Error Correction Research Articles

Determinants of External Debt and Its Impact on Socio-Economic Life in Nigeria

The research focused on analyzing the factors influencing external debt and its effects on the socio-economic conditions of Nigeria from 1986 to 2021. Data from annual time series were collected from the World Bank Development Indicator (WDI, 2022) and Central Bank of Nigeria Statistical Bulletin (CBN). Variables studied included real gross domestic product, debt service payments, exchange rate, gross domestic savings, trade openness, and misery index used as a proxy for socio-economic status. Stationarity of the variables was tested using the Augmented Deckey Fuller Unit Root Test, showing mixed order of integration me (0) at levels and me (1) at first differences. The Breusch-Godfrey Serial Correlation LM test indicated no serial correlation in the model, while the Breusch-Pagan-Godfrey Heteroskedasticity test revealed no heteroskedasticity in the residual series. The Autoregressive Distributive Lag (ARDL) Bound test confirmed a long-term relationship between external debt determinants and their impact on Nigeria’s socio-economic conditions. The study found that real gross domestic product, exchange rate, and gross domestic savings had a negative impact on the misery index, implying that an increase in these variables would reduce the misery index in Nigeria in the long run. The Error Correction test suggested that 87% of equilibrium errors were corrected annually, pointing to a steady adjustment towards the long-term equilibrium. It was recommended that efforts should be made to stabilize the exchange rate to mitigate inflation and enhance the purchasing power of the naira, ultimately reducing Nigeria’s external debt burden and improving the misery index.

Raman scattering impairments caused by 50G-PON introduction and mitigation techniques

We explore the impact of stimulated Raman scattering (SRS) in the context of multiple PON generations sharing the same optical distribution network. The 50G-PON, being the last specified ITU-T PON, imposes the use of high launch power to meet strong optical path loss requirements. We show that the XGS-PON upstream could be the first victim of the introduction of 50G-PON since its wavelength spacing maximizes Raman scattering. We exploit a model to describe both in simulation and experiment the SRS-induced depletion on XGS-PON. Assuming that 50G-PON will be deployed on the current passive infrastructure, we also exploit field data to precisely predict the amount of terminations exceeding the requirements. The results show that up to 1.8 dB can be lost on XGS-PON upstream signals, 1.3 dB on the 50G-PON upstream, and 0.5 dB on the G-PON upstream, over a distance of 20 km of fiber. Up to 3% of terminations may be affected, according to our field data exploitation. Improving the receivers’ sensitivity through either better photodiodes, signal processing, or forward error correction could relax the high launch power constraints, and thus the SRS. Deploying an optical splitter at the central office could also limit the power actually launched into the fiber while meeting high split ratios. Finally, decreasing the 50G-PON downstream wavelength seems a possible option to mitigate the Raman scattering.

Stochastic thermodynamics for biological functions

AbstractLiving systems operate within physical constraints imposed by nonequilibrium thermodynamics. This review explores recent advancements in applying these principles to understand the fundamental limits of biological functions. We introduce the framework of stochastic thermodynamics and its recent developments, followed by its application to various biological systems. We emphasize the interconnectedness of kinetics and energetics within this framework, focusing on how network topology, kinetics, and energetics influence functions in thermodynamically consistent models. We discuss examples in the areas of molecular machine, error correction, biological sensing, and collective behaviors. This review aims to bridge physics and biology by fostering a quantitative understanding of biological functions.

Cultivating "non-technical skills" in surgeons

Surgical operations are one of the high-risk activities in modern society, and surgeons in this high-pressure environment require not only excellent technical skills but also well-rounded non-technical skills. Non-technical skills encompass key abilities such as situational awareness, decision-making, communication and teamwork, leadership, and stress management, as well as the capacity for error correction feedback loops, emotional intelligence, and adaptability to complex environments. These "soft skills" help surgeons to more effectively handle emergencies during surgery, optimize team collaboration, ensure patient safety, and increase the success rate of operations. Western countries have systematized non-technical skills into physicians' training programs, while in China, further attention and promotion are still needed. By establishing comprehensive non-technical skill assessment standards and systematic training programs, the overall quality of surgeons can be enhanced, thereby ensuring patient safety, improving clinical outcomes, and fulfilling the professional mission of surgeons.

Research advances on light-adjustable intraocular lens

Refractive error is a key determinant of visual acuity post-cataract surgery. Traditional methods for addressing refractive errors have been invasive, posing the risk of permanent surgical complications. Thus, the pursuit of non-invasive techniques for correcting refractive errors after cataract surgery is of significant clinical importance. Recently, a novel class of intraocular lenses (IOL), termed light-adjustable IOL, has emerged as a potential solution for refining refractive outcomes. These IOL possess the unique ability to alter their dioptric power in vitro through exposure to specific wavelengths of light, facilitating a non-invasive approach to refractive error correction. The landscape of light-adjustable IOL is diverse, encompassing ultraviolet light-adjustable IOL, novel nitinol-based thermomechanically adjustable IOL, IOL with refractive index changes induced by femtosecond lasers, and IOL utilizing two-photon effects for dioptric adjustment. This review article aims to summarize the advancements in light-adjustable lenses, providing insights and references for ongoing research and clinical practice in this field.

Extracting error thresholds through the framework of approximate quantum error correction condition

The robustness of quantum memory against physical noises is measured by two methods: the exact and approximate quantum error correction (QEC) conditions for error recoverability and the decoder-dependent error threshold which assesses if the logical error rate diminishes with system size. Here we unravel their relations and propose a unified framework to extract an intrinsic error threshold from the approximate QEC condition, which could upper bound other decoder-dependent error thresholds. Our proof establishes that relative entropy, effectively measuring deviations from exact QEC conditions, serves as the order parameter delineating the transition from asymptotic recoverability to unrecoverability. Consequently, we establish a unified framework for determining the error threshold across both exact and approximate QEC codes, addressing errors originating from noise channels as well as those from code space imperfections. This result sharpens our comprehension of error thresholds across diverse QEC codes and error models. Published by the American Physical Society 2024

Flag Gadgets Based on Classical Codes

Fault-tolerant syndrome extraction is a key ingredient in implementing fault-tolerant quantum computation. While conventional methods use a number of extra qubits that are linear in the weight of the syndrome, several improvements have been introduced using flag gadgets. In this work, we develop a framework to design flag gadgets using classical codes. Using this framework, we show how to perform fault-tolerant syndrome extraction for any stabilizer code with arbitrary distance using exponentially fewer qubits than conventional methods when qubit measurement and reset are relatively slow compared to a round of error correction. In particular, our method requires only (2t+1)t⌈log2(w)⌉ flag qubits to fault-tolerantly measure a weight-w stabilizer. We further take advantage of the saving provided by our construction to fault-tolerantly measure multiple stabilizers using a single gadget and show that it maintains the same exponential advantage when it is used to fault-tolerantly extract the syndromes of quantum low-density parity-check codes. Using the developed framework, we perform computer-assisted search to find several small examples where our constructions reduce the number of qubits required. These small examples may be relevant to near-term experiments on small-scale quantum computers. Published by the American Physical Society 2024

QC Speller: User Interface Design of a Hands-Free Touch-Free Speller with Brain Electroencephalogram Sensory Rhythm

Nowadays, brain-computer interfaces (BCIs) are being extensively explored by researchers to recover the abilities of motor-impaired individuals and improve their communication. Text entry is one of the most important regular tasks in communication, and BCI has high application potential to develop a speller. Although BCI has been a growing research topic for the last decade, more progress is yet to be made for BCI-based spellers. Two challenges are there in BCI speller development: designing an effective graphical user interface with an optimal arrangement of symbols enabling a minimum number of control commands and reducing users’ efforts in error correction following an efficient error-correction policy. With this scope in mind, this work proposes a novel BCI speller paradigm with an efficient symbol arrangement to improve the text entry rate. Additionally, it provides a user-friendly error correction approach through six text-cursor navigation keys to enhance the accuracy of text entry. The proposed speller includes 36 target symbols and is operated with two control commands obtained from electroencephalogram motor-imagery signals. The experimental results revealed that the proposed speller outperforms the existing motor imagery-based BCI spellers when tested on ten motor-impaired users. This speller achieved a mean performance of 5.20 characters per minute without any typing error and 6.04 characters per minute with a 2.9 percent mean error. The mean correction efficiency was 0.69; that is, users corrected 69 percent of incorrect inputs with a single correction key pressed.

Quantum error correction below the surface code threshold.

Quantum error correction [1, 2, 3, 4] provides a path to reach practical quantum computing by combining multiple physical qubits into a logical qubit, where the logical error rate is suppressed exponentially as more qubits are added. However, this exponential suppression only occurs if the physical error rate is below a critical threshold. Here, we present two below-threshold surface code memories on our newest generation of superconducting processors, Willow: a distance-7 code, and a distance-5 code integrated with a real-time decoder. The logical error rate of our larger quantum memory is suppressed by a factor of when increasing the code distance by two, culminating in a 101-qubit distance-7 code with 0.143% ± 0.003% error per cycle of error correction. This logical memory is also beyond break-even, exceeding its best physical qubit's lifetime by a factor of . Our system maintains below-threshold performance when decoding in real time, achieving an average decoder latency of 63 μs at distance-5 up to a million cycles, with a cycle time of 1.1 μs. We also run repetition codes up to distance-29 and find that logical performance is limited by rare correlated error events occurring approximately once every hour, or cycles. Our results present device performance that, if scaled, could realize the operational requirements of large scale fault-tolerant quantum algorithms.

Proofreading mechanism for colloidal self-assembly

Designing components that can robustly self-assemble into structures with biological complexity is a grand challenge for material science. Proofreading and error correction is required to improve assembly yield beyond equilibrium limits, using energy to avoid kinetic traps in the energy landscape. Here, we introduce an explicit two-staged proofreading scheme for patchy particle colloidal assemblies that substantially improves assembly yield and robustness. The first stage implements local rules whereby particles increase their binding strengths when they detect a local environment corresponding to a desired target. The second stage corrects remaining errors, adding a reverse pathway inspired by kinetic proofreading. The scheme shows significant yield improvements, eliminating kinetic traps, giving a much broader temperature range with high yield. Additionally, the scheme is robust against quenched disorder in the components. Our findings illuminate a pathway for advancing the programmable design of synthetic living materials, potentially fostering the synthesis of novel biological materials and functional behaviors. Published by the American Physical Society 2024

Macroeconomic determinants of housing demand in Saudi Arabia: an autoregressive distributed lag approach

Purpose This study aims to investigate the macroeconomic factors influencing housing demand in Saudi Arabia using quarterly data for the period 2010 Q1–2024 Q2. Design/methodology/approach The autoregressive distributed lag bounds test and vector error correction model are used to determine the dynamic relationship between the macroeconomic factors. Findings The results reveal that the F-statistic value of 4.2043 is higher than the upper bound of the critical values at 5% level of significance, indicating long-run association among the series. While there is a negative and significant influence of interest and inflation rates on housing demand, income per capita and population have a positive and significant influence on housing demand. Similar result is found for the short run analysis except income per capita which has positive but insignificant impact. Moreso, the population seems to be very crucial to housing demand in both short-run and long-run periods. Social implications The outcome of the study has important policy implications by enjoining the policymakers in Saudi Arabia to consider a decisive management of monetary and fiscal policies to ensure that inflation and interest rates for housing are kept at a low level to encourage housing demand. Also, adequate policies should be put in place to ensure housing/property affordability that matches the increasing population due to tourism, urbanisation and growing birth rate. Originality/value Studies on the macroeconomic determinants of housing demand are less explored as most studies dwell more on social and demographic factors despite the importance of macroeconomic factors towards house ownerships. There is a dearth of related studies in Saudi Arabia.

The Effects of Exchange Rates Volatility and Inflation on Tanzania’s Trade Balance: Evidence from J-Curve Effect

All economies today are experiencing the volatility of exchange rates and inflation in global markets. Consequently, this affects the trade performance among trading partners globally. This study examines the effects of exchange rate volatility and inflation on Tanzania’s trade balance. Time series data spanning 1990 to 2020 were used from the World Bank and Bank of Tanzania (BOT). Moreover, J-Curve and Marshall Lerner's theories provided the theoretical arguments. Systematically, a Vector Error Correction Model (VECM) was employed for short- and long-run analysis. The findings reveal that, in the long run, inflation, Foreign Direct Investment, and Gross Domestic Product have a positive impact on the trade balance, while the Exchange Rate exerts a negative influence. In the short run, the exchange rate negatively affects Foreign Direct Investment, while Gross Domestic Product has a positive influence. Further, the gross domestic product also positively influences inflation. Furthermore, the exchange rate and gross domestic product significantly affect the trade balance negatively and positively respectively. Analysis of impulse response functions confirms the presence of the J-Curve effect, showing an initial deterioration in the trade balance following a depreciation of the domestic currency, which reverses after three periods. These findings suggest the need for effective exchange rate management, promotion of export competitiveness, and a good environment for foreign direct investment to enhance trade performance in Tanzania

Causality Relationship Between Producer and Consumer Price Indexes of Selected Meat Commodities in South Africa from 1991 to 2023

The South African meat industry plays an important role in food provision, income generation, and economic stability. However, inflation-driven volatility in commodity markets has intensified the focus on the nexus between producer and consumer price indexes, as significant meat price changes affect both producers and consumers. Therefore, this study explored the association and the causality between consumer price index (CPI) meat and producer price index (PPI) beef, mutton, pork, and chicken from 1991 to 2023 using the Vector Error Correction Model (VECM) and Granger causality test. The findings of the study revealed a short- and a long-run relationship among the variables with an adjustment speed (ECT) of 67.67%. No causal relationship was found between PPI beef and CPI meat, while unidirectional relationships were identified between CPI meat and PPI chicken, pork, and mutton. These results suggest that consumer meat prices impact production prices for chicken, pork, and mutton, but not for beef, indicating that beef price changes are influenced by factors other than general meat price fluctuations. Thus, while price controls or subsidies may manage price changes in chicken, pork, and mutton, further research or targeted strategies are needed to address the unique factors influencing beef prices. Ultimately, understanding these dynamics will enhance price stability in the meat market, benefiting consumers, producers, and the overall stability of the South African economy.

Socio-Demographic Determinants of Mortality in Bangladesh: A Time Series Analysis

Understanding the factors influencing the death rate in Bangladesh is essential for effective policy-making and addressing demographic challenges. This study aims to examine both the short-term dynamics and long-term equilibrium relationships between socio-demographic factors and the death rate of Bangladesh over a given period. It focuses on four key factors: adolescence fertility rate (AFR), life expectancy rate at birth, birth rate, and infant mortality rate (IMR). Taking an annual time series dataset from 1975 to 2021 from the World Bank (WB), the study uses the Johansen co-integration test, vector error correction model (VECM), and Granger causality test to analyze the relationships between these factors and death rate. The findings reveal short-term and long-term equilibrium links between the socio-demographic parameters and death rate. A substantial negative correlation exists between death rate and AFR and life expectancy. Additionally, a positive correlation is observed between the death rate and birth rate, and IMR. These findings provide valuable insights for decision-makers to address the death rate in Bangladesh, bridging a research gap and guiding effective socio-demographic policies. International Journal of Statistical Sciences, Vol. 24(2), November, 2024, pp 35-54

Resisting High-Energy Impact Events through Gap Engineering in Superconducting Qubit Arrays

Quantum error correction (QEC) provides a practical path to fault-tolerant quantum computing through scaling to large qubit numbers, assuming that physical errors are sufficiently uncorrelated in time and space. In superconducting qubit arrays, high-energy impact events can produce correlated errors, violating this key assumption. Following such an event, phonons with energy above the superconducting gap propagate throughout the device substrate, which in turn generate a temporary surge in quasiparticle (QP) density throughout the array. When these QPs tunnel across the qubits’ Josephson junctions, they induce correlated errors. Engineering different superconducting gaps across the qubit’s Josephson junctions provides a method to resist this form of QP tunneling. By fabricating all-aluminum transmon qubits with both strong and weak gap engineering on the same substrate, we observe starkly different responses during high-energy impact events. Strongly gap engineered qubits do not show any degradation in T1 during impact events, while weakly gap engineered qubits show events of correlated degradation in T1. We also show that strongly gap engineered qubits are robust to QP poisoning from increasing optical illumination intensity, whereas weakly gap engineered qubits display rapid degradation in coherence. Based on these results, gap engineering mitigates the threat of high-energy impacts to QEC in superconducting qubit arrays. Published by the American Physical Society 2024

Quantum computer error structure probed by quantum error correction syndrome measurements

With quantum devices rapidly approaching qualities and scales needed for fault tolerance, the validity of simplified error models underpinning the study of quantum error correction needs to be experimentally evaluated. In this work, we have assessed the performance of IBM superconducting quantum computer devices implementing heavy-hexagon code syndrome measurements with circuit sizes up to 23 qubits, against the error assumptions underpinning code threshold calculations. Circuit operator change rate statistics in the presence of depolarizing and biased noise were modeled using analytic functions of error model parameters. Data from 16 repeated syndrome measurement cycles were found to be inconsistent with a uniform depolarizing noise model, with slightly improved fits found with biased and inhomogeneous noise models. Spatial-temporal correlations investigated via Z stabilizer measurements revealed significant temporal correlation in detection events. These results highlight the nontrivial structure that may be present in the noise of quantum error correction circuits, revealed by operator measurement statistics, and support the development of noise-tailored codes and decoders to adapt. Published by the American Physical Society 2024

Exploring the Nexus between Macroeconomic Variables and Stock Market Returns in Nepal: An ARDL Bounds Testing Approach

Background: Investors and policymakers must understand how macroeconomic variables (MEVs) affect stock market behavior to maximize portfolios and maintain economic stability. Hence, it is crucial to establish a nexus between MEVs and stock market returns (SMRs). Objectives: This study seeks to assess the effects of MEV on SMRs in the long and short run. Methods: This paper analyzed the cointegrating relationship between MEVs and SMRs using a time series data set from 1994 to 2023. This study used the ARDL bounds testing approach. Results: The results confirm a cointegrating association between MEVs and SMRs in the Nepalese stock market. The error correction (ECT -1) term is significantly negative, suggesting a persistent correlation between the variables. The study also shows that interest rates negatively affect SMRs over time. Real GDP (LRGDP), inflation (LINFR), and exchange rate (LEXR) have negative but statistically insignificant associations with SMRs. However, the money supply (LMS) positively correlates with SMRs. Conclusion: The study’s findings provide practical advice for policymakers. For instance, lower interest rates increase the appeal of stocks by reducing the opportunity costs of holding bank deposits and credit costs. Therefore, policymakers are advised to maintain lower interest rates to cultivate a more appealing investment environment. Furthermore, policymakers should prioritize regulating inflation and preserving a robust foreign exchange rate to boost investors’ SMRs.

High-Performance Garbage Collection Scheme with Low Data Transfer Overhead for NoC-Based SSDC

Solid-state drives (SSDs) have become the preferred storage solution for performance-critical applications due to their high speed, durability, and energy efficiency. However, the inherent characteristics of NAND flash memory, such as block-level erasure and data fragmentation, necessitate frequent garbage collection (GC) operations to reclaim storage space. These operations, while essential, introduce significant performance overhead, particularly in modern SSD controllers (SSDCs) that utilize network-on-chip (NoC) architectures. In such architectures, GC requires substantial data transfer over interconnects for error correction, leading to increased latency and reduced throughput. This paper presents a novel GC scheme designed to minimize latency in NoC-based SSDCs. Unlike conventional methods that unconditionally transfer data for error correction, the proposed approach selectively determines the data transfer path based on the presence of errors. By leveraging the low error probability of NAND flash memory, this scheme avoids unnecessary data traversal across the interconnect, significantly reducing GC overhead. A hardware implementation using task queues ensures efficient parallelism without disrupting other operations. The experimental results demonstrate that the proposed scheme improves SSD performance across various real-world workloads, achieving up to a 26.9% reduction in average latency and a 50.0% reduction in peak latency compared to traditional GC methods. These findings highlight the potential of optimizing data traversal paths in NoC architectures, providing a scalable solution for enhancing SSD performance for diverse applications.

Near-Field Direct Writing Based on Piezoelectric Micromotion for the Programmable Manufacturing of Serpentine Structures

Serpentine microstructures offer excellent physical properties, making them highly promising in applications in stretchable electronics and tissue engineering. However, existing fabrication methods, such as electrospinning and lithography, face significant challenges in producing microscale serpentine structures that are cost-effective, efficient, and controllable. These methods often struggle with achieving precise control over fiber morphology and scalability. In this study, we developed a near-field direct writing (NFDW) technique incorporating piezoelectric micromotion to enable the precise fabrication of serpentine micro-/nanofibers by incorporating micromotion control with macroscopic movement. Modifying the fiber structure allowed for adjustments to the mechanical properties, including tunable extensibility and distinct characteristics. Through the control of the frequency and amplitude of the piezoelectric signal, the printing errors were reduced to below 9.48% in the cycle length direction and 6.33% in the peak height direction. A predictive model for the geometrical extensibility of serpentine structures was derived from Legendre’s incomplete elliptic integral of the second kind and incorporated an error correction factor, which significantly reduced the calculation errors in predicting geometric elongation, by 95.85%. The relationship between microstructure bending and biomimetic non-linear mechanical behavior was explored through tensile testing. By controlling the input electrical signals, highly ordered serpentine microstructures were successfully fabricated, demonstrating potential for use in biomimetic mechanical scaffolds.

Trade Liberalization, Foreign Investment and Economic Growth: Experience from Non-Oil Producing Countries in Africa

This study focuses on trade liberalization, foreign investment and economic growth in non-oil-producing countries of Africa using the panel autoregressive distributed lag (ARDL) model. Annual time series data spanning from 2000 to 2023. The study reveals a strong long-term relationship between trade liberalization, foreign direct investment (FDI), and economic growth in non-oil-producing African countries. This finding is evidenced by the rejection of the “no long-run relationship” hypothesis, indicating a solid and enduring connection among these factors, which aligns with previous research. Most variables conform to theoretical expectations, supporting the hypothesis that trade liberalization and FDI contribute positively to economic growth. However, FDI and exchange rates exhibit unexpected deviations, likely reflecting structural challenges common in non-oil African economies, such as barriers that limit stable FDI inflows and hinder sustainable growth. The error correction term (ECT) further suggests that these economies adjust quickly from deviations, with respective short-run adjustment rates of 90%, 10%, and 50% in different model specifications. This high responsiveness indicates that, despite short-term disruptions, these economies tend to revert swiftly to their long-term growth trajectories. Based on the findings, we recommend that policies should be directed towards the pursuit of consistent and sustainable trade liberalization by reducing trade barriers, and reduction of obstacles to foreign investment to improve economic growth in non-oil-producing countries of Africa.