The negative binomial regression model (NBRM) is a generalized linear model which relaxes the restrictive assumption by the Poisson regression model when the variance is equal to the mean. The estimation of the parameters of the NBRM is obtained using the maximum likelihood (ML) method. Maximum likelihood estimator becomes unstable when the explanatory variables are linearly dependent, a situation known as multicollinearity. Based on this, we developed a new estimator called modified jackknifed Negative Binomial Kibria-Lukman (MJNBKL) estimator for the radiation of multicollinearity in NBRM using four different biasing (shrinkage) parameters. We establish superiority condition for MJNBKL estimator over the ones. The performance MJNBKL estimator was ascertained by comparing it with the existing ones through a Monte Carlo simulation study and two real life application datasets. The results of the simulation and real life application show that MJNBKL estimator outperformed the other estimators compared with by having the smallest MSE across all sample sizes and for different levels of correlation for the four biasing parameters used and the third biasing parameter is the optimal shrinkage parameter with the lowest MSE.

Tropical regions face unique challenges in building sustainability due to high temperatures, humidity, and heavy rainfall. While building energy regulations are essential for promoting energy efficiency, their effectiveness in addressing tropical climate conditions needs to be studied more. This research aims to systematically investigate tropical building sustainability issues and evaluate the impacts of building energy regulations on these challenges. The study will identify gaps in current regulations by analyzing existing research and recommend strategies for developing more comprehensive frameworks that promote sustainable building practices in tropical regions. This research contributes to developing effective policies and strategies for achieving sustainable and energy-efficient built environments in tropical climates.

This study examined the relationship between financial sector liberalization and agricultural sector output in Nigeria using annual data spanning the period 1986-2020. Specifically, the objectives of the study are to examine the relationship between lending rate, exchange rate, commercial bank credit to agriculture, inflation rate and agricultural sector output in Nigeria. Ex-post facto research design was employed and the annual time series data were collated from Central Bank of Nigeria (CBN) Statistical Bulletin. The econometrics methods of unit root, co-integration and error correction mechanism were used for the analyses. The outcome of the ADF unit root test show that the variables were stationary. Also the co-integration result showed that there exist co-integration amongst the variables in the model. The results from Error Correction Model indicates that lending rate and inflation rate have a negative relationship on agricultural sector output while exchange rate and commercial bank credit to agriculture have positive relationship on agricultural sector output. Based on these results, this study recommends that government and policy makers in Nigerian should initial policies that will boost investments in the agricultural sector through direct provision of credits to agriculturist and banks should also lend at a very low and subsidized interest rate to enable farmers’ access agricultural loans that will boost agricultural productivity in the economy.

Tropical regions face significant energy challenges due to climatic conditions. This study investigates the interplay between sustainable architecture and building energy regulations in mitigating these challenges. The study aims to assess the effectiveness of existing building energy regulations in promoting sustainable architecture in tropical climates and identify key architectural strategies and regulatory frameworks for optimizing energy efficiency in tropical buildings. A comparative analysis of building regulations and case studies of sustainable buildings in selected tropical regions is conducted. The findings reveal that current regulations often must be revised to address tropical climates' unique energy demands. Incorporating passive design principles, renewable energy systems, and material selection is crucial for energy efficiency. It is recommended that building energy regulations be strengthened to mandate sustainable design strategies and provide incentives to promote the adoption of energy-efficient technologies.

This research delves into the evolution of architectural styles throughout the 20th century, examining the transition from traditional to modern architecture. The study aims to identify the key factors influencing this transformation and analyze the impact of modernist principles on architectural design and practice. Employing a historical and analytical methodology, the research investigates the works of influential architects and the role of technological advancements. Key findings reveal that a confluence of cultural, technological, and socioeconomic forces drove the shift towards modernism, which focused on functionality, form, and innovation. The research concludes that the modernist movement fundamentally reshaped the built environment, leaving a lasting legacy on contemporary architectural discourse. It is recommended that future studies explore the long-term implications of modernism on urban planning and sustainability, as well as the potential for a synthesis between traditional and contemporary architectural approaches.

The construction industry is a cornerstone of Nigeria's economic growth, yet it faces significant hurdles, particularly from governmental constraints. This research aims to (1) identify the primary governmental constraints impacting the Nigerian construction sector and (2) evaluate the effectiveness of existing government interventions in addressing these challenges. Employing a comprehensive literature review, this study analyzes regulatory frameworks, bureaucratic processes, corruption, political instability, and infrastructure deficiencies. It also examines the consequences of these constraints on project costs, timelines, and quality. Key findings reveal that bureaucratic red tape and corruption are the most pervasive constraints, significantly hindering project execution. Consistent government policies and adequate infrastructure also contribute to project delays and cost escalation. To enhance the construction sector's performance, it is imperative to (1) streamline bureaucratic procedures and strengthen anti-corruption measures and (2) develop and implement consistent, long-term sector-specific policies. By addressing these recommendations, the government can create a more favorable environment for construction businesses, stimulate investment, and accelerate Nigeria's overall development.

The impact of legume production on smallholder farmers' socio-economic welfare in Ma-lawi is a crucial question, given the country's aspirations for rural development and eco-nomic growth. This study investigates the effect of legume production on household wel-fare, using two waves of nationally representative data from the Integrated Household Survey and integrating geospatial techniques. A random effects model was employed to estimate the determinants of legume adoption, and the impact of legume cultivation on household welfare was assessed using income and asset holding as indicators. The results show that legume adoption significantly increases household income per capita and household asset holding by 71%. Disaggregated results reveal that adoption benefits all households, but particularly those with larger landholdings. The study concludes that accelerating legume adoption is a promising strategy for rural development in Malawi, aligning with the country's goals of achieving inclusive wealth and self-reliance in the coming decades.

The design of school environments plays a pivotal role in promoting student wellness, mindfulness, and socio-emotional learning (SEL). This article explores the integration of Environment Behaviour Studies (EBS) concepts into school design to enhance students' overall well-being and academic success. It highlights the importance of indoor environmental quality, ergonomic and flexible learning spaces, and biophilic design in fostering a healthy and engaging learning atmosphere. Additionally, the article delves into the creation of mindfulness spaces, sensory-friendly environments, and the use of colour and aesthetics to support emotional regulation and mental health. By examining case studies of successful implementations, the article underscores best practices for designing schools that promote positive social interactions, ensure safety, and reflect community values. Ultimately, this comprehensive approach to school design aims to nurture holistic development, support socio-emotional learning, and prepare students for lifelong success.

To date, several independent methods and algorithms exist exploiting constraint-based stoichiometric models to find metabolic engineering strategies that optimize microbial production performance. Optimization procedures based on metaheuristics facilitate a straightforward adaption and expansion of engineering objectives as well as fitness functions, while being particularly suited for solving problems of high complexity. With the increasing interest in multi-scale models and a need for solving advanced engineering problems, we strive to advance genetic algorithms, which stand out due to their intuitive optimization principles and proven usefulness in this field of research. A drawback of genetic algorithms is that premature convergence to sub-optimal solutions easily occurs if the optimization parameters are not adapted to the specific problem. Here, we conducted comprehensive parameter sensitivity analyses to study their impact on finding optimal strain designs. We further demonstrate the capability of genetic algorithms to simultaneously handle (i) multiple, non-linear engineering objectives, (ii) the identification of gene target-sets according to logical gene-protein-reaction associations, (iii) minimization of the number of network perturbations, and (iv) the insertion of non-native reactions, while employing genome-scale metabolic models. This framework adds a level of sophistication in terms of strain design robustness, which is exemplarily tested on succinate overproduction in Escherichia coli.

SARS-CoV-2 infection can lead to life-threatening clinical manifestations. Patients with cardiovascular disease (CVD) are at higher risk for severe courses of COVID-19. However, strategies to predict the course of SARS-CoV-2 infection in CVD patients at the time of hospital admission are still missing. Here, we investigated whether this prediction is achievable by prospectively analysing the blood immunophenotype of 94 participants, including 20 uninfected and 37 acutely SARS-CoV-2-infected CVD patients and 37 healthy donors, using a 36-colour spectral flow cytometry panel. Unsupervised data analysis revealed little differences between healthy donors and CVD patients, whereas the distribution of the cell populations changed dramatically in SARS-CoV-2-infected CVD patients. The latter had more mature NK cells, activated monocyte subsets, central memory CD4+ T cells, and plasmablasts but fewer dendritic cells, CD16+ monocytes, innate lymphoid cells, and CD8+ T cell subsets. Moreover, we identified an immune signature characterised by mucosal-associated invariant T (MAIT) cells, intermediate effector CD8+ T cells, and natural killer T (NKT) cells that is predictive for CVD patients with a severe course of COVID-19. Thus, intensified immunophenotype analyses can help identify patients at risk of severe COVID-19 at hospital admission, improving clinical outcomes through specific treatment.

The role played by non extensive thermodynamics in physical systems has been under intense debate for the last decades. With many applications in several areas, the Tsallis statistics has been discussed in details in many works and triggered an interesting discussion on the most deep meaning of entropy and its role in complex systems. Some possible mechanisms that could give rise to non extensive statistics have been formulated along the last several years, in particular a fractal structure in thermodynamics functions was recently proposed as a possible origin for non extensive statistics in physical systems. In the present work we investigate the properties of such fractal thermodynamical system and propose a diagrammatic method for calculations of relevant quantities related to such system. It is shown that a system with the fractal structure described here presents temperature fluctuation following an Euler Gamma Function, in accordance with previous works that evidenced the connections between those fluctuations and Tsallis statistics. Finally, the fractal scale invariance is discussed in terms of the Callan-Symanzik Equation.

In fisheries monitoring, catch is assumed to be a product of fishing intensity, catchability, and availability, where availability is defined as the number or biomass of fish present and catchability refers to the relationship between catch rate and the true population. Ecological monitoring programs use catch per unit of effort (CPUE) to standardize catch and monitor changes in fish populations; however, CPUE is proportional to the portion of the population that is vulnerable to the type of gear that is used in sampling, which is not necessarily the entire population. Programs often deal with this problem by assuming that catchability is constant, but if catchability is not constant, it is not possible to separate the effects of catchability and population size using monitoring data alone. This study uses individual-based simulation to separate the effects of changing environmental conditions on catchability and availability in environmental monitoring data. The simulation combines a module for sampling conditions with a module for individual fish behavior to estimate the proportion of available fish that would escape from the sample. The method is applied to the case study of the well-monitored fish species Delta Smelt (Hypomesus transpacificus) in the San Francisco Estuary, where it has been hypothesized that changing water clarity may affect catchability for long-term monitoring studies. Results of this study indicate that given constraints on Delta Smelt swimming ability, it is unlikely that the apparent declines in Delta Smelt abundance are due to an effect of changing water clarity on catchability.

Purpose: The purpose of this study is to further explore how e-loyalty and E-marketing influences E-trust and satisfy the demand by offering fresh perspectives based on research as well as emphasis on the factors influencing the E-trust such as culture as a mediator. This study not only contributed theoretically but also presented practical implementations. Design/methodology/approach: Online survey was used to obtain data by focusing the Hospitality sector (Hotel Industry) and verifying the conceptual framework. Data was collected in multiple time lags. Findings: Findings showed that the E-trust influenced by E-loyalty and E-Marketing. E-trust comes from the previous experiences, e-loyalty and e-marketing. Further, some trends such as culture influenced the e-trust. Research limitation/implications: The present study is quite suitable for those Researchers interested in learning more about the effects of E-loyalty and E-marketing on user E-trust and how to mitigate cultural influences can benefit from the current study. This research also has implications for those who wish to improve market allure and survival in digital world. This study focused on the hospitality sector (Hotel Industry) in China; however, the sector and geography could be altered to suit the needs of the study's participants. Practical implications: The present study delivers the practical guidelines which are quiet suitable for understanding the formation of E-loyalty, E-marketing, and E-trust through which specific E-marketing strategy can be designed to deal with the consumer’s E-loyalty and their expectations as per their Cultural perspective. At some particular regions/countries, cultural trends are more important than practical market. This research study practically showed that how culture changed the consumer set of mind. Originality/value: The relationship between E-loyalty, E-marketing, E-trust, specifically with the cultural influence in digital market has been the subject of few research.

With the burgeoning growth of online retail, the issue of counterfeit products has become a significant threat to both consumer trust and brand integrity, posing challenges to sustainable market practices. Online retail platforms are promoted to redesign their channel structures and enhance brand traceability to tackle counterfeits using blockchain technology. To investigate the interactions between blockchain technology and the channel structures of online retail platforms, we design a game theory model incorporating a manufacturer with(out) blockchain participation selling products via an online retail platform that operates an agency channel and/or a reselling channel. We show that the critical trade-off of blockchain participation comprises the brand assurance effect of the blockchain, the channel competition intensification effect, and the blockchain adoption cost. The platform is capable of strategically designing the channel structure to encourage (while discouraging) blockchain participation by the manufacturer. Our analysis highlights the complementarity between blockchain participation and the channel structure. Furthermore, the effect of the consumer’s belief in the reselling channel, the commission fee in the agency channel, and the substitutability between channels are investigated in depth. The research provides valuable insights for online retail platforms and policymakers seeking to foster a sustainable and trustworthy e-commerce ecosystem.

Coincident changes in abundance and behavior pose a challenge for interpreting abundance data from monitoring programs. In the San Francisco Estuary, long-term monitoring documented the declines of many species including the anadromous Longfin Smelt (Spirinchus thaleichthys). We identified seasonal patterns in reginal presence of Longfin Smelt through its life cycle using monitoring data and generalized additive modelling. We then investigated the year-to-year variability in the seasonal patterns of presence using functional data analysis (FDA). FDA separated the variability due to population size from variability due to differences in timing of presence. We found that Longfin Smelt have consistent seasonal distribution patterns and that two trawl types were needed to accurately describe those patterns. After accounting for variability due to year-class strength, shifts in the timing of presence were evident in three regions. The most variable period for the upstream regions Suisun Bay and West Delta was for age-0 fish in summer and for the downstream region Central Bay was for age-0 fish in late fall. This manifested as a delay in the typical fall re-occupation of upstream regions that comprise the study area for another monitoring study (Fall Midwater Trawl). Thus, a portion of the recent reductions in Fall Midwater Trawl abundance of Longfin Smelt resulted from changes in behavior rather than a decline in abundance. The presence of multiple monitoring surveys allowed analysis of distribution from one data set to aid interpretation of patterns in abundance from another monitoring survey. This study highlights how identifying portions of the life cycle with the most and least variability in distribution can help inform the types of management strategies that will be most effective. It also illustrates an analytical method that can be used to address the problem of confounded effects of abundance and behavior on patterns in monitoring data.

The expansion of renewable energies is progressing strongly. The influence on the power supply networks by the volatility of the infeed must be met with new concepts. In this paper we investigate the possibilities of integrating microgrids as a cooperating unit in the power supply network to support further expansion of RES power plants. In this paper a differentiation of microgrids from similar network structures is established, a classification of proposed groups is made. Then, after the description of simulation of components in a microgrid, with practical advice, an example model is shown, which aids the dimensioning of the components within a microgrid to achieve a specified goal.

Electronic waste generation has been following a continuously rising trend. With electronics containing a myriad of materials some of which are hazardous, toxic, extremely rare or precious combined with more stringent legislative laws which encourage the reuse and optimised recycling of the materials included in e-waste, the need for a holistic approach is inevitable. Such an approach should not only identify the materials found in the various types of e-waste and their respective quantities but also needs to highlight the possible handling techniques and their respective impacts and associated hazards whether to the environment or human health. Performing such a task manually would be exasperating and costly while requiring extensive resources which might not be met with a justifiable economic gain; thus, the use of the advancement in computational sustainability to draw a complete picture and aid in an informed decision-making process is crucial. The e-waste ontology developed in this paper is one way of addressing the problem since it covers the treatment domain, the hazard and the materials contained within the different types of e-waste. The ontology developed can be used directly from the protégé software or by embedding it into a developed Decision Support System.

MnSi has played a major role since the late 1970s in developing the theory of helical magnets in non-centro symmetric materials showing Dzyaloshinsky-Moriya interaction (DMI). With a long helimagnetic pitch of 175 \AA~as compared to the lattice d-spacing of 4.55\AA, it was ideal for performing neutron studies especially as large single crystals could be grown. In these studies under the application of a field of 180 mT perpendicular to Q, a so-called A-phase in the B-T phase diagram was found and interpreted as a rotation of the alignment of the magnetic helix away from the pinning axis. After the surprising discovery of the skyrmion lattice in the A-phase in 2009 much interest arose as it could be shown that the magnetic skyrmion lattice is topologically protected. Due to the rigidity of the skyrmionic lattice it is only loosely bound to the crystal lattice and therefore only relatively small current densities can already induce a motion of this lattice. Another very interesting aspect are the excitations in the spin system of MnSi. As the helimagnetic state is characterized by a long pitch of about 175 \AA, the associated characteristic excitations form a band structure due to Umklapp scattering and can only be observed at very small q with energies below 1 meV. We have investigated the the magnons in MnSi in the whole (B,T)-phase diagram starting in the single-k helimagnetic state by applying a small magnetic field B = 100 mT. This way, the complexity of the magnon spectrum is significantly reduced allowing a detailed comparison of the data with theory resulting in a full theoretical understanding of the spin system of MnSi in all its different magnetic phases.

On using a 3D model to teach students a topic in astronomy, feedback was evaluated via a questionnaire. Analysis of students' responses to the questions revealed that user interface had a significant impact on their attitudes, which in turn could increase users' willingness to use immersive technology in e-learning. The results also showed that improving visual features through immersive technology and augmented reality tools were effective. The results confirm all hypotheses about positive relationships between facilitating conditions and usability of metaverse technology for students' attention and study motivation.

Metal complexes of mesoionic carbenes (MICs) of the triazolylidene-type and their derivatives have gained increasing attention in the fields of electrocatalysis and photochemistry. The redox-activity of these metal complexes is critical for their applications in both the aforementioned fields. Easy accessibility and modular synthesis open a wide field for the design of ligands, such as bidentate ligands. The combination of a MIC with a pyridyl unit in a bidentate ligand setup increases the π-acceptor properties of the ligands while retaining their strong σ-donor properties. The analogy with the well-established 2,2'-bipyridine ligand allows conclusions to be drawn about the influence of the mesoionic carbene (MIC) moiety in tetracarbonyl group 6 complexes in cyclic voltammetry and (spectro-)electrochemistry (SEC). However, the effects of the different connectivity in pyridyl-MIC ligands remains underexplored. Based on our previous studies, we present here a thorough investigation of the influence of the two different pyridyl-MIC constitutional isomers on the electrochemical and the UV-vis-NIR/IR/EPR spectroelectrochemical properties of group 6 carbonyl complexes. Moreover, the presented complexes were investigated for the electrochemical conversion of CO2 using two different working electrodes, providing a fundamental understanding of the influence of the electrode material in the precatalytic activation.

Current VAT rules for cross-border e-commerce companies in the EU are not sustainable, because they are extremely complex and often opaque, due to the lack of tax harmonization. The aim of the research is to explore, using a qualitative method, what kind of harmonization would make the current legislation more uniform, simpler, more transparent, and easier to understand, without conflicting with the rules of any Member State. To this end, the aspects of the new platform regulation introduced on 1 July 2021 and its potential for expansion are assessed through information from possible sales models. The research suggests that the rules on platforms do not cover all possible sales models, which in our view imposes an unnecessary extra administrative burden on some businesses and makes their tax activities less transparent. In the light of the results of the research, we propose that the current EU platform regulation should be extended to cover B2B, B2C transactions and services. As a result of this suggested harmonization, a simpler, more transparent, uniform and sustainable tax system would contribute to the whitening of the economy, generating additional tax revenue for Member States.

This article is a commentary on the publication Guo J, Hai H, Ma Y. Application of extracorporeal shock wave therapy in nervous system diseases: A review. Front Neurol. (2022) 13:963849. doi: 10.3389/fneur.2022.963849 (1). In the opinion of the authors of this commentary the information provided in the Section "Principles of ESWT" in (1) is partly incorrect and misleading. This is due to the fact that important, published knowledge regarding focused extracorporeal shock wave therapy (fESWT) and radial extracorporeal shock wave therapy (rESWT) was disregarded in (1).

Hepatitis E virus (HEV) is a common cause of acute hepatitis worldwide, accounting for approximately 25% of deaths among pregnant women. We previously reported that pregnancy serum facilitates HEV replication in vitro. However, the differences in host cells with HEV infection induced by pregnancy serum and fetal bovine serum (FBS) are unclear. In this study, differentially expressed proteins were identified in HEV-infected hepatoma cells (HepG2) supplemented with different sera by using isobaric tags for relative and absolute quantitation. Proteomic analysis indicated that HEV infection significantly induced 1014 differentially expressed proteins in HEV-infected HepG2 cells when supplemented with FBS compared with pregnancy serum. Further validation by Western blot confirmed that filamin A, heat-shock proteins 70 and 90, Cytochrome c, and Thioredoxin were associated with HEV infection. This comparative analysis provides an important basis to further investigate HEV pathogenesis in pregnant women and HEV replication.

The shift towards autonomous excavators in construction and mining is a significant leap towards enhancing operational efficiency and ensuring worker safety. However, it presents challenges such as the need for sophisticated decision-making and environmental perception due to complex terrains and diverse conditions. Our study introduces the E-GTN framework, a novel approach tailored for autonomous excavation that leverages advanced multisensor fusion and a custom-designed convolutional neural network to address these challenges. Results demonstrate that GridNet effectively processes grid data, enabling the reinforcement learning algorithm to make informed decisions, thereby ensuring efficient and intelligent autonomous excavator performance. The study concludes that the E-GTN framework offers a robust solution for the challenges in unmanned excavator operations, providing a valuable platform for future advancements in the field.

In sustainable floriculture, the integration of arbuscular mycorrhizal fungi (AMF) and salicylic acid (SA) in the cultivation of statice flowers presents a promising ecofriendly approach to enhancing crop health and productivity. AMF improve nutrient uptake, particularly phosphorus, in plants, leading to stronger growth and abundant flowering while reducing the reliance on chemical fertilizers. Additionally, AMF enhance soil structure and water retention, fostering robust root systems and increasing the plant's resilience to drought and soil-borne pathogens thus improving soil health and minimizing environmental impact. Complementarily, the application of salicylic acid boosts the plant’s innate defense mechanisms, elevating its resistance to diseases, enhancing stress tolerance, helping statice flowers withstand adverse conditions such as drought and salinity, and promotes vigorous root development for better nutrient absorption. Hence, this study evaluates the effect of mycorrhizal inoculation and salicylic acid treatment on ornamental statice (Limonium sinuatum [L.] Mill.) cv. Qis White. The investigation involves two primary factors: mycorrhizal inoculation and salicylic acid concentration. For mycorrhizal inoculation, the study compares the untreated control with treatments including Glomus mossae, Gigaspora margarita, and a mixture of both fungi (applied as basal during transplanting). For salicylic acid, the study assesses the untreated control alongside treatments with Salicylic Acid at 100 mg L-1, 150 mg L-1, and 200 mg L-1 (applied as foliar spray at 45 and 90 days after transplanting) in a factorial RCBD experiment with three replications. Growth, flowering, yield and biomass parameters were assessed in this study. The results indicated that statice plants benefited from mycorrhizal inoculation, particularly with Glomus mosseae, when paired with salicylic acid @ 200 mg L-1. This was further validated by principal component analysis. AMF inoculated plants showed improved growth, and superior flower qualities compared to non-inoculated plants. Additionally, the application of salicylic acid demonstrated positive effects across various parameters. Notably mycorrhization led to a delay of 4 to 9 days in the flowering time of statice. In conclusion, mycorrhizal inoculation and salicylic acid can enhance the growth and flowering attributes of statice by choosing the appropriate mycorrhizal inoculum and optimal salicylic acid concentrations. In the future they can contribute to more sustainable and productive statice cultivation by reducing the need for chemical inputs and supporting overall plant health.

For the first time VIS/NIR-SWIR (visible and near infrared – shortwave infrared) nighttime spectra of a satellite mission are analyzed, using the EnMAP (Environmental Mapping and Analysis Program) high-resolution imaging spectrometer. The focus of this article is set on the spectral characteristics. First, the spectral calibration of EnMAP is checked based on sodium emissions of lighting. Here, applying a realized novel general method, shifts of +0.3nm for VIS/NIR and −0.2nm for SWIR are identified with uncertainties analyzed to be in the range of [−0.4nm,+0.2nm] for VIS/NIR and [−1.2nm,+1.0nm] for SWIR. These results emphasize the high accuracy of the spectral calibration of EnMAP and illustrate the feasibility of methods based on nighttime Earth observations for the spectral calibration of future nighttime satellite missions. Second, applying a realized simple general method, the dominant lighting types of Las Vegas, Nevada, USA, and thermal emissions are identified per pixel and the consistency of the outcomes is considered. These results illustrate the feasibility of the precise identification of lighting types and thermal emissions based on nighttime high-resolution imaging spectroscopy satellite products and support the specification of, in particular, spectral characteristics of future nighttime missions.

A common challenge in real-world classification scenarios with sequentially appending target domain data is insufficient training datasets during the training phase. Therefore, conventional deep learning and transfer learning classifiers are not applicable especially when individual classes are not represented or are severely underrepresented at the outset. Domain Generalization approaches reach their limits when domain shifts become too large, making them occasionally unsuitable as well. In many (technical) domains, however, it is only the defect/ worn/ reject classes that are insufficiently represented, while the non-defect class is often available from the beginning. The proposed classification approach addresses such conditions and is based on a CNN encoder. Following a contrastive learning approach, it is trained with a modified triplet loss function using two datasets: Besides the non-defective target domain class (= 1st dataset), a state-of-the-art labeled source domain dataset that contains highly related classes (e.g., a related manufacturing error or wear defect) but originates from a (highly) different domain (e.g., different product, material, or appearance) (= 2nd dataset) is utilized. The approach learns the classification features from the source domain dataset while at the same time learning the differences between the source and the target domain in a single training step, aiming to transfer the relevant features to the target domain. The classifier becomes sensitive to the classification features and – by architecture – robust against the highly domain-specific context. The approach is benchmarked in a technical and a non-technical domain and shows convincing classification results. In particular, it is shown that the domain generalization capabilities and classification results are improved by the proposed architecture, allowing for larger domain shifts between source and target domains.

Here we introduce Literature Mapper, a Python QGIS plugin that provides a method for creating a spatial bibliography manager as well as a specification for storing spatial data in a bibliography manager. Literature Mapper uses QGIS’ spatial capabilities to allow users to add location information to a Zotero library, a free and open source bibliography manager. Literature Mapper enhances the citations in a user’s online Zotero database with geo-locations by storing spatial coordinates as part of traditional citation entries. Literature Mapper receives data from and sends data to the user’s online database via Zotero’s web API. By using Zotero as the backend data storage, Literature Mapper benefits from all of its features including shared citation Collections, public sharing, and an open web API usable by additional applications, such as web mapping libraries. We evaluate Literature Mapper’s ability to provide insights into the spatial distribution of published literature by mapping the study sites described in academic publications related to California’s coastal strand vegetation. The results of this exercise are presented in static and web map form.

Despite the popularity of theraphosids, detailed reports on bite symptoms are still limited to few geographic regions and subfamilies. We therefore examined 363 published bite reports and noticed muscles cramps caused by theraphosids from nearly all continents and subfamilies. Symptoms are mostly locally restricted and mild, but 12.7% of victims experience pronounced cramps with highest incidence rates by Poecilotheriinae, Harpactirinae and Stromatopelminae subfamilies. We discuss how variations in venom quantity correlate with muscle cramp prevalence.

Households and businesses are generating unprecedented levels of electrical and electronic wastes (e-waste), fueled by modernisation and rapid obsolescence. While the challenges imposed by e-waste are similar everywhere in the world, disparities in progress to deal with it exists; with developing nations such as South Africa lagging. The increase in e-waste generation increases the need to formulate strategies to manage it. This paper presents an overview of e-waste management on a global and South African scenarios with a specific case for Cathode Ray Tube (CRT) waste management practices in South Africa. CRTs present the biggest problem for recyclers and policy makers because they contain hazardous elements such as lead and antimony. Common disposal practices have been either landfilling or incineration. The research into the South African practices with regards to CRT waste management showed that there is still more to be done to effectively manage this waste stream. This is despite clear waste regulatory frameworks in the country. However, recent developments have placed e-waste as a priority waste stream, which should lead to intensified efforts in dealing with it. Overall, these efforts should aim to maximise diversion from landfilling and to create value-addition opportunities, leading to social and environmental benefits.

Geographic information systems (GIS) are critical for mapping the geographical distribution of illness prevalence, disease transmission patterns, and spatially modeling environmental elements of disease occurrence. This study was purposively to map and cluster five diseases such as cholera, diabetes, malaria, asthma and hypertension using GIS techniques in Southern Malawi. Getis-Ord Gi* statistic was used to determine spatial distribution of diseases. Data were acquired from Malawi Demographic Health Survey (DHS) and assessed geographically using spa-tial-statistical analytical techniques, including the kernel and hotspot models. These models were developed to investigate and exhibit the dissimilar patterns of the selected diseases, as well as to depict places of high concentration, and they may be useful in understanding local patterns of diseases and their geographical correlations. The study found that asthma is high in Mangochi, Balaka, Blantyre, Thyolo, Mulanje, Chikwawa and Nsanje districts. It was also revealed that hypertension patients were highly concentrated in Blantyre, Thyolo, Chikwawa, Zomba, Mangochi and Nsanje Districts. Mangochi, Phalombe, Nsanje and Chikwawa are high risk areas of Malaria and diabetes is highest in Blantyre. Cholera is high in Mangochi, Balaka, Blantyre, Thyolo, Mu-lanje, Chikwawa and Nsanje districts.

The population dynamics of Hazel Grouse was studied by presence/ absence recording at stationary sites along fixed routes (110 km) during 1972-2019 in the central part of the Bohemian Forest (Šumava, Czech Republic). The 100-km² study area covered altitudes between 600 m (Rejstejn) and 1,253 m a.s.l., (mount Sokol). Our data base contained indices of Hazel Grouse occupancy: positive sites/ controlled sites for a yearly increasing number of Hazel Grouse occurrence sites (N = 134) for 48 years. We used a loglinear Poisson-regression method to analyze the long-term population trend for Hazel Grouse in the study area. In the period 1972 to 2006 we found a stable Hazel Grouse population (p = 0.83). From 2006-2007 to 2019, the population index dropped (-3.8% per year, p < 0.05) for the last 13 years. This decline is assumed to be influenced by habitat loss due to succession resulting in older, more open forest stands, by strongly increasing forestry and windstorm “Kyrill” followed by clear cutting, bark-beetle damage, and removal of pioneer trees in spruce plantations, which diminished buds and catkins, the dominant winter food. The influence of disturbance by increasing touristic activities and/or predation is discussed. Our results could help to optimize conservation efforts for Hazel Grouse in the Bohemian Forest.

With a global estimate of tens of thousands of arachnid enthusiasts, spiders and scorpions are gaining increasing popularity as pets in industrialised countries in Europe, Northern America and Asia. As most spiders and all scorpions are venomous and due to their mostly negative image in the public media, several governments are already considering introducing legislation to regulate the domestic care of potentially dangerous captive animals. We aimed to investigate the circumstances and effects of exposure to arachnids kept in captivity. Thus, we collected and analysed data from 354 self-reported bites and stings attributed to pet arachnids. Our data revealed that on average there were less than 20 recorded envenomations per year with ~90% preventable by due care. We also categorized the severity of the resulting symptoms and found that the vast majority of symptoms were either local (60.7%) or minor (32.8%), 5.4% were asymptomatic, only 1.1% were severe and no fatalities were recorded. Based on our database of bite and sting reports, we performed a risk assessment for arachnid pet ownership and concluded that, with the proper care, arachnids can be safely kept as pets and pose a lower risk than many other recreational activities.

Ferric oxide containing waterworks sludge can be used to reduce formation of hydrogen sulfide during anaerobic digestion. The ferric compound is reduced biochemically in the digester and forms insoluble pyrite in digester sludge. Often virgin ferric chloride is used to solve the hydrogen sulfide problem. Since 2013, Sydvatten AB has supplied a growing number of digestion plants in Sweden with ferric containing dewatered waterworks sludge from the drinking water treatment plant Ringsjöverket to limit the formation of hydrogen sulfide. At the waterworks, ferric chloride is added to enhance coagulation of organic matter from the source water. The sludge formed in this process is dewatered and landfilled, but also recycled in the biogas production in order to reduce the hydrogen sulfide concentration. In this study, the use of sludge, for hydrogen sulfide removal in digesters, was technically and economically evaluated from cases studies from 13 full-scale digesters in Sweden. Compared with use of fresh ferric chloride, the operational costs are reduced up to 50 % by using sludge. The quality of the sludge is high and its content on metals is low or very low, especially when compared with requirements from different certification standards on biosolid reuse applied in Sweden. An addition of waterworks sludge containing iron to a digester for removal of dissolved hydrogen sulfide is a technically and economic good alternative when producing biogas. It is also one step closer to a circular economy, when replacing use of virgin chemicals with the by-product waterworks sludge which saves energy, material and reduces the carbon foot-print of the waterworks.

The development of biofuels and biodiesel industry specifically, has resulted in the generation of large amounts of glycerol as a surplus. The conversion of glycerol, into chemicals with indus-trial interest, through anaerobic fermentation using E. coli as a biocatalyst is an attractive alter-native to improve economic performance in the biodiesel industry, for example through the bi-otransformation of residual glycerol into ethanol. For 2019, the size of the global ethanol market was valued at $ 89.1 billion US dollar. Biodiesel can be produced from several materials like rapeseed, palm, soya, corn, palm kernel, frying oil or olive-pomace oil (OPO). The last, can be extracted from alperujo, byproduct of olive oil process. However, olive-pomace oil converting into biodiesel is not enough established to achieve a global olive-oil/biodiesel derived process with minimized waste generation. Traditionally biodiesel production process produces an equivalent of 10% by mass of glycerol as a waste or by-product. This work explores the conver-sion of residual glycerol into chemicals like ethanol and hydrogen with a focus on projecting raw material potential availability from OPO, contributing to the promotion of the use of biofu-els and biodegradable compounds.

The synthesis and crystal structure of pyrazine-2,5-diyldimethanol (pzydmH2, C8H8N2O2) a new symmetric water-soluble N,O-chelating tetra-dentate organic ligand is reported and an environmentally friendly method was used to synthesize coordination compounds in water under ambient conditions from the reaction of pzydmH2 with the halide salts of Cu(II), Zn(II), Hg(II) and Cd(II): {[Cu(pzydmH2)0.5(µ-Br)(Br)(H2O)]·H2O}n 1, {[Zn2(pzydmH2)(µ-Cl)(Cl)3(H2O)]·H2O}n 2, [Hg2(pzydmH2)0.5(µ-Cl)2(Cl)2]n 3, {[Cd2(pzydmH2)(µ-Cl)4]·H2O}n 4, and {[Cd2(pzydmH2)(µ-Br)4]·H2O}n 5. Single-crystal X-ray diffraction analysis revealed that 1-3 are 1D coordination polymers and 4 and 5 are 3D coordination networks, all constructed by bridging pyrazine-2,5-diyldimethanol and halogen ions. The hydroxyl groups in the organic linker extend the 1D chains to non-covalent 3D networks. In all non-covalent and covalent 3D networks water molecules were trapped by strong hydrogen bond interactions. Supramolecular analysis revealed strong O-H···O, O-H···N, O-H···X and week of C-H···O, C-H···X (X = Cl, Br) hydrogen bonds, as well as π-π(pyrazine ring), metal-halogen···π(pyrazine ring) and O-H···ring(5-membered chelate ring) interactions. Also X···O weak halogen bonds are present in 1-5 (X = Cl and Br).

Below T_CO=157 K the quasi-one-dimensional charge-transfer salt (TMTTF)_2SbF_6 undergoes a pronounced phase transition to a charge-ordered ground state. We have explored the non-linear and photoconductive behavior as a function of applied voltage, laser pulse energy and temperature. Besides a decay of the photoconductive signal in a double exponential fashion in the millisecond range, we discover current oscillations in the kHz range induced by the application of short laser pulses. While the resonance frequencies do not depend on voltage or laser intensity and vary only slightly with temperature, the amplitude changes linearly with the laser intensity and voltage. The findings are discussed and compared to comparable phenomena in other low-dimensional electron systems.

Objective: Although much of the research literature has found that individuals tend to perceive their friends as similar to themselves, we hypothesized that individuals with strong narcissistic traits may be less likely to do so because of their tendency to view themselves as unique. Method: We used self-reports and friend-reports in two studies with 129 participants from Germany and 131 participants from the US to examine the moderating effects of narcissistic personality features on the tendency to perceive one’s friends as having similar humor styles. Results: The results revealed that individuals generally tend to view themselves as similar to their friends in terms of humor styles. As expected, we found a moderating effect of narcissism such that higher levels of narcissism were associated with lower levels of perceived similarity. Interestingly, individuals high in grandiose narcissism tended to devalue their close friends’ humor, and individuals high in vulnerable narcissism tended to enhance their friends’ humor compared with themselves. Conclusion: The results suggest that narcissistic individuals may tend to view their friends through a particular lens, regardless of their friends’ actual traits. This mechanism may be related to the narcissistic need to feel unique.

Industrial manipulators and parallel robots are often used for tasks like drilling or milling, that require three translational, but only two rotational degrees of freedom (“3T2R”). While kinematic models for specific mechanisms for these tasks exist, a general kinematic model for parallel robots is still missing. This paper presents the definition of the rotational component of kinematic constraints equations for parallel robots based on two reciprocal sets of Euler angles for the end-effector orientation and the orientation residual. The method allows to completely remove the redundant coordinate in 3T2R tasks and to solve the inverse kinematics for general serial and parallel robots with the gradient-descent algorithm. The functional redundancy of robots with full mobility is exploited using nullspace projection.

Protein tyrosine phosphatase receptor type E (PTPRE) is a member of the “classical” protein tyrosine phosphatase subfamily and regulates a variety of cellular processes in a tissue-specific manner by antagonizing the function of protein tyrosine kinases. PTPRE plays a tumorigenic role in different human cancer cells, but its role in retinoblastoma (RB), the most common malignant eye cancer in children, remains to be elucidated. Etoposide resistant RB cell lines and RB patients display significant higher PTPRE expression levels compared to chemosensitive counterparts and the healthy human retina, respectively. PTPRE promotor methylation analyses revealed that PTPRE expression in RB is not regulated via this mechanism. Lentiviral PTPRE knockdown (KD) induced a significant decrease in growth kinetics, cell viability, and anchorage independent growth of etoposide resistant Y79 and WERI RB cells. Caspase-dependent apoptosis rates were significantly increased and a re-sensitization for etoposide could be observed after PTPRE depletion. In vivo chicken chorioallantoic membrane (CAM) assays revealed decreased tumor formation capacity as well as reduced tumor size and weight following PTPRE KD. Expression levels of miR631 were significantly downregulated in etoposide resistant RB cells and patients. Transient miR631 overexpression resulted in significantly decreased PTPRE levels and concomitantly decreased proliferation and increased apoptosis levels in etoposide resistant RB cells, impacts mirroring PTPRE KD effects and indicating PTPRE regulation via this miR. Additionally, PTPRE KD led to altered phosphorylation of protein kinase SGK3 and - dependent on the cell line - also AKT and ERK1/2, suggesting potential PTPRE downstream signaling pathways. In summary, these results indicate an oncogenic role of PTPRE in chemoresistant retinoblastoma.

The transmission and analysis of data is one of the challenges of the 21st century. In the field of environmental measurement technology, existing broadband and wireless technologies have not been able to transmit data reliably and cost-effectively over long distances and in hard-to-reach places. LoRaWAN, an IoT technology, could be an energy-efficient, cost-effective and secure alternative as a narrowband technology in combination with battery-powered sensors and thus make an important contribution to the intelligent, largely wireless networking of objects, plants and machines (IoT), for example in the municipal sector. In addition to ecological and economic benefits, the quality of life in modern, intelligently networked cities can be enhanced by real time data acquisition. However, the prerequisite is that the quality of the data acquired via this method is sufficiently good. This paper therefore addresses the question of the quality of particulate matter data collected by low-cost sensors. To determine this, an SDS011 particulate matter sensor from Nova Fitness was ported to LoRaWAN. The sensor was installed next to a governmental measurement station. In a test that lasted five weeks, data from the SDS011 sensor were compared with those from the governmental station. Differences were identified and a correction approach was developed and applied. The efficiency of the approach was verified. Based on the results, it can be seen that the use of the low cost sensors has weaknesses. Problems can only be partially reduced. Nevertheless, the use of the low-cost sensors can be helpful for a flexible and cost effective collection of environmental data.

Abstract: The most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is the presence of poly-PR/GR dipeptide repeats which are encoded by the C9orf72 gene. Recently, it was shown that poly-PR/GR alters chromatin accessibility which results in stabilization and enhancement of transcriptional activity of the tumor suppressor p53 in several neurodegenerative disease models. Reduction of p53 protein levels in cell and model organisms protects against neurotoxicity of poly-PR, and partially protects against neurotoxicity of poly-GR. Here, we aimed to study the detailed molecular mechanisms how p53 contributes to poly-PR/GR mediated neurodegeneration. Using a combination of biophysical techniques such as nuclear magnetic resonance (NMR) spectroscopy, fluorescence polarization, turbidity assays and differential interference contrast (DIC) microscopy, we found that p53 physically interacts with poly-PR/GR and triggers liquid-liquid phase separation of p53. We identified p53 transactivation domain 2 (TAD2) as the main binding site for PR25/GR25 and show that binding of poly-PR/GR to p53 is mediated by a network of electrostatic and/or hydrophobic interactions. Our findings might help to understand the mechanistic role of p53 in poly-PR/GR - associated neurodegeneration.

Oncogenic protein E6 from Human Papilloma Virus 16 (HPV-16) mediates the degradation of Membrane-associated guanylate kinase with inverted domain structure-1 (MAGI-1), throughout the interaction of its protein binding motif (PBM) with the Discs-large homologous regions 1 (PDZ1) domain of MAG1-1. Generic variation in the E6 gene that translates to changes in the protein’s amino acidic sequence modifies the interaction of E6 with the cellular protein MAGI-1. MAGI-1 is a scaffolding protein found at tight junctions of epithelial cells, where it interacts with a variety of proteins regulating signaling pathways. MAGI-1 is a multidomain protein containing two WW (rsp-domain-9), one guanylate kinase-like, and six PDZ domains. PDZ domains played an important role in the function of MAGI-1 and served as targets for several viral proteins including the HPV-16 E6. The aim of this work was to evaluate, with an in silico approach, employing molecular dynamics simulation and protein-protein docking, the interaction of the intragenic variants E-G350 (L83V), E-C188/G350 (E29Q/L83V), E-A176/G350 (D25N/L83V), E6-AAa (Q14H/H78Y/83V) y E6-AAc (Q14H/I27RH78Y/L83V) and E6-reference of HPV-16 with MAGI-1. We found that variants E-G350, E-C188/G350, E-A176/G350, AAa and AAc increase their affinity to our two models of MAGI-1 compared to E6-reference.

Roundabouts need capacity and safety improvements compatible with manual-driven, not only with autonomous vehicles. The signaling and control of roundabouts must evolve and incorporate current technologies. For that, we approach roundabouts as synchronous switches of vehicles. This paper describes Synchronous Roundabouts with Rotating Priorities, a roundabout control system based on vehicle platoons arriving at the roundabout at speed identical to the roundabout and within the time slot assigned to their entry, avoiding conflicts and stops, thus increasing roundabout capacity and safety. Signaling is visual for human drivers and also wireless for connected and autonomous vehicles. We evaluate analytically and with simulations roundabouts of different radius for several values of the average distance between vehicles. Average delays are 28,7 % lower, with negligible dispersion. The capacity improvements depend on design parameters: in our set is moderate for small roundabouts but goes up to 70-100 % for short distances and medium and large roundabouts.

Machine learning methods have widely been applied to detect anomalies in machine and cutting tool behavior during lathe or milling. However, detecting anomalies in the workpiece itself did not get the same attention by researchers. That is why in this article, the authors present a pub-licly available multivariate time series dataset which was recorded during milling of 16MnCr5. Due to artificially introduced, though realistic anomalies in the workpiece the dataset can be ap-plied for anomaly detection. By using a convolutional autoencoder as a first model good results in detecting the location of the anomalies in the workpiece were achieved. Furthermore, milling tools with two different diameters where used which led to a dataset eligible for transfer learn-ing. The objective of this article is to provide researchers with a real-world time series dataset of the milling process which is suitable for modern machine learning research topics like anomaly detection and transfer learning.

The scratch test consists in pushing a tool across the surface of a material at a given penetration depth or applied load. It has several applications in Science and Engineering including strength testing, damage and quality control of thin films and coatings. Despite numerous attempts in scientific literature, the application of scratch test to characterizations of fracture properties remains a heavily controversial topic. Therefore, this investigation arises as an experimental study in order to assess the fracture toughness using scratch test. A study on the effect of cryogenic treatment, performed after tempering, on fracture toughness, via scratch test experiments, of different tool steels has been made. A laboratory investigation on AISI D2, AISI M2 and X105CrCoMo18 steel confirms the possibility of increasing the fracture toughness by carrying out the cryogenic treatment after the usual heat treatment

Quantification of physical activity (PA) depends on the type of measurement and analysis method making it difficult to compare adherence to PA guidelines. Therefore, test-retest reliability, criterion validity, and stability for self-reported (i.e. questionnaire and diary) and device-based measured (i.e. accelerometry with 10/60 second epochs) PA was compared in 32 adults and 32 children from the SMARTFAMILY study to examine if differences in these measurement tools are systematic. PA was collected during two separate measurement weeks and the relationship for each quality criteria was analyzed using Spearman correlation. Results showed the highest PA values for questionnaires followed by 10-second and 60-second epochs measured by accelerometers. Levels of PA were lowest when measured by diary. Only accelerometry demonstrated reliable, valid, and stable results for the two measurement weeks, the questionnaire yielded mixed results and the diary showed only few significant correlations. Overall, higher correlations for the quality criteria were found for moderate than for vigorous PA and the results differed between children and adults. Since the differences were not found to be systematic, the choice of measurement tools should be carefully considered by anyone working with PA outcomes, especially if vigorous PA is the parameter of interest.

The graphene based highly conductive and flexible devices has received momentous attraction and growth in recent years for potential multifunctional uses. The development of flexible and washable textile sensors, actuators, energy storage and energy harvesting systems. Textile fabrics coated with graphene and conductive polymers have been used for wearable self-powered e-textiles, such as tribo-electric, piezoelectric, and Thermoelectric. Herein this research, 100% woven cotton fabric is Fictionalized with graphene oxide (GO) using industrial-scale cold pad batch dyeing technique for the development of low-grade body heat into self-powered wearable e-textiles. The conductive polymer PEDOT: PSS was coated using layer by layer approach. The study demonstrates that the resultant textile electrodes showed reduced electrical sheet resistance from 2.5 MΩ to 15KΩ, with a reduced graphene oxide and further reduced to (2.5 -12.5 Ω) for conductive polymer. The sheet resistance was decreased with the number of dyeing cycles (10-15) and increased with 20 washing cycles vice versa. The study demonstrates that the sensor response and performance were improved with increasing the content percent of rGO and PEDOT: PSS. The tensile strength of as coated fabric electrodes was improved from (25.0-85.5 mPa) and fabric thickness was increased to (26-38µm) without compromising or influencing the air permeability. The resultant textile electrodes may potentially be used in smart textiles for self-powered flexible wearable generators, sensors, and energy storage. The study demonstrates that the cold pad batch dyeing method is a suitable and effective method for the fabrication of graphene-based textiles.

In 2020, students of Pakistan had to adapt to the online environment for the very first time. This study aims to analyze the perceptions of medical, dental, and allied health students about online education in Pakistan. A descriptive, cross-sectional study was done to assess the level of acceptance of undergraduate students. A pre-validated questionnaire regarding demographics, past-experience of e-learning, advantages disadvantages of e-learning, and general perception of students towards e-learning was distributed. Descriptive statistics were computed for demographics, Mann-Witney-U test was used to compare the differences of perceptions between pre-clinical year and clinical years students. Kruskal-Wallis test was applied to compare the results of three specialties of students. Chi-square was used to compare overall category-wise positive and negative responses of students. 1200 students participated in the study. The major advantage identified by all students was the ‘comfortable environment’ in which they studied online. The major disadvantage selected by preclinical year students was ‘anxiety due to social isolation’ and that chosen by clinical year students was ‘lack of patient interaction’. Overall, 72% of students had a negative perception of e-learning. Student-teacher training, student counselling sessions, and innovative techniques need to be introduced to enhance student engagement and reduce pandemic stress.

Non-invasive continuous health monitoring has become feasible with the advancement of biosensors. While monitoring certain biomarkers such as heart rate or skin temperature are now at certain maturity, monitoring molecular biomarkers is still challenging. Progress has been shown in sampling, measurement and interpretation of data towards non-invasive molecular sensors that can be integrated in daily wearable items. Towards this goal, this paper explores the potential of embroidered interdigitated transducer (IDT)-based sensors for non-invasive, continuous monitoring of human biomarkers, particularly glucose levels, in human sweat. The study employs innovative embroidery techniques to create flexible fabric-based sensors with gold-coated IDTs. In controlled experiments, we have shown the variation of glucose concentration in water can be wirelessly detected by tracking the resonant frequency of the embroidered sensors. The current sensors operate at 1.8GHz–2GHz and respond to the change of glucose concentration with a sensitivity of 0.17 MHz/(mg/dl). The embroidered IDT-based sensors with wireless sensing will be a new measurement modality for molecular wearable sensors. The establishment of a wireless sensing mechanism for embroidered IDT-based sensors will be followed by investigation of sweat for molecular detection. This will require adding functionalities for sampling and interpretation of acquired data. We envisage the embroidered IDT-based sensors offer a unique approach for seamless integration into clothing, paving the way for personalised, continuous health data capture.

Background: Bronchopulmonary dysplasia (BPD) is the most common respiratory disease in pre-term and is still associated with increased mortality and morbidity. The great interest lies in iden-tifying early biomarkers that can predict the development of BPD. Objectives: This pilot study explores the potential of e-nose for early identification of BPD risk in premature infants by analyzing volatile organic compounds (VOCs) in the exhaled breath con-densate (EBC). Materials and Methods: Fourteen mechanically ventilated very preterm infants were included in the study. Clinical parameters and EBC were collected within the first 24 hours of life. The dis-criminative ability of breath-prints between preterms who did and did not develop BPD was in-vestigated by pattern recognition, machine learning algorithm, and standard statistical methods. Results: We found that e-nose probes can significantly predict the outcome of “no-BPD” vs “BPD”. Specifically, a subset of probes (S18, S24, S14, and S6) were found to be significantly predictive, with an AUC of 0.87, 0.89, 0.82, 0.8 and p=0.019, 0.009, 0.043, 0.047, respectively. Conclusion: The E-nose is an easy-to-use, handheld, non-invasive electronic device that quickly samples breath. Our preliminary study has shown that it has the potential for early prediction of BPD in preterms.

In recent years, the prevalence of tobacco and electronic cigarette (e-cigarette) use among adolescents has raised significant public health concerns worldwide. This study aims to investigate respiratory symptoms among Polish adolescents. We conducted an online survey among Polish school students from all provinces, collecting data over two months in Spring 2021. Students voluntarily complete the anonymous survey, answering questions about respiratory symptoms, smoking habits (both traditional and electronic cigarettes), and demographic information. Analysis focused on four subgroups: non-tobacco users, traditional cigarette smokers, e-cigarette users, and dual users, totaling 10,388 pupils aged 12-18 years, predominantly attending secondary technical and comprehensive schools. A total of 10388 pupils participated in the study, 55.6 % (5778) of whom were girls and 44.4 % (4610) boys. Adolescents, who admitted using both e-cigarettes and traditional cigarettes experienced more frequent episodes of cough during the day (39.70%) and at night (18.40%) compared to their peers in other groups. Chest discomfort, including pain and pressure, was also reported more often by adolescents, who used e-cigarettes and traditional cigarettes concurrently (27.60%) compared to their peers in other groups. Chest pressure was experienced less commonly by non-smoking adolescents (14.40%) than by smokers (18.90%). Higher severity of cough during the day and at night was observed in the group of adolescents using traditional cigarettes and e-cigarettes concurrently compared to the other groups. The adolescents in the dual user group experienced more severe dyspnoea and wheezing compared to the other groups included in the comparison. The results of this study confirm the correlation between the occurrence of respiratory symptoms in adolescents who smoke cigarettes, use e-cigarettes and in dual users. The respiratory symptoms occur most frequently and are the most severe in the group of adolescents who use e-cigarettes and traditional cigarettes

BACKGROUND: Qu-aroma is a critical quality indicator for medium-high temperature Daqu (MT-Daqu), significantly influencing the aroma profile of strong-aroma Baijiu (SAB). SAB is produced across various regions in China, each with unique environmental conditions and production techniques. These regional differences are likely to cause variations in the Qu-aroma of MT-Daqu. Despite this, comprehensive research on the variations in Qu-aroma across different regions has been lacking. This study aims to address this gap by utilizing Gas Chromatography-Olfactometry-Mass Spectrometry (GC-O-MS) and electronic nose (E-nose) technology, combined with sensory evaluation, to analyze the differences in Qu-aroma characteristics and volatile compound profiles of MT-Daqu from seven distinct production areas.RESULTS: Sensory analysis identified seven broad aroma categories and 25 specific aromas characterizing the Qu-aroma of MT-Daqu samples. Chen aroma and roasted aroma were notably more prevalent in MT-Daqu samples from Sichuan compared to those from other regions (P < 0.05), while the fermentation aroma was less prominent in Sichuan samples. In total, 123 volatile compounds were detected in MT-Daqu, with 46 classified as aroma-active compounds. Among these, 21 aroma-active compounds were identified as markers distinguishing Sichuan MT-Daqu from those produced in non-Sichuan regions, showing significant differences in their concentrations (P < 0.05). Additionally, six major aroma-active compounds-ethyl isovalerate, ethyl heptanoate, hexanal, 1-nonanal, (E)-2,4-decadienal, and 2,3-dimethyl-5-ethylpyrazine-were found to significantly contribute to the aroma differences between Sichuan and non-Sichuan MT-Daqu.CONCLUSION: This study delineates the distinct Qu-aroma characteristics of MT-Daqu from various SAB production areas and identifies the aroma-active compounds responsible for these differences. The insights gained from this research offer valuable guidance for optimizing flavor profiles in MT-Daqu production, potentially enhancing the overall quality and regional distinctiveness of the product.

Agriculture is the backbone of Kenya’s economy, supporting up to 80% of the rural livelihoods. Kenya’s export horticulture is currently the leading Agriculture subsector in Kenya has evolved from small-holder farming to agro-industrial large-scale export farming dominated by multinational companies. It is regarded as an agro-industrial food system based on the economies of scale producing for mass markets outside of the production area. Much of the food consumed from this food system has undergone multiple transformations and been subject to a host of formal and informal insitutions (rules, regulations, standards, norms and values). An Anthropological study of export horticulture in Northwest Mount Kenya was carried out utilizing qualitative data collection methods in Northwest Mount Kenya region. Data was coded and analysed thematically based on grounded theory approach. The study described the institutional settings of export horticulture from an emic perspective as changing and defining the operations of the food system access and management of common pool resources, namely water and land. With the agro-industrial food system competing for these scarce resources in a semi-arid zone, there is potential for conflict and also reduced production and overall benefits to the different actors in the study area.

Extracorporeal shock wave therapy (ESWT) is a safe and effective treatment option for various pathologies of the musculoskeletal system. Many studies addressed the molecular and cellular mechanisms of action of ESWT. However, no uniform concept could be established in this matter until now. We performed a systematic review of the effects of exposure of musculoskeletal tissue to extracorporeal shock waves (ESWs) reported in the literature. The key results were as follows: (i) compared to the effects of many other forms of therapy, the clinical benefit of ESWT does not appear to be based on a single mechanism; (ii) different tissues respond to the same mechanical stimulus in different ways; (iii) just because a mechanism of action of ESWT was described in a study does not automatically mean that this mechanism was relevant to the observed clinical effect; (iv) focused ESWs and radial ESWs seem to act in a similar way; and (v) even the most sophisticated research into the effects of exposure of musculoskeletal tissue to ESWs cannot substitute clinical research in order to determine the optimum intensity, treatment frequency and localization of ESWT.

Climate analogues provide forestry practice empirical evidence of how forests are managed in “twin” regions, i.e. regions where the current climate is comparable to the expected future climate at a site of interest. But the uncertain future climate creates uncertainty in how to adapt the forests. We therefore investigate how the uncertainty in future climate affects tree species suitability and whether there is a common underlying pattern. Like most studies we employ different ensemble variants of RCP 4.5 and 8.5. But instead of focusing on a single point in future time, we resolve each variant in a climate trajectory from 2000 to 2100. We calculate climatic distances between the climate trajectories of our site of interest and the current climate in Europe, generating maps with twin regions from 2000 to 2100. Forest inventories from the twin regions allow us to trace the changes in the prevalence of 23 major tree species. We find that it is not the direction but rather the velocity of the change that differs between the scenarios. We use this pattern to propose a tree species suitability concept that integrates the uncertainty in future climate. Twin regions provide further information on silvicultural practices, pest management, product chains etc.

The healthcare sector has undergone a profound transformation, owing to the influential role played by IoMT (Internet of Medical Things) technology. However, there are substantial concerns over these devices' security and privacy-preserving nature. Current literature on IoMT tends to focus on specific security features like data confidentiality or data integrity or data availability or access control and most solutions are simulated and not tested in a real-world live network. This paper proposes a smart secure by design solution that safeguards user’s data during health and wellbeing monitoring of patients locally (home, care-home, and hospital) and remotely. The proposed innovative solution is known as Secure by Design Real Time IoMT Architecture for e-Health Population Monitoring (RTPM) for smart hospitals and any healthcare monitoring management. In this system, keys can also be generated by the patient monitoring system independent to maintain high privacy standard and trust during the monitoring process and to enable the IoMT devices run independently even if the server is compromised and are made safe from external exploits to the client nodes. However, the session keys are controlled by the trusted IoMT server to lighten the IoMT devices overheads and the session keys are securely exchanged between the client system and the monitoring server. The proposed RTPM focuses on addressing the major security requirements for an IoMT system: confidentiality, integrity, availability, conducts authentication, protect from DoS attacks and prevent from non-repudiation attack of patient medical data and the devices in a real time, sensory data communication environment for live e-health monitoring. A secure communication is tested by capturing the live network traffic and the system’s performance analysis of RTPM using different security algorithms with different key sizes of RSA, AES, and SHA shows that resource constraint low powered system can also successfully integrate with high-end state-of-the-art secure parameters and features and have the potential to support real time secure interaction. A stress test is also conducted to ensure that the system can withstand huge key sizes and different data types including multi-media information.

Abstract: Droughts are complex and gradually evolving conditions of extreme water deficits which can compromise livelihoods and ecological integrity, especially in fragile arid and semi-arid regions that depend on rainfed farming, such as Kitui West in south-eastern Kenya. Against the background of low ground-station density, 10 gridded rainfall products and four gridded temperature products were used to generate an ensemble of 40 calculations of the Standardized Precipitation Evapotranspiration Index (SPEI) to assess uncertainties in the onset, duration and magnitude of past droughts. These uncertainties were driven more by variations between the rainfall products than variations between the temperature products. Remaining ambiguities in drought occurrence could be resolved by complementing the quantitative analysis with ground-based information from key informants engaged in disaster relief, effectively formulating an ensemble approach to SPEI-based drought identification to aid decision making. The reported trend towards drier conditions in Eastern Africa was confirmed for Kitui West by the majority of data products, whereas the rainfall effect on the increasingly dry conditions was more subtle than annual and seasonal declines and greater annual variation, which warrants further investigation. Nevertheless, the effects of increasing droughts are already felt on the ground and warrant decisive action.

Porphyrinic photosensitizers (PSs) and their nano-sized polymer-based carrier systems are required to exhibit low dark toxicity, avoid side effects, and ensure high in vivo tolerability. Yet, little is known about the intracellular fate of PSs during the dark incubation period and how it is af-fected by nanoparticles. In a systematic study, high resolution magic angle spinning NMR spectroscopy combined with statistical analyses was used to study the metabolic profile of cultured HeLa cells treated with different concentrations of the PS chlorin e4 (Ce4) alone or encapsulated in carrier systems. For the latter, either polyvinylpyrrolidone (PVP) or the micelle forming polyethylene glycol (PEG)-polypropylene glycol triblock copolymer Kolliphor P188 (KP) were used. Diffusion edited spectra indicated Ce4 membrane localization evidenced by Ce4 concentration dependent chemical shift perturbation of the cellular phospholipid choline resonance. The effect was also visible in the presence of KP and PVP, but less pronounced. The appearance of the PEG resonance in the cell spectra pointed towards cell internalization of KP whereas no conclusion could be drawn for PVP that remained NMR-invisible. Multivariate statistical analyses of the cell spectra (PCA, PLS-DA and oPLS) revealed a concentration-dependent metabolic response upon exposure to Ce4 that was attenuated by KP and even more by PVP. Significant Ce4-concentration dependent alterations were mainly found for metabolites involved in the tricarboxylic acid cycle and the phosphatidylcholine metabolism. The data underline an important protective role of the polymeric carriers following cell internalization. Moreover, the current study allowed - to our knowledge for the first time - to trace the intracellular PS localization on an atomic level by NMR methods.

Soil hydraulic properties are often derived indirectly, i.e. computed from easily available soil properties with pedotransfer functions (PTFs), when those are needed for catchment, regional or continental scale applications. When predicted soil hydraulic parameters are used for the modelling of the state and flux of water in soils, uncertainty of the computed values can provide more detailed information when drawing conclusions. The aim of this study was to update the previously published European PTFs (Tóth et al., 2015, euptf v1.4.0) by providing prediction uncertainty calculation built into the transfer functions. The new set of algorithms was derived for point predictions of soil water content at saturation (0 cm matric potential head), field capacity (both -100 and -330 cm matric potential head), wilting point (-15.000 cm matric potential head), plant available water, and saturated hydraulic conductivity, as well as the Mualem-van Genuchten model parameters of the moisture retention and hydraulic conductivity curve. The minimum set of input properties for the prediction is soil depth and sand, silt and clay content. The effect of including additional information like soil organic carbon content, bulk density, calcium carbonate content, pH and cation exchange capacity were extensively analysed. The PTFs were derived adopting the random forest method. The advantage of the new PTFs is that they i) provide information about prediction uncertainty, ii) are significantly more accurate than the euptfv1, iii) can be applied for more predictor variable combinations than the euptfv1, 32 instead of 5, and iv) are now also derived for the prediction of water content at -100 cm matric potential head and plant available water content.

Ventilation in cities is crucial for the well being of their inhabitants. Therefore, local governments require air ventilation assessments (AVAs) prior to the construction of new buildings. In a standard AVA, however, only neutral stratification is considered, although diabatic and particularly unstable conditions may be observed more frequently in nature. The results presented here indicate significant changes in ventilation within most of the area of Kowloon City, Hong Kong, included in the study. A new definition for calculating ventilation was introduced, and used to compare the influence of buildings on ventilation under conditions of neutral and unstable stratification. The overall ventilation increased due to enhanced vertical mixing. In the vicinity of exposed buildings, however, ventilation was weaker for unstable stratification than for neutral stratification. The influence on ventilation by building parameters, such as the plan area index, was altered when unstable stratification was considered. Consequently, differences in stratification were shown to have marked effects on ventilation estimates, which should be taken into consideration in future AVAs.

In this paper, we present a multi-task model that predicts disparities and confidence levels in deep stereo matching simultaneously. We do this by combining its successful model for each separate task and obtaining a multitask model that can be trained with a proposed loss function. We show the advantages of this model compared to training and predicting disparity and confidence sequentially. This method enables an improvement of 15% to 30% in the area under the curve (AUC) metric when trained parallel rather than sequential. In addition, the effect of weighting the components in the loss function on the stereo and confidence performance is investigated. By improving the confidence estimate, the practicality of stereo estimators for creating distance images is increased.

Several pathotypes of enteric E. coli have been identified. The group represented by Shiga toxin-producing E. coli (STEC) is of particular interest. Raw milk and raw milk products are significant sources of STEC infection in humans; therefore, identifying pathogens at the herd level is crucial for public health. Most national surveillance programs focus solely on raw milk and raw milk cheeses that are ready for retail sale, neglecting the possibility of evaluating the source of contamination directly at the beginning of the dairy chain. In order to assess the viability of new molecular methodologies applied to raw milk filters enabling the identification of the presence of STEC serotypes in milk production and apply the same methods to identify the presence of these pathogens in calf feces we analyzed, through a commercial real-time PCR assay, a total of 290 samples coming from 18 different dairy herds; 88 bulk tank milk (BTM), 104 raw milk filters (RMF) and 98 calves’ feces samples. In total 3.4% of BTM, 41.4% of RMF and 73.4% of calves’ feces tested positive for stx presence, supporting our hypothesis that BTM is not a suitable matrix to assess the STEC presence at herd level, underestimating it. Our conclusion is that the surveillance program needs critical and extensive improvements such as RMF and calves’ feces analysis implementation in order to be more efficient in detecting and preventing STEC infections. The epidemiology of these infections and the characteristics of the pathogen clearly show how a One Health approach will be pivotal to improve our capabilities to control the spread of these infections.

This study analyzed the dynamic spatial and temporal distribution of natural disasters in Traditional Authorities Ngabu and Lundu in Chikwawa District in the Lower Shire Valley. The study assessed the vulnerability of people to disasters, evaluated the value of losses and damages incurred when disasters strike and to locate disaster hotspots. The mixed design that embraces qualitative and quantitative approaches was used. Data collection methods such as in-depth interviews, Focus Group Discussion, documentary review, structured interview and Participatory Geographical Information Systems (P-GIS) were employed. The study revealed that farming with 64%, 37% and 76% done before, during and after disasters respectively, was the main adaptive capacity to floods and drought in T/A Ngabu. In T/A Lundu, community members also valued farming with 58%, 55% and 70% done before, during and after disasters respectively. The study found that Traditional Environmental Knowledge Systems (TEKS) were highly valued in T/As Ngabu with 90% and Lundu 81%. The study also unveiled those disasters led to losses of human lives and livestock and damages to properties, environment and critical infrastructures. However, some community members still remained in the disaster-prone areas for farming, fishing, protecting the chieftaincy and ancestral reasons. The study also showed that CBDRM was highly adopted. However, disasters continued to occur and losses were increasing. Generally, CBDRM could be effective through multisectoral approach and good legal institutional framework. Therefore, the research recommends that further studies similar to this, should use GIS in assessing the efficacy of CBDRM approaches to produce hazard maps that will be used as models for disaster risk reduction in Chikwawa District in the Lower Shire Valley.

Breast Cancer (BC) is the second most common type of cancer worldwide and displays the highest cancer-related mortality among women worldwide. Targeted therapies have revolutionized the way BC has been treated in the last decades improving life expectancies of millions of women. Among the different molecular pathways that have been of interest for the development of targeted therapies are the Cyclin-Dependent Kinases (CDK). CDK inhibitors are a class of molecules that already exist in nature and those belonging to the INK4 protein family specifically inhibit the CDK4/6 proteins. CDK4/6 inhibitors specifically block the transition from the G1 to the S phase of the cell cycle by dephosphorylation of the retinoblastoma tumor suppressor protein. In the past four years CDK4/6 inhibitors palbociclib, ribociclib, and abemaciclib received their first FDA approval for the treatment of Hormone Receptor (HR)-positive and Human Epidermal growth factor Receptor 2 (HER2)-negative breast cancer after showing significant improvements in progression-free survival in the PALOMA-1, MONALEESA-2 and the MONARCH-2 randomized clinical trials, respectively. After the encouraging results from these clinical trials, CDK4/6 inhibitors have also been investigated in the other BC subtypes. In HER2-positive BC, combination of CDK4/6 inhibitors with HER2-targeted therapies showed promise in preclinical studies and their clinical evaluation is ongoing. Moreover, in triple-negative BC, CDK4/6 inhibitors efficacy has been investigated in combination with other targeted therapies or immunotherapies. This review summarizes the molecular background and clinical efficacy of CDK4/6 inhibitors as single agents or in combination with other targeted therapies for the treatment of BC. Future directions of ongoing clinical trials and predictive biomarkers will be further debated.

Background: Diagnostic accuracy of Parkinson’s disease (PD), a synucleinopathy, based on diagnostic criteria is suboptimal. A biomarker for synucleinopathies is pivotal both from a clinical and from a research aspect. CSF a-synuclein has been extensively studied over the past two decades as a candidate biomarker of synucleinopathies. Herein we present data on studies focusing on total, phosphorylated and oligomeric CSF a-synuclein in PD. Methods: Pubmed, Scopus and Web of Science were searched for studies with &gt;10 PD patients and control subjects, with data (mean, SD) on total, phosphorylated or oligomeric a-synuclein. Cohen’s d, as a measure of effect size, was calculated for all a-synuclein forms. Subgroup analysis and meta-regression were performed in an effort to explain between-study heterogeneity. Results: Thirty studies on total, six studies on oligomeric and one study on phosphorylated a-synuclein were included. Total a-synuclein was decreased and oligomeric a-synuclein increased in PD patients vs. controls. Effect size was medium for total and high for oligomeric a-synuclein. A-syn forms provided suboptimal combined sensitivity/specificity for the differentiation of PD from controls. There was significant between-study heterogeneity. PD cohort characteristics (sex, age, disease duration, UPDRS, H&amp;Y) and study characteristics (study design, healthy vs. neurological controls, control for CSF blood contamination, method of a-syn measurement) could not account for between-study heterogeneity. Publication bias was limited. Conclusions: CSF a-synuclein levels lack sufficient accuracy to be used as biomarkers for PD. Standardization of (pre)analytical variables may improve the discriminatory power of a-synuclein forms in the future.

Identifying macroeconomic events that are responsible for dramatic changes of economy is of particular relevance to understand the overall economic dynamics. We introduce an open-source available efficient Python implementation of a Bayesian multi-trend change point analysis which solves significant memory and computing time limitations to extract crisis information from a correlation metric. Therefore, we focus on the recently investigated S&P500 mean market correlation in a period of roughly 20 years that includes the dot-com bubble, the global financial crisis and the Euro crisis. The analysis is performed two-fold: first, in retrospect on the whole dataset and second, in an on-line adaptive manner in pre-crisis segments. The on-line sensitivity horizon is roughly determined to be 80 up to 100 trading days after a crisis onset. A detailed comparison to global economic events supports the interpretation of the mean market correlation as an informative macroeconomic measure by a rather good agreement of change point distributions and major crisis events. Furthermore, the results hint to the importance of the U.S. housing bubble as trigger of the global financial crisis, provide new evidence for the general reasoning of locally (meta)stable economic states and could work as a comparative impact rating of specific economic events.

Three-dimensional transfer functions (3D TFs) are generally assumed to fully describe the transfer behavior of optical topography measuring instruments such as coherence scanning interferometers in the spatial frequency domain. Therefore, 3D TFs are supposed to be independent of the surface under investigation resulting in a clear separation of surface properties and transfer characteristics. In this paper we show that the 3D TF of an interference microscope differs depending on whether the object is specularly reflecting or consists of point scatterers. In addition to the 3D TF of a point scatterer, we will derive an analytical expression for the 3D TF corresponding to specular surfaces and demonstrate this as being most relevant in practical applications of coherence scanning interferometry (CSI). We additionally study the effects of temporal coherence and disclose, that in conventional CSI temporal coherence effects dominate. However, narrowband light sources are advantageous if high spatial frequency components of weak phase objects are to be resolved, whereas for low-frequency phase objects of higher amplitude the temporal coherence is less affecting. Finally, we present an approach that explains the different transfer characteristics of coherence peak and phase detection in CSI signal analysis.

One of the key areas of the International Renewable Energy Agency’s (IRENA) programme of work is the analysis of renewable technology costs and performance and the dissemination of these results to as wide an audience as possible. In addition to analysis, IRENA seeks to engage a broad range of stakeholders in the context of this work through the Renewable Costing Alliance. The Costing Alliance brings together companies, industry association, governments and researchers to share, confidentially, data for real-world renewable energy project cost and performance, helping to build further on IRENA’s costing work to date. In this context the authors analyse the current cost differentials and cost reduction potentials for solar PV in Japan compared to best practice levels and identify the reasons for higher costs in Japan and how to reduce them. This study analyses the current installed cost differentials for utility-scale, commercial and residential rooftop solar PV systems. In addition to identifying the reasons for the cost differentials, potential policy recommendations to reduce the cost differential are identified.

Objective: To examine the dose-response relationship between average daily temperature and sunlight hours with daily steps across a 35-week period in school-aged children, and to evaluate whether there were differences by sex. Methods: We conducted a follow-up study involving 655 children (50.8% girls, mean age 10.45 ± 0.95) from six public primary schools in Cuenca, Spain. We measured daily steps using Xiaomi Mi Band 3 Smart Bracelets from October 2022 to June 2023 (over 35 weeks). We collected daily average temperature from the local weather station in Cuenca and sunlight hours during the same period. We used ANCOVA models and LOESS regression to examine the dose-response relationship between average daily temperature and daily hours of sunlight with daily steps. Additionally, we performed a multiple linear regression model. Results: Our findings revealed significant variations in daily steps across the 35 weeks. The relationship between environmental factors and daily steps was non-linear, in both girls and boys. The optimal values for higher activity levels were an average temperature of 14°C and 13 hours of sunlight. Furthermore, a 1 ºC increase in temperature was associated with an increase of 74 ± 130 steps/day, while an increase of one hour of sunlight was associated with an increase of 315 ± 237 steps/day. However, sunlight hours may act as a moderating factor. Conclusion: Our study showed a non-linear association between t average daily temperature and sunlight hours with daily steps over a 35-week period. Additional strategies may be necessary to encourage increased physical activity during periods of extreme temperatures or sunlight exposure.

Objective: To investigate whether impaired plantar cutaneous vibration perception contributes to axial motor symptoms in Parkinson’s disease (PD) and whether anti-parkinsonian medication and subthalamic nucleus deep brain stimulation (STN-DBS), show different effects. Methods: Three groups were tested: PD patients on medication (PD-MED), PD patients on medication and additional STN-DBS (PD-MED–DBS), and healthy subjects (HS) as reference. Motor performance was analyzed using a pressure distribution platform. Plantar cutaneous vibration perception thresholds (VPT) were investigated using a customized vibration exciter at 30 Hz. Results: Motor performance of PD-MED and PD-MED–DBS was characterized by greater postural sway, smaller limits of stability ranges, and slower gait, due to shorter strides, fewer steps per minute, and broader stride widths compared to HS. Comparing patient groups, PD-MED–DBS showed better overall motor performance than PD-MED, particularly for the functional limits of stability and gait. VPTs were significantly higher for PD-MED compared to HS, which suggests impaired plantar cutaneous vibration perception in PD. However, PD-MED–DBS showed less impaired cutaneous vibration perception than PD-MED. Conclusion: PD patients suffer from poor motor performance compared to healthy subjects. Anti-parkinsonian medication in conjunction with STN-DBS seems to be superior for normalizing axial motor symptoms compared to medication alone. Plantar cutaneous vibration perception is impaired in PD patients, whereas anti-parkinsonian medication together with STN-DBS is superior for normalizing tactile cutaneous perception compared to medication alone. Consequently, based on our results and the findings of the literature impaired plantar cutaneous vibration perception might contribute to axial motor symptoms in PD.

Electromobility promises to efficiently mitigate consequences of increasing traffic volume and its accompanied greenhouse gas emissions. On an individual level, electrified bikes allow emission free electrified mobility at moderate costs and consequently their stock has increased significantly in recent years. This simultaneously increases the demand for spare parts, which are often manufacturer or application-specific, and due to many variants, challenging to provide for the market. This article evaluates powder-based and extrusion-based metal additive manufacturing of a typical electrified bike component to demonstrate an alternative spare parts supply. The investigation demonstrates how these parts can be additively manufactured function equivalent and with sufficient mechanical properties, also taking economical aspects into account. Furthermore, the needed resources and related environmental consequences for metal-based additive manufacturing spare-part production are compared for both process routes. The results show that both routes are capable of producing spare-parts at comparatively same mechanical performance and resource costs, while needed resources such as energy, gases and manufacturing time are significantly lower for powder-based, respectively machine costs for extrusion-based additive manufacturing. Therefore, additive manufacturing offers a promising opportunity to produce parts in small quantities resource efficient and rapidly.

The adverse relationship between viral hepatitis and pregnancy in developing countries was seen as a reflection of retrospective biased hospital-based data collection by the West. However, the discovery of HEV from an epidemic of non-A, non-B hepatitis in Kashmir and documenting increased incidence and severity of hepatitis E in pregnancy from a house-to-house survey unmasked the unholy alliance. Among the family of HEV’s, genotype (gt)-1, with a unique ORF4-encoded protein enhancing viral polymerase activity and viral replication, is the sole HEV that shows this adverse relationship. The epidemics caused by HEV-gt1 and not by HEV-gt2 show adverse relationship with pregnancy. The pathogenesis of the unholy alliance is complex and at present not well understood. Possibly multiple factors play a role in causing severe liver disease in the mother including: infection, replication and damage to the maternal-foetal interface by HEV-gt1; vertical transmission of HEV to foetus causing severe foetal/neonatal hepatitis; and combined viral and hormone related immune dysfunction of diverse nature in the mother promoting viral replication. Management is multidisciplinary and needs a close watch for the development and management of ALF. Preliminary data suggest beneficial maternal outcomes by early termination of pregnancy in patients with lower grades of encephalopathy.

Abstract: Since the establishment of multiparty democracy in the 1990s, Malawi has experienced significant political shifts, with elections playing a crucial role in shaping the political landscape. However, there is a lack of comprehensive understanding of the spatio-temporal dynamics of election results, especially regarding voting patterns and their effects on electoral outcomes. This gap hinders political parties, politicians, and electoral stakeholders in effectively managing regional and temporal changes in voting behaviors. Geographic Information Systems (GIS) are underutilized in Malawi for studying geo-graphical and temporal election data. This study utilized GIS to analyze the spatial pat-terns of election results in Malawi since the advent of multiparty democracy. By collecting geographic data on election outcomes, including vote counts, candidate performance, voter turnout, and other relevant data, the study examined how the geographic distribution of votes impacts electoral results. GIS techniques such as spatial analysis, mapping, and spatial statistics were employed to assess the data and create maps illustrating spatial patterns in Malawi's election outcomes. The study revealed that voting patterns in Malawi are significantly influenced by regional lines. These insights can inform political campaigns, voter mobilization efforts, and strategies for electoral reform.

Two novel dsRNA mycoviruses were found in different isolates of Diplodia fraxini, NW FVA 1581 and NW FVA 1706, which were isolated from a root, associated with stem collar necrosis of Fraxinus excelsior L. Both mycelia are infected by a novel fusagravirus, which was named Diplodia fraxini fusagravirus 1 (DfFV1), and isolate NW FVA 1706 is additionally infected by a novel partitivirus, which was denominated as Diplodia fraxini partitivirus 1 (DfPV1). The one-segmented, bicistronic genome of DfFV1 is composed of about 8,500 bp. Their ORFs are connected by a 1 slippery heptamer sequence and the 3’ terminal ORF is coding for the viral RdRp. The genome of DfPV1 is composed of three, monocistronic dsRNA segments ranging from 1,755 bp (dsRNA 1) over 1,588 bp (dsRNA 2) to 1,233 bp (dsRNA 3). Based on genome organization and phylogenetic positions, DfFV1 was assigned to the proposed family of “Fusagraviridae” and DfPV1 to the genus Gammapartitivirus within the family of Partitiviridae. Ultra-structural analysis showed that polysomal structures were stabilized in the single infection and none of these structures could be isolated in the double infection. It is assumed that DfFV1 has an opportunistic lifestyle, being either protected by ribosomes or by transcapsidation from particles of DfPV1.

According to the World Health Organization, approximately 20 million people worldwide are infected annually with the hepatitis E virus (HEV). There are 4 main genotypes of HEV. Genotype 1 and genotype 2 are common in developing countries and are transmitted by contaminated water from a fecal-oral route. Genotype 3 and genotype 4 are common in developed countries and can lead to occasional transmission to humans by undercooked meat. Hepatitis E virus 1 and HEV3 can lead to fulminant hepatitis, and HEV3 can lead to chronic hepatitis and cirrhosis in immunocompromised patients. The majority of patients with HEV infection are asymptomatic and usually have spontaneous viral clearance without treatment. However, infection in immunocompromised individuals can lead to chronic HEV infection. Both acute and chronic HEV infections can have extrahepatic manifestations. No specific treatment is required for acute HEV infection, no treatment has been approved in chronic infection and no HEV vaccine has been approved by the (United States) Food and Drug Administration. This review focuses on the molecular virology (HEV life cycle, genotypes, model systems, zoonosis), pathogenesis, clinical manifestation, and treatment of chronic HEV infection, especially in immunocompromised patients, to provide clinicians a better understanding of the global distribution of these infections and the significant effect they can have on immunocompromised patients.

Background and Objectives: In recent years Electronic scooters (E-Scooters) have gained popularity, whether for private use or as a publicly available transportation method. With introduction of these vehicles, reports of E-Scooter related accidents have surged, sparking a public debate and concern. Aim of this study was to analyse epidemiological data, characteristics and severity of traumatic brain injury (TBI) related to E-Scooter accidents. Materials and Methods: This retrospective case series evaluated 28 patients who were admitted to three largest neurosurgery clinics in Riga, Latvia between time period from April to October in two separate years – 2022 and 2023 after an E-Scooter related accident. Data were collected on patient demographics, time of the accident, alcohol consumption, helmet use, type of TBI, other related injuries, treatment and assessment at discharge. Results: A total of 28 patients were admitted with TBI related to E-Scooter use, with median age 30 years (Q1-Q3, 20.25-37.25), four individuals under age of 18, majority (64%) were male. In 23 cases the injury mechanism was fall, in 5 cases collision. None were wearing a helmet at time of injury. Alcohol intoxication was evident in over half of the patients (51.5%), with severe intoxication (&gt;1.2ppm) in 75% cases among them. Neurological symptoms upon admission were noted in 50% of cases. All patients had intracranial trauma - 50% brain contusions, 43% traumatic subdural hematoma, almost 30% - epidural hematoma. Craniofacial fractures were evident in 71% of cases, fractures in other parts of body in 3 patients. 6 patients required emergency neurosurgical intervention. Neurological complications were noted in 2 patients, 1 patient died. Conclusions: E-Scooter related accidents result in a significant number of brain and other associated injuries, with notable frequency linked to alcohol influence and lack of helmet use. Prevention campaigns to raise awareness of potential risks and implementation of more strict regulations should be done.

Background: The thoracolumbar fascia (TLF) is thought to play a role in the development of LBP, but it is not yet clear which factor of TLF changes is a cause and which is an effect. Therefore, some studies used the cross-correlation function (CCR) to reveal time-dependent relationships between biomechanical and neuromotor factors. Methods: Ten patients with acute low back pain (aLBP) were matched to healthy controls. Simultaneous recording of surface electromyography (sEMG) of the erector spinae muscle (ES) and dynamic ultrasound (US) images of TLF deformation were performed during trunk extension. CCR functions and Granger causality were used to describe the relationship between the two measures. Results: CCR time lags were significant higher in the aLBP group (p = 0.04). Granger causality (GC) showed a direct effect of TLF deformation on ES activation only in the aLBP group (p &lt; 0.03). Conclusions: The results suggest that in aLBP, ES activity is significantly affected by TLF, whereas this relation-ship is completely random in healthy subjects studied with CCR and GC comparisons of dynamic US imaging and sEMG data signals. Fascia-related disturbances in neuromotor control, particularly due to altered muscle spindle functions, are suspected as a possible mechanism behind this.

In recent years, many libraries and archives have started digitizing their collections thus making maps by Indigenous peoples more easily available for scholars to study. While a number of these maps were discussed by G. Malcolm Lewis in the History of Cartography series (volume 2, book 3, Chapter 4: 1984), more have since been found and disseminated. These maps are critical in understanding the historic and current land tenure of Indigenous groups. Further, Indigenous claims to land can be seen in their connections via toponymy. European concepts of territory and political boundaries did not coincide with First Nation/American Indian views resulting in the mistaken view that Natives did not have formal concepts of their territories. Further, Tribes/First Nations with cross-border territory have special jurisdictional problems. This paper will illustrate how many Native residents were very spatially cognizant of their own lands, as well as neighboring nations’ lands, overlaps between groups, hunting territories, populations, and trade networks. Currently, the Sinixt First Nation provides a perfect example of how an Aboriginal people are inputting and using a GIS representation of their territory with proper toponymy and use areas.

Environmental and economic needs drive the increased penetration of intermittent renewable energy in electricity grids, enhancing uncertainty in market conditions prediction and network constraints. Thereafter, the importance of energy systems with flexible dispatch is reinforced, ensuring energy storage as an essential asset for these systems to be able to balance production and demand. In order to do so, such systems should participate in whole-sale energy markets, enabling competition among all players, including conventional power plants. Consequently, an effective dispatch schedule considering market and resource uncertainties is crucial. In this context, an innovative dispatch optimization strategy for schedule planning of renewable systems with storage is presented. Based on an optimization algorithm combined with a machine learning approach, the proposed method develops a financial optimum schedule with the incorporation of uncertainty information. Simulations performed with a concentrated solar power plant model following the proposed optimization strategy demonstrate promising financial improvement with a dynamic and intuitive dispatch planning method, emphasizing the importance of uncertainty treatment on the enhanced quality of renewable systems scheduling.

As customer demand for green products increases in the digital economic era, this study analyses the green innovation of the e-tailer and supplier in drop shipping models. Moreover, drop shipping e-tailers and suppliers with a drop shipping option need to make choices regarding whether to provide green or normal products to the market. When a supplier with a drop shipping option produces green products, more fees may be invested on the production of green products than on normal products. The drop shipping e-tailers and suppliers with a drop shipping option can also choose to sell normal products at a low cost, as before. This study designs four models of drop shipping e-teilers and suppliers with a drop shipping option under different choices, analyzes their operational process in drop shipping models, and investigates five theorems. The optimal pricings decisions and green degree of drop shipping e-tailers and suppliers with a drop shipping option were evaluated in this study. The impacts of the green innovation factor, green elasticity coefficient, manufacturing and distribution costs on the drop shipping e-tailers and suppliers with a drop shipping option, and the effect of other environmental parameters on the green degree of green products are also analyzed through computer simulation. The findings of the simulation analysis provide valuable guidance for e-tailers and suppliers with green innovation in drop shipping models and offer important academic and practical implications for e-commerce and the digital economy.

Whistler mode waves play a major role in regulating the lifetime of trapped electrons in the Earth's radiation belts. Specifically, whistler mode hiss waves are one of the mechanisms that maintains the slot region between the inner and outer radiation belts. The generation mechanism of hiss is a topic still under debate with at least three prominent theories present in the literature. Lightning generated whistlers in their ducted or non-ducted modes, are considered to be one of the possible sources of hiss. We present a study of new observations from the Radio Receiver Instrument (RRI) on the Enhanced Polar Outflow Probe (ePOP: currently known as SWARM-E). RRI consists of two orthogonal dipole antennas, which enables polarization measurements, when the satellite boresight is parallel to the geomagnetic field. Here we present 75 passes of ePOP - RRI from 2014 - 2018, in which lightning whistlers and hiss waves were observed. In more than 50% of those passes hiss is found to co-exist with the lightning whistlers. Moreover, the whistler observations are correlated with observations of wave power at the lower-hybrid resonance. The observations and a whistler mode ray-tracing study suggest that multiple-hop lightning induced whistlers can be a source of hiss and plasma instabilities in the magnetosphere.

The relentless challenges posed by the COVID-19 pandemic have placed immense pressure on densely populated regions, such as Hong Kong, particularly in the context of an aging population. The burgeoning demand for healthcare services has necessitated the optimization of resource al-location within healthcare systems. This research presents an innovative analytical queueing model specifically tailored to address the intricate gridlock dynamics prevalent in healthcare systems, with a focused application in the challenging landscape of COVID-19 management. Hong Kong, like numerous other regions, has experienced a demo-graphic transition leading to heightened healthcare demands. Traditional methodologies for scrutinizing gridlock issues in healthcare settings, including simulation models, often prove suboptimal within the context of sophisticated optimization frameworks. This study, however, delves into analytical queueing models, offering a more efficient and effective approach. These models have been underexplored, primarily due to the intricacies involved in modeling gridlock propagation within restricted capacity, a critical concern magnified by the COVID-19 pandemic. The novel Queueing Model introduced in this research incorporates the maintenance of queue capacities and topological aspects as exogenous parameters, rendering it exceptionally adaptable for diverse gridlock-related applications. This adaptability is especially pertinent to healthcare management during the COVID-19 crisis. The model meticulously integrates the concept of gridlock, furnishing a comprehensive comprehension of its origins and repercussions. Validation of this model involves rigorous comparison with established methodologies, exact results, and simulation data, consistently high-lighting its versatility and precision. By applying the model to healthcare management, we scrutinize the dynamics of patient flow within a Hong Kong hospital, placing specific emphasis on the critical issue of bed blockage, further exacerbated by the COVID-19 pandemic. The model's gridlock decomposition unearths the nuanced impact of bed blockage on distinct hospital units, addressing the imperative requirement for quantifying in-patient bed blockage within healthcare systems during a pandemic.

Recently, the concept of participatory democracy developed in the early 1970s has come back into fashion to revitalize the public involvement in political decision-making processes. Public par-ticipation in forest policy has been fully conceptualized by the scientific community in the late 1990s and early 2000s, but in many contexts the practical application remains unfulfilled. The aim of this study is to identify and analyze the participatory techniques used in literature to increase knowledge and facilitate its transferability into forest policies and strategies. A literature review was carried out to offer an overview of the participatory techniques adopted in the deci-sion-making process. At the end of literature review, 25 participatory techniques were identified based on over 2,000 publications. Afterwards, the participatory techniques were assessed using seven indicators (degree of participation, type and number of participants, time scale, cost, po-tential influence on policy). The results showed that the type of actors involved in the participa-tory technique is a key variable for the complexity and usefulness of the process, while the number of participants influences how information is disseminated. The Principal Component Analysis highlighted that the participatory techniques can be divided in three groups: the first group includes those techniques with a high degree of participation and a contextual high po-tential influence on policies, the second one includes techniques with a costs in terms of re-sources, while the third one consists of those with a large number of participants and reduced time requirements.

For some persistent pollutants, such as recalcitrant pesticides, the polluted water (urban, agricultural and/or industrial) treated by conventional wastewater treatment plants is in some cases insufficient to achieve the legally required level of purity. This issue is of particular concern in areas where low rainfall does not provide sufficient water resources to meet the needs of agriculture, requiring increased reuse of water from wastewater treatment plants. In this context, Advanced Oxidation Processes (AOPs) hold great promise for the removal of organic pollutants. This study first evaluates the effectiveness of UV/S2O8= compared to heterogeneous photocatalysis using UV/TiO2 processes on the degradation of two commonly used herbicides (terbutylazine and isoproturon) in aqueous solutions using a photoreactor. In addition. the effect of UV wavelength on the degradation efficiency of both herbicides was investigated. Although degradation rate was higher under UV-254/S2O8= nm than under UV-365/S2O8= nm, complete degradation of the herbicides (0.2 mg L-1) was achieved within 30 min under UV-366 nm using a Na2S2O8 dosage of 250 mg L-1 in the absence of inorganic anions. To assess the impact of water matrix, the individual and combined effects of sulphate, bicarbonate and chloride were evaluated. They can react with hydroxyl and sulphate radicals formed during AOPs to form new radicals with a lower redox potential. The results showed negligible effects of sulphate, while the combination of bicarbonate and chloride seemed to be the key for the decrease in herbicide removal efficiency found when working with complex matrices. Finally, the main intermediates detected during the photodegradation process were identified and the likely pathways are proposed and discussed.

In this study, a critical review was carried out using the Web of ScienceTM Core Collection database to analyse the scientific literature published to date to identify lines of research and future perspectives on the presence of chemical pollutants in beer brewing. Beer is one of the world's most popular drinks and the most consumed alcoholic beverage. However, a widespread challenge with potential implications for human and animal health is the presence of physical, chemical and/or microbiological contaminants in beer. Biogenic amines, heavy metals, mycotoxins, nitrosamines, pesticides, acrylamide, phthalates, bisphenols, microplastics and, to a lesser extent, hydrocarbons (aliphatic chlorinated and polycyclic aromatic), carbonyls, furan-derivatives, polychlorinated biphenyls and trihalomethanes are the main chemical pollutants found during the beer brewing process. Pollution sources include raw materials, technological process steps, the brewery environment and packaging materials. Different chemical pollutants have been found during the beer brewing process, from barley to beer. Brewing steps such as steeping, kilning, mashing, boiling, fermentation and clarification are critical in reducing the levels of many of these pollutants. As a result, their residual levels are usually below the maximum levels allowed by international regulations.

Partial Information Decompositions (PIDs) aim to categorize how a set of source variables provide information about a target variable redundantly, uniquely, or synergetically. The original proposal for such an analysis used a lattice-based approach and gained significant attention. However, finding a suitable underlying decomposition measure is still an open research question, even at an arbitrary number of discrete random variables. This work proposes a solution to this case with a non-negative PID that satisfies an inclusion-exclusion relation for any f-information measure. The decomposition is constructed from a pointwise perspective of the target variable to take advantage of the equivalence between the Blackwell and zonogon order in this setting. The zonogons correspond to the Neyman-Pearson region for an indicator variable of one target state and f-information is the expected value of quantifying its boundary. We prove that the decomposition satisfies the axioms of the original decomposition framework and guarantees non-negative partial information results. We highlight that our decomposition behaves differently depending on the used information measure, which can be utilized for different applications. We additionally show how our proposal can be used to obtain a non-negative decomposition of Rényi-information at a transformed inclusion-exclusion relation, and for tracing partial information flows through Markov chains.

Eucalyptus, a therapeutic plant mentioned in the ancient Algerian pharmacopeia, specifically two species belonging to the Myrtaceae family - E. radiata and E. cinerea, were investigated in this study for their antibacterial, antioxidant, and anti-inflammatory properties. The study used aqueous extracts (AE) obtained from these plants, and the extraction yields were found to be dif-ferent. The in vitro antibacterial activity was evaluated using a disc diffusion assay against three typical bacterial strains. The results showed that E. radiata EAq was effective against all three strains, while E. cinerea EAq was only effective against E. coli. Both extracts displayed significant antioxidant activity compared to BHT. The anti-inflammatory impact was evaluated using a pro-tein (BSA) inhibition denaturation test. The E. radiata extract was found to inhibit inflammation by 75% at a concentration of 250 g/ml, significantly higher than the placebo. Ellagic acid, a pri-mary phytochemical found in the extracts, demonstrated noteworthy toxic and pharmacokinetic characteristics and a maximum binding energy of -7.53 kcal/mol for its anti-TyrRS activity in sili-co. The study suggests that the extracts and their primary phytochemicals could enhance the effi-cacy of antibiotics, antioxidants, and non-steroidal anti-inflammatory drugs (NSAIDs). As phar-maceutical engineering experts, we believe this research contributes to developing natural-based drugs with potential therapeutic benefits.

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to an infection. Recent in-vitro studies have investigated the effects of CytoSorb hemoadsorption on endothelial function in sepsis showing a reduction in markers of endothelial dysfunction, but to this day there is a lack of clinical studies showing whether this approach could actually positively influence the disturbed vascular barrier function in septic conditions. We analyzed the data on administered fluid volumes and catecholamines to determine the potential benefit of CytoSorb hemoadsorption therapy on endothelial function in a clinical scenario. We performed a retrospective analysis of 124 septic shock patients who had undergone adjunctive treatment with CytoSorb hemadsorption therapy. We collected volume requirements, and calculated the volume balance within different time periods to obtain an assumption on the stability of the vascular barrier. We also calculated catecholamine requirements. With regard to the entire study cohort our findings revealed a significant reduction in fluid balance at 72 hours (T72) compared to both baseline (T0) and the 24-hour mark (T24). Fluid balances from T72 – T0 were significantly lower in hospital survivors compared to non-survivors. Patients who received a second catecholamine had a significantly lower in-hospital mortality. Our findings showed that use of hemoadsorption therapy results in a reduced positive fluid balance paralleled by reductions in vasopressor needs suggesting a positive effect on endothelial integrity. These results, derived from a large cohort of patients, provide valuable insights that may greatly improve our understanding of the multiple effects of hemoadsorption treatment in septic shock patients.

Water hyacinth (Eichhornia crassipes) is an invasive species that has modified ecosystem functioning in the Sacramento-San Joaquin Delta (Delta), California, USA. Studies in lakes and rivers have shown that water hyacinth alters water quality. In tidal systems, such as the Delta, water moves back and forth through the water hyacinth patch so water quality directly outside the patch in either direction is likely to be impacted. In this study, we asked whether the presence or treatment of water hyacinth with herbicides resulted in changes in water quality in this tidal system. We combined existing datasets that were originally collected for permit compliance and long-term regional monitoring into a dataset that we analyzed with a before-after control-impact (BACI) framework. This approach allowed us to describe effects of presence and treatment of water hyacinth, while accounting for seasonal patterns in water quality. We found that although effects of treatment were not detectable when compared with water immediately upstream, dissolved oxygen and turbidity became more similar to regional water quality averages after treatment. Temperature became less similar to the regional average after treatment, but the magnitude of the change was small. Taken together, these results suggest that tidal hydrology exports the effects of water hyacinth upstream, just as river flow is known to transport the effects downstream, creating a buffer of altered water chemistry around patches. It also suggests that although water hyacinth has an effect on dissolved oxygen and turbidity, these parameters recover to regional averages after treatment.

Mixed plastic packaging waste sorting residues (MPO323) were treated by thermal pyrolysis to utilize pyrolysis oil and char. The pyrolysis oil was found to contain aromatic and aliphatic hydrocarbons. Chlorine and bromine contents were up to 40,000 mg/kg and 200 mg/kg, respectively. Additionally, other elements like sulfur, phosphorous, iron, aluminum, and lead were detected, which can be interpreted as impurities regarding the utilization of the oils by means of chemical recycling. The pyrolysis char showed high contents of potentially active species like silicon, calcium, aluminum, iron, and others. To enhance the content of aromatic hydrocarbons and to reduce the level of contaminants, the pyrolysis oil was reformed with the corresponding pyrolysis char to act as an active material in a fixed bed. The temperature of the reactor and the flow rate of the pyrolysis oil feed were varied to gain insights on cracking and reforming reactions as well as on the performance with regard to decontamination.

Smartwatches are one of the most relevant fitness trends of the past two decades, and they collect increasing amounts of health and movement data. The accuracy of these data may be questionable and requires further investigation. Therefore, the aim of the present study is to validate smartwatches for use in triathlon training. Ten different smartwatches were tested for accuracy in measuring heart rate, distance (via global navigation satellite systems, GNSS), swim stroke rates and the number of swim laps in a 50 m Olympic-size pool. The optical heart rate measurement function of each smartwatch was compared to that of a chest strap. Thirty participants (15 females, 15 males) ran five 3-minute intervals on a motorised treadmill to evaluate the accuracy of the heart rate measurements. Moreover, for each smartwatch, running und cycling distance tracking was tested over six runs of 4,000 m on a 400 m tartan stadium track, six hilly outdoor runs over 3.4 km, and four repetitions of a 36.8 km road bike course, respectively. Three swimming protocols ranging from 200 m to 400 m were performed in triplicate in a 50 m Olympic-size pool, evaluating tracked distance and detected number of strokes. The mean absolute percentage errors (MAPEs) for the average heart rate measurements varied between 3.1% and 8.3%, with the coefficient of determination ranging from 0.22 to 0.79. MAPE results ranged from 0.8% to 12.1% for the 4,000 m run on the 400 m track, from 0.2% to 7.5% for the 3.4 km outdoor run, and from 0.0% to 4.2% for the 36.8 km bike ride. For the swimming tests, in contrast, the deviations from the true distance varied greatly, starting at a 0.0% MAPE for the 400 m freestyle and reaching 91.7% for the 200 m medley with style changes every 25 m. In summary, for some of the smartwatches, the measurement results deviated substantially from the true values. Measurements taken while road cycling over longer distances with only a few curves were in relative terms more accurate than for outdoor runs and even more accurate than for the 400 m track. In the swimming exercises, the accuracy of the measured distances was severely deteriorated by the medley changes among the majority of the smartwatches. Altogether, the results of this study should help in assessing the accuracy and thus suitability of smartwatches for general triathlon training.

Smartwatches provide technology-based assessments in Parkinson’s disease (PD). We present results for sensor validation and disease classification via Machine Learning (ML). A comparison setup was designed with two different series of Apple smartwatches, one Nanometrics seismometer and a high-precision shaker to measure tremor-like amplitudes and frequencies. Clinical smartwatch measurements were acquired from a prospective study including 450 participants with PD, differential diagnoses (DD) and healthy participants. All participants wore two smartwatches and within a 15-min examination. Symptoms and medical history were captured on the paired smartphone. A broad range of different ML classifiers were cross-validated. Amplitude and frequency differences between smartwatches and the seismometer were under the level of clinical significance. The most advanced task of distinguishing PD vs DD was evaluated with 74,1% balanced accuracy, 86,5% precision and 90,5% recall by Multilayer Perceptrons. Deep Learning architectures significantly underperformed in all classification tasks. Smartwatches are capable of capturing subtle-tremor signs with low noise. This study provided the largest PD sample size of two-hand smartwatch measurements and our preliminary ML-evaluation shows that such a system provides powerful means for diagnosis classification and new digital biomarkers but it remains challenging for distinguishing similar disorders.

The rapid growth of the global wearable technologies market is projected to reach $61.30 billion by 2030 which reflects a shift towards personalised health monitoring embedded in everyday activities. This paper explores the potential of embroidered interdigitated transducer (IDT)-based sensors for non-invasive, continuous monitoring of human biomarkers, particularly glucose levels, in human sweat. The study employs innovative embroidery techniques to create flexible fabric-based sensors with gold-coated IDTs. Experimental results demonstrate the sensor’s capability to detect water droplets and glucose concentrations, showcasing promising applications for health monitoring. The embroidered IDT-based sensors offer a unique approach for seamless integration into clothing, paving the way for personalised, continuous health data capture.

The background of this research is the environmental sustainability assessments in the aviation ecosystem, particularly concerning airports, are getting significant attention from the industry, regulators, and researchers. A standardized and comprehensive approach is essential for uniformly addressing the global impacts of these assessments across the industry. The main objective of this study is to develop a unique framework that encompasses the requirements of aviation regulators as well as industry and academic metrics, aiming for a standardized approach to environmental sustainability assessments at airports. The methodology used the Sum of Ranking Method to evaluate each environmental indicator precisely. It was applied to five airports globally, providing a diverse testing ground to assess the proposed metrics’ applicability and effectiveness and validate the framework. The results showed that applying the framework across these varied airport environments demonstrated its viability and effectiveness, indicating that it can be successfully applied to different airport realities. The conclusion shows that the developed framework can be successfully applied globally, suggesting that it can be a valid method for international adoption in environmental airport sustainability analysis, offering a standardized approach that could be accepted and utilized worldwide.

Megaselia scalaris and Senotainia tricuspis are two parasitoid flies of the honeybee Apis mellifera and are known to infest apiaries of different European and Mediterranean countries. However, their prevalence is still little known and no systematic control of their presence and countermeasures are currently adopted. To achieve a better knowledge about their distribution in apiaries, quantitative PCR (qPCR) based methods for their rapid detection directly in hive matrices were developed in this study. These were applied to samples of adult honeybees and hive debris collected in the summer season in Central Italy and Kosovo. In total 16 samples per type per region were analyzed. Both flies were detected in the two geographical contexts but more frequently in Central Italy. The positive apiaries in Central Italy were re-sampled one year later by capturing viable honeybees and isolating emerging flies after differentiation into adults. These were genotyped by sequencing regions of the mitochondrial cytochrome oxidase subunit I gene COI for M. scalaris and cytochrome B gene cytB for S. tricuspis amplified with specific primers designed in this study. Different genotypes of M. scalaris were detected and these were related to biotypes from distant nations. Some fly isolates were shown to harbor DNA or RNA of honeybee microbial pathogens. Results suggested to implement efficient control against these parasites in apiaries to limit their detrimental effects. The qPCR tests that have been developed can facilitate larger screening studies and early detection.

This study analyzes the eating behavior and factors associated with the presence of disordered eating attitudes in patients undergoing bariatric surgery. It is a cross-sectional, descriptive, and analytical study conducted at a hospital in the Amazon region of Brazil. The Disordered Eating Attitude Scale reduced version (DEAS-s) was used to assess the risk of eating disorders and the Three-Factor Eating Questionnaire (TFEQ-R21) to characterize eating behavior. A total of 205 patients participated, with a mean age of 37.5 ± 8.6 years, the majority being female (93.7%; p&lt;0.001), the mean BMI was 45.3±6.7 kg/m2. It was found that cognitive restraint had the highest mean (52.6±19.9; p&lt;0.001). As for the DEAS-s, the question with the highest mean was "spending one or more days without eating or consuming only liquids to lose weight" (2.80±1.99). Female participants had a higher score in the emotional eating (p=0.016). Disordered eating attitudes showed a correlation with emotional eating and uncontrolled eating. These results suggest that candidates for bariatric surgery may have susceptibility to eating disorders. The importance of a multidisciplinary team in monitoring during the preoperative period is highlighted.

Laboratory medicine is a digital science. Every large hospital produces a wealth of data each day - from simple numerical results from e.g. sodium measurements to highly complex output of “-omics” analyses, as well as quality control results and meta-data. Processing, connecting, storing, and ordering extensive parts of these individual data requires Big Data techniques. Whereas novel technologies such as artificial intelligence and machine learning have exciting application for the augmentation of laboratory medicine, the Big Data concept remains fundamental for any sophisticated data analysis in large databases. To make laboratory medicine data optimally usable for clinical and research purposes, they need to be FAIR: findable, accessible, interoperable, and reusable. This can be achieved for example by automated recording, connection of devices, efficient ETL (Extract, Transform, Load) processes, careful data governance, and modern data security solutions. Enriched with clinical data, laboratory medicine data allow a gain in pathophysiological insights, can improve patient care, or they can be used to develop reference intervals for diagnostic purposes. Nevertheless, Big Data in laboratory medicine do not come without challenges: The growing number of analyses and data derived from them is a demanding task to be taken care of. Laboratory medicine experts are and will be needed to drive this development, take an active role in the ongoing digitalization, and provide guidance for their clinical colleagues engaging with the laboratory data in research.

The following paper describes an economical, multiple model predictive control (EMMPC) for an air conditioning system of a confectionery manufacturer in Germany. The application consists of a packaging hall for chocolate bars, in which a new local conveyor belt air conditioning system is used and thus the temperature and humidity limits in the hall can be significantly extended. The EMMPC calculates the optimum energy or cost humidity and temperature set points in the hall. For this purpose, time-discrete state space models and an economic objective function with which it is possible to react to flexible electricity prices in a cost-optimised manner are created. A possible future electricity price model for Germany with a flexible EEG levy was used as a flexible electricity price. The flexibility potential is determined by variable temperature and humidity limits in the hall, which are oriented towards the comfort field for easily working persons, and the building mass. The building mass of the created room model is used as a thermal energy store. Considering electricity price and weather forecasts as well as internal, production plan-dependent load forecasts, the model predictive controller directly controls the heating and cooling register and the humidifier of the air conditioning system.

Since fine powders tend strongly to adhesion and agglomeration, their processing with conventional methods is difficult or impossible. Typically, in order to enable the handling of fine powders, chemicals are added to increase the flowability and reduce adhesion. This contribution shows that instead of additives also vibrations can be used to increase the flowability, to reduce adhesion and cohesion, and thus to enable or improve processes such as precision dosing, mixing, and transport of very fine powders. The methods for manipulating powder properties are described in detail and prototypes for experimental studies are presented. It is shown that the handling of fine powders can be improved by using low-frequency, high-frequency or a combination of low- and high-frequency vibration.