This study throws more light on the new Co-free and Ni-rich LiNi0.8Mn0.1Fe0.1O2 cathode material for lithium-ion batteries. This cobalt-free cathode material is prepared using a two-step process: the formation of an oxalate precursor by co-precipitation followed by a solid-state reaction with lithium hydroxide and iron citrate. The physico-chemical properties of LiNi0.8Mn0.1Fe0.1O2 are characterized using X-ray diffraction, Raman spectroscopy, scanning electron microscopy, thermal gravimetric analysis, and energy dispersive X-ray spectroscopy, respectively. The LiNi0.8Mn0.1Fe0.1O2 electrode tested at at C/2 rate within voltage window of 3.0-4.4 V vs. Li+/Li delivers a specific capacity of ~80 mAh g-1 and retain about 45% of its initial capacity after 100 cycles.

By using the method of high-temperature solid-phase reaction, the new piezoceramic SrBi2Nb2-2xWxSnxO9 was obtained, in which partial substitution of niobium (Nb) atoms with Sn4+ and W6+ atoms in the compound SrBi2Nb2O9 took place in the octahedra of the perovskite layer (B-position). X-ray diffraction studies have shown that these compounds are single-phase SrBi2Nb2-2xWxSnxO9 (x = 0.1, 0.2) and two-phase SrBi2Nb2-2xWxSnxO9 (x = 0.3, 0.4), but they all had the structure of Aurivillius – Smolensky phases (ASPs) with similar parameters of orthorhombic elementary cells, corresponding to the spatial group A21am. The dependences on temperature of the relative permittivity ε/ε0 and the tangent of the loss angle tan d at different frequencies were measured.

Organic fertilization is gaining importance as an alternative to chemical fertilization. However, the effects of organic products on crop quality need to be characterized, especially in those new products. Therefore, the effect of an enriched-biochar supplied with an organic fertilizer (Biochar) on yield and nutritional compounds of artichoke (Cynara cardunculus var scolymus) heads was analyzed and compared to inorganic conventional fertilization (Control). For that, number of fruits and their weights were determined together with nutritional properties of artichoke heads, as mineral content, fatty acids, content phenolic compounds and flavonoids. Results showed that biochar increased crop yield as registered by the higher number of marketable or commercial artichokes, as compared to the Control. Besides, biochar-treated plants presented significantly higher contents of Ca, Mg, and S, in the artichoke heads, but a decreased content of Co, Cu, and Zn. The fatty acids content in the Biochar-treated artichokes was also significantly higher, mainly because of the palmitic acid. On the contrary, the contents of phenolic compounds (e.g. flavonoids), were negatively and significantly affected by the Biochar application. In conclusion, the application of Biochar as soil amendment in combination with organic matter, for growing artichokes in the Semiarid Mediterranean area (e.g. Murcia Region) favoured an increasement in yield without comprising its nutritional composition. Further developments to establish protocols for extended use of Biochar in this agri-food production area are guaranteed.

This study investigates the structured spatial organization through a focus on streets, blocks and buildings, proposing them as fundamental components in conceptualizing cities as layered pal-impsests. Former Ottoman capital city, Bursa, serve as case study due to its rich evolutionary history and the potentiality of the urban heritage values/elements they demonstrate. Following the “Tanzimat” Era, a period marked by modernization and renewal, the urban fabric of Ottoman capital cities underwent significant reforms aimed at aligning them with the principles of mo-dernity. Maps dating back to the 19th century serve as the most illustrative sources for compre-hending the evolving character and layout of these cities. The foundational aspects of the charac-ter and appearance of the historic environment played crucial roles not only in shaping the mod-ern city but also in preserving and enhancing urban heritage areas by harmonizing them with contemporary urban conditions. Factors such as street age, street hierarchy, block typology, and the localization of historical landmarks are indispensable for grasping the developmental trajec-tory of these cities, offering insights that bridge spatial scales and span across historical eras. Employing a combination of qualitative and quantitative data, this research builds upon descrip-tive and analytical approaches to urban morphology. The methodology entails comprehensive morphological analysis, which involves assessing changes and persistence in the urban fabric of selected heritage site, both pre-existing and post-modernization, drawing from its historically scientific maps. The analysis focuses on abstracting key attributes such as type, configuration, size, and the relationship between the elements.

Research interest in the occurrence, distribution, fate, and toxicity of N-(1,3-Dimethylbutyl)-N’-phenyl-p-phenylenediamine (6PPD) quinone, a derivative of the tire amino antioxidant 6PPD in urban environments, has surged. While several studies have found that 6PPD quinone exhibits acute, reproductive, and behavioral toxicity as well as mutagenicity and hepatotoxicity in aquatic and terrestrial animals, its environmental exposure data are fragmented and lack coherence across the source-to-exposure continuum, making it difficult to use for risk assessment and regulatory purposes. The present work developed an aggregate exposure pathway (AEP) framework to integrate the exposure data. An AEP network was developed for the atmospheric deposition of 6PPD quinone from tire wear in the Pearl River Delta, which led to human exposure. The 6PPD quinone research was organized, visualized, and evaluated with pertinent knowledge gaps identified using the weight of evidence assessment. Eight key exposure states were identified, with only two having high confidence levels and three having low confidence levels. Empirical support for the key transitional relationships decreased from High to Low from the source to the target site, indicating an urgent need for downstream mechanistic data. The proposed AEP framework integrated diverse 6PPD quinone research, facilitating a mechanistic understanding of the source-to-outcome continuum, as well as the development of quantitative predictive models for future research and environmental regulation.

Recent studies in rural heritage tourism have highlighted that an evolutionary economic geography perspective could be helpful in determining whether cultural heritage tourism could stand as a branching-innovating trajectory. Its evolution can be understood by presenting specific mechanisms of layering, recombination and conversion that leads to path development. We contribute to rural heritage tourism by basing our study on perceptions of tourists and local officials on the Rudăria Watermills, Romania. Based on survey and interview data, we document the strengths and limits of local watermills for tourism and describe the entrepreneurial agents involved in path development. Our findings point to the important role played by a local NGO in developing a path for tourism for the watermills, as well as the active involvement of local authorities and other local cultural leaders for including the mills in national and international tourism circuits.

The extraction methods for carotenoids, xanthophylls and chlorophylls are essential processes involved in the recovery of bioactive compounds from a wide variety of natural sources, including plants, marine organisms, microorganisms and animals. These bioactive compounds, characterized by their significant functional and structurally active properties, play a crucial role in various industries, such as pharmaceuticals, nutraceuticals and food. Due to their presence in small quantities and conjugated form in nature, the extraction of these compounds can be laborious and often requires meticulous purification steps. Interestingly, the primary and secondary metabolites present in plants contribute significantly to the production of these bioactive compounds, adding to their complexity and importance. Notably, carotenoids, as natural pigments with antioxidant and nutritional properties, are known for offering numerous health benefits and are instrumental in various biological processes, including the photoprotection of plants and the prevention of chronic degenerative diseases. It is fascinating to observe that by-products generated from agricultural activities and food processing serve as abundant sources of these bioactive compounds, aligning with the principles of the circular economy and sustainable resource management. Given the diverse health benefits and multifaceted applications of these natural pigments, there is a growing interest in not only extracting but also utilizing them for industrial, nutritional and pharmacological purposes.

Tumor entities of the Central Nervous System (CNS) are defined by the WHO classification and range from benign neoplasms to highly malignant tumors, making histopathological classification challenging. This diverse spectrum complicates clinical decision-making and the interpretation and validation of clinical trial results. The methodology based on DNA methylation profiling of CNS tumors offers greater diagnostic precision compared to traditional morphological methods. In this study, we analyzed 16 DNA samples from medulloblastomas and ependymomas, obtained from paraffin-embedded blocks from the Pathology Division archives of HCFMUSP, and with prior histological analysis. The samples were processed using the Infinium MethylationEPIC BeadChip (Illumina®) and methylation data analysis tools in R Studio. The data were submitted to the MolecularNeuropathology.org platform for methylation based classification and CNV chart generation. The classifier was consistent with the previous diagnosis in all cases, refining the diagnosis in 54% of cases to subclass, 38% to subtype, and 8% to family. The platform also provided CNV estimates for 87% of cases, revealing crucial information on genetic alterations such as gains, losses, amplifications, and gene fusions. Despite the challenges of implementation within the Brazilian Public Health System (SUS), the results demonstrate the method's robustness and reproducibility, promising invaluable support for precise diagnoses and the development of more effective therapeutic strategies.

The utilization of inertial measurement units (IMUs) as wearable sensors is proliferating 1 across various domains such as healthcare, sports, and rehabilitation. This expansion is driven by 2 the continuous improvement of sensor technology to accommodate specific operational demands. 3 This paper introduces the development of a configurable wearable device capable of capturing both 4 high-frequency and low-frequency signals, tailored for a wide range of monitoring applications.Our 5 focus is on a comprehensive evaluation of the device in terms of deviation, noise levels, and precision. 6 We present initial findings that demonstrate the device’s robust performance, and put on the spotlight 7 the most critical optimizations needed to improve the device to reach the goal of a smart general-use 8 unit for human motion monitoring.

This literature review investigates the role of plumage in the hunting tactics of Velociraptor, integrating anatomical analysis and biomechanical modeling. Velociraptor, a swift and agile theropod from the Late Cretaceous, exhibited advanced intelligence and sensory capabilities that contributed to its effective predatory strategies. Recent discoveries have confirmed that Velociraptor was covered in feathers, with quill knobs indicating well-developed plumage. This review explores the potential functions of feathers beyond flight, focusing on their impact on hunting behavior. Evidence suggests that Velociraptor’s plumage likely facilitated camouflage and enhanced aerodynamic control, improving its stealth and maneuverability during high-speed chases. Additionally, feathers might have contributed to stability during incline running, further supporting its adaptability in diverse environments. Velociraptor’s hunting strategies, characterized by agility and precision, were complemented by its feathered anatomy, which may have also played a role in pack hunting and social interactions. Overall, the integration of plumage with Velociraptor’s anatomical features and behavioral adaptations underscores its efficiency as a predator, demonstrating how feathers may have been a critical factor in its successful hunting tactics.

Cryopreservation, storing biological material in liquid nitrogen (LN, −196 °C), offers a valuable option for the long-term conservation of non-orthodox seeds and vegetatively propagated species in the sector of agrobiodiversity and wild flora. Although large-scale cryobanking of germplasm collections has been increasing worldwide, the wide application of cryopreservation protocol in wild flora is hampered by difficulties in vitro propagation and a lack of universal cryopreservation protocols, among others. This study established a systematic approach to developing an in vitro culture and droplet-vitrification cryopreservation procedure for shoot tips of Scrophularia kakudensis. The standard procedure includes two-step preculture with 10% sucrose for 31 h and with 17.5% sucrose for 16 h, osmoprotection with loading solution C4-35% (17.5% glycerol + 17.5% sucrose, w/v) for 30 min, cryoprotection with A3-80% (33.3% glycerol + 13.3% dimethyl sulfoxide + 13.3% ethylene glycol + 20.1% sucrose, w/v) at 0 °C for 60 min, and cooling and rewarming using aluminum foil strips. After unloading, a three-step regrowth procedure starting with an ammonium-free medium with growth regulators was essential for developing normal plantlets from cryopreserved shoot tips. Liquid overlay on the gelled medium two weeks after inoculation resulted in vigorous growth during subcultures. Moreover, liquid overlay increased LN regeneration by up to 80%, i.e., 23% higher than no liquid overlay.

In this paper, we study nonlocal problems for a fractional diffusion equation and a degenerate hyperbolic equation with singular coefficients in the lower terms. The uniqueness of the solution to the problem is proved by the method of energy integrals. The existence of a solution is equivalently reduced to the question of the solvability of Volterra integral equations of the second kind and a fractional differential equation. For a particular solution of the proposed problem, its visualization is carried out for various values of the order of the fractional derivative. It is shown that the order of the derivative affects the intensity of the diffusion process (subdiffusion), as well as the shape of the wave front.

Introduction: Increases in contralateral range of motion (ROM) have been shown following acute high-intensity and high-duration static stretching (SS) with no significant change in contralateral force, power, and muscle activation. There are currently no studies comparing the effects of a high-intensity, low-duration (HILD) or low-intensity, high-duration (LIHD) SS on contralateral performance. Purpose: The aim of this study was to examine how HILD and LIHD SS of the dominant leg hamstrings influence contralateral limb performance. Methods: Sixteen trained participants (8 females, 8 males) completed three SS interventions of the dominant leg hamstrings; 1) HILD (6x10s at maximal point of discomfort (POD)), 2) LIHD (6x30s at initial POD), and 3) control. Dominant and non-dominant ROM, maximal voluntary isometric contraction (MVIC) forces, muscle activation (electromyography (EMG)), unilateral CMJ and DJ heights were recorded pre-test and 1-minute post-test. Results: There were no significant contralateral ROM or performance changes. Following the HILD condition, the post-test ROM for the stretched leg (110.612.60) exceeded the pre-test (106.09.00) by 4.2% (p=0.008). Similarly, with LIHD, the stretched leg post-test (112.216.50) also exceeded (p=0.06) the pre-test ROM (109.316.20) by 2.6%. There were large magnitude impairments, evidenced by main effects for testing time for force, instantaneous strength, and associated EMG. A significant ROM interaction (p=0.02) showed that with LIHD, the stretched leg significantly (p=0.05) exceeded the contralateral leg by 13.4% post-test. Conclusion: The results showing no significant increase in contralateral ROM with either HILD or LIHD SS suggesting the interventions may not have been effective in promoting crossover effects.

This systematic examines research into patients diagnosed with retinal vascular occlusive diseases (RVODs) secondary to coronavirus disease 2019 (COVID-19) infection or vaccination. RVODs include central retinal vein occlusion, branch retinal vein occlusion, central retinal artery occlusion, and branch retinal artery occlusion. Previous studies have posited a possible link between RVODs and COVID-19. RVODs are of two types: retinal vein occlusion and retinal artery occlusion. These disorders develop when retinal blood vessels become clogged by thrombi or fat deposition. The retina is an important component of the visual apparatus. Its photoreceptors are stimulated by the light hitting the eye and record its pattern. The retina then relays this visual information to the brain. When retinal blood vessels become clogged, the damage can range from slightly reduced vision to complete blindness. COVID-19 causes endothelial dysfunction and increased levels of von Willebrand factor antigens in the blood. Elevation of von Willebrand factor activates the coagulation process and platelet aggregation. The treatment methods and visual prognosis in COVID-19-related RVODs do not differ from conventional RVODs. However, ophthalmologists need to be aware of the possible relationship and should consider RVODs when they encounter patients with vision loss following COVID-19 infection or vaccination.

: Based upon the latest molecular phylogenies of Gonyosoma sensu lato, which recovered five clades with robust support, we utilize morphological characters to demonstrate the distinctiveness of each clade, resulting in the resurrection of three genera (Gonyophis Boulenger, 1891 [1], Rhynchophis Mocquard, 1897 [2], and Rhadinophis Vogt, 1922 [3]) and proposal of a new genus and a new tribe. A synopsis of the group, with descriptions and diagnoses, is provided for the five genera and eight species in addition to distribution maps and illustrations of the head of each taxon. An artificial key to the species and genera in the new tribe is presented in addition to estimated origin times for each clade.

In this paper, we consider the Cauchy problem of a time fractional nonlinear diffusion equation. According to the Kaplan’s first eigenvalue method, we first prove the blow-up of the solutions in finite time for some sufficient conditions. We next give sufficient conditions for the existence of global solutions by using the result of Zhang and Sun. In conclusions, we find the second critical exponent for the existence of global and non-global solutions via the decay rates of the initial data at spatial infinity.

Brazilian garimpeiros are a highly hard-to-reach and mobile population, with little access to basic hygiene and health services, and have been crossing the border to work irregularly in gold mines in French Guiana since the 90s. This study aimed to characterize this population and identify their main health problems. A cross-sectional study was carried out in the municipality of Oiapoque-AP, with two surveys: before (2018) and after (2019) the implementation of Malakit. Individuals were recruited from resting places and submitted to a questionnaire with demographic variables, history and knowledge of malaria, and health issues in the mines. Simultaneously, a clinical evaluation was performed. The garimpeiros were mainly men from Maranhão, Pará, and Amapá, with a low educational level and worked on average for 10 years in the mining sites. The study population mentioned numerous health problems: malaria, followed by leishmaniasis, flu, body aches, headaches, and digestive problems. Other diseases mentioned were skin diseases, bat bites, hepatitis, and HIV infection. This vulnerable population is constantly subjected to heavy routines and exposed to different diseases and infections that can spread across borders. Knowledge of this is essential for developing public health policies that can be integrated into specific epidemiological situations.

This study examined how Information Use Environments (IUEs) influence the information behavior of people living with neglected tropical diseases (PLWNTDs) and how this affects their participation in diagnosis and treatment programs. The author demonstrated that local information use environments (IUEs) significantly impacted the information behavior of people living with neglected tropical diseases (PLWNTDs'), which can be harnessed to improve their involvement in diagnosis and treatment programs. The author compared user-centered and program-centered approaches within common IUEs in remote and impoverished areas, finding that NTDs persist due to a disconnect between program organizers and the affected individuals’ information use environments (IUEs). Data was sourced from published papers, and OpenAI (ChatGPT) was used to generate list of local sources (IUEs) in affected remote communities. The findings indicated that understanding local IUEs can help program organizers enhance participation rates of individuals with NTDs in diagnosis and treatment initiatives.

The Atlantic Canada Together Enhancing Acute Stroke Treatment (ACTEAST) project is a Modified Quality Improvement Collaborative (mQIC) designed to improve ischemic stroke treatment rates and time-based efficiency in Atlantic Canada. This study specifically evaluates the implementation of the mQIC in Nova Scotia using qualitative methods. The mQIC spanned six months and included two Learning Sessions, multiple webinars, and a per-site virtual visit. Each session was followed by an action planning period to guide implementation efforts over the following 2-4 months. The Consolidated Framework for Implementation Research (CFIR) was utilized to develop a pre-tested, semi-structured interview guide, which aimed to uncover barriers and facilitators to mQIC implementation. Interviews were conducted with 14 healthcare professionals, generating 454 references that were coded into 28 CFIR constructs. Notably, 84% of these references were positively framed as facilitators. Despite this, significant barriers were identified, including resource availability, competing priorities, communication challenges, and difficulties engaging key stakeholders. Some barriers were particularly prominent during specific phases of implementation. The study findings offer valuable insights into the implementation of quality improvement initiatives in stroke care. They underscore the importance of recognizing and addressing context-specific barriers, while also leveraging identified facilitators to drive successful implementation and ultimately improve patient outcomes.

Previous studies have acknowledged the impact of weather changes on retail uncertainty. They primarily focus on understanding how weather conditions affect offline consumer behavior and aiming to develop effective marketing strategies. However, there is little research on the complex impact of weather on online shopping behavior. To bridge this gap, we conduct a study with a sample of 261 consumers from China with shopping experience in Community Retail Shops (CRSs). We utilize the S-O-R model and theories including meteorological emotional effect theory, emotional coherence and meteorological psychology to propose and validate models elucidating the relationship between weather and consumers' online shopping behavior in CRS. Our findings reveal that weather conditions affect consumers' spending patterns and purchase diversity, mediating by consumers' emotion and risk aversion, when they comfortably shop online at home. Furthermore, employing the fsQCA model, we identify the critical path through which weather conditions and consumer types influence risk aversion awareness. The results provide management implications for retailers to develop online marketing strategies for different consumer types.

To enhance the corrosion resistance of molybdenum metal in molten zinc, this study successfully fabricated TiB2 coatings on molybdenum substrates using the molten salt electrophoretic deposition technique and investigated their corrosion resistance in molten zinc. Initially, TiB2 nanoparticles with a size ranging from 50 to 150 nm were synthesized using the borothermal reduction method in NaF-AlF3 molten salts at 1238 K. Subsequently, electrophoretic deposition experiment was conducted by applying a cell voltage of 1.2 V (corresponding to an electric field of 0.6V/cm) for 1 h in the molten salts containing TiB2 nanoparticles, resulting in a uniform, continuous, and dense TiB2 coating with a thickness of 35 μm on the molybdenum substrate. Moreover, the corrosion resistance of the TiB2 coated molybdenum metal to molten zinc was tested through continuous immersion. After 120 h of immersion, the TiB2 coating showed no signs of cracking or peeling off, successfully protecting the molybdenum metal substrate from corrosion by molten zinc. The results confirm that the molten salt electrophoretic deposition technique can be used to prepare TiB2 coatings with good resistance to molten zinc corrosion on molybdenum metal.

Smart Dental Materials refer to materials used in dentistry with additional functionality to enhance treatment outcomes, which may improve oral health. Smart materials for dental restorations can react to stimuli such as a specific temperature, a different pH, or mechanical stress, repair small cracks or damage by themselves, and interact beneficially with biological surroundings. For example, they might release ions and promote tooth remineralization or have antibacterial properties to prevent bacterial growth. Others can have enhanced mechanical properties like strength and wear resistance to ensure these materials can withstand the daily masticatory forces. This review presents our current comprehension of smart dental materials designed for tooth restoration. We focused on what these materials need to be effective, like durability, biocompatibility, and aesthetic requests, besides identifying new ideas for their design. A detailed analysis of the current challenges faced in formulating these materials, such as the balance between enough ions released with proper physicochemical properties and achieving the desired biological response, was discussed. We also discussed how these cutting-edge technologies are being leveraged to overcome existing limitations, creating more dental materials with potential clinical translation. The review also discusses the practical challenges in implementation and the prospects for these materials in dentistry.

When limited area models of the hydrodynamics of the atmosphere and of the ocean are 1 run over an extended time, variability unrelated to external "drivers" emerge - this variability is 2 colloquially named "hydrodynamical noise" or just "noise". This article summarises what we have 3 learned in the past few years about the properties of such noise, and the implications for numerical 4 experimentation and analysis. The presence of this noise can be identified easily in ensembles of 5 numerical simulations, and it turns out that the intensity of the noise is closely linked to the scale- 6 dependent "memory". At the system level, this "memory" term as given by Hasselmann’s Stochastic 7 Climate model plays a key role. In the case of marginal seas, the process of baroclinic instability 8 modulated by tides and the formation of seasonal thermoclines are significant aspects. Some more 9 general aspects are discussed, such as the applicability of the Stochastic Climate model to systems 10 outside of atmospheric and oceanic dynamics, the irreversibility of tipping points and the challenges 11 of detecting changes beyond a noise level and of the attribution of causes of change.

The main purpose of this study is the determination of the optimal data acquisition and processing parameters of electric and seismic tomographic techniques, for the investigation of complex geological environments. Two different study areas, in central-east Peloponnese and SW Attica were selected, where a detailed geological mapping and surface geophysical survey were carried out. The applied geophysical survey included the application of electrical resistivity tomography (ERT) and seismic refraction tomography (SRT). The geoelectrical measurements were acquired with different arrays and electrode configurations. Moreover, various types of seismic sources were used at seventeen shot locations along the seismic arrays. For the processing of geoelectrical data, clustered datasets were created increasing the depth of investigation and the discriminatory capability. The seismic data processing included: (a) creation of synthetic models and seismic records to determine the effectiveness and capabilities of the technique, (b) spectral analysis of the seismic records to determine the optimal seismic source type and (c) inversion of the field data to create representative subsurface velocity models. The results of the two techniques successfully delineated the complex subsurface structure that characterizes these two geological environments. The application of the ERT combined with the SRT, are the two dominant, high-resolution techniques for the elucidation of complex subsurface structures.

NiO nanoparticles have been synthetized by calcination of layered double hydroxides (LDHs) precursors prepared using dimethylamine (DMA) as a precipitating agent. The incorporation of Ce and La oxides to the structure was investigated. The samples were characterized by element chemical analysis, powder X-ray diffraction, FT-IR spectroscopy, thermal analysis and specific surface area analysis. Furthermore, the optical band gaps of the semiconductor samples were estimated by ultraviolet-visible diffuse reflectance spectroscopy. The results showed that it is possible to obtain Ni-LDHs precursor with good crystallinity and a small crystal size, which can be used as precursors of NiO nanoparticles with ≈3.7 nm of crystal size. The semiconductors obtained have good values of band gaps with rather large specific surface areas, which make them suitable for their use as photocatalysts.

Leucine zipper-EF-hand containing transmembrane protein 1 (LETM1) is a mitochondrial inner membrane protein involved in mitochondrial morphology and homeostasis. LETM1 is highly expressed in many human solid cancers and correlates with poor prognosis possibly due to mitochondrial dysfunction. However, the functional role of LETM1 in the progression of hematological malignancies remains to be elucidated. In this study, we found that higher LETM1 expression was associated with a short overall survival in Diffuse Large B-Cell Lymphoma (DLBCL) and in Acute Myeloid Leukemias (AML) patients. The transcriptomic analysis showed that LETM1 expression is positively correlated with oncogenic pathways (e.g., glucose transport, stem cell maintenance, mTOR and Wnt signaling pathways, mitotic G2/M phase transition, and cell proliferation) and negatively correlated with autophagy-related processes and apoptosis. In contrast, low expression of LETM1 associated with upregulation of BECLIN-1-dependent mitophagy, which in turn improves the prognosis in both DLBCL and AML patients. Our data suggest that LETM1 is a valuable prognostic marker and a possible therapeutic target for improving the clinical outcome in hematological malignancies.

Data spaces are a relatively recent concept for a trusted and secure distributed data ecosystem through which to exchange resources in the Web. Several different efforts are currently being made to define guidance toward data space implementation, with some initiatives and organizations providing solutions and standards that address interoperability and good data exchange practices, especially in the domain of geospatial information. Geospatial Use Cases often require effective and high-quality data sharing between systems dealing with different aspects of real-world objects. However, the different solutions proposed do not yet provide a common interoperability framework with mature implementation options. This gap between concept and implementation risks confusing users and developers, instead of reciprocally strengthening the respective data spaces' infrastructures and capabilities. This paper reviews and compares some of the proposed solutions, providing mapping and integration of these blueprints to available interoperability standards. This concrete mapping is designed to support effective practical implementation of data spaces, and to guide future solutions developments.

Fortified human milk is the first choice for preterm infants. Although individualized fortification is recommended, the optimal method for this population remains uncertain. We conducted a comparative study assessing the growth effects of adjusted (AF) and targeted fortification (TF) in extremely low birth weight (ELBW) infants. This single-center, randomized, controlled clinical trial was conducted at a tertiary neonatal unit in Spain. Eligible participants were premature infants with a birthweight

Countless disasters have resulted from climate change, with severe damage to infrastructure and the economy. Their societal impacts require mental health services for the millions affected. To prepare for and respond effectively to these events, it is important to understand people’s emotions and incidents both before and after a disaster strikes. The emotions and other life incidents expressed on Twitter during the 2017 Hurricane Harvey were mined in this case study. Between August 20 and August 30, we collected a dataset of approximately 400,000 public tweets that related to the storm. Using a BERT-based model, we predicted the emotions attached to each tweet. After that, we used various natural language processing techniques to analyze the tweets themselves to understand what kind of ’topics’ were being discussed when people expressed certain ’emotions’. Applying the Latent Dirichlet Allocation (LDA) technique for topic modeling sidesteps the need for manual content analysis and allows us to find meaningful patterns in the data. Results show that there is a significant change of emotions occurred when the hurricane is at most devastating and many of life incidents become pressing demands/concerns from population such as evacuation plan, animal safety, safety update, public policy, helps, flood, and fake news.

Traffic anomaly detection is crucial for urban management, yet current research is often confined to small-scale endeavors. This study collected nine months of real-time Wuhan traffic monitoring data from Amap. We proposed Traffic-ConvLSTM, a multi-scale spatial-temporal technique based on long and short-term memory networks (LSTM) and convolutional neural networks (CNN) to effectively achieve long-term anomaly detection at the city level. First, we convert the traffic flow data into image representation, which enables the capture of the spatial correlation between traffic flow and roads and the correlation between traffic flow and roads, as well as the surrounding environment. Second, The model utilizes convolution kernels of different sizes to extract spatial features at road-level, regional-level, and city-level scales, while incorporating temporal features of different time steps to capture hourly, daily, and weekly dynamics. Additionally, varying weights are assigned to the convolution kernels and temporal features of varying spatio-temporal scales to capture the heterogeneous strengths of spatio-temporal correlations within patterns of traffic anomalies. The proposed Traffic-ConvLSTM model exhibits improved performance over existing techniques in the task of identifying long-term and large-scale traffic anomaly occurrences. Furthermore, the analysis reveals significant traffic anomalies during holidays and urban sporting events. The diverse travel patterns observed in response to various activities offer insights for large-scale urban traffic anomaly management, providing recommendations for city-level traffic control strategies.

This review examines the effects of lingonberry (Vaccinium vitis-idaea L.) on general and oral health. The effects of lingonberry are based on the vitamins, minerals, fibers and polyphenolic compounds it contains. Lingonberry's bioactive substances have a diverse range of antimicrobial, anti-inflammatory, antiproteolytic, anticarcinogenic and antioxidant properties. Research results suggest that lingonberries can have a positive effect on human health. Berries, lingonberry juice/lingonberry nectar/fermented lingonberry juice and polyphenol fractions have been used in clinical studies. Lingonberries balance post-meal blood sugar, free fatty acids and insulin levels. Fermented lingonberry juice reduces Streptococcus mutans, Candida and periodontal pathogen counts, but is probiotic because it favors growth of Lactobacilli. In addition, it increases saliva secretion and thus lowers the risk of oral infections. It lowers the clinical parameters of periodontitis and the active matrix metalloprotease-8, reducing the low-grade inflammation associated with periodontal diseases. More studies on humans are needed.

To further enhance the intelligence level of coal mining faces and achieve autonomous derivation, learning, and optimization of shearer navigation cutting, this paper proposes the methods of shearer digital twin navigation cutting motion planning based on the concept of shearer autonomous navigation cutting technology and intelligent coal mining face digital twins. The study includes the digital twin theory and the construction method of the shearer digital twin navigation cutting motion planning system based on this theory. Based on the digital twin theory, a shearer digital twin navigation cutting motion planning system was constructed. This system supports the service functions of shearer cutting digital twin, dynamic navigation map digital twin, reinforcement learning environment construction, and motion planning through the physical perception layer, comprehensive data layer, and digital-model fusion analysis layer. Finally, by comparing the effects of the DQN-NAF and DDPG deep reinforcement learning algorithms in the shearer motion planning task within the constructed digital twin environment, the results show that the DQN-NAF algorithm demonstrates better performance and stability in solving the shearer digital twin motion planning task.

Tea (Camellia L.) falls into the family Theaceae, is a valuable commercial crop, and tea products made from its buds and young leaves are favored by consumers all over the world. The more common Thea plant is Camellia sinensis (C. sinensis), but its most important relative, Camellia taliensis (C. taliensis), is also utilized by locals in the area of cultivation to manufacture tea. In this investigation, C. taliensis (DL) and C. sinensis (QJZ) were characterized in terms of their agronomic traits, physicochemical indices, metabolomics, and transcriptomics. The leaf area of DL is larger than that of QJZ; the color of DL’s buds and leaves is yellowish-green, while that of QJZ’s is green. DL’s buds and leaves are more densely velvety than those of QJZ. The HPLC results indicated that the physicochemical contents varied considerably between the two samples, with DL having greater concentrations of EGCG and GABA than QJZ, while QJZ had remarkably higher concentrations of C, CA, and EGC than DL. A total of 2269 metabolites and 362,190,414 genes were positively identified, with the number of DAMs and DEGs being 1001 and 34,026, respectively. The flavonoids, phenolic acids, and alkaloid metabolites were dramatically different between the two tea group plants. Bioinformatics profiling revealed that the DAMs and DEGs of the two tea group plants interacted with each other and were involved in metabolic pathways including “biosynthesis of secondary metabolites”, “biosynthesis of amino acids”, “biosynthesis of cofactors”, “phenylpropanoid biosynthesis”, and “flavonoid biosynthesis”. Overall, these results provide statistical support for germplasm conservation and production for both C. taliensis and C. sinensis.

Background: In recent years, computational aesthetics and neuroaesthetics have provided novel insights into understanding beauty. Building upon the findings of traditional aesthetics, this study aims to combine these two research methods to explore an interdisciplinary approach to studying aesthetics; Method: Abstract artworks were used as experimental materials. Based on traditional aesthetics and in combination, features of composition, tone, and texture were selected. Computational aesthetic methods were then employed to correspond these features to physical quantities: blank space, gray histogram, GLCM, LBP, and Gabor filters. An EEG experiment was carried out, in which participants conducted aesthetic evaluations of the experimental materials in different contexts (genuine, fake), and their EEG data was recorded to analyze the impact of various feature classes in the aesthetic evaluation process. Finally, a SVM was utilized to model the feature data, EEG data, context data, and subjective aesthetic evaluation data; Result: Behavioral data revealed that higher aesthetic ratings in the genuine context. EEG data indicated that genuine contexts elicited more negative deflections in the prefrontal lobes between 200-1000ms. Class II compositions demonstrated more positive deflections in the parietal lobes at 50-120ms, while Class I tones evoked more positive amplitudes in the occipital lobes at 200-300ms. Gabor features showed significant variations in the parieto-occipital area at an early stage. Class II LBP elicited a prefrontal negative wave with a larger amplitude. The results of the SVM models indicated that the model incorporating aesthetic subject and context data (ACC=0.76866) outperforms the model using only parameters of the aesthetic object (ACC=0.68657); Conclusion: A positive context tends to provide participants with a more positive aesthetic experience, but abstract artworks may not respond to this positivity. During aesthetic evaluation, the ERP data activated by different features show a trend from global to local. The SVM model based on multimodal data fusion effectively predicts aesthetics, further demonstrating the feasibility of the combined research approach of computational aesthetics and neuroaesthetics.

Alena Tensor is a recently discovered class of energy-momentum tensors that provides mathematical framework in which, as demonstrated in previous publications, the description of a physical system in curved spacetime and its description in flat spacetime with fields are equivalent. The description of a system with electromagnetic field based on Alena Tensor can be used to reconcile physical descriptions. 1) In curvilinear description, Einstein Field Equations were obtained with Cosmological Constant related to the invariant of the electromagnetic field tensor, which can be interpreted as negative pressure of vacuum, filled with electromagnetic field. 2) In classical description for flat spacetime, three densities of four-forces were obtained: electromagnetic, gravity, and the force responsible for the Abraham-Lorentz effect (radiation reaction force). Obtained connection of Einstein tensor with gravity and radiation reaction force, after transition to curvilinear description, excludes black hole singularities. There was obtained Lagrangian density and generalized canonical four-momentum, containing electromagnetic four-potential and a term responsible for other two forces. In this description charged particles cannot remain at complete rest and should have spin, their energy results from the existence of the energy of the magnetic moment and the density of this energy is part of the Poyting four-vector. The distribution of charged matter was expressed as polarization-magnetization stress-energy tensor, what may explain why gravity is invisible in QED. 3) In quantum picture, QED Lagrangian density simplification was obtained, and the Dirac, Schrödinger and Klein-Gordon equations may be considered as approximations of the obtained quantum solution. Farther use of Alena Tensor in unification applications was also discussed.

In recent years, electroencephalogram (EEG) emotion recognition has emerged as a research hotspot in the field of artificial intelligence (AI). Despite advancements in EEG-based emotion recognition, room for enhancing performance persists due to EEG signal redundancy and limitations in feature extraction, leading to inefficient models and emotional information loss. To fully utilize EEG's emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification, and 97.69% and 98.05% in ternary classification, surpassing relevant algorithms. Additionally, the model's efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.

This literature review investigates how the diverse habitats of Baryonyx walkeri influenced its hunting strategies, with a focus on adaptations for piscivory and generalist predation. The spinosaurid theropod Baryonyx walkeri, known for its distinctive elongated snout and conical teeth, inhabited a variety of environments during the Early Cretaceous period. Fossil evidence suggests that Baryonyx frequented fluvial and lacustrine environments, leading to the hypothesis that its primary diet consisted of fish and other aquatic organisms. Detailed analysis of its cranial morphology reveals a suite of adaptations, including robust forelimbs with a large, sickle-shaped claw, ideal for catching slippery prey. Isotopic analysis of oxygen in Baryonyx indicates a significant reliance on fish and other similar organisms. Comparisons with modern analogs, such as crocodilians, provide further insight into the behavioral ecology of Baryonyx. This review integrates paleontological data with modern ecological analogs to reconstruct the hunting strategies of Baryonyx walkeri. The findings underscore the importance of habitat diversity in shaping the evolutionary pathways of predatory dinosaurs and contribute to a broader understanding of spinosaurid ecology and behavior.

The use of individual protective covers (IPCs) to protect newly planted citrus trees from HLB infection is being widely adopted in Florida, an HLB endemic citrus producing area. It is known that IPCs positively influence most horticultural traits, increasing tree growth, flush expansion, and leaf size enabling trees to sustain a balanced carbohydrate metabolism by preventing CLas infection and induced higher leaf chlorophyll levels. This may result in more productive trees. However, as the tree grows IPCs eventually are removed, typically between 2 and 3 years after initial installation. Once IPCs are removed, trees become exposed to the ACPs and ultimately become infected. In this work we covered trees from Valencia sweet orange with IPCs for 30 months, until the trees entered fruit bearing age. We investigated how IPC protection of newly planted trees for 30 months influenced fruit quality and yield of ‘Valencia’ trees for three consecutive seasons after IPC removal compared to non-covered trees. The use of IPCs kick-started the newly planted citrus trees, resulting in more yield and fruits with better internal and external quality. After 30 months of IPC protection, tree canopies were larger and denser supporting more fruit per tree than in non-protected trees for three consecutive seasons even though by the end of the first season after IPC removal trees were HLB positive. Tree height, scion diameter, canopy volume, and leaf area were significantly improved as compared to non-covered trees. Additionally, fruit quality was significantly improved in the three seasons following IPC removal as compared to non-covered trees. However, a decline in quality was measurable in fruit from IPC trees after the second harvesting season, with trees affected by HLB. Based on the results from this study, we conclude that benefits from IPC protection may last for at least three consecutive seasons once trees enter the productive age despite CLas-infection within 12 months after IPC removal.

Mercury is classified as one of the world’s most toxic and dangerous pollutants. It tends to bio-accumulate and biomagnify within the trophic chain and is persistent. Various approaches are available to remediate Hg-affected sites, including phytoremediation, which includes the use of plants to clean up contaminated environments. Phytoremediation of mercury contamination is at-tracting increasing attention because of its advantages: it is environmentally friendly, inexpensive, simple, and can improve soil fertility. In this report, VOSviewer, and Bibliometrix software were used to analyze 457 and 697 documents published from 2000 to 2023, retrieved from the data-bases WoS and Scopus, respectively. China, India, the United States, and Spain are the top four most productive countries. The largest topic area was environmental sciences, and the Chinese Academy of Sciences was the organization that contributed the most to the overall number of pub-lications. The keywords with the highest frequency, excluding phytoremediation and mercury in WoS, were heavy metals, accumulation, cadmium, soils, and phytoextraction. In Scopus, the most frequent keywords were bioremediation, heavy metals, soil pollution, bioaccumulation, biodeg-radation, and environmental. From the above analysis, we concluded that future research should focus on 1) finding native plants, 2) increasing remediation ability through assisted phytoremedi-ation, 3) studies of molecular mechanisms in plants with phytoremediation potential, and 4) ge-netic engineering applications. This study provides insight into trending themes and serves as a reference for future research.

The different systems in the nuclear power plants (NPP) are critical and complex which requires a continuous rigorous monitoring for both normal and abnormal conditions. However, due to the nonlinearity of the dynamic behavior of these systems, implementation of artificial intelligence within the NPP components is crucial to enhance the monitoring and the predictability of the key operating parameters trend. On the other hand, lessons learned from large nuclear accident proves that a remote real-time coordination between the different stakeholders involved in the safety of the nuclear reactor is needed. This remote feature can be implemented in the existing power plants by embedding a mobile computing networks within the plant components. This network will send early warning and transmit the NPP data on real-time to different authorities such as the regulatory authority and the decision-making committees, to enhance the interpretability of the nuclear event and deliver a collaborative decision which in return mitigate the risk associated with these events and increase the overall safety of the plant. The integration of AI and mobile computing in NPP would be most of interest in countries where nuclear reactors data are challenged to reach during an accident. For instance, during the meltdown of Chernobyl, the Soviet government covered the accident from the news in an attempt to contain the consequences but there was a spread of radioactive contamination to some other Europe countries. Therefore, in the case of such scenario the implementation of mobile computing and AI would result in different outcomes as the European countries would be notified through the mobile networking and the spread of contamination would be forecasted by the AI algorithms. In this paper, we examine the different modern AI and mobile computing technologies, the different potential application, the associated features and challenges, and future work direction.

Colorectal cancer is third most common malignancy. For metastasis of rectal cancer, metastasis to skeletal muscle tissue is rare. In this case report, we describe a 51-year-old male patient with rectal cancer with neoadjuvant concurrent radiotherapy and chemotherapy followed by transanal total mesorectal excision with ileostomy. However, he had deep venous thrombosis of left leg after operation and skeletal muscle metastasis was diagnosed via tissue proof. Therefore, less possibility of metastasis increased included brain, duodenum, bone, and nervous system. The prognosis of metastasis to skeletal muscle is poor in contrast to liver or lung metastasis.

Novel freeform optical design methods can be classified in two categories, relevant to the generation of a starting point or to the development of new optimization tools. In this paper, we design a freeform TMA optimized with different surface representations using either a differential ray-tracer as a new optimization tool, or commercial ray tracer (ANSYS-ZEMAX OpticStudio) for comparison. For differential ray tracing, we use FORMIDABLE (Freeform Optics Raytracer with Manufacturable Imaging Design cApaBiLitiEs): an optical design library with differential ray tracing and NURBS optimization capabilities under European Software Community License (ESCL). NURBS allow to represent a freeform surface without needing any prior knowledge on the surface, such as the polynomial degree in polynomial descriptions. However, commercial optical design software are designed to optimize polynomial surfaces, but are not well-suited to optimize NURBS surfaces. This requires to use a custom optical design library. To demonstrate the interest of using NURBS representation, freeform telescopes are independently optimized with NURBS using FORMIDABLE, or XY polynomials with OpticStudio over different iteration cycles. We then compare the resulting systems using their RMS Field Maps to assess the optimization quality of each surface representation. We also provide a full-system comparison, including mirror freeform departures. This study shows that NURBS can be a relevant alternative to XY polynomials for freeform optimization of reflective 3-mirror telescopes.

In recent decades, the aquaculture industry has experienced significant growth worldwide, surpassing other food production sectors. This review aims to explore the dynamics of aquafeed production, particularly the shift from conventional to local feed production in Africa, driven by cost-effectiveness and the availability of raw materials. The review examines various scientific publications on aquafeed, focusing on both conventional and novel feed formulations and their impact on aquaculture and the environment. Commonly used aquafeed ingredients among African farmers include cassava, maize gluten, groundnut oilcake, sunflower oilcake, soybean meal, kale, peas, garlic, shrimp wastes, and waste blood. Novel ingredients such as insect-based diets and micro-algae formulations are also explored. Aquafeed composition impacts aqua-waste, water quality, algae, oxygen demand, fish mortality, and eutrophication. The findings highlight the need to reorient feed formulation methods and ingredients to achieve a circular economy in Africa, promoting increased fish production at minimal costs, creating employment while supporting climate adaptation and mitigation efforts. Ultimately, the aquafeed sector has the potential to grow sustainably through the adoption of feed alternatives that prioritise sustainable production and encourage beneficiation studies.

while composting of organic wastes is increasingly adopted in sustainable agriculture, continued interest on biochar application, dark soils, and compost, showed morphological aspects and functionality of biochar as a challenge to solve the CO2 aspects related to climatic change, and carbon stability in sustainable soils, as Black carbon presents long chemical permanency due to incomplete combustion of biomass. The objective of this work was to study the characteristics of soil amendments and to review the state of the art of biochar, showing differences in composition and main microorganisms with relevant presence in the soils. Arbuscular mycorrhizal spores (Scutellospora sp., Glomus like, Funneliformis geosporus, Glomus crenatum, and Acaulospora excavata, obtained from TPI soil samples are shown. New strategies are highlighted such as nutrient supplementation of compost, which can constitute the basis for improved compost-based biofertilizers in the future. Thus, the most important strategies for C sequestration are underlined to diminish substantial organic agro- and municipal wastes, increasingly disposed in the fields, landfills or either released by burning or discarding.

The aging ability of dry white wines has been increasingly recognised. The present work aimed to understand which sensory factors drive their quality evaluation by experienced tasters. Individuals assessed several aesthetic, synthetic, and analytic flavour attributes, using dark tasting glasses. Wines originated from the grape varieties Alvarinho, Arinto, Sauvignon Blanc and Pinot Bianco with a wide range of ages. Basic physical-chemical analysis, browning (Abs 420 nm), elemental composition and a partial volatile fraction were also determined. The overall quality scores were a function of complexity and balance and were negatively influenced by the perception of faultiness. The different ages could be associated with a continuous sensory space characterised by a decreasing perception of freshness and an increase in the mellowed flavours. All wines shared an austere in-mouth perception elicited by their acidity, saltiness, bitterness, smoothness and dryness. Nevertheless, quality scores were similar from the youngest to the oldest-tasted wines (17 years old). The exception was a Sauvignon Blanc wine from a recent vintage that was judged as faulty due to the perception of earthiness. Overall, the tasted wines displayed an unexpected aging ability as demonstrated by the difference between the predicted and real wine ages. To improve the recognition of old wines, the metaphor “mellowed by age” is proposed to describe flavours resulting from beneficial aging instead of “oxidised by age”.

Introduction: Lower respiratory tract infections, including pneumonia, are one of the leading causes of child mortality, especially in low-resource settings. Current guidelines rely on clinical signs for diagnosis, leading to over-prescription of antibiotics, which in turn contribute to antimicrobial resistance. Lung point of care ultrasound (L-POCUS) offers potential to improve diagnostic accuracy and reduce unnecessary antibiotic use, but lacks standardized guidelines for diagnosis and management of paediatric pneumonia. Methods and Analysis: This study utilizes a modified Delphi process to develop expert consensus guidelines for L-POCUS interpretation in paediatric pneumonia that would constitute a framework for effective guidelines for judicious antibiotic prescribing. The 5-stage iterative process includes: i) creation of a literature summary and conceptual framework, ii) first round of online surveys for expert feedback, iii) virtual meetings to discuss survey results and refine guidelines, iv) second round of online surveys, v) final analysis and development of consensus guidelines. A panel of 12-15 experts, chosen for their paediatric POCUS experience, geographic diversity, and gender balance, will participate. Consensus will be defined as ≥75% agreement. Ethics and Dissemination: Participation is voluntary, with consent obtained at the start and the option to withdraw at any time. The protocol was approved by the Ethics Commission of Bern, Switzerland. Findings will be disseminated through open access publication.

Machine learning has gained significant recognition within healthcare organizations as a potent technology for medical image analytics. Among various medical image modalities, Contrast-Enhanced CT (CECT) is widely utilized to acquire additional diagnostic information that can help to better visualize and evaluate certain structures or abnormalities in the human body. Accordingly, there is an increasing demand for machine learning systems for disease analytics using CECT. However, developing such systems presents two significant challenges: high technical complexity and high development effort. This paper presents a software platform that can effectively remedy these challenges. This platform embodies a unified software process for CECT-specific disease diagnosis including oncological diseases, cardiovascular diseases, and gastrointestinal diseases. It integrates multiple types of machine learning models into the disease diagnosis process, where the models can diagnose lesions, malignancies, tumors, medical features of tumors, temporal transitions with a contrast agent, and disease progress. The platform has been implemented in Python using Scikit-learn and TensorFlow libraries. To validate its applicability and reusability, a Hepatocellular Carcinoma (HCC) diagnosis system has been implemented.

Atmospheric pressure Microplasma is a simple, cost-effective, efficient, and eco-friendly procedure, which is superior to the traditional nanomaterials synthesis techniques. It generates high yields and allows for a controlled growth rate and morphology of nanomaterials. The silver (Ag) nanomaterials, with their unique physical and chemical properties, exhibit outstanding antibacterial and anti-fungal properties. Similarly, zinc oxide (ZnO) nanomaterials, known for their low toxicity and relatively lower cost, find wide applications in wound repair, bone healing, and antibacterial and anticancer applications. The use of core-shell nanomaterials in certain situations where some nanoparticles can cause serious harm to host tissues or organs is a testament to their potential. A benign material is coated over the core to reduce toxicity in these cases. This review compares the numerous configurations of microplasma systems used for synthesizing nanomaterials and their use in producing Ag, ZnO, and their core-shell (Ag-ZnO) nanomaterials for biomedical applications. The summary also includes the effect of control parameters, including cathode diameter, gas flow rate, precursor concentration, voltage, and current, on the nanomaterial's characteristics and applications. In addition, it provides a research gap in the synthesis of Ag, ZnO, and core shall nanomaterials by this technique, as well as the development and limitations of this technique and the use of these nanoparticles for biomedical applications.

Constructing a globally consistent high-precision map is essential for the application of mobile robots. Existing optimization-based mapping methods typically constrain robot states in pose space during the graph optimization process, without directly optimizing the structure of the scene, thereby causing the map to be inconsistent. To address the above issues, this paper presents a three-dimensional (3D) LiDAR mapping framework (i.e., BA-CLM) based on LiDAR bundle adjustment (LBA) cost factors. We propose a multivariate LBA cost factor, which is built from a multi-resolution voxel map, to uniformly constrain the robot poses within a submap. The framework proposed in this paper applies the LBA cost factors for both local and global map optimization. Experimental results on several public 3D LiDAR datasets and a self-collected 32-line LiDAR dataset demonstrated that the proposed method achieves accurate trajectory estimation and consistent mapping.

This paper assesses the association of ESG scores with stock returns and highlights the moderating role of the COVID-19 pandemic and the country's governance. The study uses panel data regressions to analyze how ESG performance influences plain, absolute, and risk-adjusted returns in a sample of European and selected non-European countries. These suggest that higher overall ESG scores are related positively to financial performance, and this relation is enhanced during the COVID-19 pandemic. Specifically, the two dimensions of ESG that matter most are environmental and governance. Country-level governance is important because firms in well-governed countries amplify the benefits of high ESG scores. The opposite is true for the higher Controversies scores, whose bad financial outcome is magnified during the pandemic. These results present an argument for the resilience of firm financial performance, dependent on strong ESG practices and governance frameworks. This holds great interest for investors and policymakers in associating good ESG considerations with the effective management of financial risks, leading to sustainable returns during periods of widespread economic uncertainty.

In this paper, we give closed-form expressions of the $p$-Frobenius number for the triple of the generalized star numbers $a n(n-1)+1$ for an integer $a\ge 4$. When $a=6$, it is reduced to the famous star number. For the set of given positive integers $\{a_1,a_2,\dots,a_k\}$, the $p$-Frobenius number is the largest integer $N$ whose number of nonnegative integer representations $N=a_1 x_1+a_2 x_2+\dots+a_k x_k$ is at most $p$. When $p=0$, the $0$-Frobenius number is the classical Frobenius number, which is the central topic of the famous linear Diophantine problem of Frobenius.

With prosperous development and successful application of deep learning technologies in the field of remote sensing, numerous deep-learning based methods have emerged for synthetic aperture radar (SAR) automatic target recognition (ATR) tasks over the past few years. Generally, most deep-learning based methods can achieve outstanding recognition performance in condition that an abundant of labeled samples are available to train the model. However, in real application scenarios, it is difficult and costly to acquire and to annotate abundant SAR images due to the imaging mechanism of SAR, which poses a big challenge to existing SAR ATR methods. Thereby, SAR target recognition under the situation of few-shot, where only a scarcely few of labeled samples are available, is a fundamental problem that needs to be solved. In this paper, we put forward a new method named enhanced prototypical network with customized region-aware convolution (CRCEPN) to specially tackle the few-shot SAR ATR tasks. To be specific, We first develop a feature extraction network based on a customized and region-aware convolution, which can adaptively adjust convolutional kernels and their receptive fields according to each SAR image’s own characteristics as well as the semantical similarity among spatial regions, thus augmenting its capability to extract more informative and discriminative features. To achieve accurate and robust target identity prediction under the few-shot condition, we then propose an enhanced prototypical network which can improve the representation ability of the class prototype by properly making use of training and test samples together, thus effectively raising the classification accuracy. Meanwhile, a new hybrid loss is designed to learn a feature space with both inter-class separability and intra-class tightness as much as possible, which can further upgrade the recognition performance of the proposed method. Experiments performed on the moving and stationary target acquisition and recognition (MSTAR) dataset and the OpenSARShip dataset demonstrate that the proposed method is competitive with some state-of-the-art methods for few-shot SAR ATR tasks.

The dissolution of CO₂ in seawater in the form of bicarbonate ions is an attractive alternative to the storage in geological formations, on the conditions that the storage is stable over long times and does not harm the marine environment. In this work, we focus on the long-term chemical stability of CO₂ absorbed in seawater as bicarbonate, by monitoring the physico-chemical properties of the solutions (pH, dissolved inorganic carbon and alkalinity), in six different sets of experiments on both natural and artificial seawater lasting up to three months. The bicarbonate treatment of natural seawater consists in pouring pre-equilibrated solutions obtained from the reaction of CO₂ and Ca(OH)₂. If the pre-equilibrated mixture does not exceed a critical threshold (ca. 1000-1500 mmol/L), the resulting bicarbonate-rich solutions can be stable for over three months.

Chronic stress, culminating in burnout, evolves gradually and is notoriously difficult to detect due to vague symptoms and individuals' hesitance to acknowledge their struggles. To expedite the identification and recognition of this condition, enabling timely psychological intervention, the integration of Artificial Intelligence (AI) is increasingly considered. This research does not assert the feasibility of an AI system managing all aspects of chronic stress's impact. However, it highlights the capability of current technology to detect stress indicators based on quantifiable data like Heart Rate (HR) and organizational climate dimensions. Although other physiological markers such as oximetry, skin galvanic response, and EKG have been explored, they have not shown reliable differentiation between stress and joy. Focused on the unique context of school principals in the Bedouin regions of Israel, this study investigates the interplay between HR, organizational climate, and stress levels. It introduces a novel application of a fuzzy logic tool that combines HR and organizational climate metrics to aid in stress diagnosis. This tool incorporates the psychologist's expertise to provide real-time data crucial for developing effective coping strategies. While the AI-supported fuzzy system does not replace professional psychological intervention, it significantly enhances the speed of condition identification and intervention planning, thus shortening the response time to stress-related issues in educational leadership within culturally specific settings. The application of such AI-driven tools is pivotal for sustaining the well-being and effectiveness of educational leaders, thereby supporting the broader goal of educational sustainability.

The Two Photon Absorption - Transient Current Technique (TPA-TCT) is a device characterisation technique that enables three-dimensional spatial resolution. Laser light in the quadratic absorption regime is employed to generate excess charge carriers only in a small volume around the focal spot. The drift of the excess charge carriers is studied to obtain information about the device under test. Neutron, proton, and gamma irradiated p-type pad silicon detectors up to equivalent fluences of about 7e15 neq/cm2 and a dose of 186 Mrad are investigated to study irradiation induce effects on the TPA-TCT. Neutron and proton irradiation lead to additional linear absorption, which does not occur in gamma irradiated detectors. The additional absorption is related to cluster damage and the absorption scales according to the non-ionising energy loss. The influence of irradiation on the two photon absorption coefficient is investigated, as well as potential laser beam depletion by the irradiation induced linear absorption. Further, the electric field in neutron and proton irradiated pad detectors at an equivalent fluence of about 7e15 neq/cm2 is investigated, where the space charge of the proton irradiated devices appears inverted compared to the neutron irradiated device.

As a result of decades of austerity, the economies of the Eurozone are experiencing under-investment and crumbling infrastructures in an era of extremely severe emergencies as the cli-mate change and aggressive global competition. The private savings glut of the rich and the strict fiscal rules suggest a crowding-in approach in partnership with big finance in a new age of in-fra-structures. If governments mint public infrastructures into investable assets, they can gen-erate steady returns for investors and asset managers who look after pensions and insurances schemes and unlock trillions now devoted to welfare state. For the big finance to accept to be partner, however, governments must take the task of de-risking returns. Innovation technology and macro-financial literacy can synergically act to enhance this new de-risking role to address in a financially sustainable way the intense phenomena of Natural Hazards (NHs) that can severely compromise economic growth. This is precisely the aim of our Public-Private Partnership (PPP) among the Department of Economics, Management and Institutions of the University of Naples and a Knowledge Transfert Management, the Department of Engineering and the Aca-demic Spin-Off “STRAIN”, of the University of Campania. Our PPP has been contributing to the eval-uation and mitigation of NHs such as floods, landslides and earthquakes since 2012. The ex-tremely advanced results of this multi-stakeholder partnership ensure a better knowledge of NHs which, as evidenced in the paper, is the fundamental input for the desired Public-Private In-surance Programmes (PIPPs).

(1) Background: The study of microbiome is being crucial for his role in major systemic diseases, in particular the oral and gut microbiota. In the last years the study of microorganism correlated for example with neurodegenerative disease is increasing the prospective of a possible link between gut microbiota and brain. Here we report a new case report about a patient evaluated genetically firstly for dementia and late-onset dyskinesia, and then tested with 16S metagenomics sequencing. (2) Methods: Starting from buccal swab, we extracted bacterial DNA and then we performed a NGS metagenomics sequencing based on the amplification of hypervariable regions of the 16S in bacteria. (3) Results: The sequencing revealed the presence of Spirochaetes Phylum, a pathogenic bacterium generally known to be able to migrate to the Central Nervous System and not only. (4) Conclusions: Oral infections as our results shows could be possible contributing factors to various neurodegenerative conditions.

Orodispersible film (ODF) is one of the novel formulations that have been currently made available that disintegrates rapidly in the mouth without the requisite for water and offer several benefits over conventional oral solid dosage formulations. This delivery system serves as a discreet and convenient mode of administration, especially in patients who have dysphagia, fluid restriction, being beneficial to pediatric, geriatric, and bedridden patients. A novel sildenafil ODF containing sildenafil citrate is formulated to be used in patients with erectile dysfunction (ED). This review discusses the advantages of ODF in improving compliance and satisfaction in these patients and describes the bioequivalence and stability studies of sildenafil ODF. This formulation offers unique benefit to patients with ED by improving their acceptance, compliance, and respecting their privacy. Moreover, the comparison of pharmacokinetic parameters between the sildenafil ODF administered with and without water and the conventional film-coated tablet were similar. It also demonstrated reliable performance that yielded a consistent product, meeting all specifications at release and after three weeks of storage under stressed conditions (60oC). Sildenafil ODF warrants improved ease of intake, taste, portability, storage, and compliance among ED patients, making it the potential most preferred formulation and drug of choice.

This study re-introduces a protein-free rapid test method for nucleic acids on paper based lateral flow assays utilizing special multichannel nitrocellulose membranes and DNA-Gold conjugates, achieving significantly enhanced sensitivity, easier protocols, reduced time of detection, reduced costs of pro-duction and advanced multiplexing possibilities. It is shown for the first time a protein-free nucleic acid based lateral flow assay (NALFA) with a limit of detection of 1 pmol of DNA. The total production duration of such an assay was successfully reduced from the currently known several days to just a few hours. The simplification and acceleration of the protocol make the method more accessible and practical for various applications. The developed method supports multiplexing, enabling the sim-ultaneous detection of up to six DNA targets. This multiplexing capability is a significant improve-ment over traditional line tests and offers more comprehensive diagnostic potential in a single assay. The approach significantly reduces the run time compared to traditional line tests, which enhances the efficiency of diagnostic procedures. The protein-free aspect of this assay minimizes the prevalent complications of cross-reactivity in immunoassays especially in cases of multiplexing. It is also demonstrated that the NALFA developed in this study is amplification-free and hence does not rely on specialized technicians, nor does it involve labour-intensive steps like DNA extraction and PCR processes. Overall, this study presents a robust, efficient, and highly sensitive platform for DNA or RNA detection, addressing several limitations of current methods documented in the literature. The advancements in sensitivity, cost reduction, production time, and multiplexing capabilities mark a substantial improvement, holding great potential for various applications in diagnostics, forensics, and molecular biology.

The advancement of urban scholarship and the effective addressing of urban environment challenges necessitate the adoption of sophisticated analytical methods. Urban scholars and policymakers need advanced analytical methods to tackle issues like gentrification, housing affordability, and urban sprawl. Predictive models are crucial in the realm of urban sciences, and hyperparameter tuning methods can significantly improve their accuracy and efficiency. Our study compares three such methods — Optuna, Random Search, and Grid Search — using a housing transaction dataset. We find that Optuna is not only 5.58 to 70.50 times faster than the other two methods when applied to Random Forest and Gradient Boosting Machine algorithms, but also achieves lower error values in key evaluation metrics on the test set, such as mean absolute error, mean squared error, mean absolute percentage error and root mean squared error.

PET imaging of bacterial infection could potentially provide added benefit for patient care by non-invasive means. [68Ga]Ga-desferrioxamine B – a radiolabelled siderophore – shows specific uptake by human-pathogenic bacteria like Staphylococcus aureus or Pseudomonas aeruginosa as well as sufficient serum stability for clinical application. Here, we provide data for automated production of [68Ga]Ga-desferrioxamine B on two different cassette based synthesis modules (Modular-Lab PharmTracer and GRP 3V) using commercially available cassettes together with an approved 68Ge/68Ga radionuclide generator. Quality control including determination of radiochemical purity as well as a system suitability test was set up via RP-HPLC on a C18 column. The two described production processes, using an acetic acid/acetate buffer system with ascorbic acid as a radiation scavenger for radiolabelling, yield ready-to-use formulations with sufficient activity yield. Batch data showed radiochemical purity of >95 % as determined by RP-HPLC and ITLC as well as excellent stability over 2 hours post production. Specifications for routine production were set up and validated with four master batches for each synthesis module. Based on this study, an academic clinical trial for imaging of bacterial infection was initiated. Both described synthesis methods enable reproducible, automated in-house production of [68Ga]Ga-desferrioxamine B for clinical application.

Human beings are positively or negatively affected by their environment. This effect has been a topic of interest for environmental psychologists, who have strived over years to understand the environmental attributes, which would be favourable to people in physical, mental, and psychological terms. The present study focusses on biophilic design, one of the popular theories in the architectural literature aimed to create high quality and liveable environments. The positive effects of biophilic design have been investigated from different perspectives and thus it has become a well-accepted approach in the relevant architectural literature. Accordingly, the present study aimed to investigate to what extent biophilic design principles were put into practice. In the context thereof, contemporary university structures were analysed within the framework of biophilic design principles. The results were suggestive of the fact that although biophilic elements were encountered in the design of these structures, they were not meant to be biophilic, nevertheless, there was an approach based on human-nature interaction. Accordingly, the principles of biophilic design were equivalent to the required parameters of a good design and that architects considered nature as an important design input.

Autoimmune diseases of the liver and biliary tract require timely and accurate diagnosis. This study evaluates the D-tek panel (D-Tek, Mons, Belgium) of 10 immunodot antigens for its effectiveness in diagnosing autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC). We retrospectively analysed serum samples from 111 patients who had undergone routine testing, including indirect immunofluorescence (IIF) and enzyme-linked immunosorbent assays (ELISA), to confirm or exclude autoimmune liver or biliary tract disease. The panel tested for M2/nPDC, M2/OGDC-E2, M2/BCOADC-E2, M2/PDC-E2, gp210, sp100, LKM1, LC1, SLA, and F-actin antigens. Results showed that all positive IIF+ELISA results were confirmed by the immunodot panel, except for two samples from patients never diagnosed with AIH. The immunodot test identified over 20 additional autoantibodies in samples initially negative by IIF, corroborated by laboratory imaging and medical history. The immunodot technique proved to be a quick, sensitive, and specific method with high overall accuracy. This study suggests that the immunodot technique may be an effective screening and confirmatory method for autoimmune liver diseases, potentially improving diagnostic efficiency and accuracy in clinical practice.

Long COVID (Post-Acute Sequelae of COVID-19, PASC) is a consequence of infection by SARS-CoV-2 that continues to disrupt the well-being of millions of affected individuals for many months beyond their first infection. While the exact mechanisms underlying PASC remain to be defined, hypotheses regarding the pathogenesis of Long COVID are varied and include (but are not limited to) dysregulated local or systemic inflammatory responses, autoimmune mechanisms, viral-induced hormonal imbalances and long-term persistence of virus and/or fragments of viral RNA or proteins. This review article is based on a comprehensive review of the wide range of symptoms most often observed in long COVID and an attempt to integrate that information into a plausible hypothesis for the pathogenesis of PASC. In particular, it is proposed that longterm dysregulation of the gut in response to viral persistence could lead to the myriad of symptoms observed in PASC.

This study measured the infrared spectra of secondary minerals in the oxidation zones of three types of copper ores: dioptase, malachite, and azurite, and detailedly assigned the peak positions of OH stretching vibrations and the origins of OH combination vibrations. Dioptase contains three types of water molecules with different orientations within its ring channels, which exhibit six kinds of OH stretching vibrations in the 3000-3600 cm-1 range, the bond length range is 2.652-2.887 Å. Among them, the 3443 cm-1 band shows strong near-infrared activity and combines with Si-O vibrations or OH bending vibrations in the structure, resulting in five combination vibration peaks in the 4000-5000 cm-1 range. Malachite contains two inequivalent hydroxyls in its structure, leading to two OH stretching vibrations in the high-frequency region, located at 3314 and 3402 cm-1, respectively. Azurite contains only one type of hydroxyl, thus only one characteristic OH stretching vibration is present, at 3424 cm-1. The OH stretching vibrations of malachite and azurite mainly combine with [CO3]2- vibrations or OH bending vibrations, leading to six and five combination peaks in the OH combination vibration region, respectively. By analyzing the combination of peak positions at 4341 cm-1 in the near-infrared spectrum, the merged OH bending vibration at 921 cm-1 in azurite was discovered. Spectroscopic research on secondary minerals can better provide a basis for ore exploration and geological remote sensing.

Metasurface constitutes one of the most promising technologies for holographic imaging; however, the work for terahertz (THz) metasurface holographic imaging is relatively limited. Here, we propose a THz dielectric geometric-propagation phase metasurface, which can operate dual-mode (reflection and transmission) and reconfigurable multifunctional holographic imaging. The dual-mode is realized by controlling the Fermi energy level (Ef) of the graphene integrated into the metasurface unit, and the reconfigurable three-channel holographic imaging in reflection or transmission mode are achieved by switching the feed polarization among left-handed circular polarization (LCP), right-handed circular polarization (RCP) and linear polarization (LP). The metasurface is designed based on the transmission mode, and a physical model for switching to the reflection mode is established. For the first time to the best of our knowledge, a reflection-transmission dynamic modulation THz holographic imaging metasurface has been developed. The holographic metasurface operates in transmission mode at Ef = 0.1 eV, and in reflection mode at Ef = 0.9 eV. Compared with recently published holographic imaging metasurfaces, the proposed metasurface offers the following advantages: high holographic efficiencies (42.5% to 49%), more holographic imaging channels, dynamic modulation dual-mode operations, and reconfigurability.

The current design of reinforcement learning methods demands exhaustive computing. Algorithms such as Deep Q-Network achieved outstanding results in the development of the area. However, the need for thousands of parameters and training episodes is still a problem. Thus, this document proposes a comparative analysis of the Q-Learning algorithm (the inception to create Deep Q Learning) and our proposed method termed M-Learning. The comparison among algorithms using Markov decision processes with delayed reward as a general testbench framework. Firstly, a full description of the main problems related to implementing Q-Learning, mainly about its multiple parameters. Then, the foundations of our proposed heuristic with its formulation and the whole algorithm were reported in detail. Finally, the methodology chosen to compare both algorithms was to train the algorithms in the Frozen Lake environment. The experimental results and an analysis of the best solutions found that our proposed algorithm highlights the differences in the number of episodes necessary and their standard variations. The code will be available on a GitHub repository once the paper is published.

Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related mortality worldwide and a major global health burden. The treatment of HCC has experienced a paradigm shift in the last few years, following the discovery of immunotherapy. However, despite the profound success of immunotherapy in other cancer types, their response in HCC remains unsatisfactory. Some of the reasons that can explain this poor response include the immunosuppressive microenvironment of HCC, the absence of reliable biomarkers for response, and drug resistance. Previous preclinical and clinical studies have highlighted the role of combination therapy in overcoming some of these hurdles. In this article, we discuss the benefit of combining immune checkpoint inhibitors (ICIs) with stereotactic body radiation therapy (SBRT) in HCC and shed light on promising clinical trials.

In this study, a decentralized incineration facility was evaluated over a three-year period, focusing on performance aspects such as burning rate, ash production, fuel and electricity consumption, and ash composition while processing animal by-products (ABP). The total cost for ABP incineration was determined to be 159 € per ton of ABP, with the major components being capital depreciation (42%), maintenance expenditures (26%), labor (18%), and transportation costs (9%). Liquified petroleum gas (LPG) consumption ranged from 3-7 kg per ton of ABP, while electricity use was between 15-20 kWh per ton of ABP incinerated. The incineration process generated 7-10% (by weight) ABP ash, which was characterized by high calcium and phosphorus content and low levels of hazardous trace elements. Leaching tests demonstrated the potential for recovering the alkaline supernatant for flue gas treatment and the phosphorus-rich slurry for fertilizer production. The findings suggest that energy recovery and valorization are crucial for minimizing operational costs and environmental impact, emphasizing the benefits of integrating advanced resource recovery techniques in ABP incineration facilities.

Zinc cobalt oxide-zinc hydroxide (ZnCo2O4-Zn(OH)2) microspheres were successfully fabricated on carbon cloth via a sample hydrothermal method. The surface morphology of these microspheres and their efficacy in degrading methyl violet were further modulated by varying the thermal annealing temperatures. The manipulation of thermal annealing temperatures was pivotal in adjusting the porosity of ZnCo2O4-Zn(OH)2 microspheres to amplify their photocatalytic performance. Various analytical techniques were utilized to evaluate the physical and chemical properties of the ZnCo2O4-Zn(OH)2 microspheres, including field-emission scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction, field-emission transmission electron microscopy, X-ray photoelectron spectroscopy, and UV-vis spectroscopy. Compared to untreated ZnCo2O4-Zn(OH)2 microspheres, those subjected to thermal annealing exhibited increased specific surface area and light absorption capacity, rendering them highly effective photocatalysts under UVC light exposure. Subsequent studies have confirmed the superior performance of ZnCo2O4-Zn(OH)2 microspheres as a reusable photocatalyst for degrading methyl violet and tetracycline. Additionally, trapping experiments during the photodegradation process involving ZnCo2O4-Zn(OH)2 microspheres have identified hydroxyl radicals (·OH) and superoxide radicals (·O2–) as the primary reactive species.

Tungsten balls with sub-100-μm diameter can function as probe tips for micro-coordinate measuring machines (CMMs) to measure ultraprecise workpieces such as ceramic bearings with a high aspect ratio. A high-precision measuring system was proposed to evaluate the roundness error of the self-made tungsten ball tips. The principles and mathematical models of the measuring system are illustrated, and the fabrication principle of tungsten balls is introduced. An analysis was conducted on the maximum allowable contact force and bending strength of the tungsten ball tips, and the elastic mechanism was designed based on the analysis. A ruby probe with a sphericity error of 130 nm (A-5003-0577, Renishaw Corporation) used as a reference sphere was measured to verify the system's effectiveness. Repeated measurement experiments were performed for two tungsten ball tips. The results show the roundness error of the tungsten ball-A is between 568.3 and 586.2 nm with a standard deviation of 6.6 nm while the tungsten ball-B’s roundness error is between 898.5 and 958.0 nm with a standard deviation of 19.7 nm. The uncertainty is calculated as 125.8 nm. The developed system can stably measure the roundness of the tungsten ball tips.

TRPS1 (Tricho-rhino-phalangeal syndrome 1), is a GATA transcriptional activator gene encoding for a protein used as a sensitive immunohistochemical marker of breast carcinomas. In dermatopathology, TRPS1 is used as a marker of mammary Paget’s disease, and is also expressed by a variety of primary cutaneous tumors, mostly of adnexal origin. So far, limited data exist on the expression of TRPS1 in metastatic skin tumors. We studied the immunohistochemical expression of TRPS1 in 72 cutaneous metastatic tumors from the breast (n: 19) and other origins (n: 53) in order to assess its diagnostic usefulness. The intensity of TRPS1 immunostaining was expressed as a histoscore: product of percentage of positive cells (scored semi-quantitatively 0-4) and staining intensity (scored 0-3). In normal skin, nuclear TRPS1 expression was observed in cells of adnexal structures (pilosebaceous follicles and sweat glands). Eighteen (18/19, 94.7%) metastatic breast carcinomas showed diffuse and strong TRPS1 positivity (histoscore 12). Lower reactivity was found in some other metastases, including from the lung (11/22), the female genital tract (3/4), the kidney (2/4), whereas most (20/22) metastases from the digestive system and peritoneum, along with a case of metastatic prostate carcinoma, were negative. These results suggest that a high histoscore for TRPS1 is in favor of the mammary origin of a metastatic cutaneous carcinoma. Although TRPS1 is not absolutely specific or sensitive of a particular primary, we believe it can be added to a panel of other markers when investigating the origin of a cutaneous metastasis, namely when this is the first manifestation of the neoplastic disease.

Bagaza virus (BAGV) is a flavivirus that affects avian species. In Europe, it was detected for the first time in Spain in 2010, exhibiting high genetic relatedness to Israel turkey meningoencephalomyelitis virus (ITMV) isolates from Israel. After a period of epidemiological silence, BAGV re-emerged causing important outbreaks in 2019 and 2021. This study aims to characterize the newly detected strains and to elucidate if these recent outbreaks were caused by single or different virus introductions into the country. Hence, Spanish BAGV isolates from 2019 (n=3) and 2021 (n=1) outbreaks, obtained from red-legged partridges in Cádiz, were sequenced and further characterized. The phylogenetic analyses showed that they belong to two different genotypes: BAGV Genotype 1 and 2. Isolates from 2019 belong to BAGV-Genotype 1, closely related to isolates from Senegal, where BAGV has been circulating since decades. In turn, the 2021 isolate belong to BAGV-Genotype 2, closely related to those detected in Spain in 2010. Additionally, the comparison of the viral polyproteins of several BAGV isolates from both genotypes support and confirm the phylogenetic findings. To conclude, BAGV has been introduced into Spain in at least three independent occasions, with alternating genetic clades, thus confirming that BAGV is able to occasionally reach southern Europe.

The properties of coatings obtained using two surface preparation methods were compared: heating and etching by ion bombardment with plasma generation by arc evaporators and heating and etching by a glow discharge. A Ti-TiN-(Ti,Cr,Al)N coating was deposited. The use of a glow discharge provides better resistance of the coating to destruction during the scratch test and wear resistance of metal-cutting tools when turning steel. As the cutting speed increases, the advantage in wear resistance of the coating deposited using a glow discharge increases. During the process of heating and etching by ion bombardment with metal ions, a nanolayer rich in cobalt and tooling elements (iron, molybdenum) is formed in the area of the interface of the coating and the carbide substrate. When heated and etched by a glow discharge, such a layer does not form. When using both methods, there is identical diffusion of tungsten into the coating and diffusion of chromium and possibly titanium into the substrate. Thus, the glow discharge heating and etching method can be effectively used in the process of PVD coating deposition.

AI tools provide individualized learning experiences tailored to specific language learners' requirements. Artificial intelligence-driven programs can customize lessons, exercises, and feedback by evaluating a learner's progress and determining strengths and shortcomings. This individualized method aids students in concentrating on their areas of weakness, thus improving their total language competency. This narrative literature review aims to gather relevant literature discussing AI tools as supplementary support in aiding a learner's language acquisition. Relevant studies stated that there are a lot of chances to improve learning outcomes when AI tools are used in language acquisition. Teachers who want to give their students more resources and help should consider including these tools in their lessons. To preserve the interpersonal and cultural components of language learning, it is imperative to strike a balance between the application of AI and conventional teaching techniques. AI tools are always accessible, providing assistance to learners whenever needed. This is especially helpful for individuals with unpredictable schedules or restricted access to conventional language learning materials.

Semi-autonomous vehicles (AVs) enable drivers to engage in non-driving tasks but require them to be ready to take control during critical situations. This "out-of-the-loop" problem demands a quick transition to active information processing, raising safety concerns and anxiety. Multimodal signals in AVs aim to deliver take-over requests and facilitate driver-vehicle cooperation. However, the effectiveness of auditory, visual, or combined signals in improving situational awareness and reaction time for safe maneuvering remains unclear. This study investigates how signal modalities affect driver’s behavior using virtual reality (VR). We measured drivers’ reaction times from signal onset to take-over response and gaze dwell time for situational awareness across twelve critical events. Furthermore, we assessed self-reported anxiety and trust levels using the Autonomous Vehicle Acceptance Model questionnaire. Results showed visual signals significantly reduced reaction times, whereas auditory signals did not. Additionally, any warning signal, together with seeing driving hazards, increased successful maneuvering. Analysis of gaze dwell time on driving hazards revealed that audio and visual signals improved situational awareness. Lastly, warning signals reduced anxiety and increased trust. These results highlight the distinct effectiveness of signal modalities in improving driver reaction times, situational awareness, and perceived safety, mitigating the “out-of-the-loop” problem and fostering human-vehicle cooperation.

This article presents a novel analysis of Indus Seal M-282 [1] excavated from Mohenjo-Daro, a key Indus Valley Civilization site. Utilizing the proposed Sindhu Prakrit alphabet, the study investigates the relationship between the seal's iconography and the inscribed text. By examining the potential for a close correlation between these elements, the analysis aims to decipher the meaning embedded within the seal's motifs, potentially offering new insights into Indus Valley communication and symbolism.

To address the problems of lining cracking and spalling of tunnel structures in coastal areas under the influence of special geologic conditions, environmental loading, and the coupling effect of chemical erosion effects, hybrid fibers were introduced to fly ash concrete in this study. The working performance, compressive strength, split tensile strength, and flexural strength of the hybrid fiber fly ash concrete were tested.The NEL chloride diffusion coefficient under steady-state conditions and the durability test for resistance to sulfate corrosion were carried out. Thus, in-depth analyses of the comprehensive performance of the hybrid fiber fly ash concrete used for tunnel lining were carried out and the damage mechanism were explored. The results showed that the hybrid fiber fly ash concrete exhibited higher strength compared to the control group concrete. However, when the fibers exceeded a certain dosage, the reduction in the working properties of the concrete structure led to the creation of larger pores in the matrix structure, which in turn affected the mechanical properties of the concrete. The most significant reduction in NEL chloride diffusion coefficient was observed when both steel fibers and coconut fibers were added at 1.0 % volumetric parameter, compared to the control group. The apparent state and compressive strength after sulfate corrosion were also minimally affected. This study ensured that the mechanical properties of the concrete were improved and also substantially improved the corrosion resistance of the matrix, providing a scientific basis for the performance improvement of tunnel lining concrete, confirming that steel-coconut fibers hybrid fiber fly ash concrete has a great potential to improve the structural load bearing capacity and durability, and may provide theoretical support for the continued use of tunneling projects and construction processes.

Age diversity in the workplace is a growing challenge. This study aimed to assess work ability among Family and Community Nurses (FCNs) in a large Local Health Authority (LHA) in Tuscany, Italy. The Work Ability Index (WAI) was administered to 178 FCNs, along with demographic and occupational data. Results showed a significant negative correlation between chronological age and WAI, indicating decreasing work ability with age. Moreover, work setting, educational attainment, and health conditions influenced work ability. Nurses working in home settings and those with higher educational levels reported better work ability. A high prevalence of health conditions, particularly musculoskeletal disorders, was observed. These findings highlight the need for targeted interventions to support FCNs' work ability and address age-related challenges. This study provides a foundation for developing strategies to optimize the nursing workforce and ensure high-quality care delivery.

Autoimmune bullous diseases (AIBDs) are a group of conditions marked by the formation of blisters and erosions on the skin and mucous membranes. Knowing that, most of the AIBDs are severe and resistant to treatment, we decided to look upon the nutritional aspect as a light for the future for both - patients and clinicians. In this review, we would like to summarize the evidence of the role of nutrition in pathogenesis and treatment of the following AIBDs: i) pemphigus, ii) bullous pemphigoid and mucous membrane pemphigoid, iii) dermatitis herpetiformis, and iv) epidermolysis bullosa aqusita.

Polyetheretherketone is a promising material for implants due to its good mechanical properties and excellent biocompatibility. Its accessibility to a wide range of applications is facilitated by the ability to process it with an easy-to-use manufacturing process such as Fused Filament Fabrication. The elimination of disadvantages associated with the manufacturing process, such as a poor surface quality, is a main challenge to deal with. As part of the mass finishing process, centrifugal disc finishing has demonstrated good results in surface optimization, making it a promising candidate for post-processing of additively manufactured parts. The objective of this study is to identify the key parameters of the centrifugal disc finishing process on the waviness of additively manufactured PEEK specimen, which has not been investigated yet. Waviness of the specimen was investigated by means of confocal laser scanning microscopy (CLSM), while weight loss was additionally tracked. Six parameters were investigated: type, amount and speed of media, use of compound, amount of water and time. Type of media, time and speed were found to significantly influence waviness reduction and weight loss. Surface electron microscopy images demonstrated the additional effects of deburring and corner rounding. Results on previous studies with specimens made of metal showed similar results. Further investigation is required to optimise waviness reduction and polish parts in a second post-processing step.

The Olympic Games are a sporting event and a catalyst for urban development in the host city. In this study, we utilized remote sensing and GIS techniques to examine the impact of the Olympic infrastructure on the surface temperature of urban areas. Using Landsat Series Collection 2 Tier 1 Level 2 data, cloud computing, and Google Earth Engine (GEE) methods, this study examines the effects of various Olympic Games facility urban planning in different historical moments and location typologies: monocentric, polycentric, peripheric and clustered Olympic ring. The GEE code applies to the Olympic Games from Paris’24 to Munich’72. However, this paper focuses specifically on the representative cases of Paris’24, Tokyo’20, Rio’16, Beijing’08, Sydney’00, Barcelona’92, Seoul’88, and Montreal’76. The study is not only concerned with obtaining absolute Land Surface Temperatures (LST), but rather the relative influence of mega-event infrastructures on mitigating or increasing the urban heat. As such, locally Normalized Land Surface Temperature (NLST) was utilized for this purpose. In some cities (Paris, Tokyo, Beijing, and Barcelona), it is identified that Olympic planning has resulted in the development of green spaces, creating "green spots" that contribute to lower-than-average temperatures. However, it should be noted that there is a significant variation in temperature within intensely built-up areas, such as Olympic villages and the surrounding areas of the Olympic stadium, which can become “hotspots”. Therefore, it is important to acknowledge that different planning typologies of Olympic infrastructure can have varying impacts on city heat islands, with the polycentric and clustered Olympic ring typologies displaying a mitigating effect. This research contributes to a cloud computing method that can be updated for future Olympic Games or adapted for other mega-events and utilizes a widely available remote sensing data source to study a specific urban planning context.

Hyperspectral small target detection (HSTD) is a promising pixel-level detection task. However, due to the low contrast and imbalance number between the target and background spatially and high dimensions spectrally, it is a challenging one. To address these issues, this work proposes a representation learning-based graph and generative network for hyperspectral small target detection. The model builds a fusion network through frequency representation for HSTD, where the novel architecture incorporates irregular topological data and the spatial-spectral feature to improve its representation ability. Firstly, a graph convolutional network (GCN) module better models the non-local topological relationship between samples to represent the hyperspectral scene’s underlying data structure. The mini-batch-training pattern of the GCN decreases the high computational cost of building an adjacency matrix for high-dimensional data sets. In parallel, the generative model enhances the differentiation reconstruction and the deep feature representation ability with respect to the target spectral signature. Finally, a fusion module compensates for the extracted different types of HS features and integrates their complementary merits for hyperspectral data interpretation while increasing detection and background suppression capabilities. Experiments on different hyperspectral data sets demonstrate the advantages of the proposed architecture.

Sandblasting materials used for dental restoration is a valuable preconditioning technique enhancing the physical properties and promotes osseointegration and cell adhesion. Ti medical grade 4 and Ti6Al4V were blasted with a series of various naturally occurring and synthetically produced spraying materials of controlled granulometry, at precise spraying duration and spraying pressure, and the results were analyzed in terms of the obtained surface roughness and by SEM analysis. It was found that in all cases, regardless of the spraying material or working conditions, the roughness profile achieved is a uniformly distributed one. A reduction in the blasting pressure by half led to a decrease in the roughness between 30 and 35%. The use of glass balls as blasting material led to decreased roughness and a more uniformly distributed roughness values for Ti as well as for Ti6Al4V regardless of spraying duration or applied pressure comparing to other spraying materials, and blasting with olivine led to increased, as well as uniformly distributed values, and hence the conclusion that one may control the roughness size by choosing one or another from the above materials, without the need of changing any other operating parameters. In the case of Ti, the achieved roughness is greater than in the case of Ti4Al6V, irrelevant of the blasting material, the differences being smaller the softer the sandblasting material due to the fact that Ti alloys have better mechanical properties and increased hardness comparing to pure Ti. SEM analysis showed that the use of sintered hydroxyapatite as an additive to the blasting material does not necessarily lead to a substantial deposition of hydroxyapatite on the substrate materials, only traces of it being identified during the analysis.

Surfactant proteins A and D (SP-A and SP-D) belong to the collectin subfamily of C-type oligomeric lectins. They are pattern-recognition molecules (PRM), able to recognise pathogen- or dan-ger-associated molecular patterns (PAMP, DAMP) in the presence of Ca2+ cations. That property enables opsonisation or agglutination of non-self or altered/abnormal self-cells, and contributes to their clearance. Like other collectins, SP-A and SP-D are characterised by the presence of four distinct domains: a cysteine-rich domain (at N-terminus), a collagen-like region, an α-helical neck domain and a globular carbohydrate-recognition domain (CRD) (at C-terminus). Pulmonary sur-factant is a lipoprotein complex, preventing alveolar collapse by reducing surface tension at the air-liquid interface. SP-A and SP-D, produced by type II alveolar epithelial cells, and Clara cells, are not only pattern-recognition molecules but also contribute to the surfactant structure and homeo-stasis. Moreover, they are expressed in a variety of extrapulmonary sites where they are involved in local immunity. The term “cancer” includes a variety of diseases: tumours start from uncontrolled growth of abnormal cells in any tissue which may further spread to other sites of the body. Many cancers are incurable, difficult to diagnose and often fatal. This short review summarises anti- and pro-tumourigenic associations of SP-A and SP-D as well as perspectives of their usefulness in cancer diagnosis and therapy.

Hemophagocytic lymphohistiocytosis (HLH) is a serious haematologic condition that can be re-lated to various diseases, including tuberculosis (TB). The patient is a previously healthy 26-years-old man, originally from Western Africa, admitted to hospital for fever and weight loss. Given the results of computed tomography (CT) scan, ocular examination and microbiologic tests, a miliary TB with pulmonary, lymph nodal and ocular involvement was diagnosed. Following introduction of antitubercular treatment (ATT) an increase in inflammation indexes and severe pancytopenia were observed; at this point the patient presented six of eight diagnostic criteria for HLH and the diagnosis of HLH secondary to TB was raised. Therefore, HLH treatment with high dose of dexamethasone was started with a good clinical response. We performed a literature re-view of TB-related HLH, which shows a high mortality rate; ATT is necessary to ensure patient survival to remove the antigenic driver. Our patients developed HLH after initiation of ATT as a paradoxical reaction, that may be linked to the release of antigens due to the bactericidal effect of ATT.

Let S be a Fermat surface of degree 5 and let k be an algebraically closed field of characteristic p = 2. We give a fibration ƒ: S → P with upper limit 1 and lower limit k, and investigate the geometric properties of fiber of ƒ. Furthermore, we investigate the fibration-preserving automorphisms group Aut_{Pwith upper limit 1 and lower limit k}(S) of ƒ. We obtain that Aut_{Pwith upper limit 1 and lower limit k}(S) is a p-group of order 256.

Predictive maintenance technologies have emerged as a transformative force in retail supply chain management, offering the potential to significantly enhance operational efficiency, reduce costs, and improve customer satisfaction. This study explores the implementation and impact of predictive maintenance within the retail sector, focusing on its benefits, challenges, technological tools, and future directions. The findings indicate that predictive maintenance enables a proactive approach to equipment management, leading to substantial reductions in downtime and maintenance costs, extended equipment lifespan, and enhanced sustainability through reduced energy consumption and waste. However, the adoption of these technologies is not without challenges. High initial costs, the need for specialized skills in data analytics and IoT, issues with data quality and reliability, organizational resistance, and cybersecurity concerns present significant barriers to successful implementation. Technological tools such as IoT sensors, data analytics platforms, machine learning algorithms, and digital twins are crucial for the effective functioning of predictive maintenance systems, providing real-time data monitoring and analysis that improve decision-making and maintenance planning. The study also highlights promising future trends, including advancements in AI, machine learning, IoT, and blockchain technologies, which are expected to further enhance predictive maintenance capabilities. To fully realize the potential of predictive maintenance, companies must address the identified challenges, invest in workforce development, and implement robust data security measures. Future research should focus on exploring these advancements, understanding the broader environmental impacts, and conducting cross-industry analyses to identify best practices. Overall, while predictive maintenance offers substantial benefits, its successful integration requires a nuanced approach that balances technological innovation with strategic and operational considerations.

In this paper we introduce the Adomian decomposition method for a class of first order fuzzy dynamic equations on arbitrary time scales for existence of solutions. The results are provided with suitable numerical examples.

This paper proposes an unusual method for the dissemination of geological sciences and the promotion of geotourism: the scientific documentary, where a representative itinerary of geological and geomorphological evolution of this portion of the Apennines was presented. The considerations that led to the identification of the geological route proposed to the editorial staff of FOCUS TV are presented in detail. At each stop there was an explanation by academic professors and researchers, mainly from the Geology Division of the University of Camerino (MC), who explained in detail the outcrops. During the episode, insights were also given into the anthropogenic frequentation of the epigean caves in Frasassi (AN), ancient places of frequentation and worship thanks to their suggestiveness and the sense of sublime that they can elicit. In addition to the illustration of the individual stops, the article offers further insights into the geomorphology of the most important geosites depicted, all of which are in nature parks or protected areas and characterized by a high landscape value. The result was the production of an episode of the television program 'Geological Wonders of Italy: The Marche and Umbria Regions', which was broadcast in October 2022 by the Italian national Mediaset group.

The human malaria parasite, Plasmodium falciparum, accounts for more than 500,000 deaths worldwide per year. From 2000 to 2019, the malaria global death toll fell from 864,000 to 576,000 deaths; however, progress on reducing this toll has since slowed, with the COVID-19 pandemic contributing to an increase in the mortality rate since 2020. The emergence of widespread resistance in P. falciparum to first-line treatment drugs has highlighted the need for new antimalarial drugs, and smarter approaches, including better combination therapies and mass drug administration. Nevertheless, recent successes of the first malaria vaccine (RTS,S/AS01) and the approval of a second (R21/MM), have renewed the promise of widely applicable vaccines in the future. Since 2015, the Eastern Mediterranean Region has experienced an overall increase in malaria cases and deaths. In the Arabian Peninsula, while most of the Gulf Cooperation Council (GCC) countries have been declared free of indigenous malaria (Bahrain, Kuwait, Qatar, and the United Arab Emirates), malaria is still endemic in two GCC countries (Saudi Arabia and Oman) and its neighbors (Yemen). Furthermore, a number of factors threaten malaria control in this region, at the level of the parasite (antimalarial drug resistance), the mosquito (the emergence of highly invasive species), the environment (climate change and increasing average temperatures), and society (imported malaria). In this review, we assess the current world-wide status of malaria in terms of public health, prevention and treatment, before providing an Arabian regional perspective, with a critical evaluation of the malaria situation in the GCC countries.

This study investigates the moderating role of information asymmetry in shaping the effect of environmental sustainability reporting on the firm value of listed manufacturing companies in Nigeria. Utilizing an ex-post facto research design, the study draws on a stratified sample of 29 manufacturing firms from a population of 43 listed on the Nigerian Exchange as of December 31, 2022. Spanning from 2007 to 2022, the study collects secondary data from annual reports, Nigerian All Share Index reports, meristem securities and register platform Admin platform and sustainability reports. Employing descriptive and inferential statistics, along with multiple regression techniques, the analysis considers Firm value as the dependent variable, Environmental sustainability reporting as independent variables, Information asymmetry (IA) as the moderating variable and Equity ratio, Return on asset and Leverage as control variables. Results indicate that information asymmetry shows a negative and significant effect on the relationship between environmental sustainability reporting and firm value. The study concluded that information asymmetry impacts firm value despite environmental disclosure efforts. The study recommends that Nigerian manufacturing companies should engage in comprehensive disclosure practices to enhance transparency and address information asymmetry through adequate stakeholder engagement. The study’s findings emphasized the need for Nigerian policy makers to enhance regulations on environmental sustainability reporting. By implementing stricter disclosure laws and standards, policy can reduce information asymmetry and foster a more transparent business environment. This could attract foreign investment and demonstrate Nigeria’s commitment to sustainable practices. Furthermore, the study also highlights the importance of transparency in maintaining stakeholder trust. Improved disclosure practices can increase public trust in the manufacturing sector, promoting corporate responsibility. This heightened transparency benefits investors and the broader community, ensuring companies are accountable for their environmental impacts, ultimately leading to better environmental stewardship and community welfare.

This research article provides an unconditional proof of an inequality proposed by \textit{Srinivasa Ramanujan} involving the Prime Counting Function $\pi(x)$, \begin{align*} (\pi(x))^{2}<\frac{ex}{\log x}\pi\left(\frac{x}{e}\right) \end{align*} for every real $x\geq \exp(547)$, using specific order estimates of the \textit{Mertens Function}, $M(x)$. The proof primarily hinges upon investigating the underlying relation between $M(x)$ and the \textit{Second Chebyshev Function}, $\psi(x)$, in addition to applying the meromorphic properties of the \textit{Riemann Zeta Function}, $\zeta(s)$ with an intention of deriving an improved approximation for $\pi(x)$.

African swine fever (ASF) continues to spread in Africa, Europe, Asia, and the island of Hispaniola increasing the need to develop more streamlined and highly efficient surveillance and diagnostic capabilities. One way to achieve this is by further optimization of already established standard operating procedures to remove bottlenecks for high-throughput screening. Real-time polymerase chain reaction (RT-PCR) is the most sensitive and specific assay available for the early detection of ASF, but it requires high quality nucleic acid extracted from the samples. Whole blood from live pigs and spleen tissue from dead pigs are the preferred samples for ASF RT-PCR. Whole blood can be used as is in nucleic acid extraction, but spleen tissues require an additional homogenization step. In this study, we compared the homogenates and swabs prepared from 52 spleen samples collected from pigs experimentally inoculated with highly and moderately virulent ASF virus strains. The results show that not only are the spleen swabs more sensitive when executed with a low-cell-count nucleic acid extraction procedure followed by RT-PCR assays, they also increase the ability to isolate ASFV from positive spleen samples. Swabbing is a convenient, simpler, and less time-consuming alternative to tissue homogenization. Hence, we recommend spleen swabs over tissue homogenates for high-throughput detection of ASFV by real-time PCR.

This study proposes and validates a novel combustion control system for Oil-Fired Boilers aimed at reducing air pollutant emissions through flame image prediction. The proposed system is easily applicable to existing ships. Traditional proportional combustion control systems supply fuel and air at fixed ratios according to the set steam load, without considering the emission of air pollutants. To address this, a stable and immediate control system is proposed, which adjusts the air supply to modify the combustion state. The combustion control system utilizes oxygen concentration predictions from flame images via SEF+SVM as control inputs, and applies Internal Model Control (IMC)-based Proportional-Integral (PI) control for real-time combustion control. Due to the complexity of modeling the image-based system, IMC parameter tuning through experimentation is essential for achieving effective control performance. Experiments conducted on a 3000 kg/h marine oil-fired boiler in actual operation optimized the controller parameters for stability and responsiveness, and validated their effectiveness. The results demonstrate the potential of the proposed system to improve combustion efficiency and reduce emissions of air pollutants. This study provides a feasible and effective solution for enhancing the environmental performance of marine oil-fired boilers. Given its ease of application to existing ships, it is expected to contribute to sustainable air pollution reduction across the maritime environment.

This case study examines the impact of Machico City Airport expansion on sus-tainable tourism. It aims to identify the key effects on the environment, local economy, and community, and provides recommendations for mitigating negative impacts while promoting sustainable development. The study emphasizes adopting sustainable tourism practices to protect Machico's biodiversity and natural resources, drawing from the ECOS MACHICO project. It highlights the importance of environmental education for tourists, residents, and tour operators. Community engagement emerges as pivotal, advocating for inclusive plan-ning that incorporates local perspectives. The multifaceted implications of airport expansion on Machico's socio-economic fabric are explored, balancing positive and negative effects on residents and local businesses. Diversifying tourism offerings beyond mass tourism is advocated, with a focus on preserving local traditions and promoting authentic cultural experiences. In summary, the research provides a foundation for sustainable tourism devel-opment, offering strategies applicable to similar destinations. The study's implications extend to understanding broader impacts of airport expansions, presenting avenues for further research. The proposed strategies serve as a blueprint for destinations fac-ing analogous challenges, promoting enduring socio-economic and environmental well-being.

This paper comprehensively explores the integration of cloud computing and advanced recommendation systems, emphasizing their pivotal roles in enhancing user experiences and operational efficiencies across digital platforms. It reviews the evolution of recommendation algorithms, highlighting their application in diverse domains such as e-commerce and media. The study evaluates the performance of advanced models like UniLLMRec against traditional counterparts using datasets from news and e-commerce domains. Additionally, the paper discusses the infrastructure architecture of cloud computing, demonstrating its capability to support scalable and efficient data processing. Through experimental insights and methodology, the research underscores the transformative impact of cloud technologies on optimizing recommendation system performance, thereby advancing digital engagement and competitiveness.

Neurodevelopmental disorders are characterised by an amalgam of genetic and epigenetic faults implicating neuronal protein-related loss-of-function and gain-of-function respectively, hence their inclusion into the category of complex diseases. Neurodevelopmental disorders are regarded as autism spectrum disorder due to this reason; that the risk factors and phenotype constitute a spectrum of faults and protein overactivity. One example of an epigenetic factor leading to the onset of neurodevelopmental delays constitutes a set of immune response-based dysregulations, as well as the excessive growth of the adaptive immune memory of the foetus or the baby following significant infectious disease during pregnancy, as well as in babies aged 0-2, given the existence of profound links between developmental immunity and developmental neurology. Given that genetic information very likely represents a form of energy, the intake of excessive pathogen-related information may transiently overload the adaptive immune memory similarly to the manner functional pathogens do whilst inducing significant illness, and if events as such occur during important stages of neuro-immunological development, then there could often be irreversible effects upon the rate of development in neurological networks that normally have a major importance in the modulation of the related cognitive and behavioural phenotype. The full extent of evidence may only be obtained via a thorough study of the applications of physical laws into biology and medicine, given the foundational role of the physical matter in the development and maintenance of life. A common misconception is that neurodevelopmental delays are characterised solely by an accumulation of protein loss-of-function incidences in the central nervous system area, rather than a disruption of neuronal region developmental rates. For example, an overexpression of neuronal proteins related to cognition factors that is accompanied by an underexpression of proteins related to social behaviour is phenotypically manifested in people with sharper rational thinking and poorer communication skills, with an impact on the abilities of decision-making as well, and this tends to be regarded as a classical example of the clinical manifestation of neurodevelopmental delays. More severe forms of autism spectrum disorder tend to implicate a more generalistic impact upon the developmental rates of key human behaviours, including those related with the development and maintenance of social and intimate relationships. Likewise, more severe implications upon regular developmental rates tend to bring a major impact upon the healthy function of related functions. As a result, lower functioning forms of neurodevelopmental delays bring fresh concerns with regards to a possible uncanny increase of incidences of deviated sexuality during years of adulthood, and in the worst cases, such deviations may lead to the planning and development of criminal activity, particularly in individuals who are or become prone to breaking the moral code that established the civilised society. What holds the concerns valid is the exponential increase in the number of lower functioning autism cases throughout the world and the major signs that such an increase will continue with a full force. One major solution to this potential future problem would be a much higher investment into awareness of the exact genetic and environmental factors that directly or indirectly result in the onset of lower-functioning autism and of the current research efforts to develop the matching support for people found in situations as such. The most important aim of future research with regards to such a scenario would be a separation of disease and disability with choices made to step into more severe forms of disease and into areas that are outside of the established moral circle.

Logistic Regression and Random Forest are used to identify risk factors that influence traffic accident fatalities in the United Kingdom. The mean decrease accuracy was used to measure variable importance. The speed limit, police attendance and quarter had an increasing influence on accident fatalities. They had a mean decrease of 102.1669, 221.5322, and 120.894 respectively. The speed limit, had a parameter estimate of 0.0046902 and a standard deviation of 0.0004875. Light Conditions: Night had a parameter estimate of 1.2657635 and a standard deviation of 0.0118409. Road Type Round About had a parameter estimate of -0.4055796 and a standard deviation of 0.0210848. Police Attendance classified as Yes had a parameter of 0.8546232 and a standard deviation of 0.0151043. The best predictors were speed limit, police attendance and quarter since they had p values that were less than 0.05. The findings of the study indicated that logistic Regression had a higher accuracy rate 79.85% as compared to 64.00% for Random Forest. A split test was used and a standard deviation of 0.0010486 was obtained for the Logistic Regression model.

High-precision displacement sensing has been widely used across from both scientific researches and industrial applications. The recent interests in developing micro-opto-electro-mechanical systems (MOEMS) have given rise to an excellent platform for miniaturized displacement sensors. Advancement in this field during past years is now yielding integrated high-precision sensors which show great potential in applications ranging from photoacoustic spectroscopy to high-precision positioning and automation. In this review, we briefly summarize different techniques for high-precision displacement sensing based on MOEMS, and discuss the challenges for future improvement.