Lower Bound Research Articles

On the Hardy number of Koenigs domains

This work studies the Hardy number of hyperbolic planar domains satisfying Abel’s inclusion property, which are usually known as Koenigs domains. More explicitly, we prove that the Hardy number of a Koenings domains whose complement is non-polar is greater than or equal to 1/2, and this lower bound is sharp. In contrast to this result, we provide examples of general domains whose Hardy numbers are arbitrarily small. Additionally, we outline the connection of the aforementioned class of domains with the discrete dynamics of the unit disc and obtain results on the range of Hardy number of Koenigs maps, in the hyperbolic and parabolic case.

Novel approaches to improving gas separation: Ionic liquids coated coke/ NH2-UiO-66-based mixed matrix membranes for CO2/N2 separation

Permeability and separation efficiency of mixed matrix membranes (MMMs) are two important aspects. Polymeric membranes offer excellent mechanical and physical properties; however, they have a low permeability. To enhance the permeability and separation performance of polyvinyl chloride (PVC) membranes, Cholinium amino acid-based (IL) were impregnated with activated coke/ NH2-UiO-66 (Zr) (AC/MOF) composite and then IL@AC/MOF filler was incorporated into PVC matrix. FTIR spectroscopy, TGA, SEM, EDX, and Brunauer-Emmett-Teller (BET) surface area measurement were used to characterize the MMMs prepared. The porous structure of MMMs nanocomposites causes AC/MOF composite to effectively accelerate gas the diffusion in the PVC matrix. The permeability measurements for CO2 and N2 were made at 288.15, 298.15, 308.15, and 318.15 K at pressure 3 bar The outcomes indicates that the incorporation of the IL@AC/MOF filler increased the permeability of the PVC/AC/MOF MMMs compared to the pure polymeric membrane. The mixed matrix membranes exhibit superior gas separation performance, surpassing the 2008 Robson's Upper Bound.

Overcoming the Limitation of Ionomers on Mass Transport and Pt Activity to Achieve High-Performing Membrane Electrode Assembly.

The membrane electrode assembly (MEA) is one of the critical components in proton exchange membrane fuel cells (PEMFCs). However, the conventional MEA cathode with a covered-type catalyst/ionomer interfacial structure severely limits oxygen transport efficiency and Pt activity, hardly achieving the theoretical performance upper bound of PEMFCs. Here, we design a noncovered catalyst/ionomer interfacial structure with low proton transport resistance and high oxygen transport efficiency in the cathode catalyst layer (CL). This noncovered interfacial structure employs the ionomer cross-linked carbon particles as long-range and fast proton transport channels and prevents the ionomer from directly covering the Pt/C catalyst surface in the CL, freeing the oxygen diffusion process from passing through the dense ionomer covering layer to the Pt surface. Moreover, the structure improves oxygen transport within the pores of the CL and achieves more than 20% lower pressure-independent oxygen transport resistance compared to the covered-type structure. Fuel-cell diagnostics demonstrate that the noncovered catalyst/ionomer interfacial structure provides exceptional fuel-cell performance across the kinetic and mass transport-limited regions, with 77% and 67% higher peak power density than the covered-type interfacial structure under 0 kPagauge of oxygen and air conditions, respectively. This alternative interfacial structure provides a new direction for optimizing the electrode structure and improving mass-transport paths of MEA.

New delay‐dependent finite‐time stabilization of Takagi–Sugeno fuzzy approaches for delayed nonlinear systems

AbstractIn this paper, the finite‐time stability and stabilization of nonlinear systems with delays is studied, via a Takagi–Sugeno approach. By using a novel Lyapunov–Krasovskii functional and introducing some fuzzy free‐weighting matrices, sufficient conditions are derived, for bounded and differentiable time‐varying delays in terms of an upper bound of the delay derivatives. Then, we achieve closed‐loop stabilization in finite time through an efficient parallel distributed compensation design. The sufficient conditions are formulated as linear matrix inequalities to achieve the desired performance. Finally, the proposed methodology is applied to various case studies, highlighting its significance.

Pharmacokinetics and Bioequivalence of Two Powders of Azithromycin for Suspension: A Nonblinded, Single-Dose, Randomized, Three-Way Crossover Study in Fed and Fasting States Among Healthy Chinese Volunteers.

Azithromycin, a macrolide antibiotic, is commonly used to treat mild-to-moderate bacterial infections. This research aimed to evaluate the pharmacokinetics (PK) properties and bioequivalence (BE) of two azithromycin (EQ 100 mg base/packet) powders for suspension in Chinese healthy participants in fed and fasting conditions. A total of 90 Chinese healthy participants were enrolled in this nonblinded, single-dose, randomized, semireplicate, three-period, three-sequence, crossover study. Of them, 42 and 40 were categorized to the fed and fasting conditions, respectively. The washout period between doses was 21 days. Blood specimens were harvested prior to administering the drug and 194 h following administration. The plasma levels of azithromycin were analyzed using a validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach. PK parameters were measured using noncompartmental analysis. This research compared BE between the reference and test products using the average bioequivalence (ABE) or reference-scaled average bioequivalence (RSABE) method, considering the within-subject variability (SWR) of the reference preparation. Adverse events (AEs) were monitored to examine safety and tolerability. The RSABE method (SWR ≥ 0.294) was used to determine the BE of maximal plasma concentration (Cmax) in both fed and fasting conditions. In the ABE approach, (SWR < 0.294) was adopted to assess the BE of the area under the plasma concentration-time curve from time zero to the last measurable time point (AUC0-t) and determine the area under the plasma concentration time curve from time zero to time infinity (AUC0-inf). In the fasting condition, the point estimate of the test/reference ratio for Cmax was 1.08, with a 95% upper confidence bound of - 0.05 < 0.00. The geometric mean ratio (GMRs) for AUC0-t and AUC0-inf was 115.21% [90% confidence interval (CI) 107.25-123.27%] and 113.07% (90% CI 105.14-121.61%), respectively. In the fed condition, the point estimate of the test/reference ratio for Cmax was 0.94, with a 95% upper confidence bound of - 0.10 < 0.00. The GMR for AUC0-t and AUC0-inf was 99.51% (90% CI of 91.03-108.78%) and 99.43% (90% CI 91.73-107.78%), respectively. These data all satisfied the BE criteria for drugs with high variability. All AEs were transient and mild, and no severe AEs were observed. Our study indicated that the test and reference products of azithromycin (EQ 100 mg base/packet) powder for suspension were bioequivalent and safe in healthy Chinese participants, irrespective of the feeding condition. CLINICAL TRIAL REGISTRATION (CHINADRUGTRIALS.ORG.CN): CTR20232646, registered on 25 August 2023.

Coinfection of Toxoplasma gondii and Other Microorganisms: A Systematic Review and Meta-Analysis.

Toxoplasmosis is a disease caused by the intracellular protozoan Toxoplasma gondii, which has infected a third of the global population. Immunocompromised individuals and children with congenital disorders are most likely to be impacted by toxoplasmosis, and accurate diagnosis is essential. Toxoplasmosis is associated with HIV, schizophrenia, and diabetes. However, few studies have analyzed the association with other microorganisms. The purpose of this study was to determine the prevalence of coinfection of Toxoplasma gondii with other pathogens. From November 1997 to June 2024, PubMed, Science Direct, LAT index, Web of Science, Google Scholar, and Research Gate were searched. The keywords used were "Toxoplasma and microorganism coinfection", "Toxoplasma coinfection and parasites", "Toxoplasma coinfection and Protozoans or Bacteria or Helminths or Nematodes or Trematodes or Mycobacterium", "Toxoplasma gondii in coinfection with virus", and "Human Toxoplasmosis and coinfection". Next, OpenMeta Analyst Software version 12.11 was used for meta-analysis, creating forest plots, and determining heterogeneity I2. A total of 17,535 patients in 48 articles, of whom 5848 were seropositive to T. gondii, were included in this review. Population studies showed that the prevalence of virus infection was most frequent (32%), followed by parasites (18.4%), bacteria (29.7%), and fungi (5.8%). The pooled prevalence of coinfection was found to be 29.1%, with a lower bound of 0.232, an upper bound of 0.350, a standard error of 0.030, and p < 0.001. Heterogeneity (I2) was 99.12%, p < 0.001, with a global variance tau2 = 0.042. Toxoplasma gondii is an opportunist that mainly affects immunocompromised populations. The main coinfections were found to be viral infections, with HIV ranking first, followed by cytomegalovirus, hepatitis B and C, rubella, herpes simplex 1 and 2, SARS-CoV-2, and coxsackie virus.

Upper Bound for the Ground State Energy of a Dilute Bose Gas of Hard Spheres

We consider a gas of bosons interacting through a hard-sphere potential with radius a\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathfrak {a}$$\\end{document} in the thermodynamic limit. We derive an upper bound for the ground state energy per particle at low density. Our bound captures the leading term 4πρa\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$4\\pi \\rho \\mathfrak {a}$$\\end{document} and shows that corrections are smaller than Cρa(ρa3)1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$C \\rho \\mathfrak {a} (\\rho {{\\mathfrak {a}}}^3)^{1/2}$$\\end{document}, for a sufficiently large constant C>0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$C > 0$$\\end{document}. In combination with a known lower bound, our result implies that the first sub-leading term to the ground state energy of a dilute gas of hard spheres is, in fact, of the order ρa(ρa3)1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\rho \\mathfrak {a}(\\rho {{\\mathfrak {a}}}^3)^{1/2}$$\\end{document}, in agreement with the Lee–Huang–Yang prediction.

Adaptive Fault-Tolerant Control of Mobile Robots with Fractional-Order Exponential Super-Twisting Sliding Mode

Industrial mobile robots easily experience actuator loss of some effectiveness and additive bias faults due to the working scenarios, resulting in unexpected performance degradation. This article proposes a novel adaptive fault-tolerant control (FTC) strategy for nonholonomic mobile robot systems subject to simultaneous actuator lock-in-place (LIP) and partial loss-of-effectiveness (LOE) faults. First, a nominal fractional-order sliding mode controller based on the designed exponential super-twisting reaching law is investigated to reduce the reaching phase time and eliminate the chattering. To address the time-varying LIP faults and uncertainties, a novel barrier function (BF)-based gain is explored to assist the super-twisting law. An estimator is designed to estimate the lower bound of the time-varying partial LOE fault coefficients, thus without requiring the boundary information of faults that is commonly requested in traditional FTC schemes. Combined with the nominal controller clubbed with BF and estimator-based LOE fault compensation term, the fault-tolerant controller is finally constructed. The proposed FTC scheme achieves fast convergence and the sliding variables can be confined in a predetermined neighborhood of the sliding manifold under actuator faults. The results show that the proposed controller has superior tracking performance under faulty conditions compared with other state-of-the-art adaptive FTC approaches.

How Sharp Are Error Bounds? –Lower Bounds on Quadrature Worst-Case Errors for Analytic Functions–

How Sharp Are Error Bounds? –Lower Bounds on Quadrature Worst-Case Errors for Analytic Functions–

Unsupervised Bushfire Burn Severity Mapping Using Aerial and Satellite Imagery

Abstract. It is critical to assess bushfire impact rapidly and accurately because bushfires play a significant role in forest degradation and present a threat to ecosystems and human lives. Over the past decades, several supervised algorithms of burn severity mapping have been proposed, facing the significant drawback of time-consuming labeling. Moreover, there is no robust framework for burn severity mapping through fusing multi-sensor, multi-resolution, and multi-temporal remote sensing imagery from satellite and aerial platforms. Therefore, this paper presents an unsupervised two-step pipeline: processing 2D data followed by 3D data for burn severity mapping, both of which are acquired from either aircraft or satellites. For the 2D data processing, our proposed unsupervised burned area detection (UsBA detection) model enhances burned area mapping accuracy by integrating Ultra-High Resolution (UHR) aerial imagery with bi-temporal medium-resolution PlanetScope imagery, using a Segment Anything Model (SAM)-assisted UNetFormer (pre-trained on the target-style public dataset – LoveDA Rural) for refinement. The model demonstrates superior burned area segmentation, evidenced by improved evaluation metrics calculated from labeled test sites. For the 3D analysis, the burned areas extracted from 2D processing are further assessed using pre- and post-event airborne laser data. We implement a voxel-based workflow, including necessary steps such as ground filtering through Superpoints in RANSAC Planes (SiRP) method and biomass change analysis. The results indicate that the 3D branch provides a reliable lower bound of the actual damage map, because the vegetation growth between two measurements remains, in essence, undetected. The proposed framework offers a more accurate and robust solution for burn severity mapping utilizing combined 2D and 3D data, evaluated on a multi-source dataset from a real bushfire event that occurred in Bushland Park, South Australia.

Deep Learning Evidence for Global Optimality of Gerver’s Sofa

The moving sofa problem, introduced by Leo Moser in 1966, seeks to determine the maximal area of a 2D shape that can navigate an L-shaped corridor of unit width. Joseph Gerver’s 1992 solution, providing a lower bound of approximately 2.2195, is the best known, though its global optimality remains unproven. This paper leverages neural networks’ approximation power and recent advances in invexity optimization to explore global optimality. We propose two approaches supporting Gerver’s conjecture that his sofa is the unique global maximum. The first approach uses continuous function learning, discarding assumptions about the monotonicity, symmetry, and differentiability of sofa movements. The sofa area is computed as a differentiable function using our “waterfall” algorithm, with the loss function incorporating both differential terms and initial conditions based on physics-informed machine learning. Extensive training with diverse network initialization consistently converges to Gerver’s solution. The second approach applies discrete optimization to the Kallus–Romik upper bound, improving it from 2.37 to 2.3337 for five rotation angles. As the number of angles increases, our model asymptotically converges to Gerver’s area from above, indicating that no larger sofa exists.

3D limit analysis of reinforced concrete with sliding along smeared cracks

Limit analysis (LA) is successfully used for investigating the bearing capacity of reinforced concrete (RC) structures. Some cautions must be taken when using this method for RC since the concrete component exhibits a softening behavior with decreasing strength and limited ductility. A commonly adopted provision consists of considering isotropic reduced values of concrete strength to be input in the analysis (empirical effectiveness factors). In this paper, an alternative and completely new approach is proposed and investigated in which concrete strength is weakened in a more targeted manner. To that purpose, the commonly used 3D truncated Mohr-Coulomb (TMC) criterion is adopted to classically describe the compressive, tensile, and shear failure of concrete. However, TMC is here in an original way enriched by additional constraints that allow to account for weakness and anisotropy induced by preferential failure patterns, assumed a priori. The limit analysis approach is then formulated for two dual analyses in the convex optimization framework, making it possible to quantify the numerical error and obtain a lower and an upper bound of the limit load. Numerical examples illustrate the agreement of the formulation with academic results and laboratory tests.

Massive MIMO uplink and downlink joint representation based on couple dictionary learning

AbstractThe challenge of jointly representing both the uplink (UL) and downlink (DL) in massive multiple input multiple output (MIMO) systems have been tackled. Considering the angular reciprocity, a couple dictionary learning (CDL) support to enhance performance and address high complexity has been introduced. This approach minimizes the number of pilots and improves accuracy. Currently, accuracy analysis of UL/DL representation primarily relies on simulation. To bridge this gap, a proportion factor (PF) operator is proposed for CDL to assess accuracy. Specifically, a qualitative analysis formula is provided for accuracy and an optimal upper bound is established. Through theoretical proof, it is demonstrated that the accuracy of CDL for representation is mainly influenced by the cross‐correlation between the pilot matrix and the dictionary matrix. Inspired by PF operator, an optimal couple dictionary learning (OCDL) algorithm using singular value decomposition (SVD) is introduced to obtain dictionary updating, aiming at high‐precision representation. By establishing normalized mean squared error (NMSE), successful representation ratio, bit error rate (BER), and constellation performance, an OCDL algorithm that outperforms existing methods is showcased and channel representation accuracy is enhanced significantly.

Exploring charge sharing compensation using inter-pixel coincidence counters for photon counting detectors by deep-learning from local information

Photon counting detectors (PCDs) have well-acknowledged advantages in computed tomography (CT) imaging. However, charge sharing and other problems prevent PCDs from fully realizing the anticipated potential in diagnostic CT. PCDs with multi-energy inter-pixel coincidence counters (MEICC) have been proposed to provide particular information about charge sharing, thereby achieving lower Cramér-Rao Lower Bound (CRLB) than conventional PCDs when assessing its performance by estimating material thickness or virtual monochromatic attenuation integrals (VMAIs). This work explores charge sharing compensation using local spatial coincidence counter information for MEICC detectors through a deep-learning method.&#xD;Approach: By analyzing the impact of charge sharing on photon count detection, we designed our network with a focus on individual pixels. Employing MEICC data of patches centered on POIs as input, we utilized local information for effective charge sharing compensation. The output was VMAI at different energies to address real detector issues without knowledge of primary counts. To achieve data diversity, a fast and online data generation method was proposed to provide adequate training data. A new loss function was introduced to reduce bias for training with high-noise data. The proposed method was validated by Monte Carlo (MC) simulation data for MEICC detectors that were compared with conventional PCDs. &#xD;Main-Results: For conventional data as a reference, networks trained on low-noise data yielded results with a minimal bias (about 0.7%) compared with > 3% for the polynomial fitting method. The results of networks trained on high-noise data exhibited a slightly increased bias (about 1.3%) but a significantly reduced standard deviation (STD) and normalized root mean square error (NRMSE). The simulation study of the MEICC detector demonstrated superior compared to the conventional detector across all the metrics. Specifically, for both networks trained on high-noise and low-noise data, their biases were reduced to about 1% and 0.6%, respectively. Meanwhile, the results from a MEICC detector were of about 10% lower noise than a conventional detector. Moreover, an ablation study showed that the additional loss function on bias was beneficial for training on high-noise data.&#xD;Significance: We demonstrated that a network-based method could utilize local information in PCDs effectively by patch-based learning to reduce the impact of charge sharing. MEICC detectors provide very valuable local spatial information by additional coincidence counters. Compared with MEICC detectors, conventional PCDs only have limited local spatial information for charge sharing compensation, resulting in higher bias and standard deviation in VMAI estimation with the same patch strategy.&#xD.

Design, Implementation, and Analysis of an Assessment and Accreditation Model to Evaluate a Digital Competence Framework for Health Professionals: Mixed Methods Study.

Although digital health is essential for improving health care, its adoption remains slow due to the lack of literacy in this area. Therefore, it is crucial for health professionals to acquire digital skills and for a digital competence assessment and accreditation model to be implemented to make advances in this field. This study had two objectives: (1) to create a specific map of digital competences for health professionals and (2) to define and test a digital competence assessment and accreditation model for health professionals. We took an iterative mixed methods approach, which included a review of the gray literature and consultation with local experts. We used the arithmetic mean and SD in descriptive statistics, P values in hypothesis testing and subgroup comparisons, the greatest lower bound in test diagnosis, and the discrimination index in study instrument analysis. The assessment model designed in accordance with the competence content defined in the map of digital competences and based on scenarios had excellent internal consistency overall (greatest lower bound=0.91). Although most study participants (110/122, 90.2%) reported an intermediate self-perceived digital competence level, we found that the vast majority would not attain a level-2 Accreditation of Competence in Information and Communication Technologies. Knowing the digital competence level of health professionals based on a defined competence framework should enable such professionals to be trained and updated to meet real needs in their specific professional contexts and, consequently, take full advantage of the potential of digital technologies. These results have informed the Health Plan for Catalonia 2021-2025, thus laying the foundations for creating and offering specific training to assess and certify the digital competence of such professionals.

Safety of Kidney Transplantation from Donors with HIV

BackgroundKidney transplantation from donors with human immunodeficiency virus (HIV) to recipients with HIV is an emerging practice. It has been performed since 2016 under the U.S. congressional HIV Organ Policy Equity Act and is currently approved for research only. The Department of Health and Human Services is considering expanding the procedure to clinical practice, but data are limited to small case series that did not include donors without HIV as controls.MethodsIn an observational study conducted at 26 U.S. centers, we compared transplantation of kidneys from deceased donors with HIV and donors without HIV to recipients with HIV. The primary outcome was a safety event (a composite of death from any cause, graft loss, serious adverse event, HIV breakthrough infection, persistent failure of HIV treatment, or opportunistic infection), assessed for noninferiority (margin for the upper bound of the 95% confidence interval, 3.00). Secondary outcomes included overall survival, survival without graft loss, rejection, infection, cancer, and HIV superinfection.ResultsWe enrolled 408 transplantation candidates, of whom 198 received a kidney from a deceased donor; 99 received a kidney from a donor with HIV and 99 from a donor without HIV. The adjusted hazard ratio for the composite primary outcome was 1.00 (95% confidence interval [CI], 0.73 to 1.38), which showed noninferiority. The following secondary outcomes were similar whether the donor had HIV or not: overall survival at 1 year (94% vs. 95%) and 3 years (85% vs. 87%), survival without graft loss at 1 year (93% vs. 90%) and 3 years (84% vs. 81%), and rejection at 1 year (13% vs. 21%) and 3 years (21% vs. 24%). The incidence of serious adverse events, infections, surgical or vascular complications, and cancer was similar in the groups. The incidence of HIV breakthrough infection was higher among recipients of kidneys from donors with HIV (incidence rate ratio, 3.14; 95%, CI, 1.02 to 9.63), with one potential HIV superinfection among the 58 recipients in this group with sequence data and no persistent failures of HIV treatment.ConclusionsIn this observational study of kidney transplantation in persons with HIV, transplantation from donors with HIV appeared to be noninferior to that from donors without HIV. (Funded by the National Institute of Allergy and Infectious Diseases; ClinicalTrials.gov number, NCT03500315.)

Inverse-designed 3D sequential metamaterials achieving extreme stiffness

Mechanical metamaterials signify a groundbreaking leap in material science and engineering. The intricate and experience-dependent design process poses a challenge in uncovering architectural material sequences with exceptional mechanical properties. This study introduces inverse-designed 3D sequential metamaterials with outstanding mechanical attributes, achieved through a novel computational framework. The explored sequences based on Schoen's I-graph–wrapped package (IWP) and Schwarz Primitive (Schwarz P) surpass the Hashin-Shtrikman upper bound of Young's modulus at relative densities of 0.24 and 0.43, outperforming previous records. Optimized Body-Centered-Cubic (BCC) truss-based sets outperform traditional ones by 72.7%. This innovative approach can be extended for metamaterial customization, involving the optimization of multi-directional Young's modulus, total stiffness, and the addition of isotropy constraints. The paper explores the characteristics and implications of this innovation, emphasizing the impact of geometric and topological variations on mechanical performance. These metamaterial sequences offer unparalleled adaptability, and hold significant potential in structural engineering and adaptive mechanical systems, opening avenues for technological advancements.

The upper bound of information diffusion in code review

BackgroundCode review, the discussion around a code change among humans, forms a communication network that enables its participants to exchange and spread information. Although reported by qualitative studies, our understanding of the capability of code review as a communication network is still limited.ObjectiveIn this article, we report on a first step towards understanding and evaluating the capability of code review as a communication network by quantifying how fast and how far information can spread through code review: the upper bound of information diffusion in code review.MethodIn an in-silico experiment, we simulate an artificial information diffusion within large (Microsoft), mid-sized (Spotify), and small code review systems (Trivago) modelled as communication networks. We then measure the minimal topological and temporal distances between the participants to quantify how far and how fast information can spread in code review.ResultsAn average code review participants in the small and mid-sized code review systems can spread information to between 72 % and 85 % of all code review participants within four weeks independently of network size and tooling; for the large code review systems, we found an absolute boundary of about 11 000 reachable participants. On average (median), information can spread between two participants in code review in less than five hops and less than five days.ConclusionWe found evidence that the communication network emerging from code review scales well and spreads information fast and broadly, corroborating the findings of prior qualitative work. The study lays the foundation for understanding and improving code review as a communication network.

Small but Unwieldy: A Lower Bound on Adjacency Labels for Small Classes

Small but Unwieldy: A Lower Bound on Adjacency Labels for Small Classes

Tighter bound for generalized multiple discrete logarithm problem via MDS matrix method

Discrete logarithm problem (DLP) is one of the fundamental hard problems used in cryptography. For 1≤k≤n, solving the k-out-of-n DLP instances is an important problem emerging in certain scenarios in public-key cryptography. Ying and Kunihiro (ACNS 2017) pioneered in studying k-out-of-n instance solutions of DLP, which is a generalized version of multiple DLP. By reducing the multiple DLP to the generalized version, they established lower bounds on the computational complexity of k-out-of-n DLP for different parameter values of k.In this paper, we further reduce the reduction complexity presented in Ying and Kunihiro's work and increase the range of k and n for the tight lower bound of k-out-of-n DLP in the generic group model, which has applications in related cryptographic schemes. To achieve the goal, the key technique is to utilize a variant of fast multipoint evaluation. We divide the discussion into two cases. In the special case when n divides p−1, by leveraging Number Theory Transform (NTT) technique, we expand k and n to a larger range. In the general case, by using a variant of fast multipoint evaluation, we increase k and n to a moderately larger range.