The global increase of road infrastructure and its impact on the environment requires serious attention to develop sustainable and environmentally friendly road materials. One group of those materials is produced by using bitumen emulsion. However, there are still scientific and technical obstacles standing against its regular application. The bitumen emulsion formulation process and compositional optimization are subjected to a high number of degrees of freedom. Consequently, obtaining the desired product is mostly based on a series of random and tedious trials because of the enormous number of tests to be carried out. The current review of the physicochemical formulation may indeed be extensively used in helping to reduce the number of unnecessary experimentations as well as discuss the vital aspects in the bitumen emulsion production process. Among these, emulsion stability, viscosity, droplet size (and distribution), bitumen emulsion chemistry, the function of the emulsion components, surfactant type, acids or alkalis, and additives are all discussed and used to define the emulsion's physical properties and reactivity. Besides, current developments in the mechanisms of breaking and setting processes are also summarized. It is discussed how emulsions are graded based on their reactivity, particle charge, and physical features. Two emulsification techniques are outlined namely the colloid mill method and the High Internal Phase Ratio (HIPR) method. Furthermore, some emulsion formulation tools/theories were identified and are explained. In that way, optimized formulations can be used to offer a practical guide for bitumen emulsion manufacturers when trying to formulate a well-defined bitumen emulsion for its use in pavement infrastructure rather than simply to meet standard specifications. This review paper aims to enable the ultimate potential of the bitumen emulsion in the field of cold recycling technology by further following up the research progress of bitumen emulsion manufacturing, therefore, this paper reviews and discusses the literature available up to now on this topic, in road engineering and emulsion chemistry.

Recently Cold Bitumen Emulsion (CBE) mixture technologies have been developed to lower the pavement construction temperatures to reduce the environmental costs and control the gas emissions. Due to its poor early mechanical strength, active fillers (i.e. cement) have been used to obtain high early stiffness in order to have the potential for timely construction of the next layer. There is, however, a lack of understanding about the impact of active fillers nature on viscoelastic behaviour and fatigue damage resistance of CBE mastics. This study, therefore, aims to identify the influence of active fillers on the rheological properties and the resulted fatigue behaviour of CBE mastic, supported by chemical analysis for the filler-bitumen emulsion. For this aim, bitumen emulsion was mixed separately with seven fillers/blended fillers to prepare the CBE mastics. Various experiments include continuous pH monitoring tests (chemical reactivity of filler-bitumen emulsion), Strain sweep (SS) tests, Temperature-Frequency Sweep (TFS) tests, Time Sweep (TS) tests, and Linear Amplitude Sweep (LAS) tests were conducted on the CBE binder and the prepared mastics. Results show that the rheological performance and the fatigue damage resistance is not only dependent on the filler inclusions, but it significantly relies on filler type and chemistry. Based on that, the raise in complex shear modulus and the decrease in viscous components were associated with a significant enhancement in fatigue performance for specific filler.

With its sights set on sustainable development, transport policy finds itself confronted with the challenge of convincing people to abandon the current path of growth and instead use small, slower vehicles with a reduced range in the future. The problem with this goal is that people's mental structures are shaped by the car ensconced in their heads. Thinking in other terms hardly seems possible; moreover, many of the products classified as vehicles, but smaller in scale than the "car" and that already exist, remain unknown, nor can they be tried out - they are quite literally nowhere to be seen. In light of this situation, the German Federal Environmental Foundation has commissioned a feasibility study to explore the establishment of a World of Experience (Erlebniswelt) of sustainable urban mobility - the EcoMobileum®. Here, the aim is to open up the horizons of a new culture of mobility in order to get people excited about the transformation of mobility.

The increased adoption of information and communication technology for smart grid applications will require innovative cyber-physical system (CPS) testbeds to support research and education in the field. The groundbreaking CPS testbeds with realistic and scalable platforms have progressively gained interest in recent years, with electric power flowing in the physical layer and information flowing in the network layer. However, CPSs are critical infrastructures and not designed for testing or direct training, as any misbehaving in an actual system operation could cause a catastrophic impact on its operation. Based on that, it is not easy to efficiently train professionals in CPSs. Aiming to support the advancement and encourage the training of industry professionals, this paper proposes and develops a complete testbed with commercial tools. The testbed can reliably replicate the performance of smart grid systems and the main potential cyber threats that electric grids may face. The complex interdependencies between the cyber and physical domains are discussed in detail, and different case scenarios are presented, providing insightful guidelines for key features and design decisions for future smart grid testbeds.

In the rescue operations the full time of action plays important role. It is a sum of planning, travel, and manipulation (in the action place) phases times. The time minimization of first two phases by autonomous vehicle for remote action is considered in the paper. For known a priori map the path planning consists of local optimal decision collected next in the general algorithm of the optimal path. Such approach significantly reduces time of path planning. The robot features and known sparse obstacles reduce the allowable robot speeds. The time of travel is calculated from allowable velocity profile. So, it can be used to estimate the travel performance. Genetic algorithm and random search-based methods for path finding with travel time optimization are exploited and compared in the paper. All the proposed time optimisation solutions of rescue operation are checked during computer simulations and results of simulation are presented.

Hydrogen storage in general is an indispensable prerequisite for the introduction of a hydrogen energy based infrastructure. In this respect, high-pressure metal hydride (MH) tank systems appear to be one of the most promising hydrogen storage techniques for automotive applications using proton exchange membrane (PEM) fuel cells. These systems bear the potential of achieving a beneficial compromise of comparably large volumetric storage density, a wide working temperature range, comparably low liberation of heat, and increased safety. The debatable term unstable metal hydride stands in the literature short for metal hydrides with high dissociation pressure at comparably low temperature. Such compounds may help to improve the merit of high-pressure MH tank systems. Consequently, in the last few years, some materials for possible on-board applications in such tank systems have been developed. This review summarizes the state-of-the-art developments of these metal hydrides, mainly including intermetallic compounds and complex hydrides and gives some guidelines for future developments. Since typical laboratory hydrogen uptake measurements are limited to 200 bar, a possible threshold for defining unstable hydrides could be a value of their equilibrium pressure of peq > 200 bar for T < 100°C. However, these values would mark a technological future target and most current materials, and those reported in this review, do not fulfill these requirements and need to be seen as current stages of development towards the intended target. For each of the aforementioned categories in the review, special care was taken not only to covers the pioneering and classical research, but also to portrait the current status and latest advances. For intermetallic compounds, key aspects focus on the influence of partial substitution on absorption/desorption plateau pressure, hydrogen storage capacity and hysteresis properties. For complex hydrides, the preparation procedures, thermodynamics and theoretical calculation are presented. Besides, challenges, perspectives, and development tendency of this field are also discussed.

The main objective of this communication is to describe the ‘Global Salt Cycle’. Giant salt accumulations are commonly found along continental margins of former rifts. The first stage in the accumulation process is saturation of newly formed oceanic crust with seawater. Final mobilisation and accumulation of the salts occurs during rifting, localised in the vicinity of relict subduction zones. Oceanic crust is created along the spreading ridges in the deep oceans of the Earth. It exchanges mass and energy with seawater in hydrothermal circulation cells that penetrate deep into the new and fractured crust. Water-rock interactions include the formation of hydrated and hydroxylated minerals, e.g., serpentinites and clay minerals. By incorporating hydroxyl groups and water in their crystal lattices, the salinity of remaining brines increases. Subduction of oceanic crust and serpentinised lithosphere transports water, hydrated minerals, and marine salts deep into the crust and mantle. Upon pressurisation and heating of the subducting slab, different parts of this water are expelled at different depths/temperatures. The resulting fluids will contain salts brought in with the slab, as well as new salts formed by water-rock interaction. The combination of elevated pressures and temperatures, water, salinity, and CO2, create permeability in the normally impermeable, peridotitic mantle, by altering the fluid-rock dihedral angles of mineral grains. This P/T-determined intergranular permeability allows ascent of saline fluids, under lithostatic pressure, within the mantle wedge, or the slab itself. The fluids produce a mechanically weakened and buoyant zone within the mantle wedge due to high pore pressure between mineral grains and reduced mantle density. During the lifetime of a subduction zone, a substantial accumulation of saline fluids within the mantle wedge and crust, is evident. Deep, fluid reservoirs accumulate between the subduction trench and the volcanic front. They may exist for hundreds of millions of years, even after the extinction of the subduction zone. Saline fluids may escape to the surface along deep faults, due to overfilling of available pores/fractures. Fluids within the mantle wedge may form rock melts or exist as supercritical, mineral rich fluids. The combination of reduced pressure due to rifting, and a saline and buoyant mantle, creates a mantle circulation that brings the accumulated, saline fluids, to crustal levels. Salts will therefore accumulate during initial stages of rifting as a result of massive fluid expulsion, phase change and boiling of mantle fluids. No extra energy is required to produce phase change and boiling. The result is formation of solid salts or dense brines/slurries invading fractured crustal rocks, or escaping to the surface/seabed. This process may take place both before and after the sea has invaded a continental rift.

We are calling for a paradigm shift in engineering education. In times of the Fourth Industrial Revolution (“4IR”), a myriad of potential changes is affecting all industrial sectors leading to increased ambiguity that makes it impossible to predict what lies ahead of us. Thus, incremental culture change in education is not an option any more. The vast majority of engineering education and training systems, having remained mostly static and underinvested in for decades, are largely inadequate for the new 4IR labor markets. Some positive developments in changing the direction of the engineering education sector can be observed. Novel approaches of engineering education already deliver distinctive, student centered curricular experiences within an integrated and unified educational approach. We must educate engineering students for a future whose main characteristics are volatility, uncertainty, complexity and ambiguity. Talent and skills gaps across all industries are poised to grow in the years to come. The authors promote an engineering curriculum that combine timeless didactic tradition, such as Socratic inquiry, project-based learning and first-principles thinking with novel elements (e.g. student centered active and e-learning by focusing on the case study and apprenticeship pedagogical methods) as well as a refocused engineering skillset and knowledge. These capabilities reinforce engineering students’ perceptions of the world and the subsequent decisions they make. This 4IR engineering curriculum will prepare engineering students to become curious engineers and excellent communicators better navigating increasingly complex multistakeholder ecosystems.

Changes in the atomic and electronic structure of silicon carbide 3C-SiC (β-SiC), resulting from lead adsorption, have been studied within the density functional theory. The tests were conducted for three representative surfaces with varying degrees of lead coverage. Results indicate that chemisorption occurs, with the strongest binding, found on the hexagonal surface (111) in interaction with three dangling bonds. The adsorption energy rises with increasing coverage, especially as the surface approaches saturation. Analysis of the data was focused on parameters important for corrosion processes such as bond distances, binding energies, Bader charges and charge density difference.

Some biostimulants, including plant origin preparations, act similarly to plant hormones. Moreover, the supplementation of known and unknown rooting cofactors can stimulate rhizogenesis in cuttings. The aim of this research was to assess the response of difficult-to-root and long-rooting stem cuttings of the once-blooming old variety Rosa ‘Hurdal’ to preparations of plant origin. The hypothesis was that plant origin preparations could enhance rooting processes by inhibiting chlorophyll a/b degradation in leaves and postponing leaf senescence, simultaneously increasing the quality of cuttings. The one-bud stem cuttings were made in four phenological stages: (H1) flower buds closed, (H2) open flowers, (H3) just after petal fall, (H4) 7-14 days after petal shedding. They were treated with either standard commercial powder preparations containing 0.4% indolebutyric acid (IBA) or 0.2% naphthalene acetic acid (NAA) as well as with commercial plant origin preparations that this work will henceforth refer to as: Algae Extract, Organic Preparation, and Plant Extract. The cuttings were evaluated after 12 weeks of rooting them in two substrates: peat-perlite and peat-sand (v:v; 1:1). Mean root percentages for both substrates were noted after preparation from stage H1 (74.5 %), H2 (59.5 %), H3 (50.8 %) shoots. The H4 cuttings didn’t root at all and were not considered further. The means for all phenology stages together were the highest by the use of 0.6 % Algae Extract, 0.012 % and 0.02 % Organic Preparation, 0.2 % and 0.4 % Plant Extract. The lowest means were reported for the control cuttings as well as NAA and IBA treatment. Plant origin preparations encouraged growth parameters but did not unequivocally inhibit the decrease of chlorophyll content in the cuttings’ leaves. Rooting percentage depended on the quality of cuttings as well as chlorophyll a/b and soluble protein content in leaves in both rooting substrates.

This paper investigates experiences of how local cultural norms and social capital influenced the disaster relief process following the 2011 GEJET disaster. To underline social capital’s multiple‐influence aspects, this paper draws from field research that focuses on collective and individual social capital in disaster relief to systematise the findings according to the social capital framework. The paper uncovers new effects of individual social capital and collective capital in a mega-disaster context, thus contributing to pushing the research agenda toward a more critical appraisal of individual social capital and collective capital. We contribute to the nascent but growing literature that clarifies the relationship between social capital and disaster resilience. A qualitative study was conducted to capture the essence of their shared experiences. Findings revealed three main themes capturing the essence of the research participants’ disaster experiences. First, disaster response relied mostly on locally driven relief due to a clear understanding of the local culture. Second, there was an urgency to establish a sense of normalcy by providing quality supplies that would help survivors. Third, Japanese gender roles and expectations were reflected in the disaster relief process. The themes establish a wide array of lived experiences that are important to reflect on the role social capital plays in the policy-making and needs assessment processes in post-disaster relief and response efforts. The findings provide insights for integrating social dimensions into a humanitarian aid culture as citizens work towards a sense of normalcy.

Twenty-first century infrastructure needs to respond to changing demographics, becoming climate neutral, resilient, and economically affordable, while remaining a driver for development and shared prosperity. However, the infrastructure sector remains one of the least innovative and digitalized, plagued by delays, cost overruns, and benefit shortfalls [1-4]. The root cause is the prevailing fragmentation of the infrastructure value chain [5]. To support overcoming the shortcomings, an integration of the value chain is needed. This could be achieved through a use-cased-based creation of federated digital platforms applied to infrastructure projects. Such digital platforms enable full-lifecycle participation and responsible governance guided by a shared infrastructure vision.

Retrogressive breach failures or coastal flow slides occur naturally in the shoreface in fine sands near dynamic tidal channels or rivers. They sometimes retrogress into beaches, shoal margins and river banks where they can threaten infrastructure and cause severe coastal erosion and flood risk. Ever since the first reports were published in the Netherlands over a century ago, attempts have been made to understand the geo-mechanical mechanism of flow slides. In this paper we have established that events, observed during the active phase, are characterized by a slow and steady retrogression into the shoreline, often continuing for many hours. This can be explained by the breaching mechanism, as elaborated in this paper. Recently, further evidence has become available in the form of video footage of active events in Australia and elsewhere, often publicly posted on the internet. All these observations justify the new term ‘retrogressive breach failure’ (RBF event). The mechanism has been confirmed in small-scale flume tests and in a large-scale field experiment. With a better understanding of the geo-mechanical mechanism, current protection methods can be better understood and new defense strategies can be envisaged. In writing this paper, we hope that the coastal science and engineering communities will better recognize and understand these intriguing natural events.

Part II, like Part I, discusses geometry, kinematics and statics in detail without taking into account power losses in meshing. The main goal of Part II, however, is to prove that there are complex and structurally coupled planetary gear systems, i.e. containing a closed circuit in which no circulation of power flow is generated. The power flow analysis is also carried out using the direct method, with a slight modification in the way of writing the equations identifying active and passive gears, i.e. at the same time the directions of power flow on all transmission paths. The analysed planetary gear system (PGS) is characterised by mobility equal to 1, i.e. single degree of freedom (DoF). It consists of three subsystems in the form of the 2KH type planetary units connected in series-parallel, specially selected to demonstrate the thesis of this paper. It consists of three subsystems in the form of single planetary subsystems of the 2KH type connected series-parallel, specially chosen to illustrate the thesis of this paper.

The results from laboratory tests and field tests, available in the open literature for over ten years, despite the announcement of high efficiency translating into increased energy efficiency and such significant ecological advantages, have not so far resulted in widespread use of fuel performance catalysts (FPC) on a global scale. Wishing to explain why the above situation occurred and to verify the operation of catalytic additives for fuels; this article presents the results of research on the effect of using catalytic additives for fuel in a brand new diesel engine. The article contains an analysis of the results of exhaust gas emission tests from the Doosan MD196TI engine. During the tests, the engine was fueled with a typical diesel fuel and the same fuel with the a catalyst additive. The catalyst was added to the liquid fuel in the form of a commercially available product distributed by ProOne company under the name FMAX. The research was carried out in the form of a test, much more developed than the approval test on a stationary braking station in accordance with the requirements of ISO 8178. The article is concluded with a comparative analysis of exhaust gas emission results illustrating the effects of a catalyst in the form of reduction of solid particles, carbon monoxide, hydrocarbons and a slight increase in nitrogen oxide emissions. In addition, the effect of the catalyst depends on the product of thermal (brake) efficiency of the engine and the calorific value (CV) of the fuel used.

Comparisons of power flows and efficiencies in two structurally quite similar cylindrical series-parallel planetary gear systems (PGSs) were performed in three separate parts of this paper. Each of these single degree of freedom (DoF) systems consists of three different 2KH subsystems connected in series-parallel. The main goal was to prove that apart from complex, structurally and dynamically coupled PGSs, there are also complex and only structurally coupled PGSs, in which the phenomenon of power flow circulation inside closed loops does not occur. Such a half-coupled type of PGS is herein called pseudo-coupled. Therefore, Part I discusses in detail the geometry, kinematics and statics of coupled PGSs in order to determine power flow paths. A comparison of the directions of power flow in both types of PGSs can be made in Part II after determining the power flow paths in the second planetary gear in a similar way. The directions of power flow in both types of PGSs were determined in a relatively simple way, thanks to the distinction between active and passive torques and thus active and passive shafts of individual subsystems. The efficiency comparison made in Part III will show whether power circulation has an influence on the efficiency value, at least in these two types of PGSs.

The growing prevalence of social robots in various fields necessitates a deeper understanding of touch in Human-Robot Interaction (HRI). This study investigates how human-initiated touch influences physiological responses during interactions with robots, considering factors such as anthropomorphic framing of robot body parts and attributed gender. Two types of anthropomorphic framings are applied: the use of anatomical body part names and assignment of male or female gender to the robot. Higher physiological arousal is observed when touching less accessible body parts than when touching more accessible body parts in both conditions. Results also indicate that using anatomical names intensifies arousal compared to the control condition. Additionally, touching the male robot resulted in higher arousal in all participants, especially when anatomical body part names were used. This study contributes to the understanding of how anthropomorphic framing and gender impact physiological arousal in touch interactions with social robots, offering valuable insights for social robotics development.

TBI is one of the most common causes of death and long term damage to health worldwide. The approved guidelines for patients with TBI include standards of treatment. However, there is lack of guidelines for monitoring or neuroprotective treatment. Cerebrolysin is a drug with a proven beneficial effect on treatment outcome in patients with TBI. There are also reports of the beneficial effect of Amantadine. Studies on the use of additional neuromonitoring are also published with increasing frequency. We decided to investigate how the result of treatment changed with the administration of Cerebrolysin and Amantadine and with additional neuromonitoring. In an observational study, we collected data on 56 patients. After the statistical analysis, it could be shown, that Cerebrolysin monotherapy increases Glasgow Outcome Scale (GOS) among our patients and it was found to interact significantly with Amantadine and neuromonitoring approach in the group of severe TBI. In conclusion, it is worth considering a multimodal approach to the treatment and monitoring of patients with TBI. However, more randomized studies are needed to confirm the method of monitoring or conducting neuroprotective therapy in patients with TBI.

The utilization of wind energy has become increasingly popular in the United States and many European countries due to its abundant natural source and optimized design. While existing wind turbines are predominantly large-scale and not suitable for standalone or distributed power production, Lubbock County in West Texas offers a diverse range of renewable energy options to meet its energy needs. The region relies heavily on utility-scale wind energy sources to supply power to the Texas Grid, replacing conventional fossil fuel-based systems. Currently, standalone solar PV systems are the preferred choice for renewable energy generation. However, West Texas possesses an ample supply of wind energy that can be harnessed to establish a microgrid and provide standalone power to rural communities. By employing the latest technology and optimizing efficiency, even in low-scale generation, a 6 kW permanent magnet alternator-based distributed wind turbine has been designed. This paper focuses on analyzing the techno-economic aspects of implementing this wind turbine in a real-world scenario, taking into account wind attributes such as velocity and available power at the specific location.

Recent years have seen an increased interest in the role of oxidative stress (OS) in pregnancy. Pregnancy inherently heightens susceptibility to OS, a condition fueled by a systemic inflam-matory response which culminates in an elevated presence of reactive oxygen species (ROS) and reactive nitrogen species (RNS) in the circulatory system. The amplified OS in pregnancy can trigger a series of detrimental outcomes such as underdevelopment, abnormal placental function, and a host of pregnancy complications, including pre-eclampsia, embryonic resorp-tion, recurrent pregnancy loss, fetal developmental anomalies, intrauterine growth restriction, and in extreme instances, fetal death. The body’s response to mitigate the uncontrolled increase in RNS/ROS levels involves trace elements that take part in non-enzymatic and enzymatic defense mechanisms, namely, copper (Cu), zinc (Zn), manganese (Mn), iron (Fe), and selenium (Se). Determination of ROS concentrations poses a challenge due to their short lifespan, prompting the use of marker proteins, including malondialdehyde (MDA), superoxide dis-mutase (SOD), glutathione peroxidase (GPx), glutathione reductase (GR), lipid peroxidation (LPO), catalase (CAT), and glutathione (GSH). These markers, indicative of redox stress intensity, can offer indirect assessments of pregnancy complications. Given the limitations in conducting experimental studies on pregnant women, animal models serve as valuable substitutes for in-depth research. This review delves into the mechanism of OS in pregnancy and underscores the pivotal role of markers in its evaluation.

In the pathogenesis of endometriosis, the differences between the eutopic and ectopic endometrium as well as between the eutopic endometrium with and without endometriosis are repeatedly pointed out. Various mechanisms have been suggested to explain these changes among them epithelial-mesenchymal transition (EMT). Recently, we suggested based on immunohistochemical data that most of the changes occur after and not before implantation of endometrial cells into ectopic locations. Furthermore, the subtle changes between eutopic endometrium with and without endometriosis and maintenance of epithelial cell-to cell contacts only suggest a partial EMT. In this study, we have re-analyzed the mRNA expression array data of eutopic and ectopic endometrium with respect to expression changes and EMT. Especially, we found that the similarity between eutopic endometrium with and without endometriosis is extremely high (~99.1%). In contrast, eutopic endometrium compared to ectopic endometrium only shows an overall similarity of ~95.3%. Analysis of some EMT-associated genes revealed small differences in the mRNA expression levels of some members of the claudin family. The array data suggest that the changes in eutopic endometrium at the beginning of the disease are quite subtle and that the majority of differences occur after implantation into ectopic locations.

In the present study, we isolated and screened thirty strains of GABA-producing lactic acid bacteria (LAB) from Indonesian traditional fermented foods. Two strains were able to convert monosodium glutamate (MSG) to GABA after 24 h of cultivation at 37oC based on thin layer chromatography (TLC) screening. 16S rDNA sequencing and proteomic identification using MALDI-TOF MS identified these two strains as Lactobacillus plantarum designated as L. plantarum FNCC 260 and L. plantarum FNCC 343. The highest yield of GABA production obtained from the fermentation of L. plantarum FNCC 260 was 809.2 mg/l of culture medium after 60 h of cultivation. Supplementation of 0.6 mM pyridoxal 5’-phosphate (PLP) and 0.1 mM pyridoxine led to the increase in GABA production to 945.3 mg/l and 969.5 mg/l, respectively. The highest GABA production of 1226.5 mg/l of culture medium was obtained with 100 mM initial concentration of MSG added in the cultivation medium. The open reading frame (ORF) of 1410 bp of the gadB gene from L. plantarum FNCC 260 encodes 469 amino acids with a calculated molecular mass of 53.57 kDa. The production of GABA via enzymatic conversion of monosodium glutamate (MSG) using purified recombinant glutamate decarboxylase (GAD) from L. plantarum FNCC 260 expressed in Escherichia coli was found to be more efficient (5-fold higher within 6 h) than the production obtained from fermentation. L. plantarum FNCC 260 could be of interest for the synthesis of GABA.

Digital federated platforms and data cooperatives for secure, trusted and sovereign data exchange will play a central role in the construction industry of the future. With the help of platforms, cooperatives and their novel value creation, the digital transformation and the degree of organization of the construction value chain can be taken to a new level of collaboration. The goal of this research project was to develop an experimental prototype for a federated innovation data platform along with a suitable exemplary use case. The prototype is to serve the construction industry as a demonstrator for further developments and form the basis for an innovation platform. It exemplifies how an overall concept is concretely implemented along one or more use cases that address high-priority industry pain points. This concept will create a blueprint and a framework for further developments, which will then be further established in the market. The research project illuminates the perspective of various governance innovations to increase industry collaboration, productivity and capital project performance and transparency as well as the overall potential of possible platform business models. However, a comprehensive expert survey revealed that there are considerable obstacles to trust-based data exchange between the key stakeholders in the industry value network. The obstacles to cooperation are predominantly not of a technical nature, but of a competitive, predominantly trust-related nature. To overcome these obstacles and create a pre-competitive space of trust, the authors therefore propose the governance structure of a data cooperative model, which is discussed in detail in this paper.

This article presents a comprehensive study on enhancing grid resilience through advanced forecasting and optimization techniques in the context of power outages. Power outages pose significant challenges to modern societies, affecting various sectors such as industries, households, and critical infrastructures. The research combines statistical analysis, machine learning algorithms, and optimization methods to address this issue to develop a holistic approach for predicting and mitigating power outage events. The proposed methodology involves the use of Monte Carlo simulations in MATLAB for future outage prediction, Long Short-Term Memory (LSTM) networks for forecasting solar irradiance and load profiles, and a hybrid LSTM-Particle Swarm Optimization (PSO) model to improve accuracy. Furthermore, the role of Battery State of Charge (SoC) in enhancing system resilience is explored. The study also assesses the techno-economic advantages of a grid-tied microgrid integrated with solar panels and batteries over conventional grid systems. The results highlight the potential of the proposed approach in strengthening grid resilience, reducing downtime, and fostering sustainable energy utilization.

A new two-step method for developing a nanocomposite of polypropylene (PP) decorated with photocatalytically active TiO2 nanoparticles (nTiO2) is proposed. This method involves low-temperature plasma functionalization of polypropylene followed by ultrasound-assisted anchoring of nTiO2. The nanoparticles, polymeric substrate, and resultant nanocomposite were thoroughly characterized using nanoparticle tracking analysis (NTA), microscopic observations (SEM, TEM, EDX), spectroscopic investigations (XPS, FTIR), thermogravimetric analysis (TG/DTA), and water contact angle (WCA) measurements. The photocatalytic activity of the nanocomposites was evaluated through the degradation of methyl orange. The individual TiO2 nanoparticles ranged from 2-6 nm in size. Oxygen plasma treatment of PP generated surface functional groups (mainly -OH and -C=O), transforming the surface from hydrophobic to hydrophilic, which facilitated efficient deposition of nTiO2. Optimized plasma treatment and sonochemical deposition parameters resulted in an active photocatalytic nTiO2/PP system, degrading 80% of methyl orange under UVA irradiation in 200 minutes. The proposed approach is considered versatile for the functionalization of polymeric materials with photoactive nanoparticles and, in a broader perspective, can be utilized for the fabrication of self-cleaning surfaces.

This paper introduces an innovative framework for the integration of artificial empathy into robot swarms to enhance communication and cooperation. The proposed model relies on fuzzy state vectors to represent the knowledge and environment of individual agents, accommodating uncertainties in the real world. Utilizing similarity measures, the model compares states, enabling empathetic reasoning for synchronized swarm behavior. A practical application example demonstrates the model’s efficacy in a robot swarm striving for a common goal. The evaluation methodology involves the Open Source Physical-based Experimentation Platform (OPEP), emphasizing empirical validation in real-world scenarios. The paper proposes a transitional environment that allows automated and repeatable execution of experiments on a swarm of robots using physical devices.

Woodland bat assemblages are usually structured in space by distance from the ground, water and obstacles, features often defining chiropteran hunting tactics. Consequently, bat species composition differs strongly among various habitats even within the same forest patch. However, when conducting local bat survey in Wolin National Park (WPN), we revealed unexpected uniformity in qualitative and quantitative structure of bat assemblages, based on mist netting and ultrasound recording. In total, 10 vespertilionid species were detected. In all methods and sampled habitats a single species, Pipistrellus pygmaeus, predominated, while no Barbastella barbastellus, an old forest specialist, was detected, despite the abundance of preferred daily roosts. We also reviewed literature for mist netted bat samples in four different habitats of lowland Polish forests. Samples usually clustered based on habitats and the same habitat classes often clustered very closely, despite representing geographically distant forests. The exception was WPN, where all four habitat classes formed a tightly packed cluster. We suppose that P. pygmaeus might act as a hyperabundant native species, a successful generalist that reduces the contribution of more specialized taxa in the assemblage. It probably benefits from both forest renaturation and anthropogenic cross-boundary subsidy, the latter including both roost availability and prey abundance.

This study applies a cluster analysis to identify typical physical activity (PA) and sedentary behaviour (SB) patterns in people with chronic obstructive pulmonary disease (COPD) before starting pulmonary rehabilitation (PR). We implemented an observational design which assessed baseline data on objectively measured PA and SB from the STAR (Stay Active after Rehabilitation) study. 355 persons wore a accelerometer (Actigraph wGT3X) for seven days before the start of their PR. Sociodemographic and disease-related parameters were assessed at the start of PR. We applied cluster analysis and compared groups applying univariate variance analyses. Data was available for 326 persons (31.6% women; age ø = 58 yr.). Cluster analysis revealed four movement clusters with distinct PA and SB patterns: sedentary non-movers (28.5%), sedentary occasional movers (41.7%), sedentary movers (19.6%), and sedentary exercisers (10.1%). The four clusters showed very different levels of moderate PA before rehabilitation (Ø daily minutes: 9; 28; 38; 70). Notably, all four clusters displayed considerably long average sitting time per day (Ø daily minutes: 644; 561; 490; 446). The groups differed significantly in disease-related parameters of GOLD severity, FEV1, CAT, and 6-Min-Walk-Test. In addition to PA promotion, PR programs should consider the reduction of sitting time as a valuable goal.

This study examines the impact of alcohol concentration on the precision of unmanned aerial vehicle (UAV) operations. While the impact of alcohol impairment on various activities is well documented, its specific influence on drone piloting accuracy remains less studied. To address this, we carried out empirical research using an original methodology and a real-world environment. The study involved a group of 35 participants performing a series of flights using a selected drone (DJI Mavic2 Pro) on a bespoke obstacle route. Between each flight series, participants consumed a measured amount of alcohol, designed to incrementally increase their blood alcohol concentration monitored via breath tests. The precision of the drone pilot was evaluated by comparing various parameters from successive test flights, such as time, distance, average speed, and incident frequency, against a baseline trial executed with zero alcohol concentration. Our results indicate a noticeable decline in UAV piloting precision corresponding with increasing alcohol concentration. Parameters such as flight time, distance, speed, and incident frequency all demonstrated this trend. We conclude that alcohol consumption detrimentally affects the accuracy of drone operations. These findings underscore the need for clear policies and guidelines regarding the operation of UAVs under the influence of alcohol.

Thanks to its valuable assessment possibilities (subjective complaints and changes in nasal patency in the course of the examination), nasal provocation test may serve as an alternative tool for oral food challenges in the future. However, this test requires successive attempts to regulate its methodology in order to develop a standardized lyophilisate form and determine the threshold dose for a positive result. The study objective was to present the methodological foundation for nasal food allergen provocation tests induced by freeze-dried powdered chicken egg white. A control group of 25 individuals with no history of allergy to chicken eggs or any other allergy was included in the study. Optical rhinometry and visual analog scale were used to assess the response of nasal mucosa to local allergen challenge. Minor variations in nasal flows as measured by optical rhinometry were observed in the provocation tests. The mean optical density measurements (as measured regardless of the allergen dose used) varied from positive to negative values and vice versa; e.g., amounting to 0.018 OD (standard deviation 0,095) at 15 minutes and −0.011 OD (standard deviation 0,090) at 30 minutes. No significant differences were observed with regard to the perceived nasal discomfort using the visual analog scale. Due to the absence of nasal mucosal reactivity, nasal challenge is an excellent methodological tool for implementing food allergen tests.

Proteasome inhibitors, like bortezomib, play a key role in the treatment of multiple myeloma (MM); however, most patients eventually relapse and eventually show multiple drug resistance, and the molecular mechanisms of this resistance remain unclear. The present study examines the expression of previously-described genes that may influence resistance to bortezomib treatment at the mRNA level (ABCB1, CXCR4, MAF, MARCKS, POMP, PSMB5, RPL5, TXN and XBP1). mRNA expression was determined in 73 MM patients treated with bortezomib-based regimens (30 bortzomib-sensitive and 43 bortezomib-refractory patients) and 11 healthy controls. RPL5 was significantly down-regulated in multiple myeloma patients as compared with healthy controls. Moreover, POMP was significantly up-regulated in MM patients refractory to bortezomib-based treatment. In multivariate analysis, high expression of PSMB5 and CXCR and autologous stem cell transplantation were independent predictors of progression-free survival, and high expression of POMP and RPL5 was associated with shorter overall survival.

Although, severe acute respiratory syndrome coronavirus – 2 (SARS-CoV 2) represents one of the biggest challenges in the world today, the exact immunopathogenic mechanism that leads to severe or critical Coronavirus Disease 2019 (COVID-19) has remained incompletely understood. Several studies have indicated that high systemic plasma levels of inflammatory cytokines result in the so-called “cytokine storm”, with subsequent development of microthrombosis, disseminated intravascular coagulation, and multiorgan-failure. Therefore, we reasoned that elevated inflammatory cytokine might act as prognostic factors. Here, we analyzed 245 serum samples of patients with COVID-19, collected at hospital admission. We assessed the levels of heat shock protein 27 (HSP27), soluble suppressor of tumorigenicity- 2 (sST2), caspase cleaved cytokeratin 18 (cCK18), 20S proteasome, and tumor necrosis factor receptor 1 (TNFR-1) and explored their associations with overall-, 30-, 60-, 90-day- and in-hospital mortality. Moreover, we investigated their association with the risk of ventilation. We demonstrated that increased serum sST2 was uni- and multivariably associated with all endpoints. However, we also identified 20S proteasome as independent prognostic factor for in-hospital mortality. Furthermore, elevated HSP27, sST2, and 20S proteasome levels at hospital admission were univariably associated with higher risk of invasive ventilation. These findings could help to identify high-risk patients early in the course of COVID-19.

This article uses machine learning analysis of wearable sensor data to explore the topic of driver differentiation. The study focuses on using detailed analyzes of data collected from wearable sensors to identify patterns that differentiate skilled drivers from inexperienced ones. On a predetermined driving route, participants experienced a variety of driving conditions, including parking, navigating cities, driving on highways and driving through residential neighborhoods. The gathered data was analyzed using machine learning techniques, yielding a classification accuracy of 94% overall. The results highlight important differences in sensor data between inexperienced and experienced drivers, providing insight into possible uses for improving safety protocols, driver education, and personalized feedback systems. The article fosters improvements in traffic safety and driver education by offering insightful information on the link between driver behavior analysis and machine learning.

Specific climate adaptation and resilience measures can be efficiently designed and implemented at the regional and local level. Climate and environmental databases are of critical importance to achieving sustainability goals (SDGs) and for the efficient planning and implementation of suitable mitigation measures: Available databases can serve municipalities as a vital starting points to determine requirements, prioritize resources and allocate investments under consideration of commonly tight budget restrictions. High-quality geo, climate and environmental data are now available – data from remote sensing, i.e. Copernicus services will be of crucial importance. Forward-looking approaches exist to using such data to derive forecasts for urban planning process optimization for municipal administrations. On municipal level, however, the existing data have so far only been used to a limited extent, since there are no practical tools for urban planning that can be used to merge and meaningfully combine remote sensing data with local data and to further process and apply in municipal planning processes. Therefore, our project CoKLIMAx aims at the development of new digital products, advanced urban services and procedures, such as the development of practice-oriented technical tools that acquire various remote sensing and in-situ data sets for validation and further processing.

Ataxin-2 (ATXN2) acts during stress-responses, modulating mRNA translation and nutrient metabolism. Atxn2 knockout mice exhibit progressive obesity, dyslipidemia and insulin resistance. Conversely, the progressive ATXN2 gain-of-function due to polyGlutamine (polyQ) expansions leads to a dominantly inherited neurodegenerative process named spinocerebellar ataxia type 2 (SCA2), with early adipose tissue loss and late muscle atrophy. We tried to understand lipid dysregulation in a SCA2 patient brain and in an authentic mouse model. Thin layer chromatography of a patient cerebellum was compared to the lipid metabolome of Atxn2-CAG100-KnockIn (KIN) mouse spinocerebellar tissue. The human pathology caused deficits of sulfatide, galactosylceramide, cholesterol, C22/24-sphingomyelin and gangliosides GM1a/GD1b, despite quite normal levels of C18-sphingomyelin. Cerebellum and spinal cord from the KIN mouse showed a consistent decrease of various ceramides, with a significant elevation of sphingosine in the more severely affected spinal cord. Deficiency of C24/26-sphingomyelins contrasted with excess C18/20-sphingomyelin. Spinocerebellar expression profiling revealed consistent reductions of CERS protein isoforms, of Sptlc2 and Smpd3, but upregulation of Cers2 mRNA, as prominent anomalies in the ceramide-sphingosine metabolism. Reduction of Asah2 mRNA correlated to deficient S1P levels. In addition, downregulations for the elongase Elovl1, Elovl4, Elovl5 mRNAs and ELOVL4 protein explain the deficit of very-long-chain sphingomyelin. Reduced ASMase protein levels correlated to the accumulation of long-chain sphingomyelin. Overall, a deficit of myelin lipids was prominent in SCA2 nervous tissue at prefinal stage, not compensated by transcriptional adaptation of several metabolic enzymes. Myelination is controlled by mTORC1 signals, so our human and murine observations are in agreement with the known role of ATXN2 yeast, nematode and mouse orthologs as mTORC1 inhibitors and autophagy promoters.

Despite substantial heterogeneity of studies, there is evidence that antibiotics commonly used in primary care influence the composition of the gastrointestinal microbiota in terms of changing the composition and/or diversity. Benzyl isothiocyanate (BITC) from the food and medicinal plant nasturtium (Tropaeolum majus) is known for its antimicrobial activity and is used for the treatment against infections of the draining urinary tract and upper respiratory tract. Against this background, we raised the question whether 14 d nasturtium intervention (3 g daily, N=30 healthy females) could also impact the normal gut microbiota composition. Spot urinary BITC excretion highly correlated with a weak, but significant antibacterial effect against Escherichia coli. A significant increase in human beta defensin 1 as parameter for host defense was seen in urine and exhaled breath condensate (EBC) upon verum intervention. Pre-to-post analysis revealed that mean gut microbiome composition did not significantly differ between groups, nor did circulating serum metabolome. On an individual level, partly large changes were observed between sampling points, though. Explorative Spearman rank correlation analysis in subgroups revealed associations between gut microbiota and the circulating metabolome, as well as between changes in blood markers and bacterial gut species.

Network effects, economies of scale, and lock-in-effects increasingly lead to a concentration of digital resources and capabilities, hindering the free and equitable development of digital entrepreneurship (SDG9), new skills, and jobs (SDG8), especially in small communities (SDG11) and their small and medium-sized enterprises (“SMEs”). To ensure the affordability and accessibility of technologies, promote digital entrepreneurship and community well-being (SDG3), and protect digital rights, we propose data cooperatives [1,2] as a vehicle for secure, trusted, and sovereign data exchange [3,4]. In post-pandemic times, community/SME-led cooperatives can play a vital role by ensuring that supply chains to support digital commons are uninterrupted, resilient, and decentralized [5]. Digital commons and data sovereignty provide communities with affordable and easy access to information and the ability to collectively negotiate data-related decisions. Moreover, cooperative commons (a) provide access to the infrastructure that underpins the modern economy, (b) preserve property rights, and (c) ensure that privatization and monopolization do not further erode self-determination, especially in a world increasingly mediated by AI. Thus, governance plays a significant role in accelerating communities’/SMEs’ digital transformation and addressing their challenges. Cooperatives thrive on digital governance and standards such as open trusted Application Programming Interfaces (APIs) that increase the efficiency, technological capabilities, and capacities of participants and, most importantly, integrate, enable, and accelerate the digital transformation of SMEs in the overall process. This policy paper presents and discusses several transformative use cases for cooperative data governance. The use cases demonstrate how platform/data-cooperatives, and their novel value creation can be leveraged to take digital commons and value chains to a new level of collaboration while addressing the most pressing community issues. The proposed framework for a digital federated and sovereign reference architecture will create a blueprint for sustainable development both in the Global South and North.

Economic risks for livestock production are caused by volatile commodities and market conditions, but also by environmental drivers like increasing uncertainties due to weather anomalies and global warming. These risks impact the gross margin of farmers and can stimulated investment decisions. For confined pig and poultry production, farmers can reduce the environmental impact by implementing specific adaptation measures to reduce heat stress. A simulation model driven by meteorological data was used to calculate heat stress impact as a projection for 2030. For a business-as-usual livestock building, the indoor climate for several adaptation measures was calculated. The weather-related value-at risk quantified the economic risks caused by global warming and the stochastic component of the weather. The results show that only energy-saving adaptation measures to reduce the inlet air temperature are appropriate to reduce the economic risk to the level of the year 1980. The efficiency of other adaptation measures to reduce heat stress is distinctly lower. The results in this study can support the decision making of farmers concerning adaptation management and investments. It can inform agricultural policy design as well as technological development.

In the last decades farm animals kept in confined and mechanically ventilated livestock buildings are increasingly confronted with heat stress (HS) due to global warming. These adverse conditions cause a depression of animal health and welfare and a reduction of the performance up to an increase of the mortality. To facilitate sound management decisions, livestock farmers need relevant arguments, which quantify the expected economic risk and the corresponding uncertainty. The economic risk was determined for the pig fattening sector based on the probability of HS and the calculated decrease in the gross margin. The model calculation for confined livestock buildings showed, that HS indices calculated by easily available meteorological parameters can be used for assessment quantification of indoor HS, which is so far difficult to determine. These weather-related HS indices can be applied not only for an economic risk assessment but also for a weather-index based insurance for livestock farms. Based on the temporal trend between 1981 and 2017, a simple model was derived to assess the likelihood of HS for 2020 and 2030. Due to global warming, the return period for a 90-percentile HS index is reduced from 10 years in 2020 to 3-4 years in 2030. The economic impact of HS on livestock farms was calculated by the relationship between an HS index based on the temperature-humidity index (THI) and the reduction of the gross margin. From the likelihood of the HS and this economic impact function, the probability of the economic risk could be determined. The reduction of the gross margin for a 10 year return period was determined for 1980 with 0.27 € per year and animal place and increased by the 20-fold to 5.13 € per year and animal place in 2030.

Background: DICER1, cancer predisposition syndrome (CPS), seems to escape timely diagnosis in pediatric patients. Case report 1: A 16-year-old female patient was referred to the endocrinology ward due to a large goiter. Her medical history indicated normal sexual maturation, with menarche occurring at 13.5 years. Over the past 2.5 years, she developed pronounced androgenic symptoms, including a deepened male voice, facial, back and neckline acne, hirsutism, and menstrual irregularities leading to secondary amenorrhoea. A thyroid ultrasound identified a multinodular goiter with cystic-solid lesions containing calcifi-cations. An abdominal ultrasound identified a 5.7x6.9 cm solid mass in the right adnexal region, displacing the uterus to the left. Histopathological examination confirmed a Sertoli-Leydig cell tumor. The patient was subjected to total thyroidectomy. Histopathology revealed benign follicular cell-derived neoplasms. Thyroid follicular nodular disease was diagnosed bilaterally. DNA analysis using NGS, confirmed by the Sanger method, revealed a pathogenic heterozygotic variant c.2953>T [p.Gln985*] in exon 18 of DICER1 gene. Case report 2: A 12-year-old male patient was admitted to the pediatric surgery unit due to a 33 ml goiter. A month prior to admission, the patient discovered a palpable nodule in his neck, accompanied by hoarseness. An ultrasound revealed a multinodular goiter. Molecular analysis revealed a pathogenic heterozygotic variant c.2782C>T [p.Gln928Ter] in exon 17 of DICER1 gene. Subsequently, a total thyroidectomy was performed, and histopathological examination revealed thyroid follicular nodu-lar disease bilaterally. Conclusion: Multinodular goiter, although rare in pediatric population, when accompanied by characteristic ultrasound and histopathological features, and by additional features such as androgen excess, warrants exclusion of DICER1 syndrome.

Idiopathic lung fibrosis (IPF) is a progressive and fatal degenerative lung disease of unknown etiology. Although in its final stages it implicates in a reactive manner all lung cell types, the initial damage involves the alveolar epithelial compartment, in particular the alveolar epithelial type 2 cells (AEC2s). AEC2s serve dual progenitor and surfactant secreting functions, both of which are deeply impacted in IPF. Thus, we hypothesize that the size of the surfactant processing compartment, as measured by Lysotracker incorporation, allows the identification of different epithelial states in the IPF lung. Flow cytometry analysis of epithelial Lysotracker incorporation delineates two populations (Lysohigh and Lysolow) of AEC2s which behave in a compensatory manner during bleomycin injury and in the donor/IPF lung. Employing flow cytometry and transcriptomic analysis of cells isolated from donor and IPF lungs, we demonstrate that the Lysohigh population expresses all classical AEC2 markers and is drastically diminished in IPF. The Lysolow population, which is increased in proportion in IPF, co-expresses AEC2s and basal cell markers resembling the phenotype of the previously identified intermediate AEC2 population in the IPF lung. In that regard, we provide an in-depth flow-cytometry characterization of Lysotracker uptake, HTII-280, proSP-C, mature SP-B, NGFR, KRT5 and CD24 expression in human lung epithelial cells. Combining functional analysis with extra- and intra- cellular marker expression and transcriptomic analysis, we advance the current understanding of epithelial cell behavior and fate in lung fibrosis.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

The impact of interaction SS with MJO on rainfall along Java Island to East Nusa Tenggara has been studied using daily rainfall observation data from 2140 weather observation stations, which are also equipped with GSMaP, OLR, and ERA5 data. There were 61 SS events found, 17 during active MJO and 44 in inactive MJO. Rainfall increases more in the western study area when the active MJO and more in the eastern study area when the inactive MJO is due to SS. SS reduces rainfall in the Jakarta region, regardless of the activity or inactivity of the MJO. SS causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the IMC, SS predominates over MJO in supporting increased water vapor transport. Large-scale synoptic circulations like the monsoon, SS, and MJO can interact with local land-sea wind circulation to produce spatiotemporal variability in rainfall on Java Island. Rainfall mostly increases in the afternoon and decreases in the morning when SS occurs, whether there is MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by lowering CIN and raising VIMFC.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Currently there are fewer depth models applied to pepper picking detection, while the existing generalized neural networks have problems such as large model parameters, long training time, and low model accuracy.In order to solve the above problems, this paper proposes a Yolo-chili target detection algorithm for chili pepper detection. First, the classical target detection algorithm yolov5 is used as a benchmark model, and an adaptive spatial feature pyramid structure combining the attention mechanism and the idea of multi-scale prediction is introduced to improve the model's detection effect on occluded peppers and small target peppers. Secondly, a three-channel attention mechanism module is introduced to improve the algorithm's long-distance recognition ability and reduce the interference of redundant testers. Finally, the quantized pruning method is used to reduce the model parameters and realize the lightweight processing of the model. Applying the method to the homemade chili pepper dataset, the AP value of chili pepper reaches 93.11%; the accuracy rate is 93.51% and the recall rate is 92.55%.The experimental results show that yolo-chili is able to achieve accurate and real-time pepper detection under complex orchards.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Pyrops candelaria is one of the common pests of fruit trees, but the research on the pathogenic microorganisms it may carry is very limited. Therefore, it is essential to reveal the pathogenic microbes it carries and their potential hazards. This study found a new virus from the transcriptome of P. candelaria, which was first reported in P. candelaria and named as PyCaV (Pyrops candelaria associated virus). RACE and bioinformatics assay revealed that the full-length of PyCaV is 10855 bp with the polyA tail, containing a single open reading frame (ORF) encoding a polyprotein consisting of 3171 amino acid (aa). The virus has a typical Iflavirus structure, including two rhv domains, a RNA helicase domain (HEL), a 3C cysteine protease domain (Pro), and a RNA-dependent RNA polymerase domain (RdRp). Further phylogenetic analysis revealed that this virus belongs to family Iflaviridae and sequence alignements analysis suggedted PyCaV is new member in unassigned genus of family Iflaviridae. Further in-depth analysis of virus-infection-part showed that PyCaV is distributing in the whole longan lanternfly, including its head, chest, and abdomen, but more PyCaV was identified in the chest. The distribution of PyCaV in different parts of P. candelaria was further explored, which showed that more PyCaV were detected in its piercing-sucking mouthparts and chest viscera. Statistical analysis showed that the PyCaV infection was affected by time and locations.

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.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

The paper describes the new method for image compression based on coordinated group signal transformation. The algorithm is a type of difference coding. Coordinated processing significantly simplifies the difference signal conversion scheme using a single group codec for all signals. The described method considers color channels as correlated signals of a multi-channel communication system. The specifics of the processed data required modification of the coordinated group processing algorithm. First, we changed how to calculate the difference signals to prevent data loss. Secondly, the group codec was supplemented with a neural network to improve the quality of reconstructed images. We considered the following types of neural networks: fully connected, recurrent, convolution, and convolution in the Fourier space. Based on the simulation results, it is best to use fully connected neural networks if the goal is to minimize processing delay time. These networks have a response time of 13 ms. On the other hand, if the priority is to improve quality in cases where delays are not critical, then convolution neural networks in the Fourier space should be used. These networks have a response time of 140 ms and are of significant interest.

As the world population grows, fulfilling the need for biomaterials in the healthcare system becomes increasingly important. Biomaterials, which include metals, polymers, ceramics, and composites, play an important role in the creation of medical devices that improve people's lives. The European Society for Biomaterials described biomaterials as non-biological materials used in medical devices to interact with biological systems. This definition has developed to encompass materials that treat, assess, or replace tissues or bodily functions. Biocompatibility, as defined by the FDA, is a key feature of biomaterials, as is the requirement to fulfil design requirements such as mechanical performance, geometry, and electrical control. Over the last decade, advances in regenerative medicine and tissue engineering have boosted biomaterials' usage in medical applications dramatically. Despite its promise, scientists, engineers, and physicians continue to face significant challenges due to the complexity of biomaterials. Biomaterials have various benefits, including biodegradability, non-toxicity, and biocompatibility, making them extremely useful for replacing, sustaining, or improving biological activities in damaged tissues. They are used in a wide range of applications, including tissue engineering implants, human tissue healing and regeneration, medication delivery systems, and biosensors. This study gives insights into the fundamental characteristics, case studies, and ethical issues associated with the usage and use of biomaterials, further examining their potential and significance in healthcare and medicine.

The studied solar pot is a recent invention, which gained a utility model protection in 2021 from the Hungarian Intellectual Property Office under patent number 5489. The device is made for environmentally friendly cooking or heating (by utilizing solar energy) of foods and liquids. Its structure is similar to a double pipe heat exchanger, it has an outer mantle and an inner cooking tank. The goals of the paper are proposing a new physically-based mathematical model describing the solar pot and carrying out computer experiments with it, assembling an experimental system of the pot connected with a solar collector and performing measurements on it. Based on the results, the solar pot can successfully be used for cooking or sterilizing foods or liquids during the studied time period, in Hungary.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

This paper is focused on typical rural settlements in the Stara Planina Mountain area in Serbia. They are distinguished by their authenticity, identity and character, and they have still not been destroyed by inappropriate development as is the case in some other mountain areas in Serbia, where the effects of urbanization, globalization and homogenization are obvious. Consequently, there is a need to prevent these effects in mountain areas where there is a threat of disbalance between development and the inherited natural and cultural values. The paper starts from several important concepts that relate contemporary approaches to cultural heritage preservation, place morphology and planning future development. The concept definitions from recent documents from related fields are used. These concepts are then applied to the area of Stara Planina Mountain and its rural settlements. The necessity for an integrative approach to planning this area with significant natural and anthropogenic potential is pointed out, including its integration into international programs of sustainable development.

Abstract: Transcription factors are crucial pre-transcriptional regulatory mechanisms that can modulate the expression of downstream genes by binding to their promoter regions. DOF (DNA binding with One Finger) proteins are a unique class of transcription factors with extensive roles in plant growth and development. Our previous research indicated a decrease in iron content in chlorotic bamboo leaves. However, to our knowledge, genes related to iron metabolism pathways in bamboo species have not yet been studied. Therefore, in the current study, we identified iron metabolism-related (IMR) genes in bamboo and determined the transcription factors that significantly influence them. Among these, DOFs were found to have widespread effects and potentially significant impacts on their expression. We identified specific DOF members in Dendrocalamus latiflorus with binding abilities through homology with Arabidopsis DOF proteins, and established connections between some of these members and IMR genes using RNA-seq data. Additionally, molecular docking confirmed the binding interactions between these DlDOFs and the DOF binding sites in the promoter regions of IMR genes. The co-expression relationship between the two gene sets was further validated using q-PCR experiments. This study paves the way for research into iron metabolism pathways in bamboo and lays the foundation for understanding the role of DOF transcription factors in D. latiflorus.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) continues to be a global threat due to its ability to evolve and generate new subvariants, leading to new waves of infection. Additionally, other coronaviruses like Middle East respiratory syndrome coronavirus (MERS-CoV, formerly known as hCoV-EMC) which first emerged in 2012, persists and continues to present a threat of severe illness to humans. The continued identification of novel coronaviruses, coupled with the potential for genetic recombination between different strains, raises the possibility of new coronavirus clades of global concern emerging. As a result, there is a pressing need for pan-CoV therapeutic drugs and vaccines. After extensive optimization of an HCV protease inhibitor screening hit, a novel 3CLPro inhibitor (MK-7845) was discovered and subsequently profiled. MK-7845 exhibited nanomolar in vitro potency with broad spectrum activity against a panel of clinical SARS-CoV-2 subvariants and MERS-CoV. Furthermore, when administered orally, MK-7845 demonstrated a notable reduction of viral burdens by &gt;6 log orders in the lungs of transgenic mice infected with SARS-CoV-2 (K18-hACE2 mice) and MERS-CoV (K18-hDDP4 mice).

The continuous casting process of helical fiber reinforced metal matrix composites was proposed, and the experimental equipment was designed and manufactured. The relationship model be-tween the process parameters and the helical shape of the fibers in the metal matrix is analyzed by differential geometry. Helical carbon fiber reinforced lead matrix composites were prepared under different conditions. When the melting temperature and cooling intensity were increased, the helical radius of helical carbon fiber in lead matrix was increased. When the fiber rotation speed was increased, the helical radius was decreased, and the helical pitch was de-creased proportionally. The experimental results are consistent with the process model. Carbon fiber rein-forced aluminum composites were prepared. Scanning electron microscopy showed that the infiltration between the aluminum matrix and the carbon fiber was not complete. As the volume fraction of carbon fiber which was added in composites is too small, the mechanical properties of the composites have not been significantly improved.

This article presents an innovative approach to the design of a safe adaptive backstepping control system. Tailored specifically for underactuated marine robots, the system utilizes simple sensors for enhanced practicality and efficiency. Given their operation in diverse oceanic environments fraught with various sources of uncertainties, ensuring the system's safe and robust behavior holds paramount importance in the control literature. To address this concern, this paper introduces a control strategy designed to ensure robustness at both the kinematic and dynamic levels. By emphasizing the compensation for the system uncertainties, the design integrates a straightforward fuzzy system structure. To further ensure the system's safety, a funnel surface is defined, followed by the design of a suitable nonlinear sliding surface as a function of the funnel and tracking error. Specifically leveraging the Lyapunov function, the study formally establishes the Semi-globally Practically Finite-time Stability of the closed-loop system, validated through simulations conducted on underactuated marine robots.

Several types of guided bone regeneration materials are available with various properties and clinical indications. Among them, dentin-derived matrix from extracted teeth is an excellent alternative to traditional graft materials, such as allografts and xenografts. Different clinical preparation protocols exist: block form versus powder form, demineralized versus non-demineralized form. Out of these methods, demineralization protocols for dentin-derived matrix from extracted teeth have been noted for a wide range of successful clinical outcomes. The purpose of this animal study was to find out the most effective method of demineralizing dentin-derived matrix to result in the highest regenerative ability in the bone graft material in rabbit calvaria. The study conducted a comparative histomorphometric analysis of four groups in distinguished matrix conditions: a control group without graft placement, a non-demineralized dentin-derived matrix graft placement group, a 15-minute demineralized dentin-derived matrix graft placement group, and a 30-minute demineralized dentin-derived matrix graft placement group. Regenerative processes were evaluated three times at 2, 4, and 8 weeks post-graft placement. These groups of rabbits were evaluated randomly in a blinded setting to prevent bias. Among the four groups compared, the group with a 15-minute demineralized dentin-derived matrix graft showed the most efficient bone regeneration in the histomorphometric analysis. Based on this animal study, it was apparent that a 15-minute demineralization of dentin-derived matrix is the preferred preparation protocol to maximize the regenerative potential in the matrix.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

Cocoa (Theobroma Cacao, L.) represents an important market that gained relevance and became an esteemed commodity thanks to cocoa powder, chocolate, and other related products. This work has analyzed 59 cocoa powder samples from the European market. Three distinct subgroups were identified: organic or conventional, alkalized or not alkalized, and raw or roasted processing. The impact of the technological process was evaluated on the pH, color, and compositional traits, as content of biogenic amines and salsolinol. The phenolic fraction was also investigated trough both common and emerging methods. Results depict that the influence of the agronomical practices (organic/conventional) did not affect significatively (p&lt;0.05) the composition of cocoa powders; similarly, the roasting process was not discriminative for the compounds traced. On the other hand, the alkalinization process greatly impacted on color, and pH, no matter of cocoa provenience, obtention, or other processes, also resulting reducing the phenolic fraction of treated samples. Principal components analysis confirmed that the alkali process acts on pH, color, and phenolic composition, but not on other bioactives molecules (BAs and salsolinol). All samples resulted safe while alkalized powders have a great reduction in beneficial biocompounds. A novel strategy could be to emphasize non-alkalized powders in the label, to meet the demand for more beneficial products.

Oral squamous cell carcinoma (OSCC) is a highly prevalent and aggressive malignancy, with mortality rates that reach 60%, mainly due to an excessive diagnostic delay. MiRNAs, a class of crucial epigenetic gene-expression regulators, have emerged as potential diagnostic biomarkers, with >200 molecules reported to be dysregulated in OSCC. We had previously established an in silico methodology for the identification of the most disease-specific molecules by bridging genetics and epigenetics. Here, we identified the stage-specific miRNAs that govern the asymptomatic early stages of oral tumorigenesis by exploiting the reverse interplay between miRNA-levels and their target-genes’ expression. Incorporating gene expression data from our group’s experimental hamster model of sequential oral oncogenesis, we bioinformatically detected the miRNAs that simultaneously target/regulate >75% of the genes that are characteristically upregulated or downregulated in the consecutive stages of hyperplasia, dysplasia and early-invasion OSCC, while exhibiting the opposite expressional dysregulation in OSCC-derived tissue and/or saliva specimens. We found that all stages share the downregulation of miR-34a-5p, miR124-3p, and miR-125b-5p, while miR-1-3p is underexpressed in dysplasia and early-invasion. Malignant early-invasion stage is distinguished by the downregulation of miR-147a and the overexpression of miR-155-5p, miR-423-3p and miR-34a-5p. The identification of stage-specific miRNA molecules may facilitate their utilization as biomarkers for presymptomatic OSCC diagnosis.

Estimating the ocean’s subsurface thermohaline information from satellite measurements is essential for understanding ocean dynamics and El Niño phenomenon. This paper proposes an improved double-output Residual Neural Network (DO-ResNet) model to concurrently estimate the ocean subsurface temperature (OST) and ocean subsurface salinity (OSS) in the tropical Western Pacific using multi-source remote sensing data, including sea surface temperature (SST), sea surface salinity (SSS), sea surface height anomaly(SSHA), sea surface wind (SSW), and geographical information (including longitude (LON) and latitude (LAT)). In the model experiment, Argo data were used to train and validate the model, and the root mean square error (RMSE), normalized root mean square error (NRMSE) and coefficient of determination (R²) were employed to evaluate the model's performance. The results showed that the sea surface parameters selected in this study have a positive effect on the estimation process, and the average RMSE and R² values for estimating OST (OSS) by the proposed model are 0.34 °C (0.05 psu) and 0.91 (0.95), respectively. Under the data conditions considered in this study, DO-ResNet demonstrates superior performance relative to the extreme gradient boosting model, random forest model, and artificial neural network model. Additionally, this study evaluates the model’s accuracy by comparing its estimations of OST and OSS across different depths with Argo-derived data, demonstrating the model's ability to effectively capture the most spatial features, and by comparing NRMSE across different depths and seasons, the model displays strong seasonal adaptability. In conclusion, this research introduces a novel artificial intelligence technique for estimating OST and OSS in the tropical Western Pacific Ocean.

The normal growth and development of skeletal muscle is essential for the health of the body. The regulation of skeletal muscle by intestinal microorganisms and their metabolites has been continuously revealed. Acetate is the predominant short-chain fatty acid synthesized by gut microbiota through the fermentation of dietary fiber, however, the underlying molecular mechanisms governing the interaction between acetate and skeletal muscle during rapid growth stage remain to be further elucidated; Here, specific pathogen-free (SPF) mice, germ-free (GF) mice, and germ-free mice supplemented with sodium acetate (GS) were used to evaluate the effects of acetate on skeletal muscle growth and development of young mice with gut microbiota deficiency; We found the concentration of serum acetate, body mass gain, succinate dehydrogenase activity and expression of myogenesis maker gene of skeletal muscle in the GS group was higher than GF group following sodium acetate supplement. Furthermore, the transcriptome analysis revealed that acetate activated biological processes regulating skeletal muscle growth and development in GF group that are inhibited due to gut microbiota deficiency. In vitro experiment, we proved that acetate up-regulated Gm16062 to promote skeletal muscle cell differentiation; Overall, our findings proved that acetate promote skeletal muscle growth and development in young mice via increase Gm16062 expression.

Phased injection of natural gas into internal combustion marine engines is a promising solution for optimizing performance and reducing harmful emissions, particularly unburned methane, a potent greenhouse gas. This innovative practice distinguishes itself from continuous injection because it allows for more precise control of the combustion process with only a slight increase in system complexity. By synchronizing the injection of natural gas with the intake and exhaust valve opening and closing times while also considering the gas path in the manifolds, methane release into the atmosphere is significantly reduced, making a substantial contribution to efforts to address climate change. Moreover, phased injection improves the efficiency of marine engines, resulting in reduced overall fuel consumption, lower fuel costs, and increased ship autonomy. This technology has been tested on a single-cylinder, large-bore, four-stroke research engine designed for marine applications, operating in dual-fuel mode with diesel and natural gas. Performance was compared with that of the conventional continuous feeding method. Evaluation of the effect on equivalent CO2 emissions indicates a potential reduction of up to approximately 20%. This reduction effectively brings greenhouse gas emissions below those of the diesel baseline case, especially when injection control is combined with supercharging control to optimize the air-fuel ratio.

In numerical simulations, achieving high accuracy without significantly increasing computational costs is often challenging. To address this, this paper presents an improved finite volume weighted essentially non-oscillatory (WENO) scheme tailored for applicability in computational fluid dynamics (CFD) and implemented in the flow solver NUAA-Turbo for simulating turbomachinery flows using both RANS and RANS/LES coupling. Firstly, the new WENO scheme is validated against classic numerical test cases to assess its stability and reliability in handling discontinuities, the Double problem, and Raleigh-Taylor (RT) instability issues. Compared to the original format, this enhanced finite volume WENO scheme demonstrates superior stability near discontinuities and resolves flow features with the same grid resolution more effectively. Next, for engineering applications related to turbomachinery, such as compressor and turbine characteristics, computations are performed using RANS, and the results obtained using WENO-ZQ3 and WENO-JS3 are compared. Finally, the new fifth-order WENO scheme is applied to RANS/LES coupled simulations of turbine wakes and film cooling. The results show that the enhanced finite volume WENO scheme offers improved stability and accuracy in engineering applications, allowing for high-precision calculations with fewer grid points to capture more detailed flow physics, thereby reducing computational costs in aerodynamic applications.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

To secure logic circuits against the illegal copying the insertion of the so-called key bit inputs using XOR/XNOR gates has been proposed in . The inserted gates modify (lock) the behavior of the original circuit and only the correct choice of the secret key bits guarantees the equivalent behaviour of the locked circuit to the original circuit. To break this kind of security, i.e. to find the secret key bits, there was a SAT solver based attack proposed in . The aim of this work is to experimentally verify this attack on several locked circuits with various number of primary inputs and outputs and with various number of gates. Except for the random placement of the key gates we evaluate also the positioning with chaining elimination. The obtained and presented results show that we were able to unlock 10 of 11 circuits within few minutes on a common PC.

Intermetallic compounds are increasingly being expected to utilize in tribological environments, but to date the works are hindered by insufficient ductility at low and medium temperature. This paper presents a novel multiphase intermetallic alloy with the chemical composition of Mo-40Ni-13Si (at.%). Microstructure characterization reveals that a certain amount of ductile Mo phases formed during the solidification process of ternary Mo-Ni-Si alloy melt, which is undoubtedly beneficial to the ductility improvement of intermetallic alloy. Tribological properties of the designed alloy, including wear resistance, friction coefficient and metallic tribological compatibility, were evaluated under dry sliding wear test conditions at room temperature. Results suggested that the multiphase alloy possesses an excellent property for room-temperature wear applications, which is attributed to the unique microstructural features and thereby good combination in hardness and ductility. The corresponding wear mechanism is also reported by observing the worn surface, subsurface and wear debris of alloy, which to be found is soft abrasive wear.

With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) is one of the important information technologies in the Internet of Things; it integrates multi-technology to detect and gather information in a network environment by mutual cooperation, using a variety of methods to process and analyze data, implement awareness, and perform tests. This paper mainly researches the localization algorithm of sensor nodes in a wireless sensor network. Firstly, a multi-granularity region partition is proposed to divide the location region. In the range-based method, the RSSI (Received Signal Strength indicator, RSSI) is used to estimate distance. The optimal RSSI value is computed by the Gaussian fitting method. Furthermore, a Voronoi diagram is characterized by the use of dividing region. Rach anchor node is regarded as the center of each region; the whole position region is divided into several regions and the sub-region of neighboring nodes is combined into triangles while the unknown node is locked in the ultimate area. Secondly, the multi-granularity regional division and Lagrange multiplier method are used to calculate the final coordinates. Because nodes are influenced by many factors in the practical application, two kinds of positioning methods are designed: the unknown node is in the positioning unit or not. When the unknown node is on the side of the positioning unit, we use the method of vector similarity. Moreover, we use the centroid algorithm to calculate the ultimate coordinates of unknown node. When the unknown node is not on the side of the positioning unit, we establish a Lagrange equation containing the constraint condition to calculate the first coordinates. Furthermore, we use the Taylor expansion formula to correct the coordinates of the unknown node. In addition, this localization method has been validated by establishing the real environment.

The electroencephalogram (EEG) is a record of brain activity. Brain Computer Interface (BCI) technology formed by the EEG signal has become one of the hotspots at present. How to extract the feature signal of EEG is the most basic research of BCI technology. In this paper, A new method of recognizing fatigue, conscious, concentrated state of human brain is proposed by the combination of discrete wavelet transform and the neural network based on EEG signal. First of all, the law signal is preprocessed by the wavelet denoising method because the law EEG signal contains a large number of high frequency noise, which is decomposed into multi-layer high frequency signal and low frequency signal. thus, δ wave, θ wave, α wave, β wave are obtained by the wavelet transform. And then, frequency band energy of the different wave is regards as the feature signal of EEG. In the experiment, the feature signal is classified by radial basic function (RBF) and annealed chaotic competitive learning network (ACCLN). RBF and ACCLN networks are trained with 500 sets of sample data and are tested by 100 sets of samples in different mental states. The experimental results show that the average accuracy of RBF network under three conditions are 88.75%, 88.25%, 88.5%, respectively, and the correct rate of ACCLN network is 97%, 98%, 98%, respectively.

This study aimed to identify whether gyrate atrophy of the choroid and retina (GACR) heterozygous individuals have possible clinical manifestations and to explore the potential pathogenic mechanism. In this retrospective study, we surveyed a two-generation pedigree of an individual diagnosed with GACR. Two family members underwent ophthalmological, hematologic, and genetic tests. An arginine-restricted diet with vitamin B6 supplementation was implemented; clinical assessments were repeated every 3 months during follow-up. Relative OAT mRNA expression was determined using real-time quantitative polymerase chain reaction. The 19-year-old compound heterozygous daughter (OAT: c.1186C&gt;T; c.748C&gt;T), had bilateral high myopia, posterior staphyloma, chorioretinal atrophy, macular abnormalities, and elevated hematologic ornithine. The 54-year-old heterozygous mother (OAT: c.1186C&gt;T), presented with bilateral severe myopia, asymmetric posterior staphyloma, retina and choroidal capillary layer atrophy, retinal pigment epithelium abnormalities, and mildly elevated hematologic ornithine. Compared to normal individuals, the daughter and mother had 29% and 46% relative OAT mRNA expression, respectively (P&lt;0.001). We believe that this is the first report of a carrier of one OAT variant allele with mild phenotypes, suggesting that family members should be aware of the possible involvement of autosomal recessive conditions. Additional data suggests nonsense mediated decay-initiated mRNA degradation may cause GACR.

Early discharge after childbirth has led to a rise in neonatal readmission, becoming a major concern in recent decades. Our research aimed to identify the risk factors and incidence of neonatal readmission, as well as explore preventive measures. Our study at the Clinical Hospital of Pediatrics in Ploiești, Romania included 108 neonates admitted during the neonatal period. This accounted for 2.06% of all admissions (5226). The most prevalent cases were malnutrition (25%), fever (20.3%) and bronchiolitis (17.5%). Diarrhea and infectious gastroenteritis were also observed (14.8%), along with acute rhinoconjunctivitis (9.2%) and late onset sepsis (3.7%). No deaths were recorded. The most significant characteristics identified were number of children (p&lt;0.001) and age at maternity discharge (p&lt;0.001). By following the prevention rules, malnutrition, feeding errors, and infections can be avoided. This includes practicing proper hand hygiene for both mothers and medical staff, as well as educating and demonstrating to mothers the benefits of breastfeeding. In addition, all newborns discharged from the maternity ward should benefit from follow-up at 7-10 days of life. Our results confirm the effectiveness of a multidisciplinary team and endorse promoting breastfeeding. Implementing quality control measures and regularly evaluating the surveillance program will help improve its effectiveness.

Wearable technology has been proposed as a potential tool to change the way of human life, such as the smart bracelet and the Google Glass. In the wearable technology, the inertial sensor has great significance in tracking the object movements. The paper focused on detecting the movements of user’s finger based on the inertial sensor to give the control signals. Firstly, the attitude matrix, which represented the transformation relation of carrier coordinate system and the navigation coordinate system, was obtained. Secondly, the attitude matrix was expressed based on the quaternions. Thirdly, the finger gesture was processed by the attitude matrix to get the attitude angle. Finally, the robot was controlled by attitude angle to make the moving action. The experimental results showed the detection of the finger movement is effective.

In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

(1) Background: The RDW-CV has predictive value in many pregnancy-related conditions. Re-search question: Can the RDW-CV be utilized predictively in pregnant patients with thrombo-philia? Aim of the study: To carry out a detailed analysis of the RDW-CV in pregnant patients with treated thrombophilia as compared with pregnant patients without thrombophilia who de-livered via cesarean section at term. (2) Methods: We studied 160 pregnant patients, including 80 pregnant patients with treated thrombophilia in the study group, and another 80 patients of a similar age and parity. The patients were referred to our hospital for delivery at term by means of a cesarean section between 1/10/2017 and 1/12/2021. Every patient received a sonogram during the first 1–2 days after the cesarean section, and their uterine evaluation was interpreted using the PUUS (Postpartum Uterine Ultrasonographic Scale). (3) Results: Our PUUS≥1 pregnant and postpartum patients with treated thrombophilia were the only group with an RDW-CV value over 14. No deep vein thrombosis was observed during hospitalization, showing that the antico-agulant treatment was necessary and effective. An RDW-CV of 14.5 was the highest value in the Rh-negative group of pregnant patients with treated thrombophilia. An RDW-CV of 14.48 was the highest level in the Rh-negative postpartum patients with treated thrombophilia. (4) Conclu-sion: An RDW-CV of ≥14 can predict uterine hematometra (PUUS≥1). The RDW-CV values were higher in Rh-negative patients.

The study of the change in entropy during the formation of stars in collapsing molecular clouds is an important area of research in astrophysics. As the cloud decreases in size, the presence of gases leads to an increase in entropy. However, the extent of this change in entropy is influenced by the amount of space available for the gases. In this scientific investigation, I conduct a detailed analysis of entropy on a small scale within the contracting cloud, following the principles of the second law of thermodynamics. Initially, my focus is on a turbulent cloud composed of N particles with a mass of M, which collapses under the force of gravity. It becomes clear that in order for the collapse to occur, gravitational energy must overcome other pressure forces that oppose it. This process results in the rapid movement of particles within the cloud, ultimately leading to a change in entropy

With the increasing concern of environment, the energy-efficiency scheduling of manufacturing industry is becoming urgent and popular. In turning processes, both spindle speed and processing time can affect the final energy consumption and thus the spindle speed and scheduling scheme need to be optimized simultaneously. Since the turning workshop can be regarded as the flexible flow shop, this paper formulates a mixed integer linear programming model for energy-efficient scheduling of flexible flow shop. Accordingly, a new decoding method is developed by considering of the optimization of spindle speed and scheduling scheme simultaneously, and an estimation of distribution algorithm adopting the new decoding method is proposed to solve large-size problems. The parameters of this algorithm are determined by statistical technique with a simplified practical case. In order to validate the proposed method, a case from practical factories is studied, in which the makespan can be shortened by 25.22%, and the consumed energy can be saved by 5.48%. These results demonstrate the effectiveness of the proposed mathematical model and algorithm.

This article delves into the complex landscape of Bitcoin halving events, analyzing the historical context and implications of these pivotal occurrences within the cryptocurrency ecosystem and on its sustainability within the landscape of financial technologies. Through an examination of past halving events in 2012, 2016, and 2020, this study meticulously scrutinizes the conditions and prices of Bitcoin before and after each halving. By synthesizing data and trends from previous events, this article aims to uncover patterns and insights that illuminate the impact of Bitcoin halving on market dynamics and sustainability, movement of the price level, reached peaks and price troughs. Furthermore, this research presents a comparative analysis of past halving events, drawing parallels and distinctions to elucidate the evolving nature of Bitcoin's price movements and market sentiment surrounding these milestone events. Looking towards the future, this study estimates predictions and expectations for the upcoming Bitcoin halving. By unraveling the intricate relationship between Bitcoin halving events and market behavior, this article seeks to provide a comprehensive understanding of the broader implications for Bitcoin's trajectory and the evolving landscape of the cryptocurrency market and its sustainability.

Multimodal remote sensing data classification can enhance the model’s ability to distinguish land features through multimodal data fusion. In this context, how to help models understand the relationship between multimodal data and target tasks is the focus of researchers. Inspired by human feedback learning mechanisms, causal reasoning mechanisms, and knowledge induction mechanisms, this paper integrates causal learning, reinforcement learning, and meta learning into a unified remote sensing data classification framework and proposed the causal meta-reinforcement learning (CMRL). First, based on feedback learning mechanisms, we have overcome the limitations of traditional implicit optimization of fusion features and customized a reinforcement learning environment for multimodal remote sensing data classification tasks. Through feedback interactive learning between agents and the environment, we help them understand the complex relationships between multimodal data and labels, thereby achieving full mining of multimodal complementary information. Second, based on the causal inference mechanism we designed causal distribution prediction action, classification reward, and causal intervention reward, capturing pure causal factors in multimodal data and cutting off false statistical associations between non-causal factors and class labels. Finally, based on the knowledge induction mechanism, we designed a bi-layer optimization mechanism based on meta-learning. By constructing a meta training task and meta validation task simulation model in the generalization scenario of unseen data, we helped the model induce cross-task shared knowledge, thereby improving its generalization ability for unseen multimodal data. The experimental results on multiple sets of multimodal datasets show that the proposed method achieved state-of-the-art performance in multimodal remote sensing data classification tasks.

Moso bamboo is famous for fast growing and biomass accumulation, as well as high annual output for timber and bamboo shoots. These high outputs require high nutrient inputs to maintain and improve stand productivity. Soil nitrogen (N), phosphorus (P) and potassium (K) are important micronutrients for plant growth and productivity. Due to high variability of soils, analysing spatial patterns of soil N, P and K stocks is necessary for scientific nutrient management in Moso bamboo forests. In this study, soils were sampled from 138 locations across Yong’an City and ordinary kriging was applied for spatial interpolation of soil N, P and K stocks. Soil N stock showed a strong spatial dependence while soil N and P stocks presented a moderate spatial dependence, indicating soil N was mainly controlled by intrinsic factors while soil N and P stocks were controlled by both intrinsic and extrinsic factors. Different spatial patterns were observed for soil N, P and K stocks across the whole study area, indicating that fertilizations with different ratios of N:P:K should be applied for different sites to maintain and improve stand productivity. The total soil N, P and K stocks within 0-60 cm were 0.624, 0.020 and 0.583 Tg, respectively.

Museums are called to respond to contemporary challenges and contribute to the formation of more progressive societies. One of the major challenges of our time is climate change and museums could construct cocreated narratives around climate and implement targeted actions for the audiences through their sensorial and affective experiences. More specifically, Geology and Palaeontology museums are repositories of knowledge on geoheritage and geoconservation, recognized for their scientific, pedagogical, cultural and recreational values. The educational potential of geological and paleontological exhibits could be used in informal education activities regarding the climate emergency. Taking the above into consideration, this study focuses on both the creation and evaluation of an educational program for the Natural History Museum of Arsakeio Campus at Psychicko.

In this paper, we study the semilinear pseudo-parabolic equations $\displaystyle u_{t} - \triangle_{\mathbb{B}}u - \triangle_{\mathbb{B}}u_{t} = \left|u\right|^{p-1}u$ on a manifold with conical singularity, where $\triangle _{\mathbb{B}}$ is Fuchsian type Laplace operator investigated with totally characteristic degeneracy on the boundary $x_{1} = 0$. Firstly, we discuss the invariant sets and the vacuum isolating behavior of solutions with the help of a family of potential wells. Then, we derive a threshold result of existence and nonexistence of global weak solution: for the low initial energy $J(u_{0})<d$, the solution is global in time with $I(u_{0}) >0$ or $\displaystyle\Vert \nabla_{\mathbb{B}}u_{0}\Vert_{L_{2}^{\frac{n}{2}}(\mathbb{B})} = 0$ and blows up in finite time with $I(u_{0}) < 0$; for the critical initial energy $J(u_{0}) = d$, the solution is global in time with $I(u_{0}) \geq0$ and blows up in finite time with $I(u_{0}) < 0$. The decay estimate of the energy functional for the global solution and the estimates of the lifespan of local solution are also given.

The Qiushuwan Cu-Mo deposit, located in the East Qinling molybdenum belt, which is a major mining site recognized for its enormous reserves of medium-sized molybdenum. In order to enhance our comprehension and ascertain supplementary mineral resources, it is critical to conduct an in-depth investigation of both the deep and peripheral regions. The primary goal of this study is to investigate the Qiushuwan Copper Molybdenum Mine, which is located in Zhenping County, Henan Province. The spread spectrum-induced polarization (SSIP) method is utilized as a means of conducting mining exploratory analysis. Significant findings have been obtained through the collection of SSIP data, geological analysis, and electrical parameter study of rock and ore samples along profile-80. By conducting a meticulous examination of the SSIP data at suitable frequencies, two prominent conductive ore bodies, specifically C2 and C4, have been successfully discovered. C2 exhibits a correlation with granite porphyry and molybdenum veins, while C4 is linked to a skarn deposit that contains a concentration of copper ore. The spatial differences in conductivity within the research area have been precisely characterized using resistivity models obtained from the SSIP data. The precision and dependability of our conclusions have been confirmed through the integration of borehole data and the matching of geological sections with inversion models. The recovered core samples show a diverse range of minerals, containing both valuable ores and minerals that have undergone alteration. Pyrite constantly appears with molybdenite in the majority of samples. The aforementioned results provide a strong foundation for future exploration initiatives and sustainable resource exploitation, enabling informed decision-making in the effective use and administration of natural resources. This study adds to the existing body of knowledge on the Qiushuwan Cu-Mo deposit and improves exploration methods in the region by utilizing the SSIP approach. The findings are a useful asset for geologists, mining experts, and stakeholders, offering essential knowledge for future exploration and sustainable utilization of resources.

Brain aging causes a wide variety of changes at molecular and cellular levels, leading to the decline of cognitive functions and increased vulnerability to neurodegenerative disorders. The research aimed at understanding the aging of the brain has made much progress in recent decades. Technological innovations such as single-cell RNA-sequencing (scRNA-seq), proteomic analyses, and spatial transcriptomic analyses have facilitated the research on the dynamic changes occurring within neurons, glia, and other cells along with their impacts on intercellular communication during aging. In this review, we introduce recent trends of how neurons and glia change during aging and discuss the impact of the brain microenvironment such as the blood-brain barrier (BBB).

Two interesting compounds such as quaternary ammonium lignin(QAL) and 2-ethylhexyl phosphoric acid mono-2-ethylhexyl ester (P507) were synthesized as ionic liquids(QP-ILs) for the extraction of metal ions. The extraction behavior of Co(II) and Ni(II) from chloride solution was compared between QP-ILs and P507. The results showed that the extraction rates of Co(II) and Ni(II) in the two solutions varied with the extraction conditions, but QP-ILs has stronger extractability for cobalt than P507, while Ni is on the contrary. Under the same conditions, the Co/Ni separation performance(βCo/Ni) in QP-ILs is superior to that in p507. At pH4.0, 55℃, concentration of 20%, extraction time of 10 minutes, the βCo/Ni of QP-ILs reached to 2703, while that of P507 was only 164. In conclusion, QP-ILs was more efficient than P507 for separating Co from mixed solutions.

Clinical, pathological, and imaging evidence in multiple sclerosis (MS) shows that inflammation starts early and progresses with age. B cells play a central role in this process, contributing to cytokine production, defective regulatory functions, and abnormal immunoglobulin production, even in the central nervous system. Anti-CD20 (aCD20) therapies, which deplete CD20+ B cells, are effective for both relapsing-remitting (RR) and progressive-relapsing (PR) MS. While effective against MS symptoms and lesions detectable by magnetic resonance imaging, aCD20 therapies can reduce the immune response to COVID-19 vaccination. By using high-parameter flow cytometry, we examined the antigen-specific (Ag+) immune response six months post-third COVID-19 mRNA-vaccination in MS patients with RR and PR forms on aCD20 therapy. Despite lower Ag+ B cell responses and lower levels of anti-SARS-CoV2, both total and neutralizing antibodies, RR and PR patients developed strong Ag+ T cell responses. We observed similar percentages and numbers of Ag+ CD4+ T cells and high proportion of Ag+ CD8+ T cells, with slight differences in T cell phenotype and functionality, that however suggested the presence of differences in immune responses driven by age and disease severity.

Lignocellulosic biomass, an abundant and renewable resource, serves as a crucial raw material for the production of biofuels, biochemicals, and various value-added products. This paper aims to develop and optimize a mild alkaline treatment of sawdust assisted by ultrasound, along with enzymatic hydrolysis of the pretreated material. The sonochemical pretreatment with alkali emerged as the optimal approach to enhance the susceptibility of cellulose to subsequent enzymatic hydrolysis, thereby increasing the yield of reducing sugars. A comparative study was performed using various ultrasonic applicators (horn and bath) and conventional assisted alkaline pretreatment. The ultrasonic assisted pretreatment revealed a higher delignification as 68% (horn) and 57% (bath) comparing with conventional pretreatment. Processes were optimized using a statistical analysis based on a 23 factorial design. The ratio between sawdust and alkanine solution (RSL = 0.5–1.5 g/100 mL), US amplitude (A = 20–60%), and working temperature (t = 30–50 °C) were selected as process factors. The optimal operating conditions to maximize the reducing sugar yield (138.15 mg GE /gsubstrate) were found as following: solid/liquid ratio RSL,opt = 1.25 g/100 mL, US amplitude Aopt = 60%, and and pretreatment temperature topt = 50 °C. The overall outcomes clearly confirmed the intensification of delignification by ultrasound assisted alkaline pretreatment