Permafrost thaw is an important aspect of Earth's carbon cycles. Initial estimates suggest that permafrost thaw could contribute anywhere between 20 to 500 Gt of CO2-eq by 2100. These estimates are all fundamentally centered around one number: active layer thickness (ALT). The deeper the ALT, the more emissions. Unfortunately, ALT is a highly spatially heterogeneous number and determined by numerous thermal, soil hydrology, and geomorphological effects. The remotely sensed active layer thickness (ReSALT) algorithm was introduced in 2010 to provide scientists with a way to model ALT heterogeneously at meter-scale resolution. However, upon inspection, this work shows that ReSALT's modeling approach is self-inconsistent. This work then introduces SCReSALT (Self-Consistent ReSALT) to solve that problem. Experimental comparisons to a past study in Utqiagvik (formerly Barrow), Alaska show significant improvement and suggest that SCReSALT should replace ReSALT. Code to reproduce all results can be found at https://github.com/jmathur25/permafrost-prediction.

Biochirality is evident in the hierarchical relation of molecular and cellular physiology during organism development and aging. Chirality influences the higher levels of biological processes, such as perception, memory and cognition, through intermolecular interactions between DNA, proteins, and lipids. At the molecular level, an organism's aging is the accumulation of macro-molecules with the aberrant composition, chirality, and folding. Cellular aging is driven by the non-physiological phase transitions (PhTs) withing membrane-bound and membrane-less compartments. Genomic instability and protein aging, as the interconnected root-causes of cell and organism aging, share two essential feature – spontaneous nature and accumulation over a lifetime. Consequently, we will analyze the interaction between the enzymatic (Enz) and spontaneous (Sp) post-translational modifications (PTMs^Enz and PTMs ^Sp). Both forms of PTMs significantly contribute to the balance of L- and D-amino acids (L/D-AAs) in organisms, modulating the functions of nervous and immune systems. The most abundant form of PTM - enzymatic phosphorylation is bio-chemically associated with the spontaneous racemization (Rz^Sp). The crass talk of enzymatic phosphorylation and spontaneous racemization, as an essential determinant of protein aging and aggregation, associated with the aberrant autophagy, apoptosis, and cell signaling, is discussed in this review.

Post-translational modifications (PTMs) represent a cornerstone in the complexity of the proteome, significantly contributing to diversifying protein structure and function. PTMs can significantly influence protein function, stability, localization, and interactions with other molecules. Therefore, it is important when choosing a protein expression system to ensure the precise incorporation of PTMs during protein synthesis, which is paramount for producing biologically active proteins. Cell-free protein synthesis (CFPS) system has emerged as a powerful protein synthesis platform and research toolkit in synthetic biology. The open nature of the system allows the reaction environment to be tailored to any protein of interest to promote specific PTMs, thus allowing for the production of a protein with the desired modifications. This review presents various PTMs achieved in the CFPS systems, providing insights into the current challenges, successes, and future prospects.

Clean production of renewable fuels is a great challenge of our scientific community. Iridium complexes have demonstrated a superior catalytic activity in the water oxidation (WO) reaction, which is a crucial step in water splitting process. Herein we have used a defective zirconium MOF with UiO-66 structure as support of a highly active Ir complex based on EDTA with formula [Ir(HEDTA)Cl]Na. The defects are induced by the partial substitution of tereftalic acid with smaller formiate groups. Anchoring of the complex occurs through a post-synthetic exchange of formiate anions, coordinated at the zirconium clusters of the MOF, with the free carboxylate group of the [Ir(HEDTA)Cl]-complex. The modified material was tested as heterogenous catalyst for the WO reaction by using Cerium Ammonium Nitrate as sacrificial agent. Although TOF and TON values are comparable to those of other iridium heterogenized catalysts, the MOF exhibits iridium leaching not limited at the first catalytic run, as usually observed, suggesting a lack of stability of the hybrid system under strong oxidative conditions.

Manual visual inspections typically conducted after an earthquake are high-risk, subjective, and time-consuming. Delays from inspections often exacerbate the social and economic impact of the disaster on affected communities. Rapid and autonomous inspection using images acquired from unmanned aerial vehicles offer the potential to reduce such delays. Indeed, a vast amount of re-search has been conducted toward developing automated vision-based methods to assess the health of infrastructure at the component and structure level. Most proposed methods typically rely on images of the damaged structure, but seldom consider how the images were acquired. To achieve autonomous inspections, methods must be evaluated in a comprehensive end-to-end manner, incorporating both data acquisition and data processing. In this paper, we leverage recent advances in computer generated imagery (CGI) to construct a 3D synthetic environment for simulation of post-earthquake inspections that allows for comprehensive evaluation and valida-tion of autonomous inspection strategies. A critical issue is how to simulate and subsequently render the damage in the structure after an earthquake. To this end, a high-fidelity nonlinear finite element model is incorporated in the synthetic environment to provide a representation of earthquake-induced damage; this finite element model, combined with photo-realistic rendering of the damage, is termed herein a physics-based graphics models (PBGM). The 3D synthetic en-vironment with PBGMs provide a comprehensive end-to-end approach for development and validation of autonomous post-earthquake strategies using UAVs, including: (i) simulation of path planning of virtual UAVs and image capture under different environmental conditions; (ii) au-tomatic labeling of captured images, potentially providing an infinite amount of data for training deep neural networks; (iii) availability of the ground truth damage state from the results of the finite-element simulation; and (iv) direct comparison of different approaches to autonomous as-sessments. Moreover, the synthetic data generated has the potential to be used to augment field datasets. To demonstrate the efficacy of PBGMs, models of reinforced concrete moment-frame buildings with masonry infill walls are examined. The 3D synthetic environment employing PBGMs is shown to provide an effective testbed for development and validation of autonomous vision-based post-earthquake inspections that can serve as an important building block for ad-vancing autonomous data to decision frameworks.

Abstract: COVID-19 Long Haulers, an estimated 3% to 12% of people infected globally with coronavirus having latter devasting symptoms 12 weeks after the initial infection is on the rise. We conducted a collaborative study with the long covid patient organization in Greece in order to estimate the prevalence, symptoms and problems that adult long haulers experience and then propose a management plan for these patients. Symptoms were obtained from 208 patients using unstructured qualitative free text entries in an anonymized online questionnaire. The majority of respondents (68.8%) were not hospitalized and had been diagnosed more than six months ago with lingering symptoms (66,8%). Eighteen different symptoms (fatigue, tachycardia, shortness of breath, parosmia etc) were mentioned in both hospitalized and community patients. Interestingly, patients with initial mild symptoms suffer from the same persistent symptoms as those who were hospitalized. Awareness of long covid sequelae seems to be low even among medical doctors. Treatment options incorporating targeted rehabilitation programs are either not available or still excluded from the management plan of long covid patients. Since long COVID is a multi-systemic entity, we propose a holistic interventional approach using a multidisciplinary medical team in order to securely and effectively diagnose and treat these specific patients. Academic and medical community must collaborate with long covid patients’ organizations so as to provide personalized medicine.

Inspired by recent work of Fink, Reeves, Palma and Farr [1] on innovation in language, gastronomy, and technology, I study how new symbol discovery manifests itself in terms of additional "word" vocabulary being available from dictionaries generated from a finite number of symbols. Several distinct dictionary generation models are investigated using numerical simulation, with emphasis on the scaling of knowledge as dictionary generators and parameters are varied, and the role of which order the symbols are discovered in.

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.

In the present study, we investigate the post-editese phenomenon, i.e., the unique features that set machine translated post-edited texts apart from human-translated texts. We use two literary texts, namely, the English children's novel by Lewis Carroll Alice’s Adventures in Wonderland (AW) and Paula Hawkins' popular book The Girl on the Train (TGOTT) translated from English into Brazilian-Portuguese to investigate whether the post-editese features can be found on the surface of the post-edited (PE) texts. In addition, we examine how the features found in the PE texts differ from the features encountered in the human-translated (HT) and machine translation (MT) versions of the same source text. Results revealed evidence for post-editese for TGOTT only with PE versions being more similar to the MT output than to the HT texts.

Conventional models do not fully explain composition of the solar system – for example, the presence of p-nuclei and post-post-Fe-nuclei remains not yet understood (and is one of the great unresolved puzzles of nuclear astrophysics in general); other puzzles exist. We offer a hypothesis which can explain the appearance of non-native elements in the solar system, and a feasible scenario for its implementation. The hypothesis suggests that a nuclear-fission "event" occurred in the inner part of the solar system at the time currently defined as the birth of the system. Conventional models have never considered fission as a contributing nuclei-production mechanism. Upon examination of the existing models and factual data (presented in volumes of publications but never combined into an aggregate), we identified one plausible scenario by which a fission event (not demolishing the entire solar system) could occur: an encounter with a compact super-dense stellar "fragment" (with specific properties) and its "explosion" in fission-cascades. Such scenario also helps resolve other long-standing puzzles of the solar system. For example, it provides that the fission-produced nuclei subsequently transformed into the material that (eventually) accreted into the "rocky" objects in the system (terrestrial planets, asteroids, etc.) and enriched the pre-existed hydrogen-helium objects (the Sun and the gaseous giants) – this offers an explanation for the planets’ inner position and compositional differences within the predominantly hydrogen-helium rest of the solar system. Other implications also follow.

Abstract: With a resurgence in ITRT (Immediate Tooth Replacement Therapy) as a method of preserving both hard and thus soft tissues for improved aesthetic outcomes, this multi-centre, retrospective study will look at two novel products and their effect on these outcomes. A new synthetic particulate graft material along with a novel Implant design was utilized in the study and a 1 year follow up assessment, analysed for hard and soft tissue regeneration.

Post-ovulatory aging (POA) is an inevitable factor during some assisted reproduction technology procedures, and results in poor fertilization rates and impaired embryo development. This study used RNA sequencing analysis and experimental validation to study the similarities and differences between in vivo- and in vitro-matured porcine oocytes before and after POA. Differentially expressed genes (DEGs) between fresh in vivo-matured oocyte (F_vivo) and aged in vivo-matured oocyte(A_vivo) and DEGs between fresh in vitro-matured oocyte (F_vitro) and aged in vitro-matured oocyte(A_vitro) were intersected to explore the co-effects of POA. It was found that "organelles", especially "mitochondria", were significantly enriched GO terms. The expression of genes related to the “electron transport chain” and “cell redox homeostasis” pathways related to mitochondrial function significantly showed low expression patterns in both A_vivo and A_vitro groups. WGCNA analysis to explore gene expression modules specific to A_vivo. Trait-modules association analysis showed that the red modules were most associated with in vivo aging. There are a total of 959 genes in the red module, which are mainly enriched in “RNA binding”, “mRNA metabolic process”, etc. GO terms, and “spliceosome” and “nucleotide excision repair” pathways. DNAJC7, IK, and DDX18 were at the hub of the gene regulatory network. And these genes were all expressed higher in A_vivo. In summary, POA affects the organelle function of oocytes. A_vivo oocytes have some unique gene expression patterns. These genes may be potential anti-aging targets. This study helps us understand the detailed mechanism of POA and provides strategies for researching oocyte aging.

Background: Patients with burn scars often suffer from a ‘vicious cycle’ in which their skin becomes dry and pruritus. This greatly reduces patients' quality of life, but there is no well-known mechanism yet, and the development of drugs for effective treatment is necessary. Objective: This study evaluated the efficacy and safety of cosmetic formulation containing arginine glutamate ion pair (named as RE:pair) on epidermal barrier function and reducing pruritus. Materials and Methods: A total of 20 patients [15 male and 5 female; average age 48.35 ± 13.13 years] participated in evaluating the effectiveness of using the RE:pair formula topically twice daily for up to 4 weeks after burn pruritus. Treatment efficacy was evaluated by Numerical Rating Scale (NRS) for itching and pain, transepidermal water loss (TEWL), skin hydration, Vancouver Scar Scale (VSS) evaluation, and the patient’s overall satisfaction. Results: This formula was well-tolerated, with significant relief of NRS for itching and pain score after 2nd weeks and 4th weeks of application (p < 0.05). The itching score was high in some patients, and overall, it decreased significantly after 4 weeks compared to before application. Also, the personal pain score decreased after 4th weeks. Overall TEWL showed 35 % improvement after 4th week, and 52 % improvement was confirmed in arms and 19 % in legs. The overall improvement effect of skin hydration was also 45 % (p = 0.0012), and the improvement effect was 40 % (p = 0.0371) in areas including arms and 54 % (p = 0.0313) in areas including legs. All patient satisfactory evaluations were "excellent". Conclusions: RE:pair formula was safe and effective in improving skin barrier and itch relief, and if further studies are conducted, it can be used as an excellent topical treatment for post-burn scar that strengthens the skin barrier.

Open pit mining is a common activity in the Yucatan peninsula for the extraction of limestone. This mining is known under the generic name of quarries, and regionally as sascaberas (sascab=white soil in Mayan language). These areas are characterized by the total removal of the natural vegetation cover and soil in order to have access to the calcareous material. The present study shows the composition and structure of the vegetation in five quarries after approximately ten years of abandonment, and the conserved vegetation near to each one of the quarries in southeastern Quintana Roo. Using a canonical correspondence analysis (CCA), the distribution of the species was determined in relation to the edaphic variables: soil depth, percentage of organic matter (OM), cationic exchange capacity (CEC), pH and texture. 26 families, 46 genera and 50 species were recorded in the quarries and 25 families, 45 genera and 47 species were recorded in the conserved areas. The dominant species in the quarries belong to the families Poaceae, Fabaceae, Rubiaceae and Anacardiaceae. The quarries with higher values of OM (1.63%), CEC (24.05 Cmol/kg), depth (11 cm) and sand percentage (31.33%) include the following species like Lysiloma latisiliquum, Metopium brownei and Bursera simaruba which are commonly found in secondary forests. On the other hand, quarries with lower values of OM (0.39%), CEC (16.58 Cmol/kg) and depth (5.02), and higher percentage of silt (42.44%) were dominated by herbaceous species belonging to the Poaceae family and by Borreria verticillata, which are typical in disturbed areas of southeastern Mexico. In all cases, the pH was slightly alkaline due to the content of calcium carbonate (CaCO3), characteristic of the soils of the region. The edaphic variables are significantly correlated with the development and distribution of vegetation, and with the structure of the communities.

In this paper we propose the generation of synthetic small and more sophisticated molecule structures that optimize the binding affinity to a target (ASYNT-GAN). To achieve this we leverage on three important achievements in A.I.: Attention, Deep Learning on Graphs and Generative Adversarial Networks. Similar to text generation based on parts of text we are able to generate a molecule architecture based on an existing target. By adopting this approach, we propose a novel way of searching for existing compounds that are suitable candidates. Similar to question and answer Natural Language solutions we are able to find drugs with highest relevance to a target. We are able to identify substructures of the molecular structure that are the most suitable for binding. In addition, we are proposing a novel way of generating the molecule in 3D space in such a way that the binding is optimized. We show that we are able to generate compound structures and protein structures that are optimised for binding to a target.

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.

Previous studies suggested that trauma-focused cognitive behavior therapy (TF-CBT) is effective in reducing symptoms of post-traumatic stress disorder (PTSD) and depression in children and adolescents. However, the effects of app-assisted TF-CBT-based interventions in psychiatric clinics compared to treatment-as-usual (TAU) are under-explored. The purpose of this study was to reveal the added value of the app-assisted TF-CBT-based intervention as an add-on to TAU. The digitalized measures of the Child and Adolescent Trauma Screen (CATS), The Adolescent Dissociative Experience Scale (A-DES), Short Moods and Feelings Questionnaire (SMFQ), PTSD Checklist (PCL-5), and Children's Post-Traumatic Cognitions Inventory (CPTCI) were applied at baseline and post-treatment. The app-assisted TF-CBT-based group participants started with higher levels of negative alterations in cognition and mood compared to TAU participants but at post-treatment, no significant differences were observed between the app-assisted TF-CBT and TAU groups. Within the app-assisted TF-CBT group, post-treatment scores were significantly lower in post-traumatic stress symptoms, intrusion symptoms, alterations in arousal and reactivity, overall post-traumatic cognitions, and belief in being "a fragile person in a scary world”. Within the TAU group, post-treatment scores were notably lower just in dissociation and intrusion symptoms. The study suggests that app-assisted TF-CBT-based intervention can be effective in addressing specific trauma-related symptoms. The findings imply the necessity for screening for traumatic experiences, incorporating trauma-informed care, implementation of TF-CBT into treatment protocols, utilization of app-assisted interventions, tailoring interventions to individual needs, and comprehensive assessment and monitoring of treatment progress.

Background: This study aimed to examine the course of Depression and anxiety in COVID-19 survivors with a psychiatric history compared with those without a psychiatric history. Methods: A web-based cross-sectional survey for COVID-19 survivors was conducted from July to September 2021. 6016 COVID-19 survivors, the accuracy of whose responses was determined to be assured, were included in analyses. Exposures included psychiatric history and time since COVID-19 infection, and the main outcomes and measures included severity of depression and anxiety, as assessed using the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7), respectively. Results: Mean severity of PHQ-9 and GAD-7 were significantly higher in participants with a psychiatric history than in those without a psychiatric history. Two-way analysis of covariance for PHQ-9 showed a significant main effect of the presence of psychiatric history and a significant interaction effect of psychiatric history × time since infection. Two-way analysis of covariance for the GAD-7 score revealed a significant main effect of the presence of psychiatric history and time since COVID-19 infection and the interaction effect of these factors. Conclusions: The course of depression and anxiety was more severe in COVID-19 survivors with a psychiatric history than in those without a psychiatric history.

Direct and indirect effects after mine operations cease must ideally be subject to perpetual monitoring routines in order to detect possible risks or avoid adverse effects on the surrounding ecosystems at an early stage. In this contribution, mining subsidence lakes created inside the nature reserve Kirchheller Heide and Hilsfeld Forest are subjected to analysis for a long-term monitoring scheme. For this purpose, we employ high-resolution unmanned aerial system (UAS)-based multispectral and thermal mapping tools to provide a fast, non-invasive and multitemporal environmental monitoring method. Specifically, we propose to monitor vegetation evolution through multispectral analysis, biotypes identification using machine learning algorithms, and water surface extent detection, together with their thermal behavior. The aim of this contribution is to present the proposed workflow and first results to establish a baseline for future analyses and subsequent surveys for longterm multi-temporal monitoring

Minimal plasmids play an essential role in many intermediate steps in molecular biology. They can for example be used to assemble building blocks in synthetic biology or be used as intermediate cloning plasmids that are ideal for PCR-based mutagenesis methods. A small backbone also opens up for additional unique restriction enzyme cloning sites. Here we describe the generation of pICOz, a 1185 bp fully functional high-copy cloning plasmid with an extended multiple cloning site (MCS). To our knowledge, this is the smallest high-copy cloning vector ever described.

Intellecta dataset emerges as an innovative synthetic dataset, engineered to enhance the cognitive processing capabilities of contemporary language models. With a composition of 11.53 billion tokens, integrating 8.01 billion tokens of synthetic data with 3.52 billion tokens of rich textbook data, Intellecta is crafted to foster advanced reasoning and comprehensive educational narrative generation. Leveraging the Mixtral-8x7B-Instruct-v0.1 model, the dataset facilitates the generation of complex thought processes and detailed, textbook-style explanations, thus enabling language models to engage in both critical thinking and profound educational discourse. This hybrid dataset stands as a testament to the potential of synthetic data in pushing the boundaries of AI, offering a repository that is not only vast and varied but also refined to align with ethical standards and intellectual rigor.

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.

Plant-based insecticides are considered among the most economical and eco-friendly chemicals for the protection of field plants and even stored grains. The sweet melon (Cucumis melo L.) insect pest causes more than 90% damage to most melon leaves, vines, and balls at its growth stage. The study looked at how effective the plant extract from Africa Basil and the synthetic insecticide Cymbush were at killing insects on sweet melon (Cucumis melo L.). The study explored four different concentrations (2.5, 50, 75, and 100%) and a synthetic insecticide, Cymbush, against insect pests of sweet melon and compared the effects of distilled water, which is used as a control in a Randomized Complete Block Design (RCBD). The toxicity percentage levels of the African basil extracts against field pests of sweet melon were 25, 50, 75, and 100%. Maximum plant protection of the crop was achieved by the synthetic insecticide Cymbush (3.0 pest point), followed by Africa basil extract B100 (3.3 pest point), whereas weak and minimum insect pest protection were observed in the control (5.53 pest point). In conclusion, these results indicate the utility of African basil plant extracts against field insect pests of sweet melon as potential botanicals to control field insect pests and mitigate the hazardous use of synthetic insecticides on humans, animals, and the environment

During early embryonic development, fertilized one-cell embryos develop into preimplantation blastocysts and subsequently establish three germ layers through gastrulation during post-implantation development. In recent years, stem cells have emerged as a powerful tool to study embryogenesis and gastrulation without the need for eggs, allowing the generation of embryo-like structures known as synthetic embryos or embryoids. These in vitro models closely resemble early embryos in terms of morphology and gene expression and provide a faithful recapitulation of early pre- and post-implantation embryonic development. Synthetic embryos can be generated through a combinatorial culture of three blastocyst-derived stem cell types, such as embryonic stem cells, trophoblast stem cells, and extraembryonic endoderm cells, or totipotent-like stem cells alone. This review provides an overview of the progress and various approaches in studying in vitro embryogenesis and gastrulation using stem cells. Furthermore, recent findings and breakthroughs in synthetic embryos and gastruloids are outlined. Despite ethical considerations, synthetic embryo models hold promise for understanding mammalian (including human) embryonic development and have potential implications for regenerative medicine and developmental research.

Mucus is a critical part of the human body’s immune system which traps and carries away various particulates such as anthropogenic pollutants, pollen, viruses etc. Various synthetic hydrogels have been developed to mimic mucus, using different polymers as their backbones. Common to these simulants is a three-dimensional gel network which is physically crosslinked and is capable of loosely entrapping water within. Two of the challenges in mimicking mucus using synthetic hydrogels include the need to mimic the rheological properties of the mucus and its ability to capture particulates (its adhesion mechanism). In this paper, we review the existing mucus simulants and discuss their rheological, adhesive and tribological properties. We show that most, but not all, simulants indeed mimic the rheological properties of the mucus but only one mimics the ability of mucus to capture particulates.

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.

Sentinel-1 (S1) extra-wide (EW) swath data in cross-polarization (horizontal-vertical, HV or vertical-horizontal, VH) are strongly affected by the scalloping effect and thermal noise, particularly over areas with weak backscattered signals, such as sea surfaces. Although noise vectors in both the azimuth and range directions are provided in the standard S1 EW data for subtraction, the residual thermal noise still significantly affects sea ice detection by the EW data. In this paper, we improve the denoising method developed in previous studies to remove the additive noise for the S1 EW data in cross-polarization. Furthermore, we propose a new method for eliminating the residual noise (i.e. multiplicative noise) at the sub-swath boundaries of the EW data, which cannot be well processed by simply subtracting the reconstructed 2-D noise field. The proposed method of removing both the additive and multiplicative noise was applied to EW HV-polarized images processed using different Instrument Processing Facility (IPF) versions. The results suggest that the proposed algorithm significantly improves the quality of EW HV-polarized images under various sea ice conditions and sea states in marginal ice zone (MIZ) of the Arctic. This is of great support for the utilization of cross-polarization SAR images in wide swaths for intensive sea ice monitoring in polar regions.

Premortem clinical diagnoses and postmortem autopsy findings do not match throughout history. These clinicopathological discrepancies are expected to be raised during the coronavirus disease 2019 (COVID-19) pandemic due to increased pressure on healthcare. At the same time, autopsies and clinicopathological discrepancies accurately display the quality of the healthcare system. To assess that, we examined the relevant works of literature according to the PRISMA-based protocol. As discrepancy rate changes in the correlation to the length of stay in the hospital, we also checked whether studies with patients from the intensive care unit (ICU) differed in discrepancies significantly. We found overall risk differences pretty much alike in "pre-COVID" and "during the pandemic" groups of studies. Based on that, we concluded that healthcare quality did not drop significantly during the pandemic. Be it as it may, the pandemic exposed some shortcomings in mortem healthcare regarding consensus to the autopsy, organ retention, burial, and the postponed burial or the digitalization of post mortem healthcare. All of these issues should be addressed in the future.

The embryonic epicardium originates from the proepicardium, an extracardiac primordium constituted by a cluster of mesothelial cells. In early embryos, the embryonic epicardium is characterized by a squamous cell epithelium resting on the myocardium surface. Subsequently, it invades the subepicardial space and thereafter the embryonic myocardium by means of epithelial-mesenchymal transition. Within the myocardium, epicardial-derived cells present multilineage potential, later differentiating into smooth muscle cells and contributing both to coronary vasculature and cardiac fibroblasts in the mature heart. Over the last decades, we have progressively increased our understanding of those cellular and molecular mechanisms driving proepicardial/embryonic epicardium formation. This study provides a state-of-the-art review of the transcriptional and emerging post-transcriptional mechanisms involved in the formation and differentiation of the embryonic epicardium.

Background: Whilst lack of concentration is a known symptom of anaemia, its association with post-stroke dementia is unclear. Methods: We used data from a UK regional stroke register. To be eligible, patient must have survived to discharge and had anaemia by WHO criteria. Dementia status and other prevalent co-morbidities were assessed using ICD-10 codes. Patients were followed till May 2015 (mean follow-up 3.7 years, total person years = 27,769). Hazard Ratio for incident dementia was calculated using Cox-proportional hazards model controlling for potential confounders. Fine and Gray model was additionally constructed using mortality as the competing risk. Results: A total of 7,454 stroke patients were included with mean age (SD) of 75.9(12.3) years (50.2% men). Those with anaemia were older, has higher disability and co-morbidity burden prior to stroke. We observed a large amount of variation in the dementia incidence rates over time and that the hazard ratio increased every year. The significant association between anaemia and dementia incidence was lost after controlling for pre-stroke Modified Rankin score (HR1.17(0.97,1.40)). With every 20g/dL increase in Hb was associated with a significant reduction in the risk of dementia after adjustment for age, sex, stroke factors and disability but lost significance after adjustment for vascular risk factors. Competing risk analyses showed similar results. Conclusion: Whilst we found no evidence of anaemia as a risk factor for post-stroke dementia, the findings may be limited by potential under recognition of post stroke dementia.

The Sars-Cov-2 pandemic led to several needed containing measures that conditioned the onset of depressive, anxiety and post-traumatic stress symptoms in population. These symptoms, espe-cially if not diagnosed and treated, can also occur in patients undergoing surgery with high im-pact on people’s lives, like hysterectomy. To evaluate the post-surgical distress and anx-ious-depressive symptoms following hysterectomy for benign disease focusing on the impact of COVID-19 pandemic. The prospective observational cohort study included patients undergoing hysterectomy for benign disease. Psychologic evaluation through social-demographic question-naires was obtained before surgery (T1), postoperatively (T2), and 3 months after surgery (T3). The HADS (Hospital Anxiety and Depression Scale) was used to evaluate anxious-depressive symptoms and the PCL-5 (Post-traumatic Stress Disorder Checklist for DSM-5) compared the on-set of post-surgical distress and anxiety and depressive symptoms. The pre-COVID-19 pan-demic period was compared to the post-COVID-19 pandemic phase. Patients treated after COVID-19 pandemic showed higher depressive symptoms rate compared to those treated before (p-value=0.02); conversely, pre-COVID-19 patients were more prone to develop a PTSD (p-value=0.04). A significative association between the occurrence PTSD and anxiety-depressive symptoms registered at T2 a (p-value=0.007) and T3 (p-value

Long COVID (LC) encompasses a constellation of long-term symptoms experienced by at least 10% of people after the initial SARS-CoV-2 infection, and so far has affected about 65 million people. The etiology of LC remains unclear; however, many pathophysiological pathways may be involved, including viral persistence; chronic, low grade inflammatory response; immune dysregulation and defective immune response; reactivation of latent viruses; autoimmunity; persistent endothelial dysfunction and coagulopathy; gut dysbiosis; hormonal dysregulation, mitochondrial dysfunction; and autonomic nervous system dysfunction. There are no specific tests for the diagnosis of LC, and clinical features including laboratory findings and biomarkers may not specifically relate to LC. Therefore, it is of paramount importance to develop and validate biomarkers that can be employed for the prediction, diagnosis and prognosis of LC and its therapeutic response. Promising candidate biomarkers that are found in some patients are markers of systemic inflammation including acute phase proteins, cytokines and chemokines; biomarkers reflecting SARS-CoV-2 persistence, reactivation of herpesviruses and immune dysregulation; biomarkers of endotheliopathy, coagulation and fibrinolysis; microbiota alterations; diverse proteins and metabolites; hormonal and metabolic biomarkers; as well as cerebrospinal fluid biomarkers. At present, there are only two reviews summarizing relevant biomarkers; however, they do not cover the entire umbrella of current biomarkers or their link to etiopathogenetic mechanisms, and the diagnostic work-up in a comprehensive manner. Herein, we aim to appraise and synopsize the available evidence on the typical laboratory manifestations and candidate biomarkers of LC, their classification based on main LC symptomatology in the frame of the epidemiological and pathogenetic aspects of the syndrome, and furthermore assess limitations and challenges as well as potential implications in candidate therapeutic interventions.

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.

Meloidogyne nematodes, commonly known as root-knot nematodes, pose a considerable threat to crop yields, resulting in significant economic losses due to their intricate biology and limited control methods. In line with the European Union's focus on promoting organic farming and soil health to encourage sustainable agricultural practices, this study explores the efficacy of two characterized bacterial communities obtained from compost, namely SynCom1 and SynCom2, against Meloidogyne javanica in tomato plants. Through pot experiments, it is demonstrated that both bacterial communities effectively suppress nematode reproduction and root infections while simultaneously enhancing various growth parameters in tomatoes. These findings underscore the potential of synthetic bacterial communities as promising tools for organic or integrated pest management, thereby supporting sustainable agricultural practices and contributing to improved crop yields.

The possibility of abrupt transitions threatens to poise ecosystems into irreversibly degraded states. Recently, it has been proposed the use of engineered microbiomes in endangered ecosystems to prevent them to cross tipping points and avoid collapse. Potential targets for such interventions include some of the most prominent life-support systems in the biosphere: drylands and coral reefs. Since engineering can require the introduction of microorganisms not present in resident communities, how can we weight the potential outcomes? One way is to use general models of species interactions where the "synthetic" strain is incorporated into a standard multispecies model. Here we follow this approach by modelling a resource-consumer community where one of the species is a modified one that acts by preserving some key resource. We show how the indirect effect of damping the decay of shared resources results in biodiversity increase, and last but not less, the successful incorporation of the synthetic within the ecological network. Further extensions and implications for future restoration and terraformation strategies are discussed.

Cryptococcus neoformans is a human multidrug-resistant yeast with high mortality rates in immunocompromised patients. Recently, the synthetic peptide Mo-CBP3-PepII emerged as a potent anticryptococcal molecule with an MIC50 at low concentration. Here, the mechanisms of action of Mo-CBP3-PepII were deeply analyzed to provide new information about how it led C. neoformans cells to death. Light and fluorescence microscopies, analysis of enzymatic activities, and proteomic analysis were employed to understand the effect of Mo-CBP3-PepII on C. neoformans cells. Light and fluorescence microscopies revealed Mo-CBP3-PepII induced the accumulation of anion superoxide and hydrogen peroxide in C. neoformans cells. In addition to a reduction in the activity of superoxide dismutase (SOD), ascorbate peroxidase (APX), and catalase (CAT) in the cells treated with Mo-CBP3-PepII. In the presence of Ascorbic acid (AsA), no ROS were detected and Mo-CBP3-PepII lost the inhibitory activity against C. neoformans. Yet, Mo-CBP3-PepII inhibited the activity of lactate dehydrogenase (LDH), ergosterol biosynthesis, and induced the decoupling of cytochrome c from the mitochondrial membrane. Proteomic analysis revealed a reduction in the abundance of proteins related to energetic metabolism, DNA and RNA metabolism, pathogenicity, protein metabolism, cytoskeleton, and cell wall organization and division. Our findings indicated that Mo-CBP3-PepII might have multiple mechanisms of action against C. neoformans cells, mitigating the development of resistance and thus being a potent molecule to be employed in the production of new drugs against C. neoformans infections.

Nervous necrosis virus (NNV) has spread throughout the world, affecting more than 120 freshwater and marine fish species. While vaccination effectively prevents disease outbreaks, the difficulty of producing sufficient viruses using cell lines continues to be a significant disadvantage for producing inactivated vaccines. This study, therefore, explored the application of synthetic peptides as potential vaccine candidates for the prevention of NNV in Asian seabass (Lates calcarifer). Using the epitope prediction tool and molecular docking, three predicted immunogenic B cell epitopes (30-32 aa) derived from NNV coat protein were selected and synthesised, corresponding to amino acid positions 5 to 34 (P1), 133 to 162 (P2) and 181 to 212 (P3). All the predicted peptides interact with Asian sea bass’s MHC class II by docking. The antigenicity of these peptides was determined through ELISA and all peptides were able to react with NNV-specific antibodies. Subsequently, the immunogenicity of these synthetic peptides was investigated by immunisation of Asian seabass with individual peptides (30 μg/fish) and a peptide cocktail (P1+P2+P3, 10 μg each/fish) by intraperitoneal injection, followed by a booster dose at day 28 post-primary immunisation. There was a subset of immunised fish that were able to induce upregulation of CD4 in the head kidney and spleen. Importantly, antibodies derived from fish immunised with synthetic peptides reacted with whole NNV virions. Taken together, these findings indicate that synthetic linear peptides based on predicted B cell epitopes exhibited both antigenic and immunogenic properties, suggesting that they could be potential vaccine candidates for the prevention of NNV in fish.

Non-homologous end-joining (NHEJ) is a major DNA repair pathway in mammalian cells that recognizes, processes and fixes DNA damages throughout the cell cycle, and is specifically important for homeostasis of post-mitotic neurons and developing lymphocytes. Neuronal apoptosis increases in the mice lacking NHEJ factors Ku70 and Ku80. Inactivation of other NHEJ genes, either Xrcc4 or Lig4, leads to massive neuronal apoptosis in the central nervous system (CNS) that correlates with embryonic lethality in mice. Inactivation of either Paxx, Mri or Dna-pkcs NHEJ gene results in normal CNS development due to compensatory effects of Xlf. Combined inactivation of Xlf/Paxx, Xlf/Mri and Xlf/Dna-pkcs, however, results in late embryonic lethality and high levels of apoptosis in CNS. To determine the impact of NHEJ factors on early stages of neurodevelopment, we isolated neural stem and progenitor cells from mouse embryos and investigated proliferation, self-renewal and differentiation capacity of these cells lacking either Xlf, Paxx, Dna-pkcs, Xlf/Paxx or Xlf/Dna-pkcs. We found that XLF, DNA-PKcs and PAXX maintain the neural stem and progenitor cell populations and neurodevelopment in mammals, which is particularly evident in the double knockout models.

The Wave Mode (WM) is a unique imaging mode of spaceborne synthetic aperture radar (SAR), which is dedicatedly designed for global ocean surface wave observations. Since it was firstly achieved in the ERS-1/SAR satellite starting from 1991, the WM data over global oceans have been continuously acquired by the ESA’s SAR instruments onboard the satellites of ERS-2 (1997 – 2011), ENVISAT (2002 – 2012), Sentinel-1A(2014--)/1B(2016--) and the Chinese GaoFen-3 SAR (2016--), for nearly 30 years. Therefore, spaceborne SAR WM data have been a ‘big data’, which however, has not been widely exploited for global ocean wave measurements. In this study, we demonstrate its application on global ocean wave measurements based on the ten-year Advanced SAR (ASAR) WM data.

Nowadays, we can observe a worldwide trend towards the development of synthetic biomaterials. Numerous researches have been carried out in order to better understand the cellular behavior involved in the inflammation and bone healing processes related to living tissues. The aim of this study is to evaluate the tissue behavior of two different types of biomaterials: synthetic nano-hydroxyapatite / beta-tricalcium phosphate and hydroxyapatite in non-critical bone defects in rat calvaria. Twenty four rats underwent surgery in which two 3 mm defects in each cavity were performed. The rats were divided into 2 groups: Group 1, using xenogen hydroxyapatite (Bio oss ™); Group 2, using synthetic nano-hydroxyapatite / beta-tricalcium phosphate (Blue Bone ™). Sixty days after the surgery, the calvaria bone defect was filled with biomaterial, the animals were sacrificed and marked with Masson's trichrome and PAS staining, and immunohistochemistry (TNF-α, MMP-9) and electron microscopy analyzes were performed. Histomorphometric analysis indicates a greater presence in the protein matrix in Group 2, in addition to higher levels of TNF-α, MMP-9. The ultrastructural analysis shows an association of material with fibroblasts in the tissue regeneration stage. Paired statistical data indicates that Blue Bone ™ can improve bone formation / remodeling when compared to biomaterials of xenogenous origin.

In this paper, we focus on developing a novel method to extract sea ice cover (i.e., discrimination/classification of sea ice and open water) using Sentinel-1 (S1) cross-polarization (vertical-horizontal, VH or horizontal-vertical, HV) data in extra wide (EW) swath mode based on the machine learning algorithm support vector machine (SVM). The classification basis includes the S1 radar backscatter coefficients and texture features that are calculated from S1 data using the gray level co-occurrence matrix (GLCM). Different from previous methods where appropriate samples are manually selected to train the SVM to classify sea ice and open water, we proposed a method of unsupervised generation of the training samples based on two GLCM texture features, i.e. entropy and homogeneity, that have contrasting characteristics on sea ice and open water. We eliminate the most uncertainty of selecting training samples in machine learning and achieve automatic classification of sea ice and open water by using S1 EW data. The comparison shows good agreement between the SAR-derived sea ice cover using the proposed method and a visual inspection, of which the accuracy reaches approximately 90% - 95% based on a few cases. Besides this, compared with the analyzed sea ice cover data Ice Mapping System (IMS) based on 728 S1 EW images, the accuracy of extracted sea ice cover by using S1 data is more than 80%.

Synthetic biology (SynBio) is an interdisciplinary field that has developed rapidly in the last two decades. It involves the design and construction of new biological systems and processes from standardized biological components, networks and synthetic pathways. The goal of Synbio is to create logical forms of cellular control. Biological systems and their parts can be re-designed to carry out completely new functions. SynBio is poised to greatly impact human health, environment, biofuels and chemical production with huge economic benefits. SynBio presents opportunities for the highly agro-based African economies to overcome setbacks that threaten food security: The setbacks are brought about by climate change, land degradation, over-reliance on food imports, global competition, and water and energy security issues among others. With appropriate regulatory frameworks and systems in place, the benefits of harnessing SynBio to boost development in African economies by far potentially outweigh the risks. Countries that are already using GMOs such as South Africa and Kenya should find the application of SynBio seamless, as it would be a matter of expanding the already existing regulations and policies for GMO use.

ABSTRACT Surfactants are a broad category of tensio-active biomolecules with multifunctional properties applications in diverse industrial sectors and processes. Surfactants are produced synthetically and biologically. The biologically derived surfactants (biosurfactants) are produced from microorganisms with Pseudomonas aeruginosa, Bacillus subtilis Candida albicans and Acinetobacter calcoaceticus as dominant species. Rhamnolipids, sophorolipids, mannosylerithritol lipids, surfactin, and emulsan are well known in terms of their biotechnological applications. Biosurfactants can compete with the synthetic surfactants in terms of performance with established advantages over the synthetic ones including eco-friendliness, biodegradability, low toxicity, and stability over a wide variability of environmental factors. However, at present, the synthetic surfactants are a preferred option in different industrial applications, because of their availability in commercial quantities, unlike the biosurfactants. Usage of synthetic surfactants introduce new species of recalcitrant pollutants to the environment and lead to undesired results where a wrong selection of surfactants is made. Substituting synthetic surfactants with biosurfactants resolves these drawbacks, thus, interest has been intensified in biosurfactant applications in a wide range of industries hitherto considered as experimental fields. This review, therefore, intends to offer an overview of diverse applications where biosurfactants have found useful, with emphases in petroleum biotechnology, environmental remediation and in the agriculture sector. Application of biosurfactant in these settings would lead to industrial growth and environmental sustainability.

In (Venetz et al., 2019), authors rebuilt the essential genome of Caulobacter crescentus through the process of chemical synthesis rewriting and studied the genetic information content at the level of its essential genes. Then, they reduced the native Caulobacter crescentus native Caulobacter NA1000 genome sequence real genome ( 4042929 bp ) to the 785,701-bp reduced synthetic genome. Here we demonstrate the existence of a palindromic-like mirror structure that exists in real genomes and disappears totally in the synthetic genome. This biomathematic meta-organization is based on characteristic proportions of Fibonacci numbers between DNA single strand nucleotides proportions TC / AG on the one hand and TG / AC on the other hand. In both cases, we suggest that this meta-structure enhances the three-dimensional cohesion of the two DNA strands of the genome. We then generalize this study to the different synthetic genomes and synthetic cells published by the Craig Venter Institute on Mycoplasma Mycoides JCVI-syn1.0 (in 2010), JCVI-syn3.0 (in 2016) and JCVI-syn3A (in 2019). Finally, in the discussion section, we extend this study to synthetic genomes of E-Coli and Yeast chromosome XII.

This paper presents a concise exploration of the synthetic biology currently to artificially 1 create life, juxtaposed against natural life’s emergence over Earth’s 4.5-billion-year history. It explores 2 the complexities of life’s origins, sustaining factors, and the consequences of synthetic life creation, 3 addressing key scientific milestones such as the Urey-Miller experiment and Jacques Monod’s pro- 4 posals. The narrative navigates through the roles of energy, Maxwell’s demons, bifurcations, and 5 genetic information in the emergence and evolution of complex biological systems. Despite significant 6 strides in genetic engineering, the challenge of creating life from scratch persists, necessitating a deep 7 understanding of diverse scientific disciplines. While synthetic biology holds promise for medicine 8 and biotechnology, the creation of truly autonomous synthetic life forms raises ethical concerns. The 9 paper also stresses the imperative for careful ethical evaluation of the societal and environmental 10 implications arising from these advancements.

Chikungunya virus is a re-emerging mosquito-borne alphavirus. Outbreaks are unpredictable and explosive in nature. Fever, arthralgia, and rash are common symptoms during the acute phase. Diagnostic tests are required to differentiate chikungunya virus from other co-circulating arboviruses, as symptoms can overlap, causing a dilemma for clinicians. Arthritis is observed during the sub-acute and chronic phases, which can flare up, resulting in increased morbidity that adversely affects activities of daily living. During the 2019 chikungunya epidemic in Thailand, cases surged in Bangkok in the last quarter of the year. Here, we demonstrate the chronic sequelae of post-chikungunya arthritis in one of our patients 1 year after the initial infection. An inflammatory process involving edema, erythema, and tenderness to palpation of her fingers' flexor surfaces was observed, with positive chikungunya IgG and negative IgM tests and antigen. The condition produced stiffness in the patient’s fingers and limited their range of motion, adversely affecting daily living activities. Resolution of symptoms was observed with a short course of an anti-inflammatory agent. More research is required to determine whether sanctuaries enable chikungunya virus to evade the host immune response and remain latent, flaring up months later and triggering an inflammatory response that causes post-chikungunya arthritis.

BACKGROUND This study investigated the association of postprandial plasma glucose (PPG) with cancer mortality using a general cohort of US adults. METHODS This cohort study included 14,860 US adults who attended the third National Health and Nutrition Examination Survey from 1988 to 1994, with mortality being followed up to December 31, 2019. The experimental exposures were levels of plasma glucose, including PPG with a fasting time of 0-3.9 h (PPG_0-3.9h) and 4-7.9 h (PPG_4-7.9h), plasma glucose with a fasting time ≥ 8 h (PG_fasting), and plasma glucose at 2 h after oral glucose tolerance test (PG_2hOGTT). Plasma glucose-associated cancer mortality risk was assessed using Cox proportional hazards models. RESULTS A 1-natural-log-unit increase in PPG_4-7.9h was associated with a higher multivariate-adjusted risk for cancer mortality [hazard ratio (HR), 3.24; 95% confidence interval (CI), 1.50-7.00]. However, PPG_0-3.9h, PG_fasting, PG_2hOGTT, hemoglobin A_1c, and insulin were not significantly associated with cancer mortality. The positive association of PPG_4-7.9h with cancer mortality remained in those without a prior diagnosis of cancer. CONCLUSIONS High PPG_4-7.9h is associated with a higher cancer mortality risk in US adults. Lowering PPG_4-7.9h may reduce cancer mortality.

Breast Angiosarcoma is a rare malignancy, accounting less than 1% of all soft tissue. It comprises primitive and secondary subtypes, such as radiogenic breast angiosarcoma (RAS). Despite the multimodal treatment, angiosarcomas represent an incurable disease for many patients and represent a cause of substantial deterioration of their quality of life. Surgery represents the cornerstone in the management, but high recurrence rates are reported. Electrochemotherapy (ECT) is practicable locoregional treatment in patients with advanced angiosarcoma, in a multimodal therapeutic strategy. ECT palliative benefit includes optimal patient compliance, good local hemostasis control, and local responses. Considering that only 22 cases are described in literature, we reported a rare case of RAS treated with ECT, after a multidisciplinary approach including Next Generation Sequencing (NGS). A literature review about the feasibility of ECT in RAS management was also performed.

Objectives: To examine the long term impact of COVID-19 on sleep patterns and development of sleep disorders. Methods: Using the centralized Massachusetts General Brigham (MGB) Research Patient Data Registry (RPDR), SARS-CoV2 positive patients were surveyed about their sleep patterns before and after the viral infection. Information related to co-morbid conditions and medications were obtained through chart review. Results: Two hundred and forty five completed surverys were analysed. Average age was 53.3 ± 16.3 years, and participants were predominantly Non-Hispanic White (84.1%) and female (74.3%). Average BMI (kg/m2) was 29.9 ± 6.9, and a greater proportion was non-smokers (63.2%). After COVID-19, there was an increase in the percentage of participants reporting difficulty initiating (31 ± 46% vs. 39 ± 49%, P=0.01), and maintaining sleep (43 ± 49% vs. 57 ± 49%, P<0.001), and use of sleep aids (24 ± 43% vs. 30 ± 45% P=0.003) with an incidence rate of 24.3%, 37.4%, and 12.3% respectively. In addition, there was an increase in daytime fatigue and the need for napping (58 ± 49% vs. 36 ± 48%, P <0.0001) with an incidence of 8% and 23% respectively. The sleep symptoms persisted beyond 12 months among 28% of the participants and were predominantly seen among women. Conclusions: Infection with SARS-CoV2 has negative effects on sleep, and a significant proportion of adults experience insomnia and daytime sleepiness beyond 12 months after recovering from the initial infection.

Despite the relative scarcity of studies focusing on pharmacotherapy in aphasia, there is evidence in the literature indicating that remediation of language disorders via pharmaceutical agents could be a promising aphasia treatment option. Among the various agents used to treat chronic aphasic deficits, cholinergic drugs have provided interesting results. In the current review, we focused on published reports investigating the impact of acetylcholine on language and further cognitive disturbances. It has been suggested that acetylcholine plays an important role in neuroplasticity and is related to several aspects of cognition, such as memory and attention. Moreover, cholinergic input is diffused to a wide network of cortical areas, which have been associated with language sub-processes. This could be a possible explanation for the positive reported outcomes of cholinergic drugs in aphasia recovery, and specifically in distinct language processes, such as naming and comprehension, as well as overall communication competence. However, evidence with regard to functional alterations in specific brain areas after pharmacotherapy is rather limited. Finally, despite the positive results derived from the relevant studies, cholinergic pharmacotherapy treatment in post-stroke aphasia has not been widely implemented. The present review aims to provide an overview of the existing literature in cholinergic pharmacotherapy interventions in post-stroke aphasia, following an integrated approach by converging evidence from neuroanatomy, neurophysiology, and neuropsychology.

Our understanding of Alzheimer’s disease (AD) pathogenesis has developed with several hypotheses over the last 40 years, including the Amyloid and Tau hypotheses, respectively. More recently, the p53 protein, well-known as ‘the guardian of the genome,’ has gained attention for its role in the early evolution of AD. This is due to p53’s central role in the control of oxidative stress and potential involvement in both Amyloid and Tau pathways. p53 is commonly regulated by post-translational modifications (PTMs), which affect its conformation, increasing its capacity to adopt multiple structural and functional states, including those that can influence several processes in AD. The following review will explore the impact of p53 post-translational modifications (PTMs) on its function and consequential involvement in AD pathogenesis.

Abstract Objectives To assess the causes and risk factors of posttraumatic stress disorder (PTSD) in adult asylum seekers and refugees. To explore whether the causes and risk factors of PTSD, between male and female adult refugees/ asylum seekers is different. Study design Systematic review of current literature. Data Sources PubMed, Web of Science, Scopus and Google Scholar up until February 2019 Method A structured systematic search was conducted in the relevant databases. Papers were excluded, if they failed to meet the inclusion and exclusion criteria. Afterwards, a qualitative assessment was performed on the selected papers. Results 12 Studies were included for the final analysis. All papers were either case studies/report or cross sectional studies. The number of traumatic events experienced by refugees/asylum seekers, is the most frequently reported pre-migration causes for PTSD development. Whilst acculturative stress, is the most common post migration stressor. There were mixed reports, regarding the causes of PTSD between both genders of refugees/asylum seekers. Conclusion This reviews’ findings, have potential clinical application into helping clinicians, to risk stratify refugees/asylum seekers for PTSD development and thus aid in embarking on earlier intervention measures. However, more rigorous research similar to this one, is needed for it to be implemented into clinical practice.

Public key encryption methods are often used to create a digital signature, and where Bob has a public key and a private key. In order to prove his identity, he will encrypt something related to the message with his private key, and which can then be checked with his public key. The main current methods of public-key encryption include RSA and ECC (Elliptic Curve Cryptography), and which involve computationally difficult operations. But these operations have not been proven to be hard in an era of quantum computers. One well-known hard problem is the solving of quadratic equations with $m$ equations with $n$ variables. This is a known NP-hard problem, even in a world of quantum computers. These can be used as post-quantum signature schemes and which involve multivariate equations. In order to understand these methods, this paper outlines a simple example of implementing the oil and vinegar method, and where we have a number of unknown oil variables and a number of known vinegar variables, and where the vinegar variables help convert the hard problem into an easy one.

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.

In this work, backscattering signatures of snow-covered lake ice and sea ice from X- and Ku-band synthetic aperture radar (SAR) data are investigated. The SAR data were acquired with the ESA airborne SnowSAR sensor in winter 2012 over Lake Orajärvi in northern Finland and over landfast ice in the Bay of Bothnia of the Baltic Sea. Co-incident with the SnowSAR acquisitions in-situ snow and ice data were measured. In addition, time series of TerraSAR-X images and ice mass balance buoy data were acquired for the Lake Orajärvi in 2011-12. The main objective of our study was to investigate relationships between SAR backscattering signatures and snow depth over lake and sea ice, with the ultimate objective of assessing the feasibility of retrieval of snow characteristics using X- and Ku-band dual-polarisation (VV and VH) SAR over freshwater or sea ice. This study constitutes the first comprehensive survey of snow backscattering signatures at these two combined frequencies over both lake and sea ice. For lake ice, we show that X-band VH-polarized backscattering coefficient (σo) and the Ku-band VV/VH-ratio exhibited the highest sensitivity to the snow depth. For sea ice, the highest sensitivity to the snow depth was found from the Ku-band VV-polarised σo and the Ku-band VV/VH-ratio. However, the observed relations were relatively weak, indicating that at least for the prevailing snow conditions, obtaining reliable estimates of snow depth over lake and sea ice would be challenging using only X- and Ku-band backscattering information.

The conducted investigation encompassed the comprehensive integration of mechanical, envi-ronmental, chemical, and microstructural evaluations of a composite amalgamating sandy soil and a synthetic polymer at two distinct concentrations (2.5% and %) across multiple curing in-tervals (0, 1, 2, 4, 7, 15, 30, and 45 days). The studied soil originates from an environmentally sig-nificant protected area in Brazil. The implementation of mechanisms for soil improvement in the region must adhere to technical criteria without causing environmental harm. Direct shear testing was conducted, permeability was assessed, and microstructure analysis and XRD and XRF/EDX studies of both the soil and composites were conducted. It was observed that longer curing times yielded improved results in shear stress, friction angle, and cohesive intercept, with SP_5% exhibiting the highest values compared to the soil and SP_2.5%. Adding the polymeric so-lution to the soil contributed to cementation and cohesion gains in the substrate. Through mi-crostructural characterization, the polymer's role as a cementing agent for the grains is evident, forming a film on the grains and binding them together. Based on the analyses and studies con-ducted in the research, it can be concluded that there is technical feasibility for applying the pol-ymeric solution at both dosages in geotechnical projects.

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.

Natural fibers have been widely used as a reinforcing material for the construction of drones. The main goal of this review is to identify a biodegradable natural fiber material that can be built for Unmanned Aerial Vehicles (UAVs). The review shows that natural fibers such as kenaf and PALF can be used as an alternative composite material, particularly for multifunctional applications where their smaller weight and less expensive characteristics make them incredibly realistic. This review also discusses the mechanical properties, advantages and disadvantages, and fabrication of the composites.

Anatomical airways parameters as length, diameter and angles have a strong effect on the flow dynamics. Aiming to explore the effect of variations of the bifurcation angle (BA) and carina rounding radius (CRR) of lower human airways on the respiratory processes, numerical simulations of airflow during inhalation and exhalation were performed using a synthetic bifurcation models. Geometries for the airways models were parameterized based on a set of different BA's and several CRR's. A range of Reynolds numbers (\Reyn) relevant to the human breathing process were selected to analyzed the airflow behaviour. The numerical results show a significant influence of BA and the CRR on the development of the airflow within the airways, and therefore affecting some relevant features of the flow, namely the deformation of velocity profiles, alterations of pressure drop, the flow patterns, and finally enhance or attenuation of wall shear stresses (WSS) appearing during the regular respiratory process. Numerical results show that increases in the bifurcation angle value are accompanied by pressure increases of about 20\%, especially in the regions close to the bifurcation. Similarly, increases in the BA value lead to a reduction in peak shear stresses of up to 70\%. For the ranges of angles and radii explored, an increase in pressure of about 20\% and a reduction in wall shear stress of more than 400\% were obtained by increasing the carina rounding radius. Analysis of the coherent structures and secondary flow patterns also revealed a direct relationship between the location of the vortical structures, the local maxima of the velocity profiles and the local vorticity minima. This relationship was observed for all branches analysed, for both the inhalation and exhalation processes of the respiratory cycle.

Recently, deep learning-based image quality enhancement models have been proposed to improve the perceptual quality of distorted synthesized views impaired by compression and Depth Image Based Rendering (DIBR) process in multiview video systems. However, due to the lack of multi-view video plus depth data, the training data for quality enhancement models is small, which limits the performance and progress of these models. Augmenting the training data to enhance the Synthesized View Quality Enhancement (SVQE) models is a feasible solution. In this paper, we suggest a deep learning-based SVQE model using more synthetic Synthesized View Images (SVIs). To simulate the irregular geometric displacement of DIBR distortion, a random irregular polygon-based SVI synthesis method is proposed based on existing massive RGB/RGBD data, and a synthetic synthesized view database is constructed, which includes synthetic SVIs and DIBR distortion masks. Moreover, to further guide the SVQE models to focus more precisely on DIBR distortion, the DIBR distortion mask prediction network which could predict the position and variance of DIBR distortion is embedded into the SVQE models. The experimental results demonstrate that by pretraining on the synthetic SVI database, the performance of the existing SVQE models could be greatly promoted. In addition, by introducing the DIBR distortion mask prediction network, the SVI quality could be further enhanced.

The classification of vessel types in SAR imagery is of crucial importance for maritime applications. However, the ability to use real SAR imagery for deep learning classification is limited, due to the general lack of such data and/or the labor-intensive nature of labeling them. Simulating SAR images can overcome these limitations, allowing the generation of an infinite number of datasets. In this contribution, we present a synthetic SAR imagery dataset with ship wakes, which comprises 46080 images for ten different real vessel models. The variety of simulation parameters includes 16 ship heading directions, 6 ship velocities, 8 wind directions, 2 wind velocities, and 3 incidence angles. In addition, we extensively investigate classification performance for noise-free, noisy, and denoised ship wake scenes. We utilize the standard AlexNet architecture and employ training from scratch. To achieve the best classification performance, we conduct Bayesian optimization to determine hyperparameters. Results demonstrate that the classification of vessel types based on their SAR signatures is highly efficient, with maximum accuracies of 96.16%, 92.7%, and 93.59%, when training using noise-free, noisy, and denoised datasets respectively. Thus, we conclude that the best strategy in practical applications should be to train convolutional neural networks on denoised SAR datasets. The results show that the versatility of the SAR simulator can open up new horizons in the application of machine learning to a variety of SAR platforms.

As synthetic/artificial life forms become more abundant and sophisticated, an increasing number of bizarre creatures - xenobots, robots, soft A-life entities, genetically engineered organisms, etc. - are invading our society. Therefore, we need to bring order to all this, to establish what is living and what is not. Here, I intend to classify all these non-natural entities and clarify their status with reference to their consideration or not as living beings, leaving the door open to an uncertain future in which perhaps we can see how "the artificial" and "the natural" merge to originate something new. To order all this "new biodiversity" and to also give entry to viruses (which are excluded of the three-domains tree of life), I propose the creation of a new domain, Lithbea (from the name: life-in-the-border entities), in which all these new human-made entities as well as the viruses will be included. Within this domain there would be two kingdoms, Virus and Humade (contraction of human-made), based on their origin, natural or human-made. A brief description of each component of Lithbea is included and the implications for society and biology of this “new biodiversity” is briefly discussed.

Increasing environmental concern and consumer demand for natural, sustainable and eco-friendly products have prompted the replacement of synthetic surfactants with their natural plant-based alternatives. Saponins are the plant based natural surfactants characterized by their foam forming properties in aqueous solution. Their natural origin makes them eco-friendly, bio-degradable and non-toxic. Further, they possess better physicochemical properties than the syn-thetic ones. They are also reported to exhibit a lot of useful biological activities such as anti-cancer, antifungal, anti-inflammatory, antimicrobial, antioxidant and cholesterol-lowering properties. Because of their excellent surface activity, biological activities and wide distribution in nature, saponin rich plants deserve deeper insight as a sustainable source of natural surfactants as they possess the potential to replace toxic synthetic surfactants abundant today. This review article is intended to provide a brief overview on the saponins with a special notion on their surface-active properties. It encourages further studies on development of commercial formulations based on saponins for the complete replacement of the synthetic counter parts, making better use of plants sources thereby contributing to global agenda of green environment.

Phase synchronization is one of the key issues that must be addressed in the bistatic synthetic aperture radar (BiSAR) system. LuTan-1 is an innovative L-band spaceborne BiSAR mission of China. An advanced synchronization scheme is used in the LuTan-1 system. The synchronization pulses are exchanged immediately after the ending time of the radar echo receiving window and before the starting time of the next pulse repetition interval. Therefore, it can not interrupt the normal SAR data acquisition, further improving synchronization frequency and avoiding the data missing effect. In order to accurately monitor system malfunctions and compensate for the phase synchronization errors introduced by hardware system, an innovative internal calibration strategy is designed and employed in the LuTan-1 mission. The test data acquired from the ground validation system of LuTan-1 are used to demonstrate the feasibility of the proposed scheme. The results validate the effectiveness of the proposed scheme and prove the promise for its future application in LuTan-1.

In this paper, we presented a method of retrieving sea surface wind speed from Sentinel-1 synthetic aperture radar (SAR) horizontal-horizontal (HH) polarization data in extra-wide mode, which have been extensively acquired over the Arctic for sea ice monitoring. In contrast to the conventional algorithm, i.e., using a geophysical model function (GMF) to retrieve sea surface wind by spaceborne SAR, we introduced an alternative method based on physical model guided neural network. Parameters of SAR normalized radar cross section, incidence angle, and wind direction are used as the inputs of the backward propagation (BP) neural network, and the output is the sea surface wind speed. The network is developed based on more than 11,000 HH-polarized EW images acquired in the marginal ice zone (MIZ) of the Arctic and their collocations with scatterometer measurements. Verification of the neural network based on the testing dataset yields a bias of 0.23 m/s and a root mean square error (RMSE) of 1.25 m/s compared to the scatterometer wind speed. Further comparison of the SAR retrieved sea surface wind speed with independent buoy measurements shows a bias and RMSE of 0.12 m/s and 1.42 m/s, respectively. We also analyzed the uncertainty of retrieval when the wind direction data of a reanalysis model are used as inputs to the neural network. By combining the detected sea ice cover information based on the EW data, one can expect to derive simultaneously sea ice and marine-meteorological parameters by spaceborne SAR in a high spatial resolution in the Arctic.

This dataset consists of integral sea state parameters of significant wave height (SWH) and mean wave period (zero-upcrossing mean wave period, MWP) data derived from the advanced synthetic aperture radar (ASAR) onboard the ENVISAT satellite over its full life cycle (2002-2012) covering the global ocean. Both parameters are calibrated and validated against buoy data. A cross-validation between the ASAR SWH and radar altimeter (RA) data is also performed to ensure that the SAR-derived wave height data are of the same quality as the RA data. These data are stored in the standard NetCDF format, which are produced for each ASAR wave mode Level1B data provided by the European Space Agency. This is the first time that a full sea state product in terms of both the SWH and MWP has been derived from spaceborne SAR data over the global ocean for a decadal temporal scale.

Robots for communication are developed extensively with emphasis on sympathy. This study deals with the growth of character and the control of its operation accordingly. The child has time to be alone with the nature of his/her robot friend. The child can interact with other people's emotional expressions through a robot. Step by step, the robot character will grow as the child grows. Through design studies, qualitative processes such as {customer experience audit, eye tracking, mental model diagrams, semantic differences} have been executed for the results. The participatory behavior research approach through user travel is mapped from the user's lead to the evidence-based design. This research considers how the synthetic characteristics can be applied to the physical growth of robot toys through the product design process. With the development of robot toy "Buddy", we tried making two variations on the robot to achieve recognizable growth. (1) A one-dimensional height scaling and (2) facial expression including the distance between two eyes on the screen. Observations represented children's reactions when "Buddy" was released to with the children. As an independent synthetic character, the robot was recognized by children who had the designed function. Robots for training may require more experimentation.

Improvements that can be attained in seasonal climate predictions in various parts of Africa using the multimodel supersensemble scheme are presented in this study. The synthetic superensemble (SSE) used follows the approach originally developed at Florida State University (FSU). The technique takes more advantage of the skill in the climate forecast data sets from atmosphere-ocean general circulation models running at many centres worldwide including the WMO global producing centers (GPCs). The module used in this work drew data sets from the Four versions of FSU coupled model system, seven models from the DEMETER project which is the forerun to the current European Ensembles Forecast System, the NCAR Model, and the Predictive Ocean Atmosphere Model for Australia (POAMA), all making a set of 13 individual models. An archive consisting of monthly simulations of precipitation was available over all the 5 regions of Africa, namely Eastern, Central, Northern, Southern, and Western Africa. The results showed that the SSE forecast for precipitation carries a higher skill compared to each of the member models and the ensemble mean. Relative to the ensemble mean (EM), the SSE provides an improvement of 18% in simulation of season cycle of precipitation climatology. In Eastern Africa, during December-February season, a north-south gradient of precipitation prevails between Tropical East Africa and the sector of the region towards Southern Africa. This regional scale climate pattern is a direct influence of the Intertropical Convergence Zone (ITZC) across the African continent during this time of the year. The SSE emerges with superior skill scores such as lowest root mean square error above the EM and the member models, for example in the prediction of spatial location and precipitation magnitudes that characterize the see-saw precipitation pattern in Eastern Africa. In all parts of Africa, and especially Eastern Africa where seasonal precipitation variability is a frequent cause huge human suffering in due to droughts and famine, the multimodel superensemble and its subsequent improvements will always provide a forecast that out weighs the best Atmosphere-Ocean Climate Model.

Satellite altimeters have been used to monitor river and reservoir water levels, from which water storage estimates can be derived. Inland water altimetry can therefore play an important role in continental water resource management. Traditionally, satellite altimeters were designed to monitor homogeneous surfaces such as oceans or ice sheets, resulting in a poor performance over small inland water bodies due to the contribution from land contamination in the returned waveforms. The advent of synthetic aperture radar (SAR) altimetry (with its improved along-track spatial resolution) has enabled the measurement of inland water levels with a better accuracy and an increased spatial resolution. This paper presents three specialized algorithms or retrackers to retrieve water levels from SAR altimeter data over inland water bodies dedicated to minimizing land contamination from the waveforms. The performances of the proposed waveform portion selection method with three retrackers, namely, the threshold retracker, Offset Centre of Gravity (OCOG) retracker and 2-step physical-based retracker, are compared. Time series of water levels are retrieved for water bodies in the Ebro River basin (Spain). The results show good agreement with in situ measurements from the Ebro Reservoir (width is approximately 1.8 km) and Ribarroja Reservoir (width is approximately 400 m) with un-biased root-mean-square errors (RMSEs) of approximately 0.28 m and 0.16 m, respectively. The performances of all three retrackers are also compared with the European Space Agency’s ocean retracker in the Sentinel-3 Level-2 product.

Possibilities of utilization of two frequencies synthetic aperture radar (SAR) operating simultaneously in P-band and S or L-band are considered. Advantages of such system are shown. They are caused by improvement of data interpretation and by decrease of ionosphere influence. Tasks of surface and subsurface sensing by the complex SAR were under investigation for vegetation, soil covers are given. As an example, the investigation results of coniferous forest areas backscattering by the spaceborne P-band SAR together with L-band SAR in the September-February period are presented. Studies have shown that the joint use of the results in L and P bands offer unique opportunities to explore the effects of changes in the backscattering properties of forest surfaces.

This article presents a narrative review of neonatal and paediatric complications in post-dated pregnancy and covers scientific views on the aetiology, pathology, risk factors, symptoms and complications of post-dated pregnancy. A pregnancy extending beyond 42 weeks of gestation is termed as a post term pregnancy. There are multiple complications that can occur in the perinatal period, some of the most common ones are stillbirth, asphyxia, meconium aspiration syndrome, fetal distress syndrome, etc which are found to be greater in post-dated pregnancy and hence ultimately leads to increased mortality and morbidity of the new born. Studies have shown that post-term pregnancy also causes increased risk of developing behavioural and emotional problems in children of paediatric age group. It is surprising not much importance has been given to the maternal and neonatal consequences of post- term pregnancies. It is not well understood why some women experience post-dated pregnancies. It is found that factors such as hormones and genetic build up, are responsible for causing post-term pregnancy in an obese female. The treatment and management of a post-term pregnancy still poses a challenge to clinicians in determining the right choice and right time for a particular intervention so that both mother and fetus can be prevented from having complications.

Introduction: Outcome measures using telerehabilitation (TR) in the context of post-stroke rehabilitation is an area of emerging research. The current review assesses the literature related to TR for patients requiring post-stroke rehabilitation. The purpose of this study additionally is to survey the outcome measures used in TR studies and to define which parts of the International Organization of Functioning are measured in trials. Methods: TR studies were searched in Cochrane Central Register of Controlled Trials, PubMed, Embase, Scopus, Google Scholar, and Web of Science from 2016 to June 2023. Two reviewers individually assessed the full text. Disagreements about inclusion or exclusion were determined by consensus or by checking with a third reviewer. Results: A total of 24 studies were included in the current review. The results were synthesized and reported considering the implications of the results within clinical practice, areas of investigation, and strategic implementation. Conclusions: The current scoping review recognized a wide range of outcome measures used in TR studies and helped elucidate gaps in the current use of outcome measures in the literature. The scoping review also informs researchers and end users (i.e. clinicians and policymakers) regarding the most suitable outcome measures for TR.

The purpose of this study was to analyze the influence of Chitosan 0.2% in various final cleaning methods on the bond strength of fiberglass post (FP) to intrarradicular dentin. Ninety bovine incisors were sectioned to obtain root remnants measuring 18 mm in length. The roots were divided: G1: EDTA 17%; G2: EDTA 17% + PUI; G3: EDTA 17% + EA; G4: EDTA 17% + XPF; G5: Chitosan 2%; G6: Chitosan 2% + PUI; G7: Chitosan 2% + EA; G8: Chitosan 2% +XPF. After carrying out the cleaning methods, the posts were installed, and the root cleaved to to generate two disks from each root third. Bond strength values (MPa) obtained from the micro push-out test data were assessed by Kruskal-Wallis and Dwass-Steel-Critchlow-Fligner tests for multiple comparisons (α = 5%). Differences were observed in the cervical third between G1 and G8 (p=0.038), G4 and G8 (p=0.003), G6 and G8 (p=0.049), and Control and G8 (p=0.019). The final cleaning method influenced the adhesion strength of cemented FP to intrarradicular dentin. Chitosan 0.2% + XPF positively influenced adhesion strength, with the highest values in the cervical third.

Actively combating post-harvest food spoilage and waste can dramatically increase the efficiency of food utilization worldwide. In climacteric fruits, chemical treatments such as 1-MCP are an effective way of reducing post-harvest spoilage and waste by inhibiting the fruit’s ability to perceive ethylene. 1-MCP treatment is increasingly being used to explore the complex nature of ripening physiology at a fundamental level, however, differences in application and quantitation methods create difficulties in comparing conclusions across studies. Here we report an effective and reproducible method for 1-MCP application and quantitation for small-medium sized research applications. By use of surrogate alkene standards 1-butene and cis-2-butene, the highly volatile and elusive 1-MCP molecule can be identified and quantified by gas chromatography and subsequent standard curves may be developed. It is hoped that the methodology outlined here can help standardize consistent 1-MCP application for post-harvest research without excessive investment in specialized equipment.

Post-evaluation of ecological redevelopment is a good method for its achievements. The eco-engineering technologies and achievements of landscape water reconstructed from aquaculture ponds in Shanghai Chenshan Botanical Garden have been introduced in this study. The sediments and water quality were also sampled and tested for basic physicochemical parameters and heavy metal concentration. The ecological redevelopment of landscape water reconstructed from aquaculture ponds was evaluated using the Nemero comprehensive pollution index method. The results shown that nutrients including organic matter, organic nitrogen and their ratio of sediment were found to be in a state of moderate pollution, while their ecological risk of heavy metals was low. Although total nitrogen and total phosphorus of water quality was really higher than that of other indexes, the decline trends of ammonia nitrogen, total nitrogen and total phosphorus was obvious presented over time. In general, this is a good example that redevelopment of water ecosystems from aquaculture ponds using eco-engineering technologies.

Residential satisfaction with post-disaster housing is crucial for the success and sustainability of a resettlement project. However, little attention has been given to this aspect in the permanent houses developed after the 2015 Gorkha earthquake. To bridge this gap, the study examined factors affecting residential satisfaction among poor displaced households resettled in the Panipokhari Integrated Settlement of Nepal. Data were collected through a questionnaire survey, interviews, and field observation. Internal consistency and reliability were assessed using Cronbach's Alpha test, while satisfaction was measured by mean satisfaction scores. The relative importance index ranked the factors, and Spearman's rank correlation coefficient analyzed their relationship with overall residential satisfaction. The study identified several crucial fac-tors influencing residential satisfaction, including the design and layout of the house, space for modification, provision of a kitchen garden and cattle shed, thermal comfort, completeness of the house, provision of a hearth, and spaces for rituals and cultural events. These findings shed light on the resettlement decisions of affected populations and provide valuable insights for policymakers, implementers, and researchers aiming for successful and sustainable resettlement outcomes.

Background: Optimal hypofractionated schedule of post-prostatectomy radiotherapy remains to be established. We evaluated treatment outcomes and toxicity of the moderately hypofractionated post-prostatectomy radiotherapy in 16 daily fractions delivered with IMRT/VMAT. The treatment schedule selection was motivated by limited technology resources. Methods: One hundred consecutive M0 patients with post-prostatectomy radiotherapy were evaluated. Radiotherapy indication was adjuvant (ART) in 19%, early salvage (eSRT) in 46% and salvage (SRT) in 35%. The dose prescription for prostate bed PTV was 52.8 Gy in 16 fractions of 3.3 Gy. The Common Terminology Criteria v.4 for Adverse Events scale was used for toxicity grading. Results: The median follow-up was 61 months. Five-year biochemical recurrence-free survival (bRFS) was 78.6%, distant metastases-free survival was 95.7% and overall survival was 98.8%. Treatment indication was the only significant factor for 5-year bRFS in multivariate analysis which was 84.6% vs. 67.6% for ART or eSRT vs. SRT respectively (HR 0.15, 95% CI 0.05–0.47, p=0.001). Acute GI toxicity grade 2 was recorded in 24%, grade 3 in 2% and acute GU toxicity grade 2 in 10% and no grade 3. Cumulative rate of late GI toxicity grade ≥2 was observed in 9% and late GU toxicity grade ≥2 in 16%. Conclusion: Observed results confirmed efficacy and acceptable toxicity of post-prostatectomy hypofractionated radiotherapy in 16 daily fractions.

Current study was to estimation the post-harvest loss of avocado at the producer level using cross-sectional data obtained from 385 proportionately sampled respondents from Wolaita and Kembata Tembaro Zones, the SNNPR of Ethiopia. Descriptive and multiple regression analysis were used to the amount and determinant of post harvest loss of avocado fruits. Estimated total post harvest- loss of avocados was 24%; of which 5.7% unacceptable harvesting methods and 4.9% of improper storage practices. The respondent's sex, education, income, training, contact with extension agents, distance from the nearest road, and off-farm income were found to be negative determinants, whereas storage accessibility and avocado harvest techniques were found to be positive determinants of post-harvest loss of avocado fruits. Post-harvest management techniques for avocados need to be better understood and used by avocado growers if they are to minimize losses. Post-harvest losses contribute considerably to food insecurity and create a problem for the source of revenue for people and the economy of the country as well. Therefore, the use of a practical and effective post-harvest loss reduction technique could be a sustainable solution to increase food availability, eliminate hunger and improve farmers' livelihoods.

The universal chirality is the commonly accepted view of nature. Biological chirality is the distinct part of the more general phenomena. Following this view, all living organisms are characterized by the non-equilibrium state of their molecular constituents. From the thermodynamic perspective, the non-equilibrium state of biomolecular ensemble holds inevitable consequences being the substrate of spontaneous reactions directed to equilibrium (not associated with life) state. At the protein level, spontaneous biological reactions represent the natural part of proteins' post-translational modifications (PTMs). The essential contribution to the origin and maintenance of the non-equilibrium state belongs to prevalent bio-molecular chirality. Correspondently, spontaneous PTMs such as racemization and glycation, working against life-supporting prevalent chirality, are known as the significant determinants of protein misfolding, dysfunctions, and aggregation. Accumulation of aberrant protein during life-span allows consideration of time-dependent spontaneous racemization and glycation as protein aging. Spontaneous PTMs of proteins is occurring in the interaction with other forms of enzymatic and non-enzymatic PTMs. In this review, we are considering the contribution of spontaneous racemization and non-enzymatic glycosylation to protein aging.

Smoking during pregnancy remains one of the most significant risk factors for poor birth outcomes. The Loma Linda University Health Comprehensive Tobacco Treatment Program (CTTP) is the largest maternal tobacco cessation program in San Bernardino County – the largest county in the contiguous US. CTTP is an eight week, incentivized, behavioral intervention for tobacco cessation for pregnant smokers. As part of program evaluation, we used a retrospective cohort design to assess smoking abstinence and to identify predictors of relapse/smoking after enrollment. Among CTTP cohort enrollees (n=233) from 2012-2013 we found: 1) a 28.4% 8 week point prevalence abstinence (PPA), and at a median of 9 months of follow-up after the PPA, 81.6% continued to indicate tobacco cessation, and 2) a high rate of relapse or loss to follow-up (56%). Our modeling of relapse/smoking after enrollment indicated that this was higher in young mothers, non-Hispanic mothers (White, Black), first/third trimester mothers, and rural mothers. The evaluation identified efficacy of the behavioral model at 8 weeks, but that relapse/smoking was occurring in disparity populations. Formative research is needed to expand the programmatic outreach and enrollment of mothers wanting to quit smoking.

Postpartum depression (PPD), a condition that affects up to the 15% of mothers in high-income countries, reduces attention toward the needs of the child and it is among the first causes of infanticide. PPD is usually identified using self-report measures and therefore the diagnosis may not always be valid. Previous studies highlighted the presence of significant differences in the acoustical properties of the vocalizations of children of depressed and healthy mothers. In this study, cry episodes of infants of depressed and non-depressed mothers are analyzed to investigate the possibility that a machine learning model can identify PPD in mothers from the acoustical properties of infants' vocalizations. Acoustic features (F0, F1-4, Intensity) are first extracted from recordings of crying infants, then novel cloud-based artificial intelligence models are employed to identify maternal depression versus non depression from estimated features. Trained model shows that commonly adopted acoustical features can be successfully used to individuate Post-Partum Depressed mothers with very high accuracy (89.5%).

Background: Paracetamol may be use as antipyretic agent for the treatment of fever, as well as an analgesic in the treatment of mild to moderate pain on post vaccination in infants. The use of Paracetamol during fever may be or may not be recommended since it may alter natural human body immune response although it may reduce pain. Objectives: This study described the relevancy of Paracetamol use post infants vaccination based on data collection systematic review analyses. This study aims to describe the effectiveness of breastfeeding in reducing pain and Paracetamol in reducing fever and pain post infants vaccination. Data Sources and Study Selection: Electronic literature search by hand searching six (6) databases which include Ovid LWW Total Access Collection and Medline, CINAHL (Cumulative Index to Nursing and Alled Health Literature) Plus with Fulltext, Science Direct, Proquest Dissertations and Theses, Proquest Education Journal and Proquest Health and Medical Complete. Additionally, manual reference checks of all articles on Paracetamol and breastfeeding post infants vaccination published in English Language between 1978 and 2017. Two level of screening were used on 9614 citations which include screening of abstracts and titles followed by full text screening. Data Synthesis: Data synthesis were tabulated into study characteristics, quality and effects. Authors of trials were not contacted for further details or provision of original data if the published report contained insufficient information. The study findings, as reported by the authors, were included in this review. The data in this research cannot be pool due to not enough data regarding odd ratio or relative risk as well as confidence interval in each study. Results: Systematic review of breastfeeding included three (3) studies from 9614 of database searching. The reviews of all these three (3) studies found significant benefit from breastfed in pain score and duration of crying as well as behavioral changes. None study stated the unbeneficial of breastfeeding before, during and after immunization. Meanwhile, systematic review of Paracetamol effectiveness included four (4) studies from 1177 of database searching. The reviews of two (2) studies found significant benefit from prophylaxis Paracetamol in fever and only one (1) study found significant benefit from prophylaxis Paracetamol in fussiness. On the other hand, there was one (1) study found not signifiant benefit from prophylaxis Paracetamol in fever. Other than that, there were two (2) studies evaluate the safety of prophylactic Paracetamol which revealed different outcomes, in which study by Prymula et. al. in 2009 found that antibody responses to several antigens were reduced significantly, and the other study by Uhari et. al. in 1988 found that antibody titres to DTP bacteria of placebo and PCM not differ significantly. Thus, Paracetamol seems to be not relevant post infants vaccination and breastfeeding was found to be beneficial post infants vaccination. Conclusions: The relevancy of giving Paracetamol post all types of vaccination may be questionable since the safety issue of this intervention may be arised. Breastfeeding before, during and after immunization are recommended for pain reduction as it was proved effectively. Finally, in deciding Paracetamol to be of rational use following infants immunization, it may need for further research which include in depth quantitative and qualitative studies to identify specific problem and causes regarding this issue.

Experimental quantification of retention factors related to post-fire strength as well as post-fire ductility of intentionally selected stainless steel grades applied in construction is the objective of research presented here. These steel grades are characterized by a two-phase austenitic-ferritic microstructure of the duplex type. In this context two mutually corresponding chromium-nickel-molybdenum steel grades have been subjected to analysis, namely X2CrNiMoN22-5-3 steel belonging to the standard duplex group (DSS 22% Cr) and X2CrMnNiN21-5-1 steel belonging to the lean duplex group (LDSS). The similarities and differences in the mechanical properties exhibited by these steel grades after effective cooling, following more or less prolonged simulated fire action conforming to several development scenarios, have been identified and indicated. The resistance of given steel grade to permanent structural changes induced by the heating program proved to be the critical factor determining these properties and resulting in many cases in increased susceptibility to brittle fracture.

Introduction: Despite more than one year passed since the first cases of SARS-CoV-2 were reported, there is still no consensus on the definition and clinical management of post-acute-COVID-19. The condition has heterogeneously been named as Chronic COVID syndrome, Post COVID-19 Syndrome, post-acute sequela of SARS-CoV-2 (PASC), and the more familiar long COVID. Method: In order to capture all relevant published studies, we undertook a multi-step search with no language restriction. The following four-step search strategy was utilized: First, a preliminary (limited) search was conducted on January 20, 2021, in Google Scholar and PubMed to identify the appropriate keywords. Then, on January 30, 2021, we adopted a search strategy of electronic databases from Cochrane Library, PsycINFO, PubMed, Embase, Scopus, and Web of sciences, using those keywords. Then, after duplicate removal, we screened all titles, abstracts, and full texts. This resulted in 66 eligible studies. Subsequently, after a forward and backward search of their references and citations an additional 54 publications were found, resulting in a total of 120 publications that formed the basis of the present analysis. The titles, abstracts, and full-texts of non-English articles were translated using Google Translate for further evaluation. We conducted our scoping review based on the PRISMA-ScR Checklist.Results: We found only one randomized clinical trial in our search. Of the 67 original studies, 22 were cohort and 28 were cross-sectional studies totaling 74.6% of the original studies. Of the total of 120 publications, 59 (49.1%) focused on signs and symptoms, 28 (23.3%) were focused on management, and 13 (10.8%) focused on pathophysiology. Ten (9%) publications focused on imaging studies. Ninety-one percent of the original investigations came from high and upper-middle-income countries, highlighting the scarcity of reports originating from low-income and lower-middle-income countries.Conclusion: The predominant symptoms among those with the so-called “Long COVID” were: fatigue, breathlessness, arthralgia, sleep difficulties, and chest pain. Recent reports also point to the risk of long-term sequela with cutaneous, respiratory, cardiovascular, musculoskeletal, mental health, neurologic, and renal involvement in those who survive the acute phase of the illness. The ambiguity and controversies in its definition have impaired proper recognition and management of those requiring additional support following the resolution of the acute phase of this infection. This has resulted in long-standing distress for the patients and their families. Our findings highlight the need for a multidisciplinary approach, support, and rehabilitation for these patients in terms of long-term mental and physical health.

Artificial intelligence (AI) has witnessed an exponential increase in its use in various applications. Recently, the academic community started to research and inject new AI-based approaches to provide solutions to traditional software engineering problems. However, a comprehensive and holistic understanding of the current status is missing. To close the above gap, synthetic knowledge synthesis was used to induce a research landscape of the contemporary research literature on the use of AI in software engineering. The synthesis resulted in 15 research categories and five themes, namely natural language processing in software engineering, use of artificial intelligence in the management of software development life cycle, use of machine learning in fault/defect prediction and effort estimation, employment of deep learning in intelligent software engineering and code management, and mining software repositories to improve software quality. The most productive country was China (n=2042), followed by the United States (n=1193), India (n=934), Germany (n=445), and Canada (n=381). A high percentage (n=47.4%) of papers were funded, showing a strong interest in this research topic. The convergence of AI and software engineering can significantly reduce needed resources, improve quality, increase user experience, and improve the well-being of software developers.

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.

Naturally-derived synthetic leather is a widely used and high-quality type of faux leather or synthetic leather. Many consumers prefer authentic leather goods due to their exceptional qualities, including high water vapor permeability and superior wearing comfort. Consequently, the exploration of artificial leather made from natural materials with exceptional qualities as an alternative to genuine leather has garnered significant interest and is now a highly studied subject. Synthetic leather, sometimes known as imitation leather, has gained popularity recently as a highly suitable alternative to genuine leather. Continuous advances in this area of research increase the range of uses for synthetic leather using natural fibers. Thus, this research aims to explore synthetic leather materials using orange peel waste, which can be applied to the fashion industry. This research applies several types of orange peel waste, such as Pomelo, Sweet orange, and Sunkist orange, to different compositions and strengthening materials, such as bandages and dacron. The resulting bio-composite materials' morphology, mechanics, and adhesive properties were evaluated following ASTM D 2209-00 and ASTM D 4533-04 standards. The results indicate that specimen 1A (Pomelo using bandage as reinforcement) has the most significant effects, with a tensile test value of approximately 472 N/cm2, an elongation of roughly 67.28 % was the highest value on sweet orange using bandage as reinforcement, and a tear resistance of around 14.28 N/cm2 for Pomelo with bandage as reinforcement. Furthermore, the test results also show that composition 2B still does not meet the standards of SNI 1294:2009 and ISO 3376 for tensile strength and ISO 3377-1 for tear strength. Additionally, statistical analysis showed no appreciable changes in the samples analyzed. Furthermore, statistical evaluations showed no significant alterations in the studied samples. The results of this experimental investigation can be explored further and used as a basic framework for the creation of bio-composites from orange peel waste for future fashion.

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 airborne and satellite-based synthetic aperture radar enables the acquisition of high-resolution SAR oceanographic images in which even the outlines of ships can be identified. The detection of ship targets from SAR images has a wide range of applications, such as the military, where the dynamic grasp of enemy targets can help improve the early warning capability of naval defence, and the civilian detection of illegal fishing vessels can help improve the level of maritime management. Due to the density of ships in SAR images, the extreme imbalance between foreground and background clutter, and the diversity of target sizes, achieving lightweight and highly accurate multi-scale ship target detection remains a great challenge. To this end, this paper proposes an attention mechanism for multiscale receptive fields convolution block (AMMRF). AMMRF not only makes full use of the location information of the feature map to accurately capture the regions in the feature map that are useful for detection results, but also effectively captures the relationship between the feature map channels, so as to better learn the relationship between the ship and the background. Based on this, a new YOLOv7-based ship target detection method, You Only Look Once SAR Ship Identification (YOLO-SARSI), is proposed, which acquires the abstract semantic information extracted from the high-level convolution while retaining the detailed semantic information extracted from the low-level convolution. Compared to the deep learning detection methods proposed by previous authors, our model is more lightweight, only 18.43M. We examined the effectiveness of our method on two SAR image public datasets: the High-Resolution SAR Images Dataset (HRSID) and the Large-Scale SAR Ship Detection Dataset-v1.0 (LS-SSDD-V1.0). The results show that the average accuracy AP50 of the detection method YOLO-SARSI proposed in this paper on the HRSID and LS-SSDD-V1.0 datasets is 4.9% and 5% higher than that of YOLOv7, respectively.

For Synthetic Aperture Radar (SAR) image registration, successive processes following feature extraction are required by both the traditional feature-based method and the deep learning method. Among these processes, the feature matching process—whose time and space complexity are related to the number of feature points extracted from sensed and reference images, as well as the dimension of feature descriptors—proves to be particularly time-consuming. Additionally, the successive processes introduce data sharing and memory occupancy issues, requiring an elaborate design to prevent memory leaks. To address these challenges, this paper introduces the OptionEM-based reinforcement learning framework to achieve end-to-end SAR image registration. This framework outputs registered images directly without requiring feature matching and calculation of the transformation matrix, leading to significant processing time savings. The Transformer architecture is employed to learn image features, while a correlation network is introduced to learn the correlation and transformation matrix between image pairs. Reinforcement learning, as a decision process, can dynamically correct errors, making it more efficient and robust compared to supervised learning mechanisms like deep learning. We present a hierarchical reinforcement learning framework combined with episodic memory to mitigate the inherent problem of invalid exploration in generalized reinforcement learning algorithms. This approach effectively combines coarse and fine registration, further enhancing training efficiency. Experiments conducted on three sets of SAR images, acquired by TerraSAR-X and Sentinel-1A, demonstrate that the proposed method’s average runtime is sub-second, achieving subpixel registration accuracy.

The Earth’s synthetic gravitational and density models can be used to validate numerical procedures applied for a global (or large-scale regional) gravimetric forward and inverse modelling. Since the Earth’s lithospheric structure is better constrained by tomographic surveys than a deep mantle, most of existing 3-D density models describe only a lithospheric density structure, while 1-D density models are typically used to describe a deep mantle density structure below the lithosphere-asthenosphere boundary. The accuracy of currently available lithospheric density models is examined in this study. The error analysis is established to assess the accuracy of modelling the sub-lithospheric mantle geoid, while focusing on the largest errors (according to our estimates) that are attributed to lithospheric thickness and lithospheric mantle density uncertainties. Since a forward modelling of the sub-lithospheric mantle geoid comprises also numerical procedures of adding and subtracting gravitational contributions of similar density structures, the error propagation is derived for actual rather than random errors (that are described by the Gauss’ error propagation law). Possible systematic errors then either lessen or sum up after applying particular corrections to a geoidal geometry that are attributed to individual lithospheric density structures (such as sediments) or density interfaces (such as a Moho density contrast). The analysis indicates that errors in modelling of the sub-lithospheric mantle geoid attributed to lithospheric thickness and lithospheric mantle density uncertainties could reach several hundreds of meters, particularly at locations with the largest lithospheric thickness under cratonic formations. This numerical finding is important for a calibration and further development of synthetic density models of which mass equals the Earth’s total mass (excluding the atmosphere). Consequently, the (long-to-medium wavelength) gravitational field generated by a synthetic density model should closely agree with the Earth’s gravitational field.

Continuous glucose monitoring devices allow diabetes condition management. However, when limited data is available, one option is to increase their size by generating synthetic samples. From a homemade wearable prototype was created a real dataset with 18 instances and 53 attributes that capture characteristics of capillary and venous blood glucose, oxygen concentration, pulse rate, skin temperature, and 24 modules and 24 phases related to bio-impedance. The objective of this article is to generate synthetic datasets, and also it investigates the ideal features subset and optimal model for non-invasive diabetes prediction. Gaussian-Copulas (GC), conditional generative adversarial networks (CG), variational autoencoders, and Copula-GAN techniques' were used to generate five synthetic datasets. Experiments show that GC1 and GC2 datasets follow min/max boundaries and are not copies of the original data. Multilayer perceptron regressor outperformed (train and test) with 2.17, 2.51 in MAE; 9.29, 13.59 in MSE; 3.05, 3.69 in RMSE, and 0.95, 0.92 in R2 in GC1, and 2.64, 3.02 in MAE; 11.43, 15.11 in MSE; 3.38, 3.89 in RMSE, and 0.94, 0.92 in R2 in GC2 with eight features. Future work is necessary to explore autoencoder and generative architectures, datasets with diverse characteristics, and the effect of the number of features.

Disinfection byproducts (DBPs) are formed whenever disinfectant ingredients are in contact with organic matter. Due to widespread increase in production and use of disinfectants and antiseptics, the presence of their components in coastal environments is increasing. However, very limited scientific literature is available in regard to the occurrence of DBPs and related compounds in the coastal zone and particularly in seawater. In this context, the aim of this preliminary compilation is to outline the main up-to-date findings and raise awareness on their increasing occurrence in coastal environments. Sampling and analysis of marine samples in the USA, Spain, China, Taiwan, Malaysia, Korea, Kuwait and Hong-Kong revealed the presence of several categories of DBPs and related compounds in coastal environments, with the highest levels being detected in urban areas, probably related to the nearby wastewater treatment plants. The investigations considered in this preliminary compilation, report the detection of DBPs and related compounds as well as the formation of toxic brominated and iodinated DBPs in high levels due to chlorination of wastewater, especially after use of seawater for flushing in toilets. New DBP groups have also been detected, namely halogenated phenolic DBPs and halopyrroles.

The objective of this study was to compare the effect of different botanical powders and synthetic chemical in controlling Sitophilus zeamais in stored maize. A laboratory experiment was done to assess three botanicals, Zingiber officinale, Moringa oleifera, Xylopia aethiopica, in controlling the S. zeamais. The results of this study demonstrated the active potentials of these plant products as plant-derived insecticides against maize weevil. The synthetic chemical used showed both higher weevil mortality and higher grain loss than the botanicals (P< 0.05). The Botanicals also showed significance difference in the mortality rate (P < 0.05) as Z. officinale recorded the highest mortality rate (5.66%) while X. aethiopica recorded the lowest mortality rate (3.66%). The control attained the highest grain damage (7.33%) while amongst the botanicals, the highest was found in Z. officinale (7.33%) and lowest was on M. oliefera (5.33%). The exit holes made by the weevils at the end of the experiment were highest (2.66) in M. oliefera whereas lowest was recorded on X. aethiopica (1.00). Z. officinale, X. aethiopica and M. oleifera were efficacious against S. zeamais instead of synthetic chemical insecticides that have environmental health hazards and they can be used in integrated pest management by farmers and foods merchants. Therefore, since these botanicals have no any adverse effects on the seeds and safe to the environment, they are recommended for future usage in storage grains to control of S. zeamais.

Cryptococcus neoformans is a multidrug-resistant human pathogenic yeast responsible for infections in immunocompromised patients. Here, Itraconazole (ITR), a commercial antifungal drug with low effectiveness against C. neoformans, was combined with different synthetic peptides Mo-CBP3-PepII, RcAlb-PepII, RcAlb-PepIII, PepGAT, and PepKAA. The mechanisms of action responsible for the synergistic effect were evaluated for the best combinations by Fluorescence Microscopy (FM). The synthetic peptides enhanced the activity of ITR by 10-fold against C. neoformans. Our results demonstrated that the combinations could induce pore formation in the membrane and overaccumulation of ROS on C. neoformans cells. Our findings indicate that our peptides successfully potentialize the activity of ITR by reducing it by 10-fold to reach antifungal activity against C. neoformans. Therefore, synthetic peptides are potential molecules to act as co-adjuvant agents in treating Cryptococcal infections.

Klebsiella pneumoniae is a multidrug-resistant opportunistic human pathogen related to various infections. As such, synthetic peptides have emerged as potential alternative molecules. Mo-CBP3-PepI has presented great activity against K. pneumoniae by presenting an MIC50 at a very low concentration (31.25 µg mL-1). Here, fluorescence microscopy and proteomic analysis revealed the alteration in cell membrane permeability, ROS overproduction, and protein profile of K. pneumoniae cells treated with Mo-CBP3-PepI. Mo-CBP3-PepI led to ROS overaccumulation and membrane pore formation in K. pneumoniae cells. Furthermore, the proteomic analysis highlighted changes in essential metabolic pathways. For example, after treatment of K. pneumoniae cells with Mo-CBP3-PepI, it was seen a reduction in the abundance of protein related to DNA and protein metabolism, cytoskeleton and cell wall organization, redox metabolism, regulation factors, ribosomal proteins, and resistance to antibiotics. These reductions lead to the inhibition of DNA repair, inhibition of cell wall turnover, protein turnover, and ROS accumulation leading to cell death. Our findings indicated that Mo-CBP3-PepI might have mechanisms of action against K. pneumoniae cells, mitigating the development of resistance and thus being a potent molecule to be employed in producing new drugs against K. pneumoniae infections.

Autofocus is an essential part of the SAR imaging process. Multi-subaperture autofocus algorithm is a commonly used autofocus algorithm for processing SAR stripmap mode data. The multi-subaperture autofocus algorithm has two main steps, the first is to estimate the phase error gradient within the subaperture, the second is to splice the phase error gradient, that is, to remove the shift amount between the estimated adjacent subapertures’ error gradients. Previous gradient-splicing algorithms assume that the estimation of subaperture error is accurate, but when the estimation of subaperture phase error gradients is not accurate enough, these algorithm performance will be degraded. A new phase error gradient splicing algorithm is proposed in this paper. It roughly estimates the shift amount first, and then finely estimates the shift amount based on the minimum-entropy criterion, which can improve the robustness of splicing especially when the estimation of the phase error gradients of the subaperture is not accurate enough. To speed up the algorithm, a variable-step-size search method is used. Simulation and experimental results show that the algorithm has enough accuracy and still has good performance when other splicing algorithms doesn’t perform well.

The research results presented in the article were carried out during the realization of the project, the aim of which is to develop a method of drying cellulose insulation in power transformers with the use of synthetic ester. This method uses a very high water absorption of the ester. During the drying of transformers, the ester is systematically contaminated with mineral oil, which gradually loses its ability to absorb water. Information on the oil concentration in the mixture is needed in two cases: at the stage of making a decision on the treatment of the mixture and during its treatment. The article presents the results of investigations of two methods: 1) based on the measurement of the mixture density, and 2) based on the measurement of the capacitance of the capacitor immersed in the mixture. The conducted research shows that the method of measuring the density of the mixture gives an uncertainty of 2.6 p. %, while the method of measuring the capacitance of a capacitor gives an uncertainty of 2.2 p. %. A significant advantage of the method of measuring the capacitance is the possibility of using it online to control the ester treatment process.

Increasingly, architects are looking towards nature to design more sustainable, efficient cities to reduce the environmental impact of urban life. At the moment, plants are incorporated into urban design for conservation or aesthetic reasons. Here, I argue plants can be rationally designed into synthetic systems based on chemical and other functional traits to increase the stability of urban infrastructure, protect native biodiversity, and promote human health while meeting key UN Sustainable Development Goals.

Sentinel-1 SAR data preprocessing is essential for several earth observation applications, including land cover classification, change detection, vegetation monitoring, urban growth, natural hazards, etc. The information can be extracted from the 2x2 covariance matrix [C2] of Sentinel-1 dual-pol (VV-VH) acquisitions. To generate the covariance matrix from Sentinel-1 single look complex (SLC) data, several preprocessing steps are required. The ESA SNAP S-1 toolbox can be used to preprocess the data to generate a [C2] matrix. The polarimetric analysis in respective application fields often starts with the covariance matrix. However, due to limited availability of Sentinel-1 SLC data preprocessing workflow standards for polarimetric applications in contemporary research methods, downstream applications unable to comply with these workflows directly. In this paper, we propose a couple of generic practices to preprocess Sentinel-1 SLC data in SNAP S-1 toolbox, which would be beneficial for the radar remote sensing user community.