In this data deposit, I describe a dataset that is the result of content mining 167,318 published articles for statistical test results. As a result of this content mining, 688,112 results from 50,845 articles were extracted. In order to provide a comprehensive set of data, the statistical results are supplemented with metadata from the article they originate from. The dataset is provided in a comma separated file (CSV) in long-format. For each of the 688,112 results, 20 variables are included, of which seven are article metadata and 13 pertain to the individual statistical results (e.g., reported and recalculated p-value). A five-pronged approach was taken to generate the dataset: (i) collect journal lists, (ii) spider journal pages for articles, (iii) download articles, (iv) add article metadata, and (v) mine articles for statistical results.

The identification of a new virus Kiparis-144 (KiparisV) in a half-fed tick I persulcatus, removed from a person in the south of the Russian Far East, determined the goal of further research - to study its role in human pathology and the characteristics of its behavior in the tick microbiome. An ELISA study of 439 blood samples from people affected by tick bites indicated a fairly frequent (up to 16.4±1.7%) encounter of people with the KiparisV virus in the territory of natural foci of the Primorsky Territory. It has been shown that this virus, when mono-infected, can cause clinical symptoms characteristic of acute respiratory diseases. During co-infection under the influence of the KiparisV, there was an increase in the activity of Borrelia spp. with the constant production of antibodies to them only of the IgM class and clinical symptoms of Lyme disease for one year (observation period). Electron microscopy of the KiparisV found in a tick removed from a patient showed a picture of the relationship of the KiparisV (up to 100 nm in size) with unknown representatives of the tick microbiome - pathogens of a viral or bacterial nature. In a comparative aspect, a similar electron microscopic picture of the interaction of the KiparisV virus with a known pathogen of viral nature, the ectromelia virus (ECTV), is presented. The importance of the electron microscopy method in describing the tick microbiome is shown. Thus, it has been established that when co-cultivated in the system the helper-virus KiparisV probably tends to use another pathogen of the tick microbiome for its reproduction, influencing its pathogenicity.

The accurate wellbore pressure control not only prevents from lost circulation/blowout and fracturing formation by managing density of drilling fluid, but also improves productivity by mitigating reservoir damage. The geothermal pressure calculated by constant parameters for geothermal well would bring big error easily, as the changes of physical, rheological and thermal properties of drilling fluids with temperature were neglected. This paper researches the wellbore pressure coupling by calculating the temperature distribution with existed model, fitting the rule of density of drilling fluid with temperature and establishing mathematical models to stimulate the wellbore pressures, which is expressed as the variation of Equivalent Circulating Density (ECD) under different conditions. With this method, temperature and ECDs in the wellbore of the first medium-deep geothermal well ZK212 Yangyi Geothermal Field in Tibet were determined, and the sensitivity analysis was simulated by assumed parameters, i.e. circulating time, flow rate, geothermal gradient, diameters of wellbore, rheological models and regimes, the results indicated the geothermal gradient and flow rate were the most influence parameters on the temperature and ECD distribution, and additives added in drilling fluid should be careful which would change the properties of drilling fluid and induce the temperature redistribution. To make sure the safe drilling, velocity of pipes tripping into the hole, depth and diameter of wellbore are considered to control the surge pressure.

Background and Objective: Patients with spinal muscular atrophy (SMA) treated with a dis-ease-modifying therapy (DMT) are often classified as responders or non-responders based on at-tainment of a specific improvement threshold on validated functional scales. This categorization may significantly impact treatment reimbursement in some countries. The aim of this research is to evaluate the perception of treatment benefit by patients considered as responder or non-responder. Methods: In this non-commercial multicenter study, 99 post-symptomatically treated SMA type I-III patients with a median age of 11.2 (0.39-57.4) years at treatment initiation were stratified into three groups based on their treatment outcomes, i.e. those exhibiting clinically significant improvement (N=41), those with non-clinically significant improvement (N=18), or those show-ing no improvement (N=40). Fifteen months after treatment initiation patients or patients’ care-givers were assessed using a patient-rated scoring system based on the Patient Global Impression of Change (PGIC) scale, comprising 22 questions targeting important aspects and tasks in the daily life of patients with SMA. Results: We found no statistical difference in patient perception of treatment benefit in 17 out of 22 domains across patient groups. Conclusion: Our results suggest that functional motor scales do not recapitulate patients and pa-tients’ caregivers experience about the effect of nusinersen treatment in SMA.

USP21, a member of the ubiquitin protease family, plays a vital role in various biological functions. However, the effects of USP21 dysfunction have yet to be fully understood. Here, we generated Usp21 knockout (KO) mice and conducted microarray to identify genes that Usp21 regulates. Its results raised several genes based on their biological characteristics, and RT-qPCR confirmed their expression. KO mice exhibited significant elevations in the expression of the genes Fabp7 and Nlrc5, which play a role in lipid metabolisms, compared to wild-type mice. Blood tests showed no impairment of liver function but did reveal elevated levels of total cholesterol and free fatty acids in KO mice compared to wild-type mice. These data suggest that Usp21 may play roles in lipid metabolism associated with Fabp7 and Nlrc5. To clarify the involvement of USP21 in human hypercholesterolemia, we examined single nucleotide polymorphisms (SNPs) around USP21 in non-hypercholesterolemic and hypercholesterolemic outpatients. We found that the rs11421 SNP downstream of USP21 was associated with hypercholesterolemia. These data suggest that USP21 plays a role in mice and human lipid metabolism and that its polymorphism may be a diagnostic marker for human hypercholesterolemia.

Sachet water (SW) is a major source of drinking water in most Nigerian homes, thus making it a possible conveyance medium for health risks due to contamination rather than for replenishment of the body. This study collected SW from three busy neighborhoods and investigated for the presence of indicator bacteria – Escherichia coli (E. coli), Total Coliform (TC), Total Heterophilic Bacteria (THB), and Staphylococcus – and some physio-chemical parameters – total dissolved solids (TDS), pH, electrical conductivity (EC), and salinity. Multi-variable and exploratory statistical methods were applied to the results to determine correlations between bacterial contamination levels and perceived brand reputation. Bacteriological test with raw SW samples appeared too numerous to count (TNC) and thus required serial dilutions. After seven dilutions, results obtained revealed that SW brands with good reputation had no TC and E. coli and was statistically significant with groupings of other SW brands (χ2 = 12.28; p < 0.05 and χ2 = 37.96; p < 0.05) respectively. Additionally, SW brands with poor reputation had mean values of TC (19.7X10^8 cfu/ml;14X10^8 cfu/ml1.15X10^8 cfu/ml) and E.coli (18.2X10^8 cfu/ml;38.7X10^8 cfu/ml,32.4X10^8 cfu/ml) exceeding threshold value of zero set by the World Health Organization (WHO). Only one sample from poor reputation brand tested positive for Staphylococcus and was not statistically significant (χ2 =5.2191; p = 0.074). Principal Component Analysis (PCA)/ Factor Analysis (FA) revealed that most of the SW had fecal contamination in an alarming magnitude. Therefore, this study suggests that periodic cleaning of distribution lines, location specific treatment, QC and QA measures should be taken to reduce water security risk for SW consumption in the region.

Current sampling methods for detecting the presence of the invasive freshwater hydrozoan Craspedacusta sowerbii rely mainly on visual confirmation of the medusa stage. Confirming the presence of the polyp stage is equally important to observing medusae since typical late summer/early fall occurrences or observations of medusae are sporadic though becoming more frequent. The polyp stage is important as it is the organism’s primary stage and is present throughout the year depending on water temperatures. Therefore, sampling methods for the polyp stage are commonly the collection of substrates such as rocks, plants or pieces of wood in a given body of water and can be cumbersome to examine. Based on preliminary culturing of the polyp stage on glass and plastic microscope slides in the lab, we designed a novel sampling methodology based on submerging 4 substrate types (small glass petri dishes, Hester-Dendy plates, plastic and glass microscope slides) to confirm the presence of C. sowerbii polyps in the field. We tested this method in various lakes in the Illinois-Indiana region (USA). The sampling method we designed was effective in that C. sowerbii polyps (and sometimes colonies) were found on both plastic and glass slides. While this method can be sufficient for detection of the polyp stage, it also shows significant potential for improvement; we highlight water flow and competition and predation from other organisms as significant factors influencing the collection of C. sowerbii polyps for future methodologies.

Brain metastases are highly evolved manifestations of breast cancer arising in a unique microenvironment, giving them exceptional adaptability in the face of new extrinsic pressures. The incidence is rising in line with population ageing, and use of newer therapies that stabilise metastatic disease burden with variable efficacy throughout the body. Historically, there has been a widely held view that brain metastases do not respond to circulating therapeutics because the blood-brain-barrier (BBB) restricts their uptake. However, emerging data are beginning to paint a far more complex picture where the brain acts as a sanctuary for dormant, subclinical proliferations that are initially protected by the BBB, but then exposed to dynamic selection pressures as tumours mature and vascular permeability increases. Here, we review key experimental approaches and landmark studies that have charted the genomic landscape of breast cancer brain metastases. These findings are contextualised with the factors impacting on clonal outgrowth in the brain: intrinsic breast tumour cell capabilities required for brain metastatic fitness, and the neural niche, which is initially hostile to invading cells but then engineered into a tumour-support vehicle by the successful minority. We also discuss how late detection, abnormal vascular perfusion and interstitial fluid dynamics underpin the recalcitrant clinical behaviour of brain metastases, and outline active clinical trials in the context of precision management.

Determination of the presence in the blood of antibodies specific to the causative agent of a particular disease (serodiagnosis) is an effective approach in medical analytical chemistry. Serodiagnostics performed in the lateral flow immunoassay format (immunochromatography) meet the modern requirements for point-of-care testing and are supported by existing technologies of large-scale diagnostic tests production—thus raising increased attention in a tense epidemiological situation. For traditional lateral flow serodiagnostics formats, a large number of nonspecific immunoglobulins in the sample significantly reduces the degree of detectable binding. To overcome these limitations, an assay based on the formation of immobilized antigen— specific antibody—labeled antigen complexes detection was proposed. However, the requirements for its implementation, providing maximum sensitivity, have not been established. This article describes the mathematical model for the above assay. The influence of the ratio of reagent concentrations on the analysis results is considered. It is noted that the formation of specific antibody complexes with several labeled antigens is the main limiting factor in reducing the detection limit, and methods are proposed to minimize this factor. Recommendations for the choice of the assay conditions, following from the analysis of the model, are confirmed experimentally.

Here, we report on ZnO nanoparticles (NPs) generated by nanosecond pulsed laser (Nd:YAG, 1064 nm) through ablation of metallic Zn target in water and air and their comparative analysis as potential nanomaterials for biomedical applications. The prepared nanomaterials were carefully characterized in terms of their structure, composition, morphology and defects. It was found that in addition to the main wurtzite ZnO phase, which is conventionally prepared and reported by others, the sample laser-generated in air also contained some amount of monoclinic zinc hydroxynitrate. Both nanomaterials were then used to modify model wound dressings based on biodegradable poly-L-lactic acid. The as-prepared model dressings were tested as biomedical materials with bactericidal properties towards S. aureus and E. coli strains. The advantages of the NPs prepared in air over their counterparts generated in water found in this work are discussed.

Biodiversity plays an important role in maintaining the ecological balance of the earth. The study of traditional knowledge related to biological resources is a hot issue in the field of international biodiversity conservation. Xishuangbanna is a key area of biodiversity and a cultural hotspot of international significance. According to the Technical Regulation for Classification, Investigation, and Inventory of Traditional Knowledge Relating to Biological Diversity issued by the Ministry of Ecology and Environment, we investigated and catalogued the traditional knowledge related to biodiversity of the Jino people who have lived in Xishuangbanna for generations, and collected 490 entries of traditional knowledge related to biodiversity of the Jino people. Drawing on the traditional knowledge diversity index calculation method proposed by Wang Guoping, the overall traditional knowledge α-diversity index of the Jino people is 0.63, indicating that the richness of the traditional knowledge of the Jinuo people is relatively high. The traditional culture related to biodiversity, the traditional knowledge related to agricultural genetic resources, and the traditional technology related to the sustainable utilization of biological resources are relatively rich and diverse. The diversity index is 0.86, 0.82 and 0.79 respectively. In addition, Xishuangbanna has invested a lot of energy in biodiversity protection, including the establishment of nature reserves, botanical gardens, zoos, ecological tea gardens and other species reserves, the promulgation of laws and policies related to biodiversity protection, and has achieved remarkable results in in-situ protection and ex-situ protection. On the basis of analyzing the progress and achievements of biodiversity conservation in Xishuangbanna, this study points out that Xishuangbanna faces challenges such as the loss of traditional knowledge, insufficient conservation efforts, and great changes in land use, and puts forward corresponding suggestions.

This study explored the intricate nexus between public service provision and land use planning, with a specific focus on the conservation of local plant species in Tambon Khao Phanom, Amphoe Khao Phanom, Krabi Province. Rooted in commitment. The research framework encompasses three fundamental activities: resource survey and collection, resource conservation and utilization, and resource development planning for public services, emphasizing land use planning for local plant species conservation. This multidisciplinary approach integrates the one-map method and draws data from the Department of Land Development to formulate a comprehensive land utilization plan that optimizes land use for biodiversity conservation. This study underscores the critical synergy between public service delivery and land use planning, highlighting their collective potential to advance community well-being and sustainable development.

This paper presents a two-stage ADC based on pseudo-differential operational transconductance amplifier (OTA), which is designed for the readout circuit of X-ray linear array sensor. This hybrid ADC employs an incremental sigma-delta ADC and a cyclic ADC, achieving a good trade-off between accuracy and conversion speed. The two stages share the same hardware to reduce power consumption and die area. A common-mood feedback module is used to suppress the influence of charge injection, and the effectiveness is demonstrated by detailed theoretical analysis. A test chip of 14-bit ADC is fabricated in 0.35μm CMOS technology. The measured root mean square (RMS) value of DNL is 0.254 LSB, and the maximum value of INL is -0.776/+1.56 LSB. The measured effective number of bits (ENOB) is 13.43 bits.

This work reports 60 marine alien molluscs, collected by two Belgian citizen scientists, from nine countries across the Mediterranean Sea and the Sea of Marmara. Some of their published observations concerning the collecting dates are compared with the year of first publication for these alien molluscs reported in the literature, which enabled to backdate some of these introductions. This underlines the importance of collaboration between volunteers and institutional scientists in tracing variations and changes in the environment and biodiversity.

This study investigates the historical variability in annual average precipitation in the northwest region of Mexico, aiming to evaluate the cumulative impact of precipitation on soil degradation and associated risks posed by rainfall. Despite being known as "The Agricultural Heart of Mexico," the region's soil has experienced significant damage to its granulometric structure due to unpredictable rainfall patterns attributed to climate change. Sixteen historical series of average annual rainfall were analyzed as stationary stochastic processes for spectral analysis. The results revealed exponential decay curves in each radial spectrum, indicating a linear relationship between frequency and amplitude. These curves identified initial impulses correlated with moments of severity for structural damages caused by rainfall-induced degradation. The degradation process, exacerbated by water stress, accelerates, as evidenced by maps illustrating approximately 75% soil damage. In the context of climate change and the uncertainty surrounding soil responses to extreme meteorological events, understanding this phenomenon becomes crucial. Recognizing the dynamic nature of soil responses to environmental stressors is essential for effective soil management. Emphasizing the need to employ numerical processes tailored to new environmental considerations related to observed soil damages is crucial for sustainable soil management practices in any region.

Climate change, increasing global food needs, and decreasing global resources brought a new era to human every-day live with a strong turn to circular economy and sustainability. Food packaging and preservation is an important global sector where enchanced research is carried out. New methods such as active packaging and chemical preservatives replacement are of major interest. Many researchers were published studies about active packaging films, replacement of chemical preservatives with natural originated extracts, and novel incorporation procedures. Sequentially to our and other scientists’ previous work, in this paper we present the results of the improvement which was achieved by incorporating the developed nanohybrid of natural-halloysite/carvacrol-extract, the pure natural carvacrol extract and the commonly used low-density-polyethylene. The well known corona-treatment procedure was employed to produced the optimum final film and the results shown that the low-density-polyethylene incorporated with natural-halloysite/carvacrol-extract nanohybrid and coated external with extra carvacrol extract exhibited aproximatelly 100% higher Young-Modulus values, slightly decreased ultimate strength by 20%, and almost stable elonation at break properties. The water-vapor and oxygen barrier increased by 40%. Finally, the antioxidant activity of the corrona-treated film increased by 28% compared to the similar but untreated product because of the lower release rate of the carvacrol.

Background and aims. Clinically significant delayed bleeding (CSDB) may complicate endoscopic colorectal submucosal dissection (ESD). Methods. We assessed the results of a prospective registry of colorectal ESD. We evaluated the effect of clip closure and PuraStat application for prevention of CSDB. Results. 40 patients with 41 colorectal ESD were included. ESD was successful in 38 lesions (92.7%), 35 with R0 resection (92.1%) and 33 with curative resection (86.8%). CSDB occurred in 3 out 38 lesions (7.9%, 95% CI [1.7 – 21.4%]), exclusively after rectal ESD (3 of 22 rectal lesions vs. 0 of 16 colonic lesions, p = 0.249). Clip closure was more frequently used after colonic ESD (12 of 16 colonic lesions vs. 2 of 22 rectal lesions, p < 0.001) and was not protective for CSDB in univariate analysis, even though no events occurred after clip closure (0 of 14 lesions with clip closure vs. 3 of 27 lesions without, p = 0.283). PuraStat was more frequently applied after ESD for rectal lesions (16 of 22 rectal lesions vs. 2 of 16 colonic le-sions, p < 0.001) and was not protective for CSDB, all three events occurring after PuraStat application (3 of 21 lesions with PuraStat application vs. 0 of 20 lesions without, p = 0.097). Conclusions. CSDB occurred exclusively after rectal ESD, and no predictive factors were identified in uni-variate analysis. Clip closure and PuraStat application were not protective for CSDB.

We present an analysis of high-resolution, near-infrared (NIR) spectra relative to the solar transit of Venus of 5-6 June 2012, as observed with the Facility Infrared Spectropolarimeter (FIRS) at the Dunn Solar Telescope in New Mexico. These observations offer the unique opportunity to probe the upper layers (between ∼84 and 150 km in altitude) of a thick, CO2-dominated atmosphere with the transmission spectroscopy technique – a proxy for future studies of highly-irradiated atmospheres of Earth-sized exoplanets. We were able to visually identify absorption lines from the two most abundant CO2 isotopologues, and from the main isotopologue of CO in the retrieved spectrum of Venus. Furthermore, we perform a cross-correlation analysis of the transmission spectrum using transmission templates generated with petitRADTRANS. With the cross-correlation technique, it was possible to confirm detections of both CO2 isotopologues and CO. Additionally, we retrieve a cross-correlation signal for O3 on Venus. We demonstrate the feasibility of high-resolution, ground-based observations to study the chemical inventory of planetary atmospheres, employing techniques commonly used in exoplanet characterization.

Digital photogrammetry has attracted widespread attention in the field of geotechnical and geological survey due to its low-cost, ease of use and contactless mode. In this work, with the purpose of studying the progressive block surficial detachments of a landslide we developed a monitoring system based on fixed multi-view time-lapse cameras. Thanks to a new-developed photogrammetric algorithm based on the comparison of photo sequences through a structural similarity metric and the computation of the disparity map of two convergent views we can quickly detect the occurrence of collapse events, determine their location and calculate the collapse volume. With the field data obtained at the Perarolo landslide site (Belluno Province, Italy), we have preliminary tested the effectiveness of the algorithm and its accuracy in the volume calculation. The method of quickly and automatically obtaining collapse information proposed in this paper can extend the potentials of landslide monitoring system based on videos or photo sequence and it will be of great significance for further research on the link between the frequency of collapse events and the driving factors.

This article presents a new input device for spastic patients and others with similar symptoms. The sensor consists of a disc used to determine positions and can replace standard joysticks in medical devices such as electric-powered wheelchairs. Using a standard joystick while operating a powered wheelchair can result in dangerous situations when spastic movements occur and extremities cramp making them uncontrollable. To avoid this, a disc was developed that can be controlled with any body part. By shifting weight (x- and y-axis) the disc can tilt in any direction creating a proportional output signal and can also be pushed down in the center (z-axis) to open a menu on a screen for example. When spasms occur it is impossible for users to get stuck on the input device because the disc is flat and can be mounted within a control panel. Body parts coming into contact with the disc would merely slide across the disc without triggering unintentional actions. The sensor presented here is also adaptive and can be adjusted to fit a user’s strength and range of motion. This proposal aims to develop an input device that enables spastic patients to operate sensitive systems safely.

In this paper, we establish the generalized Qi-type inequality involving conformable fractional integrals. The results presented here would provide extensions of those given in earlier works.

From a structural point of view, understanding interfacial electrostatic features of ligand-receptor complexes is crucial for biophysics-based design of therapeutics with improved efficacy and safety. Here, with a high-throughput structural feature extraction approach, this article reports a set of electrostatic structural features from glucagon-like peptide-1 (GLP-1) and GLP-1 receptor (GLP-1R) complex structures determined using experimental tools. Leveraging a set of computational structural biophysical analyses, this article systematically characterized the electrostatic interactions within the GLP-1-GLP-1R complexes with two sets of criteria to identify interfacial salt bridges and hydrogen bonds. Overall, the results here reveal intricate details of electrostatic interactions critical for GLP-1 binding to its receptor GLP-1R, providing biophysical insights into the stabilization of the GLP-1-GLP-1R complex structure and the molecular basis of GLP-1/GLP-1R signaling. Furthermore, the electrostatic structural features extracted from GLP-1 and GLP-1R complex structures are useful in the development of a machine learning-based ligand-receptor binding affinity calculating model, i.e., a GLP-1-GLP-1R-specific general intermolecular binding affinity calculator (GIBAC), paving the way for accelerated discovery and structure-based design of drug candidates targeting the GLP-1/GLP-1R system with improved efficacy and safety.

In this paper, we integrate the Finite Element Method (FEM) with orthogonal polynomial approximation in high-dimensional spaces to innovatively model the Moon’s surface gravity anomaly. Our aim is to approximate solutions to Laplace’s classical differential equations of gravity, employing classical Chebyshev polynomials as basis functions. Using classical Chebyshev polynomials as basis functions, the least-squares approximation was used to approximate discrete samples of the approximation function. These test functions provide an understanding of errors in approximation and corresponding errors due to differentiation and integration. These test functions provide an understanding of errors in approximation and corresponding errors due to differentiation and integration. The first application of this project is to substitute the globally-valid classical spherical harmonic series of approximations with locally-valid series of orthogonal polynomial approximations (i.e. using the FEM approach). With an error tolerance set at 10−9ms−2, we use this method to adapt the gravity model radially upwards from the lunar surface. The results showcase a need for a higher degree of approximation on and near the lunar surface, with the necessity decreasing as the radius increases. Notably, this method achieves a computational speedup of five orders of magnitude when applying the method to radial adaptation. More intrinsically, our second application involves using the methodology as an effective tool in solving boundary value problems. Specifically, we implement this approach to solve classical differential equations involved with high precision, long-term orbit propagation. This application provides a four-order of magnitude speedup in computational time while maintaining an error within the 10−10ms−2 error range for various orbit propagation tests. Alongside the advancements in orthogonal approximation theory, the FEM enables revolutionary speedups in orbit propagation without compromising accuracy.

Artificial intelligence (AI) is a current trend in computer science, which extends itself its amazing capacities to other technologies such as mechatronics and robotics. Going beyond technological applications, the philosophy behind AI is that there is a vague and potential convergence of artificial manufacture and natural world although the limiting approach may be still very far away, but why? The implicit problem is that Darwin theory of evolution focuses on natural world where breeding conservation is the cornerstone of the existence of creature world but there is no similar concept of breeding conservation in artificial world whose things are created by human. However, after developing for a long time until now, AI issues an interesting concept of generation in which artifacts created by computer science can derive their new generations inheriting their aspects / characteristics. Such generated artifacts make us look back on offsprings by the process of breeding conservation in natural world. Therefore, it is possible to think that AI generation, which is a recent subject of AI, is a significant development in computer science as well as high-tech domain. AI generation does not help us to reach near biological evolution even in the case that AI can combine with biological technology but, AI generation can help us to extend our viewpoint about Darwin theory of evolution as well as there may exist some uncertain relationship between man-made world and natural world. Anyhow AI generation is a current important subject in AI and there are two main generative models in computer science: 1) generative model that applies large language model into generating natural language texts understandable by human and 2) generative model that applies deep neural network into generating digital content such as sound, image, and video. This technical report focuses on deep generative model (DGM) for digital content generation, which is a short summary of approaches to implement DGMs. Researchers can read this work as an introduction to DGM with easily understandable explanations.

The identification of fetal cells in the blood and tissues of healthy mothers raised questions about the potential alloreactive origins of various diseases, such as autoimmunity, diabetes, arteriosclerosis, and cancer. However, the extent to which alloreactivity contributes to these diseases remains unverified. This study presents a basic mathematical disease model based on the genes’ origin and immunological interactions. This model, grounded in set theory, classifies these immunological interactions based on their intrinsic, extrinsic, and allogeneic nature. Therefore, this model offers an unexpected common theoretical foundation for understanding alloreactivity, genetic diseases, and infections. Furthermore, this model provides a valuable framework for scrutinizing the role of alloreactivity in health and disease.

This article belongs in the emerging area of research seeking ways to depolarize societies in the short run (around events such elections) as well as in a sustainable fashion. We approach the depolarization process with a model of three homophilic groups (US Democrats, Republicans and Independents interacting in the context of upcoming federal elections). We expand a previous polarization model, which assumed that each individual interacts with all other individuals in its group with mean-field interactions. We add a depolarization field which is analogous to the Blume-Capel model’s crystal field. There are currently numerous depolarization efforts around the world, some of which act in ways similar to this depolarization field. We find that for low values of the depolarization field, the system continues to be polarized. When the depolarization field increases, the polarization decreases.

At the beginning of 2020, with the onset of the pandemic, the traditional learning environment for learners drastically changed globally. Since then, most students/teachers have started and practiced distance and virtual learning/teaching. Thus, a technological breakthrough in virtual learning has followed. In connection with this, many countries worldwide have commenced allocating additional financing and funds for educational institutions' technological improvement and development. The long-term stay in distance learning has revealed and highlighted new problems students face: their knowledge level has decreased, they lack socialization skills, and they face psychological and physical health problems. Due to this negative impact on students, a need to research and evaluate how much the EU countries allocated to solve the distance learning-caused problems and what programs or models they prepared has emerged and encouraged further studies. The research has found that many countries increased their allocations very minimally, e.g., 0.0.1%, but some increased their available budgets to 32%. Notably, most countries did not separate distance learning exit funding from distance learning preparation funding. Based on the problems the countries saw, only a few states identified withdrawal from distance learning as a problem. Considering this, we set ourselves the goal to evaluate exit models from distance learning and allocated funding amounts. The following objectives were planned to achieve the goal: · to evaluate the global practice of exit from distance learning; · to determine the scope of funding for pandemic management; · to evaluate the amounts of funding allocated to manage pandemic-caused consequences and the GDP ratio. Research methods: mathematical-statistical analysis, empirical analysis, and analysis of scientific literature.

A unified critical state model has been developed for both clean sand and silty sand using the modified Cam-clay model (MCC). The main feature of the proposed model is a new critical state line equation in the e-ln(p) plane that is capable of handling both straight and curved test results. With this feature, the error in calculating plastic volumetric strain is eliminated in theory. Another crucial feature of the model is the transformed stress tensor based on the SMP (spatially mobilized plane) criterion, which takes into account the proper shear yield and failure of soil under three-dimensional stresses. Additionally, the proposed model applies the intergranular void ratio with the fines influence factor for silty sand. Only eight soil parameters are required for clean sand, and a total number of twelve soil parameters are needed for silty sand.

Can physical objects be in time-symmetry? Physical objects can only exist in a medium that has physical attributes, which means this medium is a type of energy. Is time energy? This article will show that time is not energy and there is no possibility that physical objects could be in time-symmetry. Physical objects only can be in symmetry in the time-invariant space in which they exist. In this perspective time measured with clocks is the result of the observer’s measurement in the time-invariant space. The time-symmetry model is flawed.

Arthropods are the most abundant and diverse animals on earth. Among them, pancrustaceans are an ancient and morphologically diverse group, comprising a wide range of aquatic and semi-aquatic crustaceans as well as the insects, which emerged from crustacean ancestors to colonise most terrestrial habitats. Within insects, Drosophila stands out as one of the most powerful animal models, making major contributions to our understanding of development, physiology and behaviour. Given these attributes, crustaceans provide a fertile ground for exploring biological diversity through comparative studies. However, beyond insects, few crustaceans are developed sufficiently as experimental models to enable such studies. The marine amphipod Parhyale hawaiensis is currently the best established crustacean system, offering year-round accessibility to developmental stages, transgenic tools, genomic resources, and established genetics and imaging approaches. The Parhyale research community is small but diverse, investigating the evolution of development, regeneration, aspects of sensory biology, chronobiology, bioprocessing and ecotoxicology.

In bioprocess engineering the Qualtiy by Design (QbD) initiative encourages the use of models to define design spaces. However, clear guides on how models for QbD are validated are still missing. In this review we provide a comprehensive overview about validation methods, mathematical approaches and metrics currently applied in bioprocess modeling. The methods cover analytics for data used for modeling, model training and selection, measures for predictiveness and model uncertainties. We point out general issues in model validation and calibration for different types of models and put this into context of existing health authority recommendations. This review provides the start-point for developing a guidance for model validation approaches. There is no one-fits-all approach but this review shall help to identify the best fitting validation method or combination of methods for the specific task and type of bioprocess models that is developed.

This work argues the mass term in the neutrino wavefunction propagator is due to entanglement with its associated origins. The implication being that neutrino flavor is conserved in weak processes and shared among all particles emanating from the last interaction with a nucleon. In so doing, the neutrino mass propagator is real but not ascribed to the neutrino outside of entanglement. The proposed theory will be readily testable in that reactor and solar neutrinos will oscillate but both muon decay neutrinos and accelerator neutrinos created by pure lepton interactions will not oscillate..

Baggage overweight is a significant phenomenon in the air travel in- dustry which is both regulated by the governments and highly profitable for the airlines. The recent years increase in airlines' profits is attributed to so-called ancillary payments – all consumer costs excluding the actual transportation fare. Baggage overweight fees, being a part of such pay- ments, have high profit-generation potential. Is the pricing for baggage overweight positioned correctly? The rationality of policies currently used by airlines is questionable, as they lack a customer-oriented marketing ap- proach. The general purpose of this research is to explore the possibilities of rational baggage overweight pricing for airlines by developing a multi- level price optimization model aimed to maximize company revenue. The modeling is based on determining consumer Willingness-To- Pay values for baggage overweight, and providing an optimal ticket price for them to maximize company expected revenue. The total profit value is forecasted too, based on the company market share and revenue level.

A sustainable business model describes the rationale of how an organization creates, delivers, and captures value, in economic, social, cultural or other contexts in a sustainable way. The process of sustainable business model construction forms an innovative part of business strategy. Different industries and business types have utilized sustainability business models to satisfy their economic, environmental and social goals simultaneously. This study is conducted to present the state of the art of sustainable business models in various application areas. The business models are classified and reviewed in different application groups. To do so, a review is conducted, and the findings reveal that the application of sustainability business models can be classified in 16 unique categories. The key contribution of this study is providing an insight about the state of the art of sustainable business models in various application areas and its research path.

Current-quark masses are compared to the rest masses allowed by the Helmholtz equation in a polar model. Within the uncertainty of the current u quark mass determination, the current quark mass coincides with the rest mass allowed by the Helmholtz equation in the polar model in accordance with the second root of the zero Neumann function. Current d quark mass coincides with the rest mass calculated in accordance with the third root of the Bessel zero function. On the basis of a comparison of these results with the results obtained earlier for ordinary real particles u and d quarks stability is discussed.

Objective: To investigate the use of blood levels of N-(2 cyanoethyl)valine (CEVal), a haemoglobin adduct of acrylonitrile, to assess lack of compliance with smoking cessation. Methods: We report CEVal concentrations and percentiles over time for 2 cessation groups, compliance was established using NNAL concentrations. CEVal half-life was estimated. Optimal thresholds were calculated based on receiver operating characteristics analysis. Results: At 180 days, among 67 participants in the continued smoking group and 159 assigned to smoking cessation or sole THP use. CEVal half-life was estimated to be approximately 30 days and the optimal thresholds were for NNAL at 40 pg/mL and CEVal at 35 pmol/g globin (81% sensitivity and specificity). Conclusions: A new generation of biomarkers of compliance is required, specific to the new generation of nicotine products. Methodological validation and standardisation could allow robust assessment of effects across clinical and observational studies while promoting comparability between studies. CEVal could play an important role as biomarker of compliance for smoking cessation and switching studies.

In the past few decades, the tourism sector has emerged as a significant economic activity in island nations, particularly in tropical regions. However, most of the tropical islands face similar constraints. National and international tourists visit the SIDS including A & N Islands and contribute to the GDP to significant share. The Covid-19 outbreaks in SIDs including A & N islands shows that number of people infected were less as compared to metros or big cities. However, tourism activities completely stopped due to lockdown resulting in decreasing tourist’s arrival, declined GDP and per capita income of SIDs to greater extent. The information gathered from various sources, mass media and net analysed and interpreted in this chapter. Due to Covid-19 tourist’s arrival declined which has serious consequences on the livelihood of islander. Our analysis revealed A&N Islands deficit in energy available at from different sources by 18.26%. However, they are surplus in protein. The burden of high expenditure coupled with poor infrastructure makes them more vulnerable in the circumstance of pandemic outbreaks. This outbreak has created the question of survival due to loss of jobs, halted economic activates, psychological, health unrest and livelihood threats among the depending people of these Island nations. Therefore, government interventions and subsidized package is very much essential to revive the tourism industry.

In this paper, closed forms of the sum formulas $\sum_{k=0}^{n}W_{k}^{2}$ \ for the squares of generalized Tetranacci numbers are presented. We also present the sum formulas $\sum_{k=0}^{n}W_{k+1}W_{k},$ $\sum_{k=0}^{n}W_{k+2}W_{k},$ and $\sum_{k=0}^{n}W_{k+3}W_{k}.$ As special cases, we give summation formulas of the of Tetranacci, Tetranacci-Lucas and some other fourth order linear recurrance sequences.

1,3,5-Tris-(α-naphthyl)benzene is an organic non-electrolyte with notable stability of an amorphous phase. Its glassy and supercooled liquid states were previously studied by spectroscopic and calorimetric methods. However, the thermodynamic parameters of phase transitions available from the literature are inconsistent. In this work, the heat capacities of crystalline and liquid phases, the temperature dependence of the saturated vapor pressures, fusion and vaporization enthalpies were determined using differential and fast scanning calorimetry and verified using the estimates based on solution calorimetry. The structural features of 1,3,5-tris-(α-naphthyl)benzene are discussed based on the computations performed and the data on the molecular refractivity. The consistency between the values obtained by independent techniques was demonstrated. The deviations in the previously published data were attributed to possible polymorphism.

The term `motor control´ encompasses a wide range of mechanisms thought to be implicated in the organization of movements. Their study, like that of any other scientific field, must use specific notions to get to grips with them. This review is therefore organized along a series of notions that are frequently used in motor control, and we will discuss them with particular emphasis on neurological conditions, which may disrupt normal motor functioning. We will start with a short description of the roles of space and time, in which movements take place. Subsequently we will deal with kinematics and kinetics (dynamics) of movements. Then, we will list the inputs to motoneurons (MNs), which, in different forms, convey signals from the central nervous system (CNS) to skeletal muscles and muscle spindles, including central pattern generators (CPGs), sensory inputs and supraspinal descending fiber systems. Some helpers in movement organization will be introduced, such as internal models and neuronal network models. A relatively brief section on sensory-motor learning will follow because learning abilities are required to endow the sensory-motor system with flexibility and adaptability. The major emphasis is placed on neurological processes, which result from genetic modifications, autoimmune diseases, neurodegenerative diseases, infections in the nervous system as well as vascular and traumatic lesions. These neurological diseases lead to a variety of impairments and symptoms, particularly movement derangements including cerebellar ataxia, spasticity, and (other) movement disorders such as Parkinson’s syndromes. The conclusion is that there is no unique top controller that controls ´motor control`.

Herein we present the biocatalysed preparation of mono-N-carbamate-protected precursor of antitumoral Nutlin-3a, through enantioselective alkoxycarbonylation of meso-1,2-disubstituted-1,2-diaminoethane, using enzyme lipases and dialkyl carbonates as acylating agents. A series of supported or free lipase enzymes were screened in combination with commercially available diallyl-, diethyl and dimethyl- carbonate. The reactions were conducted at different temperatures, reaction times and with variable co-solvent systems to evaluate the effect on the enzyme catalytic activity. The best results in terms of conversion, enantiomeric excess and yield were obtained when lipase from Candida antarctica B (CAL-B) was used with diallyl carbonate (DAC) conducting the reaction solventless at 75 °C.

This article raise a topic of critical examination of polypropylene, a key polymeric material, and its extensive application within the automotive industry, particularly focusing on the manufacturing of brake fluid reservoirs. The study aims to enhance the understanding of polypropylene's behavior under mechanical stresses through a series of laboratory destruction tests and numerical simulations, emphasizing the Finite Element Method (FEM). A novel aspect of this research is the introduction of the PEAK parameter, a groundbreaking approach designed to assess the material's resilience against varying states of strain, known as triaxiality. This parameter facilitates the identification of critical areas prone to crack initiation, thereby enabling the optimization of component design with a minimized safety margin, which is crucial for cost-effective production. The methodology involves conducting burst tests to locate crack initiation sites, followed by FEM simulations to determine the PEAK threshold value for the Sabic 83MF10 polypropylene material. The study successfully validates the predictive capability of the PEAK parameter, demonstrating a high correlation between simulated results and actual laboratory tests. This validation underscores the potential of the PEAK parameter as a predictive tool for enhancing the reliability and safety of polypropylene automotive components. The research presented in this article contributes significantly to the field of material science and engineering by providing a deeper insight into the mechanical behavior of polypropylene and introducing an effective tool for predicting crack initiation in automotive components. The findings hold promise for advancing the design and manufacturing processes in the automotive industry, with potential applications extending to other sectors.

There are experimental evidences that chronic social defeat stress is accompanied by development of anxiety- and depression-like state as well as downregulation of serotonergic genes in the midbrain raphe nuclei of male mice. The study was aimed at investigating the effect of chronic lithium chloride (LiCl) administrations on anxiety behavior and the expression of serotonergic genes in the midbrain raphe nuclei of affected mice. The pronounced anxiety in male mice was caused by chronic social defeat stress in daily agonistic interactions. After 6 days of social stress, defeated mice were treated with saline or LiCl (100 mg/kg, i.p. two weeks) against the background of continuing agonistic interactions. The level of anxiety was assessed using behavioral tests. The effect of chronic treatment with LiCl on the expression of serotonergic genes in the midbrain rapher nuclei was also studied. Mild anxiolytic effects of LiCl were found on communication in the partition test. Anxiogenic-like effects assessed using the elevated plus-maze and social interaction tests were found. Chronic LiCl treatment induced overexpression of the serotonergic genes in the midbrain raphe nuclei. The effects of chronic LiCl treatment depends on the method of treatment, psychoemotional state, and experimental context (tests).

Pigeonpea (Cajanus cajan) is one of the important grain legume crops cultivated in the semi-arid tropics, playing a crucial role in the economic well-being of subsistence farmers. India is the major producer of pigeonpea, accounting for over 75 per cent of the world's production. Sterility mosaic disease (SMD), caused by Pigeonpea sterility mosaic virus (PPSMV) and transmitted by the eriophyid mite (Aceria cajani), is a major constraint to pigeonpea cultivation in the Indian subcontinent, leading to potential yield losses of up to 100 per cent. The recent characterization of another Emaravirus associated with SMD has further complicated the etiology of this challenging viral disease. This review focuses on critical areas, including the current status of the disease, transmission and host-range, rapid phenotyping techniques, as well as available disease management strategies. The review concludes with insights into the future prospects, offering an overview and direction for further research and management strategies.

Background: over the past 20 years, the treatment scenario of multiple sclerosis (MS) has radically changed and an ever-increasing number of disease-modifying treatments has emerged. Among high efficacy treatment agents, monoclonal antibodies (mAbs) have become a mainstay in the MS patient’s treatment due to their targeted mechanism, high efficacy and favorable risk profile. The latter varies from drug to drug and a skin cancer warning has emerged with sphingosine 1-phosphate receptors inhibitors. Several cases of skin malignancy in people with MS (pwMS) undergoing therapy with mAbs have also been described, but dermatological follow-up is not currently indicated. Objectives: the aim of this review is to investigate cases of cutaneous ma-lignancy during mAbs therapy and to explore possible pathophysiological mechanisms to evaluate the potential need for regular dermatological follow-up in pwMS treated with mAbs. Methods: literature search for original articles and review in PubMed. No date restrictions. Results: 1019 results were retrieved. Duplicates were removed using Endnote and manually. Only peer-reviewed studies published in English were considered for inclusion. At the end of these screening procedures, 54 studies published between 2001 and 2023 that met the objectives of this review were selected and reported. Conclusions: the available data do not show a clear link be-tween monoclonal antibody (mAb) treatment in pwMS and the risk of skin cancer. At present, these treatments remain contraindicated for people with cancer. Dermatological screening is ad-visable before starting mAb treatment in pwMS, and subsequent follow-up should be individual-ised according to each patient's risk profile.

Today the Vocational Education and Training curriculum is state-regulated, combining school-based and work-based learning it is offered at upper-secondary and post-secondary levels. The main problem of nowadays period for Vocational Education and Training is about preparing a new agenda for technical education in Greece for the new circumstances. Our paper aims to enrich, redefine, and expand the current curricula and educational practices, while also proposing a complete plan for the overall reformation of Vocational Education and Training’s learning conditions from the point of view of teaching and learning analytics. Through the existing changing institutional framework, the updated bibliographic references, and the experiential data of the educational reality research, we can understand the expected needs of technological educators and decide how to address the priorities that must be determined. As a result of expectation and one of the main topics of this paper, we focus on the preparation of the trainers and the overall redefinition of the role of education in preparing graduates. This paper's main conclusions or interpretations for the cognitive orientation of the existing curricula, as well as the directions of the thinking and teaching skills of teachers, and to build confidence in the prospects of technical education in Greece.

There is considerable interest in the use of doxycycline post exposure prophylaxis (PEP) to reduce the incidence of bacterial sexually transmitted infections (STIs). An important concern is that this could select for tetracycline resistance in these STIs and other species. We searched PubMed and Google Scholar, (1948–2023) for randomized controlled trials comparing tetracycline PEP with non-tetracycline controls. The primary outcome was antimicrobial resistance (AMR) to tetracyclines in all bacterial species with available data. Our search yielded 140 studies, of which three met the inclusion criteria. Tetracycline PEP had no effect on the prevalence of tetracycline resistance in Neisseria gonorrhoeae in any of the three trials or the pooled estimates. PEP did, however, have a marked effect on the tetracycline MIC distribution in the one study where this was assessed. Prophylactic efficacy was 100% at low MICs and 0% at high MICs. In the one study where this was assessed, PEP resulted in a significant increase in tetracycline resistance in commensal Neisseria species compared to the control group but no significant effect on the prevalence of tetracycline resistance in Staphylococcus aureus. The available evidence suggests that PEP with tetracyclines could be associated with selecting tetracycline resistance in N. gonorrhoeae and commensal Neisseria species.

Buyer practices have changed as individuals are figuring out how to live with the new truth of COVID-19. Take-out and conveyance orders have expanded, and our customer has added new items to their menu because of new client inclinations. With every one of the continuous changes, the customer had numerous unanswered inquiries, for example, Smartbridge has broad involvement with café innovation development Café TECHNOLOGY CAPABILITIES :Are the most famous items as yet unchanged after COVID? :Which are the most sold item blends now? :What is the acknowledgment of new things? :What are clients purchasing alongside new things? :How have liquor deals changed? The customer previously had reports that followed item deals and operational measurements, notwithstanding, there was a need to get a more profound knowledge into item examination. The customer expected to recognize what items and introductions were being sold all the more frequently, measure the acknowledgment of new items, and figure out what items clients buy together to improve advertising efforts, advancements, and deals. he E-business industry is filling immensely in the Indian market. The modest 4G web bundles in India clearly gives a push to these ventures. Thus, as Covid19 first hit in Quite a while, individuals got terrified to go out from their homes in light of the fact that, in their mind, it's a dread of Covid. They even wonder whether or not to go out to purchase fundamental (FMCG) products. Frenzy purchasing additionally has seen and to stay away from this dread of COVID-19, individuals are offering inclinations to the E-Commerce destinations to purchase fundamental products and a few clients are new which joined to purchase fundamental merchandise during this Pandemic Lockdown period. Numerous clients are moving their purchasing conduct from disconnected retail locations to online stores. This paper examines the customer buying pattern during lockdown.

The art work of this present paper is to show properly conditions and aspects to reach stability in the process control, as also to avoid instability, by using digital PID controllers, with the intention of help the industrial community. The discussed control strategy used to reach stability is to manipulate variables that are directly proportional to their controlled variables. To validate and to put the exposed principles into practice, it was done two simulations of a continuous fermentation tank process start-up with the yeast strain S. Cerevisiae NRRL-Y-132, in which the substrate feed stream contains different types of sugar derived from cane bagasse hydrolysate. These tests were carried out through the resolution of conservation laws, more specifically mass and energy balances, in which the fluid temperature and level inside the tank were the controlled variables. The results showed the facility in stabilize the system by following the exposed proceedings.

Introduction: The 2019 novel coronavirus (COVID-19) is very contagious, and can be transmitted to other people by droplet, aerosol, sneezing, infected surface, and cough. There is no vaccine or effective treatment at this time. Therefore, the prevention of COVID-19 and the rapid diagnosis of infected patients is crucial. Method: We searched all relevant literature published up to February 28, 2020, from Embase, Scopus, PubMed, Web of Science, and the Cochrane library to collect the studies that reported clinical and laboratory characteristics of COVID-19 infected patients. The study quality was assessed with the Critical Appraisal Checklist. Depending on the heterogeneity test, we used either random or fixed-effect models to analyze the appropriateness of the pooled results. Result: Twenty studies were included in the meta-analysis, including a total of 52,251 patients with confirmed COVID-19 infection. 69.5% (95% CI 54.5-81, p < 0.001) of patients had a history of recent travel to Wuhan, contact with people from Wuhan, or lived in Wuhan. The most common symptoms among COVID-19 infected patients were fever 85.6 % (95% CI 73 -93, p < 0.001), and cough 63 % (95% CI 55.5-70, p < 0.001), respectively. The laboratory analysis showed that thrombocytosis was present in 91% (95% CI 81-98, p < 0.001) CRP was elevated in 81% (95% CI 65-91, p < 0.001), and lymphopenia in 62.5% of cases (95% CI 42-79, p < 0.001). The most common radiographic signs were bilateral involvement in 76.8% (95% CI 62.5-87, p < 0.001) and consolidation in 75.5% (95% CI 50.5-91, p < 0.001) of patients. Most patients (85.4%) were hospitalized, 20.6% of patients were admitted to the ICU in critical condition, and the mortality rate was 5.6%. Conclusions: Fever and cough are the most common symptoms of COVID-19 infection in the literature published to date. Thombocytosis, lymphopenia, and increased CRP were common lab findings although most patients included in the overall analysis did not have laboratory values reported. The most common radiographic sign was bilateral involvement in and consolidation. Among Chinese patients with COVID-19, rates of hospitalization, critical condition, and hospitalization were high in this study, but these findings may be biased by reporting only confirmed cases.

Temperature Cycle Induced Deracemization (TCID) offers a promising approach to obtain enantiopure solids from racemic mixtures. By combining rapid racemization in solution and temperature swings, homochirality is theoretically achieved. Despite theoretical expectations of doubled yields compared to traditional chiral separation methods, such as in Preferential Crystallization, experimental validation remains lacking. We applied TCID to (1-(4-chlorophenyl)-4,4-dimethyl-2-(1H-1,2,4-triazol-1-yl) pentan-3-one) (Cl-TAK), introducing a post-TCID cooling step to enhance yield and a washing step to augment enantiopurity. This refinement yielded an 89.8% mass yield with 99.1% enantiomeric excess in the crystal phase (c.e.e.) within 24 hours on an 8.75g scale, showcasing improved performance with insignificant process duration extension. Additionally, we explored the stochasticity of deracemization, observing the development from low initial crystal enantiomeric excesses(1-6% c.e.e0) at a 2.5 g scale. Kinetic analysis revealed that a 2% c.e.e0 effectively mitigates chiral flipping risks and induction time in our system. Our study underscores the potential for reduced initial c.e.e. to expedite deracemization and presents a straightforward method to optimize yield and purity, facilitating industrial application.

The European Green Deal poses a two-pronged challenge for the automotive industry: migrating to solutions based in light structures, requiring light weight concepts and light materials, while at the same time avoiding dependence towards the importation of these advanced materials. Aluminium alloys are lightweight and cost-effective materials that can successfully cover the requirements of many structural applications, however their production requires from bauxite and other Critical Raw Materials (CRM), such as Si and Mg. Aluminium alloys are fully recyclable, but scrap is usually contaminated and its use is related to an increment of impurities, tramp element and undesired inclusions. Traditionally, the use of secondary alloys has been restricted to low performance applications. The present work analyses the effect that the use of scrap has in the quantity of inclusions present in the alloy and in other properties relevant for the material processing. The study was carried out for common alloys belonging to 3 of the most common aluminium processes used in the car manufacturing industry: High Pressure Die Casting (HPDC) (EN AC-43500), extrusion (6063) and sheet metal forming (5754 and 6181). Reference alloy were mixed with different level of scrap (0, 20, 40, 60, 80 and 100%) trying to keep the chemical composition as unaffected as possible. The inclusions level of the alloy was characterized with the Prefil Foot-printer® test. In addition, the obtained materials, after being cast in an open mould, were subjected to metallographic characterization. Relevant properties to assess the formability quality of the alloys for the corresponding transforming process, were obtained: flowability test for HPDC alloy and high temperature compression for extrusion alloys. The results obtained suggest that the number of inclusions present in the melt highly increase with the amount of scrap used to produce the alloy. These inclusions are also related with an important lost of flowability, but do not have a noticeable impact on microstructure.

We present a precise and universal method for anticipating the thermodynamic characteristics of polyatomic molecules. Unlike conventional computational approaches that rely on numerous experimental spectroscopy or calorimetry data, our model only utilizes a small number of molecular constants. We accurately predicted the values of entropy, enthalpy, specific heat, and Gibbs free energy for boron trifluoride, which were in excellent accordance with the available experimental data. This investigation introduces a new approach to deal with the anharmonic vibrations of polyatomic molecules

Let $m$ and $n$ be the fixed positive integers. Suppose $\mathcal{A}$ is a von Neuman algebra with no central summands of type $I_{1}$ and $L_{m}$ be a Lie type higher derivation i.e., an additive (linear) map $L_{m} :\mathcal{A}\to \mathcal{A}$ such that \begin{equation}\label{def2} \[L_{m}(p_{n}(\mathfrak{S}_{1},\mathfrak{S}_{2},\cdots,\mathfrak{S}_{n}))=\sum_{l_1+l_2+\cdots+l_n=m}p_{n}\big(L_{l_1}(\mathfrak{S}_{1}),L_{l_2}(\mathfrak{S}_{2}),\cdots,L_{l_n}(\mathfrak{S}_{n})\big)\] %L_{m}(p_{n}(\mathfrak{S}_{1},\mathfrak{S}_{2},\cdots,\mathfrak{S}_{n}))=\sum_{l_1+l_2+\cdots+l_n=m}p_{n}\big(L_{l_1}(\mathfrak{S}_{1}),L_{l_2}(\mathfrak{S}_{2}),\cdots,L_{l_n}(\mathfrak{S}_{n})\big)\nonumber \end{equation} for all $\mathfrak{S}_{1},\mathfrak{S}_{2},\cdots,\mathfrak{S}_{n}\in \mathcal{A}$. In the present paper, we study Lie type higher derivations on von Neuman algebras and prove that every additive Lie type higher derivation on $\mathcal{A}$ has a standard form at zero product as well as at projection product. Further, we discuss some more related results.

Seizure development relies on two factors. One is the existence of an overexcitable neuronal network and the other is a trigger that switches normal activity of that network into a paroxysmal state. While mechanisms of local overexcitation have been the focus of many studies, the process of triggering remains poorly understood. We suggest that, apart from the known exteroceptive sources of reflex epilepsy – visual, auditory or olfactory, there is a range of interoceptive triggers, relevant for seizure development in Temporal Lobe Epilepsy (TLE). The hypothesis proposed here aims to explain the prevalence of epileptic activity in sleep and in drowsiness states and provide a detailed mechanism of seizure triggering by interoceptive signals.

The prediction of an extremely severe cyclonic storm (ESCS) is one of the challenging issues due to increasing intensity and its life period. In this study, an ESCS Fani that developed over Bay of Bengal region during 27 April - 4May, 2019 and made landfall over Odisha coast of India is investigated to forecast the storm track, intensity and structure. Two numerical experiments (changing two air-sea flux parameterization schemes; namely FLUX-1 and FLUX-2) are conducted with the Advanced Research version of the Weather Research and Forecasting (ARW-WRF) model by using a moving nest with fine horizontal resolution about 3 km. The high resolution (25 km) NCEP operational Global Forecast System (GFS) analysis and forecast datasets are used to derive the initial and boundary conditions, the ARW model initialized at 00 UTC 29 April 2019 and forecasted for 108 hours. The forecasted track and intensity of Fani is validated with available India Meteorological Department (IMD) best-fit track datasets. Result shows that the track, landfall (position and time) and intensity in terms of minimum sea level pressure (MSLP) and maximum surface wind (MSW) of the storm is well predicted in the moving nested domain of the WRF model using FLUX-1 experiment. The track forecast errors on day-1 to day-4 are ~ 47 km, 123 km, 96 km, and 27 km in FLUX-1 and ~54 km, 142 km, 152 km and 166 km in Flux-2 respectively. The intensity is better predicted in FLUX-1 during the first 60 h followed by FLUX -2 for the remaining period. The structure in terms of relative humidity, water vapor, maximum reflectivity and temperature anomaly of the storm is also discussed and compared with available satellite and Doppler Weather Radar observations.

Cancer-associated fibroblasts (CAFs) in the tumor microenvironment perform glycolysis to produce energy, i.e., ATP. Since the origin of CAFs is unidentified, it is not determined whether the intracellular metabolism transitions from oxidative phosphorylation (OXPHOS) to glycolysis when normal tissue fibroblasts differentiate into CAFs. In this study, we established an experimental system and induced the in vitro differentiation of mesenchymal stem cells (MSCs) to CAFs. Additionally, we performed metabolomic and RNA-sequencing analyses before and after differentiation to investigate changes in the intracellular metabolism. Consequently, we discovered that OXPHOS, which was the primary intracellular metabolism in MSCs, was reprogrammed to glycolysis. In addition, we identified CAF-specific metabolites that were expressed during this reprogramming and determined their presence in the pancreatic tumor tissues of mouse models. Thus, we conclude that normal tissue fibroblasts that differentiate into CAFs undergo a metabolic reprogramming from OXPHOS to glycolysis. Moreover, we identified the CAF-specific metabolites expressed during metabolic reprogramming as potential future biomarkers for pancreatic cancer.

The US opioid overdose epidemic has risen to an all-time high. Prescription opioids often serve as a gateway to illicit opioids which have appreciable overdose potential. Recent investigations have highlighted the efficacy and safety of marijuana-based products for pain management. Providing alternative pain treatment options may help mitigate the opioid epidemic. The distribution of codeine, fentanyl, hydrocodone, morphine, and oxycodone per 100K people and by 3-digit zip codes and overdose rates from 2014 to 2018 in California, which legalized recreational marijuana in 2016, were compared to Texas, where marijuana is functionally prohibited. Drug weights were obtained from the Automation of Reports and Consolidated Orders System and converted to oral morphine milligram equivalents. Overdose data was retrieved from the Centers for Disease Control’s WONDER database. California (-43.7%) and Texas (-27.3%) showed significant reductions in cumulative opioid distribution from 2014 to 2018. Opioid distribution per 100K people decreased -38.9% in California relative to -26.4% in Texas. Opioid and heroin overdoses increased between 1999 and 2019 by +11.6% in California but +272.7% in Texas. This evidence supports marijuana legalization as a mitigating factor to the opioid epidemic and opioid misuse.

Enterococci are gastrointestinal commensals whose hardiness allowed them to colonize very diverse environments, including soils, water, food and feed. This ability to overcome adverse conditions makes enterococci problematic once they colonize hospital niches. Together with the malleability of their genomes, the capacity to acquire and disseminate determinants of antibiotic resistance have contributed to convert what was once just another opportunistic pathogen into a first-class clinical problem. This review discusses the dimension of the emergence of enterococcal resistance to key antimicrobial agents, the dissemination of this resistance and its significance in terms of public health, with the aim of raising the awareness to the need to devise and implement monitoring programmes and effective antibiotic usage guidelines.

In recent years the number of available chemical pesticides has been significantly reduced and there have been an urgent need for discovery of alternative to chemical pesticides products, as among others the natural zeolites (zeolitic rocks). We determined the mineralogical and chemical composition of a specific and continuous layers of zeolitic rock sample (ZeotP) from Petrota, Ev-ros, Greece and evaluated its oviposition deterrent effect for the olive fruit fly Bactrocera oleae (Diptera: Terphritidae). The tested natural zeolite contained 70 wt. % Clinoptilolite, 18 wt. % Amorphous material, 7 wt. % Feldspars, 4 wt. % Cristobalite and 1 wt. % Quartz. We tested the oviposition deterrent effect of ZeotP mixed or not with an emulsifier adjuvant NU-FILM-P® in water and applied on the surface of olive fruits. The ZeotP oviposition deterrent effect for the ol-ive fly was very high under a series of tested temperatures (17°C, 20°C, 25°C and 30°C) and RHs (23%, 33%, 55%, 75%, 94%). In addition, the ZeotP residual deterrent effect after equable water spraying was high and similar to the respective effect of a pyrethroid insecticide (Decis®). Our results may contribute to an effective control of the olive fruit fly using an alternative to chemical pesticides natural zeolite (zeolitic rocks) product.

The debate about the meaning of life in the literature has been around for a while and portraits a fundamental human need to find a personal path of existence. The meaning of life phenomenon purpose lies in its impact on the psychological wellbeing. Knowing your purpose in life can make it more structured and in balance, therefore more meaningful and comprehensible. However, in the existing body of the academic literature meaning of life is discussed more from the philosophic perspective rather than a practical area, which is not helping to solve the global issues of increasing mental health problems. When social and emotional wellbeing is being affected, it is urgent to apply a practical approach to effectively overcome these states. Introduction of a new, holistic meaning of life model is an attempt to offer a practical solution for society to maintain their mental health through awareness of their life’s purpose. Previously in the pilot study (Dombrovskis, 2017) in a sample group of 100 citizens of Latvia who self-reported being in a crisis situation at the given moment, using qualitive analysis the first component for the model structure was identified – antecedent. In our research antecedent is defined as something that triggers certain action, so in crisis situation person can regain a structure and stability in life. We found 8 different antecedents that trigger behavior of those affected by crisis: achievements; power; success; development; freedom; uniqueness; interesting life and fleeing. To continue to explore other components for our model in the setting of Latvia, this study aims to investigate the demographic and personality related variables that may serve as antecedents and as such become one of component in our model structure. The study used a sample of residents of Latvia representing the total population of 1,110 respondents (633 women, 57%, and 477 men, 43%) who have completed the self-assessment questionnaire Meaning of life scale (MOLS) (online and frontally) designed by the authors on their satisfaction with different factors regarding the meaning of life. Average age of respondents (M=33.88; SD=8,527) varied from 18 to 67. The exploratory and confirmatory analysis confirms the data regarding existence of totally 16 factors: 8 antecedents identified in the pilot study and 8 new antecedents identified in the present study - family relations; level of income; relations with friends/acquaintances; state of health; organization of free time; career growth (achievements); sexual life quality and quality of education. Findings confirm a model’s structure to be complex phenomenon consisting of various components. However, findings suggest that more research should be done to fill the following gaps: 1) identify actions, which are triggered by 16 antecedents; 2) figure out F1, F2 and F3 factor role in the model structure.

A robust hydrological assessment is challenging in regions where human interference, within all aspects of the hydrological system, significantly alters the flow regime of rivers. The challenge was to extend a large-scale water resources model, GWAVA, to better represent water resources without increasing the model complexity. A groundwater and a regulated reservoir routine were incorporated into GWAVA using modifications of the existing AMBHAS-1D and Hanasaki methodologies, respectively. The groundwater routine can be varied in complexity when sufficient input data is available but fundamentally is driven by three input parameters. The reservoir routine was extended to account for the presence of large, regulated reservoirs using two calibratable parameters. The additional groundwater processes and reservoir regulation was tested in two highly anthropogenically influenced basins in India: the Cauvery and Narmada. The inclusion of the revised groundwater routine improved the simulation of streamflow in the headwater catchments and was successful in improving the representation of the baseflow component. In addition, the model was able to produce a time series of daily groundwater levels, recharge to groundwater and groundwater abstraction. The regulated reservoir routine improved the simulation of streamflow in catchments downstream of major reservoirs, where the streamflow was largely reflective of reservoir releases, when calibrated using downstream observed streamflow records. The model was able to provide a more robust representation of the annual volume and daily outflow released from the major reservoirs and simulate the major reservoir storages adequately. The addition of one-dimensional groundwater processes and a regulated reservoir routine proved successful in improving the model performance and traceability of water balance components, without excessively increasing the model complexity and input data requirements.

Curcumin, a polyphenol with a rich history spanning two centuries, has emerged as a promising therapeutic agent targeting multiple signaling pathways and exhibiting cellular-level activities that contribute to its diverse health benefits. Extensive preclinical and clinical studies have demonstrated its ability to enhance the therapeutic potential of various bioactive compounds. While its reported therapeutic advantages are manifold, predominantly attributed to its antioxidant and anti-inflammatory properties, its efficacy is hindered by poor bioavailability stemming from inadequate absorption, rapid metabolism, and elimination. To address this challenge, nano-delivery systems have emerged as a promising approach, offering enhanced solubility, biocompatibility, and therapeutic effects for curcumin. We have analyzed the knowledge on curcumin nano-encapsulation and its synergistic effects with other compounds, extracted from electronic databases. We discuss the pharmacokinetic profile of curcumin, current advancements in nano-encapsulation techniques, and the combined effects of curcumin with other agents across various disorders. By unifying existing knowledge, this analysis intends to provide insights into the potential of nano-encapsulation technologies to overcome constraints associated with curcumin treatments, emphasizing the importance of combinatorial approaches in improving therapeutic efficacy. Finally, this compilation of study data aims to inform and inspire future research into encapsulating drugs with poor pharmacokinetic characteristics and investigating innovative drug combinations to improve bioavailability and therapeutic outcomes.

Empowering women and promoting gender equality is crucial for accelerating sustainable development in fragile countries, including the Democratic Republic of Congo (DRC). However, there is scarce existing knowledge or understanding of the factors determining women’s empowerment in these contexts. We aimed to assess women's empowerment and determine its associated factors in Kinshasa, DRC. We analyzed data from the 2021 Performance Monitoring Assessment (PMA) survey. A sample of 1,365 women of childbearing age was retained for this study. Twenty empowerment items related to household decision-making, contraception use, and husband/partner influence were considered. We calculated the average women’s empowerment index (aWEI), identified the women empowerment variables using principal component analysis (PCA), and determined the associated factors for the first three principal components through the performance of multivariate binary logistic regression. In Kinshasa, the overall aWEI was estimated at 0.65. It was low for household decision-making (0.34) and high for husband/partner influence domains (0.93), respectively. Three principal components were identified and named, including the absence of threats, control of sexuality, and participation in decision-making. The factors associated with these components were having internet access, being in free union with a partner, being aged 40-49 years, and residing in a non-slum area. Increasing access to information would enable women in Kinshasa to make strategic decisions about their lives, benefiting themselves and others.

The unique structure of G4.0 PAMAM dendrimers allows the drug to be enclosed in internal spaces or immobilized on the surface. In the conducted research, the conditions for the formation of the active G4.0 PAMAM complex with doxorubicin (DOX) were optimized. The physicochemical properties of the system were monitored using DLS, CD, and fluorescence spectroscopy. The QCM-D method was chosen to determine the preferential conditions for the complex formation. The highest binding efficiency of the drug to the cationic dendrimer was observed under basic conditions when the DOX molecule was deprotonated. The decrease in the zeta potential of the complex confirms that DOX immobilizes through electrostatic interaction with the carrier's surface amine groups. The binding constants were determined from the fluorescence quenching of the DOX molecule in the presence of G4.0 PAMAM. The two-fold way of binding doxorubicin in the structure of dendrimers was visible in the ITC isotherm. Fluorescence spectra and release curves identified reversible binding of DOX to the nanocarrier. Among the selected cancer cells, the most promising anticancer activity of G4.0-DOX was observed in A375 malignant melanoma cells. Moreover, the preferred intracellular location of the complexes concerning the free drug was found, which is important from a therapeutic point of view.

Gastrointestinal parasites (GIP) are diverse parasitic organisms known to have coevolved with bacterial populations inside the gut of mammalian hosts. These helminths produce small molecules, peptides and proteins to evade or fight their hosts' immune systems. Small molecules include polar compounds, amino acids, lipids and carbohydrates. Metabolomics is an emerging field of research recently applied to study helminth infections and host-parasite interactions. This review comprehensively discusses metabolomics studies of small molecules of GIP in animals, providing insights into the available tools and techniques, databases, and analytical software. Most metabolomics investigations employed LC-MS, MS or MS/MS, NMR, or a combination thereof. Recent advancements in metabolomics platforms, including artificial intelligence (AI)-assisted software tools and databases, have propelled helminth metabolomics forward, offering new avenues to explore host-parasite interactions, immunomodulation, and the intricacies of parasitism. As our understanding of helminth metabolomics continues to expand, it promises to unveil novel perspectives and enrich the knowledge of these complex host-parasite relationships.

Background: Escalating climate change concerns have prompted the healthcare sector, particularly anaesthesia, to reassess its practices to align with environmental sustainability. Anesthetic gases like desflurane, sevoflurane, and isoflurane significantly impact the environment due to their high Global Warming Potentials (GWPs) and prolonged atmospheric lifetimes. This manuscript investigates these impacts and advocates for strategies to reduce the carbon footprint of anesthetic care while maintaining patient safety. Methods: We reviewed the environmental impacts of anesthetic gases and explored various strategies for sustainable anaesthesia. These strategies include adopting anesthetics with lower GWPs, enhancing recycling and waste reduction techniques, transitioning to intravenous anaesthesia, and implementing low-flow anaesthesia methods. We also examined barriers to these strategies, such as educational gaps, technological challenges, resistance to change, and policy limitations. Results: Adopting anesthetics with lower GWPs, such as sevoflurane over desflurane, and implementing low-flow anaesthesia can significantly reduce greenhouse gas emissions. Recycling and waste reduction techniques, though challenging, offer additional environmental benefits. Transitioning to intravenous anaesthesia can eliminate the direct GWP contributions from volatile anesthetic gases. However, these strategies require comprehensive education, advocacy for research and innovation, strategic change management, and supportive policies. Conclusions: Continuous monitoring and evaluation are crucial to ensure the effectiveness of sustainable practices in anaesthesia. Establishing robust Key Performance Indicators (KPIs) and utilizing advanced analytical tools will enable the anaesthesia community to adapt and refine practices. Collaborative efforts among clinicians, policymakers, and stakeholders are essential to significantly reduce the environmental impact of anaesthesia and promote ecological responsibility within healthcare.

A new spirurid nematode Protospirura canariensis n. sp., parasite of the black rat Rattus rattus (Rodentia: Muridae) in El Hierro Island (Canary Archipelago, Spain) is described by means of light (LM) and scanning electron microscopy (SEM). The most discriminant characteristics between the new species and the existing species in the genus Protospirura are: (a) the number of tooth-like prominences in the submedian and lateral lobes of pseudolabia, both in males and females (2 and 4, respectively), (b) the size of right and left spicules in males (643–715 µm and 309–412 µm, respectively), and (c) the number and arrangement of cloacal papillae in males. The new species has a total of 17 cloacal papillae (four large and pedunculated pairs of precloacal papillae, an unpaired precloacal papilla and four pairs of postcloacal papillae). The arrangement of postcloacal papillae are as follows: the first pair are large, pedunculated and placed near the posterior edge of cloaca; the three remaining postcloacal pairs are grouped and located near the posterior tip. In the latter group, papillae in the first pair are large and pedunculated. Parasitized host and geographical distribution are also useful criteria to distinguish P. canariensis n. sp. from the remaining species of the genus Protospirura. In addition, the cytochrome c oxidase subunit 1 (cox1) sequence of the new species is provided and compared with available data of related species.

Glioblastomas (GBMs) are the most malignant and intractable of all cancers, with an unfavourable clinical prognosis for affected patients. The objective was analysis the sensitivity of GBM cells to the antimicrobial peptides (AMPs) cathelicidin (LL-37) and protegrin-1 (PG-1), both alone and in combination with chemotherapy, to predict overall survival (OS) in the patients. The study was conducted on 27 GBM patients treated in the neurosurgical departments of the Almazov Medical Research Centre (Saint-Petersburg, Russia) from 2021 to 2024. The cytotoxic effects of chemo-therapy, AMPs and their combinations on brain tumor cells were assessed by MTT assay using 50%-inhibitory concentration (IC50). In GBM cells from the patients, LL-37 and PG-1 exhibited strong anticancer effects, surpassing those of chemotherapy drugs. These LL-37 and PG-1 anti-cancer effects were associated with a statistically significant increase in life expectancy and OS in GBM patients. These findings were confirmed by the experiments on rats with C6 glioma, where intranasal administration of LL-37 (300 μM) and PG-1 (600 μM) increased the life expectancy of the animals to 69 and 55 days, respectively, compared to 24 days in the control group (HR=4.139, p=0.0005; HR=2.542, p=0.0759). Additionally, the combination of LL-37 and PG-1 with chemo-therapy drugs showed that a high IC50 of LL-37 with cisplatin (cutoff >800 μM) in GBM cells was associated with increased life expectancy (19 vs 5 months, HR=4.708, p=0.0101) and OS in GBM patients. These combinations could be used in future GBM treatments.

The ingestion of ethanol presents a significant global public health challenge. Chronic alcohol consumption is associated with the development of conditions such as cancer, cirrhosis, hepatic diseases, cardiovascular diseases, and diabetes, as well as neurological impairments that may predispose individuals to dementia, schizophrenia, and behavioral disorders such as violence and suicide. Alcohol-related fatalities constitute 5.3% of worldwide deaths annually, totaling approximately 3 million. Notably, alcohol consumption is implicated in 25% of cirrhosis-related deaths and 4.1% of cancer-related deaths. Taurine (2-aminoethanesulfonic acid) is a non-protein β-amino acid essential for cellular homeostasis, possessing antioxidant, anti-inflammatory, and cytoprotective properties crucial for life maintenance. This study aimed to evaluate the effects of taurine administration on hippocampal neurogenesis, neuronal preservation or reverse damage in rats exposed to forced ethanol consumption. Results demonstrated the neuroprotective effects of taurine on ethanol-treated rats, promoting tissue regeneration and suggesting its pivotal role in this process. However, this aminoacid failed to induce neurogenesis in the tissues of healthy rats, implying that its activity may be contingent upon post-injury stimuli.

The work presented in this paper makes multiple scientific contributions with a specific focus on the analysis of misinformation about COVID-19 on YouTube. First, the results of topic modeling performed on the video descriptions of YouTube videos containing misinformation about COVID-19 revealed four distinct themes or focus areas - Promotion and Outreach Efforts, Treatment for COVID-19, Conspiracy Theories regarding COVID-19, and COVID-19 and Politics. Second, the results of topic-specific sentiment analysis revealed the sentiment associated with each of these themes. For the videos belonging to the theme of Promotion and Outreach Efforts, 45.8% were neutral, 39.8% were positive, and 14.4% were negative, for the videos belonging to the theme of Treatment for COVID-19, 38.113% were positive, 31.343% were neutral, and 30.544% were negative, for the videos belonging to the theme of Conspiracy Theories regarding COVID-19, 46.9% were positive, 31.0% were neutral, and 22.1% were negative, and for the videos belonging to the theme of COVID-19 and Politics, 35.70% were positive, 32.86% were negative, and 31.44% were negative. Third, topic-specific language analysis was performed to detect the various languages in which the video descriptions per topic were published on YouTube. This analysis revealed multiple novel insights. For instance, for all the themes, English and Spanish were the most widely used and second-most widely used languages, respectively. Fourth, the patterns of sharing these videos on other social media channels such as Facebook and Twitter were also investigated. The results revealed that videos containing video descriptions in English were shared the highest number of times on Facebook and Twitter. Finally, correlation analysis was performed by taking into account multiple characteristics of these videos. The results revealed that the correlation between the length of the video title and the number of Tweets as well as the correlation between the length of the video title and the number of Facebook posts was statistically significant.

We present a general theory of estimation of analysis error covariances based on cross-validation as well as a geometric interpretation of the method. In particular we use the variance of passive observation–minus-analysis residuals and show that the true analysis error variance can be estimated, without relying on the optimality assumption. This approach is used to obtain near optimal analyses that are then used to evaluate the air quality analysis error using several different methods at active and passive observation sites. We compare the estimates according to the method of Hollingsworth-Lönnberg, Desroziers et al., a new diagnostic we developed, and the perceived analysis error computed from the analysis scheme, to conclude that, as long as the analysis is near optimal, all estimates agree within a certain error margin.

State Forest Management Organizations (SFMOs) play a crucial role in the European forest sector, managing almost half the forests in the region. SFMOs are often managed for timber production only whereas, being publicly owned, they should play an important role in providing a vast range of public goods (e.g. soil protection, biodiversity conservation). Their management goals depend on the history and current conditions of the forest sector at a national level, as well as different challenges and the potential for development. Although there is a lack of knowledge about the current performance of SFMOs, there have been recent changes to their management goals and practices in response to the new demands expressed by society (e.g. transparency, social inclusion). The main purpose of this study is to analyse the current situation of SFMOs by clustering them according to indicators that reflect three pillars of the common understanding of sustainable forest management (SFM) concept. With the help of Principal Component Analysis (PCA), we grouped countries according to common characteristics of the forest sector at the national level. Results show three main clusters of SFMOs in Europe. The first cluster has rather small but commercially-oriented forestry unit together with other business activities and a strong focus on public services. The second sees itself as the protector of public interest, rather than commercially-oriented organisations. The third is mainly profit-seeking. The existence of diverse SFMO clusters shows the possibility of different approaches for SFM with a focus on different goals (e.g. profit gaining, public service delivery).

Accurate forecasting of icing thickness has a great significance for ensuring the security and stability of power grid. In order to improve the forecasting accuracy, this paper proposes an icing forecasting system based on fireworks algorithm and weighted least square support vector machine (W-LSSVM). The method of fireworks algorithm is employed to select the proper input features with the purpose of eliminating the redundant influence. In addition, the aim of W-LSSVM model is to train and test the historical data-set with the selected features. The capability of this proposed icing forecasting model and framework is tested through the simulation experiments using real-world icing data from monitoring center of key laboratory of anti-ice disaster, Hunan, South China. The results show that the proposed W-LSSVM-FA method has a higher prediction accuracy and it may be a promising alternative for icing thickness forecasting.

Characterization of fungal spider pathogens lags far behind their insect counterparts. In addition, little to nothing is known concerning ecological reservoir and/or fungal entomopathogen community surrounding infection sites. Five infected spider cadavers were identified in the neo-tropical climate of north central Florida, US, from three of which viable cultures could be obtained. Multilocus molecular phylogenetic and morphological characteristics identified one isolate as a new species of Gibellula, named, G. floridensis, and the other two as isolates of Parengyodontium album. To examine the insect fungal community sampling of different habitats/trophic levels including soil, leaf litter, leaf, and twig from the surrounding area of the infection sites were collected and analyzed by ITS amplicon sequencing. These data revealed broad but differential distribution of entomopathogenic fungi between habitats and some variation between sites, with members of genera Metarhizium and Metacordyceps from Clavicipitaceae, Purpureocillium and Polycephalomyces from Ophiocordyceps, and Akanthomyces and Simplicillium from Cordycipitaceae, predominating. However, no sequences corresponding to Gibellula or Parengyodontium, even at the genera levels could be detected. Potential explanations for these findings are discussed. These data highlight novel discovery of fungal spider pathogens and open the broader question regarding the environmental distribution and ecological niches of such host specific pathogens.

The refractive index of seawater is one of the essential parameters in ocean observation, so it is necessary to achieve high-precision seawater refractive index measurements. A seawater refractive index measurement system based on position-sensitive detectors is an effective means to achieve high-precision measurement of seawater refractive index. However, in the actual seawater refractive index measurement process, the impact of the measurement error caused by the jitter signal obtained from the measurement on the measurement results cannot be ignored. In this paper, we theoretically analyse the causes of the long jitter signals during seawater refractive index measurement and quantify the influencing factors. Through the analysis, it can be seen that the angle between the two windows in the refractive index measurement area of seawater causes a great error on the measurement results, so the angle between the two windows should be controlled within 2.06° in order to effectively reduce the measurement error. At the same time, the factors affecting the measurement accuracy of the position-sensitive detector are analysed, and the factors leading to the reduction of the measurement accuracy of the position-sensitive detector are mainly the background light, the size of the photosensitive surface, and the change of the temperature of the working environment. For the above factors, we add a narrow-band filter with a bandwidth of 0.9nm in front of the photosensitive surface of the position-sensitive detector during the construction of the measurement system, so as to filter out stray light other than the signal light source. On the premise of ensuring the measuring range of the refractive index of seawater, a position-sensitive detector with a photosensitive surface size of 4 mm×4 mm was selected. In order to reduce the temperature variation of the working environment of the position-sensitive detector, the measurement system was partitioned. In order to validate the testing error range of the optimised test system, standard seawater samples under the same conditions were measured. It can be seen that the jitter signal of the measurement system has been reduced from 0.0022mm before the optimisation to 0.0011mm after the optimisation, and the deviation of the refractive index has been reduced by 1.09×10−8RIU. The experimental results show that the refractive index of seawater has been effectively reduced by adjusting the optical path and the structure of the seawater refractive index measurement system.

Based on the minimum conduction band edge caused by the minimum channel potential resulting from the quasi-3D scaling theory and the 3D density of state (DOS) accompanied by the Fermi-Dirac distribution function on the source and drain sides, a unified semiconductor-device-physics-based ballistic model is developed for the threshold voltage of modern multiple-gate (MG) transistors, including FinFET, W-gate MOSFET, and Nanosheet (NS) MOSFET. It is shown that the thin silicon, thin gate oxide, and high work function will alleviate the ballistic effects and resist the threshold voltage degradation. Besides, as the device dimension is further reduced to give rise to the 2D/1D DOS, the lowest conduction band edge is hence increased to resist the threshold voltage degradation. The nanosheet MOSFET exhibits the largest threshold voltage among the three transistors due to the smallest minimum conduction band edge caused by the quasi-3D minimum channel potential. Compared to P-type MOSFET (P-FET), the N-FET shows more threshold voltage because the electron has a more effective mass than the hole

This work offers a new log generalized odd log-logistic exponential regression model for analyzing weekly dengue fever cases in 2022 with a location-systematic component. To achieve this, a data set of 49 observations of dengue fever cases in the Federal District of Brazil is employed. A review of the mathematical properties of the generalized odd log-logistic exponential distribution is provided, the maximum likelihood method is used to estimate the parameters, and, through Monte Carlo simulations, the accuracy of the estimators is investigated. The model's fit is assessed using global influence metrics and residual analysis. For the time scenario studied, the proposed regression identified factors that have an impact on dengue fever cases, which may contribute to improve disease control. Finally, several interpretations are addressed, and a discussion presents results that aid in better understanding the data set and future research on different data.

Software systems are often maintained by a group of experienced software developers, in order to ensure that faults which may bring the system down are less likely. Large turnover in organizations such as CERN makes it important to think of ways of onboarding newcomers on a technical project rapidly. This paper focuses on optimizing the way that people get up-to-speed on the business logic and technologies used on the project, using a knowledge-imbued large language model that is enhanced using domain-specific knowledge from the group or team’s internal documentation.

As the demand for fossil fuels continues to rise and their availability becomes increasingly limited, it is crucial to explore innovative approaches to optimize fuel combustion in existing systems. Among various engines, diesel engines are heavily reliant on fluid motion within the engine cylinder, which plays a critical role in fuel-air mixing. This abstract focuses on the potential of dynamic mathematical model simulation for multi-compartment rotor compressed combustion engines, aiming to revolutionize power generation by enhancing fuel burning efficiency. By leveraging advanced simulation techniques, this research seeks to unlock new insights into fluid dynamics and optimize fuel-air mixing, leading to more efficient and sustainable energy utilization. Through this exploration, we aim to pave the way for groundbreaking advancements in the field of combustion engines, ultimately contributing to a greener and more sustainable future. In the realm of internal combustion engines, the fluid dynamics within the engine cylinder greatly influence the combustion processes and heat transfer. For compression ignition (C.I) engines, both the bulk gas motion and turbulence characteristics play vital roles in engine performance. This study focuses on enhancing the combustibility of the fuel-air mixture in C.I engines by modifying the engine design to induce turbulence through squish and tumble flows. The modification involves creating multiple compartments on the rotor crown, comprising three small chambers spaced 120º apart. By implementing this design, the aim is to optimize the fuel-air mixing and improve the overall combustion efficiency. Through comprehensive analysis and experimentation, we seek to revolutionize C.I engine technology and pave the way for more efficient and environmentally-friendly power generation. In this study, the performance of a compression ignition (C.I) engine with a multiple compartment rotor has been analyzed under motoring conditions using computational fluid dynamics (CFD) simulations with FLUENT software. The obtained results have been compared with those of a base C.I engine. The analysis focused on the effects of the modified engine design on the tumble ratio and squish velocity, which are important parameters for fuel-air mixing and combustion efficiency. The results indicated a significant improvement with the modified engine, with a 35% increase in tumble ratio and a 31% increase in squish velocity compared to the base engine. These findings suggest that the modified engine design has the potential to enhance fuel-air mixing and combustion performance, leading to improved overall engine efficiency. This research presents promising insights into the optimization of C.I engine design and contributes to the development of more efficient and environmentally-friendly power generation technologies..

In cold-climate regions, road salt is used as a de-icer for winter road maintenance. The applied road salt melts ice and snow on roads, being washed off through storm sewer systems into nearby urban streams, harming the freshwater ecosystem. Addressing the gap in the knowledge regarding the use of deep learning approaches for urban stream water quality forecasting, the present work discusses our implementation of a “Graph Neural Network” - “Sample and Aggregate” (GNN-SAGE) model for forecasting chloride concentrations in the Credit River in Ontario, Canada. The proposed GNN-SAGE is compared to other models, including a Deep Neural Network based transformer (DNN-Transformer) and a benchmarking persistence model for 6 hours forecasting horizon. Ac-cording to the results, the GNN-SAGE model surpasses other models in providing accurate predic-tions of chloride concentrations within the assessed prediction window. Also, a SHAP analysis provides insight into the variables that influence the model’s forecasting, showing the impact of the spatiotemporal neighbouring data from the network and the seasonality variables on the model’s result. The GNN-SAGE model shows potential for use in real-time forecasting of water quality in urban streams, aiding in the development of regulatory policies to protect the vulnerable freshwater ecosystems in urban areas.

Abstract: The surge of diabetes poses a significant global health challenge, particularly in Oman and the Middle East. Early detection of diabetes is crucial for proactive intervention and improved patient outcomes. This research leverages the power of machine learning, specifically, Convolutional Neural Networks (CNNs), to develop an innovative 4D CNN model dedicated to early diabetes prediction. A region-specific dataset from Oman is utilized to enhance health outcomes for individuals at risk of developing diabetes. The proposed model showcases remarkable accuracy, achieving an average accuracy of 98.49% to 99.17% across various epochs. Additionally, it demonstrates excellent F1 score, recall, and sensitivity, highlighting its ability to identify true positive cases. The findings contribute to the ongoing effort to combat diabetes and pave the way for future research in using deep learning for early disease detection and proactive healthcare.

In this study, we propose a radiomics-clinical probability weighted model for the prediction of prognosis for NSCLC. The model combines radiomics features extracted from RT planning images with clinical factors such as age, gender, histology, and tumor stage. CT images with radiotherapy structures of 422 NSCLC patients were retrieved from The Cancer Imaging Archive (TCIA). Radiomic features were extracted from gross tumor volume (GTV). Five machine learning algorithms, namely decision trees (DT), random forests (RF), extreme boost (EB), support vector machine (SVM) and generalized linear model (GLM), were optimized by a voted ensemble machine learning (VEML) model. A probabilistic weighted approach is used to incorporate the uncertainty associated with both radiomic and clinical features and to generate a probabilistic risk score for each patient. The performance of the model is evaluated using a receiver operating characteristic (ROC). Radiomic model, clinical factors model and combined radiomic-clinical probability weighted model demonstrated good performance in predicting NSCLC survival with AUC of 0.941, 0.856 and 0.949 respectively. The combined radiomics-clinical probability weighted enhanced model achieved significantly better performance than radiomic model in 1-year survival prediction (chi-square test, p<0.05). The proposed model has the potential to improve NSCLC prognosis and facilitate personalized treatment decisions.

This research experiments with a sustainability assessment based on the Sustainable Development Goals (SDGs) of Agenda 2030 through a process of their territorialisation and implementation. This process enables the development of a Spatial Decision Support System (SDSS) that can be integrated with strategic environmental assessments in urban planning. The assessment takes place on the transversality of the sustainability concept by trying to consider together the three dimensions (environmental, social and economic) into a single assessment through the Spatial Sustainability Assessment Model (SSAM) by integrating Geographic Information Systems (GIS) and multi-criteria analyses. Economic development, social equity, and ecological integrity represent three common visions for rethinking peri-urban edges.

Auto-labeling is one of the main challenges in 3D vehicle detection. Auto-labeled datasets can be used to identify objects in LiDAR data, which is a challenging task due to the large size of the dataset. In this work, we propose a novel methodology to generate new 3D based auto-labeling datasets with a different point of view setup than the one used in the most recognized datasets (KITTI, WAYMO, etc.). The performance of the methodology has been further demonstrated with the development of our own dataset with the auto-generated labels and tested under boundary conditions on a bridge in a fixed position. The proposed methodology is based on the YOLO model trained with the KITTI dataset. From a camera-LiDAR sensory fusion, it is intended to auto-label new datasets while maintaining the consistency of the Ground Truth. The main contribution of this work is a novel methodology to auto-label autonomous driving datasets using YOLO as the main labelling system. The performance of this approach is measured retraining the contrast models of the KITTI benchmark.

Shales are well known for their strong anisotrophic properties. The classical Athy’s model on the exponential porosity reduction with the depth commonly uses based on localities only. Shale compaction curve affects the results of the basin modeling as it is important input data, thus the standard compaction curve of shales needs to be established. This study provided a new data and complies available data of Thailand shales to propose the new empirical relationship among porosity, burial depth, and geological age. The numerical data of the geological time were estimated by the application from the relationship of velocity and depth in each geological ages. The variation of the Thailand shale data due to the different geological ages was found in this study. Finally, the standard curve of shale compaction proposed by Puttiwongrak et al. [9] was examined and confirmed by this research findings.

Convective rainfall can cause dangerous flash floods within less than six hours. Thus, simple approaches are required for issuing quick warnings. The Flash Flood Guidance (FFG) approach pre-calculates rainfall levels (thresholds) potentially causing critical water levels for a specific catchment. Afterwards, only rainfall and soil moisture information is required to issue warn-ings. This study applied the principle of FFG to the Wernersbach Catchment (Germany) with excellent data coverage using the BROOK90 water budget model. The rainfall thresholds were determined for durations of 1 to 24 hours, by running BROOK90 in “inverse” mode, identifying rainfall values for each duration that led to exceedance of critical discharge (fixed value). After calibrating the model based on its runoff, we ran it in hourly mode with four precipitation types and various levels of initial soil moisture for the period 1996 – 2010. The rainfall threshold curves showed a very high probability of detection (POD) of 91% for the 40 extracted flash flood events in the study period, however, the false alarm rate (FAR) of 56% and the critical success index (CSI) of 42% should be improved in further studies. The approach proved potential as an early flood indicator for head-catchments with limited available information.

Aim. The purpose of the work was the development of a machine learning model for diagnosing the stage of liver fibrosis in patients with chronic viral hepatitis C according to the data of routine clinical examination. Materials and methods. A total of 1240 patients with chronic viral hepatitis C was examined. A set of data obtained from 689 patients balancing by the stage of liver fibrosis was used for developing and testing machine learning models. 9 routine clinical parameters were selected as the most important predictors for determining the likelihood of liver fibrosis the 3–4 stages presence: age, height, weight and body mass index of the patient, the number of platelets in the clinical blood test, levels of alanine transaminase, aspartate transaminase, gamma-glutamyltransferase, and total bilirubin in a biochemical blood test. Results. The accuracy of the developed method for determining the 3–4 stages of liver fibrosis in patients with chronic viral hepatitis C in comparison with the «gold standard» of diagnosis (liver biopsy) was 80.56% (95% CI: 69.53–88.94%), sensitivity — 66.67%, specificity — 94.44%. Conclusion. The developed method is an alternative to more expensive and geographically inaccessible studies. The method does not require the purchase of additional equipment or software, as well as additional laboratory tests, when used in real clinical practice. The introduction of the method into clinical practice can help to solve the problem of low material and territorial availability of diagnostic tests and allow determining the stage of liver fibrosis in patients with chronic viral hepatitis C.

Ebola virus (EBOV) is a negative-sense RNA virus that can infect humans and nonhuman primates with severe health consequences. Development of countermeasures requires a thorough understanding of the interaction between host and pathogen, and the course of disease. The goal of this study was to further characterize EBOV disease in a uniformly lethal rhesus macaque model, in order to support development of a well-characterized model following rigorous quality standards. Rhesus macaques were intramuscularly exposed to EBOV and one group was euthanized at predetermined time points to characterize progression of disease. A second group was not scheduled for euthanasia in order to analyze survival, changes in physiology, clinical pathology, terminal pathology, and telemetry kinetics. On day 3, sporadic viremia was observed and pathological evidence was noted in lymph nodes. By day 5, viremia was detected in all EBOV exposed animals and pathological evidence was noted in the liver, spleen, and gastrointestinal tissues. These data support the notion that EBOV infection in rhesus macaques is a rapid systemic disease similar to infection in humans, under a compressed time scale. Biomarkers that correlated with disease progression at the earliest stages of infection were observed thereby identifying potential “trigger--to-treat” for use in therapeutic studies.

The earlier analytical analysis (part A) of the Susceptible-Infectious-Recovered (SIR) epidemics model for a constant ratio k of infection to recovery rates is extended here to the semi-time case which is particularly appropriate for modeling the temporal evolution of later (than the first) pandemic waves when a greater population fraction from the first wave has been infected. In the semi-time case the SIR model does not describe the quantities in the past; instead they only hold for times later than the initial time t=0 of the newly occurring wave. Simple exact and approximative expressions are derived for the final and maximum values of the infected, susceptible and revovered/removed population fractions as well the daily rate and cumulative number of new infections. It is demonstrated that two types of temporal evolution of the daily rate of new infections j(tau) occur depending on the values of k and the initial value of the infected fraction I(0)=eta: in the decay case for k > 1-2 eta the daily rate monotonically decreases at all positive times from its initial maximum value j(0)=eta (1-eta). Alternatively, in the peak case for k<1-2 eta the daily rate attains a maximum at a finite positive time. By comparing the approximated analytical solutions for j(tau) and J(tau) with the exact ones obtained by numerical integration, it is shown that the analytical approximations are accurate within at most only 2.5 percent. It is found that the initial fraction of infected persons sensitively influences the late time dependence of the epidemics, the maximum daily rate and its peak time. Such dependencies do not exist in the earlier investigated all-time case.

Capturing complexity is both a conceptual and a practical challenge in palliative care. The HexCom model has proved to be an instrument with strong reliability and valid for describing the needs and strengths of patients in home care. In order to explore whether it is also perceived to be helpful in enhancing coordinated and patient-centered care at a practical level, a methodological study was carried out to assess the face validity of the model. Particularly, a Delphi method involving a group of 15 experts representing the full spectrum of healthcare professionals involved in palliative care was carried out. The results show that there is a high level of agreement, with a Content Validity Index-Item greater than 0.92 both with regard to the complexity model and the HexCom-Red, HexCom-Basic and HexCom-Clin instruments, and higher than 0.85 regarding the HexCom-Figure and the HexCom-Patient instruments. This consensus confirms that the HexCom model and the different instruments that are derived from it are valued as useful tools for a broad range of healthcare professional in coordinately capturing of complexity in healthcare practice.

This work investigates the utility of the National Oceanic and Atmospheric Administration’s National Water Model (NWM) for water management operations by assessing the total inflow into a select number of reservoirs across the Central and Western U.S. Total inflow is generally an unmeasured quantity, though critically important for anticipating both floods and shortages in supply over a short-term (hourly) to sub-seasonal (monthly) time horizon. The NWM offers such information at over 5,000 reservoirs across the U.S., however, its skill at representing inflow processes is largely unknown. The goal of this work is to understand the drivers for both well performing and poor performing NWM inflows such that managers can get a sense of the capability of NWM to capture natural hydrologic processes and in some cases, the effects of upstream management. We analyzed the inflows for a subset of Bureau of Reclamation (BoR) reservoirs within the NWM over the long-term simulations (retrospectively, seven years) and for short, medium and long-range operational forecast cycles over a one-year period. We utilize ancillary reservoir characteristics (e.g. physical and operational) to explain variation in inflow performance across the selected reservoirs. In general, we find that NWM inflows in snow-driven basins outperform those in rain-driven, and that assimilated basin area, upstream management, and calibrated basin area all influence the NWM’s ability to reproduce daily reservoir inflows. The final outcome of this work proposes a framework for how the NWM reservoir inflows can be useful for reservoir management, linking reservoir purposes with the forecast cycles and retrospective simulations.

Bayesian model calibration techniques are commonly employed in the characterization of nonlinear dynamic systems, as they provide a conceptual and effective framework to deal with model uncertainties, experimental errors and procedure assumptions. This understanding has resulted in the need to introduce a model discrepancy term to account for the differences between model-based predictions and real observations. Indeed, the goal of this work is to enhance model-driven Structural Health Monitoring procedures by incorporating the posterior uncertainty linked to updated model discrepancy, and thus make relevant considerations for its use in the Structural Health Monitoring. Specifically, the Bayesian inference has been applied to the calibration of nonlinear hysteretic systems to both provide: (i) most probable values (MPV) of the parameters following the calibration, and; (ii) estimates of the model discrepancy posterior distribution. The effect of the model discrepancy in the calibration is first illustrated recurring to a single degree of freedom Bouc-Wen type oscillator, and then applied for calibrating a reference nonlinear Bouc-Wen model, deriving from real data acquired on a monitored masonry building.

Modern gas turbines firing temperatures (1500-2000K) are well beyond the maximum allowable blade material temperatures. Continuous safe operation is made possible by cooling the HP turbine first stages -nozzle vanes and rotor blades- with a portion of the compressor discharge air, a practice that induces a penalty on the cycle thermal efficiency. Therefore, a current issue is to investigate the real advantage, technical and economical, of raising maximum temperatures much further beyond current values. In this paper, process simulations of a gas turbine are performed to assess HP turbine first-stage cooling effects on cycle performance. A new simplified and properly streamlined model is proposed for the non-adiabatic expansion of the hot gas mixed with the cooling air within the blade passage, which allows for a comparison of several cycle configurations at different TIT (turbine inlet temperature) and max (total turbine expansion ratio) with a realistically acceptable degree of approximation.. The calculations suggest that, at a given max, the TIT can be increased in order to reach higher cycle efficiency up to a limit imposed by the required amount and temperature of the cooling air. Beyond this limit, no significant gains in thermal efficiency are obtained by adopting higher max and/or increasing the TIT, so that it is convenient in terms of cycle performance to design at lower rather than higher max. The small penalty on cycle efficiency is compensated by lower plant cost. The results of our model agree with those of some previous much more complex and computationally expensive studies, so that the novelty of this paper lies in the original method adopted on which the proposed model is based, and in the fast, accurate and low resource intensity of the corresponding numerical procedure: all advantages that can be crucial for industry needs. The presented analysis is purely thermodynamic, with no investigation on the effects of the different configurations on plant costs, so that future work addressing a thermo-economic analysis of the air-cooled gas turbine power plant is the next logical step.

This paper studies an effective finite difference scheme for solving two-dimensional Heston stochastic volatility option pricing model problems. A dynamically balanced up-downwind strategy for approximating the cross-derivative is implemented and analyzed. Semi-discretized and spatially nonuniform platforms are utilized. The numerical method comprised is simple, straightforward with reliable first order overall approximations. The spectral norm is used throughout the investigation and numerical stability is proven. Simulation experiments are given to illustrate our results.

The hydrodynamic results obtained from the permeability of porous materials not only affect the assessment of the stream of the gas flow through those materials but they also refer to the loss of pressure energy in that flow. The direct measure of that loss is flow resistances.The results of experimental research upon the assessment of the flow resistances of porous materials with respect to gas flow. The research conducted applied to natural materials with an anisotropic gap-porous structure. The tests were carried out on a gas permeability measuring system, adapted to different shapes of porous material samples. The process issue of the total pressure drop on a porous deposit was considered in the Reynolds number category. The coefficient of flow resistance for anisotropic materials was defined and the value of this coefficient was compared to the gas stream and the total pressure drop on the porous bed was experimentally evaluated.

We have recently solved the tumbling-snake model for concentrated polymer solutions and entangled melts in the presence of both steady-state and transient shear and uniaxial elongational flows, supplemented by a variable link tension coefficient. Here, we provide the transient and stationary solutions of the tumbling-snake model under biaxial elongation both analytically, for small and large elongation rates, and via Brownian dynamics simulations, for the case of planar elongational flow over a wide range of rates, times, and the model parameters. We show that both the steady-state and transient first planar viscosity predictions are similar to their uniaxial counterparts, in accord with recent experimental data. The second planar viscosity seems to behave in all aspects similarly to the shear viscosity, if shear rate is replaced by elongation rate.

To estimate the recreational value provided by the Foy’s Lake annually using the most applicable model for on-site data is the main objective of this study. Adhere to the objective of this study; Individual Travel Cost Method (ITCM) has been applied and Zero Truncated Poisson Regression Model has been found plausible among other models to estimate consumer surplus. Based on the findings of the study, an estimate of the consumer surplus or recreational benefits per trip per visitor can be recommended as BDT 5,875 or US $ 73.44 and counting the consumer surplus per trip per visitor, the annual recreational value (total consumer surplus) provided by the lake is found to be BDT 321 million or US $ 40.2 million.

Responsible, efficient, and environmentally conscious energy consumption practices are increasingly essential for ensuring the reliability of the modern electricity grid. This study focuses on leveraging time series analysis to improve forecasting accuracy, crucial for various application domains where real-world time series data often exhibit complex, non-linear patterns. Our approach advocates for utilizing Long Short Term Memory (LSTM) and Bidirectional LSTM (BiLSTM) models for precise time series forecasting. To ensure a fair evaluation, we compare the performance of our proposed approach with traditional neural networks, time-series forecasting methods, and conventional decline curves. Additionally, individual models based on LSTM, Bi-LSTM, and other machine learning methods are implemented for a comprehensive assessment. Experimental results consistently demonstrate that our proposed model outperforms all benchmarking methods in terms of mean absolute error (MAE) across most datasets. Addressing the imbalance between activations by consumer and prosumer groups, our predictions show superior performance compared to several traditional forecasting methods, such as the Autoregressive Integrated Moving Average model (ARIMA) and Seasonal Autoregressive Integrated Moving Average model (SARIMA). Specifically, the root mean square error (RMSE) of Bi-LSTM is 5.35%, 46.08%, and 50.6% lower than LSTM, ARIMA, and SARIMA, respectively, on the May test data.

Wheat straw (WS) is a promising substrate for biogas production by anaerobic digestion (AD) due to its high carbohydrate content. An estimated 0.603 million t yr-1 of WS are generated from wheat production systems in South Africa. This is equivalent to an energy potential of 11 PJ. Despite, WS is still undervalued as a bioenergy resource in South Africa due to its structural complexity and low nitrogen content. WS disposal methods, such as use in livestock bedding, burning and burying into the soil, inter alia, are not sustainable and may contribute to global warming and climate change. Commercialization of the AD of WS needs to be further developed and promoted. Pre-treatment (i.e. physical, chemical, biological and hybrid methods) and anaerobic co-digestion (AcoD) are novel strategies that can support the conversion of WS into biogas and other value-added products. Current and future research should focus on optimizing pre-treatment and AcoD conditions towards industrialization of WS into valuable products. This paper focuses on the potential use of WS for biogas production by AD in South Africa. The aim is to create information that will promote research and development, and encourage policy makers and stakeholder participation and investment in WS biogas technology.