Respiratory infections constitute a major reason for infants and children seeking medical advice and visiting health facilities, thus remaining a significant public threat with high morbidity and mortality. The predominant viruses causing viral respiratory infections are influenza A and B viruses (Flu-A, Flu-B), Respiratory Syncytial Virus (RSV), Adenovirus and Coronaviruses. We aimed to record the incidence of RSV, SARS-CoV-2, Influenza A/B and Adenovirus cases with rapid antigen tests and validate the results with RT-PCR assay of upper respiratory specimens with a wide range of viral loads and (co)-infection patterns in children. Clinical samples were collected from early symptomatic children (presenting with fever and/or cough and/or headache within 5–7 days). The surveillance program was conducted in five private pediatrician dispensaries and one Pediatric care unit, from 10 January 2023 to 30 March 2023 in central Greece. The total sample of specimens collected was 784 young children and infants, of which 383 (48.8%) ware female and 401 were male (51.2%). The mean age of participants was 7.3 + 5.5 years. The sensitivity of FLU A & B test was 91.15% (95% CI: 84.33% -95.67%), and the specificity was 98.96% (95% CI: 97.86% - 99.58%). The sensitivity and specificity of the adenovirus and RSV test was {92.45% (95% CI: 81.79% - 97.91%), 99.32% (95% CI: 98.41% -99.78%)} and {92.59% (95% CI: 75.71% -99.09%), 99.47% (95% CI: 98.65% - 99.86%)} respectively. Lastly, the sensitivity of the SARS-CoV-2 test was 100.00% (95% CI: 79.41%-100.00%) and the specificity was 99.74% (95% CI: 99.06% - 99.97%). We recorded proportion of incidence for the Influenza-A and B, (14.3%), - (3.44%) correspondingly, followed by the adenovirus with a proportion (6.9%) and the RSV with (3.7%) incidence proportion and finally, the SARS-CoV-2 (2.3%). The combination of a new multiple rapid test with multiple antigens, will be probably a useful tool with financial impact for health systems targeting the early detection and right treatment of respiratory infections in the emergency departments in primary health care facilities.

In the present-day digital landscape, websites have increasingly relied on digital marketing practices, notably search engine optimization (SEO), as a vital component in promoting sustainable growth. The traffic a website receives directly determines its development and success. As such, website owners frequently engage the services of SEO experts to enhance their website's visibility and increase traffic. These specialists employ premium SEO audit tools that crawl the website's source code to identify structural changes necessary to comply with specific ranking criteria, commonly called SEO factors. Working collaboratively with developers, SEO specialists implement technical changes to the source code and await the results. The cost of purchasing premium SEO audit tools or hiring an SEO specialist typically ranges in the thousands of dollars per year. Against this backdrop, this research endeavors to provide an open-source Python-based Machine Learning SEO software tool to the general public, catering to the needs of both website owners and SEO specialists. The tool analyzes the top-ranking websites for a given search term, assessing their on-page and off-page SEO strategies, and provides recommendations to enhance a website's performance to surpass its competition. The tool yields remarkable results, boosting average daily organic traffic from 10 to 143 visitors.

The rapidly evolving field of artificial intelligence (AI) continues to witness the introduction of innovative open-source pre-trained models, fostering advancements in various applications. One such model is Llama 2, an open-source pre-trained model released by Meta, which has garnered significant attention among early adopters. In addition to exploring the foundational elements of the Llama v2 model, this paper investigates how these early adopters leverage the capabilities of Llama 2 in their AI projects. Through a qualitative study, we delve into the perspectives, experiences, and strategies employed by early adopters to leverage Llama 2's capabilities. For the purpose of data analysis, the capabilities inherent in the Llama 2 model were employed to conduct keyword extraction from the context of the early adopters' case studies. The findings shed light on the model's strengths, weaknesses, and areas of improvement, offering valuable insights for the AI community and Meta to enhance future model iterations. Additionally, we discuss the implications of Llama 2's adoption on the broader open-source AI landscape, addressing challenges and opportunities for developers and researchers in the pursuit of cutting-edge AI solutions. The present study constitutes an early exploration of the Llama 2 pre-trained model, holding promise as a foundational basis for forthcoming research investigations.

Objective: The Acute Cystitis Symptom Score (ACSS) was developed and validated as a self-reporting questionnaire for diagnosing and monitoring acute, uncomplicated cystitis (AC) in female patients. The study aims at the translation of the ACSS into Greek from original Russian as a source and American English as a new master version and at its linguistic validation. Material and Methods: Three independent professional native Greek translators, two of them experts in Russian and one in English, translated the ACSS from Russian and American English into Greek. The second group of three translators translated each of the three versions back into the original language to detect or correct any important discrepancies. These three Greek versions were then used for linguistic validation. Results: The English to Greek translation reflected more the spoken language, the two Russian to Greek translations more the written, formal language. A total of 60 randomly selected females and 30 healthcare professionals was asked about their preferences and to comment on each of the three translations. Considering all comments the scientific committee (SC) developed the Greek consensus version. For cognitive assessment additional 30 healthcare professionals and 30 females were asked to comment on the intelligibility of all items. Considering their comments the linguistically validated Greek study version was established by the SC. Conclusion: The linguistically validated Greek version of the ACSS can now be used for the clinical validation study.

In recent research, a growing body of empirical evidence, suggests that prosocial impact at work can play a significant role in enhancing creativity and innovativeness. Drawing from Self Determination Theory, we hypothesized that basic psychological needs and benevolence satisfaction could serve as a mediating factor in the relation between employees perceived social impact and innovative work behavior and creativity, thus illuminating the manner in which contentment of psychological needs fosters inventive proclivities within the organizational milieu. Results from a study in Greece and Canada (N=528) showed that both perceived social impact and prosocial motivation are positively associated with innovative work behavior and creativity while autonomy and competence satisfaction mediate the relation between perceived social impact and the work outcomes examined within this study. Moreover, prosocial motivation was found to moderate the relation between benevolence satisfaction and innovativeness. Findings extend prior research on the role of prosociality on creative behavior at work and provide supporting evidence for the organizations that encourage and support employees’ initiatives to make a positive difference in the lives of others.

Evidence from large epidemiological studies has shown that obesity may predispose to increased Th2 inflammation and increase the odds of developing asthma. On the other hand, there is growing evidence suggesting that metabolic dysregulation that occurs with obesity, and more specifically hyperglycemia and insulin resistance, may modify immune cell function and in some degree systemic inflammation. Insulin resistance seldom occurs on its own, and in most cases constitutes a clinical component of metabolic syndrome, along with central obesity and dyslipidemia. Despite that, in some cases, hyperinsulinemia associated with insulin resistance has been proven a stronger risk factor than body mass in developing asthma. This finding has been supported by recent experimental studies showing that insulin resistance may contribute to airway remodeling, promotion of airway smooth muscle (ASM) contractility and proliferation, increase of airway hyper-responsiveness and release of pro-inflammatory mediators from adipose tissue. All these effects indicate the potential impact of hyperinsulinemia on airway structure and function, suggesting the presence of a specific asthma phenotype with insulin resistance. Epidemiologic studies have found that individuals with severe and uncontrolled asthma have a higher prevalence of glycemic dysfunction, whereas longitudinal studies have linked glycemic dysfunction to an increased risk of asthma exacerbations. Since the components of metabolic syndrome interact with one another so much, it is challenging to identify each one's specific role in asthma. This is why, over the last decade, additional studies have been conducted to determine whether treatment of type 2 diabetes mellitus affects comorbid asthma as shown by the incidence of asthma, asthma control and asthma-related exacerbations. The purpose of this review is to present the mechanism of action, and existing preclinical and clinical data, regarding the effect of insulin resistance in asthma.

There is remarkable morphologic and genetic heterogeneity in acute myeloid leukemia (AML). In a small percentage of cases of AML, increased eosinophils and/or basophils are present in the bone marrow and sometimes in the peripheral blood. This is often a puzzling diagnostic situation but also an important finding that requires special investigation. Unique chromosomal rearrangements have been correlated with an increased number of eosinophils and basophils in AML. Identification of the underlying genetic lesion that promotes eosinophilia and basophilia can dramatically change both the prognosis and the treatment of the patient. Thus clinicians must be vigilant in searching for the cause of eosinophilia and/or basophilia in patients with AML, since the different causes may lead to different treatments and survival outcomes. In this article we examine the significance of increased eosinophils and/or basophils in the context of AML, provide guidance that simplifies the differential diagnosis, and prognostic and therapeutic information about specific subtypes of AML associated with eosinophilia and/or basophilia. Evidence supporting personalized (molecularly targeted) therapy for these patients is also presented.

Background: Hepatic erythrophagocytosis is augmented in NASH and amplifies inflammation and fibrosis. Although various pro-phagocytic signals have been identified on erythrocytes of NASH patients, the role of bound thrombospondin-1 (TSP-1), which acts as an “eat-me” signal, arginase-1, which regulates the levels of nitric oxide in erythrocytes, and phosphatidylethano-lamine (PE) which can amplify erythrophagocytosis and hepatic inflammation have not been explored. Hence, we sought to investigate the levels of arginase-1 and TSP-1 in erythrocyte lysate and PE in erythrocyte membranes of NASH patients. Methods: Twenty-four patients and 14 healthy controls participated in our study. The levels of TSP-1 and arginase were quantified by ELISA in erythrocyte lysates, and the levels of PE in erythrocyte membranes by thin layer chro-matography. Results: Erythrocytes of NAFLD patients exhibit lower levels of arginase-1 and TSP-1 (p<0.01). Erythrocyte-bound TSP-1 levels correlated with the levels of erythrocyte surface CD47. Phosphatidylethanolamine was increased in erythrocytes of NASH patients and was accompanied by increased release, indicating exposure. Conclusion: Our results imply reduced TSP-1 binding by erythrocytes which could allow free TSP-1 molecules to act on macrophages, enhancing erythrophagocytosis. Increased PE which could amplify inflammation after efferocytosis, while downregulation of arginase-1 could lead to defective efferocytosis.

The angle of seismic excitation is a significant factor of the seismic response of RC buildings. The procedure required for the calculation of the angle for which the potential seismic damage is maximized (critical angle) contains multiple nonlinear time history analyses using in each one of them different angles of incidence. Moreover, the seismic codes recommend the application of more than one accelerograms for the evaluation of seismic response. Thus, the whole procedure becomes time consuming. Herein, a method to reduce the time required for the estimation of the critical angle based on Multilayered Feedforward Perceptron Neural Networks is proposed. The basic idea is the detection of cases in which the critical angle increases the class of seismic damage compared to the class which arises from the application of the seismic motion along the buildings’ structural axes. To this end, the problem is expressed and solved as Pattern Recognition problem. As inputs of networks the ratios of seismic parameters’ values along the two horizontal seismic records' components, as well as appropriately chosen structural parameters, were used. The results of analyses show that the neural networks can reliably detect the cases in which the calculation of the critical angle is essential.

In today’s Industrial IoT (IIoT) environment, where different systems interact with the physical world, the state proposed by the Industry 4.0 standards can lead to escalating vulnerabilities, especially when these systems receive data streams from multiple intermediaries, requiring multilevel security approaches, in addition to link encryption. At the same time taking into account the heterogeneity of the systems included in the IIoT ecosystem and the non-institutionalized interoperability in terms of hardware and software, serious issues arise as to how to secure these systems. In this framework, given that the protection of industrial equipment is a requirement inextricably linked to technological developments and the use of the IoT, it is important to identify the major vulnerabilities, the associated risks and threats and to suggest the most appropriate countermeasures. In this context, this study provides a description of the attacks against IIoT systems, as well as a thorough analysis of the solutions against these attacks, as they have been proposed in the most recent literature.

The process of oxygenic photosynthesis is primarily driven by two multiprotein complexes known as photosystem II (PSII) and photosystem I (PSI). PSII facilitates the light–induced reactions of water–splitting and plastoquinone reduction, while PSI functions as the light–driven plastocyanin-ferredoxin oxidoreductase. In contrast to the highly conserved structure of PSII among all oxygen–evolving photosynthetic organisms, the structures of PSI exhibit remarkable variations, especially for photosynthetic organisms that grow in special environments. In this review, we make a concise overview of the recent investigations of PSI from photosynthetic microorganisms including prokaryotic cyanobacteria and eukaryotic algae from the perspective of structural biology. All known PSI complexes contain a highly conserved heterodimeric core; however, their pigment compositions and peripheral light-harvesting proteins are substantially flexible. This structural plasticity of PSI reveals the dynamic adaptation to environmental changes for photosynthetic organisms.

This study provides a thorough review and analysis of the evolution of the Greek vehicle fleet over the last ~30 years, which is next used for the generation of high granularity fleet projections and for the estimation of relevant environmental benefits by 2030. The integrated methodology developed takes also into account vehicle clustering and the Brown’s Double Simple Exponential Smoothing technique that together with the adoption of COPERT based emission factors allow for the estimation of the anticipated emissions in 2030. Expected 2030 emissions levels suggest a reduction across all pollutants in comparison to 2018, ranging from 3.7% for PM10 to 54.5% for NMVOC (and 46% for CO, 14% for SO2, 28% for NOX and 21% for CO2). We find that Greece is on track with national goals concerning the reduction of air pollution from the transportation sector, stressing the positive contribution of EVs and new, "greener" vehicles, and setting new challenges for the further improvement of the sector beyond the 2030 outlook.

Expert system approach, although quite old, is still quite effective in scientific areas where experts are required to make diagnoses and predictions. One of those areas is fish disease diagnosis. It is an application domain that currently employs complicated processes, which require high level skills for making accurate diagnoses. On the other hand, complete datasets for full diagnosis to be able to use machine learning techniques are not available. Therefore, in aquaculture, now more than ever, fish farmers do not have the required expertise or equipment to accurately diagnose a fish disease. For that reason, expert systems that can help in the diagnosis, prevention and treatment of diseases have been developed. In this paper, we attempt to give an overview of the expert system approaches for fish disease diagnosis developed in the last two decades. Based on the analysis of their technical and non-technical characteristics, we propose an expert system architecture and a fish disease diagnosis process aiming at improving the deficiencies of existing such systems. The proposed system can handle all kinds of fish diseases based on image and non-image data as well as on molecular tests results and can provide explanations. The diagnosis process goes through four consecutive levels, where each next level considers an additional category of parameters and provides diagnoses with higher certainty.

Smoking is a risk factor for respiratory infections and there is reasonable concern that it may affect COVID-19 susceptibility and severity. Recent studies have focused on the interaction between smoking (and nicotine) and ACE2 expression, suggesting that ACE2 up-regulation could contribute to enhanced viral cell entry. However, case series have shown that there is an unexpectedly low prevalence of smoking among hospitalized COVID-19 cases. Since early April, we were the first to hypothesize that dysfunction of the nicotinic cholinergic system (NCS) may be implicated in the pathophysiology of severe COVID-19. We recently reported that many of the clinical manifestations of severe COVID-19 could be explained by dysregulation of the NCS. In this study, we present an amino acid sequence in the receptor binding domain of the SARS-CoV-2 Spike glycoprotein which is homologous to a sequence of a snake venom toxin. We present the 3D structural location of this “toxin-like” sequence on the Spike Glycoprotein. These findings suggest that SARS-CoV-2 could potentially interact with acetylcholine receptors causing dysregulation of the NCS and the cholinergic anti-inflammatory pathway.

Background Homologous recombination deficiency (HRD) evolved into a major diagnostic marker in high grade ovarian cancer (HGOC) predicting the response to poly (Adenosine diphosphate-ribose) polymerase inhibitors (PARPi) and also platinum-based therapy. In addition to HRD, the type of peritoneal tumor spread influences treatment response and patient survival; miliary type tumor spread has poorer predicted outcome than non-miliary type tumor spread. Methods Known methods for HRD assessment were adapted for our technical requirements and the Predictive-value Integrated Genomic Instability Score (PIGIS) for HRD assessment evolved as an outcome. PIGIS was validated in HGOC samples from 122 patients. We used PIGIS to analyze whether the type of tumor spread correlated with HRD status and whether this had an impact on survival. Results We demonstrated that PIGIS can discriminate HRD positive from HRD negative samples. Tumors with miliary tumor spread are HRD negative and have a very bad prognosis with a progression free survival (PFS) of 15.6 months and an overall survival (OS) of 3.9 years. However, HRD negative non-miliary spreading tumors in our cohort had a much better prognosis (PFS 35.4 months, OS 8.9 years), similar to HRD positive tumors (PFS 34.7 months, OS 8.9 years). Conclusions Our results indicate that in a predominantly PARPi naïve cohort the type of tumor spread might be a better predictor of response to platinum sensitivity than HRD. It remains to be determined, whether this also applies for sensitivity to PARPi.

Pursuing "intelligent justice" necessitates an impartial, productive, and technologically driven methodology for judicial determinations. This scholarly composition proposes a framework that harnesses Artificial Intelligence (AI) innovations such as Natural Language Processing (NLP), ChatGPT, ontological alignment, and the semantic web, in conjunction with blockchain and privacy techniques, to examine, deduce, and proffer recommendations for the administration of justice. Specifically, through the integration of blockchain technology, the system affords a secure and transparent infrastructure for the management of legal documentation and transactions while preserving data confidentiality. Privacy approaches, including differential privacy and homomorphic encryption techniques, are further employed to safeguard sensitive data and uphold discretion. The advantages of the suggested framework encompass heightened efficiency and expediency, diminished error propensity, a more uniform approach to judicial determinations, and augmented security and privacy. Additionally, by utilizing explainable AI methodologies, the ethical and legal ramifications of deploying intelligent algorithms and blockchain technologies within the legal domain are scrupulously contemplated, ensuring a secure, efficient, and transparent justice system that concurrently protects sensitive information upholds privacy.

Design process can be divided into stages of analysis and synthesis. This paper presents the application of the object-oriented technique to the analysis as well as theoretical considerations concerning to design of gear size ranges. This analysis consists in decomposition of the designed artefact (a gear) according to the rule “from general to details view”. The basics of the object-oriented analysis were formulated. Furthermore, design phases and the objects related to theses phases were discussed. The following models have been considered: hierarchical model, entity-relationship model, data-flow model and object model. Analysis is additionally connected with interactions between particular design phases.

Alleged practices of magical assault and vampirism are a recurrent feature of popular explanations of misfortune in Tuva Republic, South Siberia. Based on a field study of healing practices in an “Association of Shamans”, this article analyses rituals of countercursing one’s antagonists in a context of Russian political domination. A central purpose of this discussion is to foreground the centrality of kinds of parasitical worship and occult threat to structures of political power in – and beyond – the region of Tuva. Focusing on a “curse-scape”, which develops from the combative practices of shamans, occult specialists and office-holders, the article probes a repertoire of healing symbols in a shaman’s courtroom. It is argued that shamanic healing draws its efficacy from appropriating hunting symbols and animal spirits, which appear in Indigenous Siberian cosmologies. The analysis shows that ideas of playing with risk during countercursing rituals structure the process of symbolic resolution. The article concludes by highlighting indigenous perceptions of a “cursed” landscape as a field where the agencies of “darkness” (and their political sponsors) are confronted with an emancipating, Buddhist religious mindset.

Although heart failure with preserved ejection fraction (HFpEF) has become the predominant heart failure subtype, it remains clinically under-recognized. This, has been attributed to the complex pathophysiological mechanisms that accompany individuals with several co-morbidities and symptoms and signs of HFpEF. Natriuretic peptides have been recognized to have important role in the diagnosis and monitoring of patients with heart failure with reduced ejection fraction (HFrEF), but their role in HFpEF remains controversial. Its seems that the role of NtproBNP in the diagnosis of HFpEF, is mainly driven by the pathophysiological characteristics of the patients.

Premature ventricular complexes (PVCs) are frequently encountered in clinical practice. The association of PVCs with adverse cardiovascular outcomes in the context of structural heart disease is well established, yet the association between PVCs and cardiovascular outcomes in the absence of structural heart disease is not fully elucidated. Cardiac magnetic resonance (CMR) seems to contribute prognostically in the latter subgroup. PVC- induced myocardial dysfunction refers to the impairment of ventricular function due to the PVCs and is mainly associated with a PVC burden greater than 10%. The surface 12- lead ECG is used to localize the anatomic site of origin and multiple algorithms have been developed to differentiate right ventricular and left ventricular outflow tract (RVOT and LVOT, respectively) origin. Novel algorithms include alternative ECG configurations and lately, sophisticated artificial intelligence methods have been utilized to distinguish the origins of outflow tract arrhythmias. The decision to therapeutically address PVCs should be taken upon the presence of symptoms or the development of PVC- induced myocardial dysfunction. The therapeutic modalities include pharmacological therapy, namely I-C antiarrhythmic drugs and beta blockers, as well as catheter ablation, which demonstrates superior efficacy and safety.

Groove pancreatitis represents a chronic focal form of pancreatitis affecting the zone between the pancreatic head and the duodenal „C” loop, known as the groove area. This is a rare condition that affects the pancreatic periampullary part, including the duodenum and the common bile duct, associated usually with long-term alcohol and tobacco misuse and being more frequent in men than in women. The most common clinical symptoms of groove pancreatitis include weight loss, acute abdominal pain, nausea, and jaundice. This report is about a 66 year old woman with a history of heavy smoking, presenting with weight loss, nausea, and upper abdominal pain. Contrast enhanced computed tomography revealed the existence of a chronic pancreatitis as well as the dilatation of the main pancreatic duct, a cyst of the pancreatic head and enlargement of the biliary tract. Conservatory treatment was initiated but with no improvement of symptoms. Since there was no indication for endoscopic retrograde cholangiopancreatography, we decided to perform a pancreatoduodenectomy, as surgery appears to be the single effective treatment.

The broad emission bump in the electromagnetic spectra observed following the detection of gravitational waves created during the kilonova event of merger of two neutron stars in August 2017, GW170817, has been linked to the heavy elements of lanthanides (Z=57-71), and a new understanding of creation of heavy elements in the r-process. The initial spectral emission bump has a wavelength range of 3000 - 7000 \AA, thus covering the region of ultraviolet (UV) to optical (O) wavelengths, and is similar to those seen for lanthanides. Most lanthanides have large number of closely lying energy levels which introduce extensive sets of radiative transitions which often form broad region of lines of significant strength. The current study explores these broad features through photoabsorption spectroscopy of 25 lanthanides ions, Ho I-III, Er I-IV, Tm I-V, Yb I-VI and Lu I-VII. With excitations only to a few orbitals up beyond the ground configurations, we find most of these ions cover large number of bound levels with open $4f$ orbital and produce tens to about hundred thousands lines that may form one or multiple broad features in X-ray to UV, O, and infrared (IR) regions. Spectrum of each of 25 ions is presented indicating presence, shape and wavelength region of the features. Accuracy of atomic data to interpret the merger spectra has been a outstanding problem. The present study aims at providing improved atomic data for energies and transition parameters obtained using relativistic Breit-Pauli approximation implemented in the atomic structure code SUPERSTRUCTURE. The present data have been benchmarked with available experimental data for energies and transition parameters. The study finds that number of ions under the present study are possible contributors of the emission bump of GW170817. All atomic data will be made available online at NORAD-Atomic-Data database.

Attackers are perpetually modifying their tactics to avoid detection and frequently leverage legitimate credentials with trusted tools already deployed in a network environment, making it difficult for organizations to proactively identify critical security risks. Network traffic analysis products have emerged in response to attackers’ relentless innovation, offering organizations a realistic path forward for combatting creative attackers. Additionally, thanks to the widespread adoption of cloud computing, Device Operators (DevOps) processes, and the Internet of Things (IoT), maintaining effective network visibility has become a highly complex and overwhelming process. What makes network traffic analysis technology particularly meaningful is its ability to combine its core capabilities to deliver malicious intent detection. In this paper, we propose a novel darknet traffic analysis and network management framework to real-time automating the malicious intent detection process, using a weight agnostic neural networks architecture. It is an effective and accurate computational intelligent forensics tool for network traffic analysis, the demystification of malware traffic, and encrypted traffic identification in real-time. Based on Weight Agnostic Neural Networks (WANNs) methodology, we propose an automated searching neural net architectures strategy that can perform various tasks such as identify zero-day attacks. By automating the malicious intent detection process from the darknet, the advanced proposed solution is reducing the skills and effort barrier that prevents many organizations from effectively protecting their most critical assets.

Background: Endovascular treatment of popliteal aneurysms (PA) has increased in the last few years, quickly becoming the main treatment in many vascular centers, based on the acceptable and promising outcomes reported in the literature. However, endograft infections are the most dangerous complication as a serious local compromise and usually require open surgical conversion and device explantation to preserve the affected extremity. Case report: We reported two patients admitted to the emergency room for pain and edema in the lower leg. Both patients have undergone exclusion of ruptured PA a few years before by endovascular graft. CTA showed a significant volume of fluid-corpuscular collection related to perianeurysmal abscess collection in both cases. Blood cultures and drained material cultures were positive for Staphylococcus Capitis in the first case and S. Aureus in the second. The antibiotics prophylaxis was performed for 10 days, then, patients underwent an open surgical conversion with a complete explantation of endovascular material and a femoro-popliteal bypass using an autologous vein in the first case and biological bovine pericardium prosthesis in the other case. Furthermore, we have questioned the literature and found eight more cases described in case report article referred to popliteal graft infections by different microorganisms, mostly presenting acute limb ischemia as the first symptom and suggesting endograft explantation with open conversion and autologous vein bypass as the commonest therapeutic choice. Conclusions: Open surgical conversion of popliteal endograft infection is the best strategy to manage peripheral infection of the popliteal stent.

While SARS-CoV-2 uses angiotensin converting enzyme 2 (ACE2) as the receptor for cell entry, it is important to examine for other potential interactions between the virus and other cell receptors. Based on the clinical observation of low smoking prevalence among hospitalized COVID-19 patients, we recently identified a “toxin-like” amino acid (aa) sequence on the receptor binding domain of the spike glycoprotein of SARS-CoV-2 (aa 375-390) with homology to a sequence of a snake venom toxin, which could interact with nicotinic acetylcholine receptors (nAChRs). We now present computational molecular modelling and docking experiments using 3D structures of the SARS-CoV-2 spike glycoprotein and the extracellular domain of the nAChR alpha9 subunit. We identified an interaction between the aa381-386 of the SARS-CoV-2 spike glycoprotein and the aa189-192 of the extracellular domain of the nAChR alpha9 subunit, a region which forms the core of the “toxin-binding site” of the nAChRs. The mode of interaction is very similar to the interaction between the alpha9 nAChR and alpha-bungarotoxin. A similar interaction was observed between the pentameric alpha7 AChR and the SARS-CoV-2 spike glycoprotein. Our findings support the hypothesis that severe COVID-19 may be associated with disruption of the nicotinic cholinergic system which could be caused by an interaction between SARS-CoV-2 and nAChRs.

Background: The purpose of this study was to examine the prevalence and effects of current smoking on adverse outcomes among hospitalized COVID-19 patients. Methods: We performed a systematic review of the literature (PubMed) for studies published until April 25. Studies were included into the analysis if they satisfied all of the following criteria: 1. To present hospitalized patients with COVID-19. 2. To classify patients into less and more severe disease, irrespective of the severity definition (defined as “adverse ourtcome”). 3. To present data on the smoking status, separately for each severity classification. We identified 18 (from a total of 1398) relevant studies. Pooled current smoking prevalence was compared with the gender-adjusted, population-based expected prevalence by calculating Prevalence Odds Ratio (POR). The association between current, compared to non-current and former, smoking and adverse outcome was examined by calculating Odds Ratio (OR). All analyses were performed using random-effects meta-analysis. Results: Among 6515 patients, 440 of whom were current smokers, the pooled prevalence of current smoking was 6.8% (95%CI: 4.8-9.1%) and the POR was 0.21 (95%CI: 0.16-0.26, P < 0.001). In Chinese studies only, the POR was 0.22 (95%CI: 0.17-0.27, P < 0.001). Current smokers were more likely to have an adverse outcome compared to non-current smokers (OR: 1.53, 95%CI: 1.06-2.20, P = 0.022). However, they were less likely to have an adverse outcome compared to former smokers (OR: 0.42, 95%CI: 0.27-0.74, P = 0.003). Conclusion: An unexpectedly low prevalence of current smoking was observed among hospitalized patients with COVID-19. Hospitalized current smokers had higher odds compared to non-current smokers but lower odds compared to former smokers for an adverse outcome. The possibility that nicotine may have a protective effect in COVID-19 which may be masked by smoking-related toxicity and by the abrupt cessation of nicotine intake when smokers are hospitalized should be explored.

The treasury of a DAO is purported to uphold the value of the DAO-issued token, and this study represents a pioneering effort to delve into these realms. We explore the relationship between the treasury and market capitalization in two DAO projects, namely Olympus DAO and KlimaDAO. Employing Granger Causality tests, we scrutinize the relationship between market capitalization and the treasuries of these DAOs. Furthermore, we use an EGARCH model to investigate the in-fluence of carbon offset tokens on KlimaDAO’s market capitalization, incorporating this variable into the model's conditional mean equation. The findings reveal a significant relationship between market capitalization and the treasuries of the DAOs, indicating a potential impact of market capitalization on treasuries. Additionally, the well-specified EGARCH model highlights the sig-nificance of carbon offset tokens, suggesting their potential to influence the overall market capi-talization of a DAO project and support its value.

This research aims to apply Artificial Intelligence (AI) methods, specifically Artificial Immune Systems (AIS), to design an optimal control strategy for a multivariable control plant. Two specific industrial control approaches are investigated: I-PD (Integral-Proportional Derivative) and PI-D (Proportional-Integral Derivative) control. The motivation for using these variations of PID controllers is that they are functionally implemented in modern industrial controllers, where they provide precise process control. The research results in a novel solution to the control synthesis problem for the industrial system. In particular, the research deals with the synthesis of I-P control for a two-loop system in the technological process of a distillation column. This synthesis is carried out using the AIS algorithm, which is the first application of this technique in this specific context. Methodological approaches are proposed to improve the performance of industrial multivariable control systems by effectively using optimization algorithms and establishing modified quality criteria. The numerical performance index ISE justifies the effectiveness of the AIS-based controllers in comparison with conventional PID controllers (ISE₁ = 1.865, ISE₂ = 1.56). The problem of synthesis of the multi-input multi-output (MIMO) control system is solved, considering the interconnections due to the decoupling procedure.

The article presents several innovative systems developed through student laboratory projects, including two autonomous vehicles, a four-legged walking robot, an active ankle-foot orthosis, a ball on beam balancing mechanism, a ball on plate system, and a manipulator arm—all powered by pneumatic artificial muscles (PAMs). Fluidic muscles offer significant potential in various mechatronic systems, robots, and manipulators due to their flexible, lightweight nature and compliance. Their ability to produce smooth and adaptable motions is particularly beneficial in applications requiring natural and human-like movement, such as rehabilitation and assistive devices. Although PAMs powered control systems face challenges with nonlinear phenomena, their biologically inspired design holds promise for future applications across various industries. These may include innovative applicability in industrial, automotive, and aerospace sectors, as well as use in sports, medical aids, entertainment, and animatronics. Incorporating self-made laboratory systems actuated by PAMs into control systems education offers a comprehensive learning opportunity that combines theoretical concepts with hands-on experience. This approach develops the necessary skills of future engineers, expanding their understanding of technical principles and preparing them for future challenges in engineering practice.

High hopes were associated with the new anti-angiogenic medicament, bevacizumab, which due to the possibility of binding to isoform A of vascular endothelial growth factor (VEGF), inhibited the creation of new blood vessels. However, not only blood vessels are responsible for the tumor cells' spread. During the process of tumor growth, lymphangiogenesis is mediated by other isoforms of the VEGF family, specifically VEGF-C and VEGF-D, which are independent of the bevacizumab action. Therefore, based on the mechanism of bevacizumab action and the processes of angio- and lymphangiogenesis, we formed three hypotheses: 1) if the lymph nodes in the primary ovarian cancers are metastatic, the outcome of bevacizumab treatment is worsened; 2) concerning the second-line treatment, bevacizumab will act in a weakened manner if the recurrence occurs in lymph nodes compared to local recurrences; 3) patients treated by bevacizumab are more likely to have recurrences in lymph nodes. These hypotheses raise the issue of the existing gap of knowledge, which concerns the effect of bevacizumab on the metastatic lymph nodes.

Arrhythmic sudden cardiac death (SCD) has an annual prevalence of 1 per 1000 while 75% of the victims suffer from ischemic and 10% from non-ischemic or hypertrophic cardiomyopathy. Altogether, these three entities account for more than 80% of the total SCD victims. Guidelines for implantable cardiac defibrillators are still dominated by LVEF<30% from the MADIT II study. In terms of arrhythmic risk stratification, the PRESERVE-EF study restored in clinical practice the two-step arrhythmic risk stratification approach based on Electrocardiographic non-invasive risk factors (NIRFs) guiding to electrophysiological study. In our times with the multiple cardiac imaging methods and artificial intelligence applications availability, this two-step approach based on integrated arrhythmia mechanisms detection, emerges as an efficient SCD risk stratification paradigm for these three entities but also for the patients with congenital heart disease.

In today's digital landscape, cybersecurity has become a priority, with attacks becoming increasingly sophisticated. Traditional security approaches are no longer enough, requiring a more dynamic and advanced response. In this context, integrating Artificial Intelligence (AI) and Machine Learning (ML) appears key to addressing this growing threat. However, despite their high effectiveness, there is a developed problem: the integration of various data sources and technologies for comprehensive protection. This article presents an in-depth review of integrating Artificial Intelligence and Machine Learning in cybersecurity, focusing particularly on Open Extended Detection and Response (Open XDR) technology. The literature review in this article was meticulously conducted with specific criteria in mind. It focused on sourcing peer-reviewed journals, authoritative cybersecurity publications, and recent conferences that primarily concentrate on the advancements in AI and ML within the cybersecurity domain, particularly from 2018 to 2023. This timeframe was chosen to ensure the inclusion of the most current and relevant developments in Open XDR technology, Intrusion Detection Systems, Endpoint Detection and Response, and Security Information and Event Management systems. Additionally, the review gave special attention to studies and reports highlighting practical implementations and real-world applications of these technologies, thereby ensuring a comprehensive understanding of their impact and effectiveness in enhancing cybersecurity resilience. The methodology used is a detailed literature review, examining how various cybersecurity components interact and function. These components include Intrusion Detection Systems (IDS), which monitor networks for malicious activities; Endpoint Detection and Response (EDR), which focuses on detecting and investigating security incidents on endpoints; and Security Information and Event Management (SIEM), systems that provide real-time analysis of security alerts. The review also considers the role of Active Directory, a directory service for Windows domain networks, and the process of log forwarding, where log files are transmitted to a central server for analysis, in the context of AI and ML. The paper delves into the development of AI and ML, underscoring their roles in cybersecurity for advanced data processing, pattern recognition, and predicting threats. It explores both supervised (where the model is trained on labeled data) and unsupervised learning (where the model learns from unlabeled data) in ML, and how these techniques bolster cybersecurity measures. The article highlights the significance of Open XDR as a critical innovation that integrates data from multiple sources for comprehensive security analysis. Further, the review discusses how the integration of AI and ML into various cybersecurity tools, such as IDS, EDR, and SIEM, augments capabilities in threat detection and response. It addresses the challenges and opportunities that AI and ML present in the cybersecurity domain, focusing on ethical issues, data privacy concerns, and the necessity for ongoing professional development in this rapidly advancing field. The paper concludes by affirming the effectiveness of merging AI and ML with these cybersecurity tools within the Open XDR framework.

This study aims to explore the possibility of estimating a multitude of kinematic and dynamic quantities using subject-specific musculoskeletal models in real-time. The framework was designed to operate with marker-based and inertial measurement units enabling extensions far beyond dedicated motion capture laboratories. We present the technical details for calculating the kinematics, generalized forces, muscle forces, joint reaction loads, and predicting ground reaction wrenches during walking. Emphasis was given to reduce computational latency while maintaining accuracy as compared to the offline counterpart. Notably, we highlight the influence of adequate filtering and differentiation under noisy conditions and its importance for consequent dynamic calculations. Real-time estimates of the joint moments, muscle forces, and reaction loads closely resemble OpenSim's offline analyses. Model-based estimation of ground reaction wrenches demonstrates that even a small error can negatively affect other estimated quantities. An application of the developed system is demonstrated in the context of rehabilitation and gait retraining. We expect that such a system will find numerous applications in laboratory settings and outdoor conditions with the advent of predicting or sensing environment interactions. Therefore, we hope that this open-source framework will be a significant milestone for solving this grand challenge.

The implementation of teaching interventions in learning needs has received considerable attention, as the provision of the same educational conditions to all students, is pedagogically ineffective. In contrast, more effectively considered the pedagogical strategies that adapt to the real individual skills of the students. An important innovation in this direction is the Adaptive Educational Systems (AES) that support automatic modeling study and adjust the teaching content on educational needs and students' skills. Effective utilization of these educational approaches can be enhanced with Artificial Intelligence (AI) technologies in order to the substantive content of the web acquires structure and the published information is perceived by the search engines. This study proposes a novel Adaptive Educational eLearning System (AEeLS) that has the capacity to gather and analyze data from learning repositories and to adapt these to the educational curriculum according to the student skills and experience. It is a novel hybrid machine learning system that combines a Semi-Supervised Classification method for ontology matching and a Recommendation Mechanism that uses a hybrid method from neighborhood-based collaborative and content-based filtering techniques, in order to provide a personalized educational environment for each student.

The serendipitous discovery of antiparasitic drugs, such as quinine and artemisinin from plant origin reveals that the search for new chemical pharmacophores from medicinal plants is valuable. The present study sought to explore the antiplasmodial, antileishmanial, and antitrypanosomal activities of extracts from Lippia adoensis. Crude extracts of L. adoensis leaves and twigs, which were obtained by extraction using 70% ethanol in water, were assayed for antiplasmodial activity against P. falciparum 3D7 and Dd2 through the SYBR green I-based fluorescence assay; and for antileishmanial, antitrypanosomal, and cytotoxic effects on Leishmania donovani, Trypanosoma brucei brucei, and Vero cells, respectively, using the resazurin colorimetric assays. The phytochemical analysis of the extracts was performed using a liquid chromatography-mass spectrometry (LC-MS) feature-based detection and molecular networking flow on Global Natural Product Social (GNPS). As a result, the crude extracts from L. adoensis inhibited growth of P. falciparum (3D7 and Dd2) (IC50s; (3D7): 10.008 and 97.467 μg/mL; (Dd2): 29.48 and 26.96 μg/mL), L. Donovani (IC50s: 22.879-10.522 μg/mL), and T. brucei brucei (IC50s: 2.3085-55.06 μg/mL). The extracts were found to be non-cytotoxic to Vero cells, thus yielding median cytotoxic concentrations (CC50s) above 100 μg/mL. The LC-MS tandem molecular networking flow predicted that the extracts contain valsafungin A and bacillamidin on the first cluster, and fatty acids, ketone and aldehyde derivatives on the second cluster. Overall, the present study demonstrated the antiparasitic effects of L. adoensis extracts, thus justifying the use of this plant in the traditional treatment of fever and malaria conditions. Nevertheless, detailed metabolomic studies and antiparasitic mechanisms of action of the extracts are expected to unveil the potential antiparasitic hit compounds.

Circular economy has recently emerged as a key strategy for promoting sustainability and reducing waste in various industrial sectors. This paper provides an overview of circularity in aerospace, wind energy, transportation, automotive and sports goods using data and information from the literature and the EC funded project "RECREATE". The survey reviews the different definitions, assessment methods and metrics used to explore and evaluate circularity, including assessment frameworks such as Life Cycle Assessment (LCA) and assessment indicators. Furthermore, explores the challenges, possibilities and the available tools for enhancing circularity, such as digital tools. The survey highlights the importance of a holistic and systemic technique to circularity, concerning all stakeholders along the value chain. Overall, this study aims to contribute to a better understanding of circular economy and provides insights for future research.

Due to its high short-term global warming potential (GWP) compared to carbon dioxide, methane (CH₄) is a considerable agent of climate change. This research is aimed at analyzing data on methane gathered at the GAW (Global Atmosphere Watch) station of Lamezia Terme (Calabria, Southern Italy) spanning seven years of continuous measurements (2016-2022) and integrating the results with key meteorological data. Compared to previous studies on detected methane mole fractions at the same station, daily-to-yearly patterns have become more prominent thanks to the analysis of a much larger data set. Overall, the yearly increase of methane at the Lamezia Terme station is in general agreement with global measurements by NOAA, though local peaks are present, and an increase linked to Covid-19 is identified. Seasonal changes and trends have proved to be fully cyclic, with the daily cycles being largely driven by local wind circulation patterns and synoptic features. Outbreak events have been statistically evaluated depending on their weekday of occurrence to test possible correlations with anthropic activities. A cross analysis between methane peaks and specific wind directions has also proved that local sources may be deemed responsible for the highest mole fractions.

The effects of wastewater step-feeding on the performance of Horizontal Subsurface Flow Constructed Wetlands (HSF CWs) are numerically investigated. The purpose is to check if this alternative feeding technique increases the ability of HSF CWs to remove pollutants. Two methodologies are used: Initially, the Tanks-In-series (TIS) methodology, based on Finite Volume Method (FVM), is analyzed by using the volumetric degradation coefficient λ. In this case the operation of CW is similar with a series of Continuous Stirred-Tank Reactors (CSTR), under steady conditions. Then, the Step-Feeding (SF) procedure is presented, when the CW is operated like a Plug Flow Reactor (PFR). The results show that the SF procedure does not improve the performance of HSF CWs on removing Biochemical Oxygen Demand (BOD), operating under Mediterranean conditions.

Diarrhea remains one of the leading causes of mortality worldwide, especially among children. Recent epidemiological studies conducted in developing countries identified Shigella species as the most predominant pathogenic bacteria responsible for diarrhea. Antimicrobial therapy is necessary for Shigella infections; however, the rapid emergence of resistance against existing antimicrobials in Shigella spp. poses a serious global health problem. To identify alternative antimicrobial compounds with activity against Shigella species, the pathogens responsible for bacterial diarrhea. In this study, we have applied antibacterial phenotypic screening to identify potent anti-Shigella compounds across a broad chemical diversity, including selected acetaminophen derivatives containing benzothiazoles backbone, and their combination with certain antibiotics. In continuation to our effort in searching potent antimicrobial compounds, we have found this time around that two acetaminophen derivatives containing benzothiazoles backbone (4a and 4b) could inhibit the growth of Shigella flexneri with common MIC value of 12.5 µg/ml. These compounds were established through a time-kill kinetics’ study to be bactericidal. Meanwhile, the 2-aminobenzothiazoles (1a and 1b) used for the synthesis of compounds 4 (a & b) were found to be poorly active (MIC: 100 µg/ml) against this pathogen. Combination studies of 4a and 4b with the least susceptible antibiotics (ceftriaxone and cotrimoxazole) demonstrated synergistic anti-Shigella activity. The present study demonstrates that the azobenzothiazole dyes 4 (a & b) can be repurposed as potential anti-Shigella compounds, which can serve as scaffolds for the development of new agents against infectious diarrhea caused by Shigella and other enteric pathogens, especially in developing countries.

This is the second of a two-paper series describing a multi-scale modeling approach developed to simulate crack sensing in polymer fibrous composites by exploiting interruption of electrically conductive carbon nanotube (CNT) networks. The approach is based on the finite element (FE) method. FE models at three different scales, namely the micro-scale, the meso-scale and the macro-scale, have been developed using the ANSYS PDL environment. In the present paper, the meso- and macro-scale analyses are described. In the meso-scale, a two-dimensional model of the CNT/polymer matrix reinforced by carbon fibers is used to develop a crack sensing methodology from a parametric study which relates the crack position and length with the reduction of current flow. In the meso-model, the effective electrical conductivity of the CNT/polymer computed from the micro-scale is used as input. In the macro-scale, the final implementation of the crack sensing methodology is performed on a CNT/polymer/carbon fiber composite volume using as input the electrical response of the cracked CNT/polymer derived at the micro-scale and the crack sensing methodology. Analyses have been performed for cracks of two different lengths. In both cases, the numerical model predicts with good accuracy both the length and position of the crack. These results highlight the prospect of conductive CNT networks to be used as a localized structural health monitoring technique.

The study of the impact of polyQ expansion driven proteotoxicity on cell metabolism has evi-denced NAD molecule as a central player in regulating metabolic response and cell repair in neurodegeneration. The decline in NAD intracellular levels represents a hallmark of ageing aris-ing from a dysregulation between NAD-consuming and biosynthetic enzymatic reactions in which NMNAT plays a key role. By an integrated bioanalytical and proteomic experimental design, the derangement of NAD metabolism deriving from the accumulation of polyQ-Htt protein has been analysed in Saccha-romices cerevisiae harbouring a 103Q-Htt and compared with wild-type Htt, in absence and in presence of a phenolic extract from EVOO, as a source of antioxidant bioactive compounds. Quantification of NAD and its precursors and proteomic analysis of the differential protein ex-pression has been performed by LC-DAD-MS. Chronological lifespan and NAD homeostasis was strongly impaired by proteotoxic polyQ-Htt, eliciting a depletion of NAD levels and accumulation of NaMN. In parallel a downregulation of Sirt2 expression levels has been observed. Phenolic extract administration had no meaningful ef-fects on NAD replenishment to prevent proteotoxicity. NaMN can represent a biomarker of accel-erated aging, and/or a signaling molecule for cell repair.

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

Oxidative stress plays an essential role in the pathological processes that trigger various chronic liver diseases and contributes to the development of hepatocarcinogenesis. Antioxidants from natural sources trap free radicals by converting them into non-harmful products and minimize oxidative stress, playing a crucial function in the treatment of free radical-induced diseases. However, the activity of these antioxidants is limited due their poor bioavailability, which is why various nano-drug delivery systems have been developed to improve their stability, promote smooth release, and targeted delivery for liver cancer treatment. Specifically, this review aims to report recent scientific findings of novel nano-formulations containing natural antioxidant molecules targeted for the treatment of liver cancer.

Photovoltaic modules should pass series of tests and examinations, verifying the electrical and thermal characteristics of the module, before being released to the market, examining the properties of the modules should undergo appropriate durability and efficiency tests under real outdoor conditions with exposure to climatic conditions and under laboratory conditions. The performance of photovoltaic cells depends on many factors, such as solar irradiance, module operating temperature, installation location, weather conditions and module shading. In this paper, three selected photovoltaic modules were examined using a large-scale steady-state solar simulator. The current-voltage (I-V) characteristics of the photovoltaic modules were experimentally tested and analyzed. The next step was to implement a three-layer artificial neural network model (MLP). The experimental data obtained in the previous step coupled with output data from MLP were then used in global sensitivity analysis (GSA). Experiments carried out on a large-scale stationary solar simulator showed differences between the values declared by the manufacturer and the values obtained from measurements of PV modules. The first module tested achieved the maximum power point greater than that specified by the manufacturer, while the other two showed power drops; it was 85-87% for the second module, and 95-98% for the third, respectively. The performed global sensitivity analysis (GSA) for the MLP model showed that the parameters: eff (22.9) and Voc/V (14.19) have the largest effect on the power-voltage relationship, while U (7.29) has the smallest effect. The usefulness of machine learning (ML) methods in the comparative analysis of PV modules has been proved.

Crystalline silver thin layers were obtained by high-energy pulsed laser ablation without heating of the deposition substrate. The fluid Plateau-Rayleigh (PRI), Rayleigh – Taylor (RTI) and Richtmyer – Meshkov (RMI) instabilities, as well as crown splash induced during pulsed laser deposition (PLD) in high energy regime, resulting in ring and pearl shaped structures, offer the benefit of increased sorption surface. These morphological structures obtained for the silver thin layers make them of interest for catalytic applications. The study presented with this work addresses both the fundamental and applied issues on the morphological structures obtained for the silver thin layer and their catalytic function in organic processes. In this sense, the catalytic action of the thin silver layer was highlighted by modifications of the Reactive Blue 21 dye (C.I.) in aqueous solution with sodium bicarbonate. Specific investigations and analyzes were carried out by electron microscopy and elemental analysis (SEM-EDX), atomic force microscopy (AFM) and profilometry, mass spectrometry, ablation plasma diagnosis, diffractograms (XRD), as well as IR spectroscopy (FTIR). In addition to the experimental investigation and analyzes, simulation of the ionization energy threshold was conducted in COMSOL for complementary evaluation on the involved processes and phenomena.

Hybrid materials are a recent addition in the field of Restorative Dentistry for computer-assisted design/ computer-assisted manufacturing (CAD/CAM) indirect restorations. The long–term clinical success of modern dental restorative materials follows a multifactorial pattern. Among the characteristics, affecting the longevity of a restoration, mechanical properties and physicο – chemical interactions are of utmost importance. While numerous researchers constantly evaluate the mechanical properties, the biological background of resin–based CAD/CAM biomaterials is scarcely investigated and, therefore, less described in the literature. This review aims to analyze the biofilm formation on the surfaces of novel hybrid, resin–based CAD/CAM materials and evaluate the methodological protocols followed to assess microbial growth. It is demonstrated that the surface structure, the composition and the finishing and polishing procedures on the surface of a dental restorative material influence the initial bacterial adhesion; however most studies focus on in vitro protocols, whereas in vivo and/or in situ research of microbiomics in CAD/CAM restorative materials is lacking, obstructing in that manner the accurate understanding of the bioadhesion phenomenon in the oral cavity.

This article aims to analyze the relationship between non-obstructive coronary artery disease (NOCAD) and atrial fibrillation (AF), exploring the underlying pathophysiological mechanisms and implications for clinical management. NOCAD and AF are prevalent cardiovascular conditions that often coexist, yet their interrelation is not well understood. NOCAD, characterized by the presence of atherosclerotic plaques without significant luminal stenosis, can lead to ischemic necrosis of cardiomyocytes and their replacement with fibrous tissue, in this way sustaining the focal ectopic activity in atrial myocardium. Atrial fibrillation, on the other hand, is the most common sustained cardiac arrhythmia, associated with an increased risk of stroke and heart failure, which may accelerate atherosclerosis and may increase oxygen consumption in the myocardium, creating a mismatch between supply and demand, thus promoting the development or worsening of coronary ischemia. Therefore, NOCAD and AF seems to be a complex Interplay with one begets another.

The thermal insulation properties of building walls are critical to the overall energy efficiency and comfort of a building. One important factor that can affect these properties is the type of bricks used in construction. Bricks can vary in their geometry and thermal coefficient, which can impact their ability to transfer heat through the wall. The geometry of a brick can affect its thermal properties by altering the amount of air trapped within it and the surface area available for heat transfer. Hollow bricks or those with complex geometries may have lower thermal conductivity than regular solid bricks due to the air pockets trapped within them. Conversely, larger surface areas on the exterior of the brick can increase heat transfer. The thermal coefficient of clay, a common material used in brick production, is another important factor. Clay has a relatively low thermal conductivity, meaning it is a poor conductor of heat. However, the quality of the clay, as well as the firing temperature and duration used in brick production, can impact its thermal coefficient. Higher firing temperatures and longer firing times can result in a more compact and dense clay brick, which can improve its thermal properties. In summary, the thermal insulation properties of building walls can be significantly affected by the type of bricks used in their construction. It is important to consider the geometry and thermal coefficient of the bricks when designing a building to achieve the desired level of thermal insulation. By selecting bricks with appropriate properties, designers can help to improve the energy efficiency and comfort of the building while reducing its environmental impact.

Atrial fibrillation has progressively become a more common reason for emergency de-partment visits, representing 0.5% of presenting reasons. Registry data have indicated that about 60% of atrial fibrillation patients who present to the emergency department are admitted, emphasizing the need for more-efficient management of atrial fibrillation in the acute phase. Management of atrial fibrillation in the setting of emergency department varies between countries and health care systems. The most plausible reason to justify a conservative rather than aggressive strategy in the management of atrial fibrillation is the absence of specific guidelines from diverse societies. Several trials of atrial fibrillation treatment strategies, including cardioversion, have demonstrated that atrial fibrillation in emergency department can be treated safely and effectively, avoiding admission. In the present study, we review the epidemiology and characteristics of atrial fibrillation pa-tients presenting to the emergency department will be reviewed, as well as the impact of diverse management strategies on atrial fibrillation-related hospital admissions. Lastly, the design and initial data of the HEROMEDICUS protocol, which constitutes an elec-trophysiology-based aggressive rhythm control strategy in patients with atrial fibrillation in the emergency department setting will be presented.

A simple protocol for preparation of O-acylated enol form - (R/S)-ethyl-2-acetoxy-4-phenyl-4H-chromene-3-carboxylate 5 was presented. The compound was characterized by 1H-, 13C-and DEPT135 NMR spectra, including {1H,1H} COSY, {1H,13C} HSQC, {1H,13C} HMBC and 2D-NOESY spectra. The preferred regioselectivity for O-acylation of 3,4-dihydrocoumarin 5 in the presence of substituent in 4-th position in the chroman ring and accounting the steric hindrance of the ester group in 3-th place was confirmed.

Background: Despite advances in the treatment of hepatocellular carcinoma (HCC) over the last few decades, treatment opportunities for patients with HCC remain limited. HCC is the most common form of liver cancer, accounting for approximately 90% of all cases worldwide. Moreover, apart from the current pharmacological interventions, hepatic resection and liver transplantation are the mainstay curative approaches for patients with HCC. Methods: This systematic review included phase I, II, III, and IV clinical trials (CTs) and randomized controlled trials (RCTs) on current treatments for patients with HCC in an Asian population (2013–2023). A total of 427 articles were screened, and 184 non-duplicate publications were identified. After screening titles and abstracts, 96 publications were excluded, and another 28 were excluded after full-text screening. The remaining 60 eligible RCTs/CTs were finally included. Results: Sixty clinical trials fulfilled our inclusion criteria and screened 36 drugs as monotherapy or combination therapy for HCC. Most studies used sorafenib alone or in combination with any of the treatment regimens. Lenvatinib or atezolizumab with bevacizumab was used for HCC after initial sorafenib treatment. Eighteen studies compared the efficacy of sorafenib with that of other drugs, including lenvatinib, cabozantinib, tepotinib, tigatuzumab, linifanib, erlotinib, resminostat, brivanib, tislelizumab, selumetinib, and refametinib. Conclusion: This study provides comprehensive insights into effective treatment interventions for HCC in Asian populations. The overall assessment indicated that sorafenib alone or in combination with atezolizumab and bevacizumab has been the first treatment choice in the past decade to achieve better outcomes in patients with HCC in an Asian population

The aim of this randomized controlled clinical trial was to compare the 2-year clinical performance of resin composite restorations placed at non-caries cervical lesions (NCCL) with one-step self-etch, total-etch, and selective enamel etch & self-etch adhesive techniques. Thirty-two patients received three resin composite restorations each at NCCLs (Tetric EvoCeram/Ivoclar/Vivadent), bonded with a total-etch adhesive agent (ExciTE F/Ivoclar/Vivadent) and a self-etch (AdheSE One F/Ivoclar/Vivadent) without and with selective enamel etching. All restorations were evaluated by two examiners at baseline, 6-, 12-, 18- and 24-months post-operation regarding retention, caries occurrence, marginal adaptation, and marginal staining. A logistic regression analysis with generalized estimating equations was used. After 2 years, the retention rate was 86,8% for total-etch, 92.26% for self-etch, and 93.63% for selective enamel etching & self-etch. No caries were detected during all the restorations. Concerning marginal adaptation, the clinically perfect restorations were 26.9% for the total-etch technique, 16% for self-etch, and 25,9% for selective enamel etch & self-etch. All three adhesive strategies provided restorations with no significant differences in the retention rate and the marginal adaptation, whereas the total etch yielded better performance for marginal staining. All the restorations were assessed as clinically acceptable after 2 years.

“Pecorino” is a typical semi-hard cheese obtained with raw or heat-treated sheep milk using procedures to valorize the raw material's chemical and microbiological properties. In the present study, using a high throughput method of 16S rRNA gene sequencing, we assessed the evolution of the microbiome composition from milk to Pecorino cheese in artisanal processes using milk from Comisana and Lacaune sheep breeds. The comparative analysis of the bacterial com-munity composition revealed significant differences in the presence and abundance of specific taxa in the milk microbiome of the Comisana and Lacaune breeds. NGS analysis also revealed differences in the curd microbiome related to dairy farming practices, which have a relevant effect on the final structure of the Pecorino-cheese microbiome.

Background and Objectives: Recent studies have focused on the association between the risk of diabetic retinopathy (DR) and rs1501299 and rs2241766 polymorphisms of the ADIPOQ gene, whereas their results remain inconclusive. Thus, a systematic review and meta-analysis was car-ried out to clarify the role of these polymorphisms in the development of DR. Materials and Methods: A systematic research of electronic databases (PubMed, Scopus, and Cochrane Library) was conducted until June 16, 2023, and a reference list of relevant articles was collected, which explored the association between rs1501299 and rs2241766 polymorphisms of the ADIPOQ gene and the risk of DR. The pooled odds ratios (OR) and 95% confidence intervals (CI) were estimated via random-effects model and the meta-analysis was implemented by using Review Manager 5.4. Results: In total, 6 out of 178 studies, with 1,888 cases (DR) and 2,285 controls (without DR), were included in the meta-analysis. A statistically significant association between rs1501299 poly-morphism and DR risk was recorded in G vs. T in the overall analysis (OR=0.84, 95% CI=0.72-0.99, p=

(1) Background: A wide literature based on loading and unloading bending tests has been carried out over the half past century for assessing the force released by superelastic wires. The aim of this investigation is not only to characterize a broadly described superelastic NiTi and a novel CuNiTi archwire, but also to provide novel insights into the load vs deflection profiles. A harmonic scenario for superelastic wires will be shown as temperature is kept constant at 37°C. However, a completely different picture will be highlighted as a temporary heating step up to 50°C is introduced within the force vs deflection profiles. (2) Methods: A variety of NiTi and a novel CuNiTi round and rectangular cross-section archwires have been investigated. Static 3-point bending tests up to a deflection level of 3.0 mm have been carried out for detecting the unloading force plateau levels occurring at 37°C. A hold deflection step of 5 min at deflection levels occurring along the unloading plateau extension is introduced. The effect of a temporary heating up to 50°C on the force plateau level released by the investigated wires is analyzed. (3) Results: Mechanical profiles suggest that the plateau force levels detected at 37°C are consistent with those broadly reported in the literature, but they only represent a single block puzzle of the force scenario that a superelastic wire releases during the orthodontic treatment. (4) Conclusions: Once a superelastic wire is bent and clinically applied, the effect of a temporary heating up to 50°C (e.g. hot food or drink ingestion) produces a significant plateau force increase whose magnitude depends on the deflection level. The highest force increase of about 50% and 40% have been detected at deflection levels located at the beginning of the unloading plateau extension for NiTi and CuNiTi wires, respectively.

MicroRNAs are small non-coding RNAs, which contribute to the regulation of many physiolog-ical and pathological processes. Conventionally, miRNAs perform their activity in the cyto-plasm, where they regulate gene expression by interacting in a sequence-specific manner with mature messenger RNAs. Recent studies point to the presence of mature miRNAs in the nucleus. This review summarizes current findings regarding the molecular activities of nuclear miRNAs. These molecules can regulate gene expression at the transcriptional level by directly binding DNA on the promoter or the enhancer of regulated genes. MiRNAs recruit to these regions dif-ferent protein complexes, resulting both in activation or repression of transcription, through a number of molecular mechanisms. Haematopoiesis is presented as a paradigmatic biological process whereby nuclear miRNAs possess a relevant regulatory role. Nuclear miRNAs may af-fect gene expression also acting on nuclear mRNA processing and on the biogenesis of miRNA themselves by regulating pri-miRNA maturation. Overall, nuclear miRNAs are biologically ac-tive molecules that can be critical for the fine tuning of gene expression and deserve further studies in a number of physiological and pathological conditions

Organisms are adapted to each other and the environment, not as tradition would have it, because natural selection made them that way, but because there is inbuilt striving towards stability and equilibrium. A General Theory of Behaviour connects imagery, affect and action with the central executive system we call Consciousness. The General Theory is founded on the assumption that the primary motivation of all of Consciousness and intentional behaviour is Psychological Homeostasis. Psychological homeostasis is as important to the organisation of mind and behaviour as Physiological Homeostasis is to the organisation of bodily systems. Consciousness processes quasi-perceptual images independently of the input to the retina and sensorium. Consciousness is the “I-Am” control centre for integration and regulation of (my) thoughts, (my) feelings and (my) actions with (my) conscious mental imagery as foundation stones. Imagery vividness, a combination of clarity and liveliness, is essential to imagining, remembering, thinking, predicting, planning and acting. Assessment of vividness using introspective report is validated by objective means such as fMRI. A significant body of work shows that vividness of visual imagery is determined by the similarity of neural responses in imagery to those occurring in perception of actual objects and performance of activities. I am Conscious, therefore I am.

Most cervical cancer cases are a result of persistent high-risk Human papillomavirus (HPV) infections. Cervical cancer is prevalent in LMICs especially in SSA where it is second most prevalent cancer. In South Africa, it is the second most common cancer affecting women aged between 15 and 44 years. The host immune response has been shown as an important factor in controlling the progression or regression of high-risk HPV infection of the cervix to cervical cancer. The risk of cervical cancer is known to be influenced by the host's genetic diversity, particularly by immune response-regulating genes such as the Human Leukocyte Antigen (HLA) class I and II genes. HLA class I genes present viral peptides to CD8+ T cells which are restricted and pre-programmed for cytotoxic functions. There is very little known about the HLA genes of South African women and how these influence outcome of HPV infections. This review aims to understand the role and influence of HLA class I genes in HPV clearance, persistence, and CD8+ T cell mediated immunity in African women by examining existing literature in this area. Understanding this role can influence and inform therapeutic vaccine design that is population specific.

The Upper Hunter Valley is a major coal mining area containing approximately 40% of the currently identified total coal reserves in New South Wales (NSW), Australia. Due to the ongoing increase of mining activities, PM10 (air-borne particle with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. This paper summarises the spatial and temporal variability modes of PM10 pollution in the region, based on long-term multi-site monitoring data and the application of the rotated principal component analysis (RPCA) and wavelet analysis techniques. RPCA identified two distinct air quality clusters/subregions in the valley, one in the west/northwest, the other in the southeast. Wavelet analysis revealed the annual cycle to be most persistent temporal mode of PM10 variability in both subregions, with intermittent signals observed at time scales of around 120, 30~90 and under 30 days. How these variation modes are related to the effects of local PM10 emissions and the influence of meteorology at different time scales deserves further attention in future work. The findings will be used in air quality reporting and forecasting in NSW. The methodology and results can also be useful for air quality research in similar regions elsewhere.

The financial crisis augmented the need to predict real estate prices. The current study examines the application of Artificial Neural Network (ANN) model and Vector Autoregressive (VAR) model in forecasting real estate prices. The study uses daily observations, which accounted for a total of 2955 observations collected. We found that ANN outperformed significantly the VAR model providing evidence that these models can be used for valuation purposes in the area of real estate and financial markets. These findings are novel and important as they provide evidence of the usefulness of more sophisticated methodologies for market participants and regulators in real estate and financial markets.

Here we present 1. a model for amplicon sequencing 2. a definition of the best assignment of a read to a set of reference sequences 3. strategies and structures for indexing reference sequences and computing the best assign- ments of a set of reads efficiently, based on (ultra)metric spaces and their geometry The models, techniques, and ideas are particularly relevant to scenarios akin to 16S taxonomic profiling, where both the number of reference sequences and the read diversity is considerable.

Thermoplastic composites are continuously replacing thermosetting composites in lightweight structures. However, the accomplished work on the fatigue behavior of thermoplastics is quite limited. In the present work, we propose a numerical modeling approach for simulating fatigue delamination growth and predicting the residual tensile strength of quasi-isotropic TC 1225 LM PAEK thermoplastic coupons. The approach is supported and validated by tension and fatigue (non-interrupted and interrupted) tests. Fatigue delamination growth is simulated using a mixed-mode fatigue crack growth model, which is based on the cohesive zone modeling method. All interfaces between the thermoplastic plies were modelled using cohesive elements. Quasi-static tension analyses on pristine and fatigued coupons were performed using a progressive damage model implementing a set of Hashin-type strain-based failure criteria and a damage mechanics-based material property degradation module. Using the fatigue model, delamination growth was predicted as a function of number of cycles at all interfaces. The results agree well with C-scan images taken on fatigued coupons during interruptions of fatigue tests. An unequal and unsymmetric delamination growth was predicted due to the quasi-isotropic lay-up. Moreover, the combined models capture the decrease in the residual tensile strength of the coupons. In the quasi-static tension analysis of the fatigued coupons, the driving failure mechanisms are the fast propagation of the pre-existing delamination and the severe matrix cracking.

Drosophila melanogaster serves as a important research model both for genetic investigations and for the study of metal toxicity, facilitating the elucidation of physiological mechanisms comparable to those of human organisms. In our research, we evaluated the toxicity effect resulting from exposure to various concentrations of lead and copper on the prolificity rates throughout the life cycle (egg-adult) of four genotypes of Drosophila melanogaster: wild-type (control), white, brown, and white-vestigial. During our study, the prolificity rates were examined across three repetitions under the impact of exposure to concentrations of 0.50, 1.00, 2.00, and 4.00 mM of copper (CuSO₄) and lead (Pb(C₂H₃O₂₎₂). Prolificity rates throughout the life cycle exhibited variations as a direct consequence of genetic factors, the concentration of exposure, and the specific type of metal, either copper or lead. The mutant white-vestigial genotype revealed an IC₅₀ concentration for prolificity inhibition at lower doses of 2.00 mM for copper and 4.00 mM for lead, in contrast to the control genotype (wild-type), which exhibited an inhibition concentration rate >IC₅₀ of 4.00 mM only in the case of copper. Our results concluded that the (i) dose influences the prolificity rate in a directly proportional manner, (ii) comparative analyses between copper and lead revealed that copper displayed toxicity across all genotypes within the concentration range of 0.50 mM to 2.00 mM. In contrast, lead exhibited toxicity within the concentration range of 1.00 mM to 4.00 mM, highlighting a (iii) more acute toxicity characteristic in the case of copper. Thus, the results of this research reflect the importance of using Drosophila melanogaster as a genetic model in the comparative study of the interaction between genetic factors and the toxicity of metals, offering significant insights into monitoring their impact and defining the maximum permissible doses on organisms.

Standard Non-Melanoma Skin Cancer (NMSC) treatment involves surgery, recently combined with chemotherapy or immunotherapy in case of advanced tumors. Exosomes, integral to carcinogenesis, are found in NMSC, releasing mediators impacting tumor progression. Nevertheless, the precise intercellular signaling role of NMSC-derived exosomes remains unclear. This review aims to elucidate their potential role in NMSC diagnosis and treatment. A systematic review encompassed literature searches in electronic databases from inception to September 2023, based on certain inclusion and exclusion criteria, addressing NMSC-derived exosomes, their molecular cargo and their implications in the diagnosis, prognosis, and treatment of NMSC. Key components were identified. Extracellular vesicle (EV) proteins and RNA emerged as diagnostic biomarkers in EV-based liquid biopsy. Circular RNA CYP24A1, known for its molecular stability, holds promise as a diagnostic biomarker. Long noncoding RNAs (lincRNA-PICSAR) and Desmoglein 2 (DSg2) are linked to drug resistance, serving as prognostic biomarkers. EV mediators are actively investigated for their potential role as drug delivery agents. In conclusion, this systematic review showed that NMSC-derived EVs display promise as therapeutic targets and diagnostic biomarkers. Further research is imperative to fully comprehend exosome mechanisms and explore their potential in cancer diagnosis and treatment.

The Predicted Mean Vote (PMV) and the Predicted Percentage of Dissatisfied (PPD) indices are used to assess the indoor environment in terms of human thermal comfort-discomfort. In this study, an experimental combined objective and subjective investigation of thermal comfort perception has been performed in students between 16-18 years old, in a non-air-conditioned school building. The objective approach included instrumentation measurements and data processing according to ISO 7730, whereas, the subjective one was based on answers collection following ISO 10551. The study is mainly devoted to the verification of Fanger’s approach in a building, in free running conditions, under a mild (moderate) climate.The comparison between instrumentation data and questionnaire results presented an underestimation of the mean vote, predicting a cooler sensation than the actual one.

Predicting the prices of cryptocurrency owing to its volatility, instability, and other factors has been challenging; investors and traders especially in Nigeria have been on a constant look for a more reliable way of knowing market trends and prices and while there has been so many research conducted using deep learning, the results for which has fall short of what investors could called a strong predictor. This research reviewed the results of many works that had been done and proposed two types of recurrent neural network (RNNs) namely Long Short-Term Memory and Gated Recurrent Unit (GRU) for predicting the future prices of two of the most common crypto assets namely Bitcoin (BTC) and Ethereum (ETH), these two were selected based on their popularity, the volume traded and their market capitalization. The experiment was conducted in a GPU Jupyter Notebook environment and the performance of our experiment was evaluated on a test set using root mean square error (RMSE) and based on its values, the LSTM presented a better performance with rsme scores of 654.66, and 80.30 respectively for BTC and ETH as compared to GRU. The paper proceeds further to compare the results of this experiment with other related works and we discovered that its performance is a great improvement.

Cotton cationization with low molecular-weight/polymeric cationic modifiers allows the effective dyeing of fabrics with reactive dyes under salt-free and more environmentally-friendly conditions. The current work focuses on the spectroscopic study of the intermolecular interactions, which dictate the physicochemical process associated with dyeing. Water-soluble copolymers of vinyl benzyl chloride and vinyl benzyl triethylammonium chloride (VBCTEAM) have been used as cellulose cationic modifiers. Dye uptake was assessed using Remazol Brilliant Blue and Novacron Ruby dyes. The study involves ATR-FTIR, UV-Vis, fluorescence and XPS spectroscopy. The results of binary polymer-rich dye-polymer aqueous solutions or dye-polymer precipitates at stoichiometric charge-ratio revealed that the sulfonate/sulfate anions of the dyes interact with the cationic VBCTEAM units of the polymer via electrostatic interactions. Moreover, the comparative study of unmodified/modified dyed cotton indicates that the dye reactive sites remain unaffected for cationized cotton, suggesting that electrostatic interactions are the main driving force for the high dyeing performance observed.

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

Wavelength selective switches (WSSs) are essential elements for wavelength division multiplexing (WDM) optical networks, as they offer cost-effective, high port-count and flexible spectral channel switching. This work proposes a new hybrid WSS architecture that leverages the beam shaping and steering features of uniform silicon nitride (SiN) based end-fire optical phased arrays (OPAs). By introducing beamforming to a WSS system, the spectral channels on the liquid crystal on silicon (LCoS) panel can be tailored and arranged properly, depending on the optical configuration, using the beam control capabilities of OPAs. Combining 3D-FDTD and ray tracing simulations, the study shows that by reducing the input beam dimensions with proper sizing of the OPAs, the WSS design with the null-steering OPAs layout and 4×No switch size features increased spectral resolution. This extensive beamforming study on the steering-enabled layout reveals the acquirement of an even higher input channel number, achieving up to the 8×No WSS scheme with flexible channel routing on the LCoS panel. Such implementation of beamsteerers can unlock an extra degree of freedom for the switching capabilities of hybrid WSS devices. The results show great promise for the introduction of OPAs in WSS systems and provide valuable insight for the design of future wireless communication links and WDM systems.

Background and Objectives: Previous studies revealed anti-angiogenic, antiproliferative and anti-inflammatory effects of Vitamin D on cancer cells. Although this body of evidence supported the correlation of high Vitamin D levels with reduced incidence rates for various malignancies, contradictory results were reported regarding non-melanoma skin cancer (NMSC). Aim of this overview was to summarize the available evidence from the existing pool of systematic reviews and meta-analyses, focusing on Vitamin D serum status, dietary intake, and Vitamin D receptor (VDR) polymorphisms in correlation to NMSC incidence. Materials and Methods: A literature search in electronic databases was conducted from inception to January 2023. Inclusion criteria were systematic reviews and meta-analyses published in peer-reviewed journals, evaluating Vitamin D serum levels, dietary and/or supplementary intake, or VDR gene polymorphisms, and reporting data on NMSC. Results: A total of 10 studies were included in the data analysis models. A positive association between Vitamin D serum levels and NMSC is highlighted. However, dietary/supplementation of Vitamin D doesn’t exhibit a likewise strong linkage to NMSC. Despite the contradictory findings, VDR polymorphisms may play a crucial role in the intricate NMSC pathogenesis. Conclusions: This umbrella review showed that high Vitamin D levels are associated with increased NMSC incidence, potentially due to its direct correlation with increased sun exposure. Further research on VDR polymorphisms is suggested to explore their true effect size on NMSC risk.

Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) frequently require primary radiochemotherapy (RCT). Despite intensity-modulation, desired radiation-induced effects observed in HNSCC, may also be observed as side-effects in healthy tissue e.g. the sternocleidomastoideus muscle (SCM). These side-effects (e.g. tissue fibrosis) depend on the interval between completion of RCT and restaging-CT. For salvage surgery, the optimal time window for surgery is currently postulated between 6 and 12 weeks after completion of RCT. Thus, no extensive tissue fibrosis is to be expected. This interval is based on studies exploring surgical complications. Studies directly exploring radiation-induced changes of the SCM in HNSCC-patients are sparse. The present study quantifies tissue alterations in SCM and paravertebral musculature (PVM) after RCT applying radiomics to determine the optimal time window for salvage surgery. Three radiomic key parameters 1) volume, 2) mean positivity of pixels (MPP) and 3) uniformity were extracted with mint lesionTM in the staging-CTs and restaging-CTs of 98 HNSCC-patients. Of these, 25 were female, the mean age was 62 (±9.6) years and 80.9% were UICC Stage IV. The mean restaging-interval was 55 (±28; range29-229) days. Only the mean volume significantly decreased after RCT from 9.0 to 8.4 and 96.5 to 91.9 ml for SCM and PVM, respectively (both p=0.007, both Cohen’s d=0.28). In addition, the mean body mass index (BMI) decreases from 23.9 (±4.2) to 21.0 (±3.6) kg/m² (p<0.001); Cohen's d = 0.9). The mean BMI-decrease significantly correlated with the volume decrease for SCM (r=0.27; p=0.007) and PVM (r=0.41; p<0.001). If t-test p-values were adjusted for the BMI-decrease, no significant change in volumes for SCM and PVM was observed (both p>0.05). The present data supports the postulated optimal interval for salvage surgery of 6 to 12 weeks. Irrespective of the remaining risk-benefit ratio of salvage surgery, the risk of additional surgical complications due to fibrosis is not supported by the present observations.

DIEP-based breast reconstruction necessitates wide undermining at the abdominal donor-site, creating large wound areas. Flap harvesting is usually conducted using electrosurgical dissection devices. This study sought to compare the clinical outcomes in patients after using the PEAK PlasmaBlade (PPB) versus monopolar electrocautery (MPE). This retrospective cohort study included 128 patients with DIEP-based breast reconstruction. Patient characteristics as well as information on the postoperative course were collected and a comparative evaluation was conducted. The MPE group exhibited significantly (p* = 0.0324) higher abdominal drainage volume (351.11 ± 185.96 ml) compared to the PPB group (279.38 ± 183.38 ml). Subgroup analysis demonstrated that PPB significantly reduced postoperative wound fluid in patients with BMI > 30 kg/m² (p* = 0.0284), without prior neoadjuvant chemotherapy (p** = 0.0041), and among non-smokers (p = 0.0046). Furthermore, postoperative pain was significantly (p**** < 0.0001) lower in the PPB cohort. This study confirms the non-inferiority of the PEAK PlasmaBlade to conventional electrocautery for abdominal flap harvesting. The PPB demonstrated advantages, notably reduced drainage volume and lower postoperative pain levels. Recognizing patient subsets that benefit more from the PPB highlights the importance of personalized device selection based on patient characteristics.

This paper presents a numerical study on the laser shock wave propagation in a 3D woven CFRP material by means of detailed and homogenized FE models. The aim of the study is to numerically characterize the shock wave response of the 3D woven CFRP in terms of back face velocity profiles and the induced damage and to investigate whether the detailed FE models could be replaced by homogenized FE models. The 3D woven geometry was designed using the TexGen software, while the numerical analyses were executed using the LS-Dyna explicit FE software. A high-strain rate behavior was considered for the matrix. The fiber bundles in the detailed models were modeled as a high fiber content unidirectional composite laminate, with its mechanical properties calculated by micromechanical equations. Both for the fiber bundles of the detailed model and the homogenized models a progressive damage material model was applied. The results of the detailed model reveal a considerable effect of material’s architecture on the shock wave propagation and the sensitivity of the back face velocity profile to the spot location. Consequently, the homogenized model is not capable of accurately simulating the shock wave response of the 3D woven composite. Moreover, the detailed predicts with high accuracy matrix cracking in the resin-rich areas and in the bundles as well as fiber failure. On the contrary, the homogenized model predicts matrix cracking at the same areas and no fiber failure.

Solid tumors are composed of a highly complex and heterogenic microenvironment, with increasing metabolic status, playing a crucial role in the clinical therapeutic outcome of conventional treatments and innovative tumor nanomedicines. Scientists, have devoted great effort in conquering the tumor microenvironment (TME) challenges, in respect of effective drug accumulation and activity in tumor site, overcoming the obstacles of abnormal vasculature, dense stroma and extracellular matrix, hypoxia, and pH gradient acidosis. In this conquest, nanomedicines targeting distinct TME features have flourished, in order to increase site specificity and deep penetration, for effective antitumor activity, and further reprogram TME promoting suppression of cancer stem cells and metastasis. Thereby, several successful nanomedicine therapeutics have been under clinical trials, and further applied in clinical practice. Various novel strategies have been employed in preclinical studies and clinical trials, among which nanomedicines based on biomaterial, that have shown great promise in improving the therapeutic efficacy, reducing side effects, and promoting synergistic activity for TME targeting. In this review, we have focused on the targeting mechanisms for solid TME by nanomedicines based on the application of natural and synthetic biomaterials. We have described critical formulations that have been considered for the design of stimuli-responsive nanomedicines for TME. The development of such systems, has significantly advanced the application of biomaterials, in combinational therapies and in immunotherapies, for improved effectiveness.

Hateful and abusive speech presents a major challenge for all online social media platforms. Recent advances in Natural Language Processing and Natural Language Understanding allow more accurate detection of hate speech in textual streams. This study presents a multimodal approach to hate speech detection by combining Computer Vision and Natural Language processing models for abusive context detection. Our study focuses on Twitter messages and, more specifically, on hateful, xenophobic and racist speech in Greek aimed at refugees and migrants. In our approach we combine transfer learning and fine-tuning of Bidirectional Encoder Representations from Transformers (BERT) and Residual Neural Networks (Resnet). Our contribution includes the development of a new dataset for hate speech classification, consisting of tweet ids, along with the code to obtain their visual appearance, as they would have been rendered in a web browser. We have also released a pre-trained Language Model trained on Greek tweets, which has been used in our experiments. We report a consistently high level of accuracy (accuracy score=0.970, f1-score=0.947 in our best model) in racist and xenophobic speech detection.

We explore the possibility to form a physical theory in $C^4$. We argue that the expansion of our usual 4-d real space-time to a 4-d complex space-time, can serve us to describe geometrically electromagnetism and nuclear fields and unify it with gravity, in a different way that Kaluza-Klein theories do. Specifically, the electromagnetic field $A_\mu$, is included in the free geodesic equation of $C^4$. By embedding our usual 4-d real space-time in the symplectic 8-d real space-time (symplectic $R^8$ is algebraically isomorphic to $C^4$), we derive the usual geodesic equation of a charged particle in gravitational field, plus new information which is interpreted. Afterwards, we formulate and explore the extended special relativity and extended general relativity an $C^4$ or$R^8$. After embedding our usual 4-d space-time in $R^8$, two new phenomena rise naturally, that are interpreted as "dark matter" and "dark energy". A new cosmological model is presented, while the geometrical terms associated with "dark matter" and "dark energy" are investigated. Similarities, patterns and differences between "dark matter", "dark energy", ordinary matter and radiation are presented, where "dark energy" is a dynamic entity and "dark matter" reveal itself as a "mediator" betwen ordinary matter and "dark energy". Moreover, "dark matter" is deeply connected with "dark energy". Furthermore, the extended Hamilton-Jacobi equation of the extended space-time, is transformed naturally as an extended Klein-Gordon equation, in order to get in contact with quantum theories. By solving the Klein-Gordon equation analytically, we derive an eigenvalue for Higg's boson mass value at 125,173945 $Gev/c^{2}$. The extended Klein-Gordon equation, also connects Higg's boson (or vacuum) with Cosmology, due to the existence of our second "time" T (cosmological time), which serve us to connect quantum theories with Cosmology. Afterwards, in the general case, we explore the symmetries of the curved Hamilton-Jacobi equation locally, in order to investigate the consequences of a $C^4$ space-time in Standard Model. An extension to Standard Model is revealed, especially in the sector of strong nuclear field. The Stiefel manifold $SU(4)/SU(2)$ seems capable not only to describe the strong nuclear field but give us,as well, enough room to explore in the future, the possibility to explain quark confinment. Our extension, flavors firstly the unification of nuclear fields and afterwards the unification of nuclear fields with electromagnetic field. The desired grand unification, is achieved locally, through the symmetry group $GL(4,C)\simeq SO(4,4)\cap U(4)$ and we present a potential mechanism to reduce the existing particle numbers to just six. Afterwards,23 present the extended Dirac equation in $C^4$ space-time (Majorana-Weyl representation) plus a preliminary attempt to introduce a pure geometric structure for fermions. Finally, we consider a new geometric structure through n-linear forms in order to give geometric explanation for quantisation

Lightning strike can cause a considerable damage in aircraft parts made from semiconducting materials such as Carbon Fiber Reinforced Plastics (CFRPs). Therefore, in recent years, the lightning strike phenomenon has attracted the interest of the academic community and the aircraft industry. Until now, the problem has been addressed mainly experimentally, while the reported numerical works are very limited. In the present work, a coupled electro-thermal FE model has been developed using the ANSYS commercial FE code to simulate the lightning strike damage in unidirectional CFRP laminates due to the Joule heat flux phenomenon. The model is based on the SOLID69 thermoelectric element and applies a non-linear, time-transient analysis. The main input to the model is the thermal-electrical properties of the composite material which vary with temperature. Using the model, a parametric study on the effect of mesh density and peak intensity on the thermal damage has been performed. Three electrical lightning strikes of low (10 kA), medium (30 kA) and high peak intensity (40 kA) have been applied according to the SAE ARP 5412 standard. The electro-thermal model has been validated against a numerical model from the literature. The numerical results reveal that the increase of peak intensity leads to the increase of the area and penetration depth of matrix thermal damage (pyrolysis) as well as to the increase of the area of fiber damage (deterioration and ablation). Through progressive damage modeling, the residual tensile strength of the CFRP plate after being subjected to lightning strike of different peak intensity has been predicted. Lightning strike initial damage has been simulated by translating the thermal field into degradation of elastic properties of the lamina. The results show an increase in the accumulated matrix damage and a decrease of tensile strength due to the initial lightning strike damage. For the maximum peak intensity of 40 kA, a decrease in tensile strength of 4.8% has been predicted

Semantic Web technologies are being increasingly adopted by the geospatial community during last decade through the utilization of open standards for expressing and serving geospatial data. This was also dramatically assisted by an ever increasing access and usage of geographic mapping and location-based services via smart devices in people’s daily activities. In this paper we explore the developmental framework of a pure Javascript client-side GIS platform exclusively based on invocable geospatial Web services. We also extend Javascript utilization on the server side by deploying a node server acting as a bridge between open source WPS libraries and popular geoprocessing engines. The vehicle for such an exploration is a cross platform Web browser capable of interpreting Javascript commands to achieve interaction with geospatial providers. The tool is a generic Web interface providing capabilities of acquiring spatial datasets, composing layouts and applying geospatial processes. In an ideal form the end-user will have to identify those services, which satisfy a geo-related need and put them in the appropriate row. The final output may act as a potential collector of freely available geospatial web services. Its server-side components may exploit geospatial processing suppliers composing that way a light-weight fully transparent open Web GIS platform.

Shiga toxins (Stxs), and more specifically the Stx2a subtype, are the major virulence factors involved in enterohemorrhagic Escherichia coli (EHEC)-associated hemolytic uremic syndrome (eHUS); a life-threatening disease causing acute kidney injury, especially in children. Cleavage of Stxs A subunit, when followed by reduction, boosts the enzymatic activity causing damage to targeted cells. This cleavage was assumed to be mostly mediated by furin during Stx intracellular trafficking. Cleavage of A subunit, without reduction, changes the binding properties of Stxs for blood components during HUS pathogenesis. To investigate whether the cleavage could occur in the intestine, even prior entering target cells, Stx2a structure was characterized after its exposure to specific host factors present in human stool. The structure of Stx2a A subunit was determined by immunoblotting after electrophoretic separation under reducing conditions. Trypsin and chymotrypsin-like elastase 3B (CELA3B), two serine proteases, were identified as potential candidates that may trigger the extracellular cleavage of Stx2a A subunit directly after its secretion by EHEC in the gut. Whether this observation indeed translates to natural infections and plays a role in eHUS pathogenesis has yet to be determined as well as whether host's protease profile could affect disease development by changing the toxin’s biological features.

The effect of doublet state metalloradical complex in a solar cell inside the common active layer poly(3-hexylthiophene)/ [6,6]-phenyl-C61-butyric acid methyl ester (P3HT/PC60BM) is explored. In this work is demonstrated that the role of the Bis-[1,3-Bis-(2,6-diisopropylphenyl)-4,5-dichloroimidazol-2-ylidene]palladium(I) hexafluoridophosphate dopant, [Pd(IPrCl)2][PF6], is crucial because, by having a stable unpaired electron in the molecule, it significantly improves the optoelectronic performance of the devices. We found the optimal concentration of this molecule in the active layer, and we demonstrated that the presence of this additive in the active layer helps to significantly improve the morphology of the device. The improvements in optoelectronic and morphological parameters are associated with a remarkable increase of photocurrent generation due to more favourable mechanisms of charge separation at the donor/acceptor (D/A) interfaces of the active layer and reduced recombinations. Moreover, the presence of this additive improves the stability of the unencapsulated solar cell against photochemical degradation produced by sunlight.

This study investigated the influence of single nucleotide polymorphisms (SNPs) in genes asso-ciated with the interferon pathway (IFNAR2 rs2236757), antiviral response (OAS1 rs10774671, OAS3 rs10735079), and viral entry (ACE2 rs2074192) on COVID-19 severity and their association with non-alcoholic fatty liver disease (MAFLD). We did not observe a significant association between the investigated SNPs and COVID-19 severity. While the IFNAR2 rs2236757 A allele correlated with higher creatinine levels upon admission and the G allele with lower band neu-trophils upon discharge, these findings require further investigation. The distribution of OAS gene polymorphisms (rs10774671, rs10735079 did not differ between MAFLD and non-MAFLD patients. Our study population's distribution of ACE2 rs2074192 genotypes and alleles differed from the European reference population. Overall, our findings suggest that these specific SNPs may not be major contributors to COVID-19 severity in our patient population, highlighting the potential role of other genetic factors and environmental influences.

Spodoptera frugiperda is an invasive pest that has spread in various parts of the world. These pests have the ability to spread and adapt highly to new habitats. Until now, it is not known with certainty the distribution of these invasive pests in Eastern Indonesia, especially Bali and Nusa Tenggara. This study aims to map the spatial distribution and genetic distribution of S. frugiperda which damages maize in the areas of Bali and Nusa Tenggara. This research was conducted using a survey method from May to September 2022 covering the islands of Bali, Lombok, Sumbawa, Sumba, Flores, and Timor. The results showed that S. frugiperda had spread evenly in Bali and Nusa Tenggara. The results of PCR amplification in the COI gene from 9 sample isolates from all research locations showed the similarity of DNA bands leading to the Spodoptera frugiperda species with a banding pattern length of 683 – 697. These results indicated that the distribution of genetic variants of corn caterpillars in Bali, NTB, and NTT was confirmed as S. frugiperda species. However, the isolated gene S. frugiferda, which was shown by the alignment results of the sequences from Lombok, was confirmed as a different strain from strains from Bali, Sumba, Sumbawa, Flores, and Timor. This incident can be seen from the difference in the protein base composition of S. frugiperda from Bali, Sumba, Sumbawa, Timor, and Flores. The results of phylogenetic analysis in this study confirmed 3 clusters of the genetic closeness of S. frugiperda. Cluster-1 comes from the results of the search for specimens of JB FAW and KB FAW from Bali, SB FAW and SB FAW Sorghum from Sumba, SW FAW from Sumbawa, KP FAW from Timor, and FL FAW from Flores. Cluster-2 is an isolate outside of our species. Cluster-3 comes from the search for LT and LS FAW specimens from Lombok. The genetic distance between cluster-1 and cluster-3 is quite far, which is 0.20 mu.

Keywords: Pain; Nociception; Disorders of Consciousness; Consciousness

The present study aimed at investigating the in vitro and in vivo susceptibility of malaria parasites to crude extracts and fractions from Polyalthia suaveolens, Uvaria angolensis, and Monodora tenuifolia. The ethanolic extracts were prepared by maceration, and were further partitioned using water, dichloromethane, hexane, and methanol. The most promising fraction was subjected to column chromatography and the sub-fractions tested for activity in vitro. The antiplasmodial effect of extracts and fractions was tested against the Chloroquine resistant (PfK1) strain in 96 wells microtiter plate format using SYBR green florescence assay. The promising fraction was further assessed for cytotoxicity and acute toxicity in Swiss albino mice and subsequently against the rodent malaria parasite, P. berghei. Qualitative phytochemical screening was also performed on the promising fraction. The methanol fractions exerted the overall better effect with that of the twigs of P. suaveolens (PStw(Ace)) showing the highest potency with a IC50 value of 3.24 µg/mL followed by the fractions of leaf of M. tenuifolia (MoTel(Ace), IC50= 3.84 µg/ml) and stem bark of P. suaveolens (IC50= 4.90 µg/ml). The phytochemical screening showed the presence of alkaloids, lactones, and phenols in the more active fraction of P. suaveolens (PStw(Ace)). The chromatographic fractionation of this fraction led to 12 sub-fractions with PS8 sub-fraction being the most active (IC50= 4.42 µg/mL). In vivo, oral administration of 2000 mg/kg b.w of fraction PStw(Ace) in mice showed no signs of toxicity. Also, fraction PStw(Ace) at 400 mg/kg b.w exerted the highest suppressive effect against P. berghei strain B throughout the 4 days experiment (% parasitaemia below 5.2%). Overall, the results achieved supported the use of the three plants in the traditional treatment of malaria in Cameroon. More interestingly, the methanolic fraction of the twigs extract from P. suaveolens might be of interest in future development of an antimalarial phytodrug.

Sparkling wines elaborated by means Ancestral method, also called Pét-Nats, are nowadays gaining an increasing share of the market. However, the scientific information about these wines is very scarce. For that reason, the aim of this research was to compare the physicochemical composition and sensory attributes of a representative sampling of commercial sparkling wines elaborated by Ancestral and Traditional methods. Ancestral sparkling wines were more heterogenous than Traditional sparkling wines because some of them showed lower internal pressure, higher turbidity, higher colour intensity and less foamability. These differences would be probably because the ancestral elaboration protocol is not so well defined as in the case of Traditional sparkling wines. However, Ancestral method has the advantage of being able to work with riper grapes and with lower doses of sulphur dioxide.

Background and Objectives: Proper use of oral anticoagulants is crucial in the management of non-valvular atrial fibrillation (AF) patients. Left atrial appendage closure (LAAC) may be considered for stroke prevention in patients with AF and contraindications for long-term anticoagulant treatment. We aimed to assess the anticoagulation status and LAAC indications in patients with AF from HECMOS (Hellenic Cardiorenal Morbidity Snapshot) survey. Materials and Methods: HECMOS was a nationwide snapshot survey of cardiorenal morbidity in hospitalized cardiology patients. HECMOS used an electronic platform to collect demographic and clinically relevant information from all patients hospitalized on March 3, 2022, in 55 different cardiology departments. In this substudy, we included patients with known AF without mechanical prosthetic valves and moderate to severe mitral valve stenosis. Patients with prior stroke, previous major bleeding, poor adherence to anticoagulants, and end-stage renal disease were considered candidates for LAAC. Results: Two hundred fifty-six patients (mean age 76.6±11.7, 148 males) were included in our analysis. Most of them (n=159; 62%) suffered from persistent AF. Mean CHA2DS2-VASc score was 4.28±1.7, while mean HAS-BLED score was 1.47±0.9. Three out of 3 patients with a CHA2DS2-VASc 0 or 1 (female) received improperly anticoagulants. Sixteen out of 18 patients with a CHA2DS2-VASc 1 or 2 (female) received anticoagulants. Thirty-three out of 235 patients with a CHA2DS2-VASc &gt; 1 or 2 (for female) did not receive improperly anticoagulants. Among 221 under anticoagulant therapy, 191 (86.4%) received non-vitamin K antagonist oral anticoagulants (NOACs) and 30 (13.6%) received vitamin K antagonists. Relative indications for LAAC were present in 64 patients with NVAF (60 had only one risk factor and 2 had two concurrent risk factors). In detail, 36 had a prior stroke, 17 patients had a history of major bleeding, 15 patients reported poor or no adherence to the anticoagulant therapy and 5 had eGFR&lt; 15 ml/min/1.73m2. Moreover, 33 had a HAS-BLED score ≥3. No LAAC treatment was recorded. Conclusions: Anticoagulation status was nearly optimal in a high thromboembolic risk population of cardiology patients, mainly treated with NOACs. One out of four AF patients should be screened for LAAC.

Breast cancer is the most common cancer in women globally, often necessitating mastectomy and subsequent breast reconstruction. Silicone mammary implants (SMIs) play a pivotal role in breast reconstruction, yet their interaction with the host immune system and microbiome remains poorly understood. This study investigates the impact of SMI surface topography on host antimicrobial responses, wound proteome dynamics, and microbial colonization. Biological samples were col-lected from ten human patients undergoing breast reconstruction with SMIs. Mass spectrometry profiles were analyzed for acute and chronic wound proteomes, revealing a nuanced interplay between topography and antimicrobial respondseproteins. 16S rRNA sequencing assessed mi-crobiome dynamics, unveiling topography-specific variations in microbial composition. Surface topography alterations influenced wound proteome composition. Microbiome analysis revealed heightened diversity around rougher SMIs, emphasizing topography-dependent microbial inva-sion. In vitro experiments confirmed staphylococcal adhesion, growth, and biofilm formation on SMI surfaces, with increased texture correlating positively with bacterial colonization. This comprehensive investigation highlights the intricate interplay between SMI topography, wound proteome dynamics, and microbial transmission. The findings contribute to understanding host-microbe interactions on SMI surfaces, essential for optimizing clinical applications and minimizing complications in breast reconstruction.

HLA class-I (HLA-I) polyreactive monoclonal antibodies (mAbs) reacting to all HLA-I alleles were developed by immunizing HLA-E monomeric heavy chain (HC) (Open Conformers, OCs). Two of the mAbs (TFL-006 and TFL-007) bound to the HC’s coated on a solid matrix. The binding was inhibited by a peptide 117AYDGKDY123, present in all alleles of the six HLA-I isoforms but masked by 2-microglobulin -m) in intact HLA-I trimers (Closed Conformers, CCs). Identical HLA-I polyreactivity is observed in IVIg administered to lower anti-HLA antibodies (Abs) in HLA-sensitized patients, but the mechanism is unknown. We hypothesized that the mAbs that mimic IVIg HLA-I polyreactivity might mimic the immunomodulatory functions of IVIg. We tested the relative binding affinity of the mAbs and IVIg for both OCs- and CCs and compared their effects on (a) the phytohemagglutinin (PHA)-activation T-cells, (b) the production of anti-HLA-II antibody (Ab) by B-memory cells, and anti-HLA-I Ab by immortalized B-cells, and (c) the upregulation of CD4+, CD25+, and Fox P3+ T-regs. The mAbs bound only to OCs, whereas IVIg is bound to both CCs and OCs. The mAbs suppressed blastogenesis and proliferation of PHA-activated T-cells, anti-HLA Ab production by B-cells and expanded the T-regs, better than IVIg. We conclude that a humanized version of the TFL-mAbs could be an ideal therapeutic IVIg-mimetic.

Visible-light photocatalysis, particularly in its application to organic synthesis, has experienced a big renaissance in the past decade. The rational design of new photocatalysts with designed and improved photocatalytic properties, that at the same time circumvents the necessity of using scarce and toxic transition metals, will predictably play a key role in photocatalysis in the next few years. Although free-base porphyrins were identified some years ago as a promising, easily accessible and easily tunable class of organic photoredox catalysts, a systematic study on the effect of the electronic nature and of the position of the substituents on both the ground-state and the excited-state redox potentials of these compounds is still lacking. We have prepared a set of known functionalized derivatives of meso-tetraphenyl porphyrin containing different substituents either in one of the meso-positions or at a beta-pyrrole carbon and we have determined their ground- and (singlet) excited-state redox potentials. This survey has led us to conclude that the introduction of a carbonyl group at the beta-pyrrolic position strongly increases the facility of the monoelectronic reduction of the porphyrin both in the ground state and in the singlet excited state. We have also prepared a second set of four previously unknown benzoyl derivatives of meso-tetraphenylporphyrin, and we have confirmed the validity of our conclusions.

The majority of investigations on microbial communities from various environments are presently built on culture-independent methods. Many studies point to the pivotal, selective role of primers targeting hypervariable regions of 16S rRNA in the metabarcoding of bacteria, including cyanobacterial communities. The selectivity of primers designed to amplify targeted regions of the 16S rRNA gene, which has been highlighted by many authors, limited effective amplification. Moreover, the type and specificity of the studied material can also negatively influence the results of 16S metabarcoding. Most of the studies of cyanobacterial communities have been performed for planktonic microbial communities that are often represented by common, well-studied species. In this study, we present the results of 16S metabarcoding analysis using three primer pairs - two already well-known and a third designed in this study - that amplify divergent regions of the 16S rRNA gene (V3-V4, V4-V6, V6) for benthic, microbial mat-forming cyanobacteria communities. Such communities can be a source of toxigenic cyanobacterial taxa and should be monitored with adequate primers. The comparison of three primer pairs suggested that those designed within the present study describe the structure and composition of highly heterogeneous cyanobacterial mats’ communities better than the others

Considering the manufacturing of automotive components, there exists a dilemma around the substitution of traditional Cast Iron (CI) with lighter metals. Nowadays, aluminium alloys, being lighter compared to traditional materials, are considered as a more environmentally friendly solution. However, the energy required for the extraction of the primary materials and manufacturing of components is usually not taken into account in this debate. In this study, an extensive literature review has been performed to estimate the overall energy required for the manufacturing of an engine cylinder block using (a) cast iron and (b) aluminium alloys. Moreover, data from over 100 automotive companies, ranging from mining companies to consultancy firms, have been collected in order to support the soundness of this investigation. The environmental impact of the manufacturing of engine blocks made of these materials is presented with respect to the energy burden; the “cradle-to-grave approach” has been implemented to take into account the energy input of each stage of the component lifecycle starting from the resource extraction and reaching to the end-of-life processing stage. Our results indicate that although aluminium components contribute towards reduced fuel consumption during their use phase, the vehicle distance needed to be covered in order to compensate for the up-front energy consumption related to the primary material production and manufacturing phases is very high. Thus, the substitution of traditional materials with lightweight ones in the automotive industry should be very thoughtfully evaluated.

The potential of quantum computing for scientific and industrial breakthroughs is immense, however, we are still in the Noisy Intermediate-Scale Quantum (NISQ) era, where the currently available quantum devices contain small numbers of qubits, are very sensitive to environmental conditions and prone to quantum decoherence. Even so, existing NISQ computers have already been shown to outperform conventional computers on specific problems and the key question is how to make use of today’s NISQ devices to achieve quantum advantage in the field of computational science and engineering (CSE). In this direction, this work proposes a hybrid computing formulation by combining quantum computing with machine learning for accelerating the solution of parameterized linear systems in NISQ devices. In particular, it focuses on the Variational Quantum Linear Solver (VQLS), which is a hybrid quantum- classical algorithm for solving linear systems of equations. VQLS employs a short-depth quantum circuit to efficiently evaluate a cost function related to the system solution. The algorithm’s circuit consists of a quantum gate sequence (unitary operators) that involves a set of tunable parameters. Then, well-established classical optimizers are utilized to tune the parameters of the sequence in order to minimize the cost function, which is equivalent to finding the system solution at an acceptable level of accuracy. In this work, it is demonstrated that machine learning tools such as feed-forward neural networks and nearest-neighbor interpolation techniques can be successfully employed to accelerate the convergence of the VQLS algorithm towards the optimal values for the circuit parameters when applied to parameterized linear systems that need to be solved for multiple parameter instances.

The importance of radar-based human activity recognition increased significantly over the last two decades in safety and smart surveillance applications due to its superiority towards vision-based sensing in the presence of poor environmental conditions, like illumination, increased radiative heat, occlusion, and fog. An increased public sensitivity for privacy protection, and the progress of cost-effective manufacturing, led to a higher acceptance and distribution. Deep learning approaches proved that the manual feature extraction that relies heavily upon process knowledge can be avoided by its hierarchical, non-descriptive nature. On the other hand, ML techniques based on manual feature extraction provide a robust, yet empirical based approach where the computational effort is comparatively low. This review outlines the basics of classical ML- and DL-based human activity recognition and its advances while taking recent progress of both categories into regard. For every category, state-of-the-art methods are introduced, briefly explained and discussed in terms of their pros, cons and gaps. A comparative study is performed to evaluate the performance and computational effort based on a benchmarking data set to provide a common basis for the assessment of the techniques’ degree of suitability.

Aquaculture by-products can be compromised an important liming material of increasing soil pH and soil fertility. The aim of this research was to assess the effect of mussel shells on soil pH, on organic matter and on soil nutrients. In this study a pot experiment was carried out at the De-partment of Ichthyology and Aquatic Environment (University of Thessaly, Greece). A acidic soil (pH 4.26) amended with 6 different proportions of mussel shell (0.0, 0.1, 0.3, 0.5, 1, 3 and 6%) in two different grain sizes (Fine powder (>1 mm) and Coarse powder (1-2 mm)), resulting in 13 treatments. According to the results, it was observed that pH, organic matter, Available P and Exchangeable K increased. Specifically, the highest pH values observed at 6% rate. Available P and Exchangeable K achieved the highest content at 6% Fine powder treatment, 46.2 and 190.1 mg kg-1, respectively. Similarly, organic matter had the highest value in 6% Fine powder pots (2.27%). Moreover, Total N concentration varied from 0.11 to 0.14 but no statistically significant different was noticed between the treatments. In conclusion, mussel shells can compose a promising liming material in the agriculture section.

Aluminum, a contentious trace element found in the environment, has been demonstrated to have harmful effects on both humans and animals. In contrast, Sempervivum tectorum, an evergreen plant, has been found to offer numerous beneficial effects for both humans and animals. Therefore, this study aims to assess the protective effect of S. tectorum on certain reproductive biomarkers in male rats exposed to aluminum. Thirty-five Wistar rats were randomly divided into five groups: NTC (no-treatment control) received distilled water; NC (negative control) received drinking water containing 1 mg/L aluminum sulfate (AS); E1 received 1 mg/L AS along with an 8% S. tectorum extract; PC (positive control) received only 8% S. tectorum extract; E2 received 1 mg/L AS for three months followed by 8% extract for one month. The study analyzed testosterone, LH, FSH, body weight, and the histological structure of the testis, epididymis, and prostate, as well as the levels of zinc, manganese, copper, and iron in these organs. Significant decreases in body weight, testis, and epididymis size were observed in the aluminum-exposed groups compared to the control, whereas these decreases were not significant in the S. tectorum-treated groups compared to the control. Aluminum exposure led to significant decreases in testosterone and LH levels, with FSH levels showing a non-significant decrease in males, which were mitigated significantly by the administration of the plant extract. Histological analysis revealed alterations in the testis, epididymis, and prostate of the AS-exposed groups, including necrosis of seminiferous tubule epithelium and Leydig cells in the testis, and basal epithelial necrosis in the epididymis and prostate. Aluminum levels increased in all organs studied, while levels of zinc, copper, iron, and manganese decreased, showing a negative and significant correlation with aluminum levels. The aqueous extract of S. tectorum demonstrated a protective effect on certain studied biomarkers in male rats affected by aluminum exposure.

This article compares chemical coagulation with electrocoagulation, two popular methods for the primary treatment of wastewater generated in the process of Underground Coal Gasification (UCG). The primary aim was to determine which method is more effective in the removal of cyanide and sulphide ions, metals and metalloids, as well as organic compounds. In both cases, experiments were conducted in batch 1 dm³ reactors, and the coagulation/flocculation process was carried out using iron ions. Four types of coagulants were tested during the chemical coagulation study: FeCl₂, FeSO₄, Fe₂(SO₄)₃, and FeCl₃. In the electrocoagulation experiments, pure iron Armco steel was used to manufacture the sacrificial iron anode. Both processes were tested under a wide range of operating conditions (pH, time, Fe dose) to determine their maximum efficiency for treating UCG wastewater. It was found that, through electrocoagulation, a dose as low as 60 mg Fe/dm³ leads to >60% cyanide reduction and >98% sulphide removal efficiency, while for chemical coagulation, even a dose of 307 mg Fe/dm³ did not achieve more than 24% cyanide ion removal. Moreover, industrial chemical coagulants, especially when used in very high doses, can be a substantial source of cross-contamination with trace elements.

Soil erosion is one of the biggest problems in the agricultural sector that can affect ecosystems and human societies. A field of 50 slope was selected to study the runoff, soil and nutrients’ loss as well as crop productivity in different treatments (conventional tillage (CT) vs. no-tillage (NT), plant vs. no plant cover, contour cultivation (CC) vs. perpendicular to the contour cultivation, (PC) under natural rainfall. The experiment was conducted in central Greece in two cultivation periods. In autumn, the field was cultivated with intercropping Triticosecale and Pisum sativum and in spring with Sunflower. The total rainfall was 141.4 mm in the 1st year and 311 mm in the 2nd. We found that runoff in the treatment of no tillage with contour cultivation was 85% lower in both years compared to the no tillage-no plant control. Therefore, the contour cultivation-no tillage treatment had a positively effect in decreasing phosphorus and potassium concentrations lost from soil: indeed, there was a decrease by 55% and 62% in P and K, respectively, in the NT compared to the CC treatments. We conclude that the NT-CC treatment with plant cover was the most effective in reducing water runoff, soil nutrients’ loss and increasing yield.

In the present study pomegranate peels and avocado peels and seeds vacuum microwave extraction solid by-products were supplemented in corn silage in order to investigate the effects on meat quality and growth rate in broiler chicken. 50 broilers were divided in two groups treated with experimental or usual fed for 43 days (group A: 25 broilers fed with avocado and pomegranate by-products and group B: 25 broilers fed with corn-silage used as control). The results showed that broiler chickens fed with diet supplemented with a mixture of pomegranate avocado by-products (group A) shown significant differences in chicken leg meat quality improving in significant level the proteins and fatty acids contents in breast and leg meat respectively. More specific ω3 and ω6 fatty acids contents were three times higher than in group B. Moreover protective effect on the decomposition of polyunsaturated fatty acids induced by free radicals presented in chicken meat based on the evaluation of lipid peroxidation by measuring thiobarbituric acid reactive substances. Pomegranate peels, avocado peels and seeds by-products appeared slight reduction on meat production while it was found to improve the qualitative chicken meat characteristics. Regarding the production costs, it was calculated that the corn-silage supplementation used in this study lead to a 75% lower cost than the commercial corn-silage used for the breeding of broilers.

This paper offers an in-depth exploration of the complex relationship between seasonality and Autism Spectrum Disorder (ASD). It reviews existing research, providing a comprehensive summary of findings and highlighting the multifaceted dimensions of seasonality as an environmental factor that influences the etiology of ASD. The discussion encompasses various factors, including birth months, maternal health, dietary choices, and vitamin D deficiency, and delves into the intricate interplay of seasonality with environmental influences such as viral infections and solar radiation. The present study raises essential questions regarding the timing of environmental influences and the factors contributing to the rising prevalence of ASD. Ultimately, it underscores the need for future epidemiological research to incorporate more extensive investigations of environmental risk factors and employ advanced statistical analyses. This comprehensive overview contributes to a deeper understanding of how seasonality factors may be linked to the occurrence of ASD and its increasing prevalence, recognizing the multifaceted and diverse nature of these interactions.

Background: Microscopic examination of acid-fast stained sputum smears for detecting mycobacterial acid-fast bacilli (AFB) remains the most economical and readily available method for laboratory diagnosis of tuberculosis (TB). However, this conventional approach has limitations, including low sensitivity and labor-intensive procedures. Methods: An automated microscopy system incorporating artificial intelligence (AI) and machine learning for AFB identification was evaluated. The study was conducted at an Infectious Disease Hospital in Jiangsu Province, China, utilizing an intelligent microscope system (TB-Scan, Wellgen Medical, Kaohsiung). A total of 1,000 sputum smears were included in the analysis, with the system capturing digital microscopic images and employing an image recognition model to automatically identify and classify AFB. Referee technicians provided the gold standard for discrepant results. Results: The automated system demonstrated an overall accuracy of 95.00% (950/1,000), sensitivity of 91.24% (177/194), and specificity of 95.91% (773/806). Notably, the system identified 21 smears as positive that were previously reported as negative, with referee technicians confirming 17 of these as true positive and retracting the test results accordingly. Recalculating the performance, the accuracy increased to 96.70% (967/1,000), sensitivity to 91.94% (194/211), and specificity to 97.97% (773/789), with a false negative rate of 8.06% (17/211) and a false positive rate of 2.03% (16/789). Conclusions: The incorporation of AI and machine learning into an automated microscopy system demonstrated the potential to enhance the sensitivity and efficiency of AFB detection in sputum smears compared to conventional manual microscopy. This approach holds promise for widespread application in TB diagnostics and potentially other fields requiring labor-intensive microscopic examination.