Search Results (274)

As interest in PV installation has spiked in recent years, the need for optimizing several factors of PV performance has become crucial. These are tilt angle and solar cell temperature (taking into account ambient temperature) and their effect on solar insolation for solar photovoltaic (PV) systems. The objective of this study is to achieve the optimal tilt angle and cell temperature accordingly by developing a MATLAB program to reach the target of maximizing the received solar insolation. To achieve this, additional solar angles such as the azimuth, hour, latitude angle, declination angle, hour angle, and azimuth angle need to be calculated. By computing the solar insolation for specific regions of interest, specifically the Gulf Cooperation Council (GCC) countries, the desired results can be obtained. Additionally, the study aims to assess the influence of PV cell temperature on the I–V curves of commercially available PV modules, which will provide insights into the impact of temperature on the performance characteristics of PV cells. By employing a developed model, the study examined the combined collective influences of solar received radiation, tilt angle, and ambient temperature on the output power of PV systems in five different cities. The annual optimal tilt angles were found to be as follows: Mecca (21.4° N)—21.48°, Fujairah (25.13° N)—25.21°, Kuwait (29.3° N)—29.38°, Baghdad (33.3° N)—33.38°, and Mostaganem (35.9° N)—2535.98°. Notably, the estimated yearly optimal tilt angles closely corresponded to the latitudes of the respective cities. Additionally, the study explored the impact of ambient temperature on PV module performance. It was observed that an increase in ambient temperature resulted in a corresponding rise in the temperature of the PV cells, indicating the significant influence of environmental temperature on PV module efficiency. Overall, the findings demonstrate that adjusting the tilt angle of PV modules on a monthly basis led to higher solar power output compared to yearly adjustments. These results underscore the importance of considering both solar radiation and ambient temperature when optimizing PV power generation. Full article

Background and Objectives: To identify clinical, ultrasound (US) and real-time elastography (RTE) characteristics indicative of malignancy in small thyroid lesions. Materials and Methods: 141 consecutive patients with incidentally discovered solid thyroid nodules (diameter ≤ 10 mm) by neck US were assessed, and RTE was performed. The nodules were classified per American (ACR-TIRADS) and European (EU-TIRADS) criteria; US-guided FNA was conducted on EU-TIRADS 5 nodules. The US and RTE features of nodules classified as benign (Bethesda II) or malignant (Bethesda V and VI) were compared. Results: 41 nodules were classified as EU-TIRADS 5. Their Fine Needle Aspiration (FNA) cytology was Bethesda II (n = 11), III-IV (n = 3), V (n = 10) or VI (n = 17). Bethesda V–VI patients had a higher rate of autoimmune thyroiditis (p = 0.015) and higher ACR-scoring points (p < 0.001) compared with Bethesda II. The elastography ratio was equal between the groups (p = 0.584). In logistic regression analysis, ACR-scoring points predicted FNA results, with an area under the curve (AUC) of 0.993 (sensitivity 92.6% and specificity of 100%). The clinical model (age, body mass index, sex, autoimmunity, L-thyroxine treatment, nodule diameter, elastography ratio) achieved an AUC of 0.744. A “mixed” model, combining clinical characteristics with the ACR scoring points, achieved perfect performance (AUC = 1.000), predicting FNA results with 100% sensitivity and specificity. Conclusions: The proposed “mixed model” can predict Bethesda V–VI in thyroid nodules <10 mm, allowing for the selection of those needing further evaluation. Full article

Water stress represents one of the most critical limiting factors affecting plant distribution, growth rate, biomass accumulation, and crop yield across diverse growth stages. Variations in species’ drought tolerance fundamentally shape global biodiversity patterns by influencing survival rates, distribution ranges, and community composition under changing environmental conditions. This study investigated the physiological responses of six plant species (Haloxylon ammodendron (H.A.), Nitraria tangutorum Bobr. (N.T.B.), Sympegma regelii Bge. (S.R.B.), Tamarix chinensis (T.C.), Potentilla fruticosa (P.F.R.), and Sabina chinensis (Linn.) Ant. (S.C.A.)) to varying water stress levels through controlled water gradient experiments. Four treatment levels were established: W1 (full water supply, >70% field water holding capacity); W2 (mild stress, 50–55%); W3 (moderate stress, 35–40%); and W4 (severe stress, 20–25%). Height growth and leaf mass per area decreased significantly with increasing water stress across all species. S.C.A. consistently exhibited the highest leaf mass per area among the six species, while H.A. showed the lowest values across all treatments. Leaf water content declined progressively with intensifying water stress, with T.C. and P.F.R. showing the most pronounced reductions (T.C.: 16.53%, 18.07%, and 33.37% under W2, W3, and W4, respectively; P.F.R.: 19.45%, 28.52%, and 36.08%), whereas N.T.B. and H.A. demonstrated superior water retention capacity (N.T.B.: 2.44%, 6.64%, and 9.76%; H.A.: 1.44%, 4.39%, and 5.52%). Water saturation deficit increased correspondingly with declining soil moisture. Diurnal leaf water potential patterns exhibited a characteristic V-shaped curve under well-watered (W1) and mildly stressed (W2) conditions, transitioning to a double-valley pattern with unstable fluctuations under moderate (W3) and severe (W4) stress. Leaf water potential showed linear relationships with air temperature and relative humidity, and a quadratic relationship with atmospheric water potential. For all six species, the relationship between pre-dawn leaf water potential and soil water content followed the curve equation y = a + b/x. Under water-deficient conditions, S.C.A. exhibited the greatest water physiological changes, followed by P.F.R. Both logarithmic and power function relationships between leaf and soil water potentials were highly significant (all F > 55.275, all p < 0.01). T.C. leaf water potential was the most sensitive to soil water potential changes, followed by S.C.A., while H.A. demonstrated the least sensitivity. These findings provide essential theoretical foundations for selecting drought-resistant plant species in arid regions of the Qaidam Basin. This study elucidates the response mechanisms of six distinct drought-tolerant plant species under water stress. It provides critical theoretical support for selecting drought-tolerant species, designing community configurations, and implementing water management strategies in vegetation restoration projects within the arid Qaidam Basin. Furthermore, it contributes empirical data at the plant physiological level to understanding the mechanisms sustaining species diversity in arid ecosystems. Full article

The main objective of this paper is to develop a maximum power point tracker (MPPT) for a photovoltaic module array (PVMA) under conditions of partial shading and sudden changes in solar irradiance. PVMAs exhibit nonlinear characteristics with respect to temperature and solar irradiance conditions. Therefore, when some modules in the array are shaded or when there is a sudden change in solar irradiance, the maximum power point (MPP) of the array will also change, and the power–voltage (P-V) characteristic curve may exhibit multiple peaks. Under such conditions, if the tracking algorithm employs a fixed step size, the time required to reach the MPP may be significantly prolonged, potentially causing the tracker to converge on a local maximum power point (LMPP). To address the issues mentioned above, this paper proposes a novel MPPT technique based on the nature-inspired idols algorithm (IA). The technique allows the promotion value (PM) to be adjusted through the anti-fans weight (afw) in the iteration formula, thereby achieving global maximum power point (GMPP) tracking for PVMAs. To verify the effectiveness of the proposed algorithm, a model of a 4-series–3-parallel PVMA was first established using MATLAB (2024b version) software under both non-shading and partial shading conditions. The voltage and current of the PVMAs were fed back, and the IA was then applied for GMPP tracking. The simulation results demonstrate that the IA proposed in this study outperforms existing MPPT techniques, such as particle swarm optimization (PSO), cat swarm optimization (CSO), and the bat algorithm (BA), in terms of tracking speed, dynamic response, and steady-state performance, especially when the array is subjected to varying shading ratios and sudden changes in solar irradiance. Full article

Bifacial Photovoltaic (bPV) technology is rapidly becoming the standard in the solar photovoltaic (PV) industry due to its ability to capture reflected radiation and generate additional energy. This experimental study analyses the electrical performance of bPV modules under specific installation conditions, including varying heights, module tilt angles (MTA), and surface reflectivity. The methodology combines controlled indoor testing with outdoor experiments that replicate real-world operating environments. The outdoor test setup was carefully designed and included dual data acquisition systems: one with independent sensors and another with wireless telemetry for data transfer from the inverter. A thermal performance model was used to estimate energy output and was benchmarked against experimental measurements. All electrical parameters were obtained in accordance with international standards, including current-voltage characteristic (I–V curve) corrections, using calibrated instruments to monitor irradiance and temperature. Indoor measurements under Standard Test Conditions yielded at bifaciality coefficient $\phi =0.732$, a rear bifacial power gain $BiFi=0.285$, and a relative bifacial gain $BiF{i}_{rel}=9.4\%$. The outdoor configuration employed volcanic red stone (Tezontle) as a reflective surface, simulating a typical mid-latitude installation with modules mounted 1.5 m above ground, tilted from 0° to 90° regarding floor and oriented true south. The study was conducted at a site located at 18.8° N latitude during the early summer season. Results revealed significant non-uniformity in rear-side irradiance, with a 32% variation between the lower edge and the centre of the bPV module. The thermal model used to determine electrical performance provides power values higher than those measured in the time interval between 10 a.m. and 3 p.m. Maximum energy output was observed at a MTA of $0°$, which closely aligns with the optimal summer tilt angle for the site’s latitude. Bifacial energy gain decreased as the MTA increased from $0°$ to $90°$. These findings offer practical, data-driven insights for optimizing bPV installations, particularly in regions between $15°$ and $30°$ north latitude, and emphasize the importance of tailored surface designs to maximize performance. Full article

Objectives: To evaluate the diagnostic accuracy of AI-assisted biparametric MRI (AI-bpMRI) in detecting prostate cancer (PCa) as a possible replacement for multiparametric MRI (mpMRI) depending on readers’ experience. Methods: This fully crossed, multireader multicase, single-centre, consecutive study retrospectively included men with suspected PCa. Three radiologists with different levels of experience independently scored each participant’s biparametric (bp) MRI, mpMRI, and AI-bpMRI according to the PI-RADS V2.1 classification. The AI-assisted image processing was based on a sequential deep learning network. Histopathological findings were used as a reference. The study evaluated the mean areas under the receiver operating characteristic curves (AUCs) using the jackknife method for covariance. AUCs were tested for non-inferiority of AI-bpMRI to mpMRI (non-inferiority margin: −0.05). Results: A total of 105 men (mean age 66 ± 7 years) were evaluated. AI-bpMRI was non-inferior to mpMRI in detecting both Gleason score (GS) ≥ 3 + 4 PCa (AUC difference: 0.03 [95% CI: −0.03, 0.08], p = 0.37) and GS ≥ 3 + 3 PCa (AUC difference: 0.04 [95% CI: −0.01, 0.09], p = 0.14) and was superior to bpMRI in detecting GS ≥ 3 + 3 PCa (AUC difference: 0.07 [95% CI: 0.02, 0.12], p = 0.004). The benefit of AI-bpMRI was greatest for the readers with low or medium experience (AUC difference in detecting GS ≥ 3 + 4 compared to mpMRI: 0.06 [95% CI: −0.03, 0.14], p = 0.19 and 0.06 [95% CI: −0.03, 0.14], p = 0.19, respectively). Conclusions: This study indicates that AI-bpMRI detects PCa with a diagnostic accuracy comparable to that of mpMRI. Full article

This work investigates the effect of interface traps on the impedance spectra of dopant-free silicon solar cells. The studied device consists of a crystalline silicon absorber with an a-Si:H/MoOx/ITO stack as the front passivating hole-collecting contact and an a-Si:H/LiF/Al stack as the rear passivating electron-collecting contact. Experimental measurements, including illuminated current–voltage (I–V) characteristics and impedance spectroscopy, were performed on the fabricated devices and after a soft annealing treatment. The annealed cells exhibit an increased open-circuit voltage and a larger Nyquist plot radius. To interpret these results, a numerical model was developed in a TCAD environment. Simulations reveal that traps located at the p/i interface (MoOx/i-a-Si:H) significantly affect the impedance spectra, with higher trap concentrations leading to smaller Nyquist plot circumferences. The numerical impedance curves were aligned to the experimental data, enabling extraction of the interfacial traps concentration. The results highlight the sensitivity of impedance spectroscopy to interfacial quality and confirm that the performance improvement after soft annealing is primarily due to reduced defect density at the MoOx/i-a-Si:H interface. Full article

Partial shading condition (PSC) for photovoltaic (PV) arrays complicates the operation of PV systems at peak power due to the existence of multiple peak points on the power–voltage (P–V) characteristic curve. Identifying the global peak among multiple peaks presents challenges, as the system may become trapped at a local peak, potentially resulting in significant power loss. Power generation is reduced, and hot-spot issues might arise, which can cause shaded modules to fail, under the partly shaded case. In this paper, instead of focusing on local peaks, several effective, precise, and dependable maximum power point tracker (MPPT) systems monitor the global peak using a fuzzy logic controller. The suggested method can monitor the total of all PV array peaks using an interleaved boost converter DC/DC (IBC), not only the global peaks. A DC/DC class boost converter (CBC), the current gold standard for traditional control methods, is pitted against the suggested converter. Four PSC-PV systems employ three-phase inverters to connect their converters to the power grid. Full article

The deformation characteristics of the surrounding rock in tunnel groups are considered critical for the design of support structures and the assurance of the long-term safety of deep-buried diversion tunnels. The deformation behavior of surrounding rock in tunnel groups was investigated to guide structural support design. Field tests and numerical simulations were performed to analyze the distribution of ground stress and the ground reaction curve under varying conditions, including rock type, tunnel spacing, and burial depth. A solid unit–structural unit coupled simulation approach was adopted to derive the two-liner support characteristic curve and to examine the propagation behavior of concrete cracks. The influences of surrounding rock strength, reinforcement ratio, and secondary lining thickness on the bearing capacity of the secondary lining were systematically evaluated. The following findings were obtained: (1) The tunnel group effect was found to be negligible when the spacing (D) was ≥65 m and the burial depth was 1600 m. (2) Both P_0.3 and P_max of the secondary lining increased linearly with reinforcement ratio and thickness. (3) For surrounding rock of grade III (IV), 95% u_lim and 90% u_lim were found to be optimal support timings, with secondary lining forces remaining well below the cracking stress during construction. (4) For surrounding rock of grade V in tunnels with a burial depth of 200 m, 90% u_lim is recommended as the initial support timing. Support timings for tunnels with burial depths between 400 m and 800 m are 40 cm, 50 cm, and 60 cm, respectively. Design parameters should be adjusted based on grouting effects and monitoring data. Additional reinforcement is recommended for tunnels with burial depths between 1000 m and 2000 m to improve bearing capacity, with measures to enhance impermeability and reduce external water pressure. These findings contribute to the safe and reliable design of support structures for deep-buried diversion tunnels, providing technical support for design optimization and long-term operation. Full article

Background and Objectives: Adequate bone quality is essential for promoting initial bone ingrowth and preventing early migration during cementless total knee arthroplasty (TKA). However, gold-standard criteria for identifying suitable bone strength have yet to be established. Dual-energy computed tomography (DECT)-based volumetric bone mineral density (vBMD) is an emerging tool for assessing bone quality. This study aimed to determine whether DECT-derived vBMD can accurately predict suitable bone strength for cementless TKA. Materials and Methods: A total of 190 patients undergoing primary TKA with a standardized posterior-stabilized implant were prospectively enrolled. Prior to TKA, DECT-derived vBMD was measured in the femoral box region. Actual bone strength was evaluated using an indentation test on resected femoral box specimens. Correlation and linear regression analyses were performed to assess the relationship between DECT vBMD and actual bone strength. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) calculations were used to determine the optimal cut-off value and diagnostic accuracy of DECT vBMD in identifying candidates suitable for cementless TKA. Results: DECT-derived vBMD exhibited a strong correlation with actual bone strength (correlation coefficient = 0.719, p < 0.01), while linear regression analysis revealed a moderate association (R² = 0.51, p < 0.01). In addition, it demonstrated excellent diagnostic performance in predicting adequate bone quality for cementless TKA, yielding an AUC of 0.984, with a sensitivity of 91.9% and a specificity of 92.0%. Conclusions: DECT-derived vBMD is a reliable and accurate tool for assessing bone strength around the knee and predicting the suitable bone quality for cementless TKA. Full article

Current–voltage (I–V) characteristics are an important measure of photovoltaic (PV) generators, corresponding to environmental conditions regarding solar irradiance and temperature. The I–V curve tracer is a widely used instrument in power engineering to evaluate system performance and detect fault conditions in PV power systems. Several technologies have been applied to develop the device and trace I–V characteristics, improving accuracy, speed, and portability. Focusing on the outdoor environment, this paper presents an in-depth analysis and comparison of the system design and dynamics to identify the I–V tracing performance based on different power conversion topologies and data acquisition methods. This is a valuable reference for industry and academia to further the technology and promote sustainable power generation. Full article

Background: Hemodialysis patients, due to impaired kidney function and compromised immune responses, face increased risks from SARS-CoV-2. Anti-nucleocapsid IgG (anti-IgG N) antibodies are a commonly used marker to assess prior infection in the general population; however, their efficacy for hemodialysis patients remains unclear. Methods: A retrospective study of 361 hemodialysis patients evaluated anti-IgG N antibodies for detecting prior SARS-CoV-2 infection. Antibody levels were measured using a chemiluminescence immunoassay (CLIA) over the four time points. Boxplots illustrated antibody distribution across sampling stages and infection status. Logistic regression and receiver operating characteristic (ROC) curve analysis determined diagnostic accuracy, sensitivity, specificity, and optimal cutoff values. Results: Among the 361 hemodialysis patients, 36 (10.0%) had SARS-CoV-2 infection. Sex distribution showed a trend toward significance (p = 0.05). Boxplot analysis showed that anti-IgG N levels remained low in non-infected patients but increased in infected patients, peaking at the third sampling. Anti-IgG N demonstrated high diagnostic accuracy (AUC: 0.973–0.865) but declined over time (p = 0.00525). The optimal cutoff at C1 was 0.01 AU/mL (sensitivity 1.00, specificity 0.94). Adjusted models had lower predictive value. Conclusions: Anti-IgG N antibodies showed high diagnostic accuracy for detecting prior SARS-CoV-2 infection in hemodialysis patients, though performance declined over time. These findings highlight the need for tailored diagnostic strategies in this vulnerable population. Full article

In this study, a comprehensive experimental framework was developed to quantitatively characterize the pore structure of a deep coal-rock (DCR; reservoirs below [3000 m]) gas reservoir. Experimentally, petrological and mineral characteristics were determined by performing proximate analysis and scanning electron microscopy (SEM) as well as by measuring vitrinite reflectance and maceral components. Additionally, physisorption and high-pressure mercury injection (HPMI) tests were conducted to quantitatively characterize the nano- to micron-scale pores in the DCR gas reservoir at multiple scales. The DCR in the NQ Block is predominantly composed of vitrinite, accounting for approximately 77.75%, followed by inertinite. The pore space is predominantly characterized by cellular pores, but porosity development is relatively limited as most of such pores are extensively filled with clay minerals. The isothermal adsorption curves of CO₂ and N₂ in the NQ Block and the DJ Block exhibit very similar variation patterns. The pore types and morphologies of the DCR reservoir are relatively consistent, with a significant development of nanoscale pores in both blocks. Notably, micropore metrics per unit mass (pore volume (PV): 0.0242 cm³/g; and specific surface area (SSA): 77.7545 m²/g) indicate 50% lower gas adsorption potential in the DJ Block. In contrast, the PV and SSA of the mesopores per unit mass in the NQ Block are relatively consistent with those in the DJ and SF Blocks. Additionally, the peak mercury intake in the NQ Block occurs within the pore diameter < 20 nm, with nearly 60% of the mercury beginning to enter in large quantities only when the pore size exceeds 20 nm. This indicates that nanoscale pores are predominantly developed in the DCR of the NQ block, which aligns with the findings from physical adsorption experiments and SEM analyses. Overall, the development characteristics of multi-scale pores in the DCR formations of the NQ Block and the eastern part of the Basin are relatively similar, with both total PV and total SSA showing an L-shaped distribution. Due to the disparity in micropore SSA, however, the total SSA of the DJ Block is approximately twice that of the NQ Block. This discovery has established a robust foundation for the subsequent exploitation of natural gas resources in DCR formations within the NQ Block. Full article

Photovoltaic (PV) technology is essential for achieving net-zero emissions by 2050. PV system efficiency is highly sensitive to irradiance, temperature, and shading. However, accurate parameter identification is critical for modeling, as PV models often exhibit multi-modal and strongly coupled characteristics. In addition, commercial datasheets typically lack sufficient parameter information, making precise parameter extraction difficult and limiting the accuracy of maximum power point predictions. To address these challenges, this research employs a novel metaheuristic algorithm called Puma Optimizer (PO) to optimize the parameters of multiple PV models. The PO’s performance is benchmarked against four advanced metaheuristic algorithms using convergence curves, error bars, and boxplots to evaluate its robustness. Results show that PO demonstrates strong adaptability and reliable performance in PV parameter optimization. Lastly, the research analyzes parameter sensitivity to help reduce computational resource usage. Visual analysis confirms that the PO parameter optimization approach provides an effective and practical solution for enhanced energy management and stable grid integration as solar adoption continues to expand. Full article

When analyzing the dynamics of wind turbines under the action of wind and ground motion, mass–point models cannot accurately predict the dynamic response of the structure. Additionally, the coupling effect between the pile foundation and the soil affects the vibration characteristics of the wind turbine. In this paper, the dynamic response of a DTU 10 MW wind turbine under the coupling effect of wind and an earthquake is numerically studied through the combined simulation of finite-element software ABAQUS 6.14-4 and OpenFAST v3.0.0. A multi-pile foundation is used as the foundation of the wind turbine structure, and the interaction between the soil and the structure is simulated by using p-y curves in the numerical model. Considering the coupling effect between the blade and the tower as well as the soil–structure coupling effect, this paper systematically investigates the vibration response of the blade–tower coupled structure under dynamic loads. The study shows that: (1) the blade vibration has a significant impact on the tower’s vibration characteristics; (2) the ground motion has varying effects on blades in different positions and will increase the out-of-plane vibration of the blades; (3) the SSI effect has a substantial impact on the out-of-plane vibration of the blade, which may cause the blade to collide with the tower, thus resulting in the failure and damage of the wind turbine structure. Full article