During the pandemic, assisted reproductive treatments suffered from major disruptions in their terms due to the restrictions imposed. The objective of this study is to evaluate the level of anxiety of women whose treatments were either suspended or delayed. Methods: Descriptive cross-sectional study conducted between April and May 2020. The State-Trait Anxiety Inventory was applied in a Spanish adapted version. The research also included social, personal, and work aspects which may be involved in the challenging situation. Results: A total of 115 patients participated in the study (73.7%). Women showed a mean in trait anxiety of 17.79 (SD = 8.80) and a mean in state anxiety of 19.95 (SD = 9.08). Neither the type of treatment nor the time of infertility are predictors of trait anxiety or state anxiety. More age pressure and more worry were associated with more trait and state anxiety (p<0.001). The most common emotional reactions to discontinuation of fertility treatments were sadness and anxiety. Conclusions: Discontinuation of fertility treatments due to confinement restrictions had a negative impact on the mental health of women who were following a process of assisted reproduction treatment, increasing their levels of emotional distress and anxiety.

children is challenging. An important advance is the 15-questions Pictorial Personality Traits Questionnaire for Children. A study on students from 10 to 13 years old in Poland validated the questionnaire but with some observations. Thus, there is a need for replication and stronger evi-dence in this age group. In Chile, we replicated the study with 3,423 4th-graders (9 to 12 years old). Teachers, in regular sessions, applied the questionnaire to their entire classes. We found similar results, including that asexual pictograms worked well in both genders. We also found positive relationships between conscientiousness, openness, and extraversion with mathematical performance. Furthermore, a combination of these three traits has a relationship with math performance twice as big as each trait alone. Moreover, students with the lowest scores in this combination of personality traits (6.6% of students) have 0.27 standard deviations less in mathematical performance than those with the highest score, which is 74.3% of students. To the best of our knowledge, this is the first time that a study finds a strong relationship between a combination of personality traits gathered with a 15-question questionnaire and fourth-graders´ math perfor-mances.

In these times, consumers mistakenly believe that the terms “expiration date” and “best before” found on packages only convey information about food safety. Consequently, a misunderstanding of these terms contributes to food waste. In this sense, the understanding and behavior of the con-sumer with respect to the two terms were evaluated; in addition, the consumer's perception of the health risks of consuming expired food was analyzed. The research was carried out with the population of the sector of Lurigancho-Chosica, Lima – Peru; sample size was 555 participants. An online survey was sent to consumers over 18 years of age, from different sociodemographic and socioeconomic conditions. In general terms, it was found that 45% (p <0.01) consider that both terms mean the same thing, this result is a problem for food safety. The 67% (p <0.05) and 45% (p <0.05) correctly defined the first and second terms, respectively; however, the behavior is not coherent with the understanding of the terms. In addition, irrational and dangerous behavior toward expired food was evidenced, i.e., they consume expired food - "expiration date", and discard expired food - "best before". Finally, the health risks they perceived from consuming expired foods of both terms were: upset stomach, vomiting, gas, intoxi-cation, and malnutrition; these perceptions are erroneous and unfounded. Sociodemographic and socioeconomic conditions influence the under-standing, behavior, and perception of health risks. Therefore, in general lines, the level of understanding of the terms was low (p<0.01), the be-havior was inappropriate toward expired food (p<0.01), and the percep-tion of the health risk of consuming expired food was incorrect (p<0.01).

Fertility preservation technologies have existed for decades, and the field is rapidly advancing; limited data exist regarding the use of these technologies by transgender patients. Many options are available for transgender patients who wish to preserve fertility before transitioning. These options include the cryopreservation of gametes, ovarian tissue, or embryos. Currently, ejaculated, or testicular sperm, immature oocytes, and ovarian tissue can be preserved for later use, but no such use option exists for immature testicular tissue. Many financial, sociological, and legal barriers and a lack of awareness among physicians and patients also hindered the utilization of these fertility preservation services. While options are abundant, usage rates are relatively low. The initial data regarding the successful use of preserved tissues appears promising, with birth rates not dissimilar to non-transgender patients. Further investigations into this area are needed. In addition, counseling regarding fertility preservation options should become a significant part of the provider-patient conversation before transitioning therapies.; fertility; transgender; reproductive technology.

. Identifying students who might have difficulty in their course of studies ahead of time is crucial. There can be many reasons for performance issues, such as personality, family, social, and/or economic. We advocate that educational systems should use machine learning to predict students’ performance based on performance factors. This would allow educational professionals and institutions to put in place a preventive plan to help students towards achievements of their educational goals and success. In this chapter, we propose a student performance prediction method and evaluate its performance. We provide a taxonomy of performance factors that help to gauge students performance from different perspectives and give insights on the categories and features that have more significant impact on students’ performance. The results of this work can be used by education institutions to put in place a student-centric approach to tackle performance issues before they create long-term effects on student’s life. In addition, it will help education policymakers to introduce a tailored approach for the population in specific areas.

In autonomous driving systems, high-speed and real-time image processing, along with object recognition, are crucial technologies. This paper builds upon the research achievements in in-dustrial item sorting systems and proposes an object recognition and sorting system for auton-omous driving. In industrial sorting lines, goods sorting robots often need to work at high speeds to efficiently sort large volumes of items. This poses a challenge to the robot's real-time vision and sorting capabilities, making it both practical and economically viable to implement a real-time and low-cost sorting system in a real-world industrial sorting line. Existing sorting systems have limitations such as high cost, high computing resource consumption, and high power consump-tion. These issues lead to the fact that existing sorting systems are typically used only in large industrial plants. In this paper, we design a high-speed, low-cost, low-resource-consumption FPGA (Field-Programmable Gate Array) based item sorting system that achieves similar perfor-mance to current mainstream sorting systems at a lower cost and consumption than existing sorting systems. The recognition part employs a morphological recognition method, which segments the image using a frame difference algorithm and then extracts the color and shape features of the items. To handle sorting, a six-degree-of-freedom robotic arm is introduced in the sorting segment. The improved cubic B-spline interpolation algorithm is employed to plan the motion trajectory and consequently control the robotic arm to execute the corresponding actions. Through a series of experiments, this system achieves an average recognition delay of 25.26ms, ensures smooth operation of the gripping motion trajectory, minimizes resource consumption, and reduces implementation costs.

Determining accurate PM2.5 pollution concentrations and understanding their dynamic patterns is crucial for scientifically informed air pollution control strategies. Traditional reliance on linear correlation coefficients for ascertaining PM2.5 related factors only uncovers superficial relationships. Moreover, the invariance of conventional prediction models restricts their accuracy. To enhance the precision of PM2.5 concentration prediction, this study introduces a novel integrated model that leverages feature selection and a clustering algorithm. Comprising three components - feature selection, clustering, and integrated prediction, the model first employs the non-dominated sorting Genetic Algorithm (NSGA-III) to identify the most impactful features affecting PM2.5 concentration within air pollutants and meteorological factors. This step offers more valuable feature data for subsequent modules. The model then adopts a two-layer clustering method (SOM+K-means) to analyze the multifaceted irregularity within the dataset. Finally, the model establishes the Extreme Learning Machine (ELM) weak learner for each classification, integrating multiple weak learners using the Adaboost algorithm to obtain a comprehensive prediction model. Through feature correlation enhancement, data irregularity exploration, and model adaptability improvement, the proposed model significantly enhances the overall prediction performance. Data sourced from 12 Beijing-based monitoring sites in 2016 were utilized for an empirical study, and the model's results compared with five other predictive models. The outcomes demonstrate that the proposed model significantly heightens prediction accuracy, offering useful insights and potential for broadened application to multifactor correlation concentration prediction methodologies for other pollutants.

The famous Wigner’s friend experiment considers an observer – the friend– and a superobserver – Wigner– who treats the friend as a quantum system and her interaction with other quantum systems as unitary dynamics. This is at odds with the friend describing this interaction via collapse dynamics, if she interacts with the quantum system in a way that she would consider a measurement. These different descriptions constitute the Wigner’s friend paradox. Extended Wigner’s friend experiments combine the original thought experiment with non-locality setups. This allows for deriving local friendliness inequalities, similar to Bell’s theorem, which can be violated for certain extended Wigner’s friend scenarios. A Wigner’s friend paradox and the violation of local friendliness inequalities require that no classical record exists, which reveals the result the friend observed during her measurement. Otherwise Wigner agrees with his friend’s description and no local friendliness inequality can be violated. In this article, I introduce classical communication between Wigner and his friend and discuss its effects on the simple as well as extended Wigner’s friend experiments. By controlling the properties of a (quasi) classical communication channel between Wigner and the friend one can regulate how much outcome information about the friend’s measurement is revealed. This gives a smooth transition between the paradoxical description and the possibility of violating local friendliness inequalities, on the one hand, and the effectively collapsed case, on the other hand.

The rapid ageing of populations around the World is creating complex challenges for national governments. The establishment of sustainable and equitable long-term care systems for old and dependent people is one of the main issues of social policy in developed countries. The aim of this work is to define a cost model for residential and day care centres for dependent persons in Cantabria (Spain). The cost model will make it possible to establish the theoretical cost of attending to the needs of the different types of dependent persons in the different types of care centres, and the methodology used could be extrapolated to other regions. The daily cost per user for elderly residential care is €53.72. The cost per user in elderly day centres (5 days) is 32.56 euros. In residential centres for people with disabilities, the values range between €47.41 and €75.25 depending on the category of the centre. In three categories of centres the public price is not enough to cover the cost (physical disability, intellectual disability, mental illness – low care), and therefore the administration should reconsider their public prices for these kind of centres if they want to really contribute to the sustainability of these residential care centres. This research will have important implications for policy-makers in a context of fulfilment of SDGs and where better support for old and disabled people and their carers, as well as fair and efficient financing of social care services, are essential to address the current and future challenges of dependency.

Introduction: Mucopolysaccharidosis type I (MPSI) is an autosomal recessive lysosomal storage disorder characterized by deficient or absent α-L-iduronidase (IDUA) enzyme activity due to pathogenic variants in IDUA gene. Early treatment with hematopoietic stem cell transplantation and/or enzyme replacement therapy is associated with improved outcomes in this progressive multisystem disease. The diagnosis is usually delayed due to late presentation and nonspecific symptoms resulting in high morbidity and mortality. The incidence of MPSI in US is estimated to be 0.26:100,000, however, it is unknown in Kuwait. This pilot study was undertaken to screen MPSI in all Kuwaiti neonates born at Farwaniya Hospital over a period of 12-months. This study examined the incidence of MPSI in a major center in Kuwait for inclusion in the national newborn screening program to enable its early detection and adequate treatment. Methods: All Kuwaiti neonates born at Farwaniya Hospital, Kuwait from December 2021 to December 2022, were screened for MPSI. The screening consisted of determining IDUA enzyme activity in dried blood spots (DBS)-derived samples by Tandem Mass Spectrometry. A follow-up genetic analysis of IDUA gene is planned to screen the cases with diminished IDUA enzyme activity as second-tier testing. Results: A total of 618 newborns, including 331 (54%) males and 287 (46%) females, were screened. Twenty of them had deficient IDUA enzyme activity but showed negative genetic testing for IDUA. However, we have diagnosed one additional female baby with MPSI, who belonged to Farwaniya Hospital, but the parents chose to deliver in a private hospital. She presented at age three months with recurrent upper airway infections, snoring and extensive Mongolian spots. The molecular study revealed previously reported pathogenic nonsense variant in IDUA c.1882C>T; p.(Arg628Ter), associated with severe phenotype. That being included, MPSI is estimated to be about 0.3% among tested females and 0.2% of all screened cases in Kuwait. Conclusion: Our study is the first to evaluate the incidence of MPSI in Kuwait. Given the single center, small number of screened babies and the short study duration thus far, it is premature to calculate the incidence of MPSI. It is anticipated that as the study continues and more infants are examined, we would be able to estimate the incidence of this disease in our population correctly. Further studies including screening newborns in all maternity hospitals in Kuwait are needed to calculate the actual incidence of MPSI. Our data supports including MPSI in national newborn screening program to allow early initiation of treatment and thus improve disease outcome.

Consumer preference for products made from transgenic technology has been widely studied, yet few studies exist exploring the factors influencing producers’ adoption of transgenic technology. Based on field surveys in Chinese provinces of Shanxi, Henan and Shandong, we employed a gambling experiment to capture producers’ risk preferences by estimating their risk aversion coefficients. We further estimated producers’ risk amplification and risk perception of GM technology. Using ordered logit model and Poisson model we identified the major factors influencing producers’ adoption of transgenic technology. We found the factors impacted the decision of producers from different regions in different ways. The results showed that over 60% of participants amplified the risk of transgenic crops. When there was potential risk, producers might not be rational even if they had high level of knowledge and cognition about the technology. Our results shed light on government policies aiming to increase the adoption of new technologies by producers.

The human T-cell leukemia virus type 1 (HTLV-1) is the only known human oncogenic retrovirus. HTLV-1 can cause a cancer called adult T-cell leukemia/lymphoma (ATL). The virus is transmitted through body fluids of infected individuals, primarily breast milk, blood, and semen. At least 5–10 million people in the world are infected with HTLV-1. In addition to ATL, HTLV-1 infection can also cause HTLV-I-associated myelopathy (HAM /TSP). ATL is characterized by low viral ex-pression and poor prognosis. The oncogenesis triggered by HTLV-1 is extremely complex and the molecular mechanisms are not fully understood. However, viral regulatory proteins Tax and HTLV-1 bZIP factor (HBZ) have been shown to play key roles in the transformation of HTLV-1-infected T cells. Moreover, several studies have shown that the final fate of HTLV-1-infected transformed T cell clones is the result of a complex interplay of HTLV-1 oncogenic protein expression with cellular transcription factors that subvert the cell cycle and disrupt reg-ulated cell death, thereby exerting their transforming effects. This review provides updated in-formation on the mechanisms underlying the transforming action of HTLV-1 and the potential therapeutic targets to combat ATL.

Cabbage (Brassica oleracea L. var. capitata) plays a very important role in the annual national vegetable supply and export trade. In recent years, the cadmium content of agricultural soils has increased. As a result, cabbage yields and quality have declined significantly. Studies have shown that selenium can counteract the harmful effects of cadmium on plants and can alleviate the stress caused by cadmium during the growth of plants. However, the mechanism of exogenous selenium application in the alleviation of cadmium stress in cabbage seedlings has not been thoroughly investigated. In this study, exogenous selenium (10μMol/L) was applied under cadmium (25μMol/L) stress and the physiological mechanisms such as biomass, photosynthetic pigment, leaf stomata parameters, selenium and cadmium content, chloroplast ultrastructure, active oxygen accumulation, leaf membrane esterification and antioxidant enzyme activity were determined. The protective mechanism of exogenous selenium on cabbage seedlings under cadmium stress was investigated. The re-sults showed that exogenous application of selenium could effectively alleviate the decrease in growth, photosynthetic pigment and gas exchange characteristics of cabbage seedlings under cadmium stress, im-prove cabbage root vitality, reduce root leaf cadmium content and alleviate cadmium stress-induced damage. Ultrastructural observation showed that cadmium stress caused the disruption of the internal structure of chloroplasts of cabbage leaves, while exogenous selenium treatment alleviated the chloroplast damage to some extent, improved the stability of the inner capsule membrane and alleviated the cadmium stress-induced damage to photosynthetic organs. Cadmium stress also caused oxidative damage and ex-cessive accumulation of ROS in the leaves of cabbage seedlings as evidenced by significant accumulation of O2-, H2O2, MDA and electrolyte leakage. On the other hand, after exogenous selenium treatment, cadmium stress- induced oxidative damage could be reduced by up-regulating the activities of antioxidant enzymes SOD, POD and APX. At the same time, cadmium stress significantly increased GSH levels, and exogenous selenium treatment further increased GSH levels, thereby increasing the tolerance of cabbage to cadmium stress. In conclusion, by protecting the photosynthetic system, eliminating excessive accumulation of reactive oxygen species in cadmium-stressed cabbage seedlings, alleviating oxidative stress and reducing cadmium levels in the plant, exogenous selenium can further improve cadmium tolerance in cabbage seedlings.

Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) have been utilised to forecast the foreign exchange market (Forex). However, such models usually exhibit unstable behaviour, as data perturbations often downgrade the functionality of the entire network due to their monolithic architecture. Hence, this study proposes a novel neuroscience-informed modular network applied to the closing prices and the sentiments retrieved from Yahoo Finance and Twitter APIs, aiming to anticipate better price fluctuations in Euro to British Pound Sterling (EUR/GBP) rather than monolithic methods. The proposed model is based on a new modular CNN, replacing pooling layers with orthogonal kernel initialisation RNNs coupled with Monte Carlo Dropout (MCD), namely MCoRNNMCD. It combines two modules: i) a convolutional simple RNN and ii) a convolutional Gated Recurrent Unit (GRU), where orthogonality and MCD are added to reduce the overfitting, assessing each module's uncertainty. These parallel feature extraction modules concatenate their outputs to a final three-layer Artificial Neural Network (ANN) decision-making module. A comprehensive comparison viewing objective evaluation metrics such as the Mean Square Error (MSE) proved that the proposed MCoRNNMCD-ANN outperformed single CNN, LSTM, GRU, and the state-of-the-art hybrid BiCuDNNLSTM, CLSTM, CNN-LSTM, and LSTM-GRU in forecasting hourly EUR/GBP closing price fluctuations.

This study focused on the predictive models incorporating machine learning techniques that induce new dynamics for forecasting energy generation, enabling effective planning, financing, and system monitoring. The research developed a machine learning-based power generation prediction model tailored explicitly for Kenya's Garissa solar power plant. The selected model demonstrated a root mean squared error of 5.23 during evaluation, resulting in a prediction accuracy of 90.42%. This high accuracy indicates that the model can be relied upon for precise generation prediction, facilitating effective planning, and system performance monitoring

Recently, NOAA has included GNSS (Global Navigation Satellite System) Radio Occultation (RO) data as one of the crucial long-term observables for weather and climate applications. To include more GNSS RO data in the numerical weather prediction system, the NOAA Commercial Weather Data Pilot program (CWDP) started to explore the commercial RO data available on the market. After two rounds of pilot studies, the CDWP decided to award the first Indefinite Delivery Indefinite Quantity (IDIQ) contract to GeoOptics and Spire Incs. in 2020. This study examines the quality of Spire data products for weather and climate applications. Spire RO data are collected from commercial CubeSats through careful comparison with the data from Formosa Satellite Mission 7–Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), ERA-5, and high-quality radiosonde data. The results demonstrated that although with lower Signal-Noise-Ratio (SNR) in general, the pattern of the lowest penetration height for Spire is similar to those for COSMIC-2. The Spire and COSMIC-2 penetrate heights are between 0.6 and 0.8 km altitude at the tropical oceans. Although using different GNSS RO receivers, the precision of Spire STRASP receivers is of the same quality as those of COSMIC-2 Global Positioning System - GPS, GALILEO, and GLObal NAvigation Satellite System – GLONASS (TGRS) receivers. The retrieval accuracy from Spire is very compatible with those from COSMIC-2. We validated Spire temperature and water vapor profiles by comparing them with collocated radiosonde data. Generally, over the height region between 8 km and 16.5 km, the Spire temperature profiles match those from RS41 RAOB very well with temperature biases &lt; 0.02 K. Over the height range from 17.8 to 26.4 km, the temperature differences are ~-0.034 K with RS41 RAOB being warmer. We also estimated the error covariance matrix for Spire, COSMIC-2, and KOMPSAT-5. Results showed that the COSMIC-2 estimated error covariance values are slightly more significant over the oceans at the mid-latitudes (45oN-30oN and 30oS-45oS), which may also be owing to COSMIC-2 SNR being lower at those latitudinal zones.

Diffuse cavernous hemangioma of the rectum (DCHR) is a rare benign lesion of vascular malformation. According to previous studies, the most reported major symptoms of DCHR are recurrent painless rectal bleeding or iron deficiency anemia[1][2][3][4][5][6]. We present a case of an 8Y11M boy who was diagnosed with DCHR by MRI. The patient underwent Laparoscopic-assisted transanal distal sigmoidectomy and sigmoido-anal anastomosis（Laparoscopic Swenson Procedure）, and recovered well. After the operation, the child had short-term fecal incontinence and loose stools, which returned to normal after half a year. Regardless of age and symptoms, early and correct diagnosis and treatment of DCHR and postoperative restoration of normal anal function are necessary. Laparoscopic Swenson procedure may be a good option for the treatment of DCHR.

Cadmium (Cd) is a major heavy metal pollutant and a significant cause of abiotic stress in the environment. Organisms have developed various pathways to protect themselves against Cd stress. MYB protein is a large transcription factor family in plants. Many members of the family have been found to regulate developmental processes and stress responses. However, the function and mechanism of MYB116 are far from clear. In a recent study, we found that MYB116 of Chinese cabbage enhances Cd tolerance in yeast. BrMYB116 is transiently inducible by Cd treatment in Chinese cabbage. When expressed in yeast cells, it enhances tolerance against Cd stress and reduces Cd accumulation in the cells. Further analysis shows that BrMYB116 protein enhances Cd tolerance in yeast cells by activating one target gene that encodes the facilitator of iron transport 3 (FIT3). ScFIT3 is activated through specific binding with its promoter. More importantly, the expression of ScFIT3, leads to a substantial reduction of Cd accumulation in both yeast and Chinese cabbage. This finding implies that a similar network may exist in other biological systems, which presents a promising avenue for enhancing Cd tolerance in plants and developing Cd-resistant crops.

Immune-mediated bowel diseases (IMBD), including Ulcerative colitis and Crohn's disease, represent a significant global health burden with their complex etiology and increasing prevalence. The connection between intestinal parasites and the gut microbiome in immune-mediated bowel disease is a complex and evolving field of research. Several studies have demonstrated that intestinal parasites can modulate the composition and function of the gut microbiome. Parasitic infections can result in alterations in the gut microbial community, including changes in microbial diversity, abundance, and metabolic activity. These changes can influence the immune response and contribute to the development of IMBDs. In contrast, the gut microbiome serves a pivotal function in maintaining intestinal homeostasis and immune regulation. Dysbiosis, characterized by changes in the gut microbial composition, has been associated with the pathogenesis of IMBDs. Imbalances in the gut microbiota can result in increased gut permeability, chronic inflammation, and aberrant immune responses, all of which are hallmarks of IMBDs. The bidirectional interaction between intestinal parasites and the gut microbiome further complicates the understanding of immune-mediated bowel diseases. Certain parasites, such as hookworms and Necator americanus, have been found to downregulate immune responses and may have therapeutic potential in treating celiac disease. On the other hand, infections with parasites like Strongyloides stercoralis and Blastocystis have been shown to mimic the symptoms of IBD, highlighting the intricate relationship between parasites and the pathogenesis of these diseases. Additional investigation is required to comprehensively elucidate the mechanisms that underlie the association between intestinal parasites and the gut microbiome in immune-mediated bowel disease. This knowledge could potentially lead to the development of targeted therapeutic strategies that aim to restore gut microbiota homeostasis and alleviate the symptoms of these debilitating conditions. By understanding and harnessing the complex interplay between parasites, the gut microbiome, and the host immune system, researchers may uncover novel approaches for the management and treatment of immune-mediated bowel diseases.

Antibiotics were once called miracle drugs which hit the market with astounding impact as it was considered the ultimate cure for infectious diseases in the mid-20th century. However, today nearly all bacteria that afflict humankind have become resistant to these wonder drugs once developed to stop them, imperilling the foundation of modern medicine. During the COVID pandemic, there was a surge in macrolide use to treat secondary infections and this persistent use of macrolide antibiotics has provoked the emergence of macrolide resistance. In view of the current dearth of new antibiotics in the pipeline, it is essential to find an alternative way to combat drug resistance. Antibiotic potentiators or adjuvants are non-antibacterial active molecules that, when combined with antibiotics, increase their activity. Thus, potentiating the existing antibiotics is one of the promising approaches to tackle and minimize the impact of antimicrobial resistance. Several natural and synthetic compounds have demonstrated effectiveness in potentiating macrolide antibiotics against MDR pathogens. The present review summarizes the different resistance mechanisms adapted by bacteria to resist macrolides and further emphasizes the major macrolide potentiators identified which could serve to revive the antibiotic and can be used for the reversal of macrolide resistance.

: There remains no acquiescence that confirms the extent to which unemployment and entrepreneurship influence each other in developing countries. Thus, an incessant invite for further debate attracted the need to assess the relationship between unemployment and entrepreneurship in terms of business formation in Namibia Given that, this study examines the relationship between unemployment and entrepreneurial activities in Namibia. Time series data were collected from the World Bank database to investigate the relationship between unemployment and entrepreneurship in Namibia. Unit root test was conducted using both the Augmented Dickey-Fuller test and the Phillips-Perron test to measure stationarity of the data and found all the variables to have no unit root after the first difference. Thus, we employed the Johansen-Juselius test of cointegration, and the results revealed the absence of a long-run relationship between the variables. Hence, we performed a vector autoregressive (VAR) model to estimate the short-run relationships and found that Namibia exhibit both the refugee and Schumpeter effects. Finally, the direction of causality between the variables was measured using the Pairwise Granger causality test and the results revealed that none of the variables was proven to granger cause the other, concluding that they are all independent of each other. Therefore, in pursuit of unemployment mitigation, we recommend policymakers to focus on other aspects beyond entrepreneurship when devising policies without jeopardizing the ease of business start-up procedures. This will incentivize entrepreneurial activities, which can eventually address other macroeconomic issues beyond unemployment.

The United Nations Organization in its agenda for 2023 approved Health and Well-being as one of the objectives of sustainable development, in this sense, Higher Education Insti-tutions contribute with interventions to improve each human process that generates a healthy life. In Latin America as well as in European countries, studies have been con-ducted to observe psychological well-being at this stage of life. The present study analyzes in a longitudinal way the psychological well-being in three times in people who attend group dynamics programs. The sample is 668 participants, with an age range between 65 and 80 years. The sample has been distributed in two analysis groups controlling for gender and age: group 1 (with group dynamics) and group 2 (without group dynamics). The Spanish adaptation of Ryff's (2006) Psychological Well-being scale α= 0.87 was ap-plied to both groups. The scale is composed of six dimensions of psychological well-being (self-acceptance, positive relationships, autonomy, mastery of the environment, purpose in life and personal growth). Statistical analyses showed significant differences between the two groups: greater psychological well-being and differences in the dimensions of positive relationships and personal growth in group 1. In addition, logistic regression analysis was carried out to test the predictive capacity of psychological well-being by the existence or not of group dynamics, with significant results in several dimensions. With the results obtained, we can conclude that group dynamics have a relevant role in con-tributing to the development of better levels of psychological well-being of the elderly with longitudinal increase in time. Future studies should be aimed at evaluating the value of group dynamics in the way of successful aging.

Machinery parts gradually wear out over time due to regular usage. To improve machinery health and prevent critical issues, a reliable prognosis framework can be implemented by monitoring the behaviour of machinery parts and issuing warnings before they reach a critical state. To achieve this, vibration data from roller bearings experiencing various fault conditions have been collected. Different techniques from the literature were combined to analyze the distinct configurations in the vibration data sets and identify the main defects in roller bearings. The significant features extracted from this analysis were then used to create optimized stochastic model equations, separately regressing inner and outer race fault features to healthy bearing features under random conditions. These models can help engineers design more dependable systems, optimize their performance, and minimize the risk of failures and downtime.

Sirtuins are a family of Class III epigenetic modifying enzymes involved in regulating cellular processes through the removal of acetyl groups from proteins. They rely on NAD+ as a coenzyme in contrast with classical HDACs (Class I, II, and IV) that depends on Zn+ for their activation, linking their function to cellular energy levels. There are seven mammalian sirtuin isoforms (SIRT1-7), each located in different subcellular compartments. Sirtuins act as master regulators of cellular homeostasis, responding to changes in nutrient availability and energy status. They play vital roles in diverse physiological and pathological conditions, making them promising therapeutic targets for various diseases, including cancer, neurodegenerative disorders, and metabolic diseases. High levels of SIRT6 are involved in the cancer progression of many tumor types and our previous studies revealed that sirtuin 6 was highly expressed in NSCLC cells and its inhibition potentially favored apoptosis and cell cycle arrest. Sirt6 emerged as a promising target and inhibitors of natural and synthetic sources are highly warranted. Imidazole derivatives are often investigated as sirtuin regulators due to their ability to interact with the binding site and modulate their activity. Imidazole bestows many possible substitutions on its ring and neighboring atoms, to design and synthesize derivatives with specific target selectivity and improved pharmacokinetic properties, optimizing drug development. We recently developed imidazole-based derivatives that potentially inhibited classical HDAC enzymes. Therefore, we evaluated the Sirtuin inhibition activity of our in-house compound comprised of imidazole derivatives and the strongest inhibition was observed with Ethyl 2-[5-(4-chlorophenyl)-2-methyl-1-H-Imidazole-4-yl) acetate against Sirt6 by in-silico and protein expression studies. Our results suggested that Ethyl 2-[5-(4-chlorophenyl)-2-methyl-1-H-Imidazole-4-yl) acetate could be a potential novel sirt6 inhibitor.

CBCT significantly impacts dental procedures and has brought significant reforms in our approach to diagnosis & treatment planning despite its limitations in differentiating soft tissues. It is an excellent imaging modality and quickly identifies sinus opacification and provides valuable in-sight into paranasal sinus pathologies with considerably lower radiation exposure. The present study aimed to investigate the occurrence of maxillary sinus abnormalities in CBCT scans, identify the frequency, type, and location of these findings, and find the correlation between the distance of periapical lesions and radiographic changes in the maxillary sinus. Two examiners independently evaluated 117 patients to diagnose and classify the cases into different abnormality subtypes. The periapical lesions most closely related to the sinus were recorded. The diameters of the left and right maxillary sinus ostium and the distance of the ostium's lower border to the sinus's osseous floor were recorded. The findings were correlated with the age and gender of these patients. The present study revealed that sixty-one patients were diagnosed with mucosal thickening (52.1%). The sinus wall most affected by mucosal thickening was the maxillary sinus floor, followed by the medial and lateral walls. Of 19 patients with periapical lesions, 15 had maxillary sinus mucosal thickening and was statistically significant (p=0.004). The high occurrence of abnormalities in the maxillary sinus emphasizes the importance for the radiologist to comprehensively interpret the whole volume acquired in CBCT images, including the entire sinus. Incidental findings may be considered in the individual clinical context of signs and symptoms, reducing the risk of overes-timating the real impact of radiographic findings.

Solid particle cationic polyacrylamide (CPAM) is one of the most commonly used organic polymer flocculants in oilfield wastewater treatment, but there are some problems, such as slow dissolution rate, and easy to form a "fish-eye" in the process of diluting into aqueous solution. However, the current liquid CPAM products also have some problems, such as low effective content, poor storage stability, degradation in a short time and high preparation cost. In this paper, a secondary processing technology of solid particle CPAM was studied, and a CPAM suspension was successfully prepared. This suspension has an effective content of 50.00%, No separation in 7 days of storage at room temperature, no separation in 30 min of centrifugation at a speed of 2000 r/min, and diluted to a 0.40 % weak gel solution in just 16.00 min. For 1000 NTU of diatomite simulated wastewater, the optimal turbidity removal rate of the suspension was 99.50%, which was higher than the optimal turbidity removal rate of 98.40% for the inorganic flocculant polymeric aluminum chloride (PAC). For oil and gas field oily wastewater, the optimal turbidity removal rate of CPAM suspension was 35.60%, which was higher than the optimal turbidity removal rate of 28.40% for solid particle CPAM.

Food and drinks can be contaminated with pollutants such as lead and strontium and this poses a serious danger to human health. For this reason, a number of effective sensors have been developed for the rapid and highly selective detection of such contaminants. TBA, a well-known aptamer developed to selectively target and thereby inhibit the protein of clinical interest -thrombin, is receiving increasing attention for sensing applications, particularly for the sensing of different cations. Indeed, TBA, in the presence of these cations, folds into the stable G-quadruplex structure. Furthermore, different cations produce small but significant changes in this structure that result in changes in the electrical responses that TBA can produce. In this article we produce an overview of the expected data regarding the use of TBA in the detection of lead and strontium, calculating the expected electrical response using different measurement techniques. Finally, we conclude that the TBA should perform better as a detector of strontium rather than lead.

Identification of plants is a challenging task which aims to identify the family, genus, and species level according to morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users to narrow down the possibilities. However, numerous morphological similarities between and within species make the classification difficult. In this paper, we tested a custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88K and 16K images for classifying plants at genus and species levels respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. The ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. ViT models also perform better for classifying plants at the species level compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success.

Methodologies for the synthesis and purification of metabolites, which have been developed following their discovery, analysis and structural identification, have been involved in numerous life science milestones. The renewed focus on the small molecule domain of biological cells has also created an increasing awareness of the rising gap between the metabolites identified and the metabolites which have been prepared as pure compounds. Due to the large number and molecular diversity of metabolites the design and engineering of resource-efficient and straightforward synthetic methodologies for their production have attracted much interest. The variety of metabolic pathways in biological cells provide a wonderful blueprint for designing simplified and resource-efficient synthetic routes to desired metabolites. Therefore, biocatalytic systems have become key enabling tools for the synthesis of an increasing number of metabolites, which can then be utilized as standards, enzyme substrates, inhibitors or products, or for the discovery of novel biological functions.

Over the past several decades, the extensive use of pyrethroids has led to the development of resistance in many insect populations, including the economically damaging pest tarnished plant bug (TPB), Lygus lineolaris on cotton. To manage TPB resistance, several commercially formulated pyrethroid-containing binary mixtures, in combination with neonicotinoids or avermectin are recommended for TPB control and resistance management in the Mid-south USA. This study aimed to evaluate the toxicity and resistance risks of four formulated pyrethroid-containing binary mixtures (Endigo, Leverage, Athena, and Hero) on one susceptible and two resistant TPB populations which were field-collected in July (Field-R1) and October (Field-R2), respectively. Based on LC50 values, both resistant TPB populations displayed variable tolerance to the four binary mixtures, with Hero showing the highest resistance and Athena the lowest. Notably, the Field-R2 exhibited 1.5-3-fold higher resistance compared to the Field-R1 for all four binary insecticides. Moreover, both resistant TPB populations demonstrated significantly higher resistance ratios toward Hero and Leverage compared to their corresponding individual pyrethroid, while Endigo and Athena showed similar or lower resistance. This study also utilized the calculated additive index (AI) and co-toxicity coefficient (CTC) analysis, which revealed that the two individual components in Leverage exhibited antagonist effects against the two resistant TPB populations. In contrast, the two individual components in Endigo, Hero and Athena displayed synergistic interactions. Considering that Hero is a mixture of two pyrethroids which can enhance the development of TPB resistance, our findings suggest that Endigo and Athena are likely superior products for slowing down resistance development in TPB populations. This study provides valuable insight for selecting the most effective mixtures to achieve better TPB control through synergistic toxicity analysis, while simultaneously reducing economic and environmental risks associated with resistance development in the insect pest.

Fertility preservation technologies have existed for decades, and the field is rapidly advancing; limited data exist regarding the use of these technologies by transgender patients. Many options are available for transgender patients who wish to preserve fertility before transitioning. These options include the cryopreservation of gametes, ovarian tissue, or embryos. Currently, ejaculated, or testicular sperm, immature oocytes, and ovarian tissue can be preserved for later use, but no such use option exists for immature testicular tissue. Many financial, sociological, and legal barriers and a lack of awareness among physicians and patients also hindered the utilization of these fertility preservation services. While options are abundant, usage rates are relatively low. The initial data regarding the successful use of preserved tissues appears promising, with birth rates not dissimilar to non-transgender patients. Further investigations into this area are needed. In addition, counseling regarding fertility preservation options should become a significant part of the provider-patient conversation before transitioning therapies.; fertility; transgender; reproductive technology.

Extracellular vesicles (EVs) are enclosed by a lipid-bilayer membrane and secreted by all types of the cells under various physiological conditions. EVs play important roles in intercellular communication and crosstalk between tissues in the body. They are classified into three groups, such as apoptotic bodies, microvesicles, and exosomes. Exosomes were isolated from biofluids including blood, urine, milk, and cell culture media. Exosomes have significant potential for drug delivery and diagnosis. However, the method of isolation affects the physical and biological properties of exosomes. Several methods based on different principles have been developed for exosome isolation. These include ultrafiltration, precipitation, ultracentrifugation, size-exclusion chromatography, and microfluidics. In this study, we applied three common methods, such as ultrafiltration, precipitation, and ultracentrifugation, to isolate exosomes from the cell culture medium and investigated the effects of these different isolation methods on the size distribution and quality of the isolated exosomes. Field emission scanning electron microscopy (FESEM) images, size distribution, total protein content, and the effect of exosomes on the viability of hypoxic cells were analyzed in this study. The analysis revealed that compared to other methods, the ultracentrifugation method can isolate exosomes with smaller diameter (ranging from 20 to 80 nm), lower total protein content (50 µg/ml), and causing the increased viability of the hypoxic cells. The precipitation method does not require special equipment and is inexpensive, if the quality and purity of this method are solved, and it can be used as the best method for exosome isolation. This study can serve as a guide for choosing the best exosome isolation method for applications in medicine according to the needs, time, cost, and equipment.

In this paper we report the results obtained in experiment PHELEX during 208 days of measurements on the search for dark photons with a multi-cathode counter with an iron cathode that revealed in 4 runs with a confidence level better than 5 σ a systematic excess of single electron events in the time interval from 8-00 till 12-00 sidereal time. The fact that we see this effect in stellar frame and do not in solar frame can be considered as evidence that the observed effect is due to dark photons.

In this paper we study a special kind of finite mixture model. The sample drawn from the model consisits of three parts. The first two parts are drawn from specified distributions f1 and f2, while the third one is drawn from the mixture. A problem of interest is whether the two distributions f1 and f2 are the same. To test this hypothesis, we first define the regular location and scale family of distributions and assume that f1 and f2 are regular denisty functions. Then the hypothesis transforms to the equalities of the location and scale parameters, respectively. To utilize the information in the sample, we use Bayes’ theorem to obtain the posterior distribution and give the sampling method. Then we propose the posterior p-value to test the hypothesis. The simulation studies show that our posterior p-value largely improves the power in both normal and logistic cases while nicely controls the Type-I error. A real halibut dataset is used to illustrate the validity of our method.

Transmembrane carriers of the Slc11 family catalyze proton (H+)-dependent uptake of divalent metal-ions (Me2+) such as manganese and iron - vital elements coveted during infection. Slc11 mechanism of high affinity Me2+ cell import is selective and conserved between prokaryotic (MntH) and eukaryotic (Nramp) homologs, though processes coupling the use of the proton motive force to Me2+ uptake evolved repeatedly. Adding bacterial piracy of Nramp genes spread in distinct environmental niches suggests selective gain of function that may benefit opportunistic pathogens. To better understand Slc11 evolution Alphafold (AF2)/Colabfold (CF) 3D predictions for bacterial sequences from sister clades of eukaryotic descent (MCb and MCg) were compared using both native and mutant templates. AF2/CF model an array of native MCb intermediates spanning the transition from outward open (OO) to inward open (IO) carrier. In silico mutagenesis targeting i) a set of (evolutionary coupled) sites that may define Slc11 function (putative synapomorphy), and ii) residues from networked communities evolving during MCb transition, indicate Slc11 synapomorphy primarily instructs Me2+-selective conformation switch which unlocks carrier inner gate, and contributes to Me2+ binding site occlusion and outer gate locking. Inner gate opening apparently proceeds from interaction between transmembrane helix (h) h5, h8 and h1a. MCg1 xenologs revealed marked differences in carrier shape and plasticity, owing partly to altered intramolecular H+-network. Yet, targeting Slc11 synapomorphy also converted MCg1 IO models to OO state, apparently mobilizing the same residues to control gates. But MCg1 response to mutagenesis differed, extensive divergence within this clade correlating with MCb-like modeling properties. Notably, MCg1 divergent epistasis marks emergence of the genus Bordetella-Achromobacter. Slc11 synapomorphy localizes to the 3D areas that deviate least among MCb and MCg1 models (either IO or OO) implying it constitutes a 3D network of residues articulating Me2+-selective carrier conformation switch which is maintained in fast evolving clades at the cost of divergent epistatic interactions impacting carrier shape and dynamics.

Enamel erosion is a process which happens every time we eat and it may be accelerated by some particular acid foods, drinks or other agents. Dental enamel when damaged by low pH substances becomes chalky, rough, opaque, yellowed and it can be related to dentinal hypersensitivity. To the present day, several possible solutions are available, therefore the aim of this study was to evaluate the effect of a biocompatible minerals serum based on calcium silicate, sodium phosphate and fluoride (Regenerate™) on the damaged enamel by four different acid liquids. 135 ovine teeth were equally divided into 5 groups and submerged for one week into lemon juice, energy drink, coffee, tea and physiologic solution for the negative control. The first 4 groups were evaluated for their color with an analogical color scale (Vita® Scale) and for their surface assigning a qualitative aspect among opaque, rough, chalky or smooth. Then they were treated with hydroxyapatite gels and re-evaluated for the same parameters. Data were checked for the normal distribution with Shapiro-Wilk test and analyzed with dependent t-test or Wilcoxon Signed Rank test, every test with a p≤0.05. Both color and surface aspect showed a strongly significant improvement after the treatment. Biocompatible minerals serum based on hydroxyapatite is able to reverse teeth erosion, improve the color and restore the smoothness of the dental enamel.

Coronary angiography, long considered the gold standard for coronary imaging, faces limitations in assessing coronary vessel wall anatomy and guiding percutaneous coronary intervention (PCI). Despite its prevalence, studies have demonstrated that it is suboptimal in estimating the severity of coronary disease and physiologic significance of stenosis. Intracoronary imaging techniques, such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT), offer promising alternatives to overcome these limitations. This review delves into the nuances of IVUS and OCT, highlighting their strengths and limitations as adjuncts to PCI. IVUS, utilizing ultrasound technology, and OCT, based on near-infrared light, each provide unique insights into coronary pathology. They differ in terms of temporal and spatial resolution, influencing their capabilities in plaque characterization and vessel assessment. The discussion navigates their historical evolution, technical specifications, and clinical utility. Meta-analyses and adjusted observational studies suggest that both IVUS and OCT-guided PCI correlate with reduced cardiovascular risks compared to angiographic guidance alone. While IVUS has demonstrated consistent benefits in terms of clinical outcomes, the evidence supporting OCT is less robust. However, the utilization of these imaging modalities remains variable across regions, with increasing adoption in recent years, particularly in IVUS-guided PCIs. Intravascular ultrasound's journey from early motion detection to current high-resolution mechanical systems is traced, including improvements in catheter size and compatibility. On the other hand, optical coherence tomography has advanced significantly, utilizing near infrared light to achieve unparalleled resolutions, albeit requiring temporary blood clearance for optimal imaging. In conclusion, IVUS and OCT offer valuable insights into coronary pathophysiology and guide interventions with improved precision compared to traditional angiography. While IVUS remains more extensively utilized, OCT's growing potential is underscored by advancements in technology, culminating in enhanced imaging capabilities. Both modalities demonstrate comparable clinical outcomes, emphasizing the need for tailored imaging choices based on individual clinical scenarios. The continued refinement and broader integration of intravascular imaging are expected to play a pivotal role in optimizing coronary interventions and patient outcomes.

The reaction of 2-bromo-1-(5-methyl-1-(4-nitrophenyl)-1H-1,2,3-triazol-4-yl)ethan-1-one (1) with 4-amino-5-((2,4-dichlorophenoxy)methyl)-4H-1,2,4-triazole-3-thiol (2) in absolute ethanol in the presence of triethyl amine as catalyst gave 2-((4-amino-5-((2,4-dichlorophenoxy)methyl)-4H-1,2,4-triazol-3-yl)thio)-1-(5-methyl-1-(4-nitrophenyl)-1H-1,2,3-triazol-4-yl)ethan-1-one (3) in 73% yield. The structure of the title heterocycle (3) was confirmed by X-ray single crystal diffraction and spectral analyses (NMR and IR).

This study has simulated the typical rainstorm on 20 July 2021 over central east China by using the first-generation Chinese Reanalysis datasets and Global Land Data Assimilation System datasets, and the Noah land surface model coupled with the advanced weather research and forecasting model. Based on this, the gridded planetary boundary layer (PBL) profiles and ensemble states within soil perturbations are collected to investigate the main land-atmosphere coupling characteristics during this modeled rainstorm by using various local coupling metrics and the introduced ensemble statistical metrics. Results have shown that (1) except for the stratospheric thermodynamics and surface thermal over mountain areas, the main characteristics of mid-low layers and surface have been well documented in this modeled rainstorm; (2) the typical coupling intensity is characterized by the dominant morning moistening, early noon weak PBL warming around 2, noontime buoyant mixing temperature deficit around 274 K, daytime PBL and surface latent flux contribution around 100 and 280 W/m2 respectively, and significant afternoon soil-surface latent flux coupling; (3) moist static energy is more significant than PBL height during the relation chains, which is consistent with the significance of surface moistening indicated by local coupling metrics. In general, wet soil contributes greatly to daytime moisture evaporation, which then increases the early noon PBL warming and enhances the noontime buoyant mixing within weak flux contribution. However, this has been suppressed by large-scale forcing such as the upper southwestern inflows of rainstorms, which has further significantly shaped the spatial distribution of statistical metrics in contrast. These quantitatively described local couplings have highlighted both the convection potential diagnoses usage for the local weather application and more applicable coupling threshold diagnoses within the finer spatial investigation.

The calibration of length is related to the national economy and people's livelihood. The traditional calibration of length value was sent the uncalibrated instrument to the laboratory and the intrinsic error of the tested instrument was obtained in the laboratory. However, calibrating the instrument in the site produced additional error. In this article, a remote calibration method of length measurement based on optical fiber information transmission following with a proof of principle system was studied to reduce the additional error. The 1.0-level displacement guide rail was calibrated according to this method. The results showed that the relative error of guide rail displacement under different lengths was within 0.6%. The expanded uncertainties of 10 μm, 100 μm and 1 mm were analyzed respectively. The calibration results meet the actual standards of the guide rail. This optical method is a good candidate for remote calibration.

Hay and straw are commonly used materials in agriculture. They are organic materials and therefore flammable. This article examines the behaviour of hay and straw when exposed to radiant heat. The objective of this study is to experimentally determine the ignition temperature of hay and straw under the influence of radiant heat. The research investigates the effects of sample type (hay and straw) and sample quantity on the thermal degradation process, temperature increase within the samples, and ignition temperature of the samples as a function of time. The ignition temperature of hay was determined to be higher (407°C) compared to straw (380°C). The results did not demonstrate a significant correlation between sample type and the thermal degradation process or the ignition temperature of hay and straw.

Abstract Aims: In recent years, electro kinetic (EK) remediation has become more popular as a novel method for removing chromium contamination from soil. This approach, however, is ineffective since it uses both cationic and anionic forms of chromium. In this work, a membrane –based technique was employed to increase the efficiency of the electro kinetic removal of chromium. Methods: Chromium removal from polluted sludge was studied in four bench-scale experiments, two of which used distilled water (EK-1, EK2 & Membrane) and two of which used acetic acid as a catholyte (EK-3, EK4 &Membrane). Results: The pH, total chromium, and fractionation of chromium in the sludge were measured after remediation. In the EK-1, EK-2 & Membrane and EK-3, EK-4 & Membrane trials, the average removal efficiency of total chromium was 47.6%, 58.6%, and 74.4%, 79.6%, respectively. Conclusion: In contrast to the electro kinetic remediation strategy, which left approximately 80% of the sludge neutral or alkaline after treatment, the use of the membrane created acidic soil conditions throughout the sludge. For example, the high field intensity used in the membrane tests may have helped to facilitate chromium desorption, dissolution and separation from the sludge, as well as enhance chromium mobility. The findings show that the membrane can improve the effectiveness of chromium removal from sludge when utilized in the EK remediation process.

The paradigm of molecular communications is applied to the concrete case for delivering electrically charged nanoparticles to tumor. Once them have been injecetd in blood it is expecetd an optimal outcome as to reduce toxicity and minimal dispersion of drugs in the blood stream. With a fraction of nanoparticles arrives to surface of tumor, the scattered part of injected ones can minimize the success of scheme of drug delivery. In this paper is presented a theory based at the sequence electrodynamics-diffusion-Bayes theorem. The resulting probability of Bayes at the end of sequence, might be telling us that dynamical processes based in the injection of electrically charged nanoparticles might be dictated by stochastic formalism more that biochemical approaches by which makes impossible to know the success or fail of drug delivery dynamics. Illustrations demonstrating the transition of a linear to nonlinear scenario are presented

Dyes, as indigo carmine have become indispensable to modern life being widely used in food, textile, pharmaceutical, medicine and cosmetic industries. Although indigo carmine is considered toxic and presents many adverse effects, it is heavily used in the food industry because the blue pigment is difficult to obtain from natural sources and is one of the most used dyes in the textile industry, especially for dyeing denim. Also, indigo carmine is one of the dyes used in medicine as diagnostic agent because it has impressive applicability in terms of diagnostic methods and surgical procedures. In the literature it is reported that indigo carmine is toxic for humans and can cause various pathologies, such as hypertension, hypotension, skin irritations, corneal and conjunctival disorders or gastrointestinal disorders. In this review, we discuss the structure and properties of indigo carmine, its use in various industries and medicine, the adverse effects of its ingestion, injection or skin contact, the effects on environmental pollution and its toxicity testing.

Electrochemical biosensors based on immobilized enzymes are among the most popular and commercially successful biosensors. Literature in this field suggests that modification of electrodes with nanomaterials is an excellent method for enzyme immobilization, which can greatly improve the stability and sensitivity of the sensor. However, the poor stability, weak reproducibility, and limited lifetime of the enzyme itself still limit the requirements for the development of enzyme electrochemical biosensors for food production process monitoring. Therefore, constructing sensing technologies based on enzyme electrochemical biosensors remains a great challenge. This article outlines the construction principles of four generations of enzyme electrochemical biosensors and discusses the applications of single-enzyme systems, multi-enzyme systems and nano-enzyme systems developed based on these principles. The article further describes methods to improve enzyme immobilisation by combining different types of nanomaterials such as metals and their oxides, graphene-related materials, metal-organic frameworks, carbon nanotubes and conducting polymers. In addition, the article highlights the challenges and future trends of enzyme electrochemical biosensors, providing theoretical support and future perspectives for further research and development of high-performance enzyme chemical biosensors.

Wildlife tourism and wildlife trade may appear juxtaposed, but are two, potentially aligning, in-come generators that could benefit conservation in developing countries. Utilising data sets collated from Madagascar’s Ministère du Tourisme and CITES respectively for the period 2007 to 2018, this study estimated levels of income from wildlife tourism and wildlife trade for Madagascar. Between 2007-2018, tourism reported yearly incomes ranging from a low of US \$1.4 million up to a high of US \$15.7 million. However, it was unclear what percentage of this figure flowed to benefit local communities. Alternatively, using reported networks for the live wildlife trade, the estimated eco-nomic value reaching collectors and/or intermediaries on Madagascar was US $72,299.80 for the period 2007 to 2018. Both revenue generators operated within different geographical areas, with tourism opportunities presenting themselves to communities adjacent NPs, while wildlife trade networks were not restricted to National Parks and operated sporadically across Madagascar. Hence, the economic benefits reached different Malagasy participants across the country. The management of both activities needs great care to ensure that environmental impacts and sus-tainability are core measures on any such activities. Whilst this study shines light on economic values and novel perspectives regarding these two trade types, it also highlighted knowledge gaps. Thus, indicating where much greater research attentions was required to allow better understanding of the specific benefits and risks from engaging with both trade types for local Malagasy people and their environments.

The role of upfront primary tumor resection (PTR) in patients with unresectable metastatic col-orectal cancer (CRC) without severe symptoms remains controversial. We retrospectively ana-lyzed the role of PTR in overall survival (OS) in different subgroups. Among 331 patients diag-nosed with synchronous metastatic CRC between 2010 and 2020, 223 were analyzed. The PTR group (n = 42) showed better performance (p = 0.038); higher frequencies of right-sided origin (p = 0.014), T4 stage (p = 0.005), M1a stage (p = 0.015), and <2 organ metastases (p = 0.002); and re-ceived fewer targeted agents (p < 0.001) than the chemotherapy group (n = 181). The PTR group showed longer OS (20.5 versus 14.0 months, p = 0.016), but PTR was marginally related to OS in multivariate analysis (p = 0.060). Male sex (p = 0.022), good performance status (p = 0.07), left-sided tumor (p = 0.069), low serum carcinoembryonic antigen level (p = 0.092), T3 stage (p = 0.029), M1a stage (p = 0.025), <2 organ metastases (p = 0.017), and administration of targeted agents, especially bevacizumab (p = 0.024), were related to survival benefit after PTR. Upfront PTR should be considered when selecting patients with favorable prognoses for bevacizumab administration.

The impact of early maternal age on several outcomes (e.g. mental health issues, delinquency, aggression, impulsivity, victimization and interpersonal difficulties) has been studied since the late 1980s. Research has demonstrated links between exposure to adverse childhood experiences (ACEs) and trauma related outcomes such as substance abuse, interpersonal and self-directed violence, and sexual risk-taking, to name a few. The current study analyzed the incidence of ACE exposure and mental health outcomes (e.g. suicidal behaviors or self-harm, psychiatric hospitalizations, and substance use) as related to early maternal age in youth known to have experienced trafficking or sexual abuse. General demographics and incidence of various experiences and clinical presentations (e.g. ACE exposure, age of mother at birth of youth and age at first birth), and history of self-harm, substance use and psychiatric hospitalization were examined in a sample of 225 youth referred for services subsequent to experiences of sex trafficking or exploitation. Relationships between ACE exposure and maternal age related to mental health outcomes was also examined. Trafficked and exploited youth reported rates of ACE exposure and poor mental health outcomes at far greater rates than the general population. Significant findings were related to early maternal age and engaging in self-harm or suicidal behaviors. Previously anticipated mediational analyses were not conducted due to the sample size and lack of correlations. Findings highlight the significant ACE exposure and high needs of exploited, trafficked and abused youth and related mental health outcomes, emphasizing the need for early and comprehensive preventive and therapeutic interventions.

Antibiotic-loaded bone cements are widely used in orthopedic surgery. However, they present issues such as a short antibiotic release time and the antibiotic resistance. These challenges necessitate the development of novel antibacterial bone cements. Non-leaching bone cement containing antibacterial motifs represents a promising advancement in this direction. Antibacterial motifs are incorporated into the cement either covalently or non-covalently, and while they will not be released, they will still exhibit surface antibacterial activity. This review comprehensively examines the structure and antimicrobial activity of prevalent non-leaching antimicrobial bone cements. Additionally, it delves into the characteristics of current methods employed for detecting surface antimicrobial activity. Finally, the future research direction of non-leaching antibacterial bone cement is discussed, with a specific focus on innovative antibacterial motifs, the mechanisms underlying non-leaching antibacterial properties, and the potential synergies achievable by combining non-leaching antibacterial bone cement with traditional antibiotics.

Pyrochlore oxides (A2B2O7) are potential nuclear waste substrate material due to their superior radiation resistance properties. We performed molecular dynamics simulations to study the structural properties and displacement cascades in ytterbium titanate pyrochlore (Yb2Ti2O7). We computed threshold displacement energy ( Ed ) and lattice constant ( ao) of Yb2Ti2O7. The effect of displacement cascades in Yb2Ti2O7 of recoils of energies 1 keV, 2 keV, 5 keV, 10 keV in different crystallographic directions ([100], [110], [111]) were studied. The number of defects is found to be proportional to the energy of incident PKA. Additionally, the Ed of pyrochlore is computed and it exhibits anisotropy. Furthermore, radiation damage in high-entropy pyrochlore (HEPy) i.e., YbYTiZrO7, YbGdTiZrO7 , Yb0.5Y0.5Eu0.5Gd0.5TiZrO7 were investigated and compared with Yb2Ti2O7. It was found that HEPy have a larger Ed as compared with Yb2Ti2O7 which exhibits characteristic of lower radiation damage resistance than HEPy. Our simulation proposed that HEPy alloys are more radiation resistant than individual pyrochlore constituents . This work will provide atomic insights in developing substrate materials for nuclear waste applications.

In this paper, we consider a pursuit-evasion game of inertial players, where pursuer’s control is subject to integral constraint, and evader’s control is subject to geometric constraint. In the pursuit problem, the main tool is the strategy of parallel pursuit. Sufficient conditions are obtained for the solvability of pursuit-evasion problems. Also, the main lemma describing the monotonicity of an attainability domain of the evader is proved and an explicit analytical formula for this domain is given. As one of the important results of our paper, the Isaacs Life-line game is solved for a special case.

Edge computing has emerged as a significant computing trend alongside the rapid expansion of the Internet of Things (IoT). Computing operations at the network’s edge offer a solution to the high latency and service overload challenges often associated with cloud computing. Additionally, the Secure Hash Algorithm-3 (SHA-3) plays a crucial role in ensuring data integrity and is implemented for numerous applications in the IoT field. Therefore, integrating the SHA-3 accelerator into edge computing is essential. Moreover, recent studies about SHA-3 have primarily focused on achieving high performance and optimizing resource utilization for SHA-3. However, these studies have overlooked the crucial aspect of data transfer between the external memory and the hash function block, as transfer time plays a significant role. This paper proposes an efficient SHA-3 architecture designed for System-on-Chip (SoC) Field Programmable Gate Array (FPGA) to address the aforementioned challenges and be suitable for real edge computing. The architecture contains three key techniques. First, the harmony of padding and Direct Memory Access (DMA) for managing the data transfer process and enhancing performance efficiency based on Serial Input to Parallel Output (SIPO) and a barrel shifter. Secondly, implementing internal pipelining within the Round Function (RF) to reduce critical path delays and optimize resource utilization. Finally, designing four modes (SHA3-224, SHA3-256, SHA3-384, and SHA3-512) to cater to various applications. Our architecture is implemented and tested on the DE10-Standard Development Kit (Cyclone V SX SoC-5CSXFC6D6F31C6N), which is integrated into the FPGA and is controlled by a Dual-Core ARM Cortex-A9 processor. The result is up to 38.34 Gbps in throughput and 5.61 Mbps/ALM in efficiency for the RF computation, 28.02 Gbps in throughput, and 3.63 Mbps/ALM for the full proposed architecture.

Real-time tracking is one of the most challenging problems in computer vision. Most Transformer-based trackers usually require expensive computational and storage power, which leads to the inability of these robust trackers to achieve real-time performance in resource-constrained devices. In this work, we propose a lightweight tracker, AnteaTrack. To localize the target more precisely, we develop a scaling-invariant max-filtering operator employing a sliding window combined with local max-pooling, which filters out the suspected target from the feature and performs an augmented representation while suppressing the background. For a more tight bounding box, we employ Pixel-Shuffle to increase the resolution of the feature map and get a more fine-grained representation of the target. In addition, AnteaTrack can run in real-time at 47 frames per second(FPS) on the CPU. We tested AnteaTrack on 5 datasets, and a large number of experiments have shown that AnteaTrack provides the most efficient solution compared to the same type of CPU real-time trackers. The code will be available at https://github.com/cnchange/AnteaTrack.

Crohn's disease (CD) is a chronic, immune-mediated inflammatory bowel disease characterized by transmural damage of various parts of the gastrointestinal tract. The aim of the study is to present our experience in pre-surgical diagnosis, selection of surgical tactics and volume of intervention in different variants of gastrointestinal tract lesions and disease activity. We undertook cross-sectional, retrospective-prospective study of 64 children who underwent surgery due to complicated CD. We analyzed CD activity via PCDAI, medications used, inflam-mation localization, and changes in mass-growth parameters at pre-surgery stage. Three patients from the group of 44 children with two-stage surgical treatment later showed inefficacy of GEBD in post-operative period. The disease progression was revealed and, therefore, subtotal colectomy was required. Three children had secondary adhesion of surgical wounds by means of active immunosuppressive therapy at preoperative period, and five patients developed suture sinuses at post-operative period. Early adhesive intestinal obstruction was revealed in 3 (4.7%) cases, and they required re-surgery. Personalized approach to the surgical treatment of children with complicated CD has shown its efficacy due to the small percentage of postoperative complications with re-surgery. There was significant improvement in mass-growth parameters, recovery of albumin levels, and anemia decrease in 96.9% of cases in the long-term postoperative period (6 months or more). Two children (3.1%) had the narrowing of anastomotic zone lumen, thus, without any obstruction. These cases were associated with violations in drug treatment

Introduction: Prostate cancer (PCa) is one of the deadliest and most common causes of malignancy and death in men worldwide, more specifically with higher prevalence and mortality in developing countries. Factors such as age, family history, race and certain genetic mutations are some of the factors contributing to the occurrence of PCa in men. The recent advances in technology and algorithms gave rise to the computer-aided diagnosis (CAD) of PCa. With the availability of medical image datasets and emerging trends in state-of-the-art machine and deep learning techniques, there is a growth in recent related publications. Materials and Methods: In this study, we present a systematic review of PCa diagnosis with medical images using machine learning and deep learning techniques. We conducted a thorough review through relevant studies indexed in four databases (IEEE, PubMed, Springer and ScienceDirect) using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. With well-defined search terms, a total of 608 articles were identified and 77 met the final inclusion criteria. Key elements in the included papers were presented and conclusions were drawn from them. Results: Findings showed that the United States has the most research in PCa diagnosis with machine learning, Magnetic Resonance Images are the most used datasets and transfer learning is the most used method of diagnosing PCa in recent times. In addition, some available PCa datasets and some key considerations for choice of loss function in the deep learning models were presented. The limitations and lessons learnt were discussed and some key recommendations were made. Conclusion: The discoveries and the conclusions of this work have been organized so as to enable researchers in the same domain to use this work and make crucial implementation decisions.

Autophagy is a highly conserved catabolic process in eukaryotic cells. Reactive nitrogen species play roles as inductors and signaling molecules of autophagy. A key mechanism of NO-mediated signaling is S-nitrosylation, a posttranslational modification (PTM) of proteins at cysteine resi-dues. In the present work we analyzed the patterns of protein S-nitrosylation during the induc-tion of autophagy in Triticum aestivum roots. The accumulation of S-nitrosylated proteins in the cells during autophagy induced by KNO2 and antimycin A was visualized using monoclonal an-tibodies by Western blot analysis, and proteins were identified using a standard bottom-up pro-teomics approach. Protein S-nitrosylation is a labile and reversible PTM, and therefore SNO group can be lost during experimental procedures. Subsequent bioinformatic analysis using predictive algorithms and protein-ligand docking showed that identified proteins possess hypothetical S-nitrosylation sites. Analyzing protein-protein interaction networks enabled us to discover the targets that can directly interact with autophagic proteins, and those that can interact with them indirectly via key multifunctional regulatory proteins. In this study, we show that S-nitrosylation is a key mechanism of NO-mediated regulation of autophagy in wheat roots. A combination of in silico predictive algorithms with a mass spectrometry analysis provides a targeted approach for the identification of S-nitrosylated proteins.

Background: Scaffold (SCA) functionalization with aptamers (APT) provides adsorption of specific bioactive molecules on biomaterials surface. The aim of this study was to observe if SCA enriched with anti-fibronectin APT can favor coagulum (PhC) and osteoblasts (OSB) differentiation. Methods: 20 ug of APT was functionalized on SCA by simple adsorption. For PhC formation, SCAs were inserted into rat calvaria defects for 17 hours. Following proper transportation (Buffer solution-PB), OSB (UMR-106 lineage) were seeded over PhC + SCAs with and without APT. Cells and PhC morphology, PhC cell population, protein labelling and gene expression were observed in different time points. Results: The APT induced higher ALP and BSP immunolabeling in OSB. CD90, CD45 and CD44 expression was more detected in APT group than when scaffolds were not functionalized. Additionally, an enriched and dense fibrin network and different cell types were observed, with more OSB and white blood cells in PhC formed on SCA with APT. The gene expression showed higher TGF-β1 detection in SCA with APT. Conclusions: The SCA functionalization with fibronectin aptamers provides a selective expression of proteins related to coagulation pattern and osteo differentiation. Additionally, aptamers increase TGF-β1 gene expression, which is highly associated with improvements in regenerative therapies.

Anode materials based on TiO2 nanoparticles of different morphologies were prepared using the hydrothermal method and characterized by various techniques, such as X-ray diffraction (DRX), scanning electron microscopy (FE-SEM), and N2 absorption. The TiO2 nanoparticles prepared were used as anode materials for lithium-ion batteries (LIBs), and their electrochemical properties were tested using discharging/charging measurements. The results showed that the initial morphology of the nanoparticles plays a minor role in battery performance after the first few cycles and that better capacity was achieved for TiO2 nanobelt morphology. The sharp drop in the specific capacity of LIB during their first cycles is examined considering changes in the morphology of TiO2 particles and their porosity properties in terms of shape and connectivity.

This paper presents a novel sensor for the detection and characterization of regions of air turbulence that would be of use to improve UAV stability in bad weather. It consists of a combined Schlieren imager and a Radar Acoustic Sounding System (RASS) to produce dual modality “images” of air movement within the measurement volume. The ultrasound modulated Schlieren imager consists of a strobed point light source, parabolic mirror, light-block and camera which are controlled by two laptops. It provides a fine scale projection of the acoustic pulse modulated air turbulence through the measurement volume. The narrow beam 40 kHz/ 17 GHz RASS produces spectra based on Bragg enhanced Doppler radar reflections from the acoustic pulse as it travels. Tests using artificially generated air vortices showed some disruption of the Schlieren image and of the RASS spectrogram. This should allow the higher resolution Schlieren images to identify the turbulence mechanisms that are disrupting the RASS spectra.

Antioxidants reduce arterial stiffness but the effects previously reported are weak. The present study evaluated the effects of 2 weeks of therapy with a combination of antioxidants (l-cysteine, thiamine, pyridoxine and ascorbic acid) compared to placebo on stiffness index (SI) a measure of arterial stiffness that is strongly correlated with central pulse wave velocity (PWV), using a Pulse Trace recorder in a diverse group of 78 volunteers. SI fell by 1.7 m/sec relative to placebo (95% confidence intervals 0.6 to 2.7 m/sec), a reduction of 19% (95% confidence intervals 9% to 31%). The Glass effect size was 1.4, indicating a very strong treatment effect which was substantially greater than found in previous studies of the effects of antioxidant therapy on arterial stiffness. The magnitude of reduction in SI was positively correlated with increasing age (r = 0.362 P = 0.02). The change in RI, a measure of compliance of small to medium size arteries, did not differ between the antioxidant and placebo groups The combination of antioxidants studied reduced PWV to a much greater extent than reported for other antioxidants. This combination may be of value in the treatment of cardiovascular disease.

Software testing is an integral yet time-consuming component of software development, and even with capable software testing resources (technology and people), it is still regarded as problematic. Test automation is widely being utilised within the software industry to provide increased testing capacity to ensure high product quality and reliability. In this paper, we are specifically addressing automated testing whereby test cases are manually written. Test automation has its benefits, drawbacks, and impacts on different stages of development. Furthermore, there is often a disconnect between non-technical and technical roles, where non-technical roles (e.g., management) predominantly strive to reduce costs and delivery time whereas technical roles are often driven by quality and completeness. Although it is widely understood that there are challenges with adopting and using automated testing, there is a lack of evidence to understand the different attitudes toward automated testing (AtAT), focusing specifically on why it is not adopted. In this paper, the authors have surveyed practitioners within the software industry from different roles to determine common trends and draw conclusions. A two-stage approach is presented, comprising a comprehensive descriptive analysis and the use of Principle Component Analysis. In total, 81 participants were provided with a series of 22 questions and their responses are compared against job role types and experience levels. In summary, 6 key findings are presented covering expertise, time, cost, tools and techniques, utilisation, organisation, and capacity

The paper examines rational Darboux-Crum transforms (RDCTs) of the Jacobi-reference (JRef) potential on the line, with an emphasis on the transformations using only normalizable seed solutions. The Cooper-Ginocchio-Khare (CGK) potential constitutes the simplest example of this rich family of exactly solvable one-dimensional (1D) potentials. It was explicitly confirmed that that an arbitrary Darboux-Crum transformation (DCT) of the given Sturm-Liouville equation (SLE) can be represented as a chain of sequential Darboux deformations of the associated Liouville potentials. If the rational SLE (RSLE) under consideration is exactly solvable and the transformation function (TF) used at each step is nodeless then each RSLE constructed in such a way was proven being exactly solvable itself. The exact solvability of RDCTs of the JRef canonical SLE (CSLE) was also confirmed for the DCTs using pairs of juxtaposed eigenfunctions (an extension of the renowned Adler theorem to the RCSLEs of our interest). By re-expressing the reference polynomial fraction (RefPF) of the transformed CSLE in terms of the Krein determinant (KD), instead of Crum Wronskian (CW), it was shown that the eigenfunctions under consideration are expressible in terms of polynomial solutions of a generalized Heun equation with positions of the most poles dependent on the exponent parameters. The outlined technique was extended to two isospectral SUSY partners of the JRef potential (as well as to its third sibling with the inserted new lowest-energy level) which, by analogy with the CGK potential, are quantized by polynomial solutions of the 2-Heun equation with all four poles at some fixed positions on the real axis.

The article is devoted to the issues of assessing the impact of changes in the delay value in the feed direction, what determines the regenerative nature of self-excitation of the cutting system, on the dynamics of metal processing on metal-cutting machines. It is this interconnected model of the cutting system that allows to identify the main dynamic effects that occur in the cutting system, including the effect of vibrations regeneration when cutting along the track. The article also has a section dedicated to the experiment on a real metalworking machine, on which vibrations of the top of the cutting wedge of the tool were measured and based on these data, a real calculation of the delay time and the magnitude of the change in the area of the cut layer was carried out, due to variations in the real feed. The conducted studies have shown that in addition to the vibrations of the cutting tool in the direction of feeding, the vibration activity of the tool in the direction of cutting plays an essential role in ensuring the regenerative effect. The delay time constant of the operator is formed, which determines the real value of the feed during cutting.

Research on wearable solutions for individuals with autism spectrum disorder (ASD) has been conducted to detect stress. However, studies on stress detection for an individual with ASD have been limited, especially on how it should design for individuals with ASD. Wearable solutions may be a tool for parents and caregivers for emotional monitoring for individuals with ASD who have a high risk of experiencing very stressful. However, wearable solutions for individuals with ASD may differ from those without ASD. Individuals with ASD have sensory sensitiveness; therefore, they do not tolerate any accessory type or discomfort to use. We used the Scopus, PubMed, WoS, and IEEE-Xplore databases to answer different research questions related to wearable solutions for individuals with ASD, physiological parameters, and algorithms of artificial intelligence used for stress detection studies found from 2013 to 2023. Our review found 34 articles; not all the studies considered individuals with ASD or were out of the scope.

Introduction: This study aimed to evaluate whether radiomic features extracted solely from the edema of soft tissue sarcomas (STS) could predict the occurrence of lung metastasis in comparison with features extracted solely from the tumoral mass. Materials and Methods: We retrospectively analyzed magnetic resonance imaging (MRI) scans of 32 STSs including 14 with lung metastasis and 18 without. Segmentation of the tumor mass and edema was performed for each MRI examination. A total of 107 radiomic features were extracted for each mass segmentation and 107 radiomic features for each edema segmentation. A two-step feature selection process was applied. Two predictive features for the development of lung metastasis were selected from the mass-related features, as well as two predictive features from the edema-related features. Two random forest models were created based on these selected features; 100 random subsampling runs were performed. Key performance metrics including accuracy and area under the ROC curve (AUC) were calculated, and the resulting accuracies were compared. Results: The model based on mass-related features achieved a median accuracy of 0.83 and a median AUC of 0.88, while the model based on edema-related features achieved a median accuracy of 0.75 and a median AUC of 0.79. Statistical analysis comparing the accuracies of the two models revealed no significant difference. Conclusion: Both models showed promise in predicting the occurrence of lung metastasis in soft tissue sarcomas. These findings suggest that radiomic analysis of edema features can provide valuable insights into the prediction of lung metastasis in soft tissue sarcomas.

This study aimed to investigate the diagnostic potential of circulating microRNAs (miRNAs) for detecting early myocardial fibrosis development in HFpEF patients. This observational study used a case-control research design. Peripheral blood samples were isolated from 25 HFpEF patients and 25 normal patients. They were measured for NTproBNP levels using ELISA, as well as MicroRNA-1, 21, and 29 levels using RT-PCR. All patients also underwent echocardiography for global longitudinal strain (GLS) to measure the myocardial fibrosis progression. Data were analyzed using SPSS 25.0. HFpEF patients had significantly higher GLS compared to the normal patients (-13±2.4% vs -19±3.2%; p &lt; 0.05), suggesting HFpEF patients tended to have myocardial fibrosis. HFpEF patients also had significantly higher microRNA-1 and microRNA-21 compared to the normal patients (p &lt; 0.05), but they had lower microRNA-1 (p &lt; 0.05). There was a positive correlation between microRNA-1 (r = 0.753; p &lt; 0.05) and microRNA-21 (r = 0.675; p &lt; 0.05) and an inverse correlation with microRNA-29 (r = -0.653; p &lt; 0.05) based on the GLS findings. By using a GLS cutoff of -15% for myocardial fibrosis, microRNA-1, microRNA-21, and microRNA-29 were found to be able to predict myocardial fibrosis based on GLS with a specificity of 78% and sensitivity of 75%. Increasing microRNA-1 and microRNA-21 followed by decreasing microRNA-29 in HFpEF patients suggest early myocardial fibrosis.

Zero-emission trucks for regional and long haul missions are an option for fossil-free freight. The viability of such powertrains and system solutions was studied conceptually in project ESCALATE for trucks with GVW of 40 tonnes and beyond through various prime mover combinations. The study covers battery and fuel cell power sources with different degrees of battery electric as well as H2 and fuel cell operation. As a design basis, two different missions with a single-charge/H2 refill were analysed. The first mission was the VECTO long haul profile repeated up to 750 km, whereas the second was a real 520 km on-road mission in Finland. Based on the simulated energy consumption on the driving cycle, on-board energy demand was estimated, and the initial single-charge operational scenarios were analysed with five different power source topologies. The traction motors of the tractor were dimensioned so that a secondary mission of GVW up to 76 tons on a shorter route can be operated. Based on the powertrain and vehicle model, various infrastructure options for charging and H2 refuelling strategy as well as various operative scenarios with indicative total cost of ownership (TCO) were analysed.

MoS2 has long been considered as a promising catalyst for hydrogen production. At present, there are many strategies to further improve its catalytic performance, such as edge engineering, defect engineering, phase engineering and so on. However, at present, there is still a great deal of controversy about the mechanism of MoS2 catalytic hydrogen production. For example, it is generally believed that the base plane of MoS2 is inert, but it has been reported that the inert base plane can undergo a transient phase transition in the catalytic process to play the catalytic role, which is contrary to the common understanding that the catalytic activity is only at the edge. Therefore, it is necessary to further understand the mechanism of MoS2 catalytic hydrogen production. In this article, we summarized the latest research progress on the catalytic hydrogen production of MoS2, which is of great significance for revisited the mechanism of MoS2 catalytic hydrogen production.

Background: Micronutrient deficiencies are common at the time of cancer diagnosis and are associated with worse prognosis. Little is known about them in cancer rehabilitation. Methods: Data from routine health related quality of life (HRQOL) were analyzed at an inpatient cancer rehabilitation center. Rehabilitation patients completed the EORTC QLQ-C30 questionnaire before and after multidisciplinary rehabilitation treatment, and three month after discharge. Selenium and zinc status was measured in whole blood at these three time points. In case of selenium deficiency up to 600 µg selenium per day as sodium selenite was supplemented. Results: A total of 271 patients (breast, colon, and pancreatic cancer) were included in the analysis. There was clinically meaningful improvement in many domains of the EORTC QLQ-C30 during rehabilitation. However, effect often waned in the three months after. Prevalence for selenium deficiency varied between 34 to 90 percent depending on cancer type (breast &lt; colon &lt; pancreas). In contrast, zinc deficiency was rare. Daily selenium supplementation of 600 µg was more efficient to correct selenium deficiency compared to 300 µg selenium per day. Rehabilitation and increasing selenium status after rehabilitation were associated with improved global quality of life, physical and emotional functioning, and fatigue. In cancer patients with decreasing selenium status, values of global quality of life, physical and emotional functioning, and fatigue were back to the values at the beginning of rehabilitation. Conclusions: Selenium deficiency is common in cancer patients admitted to a cancer rehabilitation clinic. Selenium supplementation during rehabilitation effectively corrected selenium deficiency in most cases. The positive effects of rehabilitation persisted longer, when selenium status did not decrease after rehabilitation.

Evaporating liquid sessile drop deposited on horizontal surface is an important object of applications (printing technologies, electronics, sensorics, medical diagnostics, hydrophobic coatings, etc.) and theoretical investigations (microfluidics, self-assembly of nanoparticle, crystallization of the solute, etc.). The arsenal of formulas for calculating the slow evaporation of an axisymmetric drop of capillary dimensions deposited on a flat solid surface is reviewed. Such characteristics as vapor density, evaporation flux density, total evaporation rate are considered. Exact solutions obtained in the framework of the Maxwellian model, in which the evaporation process of the drop is limited by vapor diffusion from the drop surface to the surrounding air, are presented. The summary covers both well-known results obtained during the last decades and new results published by us in the last few years, but practically unknown to the wide scientific community. The newest formulas, not yet published in refereed publications, concerning exact solutions for a number of specific contact angles are also presented. In addition, new approximate solutions are presented for the first time (total evaporation rate and mass loss per unit surface area per unit time in the whole range of contact angles ), which can be used in modeling without requiring significant computational resources.

A method for studying properties of the earth's surface tremor, measured by means of GPS, is proposed. Four characteristics of tremor are considered: the entropy of the distribution of wavelet coefficients, the Donoho-Johnston wavelet index, and two estimates of the spectral slope. The anomalous areas of tremor are determined by estimating the probability densities of extreme values of the studied properties. The criteria for abnormal tremor behavior are based on the proximity to, or the difference between, tremor properties and white noise. The greatest deviation from the properties of white noise is characterized by entropy minima and spectral slope and DJ index maxima. This behavior of the tremor is called "active". The "passive" tremor behavior is characterized by the maximum proximity to the properties of white noise. The principal components approach provides weighted averaged density maps of these 2 variants of extreme distributions of parameters in a sliding time window of 3 years are considered. Singular points are the points of maximum average densities. The method is applied to the analysis of daily time series from a GPS network in the West USA in 2009-2022. It turned out that singular points of tremor form well-defined clusters.

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

Generative artificial intelligence (AI), in particular large language models such as ChatGPT have reached public consciousness with a wide-ranging discussion of their capabilities and suitability for various professions. The extant literature on the ethics of generative AI revolves around its usage and application, rather than the ethical framework of the responses provided. In the education sector, concerns have been raised with regard to the ability of these language models to aid in student assignment writing with the potentially concomitant student misconduct of such work is submitted for assessment. Based on a series of ‘conversations’ with multiple replicates, using a range of discussion prompts, this paper examines the capability of ChatGPT to provide advice on how to cheat in assessments. Since its public release in November 2022, numerous authors have developed ‘jailbreaking’ techniques to trick ChatGPT into answering questions in ways other than the default mode. While the default mode activates a safety awareness mechanism that prevents ChatGPT from providing unethical advice, other modes partially or fully bypass the this mechanism and elicit answers that are outside expected ethical boundaries. ChatGPT provided a wide range of suggestions on how to best cheat in university assignments, with some solutions common to most replicates (‘plausible deniability,’ language adjustment of contract written text’). Some of ChatGPT’s solutions to avoid cheating being detected were cunning, if not slightly devious. The implications of these findings are discussed.

Barrier coverage is a fundamental application in wireless sensor networks, which is widely used to protect a region through intruder detection for smart city. In this paper, we study a new branch of barrier coverage, named warning barrier coverage (WBC). Different from the classic barrier coverage, WBC has the inverse protect direction, which protects unexpected visitors by warning them away from the region enclosed by sensor barriers. The WBC holds a promising prospect in many danger keep out applications for smart city. For example, a WBC can enclose the debris area in the sea and alarm any approaching ships in order to avoid their damaging propellers. One special feature of WBC is that the target region is usually dangerous and its boundary is previously unknown. Hence, the scattered mobile nodes need to detect the boundary and form the barrier coverage themselves. It is challenging to form these distributed sensor nodes into a barrier because a node can sense only the local information and there is no global information of the unknown region or other nodes. To this end, we propose a novel solution AutoBar for mobile sensor nodes to automatically form a WBC for smart city. To pursue the high coverage quality, we theoretically derive the optimal distribution pattern of sensor nodes using convex theory. Based on the analysis, we design a fully distributed algorithm that enables nodes to collaboratively move towards the optimal distribution pattern. In addition, AutoBar is able to reorganize the barrier even any node is broken. To validate the feasibility of AutoBar, we develop the prototype of the specialized mobile node, which consists of two kinds of sensors: one for boundary detection and another for visitor detection. Based on the prototype, we conduct extensive real trace driven simulations in various smart city scenarios. Performance results demonstrate that AutoBar outperforms the existing barrier coverage strategies in terms of coverage quality, formation duration, and communication overhead.

Brassinosteroids (BR) are key phytohormones involved in the regulation of major processes of cell metabolism guiding plant growth. In the past decades, new evidence made it clear that BRs also play a key role in the orchestration of plant responses to many abiotic and biotic stresses. In the present work we analyzed the impact of foliar treatment with 24-epicastasterone (ECS) on the endogenous content of major phytohormones (auxins, salicylic acid, jasmonic acid, abscisic acid) and their intermediates in soybean leaves 7 days following the treatment. Changes in the endogenous content of phytohormones have been identified and quantified by LC/MS. Obtained results point to a clear role of ECS in the upregulation of auxin content (indole-3-acetic acid, IAA) and downregulation of salicylic, jasmonic, and abscisic acid levels. These data confirm that under optimal conditions ECS in tested concentrations of 0,25 µM and 1 µM might promote growth in soybean by inducing auxin contents. Benzoic acid (a precursor of salicylic acid (SA)), but not SA itself, has also been highly accumulated under ECS treatment which indicates an activation of the adaption strategies of cell metabolism to possible environmental challenges.

The Harmonic Graphs Conjecture states that there exists an asymptotic relation involving the Harmonic Index and the natural logarithm as the order of the graph increases. This conjecture, grounded in the novel context of Prime Graphs, draws upon the Prime Number Theorem and the sum of divisors function to unveil a compelling asymptotic connection. By carefully expanding the definitions of the harmonic index and the sum of divisors function, and leveraging the prime number theorem's approximations, we establish a formula that captures this intricate relationship. This work is an effort to contribute to the advancement of graph theory, introducing a fresh lens through which graph connectivity can be explored. The synthesis of prime numbers and graph properties not only deepens our understanding of structural complexity but also paves the way for innovative research directions.

The study was conducted to prepare juice blend by using Orange, Carrot and Tiger-nut juices. Fully mature raw Orange, Tiger-nut and Carrot were processed into juice forms and combined in different ratios which were analyzed for their composition and Consumer’s acceptability. The analysis showed that the juice with higher Orange juice content had higher levels of acidity. This implies that they would last longer as they are not susceptible to spoilage by most organisms. The Juice with higher orange juice content was also found to be very rich in Vitamin C, due to inherent high amount of Vitamin C in raw Orange Fruit. However, it scored lowest in terms of general acceptability because the raw fruit was purchased separately and there’s a likelihood some of the Orange used in the Juice preparation were sour. This led to a sour taste in this Juice blend. The Juice blend that contained equal proportions of all three juices was the most acceptable to the consumers in terms of color, taste and Nutritional composition. It gave equal amounts of the unique properties of each fruit and provided a unique color and taste that was very appealing to the panelists. This product makes it possible to properly utilize these fruits, reduce post harvest losses, cater to different health needs of the consumers and ensure food security. It is recommended that further work should be done on antioxidant properties, other fruit blends and storage stability of the beverage to determine the shelf-life.

Influence of reaction time on silver nanoparticles-catalyzed oxidation of 3,3’,5,5’-tetramethylbenzidine (TMB) was evaluated via probing the oxidation process by recording the UV-Visible absorbance of the resulting colored products of TMB oxidation by hydrogen peroxide in the presence of silver nanoparticles as peroxides mimics. The time curve of the oxidation process was constructed, revealed that the concentration of the oxidation product was increased by increasing the reaction time and then levled off because the nanozyme active nodes were saturated after a certain reaction time and consequently the steady-state condition can be observed. The maximal activity of the silver nanozymes was achieved after a very short reaction time as short as 3.0 min and after this time, the color intensity of the oxidation products remained constant, revealing saturation of active nodes of nanoparticles with nanozyme-substrate.

. Various elements such as evolutions in IoT services resulting from sensoring by vehicle parts and advances in small communication technology devices have significantly impacted the mass spread of mobility services that are provided to users in need of limited resources. In particular, business models are progressing away from one-off cost towards longer term cost as represented by shared services utilizing kick-boards or bicycles and subscription services for vehicle software. Advances in shared mobility services as described are calling for solutions that can enhance reliability of data aggregate by users leveraging mobility services in the next-generation mobility areas. However, mining process to renew status, ensures continued network communication and block creation demands high performance in public block chain. This thesis proposes random certificate node selection mechanism in block network that creates blocks via node that has tokens issued for block creation and lets only specific nodes selected by encrypting token information acquires token.

This article explores the transformative role of neural networks in the realm of biology, particularly within microscopy image processing and illustrations. Neural networks have revolutionized cell segmentation and analysis, enabling precise delineation of cell boundaries and tracking of cellular behaviours. They excel in detecting subcellular structures, unravelling intricate organelle interactions. In 3D image reconstruction, neural networks navigate volumetric datasets, enhancing our understanding of spatial cellular architecture. These networks enhance disease diagnosis by identifying anomalies and irregularities, potentially revolutionizing early detection and classification. Moreover, neural networks restore and enhance microscopy images, unveiling hidden details. Lastly, they bridge art and science, fostering captivating biological art and enriching science communication. As neural networks evolve, they promise a future of limitless possibilities, weaving together technology, science, and art to illuminate the microscopic realm in unprecedented ways.

The notion of quantum-mechanics-free subsystem (QMFS) was introduced by Tsang and Caves in 2012. They showed that it is possible to design the dynamics of coupled quantum systems in such a way that one can construct a subsystem in which a given classical dynamics is realized, thus avoiding the measurement back-action of quantum mechanics. Although they mention that the Heisenberg picture equations of motion for QMFS was first proposed by Koopman in 1931 as a formulation of classical Hamiltonian dynamics in Hilbert space, in fact the connection between QMFS and Koopmann-von Neumann mechanics is deeper. Namely, quantum-mechanics-free subsystem is nothing but the realization of Sudarshan's perspective on the Koopman-von Neumann mechanics.

Solar concentration is the ability to harness solar radiation to increase the temperature of a receiver. The receiver is the component into which a heat transfer fluid can be flowed for an ORC system and produce electricity, or it can be used for high-temperature thermal storage, or even to implement thermochemical cycles. The choice of material is critical to ensure optimal performance and long-lasting operation. It is also essential that such material can operate at high temperatures and high thermal gradients. In short, material identification involves high thermal stresses that result in structural deformation. Different metal alloys were used to verify that the yield strength limit was not exceeded due to thermal stress induced by concentrated solar radiation. The problem was implemented in Matlab starting from the general heat equation. The purpose is to test whether thermal stress exceeds the yield strength, which is the condition in which elastic bonds in the material are changed, causing deformation. The best material identified was Inconel 740H, which had a high yield strength value and the lowest temperature difference. Under extreme working conditions, it can withstand thermally induced shocks.

Over the past decade, Knowledge bases (KB) have been increasingly utilized to complete and enrich the representation of queries and documents in order to improve the document retrieval task. Although many approaches have used KB for such purpose, understanding how effectively lev-erage entity-based representation still needs to be resolved. This paper proposes a Purely Enti-ty-based Semantic Search Approach for Information Retrieval (PESS4IR) as a novel solution. The approach includes (i) its own entity linking method, (ii) an inverted indexing method, and for document retrieval and ranking, (iii) an appropriate ranking method is designed to take advantage of all the strengths of the approach. We report the findings on the performance of our approach tested by queries annotated by two known entity linking tools, REL and DBpedia-Spotlight. The experiments are performed on the standard TREC 2004 Robust and MSMARCO collections. By using the REL method, for queries whose all terms are annotated and whose average annotation scores are greater than or equal to 0.75, our approach achieves the maximum nDCG@5 score (1.000). Thus, using our approach with any other document retrieval method would be an added value, unless that method achieves the maximum nDCG@5 score for those highly annotated queries.

The flavor, aroma and color of coffee may change due to mechanical damage, reducing its qual-ity. To measure the mechanical response of materials, compression tests can be performed, de-termining the effect of force application on the mechanical behavior of the fruit at different stages of ripeness. In this context, this study aimed to analyze the deformation, strain energy and equivalent von Mises stress of coffee fruits at mature, semi-mature and immature maturation stages and compressed by collapse forces. Compression in three directions (x, y and z) was sim-ulated on coffee fruit models using the finite element method, with a compression support in the direction opposite to the force application axis. The numerical simulation of the compression process allowed to verify that the more mature the fruit, the greater the associated mean defor-mation (2.20 mm mm-1, 0.78 mm mm-1 and 0.88 mm mm-1), the lower the mean strain energy (0.07 mJ, 0.21 mJ and 0. 34 mJ) and the lower the mean equivalent von Mises stress (0.25 MPa, 1.03 MPa and 1.25 MPa), corresponding to ripe, semi-ripe and immature fruits; and these proper-ties may be used to analyze how processes in the production chain affect the amount of mechan-ical damage.

Unlike animals, persistent dynamic environmental perturbations threaten plants, as they are sessile. Plants keep an inbuilt database of all epigenetic episodes during their lifetime. Present knowledge for exploiting information about how the gene network of plants contributes to epigenetic memory needs to be improved, and extensive in-depth studies are needed. Data from epigenetic memories imparts intelligent behaviour to plants, and these memories can be decoded further to investigate how these plants respond when the same abiotic stress recurs. The epigenetic phenomenon refers to gene expression patterns, including vital factors such as nucleic acids (small ribonucleic acids), histones modelling and methylation of DNA. These changes are cell cycle-associated events that may be transmitted to successive generations. Epigenetic memories due to abiotic stress are necessary for maintaining healthy ecophysiological behaviour of plants and impart the tendency to resist and adapt to challenging environmental conditions. These intelligent memories can be stored and interpreted to prepare for future challenges.

The term neuroinflammation defines the reactions of astrocytes and microglia to alterations in homeostasis in the diseased central nervous system (CNS), the exacerbation of which contributes to the neurodegenerative effects of Alzheimer's disease (AD). Local environmental conditions, such as the presence of proinflammatory molecules, mechanical properties of the extracellular matrix (ECM) and local cell-cell interactions, are determinants of glial cell phenotypes. In AD, the load of the cytotoxic/proinflammatory amyloid β peptide (Aβ) is a microenvironmental component increasingly growing in the CNS, imposing time-evolving challenges on resident cells. This study aimed at investigating the temporal and spatial variations of the effects produced by this process on astrocytes and microglia, either directly or by interfering in their interactions. Ex vivo confocal analyses of hippocampal sections from the mouse model TgCRND8 at different ages have shown that overproduction of Aβ peptide induced early and time persistent disassembly of functional astroglia syncytium and promoted a senile phenotype of reactive microglia, hindering Aβ clearance. In the late stages of disease, these patterns were altered in the presence of Aβ-plaques, surrounded by typically reactive astrocytes and microglia. Morphofunctional characterization of peri-plaque gliosis revealed a direct contribution of astrocytes in plaque buildup that might result in shielding Aβ-peptide cytotoxicity and, as a side effect, in exacerbating neuroinflammation.

Current routine diagnosis of a life-threatening central nervous system (CNS) infections is based on commercial multiplex real-time PCR (RT-PCR) and in-vitro culture investigations, targeting a limited number of pathogens, which requires implementation of a universal diagnosis at the point-of-care laboratory. This study aimed to document a case of non-routinely diagnosed meningoencephalitis in a twelve-year-old patient in Niger Republic. Metagenomic-based on real-time sequencing was applied directly on DNA/RNA extracted from 50 µL leftover CSF sample using Oxford Nanopore MinION, to detect all residual microorganisms non-routinely targeted by RT-PCR panel. In parallel, 1 ng DNA/RNA was used for paired-end Illumina library preparation to confirm the MinION results. Real-time analysis of MinION data detected 132 WU Polyomavirus specific reads after one-hour run. Blast nucleotide of the fasta sequences after assembly of both Illumina and Nanopore reads against NCBI GenBank database identified WU polyomavirus strain W33 (GenBank accession no: GU296367.1). Haemophilus influenzae specific reads (667 reads) were detected which explains the possible co-infection bacteria-DNA virus in this case. Blastn after total reads assembly identified H. influenzae strain PittGG (GenBank accession n° CP000672), belonging to the non-typable H. influenzae genotype by muti-locus-sequence-typing analysis. Furthermore, Achromobacter xylosoxidans (599 reads) were detected in this patient. Based on these findings, we classified this case as polymicrobial meningoencephalitis. Using RT-mNGS, the pathogen genome could be detected directly from a clinical sample, with no specific target. This technique seems to be an adapted method to diagnose non-routinely detectable pathogens, as well as their genotype and antimicrobial susceptibility in reduced time.

The present study aimed to evaluate the effect of the citric acid on the properties of solid pine wood, which were submitted to thermomechanical treatment. A preliminary test was performed in a previous study to evaluate the influence of different temperatures of pressing and concentrations of citric acid over the physical properties of wood. After choosing the best treatments (170°C and 5% and 10% of citric acid) it was evaluated the effect of these on the chemical properties (SEM, FTIR and pH), on the density profile using an X-ray microtomography, and on the resistance to ageing through abrasion test. The result of the chemical analysis allowed to observe an increase of the presence of ester functional groups, as well as a better coverage and higher acidity of the surface. The density profile technique allowed to observe the formation of peaks of density on the surface where the acid was applied. Lastly, it was also possible to verify an increase in the resistance to abrasion because of the application of the citric acid.

Pediatric brain tumors are the leading cause of cancer-related death in children. Diagnosis cur-rently relies on surgical biopsy to obtain tumor tissue for histological analysis. There is a great need for less invasive approaches to molecularly profile tumors and monitor therapeutic response. Liquid biopsy analysis of circulating tumor biomarkers in biofluids like cerebrospinal fluid (CSF) and blood offers a promising minimally invasive strategy. This review discusses recent advances in developing liquid biopsy assays using next-generation sequencing, digital PCR, and emerging techniques to detect circulating tumor DNA (ctDNA), cells (CTCs), and exosomes in pediatric brain tumors. The ability to use these circulating biomarkers for non-invasive diagnosis, thera-peutic targeting, tracking response to therapy, and understanding resistance mechanisms is ex-amined. Technical and clinical validation challenges to translate liquid biopsies into routine clin-ical practice are also discussed.

Bisphosphonates (BPs) are successfully used to cure a number of bone diseases characterized by metabolic osteopenia, such as Osteoporosis, or neoplastic osteolysis, such as Multiple Myeloma and Bone Metastases. These drugs exert their therapeutic effect inducing a systemic osteoclast depletion that, in turn, is responsible for a reduced bone resorption. Unfortunately, in addition to their beneficial activity, BPs can also determine a frightening side effect known as Osteonecrosis of the Jaw (ONJ). It is generally believed that the inability of osteoclasts to get rid of inflamed / necrotic bone tissue represents the main physio-pathological aspect of ONJ. In principle, a therapeutic strategy able to elicit a local re-activation of osteoclast production could counteract ONJ and promote the healing of its lesions. We have previously demonstrated that Magnesium (Mg) is a powerful inducer of osteoclast differentiation. Using a model of Vitamin D3 – dependent osteoclastogenesis, based on the U937 cell line, here we show that, surprisingly, this property of Mg is greatly enhanced by the presence of Zoledronic Acid (ZA), chosen for our study because it is the most effective among BPs. This finding allow us to hypothesize that Mg might play an important role in the topical therapy of ONJ.

Context: Despite the effort put into developing standards for structuring construction cost, and the strong interest into the field. Most construction companies still perform the process of data gathering and processing manually. That provokes inconsistencies, different criteria when classifying, misclassifications, and the process becomes very time-consuming, particularly on big projects. Additionally, the lack of standardization makes very difficult the cost estimation and comparison tasks. Objective: To create a method to extract and organize construction cost and quantity data into a consistent format and structure, to enable rapid and reliable digital comparison of the content. Method: The approach consists of a two-step method: Firstly, the system implements data mining to review the input document and determine how it is structured based on the position, format, sequence, and content of descriptive and quantitative data. Secondly, the extracted data is processed and classified with a combination of data science and experts’ knowledge to fit a common format. Results: A big variety of information coming from real historical projects has been successfully extracted and processed into a common format with 97.5% of accuracy, using a subset of 5770 assets located on 18 different files, building a solid base for analysis and comparison. Conclusion: A robust and accurate method was developed for extracting hierarchical project cost data to a common machine-readable format to enable rapid and reliable comparison and benchmarking.

This study investigates the nonlinearities in three-phase inverters for SiC-based systems and compares their performance to IGBT-based systems. An analytical model of inverter voltage distortion is developed, which accounts not only for dead time (td), switching delay time, switching frequency (fs), and voltage drops of power devices, but also for output parasitic capacitance (Cout). Experimental tests validate the model, which provides a more accurate estimate of the inverter’s output phase voltage distortion. The power device characteristics are obtained from datasheets, while Cout is determined through experimentation. Three-phase inverters with varying switching frequencies, fundamental frequencies, and dead-time values are used in simulations and experiments to determine the influence of nonlinearity on phase voltage deviation and current distortion. The results show that, due to SiC devices’ faster switching time, the phase voltage deviation and phase current distortion are lower in SiC-based inverters than in IGBT-based ones for high-frequency applications, as the dead time can be reduced.

We study the influence of high-order twisting phases on polarization states and optical angular momentum of a vector light field with locally linear polarization and a hybrid state of polarization (SoP). The initial SoP of a twisted vector optical field (TVOF) modulated by the high-order twisting phase possesses various symmetric distributions. The propagating properties of a high-order TVOF with locally linear polarization and hybrid SoP are explored, including the intensity compression, expansion, and conversion between the linear and circular polarization components. In particular, orbital angular momentum (OAM) appears in a high-order TVOF during propagation where no OAM exists in the initial field. The variation of OAM distribution in cross-section becomes more frequent with the increase of the twisting phase order. In addition, a non-symmetric OAM distribution appears in an anisotropic TVOF, leading to the rotation of the beam around the propagation axis during propagation. These results provide a new approach for optical field manipulation in a high-order TVOF.

Basil (Ocimum basilicum L.) is one of the important medicinal and aromatic plants. Light intensity is an indispensable factor for plants due to its effect on photosynthesis and physiological processes. Here, we investigated the impact of light intensities and harvesting times on the photosynthesis of green and purple basil. The experiment involved subjecting the plants to three different sunlight levels for 12 days: complete – 100%, 50%, and 30% sunlight. In addition, we scrutinize the harvesting time. The highest levels of photosynthetic and protective pigments were detected under full sunlight conditions in the purple basil harvested at noon. The highest levels of soluble and storage carbohydrates were recorded in the purple basil grown under full sunlight and harvested in the early morning. In contrast, their lowest levels were obtained in plants grown under 30% sunlight and harvested at noon time. Under all light treatments, the maximum quantum yield of photosystem II (FV/FM) was detected at 4 a.m. in both basil varieties; it decreased at noon and increased again at 5 p.m. Non-Photochemical Quenching (NPQ) got most elevated in the green variety under all light intensities at noon. However the highest NPQ was detected in the purple variety at 8 a.m. The NPQ was lowest in both basil varieties during the early morning and afternoon. Full sunlight at noon caused temporary photoinhibition and reduced car-bohydrates while enhancing pigment concentration and photo-protective mechanisms in basil plants.

(1) The study using the quails of the Manchurian golden breed was aimed at the efficacy of the food supplement based on micro-incapsulated phytase of Obessumbacterium proteus in the recombinant yeast producer Yarrowia lipolytica at a dose of 500 FYT/kg of the feed. (2) The effect of the supplement in the poultry diets on the productivity of young and adult quails was assayed; (3) It was found that the keeping the quails on the diets using the microencapsulated phytase O. proteus provided the highest live weight, the highest intensity of egg production, and the slaughter yield of animals, the lowest feed conversion compared to those in control groups and the groups getting a commercial phytase supplement based on Aspergillus ficuum. Taken together the data obtained in our experiments indicate a high degree of assimilation of phytate-containing products by the quails when using the encapsulated phytase compared to both the control and commercial preparation of phytase of the PhyA class. It can be concluded that it is a highly expedient and promising supplement based on the microencapsulated phytase of class D for feeding, which shows the best kinetic features compared to the phytases of PhyA and PhyC classes when working in the chyme of the poultry.

Introduction: congenital ureteral stenosis is one of the leading causes of impaired urinary drainage and subsequent dilatation of urinary collecting system, known as hydronephrosis or ureterohy-dronephrosis. Mechanism that leads to obstruction is not clearly known. Multiple studies in rat models have shown increased angiotensin 11 and TGFβ levels in obstructed ureteral tissue. The aim of the study is to investigate expression of fibrosis related genes in obstructive and normal ureteral tissue. Material and methods: it is a monocentric study in which nineteen patients were selected prospec-tively. 17 patients of which underwent Hynes-Anderson pyeloplasty due to the PUJO, 2 patients underwent ureteroneocystostomy due to ureterovesical junction obstruction (UVJO) and 6 patients were chosen for control group: 5 underwent nephrectomies due to the kidney tumor and 1- upper pole heminephrectomy due to the duplex kidney with normal pyeloureteric junctions in all. Tissue RNA was chemically extracted after freezing the biopsy samples in liquid nitrogen, with cDNA synthesis performed immediately after nucleic acid isolation. qPCR to evaluate the relative expres-sion of Tgfb1, Mmp1, Timp1, Pai1, Ctgf and Vegfa was performed. Expression levels of Gapdh and Gpi genes (geometric average) were used to calculate the relative expression of the investigated genes. Outliers were removed prior to calculating confidence intervals for the experimental groups, and Wilcoxon rank-sum test was performed to determine statistical significance of the differences. Results: significant differences between healthy and stenotic tissue samples in Ctgf gene expression levels were observed, with the samples from afflicted tissue showing lower expression. No statistical difference in expression levels of Tgfb1, Timp1, Vegfa, Mmp1, Pai1 was found. Discussion and conclusions: These findings suggest that tissue fibrosis similar to other tissues and organs is not the leading cause of stenosis, at least at the moment of surgery. Decreased CTGF ex-pression is indicative of developmental origin of obstruction.

This paper investigates the ion-acoustic wave structures in fluid ions for the Benjamin-Bona-Mahony-Peregrine-Burgers (BBMPB) equation. The various types of wave structures, are extracted including the three-wave hypothesis, breather wave, lump periodic, mixed-type wave, periodic cross-kink, cross-kink rational wave, M-shaped rational wave, M-shaped rational wave solution with one kink wave and M-shaped rational wave with two kink wave solutions. The Hirota bilinear transformation is a powerful tool that allows us to accurately solutions and predict the behavior of these wave structures. Through our analysis, we gain a better understanding of the complex dynamics of ion-acoustic waves and their potential applications in various fields. Moreover, our findings contribute to the ongoing research in plasma physics that utilize ion-acoustic wave phenomena. To show the physical behavior of the solutions, some 3D plots have been performed and their respective contour level, choosing different values of the parameters.

Building electric energy is characterized by a significant increase of its uses (e.g. vehicle charging), a rapidly declining cost of all related data collection and a proliferation of smart grid concepts, including diverse and flexible electricity pricing schemes. Not surprisingly, an increased number of approaches have been proposed for its modeling and forecasting. In this work, we place our emphasis on three forecasting related issues. First, on the forecasting explainability, i.e. the ability to understand and explain to the user what shapes the forecast. To this extent we rely on concepts and approaches that are inherently explainable, such as the evolutionary approach of genetic programming (GP) and its associated symbolic expressions, as well as the so-called SHAP (SHapley Additive eXplanations) values, which is a well established model agnostic approach for explainability, especially in terms of feature importance. Second, we investigate the impact of the training timeframe on the forecasting accuracy; this is driven by the realization that a fast training would allow for faster deployment of forecasting in real life solutions. And third, we explore the concept of counterfactual analysis on actionable features, i.e. features that the user can really act upon and which therefore present an inherent advantage when it comes to decision support. We have found that SHAP values can provide important insights into the model explainability. As for GP models, we have found comparable and in some cases superior accuracy when compared to its neural-network and time-series counterparts but a rather questionable potential to produce crisp and insightful symbolic expressions, allowing a better insight into the model performance. We have also found, and report here on an important potential especially for practical, decision support, solutions of counterfactuals built on actionable features and short training timeframes.

Individual investors often struggle to predict stock prices due to the limitations imposed by the computational capacities of personal laptop Graphics Processing Units (GPUs) when running intensive deep learning models. This study proposes solving these GPU constraints by integrating deep learning models with technical analysis methods. This integration significantly reduces analysis time and equips individual investors with the ability to identify stocks that may yield potential gains or losses in an efficient manner. Thus, a comprehensive buy and sell algorithm, compatible with average laptop GPU performance, is introduced in the study. This algorithm offers a lightweight analysis method that emphasizes factors identified by technical analysis methods, thereby providing a more accessible and efficient approach for individual investors. To evaluate the efficacy of this approach, we analyzed the performance of eight deep learning models: LSTM (4 layers), CNN, BiLSTM (4 layers), CNN Attention, BiGRU CNN BiLSTM Attention, BiLSTM Attention CNN, CNN BiLSTM Attention, and CNN Attention BiLSTM. These models were used to predict stock prices for Samsung Electronics and Celltrion Healthcare. The CNN Attention BiLSTM model displayed superior performance among these models, with the lowest validation mean absolute error value. In addition, an experiment was conducted using WandB Sweep to determine the optimal hyperparameters for four individual hybrid models. These optimal parameters were then implemented in each model to validate their back-testing rate of return. The CNN Attention BiLSTM hybrid model emerged as the highest-performing model, achieving an approximate rate of return of 5 percent. Overall, this study offers valuable insights into the performance of various deep learning and hybrid models in predicting stock prices. These findings can assist individual investors in selecting appropriate models that align with their investment strategies, thereby increasing their likelihood of success in the stock market.

This research focuses on monitoring the spatiotemporal changes of urban surface water in Dhaka City from 1990 to 2021, utilizing satellite imagery and the Google Earth Engine (GEE) platform. Surface water is essential for urban, environmental, and agricultural ecosystems, and its dynamics have significant implications for water resource planning and environmental management. The main objectives of this study are to assess the extent of urban surface water coverage over the last three decades and identify trends of water loss or gain in the study area. The study employs Landsat 5 TM and Landsat 8 OLI/TIRS imagery, integrating GEE with machine learning coding and WRI techniques to extract and analyze surface water data efficiently. Traditional remote sensing methods for dynamic monitoring are time-consuming and cumbersome, but GEE offers a user-friendly and accurate approach, providing easy access to satellite data and cloud-based processing. The results reveal a concerning trend in urban surface water coverage, indicating a significant reduction from 36.23 km² in 1990 to 5.83 km² in 2021, representing a loss of approximately 20 square kilometers or 45 percent of surface water over the last three decades. The decline is attributed to factors such as unplanned urban expansion, rapid real estate development, and increased industrial and economic activities in the study area. The developed algorithms utilizing GEE offer valuable insights into the maximum and minimum extent of surface water, enabling effective surface water planning and management. These findings contribute to sustainable water resource management and environmental preservation in Dhaka City.