Investments in small and medium-sized anaerobic digestion facilities have the potential to boost biogas production in Greece and other EU countries. This study aimed to evaluate the economic feasibility of anaerobic digestion facilities equipped with combined heat and power (CHP) units ranging from 50 to 400 kW, while treating livestock waste. For this purpose, data were gathered from various livestock operations (dairy cattle, poultry, swine, dairy sheep and goat) regarding their annual production, revenues, electricity and fuel usage, and waste generation. Waste samples were then collected and analyzed to assess their biochemical methane production potential. The capital and operational costs of anaerobic digestion facilities, from 50 and 400 kW, were calculated using the equations developed within the “eMT cluster” project. Findings indicate that current feed-in tariffs (FIT) of 0.21 € kWh-1 are insufficient to incentivize investment in anaerobic digestion facilities with capacities below 250 kW, highlighting the need for increased FIT rates or capital expenditure subsidies. Recommendations include shifting towards simplified technology and business models with reduced farmer involvement, coupled with supportive legislative framework and long-term electricity price guarantees. These measures are expected to foster the implementation of anaerobic digestion projects in the animal husbandry sector.

Hydroperoxides (ROOH) are known as damaging agents capable of mediating mutation, while a role as signaling agents through oxidation of protein sulfhydryls that can alter cancer-related pathways has gained traction. Glutathione peroxidase 2 (GPX2) is an antioxidant enzyme that reduces ROOH at the expense of glutathione (GSH). GPX2 is noted for a tendency of large in-creases or decreases in expression levels during tumorigenesis that leads to investigators focusing on its role in cancer. However, GPX2 is only one component of multiple enzyme families that metabolize ROOH and GPX2 levels are often very low in the context of these other ROOH reducing activities. Colorectal cancer (CRC) was selected as a case study for examining GPX2 function as colorectal tissues and cancers are sites where GPX2 is highly expressed. A case can be made for a significant impact of changes in expression levels. There is also a link between GPX2 and NADPH oxidase 1 (NOX1) from earlier studies that is seldom addressed and is discussed, presenting data on a unique association in colon and CRC. Tumor-derived cell lines are quite commonly used for pre-clinical studies involving the role of GPX2 in CRC. Generally, selection for this type of work is limited to identifying cell lines based on high and low GPX2 expression with the standard re-search scheme of overexpression in low expressing lines and suppression in high expressing lines to identify impacted pathways. This overlooks CRC subtypes among cell lines involving a wide range of gene expression profiles and a variety of driver mutation differences along with a large difference in GPX2 expression levels. A trend for low and high GPX2 expressing cell lines to segregate into different CRC subclasses, indicated in this report, suggests that choices based solely on GPX2 levels may provide misleading and conflicting results by disregarding other properties of cell lines and failing to factor in differences in potential protein targets of ROOH. CRC and cell line classification schemes are presented here that were intended to assist workers in performing pre-clinical studies but are largely unnoted in work on GPX2 and CRC. Studies are often initiated on the premise that the transition from normal to CRC is associated with up-regulation of GPX2. This is probably correct. However, the source normal cells for CRC could be almost any colon cell type, some with very high GPX2 levels. These factors are addressed in this study.

Background: The aim was to diagnose Candida in the oral cavity of subjects with type 2 diabetes mellitus (T2DM) using a genotyping technique and to compare the results with those from con-ventional diagnosis by Papanicolau (Pap) staining. Methods: Palatal mucosa smears were per-formed in 18 dental care patients diagnosed with T2DM and grade I, II, and III prosthetic stomatitis who met the inclusion criteria; 18 healthy control subjects were also included in the study. He-moglobin A1c (HbA1c) levels were determined from total blood. Using exfoliative cytology, the Pap staining technique was used to diagnose candidiasis. Exfoliative cytology was also used for molecular diagnosis; DNA was obtained for Candida genotyping and RNA was used for gene ex-pression studies. Results: Clinical patterns indicated that all subjects were positive for Candida; however, Pap analysis revealed only three positive subjects, whereas end-point polymerase chain reaction (PCR) analysis revealed fifteen subjects with some type of Candida. The most common Candida species found were Candida guilliermondii (38.8%), Candida krusei (33.3%), Candida tropicalis, and Candida lusitaniae (22.2%). Interestingly, the coexpression of different species of Candida was found in various patients. In all patients, HbA1c levels were increased. Gene expression analysis showed a significant decrease (p ≤ 0.05) in TLR2 expression in positive subjects, whereas TLR4 expression did not differ significantly among patients. Conclusions: The end-point PCR technique showed better sensitivity for diagnosis of Candida when compared with diagnosis by Pap staining. T2DM subjects showed an increased presence of C. guilliermondii that was correlated with decreased TLR2 expression

Early-season crop-type data are required for a variety of agricultural monitoring and decision-making applications. The early season in this study referred to the prophase and middle of a growth season. Early-season detection of crop types remains challenging because of limited discriminative features, especially for landscapes that are characterized by complex cropping patterns. In fact, different remote-sensing satellites can increase the frequency of data acquisition, which can provide more information in the early season. Moreover, optical and radar sensors have different degrees of sensitivity to crop parameters. Therefore, the integration and application of two types of multitemporal data are of great significance to improve the accuracy and timeliness of crop type detection.In deep learning (DL), convolutional neural network (CNN) and recurrent neural network (RNN) models have great potential for temporal feature extraction. Compared with RNNs, CNNs usually have fewer parameters and are more conducive to determining early-season detection dates of different crop types, which requires a lot of training because of the need to model on different dates. Nevertheless, revisit dates and temporal intervals of different satellites are usually different, resulting in different data acquisition time series; these data cannot be directly used as input for the same convolutional layer. To address this challenge, a Dual-1DCNN was bulit based on the CNN model in this study. Moreover, an incremental training method was used to attain the network on each data acquisition date and obtained the best detection date for each crop type in the early season. A case study for Hengshui City in China was conducted using time series of Sentinel-1A (S1A) and Sentinel-2 (S2). To verify this method, classical methods support vector machine (SVM) and random forest (RF) were implemented. The results demonstrated the following: (1) the Dual-1DCNN extracted discriminative features from S1A and S2 time series at the early season by producing the highest overall accuracy (OA: 87.23%); (2) for summer maize, cotton, and common yam rhizome, the Dual-1DCNN achieved F1 values of 92.39%, 87.71%, and 84.38%, respectively, at the early season (moreover, the early seasons were almost 40, 70, and 80 days before the end of the growth seasons, respectively). These findings suggested that the Dual-1DCNN is promising for the accurate and timely detection of crop types.

We find at least 4 quantum properties that are indeed universal in some number systems; and we can use them for quantum consciousness. Using the sets B={0,1}, N, Z, or Q has the +4 quantum properties that one can trust, as archetypes of easy communication to friends and foes, to ignoranti or cognoscenti, and for quantum computing. This paper proposes the use of Bayesian geometry to reduce the space of possible results, reducing or increasing initial beliefs by successive experimentation. This is exemplified in biology and mathematics, and can be applied to physics and other sciences. The conclusion is that an experimental fact can be absolutely verified. Any mathematical choice (as verified by computers) militating against R=Q, is under an absolutely low chance to succeed. Infinitesimals are denied based on 3^16 independent factors. This is not a probabilistic result, but based on reduction of the Bayes geometry for updating beliefs. This work applies to non-probabilistic and unknown phenomena, such as those found in oscillations (neutrino, health), evolution, and quantum computing, denies Gödel's uncertainty, and solves the liar's paradox by reflection. This connects different scientific fields with one another, in an internet, i.e., in a network of connections of multiple open networks, using the set Q, resembling a hologram, and includes entanglement.

Background: There are no known medicines or vaccines to control the COVID-19 pandemic caused by SARS-CoV-2 (nCoV). Antiviral peptides are superior to conventional drugs and may also be effective against COVID-19. Hence, we investigated the SARS-CoV-2 Spike RBD (nCoV-RBD) that interacts with hACE2 for viral attachment and entry. Methods: Three strategies and bioinformatics approaches were employed to design potential nCoV-RBD - hACE2 interaction-blocking peptides that may restrict viral attachment and entry. Firstly, the key residues interacting with nCoV-RBD - hACE2 are identified and hACE2 sequence based peptides are designed. Second, peptides from five antibacterial peptide databases that block nCoV-RBD are identified; finally, a chimeric peptide design approach is used to design peptides that can bind to key nCoV-RBD residues. The final peptides are selected based on their physiochemical properties, numbers and positions of key residues binding, binding energy, and antiviral properties. Results: We found (i) three amino acid stretches in hACE2 interact with nCoV-RBD; (ii) effective peptides must bind to three key positions of nCoV-RBD: Gly485/Phe486/Asn487, Gln493, and Gln498/Thr500/Asn501; (iii) Phe486, Gln493, and Asn501 are critical residues; (iv) AC20 and AC23 derived from hACE2 may block two key critical positions; (iv) DBP6 identified from databases can block the three sites of the nCoV-RBD interacting with one critical position Gln498; (v) seven chimeric peptides were considered promising among which cnCoVP-3, cnCoVP-4, and cnCoVP-7 are the top three; and (vi) cnCoVP-4 meets all the criteria and is the best peptide. Conclusion: All the ten peptides need experimental validation for their therapeutic efficacy.

Italy was the first country in Europe which imposed control measures of travel restrictions, quarantine and contact precautions to tackle the epidemic spread of the novel coronavirus (SARS-CoV-2) in all its regions. While such efforts are still ongoing, uncertainties regarding SARS-CoV-2 transmissibility and ascertainment of cases make it difficult to evaluate the effectiveness of restrictions. Here, we employed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model to assess SARS-CoV-2 transmission dynamics, working on the number of reported patients in intensive care unit (ICU) and deaths in Sicily (Italy), from 24 February to 13 April. Overall, we obtained a good fit between estimated and reported data, with a small fraction of unreported SARS-CoV-2 cases (19.5%; 95%CI=0%-34.7%) before 10 March lockdown. Interestingly, we estimated that the first set of restrictions reduced transmission rate in the community by 42% (95%CI=38%-46%), and that more stringent measures adopted on 23 March succeeded to drastically curb the transmission rate by 84% (95%CI=80%-88%). Thus, our estimates delineated the characteristics of SARS-CoV2 epidemic before restrictions taking into account unreported data. Further modeling after the adoption of control measures, moreover, indicated that restrictions reduced SARS-CoV2 transmission considerably.

Ionizing radiation exposure can cause damage to diverse tissues and organs, with the hematopoietic system being the most sensitive. However, limited information is available regarding the radiosensitivity of various hematopoietic cell populations in the bone marrow due to the high heterogeneity of the hematopoietic system. In this study, we observed that granulocyte-macrophage progenitors, hematopoietic stem/progenitor cells and B cells within the bone marrow showed the highest sensitivity, exhibiting a rapid decrease in cell numbers following irradiation. Nonetheless, neutrophils, natural killer (NK) cells, T cells, and dendritic cells demonstrated a certain degree of radioresistance, with neutrophils exhibiting the most pronounced resistance. By employing single-cell transcriptome sequencing, we investigated the early responsive genes in various cell types following irradiation, revealing that distinct gene expression profiles emerged between radiosensitive and radioresistant cells. In B cells, radiation exposure led to a specific upregulation of genes associated with mitochondrial respiratory chain complexes, suggesting a connection between these complexes and cell radiosensitivity. In neutrophils, radiation exposure resulted in fewer gene alterations, indicating their potential for distinct mechanisms in radiation resistance. Collectively, this study provides insights into the molecular mechanism for the heterogeneity of radiosensitivity among the various bone marrow hematopoietic cell populations.

This article investigates and studies the current situation of implementing the credit system in ordinary high schools in Zhejiang Province, and puts forward relevant suggestions. Firstly, analyze the background and objectives of implementing the credit system in ordinary high schools in Zhejiang Province. Then, through a questionnaire survey method, a sample survey was conducted on the current status of the implementation of the credit system in ordinary high schools in Zhejiang Province. The results showed that there are some problems in the management of the credit system in schools, such as unreasonable credit course settings, inaccurate recording and statistics of credits, etc. Further analysis reveals that students and parents have biases and utilitarian motives in their understanding and evaluation of the credit system.

Technological developments within the maritime sector are resulting in rapid progress that will see the commercial use of autonomous vessels, known as Maritime Autonomous Surface Ships (MASS). Such ships are equipped with a range of advanced technologies, such as IoT devices, artificial intelligence (AI) systems, machine learning (ML) based algorithms and augmented reality (AR) tools. Through such technologies, the autonomous vessels can be remotely controlled from Shore Control Centres (SCC) by using real-time data to optimise their operations, enhance safety and reduce the possibility of human error. Apart from the regulatory aspects, which are under definition by the International Maritime Organisation (IMO), cybersecurity aspects must be considered and properly addressed to prevent such complex systems from being tampered with. In this paper, we propose an approach to secure communication channels between the SCCs and the vessels using SECOM standard and the underlying digital infrastructure in charge of data collection, storage and processing by relying on a set of machine learning (ML) algorithms for anomaly detection. The proposed approach is validated against a real implementation of the SCC deployed at Livorno seaport premises. Finally, the experimental results and the performance evaluation are provided to assess its effectiveness accordingly.

The recent outbreak of a new Coronavirus has developed into a global pandemic with about 10,5 million reported cases and over 500,000 deaths worldwide. Our prospective paper reports an updated analysis of the impact that this pandemic had on the Italian agri-food sector during the national lockdown and discusses why and how this unprecedented economic crisis could be a turning point to deal with the overall sustainability of food and agricultural systems in the frame of the forthcoming European Green Deal. Its introductory part includes a wide-ranging examination of the first quarter of pandemic emergency, with a specific focus on the primary production, to be understood as agriculture (i.e. crops and livestock, and their food products), fisheries and forestry. The effect on the typical food and wine exports, and the local environment tourism segments is also taken into account in this analysis, because of their old and deep roots into the cultural and historical heritage of the country. The subsequent part of the paper is centered on strategic lines and research networks for an efficient socio-economic and territorial restart, and a faster transition to sustainability in the frame of a circular bio-economy. Particular emphasis is given to the urgent need of investments in research and development concerning agriculture, in terms of not only a fruitful penetration of the agro-tech for a next-generation agri-food era, but also a deeper attention to the natural and environmental resources, including forestry. As for the rest of Europe, Italy demands actions to expand knowledge and strengthen research applied to technology transfer for innovation activities aimed at providing solutions for a climate neutral and resilient society, in reference to primary production to ensure food security and nutrition quality. Our expectation is that science and culture return to play a central role in national society, as their main actors are capable of making a pivotal contribution to renew and restart the whole primary sector and agri-food industry, addressing also social and environmental issues, and so accelerating the transition to sustainability.

This paper examines the quantitative and qualitative situation of the current fixed and mobile Internet and its expected future. First, the number of users and penetration rate of the Internet, various types of services in different countries, the ranking of countries in terms of the mean and median download and upload Internet data speeds, Internet data volume, and number and location of data centers in the world are presented. The second task introduces and details twelve performance evaluation metrics for broadband Internet access. Third, different wired and wireless Internet technologies are introduced and compared based on data rate, coverage, type of infrastructure, and their advantages and disadvantages. Based on the technical and functional criteria, in the fourth work, two popular wired and wireless Internet platforms, one based on optical fiber and the other based on the 5G cellular network, are compared in the world in general and Australia in particular. Moreover, this paper has a look at Starlink as the latest satellite Internet candidate, especially for rural and remote areas. The fifth task outlines the latest technologies and emerging broadband Internet-based services and applications in the spotlight. Sixthly, it focuses on three problems in the future Internet in the world, namely the digital divide due to the different quality of the Internet and new Internet-based services and applications of emerging technologies, the impact of the Internet on social interactions, and hacking and insecurity on the Internet. Finally, some solutions to these problems are proposed.

In the realm of autonomous driving tort, a significant disparity exists in the parties' access to autonomous driving data and essential technical information, resulting in challenges in unilateral proof. The traditional burden of proof framework in driving litigation is inadequate for direct application in the autonomous driving sphere. As we approach the era of widespread autonomous driving operations, there is an urgent need to clarify and redefine the allocation of the burden of proof in specific litigations. Utilizing comparative legal analysis and case studies, this paper delves into the disparities in legislative provisions concerning the burden of proof for autonomous driving in Germany and China. China can learn from Germany's legislative precedence in shifting the burden of proof for 'product defect' and 'fault' onto the manufacturer, thereby requiring the infringed party to merely furnish preliminary evidence indicating a 'causal relationship between the defect and the damage.' This approach mitigates the evidentiary burden on the aggrieved party, clarifies litigation procedures, incentivizes manufacturers to enhance technology, reinforces risk management, and ultimately, facilitates the progression of autonomous driving technology.

Cocoyam is a highly nutritious root crop and very promising with vast industrial potentials. The effect of some processing methods on the proximate composition of cocoyam (Xanthosoma sagittifolium) flour was investigated by subjecting the cormels to three pre-treatment methods (soaking, fermentation and steaming) and subsequently, to two different milling methods (wet and dry-milling methods). The proximate composition namely moisture content, crude protein, crude fat, fibre, ash and carbohydrate contents of the flours obtained was carried out. The fermented samples of the wet- and dry-milled flours retained the highest nutrients compared with the soaked and steamed samples. However, the fermented dry-milled flour had the highest crude protein (5.83-6.98 %), crude fat (0.55-2.21%), ash (3.75-4.29%), and carbohydrate (83.75-87.62%), which made it the most acceptable of the samples. The milling methods (wet and dry) had significant effects (p≤0.05) on the proximate composition of the flour for the selected pretreatment methods (soaking, fermentation and steaming). Fermentation as a pretreatment method was therefore, recommended for better nutrient retention for cocoyam flour.

(1) Background: In recent years, an innovative approach has emerged in the field of toxicology for managing acute intoxications caused by lipophilic substances: intravenous lipid emulsions (ILE). Through numerous experiments and case reports, the efficacy of lipid emulsions in counteracting toxicities induced by lipophilic agents, including a significant number of antiepileptic drugs (AE), has become increasingly evident. (2) Methods: Data spanning a 10-year period (2010-2020) was analyzed by searching through multiple scientific publication platforms like PubMed, Science Direct, Research Gate, and Springer Link. The study focused on reviewing relevant case reports detailing successful Intravenous lipid emulsion (ILE) administration in pa-tients with acute intoxications with antiepileptics, specifically examining the impact of fat emul-sions on neurological status, Glasgow Coma Scale (GCS) scores, and corrected QT interval con-cerning hemodynamic instability. (3) Results: The typical symptoms of antiepileptic toxicity in-clude central nervous system depression, ataxia, and nystagmus. Intravenous lipid emulsion ap-plication resulted in an increase in Glasgow Coma Scale scores and enhanced recovery from drug intoxication. (4) Conclusions: This study provides a comprehensive overview of the potential utility of ILE as a component to antidote therapy in cases of acute AE poisoning involving neurotropic drugs. The process involves the engagement of various mechanisms of antitoxic activity.

The aim of this paper is to investigate whether multifractal analysis can be applied to study choroidal blood vessels and help ophthalmologists for the early diagnosis of retinitis pigmentosa (RP). In a case study, we use Spectral Domain Optical Coherence Tomography (SDOCT), which is a non-invasive and highly sensitive imaging technique of the retina and choroid. The image of a choroidal branching pattern can be regarded as a multifractal. Therefore, we calculate generalized Renyi point-centered dimensions, which is considered a measure of inhomogeneity of data, to prove that it increases in the patients with RP with respect to the control group.

A pump station is a very important flood control facility for mitigating inundation of urban lowland areas. It is not easy to secure a site to increase the capacity of a pump station in an urban area because of various limitations or to maximize the discharge capacity of the pump sump. Adding a facility to improve the pump capacity of a pump station may affect the flow characteristics, such as unexpected increases in the flow velocity and vorticity, and cause severe problems with operating the pump station. To solve those problems, anti-vortex devices (AVDs) have been developed and adopted for appropriate design standards. The Korean design criteria for AVDs are based on experience and foreign standards because not enough data on the AVD are available. In this study, the flow in the sump was numerically simulated at various AVD heights to collect information on improving the design and efficiency of a pump station. Consequently, an appropriate height for the AVD and changes in the flow pattern and vortex in the pump sump were determined and compared with 12 cases of inflow conditions with respect to the vertical location.

Bacteremia and fungemia are significant causes of morbidity and mortality which frequently occur as co-infections with viral respiratory infections including SARS-CoV-2. It was aimed to evaluate the microorganisms isolated from blood cultures of SARS-CoV-2 positive and negative patients and investigate their antimicrobial resistance patterns. A retrospective analysis was performed with the total number of 22,944 blood cultures sent to the laboratory between November 2020 and December 2021. Blood cultures were performed on the BD Bactec automated system. Identification was performed using conventional methods, VITEK-2 and MALDI-TOF MS. Antibacterial/antifungal susceptibility tests were performed according to EUCAST/CLSI recommendations. SARS-CoV-2 tests were performed with RT-PCR. It was detected 1,630 culture positivity belonging to 652 patients. Totally 633 of 652 patients were tested for SARS-CoV-2; 118 (18.6%) were positive and 515 (81.3%) were negative. The bacteria and fungi isolated at the high-est rate in SARS-CoV-2 positive patients were methicillin-resistant coagulase negative staphylococci (MR-CoNS) (21.5%), Escherichia coli (12.4%), Klebsiella pneumoniae (12.4%), Candida albicans (1.65%) and Candida glabrata complex (1.65%); while in negative patients, E. coli (21.3%), MR-CoNS (13.5%), K. pneumoniae (12.05%), C. albicans (2.1%), Candida parapsilosis (1.1%) and Candida tropicalis (0.9%). The fact that the most common isolate was MR-CoNS in SARS-CoV-2 positive patients (p = 0.028); the detection of Acinetobacter baumannii was more frequent (p = 0.001) and the isolation of carbapenem-resistant K. pneumoniae was at a higher rate than in SARS-CoV-2 negative patients; also, the increase in multidrug-resistant strains indicate that healthcare-associated infec-tions should not be disregarded while focusing on the outbreak.

Introduction: The development of effective vaccines has partially mitigated the trend of the SARS-CoV-2 pandemic, however, the need for orally available antiviral drugs persists. This study aims to investigate the activity of molnupiravir in combination with nirmatrelvir or GC376 on SARS-CoV-2 to verify the synergistic effect. Methods: The SARS-CoV-2 strains 20A.EU, BA.1 and BA.2 were used to infect Vero E6 in presence of antiviral compounds alone or in combinations using 5 two-fold serial dilution of compound concentrations ≤EC90. After 48 and 72 h post-infection, viability was performed using MTT reduction assay. Supernatants were collected for plaque-assay titration. All experiments were conducted three times and in triplicate. The synergistic score was calculated using Synergy Finder version 2. Results: All compounds reached micromolar EC90. Molnupiravir and GC376 showed a synergistic activity at 48 h with an HSA score of 19.33 (p<0.0001) and an additive activity at 72 h with an HSA score of 8.61 (p<0.0001). Molnupiravir and nirmatrelvir showed a synergistic activity both at 48 h and 72 h with an HSA score of 14.2 (p=0.01) and 13.08 (p<0.0001), respectively. Conclusion: Molnupiravir associated with one of the two protease-inhibitors nirmatrelvir and GC376 showed good additive-synergic activity in vitro.

Floods, recognized for their erratic behavior and devastating effects, are a significant threat as a natural disaster. In Brunei Darussalam, the impact of climate change is becoming increasingly evident through higher temperatures and an expected increase in annual rainfall (5.0mm per year from 2021 to 2050), highlighting the critical need for updated flood risk management techniques. In line with the climate resilience and adaptation objectives of WAWASAN 2035, this paper introduces an innovative approach—a cutting-edge flood risk management framework that utilizes the capabilities of big data analytics, sophisticated machine learning algorithms, and smart Internet of Things (IoT) sensors. Traditional methods, which rely on numerical and physical data modeling, often do not provide precise short-term flood forecasts. Our suggested framework uses machine learning to analyze real-time flood forecasting, sensor data and enhance warning systems, addressing the shortcomings of traditional approaches. The key advantage of this approach is its potential to drastically decrease flood-related damages, protect lives, and boost infrastructure resilience. This proposal is not only in aligns with Brunei's vision for a safe and climate-adaptable future but also marks a significant step forward in adopting innovative and sustainable flood risk management solutions amidst an evolving climate.

Recently two new degree concepts have been defined in graph theory: ev-degree and ve-degree. Also the ev-degree and ve-degree Zagreb and Randić indices have been defined very recently as parallel of the classical definitions of Zagreb and Randić indices. It was shown that ev-degree and ve-degree topological indices can be used as possible tools in QSPR researches . In this paper we define the ve-degree and ev-degree Narumi–Katayama indices, investigate the predicting power of these novel indices and extremal graphs with respect to these novel topological indices. Also we give some basic mathematical properties of ev-degree and ve-degree Narumi-Katayama and Zagreb indices.

In this paper, the ratio of gross agricultural production (GAP) and agricultural carbon emission is defined as agricultural carbon emission efficiency (ACEE). Considering rural labor transfer (RLT) increases the agricultural machinery intensity (AMI), the two are substitutes for each other and may interact with agricultural carbon emission efficiency (ACEE), we constructed a Simultaneous Equations Model (SEM) of ACEE, RLT and AMI, and analyzed the interaction mechanism of these three variables by using the Three-Stage Least Squares (3SLS) method to solve the endogeneity of the model. The following conclusions are drawn. First, RLT and AMI significantly promote the improvement of ACEE, while the improvement of ACEE and AMI further promotes RLT. Secondly, the causal relationship and influence mechanism of ACEE, RLT and AMI are interactive and multi-directional. An increase in AMI promotes ACEE, but an increase in ACEE inhibits an increase in AMI, suggesting that the marginal rate of substitution of machinery for labor is decreasing. Finally, China has significant regional heterogeneity. Labor transfer and machinery are only direct factors in increasing ACEE, while factors such as economic base, technology level and farmers' attitudes provide environmental support for the effective improvement of ACEE.

This study introduces a novel method for early prediction of Kimchi cabbage (Brassica rapa subsp. pekinensis (Lour.) Hanelt) height, utilizing drone imagery and a long short-term memory (LSTM) model. The research was conducted on a testbed at the National Institute of Agricultural Sciences (NAS) in South Korea, encompassing two distinct soil types (loam and sandy loam) to investigate their impact on growth. High-resolution drone images were captured throughout the growing season to generate a canopy height model (CHM) for estimating plant height at various stages. Missing height data were interpolated using a logistic growth curve, and an LSTM model was trained on this data to predict the final height of Kimchi cabbage at harvest. Three LSTM models were developed using time-series data collected at 29, 36, and 44 days after planting (DAP). The model trained on data from DAP 44 demonstrated the highest accuracy with a coefficient of determination (R²) of 0.83, a mean absolute error (MAE) of 2.48 cm, and a root mean square error (RMSE) of 3.26 cm, outperforming models trained on earlier data. Color-coded maps were generated to visualize the spatial distribution of predicted Kimchi cabbage heights, revealing variations in growth patterns across the testbed and confirming the model's potential for site-specific management. Considering the trade-off between accuracy and prediction timing, the model trained on DAP 36 data (MAE = 2.77 cm) was deemed optimal for informing cultivation management decisions. This research demonstrates the feasibility and effectiveness of integrating drone imagery, logistic growth curves, and LSTM models for early and accurate prediction of Kimchi cabbage height. The proposed technology enables data-driven decision-making for farmers, facilitating timely interventions based on predicted growth patterns. This could lead to improved crop yields, resource optimization, and a more sustainable agricultural future. Future research will focus on refining the model's accuracy and exploring its applicability to other crops, further expanding the potential of precision agriculture technologies.

This study analyzed the risk of falls in the elderly and the safety of the environment in a teaching hospital in Brazil. The Morse Falls Scale was used to stratify the risk of falls in 45 hospitalized elderly individuals, and a checklist was used to analyze the hospital environment. The analysis was based on the chi-square test and multiple regression. The moderate risk of falls was predominant (51.1%). The variable age group (p-value = 0.024) showed statistical evidence of association with the risk of falls. However, the multiple regression analysis showed no difference between the age groups and the risk situation for falls. The hospital wards showed an adequate arrangement of furniture, but some aspects had inadequacies, such as objects in the corridors, non-functional bells in some beds, and inadequacy of the toilet bowls in terms of the recommended height, the absence of non-slip flooring and the support bar in some bathrooms. In conclusion, the moderate risk of falls among the elderly and the adequacy of the hospital environment to technical standards were evident, with the exception of failures in the emergency communication system and sanitary installation.

Global navigation satellite system (GNSS) array antenna receivers are widely used to suppress wideband interference in navigation countermeasures. However, existing array antenna receivers all adopt digital array structure and digital beamforming technique, and it has limited analog-front-end (AFE) dynamic range. In strong interference scenarios, AFE saturation will occur, which limits the maximum interference suppression ability of the array receiver. Aiming at this issue, this paper proposes a robust wideband interference suppression method for GNSS array antenna receivers based on hybrid beamforming technique. Firstly, a novel fully connected hybrid array receiver structure is proposed; Secondly, the corresponding hybrid beamforming method is proposed at the same time, and it realizes the complete elimination of strong interference by jointly suppression in analog domain and digital domain. After mathematical simulation experiments, it is verified that compared to the digital beamforming-based anti-jamming technique, the proposed method can effectively suppress strong wideband interference, and the maximum interference suppression ability is improved by 36 dB.

There are various modeling techniques adopted for predicting the labor productivity that incorporate the influence of various factors, but neural networks are found to have strong pattern recognition and higher accuracy to get reliable estimates. To develop a construction labor productivity (CLP) model for concreting activities, data were collected through a questionnaire. The most critical influencing parameters were ranked according to their relative importance index (RII). Then the strength of the relationship between CLP and influencing parameters was analyzed using correlation coefficient results generated in Python program. Finally, the CLP model which represents the output of the crew within a certain factor was successfully developed using artificial neural networks (ANNs). Five objectives and six subjective critical influencing parameters were selected using RII. Crew experience, age of workers, and placement technique are the top three influencing parameters that have a strong relation with CLP with correlation coefficient values of 0.5681, 0.5349, and 0.5227 respectively. The developed model within these influencing parameters has a higher capability to predict the output of labor with a 92% coefficient of determination (R2) and a mean squared error of 0.316%. Therefore, the application of such a model for the accurate estimation of labor productivity is recommended.

The Internet of Things (IoT) is a concept based on the integration of various devices and methods of communication to exchange information in order to contribute to the improvement of everyday life, business and environment. This paper focuses on the establishment of a modern Internet of Things platform to ensure secure collection, processing and storage of data, under unexpected events. This platform establishes reliable connectivity which enhance system uptime; the key to success when implementing an IoT strategy. For this purpose, we proposed a hybrid approach combining different connectivity technologies to ensure the availability and smooth operation of the system and the prevention of data loss in unforeseen cases.

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density.

(1) Background: donor-derived circulating free DNA (dd-cfDNA) is an innovative biomarker with great potential for the early identification and prevention of graft damage; (2) Methods: Prospective study to analyze dd-cfDNA plasma levels in 30 kidney transplant patients during their post-transplant follow-up (15 days, 3, 6 and 9 months), to determine if the result could be of interest in the identification of possible adverse events, specially allograft rejection. In addition, the aim is also to verify the obtained data on sensitivity, specificity, NPV and PPV; (3) Results: Plasma levels of dd-cfDNA could be considered a novel biomarker of graft rejection after first term post-transplant up to several months before its clinical presentation, mainly in TCMR or ABMR. In this study, it appears to have no positive predictive value for borderline rejection or TCMR IA. Our results show a low NPV of the technique because other pathologies or biological post-transplant complications can also affect dd-cfDNA levels and they must be considered in the interpretation of the result.; (4) Conclusions: dd cfDNA could allow, together with other additional biomarkers in the context of a future score, avoid invasive biopsies in most cases, mainly in the case of suspected TCMR or ABMR.

The dimensional effect of the accumulation of an electric charge with a density of up to 270 μF/g by the system of compacted zirconium dioxide nanoparticles during exposure in an electric field (5000 V/m) under normal physical conditions is determined. Based on a qualitative complex analysis of the forms of appearance of the effect, it is shown that the place of localization of different charge carriers is the surface of nanoparticles. The supposed mechanism of this effect is considered using the theory of dispersed systems, the band theory, and the theory of contact phenomena in semiconductors. It was concluded that this mechanism is due to the phenomenon of localization of electron-type charge nanoparticles in the near-surface zone of the material in contact with the adsorption ion atmosphere. This effect is relevant for modern nanoelectronics, microsystem technology, and printed electronics.

This article considers the concepts of sustainability and sustainable development in relation to disaster risk reduction and climate change adaptation. We conceptualize sustainability from a social systemic perspective, that is, from a perspective that encompasses the multiple functionalities of a social system and their interrelationships in particular environmental contexts. The systems perspective is applied in our consideration and analysis of disaster risk reduction (DRR), climate change adaptation (CCA), and sustainable development (SD). Section 1 introduces briefly sustainability and sustainable development, followed by a brief presentation of the theory of complex social systems (Section 2). The theory conceptualizes interdependent subsystems, their multiple functionalities, and the agential and systemic responses to internal and external stressors on a social system. Section 3 considers disaster risk reduction (DRR) and climate change adaptation (CCA), emerging in response to one or more systemic stressors. It illustrates these with disaster risk reduction in the cases of food and chemical security regulation in the EU. CCA is illustrated by initiatives and developments on the island of Gotland, Sweden and in the Gothenburg Metropolitan area, which go beyond a limited CCA perspective, taking into account long-term sustainability issues. Section 4 discusses the limitations of DRR and CCA, not only their technical limitations but economic, socio-cultural, and political limitations, as informed from a sustainability perspective. It is argued that DRRs are only partial subsystems and must be considered and assessed in the context of a more encompassing systemic perspective. Part of the discussion is focused on the distinction between sustainable and non-sustainable DRRs and CCAs. Section 5 presents a few concluding remarks about the importance of a systemic perspective in analyzing DRR and CCA as well as other similar subsystems in terms of sustainable development.

A supply chain management (SCM) system is a strategic cooperative that organically integrates all supply chains to improve the performance of a company. The greatest critical success factor of SCM is partnership. Without cooperation between companies, SCM performance is limited. Does this imply, therefore, that companies within the supply chain can achieve mutual transactions equally? If the power between companies is unequal, how does this affect their partnership? The focus of this study is to assess whether power types enhance SCM performance through partnerships. We categorize power types as mediated and non-mediated. Mediated power is categorized based on coercion, reward, and legitimate, while non-mediated power is categorized based on information, expert, and reference. Therefore, this study examines how power types form a causal partnership relationship within the supply chain, and performs an empirical investigation on how the partnerships influence SCM performance.

Understanding complex biological processes of cells in culture, particularly those related to metabolism, can be biased by culture conditions, since the choice of energy substrate impacts all main metabolic pathways. When glucose is replaced by galactose cells decrease their glycolytic flux, working as an in vitro model of limited nutrient availability. However, the effect of these changes on related physiological processes such as REDOX control is not well documented, particularly in endothelial cells where mitochondrial oxidation is considered to be low. We evaluated the differences in mitochondrial dynamics and function in endothelial cells exposed to galactose or glucose culture medium. We observed that cells maintained in galactose-containing medium show higher mitochondrial oxidative capacity, more fused mitochondrial network, and higher intercellular coupling. These factors are documented to impact the cellular response to oxidative stress. Therefore, we analyzed the levels of two main REDOX regulators and found that Bovine Aortic Endothelial Cells (BAEC) in galactose media had higher levels of FOXO3 and lower levels of Nrf2 than those with glucose in the media. Thus, culture of endothelial cells in galactose containing medium may provide a more suitable condition to study in vitro mitochondrial related processes than glucose media, and deeply influence REDOX signaling in these cells.

Metabolomics profiling for accurate and reliable quantification of organic acids that carry a carboxylic acid functional group in complex biological samples, remains a major analytical challenge in clinical chemistry research. Several procedural barriers associated with quantification of clinically important carboxylic containing metabolites (CCMs) including spontaneous decarboxylation during ionization, poor chromatographic resolution, and retention on a reverse-phase column, limit the sensitivity, specificity, and reproducibility of multiple-reaction monitoring (MRM) based LC-MS assay development. We report a targeted metabolomics-based analytical method for the quantification of CCMs using phenylenediamine derivatization. Accurate and sensitive quantification of CCMs is successfully demonstrated in an array of biological matrices. Recovery of metabolites from different matrices (plasma, serum, urine, saliva, tissues, and cell extracts), ranged from 90% to 105%, with all the CVs ≤ 10%. The method showed linearity over a broad dynamic range from 0.1 ng/mL to 10 µg/mL with linear regression coefficients of 0.99 for most of the metabolites tested herein, that covers broad-based applicability with the analysis of biological samples. In most cases the LODs were as low as 0.01 ng/mL. The phenylenediamine-based derivatization of carboxyl acid library consisting of more than 70 endogenous metabolites was constructed for metabolite identification, which spanned more than 40 biological pathways. The library included a wide-variety of structurally variant CCMs such as amino acids/conjugates, short to medium chain organic acids, di/tri-carboxylic acids/conjugates, fatty acids and some ring-containing CCMs. We compared the CCMs profiles of pancreatic cancer cells with normal pancreatic epithelial cells to test and validate the biological utility of this method. The comparative profiling between cancerous and normal cells resulted in the identification of potential biomarkers in pancreatic cancer, and their correlation with several key metabolic pathways such as central carbon energy metabolism, protein metabolism, including TCA cycle, glycolysis, Gln-Glu pathway, and biosynthesis of amino acids and unsaturated fatty acids was established. The method, described herein, for the first time enables the sensitive and highly specific quantification of CCMs on small sample size with high reproducibility in a high throughput manner. Given the biological and functional significance of this class of metabolites, this mass spectrometry based targeted quantitative assay, fills an important gap and is likely to support a wide range of applications for basic, clinical, and translational research.

This paper presents the formative assessment to implement mobile portable chest X-ray (PDX) machines for Tuberculosis (TB) contact tracing in Oyo and Osun States, Nigeria. This descriptive qualitative study was carried out in 8 Local Government Areas, and 24 FGDs and 33 KIIs were conducted using a 4-stage sampling technique to select participants. Validated transcribed notes were entered and analysed using Nvivo. The respondents' ages ranged from 17-85 years, with a mean age of 42.08±14.9 years, and 4.0% had a postgraduate degree. The majority of the government officials stated that deploying the PDX machine intervention at the community level is the best means as it offers a level of convenience to the community members in the sense that there will be limited disruption to their daily activities as well as zero concerns about the cost of transportation to the health facility. The portable X-ray machine intervention should be implemented at the community level for contact tracing to allow more TB contacts living with the index patient to be screened. However, the PDX machine can also be set up in a special location, and the TB contacts can be invited for the screening.

Cirina forda caterpillars are a significant protein source in Central Africa, yet their preservation and consumption pose challenges. This study investigates the drying of Cirina forda caterpillars to enhance preservation methods and product quality. Caterpillars were subjected to drying experiments at temperatures ranging from 40°C to 70°C, using tunnel and oven dryers. The drying kinetics was analyzed using mathematical models, revealing a water diffusion-limited mechanism in all the tested conditions. The Newton model provided adequate estimations of the drying behavior, facilitating further practical dryer design. Shrinkage analysis indicated a two-step process independent of the drying conditions. Achieving a moisture content suitable for prolonged storage resulted in substantial volume loss, highlighting the challenges of preserving dried caterpillars. These findings shed light on how to optimize drying processes for Cirina forda caterpillars, crucial for sustaining protein sources in Central Africa.

In this study we were interested in the behaviors of individuals who preserve the social and organizational environment by ensuring sustainability. More specifically we are interested in allegiants behaviors. Numerous studies have highlighted the normative character of allegiance. To confer an object the status of social norm means to assign value (in terms of desirability and utility) to that object. Therefore we questioned the value attributed to allegiance. 170 employees were questioned on the desirability and utility they attribute to a future work colleague (future peer or future subordinate) starting from the answers the latter was supposed to have given to a questionnaire on allegiance. It was observed that desirability and utility make reference to two independent dimensions, utility being often more important. It was also noted there is greater severity assigned to endo-group targets (future peers) than to exo-group targets (future subordinates). Finally, it was noted there was not so much a valuation of allegiant targets, but rather a rejection of rebel targets, which raises the question of the bi-dimensionality of the valuation-devaluation process.

Adult T-cell leukemia (ATL) is an aggressive hematologic disease caused by human T-cell leukemia virus type 1 (HTLV-1) infection. Various animal models of HTLV-1 infection/ATL have been established to elucidate the pathogenesis of ATL and develop appropriate treatments. For analyses employing murine models, transgenic and immunodeficient mice are used because of the low infectivity of HTLV-1 in mice. HTLV-1 Tax and HBZ transgenic mice spontaneously develop tumors, and roles for both Tax and HBZ in cell transformation and tumor growth have been established. Severely immunodeficient mice were able to engraft ATL cell lines and have been used in preclinical studies of candidate molecules for the treatment of ATL. HTLV-1-infected humanized mice with an established human immune system are a suitable model to characterize cells in the early stages of HTLV-1 infection. This review outlines the characteristics of mouse models of HTLV-1 infection/ATL and describes progress made in elucidating the pathogenesis of ATL and developing related therapies using these mice.

Diabetes may cause an increase blood levels of cytokines inducing a rising of C reactive protein (PCR) and fibrinogen stimulating a subclinical inflammation which lead to adhesive molecules expression and to endothelial disfunction. A comprehensive panel of type 1 diabetes mellitus (T1DM) interleukins polymorphisms is not provided yet. As chronic periodontitis (CP) is considered the sixth complication of DM, a clarification is needed about the inflammatory role managed by single nucleotides polymorphisms (SNPs). The goal of this review is to focus on the significant diversity of SNPs in T1DM patients with and without CP. After a digital search on PubMed and Scopus with reference to the last 5 years, 21 items were enrolled. Several ILs were analyzed. T1DM still needs to be thoroughly explored regarding the ILs polymorphisms panel, however the last 5 years have led to the increased independence of this condition, causing autonomous inflammatory effects which requires further investigations. CP and T1DM association in children and adolescents represents a severe gap in literature that should be filled, the scarce presence of studies also about adults serves as a motivation for ulterior clinical researches

Currently SARS-CoV-2 is spreading around the world as an Omicron strain. Recently, the Omicron variants (BQ.1 and BQ.1.1) were identified as novel Variants of Concern. UpToDate, there is little information about the Omicron Variants BQ.1 and BQ.1.1. The widely altered Omicron variants are spread globally, providing a high risk of infection surges with devastating consequences in some areas. The Omicron type of SARS-CoV-2 has a harm risk of reinfection, according to early reported findings. COVID-19 Variants particularly, BQ.1 and BQ.1.1 have gained global attention and caused a worldwide sensation since their discovery. Therefore, this communication discusses the present status of COVID-19 Variants BQ.1 and BQ.1.1, and their consequences.

1) This study describes the good evolution of a 6-year-old girl genetically diagnosed with Rett syndrome (RTT), after having been treated with IGF-1, MT (MT), blackcurrant extracts (BC), and rehabilitation during 6 months. 2) The patient stopped her normal development from the first year of age. The patient showed low weight and height and met the main criteria for typical RTT. Curiously, there was pubic hair (Tanner II), very high plasma testosterone, despite low gonadotropins. No adrenal enzymatic deficits existed, and ultrasound abdominal studies were normal. Treatment consisted in IGF-1 (0.04 mg/kg/day, 5/week, sc) during 3-months and then 15-days resting, MT (50 mg/day, orally, uninterruptedly) and neurorehabilitation. The new blood tests were absolutely normal and the pubic hair disappeared. Then, a new treatment with IGF-1, MT, and BC started for another 3 months. After it, pubic Tanner stage increased to III, without a known cause. 3) The treatment followed led to clear improvements in most of the initial impairments, perhaps because of the effect of IGF-I, the antioxidant effects of MT and BC, and the increase in cyclic-glycine-proline (cGP) after BC administration. 4) A continuous treatment with IGF-1, MT and BC may recover most of the neurologic disabilities that occur in RTT.

BACKGROUND: Distal junctional kyphosis (DJK) remains a primary concern for surgeons performing cervical deformity (CD) surgery. Many times post-operative complications from CD surgeries render patients with worse recovery profiles than their peers. It is important to understand DJK recovery profiles following CD surgery patients. PURPOSE: To identify if DJK patients successfully recover from treatment/reoperation STUDY DESIGN/SETTING: Retrospective review of prospectively collected database PATIENT SAMPLE: 113 CD patients OUTCOME MEASURES: CD, HRQL, DJK, Recovery kinetics METHODS: CD patients with available BL and 2Y follow-up data. DJK angle (DJKA) was defined as >10° change in kyphosis between LIV and LIV-2, and a >10° index angle. Patients were stratified into two groups: 1) those who developed DJK by 3M and 2) those that did not develop DJK. Patients who developed DJK beyond 3M were excluded from the study. Means comparison tests analyzed differences in demographic, surgical, radiographic, and health related quality of life (HRQL) scores. Normalized HRQL scores at 3M and follow-up intervals (6M, 1Y, 2Y) were generated. Regression analysis assessed patient reported outcomes adjusting for baseline and surgical characteristics. RESULTS: 113 patients were included (17 DJK, 96 no DJK). Age (60.3 vs 62.2), gender (F: 71.0% vs 61.0%), BMI (27.0 vs 28.3), CCI (0.77 vs 0.98), OpTime (484.0 vs 556.5min), EBL (1028.3 vs 843.9mL), and presenting neurologic symptoms (70.6% vs 76.0%) were similar between groups (P > .05). DJK patients were more sagittally-malaligned preop (cervical sagittal vertical axis {cSVA}: 59.0 vs 43.9); had more osteotomies (76.5% vs 49.0%), and underwent more combined approaches (64.7% vs 26.0%), all p < .05. Posterior approaches, decompressions, and levels fused were similar between groups (p > .05). Following surgery, rate of complications and neurologic symptoms were similar between groups, except DJK patients experienced more dysphagia (17.7% vs 4.2%; p=0.034). DJK patients remained more malaligned in cSVA through 2-yr follow-up (p < .05). DJK patients exhibited worse reported outcomes from 3M to 1Y (p < .05), but these differences subsided when following patients through to 2Y: worse NDI (65.3 vs 35.3) and EQ5D (0.68 vs 0.79) scores at 1Y (both P

High-power laser facilities necessitate predicting incremental damage to final optics to identify evolving damage trends. In this study, we propose a surface damage detection method utilizing image segmentation employing ResNet-18, and a damage area estimation network employing U-Net++. Paired sets of online and offline images of optics obtained from a large laser facility is used to train the network. The trends of varying damage could be identified by incorporating additional experimental parameters. A key advantage of the proposed method is that the network can be trained end-to-end on small samples, eliminating the need for manual labeling or feature extraction. The software developed based on these models can facilitate the daily inspection and maintenance of optics in large laser facilities.

Background: Pre-pregnancy overweight and obesity of women of childbearing ages, has alarmingly a growing trend in developed countries. This study aimed to evaluate potential associations between maternal pre-pregnancy excess body weight and childhood demographic and anthropometric characteristics, as well as perinatal and postnatal outcomes. Methods: This is a cross-sectional study conducted on 5198 pre-school children aged 2-5 years old and their matched mothers that were enrolled from nine different Greek regions. Maternal and childhood anthropometric and demographic data, perinatal and postnatal outcomes were collected from medical history records or validated questionnaires. Results: A prevalence of 24.4% and 30.6% of overweight/obesity was recorded for the enrolled children and their mothers 2-5 years postpartum. In multivariate analysis, childhood overweight and obesity was significantly more frequently observed when maternal pre-pregnancy BMI status was overweight or obese [OR: 2.11 (1.80-2.42) p=0.0001]. A high prevalence of caesarean section delivery and childhood diabetes type I was also significantly associated with maternal pre-pregnancy overweight/obesity [OR:1.71 (1.33-2.19) p=0.0175) and OR: 1.27 (1.04-1.53) p=0.0014, respectively]. Conclusions: Maternal pre-pregnancy overweight and obesity rates were related with increased childhood weight status at birth and 2-5 years postpartum, highlighting the necessity of encouraging healthy lifestyle promotion, including healthier nutritional habits, and focusing on obesity population policies and nutritional interventions among women of reproducible age.

This review systematically examines the progression of the You Only Look Once (YOLO) object detection algorithms from YOLOv1 to the recently unveiled YOLOv10. Employing a reverse chronological analysis, this study examines the advancements introduced by YOLO algorithms, beginning with YOLOv10 and progressing through YOLOv9, YOLOv8, and subsequent versions to explore each version's contributions to enhancing speed, accuracy, and computational efficiency in real-time object detection. The study highlights the transformative impact of YOLO across five critical application areas: automotive safety, healthcare, industrial manufacturing, surveillance, and agriculture. By detailing the incremental technological advancements that each iteration brought, this review not only chronicles the evolution of YOLO but also discusses the challenges and limitations observed in each earlier versions. The evolution signifies a path towards integrating YOLO with multimodal, context-aware, and General Artificial Intelligence (AGI) systems for the next YOLO decade, promising significant implications for future developments in AI-driven applications.

Transformation formula under the action of a general linear fractional transformation for generalized Dedekind eta-function has been a subject of intensive study, Rademacher, Dieter, Meyer et al. However, the (Hecke) modular relation structure has not been recognized until the work of Goldstein-de la Torre, and streamlining the classical proofs in the modular relation will reveal the meaning hidden in those works. Our main aim is to elucidate the works of these researchers in the context of modular relations.

Biosensors are smart devices that convert biochemical responses to electrical signals. Designing biosensor devices with high sensitivity and selectivity is of great interest because of their wide range of functional operations. However, the major obstacles in the practical application of biosensors are their binding affinity toward biomolecules and the conversion and amplification of the interaction to various signals such as electrical, optical, gravimetric, and electrochemical signals. Additionally, enhancement of sensitivity, limit of detection, time of response, reproducibility, and stability are considerable challenges when designing an efficient biosensor. In this regard, hybrid composites have high sensitivity, selectivity, thermal stability, and tunable electrical conductivities. The integration of phthalocyanines (Pcs) with conductive materials such as carbon nanomaterials or metal nanoparticles (MNPs) improves the electrochemical response, signal amplification, and stability of biosensors. This review explores recent advancements in hybrid Pcs for biomolecule detection. Herein, we discuss the synthetic strategies, material properties, working mechanisms, and integration methods for designing electrochemical biosensors. Finally, the challenges and future directions of hybrid Pc composites for biosensor applications are discussed.

Food insecurity is a multidimensional concept adequately challenging not only the complex operationalization effort but also judgments of who is food secure and who is not. This study aimed to assess the level of household food insecurity in the study area. Both probability and non-probability sampling procedures were employed to draw the 367 respondents, key informants, and focus group discussants. The Consolidated Approach for Reportig Indicators (CARI) console model was constructed with four indicators: Food consumption score, Food energy shortfall, Food expenditure share, and Livelihood asset depletion. Descriptive statistics was used to analyze data in the models. The CARI result revealed that 41.1%, 9.3%, 20.4% and 29.2% of households were food secure, marginally food secure, moderately food insecure and severely food insecure, respectively. The overall prevalence showed that 49.6% households were food insecure and 50.4% were food secure. Moreover, female-headed households and households living the Belg and CHV livelihood zones were more food insecure than their counterparts. The study concluded that the problem of food insecurity is pervasive in the study area in general and Belg and CHV livelihood zones, in particular. Therefore, more attention and intervention should be given by policymakers and concerned development partners to alleviate the problem.

Public transportation scheduling aims to optimize the allocation of transportation resources, enhance transportation efficiency, and increase passenger satisfaction, which is crucial for building a sustainable urban transportation system. As a complement to public transportation, shared bikes provide users with a solution for the last mile of travel, compensating for the lack of flexibility in public transportation and helping to improve its utilization rate. Due to the characteristics of shared bikes, such as peak usage periods in the morning and evening and significant fluctuations in demand across different areas, the optimization of shared bike dispatch can better meet user needs, thereby reducing vehicle vacancy rates and increasing operating revenue. Addressing this issue, this paper designs a comprehensive decision-making approach for spatio-temporal demand prediction and bike dispatch optimization. For demand prediction, we designed a T-GCN based bike demand prediction model. In terms of dispatch optimization, we considered factors such as dispatch capacity, distance restrictions, and dispatch costs, and designed an optimization solution based on genetic algorithms. Finally, this paper validates the approach using shared bike operating data, shows that T-GCN can effectively predict short-term demand for shared bikes. Meanwhile, the optimization model based on genetic algorithms provides a complete dispatch solution verifying the model’s effectiveness. The shared bike dispatch approach proposed in this paper, which combines demand prediction with resource scheduling. This scheme can also be extended to other transportation scheduling problems with uncertain demand, such as store replenishment delivery and intercity inventory dispatch.

In this study, we aim to evaluate how cyclodextrin molecules affect the hydrophilicity and selec-tivity of PVDF membrane. Herein, we prepared PVDF-PVP(1-x) β-CDx membranes, with x rang-ing from 0 to 1 wt%. The membranes were deeply characterized by means of X-ray diffraction (XRD), attenuated total reflectance infrared (ATR-IR), Raman spectroscopies, Thermal gravimet-ric analysis (TGA), Contact angle measurement (CA), scanning electron microscopy (SEM) and atomic force microscopy (AFM). The study unequivocally demonstrates the effectiveness of the addition of β-CD molecules on membranes' structural, morphological, and dielectric properties. Adding 0.25wt% β-CD enhanced hydrophilicity, with CA decreasing from 72.6° to 56° and roughness decreasing from 81 to 29 nm. The PVDF-PVP(1-x) β-CDx membranes were then fully characterized using electrochemical impedance spectroscopy (EIS) to determine their dielectric properties, which clearly showed that the presence of β-CD induced polarization of the mem-brane. The separation of various dyes with different sizes and charges was utilized. These dyes included methylene blue (MB, positive, 0.504 nm), methyl red (MR, neutral, 0.487 nm), rose Bengal (RB, negative, 0.588 nm), and brilliant blue (BB, negative, 0.798 nm). Based on our re-search, we found that the membrane's selectivity is determined by both exclusion factors (such as size and dielectric properties) and inclusion inside the β-CD cage. We found that using alpha-CD instead of beta-CD led to the disappearance of dye inclusion. These findings strongly sug-gest that β-CD molecules can be a viable solution for dye removal from wastewater.

Abstract: Background: In contrast to conventional definitions, the contemporary conceptualization of adulthood emphasizes psychological characteristics over sociodemographic milestones. Concurrently, there is a growing proposition that individuals' perceptions of adulthood exert a substantial influence on the mental well-being of adolescents and adults. However, empirical examination of this hypothesis has been notably limited to date. Method: This study applied some adulthood markers, and multiple mental health indices (including Well-being, Optimism, Alexithymia, Satisfaction with life, Goldberg's index of mental health, Dark triad, and dimensional personality disorders) to a community sample comprising 1772 individuals in Spain, spanning ages from 16 to 93 years. Results: The findings support the overarching hypothesis, as perceptions of adulthood exhibit significant associations with almost all measured mental health indices, especially with those conforming a factor of Negative emotions. These associations persist even after accounting for age and socioeconomic status, and in alignment with the psychological paradigm of adulthood, they demonstrate stability across different age cohorts. Conclusions: The study establishes that such perceptions of adulthood represent a modifiable factor contributing to positive mental health. The implications of these findings for the formulation of public policies aimed at promoting mental health in the context of adulthood are deliberated, as well as a number of future studies.

Introduction: Agricultural practices significantly influence soil microbial populations and physicochemical properties, which are crucial for crop growth and quality. This study aims to investigate the impact of different agrochemical applications on soil microbial dynamics, soil physicochemical properties, as well as yield and proximate properties of maize. Methods: Carefully gathered topsoil samples at depths ranging from 1 to 15 cm, were transported to Jimma University to cultivate maize. Over a period of up to 120 days, soil and maize samples were collected at specified days to analyze various parameters, including soil pH, microbial populations, as well as nutrient content both in soil and plants. The collected data was statistically analyzed using one-way ANOVA, with a significance level of p < 0.05. Results: The soil bacterial and fungal populations were measured on days 5, 10, 20, 40, 80, and 120. The highest total mesophilic bacterial count (TMBC) was measured in the pots containing compost (G) and the lowest in pots that received macronutrient fertilizers and glyphosates (B) (i.e. 91.8 x 105 and 13.13 x 105 cfu/g of soil, respectively). The highest total mesophilic fungal count (TMFC) was observed in pots containing glyphosates and compost (F) (i.e. 67.25 x 104 cfu/g soil) and again the lowest in pot treated with macronutrient fertilizers and glyphosate (B) (i.e. 3.23 x 104 cfu/g soil). Moreover, the pots treated with macronutrient fertilizers and glyphosate (B), macronutrient fertilizers (A), and micronutrient fertilizers (C) exhibited the lowest levels of Fe and Zn. Furthermore, the pots receiving macronutrient fertilizer combined with glyphosate (B), as well as those receiving macronutrient fertilizers (A) alone had the lowest concentrations of Mn and Cu micronutrients. Finally, in maize the lowest protein, fats, and carbohydrates (g/100g) were found in the pots treated with macronutrient fertilizer combined with glyphosate (B, 2.21 ± 0.2), micronutrient fertilizer (C, 8.57 ± 0.25), and glyphosates only (D, 57.34 ± 0.1). Maize treated with compost (G) showed the highest levels of Fe, Cu, and Zn, while macronutrient fertilizer combined with glyphosate (B) resulted in the lowest content of these micronutrients. Additionally, maize receiving micronutrient fertilizer (C) had the highest concentration of Mn, whereas those treated with glyphosates (D) had the lowest. Conclusions: Significant variations in soil’s mesophilic bacterial and fungal populations, micronutrient levels, and nutritional composition were observed, indicating treatment-related changes. Generally, treatment with micromineral fertilizer combined with glyphosate (B) seemed to deplete the soil while compost treatment improved. Compost-treated soils exhibited the highest mesophilic bacterial and fungal count, as well as Fe and Zn micronutrient concentrations. The use of agrochemicals also had a negative effect on maize yield quality. The fluctuations in the soil parameters underscore the multifaceted effects of agrochemical treatments.

Epigallocatechin gallate (EGCG), the principal catechin in green tea, exhibits diverse therapeutic properties. However, its clinical efficacy is hindered by poor stability and low bioavailability. This study investigated solid particle-in-oil-in-water (S/O/W) emulsions stabilized by whey protein isolate (WPI) and sodium caseinate (NaCas) as carriers to enhance the bioavailability and intestinal absorption of EGCG. Molecular docking revealed binding interactions between EGCG and these macromolecules. The emulsions exhibited high encapsulation efficiencies and augmented EGCG bioaccessibility by 64% compared to free EGCG in a simulated gastrointestinal digestion model. EGCG-loaded emulsions demonstrated minimal cytotoxicity towards Caco-2 cells and facilitated EGCG transport across the intestinal epithelial layer without compromising tight junction integrity. Notably, EGCG-loaded emulsions protected Caco-2 cells against oxidative stress by suppressing intracellular reactive oxygen species generation. The results demonstrate the potential of WPI- and NaCas-stabilized S/O/W emulsions to enhance the bioavailability, intestinal absorption, and bioactivity of EGCG, expanding its applications in functional foods and nutraceuticals.

Polycyclic aromatic hydrocarbons (PAHs) have been reported to cause oxidative stress in metabolic processes. This study aimed to evaluate the relationship between exposure to PAHs, including benzo[a]pyrene (BaP) and 1-nitropyrene (1-NP), in the atmosphere and oxidative stress levels in the human body. This study included 44 Korean adults who lived in Cheongju, South Korea. Atmospheric BaP and 1-NP concentrations and urinary 6-hydroxy-1-nitropyrene (6-OHNP), N-acetyl-1-aminopyrene (1-NAAP), and 1-hydroxypyrene (1-OHP) concentrations were measured. The oxidative stress level was assessed by measuring urinary thiobarbituric acid reactive substances (TBARS) and 8-hydroxydeoxyguanosine (8-OHdG) concentrations. Urinary TBARS and 6-OHNP concentrations significantly differed between winter and summer. BaP exposure was significantly associated with urinary 8-OHdG concentrations in summer. However, atmospheric 1-NP did not show a significant correlation with oxidative stress marker concentrations. Urinary 1-NAAP concentration was a significant determinant for urinary 8-OHdG concentration in summer. Oxidative stress in the body increases in proportion to inhalation exposure to BaP, and more 8-OHdG is produced in the body as the amount of 1-NP, which is metabolized to 1-AP or 1-NAAP, increases.

In the past decade, targeted therapies for solid tumors, including non-small cell lung cancer (NSCLC), have advanced significantly, offering tailored treatment options for patients. However, individuals without targetable mutations pose a clinical challenge, as they may not respond to standard treatments like immune-checkpoint inhibitors (ICIs) and novel targeted therapies. While the mechanism of action of ICIs seems promising, the lack of a robust response limits their widespread use. Although the expression levels of programmed death ligand 1 (PD-L1) on tumor cells are used to predict ICI response, identifying new biomarkers, particularly those associated with the tumor microenvironment (TME), is crucial to address this unmet need. Recently, inflammatory cytokines such as interleukin-1 beta (IL-1β) have emerged as a key area of focus and hold significant potential implications for future clinical practice. Combinatorial approaches of IL-1β inhibitors and ICIs may provide a potential therapeutic modality for NSCLC patients without targetable mutations. In this review, we discuss the role of IL-1β in NSCLC, its involvement in inflammatory pathways, and explore its potential role in the treatment of NSCLC.

Advanced-Differential Interferometric SAR (A-DInSAR) has been used to monitor surface deformations in open pit mines and tailings dams. In this paper, ground deformations have been detected on the area of the tailings Dam-I at the Córrego do Feijão Mine (Brumadinho, Brazil) before its catastrophic failure occurred on 25 January 2019. Two techniques optimized for different scattering models, SBAS (Small BAseline Subset) and PSI (Persistent Scatterer Interferometry), were used to perform the analysis based on 26 Sentinel-1B images in IW mode, acquired on descending orbits from 03 March 2018 to 22 January 2019. A WorldDEM DSM product was used to remove the topographic phase component. The results provided by both techniques showed a synoptic and informative view of the deformation process affecting the study area, with a detection of persistent trend of deformations on the top, middle and bottom sectors of the dam face until its collapse, as well as the expected natural settlements on the tailings. It is worth noting the detection of an acceleration in the displacement time-series for a short period near the failure. The maximum accumulated displacements detected along the downstream slope face were -39 mm (SBAS) and -48 mm (PSI). It is reasonable to consider that Sentinel-1 would provide decision makers complementary motion information to the in-situ monitoring system for risk assessment and for a better understanding of on-going instability phenomena affecting the tailings dam.

Organisational performance is a major concern for any company wishing to remain competitive in today's market. This is why many companies have begun to integrate digital technologies into their management systems. The aim of this article is to determine the contribution of digitisation to organisational performance management, through observations and analysis of a single case study of a company that has adopted a digital transformation project. It emerged that digital transformation makes a significant contribution to organisational performance management. However, this transformation requires significant support and adaptation of skills and organisational structures.

Photoplethysmography (PPG) signals, which measure blood volume changes through light absorption, are increasingly used for non-invasive Cardiovascular Disease (CVD) detection. Analyzing PPG signals can help identify irregular heart patterns and other indicators of CVD. This research involves a thorough analysis of CVD classification using the Capnobase dataset, which includes data from 20 CVD subjects and 21 normal subjects. In the initial stage, heuristic optimization algorithms, such as ABC-PSO, the Cuckoo Search algorithm (CSA), and the Dragonfly algorithm (DFA), were applied to reduce the dimension of the PPG data. Next, these Dimensionally Reduced (DR) PPG data are then fed into various classifiers such as Linear Regression(LR), Linear Regression with Bayesian Linear Discriminant Classifier (LR-BLDC), K-Nearest Neighbors (KNN), PCA-Firefly, Linear Discriminant Analysis (LDA), Kernel LDA (KLDA), Probabilistic LDA (ProbLDA), SVM-Linear, SVM-Polynomial, SVM-RBF, to identify CVD. Classifier performance is evaluated using Accuracy, Kappa, MCC, F1 Score, Good Detection Rate(GDR), Error rate, and Jaccard Index(JI). The SVM-RBF classifier for ABC PSO dimensionality reduced values outperforms other classifiers, achieving an accuracy of 95.12% with a MCC of 0.90.

The current economic and political crisis has brought about a change in the environment in which Non-Governmental Development Organizations (NGDOs) have traditionally operated. This change can be summed up as a reduction in the funds they receive and an increase in the population they must serve. The need then arises to have mechanisms that allow an analysis of the good work performed by the NGDOs. Knowing the efficiency of the NGDOs in the management of their previous projects can contribute towards improving their future achievements. The aim of this research is to establish some objective indicators that allow an evaluation of the efficiency of these organizations. Firstly, a detailed analysis of the regulation of the three Agencies is conducted (Spanish-AECID, European- EuropeAid and American -USAID). This allows us to synthesize the indicators of good performance of the NGDO based on the study of the eligibility criteria of public donors. The research concludes with the study of the efficiency following the Promethee Approach. Our results reveals that 44.6% of the NGDOs (33 out of the 74 studied) operate inefficiently, compared to 29.7% which are efficient.

Color distortion in an image poses a challenge for classification and regression when the input data consists of pictures. Because of that, a new algorithm for color standardization of photos is proposed, which serves as a base for a deep neural network regression model. This approach utilizes a custom color template, which was developed based on an initial series of studies and digital imaging. Using the equalized histogram of R, G, B channels from the digital template and its photo, a color mapping strategy is computed. By applying this approach, the histograms are adjusted, and the colors of photos taken with a smartphone are standardized. The proposed algorithm has been developed for a series of photos where the entire surface roughly maintains a uniform color, and the differences in color between the photographs of individual objects are minor. The optimized approach was validated in the colorimetric determination procedure of vitamin C. The dataset for deep neural network in the regression variant was formed from photos of samples under two separate lighting conditions. For the concentration range of vitamin C from 0 to 87.72 µg·mL-1, the RMSE for the test set ranged between 0.75 and 1.95 µg·mL-1, in comparison to the non-standardized variant, where this indicator was at the level of 1.48-2.29 µg·mL-1. The consistency of the predicted concentration results with actual data expressed using R2 was between 0.9956 and 0.9999, for each of the standardized variants. This approach allows for the removal of light reflections on the shiny surface of solutions, which is a common problem in liquid samples. The color matching algorithm has a universal character, and its application scope is not limited.

Disaster issue consultation is crucial for effective emergency management, requiring timely and accurate information to support decision-making processes. This paper explores the integration of large language models (LLMs) with advanced prompt engineering to enhance the performance of AI systems in disaster management. We propose a novel multi-round prompt engineering approach that guides LLMs to iteratively refine their responses based on evolving disaster scenarios. Our method leverages diverse disaster-related datasets and employs a combination of accuracy metrics and a customized GPT-4 scoring system for evaluation. We conduct comprehensive experiments across multiple LLM platforms, including Qwen2, ChatGPT, Claude, and GPT-4, comparing our approach with baseline models and the Tree of Thoughts (ToT) method. The results demonstrate significant improvements in both accuracy and response quality, highlighting the effectiveness of our method in providing contextually relevant and actionable insights. Additional analysis confirms the robustness and generalizability of our approach across various disaster scenarios, establishing it as a valuable tool for enhancing disaster management practices.

Suboptimal nutrition is a leading cause of cardiometabolic disease and mortality. Biological sex is a variable that can play a role in individual response to nutritional factors and may modulate the impact of nutrition on disease. This narrative review explores the intricate interplay between sex, nutrition, and health outcomes, and the consequent importance of considering sex in nutrition research, dietary recommendations, and disease management. We examine the impact of sex on how various dietary patterns, including the Mediterranean diet, macronutrient content and quality, Western diet, and energy restriction associate with or affect metabolic health and disease risk. Understanding how sex influences the response to the diet can inform precision nutrition interventions and approaches for disease prevention and management.

Minimal/mild endometriosis (MME) is independently associated with reduced fecundity rates. In this review article, we discuss the role of laparoscopic surgery in enhancing fertility outcomes of patients with MME. Laparoscopic management of MME enhances fecundity and increases chances of spontaneous conception in appropriately selected cases. However, laparoscopy cannot be routinely recommended in asymptomatic patients with the sole purpose of diagnosing and treating potentially present MME. Equally, based on existing evidence, laparoscopic management of MME cannot be routinely recommended prior to in-vitro fertilisation (IVF) attempts, as robust evidence of benefit is lacking. As an overlap between unexplained infertility and MME cases likely exists, the development of reliable, widely available, non-invasive tests for the diagnosis of MME may revolutionize the management of cases currently classified as unexplained infertility. In a disease as diverse as endometriosis, management decisions should be based on a multitude of factors. Future studies should focus on reporting outcomes of interventions for MME on fertility and obstetric outcomes, clearly differentiating between disease stages and phenotypes.

Discoloration of endodontically treated teeth poses a significant aesthetic concern for many individuals, impacting their confidence and self-image. Ceramic veneers have emerged as a popular solution for the aesthetic restoration of such teeth. This paper explores the role of ceramic veneers in addressing tooth discoloration, examining their efficacy, durability, and aesthetic outcomes, via a clinical case. Various factors influencing the selection of ceramic veneers as a treatment modality, including shade matching, preparation techniques, and adhesive bonding, are discussed. Additionally, advancements in materials and techniques have enhanced the versatility and aesthetic appeal of ceramic veneers, making them a valuable option for achieving natural-looking and durable aesthetic restorations in individuals with discolored endodontically treated teeth.

This research evaluates the technical and financial feasibility of using Inhibitor A for brine treatment in geothermal energy production, comparing it with traditional brine acidification. Conducted at a geothermal site in Central Java, Indonesia, the study uses Decision Tree Analysis and risk Expected Monetary Value (EMV) to assess both methods. Inhibitor A demonstrates a 70% reduction in scaling compared to untreated brine, with laboratory tests indicating a 10 ppm dosage as optimal for minimizing silica scaling. Despite higher initial costs, Decision Tree Analysis shows that Inhibitor A has a lower overall risk profile than acidification. EMV analysis confirms its cost-efficiency when considering potential risks and benefits. This research advocates for the adoption of Inhibitor A, highlighting its long-term benefits and sustainability over traditional methods. The findings emphasize the importance of innovative solutions in enhancing geothermal energy systems’ efficiency and sustainability. By integrating technical performance with financial analysis, this study provides a comprehensive evaluation to inform decision-making in the geothermal sector, promoting more effective and sustainable brine treatment practices.

Incorporating ChatGPT into the classroom has several benefits that improve the educational experience for both teachers and students. ChatGPT seems useful in preparing students for success in the digital age, from personalized learning and increased instructional content to fostering collaboration, enabling bilingual classrooms, and encouraging creativity. This review offers insights regarding the perks of using ChatGPT in education as a tool for students. Among the many benefits of implementing ChatGPT in the classroom are enhanced accessibility, enhanced personalized learning, development of critical thinking skills, administrative support for educators, promotion of collaborative learning, and preparedness for a technologically advanced future. These advantages demonstrate how AI technologies have the capacity to drastically change teaching strategies and outcomes. While problems remain, the benefits of integrating ChatGPT in teaching are enormous. By integrating AI technology, educators may develop more dynamic and individualized learning environments that respond to the demands of 21st-century learners.

We present a partition of quantum observables in an open quantum system which is inherited from the division of the underlying Hilbert space or configuration space. It is shown that this partition leads to the definition of an inhomogeneous continuity equation for generic, non-local observables. This formalism is employed to describe the local evolution of the von Neumann entropy of a system of independent quantum particles out of equilibrium. Crucially, we find that all local fluctuations in the entropy are governed by an entropy current operator, implying that the production of entanglement entropy is not measured by this partitioned entropy. For systems linearly perturbed from equilibrium, it is shown that this entropy current is equivalent to a heat current, provided that the system-reservoir coupling is partitioned symmetrically. Finally, we show that any other partition of the coupling leads directly to a divergence of the von Neumann entropy. Thus, we conclude that Hilbert-space partitioning is the only partition of the von Neumann entropy which is consistent with the Laws of Thermodynamics.

This paper is showing the results of a study focused on the occurrence of failures in heterogeneous structural materials, especially on the issue of modelling the formation and propagation of cracks. Attention is paid to the application of the finite element method to various types of materials in order to find critical parameters determining the behaviour of materials during the damage process. Application of damage mechanisms and approaches to modelling the origin of crack propagation by modifications in FEM systems are presented. Furthermore, some practical applications are tested. The main effort is devoted to composites and searching for procedures when using cohesion models for their more accurate modelling, especially near the stress concentrators, or before the crack tip. The use of the cohesive approach of elements that represent the physical nature of energy release in front of the crack front has proven to be promising not only in the direct use of cohesive elements, but also in combination with modified methods of standard finite elements. The authors of this article use their long-term experience in the given issue, which they consistently confront with developments in this area in recent years.

Emerging semiconductor devices often lack accurate analytical models. The same is usually true of any devices working under extreme conditions like cryogenic temperatures. The usual workaround involves the use of approximation models, usually based on lookup tables or neural networks individually fitted to measurement data. In the case of experimental devices or ones working under extreme conditions, the number of units available for measurement is limited. As a result, the number of approximation-model instances is too small to enable a statistical simulation of even middle-sized circuits, which is a necessary step in integrated-circuit design since it provides the realistic picture of the circuit’s behavior in the presence of manufacturing process variations. Approximation models using structure parameters as inputs do exist in the literature, but are only useful if the end user knows the statistical distributions of those parameters, which is not usually the case. We propose a technique based on generative machine learning, namely the variational autoencoder, that uses only a small sample of devices to capture the essential features of their I–V curves under process variations and subsequently generates an arbitrary number of similarly disturbed curves. The model trained on as few as 20 instances per device type is shown to precisely reproduce the distributions of period and power consumption of a ring oscillator.

The many limitations of implementing anticancer strategies under the term “precision oncology” have been extensively discussed. While some authors propose promising future directions, others are less optimistic and use phrases such as illusion, hype and false hypotheses. The reality is revealed by practicing clinicians and cancer patients in various online publications, one of which has stated that “in the quest for the next cancer cure, few researchers bother to look back at the graveyard of failed medicines to figure out what went wrong.” The message is clear: novel therapeutic strategies with catchy names (e.g., synthetic “lethality”) have not fulfilled their promises despite decades of extensive research and clinical trials. The main purpose of this review is to discuss key challenges in solid tumor therapy that surprisingly continue to be overlooked by the nomenclature committee on cell death and numerous other authors. These challenges include: the impact of chemotherapy-induced genome chaos (e.g., multinucleation) on resistance and relapse, oncogenic function of caspase 3, cancer cell anastasis (recovery from late stages of apoptosis), and pitfalls of ubiquitously used preclinical chemosensitivity assays (e.g., cell “viability” and tumor growth delay studies in live animals) that score such pro-survival responses as “lethal” events. Studies outline herein underscore the need for new direction in the management of solid tumors.

With the escalation of size and complexity of modern Denial of Service attacks, there is a need for research in the context of Machine Learning (ML) used in attack execution and defense against such attacks. This paper investigates the potential use of ML in generating behavioral telemetry data using Long-Short Term Memory network and spoofing requests for the analyzed traffic to look legitimate. For this research, a custom testing environment was built, that listens for mouse and keyboard events and analyzes them accordingly. While the economic feasibility of this attack currently limits its immediate threat, advancements in technology could make it more cost-effective for attackers in the future. Therefore, proactive development of countermeasures remains essential to mitigate potential risks and stay ahead of evolving attack methods.

Solar energetic particles (SEPs) are bursts of high-energy particles that originate from the Sun and can last for hours or even days. The aim of this study is to understand how the characteristics of energetic particles was affected by the characteristic parameters of corotating interaction regions (CIRs). In particular, the particle intensity distribution with time and space in different CIRs are studied. The propagation and acceleration of particles are described by the focused transport equation (FTE). We used a three-dimensional magnetohydrodynamic (MHD) model to simulate the background field including CIRs. By changing the inner boundary conditions, we constructed CIRs with different solar wind speeds, angles between the polar axis and rotation axis, and the azimuthal widths of the fast streams. Impulsive particles are injected at the inner boundary. We then study the SEPs in different backgrounds. The results show that the CIR widths are related to the solar wind speed, tilt angles, and the azimuthal widths of the fast stream. The acceleration of particles in the reverse and forward compression regions is mainly influenced by the solar wind speed difference and the slow solar wind speed, respectively. Particles with lower energy (sub-MeV) are more sensitive to the parameters of CIRs. Different CIR parameters also greatly affect the spatio-temporal distribution of particle intensities in different ways. These results indicate that, it is crucial to consider the conditions of large-scale structure in interplanetary space when studying or predicting energetic particles. Additionally, our findings provide empirical guidance for forecasting the characteristics of SEPs.

In breast cancer, epithelial-mesenchymal transition (EMT) is positively associated with programmed death ligand 1 (PD-L1) expression and immune escape, and TWIST1 induces EMT and cancer metastasis. However, how TWIST1 regulates PD-L1 and immune evasion is unknown. This study analyzed TWIST1 and PD-L1 expression in breast cancers, investigated the mechanism for TWIST1 to regulate PD-L1 transcription, and assessed the effects of TWIST1 and PD-L1 in cancer cells on the cytotoxicity of CD8+ effector T cells. Interestingly, TWIST1 expression is associated with high-level PD-L1 in triple negative breast cancers (TNBCs). Overexpression and knockdown of TWIST1 robustly upregulates and downregulate PD-L1 expression, respectively. TWIST1 binds to the PD-L1 promoter and recruits the TIP60 acetyltransferase complex in a BRD8-dependent manner to promote PD-L1 expression, which drives immune escape of breast cancer cells by accelerating the exhaustion of CD8+ T cells. Accordingly, knockdown of TWIST1 or BRD8 or blockade of PD-L1 with a PD-L1 antibody significantly enhances CD8+ T cells to inhibit breast cancer cell growth. These results demonstrate that TWIST1 directly induces PD-L1 expression in breast cancer cells to drive immune evasion. Targeting TWIST1, BRD8 or PD-L1 in TNBC should facilitate CD8+ T cell-mediated immune therapy. TWIST1 may also serve as a biomarker for anti-PD-L1 immunotherapy.

Sorghum-nematode interactions were previously purported to produce chemicals that confer pre-infectional nematode resistance to the infective second-stage juveniles (J2) of the root-knot (Meloidogyne species) nematodes in the rhizosphere, without any contact to J2 bodies. We tested the null hypothesis in four sorghum cultivars with a wide range of pre-infectional nematode resistance relative to the susceptible tomato cultivar. Post a 56-day exposure of Meloidogyne enterolobii, J2 from soil and root samples were subjected to step-wise fixative solutions and then mounted on slides. Length-related and diameter-related morphometrics were measured using an OMAX microscope – equipped with a digital measuring software. The study was conducted over two seasons and the seasonal interactions on morphometrics were not significant. Relative to the tomato cultivar, sorghum treatments generally increased the length-related morphometrics, but decreased the diameter-related variables in both soil J2 and root J2. The null hypothesis was therefore rejected in favour to the assumption that upon exposure of J2 bodies to botanical chemicals in both soil and root samples, with certain morphometrics being adjusted to ameliorate the potential damage of hydrostatic pressure on internal organs of the infective juveniles. In conclusion, in pre-infectional nematode resistance, J2 bridge chemicals in the rhizosphere and enter the root system, where chemicals still have effects on morphometrics of nematodes.

Cellular Technology came into existence in Japan in 1979. From that time, we have seen many advances in technology. Currently, most of the person uses either 4G or 5G, among which 5G is a newer technology. 4G network was the first network to use LTE. LTE stands for Long Term Evaluation. Most people get confused between 4G and LTE, they assume both to be the same. In reality, LTE has evolved on the 4G technology. It was first introduced in 2008 to provide higher efficiency and data rates to the cellular network. It was designed to evolve the performance of the networks which includes the evolution of hardware components, optimization of software, power and cost efficiency. This work presents a study on LTE, LTE-A and VoLTE technology. We also discussed about the several packet scheduling algorithms that are being used for transmission of packets. It brings out new opportunities for the researchers to work on increasing the efficiency of those algorithms by modifications.

Artistic image completion is fundamental for the preservation and restoration of invaluable art paintings and it has experienced significant progress through the implementation of deep learning methodologies. Despite these advancements, challenges persist, even with sophisticated approaches like Generative Adversarial Networks (GANs), particularly in achieving optimal results for high-resolution paintings. Small-scale texture synthesis and the inference of missing information from distant contexts present persistent issues, leading to distortions in lines and unnatural colors, especially in art paintings with complicated structures and textures. Concurrently, patch-based image synthesis has evolved by incorporating global optimization on the image pyramid to enhance structural coherence and details. However, methods relying on gradient-based synthesis encounter obstacles related to directionality, inconsistency, and the heavy computational burdens associated with solving the Poisson equation in non-integrable gradient fields. This paper introduces a groundbreaking approach, integrating Weighted Similarity-Confidence Laplacian Synthesis, to comprehensively address these challenges and advance the field of artistic image completion. This proposal addresses challenges not only in high-resolution artistic image completion but also makes a significant contribution to the broader field of patch-based synthesis by utilizing the Laplacian pyramid for enhanced edge-aware correspondence search. Experimental result confirms the effectiveness of our approach, offering promising outcomes for the preservation and restoration of art paintings with complicated details and irregular missing regions.

A general methodology for loan amortization under arbitrary discount functions is discussed. It is shown that it is always possible to uniquely define a scheme for constructing the loan amortization schedule with an arbitrary assigned discount function. It is also shown that even if the loan amortization is carried out from the sequence of principal payments and the sequence of accrued interest, the underlying discount function can be uniquely determined at the maturities corresponding to the installment payment dates. As a special case of the proposed approach, we derive the amortization method according to the law of simple interest.

The water resources policy under climate change impacts water security, which should ensure enough water of good quality for humans and nature. Integrated water management is the state-of-the-art policy support model that, after 20 years in use, failed to achieve in many countries its primary goal of water bodies' good ecological status. Here, we show that this is due to the substantial externalities the anthropocentric character of the model generates. From the historical analysis, three main results are obtained: 1) the nature-human interplay is always composed of the coexistence of two opposite behaviors of conflict and cooperation; 2) this contradiction is a dialectical, general ontological attribute; 3) on the balance of power between nature and humans, three clusters are identified: i) naturalistic; ii) dualistic; iii) anthropocentric. A novel behaviorist dialectical conflict resolution model can resolve the differences between stakeholders and natural laws. The harmonic symbiosis of humans with nature removes environmental externalities and can lead to sustainable water security. Three case studies from the literature illustrate the merits of the new dialectical model.

Intra Voxel Incoherent Motion (IVIM) imaging provides non-invasive perfusion measurements, eliminating the need for contrast agents. The aim of this work was to explore the feasibility of IVIM in whole brain perfusion studies, where isotropic 1mm voxel is widely accepted as a standard. This study treats on validity of time limited, precise, segmentation ready Whole Brain IVIM imaging protocol suitable for clinical reality. To assess the influence of SNR on the estimation of S0, f, D* and D IVIM parameters a series of measurements and simulations under MATLAB environment were performed for three estimation techniques, utilizing known “ground truth” and noised data. Scanner specific SNR was estimated based on healthy subject IVIM MRI study in 3T scanner. Measurements were conducted for 25,6x25,6x14,4 cm FOV with 256x256 in plane resolution and 72 slices resulting in 1x1x2 mm voxel size. Simulations were performed for 36 SNR levels around measured SNR value. Single voxel grid search estimation method mean relative error for S0 f D* D estimates at measured SNR level were: 5.00%,81.91%, 76.31%, 18.34% respectively. Analysis has shown that high resolution IVIM is possible, although there is significant variation in estimation accuracy and precision depending on SNR level and chosen estimation method.

Technology-enabled maintenance via sensors and the internet of things (IoT) technologies is seen as the “new maintenance strategy”. The aim is to use these technologies to focus on unnecessary breakdowns and increase levels of asset availability where the existing of a dedicated team to maintain or data on asset condition is limited, useless or full of noise. This paper presents the integration of various sensing nodes within an automated laser cutting machine for monitoring of critical components’ conditions. The integrated system provides a centralised platform for data collection from various sensors and provides early failure detection mechanism based on specified set points with alert mechanisms utilising a custom dashboard for data visualisation. The research highlights the required stages for the identification of the appropriate components and sensory devices for the development of efficient monitoring environment.

Hydraulic fracturing in shale gas reservoirs has usually resulted in complex fracture network. The results of micro-seismic monitoring showed that the nature and degree of fracture complexity must be clearly understood to optimize stimulation design and completion strategy. This is often called stimulated reservoir volume (SRV). In the oil & gas industry, stimulated reservoir volume has made the shale gas exploitation and development so successful, so it is a main technique in shale gas development. The successful exploitation and development of shale gas reservoir has mainly relied on some combined technologies such as horizontal drilling, multi-stage completions, innovative fracturing, and fracture mapping to engineer economic completions. Hydraulic fracturing with large volumes of proppant and fracturing fluids will not only create high conductivity primary fractures but also stimulate adjacent natural fractures. Fracture network forming around every hydraulic fracture yields a stimulated reservoir volume. A model of horizontal wells which was based on a shale gas reservoir after volume fracturing in China was established to analyze the effect of related parameters on the production of multi-fractured horizontal wells in this paper. The adsorbed gas in the shale gas reservoir is simulated by dissolved gas in the immobile oil. The key to simulate SRV is to accurately represent the hydraulic fractures and the induced complex natural fracture system. However, current numerical simulation methods, such as dual porosity modeling, discrete modeling, have the following limitations: 1) time-consuming to set up hydraulic and natural fracture system; 2) large computation time required. In this paper, the shape of the stimulated formation is described by an expanding ellipsoid. Simplified stimulated zones with higher permeability were used to model the hydraulic fracture and the induced complex natural fracture system. In other words, each primary fracture has an enhanced zone, namely SRV zone. This method saves much developing fine-grid time and computing time. Compared with the simulation results of fine-grid reference model, it has shown that this simplified model greatly decreases simulation time and provides accurate results. In order to analyze the impacts of related parameters on production, a series of simulation scenarios and corresponding production performance were designed. Optimal design and analyses of fracturing parameters and the formation parameters have been calculated in this model. Simulation results showed that the number of primary fractures, half length, SRV half-width and drop-down have great effects on the post-fracturing production. Formation anisotropies also control the production performance while the conductivity of the primary fractures and SRV permeability do not have much impact on production performance. The complexity of stimulated reservoir volume has strong effect on gas well productivity. Fracture number mainly affects the early time production performance. The increase of SRV width cannot enlarge the drainage area of the multi-fractured horizontal wells, but it can improve the recovery in its own drainage region. Permeability anisotropies have much effect on production rate, especially the late time production rate. The results prove that horizontal well with volume fracturing plays an irreplaceable role in the development of ultra-low permeability shale gas reservoir.

Transition metal dichalcogenides (TMDs) monolayers exhibit unique valleytronics properties due to the dependency of the coupled valley and spin state at the hexagonal corner of the first Brillouin zone. Precisely controlling valley spin-polarization via manipulating the electron population enables its application in valley-based memory or quantum technologies. This study uncovered the uncompensated spins of the antiferromagnetic oxide (NiO) serving as the ferromagnetic (FM) order to induce valley spin-polarization in molybdenum disulfide (MoS₂) monolayers via the magnetic proximity effect (MPE). A spin-resolved photoluminescence spectroscopy (SR-PL) was employed to observe MoS₂, where the spin-polarized trions appear to be responsible for the MPE, leading to a valley magnetism. Results indicate that local FM order from the uncompensated surface of NiO could successfully induce significant valley spin-polarization in MoS₂ with the depolarization temperature approximately at 100 K, which is relatively high compared to related literature. This study reveals new perspectives and potential of AFM materials in the field of exchange-coupled van der Waals heterostructures.

Kisspeptin, a key neuropeptide derived from the KISS1 gene, is renowned for its critical role in regulating the hypothalamic-pituitary-gonadal axis and reproductive hormone secretion. Beyond its primary function in reproductive biology, emerging research has illuminated its influence in various cancers, mediating significant effects through its interaction with the G-protein coupled receptor, Kisspeptin receptor. This interaction has been implicated in modulating cellular pro-cesses such as proliferation and metastasis, making it a potential target for therapeutic interven-tion. Our study initially screened ten kisspeptin-10 analogs through cytotoxic effects of kisspep-tin-10 (KP10) and its analogs in several cancer types, including cervical, prostate, breast, and gastric cancers, with a particular focus on cervical cancer where the most profound effects were observed. Further exploration using kinase array assays revealed that these analogs specifically alter key kinases involved in cancer progression. Migration assays demonstrated a substantial decrease in cell motility, and Bioluminiscence Resonance Energy Transfer assays confirmed these analogs strong interactions with the kisspeptin receptor. Overall, our results indicate that these KP10 analogs not only hinder cervical cancer cell proliferation but also curtail migration through targeted modulation of kinase signaling, suggesting their potential as therapeutic ayfgents in managing cervical cancer progression. This comprehensive approach underscores the therapeutic promise of exploiting kisspeptin signaling in cancer treatment strategies.

This study utilises NaOH to treat composite cementitious materials containing aeolian sand and zeolite powders, which were used to replace 50% of the cement in aeolian-sand concrete (ASC). The mechanical properties of treated ASC considerably improved, especially when the NaOH dosage was 4% by mass. After curing this sample (denoted as AAZC-4) for 28 d, its compressive strength improved by 17.2% and its split tensile was increased by 16.3%. Potassium feldspar and montmorillonite in zeolite powder and SiO2 in the sand were decomposed by OH− and combined with other elements to generate various silicate gels and A-type potassium zeolite crystals inside the concrete. Microscopic examination showed that the gels and crystals intertwined to fill the pores, decreasing (increasing) the percentage of large (small) pores, thus optimising the pore structure. This substantially improved the mechanical properties of ASC. Freeze–thaw salt-intrusion tests showed that the extent of mass loss, degree of damage and loss of compressive strength of AAZC-4 were similar to those of ordinary concrete but were reduced by 36.8%, 19% and 52.1%, respectively, compared with those of ASC. Therefore, AAZC-4 has sustainable working performance in the chloride ion permeable environment in cold and arid areas.

This paper present a platform for airborne sensor applications using low-cost, open-source components carried by an easy-to-fly unmanned aircraft vehicle (UAV). The system, available in open-source [1], is designed for researchers, students and makers for a broad range of their exploration and data-collection needs. The main contribution is the extensible architecture for modularized airborne sensor deployment and real-time data visualisation. Our open-source Android application provides data collection, flight path definition and map tools. Total cost of the system is below 800 dollars. The flexibility of the system are illustrated by mapping the location of Bluetooth beacons (iBeacons) on a ground field and by measuring water temperatures in a lake.

Antarctica is the continent with the lowest local human impact, yet it is still vulnerable to contaminants coming from external sources. Emerging pollutants, like PFAS, pose an increasing threat to this environment and therefore require more in-depth investigations to understand their environmental fate and biological impacts. The present study, part of the AntaGPS project, focuses on expression analysis at the transcriptional level of genes coding for 4 antioxidant enzymes (sod1, sod2, gpx1, gpx4) in different organs of an Antarctic fish species, Trematomus newnesi. The kidney showed a higher level of expression than the liver of wildlife specimens. The mRNA levels were also assessed in fish exposed to 1.5 μg/L of PFOA for 10 days. In the liver, the treatment induced an increase in gene expression for all the considered enzymes, while in the kidney it induced a general decrease. The obtained results constitute a starting point for using the expression of antioxidant enzymes as biomarkers, both of oxidative stress and exposure to PFAS, in future biomonitoring campaigns in the Antarctic marine environment.

To control the volatility and reduce the electricity costs for indoor farming, the agrivoltaics agrotunnel introduced here uses: 1) high insulation for a building dedicated to vertical growing, 2) high-efficiency LED lighting, 3) heat pumps (HPs), and 4), solar photovoltaics (PV) provide known electric costs for 25 years. In order to size the PV array, this study develops a thermal model for agrotunnel load calculations and validates it using the Hourly Analysis Program and measured data so the effect of plants’ evapotranspiration can be included. HPs are sized, plug loads (i.e., water pump energy needed to provide for the hybrid aeroponics/hydroponics system, DC power running the LEDs hung on grow walls, and dehumidifier assisting in moisture condensation in summer) are measured/modeled. Ultimately, all models are combined to establish an annual load profile for an agrotunnel that is then used to model the necessary PV to power the system throughout the year. The results find that agrivoltaics to power an agrotunnel range from 40 to 50kW and make up an areas from 3.2 to 10.48 m²/m² of an agrotunnel footprint. Net zero agrotunnels are technically viable although future work is needed to deeply explore the economics of localized vertical food growing systems.

Nonischemic dilated cardiomyopathy (DCM) is a complex cardiovascular condition often characterized by genetic pathogenesis. Comprehensive genetic testing has become a crucial aspect of DCM diagnosis and management, offering insights into prognosis and the identification of at-risk individuals. This case series and mini literature review examines the diagnostic and therapeutic dimensions of DCM, emphasizing the role of genetic evaluation. We delve into distinct genetic pathways associated with DCM and their pathogenetic mechanisms, emphasizing the evolving significance of genetic markers, particularly in cases where arrhythmia risk is heightened. The historical reliance on cardiac morphology to subtype cardiomyopathies is being complemented by the identification of genetic variants, further refining DCM subtypes, and aiding in clinical management.The giant sarcomere protein, titin, is a pivotal determinant of cardiomyocyte stiffness and plays a crucial role in cardiac strain sensing. Titin's extensive size and complexity make it susceptible to dysregulation, which has far-reaching consequences in cardiac disorders. This case series with a literature review explores the molecular mechanisms governing titin-based forces in both health and disease. It highlights the influence of isoform diversity and post-translational modifications on myocardial stiffness and contractility. In the context of cardiac diseases, we discuss how titin properties are altered, focusing on changes in titin stiffness and protein quality control. Notably, we address the pathomechanisms associated with truncation in the titin gene (TTN) in human cardiomyopathy, shedding light on potential therapeutic approaches for conditions such as HFpEF and TTN-truncation cardiomyopathy.This comprehensive understanding of DCM and Titin’s role in cardiac physiology and pathology provides a solid foundation for addressing cases like that of our patients, who were presented with features of heart failure and arrhythmias. Despite immediate and extensive resuscitative measures, the patient's protracted response to the treatment raised questions about the potential underlying genetic factors contributing to their clinical presentation. These cases underscore the importance of genetic evaluation in unraveling the complexity of cardiomyopathies, ultimately enhancing our ability to manage and treat such challenging cases.

Streptococcus suis serotype 2 is an important swine bacterial pathogen causing sudden death, septic shock, and meningitis. However, serotype 2 strains are phenotypically and genotypically heterogeneous and composed by a multitude of sequence types (STs) whose distribution greatly varies worldwide. It has been previously shown that lipoprotein (LPP) maturation enzymes diacylglyceryl transferase (Lgt) and signal peptidase (Lsp) significantly modulate the inflammatory host response and play a differential role in virulence depending on the genetic background of the strain. Differently from Eurasian ST1/ST7 strains, the capsular polysaccharide of a North American S. suis serotype 2 ST25 representative strain only partially masks sub-capsular domains and bacterial wall components. Thus, our hypothesis is that since LPPs would be more surface exposed in ST25 strains than in their ST1 or ST7 counterparts, the maturation enzymes would play a more important role in the pathogenesis of the infection caused by the North American strain. Using isogenic Δlgt and Δlsp mutants derived from the wild-type ST25 strain, our studies suggest that these enzymes do not seem to play a role in the interaction between S. suis and epithelial and endothelial cells, regardless the genetics background of the strain used. However, a role in the formation of biofilms (also independently of the STs) has been demonstrated. Moreover, the involvement of LPP dendritic cell activation in vitro seems to be somehow more pronounced with the ST25 strain. Finally, the Lgt enzyme seems to play a more important role in the virulence of the ST25 strain. Although some differences between STs could be observed, our original hypothesis that LPPs would be significantly more important in ST25 strains due to a better bacterial surface exposition could not be confirmed.

Abstract: Acute coronary syndrome (ACS) represents the most severe manifestation of coronary artery disease (CAD), characterized by a particularly poor prognosis. Consequently, primary percutaneous coronary intervention (PPCI) is imperative in the event of acute ST-elevation myocardial infarction (STEMI). Interleukin-22 (IL-22) may be a new CAD biomarker because it signals and regulates immune and inflammatory responses. Objectives: To investigate the differences in circulating IL-22 levels between patients with STEMI undergoing PPCI and healthy controls; and to determine if these differences are associated with the culprit coronary artery, door-to-balloon time (DBT), final angiographic result, CAD classification, and the presence of diabetes mellitus (DM). Methods: A total of 280 participants were recruited, comprising 210 STEMI cases and 70 healthy controls. Participants underwent clinical and angiographic evaluation, and serum IL-22 levels were measured using enzyme-linked immunosorbent assay (ELISA). Data analysis was performed using the Mann-Whitney and Fisher’s tests, with a p < 0.05 significant. Results: Serum IL-22 levels were lower in cases (149.63, 84.99–294.56) than in controls (482.67, 344.33–641.00), p < 0.001. Lower IL-22 levels were associated with the right coronary artery (RCA) (144.57, 70.84–242.43; 146.00, 63.60–279.67; 191.71, 121.80–388.97), p = 0.033. IL-22 was lower with shorter DBT (≤ 60 minutes, 106.00, 49.60–171.71; > 60 minutes, 153.00, 88.86–313.60), p = 0.043. Conclusions: IL-22 levels were significantly lower in patients with STEMI compared to healthy controls.

The relationship between perception of anxiety and quality of life in caregivers of children with autism was verified. To verify quality of life, the Short Form Healthy Survey Item was used; perception of anxiety was assessed using the Beck Anxiety Inventory. 80 caregivers of children with autism participated, with 68.7% of caregivers being mothers. Of the total number of caregivers, 68.8% had a severe level of anxiety. Regarding quality of life, they demonstrated greater impairment in Limitation due to physical aspects, Limitation due to emotional aspects, Vitality and Pain. Caregivers with severe anxiety levels had worse quality of life in the domains of pain (p = 0.012), social aspects (p =&lt; 0.001), limitation due to emotional aspects (p = 0.001) and mental health (p =&lt; 0.001). However, in the functional capacity domain, caregivers with a moderate level of anxiety had a better physical capacity score (p = 0.001). There was a negative correlation between the general anxiety score and the general physical (p = 0.029) and general emotional component of quality of life (p =&lt; 0.001). It was found that caregivers of children with ASD present losses related to psychological factors, quality of life and the lack of social support.

Focal cerebral ischemia can lead to blood-brain barrier (BBB) breakdown, which is implicated in neuroinflammation and elevation of matrix metalloproteinases (MMPs). The role of the anti-inflammatory protein, monocyte chemotactic protein–induced protein 1 (MCPIP1) plays in the injury of BBB in stroke has not yet been reported. This study was conducted to identify and characterize the role MCPIP1 plays in BBB breakdown. Transient middle cerebral artery occlusion (MCAO) is induced in both wild-type and Mcpip1^-/- mice for 2 hours of occlusion periods followed by reperfusion for 24 or 48 hours. BBB permeability was measured by FITC-dextran extravasation, MMP-9/3 expression was analyzed by western blot, and claudin-5 and zonula occludens-1 (ZO-1) were analyzed by immunohistochemistry and western blot. After MCAO in wild type mouse is induced, there is significantly increase in MCPIP1 mRNA and protein levels. Absence of MCPIP1 leaded to significant increase in FITC-dextran leakage in peri-infarct brain, significant upregulation of MMP-9, MMP-3 and reduced levels of tight junction components, claudin-5 and ZO-1 in the brain after MCAO. Our data demonstrate that absence of MCPIP1 exacerbates ischemia-induced blood-brain barrier disruption by enhancing the expression of matrix metalloproteinases and degradation of tight junction proteins. Overall data indicate that MCPIP1 is important protective role against BBB disruption in cerebral ischemia.

Background: Systemic autoimmune rheumatic diseases (SARDs), including Systemic Lupus Erythematosus (SLE) and Rheumatoid Arthritis (RA), are characterized by chronic inflammation and autoimmunity. Identifying reliable biomarkers is crucial for enhancing diagnosis, monitoring disease progression, and evaluating therapeutic responses. This study explores the potential of serum Syndecan-1 (SDC-1) as a biomarker for these conditions and concurrently examines its relationship with free light chain (FLC) expression levels in the same patients. Methods: A retrospective analysis was performed on serum samples from 120 patients (60 RA, 60 SLE), alongside 50 healthy donors (HD). Serum levels of κ and λ FLCs were determined by turbidimetric assay, while SDC-1 levels were measured using ELISA. Statistical analyses, including the Kruskal-Wallis test, Wilcoxon-Mann-Whitney U test, multivariable linear regression and Spearman’s correlation, were employed to compare biomarker levels across groups and to explore correlations among them. Results: Significantly increased levels of SDC-1, κ-FLC, and λ-FLC were observed in patients diagnosed with RA and SLE compared to HD (p < 0.001), while no significant differences in the κ/λ ratio were noted among the groups (p = 0.4). A statistically significant difference in subject age was also identified. However, multivariate regression analysis indicated that RA and SLE statuses are significantly associated with the levels of these markers, with minimal confounding by age. A significant correlation was observed separately in all groups between the FLC markers. Conversely, no correlation was detected between SDC-1 and FLCs, nor between these markers and age. Conclusion: Elevated serum levels of FLCs and SDC-1 in RA and SLE patients compared to healthy controls underscore their potential as biomarkers for SARDs. The findings also suggest sustained plasma cells activation, supporting the SDC-1 role in the pathogenesis of these conditions.

The emergence of 6G communication technologies brings both opportunities and challenges for the Internet of Things (IoT) in Smart Cities. In this paper, we introduce an advanced network slicing framework designed to meet the complex demands of 6G Smart Cities IoT deployments. The framework development follows a detailed methodology that encompasses requirement analysis, metric formulation, constraint specification, objective setting, mathematical modeling, configuration optimization, performance evaluation, parameter tuning, and validation of the final design. Our evaluations demonstrate the framework's high efficiency, evidenced by low Round-Trip Time (RTT), minimal packet loss, increased availability, and enhanced throughput. Notably, the framework scales effectively, managing multiple connections simultaneously without compromising resource efficiency. Enhanced security is achieved through robust features such as 256-bit encryption and a high rate of authentication success. The discussion elaborates on these findings, underscoring the framework's impressive performance, scalability, and security capabilities.

This study aimed to evaluate the effectiveness of decellularized nerves for promoting nerve regeneration by transplanting them from the sciatic nerve of a rabbit to that of a rat. The Sciatic nerves were harvested from New Zealand White Rabbits (n=4). A 1-cm segment of each nerve was decellularized by Sondell’s protocol and preserved at –4℃ in Roswell Park Memorial Institute (RPMI) 1640 medium for one week. Subsequently, a defect of a similar size was created in the sciatic nerves of rats. The decellularized nerves treated with detergent were then transplanted into these defects in the rats. The study included the three following groups: Group 1 (n=4) was the decellularized xenogeneic nerve group; Group 2 (n=7) was the negative control group in which the defect remained un-repaired; and Group 3 (n=5) was composed of the positive control group where the nerve was immediately transplanted from one rat to another. The sciatic functional index (SFI) was considered to evaluate the motor function by comparing it with the normal side at 1, 2, 3, and 4 weeks, and 1, 2, and 3 months postoperatively. Furthermore, electrophysiological and immunohistochemical assessments were conducted at 4 months. Immunohistochemically, at 16 weeks postoperative, the experimental group did not show statistically significant differences compared to controls in terms of schwann cell comparison, yet exhibited favorable outcomes when compared to the positive control group. Additionally, analysis of motor function test confirmed recovery of latency and nerve conduction velocity to levels similar to those of the normal side. While the nerve allograft demonstrated superior nerve regeneration in motor function test at 3 months, markedly low values were observed in all groups. When reconstructing peripheral nerves using detergent-based decellularized xenogenic nerves, analysis of immuno-histochemistry and motor nerve conduction study reveals a promising degree of nerve regeneration. However, when compared with fresh allograft group at 3 months after operation, the sciatic functional index was lower. Significantly lower values observed across all groups compared to previous assessments indicate the need for further research into potentially influential alternative factors.Histologically, at 16 weeks postoperative, the experimentally treated group did not show statistically significant differences compared to the controls in terms of a Schwann cell comparison, but exhibited favorable outcomes when compared to the positive control group. Additionally, an analysis of the motor function testing confirmed recovery of the latency and nerve conduction velocity to levels similar to those of the normal side. While the nerve allograft demonstrated superior nerve regeneration in the motor nerve examination at 3 months, notably low values were observed in all the groups. When reconstructing the peripheral nerves using detergent-based decellularized xenogeneic nerves, an analysis of immunohistochemistry and motor nerve conduction study reveals a promising degree of nerve regeneration. However, when compared with the fresh allograft group at 3 months post-operation, the sciatic functional index was lower. The significantly lower values observed across all groups compared to those of the previous assessments indicate the need for further research of potentially influential alternative factors.

The value of artificial intelligence and machine learning applications for use in heritage research is increasingly appreciated [1]. In specific areas, notably remote sensing, data sets have increased in extent and resolution to the point that manual interpretation is problematic and availability of skilled interpreters to undertake such work is limited. Interpretation of geophysical data sets associated with prehistoric submerged landscapes is particularly challenging. Following the last glacial, sea levels rose 120 metres globally, and vast, habitable landscapes were lost to the sea. These landscapes were inaccessible until extensive remote sensing data sets were provided by the offshore energy sector. In this paper, we provide results of a research programme centred on AI applications using data from the southern North Sea. Here, an area of c.188,000 km2 of habitable terrestrial land was inundated between c. 20,000 BP and 7,0000 BP, along with the cultural heritage it contained [2]. As part of this project, machine learning tools were applied to detect and interpret features of archaeological significance from shallow seismic data. The output provides a proof-of-concept model demonstrating verifiable results and the potential for further, more complex leveraging of AI interpretation for the study of submarine palaeolandscapes. Image: Adobe Firefly Generative AI using keywords - marsh landscape deep underwater, auroch skull half-buried in peat

The Estimation of systemic risk in India is still in its infancy stage. There are several methods which are available but none of the methods are fully compatible to forecast the systemic risk since under different circumstances the factors responsible for the risk differs. In this paper the systemic risk estimation in India being carried out based on spread in daily stock market price(Difference between the bid and ask price of a share) of the top 100 firms in India according to market capitalization for the period of July2007 to March 2016. The results were compared with the Financial Stability Report published by Reserve Bank Of India for the period of March 2010 to June 2016.The results clearly indicates that there exits relationship between market illiquidity represented by spread and risks associated with the Financial System. In most of the cases the Z score (deviation from the mean/Standard Deviation) of the spread has become negative which provides the spread which is farther from the mean, also a good indicator of volatility in market and risk to financial system. It is also seen that the Systemic Risk Survey conducted by Reserve Bank of India which started during October 2011 has supported the results.

Background and Objectives: High job strain is worsening the outcome in coronary artery disease, CAD. Severe dissatisfaction on workplace, imbalance between high demands , and low rewards, are affecting the quality of life, and diminishing the duration of life, especially in CAD patients. Our study included two samples : CAD patients (experimental group), and without CAD patients, but with traditional risk factors (control group). The main objective of the study was the role played by high sensitivity C reactive protein, hs CRP, and microalbuminuria, as mediators of job strain and CAD relationship. Secondary objectives were the following: identification of the most vulnerable patients( with significant job strain) and intervention towards this category, for cardiovascular events prevention (primary or secondary). Materials and Methods: The utilized methods were the following : clinical exam; electrocardiogram; echocardiogram; non contrast enhanced computed chest tomography; laboratory findings ( lipid profile, glycemia, hs CRP, microalbuminuria); type D scale, DS 14; depression questionnaire, PHQ-9; and satisfaction with work scale, SWWS. Results: The highest values for hs CRP and microalbuminuria were noticed in patients with the lowest Likert score, for both samples CAD, and without CAD patients. The highest job strain was noticed in females. More than half of CAD patients ,with low Likert scores, revealed myocardial infarction. Conclusions: Microalbuminuria and hs CRP were statistical significant in the study as intercessors, in job strain and CAD relationship. The most vulnerable patients for vascular events were females, in both groups : CAD and “CAD waiting desk”. In CAD sample, the vascular vulnerability was also increased by high job strain.

The integration of navigation technologies into spine surgery has improved precision and safety, yet traditional free-hand techniques are still widely used in anterior cervical discectomy and fusion (ACDF). This study uses the National Inpatient Sample (NIS) database to compare free-hand ver-sus navigation-guided ACDF, analyzing complications, costs, mortality, and hospital stay. Data from 2016 to 2019 identified 85,085 ACDF patients, including 560 navigation-guided surgeries. Propensity score matching balanced the cohorts for demographics and comorbidities. Navigation-guided surgeries showed higher total costs (p

Herein, we investigated hydrogels composed of boronic Acid functionalized alginate and blended with polyvinyl alcohol of different molecular weights to control the release of metoclopramide hydrochloride (MTC) as a function of pH and shear stress. The functionalization of alginate introduced dynamic covalent bonding and pH-responsive properties that can modulate network connectivity. The study investigated the viscoelastic properties of the hydrogels, their drug release profiles, and their responsiveness to changes in pH and shear forces. The results showed higher PVA molecular weight and alkaline pH conditions increased hydrogel viscosity and stiffness due to a more stable and interconnected network structure than acidic pH. Metoclopramide release revealed that the hydrogels exhibited pH-responsive drug release behavior. The drug was more readily released under acidic conditions due to the instability of sp2-hybridized boronate ester bonds. The influence of shear forces on the release of metoclopramide was also investigated at shear rates of 1, 10, and 100 s-1, revealing their effect on matrix stiffening. The research shows that AlgBA/PVA hydrogels have unique properties, such as dynamic covalent bonding, that make them sensitive to external mechanical forces. This sensitivity makes them ideal for applications where physiological conditions trigger drug release