Porous structured metallic implants are preferable as bone graft substitutes due to their faster tissue integration mediated by bone in-growth and vascularization. The porous scaffolds/ implants should also mimic the graded structure of natural bone to ensure a match of mechanical properties. This article presents a method to design graded porous structured acetabular implant and identifies the suitable parameters for manufacturing the model through additive manufacturing. The design method is based on slice-wise modification to ensure continuity of gradation. Modification of the slices was achieved through the binary image processing route. A geodesic dome type design was adopted for developing the acetabular cup model from the graded porous structure. The model had a solid shell with the target porosity and pore size gradually changing from 65% and 950 µm, respectively, in the inner side to 75% and 650 µm, respectively, towards the periphery. The required dimensions of the unit structures, and the combinations of pore structure and strut diameter to obtain the target porosity and pore size were determined analytically. Suitable process parameters were identified to manufacture the model by Direct Metal Laser Sintering (DMLS) using Ti6Al4V powder after carrying out a detailed experimental study to minimize the variation of surface roughness and warping over different build angles of the strut structures. A dual contour scanning was implemented to simplify the scan strategy. The minimum diameter of struts that could be manufactured using the selected scanning strategy and scanning parameters was found to be 375 µm. Finally, the model was built and from the micro-CT data, the porosities and pore sizes were found to be closely conforming to the designed values. The stiffness of the structures, as found from compression testing, was also found to be well matching with that of human trabecular bone. Further, the structure exhibited compliant bending-dominated behavior under compressive loading.

The inappropriate use of pesticides in the world and particularly in Africa, explains their presence in various environmental compartments. This presence in the environment has harmful consequences on living beings, especially humans. This review, based on scientific publications, aims to analyze the problem of pesticides in Africa. From a corpus of 81 articles published in Africa on this topic between 1996 and 2019, we have outlined the issues relating to phytosanitary practices, environmental pollution, food contamination, intoxication of farmers and consumers, qualitative and quantitative analysis methods used, as well as the regulations on the subject and their application in Africa. Based on an analysis of the factors that are at the root of the problems of environmental pollution, contamination and health that they cause in Africa, possible solutions were proposed to produce healthy products and preserve our common environmental heritage.

Attempts to use computers to aid in the detection of breast malignancies date back more than 20 years. Despite significant interest and investment, this has historically led to minimal or no significant improvement in performance and outcomes with traditional computer aided detection. However, recent advances in artificial intelligence and machine learning are now starting to deliver on the promise of improved performance. There are at present more than 20 FDA approved AI applications for breast imaging, but adoption and utilization are widely variable and overall low. Breast imaging is unique and has aspects that create both opportunities and challenges for AI development and implementation. Breast cancer screening programs worldwide rely on screening mammography to reduce the morbidity and mortality of breast cancer and many of the most exciting research and available AI applications focus on cancer detection for mammography. There are however multiple additional potential applications for AI in breast imaging including decision support, risk assessment, breast density quantitation, workflow and triage, quality evaluation, response to neoadjuvant chemotherapy assessment, and image enhancement. In this review the current status, availability, and future directions of investigation of these applications are discussed, as well as the opportunities and barriers to more widespread utilization.

Advanced Nano structural hard coatings are thin materials films that range in thickness from a few nanometers to a few micrometers and are applied to different surfaces to increase their hardness and wear resistance. Physical vapor deposition (PVD) or chemical vapor deposition (CVD) methods are frequently used to deposit these coatings. These coating’s distinctive characteristics result from their microstructure, which is made up of material columns or grains with a diameter of only a few nanometers. Increased hardness, higher wear resistance, and improved tribological properties result from these short dimensions. In applications with significant wear and/or high contact pressures, such as cutting tools, bearings, and engine parts, the usage of sophisticated Nano structural hard coatings is crucial. Advanced Nano structural hard coatings include, 1. Amorphous carbon coatings with high hardness, low friction, and exceptional wear resistance are known as diamond-like carbon (DLC) coatings. DLC coatings are frequently used in a variety of industries, including the automotive, aerospace, and biomedical ones. 2. Coatings made of titanium nitride (TiN): These metallic coatings have high hardness and wear resistance. Cutting tool, machining, and aerospace industries frequently use TiN coatings. 3. Chromium nitride (CrN) coatings: These coatings have great corrosion resistance, good wear resistance, and high hardness. Cutting tools, gears, and bearings are just a few of the objects that use CrN coatings. 4. Tungsten carbide (WC) coatings: These coatings, which have a high degree of hardness and wear resistance, are frequently employed in cutting tools and other applications that require wear resistance. Advanced Nano structural hard coatings provide many advantages over conventional coatings, including better hardness, increased wear resistance, and improved tribological qualities. The automotive, aerospace, and biomedical industries are just a few that could use these coatings. In this paper the author will explain about the design synthesis and applications of advanced Nano structural hard coating in aerospace and automotive applications.

The makeup of human microbiota has been linked to a number of autoimmune disorders. Recent developments in whole metagenome sequencing and 16S rRNA sequencing technology have considerably aided research into the microbiome and its relationship to disease. Due to the inherent high dimensionality and complexity of data generated by high-throughput platforms, conventional bioinformatics techniques could only provide an inadequate explanation for the most relevant changes and seldom provide correct predictions. Machine learning, on the other hand, is a subset of artificial intelligence applications that enable the untangling of high-dimensional systems and intricate knots in correlation by learning complex patterns and improving automatically from training data without being explicitly programmed. Machine learning is increasingly being utilized to research the influence of microbes on the onset of illness and other clinical features since computer power has increased dramatically in the last few decades. In this review paper, we focused on emerging methodological approaches of supervised machine learning algorithms for identification of autoimmune disorders utilizing metagenomics data, as well as the potential benefits and limitations of machine learning models in clinical applications.

The main goal of this article is the characterization of Herz-type Besov-Morrey spaces K˙p,qαN˙μ,rs and Triebel-Lizorkin-Morrey spaces K˙p,qαE˙μ,rs via ball means of differences, atomic, molecular and wavelet decompositions. There are provided necessary facts for implying these results, which can help to explore such spaces on different domains in further researches. Proposed spaces allow to extend the class of studying functions, containing Leray projection, heat semi-group and other operators, which can be helpful in exploring weak, strong and mild solutions of nonlinear partial differential equations.

The composite post insulator composed of a large diameter mandrel and flange pressed by one-time integral pultrusion has high strength and good toughness, widely used in the existing flexible converter valve. For constructing the finite element model of the crimped post insulator, most of the flange surface and the mandrel surface are directly connected, making the simulation model's stiffness deviate from the actual model and the model distortion. Based on this, this study proposes a new finite element simplified model of crimped composite post insulator based on Multi-Point Constraints (MPC), which accurately simulates the crimping area of man-drel and flange in engineering practice. It verifies the model's reliability through static tests and characteristic vibration tests. The results show that the difference between the finite element simulation and test results is within 5 %. The finite element modeling method based on MPC local constraints is very reliable in applying crimped composite post insulators. Based on the proposed model, the influence of flange height and thickness on the mechanical properties of composite post-insulators is further explored. The results show that the influence of flange height on mechanical properties can be ignored when the height of the insulator stiff-ener ( non-press common area ) is constant. Within the allowable thickness range of the flange crimping process, the increase in flange thickness will significantly reduce the maximum bend-ing stress of the insulator and increase its safety margin. It provides a good design idea for the design of crimping composite insulators.

Cytokines and chemokines (chemotactic cytokines) are soluble extracellular proteins that bind to specific receptors and play an integral role in the cell-to-cell signaling network, in addition can promote the homing of cancer cells into different organs. We investigated the potential relationship between human hepatic sinusoidal endothelial cells (HHSECs) and several melanoma cell lines for the expression of chemokine and cytokine ligand and receptor expression during invasion of melanoma cells. In order to define the invasion related gene expression differences, we selected invasive and non-invasive subpopulations of cells after co-culturing with HHSECs. In addition, we determined protein expression of the endothelial cells before and after co-culturing with melanoma cell lines originated from primary tumors. Cell lines with increased invasive capacity after culturing with conditioned medium showed a set of receptor genes (CXCR1, IL1RL1, IL1RN, IL3RA, IL8RA, IL11RA, IL15RA, IL17RC, and IL17RD) with significantly different expression. It is very important note, that the IL11RA gene expression level was also significantly increased in primary melanoma tissues with liver metastasis as well. Proteome arrays revealed 15 differentially expressed proteins (including CD31, VCAM-1, ANGPT2, CXCL8, and CCL20) in the hepatic endothelial cells after co-cultured with melanoma cells. Our findings clearly indicate the interaction between liver endothelial- and melanoma cells. Based on our data, we assume that overexpression of the IL11RA gene might has key role in the formation of organ specific metastasis to the liver by primary melanoma cells.

In recent years, the discharge of various emerging pollutants, chemicals and dyes in water and wastewater has represented one of the prominent human problems. Since water pollution is directly related to human health, highly resistant and emerging compounds in aquatic environments will pose many potential risks to the health of all living. Therefore, water pollution is a very acute problem that has constantly increased in recent years with the expansion of various industries. Consequently, choosing efficient and innovative wastewater treatment methods to remove contaminants is crucial. Among advanced oxidation processes, electrochemical oxidation (EO) is the most common and effective method for removing persistent pollutants from municipal and industrial wastewater. However, there are still many gaps despite the great progress in using EO to treat real wastewater. This is due to the lack of comprehensive information on the operating parameters which affect the process and its operating costs. In this paper, among various scientific articles, the impact of operational parameters on the EO performances, a comparison between different electrochemical reactor configurations, and a report on general mechanisms of electrochemical oxidation of organic pollutants have been reported. Moreover, an evaluation of cost analysis and energy consumption requirements have also been discussed. Finally, the combination process between EO and another important advanced oxidation technology, PEC, called photoelectrocatalysis (PEC), has shortly been discussed and reviewed. This article showed that there is a direct relationship between important operating parameters with the amount of costs and the final removal efficiency of emerging pollutants. Optimal operating conditions can be achieved by paying special attention to reactor design, which can lead to higher efficiency and more efficient treatment. The rapid development of EO for removing emerging pollutants from impacted water and its combination with other green methods can result in more efficient approaches to face the pressing water pollution challenge.

Crop genetic diversity is most for the long-term sustainable production system. The breeding and production strategies of developing and growing uniform and homogenous varieties have created many different problems. Such populations are static and very sensitive to unpredictable stresses. In Nepal, more than 80% of seed system is informal s which has contributed greatly to creating and maintaining genetic diversity within the field particularly contributing to landrace diversity. This paper aims to assess and present the approaches and advantages of increased crop genetic diversity in the fields. The paper is developed based on experiences of implementing on-farm conservation activities carried out in Nepal since last two decades. Some of the evidences have been derived from on-going evolutionary plant breeding project being implemented in Nepal. The information is supplemented with field assessment, focus group discussion, and literature review. The major approaches to increase crop genetic diversity are evolutionary plant breeding, cultivar mixture, landrace enhancement, informal seed system, bulk method, diversifying the sources, participatory plant breeding, open pollination, etc. EPB and cultivar mixture are very simple and effective approaches to increase crop genetic diversity at field level. The involvement of farmers in these approaches helps to accelerate the population improvement particularly for landraces. The major advantages of increased crop genetic diversity are: seed maintenance by farmers themselves, minimal risk of crop failure, resilience to unpredictable stresses, increased amount of diversified nutrition, production increment each year, ease to produce organically, etc. However, there are some issues and problems associated with mixtures and diverse varieties, for example, not being able to harvest by machine, mature at a different date, difficulty in maintaining seeds and registration, etc. Crop genetic diversity should be considered for a climate-resilient and self-dependent production system. The higher the genetic diversity in farming land, the more chance of getting the multiple benefits in the agriculture system (Vernooy 2022).

It was recently shown that urban networks might exhibit two different critical points, one for the percolation of congested links through the network, and another one for the flow of vehicles through the network. It was observed that the percolation critical point happens after the flow critical point, where network throughput is maximized. This result is important because if a causal relationship exists between these two processes, it can be leveraged for improving control methods to avoid network collapse. This paper presents the results of numerical experiments to understand the possible causal relationship between the percolation and flow processes by focusing on the relative timing between the two critical points. The goal is to understand the impacts of important factors such as: (i) urban network type: long- and short-block networks, (ii) signal timing control type: fixed, random, responsive, and (iii) route choice: turning proportions at intersections. We find that the threshold density $k^*_c$ to determine if a link is congested has the main impact on the timing of the percolation transition, where lower values trigger earlier transitions. This implies that $k^*_c$ can be set such that the percolation transition happens before the flow critical point, opening the door for improved congestion management strategies. If $k^*_c$ is set to the average network critical density, maximum network throughput happen simultaneously with the percolation transition. Surprisingly, it appears that these results, and more generally, the relationship between the percolation and flow processes is independent of (i) and (ii) above.

Sunn pest is one of the most crucial noxious species in agriculture. As the sunn pest penetrates and makes damage to the grains, they can no longer be utilized to make bakery goods like bread, pasta, and other baked foods since they become unusable. Therefore, analysis and detection of damaged wheat grains are necessary for production to continue. We recommend that the dataset could be used for analysis and segmentation of the wheat grains, detection of the sunn pest damage condition, and classification of the 6 species of which the dataset consists. As mentioned, in our dataset, there are 6 different species of wheat, including Bezostaja, Müfitbey, Nacibey, Sönmez-2001, Tosunbey, and Ekiz, which are the species that were made in Türkiye. Our dataset differs from the others due to its various species and the condition, whether it is healthy or sunn pest damaged or broken wheat grain, and because the dataset is a multiclass one, it can be used for the classification of the varieties. On the other hand, when the sunn pest damage condition is taken into account, the dataset is suitable for the detection of the sunn pest damage. In addition to that, the dataset includes grains that touch each other which makes it more applicable to problems that arise in real-life. The dataset consists of 83 sunn pest damaged and 87 healthy wheat images. In addition, there are 170 images that contain 3565 wheat grains. As can be observed, the dataset contains a variety of wheat species with sunn pest affected which displays that the promised dataset is suitable for numerous machine learning problems such as classification, segmentation, and detection.

Due to the content of biologically active substances, sea buckthorn (Hippophae rhamnoides L.) is of growing interest to scientists, the food industry, pharmaceuticals, cosmetology and consumers. The aim of this study is to investigate the correlation between the chemical composition (Carotenoid content (CC), Ascorbic acid content (AAC), Total dry matters (TDM), Titratable acidity (TA), pH, Organic acids (OA)) and the Antibacterial effect (AA) (Diameter of the inhibition zone in mm of Bacillus pumilus) of four species of sea buckthorn (Clara, Dora, Cora, Mara), cultivated in the Republic of Moldova. The sea buckthorn species tested was found to have a different Carotenoid content (1.79±0.43 … 48.92±0.61 mg/100g), Ascorbic acid content (74.36±0.60 … 373.38±2.29 mg/100g), Organic acids (malic acid 5.8±0.02 ... 13.4±0.01 mg/100g, citric acid 0.08±0.00 ... 0.32±0.01 mg/100g, succinic acid 0.03±0.00 ... 1.1±0.00 mg/100g), Total dry matters (16.71±0.05 … 24.54±0.09 %), Total acidity (2.15±0.05 ... 8.76±0.00 %), and pH value (2.73±0.02 ... 3.00±0.07). The microbial activity of sea buckthorn, evaluated by the diameter of the inhibition zone, constituted for Bacillus pumilus (3.70…15.91mm/g-1 for whole sea buckthorn fruits and respectively 13.33…26.67 mm/g-1 for sea buckthorn puree).

Background and aim: Human Papillomavirus (HPV) is sexually transmitted, one of the three most common sexually transmitted infections (STIs) in both males and females, and the most common viral STI. A crucial public health strategy to protect people against HPV is through vaccination, which has shown its effectiveness in preventing HPV related diseases. Presently three types of vaccines are available (bivalent, quadrivalent, and nonavalent) and they all target at least the two most oncogenic virus genotypes (HPV 16, 18). In the past few years, the need to implement vaccination programmes that include all genders has been discussed in order to achieve herd immunity against HPV. To date, only a few countries have included young males in their vaccination programmes, so we aim through this review to provide an overview of the epidemiology of HPV and prevention strategies to prevent it, reporting the latest findings from the scientific literature.

Vehicle safety promises to be one of the Advanced Driver Assistance System (ADAS) biggest benefits. Higher levels of automation remove the human driver from the chain of events that can lead to a crash. Sensors play an influential role in vehicle driving as well as in ADAS by helping the driver to watch the vehicle’s surroundings for safe driving. Thus, the driving load is drastically reduced from steering as well as accelerating and braking for long-term driving. The baseline for the development of future intelligent vehicles relies even more on the fusion of data from surrounding sensors such as Camera, Lidar and Radar. These sensors not only need to perceive in clear weather but also need to detect accurately adverse weather and illumination conditions. Otherwise, a small error could have an incalculable impact on ADAS. As most of the current study is based on indoor or static testing. In order to solve this problem, this paper designs a series of dynamic test cases with the help of outdoor rain and intelligent lightning simulation facilities to make the sensor application scenarios more realistic. As a result, the effect of rainfall and illumination on sensor perception performance is investigated. As speculated, the performance of all automotive sensors is degraded by adverse environmental factors, but their behaviour is not identical. Future work on sensor model development and sensor information fusion should therefore take this into account.

Phytoplasma diseases pose a substantial threat to diverse crops of agricultural importance. Management measures are usually implemented only after the disease has already occurred. Early detection of such phytopathogens, prior to disease outbreak, has rarely been attempted but would be highly beneficial for phytosanitary risk assessment, disease prevention and mitigation. In this study we present the implementation of a recently proposed proactive disease management protocol (DAMA: Document, Assess, Monitor, Act) for a group of vector-borne phytopathogens. We used insect samples collected during a recent biomonitoring program in southern Germany to screen for the presence of phytoplasmas. Insects were collected with Malaise traps in different agricultural settings. DNA was extracted from these mass trap samples and subjected to PCR-based phytoplasma detection and COI sequence metabarcoding. In about 1% of the analyzed samples, phytoplasma DNA was detected. Phytoplasma group identification was performed by 16S rRNA gene sequence analysis and the detected phytoplasmas could be assigned to the 16SrI subgroups B and L. Insect species in the sample were identified by DNA metabarcoding. By using established databases, checklists, and archives, we documented historical associations and records of phytoplasmas and its hosts in the study region. For the assessment in the DAMA protocol, phylogenetic triage was performed in order to determine the risk for tri-trophic interactions (plant-insect-phytoplasma) and associated disease outbreaks in the study region. A phylogenetic heat map constitutes the basis for risk assessment and was used here to identify a minimum number of seven leafhopper species suggested to be monitored by stakeholders in this region. A proactive stance in monitoring changing patterns of association between hosts and pathogens can be a cornerstone in capabilities to prevent future phytoplasma disease outbreaks. To our knowledge, this is the first time that the DAMA protocol has been applied in the field of phytopathology and vector-borne plant diseases.

Multimodal user interfaces hold the promise to enable natural and intuitive means of human-machine interaction. But is the effort of using many sensors rewarded by the users - or is a single modality sufficient? For an industrial use case of a weld seam inspection workstation we study three independent interfaces (augmented spatial button interaction on (1) a workpiece or (2) a worktable and through (3) speech commands) and their combination (4). While users preferred the interaction on the augmented worktable when comparing single modalities, they used all three in multimodal user interface. From the isolated test of an input modality it is not possible to infer its use in a complex system. Therefore, the effort implementing and using multiple input modalities is reasonable.

Staphylococcus aureus (S. aureus), particularly Methicillin-resistant S. aureus (MRSA), is a life-threatening pathogen that causes a variety of infections in hospital and community settings. It poses a significant risk and challenge for global health that hinders our ability to control and treat bacterial infections. Recently, the emergence and spread of variant strains of bacteria, misuse of the limited available options of effective antibiotics, spread of fake drugs, and climate change that increased the contact between humans and animals’ populations carrying different bacterial has significantly increased the incidence of Multi-Drug Resistance strains (MDR). This in turn, has created a severe problem in the infection control treatment of S. aureus infected patients. Treatment options for MRSA infection are increasingly limited and complicated. Unfortunately, different strains of MRSA are showing tolerance and resistance toward vancomycin, which is the standard of care for complicated MRSA. Therefore, it is crucial now to invest developing new effective anti-biotics and synergies, develop and implement national action plans for the management of an-tibiotic resistance, as well as improving our understanding of the antimicrobial resistance mechanisms. Here, in this review we explain the main mechanisms of antibiotic resistance in MRSA and describes different approaches to manipulate it in MRSA, providing a basis for de-signing effective drugs, and shedding some light on the evolution of S. aureus.

In order to properly cover different scenarios, radiation patterns of antennas should be accordingly adjusted before fabrication. However, most antennas are unable to provide both broadside beam and designable conical beam which are usually-used radiation patterns for radio coverage. In this paper, a planar Circular Polarized (CP) annular Leaky-Wave Antenna (LWA) with conical beam is proposed, which is realized on annular Substrate-Integrated Waveguide (SIW). Broadside beam or conical beam could be easily obtained by fabricating the LWA with modified structural parameters. The central operating band is 5.8 GHz. The LWA allows only the -1th spatial harmonic to radiate, while the fundamental wave and other spatial harmonics are suppressed in slow wave mode. In order to validate the design effectiveness, two examples for broadside beam and conical beam radiation are fabricated and measured. The measurement results show good agreement with the simulation results. The proposed LWA presents a promising radiation performance and is a good candidate for wireless communication applications.

Background. To prospectively evaluate the reliability of a portable optical scanner compared to the water displacement technique for volumetric measurements of the foot and ankle, and to compare the acquisition time associated with these two methods. Methods. Foot volume was measured in 29 healthy volunteers (58 feet, 24 female/5 male) by a 3D scanner (UPOD-S 3D Laser Full-Foot Scanner ®) and by water-displacement volumetry. Measurements were performed on both feet, up to a height of 10 cm above the ground. The acquisition time for each method was evaluated. Kolmogorov-Smirnov test, Lin's Concordance Correlation Coefficient, and a Student’s t-test were performed. Results: Mean foot volume was 869.7+/-165.1cm3 (3D scanner) versus 867.9+/-155.4cm3 (water-displacement volumetry) (p <10-5). Concordance of measurements was 0.93, indicative of a high correlation between the two techniques. Volumes were 47.8 cm3 lower when using the 3D scanner versus water volumetry. After statistically correcting this underestimation, the concordance was improved (0.98, residual bias = -0.03 +/- 35.1 cm3). Mean examination time was 4.2 +/-1.7 min (3D optical scanner) versus 11.1 +/-2.9 min (water volumeter) (p<10-4). Conclusion: Ankle/foot volumetric measurements performed using this portable 3D scanner are reliable and fast, and can be used in clinical practice and research.

Regional heterogeneity of microglia was first described a century ago by Pio del Rio Hortega. Currently, new hints on microglia heterogeneity across central nervous system (CNS) regions are still being unraveled by high-throughput techniques. It remains unclear whether these spatial specificities translate into different microglial behaviors in vitro. We cultured microglia isolated from the cortex and spinal cord and analyzed the effect of the CNS spatial source on in vitro behavior by applying the same experimental protocol and culture conditions. We analyzed microglial cell numbers, function, and morphology and found a distinctive in vitro phenotype. We found that microglia were present in higher numbers in spinal cord-derived glial cultures, presenting different expression of inflammatory genes and a lower phagocytosis rate under basal conditions or after activation with LPS and IFN-. Morphologically, cortical microglial cells are more complex and present longer ramifications, which were also observed in vivo in CX3CR1+/GFP transgenic reporter mice. Collectively, our data demonstrated that microglial behavior in vitro is defined according to specific spatial characteristics acquired in the tissue. Thus, our study highlights the importance of microglia as a source of CNS for in vitro studies.

Corneal opacity is a leading cause of vision impairment and suffering worldwide. Transplantation can effectively restore vision and reduce chronic discomfort. However, there is a considerable shortage of viable corneal graft tissues. Tissue engineering may address this issue by advancing xeno- keratoplasty as a viable alternative to conventional keratoplasty. In particular, livestock decellularization strategies offer the potential to generate bioartificial ocular prosthetics in sufficient supply to match existing and projected needs. To this end, we have examined the best practices and characterizations that have supported the current state-of-the-art driving preclinical and clinical applications. Identifying the challenges that delimit activities to supplement the donor corneal pool derived from acellular scaffolds allowed us to hypothesize a model for keratoprosthesis applications derived from livestock combining 3D printing and decellularization.

Geological structures such as joints and faults in rock mass have significant influence on open pit mining. Hence, it is critical to develop a understanding of dynamic joint behaviour under blasting loading. This in turn can provide both theoretical and practical guidance to improve blasting rock fragmentation and associated bucket excavating efficiency. In this paper, delayed blasting on the highwall bench at Baiyunebo open-pit mine was used as an example, a nonlinear joint blasting model was also constructed. By simplifying the blasting wave propagation velocity, the P-wave normal incidence to the joint was obtained. The peak vibration velocity was 0.33m/s at 3.0s. The S-wave reflected by the joint interface was first reflected backward and then forward, which the peak vibration velocity was 0.027 m/s. By combining the relevant stress and displacement theories of type I and II cracks, the equipotential diagrams of the stress and displacement field with the vibration velocity of the particle were obtained. σx was positive in the direction of 0~330° and subjected to tensile stress, whereas σy was positive in the direction of 0~180° and under tensile stress. The longitudinal σy along joint was low in compressive stress distribution area and did not affect surrounding rock at the time. The stress concentration appeared in the lower right corner. Based on the continuous behavior of stress wave in joints, the asymmetry and continuous changes reflected in the whole process could not be analysed by the contour diagram. Hence, ANSYS used to analyse distribution of the stress field. The intensity of the shock wave after detonation was greater than that of the rock strength. Subsequently, the sub-layer shock wave supplemented the shock wave energy that was not enough to break the rock and induced further cracking. This was able to be visualized by the degree of color change post-processing. It was concluded that with the attenuation of the detonation wave energy, the stress exhibited a decreasing trend in this process. According to distribution of the peak effective stress, it was found that the peak value first increased to 10-12 MPa and then showed a downward trend. Overall, the results were validated against the finite element simulation and mathematical analysis.

While modeling data in reality, uncertainties in both data (aleatoric) and model (epistemic) are not necessarily Gaussian. The uncertainties could appear with multimodality or any other particular forms which need to be captured. Gaussian mixture models (GMMs) are powerful tools that allow us to capture those features from a unknown density with a peculiar shape. Inspired by Fourier expansion, we propose a GMM model structure to decompose arbitrary unknown densities and prove the property of convergence. A simple learning method is introduced to learn GMMs through sampled datasets. We applied GMMs as well as our learning method to two classic neural network applications. The first one is learning encoder output of autoencoder as GMMs for handwritten digits images generation. The another one is learning gram matrices as GMMs for style-transfer algorithm. Comparing with the classic Expectation maximization (EM) algorithm, our method does not involve complex formulations and is capable of achieving applicable accuracy.

Experimental systems to simulate future elevated CO2 conditions in the field often have large, rapid fluctuations in CO2. To examine possible impacts of such fluctuations on photosynthesis, intact leaves of field grown plants of five species were exposed to two-minute cycles of CO2 between 400 and 800 mol mol-1 lasting a total of 10 minutes, with photosynthesis, stomatal conductance and PSII fluorescence measured at the end of each half-cycle, and also 10 minutes after the end of the cycling. Prior to the cyclic CO2 treatments, steady-state responses of leaf gas exchange and fluorescence to CO2 were determined. In four of the five species, in which stomatal conductance decreased with increasing CO2, the cyclic CO2 treatments reduced stomatal conductance. In those species, both photosynthesis and the photochemical efficiency of PSII were reduced at limiting internal CO2 levels, but not at saturating CO2. In the fifth species, there was no change in stomatal conductance with CO2, and no change in either photosynthesis or PSII efficiency at any CO2 level with CO2 cycling. It is concluded that in many, but not all, species fluctuations in CO2 may reduce photosynthesis at low CO2 partly by decreasing the photochemical efficiency of photosystem II, as well as by decreasing stomatal conductance.

Background. The main impetus behind the worldwide Covid-19 vaccination campaign in 2021 was to reduce the mortality attributed to SARS-CoV-2 infection in the preceding year. Nevertheless, rigorous analyses of the mortality benefits conferred by this massive vaccination effort have been lacking. Methods Statistics offers us an essential methodological approach for measuring the impacts of Covid-19 vaccination on public health. The mathematical relation between vaccinated-alive groups can be repeated between vaccinated-dead groups with relatively high statistical reliability because of the large population numbers involved. This method also confers greater statistical usefulness because it eliminates the Simpson effect. Results Calculations were performed for each of the following five(5) four-week intervals: weeks 35-38 (2021), weeks 39-42 (2021), weeks 43-46 (2021), weeks 47-50 (2021), and weeks 50(2021)-1(2022). The results obtained confirm that the mortality of the vaccinated coronavirus-infected groups was 14.5% higher on average than the mortality of non-vaccinated coronavirus-infected groups. Conclusions Vaccinated infected groups appear to have higher average mortality than their non-vaccinated infected counterparts. The findings suggest the legitimacy of extending the statistics between vaccinated living and vaccinated dead individuals for different age groups. Calculating the impact of Covid-19 vaccination on the mortality rate is a necessary step towards satisfying the first principle of medicine: “Primum non nocere”, “Do no harm”.

This work investigates how to balance the electricity supply and demand in a carbon-neutral northern Europe. Applying a cost-minimizing electricity system model including options to invest in eleven different flexibility measures, cost-efficient combinations of strategies to manage varia-tions are identified. The results of the model are post-processed using a novel method to map the net load before and after flexibility measures are applied to reveal the contribution of each flexi-bility measure. The net load is mapped in the space spanned by the amplitude, duration, and number of occur-rences. The mapping shows that, depending on cost structure, flexibility measures contribute to reduce the net load in three different ways; 1) by reducing variations of long duration but low amplitude, 2) by reducing variations of high amplitude but short duration and low occurrence or 3) by reducing variations of high amplitude, short duration and high occurrence. It is found that cost-efficient variation management is achieved by combining wind and solar power and by combining strategies (1-3) to manage variations. The cost-efficient combination of strategies de-pends on electricity system context where electricity trade, flexible hydrogen and heat production (1) manage the majority of variations in regions with good conditions for wind power while sta-tionary batteries (3) are the main contributors in regions with good conditions for solar power.

Intracortical microelectrodes that can be implanted have the ability to capture fast-changing neuron action potentials in the living brain. Despite this potential, many obstacles must still be overcome for reliable, long-term, high-quality recordings and accurate analysis of brain activity. These challenges include improving recording quality, enhancing recording stability, increasing recording capacity, and adding multi-functional features. One potential approach to enhance implantable microelectrodes involves the advancement of materials, refinement of implantation methodologies, and augmentation of the number of sites for recording. However, these challenges are still being actively researched, and advancements in microelectrode technology are underway. The difficulties with implantable microelectrodes are evaluated, and solutions are presented from different perspectives. The latest advancements in microelectrode technology are reviewed and condensed, and future possibilities are explored.

The metabolic syndrome, first introduced by Hermann Haller in 1975, was sometimes also known as insulin resistance syndrome, syndrome X, and plurimetabolic syndrome. In 1989 it was rechristened by Kaplan as "Deadly Quartet" based on a consolidation of central obesity, impaired glucose tolerance, dyslipidemia, and systemic hypertension. Metabolic syndrome is positively associated with a pro-inflammatory and pro-thrombotic state, attributed to increased pro-thrombotic and inflammatory markers activity. Moreover, Metabolic syndrome is frequently associated with increased atherosclerotic cardiovascular disease, impaired glucose tolerance, hyperuricemia, obstructive sleep apnea, and chronic kidney disease. Despite concerted endeavors worldwide, the complexity of the pathophysiology of metabolic syndrome is still not clearly understood. Currently, therapeutic possibilities are confined to individual therapy of hyperglycemia, hypertension, hypertriglyceridemia, hyperuricemia, regular physical exercise, and a restricted diet.

The development of antimicrobial resistance to conventional antibiotics is a major global health challenge. Infections caused by multidrug-resistant gram-negative bacteria have been named one of the most urgent global health threats. Considerable efforts are devoted to developing new antibiotic drugs and investigating the mechanism of antibiotic resistance. Recently, Anti-Microbial Peptides (AMPs) have emerged as a new platform for the target and design of novel drug resistant anti-microbial agents promising a new therapeutic strategy. AMPs are rapid, potent, possess an unusually broad spectrum of activity, and have shown efficacy as topical agents. Unlike traditional therapeutics that interfere with essential bacterial enzymes, AMPs interact with microbial membranes through electrostatic interactions and physically damage cell integrity. However, naturally occurring AMPs have limited selectivity and modest efficacy. Therefore, recent efforts have focused on the development of synthetic AMP analogs as suitable drug targets. This work explores the development of novel antimicrobial agents which mimic the structure of graft-copolymers and mirror the mode of action of an AMP. Chitosan-graft-polypeptide side chains are synthesized by the ring-opening polymerization of N-carboxyanhydrides of L-lysine and L-leucine initiated from the functional groups of chitosan. The derivatives with random- and block-copolymer side chains are explored as drug targets. These graft copolymer systems exhibit activity against clinically significant pathogens and disrupt biofilm formation. This work highlights the potential of chitosan-graft-polypeptide structures in biomedical applications.

Cream cheese presents a favorable environment for the growth of pathogenic and spoilage microorganisms. The antimicrobial and antioxidant effects of plant extracts are well known, but their use is limited because they affect the physicochemical and sensory characteristics of products. Encapsulation presents an option to limit or prevent these changes. The paper presents the composition of individual polyphenols (HPLC–DAD-ESI-MS) from basil extracts (BE) with significant antioxidant activity (644.75±21.37 mM Trolox/g DW) and inhibitory effect against strains of Staphylococcus aureus, Geobacillus stearothermophilus, Bacillus cereus, Candida albicans, Enterococcus faecalis, Escherichia coli, and Salmonella Abony. The basil extract was encapsulated in sodium alginate (Alg) using the drop technique. The encapsulation efficiency of microencapsulated basil extract (MBE) was 78.59±0.01%. SEM and FTIR analyzes demonstrated the existence of weak physical interactions between the components. In the optimal concentration range of 0.6-0.9% MBE determined the inhibition of the post-fermentation process and the improvement of the degree of water retention. This led to the improvement of the textural parameters of the cream cheese, contributing to the extension of the shelf life of the product by 7 days. The influence of storage period and MBE concentration on texture parameters, pH and sensory analysis (overall acceptability) were evaluated by mutual information analysis.

Effective household and individual disaster preparedness can minimize physical harm and property damage during catastrophic events. To assess the risk and vulnerability of affected areas, it is crucial for relief agencies to understand the level of public preparedness. Traditionally, government agencies have employed nationwide random telephone surveys to gauge the public’s attitudes and actions towards disaster preparedness. However, these surveys may lack generalizability in certain affected locations due to low response rates or areas not covered by the survey. To address this issue and enhance the comprehensiveness of disaster preparedness assessments, we develop a framework that seamlessly integrates machine learning and simulation. Our approach leverages machine learning algorithms to establish relationships between public attitudes towards disaster preparedness and demographic characteristics. Using Monte Carlo simulation, we generate datasets that incorporate demographic information of the affected location based on government-provided demographic distribution data. The generated dataset is then input into the machine learning model to predict the disaster preparedness attitudes of the affected population. We demonstrate the effectiveness of our framework by applying it to Miami-Dade County, where it accurately predicts the level of disaster preparedness. With this innovative approach, relief agencies can have a clearer and more comprehensive understanding of public disaster preparedness.

The aim of Predictive Maintenance, within the field of Prognostics and Health Management (PHM), is to identify and anticipate potential issues in the equipment before these become critical. The main challenge to be addressed is to assess the amount of time a piece of equipment will function effectively before it fails, which is known as Remaining Useful Life (RUL). Deep Learning (DL) models, such as Deep Convolutional Neural Networks (DCNN) and Long Short-Term Memory (LSTM) networks, have been widely adopted to address the task, with great success. However, it is well known that this kind of black box models are opaque decision systems, and it may be hard to explain its outputs to stakeholders (experts in the industrial equipment). Due to the large number of parameters that determine the behavior of these complex models, understanding the reasoning behind the predictions is challenging. This work presents a critical and comparative revision on a number of XAI methods applied on time series regression model for PM. The aim is to explore XAI methods within time series regression, which have been less studied than those for time series classification. The model used during the experimentation is a DCNN trained to predict the RUL of an aircraft engine. The methods are reviewed and compared using a set of metrics that quantifies a number of desirable properties that any XAI method should fulfill. The results show that GRAD-CAM is the most robust method, and that the best layer is not the bottom one, as is commonly seen within the context of Image Processing.

The emergence of various electronic devices and equipment such as electric vehicles and drones requires higher energy density energy storage devices. Lithium-sulfur batteries (LSBs) are considered as the most promising new generation energy storage system owing to high theoretical specific capacity and energy density. However, the severe shuttle behaviors of soluble lithium polysulfides (LiPSs) and the slow redox kinetics lead to low sulfur utilization and poor cycling stability, which seriously hinder the commercial application of LSBs. Therefore, various catalytic materials have been employed to solve these troublesome problems. High entropy materials (HEMs), as advanced materials, can provide unique surface and electronic structures that expose plentiful catalytic active sites, which opens new ideas for the regulation of LiPSs redox kinetics. Notwithstanding many instructive reviews in the land of LSBs, while this review aims to offer a complete and shrewd summary of the current progresses in HEMs-based LSBs, including in-depth interpretation of design principles and mechanistic electrocatalysis functions as well as pragmatic perspectives.

Introduction: Parents’ behavior and practices affect many aspects of family life, including health, and many studies have proven that children's bad habits are associated with parents’ behavior and practices. Objectives: This study aimed to identify parents’ negative behaviors that might affect their families’ health and social development. Methodology: A descriptive cross-sectional study was conducted to examine the influence of parents’ behavior and practices on their family health, in which 192 respondents participated. Results: The results clarified the influence of parents on family health in several aspects. On the behavioral side, approximately 90% of the participants agreed that the behavior of parents may affect the behavior of their families, and the social and educational side results clarified the relationship between parents' illiteracy and support for the cognitive and social health of the family. Discussion: This study clarified that there is a significant relationship between illiterate parents and their ability to support their families, illustrating that the majority of participants thought that the development of the cognitive and social health of families depends on the presence of supportive parents, which has many implications for family social and psychological health. Conclusion: Parental behaviors and practices have a strong effect on their family’s health, which affects the development of the families’ cognitive and social health. Recommendation: The study recommends the need for supportive, friendly hospitals for family social health and the provision of specialized programs that support the family’s social and psychological health.

Malaria is a critical fevered illness caused by Plasmodium parasites transmitted among people through the bites of infected female Anopheles mosquitoes. Public awareness about the disease is important for the control of disease. This article proposes a mathematical model to study the dynamics of malaria disease transmission with the influence of awareness-based control interventions. We found two equilibria of the model, namely the disease-free and endemic equilibrium. Disease-free equilibrium is stable globally if basic reproduction number (R0) is less than unity (R0&lt;1). Some basic mathematical properties of the proposed model, such as nonnegativity and boundedness of solutions, the feasibility of the equilibrium points and their stability properties, have been studied. Finally, we adopted optimal control to minimize the cost of disease control and solve the problem by formulating Hamiltonian functional. The optimal use of insecticides for controlling the mosquito population is determined. Numerical simulations have been provided for the confirmation of the analytical results. We conclude that media awareness with optimal control approach is best for cost-effective malaria disease management.

Self-employed individuals comprise around 15% of Canada’s workforce. For those with cancer, frequent functional loss and diminished work ability due to side effects of the disease and its treatment significantly impact their well-being and business vitality. Compared to salaried can-cer survivors, the self-employed experience greater reductions in work hours and up to 48% greater income loss, yet most research addresses the former population. To describe self-employed Canadian cancer survivors’ experiences continuing and returning to work, our quali-tative study examines their strategic efforts to continue working throughout the disease trajecto-ry or return to work post-recovery. Employing an interpretive description approach and an in-terview guide based on a vocational rehabilitation model for cancer survivors, we analyze data from 23 participants—both French- and English-speaking—from six Canadian provinces, with eight different job types and nine different cancer diagnoses. Our constant comparative analysis of the transcribed interviews reveals four major themes and twelve sub-themes: Impact of can-cer on the self-employed function (physical, cognitive, and psychological), on their ability to maintain their business, and financial well-being, and facilitating factors for working with can-cer. Cancer disclosure and non-disclosure were both deemed viable strategies, but ceasing work was not. We thus recommend professional support for self-employed cancer survivors in plan-ning any necessary business modifications to accommodate their condition and cancer treatment to lessen the negative impact of cancer on self and on their business well-being.

Nanostructured dipeptide self-assemblies exhibiting quantum confinement are of great interest due to their potential applications in the field of materials science as optoelectronic materials for energy harvesting devices. Among those, aromatic cyclo-dipeptides containing the amino acid tryptophan are wide-band gap semiconductors displaying high mechanical rigidity, photoluminescence and piezoelectric properties to be used in power generation. In this work, we report the fabrication of hybrid systems based on chiral cyclo-dipeptide L-Tryptophan- L-Tryptophan incorporated into biopolymer electrospun fibers. The micro/nanofibers contain self-assembled nanospheres embedded into the polymer matrix are wide-band gap semiconductors (gap energy 3.8 eV), display blue photoluminescence and relevant piezoelectric and pyroelectric properties with coefficients as high as 57 pCN-1 and 35×10-6 Cm-2k-1, respectively. They are therefore promise systems for thermal sensing and energy harvesting applications.

Acanthopanax senticosus(rupr. rt. Maxim.; AS) is a medicinal plant used in the clinical treatment of cerebrovascular diseases and central nervous system disorders, significantly improving blood lipid levels and endothelial cell function in patients with acute cerebral infarction. Isofraxidin, one of the active ingredients of AS, is the core of the medical effects, and its extraction and purification depend on organic solvents. Deep eutectic solvents (DESs) is a new green solvent, synthesized by intermolecular hydrogen bonding between hydrogen bond donors (HBD) and hydrogen bond acceptors (HBA), which has non-toxic, high separation and purification efficiency, and environmentally friendly compared with traditional organic solvents. In this paper, DES was used for the extraction of isofraxidin from AS. The primary findings demonstrate that the DESs had a viscosity higher than that of ethanol, and even adding a tiny amount of water (about 10%) would trigger solvent redistribution, leading to a considerable reduction in solvent viscosity. In comparison to ethanol, the extraction rate of isofraxidin by DESs was 2-3 times higher. Thus, this work developed a new technique for using green extraction of isofraxidin that has some practical implications.

Isometric exercises for physiotherapeutic rehabilitation are often prescribed, with little quantification of the load being prescribed. This article aimed to provide a framework and practical examples of how the physiotherapist may take a more quantitative evidence-based approach to isometric assessment, monitoring, and exercise prescription of knee osteoarthritis, by integrating a strain gauge into their practice. Strength measures to monitor were discussed. A series of fourteen studies were reviewed, with the intent of identifying isometric exercises that had been utilized in the rehabilitation of knee osteoarthritis. Of the fourteen studies, the three most identified isometric exercises were seated knee extension, knee flexion, and the supine straight leg raise. The integration of strain gauge technology with these exercises provided the focus of the remainder of the article.

United Nations Framework Convention on Climate Change (UNFCCC) has recently established the Reducing Emissions from Deforestation and forest Degradation (REDD+) program that requires countries to report their carbon emissions and sink estimates through national greenhouse gas inventories (NGHGI). Thus, developing automatic systems capable of estimating the carbon absorbed by forests without in-situ observation becomes essential. To support this important need, in this work we introduce ReUse, a simple but effective deep-learning approach to estimate the carbon absorbed by forest areas based on remote sensing. The novelty of the proposed method is in the use of the public above-ground biomass (AGB) data from the European Space Agency's Climate Change Initiative Biomass project as ground truth to estimate the carbon sequestration capacity of any portion of land on Earth using Sentinel-2 images and a pixel-wise Regressive UNet. The approach has been compared to two literature proposals, using a private dataset and human-engineered features. The results show a greater generalization ability of the proposed approach, with a decrease in Mean Absolute Error and Root Mean Squared Error, respectively, of 16.9 and 14.3 in the area of Vietnam and 4.7 and 5.1 in the area of Myanmar over the runner-up. Finally, as a case study, we reported an analysis made for the Astroni area, a nature reserve located near the metropolitan area of Naples in southern Italy, struck by a large fire, producing predictions consistent with values found by experts in the field. These results further support the use of such an approach for the early detection of AGB variations, both in urban and rural areas.

Sometimes when diabetic retinopathy (DR) is found and treated quickly, vision loss can indeed be spared. This study deploys a deep learning (DL) model that can discover all 5 stages of DR more accurately than other methods. The proposed methodology shows two cases scenarios: case 1 with image enhancement using CLAHE and ESRGAN, and case 2 without image enhancement. Augmentation techniques are then employed to produce a balanced dataset with the identical criteria for both scenarios. The generated model using DenseNet-121 on the APTOS dataset outperformed other approaches for locating the 5 stages of DR, with an accuracy of 98.7 percent for case 1 and 81.2 percent for case 2. Using CLAHE and ESRGAN was shown to improve a model's performance and ability to learn.

“Sustainable development” (SD) is a term that has gained prominence in the international dia-logue around development. Many, however, continue to misunderstand the concept, its principles, its development, and its operationalization. The wide variety of definitions and interpretations of SD lean toward institutional and social prerogatives rather than unifying the essence of the con-cept, which is rooted in conventional ideas and values. By delving deeper into the paradigm, its history, and its potential, this research sought to contribute to ongoing discussions about sus-tainable development. The literature was thoroughly analyzed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020. This historical and conceptual analysis sought to update the body of knowledge on sustainability and sustainable development by examining the metaphorical and epistemological underpinnings of SD’s various definitions, evolutions, and principles. The research concludes and argues that intergenerational justice, based on the environment, economy, and society, is the central tenet of the entire sustainable develop-ment argument. The focus and consideration of interested parties are moving from the protection of the environment to social sustainability. The future of SD is likely to continue to focus much more on the social pillar and integrate digitalization in implementing the SD concept, especially in the fourth industrial revolution. To promote ethical human behavior and activities worldwide, at national and local levels, decision-makers must be continuously cognizant of the interdepend-encies, direct interactions, and balance between the three core constructs of SD.

Coastal marine ecosystems worldwide, like Florida Bay, are increasingly affected by tide alteration and anthropogenic disturbances which affect water quality imbalance leading to algal blooms. Increased bloom persistence is a serious threat due to the long-lasting impact on processes like carbon cycle and services like species presence. However, exploring eco-environmental feedback patterns of algal blooms remains challenging and poorly investigated, also due to the paucity of data. Florida Bay, taken as an epitome, has long experienced algal blooms in its central and western regions, and in 2006 an unprecedented bloom occurred in the eastern habitats. We analyzed the occurrence of blooms from three perspectives: (1) the spatial spreading networks of chlorophyll-a (CHLa) that pinpoints source and unbalanced habitats; (2) the fluctuations of water quality factors pre- and post-bloom outbreaks to in assess environmental impacts of ecological dysbiosis and target prevention and control of algal of blooms; and (3) the biogeochemical-spreading network topological co-evolution to quantify ecosystemic stability and ecological shift likelihood in long-term. Here, we propose Transfer Entropy (TE) to quantify dynamical interactions between spatial areas and biogeochemical factors (ecosystem connectome) underpinning bloom emergence and spreading, as well as environmental effects; the Pareto principle is defined for identifying the salient eco-environmental interactions of CHLa. We quantified the spatial dynamics of algal blooms, and thus obtained areas in need for ecological monitoring and potential bloom control. Results show that algal blooms are increasingly persistent over space with long-term negative effects on water quality factor. A dichotomy is reported between spatial ecological corridors of spreading and biogeochemical networks as well as divergence from the optimal eco-organization: randomization of the former due to nutrients' overload and temperature increase leads to scale-free CHLa spreading and extreme outbreaks a posteriori. Subsequently this increases bloom persistence, turbidity and salinity with potentially strong ecological effects on highly biodiverse and vulnerable areas such as tidal flats and marshes. Algal blooms are important ecosystem regulators of nutrient cycles; however, beyond limit chlorophyll-a outbreaks cause aquatic species mortality due to their effect on water turbidity, nutrient balance (nitrogen and phosphorus in particular), salinity and temperature. Beyond compromising local environmental quality, socio-ecological services are also compromised at large scales, yet ecological assessment models like the one presented are in need of application in subtropical and tropical bays worldwide.

With the advent of Neural Machine Translation, the more the achievement of human-machine parity is claimed at WMT, the more we come to ask ourselves if their evaluation environment can be trusted. In this paper, we argue that the low quality of the source test set of the news track at WMT may lead to an overrated human parity claim. First of all, we report nine types of so-called technical contaminants in the data set, originated from an absence of meticulous inspection after web-crawling. Our empirical findings show that when they are corrected, about 5% of the segments that have previously achieved a human parity claim turn out to be statistically invalid. Such a tendency gets evident when the contaminated sentences are solely concerned. To the best of our knowledge, it is the first attempt to question the “source” side of the test set as a potential cause of the overclaim of human parity. We cast evidence for such phenomenon that according to sentence-level TER scores, those trivial errors change a good part of system translations. We conclude that to overlook it would be a mistake, especially when it comes to an NMT evaluation.

High-level performance in mountain sports would be unlikely unless different emotional factors are taken into account through the analysis of psychological characteristics such as mood, resilience or motivation, among many others. In this study, 788 people with a sports degree from the Spanish Federation of Mountain Sports and Climbing (FEDME) participated, 75.3% are men and 24.5% are women. The mean age of the participants was 49.8 years (±12.8), ranging from 18 to 76 years. The Wong Law Emotional Intelligence Scale (WLEIS-S), the RS-14 Resilience Scale and the Satisfaction with Life Scale (SWLS) instrument were used. The aim of this research was to determine the relationship between the dimensions of emotional intelligence, resilience and life satisfaction. The results showed a relationship between several of the dimensions from the instruments used (p<.01). In terms of gender, higher scores were found for women than for men. The regression model shows that both the dimensions of emotional intelligence [Appraisal of own emotions (β=.104; p<.001); Use of emotions (β=.30; p&lt;.001); Emotional Regulation (β=.103; p<.001)] and resilience [Personal competence (β=.402; p<.001)], are predictors of greater life satisfaction, with 44.1% positively explained by the regression model. Further proposals should extend the results obtained with the analysis of more sports modalities and provide evidence that would complement those extracted in this research.

The extracellular matrix (ECM) is a ubiquitous member of the body and is key to the maintenance of tissues and organs integrity. Initially thought to be a by-stander in many cellular processes, the extracellular matrix has been shown to have diverse components that regulate and activate many cellular processes and ultimately influence cell phenotype. Importantly, the ECM composition, architecture, and stiffness/elasticity influence cellular phenotypes. Under normal conditions and during development, the synthesized ECM is constantly undergoing degradation and remodeling processes via the action of matrix proteases that maintain tissue homeostasis. In many pathological conditions including fibrosis and cancer, the ECM synthesis, remodeling, and degradation is dysregulated causing its integrity to be altered. Both physical and chemical cues from the ECM are sensed via receptors including integrins and play key roles in driving cellular proliferation and differentiation and in various disease progression such as cancers. Advances in ‘omics’ technologies have seen an increase in studies focussing on bi-directional cell-matrix interactions and here we highlight emerging knowledge on the role played by the ECM during normal development and in pathological conditions. This review summarizes current ECM-targeted-therapies that can modify tumor ECM to overcome drug resistance and better cancer treatment.

Currently, there is increasing industrial demand for rare earth elements (REE) as these elements are now integral to the manufacture of many carbon-neutral technologies. The depleting REE ores and increasing mining costs are prompting to look for alternative sources for these valuable metals, particularly from waste streams. Although REE concentrations in most of the alternate resources are lower than current REE ores, some sources such as marine sediments, coal ash, and industrial wastes like red mud are looking promising with significant concentrations of REE in them. This review focuses on the alternative resources for REE such as ocean bottom sediments, continental shelf sediments, river sediments, stream sediments, lake sediments, phosphorites deposits, industrial waste products like red mud, and phosphogypsum, coal, coal fly ash, and related materials, waste rock sources from old and closed mines, acid mine drainage, and recycling of e-waste. Possible future Moon exploration and mining for REE and other valuable minerals are also discussed. It is evident that REE extractions from both primary and secondary ores alone are not adequate to meet the current demand, and sustainable REE recovery from the alternative resources described here is also necessary to meet the growing REE demand. An attempt is made to identify the potential of these alternative resources and sustainability challenges, benefits, and possible environmental hazards to meet the growing challenges in meeting the future REE requirements.

The development of autonomous vehicles is becoming increasingly popular and gathering real world data is considered a valuable task. Many datasets have been published recently in the autonomous vehicle sector, with synthetic datasets gaining particular interest due to availability and cost. For a real implementation and correct evaluation of vehicles at higher levels of autonomy it is also necessary to consider human interaction, which is precisely something that lacks in existing datasets. In this article the UPCT dataset is presented, a public dataset containing high quality, multimodal data obtained using state of the art sensors and equipment installed onboard the UPCT’s CICar autonomous vehicle. The dataset includes data from a variety of perception sensors including 3D LiDAR, cameras, IMU, GPS, encoders, as well as driver biometric data and driver behaviour questionnaires. In addition to the dataset, the software developed for data synchronisation and processing has been made available. The quality of the dataset was validated using an end-to-end neural network model with multiple inputs to obtain speed and steering wheel angle and obtained very promising results.

In its 8th Malaysia Plan (MP*), the Malaysian government has given nanotechnology development a high priority and has been made a Strategic Research (SR) programme. Consequently, an exhaustive and long-term approach is essential. Additionally, specific laws are required to provide an optimal health and safety environment for workers. Consequently, the current study intends to assist Malaysian policymakers in promoting improved safety, risk assessment, and management for nanotechnology workplaces, as well as drafting a comprehensive policy for the recently released DOSH guideline in 2018. Utilizing a unique methodology, this study evaluated the assessment and management of nanotechnology health and safety risks in Malaysia using the international risk governance council (IRGC) framework. In addition to document analysis, n = 20 semi-structured interviews were conducted with representatives of several nanotechnology platforms to collect data that was then analyzed thematically. The research evaluated current workplace safety regulations and laws. Consequently, we propose a future dynamic strategy for Malaysian nanotechnology with more favourable upgrades supported by increased concentrations in the following areas: I policy creation, ii) comprehensive management system, iii) knowledge transfer, and iv) infrastructure management. In addition, the findings highlight the need of cross-sectional communication in bridging existing gaps. This study laid the groundwork for a more systematic and comprehensive health and safety strategy.

This paper examines the potential of Artificial Intelligence (AI) to address societal megatrends, with a specific focus on OpenAI’s Generative Pre-Trained Transformer 3 (GPT-3). To do this, we con-ducted an analysis using GPT-3 in order to explore the benefits of AI for digitalization, urbanization, globalization, climate change, automation and mobility, global health issues and aging population. We also looked at emerging markets as well as sustainability in this study. Interaction with GPT-3 was done solely through prompt questions and generated responses were analyzed. Our results indicate that AI can significantly improve our understanding of these trends by providing insights into how they develop over time and what solutions could be implemented. Further research is needed to determine how effective AI will be in addressing them successfully but initial findings are encouraging. Our discussion focuses on the implications of our findings for society going forward and suggests that further investigation should be done into how best to utilize new technologies like GPT-3 when tackling these challenges. Lastly, we conclude that while there is still much work left to do before any tangible effects can be seen from utilizing AI tools such as GPT-3 on societal mega-trends; early indications suggest it may have a positive impact if used correctly.

November 15th, 2022 was selected as the day where the human population reached the 8 billion mark [1]. This new reality will force the governments around the world to find ways to sustainably produce and secure food, water, and energy for their countries [2-4]. In terms of water, its quality and availability has been a matter of great concern in recent decades [5], especially with the emergence of new organic and inorganic pollutants [6]. Among organic contaminants, the detection of trace amounts of fluoroquinolone antibiotics, such as ciprofloxacin (CFX) and levofloxacin (LFX), in natural water bodies, has been of great concern in the scientific community [7,8]. Some of the side effects of the consumption of these antibiotics are nausea, diarrhea, abdominal pain, rash, low sugar levels, and antibiotic resistance to bacterial infections, among others [9,10]. It was estimated that in 2019 more than 1.27 million people died due to antibiotic-resistant bacterial infections [11], and this number is expected to rise to 10 million by 2050, if the trend continues [12]. Because of this, new ways to degrade antibiotics from water have been developed over the years. A method that has been implemented for some time is the use of photocatalysts for the degradation of these compounds in water [13]. Semiconductors such as titanium oxide (TiO2), zinc oxide (ZnO), zinc sulfide (ZnS), cadmium sulfide (CdS), strontium peroxide (SnO2), or tungsten trioxide (WO3), among others, are commonly used in photocatalytic processes [14-16]. Zinc oxide has been widely used due to its low cost and stability in aqueous solution, easy production, and because it is an environmentally friendly material [17,18]. It has been identified that some of the disadvantages of ZnO as photocatalyst are photocorrosion, recombination of electron-hole pairs, fast backward reactions, and inability to use visible light [18]. Multiple approaches have been implemented over the years to reduce these limitations. One of them is the use of noble metals such as platinum (Pt), gold (Au), or even silver (Ag) as cocatalysts [15-17,19]. These metals can increase the photocatalytic activity by reducing the recombination of electron-hole pairs, as well allowing the use of visible light [20]. For example, Quin and coworkers [21] prepared a bio-inspired hierarchical assembly of carbonized spinach leaves@Au/ZnO for the degradation of CFX under visible light. The results showed a degradation of 61% of the antibiotic in a period of 180 minutes. Chankhanittha et al. [22] developed different Ag@ZnO composites for the complete degradation of red dye and ofloxacin antibiotic in 25 and 80 minutes, respectively. The researchers attributed the improved photoactivity to the high electron-hole separation efficiency at the photocatalyst interface, as well as the creation of the Schottky barrier at the silver-zinc oxide interface.

This paper is introducing KABADA (Knowledge Alliance of Business Idea Assessment: Digital Approach) unique tool, together with opinions of young people about entrepreneurship, their skills and experience with this tool. The focus is on non-business students who study natural sciences, engineering and other areas at the Faculty of Forestry and Wood Technology at Mendel University in Brno, Czech Republic. KABADA tool has been developed and tested by a team of international experts. It can be used to improve forester management. This structured, Web-based, platform which is based on theoretical research, relevant statistics, and artificial intelligence insights, guides entrepreneurs through every step of the way including what challenges and opportunities lie ahead. The research included survey answers from 60 university students before and after using KABADA tool. The results show that students are interested in entrepreneurship but do not have the knowledge, experience and support from curriculum. Majority of students had no or very low experience with entrepreneurship nor any entrepreneurship training or study course before. After using the tool, students declared to have higher knowledge of entrepreneurship and the number of students who intended to become an entrepreneur increased. The tool is available on-line, free of charge.

Following the central dogma of molecular biology, gene expression variability can aid in predicting and explaining the wide variety of protein products, functions, and, ultimately, variability in phenotypes. There is currently overlapping terminology used to describe the types of variability in gene expression profiles, and overlooking these nuances can misrepresent important biological information. Here, we describe transcriptional diversity as quantifying transcriptional changes as a measure of the variability in 1) the total expression of all genes or a gene across samples (transcriptome diversity) or 2) the isoform-specific expression of a given gene (isoform diversity). We first overview modulators and quantification of gene expression variability. Then, we discuss the role alternative splicing plays in driving transcript isoform expression variability and how isoform diversity can be quantified. Additionally, we overview computational resources for calculating transcriptome and isoform diversity for short- and long-read sequencing data. Finally, we discuss future applications of transcriptional diversity. This review provides a comprehensive overview of how gene expression variability arises, and how measuring it determines a more complete picture of heterogeneity across proteins, cells, tissues, organisms, and species

A progressive and chronic neurological condition called MSA (Multiple System Atrophy) is characterized clinically by varying degrees of dysautonomia, cerebellar ataxia, and parkinsonism. The concept of mitochondrial dysregulation in MSA is one perspective in handling this neurodegenerative disease. Damage to functional mitochondria is driven by the presence of ɑ-Synuclein-induced mitochondrial localization. The goal of MSA treatment up until now has been to reduce symptoms. One of the innovations in the treatment of MSA could be the novel idea based on mitochondrial reprogramming pathways. Mitochondrial reprogramming can be done in various ways in which the use of hydrogen, magnesium and low-dose hydrogen peroxide.

Pharmacovigilance databases are showing evidence of injury in the context of the COVID-19 modified mRNA shots. According to recent publications, adverse event reports linked to the mRNA COVID-19 products largely point to the spike protein as an aetiological agent of adverse events, but we propose that the platform itself may be culpable. To assess the safety of current and future mRNA vaccines, further analysis on the risks due to the platform itself, and not specifically the expressed antigen. If harm can be exclusively and conclusively attributed to the spike protein, then it is possible that future mRNA vaccines expressing other antigens will be safe. If harms are attributable to the platform itself, then regardless of the toxicity, or lack thereof, of the chosen payload therein, the platform may be inherently unsafe, pending modification. In this work, we examine previous studies of RNA-based delivery by a lipid nanoparticle and break down the possible etiological elements of harm.

This paper studies pandemic viruses that spread during the period (1759–2020) according to solar activity cycles. Our findings and results include the following: (1) The severity of a pandemic correlates negatively with the strength of solar activity; (2) Pandemic viruses are classified into three types based on their compatibility with solar activity associations. Most of them spread through the quiet Sun, where viruses survive better in cold and rainy weather, and in stable geomagnetic fields without strong disturbances; (3) The emergence of new strains of influenza viruses was manifested in two ways. First, the annual epidemics due to antigenic drift. Second, pandemics recur every 1–12 solar cycles (about 11–120 years) due to viral reassortment of new subtypes, which results in antigenic shifts; (4) Pandemic viruses have two groups according to their recurring period: first, recurring in nine solar cycles; second, recurring in twelve solar cycles. Furthermore, we reassort pandemic viruses from their previous spread in the same periodic classification. Moreover, we derive a periodicity formula for each subtype of the pandemic virus as a spread date.

Objectives: One of the home-made herbal remedy being traditionally used against gout is evaluated to identify any new and characteristic marker compound which may be used as characteristic analytical marker to standardize this polyherbal remedy. Materials and method: A distinct and remarkable peak in the HPLC chromatogram of remedy was identified which was further isolated by fraction collector. This fraction was then evaporated and characterized for structure elucidation using set of various techniques such as RP-HPLC,UV, FTIR, TLC, EIMS and NMR. Results: The compound characterized was non polar compound, ester of betulin and palmitoleic acid. Although the remedy has been standardized using set of four markers as discussed in literature but this newly developed marker compound can be used to further standardize this remedy and other herbal preparations comprising of this marker compound.Conclusion: Hence the isolated compound can be used as novel analytical marker in the standardization of this herbal remedy and the other herbal preparations containing such marker compound

Microbial immune escape represents the primary cause of induced pathogenesis in humans, and it represents a pivotal method used by viral agents to increase their load and suppress key mechanisms of the innate and adaptive immune system. This phenomenon represents the primary factor that led to the onset of the 1918-1920 A(H1N1) Influenza and 2020-2022 COVID-19 pandemics, and it possibly played a major role in the onset of the AIDS pandemic as well. Moreover, repeated incidents of immune evasion could be associated with higher rates of cellular aging (Jackson et al., 2017), most likely due to the consequent increased demands of energy consumption. Highly developed viral immune evasion ultimately indicates the high inner intelligence of human immunity due to reflective and imitative characteristics of reactions that are produced against initial actions. Ribonucleic acid-based viral genomes contain open reading frames, which consist of genes producing sixteen non-structural proteins. Such proteins play a considerable role in desensitizing first-line immunity during cellular infection, and non-structural proteins 1, 10 and 16 have the strongest effects against a healthy expression rate of Type I and Type III Interferon-encoding genes. Type I Interferons consist of IFN-alpha, -beta, -delta, -epsilon, -omega, -tau and -zeta, whilst Type III Interferons consist of IFN-lambda1, -lambda2 and -lambda3, and they act as stimulators of intracellular signalling cascades that in turn lead to the activation and expression of interferon-stimulated genes (Brown et al., 2022). The earlier the interferon-stimulated genes are activated, the lower the extent of pro-inflammatory mediation and overall, the more effective the antiviral immune response will be, given the exponential nature of the viral load increase. Non-structural protein 16 methylates the 5’ cap of the virus, making the pathogen-associated molecular patterns less recognisable by pattern-recognition receptors, and it requires activation by bonding with non-structural protein 10. It is preserved in the S-Adenosyl-L-Methionine pocket of the SARS-CoV-2 genome. Non-structural protein 1 (NS1) directly cleaves the host cell mRNA producing Type I and possibly Type III Interferons, thereby preventing a translation process of the immune proteins. NS1 has recently been found to often be packaged into exosomes once secreted by the viral genome in the cytosol, meaning that exocytosis and paracrine signalling to neighbouring cells before their actual infection is possible. As a result, NS1 is highly capable of silencing the first-line immune responses of uninfected neighbouring cells as well, thereby highlighting the need to adjust the focus of therapeutics and vaccinology toward first-line immunity and further indicating its foundational importance in the support for the development of precise and balanced defenses against microbial agents of concern (EL SAFADI et al., 2022).

Advances in nanomedicine bring the attention of researchers to the molecular targets which can play a major role in the development of novel therapeutic and diagnostic modalities for cancer management. The choice of a proper molecular target can decide on the efficacy of the treatment and endorse the personalized medicine approach. Gastrin-releasing peptide receptor (GRPR) is a G-protein-coupled membrane receptor, well known to be overexpressed in numerous malignancies including pancreatic, prostate, breast, lung, colon, cervical and gastrointestinal cancers. Therefore, many research groups express a deep interest in targeting GRPR with their nanoformulations. A broad spectrum of the GRPR ligands has been described in the literature, which allows tuning of the properties of the final formulation, particularly in the field of the ligand affinity to the receptor and internalization possibilities. Hereby the recent advances in the field of applications of various nanoplatforms which are able to reach the GRPR expressing cells are reviewed.

Previous studies demonstrate the critical importance of non-coding RNAs interfacing with chromatin-modifying machinery resulting in promoter-enhancer-based gene regulation and raise the possibility that many other enhancer-like RNAs may operate via similar mechanisms. Critically, more than 80% of the disease-linked variations identified in genome-wide studies are located in the non-coding regions of genomes, especially non-coding RNA, suggesting non-coding RNAs are relevant to disease. Thus, a critical path forward for understanding non-coding RNAs' role, especially long non-coding RNAs, is to understand the genomic regions' transcriptional regulation, especially non-coding regions. Here, we developed a user-friendly R package called SomaGene for studying and identifying enhancer-like non-coding RNAs with enriched somatic mutations in the cancer genome. SomaGene accepts different genomic variants (whole genome/exome somatic point mutations, structural variations, copy number variations) to identify those RNAs that significantly mutated in diseases (e.g., cancer). It then uses multiple publicly available genomics and epigenetics datasets including ENCODE epigenomics annotations, FANTOM5 tissue-specific expression profiles, disease-associated genome-wide association SNPs, and tissue-specific eQTL pairs to identify those RNAs with potentially enhancer function. SomaGene, as a powerful R package, can provide the opportunity to cancer scientists to study the roles of non-coding RNAs in different cancer genomes.

A Traumatic brain injury (TBI) is among the main causes of sudden death after head trauma. These injuries can result in severe degeneration and neuronal cell death in the CNS, including the retina which is a crucial part of the brain responsible for perceiving and transmitting visual information. The long-term effects of mild-repetitive TBI (rmTBI) are far less studied thus far, even though damages induced by repetitive injuries occurring in the brain are more common, especially amongst athletes. rmTBI can also have a detrimental effect on the retina and the pathophysiology of these injuries are likely to differ from the severe TBI (sTBI) retinal injury.Here we showed how rmTBI and sTBI can dissimilarly affect the retina. Our results indicate an increase in the number of activated microglial cells and Caspase3-positive cells in the retina in both traumatic models, suggesting a rise in the level of inflammation and cell death after TBI. The pattern of microglial activation appears evenly distributed and widespread but differs amongst the various retinal layers. sTBI induced microgial activation in both the superficial and deep retinal layers. In contrast to sTBI, no significant change occurred following the repetitive mild injury in the superficial layer, only the deep layer (spanning from the inner nuclear layer to the outer plexiform layer) shows microglial activation. This difference suggests that alternate response mechanisms play a role in the case of the different TBI incidents. The Caspase3 activation pattern showed a uniform increase in both the superficial and deep layers of the retina. This suggests a different action in the course of the disease in sTBI and rmTBI models and points to the need for new diagnostic procedures.Our present results suggest that the retina might serve as such a model of head injuries since the retinal tissue reacts to both forms of TBI and is the most accessible part of the human brain.

Postpartum depression (PPD) can predispose to physical and mental health problems in women. However, PPD is associated with health and perceived social support but their causal relationship is unclear. Therefore, this study intended to evaluate the association of PPD with insomnia, mental health, and physical health. Convenience sampling technique was used to collect data from 320 (52.8 %) young and middle aged postpartum women, in the outpatient departments of obstetrics and gynecology in Government Maula Bakhsh Hospital, District Head Quarter in Sargodha, Pakistan. The Edinburgh Postnatal depression scale, Pittsburg sleep quality index, Warwick-Edinburgh mental wellbeing scale, Patient health questionnaire, and Multidimensional scale of perceived social support were used to measure study variables. Results revealed a significant positive relationship of PPD with physical health (r= .45, p=.001), while a negative relationship with insomnia (r= -.24, p<.001), and perceived social support (r= -.38, p=.001). Results further confirmed that perceived social support played a moderating role (β = .97, p=.01) in the relationship between PPD and mental health among females. This study concluded that perceived social support has an important role in PPD and women’s health. The study also concluded that poor health is a risk indicator for identifying aid in the early stages of postpartum among women.

Objectives Assess rates of adverse events (AE) after COVID-19 vaccines experienced by women of reproductive age, focusing on pregnancy and menstruation, using data collected by the US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS) database. Design Population-based retrospective cohort study. Setting US and global entries in US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS). Participants CDC VAERS entries from January 1, 1998 to June 30, 2022. Interventions None. Main Outcome Measures A proportional reporting ratio analysis is performed using data in the VAERS system comparing adverse events (AE) reported post-COVID-19 vaccines with that of post-Influenza vaccines. Results COVID-19 vaccines, when compared to the Influenza vaccines, are associated with a significant increase in AE with all proportional reporting ratios of > 2.0: menstrual abnormalities, miscarriage, fetal chromosomal abnormalities, fetal malformation, fetal cystic hygroma, fetal cardiac disorders, fetal arrhythmias, fetal cardiac arrest, fetal vascular malperfusion, fetal growth abnormalities, fetal abnormal surveillance, fetal placental thrombosis, low amniotic fluid, preeclampsia, premature delivery, preterm premature rupture of membrane, fetal death/stillbirth, and premature baby death (all p values were much smaller than 0.05). When normalized by time-available, doses-given, or persons-received, all COVID-19 vaccine AE far exceed the safety signal on all recognized thresholds. Conclusions Pregnancy complications and menstrual abnormalities are significantly more frequent following COVID-19 vaccinations than Influenza vaccinations. A worldwide moratorium on the use of COVID-19 vaccines in pregnancy is advised until randomized prospective trials document safety in pregnancy and long-term follow-up in offspring.

The research is on the SuperHyperGirth and the neutrosophic SuperHyperGirth. A SuperHyperGraph has SuperHyperGirth where it’s the longest SuperHyperCycle. To get structural examples and instances, I’m going to introduce the next SuperHyperClass of SuperHyperGraph based on SuperHyperGirth. It’s the main. It’ll be disciplinary to have the foundation of previous definition in the kind of SuperHyperClass. This SuperHyperClass is officially called “SuperHyperFlower”. If there’s a need to have all SuperHyperCycles until the SuperHyperGirth, then it’s officially called “SuperHyperOrder” but otherwise, it isn’t SuperHyperOrder. There are two instances about the clarifications for the main definition titled “SuperHyperGirth”. These two examples get more scrutiny and discernment since there are characterized in the disciplinary ways of the SuperHyperClass based on SuperHyperGirth and they’re called “SuperHyperFlower.” A SuperHyperGraph has “neutrosophic SuperHyperGirth” where it’s the strongest [the maximum value from all SuperHyperCycles amid the minimum value amid all SuperHyperEdges from a SuperHyperCycle.] SuperHyperCycle. In “Cancer’s Recognitions”, the aim is to find either the longest SuperHyperCycle or the strongest SuperHyperCycle in those neutrosophic SuperHyperModels. For the longest SuperHyperCycle, called SuperHyperGirth, and the strongest SuperHyperCycle, called neutrosophic SuperHyperGirth, some general results are introduced. Beyond that in SuperHyperStar, all possible SuperHyperPaths have only two SuperHyperEdges but it’s not enough since it’s essential to have at least three SuperHyperEdges to form any style of a SuperHyperCycle. There isn’t any formation of any SuperHyperCycle but literarily, it’s the deformation of any SuperHyperCycle. It, literarily, deforms and it doesn’t form. A basic familiarity with SuperHyperGraph theory and neutrosophic SuperHyperGraph theory are proposed.

Terminalia arjuna possesses significant cardio protective, antidiabetic and antioxidant properties as these properties are described in Ayurveda. In the present study, three flavonoids were isolated through the separation and chromatographic purification of the whole plant material of T. arjuna. Spectroscopic characterization identified one of them as a new flavonoid “Terminalone A (1)” and two known flavonoids i.e. 6-hydroxy-2-(4-hydroxyphenyl)-7-methoxy-4H-chromen-4-one (2) and 2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-4H-chromen-4-one (3). The bioactivity studies showed considerable antibacterial and antioxidant (DPPH was used as a scavenger) potential for all the three compounds 1-3 where the compound 1 showed strong antibacterial and antioxidant activity.

A novel scheme that can simultaneously measure the Doppler frequency shift (DFS) and angle of arrival (AOA) of microwave signals is proposed. At the signal receiving unit (SRU), two echo signals and the reference signal are modulated by a Sagnac loop structure and sent to the central station (CS) for processing. At the CS, two low-frequency electrical signals are generated after polarization control and photoelectric conversion. The DFS without direction ambiguity and wide AOA measurement can be real-time acquired by monitoring the frequency and power of the two low-frequency electrical signals. In the simulation, an unambiguous DFS measurement with errors of ±3×10-3 Hz and a -90° to 90° AOA measurement range with errors of less than ±0.5° are realized. The safety and robustness of the system to environmental disturbance are improved, and it is more suitable for the modern electronic warfare system.

This exploratory study examined the impacts of COVID-19 and emerging challenges and opportunities from aviation recovery. Using archival and secondary data analysis, the study found that there are several challenges to aviation recovery chief among them are labour challenges and extreme weather events, which have been responsible for traffic disruptions in major aviation markets such as Europe and the USA. Other emerging challenges include high debt, inflation, interest rates, fuel, cost of labour, and general operational costs. The study recommends several interventions to address the sector’s challenges, including adopting risk disaster preparedness and management to foster sustainability.

High-grade gliomas are the most common and aggressive adult primary brain tumors with a median survival of only 12-15 months. Current standard therapy consists of maximal safe surgical resection followed by DNA-damaging agents, such as irradiation and chemotherapy that can delay but not prevent inevitable recurrence. Some have interpreted glioma recurrence as evidence of glioma stem cells which persist in a relatively quiescent state after irradiation and chemotherapy, before the ultimate cell cycle re-entry and glioma recurrence. Conversely, latent cancer cells with a therapy-induced senescent phenotype have been shown to escape senescence, giving rise to more aggressive stem-like tumor cells than those present in the original tumor. Therefore, approaches are needed to either eliminate or keep these glioma-initiating cells in a senescent state for a longer time to prolong survival. In our current study, we demonstrate that the radiation-induced cell cycle inhibitor P21 can provide a powerful route to induce cell death in short-term explants of PDXs derived from three molecularly diverse human gliomas. Additionally, cells not killed by P21 overexpression were maintained in a stable senescent state for longer than control cells. Collectively, these data suggest that P21 activation may provide an attractive therapeutic target to improve therapeutic outcomes.

In past years, lithium-ion batteries (LIBs) can be found in every aspect of life, and batteries, as energy storage systems (ESSs), need to offer electric vehicles (EVs) more competition to be accepted in markets for automobiles. Thick electrode design could reduce the use of non-active materials in batteries that its energy density would be improved and its cost would be cut. However, thick electrodes are limited by their weak mechanical stability and poor electrochemical performance, these limitations could be classified as the critical cracking thickness (CCT) and the limited penetration depth (LPD). The understanding of the CCT and the LPD have been proposed and the recent works on breaking the CCT and improving the LPD are listed in this article. By comprising these attempts, some thick electrodes could not offer higher mass loading or higher accessible areal capacity that would defeat the purpose.

The goal of our study was to examine the effect of regional characteristics of living environment on individual a priori and a posteriori dietary patterns of the Russian population. For the analysis, we used cross-sectional data from the Epidemiology of Cardiovascular Diseases in the Regions of the Russian Federation study of 2013-2014. The sample included 18,054 men and women 25-64 years of age from 12 regions. Based on the frequency of consumption of basic foods, four a posteriori empirical dietary patterns (EDPs), along with an a priori cardioprotective dietary pattern (CPDP) were identified. To describe the regional living environment, 5 regional indices were used. The adherence to the meat-based EDP was directly associated with deterioration of social living conditions and the more northerly location of the region of residence. The probability of CPDP increased with deterioration of social living conditions, an aggravation of demographic crisis, higher industrial development of the region, as well as with a decline in the economic development of the region, income and economic inequality of the population. We detected some gender-dependent differences in associations. The revealed patterns reflect the national dietary preferences of Russians, and regional indices characterize the effect of living environment.

Vacuum pump wear is the most prevalent failure mode of the IBA Synthera® automated radiochemistry system. Rebuilding or replacing the pump causes equipment downtime and increases the radiation exposure of the service personnel. We built a dedicated test device to assess new or rebuilt pumps prior to installation, thus reducing downtime and radiation exposure during repairs. The Testbed incorporates a microprocessor that actuates the pump, valves, pressure sensor, and communicates with the user through lights, buttons, and an alphanumeric screen. The Testbed increases productivity and safety in the radiochemistry laboratory.

Today, concepts such as Emotional Education and Emotional Intelligence are recognized by many authors and researchers, emphasizing the importance of their development in all people, but especially in schools, specifically in teachers or educators and children. However, we still find many shortcomings within the schools that are needed to continue working. The aim of this study is to investigate the presence of emotional intelligence and empathy in teachers, through a sample of 42 participants. The research was conducted based on two validated and highly reliable assessment tools, called TMMS-24 and TECA. The results of the TMMS-24 indicate that a large percentage of participants have an adequate score of emotional intelligence. The results of the TECA indicate that most of the participants are in the middle, high or extremely high scores in relation to the level of empathy.

Sustainable teacher development is the key to the success in the program of Master of Translation and Interpretation (MTI) but there was limited research on their current situation and needs in China. In this study 514 teachers from 32 provinces, municipalities and autonomous regions across China were investigated by means of quantitative questionnaires and online interviews concerning their current situation of career development and this research presented a comprehensive description of their age, academic qualifications and professional title. Also this study expounded the current situation and difficulties in academic research, teaching, translation practice and staff training. The findings were as follows. 1：In spite of reasonable age structure, approximately 50% of them had less than three years’ teaching experience in MTI. 2: There was a rise in the number of MTI teachers with doctoral degree but they found it hard to offer students professional guidance. 3: A large proportion of MTI teachers were in a slow stream of promotion in the title of professional post. 4: The proportion of the academic achievements related to translation in all the research projects and papers was small. 5: A majority of them worked as part-time translators. 6: About half of the teachers were not very satisfied with the effectiveness in their staff training program. Therefore it is suggested that more opportunities be provided for the MTI teachers to conduct translation practice in the professional sector and more researches be needed to thoroughly understand their requirement in terms of career development with a view to bridging the gap between content in the teacher training and their actual needs.

To have a better protection, strong toughness and good flexibility, all lives and plants must have skins, similarly, all books should have covers. In this paper, considering interlayer friction as a perturbation, we formulate a hardcover-book-like laminated plates with internal friction. For a quasi-static problem, detail analysis on the bending response and energy dissipation are carried out for a three-point-supported plates. Our numerical investigations show that the hardcover is more essential than the core layers in terms of bending response, and the energy dissipation within per loading-unloading cycle can be made to vary by a considerable amount. The central goal of studying is not only to predict the bending deformation of the book-like-plates, but also as a representative case to help finding some clue on the universal behaviours of multilayered architectures with internal friction.

The stick-free flight stability is an old-fashioned and non-progressive issue; nevertheless, it is still existent, and of significant importance to the design of aircraft whose control system is reversible. The problem’s existence necessitates a deep assessment of stick-free flight stability throughout the aircraft design. Up to now, this problem has been addressed using either analytical approaches, which are only related to the static stability evaluation, or performing flight tests. In this study, the problem is handled in its entirety, from static and dynamic flight stability assessment to design criteria with a comprehensive perspective. Moreover, it is also exhibited that contrary to what has been generally proposed in the literature, limiting the problem of stick-free flight stability through static stability assessment is far from the main challenge. As a brief scope, the derivation of the control surface dynamics, a stick-free trim algorithm, and assessment rationale of the stick-free static and dynamic flight stability using a simulation approach are proposed. As a consequence, the aim is to set a broad understanding for designers related to this phenomenon and add adjunct design criteria in the design optimization process by approaching it in terms of modeling, simulation, and flight test perspective.

Gravity played an important role in the development of life on earth. The effect of gravity on a living organisms can be investigated by controlling the magnitude of gravity. Most reduced gravity experiments are conducted on the lower earth orbit (LEO) in the International Space Station (ISS). However, running experiments in ISS face challenges such as high cost, extreme condition, lack of direct accessibility, and long waiting period. Therefore, researchers have developed various ground-based devices and methods to perform reduced gravity experiments. However, the search for life outside the earth requires more intensive research. Advancements in conventional methods and the development of new tools are required for this purpose. The advantages of Lab-on-a-Chip (LOC) devices make them an attractive option for simulating microgravity. This paper briefly reviews the advancement of LOC technologies for simulating microgravity in a earth-based laboratory.

Several studies have highlighted the importance and evolution of process safety leadership and culture in various industries. However, none has focused on the palm oil milling industry yet. This paper critically reviews the latest developments in the palm oil milling process and unit operations leading to process safety concerns. It also discusses the Principle of 3C that is applied to explain repeat accidents and the four-level safety culture in the palm oil milling industry. For this purpose, the author presents case studies of two key palm oil companies in Malaysia. Overall, this paper offers guidelines to leaders in the palm oil milling industry about the required process safety leadership and culture to be understood in order to improve their safety outcomes.

In the olive orchard on the western part of Istria, Croatia, twig and branch dieback was observed on several olive trees from the local cultivar ‘Buza’. In total, seven samples from symptomatic trees were collected. Samples were analyzed, and four fungal isolates showed morphological similarities to the species Phaeoacremonium iranianum. One isolate, chosen as a representative, was taken for molecular identification and pathogenicity tests. Based on DNA sequence data of ITS1/ITS4, βt2a/βt2b, EF1-728F/EF1-986R, the isolate was identified as P. iranianum. Pathogenicity tests were conducted on detached olive branches and olive trees in the greenhouse, and identified fungal species was pathogenic on olive. To the best of our knowledge, this is the first report of twig and branch dieback on olive causing by phytopathogenic specie of fungus Phaeoacremonium iranianum.

The quality of yarn is essential in the control of the fabrics processes. There is some commercial equipment that measures the quality of yarn based on sensors, of different types, used for collecting data about some yarn characteristic parameters. The existing equipment, for the above-mentioned purpose, is characterized by its high size and cost, and for allowing the analysis of only few yarn quality parameters. Thus, this paper presents the development and results obtained with the design of a mechatronic prototype integrating a computer vision system that allows, among other parameters, the analysis and classification, in real time, of the hairs of the yarn using artificial intelligence techniques. The system also determines other characteristics inherent to the yarn quality analysis, such as: linear mass, diameter, volume, twist orientation, twist step, average mass deviation, coefficient of variation, hairiness coefficient, average hairiness deviation and standard hairiness deviation, as well as performs spectral analysis. A comparison of the obtained results with the designed system and a commercial equipment was performed validating the undertaken methodology.

In recent years, Nigeria is witnessing increasing frequency of flood occurrence with devastating impact translating into significant loss of lives (in Nigeria, over 300 people died in September 2022) and properties. Addressing flood disaster requires holistic approach from policy and governance perspectives, integration of policies and programs and synergies between institutions. Using synergies and eliminating trade-offs, flood governance and policy coherence integrate all relevant policy fields and institutions to achieve common policy outcomes. The objective of this study is to examine and understand how flood governance and policy coherence are approached, as well as institutional design and implementation for coherence in Nigeria. The findings revealed that there is no single flood policy in Nigeria. Due to this, there is no focus and no defined objectives for flood governance, prevention, control, and management, and no imperative for the government to seek both short-term and long-term flood solutions. There is no synergy and coordination among institutions for flood governance in the country. Since the country established the federal ministry of environment in 1999, the environment, floods, and climate-related hazards were given less priority. State and local governments handle most flood disasters and emergencies. Federal assistance is provided, however, when flood disasters exceed the capabilities of local and state governments. This study recommends that across the country, flood policy needs to be designed, formulated, and implemented while assigning governance responsibility and decentralizing policy to state and local governments.

Tin (IV) oxide nanoparticles (SnO2 NPs) have received a lot of interest because of their interesting features. SnO2 NPs have proven productive in a range of fields, including water purification, supercapacitors, batteries, antibacterial and antioxidant agents, and others. SnO2-based nanoparticles found a wide range of applications after incorporating materials with varying chemical compositions. SnO2 NPs and their nanocomposites have been used effectively as antibacterial agents against various pathogenic bacteria, photocatalysts for dye degradation, and electrode materials for supercapacitors (SCs). This article covers the characteristics of SnO2 NPs, SnO2 nanocomposite materials, applications of SnO2 NPs and their composite materials, including antibacterial, energy storage, and photocatalysis, as well as some significant recent studies.

Tubulin superfamily (TSF) proteins are widespread and known for multifaceted roles as cytoskeletal proteins underpinning many basic cellular functions including morphogenesis, division, and motility. In eukaryotes, tubulin assembles into microtubules, a major component of the dynamic cytoskeletal network of fibres, whereas the bacterial homolog FtsZ assembles the division ring at midcell. Functions of the lesser-known archaeal TSF proteins are beginning to be identified, and show surprising diversity, including homologs of tubulin and FtsZ, and a third archaea-specific family, CetZ, implicated in the regulation of cell shape and possibly other unknown functions. In this study, we defined sequence and structural characteristics of the CetZ family and CetZ1 and CetZ2 subfamilies, identified CetZ groups and diversity amongst archaea, and identified potential functional relationships through analysis of the genomic neighbourhoods of cetZ genes. At least three subfamilies of orthologous CetZ proteins were identified in the archaeal class Halobacteria, including CetZ1 and CetZ2 and a novel uncharacterized subfamily. CetZ1 and CetZ2 were correlated to one another and to cell shape and motility phenotypes across diverse Halobacteria. Amongst other known CetZ clusters in orders Archaeoglobales, Methanomicrobiales, Methanosarcinales, and Thermococcales, an additional uncharacterized group from Archaeoglobales and Methanomicrobiales affiliated strongly with Halobacteria CetZs, suggesting they originated via horizontal transfer. Subgroups of Halobacteria CetZ2 and Thermococcales CetZ genes were found adjacent to different type IV pili regulons, suggesting a potential utilization of CetZs by type IV systems. More broadly conserved cetZ gene neighbourhoods included nucleotide and cofactor biosynthesis (e.g., F420) and predicted cell surface sugar epimerase genes. The findings imply that CetZ subfamilies are involved in multiple functions linked to the cell surface, biosynthesis and motility.

Evolution of SARS-CoV-2 has followed similar trends as other RNA viruses, e.g., HIV-1 and influenza A. Rapid initial diversification was followed by strong competition and rapid succession of dominant variants. Host-initiated RNA editing has been the primary mechanism for introducing mutations. A significant number of mutations were detrimental and were quickly purged. Fixed mutations are mostly diversifying mutations selected for host adaptation and immune evasion, with the latter accounting for more of the changes. However, immune evasion often comes at the cost of functionality, so that optimal functionality is still far from being accomplished. Instead, selection for antibody-escaping variants and accumulation of near-neutral mutations has led to suboptimal codon usage and reduced replicative capacity as demonstrated in non-respiratory cell lines. Beneficial adaptation of the virus includes reduced infectivity in lung tissues and increased tropism for the upper airway, resulting in shorter incubation periods, milder diseases, and more efficient transmission between people.

Leptospirosis is an important zoonotic disease, causing about 60,000 deaths annually. One of the reasons for the severe course of leptospirosis is a cytokine storm, which develops as a result of an excessive immune response. The gut microbiota that resides in the gastrointestinal tract provides essential health benefits to its host, particularly by regulating immune homeostasis and a bidirectional relationship with many internal organs. A change in the gut microbiota can be caused not only by antibiotics, but also by infectious agents such as the coronavirus or the flu virus. It is known that L. interrogans can change the microbiota of mice. Thus, gut dysbiosis in leptospirosis can affect the clinical course of the disease, through the gut–organ axis. Modulation of intestinal microbiota by probiotics and/or fecal microbiota transplantation in leptospirosis may become an important area of scientific research.

Cancer metastasis into the brain constitutes one of the most severe but not uncommon development of cancer growth. Several factors control how cancer types interact with the brain to establish metastasis These factors include system of migration, system of infiltration of the blood-brain barrier and the interaction with host cells (e.g., neurons, astrocytes) and the immune system fight against metastasis in the brain. Although, brain radiotherapy is the main treatment procedure carried out to treat, new therapies are emerging that constitute a glimpse of hope for increasing the diminutive life expectancy currently forecasted to cancer patients who are facing the prospectus of brain metastasis. However applying these therapeutic strategies has been has not been effective. Thus there is a need for better understanding of the metastasis process in order to suggest novel therapeutic targets. In this review, we follow the journey of various cancer cells from their primary location through the various process that they undergo including EMT, penetration of the ECM, intravasation, extravasation and infiltration of the blood brain barrier ending up with colonization and angiogenesis. In each phase, we focus on molecules that could potentially be drug target candidates.

As a model for economic and ecological systems, replicator dynamics represents a basic form of agent competition for finite resources. Here, we investigate the effects of stochastic resetting in this kind of processes. Random reset events abruptly lead individual resources to a small value from which dynamics must start anew. Numerical results show that resource distribution over the population of competing agents develops highly nonuniform profiles, exhibiting clustering and fluctuations with anomalous dependence on the population size. This non-standard statistical behavior jeopardizes an analytical treatment based on mean-field assumptions. We propose alternative simplified analytical approaches which provide a stylized description of entropy evolution for the clustered distribution of resources and explain the unusually slow decrease of fluctuations.

As the global energy crisis continues, efficient hydrogen production is one of the hottest topics these days. In this sense, establishing catalytic trends for hydrogen production is essential for choosing proper H2 generation technology and catalytic material. Volcano plots for hydrogen evolution in acidic media are well-known, while volcano plot in alkaline media was constructed ten years ago using theoretically calculated hydrogen binding energies. Here we show for the first time that the volcano-type relationships are largely maintained in a wide range of pH values, from acidic to neutral and alkaline solutions, using theoretically calculated hydrogen binding energies on clean metallic surfaces and experimentally measured hydrogen evolution overpotentials. If metallic surfaces are exposed to high anodic potentials, hydrogen evolution can be boosted or significantly impeded, depending on the metal and the electrolyte in which the reaction occurs. Such effects are discussed here and can be used to properly tailor catalytic materials for hydrogen production via different water electrolysis technologies.

In this paper, we give some upper and lower bounds for the multiplicative Randic index, reduced reciprocal Randic index, Narumi-Katayama index and symmetric division index a graph using solely the vertex degrees. Then we obtain upper and lower bounds for these indices for the complete graphs, path graphs and Fibonacci-sum graphs. Finally, we compared the bounds of these indices for a general graph and some special graphs.

Diffuse intrinsic pontine glioma (DIPG) is recognized as a pediatric brainstem cancer with a 0% survival rate. On a molecular basis, DIPG commonly results from mutations in histone H3, specifically a mutation in the H3K27M gene, that promotes tumorigenesis and results in presentation of this fatal brainstem tumor. DIPG is challenging to treat, as surgical intervention is inefficacious due to the location where the glioma resides. To date, traditional treatments such as radiation, chemotherapy, and immunotherapy have not increased survival rates and have only been successful at relieving symptoms. Future therapeutic approaches such as proton beam radiation, Chimeric Antigen Receptor T Cell (CAR-T) immunotherapy, and alternative epigenetic pharmaceuticals are under investigation for potential benefits. Various clinical trials have also explored these treatment procedures to discover potential increases in survival rates in both animal and human studies. In this review, we will evaluate the pathology and molecular characteristics of DIPG, the current and future approaches to DIPG treatment; and, lastly, we will discuss clinical trials that have been completed to develop successful treatment options.

By constructing a static map, the library robot can navigate and access documents autonomously, which greatly improves efficiency; however, for libraries where shelves can be moved, map changes do not allow for direct navigation, and also sensors such as radar and camera are relatively expensive, so we propose a low-cost navigation algorithm based on real-time ranging data and map matrices, and designed a mobile archive access robot. In order to obtain real-time distance data, nine near/long range sensors were mounted on the chassis and a composite digital filtering algorithm was designed based on different moving area characteristics; then the access task matrix and map matrix were designed based on the archive access task and the location characteristics of the archive shelf placement, the robot can rely on the range data to update the map matrix during the moving process, complete its own positioning, and use the task matrix The robot can use the task matrix to complete autonomous navigation and access to multiple files. Experiments show that the filtered positioning accuracy can reach 1cm, while the robot can move to the target shelf autonomously, which is more practical and less costly.

Abstract: Background: COVID-19 is a respiratory disease that eventually became pandemic with 300 million people infected around the world. Alongside the improvement in COVID-19 management and vaccine development, identifying biomarkers for COVID-19 has recently reported to help in early prediction and managing severe cases which might improve outcome. The Aim of our study was to find out if there is any correlation between clinical severity and elevated hematological and biochemical markers in Covid-19 patients and its effect on the outcome Methods: We have collected data retrospectively of socio-demographic, medical history, biomarkers, and diseases outcome from five hospitals and health institutions in the Kingdom of Saudi Arabia. Results: Pneumonia was the most common presentation of COVID 19 in our cohort. All biomarkers (D-Dimer, CRP, troponin, LDH and ferritin) except for the mean lowest white blood cells were found to have significant correlation (p<0.05) with worse COVID-19 disease outcomes. There was a sig-nificant association between the inflammatory biomarkers and the disease severity of COVID 19 patients (p<0.001). Patients with evidence of severe respiratory disease particularly who required mechanical ventilation (MV) had higher biomarkers, when compared to those with stable respiratory condition (p<0.001). Conclusion: Identifying biomarkers predicts outcome for COVID-19 patients and may significantly help in the management.

Humans are a vision-dominated species, and what we see depends on where we look. Therefore, eye movements (EM) are essential to our interactions with the environment, and experimental findings show EM is affected in neurodegenerative disorders (ND). It could be a reason for some cognitive and movement disorders in ND. Therefore, we aim to determine if changes in EM-evoked responses can tell us about ND, such as Alzheimer’s (AD) and Parkinson’s Disease (PD) progression in different stages. In the present review, we have analyzed the results of neurological, psychological, and EM (saccades, antisaccades, pursuit) tests to predict disease progression with Machine Learning (ML) methods. Described predictive algorithms are using various approaches, including Granular Computing, Naive Bayes, Decision Trees/Tables, Logistic Regression, C-/LinearSVC, KNC, and Random Forest. We demonstrated that EM is a robust biomarker for assessing symptom progression in PD and AD. There are also navigation problems in 3D space in both diseases. Consequently, we investigated EM experiments in the virtual space and how they may help find neurodegeneration-related brain changes. In conclusion: EM parameters with clinical symptoms are powerful precision instruments that, in addition to predictions of ND progression with the help of ML, could be used to indicate the different preclinical stages of both diseases.

Biochemical oxygen demand (BOD) is one of the most important factors to consider when evaluating water contamination. BOD5 is the amount of oxygen consumed in five days by microorganisms that oxidize biodegradable organic materials in an aerobic biochemical manner. The primary objective of this effort is to use microbial fuel cells (MFCs) to shorten the time required for BOD5 measurements. We created a regression artificial neural network (AI), and the predictions we obtained for BOD5 measurements were taken over 6 – 24 hours with an average error of just 7%. The outcomes demonstrated by our AI MFC/BES BOD5 sensor’s viability for use in real-world scenarios.

Real estate has the dual characteristics of consumption and investment. Under the inherent concept of "where there is land, there is wealth", real estate has become the investment target of the main asset. In addition to the supply and demand of the market will affect the price of real estate, many general economic factors will also have a certain impact on the price of real estate. This paper pays a special focus on the effects of MRT on housing prices, finding the closer a house is to an MRT station, the higher its price. In addition, convenience stores are very popularized, and this research report is also interested in whether the number of convenience stores within walking distance will affect the house price. In a word, these two factors do affect housing prices significantly.

Rose (Rosa spp.), especially R. hybrida, is one of the most popular ornamental plants in the world and the third largest cut flower crop in Taiwan. Rose mosaic disease (RMD), showing mosaic, line patterns and ringspots on leaves, is a common rose disease caused by complex infection of various viruses. Due to pests and diseases, the rose planting area in Taiwan has been decreasing since 2008; however, no rose virus disease has been reported in the past five decades. In the spring of 2020, rose samples showing RMD-like symptoms were observed at an organic farm in Chiayi, central Taiwan. The virome in the farm was analyzed by RNA-seq. Rose genomic sequences were filtered from the obtained reads. The remaining reads were de novo assembled to generate 294 contigs, 50 of which were annotated as viral sequences corresponding to 10 viruses. Through reverse transcription-polymerase chain reaction validation, a total of seven viruses were detected, including six known rose viruses, namely apple mosaic virus, prunus necrotic ringspot virus, rose partitivirus, apple stem grooving virus, rose spring dwarf-associated virus and rose cryptic virus 1, and a novel ilarvirus. After completing the whole genome sequencing and sequence analysis, the unknown ilarvirus was demonstrated as a new species, tentatively named rose ilarvirus 2. This is the first report of the rose viruses in Taiwan.

One of the possible mechanisms causing significant emissions of methane into the atmosphere within the Arctic shelf may be the decomposition of gas hydrates. Their accumulations within the Arctic shelf formed during Ice Age almost simultaneously with the formation of permafrost, which contributed to the emergence of a zone of stable existence of gas hydrates. The subsequent flooding of the Arctic shelf led to the degradation of the permafrost and the violation of the conditions for the existence of hydrates. To assess the state of the stability zone, methods of mathematical numerical modeling are used. Standard seismic methods are widely used to localize gas hydrates, but monitoring their physical state requires the development of fundamentally new approaches based on solving multiparameter inverse seismic problems. In particular, the degree of attenuation of seismic energy is one of the objective parameters for assessing the consolidation of gas hydrates: the closer they are to the beginning of decomposition, the higher the attenuation, and hence the lower the quality factor. Thus, the methods of seismic monitoring of the state of gas hydrates in order to predict the possibility of developing dangerous scenarios should be based on solving a multi-parameter inverse seismic problem. This publication is devoted to the presentation of this approach.

Others have proposed that living systems are characterized by the possession of a kind of information unique to them. This information, variously called semantic, symbolic, or coding information conveys meaning from senders to recipients, most commonly among genome and other cellular components, different cells, organisms, etc., enabling all biological functions. Unlike other kinds of information, it is only indirectly quantifiable and does not increase by copying. Here, the term system information is used to encompass the entire package of coding information enabling all organisms of a species to complete their life cycles through possession of its copy (Crkvenjakov and Heng 2021). System information grows in a nonreductive evolution only during speciation proper by the acquisition of novel functions by daughter species. Contemporary science agrees that species are units of evolution but has failed to recognize and parse the importance of phases of speciation and stasis for evolution. Confinement of system information change to speciation only explains for the first time why there are species and why their number increases nearly exponentially throughout evolution. More importantly, here we define that evolution as a process operating on a planetary scale, while chance based, is non-random mathematically since it obeys the Laws of Information which dictate the behavior of System information in organisms. Growth and persistence of system information on the non-degenerative portion of Tree of Life follow the law of conservation, which states that its growth is as parsimonious (minimal) as possible and the persistence of parental system information the maximal possible in each unit speciation step. This formulation is a restatement of Loewnstain's (1999) principle of information economy and our lock-in law (Crkvenjakov and Drmanac 2007). The principle holds that since, on chance assumption, the system information change cost is directly proportional to time, more costly pathways of achieving the same new functional goal will be, almost without exception, competed out by the less costly ones. As a corollary of the conservation law, the speciation law states that speciation follows the most economical way of growth of system information while conserving the existing one, which is horizontal information transfer by molecular sex (uptake of exogenous nucleic acid into the progeny genome) by exchange among two parents from maximally possible divergent lineages. The speciation law dictates that molecular sex mode be used since it is the most parsimonious one. The molecular sex cost in information bits is zero to the recipient, which is not the case with the generally accepted mode of vertical accumulation of information bits in a population gene pool within a lineage.

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

Monkeypox virus infection is a recognized public health emergency. Little research has been done on treatment options for this disease. Until recently, there was not a single published work describing the usage of specific drugs in human patients with monkeypox virus infection. This paper gives the first bibliometric analysis of monkeypox treatment options based on data available on PubMed and Scopus. It also reviews the specific drugs used in the treatment of monkeypox. That includes data on Tecovirimat, Cidofovir, Brincidofovir, and Vaccinia Immune Globulin. Tecovirimat is a promising option in progressive disease in terms of efficacy and safety. However, Brincidofovir has been associated with discontinuation of treatment. Cidofovir is also not the preferred drug among physicians. Currently, Tecovirimat can be further used for the management of aggravating cases. More studies should be conducted on Tecovirimat to treat this condition, mainly through controlled trials.