This paper reports for the first time on a new layered magnetic heterometallic erbium telluride EuErCuTe₃. Single crystals of the compound were obtained from the elements at 1120 K using CsI as a flux. The crystal structure of EuErCuTe₃ was solved in the space group Cmcm (a = 4.3086(3) Å, b = 14.3093(9) Å, and c = 11.1957(7) Å) with the KZrCuS₃ structure type. In the orthorhombic structure of erbium telluride, distorted octahedra ([ErTe₆]⁹⁻) form two-dimensional layers ($\left\{{\left[\mathrm{E}\mathrm{r}{\left(\mathrm{T}\mathrm{e}1\right)}_{2/2}^e{\left(\mathrm{T}\mathrm{e}2\right)}_{4/2}^k\right]}^{-}\right\}_{\infty }^2)$, while distorted tetrahedra ([CuTe₄]⁷⁻) form one-dimensionally connected substructures ($\left\{{\left[\mathrm{C}\mathrm{u}{\left(\mathrm{T}\mathrm{e}1\right)}_{2/2}^e{\left(\mathrm{T}\mathrm{e}2\right)}_{2/1}^t\right]}^{5-}\right\}_{\infty }^1$) along the [100] direction. The distorted octahedra and tetrahedra form parallel two-dimensional layers ($\left\{{\left[\mathrm{C}\mathrm{u}\mathrm{E}\mathrm{r}{\mathrm{T}\mathrm{e}}_3\right]}^{2-}\right\}_{\infty }^2)$ between which Eu²⁺ ions are located in a trigonal-prismatic coordination environment (${\left[{\mathrm{E}\mathrm{u}\mathrm{T}\mathrm{e}}_6\right]}^{10-})$. The trigonal prisms are connected by faces, forming chains ($\left\{{\left[{\mathrm{E}\mathrm{u}\left(\mathrm{T}\mathrm{e}1\right)}_{2/2}{\left(\mathrm{T}\mathrm{e}2\right)}_{4/2}\right]}^{2-}\right\}_{\infty }^1$) along the [100] direction. Regularities in the variations in structural parameters were established in the series of erbium chalcogenides (EuErCuCh₃ (Ch = S, Se, and Te)) and tellurides (EuLnCuTe₃ (Ln = Gd, Er, and Lu)). Ab-initio calculations of the crystal structure, phonon spectrum, and elastic properties of the compound EuErCuTe₃ were performed. The types and wavenumbers of fundamental modes were determined, and the involvement of ions in the IR and Raman modes was assessed. The experimental Raman spectra were interpreted. The telluride EuErCuTe₃ at temperatures below 4.2 K was ferrimagnetic, as were the sulfide and selenide derivatives (EuErCuCh₃ (Ch = S and Se)). Its experimental magnetic characteristics were close to the calculated ones. The decrease in the magnetic phase transition temperature in the series of the erbium chalcogenides was discovered. Full article

A high-precision catadioptric telescope such as a space-borne telescope is usually tested with interferometer to check the optical quality in assembly. The coarse and fine alignment of the telescope are mainly based on the information from the coordinate measuring machine and the fringe pattern of the interferometer, respectively. In addition, further fine-tuning can be achieved according to the variation in wavefront error and Zernike data. The issue is that the vast majority of the catadioptric telescopes contain plural lens surfaces which could produce unwanted ghost fringes, disturbing the wavefront measurement. Technically, off-axis installation to shift away ghost fringes from central interferogram could be acceptable in some cases. Nevertheless, in this paper, the source of ghost fringe in interferometric measurement for catadioptric telescopes is investigated with light path simulation, and a solution of reducing the f-number of the diverger lens is proposed to eliminate the ghost fringe disturbance. Both simulation and experimental results verify the effectiveness of the proposed concept. Full article

Electrical tomography sensors have been widely used for pipeline parameter detection and estimation. Before they can be used in formal applications, the sensors must be calibrated using enough labeled data. However, due to the high complexity of actual measuring environments, the calibrated sensors are inaccurate since the labeling data may be uncertain, inconsistent, incomplete, or even invalid. Alternatively, it is always possible to obtain partial data with accurate labels, which can form mandatory constraints to correct errors in other labeling data. In this paper, a semi-supervised fuzzy clustering algorithm is proposed, and the fuzzy membership degree in the algorithm leads to a set of mandatory constraints to correct these inaccurate labels. Experiments in a dredger validate the proposed algorithm in terms of its accuracy and stability. This new fuzzy clustering algorithm can generally decrease the error of labeling data in any sensor calibration process. Full article

During shield construction in underground spaces, synchronous grouting slurry is poured between the surrounding rock and tunnel lining to ensure stability. For synchronous grouting slurries, few studies have investigated the relationship between the rheological parameters and physical properties, grout-segregation mechanism, and anti-segregation performance. Therefore, we explored the relationships between the slurry rheological parameters, segregation rate, and bleeding rate. Cement, sand, fly ash, and bentonite were used to prepare the slurry, and the effects of different polycarboxylate water-reducing agents and dispersible latex powder dosages were studied. The rheological parameters of 16 groups of uniformly designed slurries were tested, and the data were fit using the Herschel–Bulkley model. The optimal mix ratio lowered the slurry segregation rate, and its rheological behaviour was consistent with the Herschel–Bulkley fluid characteristics. High-yield-shear-stress synchronous grouting slurries with high and low viscosity coefficients were less likely to bleed and segregate, respectively. The optimised slurry fluidity, 3 h bleeding rate, 24 h bleeding rate, segregation rate, coagulation time, and 28 days compressive strength were 257.5 mm, 0.71%, 0.36%, 3.1%, 6.7 h, and 2.61 MPa, respectively, which meet the requirements of a synchronous grouting slurry of shield tunnels for sufficiently preventing soil disturbance and deformation in areas surrounding underground construction sites. Full article

Japanese plums have relatively high water requirements, which depend on supplementing rainfall volumes with accurately quantified irrigation water. There is a lack of knowledge on the seasonal water requirements of plum orchards. This gap in the literature poses an imminent threat to the long-term sustainability of the South African plum industry, which is particularly plagued by climate change and diminishing water resources. The systematic literature review conducted in this study aimed to provide a foundation for supporting water management in irrigated Japanese plum [Prunus salicina Lindl.] orchards. Seventeen peer-reviewed articles obtained from the literature were analyzed. Approximately 66% of the cultivars were cultivated under different regulated deficit irrigation regimes for water-saving purposes and to increase fruit quality. This review of our knowledge provided benchmark figures on the annual water requirements of Japanese plums. The full-year plum crop water requirements obtained from the literature ranged between 921 and 1211 mm a⁻¹. Canopy growth, pruning and growing season length were the most common causes of differences in the water requirement estimates. Further research is required to measure the water requirement of plums from planting to full-bearing age and the response of plum trees to water stress, especially in the South African context. Full article

Two species of black flies (Simuliidae) in Thailand, Simulium chumpornense Takaoka and Kuvangkadilok, 2000, and S. khelangense Takaoka, Srisuka & Saeung, 2022, are potent vectors of avian blood protozoa of the genera Leucocytozoon and Trypanosoma and are pests of domestic avian species. Although the adults are abundant throughout Thailand, information on their breeding habitats is limited, and the immature stages of S. khelangense are unknown. We collected the larvae and pupae of S. khelangense from the Mekong River, the first-ever record of Simuliidae from this large continental river. Mitochondrial cytochrome c oxidase I and internal transcribed spacer 2 were used to associate the larvae and pupae with known adults. Both genetic markers strongly supported their identity as S. khelangense. The larvae and pupa of S. khelangense are described. The pupal gill filaments, larval abdominal protuberances, and setae distinguish this species from other members of the S. varicorne species group. The immature stages of S. chumpornense inhabit a wide variety of flowing waters, from small streams (3 m wide) to enormous continental rivers (400 m wide); thus, S. chumpornense is a habitat generalist. In contrast, S. khelangense was found only in the large Mekong River and is, therefore, a habitat specialist. Both species can exploit their principal habitats and produce abundant adult populations. Full article

This paper introduces a soft, cable-driven parallel robot for minimally invasive surgeries. The robot comprises a pneumatic inflatable scaffold, six hydraulic, folded pouch actuators, and a hollow, cylindrical end-effector offering five degrees of freedom. A key development is the design of the pouch actuators, which are small, low-profile, simple structures, capable of a high stroke of 180° angular displacement. The scaffold, actuators, and plastic cables are economically and rapidly fabricated using laser cutting and welding techniques. Constructed primarily from soft plastic materials, the robot can be compactly folded into a cylinder measuring 110 mm in length and 14 mm in diameter. Upon inflation, the scaffold transforms into a hexagonal prism structure with side lengths of 34 mm and edge lengths of 100 mm. The kinematic model of the robot has been developed for workspace calculation and control purposes. A series of tests have been conducted to evaluate the performance of the actuator and the robot. Repeatability tests demonstrate the robot’s high repeatability, with mean and root mean square errors of 0.3645 mm and 0.4186 mm, respectively. The direct connection between the end-effector and the actuators theoretically eliminates cable friction, resulting in a hysteresis angle of less than 2°, as confirmed by the tracking results. In addition, simulated surgical tasks have been performed to further demonstrate the robot’s performance. Full article

Caudal regression syndrome (CRS) is a rare congenital malformation characterized by incomplete development of the lower spine and spinal cord. Its estimated incidence ranges from 1 to 2 per 100,000 live births, leading to a spectrum of clinical presentations. Although most cases are diagnosed during childhood, only a small number of cases have been documented in adults in the medical literature. Case Report: A 27-year-old woman underwent an outpatient magnetic resonance imaging (MRI) of the thoracolumbar spine due to severe lower back pain experienced for the first time. Despite congenital leg abnormalities and multiple childhood surgeries, no further investigations were conducted at that time. MRI revealed congenital anomalies consistent with CRS, including coccygeal agenesis, L5 sacralization, and spinal cord defects. The patient also had a long-standing pilonidal cyst treated conservatively, now requiring operative treatment due to an abscess. Conclusions: This report underscores a rare case of CRS initially misdiagnosed and mistreated over many years. It emphasizes the importance of considering less common diagnoses, especially when initial investigations yield inconclusive results. This clinical case demonstrates a highly valuable and educative radiological finding. In the literature, such cases with radiological findings in adults are still lacking. Full article

In order to precisely reproduce the precise seeding process of the population in the air-suction seed-metering device, it is necessary to execute accurate modeling of seed particles using the bonded-particle model, in combination with the discrete element method (DEM) and computational fluid dynamics (CFD). Through the repose angle, slope screening, rotating container, and particle sedimentation experiments, in this paper, the influence of the filling accuracy of the bonded-particle model on the flow behavior and mixing characteristics of the seed population was first explored based on EDEM software. The viability of the suggested modeling approach for pelleted vegetable seeds, as described in this study, was confirmed by comparing experimental and simulation outcomes. The surface roughness values obtained from the studies above were utilized to assess the accuracy of the bonded-particle model in filling. Additionally, a mathematical technique for determining the surface roughness was provided. Furthermore, an analysis of the multiple contacts in the bonded-particle model was also performed. The results indicated that the simulation results closely matched the experimental data when the number of sub-spheres in the bonded-particle model was equal to or more than 70, as measured by the standard deviation. In addition, the most optimal modeling scheme for the pelletized vegetable seed bonded-particles, based on the cost of coupling simulation, was found to be the bonded-particle surface roughness (BS) with a value of 0.1. Ultimately, a practical example was utilized to demonstrate the utilization of the pelleted vegetable seed bonded-particle model and the DEM-CFD coupling approach in analyzing the accuracy of the seeding process in the air-suction seed-metering device. This example will serve as a valuable reference point for future field studies. Full article

As strawberries are a widely grown cash crop, the development of strawberry fruit-picking robots for an intelligent harvesting system should match the rapid development of strawberry cultivation technology. Ripeness identification is a key step to realizing selective harvesting by strawberry fruit-picking robots. Therefore, this study proposes combining deep learning and image processing for target detection and classification of ripe strawberries. First, the YOLOv8+ model is proposed for identifying ripe and unripe strawberries and extracting ripe strawberry targets in images. The ECA attention mechanism is added to the backbone network of YOLOv8+ to improve the performance of the model, and Focal-EIOU loss is used in loss function to solve the problem of imbalance between easy- and difficult-to-classify samples. Second, the centerline of the ripe strawberries is extracted, and the red pixels in the centerline of the ripe strawberries are counted according to the H-channel of their hue, saturation, and value (HSV). The percentage of red pixels in the centerline is calculated as a new parameter to quantify ripeness, and the ripe strawberries are classified as either fully ripe strawberries or not fully ripe strawberries. The results show that the improved YOLOv8+ model can accurately and comprehensively identify whether the strawberries are ripe or not, and the mAP50 curve steadily increases and converges to a relatively high value, with an accuracy of 97.81%, a recall of 96.36%, and an F1 score of 97.07. The accuracy of the image processing method for classifying ripe strawberries was 91.91%, FPR was 5.03%, and FNR was 14.28%. This study demonstrates the program’s ability to quickly and accurately identify strawberries at different stages of ripeness in a facility environment, which can provide guidance for selective picking by subsequent fruit-picking robots. Full article

Convolutional neural network (CNN) models were devised and evaluated to classify infrared thermal (IRT) images of pediatric wrist fractures. The images were recorded from 19 participants with a wrist fracture and 21 without a fracture (sprain). The injury diagnosis was by X-ray radiography. For each participant, 299 IRT images of their wrists were recorded. These generated 11,960 images (40 participants × 299 images). For each image, the wrist region of interest (ROI) was selected and fast Fourier transformed (FFT) to obtain a magnitude frequency spectrum. The spectrum was resized to 100 × 100 pixels from its center as this region represented the main frequency components. Image augmentations of rotation, translation and shearing were applied to the 11,960 magnitude frequency spectra to assist with the CNN generalization during training. The CNN had 34 layers associated with convolution, batch normalization, rectified linear unit, maximum pooling and SoftMax and classification. The ratio of images for the training and test was 70:30, respectively. The effects of augmentation and dropout on CNN performance were explored. Wrist fracture identification sensitivity and accuracy of 88% and 76%, respectively, were achieved. The CNN model was able to identify wrist fractures; however, a larger sample size would improve accuracy. Full article

1,3-Alternate calix[4]arenes were prepared, having bulky adamantyl groups in the p-positions of all four aromatic units of the macrocycles and pairs of propargyl or 2-azidoethyl groups alternating with n-propyl groups at the phenol oxygen atoms. The step-wise syntheses were carried out through a selective distal alkylation of the parent p-adamantylcalix[4]arene with propargyl bromide or 1,2-dibromoethane, resulting in calix[4]arenes bearing pairs of propargyl or 2-bromoethyl groups at their narrow rims. The bromine atoms were replaced by azide groups, and then both calix[4]arene diethers were exhaustively alkylated at the remaining OH-groups with 1-iodopropane under stereoselective conditions to fix the macrocycles in an 1,3-alternate shape. The structures of the prepared p-adamantylcalix[4]arenes were confirmed by NMR and HRMS data, and, for the 1,3-alternate dipropargyl ether, the X-ray diffraction data were also collected. Preliminary data on the reactivity of the prepared calixarenes under the CuAAC conditions suggested a strong steric hampering created by the adamantane units nearby the reacting alkyne or azide groups that affected the outcome of the two-fold cycloaddition involving the calixarene bis(azides) or bis(alkynes) as complementary partners. Full article

The optimal designing of the hybrid energy system (HES) is a challenging task due to the multiple objectives and various uncertainties. Especially for HES, primarily powered by solar energy, the reference solar radiation data directly impact the result of the optimization design. To incorporate the stochastic characteristics of solar radiation into the sizing process, a data-driven stochastic modeling method for solar radiation is proposed. The method involves two layers of stochastic processes that capture the intraday variation and daily evolution of solar radiation. First, the clearness index (CI) is introduced to describe the radiation intensity at different times. Then, the daily clearness state (DCS) is proposed, based on the statistical indicators of the intraday CI. The Markov model is used to describe the stochastic evolutionary characteristics between different DCSs. The probabilistic distribution of the CI under different DCS is obtained based on the diffusion kernel density estimation (DKDE), which is used for the stochastic generation of the CI at various times of the day. Finally, the radiation profile required for the optimal design is obtained by the stochastic generation of the DCS sequences and the intraday clearness index under corresponding states. A case study of an off-grid solar-powered HES is provided to illustrate this methodology. Full article

Lowland tropical rainforests provide an abundance of biodiversity as well as dynamic and stable ecosystems. These forests include tropical peat forests in various locations and forest types that have vegetation structure and composition characteristics, and carbon stocks that still need to be explored more deeply. Research on the structure and the composition of the vegetation and carbon stock in the old secondary peat forest was carried out in the protected areas of Bukit Batu, Riau Province, and Muara Merang, South Sumatra Province. Based on a 1-hectare permanent plot established in Bukit Batu and Muara Merang, 25 subplots of 20 m by 20 m were established in each location for measurement purposes. The results showed that Bukit Batu and Muara Merang had 42 and 36 species belonging to 26 and 20 families, respectively. Bukit Batu had a species diversity index (H’) of 2.93, and the dominant tree species were Palaquium xanthochymum with an importance value index (IVI) = 66.27%, Eugenia sp. (IVI = 32.76%), and Litsea sp. (IVI = 18.39%). The Muara Merang location had a species diversity index (H’) of 2.82, and the dominant tree species were Eugenia sp. (IVI = 60.88%), Alseodaphne insignis (IVI = 26.34%), and Adenanthera pavonina (IVI = 22.11%). In Bukit Batu, forest stands with a diameter of ≥10 cm contained a biomass of 178.10 tonnes/ha and carbon stock of 83.70 tonnes C/ha, which is equal to 307.20 tonnes CO₂/ha. Meanwhile, in Muara Merang, it was 190.41 tonnes/ha and 89.49 tonnes C/ha, which is equal to 328.44 tonnes CO₂/ha. This research, especially that in Bukit Batu, Riau Province, enriches the data and information available to date and is very useful in supporting restoration practices in Riau Province’s Giam Siak Kecil Biosphere Reserve, which was designated by UNESCO as part of the Man and Biosphere Program. Full article

Empirical evidence supports the simultaneous relationship between parental warmth and child-to-parent violence (CPV). However, no studies analyze the lagged effects of perceived parental warmth and the potential impact of cognitive mechanisms legitimizing immoral behavior on this relationship. This study aimed to examine the mediating role of moral disengagement strategies (reconstruction of immoral behavior, obscuring personal responsibility, misrepresenting injurious consequences, and blaming the victim) in the relationship between the perceived paternal and maternal warmth dimensions (warmth-communication and criticism-rejection) during childhood and CPV towards the father and mother. The sample included 2122 Spanish adolescents (57.7% female) aged 13 to 18 years. The Child-to-Parent Violence Questionnaire (CPV-Q), the Mechanisms of Moral Disengagement Scale (MMDS-S), and the Warmth Scale were used as assessment instruments. The results indicate that paternal and maternal warmth-communication is negatively associated with CPV, whereas paternal and maternal criticism-rejection and moral disengagement strategies are positively related to CPV. The mediation models show that the reconstruction of immoral behavior plays a crucial mediation role in the relationship between paternal and maternal warmth-communication and CPV as well as in the relationship between maternal criticism-rejection and CPV. The results emphasize the necessity of early prevention programs for parents promoting positive parenting practices, including parental warmth, to foster children’s adaptive socio-cognitive development. In addition, addressing moral disengagement in adolescents could help prevent or stop a pattern of violent behavior toward parents. Full article

The precise estimation of fluid motion is critical across various fields, including aerodynamics, hydrodynamics, and industrial fluid mechanics. However, refraction at complex interfaces in the light path can cause image deterioration and lead to severe measurement errors if the aberration changes with time, e.g., at fluctuating air–water interfaces. This challenge is particularly pronounced in technical energy conversion processes such as bubble formation in electrolysis, droplet formation in fuel cells, or film flows. In this paper, a flow field estimation algorithm that can perform the aberration correction function is proposed, which integrates the flow field distribution estimation algorithm based on the Particle Image Velocimetry (PIV) technique and the novel actuator-free adaptive optics technique. Two different multi-input convolutional neural network (CNN) structures are established, with two frames of distorted PIV images and measured wavefront distortion information as inputs. The corrected flow field results are directly output, which are divided into two types based on different network structures: dense estimation and sparse estimation. Based on a series of models, a corresponding dataset synthesis model is established to generate training datasets. Finally, the algorithm performance is evaluated from different perspectives. Compared with traditional algorithms, the two proposed algorithms achieves reductions in the root mean square value of velocity residual error by 84% and 89%, respectively. By integrating both flow field measurement and novel adaptive optics technique into deep CNNs, this method lays a foundation for future research aimed at exploring more intricate distortion phenomena in flow field measurement. Full article

Pharmaceuticals are used to improve the lives of people across the globe. The high demand for their fabrication and use causes a very serious environmental threat since their presence is ubiquitous in aqueous matrices. For this reason, the synthesis, characterisation, and efficiency of three chitosan-based materials to eliminate pharmaceutical mixtures from aqueous solutions were examined in the present study. The target mixture comprised seven widely used drugs: carbamazepine, cyclophosphamide, adefovir, levofloxacin, metronidazole, glibenclamide, and trimethoprim. The grafting of poly(ethylene imine) and poly(acrylamide) on the chitosan structure allowed its physical characteristics to be controlled. An adsorption assessment was performed at different pH values, and it was concluded that pH = 4 was the optimum value. The adsorption kinetics revealed that the adsorption of a drug mixture involves a combination of physical and chemical adsorption. The adsorption process appeared to be finished after 1 h for all compounds of the studied mixture, with CS-AMI exhibiting the fastest kinetics. Mass adsorption experiments were also carried out to determine its effects. Overall, the grafting process significantly increased the adsorption capacity over the pristine material. Specifically, the highest capacity increase for CS-PEI was ~220% for carbamazepine, and for CS-AMI, it was 158% for trimethoprim. FT-IR, SEM, and XRD were used for the characterisation of the polymers. Based on the findings, the three materials are suggested as very effective adsorbents for the elimination of medicine residues from aqueous matrices. Full article

Landslide disasters have garnered significant attention due to their extensive devastating impact, leading to a growing emphasis on the prompt and precise identification and detection of landslides as a prominent area of research. Previous research has primarily relied on human–computer interactions and visual interpretation from remote sensing to identify landslides. However, these methods are time-consuming, labor-intensive, subjective, and have a low level of accuracy in extracting data. An essential task in deep learning, semantic segmentation, has been crucial to automated remote sensing image recognition tasks because of its end-to-end pixel-level classification capability. In this study, to mitigate the disadvantages of existing landslide detection methods, we propose a multiscale attention segment network (MsASNet) that acquires different scales of remote sensing image features, designs an encoder–decoder structure to strengthen the landslide boundary, and combines the channel attention mechanism to strengthen the feature extraction capability. The MsASNet model exhibited an average accuracy of 95.13% on the test set from Bijie’s landslide dataset, a mean accuracy of 91.45% on the test set from Chongqing’s landslide dataset, and a mean accuracy of 90.17% on the test set from Tianshui‘s landslide dataset, signifying its ability to extract landslide information efficiently and accurately in real time. Our proposed model may be used in efforts toward the prevention and control of geological disasters. Full article

Vulvar carcinoma is a rare cancer affecting the genital tract, constituting 4% of gynecological tumors. Vulvar squamous cell carcinoma (VSCC) is the most common type. Diagnosis relies on biopsy during vulvoscopy, plus imaging such as ultrasonography (USG), magnetic resonance imaging (MRI) and positron emission tomography (PET). This review aims to lay out a thorough overview as to the current preoperative management of VSCC, both in case of vulvar and lymph node involvement. The data research was conducted using the following databases: MEDLINE, EMBASE, Web of Sciences, Scopus, ClinicalTrial.gov, OVID and Cochrane Library from 2010 to 2024. The selection criteria included only original articles. Seventeen studies were assessed for eligibility. A concordance rate of 62.3% for vHSIL and 65.2% for carcinoma at vulvoscopy, with a sensitivity of 98%, specificity of 40%, PPV (Positive Predictive Value) of 37% and NPV (Negative Predictive Value) of 98% in identifying malignant lesions was found. Regarding the reliability of PET for staging and assessing lymph node involvement, a mean SUV (Standardized Uptake Value) for malignant vulvar lesions of 8.4 (range 2.5–14.7) was reported. In the case of MRI, useful for the evaluation of loco-regional infiltration and lymph node involvement, the ratio of the short-to-long-axis diameter and the reader’s diagnostic confidence for the presence of lymph node metastasis yielded accuracy of 84.8% and 86.9%, sensitivity of 86.7% and 87.5%, specificity of 81.3% and 86.2%, PPV of 89.7% and 87.5% and NPV of 76.5% and 86.2%, respectively. A long lymph node axis >10 mm and a short diameter > 5.8 mm were found to be predictors of malignancy. At USG, instead, the two main characteristics of potentially malignant lymph nodes are cortical thickness and short axis length; the combination of these ultrasound parameters yielded the highest accuracy in distinguishing between negative and positive lymph nodes. Despite the heterogeneity of the included studies and the lack of randomized clinical trials, this review provides a broad overview of the three imaging tools used for the presurgical management of VSCC. Nowadays, although MRI and PET represent the gold standard, ultrasound evaluation is taking on a growing role, as long as it is carried out by expert sonographer. The management of this rare disease should be always performed by a multidisciplinary team in order to precisely stage the tumor and determine the most suitable treatment approach. Full article

Tobacco use disorder represents a significant public health challenge due to its association with various diseases. Despite awareness efforts, smoking rates remain high, partly due to ineffective cessation methods and the spread of new electronic devices. This study investigated the impact of prolonged nicotine exposure via a heat-not-burn (HnB) device on selected genes and signaling proteins involved in inflammatory processes in the rat ventral tegmental area (VTA) and nucleus accumbens (NAc), two brain regions associated with addiction to different drugs, including nicotine. The results showed a reduction in mRNA levels for PPARα and PPARγ, two nuclear receptors and anti-inflammatory transcription factors, along with the dysregulation of gene expression of the epigenetic modulator KDM6s, in both investigated brain areas. Moreover, decreased PTEN mRNA levels and higher AKT phosphorylation were detected in the VTA of HnB-exposed rats with respect to their control counterparts. Finally, significant alterations in ERK 1/2 phosphorylation were observed in both mesolimbic areas, with VTA decrease and NAc increase, respectively. Overall, the results suggest that HnB aerosol exposure disrupts intracellular pathways potentially involved in the development and maintenance of the neuroinflammatory state. Moreover, these data highlight that, similar to conventional cigarettes, HnB devices use affects specific signaling pathways shaping neuroinflammatory process in the VTA and NAc, thus triggering mechanisms that are currently considered as potentially relevant for the development of addictive behavior. Full article

In an effort to overcome the problems with typical optimization algorithms’ slow convergence and tendency to settle on a local optimal solution, an improved golden jackal optimization technique is proposed. Initially, the development mechanism is enhanced to update the prey’s location, addressing the limitation of just relying on local search in the later stages of the algorithm. This ensures a more balanced approach to both algorithmic development and exploration. Furthermore, incorporating the instinct of evading natural predators enhances both the effectiveness and precision of the optimization process. Then, cross-mutation enhances population variety and facilitates escaping from local optima. Finally, the crossbar strategy is implemented to change both the individual and global optimal solutions of the population. This technique aims to decrease blind spots, enhance population variety, improve solution accuracy, and accelerate convergence speed. A total of 20 benchmark functions are employed for the purpose of comparing different techniques. The enhanced algorithm’s performance is evaluated using the CEC2017 test function, and the results are assessed using the rank-sum test. Ultimately, three conventional practical engineering simulation experiments are conducted to evaluate the suitability of IWKGJO for engineering issues. The results obtained demonstrate the beneficial effects of the altered methodology and illustrate that the expanded golden jackal optimization algorithm has superior convergence accuracy and a faster convergence rate. Full article

Research simultaneously examining building energy consumption and outdoor thermal comfort within urban environments remains limited. Few studies have delved into the sensitivity of design parameters based on building energy consumption and outdoor thermal comfort. The purpose of this study is to investigate the correlations between urban morphological design parameters and performance indicators, focusing on building energy consumption and outdoor thermal comfort (UTCI), across different urban block layouts in hot-humid regions, like Guangzhou. By establishing six fundamental morphological models—three individual unit layouts and three group layouts—the research explores both control and descriptive parameters through extensive simulation studies. Scatter plot visualizations provide insights into the impacts of various design parameters on energy consumption and UTCI, facilitating a comprehensive analysis of trends and quantitative relationships. Additionally, the study conducts sensitivity analyses on design parameters under different layout conditions to highlight their influences on target performance indicators. The findings reveal common trends, such as the significant impacts of plan dimensions and the Floor Area Ratio (FAR) on energy efficiency and outdoor comfort, as well as differential patterns, such as the varying sensitivities of the Shape Factor (S/V) and the Sky View Factor (SVF), across individual and collective layouts. Ultimately, this study offers a nuanced understanding of urban block morphology’s role in creating sustainable, comfortable, and energy-efficient urban environments, providing valuable guidelines for urban form design in hot-humid climates. Full article