamatan kondisi sungai sebagai river boundary, data imbuhan air tanah (infiltrasi) diperoleh dengan menggunakan neraca air tanah dari olahan data curah hujan dan suhu udara, pengukuran tinggi muka air tanah sebagai penentuan alat validasi model untuk mendekati kondisi nyata di lapangan. Hasil dari penelitian ini berupa model aliran air tanah yang dapat digunakan untuk sistem manajemen air tanah sebagai alat pengambilan keputusan bagi pihak perencana proyek dan lembaga pemerintah dalam memprediksi perubahan sistem aliran air tanah, penentuan lokasi pembangunan dan dapat sebagai monitoring intrusi air laut di masa depan sebagai perkotaan yang berada di pinggir pantai.
ESTIMASI KONSEPTUAL BIAYA PEMBANGUNAN DRAINASE DI WILAYAH KOTA SUKABUMI MENGGUNAKAN MODEL
Authors: Paikun Mochammed Paikun
Published: November 2021

Drainase merupakan bagian penting dalam penataan system penyediaan air dibidang pertanian, tata ruang dan sebagainya, oleh karena itu pembangunan drainase merupakan bagian penting. Pembangunan saluran drainase memerlukan biaya, tetapi mengestimasi biaya membutuhkan data perencanaan secara detiail, perlu analisa biaya material, tenaga kerja, alat, dan membutuhkan waktu yang cukup lama. Pada tahap awal penetapan anggaran biaya sering belum tersedia data gambar, sehingga tidak ada dasar untuk menentukan jumlah anggaran. Oleh karena itu penelitian ini penting untuk menghasilkan model, sebagai rumus untuk memperediksi biaya tahap awal ketika data gambar belum ada. Model ini dihasilkan menggunakan metode analisis regresi. Data analisis yang digunakan adalah data rencana anggaran biaya terperinci pembangunan drainase berdasarkan populasi pembangunan drainase tahun 2018-2020 diwilayah kota Sukabumi. Memprediksi biaya pembangunan drainase menggunakan model hasil penelitian ini, cukup memasukkan volume pembangunan drainase, maka total biaya pembangunan dapat di ketahui dengan cepat. Model ini khusus untuk memprediksi biaya pembangunan drainase terbuka dengan spesifikasi pasangan batu yang di plester aci, sedangkan untuk memprediksi biaya pembangunan derainase tertutup seperti drainase gorong -gorong, u-dits, gravel dan lain-lain perlu penelitian lebih lanjut, karena spesifikasinya berbeda.
How Point-of-Care Ultrasound led to a diagnosis of May-Thurner Syndrome
Authors: Belkin Daniel , Belkin Mitchell , Ashrafi Maedeh , Vegivinti Charan , Wang Yung-Hsien , Palaiodimos Leonidas
Published: November 2021

A 65-year-old man with a history of a left-sided inguinal hernia presented with three days of left-sided groin pain worsened with exertion and fatigue. The patient was afebrile but tachycardic, and physical examination revealed a tender, erythematous immobile bulge in his left groin. Laboratory studies revealed leukocytosis. Lymphadenopathy secondary to infectious or inflammatory etiology was suspected. However, point-of-care ultrasound (POCUS) identified extensive deep vein thrombosis (DVT) of the lower left limb. Follow-up imaging revealed this to be secondary to May-Thurner syndrome, a mechanical compression of an iliocaval vein against the lumbar vertebrae by a common iliac artery. This report demonstrates how POCUS can be used to identify lower extremity DVT, thereby expediting diagnosis and treatment and potentially preventing complications.