Leakage Effects Research Articles

The effect of clean energy investment on CO2 emissions: Insights from a Spatial Durbin Model

We estimate the direct and indirect effects of clean energy investment on carbon emissions using a Spatial Durbin Model fitted to a panel of 72 countries from 2000 to 2018. We find that a 1 percent increase in domestic clean energy investment reduces domestic carbon emissions by approximately 0.05 percent on average, controlling for country characteristics. However, this benefit is offset by a carbon leakage effect, whereby a 1 percent increase in clean energy investment among neighboring countries leads to about a 0.28 percent increase in domestic carbon emissions. This is suggestive of the outsourcing of pollution from one country to another and indicates that ad hoc policies to promote clean energy investment may be ineffective in achieving global emissions abatement. We conclude that a coordinated international policy framework is required to prevent jurisdiction-shopping by polluters.

Eliminating polarization leakage effect for neutral hydrogen intensity mapping with deep learning

ABSTRACT The neutral hydrogen (H i) intensity mapping (IM) survey is regarded as a promising approach for cosmic large-scale structure studies. A major issue for the H i IM survey is to remove the bright foreground contamination. A key to successfully removing the bright foreground is to well control or eliminate the instrumental effects. In this work, we consider the instrumental effects of polarization leakage and use the U-Net approach, a deep learning-based foreground removal technique, to eliminate the polarization leakage effect. The thermal noise is assumed to be a subdominant factor compared with the polarization leakage for future H i IM surveys and ignored in this analysis. In this method, the principal component analysis (PCA) foreground subtraction is used as a pre-processing step for the U-Net foreground subtraction. Our results show that the additional U-Net processing could either remove the foreground residual after the conservative PCA subtraction or compensate for the signal loss caused by the aggressive PCA pre-processing. Finally, we test the robustness of the U-Net foreground subtraction technique and show that it is still reliable in the case of existing constraint error on H i fluctuation amplitude.

Lightweight Read Reference Voltage Calibration Strategy for Improving 3-D TLC NAND Flash Memory Reliability

Flash memory has gradually become the dominant storage device in the consumer market and data centers since the storage capacity increases and production costs decline. Unfortunately, as the bit density of flash memory increased, the severity of reliability issues has escalated. Read retry is necessary to recover high bit-error-rate flash data; however, read retry requires the flash to perform sequential read operations, which significantly increases read latency. To improve the flash memory read performance, a reliable adaptive optimization strategy for flash memory read reference voltage (RRV) is urgently needed. In this paper, we performed a full range of error characterization tests on three-dimensional (3-D) triple-level cell (TLC) flash memory, focusing on the effects of retention leakage, P/E wear, and interlayer variation on the threshold voltage. Finally, a lightweight flash memory RRV calibration strategy was constructed. The experiment results show that the predicted RRV using the proposed strategy is very close to the actual optimal RRV, reducing the raw bit error rate (RBER) of the same model of flash memory by up to 93.2%.

Collate of UK and Malaysia Buildings Defects Data: Triangulation Converged of Qualitative and Quantitative Real Project Data Census

Buildings serve several societal needs – occupancy, primarily as shelter from weather, security, living space, privacy, to store belongings, and to comfortably live and work. So, societally, building assures us the spaces needed for our continued work, education, entertainment, healthcare, and general well-being. To maintain buildings in good condition is a big challenge. Buildings do leaks. Here are some effects of building leakage: Metals in the building start to corrode. Timber decays because of dry rot as a result of a damp environment. All electric fittings deteriorate due to dampness. Thus, regardless in Malaysia or UK (United Kingdom), building maintenance practice need good practice indeed. In UK, there are different types of maintenance been practiced. Those are four different types of maintenance: corrective, preventative, risk-based and condition-based. In this paper, the triangulation of the qualitative and quantitative data of the UK and Malaysia building defects info been converged in various tables using IBM’s SPSS (version 27) statistical software. The triangulation convergence of the UK and Malaysia data reveals that UK has always been right at the top. The UK developers deliver very good quality buildings and always have a heritage of ambitious designers. However, the statistical findings still reveal that BLS (Building Leakage Syndrome) was adding to the bill. Problem solving may not have standardised solutions. As a conclusion, the issue around BLS need to look at very carefully even in the UK side.

Transferring four-dimensional atomic states at one step between separated cavities

This paper is concentrated on one-step transferring four-dimensional atomic states between atoms trapped in distant cavities connected by an optical fiber. Compared with the conventional schemes, one-step transferring four-dimensional atomic states means higher efficiency in preparing quantum network. In addition, we also calculate the effects of photon leakage out of cavity and fiber in this quantum process. The result shows the high fidelity can be reached based on the current experimental conditions.

Assessing forest conservation outcomes of a nature reserve in a subtropical forest ecosystem: effectiveness, spillover effects, and insights for spatial conservation prioritization

Protected areas (PAs) are pivotal in the conservation of global forest ecosystems, and understanding their effectiveness and spillover effects is crucial to evaluate their overall performance. While PAs are well-documented for their role in reducing deforestation, research examining their influence on mitigating non-stand replacement forest degradation or forest carbon emissions remains insufficient. Additionally, the nuanced heterogeneity in the effectiveness and spillover effects of PAs are not yet fully understood, impeding our ability to leverage outcome-based evidence for crafting spatial conservation strategies to expand PAs. In this study, integrating a rigorous counterfactual analysis and remote sensing observations, we probed the effectiveness and spillover effects of the Gutianshan National Nature Reserve (GNNR), located in Kaihua County of China, in curbing forest degradation, forest loss, and forest carbon emissions. We also explored the heterogeneity of these effects and identified spatial conservation priorities based on nonuniform impacts of effectiveness. Our findings showed that the GNNR designation remarkably curtailed forest degradation, forest loss, and forest carbon emissions by 78.56 %, 95.54 %, and 97.01 %, respectively, while also extending these mitigating effects to adjacent areas. However, we also detected leakage effects, causing a displacement of forest carbon emissions in areas 5–15 km around the reserve. The effectiveness and spillover effects exhibited heterogeneous patterns across geographical conditions. Informed by this heterogeneity, we pinpointed areas showing high conservation suitability as spatial conservation priorities, covering 35.64 % of Kaihua County, thereby boosting future forest and carbon management efforts. Our results advance the understanding of PA effectiveness and spillover effects within low-altitude subtropical forest ecosystems and offer insights into integrating outcome-based and area-based conservation approaches to achieve the 30 × 30 conservation target at a regional scale.

Combined Method for Informative Feature Selection for Speech Pathology Detection

The task of detecting vocal abnormalities is characterized by a small amount of available data for training, as a consequence of which classification systems that use low-dimensional data are the most relevant. We propose to use LASSO (least absolute shrinkage and selection operator) and BSS (backward stepwise selection) methods together to select the most significant features for the detection of vocal pathologies, in particular amyotrophic lateral sclerosis. Features based on fine-frequency cepstral coefficients, traditionally used in speech signal processing, and features based on discrete estimation of the autoregressive spectrum envelope are used. Spectral features based on the autoregressive process envelope spectrum are extracted using the generative method, which involves calculating a discrete Fourier transform of the report sequence generated using the autoregressive model of the input voice signal. The sequence is generated by the autoregressive model so as to account for the periodic nature of the Fourier transform. This improves the accuracy of the spectrum estimation and reduces the spectral leakage effect. Using LASSO in conjunction with BSS allowed us to improve the classification efficiency using a smaller number of features as compared to using the LASSO method alone.

PSIICOS projection optimality for EEG and MEG based functional coupling detection

Functional connectivity is crucial for cognitive processes in the healthy brain and serves as a marker for a range of neuropathological conditions. Non-invasive exploration of functional coupling using temporally resolved techniques such as MEG allows for a unique opportunity of exploring this fundamental brain mechanism.The indirect nature of MEG measurements complicates the estimation of functional coupling due to the volume conduction and spatial leakage effects. In the previous work (Ossadtchi et al., 2018), we introduced PSIICOS, a method that for the first time allowed us to suppress the volume conduction effect and yet retain information about functional networks whose nodes are coupled with close to zero or zero mutual phase lag.In this paper, we demonstrate analytically that the PSIICOS projection is optimal in achieving a controllable trade-off between suppressing mutual spatial leakage and retaining information about zero- or close to zero-phase coupled networks. We also derive an alternative solution using the regularization-based inverse of the mutual spatial leakage matrix and show its equivalence to the original PSIICOS.We then discuss how PSIICOS solution to the functional connectivity estimation problem can be incorporated into the conventional source estimation framework. Instead of sources, the unknowns are the elementary dyadic networks and their activation time series are formalized by the corresponding source-space cross-spectral coefficients. This view on connectivity estimation as a regression problem opens up new opportunities for formulating a set of principled estimators based on the rich intuition accumulated in the neuroimaging community.

LFM signal parameter estimation in the fractional Fourier domains: Analytical models and a high-performance algorithm

The index of the peak magnitude of the fractional Fourier transform (FrFT) of linear frequency modulated (LFM) signals has been widely used as a powerful chirp-rate estimator. In this paper, we propose analytical approximations for the peak FrFT magnitude (PFM) of mono and multicomponent LFM signals, both for noiseless and noisy cases. In addition, we present a novel coarse-to-fine FrFT-based algorithm designed specifically for chirp-rate estimation of multi-component LFM signals. Our approach entails an initial coarse estimation of the chirp-rates for each component by utilizing our proposed mathematical models. By leveraging these models, we achieve improved performance and a reduced signal-to-noise breakdown threshold. Furthermore, we incorporate a unique and efficient estimate-and-subtract strategy to refine the estimated parameters using our proposed models. Rather than removing the components from the LFM signal, we utilize the derived model to identify and remove peaks in the PFM. This strategy enhances the algorithm’s capability to handle challenging scenarios. Extensive simulation results demonstrate that our proposed algorithm performs very close to the Cramér–Rao lower bound. It effectively eliminates the leakage effect between signal components, avoids error propagation, and maintains an acceptable computational cost compared to other state-of-the-art methods.

Reduction of pollution loads based on sewage treatment projects around a lake: A case study on Erhai Lake.

Erhai Lake is a highland freshwater lake in Dali, China. Rapid tourism development has generated large amounts of pollutants. Since 2015, six wastewater treatment plants (WWTPs) have been built to treat wastewater collected through sewage interception projects. In this study, reductions in the pollution load of wastewater from different sources were evaluated by considering the effects of groundwater leakage, microbial degradation, and rainfall-runoff. The results showed that the systems reduced the chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) loads by 85, 83, and 85%, respectively. Discharge wastewater has the characteristics of a low concentration of domestic sewage discharge, large tourist sewage discharge, and high concentration of livestock wastewater. Due to the high groundwater level, there is groundwater infiltration in the influent water of WWTPs, which dilutes the pollutant concentration of the influent and, therefore, results in a lower treatment efficiency. Further treatment of tailwater also reduced the pollution loads discharged into the lake as well as the COD and TN by 10.25 and 22.90%, respectively. The results indicate that groundwater infiltration in the sewer network system is the primary target to be addressed in future developments.

Passive anti-leakage of blue light for phosphor-converted white LEDs with crystal nanocellulose materials

A phenomenon known as "blue-light leakage" caused by overheating pcW-LEDs has recently been identified, and it poses a risk to users. This study focuses on investigating and optimizing a solution to address this issue. To tackle the problem of overheating and blue light leakage, we explored the application of a specific thermochromic material called crystal nano cellulose (CNC). We introduced CNC inside the epoxy lens of white LEDs. Importantly, under standard conditions, CNC has a negligible impact on the optical properties of the output white light. However, when overheating conditions arise, leading to blue light leakage, the temperature increase triggers a darkening effect in CNC. This thermochromic behavior of CNC allows it to strongly absorb the blue light, resulting in a significant suppression of the output luminous flux. As a result, the lamp dims, which not only prevents the user's eyes from being exposed to harmful bluish light but also serves as an indicator of aging in the pcW-LED. By implementing CNC as a responsive material in the design of white LEDs, this study offers a practical and effective solution to mitigate the negative effects of blue-light leakage caused by overheating. This improvement enhances the safety and comfort of users while also providing an early warning system for the aging of pcW-LEDs.

Investigation of fatigue damage of new-old concrete interface based on piezomagnetic effect

Prefabricated concrete structures that employ wet connections create a new-old concrete interface between the pre-cast and cast-in-place layers. To enhance interfacial bonding performance in practical engineering, steel shear keys are frequently employed. The performance of the new-old concrete interface is critical in determining the fatigue performance of prefabricated concrete structures. Therefore, detecting and monitoring interface fatigue damage is essential for the life prediction and damage assessment of the entire structure. This study measured and analysed the piezomagnetic signal of the new-old concrete interface with shear keys under both static and cyclic loads. The piezomagnetic induction intensity was studied based on multiple damage indicators, such as steel strain and interface deformation. The relationship between the piezomagnetic signal and interface fatigue damage was analysed. The magneto-mechanical effect, dislocation effect, and magnetic leakage effect govern the piezomagnetic field change in different fatigue stages. It is found that the piezomagnetic signal exhibits similarities with conventional fatigue damage indicators, undergoing a three-stage variation pattern. Moreover, it demonstrates greater sensitivity to stress loading history and can better reflect the evolution of microstructural defects within the material. Finally, a simulated model of the magnetisation of the shear key at the new-old concrete interface was established and validated.

Information Leakage in Deep Learning-Based Hyperspectral Image Classification: A Survey

In deep learning-based hyperspectral remote sensing image classification tasks, random sampling strategies are typically used to train model parameters for testing and evaluation. However, this approach leads to strong spatial autocorrelation between the training set samples and the surrounding test set samples, and some unlabeled test set data directly participate in the training of the network. This leaked information makes the model overly optimistic. Models trained under these conditions tend to overfit to a single dataset, which limits the range of practical applications. This paper analyzes the causes and effects of information leakage and summarizes the methods from existing models to mitigate the effects of information leakage. Specifically, this paper states the main issues in this area, where the issue of information leakage is addressed in detail. Second, some algorithms and related models used to mitigate information leakage are categorized, including reducing the number of training samples, using spatially disjoint sampling strategies, few-shot learning, and unsupervised learning. These models and methods are classified according to the sample-related phase and the feature extraction phase. Finally, several representative hyperspectral image classification models experiments are conducted on the common datasets and their effectiveness in mitigating information leakage is analyzed.

A Review of CO2 Marine Geological Sequestration

Carbon dioxide (CO2) sequestration plays a crucial role in reducing the levels of atmospheric CO2 and mitigating the harmful effects of global warming. Among the various CO2 sequestration technologies, CO2 marine geological sequestration emerges as a safer and more efficient alternative compared with traditional terrestrial geological sequestration. This is highly attributed to its expansive potential, safe distance from aquifers, and stable temperature and pressure conditions. This paper reviews and evaluates the main CO2 marine geological sequestration technologies, including CO2 sequestrations in shallow marine sediments, CO2, sub-seabed aquifers, and CO2-CH4 replacement. The goal of this paper is to shed light on the mechanism, potential, and challenges of each technology. Given the importance of safety in CO2 sequestration, this review also explores the potential adverse effects of CO2 leakage from reservoirs, particularly its impact on marine environments. Finally, we discuss potential development trends in CO2 marine geological technology.

Modeling of a Dual Air-Gap Liquid-Cooled Eddy Current Retarder Considering Transient Permeability

This paper proposes a model for the electromagnetic performance of the dual air-gap liquid-cooled eddy current retarder (DAL-ECR) considering the transient permeability. First, the structure and working principle of the DAL-ECR are introduced. Next, the analysis model of the static air-gap flux density considering the flux leakage and end effect is established based on the piecewise function method and the magnetic equivalent circuit (MEC). Then, based on the skin effect of the electromagnetic field in the retarder, an iterative method for solving the transient permeability of the stator is proposed. According to Faraday’s and Ampere’s laws, the analysis model of the static air-gap flux density, and the transient permeability, the analysis model of the transient air-gap flux density is established. The braking torque of the DAL-ECR is then calculated while taking the actual path of the eddy current and the skin effect on the permeability of the stator into consideration. Finally, the calculation accuracy of the model was verified by the finite element method (FEM) and the bench test.

Strategic selling agreement and information management under leakage in an e-commerce supply chain

Nowadays, numerous manufacturers sell products through both an online e-tailer and an offline retailer. The e-tailer can use its rich sales data to predict the demand information and thus has the information advantage. This study develops a game-theoretic model to study the e-tailer’s selling agreement selection and information sharing policy in this multi-channel supply chain. The reselling agreement is adopted by offline retailer, while the reselling or the agency selling agreement can be prepared by the online e-tailer. Our analysis shows that the e-tailer’s information sharing strategy are quite different under these two agreements. That is, the e-tailer has an incentive to share information with the manufacturer voluntarily in the agency selling agreement whereas sharing information hurts the e-tailer in the reselling agreement. Interestingly, under an agency selling agreement, information sharing can make the manufacturer, the offline retailer, and the e-tailer becomes better than the non-information sharing scenario (i.e., Pareto-improvement). However, the reselling e-tailer only shares information with the manufacturer by virtue of information sharing contracting and the all-win outcomes are achieved if the demand uncertainty is high and the competition between the e-tailer and retailer is moderate. Furthermore, the interaction between the large commission rate and the less demand uncertainty drive the e-tailer to adopt the agency selling agreement; otherwise, the reselling agreement is the best choice for the e-tailer. Finally, we demonstrate that, when the e-tailer shares information with the manufacturer, the competing offline retailer always becomes better off due to the information leakage effect.

The effect of leakage on pressure loss of rotary regenerative heat exchangers

The pressure loss of the rotary exchanger is an important parameter that affects the energy consumption. Based on the literature review, the available correlations for calculating the pressure loss of rotary regenerative heat exchangers are presented in the article. The article presents extensive experimental research of rotary regenerative exchangers with different wheel geometries. A total of nine exchangers with eight different heat wheel geometries were investigated. The experiment was divided into two tasks concerning the pressure loss of the wheel channel and the total pressure loss of the built-in exchanger. The results of both approaches show differences that are caused by the leakage of rotary exchangers, which is their natural property. Based on the results of the experiment, correlations were proposed for determining the coefficient of friction in a channel in the shape of a sinusoid and a correlation for calculating the total pressure loss of the built-in rotary exchanger. The presented correlations have been experimentally verified and can be applied with a sufficient accuracy of ±5%. The new correlations were compared with the published results. The article discusses the effect of leakage of exchangers equipped with a labyrinth seal. Based on the experimental investigation, it was found that the leakage of the examined exchangers varies in a wide range of 1 to 4% and depends on the quality of the exchanger construction.

Numerical simulation and validation of local wind environment of twin-box girder with wind barriers

Computational fluid dynamics (CFD) was used to reproduce wind fields around a twin-box girder. Wind tunnel tests and field measurements were conducted to verify the accuracy of the CFD results. Variations in wind speed at different heights and crosswind reduction effects with different barriers were also examined using CFD simulation; the barriers had significant reduction effects. The reduction effectiveness was closely related to the barrier height and position; porosity was also a crucial factor. The wind speed profiles of a twin-box girder and a single box girder were analysed to determine why the wind speeds above the downstream deck were lower than above the windward deck of the twin-box girder. The results show that the incoming flow leaked downward through the slotted parts of the bridge and formed regulation vortices. Wind speeds were lower above the downstream deck than above the upstream deck as a result of leakage effects. The gap width also influenced the wind environment around the bridge deck.

Risk factors, quality of life, and oncological effects of refractory anastomotic leakage for laparoscopic intersphincteric resection.

Refractory anastomotic leakage (RAL) after intersphincteric resection (ISR) usually leads to failure of protective stoma reversal in ultralow rectal cancers. The aim of this study is to assess the risk factors and oncological outcomes of both anastomotic leakage (AL) and RAL, and quality of life (QoL) of RAL after laparoscopic ISR (LsISR). A total of 371 ultralow rectal cancer patients with LsISR were enrolled from a tertiary colorectal surgery referral center. Risk factors for AL and RAL were identified by logistic regression. Three-year disease-free survival (DFS) of AL and RAL was analyzed by the Cox regression. QoL of RAL group (compared with non-RAL group) was assessed using the European Organization for Research and Treatment of Cancer QLQ-C30 and QLQ-CR29 questionnaires. The rates of AL and RAL after LsISR accounted for 8.4% (31/371) and 4.6% (17/371) in this cohort, respectively. Non-left colic artery preservation (odds ratio [OR]=3.491, P=0.009), neoadjuvant chemoradiotherapy (nCRT) (OR=6.038, P<0.001), and lower anastomosis height (OR=5.271, P=0.010) were independent risk factors for AL, while nCRT (OR=11.602, P<0.001) was the only independent risk factor for RAL. Male (hazard ratio [HR]=1.989, P=0.014), age>60years (HR=1.877, P=0.018), and lymph node metastasis (HR=2.125, P=0.005) were independent risk factors of poor 3-year DFS, but not RAL (P=0.646). RAL patients have significantly worse global health status, worse emotional and social function scores at the late postoperative stage, and worse urinary and sexual function at the early postoperative stage (all P<0.05). Neoadjuvant chemoradiotherapy was an independent risk factor for RAL after LsISR. RAL shows similar oncological outcomes, but with poor QoL.

The Effect of Early Posttrabeculectomy Bleb Leakage on Surgical Outcome: A Prospective Cohort Study.

To evaluate the effect of early posttrabeculectomy bleb leakage on trabeculectomy surgery outcomes and success rate. The present prospective cohort study was conducted on 203 eyes of 203 patients who underwent trabeculectomy at Torfeh and Imam Hossein Medical Centers, Tehran, Iran, between 2016 and 2021. Patients were divided into two groups: those with early bleb leakage (within the 1st month of surgery) and those without bleb leakage. The success rate of surgery was compared 12, 18, and 24 months after surgery in the two groups. The average intraocular pressure (IOP) and the need for medications in patients 1, 3, 6, 9, 12, 18, and 24 months after the trabeculectomy were also compared. Bleb leakage was detected in 33 eyes during the 1st month after a trabeculectomy (16.3%). The mean decrease in IOP in the group with leakage was significantly lower than in patients without leakage at 1, 6, 9, 12, 18, and 24 months after surgery (P < 0.05). The need for antiglaucoma medication was significantly higher among patients with bleb leakage at 3 months (P = 0.04) and 9 months (P = 0.047) after surgery (P < 0.05). The success rate at 12, 18, and 24 months after surgery was significantly lower in the group with leakage than the group without. The results of our study suggest that early posttrabeculectomy bleb leakage negatively impacts surgery success. Furthermore, IOP reduction was lower in patients with early leakage.