This article develops a multi-perspective view on motivations and methods for tobamovirus purification through the ages, and presents a novel efficient, easy-to-use approach that can be well-adapted to different species of native and functionalized virions. We survey the various driving forces prompting researchers to enrich tobamoviruses: from the search for the causative agents of mosaic diseases in plants to their increasing recognition as versatile nanocarriers in biomedical and engineering applications. Best practice and also rarely applied options for the serial processing steps required for successful isolation of tobamoviruses are then reviewed. Adaptations for distinct particle species, pitfalls and 'forgotten' or underrepresented technologies are considered as well. The article is topped off with our own development of a method for virion preparation, rooted in historical protocols. It combines selective re-solubilization of polyethylene glycol (PEG) virion raw precipitates with density step gradient centrifugation in biocompatible iodixanol formulations, yielding ready-to-use particle suspensions. This newly established protocol and some considerations for perhaps worthwile further developments could serve as putative stepping stones towards preparation procedures appropriate for routine practical uses of the multivalent soft-matter nanorods.

The purported cognitive benefits associated with nicotine and its metabolites in the brain are a matter of debate. In this review, the impact of the pharmacologically active metabolite of a nicotine derivative produced by bacteria (6-hydroxy-L-nicotine) on memory, oxidative stress, and the activity of the cholinergic system in the brain was examined. A search in the PubMed, Science Direct, Web of Science, and Google Scholar databases, limiting entries to those no later than July 2023, was conducted. The search focused specifically on articles pertaining to nicotine metabolites, memory, oxidative stress, cholinergic system activity, as well as enzymes or pathways related to nicotine degradation in bacteria. The preliminary search resulted in 696 articles, and following the application of exclusion criteria, 185 articles were deemed eligible for inclusion. This review focuses on experimental studies supporting nicotine catabolism in bacteria, and the chemical and pharmacological activities of nicotine and its metabolite 6-hydroxy-L-nicotine.

Tobacco Free Nicotine (TFN) Electronic Nicotine Delivery Systems (ENDS) are yet to be classified as tobacco products; consequently, there is ambiguity over whether Food and Drug Administration (FDA) regulatory authority can be extended to include TFN e-cigarettes. In recent years, a more significant number of e-cigarette companies have been manufacturing TFN-containing e-cigarettes and e-liquids to circumvent FDA regulations. While studies have shown that aerosols generated from tobacco-derived nicotine-containing e-cigarettes contain significant Reactive Oxygen Species (ROS) levels, no comparison studies have been conducted using TFN e-cigarettes. This study uses a single puff aerosol generator to aerosolize TFN and tobacco-derived nicotine-containing vape-products and subsequently involves semi-quantifying ROS generated by these vape products in H2O2 equivalents. We found that the differences between ROS levels generated from TFN and tobacco-derived nicotine-containing vape products vary by flavor. TFN tobacco flavors and fruit flavors are more toxic in terms of ROS generation than menthol/ice and drink/beverage flavored products using TFN. The type of salt nicotine used in vape products, TFN or tobacco-derived nicotine, impacts the level of ROS generated from flavored vape products. Thus, a better understanding of the type of salt nicotine used in e-cigarettes (tobacco-derived or synthetic), has modulating effect on lung oxidative stress.

This study introduces and demonstrates a comprehensive, accurate, unbiased approach to robust quantitative comparison of Electronic Nicotine Delivery Systems (ENDS) appropriate for establishing substantial equivalence (or lack thereof) between tobacco products. The approach is demonstrated across a family of thirteen pen- and pod-style ENDS products. Methods employed consist of formulating a robust emissions surface regression model, quantifying the empirical accuracy of the model as applied to each product, evaluating relationships between product design characteristics and maximum emissions characteristics, and presenting results in formats useful to researchers, regulators, and consumers. Results provide a response surface to characterize emissions (total particulate matter and constituents thereof) from each ENDS appropriate for use in a computer model and for conducting quantitative exposure comparisons between products. Results demonstrate that emissions vary as a function of puff duration, flow rate, E-Liquid composition, and device operating power. Further, results indicate that regulating design characteristics of ENDS devices and consumables may not achieve desired public health outcomes; it is more effective to regulate maximum permissible emissions directly. Three emissions outcome measures (yield per puff, mass concentration and constituent mass ratio) are recommended for adoption as standard quantities for reporting by manufacturers and research laboratories. The approach provides a means of (a) quantifying and comparing maximal emissions from ENDS products spanning their entire operating envelope, (b) comparative evaluation of ENDS devices and consumable design characteristics, and (c) establishing comparative equivalence of maximal emissions from ENDS. A consumer-oriented product emissions dashboard is proposed for comparative evaluation of ENDS exposure potential. Maximum achievable power dissipated in the coil of ENDS is identified as a potentially effective regulatory parameter.

Due to related uncertainties brought by changes in energy consumption and the integration of rooftop photovoltaic systems, the accuracy and availability of load profiling data are difficult to achieve. However, project managers and planners use a precise load profile as a crucial tool when determining whether the feeder must be updated or de-loaded. The paper aims to create a non-intrusive monitoring system that predicts the synthetic load profiles behavior of energy consumption using a Light Gradient Boosted and Support Vector Machine (SVM) machine learning technique. The most effective ML algorithm is chosen, and it has the potential to be assessed and verified using validation curves, residuals model generation, and prediction error metrics based on the following key statistical indicators: Mean Absolute Error, Mean Square Error, Root Mean Square Error, R-Square, Root Mean Squared Logarithmic Error, and Mean Absolute Percentage Error. The most effective ML has the potential to be assessed and verified using validation curves, residual model generation, and prediction error metrics based on the following key statistical indicators. The result shows that the estimation of the Irms avg -based on LightGBM is more accurate than the SVM because of its quick, economical, and difficult to overfit, particularly with high-dimensional data, speed, and efficiency of the MAE (3.0698), MSE (15.2757), RMSE (3.9020), RMSLE (0.1433), and MAPE (0.0049) respectively. Additionally, the machine learning model shows that, when compared to the SVM, the LightGBM model had the highest accurate prediction, with R-Square values of 89.8%, 90.3%, and 88.5% for Irms_A_avg, Irms_B_avg, and Irms_C_avg, respectively for Brakfontein Substation supply region, and best represents a diverse customer base.

Introduction: Oral Nicotine Pouches (ONPs) are the new form of nicotine pouches that have become a type of emerging smokeless tobacco product sold by various tobacco companies. These smokeless tobacco products are being marketed for usage all over as Snus containing tobacco-derived nicotine (Natural) or as tobacco-free nicotine (Synthetic) as substitutes for other tobacco products that are limited in public places. ONPs have become popular tobacco products among adolescents/young adults and over 50% of young adult users of ONP use flavored ONP, such as menthol/mint, tobacco, dessert/candy, and fruity, being the most popular flavors. Various new ONP flavors are currently popular locally as well in the online market. Tobacco, Menthol, and fruit-flavored ONPs could motivate cigarette smokers to alteration to ONPs. Methods: We expanded our knowledge on natural/synthetic ONP flavors wheels to available data on ONPs, describing in detail their flavors and brands (US and Europe) in both natural/Synthetic ONP categories. We classified over 152 snus and 228 synthetic ONPs into the following flavor categories: “Tobacco”, “Menthol/Mint”, “Fruity”, “Candy/Deserts”, “Drink”, “Aroma”, “Spices” and “Mixed Flavors”. Results: Based on total numbers, wefound that the most popular ONPs flavor sold as tobacco and menthol to be among natural ONPs, among synthetic ONPs fruity and menthol as the most prominent flavors with varying concentrations of nicotine and other flavoring chemicals including coolant WS-23. We also illustrated possible molecular targets and toxicities due to exposure to ONPs activating several signaling cascades like AKT and NF-B might possibly lead to apoptosis and epithelial mesenchymal transition (EMT). Conclusions: Considering the marketing of ONP products with various flavor profiles and most of these products containing tobacco/menthol/fruit flavor, it is likely to have regulation and marketing disclaimer on some of these products. Further, it would be logical to determine how the market reacts in terms of compliance and non-compliance with flavor restrictions by the regulatory agencies.

The reviews usefulness has been the aim of several research studies. However, results regarding the significance of usefulness determinants are often contradicting, thus decreasing the accuracy of reviews’ helpfulness estimation. Also, bias in user reviews attributed to differences e.g. in gender, nationality, etc., may result into misleading judgments thus diminishing reviews’ usefulness. Research is needed for sentiment analysis algorithms that incorporate bias embedded in reviews, thus improving their usefulness, readability, credibility, etc. This study utilizes fuzzy relations and fuzzy synthetic evaluation (FSE) in order to calculate reviews’ usefulness by incorporating users’ biases as expressed in terms of reviews’ articulacy and sentiment polarity. It selected and analysed 95.678 hotel user reviews from Tripadvisor, for five nationalities. The findings indicate that there are differences among nationalities. The British are most consistent in their judgments expressed in titles and review documents. The British and the Greek review titles suffice to convey any negative sentiments. The Dutch use fewer words in their reviews than the other nationalities. This study suggests that fuzzy logic captures subjectivity which is often found in reviews, and it can be used to quantify users’ behavioral differences, calculate reviews usefulness, and provide the means for developing more accurate voting systems.

Currently 7.6% of the U.S. young adults aged 18-24 years old currently use e-cigarettes. This study piloted three methods of ENDS cessation by measuring cessation rates, motivational techniques that contributed to cessation success, and participants’ changes after decreasing vape use. Participants were randomized into three study arms [nicotine replacement therapy (NRT) + behavioral support, vape-taper + behavioral support, self-guided] in a 1:1:1 ratio. All participants were invited to attend 9 in-person or phone appointments over the 6 month study period. At 12 weeks, 3 of 7 (42.9%) participants in the NRT + behavioral support arm, 6 of 8 (75%) vape-taper + behavioral support arm, and 7 of 9 (77.8%) self-guided arm self-reported being vape- and nicotine-free. At 6 months, 3 of 7 (42.9%) participants in the NRT + behavioral support arm, 6 of 8 (75%) vape-taper + behavioral support arm, 4 of 9 (44.4%) self-guided arm self-reported being vape- and nicotine-free. A challenge to quitting and remain quit is social pressures, but participants identified self-control and establishing new habits to be the best methods to overcome the desire to vape. Participants who received behavioral support and a vape-taper plan from pharmacists were more likely to be vape- and nicotine-free at 6 months.

(1) Background: Nicotine is implicated in the SARS-COV-2 infection through activation of the α7-nAChR and over-expression of ACE2. Our objective is to clarify the role of nicotine in SARS-CoV-2 infection exploring its molecular and cellular activity. (2) Methods: HBEpC or si-mRNA-α7-HBEpC were treated for 1, 48 h or continuously with 10-7 M Nicotine, a concentration mimicking human exposure to a cigarette. Cell viability and proliferation were evaluated by trypan blue dye exclusion and cell counting, migration by cell migration assay, senescence by SA-beta-Gal activity, and anchorage-independent growth by cloning in soft agar. Expression of Ki67, p53/phospho-p53, VEGF, EGFR/pEGFR, phospho-p38, intracellular Ca+2, ATP and EMT were evaluated by ELISA and/or western blotting. (3) Results: Nicotine induced through α7-nAChR (i) increase in cell viability (ii) cell proliferation; (iii) Ki67 over-expression, (iv) phospho-p38 up-regulation (v) EGFR/pEGFR over-expression; (vi) increase in basal Ca+2 concentration, (vii) reduction of ATP production; (viii) decreased level of p53/phospho-p53, (ix) delayed senescence, (x) VEGF increase, (xi) EMT and consequent (xii) enhanced migration, and (xiii) ability to grow independently of the substrate. (4) Conclusions: Based on our results and on evidence showing that Nicotine potentiates viral infection it is likely that Nicotine is involved in SARS-CoV-2 infection and severity

Background: Exercise is increasingly understood as an important resource for people with harmful substance use, including those in prison. Little is known about how inmates adopt various health behaviors during incarceration, without interventions. Methods: This study analyzed self-reports from 1468 inmates in Norwegian prisons, compared them according to harmful substance use pre-incarceration, and explored changes in exercise and nicotine use during incarceration. Results were presented in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Results: Inmates with harmful substance use reported higher rates of smoking, smokeless tobacco, and physical inactivity pre-incarceration than inmates without harmful use. However, inmates with harmful use also exhibited more behavioral changes: they adopted exercise, ceased smoking, and adopted smokeless tobacco at higher rates during incarceration than the non-harmful group. Conclusions: Exercise is being taken up by a significant proportion of inmates, and may in particular be a replacement behavior for substance use. However, unhealthy behaviors are also begun or maintained. If prisons were used as an arena to facilitate healthy behaviors, the public health benefits to a marginalized group such as substance-using inmates could be substantial.

Introduction. Few studies have compared the dependence to different tobacco and nicotine products. Besides how dependence may vary between tobacco products there is even less known how it relates to other common drugs, e.g. caffeine. In this study degree of dependence was compared between snus, cigarettes, nicotine replacement (NR), electronic cigarettes and coffee. Methods. An internet panel was used to obtain a representative sample of 3001 Swedes. The responders were asked among other related things about their use of snus, NR, traditional cigarette or e-cigarette use and coffee consumption. The indicators of dependence used were: A. the Heavy Smoking Index, B. The proportions that used within 30 min after raising in the morning, C. rating the first use in the morning as the most important and D. Stating that it would be very hard to give up entirely. Results. Significantly fewer among coffee drinkers started use within 30 minutes of awakening compared with all other products. The first use of the day was found to be more important for snus users compared with other products. On HSI there was no difference between snus and cigarettes. Snus and cigarettes were rated as being more difficult to give up than NR and coffee. Conclusion. Dependence to traditional cigarettes and snus seem to be relatively similar while NR was rated lower and coffee lowest. Since the prevalence of caffeine use in all forms is so much more prevalent than nicotine use there might be more persons in the society heavily dependent on caffeine. Implication. Tobacco products are likely more dependence forming that NR products and coffee. The addiction to coffee or caffeine is seldom discussed in the society. But if there are more individuals heavily dependent on coffee than nicotine and some nicotine containing products like snus and even more so NR are not that much more harmful than coffee how problematic is the addiction?

MIMO (multiple-input multiple-output) radar provides much more flexibility than the traditional radar for its ability to realize far more observation channels than the actual number of T/R (transmit and receive) elements. Designing the array of MIMO imaging radar, the commonly used virtual array theory generally assumes that all elements are placed on the same line. However, due to the physical size of the antennas and coupling effect between T/R elements, a certain height difference between T/R arrays is essential, resulting in the defocusing of edge points of the scene. On the other hand, the virtual array theory implies far-field approximation, leading to inevitable high grating lobes in the imaging result of near-field edge points of the scene observed by common MIMO array. To tackle these problems, this paper derives the relationship between target’s PSF (point spread function) and pattern of T/R arrays, by which the design criterion of near-field imaging MIMO array is presented. Firstly, the proper height between T/R arrays is designed to focus the near-field edge points well. Secondly, the far-field array is modified to suppress the grating lobes in the near-field area. Finally, the validity of the proposed methods is verified by simulations and an experiment.

The aim of this study was to evaluate the use of a flexible synthetic polymer bone graft to provide implant stability in the absence of implant stability during implant placement in a dense cortical bone model. Sockets were prepared on polyurethane blocks according to the standard implant socket drilling protocol in the control group, both oversizing and deepening in group 2, and oversizing only in group 3. In groups 2 and 3, flexible synthetic polymer bone grafts were placed in the sockets prior to implant placement. The implants were placed at bone level in all groups. The highest torque value obtained was recorded as the insertion torque. 75 implant sites in 3 groups were included in the study. The torque values of the implants in the control group were significantly higher than those of the implants with the oversized and deepened sockets and the oversized-only sockets (p<0.05; p<0.01).The torque values of the implants with the oversized and deepened sockets were significantly higher than those of the implants with the oversized-only sockets (p<0.01). In this study, flexible synthetic polymer bone graft was shown to be effective in achieving implant stability in the management of implants with loss of primary stability.

Uridine diphosphate (UDP)-glycosyltransferases (UGTs) are major phase II detoxification enzymes involved in glycosylation of lipophilic endobiotics and xenobiotics, including phytoalexins. Nicotine, one of the most abundant secondary plant metabolites, is highly toxic to herbivorous insects. Plant-herbivore competition has been the major impetus for evolution of large superfamilies of UGTs and other detoxification enzymes. However, UGT functions in Myzus persicae adaptation have remained unknown. In this study, UGT inhibitors (sulfinpyrazone and 5-nitrouracil) significantly increased nicotine toxicity in M. persicae nicotianae, suggesting UGTs may be involved in nicotine tolerance. One hundred one UGT transcripts identified from the M. persicae genome/transcriptome were renamed according to UGT Nomenclature Committee guidelines and clustered into 11 families: UGT329, UGT330, UGT339, UGT341-UGT345, and UGT348-UGT350. UGT344 contained the most UGTs (fifty-seven). Ten UGTs (UGT330A3, UGT339A2, UGT341A6, UGT342B3, UGT343C3, UGT344D5, UGT344D8, UGT348A3, UGT349A3 and UGT350A3) were overexpressed in M. persicae nicotianae compared with M. persicae sensu stricto. UGT330A3/UGT344D5/UGT348A3/UGT349A3 knockdown significantly increased M. persicae nicotianae nicotine sensitivity, suggesting UGT upregulation in this subspecies may be associated with nicotine tolerance and thus host adaptation. This study reveals possible UGTs relevant to nicotine adaptation in tobacco-consuming M. persicae nicotianae and might facilitate further validation of the roles of these UGTs in nicotine tolerance.

The article features the structure and functions of plant synthetic promoters frequently exercised to precisely regulate complex regulatory routes. The composition of plant native promoters together with interacting proteins is presented to provide a better understanding of tasks associated with synthetic promoter development. The production of synthetic promoters is conferred on relatively small libraries produced generally by basic molecular or genetic engineering methods such as cis-element shuffling or domain swapping. Moreover, the preparation of large-scale libraries supported by synthetic DNA fragments, directed evolution, and machine or deep learning methodologies is presented. A particularly interesting group of synthetic promoters are bidirectional forms that enable the putative expression of up to 6–8 genes by one regulatory element. The introduction and controlled expression of several genes after one transgenic event strongly decreases the frequency of such problems as complex segregation patterns and random integration of multiple transgenes. These complications are commonly observed during transgenic crop development through traditional, multistep transformation by genetic constructs containing a single gene. Another path to solving problems associated with the low complexity and homology of already tested DNA fragments is through orthogonal expression systems composed of synthetic promoters and trans-factors that do not occur in nature or arise from different species. Their structure, functions, and applications are rendered in the article.

Abstract: The biological process of photosynthesis was critical in catalyzing the oxygenation of Earth’s atmosphere 2.5 billion years ago, changing the course of development of life on Earth. Recently, the fields of applied and synthetic photosynthesis have utilized the light-driven protein-pigment supercomplexes central to photosynthesis for the photocatalytic production of fuel and other various valuable products. The reaction center Photosystem I is of particular interest in applied photosynthesis due to its high stability post-purification, non-geopolitical limitation, and its ability to generate the greatest reducing power found in Nature. These remarkable properties have been harnessed for the photocatalytic production of a number of valuable products in the applied photosynthesis research field. These primarily include photocurrents and molecular hydrogen as fuels. The use of artificial reaction centers to generate substrates and reducing equivalents to drive non-photoactive enzymes for valuable product generation has been a long-standing area of interest of the synthetic photosynthesis research field. In this review, we cover advances in these areas and further speculate synthetic and applied photosynthesis as photocatalysts for the generation of valuable products.

Alcohol and nicotine are widely-abused legal substances worldwide. Relapse to alcohol or tobacco seeking and consumption after abstinence is a major clinical challenge, and is often evoked by cue-induced craving. Therefore, disruption of the memory for the cue-drug association is expected to suppress relapse. Memories have been postulated to become labile shortly after their retrieval, during a “memory reconsolidation” process. Interference with the reconsolidation of drug-associated memories has been suggested as a possible strategy to reduce or even prevent cue-induced craving and relapse. Here, we surveyed the growing body of studies in animal models and in humans assessing the effectiveness of pharmacological or behavioral manipulations in reducing relapse by interfering with the reconsolidation of alcohol and nicotine/tobacco memories. Our review points to the potential of targeting the reconsolidation of these memories as a strategy to suppress relapse to alcohol drinking and tobacco smoking. However, we discuss several critical limitations and boundary conditions, which should be considered to improve the consistency and replicability in the field, and for development of an efficient reconsolidation-based relapse prevention therapy.

Nicotine is a pharmacologically active component of tobacco which adversely affects the male reproductive system and fertility and Icariin (ICA) is the main active ingredient of Epimedium herba which has been used to treat several male reproductive problems. This study was aimed at investigating the protective or ameliorative effect of ICA against reproductive toxicity induced by intraperitoneal injection of nicotine in mice. Forty male mice were randomly divided into 4 groups: control, nicotine (0.75 mg/kg intraperitoneally), icariin (ICA, 75 mg/kg), and icariin plus nicotine (ICA + nicotine) group. After 35 days of treatment, the mice were weighed, sacrificed, and their reproductive organs were collected and examined for further studies. In the nicotine-treated group, epididymal sperm density and serum testosterone concentrations significantly decreased relative to the control group. Nicotine also caused oxidative damage as shown by significant reduction in the activities of antioxidant enzymes and an elevation in Malondialdehyde (MDA) levels. Icariin on the other hand, improved the reduction in sperm characteristics, hormone levels, and activities of antioxidant enzymes alterations observed in the nicotine treated mice. These findings indicate that the nicotine-induced reproductive toxicity and oxidative damages on male reproductive tissues can be effectively attenuated by icariin.

The dynamics of surface and sub-surface water events can lead to slope instability resulting in anomalies such as slough slides on earthen levees. Early detection of these anomalies by a remote sensing approach could save time versus direct assessment. We have implemented a supervised Mahalanobis distance classification algorithm for the detection of slough slides on levees using complex polarimetric Synthetic Aperture Radar (polSAR) data. The classifier output was followed by a spatial majority filter post-processing step which improved the accuracy. The effectiveness of the algorithm is demonstrated using fully quad-polarimetric L-band Synthetic Aperture Radar (SAR) imagery from the NASA Jet Propulsion Laboratory’s (JPL’s) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). The study area is a section of the lower Mississippi River valley in the southern USA. Slide detection accuracy of up to 98 percent was achieved, although the number of available slides examples was small.

Historically the use of artificial intelligence (AI) in paediatrics dates back to 1984 with the intro-duction of a computer-assisted medical decision-making system called SHELP. Since then, research on the use of AI in pediatrics has become much more popular, and the number of reviewed publications largely increased. Consequently, a need for a holistic research landscape enabling researchers and other interested parties to gain insights into, deepen their knowledge about or inform them about the use of AI in pediatrics arised. To fill this gap a novel methodology named synthetic knowledge synthesis was applied. Using SKS we identified most prolific countries, in-stitutions, source titles, funding agencies, research themes, research gaps and hot spots.

The transformation of the state of polarization of a light beam by its linear interaction with a material medium can be modeled through the Stokes-Mueller formalism. The Mueller matrix associated with a given interaction depends on many aspects of the measurement configuration. In particular, different Mueller matrices can be measured for a fixed material sample depending on the spectral profile of the light probe. For a given light probe and a given sample with inhomogeneous spatial behavior, the polarimetric descriptors of the point-to-point Mueller matrices can be mapped leading to respective polarimetric images. The procedure can be repeated sequentially by using light probes with different central frequencies. In addition, the point-to-point Mueller matrices consecutively measured can be combined synthetically through convex sums leading to respective new Mueller matrices, in general with increased polarimetric randomness, thus exhibiting specific values for the associated polarimetric descriptors, including the indices of polarimetric purity, and generating new polarimetric images which are different from those obtained from the original Mueller matrices. In this work, the fundamentals for such synthetic generation of additional polarimetric images are described, providing a new tool that enhances the exploitation of Mueller polarimetry.

Indole is a versatile pharmacophore widely distributed in bioactive natural products. This privileged scaffold has been found in a variety of molecules isolated from marine organisms such as algae and sponges. Among these, indole alkaloids represent one of the biggest, most promising family of compounds, having shown a wide range of pharmacological properties, including anti-inflammatory, antiviral and anticancer activities. The aim of this review is to show the current scenario of marine indole alkaloid derivatives, covering not only the most common chemical structures, but also new synthetic routes developed during the last years as well as promising therapeutic applications.

Aims and Background: People living with mental disorders experience a disproportionately higher burden of tobacco-related disease than the general population. Long-term substitution with less harmful nicotine products could reduce the tobacco-related harm among this population. This study investigated the views and preferences of people with mental health disorders about different nicotine products and their use as long-term substitutes for cigarettes. Methods: Semi-structured focus group discussion followed by a brief questionnaire. The discussion transcripts were analysed for content and themes and quantitative data summarised with descriptive statistics. Results: Twenty-nine participants took part in four focus groups. Vaping devices were the most acceptable nicotine products discussed, however preferences for nicotine products were idiosyncratic and varied along aesthetic, pragmatic, sensory and symbolic dimensions. The concept of tobacco harm reduction was unfamiliar to participants, however they generally agreed with the logic of replacing cigarettes with less harmful nicotine products. Barriers to activating tobacco harm reduction included the symbolism of smoking and quitting; the importance placed on health; the consumer appeal of alternatives; and cost implications. Discussion and Conclusion: Engaging this population in tobacco harm reduction options will require communication that challenges black and white thinking (a conceptual framework in which smoking cigarettes or quitting all nicotine are the only legitimate options) as in practice this serves to support the continuance of smoking. Consumers should be encouraged to trial a range of nicotine products to find the most acceptable alternative to smoking that reduces health harms. Providing incentives to switch to nicotine products could help overcome barriers to using less harmful nicotine products among mental health consumers.

The ability to read and quantify nucleic acids such as DNA and RNA using sequencing technologies has revolutionized our understanding of life. With the emergence of synthetic biology, these tools are now being put to work in new ways - enabling de novo biological design. Here, we show how sequencing is supporting the creation of a new wave of biological parts and systems, as well as providing the vast data sets needed for the machine learning of design rules for predictive bioengineering. However, we believe this is only the tip of the iceberg and end by providing an outlook on recent advances that will likely broaden the role of sequencing in synthetic biology and its deployment in real-world environments.

Bone is a dynamic tissue with the capacity of repair and regeneration in specific conditions. Nevertheless, due to the increased incidence of bone disorders, the need of bone grafts has been growing over the past decades and the development of an ideal bone graft with optimal properties remains a clinical challenge. This review addresses the bone properties (morphology, composition and their repair and regeneration capacity) and puts the main focus on the potential strategies for developing bone repair and regeneration materials. It describes the requirements for designing a suitable scaffold material, types of materials (polymers, ceramics and composites) and techniques to obtain the porous structures (additive manufacturing techniques/robocasting or derived from marine skeletons) for bone tissue engineering applications. The main objective of this review is to gather the knowledge on the materials and methods for the production of scaffolds for bone tissue engineering and highlighting the potential of natural porous structures such as marine skeletons as promising alternative bone graft substitute materials without any further mineralogical changes, or after partial or total transformation into calcium phosphate. The suitability of the marine-derived porous bone graft substitutes for the intended applications will be also discussed.

Biometric fingerprint identification hinges on the reliability of its sensors, however, calibrating and standardizing these sensors poses significant challenges, particularly in regard to repeatability and data diversity. To tackle these issues, we propose methodologies for fabricating synthetic 3D fingerprint targets, or phantoms, that closely emulate real human fingerprints. These phantoms enable the precise evaluation and validation of fingerprint sensors under controlled and repeatable conditions. Our research employs laser engraving, 3D printing, and CNC machining techniques, utilizing different materials. We assess the phantoms' fidelity to synthetic fingerprint patterns, intra-class variability, and interoperability across different manufacturing methods. The findings demonstrate that a combination of laser engraving or CNC machining with silicone casting produces finger-like shaped phantoms with high accuracy and consistency for rolled fingerprint recordings. For slap recordings, direct laser engraving of flat silicone targets excels and in the contactless fingerprint sensor setting, 3D printing and silicone filling provides the most favorable attributes. Our work enables a comprehensive, method-independent comparison of various fabrication methodologies, offering a unique perspective on the strengths and weaknesses of each approach. This facilitates a broader understanding of fingerprint recognition system validation and performance assessment.

While rapidly becoming a main thread in the development of new therapies, the rise of synthetic biology is also tied to concerns about the potential impact on ecosystems. That is particularly relevant in the of deployment in natural habitats, including the human microbiome. These concerns have boosted the analysis of diverse strategies of containment, from engineered cell death to xenobiology to the creation of Xeno nucleic acids. However, little attention has been paid to the potential containment implicit in nonlinear ecological interactions and the lessons provided by the population dynamics models used in community ecology. If we consider synthetic strains as some class of "species" embedded within an ecological context, it is possible to show that some network interaction patterns and their associated nonlinear responses can offer a reliable source of containment. Here we present and discuss some simple examples of these "ecological firewalls" that could help provide a self-regulating biocontainment. Our firewall designs can help to ensure that engineered organisms have a limited spread while, when required, preventing their extinction. The basic synthetic designs and their dynamical behaviour are presented, each one inspired in a given ecological class of interaction. Their possible applications are discussed and the broader connection with invasion ecology outlined.

Cognitive networks have evolved to cope with uncertain environments in order to make reliable decisions. Such decision making circuits need to respond to the external world in efficient and flexible ways, and one potentially general mechanism of achieving this is grounded in critical states. Mounting evidence has shown that brains operate close to such critical boundaries consistent with self-organized criticality (SOC). Is this also taking place in small-scale living systems, such as cells? Here we explore a recent model of engineered gene networks that have been shown to exploit the feedback between order and control parameters (as defined by expression levels of two coupled genes) to achieve a SOC state. We suggest that such SOC motif could be exploited to generate adaptive behavioral patterns and might help design fast responses in synthetic cellular and multicellular organisms.

The prolonged exposure to nicotine and the development of nicotine dependence have significant implications for cancer risk. Tobacco use, driven by nicotine addiction, is a major contributing factor to the development of various types of cancer. Smoking tobacco, in particular, has been strongly associated with an increased risk of lung cancer, as well as other malignancies. The harmful chemicals present in tobacco products, including carcinogens, can cause DNA damage and promote the initiation and progression of cancerous cells. This article presents a comprehensive literature review on the neurobiology of nicotine dependence and its implications for tobacco use treatment. Nicotine dependence is a complex phenomenon involving various neurobiological mechanisms. When nicotine enters the body, it binds to nicotinic acetylcholine receptors in the brain's reward circuitry, triggering the release of neurotransmitters like dopamine, serotonin, and norepinephrine. Over time, repeated nicotine exposure leads to neuroadaptive changes in the brain, resulting in increased motivation to seek and use the drug. Understanding the neurobiology of nicotine dependence is crucial for developing effective treatment strategies. Pharmacological interventions, such as nicotine replacement therapy and medications like bupropion and varenicline, can help individuals manage cravings and withdrawal symptoms. Additionally, behavioral therapies and counseling play a vital role in enhancing self-efficacy and providing support for smoking cessation efforts. By reviewing the existing literature, this article sheds light on the intricate neural pathways and processes involved in nicotine addiction. It emphasizes the importance of a multidimensional approach that combines pharmacological treatments and behavioral interventions to address the physiological and psychological aspects of nicotine dependence. This knowledge can inform the development of more targeted and personalized treatment approaches to help individuals overcome tobacco addiction and improve their chances of successful smoking cessation.

The article explores the concept of 'synthetic man' (SM) in the context of 'synthetic biology' (SB), analysing the potential, challenges, and ethical implications of these achievements. Through dialogue with ChatGPT 4, an in-depth understanding of the evolution, contributions of SM, ChatGPT's contribution, and concerns associated with SM is sought, providing insight into how this technology could affect our society. Our study uses a structured dialogue framework with ChatGPT that addresses essential SM questions regarding SM history, contributions, challenges, and concerns. ChatGPT responses are analysed to extract relevant information and identify trends and insights. The ChatGPT dialogue reveals that MS is still a theoretical and speculative concept with significant advances in gene therapy and genetic engineering. The potential contributions of SM in addressing global challenges such as health, environment and education are identified. Ethical and social concerns such as health risks and psychological impact are also highlighted. Differences in ChatGPT responses were observed between different sessions or even within the same session, which highlighted the limitations in the replicability of the research and sometimes the need for clarification of the questions. The article is distinguished by its unique approach of using an advanced language model to explore a complex and speculative topic. The LLM Dialogue Framework on Technology (LLM-DFonTech) framework proposal for structured dialogue with ChatGPT on various technological topics related to the original contribution provides an adaptable tool for interdisciplinary research in emerging technologies. This methodology opens up new possibilities for analyzing and developing trends in technology and society.

Rapid haemostasis during surgery is essential when one wants to reduce the duration of opera-tions, reduce the need for transfusions, and above all when one wants to achieve better patient management. The use of haemostatic agents, sealants and adhesives improves the haemostatic process by offering several advantages, especially in vascular surgery. These agents vary widely in their mechanism of action, composition, ease of application, adhesion to wet or dry tissue, im-munogenicity and cost. The most used are cyanoacrylate-based glues (Glubran 2) or polysaccharide hydrogel-microsphere powder (AristaTMAH). This work is based on a retrospective study carried out on a sample of patients with different vascular diseases (FAV, pseudoaneurysm and PICC application) in which two different haemostatic sealants were used. The aim was to assess the safety, the advantages and the ability of both sealants to activate the haemostatic process at the affected site, also in relation to their chemical-physical characteristics. The obtained results showed that the application of Glubran 2 and AristaTMAH as surgical wound closure systems is effective and safe as the success achieved was ≥94% on anastomoses of FAV; 100% on stabilization of Picc catheters; ≤95% on pseudoaneurysms.

The structure of synthetic mRNAs as used in vaccination against cancer and infectious diseases contain specifically designed caps followed by sequences of the 5’ untranslated repeats of β-globin gene. The strategy for successful design of synthetic mRNAs by chemically modifying their caps aims to increase resistance to the enzymatic deccapping complex, offer a higher affinity for binding to the eukaryotic translation initiation factor 4E (elF4E) protein and enforce increased translation of their encoded proteins. However, the cellular homeostasis is finely balanced and obeys to specific laws of thermodynamics conferring balance between complexity and growth rate in evolution. An overwhelming and forced translation even under alarming conditions of the cell during a concurrent viral infection, or when molecular pathways are trying to circumvent precursor events that lead to autoimmunity and cancer, may cause the recipient cells to ignore their differential sensitivities which are essential for keeping normal conditions. The elF4E which is a powerful RNA regulon and a potent oncogene governing cell cycle progression and proliferation at a post-transcriptional level, may then be a great contributor to disease development. The mechanistic target of rapamycin (mTOR) axis manly inhibits the elF4E to proceed with mRNA translation but disturbance in fine balances between mTOR and elF4E action may provide a premature step towards oncogenesis, ignite pre-causal mechanisms of immune deregulation and cause maturation (aging) defects.

Saponite is a trioctahedral 2:1 smectite with the ideal composition MxMg3AlxSi4-xO10(OH,F)2.nH2O (M = interlayer cation). Both the success of the saponite synthesis and the determination of its applications depends on robust knowledge of the structure and composition of saponite. Among the routine characterization techniques spectroscopic methods are the most common. This review, thus, provides an overview of various spectroscopic methods to characterize natural and synthetic saponite with focus on the extensive work by one of the authors (JTK). The IR and Raman spectra of natural and synthetic saponites are discussed in detail including the assignment of the observed bands. The crystallization of saponite is discussed based on the changes in the IR and Raman spectra and a possible crystallization model is provided. Infrared emission spectroscopy has been used to study the thermal changes of saponite in-situ including the dehydration and (partial) dehydroxylation up to 750˚C. 27Al and 29Si Magic-Angle-Spinning Nuclear Magnetic Resonance Spectroscopy is discussed (as well as 11B and 71Ga for B- and Ga-Si substitution) with respect to, in particular, Al(IV)/Al(VI) and Si/Al(IV) ratios. X-ray Photoelectron Spectroscopy provides besides chemical information also some information related to the local environments of the different elements in the saponite structure as reflected by their binding energies.

Preeclampsia (PE) is a serious complication of pregnancy with a pathogenesis that is not fully understood, though it involves the impaired invasion of extravillous trophoblasts (EVTs) into the decidual layer during implantation. Recently, others have found that diverse cell types, including EVTs, produce exosomes filled with molecular cargo (mainly proteins and RNAs) that can be transported to other cells and organs both locally and long-range. The cargo delivered by exosomes can signal to and modify the receiving cells and their environment, and EVT-derived exosomes may influence the pathogenesis of PE. Because the risk of PE is actually decreased by cigarette smoking, we considered the possibility that nicotine, a critical component of tobacco smoke, might protect against PE by modifying the content of exosomes from EVTs. In this study, we applied nicotine stimulation to cultured EVTs and subjected their secreted exosomes to proteomic analysis. We identified many proteins whose abundance in exosomes was modified by nicotine treatment of the donor EVTs, and we used bioinformatic annotation and network analysis to select five key hub proteins with potential roles in the pathogenesis or prevention of PE.

A wide variety of bacteria, fungi and plants can produce bioactive secondary metabolites, which are often referred to as natural products. With the rapid development of DNA sequencing technology and bioinformatics, a large number of putative biosynthetic gene clusters have been reported. However, only a few natural products can be detected when isolated species are grown under conventional laboratory conditions, as most biosynthetic gene clusters are not expressed or are expressed at extremely low levels at these conditions. With the rapid development of synthetic biology, advanced genome mining and modification strategies have been reported, and they provide new opportunities for discovery of natural products. This review discusses advances in recent years that can accelerate the design, build, test, and learn (DBTL) cycle of natural product discovery, and prospects trends and key challenges for future research directions.

This article describes techniques employed in the production of a synthetic dataset of driver telematics emulated from a similar real insurance dataset. The synthetic dataset generated has 100,000 policies that included observations about driver’s claims experience together with associated classical risk variables and telematics-related variables. This work is aimed to produce a resource that can be used to advance models to assess risks for usage-based insurance. It follows a three-stage process using machine learning algorithms. The first stage is simulating values for the number of claims as multiple binary classifications applying feedforward neural networks. The second stage is simulating values for aggregated amount of claims as regression using feedforward neural networks, with number of claims included in the set of feature variables. In the final stage, a synthetic portfolio of the space of feature variables is generated applying an extended SMOTE algorithm. The resulting dataset is evaluated by comparing the synthetic and real datasets when Poisson and gamma regression models are fitted to the respective data. Other visualization and data summarization produce remarkable similar statistics between the two datasets. We hope that researchers interested in obtaining telematics datasets to calibrate models or learning algorithms will find our work valuable.

After screening nearly 1000 synthetic peptides, a synthetic peptide termed JAL-AK22 (KYEGHWYPEKPYKGSGFRCIHI) derived from the BoxA domain in Tob1 protein was found to activate both unfolded and folded proMMP-7. In addition, JAL-AK22 showed auto-proteolytic activity. Interestingly, the smaller derivative of JAL-AK22 termed JAL-TA9 (YKGSGFRMI) also possessed auto-proteolytic activity and cleaved 2 fragment peptides (MMP18-33 and MMP18-40) derived from the prodomain of proMMP-7 under physiological conditions. These proteolytic activities were inhibited by AEBSF, a serine protease inhibitor. Our results demonstrate that a small synthetic peptide consisting of only 9 amino acids has serine protease-like activity and activates proMMP-7 by cleaving the prodomain region. We thus propose calling small peptides possessing with protease-like activity Catalytides (catalytic peptides). We expect that our findings will stimulate the development of novel Catalytides and related applications.

We assessed if there were any sex-related differences in the ability of nicotine to increase plasma corticosterone secretion after single or repeated nicotine administration. For single-dose studies, male and female mice were habituated to the test room for 1 h and injected with saline or nicotine (0.25 or 1 mg/kg, s.c.). In repeated-dosing studies, mice were injected with saline or nicotine (1 mg/kg, s.c.) once daily for six days, and, on day 7, received nicotine (1 mg/kg, s.c.). The mice were euthanized 15 min later, and trunk blood was collected for the measurement of corticosterone, nicotine, and cotinine. Our results showed that saline or nicotine each significantly increased plasma corticosterone levels in both male and female mice, with a greater response in female mice. Plasma corticosterone levels were increased in male but not female mice after repeated compared to single nicotine administration. The level of cotinine, a biomarker of nicotine use, was significantly higher in female than in male mice. Taken together, these novel findings suggest that female mice responded to nicotine and stress of handling more than male mice and provide for the first-time quantitative data on the male-female differences in nicotine-induced elevations of corticosterone and of cotinine.

Nicotine exposure may affect NSCLC is associated with lung cancer in humans. Whether nicotine exhibits carcinogenesis promoted activities in tumor growth still unknown. Nicotine is known to have dichotomous effects on cancer biology, acting like a pro- or anti-carcinogenesis agent. There are different functions between adenocarcinoma and squamous NSCLC cancer cells. Excess generation of nicotine may inhibit mitochondrial metabolism, protein modification, and DNA cleavage. Materials and Methods: We used the H520 NSCLC line obtained from human lung epithelial cells to detected nicotine growth and toxicity using MTT assay and western blotting. The concentration of nicotine stimulated cell growth to correspond to low concentration, while high concentration was cytotoxic. Results: According to MTT assay results, at 1.0 μM nicotine has significantly enhanced the H520 cell viability (%). Nicotine induced lung cancer carcinogenesis through mechanisms of α7nAchR, EGFR, HDAC2/4/5, Cyclin D/Cyclin E, Bcl-2, p-Akt, and inflammatory proteins of NF-KappaB and COX2 increases at 1.0 μM. Apoptosis proteins were decreases at 1.0 μM nicotine by p21, p27, c-jun, and p38α using western blotting. Nicotine stimulates tumor growth is mediated through α7nicotinic-acetylcholine receptors (α7nAChR), possibly involving inflammation. On the other hand, at high nicotine concentrations (> 1.0 μM) with consistent cytotoxic effects and appeared to be due to direct cell kill. Nicotine can prevent apoptosis induced by NSCLC. Conclusion: Therefore, the effects on chemotherapeutics by NSCLC malignant cell lines, nicotine in concentrations as low as 1.0 μM decreased. These mechanisms are responsible for the genotoxic effects caused by nicotine. This leads to downstream effects on decreased apoptosis, increased cell proliferation and transformation. The malignant NSCLC cells respond to the treatment with nicotine in lung cancer, the nicotine-mediated induction of growth may provide one of its links to α7nAchR or EGFR.

Scientists and astronomers have attached Scientists and astronomers have attached great importance to the task of discovering new exoplanets, even more so if they are in the habitable zone. To date, more than 4300 exoplanets have been confirmed by NASA, using various discovery techniques, including planetary transits, in addition to the use of various databases provided by space and ground-based telescopes. This article proposes the development of a deep learning system for detecting planetary transits in Kepler Telescope lightcurves. The approach is based on related work from the literature and enhanced to validation with real lightcurves. A CNN classification model is trained from a mixture of real and synthetic data, and validated only with real data and different from those used in the training stage. The best ratio of synthetic data is determined by the perform of an optimisation technique and a sensitivity analysis. The precision, accuracy and true positive rate of the best model obtained are determined and compared with other similar works. The results demonstrate that the use of synthetic data on the training stage can improve the transit detection performance on real light curves.

The effect of high temperature (HT) stress on nicotine biosynthesis in Nicotiana attenuata was examined. Nicotine content was measured in mature leaves, young sink leaves and in roots from well-watered plants grown at 25 °C as controls and from plants exposed to 38 °C and 43 °C temperatures applied for 24, 48, 72 and 96-hr duration. At 38 °C, all leaf nicotine levels were significantly less than control plants for up to 72-hr exposure but rose sharply thereafter to levels significantly greater than controls with 96-hr exposure. In contrast, plants exposed to 43 °C never exhibited a reduction in leaf nicotine content and showed a significant increase in content with just 48-hr exposure. When radioactive 11CO2 was administered to plants, HT stress significantly reduced fixation. Furthermore, radiocarbon flux analysis revealed that ‘new’ C partitioning (as 11C) into the [11C]-amino acid pool was significantly reduced with HT stress as were yields of [11C]-aspartic acid, an important amino acid in nicotine biosynthesis, and its beta-amido counterpart [11C]-asparagine significantly reduced. In contrast, [12C]-aspartic acid levels appeared unaffected at 38 °C but were significantly elevated at 43 °C relative to controls. Additionally, [12C]-asparagine levels were significantly elevated at both stress temperatures. Finally, leaf total soluble protein (TSP) was reduced 39% with long exposures to both stress temperatures. However, Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) which was 41% TSP appeared unaffected by HT stress. Altogether, these results support the theory that plant proteins other than Rubisco degrade at elevated temperatures freeing up essential amino acids supporting the nicotine biosynthetic machinery, and while feedback might downregulate de novo amino acid synthesis from ‘new’ C resources, more than likely plant C/N rebalancing caused by HT reductions in C input restricted N uptake, which in turn, limited this process.

The postnatal rodent spinal cord in-vitro is a useful model to investigate early pathophysiological changes after injury. While low dose nicotine (1µM) induces neuroprotection, how higher doses affect spinal networks is unknown. Using spinal preparations of postnatal wild-type Wistar rat and Wnt1Cre2:Rosa26Tom double-transgenic mouse, we studied the effect of nicotine (0.5-10µM) on locomotor networks in-vitro. Nicotine 10µM induced motoneuron depolarization, suppressed monosynaptic reflexes, and decreased fictive locomotion in rat spinal cord. Delayed fall in neuronal numbers (including motoneurons) of central and ventral regions emerged without loss of dorsal neurons. Conversely, nicotine (0.5-1µM) preserved neurons throughout the spinal cord and strongly activated the Wnt1 signaling pathway. High-dose nicotine enhanced expression of S100 and GFAP in astrocytes suggesting their response to stress. Excitotoxicity induced by kainate was contrasted by nicotine (10µM) in the dorsal area and persisted in central and ventral regions with no change basal Wnt signaling. When combining nicotine with kainate, the activation of Wnt1 was reduced compared to kainate/sham. The present results suggest that high dose nicotine was neurotoxic to central and ventral spinal neurons as the neuroprotective role of Wnt signaling became attenuated. This also corroborates the risk of cigarette smoking for the foetus/newborn since tobacco contains nicotine.

Genetic switches can be utilized for many purposes in synthetic biology including the assembly of complex genetic circuits to achieve sophisticated cellular systems and the construction of biosensors for real-time monitoring of intracellular metabolite concentrations. Although genetic switches have mainly been developed in prokaryotes to date, eukaryotic genetic switches are increasingly being reported as both rational and irrational engineering technologies mature. In this review, we describe genetic switches in yeast based on synthetic transcription factors and/or synthetic promoters. We also discuss directed evolution technologies for the rapid and robust construction of yeast genetic switches.

Additive manufacturing (AM) has revolutionized the field of biopolymers by providing a range of opportunities to create complex and intricate structures. Here we provide an overview of developments in biopolymer AM, first in the context of how natural systems have impacted the synthetic processes of AM, and secondly in the context of how synthetically derived structures can be used for biomedical applications. In particular, we explore the range of biopolymers developed for AM, AM techniques for biopolymers, and potential biocompatible medical applications with a focus on four categories of tissue in the human body: skin, bone, heart, and nerve. Despite the current challenges of the technology, exciting results in tissue regeneration, synthetic replacements for natural grafts, and complex dynamic organoids have already come to pass - with many more possible in the future.

What is the potential for synthetic biology as a way of engineering, on a large scale, complex ecosystems? Can it be used to change endangered ecological communities and rescue them to prevent their collapse? What are the best strategies for such ecological engineering paths to succeed? Is it possible to create stable, diverse synthetic ecosystems capable of persisting in closed environments? Can synthetic communities be created to thrive on planets different from ours? These and other questions pervade major future developments within synthetic biology. The goal of engineering ecosystems is plagued with all kinds of technological, scientific and ethic problems. In this paper we consider the requirements for Terraformation, i. e. for changing a given environment to make it hospitable to some given class of life forms. Although the standard use of this term involved strategies for planetary terraformation, it has been recently suggested that this approach could be applied to a very different context: ecological communities within our own planet. As discussed here, this includes multiple scales, from the gut microbiome to the entire biosphere.

The use of spirocycles in drug discovery and medicinal chemistry has been booming in the last two decades. This has clearly translated in the landscape of approved drugs. Among two dozen clinically used medicines containing a spirocycle, 50% have been approved in the 21st century. The present review focuses on the notable synthetic routes to such drugs invented in industry and academia and is intended to serve as a useful reference source of synthetic as well as general drug information for researchers engaging in the design of new spirocyclic scaffolds for medicinal use or embarking upon analog syntheses inspired by the existing approved drugs.

In this paper, a new millimeter wave 3D imaging radar is proposed. The user just needs to move the radar along a circular track, a high resolution 3D imaging can be generated. The proposed radar uses the movement of itself to synthesize a large aperture in both the azimuth and elevation directions. It can utilize inverse Radon transform to resolve 3D imaging. To improve the sensing result, compressed sensing approach is further investigated. The simulation and experimental result further illustrated the design. Because a single transceiver circuit is needed, a light, affordable and high resolution 3D mmWave imaging radar is illustrated in the paper.

UAV network operation enables gathering and fusion from disparate information sources for flight control in both manned and unmanned platforms. In this investigation, a novel procedure for detecting runways and horizons as well as enhancing surrounding terrain is introduced based on fusion of enhanced vision system (EVS) and synthetic vision system (SVS) images. EVS and SVS image fusion has yet to be implemented real-world situations due to signal misalignment. We address this through a registration step to align the EVS and SVS images. Four fusion rules combining discrete wavelet transform (DWT) sub-bands are formulated, implemented and evaluated. The resulting procedure is tested on real EVS-SVS image pairs and pairs containing simulated turbulence. Evaluations reveal that runways and horizons can be detected accurately even in poor visibility. Furthermore, it is demonstrated that different aspects of the EVS and SVS images can be emphasized by using different DWT fusion rules. The procedure is autonomous throughout landing, irrespective of weather. We believe the fusion architecture developed holds promise for incorporation into head-up displays (HUDs) and UAV remote displays to assist pilots landing aircraft in poor lighting and varying weather. The algorithm also provided a basis rule selection in other signal fusion applications.

Heterodimeric approach has emerged as a promising method for simultaneously targeting multiple receptors on tumor cells using a single molecule. Simultaneous targeting of the prostate-specific membrane antigen (PSMA) and the gastrin-releasing peptide receptor (GRPr) holds the potential to improve the accuracy of prostate cancer diagnosis. This study aimed to develop and compare six alternative routes for stereoselective synthesis of heterobivalent conjugates designed to deliver the chelating agent DOTA to PSMA/GRPr receptors. The comparison of these alternative synthetic approach, considered such factors as efficiency, complexity, synthesis and purification characteristics, as well as yields of the target compounds has been made. Optimal conditions for the stereoselective synthesis of heterobivalent ligands to PSMA and GRP, which could serve as molecular platforms for the targeted delivery of therapeutic and/or diagnostic agents to these receptors, were determined. For synthesized heterobivalent ligand 26^x and heterobivalent conjugate with DOTA 27 complete signal assignment in ¹H, ¹³C, and ¹⁵N NMR spectra was achieved using 2D NMR techniques. Based on these data, comprehensive signal assignments were provided for all final compounds in their NMR spectra.

Synthetic cathinones, derived from cathinone found in the plant Catha edulis, represent the second-largest and most frequently seized group of new psychoactive substances. They are considered as β-keto analogs of amphetamine, sharing pharmacological effects with amphetamine and cocaine. This review describes the neurotoxic properties of synthetic cathinones, encompassing their capacity to induce neuroinflammation, dysregulate neurotransmitter systems, and alter in monoamine transporters and receptors. Additionally, it discusses the rewarding and abuse potential of synthetic cathinones drawing from findings obtained through various preclinical animal models, contextualized with other classical psychostimulants. The review also offers an overview of current abuse trends of synthetic cathinones on the illicit drug market, specifying the aspects covered, and underscores the risks they pose to public health.

Environmental DNA (eDNA) sampling has emerged as a powerful approach for monitoring biodiversity in the context of diverse terrestrial and aquatic ecosystems, and has broad potential for both environmental surveys and species management. eDNA studies focusing on plant and animal species have capitalized on analytical methodologies developed originally for metagenomic studies of microorganisms, and on technological improvements in sample collection. However, while eDNA studies have proliferated rapidly, efforts to standardize sampling and analytical methods are still nascent. Critically, fundamental data concerning the distribution and persistence of eDNA in different ecological contexts are lacking, complicating both confidence in species detection and comparability between studies. We propose that key deficits could be addressed by using well-designed synthetic DNA standards or tracers, which are widely used in fields ranging from medical diagnostics to hydrology. In-field application of a standardized mixture of barcoded synthetic DNA fragments of varying lengths and concentrations that are recovered concommitantly with eDNA sampling should provide critical yet missing data on environmental DNA distribution and turnover, as well as an internal molecular standard to enhance both species detection and comparability between eDNA studies.

Streptomyces sp. HNS054, which was previously isolated from a marine sponge, demonstrates vigorous growth and facile genetic modification. This study explores its potential as a marine ac-tinomycete chassis through complete genome sequencing and genetic engineering. With a 7.5 Mb genome containing 6678 predicted genes, 21 secondary metabolic biosynthetic gene clusters (BGCs), and 8 common site-specific recombination (SSR) system attB loci, HNS054 shows a close phylogenetic relation to S. griseoincarnatus strain RB7AG. Utilizing multiplexed site-specific ge-nome engineering (MSGE) and the CRISPR/Cas9 method, engineered strains derived from HNS054 (with three copies of the target BGCs) produce higher amounts of aborycin and ac-tinorhodin than S. coelicolor M1346 (containing three copies of the same BGCs). HNS054 stands out for its remarkable characteristics, including salt tolerance, rapid growth, and compatibility with synthetic biology tools, and positions it as a promising candidate for developing marine ac-tinomycete hosts to enhance secondary metabolite production.

Cytokines are a family of proteins which play a major role in the regulation of immune system, and enter the development of several diseases from rheumatoid arthritis to cancer and, more recently, COVID-19. Therefore, many efforts are currently being spent in therapy and diagnosis, producing inhibitory drugs, as well as biosensors for a rapid, poor invasive, and effective detection. In this regards, even more efficient cytokine receptors are under investigation. In this paper we analyze a set of receptors of cytokine IL-6, investigating their topological features by means of a theoretical approach. Our results suggest a topological indicator that may help in the identification of those receptors having the highest complementarity with the protein, a feature expected to ensure a stable binding. Furthermore, we propose and discuss the use of these receptors in an ideal experiment.

This comprehensive scientific review provides an in-depth analysis of both the natural compounds, pyrethrins, and their synthetic derivatives, pyrethroids, focusing on their classification, biosynthesis, mechanism of action, general and pharmaceutical uses, as well as their toxicity and environmental impact. Pyrethrins, derived from certain plant species, have long been recognized for their potent insecticidal properties. The review begins by examining the classification of pyrethrins and pyrethroids, elucidating their structural characteristics and unique features within the field of natural and synthetic compounds. The biosynthetic pathways responsible for producing pyrethrins in plants are discussed, highlighting the enzymatic reactions and genetic regulation involved. In addition, the synthesis of pyrethroid derivatives is explored, including both natural and synthetic sources and potential optimization strategies. Understanding the mechanisms of action by which pyrethrins and pyrethroids exert their insecticidal effects is a crucial aspect of this review. Complex interactions with the nervous systems of target organisms are examined, providing insights into their selective toxicity and modes of action. In addition, the various applications of these compounds are explored, from their use in agriculture for pest control to their incorporation into household insecticides and potential pharmaceutical applications. The review also critically evaluates the potential toxicity of pyrethrins and pyrethroids to human health. By consolidating current knowledge and research findings, this review provides a comprehensive understanding of the properties and applications of pyrethrins and pyrethroids, highlighting their benefits and risks, and the importance of responsible and sustainable use in various areas.

The study of ecosystems, both natural and artificial, has historically been mediated by population dynamics theories. In this framework, quantifying population numbers and related variables (associated with metabolism or biological-environmental interactions) plays a central role in measuring and predicting system-level properties. As we move towards advanced technological engineering of cells and organisms, the possibility of bioengineering ecosystems (from the gut microbiome to wildlands) opens several questions that will require quantitative models to find answers. Here, we present a comprehensive survey of quantitative modelling approaches for managing three kinds of synthetic ecosystems, sharing the presence of engineered strains. These include test tube examples of ecosystems hosting a relatively low number of interacting species, mesoscale closed ecosystems (or ecospheres), and macro-scale, engineered ecosystems. The potential outcomes of synthetic ecosystem designs and their limits will be relevant to different disciplines, including biomedical engineering, astrobiology, space exploration and fighting climate change impacts on endangered ecosystems. We propose a space of possible ecosystems that captures this broad range of scenarios and a tentative road map for open problems and further exploration.

Active flow control is a promising technology for reducing noise, emissions, and power consumption in various applications. To better understand the performance of synthetic jet actuators, a computational model that couples structural mechanics with electrostatics, pressure acoustics, and fluid dynamics has been needed. The model presented here has been validated against experimental data and then used to investigate the fluid behavior inside and outside the synthetic jet actuator cavity, impacts of thermoviscous losses on capturing the acoustic response of the actuator, and viability of different modeling methods of diaphragms in computational simulations. The results capture the feedback from the fluid onto the diaphragm and highlight the need for careful acoustic modeling.

Industrial Control Systems (ICS) are integral to managing and optimizing processes in various industries, including manufacturing, power generation, and more. However, the scarcity of widely adopted ICS datasets hampers research efforts in areas like optimization and security. This scarcity arises due to the substantial cost and technical expertise required to create physical ICS environments. In response to these challenges, this paper presents a groundbreaking approach to generating synthetic ICS data through a data-driven ICS network simulation. We circumvent the need for expensive hardware by recreating the entire ICS environment in software. Moreover, rather than manually replicating the control logic of ICS components, we leverage existing data to autonomously generate control logic. The core of our method involves the stochastic setting of setpoints, which introduces randomness into the generated data. Setpoints serve as target values for controlling the operation of the ICS process. This approach enables us to augment existing ICS datasets and cater to the data requirements of machine learning-based ICS intrusion detection systems and other data-driven applications. Our simulated ICS environment employs virtualized containers to mimic the behavior of real-world PLCs and SCADA systems, while control logic is deduced from publicly available ICS datasets. Setpoints are generated probabilistically to ensure data diversity. Experimental results validate the fidelity of our synthetic data, emphasizing its ability to closely replicate temporal and statistical characteristics of real-world ICS networks. In conclusion, this innovative data-driven ICS network simulation offers a cost-effective and scalable solution for generating synthetic ICS data. It empowers researchers in the field of ICS optimization and security with diverse, realistic datasets, furthering advancements in this critical domain. Future work may involve refining the simulation model and exploring additional applications for synthetic ICS data.

This work presents the possibility of using a synthetic membrane for pretracing mucosal penetration studies. The permeability of two types of membranes, porcine oral mucosa and a synthetic Nuclepore membrane, to water was compared. Moreover, the water permeability of membranes modified with waterproofing formulations was measured to study their ability to protect against the penetration of viruses, toxins, etc. A very good correlation was obtained between the transmucosal water loss (TMWL) values of the artificial membrane and the mucosa. These results support the possible use of this synthetic membrane in the screening of the water permeability of formulations. In addition, studies of the permeation of different actives, drugs and biocides through the two membranes were carried out, and these results were compared with their skin permeation data. The synthetic membrane does not seem to discern between compounds in terms of permeability, which could be due to the lack of lipids in the composition of this synthetic membrane. Therefore, Nuclepore alone cannot be used as a model for the release of actives. Additionally, the permeation of caffeine through intact or modified membranes incorporating waterproofing formulations was also studied. In this case, similar permeation profiles through the synthetic membrane and mucosa were found. The results from these assays should lend support to the use of this synthetic membrane when screening formulations to be applied in oral penetration studies.

In this work, we present a transceiver front-end in SiGe BiCMOS technology that can provide an ultra-wide bandwidth of 100 GHz at millimeter-wave frequencies. The front-end employs a novel configuration for low-loss distribution of broadband generated pulses as well as coherent spatial combining of received pulses. This leads to the realization of a fully integrated ultra-high-resolution imaging chip for biomedical applications. We realized an ultra-wide imaging bandwidth of 100 GHz by the integration of two adjacent, disjointed frequency sub-bands of 10–50 GHz and 50–110 GHz respectively. The transceiver front-end is capable of both transmit (TX) and receive (RX) operations. This is a key building-block for a scalable system in which a unit cell is repeated in the X and Y directions resulting in less power and area consumption. The imaging elements were designed and fabricated in Global Foundry 130-nm SiGe 8XP BiCMOS process technology.

CT scans are currently the most common imaging modality used for suspected stroke patients due to their short acquisition time and wide availability. However, MRI offers superior tissue contrast and image quality. In this study, eight deep learning models are developed, trained, and tested using a dataset of 181 CT/MR pairs from stroke patients. The resultant synthetic MRIs generated by these models are compared through a variety of qualitative and quantitative methods. The synthetic MRIs generated by a 3D UNet model consistently demonstrated superior performance across all methods of evaluation. Overall, the generation of synthetic MRIs from CT scans using the methods described in this paper produces realistic MRIs that can guide the registration of CT scans to MRI atlases. The synthetic MRIs enable the segmentation of white matter, gray matter, and cerebrospinal fluid using algorithms designed for MRIs, exhibiting a high degree of similarity to true MRIs.

InSAR and associated analytic methods enable relative surface deformation measurements from low Earth orbit with a potential accuracy of centimeters to millimeters. However, assessing the actual accuracy of individual points can be quite difficult. The analytic methods are complicated enough that na¨ıve analytic error propagation is infeasible, and, in many settings, InSAR practitioners lack sufficient ground truth to assess results. Phase noise due to partial decorrelation from changes in the scattering properties of the ground is a prominent source of accuracy loss. In this paper we present a method to assess the loss of precision due to this component of phase noise. The proposed method consists of generating synthetic data whose statistical properties match that of the actual input SAR data stacks, and then using the synthetic data for an ensemble calculation. The spread of the results of the ensemble calculation indicates the loss of precision. We show examples of the ensemble analysis at a mining operation in South Africa, and demonstrate the ability to assess the most reliable methods for particular points of interest using this ensemble analysis and the ability to filter out points based on the width of the spread of results

In organic synthesis, due to their high electrophilicity and leaving group properties, halogens play pivotal roles in the activation and structural derivations of organic compounds. Recently, cyclizations induced by halogen groups that allow the production of diverse targets and the structural reorganization of organic molecules have attracted significant attention from synthetic chemists. Electrophilic halogen atoms activate unsaturated and saturated hydrocarbon moieties via the generation of halonium intermediates, followed by the attack of carbon-, nitrogen-, oxygen-, and sulfur-containing nucleophiles to give highly functionalized carbo- and heterocycles. Interestingly, new transformations of halogenated organic molecules that can control the formation and stereoselectivity of the products according to the difference in the size and number of halogen atoms have recently been discovered. These unique cyclizations may possibly be used as efficient synthetic strategies with future advances. In this review, innovative reactions controlled by halogen groups are discussed as a new concept in the field of organic synthesis.

The hybrid seeds of several important crops with supreme qualities, including yield, biotic and abiotic stress tolerance, have been cultivated from decades. Thus far, a major challenge with hybrid seed, it does not hold ability to produce plants with same qualities over subsequent generations. Apomixis exist naturally an asexual mode of reproduction in flowering plants via avoiding meiosis and ultimately leads to seed production. Apomixis possess potential to preserve hybrid vigor for multiple generations for economically important plant genotypes. The evolution and genetics of asexual seed production is unclear and need much more efforts to find its genetic architecture. To fix hybrid vigor synthetic apomixis has been suggested an alternative. The development of MiMe (Mitosis instead of Meiosis) genotypes are utilized further for clonal gametes production. However, the identification and parental origin of genes responsible for synthetic apomixis are less known and need further understanding. Genome modifications utilizing genome editing technologies (GETs) like clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (cas9) a reverse genetics tool has paved way to utilize emerging technologies in plant molecular biology. From the last decade, several genes in important crops have been successfully edited. The vast availability of GETs has made the functional genomics studies easy to conduct in crops important for food security. The disruption of expression of genes specific to egg cell MATRILINEAL (MTL) or BABY BOOM1 (BBM1) through CRISPR/Cas genome editing system can promote haploid plants. The establishment of synthetic apomixis by engineering MiMe genotype by genome editing BBM1 expression or disruption of MTL leads toward clonal seed production. In present review, we discussed the current development in plants by utilizing CRISPR/Cas9 technology and its possibility of promoting apomixis in crops to preserve hybrid vigour. In addition to this, genetics, evolution, epigenetic modifications and strategy for MiMe genotype development has been discussed in detail.

In this paper we develop and explore a methodical pipeline for swimmer localisation in outdoor environments. The developed framework is intended to be used for enhancing swimmer safety. A main issue we deal with by the proposed approach is the lack of real world training data in such outdoor environments. Natural lighting changes, dynamic water textures and possibly barely visible swimming persons are key elements to approach. We account for these difficulties by adopting an effective background removal technique with available training data. This allows us to edit swimmers into natural environment backgrounds for the use in subsequent image augmentation. We created 17 training datasets with real images, synthetic images and a mixture of both to investigate different aspects and characteristics of the proposed approach. The datasets are used to train a YOLO architecture for the possible future application in real-time detection. The trained framework is then tested and evaluated on outdoor environment imagery acquired by a safety drone to investigate and confirm the usefulness for outdoor swimmer localisation.

In addressing the challenges of data scarcity in biometrics, this study explores the generation of synthetic palmprint images as an efficient, cost effective, and privacy preserving alternative to real-world data reliance. Traditional methods for synthetic biometric image creation primarily involve orientation modifications and filter applications, with no established method specific to palmprints. We introduced the utilization of the “Style-based generator”, StyleGAN2-ADA, from the StyleGAN series, renowned for generating high-quality images. Furthermore, we explore the capabilities of its successor, StyleGAN3, which boasts enhanced image generation, facilitating smooth and realistic transitions. By comparing the performance of StyleGAN3 on public dataset, we aim to establish the most efficient generative model for this purpose. Evaluations were conducted using the SIFT (Scale-Invariant Feature Transform) algorithm into our evaluation framework. Preliminary findings suggest that StyleGAN3 offers superior generative capabilities, enhancing equivariance in synthetic palmprint generation.

Several studies in computer vision have examined specular removal, which is crucial for object detection and recognition. This research has traditionally been divided into two tasks: specular highlight removal, which focuses on removing specular highlights on object surfaces, and reflection removal, which deals with specular reflections occurring on glass surfaces. In reality, however, both types of specular effects often coexist, making it a fundamental challenge that has not been adequately addressed. Recognizing the necessity of integrating specular components handled in both tasks, we constructed a Specular-Light (S-Light) DB for training single-image-based deep learning models. Moreover, considering the absence of benchmark datasets for quantitative evaluation, the Multi-Scale Normalized Cross Correlation (MS-NCC) metric, which considers the correlation between specular and diffuse components, was introduced to assess the learning outcomes.

Cellular organisms possess intricate DNA damage repair and tolerance pathways to manage various DNA lesions arising from endogenous or exogenous sources. Dysregulation of these pathways is associated with cancer development and progression. Synthetic lethality (SL), a promising cancer therapy concept, involves exploiting the simultaneous functional loss of two genes for selective cell death. PARP inhibitors (PARPis) have demonstrated success in BRCA-deficient tumors. Cisplatin (CPT), a widely used chemotherapy agent, forms DNA adducts and crosslinks, rendering it effective against various cancers but less so for prostate cancer (PCa) due to resistance and toxicity. Here, we explore the therapeutic potential of TLK1, a kinase upregulated in androgen-insensitive PCa cells, as a target for enhancing CPT-based therapy. TLK1 phosphorylates key homologous recombination repair (HRR) proteins RAD54L and RAD54B, critical for HRR alongside RAD51. The combination of CPT with TLK1 inhibitor J54 exhibits SL in androgen-insensitive PCa cells. The formation of double-strand break intermediates during inter-strand crosslink processing necessitates HRR for effective repair. Therefore, targeting TLK1 with J54 enhances the SL of CPT by impeding HRR, leading to increased sensitivity in PCa cells. These findings suggest a promising approach for improving CPT-based therapies in PCa, particularly in androgen-insensitive cases. By elucidating the role of TLK1 in CPT resistance, this study provides valuable insights into potential therapeutic targets to overcome PCa resistance to CPT chemotherapy. Further investigations into TLK1 inhibition in combination with other DNA-damaging agents may pave the way for more effective and targeted treatments for PCa and other cancers that exhibit resistance to traditional chemotherapy agents.

The concerning rise in emergence and prevalence of resistant strains to drugs of M. tuberculosis has ,the prompted researchers to look for new and effective treatments. With this motive, biscoumarins were identified as the lead molecules on a whole-cell-based screening of several less explored low molecular weight bioactive compounds against M. tuberculosis strains. Among the screened biscoumarins, the highest dock score derivatives were synthesized (a-h) using a programmable microwave synthesizer for better yields and reaction control. The synthesized derivatives were evaluated against H37Rv, H37Ra, M. smegmatis, an MDR surrogate model, and other bacterial strains for the structure-activity response. Assessment of the synthesized library against mycobacterial strains led to the identification of compounds (f and d) as lead anti-tuberculosis agents. Compounds (f and d) exhibited less toxicity against human cell lines. At the same time, it displayed enjoyable activity wherein MIC concentrations were observed to be 16- and 32 µg/mL against the susceptible H37Rv, and H37Ra strains of M. tuberculosis and MIC value of 128 µg/mL for M. smegmatis, respectively. For mechanistic insights and identification of drug binding targets, molecular docking and dynamic simulations were employed for a panel of 16 mycobacterial enzymes essential for mycobacterial growth and survival. These in silico studies revealed the DprE1 enzyme as a druggable target for the anti-tuberculosis activity of the selected biscoumarins derivatives. Further investigation is underway in our laboratory, leading to its development as an anti-tuberculosis drug (animal model studies).

Accurate lithium battery diagnosis and prognosis is critical to increase penetration of electric vehicles and grid-tied storage systems. They are both complex due to the intricate, nonlinear, and path-dependent nature of battery degradation. Data-driven models are anticipated to play a significant role in the behavioral prediction of dynamical systems such as batteries. However, they are often limited by the amount of training data available. In this work, we generated the first big data comprehensive synthetic datasets to train diagnosis and prognosis algorithms. The proof-of-concept datasets are over three orders of magnitude larger than what is currently available in the literature. With benchmark datasets, results from different studies could be easily equated, and the performance of different algorithms can be compared, enhanced, and analyzed extensively. This will expend critical capabilities of current AI algorithms, tools, and techniques to predict scientific data.

Genome-wide association studies (GWAS) have identified and reproduced thousands of diseases associated loci but many of them are not directly interpretable due to the strong linkage disequilibrium among variants. Transcriptome-wide association studies (TWAS) incorporated expression quantitative trait loci (eQTL) cohorts as reference panel to detect associations with the phenotype at the gene level and were gaining popularity in recent years. For nicotine addiction, several important susceptible genetic variants were identified by GWAS, but TWAS that detected genes associated with nicotine addiction and unveiled the underlying molecular mechanism were still lacking. In this study, we used eQTL data from the Genotype-Tissue Expression (GTEx) consortium as reference panel to conduct tissue specific TWAS on cigarettes per day (CPD) over 13 brain tissues in two large cohorts: UK Biobank (UKBB; N=142,202) and the GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN; N=143,210), and then meta-analyzed the results across tissues while considering the heterogeneity across tissues. We identified three major clusters of genes with different meta-patterns across tissues consistent in both cohorts, including homogenous genes associated with CPD in all brain tissues, partially homogeneous genes associated with CPD in cortex, cerebellum and hippocampus tissues, and lastly the tissue-specific genes associated with CPD in only few specific brain tissues. Downstream enrichment analyses on each gene cluster identified unique biological pathways associated with CPD and provided important biological insights into the regulatory mechanism of nicotine dependence in the brain.

Environmental effects and climate change are lately representing an increasing strain of the coastal areas which topography strongly depends on these conditions. However, the processes by which weather and environmental phenomena influence the highly variable beach morphology are still unknown. A continuous monitoring of the beach environment is necessary to implement protection strategies. This paper presents the results of an innovative study performed on a coastal area using satellite remote sensing data with the aim of understanding how environmental phenomena affect beaches. Two-years of synthetic aperture radar (SAR) Sentinel-1 images are used over a test area in Noordwijk, the Netherlands. At the same time as the SAR acquisitions, information on tidal and weather conditions are collected and integrated from nearby meteorological stations. Dedicated codes are implemented in order to understand the relationship between the SAR amplitude and the considered phenomena: wind, precipitation, tidal conditions. Surface roughness is taken into account. The results indicate a strong correlation between the amplitude and the wind. No particular correlation or trend could be noticed in the relation with the precipitation. The analysis of the amplitude also shows a decreasing trend moving from the dry area of the beach towards the sea and the correlation coefficient between the amplitude and the tide level gets negative with the increase of the water content.

The capacity and the mechanism of the adsorption of aqueous barium (Ba), cobalt (Co), strontium (Sr) and zinc (Zn) by Ecuadorian (NatAllo) and synthetic (SynAllo-1 and SynAllo-2) allophanes were studied as a function of contact time, pH and metal ion concentration using kinetic and equilibrium experiments. The mineralogy, nano-structure and chemical composition of the allophanes were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, transmission electron microscopy and specific surface area analyses. The evolution of adsorption fitted to a pseudo-first-order reaction kinetics, where equilibrium between aqueous metal ions and allophane was reached within < 10 min. The metal ion removal efficiencies varied from 0.7 to 99.7 % at pH 4.0 to 8.5. At equilibrium, the adsorption behavior is better described by the Langmuir model than by the Dubinin-Radushkevich model, yielding sorption capacities of 10.6, 17.2 and 38.6 mg/g for Ba^(2+), 12.4, 19.3 and 29.0 mg/g for HCoO_2^-, 7.2, 15.9 and 34.4 mg/g for Sr^(2+) and 20.9, 26.9 and 36.9 mg/g for Zn^(2+), respectively, by NatAllo, SynAllo-2 and SynAllo-1. The uptake mechanism is based on a physical adsorption process. Allophane holds great potential to remove aqueous metal ions and could be used instead of zeolites, montmorillonite, carbonates and phosphates for wastewater treatment.

Providing data on usage patterns is key to assessing the reduced-risk potential of novel tobacco and nicotine products at a population level. We performed a nationwide cross-sectional survey of the general population in Japan to assess usage patterns after the introduction of tobacco heating products (THPs). Eligible participants were Japanese residents, aged 20 years or older who consented to complete the survey. Individuals living in institutions were excluded. A three-stage probability sampling method was applied that was geographically stratified by street blocks proportionate to population density. Respondents self-reported patterns of product use and reasons for THP use. Complete responses were available from 5,306 individuals, of whom 933.5 (17.6%) were current users, 984.2 (18.5%) were former users and 3388.4 (63.9%) were never users of tobacco products. Cigarettes were used by 14.6% of current tobacco product users and THPs by 5.3%. Cigarettes and THPs were used exclusively by 64.5% and 12.2%, respectively, and both were used by 12.7%. The most common reasons reported for THP use were perceived reduction in harm to self and others compared to cigarettes. While the prevalence of cigarette use in Japan is decreasing, THPs seem to be increasingly used as long-term alternatives to cigarette smoking.

The idea that the Earth system self-regulates in a habitable state was proposed in the 1970s by James Lovelock, who conjectured that life plays a self-regulatory role on a planetary-level scale. A formal approach to such hypothesis was presented afterwards under a toy model known as the Daisyworld. The model showed how such life-geosphere homeostasis was an emergent property of the system, where two species with different properties adjusted their populations to the changing external environment. So far, this ideal world exists only as a mathematical or computational construct, but it would be desirable to have a real, biological implementation of Lovelock's picture beyond our one Biosphere. Inspired in the exploration of synthetic ecosystems using genetic engineering and recent cell factory designs, here we propose such a living, microbial Daisyworld. This is based on a synthetic microbial ecosystem using pH as the external, abiotic control parameter. Several case studies are considering, including two, three and multiple species assemblies. Despite that oscillatory dynamics and chaos emerge in the latter case, it is shown that global regulation is also achieved in most cases as species diversity increases. The alternative implementations and their implications of this model in other synthetic biology scenarios, including ecosystem engineering, are outlined.

Abstract ObjectivesThe aim of this perspective is to report the use of synthetic data as a viable method in women’s health given the current challenges linked to obtaining life-course data within a short period of time and accessing electronic healthcare data. Methods We used a 3-point perspective method to report an overview of data science, common applications, and ethical implications. Results There are several ethical challenges linked to using real-world data, consequently, generating synthetic data provides an alternative method to conduct comprehensive research when used effectively. The use of clinical characteristics to develop synthetic data is a useful method to consider. Aligning this data as closely as possible to the clinical phenotype would enable researchers to provide data that is very similar to that of the real-world. Discussion Population diversity and disease characterisation is important to optimally use data science. There are several artificial intelligence techniques that can be used to develop synthetic data. ConclusionSynthetic data demonstrates promise and versatility when used efficiently aligned to clinical problems. Therefore, exploring this option as a viable method in women’s health, in particular for epidemiology may be useful.

This paper provides a methodology for the production of synthetic images for training neural networks to recognise shapes and objects. There are many scenarios in which it is difficult, expensive and even dangerous to produce a set of images that is satisfactory for the training of a neural network. The development of 3D modelling software has nowadays reached such a level of realism and ease of use that it seemed natural to explore this innovative path and to give an answer regarding the reliability of this method that bases the training of the neural network on synthetic images. The results obtained in the two proposed use cases, that of the recognition of a pictorial style and that of the recognition of migrants at sea, leads us to support the validity of the approach, provided that the work is conducted in a very scrupulous and rigorous manner, exploiting the full potential of the modelling software. The code produced, which automatically generates the transformations necessary for the data augmentation of each image, and the generation of random environmental conditions in the case of Blender and Unity3D software, is available under the GPL licence on GitHub. The results obtained lead us to affirm that through the good practices presented in the article, we have defined a simple, reliable, economic and safe method to feed the training phase of a neural network dedicated to the recognition of objects and features, to be applied to various contexts.

Haemodynamic indices are widely used in clinical practice for deciding on a particular type of treatment. Low quality of the CT data and tachycardia complicate interpretation of the measured or simulated values. In this work, we present a novel approach for evaluating resistances in terminal coronary arteries. Using 14 measurements from 10 patients, we show that this algorithm retains the accuracy of 1D haemodynamic simulations in less detailed (truncated) geometric models of coronary networks. We also apply the variable systole fraction model to study the effect of elevated heart rate on the values of FFR, CFR and iFR. We conclude that tachycardia may produce both overestimation or underestimation of coronary stenosis significance.

Whether evaluating gridded population dataset estimates (e.g. WorldPop, LandScan) or household survey sample designs, a population census linked to residential locations are needed. Geolocated census microdata data, however, are almost never available and are thus best simulated. In this paper, we simulate a close-to-reality population of individuals nested in households geolocated to realistic building locations. Using the R simPop package and ArcGIS, multiple realizations of a geolocated synthetic population are derived from the Namibia 2011 census 20% microdata sample, Namibia census enumeration area boundaries, Namibia 2013 Demographic and Health Survey (DHS), and dozens of publicly available spatial datasets. Realistic household latitude-longitude coordinates are manually generated based on public satellite imagery. Simulated households are linked to latitude-longitude coordinates by identifying distinct household types with multivariate kmeans analysis, and modelling a probability surface for each household type using Random Forest machine learning methods. We simulate five realizations of a synthetic population in Namibia's Oshikoto region, including demographic, socioeconomic and outcome characteristics at the level of household, woman, and child. Comparison of variables in the synthetic population were made with 2011 census 20% sample and 2013 DHS data by primary sampling unit/enumeration area. We found that synthetic population variable distributions matched observed observations and followed expected spatial patterns. We outline a novel process to simulate a close-to-reality microdata census geolocated to realistic building locations in a low- or middle-income country setting to support spatial demographic research and survey methodological development while avoiding disclosure risk of individuals.

Fungal infections pose a significant threat to human health, particularly in immunocompromised individuals. Due to several factors, such as the inappropriate use of antimicrobial drugs, the emergence of resistance in microorganisms, and increasing demand for less cytotoxic antifungal agents for immunocompromised patients, antifungal research has gained significant attention in recent years. Antifungal peptides, and among them, cyclic peptides, are a class of antifungal agents that have been under development since the 1960s. Using cyclic peptides as a promising approach for combating antifungal resistance in pathogenic fungi has gained significant attention in recent years. The identification of antifungal cyclic peptides from various sources has been possible due to the widespread interest in peptide research in recent decades. It is increasingly important to evaluate the narrow to broad-spectrum antifungal activity and the mode of action of synthetic and natural cyclic peptides for both synthesized and extracted peptides. This short review aims to highlight some of the antifungal cyclic peptides isolated from bacteria, fungi, and plants, taking into consideration the progress made in peptide research. Additionally, it provides a summary of synthetic cyclic peptides with antifungal activity and discusses the potential future of utilizing combinations of antifungal peptides from different sources. The review underscores the need for further exploration of the novel therapeutic applications of these abundant and diverse cyclic peptides.

In terms of obtaining fuels as well as chemicals with or without catalysts at different conditions, the plum seed stands out as an alternative biomass source. Under varying heating rates (10, 50, and 100ºC min-1) and pyrolysis temperatures (400, 450, 500, 550 and 600 °C), the plum seed was pyrolysed at constant sweep gas flow at a constant rate (100 cm3min-1) in a tubular fixed bed reactor. According to the results, an oil yield reaching to a maximum of %45 was procured at the heating rate of 100 ºCmin-1 and the pyrolysis temperature of 550ºC in non-catalytic procedure. The catalytic pyrolysis was carried out in optimum conditions with two selected commercial catalysts, namely ZSM-5 and PURMOL-CTX and clinoptilolite (natural zeolite, NZ) with catalyst ratio of 10 % of raw material. Along with the catalyst addition, the quantity and the quality of bio-oil increased including the calorific value, removal of oxygenated groups, and hydrocarbon distribution. An increase related to the desirable products like phenols, alkene, and alkane and a decrease in undesirable products like acids were observed in the presence of catalysts. When all the results are considered and evaluated, using zeolite materials in the pyrolysis as catalysts is a recommendable option to achieve enhanced chemicals and fuels.

Ants of the genus Solenopsis are important invasive pests in the world. Due to their high dispersion capacity, aggressive behavior and because they feed on various sources of vegetable and animal protein, these insects have caused serious damage to public health and agriculture. The control has usually been carried out through the use of organosynthetic insecticides. However, due to the ecological and environmental impacts caused by the use these products, more sustainable alternatives have been sought for their control. Faced with these problems and due to the scarcity of registered products for the control of these insects, we aimed with this study to synthesize and evaluate the anticidal potential of carvacrol derivatives. The lethal and sublethal effects caused by these derivatives were compared with the essential oil of Lippia gracilis (50.7% carvacrol) and with the base molecule — carvacrol. Carvacryl benzoate was the most toxic derivative to Solenopsis sp. with an LD50 of 3.20 g/ mg. This compound was about 2 and 7.6 times, more toxic than carvacrol at the doses needed to kill 50 and 90% of populations, respectively. The workers of Solenopsis sp. showed a rapid reduction in survival when exposed to carvacrol (LT50 = 8.43h) and carvacryl benzoate (LT50 = 8.87h). Insects treated with sublethal doses of the compounds did not show significant effects on self-cleaning, allogrooming and aggregation, with the exception of those treated with L. gracilis essential oil. The oil increased self-cleaning and reduced allogrooming and aggregation. Ants treated with carvacrol and carvacryl benzoate showed greater distance and speed when compared to the control. These compounds decreased meanders and angular velocity. When live workers were exposed to dead individuals at the LD90 of the compounds, carvacryl benzoate was the derivative that most reduced insects survival, due to horizontal transfer. These results show the potential of the carvacrol derivative — carvacryl benzoate — for the alternative management of ants of the genus Solenopsis sp.

Nowadays, diamonds are widely used in science and technology. However, the properties of diamonds due to their defects are not fully understood. In addition to optical methods, positron annihilation spectroscopy (PAS) can be successfully used to study defects in diamonds. Positrons are capable of detecting vacancies, small and large clusters of vacancies induced by irradiation, by providing information about their size, concentration, and chemical environment. By mapping in the infrared (IR) range, it is possible to consider the admixture composition of the main inclusions of the whole plate. The article presents the results of the study of defects in synthetic diamond plates, one of which was irradiated by electrons. Presents data about the distribution of the defect concentration obtained by Infrared spectroscopy. PAS with a monochromatic positron beam can be used as a non-destructive technique of detecting defects (vacancy) distribution over the depth of diamond plates.

The analysis of microscopy images has always been an important yet time consuming process in in materials science. Convolutional Neural Networks (CNNs) have been very successfully used for a number of tasks, such as image segmentation. However, training a CNN requires a large amount of hand annotated data, which can be a problem for material science data. We present a procedure to generate synthetic data based on ad-hoc parametric data modelling for enhancing generalization of trained neural network models. Especially for situations where it is not possible to gather a lot of data, such an approach is beneficial and may enable to train a neural network reasonably. Furthermore, we show that targeted data generation by adaptively sampling the parameter space of the generative models gives superior results compared to generating random data points.

Dynamic hedging has been adopted by many insurance companies to mitigate the financial risks associated with variable annuity guarantees. In order to simulate the performance of dynamic hedging for variable annuity products, insurance companies rely on nested stochastic projections, which is highly computationally intensive and often prohibitive for large variable annuity portfolios. Metamodeling techniques have recently been proposed to address the computational issues. However, it is difficult for researchers to obtain real datasets from insurance companies to test metamodeling techniques and publish the results in academic journals. In this paper, we create synthetic datasets that can be used for the purpose of addressing the computational issues associated with the nested stochastic valuation of large variable annuity portfolios. The runtime used to create these synthetic datasets would be about 3 years if a single CPU were used. These datasets are readily available to researchers and practitioners so that they can focus on testing metamodeling techniques.

The leaves of Nicotiana glauca (Solanaceae) plant, are known for its major cause of health concern. This study investigated the antioxidant activity and polyphenols composition of aerial parts of N.glauca collected from its wild habitat in Jordan, using Methanol-Conventional (MC) and deep eutectic solvents (DESs) extraction methods in addition to nicotine content determination using UHPLC. The results have shown that the MC extract contains fewer total phenols and flavonoid content than the DES extract at ratio of 90% (0.1194 ±0.009 and 0.311± 0.020 mg/mL equivalent to gallic acid) and (0.01084±0.005 and 0.928 ± 0.09 mg/mL equivalent to rutin), respectively. Moreover, the study showed that the MC extract contains 635.07 ppm nicotine compared to the DES extraction method, which contains 1194.91 ppm. Both the MC and the DES extracts exhibited weak antioxidant activities with the highest was 33%inhibition equivalent to ascorbic acid was found for DES at (90%) ratio. The UHPLC-MS/MS analysis revealed the presence of variations in the detected compounds between the two extraction methods used. This study found that en-vironmentally friendly DES extraction of N. glauca produced higher phenol and flavonoid content than MC method, highlighting green chemistry methods' superior efficiency and environmental benefits for extracting valuable phytoconstituents.

Background: There is now evidence that immune and opioid systems show functional reciprocal relationships and that both systems may participate in the pathophysiology of major depression (MDD). Objective: The present study was carried out to delineate differences between MDD patients and healthy controls in dynorphin and kappa opioid receptor (KORs) in association with levels of β-endorphins and mu opioid receptors (MORs), interleukin-6 (IL-6) and IL-10. Method: The present study recruited 60 drug-free male participants with MDD aged 24-70 year and 30 age-matched healthy males as control group and measured serum levels of dynorphin, KOR, β-endorphin, MOR, IL-6 and IL-10. Results: Serum dynorphin, KOR, β-endorphin and MOR are significantly increased in MDD as compared with controls. The increases in the dynorphin/KOR system and β-endorhin/MOR system are significantly intercorrelated and are both strongly associated with increased IL-6 and IL-10 levels. Dynorphin, β-endorphin, KOR and both cytokines showed a good diagnostic performance for MDD versus controls, whereby both opioid peptides and cytokines show a bootstrapped (n=2000) area under the receiver operating curve of 0.972. KOR and the dynorphin/KOR system are both significantly decreased in depressed subjects with comorbid nicotine dependence. Conclusion: Our findings suggest that in MDD, immune activation is associated with a simultaneous activation of dynorphin/KOR and β-endorhin/MOR signaling and that these opioid systems may participate in the pathophysiology of depression by a) exerting immune regulatory activities attenuating the primary immune response; and b) modulating reward responses and mood as well as emotional and behavioral responses to stress.

Traditional asexual propagation of hops limits its phytosanitary quality and the concomitant plant availability. This scenario worsens with the global climate change. In this study we develop protocols for in vitro propagation of Humulus lupulus var. mapuche. Two explant types were evaluated: shoot tips, from field material collected in Río Negro province (Argentina), and nodal segments, from vitroplants. Different growth regulator, such as 6-Benzylaminopurine, gibberellic acid, indole-3-butyric acid and indole-3-acetic acid, was used to induce desired morphogenic responses. Additionally, the impact of abscisic acid application on acclimatization was assessed, and resulted in robust growth and reduced plant stress symptoms during ex vitro adaptation. Also, the study develops a protocol for synthetic seeds production, with storage at 4°C to enhance conservation and plant material transport, ensuring a constant supply of female plants. This comprehensive approach addresses current producer demands and emerging climate challenges. The findings highlight the fundamental role of in vitro multiplication of hops in improving plant material availability and quality, with significant implications for the brewing industry and related sectors.

Facial recognition systems are widely used systems around the globe. Their applications in real world scenarios like law enforcement, surveillance, ID card identification, information security, access control and many more has made them very important in today’s world. These systems have shown promising results and excellent performance; however, these systems need tremendous number of facial images for training before they are implemented in the real-world scenarios. The problem arises when we face lack of training images due to which the performance of such systems decreases exponentially. The problem becomes even worse when there is only one image per subject for training our facial recognition system, the probe image might contain variation like illumination, expression and disguise which are hard to be accurately recognized. Generative models have achieved great success for handling the lack of training data by generating synthetic data that resembles the original data. We have created a new method by fine tuning the basic Conditional Generative Adversarial Network (CGAN) to generate synthetic facial images provided only single image per subject. These synthetic facial images contain six variations that are smile, anger, stare, illumination and disguise. We increased the size of the dataset and then applied a convolutional neural network for facial recognition, which improved the accuracy of our system from 0.76 to 0.99.

The ability of deep learning to process vast data and uncover concealed malicious patterns has spurred the adoption of deep learning methods within the cybersecurity domain. Nonetheless, a notable hurdle confronting cybersecurity researchers today is the acquisition of a sufficiently large dataset to train deep learning models effectively. Privacy and security concerns associated with using real-world organization data have made cybersecurity researchers seek alternative strategies, notably focusing on generating synthetic data. Generative Adversarial Networks (GANs) have emerged as a prominent solution, lauded for their capacity to generate synthetic data spanning diverse domains. Despite their widespread use, the efficacy of GANs in generating realistic cyber attack data remains a subject requiring thorough investigation. Moreover, the proficiency of deep learning models trained on such synthetic data to accurately discern real-world attacks and anomalies poses an additional challenge that demands exploration. This paper delves into essential aspects of generative learning, scrutinizing their data generation capabilities, and conducts a comprehensive review to address the above questions. Through this exploration, we aim to shed light on the potential of synthetic data in fortifying deep learning models for robust cybersecurity applications.

Benzylsuccinate is generated in anaerobic toluene degradation by radical addition of toluene to fumarate and further degraded to benzoyl-CoA by a beta-oxidation pathway. Using metabolic modules for benzoate transport and activation to benzoyl-CoA and the enzymes of benzylsuccinate beta-oxidation, we established an artificial pathway for benzylsuccinate production in Escherichia coli, which is based of its degradation pathway running in reverse. Benzoate is supplied to the medium, but needs to be converted to benzoyl-CoA by an uptake transporter and a benzoate-CoA ligase or CoA-transferase. In contrast, the second substrate succinate is endogenously produced from glucose under anaerobic conditions, and the constructed pathway includes a succinyl-CoA:benzylsuccinate CoA-transferase that activates it to the CoA-thioester. We present first evidence for the feasibility of this pathway and explore product yields under different growth conditions. Compared to aerobic cultures, the product yield increased more than 1000-fold in anaerobic glucose-fermenting cultures and showed further improvement under fumarate-respiring conditions. An important bottleneck to overcome appears to be product excretion, based on much higher recorded intracellular concentrations of benzylsuccinate, compared to those excreted. While no export system is known for benzylsuccinate, we observed an increased product yield after adding an unspecific mechanosensitive channel to the constructed pathway.

The study of velocimetry is important for characterizing and comprehending the effects of fluid flow, and the Particle Image Velocimetry (PIV) technique is one of the primary approaches for understanding the velocity vector field in a test section. Commercial PIV systems are expensive, with one of the main cost factors being high-speed camera equipment capable of capturing images at high frames per second (fps), rendering them impractical for many applications. This study proposes an evaluation of utilizing smartphones as image acquisition systems for PIV technique application. An experimental setup inspired by the known angular displacement of synthetic particles is proposed. A stepper motor rotates a plate containing an image of synthetic particles on its surface. The motion of the plate is captured by the smartphone camera, and the images are processed using PIVlab-MatLab® software. The use of two smartphones is assessed, with acquisition rates of either 240 fps or 960 fps and varying angular velocities. The results were satisfactory for velocities up to 0.7 m/s at an acquisition rate of 240 fps and up to 1.8 m/s at 960 fps, validating the use of smartphones as a cost-effective alternative for the PIV technique.

Bitumen is produced from non-renewable natural resources, continuously deplete and intrigues researchers to look for alternative binders. Annually, tons of waste engine oil (WEO) and crumb rubber (CR) are discarded unsustainably and pose a significant environmental threat. Adding these industrial waste products to asphalt provides a safe and cost-effective way for their disposal and improves the bitumen's performance in parallel. This study uses various combinations of waste engine oil and crumb rubber with 60/70 penetration grade bitumen to produce a partially synthetic bitumen. Adhesion being one of the critical characteristics of the bituminous binder has been assessed using the bitumen bond strength test along with physical and rheological properties. Results showed that waste engine oil with crumb rubber inclusion increases penetration and decreases the softening point, viscosity, complex modulus, and bonding strength. Additionally, polyphosphoric acid (PPA) in smaller dosages was also incorporated into the optimum percentage of CR + WEO to improve the properties of the binder. The results confirm that binder modification with waste engine oil and crumb rubber can be more effective with PPA. It is concluded that 35% of waste can replace the virgin binder giving a cost-effective and environmentally friendly solution.

3,4-Dihydro-2(1H)-pyridones (3,4-DHPo) and their derivatives are privileged structures present in natural products, which has been increased its relevance due to its biological activity in front of a broad range of targets, but especially for its importance as synthetic precursors of a variety of compounds with marked biological activity. Taking into account the large number of contributions published over the years regarding this kind of heterocycle, here we presented a current view of 3,4-dihydro-2(1H)-pyridones (3,4-DHPo), which include general aspects such as those related to nomenclature, synthesis, and biological activity; but also highlighting the importance of DHPo as building blocks of other relevance structures.

Scattering has been always considered a problem in most of the imaging and holography systems. In this project, a 3D imaging system has been developed based on scattering against common beliefs. The 3D imaging system consists of only two components namely a scattering lens, fabricated by grinding the surface of a convex lens using sandpaper and a web camera. The point spread function (PSF) in the form of speckle distribution was recorded using a laser source in the first step. A synthetic object was selected which was convolved with the PSF in a computer to generate the object intensity distribution. The image of the object was reconstructed by processing the PSF and object intensity distribution using a computational reconstruction method called non-linear reconstruction. The recorded PSF was scaled and the process was repeated for a different synthetic object. The concept was extended to 3D by summing the object intensity distributions generated using PSFs with different scaling factors. The image at different planes can be reconstructed using the PSFs corresponding to that plane.

A common reactor type in the chemical and process industry is the fixed-bed reactor. Accurate modeling can be achieved with particle-resolved Computational Fluid Dynamic (CFD) simulations. However, the underlying bed morphology plays a paramount role. Synthetic bed-generation methods are much more flexible and faster than image-based approaches. In this study, we look critically at the two different bed generation methods: Discrete Element Method (DEM) (in the commercial software STAR-CCM+) and the rigid-body model (in the open-source software Blender). The two approaches are compared in terms of synthetically generated beds with experimental data of overall and radial porosity, particle orientation, as well as radial velocities. Both models show accurate agreement for the porosity. However, only Blender shows similar particle orientation than the experimental results. The main drawback of the DEM is the long calculation time and the shape approximation with composite particles.

Advances in genetic engineering have placed synthetic biology at a prime position to develop new products, materials, and services that could contribute to the 2030 UN Sustainable Development goals. These include novel materials for water purification, new bio-based products to replace toxic industrial chemicals, and engineered organisms for bioremediation. Supporting the development of synthetic biology initiatives in developing countries is needed to ensure these benefits are open to all.

The Surface Water and Ocean Topography (SWOT) mission, to be launched in 2021, will provide water surface elevations, slopes, and river width measurements for rivers wider than 100 m. In this study, synthetic SWOT data are assimilated in a regional hydrometeorological model in order to improve the dynamics of continental waters over the Garonne catchment, one of the major French catchments. The aim of this paper is to demonstrate that the sequential assimilation of SWOT-like river depths allows the correction of river bed roughness coefficients and thus simulated river depths. An extended Kalman Filter is implemented and the data assimilation strategy was applied to four experiments of gradually increasing complexity regarding observation and model error over the 1995-2000 period. With respect to a “true” river state, assimilating river depths allows the proper retrieval of constant and spatially distributed roughness coefficients with a root mean square error of 1 m1/3 s-1, and the estimation of associated river depths. It was also shown that river depth differences can be assimilated, resulting in a higher root mean square error for roughness coefficients with respect to the true river state. The last study shows how one can take into account more realistic sources of SWOT error measurements, in particular the importance of the estimation of the tropospheric water content in the process.

A hallmark of eutherian pregnancy is its dependency on elevated progesterone levels for its entire length. This fact substantially affected the evolution of pregnancy and even the life history of eutherians. Progesterone synthesis by the ovarian corpus luteum, however, long predates all origins of vertebrate viviparity, which requires reconsidering the role of the corpus luteum and progesterone before and beyond placental mammals. Pregnancy originated repeatedly by co-opting the ancestral luteal phase of the ovarian cycle. Therefore, it represents a physiological equivalent and “serial homolog” of the nonpregnant luteal phase. Because of this relationship, we argue that understanding the origin and evolution of pregnancy can substantially benefit from examining the evolution and regulation of the corpus luteum during nonpregnancy. In the first part of this paper, we investigate what is known about the evolution of the corpus luteum and its changing regulation and function across vertebrates, covering both pregnant and nonpregnant cycles wherever possible. Studying pregnancy in the context of the nonpregnant cycle reveals the key evolutionary innovation that facilitated the characteristically long eutherian pregnancies: the regulatory decoupling of the pregnant and nonpregnant cycle, that is, the evolution of maternal recognition of pregnancy. Only after the two cycles became separately modifiable, could gestation length increase without deleteriously extending the time to the next fertile phase. In this review, we argue that, assuming selection for body size increase, the origin of MRP led to a punctuated increase of gestation length, which could imply that we overestimate pregnancy length in the eutherian ancestor when using conventional phylogenetic inference methods. Mechanistically, decoupling between cycles means that the progesterone-dominated phase in pregnancy is extended beyond that of nonpregnancy. In eutherians, this is achieved by extending the lifespan of progesterone-producing corpus luteum, providing additional corpora lutea, extraovarian sources of progesterone, or a combination of these. Alternatively, it can also be accomplished by shortening the nonpregnant cycle. The differences in underlying mechanisms for decoupling among the major eutherian lineages suggest that they originated independently, which leads us to conclude that eutherian gestation consists of parts that are not homologous across eutherians. Consequently, eutherian gestation length is not a homologous trait that can be productively compared across species directly. Finally, we find no evidence for an increase in gestational length due to maternal-fetal conflict. Rather, as long appreciated, body size explains a major portion of the variation in gestation length in eutherians. This suggests that the increase in eutherian gestation length was driven by the need to accommodate an increasing body size, a well-documented trend (Cope’s rule), once independent evolution of pregnant and non-pregnant cycles became possible.

The heavy transition metal tantalum (Ta) offers a wide range of applications, especially in the field of electronics, e.g. Ta capacitors with a comparatively long life-time. Therefore, electronic scrap containing these components is a potentially valuable secondary source of this metal. However, the recovery of Ta, as other critical raw materials, that are lost in pyrometallurgical slags can be a challenging process. As a way of overcome this, the "engineered artificial minerals" EnAM approach is proposed by first searching for suitable host minerals and characterizing them. A favorable prerequisite is the enrichment of the desired element(s) in compounds that have particularly suitable properties for this purpose, such as morphology, crystal size, surface or magnetic properties. Subsequently, the slag system is adapted (e.g. chemism, solidification curve, cooling and holding times) to optimize this compound. This paper presents the results of mineralogical characterization of Ta-containing iron (Fe)-rich synthetic slags in reducing environment under different cooling rates, and describes and discusses the incorporation of Ta into the different compounds detected by powder X-ray diffraction (PXRD) and electron beam microanalysis (EPMA). Additionally, the speciation of Fe and Ta was accessible through X-Ray absorption near edge structure (XANES) spectroscopy. EPMA also provides a first semi-quantitative assessment of the Ta distribution in these individual compounds. According to this, depending on the cooling rate the enrichment factor is highest in tantalite/perovskite-type oxides (FexTayO6, CaxFeyTazO3) with up to 60 wt.% Ta and ‘tantalomagnetite’ (FeII(FeIII(2-5/3xTax)O4) with a maximum of ~ 30 wt.% Ta (only fast cooling). This is followed by a perovskite-like silicon containing oxide (XYO3) with 12-15 wt.-% Ta (only slow cooling), and a hedenbergite-like compound (XYZ2O6) with varying content of 0.3 - 7 wt.-%. The Ta-concentration in pure Fe, Fe(1-x)O, hercynitic spinel and hematite is negligible. Since a larger fraction of potentially amorphous hedenbergitic matrix is formed at faster cooling, in this case the main Ta is enriched in this compound despite the significantly lower Ta content.

In recent years, Synthetic Aperture Radar (SAR) has received attention in the Automatic Target Recognition (ATR) field due to its ability to acquire images both day and night, combined with the superior resolution offered by the latest sensors. However, despite advances, there remains a deficiency in dataset quality and quantity. This has necessitated the use of simulated data to overcome challenges associated with obtaining large quantities of high-quality images of targets and their subsequent labeling. In this study, we trained a Convolutional Neural Network (CNN) using a simulated dataset, subsequently employing it to classify real images from the MSTAR dataset. Traditional training methodologies often struggle with generalization when confronted with domain disparities between simulated and real data. To mitigate this, we exploited Margin Disparity Discrepancy (MDD), a domain adaptation technique not previously explored in SAR context. Findings from this study showcased a 13% increase in classification accuracy and improved generalization using MDD. Through Explainable AI (XAI) techniques such as t-SNE and other metrics like Kullback Leibler Divergence (KLD), we revealed a more distinct alignment of feature spaces between the two domains after domain adaptation, emphasizing MDD’s role in enhancing model accuracy and generalization.