Updated Code Research Articles

ConfExp: Root-Cause Analysis of Service Misconfigurations in Enterprise Systems

Misconfiguration is a known and increasingly serious problem in enterprise systems due to frequent code updates and retuning of the configuration parameters. Diagnosing complex, residual misconfiguration problems that lead to inaccessible services or failed transactions often starts with either a user complaint or observation by administrators, followed by a largely manual process of deciding what tests to run and how to proceed with further testing based on the test results. The goal of this paper is to automate this process and thereby make root-cause analysis of accessibility related misconfigurations much speedier and much more effective. We explore a domain-knowledge-driven methodology, called ConfExp using a network emulator that runs real enterprise networking protocols. Thus, by using commonly used tests, we show that the root-cause can be determined in all cases where discriminative tests exist. The methodology also highlights areas where more discriminative tests are needed to pinpoint the precise configuration variables at fault.

Selecting the Optimal DFT Functionals for Reproducing the UV‐Vis Properties of Transition‐Metal Photocatalysts

AbstractWe have applied our practice‐oriented TDDFT benchmark strategy to assess the performance of pure, hybrid, range‐separated hybrid and double‐hybrid functionals for reproducing the electronic spectra of a set of 137 transition‐metal complexes. Our results enable simple pre‐screening of new transition‐metal based photocatalysts. The reference data is based on recently published measurements, from which we have established a new database. The database is named TMPHOTCAT‐137 to reflect the number of complexes (with Cu, Ru, Ir, Fe, Au, Mo and W centres) included and the fact that all of them are either proven or potential photocatalysts. We have found that the M06 functional is the best performer both in terms of practical accuracy and consistency for all metals except Fe. While B3LYP is similarly accurate for Ru and Ir complexes, for the rest of the metals significant wavelength scaling is necessary. Compared to our previous benchmark for organic photocatalysts, double‐hybrid functionals exhibit considerably poorer results while the range separated hybrids CAM−B3LYP and ωB97X−D offer the most consistent performance for both datasets. Among the metals, iron proved to be most difficult for TDDFT: even M06 predicts singlet‐singlet absorption spectra and quintet ground states erroneously, especially for weak ligand fields (i. e., only Fe−N bonds). The functionals that do not exhibit this behaviour are the pure (GGA, meta‐GGA) functionals, but the role of HF exchange in the spectral prediction is equivocal; while functionals with high amounts of HF exchange perform insufficiently, smaller amount of exact exchange yields overall better performance (M06, B3LYP). We have also shown that inclusion of spin‐orbit coupling for the heavier metals does not improve the results. The updated spectrum optimizer code, the TMPHOTCAT‐137 database and the Jupyter Notebook used for analysis are available at github.com/PeterF1234/spectrum_optimizer.

Realistic binary neutron star initial data with Elliptica

Abstract This work introduces the Elliptica pseudo-spectral code for generating initial data of binary neutron star systems. Building upon the recent Elliptica code update, we can now construct initial data using not only piecewise polytropic equations of state, but also tabulated equations of state for these binary systems. Furthermore, the code allows us to endow neutron stars within the binary system with spins. These spins can have a magnitude close to the mass shedding limit and can point in any direction.

Numerical modeling of thermal dust polarization from aligned grains in the envelope of evolved stars with updated POLARIS

Abstract Magnetic fields are thought to influence the formation and evolution of circumstellar envelopes around evolved stars. Thermal dust polarization from aligned grains is a promising tool for probing magnetic fields and dust properties in these environments; however, a quantitative study on the dependence of thermal dust polarization on the physical properties of dust and magnetic fields for these circumstellar environments is still lacking. In this paper, we first perform the numerical modeling of thermal dust polarization in the IK Tau envelope using the magnetically enhanced radiative torque (MRAT) alignment mechanism implemented in our updated POLARIS code, accounting for the effect of grain drift relative to the gas. Despite experiencing grain drift and high gas density $n_{\rm gas} > 10^6\, \rm cm^{-3}$, the minimum grain size required for efficient MRAT alignment of silicate grains is $\sim 0.007 - 0.05\, \rm \mu m$ due to strong stellar radiation fields. Ordinary paramagnetic grains can achieve perfect alignment by MRAT in the inner envelope of $r < 500\, \rm au$ due to stronger magnetic fields of B ∼ 10 mG - 1G, producing the polarization degree of ∼10 %. The polarization degree can be enhanced to ∼20-40 % for superparamagnetic grains with embedded iron inclusions. The magnetic field geometry affects the resulting polarization degree due to the projection effect. We investigate the effect of rotational disruption by RATs (RAT-D) and find that the RAT-D effect decreases the dust polarization degree due to the decrease in the maximum grain size. Our modeling results motivate further observational studies at far-infrared/sub-millimeter to constrain the properties of magnetic fields and dust in evolved star’s envelopes.

Interstitial Lung Disease Epidemiology in the Past Three Decades: A Narrative Review.

Current epidemiological data on interstitial lung disease (ILD) are still poor. The principal cause of the discordant data is associated with a heterogeneous group of respiratory diseases that includes a large number, about 200 families, with low frequency, distinct and sometimes unknown etiology, and different progression. In fact, some conditions spontaneously resolve, whereas others, such as IPF and most non-IPF ILDs, progress to respiratory failure and death despite treatment. Furthermore, epidemiological data are limited. The scope of the narrative review is to report ILD incidence and prevalence in registries from different countries in the last three decades. We identified 20 ILD registries (17 prospective and 3 retrospective) from major countries in Europe (n = 10), Asia (n = 7), North America (n = 2), and Oceania (n = 1). Significant discrepancies in ILD and ILD subtype prevalence and incidence among countries are reported in registries. These discrepancies could be determined by different ethnicities and socioeconomic conditions as well as by updates in disease diagnosis and classification. ILD epidemiological registries are progressively ameliorating through better adherence to updated guidelines and classification codes. An accurate and definite diagnosis and compilation of ILD epidemiological registries will be useful for a more precise monitoring of disease progression and treatment. Future research to identify the populations with the highest risk factors, including genetic and molecular studies, and implementation of disease progression scores are needed to improve ILD clinical assessment.

Automatically Recommend Code Updates: Are We There Yet?

In recent years, large pre-trained Language Models of Code (CodeLMs) have shown promising results on various software engineering tasks. One such task is automatic code update recommendation, which transforms outdated code snippets into their approved and revised counterparts. Although many CodeLM-based approaches have been proposed, claiming high accuracy, their effectiveness and reliability on real-world code update tasks remain questionable. In this article, we present the first extensive evaluation of state-of-the-art CodeLMs for automatically recommending code updates. We assess their performance on two diverse datasets of paired updated methods, considering factors such as temporal evolution, project specificity, method size, and update complexity. Our results reveal that while CodeLMs exhibit higher performance in settings that ignore temporal information, they struggle in more realistic time-wise scenarios and generalize poorly to new projects. Furthermore, CodeLM performance decreases significantly for larger methods and more complex updates. Furthermore, we observe that many CodeLM-generated “updates” are actually null, especially in time-wise settings, and meaningful edits remain challenging. Our findings highlight the significant gap between the perceived and actual effectiveness of CodeLMs for real-world code update recommendation and emphasize the need for more research on improving their practicality, robustness, and generalizability.

BOATSv2: new ecological and economic features improve simulations of high seas catch and effort

Abstract. Climate change and industrial fishing are having profound effects on marine ecosystems. Numerical models of fish communities and their interaction with fishing can help assess the biogeochemical and socioeconomic dynamics of this coupled human–natural system and how it is changing. However, existing models have significant biases and do not include many processes known to be relevant. Here we describe an updated version of the BiOeconomic mArine Trophic Size-spectrum (BOATS) model for global fish and fishery studies. The model incorporates new ecological and economic features designed to ameliorate prior biases. Recent improvements include reduction of fish growth rates in iron-limited high-nutrient low-chlorophyll regions and the ability to simulate fishery management. Features added to BOATS here for the first time include (1) a separation of pelagic and demersal fish communities to provide an expanded representation of ecological diversity and (2) spatial variation of fishing costs and catchability for more realistic fishing effort dynamics. We also introduce a new set of observational diagnostics designed to evaluate the model beyond the boundary of large marine ecosystems (66 commonly adopted coastal ocean ecoregions). Following a multi-step parameter selection procedure, the updated BOATSv2 model shows comparable performance to the original model in coastal ecosystems, accurately simulating catch, biomass, and fishing effort, and markedly improves the representation of fisheries in the high seas, correcting for excessive high seas and deep-sea catches in the previous version. Improvements mainly stem from separating pelagic and demersal energy pathways, complemented by spatially variable catchability of pelagic fish and depth- and distance-dependent fishing costs. The updated model code is available for simulating both historical and future scenarios.

The influence of syn‐depositional compaction on clastic sediment distribution in river‐dominated deltas: A modelling study

AbstractSyn‐sedimentary compaction or consolidation is an important process in deltaic environments because it affects both the local morphodynamics and hydrodynamics as well as the delta‐scale accommodation space. However, the impact of syn‐depositional compaction on the sediment distribution and the interdependency between different delta areas related to the sediment budget are not fully understood. This paper simulates syn‐depositional compaction using improved 1D grain‐size compaction formulations, integrated into hydrodynamic and morphodynamic modelling software Delft3D. The updated code is used to model sedimentation in mud‐rich deltas under various compaction rate scenarios, which represents the maximum compaction rate potential of sediment that experiences the highest overburden stress in the delta. The simulated deltas are analysed by first classifying their plan‐view area development into depositional elements: distributary channel, underfilled channel, delta plain, mouth bar, delta front and pro delta depositional elements. Then, sedimentation by mass, accommodation space and depositional segment metrics are calculated using the interpreted depositional elements. The results for zero compaction rate scenarios (0 mm year−1) show that limited space‐varying and temporal‐varying accommodation is available to deposit sediment in the delta plain depositional element. Therefore, the sedimentation mainly occurs in the mouth bar depositional element. For low‐mid compaction rate scenarios (0.01–1 mm year−1), the additional syn‐depositional accommodation space in the delta plain depositional element increases sedimentation in this area, limiting sedimentation in the mouth bar depositional element. For high compaction rate scenarios (>1 mm year−1), a further increase in the accommodation space in the delta plain depositional element leads to lateral sedimentation attributed to channel relocation, where the sedimentation mainly occurs in the mouth bar depositional element. This study shows that, although considered a gradual process, syn‐sedimentary compaction does impact long‐term delta evolution by influencing the distribution of sedimentation in the delta.

Automated Security Vulnerability Backlog Management

In today’s fast-paced development environments, security vulnerabilities often emerge at the same rapid rate as code updates. Security teams and developers face challenges in addressing these vulnerabilities while maintaining operational efficiency. Managing a security backlog manually can be cumbersome, slow, and prone to human error. Automating the security vulnerability backlog allows organizations to track, prioritize, and mitigate security risks more efficiently and effectively, ensuring a secure software development lifecycle (SDLC) without sacrificing agility. This white paper outlines the need for an automated security backlog, the benefits it provides, and strategies for implementing it using modern DevSecOps tools. Keywords — Automated security backlog, vulnerability management, CI/CD, DevSecOps, risk- based prioritization, SAST, DAST, software composition analysis, continuous security, vulnerability tracking, security remediation, cybersecurity automation, security risk management

Improvements of the dynamics code TMSR3D for molten salt reactor leveraging triangular prism nodal method

Dynamic simulation with coupled model of neutronics/thermal-hydraulics (TH) is one of the crucial aspects in safety analysis for molten salt reactor (MSR), which requires a deeper insight into the interactions among hydrodynamics, heat transfer and neutron kinetics because of its special characteristics induced by fuel drift, in comparison to the traditional reactors using solid fuels. To improve the geometric adaptability and calculation precision of the MSR specific dynamics code TMSR3D based on quadrilateral nodal method and TH module including the multi-channel flow and single-channel heat transfer models, the analytic basis function expansion nodal (ABFEN) method using triangular prism nodes is implemented to solve the static neutron diffusion equations, an implicit backward difference method along with exponential transformation is adopted to deal with the neutron kinetics problems, and the concentration equations of delayed neutron precursors (DNP) considering fuel flow are solved by the method of characteristics. The VVER-440 transient benchmark is first selected to validate capacity of the updated code for simulating core with hexagonal assemblies. Subsequently, the Molten Salt Reactor Experiment (MSRE) is simulated for further validation, in which the steady-state characteristics including delayed neutron loss induced by circulating fuel, profiles of reactor temperature and DNP, impact of fuel residence time in external loop on the effective yields of delayed neutrons, two fuel pump driven transients, and the natural convection are analyzed and discussed in detail. The results agree well with that from similar codes and the experimental values, which indicate that the improvements conducted for TMSR3D are effective and correct.

Evidence of Grain Alignment by Magnetically Enhanced Radiative Torques from Multiwavelength Dust Polarization Modeling of HL Tau

The Atacama Large Millimeter/Submillimeter Array has revolutionized the field of dust polarization in protoplanetary disks across multiple wavelengths. Previous observations and empirical modeling have suggested multiple mechanisms of dust polarization toward HL Tau, including grain alignment and dust scattering. However, a detailed modeling of dust polarization based on grain alignment physics is not yet available. Here, using an updated POLARIS code, we perform numerical modeling of dust polarization arising from both grain alignment by the magnetically enhanced radiative torque mechanism and self-scattering to reproduce the HL Tau polarization observed at three wavelengths of 0.87, 1.3, and 3.1 mm. Our modeling results show that the observed multiwavelength polarization could be reproduced only when large grains contain embedded iron inclusions and those with slow internal relaxation must have wrong internal alignment (i.e., the grain’s major axis parallel to its angular momentum). The abundance of iron embedded inside grains in the form of clusters is constrained to be ≳16%, and the number of iron atoms per cluster is N cl ∼ 9 × 102. Maximum grain sizes probed at wavelengths of λ = 0.87, 1.3, and 3.1 mm are constrained at ∼60, 80, and 90 μm, respectively.

Numerical Modeling of Four-Pile Caps Using the Concrete Damaged Plasticity Model

Four-pile caps made from concrete are essential elements for the force transfer from the superstructure to piles or pipes. Due to the difficulties in carrying out full-scale tests and all the instrumentation involved, the use of numerical models as a way to study the mechanical behavior of these elements presents itself as a good alternative. Such numerical studies usually provide useful information for the update and improvement of normative standards and codes. The concrete damaged plasticity (CDP) constitutive model, which combines damage and plasticity with smeared-crack propagation, stands out in the simulation of reinforced concrete. This model is composed of five parameters: dilatation angle (ψ), eccentricity (ϵ), ratio between biaxial and uniaxial compressive strength (σbo/σco), failure surface in the deviator plane normal to the hydrostatic axis (Kc), and viscosity (μ). For unidimensional elements, the values of the CDP parameters are well defined, but for volumetric elements, such as concrete pile caps, there is a gap in the literature regarding the definition of these values. This fact ends up limiting the use of the CDP on these structural elements due to the uncertainties involved. Therefore, the aim of this research was to calibrate two numerical models of concrete four-pile caps with different failure modes for the evaluation of the sensitivity of the CDP parameters, except for ϵ, which remained constant. As a result, the parameters σbo/σco and Kc did not significantly influence the calibration of the force × displacement curves of the simulated structures. Values of ψ and μ equal to 36° and 1 × 10−4, respectively, are recommended for “static” analysis, while for “quasi-static” analysis, ψ values ranging between 45° and 50° are suggested according to the failure mode. The results also showed to be sensitive to the constitutive relation of concrete tensile behavior in both modes of analysis. For geometric parameterization, the “static” analysis is recommended due to the lower coefficient of variation (3.29%) compared to the “quasi-static” analysis (19.18%). This conclusion is supported by the evaluation of the ultimate load of the numerical models from the geometrically parametric study compared to the results estimated by an analytical model.

Automated Security Testing in DevOps Environments Using AI and ML

The rapid adoption of DevOps practices has transformed the software development landscape by emphasizing continuous integration, continuous delivery (CI/CD), and agile methodologies. However, this rapid pace of development often introduces significant security challenges, as traditional security testing methods struggle to keep up with the accelerated release cycles. To address these challenges, the integration of Artificial Intelligence (AI) and Machine Learning (ML) into automated security testing has emerged as a promising solution. This paper explores the use of AI and ML to enhance automated security testing within DevOps environments, offering a comprehensive approach to identifying, predicting, and mitigating security vulnerabilities in real time. Automated security testing leverages AI and ML algorithms to analyze code, detect anomalies, and predict potential security threats. These technologies enable the continuous monitoring of codebases, allowing for the early identification of vulnerabilities before they are exploited. By incorporating AI-driven security testing into the CI/CD pipeline, organizations can ensure that security is not an afterthought but a continuous process integrated into every stage of the software development lifecycle. AI and ML models can be trained to recognize patterns associated with security risks, such as code injection, unauthorized access, and data leakage. These models continuously learn from new data, improving their accuracy over time and adapting to evolving threats. The dynamic nature of AI-driven security testing makes it particularly suited for DevOps environments, where frequent code changes and updates can introduce new vulnerabilities. Moreover, AI and ML can assist in automating complex tasks, such as threat modeling, risk assessment, and the prioritization of security issues, enabling security teams to focus on higher-order tasks that require human expertise.

Flexible and Reconfigurable OFDM Implementation in DSP Platform for Various Purposes and Applications.

In the modern technological era of sophisticated applications and high-quality communications, a platform of clever strategy and quickly updated systems is needed. It should be capable of withstanding the fastest emerging problems like signal attenuation and hostile actions intended to harm the whole network. The main contributions of this work are the production of an OFDM system (with low cost) that can sustain high-speed communications and be easily adjusted with new integrated code while exhibiting the feasibility of implementing a transmitter-receiver system in the same DSP and demonstrating the holistic approach with the qualitative integration of such an architecture in a warfare scenario. Specifically, in this research, the point of view is toward three facts. The first is to show a method of quick self-checking the operational status of a digital signal processor (DSP) platform and then the pedagogical issues of how to fast check and implement an updated code inside DSPs through simple schematics. The second point is to present the prototype system that can easily be programmed using a graphical user interface (GUI) and can change its properties (such as the transmitted modulated sinusoids-orthogonal frequency division multiplexing subcarriers). Alongside the presentation, the measurements are presented and discussed. These were acquired with the use of an oscilloscope and spectrum analyzer. The third point is to qualitatively show the application of such a system inside a modern warfare environment and to recommend various potential system responses according to the development of such a platform of reconfigurable implemented OFDM systems. The implementation was performed for two types of systems: (1) transmitter and (2) transmitter-receiver system. Notably, the system acts quickly with a delay of about 1 msec in the case of transmitting and receiving in the same DSP, suggesting excellent future results under real conditions.

A numerical model database for rapid seismic damage assessment of typical regular reinforced concrete frame structures in urban building clusters

A vast city usually encompasses hundreds of thousands or even millions of buildings, majority of which are regular buildings with typical structural configurations. In the seismic damage simulation of cities, efficient and reliable simplified models are required to represent these buildings. A numerical model database of typical regular reinforced concrete (RC) frame structures was developed, utilizing shear models to simulate these RC frame structures. In contrast to existing shear models that are automatically generated based solely on the fundamental rules regulated by the theories of structures and the design codes, the shear models in this study were calibrated using refined numerical models to guarantee precise depiction of RC frame structures. The effects of reinforcement corrosion and the year of construction on structural performance were also considered. First, 108 RC frame structures were designed with typical configurations, strictly adhering to the regulations of design codes. Second, the refined models of the RC frame structures were established with modified material parameters to account for reinforcement corrosion, resulting in 540 refined models. Afterward, the parameters of each shear model were calibrated through cyclic pushover analysis of the corresponding refined numerical model. Finally, the characteristic points of the shear models were further modified to consider the different redundant capacities of the structures constructed in three time phases due to the update of design codes, by which a simplified numerical model database containing 1620 shear models was developed. The models' accuracy in predicting fundamental periods and seismic damage states was verified by comparing them to the refined models and three real RC frame buildings. The effects of the reinforcement corrosion and year of construction on the seismic damage states of the RC frame structures were also discussed. The developed numerical model database can be utilized for the seismic damage assessment of RC frame structures in urban building clusters.

Probing 3D Magnetic Fields Using Thermal Dust Polarization and Grain Alignment Theory

Magnetic fields are ubiquitous in the Universe and are thought to play an important role in various astrophysical processes. Polarization of thermal emission from dust grains aligned with the magnetic field is widely used to measure the 2D magnetic field projected onto the plane of the sky, but its component along the line of sight is not yet constrained. Here, we introduce a new method to infer 3D magnetic fields using thermal dust polarization and grain alignment physics. We first develop a physical model of thermal dust polarization using the modern grain alignment theory based on the magnetically enhanced radiative torque alignment theory. We then test this model with synthetic observations of magnetohydrodynamic simulations of a filamentary cloud with our updated POLARIS code. Combining the tested physical polarization model with synthetic polarization, we show that the B-field inclination angles can be accurately constrained by the polarization degree from synthetic observations. Compared to the true 3D magnetic fields, our method based on grain alignment physics is more accurate than the previous methods that assume uniform grain alignment. This new technique paves the way for tracing 3D B-fields using thermal dust polarization and grain alignment theory and for constraining dust properties and grain alignment physics.

Reducing inter-unit pollutant transfer through multifamily unit compartmentalization

Compartmentalization, which refers to air sealing each unit within a building from the exterior and other interior spaces, has been proposed as a strategy to improve indoor air quality and energy efficiency in multifamily buildings. This study collected field data on air tightness and pollutant transfer in three new-construction multifamily buildings in California, which was used to develop a model in CONTAM that simulated the impact of leakage levels, ventilation strategies, and climate zones on inter-unit pollutant transfer in multifamily buildings. Air leakage testing found an average total unit leakage of 0.8 L/s50/m2, almost twice as tight as California’s current compartmentalization requirement (1.5 L/s50/m2). Two buildings designed with balanced ventilation systems were measured to have imbalanced continuous unit ventilation flows, which were further imbalanced by intermittent exhaust fan operation. Tracer gas testing in two buildings indicated that only about 1–3% of the total air entering a unit came from each neighbouring unit. Furthermore, all particles were apparently removed along the way, as there was no observable particle matter transfer at the tested air tightness levels (0.6–0.9 L/s50/m2). Modelling results indicated that leakier units led to greater dilution of pollutants generated within the unit but increased gaseous pollutant transfer from neighbouring units. The average concentration of benzene, a proxy gas for cigarette smoke, transferred into non-smoking units from neighbours who did smoke almost doubled, surpassing acceptable exposure levels, in the leaky simulation (2.3 L/s50/m2) compared to the tight simulation (0.8 L/s50/m2). Overall, this study suggests that stricter compartmentalization requirements should be adopted in multifamily building code updates, as tighter requirements appear to be manageable for builders and beneficial for indoor air quality when combined with mechanical ventilation.

Vertical Elastic Acceleration Response Spectra for Vrancea Intermediate-Depth Earthquakes

This study is focused on the evaluation of vertical elastic acceleration response spectra for Vrancea intermediate-depth earthquakes in Romania in the context of the ongoing update of the national seismic design code. The ground motion database employed in this research consists of about 500 ground motions recorded during moderate and large Vrancea intermediate-depth earthquakes with moment magnitudes MW ≥ 5.2. The analysis of the dataset showed that a single ground motion recording had a peak ground acceleration larger than 0.20 g. The results of the analyses showed that no significant differences between the control periods of the vertical elastic response spectra as a function of the site class could be inferred. It was also observed that the mean value of the amplification factor computed for the entire ground motion database was about 2.5, irrespective of the earthquake magnitude, site class, or level of horizontal peak ground acceleration. However, larger-magnitude earthquakes generate larger spectral amplifications in the medium- and long-period ranges. The analysis of the ground motions recorded in Bucharest area revealed a magnitude dependency of the control period for the vertical ground motion TC,v. Finally, a single spectral shape for vertical acceleration response spectra characterized by a maximum dynamic amplification factor of 2.5 and control periods TBv and TCv of 0.05 s and 0.60 s is proposed for design purposes. This aspect allows for a major update from the current version of the national seismic design code which proposes control periods of the elastic vertical response spectrum dependent on the horizontal ones. The short-period (at T = 0.2 s) and long-period (at T = 1.0 s) ratios of the vertical acceleration response spectrum to the corresponding horizontal ones are 0.50 and 0.40.

Effects of grain magnetic properties and grain growth on synthetic dust polarization of MHD simulations of low-mass Class 0/I YSOs

ABSTRACT Thermal dust polarization is a powerful tool to probe magnetic fields ($\boldsymbol{B}$) and grain properties. However, a systematic study of the dependence of dust polarization on grain properties in protostellar environments is not yet available. In this paper, we post-process a non-ideal MHD simulation of a collapsing protostellar core with our updated POLARIS code to study in detail the effects of iron inclusions and grain growth on thermal dust polarization. We found that superparamagnetic (SPM) grains can produce high polarization degree of $p \sim 10\!-\!40~{{\ \rm per\ cent}}$ beyond ∼500 au from the protostar because of their efficient alignment by magnetically enhanced radiative torque mechanism. The magnetic field turbulence in the envelope causes the decrease in p with increasing emission intensity I as p ∝ Iα with the slope α ∼ −0.3. But within 500 au, SPM grains tend to have inefficient internal alignment and be aligned with $\boldsymbol{B}$ by RATs only, producing lower $p \sim 1~{{\ \rm per\ cent}}$ and a steeper slope of α ∼ −0.6. For paramagnetic (PM) grains, the alignment loss of grains above $1\, {\mu \rm {m}}$ in the inner ∼200 au produces $p \lt \lt 1~{{\ \rm per\ cent}}$ and the polarization hole with α ∼ −0.9. Grain growth can increase p in the envelope for SPM grains, but cause stronger depolarization for SPM grains in the inner ∼500 au and for PM grains in the entire protostellar core. Finally, we found the increase of polarization angle dispersion function S with iron inclusions and grain growth, implying the dependence of B-field strength measured using the David–Chandrasekhar–Fermi technique on grain alignment and grain properties.

Data Storage and Reliability Analysis on the Internet of Things Based on Pyramid Code

As the IoT (Internet of Things) develops, computers and devices generate a lot of data that needs to be processed and stored. Pyramid code, as an update of the Reed-Solomon code, is suitable for correcting data failure on various sides as an erasure code. Not only does Pyramid code reduce the cost of computation, but it can also meet the reliability and security requirements of IoT. The convenience of the Pyramid code is evaluated by comparing the (15, 12) RS code to the (16, 12) Pyramid code in this paper. Then, section 4 investigates how Pyramid code can match the needs of reliability, security, cost-effectiveness, etc. After that, the following section aims to give the applications of Pyramid code in IoT. There are many applications and this section concludes the several outstanding scenarios, such as healthcare, smart city, etc.