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

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

The recent growth of high-resolution spatial data, especially in developing urban environments, is enabling new approaches to civic activism, urban planning and the provision of services necessary for sustainable development. A special area of great potential and urgent need deals with urban expansion through informal settlements (slums). These neighborhoods are too often characterized by a lack of connections, both physical and socioeconomic, with detrimental effects to residents and their cities. Here, we show how a scalable computational approach based on the topological properties of digital maps can identify local infrastructural deficits and propose context-appropriate minimal solutions. We analyze 1 terabyte of OpenStreetMap (OSM) crowdsourced data to create worldwide indices of street block accessibility and local cadastral maps and propose infrastructure extensions with a focus on 120 Low and Middle Income Countries (LMIC) in the Global South. We illustrate how the lack of physical accessibility can be identified in detail, how the complexity and costs of solutions can be assessed and how detailed spatial proposals are generated. We discuss how these diagnostics and solutions provide a multiscalar set of new capabilities – from individual neighborhoods to global regions – that can coordinate local community knowledge with political agency, technical capability, and further research.

This study examines the prospective association of egg consumption with multiple domains of cognitive function in older, community-dwelling men and women followed 16.3 years. Participants were 617 men and 898 women from the Rancho Bernardo Cohort aged 60 and older who were surveyed about egg intake/week in 1972-74, and attended a 1988-91 research visit when cognitive function was assessed with 12 tests. Analyses showed that egg intake ranged from 0-24/week (means: men=4.23.2, women=3.52.7, p<0.0001). In men, covariate-adjusted regressions showed egg intake was associated with better performance on Buschke total (p=0.04), long-term (p=0.02) and short-term (p=0.05) recall. No significant associations were observed in women (p’s>0.05). Analyses in those <60y at in 1972-74 showed egg intake was positively associated with scores on Heaton copying(p<.04) and the Mini-Mental Status Exam(MMSE;p<.02) in men, and category fluency(p<0.05) in women. Egg intake was not significantly associated with odds of poor performance on MMSE, Trails B, or category fluency in either sex. These reassuring findings suggest there are no long-term detrimental effects of egg consumption on multiple cognitive function domains, and for men, there may be beneficial effects for verbal episodic memory. Egg consumption in middle-age may also be related to better cognitive performance later in life.

Over the past few decades, the growth of the urban population has been remarkable. Nowadays, 50% of the population lives in urban areas, and forecasts point that by 2050 this number will reach 70%. Today, 64% of all travel made is within urban environments and the total amount of urban kilometers traveled is expected to triple by 2050. Thus, seeking novel solutions for urban mobility becomes paramount for 21st century society. In this work, we discuss the performance of vehicular networks. We consider the metric Delta Network. The Delta Network characterizes the connectivity of the vehicular network through the percentage of travel time in which vehicles are connected to roadside units. This article reviews the concept of Delta Network and extends its study through the presentation of a general heuristic based on the definition of scores to identify the areas of the road network that should receive coverage. After defining the general heuristic, we show how small changes in the score computation can generate very distinct (and interesting) patterns of coverage, each one suited to a given scenario. In order to exemplify such behavior, we propose three deployment strategies based on simply changing the computation of scores. The results show that the strategies derived from the general heuristic are very interesting, all of them deploying roadside units in a circle pattern around the traffic epicenter.

A study on flywheel geometries is presented here with the use of finite element modelling (FEM) simulations. The study analyses the stress behaviour of flywheel rotors subject to the rotational speed that creates the maximum stress that the flywheel can support, and then calculates the rotational energy mass ratio (energy density) for each geometry. The obtained geometry was Gaussian section for the Flywheel rotor. The used material for the simulations is carbon fibre Hexcel UHM 12000. The best results were a rotational speed of ≈279.000 rpm and rotational energy density of ≈ 440 Wh/kg for a single disk, but this keeps the total energy low. To increase the total energy, Flywheels with 2 and 3 rotors were analysed. Then the stability under rotation of these Flywheels were analysed, some instability was found and a solution was presented.

Gilbert's syndrome (GS) is a common hereditary condition characterized by mild increases in serum bilirubin levels due to inherited defects in bilirubin metabolism. This review, based on data from peer-reviewed articles and journals spanning from 1977 to January 2024, provides a comprehensive overview of over four decades of research on GS. Early studies primarily focused on defining the clinical and genetic characteristics of the syndrome, laying the foundation for subsequent investigations. More recent research has delved into the genetic mechanisms underlying the reduced expression of bilirubin UDP-glucuronosyltransferase, which has significantly enhanced our understanding of the pathogenesis of GS. Furthermore, recent studies have shed light on the clinical implications of GS, including its association with non-alcoholic fatty liver disease and mortality risk, highlighting the complex interplay between genetic factors, bilirubin metabolism, and clinical outcomes. Despite its generally benign nature, thorough research is essential to fully understand the impact of GS on patients' lives. This review emphasizes the importance of ongoing research to deepen our understanding of GS and its broader implications.

This article explores the lack of unanimity regarding the nomenclature used to refer to the field of research that explores the intersection between art and science. A series of examples of nomenclatures and the context in which they are applied are listed and referenced. The diverse terminology reflects the heterogeneity, transdisciplinarity, and complexity of a research field in full expansion.

Over the past decades, overweight and obesity has become a global epidemic and the leading threat for death. To prevent the serious risk, an overweight or obese individual must apply a long-term weight-management strategy to control food intake and physical activities, which is however, not easy. Recently, with the advances of information technology, more and more people can use wearable devices and smartphones to obtain physical activity information, while they can also access various health-related information from Internet online social networks (OSNs). Nevertheless, there is a lack of an integrated approach that can combine these two methods in an efficient way. In this paper, we address this issue and propose a novel mobile-social framework for health recognition and recommendation, namely, H-Rec². The main ideas of H-Rec² include (1) to recognize the individual's health status using smartphone as a general platform, and (2) to recommend physical activity and food intake based on personal health information, life science principles, and health-related information obtained from OSNs. To demonstrate the potentials of the H-Rec² framework, we develop a prototype that consists of four important components: (1) an activity recognition module that senses physical activity using accelerometer, (2) a health status modeling module that applies a novel algorithm to generate personalized health status index, (3) a restaurant information collection module that collects relevant information from OSN, and (4) a restaurant recommendation module that provides personalized and context-aware recommendation. To evaluate the prototype, we conduct both objective and subjective experiments, which confirm the performance and effectiveness of the proposed system.

Tabebuia aurea (Silva Manso) Benth. & Hook. f. The ex S.Moore (yellow ipe), belonging to the Bignoniaceae family, used in the popular for fever, inflammation and healing of skin wounds. The extract was prepared by maceration, using 70% ethanol. Through HPLC analysis, it was possible to identify substances, mainly phenolic, such as lapachol, present in Bignoniaceae. The phenolic content was 21.36 mg / Eag in the antioxidant activity, the effective concentration of 50% was 53.03 ± 1.14 µg / mL. The antimicrobial activity against S.aureus, E. coli and C. albicans was evaluated by microdilution in broth, which verified action against the tested microorganisms. Cell viability has been inhibited for tumor cells, although this has not been observed for normal cells. The LD50 against A.aegypti mosquito larvae was 3504.6 mg / L and there was no mortality in the concentration tested for the snail B.glabrata. Nontoxic or low toxicity for A. salina and T. molitor, respectively, and did not exhibit hemolytic action at concentrations of antibacterial effect. Given the above, it was concluded that the bark extract of the studied species has bioprospecting potential for the future development of antimicrobial products.

This article introduces a novel payload structure, which has been experimentally proven to have smaller impact force while the carried internal electronics remains intact. The study describes in details how materials and geometric structures were chosen based on information analysis. It is clarified how possible geometric structures and materials can be chosen to yield optimal efficiency. Finite element method simulations were carried out to investigate the mechanical properties of several geometric structures, which has led to the dodecahedron form. For the frame, Polylactic Acid were chosen as an optimal material. A low air pressure test for parts of the structure, and also the whole structure were carried out with successful results. Drop tests, with force measuring sensors and high speed videos, were carried out for measuring and comparing the maximal impact force of classical payloads and the novel one. Laboratory and real life tests demonstrated that the developed new structure is safer and it is applicable.

This paper provides the state of the art of data science in economics. Through a novel taxonomy of applications and methods advances in data science are investigated. The data science advances are investigated in three individual classes of deep learning models, ensemble models, and hybrid models. Application domains include stock market, marketing, E-commerce, corporate banking, and cryptocurrency. Prisma method, a systematic literature review methodology is used to ensure the quality of the survey. The findings revealed that the trends are on advancement of hybrid models as more than 51% of the reviewed articles applied hybrid model. On the other hand, it is found that based on the RMSE accuracy metric, hybrid models had higher prediction accuracy than other algorithms. While it is expected the trends go toward the advancements of deep learning models.

In this paper, inspired by recent articles of G. Anatriello and G. Vincenzi (see \cite{Ana}), and G. Cerda-Morales (see \cite{Cer1,Cer2}), we will introduce the third-order $\overline{h}$-Jacobsthal and third-order $\overline{h}$-Jacobsthal--Lucas sequences and their associated quaternions. The new results that we have obtained extend most of those obtained in \cite{Cer2}.

This research work uses a simplified approach to combine location information from beacons propagation signal interaction with a mobile device with local building information to give real-time location and guidance to a user inside a building. This is an interactive process with visualisation information that can help user’s orientation inside unknown buildings and the data stored from different users can provide useful information about users movements inside a public building. Beacons installed on the building at specific pre-defined position emit signals that give a geographic position with an associated imprecision, related with Bluetooth’s range. This uncertainty is handled by building layout and users’ movement in a developed system that maps users’ position, gives guidance and store user movements. This system is based on an App (Find Me!) for Android OS (Operating System) which captures the Bluetooth Low Energy (BLE) signal coming from the beacon(s) and shows, through a map, the location of the user ‘s smartphone and guide him to the desired destination. Also, the beacons can deliver relevant context information. The application was tested by a panel of new and habitual campus users against traditional wayfinding alternatives yielding navigation times about 30% smaller, respectively.

Bicycling is a tremendously efficient means of transportation both in socio-economic and environmental sustainability parameters. Therefore, they are fast becoming the primary mode of transportation in some other parts of Africa. Quelimane is a city which is found in Mozambique where bicycle-taxi is a major means of transportation. However, very little is known about the social and economic profiles of these city bicycle-taxi riders. Hence, the aim of this study was to determine the socio demographic and economic profile of bicycle-taxi riders. A cross-sectional study survey using a simple random probabilistic sample (n = 357, α = 0.05) was conducted. The questionnaire consisted of 20 items in five major groups, sociodemographic, economics, riding factors, safety and motivational factors. Pearson Chi square, t test and linear regression tests were carried out to test for statistical analysis. The activity is carried out mostly by males (98.9 %), under the age of 35 years. Their academic records, ranking highest, with secondary education background, bicycles are obtained through rental programs in order to perform taxing. After expenses, daily earnings generate a total revenue of USD 5.75. Sex, marital status, house type, years riding, bicycle make and meal per day, are associated with daily revenue income. Bicycle-taxi activity in Quelimane is an income generating activity. Mainly young citizens are involved due to the high unemployment rate. Nonetheless, bicycle taxing created an untapped market for self-employment, where the majority of youths in Quelimane generate their own revenue, thereby improving their livelihood.

We have investigated the antiferromagnetic phase transition in the frustrated and multiferroic hexagonal manganites $h$-(Y$_{0.98}$ Eu$_{0.02}$)MnO$_3$ (YEMO) and $h$-YMnO$_3$ (YMO). Elastic neutron scattering has been used to study in detail the phase transition in YMO and YEMO in zero pressure and in YMO at a hydrostatic pressure of 1.5~GPa. In zero pressure, we find the critical temperature $T_{\rm N} = 72.11(5)$~K and 71.3(1)~K and the critical exponent $\beta = 0.206(3)$ and 0.22(2), for YEMO and YMO, respectively. This is in agreement with earlier work by Roessli {\em et al.}. In applied hydrostatic pressure of 1.5~GPa, the ordering temperature increases to $T_{\rm N} = 75.2(5)$~K, in agreement with earlier reports, while $\beta$ is unchanged. Inelastic neutron scattering was used to determine the anisotropy spin wave gap at the phase transition, expected from spin wave theory to close with a critical exponent $\beta'$ identical to the one of the order parameter, $\beta' = \beta$. Our results indicate that the gap in YEMO indeed closes at $T_{\rm N}=72.4(3)$~K with $\beta' = 0.24(2)$, while the in-pressure gap in YMO closes at 75.2(5)~K with an exponent of $\beta' =0.19(3)$. In addition, the low-temperature anisotropy gap was found to have a slightly higher absolute value under pressure. The consistent values obtained for $\beta$ in the two systems support the likelihood of a new universality class for triangular, frustrated antiferromagnets.

The treatment of the bulky Rind-based dibromosilanes, (Rind)2SiBr2 (2) [Rind = 1,1,7,7-tetra-R1-3,3,5,5-tetra-R2-s-hydrindacen-4-yl: EMind (a: R1 = Et, R2 = Me) and Eind (b: R1 = R2 = Et)], with two equivalents of tBuLi in Et2O at low temperatures resulted in the formation of blue solutions derived from the diarylsilylenes, (Rind)2Si: (3). Upon warming the solutions above −20 °C, the blue color gradually faded, accompanying the decomposition of 3 and yielding the cyclic hydrosilanes (4) via intramolecular C−H bond insertion at the Si(II) center. The molecular structures of the bulky Eind-based 3b and 4b were confirmed by X-ray crystallography. Thus, at −20 °C, blue crystals were formed (Crystal-A), which were identified as mixed crystals of 3b and 4b. Additionally, colorless crystals of 4b as a singular component were isolated (Crystal-B), whose structure was also determined by an X-ray diffraction analysis. Although the isolation of 3 was difficult due to their thermally-labile nature, their structural characteristics and electronic properties were discussed based on the experimental findings complemented by computational results. We also examined the hydrolysis of 3b to afford the silanol, (Eind)2SiH(OH) (5b).

The human landscape transforming activity contributes to the global change of vegetation in different forms. Hunting is one of the most ancient human landscape-shaping activities. Feeders for hunting are particularly disruptive to vegetation. In the present study, we conducted a vegetation survey in these highly disturbed places. We are investigating the vegetation dynamics over several years in in the turkey oak–sessile oak zone, in two areas with different moisture and shade conditions (forest and clearing). One important background factor is changes in precipitation and temperature. The novelty of our present study lies in the fact that the observation takes place with continuous disturbance, where the human influence is very large. Our results confirm that the weed infestation be detectable at bait sites over a long period, and the interannual changes were typical in every year, according to the fact that in August, more weed species are usually present with a greater cover at the bait sites. The main meteorological factors played a role in the degree of weed infestation in each year. There was a higher proportion of vegetation regeneration in wetter years, while dry periods do not favor successional processes. With the drying of the climate, the disturbed areas are constantly losing their natural value, but wetter weather is not an automatic solution either. A more precise understanding of vulnerable systems and careful planning of treatment interventions is necessary.

This paper presents new perspectives of photonic technologies for capsule endoscopy. It is firstly presented a review about conventional endoscopy (upper endoscopy and colonoscopy), followed by capsule endoscopy (CE), as well as their techniques, advantages, and drawbacks. The technologies for CEs presented in this paper have the potential of integration on the existing endoscopic systems commercially available. Such technologies include narrow band imaging (NBI), photodynamic therapy (PDT), confocal laser endomicroscopy (CLE), Optical coherence tomography (OCT) and Spectroscopy in order to improve the performance of the gastrointestinal (GI) tract examination. In the context of NBI, two optical filters were designed and fabricated for integration into endoscopic capsules, allowing the visualization of light centered at the 415 nm and 540 nm. These optical filters are based on the principle of Fabry-Perot and were made of thin-films of titanium dioxide (TiO2) and silicon dioxide (SiO2). Moreover, strategies and aid solutions for the adaptation of ECs for PDT are also discussed.

Background: Tetanus is an acute, fatal disease caused by exotoxins released from Clostridium tetani during infections. A protective humoral immune response can be induced by vaccinations with pediatric and booster combinatorial vaccines that contain inactivated tetanus neurotoxin (TeNT) as a major antigen. Although some epitopes in NeNT have been described using various ap-proaches, a comprehensive list of its antigenic determinants that are involved with immunity have not been elucidated. To that end, a high resolution analysis of the linear B-cell epitopes in NeNT was performed using antibodies generated in vaccinated children. Methods: Two hundred sixty-four peptides that cover the entire coding sequence of TeNT protein were prepared in situ on a cellulose membrane by SPOT synthesis and probed with sera from children vaccinated (ChVS) with a triple DTP-vaccine to map continuous B-cell epitopes that were further characterized and validated by immunoassays. Results: Forty-three IgG epitopes were identified. Four (TT-215-218) were chemically synthesized as Multiple Antigen Peptides (MAPs) and used in peptide ELISAs to screen post-pandemic DTP vaccinations. The assay displayed a high performance with high sensitivity (99.99%) and specificity (100%). Conclusions: The complete map of linear IgG epitopes induced by vaccination with inactivated TeNT highlights three key epitopes involved in the ef-ficacy of the vaccine. Antibodies against epitope TT-8/G can block enzymatic activity, and those against epitopes TT-40/G and TT-42/G can interfere with TeNT binding to neuronal cell receptors. We further show that four of the epitopes identified can be employed in peptide ELISAs to assess vaccine coverage. Overall, the data suggest a set of select epitopes to engineer new, directed vaccines

We have recently introduced the possibility of performing operando small-angle X-ray scattering measurements using a novel industrially relevant injection moulding system for plastics. We show that useful time-resolving measurements can be performed with a time-cycle of 1s and we highlight the possible steps to reduce this to 0.5s. We show how we can use the transmission measurements to provide a time-marker when plastic first enters the mould cavity in the region probed by the incident X-ray beam. We show the opportunities provided by this experimental stage mounted on the NCD-SWEET beamline at ALBA to probe the reproducibility of the injection moulding system on different scales. The design of the equipment allows the development of the structure and the morphology to be evaluated in different parts of mould cavity and we evaluate any differences in a rectangular mould cavity. We identify future prospects for this equipment in terms of novel mould heating and cooling systems and the opportunities for quantitatively evaluating radical approaches to injection moulding technology.

We report on the occurrence of natural Magnesium Alumina Silicate Hydrate (M-(A)-S-H) cement at Feragen and Leka in eastern and western Trøndelag Norway, respectively. Both occurrences are located in the sub-arctic climate zone and form in glacial till and moraine material deposited on ultramafic rock during the Weichselian glaciation. Weathering of serpentinized peridotite dissolve brucite and result in a relative high pH alkaline fluid that subsequently reacts with the felsic minerals of the till (quartz, plagioclase, K-feldspar) to form a cement consisting of an amorphous material or a mixture of nanocrystalline Mg-rich phyllosilicates, including illite. The presence of plagioclase in the till results in the enrichment of alumina in the cement, i.e., forms M-A-S-H instead of the M-S-H cement. Dissolution of quartz results in numerous etch-pits and negative quartz crystals filled with M-A-S-H cement. Where the quartz dissolution is faster that the cement precipitation, a honeycomb-like texture is formed. Compositionally the cemented till (tillite) contains more MgO and has a higher loss of ignition than the till, suggesting that the cement is formed by a MgO fluid that previously reacted with the peridotite. The M-(A)-S-H cemented till represent a new type of duricrust, coined magsilcrete. The study of natural Mg-cement provides information on peridotites as a Mg-source for Mg-cement and as a feedstock for CO2 sequestration.

The problem addressed in this article consists of the motion control of a quadrotor, comprising model disturbances and uncertainties. In order to tackle model uncertainty, adaptive control based on reinforcement learning is used. The distinctive feature of this article, in comparison with other works on quadrotor control using reinforcement learning is the exploration of the underlying optimal control problem in which a quadratic cost and a linear dynamics allow an algorithm that runs in real time. Instead of identifying a plant model, adaptation is obtained by approximating the performance index given by the Q-function using directional forgetting recursive least squares that rely on a linear regressor build from quadratic functions of input/output data. The adaptive algorithm proposed is tested in simulation in a cascade control structure that drives a quadrotor. Simulations show the improvement in performance that results when the proposed algorithm is turned on.

The ultimate goal of this paper was to examine the degree of elasticity between two variables, namely, agricultural credit and agricultural growth, in Angola in the period 2003–2022. Time series data were fitted into the ARDL test using various econometric techniques such as the ADF stationarity test, Granger causality and the ordinary least squares method as well as a vector error correction model (VECM) to analyze the relationship between agricultural credit and agricultural economic growth, showing a causal relationship. Both the impacts through elasticities and the optimal point existing in this relationship were estimated. It was concluded that the impact of agricultural credit on agricultural GDP was 14.41%. Granger causality shows signs of a positive linkage between agricultural credit and agricultural GDP. However, there is a causal relationship between agricultural credit and agricultural GDP, in a unidirectional aspect. This result is consistent with most of the earlier studies reviewed in the literature, confirming that credit-oriented monetary policies can boost economic growth and, consequently, development in Angola. It is important for agricultural credit systems to be designed in a way that ensures equitable access, fair interest rates, and appropriate risk management mechanisms. Additionally, monitoring and evaluation mechanisms should be in place to assess the environmental and social impacts of credit programs on agricultural sustainability. It is worth noting that this is a first-of-a-kind study on the matter of the Angolan credit experience, specifically for the agricultural sector. Angola is still searching for a sustainable credit model that could be used as a catalyzer to boost growth and contribute to economic development.

In this paper a full state feedback control of a double inverted pendulum on a cart (DIPC) are designed and compared. Modeling is based on Euler-Lagrange equations derived by specifying a Lagrangian, difference between kinetic and potential energy of the DIPC system. A full state feedback control with H infinity and H 2 is addressed. Two approaches are tested: open loop impulse response and a double inverted pendulum on a cart with full state feedback H infinity and H 2 controllers. Simulations reveal superior performance of the double inverted pendulum on a cart with full state feedback H infinity controller.

Using the h-index to assess individual researchers is not only unethical and unfair but also inaccurate and misleading. This index fails to offer a reliable measure of a researcher's impact based on their citation scores. Beyond statistical and conceptual considerations, authorship practices, especially in the case of multi-authored publications, give rise to significant problems that often go unnoticed. While some modifications of the h-index have been proposed to mitigate these weaknesses, the fundamental deficiencies persist. Most of these flaws have been effectively addressed by the c-score, a composite citation index. The c-score excludes self-citations, normalizes the number of citations by considering the number of authors in each paper, and takes into account first, single, and last authorship. This approach provides a more realistic measure of the impact of each individual researcher based on raw citations.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

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

Changes in food quality can dramatically impair zooplankton fitness, especially in eutrophic water bodies where cyanobacteria are usually predominant. Cyanobacteria are considered a food with low nutritional value, besides some species can produce bioactive secondary metabolites reported as toxic to zooplankton. Considering that cyanobacteria can limit survival, growth and reproduction of zooplankton, we hypothesized that the adverse effects of the dietary exposure of Daphnia species to saxitoxin-producing cyanobacteria depend on the relative abundance of nutitious food source in the diet. Life table experiments were conducted with different diets: 1) without nutritional restriction, where neonates were fed with diets at a constant green algae (Monoraphidium capricornutum) biomass as a nutritious food source, and increasing cyanobacterial concentration (STX-producing Raphidiopsis raciborskii), and 2) with diets consisting of different proportions of M. capricornutum (nutritious) and R. raciborskii (poor food) at a total biomass 1.0 mg C L 1. In general, the presence of high proportions of cyanobacteria promoted a decrease in Daphnia somatic growth, reproduction and intrinsic rate of population increase (r) in both diets with more pronounced effects in the nutritionally restricted diet (90% R. raciborskii). Two-way ANOVA revealed significant effects of species/clone and treatments in both assays, with significant interaction between those factors only in the second assay. Regarding the grazing assay, only D. laevis was negatively affected by increased cyanobacterial proportions in the diet. In the life table assay with constant edible food, a reduction in the reproduction parameters and the intrinsic rate of population increase (r) of all species was observed, In conclusion, we found adverse effects of the toxic cyanobacterial strain R. raciborskii on Daphnia fitness, regardless of the constant amount of nutritious food available, proving the toxic effect of R. raciborskii and the nutritional quality of the food has a greater influence on the fitness of these animals.

In this paper, we propose an imagined speech-based brain wave pattern recognition using deep learning. Multiple features were extracted concurrently from eight-channel Electroencephalography (EEG) signals. To obtain classifiable EEG data with fewer number of sensors, we placed the EEG sensors on carefully selected spots on the scalp. To decrease the dimensions and complexity of the EEG dataset and to avoid overfitting during the deep learning algorithm, we utilized the wavelet scattering transformation. A low-cost 8-channel EEG headset was used with MATLAB 2023a to acquire the EEG data. The Long-Short Term Memory Recurrent Neural Network (LSTM-RNN) was used to decode the identified EEG signals into four audio commands: Up, Down, Left, and Right. Wavelet scattering transformation was applied to extract the most stable features by passing the EEG dataset through a series of filtration processes. Filtration has been implemented for each individual command in the EEG datasets. The proposed imagined speech-based brain wave pattern recognition approach achieved a 92.50% overall classification accuracy. This accuracy is promising for designing a trustworthy imagined speech-based Brain-Computer Interface (BCI) future real-time systems. For better evaluation of the classification performance, other metrics were considered, and we obtained 92.74%, 92.50% and 92.62% for precision, recall, and F1-score, respectively.

Dry powder inhalers are used by a large number of patients worldwide to treat respiratory diseases. The objective of this work is to experimentally investigate changes in aerosol particle diameter and particle number concentration of pharmaceutical aerosols generated by five dry powder inhalers under realistic inhalation and exhalation conditions. The active respiratory system model (xPULM™) was used as a model of the human respiratory system and to simulate a patient undergoing inhalation therapy. A mechanical upper airway model was developed, manufactured and introduced as a part of the xPULM™ to represent the human upper respiratory tract with high fidelity. Integration of optical aerosol spectrometry technique into the setup allowed for evaluation of pharmaceutical aerosols. The results show that the upper airway model increases the resistance of the overall system and act as a filter for bigger particles (>3 µm). Furthermore, there is a significant difference (p < 0.05) in mean particle diameter between inhaled and exhaled particles with the majority of the particles depositing in the lung. The minimum deposition is reached for particle size of 0.5 µm. The mean particle number concentrations exhaled are 2.94% (BreezHaler®), 2.66% (Diskus®), 10.24% (Ellipta®) 2.13% (HandiHaler®) and 6.22% (Turbohaler®). In conclusion, the xPULM™ active respiratory system model is a viable option for studying interactions of pharmaceutical aerosols and the respiratory tract in terms of applicable deposition mechanisms. The model can support the reduction of animal experimentation in aerosol research and provide an alternative to experiments with human subjects.

A modular approach to the construction of electric machines, drive systems, power supply systems is a new direction of modern technology development. Especially, the modular approach is promising for electric vehicles due to such positive aspects as increased efficiency, fault tolerance, overall reliability, safety, enhanced control capabilities, etc. In this work, the modular approach is comprehensively applied to an EV powertrain system, which includes a dual three-phase (DTP) BLDC motor with two machine modules of an asymmetric configuration, two battery modules and a supercapacitor module (SCM). The proposed H–H configuration of modular EV powertrain system includes four voltage source inverters that combine the power modules with the open ends of the windings (OEW) of the module machine armature, and provide control of their operation. Based on the developed mode system of the OEW machine module operation for EV traction and braking, a general control algorithm for the proposed configuration of the modular EV powertrain system has been developed. It combines the control of the operating modes with the functions of maintaining the required SOC level of the SCM and equalizing the SOCs of the two battery modules. The conducted simulation and experimental studies confirmed the workability and effectiveness of the proposed solutions.

Recently, new semantic segmentation and object detection methods have been proposed for direct processing of three-dimensional (3D) LiDAR sensor point clouds. LiDAR can produce highly accurate and detailed 3D maps of natural and man-made environments and is used for sensing in many contexts due to its ability to capture more information and its robustness to dynamic changes in the environment. In addition, the cost of LiDAR sensors has decreased in recent years, which is an important factor for many application scenarios. The challenge with 3D LiDAR sensors like the Velodyne HDL-64E S2 is that they can output large 3D data at up to 1,300,000 points per second, which is difficult to process in real time when applying complex algorithms and models for efficient semantic segmentation. Most existing approaches are either only suitable for relatively small point clouds or rely on computationally intensive sampling techniques to reduce their size. As a result, most of these methods do not work in real-time in realistic field robotics application scenarios, making them unsuitable for practical applications. Systematic point selection is a possible solution to reduce the amount of data to be processed, but although it is memory and computationally efficient, it selects only a small subset of points, which may result in important features being missed. To address this problem, we propose a new approach to semantic segmentation in forestry that uses a systematic sampling method in which the local neighbors of each point are retained to preserve geometric details. Our approach has been shown to process up to 1 million points in a single pass. It outperforms the state of the art in efficient semantic segmentation in large datasets such as Semantic3D. We also present a preliminary study on the performance of LiDAR-only data, i.e., intensity values from LiDAR sensors without RGB values for semi-autonomous robot perception.

From the merge of arts and crafts towards a practice for mass production of desirability, consumption and product development in a capitalist economy of scale, design has lost its natural ability of problem comprehension and tension alleviation. The modern world needs the creativity, flexibility, and responsiveness embedded into design practices, mostly when a behavioural change, either individual or organizational, is intended. Still, the informality nature of the field is creating a gap between the study, research, and industrial design practice. Here it is presented the Biology of Creativity Model (BoC) which is a design-by-analogy method that promotes an empowered design practice through analysis of mostly biology reference texts for enhanced creativity and innovation performance in a diverse array of contexts.

In this paper, the design and analysis of coupled tank water level control system is done using robust control theory. The main aim of this work is to improve level controlling mechanisms in industries and household areas. In this paper, H ∞ and μ –synthesis controllers are designed to improve the level control system. The coupled tank water level control system is designed using the proposed controller’s comparison and tested for tracking a reference level signals (step, sine wave and random) and simulation results have been analyzed successfully. Finally the comparative simulation results prove the effectiveness of the proposed coupled tank water level control system with H ∞ controller for improving the tracking mechanism performance of the system.

In this work, we introduce the class of h-MN-convex functions by generalizing the concept of MN-convexity and combining it with h-convexity. Namely, let M : [0, 1] → [a, b] be a Mean function given by M (t) = M (t; a, b); where by M (t; a, b) we mean one of the following functions: A_t (a, b) := (1 − t) a + tb, G_t (a, b) = a^1−tb^t and H_t (a, b) := $\frac{ab}{ta+\left(1-t\right)b}=\frac{1}{A_t\left(\frac{1}{a},\frac{1}{b}\right)}$ with the property that M (0; a, b) = a and M (1; a, b) = b. Let I, J be two intervals subset of (0, ∞) such that (0, 1) ⊆ J and [a, b] ⊆ I. Consider a non-negative function h : J → (0, ∞), a function f : I → (0, ∞) is said to be h-MN-convex (concave) if the inequality f (M (t; x, y)) ≤ (≥) N (h(t); f (x), f (y)), holds for all x, y ∈ I and t ∈ [0, 1]. In this way, nine classes of h-MN-convex functions are established, and therefore some analytic properties for each class of functions are explored and investigated. Characterizations of each type are given. Various Jensen’s type inequalities and their converses are proved.

One of the main challenges of cultured meat is reducing the costs of production, often described as scaling. The main components of the cultivation process include: cells, media, scaffolds and bioreactors. This work presents an alternative to current stainless steel or glass bioreactors and uses food-grade plant-based scaffolds. Bioreactors must be sterile and leak-free to maintain a proper environment for cell growth. Thermoplastic films are a popular material for constructing these fluidic systems, but traditional methods of welding these film are expensive and do not allow rapid prototyping resulting in high research and development costs for companies. In this study, a laser welding method was developed to join thermoplastic films in a way that prevents contamination and leaks, affording effective macro-fluidics fabrication. This technique was tested using polyethylene (PET) films and a laser cutter operating with settings calibrated for the material to be welded or cut. The laser welding method was found to produce strong, leak-free seals in PET films with minimal heat-induced damage to the films. The ability to design fluidics, chambers and ports of various size. Using this method afforded the incorporation of plant-based scaffolds from food-grade plants (Rice). The laser welding method developed in this study provides a reliable, contamination-free method for the rapid fabrication of fluidic systems for cell cultivation. This technique has the potential to be compatible with a vast range of cell types and scaffolds and to be widely adopted in tissue engineering for regenerative medicine and food applications such as cultured meat.

Detecting and monitoring changes in soil salinity through remote sensing provides an opportunity for field assessment in regions where on-site measurements are limited. This investigation, carried out in Siwa Oasis, Egypt, aimed to assess the efficacy of several soil salinity indices derived from Landsat 5 and 7 satellite images. To achieve this, 56 on-site ground measurements were utilized for evaluation purposes. The study aimed to improve the correlation between EC and index values and explore the relationship between salinity and changes in land cover. Eleven spectral indices were calculated for nine scenes captured in different months from August to December. The first approach involved stacking the data to identify the index with the strongest correlation with ground EC values, without the need for complex analysis or EC value ranging. In the second approach, the ground EC measurements were classified into seven different salinity categories, and the correlation coefficient was calculated between each index and each salinity category. The third approach analyzed the data temporally, considering different salinity levels. Lastly, a spatial correlation analysis was conducted between EC and index values in the fourth scenario. The initial approach revealed a weak correlation due to substantial variation in EC values. However, the SI index demonstrated the highest correlation coefficient of 0.38. In the second scenario, the S2 index exhibited the highest correlation of 0.96 for moderate salinity samples. The third scenario showed that the S1 index achieved the highest correlation value of 0.99 for moderately saline areas. In the fourth scenario, the SI index exhibited the strongest correlation among all four ponds with correlation coefficients of 0.23, 0.23, 0.18, and 0.61. Notably, the correlations observed in the second and third scenarios demonstrated higher correlation coefficients compared to both the first and fourth scenarios. The study highlighted significant variations in EC levels related to land cover types and pond elevation. Additionally, remote sensing methods detected a 48% increase in total vegetated area over 17 years, showing the potential of remote sensing techniques in salinity monitoring for expanding agriculture and improving land management.

We hypothesize the possible route of introduction of the cosmopolitan DENV-2 genotype into Brazil through the border with Peru. The five sequences presented in this study create a geographical link with the three others sequences of this genotype already recorded on the continent.

Southern highbush blueberry plantations have been expanded into worldwide non-traditional growing areas with elite cultivars and improved horticultural practices. This article presents a comprehensive review of current production systems – alternatives to traditional open field production – such as production in protected environments, high-density plantings, evergreen production, and container-based production. We discuss the advantages and disadvantages of each system and compare their differences to the open field production. In addition, potential solutions have been provided for some of the disadvantages. We also highlight some of the gaps existing between academic studies and production in industry, providing a guide for future academic research. All these alternative systems have shown the potential to produce high yields with high quality berries. Alternative systems, compared to the field production, require higher establishment investments and thus create an entry barrier for new producers. Nevertheless, with their advantages, alternative productions have potential to be profitable.

The spin-1/2 quantum transverse Ising model, defined on a ladder structure, with nearest-neighbor and four-spin interaction on a plaquette, is studied by using exact diagonalization and finite-size-scaling procedures. The quantum phase transition between the ferromagnetic and paramagnetic phases has been obtained in the thermodynamic limit. The critical transverse field decreases as the antiferromagnetic four-spin interaction increases, and reaches a multicritical point. However, the exact diagonalization approach was not able to capture the essence of the dimer phase beyond the multicritical transition.

In this research paper we describe the development phase of a low-cost LoRa IoT solution applied to a kindergarten school with three years results. A set of sensors solution was developed in a LoRa communication board, battery powered, providing a simplified setup process. These sensors were used in order to measure temperature, humidity, luminosity, air quality and presence. Also, energy monitor solutions were integrated. The acquired data is transmitted and analysed for knowledge extraction, identifying savings and other related KPIs. From data, automatic saving actions were performed towards heating and cooling systems, lighting and a set of if-then actions were developed for automatic cost-saving actions, based on infrared signals to heating/cooling systems using some procedure of external command devices. This approach avoids the usage of proprietary vendor solutions in a flexible approach that can easily be deployed to any building facility. This is an important achievement since most of the building consumption is based on heating and cooling systems. In a three years test of the solution, the total energy consumption savings surpassed 20%

There is much discussion regarding the Sustainable Development Goals’ (SDGs) capacity to promote inclusive development. While some argue that they represent an opportunity for goal-led alignment of stakeholders and evidence-based decision-making, other voices express concerns as they perceive them as a techno-managerial framework that measures development according to quantitatively defined parameters and does not allow for local variation. We argue that the extent to which the positive or negative aspects of the SDGs prevail depends on the monitoring system’s ability to account for multiple and intersecting inequalities. The need for sub-nationally (urban) representative indicators poses an additional methodological challenge – especially in cities with intra-urban inequalities related to socio-spatial variations across neighbourhoods. This paper investigates the extent to which the SDG indicators’ representativeness could be affected by inequalities. It does so by proposing a conceptual framing for understanding the relation between inequalities and SDG monitoring, which is then applied to analyse the current methodological proposals for the indicator framework of the “urban SDG”, Goal 11. The outcome is a call for 1) a more explicit attention to intra-urban inequalities, 2) the development of a methodological approach to “recalibrate” the city-level indicators to account for the degree of intra-urban inequalities, and 3) an alignment between methodologies and data practices applied for monitoring SDG 11 and the extent of the underlying inequalities within the city. This would enable an informed decision regarding the trade-off in indicator representativeness between conventional data sources, such as censuses and household surveys, and emerging methods, such as participatory geospatial methods and citizen-generated data practices.

Disorders associated with substance abuse are a major public health crisis with few treatment options. According to World Health Organization (WHO) ethanol is the most widely used drug in the world, and it represents a risk factor for the advent of disease, disability, and eventually death. Foetal Alcoholic Spectrum Disorders (FASD) is a diagnostic term to describe the range of effects that can occur in an individual whose mother drank alcohol during pregnancy. These effects encompass both physical, mental, behavioural and further lifelong disabilities. Besides, ethanol can harm the gut microbiota. Gut microbiome is firstly acquired from the mother and it is crucial for intestinal homeostasis during hosts’ lifetime. It is responsible for producing metabolites that benefits and protects the host from harm microbial colonization. Knowledge about the interactions between human gut microbes and the developing nervous system is still scarce. Nevertheless, animal models have shown that gut bacteria and microbial metabolites are strongly associated with Central Nervous System (CNS) homeostasis. Endotoxins such as Lipopolysaccharides (LPS) are hypothesized to have a major role in neurodegeneration, however, conclusions must be taken with care due to differences in sensitivity between humans and mice. In this review we focus on the role of gut microbiota on the neurodevelopment of mice when ethanol consumption is one of the major stressors during prenatal period. We detail the range of the endotoxin hypothesis in describing endotoxins’ contribution to neurodegeneration and the influence that kynurenine pathway has on the process.

Despite the continued growth of the sport, particularly among recreational athletes, very little is known about how triathletes prepare for an event. The aim of this study was to identify the training characteristics of recreational-level triathletes and assess how their preparation for a triathlon influences their health and fatigue. During the 6 weeks prior to an Olympic distance triathlon, and the 2 weeks after the event, ten (5 males, 5 females) recreational athletes completed a daily training log to provide information on every training session. In addition, participants answered the Daily Analysis of Life Demands Questionnaire (DALDA), the Training Distress Scale (TDS), and the Alberta Swim Health Questionnaire weekly. Training loads were calculated using session-based rating of perceived exertion (sRPE) and training impulse (TRIMP). Every week of training was compared to week 1 to determine how athletes’ training and health changed throughout the study. In the 6 weeks leading up to the event, training loads, total minutes trained, and time spent in each training zone did not differ significantly. Significant reductions in training duration (Z=2.39, p=0.017, ES = 0.90), training strain (Z=2.59, p=0.009, 0.98), and number of sessions (Z=2.49, p=0.012, ES = 0.94) were seen on week 6. Training intensity distribution favored a threshold approach with athletes spending 56% of their training time at zone 1, 40% at zone 2, and 4% at zone 3. No significant changes were seen in the DALDA or TDS questionnaires. The results show that while the training intensity distribution of recreational-level triathletes does not follow a polarized model, these athletes were able to maintain their health while preparing for an Olympic distance triathlon.

This paper aims to unify q-derivative/q-integral and h-derivative/h-integral in a single definition, this will be called q−h-derivative/q−h-integral. These notions are further extended on finite interval [a,b] in the form of left and right q−h-derivatives and q−h-integrals. Some inequalities are studied for q−h-integrals which are directly connected with well known results. In diverse fields of science and engineering the theory based on q-derivatives/q-integrals and h-derivatives/h-integrals can be unified by using the concept of q−h-derivative/q−h-integral.

In this study, we define new classes of convexity called of h-Godunova-Levin and h-Godunova-Levin preinvexity, through which some new inequalities of Hermite-Hadamard type were established. These new classes are the generalisation of several known convexity including the s-convex, P-function, Godunova-Levin. Further, the properties of h-Godunova-Levin function were also discussed. Meanwhile, the applications of h-Godunova-Levin Preinvex function are given

In this work, several inequalities of Popoviciu type for h-MN-convex functions are proved, where M and N are denote to Arithmetic, Geometric and Harmonic means and h is a non-negative superadditive or subadditive function.

Renewable resources gain increasing interest as source for environmentally benign biomaterials, such as drug encapsulation/release compounds, and scaffolds for tissue engineering in regenerative medicine. Being the second largest naturally abundant polymer, the interest in lignin valorization for biomedical utilization is rapidly growing. Depending on resource and isolation procedure, lignin shows specific antioxidant and antimicrobial activity. Today, efforts in research and industry are directed toward lignin utilization as renewable macromolecular building block for the preparation of polymeric drug encapsulation and scaffold materials. Within the last five years, remarkable progress has been made in isolation, functionalization and modification of lignin and lignin-derived compounds. However, literature so far mainly focuses lignin-derived fuels, lubricants and resins. The purpose of this review is to summarize the current state of the art and to highlight the most important results in the field of lignin-based materials for potential use in biomedicine (reported in 2014–2018). Special focus is drawn on lignin-derived nanomaterials for drug encapsulation and release as well as lignin hybrid materials used as scaffolds for guided bone regeneration in stem cell-based therapies.

Most research on colostrum quality and colostrum management focuses on maternal IgG transfer to the newborn calf. However, in addition to being a source of antibodies, colostrum has other components that influence passive immune transfer, nutrition, gut maturation, and thermoregulation. In this review, the constituents in the bovine colostrum, as well as their variation, are explored and it is discussed the biological role of colostrum on the newborn calf. Protein is the nutrient in higher concentration and fat is the nutrient with the most variation. There is a pronounced amplitude in the total solids content of colostrum, but the average concentration does not vary much between studies (24.7%). Bovine colostrum major components can vary with several factors, such as the region, season, breed, dry period length, and nutritional aspects of the dam. Bioactive components, cells, and microbiome variability are less understood, besides IgG. Regardless, they play crucial distinct roles in the physiological development of the newborn. However, a multi-interactive effect between these components, cells, and microorganisms is more likely to occur. Recently researched components in colostrum like miRNA, nucleo(t)sides, the milk fat globule membrane, oligosaccharides, minor proteins, and the microbiome are examples of promising interest areas of study.

Introduction: Body size is correlated with many aspects of an animal species' natural history, such as life span, abundance, dispersal capacity and diet breadth. However, contrasting trends have been reported for the relationship between body size and these ecological traits. Methods: Butterfly species from fruit-feeding guilds were used to investigate whether body size correlates with species abundances, dispersal, permanence, and diet breadth in a Neotropical savanna in Brazil (Cerrado). We used Blomberg’s K and Phylogenetic Generalized Least Squares models (PGLS) to measure phylogenetic signal strength in species traits, and to estimate size-dispersal-diet breadth associations while taking shared ancestry into account. Results: 539 individuals from 27 species were captured, and 190 individuals were recaptured, representing a 35% recapture rate. We found that body size negatively influenced butterfly abundance. In contrast, body size was positively associated with dispersal levels, distance traveled, number of traps visited, individual permanence, and diet breadth. These results indicate that larger butterflies have a greater proportion of dispersing individuals over longer distances, as they permanence were detected over longer periods than their smaller relatives. Moreover, larger butterflies are more generalized, based on the number of host plant families and genera they consume. Smaller butterflies demand fewer resources, which is reflected in their higher survival in small patches, and may explain their lower dispersal ability, and higher diet specialization. Nevertheless, lower dispersal ability, if not compensated by large population sizes, may threaten small-bodied species inhabiting environments with intense deforestation rates, such as the Cerrado. Conclusions: Body size positively influences dispersal and diet breadth in the fruit-feeding butterflies collected in this study.

Objective: To evaluate the direct costs of treating patients with neuromyelitis optica spectrum disorders (NMOSD) in outpatient care, from a hospital and Unified Health System (SUS) perspective. Methods: Observational study with data collection by microfunding, carried out with patients diagnosed with neuromyelitis optics, treated at a university hospital, in the city of Rio de Janeiro. Mann-Whitney tests were performed to measure cost differences between patient groups by disease severity and analysis perspective. Results: Nine individuals with a median age of 48 years (IQR 30 - 59 years) were included. The median total costs for patients with greater severity from the perspective of the SUS and the hospital were R$ 21,638.22 (IIQ: R$ 15,614.63; R$ 25,985.32) and R$ 32,094.11 (IIQ: R$ 25,610 .60; R$ 38,617.25) respectively. For patients with moderate severity the median was R$ 7,339.85 (IIQ: R$ 6,235.45; R$ 11,912.05) from the SUS perspective and R$ 11,505.80 (IIQ: R$ 7,339.85; R$ 22,424.76) from the perspective of the hospital, where the use of medications had a major impact. Conclusion: The main cost drivers were medicines, especially those used off-label, and procedures.

The study of eco-evolutionary feedbacks is in clear recent expansion. However, most studies concern predator-prey and host-parasite interactions, while the analysis of eco-evolutionary feedbacks involving sexual interactions is lagging behind. This is at odds with the potential of these interactions to engage in such processes. Indeed, there is now ample evidence that sexual selection is affected by ecological change. There is also evidence that sexual selection traits evolve rapidly, which may modify the ecological context of species, and thus the selection pressures they will be exposed to. Here, we first set a clear distinction between processes in which ecology drives evolution and those in which the contemporary evolution of populations may change their ecology, depending on which traits act as drivers and objects of change. We then review evidence for these processes and discuss examples of closed eco-evolutionary feedbacks in an attempt to understand how we can tear this loop apart. We suggest that a better understanding of eco-evolutionary feedbacks of sexual selection may help us understand the effects of sexual selection on the rate of adaptation, speciation, and extinction, and thus foster future research in this area.

The current management of colorectal cancer liver metastasis (CRCLM) patients involves a multidisciplinary approach with surgical resection remaining the primary curative option. The advances in liver surgery have improved outcomes, enabling more patients to undergo surgery successfully. In addition, the development of imaging software has improved the preoperative planning and patient selection for surgery and other interventions. Systemic therapies, such as targeted therapies and immunotherapies have enhanced the chances of complete resection. Targeted agents in combination with chemotherapy, have shown efficacy in downstaging tumors and increasing resectability.

On the H-type group G⊂Rm×Rn, we study the existence of solutions for the Brezis-Nirenberg problem

Most Acinetobacter baumannii strains are naturally competent. Although some information is available about factors that enhance or reduce the frequency of transformation of this bacterium, the regulatory elements and mechanisms are barely understood. In this article, we describe studies on the role of H-NS in the regulation of expression of genes related to natural competency and the ability to uptake foreign DNA. The expression levels of the natural transformation-related genes pilA, pilT, pilQ, comEA, comEC, comF, and drpA were significantly increased in a Δhns derivative of Acinetobacter baumannii A118. Complementation of the mutant with a recombinant plasmid harboring hns restored expression levels of six of these genes (pilT remained expressed at high levels) to those of the wild-type strain. The transformation frequency of the A. baumannii A118 Δhns strain was significantly higher than that of the wild-type. Similar, albeit not identical, effects occurred when hns was deleted from the hypervirulent A. baumannii AB5075 strain. Reduction of gene expression in a few cases was not as pronounced as to reach wild-type levels, and expression of comEA was enhanced further. In conclusion, the expression of all seven transformation-related genes was enhanced after deleting hns in A. baumannii A118 and AB5075, and these modifications are accompanied by an increase in the cells’ transformability. The results demonstrate a role of H-NS in A. baumannii’s natural competence.

Introduction: The trophoblast derived angiogenic factors are considered to play an important role in the pathophysiology of various complications of pregnancy. The aim of this study was to establish relationship between concentrations of soluble Human Leukocyte Antigen-G (sHLA-G) in maternal serum and amniotic fluid at 16-22 weeks of gestation and the sonographic measurements of the fetal and placental growth. Materials and methods: sHLA-G in serum and amniotic fluid, as well as fetal biometric data and placental volume and perfusion indices were determined in 41 uncomplicated singleton pregnancies. Results: The sHLA-G levels were unchanged both in amniotic fluid and in serum during mid-pregnancy. The sHLA-G level in serum correlated positively with amniotic sHLA-G level (β=0.63, p<0.01). Significant correlation was found between serum sHLA-G level and abdominal measurement (β=0.41, p<0.05) and estimated fetal weight (β=0.41, p<0.05). The amniotic sHLA-G level and placental perfusion (VI: β = -0.34, p<0.01 and VFI: β = -0.44, p<0.01, respectively) were negatively interrelated. A low amniotic sHLA-G level was significantly associated with nuchal translucency (r = -0.102, p<0.05). Conclusions: sHLA-G assayed in amniotic fluid might be a potential indicator for placental function, whereas the sHLA-G level in serum can be a prognostic modality for feto-placental insufficiency.

Chromoblastomycosis (CBM) and phaeohyphomycosis (FEO) are infections caused by melanized filamentous fungal agents, primarily found in tropical and subtropical regions. Both infections pose significant challenges for the correct identification of the causative agent due to their morphological similarity, making conventional methods of morphological analysis highly subjective. Therefore, molecular techniques are necessary for the precise determination of these species. In this regard, this study aimed to contribute to a new methodology based on PCR-RFLP for the identification of agents causing CBM and FEO. Sequences from the ITS region were used to identify potential restriction enzyme sites in silico, followed by in vitro validation using the selected restriction enzymes. The obtained results were compared with species identification through morphological analyses and sequencing. The results demonstrated that the PCR-RFLP applied in this study accurately identified two major agents of chromoblastomycosis, Fonsecaea pedrosoi and Fonsecaea monophora, as well as Cladophialophora bantiana and Exophiala dermatitidis, both causative agents of phaeohyphomycosis. In this context, the proposed assay can complement current methods for identifying these species, aiding in diagnosis, and contributing to the proper management of these infections.

Visual impairment and blindness are a growing public health problem, as they reduce the quality of life of millions of people. The management and treatment of these diseases represent a scientific and therapeutic challenge, since the different cellular and molecular actors involved in the pathophysiology are still being identified. The visual system components, particularly the retinal cells, are extremely sensitive to genetic or metabolic alterations, and immune cells activated by insults contribute to biological events that culminate with vision loss and irreversible blindness. Several ocular diseases are linked to retinal cell loss, and diseases such as retinitis pigmentosa, age-related macular degeneration, glaucoma and diabetic retinopathy are characterized by pathophysiological hallmarks that represent possibilities to study and develop novel treatments for retinal cells degeneration. Here, we present a compilation of revisited information on retinal degeneration, including pathophysiologic and molecular features, biochemical hallmarks and possible directions for novel treatments, aiming to assist as a guide for innovative research. The expansion of knowledge of the mechanistic bases of the pathobiology of eye diseases, including information on the complex interactions of genetic predisposition, chronic inflammation, and environmental and aging-related factors will allow the identification of new therapeutic strategies.

Design has often been interpreted as a practice of creating novel objects. However, the relationships between objects analysed upstream the process of creation have been under-studied. Here it is presented a model for enhancing the design practice by fostering a deep work on the relationships of mundane objects. The Three-dimensional Narratives (TdN) model comprises a stepwise five phases work package that facilitates a varied range of analyses to improve the creativity and innovation of any project led by any type of participants. One particular feature of the TdN model is the appropriation of concepts coming from non-design fields such physics and biology to both developing the work of the model and to improve the comprehension and outcomes of the enrolled participants. During three Case Studies with children, youngsters, and older participants the TdN model was validated, and its usability was successfully assessed. The TdN model shows that there is a need for a deeper design practice and that it is relevant to improve the lexicon of designers in order to facilitate a broader and design practice, irrespectively of the aim of the proposed project and nuances of the audience.

Reactions in water between the Cu2(µ-EGTA) chelate (EGTA = ethylene-bis(oxyethyleneimino)tetraacetate(4-) ion) and 2,6-diaminopurine (Hdap) in molar ratios 1:1 and 1:2 yield only blue crystals of the ternary compound [Cu4(μ-EGTA)2(μ-H(N3)dap)2(H2O)2]·7H2O (1) that has been studied by single crystal X-ray diffractometry, various physical methods (thermal stability, spectral and magnetic properties), as well as DFT theoretical calculations. In the crystal, uncoordinated water is disordered. The tetranuclear complex molecule also has some irrelevant disorder in an EGTA-ethylene moiety. In the complex molecule, both bridging organic molecules act as binucleating ligands. There are two distorted five- (type 4+1) and two six- (type 4+1+1) Cu(II) centres. Each half EGTA acts as a tripodal tetradentate Cu(II) chelator, with mer-NO2+O(ether, distal) conformation. Hdap exhibits the tautomer H(N3)dap, with the dissociable H-atom on its less basic N-heterocyclic atom. These features favour the efficient cooperation between Cu-N7 or Cu-N9 bonds with appropriate O-EGTA atoms, as N6-H···O or N3-H···O interligand interactions respectively. Bridging role of both organics determines the tetranuclear dimensionality of the complex in 1. In this crystal, such molecules associate in zig-zag chains, built by alternating ,-interactions between the five- or six-atom rings of Hdap ligands of adjacent molecules. DFT theoretical calculations (using two different theoretical models and characterized by the quantum theory of “atoms in molecules”) reveal the importance of these ,-interactions between Hdap ligands, as well as that corresponding to the referred hydrogen bonds in the contributed tetranuclear molecule.

There is now evidence that, based on cytokine profiles, bipolar disorder (BD) is accompanied by simultaneous activation of the immune-inflammatory response system (IRS) and the compensatory immune-regulatory system (CIRS), and that both components may be associated with the staging of illness. Nevertheless, no BD studies have evaluated the IRS/CIRS ratio using CD (cluster of differentiation) molecules expressed by peripheral blood activated T effector (Teff) and T regulatory (Treg) subpopulations. This study examined T cell subsets both before and after ex vivo anti CD3/CD28 stimulation using flow cytometric immunophenotyping in 25 euthymic BD patients and 21 healthy controls as well as human cytomegalovirus (HCMV)-specific IgG antibodies. BD is associated with a significantly lowered frequency of baseline (unstimulated) CD3+CD8+CD71+ and CD4+CD25+FOXP3 and increased CD4+CD25+FOXP3+CD152+ frequencies and with lowered stimulated frequencies of CD3+CD8+CD71+, CD4+CD25+FOXP3+CD152+ and CD4+CD25+FOXP3+GARP cells and, consequently, by an increased stimulated Teff/Treg ratio. Moreover, the number of manic, but not hypomanic or depressive episodes, is significantly and negatively associated with the stimulated proportions of CD3+CD4+CD154+, and CD69+ and CD71+ expression on CD4+ and CD8+ cells, while duration of illness (≥ 10 years) is accompanied by a depleted frequency of stimulated CD152+ Treg, and CD154+ and CD71+ CD4+ T cells. BD and anti-human cytomegalovirus (HCMV) IgG levels significantly interact to decrease the expression of CD4+CD25+FOXP+GARP T phenotypes. In conclusion, BD is characterized by deficits in immune-regulatory functions while the staging of illness is characterized by additional impairments is Teff and Treg activation. HCMV seropositivity may contribute to an immune-risk phenotype associated with BD.

Today, more than 70 million tons of lignin are produced by the pulp and paper industry every year. However, the utilization of lignin as a source for chemical synthesis is still limited due to the complex and heterogeneous lignin structure. The purpose of this study was a selective photodegradation of industrially available kraft lignin in order to obtain appropriate fragments and building block chemicals for further utilization, e.g. polymerization. Thus, kraft lignin obtained from soft wood black liquor by acidification was dissolved in sodium hydroxide and irradiated at a wavelength of 254 nm with and without the presence of titanium dioxide in various concentrations. Analyses of the irradiated products via SEC showed decreasing molar masses and decreasing polydispersity indices over time. At the end of the irradiation period the lignin was depolymerised to form fragments as small as the lignin monomers. TOC analyses showed minimal mineralisation due to the depolymerisation process.

Infections contribute to carcinogenesis through inflammation-related mechanisms. It is well established that H. pylori infection is an etiological factor in gastric carcinogenesis. However, the mechanism through which H. pylori infection contributes to the development of gastric cancer has not been fully elucidated. H. pylori-associated chronic inflammation is linked to genomic instability via reactive oxygen and nitrogen species (RONS). In this article, we summarize the current knowledge of H. pylori-induced double strand breaks (DSBs). Further, we will provide mechanistic insight into how processing of oxidative DNA damage via base excision repair (BER) leads to double strand breaks (DSBs). We review the recent progress how H. pylori infection triggers NF-kB /iNOS versus NF-kB/nucleotide excision repair (NER) axis mediated DSBs to drive genomic instability. Taken together, this review discusses current findings related to DSBs and their implications for the mechanisms of DSB repair.

In this paper we obtain some inequalities of Hermite-Hadamard type for composite convex functions. Applications for AG, AH-h-convex functions, GA, GG, GH-h-convex functions and HA, HG, HH-h-convex function are given.

In the Republic of Moldova, nearly 90% of all deaths are due to noncommunicable diseases (NCDs), tha majority of which (58%) are caused by cardiovascular disease (CVD). Excess salt (sodium) and inadequate potassium intakes are associated with high CVD. Moreover, salt iodisation is the preferred policy to prevent iodine deficiency and associated disorders. However, there is no survey that has directly measured sodium, potassium and iodine consumption in adults in the Republic of Moldova. The aim is to estimate population sodium, potassium and iodine intakes and explore knowledge, attitudes and behaviour (KAB) towards the use of salt, amongst the adult population in the Republic of Moldova. Proportional random samples of adults were obtained from 28 of the 37 Districts and Municipalities and one Administrative Territorial Unit of Moldova. Participants attended a screening including demographic, anthropometric and physical measurements. Dietary sodium, potassium and iodine intakes were assessed by 24h urinary sodium (UNa), potassium (UK) and iodine (UI) excretions. Creatinine was measured. KAB was collected by questionnaire. Eight hundred and fifty-eight participants (326 men and 532 women, 18–69 years) were included in the analysis (response rate 66%). Mean age was 48.5 yrs (SD 13.8). Mean UNa was 172.7 (79.3) mmoL/day, equivalent to 10.8 g of salt/day and potassium excretion 72.7 (31.5) mmoL/day, equivalent to 3.26 g/day. Men ate more sodium and potassium than women. Only 11.3% of the sample had a salt intake below the World Health Organization (WHO) recommended target of 5 g/day and approximately 39% met WHO targets for potassium excretion (>90 mmoL/day). Whilst 81.7% declared limiting their consumption of processed food and over 70% declared not adding salt at the table, only 8.8% looked at sodium content of food, 31% still added salt when cooking and less than 1% took other measures to control salt consumption. Measures of awareness were significantly more common in urban compared to rural areas. Mean urinary iodine was 225 (SD: 152; median 196) mcg/24h, with no difference between sexes. According to WHO criteria, 41.0% had adequate iodine intake, 28.6% had intake below requirements and 17.8% and 12.6% had above requirement or excessive levels, respectively. Iodine content of salt table was 21.0 (SD: 18.6) mg/kg, with no difference between men and women. However, the content was lower in rural than urban areas (16.7 [SD: 18.6] vs 28.1 [SD: 16.5] mg/kg, p<0.001). There were weak or no correlations between urinary sodium and iodine excretions, and between urinary iodine excretion and iodine concentration in the table salt used in the participants’ households, indicating that in most cases participants were not using iodised salt as their main source of salt, more so in rural areas. In the Republic of Moldova, salt consumption is unequivocally high, potassium consumption is lower than recommended, both in men and in women, whilst iodine intake is still inadequate in 1 in 3 people, although severe iodine deficiency is rare. Salt consumed is often not iodised, with less iodised salt being used in rural areas.

In this study, the degradable superhydrophobic Mg/P/Z/F/H (magnesi-um/poly(-caprolactone)/zinc oxide/1H,1H,2H,2H-perfluorodecyltriethoxysilane (PFDTES)/ heating process) composite materials were prepared through one-step method for enhancing the corrosion resistance of AZ91D magnesium alloys. Electrochemical measurements showed that Mg/P/Z/F/H materials significantly improved the corrosion resistance of magnesium alloys in 3.5 wt.% NaCl. The self-cleaning, adhesion and stability tests suggested that Mg/P/Z/F/H composite materials had well self-cleaning properties, good adhesion strength and stability in wet atmosphere.

The antiradical and antimicrobial activity of lignin and lignin-based films are both of great interest for applications such as food packaging additives. The polyphenol structure of lignin in addition to the presence of O-containing functional groups is potentially responsible for these activities. This study used DPPH assays to discuss the antiradical activity of HPMC/lignin and HPMC/lignin/chitosan films. The scavenging activity (SA) of both binary (HPMC/lignin) and ternary (HPMC/lignin/chitosan) systems was affected by the percentage of the added lignin: the 5% addition showed the highest activity and the 30% addition had the lowest. Both, scavenging activity and antimicrobial activity are depending on the biomass source showing the following trend: organosolv of softwood > Kraft of softwood > organosolv of grass. Testing the antimicrobial activities of lignins and lignin-containing films showed high antimicrobial activities against gram-positive and gram-negative bacteria at 35 °C and at low temperatures (0-7 °C). Purification of kraft lignin has a negative effect on the antimicrobial activity while storage has positive effect. The lignin release in the produced films affected the activity positively and the chitosan addition enhances the activity even more for both gram-positive and gram-negative bacteria. Testing the films against spoilage bacteria that grow at low temperatures revealed the activity of the 30% addition on HPMC/L1 film against both B. thermosphacta and P. fluorescens while L5 was active only against B. thermosphacta. In HPMC/lignin/chitosan films the 5% addition exhibited activity against both B. thermosphacta and P. fluorescens.

During mechanical ventilation, a disparity between flow, pressure or volume demands of the patient and the assistance delivered by the mechanical ventilator often occurs. Asynchrony effect and ventilator performance are frequently studied from ICU datasets or using commercially available lung simulators and test lungs. This paper introduces an alternative approach of simulating and evaluating patient-ventilator interactions with high fidelity using the electro-mechanical lung simulator xPULM™ under selected conditions. The xPULM™ approximates respiratory activities of a patient during alternating phases of spontaneous breathing and apnoea intervals while connected to a mechanical ventilator. Focusing on different triggering events, volume assist-controlled (V/A-C) and pressure support ventilation (PSV) modes were chosen to test patient-ventilator interactions. In V/A-C mode a double-triggering was detected every third breathing cycle leading to an asynchrony index of 16.67%, being classified as severe. This asynchrony causes a major increase of Peak Inspiratory Pressure PIP = 12.80 ± 1.39 cmH2O and Peak Expiratory Flow PEF = -18.33 ± 1.13 L/min when compared to synchronous phases of the breathing simulation. Additionally, events of premature cycling were observed during PSV mode. In this mode, the peak delivered volume during simulated spontaneous breathing phases almost doubles compared to apnoea phases. The presented approach demonstrates the possibility of simulating and evaluating disparities in fundamental ventilation characteristics caused by double-triggering and premature cycling under V/A-C and PSV ventilation modes. Various dynamic clinical situations can be approximated and could help to identify undesired patient-ventilation interactions in the future. Rapidly manufactured ventilator systems could also be tested using this approach.

Coagulation is the most sensitive step in drinking water treatment. Underdosing may not yield the required water quality, whereas overdosing may result in higher costs and excess sludge. Traditionally, the coagulant dosage is set based on bath experiments performed manually. Therefore, this test does not allow real-time dosing control, and its accuracy is subject to operator experience. Alternatively, solutions based on machine-learning (ML) have been evaluated as a computer-aided alternative. Despite these advances, there is open debate on the most suitable ML method applied to the coagulation process, capable of the most highly accurate prediction. This study addresses this gap, where a comparative analysis between ML methods was performed. As a research hypothesis, a novel data-driven fuzzy inference system (FIS) should provide the best performance due to its ability to deal with uncertainties inherent to complex processes. Although ML methods have been widely investigated, only a few studies report hybrid neuro-fuzzy systems applied to coagulation. Thus, to the best of our knowledge, this is the first study thus far to address the accuracy of this novel data-driven FIS for such application. The novel FIS provided the smallest error (0.86), indicating a promising alternative tool for real-time and highly accurate coagulant dosing in drinking water treatment.

Excess salt and inadequate potassium intakes are associated with high cardiovascular disease (CVD). In Montenegro, CVD is the leading cause of death and disability. There is no survey that has directly measured salt and potassium consumption in Montenegro. The aim is to estimate population salt and potassium intakes and explore knowledge, attitudes and behaviour (KAB), amongst the adult population of Podgorica. Random samples of adults were obtained from primary care centres. Participants attended a screening including demographic, anthropometric and physical measurements. Dietary salt and potassium intakes were assessed by 24h urinary sodium (UNa) and potassium (UK) excretions. Creatinine was measured. KAB was collected by questionnaire. Six hundred and thirty-nine (285 men, 25-65 years) were included in the analysis (response rate 63%). Mean UNa was 186.5 (SD 90.3) mmol/day, equivalent to 11.6g of salt/day, and potassium excretion 62.5 (26.2) mmol/day, equivalent to 3.2g/day. Only 7% of them had a salt intake below the WHO recommended target of 5g/day, and 13% ate enough potassium (>90 mmol/day). The majority (86%) knew that high salt causes ill-health. However, only 44% thought it would be useful to reduce consumption. Salt consumption is high, and potassium consumption is low, in men and women living in Podgorica.

Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews of static scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path traced results, but with a greatly reduced computational complexity allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering.

The focus of our study was the changes in the composition of semi-natural dry grasslands in Hungary. Since these valuable habitats were created with the help of humans, their preservation also requires regular treatment. Our mowing experiment aimed to investigate the suppression of the native Calamagrostis epigejos L. Roth. In Hungary, in the Cserhát Mountains, eight permanent plots were mowed twice a year. The vegetation was sampled annually between 2001 and 2011. The effects of mowing were investigated with repeated measures analysis of variance (ANOVA). After 10 years, the C. epigejos cover of the mowed plots decreased significantly, from the initial average of 62.38 to 7.50%. Surprisingly, we also experienced a similar decrease in the control plots. Regular treatment also had a positive effect on the number of species and diversity. Species richness increased continuously in both treatment types, which indicates the combined effect of vegetation succession and treatment. The biomass growth of other Poaceae and Fabaceae species, which are important from a grassland management perspective, was also facilitated by mowing. Our results suggest that long-term in situ experiments and continuous botanical studies are needed to establish a reliable utilization of grasslands.

This paper addresses a mode-dependent state-feedback H∞ control for descriptor hybrid systems, considering both the absence and presence of actuator saturation. Firstly, the necessary and sufficient conditions for the stochastic admissibility criterion with H∞ performance ? of the closed-loop system is proposed. Given the proposed non-convex condition, the author reformulates it into linear matrix inequalities (LMIs). Then, to extend the result to the systems with actuator saturation, the actuator saturated control input is expressed as a linear combination of given state-feedback control input and a virtual control input that remains under the saturation level. To verify this expression, the set invariant condition is also suggested by using the singular mode-dependent Lyapunov function candidate. Therefore, the LMI conditions for the existence of the mode-dependent state-feedback H∞ control and the ellipsoidal shape of invariant set are successfully derived. Two numerical examples demonstrate the effectiveness of the proposed approach in optimizing H∞ performance $\gamma$ and identifying the largest invariant set.

The purpose of this study is to estimate the mean transitioning probabilities from a Healthy state to malaria positive uncomplicated state or to malaria positive severe state. It also classifies the various transitioning probabilities of moving through the various states based on some baseline characteristics. Malaria test results for 2019 over a 12-month period were collected from the University of Ghana school clinic. An H-U model for the study was developed and the transition rates from the cross-sectional data are indicated. With two states Healthy (H) and Uncomplicated (U) forming a state space, there were four possible transitions. The results show that the probability of transitioning from a Healthy state to a malaria positive state is 0.03% while the probability that an individual will remain at Healthy state (H) after the test is 99.73%. It was found that if an individual is already positive and has taken medication the probability that its second test came out negative is 6.45% while the chances that it will remain positive but uncomplicated is 93.55%. The study also showed that in the long run, about 95.98% of persons who visited the student clinic with malaria symptoms recorded negative tests for malaria parasite while about 4% recorded positive for malaria. In terms of disaggregation by gender, it was realized that the number of reported negative test results were higher for females (97.08%) than for males (96.13%). However, the infection rate is higher for males (3.87%) than females (2.92%). It is recommended that in as much as the University of Ghana has two health centers (a clinic and hospital), there should be a centralized system to track students’ health so research done would not be biased.

In this paper, modelling designing and simulation of a Ward Leonard layout system is done using robust control theory. In order to increase the performance of the Ward Leonard layout system with H infinity optimal control synthesis and H infinity optimal control synthesis via gamma-iteration controllers are used. The open loop response of the Ward Leonard layout system shows that the system needs to be improved. Comparison of the Ward Leonard layout system with H∞ optimal control synthesis and H infinity optimal control synthesis via gamma-iteration controllers to track a desired step speed input have been done. Finally, the comparative simulation results prove the effectiveness of the proposed Ward Leonard layout system with H infinity optimal control synthesis controller in improving the percentage overshoot and the settling time.

Abstract: The increased penetration of renewables in distribution power systems has motivated researchers to take significant interest in local energy transactions. The major goal of Local Energy Markets (LEM) is to promote the participation of small consumers in energy transactions and providing an opportunity for transactive energy systems. Such energy transactions in LEM are considered as a bi-level optimization problem in which all agents at upper and lower levels try to maximize their profits. But typical bi-level problem is very complex as it is inherently nonlinear, discontinued and strongly NP-hard. So, this article proposes the application of hybridized Cross Entropy Covariance Matrix Adaptation Evolution Strategy (CE-CMAES) to tackle such a complex bi-level problem of LEM. The proposed CE-CMAES secured the 1st rank in Testbed-2 entitled, “Bi-level optimization of end-users’ bidding strategies in local energy markets (LM)” at international competitions on Smart Grid Problems, held at GECCO 2020 and WCCI 2020. CE method is used for global exploration of search space and CMAES is used for local exploitation as its adaptive step-size mechanism prevents its premature convergence. A practical distribution system with renewable energy penetration is considered for simulation. The comparative analysis shows that the overall cost, mean fitness and Ranking Index (R.I) obtained from CE-CMAES are superior to those obtained from the state-of-the-art participated algorithms. Wilcoxon Signed Rank Statistical test also proves that CE-CMAES is statistically different from the tested algorithms.

Papain-like lysosomal cysteine proteases include 11 human cysteine cathepsins which act as endopeptidases and/or exopeptidases. They are involved in numerous physiological and pathological processes. Among them, only cathepsins B, H, C, and X/Z exhibit exopeptidase activity. Their activities are tightly regulated in various ways to prevent potentially hazardous effects on the cell. In this review, we focus on the structural and functional aspects of these four cysteine cathepsins and their role in neurodegeneration and cancer. Neurodegenerative disorders of aging share an endolysosomal dysfunction and accumulation and spread of oligomeric forms of neurotoxic proteins. The accumulation of various protein aggregates activates the microglia, thus inducing the activation and release of cysteine cathepsins and proinflammatory cytokines, leading to neurodegeneration. In cancer, cysteine cathepsins participate in tumor progression and metastasis. Tumor–stromal crosstalk leads to activation of the stroma and overexpression and secretion of proteolytic enzymes, triggering extracellular matrix degradation and the release of soluble factors. Activated stromal cells (i.e., macrophages, fibroblasts, mast cells) secrete additional growth factors, cytokines, and chemokines that are responsible for the regulation of processes leading to tumor progression and metastasis. Therefore, a better understanding of the role of cysteine cathepsins in neurodegeneration and cancer could lead to novel targeted therapeutic approaches.

In this paper, the design and control of a hydraulic system based tire changer machine have been analyzed and simulated using Matlab/Simulink Toolbox successfully. The machine have a displacement input which is a leg pedal displacement in order to push the piston of the pump to fed the motor with a pressured hydraulic fluid to rotate the tire with an angular speed to mount and dismount it. Augmentation based H_∞ and H₂ optimal synthesis controllers have been used to improve the performance of the machine. Comparison of the proposed controllers for tracking a reference input speed have been done using two reference inputs (step and random) signals. Finally the comparative simulation results proved the effectiveness of the proposed tire changer with H synthesis controller in improving the settling time and percentage overshoot.

Recessive dystrophic epidermolysis (RDEB) is a rare, inherited and currently incurable skin blistering disorder characterized by cyclically recurring wounds coexisting with chronic non-healing wounds. In a recent clinical trial three intravenous infusions of skin-derived ABCB5+ mesenchymal stromal cells (MSCs) to 14 patients with RDEB improved healing of wounds that were present at baseline. Since in RDEB even minor mechanical forces perpetually provoke the development of new or recurrent wounds, a post-hoc analysis of patient photographs was performed to specifically assess the effects of ABCB5+ MSCs on new or recurrent wounds by evaluating 174 wounds that occurred after baseline. During 12 weeks of systemic treatment with ABCB5+ MSCs the number of newly occurring wounds declined. When compared to the previously reported healing responses of the wounds present at baseline, the newly occurring wounds healed faster, and a greater portion of healed wounds remained stably closed. These data suggest a previously undescribed skin-stabilizing effect of treatment with ABCB5+ MSCs and support repeated dosing of ABCB5+ MSCs in RDEB to continuously slow the wound development and accelerate the healing of new or recurrent wounds before they become infected or progress to a chronic, difficult-to-heal stage.

Atrial fibrillation (AF) is a cardiac arrhythmia caused by electrophysiological anomalies in the atrial tissue, tissue degradation, structural abnormalities, and comorbidities. A direct relation exists between AF and altered mitochondrial activity resulting from membrane potential loss, contractile dysfunction, or decreased ATP levels. This review aimed to elucidate the role of mitochondrial oxidative mechanisms in AF pathophysiology, the impact of mitochondrial oxidative stress on AF initiation and perpetuation, and current therapies. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews. PubMed, Excerpta Medica Database, and Scopus were explored until June 2023 using "MESH terms." Bibliographic references from relevant papers were also included. Oxidative stress is an imbalance that causes cellular damage from excessive oxidation, resulting in conditions such as AF. An imbalance in reactive oxygen species production and elimination can cause mitochondrial damage, cellular apoptosis, and cardiovascular diseases. Oxidative stress and inflammation are intrinsically linked, and inflammatory pathways are highly correlated with the occurrence of AF. AF is an intricate cardiac condition that requires innovative therapeutic approaches. The involvement of mitochondrial oxidative stress in the pathophysiology of AF introduces novel strategies for clinical treatment.

Background: The purpose of this review is to clarify the natural course of Benign Paroxysmal Torticollis (BPT) and to update the relationship of this disorder with migraine. BPT belongs to a group of “episodic syndromes that may be associated with migraine” and is diagnosed when according to diagnostic criteria of the International Classification of Headache Disorders, 3rd edition. It is present in infants and young children and it is an underdiagnosed manifestation, because it is not well recognized and in most cases with a benign evolution, but requires careful differential diagnosis. It was first described by Snyder in 1969 as a movement disorder, a cervical dystonia consequent to labyrinthic disorder.Materials and methods: The PubMed and Web of Science databases were consulted from 1968 to 2024, according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines ,2020.( PRISMA)Results: 113 articles were identified, 86 selected and 20 considered for the purpose of this review. The clinical studies were considered in relation to evolution, cognitive and motor development, to genetic and not genetic etiology, to the relationship with migraine with and without aura, vestibular migraine, hemiplegic migraine, and paroxysmal vertigo.

Many corporations have now revised their value statements to showcase their commitment to sustainable development and green business due to the pressing issues of climate and environmental damage. Despite the importance of value statements that can direct companies to achieve sustainable goals, what kind of values can be perceived as organizational orientations to sustainability remains unknown. This study explores how the general public views the inclusion of sustainable components in value statements from the listed companies in Hong Kong by using Q-sort methodology (n = 30). Analyzing the final sample of 40 value statements extracted from 27 listed companies, we identified three factors related to sustainability, namely, Empowering business process management, Empowering customer-centric excellence, and Empowering sustainable progress. This study provides an additional component to the traditional triple bottom line by suggesting that internal operation of a company is an emerging idea to understand corporate sustainability.

The reaction of mercaptoacetic acid esters with pentachloro-2-nitro-1,3-butadiene provides appropriate precursors for the synthesis of 2,3,4-trisubstituted benzo[h]quinolines. These heterocycles are easily accessible via a single-step reaction with 1-naphthyl- or 1-anthracenylamine, respectively. Due to steric bulk and high electron density ring closure to benzo[h]quinolines takes place, exclusively. Such highly substituted annelated pyridine systems can be modified in subsequent, selective reactions to build up new N-heterocycles with promising microbiological properties. Antibacterial and antiproliferative assays against four cell mammalian cell lines demonstrate that some of the sulfur-substituted benzo[h]quinolines analogs display potent phenotypic bioactivities in the single-digit micromolar range.

Hypotrochoidal profile contours have been produced in industrial applications in recent years using twin-spindle processes, and they are considered effective high-quality solutions for positive shaft–hub connections. This study mainly concerns analytical approaches to determine the bending stresses in hypotrochoidal profile shafts. The formulation was developed according to bending principles using the mathematical theory of elasticity and conformal mappings. The loading was further used to investigate the rotating bending behaviour. The stress factors for the classical calculation of maximum bending stresses were also determined for all those profiles presented and compiled in the German standard DIN3689-1 for practical applications. The results were also compared with the corresponding numerical and experimental results, and very good agreement was observed. Additionally, based on previous work, the stress factor was determined for the case of torsional loading to calculate the maximum torsional stresses in the standardised profiles, and the results are listed in a table. This study contributes to the further refinement of the current DIN3689 standard.

Cervical cancer is one of the ailments that endangers the health of women all over the world and causes infertility. Fortunately, this disease can be avoided. Both the results and participation rates of the current preventative strategy remain poor. Hence, preventative or early detection methods remain challenging and open. In gynecology and computer science fields, few studies on identifying cervical cancer are based on behavior risk factor and machine learning. Moreover, various social and behavioral aspects might often make it more difficult to detect cervical cancer especially in low‑ and middle‑income countries (LMICs). Accordingly, focus on predicting the presence of cervical cancer through behavioral risk factors is the basic structure of this research. We proposed an approach to classify cervical cancer from a social-behavioral perspective using logistic regression to predict cervical cancer. We got significantly improved outcomes than the existing methods. Moreover, we used feature engineering to formulate less dimensionality as a pre-processing step and optimized parameters to be prepared for classification phase. The results proved that using the logistic regression with regularization type L1 had a promising performance. The accuracy of Logistic Regression (LR) L1 was 97.2%. Such results support the proposed work as a reliable classification predictive tool.

Due to the digitization and Internet of Things revolutions, the present electronic world has a wealth of cybersecurity data. Efficiently resolving cyber anomalies and attacks is becoming a growing concern in today's cyber security industry all over the world. Traditional security solutions are insufficient to address contemporary security issues due to the rapid proliferation of many sorts of cyber-attacks and threats. Utilizing artificial intelligence knowledge, especially machine learning technology, is essential to providing a dynamically enhanced, automated, and up-to-date security system through analyzing security data. In this paper, we provide an extensive view of machine learning algorithms, emphasizing how they can be employed for intelligent data analysis and automation in cybersecurity through their potential to extract valuable insights from cyber data. We also explore a number of potential real-world use cases where data-driven intelligence, automation, and decision-making enable next-generation cyber protection that is more proactive than traditional approaches. The future prospects of machine learning in cybersecurity are eventually emphasized based on our study, along with relevant research directions. Overall, our goal is to explore not only the current state of machine learning and relevant methodologies but also their applicability for future cybersecurity breakthroughs.

Artificial Intelligence (AI) is a leading technology of the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR), with the capability of incorporating human behavior and intelligence into machines or systems. Thus AI-based modeling is the key to building automated, intelligent, and smart systems according to today's needs. To solve real-world issues various types of AI such as analytical, functional, interactive, textual, and visual AI can be applied to enhance the intelligence and capabilities of an application. However, developing an effective AI model is a challenging task due to the dynamic nature and variation in real-world problems and data. In this paper, we present a comprehensive view on "AI-based Modeling" with the principles and capabilities of potential AI techniques that can play an important role in developing intelligent and smart systems in various real-world application areas including business, finance, healthcare, agriculture, smart cities, cybersecurity and many more. We also emphasize and highlight the research issues within the scope of our study. Overall, the goal of this paper is to provide a broad overview of AI-based modeling that can be used as a reference guide by academics and industry people as well as decision-makers in various real-world scenarios and application domains.

Educational institutions must identify students who are academically struggling to provide them with necessary support to improve their performance. In this context, recommendation systems powered by deep learning techniques are vital for detecting and categorizing such students. These systems help students plan their future by uncovering patterns in their historical academic data. This study introduces a new deep learning model designed to classify academically underperforming students in educational settings. The model incorporates a Gated Recurrent Neural Network (GRU) and includes specific neural network features like a dense layer, max-pooling layer, and the ADAM optimization algorithm. The model's training and evaluation were conducted using a dataset comprising 15,165 student assessment records from various academic institutions. The performance of the developed GRU model was benchmarked against other educational recommendation systems, including Recurrent Neural Network models, AdaBoost, and the Artificial Immune Recognition System v2. The proposed GRU model demonstrated remarkable accuracy, achieving an overall rate of 99.70%.

: Extra- and intra-cellular activity occurs under the direction of numerous inter-molecular interactions, and in any tissue or cell, molecules are densely packed, thus promoting those molecular interactions. Galectins and chemokines, the focus of this review, are small, protein effector molecules that mediate various cellular functions, in particular cell adhesion and migration, as well as cell signaling/activation. In the past, researchers have reported that combinations of these (and other) effector molecules act separately, yet sometimes in concert, but nevertheless physically apart and via their individual cell receptors. This view that each effector molecule functions independently of the other limits our thinking about functional versatility and cooperation, and, in turn, ignores the prospect of physiologically important inter-molecular interactions, especially when both molecules are present or co-expressed in the same cellular environment. This review is focused on such protein-protein interactions with chemokines and galectins, their homo- and hetero-oligomeric structures that they can form, and the functional consequences of those paired interactions.

Due to the rising dependency on digital technology, cybersecurity has emerged as a more prominent field of research and application that typically focuses on securing devices, networks, systems, data and other resources from various cyber-attacks, threats, risks, damages, or unauthorized access. Artificial Intelligence (AI), also referred to as a crucial technology of the current Fourth Industrial Revolution (Industry 4.0 or 4IR), could be the key to intelligently dealing with these cyber issues. Various forms of AI methodologies, such as analytical, functional, interactive, textual as well as visual AI can be employed to get the desired cyber solutions according to their computational capabilities. However, the dynamic nature and complexity of real-world situations and data gathered from various cyber sources make it challenging nowadays to build an effective AI-based security model. Moreover, defending robustly against adversarial attacks is still an open question in the area. In this paper, we provide a comprehensive view on "Cybersecurity Intelligence and Robustness", emphasizing multi-aspects AI-based modeling and adversarial learning that could lead to addressing diverse issues in various cyber applications areas such as detecting malware or intrusions, zero-day attacks, phishing, data breach, cyberbullying and other cybercrimes. Thus the eventual security modeling process could be automated, intelligent, and robust compared to traditional security systems. We also emphasize and draw attention to the future aspects of cybersecurity intelligence and robustness along with the research direction within the context of our study. Overall, our goal is not only to explore AI-based modeling and pertinent methodologies but also to focus on the resulting model's applicability for securing our digital systems and society.

The digital world has a wealth of data, such as Internet of Things (IoT) data, business data, health data, mobile data, urban data, security data, and many more, in the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR). Extracting knowledge or useful insights from these data can be used for smart decision-making in various applications domains. In the area of data science, advanced analytics methods including machine learning modeling can provide actionable insights or deeper knowledge about data, which makes the computing process automatic and smart. In this paper, we present a comprehensive view on "Data Science'' including various types of advanced analytics methods that can be applied to enhance the intelligence and capabilities of an application through smart decision-making in different scenarios. We also discuss and summarize ten potential real-world application domains including business, healthcare, cybersecurity, urban and rural data science, and so on by taking into account data-driven smart computing and decision making. Based on this, we finally highlight the challenges and potential research directions within the scope of our study. Overall, this paper aims to serve as a reference point on data science and advanced analytics to the researchers and decision-makers as well as application developers, particularly from the data-driven solution point of view for real-world problems.

Vehicle windshield wiper system increases the driving safety by contributing a clear shot viewing to the driver. In this paper, modelling, designing and simulation of a vehicle windshield wiper system with robust control theory is done successfully. H∞ loop shaping and robust pole placement controllers are used to improve the wiping speed by tracking a reference speed signals. The reference speed signals used in this paper are step and sine wave signals. Comparison of the H∞ loop shaping and robust pole placement controllers based on the two reference signals is done and convincing results have been obtained. Finally the comparative results prove the effectiveness of the proposed H∞ Loop Shaping controller to improve the wiping mechanism for the given two reference signals.

Academic publishing is undergoing a highly transformative process, and many rules and value systems that were in place for years are being challenged in unprecedented forms leading to the evolution of novel ways of dealing with new pressures. One of the most important aspects of an integrated and valid academic literature is the ability to screen publications for errors during peer review to weed out mistakes, fraud and inconsistencies, such that the final published product represents a product that has value, intellectually, and otherwise. It is difficult to claim the existence of perfect manuscripts. The level of errors that exist in a manuscript will depend on the rigor of the research group and of the peer review process that was used to screen that paper. When errors slip into a final published paper, either through honest error or misconduct, and are not detected during peer review and editorial screening, but are spotted during post-publication peer review, an opportunity is created to set the record straight, and to correct it. To date, the most common forms of correcting the literature have been errata, corrigenda, expressions of concern, and retractions. Despite this range of corrective measures, which represent artificially created corrals around pockets of imperfect literature, certain cases do not quite fit this mold, and new suggested measures for correcting the literature have been proposed, including manuscript versioning, amendments, partial retractions and retract and replace. In this commentary, a discussion of the evolving correction of the literature is provided, as are perspectives of the risks and benefits of such new measures to improve it.

In this paper, we identify issues and possible solutions in the key area of large-scale antenna systems, also know as Massive Multiple Input Multiple Output (MIMO) systems. Additionally, we propose the use of Massive MIMO technology as a means to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel (PNSCH), the capacity of the MTC network and, in turn, that of the whole system, can be increased by grouping Machine-Type Communication (MTC) devices into clusters and letting each cluster share the same time-frequency physical resource blocks. We study the feasibility of applying sub-optimal linear detection to the problem of detecting a large number of MTC devices sharing the same time-frequency resources at the uplink of a base station (BS) equipped with a large number of antennas, M. In our study, we derive the achievable lower-bound rates for the studied sub-optimal linear detectors and show that the transmitted power of each MTC device can be reduced as M increases, which is a very important result for powerconstrained MTC devices running on batteries. Our simulation results suggest that, as M is made progressively larger, the performance of sub-optimal linear detection methods approach the matched filter bound, also known as perfect interference-cancellation bound.

Nanoindentation load-depth (P-h) plots is the basis for determination of mechanical properties of the samples and is especially vital for thin coatings deposited on substrates of various mechanical makeup from amorphous-brittle (borosilicate glass) to Silicon (having different crystallographic texture) to ductile substrates like stainless steel as well other aspects like indenter tip shape. The elastic-plastic response by simulated P-h plots as per modified empirical relations have been presented. The outcomes of this computational studies enlighten the database on the P-h plots for various coating/substrate systems and shall aid in the analysis of experimental P-h plots obtained,

Na⁺/H⁺ exchangers (NHEs) are known to be important regulators of pH in multiple intracellular compartments of eukaryotic cells. Sperm function is especially dependent on changes in pH and thus it has been postulated that NHEs play important roles in regulating the intracellular pH of these cells. For example, in order to achieve fertilization, mature sperm must maintain a basal pH in the male reproductive tract and then alkalize in response to specific signals in the female reproductive tract during the capacitation process. Eight NHE isoforms are expressed in mammalian testis/sperm: NHE1, NHE3, NHE5, NHE8, NHA1, NHA2, NHE10, and NHE11. These NHE isoforms are expressed at varying times during spermatogenesis and localize to different subcellular structures in developing and mature sperm where they contribute to multiple aspects of sperm physiology and male fertility including proper sperm development/morphogenesis, motility, capacitation, and the acrosome reaction. Previous work has provided evidence for NHE3, NHE8, NHA1, NHA2, and NHE10 being critical for male fertility in mice and NHE10 has recently been shown to be essential for male fertility in humans. In this article we review what is known about each NHE isoform expressed in mammalian sperm and discuss the physiological significance of each NHE isoform with respect to male fertility.

A simple undirected graph $\Gamma=(V_\Gamma,E_\Gamma)$ admits an $H$-covering if every edge in $E_\Gamma$ belongs to at least one subgraph of $\Gamma$ that isomorphic to a graph $H$. For any graph $\Gamma$ admitting $H$-covering, a total Labelling $\beta: V_\Gamma \cup E_\Gamma \longrightarrow \{1,2,\dots,p\}$ is called an $H$-irregular total $p$-labelling of $\Gamma$ if every two different subgraphs $H_1$ and $H_2$ of $\Gamma$ isomorphic to $H$ have distinct weights where the weight $w_\beta(K)$ of subgraph $K$ of $\Gamma$ is defined as $w_f(K):=\displaystyle \sum_{v\in V_K} f(v) + \sum_{e\in E_K} f(e)$. The smallest number $p$ for which a graph $\Gamma$ admits an $H$-irregular total $p$-labelling is called the total $H$-irregularity strength of $\Gamma$ and is denoted by $ths(\Gamma)$. In this paper, we determine the total $H$-irregularity strength of edge comb product of two graphs.

This article will briefly review the progress of h-BN based solid-state metal semiconductor metal (MSM) neutron detectors. In the last decade, several groups have been working on hexagonal boron nitride (h-BN) based solid-state neutron detectors. Recently, the detection efficiency of 59% has been reported. Efficient, low-cost neutron detectors made from readily available materials are essential for various applications. Neutron detectors are widely used to detect fissile materials and nuclear power plants for security applications. The most common and widely used neutron detectors are 3He based, which are sometimes bulky, difficult to transport, have high absorption length, need relatively high bias voltage (>1000 V), and have low Q-value (0.764 MeV). Also, 3He is not readily available material. Thus, there is a strong need to find an alternative detection material. 10B isotope has a high neutron absorption cross-section, and it has been tested as a coating on the semiconducting materials. Due to the two-step process, neutron capture through 10B, and then electron-hole pair generation in a typical semiconducting material, the efficiency of these devices is not up to the mark. The progress in h-BN based detectors requires a review to envision the further improvement in this technology.