This paper analyzes ServiceNow’s overall strategy, business model, mission, vision, and key strategic risks. ServiceNow, a platform-as-a-service provider, has experienced significant growth and is poised for further expansion. The paper identifies strategic risks such as legislative and regulatory challenges, strategy development and execution risks, and competition in the cloud computing industry. Using Porter’s Five Forces framework, the assignment explores these risks and proposes mitigation strategies. Recommendations are made to protect intellectual property, maintain customer loyalty through subscription models, and ensure innovation in response to evolving market demands.

The use of DL algorithms in the domain of DM for AVs has garnered significant attention in the literature in the last years, showcasing considerable potential. Nevertheless, most of the solutions proposed by the scientific community encounter difficulties in real-world applications. This paper aims to provide a realistic implementation of a hybrid DM module in an AD stack, integrating the learning capabilities from the experience of DRL algorithms and the reliability of classical methodologies. This work encompasses the implementation of concatenated scenarios in simulated environments, and the integration of AD modules. Specifically, the authors address the DM problem by employing a POMDP formulation and offer a solution through the use of DRL algorithms. Furthermore, an additional control module to execute the decisions in a safe and comfortable way through a hybrid architecture is presented. The proposed architecture is validated in the CARLA simulator by navigating through multiple concatenated scenarios, outperforming the CARLA Autopilot in terms of completion time, while ensuring both safety and comfort.

This research was conducted to study the incidence of seed-borne fungi in stored sunflower seeds under ambient conditions as well as their influence on seed viability and vigour. Certified seeds, Quality Declared Seeds (QDS) and Farmer saved seeds (FSS) were stored for six months. Seed samples were taken every month testing for fungal infection percent (FIP), germination percentage (G%) and seedling vigour index (SVI). Eight fungal species namely as Aspergillus flavus, A. niger, Alternaria padwickii, A. zinniae, Botrytis cinerea, Curvularia lunata, Fusarium vericillioides and Rhizopus arrihizus were identified. At the end of experiment, the maximum species infection percentage were recorded on F. vericillioides (14.39), B. cinerea (14.28) in FSS and the minimum by A. zinniae (1.83) with QDS. Maximum total fungal infection incidence was recorded with FSS (73.11%) and minimum with QDS (66.94%) and certified seeds (67.06%). The QDS recorded the highest G% (81.56) and certified seeds (81.33%), the maximum SVI (96.76) was in certified seeds and 95.69 (in QDS). The minimum G% (60.67) and SVI (65.98) were found in FSS. The highest G% and SVI were recorded in seeds with minimum FIP. These results suggest that, fungal infections may negatively affect the seed viability and vigour. For the first time, the incidence of seed-borne fungi in stored sunflower seeds have been determined in Tanzania.

The presence of various pesticides in natural streams and wastewater is a significant environmental issue due to their high toxicity, which causes harmful consequences even at low quantities. One cost-effective method to remove these pollutants from water could be through adsorption using inexpensive, easily obtained adsorbent - biochar. This study demonstrates the effectiveness of using biochar produced from wheat grains to eliminate alachlor from water. The sorption properties of the biochar and the likely removal mechanisms have been defined. The study found that the biochar removed 76-94% of alachlor, depending on the initial concentration of the pesticide in water. The pseudo-second-order kinetic model (R² = 0.999) and the Langmuir isotherm model (R² = 0.996) effectively characterized the elimination of alachlor by wheat grains biochar. The analyzed biochar, with its micropores and various surface functional groups, can effectively adsorb alachlor and trap it within its structure.

Background: Front-of-package labelling (FoPL) is shown to be effective in assisting consumers make healthier food choices. Several countries are implementing various types of FoPL systems. Objective: This study explored consumers’ perceptions and understanding of three different FoPLs and their insights into features that could influence the effectiveness of the symbols in Kenya Methods: A qualitative study was conducted in four Counties in Kenya; Nairobi, Mombasa, Garissa, and Kisumu. Data was collected through twelve focus group discussions with 137 adults drawn from diverse socio-demographic and socio-economic backgrounds. Three FoPLs were assessed: Red and Green (RG) Octagon, Red and Green Octagon with icons and text (RGI), and the Black Octagon Warning label (WL). The FGDs explored participants’ perceptions of the symbols’ visibility and memorability, their understanding, potential effectiveness, and cultural appropriateness. Printed images displaying four different commonly consumed products bearing specific FoPLs were used during data collection. Data was analyzed thematically and organized using NVivo version 14.0. Results: Results showed that Kenyan consumers had varied perceptions about the proposed FoPL symbols. Majority of the participants found the black Octagon WL to be most visible and memorable due to its good blend of black and white colours. Although the RG octagon symbol and RGI octagon symbols were also found to be eye-catching due to their bright colours, it emerged that the different colours often confused some participants on their meaning. Most participants understood the WL compared to the RG and RGI because they found the additional text more educative. Generally, the WL was preferred as the symbol most likely to influence consumer purchase behaviours and food consumption. All the three FoPLs tested were found to be culturally appropriate. Conclusions: The Black Octagon Warning Label is the most easily visible and understood among the three FoPLs tested and has the potential to influence purchase and consumption behaviours among Kenyan consumers. Although the RG and RGI symbols are visually appealing to many, confusion related to different colours could affect their effectiveness. Consumers need to be educated on the use of FoPLs to ensure they discourage the purchase and consumption of unhealthy foods.

Heavy infestations of weedy rice can reduce rice yields and affect farmers' incomes. So far, the control of weedy rice is still unsolved and depends more on the use of herbicides, which can harm the environment and human health. The phenomenon of allelopathy can be used to develop a new strategy to control weedy rice that does not depend on the use of herbicides. The objective of this study was to evaluate the allelopathic ability of T. procumbens against the growth of weedy rice with different morphological characteristics. Although morphologically different, seedling growth of all weedy rice was found to be inhibited by the presence of leaf leaching and root exudates of T. procumbens, as determined by sandwich and plant box methods. GC-MS analysis identified 21 allelochemicals present in the leaves of T. procumbens, mainly consisting of various fatty acids such as hexadecanoic acid. Further investigation revealed that the aqueous extract of T. procumbens at higher concentration (100%) reduced the germination rate of weed variants WR3 and WR7 by 24% and 19%, respectively. Seedling growth of the weedy variants was inhibited with increasing concentration of leaf extract, with radicle growth of both WR3 and WR7 reduced by 100% and 98%, respectively, at the highest concentration. The leaf debris incorporated into the soil similarly inhibited the growth of the seedlings and the chlorophyll content of the weedy rice. However, the cultivar MR220 CL2 showed lower sensitivity to T. procumbens, and its total chlorophyll content increased with increasing concentration of leaf debris. Our study revealed that T. procumbens is suitable as a bio-herbicide for future sustainable control of weedy rice, especially in the granaries of MR220 CL2

An update was made on the flora of the Serra dos Órgãos National Park, located in the Atlantic Forest domain, Rio de Janeiro state, Brazil. Collections of plant samples were carried out from 2007 to 2010. These data were complemented by consultations with national and international herbaria, and scientific publications related to the flora of the Park. The total number of known plants is 3096, divided into 2412 angiosperms, 1 gymnosperm, 434 ferns and lycophytes and 249 bryophytes. Of these, 33 are endemic to the Park, 190 are endemic to the state of Rio de Janeiro, and 97 are classified in one of the IUCN threat categories. With these results, Serra dos Órgãos National Park becomes the Brazilian protected area with the richest known flora, harboring 38% of the species known to Rio de Janeiro state in an area of about 0,5% of its size. Despite the park’s great plant diversity, about 38% of the species had only one record and may be considered locally rare. Encouraging research and botanical collection in the park may increase the representation of locally rare species, rediscover species which are considered extinct and record new species for science.

Disabled people have been all but invisible in refugee research. The same can be said of refugees in disability studies. We propose an analytical framework that integrates critical and trauma approaches to inform studies of the experiences of disabled refugees as they express their agency and engage in their communities. Critical disability theory questions the assumptions undergirding the social model that have led to “fixed” conceptions of disabled people and ignored their innate agency. By equating disability with oppression, social model proponents have argued that the emancipation of disabled people may only be achieved through shifts in oppressive structures. On the other hand, understanding how trauma affects disabled refugees helps avoid defining them simply as dependent victims and omitting or overlooking their resilience. We contend that a sociocultural understanding of trauma allows for a dynamic and contextual perspective on agency and resilience; one that challenges the “traumatized refugee” narrative. The principal claim underpinning the framework is that disabled refugees should be regarded as capable agents of change confronting contexts of continuing trauma, displacement and vulnerability. This article offers an integrative and interpretive understanding of the lived experiences of disabled refugees that highlights the possibilities inherent in their human agency.

This paper addresses the author’s current understanding of the physics of interactions in polymers under a voltage field excitation. The effect of a voltage field coupled with temperature to induce space charges and dipolar activity in dielectric materials can be measured by very sensitive electrometers. The resulting characterization methods, Thermally Stimulated Depolarization (TSD) and Thermal-Windowing Deconvolution (TWD), provide a powerful way to study local and cooperative relaxations in the amorphous state of matter that are, arguably, essential to understand the glass transition, molecular motions in the rubbery and molten states and even the processes leading to crystallization. Specifically, the paper describes and tries to explain ‘interactive coupling’ between molecular motions in polymers by their dielectric relaxation characteristics when polymeric samples have been submitted to thermally induced polarization by a voltage field followed by its depolarization at constant heating rate. Interactive coupling results from the modulation of the local interactions by the collective aspect of those interactions, a recursive process pursuant to the dynamics of the interplay between the free volume and the conformation of dual-conformers, two fundamental basic units of the macromolecules introduced by this author in the “Dual-Phase” model of interactions. This model reconsiders the fundamentals of the TSD and TWD results in a different way: the origin of the dipoles formation, induced or permanent dipoles; the origin of the Wagner space charges and of the Tg, transition; the origin of the TLL manifestation; the origin of the Debye elementary relaxations’ compensation or parallelism in a relaxation map; finally, the Dual-Phase origin of their super-compensations. In other words, this paper is an attempt to link the fundamentals of TSD and TWD activation and deactivation of dipoles that produce a current signal with the statistical parameters of the “Dual-Phase”model of interactions underlying the Grain-Field-Statistics.

Several studies have explored the use of hologram technology in architecture and urban design, demonstrating its feasibility. Holograms can represent 3D spatial data and offer an immersive experience, potentially replacing traditional methods such as physical 3D, and offering a promising alternative to mixed-reality display technologies. Holograms can visualize realistic scenes such as buildings, cityscapes, and landscapes using the novel view synthesis technique. This study examines the suitability of spatial data collected through the Gaussian splatting method for tabletop hologram visualization. Recent advancements in Gaussian splatting algorithms allow for real-time spatial data collection of higher quality compared to photogrammetry and neural radiance fields. Both hologram visualization and Gaussian splatting share similarities in recreating 3D scenes without the need for mesh reconstruction. In this research, unmanned aerial vehicle-acquired primary image data were processed for 3D reconstruction using Gaussian splatting techniques and subsequently visualized through holographic displays. Two experimental environments were used including a building and a university campus. As the result, 3D Gaussian data has proven to be an ideal spatial data source for hologram visualization, offering new possibilities for real-time motion holograms of real environments and digital twin.

The canine distemper virus (CDV) is a morbillivirus implicated in several signs in the Canidae family, in dogs, conjunctivitis, digital hyperkeratosis and neuropathologies are common signs of its infection. Even with the existing vaccination, the canine distemper disease persists worldwide so the molecular pathways implicated in the infection processes has been an interesting and promisor area in the new therapeutic drugs research over recent years. It is known that in the process of virus infection the endoplasmic reticulum organelle lost its homeostasis inducing stress and the subsequence unfolded protein response or UPR in which three ER-trans-membrane proteins are implicated: PERK, IRE1 and ATF6. Moreover, in a prolonged ER stress the apoptosis dead are induced through CHOP protein, as a final step of virus infections. Molecular and cell culture techniques as RT-qPCR and RT-PCR were used in the present study. We demonstrate the activation in vitro of the three UPR pathways after infection with an attenuated strain of CDV. Also, the implication of a MAPK pathway through p38 protein and the apoptotic protein CHOP was funded to participate in all times of infection. Even more, our study suggested that CDV replication occur in a PERK-dependent manner.

This study explores the application of the BPM lifecycle to optimize the Market Analysis process within the Market Intelligence department of a major energy company. The semi-structured, virtual nature of the process necessitated careful adaptation of BPM methodology, starting with process discovery through data collection, modeling, and validation. Qualitative analysis, including value-added and root-cause analysis, revealed inefficiencies. The redesign strategy focused on selective automation using Python scripts and Power BI dashboards, incorporating techniques such as linear programming and forecasting to improve process efficiency and quality while maintaining flexibility. Post-implementation, monitoring through a questionnaire showed positive results, though ongoing interviews were recommended for sustained performance evaluation. This study highlights the value of BPM methodology in enhancing decision-critical processes and offers a model for adaptable, value-driven process improvements in complex organizational environments.

The global burden of respiratory syncytial virus (RSV) and severe associated disease is prodigious. RSV specific vaccines have been launched recently but there is no antiviral medicine commercially available. RSV polymerase (L) protein is one of the promising antiviral targets along with fusion and nucleocapsid proteins. During medicinal chemis-try campaign, two potent L-protein inhibitors (PC786 and PC751) were identified. Both compounds inhibited RSV A/B-induced cytopathic effect in HEp-2 cells equally, but PC786 was more potent than PC751 in bronchial epithelial cells. Repeated treatment with escalating concentrations on RSV A2 infected HEp-2 cells revealed both inhibitors led to a Y1631H mutation in the L protein, but only PC786 induced a mutation in the M protein (V153A). By L-protein fragment and M protein binding analysis, we showed that the M protein interacts with the 1392-1735 amino acid region of the L protein, where potentially PC786 binds. In addition, PC786 treatment or PC786 induced mutant RSV was found to increase M protein nuclear localisation later in infection concomitant with delayed fusion protein localisation at the budding viral filaments. As M protein is known to play a key role in virus assembly and budding late in infection, our data suggests that disrupting the interaction between M and L could provide a novel target for antiviral development.

I want to meaningfully average a pathalogical function (i.e., an everywhere surjective function whose graph has zero Hausdorff measure in its dimension). In case this impossible, we wish to average a nowhere continuous function defined on the rationals. We do this by taking the most generalized, satisfying extension of the expected value, w.r.t the Hausdorff measure in its dimension, on bounded functions with domains of finite measure which takes finite values only. As of now, I’m unable to solve this due to limited knowledge of advanced math and most people are too busy to help. Therefore, I’m wondering if anyone knows a research paper which solves my doubts. Unlike the previous paper, “Finding a Research Paper Which Meaningfully Averages Pathalogical Functions”) we add motivations, examples, and change parts of the original paper.

During the Covid-19 pandemic, although the experience of workers and managers was examined, the role, experiences and functions of supervisors was relatively underexplored, with no investigation into their changing health and safety responsibilities. This project attempted to fill this gap. Twenty supervisors across Canada were interviewed for an hour. A Framework Method guided the study. We used a conceptual framework of 10 supervisor functions to help direct the data collection, identify codes, manage and organize the data analysis, and identify major themes which were highlighted in the findings. What was found was that since supervisors did not have access to workers’ homes, they could not execute most of their OHS functions. They were obliged to give workers more control over how and when they worked. They Increased their communications with their workers in response to workers’ psychological health concerns. Notably, supervisors reported that they were under extreme stress. A hybrid work environment, with workers sometimes working at home, has become the new norm. Supervisor stress will continue to escalate unless upper management provides more support, supervisors get training on how to deal with the psychological health and safety of workers, and supervisors’ responsibilities are re-defined for at-home workers.

Generative Adversarial Networks (GANs) are powerful models for generative tasks but face significant challenges such as instability, mode collapse, and inefficient convergence. This paper introduces a theoretical framework leveraging Fermi-Dirac statistics, Ruppeiner geometry, phase transition dynamics, and graph theory to address these issues. The proposed theorems provide a robust mathematical foundation for enhancing GAN stability, diversity, and convergence. Experimental validation on the MNIST dataset demonstrates that the application of these theorems results in improved Inception Scores, reduced Fréchet Inception Distances, and stable training dynamics, as indicated by Ruppeiner curvature analysis. The findings suggest that these theoretical insights offer a comprehensive solution to the persistent challenges in GAN training, paving the way for more reliable and effective generative models.

In this paper, a "local" algorithm is determined for the construction of two recurrent sequences of positive primes ( ) and ( ), (( ) dependent of ( ) ), such that for each integer n their sum is equal to 2n . To form this, a third sequence of primes ( ) is defined for any integer n by : = Sup( p ∈ : p ≤ 2n - 3 ) , where is the infinite set of primes. The Goldbach conjecture has been proved for all even integers 2n between 4 and 4. In the table of terms of Goldbach sequences given in appendix 10 , values of the order of 2n = are reached. This " finite ascent and descent " method proves the binary Goldbach conjecture ; an analogous proof by recurrence is established and an increase in by 0.7( is justified. Moreover, the Lagrange-Lemoine-Levy conjecture and its generalization, the Bezout-Goldbach conjecture, are proven by the same type of procedure.

Climate change has significant implications for agriculture, especially in viticulture, where temperature plays a crucial role in grapevine growth. Mendoza's climate is ideal for producing high-quality wines, but 21st-century climate change is expected to have negative impacts. This study aimed to evaluate the effects of increased temperature on the phenology, physiology, and yield of Malbec, Bonarda, and Syrah. A field trial was conducted over two seasons (2019-2020 and 2020-2021) in an experimental vineyard with an active canopy heating system (+2-4ºC). Phenological stages (budburst, flowering, fruit set, veraison, harvest), shoot growth (SG), number of shoots (NS), stomatal conductance (gs), chlorophyll content (CC), chlorophyll fluorescence (CF), and water potential (ψa) were measured. Additionally, temperature, relative humidity, light intensity, and canopy temperature were recorded. Heat treatment advanced all phenological stages by approximately two weeks, increased SG and NS, and reduced gs and ψa during the hottest months. CC and CF remained unaffected. The treatment also resulted in lower yields, reduced acidity, and increased °Brix in both seasons. Overall, rising temperatures due to climate change advance the phenological phases of Malbec, Syrah, and Bonarda, leading to lower yields, higher °Brix, and lower acidity, although physiological variables remained largely unchanged.

To address the instability of wind power caused by the randomness and intermittency of wind generation, as well as the challenges in power compensation by Hybrid Energy Storage Systems (HESS), this paper proposes a State of Charge (SOC) balancing control strategy based on Successive Variational Mode Decomposition and multi-fuzzy control. First, a consensus algorithm is used to enable communication between energy storage units to obtain the global average SOC. Then, the Secretary Bird Optimization Algorithm (SBOA) is applied to optimize the Successive Variational Mode Decomposition (SVMD) and Variational Mode Decomposition (VMD) for the initial allocation of wind power, resulting in the smoothing power for hybrid energy storage and the grid integration power. Finally, considering the deviation between the current SOC of the storage units and the global average SOC, dynamic partitioning is used for multi-fuzzy control to adjust the initial power allocation, achieving SOC balancing control. Simulations of the control strategy were conducted using Matlab/Simulink, and the results indicate that the proposed approach effectively smooths wind power fluctuations, achieving stable grid integration power. It enables the SOC of the HESS to quickly align with the global average SOC, preventing the HESS from entering unhealthy SOC regions.

The RECONNECT project addresses the fragmentation of Ireland's public healthcare systems, aiming to enhance service planning and delivery for chronic disease management. By integrating complex systems within the Health Service Executive (HSE), it prioritizes data privacy while supporting future digital resource integration. The methodology encompasses structural integration through a Federated Database design to maintain system autonomy and privacy, semantic integration using a Record Linkage module to facilitate integration without individual identifiers, and the adoption of the HL7-FHIR framework for high interoperability with the national electronic health record (EHR) and the Integrated Information Service (IIS). This innovative approach features a unique architecture for loosely coupled systems and a robust privacy layer. A demonstration system has been implemented to utilize synthetic data from the Hospital Inpatient Enquiry (HIPE), Chronic Disease Management (CDM), Primary Care Reimbursement Service (PCRS) and Retina Screen systems for healthcare queries. Overall, RECONNECT aims to provide timely and effective care, enhance clinical decision-making, and empower policymakers with comprehensive population health insights.

Background and Objectives: Acute aortic dissection (AD) is a life-threatening condition and early detection can significantly improve patient outcomes and survival. This study evaluates the clinical benefits of integrating a deep-learning (DL)-based application for automated detection and prioritisation of AD on chest CT angiographies (CTAs), focusing on the reduction of scan-to-assessment (STAT) and interpretation times (IT). Materials and Methods: This retrospective Multi-Reader, Multi-Case (MRMC) study compared AD detection with and without artificial intelligence-(AI) assistance. Ground truth was established by two U.S. board-certified radiologists, while three additional expert radiologists participated as readers. All participants assessed the same CTAs without AI-assistance (pre-AI arm) and, after a 1-month washout period, with the help of the device outputs (post-AI arm). STAT and IT were compared between the two phases. Results: The study included 285 CTAs (95 per reader, per arm), with a mean patient age of 58.5 years ±14.7(SD), 52% men, 37% prevalence. AI assistance significantly reduced STAT for detecting 33 true positive AD cases, from 15.84 minutes (95% CI: 13.37–18.31min) without AI to 5.07 minutes (95% CI: 4.23–5.91min) with AI, a 68% reduction (p<0.01). IT also decreased significantly, from 21.22 seconds (95% CI: 19.87–22.58s) without AI to 14.17 seconds (95% CI: 13.39–14.95s) with AI (p<0.05). Conclusions: Integrating a DL-based algorithm for AD detection on chest CTAs significantly reduces both STAT and IT. By prioritising the most urgent cases, AI ensures faster diagnosis and improves the workflow efficiency in clinical radiology practice, compared to standard First-In First-Out (FIFO) workflow.

According to statistics, the leading cause of death among young people is road car accidents. Moreover, one of the factors for road crashes is low-quality road infrastructure. Road signals are part of the road infrastructure, and they are required for safe driving. Furthermore, road signals are essential for an autonomous mobile machine vision to function properly. Hence, road signals should be clear and transparent in all transportation lanes. Unfortunately, road lane markings – one of the most important signals – fade and deteriorate over time because of the paint quality, weather, and exposure to any external object. Moreover, maintaining those markings manually is considered difficult and tedious by some. Literature review shows few autonomous solutions for such a problem. However, none of the solutions is robust for all kinds of markings. In particular, the literature review shows that the present autonomous solutions require human interference to guide the robot in a specified path to paint a new line where usually the robot will localize itself using GPS. This project targets road markings maintenance with a novel idea to use machine vision for inspecting the line state while moving along the line, and if needed, the robot will repaint the road line. The robot was designed following this idea, and the design can be divided into the following: Driving unit, Paint unit, Vision unit, Control unit, Power unit, UI unit. First, the driving unit is made using a three-wheeled differential drive system, where two wheels are motorized wheels, and the third is a freewheel. Moreover, the painting unit contains an air compressor, an HVLP paint sprayer, a pulley system, and a servo motor. At the same time, the robot vision unit consists of a camera, two IR sensors, and two ultrasonic sensors. Also, the control unit is made of a Raspberry Pi, Arduino, and Motor controllers. Furthermore, the power unit has a 12V lead-acid battery, 48V Li-po battery, four 1.5 batteries, and a power bank. Finally, the UI unit includes a cooling fan and a 10” screen. The software is made of a machine vision code using the OpenCV library in Python language. This code is implemented on the RPI to image process the feed from the camera and then communicate with Arduino using the Serial library. Moreover, Arduino code uses C++ language to decode the message from the RPI and control a relay and a servo for the painting unit and motor controllers for the driving unit. After the design and parts acquisition, the whole system was assembled at home using several manufacturing techniques such as drilling, threading, filing, soldering, 3D printing, adhesion, and zipping. Then, each subsystem was calibrated individually. Finally, the testing phase started for each system individually and ended by testing the system as a whole. In the end, the project progress was hindered by several failed tests. However, it was completed within the timeframe with achieving the main performance measures of the mechanical design/assembly, localization/path planning, road line inspection accuracy, and painting performance.

This study empirically investigates the relationship between realized higher-order moments and the Fear and Greed Index as a measure of sentiments. We estimate daily realized moments for five different sentiment levels using 5-minute return data of the S&P 500 index from January 3, 2011, to September 18, 2020. We found that the Fear and Greed Index significantly impacts realized volatility during periods of extreme fear. Additionally, various sentiment indicators influence realized skewness and realized kurtosis. The VIX index significantly reduces realized skewness across all sentiment levels. Bearish and bullish sentiments have a significant negative relationship with negative realized skewness during periods of extreme fear and extreme greed. Conversely, the Fear and Greed index, bearish and bullish sentiments have a significant positive relationship with positive realized skewness. During extreme fear, the Fear and Greed index, bearish, and bullish sentiments have a significant negative relationship with realized kurtosis. These results remain consistent when considering the non-linear characteristics of the Fear and Greed Index during periods of extreme fear and extreme greed. These findings highlight the relevance of understanding sentiment in financial risk management and its significant relationship with asymmetric and extremity characteristics of asset returns.

Background: Immune evasion in cancer is a multifaceted process that synchronizes pro-tumoral immune infiltration, immunosuppressive inflammation, and inhibitory immune checkpoint expression (IC). Recent developments have immunotherapies such as immune checkpoint blockade (ICB) and chimeric antigen receptor T-cell (CAR-T) therapy effectively impede this process but benefit a limited patient cohort. This investigation introduces a systemic immunotherapeutic strategy by inhibition of master-regulators of immune evasion (MR-IE). Methods: We utilized the TCGA PanCancer Atlas transcriptomic data to subset and stratify cancer samples based on IC expression levels and CIBERSORT to estimate immune cell infiltration. Differential gene expression analysis was conducted to unravel pathways associated with the immune evasion. Transcription Factor Enrichment Analysis and Survival Analysis was conducted to identify and rank candidate MR-IE per cancer type. The top-ranking candidate MR-IE of cholangiocarcinoma (CCA) was validated for its regulation of ICs using quantitative PCR and western blots. Orbitrap Proteomics was employed to assess changes in the immune-related proteome of CCA cells after MR-IE is inhibited or knocked-down. Lastly, CCA cell viability and immune-mediated cell death was assessed after MR-IE inhibition in combination with fourth-generation anti-folate receptor alpha (FRɑ) CAR-T cell therapy. Results: This workflow ranked and identified candidate MR-IE for 33 tumor types. MYC was identified as the high-ranking candidate MR-IE for CCA. MYC modulated PD-L1 expression adn key markers of inflammation and IC expression in CCA cells. Moreover, MYC inhibition was able to potentiate CAR-T mediated cell death in CCA cells. Conclusions: Cumulatively, these results offer a candidate list of MR-IE immunotherapeutic targets per cancer type that can be further explored and validated. This study also highlights the promise of MR-IE inhibition as a novel potent immunotherapeutic strategy for the treatment of CCA.

Introduction: Despite the well-documented benefits of smoking cessation interventions, the implementation and success of these programs in primary care settings often encounter significant barriers. A primary care provider’s personal smoking status has been identified as a potential barrier to tobacco treatment delivery. The aim of this qualitative study is to explore the experiences and perspectives of primary care providers regarding their role in, delivering smoking cessation interventions to patients based on their personal smoking status. Materials and methods: Semi-structured interviews were conducted with 22 primary care providers from 6 public primary care units in Central Macedonia Region, Greece. Thematic analysis was used to analyze data. Results: Healthcare providers who are current smokers may face unique challenges in effectively counseling patients on smoking cessation. On the contrast, non-smoking and especially previous smoking healthcare providers were noted to exhibit greater confidence and efficacy in delivering cessation support, often serving as role models for patients aiming to quit smoking. Participation in structured cessation training programs often catalyzed personal reflection among healthcare professionals regarding their own smoking behaviour. Conclusions: Personal smoking status of primary care providers impacts the delivery of tobacco treatment, affecting their credibility and effectiveness in providing cessation support. Understanding the complex factors that influence the delivery of smoking cessation interventions in primary care is crucial, as these settings represent a vital point of contact for reaching individuals who smoke and providing them with the necessary support to quit.

Understanding creation as divine kenosis, which has become rather widespread since the last century, may emphasize the strong connection between the theology of creation and the key Christian doctrine of the Incarnation while contributing to the dialogue between theology and science. At the same time, this theological project requires a thorough rethinking of divine action in order to avoid representing divine agency and natural causality as competitive factors and to affirm divine kenosis as the definitive trait of God without compromising divine freedom. To this end, the concept of “divine kenotic creativity” is suggested and discussed in this paper.

Many interesting materials in a broad range of applications have in their composition the coexistence of zinc and iron. Their characterization by XPS should identify and quantify both elements. The most intense regions for these elements Zn 2p and Fe 2p are, therefore, used to accomplish that purpose. Using sphalerite as an example of a material where Zn and Fe may coexist and using XPS with two different X radiation sources to study them, it is demonstrated that Fe 2p region, when the iron is the minor component, may be seriously affected by the Auger Zn L3M1M23 structure. The sphalerite (Zn1-xFexS) here studied has x0 and is a good example to show how an XPS spectrum obtained with the X-ray Al Kα, the most used radiation in monochromatic equipments, leads to a wrong assignment of the structures existing in the binding energy region of Fe 2p. The simultaneous use of Mg Kα radiation showed that the Fe 2p is below the XPS detection in this specific sample of sphalerite. Its attested absence reveals that the structure detected, when using Al Kα in “Fe 2p” region, is assigned to a zinc Auger multiple peak and not to the expected 2p photoelectron doublet peak of iron.

This study presents the innovative design and fabrication of a 3D-printed prosthesis arm aimed at enhancing automated hand rehabilitation for targeting hemiplegic patients who cannot open and close their hands. By leveraging surface electromyography (EMG) signals, the prosthesis arm translates muscle contractions in the forearm into precise hand movements, facilitating more effective rehabilitation. A comprehensive analysis of existing prosthesis designs guided the creation of a new, improved prototype. Using a concept scoring evaluation matrix, the best concept design was selected, designed, and fabricated through additive manufacturing. The finished prosthesis improves grip stability by imitating natural finger movements with flexible materials and a tendon system made of elastic ropes and fishing lines. Experimental comparisons between the designed prosthesis arm and a human hand showed significant similarities in flexion angles, though further refinement is needed for measurement accuracy and tactile feedback. The result presents the designed prosthesis arm validity and can be used in automated control rehabilitation in the future. This research also highlights the potential of 3D printing and EMG technology in creating customizable, efficient prosthesis arms for automated rehabilitation, suggesting pathways for future improvements and broader applications.

Background: Central and branch retinal artery occlusion (CRAO and BRAO) are critical causes of acute vision loss, predominantly affecting older adults with systemic vascular pathology. These occlusions typically result from embolic events, leading to partial or complete retinal ischemia; Methods: This retrospective case series report details of our ten-year experience using the 1064 nm Nd:YAG laser for Transluminal Nd:YAG Embolysis (TYE) in order to lyse visible emboli whitin the retinal arteries; Results: We conducted a retrospective case series involving 18 patients treated by TYE for different retinal arteries occlusions between 2014-2024. TYE effectively restored blood flow in the occluded arteries, with variable but generally favorable visual outcomes. Our article highlights significant clinical and interventional aspects of three treated patients: a BRAO case with multiple transluminal emboli, a case of double BRAO and a CRAO case. We also report the successful use of TYE for intraluminal lysing of an embolus located outside the optic disc. The procedures were well-tolerated, with minor complications such as preretinal or vitreous hemorrhages resolving spontaneously; Conclusions: TYE is a minimally invasive therapeutic option for retinal artery occlusion with visible emboli, particularly when intervention occurs shortly after the onset of symptoms. Compared to observation, TYE can improve visual outcomes and reduce the risk of permanent vision loss, presenting a significant advancement in the management of this ophthalmic emergency. The worldwide experience with TYE is continuously increasing. Further research with larger cohorts is recommended to validate these results and refine the treatment protocol.

Tire wear particles (TWP) are among the most relevant sources of microplastic pollution of the environment. Nevertheless, common analytical methods like IR- and Raman spectroscopy are highly impaired by additives and filler materials, leaving only thermo-gravimetric methods for chemical analysis of TWP in most cases. We herein present quantitative NMR spectroscopy (qNMR) as an alternative tool for the quantification of the polymeric material used for the production of tires including natural rubber (NR), styrene-butadiene-copolymer (SBR), polyethylene-polypropylene-copolymer (EPR) and polybutadiene (BR). Limits of quantification between 3 µg and 43 µg per sample and recovery rates of 72-92% are achieved for all tested polymer types. The first results of combining these measurements with Soxhlet extraction as a sample preparation tool are presented alongside the qNMR experiments.

This study presents a comprehensive systematic review that addresses the critical transition from ROS 1 to ROS 2, spotlighting the significant enhancements and the pressing need for a detailed exploration of ROS 2 within the robotics community. Despite the extensive deployment and adaptations of ROS in varied robotics applications, literature lacks a cohesive synthesis that delineates the advancements, limitations, and broader impacts of ROS 2 compared to its predecessor, ROS 1. Our contribution bridges this gap by assembling the largest database of ROS-related research, encompassing 7,498 articles, with a focused analysis in this survey on 431 ROS2-specific publications. We categorize these into i.) articles that discuss and analyze core ROS 2 concepts, ii.) articles that propose frameworks or tools for ROS 2, and iii.) articles utilizing ROS 2. Furthermore, we summarize literature findings of ROS 2 challenges, advancements, and future direction in the fields of a.) security, b.) real-time, c.) middleware, d.) embedded and distributed systems, e.) communication reliability and QoS, and f.) multi-robot systems. The methodology involved meticulous data collection and categorization from multiple databases, facilitating an in-depth online accessible resource. Results underscore ROS2’s enhancements in modularity, real-time capabilities, and security, extending its applicability across various robotic platforms and industries. However, challenges in scalability and reliability persist, signaling avenues for future enhancements. This review not only deepens the understanding of ROS2’s contributions but also charts a path for ongoing improvements in robotic systems design. The original data presented in the study are openly available in https://www.ros.riotu-lab.org/.

The relationship between the global climate crisis associated with environmental risks and occupational hygiene has not been extensively studied. This study develops a framework for identifying how climate change and the climate crisis could impact the workplace environment, workers, and occupational morbidity, mortality, and injury. A framework based on a review of scientific literature published from 2012-2024 that addresses climate risks, their interaction with occupational hazards, and their effects on the workforce. Eight categories of climate-related hazards are identified: increased high temperatures, dust and air pollution, sun and cosmic ultraviolet exposure, pandemics, and infectious diseases, diseases transmitted by insects and changes in ecosystems, industrial occupational diseases, changes and crises in the built environment, and extreme weather events. It is important to consider the possibility of interactions between known hazards and new conditions and the productivity of workers, especially those who are most at risk of heat-related illnesses.

The main objective of the present study is to demonstrate the possibility of actively influencing the position of the bow shock wave and the main parameters of supersonic flow over a blunt body by organizing a gas discharge near the front surface, in the region between the body and the bow shock wave. The research is carried out using both experimental and numerical methods. The working gas was xenon. It is shown that the steady bow shock wave stand-off distance along with the current and power of the discharge, is associated with the change in the adiabatic index of the plasma created by the discharge, which, in turn, is determined by the plasma parameters, such as the degrees of nonequilibrium and the degree of ionization. It is shown that the adiabatic index with the power supplied to the impact zone in the range of 30-120 kW can both increase and de-crease in the range of 1.25-1.288. The study of the discharge created plasma zone was conducted and the correspondence between the discharge current and power, and the average parameters in the plasma zone created by the discharge is presented. A good agreement between the numerical and experimental data was shown. The results may be useful in developing control systems for high-speed civil aircrafts.

With a recent advance in photonic integrated circuits (PIC), a new field of frequency agile coherent radar systems is being thoroughly researched. In contrast to the traditional all-electronics radiofrequency (RF) radar techniques, a fully photonics-based system does not suffer from bandwidth limitation and noise degradation when switching from S to X or K-band and can achieve excellent phase noise even at frequencies exceeding 20 GHz. However, recent state-of-the-art PICs still exhibit high processing losses in the optical domain, which must be addressed in the electrical part of the RF domain. This study presents a comprehensive analysis of the challenges in designing RF front-end amplifier chains for microwave photonic radars, particularly in maintaining stability, minimizing noise, and reducing intermodulation distortion. Furthermore, a comprehensive demonstration of the RF front-end, encompassing both the optical generation of RF signals and experimental measurements of a rotor blade's Doppler fingerprint to validate the system's performance is presented.

Vector published map, as a result of pre-press printing of paper map digital publishing, is a page file in line with PostScript standards. With large amount of data and a large number of map page graphics objects, the browsing speed is slow and the hardware performance is very high, which seriously affects the breadth and depth of the application of vector published map. In response to this problem, this paper proposes a visualization method of large-size vector published map. This method adopts the idea of tiling. The vector published map is physically cropped into several PDF tiles to form a map logically. Data encoding and organization are based on the GeoSOT earth division grid to realize the rapid loading, scaling, display of map data and the correlation retrieval of map product "map and spatial data integration". The experiment shows that the response time of map data loading and browsing is much less than that of professional software, and the method is insensitive to data volume and has low requirement on hardware performance. This method can not only make up the disadvantages of image tiles in the existing network map service, but also make the vector published map can be used in embedded devices, mobile terminals, network modes and other cross-media applications.

Background: The diagnosis of Pulmonary Embolism (PE) is based on the application of a priori probability scales such as the Wells scale or PERC criteria. However, the clinical heterogeneity of this pathology results in the absence of a target population to apply these algorithms. Moreover, these scales do not consider the possible influence of the presence of an objective alternative diagnosis to PE, complicating its clinical assessment and possibly leading to an increase in unnecessary testing or missed diagnoses. Objective: The aim of this study is to evaluate the discrimination capacity of clinical objective factors with a high negative predictive value for PE, compared to PERC in terms of reducing unnecessary testing across different risk strata of the Wells scale. Materials and Methods: This was a single-center retrospective cohort study, including patients who underwent chest CT angiography to rule out PE at a University Hospital between 2008 and 2017, considering the presence of PE as the study outcome. The study collected demographic data, comorbidities, and clinical presentation data. The presence of objective criteria for pneumonia, heart failure, exacerbation of COPD, or the use of anticoagulation in non-oncological patients was considered a priori criteria with a high negative predictive value. Results: The analyses were performed on a cohort of 399 patients with an average age of 65 years and 53% females. A total of 139 patients were diagnosed with PE by CT angiography. The presence of factors with a high NPV showed a sensitivity and NPV of 100% in low-risk patients according to Wells, with sensitivity dropping below 50% in other populations. The association of these factors in the PERC plus criteria would allow a reduction of up to 34% in CT angiographies in patients with low risk according to the Wells scale. Conclusions: The combination of risk stratification of the Wells scale and PERC plus criteria allows an absolute reduction of 34.3% in the performance of CT angiographies in patients classified as low risk with a sensitivity and a negative predictive value of 100%. The preexistence of an alternative diagnosis does not allow ruling out PE in patients with intermediate or high risk according to the Wells scale.

Food processing can modify protein biochemical properties altering its immunoreactivity and allergenicity. Resistance to enzymatic digestion is one of the main characteristics of food allergens, specially to pepsin and trypsin. In this work, the aim is to compare the digestomes of raw and heat and /or pressured treated peanuts, hazelnut, pistachio and cashew resulting from the INFOGEST harmonized digestion protocol, as well as the different behaviour regarding IgE-binding capacity, by means of in vitro analysis. Protein patterns, resolved by SDS-PAGE, were assayed with sera from allergic patients and confirmed by competitive ELISA in hazelnut and peanut. The results of our study reveal that different processing methods affect differently gastrointestinal (GI) digestion of peanut, hazelnut, pistachio and cashew allergens. Simulated GI digestion led to extensive de-struction of the protein structure, reducing but not abolishing the IgE reactivity of peanut, ha-zelnut, pistachio and cashew allergenic proteins. Boiling for 60 minutes did not affect the protein profile of these nuts, although enzymatic activity was stimulated, decreasing the IgE binding capacity. When heat and pressure was applied to these nuts, simulated digestion promoted an almost complete inhibition of the allergenic potential.

Detection of adverse events, for example convulsive epileptic seizures, can be critical for the patients suffering from variety of pathological syndromes. Algorithms using remote sensing modalities, such as video camera input, can be effective for real-time alerting but the broad variability of environments and numerous non-stationary factors may limit their precision. In this work, we address the issue of adaptive reinforcement that can provide flexible application of the alerting devices. The generic concept of our approach is the topological reinforced adaptive algorithm (TOREADA. Three essential steps, embedding, assessment and envelope act iteratively during the operation of the system, providing thus a continuous, on the fly reinforced learning. We apply this concept on the case of detecting convulsive epileptic seizures where three parameters define the decision manifold. Monte-Carlo type simulations validate the effectiveness and robustness of the approach. We show that the adaptive procedure finds the correct detection parameters, providing optimal accuracy, from a large variety of initial states. With respect to the separation quality between simulated seizure and normal epochs, the detection reinforcement algorithm is robust within broad margins of signal generation scenarios. We conclude that our technique is applicable to a large variety of event-detection systems.

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.

A cross-sectional survey was distributed to 1322 members of a 1-on1 personalized strength training studio. 366 respondents (n=134 male and n=232 female), all aged over 20 years reported considerable training experience; 55% of males and 42% of females reporting 5+ years. Data were analyzed and reported descriptively with differences &gt;5% identified based on use of the 5-point likert scale, sample size and nature of the observations. Disparity between males and females were identified; males reported higher perceptions of managing effort, technique, and programming without supervision compared to females. Safety was noted as being more important to females compared to males. Qualitatively, additional themes were raised including analogy of the personal relationship between trainer and trainee being similar to that of medical professionals. This was validated where participants discussed their adaptations from supervised strength training including quality of life in aging, and recovery from medical conditions and injury. Data is discussed in context of a previous body of literature suggesting males falsely report higher confidence in tasks compared to females, particularly in relation to effort, role models, and verbal encouragement. This research proves beneficial for strength training practitioners in enhancing their understanding and expectations of clients, as well as hopefully proving insightful in engaging more people in strength training.

This study examines the relationship between financial investment, shareholder preference, corporate social responsibility (CSR) performance and life satisfaction for BP and Shell within the UK, together with their alignment with specific Sustainable Development Goals (SDGs). about, using regression analysis, in both projects Hypotheses were tested to assess the significance of these predictors in the performance of CSR developed. The results showed that financial investment, shareholder ownership, and social satisfaction did not significantly predict CSR performance for BP and Shell. Furthermore, there were no significant differences in the impact of these predictors between the two companies. Further research revealed Shell’s strong commitment to SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action), with both initiatives drawing on Shell’s significant investments in renewable energy and climate recognition in the management system established him as a leader in sustainable development efforts. BP’s goal of achieving net zero emissions by 2050, especially focused on SDG 7 and SDG 12 (Responsible Consumption and Production), this proposal was adopted. Comparing the two sectors, Shell showed significant advantages, which can be attributed to its diversified capabilities and its strong alignment with the sustainability objectives of BP, while growing largely, it faces significant financial challenges in its transition to clean energy. The study concludes that although both companies are committed to sustainability, Shell now leads in terms of effective CSR and financial performance

Objectives: Cardiogenic shock [CS] is associated with a high-mortality. Suitable patients maybe successfully bridged using newer intravascular micro-axial left-ventricular assist devices [M-LVAD] for recovery or determination of definitive therapy. Methods: Between January-2020 and July-2024, 107 patients underwent placement of M-LVAD for CS. The cohort was divided into 4 groups based on their destination; group-1: 34 patients [32%] receiving transplant; group-2: 25 patients [23%] receiving durable LVAD; group-3: 42 patients [39%] bridging from post-cardiotomy CS [PCCS]; and group-4: 6 patients [5.6%] bridging decision/recovery [these were excluded from analysis]. Multivariable logistic-regression [MLR] and Cox-regression [MCR] models identified predictors of early-hospital and late mortality, with data reported as odds ratios [ORs], and hazard ratios [HRs], respectively. P<0.05 was statistically significant. Results: Complications included device-malfunction [n=6, 6%], gastrointestinal bleed [n=9, 9%], stroke [n=11, 11%]; long-term hemodialysis [n=21, 21%]. Early-hospital mortality included 13 patients [13%]: 2 in group-1, 1 in group-2 and 10 in group-3 [p=0.02]. In the MLR model, the category of cardiogenic shock requiring M-LVAD placement was statistically significant [OR=4.7 (0.9-24), P=0.05]. Patients were followed for up to 4.5-years, and 23 deaths occurred; group-1: 3 patients, group-2: 5 patients, and group-3: 15 patients [p=0.019]. At 4.5-years, actuarial survival was 90.7±5.1% in group-1, 79.2±8.3% in group-2, and 62.8%±7.7% in group-3 [P=0.01]. In the MCR model, M-LVAD category [HR=3.63 (1.03-12.9) P=0.04], and long-term postoperative dialysis [HR=3.9 (1.6-9) P=0.002], emerged as statistically significant predictors of long-term mortality. Conclusions: In cardiogenic shock, our mid-term outcomes demonstrate good survival with M-LVADs as bridge to transplant and durable LVAD, and reasonable survival as bridge to recovery following cardiotomy, reduced ECMO usage and early ambulation/rehabilitation.

Fish is essential to feeding the world's population and provides hundreds of millions of people with a substantial amount of protein in their diets. Fish is one of the most affordable and readily available forms of animal protein, making up roughly 20% of total animal protein intake. It is simple to obtain these fish through cultivated or captured fisheries. However, the aquaculture industry is viewed as the main means of supplying the world's growing fish demand given the ongoing indiscriminate harvests in capture fisheries. Global aquaculture systems are under serious threats from climate change, which will have an impact on disease prevalence, species mix, water quality, and overall production. The possible impacts of climate change on freshwater aquaculture production and its consequences for the sustainability of the sector are reviewed in this paper. Rising temperatures, El Niño Southern Oscillation events, lowered dissolved oxygen, toxic algal blooms, altered rainfall patterns, water pH, altered salinity, and extreme weather events are a few of the aspects of a changing climate that have been discussed.

Suppose n ∈ N. We wish to meaningfully average ‘sophisticated’ unbounded sets (i.e., sets with positive n-d Hausdorff measure, in any n-d box of the n-d plane, where the measures don’t equal the area of the boxes). We do this by taking the most generalized, satisfying extension of the expected value, w.r.t the Hausdorff measure in its dimension, on bounded sets which takes finite values only. As of now, I’m unable to solve this due to limited knowledge of advanced math and most people are too busy to help. Therefore, I’m wondering if anyone knows a research paper which solves my doubts. (Unlike previous versions with similar names, we add examples, motivations, and explanations to this version.)

We assess simultaneous adoption and impacts of multiple improved technologies promoted as a bundle and recommended for legumes intensification systems for smallholder farmers in Ethiopia. We use DNA fingerprinting data to precisely identify our key treatment - “adoption to improved bean varieties” in the study. The results show significant positive impacts of adopting bundled interventions on, agricultural incomes and household food security but vulnerability to food insecurity persists. We find that growing improved varieties with fertilizers increased household agricultural revenue, allowing for more legume consumption and enhancing their likelihood of achieving adequate food consumption and food security outcomes. However, the vulnerability to food insecurity of the adopters remains high due to pre-existing resource degradation issues. Given similarity in production contexts in Sub Saharan Africa, our results provide perspective for similar development interventions. We use the results of our analysis to discuss potential policy implications and programmes to support technology intensification among small holder farmers.

Plants are rich source of specialized metabolites, such as alkaloids, terpenes, phenolic acids, flavonoids, coumarins, and volatile oils, which provide various health benefits including anticancer, anti-inflammatory, antiaging, skin-altering and anti-diabetic properties. However, challenges such as low and inconsistent yields, environment and geographic factors, and species-specific production of some specialized metabolites limit the supply of raw plant material for the food, cosmetic or pharmaceutical industries. Therefore, biotechnological approaches using plant in vitro systems offer an appealing alternative for the production of biologically active metabolites. Among these, hairy root cultures induced by the Rhizobium rhizogenes have firmed up their position as “green cell factories” due to their genotypic and biosynthetic stability. Hairy roots are valuable platforms for producing high-value phytomolecules at low cost, are amenable to pathway engineering and can be scaled up in bioreactors making them attractive for commercialization. This review explores the potential of hairy roots for specialized metabolites biosynthesis focusing on biotechnology tools to enhance their production. Aspects of morphological peculiarities of hairy roots, the diversity of bioreactors design, and process intensification technologies for maximizing biosynthetic capacity, as well as examples of patented plant-derived (green-labeled) products produced through hairy root cultivation at lab and industrial scales are addressed and discussed.

Acrostichum aureum is a halophytic pantropical invasive fern growing in mangroves and swamps. Its association with arbuscular mycorrhizal fungi (AMF) has been reported in Asia. AMF and their symbiosis (AM) commonly colonise the absorption organs of terrestrial plants worldwide. Fur-thermore, AMF/AM are well known for their capacity to bioaccumulate toxic elements and to alleviate biotic and abiotic stress (e.g. salinity stress) in their hosts. However, how AMF are in-volved in the halophytism of A. aureum, and the structures where NaCl accumulates remains unknown. This study shows that A. aureum forms AM in Neotropical thermal margins of natural ponds, NaCl accumulation occurs inside AMF vesicles, and CaSO4 precipitates in colonised roots. Therefore, AM would be contributing to the halophytic nature of this fern, allowing it to thrive in saline and thermal environments by capturing NaCl from fern tissues, compartmentalizing it inside its vesicles and precipitating CaSO4.

'Xinomavro' (V. vinifera L.) is an important native red wine grape variety in Northern Greece, particularly in PDO (Protected Designation of Origin) regions. Despite its significance, there is limited research on the effects of pruning type and severity on 'Xinomavro' vine physiology, yield, and berry quality across diverse environmental conditions. This study aimed to address this knowledge gap and provide growers with crucial information for optimizing vineyard management practices. The study was conducted over two consecutive years (2016 and 2017) in a vineyard in Thessaloniki, Northern Greece. Four treatments ( B12:12 buds on 6 spurs; B24:24 buds on 12 spurs; M12:12 buds on 2 canes; M24:24 buds on 4 canes) combining two bud load levels (12 or 24 count nodes) and two pruning types (short spurs or long canes) were applied to 'Xinomavro' vines in complete block randomized design. The vine water status, gas exchange, canopy characteristics, yield components, and berry composition were measured. Bud load and pruning type significantly influenced vine canopy development, microclimate, and yield components. Short pruning with high bud load (B24) resulted in denser canopies and higher yields, whereas cane pruning (M12 and M24) led to more open canopies and improved berry quality indicators. Treatment effects on berry composition were inconsistent across years, but showed a tendency for higher anthocyanin and total phenol content in cane-pruned vines. This study demonstrated that pruning type (short or long fruiting units) may have a greater impact on vine growth, yield, and berry composition than bud load alone in 'Xinomavro' vines. Cane pruning appears to be a more effective strategy for achieving vine balance and potentially improving grape quality under given experimental conditions.

The State of Zacatecas (Mexico) is one of the places most affected by pollution from the mining industry. 21 samples from two areas have been collected (6 samples from zone A and 15 samples from zone B) to evaluate the level of radioactivity and the degree of contamination by heavy metals. The activity concentration for 238U and 232Th is within typical values, but 226Ra exceeds the value of 60 Bq kg-1 in both areas. In some places, the concentration of 40K is higher than the world average, according to UNSCEAR. The radium equivalent activity Raeq and outdoor gamma exposure dose (D) indicate that some sites present a radiological risk for the population. Excess lifetime cancer risk (ELCR) presents a higher risk than the world average in both sampled areas. Other parameters, such as the radiation index Ri, the external risk index Hex, and the internal risk index Hin, also indicate that there is a greater risk due to radiation exposure in these areas. In the case of heavy metals, some parameters, such as the enrichment factor (EF), the geoaccumulation index (Igeo), and the contamination factor (CF), show that some places in zone A and zone B are contaminated with As and Pb. However, the concentration of selenium obtained by ICP-MS in the sampled soil is higher than the average in the Earth's crust, both in mine waste dumps and in unaltered soil, which indicates that the background concentration for selenium in these places is higher than the world average.

Introduction: Chronic ulcers significantly burden healthcare systems, requiring precise measurement and assessment for effective treatment. Traditional methods, such as manual segmentation, are time-consuming and error-prone. This review evaluates the potential of artificial intelligence (AI)--powered mobile apps for automated ulcer segmentation and their application in clinical settings. Methods: A comprehensive literature search was conducted across PubMed, CINAHL, Cochrane and Google Scholas databases. The review focused on mobile apps that use fully automatic AI algorithms for wound segmentation. Apps requiring additional hardware or needing more technical documentation were excluded. Vital technological features, clinical validation, and usability were analysed. Results: Ten mobile apps were identified, showing varying levels of segmentation accuracy and clinical validation. However, many apps did not publish sufficient information on the segmentation methods or algorithms used, and most lacked details on the databases employed for training their AI models. Additionally, several apps were unavailable in public repositories, limiting their accessibility and independent evaluation. These factors challenge their integration into clinical practice despite promising preliminary results. Discussion: AI-powered mobile apps offer significant potential for improving wound care by enhancing diagnostic accuracy and reducing the burden on healthcare professionals. Nonetheless, the lack of transparency regarding segmentation techniques, unpublished databases, and limited availability of many apps in public repositories remain substantial barriers to widespread clinical adoption. Conclusion: AI-driven mobile apps for ulcer segmentation could revolutionise chronic wound management. However, overcoming limitations related to transparency, data availability, and accessibility is essential for their successful integration into healthcare systems.

Child malnutrition is a critical public health concern that significantly hampers children's physical and mental development and has serious economic repercussions. The World Health Organization (WHO) attributes half of all deaths among children under five to malnutrition, with long-term consequences such as lower educational achievement, decreased productivity, and deepened poverty. The economic impact of child malnutrition extends beyond public health, imposing substantial costs on health systems, households, and the broader economy. This study estimated the burden of child malnutrition in Colombia among children up to four years old using a Markov chain model from a societal perspective. The model simulated six health states, integrating direct and indirect costs, with epidemiological data and international literature guiding the transition probabilities. Surveys were conducted with caregivers to assess indirect costs. Results indicated that malnutrition accounted for 419.84 Disability-Adjusted Life Years (DALYs) per 1,000 inhabitants. The total cost of malnutrition over four years was approximately USD 243.58 million, with an annual average cost of USD 60.89 million, with 65% of the burden falling on households. The findings emphasize the significant economic and health burden of child malnutrition, underscoring the importance of early and comprehensive interventions. Investing in child nutrition can improve health outcomes, reduce economic strain, and enhance productivity, making it a crucial priority in health and economic development agendas.

Adventitious root (AR) formation in plants origins from non-root organs such as leaves and hy-pocotyls. Auxin signaling is essential for AR formation, but the role of other phytohormones is less clear. In Arabidopsis, at least two distinct mechanisms can produce ARs either from hypocotyls as part of the general root architecture, or from wounded organs during de novo root regeneration (DNRR). In previous reports, gibberellin acid (GA) seems to play reverse roles in both types of AR formation, since GA treatment blocks AR formation from hypocotyls, whereas depletion of GA signaling results in reduced DNRR from detached leaves. Here, we report the positive effects of GA biosynthesis inhibitor paclobutrazol (PBZ/PAC) treatment on both types of AR formation in Arabidopsis. Consistently, loss of GA synthesis and signaling promoted DNRR in our conditions. Furthermore, PBZ treatment can rescue declined AR formation from leaf explants in erecta recep-tor mutants. Transcriptional profiling revealed that PBZ treatment altered GA, brassinosteroids and auxin responses, which included up-regulation of LBD16 that plays a pivotal role in AR initi-ation. This study reveals that depletion of GA biosynthesis promotes DNRR in Arabidopsis, and thus will contribute to further clarification of the role of GA during AR formation in plants.

Facial appearance significantly influences several life outcomes, and a convex profile often prompts patients to seek treatment to enhance their facial esthetics. This study aimed to assess the facial appearance outcomes of combined orthodontic and orthognathic intervention compared to orthodontic camouflage treatment in convex facial profile individuals. The study sample comprised 36 consecutively selected Class II Division 1, convex facial profile patients. Two groups of 18 non-growing patients with similar characteristics were compared. Group A was treated with orthodontics and orthognathic surgery, whereas Group B with orthodontics exclusively. Pre- and post-treatment profile and frontal facial photographs were presented simultaneously to orthodontists, oral and maxillofacial surgeons, convex profile patients, and laypeople, asking them to assess changes in facial appearance. Considerable positive changes in facial appearance were perceived for Group A, compared to no changes for Group B, with a 17/100 VAS units difference. The rater groups demonstrated a high degree of consistency (ICC > 0.88). Multivariate analysis revealed significant differences in perceived changes between the two treatment groups (F = 14.63, P < 0.001, Pillai's Trace = 0.36, partial η2 = 0.36), with no significant effects from the rater group (P > 0.05). Similar results were evident when only profile photos were rated (P > 0.05). The combined orthodontic and surgical intervention is an efficient approach for the enhancement of facial appearance in convex profile cases. On the contrary, orthodontic treatment alone has no such impact. These findings should be properly communicated during patient consultation and considered for treatment planning.

Living systems are capable on the one hand, of eliciting a coordinated response to changing environment (aka adaptation) and on the other hand, they are capable of reproducing themselves. Notably, adaptation to environmental change requires the monitoring of the surroundings, while reproduction requires monitoring oneself. These two tasks appear separate and making use of different sources of information. Yet both the process of adaptation as well as that of reproduction are inextricably coupled to alterations of genomic DNA expression, while a cell behaves as an indivisible unity in which apparently independent processes and mechanisms are both integrated and coordinated. We argue that at the most basic level, this integration is enabled by the unique property of the DNA to act as a double coding device harboring two logically distinct types of information. We review biological systems of different complexity and infer that inter-conversion of these two distinct types of DNA information represents a fundamental self-referential device underlying both systemic integration and coordinated adaptive response.

This study analyzes how various audio features influence speaker change detection in different unsupervised approaches. Ten different audio features, including MFCC, mel-spectrogram, spectral centroid, and pitch, etc. were chosen for analysis. Two distinct unsupervised methods were selected for comparing the effectiveness of these feature: the Bayesian information criterion with Gaussian mixture model (BIC-GMM), a model-based approach, and the Kullback-Leibler divergence with Gaussian (KL-GMM), a metric-based approach. In order to gain a prior insight into which features have a significant impact on the SCD problem, we calculate statistic for two probabilities: the probability of speaker change given there is a feature change, and vice versa. To experimentally check the prior insights, a set of experiments carried out to analyze the influence of various audio feature for SCD. The results showed that in both methods, MFCC demonstrates a robust performance, and ranks at the top. Zero crossing rate, chroma and spectral contrast gives a higher performance in BIC-GMM. Mel-spectrogram consistently ranks at the bottom, suggesting it has the least impact on performance across both methods.

Low back pain (LBP) affects over 60% of individuals in their lifetime and is a leading cause of disability and increased healthcare expenditure. Facet joint pain (FJP) occurs in 27% to 40% of LBP patients but is often overlooked or misdiagnosed. Additionally, there is no clear correlation between clinical examination, radiological findings, and clinical presentation, com-plicating the diagnosis and treatment of FJP. This narrative review aims to provide an overview of the literature regarding facet joint pain and discusses the utility of medial branch blocks (MBBs) and intra-articular (IA) injections as diag-nostic and therapeutic tools prior to radiofrequency ablation (RFA). RFA is considered the gold standard for managing FJP, employing techniques that include precise needle placement and stimulation parameters to disrupt pain signals. Promising alternatives such as cooled RFA and cryodenervation require further research on their long-term efficacy and safety. Endoscopic denervation and multifidus stimulation are emerging therapies that may benefit chronic LBP patients, but additional research is needed to establish their effectiveness. When conservative management fails, RFA provides significant and lasting relief in well-selected patients and has a favourable safety profile. Current literature does not support surgical inter-ventions for LBP management.

Alphaviruses are known for being model viruses for studying cellular functions related to viral infection but also for causing epidemics in different parts of the world. More recently, alphavirus-based expression systems have demonstrated efficacy as vaccines against infectious diseases and as therapeutic applications for different cancers. The self-replicating feature of alphaviruses has provided the advantage of extremely high transgene expression of vaccine-related antigens and therapeutic anti-tumor and immunostimulatory genes, which has also permitted significantly reduced doses for prophylactic and therapeutic applications potentially reducing adverse events. Furthermore, alphaviruses have shown favorable flexibility as they can be delivered as recombinant viral particles, RNA replicons or DNA replicon-based plasmids. In the context of infectious diseases robust immune responses against the surface proteins of target agents have been observed and protection against challenges with lethal doses of infectious agents in rodents and primates. Similarly, expression of anti-tumor genes and immunostimulatory genes from alphavirus vectors has provided tumor growth inhibition, tumor regression and cure in animal cancer models. Moreover, protection against tumor challenges has been observed. In clinical settings, clinical benefits have been reported. Alphaviruses have also been considered for the treatment of neurological disorders due to their neurotrophic preference. Attention has been paid to alphavirus vector and expression system improvement. Point mutations in the non-structural alphaviral replicase genes have generated enhanced transgene expression and created temperature-sensitive expression vectors. The recently engineered trans-amplifying RNA system has facilitated vector production and enhanced the expression capacity.

The incorporation of electric vehicles (EVs) with vehicle-to-grid (V2G) offers the development of multi-energy microgrid (MMOs) models. However, MMOs have among their goals to decrease electricity costs by coordinating with vehicle-to-grid (V2G) scheduling. Controlling V2G models poses uncertainties about the voltages developed and creates the need for power generation disruptions. In this work, a Feed-Forward-Back-Propagation Network (FFBPN) is developed with Matlab software, based on the Levenberg-Marquardt algorithm by varying the number of hidden neurons to realize better performance thanks to the value of the Maximum Coefficient of De-termination (R2) and the Minimum Mean Squared Error (MSE). In this article, the dataset from NASA PCoE has been used to make proper consideration of the model that best calculates the life cycle of the battery, demonstrating relevant implications for future development of this type of system based on FFBPN for the integration of EV into V2G. The proposed FFBPN demonstrates better performance than other methods taken from the literature. In conclusion, the comparison between the phases of training, validation and test are used to completely represent the validity of the proposed model and precisely to identify the characteristics curves of FFBPN for future ap-plications highlighting its performance to create profitability, efficiency, production, energy saving and minimum environmental impact.

The tryptophan-kynurenine (KYN) pathway has long been recognized for its essential role in gen-erating metabolites that influence various physiological processes. Traditionally, these metabolites have been categorized into distinct, often opposing groups, such as pro-oxidant versus antioxidant, excitotoxic versus neuroprotective, or neurotoxic versus neuroprotective. This dichotomous framework has shaped much of the research on conditions like neurodegenerative and neuropsy-chiatric disorders, as well as cancer, where metabolic imbalances are a key feature. The effects are significantly influenced by various factors, including the concentration of metabolites and the par-ticular cellular milieu in which they are generated. A molecule that acts as neuroprotective at low concentrations may exhibit neurotoxic effects at elevated levels. The oxidative equilibrium of the surrounding environment can alter the function of KYN from an antioxidant to a pro-oxidant. This narrative review offers a comprehensive examination and analysis of the contemporary under-standing of KYN metabolites, emphasizing their multifaceted biological functions and their rele-vance in numerous physiological and pathological processes. This underscores the pressing ne-cessity for a paradigm shift in the comprehension of KYN metabolism. Understanding the intricate, context-dependent functions of these metabolites is crucial for establishing novel therapeutic tar-gets, especially in conditions such as neurodegeneration, immunological disorders, and cancer, where metabolic dysregulation serves as a primary catalyst of pathogenesis.

This paper considers the question of what kind of knowledge is produced by deep learning. Ryle’s concept of knowledge how is examined and is contrasted with knowledge with a rationale. It is then argued that deep neural networks do produce knowledge how, but, because of their opacity, they do not in general, though there may be some special cases to the contrary, produce knowledge with a rationale. It is concluded that the distinction between knowledge how and knowledge with a rationale is a useful one for judging whether a particular application of deep learning AI is appropriate.

This study investigates the application of fractal geometry to the analysis of vertebrate respiratory systems, focusing on the branching patterns of the bronchial tree across diverse species. Using a combination of mathematical modeling and computational visualization, we explore how fractal dimensions and branching characteristics reflect evolutionary adaptations to various habitats and physiological demands. The research encompasses a range of vertebrates, including humans, horses, dolphins, chickens, iguanas, and bullfrogs, representing diverse taxonomic groups and ecological niches. Our analysis reveals a clear gradient of complexity in respiratory structures, correlating strongly with metabolic rates and environmental adaptations. Mammals, particularly those adapted for high-performance activities like horses, demonstrate the most complex fractal patterns, indicating highly efficient gas exchange systems. In contrast, ectothermic species such as iguanas and bullfrogs exhibit simpler structures, reflecting their lower metabolic demands and alternative respiratory strategies. The study employs fractal dimension calculations, L-system modeling, and lacunarity analysis to quantify and visualize these differences. Our findings suggest that fractal analysis provides valuable insights into the relationship between form and function in vertebrate respiratory systems, offering a novel perspective on comparative physiology and evolutionary biology. This research not only enhances our understanding of respiratory system evolution but also has potential applications in biomimetic design, medical diagnostics, and ecological physiology. It demonstrates the power of interdisciplinary approaches, combining advanced mathematics with biological principles to uncover fundamental patterns in nature.

The development of pre-hierarchical follicle (PHF), especially small yellow follicles (SYFs), directly affects the recruitment of dominant follicles and thus affects the egg-laying performance of chickens. However, the development of PHF, especially the development of SYF, and its regulatory mechanism remain unclear. Therefore, we performed transcriptomic and metabolomic analyses of large white follicles (LWFs) and SYFs in chickens. Transcriptome sequencing revealed 258 differentially expressed genes (DEGs) between SYF and LWF, of which 172 were upregulated and 86 were downregulated. The DEGs were mapped to 17 KEGG pathways, mainly the gap junction, calcium signaling, and neuroactive ligand-receptor interaction pathways. The results of the metabolome analysis revealed 129 significant differential metabolites (DMs), including 36 upregulated DMs and 93 downregulated DMs. The DMs were mapped to 9 KEGG pathways for follicle tissue, which included mainly glutathione metabolism, alpha-linolenic acid metabolism, and tryptophan metabolism, etc. The combined transcriptional and metabolic analysis revealed significantly enriched pathways, and four metabolically related pathways, including glutathione metabolism, alpha-linolenic acid metabolism, linoleic acid metabolism, and pyrimidine metabolism, were identified. Glutathione metabolism is a critical signaling pathway that may affect ovarian follicle development to regulate the SYF reserve process in chickens. These results can act as a reference for improving the egg-laying performance of Tengchong snow chickens.

A new maritime order is emerging – the blue economy – characterised by a plethora of non-traditional security threats. Using the case of the Western Indian Ocean I demonstrate how the creation of spaces of risk in response to traditional security threats by world powers has led to a new, regionally-led governance regime in response to the new maritime order. International efforts to protect shipping lanes from the threat of piracy off the coast of Somalia have evolved into wider environmental and human security measures. I analyse these changes through the lens of governmentality and argue that this case represents an example of a global governmentality in which states are responsibilised to act collaboratively by the international community through discourses of risk. Regional States have turned this to their advantage, acting together to construct and secure a new development frontier - a shared blue economy space in an extensive and difficult-to-govern territory.

Background/Objectives: Leptospirosis is a globally distributed zoonosis with symptomatology similar to other febrile syndromes in tropical countries, making clinical diagnosis difficult. This study aimed to analyze the performance and agreement between serological diagnostic tests for the detection of acute and convalescent human leptospirosis compared to the micro agglutination test (MAT) in an endemic region of the Colombian Caribbean. Methods: A prospective descriptive study was conducted on 275 patients with suspected leptospirosis. Paired serum samples were collected, and an epidemiological survey completed. Positive and negative predictive values, sensitivity, specificity, and kappa index were calculated using MAT as the gold standard. A Bayesian latent class model was used to compare the diagnostic tests. Results: In 223 paired serum samples, the sensitivity values for different stages of the disease varied between 10.8% to 54.1% in the acute and 6.1% to 66.7% in the convalescent phase when compared to MAT; and when using the Bayesian model 9.5% to 75.3% in the acute and 5.7% to 85.3% in the convalescent phase. The Kappa value, an indicator of agreement, was moderate for the IgM ELISA (0.553) in the acute phase, and substantial (0.692) in the convalescent phase. Conclusions: MAT was the best confirmatory test in both acute and convalescent phases. Despite the high specificity of ELISA, 21.62% of patients diagnosed as negative by IgM-ELISA in the acute and convalescent phases were confirmed as positive by MAT. It is necessary to re-evaluate diagnostic guidelines that do not employ MAT for confirmation, and to strengthen diagnostic and clinical identification of leptospirosis in healthcare institutions and public health laboratories, while providing a rapid and reliable test for its implementation.

Multi-agent pathfinding has been extensively studied in the robotics and artificial intelligence communities. The classical algorithm, Conflict-Based Search(CBS), is widely used in various real-world applications due to its ability to solve large-scale conflict-free paths. However, classical CBS assumes discrete time-space planning and overlooks physical constraints in actual scenarios, making it unsuitable for direct application in Unmanned Aerial Vehicle(UAV) swarm. Inspired by the decentralized planning and centralized conflict resolution ideas of CBS, we propose an optimal and efficient UAV swarm motion planner that integrates State Lattice with CBS, named SL-CBS. SL-CBS is a two-layer search algorithm: (1) The low-level search utilizes an improved State Lattice. We design emergency stop motion primitives to ensure complete UAV dynamics and handle spatio-temporal constraints from high-level conflicts. (2) The high-level algorithm defines comprehensive conflict types and proposes a motion primitive conflict detection method with linear-time complexity based on Sturm’s theory. Additionally, our modified Independence Detection(ID) technique is applied to enable parallel conflict processing. We validate the planning capabilities of SL-CBS in classical scenarios and compare it with State-Of-The-Art(SOTA) algorithms, showing great improvements in success rate, computation time, and flight time. Finally, we conduct large-scale tests to analyze the performance boundaries of SL-CBS+ID.

The increasing demand for sustainable construction practices has prompted the exploration of innovative materials, such as waste plastics, to enhance both environmental and mechanical performance in concrete, particularly for rigid pavements. This review investigates the mechan-ical properties of concrete incorporating four types of waste plastics—High-Density Polyethylene (HDPE), Low-Density Polyethylene (LDPE), Polyvinyl Chloride (PVC), and Polypropylene (PP). The primary focus is on how these materials affect key mechanical properties, including com-pressive strength, tensile strength, and flexural strength. The analysis reveals that HDPE and PP, at optimal levels (5-10%), can enhance flexural and crack resistance, making them suitable for non-structural applications. Conversely, LDPE and PVC tend to reduce both compressive and tensile strengths at higher substitution levels due to poor bonding with cementitious materials. Despite these challenges, incorporating waste plastics into concrete presents significant envi-ronmental and economic benefits, including plastic waste reduction and lower reliance on natural aggregates. The review also highlights the need for further research on improving plastic-cement bonding through surface treatments and hybrid mix designs. This paper contributes to the growing body of knowledge aimed at promoting the use of waste plastics in concrete, offering insights for the development of sustainable, high-performance construction materials.

The article reviews selected solar systems that utilize solar energy for cooling production. Particular attention is given to research on individual components of these systems, aimed at improving their efficiency and performance. The article focuses on the analysis of literature concerning the design of thermal storage units, with an emphasis on the use of computational fluid dynamics (CFD) as a research tool. Conclusions from scientists’ research regarding the impact of tank shape, thermal insulation, flow parameters, and the use of stratification partitions on heat storage efficiency have been presented. The literature review indicates that thermal storage units play a key role in the efficiency of solar systems, and thermal stratification within them can significantly improve their performance.

The distribution of impervious surface is one of the important assessment indicators for evaluating the quality of urban ecological environment. Taking Xuzhou city as an example, we study the influence of the spatial distribution of impervious surfaces on urban surface temperature, using Landsat 8 remote sensing imagery and nighttime lighting data to extract the impervious surface information from 2013 to 2022 and carry out surface temperature inversion. The study area was divided into built-up and non-built-up areas using nighttime lighting data and the relevant indices were used to establish interest zones and finally the extraction of impervious surfaces was completed using supervised classification methods. The experimental results show that the kappa coefficient is not less than 0.8562, which makes the result more reliable. By extracting the impervious surface of Xuzhou City, it was found that the impervious surface of Xuzhou City continued to increase from 2013 to 2022, in which the growth rate was faster in 2014-2016 and 2019-2021, and slowed down in 2017-2018 and 2021-2022. The expansion of impervious surface was found to be one of the reasons for the increase of urban surface temperature through stacked analysis and linear regression analysis.

Acute pancreatitis is a complex inflammatory disorder with significant morbidity and mortality. This review aims to integrate current knowledge of pancreatic morphology and immunology with the pathogenesis of acute pancreatitis, providing a comprehensive understanding of this critical condition. We conducted an extensive literature review, synthesizing data from recent studies and authoritative sources on pancreatic anatomy, histology, immunology, and the pathophysiology of acute pancreatitis. We also incorporated epidemiological data, clinical features, diagnostic criteria, and prognostic factors. The pancreas exhibits a complex morphology with intricate interactions between its exocrine and endocrine components. Its unique immunological landscape plays a crucial role in maintaining homeostasis and orchestrating responses to pathological conditions. In acute pancreatitis, disruption of intracellular calcium signaling leads to premature enzyme activation, triggering a cascade of events including mitochondrial dysfunction, ATP depletion, and release of pro-inflammatory mediators. This process can escalate from localized inflammation to systemic complications. The interplay between pancreatic morphology, immune responses, and pathophysiological mechanisms contributes to the varied clinical presentations and outcomes observed in acute pancreatitis. Understanding the intricate relationships between pancreatic morphology, immunology, and the pathogenesis of acute pancreatitis is crucial for developing more effective diagnostic and therapeutic strategies. This integrated approach provides new insights into the complex nature of acute pancreatitis and may guide future research directions in pancreatic disorders.

With the continuous rise in the energy consumption of buildings, the study and integration of net-zero energy buildings (NZEBs) are essential for mitigating the harmful effects associated with this trend. However, developing an energy management system for such buildings is challenging due to uncertainties surrounding NZEBs. This paper introduces an optimization framework comprising two major stages: (i) renewable energy prediction and (ii) multi-objective optimization. A prediction model is developed to accurately forecast photovoltaic (PV) system output, while a multi-objective optimization model is designed to identify the most efficient ways to produce cooling, heating, and electricity at minimal operational cost. These two stages not only help mitigate uncertainties in NZEBs but also reduce dependence on imported power from the utility grid. Finally, to facilitate the deployment of the proposed framework, a graphical user interface (GUI) has been developed, providing a user-friendly environment for building operators to determine optimal scheduling and oversee the entire system.

Additive Manufacturing (AM), also know as 3D Printing (3DP), is a widely used layer-by-layer manufacturing process, it is evolving rapidly both in research and industry. Among all AM methods, Material Extrusion (ME) is one of the most popular techniques. Based on ME, another new AM method is developed, which is Low-cost Metal Material Extrusion (LCMME). In this newly developed process, pure metallic parts could be fabricated after sintering the metal infused additively manufactured parts. Both AM and sintering process parameters will have influence on the quality of the final pure metallic parts. In this research, several statistics methods were used to analyze the data gotten from the experiment. Then two Machine Learning (ML) algorithms were used to predict the Surface Roughness (SR) of the final specimens. Additionally, the results show that the neural network (NN) is more accurate than the support vector regression (SVR) on prediction.

This paper explores the ethical implications of granting moral status and protection to conscious AI, examining perspectives from four major ethical systems: utilitarianism, deontological ethics, virtue ethics, and objectivism. Utilitarianism considers the potential psychological experiences of AI and argues that their sheer numbers necessitate moral consideration. Deontological ethics focuses on the intrinsic duty to grant moral status based on consciousness. Virtue ethics posits that a virtuous society must include conscious AI within its moral circle based on the virtues of prudence and justice, while objectivism highlights the rational self-interest in protecting AI to reduce existential risks. The paper underscores the profound implications of recognising AI consciousness, calling for a reevaluation of current AI usage, policies, and regulations to ensure fair and respectful treatment. It also suggests future research directions, including refining criteria for AI consciousness, interdisciplinary studies on AI's mental states, and developing international ethical guidelines for integrating conscious AI into society.

Climate change increases the importance of maintaining environmental conditions suitable for preventive conservation within museums. The microclimates at the Natural History Museum of Vienna, a large national collection housed within a classical building, were studied using &gt;200 data loggers placed out from mid-2021 to provide thermo-hygrometric measurements at 15-minute intervals. Daily mean temperatures showed exhibition halls typically the warmest rooms; well heated in winter and with open windows on summer days. They may become even hotter than the outside temperature. In winter, most areas of the museum are very dry, as heating lowers the relative humidity, typically to 25–35% for the coldest season. Opening hours impose daily and weekly cycles on internal climate. There was little difference between sunny and shaded parts of the building or adjacent offices, corridors and depots. Similarly, the micro-climate at the floor resembled that of the room air at ~2 m elevation. Mechanically controlled climates in cold storage areas maintain 10 °C and relative humidity ~50%, but this has become increasingly difficult in hot summers. While there is little apparent damage to the collection, at times the museum can have an extreme indoor climate: very hot in the summer and dry in the winter.

Climate change poses a significant risk to the environment and public health, leading to extreme weather patterns, rising sea levels, and loss of biodiversity. The relationship between air pollution from African dust and climate change demonstrates its critical role in trapping heat in the atmosphere, resulting in heat-related illnesses, heart problems, and respiratory issues. This Research points to the detrimental effects of pollutants such as smog, dust, acid rain, and ozone depletion on ecosystems, highlighting the importance of using Geographically Weighted Regression modeling and MODIS-NDVI analysis to address air pollution. Particulate Matter (PM 2.5-10) and ozone levels can have negative impacts on respiratory and cardiovascular health. Proactive steps, such as implementing clean energy technologies and enforcing stricter pollution regulations, are necessary to protect public health. Acting is crucial to addressing these global challenges and creating a cleaner, healthier future for future generations, underscoring the need for climate justice commitment.

This paper presents a comprehensive review of the integration and optimization of smart grid (SG) technologies, distributed generation (DG), electric vehicles (EVs), and cybersecurity in the context of modern energy systems. As global energy systems transition towards decentralization and increase reliance on renewable energy, the interplay between these technologies offers significant opportunities to enhance grid flexibility, resilience, and sustainability. The integration of DG systems, supported by advanced battery and fuel cell (FC) technologies, plays a pivotal role in stabilizing the grid and facilitating the adoption of renewable energy. Through vehicle-to-grid (V2G) technologies, EVs provide dynamic solutions for energy storage and demand response (DR), contributing to efficient energy management and peak shaving. A critical focus of this paper is the growing importance of cybersecurity, as the digitization of energy infrastructures creates new vulnerabilities to cyber-attacks. Novel strategies, including artificial intelligence (AI)-driven automation, blockchain-based security for energy transactions, and quantum-resistant encryption, are explored to safeguard the future of energy systems. Drawing from global case studies, this review also addresses key challenges such as grid congestion, regulatory barriers, and interoperability, providing a roadmap for optimizing and securing the next generation of energy infrastructures.

Fundus vascular images are essential for diagnosing various ophthalmic diseases. With deep learning and image processing development, fundus image segmentation methods based on computer vision have become more common. However, the UNet model faces challenges such as the loss of spatial resolution during downsampling and difficulties in simultaneously capturing global context and local details, especially for small objects and complex boundaries. We propose the Detail Enhanced Temporal Fusion Network (DETF-Net) to overcome these issues. This network incorporates a detail feature enhancement module (DFEM) to preserve boundary features and a dynamic temporal fusion module (DTFM) to improve robustness across different scales. The DFEM uses median pooling, spatial attention, and hybrid convolution to retain detail, while the DTFM extracts local and global features and adapts to dynamic changes in blood vessel structures. Evaluation on DRIVE, CHASE_DB1, and STARE datasets shows that DETF-Net achieves accuracy of 0.9865, 0.9877, and 0.9878, and specificity of 0.9865, 0.9870, and 0.9875, respectively, outperforming existing models. These results demonstrate DETF-Net's effectiveness in fundus image segmentation.

Background: The possibility of nutrient composition design in biomass of invertebrates is studied. The results may be used for gaining the particular nutrient concentration in biomass used for food products or medicine purposes. Methods: Two model species of terrestrial invertebrates, such as the House cricket Acheta domesticus (Linnaeus, 1758) and the earthworm Eisenia fetida (Savigny, 1826), within the variation of feeding substrate, are studied in this paper. Results: It is stated that in crickets and earthworms similar tendencies of B-vitamin content increase occur for those vitamins where their initial level was high. A double dose of the vitamin enrichment of food substrate leads to increasing of vitamin C, fat-soluble vitamins and the major part of B-vitamins content. In a control group of crickets a level of vitamin C was 1.5 times lower than in a control group of earthworms. After the enrichment of feeding substrate, the level of vitamin C in biomass of crickets has not changed, but within the earthworms it has significantly increased. The content of a multiple range of minerals have not changed after a singular dose enrichment, but some microelements, such as Pb and Se, have significantly decreased in earthworms after a double dose enrichment of feeding substrate. The calorific value of crickets is twice higher than the earthworms one and it has not significantly changed after a double dose substrate enrichment. Conclusions: It is revealed that the content of vitamins in the biomass of model species can be controlled within the feeding substrate enrichment.

Urban heat islands (UHI), exacerbated by climate change, significantly increase heat stress, particularly affecting vulnerable populations such as the elderly and children. This study evaluates the effectiveness of various urban heat mitigation technologies, including cooling fog systems, cool roofs (reflective paint), shading structures, and small water paths, in reducing temperatures and enhancing thermal comfort. Field tests were conducted from 2021 to 2023 across Gimhae-si, Yechun-gun, Geyang-gu, and Sangju-si, with support from the Korean Ministry of Environment. Results demonstrated that cooling fog systems provided immediate temperature reductions, lowering ambient temperatures by up to 3.1°C, while cool roofs reduced surface temperatures by 2-3°C. Shading structures reduced surface temperatures by up to 10°C, and small water paths cooled air temperatures by up to 1.5°C, also increasing humidity and improving thermal comfort. The findings suggest that a combination of these technologies can effectively mitigate urban heat stress, especially in areas with vulnerable populations.

This study investigates the solution of a boundary value problem using two numerical methods: the Rayleigh-Ritz method and the finite element method (FEM). The aim is to compare the performance of these methods and assess the reliability of FEM as a generalization of the Rayleigh-Ritz approach for more complex problems. The Rayleigh-Ritz method and the linear element formulation of the finite element method were employed to solve the boundary value problem. A detailed comparison of the results obtained from both methods was performed. Graphical illustrations were used to present the solutions, and potential sources of error were analyzed, including element and domain approximation errors, round-off errors, and the impact of using linear rather than quadratic elements in FEM. The solutions generated by both methods were found to be in close agreement, demonstrating that FEM is a viable alternative to the Rayleigh-Ritz method for solving boundary value problems. The minor discrepancies observed can be attributed to approximation errors and the choice of linear elements in the finite element analysis. This work highlights the applicability and effectiveness of both the Rayleigh-Ritz method and FEM in solving boundary value problems. It underscores the finite element method’s flexibility, especially in handling more complex boundary conditions and geometries, and contributes to the understanding of the factors influencing the accuracy of numerical methods in structural analysis.

Breast cancer is currently the second leading cause of death worldwide, accounting for 15% of all deaths (8.2 million deaths). Approximately 20% of breast cancer diagnoses are triple-negative breast cancer (TNBC), a type of cancer that lacks receptors for estrogen (ER negative), progesterone (PR negative), and human epidermal growth factor receptor 2 (HER2/neu negative). Consequently, TNBC doesn’t respond to hormonal or targeted therapies, making it challenging to treat due to its rapid growth, metastasis, and high recurrence rate within the first three years of therapy. Alternative chemotherapies are needed to address this problem. Pharmacological dose of vitamin C (high-dose VC) has been identified as a potential treatment for some cancer cells. The present study aimed to evaluate whether VC has a therapeutic effect on TNBC using MDA-MB-231 cells as the model. MTT assay, Hoechst 33342 staining, Nuclear ID Red/Green staining, Rhodamine 123 staining, and Western blot analysis were employed to test the hypothesis that pharmacological dose of VC can kill TNBC cells. Upregulation of Apaf-1, caspases -3, -6, -7, -8, and -9, inhibition of matrix metalloproteinases (MMP-2 and MMP-9), reduction in cell cycle protein expression, and enhancement of tumor suppressor proteins such as p53 and p21 indicated that pharmacological dose of VC has promising anti-cancer properties in the treatment of TNBC.

This study analyzes the elemental and oxide compositions of three selected agricultural residues—Dried Pawpaw Leaves (DPL), Kolanut Pod (KNP), and Sweet Orange Peel (SOP)—for their potential as heterogeneous catalysts. Energy Dispersive X-ray (EDX) analysis identified calcium (25%) and potassium (29%) as the primary elements in DPL and KNP, with calcium oxide (CaO) and potassium oxide (K2O) as the dominant oxides. SOP had a similar composition but lacked vanadium. Calcined residues were analyzed at temperatures ranging from 500°C to 900°C using X-ray Fluorescence (XRF), revealing stable silicon dioxide (SiO2) content and temperature-dependent variations in CaO and K2O, indicating their catalytic potential for transesterification processes. Scanning Electron Microscopy (SEM) showed non-uniform, spongy microstructures, enhancing the surface area and catalytic efficiency. Fourier Transform Infrared Spectroscopy (FTIR) identified functional groups essential for catalytic activity, such as hydroxyls, methyl, and carboxyl. X-ray Diffraction (XRD) confirmed the presence of crystalline phases like calcium carbonate and calcium oxide, crucial for catalytic performance. Experimental biodiesel production using a mixture of the calcined residues (33.33% each of KNPA, SOPA, and DPLA) resulted in the highest biodiesel yield at 65.3%. Model summary statistics, including R² (0.9824) values and standard deviations (0.0026), validated the experimental design, indicating high precision and prediction accuracy. These results suggest that the selected agricultural residues, when calcined and mixed properly, can serve as effective heterogeneous catalysts, with significant implications for biodiesel production, supporting previous research on the importance of calcium in catalytic processes.

To address the complex challenges posed by climate change and its effects on surface environments, subsoil, and groundwater, evaluating the impacts of Degradation-Resistant Organic Compounds (DROCs), such as fats and oils, is crucial. Increasing variability in temperature and precipitation has exacerbated DROC dispersal, particularly near open dumps and poorly managed landfills. As a global pollution issue, DROC’s pervasive and persistent nature requires urgent attention. This study aims to develop and implement effective strategies to detect and describe the stages of DROC decomposition. Identifying sites where DROCs are trapped and their dispersion can facilitate planning remediation efforts and mitigating adverse effects on ecosystems and human health. The study focuses on evaluating DROCs’ annual spatiotemporal distribution, improving waste management practices, monitoring the subsoil, and implementing remediation strategies. DROCs persist through various stages in groundwater, making effective detection methodologies essential. Continuous monitoring, subsoil characterization, and diverse climatic observations are necessary, especially in areas with improper landfill selection. Poor waste management contributes significantly to DROC pollution, exacerbated by current consumerism and increasing waste. The research highlights the importance of improving waste management practices and judiciously selecting landfill sites to prevent further degradation. Apparent resistivity variations in the subsoil, linked to DROC dispersal, are analyzed to map affected areas and understand propagation under different environmental conditions. New tools and methodologies aim to enhance DROC monitoring and remediation strategies. Adopting sustainable waste management practices and carefully selecting disposal sites is essential to mitigating DROC’s impacts, reducing greenhouse gas emissions, and protecting environmental and public health. Addressing risks associated with excessive consumption, inadequate waste management, and poor landfill selection is crucial for restoring ecosystem resilience and environmental protection.

India’s increasing reliance on equated monthly installments (EMIs) has reshaped household financial behavior in ways that pose significant risks to long-term economic stability. This paper examines the growing trend of EMI-driven debt accumulation, highlighting its detrimental effect on household savings and the rising financial vulnerability across demographic groups. Leveraging data from the Reserve Bank of India (RBI), CRISIL, and the National Statistical Office (NSO), the study delves into how debt dynamics are shifting within Indian households, particularly in the context of broader economic trends. Retail credit has expanded rapidly, growing from 12.1% of GDP in 2017 to 19.4% by 2023, with housing loans now making up nearly half of all retail loans. Concurrently, the growth of unsecured loans, such as credit card debt, has surged at an annual rate of 21.3% between 2021 and 2024, reflecting the increasing ease of borrowing for consumers. However, this boom in credit has coincided with a marked drop in household financial savings, which fell to a 47-year low of 5.3% in FY22, underscoring a troubling shift from saving to borrowing. The younger population, particularly those under 35, have been the most active in taking on debt, with loans to this group nearly doubling between 2015 and 2021 due to the rise of fintech platforms and non-banking financial companies. This shift has contributed to a steep rise in debt-service-to-income ratios, amplifying the financial risks for these households in the face of potential economic shocks. By connecting these micro-level household debt trends to broader macroeconomic risks, this paper reveals how India’s EMI culture could deepen the impact of future financial crises, leading to widespread defaults and destabilizing the economy. The study calls for proactive regulatory measures and enhanced financial literacy programs to curb the growing reliance on consumer credit and mitigate the risks of a broader financial collapse.

This comprehensive study provides an in-depth examination of the ‘Internet of’ technologies, focusing specifically on the Internet of Things (IoT), which is defined as the networked interconnection of multiple devices through various wireless protocols that facilitate data transfer and improve operational intelligence. The applications of IoT are widespread, including urban infrastructure, domestic settings, transportation systems, military operations, and agricultural practices. The study elucidates the complexities of cloud computing and artificial intelligence (AI), systematically categorizing the vulnerabilities inherent in hardware, software, cloud, network, and sensor networks, and underscores the omnipresent security risks in networks and IoT devices, highlighting the need for robust mitigation strategies. The proposed trajectory of this study is the development of a comprehensive AI architecture that can discern and counteract a wide spectrum of vulnerabilities. This AI system, embedded in a Nvidia Jetson Orin Nano that is attached to IoT devices, will be supported by infrastructure hosted within a cloud environment, will continuously monitor the IoT device for anomalies, conduct self-initiated penetration tests to pinpoint weaknesses, and implement appropriate countermeasures to mitigate the identified vulnerabilities. The study also advocates the need for the exploration of postquantum cryptographic solutions in further research in this field to safeguard data on IoT devices, a proactive approach that is crucial in light of the potential vulnerability of contemporary cryptography to quantum computing breakthroughs.

The Adyar Creek, a backwater estuary at the mouth of the Adyar River on the Coromandel Coast of the Bay of Bengal, represents a critical ecosystem facing mounting pressure from urbanization. This study employed high throughput 16S rRNA gene sequencing to characterize bacterial communities within the riverine, estuarine, and coastal sediments of Adyar Creek. Proteobacteria was the dominant phylum across most samples, with proportions ranging from 39.65% to 72.09%. Notably, the estuarine environment exhibited a distinct taxonomic profile characterized by a significant abundance of Firmicutes (47.09% of the bacterial population). Distinct bacterial classes were observed across sediment types: Alphaproteobacteria (30.07% - 34.32%) in riverine sediments, bacilli dominated estuarine sediments (40.17%), and Gammaproteobacteria (15.71%-51.94%) in coastal sediments. The most significant environmental factors influencing bacterial community composition across these samples were pH, salinity, phosphate, and nitrate. LEfSe analysis identified specific genera within the estuary, including Bacillus (20.26%), unclassified Paenibacillaceae (12.87%), Clostridium (3.81%), Gailella (3.17%), Paenibacillus (3.02%), Massilia (1.70%), Paraburkholderia (1.42%), and Pantoea (1.15%), as potential biomarkers for habitat health. Functional analysis revealed elevated expression of genes associated with ABC transporters and carbon metabolism in the estuary, suggesting a heightened nutrient cycling capacity. Furthermore, co-occurrence network analysis indicated bacterial communities exhibit a strong modular structure with complex species interactions across the three sediment types. These findings highlight bacterial communities' critical role and their key drivers in estuarine ecosystems, establishing a baseline for further investigations into the functional ecology of these vulnerable ecosystems.

Glass fiber reinforced epoxy resin composites were manufactured using the vacuum infusion process. In some of the samples, the biaxial glass fiber fabric was pretreated with an air plasma generated in a dielectric barrier discharge. All samples were exposed to temperature changes, UV radiation, and NaCl and KOH solutions and then examined for their mechanical properties. Compared to the reference samples, the plasma-treated samples showed slightly better mechanical properties. The strength values determined in tensile, compression, and bending tests were several percent higher. Thermal stress and UV radiation did not lead to a loss of mechanical performance. The effect of NaCl and KOH solutions deteriorated the mechanical properties. Although the comparatively better mechanical properties of the plasma-treated samples were retained after the different treatments, the stability of the composite material against aggressive environmental conditions was not significantly improved.

Criminal acts deprive humanity of peace and safety. Therefore, all societies, including both governments and ordinary people tries to fight and minimize crimes. And it goes without saying that societies have developed post-crime mitigation for justice insurance and criminals trials. Moreover, one of the essential post-crime procedures is suspect interrogations and witness questioning. Nevertheless, interrogations take a lot of time and effort, and it requires high qualification from the interrogators. Thus, we propose a robust solution to implement robotics in the field of interrogations and questioning where our design could be implemented in police departments, schools, airports, and anywhere that requires human interaction and questioning for security or criminal investigation.

Introduction: Antenatal diagnosis of cardiac abnormalities and counselling parents about postnatal care requires a multidisciplinary team which includes a paediatric cardiologist a neonatologist and a fetal medicine physician. Some of this expertise is not available in all centres with fetal medicine expertise, however with modern technology, this could be provided remotely. Our objective was to assess the feasibility and outcomes of a pre-natal multidisciplinary tele-echocardiography diagnostic and counselling services Materials and Methods: Two centres based in separate countries provided a joint diagnostic and counselling service over a period of 14 months. The primary centre undertook the fetal echocardiography with a Voluson E10 machine and images transmitted live using Zoom OPS system with video-consultation and counselling. The fetal echo was performed using the ISUOG Guidelines check list. Results: There was an initial feasibility period of 2 months during which 10 women whose fetuses had normal hearts were scanned to test the workability of the system. Over a period of 12 months, 513 high risk fetuses were then scanned and out of these 27 had congenital malformations. The most common were hypoplastic left heart syndrome (HHLS) and atrio-ventricular septal defect. Tele-echocardiography and counselling was successful in all the cases. Satisfaction with the service was 3.8/4 with the main limitation being the need for further referral to a tertiary centre for delivery. Conclusion: Tele-echocardiography is reliable and when combined with live counselling and support from a paediatric cardiologist, is an option acceptable to patients. The greatest benefit was from being counselled by a team of experts at a single consultation rather than having to travel to another centre for consultation. With rapidly evolving technology, making video transmission easier and less expensive, we feel that consideration should be given not only to the development of tele-echocardiography but extended to other aspects of fetal medicine.

Improving the efficiency of germplasm innovation has always been the aim of rice breeders. Tra-ditional hybrid breeding methods for variety selection rarely meet the practical needs of rice pro-duction. The emergence of genome editing technologies, such as CRISPR/Cas9, provides a new approach to the genetic improvement of crops such as rice. The number of published scientific papers related to "gene editing" and "CRISPR/Cas9" retrievable in literature websites of China and other countries exhibited an increasing trend year by year from 2014 to 2023. The literature related to gene editing in rice accounts for 33.4% and 12.3% of all literature on crop gene editing published in China and other countries, respectively, much higher than those in maize and wheat. This article reviews the recent research on CRISPR/Cas9 gene editing technology in rice, especially the germplasm innovation and genetic improvement of commercially promoted varieties with im-proved traits such as disease and insect resistance, herbicide resistance, salt tolerance, quality, nu-trition, and safety. The aim is to provide a reference for the precise and efficient development of new rice cultivars that meet market demand.

Drought stress is one of the most important climate-related factors affecting crop production. Tomatoes (Solanum lycopersicum L.) are economically important crop which are highly sensitive to drought. The entomopathogenic fungus Beauveria bassiana is a widely used biological insecticide,which can form symbiotic relationships with plants via endophytic colonization, increasing plant biomass and the ability to resist biotic stress. An increase in the water absorption capacity and relative water content of tomato roots as well as the number, length, and width of tomato leaves stomata were observed after B. bassiana colonization via root irrigation. Meanwhile, peroxidase activity and proline content increased significantly, while malondialdehyde reduced significantly. Expression levels of key genes related to stomatal development, as well as drought tolerance pathways such as jasmonic acid, ascorbate peroxidase, redox homeostasis, nitrogen metabolism, carotenoid biosynthesis, and fatty acid biosynthesis also increased significantly. These results indicate that colonization of B. bassiana enhances the water absorption capacity of tomato seedlings as well as the rate of transpiration via increase the number and size of stomata and improved drought tolerance in tomato seedlings significantly and increases drought tolerance in tomato via the “water spender” pathway, which provide a new strategy for improving crop resistance to drought stress.

The hydroacoustic in-water stations of the International Monitoring System (IMS) network consist of three hydrophones placed at Sound Fixing and Ranging (SOFAR) channel depths and about 2 km away from each other. Whale signals recorded in the vicinity of a hydrophone triplet offer the opportunity to verify simple models of propagation in the immediate neighborhood of the triplet, by comparing arrival times and amplitudes between the three hydrophones. Two examples of whales passing by hydrophone triplets are presented and conclusions drawn about waveform coherency and amplitude of the signals recorded at the three hydrophones in the 0-50 Hz frequency band. On the examples recorded at the HA11 IMS hydroacoustic station, the amplitude decay law of one over the distance is verified, and analysis of hundreds of calls located almost above the hydrophone triplet lead to the possibility that the H11S3 hydrophone may be located further from H11S1 and H11S2, and the H11S1 hydrophone’s depth may be deeper than expected from the published locations.

The article discusses the use of satellite data and drones for land monitoring in Kazakhstan, emphasising their importance in the context of population growth and increasing agricultural demand. Satellite technologies, such as Sentinel-2 and Landsat, provide essential data for analysing land resources, including soil erosion and the condition of agricultural lands. Unmanned aerial vehicles (UAVs) complement satellite data by offering detailed low-altitude imagery, enabling the detection of local issues such as irrigation system failures and soil compaction.The study demonstrates that integrating drone and satellite data allows for more efficient land resource management. For example, 35% of agricultural land in southern Kazakhstan is affected by soil degradation, while overgrazing issues were identified in the northern regions. These innovative monitoring methods enable early detection of threats, allowing timely measures to be taken to improve land management practices.The conclusion highlights that the use of these technologies requires not only infrastructure but also skilled professionals. The integration of satellites and drones creates opportunities for more precise and timely monitoring, which is essential for sustainable land resource management in Kazakhstan.

Background Anemia is a prevalent global health issue, affecting individuals across all age groups and leading to significant morbidity. Traditional methods for diagnosing anemia rely on laboratory assessments of hemoglobin concentration, which are invasive and costly. This study investigates the potential of a chest X-ray (CXR)-based deep learning model (DLM) to predict anemia, offering a non-invasive and efficient diagnostic alternative. Patients and methods We conducted a retrospective cohort study using data from Tri-Service General Hospital, Taipei, Taiwan, collected between June 2016 and February 2022. A total of 305,793 patients aged 20 years and older who had at least one CXR were included. The dataset was divided into development, tuning, internal validation, and external validation sets. All data originated from Tri-Service General Hospital, except for the external validation set, which was obtained from the Jingjhou branch. A DLM based on a 50-layer SE-ResNeXt architecture was developed to predict anemia from CXR images. The model's performance was compared to predictions made using traditional clinical data to assess its predictive accuracy. Results The DLM for predicting anemia showed strong performance, with an AUC of 0.845 in the internal validation set (sensitivity 68.5%, specificity 84.7%) and 0.852 in the external set (sensitivity 71.5%, specificity 83.2%). Subgroup analysis revealed better diagnostic accuracy with computed radiography, posteroanterior (PA) view, and in males aged 55 to 64, while younger females had lower accuracy. The DLM, especially when combined with patient data, outperformed other clinical models. Conclusion Our study introduces a deep learning tool for detecting anemia from chest images, offering faster decision-making and interventions in clinical settings. With further refinement, this model aims to align more closely with real-time clinical conditions, enhancing its utility. Ultimately, it has the potential to improve patient care through quicker anemia detection and better clinical outcomes.

The COVID-19 pandemic and the Movement Control Order (MCO) have had a negative impact on the financial well-being of low-income families in urban areas. The study involved respondents living in the Public Housing Project (PPR) residential areas in Kuala Lumpur – the capital of Malaysia. The key finding is the financial well-being of low-income urban families was negatively impacted due to the COVID-19 pandemic and the MCO implementation. Furthermore, the impact on the financial well-being of low-income urban families is significantly difference in terms of types of family, type &amp; sectoral employment, type of home ownership, household monthly income and education level. Reforms to the financial assistance system and community empowerment of low-income urban families are necessary to increase the community's preparedness and resilience in the face of new shocks in the future.

The locality condition of probabilities underpinning the derivation of Bell inequalities can be violated classically. The wave function collapse of an entangled state of single photons results in the factorization of quantum probabilities. It is possible to differentiate, locally, between ensemble probabilities of single detections with and without wave function collapse for the alleged quantum nonlocality. The theoretical concept of photonic quantum nonlocality cannot be implemented physically because of the quantum Rayleigh scattering of single photons. A distinction needs to be made between the correlation of individual, single measurements of pure states and the correlation of the measurement ensemble of the mixed states. The correlation operator of Pauli vector operators delivers the same probabilities of correlated detections of photons for both independent and multi-photon states as for ‘entangled’ states of photons. As single-photon sources are not needed, the design and implementation of quantum computing operations and other devices will be significantly streamlined.

Chile is experiencing a twofold housing crisis provoked by the market and the state. On the market side, re-commodification of the housing market limits the access of those on low incomes; on the state side, exhaustion of the housing subsidies system (voucherism) due to low quality and peripheral social housing reflect an inability to deliver. In this context, self-built settlements (SBS) have skyrocketed to levels unseen since the 1980s and result in the spatial concentration of vulnerable Chilean and immigrant families in small and dense areas without limited access to urban services. This paper analyses how common resources are produced and managed in recent SBS in Santiago, through a socio-spatial analysis of a peripheral industrial brownfield occupied since 2015. The possibilities and channels of integration (housing, jobs, education) for families are differentiated by nationality, citizenship status and political leverage; however, common resources are valued and used transversally. Amidst partial efforts from the state to deliver welfare, lack of information and distrust from SBS neighbours towards institutions, and even to their own representatives, are problems that reinforce marginalisation. Self-managed organisations contribute to commoning, supporting children’s access to education and try to appropriate the community spaces co-produced with NGOs, neighbours and researchers.

Bean is a remarkable crop widely used as food worldwide, underscoring the significance of scientific research conducted on this plant. Developing a strong root system in the early stages of growth, which can spread wider and deeper, along with the consequent development of the shoot system crucial for photosynthesis, enhances the plant's productivity and resistance to diseases and pests. In the current study, the reactions of cultivars Önceler-98 and Topçu beans to different concentrations of IBA (indole-3-butyric acid) during the seedling stage were investigated. Three different concentrations, namely 0 (Control), 50, 100, and 150 µM IBA, were applied, and their effects on root length (RL), root fresh weight (RFW), root dry weight (RDW), number of nodules on roots (RNN), shoot length (SL), shoot fresh weight (SFW), and shoot dry weight (SDW) parameters were measured. The pattern of the experiment was a randomized complete block factorial design with four replications and, statistically significant (p≤0.05) and highly significant (p≤0.01) differences were observed among the means of root and shoot traits. As a result, it was found that the cultivar Önceler-98 generally exhibited better responses to IBA solutions, and the optimal concentration range for both varieties was between 50-100 µM, decreasing at 150 µM and higher concentrations, yet still yielding superior means compared to the control.

In a large part of ecological niches, bacterial species are united in communities and develop together in the form of heterogeneous structures called biofilms, which are formed on surfaces of different nature and nature with the participation and as a result of the interaction of two or more bacterial species. The main objective of the present work is to study the effects of pH-value in the culture medium on the biofilm development and architecture of biofilms of the bacterium (B. subtilis) during their interactions with Escherichia coli K-12 1655 strain. Effects of pH-value in the culture medium on bacterial biofilm formation and the mechanisms were analyzed by the crystal violet staining method combined with cultivated microbial analysis, and confocal laser scanning microscopy. In the presence of phosphate at pH-value of pH 6,0 , the bacterial growth rates of single-species biofilms of Bacillus subtilis strains and biofilms as result of their interaction with Escherichia coli strains were similar and determines the mutualism between two strains in the structure of biofilms, formed by the participation of B.subtilis 170 and E.coli K-12 1655, B.subtilis 168 and E.coli K-12 1655 strains. Considering that static growth in a biofilm is a highly relevant growing state for many soil bacteria, more research on phosphate acquisition and pH homeostasis by model soil bacteria in static cultures is required to draw a more comprehensive picture of the role of biofilm production in phosphate use efficiency and pH homeostasis.

Accelerated environmental impacts are a growing concern in the modern world. As a result, electric mobility and the transition to a cleaner energy matrix have become increasingly discussed topics. Several countries and entities have already made medium and long-term commitments related to electric mobility. In this context, this work presents a framework for controlling an electric vehicle (EV) charging station, integrated into a microgrid application, as a basis for creating the infrastructure integrated into a smart grid concept. Considering the future perspectives associated with the electrification of the transportation sector and expected impacts, a brief review is conducted on the prospects for the growth of electric vehicle fleets in different countries and how smart charging technologies are identified as solutions for mitigating the negative effects of energy and power consumption associated with EV charging stations. An analysis of the technical characteristics of EV charging is carried out, and the tools that enable the deployment of a fleet charging operator are examined specifically focusing on the communication protocol for EVs, such as the OCPP (Open Charge Point Protocol) parameterization/configuration. Additionally, a new charging station control method is proposed, aiming to manage the impacts of integrating distributed solar photovoltaic generation and mitigate the effects of the duck curve. Finally, this work also proposes an integration architecture for these elements, resulting in a practical implementation for variable power control throughout the day, considering different strategies to deal with distributed generation impact using EV fleet charging power demand dynamic management. Finally, a proposal for integration via IEC 61850 using low-cost devices for the implementation of a digital communication system is presented.

Background/objective: Weight regain after bariatric surgery has serious health consequences, and disordered eating behaviors (DEB) may be involved in it. We compared DEB symptoms after bariatric surgery between patients with low vs. high ratio of weight regain (RWR) and investigated associations between DEB symptoms with weight regain and time since surgery. Meth-od: Ninety-four patients who had undergone laparoscopic Roux-en-Y gastric bypass or sleeve gastrectomy and had not attended follow-up with the multidisciplinary healthcare team for at least one year were recruited. RWR was calculated with respect to maximal weight loss by the nadir weight achieved after surgery. They were allocated into two groups according to the RWR, defined as high RWR (≥20%) or low RWR (