Osteoporosis constitutes a significant public health concern necessitating proactive prevention, treatment, and monitoring efforts. Timely identification holds paramount importance in averting fractures and alleviating the overall disease burden. The realm of osteoporosis diagnosis has witnessed a surge in interest in machine learning applications. This burgeoning technology excels at recognizing patterns and forecasting the onset of osteoporosis, paving the way for more efficacious preventive and therapeutic interventions. Smart walkers emerge as valuable tools in this context, serving as data acquisition platforms for datasets tailored to machine learning techniques. These datasets, trained to discern patterns indicative of osteoporosis, play a pivotal role in enhancing diagnostic accuracy. In this study, encompassing 40 participants—20 exhibiting robust health and 20 diagnosed with osteoporosis—data from force sensors embedded in the handlebars of conventional walkers were gathered. A windowing action was used to increase the size of the dataset. The data were normalized, and k-fold cross-validation was applied to assess how well our model performs on untrained data. We used multiple machine learning algorithms to create an accurate model for automatic monitoring of users’ gait, with the Random Forest classifier performing the best with 95.40% accuracy. To achieve the best classification accuracy on the validation dataset, the hyperparameters of the Random Forest classifier were further adjusted on the training data. The results suggest that machine learning-based automatic monitoring of gait parameters could lead to accurate, non-laborious, cost-effective, and efficient diagnostic tools for osteoporosis and other musculoskeletal disorders. Further research is needed to validate these findings. Full article

Target geolocation in long-range oblique photography (LOROP) is a challenging study due to the fact that measurement errors become more evident with increasing shooting distance, significantly affecting the calculation results. This paper introduces a novel high-accuracy target geolocation method based on multi-view observations. Unlike the usual target geolocation methods, which heavily depend on the accuracy of GNSS (Global Navigation Satellite System) and INS (Inertial Navigation System), the proposed method overcomes these limitations and demonstrates an enhanced effectiveness by utilizing multiple aerial images captured at different locations without any additional supplementary information. In order to achieve this goal, camera optimization is performed to minimize the errors measured by GNSS and INS sensors. We first use feature matching between the images to acquire the matched keypoints, which determines the pixel coordinates of the landmarks in different images. A map-building process is then performed to obtain the spatial positions of these landmarks. With the initial guesses of landmarks, bundle adjustment is used to optimize the camera parameters and the spatial positions of the landmarks. After the camera optimization, a geolocation method based on line-of-sight (LOS) is used to calculate the target geolocation based on the optimized camera parameters. The proposed method is validated through simulation and an experiment utilizing unmanned aerial vehicle (UAV) images, demonstrating its efficiency, robustness, and ability to achieve high-accuracy target geolocation. Full article

A device called a heat exchanger is used to exchange heat transfer between two fluids with different temperatures. Because of its durability and ability to handle high-pressure application, the concentric double pipe heat exchangers are widely utilized for numerous industrial applications. To conserve pumping power energy, many researchers were involved in study of the nanoparticles to be embedded in the fluid, which will enrich the fluid thermal conductivity and surface area. This article demonstrates the flow characteristics and convective heat transfer of nanofluids containing 0.2, 0.4 and 0.6 of vol% TiO₂ nanoparticles dispersed in water under turbulent conditions, which mainly can be used for cooling nuclear reactors applications. Reynolds numbers varying from 4000 to 18,000 are examined numerically. The convective heat transfer coefficient results of the nanofluid agree well against experimental data, which are slightly more than that of base water at 1.94%. The results of the numerical model showed that the convective heat transfer coefficient of nanofluids will increase when the Reynolds and volume fraction increases. By increasing the temperature of the annular hot water, the heat transfer rate will increase, showing no major impact to the convective heat transfer coefficient of nanofluids. A generalised solution predicting the convective heat transfer coefficient for extensive nanoparticle materials is proposed. The conclusion of the empirical equation is tested among published data and the results are highly congruent, confirming the strength of the gamma equation. Full article

Berberis microphylla, commonly known as calafate, is one of the most promising species of Chilean Patagonia to be domesticated, due to its anthocyanin-rich berries. The main aim of this study was to understand the genetic structure of the wild populations of B. microphylla in the main regions where it grows and its relationship with phenolic secondary metabolite profiles. Ripe berry samples and leaves were collected from the Aysén and Magallanes regions. Genetic analyses were carried out using 18 microsatellite markers. Phenolic compounds were extracted from the ripe fruits and were quantified using high-performance liquid chromatography (HPLC). Their antioxidant capacity was determined according to the Trolox equivalent antioxidant capacity (TEAC) assay. Total phenols were measured as their absorbance at a wavelength of 280 nm. Both the genetic and chemometric data were explored using unsupervised and supervised methods. The genetic markers suggest the existence of three groups, two of them corresponding to the Aysén and Magallanes samples, and the third corresponding to Chile Chico (a district in Aysén), which was the most divergent of the three. Similar results were observed in the phenolic profile obtained with chemometric analysis, with the same samples forming a separate third group. The differentiation achieved using the genetic and chemical data may be the result of intrinsic genetic differences, environmental effects on fruit maturity, or the sum of both factors. These are all points to consider in the domestication of this valuable species by selecting individuals with desirable traits and contrasting phenotypes. Full article

This paper introduces a self-attention Vision Transformer model specifically developed for classifying breast cancer in histology images. We examine various training strategies and configurations, including pretraining, dimension resizing, data augmentation and color normalization strategies, patch overlap, and patch size configurations, in order to evaluate their impact on the effectiveness of the histology image classification. Additionally, we provide evidence for the increase in effectiveness gathered through geometric and color data augmentation techniques. We primarily utilize the BACH dataset to train and validate our methods and models, but we also test them on two additional datasets, BRACS and AIDPATH, to verify their generalization capabilities. Our model, developed from a transformer pretrained on ImageNet, achieves an accuracy rate of 0.91 on the BACH dataset, 0.74 on the BRACS dataset, and 0.92 on the AIDPATH dataset. Using a model based on the prostate small and prostate medium HistoEncoder models, we achieve accuracy rates of 0.89 and 0.86, respectively. Our results suggest that pretraining on large-scale general datasets like ImageNet is advantageous. We also show the potential benefits of using domain-specific pretraining datasets, such as extensive histopathological image collections as in HistoEncoder, though not yet with clear advantages. Full article

Knowledge of a person’s level of skin pigmentation, or so-called “skin tone”, has proven to be an important building block in improving the performance and fairness of various applications that rely on computer vision. These include medical diagnosis of skin conditions, cosmetic and skincare support, and face recognition, especially for darker skin tones. However, the perception of skin tone, whether by the human eye or by an optoelectronic sensor, uses the reflection of light from the skin. The source of this light, or illumination, affects the skin tone that is perceived. This study aims to refine and assess a convolutional neural network-based skin tone estimation model that provides consistent accuracy across different skin tones under various lighting conditions. The 10-point Monk Skin Tone Scale was used to represent the skin tone spectrum. A dataset of 21,375 images was captured from volunteers across the pigmentation spectrum. Experimental results show that a regression model outperforms other models, with an estimated-to-target distance of 0.5. Using a threshold estimated-to-target skin tone distance of 2 for all lights results in average accuracy values of 85.45% and 97.16%. With the Monk Skin Tone Scale segmented into three groups, the lighter exhibits strong accuracy, the middle displays lower accuracy, and the dark falls between the two. The overall skin tone estimation achieves average error distances in the LAB space of $16.40\pm 20.62$. Full article

The pulsed- and steady-pedestal paradigms were designed to track increment thresholds (ΔC) as a function of pedestal contrast (C) for the parvocellular (P) and magnocellular (M) systems, respectively. These paradigms produce contrasting results: linear relationships between ΔC and C are observed in the pulsed-pedestal paradigm, indicative of the P system’s processing, while the steady-pedestal paradigm reveals nonlinear functions, characteristic of the M system’s response. However, we recently found the P model fits better than the M model for both paradigms, using Gabor stimuli biased towards the M or P systems based on their sensitivity to color and spatial frequency. Here, we used two-square pedestals under green vs. red light in the lower-left vs. upper-right visual fields to bias processing towards the M vs. P system, respectively. Based on our previous findings, we predicted the following: (1) steeper ΔC vs. C functions with the pulsed than the steady pedestal due to different task demands; (2) lower ΔCs in the upper-right vs. lower-left quadrant due to its bias towards P-system processing there; (3) no effect of color, since both paradigms track the P-system; and, most importantly (4) contrast gain should not be higher for the steady than for the pulsed pedestal. In general, our predictions were confirmed, replicating our previous findings and providing further evidence questioning the general validity of using the pulsed- and steady-pedestal paradigms to differentiate the P and M systems. Full article

Climate change is a notable challenge for agriculture as it affects crop productivity and yield. Increases in droughts, salinity, and soil degradation are some of the major consequences of climate change. The use of microorganisms has emerged as an alternative to mitigate the effects of climate change. Among these microorganisms, dark septate endophytes (DSEs) have garnered increasing attention in recent years. Dark septate endophytes have shown a capacity for mitigating and reducing the harmful effects of climate change in agriculture, such as salinity, drought, and the reduced nutrient availability in the soil. Various studies show that their association with plants helps to reduce the harmful effects of abiotic stresses and increases the nutrient availability, enabling the plants to thrive under adverse conditions. In this study, the effect of DSEs and the underlying mechanisms that help plants to develop a higher tolerance to climate change were reviewed. Full article

The effects of pineapple residue (PR) on fermentation quality, chemical composition, and bacterial community of corn straw (CS) silage were evaluated. CS was ensiled with 0% control group (CON), 15% (P1), 30% (P2), and 45% (P3) PR on a fresh matter (FM) basis for 45 days. P3 had lower dry matter (DM) and crude protein (CP) contents but higher ammonia-N (NH₃-N) content than the other three groups (p < 0.05). Compared with the other groups, P1 had lower a pH and higher lactic acid and acetic acid contents (p < 0.05). The lactic acid bacteria count in P1 was higher than in P2 and P3 (p < 0.05); the number of yeast in P2 was higher than in the other groups (p < 0.05). With the increasing proportion of PR addition, the relative abundance of Lactobacillus gradually increased, and the dominant genus in P3 was Acetobacter. In summary, the addition of PR can improve the quality of CS silage, and the optimum addition ratio for PR was 15% on a FM basis. Full article

Denture stomatitis (DS) is a very common disease in wearers of removable complete and partial dentures with a worldwide prevalence in the range of 20–67%. Both industrially developed and impoverished nations are affected by the illness. DS is often associated with ill-fitting dentures or a fungal infection with Candida spp. Candida is normally found in the oral cavity microbiota, but it can be harmful to the health of elderly people with underlying diseases. Therefore, the purpose of the present study is to offer the most recent information about the epidemiology, etiology, and global distribution of Candida species associated with DS through a systematic review. Several databases, including Medline, Web of Science, and Scopus, were used to conduct an extensive search of the literature published in the previous 20 years. The selection of studies was performed by two authors. The extracted data were as follows: author, year of publication, country, sample, frequency of DS, method of diagnosing stomatitis, species of Candida, risk factors, and etiology of the disease. The JBI Critical appraisal tools were used to assess the quality of the studies. Eventually, twenty-eight studies were included in the systematic review. Twenty-one studies investigated DS, while seven studies examined Candida colonization in patients using removable dentures. The results show that the main causes of DS include the type of dentures, continuous wearing of dentures, and the formation of a Candida biofilm, which is facilitated by poor dental hygiene. Additionally, previous studies have pinpointed the significance of the salivary flow, saliva composition, and salivary pH. The findings of the current review indicate that it is crucial to monitor denture wearers for the appearance of DS, especially the patients whose immunity has been impaired due to a systemic condition. Finally, frequent follow-ups should include a clinical examination and microbial swabs of the palatal mucosa and the mucosal surface of the denture. Full article

The objective of this work is to compare the levels of bioactive compounds in fresh and freeze-dried basil leaves (Ocimum basilicum), using methodological procedures that follow internationally recommended and accepted standards. The results show comparisons of bioactives between fresh and freeze-dried leaves, respectively, with results expressing the average levels of vitamin C (9.50–63.3 mg/100 g); total polyphenols (1.8–3.9 mgEAG/g); flavonoids (0.73–1.78 mg/g); chlorophyll a (2287.8–1003.8 μg/100 g); chlorophyll b (2606–2287 μg/100 g) and total carotenoids with averages of 16.71–20.6 mg/100 g). Regarding color, there was variation in the parameters L*, a*, and b* of the dry sample, but the tendency towards green e (a+) and yellow (b−) was maintained. Infrared analysis (FTIR) demonstrated the presence of functional groups related to cellulose, hemicellulose, and lignin. Thermogravimetry (TG/DTG) shows stability in the range of 234 °C, showing a more intense mass loss at 294.6 °C. Given the data, it is possible to infer that the application of freeze-drying produces few changes in bioactive compounds and chemical groups and maintains good thermal stability, proving to be a viable alternative to increasing the commercialization of basil leaves, as it prolongs their useful life, and increases the forms of food applications. Full article

Recent advancements in biomimetics have spurred significant innovations in prosthetic limb development by leveraging the intricate designs and mechanisms found in nature. Biomimetics, also known as “nature-inspired engineering”, involves studying and emulating biological systems to address complex human challenges. This comprehensive review provides insights into the latest trends in biomimetic prosthetics, focusing on leveraging knowledge from natural biomechanics, sensory feedback mechanisms, and control systems to closely mimic biological appendages. Highlighted breakthroughs include the integration of cutting-edge materials and manufacturing techniques such as 3D printing, facilitating seamless anatomical integration of prosthetic limbs. Additionally, the incorporation of neural interfaces and sensory feedback systems enhances control and movement, while technologies like 3D scanning enable personalized customization, optimizing comfort and functionality for individual users. Ongoing research efforts in biomimetics hold promise for further advancements, offering enhanced mobility and integration for individuals with limb loss or impairment. This review illuminates the dynamic landscape of biomimetic prosthetic technology, emphasizing its transformative potential in rehabilitation and assistive technologies. It envisions a future where prosthetic solutions seamlessly integrate with the human body, augmenting both mobility and quality of life. Full article

Fiber-reinforced cement composites, particularly those incorporating natural fibers like cellulose, have gained attention for their potential towards more sustainable construction. However, natural fibers present inherent deficiencies in mechanical properties and can benefit from hybridization with carbon fibers. This study focuses on the incorporation of cellulose and carbon fibers, in varying contents, into fibrocement composites, employing a Response Surface Methodology (RSM) to optimize the material characteristics. The methodology involves testing, encompassing flexural tensile, compression, and fracture toughness tests. The results indicate an increasing trend in flexural strength for higher carbon fiber content, peaking near 5%. A plateau in flexural strength is observed between 1.2% and 3.6% carbon fiber content, suggesting a range where mechanical properties stabilize. Compressive strength shows a plateau between 1.2 and 3.6% and reaches its highest value (≈33 MPa) at a carbon fiber content greater than 4.8%, and fracture toughness above 320 MPa·m^1/2 is achieved with carbon fiber content above 3.6%. This study offers insights into optimizing the synergistic effects of cellulose and carbon fibers in fibrocement composites. Full article

Introduction: Monoclonal antibodies (mAbs) are important therapeutics. However, the enhanced potential for aggregation has become a critical quality parameter during the production of mAbs. Furthermore, mAb aggregation may also present a potential health risk in a clinical setting during the administration of mAb therapeutics to patients. While the extent of immunotoxicity in patient populations is uncertain, reports show it can lead to immune responses via cell activation and cytokine release. In this study, an autologous in vitro skin test designed to predict adverse immune events, including skin sensitization, was used as a novel assay for the assessment of immunotoxicity caused by mAb aggregation. Material and Methods: Aggregation of mAbs was induced by a heat stress protocol, followed by characterization of protein content by analytical ultra-centrifugation and transmission electron microscopy, revealing a 4% aggregation level of total protein content. Immunotoxicity and potential skin sensitization caused by the aggregates, were then tested in a skin explant assay. Results: Aggregated Herceptin and Rituximab caused skin sensitization, as shown by histopathological damage (grade II–III positive response) together with positive staining for Heat Shock Protein 70 (HSP70). Changes in T cell proliferation were not observed. Cytokine analysis revealed a significant increase of IL-10 for the most extreme condition of aggregation (65 °C at pH3) and a trend for an overall increase of IFN-γ, especially in response to Rituximab. Conclusion: The skin explant assay demonstrated that aggregated mAbs showed adverse immune reactions, as demonstrated as skin sensitization, with histopathological grades II-III. The assay may, therefore, be a novel tool for assessing immunotoxicity and skin sensitization caused by mAb aggregation. Full article

This study aims to explore the relationship of the low-density lipoprotein cholesterol (LDL-C)/high-density lipoprotein (HDL-C) ratio with glycated hemoglobin (HbA1c), renal dysfunction, coronary heart disease (CHD) and cardiac structure and function in elderly patients with hypercholesterolemia. Methods: A total of 1129 hospitalized Chinese elderly (aged ≥ 65 years) with hypercholesterolemia were collected retrospectively. The patients were divided into low (<2.63), moderate (≥2.63 to <3.33) and high (≥3.33) LDL-C/HDL-C ratio groups according to the tertiles of LDL-C/HDL-C. Results: Regression analysis of the LDL-C/HDL-C ratio with metabolic and echocardiographic parameters revealed that a high LDL-C/HDL-C ratio (≥3.33) was associated independently with male gender, elevated HbA1c, decreased estimated glomerular filtration rate (eGFR), prevalent CHD and left ventricular dilatation (all p < 0.05). Conclusions: A high LDL-C/HDL-C ratio was associated with male gender, increased HbA1c, decreased eGFR, CHD and enlarged left ventricle in elderly with hypercholesterolemia. Full article

In this paper, we present sufficient conditions for Hyers–Ulam-Rassias stability of nonlinear implicit higher-order Volterra-type integrodifferential equations from above on unbounded time scales. These new sufficient conditions result by reducing Volterra-type integrodifferential equations to Volterra-type integral equations, using the Banach fixed point theorem, and by applying an appropriate Bielecki type norm, the Lipschitz type functions, where Lipschitz coefficient is replaced by unbounded rd-continuous function. Full article

Ratoon rice, the cultivation of a second crop from the stubble after the main harvest, is recognized as an eco-friendly and resource-saving method for rice production. Here, a field experiment was carried out in the Yangtze River region to investigate the impact of varying stubble heights on the grain quality of ratoon rice, as well as to compare the grain quality between the main and ratoon season. This study, which focused on 12 commonly cultivated rice varieties, conducted a comprehensive analysis assessing milling characteristics, appearance, and cooking quality. The results show that ratoon rice crops exhibited a higher milled rice rate and head rice rate compared to the main rice crops. Conversely, chalky rice percentage, chalkiness degree, and amylose content were lower in ratoon rice crops. Principal component analysis grouped eight relevant quality indicators of rice quality which were concentrated into three categories, with amylose content identified as the key indicator of rice quality for distinguishing between different stubble heights. Random forest results reveal a robust and significant correlation between appearance quality index and amylose content. Subordinate function analysis indicated that a stubble height of 30 cm resulted in optimal rice quality, with Lingliangyou 211 exhibiting the highest quality and Xiangzao Xian 32 the lowest. Overall, our study suggests that ratoon rice crops generally outperform main rice crops in terms of quality, with the optimal measurement at a stubble height of 30 cm. This study holds substantial importance for selecting appropriate stubble heights for ratoon rice crops and enhancing overall rice quality. Full article

Traumatic brain injury manifests itself in various forms, ranging from mild impairment of consciousness to severe coma and death. Traumatic brain injury remains one of the leading causes of morbidity and mortality. Currently, there is no therapy to reverse the effects associated with traumatic brain injury. New neuroprotective treatments for severe traumatic brain injury have not achieved significant clinical success. Methods: A literature review was performed to summarize the recent interdisciplinary findings on management of traumatic brain injury from both clinical and experimental perspective. Results: In the present review, we discuss the concepts of traditional and new approaches to treatment of traumatic brain injury. The recent development of different drug delivery approaches to the central nervous system is also discussed. Conclusions: The management of traumatic brain injury could be aimed either at the pathological mechanisms initiating the secondary brain injury or alleviating the symptoms accompanying the injury. In many cases, however, the treatment should be complex and include a variety of medical interventions and combination therapy. Full article

The constant and dynamic interaction between ventricular function and arterial afterload, known as ventricular-arterial coupling, is key to understanding cardiovascular pathophysiology. Ventricular–arterial coupling has traditionally been assessed invasively as the ratio of effective arterial elastance over end-systolic elastance (E_a/E_es), calculated from information derived from pressure–volume loops. Over the past few decades, numerous invasive and non-invasive simplified methods to estimate the elastance ratio have been developed and applied in clinical investigation and practice. The echocardiographic assessment of left ventricular E_a/E_es, as proposed by Chen and colleagues, is the most widely used method, but novel echocardiographic approaches for ventricular–arterial evaluation such as left ventricle outflow acceleration, pulse-wave velocity, and the global longitudinal strain or global work index have arisen since the former was first published. Moreover, multimodal imaging or artificial intelligence also seems to be useful in this matter. This review depicts the progressive development of these methods along with their academic and clinical application. The left ventricular–arterial coupling assessment may help both identify patients at risk and tailor specific pharmacological or interventional treatments. Full article

The addition of soil amendments and plants in heavy metal-contaminated soil can result in a significant impact on physicochemical properties, microbial communities and heavy metal distribution, but the specific mechanisms remain to be explored. In this study, Koelreuteria paniculata was used as a test plant, spent mushroom compost (SMC) and attapulgite (ATP) were used as amendments, and manganese slag was used as a substrate. CK (100% slag), M0 (90% slag + 5% SMC + 5% ATP) and M1 (90% slag + 5% SMC + 5% ATP, planting K. paniculata) groups were assessed in a pilot-scale experiment to explore their different impacts on phytoremediation. The results indicated that adding the amendments significantly improved the pH of the manganese slag, enhancing and maintaining its fertility and water retention. Adding the amendments and planting K. paniculata (M1) significantly reduced the bioavailability and migration of heavy metals (HMs). The loss of Mn, Pb and Zn via runoff decreased by 15.7%, 8.4% and 10.2%, respectively, compared to CK. K. paniculata recruited and enriched beneficial fungi, inhibited pathogenic fungi, and a more stable fungal community was built. This significantly improved the soil quality, promoted plant growth and mitigated heavy metal toxicity. In conclusion, this study demonstrated that the addition of SMC-ATP and planting K. paniculata showed a good phytostabilization effect in the manganese slag and further revealed the response process of the fungal community in phytoremediation. Full article

Integrated photonic platforms have rapidly emerged as highly promising and extensively investigated systems for advancing classical and quantum information technologies, since their ability to seamlessly integrate photonic components within the telecommunication band with existing silicon-based industrial processes offers significant advantages. However, despite this integration facilitating the development of novel devices, fostering fast and reliable communication protocols and the manipulation of quantum information, traditional integrated silicon photonics faces inherent physical limitations that necessitate a challenging trade-off between device efficiency and spatial footprint. To address this issue, researchers are focusing on the integration of nanoscale materials into photonic platforms, offering a novel approach to enhance device performance while reducing spatial requirements. These developments are of paramount importance in both classical and quantum information technologies, potentially revolutionizing the industry. In this review, we explore the latest endeavors in hybrid photonic platforms leveraging the combination of integrated silicon photonic platforms and nanoscale materials, allowing for the unlocking of increased device efficiency and compact form factors. Finally, we provide insights into future developments and the evolving landscape of hybrid integrated photonic nanomaterial platforms. Full article