Electrochemical fluorination on nickel anodes, also known as the Simons’ process, is an important fluorination method used on an industrial scale. Despite its success, the mechanism is still under debate. One of the proposed mechanisms involves higher valent nickel species formed on an anode acting as effective fluorinating agents. Here we report the first attempt to study fluorination by means of first principles investigation. We have identified a possible surface model from the simplest binary nickel fluoride (NiF2). A twice oxidized NiF2(F2) (001) surface exhibits higher valent nickel centers and a fluorination source that can be best characterized as an [F2]^- like unit, readily available to aid fluorination. We have studied the adsorption of CH4 and the co-adsorption of CH4 and HF on this surface by means of periodic density functional theory. By the adsorption of CH4, we found two main outcomes on the surface. Unreactive physisorption of CH4 and dissociative chemisorption resulting in the formation of CH3F and HF. The co-adsorption with the HF gave rise to four main outcomes, namely the formation of CH3F, CH2F2, CH3 radical, and also physisorbed CH4. Full article

The assessment of leg asymmetries is gaining scientific interest due to its potential impact on performance and injury development. Athletes around puberty exhibit increased gait variability due to a non-established running pattern. This study aims to describe the asymmetries in the spatiotemporal running parameters in developmentally aged athletes. Forty athletes under 14 (U14) (22 females and 18 males) were assessed running on a treadmill at constant speeds of 12 and 14 km·h⁻¹ for 3 min. Step length, step frequency, along with contact (CT) and flight time, both in absolute values and as a percentage of step time, were recorded using a RunScribe sensor attached to the laces of each shoe. U14 runners exhibited high bilateral symmetry in the spatiotemporal parameters of running, with mean asymmetry values (1–5.7%) lower than the intra-limb coefficient of variation (1.7–9.6%). Furthermore, bilateral asymmetries did not vary between the two speeds. An individual-based interpretation of asymmetries identified subjects with consistent asymmetries at both speeds, particularly in terms of CT and contact ratio (%, CT/step time). This study confirms the high symmetry of pubertal runners and paves the way for the application of portable running assessment technology to detect asymmetries on an individual basis. Full article

Stock market manipulation, defined as any attempt to artificially influence stock prices, poses significant challenges by causing financial losses and eroding investor trust. The prevalent reliance on supervised learning models for detecting such manipulations, while showing promise, faces notable hurdles due to the dearth of labeled data and the inability to recognize novel manipulation tactics beyond those explicitly labeled. This study ventures into addressing these gaps by proposing a novel detection framework aimed at identifying suspicious hourly manipulation blocks through an unsupervised learning approach, thereby circumventing the limitations of data labeling and enhancing the adaptability to emerging manipulation strategies.Our methodology involves the innovative creation of features reflecting the behavior of stocks across various time windows followed by the segmentation of the dataset into k subsets. This setup facilitates the identification of potential manipulation instances via a voting ensemble composed of k isolation forest models, which have been chosen for their efficiency in pinpointing anomalies and their linear computational complexity—attributes that are critical for analyzing vast datasets.Evaluated against eight real stocks known to have undergone manipulation, our approach demonstrated a remarkable capability to identify up to 89% of manipulated blocks, thus significantly outperforming previous methods that do not utilize a voting ensemble. This finding not only surpasses the detection rates reported in prior studies but also underscores the enhanced robustness and adaptability of our unsupervised model in uncovering varied manipulation schemes. Through this research, we contribute to the field by offering a scalable and efficient unsupervised learning strategy for stock manipulation detection, thereby marking a substantial advancement over traditional supervised methods and paving the way for more resilient financial markets. Full article

In recent years, the artificial potential field has garnered significant attention in ship route planning and traffic flow simulation. However, the traditional artificial potential field method faces challenges in accurately simulating a ship’s customary route and navigating experience, leading to significant deviations in prediction results. To address these issues, in this study, we propose an innovative method for simulating and predicting ship traffic flow, building upon the artificial potential field approach. We introduce an AIS track heat map based on the kernel density function and enhance the artificial potential field model by incorporating factors, such as ship navigation habits and ship size. Through a comparison of traffic flow changes before and after the construction of a wind farm, the optimized model demonstrates its effectiveness in improving the accuracy of prediction results. Full article

The conventional synthesis of the Metal–Organic Framework (MOF) MIL-101(Cr)-SO₃H employs hydrofluoric acid as the modulator, posing handling challenges due to its irritating, corrosive, and toxic nature, as well as its reactivity with glass and metals. This study aims to find a new hydrofluoric acid-free synthesis route for MIL-101(Cr)-SO₃H, proposing acetic acid and nitric acid as modulator alternatives. Four MIL‑101(Cr)‑SO₃H samples were prepared: one without any modulator and the other three using a similar volume of either hydrofluoric acid, acetic acid, or nitric acid as the modulator. The so-obtained mass yield ranked as follows: without any modulator (32.6%) > acetic acid (29.6%) > nitric acid (25.2%) >> hydrofluoric acid (2.2%), whereas the total pore volume and BET surface area followed the order: hydrofluoric acid (0.87 cm³ g⁻¹, 1862 m² g⁻¹) > nitric acid (0.81 cm³ g⁻¹, 1554 m² g^‑1) > acetic acid (0.72 cm³ g⁻¹, 1374 m² g⁻¹) > without any modulator (0.69 cm³ g⁻¹, 1342 m² g⁻¹). Despite the superior texture parameters obtained using hydrofluoric acid, the low synthesis yield and associated risks make this route non-viable. Acetic or nitric acid-based synthesis offers a promising alternative with a drastically higher yield, safer handling, and reduced environmental impact. In an attempt to improve the textural properties of the hydrofluoric acid-free MOFs, a series of samples were produced with increasing amounts of acetic acid, achieving BET surface areas of up to 1504 m² g⁻¹ and pore volumes of up to 0.81 cm³ g⁻¹. Full article

Oxidative stress forms part of the molecular basis contributing to the development and manifestation of myopia, a refractive error with associated pathology that is increasingly prevalent worldwide and that subsequently leads to an upsurge in degenerative visual impairment due to conditions that are especially associated with high myopia. The purpose of our study was to examine the interrelation of potential oxidative-stress-related metabolites found in the aqueous humor of high-myopic, low-myopic, and non-myopic patients within a clinical study. We conducted a cross-sectional study, selecting two sets of patients undergoing cataract surgery. The first set, which was used to analyze metabolites through an NMR assay, comprised 116 patients. A total of 59 metabolites were assigned and quantified. The PLS-DA score plot clearly showed a separation with minimal overlap between the HM and control samples. The PLS-DA model allowed us to determine 31 major metabolite differences in the aqueous humor of the study groups. Complementary statistical analysis of the data allowed us to determine six metabolites that presented significant differences among the experimental groups (p < 005). A significant number of these metabolites were discovered to have a direct or indirect connection to oxidative stress linked with conditions of myopic eyes. Notably, we identified metabolites associated with bioenergetic pathways and metabolites that have undergone methylation, along with choline and its derivatives. The second set consisted of 73 patients who underwent a glutathione assay. Here, we showed significant variations in both reduced and oxidized glutathione in aqueous humor among all patient groups (p < 0.01) for the first time. Axial length, refractive status, and complete ophthalmologic examination were also recorded, and interrelations among metabolic and clinical parameters were evaluated. Full article

In this study, hydrothermal co-liquefaction of restaurant waste for biocrude production was conducted. The feedstock was resembled using the organic fraction of restaurant waste and low-density polyethylene, polypropylene, polystyrene, and polyethylene terephthalate, four plastic types commonly present in municipal solid waste. Using design of experiment and a face-centered central composite design, three factors (feedstock plastic fraction, temperature, time) were varied at three levels each: feedstock plastic fraction (0, 0.25, 0.5), temperature (290 °C, 330 °C, 370 °C), and reaction time (0 min, 30 min, 60 min). The literature reports positive synergistic interactions in hydrothermal co-liquefaction of biomass and plastics; however, in this work, only negative synergistic interactions could be observed. A reason could be the high thermal stability of produced fatty acids that give little room for interactions with plastics. At the same time, mass might transfer to other product phases. Full article

The task of tree species classification through deep learning has been challenging for the forestry community, and the lack of standardized datasets has hindered further progress. Our work presents a solution in the form of a large bark image dataset called CentralBark, which enhances the deep learning-based tree species classification. Additionally, we have laid out an efficient and repeatable data collection protocol to assist future works in an organized manner. The dataset contains images of 25 central hardwood and Appalachian region tree species, with over 19,000 images of varying diameters, light, and moisture conditions. We tested 25 species: elm, oak, American basswood, American beech, American elm, American sycamore, bitternut hickory, black cherry, black locust, black oak, black walnut, eastern cottonwood, hackberry, honey locust, northern red oak, Ohio buckeye, Osage-orange, pignut hickory, sassafras, shagbark hickory silver maple, slippery elm, sugar maple, sweetgum, white ash, white oak, and yellow poplar. Our experiment involved testing three different models to assess the feasibility of species classification using unaltered and uncropped images during the species-classification training process. We achieved an overall accuracy of 83.21% using the EfficientNet-b3 model, which was the best of the three models (EfficientNet-b3, ResNet-50, and MobileNet-V3-small), and an average accuracy of 80.23%. Full article

Recent technological advances, including capsule endoscopy (CE) and balloon-assisted endoscopy (BAE), have revealed that small intestinal disease is more common than previously thought. CE has advantages, including a high diagnostic yield, discomfort-free, outpatient basis, and physiological images. BAE enabled endoscopic diagnosis and treatment in the deep small bowel. Computed tomography (CT) enterography with negative oral contrast can evaluate masses, wall thickening, and narrowing of the small intestine. In addition, enhanced CT can detect abnormalities outside the gastrointestinal tract that endoscopy cannot evaluate. Each modality has its advantages and disadvantages, and a good combination of multiple modalities leads to an accurate diagnosis. As a first-line modality, three-phase enhanced CT is preferred. If CT shows a mass, stenosis, or wall thickening, a BAE should be selected. If there are no abnormal findings on CT and no obstructive symptoms, CE should be selected. If there are significant findings in the CE, determine the indication for BAE and its insertion route based on these findings. Early diagnosis of small intestinal tumors is essential for favorable outcomes. For early diagnosis, the possibility of small bowel lesions should be considered in patients with unexplained symptoms and signs after examination of the upper and lower gastrointestinal tract. Full article

Stress is an important risk factor for the onset of anxiety and depression. The ability to cope with stressful events varies among different subjects, probably depending on different genetic variants, sex and previous life experiences. The Val66Met variant of Brain-Derived Neurotrophic Factor (BDNF), which impairs the activity-dependent secretion of BDNF, has been associated with increased susceptibility to the development of various neuropsychiatric disorders. Adult male and female wild-type Val/Val (BDNF^V/V) and heterozygous Val/Met (BDNF^V/M) mice were exposed to two sessions of forced swimming stress (FSS) per day for two consecutive days. The mice were behaviorally tested 1 day (short-term effect) or 11 days (long-term effect) after the last stress session. Protein and mRNA levels were measured in the hippocampus 16 days after the end of stress exposure. Stressed mice showed a higher anxiety-like phenotype compared to non-stressed mice, regardless of the sex and genotype, when analyzed following the short period of stress. In the prolonged period, anxiety-like behavior persisted only in male BDNF^V/M mice (p < 0.0001). Interestingly, recovery in male BDNF^V/V mice was accompanied by an increase in pCREB (p < 0.001) and Bdnf4 (p < 0.01) transcript and a decrease in HDAC1 (p < 0.05) and Dnmt3a (p = 0.01) in the hippocampus. Overall, our results show that male and female BDNF Val66Met knock-in mice can recover from subchronic stress in different ways. Full article

The conversion of lignocellulosic agricultural waste into biofuels and other economically valuable compounds can reduce dependence on fossil fuels, reduce harmful gas emissions, support the sustainability of natural resources, including water, and minimize the amount of waste in landfills, thus reducing environmental degradation. In this paper, the conversion of agricultural wastes into biomethane, biohydrogen, biodiesel, bioethanol, biobutanol, and bio-oil is reviewed, with special emphasis on primary and secondary agricultural residues as substrates. Some novel approaches are mentioned that offer opportunities to increase the efficiency of waste valorization, e.g., hybrid systems. In addition to physical, chemical, and biological pretreatment of waste, some combined methods to mitigate the negative effects of various recalcitrant compounds on waste processing (alkali-assisted thermal pretreatment, thermal hydrolysis pretreatment, and alkali pretreatment combined with bioaugmentation) are evaluated. In addition, the production of volatile fatty acids, polyhydroxyalkanoates, biochar, hydrochar, cellulosic nanomaterials, and selected platform chemicals from lignocellulosic waste is described. Finally, the potential uses of biofuels and other recovered products are discussed. Full article

Food allergy (FA) has become a common global public health issue, with a growing prevalence in the modern world and a significant impact on the lives of patients, their families, and caregivers. It affects every area of life and is associated with elevated costs. Food allergy is an adverse immune reaction that occurs in response to a given food. The symptoms vary from mild to severe and can lead to anaphylaxis. This is why it is important to focus on the factors influencing the occurrence of food allergies, specific diagnostic methods, effective therapies, and especially prevention. Recently, many guidelines have emphasized the impact of introducing specific foods into a child’s diet at an early age in order to prevent food allergies. Childhood allergies vary with age. In infants, the most common allergy is to cow’s milk. Later in life, peanut allergy is more frequently diagnosed. Numerous common childhood allergies can be outgrown by adulthood. Adults can also develop new IgE-mediated FA. The gold standard for diagnosis is the oral provocation test. Skin prick tests, specific IgE measurements, and component-resolved diagnostic techniques are helpful in the diagnosis. Multiple different approaches are being tried as possible treatments, such as immunotherapy or monoclonal antibodies. This article focuses on the prevention and quality of life of allergic patients. This article aims to systematize the latest knowledge and highlight the differences between food allergies in pediatric and adult populations. Full article

Background/Objectives: this systematic review aims to explore the efficacy and safety of the laparoscopic ligation of the inferior mesenteric artery (IMA) as an emerging trend for addressing a type II endoleak following endovascular aortic aneurysm repair (EVAR). Methods: A comprehensive literature search was conducted across several databases including Medline, Scopus, and the Cochrane Central Register of Controlled Trials, adhering to the PRISMA guidelines. The search focused on articles reporting on the laparoscopic ligation of the IMA for the treatment of a type II endoleak post-EVAR. Data were extracted regarding study characteristics, patient demographics, technical success rates, postoperative outcomes, and follow-up results. Results: Our analysis included ten case studies and two retrospective cohort studies, comprising a total of 26 patients who underwent a laparoscopic ligation of the IMA between 2000 and 2023. The mean age of the cohort was 72.3 years, with a male predominance (92.3%). The mean AAA diameter at the time of intervention was 69.7 mm. The technique demonstrated a high technical success rate of 92.3%, with a mean procedure time of 118.4 min and minimal blood loss. The average follow-up duration was 19.9 months, with 73% of patients experiencing regression of the aneurysmal sac, and no reports of an IMA-related type II endoleak during the follow-up period. Conclusions: The laparoscopic ligation of the IMA for a type II endoleak following EVAR presents a promising, minimally invasive alternative with high technical success rates and favorable postoperative outcomes. Despite its potential advantages, including reduced contrast agent use and radiation exposure, its application remains limited to specialized centers. The findings suggest the need for further research in larger prospective studies to validate the effectiveness of this procedure and potentially broaden its clinical adoption. Full article

This paper presents the methodology of measuring chip temperature in the cutting zone in the rough milling of magnesium alloys. Infrared measurements are taken to determine the effect of variable cutting speed, feed per tooth, and depth of cut on the maximum temperature of chips. Thermal images of chip temperature for a generated collective frame and corresponding histograms are presented. Chip temperatures are presented in numerical terms as median and average values; maximum and minimum values; range; and standard deviation. Box plots are also shown for selected machining conditions. The problems arising during signal recording with a mean emissivity coefficient ε = 0.13, a value which is dedicated during machining magnesium alloys, are discussed in detail. Chip temperatures obtained in the tests do not exceed approx. 420 °C. Therefore, the dry rough milling process carried out with carbide tools with different blade geometries can be considered safe for a wide range of machining parameters. The proposed methodology of chip temperature measurement and result processing is a new and effective approach to safety assessment in the dry milling of magnesium alloys. Full article

The role of rice genomics in breeding progress is becoming increasingly important. Deeper research into the rice genome will contribute to the identification and utilization of outstanding functional genes, enriching the diversity and genetic basis of breeding materials and meeting the diverse demands for various improvements. Here, we review the significant contributions of rice genomics research to breeding progress over the last 25 years, discussing the profound impact of genomics on rice-genome sequencing, functional-gene exploration, and novel breeding methods, and we provide valuable insights for future research and breeding practices. Full article

In this paper, we present a novel approach referred to as the audio-based virtual landmark-based HoloSLAM. This innovative method leverages a single sound source and microphone arrays to estimate the voice-printed speaker’s direction. The system allows an autonomous robot equipped with a single microphone array to navigate within indoor environments, interact with specific sound sources, and simultaneously determine its own location while mapping the environment. The proposed method does not require multiple audio sources in the environment nor sensor fusion to extract pertinent information and make accurate sound source estimations. Furthermore, the approach incorporates Robotic Mixed Reality using Microsoft HoloLens to superimpose landmarks, effectively mitigating the audio landmark-related issues of conventional audio-based landmark SLAM, particularly in situations where audio landmarks cannot be discerned, are limited in number, or are completely missing. The paper also evaluates an active speaker detection method, demonstrating its ability to achieve high accuracy in scenarios where audio data are the sole input. Real-time experiments validate the effectiveness of this method, emphasizing its precision and comprehensive mapping capabilities. The results of these experiments showcase the accuracy and efficiency of the proposed system, surpassing the constraints associated with traditional audio-based SLAM techniques, ultimately leading to a more detailed and precise mapping of the robot’s surroundings. Full article

High-pressure pipelines are critical for transporting hazardous materials over long distances, but they face threats from third-party interference activities. Preventive measures are implemented, but interference accidents can still occur, making the need for high-quality detection strategies vital. This paper proposes an end-to-end Artificial Intelligence of Things (AIoT) solution to detect potential interference threats in real time. The solution involves developing a smart visual sensor capable of processing images using state-of-the-art computer vision algorithms and transmitting alerts to pipeline operators in real time. The system’s core is based on the object-detection model (e.g., You Only Look Once version 4 (YOLOv4) and DETR with Improved deNoising anchOr boxes (DINO)), trained on a custom Pipeline Visual Threat Assessment (Pipe-VisTA) dataset. Among the trained models, DINO was able to achieve the best Mean Average Precision (mAP) of 71.2% for the unseen test dataset. However, for the deployment on a limited computational-ability edge computer (i.e., the NVIDIA Jetson Nano), the simpler and TensorRT-optimized YOLOv4 model was used, which achieved a mAP of 61.8% for the test dataset. The developed AIoT device captures the image using a camera, processes on the edge using the trained YOLOv4 model to detect the potential threat, transmits the threat alert to a Fleet Portal via LoRaWAN, and hosts the alert on a dashboard via a satellite network. The device has been fully tested in the field to ensure its functionality prior to deployment for the SEA Gas use-case. The AIoT smart solution has been deployed across the 10km stretch of the SEA Gas pipeline across the Murray Bridge section. In total, 48 AIoT devices and three Fleet Portals are installed to ensure the line-of-sight communication between the devices and portals. Full article

Pressure ulcers carry a significant risk in clinical practice. This paper proposes a practical and interpretable approach to estimate the risk levels of pressure ulcers using decision tree models. In order to address the common problem of imbalanced learning in nursing classification datasets, various oversampling configurations are analyzed to improve the data quality prior to modeling. The decision trees built are based on three easily identifiable and clinically relevant pressure ulcer risk indicators: mobility, activity, and skin moisture. Additionally, this research introduces a novel tabular visualization method to enhance the usability of the decision trees in clinical practice. Thus, the primary aim of this approach is to provide nursing professionals with valuable insights for assessing the potential risk levels of pressure ulcers, which could support their decision-making and allow, for example, the application of suitable preventive measures tailored to each patient’s requirements. The interpretability of the models proposed and their performance, evaluated through stratified cross-validation, make them a helpful tool for nursing care in estimating the pressure ulcer risk level. Full article

The generation of co-speech gestures for digital humans is an emerging area in the field of virtual human creation. Prior research has progressed by using acoustic and semantic information as input and adopting a classification method to identify the person’s ID and emotion for driving co-speech gesture generation. However, this endeavor still faces significant challenges. These challenges go beyond the intricate interplay among co-speech gestures, speech acoustic, and semantics; they also encompass the complexities associated with personality, emotion, and other obscure but important factors. This paper introduces “DiT-Gestures”, a speech-conditional diffusion-based and non-autoregressive transformer-based generative model with the WavLM pre-trained model and a dynamic mask attention network (DMAN). It can produce individual and stylized full-body co-speech gestures by only using raw speech audio, eliminating the need for complex multimodal processing and manual annotation. Firstly, considering that speech audio contains acoustic and semantic features and conveys personality traits, emotions, and more subtle information related to accompanying gestures, we pioneer the adaptation of WavLM, a large-scale pre-trained model, to extract the style from raw audio information. Secondly, we replace the causal mask by introducing a learnable dynamic mask for better local modeling in the neighborhood of the target frames. Extensive subjective evaluation experiments are conducted on the Trinity, ZEGGS, and BEAT datasets to confirm WavLM’s and the model’s ability to synthesize natural co-speech gestures with various styles. Full article

In this paper, we address the challenge of ensuring stability in bipedal walking robots and exoskeletons. We explore the feasibility of real-time implementation for the Predicted Step Viability algorithm (PSV), a complex multi-step optimization criterion for planning future steps in bipedal gait. To overcome the high computational cost of the PSV algorithm, we performed an analysis using 11 classification algorithms and a stacking strategy to predict if a step will be stable or not. We generated three datasets of increasing complexity through PSV simulations to evaluate the classification performance. Among the classifiers, k Nearest Neighbors, Support Vector Machine with Radial Basis Function Kernel, Decision Tree, and Random Forest exhibited superior performance. Multi-Layer Perceptron also consistently performed well, while linear-based algorithms showed lower performance. Importantly, the use of stacking did not significantly improve performance. Our results suggest that the feature vector applied with this approach is applicable across various robotic models and datasets, provided that training data is balanced and sufficient points are used. Notably, by leveraging classifiers, we achieved rapid computation of results in less than 1 ms, with minimal computational cost. Full article

Coaxial magnetic gears have piqued the interest of researchers due to their numerous benefits over mechanical gears. These include reduced noise and vibration, enhanced efficiency, lower maintenance costs, and improved backdrivability. However, their adoption in industry has been limited by drawbacks like lower torque density and slippage at high torque levels. This work presents an analytical 2D model to compute the magnetic potential in Halbach array coaxial magnetic gears for every rotational angle, geometry configuration, and magnet specifications. This model calculates the induced torques and torque ripple in both rotors using the Maxwell Stress Tensor. The results were confirmed through Finite Element Analysis (FEA). Unlike FEA, this analytical model directly produces harmonics values, leading to faster computational times as it avoids torque calculations at each time step. In a case study, a standard coaxial magnetic gear was compared to one with a Halbach array, revealing a 14.3% improvement in torque density and a minor reduction in harmonics that cause torque ripple. Additionally, a case study was conducted to examine slippage in both standard and Halbach array gears during transient operations. The Halbach array coaxial magnetic gear demonstrated a 13.5% lower transmission error than its standard counterpart. Full article

The purpose of this work is to investigate the controllability of non-instantaneous impulsive (NII) Hilfer fractional (HF) neutral stochastic evolution equations with a non-dense domain. We construct a new set of adequate assumptions for the existence of mild solutions using fractional calculus, semigroup theory, stochastic analysis, and the fixed point theorem. Then, the discussion is driven by some suitable assumptions, including the Hille–Yosida condition without the compactness of the semigroup of the linear part. Finally, we provide examples to illustrate our main result. Full article