A crucial role is played by personal biomedical data when it comes to maintaining proficient access to health records by patients as well as health professionals. However, it is difficult to get a unified view pertaining to health data that have been scattered across various health center/hospital sections. To be specific, health records are distributed across many places and cannot be found integrated easily. In recent years, blockchain is regarded as a promising explanation that helps to achieve individual biomedical information sharing in a secured way along with privacy preservation, because of its benefit of immutability. This research work put forwards a blockchain-based managing scheme that helps to establish interpretation improvements pertaining to electronic biomedical systems. In this scheme, two blockchain were employed to construct the base of it, where the second blockchain algorithm is used to generate a secure sequence for the hash key that generated in first blockchain algorithm. The adaptively feature enable the algorithm to use multiple data types and combine between various biomedical images and text records as well. All the data, including keywords, digital records as well as the identity of patients are private key encrypted along with keyword searching capability so as to maintain data privacy preservation, access control and protected search. The obtained results which show the low latency (less than 750 ms) at 400 requests / second indicate the ability to use it within several health care units such as hospitals and clinics.

This research explores and analyzes the challenges and opportunities due to globalization's impact on sustainable strategic management. The research uses a mixed-method design, combining primary and secondary data collection methods. Secondary data is sourced from various credible publications and analyzed through an extensive literature review. A case study approach is adopted, involving semi-structured interviews with six experienced managers from Tazweed Venture Capital in Jordan. The study employs a qualitative, descriptive, and analytical approach to develop a conceptual framework by exploring managers' experiences and perspectives on Globalization and its impact on Sustainable Strategic Management. The findings identify challenges of environmental degradation, economic inequality, transportation and logistics pressures, and compliance challenges for sustainability. While implementing sustainable practices incurs upfront costs, accessing renewable energy markets and financial support presents opportunities. Tazweed successfully implements sustainable strategic management, emphasizing stakeholder engagement and collaboration across departments. This research offers valuable insights and guidance for companies navigating globalization's impact on sustainability strategic management.

Significant amount of oil remains in the reservoir after primary and secondary operations and to recover the remaining oil, enhanced oil recovery (EOR) can be applied as one of the feasible options remaining nowadays. In this study new nano polymeric materials have been prepared from purple yam and cassava starches. The yield of purple yam nanoparticles (PYNPs) was 85% and that of cassava nanoparticles (CSNPs) is 90.53%. Synthesized materials were characterized through particle size distribution (PSA), zeta potential distribution, Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC) and transmission electron microscopy (TEM). The performance of PYNPs in recovering oil was better than CSNPs as found from recovery experiments. Zeta potential distribution results confirmed the stability of PYNPs over CSNPs (-36.3 mV for PYNPs and -10.7 mV for CSNPs). The optimum concentration for these nanoparticles has been found from interfacial tension measurements and rheological properties and it was 0.60 wt.% for PYNPs and 0.80 wt.% for CSNPs. More incremental recovery (33.46%) has achieved for the polymer that contained PYNPs in comparison to the other nano-polymer (31.3%). This opens the inception for a new technology for polymer flooding that may replace the conventional method that depends on partially hydrolyzed polyacrylamide (HPAM).

This manuscript presents a study on the spatial relationships between bike accidents, the built environment, land use, and transportation network characteristics in Budapest, Hungary using Geographic Weighted Regression (GWR). The sample period included bike crash data between 2017 and 2022. The findings provide insights into the spatial distribution of bike crashes and their severity, which can be useful for designing targeted interventions to improve bike safety in Budapest and be useful for policymakers and city planners in developing effective strategies to reduce the severity of bike crashes in urban areas. The study reveals that the built environment features, such as traffic signals, road crossings, and bus stops, are positively correlated with the bike crashes index, particularly in the inner areas of the city. However, traffic signals have a negative correlation with the bike crash index in the suburbs, where they may contribute to making roads safer for cyclists. The study also shows that commercial activity and PT stops have a higher impact on bike crashes in the northern and western districts. The GWR analysis further suggests that one-way roads and higher speed limits are associated with more severe bike crashes, while green and recreational areas are generally safer for cyclists. Future research should be focused on the traffic volume and bikes trips’ effects on the severity index.

Pyrochlore oxides (A2B2O7) are potential nuclear waste substrate material due to their superior radiation resistance properties. We performed molecular dynamics simulations to study the structural properties and displacement cascades in ytterbium titanate pyrochlore (Yb2Ti2O7). We computed threshold displacement energy ( Ed ) and lattice constant ( ao) of Yb2Ti2O7. The effect of displacement cascades in Yb2Ti2O7 of recoils of energies 1 keV, 2 keV, 5 keV, 10 keV in different crystallographic directions ([100], [110], [111]) were studied. The number of defects is found to be proportional to the energy of incident PKA. Additionally, the Ed of pyrochlore is computed and it exhibits anisotropy. Furthermore, radiation damage in high-entropy pyrochlore (HEPy) i.e., YbYTiZrO7, YbGdTiZrO7 , Yb0.5Y0.5Eu0.5Gd0.5TiZrO7 were investigated and compared with Yb2Ti2O7. It was found that HEPy have a larger Ed as compared with Yb2Ti2O7 which exhibits characteristic of lower radiation damage resistance than HEPy. Our simulation proposed that HEPy alloys are more radiation resistant than individual pyrochlore constituents . This work will provide atomic insights in developing substrate materials for nuclear waste applications.

Active transportation, such as walking, cycling, and micro-mobility modes, has received a lot of attention in recent years due to its potential benefits to urban residents, such as less traffic, better air quality, more opportunities to get exercise, and an overall higher quality of life. In this study, we used Classification and Regression Trees (CART) to compare and contrast three mobility options: shared micro-mobility, individual micro-mobility, and walking. We surveyed 219 people living in Budapest, Hungary, to learn more about their travel habits and investigate the demographic elements that influence people's mode choice, such as age, gender, ownership of micro-mobility modes, education, job, and income. Results showed that ownership of personal micro-mobility modes, and age as important predictors of active travel mode choice. Males seem to prioritize cost and weather conditions when choosing shared micromobility modes, while females value safety and weather conditions. Our findings can guide policy decisions and urban planning initiatives by identifying the most significant predictors of mode choice and evaluating the possible benefits and drawbacks of each mode.

Background: The mortality and severity in COVID-19 is increased in patients with comorbidities. The aim of this study was to evaluate the unknown risk of severity and mortality in COVID-19 patients with underlying kidney and liver diseases. Method: We retrieved data on the clinical features and primary composite end point of COVID-19 patients released from inception till 16^th of April 2020 from Medline and Embase. The data on two comorbidities, liver diseases and chronic kidney disease, present in COVID-19 were pooled and statistically analysed to explain the associated severity and mortality rate. Results: 142 abstracts were screened, and 41 full articles were then read. In total, 22 studies including 5595 COVID-19 patients were included in this study with case fatality rate of 16%. The prevalence of liver diseases and CKD were 3% (95%CI; 2%-3%) and 1% (95%CI; 1%-2%) respectively. In patients with COVID-19 and underlying liver diseases, 57.33% (43/75) cases were severe with 17.65% mortality. While in CKD patients with COVID-19, 83.93% (47/56) severity and 53.33% (8/15) mortality were reported. Conclusion: This study found an increased risk of severity and mortality in COVID-19 patients with liver diseases and CKD. This will allow for better clinical management and inform more stringent preventative measures for this group of patients.

This study presents an analysis of the spatial and temporal distribution of the two large destructive earthquakes that occurred in Lake Van area on October 23, and November 9, 2011, together with the azimuth-dependent distribution of the seismic activity and microseismicity clusters after the mainshocks, associated with the complex rupture processes of their aftershock sequence. The sequence began with the magnitude Mw 7.1 earthquake of 23 October and a second destructive earthquake of Mw 5.6. The aftershock sequences of the two mainshocks were linked to the local crustal faults beneath Lake Van area, followed successively and produced unusually intense activity and significant damage in the area. The main purposes of this study are to document the spatial and temporal distribution and evolution of the October 23, 2011 aftershock hypocenters and the azimuth-dependent distribution of seismic activity, and to understand the spatial and temporal character of the aftershock sequence using the distributional and evolutional patterns of the aftershock hypocenters. A total of 10,000 aftershocks were obtained from seismic data with a high signal-to-noise ratio over collected over three years from October 23, 2011 to March 2014. These aftershocks were plotted for the time periods from November 2011 through March 2012 to March 2014 and ≈ 5000 aftershocks were retained in the depth versus distance cross-sections to detect the clusters in the first step of study (November 2011–March 2012). The focal depth distribution of the aftershock clusters, the migration of hypocenter activity and microseismicity clusters were analyzed and the distributional patterns of the detected clusters were assessed using the geometric distribution of the aftershock hypocenters. The spatial and temporal distribution of aftershocks reveal interesting key features of the deep rupture complexity of the Van earthquake: (1) most prominent aftershocks have been located in the upper crust at depths shallower than 10 km beneath ruptured area, indicating that the upper crust is brittle and seismogenic; (2) two spatial clusters have been detected at 8-10 km depths and the upward extrapolation of these clusters intersects with faults; the main cluster (60 km wide) bounded by inferred reverse faults (f3 and f4) and the central cluster (25–30 km wide) bounded by faults (f1 and f2); (3) these spatial clusters form the largest volumetric pattern of the conical-shaped cluster at depths of about 25–30 km of the azimuth-dependent rotational projections, suggesting azimuthal distributions of deep rupture characteristics; and (4) the strongest temporal cluster of microseismicity derived from temporal distribution of aftershocks has been detected within an area of about 2.5–3.0 km² and it is spatially observed at 20 km depth within the central cluster, suggesting progressive failure of the adjacent patches of possible fault.

Although the phenomenon of serial killers has received great attention from media, governments, and public, very little information is known about them and very few theories are presented by researchers specifically their definition and motives for killing. Through cross tabulation analysis of top ninety-eight serial killers, this present study poses six questions that investigate the correlations between, offender's gender, offender's level of education, time span of killing, killing severity, number of victims, killer's type of abuse, motives for killing, and victim's profile. Findings show that males kill more than females and for longer time, less educated serial killers kill more horribly, female serial killers consider their family members easy target, and finally males kill most for enjoyment and sex and females kill for financial gains.

Bulukumba Regency, South Sulawesi, Indonesia is one of the centres for whiteleg shrimp, Litopenaeus vannamei production that applies intensive technology. However, no information has been obtained regarding the characteristics and status of water quality in coastal areas with environmentally friendly concepts and the potential to receive a waste load. The study aimed to determine the performance of whiteleg shrimp culture in relation to temporal and spatial aspects and characteristic and water quality status. Measurement and sampling of water were carried out before stocking/initial of culture whiteleg shrimp (rainy season) and end of culture/after harvesting of whiteleg shrimp (dry season) at two locations in the coastal area of ​​Bulukumba Regency, namely Bonto Bahari Subdistrict (BB) and Gantarang Subdistrict (GT). Variables measured and analyzed included temperature, salinity, pH, dissolved oxygen, nitrate, nitrite, ammonia, phosphate, total suspended solids, and total organic matter. Data analysis with descriptive statistics, multivariate statistics, and non-parametric statistics. The Storet (Storage and Retrieval) method was used to determine the water quality status. The results showed that the culture of whiteleg shrimp was technology-intensive with a stocking density of 110 - 220 ind/m² with productivity between 13.9 - 44.4 tons/ha/cycle. The predicted waste load of N is 28.00 tons/cycle and P reaches 6.61 tons/cycle. Another result was that changes in water quality status during the rainy season were classified as moderately polluted at the BB location and complying quality standards at the GT location, while in the dry season, both locations were categorized as heavily polluted. Variables of water quality that caused the decrease in water quality status in both locations (BB and GT) were observed to increase salinity, nitrate concentration, and ammonia concentration. However, there was a decrease in dissolved oxygen concentration in the dry season.

Background: Generative artificial intelligence (Gen-AI) has emerged as a transformative tool in research and education. However, there is a mixed perception about its use. This study assessed the use, perception, prospect, and challenges of Gen-AI use in higher education. Methods: This is a prospective, cross-sectional survey of university students in the United Kingdom (UK) distributed online between January and April 2024. Demography and perception of Gen-AI and other AI tools were assessed and statistically analysed to assess the difference in perception between various subgroups. Results: A total of 136 students responded to the survey of which 59% (80) were male. The majority were aware of Gen-AI and other AI use in academia (61%) with 52% having personal experience of the tools. Grammar correction and idea generation were the two most common tasks of use, with 37% being regular users. Fifty-six percent of respondents agreed that AI gives an academic edge with 40% holding a positive overall perception about the use in academia. Comparatively, there was a statistically significant difference in overall perception between different age ranges (I² = 27.39; p = 0.002) and levels of education (I² = 20.07; p < 0.001). Also, 83% of students believe AI use will increase in academia with over half agreeing it should be integrated into learning. Plagiarism (33%), privacy issues (14%), and lack of clarity by the university (13%) remain the top concerns regarding the use of Gen-AI and other AI tools in academia. Conclusions: Gen-AI and other AI tools are being used and their use will continue to grow in higher education. While current use is challenging due mainly to plagiarism fear and lack of clarity by the university, most users believe AI should be integrated into the university curriculum.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Caregiving thinking is the ability to make connections between thought and emotion and encourages man to build a system of reflective value to judge matters compassionately and lovingly. Therefore, this study aims to investigate the components of caring thinking in Persian books in the first year of secondary education. This research is a descriptive and content analysis using the Shannon Entropy method. The sources analyzed are three volumes of the textbook of the first year of high school in 2021-2022. The research tool is a content analysis checklist according to the components of caring thinking, the validity of which was verified by Five experts in education. According to the analysis of the content of the book under study, it can be stated that in the Persian textbooks of the first year of high school, the critical factor of the component of normative thinking (0.2051), the component of appreciative thinking (0.2043), the component of active thinking (0.2020), Was the component of empathetic thinking (0.1957) and the component of affective thinking (0.1929). Therefore, the coefficient of the importance of the components of caring thinking in the Persian books of the first year of high school is not the same, and balance is not observed in regulating the content of these books. Considering the vital role of caring thinking in students' lives, it is suggested that the authors of textbooks pay attention to this crucial issue while reviewing the content of Persian books in the first year of high school.

The use of miniplates for stabilizing bones after orthognathic surgeries, has become increasingly popular for their effectiveness in ensuring stability and promoting swift recovery. However, the post-surgical fate of these miniplates remains a subject of contention among surgeons. Some advocate for their removal, while others suggest leaving them in place. The aims of this study, is to evaluate the incidence, causes, and potential risk factors associated with the removal of miniplates in orthognathic surgeries. A comprehensive meta-analysis was conducted by reviewing studies from various databases like PubMed, Google Scholar, Research Gate, Embase, and Scopus, focusing on publications from 1989 to 2023. Ten studies encompassing a total of 1603 patients which conformed to the inclusion criteria were selected and included in the meta-analysis. With M:F ratio range from 4:1 to 109:141. Total number of miniplates inserted was 5595, and total number of miniplates removed were 294 (5.3%). The most common reasons for miniplates removal were, infection was reported in 161 cases (2.9%), followed by miniplates exposure (34 cases, 0.6%) and palpable plates (23 cases 0.4%). Other indications included pain, patient’s preference, and temperature sensitivity. Relatively less common reasons that resulted in miniplates removal include, sinusitis, second surgery and dental pathology. The mean duration of miniplates removal was 5.5 months with the majority of miniplates (56.1%) were removed from the mandible compared to maxilla. In conclusion, this meta-analysis underscores the importance of miniplate removal in cases where hardware causes diverse complications and physical discomfort. The primary reasons for miniplates removal were infections and plates exposure, with the mandible being the most common site for removal. These findings emphasize the need for continued monitoring to assess the fate of miniplates in orthognathic surgery and provide valuable insights for future clinical decision-making.

Sensitive and precise nucleic acid detection is critical for clinical diagnostics and biotechnological advancements. Diagnostic in infectious disease field is very unique from diagnosing any other disease, that is time is of the essence; in outbreaks people die even with each passing hour in some cases, if the correct diagnosis wasn't make; for example Zika in particularly is a very challenging virus to diagnose, because it's in very few numbers of copies in the infected person, so it need high sensitive diagnostic approach to spot it, In particular, the advanced tools SHERLOCKv2 and DETECTR, give almost an immediate detection of attomolar amounts of pathogenic nucleic acids with specificity similar to that of PCR but with slight technical settings and that will guide the correct intervention for the patient. SHERLOCKv2 and DETECTR technologies are game changers for our ability to identify infectious disease and rapid detection of tumor DNA or cancer-related viruses with ultra-sensitive tests that don’t require a lot of complicated processing to go through. In this paper, we will review cutting-edge infectious disease diagnosis by CRISPR-Cas systems.

Currently SARS-CoV-2 is spreading around the world as an Omicron strain. Recently, the Omicron variants (BQ.1 and BQ.1.1) were identified as novel Variants of Concern. UpToDate, there is little information about the Omicron Variants BQ.1 and BQ.1.1. The widely altered Omicron variants are spread globally, providing a high risk of infection surges with devastating consequences in some areas. The Omicron type of SARS-CoV-2 has a harm risk of reinfection, according to early reported findings. COVID-19 Variants particularly, BQ.1 and BQ.1.1 have gained global attention and caused a worldwide sensation since their discovery. Therefore, this communication discusses the present status of COVID-19 Variants BQ.1 and BQ.1.1, and their consequences.

This paper aimed to describe an atlas of the head of the crested porcupine (Hystrix cristata), applying advanced imaging techniques such as MRI. Furthermore, by combining the images acquired through these techniques with anatomical gross sections, we obtained an adequate description of the structures that form the CNS and associated structures of this species. This anatomical information could serve as a valuable diagnostic tool for the clinical evaluation of different pathological processes in porcupines such as abscesses, skull malformations, fractures, and neoplasia.

Emerging infectious diseases (EIDs) continue to be a problem all across the world, but in certain areas the threat is greater than in others. The detection of new diseases will aid in the focus of surveillance efforts. Specifically, identifying a "patient zero" is critical step to help limit further transmission. In fact, several factors have been found to contribute to emerging infectious diseases emergence and transmission. Antigenic drift is an important factor that affects vaccine effectiveness and it is important for scientists and healthcare providers alike to understand how this process works in order to ensure that people receive effective vaccinations against infectious diseases. However, recent advances in biotechnology, immunology and artificial intelligence have enabled us to make progress in diagnosis, treatment, prevention and control of infectious diseases. The fight against infectious diseases will always be ongoing, but the advancement of bioscience offers a promising outlook for the near future. In the last two decades, several high impact zoonotic disease outbreaks have been linked to bat-borne viruses. These include SARS coronavirus, Hendra virus and Nipah virus. In addition, it has been suspected that ebolaviruses and MERS coronavirus are also linked to bats. It is being increasingly accepted that bats are potential reservoirs of a large number of known and unknown viruses, many of which could spillover into animal and human populations. In this article, we discuss the potential risk factors that contribute in emerging infectious diseases. Also, we discuss the management of disease prevention and control.

In this work, the Pumped Storage Unit (PSU) is proposed to be integrated with wind-thermal generation system owned by a company whose aim is to maximize its profit through optimal self-scheduling of its units by finding the best bidding strategy in day-ahead energy market. The mathematical formulation of the scenario based unit-commitment and coordinated trading problem is formulated as a stochastic mixed integer linear program. The formulation takes into account several uncertain parameters; such as the wind power generation, energy market prices, and imbalances up/down prices. The expected total profit obtained from energy trading with and without coordinating pumped storage system (PSS) with thermal-wind generation system were compared, and a significant improvement in profit resulted from coordination was observed. Furthermore, coordination between PSS and wind-thermal generation improve the conditional value at risk (CVaR) which monitors the biding risk level.

Respiratory viral infections, including influenza, respiratory syncytial virus (RSV), and, more recently, the coronavirus disease 2019 (COVID-19) pandemic, continue to pose significant global health threats. Conventional treatments for these infections often face challenges such as limited efficacy, the emergence of drug-resistant strains, and the requirement for frequent administration. In recent years, nanobodies have emerged as a promising class of therapeutic agents due to their unique properties, including small size, high stability, and specific binding capabilities. This mini-review article focuses on the application of nanobodies as spray and aerosol particles for the treatment of respiratory viral infections. Furthermore, we highlight the remarkable efficacy of nanobodies in preclinical and clinical studies against respiratory viruses, including their ability to neutralize viral particles, inhibit viral replication, and modulate the host immune response. We discuss the potential advantages of using nanobodies as inhalable formulations, including their improved delivery to the respiratory tract, enhanced stability in aerosol form, and reduced systemic side effects. Additionally, we explore the various strategies employed to engineer nanobodies for optimal aerosol delivery, such as conjugation to carrier particles or formulation as dry powders. We also examine the potential challenges and limitations associated with the development of nanobody-based aerosol therapies, including production scalability, cost-effectiveness, and regulatory considerations.

Zirconium nitride (Zr-N) is a candidate material for inert matric fuel elements in breeder reactors. They have shown exceptional resistance to radiative corrosive environments. They have shown excellent resistance to radiation stability at operational conditions in current generation reactors. But being a candidate nuclear fuel material in generation reactors, their radiation stability at higher temperature conditions observed has not been reported. We have employed molecular dynamics simulations to study the damage cascades and radiation stability of ZrN at 600K. The process of primary damage evolution by considering varying overlapping cascades with 10, 20 keV incident PKA’s reported here. The defects interface interaction and diffusion mechanism at the interface are reported.

In the pre era of synthetic antibodies, pharmaceutical companies depend on finding novel drugs from medicinal plants and other traditional resources; while in present, technological advances in biology, computer and robotics give the researchers the ability to rewrite and edit DNA in order to synthesize very large sets of drug candidates; these novel and improved candidates serves the basis for creating another library of drug candidates and so on until we find the right biomolecule for the disease of interest. all these technologies combined together to synthesize therapeutic antibodies for many types of cancer, autoimmune diseases, and infectious diseases, that can address diseases much more readily to very rapidly get therapeutics into patients so that we can potentially have an impact on disease. The antibodies mechanism is recognize and bind to disease cells and pinpoint the immune system to attack those cells effectively. Now a days, they dependent on computational approach to guide and accelerate the process of antibodies engineering by combination of selection system and use of high-throughput data acquisition and analysis to build and construct populations of next generation antibodies that are thermo-stable, non-immunogenic as possible, and to be administered to many humans as possible. In this review, I will discuss the latest in silico methods for antibodies engineering.

Social media platforms are not serving only as tools of communication rather they are acting like intricate systems managing our interactions. A major setback to our interactions occur when the flow of information in these networks gets distorted through polarization. It resembles a society where every debate turns into divide. Our research focuses exclusively on quantifying polarization as well as solving this issue head-on. In order to accurately gauge polarization, we’ve developed a new method that takes into consideration majority of its influencing factors. This helps us in correctly quantifying the polarization value of a given network and then by proposing it as an optimization problem we are attempting to maximally decrease polarization while staying within the set budget. We test our method on synthetic and real-world data sets, and find out that polarization is declining, and diversity is increasing. This proves that our recommendation engine has a penchant for finding the ideal connections between the nodes to start a dialogue. Our research presents a successful tactic to quantifying and reducing polarization in social media networks. The results indicate that our novel metric and intervention technique are effective in dismantling echo chambers, thereby promoting diversity in these networks.

Background and objectives: This study were designed to determine uric acid concentration and renal histopathology of M. calabura L. stem bark extract in diabetic rats and to compare the natural product of M. calabura L. stem bark extract with allopurinol. Materials and Methods: A completely randomized design was used for the experiment which consisted of 6 treatment groups, each consisting of 4 rats, as follows: 1) NR, normal rat; 2) KN, diabetic rat (negative control); 3) KP, diabetic rats given allopurinol 10 mg/kg body weight; 4) EM150, diabetic rats given the test extract 150 mg/kg body weight/day; 5) EM300, diabetic rats given the test extract 300 mg/kg body weight/day; and 6) EM450, diabetic rats given the test extract 450 mg/kg body weight/ day. Results: The results showed that M. calabura L. stem bark extract decrease (p<0.05) uric acid levels in diabetic rats and no specific damage to renal proximal tubular cells was seen. Conclusions: It was concluded that M. calabura L. stem bark extract has a potential as an antihyperuricemic in diabetic rats. The recommended does was 300 mg/kg body weight to provide a significant effect on reducing the uric acid level in diabetic rats. Our findings support the use of this plant as a treatment for gout and other inflammatory diseases.

Background and objectives: The fact that the results of troponin and Nt-proBNP interfere from biotin caused some commercial firms to update their measurement methods. In particular, the clinical incompatibility of cardiac test results may affect the risk of morbidity and mortality. The aim of this study is to investigate the interference effects of 7 different contrast agents on cardiac markers (Troponin-I, Nt-proBNP, Mass CK-MB, CK, AST, LDH) and coagulation tests (PT, APTT). Materials and Methods: Seven different contrast medias were added into control materials by using interference protocol. Concentration of PT, APTT, CK, AST, LDH, Mass CK-MB, Troponin-I, Nt-proBNP were measured by Sysmex CS-2100, Abbott c16000, Siemens Centaur XP and AFİAS-6 analyzer. The amount of deviations from target values were calculated. Results: 7 different contrast medias caused negative interference in troponin levels between 57.43% and 62.87%. It was found that different contrast medias produced false negativity in the Nt-proBNP test ranging from 6.11% to 96.01%. Enzymes and coagulation tests have been less affected. Conclusions: Different contrast medias may cause false negative cTnI and Nt-proBNP. Therefore, the contrast medias which causes the least interference should be preferred. The results of samples taken in the first hour of contrast imaging should be interpreted with care.

Background and Objectives: The current study aimed to determine the impact of fasciotomy on mortality and morbidity in children and adults with crush-related AKI following the 2023 Kahramanmaraş earthquakes. Materials and Methods: The study included individuals who had suffered crush injuries after the 2023 Kahramanmaraş earthquakes and were identified as having acute kidney injury (AKI). Patients with AKI were divided into two groups based on age: those under 18 years and those over 18 years. A comparative analysis was conducted between the mortality and morbidity rates of patients who underwent fasciotomy and those who did not. Disseminated intravascular coagulopathy (DIC), sepsis, and adult respiratory distress syndrome (ARDS) have all been identified as contributors to morbidity. Results: The study was conducted with a total of 40 patients (21 males and 19 females) aged between four and 83 years. A total of 21 patients underwent fasciotomy and the patients underwent varying numbers of fasciotomy, ranging from zero to 11. The mortality rate was 12.5%, corresponding to five adult patients. No instances of mortality were reported in the paediatric cohort. The application of fasciotomy in instances of crush-induced AKI did not result in elevated levels of mortality in either the paediatric or adult demographic. Within the adult population, a substantial difference in the duration of dialysis was observed between individuals who underwent fasciotomy and those who did not. A statistically significant increase in the number of fasciotomy incisions was observed in patients diagnosed with sepsis compared with those without sepsis. The study found a significant positive correlation between the number of fasciotomy incisions and dialysis days. Conclusions: Neither adult nor paediatric patients with crush-induced AKI showed an increased risk of death after fasciotomy. The number of fasciotomy incisions significantly correlated with the development of sepsis. Despite experiencing delays in hospital admission for paediatric patients, the incidence of both crush syndrome and mortality rates among children remained relatively low.

The purpose of this study is to investigate the effect of academic advising on changing or maintaining majors in university degrees. It is also a goal of the study to determine which semester of the course study is most likely or less likely witness the change of major and whether advising contributes to that change. Through this correlational study, the researchers explored students’ perceptions about the academic advising they received and the relationship of its absence on students’ major change. The participants were 1725 undergraduate students from all year levels. One survey is used to collect the data for this study: Influences on Choice of Major Survey. Based on the findings, it is found that university advisors have a very poor effect on students' decisions to select their majors as 45.6% of the 1725 participants indicate NO influence of advising in their survey answers. Whereas career advancement opportunities, students' interests, and job opportunities indicate a strong effect on their majors’ selections as they score the highest means of 3.76, 3.73, 3.64 respectively. In addition, findings show that students are most likely changing their majors in their second year and specifically in the second semester. Second year major change scored 36.9% in the second semester and 30.9% in the first semester. More importantly, results indicate that there is a positive significant correlation between college advisor and change major in the second year (p = 0.000). It is to researchers understanding based on the findings that when students receive enough academic advising in the first year of study and continues steadily to the next year, the possibilities of students changing their majors decreases greatly.

Focal vibration therapy can provide neurophysiological benefits. Unfortunately, standardized protocols are non-existent. Previous research presents a wide range of protocols with a wide range of effectiveness. This paper is part of a broader effort to identify effective, standardized protocols for focal vibration therapy. The vibration characteristics of four commercially available focal vibration devices that have been used for research and clinically were measured. An accelerometer was used for the measurements. Frequency and peak-to-peak amplitude were measured. Measurements were made when the devices were free and then again when they were strapped to the human body. Vibration frequency ranged from 120 to 225 Hz. Free vibration amplitude ranged from 2.0 to 7.9 g’s (peak-to-peak). When the devices were strapped to the body (constrained), vibration amplitude decreased by up to 65.7%. These results identify effective ranges of focal vibration frequency and amplitude. They illustrate the importance of identifying vibration environment, free or constrained, when quoting vibration characteristics. Finally, the inconsistency of multi-actuator devices is discussed. These results will guide protocol development for focal vibration and potentially better focal vibration devices.

Climate change affects both human and natural systems. Afghanistan ranked globally on the top of highly vulnerable countries to the adverse effects of climate change. The agricultural communities of Afghanistan is highly affected by climate change. Understanding farmers’ real experiences on changing climate become crucial in planning the future adaptation strategies. This study assessed the farmers' perception of climate change and its impacts on farming communities. Primary data were collected through face-to-face interviews conducted with 120 household heads. Additional qualitative data were collected by conducting 4 Focus Group Discussions (FGDs), 4 Historical Timeline Calendars (HTCs), 18 Key Informant Interviews (KII), and sketches of 4 Crop Calendars. The study reveals that climate indicators have varied and changed. The farmers express their experiences of decreasing snowfall in winter and annual rainfall in spring and summer, which led to the intensity and frequency of drought and water shortages for agriculture and rangelands in the upper and lower part of the valleys. The temperatures in winter and summer have increased and led to earlier snow melting, earlier blooming, flowering, and greening of the plants. These changes affected both positively and negatively. There is a half-month new opportunity for cultivation and increased earlier animal ranching in the rangelands. These findings can be valuable inputs for developing effective and efficient adaptation strategies.

Background and Aim: It is generally accepted that oxidative stress mediators play an important role in ischemia-reperfusion injury(I/R), although the exact mechanism is not fully elucidated. While the impact of silymarin on I/R injury in several tissues, including the myocardial, cerebral, gastric and liver tissue, has been examined, the present state of research on this topic remains insufficient to provide a widely accepted understanding. For this purpose, our objective was to examine the effect of silymarin on muscle tissue in rats subjected to lower extremity I/R injury. Method: After ethics committee approval, 18 male Wistar albino rats weighing between 225-275 g were used. The rats were divided into three groups containing six mice each, Control,Ischemia-Reperfusion and Silymarin-Ischemia/Reperfusion groups. Silymarin was administered intraperitoneally 30 minutes before the procedure.( 100 mg/kg-1 ) In the I/R groups, an atraumatic microvascular clamp was placed in the infrarenal abdominal aorta. After 120 minutes, the clamp was removed and reperfusion was achieved for 120 minutes. In muscle tissue samples taken at the end of the reperfusion period; Malondialdehyde (MDA) levels, catalase (CAT) enzyme activity levels and histopathological parameters were compared. Results: In the histopathological examination, no degeneration was observed in the muscle fibers in the control group, while findings of striated muscle damage such as muscle atrophy hypertrophy, muscle degeneration-congestion, internal of the muscle nucleus-oval-central nucleus, fragmentation-hyalinization and leukocyte cell infiltration were observed in the I/R group. In the S-I/R group, muscle atrophy hypertrophy, internal of the muscle nucleus-oval-central nucleus, fragmentation-hyalinization and leukocyte cell infiltration were observed to improve these damaged areas compared to the I/R group. MDA levels in the I/R group were found to be significantly higher than in the control and S-I/R groups. CAT enzyme activity was found to be significantly higher in the I/R group than in the control group. Conclusion:Our study revealed that the administration of silymarin at a dosage of 100 mg/kg-1 by intraperitoneal injection 30 minutes before ischemia in rats effectively decreased lipid peroxidation and oxidative stress. Additionally, it successfully reduced the injury caused by ischemia/reperfusion in muscle histology.

This study aimed to screen the antibacterial activity of essential oils from different parts (leave and stem) of Salvia officinalis against some Gram positive and Gram negative bacteria using agar disc diffusion test, then the extracts were prepared by hydro distillation to extract the essential oils. Maceration and hexane extraction by Soxhlet were used to obtain crude extracts from the leave and stem. Essential oils from the leaves and the ethyl acetate extract of the leaves showed higher antimicrobial activity, while hexane extract of leaves and stems showed moderate antibacterial activity. In contrast the essential oil from the stems showed very low antibacterial activity. It was observed that the results gram positive bacteria (staphylococcus aureus) was more sensitive than Gram negative (Echerichia coli).

This study investigated the influence of nutrient inputs and their timing on saffron yield and quality. The study was conducted from 2016 to 2020 and involved the application of eight different fertilization treatments at various stages of saffron growth. These treatments included single doses in Autumn (A), Winter (W), and Spring (S); double doses in Winter-Spring (AW), Autumn-Spring (AS), and Winter-Spring (WS); and a triple dose in Autumn-Winter-Spring (AWS). A control group (C) received no fertilizer. A compound fertilizer with a 15-15-15 composition was applied across all treatments, with nitrogen (N) rates of 67.5 kg/ha for single doses (A, W, S), 135 kg/ha for double doses (AWF, ASF, WSF), and 202.5 kg/ha for the triple dose (AWSF). Similar rates were applied for phosphorus (P) and potassium (K). The findings demonstrated that fertilization generally enhanced saffron attributes. The triple dose treatment yielded the most effective results. The timing of fertilization also played a crucial role, as split applications during different growth stages led to higher production especially winter fertilization. However, spring fertilization had limited impact due to decreased plant activity and reduced nutrient absorption during that period. Although the yield increased, the qualitative aspects of saffron, including color (crocin), taste (picrocrocin), and aroma (safranal), were not significantly influenced by the fertilization treatments. Nevertheless, these attributes remained within the natural limits defined by ISO-3632, indicating that fertilization practices did not compromise saffron quality. Our study highlights the significance of nutrient inputs and their timing in optimizing saffron yield. It provides valuable insights for developing efficient fertilization programs to enhance saffron production while preserving its quality characteristics.

The corrosion morphology in grade 2205 duplex stainless steel wire has been studied to understand the nature of pitting and the causes of the ferrite phase's selective corrosion in acidic NaCl solution. It is shown that the corrosion mechanism is always pitting, which either manifests lacy cover perforation or densely-arrayed selective cavities developing on the ferrite phase. Pits with a lacy metal cover form in concentrated chloride solutions, whereas the ferrite phase's selective corrosion develops in diluted electrolytes, showing dependency on the chloride-ion concentration. The pit perforation is probabilistic and occurs on both austenite and ferrite grains. The lacy metal covers collapse in concentrated solutions but remain intact in diluted electrolytes. The collapse of the lacy metal cover happens due to hydrogen embrittlement. Pit evolution is deterministic and occurs selectively in the ferrite phase in light chloride solutions.

Community-acquired pneumonia (CAP) is among the most common causes of death and one of the leading healthcare concerns worldwide. It can evolve into sepsis and septic shock, which have a high mortality rate, especially in critical patients and comorbidities. The definitions of sepsis were revised in the last decade as “life-threatening organ dysfunction caused by a dysregulated host response to infection”. Procalcitonin (PCT), C-reactive protein (CRP), and complete blood count including white blood cells are among the most commonly analyzed sepsis-specific biomarkers also used in pneumonia in a broad range of studies. It appears to be a reliable diagnostic tool to expedite care of these patients with severe infections in the acute setting. PCT was found superior to most other acute phase reactants and indicators, including CRP as a predictor of pneumonia, bacteremia, sepsis and poor outcome. In addition, PCT use is beneficial to judge timing for cessation of antibiotic treatment in most severe infectious states. The clinicians should be aware of strengts and weaknesses of known and potential biomarkers in expedient recognition and management of severe infections. This manuscript is intended to present an overview of the definitions, complications and outcomes of CAP and sepsis, with special regard to PCT and other important markers.

Particle Image Velocimetry (PIV) is a widely used experimental technique for measuring flow. In recent years, open-source PIV software has become more popular as it offers researchers and practitioners enhanced computational capabilities. Software development for graphical processing unit (GPU) architectures requires careful algorithm design and data structure selection for optimal performance. PIV software, optimized for central processing units (CPUs), offer an alternative to specialized GPU software. In the present work, an improved algorithm for the OpenPIV-Python software is presented and implemented under a traditional CPU framework. The Python language was selected due to its versatility and widespread adoption. The algorithm was also tested on a supercomputing cluster, a workstation, and Google Colaboratory during the development phase. Using a known velocity field, the algorithm precisely captured the time-average flow, monetary velocity fields, and vortices.

On 17 June 2022, the U.S. FDA authorized the Pfizer-BioNTech and Moderna COVID-19 (SARS-CoV-2) vaccines for emergency use in children ages 6 months – 4 years. Seroprevalence has increased during the current Omicron variant wave for children under 5 years and the burden of hospitalization for this age group is similar or exceeds other pediatric vaccine preventable diseases. Research following the October 2021 approval of vaccines for children 5 – 11 indicates high prevalence of parental vaccine hesitancy and low uptake, underscoring the urgency of understanding attitudes and beliefs driving parental COVID-19 vaccine rejection and acceptance for younger children. One month prior to FDA approval, in the present study 411 U.S. female guardians of children 1 – 4 years from diverse racial/ethnic, economic, and geographic backgrounds participated in a mixed method online survey assessing determinants of COVID-19 pediatric vaccine hesitancy. Only 31.3% of parents intended to vaccinate their child, 22.6% were unsure, and 46.2% intended not to vaccinate. Logistic regression indicated significant barriers to vaccination uptake including: Concerns about immediate and long-term vaccination side effects for young children, the rushed nature of FDA approval and distrust in government and pharmaceutical companies, lack of community and family support for pediatric vaccination, conflicting media messaging, and lower socioeconomic status. Vaccine-resistant and unsure parents were also more likely to believe children were not susceptible to infection and that the vaccine no longer worked against new variants. Findings underscore the need for improved public health messaging and transparency regarding vaccine development and approval, the importance of community outreach, and increased pediatrician attention to parental concerns to better improve COVID vaccine uptake for young children.

The rapid development of technology has led to the implementation of data-driven systems whose performance heavily relies on the amount and type of the data itself. In the latest decades, in the fields of bioengineering data management, among others, eye-tracking data has become one of the most interesting and essential components for many medical, psychological, and engineering research applications. However, despite the large usage of eye-tracking data in many studies and applications, a strong gap is still present in the literature regarding real-time data collection and management, which led to strong constraints for the reliability and accuracy of on-time results. To address this gap, this study aims to introduce a system that enables the collection, processing, real-time streaming, and storage of eye-tracking data. The system is developed by using Java programming language, WebSocket protocol, and Representational State Transfer (REST), improving the efficiency in transferring and managing eye-tracking data. Results were computed in two test conditions, i.e., local and online scenarios, within a time window of 100 seconds. The experiments conducted for this study were carried out by comparing the time delay between two different scenarios. Even if preliminary, results showed a significantly improved performance of data management systems in managing real-time data transfer. Overall, this system can significantly benefit the research community by providing real-time data transfer and storing the data, enabling more extensive studies using eye-tracking data.

A selective permeable membrane between two different solutions can generate osmotic pressure, Donnan potential, and ion/pH gradients based on various factors such as membrane type, solute concentration and temperature. In this study, we introduce a novel method for extracting energy from ion gradients through an innovative cycle, presenting intriguing experimental findings. Additionally, by leveraging Raoult’s Law, which describes the relationship between vapor pressure and solute presence, in conjunction with osmosis within a closed system, we successfully engineer the simplest iteration of Maxwell’s demon device. This pioneering approach to sustainable energy generation harnesses ambient temperature marking a significant advancement in energy research. Finally this renewable energy source is available all the time and everywhere.

Maxillofacial fractures are a prevalent occurrence, and the widespread use of miniplates to stabilize and secure these fractures during surgery is common. However, the post-surgical fate of these miniplates remains a subject of contention among surgeons. Some advocate for their removal, while others suggest leaving them in place. This study aims to perform an extensive meta-analysis of pertinent studies to ascertain the destiny of miniplates employed in maxillofacial surgery and discuss the consequences of either their extraction or retention. To execute this meta-analysis, an exhaustive search was conducted across multiple databases, encompassing PubMed, Scopus, and Google Scholar. Keywords such as "titanium miniplates," "screws," "maxillofacial surgery," "complications," and "removal" were utilized to identify pertinent studies. The search was constrained to studies published between 1989 and 2022. The analysis encompassed only studies reporting outcomes related to miniplates in maxillofacial surgery, including complication rates and removal frequencies. Eleven studies conformed to the inclusion criteria and were incorporated into the meta-analysis, encompassing a total of 2240 patients. All the studies had a retrospective design, with the largest study involving 800 patients. The overall complication rate was determined to be 13.3%. The most prevalent reasons for miniplate removal included patient preference, tooth extraction, and infections. The average time span for miniplate removal was 10.7 months, with the most prolonged reported duration being 24 years. These findings imply that immediate removal might not be imperative in the majority of instances. In conclusion, our meta-analysis underscores the necessity of removing miniplates in cases where hardware leads to a variety of complications and physical discomfort. Principal factors driving plate removal included patient requests, tooth extractions, and infections. Ordinarily, plate removal took place within the span of 6 to 12 months, with the mandible being the most frequent site for removal. These findings accentuate the significance of extended monitoring to assess the trajectory of miniplates in maxillofacial surgery and provide valuable insights for future clinical decisions. To validate these conclusions and gain deeper insights into the factors influencing plate removal in maxillofacial surgery, further research with larger participant cohorts and standardized outcome reporting is imperative.

BACKGROUND: Lower limb skeletal muscle ischemia-reperfusion (IR) injury associated with increased morbidity and mortality is common in several clinical situations such as aortic aneurysms repairment, peripheral arterial surgery, vascular injury repairment, and shock. Although it is generally accepted that oxidative stress mediators have a significant role in IR injury, its precise mechanism is still unknown. Anecdotally, it is sustained not only by structural and functional changes in the organ it affects but also by damage to distant organs. The purpose of this report is to illustrate the effect of proanthocyanidin on IR injury. METHODS: In our study, 18 male Wistar albino rats were used. The subjects were divided into three groups of six each. (Group Control-C, Group Ischemia-Reperfusion -IR, Group Ischemia-Reperfusion and Proanthocyanidin-IR-PRO). Intraperitoneal proanthocyanidin was given to the IR and proanthocyanidin groups 30 minutes before laparotomy and 1-hour ischemia led to these two groups. After one hour, reperfusion started. Muscle atrophy-hypertrophy, muscle degeneration-congestion, fragmentation-hyalinization, muscle oval-central nucleus ratio, leukocyte cell infiltration, catalase enzyme activity, and TBARS were all examined in lower-limb muscle samples after one hour of reperfusion. RESULTS: When skeletal muscle samples were evaluated histopathologically, it was discovered that muscle atrophy-hypertrophy, muscle degeneration-congestion, fragmentation-hyalinization, and leukocyte cell infiltration with oval-central nucleus standardization were significantly higher in the IR group than group control and group IR-proanthocyanidin. Besides, oval-central nucleus standardization was significantly higher in the IR and proanthocyanidin group than in the control group. TBARS levels were significantly higher in the IR group than in the control and IR-proanthocyanidin groups while, catalase enzyme activity was found to be significantly lower in the IR group than in the control and IR and proanthocyanidin groups. CONCLUSION: As a consequence of our research, we discovered that proanthocyanidins administered before IR have a protective impact on skeletal muscle in rats. Further research in this area is required.

A U.S. government health agency conducted epidemiological studies to evaluate whether exposures to drinking water contaminated with volatile organic compounds at U.S. Marine Corps Base Camp Lejeune, North Carolina, were associated with increased health risks to children and adults. These health studies required knowledge of contaminant concentrations in drinking water—at monthly intervals—delivered to family housing, barracks, and other facilities within the study area. Because concentration data were limited or unavailable during much of the period of contamination (1950s–1985), the historical reconstruction process was used to quantify estimates of monthly mean contaminant-specific concentrations. This paper integrates many efforts, reports, and papers into a synthesis of the overall approach to, and results from, a drinking-water historical reconstruction study. Results show that at the Tarawa Terrace water treatment plant (WTP) reconstructed (simulated) tetrachloroethylene (PCE) concentrations reached a maximum monthly average value of 183 micrograms per liter (ug/L) compared to a one-time maximum measured value of 215 ug/L and exceeded the U.S. Environmental Protection Agency’s current maximum contaminant level (MCL) of 5 ug/L during the period November 1957–February 1987. At the Hadnot Point WTP, reconstructed trichloroethylene (TCE) concentrations reached a maximum monthly average value of 783 ug/L compared to a one-time maximum measured value of 1,400 ug/L during the period August 1953–December 1984. The Hadnot Point WTP also provided contaminated drinking water to the Holcomb Boulevard housing area continuously prior to June 1972, when the Holcomb Boulevard WTP came on line (maximum reconstructed TCE concentration of 32 ug/L) and intermittently during the period June 1972–February 1985 (maximum reconstructed TCE concentration of 66 ug/L). Applying the historical reconstruction process to quantify contaminant-specific monthly drinking-water concentrations is advantageous for epidemiological studies when compared to using the classical exposed versus unexposed approach.

Human decision-making is increasingly supported by artificial intelligence (AI) systems. From medical imaging analysis to self-driving vehicles, AI systems are becoming organically embedded in a host of different technologies. However, incorporating such advice into decision-making entails a human rationalization of AI outputs for supporting beneficial outcomes. Recent research suggests intermediate judgments in the first stage of a decision process can interfere with decisions in subsequent stages. For this reason, we extend this research to AI-supported decision-making to investigate how intermediate judgments on AI-provided advice may influence subsequent decisions. In an online experiment (N=192), we found a consistent bolstering effect in trust for those who made intermediate judgments and over those who did not. Furthermore, violations of total probability were observed at all timing intervals throughout the study. We further analyzed the results by demonstrating how quantum probability theory can model these types of behaviors in human-AI decision-making and ameliorate the understanding the interaction dynamics at the confluence of human factors and information features.

The importance of this study may be defined by using the smart techniques to earned value indicators of residential buildings projects in Republic of Iraq, only one development intelligent forecasting model was presented to predict Schedule Performance Index (SPI), Cost Performance Index (CPI), and To Complete Cost Performance Indicator (TCPI) are defined as the dependent. The approach is principally influenced by the determining numerous factors which effect on the earned value management, that involves Iraqi historical data. In addition, six independent variables (F1: BAC, Budget at Completion., F2: AC, Actual Cost., F3, A%, Actual Percentage., F4: EV, Earned Value. F5: P%, Planning Percentage., and F6: PV, Planning Value) were arbitrarily designated and satisfactorily described for per construction project. It was found that ANN has the capability to envisage the dust storm with a great accuracy. The correlation coefficient (R) has been 90.00%, and typical accuracy percentage has been 89.00%.

Workers involved in scaffolding erection and dismantling activities are exposed to various physical risk factors. However, no existing study indicates that awkward working postures in scaffolding activities lead to musculoskeletal system disorders (MSDs). This study explores the ergonomic risks intrinsic to scaffolding tasks in refinery construction using the Ovako Working Posture Analysing System (OWAS).In the refinery, the utilized scaffolding encompasses an area of 319674 square meters and a volumetric extent of 603294 cubic meters. Observations were conducted on the postures of 500 scaffolding group workers across 5210 locations within the site, culminating in capturing 2000 photographic records. The mass of each scaffolding component was meticulously determined. After three months of observation, medical records were consulted for further insights. A statistical analysis employing the Pearson correlation technique was conducted to scrutinize the relationship between the ages of the scaffolding workers and the incidence of MSDs, alongside patterns of absenteeism. This analysis elucidated a robust and statistically significant correlation between the age of the workers and the prevalence of MSD associated with their occupational activities.As a result of the results of the OWAS ergonomic risk assessment, a number of regulatory changes were made to the scaffolding workforce, and then medical records were looked over again. This re-evaluation revealed a marked reduction in MSDs. The OWAS method's reliance on simple observational techniques holds substantial merit for its application within construction environments. Our research underscores the exposure of workers engaged in scaffolding tasks within continuous projects, such as refinery construction, to substantial ergonomic risks.

Several factors impact the durability of concrete bridge decks, including traffic loads, fatigue, temperature changes, environmental stress, and maintenance activities. Detecting problems such as corrosion, delamination, or concrete degradation early on can lower maintenance costs. Nondestructive evaluation (NDE) techniques can detect these issues at early stages. Each NDE method, meanwhile, has limitations that reduce the accuracy of the assessment. In this study, multiple NDE technologies were combined with machine learning algorithms to improve the interpretation of half-cell potential (HCP) and electrical resistivity (ER) measurements. A parametric study was performed to analyze the influence of five parameters on HCP and ER measurements, such as degree of saturation, corrosion length, delamination depth, concrete cover, and moisture condition of delamination. The results were obtained through finite element simulations and used to build two machine learning algorithms, a classification algorithm and a regression algorithm, based on the Random Forest methodology. The algorithms were tested using data collected from a bridge deck in the BEAST® facility. Both machine learning algorithms were effective in improving the interpretation of ER and HCP measurements using data from multiple NDE technologies.

The COVID-19 pandemic has unveiled the critical role that supercomputers play in addressing global health crises. This perspective article explores the transformative impact of supercomputing in pandemic response, highlighting how these powerful machines have transitioned from crisis management tools to essential components of preparedness strategies. In this article, we examine the key contributions of supercomputers in combating the pandemic, including their ability to accelerate scientific research, facilitate data analysis, model complex scenarios, and optimize resource allocation. Furthermore, we delve into the role of supercomputing in strengthening public health infrastructure and preparedness. We analyze the lessons learned from the pandemic and emphasize the need for proactive investment in supercomputing capabilities, data infrastructure, and computational expertise as a crucial element of pandemic preparedness efforts. By harnessing the potential of supercomputers, countries can establish robust computational frameworks that enable real-time monitoring, early detection, and effective response to future outbreaks. Moreover, we address the challenges faced by supercomputing initiatives, including the need for enhanced international collaboration, equitable access to computing resources, and the ethical considerations associated with data privacy and security. We discuss potential strategies to overcome these challenges and foster a global network of interconnected supercomputing centers dedicated to pandemic preparedness and response. Finally, we highlight ongoing research and development efforts aimed at advancing supercomputing technologies, such as exascale computing and quantum computing, and their potential to revolutionize pandemic response. We emphasize the importance of sustained investment in research and development to ensure that supercomputing remains at the forefront of future pandemic preparedness strategies.

This research aimed to improve the interpretation of electrical resistivity (ER) results in concrete bridge decks by utilizing results from multiple nondestructive evaluations (NDE) techniques in machine learning algorithms. To achieve this, a parametric study was first conducted using numerical simulations to investigate the effect of various parameters on ER measurements, such as the degree of saturation, corrosion length, delamination depth, concrete cover, and the moisture condition of delamination. A data set from this study was used to build a machine-learning algorithm based on the Random Forest methodology. This algorithm was then implemented on data collected from a bridge deck in the BEAST® facility. The presented results demonstrate an improvement in the interpretation of ER measurements using data from other NDE technologies.

Marburg virus disease (MVD) is a hemorrhagic fever and cause death up to 88% of people and is the same as Ebola virus, It is transmitted through skin contact or mucous membrane in the eyes, nose or mouth with blood or body fluids like urine, saliva sweat, feces and by object contaminated with body fluids. Despite these facts, yet there is no approved vaccine have been developed for the eradication of Marburg virus infections. Therefore, this study described a multi epitope-based peptide vaccine against Marburg virus viral protein 35, using several immunoinformatics tools combined with molecular docking studies. Utilizing Vaxijen 2.0 server, the V35 protein revealed to be antigenic with a score of 0.4316. Prediction of the T-cell and B-cell epitopes was then conducted. RTFDAFLGV epitope was found to be the most promising one with binding affinity to the highest numbers of MHC I alleles, a positive score in the Class I immunogenicity study and non-allergen. These results were further confirmed by the good interaction of RTFDAFLGV to the groove of HLA-A*02:01 with binding energy of -8.1 kcal/mole. Finally, the vaccine was cloned in silico to ensure its validity and efficiency of expression. To ensure its safety and immunogenic profile, in-vitro and in-vivo bioassays are recommended to confirm these findings.

With the rapid development of science and technology, many new concepts and terms appear, especially in English. Other languages try to express these concepts with words from their own vocabulary. In the specific case of Arabic, there are many ways to find a counterpart for a particular new concept, such as using an existing word to denote the new concept, derivation, and blending. When these methods fail, the new concepts are simply phonetically transliterated. This has the disadvantage that most of the transliterated terms do not conform to the rules of the Arabic language and lead to a distortion of the language. Some modern linguists call for using the generation strategy to translate the new terms into Arabic by using the unused Arabic roots. Therefore, it is necessary to provide a resource that contains all Arabic roots with a categorization of what is used, what is available for use, and what is rejected according to the phonetic system. This work provides a comprehensive lexicon that contains all possible Arabic triliteral roots, determines the status of each root in terms of usage and acceptability, and provides a mechanism for giving preference to roots when there is more than one root that indicates the desired meaning.

With the rapid development of science and technology, many new concepts and terms appear, especially in English. Other languages try to express these concepts with words from their own vocabulary. In the specific case of Arabic, there are many ways to find a counterpart for a particular new concept, such as using an existing word to denote the new concept, derivation, and blending. When these methods fail, the new concepts are simply phonetically transliterated. This has the disadvantage that most of the transliterated terms do not conform to the rules of the Arabic language and lead to a distortion of the language. Some modern linguists call for using the generation strategy to translate the new terms into Arabic by using the unused Arabic roots. Therefore, it is necessary to provide a resource that contains all Arabic roots with a categorization of what is used, what is available for use, and what is rejected according to the phonetic system. This work provides a comprehensive lexicon that contains all possible Arabic triliteral roots, determines the status of each root in terms of usage and acceptability, and provides a mechanism for giving preference to roots when there is more than one root that indicates the desired meaning.

In this study, we introduce a new type curve in 3-dimensional space which called B-lift curve and we obtain the Frenet operators of the B-lift curve. Moreover, we consider the correpondence of Frenet operators between the Blift curve and the natural lift curve. Finally, we investigate the B-lift curve according to the main curve is slant helix or darboux helix.

Objective: It was aimed to investigate the cerebral vascular territories in stroke patients with NVAF as an etiologic factor. Material and Methods: A total of 104 patients who were referred to our hospital between January 2015 and September 2016, who were over 55 years of age, identified or documented as having a standard ECG or Holter ECG record on their medical history, and diagnosed with stroke were included. Our study was designed as a retrospective analysis of prospective data. Detailed history, physical examination and electrocardiography (ECG) evaluations of the patients were performed. Descriptive statistics were used in the detection of findings, and t-test, Pearson-square test and Fisher's exact test were used for differences analysis. Results: 53.8% (N = 56) of the patients were male and 46.2% (N = 48) were female. The mean age was 73.5. MCA was the most common site of vascular involvement in NVAF-dependent strokes. In MCA vascular territory, ischemic infarcts were detected most frequently in the upper and lower divisions. SCA and PCA followed MCA. Approximately 64% of the NVAF-related strokes were anterior circulation infarction (ASE) and 22% were posterior circulation infarct (PSE). There was a significant difference in age and past stroke history factors in favor of ASE (p<0.05). There was no significant difference between ASE and PSE in HT, cardiac history and DM factors (p>0.05). Conclusion: It was emphasized that the area of the vessel that underwent ischemia in the acutely displayed infarcts and the etiological factor for this vessel area could be predicted

In this study, two donor-acceptor (D-A) type conjugated polymers namely PQSeCz and PQSeFl were designed and synthesized. Selenophene was incorporated as a π -bridge, quinoxaline as an acceptor unit while carbazole and fluorene were used as the donor units. Polymers were synthesized via palladium catalyzed Suzuki polymerization reaction. All molecules were characterized by 1H and 13C NMR Spectroscopy. The weight and number average molecular weights of the two polymers were determined by gel permeation chromatography (GPC). Electrochemical and spectroelectrochemical characterizations of the polymers were performed to investigate their optoelectronic properties. Oxidation potentials were 1.15 V/ 0.82 V and 1.11 V/ 0.82 V for PQSeCz and PQSeFl respectively, while reduction potentials were -1.26 V /-1.14 V and -1.48 V/ -1.23 V, respectively. In the visible region, maximum absorption wavelengths for the two polymers were 551 nm and 560 nm, respectively. Optical band gaps (Egop) were found from the lowest energy π – π∗ transition onsets as 1.71 eV and 1.58 eV, respectively. Both polymers showed good solubility in common solvents.

A method for accurately determining the chemical composition of deposits at the bottom of pores during the electrocoloring (e-coloring) of aluminum anodic oxide (AAO) layers in tin-based solutions is developed. The aluminum samples were AC e-colored after DC sulfuric anodization. Free-standing, tin e-colored aluminum oxide film was obtained by selective dissolution of the metallic aluminum from the AAO in copper chloride solution to access the deposit directly at the bottom of the pore. This allowed us to take XPS analysis directly from the deposits at pore bottoms without any interference from the base material or insulating barrier layer. The results revealed the presence of a mixture of tin oxide and metal in the deposits, which were richer in oxide content. Furthermore, a cyclic voltammetry experiment mimicking real polarization conditions during AC conditions was optimized and used to gain a deeper understanding of the electrochemical reactions that occur during AC electrocoloring. The comparison of CV results in tin-free and tin-containing electrolytes indicated that the tin deposited during a cathodic cycle is oxidized in the anodic cycle. The formation of tin based deposits radically changed the CV behavior. The XPS and cyclic voltammetry results consistently show that the deposits formed during e-coloring comprised a mixture of metallic and oxidic tin species richer in oxide content.

This paper presents the experimental and numerical studies of the vertical stress distribution beneath the centerline of circular footings resting on the sand. Vertical stress values due to circular load in medium-dense sand were measured using soil stress transducers. Reduced-scale laboratory model tests were carried out in a square-shaped test box and vertical stresses were measured at the centerline of the circular footing at different depths of the sand. In order to determine the effect of footing width on vertical stress distribution, laboratory experiments were performed on circular footings of different diameters. In addition, a series of finite element analyses was carried out on the test model to validate the findings of the experimental study. In the numerical analysis, the sand was modeled as a non-linear elastoplastic material. The analyses were performed using the finite element method with two-dimensional axisymmetric and three-dimensional conditions. The results obtained from laboratory model tests and numerical analysis were compared with the vertical stress values obtained from the theoretical solution in the literature. Vertical stress distribution in horizontal planes at any depth from the footing base shows the same characteristic form in all methods. However, some differences were observed between experimental, numerical, and theoretical results and discussed.

The current study aims to fermentation parameter for producing microbial products. Microwave parameters consist on 245 MHz, and 600-watt for 60 seconds. Ethyl acetate was the best solvent used for extraction purposes. Antioxidant properties were differentiated by blocking the oxidation of the linoleic acid with an inhibition rate of 73.13% at a concentration of 200 mg/mL, in addition to increasing its effectiveness for free radical extraction and reduction strength by increasing concentrations gradually. The bond ability to irons was lower compared to the EDTA-2Na, in addition to the obtained total content corresponding to phenolic compounds in the ethyl acetate extract of fermented rice (Koji) by A. flavus was 232.11 mg, on the basis of galic acid/mg. The stability of the antioxidant compounds of the ethyl acetate extract of fermented rice (Koji) by A. flavus was also studied; showing stability under neutral conditions, as well as at high temperatures (185 °C during two hours). However, no stability was obtained under acidic and alkaline conditions.

COVID-19 poses a significant burden to healthcare systems. Healthcare organisations with a better health innovation infrastructure have faced a reduced burden and achieved success in curbing COVID-19. In Saudi Arabia, digital technologies have played a vital role in fighting SARS-CoV-2 transmission. In this paper, we aimed to summarise the experience of optimising digital health technologies in Saudi Arabia as well as discuss capabilities and opportunities during and beyond the COVID-19 pandemic. A literature review was conducted up to September 2021 to retrieve peer-reviewed articles that critique the use of digital health technology platforms (DHTPs) in Saudi Arabia during the COVID-19 outbreak. A small but significant body of literature examined the digital response to the COVID-19 pandemic in Saudi Arabia. Health officials succeeded in optimising and maintaining a strategy to mitigate the spread of the virus via different digital technologies, such as mobile health applications, artificial intelligence, and machine learning. The quick digital response in Saudi Arabia was facilitated by governmental support and considering users and technology determinants. Future research must concentrate on establishing and updating the guidelines for using DHTPs.

Atmospheric pollens were investigated using the Lanzoni VPSS 2000 device for 2 years between 2012 and 2013 in the Sarıkamış district of Kars province, one of the highest regions of Türkiye. A total of 37909 pollen grains were collected; 15,298 pollen grains in 2012 and 22611 pollen grains in 2013. Out of 43 identified taxa, 21 were arboreal and 22 were non arboreal. Pollen from arboreal plants accounted for 36.34% (13778 pollen) of the total, while pollen from non arboreal plants accounted for 63.56% (24095 pollen). The most frequent arboreal plants pollen in the Sarıkamış atmosphere were Pinaceae (29.79%), Cupressaceae/Taxaceae (2.54%), and Morus (1.30%). The main non arboreal plants pollen in the atmosphere of Sarıkamış were Poaceae (44.60%), Artemisia (2.98%), Amaranthaceae (2.79%), Rumex (2.41%), Urticaceae (2.33%), Plantago (2.19%), and Boraginaceae (1.40%). The maximum pollen concentration was observed in June.

In this paper, we introduce ResNetMF, a groundbreaking approach that harnesses the power of residual network matrix factorization to revolutionize recommendation systems. ResNetMF integrates residual networks, renowned for their ability to capture intricate patterns and features, with matrix factorization techniques that excel in modelling user-item interactions. This fusion presents a novel solution that surpasses the limitations of traditional recommendation systems. Through comprehensive experimentation and evaluation of diverse datasets, ResNetMF demonstrates remarkable enhancements in recommendation accuracy and efficiency. By effectively capturing both linear and nonlinear relationships in user-item interactions, ResNetMF provides superior recommendation quality. The outcomes from experiments unequivocally highlight the superiority of ResNetMF over existing state-of-the-art recommendation approaches, thereby validating its innovative nature and underscoring its potential to shape the future of recommendation systems. Through the integration of the deep residual network, ResNetMF approach facilitates the training of neural networks, enabling them to explore the underlying data layers more comprehensively. Extensive experimentation and evaluation across various datasets provide compelling evidence for the superiority of ResNetMF. Moreover, the proposed method utilized natural language processing (NLP) techniques for targeted information dissemination in recommendation systems, emphasizing the importance of personalized and relevant recommendations for user satisfaction and engagement.

Trajectory Optimization (TO) is the sequence of processes that are considered in order to produce the best path that mends the overall performance or reduces the consumption of the resources where the restriction system remains maintained. In this survey, an inclusive review of the latest advancements in modeling and optimization of trajectory generation in robotic applications will be discussed broadly. In recent times, numerous studies have employed optimal control techniques involving direct and indirect methods in order to convert the authentic Trajectory Optimization problem into a constrained parameter optimization problem. Moreover, a huge variety of optimization algorithms such as Genetic Algorithms (GA), Simulated Annealing (SA), Sequential Quadratic Programming (SQP), and Particle Swarm Optimization (PSO) are used aiming to find the optimal solutions for trajectory planning. It is observable that, minimizing the jerk, energy consumption, and execution time among the most widely used design objectives, on the other hand, the robot’s joints configurations and the motor torques are the most used design variables. This paper aims to review the fundamental techniques and their coincident robotic applications in the field of trajectory optimization aiming to afford some steering for related researchers.

International law faces numerous challenges in the 21st century, ranging from the traditional issues of sovereignty to emerging threats like cyber warfare and climate change. This article explores the evolving landscape of international law, discussing both the challenges it faces and the prospects for its future. By examining the role of international organizations, the impact of technological advancements, and the growing influence of non-state actors, this article provides a comprehensive overview of the current state of international law and offers insights into how it can adapt to meet the demands of an increasingly interconnected world.

Energy savings have been a major driver for improving building airtightness in the last period. Air infiltration has an important influence on energy efficiency and significantly influences the indoor air quality and pollutant distribution in residential buildings. Pressure difference lead to air permeability through the building envelope via cracks and un-controlled air leaks, which increase not only energy consumption, also cause noise from the outside and entering particles harmful to human health. Therefore, the issue of airtightness of the building envelope has been included in the standards and regulations. Building airtightness is influenced by various design parameters such as window/wall ratio, type of joinery, size of usage area, wall material and the insulation application also the quality of workmanship. In this study, the airtightness performance of 43 different residentials in Balıkesir was deter-mined by the BlowerDoor test measurement and in the context of airtightness the architectural design parameters impact was investigated. The air exchange rate (n50) values of 43 residences were obtained between 1.94 - 49.02 h-1 and compared with the existing standards. In addition, “usage area” was determined as the most effective parameter, followed by the size of the usage area, the transparency rate of the facades, the wall material type and the insulation status.

In this work, PMMA(Poly methyl methacrylate) microfluidic system was used as a micro-reactor for urea hydrolysis by urease enzyme with use conductivity principle and utilize sound level meter(SLM) App in smartphone as a novel detector by considering the peak height in the App as an indicate for urea concentration. the advantage of use small volume and how the reaction carried on in the microfluidic system with simple and low cost are discussed, and the results were analyzed and statically determine. The linearity, detection limit (3×noise )and Correlation Coefficient, 62.5-500 ppm, 31.25 ppm and 0.992 respectively also, recovery studied were between(98.5-100.13%).

Abstract: In this study the essential oils of Salvia officinalis growing in Sudan, were obtained by hydrodistillation and analyzed by Gas chromatography mass spectrometer, forty tow compounds were identified. The essential oil composition of S.officinalis found that it had many important compounds. The detected main compounds were oxygenated monoterpenes followed monohydrocarbone, squiterpenes and other compounds. The main essential oil constituents were α-terpineol (33.07%), camphor (11.57%), α-pinene (8.96%) camphene (5.09%) β-cymen (5.40 %) caryphyllene (3.76%) β-myrcene (3.65%) β-menth1-en-b-ol (3.45%) bomeol (3.38%) β-pinene (2.74%) Epiglobulol (2.59%) 1,8 Cineol (2.24%) and trans-β- terpinyl butanone(2.00% ).

The Atlantic puffin is a medium-sized seabird with black and white plumage and orange feet. It is distributed mainly along the northern Atlantic Ocean and due, among other reasons, to human activities, it is in a threatened situation and classified as a vulnerable species according to the International Union of Conservation of Nature (IUCN). In this study, we used a total of 20 carcasses of juvenile Atlantic puffins to perform anatomical cross sections and magnetic resonance images. Thus, an adequate description of the head was made, providing valuable information that could be helpful as a diagnostic tool for veterinary clinicians, who increasingly treat these birds in zoos, rehabilitation centers and even in the wild.

Immobilization of enzymes is a good field of study to expand the life of enzyme in and lowering the cost of the chemical processes such as separation processes. Urease is an important enzyme with medical and industrial applications. The aim of the present study is to prepare an immobilized urease on a strong cation exchange resin (Amberlite IR120 -Na) and study of its activity and stability. We monitored the liberation of Na ions in the collected fractions and searching for protein in the fractions as an indicators of immobilization by ion exchange phenomenon. Sodium is measured using atomic absorption spectroscopy techniques, while protein tested by Bradford’s method. Immobilized urease activity was evaluated by salicylate-hypochlorite method. The results indicated a complete immobilization of urease enzyme on the resin surface with reserving 92% of the activity of free enzyme. The immobilized urease enzyme on resin showed good stability and it has a 62% of its activity after 154 days of storage at room temperature. It is concluded that a new immobilized urease enzyme system is prepared with good enzyme activity and stability.

This paper investigates the effects of air void topology on hydraulic conductivity in asphalt mixtures with porosity in the range 14%-31%. Virtual asphalt pore networks were generated using the Intersected Stacked Air voids (ISA) method, with its parameters being automatically adjusted by the means of a differential evolution optimisation algorithm, and then 3D printed using transparent resin. Permeability tests were conducted on the resin samples to understand the effects of pore topology on hydraulic conductivity. Moreover, the pore networks generated virtually were compared to real asphalt pore networks captured via X-ray Computed Tomography (CT) scans. The optimised ISA method was able to generate realistic 3D pore networks corresponding to those seen in asphalt mixtures in term of visual, topological, statistical and air void shape properties. It was found that, in the range of porous asphalt materials investigated in this research, the high dispersion in hydraulic conductivity at constant air void content is a function of the average air void diameter. Finally, the relationship between average void diameter and the maximum aggregate size and gradation in porous asphalt materials was investigated.

Background and objectives: Lipoid proteinosis (LP) is an autosomal recessive transfer lysosomal storage disease, characterised by the accumulation of hyalin substance in the mucous membranes, skin, internal organs and brain, for which there is no biochemical diagnostic method. The aim of this study was to determine the carnitine and acylcarnitine metabolic profile with LC-MS/MS in LP patients and thereby examine the potential of this as a new biochemical method in the determination of biochemical markers in LP patients. Materials and Methods: In this study, 27 carnitine and acylcarnitine esters were measured with LC-MS/MS in serum samples taken from 14 healthy control subjects and 14 patients who presented at the Skin and Venereal Diseases Polyclinic and were diagnosed with LP as a result of clinical, radiological and histopathological examinations. Results: The results of the study showed that C0 (free carnitine) C3, C4, C4:DC, C5DC, C6, C8, C14:1, C14:2, C16 and C18 acylcarnitines were statistically significantly reduced in the LP patients (p<0.05, p<0.01). Conclusions: It was concluded that the application of carnitine profile screening, which is an inexpensive, rapid and reliable method, could make a contribution to the differential diagnosis as aa supporting laboratory test in individuals with suspected LP.

Plastics are highly beneficial for the day-to-day activities of human beings; however, their decomposition is limited due to their strong covalent bonding. The concept of degradation of these big molecules into smaller ones or monomers was attempted by several researchers in the preceding decades with limited success. Pyrolysis is one of the ideas used to convert plastics into fuel, rather than small molecules, compared to the crowded structure of polymers. Among these plastics, low-density polyethylene (LDPE) is largely used as carry bags throughout the world, and, herein, the results of catalytic pyrolysis of the conversion of LDPE into fuel are reported. Different dosages of zinc oxide (ZnO) were used as a catalyst to do the pyrolysis at a specific temperature in a batch reactor specially designed at our laboratory. 0.6 g of ZnO was found to be the optimal dosage for a 50 g waste LDPE batch to get the maximum oil yield. The yielded oil was analyzed chemically through Fourier transform infrared spectroscopy (FTIR) and Reformulyzer M4 Hydrocarbon Group Type Analyzer. Evaluation of physical and chemical exergy along with exergetic efficiency of the process was done.

The sudden outbreak of the COVID-19 pandemic challenged education systems worldwide to quickly pivot their teaching-learning processes from in-person to virtual modes in order to control the spread of the virus. In a short period of time, teachers were forced to adopt new remote teaching methods to ensure the continuation of education. This paper examines how teachers in Pakistan leveraged mobile technology as an alternative teaching strategy to provide access to education during these unprecedented times. Through in-depth individual interviews with selected teachers, the study explores the potential of mobile technology to transform traditional teaching methods into interactive learning environments. The findings highlight the importance of embracing new pedagogical possibilities offered by mobile technology and the need for effective teacher professional development in the post-pandemic era. The study offers valuable insights into how mobile technology can be effectively utilized in education, even in the most challenging circumstances.

Time-series analysis is a widely used technique across various fields and industries, as it helps in understanding, predicting, and forecasting the behavior of data points over time. These fields include but are not limited to finance, economics, healthcare, transportation, etc. In the case of this paper, we have focused on finance. Predicting future values of financial time series offers several benefits. Accurate forecasts can help investors make better decisions about their investments. To predict future values, deep learning algorithms are commonly used since it is an effective method with complex data. In this study, we conduct a study that investigates the use of different data pre-processing techniques on deep learning algorithms in predicting the time series values. To conduct this experimental study, we utilize an open source software, which using long short-term memory technique as the representative deep learning technique, published in github software code repository platform. With this study, we investigate the effects of autoencoder and discrete wavelet transform data pre-processing techniques in time-series prediction. We discuss the details of the experimental study and report our results. The results show that time series prediction (using backtesting methodology) without any data pre-processing leads to 12.6% for mean absolute percentage error. The results also show that, time series prediction with the data preprocessing techniques (Wavelet Transform and Stacked Autoencoder) lead to 3.4%

As the world is striving to recover from the shockwaves triggered by the Covid-19 crisis, all hands are needed on deck to transition towards a green recovery and make peace with nature as prerequisites of a global sustainable development pathway. In this paper, we examine the blockchain hype and the gaps in data and tools to build promising use cases for blockchain technology to accelerate global efforts in the decade of action towards achieving the SDGs. We attempted to break the hype-cycle portraying blockchain’s superiority by navigating a rational blockchain use case development approach. By prototyping an SDG Acceleration Scorecard to use blockchain-enabled solutions as SDG accelerators, we aim to provide useful insights towards developing an integrated approach that is fit-for-purpose to guide organizations and practitioners in their quest to make informed decisions to design and implement blockchain-backed solutions as SDG accelerators. Acknowledging the limitations in prototyping such tools, we believe these are minimally viable products and should be considered as living tools that can further evolve as the blockchain technology is getting mature, its pace of adoption increasing, and its lessons learned, good practices and standards widely shared and internalized by teams and organizations working on innovation for development.

In birds, unlike mammals, there is no complete separation between the thoracic and abdominal cavities. Instead, they have the coelomic cavity where most main organs are found. Therefore, an adequate knowledge of the anatomy of the coelomic cavity is of great importance for veterinarians, biologists and the scientific community. This study aimed to evaluate the coelomic cavity anatomy in the Atlantic puffins (Fratercula Arctica) using anatomical sections and computed tomography images.

ASTM A743 CA6NM alloy is a martensitic stainless steel typically used in energy industry -runners and hydraulic turbine components- due to its superior toughness, yield and fatigue properties. In both the manufacturing, shielded metal arc welding is applied to join for this grade steels. However, weldability of the steels is limited due to formation of hard and brittle phases such as untempered martensite during welding and post weld heat treatment processes. The formation causes a reduction in toughness. In this study, influence of post-weld heat treatment procedure (single tempering and double tempering) and parameters on microstructure and hardness of AWS410NiMo all weld metal. Hardness tests were conducted from weld metal. Microstructures of the all weld metals subjected to different heat treatment process were characterized.

High dimensional datasets are highly likely to have redundant, irrelevant, and noisy features that negatively affect the performance of the classification algorithms. Selecting the most relevant features and reducing the dimensions of datasets by removing the undesired features is a dimensional reduction technique called Feature Selection (FS). In this paper, we propose an FS approach based on the Black Hole Algorithms (BHO) with a mutation technique called MBHO. Generally, BHO contains two major phases. At the exploitation phase, a set of stars are modified based on some rule and according to some objective function, the best star is selected as the black hole which attracts other stars. Furthermore, when a star gets closer to the event horizon, it will be swallowed and a new one will be randomly generated in the search space which thus is the exploration phase. However, randomness may cause the algorithm to fall into the trap of local optima, and to overcome such complications, inversion mutation is used. Furthermore, we modify a widely utilized objective function in most of the proposed works for wrapper feature selection by combining two new terms that are based on the correlation among the selected subset of features and the features and the classification label. We also utilize a transfer function, known as the V2 transfer function, to convert continuous values into discrete ones to enhance search. We assess our approach via extensive evaluation experiments using fourteen benchmark datasets. We benchmark the performance of a wrapper FS approach called Binary Cuckoo Search (BCS), and three filter-based FS approaches (namely Mutual Information Maximisation (MIM), Joint Mutual Information (JMI), and minimum Redundancy Maximum Relevance (mRMR)). Our evaluation has shown that the proposed model is an effective approach for FS, in selecting better features that enhance the performance metrics on the classifiers. Thus, MBHO can be utilized as one alternative to the existing state-of-art-approaches. We release the source codes of our implementation for the community to build on with new methods and datasets.

Introduction: Physiotherapy exercises administered to preterm infants in the NICU can enhance motor skills and expedite the discharge process for infants born before 30 weeks of gestational age. The research delves into the influence of physiotherapy programs on these preterm infants' activity and participation levels. Methods: The intervention group received a one-month physiotherapy program including massage around the mouth, mobilization and weight-bearing exercises, and massage therapy for the extremities, while the control group did not. The motor skills were evaluated by the Test of Infant Motor Performance (TIMP), Dubowitz Neurological examination, and Preterm Oral Feeding Readiness Scales (POFRAS). Results: There was a significant difference in The TIMP, Dubowitz Optimal Score, Type of Non-Invasive Ventilation, TIMP Range, and POFRAS scores in the physiotherapy group rather than the control group (p<0.05). There were no differences in the length of stay in the NICU, respiration rate, heart rate, body temperature, oxygen saturation, body weight on the evaluation day, body weight at discharge, head circumference at discharge between the groups (p>0.05) Discussion: We conclude that physiotherapy in NICU improves the motor outcomes, activity and participation in preterm infants rather than the body functions and structure like vital signs and infants’ body weight.

Background: Eukaryotes whole-genome sequencing is crucial for species identification, gene detection and protein-annotation. Oxford Nanopore sequencing serves as an affordable and rapid platform for sequencing eukaryotes, however the relatively higher error rates require computational and bioinformatic efforts to produce more accurate genome assemblies. Here, we evaluated the effect of read correction tools on eukaryotes genome completeness, gene detection and protein-annotation. Methods: Reads generated by ONT of four eukaryotes, C. albicans, C. gattii, S. cerevisiae, and P. falciparum, were assembled using minimap2 and underwent three rounds of read correction using flye, medaka and racon. The generates consensus FASTA files were compared for total length (bp), genome completeness, gene detection, and protein-annotation by QUAST, BUSCO, BRAKER1 and InterProScan, respectively. Results: genome completeness was dependent on assembly method rather than read correction tool, however, medaka performed better than flye and racon. Racon significantly performed better than flye and medaka in gene detection, while both racon and medaka significantly performed better than flye in protein-annotation. Conclusion: We show that three rounds of read correction significantly affects gene detection and protein-annotation which are dependent on assembly quality in preference to assembly completeness.

Blockchain is a path-breaking paradigm, and cryptocurrencies are one of the main application areas of Blockchain technology. Bitcoin leads the cryptocurrency markets, both in terms of market capitalization and in scientific interest. In this paper, we performed a comprehensive bibliometric study of the Bitcoin-related literature. Using the Scopus database, we created a sample that comprises 4495 documents written in the 2011–2020 period. Furthermore, we provided insights about dimensions such as the change in the number of publications over the course of years, the main research areas, types of published documents, most important platforms and sources of Bitcoin publications, highly cited studies, productive authors, author’s countries, and finally main funders of Bitcoin-related research. Lastly, our bibliometric study manifests the current state and future path of Bitcoin literature from distinct perspectives.

Environmental psychology plays an important role in the overall development of human mental health. Student activism and health concerns also arose about the human health costs associated with a healthy built environment. This research focuses on recent design "trends", active design, and their relationship to environmental psychology and campus health. This study investigates how an active design approach can improve the environmental psychology of universities to achieve a healthy campus for students to be healthy. The total student participants are 428, 176 male (41.2%) and 251 female (58.8%), from ten university campuses. The methodology is a questionnaire survey including an active design approach based on physical activity categories with SPSS analyses. The results of this study revealed that only 19.7% of students were active on campus, 74.6% active off campus, and 5.7% active on and off campus. Students are more interested in social activity than in mental and physical activity. In addition, the ob-stacles to students' physical inactivity are lack of time, opportunities on campus and the psychological feeling of anxiety, depression and tension due to social activity and work performance in universities. In conclusion, a model is designed to demonstrate the relationship between environmental psychology and active design variables

Aims: The lack of information about the inter variability of the test results obtained by CLSI and EUCAST requires further clarifications to interpret antimicrobial susceptibility patterns better. This study aimed to compare the CLSI and EUCAST interpretations of the antimicrobial susceptibility test results of the ESBL–producing uropathogenic Escherichia coli and Klebsiella pneumonia strains. Methods: After obtaining 157 ESBL-producing E. coli and 95, ESBL-producing K. pneumonia isolates from the urine specimens of the patients, Kirby-Bauer’s disc diffusion method was used for conducting antimicrobial susceptibility test. The test procedures and the interpretation of the results were carried out according to the year 2017 versions of both of the two guidelines. For the statistical comparison of concordance between the two guidelines, the Kappa coefficients and the concordance rates were calculated. Results: The results were graded in the range from perfect to poor agreement. For E. coli, interpretations of the AST results revealed a moderate to perfect agreement between both methods. Weighted Kappa agreement scores in the range from 0.42 to 1. The agreement for AMC, TPZ30/6, ceftazidime 10, meropenem, and aztreonam was poor without any inconsistencies. For Klebsiella, the kappa agreement score was in the range from 0.25 to 1. It was incompatible with AMC, TPZ 30/6, ceftazidime 10, aztreonam; there was poor agreement for cefepime, amikacin and ertapenem. Conclusions: Our results showed agreement between the two guidelines for uropathogenic extended-spectrum ß-lactamase producing Escherichia coli and Klebsiella pneumoniae but also showed inconsistencies between two guidelines. Therefore, the results of our study contribute to the comparison of these guidelines for interpreting antibiotic susceptibilities.

Background: Vaccinating children against COVID-19 is an essential public health strategy in order to reach herd immunity and prevent illness among children and adults. Parents are facing tremendous stress in relation to the COVID-19 pandemic and the effectiveness of the COVID-19 vaccination program for children. In this study, we aimed to investigate parents’ willingness to vaccinate their children against COVID-19 in North Kivu province (DRC). Methods: A cross-sectional survey between December 01, 2021 to January 20, 2022 in 6 health zones (Goma, Karisimbi, Butembo, Beni, Kamango and Katwa) was conducted in the province of North Kivu. In each health zone, we selected 5 clusters (Health area) using the method of probabilistic selection proportional to population size. In total, 522 parents participated in our study. Results: Overall, 32.8% of parents intended to vaccinate their children. In the multivariate analysis, younger age of parents (aOR : 2.40, CI : [1.50-3.83]), higher level of fear that “a member of my family” could contract COVID-19 (aOR : 2.35, CI : [1.38-4.02]), higher level of perceived vulnerability to COVID-19 within the family (aOR : 1.70, CI : [1.005-2.2881]), higher level of perceived susceptibility to COVID-19 within the family (aOR : 3.07, CI : [1.80-5.23]), and history of vaccination against COVID-19 among parents (aOR : 16.47, CI : [8.39-32.33]), were significantly associated with the intention to have their children or adolescents vaccinated. Conclusion: Willingness of parents to vaccinate their children against the COVID-19 vaccination was low in North Kivu. There is undeniably in this region a need to reinsure the populations about vaccine safety for both children and adults. Public health authorities should also address widespread misinformation about vaccines in a timely manner.

Natural gas combined cycle power plants (CCPPs) are widely used to meet peak loads in electric energy production. Continuous monitoring of the output electrical power of CCPPs is a requirement for power performance. In this study, the role of ambient temperature change having the greatest effect on electric production is investigated for a natural gas CCPP. The plant has generated electricity for fourteen years and setup at 240 MW in Aliağa, İzmir, Turkey. Depending on the seasonal temperature changes, the study data were obtained from each gas turbine (GT), steam turbine (ST) and combined cycle blocks (CCBs) in the ambient temperature range of 8-23°C. It has been found that decreases of the electric energy in the GTs because of the temperature increase and indirectly diminishes of the electricity production in the STs. As a result, the efficiency of each GT, ST and CCB reduced, although the quantity of fuel consumed by the controllers in the plant was decreased. As a result of this data, it has been recommended and applied that additional precautions have been taken for the power plant to bring the air entering the combustion chamber to ideal conditions and necessary air cooling systems have been installed.

The impacts of spice (sumac, cumin, black pepper, and red pepper) extract on Gram-positive (S. aureus and E. faecalis) and Gram-negative (K. pneumonia, P. aureginosa, C. jejuni, A. hydrophila, S. Paratyphi A, and Y. enterocolitica) food-borne pathogen bacterial strains (FBP) for their antibacterial activity and accumulation of ammonia (AMN), trimethylamine (TMA), and biogenic amines (BAs) in tyrosine decarboxylase broth (TDB) were investigated. Sumac extract exhibited the highest an-tibacterial potential against all FBP followed by cumin and peppers. Ammonia (AMN) production (844.24-543 mg/L) was strongly inhibited by sumac extract (55.10 mg/L), whilst suppression of trimethylamine (TMA) production (53.66-3.21 mg/L) was observed by sumac (1.28 mg/L), followed by red pepper (0.91 mg/L) extract. Cumin extracts stimulated the production of cadaverine, spermidine, tryptamine, and 2-phenylethylamine. Furthermore, sumac extracts inhibited hista-mine and tyramine production in the majority of FBP. This research suggests the application of sumac extracts as natural preservatives for inhibiting the growth of FBP and inhibiting the pro-duction of AMN, TMA, and BAs.

Education for Sustainable Development (ESD) is a global initiative towards transforming education for sustainability. The integration of SD into the education portfolio is considered to be an important approach that ensures strategic alignment of higher education with SDGs. A document review was used to identify and discuss the difference between transmissive and transformative education in relation to SDGs and in the context of Somali education. In this trajectory, it is expected that the concept of ‘‘transformative education is likely to become more common to meet the emerging social, economic and environmental issues, yet practical challenges remain in Somaliland HE sector. The roadmap towards addressing transformative education for sustainability is not included in the Somaliland national portfolios; particularly ESD has not been presented. In this regard, this paper proposed a generic framework that spotlights the integration of HEIs and the national development goals (NDGs) in Somaliland. Meanwhile, developed and developing countries are prioritizing structural transformation in their HEIs that are tailored to national and regional development programs. Consistent with the Rio + 20 outcomes, the authors analyzed the concept of the ‘‘sustainable university’’ and identified the fact that it is practically divided into three interrelated and complementary categories, namely social-, environmental-, and economic-oriented university in pursuit of actualizing SD. The paper recommends major reforms in the education sector including availing investment portfolios for R&D, renovation of education goals and transforming universities for sustainability

Background: In recent years, whole blood parameters and derivatives have been used as prognostic criteria in the course of the disease in various diseases. The prognostic nutritional index (PNI), the systemic immune-inflammation index (SII), the neutrophil-lymphocyte ratio (NLR) have been adapted as an indicator of inflammation and have been widely studied to define the severity of inflammation in some diseases. The aim of this study was to evaluate the relationship between parameters such as NLR, SII, PNI, controlling nutritional status (CONUT) score, nutritional risk index (NRI) and with immunonutrition status and disease activity in patients with ischemic stroke of small vessel, large vessel and other etiologies. Methods: We retrospectively evaluated the records of 1454 consecutive ischemic stroke patients hospitalized in the emergency department of Gaziosmanpasa Education and Research Hospital from 2019 to 2023. Results: Of the 1350 SVO patients included in the study, 58.8% had small vessel, 29.3% had large vessel and 11.9% had other etiologies. There was a significant difference between the 3 etiology groups for PNI and CONUT. The median PNI was 47.03 (41.33-52.85) in the other etiology group, 35.29 (33.69-37.25) in the small vessel group, and 34.11 (30.23-36.87) in the large vessel group. The CONUT median was 5(5-6) in the small vessel group, 5(4-6) in the large vessel group and 4(4-4) in the other etiology group. In addition, CONUT and PNI were also found to be independent risk factors for death. A negative significant correlation was observed between PNI and NLR (r:-0.692), SII (r:-0.591), CONUT (r:-0.685). Significant correlations were observed between CONUT and NLR (r:0.402), SII (r:0.312). Conclusion: PNI and SII were significantly associated with disease activity. PNI, CONUT and NRI as a more accurate prognostic indicator of nutritional status in patients with ischemic stroke of small vessel, large vessel and other etiologies. NLR and SII may be important predictive markers in the course and prognosis of stroke.

The novel coronavirus disease (COVID-19) pandemic is provoking a prevalent consequence on mental health because of less interaction among people, economic collapse, negativity, fear of losing jobs, and death of the near and dear ones. To express their mental state, people often are using social media as one of the preferred means. Due to reduced outdoor activities, people are spending more time on social media than usual and expressing their emotion of anxiety, fear, and depression. On a daily basis, about 2.5 quintillion bytes of data are generated on social media, analyzing this big data can become an excellent means to evaluate the effect of COVID-19 on mental health. In this work, we have analyzed data from Twitter microblog (tweets) to find out the effect of COVID-19 on peoples mental health with a special focus on depression. We propose a novel pipeline, based on recurrent neural network (in the form of long-short term memory or LSTM) and convolutional neural network, capable of identifying depressive tweets with an accuracy of 99.42%. Preprocessed using various natural language processing techniques, the aim was to find out depressive emotion from these tweets. Analyzing over 571 thousand tweets posted between October 2019 and May 2020 by 482 users, a significant rise in depressing tweets was observed between February and May of 2020, which indicates as an impact of the long ongoing COVID-19 pandemic situation.

Reactive powder concrete (RPC) is a modern form of cementitious material. Major components include cement with a very low water-to-binder (w/b) ratio, steel fibres, superplasticizers, and very fine additives used in place of coarse aggregate, and very little water. The primary goal of this study is to examine the impact of immersion in sulfuric acid on compressive strength and to evaluate the impact of curing procedures on the preparation of RPC with high characteristics. The experimental work includes 4 mixes, which are prepared using 30 mm hooked-end steel fibers with a ratio of 0.4 by volume, silica fume and metakaolin with a ratio of 25% of cement weight. Compressive and indirect tensile strengths, ultrasonic velocity, and bulk density tests were conducted on the RPC that was prepared to evaluate its qualities. The results showed that heat curing resulted in a greater increase in strength than water curing did, and that mechanical properties improved with increasing SF more than MK additions. Heat-cured RPC demonstrated greater resistance to sulfuric acid immersion tests on compressive strength compared to water-cured RPC.

Our study examines the association of the presence of mildew, cockroaches, and pets in homes as well as household dust allergens with the prevalence and/or severity of allergic diseases. No study has concurrently assessed home environment exposures in relation to allergic conditions in the general US population. Data from 5,409 participants from the 2005-2006 National Health and Nutrition Examination Survey living in their current homes for ≥1 year were analyzed. Multivariate logistic regression analyses between home exposures and allergic diseases prevalence and severity were performed. In adjusted analyses, mildew was associated with higher current asthma, allergies, and allergic rhinitis prevalence; endotoxin, with higher current asthma prevalence), and dust Canis familiaris (Can f) 1, with higher allergic rhinitis prevalence. However, presence of cockroaches and dust Dermatogoides farinae (Der f) 1 were associated respectively with lower current asthma and allergies prevalence. Presence of mildew, dust Der f1, Dermatogoides pteronyssinus (Der p) 1, Feline domesticus (Fel d) 1, and endotoxin were all associated with asthma and/or wheeze severity. Non-atopic asthma was more frequent with mildew and/or musty smell dust and higher dust Fel d1 concentration, while atopic asthma was more prevalent with higher Can f1and endotoxin concentrations in dust. This study confirms previous relationships and reports novel associations, generating hypotheses for future research.

The present grievous situation of the tuberculosis disease can be improved by efficient case management and timely follow-up evaluations. With the advent of digital technology this can be achieved by quick summarization of the patient-centric data. The aim of our study was to assess the effectiveness of the ODK Scan paper-to-digital system during testing period of three months. A sequential, explanatory mixed-method research approach was employed to elucidate technology use. Training, smartphones, application and 3G enabled SIMs were provided to the four field workers. At the beginning, baseline measures of the data management aspects were recorded and compared with endline measures to see the impact of ODK Scan. Additionally, at the end, users’ feedback was collected regarding app usability, user interface design and workflow changes. 122 patients’ records were retrieved from the server and analysed for quality. It was found that ODK Scan recognized 99.2% of multiple choice bubble responses and 79.4% of numerical digit responses correctly. However, the overall quality of the digital data was decreased in comparison to manually entered data. Using ODK Scan, a significant time reduction is observed in data aggregation and data transfer activities, however, data verification and form filling activities took more time. Interviews revealed that field workers saw value in using ODK Scan, however, they were more concerned about the time consuming aspects of the use of ODK Scan. Therefore, it is concluded that minimal disturbance in the existing workflow, continuous feedback and value additions are the important considerations for the implementing organization to ensure technology adoption and workflow improvements.

The history of agricultural terraces dates back to agricultural society; and throughout history, they have enabled agricultural activities to be carried out on lands with irregular relief. They have also served as an essential element of rural landscapes due to their architectural features, building materials, and techniques, as well as the landscapes they create. Furthermore, terraces also contribute to soil conservation by preventing erosion, adding organic matter to the soil, and harvesting rainwater. The significance of agricultural terraces in the cultural landscape has triggered the need to define and classify them. In this regard, agricultural terraces across many different locations have found their place on the List of Globally Important Agricultural Heritage Sites (GIAHS) and UNESCO cultural heritage lists. In the present study, the agricultural terraces of the Erikli neighborhood of the Uzundere district were mapped through surveys, drone shots, and orthophotos, and analyzed based on the size and density indices previously used in the classification of Alpine terraces. The study is important in terms of demonstrating the use of drone technology in mapping agricultural terraces. The results of the study revealed that 51.6% of the agricultural terraces in the study area had very steep slopes and 22195 meters of total stone wall length, the average density index was 523.29 m/ha, and 76.4% of the terraces were meso and macro in character. Moreover the study shows that the terraces in the region are more susceptible to deterioration.

In this work, an improved collocation method based on the Bernoulli polynomials is presented to solve the Volterra integral equation (VIE) of the second kind. The main idea of the proposed method is to improve the results of the classic Bernoulli collocation method (BCM) by dividing the interval into some sub-intervals and considering the collocation points on each of them. Here, the zeros of the shifted Chebyshev polynomials (SCPs) are considered as collocation points. Then, BCM is applied step by step from the first sub-interval to the last one. By this process, a system of algebraic equations is attained for each sub-interval that could be easily solved. Convergence of the scheme is analyzed. For the purpose of demonstrating the validity, applicability, and efficiency of the suggested scheme several numerical examples are provided. Numerical results illustrate that the accuracy of the improved Bernoulli collocation method (IBCM) is more than BCM.

Monoclonal antibody (mAb) therapy has revolutionized the treatment of various diseases, including cancer and autoimmune disorders. However, the emergence of SARS-CoV-2 variants, as well as other pathogenic variants, poses challenges in maintaining the therapeutic efficacy of mAbs. In this mini review article, we aim to explore the strategies to overcome variants resistance in mAb therapy against viral infections. Firstly, we discuss the mechanisms through which variants can evade the neutralizing effects of mAbs. Understanding these mechanisms is crucial in developing targeted approaches to combat resistance. Next, we delve into the strategies being pursued to address variants resistance. These include developing new mAbs or antibody cocktails that target multiple epitopes, engineering mAbs with improved binding affinities or enhanced neutralizing capabilities, and exploring alternative therapeutic modalities such as bispecific antibodies or antibody-drug conjugates. Furthermore, we highlight the role of computational modeling and artificial intelligence in predicting variant escape mutations and aiding in the design of more effective mAbs. Additionally, we examine the importance of continuous surveillance and monitoring of emerging variants to inform treatment strategies. This article emphasizes the urgent need for proactive approaches to tackle variants resistance in mAb therapy. By combining innovative design strategies, computational modeling, and vigilant surveillance, we can maintain the therapeutic effectiveness of mAbs and stay ahead in the battle against evolving pathogens and viral infections.

The integration of bioinformatics in drug discovery has revolutionized the field of pharmaceutical research. The use of computational tools and techniques has enabled researchers to analyze vast amounts of data, identify potential drug targets, and design new drugs with greater precision and efficiency. The integration of bioinformatics has also facilitated the development of personalized medicine, where drugs can be tailored to individual patients based on their genetic makeup. However, there are still challenges that need to be addressed, such as the need for more accurate predictive models and the ethical considerations surrounding the use of patient data. Overall, the integration of bioinformatics in drug discovery holds great promise for improving human health and advancing our understanding of disease mechanisms. In this mini-review, we discuss how Bioinformatics plays a crucial role in each step of drug discovery by providing tools and techniques to analyze large amounts of data generated from various sources, as well as the challenges and the opportunities offered by bioinformatics.

Investment management is a common process and practice used for achieving a desirable investment goal or outcome. Investment assessment should be carried out at various stages of project realization in accordance with capital investment volume. Investment risk management implies the effective control of all procedures and monitoring of risks in all phases of the investment project. Because of the reason that a single indicator in probability calculation of achieving optimal return from the investment does not exist, performing sufficiently reliable estimates of the quality of investments becomes a tedious task. There are many indicators, factors, and criteria required for consideration to reach the effective solution of the investment problem. Unfortunately, the systematic variation of economic situations in the marketplace stipulates the continuous and frequent changes of investment conditions and environment in which the investor should act and operate. Hence, the rules required for providing a reasonable quality of investment projects can be based only on investor’s management strategy and rely on investor’s intuition and practice. The importance of classification in investment management and decision making process is undeniable. The objects to be classified are described using assessments in accordance with various criteria which can be both quantitative and qualitative. With a competent formulation of the investment process, both methods are used in parallel. There exist various decision making approaches for the investment management, and simple additive weighting (SAW) is one of the well-known multi-criteria decision making (MCDM) methods aiming to provide an optimal decision for decision maker when solving various real-life problems, and particularly, investment problem. In this paper, fuzzy simple additive weighting (FSAW) method in group decision making is applied to undertake the capital investment expenditure for purchasing cars with the purpose of renting them to the public. The development of existing FSAW method is accomplished and this process involves the sensibility of outcomes to changes in the rate of fuzziness represented with decisions taken. Eventually, the degree of fuzziness involved in an analysis that directly attempts to model the immanent vagueness and imperfectness in particular precedency judgments made, is determined. A numerical example illustrates the importance and effectiveness of the suggested approach with the aim of ranking alternatives and hence, determining the most preferred alternative in MCDM problem.

We aimed to evaluate the effect of hypoxia caused by different levels of chronic carbon monoxide (CO) exposure via total AgNOR area/total nuclear area (TAA/TNA) ratio and mean AgNOR number on rat brain tissue. Eighteen Albino Wistar adult male rats were randomly divided into three groups (control as group A, 1000ppm and 3000ppm concentration of CO gas exposed as group B and C, respectively). CO gas was chronically given as 30 min a day during seven days. Statistically significant differences were found among the groups for both mean AgNOR number (χ2=12.051, p=0.002) and TAA/TNA (χ2=12.316, p=0.002), respectively. When the two groups are compared in terms of TAA/TNA ratio, statistically significant differences were detected between control and 1000ppm (Z=-2.882, p=0.004), between control and 3000 ppm (Z=-2.882, p=0.004) for TAA/TNA ratio. Statistically significant differences were found between control and 1000 ppm (Z=-2.882, p=0.004), between control and 3000 ppm (Z=-2.887, p=0.004) for mean AgNOR number. It is important to determine new markers with high sensitivity and easy to apply in order to determine the effect of toxication in different organs and tissues (especially brain tissues) that are chronically exposed to carbon monoxide intoxication. It seems that AgNOR may be used for this purpose.

Advancements in deep learning and availability of medical imaging data have led to use of CNN based architectures in disease diagnostic assisted systems. In spite of the abundant use of reverse transcription-polymerase chain reaction (RT-PCR) based tests in COVID-19 diagnosis, CT images offer an applicable supplement with its high sensitivity rates. Here, we study classification of COVID-19 pneumonia (CP) and non-COVID-19 pneumonia (NCP) in chest CT scans using efficient deep learning methods to be readily implemented by any hospital. We report our deep network framework design that encompasses Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory (biLSTM) architectures. Our study achieved high specificity (CP: 98.3%, NCP: 96.2% Healthy: 89.3%) and high sensitivity (CP: 84.0%, NCP: 93.9% Healthy: 94.9%) in classifying COVID-19 pneumonia, non-COVID-19 pneumonia and healthy patients. Next, we provide visual explanations for the CNN predictions with gradient-weighted class activation mapping (Grad-CAM). The results provided a model explainability by showing that Ground Glass Opacities (GGO), indicators of COVID-19 pneumonia disease, were captured by our CNN network. Finally, we have implemented our approach in three hospitals proving its compatibility and efficiency.

Different products from a unique Propolis extract, Propolis (bee glue), an of resinous consistency produced by bees, has been used as indigenous medicine for the treatment of several diseases in some contrary. Safety assessment of propoils extracts with respect to antimicrobial activity against three bacterial isolates, Proteus Mirabilis , Klebsiella Pneumonia and Staphylococcus Qureus.The result showed that the main composition of the extract was Anthraquinone, the last one was responsible for the biological activity of the extract. FT-IR, UV results showed more than eight peaks for represent the main fine composition of the extract. The present study also showed that the extract has antibacterial activity against three bacterial isolates

The digital elevation model (DEM) is one of the key geospatial datasets used in many fields of engineering and science for countless applications. In this contribution, we assess the vertical accuracy of the Advanced Land Observing Satellite (ALOS) World 3D-30m (AW3D30) DEM using the runway method (RWYM). The RWYM utilizes the longitudinal profiles of runways which are reliable and ubiquitous reference data. A reference dataset used in this project consists of 36 runways located at various points throughout the world. The same dataset was previously used to test the accuracy of WorldDEM^TM. Our study indicates that AW3D30 has a remarkably high RMSE of 1.78 m (one σ). However, while analyzing the results, it has become apparent that it also contains a widespread elevation anomaly. We conclude that this anomaly is the result of uncompensated sensor noise and the data processing algorithm (downsampling of the higher resolution data). We believe that this issue should be communicated to the user community. Also, we would like to note that the traditional accuracy assessment of a DEM, e.g., statistical assessment of the elevation differences = model – reference, does not allow for identification of these type of anomalies in a DEM.

The objectives of this study were to evaluate fixed risk factors associated with PWM and to estimate genetic parameters for PWM. A total of 927 birth records from a mixed population of purebred and crossbred Boer and Spanish goats born between 2016 and 2023 at the International Goat Research Center (IGRC) were used for this study. Four binary traits were studied: D0-3 (death within 3 days after birth), D4-60 (death between 4 and 60 days), D61-90 (death between 61 and 90 days), and D0-90 (death within 90 days). Logistic regression models were used to evaluate the risk factors associated with PWM traits. Bayesian threshold models and Gibbs sampling were used to estimate the genetic parameters. Birth weight, season, litter size, sex, dam age, breed, and heterosis were found to be significantly associated with at least one of the PWM traits. Heritability estimates were 0.263, 0.124, 0.080, and 0.207, for D0-3, D4-60, D61-90, and D0-90, respectively. The genetic correlations between the studied traits ranged from 0.892 (D0-3 and D0-90) to 0.999 (D0-3 and D61-90). These results suggest that PWM in goats is influenced by both non-genetic and genetic factors and can be reduced by management, genetic selection, and crossbreeding approaches.

Hand tracking enables controller-free interaction with virtual environments, which can, compared to traditional handheld controllers, make virtual reality (VR) experiences more natural and immersive. As naturalness hinges on both technological and user-based features, fine-tuning the former while assessing the latter can be used to increase usability. For a grab-and-place use case in immersive VR, we compared a prototype of a camera-based hand tracking interface (Leap Motion) with customized design elements to the standard Leap Motion application programming interface (API) and a traditional controller solution (Oculus Touch). Usability was tested in 32 young healthy participants, whose performance was analyzed in terms of accuracy, speed and errors as well as subjective experience. We found higher performance and overall usability as well as overall preference for the handheld controller compared to both controller-free solutions. While most measures did not differ between the two controller-free solutions, the modifications made to the Leap API to form our prototype led to a significant decrease in accidental drops. Our results do not support the assumption of higher naturalness for hand tracking but suggest design elements to improve the robustness of controller-free object interaction in a grab-and-place scenario.