Compressibility Factor Research Articles

Virtual cylindrical PET for efficient DOI image reconstruction with sub-millimetre resolution

Objective. Image reconstruction in high resolution, narrow bore PET scanners with depth of interaction (DOI) capability presents a substantial computational challenge due to the very high sampling in detector and image space. The aim of this study is to evaluate the use of a virtual cylinder in reducing the number of lines of response (LOR) for DOI-based reconstruction in high resolution PET systems while maintaining uniform sub-millimetre spatial resolution. Approach. Virtual geometry was investigated using the awake animal mousePET as a high resolution test case. Using GEANT4 Application for Tomographic Emission (GATE), we simulated the physical scanner and three virtual cylinder implementations with detector size 0.74 mm, 0.47 mm and 0.36 mm (vPET1, vPET2 and vPET3, respectively). The virtual cylinder condenses physical LORs stemming from various crystal pairs and DOI combinations, and which intersect a single virtual detector pair, into a single virtual LOR. Quantitative comparisons of the point spread function (PSF) at various positions within the field of view (FOV) were compared for reconstructions based on the vPET implementations and the physical scanner. We also assessed the impact of the anisotropic PSFs by reconstructing images of a micro Derenzo phantom. Main results. All virtual cylinder implementations achieved LOR data compression of at least 50% for DOI PET reconstruction. PSF anisotropy in radial and tangential profiles was chiefly influenced by DOI resolution and only marginally by virtual detector size. Spatial degradation introduced by virtual cylinders was most prominent in the axial profile. All virtual cylinders achieved sub-millimetre volumetric resolution across the FOV when 6-bin DOI reconstructions (3.3 mm DOI resolution) were performed. Using vPET2 with 6 DOI bins yielded nearly identical reconstructions to the non-virtual case in the transaxial plane, with an LOR compression factor of 86%. Resolution modelling significantly reduced the effects of the asymmetric PSF arising from the non-cylindrical geometry of mousePET. Significance. Narrow bore and high resolution PET scanners require detectors with DOI capability, leading to computationally demanding reconstructions due to the large number of LORs. In this study, we show that DOI PET reconstruction with 50%–86% LOR compression is possible using virtual cylinders while maintaining sub-millimetre spatial resolution throughout the FOV. The methodology and analysis can be extended to other scanners with DOI capability intended for high resolution PET imaging.

Delayed postoperative neurological deficits from scoliosis correction: a case series and systematic review on clinical characteristics, treatment, prognosis, and recovery.

This study was designed to investigate the clinical features, treatment modalities, and risk factors influencing neurological recovery in patients who underwent scoliosis correction with delayed postoperative neurological deficit (DPND). Three patients with DPND were identified from 2 central databases for descriptive analysis. Furthermore, all DPND cases were retrieved from the PubMed and Embase databases. Neurological function recovery was categorized into complete and incomplete recovery groups based on the American Spinal Injury Association (ASIA) impairment scale. Two patients were classified as type 3, and one was classified as type 2 based on the MRI spinal cord classification. Intraoperative neurophysiological monitoring (IONM) was consistently negative throughout the corrective procedure, and intraoperative wake-up tests were normal. The average time to DPND development was 11.8h (range, 4-18h), and all three patients achieved complete recovery of neurological function after undergoing revision surgery. A total of 14 articles involving 31 patients were included in the literature review. The mean time to onset of DPND was found to be 25.2h, and 85.3% (29/34) of patients experienced DPND within the first 48h postoperatively, with the most common initial symptoms being decreased muscle strength and sensation (26 patients, 83.9%). Regarding neurological function recovery, 14 patients were able to reach ASIA grade E, while 14 patients were not able to reach ASIA grade E. Univariate analysis revealed that preoperative diagnosis (p = 0.004), operative duration (p = 0.017), intraoperative osteotomy method (p = 0.033), level of neurological deficit (p = 0.037) and deficit source (p = 0.0358) were significantly associated with neurological outcomes. Furthermore, multivariate regression analysis indicated a strong correlation between preoperative diagnosis (p = 0.003, OR, 68.633; 95% CI 4.299-1095.657) and neurological prognosis. Our findings indicate that spinal cord ischemic injury was a significant factor for patients experiencing DPND and distraction after corrective surgery may be a predisposing factor for spinal cord ischemia. Additionally, it is important to consider the possibility of DPND when limb numbness and decreased muscle strength occur within 48h after corrective scoliosis surgery. Moreover, emergency surgical intervention is highly recommended for DPND caused by mechanical compression factors with a promising prognosis for neurological function, emphasizing the importance of taking into account preoperative orthopedic diagnoses when evaluating the potential for neurological recovery.

Revised Enskog theory and molecular dynamics simulations of the viscosities and thermal conductivity of the hard-sphere fluid and crystal.

Hard-sphere (HS) shear, longitudinal, cross, and bulk viscosities and the thermal conductivity are obtained by molecular dynamics (MD) simulations, covering the entire density range from the dilute fluid to the solid crystal near close-packing. The transport coefficient data for the HS crystal are largely new and display, unlike for the fluid, a surprisingly simple behavior in that they can be represented well by a simple function of the density compressibility factor. In contrast to the other four transport coefficients (which diverge), the bulk viscosity in the solid is quite small and decreases rapidly with increasing density, tending to zero in the close-packed limit. The so-called cross viscosity exhibits a different behavior to the other viscosities, in being negative over the entire solid range, and changes sign from negative to positive on increasing the density in the fluid phase. The extent to which the viscosity tensor and thermal conductivity of the HS crystal can be represented by revised Enskog theory (RET) is investigated. The RET expressions are sums of an instantaneous (I), a kinetic (K), and a so-called α part. The I part of the transport coefficients evaluated directly by MD are statistically indistinguishable from those of the corresponding kinetic theory (Enskog and RET) expressions. For the K part the integral over the spatial two-particle distribution function at contact was determined and the α part was estimated using the direct correlation function and density functional theory approximations. All three parts were determined in this work which allowed the accuracy of RET for solid systems to be assessed rigorously. It is found that in the case of the thermal conductivity the predictions of RET are in excellent agreement with the MD results. Also, for the shear viscosity the agreement over the entire solid phase is quite good but is considerably worse for the three remaining viscosities in the solid phase.

Circulatory Failure in the Central Retinal Artery during Medial Orbital Wall Blow-out Fracture Repair

Purpose: We report a case of visual impairment due to circulatory failure in the central retinal artery during blow-out fracture repair.Case summary: A 16-year-old male with no underlying disease was diagnosed with a trapdoor type medial orbital wall blow-out fracture after a motorcycle accident and underwent blow-out fracture repair. During the surgery, his left eye was nearly completely dilated. Postoperatively, the visual acuity in the left eye was hand motion and there was ptosis of the left upper eyelid. Concerned with the possibility of orbital implant compression, computed tomography was performed immediately and a second operation was performed. However, there was no direct compression originating from the intraocular implant or any signs of active bleeding. The following day, optical coherence tomography and fluorescein angiography revealed a cherry-red spot on the central fovea with edema of the inner retinal layer and delayed arterial circulation. Under a diagnosis of incomplete central retinal artery occlusion, the patient was treated with intraocular pressure-lowering eye drops and intravenous mannitol. Despite prompt intervention, the visual acuity of the left eye did not improve beyond 0.04 at the 2-year follow-up.Conclusions: When there is visual impairment and pupillary dilation after blow-out fracture repair, we should consider not only compressive factors but also the possibility of central retinal artery occlusion or circulatory failure. In such cases, retinal examinations should be done to assess the retinal blood flow and enable early detection of any complications allowing prompt appropriate intervention.

Experimental (ρ,P,T) data of H2 + CH4 mixtures at temperatures from 278 to 398 K and pressures up to 56 MPa

The blending of hydrogen and natural gas (H2-NG) has emerged as a crucial and cost-effective means for processing hydrogen fluids through natural gas networks thereby aiding transition to net-zero energy. Nonetheless, the effective adaptation of H2-NG mixtures, especially up to 20% hydrogen concentrations, to existing natural gas distribution and storage facilities relies heavily on a comprehensive understanding of their thermophysical properties. We measured densities of three binary mixtures of hydrogen and methane (xH2 = 0.0532, 0.0858, and 0.2031) at temperatures between 278 and 398 K, and pressures up to 56 MPa using a vibrating tube densimeter (VTD). The VTD was calibrated using H2 and H2O. The measured densities were in reasonable agreements with the predictions of two thermodynamic equations of states (EoSs), Multi-Fluid Helmholtz Energy Approximation (MFHEA) and Peng-Robinson (PR). The average absolute relative deviation (AARD) for the measured density against the predictions of the PR EoS are 1.07%, 1.09%, and 0.89% for xH2 = 0.0532, 0.0858, and 0.2031 mol fractions respectively. While the AARD for the measured density against the predictions of MFHEA EoS are 0.16%, 0.16%, and 0.32% for xH2 = 0.0532, 0.0858, and 0.2031 mol fractions respective. The MFHEA EoS, which has the structure of GERG-2008, has better agreements with our density data than the PR EoS. The relative high deviations with PR EoS results from the PR's simple structure making it deficient in calculating thermal properties of natural gas in saturated-liquid and homogeneous states. In addition, the uncertainty of the measured density was determined, and the experimental data were compared with available literature data. Finally, the compressibility factor (Z), speed of sound (w), specific heat capacity at constant volume (CV), and specific heat capacity at constant pressure (Cp) were obtained from the experimental results and were compared with the predictions of MFHEA EoS. This work provides accurate density and other thermophysical data useful for engineering/process designs and modelling of H2 and natural gas systems thereby enhancing energy transition strategy.

Enhanced Video Super-Resolution Network towards Compressed Data

Video super-resolution (VSR) algorithms aim at recovering a temporally consistent high-resolution (HR) video from its corresponding low-resolution (LR) video sequence. Due to the limited bandwidth during video transmission, most available videos on the internet are compressed. Nevertheless, few existing algorithms consider the compression factor in practical applications. In this paper, we propose an enhanced VSR model towards compressed videos, termed as ECVSR, to simultaneously achieve compression artifacts reduction and SR reconstruction end-to-end. ECVSR contains a motion-excited temporal adaption network (METAN) and a multi-frame SR network (SRNet). The METAN takes decoded LR video frames as input and models inter-frame correlations via bidirectional deformable alignment and motion-excited temporal adaption, where temporal differences are calculated as motion prior to excite the motion-sensitive regions of temporal features. In SRNet, cascaded recurrent multi-scale blocks (RMSB) are employed to learn deep spatio-temporal representations from adapted multi-frame features. Then, we build a reconstruction module for spatio-temporal information integration and HR frame reconstruction, which is followed by a detail refinement module for texture and visual quality enhancement. Extensive experimental results on compressed videos demonstrate the superiority of our method for compressed VSR. Code will be available at https://github.com/lifengcs/ECVSR .

Thermodynamic crossovers in supercritical fluids

Can liquid-like and gas-like states be distinguished beyond the critical point, where the liquid-gas phase transition no longer exists and conventionally only a single supercritical fluid phase is defined? Recent experiments and simulations report strong evidence of dynamical crossovers above the critical temperature and pressure. Despite using different criteria, many existing theoretical explanations consider a single crossover line separating liquid-like and gas-like states in the supercritical fluid phase. We argue that such a single-line scenario is inconsistent with the supercritical behavior of the Ising model, which has two crossover lines due to its symmetry, violating the universality principle of critical phenomena. To reconcile the inconsistency, we define two thermodynamic crossover lines in supercritical fluids as boundaries of liquid-like, indistinguishable, and gas-like states. Near the critical point, the two crossover lines follow critical scalings with exponents of the Ising universality class, supported by calculations of theoretical models and analyses of experimental data from the standard database. The upper line agrees with crossovers independently estimated from the inelastic X-ray scattering data of supercritical argon, and from the small-angle neutron scattering data of supercritical carbon dioxide. The lower line is verified by the equation of states for the compressibility factor. This work provides a fundamental framework for understanding supercritical physics in general phase transitions.

Design, implementation, and analysis of a compressed sensing photoacoustic projection imaging system.

Compressed sensing (CS) uses special measurement designs combined with powerful mathematical algorithms to reduce the amount of data to be collected while maintaining image quality. This is relevant to almost any imaging modality, and in this paper we focus on CS in photoacoustic projection imaging (PAPI) with integrating line detectors (ILDs). Our previous research involved rather general CS measurements, where each ILD can contribute to any measurement. In the real world, however, the design of CS measurements is subject to practical constraints. In this research, we aim at a CS-PAPI system where each measurement involves only a subset of ILDs, and which can be implemented in a cost-effective manner. We extend the existing PAPI with a self-developed CS unit. The system provides structured CS matrices for which the existing recovery theory cannot be applied directly. A random search strategy is applied to select the CS measurement matrix within this class for which we obtain exact sparse recovery. We implement a CS PAPI system for a compression factor of 4:3, where specific measurements are made on separate groups of 16 ILDs. We algorithmically design optimal CS measurements that have proven sparse CS capabilities. Numerical experiments are used to support our results. CS with proven sparse recovery capabilities can be integrated into PAPI, and numerical results support this setup. Future work will focus on applying it to experimental data and utilizing data-driven approaches to enhance the compression factor and generalize the signal class.

Study on the Freeze-Thaw Resistance of Concrete Pavements in Seasonally Frozen Regions.

In seasonally frozen regions, concrete pavement is exposed to cycles of freeze-thaw and erosion from de-icing salt, which can lead to unfavorable service conditions and vulnerability to damage. This paper examines the compressive strength, flexural-tensile strength, abrasion resistance, permeability, and spacing factor of concrete, taking into account the impact of various curing conditions, de-icing salt solutions, and mass fractions on the concrete's freeze-thaw resistance. Two test methods, the single-face method and the fast-freezing method, were used to comparatively analyze the freeze-thaw resistance of concrete. The analysis was based on the surface scaling, water absorption rate, mass loss rate, relative dynamic elastic modulus, and relative durability index. The results indicate that the presence of salt solution significantly worsened the degree of concrete damage caused by freeze-thaw cycles. The use of freeze-thaw media, specifically sodium chloride (NaCl), calcium chloride (CaCl2), and potassium acetate (KAc) at mass fractions of 5%, 4.74%, and 5%, respectively, had the greatest impact on the surface scaling of concrete. However, their effect on the water absorption rate was inconsistent. When the freeze-thaw medium was water, the concrete's relative dynamic elastic modulus and relative durability index were 9.6% and 75.3% higher, respectively, for concrete cured in 20 °C-95% RH conditions compared to those cured in 0 °C-50% RH conditions. We propose a comprehensive relative durability index (DFw) by combining the results of two methods of freeze-thaw tests. The DFw of concrete cured in 0 °C-50% RH conditions was 83.8% lower than that of concrete cured in 20 °C-95% RH conditions when exposed to a freeze-thaw medium of 5% mass fraction NaCl solution. To evaluate the salt freeze-thaw resistance of concrete pavement, it is recommended to use surface scaling and DFw together.

Strength, carbon emissions, and sorptivity behavior of cement paste and mortar containing thermally activated clay

The detrimental impact of anthropogenic gases such as carbon dioxide, methane, and nitrous oxide has become a pressing concern across various industries. In this study, thermally activated clay (TAC) was investigated as a substitute for Portland cement in proportions ranging from 10 to 40 wt%. Compressive strength and efficiency factors were employed to ascertain the optimal mortar mixture. Both the control mortar and the optimal blend underwent capillary water sorptivity tests. Fourier Transformed Infrared spectroscopy (FT-IR) was utilized to gain insight into the hydration process and pozzolanic reaction within the mortar mixtures. Furthermore, the study assessed the impact of the optimized blended mortar on greenhouse gas emissions through estimated carbon dioxide equivalent values. Results revealed that incorporating 30% TAC attained the maximum strength of approximately 33, 36, and 48 MPa at 3, 7, and 28 days respectively compared with the other mortars. The mortar containing 30% TAC enhances both compressive strength and efficiency factors, demonstrating effective pozzolanic activity and minimal compromise on performance. Notably, the inclusion of 30% TAC also led to reduced water absorption rates, indicating improved durability-related performance. Additionally, the study uncovered the superior performance of the 30% TAC mix in terms of efficiency factors and carbon savings. FTIR analysis provided novel insights into the hydration and pozzolanic reactions induced by TAC, resulting in the formation of compounds contributing to enhanced compressive strength over time. This research advocates for the substitution of Portland cement with TAC as a low-carbon binder alternative to traditional Portland cement binders.

Using the Zeno line to assess and refine molecular models.

The Zeno line is the locus of points on the temperature-density plane where the compressibility factor of the fluid is equal to one. It has been observed to be straight for a broad variety of real fluids, although the underlying reasons for this are still unclear. In this work, a detailed study of the Zeno line and its relation to the vapor-liquid coexistence curve is performed for two simple model pair-potential fluids: attractive square-well fluids with varying well-widths λ and Mie n-6 fluids with different repulsive exponents n. Interestingly, the Zeno lines of these fluids are curved, regardless of the value of λ or n. We find that for square-well fluids, λ ≈ 1.8 presents a Zeno line, which is the most linear over the largest temperature range. For Mie n-6 fluids, we find that the straightest Zeno line occurs for n between 8 and 10. Additionally, the square-well and Mie fluids with the straightest Zeno line showed the closest quantitative agreement with the vapor-liquid coexistence curve for experimental fluids that follow the principle of corresponding states (e.g., argon, xenon, krypton, methane, nitrogen, and oxygen). These results suggest that the Zeno line can provide a useful additional feature, in complement to other properties, such as the phase envelope, to evaluate molecular models.

The Influence of CO2 Physical Properties on Casing and Its Prediction Method

In order to reveal the physical properties of CO2 under actual formation conditions, this paper establishes a mathematical model of the temperature field and pressure field in the wellbore under CO2 injection conditions, optimizes the state equation of CO2 physical-property parameters, calculates the change trend of CO2 density, viscosity, and compression factor along the wellbore, and obtains the influence law of CO2 corrosion on the casing and interface. The viscosity showed a downward trend along the well depth; the compression factor showed an upward trend. The surfaces of the three casings were smooth and flat without obvious defects, the cement structure was dense, and there was no obvious pore structure. After corrosion, with the increase of Cr content, the change of interfacial corrosion decreases. The morphology of the Q125 and 3Cr interface is loose after corrosion, while there is no obvious change in the 13Cr interface. With the prolongation of corrosion time, low wellbore internal pressure easily causes casing yield, and high wellbore internal pressure easily causes cement-sheath compression failure. The circumferential stress of the casing increases with the corrosion time extension, and the radial stress of the casing and cement sheath decreases first and then increases with the corrosion time. The compressive strength of the cement sheath does not exceed the compressive strength.

الخصائص الفيزيائية والكيميائية الكاذبة والديناميكية الحرارية للغازات الطبيعية

Physiochemical, pseudocritical, pseudoreduced and thermodynamic properties play an important role for determination natural gas quality and specifications. Nowadays natural gas regard as one of the importance natural source of energy supply due to its high heating value, clean source, no emissions and environmental friendly. In addition, it began to replace the oil as a fuel in various purposes and as essential feed for petrochemical industries. Consequently, the different properties of natural gas mixtures must be investigated to determine their specifications. This study was aiming to distinguish these properties using correlations and mathematical models for assessment. These properties include the physical such as molecular weight (M_w), density(ρ), specific gravity(γ), compressibility factor (z), gas viscosity (μ_g), gas formation volume factor (B_g), gas thermal compressibility (C_g) and water content as well as pseudocritical pressure (p_pc), pseudocritical temperature (T_pc), pseudoreduced pressure (p_pr), pseudoreduced temperature (T_pr). Also, the thermodynamic properties e. g. Gross heating value, thermal conductivity, and specific heat of natural gas mixtures were determined. The study has been conducted on the natural gases of Zelten, Al Ragoba, Al Hotaiba gasfields and Al Braiga terminal to predict and estimate the physical, pseudocritical and thermodynamic properties by using correlation and mathematical models methods. The obtained results revealed that there is a variance between these properties of the natural gas mixtures, which may be attributed to the chemical compositions of components and their behaviors. On the other hand, these characterizations can be used as guide to understand the gases behavior during the different operations and natural gases treatment processes. Keywords: Natural gas, physiochemical, pseudocritical, pseudoreduced thermodynamic properties, and correlations

Real Gas Effects in High-Pressure Ignition of n-Dodecane/Air Mixtures.

This work studies the real gas effects on the autoignition of hydrocarbon fuels under high pressures, using normal dodecane (n-dodecane) as the representative fuel and the Redlich-Kwong equation of state (EoS) as the real gas description. It is demonstrated that the real gas description yields a shorter ignition delay time (IDT) compared with the ideal gas description, especially in low-temperature regimes which could encompass the negative temperature coefficient (NTC) phenomena and has a stronger dependence on the molecular volume than the attractive potential. The study further shows that high pressure facilitates low-temperature reaction pathways, where the compressibility factors of key reactants contribute to real gas effects. Moreover, the results suggest that accounting for real gas behavior leads to an increase in the formation of polycyclic aromatic hydrocarbons (PAHs), which, in turn, promotes soot generation.

Estimating the natural gas compressibility factor using a statistical correlations and machine learning approaches

Gas compressibility factor plays an critical role in petroleum engineering applications such as gas metering, pipeline design, reserve estimation, gas flow rate, material balance calculations, and many other significant tasks. Therefore, it is crucial to accurately estimate the gas compressibility factor. There have been a lot of studies on calculating the gas compressibility factor from laboratory data, which can be summarized into two main approaches: statistical correlations and machine learning algorithms. In this study, on statistical correlations the authors implement explicit and implicit method while on machine learning algorithms, we use Artificial Neural Network (ANN) and Least-Squares Support Vector Machine (LS-SVM). The data was collected from open literature. Implementing the two approaches mentioned above and comparing statistical parameters such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R2 ) found that machine learning algorithms give much more accurate estimation results than statistical correlations, and besides, the ANN algorithm has the most accurate prediction results with the lowest MSE and RMSE (0.000002 and 0.0016) and the highest R2 (0.9999). The high-precision calculation results show that the ANN algorithm mentioned above can be applied to estimate other real gas compressibility factor data sets. On the other hand, this study can be extended to another subset of machine learning algorithms, such as deep learning and ensemble learning.

Altering optical zone diameter, reverse curve width, and compression factor: impacts on visual performance and axial elongation in orthokeratology

PurposeTo investigate the effects of modifications in back optical zone diameter (BOZD), reverse curve width (RCW), and compression factor (CF) on refractive error changes and axial elongation in myopic children undergoing orthokeratology (ortho-k) over a 12-month period. MethodIn this retrospective study, data from 126 myopic children undergoing ortho-k fitting were analyzed. Subjects were categorized into four distinct groups based on lens design parameters: Group A (BOZD 6.0 mm, RCW 0.6 mm, CF 0.75 D); Group B (BOZD 6.0 mm, RCW 0.6 mm, CF 1.25 D); Group C (BOZD 5.4 mm, RCW 0.9 mm, CF 1.25 D); and Group D (BOZD 5.0 mm, RCW 1.1 mm, CF 1.25 D). The study evaluated uncorrected visual acuity (UCVA), corneal topography, and axial length (AL) at intervals, using Linear Mixed Models (LMMs) for time-based changes, and ANOVA or Kruskal-Wallis tests for group differences in AL elongation. A multivariable regression analysis identified factors independently associated with AL elongation. ResultsWithin the first day and week, all four groups displayed significant improvements in UCVA and alterations in corneal curvature, which subsequently stabilized. Although UCVA variations between groups were subtle, Group D had less corneal curvature change than Groups A and B initially and exhibited significantly less AL elongation after one year. No significant difference in corneal curvature change or AL elongation was observed between Group C and the other groups. Multiple regression analysis indicated that older baseline age, greater baseline spherical equivalent refractive error, and smaller BOZD were associated with less AL elongation. ConclusionThe study reveals a positive correlation between BOZD and axial length growth over the 12-month period. A pure 0.5 D CF increment demonstrates a nonsignificant impact. This study provides new ideas into optimizing the parameters of ortho-k lenses.

Half-spectrum OFDM to quadruple the spectral efficiency of underwater wireless optical communication with digital power division multiplexing.

Improving the spectrum efficiency (SE) is an effective method to further enhance the data rate of bandwidth-limited underwater wireless optical communication (UWOC) systems. Non-orthogonal frequency-division multiplexing (NOFDM) with a compression factor of 0.5 can save half of the bandwidth without introducing any inter-carrier-interference (ICI) only if the total number of subcarriers is large enough, and we termed it as half-spectrum OFDM (HS-OFDM). To the best of our knowledge, this is the first reported work on a closed-form HS-OFDM signal in the discrete domain from the perspective of a correlation matrix. Due to the special mathematical property, no extra complex decoding algorithm is required at the HS-OFDM receiver, making it as simple as the conventional OFDM receiver. Compared with traditional OFDM, HS-OFDM can realize the same data rate, but with a larger signal-to-noise ratio (SNR) margin. To fully use the SNR resource of the communication system, we further propose a digital power division multiplexed HS-OFDM (DPDM-HS-OFDM) scheme to quadruple the SE of conventional OFDM for the bandwidth-starved UWOCs. The experimental results show that HS-OFDM can improve the receiver sensitivity by around 4dB as opposed to conventional 4QAM-OFDM with the same data rate and SE. With the help of the DPDM-HS-OFDM scheme, the data rate of multi-user UWOC can reach up to 4.5Gbps under the hard-decision forward error correction (HD-FEC) limit of a bit error rate (BER) of 3.8×10-3. Although there is some performance degradation in comparison with single-user HS-OFDM, the BER performance of multi-user DPDM-HS-OFDM is still superior to that of conventional single-user 4QAM-OFDM. Both single-user HS-OFDM and multi-user DPDM-HS-OFDM successfully achieve 2Gbps/75m data transmission, indicating that the DPDM-HS-OFDM scheme is of great importance in bandwidth-limited UWOC systems and has guiding significance to underwater wireless optical multiple access.

Novel lossy compression method of noisy time series data with anomalies: Application to partial discharge monitoring in overhead power lines

In overhead power transmission lines, particularly in regions like natural parks where establishing a safe zone is difficult, the adoption of cross-linked polyethylene insulated covered conductors (CCs) helps prevent outages due to vegetation contact. However, these CCs are susceptible to partial discharge (PD) activity, which can degrade insulation and lead to system failures. Detecting and analyzing PD are essential for maintaining power system reliability and safety. A key challenge in PD monitoring is transmitting the large volumes of PD signal data over unreliable 2G networks, as existing compression methods either compromise on data integrity or are ineffective. This paper introduces a novel lossy compression technique utilizing an autoencoder with skip connections and correction data to address this issue. Unlike previous algorithms that struggle with noisy time series data and fail to preserve crucial anomaly information, our method reconstructs the signal without anomalies, which are subsequently restored using correction data. Achieving a compression factor of about 25 (reducing data to 4.1% of its original size), this approach maintains essential PD signal features for analysis. The effectiveness of our method is validated by three classification algorithms, showing promise for future fault detection, diagnosis, and memory space reduction. This innovative compression solution marks a significant advancement in PD data processing, offering a balanced trade-off between compression efficiency and data fidelity, and paving the way for enhanced remote monitoring in power transmission systems.

Solubility of Methane in Ionic Liquids for Gas Removal Processes Using a Single Multilayer Perceptron Model

In this work, four hundred and forty experimental solubility data points of 14 systems composed of methane and ionic liquids are considered to train a multilayer perceptron model. The main objective is to propose a simple procedure for the prediction of methane solubility in ionic liquids. Eight machine learning algorithms are tested to determine the appropriate model, and architectures composed of one input layer, two hidden layers, and one output layer are analyzed. The input variables of an artificial neural network are the experimental temperature (T) and pressure (P), the critical properties of temperature (Tc) and pressure (Pc), and the acentric (ω) and compressibility (Zc) factors. The findings show that a (4,4,4,1) architecture with the combination of T-P-Tc-Pc variables results in a simple 45-parameter model with an absolute prediction deviation of less than 12%.

High spectral efficiency modulation scheme based on joint interaction of orthogonal compressed chirp division multiplexing and power superimposed code.

In this paper, we propose a high spectral efficiency modulation scheme based on joint interaction of orthogonal compressed chirp division multiplexing (OCCDM) and power superimposed code (PSC) under the intensity modulation and direct detection (IM/DD) system. OCCDM is a novel orthogonal chirp division multiplexing technology featuring spectral compression through the implementation of processing similar to a discrete Fourier transform, enhancing the spectral efficiency (SE) through bandwidth savings without loss of orthogonality of each chirp. Meanwhile, PSC technology enables multiple code words being transmitted superimposed on the same chirp. This technique involves allocating varying power levels to different users, thereby distinguishing them, increasing the transmission's net bit rate and substantially boosting the SE. The transmission has been performed experimentally using a 2 km 7-core fiber span. The impact of the above-mentioned technologies on the bit error rate (BER) performance is assessed in the power, frequency, and joint domain. The BER and enhancements in the SE can be balanced when the spectral bandwidth compression factor (α) and power distribution ratio are equal to 0.9 and 4, respectively. The observed outcome leads to the transmission's SE increase to more than double the baseline value, at 2.22 times. Based on the above analysis, we believe this structure is expected to become a potential for developing next-generation PON.