This article explores the use of vegetation indices (VIs) in remote sensing for estimating standing wood volume and volume increments in forest ecosystems. The study investigates the correlations between various VIs and wood volume across different forest stand age classes, focusing on the effectiveness of commonly used indices such as Squared Ratio Simple Red Edge (SQSR) and Red-Edge Ratio Vegetation Index (RERVI), as well as other typical indicators including Enhanced Vegetation Index (EVI), Red-Edge EVI (RE-EVI), and Green Normalized Difference Vegetation Index (GNDVI). Additionally, the analysis considers a pair of indicators based on blue and near-infrared channels, resembling the Blue-normalized Difference Vegetation Index (BNDVI). The research reveals that quadratic and power-law models of SQSR and RERVI demonstrate higher correlations (>0.40) with wood volume, especially in younger forest stands (>0.80). Furthermore, the study highlights the potential of NDII and NDWI indices for estimating volume increments in certain classes of forest stands (0.70). However, correlations vary across different forest stand classes, suggesting the need for further investigation into the reliability of VIs for monitoring wood volume and volume increments in forest ecosystems. Overall, this research contributes to the understanding of the applicability of VIs in remote sensing for forest management and ecosystem monitoring.

This review discusses approaches and implementations of flowrate sensing and measurement in smart inhalers for effective respiratory disease management. It highlights the importance of compliance with proper inhaling techniques and consistent adherence for managing respiratory conditions. Methods and relevant commercial and prototype research-type devices for sensing and measuring inhalation flowrate in smart inhalers are studied and compared. The study argues that utilisation of acoustic analysis and air pressure sensing is a promising approach to detect and evaluate the inhaling action ultimately allowing to improve the treatment outcomes and life quality of patients with respiratory diseases.

With the widespread of embedded sensing capabilities of mobile devices, there has been unprecedented development of context-aware solutions. This allows the proliferation of various intelligent applications such as those for remote health and lifestyle monitoring, intelligent personalized services, etc. However, activity context recognition based on multivariate time series signals obtained from mobile devices in unconstrained conditions is naturally prone to imbalance class problems. This means that recognition models tend to predict classes with the majority number of samples whilst ignoring classes with the least number of samples, resulting in poor generalization. To address this problem, we propose to augment the time series signals from inertia sensors with signals from ambient sensing to train deep convolutional neural networks (DCNN) models. DCNN provides the characteristics that capture local dependency and scale invariance of these combined sensor signals. Consequently, we developed a DCNN model using only inertial sensor signals and then developed another model that combined signals from both inertia and ambient sensors aiming to investigate the class imbalance problem by improving the performance of the recognition model. Evaluation and analysis of the proposed system using data with imbalanced classes show that the system achieved better recognition accuracy when data from inertial sensors are combined with those from ambient sensors such as environment noise level and illumination, with an overall improvement of 5.3% accuracy.

During the last decade, smart materials have increasingly impacted on several niches, among which that of one-off/limited edition experimental fashion. Thanks to their performativity, due to the implementation of Smart Materials Systems, they have reached indeed catwalks as well as museums and galleries. As boundaries between what-is-art and what traditionally was not supposed to be art are now turning into osmotic membranes, zooming on how smart materials are highly contributing to outline the new creative landscape can provide with interesting and compelling issues. Introducing three different areas of experimental fashion, named Multi-sensory dresses, Empathic dresses, and Bio-smart dresses and accessories, respectively covering the world of in-Lab experiments and design collaborations in relation to the application of advanced smart materials systems, the article discuss some of the implications in term of Design Thinking and Design Aesthetics.

Biomimetic stimuli-responsive materials can respond to various external stimuli in the form of structural or morphological transformations by actively or passively converting input energy into mechanical energy. They are the core element of soft actuators for typical smart devices like soft robots, artificial muscles, intelligent sensors and nanogenerators. While significant progresses have been made in bioinspired stimuli-responsive materials, they have not yet achieved the remarkable properties in biological systems. In this review, we will discuss recent advances in biomimetic stimuli-responsive materials that are instrumental for soft actuators. Different stimuli-responsive principles for soft actuators are firstly discussed, including fluidic, electrical, thermal, magnetic, light and chemical stimuli. We further summarize the state-of-the-art stimuli-responsive materials for soft actuators and explore the advantages and disadvantages of using electroactive polymers, magnetic soft composites, hydrogels, liquid crystal elastomers, shape memory alloys and chemical-responsive materials. Finally, we provide a critical outlook on the field of stimuli-responsive soft actuators, and emphasize the challenges in the process of their implementation to various industries.

The rapid pace of urbanization, coupled with the growing need for environmental sustainability and technological innovation, has brought smart city initiatives to the forefront of global urban development. This paper provides a comparative analysis of smart city policies from leading cities such as Oslo, Zurich, and Canberra, and derives strategic insights for Qatar. By examining the strategies, priorities, outcomes, and challenges associated with implementing smart city initiatives in these cities, the study identifies areas of alignment and divergence with Qatar's own smart city policy framework. The research highlights potential opportunities for cross-learning and suggests how Qatar can leverage lessons from international best practices to enhance its smart city initiatives. Key areas of focus include fostering strategic partnerships, promoting innovation, and ensuring effective governance and data management systems. The findings provide actionable insights to improve the effectiveness of Qatar's smart city projects, aligning them with the Qatar National Vision 2030.

This paper presents a comprehensive review of the transformative impact of 3D printing technology on smart cities. As cities face rapid urbanization, resource shortages, and environmental degradation, innovative solutions such as additive manufacturing (AM) offer potential pathways for sustainable urban development. By synthesizing 66 publications from 2015 to 2024, the study examines how 3D printing improves urban infrastructure, enhances sustainability, and fosters community engagement in city planning. Key benefits of 3D printing include reducing construction time and material waste, lowering costs, and enabling the creation of scalable, affordable housing solutions. The paper also addresses emerging areas such as the integration of 3D printing with digital twins (DT), machine learning (ML), and AI to optimize urban infrastructure and predictive maintenance. It highlights the use of smart materials and soft robotics for structural health monitoring (SHM), and repairs. Despite the promising advancements, challenges remain in terms of cost, scalability, and the need for interdisciplinary collaboration among engineers, urban planners, and policymakers. The findings suggest a roadmap for future research and practical applications of 3D printing in smart cities, contributing to the ongoing discourse on sustainable and technologically advanced urban development.

: Medical gloves, along with masks and gowns, serve as the initial line of defense against poten-tially infectious microorganisms and hazardous substances in the health sector. During the COVID-19 pandemic, medical gloves played a significant role, as they were widely utilized by society in daily activities as a preventive measure. These products demonstrated their value as important personal protection equipment (PPE) and reaffirmed their relevance as infec-tion-prevention tools. This review describes the evolution of medical gloves since the discovery of vulcanization by Charles Goodyear in 1839, which fostered the development of this industry. Regarding the current market, a comparison of the main properties, benefits, and drawbacks of the most widespread types of sanitary gloves is presented. The most usual gloves are produced from natural rubber (NR), polyisoprene (IR), acrylonitrile butadiene rubber (NBR), polychloroprene (CR), polyethylene (PE), and poly(vinyl chloride) (PVC). Furthermore, the environmental impacts of the conventional natural rubber gloves manufacturing process and mitigation strate-gies, such as bioremediation and rubber recycling, are addressed. In order to create new smart medical gloves with improved properties, several biopolymers (e.g. poly(vinyl alcohol) and starch) and additives such as biodegradable fillers (e.g., cellulose and chitin), reinforcing fillers (e.g. silica and cellulose nanocrystals), and antimicrobial agents (e.g., biguanides and quaternary ammonium salts) have been evaluated. This paper covers these smart materials and describes different innovative prototypes of gloves and coatings designed with them.

The exposure to extreme temperatures in workplaces involves physical hazards for workers. A poorly acclimated worker may have lower performance and vigilance and may therefore be more exposed to accidents and injuries. Due to the incompatibility of the existing standards implemented in some workplaces and the lack of thermoregulation in many protective equipment, thermal stress remains one of the most frequent physical hazards in many work sectors. However, many of these problems can be overcome with the use of smart textile technologies that enable intelligent thermoregulation in personal protective equipment. Smart textiles can detect, react and adapt to many external stimuli. Interconnected sensors and actuators that interact and react to existing risks can provide the wearer with increased safety, protection and comfort. Thus, the skills of smart protective equipment can contribute to the reduction of errors and the number and severity of accidents in the workplace, and thus promote improved performance, efficiency and productivity.This review provides an overview and opinions of authors on the current state of knowledge on these types of technologies by reviewing and discussing the state of the art of commercially available systems and the advances made in previous research works.

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.

The distribution of tiny sensors over a specific area was first proposed in the late 1990s as a concept known as Smart Dust. Several efforts focused primarily on computing and networking capabilities but quickly ran into problems related to power supply, cost, data transmission, and environmental pollution. To overcome these limitations, we propose using paper-based (confetti-like) chemosensors that exploit the inherent selectivity of chemical reagents, such as colorimetric indicators. In this work, cheap and biodegradable passive sensors made from cellulose could successfully indicate the presence of hazardous chemicals, e.g., strong acids, by a significant color change. A conventional color digital camera attached to a drone could easily detect this from a safe distance. The collected data was processed to define the hazardous area. Our work presents a combination of the smart dust concept, chemosensing, paper-based sensor technology, and low-cost drones for flexible, sensitive, economical, and rapid detection of hazardous chemicals in high-risk scenarios.

Smart living, a concept that has gained increasing attention in recent years, revolves around integrating advanced technologies in homes and cities to enhance the quality of life for citizens. Sensing and human action recognition are crucial aspects of this concept. Smart living applications span various domains, such as energy consumption, healthcare, transportation, and education, which greatly benefit from effective human action recognition. This field, originating from computer vision, seeks to recognize human actions and activities using not only visual data but also many other sensor modalities. This paper comprehensively reviews the literature on human action recognition in smart living environments, synthesizing the main contributions, challenges, and future research directions. This review selects five key domains: Sensing Technology, Multimodality, Real-time Processing, Interoperability, and Resource-Constrained Processing, as they encompass the critical aspects required for successfully deploying human action recognition in smart living. These domains highlight the essential role that sensing and human action recognition play in successfully developing and implementing smart living solutions. This paper serves as a valuable resource for researchers and practitioners seeking to explore further and advance the field of human action recognition in smart living.

Metal oxide p-n heterojunction nanofibers (NFs) are among the most promising approaches to enhancing the efficiency of gas sensors. In this paper, we report the preparation of a series of p-NiO-loaded n-ZnO NFs, namely (1 − x) ZnO-xNiO (x = 0.03, 0.05, and 0.1 wt%), for hydrogen gas sensing experiments. Samples were prepared through the electrospinning technique followed by a calcination process. The sensing experiments showed that the sample with 0.05 wt% NiO loading resulted in the highest sensing performance at an optimal sensing temperature of 200 °C. The sensing mechanism is discussed in detail and contributions of the p-n heterojunctions, metallization of ZnO and catalytic effect of NiO on the sensing enhancements of an optimized gas sensor are analyzed. This study demonstrates the possibility of fabricating high-performance H₂ sensors through the optimization of p-type metal oxide loading on the surfaces of n-type metal oxides.

Incorrect sitting posture, characterized by asymmetrical or uneven positioning of the body, often leads to spinal misalignment and muscle tone imbalance. Prolonged maintenance of such postures can adversely impact well-being and contribute to the development of spinal deformities and musculoskeletal disorders. In response, smart-sensing chairs equipped with cutting-edge sensor technologies have been introduced as a viable solution for real-time detection, classification, and monitoring of sitting postures, aiming to mitigate the risk of musculoskeletal disorders and promote overall health. This comprehensive literature review evaluates the current body of research on smart-sensing chairs, with a specific focus on the strategies used for posture detection and classification, as well as the effectiveness of different sensor technologies. A meticulous search across MDPI, IEEE, and Google Scholar databases yielded 34 pertinent studies that utilize non-invasive methods for posture monitoring. The analysis reveals that Force Sensing Resistors (FSR) are the predominant sensors utilized for posture detection, whereas Convolutional Neural Networks (CNN) and Artificial Neural Networks (ANN) are the leading machine learning models for posture classification. However, it was observed that CNNs and ANNs do not outperform traditional statistical models in terms of classification accuracy, due to constrained size and lack of diversity within training datasets. These datasets often fail to comprehensively represent the array of human body shapes and musculoskeletal configurations. Moreover, this review identifies a significant gap in the evaluation of user feedback mechanisms, essential for alerting users to their sitting posture and facilitating corrective adjustments.

Water stable proteins may offer a new field of applications in smart materials for buildings and infrastructures where hydraulic reactions are involved. In this study, cement mortars modified through water-soluble silk fibroin (SF) are proposed. Water-soluble SF obtained by redissolving SF films in phosphate buffer solution (PBS) showed the formation of a gel with β-sheet features of silk II. Electrical measurements on SF indicate that calcium ions are primarily involved in the conductivity mechanism. By exploiting the water solubility properties of silk II and Ca2+ ion transport phenomena and its trapping effect over water molecules, SF provides piezoresistive and piezocapacitive properties to cement mortars, thus enabling self-sensing of mechanical strain which is quite attractive in structural health monitoring applications. SF/cement-based composite introduces the capacitive gauge factor that surpasses the traditional resistive gauge factor reported in the literature by threefold. Cyclic voltammetry measurements demonstrated SF cement mortars possess memcapacitive behavior for positive potentials around +5 V, attributed to an interfacial charge build-up modulated by the SF concentration and the working electrode. Electrical square-biphasic excitation combined with cyclic compressive loads revealed memristive behavior during the unloading stages. These findings along with the availability and the sustainability of SF pave the way for the design of novel multifunctional materials, particularly for applications in masonry and concrete structures.

Different contact materials along with optimization of the deposition techniques expand the possibilities to obtain high performance room temperature CdTe-based X/γ-ray detectors. The heterostructures with ohmic (MoOx) and Schottky (MoOx, TiOx, TiN, and In) contacts, created by DC reactive magnetron sputtering and vacuum thermal evaporation, as well as In/CdTe/Au diodes with a p-n junction, formed by laser-induced doping, were developed and investigated. Depending on the pre-treatment of the surface of semi-insulating p-CdTe crystals, deposition of a MoOx film formed an ohmic or Schottky contact. Based on the calculations and IV characteristics of the fabricated Mo-MoOx/р-CdTe/MoOx-Mo, In/CdTe/MoOx-Mo, Ti-TiOx/р-CdTe/MoOx-Mo, and Ti-TiN/р-CdTe/MoOx-Mo Schottky-diode detectors, the current transport processes were described in the models of the carrier generation-recombination within the space-charge region (SCR) at low bias voltages, and space-charge limited current at higher voltages, respectively. The energies of generation–recombination centers, density of trapping centers, and carrier lifetimes were determined. A sharp increase in the reverse current in the Mo-MoOx/р-CdTe/MoOx-Mo, Ti-TiOx/р-CdTe/MoOx-Mo, and Ti-TiN/р-CdTe/MoOx-Mo heterostructures at high bias was discussed in frames of the Poole–Frenkel emission model. Nanosecond laser irradiation of the In electrode, pre-deposited on the p-CdTe crystals, resulted in an increase in the voltage range, corresponding to the carrier generation-recombination in the SCR, in the IV characteristics of the In/CdTe/Au diodes. Such In/CdTe/Au p-n junction diodes demonstrated high energy resolutions (7%@59.5 keV, 4%@122 keV, and 1.6%@662 keV).

A position sensing glove, called SmartScan, that creates a 3D virtual model of a real object is presented. The data from the glove is processed by a volume minimization algorithm to validate the position sensor data. This allows only data from the object’s surface to be retained. The data validation algorithm allows the user to progressively improve an image by repeatedly moving their hand over the object. In addition, the user can choose their own balance between feature resolution and invalid data rejection. The SmartScan glove is tested on a foot model and is shown to be robust against motion artifacts, and has a mean accuracy of 2.9 mm (compared to a 3D model generated from optical imaging) without calibration.

Tinnitus is an auditory phantom perception in the ears or head in the absence of a corresponding external stimulus. There is currently no effective treatment available that reliably reduces tinnitus. Educative counseling is a treatment approach that aims to educate patients and inform them about possible coping strategies. For this feasability study, we implemented educational material and self-help advice in a smartphone app. Participants used the educational smartphone unsupervised during their daily routine over a period of 4 months. Comparing the tinnitus outcome measures before and after smartphone-guided treatment, we measured changes in the tinnitus-related distress, but not in tinnitus loudness. Improvements on the Tinnitus Severity numeric rating scale reached an effect size of .408, while the improvements on the THI were much smaller with an effect size of .168. Analysis on the user behavior showed that frequent and intensive use of the app is a crucial factor for treatment success: participants that used the app more often and interacted with the app intensively, reported a stronger improvement of the tinnitus. Between study allocation and final assessment, 26 of 52 participants dropped out of the study. Reasons for the dropouts and lessons for future studies are discussed in this paper.

Polymeric composites are prone to undergo damage, such as microcracks, during their operation, that can ultimately lead to catastrophic failure. To contradict such problem, effort has been put, by the scientific community, towards developing self-healing composites that, by mimicking biological systems, can autonomously and prematurely repair flaws, extending durability and improving security of materials. The present review explores the progress being made in such area, focusing on extrinsic self-healing methods, considering that they can be employed to a variety of materials. Reservoir-based techniques, that resort to capsules, hollow fibers or microvascular networks, and thermoplastic-based ones are overviewed, prioritizing innovative approaches made in recent years. At last, promising practical applications for self-healing composites are highlighted and future challenges and opportunities are pointed out.

In this study, a graphene-doped porous silicon (G-doped/p-Si) substrate for low ppm H₂ gas detection by an inexpensive synthesis route was proposed as a potential noble graphene-based gas sensor material and to understand the sensing mechanism. The G-doped/p-Si gas sensor was synthesized by a simple capillary force-assisted solution dropping method on p-Si substrates, whose porosity was generated through an electrochemical etching process. G-doped/p-Si was fabricated with various graphene concentrations and exploited as a H₂ sensor operated at room temperature. The sensing mechanism of the sensor with/without graphene decoration on p-Si was proposed to elucidate the synergetic gas sensing effect generated from the interface between the graphene and p-type silicon.

3D printing technology has made significant strides in smart textiles—fabrics embedded with electronics like conductive fibers and sensors—now widely applied in areas such as health con-dition monitoring, wearable energy-harvesting devices, and interactive textiles that respond to environmental conditions and color changes. Different 3D printing methods, such as Fused Deposition Modeling (FDM), Selective Laser Sintering (SLS), Direct Ink Writing (DIW), and PolyJet printing, are used in the fabrication of smart textiles. This study provides a detailed, applica-tion-specific overview of 3D printing technologies—such as FDM, SLS, DIW, and PolyJet print-ing—and their use in smart textiles across various sectors, including wearable technology, medical textiles, and smart fashion design. We gathered articles and reports from Scopus and Google Scholar, providing a concise assessment of 3D printing materials for smart textiles to give readers a quick understanding of the field. The timeline of 3D printing’s use in smart textiles, from 2016 to 2023, highlights significant advancements in various additive manufacturing techniques applied to smart textiles. The review emphasizes the importance of understanding 3D printing techniques such as FDM, SLS, DIW, and PolyJet, as their applicability for selecting the best approach to in-corporating advanced functionalities into smart textiles.

According to the risk investigations of being involved in an accident, alcohol-impaired driving is one of the major causes of motor-vehicles accidents. Preventing highly intoxicated persons from driving would potentially save many lives. This paper proposes a lightweight in-vehicle alcohol detection that processes the data generated from 6-alcohol sensors (MQ-3 Alcohol Sensors) using an optimizable shallow neural network (O-SNN). The experimental evaluation results exhibit a high-performance detection system scoring a 99.8% of detection accuracy with a very short inferencing delay of 2.22 µ seconds. Hence, the proposed model can be efficiently deployed and used to discover in-vehicle alcohol with high accuracy and low inference overhead as a part of the driver alcohol detection system for safety (DADSS) system aiming at massive deployment of alcohol sensing systems that could potentially save thousands of lives annually.

Smart air filters are beneficial to provide highly efficient particle removal, treat multiple contaminants simultaneously and conserve energy during air filtration processes. Herein, a type of self-supporting smart air filter (SSSAF) was fabricated by sandwiching the VOC-responsive PZT/PVDF electrospun membrane with two metal mesh electrodes. Besides the high filtration efficiency for sub-micron particles, the SSSAF showed good responses to pressure drop in the range of 0 to 500 Pa via the electroactivity of PZT/PVDF membrane. In addition, the SSSAF achieved VOC sensing function via the swelling properties of PZT/PVDF membrane in organic vapors, demonstrated by its signal to 50 to 200 ppm ethanol gases. The SSSAF based nanogenerator was employed to harvest wind energy, which was further applied to inhibit bacterial growth without the need of additional power input. The results provide new insight into development of all-in-one smart air filters.

Gold nanoparticles (NPs) are among the most commonly employed metal NPs in biological applications, with their distinctive physicochemical features. Their extraordinary optical properties, stemming from the strong localized surface plasmon resonance (LSPR), contribute to the devel-opment of novel approaches in the areas of bioimaging, biosensing, and cancer research, especially for photothermal and photodynamic therapy. The ease of functionalization with various lig-ands provides a novel approach to the precise delivery of these molecules to targeted areas. Gold NPs ability to transfer heat and electricity positions them as valuable materials for advancing thermal management and electronic systems. Moreover, their inherent characteristics, such as in-ertness, give rise to the synthesis of novel antibacterial and antioxidant agents as they provide a biocompatible and low-toxic approach. Chemical and physical synthesis methods are utilized to produce gold NPs. The pursuit of more ecologically sustainable and economically viable large-scale technologies, such as environmentally benign biological processes referred to as green/biological synthesis, has garnered increasing interest among global researchers. Green synthesis methods are favorable among other synthesis techniques as they minimize the necessity for hazardous chemicals in the reduction process due to their simplicity, cost-effectiveness, energy efficiency, and biocompatibility. This article discusses the importance of gold NPs, their optical and conductivity properties, antibacterial, antioxidant, and anticancer properties, synthesis methods, contemporary uses, and biosafety, emphasizing the need to understand toxicology principles and green commercialization strategies.

Fabrication of durable materials with excellent oil adsorption capacity and separation performance for the treatment of oily wastewater is meaningful based on smart responsiveness. Herein, a solvent-responsive melamine sponge (MS) was developed via silanization followed by the in-situ growth of zeolitic imidazolate framework-8 (ZIF-8). Detailed characterization of the resultant composite MS was conducted using scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The multiscale hierarchical MS substrate exhibited highly hydrophobic property in the pH range of 1-11, along with a satisfactory adsorption capacity in the range of 65.4-134.2 g/g for different oils. The modified surface transformed from superhydrophobicity/superlipophilicity to superhydrophilicity/underwater superoleophobicity upon ethanol wetting, reverting to its original superhydrophobic state upon drying. The separation flux of the MS substrate was above 1.5×104L/m2h for both oil and water removal, along with the separation efficiency more than 98.7%. No obvious changes of the separation performance after 50 successive immiscible oil/water separation indicated the excellent durability and robustness of the anchored ZIF-8 nanoparticles on the surface of modified MS substrate. More importantly, oil-in-water emulsion separation was successfully carried out via the ZIF-8 MS composite with a high separation efficiency over 99.1%. The developed smart sponge with high oil absorption capacity, excellent chemical stability and fire resistance exhibited a wide range of potential practical applications in the convenient treatment of oily wastewater.

Some studies have demonstrated that in vivo degradation processes are influenced by the material’s physico-chemical properties. The present study compares two hydroxyapatites manufactured on an industrial scale, deproteinized at low and high temperatures, and how physico-chemical properties can influence the mineral degradation process of material performance in bone biopsies retrieved 6 months after maxillary sinus augmentation. Residual biomaterial particles were examined by field scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX) to determine the composition and degree of degradation of the bone graft substitute material. According to the EDX analysis, the Ca/P ratio significantly lowered in the residual biomaterial (1.08±0.32) compared to the initial composition (2.22±0.08) for the low-temperature sintered group, which also presented high porosity, low crystallinity, low density, a large surface area, and poor stability and a high resorption rate compared to the high-temperature sintered material. This demonstrates that variations in the physico-chemical properties of bone substitute material clearly influence the degradation process. Further studies are needed to determine whether the resorption of deproteinized bone particles proceeds slowly enough to allow sufficient time for bone maturation to occur.

The field of power harvesting has experienced significant growth over the past few years due to the ever-increasing desire to produce portable and wireless electronics with extended lifespans. The present work aims to introduce an approach to harvesting electrical energy from a mechanically excited piezoelectric element and investigates a power analytical model generated by a smart structure of type polyvinylidene fluoride(PVDF) that can be stuck onto fabrics and flexible substrates, although we report the effects of various substrates and investigates the sticking of these substrates on the characterization of the piezoelectric material.

High rates of phosphorus (P) currently being applied to soils for the production of vegetables in the Mekong Delta, Vietnam has led to the concern of its negative effect on the economics and the environment. This research presents a comprehensive study on the determination of P supplying capacity in this region of Vietnam to examine the possibility of reducing P fertilizer input. One hundred twenty (120) soil samples were collected to evaluate total P and Bray 1 available P in the soils. Phosphorus maximum sorption, degree of P saturation, P release, and the effect of P fertilizer on corn (Zea mays L.) yield in greenhouse and fields were also determined. Total P concentrations of 56.7% soil samples evaluated yielded high P concentrations (>560 mg P/kg), while 74.2% of the samples had high Bray 1 available P concentrations (>20 mg P/kg soil). Maximum P sorption ranged from 149 to 555 mg P/kg soil, respectively and has negative correlation to available P (r = - 0.63*), degrees of P saturation ranged from 0.63 to 5.46% correlated to available P (r = 0.98**) and maximum P release ranged from 1.2 to 61.9 mg P/kg soil, respectively correlated to available P (r = 0.96**). Corn grown in soils with available P concentrations >15 mg P/kg did not respond to P fertilizer in greenhouse or field experiments. We conclude that many farmers in this region can reduce P fertilizer input, thus increasing their profits and reducing negative environmental impacts associated with excess soil P for sustainable agriculture.

Inhibition of quorum sensing (QS)-dependent biofilm formation and virulence is extensively investigated as a novel approach to combat bacterial pathogens by impeding their ability to cause antibiotic-tolerant diseases. Such strategies are considered a promising alternative to conventional antibacterial therapy since interrupting the central cell-to-cell communication system imposes less selective pressure on the target pathogen. In this study, novel hybrid compounds composed of anthranilic acids substituted with halogens at different positions of the phenyl ring, and 4-(2-aminoethyl/4-aminobuthyl)amino-7-chloroquinoline linked via 1,3,4-oxadiazole were synthesized using standard procedures. Their anti-QS activities were evaluated using Chromobacterium violaceum ATCC31532 (anti-biofilm and bactericidal activities) and Pseudomonas aeruginosa PAO1 (anti-biofilm/-virulence activities). The results showed that compounds 15–19 and 23 inhibited the production of violacein, the QS-inducible pigment, in C. violaceum to a similar extent as the model QS inhibitor - quercetin (83.5–90%). Compound 15 exhibited the strongest effect on P. aeruginosa in the anti-biofilm screening, reducing its ability to form biofilm by almost 50%, while compounds 16 and 19 were able to reduce the biofilm formation by approximately 30%. However, compound 23 did not demonstrate significant anti-biofilm activity and only inhibited pyocyanin production in P. aeruginosa. In conclusion, this study suggests that 1,3,4-oxadiazoles 15, 16, and 19 are the most promising compounds for future research as novel QS inhibitors against Gram-negative bacteria equipped with different QS signaling pathways.

Soil water balance (SWB) in woody crops is sometimes difficult to estimate with one-dimensional models because these crops do not completely cover the soil and usually have a deep root system, particularly when cropped under rainfed conditions in a Mediterranean climate. In this study, the actual crop evapotranspiration (ETc act) is estimated with the soil water balance model SIMDualKc which uses the dual-Kc approach (relating the fraction of soil cover with the crop coefficients) to improve the estimation of the water requirements of a rainfed vineyard, using data from a deep soil profile. The actual basal crop coefficient (Kcb act) obtained using the SIMDualKc model was compared with the Kcb act estimated using the A&P approach, which is a simplified approach based on measurements of the fraction of ground cover and crop height. Spectral vegetation indices derived from Landsat-5 satellite data were used to determine the fraction of ground cover (fc VI) and thus, the density coefficient (Kd). The SIMDualKc model was calibrated using soil water content (SWC) measurements down to a depth of 1.85 meters, which significantly improved the conditions for using a SWB estimation model. The test of the model was performed using a different SWC dataset. A good agreement between simulated and field measured SWC was observed for both data sets along the crop season, with RMSE<12.0 mm, NRMSE <13%. The calibrated Kcb values were 0.15, 0.60 and 0.52 for the initial, mid-season, and end season, respectively. The ratio between actual (ETc act) and crop evapotranspiration (ETc) was quite low between veraison and maturity (mid-season), corresponding to 36%, indicating that the rainfall was not sufficient to satisfy the vineyards water requirements. Spectral vegetation indices used to compute fc VI were unable to fully track the plants’ conditions when water stress. However, ingestion of data from remote sensing showed promising results that could be used to support decisions making in irrigation scheduling. Further studies on the use of the A&P approach using remote sensing data are required.

When focusing on materials science in civil engineering, the current trend is to investigate the use of innovative solutions in order to enhance thermal and energy performances. This trend is amplified with the need for a sustainable development strategy for the construction sector. This paper assesses the integration of a Phase Change Material (PCM) in cement intended for building construction. The key characteristic of PCMs is their capacity to absorb energy and restore it. In building construction, this feature could be harnessed to save energy by incorporating PCMs in the materials used. In this study, passive integration of PCM in cement was tested and thermal properties of such an integration was assessed. The results provide insights into how PCMs affect cement as part of the concrete mixture, thus identifying the contribution of PCM-based cements in concrete mixtures.

Orthostatic hypotension (OH) is a condition marked by a significant drop in blood pressure upon standing, resulting from impaired autonomic regulation of vascular tone and blood volume. This study investigates the prevalence, physiological mechanisms, and occupational risk factors for OH among high-risk professions in Nepal, such as traffic police, security guards, and shopkeepers. Using a cross-sectional design, participants were evaluated for blood pressure variability, autonomic function, and fluid balance. The findings reveal a high incidence of OH, linked to reduced baroreceptor sensitivity and impaired sympathetic activation due to prolonged standing and inadequate hydration. This study highlights the need for tailored clinical interventions and workplace modifications to mitigate OH in vulnerable occupational groups.

Sewage sludge is an organic waste generated in waste-water treatment plants with certain content of nutrients, what may potentially be used as a source of slow release fertilizer, especially as phosphorus (P) source, but it demands some pre-treatment and the content of P is much lower compared to soluble mineral fertilizers. For these reasons, composted sewage sludge was used to manufacture pelletized organomineral fertilizers, mixing it with the inorganic sources monoammonium phosphate (MAP) and AshDec® (ASD) (thermochemically incinerated sewage sludge). The fertilizers were physiochemically characterized and evaluated as to the dynamics of soil P solubilization, and the forms of P remaining according to its lability. The sources evaluated were: organic compost of sewage sludge powder (SSC), pelletized SSC (SCP), pelletized organominerals SSC+MAP (S+MAP) and SSC+ASD (S+ASD), ASD alone, all compared to a soluble mineral fertilizer (MAP), and a control without P fertilizer. A test was conducted in leaching columns with 50 g of soil (Oxisol), where the fertilizers were applied at a dose of 100 mg P/column, and 30 mL of water or 2% citric acid were added daily for 30 consecutive days. The collected leachates had pH measured and P content determined. Pelletizing process resulted in denser products and promoted more gradual P release. The organomineral S+MAP was the most water-soluble recycled source, solubilizing about 70% of the total P, while the others presented much lower solubilization (<20%). In contrast, all fertilizers showed high solubility in 2% citric acid (except for S+ASD). After leaching, the greatest amount of P remaining in the soil as labile and moderately labile. Composting and the AshDec process produced materials with slow P solubilization, which would be favoured to solubilize in acidic soils and acidic rhizosphere conditions. In turn, the organomineral mixture of SSC with a highly soluble mineral fertilizer (MAP) resulted in a promising product with intermediate nutrient solubility, better synchronized with crop demand, thus increasing efficiency in P use.

The agricultural sector is vital to the economies of many countries, particularly in developing country, providing livelihoods for millions and significantly contributing to GDP, food security, and social stability. Off-takers play a critical role in addressing these challenges by providing market certainty through predetermined purchase agreements. Engaging in contract farming and offering capital, technical assistance, and market access, off-takers help stabilize income, facilitate capital access, enhance technology adoption, and ensure business continuity. This research employs the Systematic Literature Review (SLR) method and secondary data analysis. Based on the review, the multifaceted benefits of agricultural off-takers include increased production and fostering entrepreneurial skills among farmers. Hence, fostering partnerships between farmers and off-takers is crucial for enhancing agricultural competitiveness, sustainability, and farmer well-being. Leveraging off-takers' potential and promoting collaboration within agricultural clusters can foster thriving agricultural ecosystems, ensuring food security and economic prosperity in rural communities.

In this paper, we introduce the (ρ,q)-analogue of the p-adic factorial function. By utilizing some properties of (ρ,q)-numbers, we obtain several new and interesting identities and formulas. We then construct the p-adic (ρ,q)-gamma function by means of the mentioned factorial function. We investigate several properties and relationships belonging to the foregoing gamma function, some of which are given for the case p = 2. We also derive more representations of the p-adic (ρ,q)-gamma function in general case. Moreover, we consider the p-adic (ρ,q)-Euler constant derived from the derivation of p-adic (ρ,q)-gamma function at x = 1. Furthermore, we provide a limit representation of aforementioned Euler constant based on (ρ,q)-numbers. Finally, we consider (ρ,q)-extension of the p-adic beta function via the p-adic (ρ,q)-gamma function and we then investigate various formulas and identities.

Information and communication technologies play an increasingly important role in the process of knowledge and management of places at different scales. ICTs allow a rapid diffusion of data not only through institutional channels but also through social networks where the smart community share experiences and perceptions. In this sense, ICTs become strategic tools to support the promotion of sustainable tourism development of territories, especially if the digital data are organised within a circular smart dashboard. This research focuses on the case study of the Santa Barbara Walk (SBW), an ancient mining route in the Sulcis Iglesiente region (Sardinia, Italy), where the authors have recognized a state of disorganization in slow tourism promotion activities. In fact, if the SBW represents a network - material infrastructure - which connects the main points of interest along the Walk, its digital network - intangible infrastructure - is fragmented in terms of policies and contents. The goal of this study is to provide a comprehensive set of data and to propose the architecture and design for a circular dashboard of the SBW, capable of organizing information concerning the main features of the walk, in order to facilitate a shared governance for an effective tourism promotion.

Smart farm is a technology that greatly helps improve the productivity and quality of crops and is being actively introduced into indoor environments such as green houses. However, it has not yet been distributed to field-grown crops. The main reason is that, unlike indoor environments, it is very difficult to collect sensor data for monitoring the growth environment of crops in open fields where weather conditions change significantly and power supply is difficult. Additionally, because various sensors are used, the data formats of the devices are different, making it difficult to process. This paper presents a field crop growth environment monitoring and big data analysis system. The proposed system first solves power supply and data communication problems using solar power generation and LPWA technology. Additionally, based on the oneM2M architecture, data from various sensors is transmitted to the server using standardized technology. The transmitted data is stored and managed on the server as big data, and can be used to predict the production and quality of field-grown crops and take appropriate measures. The proposed system is expected to create an environment optimized for the growth of field crops and help prevent and manage diseases.

Objectives: In Nigeria, modern contraceptive use remains relatively low despite numerous efforts to increase awareness and accessibility. This study examined the geopolitical factors influencing modern contraceptive use in North-central Nigeria Design: Using data from the 2021 Nigeria Multiple Indicator Cluster Survey, this study quantitatively investigated the factors influencing modern contraceptive use among women of reproductive age. The data were analyzed using R studio. Respondents' characteristics were described using frequency and percentage. A logistic regression model was employed to identify factors associated with modern contraceptive usage in the north-central region of Nigeria. Bivariate logistic regression was carried out between the explanatory and response variables. Settings: This study focused specifically on the north-central zone of Nigeria comprising 6 states, namely, Benue, Kogi, Kwara, Nasarawa, Niger, and Plateau states with the Federal Capital Territory (FCT). Results: Nearly one-third (30.1%) of the respondents are above 35 years of age. 3 out of every 5 (61.2%) respondents are currently married. This study found that the average modern contraceptive usage among women of reproductive age in north Central Nigeria is less than 15%. Age, education, childbirth delivery method, number of children, access to media, and state of residence are key drivers of modern contraceptive adoption and utilization among women of reproductive age in north-central Nigeria. Conclusion: This study finds it plausible to increase the awareness and sensitization of modern contraceptives and contraceptive usage in this region. There is a need for health education on the benefits and relevance of modern contraceptive usage.

Introduction: Early childhood caries is a significant public health problem among preschool children. The COVID-19 pandemic, which restricted dental services, altered family dynamics, affected child development, and created new demands on caregivers, may have exacerbated this issue. Objective: Analyze the occurrence and severity of caries and identify associated factors in preschool children attending public municipal daycare centers in Salvador, Bahia, Brazil, Methodology: A cross-sectional epidemiological study was conducted to investigate caries in children aged 2 to 5 years in 2022 and 2023. Caries was assessed using the decayed, extracted, filled, and missing teeth (DEFT) index, and prevalence was calculated. Sociodemographic, family dynamic, dietary, and healthcare utilization data were obtained through a questionnaire. After descriptive and exploratory analyses, robust Poisson multivariable regression was conducted at a 5% significance level, considering socioeconomic, psychosocial, and behavioral aspects. Results: A total of 440 preschoolers participated, with a mean age of 55 months. The majority were Black or mixed race (88.86%) and female (52.73%). The prevalence of caries was 30.91% and the mean DEFT score was 1.1. In the multivariable analysis, low family income (up to one minimum wage) and not playing outdoors during the pandemic were associated with a higher prevalence of caries. Conclusion: The prevalence and severity of caries remain high, and the pandemic has contributed to the maintenance of this epidemiological scenario. Public health measures and policies promoting social justice should be planned to improve oral health conditions in childhood.

In this study, we propose a conservative and compact finite difference scheme designed to preserve both the mass change rate and energy for solving the sixth-order Boussinesq equation with the surface tension. Theoretical analysis confirms that the proposed scheme achieves second-order accuracy in temporal discretization and fourth-order accuracy in spatial discretization. The solvability, convergence, and stability of the difference scheme are rigorously established through the application of the discrete energy method. Additionally, a series of numerical experiments are conducted to illustrate the effectiveness and reliability of the conservative scheme for long-time simulations.

In this paper, we introduce a new class of $(p,q)$-analogue type of Fubini numbers and polynomials and investigate some properties of these polynomials. We establish summation formulas of these polynomials by summation techniques series. Furthermore, we consider some relationships for $(p,q)$-Fubini polynomials associated with $(p,q)$-Bernoulli polynomials, $(p,q)$-Euler polynomials and $(p,q)$-Genocchi polynomials and $(p,q)$-Stirling numbers of the second kind.

This paper explores the intersection of geometry and music, investigat- ing how mathematical structures shape musical theory, composition, and perception. It begins by examining the geometric foundations of pitch organization, including the circular representation of pitch classes and the tonal space. We then explore rhythmic structures through symmetry, analysing how patterns in time are geometrically conceived. Finally, the study examines more recent developments in computational music theory, such as the use of topological data analysis to model musical transformations and voice leading.

Polluting discharges are produced at a rate that is inexorably rising in tandem with human activity development. Eutrophication and other matters, such as offensive aquatic life, require wastewater to be treated before being discharged into the environment. Prior releasing into water bodies, the treated waters must to undertake laboratory analysis. For this purpose, an analysis using standard methods was carried out at the Laboratory Waterworks in Debrecen on various samples taken from various wastewater treatment plants (sewage treatment plants) in Hungary. The overall objective of this study was to assess the quality of the effluents from the fourteen (14) wastewater treatment plants and investigate their efficiency by measuring various physicochemical parameters and microbiological parameters as excellent indicators to evaluate the performance of the studied wastewater treatment plants. The microbiological indicator monitored was the heterotrophic count (HPC) by estimating its total number, which provides useful information for the assessment and monitoring of water samples. The determination of physicochemical parameters included biological oxygen demand (BOD5), chemical oxygen demand (COD) and nitrite -N (NO2), ammonia-N (NH3-N), nitrate-N (NO3) total phosphorus (TP), Kjeldahl- Nitrogen (organic N+ammonia-N) (TKN), total inorganic N (TI), total suspended solids (TSS) and total nitrogen (TN). The performance of the wastewater treatment plants examined was checked and the results were conclusive. In the future, solutions should be applied to these wastewater treatment plants and some recommendations are suggested.

Formaldehyde is generated via the biochemical and chemical pathways, and it widely exists in foods. Its chronic exposure causes carcinogenic, neurotoxic, reproductive, allergic, immunological, genetic and respiratory toxicities. However, food-sourced formaldehyde is usually neglected due to its rapid metabolism after intake. Compared with its residual level in processed foods, a large proportion of formaldehyde disappears because of its high reactivity. Nevertheless, its elimination reaction mechanism and the potential consequences remain unclear. In this review, the disappearing pathway of formaldehyde from two aspects, the formation of formaldehyde-derived toxins and aromas, was reviewed. This review article may help food scientists take appropriate strategies to use the beneficial reactions of formaldehyde or divert its harmful effects to beneficial ones.

Employee turnover is a significant issue for financial institutions, impacting productivity, increasing recruitment costs, and disrupting critical operations. In this project, this study aimed to predict employee turnover using a dataset containing attributes such as employee satisfaction, performance, and tenure. By framing the task as a binary classification problem, this study employed CatBoost and XGBoost, two advanced regression-based algorithms, to develop predictive models. This paper's analysis demonstrated that CatBoost outperformed XGBoost across all evaluation metrics, including MAE, MSE, RMSE, and R², making it the more effective model for predicting turnover in the financial sector. The study highlights key factors contributing to employee attrition, such as job satisfaction, tenure, and promotion opportunities, offering actionable insights for retention strategies. Additionally, by predicting probabilities rather than binary outcomes, this study aims to make more detailed decisions about employee retention. This research provides valuable tools for financial institutions to mitigate the risk of turnover, retain critical talent, and ensure operational continuity.

Granular material is one of the most common in nature. Recently, there has been a significant amount of interest in the granular materials, such as powders or sand. It is challenging to describe the motion of such kind of macroscopic size matter, because it behaves like solid, fluid or gas. Size division, pattern formation, avalanches, packing and convection - these are just a few examples from a wide range of observed phenomena that occur during the motion process of granular matter. Most of these processes are based by flow and no wonder that much effort has been devoted to obtain a hydrodynamic description in which granular materials are treated as a continuous medium. During the research of vertically shaken granular medium motion in an opened container it was found that experimental and numerical results are explained by hydrodynamic theory. This paper investigates the motion of a granular matter for a shallow, vertically shaken bed. We assume the Leidenfrost state as initial and the matter resembles a fluid heated up from below.A one-dimensional isothermal and a non-isothermal problem of granular material motion,simulatedby a hydrodynamic model are considered, and the material is assumed to be a continuous medium. The local temporal solvability of isothermal and non-isothermal initial boundary-value problem in Sobolev’s spaces is proved. This work presents a numerical study of the one-dimensional model of granular medium flow. The feature of this model is consideration of the Navier-Stokes equations accounting an interpolation form of VanderWaals constitutive equation for pressure. A finite-difference approximation for numerical solution is proposed.

This bibliometric study analysed breast cancer research trends and outputs from 2014 to 1 2023, utilising data from the Scopus database. The primary objectives include analysing publication 2 growth, citation metrics, document type distribution, leading countries, preferred journals and 3 authorship patterns. The study reveals a significant increase in breast cancer research publications, 4 with a total of 12,073 documents and 216,769 citations over the ten-year period. The United States 5 leads in publication output and citation impact, followed by China and Japan. Articles are the 6 predominant document type for total 73.4% of publications, while reviews and book chapters also 7 contribute notably. The most preferred journals for publishing breast cancer research include Breast 8 Cancer Research and Treatment, Clinical Breast Cancer, and Breast Cancer Research. Authorship 9 patterns show a trend towards multi-authored papers, with a substantial number of papers having 10 more than five authors. The study underscores the global collaborative effort in advancing breast 11 cancer research and highlights key areas for future exploration.

Pichia pastoris is extensively employed as a host for expressing foreign proteins, and its secretion system is especially advantageous for efficient protein purification. Ulp1 is essential for the cell cycle. In Saccharomyces cerevisiae, the absence of Ulp1 leads to G2/M cell cycle arrest. Similarly, in Pichia pastoris, we also observed G2 phase stalling in Ulp1 knockout cells. RNA-seq data revealed significant changes in seven genes, including INO1. Interestingly, overexpressing INO1 in Ulp1 knockout cells restored cell proliferation, suggesting that Ulp1 regulates cell proliferation through INO1. However, adding extra inositol to Ulp1 knockout cells was not able to restore cell prolifera-tion, indicating that the enzyme activity of INO1 is not essential for cell proliferation. Our data provide new insights into Ulp1 functions in the cell cycle and raise new questions about yeast cell cycle regulation.

Background and Objectives: A degenerative joint disease that primarily affects the elderly, osteoarthritis (OA) causes pain, decreased mobility, and a lower quality of life. The effectiveness of GerovitalH3, a biotrophic medication created by Ana Aslan, in reducing pain and enhancing function in older people with osteoarthritis in the knee and hip is assessed in this study. Materials and Methods: Two groups of 201 patients aged 65 and older participated in a randomized, case-control clinical trial. One group received physical therapy and GerovitalH3 periarticular injections, while the other group received just physical therapy. In addition to functional evaluations using the Lequesne Index, Activities of Daily Living (ADL), and Instrumental ADL (IADL) scores, pain was assessed using a Visual Analogue Scale (VAS). Results: The GerovitalH3 group showed a substantial decrease in pain (p<0.001) and an improvement in daily activities (p<0.001) when compared to the control group. However, there was no significant difference in walking scores (p = 0.171). There were no significant adverse effects noted. GerovitalH3 did not outperform physical therapy for reducing depression, even though both groups displayed some improvement in this area. Conclusions: This study opens a new possibility for periarticular injections of Gerovital H3 treatment combined with physical therapy, which may represent a safe and effective non-surgical option for elderly individuals struggling with OA pain and functional limitations. The findings of this study reinforce the need for further research, particularly randomized controlled trials with larger sample sizes and longer follow-up periods.

Background: Nanotechnology has emerged as a promising field of study, aiming to revolutionize healthcare through the innovative development of drugs, diagnostic tools, and medical devices. As a result, healthcare professionals in training are constantly faced with the challenge of understanding and applying these emerging technologies. The objective of this study is to determine the factors to consider for including the teaching of nanotechnological tools in medical specialty postgraduate programs. Methods: A study based on the Nominal Group Technique (NGT) was conducted to identify the factors that promote and hinder the implementation of nanotechnology in certain postgraduate programs where nanotechnology is employed, such as Internal Medicine, Critical Care Medicine, Family Medicine, and Clinical Pharmacology at the School of Medicine of Universidad de La Sabana. A framework analysis was used to analyze the collected data. Results: Based on the two research questions, several aspects were identified for the inclusion of nanotechnology in the medical practice of specialties. Key challenges include lack of knowledge and resource availability, misinformation, and lack of knowledge, as well as paradigmatic analysis as the main obstacles to the use of nanotechnology. Conclusions: The findings provide a first-time study on nanotechnology curricula within medical specialty programs in Colombia, with potential extrapolation to similar situations in other medical schools.

The species and bio-availability of phosphorus (P) in primary, secondary and digested sludge were fractionated and further analyzed in this study. Results showed that inorganic P (IP) was the primary P fraction in the secondary sludge and digested sludge, in which non-apatite IP (NAIP) amounted to 91.6% and 69.3% of IP, respectively. Organic P (OP), accounting for about 71.7% of total P (TP), was the dominant P composition in primary sludge. The content of bio-available P was about 9.7, 43.4, 29.8 mg-P/g-TS in primary sludge, secondary sludge and digested sludge, respectively, suggesting secondary sludge is the optimal choice when land application of sewage sludge is taken into consideration, followed by digested sludge and primary sludge. Polyphosphate and orthophosphate, comprising approximately 54.3% and 89.2% of TP, was the dominant P species in the secondary sludge and digested sludge, respectively. Monoester-P (54.6% of TP in extract) and diester- P (24.1%) were identified as OP species in primary sludge by Phosphorus-31 nuclear magnetic resonance (31PNMR). The present results would be helpful for P recovery and recycle from sewage sludge in wastewater treatment plant.

We conducted a comparative study on the development of two synthetic methods. The solvent-free synthesis is a green chemistry method developed in a bid to ameliorate environmental adverse effects of the conventional solvent-based synthesis. The synthesis of novel dichloro and polymethoxy p-nitrophenylhydrazones through solvent free technique gave moderate to high yields which were however lower than those of the solvent-based method. The established solvent-free approach has several benefits, including universality and simplicity of the approach, catalyst-free conditions, non-use of an organic solvent, quick reaction time, fast and efficient workup, and un-solvated pure products in moderate to high yields.

As digital technology has become an integral part of urban’s daily operations; the urban landscape is constantly evolving with the needs of its society. This new reality allowed Municipalities to exert a higher influence in the national and local economy. Through deliberate planning and executing initiatives, they can ignite the local financial ecosystem to growth. In line with this, the paper aims to understand the possibilities available to the Greek Municipalities to exploit the smart city benefits to foster economic development. It is essential to understand the role of different factors including the strategy during the planning and implementing phases of initiatives concerning economy and innovation in a smart city. To achieve this, a tailor-made questionnaire and advanced statistical techniques are applied. The main findings highlight the importance to plan initiatives aligned with the needs of the municipality and the business environment. The existence of a smart city strategy has a catalytic effect on the final impact of the implemented initiatives on the urban environment. A systematic analysis of the smart cities’ dynamics and the new state of the urban environment can help the local actors focus on the value creation and public service provision, fostering innovation and profitability.

Background: RO and ChRCC are kidney tumours with overlapping characteristics, making differentiation between them challenging. Objectives: The objective of this research is to create a radiogenomics map by correlating radiomic features to molecular phenotypes in ChRCC and RO, using resection as the gold standard. Methods: Fourteen patients (6 RO and 8 ChRCC) were included in the study. A total of 1,875 radiomic features were extracted from CT scans, alongside 632 cytobands containing 16,303 genes from the genomic data. Results: Feature selection algorithms applied to the radiomic features resulted in 13 key features. From the genomic data, 24 cytobands highly correlated with histology were selected and cross-correlated with the radiomic features. The analysis identified four radiomic features that were strongly associated with seven genomic features. Conclusion: These findings demonstrate the potential of integrating radiomic and genomic data to enhance the differential diagnosis of RO and ChRCC, paving the way for more precise and non-invasive diagnostic tools in clinical practice.

This paper presents an approach to assess and improve the cybersecurity infras- tructure of developing countries. We have highlighted and addressed the critical gaps through a hybrid approach encompassing SWOT analysis, benchmarking using Data Envelopment Analysis (DEA) and, Root Cause Analysis (RCA). This approach has provided a strong basis for evaluating cybersecurity performance by combining qualitative insights with quantitative metrics. As a case study, we have compared an underdeveloped country’s (Pakistan) cybersecurity pos- ture to five highly developed countries (Lithuania, Estonia, Singapore, Spain,and Norway). Our analysis has identified cybersecurity shortcomings and pro- vided actionable recommendations within a flexible framework, applicable for all developing countries to identify and address vulnerabilities, and align their cybersecurity infrastructure with international standards.

The increasing energy consumption and industrial activities that release carbon dioxide (CO2) emissions into the atmosphere have become one of the most serious environmental issues of today. This article discusses the current status in Azerbaijan regarding the development of effective approaches to reduce carbon emissions and ensure sustainable development, and it proposes relevant strategies for managing the carbon footprint. By exploring the interrelationship between the economy and the environment, it aims to contribute to the formation of more effective policies for managing CO2 emissions in Azerbaijan. According to the results of the econometric model established within the research for the period of 1990-2023, as the Azerbaijan economy grows, per capita CO2 emissions tend to increase, which can be linked to rising industrial activity, energy consumption, and other factors driving economic growth. The presence of a positive long-term relationship between population growth and per capita CO2 emissions can be attributed to higher overall energy consumption, increased demand for goods and services, and rising transportation needs. The strong correlation between economic growth and CO2 emissions suggests that it may be too early to assert the validity of the Kuznets curve for Azerbaijan economy as a developing country.

Fluctuations in kynurenic acid (KYNA) and brain-derived neurotrophic factor (BDNF) levels in the brain reflect its neurological status. The aim of the study was to investigate the effect of transiently elevated KYNA concentration in the cerebroventricular circulation on the expression of BDNF and its high-affinity tropomyosin-related kinase receptor B (TrkB) in specific structures of the sheep brain. Intracerebroventricularly cannulated anestrous sheep were subjected to a series of four 30-min infusions of KYNA: 4×5 μg/60 μL/30 min (KYNA20, n=6) and 4×25 μg/60 μL/30 min (KYNA100, n=6) or a control infusion (n=6), at 30-min intervals. Sections of the hippocampal CA3 field, amygdala (AMG), prefrontal cortex (PCx), and the hypothalamic medial-basal (MBH) and preoptic (POA) areas were dissected from the brain immediately after the experiment. The highest concentration of BDNF protein was found in the CA3 field (P&lt;0.01), which was 8-fold higher than in the AMG and 12-fold higher than that in the PCx (MBH and POA were not analyzed). The most pronounced BDNF mRNA expression was observed in the MBH followed by the PCx, POA, AMG and CA3, while the highest abundance of TrkB mRNA was recorded in the AMG followed by the MBH, PCx, CA3 and POA. KYNA increased (P&lt;0.05-P&lt;0.01) BDNF protein levels and the expression of its gene in the brain structures examined, with the effect varying by dose and brain region. KYNA, particularly at the KYNA100 dose, also increased (P&lt;0.01) TrkB gene expression, except for the AMG, where the lower KYNA20 dose was more effective (P&lt;0.01). These findings suggest a positive relationships between KYNA levels in the cerebroventricular circulation and BDNF-TrkB expression in specific brain regions in a sheep model. This indicates that a transient increase in CSF KYNA concentration can potentially restore BDNF production, whose deficiency underlies numerous neurological disorders.

Diospyros kaki, the most widely cultivated species of persimmon, has been long used in traditional medicine since its leaves extracts contain high amounts of flavonoids and terpenoids, endowed with potential antioxidant, anti-inflammatory, anticancer, antidiabetic and antimicrobial effects. Re-cently, many in vitro and in vivo studies have assessed different potential health benefits of per-simmon leaves; however, its anticancer activity towards colorectal cancer (CRC), the second deadliest cancer in Western countries, has not been investigated in depth. Since CRC current therapies are associated with serious side effects and show no efficacy towards patients carrying RAS/BRAF mutations, the search for new and more effective therapies has turned to plant extracts, which could help reduce conventional drugs dosages and toxicity. The effect of Diospyros kaki al-coholic extract has been investigated on E705 CRC cell line, representative of most CRC patients, and on SW480 cells, carrying a KRAS activating mutation. This extract is effective in reducing tumor cells viability, without affecting the healthy mucosa cell line CCD 841, and it triggers apoptosis in CRC cells, by disrupting mitochondrial functionality and increasing oxidative stress.

Pre-transport management activities can cause stress, injuries, and mortality in poultry. This study aimed to gather information about the current pre-transport practices (selection of unfit chickens, catching preparations, catching, and crating) for spent hens and broilers by questioning Flemish poultry farmers. The results showed that catching preparations such as an extra selection of chickens unfit for transport was performed by a minority of the poultry farmers, and that layer farmers were less in line with the EU-legislation for water and feed withdrawal than broiler farmers. All birds were caught inverted except for one broiler farmer who used mechanical catching (not yet common in Flanders). Additionally, mechanical catching may involve extra costs, increased biosecurity risks, and specific recommendations for the stable (height and width). The broiler farmers preferred mechanical catching for broiler catchers' well-being, while upright catching was considered better for animal welfare than catching more than three chickens by one/two legs, mechanically, or by wings. Awareness of the need to perform an extra selection by the poultry farmers before catching is required. Preparations like closing areas under the aviary system and removing litter (layers) can further streamline the process and reduce animal suffering.

This stability analysis method is simply represented and understood on a Bode plot of two impedances without complex equations. The external impedance of the charging system is properly quantified and designed based on the stability criteria by analyzing.

Arbutus unedo (strawberry tree) is a small Mediterranean tree capable of vigorous regrowth after disturbances like fire. Traditionally used for biomass fuel, its bark and branches hold potential for higher-value products through ecovalorisation into liquid mixtures that could replace petro-leum-based materials. This study aimed to explore the chemical composition of various compo-nents of Arbutus unedo and to produce a liquefied material from its internal (IB) and external bark (EB). Chemical compositions of internal and external bark were determined using TAPPI standards including ash, extractive content, lignin, and cellulose. Metal cations were analyzed by ICP. Liquefaction of bark was optimized in a PARR reactor, evaluating factors such as particle size, temperature, and time and the best polyols were monitored by FTIR-ATR. Polyurethane foams were made with internal and external bark liquefied materials by polymerization with isocyanate, a catalyst and water as blowing agent. Results showed that EB has a higher extractive and lignin content, while IB contains more cellu-lose. Liquefaction yields were higher for IB (74%) than EB (68%), with IB yielding polyols that produced stronger and more resilient foams. Mechanical properties of the foams were influenced by the NCO/OH ratio and catalyst levels. Overall, the internal bark demonstrated superior performance for foam production, highlighting its potential as an eco-friendly alternative to petroleum-derived materials.

Introduction: Leptin and ghrelin are two hormones that play a role in weight homeostasis. Leptin, which is produced primarily by adipocytes and is dependent on body fat mass, suppresses appetite and increases energy expenditure. Conversely, ghrelin is the “hunger hormone”, it stimulates appetite and promotes fat storage. Bariatric surgery significantly alters the levels and activity of these hormones, contributing to weight loss and metabolic improvements. Clarifying the interplay between bariatric surgery, weight loss, physical exercise, leptin, and ghrelin is essential for developing comprehensive strategies for optimizing long-term outcomes for candidates for bariatric surgery, especially sarcopenic patients. Methods: This was a randomized controlled study with two groups (n=22). The patients in both groups have obesity and sarcopenia. A Roux-en-Ygastric bypass (RYGB) procedure was performed in all patients. The intervention group participated in a structured exercise program three times per week beginning one month after surgery and lasting 16 weeks. Patient assessment was performed before surgery (baseline) and after completion of the exercise program. The control group received the usual standard of care and was assessed similarly. Results: After surgery, weight, BMI and lean mass decreased significantly in both groups from baseline to the second assessment. Leptin was not significantly different from baseline to the second assessment in the physical exercise group but was significantly lower in the control group (p=0.05). Ghrelin increased over time in both groups, but the differences were not significant. When we associated leptin (the dependent variable) with weight (the independent variable), we found that lower weight was associated with lower leptin levels. A similar relationship was also observed between leptin and sarcopenia parameters (muscle strength and mass), as well as with bone health parameters (bone mineral density and t-score). Higher ghrelin levels were significantly associated with higher t-scores and z-score (p<0.05). Conclusion: Exercise has been shown to have a significant effect on leptin and ghrelin levels after bariatric surgery. By incorporating regular physical activity into their lifestyle, bariatric patients can optimize their weight loss outcomes and improve their overall health. After the physical exercise protocol, patients in the intervention group revealed more established leptin levels, which may indicate a protected pattern concerning decreased leptin levels. An unfavorable profile was evidenced, according to which greater weight loss, sarcopenia, and osteoporosis were associated with lower leptin levels.

Among the theoretical problems with the prevailing theory of cosmology, Lambda Cold Dark Matter (λCDM), the most serious appears to be the twofold problem with the cosmological constant lambda: Dark Energy and Hubble Tension. Despite a two-decade search for systematic errors in astrometry the problems have not been resolved. This paper posits a potential source of error that may have affected astrometry related to the current and past measurements of lambda.

Differential beamforming has attracted much research since it can utilize the array with small aperture size to form frequency-invariant beampatterns and achieve high directional gains. It has recently been applied to the linear loudspeaker array to produce a broadside frequency-invariant radiation pattern. However, designing steerable frequency-invariant beampatterns for the linear loudspeaker array has yet to be explored. This paper proposes a method to design the steerable differential beamformer with the linear loudspeaker array. We first determine the target differential beampatterns according to the desired direction, the main lobe width, and the beampattern order. Then, we transform the target beampattern into the modal domain for representation. The Jacobi-Anger expansion is subsequently used to design the beamformer so that the resulting beam pattern matches the target differential beam pattern. Furthermore, based on the criterion of minimizing the mean square error between the synthesized beam pattern and the ideal one, a multi-constraint optimization problem is formulated to calculate the optimal desired weighting vector. Simulations and experimental results show that the proposed method can achieve steerable frequency-invariant beamforming over 300 Hz – 4 kHz.

N-(diisopropylphosphanyl)benzamide, PhC(O)NHPiPr2, has been synthesized in good yield following two alternative procedures that employ benzamide as the starting material. The first one is a two-step preparation, in which N-(trimetilsilyl)benzamide is reacted with PiPr2Cl, to give the title compound in good yield, whereas the second one is a straightforward synthesis which converts benzamide into N-(diisopropylphosphanyl)benzamide by reaction with PiPr2Cl in the presence of N,N-dimethylpyridin-4-amine (DMAP) and triethylamine. NMR spectroscopy and X-ray diffraction analyses have been performed to characterize the new compound and elucidate its molecular structure in the solid state. N-(diisopropylphosphanyl)benzamide adds to the limited family of amido-substituted phosphines, RC(O)NHPR’2, which can be classified as bidentate hybrid P,O-ligands, both in their neutral and anionic forms, the latter achievable by deprotonation of the NH group.

Universities, like cities, have embraced novel technologies and data-based solutions to improve their campuses with ‘smart’ becoming a welcomed concept. Campuses in many ways are small-scale cities. They increasingly seek to address similar challenges and to deliver improved experiences to their users. How can data be used in making this vision a reality? What can we learn from smart campuses that can be scale up to smart cities? A short research study was conducted over a three-month period at a public university in the United Kingdom employing stakeholder interviews and user surveys, aiming at gaining insight into these questions. Based on the study, the authors suggest that making data publicly available could bring many benefits to different groups of stakeholders and campus users. These benefits come with risks and challenges such as data privacy and protection and infrastructure hurdles. However, if these challenges can be overcome, open data could contribute significantly to improving campuses and user experiences, and potentially set an example for smart cities.

The introduction of non-conventional renewable energies (photovoltaic and wind, in the residential case) demand new proposals and opportunities to obtain a domestic energy management system (HEMS), which allows reducing the use of electrical energy. The HEMS incorporates artificial intelligence (AI) techniques to respond to energy demand (DR), which can control, switch, turn on and off, modifying the consumption profile, reducing monthly billing, which as a consequence brings improvement. of the quality of life at home. Based on what has been described, a model for identifying electrical appliances and determining consumption patterns for the home is proposed, using intrusive measurement/actuator equipment called Smart Socket. The Smart Socket measures the electrical variables of voltage and current in real time, calculating the powers and active-reactive-apparent energies of each household appliance (or the most relevant ones). The information provided by the Smart Socket is used as a basis to configure the HEMS, with the aim of optimizing energy use using artificial intelligence techniques and tools, thus reducing energy consumption, CO2 emissions and the user's monthly billing. residential.

Solid propellants have significant applications in aerospace, and improving their combustion performance has become a hot research topic in recent years. Carbon black (CB) has been widely used in the field of catalytic pyrolysis due to its low cost, controllable morphology, and ease of modification. Herein, we first investigates the structure-activity relationship between the physicochemical properties of nine types of CB with a particle size range of 1-15 μm and a mass fraction of 5%, including oil absorption value, compression oil absorption value, and oxygen content, and the catalytic pyrolysis of ammonium perchlorate (AP), concluding that the function relationship between oil absorption value and high-temperature peak is Y1=1032.67-9.618x+0.038x2, the function relationship between compression oil absorption value and high-temperature peak is Y2=145.537+62.365ln(x), and the function relationship between oxygen content and high-temperature peak is Y3=e(6.085-0.02/x). Based on these, we further uses coal tar, which is abundant in sources, as the raw material to prepare five types of coal-based CB marked as CB1-CB5 at pyrolysis temperatures of 1000~1800 ℃. The relative error between the actual peak value and the predicted value of the CB/AP composite particles is less than 5%, proving that the peak temperature model of CB/AP composite particles can guide actual production. This study contributes to promoting CB application in improving the catalytic pyrolysis performance of ammonium perchlorate and enhancing the high added value utilization of coal-derived products.

Generative adversarial networks consisting of two parts, generator and discriminator, have obtained acceptable results in classification, prediction and generation of new samples in the discussion of 4G, 5G and 6G. In this article, the aim is to review a comprehensive study in relation to these networks. At the beginning of this research, different topics such as network training, network error checking and types of GAN's are investigated. In the following, the applications of GAN will be discussed separately.

The gut, often referred to as the "second brain," has significant contributions in the maintaining of the good bacteria contribute enormous role such as digestion, produce essential vitamins, support the immune system, and protect against harmful bacteria. The beneficial flora including Akkermansia muciniphila, Adlercreutzia equolifasciens, Barnesiella, Christensenella minuta, and Oxalobacter formigenes, along with their derived bioactive metabolites emerged as a key player in maintaining host metabolic and immune health. Dietary choices such as blending of prebiotic, fermented, symbiotic, anti-inflammatory foods, and secondary metabolites from a wide variety of plants and fruits promotes the diversity, composition, and stability of beneficial intestinal microbes. The colourful plant foods rich in phytochemicals bioactive compounds such as carotenoids, flavonoids, polyphenols, alkaloids, anthocyanins, and capsaicin offer a wide array of unique properties such as analgesics, antioxidants, anti-inflammatory, antimicrobials effect and promoting the abundance of beneficial gut bacteria and their bioactive metabolites confer numerous health-promoting effects. Here, we present knowledge about most beneficial gut bacteria and their derived metabolites in terms of their sources and health benefits. Finally, we discuss best foods that skew towards promoting healthy intestinal microbes.

This article presents a method for detecting P, QRS, T, and U waves in electrocardiogram (ECG) signals through advanced signal processing techniques, including a Butterworth bandpass filter and peak finding algo- rithms. The results are evaluated against the voltage ranges recommended in the literature, underscoring the importance of accurate wave detection for the diagnosis of various cardiac conditions.

Additive Manufacturing (AM) methods are increasingly beign abopted in the industry as an alternative for mass production. In particular, Fused Deposition Modeling (FDM) technology is leading the way in this field. However, the adhesion of layers in products produced using FDM technology is an important issue. These products are particularly vulnerable to forces acting parallel to the layers and specially to impact strength. This study aims to optimize the impact strength against loads acting parallel to the layers (ZX orientation) of PA6, one of the most widely used materials in the industry. This orientation is critical in term of mechanical properties, and the mechanical characteristics are significantly lower compared to other orientation. In this study, filaments containing pure PA6 with 15% short carbon fiber and 30% glass fiber were utilized. Additionally, printing temperature, layer thickness and heat treatment duration were used as independent variables. An L9 orthogonal array was employed in this study, and each experiment was repeated three times to conduct impact strength tests. Characterization, Taguchi optimization, a factor analyses were performed, followed by fracture surface characterization by SEM. As a result, the highest impact strength was achieved with pure PA6 at 8.9 kJ/m2, followed by PA6 GF30 at 8.1 kJ/m2 and the lowest impact strength was obtained with PA6 CF15 at 6.258 kJ/m2. When compared to the literature and manufacturer datasheets, it was concluded that the impact strength values have significantly increased, and the chosen experimental factors and their levels, particularly nozzle temperature, were effective.

For Sir Ronald Fisher, it is important to consistently obtain significant p-values to support an experimental hypothesis. So, replicating experiments to obtain independent p-values is a legitimate and desirable research practice. Several simple statistics have been proposed to meta-analyze p-values, all assuming that they are genuine, i.e. observations from independent standard Uniform random variables. But, as publication bias favors the studies that report "significant" p-values, when a p&gt;0.05 is obtained for the outcome of an experiment, some researchers will "fall into temptation" and decide to replicate the experiment in the hope of getting a smaller second p-value, ideally a significant one. Consequently, if the smallest of two p-values is reported, this is a Beta(1,2) distributed "fake" p-value, not a uniformly distributed genuine p-value. This is an unacceptable scientific research practice, and moreover the detection of fake p-values is unpractical. Even when it is possible, the analytic results to accommodate their existence in combined tests are cumbersome. For an informed decision, inclusive when the presence of fake p-values in a sample of p-values to be meta-analyzed is probable, tables with simulated critical values for the usual combined testing are supplied. This will also allow comparisons to be made between several combined tests.

The global malaria community has picked up the theme of malaria elimination in greater than 90 % of the world’s population in the next decade. The recent reports of P. vivax in all sub-Saharan Africa, including Duffy negative individuals, threaten the efforts to achieve elimination. This is not only in view of strategies that are tailored only to P. falciparum elimination, but also due to currently revealed biological characteristics of P. vivax concerning the relapse patterns of hypnozoites and conservation of a large biomass at cryptic sites in the bone marrow and spleen. A typical scenario has been observed in Botswana from the period between 2008 to 2018, which palpably projects how P. vivax could endanger efforts at malaria elimination where the two parasites co-exist. The need for the global malaria community, NMPs, funding agencies and relevant stakeholders to engage in a forum to discuss and recommend clear pathways for sub-Saharan Africa regarding malaria elimination including P. vivax, is warranted.

Academic and corporate research has been focusing on analyzing stock performances, financial markets, and investment strategies for decades. According to Lynch and Rothchild (1989), certain investments can be described as plays. In this work, the authors use the term for investments in value stocks, spin-offs, and turnarounds to analyze the long-term stock performance and risk-adjusted excess returns of up to five years for those stocks. Additionally, stocks with a supe-rior return performance are identified within an investment play based on low P/E and P/B mul-tiples. The study finds that value stocks, spin-offs, and turnarounds outperform the S&P 500 on average on a one-, three- and five-year investment horizon. The analysis of the three investment plays confirms earlier studies that investment plays constitute a profitable investment opportunity. Moreover, the research exemplifies that private investors could achieve an excess return (alpha) through a passive buy-and-hold investment strategy. Overall, the analysis provides a deeper in-sight into the long-term performance of value stocks, spin-offs, and turnarounds.

The complexity and interconnection of smart cities provide huge political, technical, and socioeconomic challenges for the designers, integrators, and organisations who are responsible for the administration of these new entities. A growing number of studies are concentrating their attention on the safety, privacy, and potential dangers that exist within smart cities. These studies are drawing attention to the dangers that are associated with information security as well as the challenges that smart city infrastructure faces in the management and processing of personal data. This state of the art review of the literature analyses a number of issues pertaining to smart homes, offers a helpful synthesis of the important information found in the primary research, and creates a model for the interaction between smart cities. An overview of smart home research incorporating machine learning, including everything from definition to current research state. The state of art begins with a smart home definition, followed by descriptions of smart home elements, typical research projects, smart home network research status, smart home appliances, and difficulties. The term "smart home" refers to a subcategory of "everyday computing" that includes "smart technology" in order to improve a person's level of convenience, health, safety, and security while also reducing their When controlled by artificial intelligence, the applications for the smart home provide users with context-aware settings, services, and remote control, which significantly increases the level of user satisfaction.

Over the recent decades people’s (rural and urban) communities are facing numerous social and economic changes and challenges. Some of those challenges have been increasingly addressed through the lenses of technological developments and digitalization. In this paper we have made a review of already existing practices while focusing on the existing implementations of the smart village concept and the importance of digital transformation for rural areas. We give special attention to EU policies which we are using as an already existing framework for understanding our own forthcoming examples. We have shown the parallels between the findings and insights from different regions and made an evaluation of presented practices. Our main argument stems from our own previous experiences and experiences of other research approaches, and is grounded on the argument that rural areas are not uniform, and that smart rural development has to be applied in combination with place-based approach. We present the cases of Slovenian pilot practices and support our argument by proposing the FabVillage concept.

The article describes the application of the Smart City concept and the economic opportunities it creates, infrastructure and services, and opportunities to improve governance. The main features of the Smart City concept, development directions and evolution, standards and solutions, factors and obstacles to its implementation have been analyzed by the author. The experience of different countries in the application of digital technologies is discussed. The article provides the scope and structure of the "smart" market, application stages and scenarios. International experience in this field was widely analyzed and examples were given, comparisons were made and suggestions were made. The article talks about smart cities, the construction of which has already begun in Azerbaijan. The application of the smart city concept in Azerbaijan has been studied. It is stressed that the spread of digital technologies for the construction of a smart city in Azerbaijan is a prerequisite. The Network Readiness Index (NRI) identifies the indicators that are holding back Azerbaijan in the ranking for 2021. In our study, based on the growth dynamics for 2017-2020, the forecast was calculated by analyzing the trend in the ICT development index in Azerbaijan for 2022-2025.

This study presents the experimental and analytical evaluations on an innovative connection class under cyclic loading. The connection was an H- or I-shaped section as a short stub column (SSC) between the end-plate and the column. The stub section was bolted to the column flange on the one side and bolted to the beam along with the welded end-plate on the other side. Stiffeners were installed on the webs and flanges of the beam and stub to ensure the necessary stiffness of the connection. The variables included thickness of stub flange/web and height of stub web. The cyclic loading was applied on a sample of the proposed connection according to AISC ANSI/AISC 341-16 loading protocol. Experimental observations displayed that the proposed connection, one can either employ hot rolling sections or create the connection as a plate girder, in which case the flange thickness and stub web, as well as the distance between two flanges and their height, was obtained according to the demand and performance of the structure. The optimum cross-section of the stub was then obtained. Also, the analytical model was calibrated using the finite element method (FEM), and its performance was confirmed. The effective parameters of the proposed connection were determined by modeling in the FEM software, and the design method was presented.

Objective: In recent years, the field of Essential Thrombocythemia (ET) research has seen a significant accumulation of scientific findings, but comprehensive bibliometric analyses remain lacking. This study aims to fill that gap by performing a thorough bibliometric analysis of ET research, identifying key contributors and collaboration networks, and mapping the development trends to provide insights for future research directions. Methods: A bibliometric analysis of ET-related publications from 2001 to 2024 was conducted using CiteSpace, VOSviewer, and R packages. Data were retrieved from the Web of Science Core Collection, with a focus on publication volume, citation analysis, co-authorship networks, co-citation relationships, and citation bursts. Results: A total of 4,297 studies published in 778 journals were included in the analysis. ET research has seen rapid growth, with researcher clusters in the United States and Europe driving progress through extensive regional and international collaborations. Leading researchers, such as Ayalew Tefferi from the Mayo Clinic and Alessandro M. Vannucchi from the University of Florence, have made significant advances in ET classification, molecular mechanisms, targeted therapies, and disease management. The discovery of driver mutations, such as JAK2, has revolutionized the diagnostic and therapeutic approaches to ET. Research focus has shifted from clinical morphological diagnosis to molecular diagnostics, with the field now entering the era of targeted therapies. However, the inherent heterogeneity of ET continues to present challenges for the widespread implementation of personalized precision treatment. Conclusion: Bibliometric analysis demonstrates significant advances in ET research, particularly in molecular pathology and targeted therapies. However, the heterogeneity of ET remains a major obstacle to personalized treatment. Future research should focus on further elucidating the pathogenesis of ET and improving stratified management approaches to achieve individualized precision therapy.

Phosphorus (P) is an essential element in food production, but it is often largely unavailable for plants as it persists in soils in immobilized forms. Farmers have been using P fertilizers extensively to overcome this unavailability, leading to the exhaustion of non-renewable deposits of phosphorite, rising fertilizers prices and causing several environmental impacts such as eutrophication. Its large-scale utilization is also inefficient since most of the added P becomes quickly unavailable for the plants. Therefore, farming solutions that improve P uptake, P use efficiency of plants and P mobilization in soils are highly important. In this narrative review, we summarized and explored the link between the Silicon (Si) and P cycles in soils. Silicon is quasi-essential for plants, and it has been established that its presence in soil and uptake by plants has several benefits, especially in toxic and nutrient-deficient conditions. Here, we established that Si in soils can affect crop production in P-deficient conditions through: 1) the pH effect – Si improves organic matter decomposition and decreases Al3+ availability; the Si uptake effect – the deposited Si in the plant improves its photosynthetic performance, improves the root ability to uptake P, improves organic matter decomposition and increases P/Mn ration in plant, improving P use; and 3) the Si soil effect – Si stimulates phosphorite rocks weathering and competes with P for the binding places at the surface of Ak and Fe hydroxides, releasing P into soil solution. This positive effect of Si on P mobilization in soils and consequent use by crops should be further disseminated to farmers and other relevant stakeholders.

Cystic fibrosis (CF) diagnosis can be a challenge due to the large spectrum of pathogenic variants in the CFTR gene and the effects of complex alleles. Next-generation sequencing has improved our understanding of the contribution of these complex alleles to the wide spectrum of CF clinical symptoms and to the response to medications. Herein, we studied nine CF patients from six unrelated families carrying the complex allele p.[Ile148Thr;Ile1023_Val1024del] with a frequency of 0.18%. All the patients were from Central Mexico. This complex allele was found in trans with Class I and II pathogenic variants (PVs) such as [c.1521_1523del, p.(Phe508del), and c.3231_3232del, p.(Phe1078Profs*77)]. A targeted search of a dataset of 2,217 exomes from healthy individuals revealed that eight individuals (0.18%) carried the p.(Ile148Thr) variant, but only one (0.022%), who was also born in Central Mexico, was a carrier of the complex allele. These findings led us to hypothesize a founder effect for the p.[Ile148Thr;Ile1023_Val1024del] complex allele in Mexican patients with CF, probably through migration from the French-Canadian population in Mexico. Finally, protein modeling revealed that this complex allele disrupts the secondary structure of the CFTR protein and might alter the ion flow.

Increasingly, information technology facilitates the storage and management of data useful for risk analysis and event prediction. Studies on data extraction related to occupational health and safety are increasingly available; however, due to its variability, the construction sector warrants special attention. This review is conducted under the research programmes of the National Institute for Occupational Accident Insurance (Inail). Objectives: The research question focuses on identifying which data mining (DM) methods, among supervised, unsupervised, and others, are most appropriate to be applied to certain investigation objectives, types, and sources of data, as defined by the authors. Methods: Scopus and ProQuest were the main sources from which we extracted studies in the field of construction, published between 2014 and 2023. The eligibility criteria applied in the selection of studies, were based on the Preferred Reporting Items for Systematic Review and meta-analysis (PRISMA). For exploratory purposes, we applied hierarchical clustering, while for in-depth analysis, we use principal component analysis (PCA) and meta-analysis. Results: The search strategy based on the PRISMA eligibility criteria, provided us with 61 out of 2,234 potential articles, 202 observation, 91 methodologies, 4 survey purposes, 3 data sources, 7 data types, and 3 resource type. Cluster analysis and PCA organized the information included in the paper dataset into two dimensions and labels: "supervised methods, institutional dataset, and predictive and classificatory purposes" (correlation 0.97÷8.18E-01; p-value 7.67E-55÷1.28E-22) and the second, Dim2 "not-supervised methods; project, simulation, literature, text data; monitoring, decision-making processes; machinery and environment" (corr. 0.84÷0.47; p-value 5.79E-25÷3.59E-06). We answered the research question regarding which method, among supervised, unsupervised, or other, is most suitable for application to data in the construction industry. Conclusions: The meta-analysis provided an overall estimate of the better effectiveness of supervised methods (Odds Ratio = 0.71, Confidence Interval 0.53÷0.96) compared to not-supervised methods.

In this paper, various Ni-P composite coatings containing toner, MoS2, and nano-SiO2 particles were deposited on steel substrates by the electroless method. Then, the electrochemical properties of these coatings after a heat treatment process were compared. The microstructural evaluations were also done by using the optical and electron microscopy methods. Both Tafel polarization and electrochemical impedance spectroscopy techniques were utilized to survey the electrochemical behavior of such coatings. The surface morphology of all coatings contained cauliflower-like nodules. The X-ray diffraction patterns showed the crystalline phases of Ni and Ni3P for all coatings after the heat-treatment step. Obtained results showed that all composite coatings exhibited lower corrosion rates with respect to Ni-P coatings. Such a reduction was about 21.6-92.2%. This behavior was attributed to the presence of reinforcement as barriers for corrosive ion diffusion through the coating plus the changes in detected phases and thickness. Electrochemical impedance spectroscopy test results also demonstrated that the increase in the polarization resistance for composites coatings was about 18.4-85.3% after 1 h immersion in a 0.6M NaCl solution; however, when the immersion time increased to 24 h, such increased resistance changed to 18.1 to 73.1%. Totally, despite the lower deposition rate, the presence of MoS2 and nano-SiO2 particles were more effective than toner particles to raise the corrosion rate of the Ni-P coating.

In this paper, we investigate p-adic q-integral (q-Volkenborn integral) on Z_p of p-adic gamma function via their Mahler expansions. We also derived two q-Volkenborn integrals of p-adic gamma function in terms of q-Daehee polynomials and numbers and q-Daehee polynomials and numbers of the second kind. Moreover, we discover q-Volkenborn integral of the derivative of p-adic gamma function. We acquire the relationship between the p-adic gamma function and Stirling numbers of the first kind. We finally develop a novel and interesting representation for the p-adic Euler constant by means of the q-Daehee polynomials and numbers.

It is known that the class of p-normed spaces (0 < p ≤ 1) is an important generalization of usual normed spaces with rich topological and geometrical structure, but the most of tools and general principles in nature with nonlinearity have not been developed yet, thus the main goal of this paper is to develop tools for nonlinear analysis under the framework of p-vector spaces. In particular, we first develop the general fixed point theorems which provide solutions to answer Schauder conjecture since 1930’s in the affirmative for p-vector spaces when p = 1 (which is just general topological vector spaces); then the one best approximation result for upper semi-continuous mappings is given, which is used as a powerful tool to establish fixed points for non-self set-valued mappings with either inward or outward set conditions; and finally we establish comprehensive existence results of solutions for Birkhoff-Kellogg Problems, and the general principle of nonlinear alternative by including Leray-Schauder alternative and related results. The results given in this paper not only include the corresponding results in the existing literature as special cases, but also expected to be useful tools for the study of nonlinear problems arising from theory to practice.

This article aims to analyze household energy data to predict electricity self-sufficiency and identify the key features that impact it. For this purpose, we use SHAP (Shapley Additive Explanations), LightGBM (Light Gradient Boosting Machine), and a correlation heatmap-based framework to analyze 12 months of energy and questionnaire survey data collected from over 200 smart houses in Kitakyushu, Japan. We use the SHAP summary plot to identify the impact-wise order of key features influencing the electricity self-sufficiency rate (ESSR). Using SHAP, we demonstrated that key features are; housing types, average monthly electricity bill, floor heating, electric capacity, number of washing and drying machines, fee plans, occupation of household head, total floor area, average monthly gas bill, cooking equipment, etc. Furthermore, we adopted the LightGBM classifier with $\ell^1$ regularization to extract the most significant features and predict the electricity self-sufficiency rate of households. This LightGBM-based model can also predict the electricity self-sufficiency rate of households that did not participate in the questionnaire survey. A heat map is also used to analyze the correlation among household variables. The findings discussed in this article offer valuable insights for energy policymakers to achieve the targets of energy self-sufficient houses.

The main aim of this paper is to set some correlations between Boole polynomials and p-adic gamma function in conjunction with p-adic Euler contant. We develop diverse formulas for p-adic gamma function by means of their Mahler expansion and fermionic p-adic integral on ℤ_{p}. Also, we acquire two fermionic p-adic integrals of p-adic gamma function in terms of Boole numbers and polynomials. We then provide fermionic p-adic integral of the derivative of p-adic gamma function and a representation for the p-adic Euler constant by means of the Boole polynomials. Furthermore, we investigate an explicit representation for the aforesaid constant covering Stirling numbers of the first kind.

This paper presents an innovative methodology for enhancing museum visitor experiences through personalized content delivery using a combination of explicit and implicit visitor profiling. The approach integrates Bluetooth Low Energy (BLE) smart badges to collect telemetry data, enabling precise visitor localization and dynamic group formation based on real-time proximity and shared interests. Initial profiling begins with OAuth registration and brief surveys, which is then refined through continuous tracking of exhibit interactions and time spent at each exhibit. An AI-driven system delivers content to individual and group profiles, fostering both personalized learning and social interaction. This methodology addresses the limitations of traditional profiling by adapting to visitor behaviors in real-time while maintaining a strong focus on data privacy and ethical considerations. The proposed system not only enhances engagement and satisfaction but also sets the stage for future advancements in personalized cultural experiences.

Background: Smart transport plays a crucial role in urban planning and the transition from traditional to smart cities in developing countries with sustainability requirements.Traditional cities in developing countries often suffer from traffic congestion,air pollution, and inadequate public transportation systems,which can impede economic growth and negatively impact the quality of life for residents. Smart transport solutions can address these challenges by providing more efficient, sustainable.Here is a possible business model for an ITS system in a high-potential city in Iran,Based on IoT analysis, Mashhad city in Iran selected as a high-potential city to be changed to a smart city in the transportation sector.In the localization business model,the Uber smart transportation business model as a successful world experience is considered the base model. Methods: Based on the literature review,various criteria and sub-criteria were identified and determined in designing a new localized transportation business model.A questionnaire was prepared and filled with the help of 11 experts,method IAHP technique; Results:The present study showed the possibility of monthly payments for customers,software development, and the addition of luxury cars are among the most important sub-criteria with high weights;Conclusions: Working with transport companies,schools and universities as key partners solves reaching a strong and sustainable smart transportation system.

This study assessed stakeholders’ perception on the prospects and challenges of practising Climate–Smart Agroforestry in the Asunafo North Municipal Assembly in the Ahafo Region in Ghana. Interviewer administered questionnaires were used to collect cross-sectional data from 250 cocoa, food and cash crop farmers drawn from four (4) communities using simple random sampling. And nine (9) in-depth interviews were also conducted to elicit key stakeholder perspectives. Stakeholders also held the view that Climate-Smart Agroforestry encourages the use of stress-tolerant crop varieties, increase income, improve soil productivity, diversify farm produce, urges the reduction of input supply and recommends the timely usage of the inputs, ensures better market system for farm produce, cost of production decreases during the practice of Agroforestry, agro-ecological functions and Climate-Smart Agroforestry can best help adapt to the threats of climate change in the agriculture sector. The challenges included insecure tree ownership right, fast-declining soil fertility and long maturity period of Agroforestry trees, land tenure issues, illegal tree logging (chainsaw operators) on farms, lack of practical understanding of the approach, inadequate knowledge and information and inadequate supportive facilities in the study area. The study recommends further studies on the existing forest policy and legislations and its implications on the practice and adoption of Climate-Smart Agroforestry in respond to climate change in the area.

In the smart city, information and communications technologies (ICTs) are proposed as solutions to urban challenges, including sustainability concerns. While sustainability commonly refers to economic and environmental dimensions, the concept also contains a social component. Our study asked how smartphone applications (apps) address social sustainability challenges in urban transport, if at all. We focused on transport disadvantages experienced due to low income, physical disability, and language barriers. A review of 60 apps showed that transport apps respond to these equity and inclusion issues in two ways: (a) by employing universal design in general-use apps; including cost-conscious features; and providing language options (b) by specifically developing smartphone apps for persons with disabilities. The article discusses the study by positioning it in the literature of smart cities as well as socially sustainable transport.

The construction industry has witnessed the increasing use of digital tools and smart solutions, particularly, in the realm of buildings energy automation within the concept of smart cities. While to truly realize the potential benefits of smart cities, a broader scope of smart initiatives is required to support the transition from smart buildings towards smart neighbourhoods, appreciated as the critical unit of urban development. To support this interplay of smart solutions between buildings and neighbourhoods, this article aims to collect and review all smart solutions presented in existing scientific articles, technical literature, and realized European projects. These solutions are classified under two main sections of buildings and neighbourhoods, which are investigated through five domains: buildings energy-related uses, renewable energy sources, water, waste, and open space management. Showcasing the quantitative outcomes demonstrates the potential benefits of implementing smart solutions from buildings to neighbourhoods. Moreover, this research concludes that the true enhancement of energy conservation goes beyond the buildings’ energy component and can be genuinely achieved by integrating intelligent elements of the neighbourhood, due to their strong interdependencies. Future research is recommended to focus on assessing the effectiveness of these solutions towards resource conservation.

In the domain of software engineering, the accurate and effective classification of requirements is of paramount importance. Proper classifications of these requirements enable developers to create robust and error-free software solution. Traditional methods of user requirements classification face the issue of the reliance on manual processes, which are time-consuming, labor-intensive, and prone to human error. The limitations of traditional methods underscore the need for more automated, scalable, and robust approaches to user requirements classification in order to meet the demands of modern software development practices. To improve the classification process, we employed a Deep Learning (DL) methodology termed the Bidirectional Long Short-Term Memory (Bi-LSTM) model to conduct feature extraction, after which we merged these feature vectors into ML classifiers. Our research methodology is structured around a five-step process. Initially, the textual input is tokenized and converted to lowercase. Subsequently, we eliminate all punctuation. The pre-processed text is then subjected to a Bi-LSTM (Bidirectional Long Short-Term Memory) model for feature vector extraction. After that, this feature vector is fed into different classifiers such as Medium KNN, Cubic KNN, Linear SVM, Quadratic SVM, and Cubic SVM and obtained an accuracy of around 99.60% to 99.80% on a publicly available dataset of requirements.

Galactic rotation curve was formulated before the Sgr A* had been confirmed. The action of the Sgr A* on the rotation curve has not been considered. Now, it was observed that the fastest stars in the Milky Way is in the distance less than 0.5pc from the Sgr A*. It is contradicted with the current galactic rotation curve in which the orbital velocity near the center of the galaxy is the smallest. And, because of the advance of technology, it was observed that the circular velocity curve of the Milky Way from 5 to 30 kpc is with a significantly faster decline (Keplerian decline) compared to the inner parts. It is contradicted with the current curve in which the out parts could be larger or no decline. And, it was observed that the fast galaxy bar continue challenge the standard cosmology. For the reasons, we present an improved galactic rotation curve.

As a branch of regional innovation theories, social filter theory fundamentally reveals the reasons for the geography of innovation in different countries and regions. However, compared with some other regional innovation theories, social filter theory has been as silent as a sleeping beauty and hasn’t been fully developed. For enriching and developing social filter theory, this article systematically traces the source and comments on four aspects: the concept of social filter, the construction and measurement of indicators of social filter, the mechanism and empirical re-search of social filter affecting regional innovation and innovation transformation. Until recently regional innovation theories primarily focused on the superficial description of the phenomenon of innovation, but lack of attention to the local social filter condition of innovation generation and innovation transformation, which are the pre-condition of constructing mature innovation system. Therefore, additional efforts are still required to fill the current knowledge gap from the recom-mended directions in the article.

This study examines the significant impact of Houthi insurgent activities on maritime traffic within the strategic Red Sea and Suez Canal routes, essential conduits for global trade. It explores the correlation between regional instability, exemplified by Houthi actions from November 19, 2023, to February 5, 2024, and changes in maritime traffic patterns and operational efficiency. This study seeks to answer a critical question in transport geography: How does regional instability, exemplified by Houthi insurgent activities, affect maritime traffic patterns and the operational efficiency of the Red Sea and Suez Canal? Using descriptive statistics, qualitative analysis, and geospatial methods, the research highlights recent trends in maritime traffic and incidents, revealing spatial and geopolitical challenges in this crucial trade route.Findings indicate a notable decline in maritime activity in the Gulf of Aden and Suez Canal due to security concerns from Houthi attacks, prompting a significant shift to alternative routes, particularly around the Cape of Good Hope. This shift underscores the broader implications of regional instability on global trade and the importance of maintaining uninterrupted maritime flow. The study also emphasizes the economic ramifications, such as increased operational costs and freight rates due to longer transit times and enhanced security measures.The research concludes with a call for improved maritime security protocols and international cooperation to protect these strategic maritime pathways. It contributes to the discourse on transport geography by quantifying the direct impacts of regional conflicts on maritime logistics and proposing strategies for future resilience, highlighting the interconnected nature of global trade and security and the need for collective action against evolving geopolitical challenges.

The fall armyworm (FAW), Spodoptera frugiperda, a major pest in maize production, was assessed for its temporal and spatial distribution in maize fields during both the off and rainy seasons of 2021 and 2022. In this study, 30 and 50 maize plants were randomly sampled using a "W" pattern during the dry and rainy seasons, respectively. Larval density, infestation rates, and damage severity were monitored over time. Taylor's power law and the mean crowding aggregation index were applied to evaluate the dispersion patterns of the larvae. The results indicate a higher infestation rate and larval density in agroecological zone AZE 8 (fisheries zone of South Benin) compared to AZE 6 (ferralitic soils zone) during the off-season. In the rainy season, while the percentage of damaged plants was higher in AZE 8, no significant differences in larval density between the two zones were observed. The dispersion analysis revealed moderate aggregation (aggregation index = 1.25) with a basic colony of 2.08 larvae, reflecting the aggregation oviposition behavior of FAW. This study provides valuable monitoring data on the FAW's distribution, offering insights for further research on population dynamics and developing predictive models for integrated pest management strategies.

Objective: To explore the acceptability and feasibility of conducting comprehensive, community-based, hy-brid (in-person and virtual) mental health screening and feedback with diverse youth in the community. Methods: The Screening and Support for Youth intervention provides comprehensive assessment and thera-peutic feedback in community settings including symptoms, diagnoses, functional impairment, suicide, and clinical risk. Symptom severity, seven diagnoses and suicidality were assessed with the Kiddie Computer-ized Adaptive Test. Functional impairment was evaluated by youth self-report on the Weiss Functional Im-pairment Rating Scale. Measures were scored according to nationally developed norms and an algorithm was developed to aggregate symptoms and functioning to determine clinical risk. The results were discussed with participants in a motivational interview to promote insight and engagement in an online intervention. Results: Methodological innovations included using a QR code for recruitment, integrated in-person and virtual participation, and expansion from in-person recruitment within the schools to virtual engagement with youth throughout the community. The final sample included disproportionately more Black or African American and Hispanic youth as compared to school and community statistics, suggesting that hybrid re-search may facilitate recruitment of diverse populations. Qualitative interviews indicated that the screening and feedback raised youth awareness of their wellbeing and/or distress, its impact on their functioning, and engagement with options for improving wellbeing. Conclusion: Hybrid research, developed as a necessity during the pandemic, proved advantageous to the feasibility and acceptability of community-based recruit-ment of at risk, minoritized youth.

In order to deal with imprecision, ambiguity, and uncertainty in data analysis, Pawlak introduced rough set theory in 1982. This paper aims to expand the scope of basic set theory developed by presenting the notions of δP-upper and δP-lower approximations, that are based on the notion of δP-open sets, we additionally examine a few of their fundamental characteristics.