Service robots operating in indoor environments should recognize dynamic changes from sensors, such as RGB-D camera, and recall the past context. Therefore, we propose a context query-processing framework, comprising spatio-temporal robotic context query language (ST-RCQL) and spatio-temporal robotic context query-processing system (ST-RCQP), for service robots. We designed them based on the spatio-temporal context ontology. ST-RCQL can query not only the current context knowledge but also the past. In addition, ST-RCQL includes a variety of time operators and time constants, and thus queries can be written very efficiently. The ST-RCQP is a query-processing system equipped with a perception handler, working memory, and backward reasoner for real-time query-processing. Moreover, ST-RCQP accelerates query-processing speed by building a spatio-temporal index in the working memory, where percepts are stored. Through various qualitative and quantitative experiments, we demonstrate the high efficiency and performance of the proposed context query-processing framework.

The ageing transformation of digital health services faces issues of how to distinguish influencing factors, redesign services, and effectively promote measures and policies. In this study, in-depth interviews are conducted and grounded theory applied to open coding, main axis coding, and selective coding to form concepts and categories. Trajectory equifinality modeling clarified the evolution logic of digital transformation. Based on the theory of service ecology, a digital health service ageing model is constructed from the "macro-medium-micro" stages and includes governance, service, and technology transformation paths. The macro stage relies on organizational elements to promote the institutionalization of management and guide the transformation of governance for value realization, including the construction of three categories: mechanism, indemnification, and decision-making. The meso stage relies on service elements to promote service design and realize service transformation suitable for aging design, including the construction of three categories: organization, resources, and processes. The micro stage relies on technical elements to practice experiencing humanization, including the construction of three categories: target, methods, and evaluation. These results deepen the understanding of the main behaviors and roles of macro-organizational, meso-service, and micro-technical elements in digital transformation practice and have positive significance for health administrative agencies to implement action strategies.

A new requirement for the manufacturing companies in Industry 4.0 is to be flexible with respect to changes in demands, requiring them to react rapidly and efficiently on the production capacities. Together with the trend to use Service-Oriented Architectures (SOA), this requirement induces a need for agile collaboration among supply chain partners, but also between different divisions or branches of the same company. In order to address this collaboration challenge, we~propose a novel pragmatic approach for the process analysis, implementation and execution. This~is achieved through sets of semantic annotations of business process models encoded into BPMN 2.0 extensions. Building blocks for such manufacturing processes are the individual available services, which are also semantically annotated according to the Everything-as-a-Service (XaaS) principles and stored into a common marketplace. The optimization of such manufacturing processes combines pattern-based semantic composition of services with their non-functional aspects. This is achieved by means of Quality-of-Service (QoS)-based Constraint Optimization Problem (COP) solving, resulting in an automatic implementation of service-based manufacturing processes. The produced solution is mapped back to the BPMN 2.0 standard formalism by means of the introduced extension elements, fully detailing the enactable optimal process service plan produced. This approach allows enacting a process instance, using just-in-time service leasing, allocation of resources and dynamic replanning in the case of failures. This proposition provides the best compromise between external visibility, control and flexibility. In this way, it provides an optimal approach for business process models' implementation, with a full service-oriented taste, by implementing user-defined QoS metrics, just-in-time execution and basic dynamic repairing capabilities. This paper presents the described approach and the technical architecture and depicts one initial industrial application in the manufacturing domain of aluminum forging for bicycle hull body forming, where the advantages stemming from the main capabilities of this approach are sketched.

The need for a relatively quick solution to the problem of providing highways with roadside service facilities necessitates the development of a series of appropriate standard projects. To increase the efficiency of these series, it is advisable to carry out the interconnection of space-planning solutions based on a particular module. Taking into account the variety of planning and landscape characteristics of the sites for the placement of objects of the mainline service, it seems advisable to choose as a module not a square or rectangular, but a triangular configuration, which allows in most cases to harmoniously block the modules. The proposed roof module in the form of a "regular" triangle facing the tetrahedron has a structural basis in the form of a single-tier rod spatial plate. The principal space-planning solutions of all four dozen objects from the approved nomenclature of the mainline service performed in the process of analyzing the possibilities show the real possibility of solving the development tasks on the basis of this system. The use of the proposed modular system makes it possible to successfully solve a number of tasks to reduce the harmful impact on the environment and effectively use renewable energy sources.

The aim of this study was to assess if the ovine articular cartilage serine proteinase inhibitors (SPIs) were related to the Kunitz inter-α-trypsin inhibitor (ITI) family. Ovine articular cartilage was finely diced and extracted in 6M urea and SPIs isolated by sequential anion exchange, HA affinity and Sephadex G100 gel permeation chromatography. Selected samples were also subjected to chymotrypsin and concanavalin-A affinity chromatography. Eluant fractions from these isolation steps were monitored for protein and trypsin inhibitory activity and pooled fractions assessed by affinity blotting using biotinylated trypsin to detect active SPIs and by Western blotting using antibodies to α1-microglobulin, bikunin, TSG-6 and 2-B-6 (+) CS stub epitope generated by chondroitinase-ABC digestion. This identified 2-B-6 (+) positive 220-250,120, 58 and 36 kDa SPIs. The 58 kDa SPI contained α1-microglobulin, bikunin and chondroitin-4-sulphate stub epitope consistent with its identity as the α1-microglobulin-bikunin (AMBP) precursor and was also isolated by concanavalin-A lectin affinity chromatography indicating it had N-glycosylation. Kunitz protease inhibitor (KPI) species of 36, 26, 12 and 6 kDa could be autolytically generated by prolonged storage of the aforementioned 120 and 58 kDa SPIs; chymotrypsin affinity chromatography also generated the 6kDa SPI. KPI domain 1 and 2 SPIs were separated by concanavalin lectin affinity chromatography, domain 1 displayed affinity for this lectin indicating it had N-glycosylation. KPI 1 and 2 both displayed potent inhibitory activity towards trypsin, chymotrypsin, kallikrein, leucocyte elastase and cathepsin G. Localisation of versican, lubricin and HA in the surface regions of articular cartilage represented probable binding sites for the ITI SPs with likely importance in the preservation of joint function.

Several articles have reported that the low number of COVID-19 cases in Japan is attributed to the small number of diagnostic RT-PCR tests performed. The criticism is based on the low number of the tests performed, and they suspected there would be more potential cases in Japan. The use of pre-test probability among tested subjects is proposed in order to evaluate of the sufficiency of test availability instead of the number of the tests. The pre-test probability means the average probability, i.e., ‘suspicion level’, of having coronavirus among the tested subject in a country. The higher pre-test probability is regarded as less sufficient opportunity of the tests, and the test availability could be evaluated by the pre-test probability. Thus, potential problems of underestimation of COVID-19 cases by insufficient amount of the test would be clear by using pre-test probability. The comparison of the pre-test probability could be replaced with that of the positive rate of the test because of the linear relationship between them under the assumption of common sensitivity and specificity. Japan shows the third lowest rate (8.6%), and is considered that the considerably sufficient number of the tests have been performed. In conclusion, the positive rate of the test as a surrogate index of the pre-test probability is useful to evaluate the sufficiency of test amount instead of the number of the tests performed. In present, the potential problem of underestimation by insufficient test availability would be less serious in Japan.

Alzheimer’s disease and related dementias (ADRD) remain a public health challenge in developing counties. We developed a needs-based essential care service package (ECSP) for care planning of persons living with dementia (PLWD) using a cross-sectional survey among PLWD in institutions in six cities in China (n= 1,299). Face-to-face interviews were conducted with caregivers of PLWD by trained staff between 2018 and 2019. Care service needs and utilization by the level of cognitive impairment were summarized. The average age of PLWD was 80.7 years. 76% of participants had severe cognitive impairment. The needs-based ECSP with 30 service items would be sufficient in supporting care services of PLWD in China, of which seven items are core care. The selection plan for ECSP at different levels is designed as “General Care Services + Selective Care Services”, in which service items for low-, mid-and high-level care for PLWD are 7+3, 7+6, and 7+10, respectively. The findings provide the first large-scale data on service needs and utilization of PLWD in mainland China. The ECSP for PLWD advanced in the paper was a practicable and effective quantitative management means. It is deserved to application in a large scale.

Obesity in Australia is rapidly rising, and is a major public health concern. Obesity increases risk of breast cancer and worse associated outcomes, yet breast screening participation rates in Australia are suboptimal and can be lower in higher risk, obese women. This study qualitatively explored barriers to breast screening participation in obese women in Australia. In-depth interviews (n=29), were conducted with obese women (BMI 30) and key health stakeholders. A disconnect between stakeholders’ and women’s perceptions was found. For women, low knowledge around a heightened need to screen existed, they reported limited desire to prioritize personal health needs, reluctance to screen due to poor body image and prior negative mammographic experiences due to issues with weight. Stakeholders perceived few issues in screening obese women beyond equipment limitations, and health and safety issues. Overall, weight was a taboo topic among our interviewees, indicating that a lack of discourse around this issue may be putting obese women at increased risk of breast cancer morbidity and mortality. Consideration of breast screening policy in obese women is warranted. Targeted health promotion on increased breast cancer risk in obese women is required as is a need to address body image issues and encourage screening participation.

The annual budget for the United States National Park Service was roughly three billion dollars in 2016. This is distributed amongst 405 National Parks, 23 national scenic and historic trails, and 60 wild and scenic rivers. Entrance fees and concessions generate millions of dollars in income for the National Park Service; however, this metric fails to account for the total value of the National Parks. In failing to consider the value of the ecosystem services provided by the National Parks we fail to quantify and appreciate the contributions our parks make to society. This oversight allows us to continue to underfund a valuable part of our natural capital and consequently damage our supporting environment, national heritage, monetary economy, and many of our diverse cultures. We explore a simple benefits transfer valuation of the United States national parks using National Land Cover Data from 2011 and ecosystem service values determined by Costanza (et al). This produces an estimate suggesting the parks provide $84 billion / year in ecosystem service value. If the natural infrastructure 'asset' that is our national park system had a budget comparable to a piece of commercial real estate of this value, the annual budget of the National Park Service would be roughly an order of magnitude larger at something closer to $30 billion rather than $3 billion.

Quality of Service (QoS) has a significant role in the provision of resources within service oriented distributed systems. In Quality of Service, cloud computing creates new challenges for improvements using the concept of virtualization. Currently, Cloud Computing is very emerging technology in every field of data storage and resource distribution over the network. Considering this new emerging technology, for the ease of data accessibility, price, resource use, restoration, response time and number of constraints the quality performance measures need to be upgraded. The paper highlights the research gap in providing a solution to achieve a Quality of Services in Cloud Computing. We also review the issues and challenges arising in cloud computing to guarantee quality.

This paper describes the development of a laser-based people detection and obstacle avoidance algorithm for a differential-drive robot, which is used for transporting materials along a reference path in hospital domains. Detecting humans from laser data is an important functionality for the safety of navigation in the shared workspace with people. Nevertheless, traditional methods normally utilize machine learning techniques on hand-crafted geometrical features extracted from individual clusters. Moreover, the datasets used to train the models are usually small and need to manually label every laser scan, increasing the difficulty and cost of deploying people detection algorithms in new environments. To tackle these problems, (1) we propose a novel deep learning-based method, which uses the deep neural network in a sliding window fashion to effectively classify every single point of a laser scan. (2) To increase the speed of inference without losing performance, we use a jump distance clustering method to decrease the number of points needed to be evaluated. (3) To reduce the workload of labeling data, we also propose an approach to automatically annotate datasets collected in real scenarios. In general, the proposed approach runs in real-time, performs much better than traditional methods, and can be straightforwardly extended to 3D laser data. Secondly, conventional pure reactive obstacle avoidance algorithms can produce inefficient and oscillatory behaviors in dynamic environments, making pedestrians confused and possibly leading to dangerous reactions. To improve the legibility and naturalness of obstacle avoidance in human crowded environments, we introduce a sampling-based local path planner, similar to the method used in autonomous driving cars. The key idea is to avoid obstacles by switching lanes. We also adopt a simple rule to decrease the number of unnecessary deviations from the reference path. Experiments carried out in real-world environments confirmed the effectiveness of the proposed algorithms.

Statistical management policy and system plays significant role in development of any nation as it guides the planner to analyze the gaps, design programs and allocate budget in efficient manner. Globally, design and usage of statistical management system varies relying on country specific ability and resources availability. Government of Nepal has been managing database in individual as well as thematic manner. Policy wise, thematic database is in operation based on Statistics Act 1958 and individual database is in operation based on Birth, Death and Other Personal Related Events Registration Act 1976. Though civil registration related policies have been either updated or newly formed, sectoral statistic management related policy has not been updated since its first promulgation period (1958). With no policy supporting the consolidated statistical management system, government as well as non-government agencies has been investing millions of dollars annually to collect, compile and analyze individual related data and fulfill their respective objectives. It has forced the government services and performance to be paper-based, time-consuming and tedious thus creating dis-trust among citizen each passing day. Though, formulation of legal instrument promoted digital movement and mandated shift towards e-government modality, the process has been low. Theoretically, Technology Acceptance Model (TAM) state the need of having advanced and efficient technology to be in place in current setting to improve governance, efficiency, accountability, transparency and trust. Also, the same theory state the requirement of strong willingness and motivation from the users (government, non-government and citizen) to adopt the technology based policy and system. As the integrated statistical management policy emphasizes on technology-based system or digital system, the perspectives of Technology Acceptance Model also termed as Information System Theory aid in understanding the context, conceptualizing and addressing the needs with an establishment and implementation of digital system or technology based system. This policy paper applied the Technology Acceptance Model (TAP) to examine the underlying opportunities and challenges associated with an integrated statistical management policy. With existing gaps in existing policy, system and practice alongside an overview of opportunities and challenges, this paper recommends the need of stand-alone integrated statistical management policy to consolidate sectoral as well as civil related information through single system based on recommended policy.

Cardiotonic glycoside toxins, originally isolated from plants or amphibians, have been proposed as mammalian cardiotonic hormones. This paper is a review and update of the discovery of [i] a new class of steroid hormones, [ii] the path for their biosynthesis and [iii] some preliminary data on their function. The compounds are phosphoester conjugates and share a characteristic structural feature, a lactone ring, with [a] one class of synthetic potassium sparing diuretics and with [b] plant and amphibian cardiotonic steroids. Purification was initially monitored by cross reaction with steroid sulfate assays and later with digoxin-specific assays. Six compounds were purified by HPLC to near homogeneity and characterized by Tandem mass spectroscopy (MS-MS) and 31P-NMR. Three were digoxin-like materials (DLM) with 23 carbon atoms. The two extra carbon atoms form a spiral lactone E-ring. Several additional spiral lactones have been identified by MS-MS. In a pilot study, based on MS analysis, we evaluated phosphocholine steroid levels in individual serum samples in patients with pre-eclampsia (n=20). The control group of normotensive pregnant women (n=20) was used to estimate the mean and standard deviation. Twelve of the women with pre-eclampsia had a z-score over 2 for at least one of the four phosphocholine steroids. In contrast, only 1 sample from the normotensive women had a z-score over 2. The observation that there are two patterns, one with elevated phosphocholine steroid levels and one without the elevation, suggests that there may be two different underlying causes of pre-eclampsia. We now need to extend the study to determine which pattern predicts progression to life-threatening hypertension in pregnant women. This pilot study illustrates that it is possible to evaluate individual endogenous cardiotonic hormones without relying on antibodies developed to plant or amphibian toxins.

Shells, probably like no other product of nature, have played an important role in the history of mankind. The pre-Hispanic civilizations of Ibero-America also used certain type of shells profusely in their religious ceremonies, in particular, in Ecuador there were two species of main importance, the Spondylus princeps and the Spondylus calcifer broadly employed to manufacture ornaments that possess a strong symbolic, religious and social meaning and that were almost exclusively used by ruling classes. Among these ornaments, the faces carved on the Spondylus shells are little known. In the present study, we chose a total of fifteen (15) pieces from the Pastor Restrepo Lince´s archaeomalacology collection to understand the possible uses of these objects, through the interpretation of the gestures represented on the faces, their dimensions, and their geographical distribution in pre-Hispanic Ecuador. To achieve the proposed objective, we approach the present investigation from the perspective of the formal analysis of concepts, which is a mathematical theory of representation of knowledge, finding that these faces carved in Spondylus, were used daily or in special ceremonial occasions and that its use was common in all the regional cultures of ancient Ecuador, from the oldest such as Valdivia, and for more than 2000 years, indicating a long tradition of the use of Spondylus as an object of great symbolic and economic value until the arrival of the Spanish

Parkinson's Disease (PD) is a neurodegenerative disorder that affects the motor system of the human body. Currently, the available treatments are limited and often have undesirable side effects. In this context, the aim of this study was to develop a novel combinational formulation of Apomorphine and Quetiapine and evaluate its efficacy in a rat model of PD. The formulation was prepared using the solvent evaporation technique and characterized for its physicochemical properties. The in-vitro drug release was evaluated using the Franz diffusion cell method, and the pharmacokinetics of the combination was studied in rats. The behavioural and biochemical parameters were evaluated in the rats using the Rotarod, pole test, and biochemical assays. The results showed that the developed formulation had satisfactory physicochemical properties and exhibited sustained drug release. The pharmacokinetic studies showed that the combination exhibited a longer residence time than the individual drugs. The behavioural and biochemical parameters showed that the combination was effective in improving motor function and reducing oxidative stress. In conclusion, the developed Apomorphine and Quetiapine combination formulation showed promising results in improving motor function and reducing oxidative stress in rat model of PD. Further studies are required to evaluate the safety and efficacy of the developed formulation in humans.

Background. Specific clinical risk factors that may be associated with ambulatory outcome following thrombolysis therapy in ischemic stroke patients with pre-stroke depression is not fully understood. This was investigated. Methods. Multivariate analyses were performed to identify predictors of functional ambulatory outcomes. Patient demographics and clinical risk factors served as predictive variables, while improvement or no improvement in ambulatory outcome was considered as the primary outcome. Results. A total of 595 of these patients received rtPA of which 310 patients presented with pre-stroke depression, 217 had no improvement in functional outcome, while 93 patients presented with an improvement in functional outcome. Carotid artery stenosis (OR= 11.577, 95% CI, 1.281 – 104.636, P=0.029) and peripheral vascular disease (OR= 18.040, 95% CI, 2.956-110.086, P=0.002) were more likely to be associated with an improvement in ambulation. Antihypertensive medications (OR= 7.810, 95% CI, 1.401 –43.529, P=0.019),previous TIA (OR= 0.444, 95% CI, 0.517 –0.971, P=0.012), and congestive heart failure (OR= 0.217, 95% CI, 0.318 –0.402, P=0.030) were associated with a no improvement in ambulation. Conclusion. After adjustment for covariates, more clinical risk factors were associated with no improvement when compared with improvement in functional outcome following thrombolysis therapy in an acute ischemic stroke population with pre-stroke depression.

The nondestructive testing of reinforced concrete chimneys, especially the high ones, is an important element of the assessment of their condition, making it possible to forecast their safe service lifespan. Industrial chimneys are often exposed to the strong action of acidic substances – they are adversely affected by the flue gas condensate on the inside and by acid precipitation on the outside. Initially, this results in the corrosion of the shell concrete and then in the corrosion of the reinforcing steel. During the service life of such chimneys their condition should monitored in order to prevent structural failures and indicate the most endangered parts of the structure. Owing to thermographic surveys one can monitor the hazards leading to the degradation of the chimney structure, which is particularly vital when due to the character of the production process the chimney cannot be put out of operation. The methods for the interpretation of results from thermovision studies to determine the safety and durability of industrial chimneys are shown.

This observational study was ordered by the Medical Practitioners’ Chamber in Warsaw. The objective of the study was to evaluate the health status of physicians in relation to their occupational duties. Professional burnout was considered relative to different features of personality. This study was initially carried out from 2005–2008, but further analysis of burnout and personality was carried out from 2017–2018. The research tools were anonymous, validated questionnaires. The sample size was based on the size of the population— the registry of the Regional Chamber of Medical Practitioners— and literature on burnout prevalence. The respondents’ work places were randomly selected from the Mazovian District register. The test on burnout was completed by 378 respondents, while 62 subjects completed a personality test. Results showed that burnout syndrome was an occupational problem for healthcare workers. Professional burnout affected as many as 42% of respondents(n = 158). It affected two age groups in particular: physicians up to 31 years old and individuals aged 41-50. Moreover, neuroticism was found to be significantly related to burnout syndrome. In conclusion, burnout syndrome is common among medical practitioners, and neuroticism may be correlated with burnout syndrome.

In recent years, autonomous robots have proven capable of solving tasks in complex environments. In particular, robot manipulations in activities of daily living (ADL) for service robots have been in wide use. However, manipulations such as loading a dishwasher or folding laundry are difficult to automate robustly. In addition, manipulations of grasping multiple objects in domestic environments present difficulty. To perform those applications better, we developed robotic systems based on shared autonomy by combining the cognitive skills of a human operator with autonomous robot behaviors. In this work, we present techniques for integration of a shared autonomy system for assistive mobile manipulation and new strategies to support users in the domestic environment. We demonstrate that the robot can grasp multiple objects with random size at known and unknown table heights. Specifically, we developed three strategies for manipulation. From experimental results, we observed that the first strategy has the highest success rate (70% for random objects) up to 70 cm table height. Two other strategies perform better for 80 cm to 100 cm table height. The success rate of the second and third strategies shows an average 63.3% and 73.3%, respectively, for grasping random objects. We also demonstrated these strategies using two intuitive interfaces, a visual interface in rviz and a voice user interface with speech recognition, which are suitable for elderly people. In addition, the robot can select strategies automatically in random scenarios, which make the robot intelligent and able to make decisions independently in the environment. We obtained interesting results showing that the robot adapts to the environmental variation automatically. After these experimental demonstrations, our robot shows the capabilities for employment in domestic environments to perform actual tasks.

The prevalence of corona virus and the novel COVID-19 disease in the entire globe has exacerbated different impact on socioeconomic spectrum in the world, including water use pattern. Thus a research was conducted to examine the comparative use of water during pre- and post-COVID-19 lockdown pattern among post-primary schools in Iwo, Osun State, Nigeria. A survey was conducted among fifteen schools which were randomly selected, but with eight public and seven private schools for the investigation. Both descriptive and inferential statistical techniques were used in data analysis. The results revealed that the major source of water to the schools investigated is ground water which is obtained through hand-dug wells and boreholes. It was further discovered that there was increase in water use during post-COVID-19 lockdown era as a result of the directive by the government that clean water should be provided for hand-washing by all schools regardless of the owner to curtail the spread of COVID-19 disease in the country. One sample t-test also revealed that there was a significant difference in water use at (p<0.01) level. It is recommended that the government and other stakeholders in water sector to ensure that all-time and non-seasonal dependent source of water be provided rather than ground water source which is susceptible to variations in water yields from seasonal variations. This will enable continuous clean water supply, for all purposes, including COVID-19 protocols.

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the second Joint Polar Satellite System (JPSS) completed its sensor level testing in February 2018. The JPSS-2 (J2) mission is scheduled to launch in 2022, and will be very similar to its two predecessor missions, the Suomi National Polar-orbiting Partnership (SNPP) mission, launched on 28 October 2011, and JPSS-1 (renamed NOAA-20) launched on 18 November 2017. VIIRS instrument has 22 spectral bands covering the spectrum between 0.4 and 12.6 mircron: 14 reflective solar bands (RSB), 7 thermal emissive bands (TEB), and one day-night band (DNB). It is a cross-track scanning radiometer capable of providing global measurements through observations at two spatial resolutions, 375 m and 750 m at nadir for the imaging bands and moderate bands, respectively. This paper will provide an overview of J2 VIIRS characterization methodologies and calibration performance during the pre-launch testing phases performed by the National Aeronautics and Space Administration (NASA) VIIRS Characterization Support Team (VCST) to evaluate the at-launch baseline radiometric performance and generate the parameters needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). Key sensor performance metrics include the signal to noise ratio (SNR), radiance dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, spectral performance, response versus scan-angle (RVS), and scattered light response. A set of performance metrics generated during the pre-launch testing program will be compared to both the SNPP and JPSS-1 VIIRS sensors.

This study presents a pre-processing approach adopted for the radar reflectivity data assimilation and results of simulations with the Harmonie numerical weather prediction model. The method shows an improvement of precipitation prediction within the radar location area in both the rain rates and spatial pattern presentation. With the assimilation of radar data, the model simulates larger water content in the middle troposphere within the layer from 1 to 6 km, with major variations at 2.5–3 km; it also reproduces better the mesoscale belt and cell patterns of precipitation fields.

Remaining service life (RSL) of pavement, as a sign of future pavement performance, has always received growing attention from pavement engineers. The RSL describes the time from the moment of pavement inspection until such a time when a major repair or reconstruction is required. The conventional approach to determining RSL involves using non-destructive tests. These tests, in addition to being costly, interfere with traffic flow and compromise users' safety. In this paper, surface distresses of pavement have been used to estimate the pavement’s RSL in order to eliminate the aforementioned problems and challenges. To implement the proposed theory, 105 flexible pavement segments were taken from Shahrood-Damghan Highway (Highway 44) in Iran. For each pavement segment, the type, severity, and extent of surface damage and pavement condition index (PCI) were determined. The pavement RSL was then estimated using non-destructive tests include Falling Weight Deflectometer (FWD) and Ground Penetrating Radar (GPR). After completing the dataset, the modeling was conducted to predict RSL using three techniques include Support Vector Regression (SVR), Support Vector Regression Optimized by Fruit Fly Optimization Algorithm (SVR-FOA), and Gene Expression Programming (GEP). All three techniques estimated the RSL of the pavement by selecting the PCI as input. The Correlation Coefficient (CC), Nash-Sutcliffe efficiency (NSE), Scattered Index (SI), and Willmott’s Index of agreement (WI) criteria were used to examine the performance of the three techniques adopted in this study. In the end, it was found that GEP with values of 0.874, 0.598, 0.601, and 0.807 for CC, SI, NSE, and WI criteria, respectively, had the highest accuracy in predicting the RSL of pavement.

In Differentiated Services (DiffServ) architecture, Priority Service System (PSS) plays a vital responsibility to provide Quality-of-Service (QoS) for the applications based on networks. Priority queuing systems has always been a subject of interest for analytical modelling and evaluating the performance. However, previous works have mainly focused on performing priority queuing under range dependent traffics, namely Short Range Dependent (SRD) or Long Range Dependent (LRD). Recent studies revealed that realistic traffic demonstrates a heterogeneous nature for the modern networks that provide multiple services. In this paper, the results of analytical and simulation models of dynamic priority service systems is reviewed to study the heterogeneous traffic impact on designing and performance of the systems based on networks. In this paper, the results of analytical and simulation models of dynamic priority service systems is reviewed to investigate the impact of heterogeneous traffic on the design and performance of network-based systems. Here, the time of presence of requests in limited and unlimited buffer system is restricted. If the restriction is violated, the requests will be lost. The results of experiments conducted on both models are compared and it is identified that they differ in the allowable limit (2-9) %.

OpenAI has managed to turn 100 million heads in two months towards their new Language model tool (LM) ChatGPT. The third generation Generative Pretrained Transformer (GPT-3) has the capacity to tackle simple to complex and sophisticated problems, while providing reasoning behind its generated answers. ChatGPT can be used to increase productivity and improve efficiency and face challenging problems. Programming mobile applications is a challenging task that requires professional software engineers, skills and abilities to be developed. The following paper takes a case study approach to assess how novice app developers can use ChatGPT to generate Java scripts that will be used in Android studio to create a functional application. The results after, many iterations and ongoing conversations with ChatGPT managed to create an application for the anticipated function. Important insights have been drawn from the case study that could set the ground for any novice user seeking to create applications using Java scripting and Android Studio.

Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors influence COVID-19 by applying the Adverse Outcome Pathway (AOP) framework well-established in regulatory toxicology. This framework aims to model the sequence of events starting from an initial interaction of a stressor with the organism and the progress through key biological events leading to an adverse health outcome. Several linear AOPs depicting pathways from the binding of the virus to ACE2 up to clinical outcomes observed in COVID-19 patients have been developed and integrated into a network offering a unique overview of the mechanisms underlying the disease. As SARS-CoV-2 infectibility and ACE2 activity are the major starting points and inflammatory response is central in the development of COVID-19, we evaluated how eleven intrinsic and extrinsic factors modulate those processes impacting clinical outcomes. Applying this AOP-aligned approach enables the identification of current knowledge gaps orientating for further research and allows to propose biomarkers to identify of high-risk patients. This approach also facilitates expertise synergy from different disciplines to address public health issues.

Ionic liquids have been recognised as interesting solvents applicable in the efficient lignocellulosic biomass valorisation, especially in the biomass fractionation into individual polymeric components or direct hydrolysis some of biomass fractions. Considering the chemical character of ionic liquids, two different approaches, paved the way for a fractionation of biomass. The first strategy integrated a pre-treatment, hydrolysis and conversion of biomass through the employment of hydrogen-bond acidic 1-ethyl-3-methyimidazolim hydrogen sulfate ionic liquid. The second one relied on the use of a three-step fractionation process with hydrogen-bond basic 1-ethyl-3-methylimidazolium acetate to produce high purity cellulose, hemicellulose and lignin fractions. The proposed approaches were scrutinised for wheat straw and eucalyptus residues. Those different biomasses allowed understanding that enzymatic hydrolysis yields are dependent on the crystallinity of pre-treated biomass. The use of acetate based ionic liquid allowed to change crystalline cellulose I to cellulose II and consequently enhanced glucan to glucose yield to 93.14.1 mol% and 82.91.2 mol% for wheat straw and eucalyptus, respectively. Whereas for hydrogen sulfate ionic liquid, the same enzymatic hydrolysis yields were 61.6  0.2 mol% for wheat straw and only 7.90.3 mol% for eucalyptus residues. These results demonstrate the importance of either ionic liquid character or biomass type on the efficient biomass processing.

Recent advancements of computer and electronic systems have motivated the extensive use of intelligent systems for automation of agricultural industries. In this study, the temperature variation of the mushroom growing room is modeled through using a multi-layered perceptron (MLP) and radial basis function networks. Modeling has been done based on the independent parameters including ambient temperature, water temperature, fresh air and circulation air dampers, and water tap. According to the obtained results from the networks, the best network for MLP is found to be the second repetition with 12 neurons in the hidden layer and 20 neurons in the hidden layer for radial basis function networks. The obtained results from comparative parameters for two networks showed the highest correlation coefficient (0.966), the lowest root mean square error (RMSE) (0.787) and the lowest mean absolute error (MAE) (0.02746) for radial basis function. Therefore, the neural networks with radial basis function was selected as the optimal predictor for the behavior of the system.

: Following the phenomenal growth of and competition among coffee chain retailers, the coffee chain market has expanded substantially thanks to rising income levels, the increasing young population, and rapidly changing lifestyles. Attracting consumers’ attention and enhancing their loyalty behaviors have become very difficult for coffee chain retailers. This study seeks to understand the mechanisms through which emotions and the dedication-constraint model lead to brand loyalty and willingness to pay more to certain coffee chain retailers. Emotions and the dedication-constraint model are major factors in the research, but few studies have combined them to examine the formation of loyalty behaviors. This study synthesizes emotional responses and the dedication-constraint model to develop a theoretical model. Based on the ambivalent view of emotions, it also examines how positive and negative emotions affect the combination of brand loyalty and willingness to pay more to certain coffee chain retailers. Moreover, it identifies the antecedents of affective and calculative commitments in the context of coffee chain retailers. Our findings indicate that loyalty behaviors (dedication- and constraint-based mechanisms from brand loyalty and willingness to pay more to certain coffee chain retailers), emotional responses, and affective and calculative commitments significantly affect brand loyalty directly and indirectly through both positive and negative emotions. Furthermore, service quality, physical environment quality, and price fairness significantly affect affective commitments, while price fairness significantly affects both affective and calculative commitments. Finally, affective and calculative commitments significantly affect willingness to pay more, both directly and indirectly, through positive emotions and affect it directly through negative emotions. The results’ theoretical and managerial implications and possible future research directions are discussed.

Introduction: Since its discovery in late 2019, the novel coronavirus (SARSCOVID-2) that causes COVID-19 has spread fast, prompting the World Health Organization (WHO) to designate the disease a worldwide pandemic on March 11, 2020.The epidemic has profoundly altered the preexisting global sexual and reproductive health landscape .The virus’s load has put ordinary services in jeopardy and harmed other health priorities. This encompasses both the provision and the supply of contraceptives, sexual health, new born and maternal health services. This Scoping review therefore mapped the availability evidence on the impact and effects of the COVID-19 disease outbreak on sexual and reproductive health. Methods: The methodological framework by Arksey and O’Malley guided this scoping review. A literature search was conducted from the following databases: Embase, PubMed, CINAHL, Scopus, WOS, and AJOL. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram and the preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) checklist were used to document the review process. The Strobe critical review checklist was used to determine the quality of the included studies. Results:19 studies were reviewed, out of which 4 were cross sectional studies, 1 was an observational study, 1 was a descriptive analytical study and the rest were qualitative studies .Majority of the studies showed evidence on the impact of COVID-19 and family planning service, maternal and child services, and three studies reported on COVID-19 and sexual behaviour. Five of the nineteen included studies reported on the impact of COVID-19 and family planning service. Conclusion: This scoping review has granted the assessment of the impact of novel SARS-CoV-2 on Sexual and reproductive health services with regards to sexual behaviour, family planning and maternal, neonatal and child health. From the 18 articles identified and reviewed, the overall responses stipulated a significant reduction in client’s utilization of services due to challenges experiences in service implementation such as stock outs. In addition, low demand for reproductive health services by clients due to restrictions imposed on the movements of people to curb the spread of the virus. It is therefore important that Governments and relevant stakeholders in Maternal and Sexual Reproductive Health prioritize development of policies and practices that protect women from the impacts of the pandemic. Furthermore, regular audits to detect trends in MSRH are necessary to inform on going mitigation efforts.

Multigranulation is a new approach to the Rough Set Theory, where several separability relationships are used to obtain different granulations of the universe. The Multigranulation starts from the existence of different contexts or subsets of features to characterize the objects of the universe. In this paper, a method for the generation of contexts from the construction of similarity relations is proposed.The proposed solution was evaluated in an international database using the KNN classifier. It was also applied in the solution of a real problem in Civil Engineering specifically in Traffic Engineering, the contexts generated from the proposal used to determine the features of higher incidence in the service level of the road. The results achieved both in the international database and in the proposed application demonstrate the applicability of the proposed method.

During the past few decades, hybrid nanoparticles (HNPs) based on a magnetic material and gold have attracted interest for applications in catalysis, diagnostics and nanomedicine. In this paper, magnetic CoFe2O4/Au HNPs with an average particle size of 10–20 nm decorated with 2-nm gold clusters were prepared using methionine as a reducer and an anchor between CoFe2O4 and gold. The obtained nanoparticles were studied by X-Ray diffraction (XRD), transmission electron microscopy (TEM), Fourier-transform infrared (FT-IR) spectroscopy and X-Ray photoelectron spectroscopy (XPS) and UV-Vis spectroscopy techniques. The TEM images of the HNPs obtained after one, six and ten gold deposition cycles showed that the surface of cobalt ferrite was covered with gold nanoclusters, which slightly increased with an increase in the number of gold deposition cycles (from 2.12 ± 0.15 nm after one cycle to 2.46 ± 0.13 nm after ten cycles) without any change in surface density. The magnetic measurements showed that the obtained HNPs possessed typical ferrimagnetic behaviour, which corresponds to that of CoFe2O4 nanoparticles. The toxicity evaluation of the synthesised HNPs on Chlorella vulgaris indicated that they can be applied to biomedical applications such as magnetic hyperthermia, photothermal therapy, drug delivery, bioimaging and biosensing.

Students are regarded as frequent users of mobile phones which has proven to be a convenient and acceptable method to promote healthy lifestyle. Students usually engage in relatively high levels of risky behavior and make unhealthy lifestyle choices, a study that investigates how health students access health information is necessary. The study adopted a descriptive cross-sectional study which was undertaken among third-year nursing students from three nurses training institutions in Ghana. A total of 270 students participated in the study. Most of the respondents who were currently subscribers of the health messages reported that they usually received health information on reproductive health issues, nutrition, and practicing safe sex. Most of the health students revealed that they needed more information on safe sex, diet, managing weight, and stress management. The results also show that health students are likely to remember and share short messages with friends. The findings serve as an ‘eye-opener’ for health educators and mobile service providers concerning factors that should be taken into consideration when framing health text messages that will attract health students.

Background: We conducted research on the newly developed personalized recommendation service (PRS) of the global network of Korean scientists and engineers (KOSEN) in order to explore the information usage behavior and importance of the PRS used by Korean scientists and engineers. Methods: In order to understand information usage behavior, we gathered data from 513 survey results and analyzed them in terms of information usage behavior and the corresponding importance in each of the service quality areas. Results: We analyzed the 321 outcomes that indicated non-use of the PRS in order to understand the underlying reason(s); we employed 192 results that demonstrated the use of functionality to examine information usage behavior and importance. They found that the predominant motive for non-use of the service resulted from the respondents not knowing how to use it. According to demographic characteristics, the usage behavior of the PRS showed a difference regarding the purpose of using the service in the categories of gender and major field of study. Furthermore, users were concerned with various components of the PRS such as ease of use, design, relevance of content, user support, and interactivity. Conclusions: We suggest reinforcing user education degree and promotion to enhance the PRS. Since users were concerned with ease of use, design, relevance, user support, and interactivity, we recommend these as major points for improvement.

The Asian weaver ant (Oecophylla smaragdina) is a natural enemy, generalist predator of diverse major pest species (i.e. the highly destructive oriental fruit fly Bactrocera dorsalis) in economically strategic agricultural landscapes in Australia and Southeast Asia countries. For effective implementation of the weaver ant for biological control of the invasive bagworms Metisa plana, the dominant pest in the oil palm plantation, its distribution was investigated in Malaysia. From 2018-2022, censuses were first carried out to record Oecophylla colonies presence. Oecophylla colonies’ occupation patterns were monitored on 8 selected plantations. To distinguish between brood and barracks nests, 26 captured nests were evaluated to define the main predictor variable for its practical visual identification. More than 11000 palms with 10821 nests for over 500 colonies were sampled in this study. Results showed that O. smaragdina colonies distribution pattern exhibited three-dimensional ubiquitous occupation dominance. We also found that by observing the colony’s dense population spatial arrangements, it demonstrates them as spreading by waves featuring interconnected irregular geometrical patches shaped for each colony. The height to the ground nest location in palm canopies was the significant visual discriminant factor between Brood and barrack nests. Moreover, polydomous arboreal nesting behavior occupation occurred irrespective of palms or associated host plants sizes (≥ 3 m), throughout the year. However, colony nesting behaviors were polydomous and monodomous on shorter plants (≥ 2 m), while being strictly monodomous on small plants (≤ 1.5 m). Colonies occupied an average 3 to 4 palms yearly beginning from the newly founding phase up to the stable mature phase (3 to 4 years). Furthermore, we found that matured stable colonies (3 ≥ age ≥13) occupied 10-12 palms on average, on 800 m² to 2500 m² area delimited by a minimum average 20 m² of “no ants land” zone between each colony. Our results suggest that a sustained agriculture system in this area would be possible with the presence of matured colonies nests exploitation which could provide an efficient biological control ecosystem service.

Radio Frequency Interference (RFI) detection and characterization play a critical role to in ensuring the security of all wireless communication networks. Advances in Machine Learning (ML) have led to the deployment of many robust techniques dealing with various types of RFI. To sidestep an unavoidable complicated feature extraction step in ML, this paper proposes an efficient end-to-end method using the latest advances in deep learning to extract the appropriate features of the RFI signal. Moreover, this study utilizes the benefits of transfer learning to determine both the type of received RFI signals and their modulation types. To this end, the scalogram of the received signals is used as the input of the pre-trained convolutional neural networks (CNN), followed by a fully-connected classifier. This study considers a digital video stream as the signal of interest (SoI), transmitted in a real-time satellite-to-ground communication using DVB-S2 standards. To create the RFI dataset, the SoI is combined with three well-known jammers namely, continuous-wave interference (CWI), multi- continuous-wave interference (MCWI), and chirp interference (CI). This study investigated four well-known pre-trained CNN architectures, namely, AlexNet, VGG-16, GoogleNet, and ResNet-18, for the feature extraction to recognize the visual RFI patterns directly from pixel images with minimal preprocessing. Moreover, the robustness of the proposed classifiers is evaluated by the data generated at different signal to noise ratios (SNR).

Access to food systems is essential to sustain urban life. In this paper, we discuss the differences concerning accessibility levels to food systems among potential consumers in Belo Horizonte, Brazil. The goal was to characterize spatial mismatches regarding food opportunities and identify suitable areas for sustainable food mile solutions, such as non-motorized home delivery and purchase trips. For this, we have spatially related: (i) the population concentration; (ii) the income of households; and (iii) accessibility measures considering both the spatial structure of food retailers and the distance between households and stores, considering the food mile. We have then used spatial statistics and spatial analysis methods to determine the spatial pattern of variables and the cumulative opportunity measure for households. There is great spatial differentiation regarding the accessibility levels of food retailers and the results can be considered to support the development of policy and land use regulation that can stimulate non-motorized and collaborative delivery as an effective last-mile solution.

Background: The world-wide rate of obesity is increasing continuously, representing a serious medical threat since it is associated with a variety of diseases including type 2 diabetes, cardiovascular disease, and numerous cancers. Sophora japonica is used as a traditional herb for medicinal purposes in eastern Asia. However, the anti-obesity effects of S. japonica fruit have not been explored. Objective: The aim of this study is to investigate the inhibition of adipocyte differentiation and adipogenesis by an ethanol extract of S. japonica fruit (EESF) in 3T3-L1 pre-adipocytes. Methods: MTT assay, Oil Red O staining, and Triglyceride contents were used to investigate lipid accumulation in 3T3-L1 cells to clarify adipocyte differentiation. The expression levels of various molecular signals associated with adipogenesis and lipogenesis were examined by western blot analysis. Results: Our results demonstrate that EESF suppressed the terminal differentiation of 3T3-L1 pre-adipocytes in a dose-dependent manner, as confirmed by a decrease in lipid droplet number and lipid content through Oil Red O staining. EESF significantly reduced the accumulation of cellular triglyceride, which was associated with a significant inhibition of the levels of pro-adipogenic transcription factors, downregulated the expression levels of adipocyte-specific proteins. Furthermore, EESF treatment effectively increased the phosphorylation of AMPK and ACC. Conclusions: These results together indicate that EESF has significant effects on the inhibition of adipogenesis and acts by stimulating the AMPK signaling pathway. Further studies will be needed to identify the active compounds in S. japonica.

The novel coronavirus (COVID-19) was first reported in the U.S. on December 29, 2019 and has spread rapidly throughout the country, affecting individuals with varying severity due to their risk status. According to the Centers for Disease Control and Prevention, it is estimated that 45.4% of US adults are at higher risk for complications from coronavirus disease because of cardiovascular disease, diabetes, respiratory disease, hypertension, or cancer. In this study, we developed a mathematical model to assess the impact of a COVID-19 vaccine among low and high risk groups. Numerical simulations shows vaccinating both low and high risk groups simultaneously, rather than prioritizing the vaccine on high risk group only, further reduces the daily mortality. The result supports the need for an aggressive vaccination program, regardless of whether individuals are within the low or high risk population.

We present a methodology to enable users to interact with statistical information owned by an institution and stored in a cloud infrastructure. Mainly based on R, this approach was developed following the open-data philosophy. Also, since we use R, the implementation is mainly based on open-source software. R gives several advantages from the point of view of data management and acquisition, as it becomes a common framework that can be used to structure the processes involved in any statistical operation. This simplifies the access to the data and enable to use all the power of R in the cloud information. This methodology was applied successfully to develop a tool to manage the data of the Centre d’Estudis d’Opinió, but it can be applied to other institutions to enable open access to its data. The infrastructure also was deployed to a cloud infrastructure, to assure the scalability and a 24/7 access.

Earnings management and financial distress are two critical facets of financial management in corporations that have lately been the focus of thorough research from both scholars and practitioners. The purpose of the research is to evaluate the influence of financial distress on the earnings management of companies listed at the NSE during the pre- and post-COVID eras. Multiple linear regression was applied in this study to examine the causal association between earnings management and financial distress. To assess the effect of financial distress on earnings management, the study analyzed data from 37 listed companies during the pre-COVID and post-COVID periods. The methodology also takes into account control factors like firm size, GDP, and inflation. The pre-COVID research indicates a significant positive correlation between financial strain and earnings management. In contrast, the correlation between financial distress and earnings management is not statistically significant in the post-COVID analysis. However, research shows that firm size has a statistically significant negative influence on managing earnings. The results of this study show that smaller firms are more inclined to engage in earnings management during the post-COVID era than bigger ones.

Forest fires are part of a set of natural disasters that have always affected regions of the world typically characterized by a tropical climate with long periods of drought. However, due to climate change in recent years, other regions of our planet have also been affected by this phenomenon, never seen before. One of them is certainly the Italian peninsula, and especially the regions of southern Italy. For this reason, the scientific community, as well as remote sensing one, is highly concerned in developing reliable techniques to provide useful support to the competent authorities. In particular, three specific tasks have been carried out in this work: (i) fire risk prevention, (ii) active fire detection, and (iii) post-fire area assessment. To accomplish these analyses, the capability of a set of spectral indices, derived from spaceborne remote sensing (RS) data, is assessed to monitor the forest fires. The spectral indices are obtained from Sentinel-2 multispectral images of the European Space Agency (ESA), which are free of charge and openly accessible. Moreover, the twin Sentinel-2 sensors allow to overcome some restrictions on time delivery and observation repeat time. The performance of the proposed analyses were assessed experimentally to monitor the forest fires occurred in two specific study areas during the summer of 2017: the volcano Vesuvius, near Naples, and the Lattari mountains, near Sorrento (both in Campania, Italy).

Memphis aquifer is the primary drinking water source in Shelby County (Tennessee, USA) and supplies industrial, commercial, and residential water. Memphis aquifer is separated from the Shallow aquifer by a clayey layer known as Upper Claiborne Confining Unit (UCCU). All of the production wells in the Memphis area are screened in the Memphis aquifer or even deeper in the Fort Pillow aquifer. Traditionally, it was assumed that the UCCU could fully protect the Memphis aquifer from the contaminated Shallow aquifer groundwater. However, recent studies show that at some locations the UCCU is thin or absent which possibly leads to the contribution of Shallow aquifer to the Memphis aquifer. Accurately locating the breaches demands expensive and difficult geological or geochemical investigations, especially within an urban area. Hence, a pre-field investigation to identify the locations where the presence of breaches is likely can significantly reduce the cost of field investigations and improve the their results. In this study, to identify the locations where the presence of breaches in the UCCU is likely we use three different analyses: (1) pilot point calibration (PPC), (2) velocity and flow budget (VFB), and (3) particle tracking (PT) to post-process the developed groundwater results. These pre-field numerical investigations provide relevant and defensible explanations for groundwater flow anomalies in an aquifer system for informed decision-making and future field investigations. In this study, we identify five specific zones within the broad study area which are reasonable candidates for the future field investigations. Finally, we test the results of each analysis against other evidence for breaches to demonstrate that the results of the numerical analyses are reliable and supported by previous studies.

The intricate nature of congenital heart disease requires understanding of complex, patient-specific three-dimensional dynamic anatomy of the heart, from imaging data such as three-dimensional echocardiography for successful outcomes from surgical and interventional procedures. Conventional clinical systems use flat screens and therefore display remains two-dimensional, which undermines the full understanding of the three-dimensional dynamic data. Additionally, control of three-dimensional visualisation with two-dimensional tools is often difficult, so used only by imaging specialists. In this paper we describe a virtual reality system for immersive surgery planning using dynamic three-dimensional echocardiography, which enables fast prototyping for visualisation such as volume rendering, multi-planar reformatting, flow visualisation, and advanced interaction such as three-dimensional cropping, windowing, measurement, haptic feedback, automatic image orientation, and multi-user interactions. The available features were evaluated by imaging and non-imaging clinicians, showing that the virtual reality system can help improve understanding and communication of the three-dimensional echocardiography imaging and potentially benefit congenital heart disease treatment.

To keep its business reliable, Google is concerned to ensure quality of apps on the store. One crucial aspect concerning quality is security. Security is achieved through Google Play protect and anti-malware solutions. However, they are not totally efficient since they rely on application features and application execution threads. Google provides additional elements to enable consumers to collectively evaluate applications providing their experiences via reviews or showing their satisfaction through rating. The latter is more informal and hides details of rating whereas the former is textually expressive but requires further processing to understand opinions behind. Literature lacks approaches which mine reviews through sentiment analysis to extract useful information to improve security aspects of provided applications. This work goes in this direction and in a fine-grained way, investigates in terms of confidentiality, integrity, availability and authentication (CIAA). While assuming that reviews are reliable and not fake, the proposed approach determines review polarities based on CIAA-related keywords. We rely on the popular classifier Naive Bayes to classify reviews into positive, negative and neutral sentiment. We then provide an aggregation model to fusion different polarities to obtain application global and CIAA reputations. Quantitative experiments have been conducted on 13 applications including e-banking, live messaging and anti-malware apps with a total of 1050 security-related reviews and 7.835.322 functionality-related reviews. Results show that 23% of applications (03 apps) have a reputation greater than 0.5 with an accent on integrity, authentication and availability, while the remaining 77% has a polarity under 0.5. Developers should make lot of efforts in security while developing codes and that more efforts should be made to improve confidentiality reputation. Results also show that applications with good functionality-related reputation generally offer bad security-related reputation. This situation means that even if the number of security reviews is low, it does not mean that security aspect is not a consumer preoccupation. Unlike, developers put much more time to test whether applications works without errors even if they include possible security vulnerabilities. A quantitative comparison against well-known rating systems reveals effectiveness and robustness of CIAA-RepDroid to repute apps in terms of security. CIAA-RepDroid can be associated to existing rating solutions to recommend developers exact CIAA aspects to improve within source codes.

Artificial groundwater recharge is commonly used for drinking water supply. The resulting water quality is highly dependent on the raw water quality. In many cases, pre-treatment is required. Pre-treatment improves the drinking water quality, although how and to what extent it affects the subsequent pond water quality and infiltration process, is still unknown. We evaluated two treatment systems by applying different pre-treatment methods for raw water from a eutrophic and temperate lake. An artificial recharge pond was divided into two parts, where one received raw water, only filtered through a micro-screen with 500 µm pores (control treatment), while the other part received pre-treated lake water using chemical flocculation with polyaluminium chloride (PACl) combined with sand filtration, i.e. continuous contact filtration (contact filter treatment). Water quality such as cyanobacterial biomass, microcystin-LR as well as organic matter and nutrients were measured in both treatment processes. We found cyanobacterial biomass and microcystin-LR level after the contact filter treatment was significantly different from the control treatment and also significantly different in the pond water. In addition, with contact filter treatment, total phosphorus (TP) and organic matter removal were significantly improved in the end water, TP was reduced by 96 % (< 20 µg/L) and the total organic carbon (TOC) was reduced by 66 % instead of 55 % (TOC content around 2.1 mg/L instead of 3.0 mg/L). This full-scale onsite experiment demonstrated effective pre-treatment would benefit a more stable water quality system, with less variance and lower cyanotoxin risk. In a broader drinking water management perspective, the presented method is promising to reduce cyanotoxin risk, as well as TP and TOC, which are all predicted to increase with global warming and extreme weather.

Service pricing is a bottleneck in the development of innovation services, as it is the issue of most concern between the suppliers and demanders. In this paper, a negotiation pricing model that is based on the multiobjective genetic algorithm is developed for innovation service pricing. Regarding the service pricing process as a multiobjective problem, the objective functions, which include the service price, service efficiency, and service quality, for suppliers and demanders are constructed. As the solution of a multiobjective problem is typically a series of alternatives, another negotiation process is necessary for determining the final decision. A learning strategy is adopted during the negotiation process to simulate reality. Finally, the model is implemented for an innovation service transaction, the objective of which is to identify the optimal price plan. The results demonstrate that the model can provide quantitative decision support for the pricing of an innovation service and ultimately yield a win-win result for both the supplier and demander of the innovation service. Furthermore, the influence of the parameters during the negotiation process is analyzed in detail. The effects of the learning strategy on accelerating the negotiation process, as well as the chosen of reasonable parameters are given.

We propose a notion of $(q,\sigma,\tau)$-differential graded algebra, which generalizes the notions of $(\sigma,\tau)$-differential graded algebra and $q$-differential graded algebra. We construct two examples of $(q,\sigma,\tau)$-differential graded algebra, where the first one is constructed by means of generalized Clifford algebra with two generators (reduced quantum plane), where we use a $(\sigma,\tau)$-twisted graded $q$-commutator. In order to construct the second example, we introduce a notion of $(\sigma,\tau)$-pre-cosimplicial algebra.

In addition to the traditional QoS metrics of delay, delay jitter, and packet loss probability (PLP), Quality of Experience (QoE) is now widely accepted as a numerical proxy for actual user experience. The literature has reported many mathematical mappings between QoE and QoS. These QoS parameters are measured by the network providers using sampling. There are some papers studying sampling errors in QoS measurements; however there is no account of propagation of these sampling errors to QoE evaluation. In this paper, we used industrially acquired measurements of PLP and jitter to evaluate the sampling errors and correlation in measurements. Focussing on Video-on-demand (VoD) applications, we use subjective testing and regression to map QoE metrics onto PLP and jitter. The resulting mathematical functions of QoE and theory of error propagation was used to evaluate the propagated error in QoE, and this error was represented as confidence interval. Using the guidelines of UK government for sampling, our results indicate that confidence intervals around estimated QoE in a busy hour can be between MOS=1 to MOS=5 at targeted operating point of QoS parameters. These results are a new perspective on QoE evaluation, and are of great significance to all organisations that need to estimate the QoE VoD applications precisely.

Based on the topology of wide area protection system (WAPS), after studying the reliability of hardware system and information flow in the WAPS and establishing the reliability assessment model, the multi-service reliability analysis method with multi monitoring and protection tasks in WAPS was proposed. In the model, the impact of network quality of service (QoS) such as information flow loss and delay, is studied. On the base of the model, the multi-service reliability evaluation method is employed to analyze the reliability of a WAPS of IEEE14 node power system, and the key nodes of the WAPS is given, which provides a basis for improving the reliability of the WAPS.

BACKGROUND AND PURPOSE—Atherosclerotic plaque instability and rupture in patients with asymptomatic carotid artery stenosis (ACAS) is a leading cause of major adverse cardiac events (MACE). This could be mainly evidenced in patients with pre-diabetes. Indeed, the altered glucose homeostasis and insulin resistance could cause over-inflammation of atherosclerotic plaque, favoring its conversion to unstable phenotype with rupture and MACE. Notably, the metformin therapy reducing the metabolic distress and the inflammatory burden, could lead to reduction of MACE in ACAS patients with pre-diabetes. In this setting, microRNAs (miRs) could be used as molecular biomarkers of atherosclerosis progression, plaque rupture and worse prognosis in normoglycemics (NG) vs. pre-diabetics metformin users (PDMU) vs. pre-diabetics non metformin users (PDNMU). However, the aim of our study was to investigate a wide miRNA panel in peripheral blood exosomes from patients with ACAS divided in NG vs. PDMU vs. PDNMU, and to associate the circulating miRNA expression profiles with MACE at 2 years of follow-up after endarterectomy. METHODS—The study included 234 patients with ACAS divided in NG (n 125), PDNMU (n 73) and PDMU (n 36). The miRs’ expression profiles of circulating exosomes were determined at baseline and at 2 years of follow-up by Affymetrix microarrays from plasma samples of the patients from any study cohort. Then we collected and analyzed MACE at 2 years of follow-up in NG vs. PDMU vs. PDNMU. RESULTS—prediabetics vs. NG had over-inflammation (p<0.05) and over expressed miR 24 and miR 27 at baseline. At 2 years of follow-up PDNMU vs. NG, PDMU vs. NG and PDNMU vs. PDMU over-expressed inflammatory markers and miR 24, miR 27, miR 100, miR 126 and miR 133 (p<0.05). Finally, at follow-up end we observed a significant difference about MACE comparing PDNMU vs. NG (n 27 (36.9%) vs. n 8 (6.4%); p<0.05), PDNMU vs. PDMU (n 27 (36.9%) vs. n 6 (16.6%); p <0.05), and PDMU vs. NG (n 6 (16.6%) vs. n 8 (6.4%); p<0.05). Admission glucose values (HR 1.020, CI 95% [1.001-1.038], p 0.029), atheromatous carotid plaque (HR 5.373, CI 95% [1.251-11.079], p 0.024), and miR 24 (HR 3.842, CI 95% [1.768-19.222], p 0.011) predicted MACE at 2 years of follow-up. CONCLUSIONS—Specific circulating miRs could be over-expressed in pre-diabetics and specifically in PDNMU vs. PDMU after endarterectomy. MiR24, hyperglycemia and atheromatous plaque could predict MACE at 2 years of follow-up.

(1) Background: Artificial Intelligence (AI) models have shown potential in various educational contexts. However, their utility in explaining complex biological phenomena, such as Intrinsically Disordered Proteins (IDPs), requires further exploration. This study empirically evaluated the performance of various Large Language Models (LLMs) in the educational domain of IDPs. (2) Methods: Four LLMs, GPT-3.5, GPT-4, GPT-4 with Browsing, and Google Bard (PaLM 2), were assessed using a set of IDP-related questions. An expert evaluated their responses across five categories: accuracy, relevance, depth of understanding, clarity, and overall quality. Descriptive statistics, ANOVA, and Tukey's honesty significant difference tests were utilized for analysis. (3) Results: The GPT-4 model consistently outperformed the others across all evaluation categories. Although GPT-4 and GPT-3.5 were not statistically significantly different in performance (p&gt;0.05), GPT-4 was preferred as the best response in 13 out of 15 instances. The AI models with browsing capabilities, GPT-4 with Browsing and Google Bard (PaLM 2) displayed lower performance metrics across the board with statistically significant differences (p&lt;0.0001). (4) Conclusion: Our findings underscore the potential of AI models, particularly LLMs such as GPT-4, in enhancing scientific education, especially in complex domains such as IDPs. Continued innovation and collaboration among AI developers, educators, and researchers are essential to fully harness the potential of AI for enriching scientific education.

Based on the Organizational Support Theory, this study examines the relationship between human resource management practices and service performance of sharing workers by demonstrating the mediation role of work engagement. We tested this theoretical model using an in-person interview questionnaire survey of 318 downwind drivers. Results showed that: (1) the main effect of human resource management practices of sharing workers on service performance was significant; (2) work engagement played a prominent mediation role between human resource management practices and service performance of sharing workers; (3) the mediation role of employee vigor between the platform incentives and the performance of employee services was significant; (4) employee dedication had an obvious and indirectly positive mediating effect between sharing workers' dimensions of human resource management practice and their service performance; (5) employee absorption on the mediation role between the various dimensions of the sharing human resources management practices (platform support, platform incentives and platform constraints) and employee service performance was significant. This study has important value for the study on human resource management practices in the context of sharing economy, and provides practical enlightenment for employee management of the sharing economy platform.

This study evaluated the impact of didactic videos and service user testimonial videos on mental illness stigma among medical students. Two randomized controlled trials were conducted in Nepal. Study 1 examined stigma reduction for depression. Study 2 examined depression and psychosis. Participants were Nepali medical students (Study 1:n=94, Study 2:¬n=213) randomized to three conditions: a didactic video based on the mental health Gap Action Programme (mhGAP), a service user video about living with mental illness, or a control condition with no videos. In Study 1, videos only addressed depression. In Study 2, videos addressed depression and psychosis. In Study 1, both didactic and service user videos reduced stigma compared to the control (F2,91=6.37, p=0.003). In Study 2 (depression and psychosis), there were no differences among the three arms (F2,210=2.07, p=0.13). When comparing Study 1 and 2, there was greater stigma reduction in the service user video arm with only depression versus service user videos with depression and psychosis (t(31)=-3.04, p=0.005). In summary, didactic and service user videos were associated with decreased stigma when content addressed only depression. However, no stigma reduction was seen when including depression and psychosis. This calls for different strategies based on types of mental illnesses. ClinicalTrials.gov identifier: NCT03231761

Prestress loss evaluation in prestressed strand is essential for prestressed structures. However, the sensors installed outside the duct can only measure the total prestress loss. The sensors attached on strand inside the duct also have several problems, such as inadequate durability in an aggressive environment, vulnerable damage at tensioning and so on. This paper proposes a new installation method for long-gauge fiber Bragg grating (LFBG) sensor to prevent accidental damage. Then the itemized prestress losses were determined in each stage of the pre-tensioning and post-tensioning according to the LFBG measurements. We verified the applicability of the LFBG sensors for prestress monitoring and the accuracy of the proposed prestress loss calculation method during pre-tensioning and post-tensioning. In the pre-tensioning case, the calculated prestress losses had less deviation from the true losses than those obtained from foil-strain gauges, and the durability of the LFBG sensors was better than foil-strain gauges, whereas in post-tensioning case, the calculated prestress losses were close to those derived from theoretical predictions. Finally, we monitored prestress variation in the strand for 90 days. The itemized prestress losses at each stages of post-tensioning were obtained by the proposed calculation method to show the prospect of the LFBG sensors in practical evaluation.

The Portuguese health system has a universal, public, general National Health Service (NHS), tending towards free healthcare access. Created in 1979, this delivery model developed from the integration and complementarity between the different response levels (primary, hospital, continuing, and palliative care). However, over these 40 years, the initially centralized system underwent a decentralization process with the creation of Regional Health Administrations in the five mainland administrative regions. Since then, the entire NHS has settled around this new organization. The most recent step started in 2018 with decentralizing primary health care skills to 190 municipalities. This paper presents the various critical issues involved in the latest gradual decentralization process in health, intending to bring services closer to the citizens, and more focused on their needs. The article identifies and discusses the implications of this experience based on the steps foreseen in the already published legal texts.

The agricultural sector, even though it has been greatly reduced and is in constant transformation, continues to be of strategic importance. Although it does not represent a quantitatively relevant employment sector, the dynamics are interesting because they reflect the structural, economic and social transformations that are affecting the sector in recent years; there is a growing need for external labour that corresponds to a massive recourse of foreigners to work. Innovative approaches are required to explore the capacity of social farming to create a sustainable and inclusive workplace for migrant. The overall methodological approach of the paper seeks to synthesize fieldwork research and qualitative interviewing to validate the Italian inclusive model. To do this, we have selected four experiences of Italian social agriculture in which migrants are included.

We aimed to assess the caffeine intake before and during pregnancy, compliance with caffeine recommendations during pregnancy (200 mg/day) and factors associated with higher intakes before and in first trimester of pregnancy. Caffeine consumption was collected in a Spanish cohort of pregnant women through a validated food questionnaire, before and in each trimester of gestation (T1, T2 and T3). 463 pregnant women were recruited and follow-up through pregnancy. Compliance with caffeine intake recommendations during pregnancy and quintiles of mg/day of caffeine before and in T1 of pregnancy were calculated. A multivariate logistic regression, comparing extreme quintiles of consumption (Q1 vs Q5) was used. Mean caffeine intake before pregnancy was 120.05 mg/day (SD 117.85), 42.76 mg/day (SD 63.90) at 12th GW, 42.00 mg/day (SD 59.76) at 24th GW and 39.34 mg/day (SD 50.9) at 32nd GW (p&lt;0.001). 86% of women complied with caffeine recommendations during pregnancy. At pregnancy (T1), being an active smoker was associated with Q5 &gt; 100.1 mg/day, aOR = 22.69; 95% CI 4.67- 110.26. igh diet quality, aOR = 0.30; 95% CI, 0.13- 0.68, and moderate physical activity level, aOR= 0.44; 95% CI, 0.19-1.00, were inversely associated with Q5 &gt; 100.1 mg/day. Pregnant women are mostly adhering to current caffeine intake guidelines. Higher caffeine intake at pregnancy is associated with other unhealthy habits during pregnancy.

This study aimed to assess prescription transfer and medicines collection through Wasfaty, an electronic prescription service recently introduced in Saudi Arabia. A link to a cross-sectional online questionnaire was sent to all students and staff at the University of Jeddah, targeting beneficiaries who received e-prescriptions at the University Medical Centre (n = 2067). The questionnaire comprised 20 items under the following sections; demographics, patient perceptions and satisfaction with the Wasfaty service, and the availability of medicines. Of the 217 questionnaires received, the majority were filled by females (n = 125, 57.6%). Most were satisfied with the initial registration process of Wasfaty (n = 183, 84.1%). However, almost one-third of the participants reported that they could not find the prescribed medicines (n = 64, 29.7%), and most of them had to look for another pharmacy to obtain their treatment (n = 138, 63.9%). Respondents voiced their displeasure owing to the lack of access to certain pharmaceuticals, including anti-hypertensives and antidiabetics. This pilot study identified some challenges relating to the use of the Wasfaty service. Further attention to these challenges is required from the service providers, and a large-scale national study is warranted.

The adoption of digital health technologies accelerated during Covid-19, with concerns over the equity of access due to digital exclusion. Using data from a text-based online mental health service for children and young people we explore the impact of the pandemic on service access and presenting concerns and whether differences were observed by sociodemographic characteristics in terms of access (gender, ethnicity and deprivation). We used interrupted time-series models to assess whether there was a change in the level and rate of service use during the Covid-19 pandemic (April 2020-April 2021) compared to pre-pandemic trends (June 2019-March 2020). Routinely collected data from 61221 service users were extracted for observation, those represented half of the service population as only those with consent to share their data were used. The majority of users identified as female (74%) and White (80%), with an age range between 13 and 20 years of age,. There was evidence of a sudden increase (13%) in service access at the start of the pandemic (RR 1.13 95% CI 1.02, 1.25), followed by a reduced rate (from 25% to 21%) of engagement during the pandemic compared to pre-pandemic trends (RR 0.97 95% CI 0.95,0.98). There was a sudden increase in almost all presenting issues apart from physical complaints. There was evidence of a step increase in the number of contacts for Black/African/Caribbean/Black British (38% increase; 95% CI: 1%-90%) and White ethnic groups (14% increase; 95% CI: 2%-27%) ), the sudden increase in service use at the start of the pandemic for the most (58% increase; 95% CI: 1%-247%) and least (47% increase; 95% CI: 6%-204%) deprived areas. During the pandemic, contact rates decreased, and referral sources change at the start. Findings on access and service activity align with other studies observing reduced service utilisation. The lack of differences in deprivation levels and ethnicity at lockdown suggests exploring equity of access to the anonymous service. The study provides unique insights into changes in digital mental health use during Covid-19 in the UK.

The article focuses on the integrated environmental accounting model called 'eValue', developed for protected areas and applied in the research programme coordinated by the Italian Ministry of the Environment and aimed at implementing an environmental accounting system for Italian Marine Protected Areas (MPAs). eValue adopts a cost-benefit analysis approach. Financial accounting based on costs and revenues is integrated with environmental accounting, which reflects environmental costs and environmental revenues, i.e. environmental benefits. The environ-mental costs assess the impacts related to human activities in the MPA expressed by calculating the carbon footprint and the environmental benefits of the marine ecosystem services calculated by applying monetary valuation techniques. The values thus estimated flow into the annual flow account, where the value produced (or consumed) by the MPA is estimated by difference. The eValue model was applied to the Porto Cesareo MPA (Italy). eValue showed that the annual benefit-cost ratio reaches a value of 3.4. Furthermore, the ratio of net benefit to public funding is 3.7, completely covering the amount of public transfers and thus summarizing the MPA overall value for money.

Call set up success rate (CSSR) in a mobile network is an important quality parameter, which directly influences overall key performance indicators (KPIs) of the network service providers. Network KPIs especially the CSSR is the fraction of the attempts to make a call that result in a successful connection to the dialled number. Nevertheless, all call attempts do not end with a connection to the dialled number. In this research, six sigma methodology is applied to improve the call quality of a legacy mobile network and subsequently to boost comprehensive CSSR of a telecom service provider. This research elucidates an empirical study of improving overall CSSR by employing DMAIC methodology consisting of five stages, e.g. Define, Measure, Analysis, Improve and Control. In addition, analytic hierarchy process (AHP) technique is used for determining the vital causes out of all the identified network parameters affecting overall CSSR. Furthermore, the identified vital parameters are being upgraded in order to improve the overall CSSR and finally the system achieved a higher CSSR.

This article shows the numerical results and the analysis of households' degree of knowledge in an intermediary city such as Huelva (Andalusia, Spain) about the sustainable use of urban water. It analyzes the needs and values regarding water and the attitudes that households maintain regarding the acceptance of reclaimed water and the use of new technologies to achieve more efficient and sustainable consumption. These results are part of the stages of needfinding and synthesis of Design Thinking methodology, adopted as a framework to improve the efficiency and sustainability of urban water among households in this city. Different statistical analysis techniques of surveys sent to households and the use of clustering are the mathematical tools used to draw conclusions and recommendations that allow the design of a web-based prototype grounded on Product Service Systems methodology, as a tool to improve the engagement of households concerning water and align citizens with the sustainability of their city. Strategies of customization and technological facilitators will be the means to improve the hydrosocial contract among households in Huelva in future later stages of the project.

Dietary components are important for the structural and functional development of the brain. Among these, docosahexaenoic acid,22:6n-3 (DHA) is critically required for the structure and development of the growing fetal brain in utero. DHA is the major n-3 long-chain fatty acid in brain gray matter representing about 15% of all fatty acids in the human frontal cortex. DHA affects neurogenesis, neurotransmitter, synaptic plasticity & transmission, and signal transduction in the brain. Studies in animals and humans show that adequate levels of DHA in neural membranes are important for cortical astrocyte maturation and vascular coupling, and helps cortical glucose uptake and metabolism. In addition, specific metabolites of DHA are bioactive molecules that protect tissues from oxidative injury and stress in the brain. A low DHA level in the brain results in behavior changes and is associated with learning problems and memory deficits. In humans, the third trimester-placental supply of maternal DHA to the growing fetus is critically important as the growing brain obligatory requires DHA during this window period. Besides, DHA is also involved in the early placentation process, essential for placental development. This underscores the critical importance of maternal DHA intake for the structural and functional development of the brain. This review describes DHA's multiple roles during gestation, lactation, and the consequences of its lower intake during pregnancy and postnatally on the children's brain development and function.

In the new period, the state has made every effort to promote the new urbanization of public sports service. Entropy method, coupled coordination model, cold hot spot analysis is used to explore the dynamic relationship between public sports services and the development of new urbanization in China from 2008 to 2017. The results show that: (1) The development of the internal subsystem of public sports service is not balanced, the sports financial investment system grows rapidly, but the development of professional sports talent team is slow. (2) The imbalance of regional development cannot be ignored, and the public sports service level shows a decreasing gradient from east to west. (3) The regional development features are different. The eastern region is dominated by the coordinated development of sports public service and urbanization, while the central region is mainly in the type of public sports service lag, while the western region has multiple complex characteristics of low-level coordination and public sports service lag. Therefore, it is proposed that the construction of modern public sports service system should be investigated in the context of the development of new urbanization. It should be promoted from the following aspects: promoting the extension of public sports service to rural areas, engendering the "citizen's right" of sports health to the migrant population, conforming to the trend of mass sports intelligence, developing green sports and revitalizing idle sports assets in cities.

Speech/music classification that facilitates optimized signal processing from classification results has been extensively adapted as an essential part of various electronics applications, such as multi-rate audio codecs, automatic speech recognition, and multimedia document indexing. In this paper, a new technique to improve the robustness of speech/music classifier for 3GPP enhanced voice service (EVS) using long short-term memory (LSTM) is proposed. For effective speech/music classification, feature vectors implemented with the LSTM are chosen from the features of the EVS. Experiments show that LSTM-based speech/music classification produces better results than conventional EVS under a variety of conditions and types of speech/music data.

Lung cancer is the leading cause of global cancer-related mortality resulting in ~1.8 million deaths annually. Systemic, molecular targeted, and immune therapies have provided significant improvements of survival outcomes for patients. However, drug resistance usually arises and there is an urgent need for novel therapy screening and personalized medicine. 3D patient-derived organoid (PDO) models have emerged as a more effective and efficient alternative for ex vivo drug screening than 2D cell culture and patient-derived xenograft (PDX) models. In this review, we performed an extensive search of lung cancer PDO-based ex vivo drug screening studies. Lung cancer PDOs were successfully established from fresh or biobanked sections/biopsy of lung tumors, PDXs, and pleural affusion. PDOs were subject to ex vivo drug screening with chemotherapy, targeted therapy and immune therapy agents. PDOs mainly recapitulated the genomic alterations, transcriptomic landscape and drug sensitivity of primary tumors. Although sample sizes of the previous studies were limited and some technical challenges remained, PDOs showed promise to screen novel therapy drugs. With the technical advance of high throughput, tumor-on-chip, combined microenvironment, and air-liquid interface (ALI), the drug screening using PDOs would serve better for precision care of lung cancer patients.

Study aimed to evaluate the impact of integrating family planning with maternal, newborn, and child health (FP-MNCH) on uptake of modern contraceptive methods and related health outcomes in two districts of the province of Sindh, Pakistan. Impact of intervention was evaluated using a quasi-experimental control before-after study design. Intervention included capacity building of healthcare providers and outreach workers, ensuring sustained supplies of family planning commodities, data-driven decision-making, and community engagement activities. Data was collected through household surveys at baseline (December2020) and endline (December 2022). The sample size was estimated as 880 married women of reproductive age (MWRA) in each district. The Difference and Difference(DiD) analytical method was used to estimate the impact of intervention adjusted for potential confounding factors. There was statistically significant increase of 11.3% in the current use of MCM in the intervention group compared to the control group (p value <0.001), with increases observed in the uptake of injection , implants, and condoms. Additionally, there was an increase in the proportion of women who had ANC visits (DiD 10.5% p value 0.003), FP counselling during ANC (DiD 15.6% p value < 0.001), LHW visits during pregnancy (DiD 15.1% p value 0.021), PNC check-ups for mother (DiD 25.2% p value <0.001), LHW visits after delivery (DiD 20.4% p value <0.001), and LHW advised for family planning at PNC visit n (DiD 14.5% p value 0.030). This study provides strong evidence for the scaling-up of integrated interventions through existing health care platforms utilizing human resources deployed by the government. This FP-MNCH model has the potential to be adopted in other provinces and at federally administered areas for both health and population planning. This model should be considered for replication in other districts of Sindh to accelerate current level of integration already existing.

The rise in prevalence of obesity in women of reproductive age in both developed and developing countries might propagate intergenerational cycles of detrimental effects on metabolic health, contributing to substantial economic burden on society. Placental lipid metabolism might be disrupted by maternal obesity, which possibly affects the life-long health of the offspring. Here, we investigated placental lipid metabolism and handling from women with pre-gestational obesity as a sole pregnancy complication and compared to placental responses of lean women. Open profile and targeted lipidomics were used to assess placental lipids and oxidized products of docosahexahenoic acid (DHA), neuroprostanes, and arachidonic acid (AA), isoprostanes. Placental fatty acid transporters FABP1, FABP3 and endothelial lipase protein were measured. Despite no signs of overall alterations in lipid content, increased contents of DHA, AA, DHA-derived neuroprostanes and AA-derived isoprostanes and decreased content of FABP1 protein were found in placentas from obese women. Multivariate analyses suggested that these oxidised fatty acids are associated with maternal and placental inflammation and also with birth weight. These results might shed light on the molecular mechanisms associated with altered fatty acid metabolism and lipid handling in maternal pre-gestational obesity, placing these oxidized fatty acids as novel mediators of placental function.

The zebrafish is now an important model organism for cancer biology studies and provides some unique and complementary opportunities in comparison to the mammalian equivalent. The translucency of zebrafish has allowed in vivo live imaging studies of tumour initiation and progression at the cellular level thus providing novel insights into our understanding of cancer. Here we summarise and discuss available transgenic zebrafish tumour models and what we have gleaned from them with respect to cancer inflammation. In particular, we focus on the host inflammatory response toward transformed cells during the pre-neoplastic stage of tumour development. We discuss features of tumour associated macrophages and neutrophils in mammalian models and present evidence which supports the idea that these inflammatory cells promote early stage tumour development and progression. Direct live imaging of tumour initiation in zebrafish models has shown that the intrinsic inflammation induced by pre-neoplastic cells is tumour promoting. Signals mediating leukocyte recruitment to pre-neoplastic cells in zebrafish correspond to signals mediating leukocyte recruitment in mammalian tumours. The activation state of macrophages and neutrophils recruited to pre-neoplastic cells appears to be heterogenous, as seen in mammalian models, which provides an opportunity to study the plasticity of innate immune cells during tumour initiation. Although several potential mechanisms are described that might mediate the trophic function of innate immune cells during tumour initiation in zebrafish, there are several unknowns that are yet to be resolved. Rapid advancement of genetic tools and imaging technologies for zebrafish will facilitate research into the mechanisms that modulate leukocyte function during tumour initiation and identify targets for cancer prevention.

A divergent selection experiment on environmental sensitivity was performed in rabbits. The aim of this study was to estimate the correlated response in kits’ weight and its survival, and weight distance from birth to weaning. Weight distance was calculated as the absolute values of the differences between the individual value and the mean value of its litter. Also, relationship between probability of survival at 4 d of age and weight at birth was studied. Environmental sensitivity was measured as litter size variability. A total of 2484 kits from 127 does of the low line (selected for reducing litter size variability) and 1916 kits of 114 does of the high line (selected for increasing litter size variability) of the 12th generation were weighed. Bayesian methodology was used to estimate the correlated response to selection, and LOGISTIC procedure of SAS was used to estimate the relationship between weight and probability of survival. Both lines showed similar individual weight at birth and at weaning, and similar survival at birth and at 4 d of age. Survival at weaning was higher in the low line than in the high line (0.67 and 0.62; P= 0.93). Weight distance was higher at birth but lower at weaning in the low line (47.8 g and 54.1 g; P=0.98). Kit’s weight at birth affected its survival. In conclusion, selection for environmental sensitivity showed correlated response in kits survival and in homogeneity of litter weight at weaning.

The popularity of cloud computing is growing owing to its large data storage capacity and high computation power. It provides online, on-demand, scalable application solution, removes hardware and software barriers for non-specialist, rapidly integrates and deploys desired and necessary facilities, supports quick upgrading and addition of features. Users get benefitted with the selection of the appropriate cloud computing platform for their projects. Here, our paper provides a comprehensive overview of the services provided to the users by the most common cloud computing service providers. This paper could be used as a reference while selecting the best service provider based on the requirements of the projects.

We transformed the existing learning program Language Shower, which is used in some Norwegian day-care centers in the Grorud district of Oslo municipality, into a digital solution using an app for smartphone or tablet with the option for further enhancement of presentation by a NAO robot. The solution was tested in several iterations and multiple day-care centers over several weeks. Measurements of the children’s progress across learning sessions indicate a positive impact of the program using a robot as compared to the program without robot. In-situ observations and interviews with day care center staff confirmed the solution’s many advantages, but also revealed some important areas for improvement. In particular, the speech recognition needs to be more flexible and robust, and special measures have to be in place to handle children speaking simultaneously.

Abstract: In network science and big data, the concept of finding meaningful infrastructures in networks has emerged as a method of finding groups of entities with similar properties within very complex systems. The whole concept is generally based on finding subnetworks which have more properties (links) amongst nodes belonging to the same cluster than nodes in other groups (A concept presented by Girvan and Newman, 2002). Today meaningful infrastructure identification is applied in all types of networks from computer networks, to social networks to biological networks. In this article we will look at how meaningful infrastructure identification is applied in biological networks. This concept is important in biological networks as it helps scientist discover patterns in proteins or drugs which helps in solving many medical mysteries. This article will encompass the different algorithms that are used for meaningful infrastructure identification in biological networks. These include Genetic Algorithm, Differential Evolution, Water Cycle Algorithm (WCA), Walktrap Algorithm, Connect Intensity Iteration Algorithm (CIIA), Firefly algorithms and Overlapping Multiple Label Propagation Algorithm. These al-gorithms are compared with using performance measurement parameters such as the Mod-ularity, Normalized Mutual Information, Functional Enrichment, Recall and Precision, Re-dundancy, Purity and Surprise, which we will also discuss here.

In developing countries today, population growth and the penetration of higher standard of living appliances in homes has resulted in a rapidly increasing residential load. In South Africa, the recent rolling blackouts and electricity price increase only highlighted this reality calling for sustainable measures to reduce the overall consumption and peak load. The dawn of the smart grid concept, embedded systems and ICTs have paved the way to novel HEMS design. In this regard, the Internet of Things (IoT), an enabler for smart and efficient energy management systems is seeing increasing attention for optimizing HEMS design and mitigate its deployment cost constraints. In this work, we propose an IoT platform for residential energy management applications focusing on interoperability, low-cost, technology availability and scalability. We focus on the backend complexities of IoT Home Area Networks (HAN) using the OCF IoTivity-Lite middleware. To augment the quality, servicing and reduce cost and complexities, this work leverages open-source Cloud technologies from Back4App as BaaS to provide consumer and Utilities with a data communication platform within an experimental study illustrating time and space agnostic “mind-changing” energy feedback, Demand Response Management (DRM) and appliance operation control via a HEM App via an Android smartphone.

Recent global trends related to the increasing use of e-commerce are becoming a challenge for courier transport especially in the last-mile process of delivering products to the final retail recipient. One of the delivery methods is the personal collection of the parcel in an automated post box, available 24/7 for the customer. This research aims to define the most important attributes of the courier services quality, including the delivery of parcels through automated sending and receiving parcel lockers, leveraging advanced technologies, data, and connectivity to enhance the quality of life, sustainability, and efficiency for city residents. The research was based on a preliminary selection of the most important features of parcel lockers’ service quality, which were extracted from the analysis of scientific literature and previous research. The analysis was carried out by conducting a survey among city parcel locker users that provided data coded according to the dimensions of the Kano model. This allowed to conclude that the location of parcel stations, ensuring improvements for the disabled, adjusting the size of the parcel to the size of the box, proper placement of the parcel in the box and a properly functioning dedicated application are the most important features in the process of automatic delivery of parcels to recipients in urban areas. This paper enriches the literature on customer service quality of self-service technologies for last-mile delivery with the use of automated parcel lockers.

Antimicrobial resistance (AMR) remains a challenge in Kenya, while the extent remains unknown. To assess the knowledge, cultural beliefs, practices, and behavioral patterns among multisectoral stakeholders in Kenya. The cross-sectional survey was conducted in August 2021 among farmers, animal health service providers and AMR researchers. Regional digital data collection tool developed by FAO was shared and responses obtained through mail, phone calls and direct interviews. Descriptive and inferential analysis were conducted. Antimicrobials were mostly sourced from agro-veterinary shops and from veterinary professionals. Farmers, often implement self-treatment and reported overuse, unnecessary use, and sometimes fail to complete the dosage in livestock. More farmers reported to have heard about antibiotics as compared to antimicrobials, mostly from friends and radio program, however only 9.2% could correctly differentiate the two. Animal Health Service Providers (AHSP) were the source of information to farmers regarding AMR. AHSPs mainly relied on suppliers and distributors for information about antibiotics. Both farmers and AHSPs treated viral infections with antibiotics. One Health Partners (OHPs) had higher knowledge and largely favorable attitudes towards AMR. Up to 72.7% of OHPs from training institutions had AMR included in training curriculum however, they were optimistic livestock farmers and government were less concerned about AMR. Gaps in knowledge and practice on Antimicrobial Stewardship (AMS) were observed in all categories of stakeholders. Given the documented knowledge-practice gap, innovative solutions are needed for both AHSPs and farmers to promote good antimicrobial stewardship practices and to mitigate burdens of AMR. Outcomes of this research should deepen the understanding of critical information and trigger behavioral change in usage and stewardship of antimicrobials.

The estimation of ecological service system value of water resources in Tarim river basin is of great significance for resource allocation management and ecological protection. However, there is still no unified and complete evaluation method for ecological service system value of inland river in China. Based on the perspective of the whole value chain, the study classifies its ecological service functions, and divides 11 sub-categories into 4 categories (supply, regulation, culture and support) as evaluation indicators to carry out quantitative evaluation. The results showed that the total value of ecological service system in Tarim river basin in 2018 was 4156.5247×108 Yuan, and the value of regulating function, cultural function, supporting function and supply function were successively from high to low, which were as follows: 2565.6825×108 Yuan, 1009.5471×108 Yuan, 884.0770×108 Yuan, 20.3350×108 Yuan, among which the value of regulation function is dominant.

Because of an often complicated and difficult-to-access care system, help-seeking for people with suspected dementia can be stressful. Difficulty in help-seeking may contribute to carer burden, in addition to other known stressors in dementia care. This study examined the relationship between perceived help-seeking difficulty and carer burden, and the barriers contributing to perceived difficulty. We interviewed 110 carers accessing a community-based dementia assessment service for suspected dementia of a family member for their perceived difficulty, delays, and barriers in help-seeking, and carers burden in terms of role strain, self-criticism, and negative emotions. Linear regression models showed that perceived help-seeking difficulty is associated with carer self-criticism, while carer role strain and negative emotions are associated with symptom severity of the person with dementia but not help-seeking difficulty. Inadequate knowledge about symptoms, service accessibility, and affordability together explained more than half of the variance in perceived help-seeking difficulty (Nagelkerke R2 = .56). Public awareness about symptoms, support in navigating service, and financial support may reduce perceived difficulty in help-seeking, which in turn may reduce carer self-criticism during the early course of illness.

In 1937,German mathematician L.Collatz proposed a conjeture:for any positive integer,if it is even,divide it by 2;if it is odd,multiply it by 3 and 1 to get an even number;keep going on and on, the final result is 1.This paper gives a sequence classification of odd numbers,and gives 1-1 mapping of odd numbers and odd number sequences,and uses these results to give a proof of this conjecture.

We present a normative methodology, for value-pricing B2B services, using a Nash Equilibrium mechanism. Value is fundamental to any service, yet it has defied a definition. The literature is conspicuously silent on how to define value, but abounds in richly descriptive characterizations. To overcome this deficit, we focus on the financial economics of service-value. We formulate an axiomatic definition and a differential equation that embodies the idea of service-value. We specify a set of value axioms and multidisciplinary postulates that coherently form our service-value constructs. Value-pricing is challenging. It is natural that providers desire a high price and customers want a low price. Realistically, both will agree on a win-win price. To uncover this price, we specify an algorithm to reveal the Nash Equilibrium. Once agreed, it validates providers’ and customers’ commitments, and payment obligations. Service value is cocreated by both provider and customer. For a reciprocal process, its treatment is remarkably asymmetric favoring the customer. We argue that one-sided descriptions of value-in-use and value-proposition are limiting mental models. We propose the additional ideas of value-from-use and value-supposition to strengthen the conceptual symmetry of cocreation. Our work reveals a critical gap in service science, metrology. Metrology, the science of measurements, is absent from service-science. Service-value is silent on the questions of quantities, units, scales, measurement principles and instruments. We argue for a call to action for Service Metrology. We sketch a roadmap of actionable suggestions to get started.

Background: The COVID-19 pandemic has sped up digital health transformation across the health sectors to enable innovative health service delivery. Such transformation relies on competent managers with the capacity to lead and manage. However, the health system has not adopted a holistic approach in addressing the health management workforce development needs, with many hurdles to overcome. The objectives of this paper are to present the findings of a three-step approach in understanding the current hurdles in developing a health management workforce that can enable and maximise the benefits of digital health transformation, and to explore ways of overcoming such hurdles. Methods: A three-step, systematic approach was undertaken, including an Australian digital health policy documentary analysis, an Australian health service management postgraduate program analysis, and a scoping review of international literatures. Results: The main findings will guide the formulation of strategies in developing a digitally enabled health management workforce in the digital health era. Conclusions: With the ever-changing landscape of digital health, being able to lead and manage in times of system transformation requires a holistic approach to develop the necessary health management workforce capabilities and system-wide capacity. The evidence would support that this can be achieved with the required system, policy, educational and professional organizational enablers, which drive a digital health focused approach across all the healthcare sectors, in a coordinated and contextual manner.

This work focused on proposing a plan for improvement and control of the customer service process in a customer service center, based on a waiting line analysis where it describes all the elements that interact in the system and a statistical analysis of processes to define the state in which it operates. Subsequently, the simulation of processes is applied to represent the system studied, and with it, to be able to evaluate different strategies for improvement and increase in productivity. The following strategies were evaluated: correction of the instability of customer service processes, establishment of new specification limits according to the promise of value to be fulfilled to customers, human resource management, administrative technical support. Finally, with the results obtained from the simulation of the system, the improvement and productivity increase plan is planned according to the DMAMC (Define, Measure, Analyze, Improve, Control, or DMAIC) continuous improvement cycle established in six sigma

A large number of smart devices (things) are being deployed with the swift development of Inter- net of Things (IOT). These devices, owned by different organizations, have a wide variety of services to offer over the web. During a natural disaster or emergency (i.e., a situation), for example, relevant IOT services can be found and put to use. However, appropriate service matching methods are required to find the relevant services. Organizations that manage situation responses and organizations that provide IOT services are likely to be independent of each other, and therefore it is difficult for them to adopt a common ontological model to facilitate the service matching. Moreover, there exists a large conceptual gap between the domain of discourse for situations and the domain of discourse for services, which cannot be adequately bridged by existing techniques. In this paper, we address these issues and propose a new method, WikiServe, to identify IOT services that are functionally relevant to a given situation. Using concepts (terms) from situation and service descriptions, WikiServe employs Wikipedia as a knowledge source to bridge the conceptual gap between situation and service descriptions and match functionally relevant IOT services for a situation. It uses situation terms to retrieve situation related articles from Wikipedia. Then it creates a ranked list of services for the situation using the weighted occurrences of service terms in weighted situation articles. WikiServe performs better than a commonly used baseline method in terms of Precision, Recall and F measure for service matching.

The introduction of tenofovir-derived prodrugs has revolutionised the prevention and management of HIV, which has coincided with 23% reduction in new HIV incidences globally. To date, there are two formulations of tenofovir-derived nucleoside reverse transcriptase inhibitor (NRTI): tenofovir disoproxil fumarate/emtricitabine (TDF/FTC) and tenofovir alafenamide fumarate/emtricitabine (TAF/FTC). Although these prodrugs have shown favourable safety profile, their effects on cardiovascular health are differ from one another: TDF/FTC exhibits potential lipid-lowering effect, TAF/FTC demonstrates potential lipid-inducing effect, which is a major risk factor for cardiovascular diseases. However, this issue has not been previously elucidated, especially among the marginalised populations [lesbian, gay, bisexual and transgender (LGBT) and men who have sex with men (MSM)] who are likely be the main users of these prodrugs. This is of clinically significance as the cardiovascular health in these populations is often overlooked, in addition to a lack of appropriate cardiovascular risk prediction algorithm. Therefore, this review aims to (1) highlight the cardiovascular risks of tenofovir-derived prodrugs in the marginalized populations, and also to (2) establish the importance of having a cardiovascular risk prediction model that is specific to this particular populations so that their health management could be more comprehensive.

The Bologna Process and the European Higher Education area require the application of new active methodologies in the classroom that place the student at the center of his or her learning process. In the present work we analyze the application of a Service-Learning methodology in the context of a Final Degree Dissertation (FDD) in the degree in Environmental Sciences at the University of Extremadura (Spain). The project deals with an isolated Kichwa community in Ecuador and involves the development of alternative science education materials for the capacitation of in-service science teachers. This paper evaluates how an FDD carried out according to self-learning (SL) principles can help in the acquisition of so-called soft skills and how these can be focused in the promotion of the Sustainable Development Goal (SDG) knowledge and achievement. To this end, a qualitative study of the experience and a deep evaluation, followed by a final reflection, were carried out. According to the preliminary results, we can conclude that Higher Education should include SDGs in its teaching praxis and could do this successfully using the SL methodology.

This work presents updated reconstructions of watershed runoff to San Francisco Estuary from tree-ring data to AD 903, coupled with models relating runoff to freshwater flow to the estuary and salinity intrusion. We characterize pre-development freshwater flow and salinity conditions in the estuary over the past millennium and compare this characterization with contemporary conditions to better understand the magnitude and seasonality of changes over this time. This work shows that the instrumented flow record spans the range of runoff patterns over the past millennium (averaged over five, ten, twenty and one hundred years), and thus serves as a reasonable basis for planning-level evaluations of historical hydrologic conditions in the estuary. Over annual timescales we show that, although median freshwater flow to the estuary has not changed significantly, it has been more variable over the past century compared to pre-development flow conditions. We further show that the contemporary period is generally associated with greater spring salinity intrusion and lesser summer-fall salinity intrusion relative to the pre-development period. Thus, salinity intrusion in summer and fall months was a common occurrence under pre-development conditions and has been moderated in the contemporary period due to the operations of upstream reservoirs, which were designed to hold winter and spring runoff for release in summer and fall. This work also confirms a dramatic decadal-scale hydrologic shift in the watershed from very wet to very dry conditions during the late 19th and early 20th centuries; while not unprecedented, these shifts have been seen only a few times in the past millennium. This shift resulted in an increase in salinity intrusion in the first three decades of the 20th century, as documented through early records. Population growth and extensive watershed modification during this period exacerbated this underlying hydrologic shift. Putting this shift in the context of other anthropogenic drivers is important in understanding the historical response of the estuary and in setting salinity targets for estuarine restoration. By characterizing the long-term behavior of San Francisco Estuary, this work supports decision-making in the State of California related to flow and salinity management for restoration of the estuarine ecosystem.

Rare diseases are characterized by a wide diversity of signs and symptoms and vary not only from disease to disease, but also from person to person, and living with a disease leads patients to peculiar experiences and treatments, without limits of time and space, as they extend to various environments and relationships of their lives. The objective of this study is the theoretical interaction between Value Co-creation (VC) and the Stakeholder Theory (ST) with the Shared Decision Making (SDM) health care theory. It is configured as a multiparadigmatic proposal by enabling the analysis of multiple perspectives of different stakeholders in health care. Thus, Co-created Decision Making (CDM) emerges in a logic dominated by service, with emphasis on intangible aspects and the interactivity of the relationships. It goes beyond the clinical office and the doctor-patient relationships, as studied in SDM, extending to all environments and interactions that add value to the patient's treatment. It was concluded that the essence of this new theory proposed here is neither in patient-centered care nor in patient self-care, but in co-created relationships with and between stakeholders in both directions, including non-health care environments that are important to the patient, such as relationships with friends, family, other patients with the same disease, social media, public policies, and the practice of pleasurable activities.

This study was aimed at investigating the protective effects of glass ionomer cement (GIC) and surface pre-reacted glass ionomer (S-PRG) fillers used as dental restorative materials on demineralization of bovine enamel. GlasIonomer FX ULTRA (FXU), Fuji IX GP Extra (FIXE), CAREDYNE RESTORE (CDR) were used as GICs. PRG Barrier Coat (BC) was used as the S-PRG filler. They were incubated in a lactic acid solution (pH = 4.0) for 6 d at a temperature of 37 °C. The mineral was etched from the enamel surface, and a large number of Ca and P ions were detected in solution. The Al, F, Na, Sr, and Sr ions were released in GICs and S-RPG fillers. The Zn ion was released only in CDR and the B ion was released only in BC. The presence of apparent enamel prism peripheries was observed after 6 d of treatment for the group containing only enamel blocks. pH values for the FXU, FIXE, CDR, BC, and enamel block groups after 6 d were 6.5, 6.6, 6.7, 5.9, and 5.1, respectively. Therefore, the observed pH neutralization effect suppressed progression of caries due to the release of several ions from the restoratives.

This study explores the impact of the ‘pre-intervention effects’ of a community-based interventions. This refers to participatory research processes and parallel publicity in the media on changes in alcohol use and relevant mechanisms (rules and norms about alcohol, accessibility of alcohol in a formal setting) among adolescents before any intervention is implemented. In a quasi-experimental study, adolescent data were collected twice by means of self-report among adolescents living in two municipalities (control and experimental condition). Regression analysis showed pre-intervention main effects on adolescents’ perceived accessibility of alcohol in a formal setting. Moreover, among adolescents aged 15 years and older, the normative decline in strictness of rules and norms was less steep in the experimental condition compared to the control condition. Also, adolescents aged 14 years and younger in the experimental condition reported more weekly drinking compared to their peers in the control condition. No differential effects across gender were found. To conclude, applying a co-creational approach in the development of an intervention, not only contributes to more effective interventions in the end, but involvement of and discussions in the community at the start of intervention planning are contributing to changes in targeted factors. This implies that public discussions about the development of intervention strategies should be considered as an essential feature of co-creation in community-based interventions.

Kaposi’s sarcoma-associated herpesvirus (KSHV) is the etiologic agent of Kaposi’s sarcoma, primary effusion lymphoma (PEL) and multicentric Castleman’s disease. During KSHV lytic infection, lytic-related genes, categorized as immediate-early, early, and late genes, are expressed in a temporal manner. The transcription of late genes requires the virus-specific pre-initiation complex (vPIC), which consists of viral transcription factors. However, the characterization of the protein-protein interactions of the vPIC factors has not been completely elucidated. KSHV ORF18 is one of the vPIC factors, and its interaction with other viral factors has not been sufficiently revealed. Here, we analyzed the interaction between ORF18 and another vPIC factor, ORF30, in living cells using the bimolecular fluorescence complementation (BiFC) assay. We identified four amino-acid residues (Leu29, Gln36, His41 and Trp170) on ORF18 that were responsible for its interaction with ORF30. The artificial intelligence (AI) system AlphaFold2 predicted that identified four residues are exposed to the surface of ORF18 and located in proximity to each other in the surface of ORF18. Thus, AI-predicted model supports the importance of four residues for binding of ORF18 to ORF30. Our results indicated that wet experiments in combination with AI may enhance the structural characterization of vPIC protein-protein interactions.

With increasing availability of alternative mobility options for city transportation system, it is necessary to better understand how emerging mobility are impacting the travel demand and consumer-social surplus. However, few study has been conducted to evaluate the social welfare effects of the range of vacant trip in mobility oriented development(MOD) mode. This paper identified the vacant trip and loading rate evaluation model under mobility oriented development mode. recommended solutions to enhance the effective operation of the different mobility services under numerical illustrations, which can offer some beneficial guidance and theoretic basis to the efficiency of MOD in planning and management aspects.

In the evolving landscape of cybersecurity threats, the Permanent Denial of Service (PDoS) attacks have emerged as a particularly damaging form of cyber aggression. Unlike the more well-known Denial of Service (DoS) attacks, which disrupt services temporarily, PDoS attacks aim to inflict irreversible damage to systems, often resulting in significant system overhauls and requiring hardware replacement. To enable the development of effective security measures, but also to address the knowledge gaps, this paper offers an in-depth exploration of PDoS attacks, emphasizing their distinguishing characteristics, underlying mechanisms, and potential further development. Through a comprehensive case study, the research highlights diverse tactics and strategies employed by attackers, from targeting IoT devices to manipulating boot processes and exploiting firmware vulnerabilities. A novel classification of PDoS attack vectors is proposed, that also explains the ways in which the systems can be compromised. The findings confirm the pressing need for adaptive and robust defense mechanisms to mitigate the threats posed by PDoS attacks in our interconnected digital world.

Voltage Stability & Control, is very crucial compared to other Power System (PS) Quality and Stability issues. Long-Vertical-Power-Flows in Conventional Grids, causes voltage drops which in turn causes huge power losses, especially in the Medium Voltage (MV) and Low Voltage (LV) Distribution Networks. Such technical losses in abysmally-planned weak distribution networks, lead to substantial loss of revenues to the utility grid. Apart from classic Voltage Regulation (VR) techniques, with the rise of Distributed Generation (DG) based on Renewable Energy Sources (RES), Horizontal-Power-Flows can be introduced in the network, through various Smart Grid techniques. Coupling such sources, near load centers shall mitigate long flows from expensive conventional sources at times of huge demands, improving feeders’ Voltage Profile. This Ancillary Service of Voltage Support from DG RESs shall thereby alleviate revenue losses caused by long-power-flows in weak distribution grids. For a developing country like Pakistan, loss of revenue from an already expensive utility gives huge blow to the economy. So, a similar technique for voltage support is proposed for an 11-kV feeder, which faces similar problem, and the results are remarkable. The technique is implemented using OpenDSS Tool by modelling 3MWp PV Penetration along with some future storage.

Body Expression (BE) has been defined in the past decades as a discipline within Physical Education (PE) with very particular characteristics and a strong emotional component. In this study, a programme of this discipline was applied to university Physical Activity and Sports Sciences (PASS) students from six consecutive academic years: three prior to and three during the pandemic. A pre-post design was used to determine how the BE programme affected the university students' self-concept (SC). To do so, a questionnaire with a multidimensional approach to this construct was administered, whose dimensions were closely related to the BE programme's characteristics. The results revealed significant improvements in the final SC, compared to the initial SC. Men reported lower SC values than women before the programme implementation, but higher at the end. Therefore, the change was larger in men, so the programme may have had an equalising effect between groups. It was also verified that the pandemic had particularly affected women.

How, if at all, consciousness can be part of the physical universe remains a baffling problem. This article outlines a new, developing philosophical theory of how it could do so, and offers a preliminary mathematical formulation of a physical grounding for key aspects of the theory. Because the philosophical side has radical elements, so does the physical-theory side. The philosophical side is radical, first, in proposing that the productivity or dynamism in the universe that many believe to be responsible for its systematic regularities is actually itself a physical constituent of the universe, along with more familiar entities. Indeed, it proposes that instances of dynamism can themselves take part in physical interactions with other entities, this interaction then being “meta-dynamism” (a type of meta-causation). Secondly, the theory is radical, and unique, in arguing that consciousness is necessarily partly constituted of meta-dynamic auto-sensitivity, in other words it must react via meta-dynamism to its own dynamism, and also in conjecturing that some specific form of this sensitivity is sufficient for and indeed constitutive of consciousness. The article proposes a way for physical laws to be modified to accommodate meta-dynamism, via the radical step of including elements that explicitly refer to dynamism itself. Additionally, laws become, explicitly, temporally non-local in referring directly to quantity values holding at times prior to a given instant of application of the law. The approach therefore implicitly brings in considerations about what information determines states. Because of the temporal non-locality, and also because of the deep connections between dynamism and time-flow, the approach also implicitly connects to the topic of entropy insofar as this is related to time.

Socio-ecologic, socio-economic, and socio-technical transitions are opportunities that require fundamental changes in the system. These will encounter matters associated with security, service adoption by end-users, infrastructure and availability. The purpose of this study is to examine and overcome the risks to take advantage of opportunities through the novel Risky-Opportunity Analysis Method (ROAM). A novel quantitative method is designed to determine when, after making some changes, the risks become acceptable so that the opportunity does not deviate from the objectives. The approach provided a quantitative evaluation of the possible changes in parallel with digitization, towards providing a green Service Supply Chain (SSC). The result of ROAM shows that the most cost-effective change to increase the resilience of the system is a solution (SMS) which is different from that identified by a TOPSIS multi-criteria method. Real-word decisions in change management should tackle the complexity of systems and uncertainty of events during and after transition through a careful analysis of the alternatives. A case-study was carried out to evaluate the alternatives of an ancillary service in the Payment Service Providers (PSP). The comparison of the ROAM results with the traditional TOPSIS of the case-study unveils the priority of the ROAM in practice when the alternatives are Risky-Opportunities. The existing risk assessment tools do not take advantage of risky opportunities. To this aim, the current article introduces the term Risky-Opportunity, and two indexes Stress and Strain of the alternatives that are designed to be employed in the new quantitative ROAM approach.

Internet of Things (IoT) is a massive network of tiny devices connected internally and to the in-ternet. It is uniquely identified in the network (i.e. dedicated IP) and can share the information with other devices. However, the low power and low resources that distinguish IoT devices render them unsecure and targeted by different kinds of attacks since IoT devices cannot toler-ate heavy security models. Also, due to the heavy nature of famous protocols such as HyperText Transport Protocol (HTTP), it is costly to be used with IoT devices, and alternatively, different lightweight protocols are implemented to fit IoT devices. One of the prevailing protocols used over IoT networks is the Constrained Application Protocol (CoAP). Therefore, CoAP is popular, and that makes it targeted by different types of attacks. One of the major attacks that target CoAP is distributed denial of service (DDoS) attacks. DDoS aims to overwhelm the resources of the target and make them unavailable to legitimate users. As a result, different kinds of meth-ods were used to secure CoAP against DDoS attacks such as Datagram Transport Layer Secu-rity (DTLS) and Lightweight and Secure Protocol for Wireless Sensor Networks (LSPWSN). However, the existing models suffer from two issues: DTLS is not designed for constrained devices and is considered a heavy protocol. Besides, LSPWSN is working over the network layer, not in the application layer that CoAP works on. In this paper, we build a machine learn-ing model that can detect the DDoS attacks against CoAP with an accuracy of 98%. The CIDAD dataset is extended from ~11000 to 100,000 samples using GANs because it has fewer samples of malware (less than 0.2% of the total dataset). Our model outperforms the existing models that target securing CoAP in the application layer and obtains 93% of accuracy.

This study examined the status of Education for Sustainable Development (ESD) practices and the understanding of Sustainable Development (SD) among Saudi kindergarten teachers in a specific governorate. Two hundred twenty-seven kindergarten teachers participated, and data was collected through a questionnaire. The results indicated that most kindergarten teachers (89.9%) were unaware of SD. The overall status of ESD practices among the participating teachers was weak, with an average score of 2.60 out of 4. Among the different dimensions, values (2.74), competencies (2.69), and practice (2.65) obtained relatively higher scores, while the content dimension (2.49) received the lowest score. Significant differences were found in the mean scores of ESD practices based on teachers’ qualifications and the type of school. However, no differences were observed based on experience. The lack of awareness regarding SD emerged as the primary barrier to implementing ESD in kindergarten institutions. Expanding teacher training was identified as the most crucial step in promoting ESD in kindergartens. The findings highlight the importance of raising awareness among Saudi kindergarten teachers about SD, providing professional development opportunities to enhance ESD implementation in classrooms, and creating teaching materials aligned with ESD principles.

Quality of Service (QoS) metrics deal with network quantities, e.g. latency and loss, whereas Quality of Experience (QoE) provides a proxy metric for end-user experience. Many papers in the literature have proposed mappings between various QoS metrics and QoE. This paper goes further in providing analysis for QoE versus bandwidth cost. We measure QoE using the widely accepted Mean Opinion Score (MOS) rating. Our results naturally show that increasing bandwidth increases MOS. However, we extend this understanding by providing analysis for internet access scenarios, using TCP, and varying the number of TCP sources multiplexed together. For these target scenarios our analysis indicates what MOS increase you get by further expenditure on bandwidth. We anticipate that this will be of considerable value to commercial organizations responsible for bandwidth purchase and allocation.