Even though algorithmic composition might be considered a centuries-old concept, it has been gaining particular momentum since the introduction of computer-based techniques. The development of artificial intelligence (AI) methods, culminating in the latest achievements of deep learning techniques, has provided tools to automatically compose and even produce music. This paper discusses various aspects of the entire process within a context of designing a system able to automatically generate a score and recordings belonging to selected musical genres. It begins with the idea and design overview, followed by considerations regarding the algorithmic formulation of selected musical rules and principles. The system implements a hybrid approach, combining conventional, i.e., stochastic or rule-based, and AI elements. The latter are applied to facilitate the generation of selected layers of composition and to constitute a classifier with a task of evaluating the generated recordings. Selected stages of music generation are discussed, for example how motifs are processed into phrases and how phrases are used in the context of a whole song. To validate the system operation results, an evaluation of the quality of the produced music recordings was conducted, including a test with a group of listeners. The analysis also touches upon some legal aspects related to the creation of algorithmic compositions. Full article

Obesity, indicated by Body Mass Index (BMI), is a risk factor for type 2 diabetes. However, its association with glycated hemoglobin (HbA1c), a crucial indicator of blood-sugar control, may vary across different populations and disease statuses. Data from the National Health and Nutrition Examination Survey (NHANES) 2017–2018 were analyzed. Participants aged 18–79 years with complete information on BMI, diabetes status, and HbA1c were included (n = 4003). Linear regression models were used to assess the association between BMI and HbA1c, adjusting for demographic confounders, smoking status, alcohol consumption, and healthcare access. Among participants without diabetes, BMI was positively associated with HbA1c levels (coefficient: 0.015, 95% CI: 0.01, 0.02; p-value < 0.05), after adjusting for potential confounders. However, this association was not significant among those with diabetes (coefficient: −0.005, 95% CI: −0.05, 0.04; p-value > 0.1). Our findings suggest a differential relationship between BMI and HbA1c in individuals with and without diabetes. While BMI remains a significant predictor of HbA1c in non-diabetic individuals, its significance diminishes in those with diabetes. Full article

Brain cancer is a life-threatening disease requiring close attention. Early and accurate diagnosis using non-invasive medical imaging is critical for successful treatment and patient survival. However, manual diagnosis by radiologist experts is time-consuming and has limitations in processing large datasets efficiently. Therefore, efficient systems capable of analyzing vast amounts of medical data for early tumor detection are urgently needed. Deep learning (DL) with deep convolutional neural networks (DCNNs) emerges as a promising tool for understanding diseases like brain cancer through medical imaging modalities, especially MRI, which provides detailed soft tissue contrast for visualizing tumors and organs. DL techniques have become more and more popular in current research on brain tumor detection. Unlike traditional machine learning methods requiring manual feature extraction, DL models are adept at handling complex data like MRIs and excel in classification tasks, making them well-suited for medical image analysis applications. This study presents a novel Dual DCNN model that can accurately classify cancerous and non-cancerous MRI samples. Our Dual DCNN model uses two well-performed DL models, i.e., inceptionV3 and denseNet121. Features are extracted from these models by appending a global max pooling layer. The extracted features are then utilized to train the model with the addition of five fully connected layers and finally accurately classify MRI samples as cancerous or non-cancerous. The fully connected layers are retrained to learn the extracted features for better accuracy. The technique achieves 99%, 99%, 98%, and 99% of accuracy, precision, recall, and f1-scores, respectively. Furthermore, this study compares the Dual DCNN’s performance against various well-known DL models, including DenseNet121, InceptionV3, ResNet architectures, EfficientNetB2, SqueezeNet, VGG16, AlexNet, and LeNet-5, with different learning rates. This study indicates that our proposed approach outperforms these established models in terms of performance. Full article

Contamination of groundwater with fluoride represents a significant global issue, with high concentrations posing serious public health threats. While fluoride is a critical element in water, excessive levels can be detrimental to human health and potentially life-threatening. Addressing the challenge of removing fluoride from underground water sources via nanotechnological approaches is a pressing concern in environmental science. To collate relevant information, extensive literature searches were conducted across multiple databases, including Google Scholar, PubMed, Scopus, Web of Science, the American Chemical Society, Elsevier, Springer, and the Royal Society of Chemistry. VOS Viewer software version 1.6.20 was employed for a systematic review. This article delivers an exhaustive evaluation of various groundwater fluoride removal techniques, such as adsorption, membrane filtration, electrocoagulation, photocatalysis, and ion exchange. Among these, the application of nanoparticles emerges as a notable method. The article delves into nano-compounds, optimizing conditions for the fluoride removal process and benchmarking their efficacy against other techniques. Studies demonstrate that advanced nanotechnologies—owing to their rapid reaction times and potent oxidation capabilities—can remove fluoride effectively. The implementation of nanotechnologies in fluoride removal not only enhances water quality but also contributes to the safeguarding of human health. Full article

Gardenia jasminoides Ellis is an evergreen shrub with white fragrant flowers, and it is cultivated for its ornamental, aromatic and medicinal value. The present study aimed to select desirable genotypes for potential commercial exploitation as pot plants or use in perfumery. Thus, 32 genotypes of G. jasminoides plants derived from seedlings, whose seeds were obtained from Australia and the USA, were evaluated for their genetic diversity in relation to four commercial cultivars (‘Pelion’, ‘Joy’, ‘Grandiflora’ and ‘Kimberly’, used as reference cultivars) using ISSR and SCoT markers. A cluster analysis separated the gardenia genotypes into the following three clusters: one cluster comprised the 16 genotypes originating from Australia, one included the 16 genotypes originating from the USA, and the third cluster contained the four reference cultivars. In other words, there was a clear demarcation of the genotypes investigated according to their geographical origin. In addition, the gardenia genotypes were evaluated for their morphological and chemical characteristics. Thus, flower- and leaf-related traits with ornamental value were measured, while the volatile compounds of flower extracts were identified with GC-MS analysis. Genotype 29-5 was selected for its acceptable morphological traits and genotype 51-8 for its rich volatile compounds. The major volatile compounds responsible for the floral aroma of the various gardenia genotypes examined were α-farnesene, benzyl tiglate, cis-3-hexenyltiglate, jasminelactone and linalool. Full article

The mechanical properties of a plug seedling substrate determine whether it will crush during the transplantation, thereby affecting the integrity of the root system and the survival rate of transplanted seedlings. In this study, we measured eight morphological parameters of pepper seedlings using machine vision and physical methods, and the corresponding substrate mechanical parameters of the plug seedlings were tested using a texture analyzer. Based on the experimental data, a BPNN framework was constructed to predict the substrate mechanical properties of plug seedlings at different growth stages. The results indicate that the BPNN with a framework of [8, 15, 15, 1] exhibits higher R² and lower errors. The mean absolute error (MAE), mean squared error (MSE), and mean absolute percentage error (MAPE) values are 7.669, 88.842, and 9.076%, respectively, with an R² of 0.867. The average prediction accuracy of 20 test data set is 90.472%. Finally, predictions and experimental validations were conducted on the substrate mechanical properties of seedlings grown for 47 days. The results revealed that the BPNN achieved an average prediction accuracy of 93.282%. Additionally, it exhibited faster speed and lower computational costs. This study provides a reference for the non-intrusive estimation of substrate mechanical properties in plug seedlings and the design and optimization of transplanting an end-effector. Full article

This study uses machine learning to investigate the effects of firm and CEO characteristics on stock price crash risk by collecting massive data on publicly listed firms in China. The results show that eXtreme Gradient Boosting (XGBoost) is the most effective model for predicting stock price crash risk, with relatively satisfactory performance. Meanwhile, the SHapley Additive exPlanations (SHAP) method is used to interpret the importance of features. The results show that the average weekly return of a firm over a year (RET) contributes the most and is negatively associated with crash risk, followed by Sigma, IPO age, and firm size. We also found that, among CEO characteristics, CEO pay contributes substantially to crash risk at the firm level. Our findings have important implications for research into the impact of firm and CEO characteristics on stock price crash risk and provide a novel way for investors to plan their investment decisions and risk-taking behavior rationally. Full article

Multimetric indices play a pivotal role in assessing river ecological quality, aligning with the European Water Framework Directive (EU WFD) requirements. However, indices developed specifically for large rivers are uncommon. Our objective was to develop a fish-based tool specifically tailored to assess the ecological quality in Portuguese large rivers. Data were collected from seven sites in each of three Portuguese large rivers (Minho, Guadiana, and Tagus). Each site was classified using an environmental disturbance score, combining different pressure types, such as water chemistry, land use, and hydromorphological alterations. The Fish-based Multimetric Index for Portuguese Large Rivers (F-MMIP-LR) comprises four metrics: % native lithophilic individuals; % alien individuals; % migrant individuals; and % freshwater native individuals, representing compositional, reproductive, and migratory guilds. The index showed good performance in separating least- and most-disturbed sites. Least-disturbed sites were rated ‘high’ or ‘good’ by F-MMIP-LR, contrasting with no such classification for most-disturbed sites, highlighting index robustness. The three rivers presented a wide range of F-MMIP-LR values across the gradient of ‘bad’ to ‘high’, indicating that, on a large spatial extent, the biological condition was substantially altered. The F-MMIP-LR provides vital information for managers and decision-makers, guiding restoration efforts and strengthening conservation initiatives in line with the WFD. Full article

The mesocotyl is of great significance in seedling emergence and in responding to biotic and abiotic stress in maize. The NAM, ATAF, and CUC2 (NAC) transcription factor family plays an important role in maize growth and development; however, its function in the elongation of the maize mesocotyl is still unclear. In this study, we found that the mesocotyl length in zmnac17 loss-of-function mutants was lower than that in the B73 wild type. By using transcriptomic sequencing technology, we identified 444 differentially expressed genes (DEGs) between zmnac17-1 and B73, which were mainly enriched in the “tryptophan metabolism” and “antioxidant activity” pathways. Compared with the control, the zmnac17-1 mutants exhibited a decrease in the content of indole acetic acid (IAA) and an increase in the content of reactive oxygen species (ROS). Our results provide preliminary evidence that ZmNAC17 regulates the elongation of the maize mesocotyl. Full article

The Applications of silica aerogel are limited due to its brittleness and low strength. As a result, it is essential to strengthen and toughen it. Organic nanofibers are one of the preferred reinforcement materials. In this work, we designed and fabricated flexible and compressible nanostructure-assembled aramid nanofiber/silica composites aerogel (ANF/SiO₂ aerogel) to improve the mechanical strength and flexibility of silica aerogel without compromising thermal insulation properties. The aramid nanofiber/silica composite aerogels were prepared by immersing the aramid nanofiber wet gel into the silica sol for a certain period of time followed by freeze drying without solvent replacement. The surface modifier 3-aminopropyltriethoxysilane (APTES) was used as a coupling agent to form chemical linkage between the ANF fiber and silica gel. It was observed that APTES can effectively drive the silica sol to infuse into ANF hydrogel, promoting the assembly of silica gel onto the fiber surface and a uniform distribution in the network of ANF. The compressive resilience, thermal stability, and thermal insulation properties of the composite aerogels were evaluated by inducing the silica aerogel into the ANF network to form a protective layer on the fiber and change the pore structure in the ANF network. Full article

5-azacytidine (AZA), a representative DNA-demethylating drug, has been widely used to treat myelodysplastic syndromes (MDS). However, it remains unclear whether AZA’s DNA demethylation of any specific gene is correlated with clinical responses to AZA. In this study, we investigated genes that could contribute to the development of evidence-based epigenetic therapeutics with AZA. A DNA microarray identified that AZA specifically upregulated the expression of 438 genes in AZA-sensitive MDS-L cells but not in AZA-resistant counterpart MDS-L/CDA cells. Of these 438 genes, the ALOX12 gene was hypermethylated in MDS-L cells but not in MDS-L/CDA cells. In addition, we further found that (1) the ALOX12 gene was hypermethylated in patients with MDS compared to healthy controls; (2) MDS classes with excess blasts showed a relatively lower expression of ALOX12 than other classes; (3) a lower expression of ALOX12 correlated with higher bone marrow blasts and a shorter survival in patients with MDS; and (4) an increased ALOX12 expression after AZA treatment was associated with a favorable response to AZA treatment. Taking these factors together, an enhanced expression of the ALOX12 gene may predict favorable therapeutic responses to AZA therapy in MDS. Full article

Sepsis and acute kidney injury (AKI) are two major public health concerns that contribute significantly to illness and death worldwide. Early diagnosis and prompt treatment are essential for achieving the best possible outcomes. To date, there are no specific clinical, imaging, or biochemical indicators available to diagnose sepsis, and diagnosis of AKI based on the KDIGO criterion has limitations. To improve the diagnostic process for sepsis and AKI, it is essential to continually evolve our understanding of these conditions. Delays in diagnosis and appropriate treatment can have serious consequences. Sepsis and AKI often occur together, and patients with kidney dysfunction are more prone to developing sepsis. Therefore, identifying potential biomarkers for both conditions is crucial. In this review, we talk about the main biomarkers that evolve the diagnostic of sepsis and AKI, namely neutrophil gelatinase-associated lipocalin (NGAL), proenkephalin (PENK), and cell-free DNA. Full article

Aim and Objectives: We aimed to test the predictive value of readily accessible and easily performed post-surgical “bedside tests” on their validity of long-term urinary incontinence (UI) (≥12 months) in patients following robot-assisted laparoscopic radical prostatectomy (RALP). Material and Methods: Patients undergoing RALP between July 2020 and March 2021 were prospectively included and subdivided into two groups based on their pad usage after 12 months (0 vs. ≥1 pad). After catheter removal, patients performed a 1 h pad test, documented the need for pad change in a micturition protocol and received post-voiding residual urine volume ultrasound. Univariate and multivariable analyses were used to demonstrate the predictive value of easily accessible tests applied after catheter removal for UI following RALP. Results: Of 109 patients, 47 (43%) had to use at least one pad (vs. 62 (57%) zero pads) after 12 months. Univariate testing showed a significant difference in urine loss between both groups evaluated by the 1 h pad test performed within 24 h after catheter removal (70% < 10 mL, vs. 30% ≥ 10 mL, p = 0.004) and in the need for pad change within the first 24 h after catheter removal (14% dry pads vs. 86% wet pads, p = 0.003). In multivariable analyses, the combination of both tests (synoptical incontinence score) could be confirmed as an independent predictor for UI after 12 months (p = 0.011). Conclusions: Readily accessible “everyday” diagnostics (pad test/change of pads after catheter removal) following RALP seem to be associated with a higher rate of long-term UI. This finding is crucial since patients with a potentially higher need for patient education and counselling can be identified using these readily accessible tests. This could lead to a higher patient satisfaction and improved outcomes. Full article

This study investigated the effect of intraocular pressure (IOP) reduction on pulsatile displacement within the optic nerve head (ONH) in primary open-angle glaucoma (POAG) patients with and without axial myopia. Forty-one POAG patients (19 without myopia, 9 with axial myopia and 13 glaucoma with no intervention) participated. Swept-source optical coherence tomography (OCT) videos of the ONH were obtained before and after IOP-lowering treatment (medical or surgical) achieving a minimum IOP drop of 3 mmHg. A demons registration-based algorithm measured local pulsatile displacement maps within the ONH. Results demonstrated a significant 14% decrease in pulsatile tissue displacement in the non-myopic glaucoma cohort after intervention (p = 0.03). However, glaucoma patients with axial myopia exhibited no statistically significant change. There were no significant changes in the pulsatile ONH deformation in the control group. These findings suggest a potential link between IOP reduction and reduced pulsatile displacement within the ONH in POAG patients without myopia, offering new insights into the disease’s pathophysiology and warranting further investigation into underlying mechanisms and clinical implications. Full article

Kelp forests in Korean waters, mainly consisting of Ecklonia cava, provide ecologically and economically important ecosystems. However, they are severely threatened by increasing sea surface temperature (SST). In 2023, an unusually high SST was observed in the northern East China Sea, where the average SST from August to November 2023 was found to be 1.1 °C higher than the average SST during the same period over the last two decades. Our photo images and videos reveal increasing feeding on E. cava populations by tropical herbivore rabbitfish (Siganus canaliculatus, Siganus fuscescens) associated with the impact of increasing SST. Given the fall reproductive peak of E. cava population, increased herbivory by tropical rabbitfish could have a significant adverse impact on the composition of temperate kelp forests. Full article

We investigated the impacts of the COVID-19 pandemic on hepatitis C (HCV) treatment initiation, including by birth cohort and injection drug use status, in British Columbia (BC), Canada. Using population data from the BC COVID-19 Cohort, we conducted interrupted time series analyses, estimating changes in HCV treatment initiation following the introduction of pandemic-related policies in March 2020. The study included a pre-policy period (April 2018 to March 2020) and three follow-up periods (April to December 2020, January to December 2021, and January to December 2022). The level of HCV treatment initiation decreased by 26% in April 2020 (rate ratio 0.74, 95% confidence interval [CI] 0.60 to 0.91). Overall, no statistically significant difference in HCV treatment initiation occurred over the 2020 and 2021 post-policy periods, and an increase of 34.4% (95% CI 0.6 to 75.8) occurred in 2022 (equating to 321 additional people initiating treatment), relative to expectation. Decreases in HCV treatment initiation occurred in 2020 for people born between 1965 and 1974 (25.5%) and people who inject drugs (24.5%), relative to expectation. In summary, the pandemic was associated with short-term disruptions in HCV treatment initiation in BC, which were greater for people born 1965 to 1974 and people who inject drugs. Full article

The materials traditionally used for implant applications, such as titanium alloys, cobalt chromium, and zirconium, often require surface modifications to achieve the desired osseointegration. These materials still have the problematic stress-shielding effect. To limit stress shielding, PEEK is the superior alternative to fulfill implant needs. However, the traditional methods of modifying and functionalizing the surface of PEEK are often expensive, time consuming, and are not easily translated into commercialization. Sulfonation is a process, which is dependent on controllable factors. Thus far, no research has been performed to optimize the sulfonation process. Our data suggest that the process factors can be controlled and optimized. Cellular activity was examined on the optimized PEEK surfaces through testing with pre-osteoblast MC3T3-E1 cells through cell viability (MTT assay), cell proliferation (DNA assay), cell differentiation (ALP assay), and cell mineralization (Alizarin red assay). Overall, sulfonated and heat-treated PEEK exhibited a statistically significant increase in DNA content over the course of 21 days, indicating more cell proliferation and viability for that surface. In vitro testing results showed that the optimized sulfonated and heat-treated PEEK exhibited superior cell proliferation and mineralization performance over smooth PEEK and sulfonated-only PEEK. Full article

The application of sanitary sewage using subsurface drip irrigation can mitigate current challenges related to water availability and food production. However, before implementing these techniques, it is crucial to conduct studies to assess their impacts on soil and plants. The objective of this study was to evaluate chemical changes in the soil and the development of cowpeas subjected to sanitary sewage applied by drippers with different flow rates and installation depths. Drippers were positioned at various depths (0 to 30 cm) and operated with flow rates of 1.6 and 3.8 L h⁻¹. Cowpeas were cultivated in pots with clayey soil, using synthetic sanitary sewage based on the maximum limit of nitrogen fertilization. Irrigation management was controlled in terms of soil moisture, which was monitored using TDR probes. The results indicated that reducing the depth of the drippers positively affected grain production and the development of cowpeas. Fertigation with sanitary sewage at greater depths increased soil phosphorus concentrations and base saturation. Dripper depth also influenced soil concentrations of phosphorus, potassium, calcium, and magnesium, while sodium concentrations decreased with greater depth. It is concluded that dripper flow rates did not impact soil chemical parameters or the agronomic characteristics of cowpeas. However, despite nutrient supply at greater depths, the subsurface drip irrigation system proved unsuitable for cowpea production in clayey soil. Full article

Cellulose/silica nanocomposites, synthesised through the sol–gel technique, have garnered significant attention for their unique properties and diverse applications. The distinctive characteristics of these nanocomposites are influenced by a range of factors, including the cellulose-to-silica ratio, precursor concentration, pH, catalysts, solvent selection, temperature, processing techniques, and agitation. These variables play a pivotal role in determining the nanocomposites’ structure, morphology, and mechanical properties, facilitating tailoring for specific applications. Studies by Raabe et al. and Barud et al. demonstrated well-deposited silica nanoparticles within the interstitial spaces of cellulosic fibres, achieved through TEOS precursor hydrolysis and the subsequent condensation of hydroxyl groups on the cellulose fibre surface. The introduction of TEOS established a robust affinity between the inorganic filler and the polymer matrix, emphasising the substantial impact of TEOS concentration on the size and morphology of silica nanoparticles in the final composites. The successful functionalisation of cellulose fibres with the TEOS precursor via the sol–gel method was reported, resulting in reduced water uptake and enhanced mechanical strength due to the strong chemical interaction between silica and cellulose. In research conducted by Feng et al., the silica/cellulose composite exhibited reduced weight loss compared to the pristine cellulose matrix, with the integration of silica leading to an elevated temperature of composite degradation. Additionally, Ahmad et al. investigated the effects of silica addition to cellulose acetate (CA) and polyethylene glycol membranes, noting an increase in Young’s modulus, tensile strength, and elongation at break with silica incorporation. However, concentrations exceeding 4% (w/v) resulted in significant phase separations, leading to a decline in mechanical properties. Full article

Some of the earliest known engravings are described, analyzed, and interpreted, following their microscopic examination. They are of significance in exploring the cognitive evolution of hominins several hundred thousand years ago and have not been described together before. The Steinrinne site near Bilzingsleben, north of Weimar, Germany, is one of Europe’s most important Lower Paleolithic occupation sites. Its extensive human habitation floor, excavated over 1000 square meters, comprises some of the world’s oldest evidence of dwellings, broadly matching or exceeding the age of examples proposed in Africa, India, and France. It has yielded numerous hominin remains, many wooden artefacts, other exquisitely preserved organic remains, and more portable engravings than any other Middle Pleistocene site. The latter are reviewed here, presenting the results of a detailed microscopic examination of the main finds. Bilzingsleben has so far produced the largest number of engraved Lower Paleolithic objects reported, which are particularly important to exploring the cognitive developments of hominins. Full article

The apothecial fungus Ramomarthamyces octomerus sp. nov. is described from specimens collected in Mediterranean climate regions in southern Portugal, Spain (Canary Islands), and the Dalmatian region of Croatia. Presumably saprobic, R. octomerus occurs on intact, decorticated wood of Laurus novocanariensis and Olea europaea. Ascospores are cylindric-ellipsoid and seven-septate. Surprisingly, in our four-locus phylogenetic analysis (nuSSU, ITS1-5.8S-ITS2, LSU, mtSSU), this fungus clusters among species of Cyclaneusma, Marthamyces, Naemacyclus, and Ramomarthamyces in a core Marthamycetaceae clade that circumscribes primarily leaf-inhabiting, filiform-spored species. In addition, the asci of R. octomerus possess an amyloid pore, but the reaction varies between specimens collected in the Canary Islands and those collected in Portugal and Croatia. The occurrence of an amyloid reaction in the asci of R. octomerus challenges the characterization of Marthamycetales taxa as possessing inamyloid asci. In our discussion we provide background and analysis of these notable observations. Full article

As little evidence is available, we report the oral health of neurogeriatric inpatients and the association with hematological parameters representing systemic health. We performed a cross-sectional investigation of 30 patients undergoing neurogeriatric early rehabilitation and excluded systemic inflammation as a trigger for oral infection (C-reactive protein >5 mg/dL). Outcomes included oral health and hygiene status and routine laboratory parameters. Patients (mean age 79 ± 6 years, mean comorbidities 7 ± 3, and mean Barthel Index at hospital admission 31 ± 18) had impaired oral health (mean 18 ± 7 of their own teeth, elevated plaque indices (2.5 ± 0.4), and bleeding on probing (26 ± 17)), representing short- and long-term reduced oral hygiene. Twenty-four (80%) patients had periodontitis. Laboratory parameters for inflammation, nutrition, and anemia did not correlate with oral health parameters (p > 0.05). The number of teeth correlated moderately with total protein (Spearman’s rank correlation coefficient (r_s) = 0.524; p = 0.003). Plaque indices correlated weakly with number of teeth (r_s = −0.460; p = 0.010) and periodontitis diagnosis (r_s = 0.488; p = 0.006). Thus, highly vulnerable neurogeriatric inpatients had reduced oral health and hygiene independent of laboratory parameters, representing a high-risk population for oral health problems even without clinically proven systemic infection. This should be considered in future interprofessional therapy planning. Full article