Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC) are constantly threatening global public health. With no end date, the pandemic still persists with the emergence of novel variants that threaten the effectiveness of diagnostic tests and vaccines. Mutations in the Spike surface protein of the virus are regularly observed in the new variants, potentializing the emergence of novel viruses with different tropism from the current ones, which may change the severity and symptoms of the disease. Growing evidence has shown that mutations are being selected in favor of variants that are more capable of evading the action of neutralizing antibodies. In this context, the most important factor guiding the evolution of SARS-CoV-2 is its interaction with the host’s immune system. Thus, as current vaccines cannot block the transmission of the virus, measures complementary to vaccination, such as the use of masks, hand hygiene, and keeping environments ventilated remain essential to delay the emergence of new variants. Importantly, in addition to the involvement of the immune system in the evolution of the virus, we highlight several chemical parameters that influence the molecular interactions between viruses and host cells during invasion and are also critical tools making novel variants more transmissible. In this review, we dissect the impacts of the Spike mutations on biological parameters such as (1) increase of Spike binding affinity to hACE2; (2) bound time for the receptor to be cleaved by the proteases; (3) how mutations associate with increase of RBD up-conformation state in the Spike ectodomain; (4) expansion of uncleaved Spike protein in the virion particles; (5) increment of Spike concentration per virion particles; and (6) evasion of the immune system. These factors play key roles in the fast spreading of SARS-CoV-2 variants of concern, including the Omicron.

This paper describes the successful application of the Transformer model used in the natural language processing and vision tasks as a means of processing the time series of signals from gyroscope and accelerometer sensors for the classification of human activities. The Transformer model is based on deep neural networks with many layers which can generalize well on signals. All measured signals come from a smartphone placed in a waist bag. Activity prediction is sequence-to-sequence, each time step of the signal is assigned a designation of the performed activity. Emphasis is placed on attention mechanisms, which express individual dependencies between signal values within a time series. In comparison with another recent result, the recognition precision was improved from 89.67 percent to 99.2 percent. The transformer model should in the future be included among the top options in machine learning methods for human activity recognition.

The ratio of males to females with ASD is generally quoted as 4:1 though it is believed that there are biases preventing females being diagnosed and that the true ratio is lower. These biases have not been clearly identified or quantified. Starting with a clinical dataset of 1711 children <18 years old four different methods were employed in an inductive study to identify and quantify the biases and calculate the proportion of females missed. A mathematical model was constructed to compare the findings with current published data. The true male to female ratio appears to be 3:4. Eighty per cent of females remain undiagnosed at age 18 which has serious consequences for the mental health of young women.

As V2X technology develops, acute problems related to reliable and secure information exchange between network objects in real time appear. The article aims to solve the scientific problem of building a network architecture for reliable delivery of correct and uncompromised data within the V2X concept to improve the safety of road users, using blockchain technology and mobile edge computing (MEC). The authors present a formalized mathematical model of the system, taking into account the interconnection of objects and V2X information channels, and an energy-efficient algorithm of traffic offloading to the MEC server. The paper presents the results of application of blockchain technologies and mobile edge computing in the developed system, their description, evaluation of advantages and disadvantages of the implementation.

Sustainability is very important in business. The residential high-rise building all firms wanted to successful and sustainability in business. There is need the construction to completed low time, low cost and high quality in construction work. Therefore, real estate developers must find various strategies to use in construction projects to achieve goals and success of the firm. The purpose of this study was to indicate the very importance of knowledge management can lead to sustainability in business. Analyze 14 critical success to sustainability in residential high-rise building projects, collected questions from literature review, and survey in deep interview senior managers of 15 projects real estate development firms listed on the stock market of Thailand. Budget building more than 1000 million baht per project. From conceptual frame work five foundations integrated to knowledge management of critical success (KMITL PROCESS) used made tool survey in deep interview the critical success to sustainability in residential high-rise building project from project managers. Used IBM SPSS evaluated the critical success to sustainability. Found was one very important of critical success to sustainability, which was quality of products x̄ = 4.83. All 14 critical success to sustainability was found can applied made the knowledge management of critical success to sustainability in residential high-rise building project in firm. Especially in the field of construction managements project can used improve of all construction projects.

We show that an exponential income distribution will emerge spontaneously in a peer-to-peer economic network that shares the publicly available technology. Based on this finding, we identify the exponential income distribution as the benchmark structure of the well-functioning market economy. However, a real market economy may deviate from the well-functioning market economy. We show that the deviation is partly reflected as the invalidity of exponential distribution in describing the super-low income class that involves unemployment. In this regard, we find, theoretically, that the lower-bound u of exponential income distribution has a linear relationship with (per capita) unemployment compensation. In this paper, we test this relationship for the United Kingdom from 2001 to 2015. Our empirical investigation confirms that the income structure of low and middle classes (about 90% of populations) in the United Kingdom exactly obeys exponential distribution, in which the lower-bound u is exactly in line with the evolution of unemployment compensation.

Indonesia is an interesting case study for students of sustainable development and sustainable energy due to its ability to connect the multiple “worlds” it has become part of. Indonesia is an important bridge to Muslim countries, the voice of the Global South in the G20 and a main pillar of the 134-country-strong G77. Indonesia’s development trajectory is also key to the achievement of the Paris Climate Agreement as well as of the 2030 Agenda. Students can learn from how Indo-nesia address contradictions that would have been unsurmountable for other countries. Indone-sia’s energy transition offers helpful lessons, because of its aspiration to become a developed country by 2045. This goal is only possible when a country is able to effectively address barriers and caveats to sustainable energy. It is interesting how Indonesia focuses on silver linings and come up with pragmatic solutions to energy-related issues. This is followed by the “teaching guide,” which provides recommendations how the lessons from Indonesia can be embedded into a learning experience. The “learning activation approach” is introduced, which encourages stu-dents to systematically reflect on the complexity of selected contexts and understand this com-plexity by looking at the technical issues and processes that allow decision-making.

Peer-to-peer (P2P) energy trading is a new data-driven business model currently being trialed within the energy sector. Introducing P2P transactions to an essential service such as energy could have far-reaching implications for individuals and the grid. This paper raises considerations and questions from social, economic/markets and regulatory points of view, that should be understood and addressed by societies and policymakers. It does this by considering under what circumstances it is reasonable to conceptualize P2P energy trading as part of the sharing economy, and drawing parallels to the sharing economy experience in other sectors. In order to reap the full societal benefits, while avoiding considerable risks to infrastructure and individuals, a policy approach promoting dialogue and innovation is necessary. We suggest the regulatory sandbox is the most appropriate tool to achieve this and would help avoid the breakdown of trust between policymakers and platform companies observed in other sectors.

Paraphrase generation is an important yet challenging task in NLP. Neural network-based approaches have achieved remarkable success in sequence-to-sequence(seq2seq) learning. Previous paraphrase generation work generally ignores syntactic information regardless of its availability, with the assumption that neural nets could learn such linguistic knowledge implicitly. In this work we make an endeavor to probe into the efficacy of explicit syntactic information for the task of paraphrase generation. Syntactic information can appear in the form of dependency trees which could be easily acquired from off-the-shelf syntactic parsers. Such tree structures could be conveniently encoded via graph convolutional networks(GCNs) to obtain more meaningful sentence representations, which could improve generated paraphrases. Through extensive experiments on four paraphrase datasets with different sizes and genres, we demonstrate the utility of syntactic information in neural paraphrase generation under the framework of seq2seq modeling. Specifically, our GCN-enhanced models consistently outperform their syntax-agnostic counterparts in multiple evaluation metrics.

Why are pieces of spaghetti generally broken into three to ten segments instead of two as one thinks? How can one obtain the desired number of fracture segments? For these problems, in this paper a strand of spaghetti is considered an elastic rod, and the finite-element software ABAQUS is used to simulate the detailed fracture dynamics of the elastic rod. By changing the size (length and diameter) of the rod, the relevant data on the fracture limit curvature and the number of fractured segments of the elastic rod are obtained. The ABAQUS simulation results confirm the scientific judgment of B. Audoly and S. Neukirch (Fragmentation of rods by cascading cracks: Why spaghetti does not break in half. Phys Rev Lett 95: 095505). Using dimensional analysis to fit the finite-element data, two relations of the elastic rod fracture dynamics are obtained: (1) the relationship between the fracture limit curvature and the diameter, and (2) the relationship between the number of fracture segments and the diameter-length ratio. Results reveal that when the length is constant, the larger the diameter (the smaller the diameter-length ratio D/L), the smaller the limit curvature; and the larger the diameter-length ratio D/L, the fewer the number of fractured segments. The relevant formulations can be used to obtain the desired number of broken segments of spaghetti by changing the diameter-to-length ratio.

1) Background: Intellectual disability is more common in low- and middle-income countries than in high-income countries. Stigma and discrimination have contributed to barriers to people with intellectual disability accessing healthcare. As part of a larger study on caregiving of children with intellectual disability in urban Cape Town, South Africa, we interviewed a sub-group of families who had never used the intellectual disability services available to them, or who had stopped using them; 2) Methods: We employed a qualitative research design and conducted semi-structured interviews to explore the views and perspectives of parents and caregivers of children with intellectual disability who are not using specialised hospital services. We developed an interview guide to help explore caregivers’ and parents’ views; 3) Results: Results revealed that caregivers and parents of children with intellectual disability did not use the service due to financial difficulties, fragile care networks and opportunity costs, community stigma and lack of safety, lack of faith in services and powerlessness at effecting changes, and self-stigmatisation; 4) Conclusion: Current findings highlight a need for increased intervention at community level and collaboration with community-based projects to facilitate access to services, and engagement with broader issues of social exclusion.

Achieving sustainable management of forests in China is becoming increasingly important with more awareness and realization of the importance of forests in environmental protection. Forest certification, a market-based instrument to promote sustainable forest management, has been recognized by many countries including China. While landowners’ perception and perspective regarding this voluntary program have been well-documented in literature, how to motivate and incentivize landowners to participate in forest certification remained under-studied questions. With the face-to-face survey of landowners in Shandong, China, this study analyzed landowners’ willingness to accept compensation for participating in forest certification. Results indicated that landowners average accepted compensation, in terms of increased timber price, was about RMB120 (~$17.2)/m3 to have their forests certified. Results from multiple regression showed that the level of such compensation required for certification adoption was influenced by ownership size, owners’ demographics, certification program requirements, as well as importance placed on timber sale. These findings would inform policy-makers in designing compensation-related polices and establish incentive-based mechanisms to motivate landowners participate in forest certification programs in China.

Despite the long and extensive history of 3D technology, it has recently attracted the attention of researchers. This technology has become the center of interest of young people because of the real feelings and sensations it creates. People see their environment as 3D because of their eye structure. In this study, it is hypothesized that people lose their perception of depth during sleepy moments and that there is a sudden transition from 3D vision to 2D vision. Regarding these transitions, the EEG signal analysis method was used for deep and comprehensive analysis of 2D and 3D brain signals. In this study, a single-stream anaglyph video of random 2D and 3D segments was prepared. After watching this single video, the obtained EEG recordings were considered for two different analyses: the part involving the critical transition (transition-state) and the state analysis of only the 2D versus 3D or 3D versus 2D parts (steady-state). The main objective of this study is to see the behavioral changes of brain signals in 2D and 3D transitions. To clarify the impacts of the human brain’s power spectral density (PSD) in 2D-to-3D (2D_3D) and 3D-to-2D (3D_2D) transitions of anaglyph video, 9 visual healthy individuals were prepared for testing in this pioneering study. Spectrogram graphs based on Short Time Fourier transform (STFT) were considered to evaluate the power spectrum analysis in each EEG channel of transition or steady-state. Thus, in 2D and 3D transition scenarios, important channels representing EEG frequency bands and brain lobes will be identified. To classify the 2D and 3D transitions, the dominant bands and time intervals representing the maximum difference of PSD were selected. Afterward, effective features were selected by applying statistical methods such as standard deviation (SD), maximum (max), and Hjorth parameters to epochs indicating transition intervals. Ultimately, k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) algorithms were applied to classify 2D_3D and 3D_2D transitions. The frontal, temporal, and partially parietal lobes show 2D_3D and 3D_2D transitions with a good classification success rate. Overall, it was found that Hjorth parameters and LDA algorithms have 71.11% and 77.78% classification success rates for transition and steady-state, respectively.

A growing number of households benefit from the government subsidies to install renewable generation facilities such as PV panels, used to gain independence from the grid and provide cheap energy. In the Romanian electricity market, these prosumers can sell their generation surplus only at regulated prices, back to the grid. A way to increase the number of prosumers is to allow them to make higher profit by selling this surplus back into the local network. This would also be an advantage for the consumers, who could pay less for electricity exempt from network tariffs and benefitting from lower prices resulting from the competition between prosumers. One way of enabling this type of trade is to use peer-to-peer contracts traded in local markets, run at microgrid (μG) level. This paper presents a new trading platform based on smart peer-to-peer (P2P) contracts for prosumers energy surplus trading in a real local microgrid. Several trading scenarios are proposed, which give the possibility to perform trading based on participants’ locations, instantaneous active power demand, maximum daily energy demand and the principle of first come first served implemented in an anonymous blockchain trading ledger. The developed scheme is tested on a low-voltage (LV) microgrid model to check its feasibility of deployment in a real network. A comparative analysis between the proposed scenarios, regarding traded quatities and financial benefits is performed.

Background: Alzheimer’s disease (AD), the most threatening neurodegenerative diseases, is characterized by the loss of memory and language function, an unbalanced perception of space and other cognitive and physical manifestations. Pathology of the AD is characterized by neuronal loss, and the extensive distribution of senile plaques and neurofibrillary tangles (NFTs). The role of environment and the diet in the AD is being studied actively, and nutrition is certainly one of the main factors playing a prominent role in the prevention of neurodegenerative diseases. In this context, the relationship between dementia and wine use/abuse has received increased research interest in recent times, with varying and often conflicting results. Scope and approach: This review aims to critically summarize the most recent studies conducted to clarify the relationship between wine drinking and AD, as well as whether effects are influenced by quantity and/or frequency of drinking. Key findings and Conclusion: Overall, based on the interpretation of various studies, it can be concluded that there is no indication that light to moderate alcohol drinking is detrimental to cognition and dementia, and it is not possible to define whether alcohol could be used as a means to reduce risk of developing AD.

The transition towards a renewable energy system is essential in order to reduce greenhouse gas emissions. The increase in the share of variable renewable energy sources (VRES), which mainly comprise wind and solar energy, necessitates storage technologies by which the intermittency of VRES can be compensated for. Although hydrogen has been envisioned to play a significant role as a promising alternative energy carrier in a future European VRES-based energy concept, the optimal design of this system remains uncertain. In this analysis, a hydrogen infrastructure is posited that would meet the electricity and hydrogen demand for a 100% renewable energy-based European energy system in the context of 2050. The overall system design is optimized by minimizing the total annual cost. Onshore and offshore wind energy, open-field photovoltaics (PV), rooftop PV and hydro energy, as well as biomass, are the technologies employed for electricity generation. The electricity generated is then either transmitted through the electrical grid or converted into hydrogen by means of electrolyzers and then distributed through hydrogen pipelines. Battery, hydrogen vessels and salt caverns are considered as potential storage technologies. In the case of a lull, stored hydrogen can be re-electrified to generate electricity to meet demand during that time period. For each location, eligible technologies are introduced, as well as their maximum capacity and hourly demand profiles, in order to build the optimization model. In addition, a generation time series for VRES has been exogenously derived for the model. The generation profiles of wind energy have been investigated in detail by considering future turbine designs with high spatial resolution. In terms of salt cavern storage, the technical potential for hydrogen storage is defined in the system as the maximum allowable capacity per region. Whether or not a technology is installed in a region, the hourly operation of these technologies, as well as the cost of each technology, are obtained within the optimization results. It is revealed that a 100 percent renewable energy system is feasible and would meet both electricity demand and hydrogen demand in Europe.

We propose the traditional goal of cancer therapists to develop a single drug or drug combination that can, by itself, eliminate all cancer cells within a host has neglected potential treatments that may achieve curative outcomes by strategically combining agents that are individually effective but non-curative. We derive basic principles for such an approach from the eco-evolutionary dynamics of background extinctions in which a “first strike” reduces the size and heterogeneity of the initial population and is followed immediately by demographic and ecological “second strikes” that push the population below an extinction threshold. This proposed strategy appears identical to the empirically-derived curative therapy in childhood Acute Lymphocytic Leukemia.

Globally, public acceptance of waste-to-energy (WtE) incinerators is a crucial factor in implementing national waste-to-energy policies. This study adds to the literature on anti-incinerator sentiment by drawing upon an extended psychological-emotional model that integrates place-, trust-, and fairness-based pathways. A total of 338 residents in the Asuwei area in North Beijing completed a survey on a proposal to construct a WtE incinerator in the vicinity. Hierarchical regression analyses indicate that place attachment positively enhances anti-incinerator sentiment through direct effects, as well as through moderation and mediation effects between risk perception and opposing willingness. Further, institutional trust negatively moderates the impact of perceived risk on anti-incinerator sentiment, in addition to directly reducing perceived risk. Trust also influences anti-incinerator sentiment via risk perception, attesting to the effectiveness of a casual model of trust. Likewise, fairness perception acts as another determinant of opposing sentiment, similar to trust. We further reveal that procedural fairness plays a more significant role in predicting anti-incinerator sentiment than does distributional fairness. These findings demonstrate the importance of using a range of instrumental and more affective strategies to promote social acceptance of renewable energy infrastructure.

This paper deals with the techno-economic study of the hybrid renewable energy system based on energy storage aspect under the form of hydrogen and methane. Indeed, with the intermittency of the renewable energy sources such as photovoltaic and wind energy, several problems of produced energy injection to the power system network can be encountered due to the shortage or the excess of these sources. This situation appeals the use of systems that ensure the stability of network based on the storage of energy surplus into gas using electrolyzer systems, which will be used afterward to cover the eventual shortage. In the present paper, the study of performance of each pathway of methane and hydrogen storage has been performed by the treatment of multiple scenarios via different architecture case studies in an Algerian location. Whereas, the energy produced by the photovoltaic system, the wind energy and the gas micro turbine sources are considered similar in each case. The modeling and simulation of the studied system operation under optimization criteria has been performed in this work, where the main aim is to define the appropriate configuration taking into account the different with low costs of investment, maintenance operation and immediate reactivity with a big storage capacity.

We study two fundamental linguistic channels ‒ the Sentences and the Interpunctions channels ‒ and show they can reveal deeper connections between texts. The theory applied does not follow the actual paradigm of linguistic studies. As study‒case, we consider the Greek New Testament, with the purpose of determining mathematical connections between its texts and possible differences in writing style (mathematically defined) of writers, and in reading skill required to their readers. The analysis is based on deep‒language parameters and communication/information theory. To set the New Testament texts in the larger Greek Classical Literature, we consider texts written by Aesop, Polybius, Flavius Josephus and Plutarch. The results largely confirm what scholars have found about the New Testament texts giving, therefore, credibility to the theory. The gospel according to John is very similar to Fables written by Aesop. Surprisingly, the Epistle to the Hebrews and Apocalypse, are each other “photocopy” in the two linguistic channels, and not linked to all other texts. These two texts deserve further study by historians of the early Christian Church Literature at the level of meaning, readers and possible Old Testament texts which might have influenced them. The theory can guide scholars to study any literary corpus.

Hubei, Hunan and Henan Provinces are located in Central China, a region with extensive transport networks and trade. Bursaphelenchus xylophilus, the causative agent of pine wilt disease, is spreads mainly through human activities. In order to further understand the genetic structure of PWN in Central China, we studied the genetic information of PWN populations in this region and compared the genetic relationship with strains from Guangdong and Jiangsu provinces. We found that the HB (Hubei) 15, HEN (Henan) 20, HN (Hunan) 07, HN08 and HN10 had significantly more SNPs and homozygotes than other strains from Central China, and their most frequent mutant genotypes also differed from other strains. The clustering results indicated that HB15, HEN 20, HN07, HN08 and HN10 were genetically distinct from other strains and closely related to Guangdong strains. We also observed significant genetic variation among strains in Henan province, suggesting that some of them might have different transmission sources than those from Hubei and Hunan provinces. The results provide a basis for tracing the origin and spread of PWD in China.

The salt marshes, lying at the land-sea temperate interface, furnish a plethora of ecosystems services such as biodiversity niche support, ocean-climate change regulation, ornithology recreo-tourism or plant gathering by hand. They undergo significant worldwide losses due to their conversion into crop fields and to their spatial compression between the rising sea-level and the armoring shoreline. Their monitoring however requires to use a suite of remote sensing sensors to embrace the regional scale while capturing the plant details. This research innovatively adopts a multiscale approach using a cascading spaceborne and airborne process, from the 10-m Sentinel-2, through the 3-m Dove, to the 0.03-m unmanned airborne vehicle (UAV) imageries. The high to very high temporal resolution of the Sentinel-2 and Dove enabled to cover twenties and tens of km2 over five and four years, respectively, in the form of normalized difference vegetation index (NDVI) classes, associated with microphytobenthos, low, medium and high salt marsh vegetation, including the opportunistic Elyma genus. The NDVI was then modelled at the UAV scale (a few km2) using a three-layered NN prediction, providing the final near-infrared (NIR), and the intermediate red, green and blue reflectance imageries, calibrated/validated/tested with the Dove reflectance imageries (R2NIR=0.98, R2red=0.88, R2green=0.84, and R2blue=0.90). The 100fold increase in pixel size allowed to detect the decimeter-scale objects of the tidal flats and salt marshes, to enlarge the NDVI class ranges, and hold great promise to model other spectral bands at the UAV scale for further deeply enhancing the salt marsh mapping.

Acute high altitude illnesses are of great concern for physicians and people traveling to high altitude. High Altitude Pulmonary Edema (HAPE) can be better understood through the Oxygen Transport Triad which involves the Pneumo-Dynamic Pump (Ventilation), the Hemo-Dynamic Pump (Heart and circulation), and Hemoglobin. The two pumps are the first physiologic response upon initial exposure to hypobaric hypoxia. Hemoglobin is the balancing energy-saving time-evolving equilibrating factor. The increased hemoglobin at high altitude reduces the percentage of dissolved oxygen in the arterial oxygen content with respect to sea level. At high altitude, the acid-base balance must be adequately interpreted using the high altitude Van-Slyke correction factors. Pulse-oximetry measurements during breath-holding at high altitude allow for the evaluation of high altitude diseases. The Tolerance to Hypoxia Formula shows that, paradoxically, the higher the altitude the more tolerance to hypoxia. All organisms adapt physiologically and optimally to a high-altitude environment to survive. Reduction of pulmonary hypertension in HAPE through oxygen administration results in a favorable outcome.

Parkinson’s disease (PD) is the second most common degenerative disease which may cause blood pressure abnormalities due to autonomic dysfunction. Early morning rise of blood pressure which is called morning surge is found to be related with some cardiovascular diseases when it is exaggerated. We wanted to search the relation of Morning blood pressure surge (MBPS) and inflammation in PD. Method: Ambulatory blood pressure monitoring for 24 hours, fibrinogen to albumin ratio, hs-CRP are used in this retrospective study. Fifty idiopathic PD patients and 50 age and sex matched control cases were included. MBPS, it has been defined as the difference between morning BP (measured 2 hours after awakening) and the lowest night-time BP. Body mass index (BMI) is used as an independent variable. Results: Median value of MBPS for PD group (21,63) was significantly different from the control group values (18,63) (p

Green and low-carbon development has become an important embodiment of China's path to becoming a strong agricultural country. How to enable agricultural enterprises to better adopt green technologies and conduct production and operation with the concept of sustainable development has become a key link. This article utilizes a structural equation model (SEM) to analyze the role paths and mediating effects of organizational learning ability and policy orientation in agricultural enterprises' market orientation and willingness to adopt green technologies[ The definition of green technology in this paper refers to Guo Kesha, Tian Xiaoxiao. Green technology and green transformation of industrial development mode [J]. Tianjin Social Sciences, 2024 (02) :99-107, including green manufacturing (production) technology and green service technology.]. The results show that market orientation, organizational learning ability, and policy effectiveness have significant direct positive impacts on the willingness to adopt; market orientation has a significant positive impact on agricultural enterprises' organizational learning ability, organizational learning ability has a significant positive impact on policy orientation, and market orientation has a significant positive impact on policy effectiveness; the results of mediation analysis also indicate that learning ability has a significant mediating effect between market orientation and willingness to adopt, and policy effectiveness has a significant mediating effect between market orientation and willingness to adopt. Through difference analysis, it is believed that the mediating effects of the three paths are equally important, and organizational learning ability and policy effectiveness play a partial mediating role in agricultural enterprises' willingness to adopt green technologies. Based on this, policy suggestions are proposed to improve enterprises' own organizational learning ability, increase the promotion of policies related to green technologies, improve relevant policies for the application of green technologies, and increase research and development efforts for green technologies.

To reduce the redundant counting of TDC in high-speed applications and thus reduce power consumption, a TDC architecture is proposed to quantify the difference between two adjacent rows of pixel signals. This structure can remove the identical part between two rows of pixel signals by adjusting the start and stop signal of the TDC, which will reduce the number of flipping of D flip-flops in the TDC. In the 110nm CMOS process, simulation results show that this design achieves an effective number of bits (ENOB) of 4.72 bits and a Figure of Merit (FoM) of 104.7 fJ/step - 162.3 fJ/step with a power consumption ranging from 60 µW to 93 µW. Compared with traditional counting methods, the proposed TDC can reduce counting power consumption by 30%.

The benefits of cycling as a sustainable transportation mode are widely recognized. Cycling to work offers numerous advantages for individuals, employers, the environment, and society, ranging from improved physical health, wellbeing, and productivity to enhanced public health and reduced carbon emissions. Many governments around the world have implemented various policy measures, interventions, and initiatives to promote cycling. Some cities and towns have encouraged workplaces to provide bike-friendly amenities, such as secure bike parking/storage and shower and changing facility (referred to as end-of-trip facilities), to accommodate cyclists and motivate more employees to embrace sustainable transportation options. However, the presence or absence of such amenities has been found to both positively influence cycling behavior or deter some individuals from cycling to work. Despite the desirability of these amenities, the number of office buildings equipped with bike storage and shower/changing facility remains small, and their economic value is not well understood. In this paper, we aim to investigate whether the presence of cycling-supportive facilities could add value to office buildings. Specifically, we conduct a study using data from office buildings across England as of the end of 2021. We employ hedonic techniques to examine whether office buildings with bike storage and/or shower facility command a rent premium and whether the existence of a rent premium for bike storage and/or shower facility vary by location and across regions in England, independently from any premium associated with BREEM certification. We find that the buildings with bike storage and shower facility secure rent premiums respectively. The level of rent premiums varies with location and regions. The variations of premium are driven by the shortage of the supply of these facilities.

The aim of the research was to determine the most productive tree cutting methods and the factors influencing them in flat and sloping terrain in tree plantations in Brazil. The study utilized drone-captured video material from eucalyptus and pine plantations harvesting operations. In both terrains, two cutting methods were compared, differing in the felling to the side method used: either at the edge of the harvesting front or inside. In addition, on flat terrain, the efficiency of forward felling was studied in relation to the aforementioned methods. In slope terrain, the machines were also equipped with a winch assistance system. Statistical tests were used to determine the most productive cutting methods by analyzing differences in productivity. With an average tree size of 0.3 m3, cutting productivity was 45 m3/E0h in pine cuttings and 55 m3/E0h in eucalyptus cuttings. The average cutting productivity on flat terrain was about 11 m3/E0h higher than on sloping terrain, mainly due to the time spent attaching the winch assistance system, which was a necessary phase of the work in sloping terrain. The research results suggest that it would be the most productive to use sideways felling inside the harvesting front method. However, the need for further research is evident if we want to precisely identify the harvesting conditions and work phases in the tree cutting cycle affecting the differences in the productivity of the harvesting chain in tree plantations.

The paper proposes a methodological way to compensate the imbalance between energy generation and consumption using the battery block of electric vehicles as energy reservoir through the well-known Vehicle to Grid system (V2G). The method is based on a simulation process developed by the authors that take into consideration the daily fluctuations of energy consumption as well as the power level generated by an energy source, either conventional, renewable or hybrid. The study shows that for very large electric vehicle fleet the system renders non-viable, since the remaining energy in the battery block to let the electric vehicle usable for running during daytime avoids to compensating for the energy grid imbalance, only allowing to cover a percentage of the energy imbalance, which the proposed methodology may optimize. The analysis of the proposed methodology also shows the viability of the system when being applied to a small fleet of electric vehicles, not only compensating for the energy imbalance but also preserving the required energy in the battery of the electric vehicle to make it run. The method allows predicting the optimum size of electric vehicle battery, which depends on the energy generation level, coverage factor of the energy imbalance and size of the electric vehicle fleet.

Commercial buildings situated in hot and humid tropical climates rely significantly on cooling systems to maintain optimal occupant comfort. A well-accurate day-ahead load profile prediction plays a pivotal role in planning the energy requirements of cooling systems. Despite the pressing need for effective day-ahead cooling load predictions, current methodologies have not fully harnessed the potential of advanced deep-learning techniques. This research paper aims to address this gap by investigating the application of innovative deep learning models in day-ahead hourly cooling load prediction for commercial buildings situated in tropical climates. A range of deep learning techniques, including Deep Neural Network, Convolutional Neural Networks, Recurrent Neural Networks, and Long Short-Term Memory networks are employed to enhance prediction accuracy. Furthermore, these individual deep learning techniques are synergistically integrated to create hybrid models, such as CNN-LSTM and Sequence-to-Sequence models. An extensive comparative analysis is conducted to identify the most effective hybrid model. Sequence-to-sequence model provided better performance compared to the other single and hybrid models. Experiments are conducted to choose the time horizons from the past that can serve as input to the models. Further, the influence of various categories of input parameters on prediction performance has been assessed. Historical cooling load, calendar features and outdoor weather parameters are found in decreasing order of influence on prediction accuracy. This research focuses on buildings located in Singapore and presents a comprehensive case study to validate the proposed models and methodologies.

Pedestrians, bicyclists, scooterists are Vulnerable Road Users (VRU) in traffic accidents. The number of fatalities and injuries in traffic accidents involving vulnerable road users has been steadily increasing in the last two decades in the U.S. even though road vehicles now have perception sensors like camera to detect risk and issue collision warnings or apply emergency braking. Perception sensors like camera are highly affected by lighting and weather conditions. Camera, radar and lidar cannot detect vulnerable road users in partially occluded and occluded situations. This paper proposes the use of Vehicle-to-VRU communication to inform nearby vehicles of VRUs having trajectories with potential collision risk. An Android smartphone app with low energy Bluetooth (BLE) advertising is developed and used for this communication. The same app is also used to collect motion data of VRUs for training. VRU motion data is smoothed using a Kalman filter and an LSTM neural network is used for future motion prediction. This information is used in an algorithm comparing Time-To-collision-Zone (TTZ) for the vehicle and VRU and issue a driver warning with different severity levels. The warning severity level is based on analysis of real data from a smart intersection for close vehicle and VRU interactions. The resulting driver warning system is demonstrated using proof-of-concept experiments. The method can easily be extended to a VRU collision mitigation system.

A significant amount of data is available for bench-scale fire assessments. However, there is little surrounding large-scale tests and even less so for bench-to-large scale comparisons. Large-scale tests require more material, time and preparation, making them more expensive than bench-scale assessments. However, large-scale testing is an essential component to bench-scale fire testing. The bench-scale tests must be representative of both large-scale and real fire behaviour to provide an insight into how a material or product will behave in the event of a fire during its end use application. The few existing studies reviewed in this study show more guidance and data is needed, especially on a large-scale. Unfortunately, the data that is presented is done so in an inconsistent manner using various means of presentation, statistical analysis, and modelling that doesn’t show clear comparisons between bench and large scale. Currently, no bench-scale method shows good agreement with large-scale fire behaviour. Overall, there is a need for more large-scale testing and data for direct comparisons to be made.

Bounded number theory says that number is not infinite; that is, the number is limited. To come to a conclusion about limited number, one needs to understand the meaning of math and varying spaces, so one needs to understand that math and spaces interact. A matemática tem a função de descrever com precisão o mundo, onde os números representam elementos ou fatos que racionalmente elementos ou fatos pertencem ao espaço, e os espaços têm propriedades que os diferenciem de outros espaços; portanto, não há nenhum elemento ou fato infinito devido a diferenças nas propriedades dos espaços não permite o elemento ou fato em todos os espaços.

Background and Objectives: The severity of acute pancreatitis (AP) is graded as mild (MAP), moderately severe (MSAP), and severe (SAP) according to the revised Atlanta Classification. Determining the severity of AP is the main goal in the early time of AP. The aim of this study was to compare laboratory parameters or indices including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and neutrophil-creatinine index (NCI) at admission for predicting severity of AP. Materials and Methods: In this retrospective study, the data from patients who admitted with diagnosis of AP between January 2018 and December 2021 were collected. Laboratory parameters and indices including NLR, PLR and NCI were compared in the discrimination of AP severity groups. Results: A total of 421 patients [MAP group (n=213), MSAP group (n=158) and SAP group (n=50)] were included. WBC count, neutrophil count, hematocrit, CRP, BUN, creatinine, NLR and NCI were significant parameters to discriminate AP subgroups. The AUROC analysis for discriminating MSAP from MAP showed that WBC (AUC: 0.723, 95% CI: 0.674-0.768, p&lt;0.001), hematocrit (AUC: 0.566, 95% CI: 0.514-0.607, p=0.032), NLR (AUC: 0.649, 95% CI: 0.598-0.698, p&lt; 0.001) and NCI (AUC: 0.749, 95% CI: 0.701-0.792, p&lt;0.001) were statistically significant parameters. Similarly, AUCs to discriminate SAP from MSAP were (AUC: 0.649, 95% CI: 0.579-0.713, p &lt; 0.001) for WBC, (AUC: 0.703, 95% CI: 0.621-0.785, p&lt; 0.001) for BUN, (AUC: 0.602, 95% CI: 0.532-0.669, p=0.029) for CRP and (AUC: 0.742, 95% CI: 0.676-0.800, p&lt;0.001) for NCI. Logistic regression analyses indicated that NCI was the only parameter to discriminate MSAP form MAP (OR: 1.119, 95% CI: 1.015-1.235, p=0.023) and SAP from MSAP (OR: 1.113, 95% CI: 1.042-1.888, p = 0.001). Conclusions: The present study enabled the identification of neutrophil-creatinine index as a new prognostic tool for the assessment AP severity at hospital admission.

The current study primarily aimed to simulate detonation initiation via turbulent jet flame acceleration in partial-premixed H2-air mixtures. Different vertical concentration gradients were generated by varying the duration of hydrogen injection (referred to as diffusion time) within an enclosed channel filled with air. H2-air mixtures with average hydrogen concentrations of 22.5% (lean mixture) and 30% (near stoichiometric mixture) were investigated at diffusion times of 3, 5, and 60 seconds. Numerical results show that the vertical concentration gradient has a major influence on the early-stage of flame acceleration (FA). In the stratified lean mixture, detonation began in all the diffusion times, and comparing the flame-speed graphs showed that a decrease in the diffusion time and an increase in the mixture inhomogeneity speeded up the flame propagation and the jet flame to detonation transition occurrence in the channel. In the stratified H2-air mixture with an average hydrogen concentration of 30%, transition from a turbulent jet flame to detonation occurred in all the cases, and the mixture inhomogeneity weakened the FA and delayed the detonation initiation.

Liver transplantation is currently the only curative therapy for patients with liver cirrhosis. Not all patients in the natural course of the disease will undergo transplantation, but the majority of them will experience portal hypertension and its complications. In addition to medical and endoscopic therapy, a key role in managing these complications is played by the placement of a transjugular intrahepatic portosystemic shunt (TIPS). Some indications for TIPS placement are well-established and they are expanding and broadening over time. This review aims to describe the role of TIPS in managing patients with liver cirrhosis, considering them as potential candidates for liver transplantation. As far as is known TIPS placement seems not to affect the surgical aspects of liver transplantation, in terms of intra operative bleeding rates, postoperative complications or length of stay in the Intensive Care Unit. However, the placement of a TIPS “towards transplant" can offer advantages in terms of enhancing the patient's clinical condition at the time of transplantation and improving patient survival. Additionally, the TIPS procedure can help preserve the technical feasibility of the transplant itself. In this context, indications for TIPS placement may be expanded and considered at an earlier stage. TIPS insertion can also lead to serious adverse events and there are no evidence-based recommendations on this topic to date. For these reasons further studies are needed to make reliable recommendations for TIPS in the pre-transplant setting.

Molnupiravir, a prodrug known for its broad antiviral activity, demonstrated efficacy in animal models of Covid-19, prompting clinical trials where initial results indicated a significant effect against the disease. However, subsequent clinical studies did not confirm these findings, leading to the rejection of molnupiravir for permanent market authorization in many countries. This report critically assessed 19 studies published in 17 reports that investigated the efficacy of molnupiravir in animal models of Covid-19 with the purpose of determining how well the design of these models informed human studies. We found that the administered doses of molnupiravir in most studies involving animal Covid-19 models were disproportionately higher than the dose rec-ommended for human use. Specifically, when adjusted for body surface area, half of the doses of molnupiravir used in the animal studies were more than twice as high as the human dose. Addi-tionally, the drug was frequently given prophylactically or shortly after SARS-CoV-2 inoculation in these models, in contrast to clinical trials where such timing is not consistently achieved. Furthermore, the recommended five-day treatment duration for humans was exceeded in several animal studies. Collectively, we suggest that these design elements in the reported animal studies contributed to a bias favoring molnupiravir, and thus inflated expectations for its efficacy against Covid-19. Addressing these elements may offer avenues to enhance the clinical efficacy of mol-nupiravir for treatment of Covid-19 that include dose increment, early treatment, and admin-istration by inhalation along with use of molnupiravir in antiviral combination therapy.

This paper introduces an advanced method that integrates contingent valuation and machine learning (CVML) to estimate residents’ demand for reducing or mitigating environmental pollutions and climate change. To be precise, CVML is an innovative hybrid machine-learning model, and it can leverage a limited amount of survey data for prediction and data enrichment purposes. The model comprises of two interconnected modules: Module I, an unsupervised learning algorithm, and Module II, a supervised learning algorithm. Module I is responsible for grouping the data into groups based on common characteristics, thereby grouping the corresponding dependent variable, whereas Module II is in charge of demonstrating the ability to predict and the capacity to appropriately assign new samples to their respective category based on input attributes. Take a survey on the topic of air pollution in Hanoi in 2019 as an example, we found that CVML can predict households’ willingness– to– pay for polluted air mitigation at a high degree of accuracy (i.e., 98%). We found that CVML can help users reduce costs or save resources because it makes use of secondary data that is available on many open data sources. These findings suggest that CVML is a sound and practical method that could be widely applied in a wide range of fields, particularly environmental economics and sustainability science. In practice, CVML could be used to support decision-makers in improving the financial resources to maintain and/or further support many environmental programs in years to come.

Environmental concerns, among other causes, are leading to meat replacement in the diet by healthy, nutritious and tasty foods. Alternative protein sources of plant origin can be an alternative to meat, but their low biological value proteins can be a problem. Novel foods, such as insect meals, can meet currently consumer demands. Therefore, this research has developed innovative prototypes of analogue burgers with animal and vegetable proteins. Concerned about health and allergies, a prototype incorporating soya to satisfy coeliacs was developed. An iterative and heuristic process was carried out to test the product development feasibility. The main raw materials used were insect flour (Tenebrio molitor), seitan and soya. In addition, oat and sodium alginate were used as binders. Shelf-life of the new product was evaluated by physicochemical (pH, aw, moisture, colour, acidity and peroxide index) and sensory analysis (quantitative analysis -QDA-). The production of the burger analogues was feasible. Product characterisation showed significant differences (p < 0.05) among samples for organoleptic properties, highlighting texture changes. Using a multivariate model, it was established “The best before date” at 7 days for all developed prototypes, conditioned by microbial growth. Finally, the spoilage model indicated an important contribution to bacterial growth with a notable modification in the pastiness and hardness of the burger analogues developed.

It is known from ancient Egyptian mathematical papyri that the Egyptians were able to calculate the area of a circle with great accuracy. How they found the formula for this calculation was still unknown. Here it is shown how the unknown ancient Egyptian mathematician found a method for calculating the area of a circle and the ratio of a circle’s circumference to diameter.

Waste-to-Hydrogen (Wahh) is a process of converting waste into hydrogen gas through various methods such as thermal conversion, biological conversion, and chemical conversion. This process not only helps in managing waste but also provides a clean source of energy as hydrogen is a renewable energy source that produces zero greenhouse gas emissions during combustion. Wahh has the potential to provide a sustainable solution for energy generation and waste management in the current scenario of globally increasing energy demands. This study aims to examine the properties and energy efficiencies of various renewable fuels including fuelwood, biogas, biomethane, and biohydrogen with a specific focus on differentiating the characteristics of biohydrogen. The paper explores the emerging concepts of waste-to-hydrogen microgrids, biohydrogen refineries, biohydrogen prosumer networks, and a biohydrogen circular economy, as well as Public-Private-People Partnerships (4Ps) and the hydrogen-centric renewable energy revolution, which are taking shape in industrialized countries. The study presents a comprehensive feasibility analysis of these concepts in the context of Nepal. The results of this research will provide valuable insights into the potential for adopting these innovative technologies in Nepal and will contribute to the development of a sustainable and efficient energy system.

Within this paper, a machine learning algorithm is used to investigate the importance of certain setpoints and parameters in the filtration processes of a large-scale water treatment facility. Previously, a model for the filtration process based on Run-to-Run Control was proposed and tested against sample data from the treatment plant, but it was quickly found that such a model was incompatible for successfully computing setpoints of operation which minimize the energy cost of running the filtration systems. The machine learning model described herein is an attempt to elucidate the importance of the available data on the filtration systems and to identify the most important variables that influence the filtration run time.

This research aims to contribute to the growing body of knowledge of Collaborative Consumption (CC) by exploring the motivations that influence the use of Peer-to-Peer (P2P) accommodation platforms from the demand side. There has been a significant increase in interest in sustainable choices regarding P2P accommodation in recent years. To address this gap and contribute to the collaborative consumption and P2P accommodation theory a quantitative study was conducted through a survey yielding 235 responses from both users and non-users of P2P platforms. The findings of this study suggest that P2P accommodation platform usage is influenced by multiple motivations, including sustainability, belonging, economic benefits, and convenience. Interestingly, the study also found that individuals with higher levels of academic qualifications are more likely to adopt this mode of consumption. Moreover, the study is the first of its kind to quantitatively address this topic and, therefore, contributes significantly to the field of collaborative consumption and P2P accommodation theory. By understanding the motivations of P2P platform users, policymakers and practitioners can develop targeted strategies to promote sustainable choices in this sector. Overall, this study provides a useful framework for future research on collaborative consumption and sustainable P2P accommodation.

The combination of non-steroidal anti-inflammatory drugs (NSAIDs) with non-opioid analgesics is common in clinical practice for the treatment of acute pain conditions like post-operative and post-traumatic pain. Besides that, and despite the very satisfactory results achieved by oral analgesics, parenteral analgesia is a key tool in the treatment of painful conditions when the enteral routes are not convenient. The parenteral ready-to-use fixed-dose combinations of NSAIDs with non-opioid analgesics like paracetamol or metamizole could play a central role in the treatment of painful conditions since they are able to gather into only one formulation the advantages of multimodal and parenteral analgesia. Surprisingly, only very recently a parenteral ready-to-use fixed-dose combination of Ibuprofen/Paracetamol was launched to the market. This review aims to review the current availability of NSAID-based Parenteral Fixed-dose combinations with paracetamol and metamizole in the European and American markets, and how the combination of such drugs could play a central role in a multimodal analgesia strategy. Also, it is explored how the parenteral formulations of NSAIDs, paracetamol, and metamizole could serve as starting elements for the development of new parenteral ready-to-use fixed-dose combinations. With this review, we concluded that, despite the well-recognized utility of combining NSAIDs with non-opioid analgesics, there are in the literature several randomized clinical trial studies unable to demonstrate clear advantages concerning their efficacy and safety. In the future, it is deemed necessary to perform clinical trials specifically designed to assess the efficacy and safety of these fixed-dose formulations to generate solid evidence of their clinical advantages.

In this paper, inspired by quantum field theory, or more specifically QED, we propose a dynamical model for relativity. By adopting the approach provided by this dynamical model, we provide a dynamical explanation for relativistic phenomena such as length contraction, time dilation and clock desynchronization. The result of the dynamical approach for clock desynchronization is especially interesting. Our dynamical approach exhausts the freedom for different clock synchronizations on frames accelerated from an initial reference frame, which is allowed by Einstein’s principle approach. Furthermore, our dynamical approach arrives at the interesting conclusion that Einstein’s equivalence principle and gravitational redshift are necessary to explain special relativistic clock desynchronization. This result shows that special relativity by itself is an incomplete theory. If our dynamical model assumptions are assumed to be valid at a fundamental level, it implies some modifications to quantum field theory and general relativity via the equivalence principle. These modifications have been discussed.

The manuscript presents a unified methodology for the engineering design of resonant inverters used for power sources to power various technologies based on induction heating. The methodology is compiled using the generalized consideration of electromagnetic processes in a series RLC circuit and the quasi-boundary method for the analysis of resonant inverters with and without reverse diodes operating in soft and hard commutation modes. On this basis, the transmission functions of the inverters are derived, and the matching between the parameters of the inverter and the load through complicated output circuits is also considered. The basic ratios for determining the circuit elements and their current and voltage loading are presented. The methodologies are verified using several computational examples, simulations and measurements from induction heating devices. The simplified design approach presented is useful for its application in power electronics training and also in the design of various devices using the principle of induction heating. Another important result is the achievement of formalization and algorithmization of the design process, which is a consequence of the application of a unified approach both in the analysis and in the design of a whole class of power electronic devices.

An out-of-hospital cardiac arrest (OHCA) is one of the leading causes of death in the world. The survival rate can be influenced by the Chain of Survival. The school is the institution that has the opportunity to promote the education of citizens in Basic Life Support (BLS), increasing the number of trained bystanders. This study aimed to identify the theoretical and practical knowledge and self-reported skills in BLS, in order to characterise the motivation to intervene in an emergency situation. A quantitative, descriptive, cross-sectional, and analytical study of the survey type was developed with a sample of 1215 students enrolled in 10th grade of secondary education in 2019-2020 in Portugal. The results point to a fragile appropriation of theoretical and practical knowledge in the field of BLS. Self-declared competences tend to rank below the theoretical knowledge manifested. Motivation to intervene is high: students are sensitive to the topic, willing to learn and highlight the importance and social relevance of the topic. We conclude that students do not feel nor are able to intervene in an OHCA episode. It seems necessary to develop didactic proposals that align the teaching of BLS with the Essential Learning at the end of compulsory education in Portugal.

Human and animal waste, including waste products originating from human or animal digestive systems such as urine, feces, and animal manure, have constituted a nuisance to the environment. Inappropriate disposal and poor sanitation of human and animal waste often cause negative impacts on human health through contamination of the terrestrial environment, soil, and water bodies. Therefore, it is necessary to convert these wastes into useful resources to mitigate their adverse environmental effect. The present study provides an overview and research progress of different thermochemical and biological conversion pathways for the transformation of human- and animal-derived waste into valuable resources. The physicochemical properties of human and animal waste are meticulously discussed as well as nutrient recovery strategies. In addition, a bibliometric analysis is provided to identify the trends in research and knowledge gaps. The results reveal that the U.S.A, China and England are the dominant countries in the research areas related to resource recovery from human or animal waste. In addition, researchers from the University of Illinois, the University of California Davis, the Chinese Academy of Science and Zhejiang University are front runners in research related to these areas. Future research should be centred on developing technologies for the on-site recovery of resources, exploring integrated resource recovery pathways, and exploring different safe waste processing methods.

The aim of this study was to estimate the association between fear of COVID-19 and risk perception with preventive behavior in health professionals from three Latin American countries. An analytical cross-sectional study was conducted. Health professionals with on-site care in Colombia, Ecuador, Guatemala, and Peru were surveyed. Information was collected through an online self-report questionnaire. The main variables were preventive behavior as the dependent variable and fear of COVID-19 and risk perception as independent variables. Linear regression was used, and Beta coefficients and p-values were calculated. 435 health professionals were included, the majority were aged 42 years or older (45.29%, 95%CI: 40.65%-50.01%) and female (67.82%, 95%CI: 63.27%-72.05%). It was shown that the greater the fear of COVID-19, the greater the preventive behavior of COVID-19 infection (B=2.21, p=0.002 for total behavior; B=1.12, p=0.037 for additional protection at work; B=1.11, p<0.010 for hand washing). The risk perception of COVID-19 infection had a slight direct relationship with preventive behaviors (B=0.28, p=0.021 for total behavior; B=0.13, p=0.015 for hand washing), with the exception of the preventive behavior of using additional protection at work (p=0.339). We found that fear and risk perception are associated with increased practice of hand washing and use of additional protection at work. Further studies are required on the influence of working conditions, job performance and the occurrence of mental health problems in frontline personnel with regard to COVID-19.

This article mainly proposes the point of view that financial literacy curriculum aims to make kinds of people, to make people with financial creativity of resource integration thinking and continuous ‘to conscience’ of morality, which is cultivate a way of thinking that can maximize benefits through the use of resource integration and constantly ‘to conscience’ to achieve goals for participants in financial structures with balanced interests. In this sense, this article argues that financial literacy is to make kinds of people with a financial mindset and constantly strengthen ‘to conscience’ through uniting of knowledge and action to achieve human well-being and benign operation of society. In this sense, this article attempts to determine what is really taught in financial literacy education in terms of curriculum theory. That is to improve creativity by cultivating financial thinking with constant ‘to conscience’. The views of this paper provide a new way of thinking about financial literacy education assessment. This changes the evaluation criteria of financial literacy education from the result-oriented of wealth growth to the process-oriented of financial creativity growth, trying to move the criticism of financial literacy education curriculum and evaluation from controversy to unity.

In previous studies regarding the osseointegration of zirconia (ZrO2) implants, a lack of consistency was observed in the surface topographies of the ZrO2 and Ti samples because of the difficult processability of ZrO2 surfaces. To resolve this problem, we used the molecular precursor method (wet process), which is a surface-modifying technique that can easily change the surface chemistry without changing the surface topography. A roughened Ti surface was prepared using sandblasting (large-grit) and acid treatment. We were able to create ZrO2-coated Ti implants with the same topography as that of roughened Ti substrates using the molecular precursor method, which solution contained a Zr complex. The uniform presence of tetragonal Zr was confirmed, and the apparent zeta potential of the surface of the ZrO2-coated Ti implant was higher than that of Ti. In animal experiments, ZrO2-coated Ti implants showed an equivalent or higher bone-to-implant contact ratio compared to that of the non-coated implants inserted into the femur bone defects of the rats. ZrO2 with the same surface topography as that of roughened Ti exhibits a promotion of osteogenesis equivalent to or better than that of Ti in the early stages of bone formation.

Modularity and organizational hierarchy are important concepts in understanding the structure and evolution of interactions in complex biological systems. In this work, we introduce and use a spectral characterization measure (Spectral Entropy) to quantify modularity in protein-to-protein interaction (PPI) networks in species across the tree of life. We evaluated the relation between the size of a PPI network and its (Spectral Entropy-based) modularity, and found a sigmoidal response between the two. We also found significant differences in the distribution of Spectral Entropy values among the three domains of life (Bacteria, Archaea, Eukaryotes). To explore further correlations with biological traits, we focused solely on bacterial PPI networks, which are the most numerous among the three domains and had associated trait metadata, and investigated how modularity impacts or is impacted by growth, aerobicity, selection and location on the tree of life. We found no relation between maximal growth rate and Spectral Entropy, but a strong dependence between G-C content (a proxy for selection) and Spectral Entropy. We also discovered that Spectral Entropy is negatively affected by phylogenetic placement (evolutionary distance from the last universal common ancestor). The general nature of the Spectral Entropy measure of hierarchical modularity in networks suggests that it will be useful in other settings where structural properties of real-world networks are being compared.

Molecular mechanisms for N2 fixation (solar NH3) and CO2 conversion to C2+ products in enzymatic conversion (Nitrogenase), electrocatalysis, metal-complexes and plasma-catalysis are analysed and compared. It is evidenced that differently from what present in thermal and plasma-catalysis, the electrocatalysis path requires not only the direct coordination and hydrogenation of undissociated N2 molecule, but to realize a series of features present in the Nitrogenase mechanism. There is the need of i) a multi-electron and -proton simultaneous transfer, not as sequential steps, ii) forming bridging metal hydride species, iii) generate intermediates stabilized by bridging multiple metal atoms, iv) have the capability of the same sites to be effective both in N2 fixation and in COx reduction to C2+ products. Only iron oxide/hydroxide stabilized at defective sites of nanocarbons was found to have these features. This comparison of the molecular mechanisms in solar NH3 production and relations with CO2 reduction is proposed to be a source of inspiration to develop the next generation electrocatalysts to address the challenging transition to a future sustainable energy and chemistry beyond fossil fuels.

In light of the latest trends in global installed capacities, the importance of variable renewable energy sources (VRES) to future energy supply systems is evident. Despite this, the inherent intermittency of VRES remains an obstacle to their widespread adoption. Green hydrogen is often suggested as an energy carrier that can account for this in a sustainable manner. In the analysis, a robust European energy system in the context of 2050 and with 100% VRES energy supply is designed through an iterative minimal cost-optimization approach that ensures robust security of supply over 38 weather-year scenarios (1980-2017). The impact of spatial VRES variability is factored in by defining exclusive VRES groups within each optimization region and, from this, it can be seen that higher numbers of groups in each region offer cheap electricity generation locations to the optimizer and thus decrease the total annual cost of the system. Beyond this, the robust system design and impact of inter-annual variability is identified by iteratively combining the installed capacities of different system designs obtained by applying 38 historical weather years. The robust system design outlined here has significantly lower capacities in comparison to the maximum regional capacities obtained in the first round of optimization.

Biogas contains more than 40% CO2 that can be removed to produce high quality CH4. Recently, CH4 production from CO2 methanation has been reported in several studies. In this study, CO2 methanation of biogas was performed over a 20 wt% Ni-Mg-Al catalyst, and the effects of CO2 conversion rate and CH4 selectivity were investigated as a function of CH4, O2, H2O, and N2 compositions of the biogas. At a gas hourly space velocity (GHSV) of 30,000/h, the CO2 conversion rate was ~79.3% with a CH4 selectivity of 95%. In addition, the effects of the reaction temperature (200–450 °C), GHSV (21,000–50,000/h), and H2/CO2 molar ratio (3–5) on the CO2 conversion rate and CH4 selectivity over the 20 wt% Ni-Mg-Al catalyst were evaluated. The characteristics of the catalyst were analyzed using Brunauer-Emmett-Teller (BET) surface area analysis, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). The catalyst was stable for approximately 200 h at a GHSV of 30,000/h and a reaction temperature of 350 °C. CO2 conversion and CH4 selectivity were maintained at 75% and 93%, respectively, and the catalyst was therefore concluded to exhibit stable activity.

General wisdom thinks that the central of blackholes are singular and featured by mass, charge and spin exclusively; the microstate reflected in the Bekenstein-Hawking entropy can be accounted for only in some quantum gravity. We challenge this wisdom with two exact solution families to the sourceful Einstein equation which describe dust ball with oscillatory inner structure and variety of mass profiles. We attribute the matter content's oscillation across the central point of the system to the forward scattering domination in high energy collisions induced by inter-gravitating acceleration and provide their Penrose-Carter diagram representation and quantum description briefly. Our solution family provides a very simple semi-classic picture for the micorstate definition of black holes.

Purpose: To explore the influence of education and other factors on an athlete’s decision to return to sport post-concussion injury, and whether general risk-taking tendencies are related to return to sport post-concussion decisions in these athletes. Participants and Methods: A self-administered electronic survey was designed to examine their decision-making process when faced with scenario-based questions regarding returning to sport post-concussion injury. Students from the Health Sciences and Medicine Faculty at Bond University were invited to participate. Participants were allocated to a concussion education or non-education group prior to commencement of questionnaire via the random generator on Qualtrics software function. The risk propensity scale was used to assess the risk aversion of each participant. Results: Sixteen respondents were randomized evenly to education and non-education groups. Seven (43.8%) had previously received concussion education training prior to completing the questionnaire, with one (14%) choosing to return to sport in the scenario-based questions. The education group reported two (25%) respondents return to sport, while three (75%) respondents out of four returned to sport with no education or previous concussion training. Influential factors that impacted the decision whether to return to sport or not included: game importance, concussion severity and symptoms, and various internal and external factors. Finally, there was a divergence in results from the risk propensity scale when deciding to return to sport and general risk-taking propensities. Conclusion: This study identified several influential factors including game importance, concussion severity and symptoms which play a significant role in the return to sport decisions post-concussion injury.

It has been a long time since the world has experienced a pandemic with such a rapid devastating impact as the current COVID-19 pandemic. The causative agent, the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) is further unusual in that it appears capable of infecting many different mammal species. As a significant proportion of people worldwide are infected with SARS-CoV-2 and may spread the infection unknowingly before symptoms occur or without any symptoms ever occurring, there is a non-negligible risk of humans spreading SARS-CoV-2 to wildlife, in particular mammals. Because of SARS-CoV-2’s evolutionary origins in bats and reports of humans transmitting the virus to pets and zoo animals, regulations for prevention of human-to-animal transmission have so far focused mostly on these animal groups. Here, we summarize recent studies and reports that show that a wide range of distantly related mammals are likely susceptible to SARS-CoV-2 and that susceptibility or resistance to the virus is in general not predictable, or only to some extent, by phylogenetic proximity to known susceptible or resistant hosts. In the absence of solid evidence on the SARS-CoV-2 susceptibility/resistance for each of the >5,500 mammal species, we argue that sanitary precautions should be taken when interacting with any mammal species in the wild. Preventing human-to-wildlife SARS-CoV-2 transmission is important for protecting these (sometimes endangered) animals from disease, but also to avoid establishment of novel SARS-CoV-2 reservoirs in wild animals. The risk of repeated re-infection of humans from such a wildlife reservoir could severely hamper SARS-CoV-2 control efforts. For wildlife fieldworkers interacting directly or indirectly with mammals, we recommend sanitary precautions such as physical distancing, wearing face masks and gloves, and frequent decontamination, which are very similar to regulations currently imposed to prevent transmission among humans.

Renewable energy sources (RES) will play a crucial role in future sustainable energy systems. In scenarios analyzing future energy system designs, a detailed spatial and temporal representation of renewable-based electricity generation is essential. For this, sufficiently representative weather data are required. Most analyses performed in this context use the historical data of either one specific reference year or an aggregation of multiple years. In contrast, this study analyzes the impact of different weather years based on historical weather data from 1980 through 2015 in accordance with the design of an exemplary future energy system. This exemplary energy system consists of on- and offshore wind energy for power-to-hydrogen via electrolysis, including hydrogen pipeline transport for most southwestern European countries. The assumed hydrogen demand for transportation needs represents a hypothetical future market penetration for fuel cell-electric vehicles of 75%. An optimization framework is used in order to evaluate the resulting system design with the objective function of minimizing the total annual cost (TAC) of the system. For each historical weather year, the applied optimization model determines the required capacities and operation of wind power plants, electrolyzers, storage technologies and hydrogen pipelines to meet the assumed future hydrogen demand in a highly spatially- and temporally-detailed manner, as well as the TAC of the system. Following that, the results of every individual year are compared in terms of installed capacities, overall electricity generation and connection to the transmission network, as well as the cost of these components within each region. The results reveal how sensitive the final design of the exemplary system is to the choice of the weather year. For example, the TAC of the system changes by up to 20% across two consecutive weather years. Furthermore, significant variation in the optimization results regarding installed capacities per region with respect to the choice of weather years can be observed.

By combing continuum topology optimization (TO) method and lattice structure technique, a sandwich aircraft spoiler with a high stiffness-to-weight is designed. TO method is served to produce the shell of the aircraft spoiler and the lattice structure, used as cores, is employed to support the shell. TO problem is established as maximizing the stiffness of the structure with limited material volume. Density-based method is utilized to achieve a 0/1 solution. We then empirically replace the core of the aircraft spoiler by using 3D kagome lattice structure. Two different materials, i.e., aluminum alloy and titanium alloy, are synthetically applied to further reduce the weight and simultaneously improve the strength of the aircraft spoiler. Numerical simulations are conducted to show that the designed aircraft spoiler can meet the service environment with a reduction of its weight by approximately 80% when compared with that of the initial design model. Finally, we have fabricated the designed model with photosensitive resin by using 3D printing technique.

Drug delivery to the brain represents a challenge especially in the therapy of central nervous system malignancies. Simvastatin (SVT), as other statins, has shown potential anticancer properties that are difficult to exploit in the CNS. In the present work the physico-chemical, mucoadhesive and permeability enhancing properties of simvastatin-loaded poly-ε-caprolactone nanocapsules coated with chitosan for nose-to-brain administration were investigated. Lipid-core nanocapsules coated with different molecular weight (MW) chitosans (LNCchit) prepared by a novel one-pot technique were characterized for particle size, surface charge, particle number density, morphology, drug encapsulation efficiency, interaction between surface nanocapsules with mucin, drug release and permeability across two nasal mucosa models. Results show that all formulations present adequate particle size (below 220 nm), positive surface charge, narrow droplet size distribution (PDI<0.2) and high encapsulation efficiency. Nanocapsules presented controlled drug release and mucoadhesive properties dependent on the MW of the coating chitosan. The results of permeation across RPMI 2650 human nasal cell line evidenced that LNCchit increased the permeation of SVT. In particular, the amount of SVT permeated after 4h for nanocapsules coated with low MW chitosan, high MW chitosan and control SVT was 13.91 ± 0.78 µg, 9.15 ± 1.23 µg and 1.42 ± 0.21 µg respectively. These results were confirmed by the SVT ex vivo permeation across rabbit nasal mucosa. This study highlighted the suitability of LNCchit as promising strategy for the administration of simvastatin for a nose-to-brain approach for the therapy of brain tumors.

Location-Based Services (LBS) have been widely deployed for the connected vehicle (CV) applications such as vehicle navigation,vehicle tracking and location-based augmented reality. The current LBS deployments have limitations in supporting time-critical CV use cases, including vehicle to vehicle (V2V), vehicle to infrastructure (V2I) and vehicle-to-people (V2P) safety applications. The paper presents the new LBS framework based on the publish-subscribe communication paradigm, to enable device-to-device (D2D) connections through use of selected application protocols in the application layer of the TCP/IP layered protocol model. Two publish-subscribe application protocols, Distributed Data Service (DDS) real-time publish and subscribe (DDS-RTPS) and Message Queue Telemetry Transport (MQTT), are introduced to support the LBS D2D applications. A number of test scenarios with Mosquitto MQTT and OpenDDS under 4G-mobile broadband (MBB) services are designed to assess the transmit/receive round-trip time (RTT) and packet-loss rate (PLR) with settings of a publisher to multiple subscribers, to simulate the connections to multiple vehicles. The transmission frequency is set for 10 Hz and the message sizes vary from 100 to 2000 Bytes. The PLRs are defined as the percentages of the delayed messages beyond a delay limit. Static test results with OpenDDS show that for the RTT delay beyond the limit of 100 ms, the total PLRs range between 5.25% and 8.76% for the message size of 50 to 2000 Bytes. Vehicle testing results with Mosquitto show that PLRs for the RTT delays between 200 ms and 1000 ms are 0.63%, 3.58% and 5.77%, for connections with 1, 4 and 10 vehicles, respectively. The results demonstrate the potential of the D2D LBS framework for medium-demanding CV safety applications such as V2P and V2I use cases, taking advantages of the 4G-MBB services and 5G extreme mobile broadband (eMBB) services and mobile devices generally available with all road users.

The seasonally adjusted civilian labor force participation rate, the sum of employed and unemployed persons as a percentage of the civilian non-institutional population, is analysed in the general to specific modelling framework with a saturating set of step indicators from January 1977 through June 2018. The results indicate that, ceteris paribus, the rise in the ratio of women to men in the labor force in addition to positive demographic movements can largely account for the rise in the labor force participation rate up to January 2000. Subsequently, the aging population helps to explain the decline. Recessions play a transitory role.

The speech-to-song illusion is a type of auditory illusion that the repetition of a part of a sentence would change people’s perception tendency from speech-like to song-like. The study aims to examine how pace, emotion, and language tonality affect people’s experience of the speech-to-song illusion. It uses a between-subject (Pace: fast, normal, vs. slow) and within-subject (Emotion: positive, negative, vs. neutral; language tonality: tonal language vs. non-tonal language) design. Sixty Hong Kong college students were randomly assigned to one of the three conditions characterized by pace. They listened to 12 audio stimuli, each with repetitions of a short excerpt, and rated their subjective perception of the presented phrase, whether it sounded like a speech or a song, on a five-point Likert-scale. Paired-sample t-tests and repeated measures ANOVAs were used to analyze the data. The findings reveal that a faster speech pace could strengthen the tendency of the speech-to-song illusion. Neither emotion nor language tonality show a statistically significant influence on the speech-to-song illusion. This study suggests that the perception of sound should be in a continuum and facilitates the understanding of song production in which speech can turn into music by having repetitive phrases and to be played in a relatively fast pace.

The impact of an unlicensed low-cost taxi in Bangladesh is very severe, especially in municipal cities. Day by day the numbers of unlicensed low-cost taxi are increasing by jumping up and creating pressure on traffic and transportation system. The aim of this study is to find out the causes of increasing illegal taxi and the extent of this vehicle in the municipalities of Bangladesh. Pabna municipality is used as a case study due to the more activeness of illegal taxi then the other municipalities. To achieve the objectives, the researcher used a qualitative approach to acquire more depth about the problems. Besides a direct observation of the study area, an open-ended questionnaire survey and HIS survey were conducted. The illegal low-cost taxi is very active it was analyzed through the field survey. A statistical model was developed to understand the actual causes of increasing illegal low-cost taxi, where ten predicted hypotheses (age, education level, marital status and family member support of illegal drivers, and the variable of commuter satisfaction e.g. safety, comfort, continuous service, affordability of service, reliability of service and driver behavior) were tested. The model was run through the multiple regression analyses technique in SPSS and the result proved that education level of illegal low-cost taxi drivers, and the commuter satisfaction variable (safety and comfort) had a positive and significant effect of increasing illegal low-cost taxi in the study area. However other variable had no significant effect in case of increasing illegal low-cost taxi. Besides the safety and comfort, steady job for the operators, provision of continuous, individual and door to door service system are the main reasons for increasing the illegal low-cost taxi in the study area. Finally, the researcher concludes with the requirement of some necessary action from the responsible authority on vehicular regulation for the improvement of the local public transport system in Bangladesh.

Graph coloring is a manifestation of graph partitioning, wherein, a graph is partitioned based on the adjacency of its elements. Partitioning serves potentially as a compartmentalization for any structural problem. Vertex coloring is the heart of the problem which is to find the chromatic number of a graph. The fact that there is no general efficient solution to this problem that may work unequivocally for all graphs opens up the realistic scope for combinatorial optimization algorithms to be invoked. The algorithmic complexity of graph coloring is non-deterministic in polynomial time (NP) and hard. To the best of our knowledge, there is no algorithm as yet that procures an exact solution of the chromatic number comprehensively for any and all graphs within the polynomial (P) time domain. However, several heuristics as well as some approximation algorithms have been attempted to obtain an approximate solution for the same. Here, we present a novel heuristic, namely, the 'trailing path', which returns an approximate solution of the chromatic number within polynomial time, and, with a better accuracy than most existing algorithms. The ‘trailing path’ algorithm is effectively a subtle combination of the search patterns of two existing heuristics (DSATUR and Largest First), and, operates along a trailing path of consecutively connected nodes (and thereby effectively maps to the problem of finding spanning tree(s) of the graph) during the entire course of coloring, where essentially lies both the novelty and the apt of the current approach. The study also suggests that the judicious implementation of randomness is one of the keys towards rendering an improved accuracy in such combinatorial optimization algorithms. Apart from the algorithmic attributes, essential properties of graph partitioning in random and different structured networks have also been surveyed, followed by a comparative study. The study reveals the remarkable stability and absorptive property of chromatic number across a wide array of graphs. Finally, a case study is presented to demonstrate the potential use of graph coloring in protein design – yet another hard problem in structural and evolutionary biology.

In 1990 the Malaysian Government launched Vision 2020 with the goal of Malaysia becoming a ‘fully developed country’ by the year 2020. In this drive for development the country has been examining many of its key natural assets, exploring how to both preserve them whilst ensuring that they make the maximum possible contribution to national development goals. Endau Rompin is one of these assets, being the second largest National Park in Peninsula Malaysia. The rich tropical rainforest flora and fauna of the Park and its hinterland, however, are threatened by various anthropogenic forces, most notably deforestation and poaching; both of which have taken the Park’s flagship species - the Tiger Panthera tigris jacksoni – towards the brink of local extinction. Malaysia’s statutory East Coast Economic Region Development Council commissioned a study to consider ways of increasing tourism revenues from the Park while at the same time reversing these threats. The key conclusion drawn is that a more holistic, landscape-scale approach should be adopted, with Endau Rompin forming part of a wider strategic economic zone based around sustainable tourism and land management. The proposed expanded zone extends eastwards beyond the confines of the Park, across the coastal plain to the South China Sea, and onwards to the neighbouring Mersing Islands. This expanded zone is referred to as Malaysia’s new ‘Rainforest to Reef Region’.

The population’s mobility in urban areas is a necessary variable in the modeling of risk scenarios caused by atmospheric contamination. The inclusion of this concept makes static models more dynamic while considering people within a city to be an entity with complex mobility processes. We propose a conceptual and methodological tool to make the representation of the social, economic and territorial components, as well as the patterns in the population´s mobility to delimitate risk areas for human health by exposure of contaminants. In the volatile organic compounds (VOC), benzene, ethylbenzene, toluene and xylene (BTEX) are amongst the most dominant substances in fugitive vapor emissions in gas stations (GS). In urban areas, the exposure to BTEX by residential proximity and proximity to other facilities, which cause intra-urban agglomeration, can impact and affect human health. This model seeks to facilitate the focalization, identification and prioritization of risk areas by BTEX environmental contamination. This article goes beyond de conceptual framework. It suggests methodological and instrumental aspects to be applied in other cities. The government agencies must consider these results when establishing rules, permissions and procedures to reduce environmental pollution for managing the risk in a complex urban environment.

There is a growing concern about climate change being a serious threat to insurance business sustainability. Knowing if climate warming is a cause for claims and losses increase, and how this cause-effect relationship will develop in the future are two open major questions. In this article, we answer both questions by particularizing the geographical area of Spain, and a precise risk, hailstorm in crop insurance in the line of business of wine grapes. We measure climate change thanks to the Spanish Actuarial Climate Index (SACI). We use a database containing all the claims caused by hail risk in Spain from 1990 to 2022. With homogenized data, we consider as dependent variables the monthly number of claims, monthly number of loss costs equal to one, and monthly total losses. The independent variable is the monthly Spanish Actuarial Climate Index (SACI). We try to explain the former through the latter using regression and quantile regression models. Our main finding is that climate change as measured by SACI explains these three dependent variables. We also give an estimation of the increase of the monthly total losses Value at Risk, corresponding to a future increase in climate change measured in units of SACI. Spanish crop insurance managers should carefully incorporate these conclusions into their decision-making process to keep this line of business sustainable in the future.

Whole genome duplication (WGD) or polyploidization can occur at the cellular, tissue, and organismal levels. At the cellular level, tetraploidization has been proposed as a driver of aneuploidy and genome instability, and correlates strongly with cancer progression, metastasis, and development of drugs resistance[1–6]. WGD is also a key developmental strategy for regulating cell size, metabolism, and cellular function[1,7–10]. In specific tissues, WGD is involved in normal development (e.g. organogenesis), tissue homeostasis, wound healing, and regeneration[10–17]. At the organismal level, WGD propels evolutionary processes such as adaptation[18], speciation[19], and crop domestication[20]. An essential strategy to further our understanding of the mechanisms promoting WGD and its effects is to compare isogenic strains that differ only in their ploidy. Caenorhabditis elegans (C. elegans) is emerging as an animal model for these comparisons, in part because relatively stable and fertile tetraploid strains can be produced rapidly from nearly any diploid strain[7]. Here we review the use of Caenorhabditis polyploids as tools to understand important developmental processes (e.g. sex determination, dosage compensation, and allometric relationships)[21–27] and cellular processes (e.g. cell cycle regulation, chromosome dynamics during meiosis)[28–32]. We also discuss how the unique characteristics of the C. elegans WGD model will enable significant advances in our understanding of mechanisms of polyploidization and its role in development and disease.

Piezoelectric nanotransducers may offer key advantages in comparison with conventional piezoelectrics, including more choices for types of mechanical input, positions of the contacts, dimensionalities and shapes. However, since piezo-semiconductive nanostructures are generally much easier to fabricate and integrate into functional systems than insulating materials, modeling becomes significantly more intricate and the effects of free charges have been considered only in a few studies. The available reports are complicated by the absence of proper nomenclature and figures of merit. Besides, some analyses are incomplete. For instance, the local piezopotential and free charges within axially strained conical piezo-semiconductive nanowires have only been systematically investigated for very low doping (1016 cm-3) and under compression. Here we give the definitions for the enhancement, depletion, base and tip piezopotentials, their characteristic lengths and both the tip-to-base and the depletion-to-enhancement piezopotential-ratios. As an example, we use these definitions for analyzing the local piezopotential and free charges in n-type ZnO truncated conical nanostructures with different doping levels (intrinsic, 1016 cm-3, 1017 cm-3) for both axial compression and traction. The definitions and concepts presented here may offer insight for designing high performance piezosemiconductive nanotransducers.

Background. Escherichia coli commonly causes catheter-related bloodstream infection (C-RBSI) in specific populations. The differential time to positivity (DTTP) technique is the recommended conservative procedure for diagnosing C-RBSIs. Methods. We conducted a retrospective study of episodes in which E. coli was isolated from catheter lumens obtained using the DTTP technique. We analysed microbiological and clinical data based on the DTTP technique as either catheter colonization, C-RBSI, or non-C-RBSI. Results. We included 89 catheter blood cultures classified as follows: catheter colonization, 33.7%; C-RSBI, 9.0%; and non-C-RBSI, 57,3%. Catheter withdrawal was 15.7% without positive catheter-tip cultures. We found no statistically significant differences in catheter type, antibiotic treatment, or clinical outcome among groups, except for the frequency of catheter lock therapy or in the frequency of successful treatment. Mortality was associated with C-RBSI in only 1 patient. Conclusion. E. coli bacteremia diagnosed by the DTTP technique was non-catheter related in most patients. As the majority of the catheters were retained, E. coli bacteremia could not be microbiologically confirmed or ruled out as catheter related by catheter-tip culture. Future studies are needed to assess the profitability of the DTTP technique for diagnosing E. coli C-RBSIs..

This retrospective study examines 248 test-bolus examinations preceding contrast-enhanced magnetic resonance angiography (CE-MRA) to extract clinically relevant data for critical limb ischemia (CLI) management. Methods involved a retrospective review of test-bolus exams, analysing 60 graphs for time-to-peak (TTP), full-width half-maximum (FWHM) time, and time to continual rise in signal intensity. These values were correlated with heart function parameters (ejection fraction, ASA-Classification, Lee-Index, and MET-Score). Results indicate a mean TTP of 31.2 ± 7.3s, showing a correlation between ejection fraction and ASA classification. Patients with atrial fibrillation exhibited prolonged TTP compared to those without. Despite population heterogeneity, findings facilitate risk stratification for limb-saving interventions in CLI. TTP emerges as a potential clinical cardiovascular parameter and a risk factor for vascular interventions. Given the variation in injection protocols across centres, this study underscores the importance of precise bolus arrival time documentation for future multicentre studies.

Pipeline conflicts arising from data dependencies are a common issue encountered in the hardware implementation of layered QC-LDPC decoders. This paper proposes an efficient layered decoding architecture to reduce pipeline conflicts without introducing stall cycles, by reordering the processing order offline and using the patch method based on variable-to-check message. The experimental results on the LDPC code of the IEEE802.16 standard in the OFDM-PON system demonstrate that the proposed architecture has a sensitivity improvement of 0.125 dBm and 0.375 dBm, respectively, compared with our previous work and the method described in the other work.

Silicon Photomultipliers find applications across various fields. One potential Silicon Photomultiplier application domain is neutrino telescopes, where they may enhance the angular resolution. However, the elevated dark count rate associated with Silicon Photomultipliers represents a significant challenge to their widespread utilization. To address this issue, it is proposed to use Silicon Photomultipliers and Photomultiplier Tubes together. The Photomultiplier Tubes signals would serve as a trigger to mitigate the dark count rate, thereby preventing undue saturation of the available bandwidth. This paper presents an investigation into a fast and resource-efficient method for filtering Silicon Photomultiplier dark count rate. A low-resource and fast coincident filter has been developed, which removes the Silicon Photomultiplier dark count rate by using as trigger the Photomultiplier Tube input signals. The architecture of the coincidence filter, together with the first results obtained, which validate the effectiveness of this method are presented.

There are two generic approaches to curing any medical condition. The first treats every patient for all of the known possible causes that contribute to pathogenesis; the second individualizes potentially curative therapy by identifying in each separate patient only those components of pathogenesis that are actually operative, and treating those. This article adopts the second approach for formulating a cure of Alzheimer’s dementia (AD). Components of AD’s pathogenesis are, in alphabetical order: circadian rhythm disturbances, depression, diabetes and insulin resistance, dyslipidemia, hypertension, inflammation, metabolic syndrome, mitochondrial dysfunction, nutritional deficiencies, TGF-β deficiency, underweight, vascular abnormalities, and Wnt/β-catenin deficiency. For each component, data are described that show the degree by which its prevalence is more in the patients with mild cognitive impairment (MCI) who did not revert to having normal cognition than in those who did, because the former group is the pool of patients from among which future AD may develop. Addressing only those components that are present in a particular individual, is potentially a curative strategy. Published data indicate that curative therapy requires that the number of such components to address should be ≥3. Although structural brain changes cannot be directly addressed, the impaired neural tracts result from many of the reversible causal elements, so correcting them will benefit those tract

It is unavoidable that the characteristics of the robot system alter inexactly or cannot be correctly determined during movement and are impacted by external disturbances. There are many adaptive control methods, such as sliding control or neural control, to improve the quality of trajectory tracking for robot motion systems. Still, those methods require a large amount of computation related to solving the problem of constrained nonlinear optimization problem. The article presents some techniques for determining an intelligent controller's online learning function parameters, including two circuits: the inner circuit is a state feedback linearized controller, and the outer course is an Interactive learning controller and does not use the robot's mathematical mode with function parameters online optimal learning and intelligent online learning closely following the joint model to stabilize the robot system. Finally, the 2-DOF planar robot simulation is performed on Matlab software R2022b. The findings indicate that outstanding tracking performance is achievable.

Inverse optimal control is a method for recovering the cost function used in an optimal control problem in expert demonstrations. Most studies on inverse optimal control have focused on building the unknown cost function through the linear combination of given features with unknown cost weights, which are generally considered to be constant. However, in many real-world applications, the cost weights may vary over time. In this study, we propose an adaptive online inverse optimal control approach based on a neural-network approximation to address the challenge of recovering time-varying cost weights. We conduct a well-posedness analysis of the problem and suggest a condition for the adaptive goal, under which the weights of the neural network generated to achieve this adaptive goal are unique to the corresponding inverse optimal control problem. Furthermore, we propose an updating law for the weights of the neural network to ensure the stability of the convergence of the solutions. Finally, simulation results for an example linear system are presented to demonstrate the effectiveness of the proposed strategy. The proposed method is applicable to a wide range of problems requiring real-time inverse optimal control calculations

People are drawn to woodcut-style designs due to their striking visual impact and strong contrast. However, traditional woodcut prints and previous computer-aided methods have not addressed the issues of dwindling design inspiration, lengthy production times, and complex adjustment procedures. We propose a novel network framework, the Woodcut-style Design Assistant Network (WDANet), to tackle these challenges. Notably, our research is the first to utilize diffusion models to streamline the woodcut-style design process. We've curated the Woodcut-62 dataset, featuring works from 62 renowned historical artists, to train WDANet in absorbing and learning the aesthetic nuances of woodcut prints, offering users a wealth of design references. Based on a noise reduction network, our dual cross-attention mechanism effectively integrates text and woodcut-style image features. This allows users to input or slightly modify a text description to quickly generate accurate, high-quality woodcut-style designs, saving time and offering flexibility. As confirmed by user studies, quantitative and qualitative analyses show that WDANet outperforms the current state-of-the-art in generating woodcut-style images and proves its value as a design aid.

Natural gas plays a significant role in Tunisia's energy mix. Tunisia imports 66% of natural gas (NG) from Algeria (ANG), and the rest is provided by local gas fields mainly Miskar gas (MNG). To counteract this deficit, the Power-to-Gas approach emerges as a promising solution, given Tunisia's abundant renewable energy resources. By blending green hydrogen into the NG network, it is possible to (i) address the current energy crisis, (ii) lower the carbon intensity of the gas grid, and (iii) encourage sector coupling through the use of various renewable energy sources. This study presents an overview of various interchangeability indicators and investigates accordingly the allowable ratios for hydrogen blending with two types of natural gas distributed in Tunisia (ANG and MNG). It also explores the impact of hydrogen injection on the energy content variation and various combustion parameters. The results confirm that both ANG and MNG can withstand a maximum hydrogen blend of up to 20%. The article concludes with recommendations for further experimental testing of the findings and emphasizes the need to look into infrastructure and safety requirements with regards to the Natural gas network in Tunisia. This research serves as a critical step towards harnessing the potential of green hydrogen in Tunisia.

This paper delves into the essential role of local communities in mitigating climate change in the post-pandemic landscape, with a specific focus on Barangay Acmac, Iligan City, Philippines. Employing a qualitative research approach, the study integrates in-depth literature reviews, informal interviews with participants (B-Part 1 to B-Part 20), meticulous observations, and thematic analysis. The research has uncovered crucial insights, including variations in community climate change awareness that emphasize the necessity of comprehensive education and awareness campaigns. It highlights the significance of community-driven initiatives, adaptation, and resilience as key elements in addressing climate change. Collaborative efforts between local government officials and the community are showcased as effective instruments of climate change mitigation, yet challenges persist, including addressing the perceived powerlessness of some community members. The methodology, participants, and theoretical framework offer a robust foundation for exploring community responses to climate change. Drawing from a diverse theoretical framework, this study presents a comprehensive understanding of the climate change and pandemic intersection. The findings firmly establish that local communities are pivotal players in the global endeavor to mitigate climate change, underscoring the need for collective action, extensive education, and shared responsibility. The post-pandemic era presents a unique opportunity for local communities, policymakers, barangay officials, and residents to champion climate education, foster community-driven initiatives, and empower individuals to enact change at the grassroots level. The collaborative spirit observed in Barangay Acmac in 2022 serves as a model for communities worldwide, offering a blueprint for addressing similar challenges. Overall, this paper concludes with a resounding call to action, advocating for the recognition of local communities as the driving force in climate change mitigation, stressing that the power to combat climate change resides within these communities. The time for action is now, and local communities are the catalysts of this essential mission.

The aim of this article is to review hydrogen combustion applications within the energy transition framework. Hydrogen blends are also included, from the well known hydrogen enriched natural gas (HENG) to the hydrogen and ammonia blends whose chemical kinetics is still not clearly defined. Hydrogen and hydrogen blends combustion characteristics will be firstly summarized, in terms of standard properties like the laminar flame speed and the adiabatic flame temperature, but also evidencing the critical role of hydrogen preferential diffusion in burning rate enhancement and the drastic reduction in radiative emission with respect to natural gas flames. Then, combustion applications in both thermo-electric power generation (based on internal combustion engines, i.e., gas turbines and piston engines) and hard-to-abate industry (requiring high temperature kilns and furnaces) sectors will be considered, highlighting the main issues due to hydrogen addition related to safety, pollutant emissions, and potentially negative effects on industrial products (e.g., glass, cement and ceramic).

This study aims to investigate how the adoption of an online to offline (O2O) transition strategy impacts the sales volume of Kampoeng Merdeka Clothing. The O2O strategy includes various components, such as establishing O2O platforms, delivering personalized services, ensuring secure transactions, and engaging in offline business activities. The research employs a quantitative approach, focusing on consumers who have made clothing purchases from Kampoeng Merdeka Clothing in Macassar. The sample size comprises 83 respondents, deliberately selected using the Slovin approach. The data analysis and methodology involve the application of Partial Least Squares (PLS) structural equation modeling to assess both the external and internal models. The findings of this study emphasize the significant and positive influence of the variables "Build O2O Network Platform," "Provide Personalized Experience," "Safeguard Transactions Security," and "Offline Business" on driving the sales growth of Kampoeng Merdeka Clothing. These results indicate that the O2O transition strategy has a substantial impact on the brand's sales performance, with the establishment of O2O platforms and personalized services playing crucial roles. Additionally, ensuring secure transactions and engaging in offline business activities further contribute to the overall success of Kampoeng Merdeka Clothing in the market. This research sheds light on the effectiveness of the O2O approach in boosting sales for clothing brands and underscores the importance of integrating online and offline elements to maximize business outcomes.

This paper offers a set of comprehensive guidelines aimed at facilitating the widespread adoption of hydrogen in the industrial hard-to-abate sectors. The authors begin by conducting a detailed analysis of these sectors, providing an overview of their unique characteristics and challenges. The paper delves into specific elements related to hydrogen technologies, shedding light on their potential applications and discussing feasible implementation strategies. By exploring the strengths and limitations of each technology, the paper offers valuable insights into its suitability for specific applications. Finally, through a particular analysis focused on the steel sector, the authors provide in-depth information on the potential benefits and challenges associated with hydrogen adoption in this particular context. By emphasizing the steel sector as a focal point, the authors contribute to a more nuanced understanding of hydrogen's role in decarbonizing industrial processes and inspire further exploration of its applications in other challenging sectors.

Higher salt (sodium) intake has been associated with a higher blood pressure (BP). The association degree may be influenced by factors such as age, origin and dietary components. This study aimed to evaluate the 24-hours urinary sodium (Na) and potassium (K) excretion in normotensive and hypertensive Dominicans adults and estimate their salt intake. 163 volunteers (18-45, 46-80 years) participated in a cross-sectional study. 24-hours Na and K urinary excretion were measured using an ion selective electrode technique. Na and K urinary excretion (99.4±46.5 and 35.0±17.5 mmol/24h) did not correlated with BP, except in the normotensive group in which K correlated with SBP (0.249, p=0.019). Na and K excretion were similar for normo- and hypertensive subjects. Na-to-K molar ratio (3.1±1.3) was higher in younger subjects (p=0.040). Na-to-K ratio was associated with DBP in the total group (r=0.153, p=0.052), in the hypertensive group (r=0.395, p<0.001) and in the older group with SBP (0.350, p=0.002) and DBP (0.373, p<0.001). In the older group, Na-to-K ratio and DBP correlated after controlling for subjects with hypertension controlled by treatment (r=0.236, p=0.041). The Na-to-K ratio correlated, when salt intake was over 5g/d (52.2%), with SBP (rho=0.219, p=0.044) and DBP (rho=0.259, p=0.017). Determinants of BP were age-dependent and in younger subjects were: sex (SBP, beta: 14.02±2.87, p<0.001) and body mass index (BMI) (beta:-12.07±3.72, p=0.001, beta:9.44±2.87, p=0.001, for SBP and DBP, respectively) and, in the olders, the Na-to-K ratio, for SBP (beta:6.7±2.4, p=0.005) and DBP (beta:3.8±1.1, p<0.001). The mean Na and salt intakes (2.3 and 5.8 g/d) were slightly higher and K intake lower (1.4 g/d) than WHO recommendations.

Abstract: Systemic inflammatory response syndrome (SIRS) is a clinical diagnosis based on abnormalities in patients' vital signs and white blood cell count. Neutrophil-lymphocyte ratio (NLR) is used as an easily accessible parameter to assess the patient's inflammatory status and stress. There are some studies showing that NLR affected by the inflammatory response is a criterion to support the diagnosis of SIRS. In this study, it was aimed to compare the interrelation between SIRS (+) and SIRS (-) groups in patients with high positive feline coronavirus (FCoV) in the light of NLR. Based on the anamneses, physical examination findings, laboratory findings, enzyme immunoassay antibody test kit titer were included in the sick groups. These patients were further categorized based on the presence of SIRS symptoms, vital signs and laboratory findings. The NLR as diagnostic marker demonstrated to differ between high antibody titer FCoV positive and healthy cats. However the diagnostic significance of NLR remains questionable between the high antibody titer FCoV positive cats with SIRS (+) and SIRS (-). As a result of our study NLR can be used as a blood parameter like albumin/globulin ratio and elevated total bilirubin in cats with high FCoV antibody titer and high probability of developing FIP.

The basic constitutional freedoms and rights of a person and citizen are in principle unlimited: the full scope of their exercise is the rule, and the restriction determined by law can only be an exception based on explicit constitutional authority and the legitimate aim of the restriction determined by the Constitution. That being so, the restrictions - in addition to being based on constitutional authority and pursuing constitutional objectives - should be commensurate with the needs to achieve these objectives. This means that restrictive legal rules must be suitable for achieving the legitimate aim pursued, must not be stricter than necessary and must be balanced between the constitutionally guaranteed subjective right of the individual and the interests of society. In this scholar paper, the authors point out the economic and legal consequences of the violation of individual privacy and data protection rights caused by the public disclosure of personal data of people who, at a certain time, were obliged to self-isolate due to suspicion of Covid-19 virus infection.

One of the models that could be used to understand the adoption of vaccine uptake is the Health Belief Model (HBM). The aim of this study is to assess the role of HBM constructs and perceived health status (PHS) on vaccination status of individuals and to understand the role of socio-demographic variables on HBM scoring. A comparative cross-sectional telephone survey was conducted among 1,325 vaccinated (60.0%) and non-vaccinated (40.0%) vaccinated individuals aged 40 years and above in July 2021 in Punjab province, Pakistan. A higher level of education was the strongest predictor of positive HBM. All constructs of HBM, PHS and cues-to-action were significant predictors of COVID-19 vaccination uptake with perceived benefits as the strongest predictor. In order to expand the vaccination coverage, doubled pronged interventions utilizing both ICT and human resources should be designed that address each barrier perceived by individuals and understandably communicate the benefits of COVID-19 vaccine to the broader population.

The effects of transcranial magnetic stimulations (TMS) show that the human brain is impacted by some magnetic fields (EMFs). Moreover, after a delay, it produces potentials that reveal a subsequent processing of this impact. The human brain might also be sensitive to very weak magnetic fields of extremely low frequencies (vwEMFelf). Namely, to the vwEMelf produced by the brain of other persons when they process visual stimuli. In effect, two studies report that the event-related brain potentials (ERPs) that are evoked by presenting a picture to a participant can be modulated by simultaneously presenting a picture to a partner. To confirm it here, we followed most of the methods of these studies. We recorded the ERPs evoked by presenting, at each trial, the photograph of a face. Simultaneously and, most importantly, privately, we presented a partner with the same or with a different face photograph. ERPs of participants were found to depend on that sameness (p0.001), unbeknownst to them. These joint processing effects (JPEs), confirm a sensitivity of the human brain to the vwEMFelf produced by other brains.

A major challenge in the clinical management of patients with mesial temporal lobe epilepsy (MTLE) is identifying those who do not respond to antiseizure medication (ASM), allowing for the timely pursuit of alternative treatments, such as epilepsy surgery. Here, we investigated changes in plasma metabolites as biomarkers of pharmacoresistance in patients with MTLE. Furthermore, we used the metabolomics data to gain insights into the mechanisms underlying MTLE and response to ASM. We performed an untargeted metabolomic method using magnetic resonance spectroscopy and multi- and univariate statistical analyses to compare data obtained from plasma samples of 28 patients with MTLE compared to 28 controls. The patients were further divided according to response to ASM: 20 patients were refractory to treatment, and eight were responsive to ASM. We only included patients using carbamazepine in combination with clobazam. We compared the group of patients with controls and found that the profiles of glucose (p = 0.01), saturated lipids (p = 0.0002), isoleucine (p = 0.0001), β-hydroxybutyrate (p = 0.0003), and proline (p = 0.02) were different in patients compared to controls (p &lt; 0.05). In addition, lipoproteins (p = 0.05), lactate (p = 0.05), glucose (p = 0.05), unsaturated lipids (p = 0.05), isoleucine (p = 0.05), and proline (p = 0.05), could discriminate between the two groups of patients classified according to response to ASM. The identified metabolites were linked to different biological pathways related to cell energy metabolism, and pathways linked to inflammatory processes and the modulation of neurotransmitter release and activity in MTLE. In contrast, we found that pyruvate metabolism may be linked to resistance to ASM. In conclusion, in addition to insights into the mechanisms underlying MTLE and the response to treatment with ASM, our results suggest that plasma metabolites may be used as biomarkers of disease and response to ASM in patients with MTLE. These findings warrant further studies exploring the clinical use of metabolites to assist in decision-making when treating patients with MTLE.

We describe a method for protein quantification and for mRNA quantification in small sample quantities of human induced pluripotent stem-cell-derived-cardiomyocytes (hiPSC-CMs). Demonstrated here is how the capillary-based protein detection system Wes^TM by ProteinSimple and the Power SYBR^TM Green Cells-to-CT^TM Kit by Invitrogen can be applied to individual samples in a 96-well microplate format and thus made compatible with high-throughput (HT) cardiomyocyte assays. As an example of the usage, we illustrate that Cx43 protein and GJA1 mRNA levels in hiPSC-CMs are enhanced when the optogenetic actuator, channelrodopsin-2 (ChR2), is genetically expressed in them. Instructions are presented for cell culture and lysate preparations from hiPSC-CMs, along with optimized parameter settings and experimental protocol steps. Strategies to optimize primary antibody concentrations as well as ways for signal normalization are discussed, i.e. antibody multiplexing and total protein assay. The sensitivity of both the Wes and Cells-to-CT kit enables protein and mRNA quantification in a HT format, which is important when dealing with precious small samples. In addition to being able to handle small cardiomyocyte samples, these streamlined and semi-automated processes enable quick mechanistic analysis.

Plants characterized by a soft or weak steam, such as climbing plants, need to find a potential support (e.g., wooden trunk) to reach greater light exposure. Since Darwin’s research on climbing plants, several studies on their searching and attachment behaviors have demonstrated their unique ability to process different support features to modulate their movements accordingly. Nevertheless, the strategies underlying this ability are yet to be uncovered. The present research tries to fill this gap by investigating how the interaction between above- (i.e., stem, tendril, …) and belowground (i.e., the root system) plant organs influence the kinematics of the approach-to-grasp movement. With three-dimensional (3D) kinematical analysis, we characterized the movement of pea plants (Pisum sativum L.) towards a support with different thicknesses above and belowground (i.e., thin below, thick aboveground, or the opposite). As a control condition, the plants were presented to supports with the same thickness below- and aboveground (i.e., either entirely thin or thick). The results suggest an integration between the information from below- and aboveground for driving the reach-to-grasp behavior of the aerial plant organs. Information about the support conveyed by the root system seems particularly important to fulfil the end-goal of the movement.

Both academic literature and global organizations have emphasized the need for responsible water consumption, as stated in the Sustainable Development Goal 12. However, individuals’ water-saving behaviors in their current state are not enough. This situation entails a resistance to change (RC) in consumer habits and a lack of perceived risk of scarcity. The novelty of this study lies in examining the influence of RC (through its emotional, cognitive, and confidence components) and perceived risk on water-saving intention. Interviews (n = 384) were conducted in the southeast Mediterranean area of Spain by interviewers using a paper-and-pencil questionnaire. The results of the structural equation modeling show that the perceived risk and the components of cognitive rigidity and negative emotions exert a direct influence on water-saving habits and an indirect influence on water-saving intention. None of the components of RC directly influence intention, and a lack of confidence in the outcomes of water saving does not influence water-saving habits or water-saving intention. In addition to the results obtained, the novelty of the work lies in the idea that in order to influence the perception of the risk of water scarcity through awareness campaigns, it is better to use an emotional message rather than showing facts or information, because this does not drive water saving behavior.

Peer-to-peer (P2P) energy trading – where energy prosumers transact directly between each other – could help enable transition to a low-carbon energy system. If it is to be supported in policy and regulation, it is important to anticipate the distributional impacts (or how it might impact segments of society differently). However, real-world evidence on P2P energy trading is currently extremely limited. To address this challenge in the short- to medium-term, this study aimed to explore what might be learned from the extensive body of research on a comparable offering in the accommodation sector: Airbnb. A realist review approach was employed to maximise transferability of findings, focused on what mechanisms are thought to lead to what distributional outcomes, in what contexts. On the basis of the review, participation in (and receipt of benefits of) P2P energy trading schemes would be expected to represent disproportionately those living in areas with network management challenges, who are younger and more highly educated. The review also raised the prospect of discrimination on the basis of characteristics such as race and gender where there are high levels of individual choice over who to trade with. Recommendations include monitoring, incentivising diversity, anonymization, and limiting trading choices.

High-performance motor drives that operate in harsh conditions require an accurate and robust angular position measurement to correctly estimate the speed and reduce the torque ripple produced by angular estimation error. For that reason, a resolver is used in motor drives as a position sensor due to its robustness. A resolver-to-digital converter (RDC) is an observer used to get the angular position from the resolver signals. Most RDCs are based on angle tracking observers (ATOs). On the other hand, generalized predictive control (GPC) has become a powerful tool in developing controllers and observers for industrial applications. However, no GPC-based RDC with zero steady-state error during constant speed operation was proposed. This paper proposes an RDC based on a second-order difference GPC (SOD-GPC). In SOD-GPC, the second-order difference operator is applied to design a GPC model with two embedded integrators. Thus, the SOD-GPC is used to design a type-II ATO whose steady-state angle estimation error tends to zero during constant speed operation. Simulation and experimental results prove that the proposed RDC system has better performance than other literature approaches.

The primary purpose of the study was the determination of the spatial day-to-day variability of extreme temperatures in Poland and the dependency of large temperature changes on atmospheric circulation in accordance with the Grosswetterlagen (GWL) classification. The goal was implemented based on data from 1966 to 2015, made available by the Institute of Meteorology and Water Management – National Research Institute. Day-to-day changes in maximum and minimum temperatures were designated with a rate of ≥ 6 °C (large) and with a rate of ≥ 12 °C (very large) and their spatial distribution was presented. Finally, the analysis of the dependency of considerable temperature changes on atmospheric circulation in accordance with the Grosswetterlagen (GWL) classification was conducted. The obtained results showed that in Poland in the period 1966-2015 the number of large changes in both Tmax and Tmin slightly increased, although the fluctuations show spatial variability. Large changes in Tmax occur more frequently in spring, and in Tmin in winter. Large changes in Tmax and Tmin are mainly recorded during cyclonic circulation, however, the anticyclonic circulation types favour especially large decreases in Tmin.

Over the past decade, wireless communication technologies have developed significantly for intelligent applications in road transport. This paper provides an overview of telecommunications-based intelligent transport systems with a focus on ensuring system safety and resilience. In vehicle-to-everything, these problems are extremely acute due to the specifics of the operation of transport networks, which requires the use of special protection mechanisms. In this regard, it was decided to use blockchain as a system platform to support the needs of transport systems for secure information exchange. This paper describes the technological aspects of implementing blockchain technology in vehicle-to-network; the features of such technology are presented, as well as the features of their interaction.

This study presents a new kinetic scheme for the mass yield prediction of waste lignocellulosic biomasses treated by Hydrothermal Carbonization (HTC). The proposed reactions are based on the decomposition, solubilization, and polymerization of each main fraction of the biomass: cellulose, hemicellulose, and lignin. The ash content was assumed to be inert. The kinetic parameters have been obtained by non-linear adjustment using a data set with 220 experimental runs collected from the literature. The results indicate that the pre-exponential factors range was from 7.33 x10¹ to 1.412x10⁵ min^-1, and activation energies were between 33.75 y 225.3 kJ/mol. A good fit is achieved between the observed and predicted data with an R² of 0.81 and an RMSE of 7.7 %. The proposed scheme was validated with the experimental data obtained by the HTC of sawdust (Pinus radiata) and rapeseed (Brassica napus). The experiments were carried out at temperatures of 190, 220, and 250 ºC and reaction times of 0, 30, 60, 90, and 120 min. The predicted values showed an average error of 2.3 and 3.5 %, respectively. Therefore, the kinetic scheme is a useful tool in the conversion analysis of waste biomass treated by HTC.

The tobacco epidemic is one of the leading public health threats the world has ever faced and public health policy that seeks to limit the problem may not only have to target the price of tobacco but also the initiation stage in a smoker’s life – the adolescent stage. This research contributes to the health economics literature by using a Bayesian hierarchical logistic model, estimated using Hamiltonian Monte Carlo (HMC) methods to empirically identify what drives the intentions to quit smoking among adolescent smokers in Zambia. Results suggest that among the junior secondary school-going adolescent smokers in Zambia, about 63% have plans to quit smoking. We find socio-demographic characteristics and several tobacco-smoking-related factors as the main drivers of adolescent smokers’ plans to quit smoking. Most importantly, we provide insights that could be useful to help adolescent smokers realize their quitting plans.

Background: Telemedicine (interconsultation between primary and hospital care teams) has been operating in the counties of Central Catalonia Bages, Moianès and Berguedà since 2011 in the specialties of teledermatology, teleulcers, teleeyelids and teleaudiometries. For the period until the end of 2019, a total of 52,198 visits have been recorded. Objective: To analyse the differential costs between telemedicine and usual care in a semi-urban environment. Methodology: A cost-minimization evaluation, including direct and indirect costs from a societal perspective, distinguishing healthcare and user’s costs, within a three-month period. Results: Telemedicine saved € 780,397 over the period analysed. A differential cost favourable to telemedicine of about € 15/visit has been observed, the patient being the largest beneficiary of this saving (by 85%) in terms of shorter waiting times and travel costs. From the healthcare system perspective, moving the time spent in a hospital care consultation to primary care is efficient in terms of the total time devoted per patient. In social terms and in this context, telemedicine is more efficient than usual care. Conclusion: Users’ saving of time in terms of consultation and travel is the main driver of interconsultation between primary and hospital care savings in a semi-urban context. The telemedicine service is also economically favourable for the healthcare system, enabling it to provide a more agile service, which also benefits the healthcare professionals.