Governments all over the world are currently grappling with the COVID-19 pandemic. While some countries were very hard hit, others were only mildly hit but all are still taking measures to mitigate the consequences. The virus emerged in December 2019 in Wuhan, China and spread to most continents by the beginning of March 2020, which led to the World Health Organization declaring it as a pandemic on the 11^th of March 2020. Since it was a novel disease, there was limited information on the virus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) belongs to the same family as the Severe Acute Respiratory Syndrome Coronavirus 1 (SARS-CoV-1) and the Middle East Respiratory Syndrome Coronavirus (MERS-CoV). Researchers all over the world started working simultaneously to understand the virus to provide the necessary treatment regime or vaccine in order to reduce the impact of the virus on its victims. Africa and other developing countries with limited resources and poor planning and management are expected to be among the worst hit in the long run. The implications of the COVID-19 on food, water, hygiene, sanitation, and the environment in Africa have been reviewed in this paper, as well as possible implications they may pose to the population, based on the existing common practices and their immediate impacts. This information can assist policymakers in Africa to adequately plan the management of the COVID-19 in order to lessen its impact on the population.

A relevant aspect in the epidemiology of Tegumentary Leishmaniasis (TL) is the Leishmania parasites carrying a viral endosymbiont Leishmania RNA Virus 1 (LRV1), a dsRNA virus. Leishmania parasites carrying LRV1 are prone to causing more severe TL symptoms, increasing the likelihood of unfavorable clinical outcomes. LRV1 has been observed in cultured strains of five L. (Viannia) species, and host specificity was suggested when studying LRV1 from L. braziliensis and L. guyanensis strains. The coevolution hypothesis of LRV1 and Leishmania was based on phylogenetic analyses, implying an association between LRV1 genotypes, Leishmania species, and their geographic origins. This study aimed to investigate LRV1 specificity to Leishmania (Viannia) species hosts by analyzing LRV1 from L. (Viannia) species. To this end, LRV1 was screened in L. (Viannia) species other than L. braziliensis or L. guyanensis, and it was detected in 11 out of 15 L. naiffi and in 2 out of 4 L. shawi. Phylogenetic analyses based on partial LRV1 genomic sequencing supported the hypothesis of host specificity, as LRV1 clustered according to their respective Leishmania species hosts. These findings underscore the importance of investigating Leishmania and LRV1 coevolution and its impact on Leishmania (Viannia) species dispersion and pathogenesis in the American Continent.

A sequence of new acetamide derivatives 9-15 of primary, secondary amine, and para-toluene sulphinate sodium salt have been synthesized under microwave irradiation and assessed in vitro for their antibacterial activity against one Gram-positive and two Gram-negative bacterial species such as S. pyogenes, E. coli, and P.mirabilis using the Mueller-Hinton Agar diffusion (well diffusion) method. The synthesized compounds with significant differences in inhibition diameters and MICs were compared with those of amoxicillin, ampicillin, cephalothin, azithromycin and doxycycline. All of the evaluated acetamide derivatives were used with varying inhibition concentrations of 6.25, 12.5, 37.5, 62.5, 87.5, 112.5 and 125 µg/ml. The results show that the most important antibacterial properties exercised by the synthetic compounds 9 and 11 bearing para-chlorophenyl moiety incorporated into the 2-position moiety of acetamide 2. The molecular structures of the new compounds were determined using FT-IR, 1H-NMR techniques.

Accurate classification of objects in 3D point clouds is a significant problem in several applications, such as autonomous navigation and augmented/virtual reality scenarios, which has become a research hot spot. In this paper, we presented a deep learning strategy for 3D object classification in augmented reality. The proposed approach is a combination of the GRU and LSTM. LSTM networks learn longer dependencies well, but due to the number of gates, it takes longer to train; on the other hand, GRU networks have a weaker performance than LSTM, but their training speed is much higher than GRU, which is The speed is due to its fewer gates. The proposed approach used the combination of speed and accuracy of these two networks. The proposed approach achieved an accuracy of 0.99 in the 4,499,0641 points dataset, which includes eight classes (unlabeled, man-made terrain, natural terrain, high vegetation, low vegetation, buildings, hardscape, scanning artifacts, cars). Meanwhile, the traditional machine learning approaches could achieve a maximum accuracy of 0.9489 in the best case.

Integrating nanomaterials like carbon nanotubes (CNTs) and iron oxide (Fe₃O₄) into epoxy composites has significant interest due to their potential to enhance mechanical properties. This study evaluates the impact of dispersion quality on the mechanical performance of CNT/Fe₃O₄/Epoxy composites, comparing stirring and sonication methods at three different loadings: 0.1, 0.3, and 0.5 wt.%. Tensile testing revealed that sonicated composites consistently outperformed stirred composites, with a significant increase in elastic modulus and ultimate tensile strength (UTS). However, fracture strain decreased in both composite types compared to pure epoxy, with sonicated composites experiencing a more significant reduction than stirred composites. These results underscore the importance of high-quality dispersion for optimizing mechanical properties.

Objective: The COVID-19 pandemic inferred on neuro-oncological patients (PTS) and the caregivers regarding tumor care and emotional functioning. This study aimed to understand how COVID-19 affects their psychological state and relations between PTS and health personnel in neuro-oncology. Methods: A cross-sectional study on neuro-oncological PTS and their caregivers. Results: A total of 162 PTS and 66 caregivers completed the questionnaire. The 37.5% of PTS perceived greater risk of contracting the COVID-19 compared to the general population. On the 0-10 scale, PTS tumor-related anxiety score was 5.8 and COVID-related 4.6. The caregivers reported 7.7 and 5.5 respectively. The QoL was described at least as good in 75% of both PTS and caregivers; the caregivers’ care burden increased in 22.7% during the pandemic, with no correlation with QoL. Future perception often changed both in PTS and in the caregivers. Cancer treatment schedule was changed in 18.5%, including for PTS decision. However, the 93.5% of PTS was satisfied with the overall care. Conclusion: A considerable proportion of PTS and caregivers still perceived the tumor disease as more burdensome than the pandemic, and perceived their future as more uncertain. Such data rinforce the need to build a proficient alliance between PTS and health personnel.

Non-alcoholic fatty liver disease (NAFLD) affects up to a quarter of the adult population in many developed and developing countries. This spectrum of liver disease ranges from simple steatosis to nonalcoholic steatohepatitis (NASH) and cirrhosis. The incidence of NASH is projected to increase by up to 56% over the next 10 years. There is growing epidemiological evidence that NAFLD has become the fastest growing cause of hepatocellular carcinoma (HCC) in industrialized countries. The annual incidence of HCC varies between patients with NASH cirrhosis and patients with noncirrhotic NAFLD. In this review, NAFLD/NASH-associated HCC will be described, including its epidemiology, risk factors promoting hepatocarcinogenesis, and management of HCC in patients with obesity and associated metabolic comorbidities, including preventive strategies and therapeutic approaches to address this growing problem.

Background: Permanent tracheostomy because of total laryngectomy surgery entails great conse-quences for the patient regarding respiratory physiopathology such as the filtering, humidifying, and heating function of the air by the nose is lost. The use of special stomal filters can determine adequate protection of the trachea-broncho-pulmonary system with a reduction in respiratory pathologies. In fact, in most cases laryngectomee patients are first cigarette smokers who for this reason already have also respiratory diseases such as chronic obstructive pulmonary disease (COPD). Despite the availability of tracheal filters, multiple times, as reported in the literature, the patient tends to limit their use due to reported breathing difficulties, especially in conditions of intense breathing. Methods: The objective of this clinical study was to evaluate the most suitable stomal filter for the laryngectomee patient during physical activity. The filters studied were an INHEALTH device (Blom-Singer SpeakFree HME); two ATOS devices (Provox® Life™ Energy HME and Provox® Life™ Home HME); and an FAHL device (Laryvox HME Sport). Results: For this purpose, the performances of 31 laryngectomee patients, subjected to medi-um-high physical effort, were analyzed through a standardized pneumological test, the Six Minute Walking Test (6MWT) which involves a sustained walk lasting six minutes, with evaluation , every 60 seconds, heart rate, oxygen saturation and meters travelled; furthermore, it examines two sub-jective indices, namely, the basal and final dyspnea index and the initial and final muscular fatigue index.

Since 2017 Cartagena UNESCO World Heritage has threatened to be categorized as "in Danger" by UNESCO. This research analyzes two main critical aspects, Governance and Current state of the Site. Regarding Governance, the study aims to identify strengths, weaknesses, opportunities and treats in the UNESCO Site. Exemplary heritage management systems are studied to propose an adaptable management approach specifically for Cartagena. On the other hand, a comprehensive analysis is conducted utilizing a photographic report that highlights the major issues arising from inadequate heritage management. Hyperspectral images obtained from a previous study are employed to identify vegetation and asbestos-cement roofs within the cultural heritage Site. The study reveals that the ambiguity surrounding decision-making authority for heritage management, distributed between the Mayor's Office and the Ministry of Culture, is a primary challenge. This fragmentation has resulted in duplicated efforts and a lack of coordinated action, significantly compromising the conservation and protection of the cultural heritage Site. Moreover, twelve current shortcomings of cultural heritage in Cartagena are identified through authors' five-year on-site regular visits, photographic reports and observation. To address the prevailing concerns, a new line of command for cultural heritage management is proposed as the most effective means of tackling these challenges. Additionally, general recommendations are presented to mitigate the existing problems and prevent the classification of Cartagena's heritage as "at risk" by UNESCO in the near future. This research provides a scientific perspective, drawing upon years of experience studying heritage and residing in the city, devoid of political influences or conflicts of interest.

Lignocellulosic fibers are widely applied as composite reinforcement due to their properties. The thermal degradation behavior determines the maximum temperature in which the fiber can be applied without significant mass loss. It is possible to determine these temperatures using Thermogravimetric Analysis (TG). In particular, when curves are obtained at different heating rates, kinetic parameters can be determined and more detailed characteristics of the material are obtained. However, every curve obtained at a distinct heating rate demands material, cost, and time. Methods to predict thermogravimetric curves can be very useful in the materials science field and in this sense mathematical approaches are powerful tools if well employed. For this reason, in the present study, curaua TG curves were obtained at three different heating rates (5, 10, 20, and 40 °C.min-1) and Vyazovkin kinetic parameters were obtained. After, the experimental curves were fitted using an artificial neural network (ANN) approach followed by a Surface Response Methodology (SRM). Curves at any heating rate between the minimum and maximum experimental heating rates were obtained with high reliability. Finally, Vyazovkin kinetic parameters were tested again with the new curves showing similar kinetic parameters from the experimental ones. In conclusion, due to the capability to learn from the own data, ANN combined with SRM seems to be an excellent alternative to predict TG curves that do not test experimentally, opening the range of applications.

Objective: The causes of vertigo and dizziness in children are diverse and require attention from various specialists. Numerous authors have reported that the commonest type of vertigo in children is migraine-associated vertigo (vestibular migraine and benign paroxysmal vertigo of childhood - BPV). We aimed to check whether this could be applied to our group of patients. Materials and methods: A retrospective case series of 257 consecutive pediatric vertigo and diz-ziness patients referred to the tertiary pediatric ENT clinic from 2015 to 2020. Patients received a complete audiovestibular workup and were referred to pediatric neurologists and other special-ists depending on the signs and symptoms. Results: Of 257 children aged 1-17 years, almost one fifth of them, 49/257 (19.1 %) had a central type of vertigo, 20/257 of them (7.8%) had benign paroxysmal vertigo of childhood and 4/257 (1.6%) had a migrainous type of vertigo. Most of the children, 112/257 (43.6%), remained unclas-sified, without a final diagnosis. Conclusion: Due to the numerous possible causes, a child presenting with dizziness and vertigo requires a multidisciplinary approach. In the majority of cases, vertigo spells are self-limiting. They stop spontaneously and sometimes remain clinically undiagnosed. The most prevalent reasons for pediatric vertigo may be temporary hemodynamic (vaso-vagal) and psychological imbalance.

Bilateral recurrent nerve damage following total thyroidectomy in thyroid surgery represents severe complications. These complications have almost low incidence thanks also by using the Nerve Intraoperative Monitoring. The aim of this observational retrospective study is to evaluate the inception mode and the recovery time for different clinical laryngeal pictures that arise from this surgery. We enrolled 25 patients with bilateral vocal folds mobility deficit between October 2017 and October 2022, diagnosed in ENT Unit of University of Campania “L. Vanvitelli”, out of a total of 1417 patients undergoing total thyroidectomy. The 25 patients (23F,2M) aged from 24 to 78 years old (average age 51.7) presented a bilateral vocal folds motility deficit (occurring in about 0.1% of cases). All patients underwent 9 months diagnostic/therapeutic process, which started approximately 30 days after thyroid surgery. There are several outcomes of these complications with functional laryngeal defects being mainly related to respiratory and phonatory activities. These clinical manifestations evolve in different ways within a context of a wide range of possibilities, from spontaneous bilateral or monolateral recovery to functional or surgical restoration. This study allowed the acquisition of useful information about prognostic indications and an adequate therapeutic process, based on the specific clinical characteristics.

Lung cancer remains a pervasive global health challenge, necessitating precise and efficient classification methods to inform optimal treatment strategies. In this study, we investigate the potential of machine learning algorithms in developing a computer-aided diagnostic tool for early and accurate lung cancer classification, leveraging essential protein biomarkers as predictive features. Our investigation reveals the superiority of Deep Neural Networks (DNNs) in lung cancer classification, achieving an impressive accuracy of 96.91%. This highlights the transformative potential of DNNs in facilitating real-world clinical applications, offering clinicians a powerful tool for accurate diagnosis and prognosis. Additionally, we analyze the performance of Ensemble Methods, including Voting (91.75%) and Bagging (93.81%), as viable alternatives to DNNs. These ensemble techniques demonstrate robust performance, further underlining their utility in lung cancer classification tasks. Furthermore, our study underscores the critical role of hyperparameter tuning, particularly in adjusting parameters such as min child weights and learning rates, in mitigating overfitting and enhancing the generalizability of diverse machine learning models. For instance, Support Vector Machines (SVM) exhibit varying accuracies ranging from 74.23% to 95.88% across different hyperparameter configurations, emphasizing the importance of hyperparameter optimization in maximizing model performance. In summary, our comprehensive comparative analysis sheds light on the efficacy of different machine learning approaches in lung cancer classification. By leveraging advanced algorithms and optimizing model parameters, researchers and clinicians can harness the power of machine learning to advance early detection and personalized treatment strategies for lung cancer patients.

Driven by the importance of early detection for improving patient outcomes, this study investigates the effectiveness of various machine learning algorithms in predicting lung cancer based on clinical data. Lung cancer remains a significant global health concern, and this research seeks to contribute to advancements in early diagnosis through the application of machine learning techniques. The dataset consists of 385 training and 97 test samples, with a k-fold cross-validation approach (k=5) utilized to mitigate overfitting. Additionally, the ADASYN oversampling technique is employed to address class imbalance. Our analysis includes traditional algorithms such as Logistic Regression and Decision Trees, as well as ensemble methods like XGBoost, LGBM, and AdaBoost. Furthermore, we explore the effectiveness of deep learning models, particularly Deep Neural Networks (DNN). Results demonstrate promising accuracy rates across all models, with some outperforming others in terms of precision, recall, and F1-score. Our findings reveal that LGBM achieves the highest accuracy among all models, with an accuracy rate of 96.91%. It also exhibits superior performance in terms of precision, recall, and F1-score, particularly in classifying both positive and negative instances of lung cancer.

The present study reports a critical review of NIO's business model, considering the evolving landscape of the electric vehicle market and servicing. The objective of this study is to develop a comprehensive framework that facilitates the identification of key elements characterizing a company's business model and highlights ongoing transformations, crucial for adaptation and survival in a rapidly changing environmental context. Focusing on the case study of NIO, a relatively young Chinese original equipment manufacturer (OEM) specializing in high-tech electric cars, the research delves into the challenging scenario of the Chinese electric vehicle market, which has recently faced a bubble in 2023. The market proliferation, supply chain disruptions, and price wars triggered by Tesla have resulted in a survival struggle for numerous automotive startups, leaving larger companies with increasing market shares. Despite facing adversities, NIO managed to secure a promising segment, catering to premium-range battery electric vehicles (BEVs), establishing a competitive advantage through differentiation. By pursuing ambitious investments, the company aims to create economies of scope and achieve cost leadership, venturing into new market sectors and vertically integrating the production chain. Given NIO's agility in adapting to market conditions, aggressive entry into new segments, and a strategic vision for the future, it serves as an excellent candidate for testing and validating the proposed framework. The research sheds light on NIO's trajectory and offers insights into its potential for sustained growth in the dynamic electric vehicle market.

Human arteries show structural and functional peculiarities according to the nutrient and oxygen needs of a specific vascular district. This architectural heterogeneity is reflected in the pathological setting of cardiovascular diseases (CVDs). Indeed, the responsiveness to cardiovascular risk factors, the morphological and molecular patterns are discriminating factors among CVDs affecting different vascular beds. Micro-RNAs (miRNAs) are endogenous regulators of gene expression and fine tuners of vascular cell differentiation, thus these non-coding RNAs can modulate the arterial heterogeneity. The identification of a miRNA signature artery-specific would be promising in the therapy of CVDs, especially in frail elderly patients. In the present review we will provide a concise description of the arterial tree heterogeneity on structural and cellular basis, mainly in the pathological context. Secondly, we will address the miRNA potential as crucial mediators of arterial heterogeneity focusing on abdominal aorta and femoral artery, with the final goal of strengthening the search of more targeted therapies in CVDs and stratification approaches in frail elderly patients.

Crigler-Najjar Syndrome (CNS) is a rare genetic disorder caused by mutations in the UGT1A1 gene, leading to impaired bilirubin conjugation and severe unconjugated hyperbilirubinemia. CNS presents in two forms: CNS type 1 (CNS1), the more severe form with a complete absence of UGT1A1 activity, and CNS type 2 (CNS2), with partial enzyme activity. CNS1 requires aggressive management, including phototherapy and plasmapheresis, but liver transplantation (LT) remains the only definitive cure. The timing of LT is critical, as it must be performed before the onset of irreversible brain damage (kernicterus), making early intervention essential. However, LT poses risks such as graft rejection and lifelong immunosuppression. CNS2 is milder, with patients re-sponding well to phenobarbital and having a lower risk of kernicterus. Recent advancements in gene therapy and autologous hepatocyte transplantation offer promising alternatives to LT. Gene therapy using adeno-associated virus (AAV) vectors has shown potential in preclinical studies, though challenges remain in pediatric applications due to liver growth and pre-existing immunity. Autologous hepatocyte transplantation avoids the risks of rejection but requires further research. These emerging therapies provide hope for more effective and less invasive treatment options, aiming to improve the quality of life for CNS patients and reduce reliance on lifelong interven-tions.

Africa is gradually becoming an epicentre for the COVID-19 pandemic. From the current trends of the disease, Africa might be the last hardest hit continent. While scientific investigations are ongoing to develop effective management through medications and vaccines, existing knowledge, perceptions and attitudes could be harnessed to develop an effective strategy to curb community transmission of the COVID-19. The present study assessed the awareness level, perceptions and attitudes of people living in rural, peri-urban and urban communities in Northern Ghana and their preparedness for the prevention and containment of COVID-19. We conducted a face-to-face interview and administered 553 semi-structured questionnaires in eighteen (18) rural and peri-urban/urban communities under Tolon District, Kumbungu Districts, Sagnarigu Municipality, Savelugu Municipality and Tamale Metropolis from 23^rd of April to 8^th of June 2020. The percentage of male to female among the respondents was 56.8% and 43.2%, respectively. Nearly half (41%) of the respondents had no formal education and 91.3% of them were Muslims. Most of the respondents (85%) held the view that COVID-19 is a punishment from God. There was a significant difference (P<0.05) between the time rural and peri-urban/urban communities first heard of COVID-19. Majority (63%) of the rural respondents depended on radio, while the peri-urban/urban respondents (51%) relied on television for information on COVID-19. All respondents were aware of COVID-19 and 91.7% could mention at least two symptoms of the disease but 18% believed there was no COVID-19 in Ghana. Most of the respondents (69.6%) believed they will not contract the virus. Our findings may provide useful data to government and other stakeholders in the COVID-19 fight.

The aim of this study was to assess precipitation (P) by analyzing data from in situ stations compared with those from solely remote sensing products CHIRP and CMORPH, with a reference station in the city. The evapotranspiration (ET) was analyzed directly using SSEBop. The region chosen for this study was the Metropolitan Area of Belem (MAB), close to the estuary of the Amazon River and the mouth of the Tocantins River. Belem is the rainiest state capital of Brazil, which causes a myriad of problems for the local population. The monthly best fit is shown here. In this study, we analyzed P and ET from local stations and compared them with those from satellite products. The main metrics RMSE, NRMSE, MBE, R2, Slope, and NS were used. For the reference station, the automatic and conventional CHIRP and CMORPH results, in mm/month, were as follows: automatic CHIRP: RMSE = 93,3, NRMSE = 0.32, MBE = −33,54, R2 = 0.7048, Slope = 0.945, NS = 0.5668; CMORPH: RMSE = 195,93, NRMSE = 0.37, MBE = −52,86, R2 = 0.6731, Slope = 0.93, NS = 0.4344; conventional station CHIRP: RMSE = 94.87, NRMSE = 0.32, MBE = −33.54, R2 = 0.7048, Slope = 0.945, NS = 0.5668; CMORPH: RMSE = 105.58, NRMSE = 0.38, MBE = −59.46 R2 = 0.7728, Slope = 1.007, NS = 0.4308. This was compared with the pixel and in situ station data. The ET ranges, on average, between 83 mm/month in the Amazonian summer and 112 mm/month in the Amazonian winter. This work concludes that, although CMORPH has a coarser resolution of 0.25° compared to CHIP’s 0.05° for MAB at a monthly resolution, the remote sensing products were reliable. SSEBop also showed reliable performance. For analyses of the consistency of precipitation time series, these products could provide more accurate information.

Among various metal-based nanoparticles, silver nanoparticles (AgNPs) manifest superior inhibitory effect against several microorganisms. In fact, the AgNPs based therapy has been reported to inhibit both sensitive as well resistant isolates of bacteria and other disease causing microbes with equal propensity. Keeping this fact into consideration, we executed bio-mediated synthesis of AgNPs employing Hibiscus rosa sinensis flower extract. The as-synthesized AgNPs were evaluated for their potential to inhibit Streptococcus mutans (S. mutans), one of the main causative bacteria for dental caries. Beside several other reasons, orthodontic appliances have also been reported to facilitate infliction of oral cavity with a range of microbes including S. mutans. To determine the growth inhibitory and anti-adherence activity of AgNPs on orthodontic appliance, we performed microbiological assays employing AgNPs adsorbed on to the orthodontic wires. Topographic analysis of orthodontic wires was executed by scanning electron microscopy. In addition to antimicrobial and antibiofilm activity against oral S. mutans, the as-fabricated AgNPs demonstrated significant inhibitory and anti-biofilm properties against other biofilm forming bacteria such as Escherichia coli and Listeria monocytogenes as well.

A qualitative analysis of pressure acting within the human eye is presented. The situation emerging within the human eye in rest and human eye of accelerated/training person should be distinguished. When the person is in rest, the hydrostatic pressure is much larger than the Laplace pressure. The dynamic (Bernoulli pressure) emerging from intraocular flows in this case is negligible. The situation is rather different for accelerated or decelerated person. In this case, the dynamical pressure and the water hammer pressure become dominant. Under certain circumstances, the water hammer pressure may be larger than the ultimate tensile strength of retina, choroid and the Bruch membrane‐choroid complex, which may possibly affect the retina. As a recommendation: physical training, which is not accompanied with ultimate acceleration/acceleration of the body, may be performed after posterior vitreous detachment; however, potentially traumatic activities such as boxing or competitive diving should be avoided.

Erosion caused by the repeated impact of particles on a substance surface is a usual wear method resulting in gradual and continual loss of objects. It is a crucial problem in several modern industries because their surfaces are frequently subjected to destructive erosive situations. Polymers and their hybrid materials include several applications to be used as a coating in the form of powder for different applications. This review paper aims to provide extensive information on the erosion behavior of thermoset and thermoplastic neat resin and their hybrid materials composites. Focus is specifically paid to highlight the influence of properties of selected materials, impingnation parameters such as incident Angle of erodent, impact velocity of erodent, erodent nature, and the erosion mechanism. The review further extends the information about the erosion techniques and numerical simulation methods used for wear studies of surfaces. An investigation has been carried out for researchers to explore the selection of materials and methods in terms of conditions and parameters to meet the current and future needs and challenges for the protection of surfaces of the advanced industries. During review according to the findings achieved from the literature of the past fifty years, it has been noted that the thermoplastic nature of the composite is a key component to determine the anti-wear properties, the composites with lower glass transition, higher ductility, and greater crystallinity can provide better protection to erosion in advance surface applications.

Vegetation identification using remote sensing is essential for understanding terrestrial ecosystems and monitoring climate change. This technology by providing high-resolution images of the Earth's surface from satellites, aircraft, and drones has revolutionized the way scientists study and un-derstand vegetation patterns, providing information on the distribution, structure, and health of plant communities in different regions and biomes. However, identifying vegetation in multi and hyperspectral images remains a difficult, time-consuming, and costly process. Traditional methods for vegetation mapping involve the in-terpretation of spectral indices such as the Normalized Difference Vegetation Index (NDVI), alt-hough they often suffer from limitations such as manual interpretation and limited spatial resolution of satellite images. Furthermore, machine learning techniques, artificial neural networks, decision trees, support vector machines, and random forests have shown promising results in identifying and classifying vegetation cover from hyperspectral images. However, due to the need for per-son-nel with specialized expertise, their application on a large scale is still challenging. On the other hand, correlation methods between curves have emerged as powerful and simplified tool for comparing spectral signatures of hyperspectral image pixels and efficiently classifying vegetation in a study area. Pearson's correlation coefficient and spectral angle mapper are among the most common correlation methods used in vegetation mapping. These correlation methods, among many others available, offer an easily implemented and computationally efficient approach, making them particularly useful for applications in developing countries or regions with limited resources. In this article, a comparative study of correlation/distance metrics was conducted for the detection of vegetation pixels in hyperspectral images. The study allowed for the comparison of five distance and/or correlation metrics: direct correlation, cosine similarity, normalized Euclidean distance, Bray-Curtis’s distance, and Pearson correlation. The two metrics that yielded the best accuracy results in vegetation pixel detection were direct correlation and Pearson correlation. Based on the selected methods, a vegetation detection algorithm was implemented and validated on a hyper-spectral image of the Manga neighborhood in Cartagena de Indias, Colombia. The spectral library was utilized for image processing, while the numpy and scipy libraries in the Python programming language were used for the mathematical calculation of correlations. Both the study's approach and the implemented algorithm aim to serve as a reference for conducting detection studies of various material types in hyperspectral images using open-access programming platforms.

Monte Carlo techniques have been extensively used for planning laser-based clinical procedures such as photobiomodulation. However, the effect of several biological tissue characteristics, including morphological structure and physiological parameters, has not been carefully addressed in many applications. Specifically, many questions remain concerning the effect of skin phototype and body mass index on the efficacy of photobiomodulation for extraoral therapies. To address these questions, a Monte Carlo simulation model was developed to analyze the effects of body mass index-dependent skin structure and Fitzpatrick skin type, specifically tailored for the morphological characteristics of cheek tissue. The model describes the settings of a typical oral photobiomodulation treatment protocol for pain relief, namely the use of 660 nm and 808 nm laser wavelengths and a therapeutic dose of 2.0 J/cm² on the masseter muscle. The simulations were used to train a machine learning predictive model aimed at accelerating the treatment planning stage and assessing the importance of patient-specific parameters. A multiple regression approach was adopted to predict muscle dose and treatment time for the effective delivered dose.

“White matter disease” identifies series of different conditions and pathological mechanisms: autoimmune, infectious, toxic-metabolic and vascular. Each of these leads to a global impairment of the neural myelination process through the secondary destruction of previously myelinated structures. To date, the imaging spectrum represents an irreplaceable tool to detect these lesions, describe their distribution patterns and stage them over time. This study aims presents a pictorial review of white matter disease, from pathology to imaging spectrum, reporting current main staging systems with greater emphasis to relationship between cerebrovascular disease and white matter hyper-intensity appearance, and the newest advances in this field.

The escalating demand for multifunctional and advanced materials for growing industries has turned scientific exploration to graphene-based hybrid filler polymer composites. The introduction of graphene with other fillers into polymer matrices results in astonishing properties and thus has gained significant attention in recent years. This study addresses the significance of graphene-based hybrid filler polymer composites in progressive materials science and engineering. The paper encloses some traditional and current preparation techniques employed in the fabrication of composites and a comprehensive review of successfully prepared graphene hybrid polymer composites with enhanced mechanical, thermal, and electrical properties reported in published research. The role of different factors, e.g., filler type, aspect ratios, filler-matrix compatibility, dispersion effects, homogeneity, filler orientation through polymer matrices, and curing conditions, are summarized. Finally, the applications in heavy industries, e.g., aerospace, electronics, energy storage, and automotive sectors were also analyzed. We hope this study will serve as a practical resource for new researchers and practitioners to understand and harness the full potential of these composites in various scientific and industrial fields.

The rise in dependency upon information present on web and social networks has increased the importance of content credibility systems. These sys- tems can help the users to make a right decision related to buying a product, utiliz- ing a service and etc. Application areas including social network blogs of different subjects such as health, food, education, politics and product review/ratings some- times suffer incredible and wrong information flow. The content credibility sys- tems can help users to identify the credible information on these various forums. Recently, researchers have proposed certain mechanisms for these systems, out of which reputation based systems have gained most attention. However, reputa- tion systems are vulnerable to reputation based attacks, like Sybil, Slandering, and Whitewash promoting spread of wrong information. The authors have proposed a defense mechanism against these attacks that is based upon Bayesian Model. The proposed defense mechanism provides protection against these attacks so that fake or wrong information could be prevented. The authors evaluated the proposed mechanism in three different scenarios and presented the results in terms of pre- cision, recall and rate of change in rank. The results reveal almost 88%prevention against these attacks in comparison to the baseline systems.

Abstract This study delved into the application of various machine learning (ML) models for the classification of lung cancer levels. Through meticulous monitoring of parameters such as minimum child weight and learning rate, efforts were made to mitigate overfitting while optimizing model performance. The Deep Neural Network (DNN) emerged as a standout performer, showcasing robust performance across training, validation, and testing stages. Ensemble methods like voting and bagging also demonstrated promising results. However, Support Vector Machine (SVM) models with the Sigmoid kernel faced challenges in achieving satisfactory performance. Overall, the investigation sheds light on the efficacy of different ML models in lung cancer level classification and underscores the importance of parameter tuning to address overfitting concerns.

In response to the burgeoning global demand for premium agricultural products, particularly within the competitive nut market, this paper introduces an innovative methodology aimed at enhancing the grading process for almonds and their shells. Leveraging state-of-the-art Deep Convolutional Neural Networks (CNNs), specifically the AlmondNet-20 architecture, our study achieves exceptional accuracy exceeding 99%, facilitated by the utilization of a 20-layer CNN model. To bolster robustness in differentiating between almonds and shells, data augmentation techniques are employed, ensuring the reliability and accuracy of our classification system. Our model, meticulously trained over 1000 epochs, demonstrates remarkable performance, boasting an accuracy rate of 99% alongside a minimal loss function of 0.0567. Rigorous evaluation through test datasets further validates the efficacy of our approach, revealing impeccable precision, recall, and F1-score metrics for almond detection. Beyond its technical prowess, this advanced classification system offers tangible benefits to both industry experts and non-specialists alike, ensuring globally reliable almond classification. The application of deep learning algorithms, as showcased in our study, not only enhances grading accuracy but also presents opportunities for product patents, thereby contributing to the economic value of our nation. Through the adoption of cutting-edge technologies such as the AlmondNet-20 model, we pave the way for future advancements in agricultural product classification, ultimately enriching global trade and economic prosperity.

This work aimed to study the thermal and crystalline properties of poly (1,4-phenylene sulfide)@carbon char nanocomposites. Coagulation-processed nanocomposites of polyphenylene sulfide were prepared using synthesized mesoporous nanocarbon of coconut shell as reinforcement. The mesoporous reinforcement was synthesized using a facile carbonization method. The investigation of the properties of nanocarbon was done by SAP, XRD, and FESEM analysis. The research was further propagated via the synthesis of nanocomposite by the addition of characterized nanofiller into poly (1,4-phenylene sulfide) at five different combinations. The coagulation method was utilized for the nanocomposite formation. The obtained nanocomposite was analyzed using FTIR, TGA, DSC, and FESEM analysis. The BET surface area and average pore volume of bio-carbon prepared from coconut shell residue were calculated to be 1517 m2/g and 2.51 nm respectively. The addition of nanocarbon to poly (1,4-phenylene sulfide) has led to an increase in thermal stability and crystallinity up to 6% loading of filler. The minimum achievable glass transition temperature is for 6 % doping of filler into the polymer matrix. It was established that the thermal, morphological, and crystalline properties have been tailored by synthesizing their nanocomposites with mesoporous bio-nanocarbon obtained from coconut shells. So, the loading of filler into poly (1,4-phenylene sulfide) can be optimized to enhance its thermoplastic properties for surface applications.

By taking advantage of a stability criterion established recently, the critical temperature T_c is reckoned with help of the microscopic parameters, characterising the normal and superconducting electrons, namely the independent-electron band structure and a repulsive two-electron force. The emphasis is laid on the sharp T_c dependence upon electron concentration and inter-electron coupling, which might offer a practical route toward higher T_c values and help to understand why high-T_c compounds exhibit such remarkable properties.

The coffee leaf miner Leucoptera coffeella (Guérin-Mèneville & Perrottet), is a key pest in coffee producing countries. During their development, the larvae feed on the palisade parenchyma of the leaves forming mines. As a result, the photosynthetic area of the plant decreases, affecting coffee production. Despite the severity of the damage caused by coffee leaf miner (CLM), morphological aspects of the larval development and the adult genitalia remain unknown. It is important to identify more susceptible targets to an efficient and narrow control by natural or synthetic approaches, relies on determining the larval instars. Equally important is the sexing of the adult, in experiments aiming efficient ways to control CLM, as the study of pheromone-based control methods. This work presents the first morphological description of the four larval instars and the adult genitalia of L. coffeella. In each larval instar, we measured the Mean ± SD (mm) of the cephalic capsules (1^st 0,14±0,03; 2^nd 0,25±0,04; 3^rd 0,32±0,03; 4^th 0,42±0,03) and observed the following morphological details: primary setae, prolegs, crochets and ecdysial line of the cephalic capsule. In the adults, we observed the sexual structures present in both genitalia: male - bulbus ejaculatorius, valva, anellus, gnathos and aedeagus and female - ovipositor, sclerite and corpus bursae. The dissection of the adult specimens confirmed that the external morphology corresponds to the correct sex attribution in CLM adults. These results may support innovative and improved control strategies for CLM Integrated Pest Management (IPM).

The aim of the present study was to investigate the acute effect of caffeine supplementation on performance in official soccer matches. In double-blind, randomized crossover design, 13 professional soccer players performed two complete matches, with Caffeine (CAF) (6 mg/kg) and placebo (PLA) supplementation. Two-way repeated measures ANOVA showed that there was no effect of supplementation on the total distance covered (p = 0.536; ŋp² =0.033) or the total distance covered at different speeds (p = 0.453; ŋp² = 0.048), acceleration or deceleration (p = 0.387; ŋp² = 0.063) number of sprints (p = 0.521; µ² = 0.035) Heart Rate mean (p = 0.484; ŋp² = 0.042) Heart Rate maximum (p = 0.110; ŋp² = 0.199), Rate Perceived Effort (p = 0.151) or efficiency index (p = 0.480). Therefore, acute caffeine supplementation not effective to increase the performance of soccer players in official matches.

Bone tissue engineering has developed significantly in recent years as the increasing demand for bone substitutes due to trauma, cancer, arthritis, and infections. The scaffolds for bone regeneration need to be mechanically stable and have a 3D architecture with interconnected pores. With the advances in additive manufacturing technology, these requirements can be fulfilled by 3D printing scaffolds with controlled geometry and porosity using a low-cost multistep process. The scaffolds, however, must also be bioactive to promote the environment for the cells to regenerate into bone tissue. To determine if a low-cost 3D printing method for bespoke SiOC(N) porous structures can regenerate bone these structures were tested for osteointegration potential by using human mesenchymal stem cells (hMSCs). This includes checking the general biocompatibilities under the osteogenic differentiation environment (cell proliferation and metabolism). Moreover, cell morphology was observed by confocal microscopy and gene expressions on typical osteogenic markers at different stages for bone formation were determined by real-time PCR. The results of the study showed the pore size of the scaffolds had a significant impact on differentiation. A certain range of pore size could stimulate osteogenic differentiation, thus promoting bone regrowth and regeneration.

Despite the availability of COVID-19 vaccines, the global pandemic remains a significant health challenge. Timely detection of the virus is crucial for effective containment efforts, prompting the exploration of machine learning (ML) models for COVID-19 detection. highlights the ongoing significance of COVID-19 as a global health crisis despite the availability of vaccines. To address the need for timely virus detection, the study explores the efficacy of machine learning (ML) models, including DNN, Voting, Bagging, SVC_rbf, SVC_linear, SVC_polynomial, and SVC_sigmoid, in predicting COVID-19 infection probability. With a dataset comprising 4000 samples split into 3200 for training and 800 for testing, the analysis reveals that DNN and Voting models demonstrate the highest performance, achieving an impressive accuracy of 89%. These results underscore the potential of ML techniques, particularly DNN and ensemble methods like Voting, in facilitating early COVID-19 detection and contributing to effective pandemic management. The study emphasizes the importance of continued research to further refine and optimize ML-based COVID-19 detection systems.

The electromagnetic inference is an issue from decades, where working for a better shielding material is still on-going. The purpose of this study is to review the existing methods in the formation of graphene, metal and polymer-based composites. Study indicates that in graphene and metal-based composites, the utilization of alternating deposition method showed the highest shielding effectiveness, whereas, in polymer-based composite, the utilization of chemical vapor deposition method showed highest shielding effectiveness. However, this review reveals that still there is a gap in the literature in terms of the selection of the method. Although there are various available methods which researchers adopt as per their convenience, none of the studies makes a comparison of the methods to form a similar composite. Therefore, as a future gap researcher needs to adopt various methods to form a single composite and then make a comparison of shielding effectiveness. This act will be useful for future researchers to select the appropriate method.

The escalating reliance on revolutionary online web services has introduced heightened security risks, with persistent challenges posed by phishing despite extensive security measures. Traditional phishing systems, reliant on machine learning and manual features, struggle with evolving tactics. Recent advances in deep learning offer promising avenues for tackling novel phishing challenges and malicious URLs. This paper introduces a two-phase stack generalized model named AntiPhishStack, designed to detect phishing sites. The model leverages the learning of URLs and character-level TF-IDF features symmetrically, enhancing its ability to combat emerging phishing threats. In Phase I, features are trained on a base machine learning classifier, employing K-fold cross-validation for robust mean prediction. Phase II employs a two-layered stacked-based LSTM network with five adaptive optimizers for dynamic compilation, ensuring premier prediction on these features. Additionally, the symmetrical predictions from both phases are optimized and integrated to train a meta-XGBoost classifier, contributing to a final robust prediction. This work's significance lies in advancing phishing detection with AntiPhishStack, operating without prior phishing-specific feature knowledge. Experimental validation on two benchmark datasets, comprising benign and phishing or malicious URLs, demonstrates the model's exceptional performance, achieving a notable 96.04% accuracy. This research adds value to the ongoing discourse on symmetry and asymmetry in information security and provides a forward-thinking solution for enhancing network security in the face of evolving cyber threats.

We consider a constrained optimal control problem and an extension of it, in which the set of strict-sense trajectories is enlarged. Extension is a common procedure in optimal control, used to derive necessary and sufficient optimality conditions for the original problem from the extended one, which usually admits a minimizer and has a more regular structure. However, this procedure fails if the two problems have different infima. It is therefore relevant to identify such situations. Following on from earlier work by Warga but adopting perturbation techniques developed in non-smooth analysis, we investigate the relation between the occurrence of an infimum gap and abnormality of necessary conditions. For a notion of local minimizer based on control distance and an extension including the impulsive one, we prove that (i) a local extended minimizer which is not a local minimizer of the original problem and (ii) a local strict-sense minimizer which is not a local minimizer of the extended problem, both satisfy the extended maximum principle in abnormal form. The main novelty is result (ii), as until now it had only been shown that a strict-sense minimizer which is not an extended minimizer is abnormal for an `averaged version’ of the maximum principle.

As of today, 20 disease modifying drugs (DMD) have been approved for the treatment of relapsing multiple sclerosis (MS) and, based on their efficacy, they can be grouped into moderate-efficacy DMDs and high-efficacy DMDs. The choice of the drug mostly relies on the judgement and experience of neurologists and the evaluation of therapeutic response can only be obtained by monitoring clinical and magnetic resonance imaging (MRI) status during follow up. In an era where therapies are focused on personalization, the aim of this study is to develop a modeling infrastructure to predict the evolution of relapsing MS and the response to treatments. We built a computational modeling infrastructure named UISS (Universal Immune System Simulator) able to simulate the main features and dynamics of the immune system activities. We extended UISS to simulate all the underlying MS pathogenesis and its interaction with the host immune system. This simulator is a multi-scale, multi-organ, agent based simulator with an attached module capable of simulating the dynamics of specific biological pathways at the molecular level. We simulated six MS patients with different relapsing-remitting courses. These patients were characterized on the basis of their age, sex, presence of oligoclonal bands, therapy and MRI lesion load at onset. The simulator framework is made freely available and can be used following the links provided in the availability section. Even though the model can be further personalized employing immunological parameters and genetic information, based on the available data we generated a few simulation scenarios for each patient, including those who matched the real clinical and MRI history. Moreover, for two patients, the simulator anticipated the timing of subsequent relapses, which really occurred, suggesting that UISS may have the potential to assist MS specialists in predicting the course of the disease and the response to treatment.

The flexitarian diet, which emphasizes a reduction in meat consumption, has been identified as a crucial factor in transitioning to sustainable food systems that can help combat climate change and improve food and nutritional security, particularly in areas where food choices are abundant. Despite Brazil being a major meat producer, meat consumption among Brazilians has been decreasing in recent years, with a growing portion of the population adopting meat-free and meat-reduced dietary models. In this study, we conducted the first non-industry funded scientific investigation of Brazilian flexitarians, with the goal of characterizing their socio-economic and demographic characteristics, motivations for adopting flexitarianism, frequency of animal-based meat consumption, and main substitutes consumed. Data was collected from 1029 self-identified flexitarians in Brazil. Our findings indicate that the flexitarian food model is primarily adopted by women and is motivated by concerns about the environmental impact of meat consumption, personal health, and animal welfare. Flexitarians were found to have a consumption profile that can be divided into three groups: low (consuming meat 36 times a week), medium (consuming meat 7 times a week), and high (consuming meat 4 times a week). The flexitarian meals pattern is characterized by lower consumption of beef (less than 2 times per week) and higher consumption of chicken (3 times per week) and is supplemented by plant-based protein sources and eggs as the main meat substitutes.

The UK aviation industry is committed to achieving net zero emissions by 2050 through sustainable measures, and one of the key aspects of this effort is the implementation of Unmanned Traffic Management (UTM) systems. These UTM systems play a crucial role in enabling the safe and efficient integration of unmanned aerial vehicles (UAVs) into the airspace. As part of the Airspace of the Future (AoF) project, the development and implementation of UTM services have been prioritized. The paper aims to create an environment where routine drone services can operate safely and effectively. To facilitate this, a digital twin of the National Beyond Visual Line of Sight Experimentation Corridor has been created. This digital twin serves as a virtual replica of the corridor and allows for the synthetic testing of unmanned traffic management concepts. The implementation of the digital twin involves both simulated and hybrid flights with real drones. Simulated flights allow for the testing and refinement of UTM services in a controlled environment. Hybrid flights, on the other hand, involve the integration of real drones into the airspace to assess their performance and compatibility with the UTM systems. By leveraging the capabilities of UTM systems and utilizing the digital twin for testing, the AoF project aims to advance the development of safer and more efficient drone operations. Experimentation Corridor has been developed to simulate and test concepts related to managing unmanned traffic. The paper provides a detailed account of the implementation of the digital twin for the AoF project, including simulated and hybrid flights involving real drones.

The horizontal flatbed electrophoresis system has been used for the electrophoresis of protein samples and is often preferred for a two-dimensional polyacrylamide gel electrophoresis. In currently available equipment, cathode and anode electrodes were placed on top of a gel at each end. An electric field entered from the top of a gel, and its strength was relatively weaker in the bottom part of the gel. Such configuration caused migrating protein bands to lie down forward in the migrating direction. New electrodes, i.e., the clamp-shaped and the double-deck electrodes, were developed to simultaneously apply an electric field from the top and bottom of a gel. Electrophoretic separation with these electrodes made protein bands more focused and improved protein band resolutions. When the FIGE technique was tested together with new electrodes, protein bands were aligned nearly vertically and showed the best electrophoretic resolutions.

In the realm of agribusiness, transformative shifts are underway, propelled by the growing demands and expanding scales of grain production. This evolution calls for a critical reevaluation of the existing paradigms in coffee production and marketing paradigms, with a specific focus on integrating Artificial Intelligence (AI). This work aims to review, synthesize, and summarize the available data regarding how Machine Learning (ML) has been used to detect and classify characteristics in coffee beans and leaves. For this purpose, a comprehensive literature review of the most significant research contributions describing the application of AI for advanced classification techniques in coffee agriculture has been carried out. Our analysis suggests that implementing AI technologies allows the classification of coffee, encompassing various attributes such as maturity, roast intensity, disease identification, flavor profiles, and overall quality. More largely, this technological advancement holds the potential to revolutionize coffee farming by providing producers and agricultural specialists with sophisticated tools to enhance production efficiency, minimize costs, and improve the accuracy and confidence of their decision-making processes.

Background This study aimed to examine the acute effects of different pre-ST strategies on muscular performance and blood pressure (BP) responses in recreationally strength-trained women. Methods: Twelve overweight women with normal-to-elevated BP were recruited and performed six exper-imental protocols in a randomized order: 1) control protocol (CC) – BP assessed without exercises performed, 2) strength training (ST), 3) foam rolling warm-up followed by strength training (FR+ST), 4) specific warm-up followed by strength training (SW+ST), 5) aerobic exercise followed by strength training (AE+ST), and 6) stretching exercises followed by strength training (SE+ST). Strength training consisted of three sets at 80% of 10RM with a self-suggested rest interval between sets for bench press, back squat, bench press 45º, front squat, lat pull-down, leg press, shoulder press, and leg extension. Results: All experimental protocol had a lower total training volume, fa-tigue index, and repetitions performance in relation to ST (p

The extensive use of engineered nanoparticles (ENPs) such as zinc oxide nanoparticles (ZnO NPs) in various commercial fields has spurred significant concern about its possible toxicological effects of ZnO NPs on human health and eco-system. Therefore, it is substantial to understand the aggregation phenomena which could attenuate this effect. This data article provides information on aggregation of ZnO NPs under the influence of various parameters of water chemistry. Moreover, Taguchi orthogonal array L27(313) design matrix was used to evaluate the effect of multiple parameters in aqueous solution. The data were obtained from single beam UV-Vis spectrophotometer (Optizen 2120 UV, Mecasys, Korea) using Optizenview 4.2.5 PC interference software, Fourier transform infrared spectrometer (FT/IR-4700, spectroscopy, JASCO Analytical Instruments, Easton, USA) and particle electrophoresis (NanoZS, Zetasizer, Malvern Instruments Ltd, Worcestershire, UK). The dataset draws attention on dominant parameters influencing aggregation of ZnO NPs in water. The analysis of variance (ANOVA) data revealed that electrolyte concentration, type and natural organic matter (NOM) concentration were the most significant parameters. Furthermore, FT-IR data presents a possible mechanism of ZnO NPs stabilization in the presence of different NOM. This data will be helpful for the development of environmental risk assessment strategies and prediction of fate and mobility of other ENPs in the aquatic environment.

Leishmania parasites present astonishing adaptative abilities that represent a matter of life or death within disparate environments during the heteroxenous parasite life cycle. From an evolutionary perspective, organisms develop methods of overcoming such challenges. Strategies that extend beyond the genetic diversity have been discussed and include variability between parasite cells during the infections of their hosts. The occurrence of Leishmania subpopulation fluctuations with variable structural genomic contents demonstrates that a single strain might shelter the variability required to overcome inconsistent environments. Such intrastrain variability provides parasites with an extraordinary ability to adapt and thus survive and propagate. However, different perspectives on this evolution have been proposed. Strains or species living in the same environment can cooperate but also compete. These interactions might increase the replication rate of some parasites but cause the loss of more aggressive competitors for others. Adaptive responses to intra- and interspecific competition can evolve as a fixed strategy (replication is adapted to the average genetic complexity of infections) or an optional strategy (replication varies according to the genetic complexity of the current infection). This review highlights the complexity of interspecies and intrastrain interactions among Leishmania parasites as well as the different factors that influence this interplay.

Graphene hybrid-filler polymer composites have emerged as prominent materials that revolutionize heavy industries. This study encapsulates the in-depth analysis of different influential factors such as filler/graphene type, aspect ratios, dispersion methods, filler-matrix compatibility, fiber orientation, synergistic effects, different processing techniques, and post-curing conditions that affect the processing, properties and determine the resultant applications of graphene hybrid polymer composites. Additionally, it discusses the substantial role of graphene collaboration with other fillers such as carbon nanotubes, silica, nano-clays and metal oxides to produce functionalized hybrid polymer composites with synergistically enhanced tailored properties to offer solutions for heavy industries like aerospace, automotive, electronics, and energy harvesting. The review concludes with some suggestions and outlook on the future of these composite materials by emphasizing the need for continued research to fully optimize their potential.

The videofluorographic study is indicated for diseases potentially causing dysphagia and aspiration, such as gastrointestinal reflux disease, cancers of the oropharynx and esophagus, and certain neurologic diseases needing swallowing assessment. The study is designed to survey the anatomy and physiology of swallowing to diagnose any swallowing impairment and is standardized using scales such as the Modified Barium Swallow Impairment Profile (MBSImP). The procedure requires the patient to swallow a barium contrasted bolus which helps to visualize and obtain a real-time result. There are certain complications of the procedure including radiation exposure which requires necessary safety protocols to be followed.

The goal of this study was to characterize the initial growth trajectory of Epicrates assisi, 1 Epicrates cenchria, and Epicrates crassus snakes raised in captivity. An exponential model with 2 parameters for birth weight (A) and growth rate (k) was fitted for each animal. There was a significant 3 difference A and k among the three species, the means (standard error) for A and k parameters were 4 31 (0.3) g and 0.0027 (0.00006) for E. assisi, 27.6 (0.6) g and 0.0046 (0.00013) for E. cenchria and 25.9 5 (1.4) g and 0.0033 (0.00027) for E. crassus. We showed a significative variability between species for 6 initial growth trajectory. In addition, we also demonstrated the existence of variability within species, 7 which can be used to change the growth trajectory of snakes, being a tool for selection and genetic 8 improvement.9

Background The acknowledgment of computed tomography (CT) defined diagnosis in high prevalence northern Italy may identify more patients with Coronavirus Disease-2019 (COVID 19) infection, than RT-PCR alone. Methods We retrospectively reviewed 148 chest CT scans of oncological patients who were referred to the Radiological Unit of Policlinico S. Marco from 1st of February 2020 to 30th of April 2020, during the Covid-19 outbreak in Bergamo area. Therefore, we analyzed RT-PCR tests of these 148 patients. Results Among 32 patients with diagnosis of COVID-19 infection: 17 patients were asymptomatic or had mild symptoms (53.1%), while 15 developed severe disease (46.8%). The incidence of COVID-19 infection is 22.9%, the mortality rate is 18.8%. Severe COVID-19 disease is associated with higher median age. We did not find any correlation between disease severity and sex, smoke or cardiovascular comorbidities. Remarkably, patients who were on treatment developed milder disease than cancer patients who were not on treatment. Conclusions The acceptance of CT-defined diagnosis in high prevalence area like Bergamo highlighted a larger number of COVID-19 oncological population than RT-PCR alone, in particular asymptomatic and mild symptomatic patients. We observed that actively treated patients had milder disease, according to previous studies that suggested a protective role of immunosuppression.

High Resolution Melting Analysis (HRM) has been pointed as a suitable alternative method to detect and identify Leishmania species. Herein, we aimed to evaluate the sensitivity, specificity, accuracy, and limitations of a HSP70-HRM protocol both as a diagnostic scheme applied in clinical samples and as a species typing tool for laboratory research and reference services. Our data reveal the pronounced species-typing potential of the HSP70-HRM in DNA from cultured parasites. For clinical samples, however, we advise caution due to the parasite load-dependent accuracy. In the light of these findings and considering the importance of parasite load determination for clinical and research purposes we recommend the integration of the presented typing scheme and the previously published Leishmania quantifying approach as combined tools for clinicians, surveillance, and research.

Hollow and concrete-filled steel tubes (CFSTs) are widely used as columns in many structural systems and local buckling can occur when they are subjected to axial compression loading. The critical regions for the local buckling of the columns are near the ends of the column where the moments are the highest. To strengthen the critical regions of the CFSTs the CFRP provides a simple and effective method which used previously as an enhancement for both of strength and ductility. So, this study suggests investigating the axial load behaviour of CFST strengthened with CFRP using FE method after a verification study and then a various parametric studies were carried out to cover the effect of the CFRP layers, number, confinement length and position. The FE results proved that, one CFRP sheet with thickness equal to 1.2 mm was strengthened the composite column by 8.5%, two CFRP sheets with total thickness equal to 2.4 mm was strengthened the composite column by 23.5%, three CFRP sheets with total thickness equal to 3.6 mm was strengthened the composite column by 35.1% and four CFRP sheets with total thickness equal to 4.8 mm was strengthened the composite column by 44.5%. Moreover, this study proved that by strengthened the composite columns with CFRP sheets with different lengths, the axial load resistance was improved by 8.5%, 4.6%, 0.1% and 0.0% for length percentages 100%, 75%, 50% and 25% respectively.

Nowadays, there is an increasing concern about environmental challenges ranging from emissions to overconsumption. Most of the environmental problems today are direct consequences of human consumption. Understanding the factors that affect consumer purchasing decisions is critical to developing demand for and commitment to sustainable consumption. In this regard, this study aims to explore the environmentally sustainable consumption behavior of Ethiopian consumers by using an extended model of the theory of planned behavior. Data were collected using a self-administered questionnaire having open and closed-ended questions. A total of 523 Ethiopian consumers were selected using convenience sampling technique. Structural equation modeling with AMOS V.26.0. was applied for data analysis. The findings show that Ethiopian consumers have very low awareness about the impact of their clothing consumption and disposal. Their consideration of sustainability attributes during purchasing decisions is also low. The structural equation model analysis showed that all variables had a positive and significant effect on the dependent variables at p<0.05, except the effect of personal norms on an environmentally responsible purchasing intention. These results provide additional evidence on the role of environmental labels in purchasing sustainable apparel products. The results of the study allow a better understanding of the factors determining sustainable consumption behavior and suggest practical solutions to their producers. As theory-building activities, with implications for the conceptualization of sustainable consumption behavior are sparse in the literature, this work has also been able to detect sustainable consumption behavior trends and practices by using the availability of a sustainable apparel product and consumers price perceptions of environmentally responsible apparel as a mediating effect of intention and behavior in developing countries, particularly Ethiopia.

Background: Acute intermittent porphyria (AIP) is caused by haploinsufficiency of porphobilin-ogen deaminase (PBGD) enzymatic activity. Acute attacks occur in response to fasting and altera-tions in glucose metabolism, insulin resistance and mitochondrial turnover may be involved in AIP pathophysiology. Therefore, we investigated the metabolic pathways in PBGD-silenced hepatocytes and assessed the efficacy of an insulin-mimic, the α-lipoic acid (α-LA) as a potential therapeutic strategy. Methods: HepG2 cells were transfected with a siRNA targeting PBGD (siPBGD). Cells were cul-tured with low glucose concentration to mimic fasting and exposed to α-LA alone or with glu-cose. Results: At baseline, siPBGD cells showed lower expression of genes involved in glycolysis and mitochondrial dynamics along with reduced total ATP levels. Fasting further unbalanced gly-colysis by inducing ATP shortage in siPBGD cells and activated DRP1, which mediates mito-chondrial separation. Consistently, siPBGD cells in fasted state showed the lowest protein levels of Complex IV which belong to the oxidative phosphorylation (OXPHOS) machinery. α-LA up-regulated glycolysis and prompted ATP synthesis and triglyceride secretion, thus possibly providing energy fuels to siPBGD cells by improving glucose utilization. Finally, siPBGD exposed to α-LA plus glucose raised mitochondrial dynamics, OXPHOS activity and energy production. Conclusions: α-LA-based therapy may ameliorate glucose metabolism and mitochondrial dys-functions in siPBGD hepatocytes. Keywords: AIP, PBGD, glucose metabolism, mitobiogenesis, α-lipoic acid

Pancreatic neuroendocrine tumor (P-NET) is a rare neoplasm originating in the neuroendocrine system. Carcinoid syndrome occurs in approximately 19% of patients with functional P-NETs, typically when liver metastases occur. NETs diagnosis is frequently late, along with symptoms related to hormone hypersecretion. We described the case of a patient with a low-grade non-functional P-NET, but with a typical clinical presentation of a carcinoid syndrome; moreover, we reviewed the literature regarding this topic. An 81-year-old male was admitted to our Department of Internal Medicine at Cannizzaro Hospital (Catania, Italy) because of the onset of abdominal pain with nausea, loose stools and episodic flushing. Firstly, an abdominal contrast-enhanced CT scan showed a small pancreatic hypervascular mass; then a gallium-68 DOTATOC integrated PET/CT revealed an elevated expression of SSTR receptors. Serum Chromogranin A and urinary 5-HIAA measurements resulted negative. Given the small size of the lesion (8 mm), we preferred to perform an endoscopic ultrasonography (EUS) with fine-needle biopsy (EUS-FNB), allowing the diagnosis of low-grade (G1) non-functional P-NET (NF-P-NET). Surgery was waived, while a follow-up strategy was chosen. Early recognition of P-NETs, although rare, is necessary to improve patient’s survival. EUS-FNB should be the protocol of choice for an early characterization of these tumors.

Background: To compare photodynamic therapy 41 and the use of probiotics in reducing halitosis assessed through gas chromatography and microbiome analysis. Methods: Participants aged from 18 to 25 years, showing sulfide (SH2) ≥ 112 ppb on gas chromatography, were selected. They were divided into 4 treatment groups: Group 1 - Tongue Scraping; Group 2- Antimicrobial Photodynamic Therapy (aPDT); Group 3- Probiotics; Group 4- Antimicrobial Photodynamic Therapy (aPDT) and Probiotics. The halimetry process was performed before, immediately after the treatments, 7 days, 14 days and 30 days after the initial collection. The collections for later microbiological analysis were made along with the halimetry, for the microbiome analysis. Results: Treatment with aPDT or probiotics under these experimental conditions was not able to change the bacteria present in the biofilm of the tongue. Conclusions: More research is needed to know the behavior of the oral microbiome in the presence of halitosis and the effectiveness of new treatments.

Complex interactions between gene variants and environmental risk factors underlie the pathophysiological pathways in major psychiatric disorders. Autism Spectrum Disorder is a psychiatric condition in which susceptible alleles along with epigenetic memories contribute to the mutational landscape of the ailing brain. The present work reviews recent evolutionary, molecular, and epigenetic mechanisms potentially linked to the etiology of autism. First, we present a clinical vignette to describe clusters of maladaptive behaviors frequently diagnosed in autistic patients. Next, we microdissect brain regions pertinent to the nosology of autism as well as cell networks from the bilateral body plan. Lastly, we catalog a number of pathogenic environments associated with disease risk factors. This set of perspectives provides emerging insights into the dynamic interplay between epigenetic and environmental variation in the development of Autism Spectrum Disorders.

This study assessed the impacts of genotypes, environments, and their interaction on the performance of elite cowpea lines for key adaptive, grain yield, and associated traits across different locations. A total of 42 elite genotypes were evaluated in five Nigerian environments, representing various savanna ecologies during the 2021 growing season. The experimental design employed was an alpha lattice arrangement, replicating each genotype three times. The results revealed significant differences among genotypes, environments, and genotype-by-environment interaction for most traits, including days to maturity, 100 seed weight, and grain yield. GGE biplot showed G21 (IT14K-2111-2) and G25 (IT15K-2386-1) as the most stable genotypes across the five environments, G41(IT1K-61-82) was best adapted to Ibadan and Shika, G5 (245-1) was best adapted to Bagauda and Gumel while G30 (IT16K-2365-1) was best adapted to Bauchi. G21 and G25 could be recommended across the five test environments while G41, G30 and G5 are specific to the adapted environments.

The organic solar cells (OSCs) have drawn attention in the past decade due to its cynosure in industrial manufacturing because of its promising properties such as low weight, highly flexible and low cost production. However, low η restricts the utilization of OSCs for potential application such as low cost energy harvesting devices. In this paper, OSCs structure based on triple junction tandem scheme is reported with three different absorber materials with the objective to enhance the absorption of photons which in turn improves the η, as well as its correlating performance parameters. The investigated structure gives the higher value of η = 14.33% with Jsc=16.87 (mA/m2), Voc=1.0 (V), and FF=84.97% by utilizing a stack of three different absorber layers with different band energies. The proposed structure is tested under 1.5 (AM) with 1 sun (W/m2). The impact of top, middle and bottom sub cells thickness on η is analyzed with a terse to find the optimum thickness for three sub cells to extract high η. The optimized structure is then tested with different electrode combination and the highest η is recorded with FTO/Ag. Moreover, the influence of upsurge temperature is also demonstrated on the proposed structure and observed that the upsurge temperature has greatly affected the electrical parameters of the device and η decreases from 14.33% to 11.40% when the temperature of the device rises from 300-400 K.

The concept of gray-zone lymphoma (GZL) has been progressively refined since its in-troduction in the literature in 1998. For several years, it was applied to a rather broad spectrum of conditions, posing the problem of the differential diagnosis between any type of Hodgkin lymphoma (HL) and diffuse large B-cell lymphoma, with special reference to primary mediasti-nal forms (PMBL). Officially recognized as a provisional entity in the 4th and revised 4th editions of the WHO Classification of Tumour of Haematopoietic and Lymphoid Tissues with the term “B-cell lymphoma unclassifiable with features intermediate between diffuse large B-cell lym-phoma and classical Hodgkin lymphoma”, it was limited to tumours, which showed either morphologic features reminiscent of classical HL (CHL) but carrying a complete B-cell pheno-type or conversely provided with a PMBL morphology but revealing CHL phenotypic charac-teristics. The definition of GZL has been further revised in the recently published International Lymphoma Classification and 5th Edition of the WHO Classification of Haemato-lymphoid Tu-mours, which have limited it to mediastinal neoplasms based on emerging molecular evidences. The aim of this review is to critically discuss the issue of GZL, also in the light of the suboptimal response to current therapies.

Although metastasis is the primary cause of death on patients with malignant solid tumors, efficient antimetastatic therapies are not clinically available thus far. Sulfated glycosaminoglycans from marine sources have shown promising pharmacological effects, acting in different steps of the metastatic process. Oversulfated dermatan sulfate from ascidians is effective in preventing metastasis by inhibition of P-selectin, a platelet surface protein involved in the platelet-tumor cell emboli formation. We report in this work that the heparan sulfate isolated from the viscera of the ascidian Phallusia nigra drastically attenuates metastasis of colon carcinoma cells in mice. Our in vitro and in vivo assessments demonstrate that the P. nigra glycan has very low anticoagulant and antithrombotic activities and a reduced hypotension potential, although efficiently preventing metastasis. Therefore, it may be a promising candidate for the development of a novel anti-metastatic drug.

Background and Aim: Pancreatic cancer (PC) is a highly aggressive malignancy associated with low survival rates. Many chemotherapeutic regimens have been investigated for advanced unresectable and metastatic PC, but with only minimal improvement in survival and prognosis. The present study aimed to investigate the anti-cancer function of free and nano-encapsulated hydroxytyrosol (Hyd) and curcumin (Cur), and its combinations (Hyd-Cur) on the PANC-1 cell line.Methods: The poly lactide-co-glycolide-co-polyacrylic acid (PLGA-co-PAA) nano-encapsulated Hyd and Cur were synthesized, and MTT assay was performed to evaluate cytotoxic effects of free and nano-encapsulated Hyd, Cur, and Hyd-Cur. Moreover, effects of free and nano-encapsulated Hyd, Cur, and Hyd-Cur were evaluated on viability, migration, morphological alterations, colony formation, and apoptosis on PANC-1 cell line. The mRNA expression levels of MMP2, MMP9, BAX, BCL-2, and Cas9 genes were assessed after treated PANC-1 cells with free and nano-encapsulated Hyd, Cur, and Hyd-Cur.Results: The obtained results showed that free and nano-encapsulated Hyd, Cur, and Hyd-Cur treatments significantly decreased the viability, migration, and colony formation in the PANC-1 cells. Furthermore, apoptosis rates in PANC-1 cells were increased in a concentration and time dependent manner in all of the treatment groups. Moreover, anti-proliferative activity of nano-encapsulated Hyd-Cur was significantly more than other treatments.Conclusion: According to our results, Hyd-Cur combination and nano-encapsulation therapy exerts more profound apoptotic and anti-proliferative effects on PANC-1 cell line than free Hyd or Hyd monotherapy.

Vascular inflammation is recognized as the primary trigger of acute coronary syndrome (ACS). However, current noninvasive methods are not capable of accurately detecting coronary inflammation. Epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT), in addition to their role as an energy reserve system, have been found to contribute to the development and progression of coronary artery calcifica-tion, inflammation, and plaque vulnerability. They also participate in the vascular re-sponse during ischemia, sympathetic stimuli, and arrhythmia. As a result, the evalua-tion of EAT and PCAT using imaging techniques such as computed tomography (CT), cardiac magnetic resonance (CMR), and nuclear imaging has gained significant atten-tion. PCAT-CT attenuation, which measures the average CT attenuation in Hounsfield units (HU) of the adipose tissue, reflects adipocyte differentiation/size and leukocyte infiltration. It is emerging as a marker of tissue inflammation and has shown prognos-tic value in coronary artery disease (CAD), being associated with plaque development, vulnerability, and rupture. In patients with acute myocardial infarction (AMI), an in-flammatory pericoronary microenvironment promoted by dysfunctional EAT/PCAT has been demonstrated, and more recently, it has been associated with plaque rupture in non-ST-segment elevation myocardial infarction (NSTEMI). Endothelial dysfunc-tion, known for its detrimental effects on coronary vessels and its association with plaque progression, is bidirectionally linked to PCAT. PCAT modulates the secretory profile of endothelial cells in response to inflammation and also plays a crucial role in regulating vascular tone in the coronary district. Consequently, dysregulated PCAT has been hypothesized to contribute to type 2 myocardial infarction with non-obstructive coronary arteries (MINOCA) and coronary vasculitis. Recently, quan-titative measures of EAT derived from coronary CT angiography (CCTA) have been included in artificial intelligence (AI) models for cardiovascular risk stratification. These models have shown incremental utility in predicting major adverse cardiovas-cular events (MACE) compared to plaque characteristics alone. Therefore, the analysis of PCAT and EAT, particularly through PCAT-CT attenuation, appears to be a safe, valuable, and sufficiently specific noninvasive method for accurately identifying cor-onary inflammation and subsequent high-risk plaque. These findings have been sup-ported by biopsy and in vivo evidence. Although speculative, these pieces of evidence open the door to a fascinating new strategy in cardiovascular risk stratification. The incorporation of PCAT and EAT analysis, mainly through PCAT-CT attenuation, could potentially lead to improved risk stratification and guide early targeted primary pre-vention and intensive secondary prevention in patients at higher risk of cardiac events.

Microbiological control of dental pathologies presents a significant clinical challenge for dental surgeons, particularly considering drug-resistant microorganisms. To address this issue, Antimi-crobial Photodynamic Therapy (PDT) has emerged as an effective and complementary technique for microbial reduction. This therapy involves the application of a photosensitizer dye (PS) either topically or systemically, followed by exposure to low-power lasers with appropriate visible light wavelengths. PDT has found a valuable place in dentistry across various specialties, including surgery, periodontics, endodontics, dentistry, implantology, orthodontics, and pediatrics. In the realm of pediatric dentistry, managing microorganisms during dental treatments has become a major challenge.This article reviews the evidence supporting the potential of photodynamic therapy in combating bacteria, fungi, and viruses, with a particular focus on areas such as endodontics, restoration in deciduous teeth, implantology, and periodontics for bacterial control. Additionally, PDT has shown promise in stomatology, specifically in the treatment of mucositis and herpes. Considering its promising results and ease of application, photodynamic therapy presents an in-teresting alternative for clinical practice. However, it is important to note that specific protocols must be followed for each application, encompassing the type of photosensitizer, concentration, pre-irradiation time, light type, wavelength, energy, power, and mode of light delivery. Researchers have been steadily refining these protocols to facilitate PDT's integration into clinical practice.

Long noncoding RNAs (lncRNAs) are known to play key roles in breast cancers; however, detailed mechanistic studies of lncRNA function have not been conducted in large cohorts of breast cancer tumors, nor have inter-donor and inter-subtype variabilities been taken into consideration. Here we provide the first identification and annotation of the human BORG lncRNA gene. Using multiple tumor cohorts of human breast cancers, we show that while BORG expression is strongly induced in breast tumors as compared to normal breast tissues, the extent of BORG induction varies widely between breast cancer subtypes and even between different tumors within the same subtype. Elevated levels of BORG in breast tumors are associated with the acquisition of core cancer aggression pathways, including those associated with basal tumor and pluripotency phenotypes, and with epithelial-mesenchymal transition (EMT) programs. While a subset of BORG-associated pathways was present in high BORG-expressing tumors across all breast cancer subtypes, many were specific to triple-negative breast cancer tumors. Finally, we show that genes induced by heterologous expression of BORG in murine models of TNBC both in vitro and in vivo strongly overlap with those associated with high BORG levels in human TNBC tumors, indicating that human BORG is a novel driver of the highly aggressive basal TNBC tumor phenotype.

The coffee leaf miner (CLM) Leucoptera coffeella moth is a major threat to coffee production. Insect damage is related to the feeding behavior of the larvae on the leaf. During the immature life stages, the insect feeds in the mesophyll, triggering necrosis and causing loss of photosynthetic capacity, defoliation, and significant yield loss to coffee crops. Chemical control is mandatory to sustain the coffee production chain, though market requirements move towards conscious consumption, claiming for more sustainable methods. In this overview, we discuss aspects about the CLM concerning biology, history, geographical distribution, economic impacts, and the most relevant control strategies in progress. Insights to develop an integrate approach for a safer and eco-friendly control of the CLM are discussed, including bio-extracts, nanotechnology, pheromones, and tolerant cultivars.

The blood counts of α thalassemia carriers (α-thal) are similar to those of β thalassemia carriers, except for Hgb A2 that is not elevated. The objective of this study was to determine whether mathematical formulas are effective for detecting suspected α-thal. The data were obtained from the database of the prevention program for detecting couples at risk for having a child with hemoglobinopathy. RBC indices were analyzed using mathematical formulas and the sensitivity and negative predictive value (NPV) calculated. Among 1334 blood counts suspected α-thal analyzed, only the Shine&Lal and the Support Vector Machine formulas revealed high sensitivity and NPV. Sensitivity was 85.54 and 99.33% and NPV 98.93 and 99.93%, respectively. Molecular defects were found in 291, 81 had normal α genes. Molecular analysis was not performed in 962. Based on these results, mathematical formulas incorporating one of these reliable formulas for detecting suspected α or β thalassemia carriers in the program of the automatic analyzers can flag these results and increase the awareness of the primary physicians about the carrier risk and send an alert with a recommendation for further testing.

Abstract: This study aimed to assess the agronomic performance and yield stability of elite white yam (Dioscorea rotundata) genotypes across diverse Nigerian environments. Twenty-five genotypes were evaluated at three locations in two consecutive growing seasons, 2022 and 2023. The genotypes were assessed for their agronomic performance, tuber yield and related traits using various analytical tools such as AMMI (Additive main effects and multiplicative interaction) and MTSI (Multi-trait stability index). The AMMI analysis revealed significant differences among the genotypes and across the environ-ments for all traits (p

The demand for polymer composites with improved mechanical and electrical properties is crucial for advanced aerospace, electronics, and energy storage applications. Single-walled carbon nanotubes (SWCNTs) and iron oxide (Fe₃O₄) nanoparticles are key fillers that enhance these properties, yet challenges like orientation, uniform dispersion, and agglomeration must be addressed to realize their full potential. This study focuses on developing SWCNTs/Fe₃O₄ epoxy composites by keeping the SWCNT concentration constant at 0.03 Vol.% and varying Fe₃O₄ concentrations at 0.1, 0.5, and 1 Vol.% with two different configurations: randomly orientated (R-) and magnetic field-assisted horizontally aligned (A-) SWCNTs/Fe3O4 epoxy composites and investigates the effects of filler concentration, dispersion, and magnetic alignment on the mechanical and electrical properties. The research reveals that both composite configurations achieve an optimal mechanical performance at 0.5 Vol.% Fe₃O₄, while A- SWCNTs/Fe3O4 epoxy composites outperformed at all concentrations. However, at 1 Vol.% Fe₃O₄, mechanical properties decline due to nanoparticle agglomeration, which disrupts stress distribution. In contrast, electrical conductivity peaks at 1 Vol.% Fe₃O₄, indicating that the higher density of Fe₃O₄ nanoparticles enhances the conductive network despite the mechanical losses. This study highlights the need for precise control over filler content and alignment to optimize mechanical strength and electrical conductivity in SWCNTs/Fe₃O₄ epoxy nanocomposites.

Heart transplantation (HT) represents the mainstream therapy of end-stage heart failure for selected patients with a median survival of more than 10 years after surgery and substantial improvement in quality of life. Current guidelines suggest a variety of examinations including invasive (coronary angiography and endomyocardial biopsy (EBM) and non-invasive methods (echocardiography, stress echocardiography, computed tomography, PET and MRI) to monitor HT patients. Guidelines do not specify the timing of echocardiographic evaluations and do not recommend echocardiography as an alternative to serial EMB in rejection monitoring [2]. They still recommend as gold standard coronary angiography to be done 1 year after surgery and every 2 years after. In this review we will discuss the advantages of non-invasive techniques over the invasive ones for an adequate follow-up of HT patients.

Background: Synovial sarcoma is a rare soft tissue tumor that constitutes 5-10% of all soft tissue sarcomas. Early diagnosis and risk stratification are essential for effective management. This study leverages machine learning models to improve the risk stratification of mortality in synovial sar-coma patients. Methods: This retrospective cohort study utilized data from the Surveillance, Epidemiology, and End Results (SEER) database to analyze patients diagnosed with synovial sarcoma between 2004 and 2015, as well as a validation cohort diagnosed from 2018 onward. The dataset encompassed demographic data, clinical characteristics, staging, treatment modalities, and outcomes. Four ma-chine learning models—support vector classifier (SVC), k-nearest neighbors (KNN), Gaussian naive Bayes, and gradient boosting—were trained and evaluated. Model performance was assessed using sensitivity, specificity, AUC-ROC, and Brier score. SHAP analysis was performed to determine the most influential features impacting model predictions. The top-performing model was validated using the 2018+ cohort. Results: The study included a total of 762 patients, with an average age of 39.4 years. The support vector classifier (SVC) outperformed the other models, achieving an AUC-ROC of 0.8153 (95% CI: 0.7578 to 0.8677) and a Brier score of 0.1715. Upon external validation with the 2018+ cohort, the SVC model yielded an AUC-ROC of 0.8179 (95% CI: 0.7632 to 0.8666). Key prognostic factors identified through SHAP analysis included tumor size, patient age, presence of metastasis, tumor differentiation, and cancer stage. Conclusion: Machine learning models can be used to stratify the risk of death in synovial sarcoma patients effectively, with the support vector classifier showing the most promise.

Advanced heart failure (AHF) presents a complex landscape with challenges spanning diagnosis, management, and patient outcomes. In response, the integration of multimodality imaging techniques has emerged as a pivotal approach. This comprehensive review delves into the profound significance of these imaging strategies within AHF scenarios. Multimodality imaging, encompassing echocardiography, cardiac magnetic resonance imaging (CMR), and cardiac computed tomography (CCT), stands as a cornerstone in the care of patients with both short- and long-term mechanical support devices. These techniques facilitate precise device selection, placement, and vigilant monitoring, ensuring patient safety and optimal device functionality. In the context of orthotopic cardiac transplant (OTC), the role of multimodality imaging remains indispensable. Echocardiography offers invaluable insights into allograft function and potential complications. Advanced methods, like speckle tracking echocardiography (STE), empower the detection of acute cell rejection. CMR and CCT further enhance diagnostic precision, especially concerning allograft rejection and cardiac allograft vasculopathy. This comprehensive imaging approach goes beyond diagnosis, shaping treatment strategies and risk assessment. By harmonizing diverse imaging modalities, clinicians gain a panoramic understanding of each patient's unique condition, facilitating well-informed decisions. Thus, this review underscores the irreplaceable role of multimodality imaging in elevating patient outcomes, refining treatment precision, and propelling advancements in the evolving landscape of advanced heart failure management.

Background: In this investigation, we explored the effects of pharmacological cholinergic stimulation on cardiac function and renal inflammation following acute myocardial infarction (AMI) in spontaneously hypertensive rats (SHRs). Methods: Adult male SHRs were randomized into three experimental groups: sham-operated; AMI+Veh (infarcted, treated with vehicle); and AMI+PY (infarcted, treated with the cholinesterase inhibitor pyridostigmine bromide (PY) - 40 mg/kg, once daily for seven days). Rats were euthanized 7 or 30 days post-surgery. Clinical parameters were assessed on the day before euthanasia. Subsequent to euthanasia, blood samples were collected and renal tissues were harvested for histological and gene expression analyses aimed to evaluate inflammation and injury. Results: Seven days post-surgery, the AMI+PY group demonstrated improvements in left ventricular diastolic function and autonomic regulation, and a reduction in renal macrophage infiltration compared to the AMI+Veh group. Furthermore, there was a notable downregulation of pro-inflammatory gene expression and an upregulation of anti-inflammatory gene expression. Analysis 30 days post-surgery showed that PY treatment had a sustained positive effect on renal gene expression, correlated with a decrease in biomarkers indicative of subclinical kidney injury. Conclusion: Short-term cholinergic stimulation with PY provides both cardiac and renal protection by mitigating the inflammatory response after AMI.

STUDY QUESTION: Which are the main research interests among patients of assisted reproductive technologies (ART)? SUMMARY ANSWER: Patients identified as research priorities that deserve further investigation: success rates and risks of ART, side-effects of treatments, resources to cope with infertility, effectiveness of alternative therapies, lifestyle habits to protect fertility, oocyte quality and ovarian reserve, and causes of genetic or hereditary infertility. WHAT IS KNOWN ALREADY: The involvement of patients and caregivers in setting research agendas in medicine has gathered significant momentum in the last decade. Patients’ involvement in setting research priorities offers several benefits: improved patient knowledge and awareness of their condition; greater understanding of the medical professionals of the impact of the condition on patients’ quality of life; reduced costs associated with redundant research activities. This is may be also applicable to research in infertility and ART, where patients’ interests have never been explored before. STUDY DESIGN, SIZE, DURATION: This is a cross-sectional study that consists of an anonymous online survey, which was sent up to three times to 2112 patients from 11 fertility centers in 5 countries between January-December 2018. The study design was based on the James Lind Alliance priority setting partnership model, which comprises the identification of patients groups, the exploration of the research agenda, the analysis of collected data and identification of priorities. PARTICIPANTS/MATERIALS, SETTING, METHODS: Overall, 2112 patients were contacted, and 945 surveys were answered (RR: 44.7%). Patients were asked to identify research questions relevant to them in the areas of infertility causes and prevention, fertility treatments (medication and ART), and the emotional aspects of infertility. Answers were categorized in topics and ranked by frequency. A long list of the top-30 research topics was extracted from the aggregate results, from which, a short list of the top-10 research topics was created. At the end, 10 research questions related to each of the 10 research topics were constructed, based on the answers given by patients. MAIN RESULTS AND THE ROLE OF CHANCE: Female (845, 89.4%) and male (100, 10.6%) patients were included. The mean age of patients was 37.8 (SD 1.74). Most of the patients did not have children at the time of the survey (523, 59%), while 51 (5.7%) were pregnant. Sixty (6.3%) patients did not start treatment, 579 (61.3%) were performing a treatment with their own gametes and 304 (32.2%) were treated through gamete donation. Patients were mainly interested in the effectiveness of ART -especially per clinical profile-, side effects of drugs, protection of fertility and prevention of infertility –especially through diet and exercise-, and psychological aspects of the infertility journey. The top-10 research questions (and weight) obtained were: 1) What are the side-effects of ART treatments? (41.6%); 2) What are the most effective methods to cope with infertility from the psychological point of view? (37.2%); 3) What effects could diet have on fertility? (25.9%); 4) What are ART success rates per clinical profile? (25.9%); 5) Are there habits and lifestyle factors that could prevent infertility? (20.0%); 6) What are the long-term risks associated to ART? (18.5%); 7) Are alternative therapies such as acupuncture, yoga, and meditation effective to treat/prevent infertility? (18.5%); 8) What is the impact of exercise on fertility? (15.4%); 9) How does oocytes quantity and quality affect fertility? (9.5%); 10) What are the genetic patterns or hereditary conditions causing/related to infertility? (9.5%). LIMITATIONS, REASONS FOR CAUTION: Although all respondents had attended a fertility center, not all of them were diagnosed as infertile (i.e. single women) and had started treatment at the time of response, while a few were pregnant; their priorities for research might have been influenced by their infertility journey. Also, all participants attended private fertility centers: areas of interest may be different in public settings. WIDER IMPLICATIONS FOR THE FINDINGS: Researchers and clinicians should keep in mind that, in addition to improvement of treatments’ success rates and side-effects, patients greatly value research on causes, prevention and emotional aspects of infertility. As their views might differ from those of medical professionals, patients’ voices should be incorporated in setting infertility research priorities.

This study investigated the effects of dietary garlic powder and fermented garlic powder supplementation at 1% and 2% levels on growth performance, digestive tract efficacy, blood biochemistry, immunity, and antioxidant status of Liza ramada (n=225 fish; 86.00±0.42 g) over a 60-day period. Fish fed diets supplemented with both forms of garlic at both levels exhibited significantly improved final body weight, weight gain, specific growth rate, and feed conversion ratio compared to the control group. Digestive enzyme activities (amylase, lipase, and protease) were significantly enhanced in all supplemented groups. Blood biochemical analysis revealed reduced glucose levels and increased total protein in garlic-supplemented groups, with no adverse effects on liver or kidney function markers. Immune parameters, including lysozyme activity, bactericidal activity against Streptococcus agalactiae, alternative complement pathway (ACP), and, respiratory burst (NBT) were significantly enhanced in garlic-supplemented groups, with fermented garlic showing more pronounced effects. Antioxidant enzyme activities (SOD, CAT, and GPx) were also significantly increased in all supplemented groups, particularly in those fed fermented garlic. No significant differences in survival rates were observed among treatments. The results suggest that both garlic powder and fermented garlic powder supplementation, especially at the 2% level, can effectively improve growth, feed utilization, immune function, and antioxidant status in L. ramada. Fermented garlic generally demonstrated superior effects, indicating its potential as a beneficial feed additive in aquaculture. Based on these findings, it is recommended to incorporate fermented garlic powder at a 2% level in L. ramada diets to optimize growth performance and health status. Further research is warranted to investigate the long-term effects and cost-effectiveness of this supplementation strategy in commercial aquaculture settings.

In this review, we covered the recent advances in synthesis of gold nanoparticles and their uses in degradation of dyes. This study provides framework to develop a low cost, ecofriendly and highly efficient synthesis of gold nanoparticles. These synthetic methods do not produce any toxic byproduct. The present study is focus on removal of dyes by Au-NPs because gold nanoparticles act as good absorbent for dyes in short time. Synthesis of Au-NPs from plant extract e.g. marine alga, Scutellarin Barbata, A.nigra, Fruit peels, Bacillus marisflavi from raw silk cocoons, amylopectin and poly acrylic acid, L.asparagine, Grephene oxide, IPEI coated Au-NPs. The synthesizes Au-NPs were used further for removal of dyes like methylene blue (MB), Rhodamine B (RB) Degradation, methylene orange, acid red degradation, Congo red.

Leishmaniasis remains a significant global health concern, with current treatments relying on outdated drugs associated with high toxicity, lengthy administration, elevated costs, and drug resistance. Consequently, the urgent need for safer and more effective therapeutic options in leishmaniasis treatment persists. Previous research has highlighted selenium compounds as promising candidates for innovative leishmaniasis therapy. In light of this, a library of 10 selenium-containing diverse compounds was designed and evaluated in this study. The compounds were subjected to screening against L. amazonensis promastigotes, and their cytotoxicity was assessed in NIH/3T3 cells. Among the tested compounds, MRK-106 and MRK-108 displayed the highest potency against L. amazonensis promastigotes while demonstrating reduced cytotoxicity. Notably, MRK-106 and MRK-108 exhibited IC50 values of 3.97 µM, 4.23 µM, respectively, and most of the tested compounds showed low cytotoxicity in NIH/3T3 cells (CC50 &gt; 200 µM). Although these results are promising, additional investigations focusing on intracellular amastigotes are required to determine the antileishmanial activity of the compounds. In conclusion, the identified selenium-containing compounds hold considerable potential as antileishmanial drug candidates and warrant further exploration in subsequent studies. These findings represent a significant step towards the development of safer and more effective therapies for leishmaniasis, addressing the pressing need for novel and improved treatments.

To assess the efficacy of washing cloth masks, we simulated SARS-CoV-2 contamination in tricoline fabric and tested decontaminants to reduce viral particles. Viral suspensions using two variants (B.1.1.28 and P.1) were inoculated in these fabrics, and the inactivation kinetics were evaluated after washing with various household disinfection products (Soap powder, Lysoform®, Hypochlorite sodium and 70% Alcohol), rinse numbers, and exposure times. Afterward, the fabrics were washed in sterile water, viral RNA extracted and amplified using RT-qPCR. Finally, viral replication in cell cultures was examined. Our findings show that all biocidal treatments successfully disinfected the tissue tested. Some products showed less reduction in viral loads, Soap powder (1.60 x 104, 1.04 x 103), Soap powder and Lysoform® (1.60 x 104, 1.04 x 103) and Alcohol 70% (1.02 x 103, 5.91 x 101) respectively. However, when sodium hypochlorite was used, this reduction was significantly increased (viral inactivation in 100% of the washes). After the first wash, the reduction of viral particles was greater for the P.1 variant than for the B.1.1.28 variant (W = 51759, p 0.05). In conclusion the sodium hypochlorite role on cloth masks disinfection may also have implications for future health emergencies as well as recommended by WHO.

Imidazo[1,2-a]pyridines have been studied regarding drug development. The objective of this work was to evaluate the antileukemic capacity of imidazo[1,2-a]pyridine derivatives by screening its ability as a pro-oxidant. Imidazo[1,2-a]pyridine derivatives were synthesized and oral bioavailability and toxicity were analyzed in silico. Redox screening was performed on human Kasumi, KG-1, K562 and Jurkat leukemia cells. The imidazo[1,2-a]pyridine derivative and the most responsive leukemic cell were selected for cytotoxicity, cell proliferation, cell senescence and oxidative stress assays. The predictive toxicity analysis showed a possible effect on the reproductive system, but without mutagenic, carcinogenic or irritability effects. MRK-107 against K562 cells was the compound that showed the best redox profile. MRK-107 did not induce cell death in K562 and monocyte cells. However, this compound was able to decrease cell proliferation and increase cell senescence after 48 and 72 hours. Furthermore, MRK-107 induced oxidative stress in K562 cells after 72h, increasing lipid peroxidation and decreasing reduced glutathione (GSH) contents. This study demonstrated that MRK-107-induced senescence with the involvement of oxidative stress as a possible mechanism of action, addressing this compound as a potential antitumor drug against chronic myeloid leukemia.

Fear extinction requires coordinated neural activity within the amygdala and medial prefrontal cortex (mPFC). Any behavior has a transcriptomic signature that is modified by environmental experiences, and specific genes are involved in functional plasticity and synaptic wiring during fear extinction. Here, we investigated the effects of optogenetic manipulations of prelimbic (PrL) pyramidal neurons on amygdala gene expression to analyze the specific transcriptional pathways involved in adaptive and maladaptive fear extinction. To this aim, transgenic mice were (or not) fear-conditioned and during the extinction phase they received optogenetic (or sham) stimulations over PrL pyramidal neurons. At the end of behavioral testing, electrophysiological (neural cellular excitability and Excitatory Post-Synaptic Currents) and morphological (spinogenesis) correlates were evaluated in the PrL pyramidal neurons. Furthermore, transcriptomic cell-specific RNA-analyses (differential gene expression profiling and functional enrichment analyses) were performed in amygdala pyramidal neurons. Our results show that the optogenetic activation of PrL pyramidal neurons in fear-conditioned mice induces fear extinction deficits, reflected in an increase of cellular excitability, excitatory neurotransmission, and spinogenesis of PrL pyramidal neurons, and in strong modifications of the transcriptome of amygdala pyramidal neurons. Understanding the electrophysiological, morphological and transcriptomic architecture of fear extinction may facilitate the comprehension of fear-related disorders.

All severe cases of SARS-CoV-2 infections are characterized by a high risk of disease progression towards ARDS, leading to bad outcome. Respiratory symptoms in COVID-19 patients often do not correspond to disease’s worsening. A dysregulated host response to the large viral load could play a key role in the disease progression. In our sample median age was 74 years (72-75) and 54% were men. Median period of hospitalization was 9 days. Firstly, we observed an asynchronous trend of neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) in 764 selected among 963 patients who were consecutively recruited in two hospitals (Cannizzaro, S. Marco) in Catania, Italy. NLR values in deceased patients showed an increase from baseline over time. By contrast, CRP tended to fall from baseline to median day of hospitalization in all four subgroups, but steeply increased at the end of hospitalization only in ICU-admitted patients. Then we evaluated the relationships between NLR and CRP as continuous variables with PaO2/FiO2 ratio (P/F). Finally, we made mediation and moderation analyses to determine the link between inflammation (CRP), immune system (neutrophils and lymphocytes) and respiratory failure (P/F). CRP, neutrophils and P/F are linked in the same pathogenetic chain leading to respiratory failure.

To effectively combat the COVID-19 pandemic, the state government of Bahia, Brazil, has distributed intensive and non-intensive care units along the nine regions that divide the state of Bahia, such that COVID-19 patients could be easily hospitalized in health care units located at the same regions where they live. However, the observed hospitalizations networks for COVID-19 patients shows that a considerable number of COVID-19 patients had to travel beyond their region of residence to be hospitalized. Hence, this study indicates that the current distribution of health care units in Bahia, Brazil, is not sufficient to effectively reduce the distances traveled by COVID-19 patients requiring hospitalization. We believe that such unnecessary travels to distant hospitals may put the sick patients as well as healthy people involved in the transportation process in risk, further delaying the stabilization of the COVID-19 pandemic in each region of the state of Bahia.

Rhabdomyosarcoma is a rare cancer arising in skeletal muscle that typically impacts children and young adults. It is a worldwide challenge in child health as treatment outcomes for metastatic and recurrent disease still pose a major concern for both basic and clinical scientists. The treatment strategies for rhabdomyosarcoma include multi-agent chemotherapies after surgical resection with or without ionization radiotherapy. In this comprehensive review, we first provide a detailed clinical understanding of rhabdomyosarcoma including its classification and subtypes, diagnosis, and treatment strategies. Later we focus on chemotherapy strategies for this childhood sarcoma and discuss the impact of three mechanisms that are involved in chemotherapy response including apoptosis, macro-autophagy, and the unfolded protein response. Finally, we discuss in vivo mouse and zebrafish models, and in vitro 3-dimensional bioengineering models of Rhabdomyosarcoma to screen future therapeutic approaches and promote muscle regeneration.

Background: Early diagnosis of postoperative complications is an urgent task, allowing timely prescribing of appropriate therapy and reducing the cost of patient treatment. Prognostic models based on various data could help in the early diagnosis of postoperative complications after cardiac surgery. Objectives: The purpose of the study was to determine whether an integrated approach based on clinical data along with metabolites and biomarkers had greater predictive value than the models built on less data. Methods: The study included patients (n=62) admitted for planned cardiac surgery (coronary artery bypass grafting with cardiopulmonary bypass), who were retrospectively divided into two groups depending on the presence (n=26) or absence (n=36) of postoperative complications of all types. Clinical and laboratory data on the first day after surgery were analyzed. Additionally, patients' blood samples were collected before and on the first day after surgery to determine biomarkers (interleukin-6, procalcitonin, NT-proBNP, high-sensitivity troponin T) and metabolites (8 aromatic and 2 dicarboxylic acids were detected using gas chromatography-mass spectrometry). Results: Patients before surgery, compared with healthy donors, differed in the concentration of metabolites (p &lt; 0.05), and had concentrations of a number of biomarkers exceeding the corresponding reference values. Multivariate PLS-DA models, predicting the presence or absence of postoperative complications, were built using clinical data (ROC-AUC=0.71), concentrations of metabolites and biomarkers (ROC-AUC=0.60), and the entire data set (ROC-AUC=0.75). For comparison we built univariate models using the EuroScore2 (ROC-AUC=0.59) and SOFA (ROC-AUC=0.76) scales; concentrations of lactate (ROC-AUC=0.71), the dynamic changes of 4-hydroxyphenyllactic acid (ROC-AUC=0.69), and the sum of three sepsis-associated metabolites (ROC-AUC=0.70). The proposed complex model using entire data set was comparable to the SOFA scale, which confirms the expediency of searching for new predictive models based on a variety of factors.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

The impact of interaction SS with MJO on rainfall along Java Island to East Nusa Tenggara has been studied using daily rainfall observation data from 2140 weather observation stations, which are also equipped with GSMaP, OLR, and ERA5 data. There were 61 SS events found, 17 during active MJO and 44 in inactive MJO. Rainfall increases more in the western study area when the active MJO and more in the eastern study area when the inactive MJO is due to SS. SS reduces rainfall in the Jakarta region, regardless of the activity or inactivity of the MJO. SS causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the IMC, SS predominates over MJO in supporting increased water vapor transport. Large-scale synoptic circulations like the monsoon, SS, and MJO can interact with local land-sea wind circulation to produce spatiotemporal variability in rainfall on Java Island. Rainfall mostly increases in the afternoon and decreases in the morning when SS occurs, whether there is MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by lowering CIN and raising VIMFC.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

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

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Currently there are fewer depth models applied to pepper picking detection, while the existing generalized neural networks have problems such as large model parameters, long training time, and low model accuracy.In order to solve the above problems, this paper proposes a Yolo-chili target detection algorithm for chili pepper detection. First, the classical target detection algorithm yolov5 is used as a benchmark model, and an adaptive spatial feature pyramid structure combining the attention mechanism and the idea of multi-scale prediction is introduced to improve the model's detection effect on occluded peppers and small target peppers. Secondly, a three-channel attention mechanism module is introduced to improve the algorithm's long-distance recognition ability and reduce the interference of redundant testers. Finally, the quantized pruning method is used to reduce the model parameters and realize the lightweight processing of the model. Applying the method to the homemade chili pepper dataset, the AP value of chili pepper reaches 93.11%; the accuracy rate is 93.51% and the recall rate is 92.55%.The experimental results show that yolo-chili is able to achieve accurate and real-time pepper detection under complex orchards.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

The aim of this retrospective study was to compare the clinical outcomes of treating isolated surgical neck fractures of the humerus using either the intramedullary nail or the MIROS (Minimally Invasive Reduction and Osteosynthesis System®) system. The study included 42 patients who underwent surgical treatment at the Polyclinic from January 2014 to June 2020. The results indicated that both treatments were effective; however, the MIROS system exhibited a higher complication rate. Intramedullary nailing was more reliable, thus recommended as the primary treatment method. This study underscores the importance of selecting the appropriate fixation technique to minimize complications and enhance patient outcomes.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

Excess nitrogen in agricultural drainage poses a serious threat to the water quality safety of the Yellow River basin. Utilizing aquatic plants to modify the rhizosphere microbial community structure and facilitate nitrogen transformation is a crucial strategy for mitigating regional water eutrophication. Our results revealed that the denitrification rate (DR), dissimilatory nitrate reduction to ammonium rate (DNRAR) and nitrogen fixation rate (NFR) of rhizosphere sediments exhibited a significant increase in artificially cultivated ditch. Compared with those in natural ditches, the richness of the bacterial community and the relative abundances of Bacteroidota, Verrucomicrobiota, Firmicutes, Anaeromyxobacter and Geobacter, which are involved mainly in the nitrogen cycle, in the rhizosphere sediments of artificially cultivated ditch were significantly greater due to improvements in environmental conditions. In artificially cultivated ditch, the dominant functional genes affecting DRNARs in the rhizosphere sediments of P. australis were nrfC and nrfA, while DRs were driven mainly by norB and napA, which were influenced by the nitrogen and carbon levels; and the dominant functional genes affecting NFRs in the rhizosphere sediments of T. orientalis were nifD, nifK and nifH. Our results provide a scientific basis for the use of aquatic plants for mitigating excess nitrogen levels in agricultural drainage.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.