This work investigated the isothermal holding time dependence of the densification, microstructure, weight loss and tensile properties of Fe-Mn-Si powder compacts. Elemental Fe, Mn and Si powder mixtures with a nominal composition of Fe-28Mn-3Si (in weight percent) were ball milled for 5h and subsequently pressed under a uniaxial pressure of 400 MPa. The compacted Fe-Mn-Si powder mixtures were sintered at 1200 ℃ for 0, 1, 2 and 3 h, respectively. In general, the density, weight loss and tensile properties increased with the increase of isothermal holding time. A significant increase in density, weight loss and tensile properties occurred in the compacts isothermally holding for 1 h, as compared to those with no isothermal holding. However, further extension of isothermal holding time (2 and 3 h) only played a limited role in promoting the density and tensile properties. The weight loss of the sintered compacts was mianly caused by the sublimation of Mn in Mn depletion region on the surface layer of the sintered Fe-Mn-Si compacts. The length of the Mn depletion region increased as isothermal holding time increased. A single α-Fe phase was detected on the surface of all the sintered compacts, and the locations beyond the Mn depletion region were comprised of a dual dominant γ-austenite and minor ε-martensite.

This study aimed to explore the fermentation behavior of selected potential probiotic strains during sorghum fermentation, considering their microbial counts, pH levels, and antibacterial activity, their ability to break down starch. The fermentation processes were conducted in the presence and absence of glucose, and the lactic acid bacterial strains underwent controlled fermentation to assess microbial counts, amylase activity, pH, and lactic acid levels in the presence and absence of glucose. In addition, the inhibitory activity of these potential probiotic strains against pathogenic bacteria (Salmonella typhimurium, Escherichia coli, and Staph-ylococcus aureus) was examined through co-culturing. The results demonstrated that all nine Lactobacillus strains exhibited robust growth in both sugar and sugar-free fermentation experiments. Glucose supple-mentation significantly enhanced lactic acid yield which was in a range of 0.19-0.52 % compared to fer-mentation without glucose with a range of 0.03-0.29 %. The selected Lactobacillus strains effectively lowered the pH to less than 4 after 24 hours, producing substantial lactic acid. Notably, in the absence of glucose, only Lb. helveticus D7 and Lb. amylolyticus D12 achieved pH levels below 4 after 8 hours, producing the highest lactic acid amounts of 0.27 and 0.29 % after 24 hours, respectively. Amylase activity was detected on two strains D7 and D12. Furthermore, most of the tested Lactobacillus strains demonstrated complete inhibition of pathogen growth after 24 hours of co-culturing, suggesting their potential for enhancing the safety quality of sorghum-based fermented products.

Background/Objectives: The global push to eliminate tuberculosis (TB) as a public health threat is in-creasingly urgent, particularly in high-burden areas like O.R. Tambo District Municipality, South Africa. Drug-resistant TB (DR-TB) poses a significant challenge to TB control efforts and is a leading cause of TB-related deaths. This study aimed to assess DR-TB transmission patterns and predict future cases using geospatial and predictive modeling techniques. Methods: A retrospective cohort study was conducted across five decentralized DR-TB facilities in O.R. Tambo District Municipality from January 2018 to De-cember 2020. Data were obtained from Statistics South Africa, and patient GPS coordinates were used to identify clusters of DR-TB cases via DBSCAN clustering. Hot Spot Analysis (Getis-Ord Gi) was performed, and two predictive models (Linear Regression and Random Forest) were developed to estimate future DR-TB cases. Analyses were conducted using Python 3.8 and R 4.1.1, with significance set at p < 0.05. Results: A total of 456 DR-TB patients were enrolled, with 56.1% males and 43.9% females. The mean age was 37.5 (±14.9) years. The incidence of DR-TB was 11.89 cases per 100,000 population, with males dispropor-tionately affected. Key risk factors included poverty, lack of education, and occupational exposure. DR-TB types included RR-TB (60%), MDR-TB (30%), Pre-XDR-TB (5%), XDR-TB (3%), and INHR-TB (2%). Spatial analysis revealed significant clustering in socioeconomically disadvantaged areas. A major cluster was identified, along with a distinct outlier. Predictive models indicated differing trends, with the Random Forest model predicting stabilization at 30 cases per year by 2022, while the Linear Regression model projected a decline to zero by 2026. Conclusions: The study highlights the need for targeted interventions in vulnerable populations to curb DR-TB transmission and improve treatment outcomes.

Public-Private Partnerships (P3 or PPPs) have been utilized and studied more frequently over the past couple of decades for both infrastructure projects and building development projects. Based upon the records of the outcomes of these projects there is a plethora of data that demonstrates the benefits and challenges that this delivery method poses. As the name suggests, these partnerships allow for public goals to become realized while also providing opportunities for the private sector to gain business success. These two often divergent interests are finding mutual benefit but the process of compromises also comes with some disadvantages that should be understood in order to make decision of whether the risk/reward equation works for all stakeholders. In particular, this paper will focus on how PPPs affect the construction aspects of projects and will assert how to understand the risks and evaluate the benefits from a construction perspective.

Analysis of land use/land cover (LULC) in the catchment areas is the first action toward safeguarding the freshwater resources. The LULC information in the watershed has gained popularity in the natural science field as it helps water resource managers and environmental health specialists develop natural resource conservation strategies based on available quantitative information. Thus, remote sensing is the cornerstone in addressing environmental-related issues at the catchment level. In this study, the performance of four machine learning algorithms (MLAs), such as Random Forests (RF), Support Vector Machine (SVM), Artificial Neural Networks (ANN), and Naïve Bayes (NB) was investigated to classify the catchment into nine relevant classes of the undulating watershed landscape using Landsat 8 Operational Land Imager (L8-OLI) imagery. The assessment of the MLAs were based on the visual inspection of the analyst and the commonly used assessment metrics, such as user’s accuracy (UA), producers’ accuracy (PA), overall accuracy (OA), and kappa coefficient. The MLAs produced good results, where RF (OA= 97.02%, Kappa= 0.96), SVM (OA= 89.74 %, Kappa= 0.88), ANN (OA= 87%, Kappa= 0.86), and NB (OA= 68.64 Kappa= 0.58). The results show the outstanding performance of the RF model over SVM and ANN with a small margin. While NB yielded satisfactory results, which could be primarily influenced by its sensitivity to limited training samples. In contrast, the robust performance of RF could be due to an ability to classify high-dimensional data with limited training data.

Droughts have negative impacts on agricultural productivity and economic growth. Effective monitoring and accurate forecasting of drought occurrences and trends are crucial for minimizing drought losses and mitigating their spatial and temporal effects. In this study, trend dynamics in monthly total rainfall time series measured at Cape Town International Airport were analyzed using Mann-Kendall (MK) test, Modified Mann-Kendall (MMK) and innovative trend analysis (ITA) were examined. Additionally, we utilized hybrid prediction method that combined the model with the complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) technique, the autoregressive integrated moving average (ARIMA) model, the long short-term memory (LSTM) network (i.e. CEEMDAN-ARIMA-LSTM) to forecast SPI values of 6-, 9-, and 12-months using rainfall data between 1995 and 2020 from Cape Town International Airport meteorological rainfall stations. The results demonstrate the following essential points: (1) The trend analysis results of the total monthly rainfall values indicate a significant decreasing trend with the negative z-score (MK= -3.7541 and MMK= - 4.0773). ITA also indicated a significant downwards trend of rainfall in the study area. (2) As the forecasting horizon increases, the prediction accuracy of the models and CEEMDAN-combined models gradually improves, reaching their optimum performance at the 12-month horizon. (3) CEEMDAN efficiently stabilizes time-series data, resulting in greater prediction accuracy in the hybrid model compared to individual models at all timescales. (4) The RMSE and R2 values for the hybrid CEEMDAN-ARIMA-LSTM model at a 12-month forecasting horizon are 0.042 and 0.995, demonstrating the applicability of this hybrid approach for drought forecasting.

Chronic kidney disease (CKD) bears a heavy burden on patients and the health care system as whole. The incidence of CKD has been increasing in the Arab world over the years due to increases in Diabetes and hypertension which are the most prominent causes of CKD. Syrians are at higher risk for diabetes and hypertension due to the crisis that the country has been going through. 297 patients’ charts were examined in the kidney surgical hospital in Damascus Syria to determine risk factors for CKD, prevalence of diabetes among them and its associating demographic factors along with changes in serum creatinine, urea, fasting blood glucose levels and MDRD score among diabetic CKD patients. 64.6% of patients were above 50, 61.6% were males and 35.4% were diabetic. Patients with diabetes had lower creatinine levels upon admission than non-diabetics. The correlation between fasting blood glucose level and serum creatinine, urea and MDRD was not statistically significant. This paper shows that the prevalence of diabetes among CKD patients is similar in Syrians to the rest of the world despite the increase of diabetes incidence.

Tuberculosis (TB) remains a global health threat, necessitating innovative strategies for control and prevention. This comprehensive review explores the Mycobacterium tuberculosis Lysine Exporter (LysE) gene, unveiling its multifaceted roles and potential uses in controlling and preventing tuberculosis (TB). As a pivotal player in eliminating excess L-lysine and L-arginine, LysE contributes to the survival and virulence of M. tuberculosis. This review synthesizes findings from different electronic databases and includes 13 studies focused on the LysE of M. tuberculosis. The research unveils that LysE can be a potential drug target, a diagnostic marker for TB, and a promising candidate for vaccine development. The absence of LysE in the widely used BCG vaccine underscores its uniqueness and positions it as a novel area for TB prevention. In conclusion, this review underscores the significance of LysE in TB pathogenesis and its potential as a drug target, diagnostic marker, and vaccine candidate. The multifaceted nature of LysE positions it at the forefront of innovative approaches to combat TB, calling for sustained research efforts to harness its full potential in the global fight against this infectious disease.

Background: Corticosteroids (CS) are crucial for managing various medical conditions, but long-term use is associated with significant risks. Balancing the therapeutic benefits and potential hazards requires careful prescription and monitoring. This study explores Jordanian physicians' knowledge, experiences, and concerns regarding CS prescriptions. Methods: This was a cross-sectional study conducted between March and August 2023, using an online link distributed using social media platforms. Results: A total of 171 physicians enrolled in the study were predominantly male, with a median age of 31 years. Two-thirds worked in central Jordan, and one-third were general practitioners. The majority (86.5%) had experience both in topical (83.1%) and injectable (81.1%) dosage forms. Physicians demonstrated high knowledge (median score 11/11) and major concerns (median fear score 3.5/5) about CS. Major worries included the risk of osteoporosis (73.7%) and hyperglycemia (66.7%). Sociodemographic factors did not significantly impact their knowledge or fears. Conclusion: Our study showed that physicians have a high knowledge level about CSs but have major concerns about CS side effects, particularly osteoporosis and hyperglycemia. These findings highlight the need for targeted interventions to address these fears, enhancing physician confidence and improving patient management outcomes.

The preparation of gold nanoparticles (AuNPs) involves a variety of chemical and physical methods. These methods use toxic and environmentally harmful chemicals. Consequently, the synthesis of AuNPs using green chemistry has been under investigation to develop eco-friendly nanoparticles. One method to achieve this is the use of plant-derived phytochemicals capable of reducing gold ions to produce AuNPs. The aim of this study was to implement a facile microtitre-plate method to screen a large number of aqueous plant extracts to determine the optimum concentration (OC) to bio-synthesize the AuNPs. Several AuNPs of different sizes and shapes were successfully synthesized and characterized from seventeen South African plants. The characterization was done using Ultra Violet-Visible Spectroscopy, Dynamic Light Scattering, High Resolution Transmission Electron Microscopy and Energy-Dispersive X-ray Spectroscopy. We also studied the effects of temperature on the synthesis of the nanoparticles and measured its effect on the particle size of the synthesized AuNPs and the data showed that changes in temperatures affect the size and dispersity of the generated AuNPs. Further, some of the synthesized AuNPs were stable upon incubation with different biological solutions in vitro.

With increased vulnerabilities and vast technology landscapes, it is extremely critical to build systems which are highly resistant to cyber-attacks, to break into systems to exploit. It is almost impossible to build 100% secure authentication & authorization mechanisms merely through standard password / PIN (With all combinations of special characters, numbers & upper/lower case alphabets and by using any of the Graphical password mechanisms). The immense computing capacity and several hacking methods used, make almost every authentication method susceptible to cyber-attacks in one or the other way. Only proven / known system which is not vulnerable in spite of highly sophisticated computing power is, human brain. In this paper, we present a new method of authentication using a combination of computer’s computing ability in combination with human intelligence. In fact this human intelligence is personalized making the overall security method more secure. Text based passwords are easy to be cracked ^[6]. There is an increased need for an alternate and more complex authentication and authorization methods. Some of the Methods ^{[7] [8]} in the category of Graphical passwords could be susceptible, when Shoulder surfing/cameras/spy devices are used.

In many parts of the Asia, particularly in the arid regions of the middle east the date palm i.e. Phoneix dactylifera L. is considered a significant plant both culturally and economically. Over the past decade numerous biotechnological tools have been applied to revolutionize the date palm research and its cultivation process. In this comprehensive review ,we provided the in depth overview of the cutting edge developments in the date palm biotechnology, mentioning the important areas such as genomics, genetic engineering, in vitro propagation, omics technologies, and the integration of the artificial intelligence and machine learning (AI-ML).Due to these advancements ,in the date palm production how the date palm production lead the production of superior date palm cultivars with the improved yield ,fruit quality and resilience to biotic and abiotic stresses. Also it explores the application of the biotech tools in the enhancing pest and disease management strategies, increasing date palm productivity and developing the date palm based bio-factories for the production of high value compounds. This review highlights the current challenges faced by the date palm industries ,including the limited water resources ,genetic erosion , pests and disease and the need for improved postharvest handling and processing. It examines how these tools coupled with AI-based approaches can be leveraged to address these challenges and ensure the long term sustainability of date palm cultivation.

Organisational performance is a major concern for any company wishing to remain competitive in today's market. This is why many companies have begun to integrate digital technologies into their management systems. The aim of this article is to determine the contribution of digitisation to organisational performance management, through observations and analysis of a single case study of a company that has adopted a digital transformation project. It emerged that digital transformation makes a significant contribution to organisational performance management. However, this transformation requires significant support and adaptation of skills and organisational structures.

Private Set Intersection (PSI) is a cryptographic method in secure multi-party computation that allows entities to identify common elements in their datasets without revealing their private data. Traditional approaches assume similar-sized datasets and equal computational power, overlooking practical imbalances. In real-world applications, dataset sizes and computational capacities often vary, particularly in the Internet of Things and mobile scenarios where device limitations restrict computational types. Traditional PSI protocols are inefficient here, as computational and communication complexities correlate with the size of larger datasets. Thus, adapting PSI protocols to these imbalances is crucial. This paper explores unbalanced PSI scenarios where one party (the receiver) has a relatively small dataset and limited computational power, while the other party (the sender) has a large amount of data and strong computational capabilities. It introduces three innovative solutions for unbalanced PSI: unbalanced PSI protocol based on Cuckoo filters, unbalanced PSI protocol based on single cloud assistance, and unbalanced PSI protocol based on dual cloud assistance, each addressing the shortcomings of the previous solution. These protocols primarily optimize database computational load, storage capacity, protocol execution time, and security. Depending on performance and security needs, different protocols can be employed for applications such as private contact discovery.

Introduction: It has long been accepted that trauma is one of the most important and frequent predisposing factors for onychomycoses . However, the role of direct trauma in the pathogenesis of fungal nail infections was only recently been elucidated in a series of 32 cases of post-traumatic single-digit onychomycosis. The importance of repeated trauma due to foot and toe abnormalities was rarely investigated.Aim of the study: This is a multicenter single-author observational study over a period of 6 years performed at a specialized nail clinic in three countries. All patient photographs taken by the author during this period were screened for toenail alterations and all toe onychomycosis cases were checked whether they contained enough information to evaluate potential foot and toe abnormalities. Particular attention was paid to the presence of hallux valgus, hallux valgus interphalangeus, hallux erectus, inward rotation of the big toe and outward rotation of the little toe, as well as splay foot. Only cases with unequivocal proof of fungal nail infection by either histopathology, mycologic culture or polymerase chain reaction (PCR) were accepted.Results: Of 1653 cases, 185 were onychomycoses proven by mycologic culture, PCR or histopathology. Of these, 179 involved at least one big toenail, 6 affected one or more lesser toenails. Three patients consulted us for another toenail disease and the onychomycosis was diagnosed as a second disease. Eight patients had a pronounced tinea pedum. Relatively few patients had a normal big toe position (n = 9). Most of the cases had a mild to marked hallux valgus (HV) (105) and a hallux valgus interphalangeus (HVI) (143), hallux erectus was observed in 43 patients, the combination of HV and HVI was observed 83 times. Discussion: The very high percentage of foot and toe deformations was surprising. It may be hypothesized that this is not only a pathogenetically important factor but may also play an important role for the localization of the fungal infection as no marked hallux deviation was noted in onychomycoses that affected the lesser toes only. As the management of onychomycoses is a complex procedure involving the exact diagnosis with determination of the pathogenic fungus, the nail growth rate, the type of onychomycosis, its duration and predisposing factors, anomalies of the toe position may be important. Among the most commonly mentioned predisposing factors are peripheral circulatory insufficiency, venous stasis, peripheral neuropathy, immune deficiency and iatrogenic immunosuppression whereas foot problems are not given enough attention. Unfortunately, many of these predisposing and aggravating factors are difficult to treat or to correct. Generally, when explaining the treatment of onychomycoses to the patients, the importance of these orthopedic alterations is not or only insufficiently discussed. In view of the problems encountered with the treatment of toenail mycoses, this attitude should be changed in order to make the patient understand why there is such a low cure rate despite excellent minimal inhibitory drug concentrations in the laboratory.

This study aimed at characterizing the composition and performing chemical speciation modelling to determine species that are abundant in the coal fly ash (CFA) and soil samples sourced from Hendrina Power station located in Mpumalanga Province. All CFA samples were alkaline in nature with pH values ranging between 8.11 ± 0.07 and 8.60 ± 0.03 with an electrical conductivity (EC) ranging between 301.70 and 1515.00 µS/cm while EC of control soil was 103.10 µS/cm. The control soil pH was found to be 6.24 ± 0.13 and total organic carbon values ranged between 2.68 and 85.82 mg/kg and some percentage organic carbon values of CFAs were found to be greater than 8%, which is above the permissible limits of hazardous waste dumping. Oxidation-reduction potential values were negative in all CFA samples and positive in soil. The speciation modelling showed that the potential for a trace metal to have hazardous effects in soil systems depends on its concentration, specific form and interactions with other constituents in CFA. The slow release of metals from CFA to soil was assessed by looking at how a given metal is distributed throughout its several possible chemical forms. The presence of divalent cations (Pb2+, Cu2+, Zn2+, etc.) in CFAs might pose a threat to soil quality. In the competition for binding sites on ferric hydroxides, dissolved metal ions faced off against other metals. Protons (H+) were seen to be in competition with Pb, Cu and Zn for the ability to bind to hydroxyl (OH-) groups and this is due to chemical precipitation and surface complexation.

Debates regarding human capital disclosure (HCD) emphasise the usefulness of people-related information in stimulating investor confidence and building stakeholder trust. Despite this, human capital (HC) information is interwoven in most international sustainability reporting standards such as the global reporting initiative (GRI), thereby concealing the impact of human resource (HR) practices in shareholder value creation. The aim of this study is to develop a taxonomy to assess HCD in the sustainability reports to capture the true value of HC distinctively. A content analysis-based study with a deductive approach was followed by utilising the GRI standards to isolate and classify people-related information into an HCD sustainability taxonomy. 40% HC metrics were extracted from the GRI standards and subsequently classified into 7 dimensions, namely, human capital allocation, human capital wellbeing, human capital investment, human capital network, human capital governance, human capital risk and human capital earnings. Furthermore, 40 GRI content indexes of the companies listed in the Johannesburg Stock Exchange (JSE) revealed that most disclosures are covered in the human capital governance and human capital earnings categories. HCD sustainability provides investors and HR professionals with a useful tool to assess people-related information from the sustainability reports for isolating the true value of HC.

A 2-month incubation study was carried out using two soil types to determine nitrogen mineralization of different inorganic-organic amendments. The following seven treatments (T) were established; T1 = control, T2 = 5 g of dry algae per kg of soil (100%DA), T3 = 136g of agri-mat per kg of soil (100%GA), T4 = 61 g of ground grass per kg of soil (100%GG), T5 = 2.5 g of dry algae + 2.5 g of nitrogen fertilizer (NF) per kg of soil (50%DA50NF), T6 = 50%GA50NF, T7 = 50%GG50NF. Three samples per treatment were drawn at 0, 3, 7, 15, 30, 45, and 60 days for mineral-N determination. A 2-month glasshouse experiment was established afterwards with the following five treatments: T1 = Control, T2 = 50%DA, T3 = 50%GA, T4 = 50%GG, and T5 = 100NF. The results indicated that nitrogen mineralization was significantly higher in organic-inorganic amendments compared to sole organic amendments. The percentage differences ranged from 157% to 195%. The 50%DA treatment increased spinach yield by 20.6% in sandy loam and 36.5% in loam soil. It is difficult to fully recommend the 50%DA treatment without field-scale evaluation, but it is a promising option to be considered.

Aim: Ovarian cancer is the leading cause of gynecological cancer deaths worldwide. Treatment methods are listed as surgery, chemotherapy and radiotherapy depending on the stage of the cancer, but developing resistance to chemotherapy increases the need for alternative agents that act on the same pathways. In this study, the effects of rosmarinic acid (RA) and doxorubicin (DX) on the activation of FOXP3, an important tumor suppressor gene, in OVCAR3 cells were examined. Material Method: In the study, human ovarian adenocarcinoma cell line was used. MTT test was applied to determine the effect of rosmarinic acid and doxorubicin on the proliferation of OVCAR3 cells. Expression levels of FOXP3 for cell proliferation and Capase-3 for Apoptosis were determined by qRT-PCR and Western blot analysis. Wound healing model was applied to determine metastasis. The results were evaluated with one-way ANOVA in SPSS 20.0 program as p≤0.05. Results: It was determined that rosmarinic acid alone and in combination with doxorubicin inhibited the proliferation of OVCAR3 cells in a time- and dose-dependent manner for 24, 48 and 72 hours, and caused the cells to die by causing them to undergo apoptosis. It was observed that Caspase-3 expression increased approximately tenfold in OVCAR3 cells, while FOXP3 expression increased only in RA treatment and was downregulated in DX and RA+DX treatments. Coclusion According to the results of our study, it was observed that many steps of the signaling pathways related to proliferation, migration and apoptosis were affected by the combination of RA and DX in OVCAR3 cells. This shows that RA will gain an important place in cancer treatment with more comprehensive studies.

Aim: Ovarian cancer is one of the most frequently diagnosed cancers in women in the world. Recognition of the differences between tumors in cancers and resistance to treatment in patients have made the treatment potential of chemotherapy, radiotherapy and immunotherapy controversial. Especially against drug resistance, laboratories have implemented the drug diversion system by putting old drugs into new forms. In this study, the cytotoxic and apoptotic effects of the combination of doxorubicin (DX) and thymoquinone (TQ) on ovarian adenocarcinoma cells (OVCAR3) were investigated. Material Method: OVCAR3 cell line was cultured in RPMI medium containing 10% FBS, 1% penicillin/streptomycin. Cell viability and cell growth rate were determined by MTT viability test by combining doxorubicin and thymoquinone. Nucblue immunofluorescent staining was used to determine the mechanism of cell death at different doses of doxorubicin and thymoquinone compounds, qRT-PCR to determine the pathways underlying the apoptotic mechanism, and western blot methods to show protein levels. Result: We found that the combination of DX and TQ reduced the viability of OVCAR3 cells (MTT assay), induced apoptosis (RAF, RAS, Bcl2, Bax by qRT-PCR) and increased RAF, RAS protein levels in TQ and DX-treated cells by western blot analysis. Conclusion: The results obtained revealed for the first time that combining DX and TQ also had cytotoxic/apoptotic and anti-proliferative effects against ovarian adenocarcinoma cells.

Since the mid-1990s probiotics have been proven to support the treatment of several gastrointestinal diseases. Additionally, probiotics have been taken as a common panacea for civilization diseases. To date, the only probiotic yeasts with evidence of health-promoting effects are Saccharomyces cerevisiae var. boulardii. The probiotic properties are strain-dependent, whereby it is crucial to develop methods to verify the probiotic-enriched food authentication including the growing number of dietary supplements with simplified commercialisation procedures. Due to the significant genetic similarity of S. cerevisiae var. boulardii to S. cerevisiae, qPCR-HRM analysis was tested, which has a very high sensitivity for polymorphism detection and enables simultaneous identification of the microorganism in the presence of the reference sample. The effectiveness of interspecies primer pairs and intragenus primer pairs designed to amplify heterogeneous regions was examined. HRM analysis using primers for 18SrRNA and ITS allowed for identification of S. cerevisiae var. boulardii at the species level. S. cerevisiae var. boulardii was efficiently identified at the variety level with amplification of HO and RPB2 in the single- and multi-component DNA extracts. The RPB2 amplicon showed the highest intraspecies differentiation power. The predominance of S. cerevisiae var. boulardii in the mixtures tested was crucial for identification using qPCR-HRM analysis and quantitatively corresponded to the strain content in the probiotic-enriched food matrices.

This study investigates the complex role of financial risks in the context of public–private partnerships (PPPs) in India and their relationship to the amount and extent of investments made by private partners (s). We hypothesize that subsidies, bid criteria, and risk have a positive relationship with investments made by private partners. A project’s leverage moderates these relationships. Regression was used to analyze the hypotheses using SPSS 24 and PROCESS Macro. Data from the World Bank were collected from 2009 to 2019 for the study variables. Interestingly, our research finds support for these relationships that may seem contrary to some commonly-held notions of risk relationships, such as – the government using ‘viability gap’ funding to attract private investment and ‘leverage’ does not moderate the relationship between risk assumed and private investment. This study is among the first to recognize and elaborate on financial risk relationships, specifically in the context of Indian PPPs. These findings are significant for both private and public participants in terms of financial considerations in PPP projects, especially in emerging markets.

This paper explores the application of the generalized double reduction method to the (1+1)-dimensional Kaup-Boussinesq (K-B) system, which models nonlinear wave propagation. Double reduction method is a structured and systematic approach in the analysis of partial differential equations (PDEs). We first identify the Lie point symmetries of the K-B system and construct four non-trivial conservation laws using the multiplier method. The association between the Lie point symmetries and the conservation laws is established, and the generalized double reduction method is then applied to transform the B-K system into second-order differential equations or algebraic equations. The reduction process allowed us to derive two exact solutions for the K-B system, illustrating the method’s effectiveness in handling nonlinear systems. This work highlights the effectiveness of the generalized double reduction method in simplifying and solving nonlinear nonlinear systems of PDEs, contributing to a deeper understanding of the systems.

Exogenous melatonin, a nutraceutical for maintaining a healthy sleep-wake cycle and managing sleep disorders, requires large, repeated doses due to low bioavailability and short half-life. This necessitates the development of a sustained-release formulation with a longer half-life and sustained plasma concentration. Therefore, exogenous novel 5 mg sustained-release melatonin capsules (Melatonin-SR, test product) were formulated. This open-label cross-over study compared the pharmacokinetics (maximum concentration [Cmax], time to reach Cmax [Tmax], area under the curve [AUC] and elimination half-life [t1/2]) and safety of Melatonin-SR with 5 mg immediate-release melatonin capsules (Melatonin-IR, reference product) after single-dose oral administration in healthy fasting adults. Sixteen participants (aged 18-45 years) were randomized (1:1) to receive either Melatonin-SR or Melatonin-IR in two periods with a 7-day washout period. Melatonin-SR reported lower Cmax (11446.87 pg/mL) compared to Melatonin-IR (22786.30 pg/mL). The mean Tmax of Melatonin-SR and Melatonin-IR was 1.26 h and 0.87 h, respectively. The mean t1/2 of Melatonin-SR (5.10 h) was prolonged by five-fold compared to Melatonin-IR (1.01 h). One adverse event (vomiting) was reported following administration of the Melatonin-IR. Melatonin-SR resulted in higher and sustained plasma melatonin concentrations for an extended period and was well-tolerated. Hence, Melatonin-SR may be a promising nutraceutical for maintaining healthy sleep.

The Internet of Things (IoT) has become one of the most attractive domains nowadays. It works by creating a special network between physical devices such as vehicles, home equipment, and other items. In recent days, the common technologies of communication such as Wi-Fi and 2G/3G/4G cellular are insufficient for the IoT networks because they are designed to serve appliances with immense processing capabilities such as laptops and PCs. Moreover, most of these technologies are centralized and use an existing infrastructure. Currently, the new communication technologies such as Z-Wave, 6LowPAN, and Thread are dedicated to the IoT and have been developed to meet its requirements. These technologies can handle many factors such as range, data requirements, security, power demands, and battery life. Nevertheless, the security issues in IoT systems have major concerns and matters because vulnerabilities in such systems may result in fatal catastrophes. In this paper, an enhanced IoT security framework for authentication and authorization is proposed and implemented to protect the IoT protocols from different types of attacks such as man-in-the-middle attack, reply attack, and brute force attack. The proposed framework combines an enhanced token authentication that has identity verification capabilities and a new sender verification mechanism on the IoT device side based on time stamp, which in turn can mitigate the need for local identity verification methods in IoT devices. The proposed IoT security framework is tested using security analysis with different types of attacks compared with previous related frameworks. The analysis shows the high capability of the proposed framework to protect IoT networks against many types of attacks compared with current available security frameworks. Finally, the proposed framework is developed using Windows application to simulate the framework phases, check its validity through the real network, and calculate the payload time is adds.

The effect of land use on sandy soils of southern Botswana was carried out by comparing the composition and properties of soil organic matter. Virgin and disturbed soils were sampled from savanna ecosystems (Central District and Kweneng District). The biodegradability of organic matter was evaluated by incubation in the laboratory. Humic fractions were quantified and humic acids were analyzed by visible and infrared spectroscopy. The results indicate that continued disturbance, whether due to grazing or subsistence farming, has resulted in small significant changes in the concentration of available nutrients and organic matter in the soil. Nevertheless, substantial changes could be established in soil C/N ratio, humic acid/fulvic acid ratio and in the biodegradability of soil organic matter and the structural characteristics of humic acids. The increased aromaticity of humic acid (visible and IR spectroscopies) following disturbance, suggests increased biogeochemical activity and/or the impact of abiotic processes (such as periodic fires) selectively removing aliphatic constituents. The overall results indicate a low potential soil fertility, the sustainable preservation of which depending more on features related to quality than to the total amount of the soil organic matter, which shows considerable aromatization parallel to its degree of association with the mineral fraction.

Globally, 77\% of the elderly aged 65 and above suffer from multiple chronic ailments, according to recent research. However, several barriers within the healthcare system in the developing world hinder the adoption of home-based patient management. IoMT is beneficial for healthcare personnel, but its application raises security concerns, particularly in authentication. Several authentication techniques have been proposed which, however, lack a balance of security and usability. By analyzing the shortcomings of the existing authentication methods and the available sensors on smartphones, this paper proposes to explore the possibility of using a smartphone’s embedded sensors for elderly user identification process in IoMT. We proposed an adaptive authentication technique for the elderly patients using the MAPE-K$_{\text{HMT}}$ framework by developing an android application that takes as input, the user’s contextual information including device fingerprint, location, network, and user data to monitor the user and estimate the risk associated with a user using the Naïve Bayes algorithm. The risk score was then used as input to the rule-based module that assigned authenticators according to user age, health condition and available authenticators. The model demonstrated high accuracy in distinguishing between authorized and unauthorized access attempts and supported the usable security goal for the elderly users.

The integration of drone technology into healthcare logistics presents a significant opportunity to enhance the speed, reliability, and efficiency of medical sample transportation. This study inves-tigates the current advancements in drone technology, focusing on its application in the rapid and secure delivery of medical samples, particularly in urban and remote regions where traditional transportation methods often face challenges. Utilizing a combination of recent technological de-velopments such as AI-driven navigation systems, real-time monitoring, and secure payload management, the study examines how drones can mitigate logistical barriers like traffic conges-tion and geographical isolation. The research methodology includes a comprehensive review of recent case studies from various regions, illustrating the practical applications and benefits of drones in healthcare. The results demonstrate a substantial reduction in transportation time and costs, along with improved accessibility to healthcare services in underserved areas. The study concludes that, while challenges such as regulatory hurdles and privacy concerns remain, the on-going advancements in drone technology and supportive regulatory frameworks have the poten-tial to revolutionize medical logistics, ultimately improving patient outcomes and healthcare de-livery.

Hard tissue apposition along the root canal walls is a slow, normally occurring physiological aging process. In response to tooth wear, local deposition of hard tissue may also occur in the pulp at a slow pace. Sometimes, the rate of hard tissue deposition acceleration may seem to be uncontrolled after dental trauma, autotransplantation, and orthodontic therapy, leading to rapid partial or total obliteration of the root canal space. This situation is called calcific metamorphosis (CM) or pulp canal obliteration (PCO). Although the incidence of pulpal necrosis in these teeth is believed to be infrequent, conventional endodontic therapy in severely calcified canals poses extreme difficulties and a higher risk for procedural accidents. This article aims to review the available approaches for the predictable negotiation of calcified canals and to introduce the buckling resistance activation test (BRAT) technique.

A Wireless Body Area Network (WBAN) is a network of wirelessly connected sensing and actuating devices. WBANs used for recording biometric information and administering medication are classified as part of a Cyber Physical System (CPS). Preserving user security and privacy is a fundamental concern of WBANs, which introduces the notion of using biometric readings as a mechanism for authentication. Extensive research has been conducted regarding the various methodologies (e.g. ECG, EEG, gait, head/arm motion, skin impedance). This paper seeks to analyze and evaluate the most prominent biometric authentication techniques based on accuracy, cost, and feasibility of implementation. We suggest several authentication schemes which incorporate multiple biometric properties.

Dye-sensitized solar cells (DSSCs) belong to the group of thin-film solar cells which have been extensively researched for over two decades due to their low cost of fabrication, flexibility and ability to function under low-light conditions. Some issues have to be addressed in terms of energy losses, material integration, weak photocurrent generation and stability to improve the performance of DSSCs. One of the approaches to enhance the performance of DSSCs is through luminescent materials. These are materials which can absorb light and re-emit at different wavelengths which can be used to convert ultraviolet (UV) and near infra-red (NIR) light that are not efficiently utilized by the DSSCs, into visible light that can be absorbed. The main objective of this article is to provide a comprehensive review on the impact of luminescent materials in DSSCs. Research interest in luminescent materials particularly, down conversion, up conversion and quantum dots were analyzed from the “Web of Science”. It reflected a remarkable number of over 200, 000 publications in the past decade. Therefore, the state of the art of luminescent materials for enhancing the performance of the solar cells were reviewed, which showed significant potential in enhancing the performance of DSSCs.

Unevenly distributed rainfall leads to reduced potato water productivity (WP) under rainfed production. Understanding practices that can increase WP is vital. Objectives were to (i) understand seasonal variables that influence WP under rainfed conditions and (ii) the effect of the integration of cultivar, locality, mulch on potato WP. The study was under two agroecological zones Appelsbosch (Mbalenhle locality), and Swayimane (Stezi, and Mbhava locality), under smallholder. A split plot, in a randomized complete block design experiment, consists of mulching (mulch and not mulch), and selected cultivars. Soil water content (SWC), yield, and climatic conditions were collected, water use (ET) and WP were calculated. Rainfall, ET, and SWC had a significant influence on seasonal WP. Cultivar x mulch x locality had an insignificant effect on WP, however, locality x cultivars significantly altered potato WP. Localities that had lower vapor pressure deficit (VPD), low relative humidity, and sandy soil had higher potato WP of 14.53 kg m-3. The findings suggest that localities that have less atmospheric dryness and cultivars that show stability of yield across seasons can be an easy-to-apply practice for increasing potato WP under a resource-limited environment. Mulch is important when the distribution of intra-annual rainfall does not match crop water requirements.

Abstract: Dispersal strategies of a species can affect its invasion success. Investigation into the dispersal strategies of invasive species in relation to different factors helps our understanding of the invasion mechanisms and provides knowledge for population management and invasion evaluation. Tetranychus ludeni Zacher (Acari: Tetranychidae) is an invasive species, which is native to Europe but now cosmopolitan. Here, we examined the effects of age and density on dispersal in mated females. Our results show that older females with more eggs were more likely to disperse and moved longer distances than younger ones with fewer eggs. Older females spread most of their eggs out of the natal habitats and over longer distances, which reduced competition and increased offspring fitness. Females significantly increased dispersal probability and distance with the increase of population density to avoid crowding. The synchronization of dispersal and reproduction, along with the positive density-dependent dispersal strategy, may facilitate habitat colonization and invasion speed of T. ludeni.

Abstract: Experiments conducted to date to verify the relativistic gravitational time dilation have limited scientific significance because the basic postulate of Einstein’s relativistic GR that the same time (t0) is measured in all non-inertial frames of reference, because all non-inertial frames of reference must be equal, has not yet been verified by time measurements. According to Einstein's relativistic GR, a correlation between time and different gravitational potentials must be the result of a relative relation between non-inertial frames of reference and must not the result of any other physical influence. An experiment that can differentiate between a causal correlation (relative relation) and an apparent correlation (relativistic relation) between time and gravitational potentials is still outstanding. The expressions "relative" and "relativistic" are often used as synonyms. However, Einstein's GR is a relativistic theory. In the case of general relativity, relativistic means that time depends only on the relative relation between non-inertial frames of reference and not on other physical factors. The author proposes an easy-to-realize experiment that is able to distinguish between a causal correlation (relative relation) and an apparent correlation (relativistic relation) between time and gravitational potentials, which can confirm or falsify Einstein's relativistic GR. .

In recent years, technical processes for the sequestration of CO2 through industrial waste mineral carbonation have been explored and developed. There is a large portfolio of Carbon Capture, Uti-lisation and Storage (CCUS) techniques that have been employed on a laboratory and at pilot scale. These include geological storage, ocean storage and mineralisation by carbonate ores. In view of this, the main purpose of this research was to investigate and explore chemical variables, particularly ammonium salts as lixiviants for calcium mineral extraction from iron making slag. The slag in use was acquired from a Steel Mill in the Vaal Triangle Region in Gauteng, South Af-rica. The experimental test work was conducted using different ammonium lixiviants, namely, NH4NO3, NH4Cl and CH3COONH4 to understand the influence of anion type as well as possible differences in mechanisms of interactions. Lixiviant concentration as well as the reaction time were varied in this research study. The three selected ammonium based lixiviants showed different extents of calcium extraction owing to differences in the anion groups. NH4NO3, NH4Cl and CH3COONH4 were found capable of dissolving 50% to 80% of calcium from the selected slag for different molar concentrations. Anion type and leaching time also had significant influences on the leaching of calcium from the slag. Rapid pH degradation resulted in better calcium extraction ca-pabilities. This work has shown that the selected ammonium salts have a potential as lixiviants for calcium dissolution from iron making blast furnace slags. These lixiviants would therefore be important to consider during calcium mineral carbonation for CO2 sequestration.

Background Although the management of the majority of patients with IBS is dealt with by General Practitioners, randomized clinical trials and treatment guidelines are developed mostly in academic settings. Probiotics are one of the most investigated treatment modality for this condition. Scarce information is available as regards GPs attitude in this regard. Methods A literature search was performed to identify papers specifically dealing with probiotic treatment of IBS in the general practice setting. Moreover, the preliminary results of a survey on this topic conducted by the authors among general practitioners in a province in northern Italy are reported. Results Five papers specifically addressing probiotic treatment of IBS in general practice were found. The response rate varied from 4 to 100%. The prescription rate of probiotics by GPs in IBS varied from <10 to 46%, regardless of the patients’ bowel habits. Physicians’ satisfaction with this treatment varied from 20 to 93%. The variability of these results probably depends on factors such as differences in the interpretation of the available data on probiotics use in IBS and traditional/ cultural differences. Moreover, compliance with patient satisfaction, may play a role. Conclusions The reported data on the treatment of IBS with probiotics in general practice is scarce and inhomogeneous, thus it does not allow firm conclusions. It is suggested that the involvement in research on the use of probiotics in IBS of physicians working in general practice would be useful in order to pursue more reliable and useful results, since the majority of the IBS population is followed in general practice and may differ from the one represented in academic clinical trials.

User-generated passwords often pose a security risk in authentication systems. However, providing a comparative substitute poses a challenge, given the common tradeoff between security and user experience. This paper integrates cryptographic methods (both asymmetric and symmetric), steganography, and a combination of physiological and behavioral biometrics to construct a prototype for a passwordless authentication system. We demonstrate the feasibility of scalable passwordless authentication while maintaining a balance between usability and security. We employed threat modeling techniques to pinpoint the security prerequisites for the system, along with choosing appropriate cryptographic protocols. In addition, a comparative analysis is conducted, examining the security impacts of the proposed system in contrast to that of traditional password-based systems. Results from the prototype indicate that authentication is possible within a timeframe similar to passwords (within 2 seconds), without imposing additional hardware costs on users to enhance security or compromising usability. Given the scalable nature of the system design and the elimination of shared secrets, the financial and efficiency burdens associated with password resets are alleviated. Furthermore, the risk of breaches is mitigated, as there is no longer a need to store passwords and/or their hashes. Differing from prior research, our study presents a pragmatic design and prototype that deserves consideration as a viable alternative for both password-based and passwordless authentication systems.

We give three new authentication schemes without secrecy. The first two on finite fields and Galois rings, using Gray map for this link. The third construction is given on Galois rings. The main achievement in this work is to obtain optimal impersonation and substitution probabilities in the schemes. Additionally, in the first and second scheme, we simplify the source space and bring a better relationship between the size of the message space and the key space than the given in [8]. Finally, we provide a third scheme on Galois rings, which generalizes the scheme over finite fields constructed in [9].

Authentication systems based on biometrics characteristics and data represents one of the most important trend in the evolution of our world. In the near future, biometrics systems will be everywhere in the society, such as government, education, smart cities, banks etc. Due to its uniqueness characteristic, biometrics systems will become also vulnerable, privacy being one of the most important challenge. The classic cryptographic primitives are not sufficient to assure a strong level of secureness for privacy. The following work paper represents an effort to present the main cryptographic techniques and algorithms that can give us the possibility to raise a certain level of secureness for privacy. We will show their own challenges (strengths and weaknesses). We will demonstrate how we can use the most common and well-known techniques and algorithms in order to get a maximum efficiency and a high level in assuring the integrity of the biometrics data.

This study examines the evolution of the two-factor authentication method and its adaptability to the online education system. Two-factor authentication is a security measure used especially in areas where information such as banking is valuable. Parallel to technological developments, it has developed as much as daily. It aims to take security one step forward because it is composed of two phases. Today, banking, IOT devices, public transport tickets and many other areas are used. Two-factor authentication methods against security attacks in the field of information are also being updated. In recent years, new technologies such as biometric (iris pattern, retinal pattern, etc.) or behavioral biometry (location tracking, walking information, touch speed etc.) were studied. Instead of physically studying somewhere like going to a course in modern society, online trainings become more advantageous. Most of these online trainings are given certificates such as participation certificate, success certificate, etc. The main problem here is whether the person who is being certified is true. In the study conducted in line with these details, there is a proposal for the application of the Mimic Control Method with Sound Intensity (MCMSI) method for on-line training by examining the two-factor authentication techniques up to the day.

Coal fly ash (CFA) generated from coal-fired power plants (C-FPPs) is continuing to be an environmental health concern due to its potential to contaminate groundwater, surface water, air, and soil, leading to the degradation of land. This study investigated the effectiveness of Helichrysum splendidum Less. for phytoremediation of CFA-polluted sites by conducting pot trials experiments in 14 weeks. Plants of the same age were transplanted into CFA collected from Hendrina Power station to assess their potential in assimilating metallic pollutants (As, Cd, Co, Cu, Mn, Ni, Pb, and Zn) into their tissues and untreated plants were used as controls. Inductively coupled plasma-mass spectrometry was used to quantify the amount of trace elements in samples and the translocation factor (TF) and bioconcentration factor (BCF) were determined to evaluate the phytoremediation potential of Helichrysum splendidum. The results revealed that higher concentrations of As, Ni and Zn were accumulated in the aerial parts as indicated by the TF values greater than 1. In contrast, higher amounts of Cu, As and Zn were found in the roots for CFA grown plants, as demonstrated by their BCF values 1.22, 1.19 and 1.03, respectively. Although CFA medium had restricted growth of some plants as compared to the controls, the results showed an interesting removal efficiency ranging between 18.0 to 56.7% with highest reported for Cu and Zn. Gas exchange analysis revealed that photosynthetic parameters were almost similar in the CFA and control soil pots. The study can confirm that Helichrysum splendidum has phytoextraction and phytostabilization potentials and can be effectively employed for restoration of CFA dams.

Six bacterial strains with differing abilities to produce varying concentrations of Indole Acetic Acid were tested individually and in consortia for plant growth promoting and fitness related traits of Cicer arietinum. In all experiments the presence of the nitrogen fixer Mesorhizobium ciceri resulted in increased biomass production. In the absence of this strain, IAA Psedomonas putida and Bacillus megaterium hinder plant growth and fitness related traits. The application of mixes of the three strains always resulted in better plant performance when M. ciceri was present. Whereas P. putida has a noticeable plant growth-promoting effect B. megaterium resulted less effective. The low levels of IAA produced by the selected strains had a significantly greater positive effect on plant biomass accumulation, flower, pods and seed production as well as on total plant nitrogen and nitrogen concentration in seed than high IAA producer strains.

Generating electricity from coal combustion is highly associated with ongoing pollution problems that negatively impact the environment. Coal fly ash (CFA) is a predominant waste by-product of coal combustion which is disposed of in exposed ash dams constructed in the vicinity of power stations. Its disposal requires a large piece of land and therefore more land is converted to unproductive disposal sites, degrading the ecosystem. This waste material is classified as a hazardous substance in South Africa due to unacceptable levels of inorganic and persistent organic pollutants and its potential for dust creation. CFA is recycled and sold to the building and construction sectors, but the rate of its utilization is far less than the production rate resulting to high volumes that is stockpiled in disposal sites. More than 500 million tons CFA is produced yearly and over 200 million tons yearly remain unused globally and more CFA will continue to be produced due to high consumer energy demands, especially in countries with heavy reliance on coal for power generation. In this context, the paper discusses production of CFA, pollution problems due to its disposal, examines existing gaps within the scope of ash dam restoration processes and presents opportunities offered by phytoremediation (a low-cost and environmentally friendly technology that utilizes plants to restore the degraded environments). Ecological restoration through the use of socio-economically valuable plants (aromatic plants, legumes and grasses) has potential in addressing societal challenges and consequently impacting positively the livelihood of communities.

Satellite-based rainfall estimation products provide a vital alternative source of rainfall data in areas where conventional precipitation measurement is not readily available. In order to facilitate the use of these products there is the need to evaluate their accuracies. This study evaluated the accuracy of three satellite rainfall products; TMPA 3B42RT, TMPA 3B42 and CMORPH in the Pra basin (23,330 km²) of Ghana. The evaluation was through the point-to-pixel method by comparing 0.25°x 0.25° satellite grids to gauged rainfall based on gauge locations and analyzed statistically using correlation coefficient (r), bias and percent bias (pBias) as the performance verification methods. Seven (7) gauge stations with no missing data for the period of 2003-2008 was used in the evaluation. The analysis was based on daily, monthly, annual and seasonal timescales. Our results showed a good correlation between the TMPA products and the gauged data on all timescales considered. The CMORPH on the other hand showed huge overestimation at all gauge locations. The TMPA 3B42 was seen to be the best amongst the three products. The overall rainfall in the basin was well depicted by the TMPA 3B42 and 3B42RT. Although there wasn’t a perfect match between the 3B42RT and 3B42 products and the gauged rainfall, these products can be used to supplement gauged rainfall measurements in the basin and in estimation of rainfall in ungauged basins with similar characteristics.

The study aimed to estimate the prevalence of respiratory symptoms and to assess respiratory health risks associated with Particulate Matter (PM) exposure among the residents of Windhoek, Namibia. Objectives: To measure particulate pollution concentration in Windhoek through monitoring of particulate matter concentration and to identify any associations between particulate pollution, individual location and respiratory health among the Windhoek resident’s. Methods: an adapted standardized self-administered questionnaire was used to collect respiratory health related data as well as previous exposure, while PM monitoring was done using ASTM D1739 reference method. Results: A high prevalence was observed for cough (43%), breathlessness (25%), and Asthma (11.2%). PM was found to be a significant risk factor for episode of cough and phlegm, while high PM exposure category had increased odds ratio for episode of phlegm and cough (OR: 2.5, 95% CI: 0.8-8.0). No association was observed between location and respiratory health outcomes. Conclusion: The study found high levels of PM concentration across all Windhoek suburbs which were above the German, American and EPA. Enactment of legislation relating to the control and monitoring of PM related emissions at point of generation is required at country and city level.

Introduction: intraocular pressure (IOP) measurement is an essential part glaucoma’s diagnosis and follow-up. Goldmann applanation tonometry (GAT) is the gold standard for IOP measurement but it’s affected by many factors like central corneal thickness (CCT). Racial differences in CCT are reported but the Syrian population was never studied. Research design and methods: 57 subjects with 114 eyes visiting Damascus hospital were examined and 100 eyes were included. IOP was measured using GAT and CCT was measured using OCULUS Pentacam AXL Corneal Topography, demographic data and history of ocular surgery, systemic co-morbidities and history of medications were collected. IOP values were corrected for CCT. Results: 56% were males, the mean age was 48.1. 24% of subjects had hypertension. Males had higher CCT with 557.23± 25.33 compared with 531.34 ± 41.88 for females. There was a moderately positive correlation between CCT and IOP (r=0.232, p-0.02), CCT and IOP values were linearly correlated (ANOVA, p=0.02). Conclusions: This study showed that the correlation between CCT and IOP is present in the Syrian population. Males had a slightly thicker corneas than females and CCT didn’t significantly change with age.

The recent COVID-19 pandemic has showcased the implications of using virtual private networks (VPNs) as home-working is now common. Establishing the current state of knowledge on VPNs and their processes is vital. This corroborates an up to date understanding on the fundamentals of VPNs and their usage in today’s society; it informs on how to better use VPNs too. Insight into the security issues VPNs face and possible solutions to these allows for the identification of gaps for potential future research. Addressing these gaps would then indicate how to further improve VPNs, making sure VPNs are indeed beneficial to users.

With the rapid development of intelligent transportation, Vehicle Ad hoc Networks (VANETs) is becoming increasingly important.As a critical component of intelligent transportation systems, the Conditional Privacy-Preserving Authentication (CPPA) scheme plays a significant role in ensuring drivers' privacy and security.However, current CPPA schemes still face limitations in terms of security and efficiency, with these schemes either imposing higher computational overhead for enhanced security or compromising some level of security to reduce overhead. Motivated by this challenge, we propose a CPPA scheme that strikes a better balance between efficiency and security.By leveraging the token mechanism to achieve multiple authentication and minimizing information leakage. Furthermore, our performance analysis demonstrates that our ECC-based algorithm can significantly reduce overhead, with pseudonymous generation requiring only 0.0039ms.

The rapid growth of smartphone financial services raises the need for secure mobile authentication. Continuous authentication is a user-friendly way to strengthen the security of smartphones by implicitly monitoring a user’s identity through sessions. Mobile continuous authentication can be viewed as an anomaly detection problem in which models discriminate between one genuine user and the rest of the imposters (anomalies). In practice, complete imposter profiles are hardly available due to the time and monetary cost, while leveraging genuine data alone yields poor generalized models due to the lack of knowledge about imposters. To address this challenge, we recast continuous mobile authentication as a few-shot anomaly detection problem, aiming to enhance the inference robustness of unseen imposters by using partial knowledge of available imposter profiles. Specifically, we propose a novel deep learning-based model, namely Local Feature Pooling based Temporal Convolution Network (LFP-TCN), which directly models raw sequential mobile data, aggregating global and local feature information. In addition, we introduce a random pattern mixing augmentation to generate class-unconstrained imposter data for the training. The augmented pool enables characterizing various imposter patterns from limited imposter data. Finally, we demonstrate practical continuous authentication using score-level fusion, which prevents long-term dependency or increased model complexity due to extended re-authentication time. Experiments on two public benchmark datasets show the effectiveness of our method and its state-of-the-art performance.

We evaluated the dentofacial characteristics and temporomandibular disorder (TMD) symptomatology of patients with orthopedic instability before and after deprogramming with a stabilization splint. Sixty patients with the signs and symptoms of TMD were assessed using the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) and underwent stabilization splint therapy to place the condyles in a more stable musculoskeletal position. The amount of condylar displacement was evaluated using the condylar position indicator (CPI). Six-teen angular and linear hard tissue landmarks were traced and compared from lateral cephalo-grams taken in the maximum intercuspation (MI) position before and in the centric relation (CR) position after the splint therapy. Following the splint therapy, the signs and symptoms of TMD were significantly reduced or completely eliminated in more than 90% of the patients. Compared with the values registered before the splint therapy, a significant reduction in the mean values of condylar displacement was observed on both sides of the vertical, horizontal, and transverse planes of space after the splint therapy. A comparison of pre- and post-splint lateral cephalograms revealed that, following the splint therapy, the mandible moved more posteriorly and rotated more in a clockwise direction. In patients with orthopedic instability and signs and symptoms of TMD, deprogramming of the neuromuscular system with a stabilization splint is highly recommended to provide a correct orthodontic diagnosis and improve the health of temporomandibular joint structures.

With the rise of the Internet of Things (IoT), maintaining data confidentiality and protecting user privacy have become increasingly challenging. End devices in IoT are often deployed in unattended environments and connected to open networks, which can make them vulnerable to physical tampering and other security attacks. Different authentication key agreement (AKA) schemes have been validated to date, but most schemes do not cover the necessary security features or are incompatible with resource-constrained end devices. Besides, their security proofs have been performed under the real-or-random model, which is not guaranteed to be secure in real applications. To reduce the weaknesses, we present an AKA protocol for end devices and servers. The proposal leverages the ECC-based key exchange mechanism and one-way hash function-based message authentication method to achieve mutual authentication, user anonymity, and forward security. Formal security proof of the proposed scheme is performed under the standard model with the elliptic curve encryption computational assumptions, and an automatic formal verification was performed with ProVerif. Further, the performance comparison verifies that our scheme reduces computation and communication costs while providing improved security features.

Urban transit planning is going through a transition to greater private investment in many parts of the world and is now on the agenda in Australia. After showing examples of private investment in transit globally the paper focuses on historical case studies of private rail investment in Western Australia. These case studies mirror the historical experience in rapidly growing railway cities in Europe, North America and Asia (particularly Japan), and also the land grant railways that facilitated settlement in North America. The Western Australian experience is noteworthy for the small but rapidly growing populations of the settlements involved, suggesting that growth, rather than size, is the key to successfully raising funding for railways through land development. The paper shows through the history of transport, with particular reference to Perth, that the practice of private infrastructure provision can provide lessons for how to enable this again. It suggests that new partnerships with private transport investment as set out in the Federal Government City Deal process, should create many more opportunities to improve the future of cities through once again integrating transit, land development and private finance.

South Africa (SA) is grappling with a severe food insecurity crisis exacerbated by socioeconomic challenges. This resulted in the Department of Basic Education (DBE) advocating for the establishment of vegetable gardens at schools. However, information on the suitability of the soils in SA for sustainably growing Beetroot is unavailable. This study aimed to assess the suitability of soils for sustainable Beetroot production at various schools in the Kgakotlou circuit. Four Secondary Schools were selected: Mothimako, Madipoane, Klaas Mothapo and Phomolong. A detailed soil survey was carried out to study soils in vegetable gardens. Soil samples were collected for laboratory analysis of physicochemical properties. The soil suitability was evaluated using the physicochemical properties of the soils and optimal soil requirements for Beetroot production. We found various soils in the schools, including Cambisols (Hutton and Nkonkoni), Leptosol (Glenrosa), Plinthosol (Westleigh), and Acrisols (Tshiombo and Tubatse). Portions of the gardens on Hutton and Westleigh soil were moderately suitable (S2), limited by electrical conductivity (EC). Meanwhile, portions of Tshiombo, Tubatse, and Nkonkoni were marginally suitable (S3), limited by pH and EC. Portions on Glenrosa soil at Klaas Mothapo and Phomolong were not suitable (NS) and were limited by shallow depth, soil pH and EC. The results reveal the importance of considering soil suitability before establishing vegetable gardens in school settings. Indexing soil suitability using the physicochemical properties of soil resources for sustainable beetroot production is proposed for schools in the Kgakatlou circuit and other parts of SA.

The article covers the Surveyor Institute's historical context and its role in the legal order of land rights registration. It highlights the importance of GPS technologies in ensuring the accuracy of registering rights to real estate. The article reviews the role of systematic registrations in clarifying overlapping cadastral data and preventing neighborhood disputes. Additionally, it underscores the challenges related to surveying activities in Georgia and emphasizes the importance of establishing a legal framework for this profession.

Considering that cryptocurrencies are now present in practically every financial transaction because they are widely accepted as an alternate means of making payments and exchanging currencies, academics and economists have more opportunities to study cryptocurrency prices. Over the years, investors, traders and investment banks have found it difficult to predict the closing daily price of Ethereum due to its rapid price fluctuation. The daily closing price of cryptocurrency is essential to consider when trading or investing in Ethereum. This report focuses on carrying out a comparative study of the predictive capabilities of deep machine learning algorithms with a stacking ensemble modelling framework using daily historical observations of the price of Ethereum obtained from Coindesk, tweets extracted from Twitter ranging from the 1st of August 2022 to the 8th of August 2022 and other five covariates (closing price lag1, closing price lag2, noltrend, daytype and month) engineered from the closing price of Ethereum. Seven models are used to compute the forecasts for the daily closing price of Ethereum; these are the recurrent neural network, ensemble stacked recurrent neural network, gradient boosting machine, generalized linear model, distributed random forest, deep neural networks and stacked ensemble for gradient boosting machine, generalized linear model, distributed random forest and deep neural networks. The main evaluation metric used is the mean absolute error. According to MAE, RNN forecasts outperform the other model’s forecasts in this study, producing an MAE of 0.0309.

Background: Amidst escalating climate change concerns, sustainable practices in healthcare logistics are critical. This study evaluates the ecological impact and efficiency of medical sample transportation using drones, combustion cars, and electric cars across diverse terrains and weather in Liechtenstein and Switzerland. Methods: We conducted a comparative analysis of CO2 emissions, transport distances, and delivery times for each transportation modality. Data collection involved multiple runs under various conditions, with CO2 emissions measured using onboard systems, and transport efficiency assessed via GPS tracking and time monitoring. Results: Combustion cars exhibited the highest average CO2 emissions at 159.5 grams per kilometer (g/km). Electric cars emitted significantly less, averaging 3.43 g/km, which is 2.15% of combustion car emissions. Drones were the most environmentally friendly, with an average emission of 0.09 g/km, representing 0.07% of combustion car emissions and 2.6% of electric car emissions. Drones also showed substantial transport efficiency, covering 17% shorter distances on flat terrain and 24% shorter in mountainous areas, with time savings ranging from 13% to 80%. Conclusion: This study highlights the potential of drone technology to revolutionize healthcare logistics by reducing environmental impact and optimizing operational efficiency. Integrating drones can significantly lower the carbon footprint, improve sample integrity, and enhance patient care, promoting a greener, more resilient healthcare system.

This paper discusses a significant public-private partnership (PPP) formed by the government and Taiwanese Farmer Associations. Particularly, it will investigate a pattern of the PPP that has successfully promoted rural development and agricultural modernization in Taiwan since 1950s. Taiwanese Farmer Associations (hereafter TFAs), similar to agricultural cooperatives in South Korea and Japan, have played a policy agent in fostering rural development in this island state since 1950s. TFA’s performance inherently came from Japanese Cooperatives before World War II. The Performances of those farmer organizations are combinations of economic, social, and educational synergies. The rural development experiences in Taiwan demonstrate that success of rural modernization is carried out by a special public-private partnership (PPP). First, this paper discusses formation and development of farmer cooperative organizations in East Asian societies and compare the similarities and differences of practice of those organizations and their relations to the governments among Taiwan, South Korea, and Japan. Secondly, this paper examines collaborative mold and process in which both the government and Taiwan Farmer Associations have been extensively involved. A specific cooperative apparatus between the government and TFA functioning and operating as a perfect PPP has been formed under administrative guidance of the state. Thirdly, this paper looks at input and various supports in financial and policy perspective by the public sector. Fourthly, the paper discusses legal framework, administrative apparatus, and governance pattern for TFA. Fifthly, the paper discuses that a specific PPP successfully involving in rural modernization in Taiwan is significantly derived from the state’ guidance that properly regulates a collaboration between the government and TFA. So-call East Asian model of PPP in agricultural modernization and rural community development may become a valuable experience for most of developing countries.

This paper examines a persuasion game between two agents with one-sided asymmetric information, where the informed agent can reveal her private information prior to playing a Battle-of-the-Sexes coordination game. We find that in the presence of strategic uncertainty in coordination there exists an equilibrium where there is no 'unraveling' of information. We provide a purification argument for this mixed strategy equilibrium to strengthen the central result, which is robust to several extensions, including both-sided asymmetric information and imprecise information revelation.

This comprehensive review digs into the complex landscape of the Metaverse, focusing on user perceptions and the critical roles of usability, social influence, and interoperability. The paper integrates various scholarly insights, underscoring the Metaverse's evolving significance in the digital realm and its implications across diverse sectors. Central to the findings is the importance of usability. The influence of social factors is also prominent, shaping user behavior and decision-making within these virtual spaces. Interoperability becomes a big problem, showing how important it is to have standard protocols and technologies so that experiences on different Metaverse platforms are smooth and seamless. The review further reveals insights into user experience and accessibility, emphasizing the need for inclusive, ergonomic, and user-friendly design to enhance engagement and reduce barriers. Moreover, the paper discusses the ethical and societal implications of the Metaverse, including issues like digital harassment, aggressive marketing, and privacy concerns, which call for responsible development and robust regulatory frameworks. Additionally, the review identifies gaps in current research, particularly in user experience in healthcare applications, the impact of the Metaverse on educational outcomes, and the need for more empirical studies on the long-term effects of Metaverse interactions on user behavior and psychology. This synthesis offers a detailed overview of current user perceptions and challenges within the Metaverse and sets the stage for future research directions, aiming to foster a secure, inclusive, and interoperable Metaverse environment that aligns with ethical standards and societal needs.

Due to the rapid growth of the Internet of Things (IoT), securing communications between a huge number of devices has become very difficult. Access controls and authentication secure the connection between IoT devices and protect sensitive data from unauthorized users or malicious attackers. In this paper, we provide a comprehensive review to emphasize the critical role of authentication and access control in securing IoT environments. This paper explores different types of access controls, like Attribute-Based Access Control and Role-Based Access Control. Furthermore, it demonstrates different authentication techniques, like passwords and biometrics. Based on the previous mechanisms, we discuss different IoT security challenges regarding authentication and access control mechanisms and highlight future directions. In addition, this paper investigates the integration between access control and authentication to safeguard IoT communications.

Two new systematic authentication codes based on the Gray map over a Galois ring are introduced. The first introduced code attains optimal impersonation and substitution probabilities. The second code improves space sizes but it does not attain optimal probabilities. Besides it is conditioned to the existence of a special class of bent maps on Galois rings.

Competent authorities of many countries, including Belgium, impose control measures (preventing wild bird access to feeders and water facilities, indoor confinement of captive birds, or fencing off outdoor ranges with nets) to professional and non-professional keepers of birds to prevent the spread of avian influenza (AI). Flemish laying hen farmers (FAR, n = 33) and private keepers of captive birds (PRI, n = 263) were surveyed about their opinion on, and compliance with, AI-measures legally imposed during the most recent high-risk period before this survey in 2021. Participants answered questions on a 5-point Likert scale (1 = the worst, 3 = neutral, and 5 = the best). FAR indicated better compliance with the AI-measures compared to PRI, except for confinement with nets. PRI and FAR perceived the level of compliance with AI-measures by other private bird keepers to be lower compared to themselves. FAR regarded the AI-measures as more effective than PRI. To prevent the spread of AI more effectively, national authorities could focus on information campaigns explaining to private bird keepers, in particular, the need for the various control measures that they impose, implement alternative control measures that have broader support or implement stricter enforcement of the control measures.

Internal and external factors influence the tendency of corruption. One of these internal factors is Dark Triad Personality, religiosity, and compensation, while the external factors are the organizational culture. This first study was conducted on 222 private employees and the second study 205 state employee in the East Java area. All subjects have worked at the company for at least 1 year and have a position as the staff, administrator, manager, and age range from 22 to 55. The results of the first study using regression analysis showed that: there was a significant correlation between dark triad personality, organization culture, and the tendency of corruption of private employee (F = 60,132; p = 0,000); there was a significant negative correlation between organizational culture and tendency of corruption (p = 0,000); there was a positive correlation between dark triad personality and the tendency of corruption (p = 0.05). The results of the second study using regression analysis showed that: there was a significant correlation between religiosity, compensation, and the tendency of corruption of state employee (F = 65.950; p = 0,000); there was a significant negative correlation between religiosity and tendency of corruption (p = 0,000); there was no correlation between compensation and tendency of corruption (p = 0.074). This research's practical implication is: the company or institution must always create a positive perception of organizational culture, minimize dark triad personality, and maximize religiosity to reduce the tendency of corruption among employees.

Internet of Things (IoT) devices are going to be the primary data source in smart cities, often generating and communicating critical, sensitive, and private data that face threats of confidentiality breaches due to the rise of quantum computers. Even though NIST has approved post-quantum cryptography (PQC) schemes that promise to protect from quantum computer threats, these schemes can not be implemented efficiently on IoT devices, which often have computational and memory constraints. Hence, due to the substantial key size requirements and computationally intensive nature of PQC schemes, their direct deployment on IoT devices within smart city architecture is impeded by inherent computational and storage limitations. Consequently, it is imperative to devise PQC-based, resource-efficient authentication protocols tailored to IoT devices operating within smart cities. In this paper, we propose an offloading scheme that uses PQ Edge Server (PQES) for the network that performs PQC-related computation and memory operations for IoT devices in the network. The suggested technique transfers all storage and processing responsibilities from IoT devices in a network to ensure their normal operation and performance without any compromise. PQES generates a distinct PQ key pair for every network device and oversees a separate stream for each device. Therefore, IoT devices in the network may function without cryptographic processes, improving their efficiency by removing the need for conventional cryptography. Our results show that the proposed scheme reduces RAM usage to 1.05 KB and CPU usage to 1.75%, with maximum CPU context switches of 92.8. The proposed scheme uses TCP, a transport layer protocol, which is applicable to lightweight end devices without application-level protocols like HTTP or MQTT. When benchmarked on a Raspberry Pi, the PQES can handle 1000 concurrent connections and use a maximum of 73.5% of RAM. In comparison, previous research used at least 5.1 MB of RAM for one concurrent connection and may use up to 552.6 MB of RAM for 1000 concurrent connections. The maximum CPU usage for our method was 1.75%, whereas the previous proposal had a utilization of 67.1%. The greatest CPU context switches for our system were 92.8, far lower than the 3449 observed for the usual approach. Hence, our proposed scheme reduces the computational, memory, and network load for IoT devices by manifolds and increases device performance while providing PQC security.

Conditional Privacy Preserving Authentication (CPPA) schemes are an effective way of securing communications in Vehicular Adhoc Networks (VANETs), as well as ensuring user privacy and accountability. Cryptanalysis plays a crucial role in pointing out the vulnerabilities in existing schemes to enable the development of more resilient ones. In 2019, Zhang proposed a CPPA scheme for VANET security (PA-CRT), based on identity batch verification (IBV) and Chinese remainder theorem (CRT). In 2023, this scheme was crypt-analyzed by Tao. In this paper we provide our own crypt analysis of Zhang’s scheme and propose counter measures to mitigate Tao’s attacks. Furthermore, in 2021, Xiong proposed a Certificateless Aggregate Signature (CLAS) scheme which was cryptanalyzed by Shim in 2023. Xiong subsequently proposed a modified CLAS scheme which is also cryptanalyzed in this paper.

Seniors safety is a compelling need, which necessitates 24/7 real-time monitoring and timely dangerous action recognition. Being able to mirror characteristics of physical objects (PO) to corresponding logical objects (LO) and seamlessly monitor their footprints thus detect anomaly parameters, Digital Twins (DT) has been considered a practical way to provide virtual health services for seniors safety. Meanwhile, widely adopted Internet of Medical Things (IoMT) consisting of wearable sensors and non-contact optical cameras for self and remote health data monitoring also raises concerns on information security and privacy violation. Therefore, security of POs, LOs and reliable data sharing among healthcare professionals are challenging as constructing trust and privacy-preserving virtual health services. Thanks to characteristics of decentralization, traceability and unalterability, Blockchain is promising to enhance security and privacy properties in many areas like data analysis, finance and healthcare. This paper envisions a lightweight authentication framework (LAF) to enable secure and privacy-preserving virtual healthcare services. Leveraging Non-Fungible Token (NFT) technology to tokenize LOs and data streams on blockchain, anyone can certify the authenticity of a digital LO along with its synchronized data between PO without relying on a third-party agency. In addition, the NFT-based tokenization not only allows owners fully control their IoMT devices and data, but it also enables verifiable ownership and traceable transferability during data sharing process. Moreover, NFT only contains references to encrypted raw data that are saved on off-chain storage like local files or distributed databases, such a hybrid storage strategy ensures privacy-preservation for sensitive information. A proof-of-concept prototype is implemented and tests are conducted on a case study of seniors safety. The experimental evaluation shows the feasibility and effectiveness of the proposed LAF solution.

With the advent of modern technologies, the healthcare industry is moving towards a more Personalised smart care model. The enablers of such care models are the Internet of Things (IoT) and Artificial Intelligence. These technologies collect and analyse data from persons in care to alert relevant parties if any anomaly is detected in a patient’s regular pattern. However, such reliance on IoT devices to capture continuous data extends the attack surfaces and demands high-security measures. Both patients and devices need to be authenticated to mitigate a large number of attack vectors. The biometric authentication method has been seen as a promising technique in these scenarios. To this end, this paper proposes an AI-based multimodal biometric authentication model for single and group-based users’ device-level authentication that increases protection against the traditional single modal approach. To test the efficacy of the proposed model, a series of AI models are trained and tested using physiological biometric features such as ECG (Electrocardiogram) and PPG (Photoplethysmography) signals from five publicly available datasets from Physionet and Mendeley data repositories. The multimodal fusion authentication model shows promising results with 99.8% accuracy and an Equal Error Rate (EER) of 0.16.

When we talk about the Internet of Things, we are referring to the connecting of things to a1 physical network that is embedded with software, sensors, and other devices that allow information2 to be exchanged between devices. It is possible that the interconnection of devices will present3 issues in terms of security, trustworthiness, reliability, and confidentiality, among other things.4 The proposed approach is effective at detecting intrusions into the Internet of Things network.5 Initially, the privacy-preserving technology was deployed utilising a Blockchain-based methodology6 to ensure that personal information was protected. Patients’ health records (PHR) security is the7 most crucial component of encryption over the Internet because of the value and importance of these8 records, particularly in the context of the Internet of Medical Things (IoMT). The search terms access9 mechanism is one of the most common approaches used to access personal health records from a10 database, but it is vulnerable to a number of security flaws. However, while blockchain-enabled11 healthcare systems provide increased security, they may also introduce weaknesses into the current12 state of the art. Blockchain-enabled frameworks have been proposed in the literature as a means13 of resolving those challenges. These solutions, on the other hand, are primarily concerned with14 data storage, with Blockchain serving as a database. To enable secure search and keyword-based15 access to a distributed database, this study proposes the use of blockchain technology as a distributed16 database, together with a homomorphic encryption mechanism. Aside from that, the suggested17 system includes a secure key revocation mechanism that can be used to automatically update various18 policies.As a result, our proposed approach provides greater security, efficiency, and transparency19 while also being more cost-effective. We have compared the findings of our proposed models with20 those of the benchmark models, if appropriate. Our comparison research demonstrates that our21 suggested framework provides a more secure and searchable mechanism for the healthcare system22 than the current state of the art.

Identifying or authenticating a computer user are necessary steps to keep systems secure on the network and to prevent fraudulent users from accessing accounts. Keystroke dynamics authentication can be used as an additional authentication method. Keystroke dynamics involves in-depth analysis of how you type on the keyboard, analysis of how long a key is pressed or the time between two consecutive keys. This field has seen a continuous growth in scientific research. In the last five years alone, about 10,000 scientific researches in this field have been published. One of the main problems facing researchers is the small number of public data sets that include how users type on the keyboard. This paper aims to provide researchers with a data set that includes how to type free text on the keyboard by 80 users. The data were collected in a single session via a web platform. The dataset contains 410,633 key-events collected in a total time interval of almost 24 hours. In similar research, most datasets are with texts written by users in English. The language in which the users wrote for this research is Romanian. This paper also provides an extensive analysis of the data set collected and presents relevant information for the analysis of the data set in future research.

This critical review revisited the new classification system for periodontitis, specifically for staging, suggesting modifications, and introducing a new flowchart for a better clinical evaluation. It evaluated articles published between 2018 and 2024 in the English language, which had an educational motivation focused on staging periodontitis. PubMed/MEDLINE, Web of Science, and Embase databases were used to retrieve the articles. The focus questions involved the analysis of all parameters for staging periodontitis. A total of 836 articles were initially found; 388 duplicated were excluded; 448 were evaluated by title and abstract; 26 articles followed for full-text reading, and 6 articles were included in this critical review (k=0.98). All articles included detailed parameters and steps about how to diagnose periodontitis. Therefore, it was possible to observe instability and “gray zones” in the staging step, which was due to a lack of priority and an organized order sequence. This review suggests the severity parameters cannot be overcome by complexity parameters, following a cumulative sequence: CAL (1^st), RBL (2^nd), TLP (3^rd), and, after, complexity parameters. An exception must be permitted only for complexity factors between Stages III and IV that can change the initial Stage (III or IV) obtained through the severity analysis, but only between themselves. Moreover, for patients without tooth loss or with TLP of ≤4 teeth (without need for complex rehabilitation) and presenting any type of drifting or flaring or a secondary traumatic occlusion, it cannot be a justification for moving the diagnosis from Stage III to Stage IV.

This study aims to explain individual engagement in sustainable waste management behaviors (SWMBs) based on the application of protection motivation theory (PMT). SWMBs include waste avoidance, green purchasing behavior, reuse and recycle, and waste disposal behaviors. This study applies PMT to explore how individuals’ SWMBs are influenced by their perceived threats caused by environmental contamination from waste disposal and their perceived coping capability. The Bangkok metropolitan area was selected as a case study because it has faced serious waste management problems caused by massively increasing amounts of solid waste during the last ten years. Questionnaire surveys were conducted with 193 public and private officers residing in the city of Bangkok. The one-way analysis of variance (ANOVA) was performed to justify the effect of individual threat appraisal and coping appraisal on the engagement in SWMBs. The results demonstrated that respondents’ self-efficacy highly influenced all types of SWMBs. The perceived probability of being impacted from pollutants influenced all of the SWMBs except green purchasing behaviors. Response efficacy did not influence all SWMBs; however, the perceived severity of adverse consequences caused by pollutants highly influenced reuse and recycle behaviors. It could be suggested that PMT is well suited for investigating low-cost and simple SWMBs. It could also be suggested that different communication campaigns should be established to enhance citizens’ engagement in each type of SWMB.

Objectives: The goal of this pilot study was to validate and introduce a new AI tool (algorithm), providing and comparing (1) the periodontal/peri-implant diagnosis between professional (specialist) and automated tool, (2) risk assessment and prognostication with the algorithm, and (3) establish cut-off limits for clinically significant disease with a new score system (GF-PeDRA score). Methods: All patients were evaluated by two evaluators, and in case of any divergence, the case was revisited and discussed until clarification and definition. The validation sample constituted 221 patients. The AI tool (GF-PeDRA©) had eighteen parameters to be assessed, involving systemic and local predictors, achieving an octadecagon (an eighteen-sided polygon). The parameters were: (1) The highest probing depth (PD); (2) Number of interproximal sites with bone loss; (3) The highest clinical attachment loss (CAL); (4) Maximum radiographic bone loss (RBL); (5) Bleeding on probing (% BoP); (6) Bone loss pattern; (7) Tooth loss including periodontally hopeless teeth planned for extraction; (8) Evidence of progression over five years; (9) Need for complex rehabilitation; (10) Patient’s age; (11) CAL and biofilm accumulation; (12) Smoking; (13) Diabetes; (14) Extension and distribution of the disease; (15) Peri-implant disease; (16) Other systemic conditions (other than diabetes); (17) Furcation involvement; and (18) Necrotizing lesion. A new score system (GF-PeDRA© score) based on the percentual of the octadecagon area is obtained; if the area was ≥0% to ≤9%, the prognosis is good; ≥10% and ≤ 24%, it is fair; ≥25% and ≤37%, poor; ≥38% and ≤49%, it is questionable; and between ≥50% to ≤100%, the prognosis is hopeless. Results: 221 patients were enrolled, with a mean age of 46.73. 5301 teeth were examined. 187 non-smokers (84.62%) and 34 smokers (15.38%) were included. 193 (87.33%) patients did not have diabetes, whereas 28 (12.67%) had. Comparing the diagnosis between both evaluators, k=0.83; all disagreed cases were re-discussed, and a final decision/diagnosis was reached. After this, the diagnosis found was contrasted with the diagnosis achieved by GF-PeDRA© and a perfect agreement was observed, 100% (k=1.0). 28 patients were diagnosed as periodontally healthy, 55 with plaque-induced gingivitis, and 138 with periodontitis. Only one case of molar/incisor pattern was observed. No peri-implant disease or necrotizing condition was found. The mean CAL found was 3.19 mm; 25 patients (11.31%) had a furcation involvement. The mean percentual of BoP found was 28.67% (median = 19%; maximum: 100%; minimum: 100%); and the mean PD was 5.31 mm. The mean of the new GF-PeDRA© score (ranging from 0% to 100%) was 28.64%, with a median of 32.2% (minimum: 0.6% and maximum: 64.1%). Then, analyzing the GF-PeDRA© score of 221 patients enrolled, 48 (21.73%) were sorted as a Good prognosis for periodontal treatment, 43 (19.45%) had a Fair prognosis, 43 (19.45%) had a Poor prognosis, 68 (30.77%) had a Questionable prognosis, and 19 (8.60%) had a Hopeless prognosis. Conclusion: The new AI tool (GF-PeDRA©) was validated and proved to be extremely helpful in diagnosing and providing risk assessment and prognosis.

Background: The integration of unmanned aerial vehicles (UAVs), commonly known as drones, into medical logistics offers transformative potential for the transpor-tation of sensitive medical materials, such as blood samples. Traditional car transportation is often hindered by traffic delays, road conditions, and geographic barriers, which can compromise timely delivery. Methods: This study provides a comprehensive analysis comparing high-speed drone transportation with traditional car transportation under various weather conditions. Blood samples, including EDTA whole blood, Serum, Li-Heparin Plasma, and citrate plasma tubes, were transported via both methods across temperatures ranging from 4 to 20 degrees Celsius. The integrity of the samples was assessed using a wide array of analytes and statistical analyses, including Passing-Bablok regression and Bland-Altman plots. Results: The results demonstrated that drone transportation maintains blood sample integrity comparably to traditional car transpor-tation. For serum samples, the correlation coefficients (r) ranged from 0.830 to 1.000, and the slopes varied from 0.913 to 1.111, with minor discrepancies in five analytes (total bilirubin, calcium, ferritin, potassium, and sodium). Similar patterns were observed for EDTA, Lithium-Heparin, and Citrate samples, indicating no significant differences between transportation methods. Conclusions: These findings highlight the potential of drones to enhance the efficiency and reliability of medical sample transport, particularly in scenarios requiring rapid and reliable delivery. Drones could significantly improve logistical operations in healthcare by overcoming traditional transportation challenges.

Well-annotated gene and genomic sequences serve as a foundation for making inferences in molecular biology and evolution, and can directly impact public health. The first SARS-CoV-2 genome was submitted to GenBank and used to develop the two successful vaccines. Conserved protein domains are often chosen as targets for developing antiviral medicines or vaccines. Mutation and substitution patterns provide crucial information not only on functional motifs and genome/protein interactions but also for characterizing phylogenetic relationships among viral strains. These patterns, together with the collection time of viral samples, serve as the basis for addressing the question of when and where the host-switching event occurred. Unfortunately, viral genomic sequences submitted to GenBank undergo little quality control, and critical information in the annotation is frequently changed without being recorded. Researchers often have no choice but to hold blind faith in the accuracy of the sequences. There have been reports of incorrect genome annotation but no report that casts doubt on the genomic sequences themselves because it seems theoretically impossible to identify genomic sequences that may not be authentic. This paper takes an innovative approach to show that some SARS-CoV-2 genomes submitted to GenBank cannot be possibly authentic. Specifically, some SARS-CoV-2 genomic sequences deposited in GenBank with collection time in 2023 and 2024, isolated from saliva, nasopharyngeal, sewage, and stool are identical to the reference genome of SARS-CoV-2 (NC_045512). The probability for such occurrence is effectively 0. I also compile SARS-CoV-2 genomes with changed sample collection time. One may led astray in bioinformatic analysis without being aware of errors in sequences and sequence annotation.

The objective of this study was to compare single-needle arthrocentesis with the conventional two-needle arthrocentesis, as well as, additional intracapsular injection of hyaluronic acid or platelet rich fibrin. 96 patients with established osteoarthritis (OA) (n= 48) or with internal de-arrangement (DD) (n= 48) were assigned for single-needle arthrocentesis with distension of the joint or conventional two-needle arthrocentesis with or without intracapsular injection of the medication (hyaluronic acid- HA or platelet-rich plasma- PRP) performed every month in the period of 6 months. The maximum mouth opening and pain as measured by the visual analog scale (VAS) were compared. Each group exhibited significant improvement: decrease of pain and in-creased mouth opening. Single- puncture technique provided similar pain reduction as two needle approach but provided significantly better results in maximum mouth opening. Reduction of pain was similar when comparing between the OA and DD cohorts, however patients with disc dis-placement reached significantly better mouth opening than OA. Intracapsular application of medication contributed to significant decrease of pain in both HA and PRP groups, with plate-let-rich fibrin being significantly superior in terms of mouth opening increase over HA.

This article focuses on developing a continuous authentication system using behavioral biometrics to recognize users accessing computing devices. The user’s distinct behavioral biometric is captured through keystroke dynamics, and reward-based reinforcement learning (RL) ideas are applied to recognize them throughout the session. The suggested system adds an extra layer of security to traditional authentication methods, forming a robust continuous authentication system that can be added to static authentication systems. The methodology involves training a RL model to detect unusual user typing patterns and flag suspicious activity. Each user has an agent trained on their historical data, which is preprocessed and used to create episodes for the agent to learn from. The environment involves fetching observations and randomly corrupting them to learn out-of-order behavior. The observation vector includes both running features and summary features. The re-ward function is binary and minimalistic. The Principal Component Analysis (PCA) model is used to encode the running features, and the Double Deep Q-Network (DDQN) algorithm with a fully connected neural network is used as the policy net. The evaluation achieved an average training accuracy and EER (equal error rate) of 94.7% and 0.0126 and test accuracy and ERR of 81.06% and 0.0323 for all users when the number of encoder features was increased. Therefore, it is concluded that by continuously learning and adapting to changing behavior patterns, this approach can provide more secure and personalized authentication, lowering the possibility of unauthorized access and cyberattacks. Overall, the use of reinforcement learning and behavioral biometrics for continuous authentication has the potential to significantly enhance security in the digital age and are effective in identifying each user.

In this paper, we propose a lightweight physical layer aided authentication and key agreement (PL-AKA) protocol in the internet of things (IoT). Conventional evolved packet system AKA (EPS-AKA) used in long-term evolution (LTE) systems may suffer from congestions in core networks by the large signaling overhead as the number of IoT devices increases. Thus, in order to alleviate the overhead, we consider a cross-layer authentication by integrating physical layer approaches to cryptography-based schemes. To demonstrate the feasibility of the PL-AKA, universal software radio peripheral (USRP) based tests are conducted as well as numerical simulations. The proposed scheme shows a significant reduction in signaling overhead compared to the conventional EPS-AKA in both simulation and experiment. Therefore, the proposed lightweight PL-AKA has the potential for practical and efficient implementation of large-scale IoT networks.

The Study proposes possible solution to enhance Password Authentication using Association Technique based on the Ecological theory of memory and data at the Presbyterian university College Ghana. The study used a deductive research approach and employed two empirical Studies using the non-probability sampling technique where few respondents were selected in categories out of the populace by means of openness in other to get similar categories of respondents with different age groups and education background. The two Empirical study also used a quasi-experimental approach which structure incorporate observation, experimental treatment and timing. The First empirical study carried out an investigation to identify existing Password authentication Technique used by End Users, as well as their behavior in password utilization through a self-completed questionnaires which was analyzed using SPSS version 21 . The Second empirical study was an experiment to compared three kinds of password constructions that is own set, modified dictionary, and association against one another to see which of them would be best meet the ecological theory of memory and data which aims at creating a secured password that is easy to recall. The computation and evaluation of password construction was done using My1login Password meter whiles Levenshtein Distance String Edit Software was also used to compute the memorability of all given password. Across-tabulation was then employed out of the experiment using SPSS version 21. The result from the analysis revealed that the majority of the respondents do have weak passwords and also have few passwords which they even end up sharing with families and friends and reuse it. This confirms statements made by researchers that human being is the weakest connection in information system securities. To maintain Confidentiality, Availability and Integrity of data, the study therefore recommended the use of the Association Password technique which makes it easier to develop a much secured password that is difficult to crack but easy remember.

Comparative analysis of mortality rates between public and private healthcare systems remains a critical yet complex area of study. This article synthesizes findings from extensive academic literature and empirical studies to examine the relationship between healthcare system type and patient outcomes across various countries. By focusing on mortality rates as a key indicator, we elucidate the nuanced impacts of public versus private healthcare delivery. Our analysis reveals the multifaceted challenges inherent in both systems and their implications for patient survival. We conclude by identifying crucial gaps in current research and proposing policy recommendations to optimize healthcare outcomes in diverse global contexts.This revised abstract:Starts with a strong opening statement that immediately captures the topic's importance. Clarifies the article's methodology (synthesizing existing literature and studies).Specifies the focus on mortality rates as the primary outcome measure.Hints at the complexity of the findings, avoiding oversimplification.Ends with a clear statement about the article's contributions to both research and policy.

The large and interconnected nature of the Internet of Things (IoT) presents unique security challenges, even as it revolutionizes various sectors. With numerous devices, often limited in resources, traditional perimeter-based security methods struggle to keep pace. The "never trust, always verify" principle of zero trust security offers a viable solution. Zero trust security is a concept which has become increasingly popular, using key exchange techniques to ensure secure and authenticated communication within the network, especially in managing risks in critical infrastructure. Authentication is a process to identify an entity, a prerequisite for authorization, and essential for granting access control. It fundamentally relies on trust management and various methods to generate and manage cryptographic keys for authentication. The aim of this study is to enhance zero trust security in the context of the Internet of Things by investigating authentication methods and discussing several potential solutions for successful implementation. This study also presents the performance evaluation criteria for authentication in IoT and introduces advanced approaches for different scenarios, including lightweight cryptography, mutual authentication, and blockchain technology. Finally, we address challenges related to implementation and future directions for research.

In recent years, the internet of things has been widely utilized in various fields, such as in smart factories or connected cars. As its domain of application has expanded, it has begun to be employed using multi-server architectures for a more efficient use of resources. However, because users wishing to receive IoT services connect to multi-servers over wireless networks, this can expose systems to various attacks and result in serious security risks. To protect systems (and users) from potential security vulnerabilities, a secure authentication technology is necessary. In this paper, we propose a smart card-based authentication protocol, which performs the authentication for each entity by allowing users to go through the authentication process using a smart card transmitted from an authentication server, and to login to a server connected to the IoT. Furthermore, the security of our proposed authentication protocol is verified by simulating a formal verification scenario using AVISPA, a security protocol-verification tool.

Background: Patients with thromboembolic disease, prosthetic valves, or coagulation issues are commonly prescribed anticoagulants and antiplatelets. Although common professional oral hygiene might not represent a health concern for these patients, anticoagulant and antiplatelet medication might constitute a challenge for dentists and dental hygienists since possible prolonged bleeding might interfere with dental procedures. The aim of the present study was to investigate the bleeding time of different anticoagulants and antiplatelets during a professional hygiene session adapting the Ivy test to the oral environment; Methods: 93 consecutive patients undergoing professional oral hygiene were recruited. Debridement during oral hygiene was performed using ultrasonic mechanical instrumentation, and bleeding sites were assessed and treated with gentle pressure using sterile gauzes. The time for bleeding cessation was recorded. Patients were categorized into six groups based on their drug intake, Control: no anticoagulants or antiplatelets DTI: direct thrombin inhibitors (dabigatran) AntiXa: directa factor Xa inhibitors (endoxaban, apixaban, rivaroxaban) VKA: vitamin K antagonists (warfarin, acenocoumarol) SAPT: single anti-platelet therapy (acetylsalicylic acid or clopidogrel) DAPT: dual anti-platelet therapy (acetylsalicylic acid and clopidogrel). Bleeding time was measured in seconds and mean values were assessed among the different groups. Differences between groups were investigated with Kruskal-Wallis test followed by Dunn’s post-hoc correction for multiple comparisons or two-way ANOVA followed by Dunnett post-hoc; Results: Control patients presented the lowest bleeding time 50 sec, followed by AntiXa (98), SAPT (105), DTI (120), DAPT (190) and VKA (203). A statistically significant difference was present among control and DTI (p=0.004), VKA (p&lt;0.001), DAPT (p&lt;0.001). Conclusions: Based on the present outcomes, an increased risk of prolonged bleeding emerged in patients taking VKA and DAPT. However, bleeding did not interfere with the oral hygiene ses-sion The optimal period for dental treatment of these patients should be 2-3 hours before the next dose, without the need to temporarily suspend the medication.

Purpose: This study was designed to investigate the ability of telemonitoring involving a secure elec-tronic database called “Alsayed System for Applied Medical-Care Improvement” (ASAMI) to detect at least 95% of acute exacerbations of chronic obstructive pulmonary disease (AECOPD). Methods: This prospective observational study, which took place over 16 months in 2022-2023, was based at a medi-cal center in Jordan. The study group participants were patients with COPD (from seven countries) with mixed levels of airflow limitation severity, and every participant was followed for six months. A customized, password-protected version of ASAMI was used to collect data during the study. The implemented diary included questions on daily symptoms such as cough, dyspnea, sputum, and daily physical activities. The detection of AECOPD events was initially based on daily questionnaires com-pleted by patients, followed by the assessment of a healthcare practitioner. Results: 87 participants were monitored for AECOPD. During the study, 78/87 (89.7%) patients presented with one or more exacerbation episodes. The mean (range) age was 59.7 (45-81) years, predominantly male (66%), with moderate airflow limitation (n=42, 48%). Compliance with the provision of daily symptom data was very high, 98% over the entire study period. A total of 189 confirmed AECOPD episodes were reported. Almost all patients and practitioners showed favorable satisfaction with the role of the ASAMI-related service (96% reported a score of 10 satisfaction). The telemonitoring tool was able to detect 99% of AECOPD episodes. Conclusion: The novel ASAMI software was effective as a telemonitoring tool to detect the episodes of AECOPD. The tool was suggested for daily, continuous reporting of respiratory symptoms, with the key benefits being ease of use, patient acceptance, and collation of supplementary data when exacerbations occur. The effects of its widespread use on decision-making can be clarified by evaluating its impact on routine clinical decision-making.

Abstract: The study used whole-genome sequencing (WGS) and bioinformatics analysis for the genomic characterization of 60 isolates of Listeria monocytogenes isolated from cattle farms, cattle abattoirs, and retail outlets in Gauteng province, South Africa. The isolates' sequence types (STs), clonal complexes (CCs), and lineages were determined using in silico multilocus sequence typing (MLST). We used BLAST-based analyses to identify virulence and antimicrobial genes, plasmids, proviruses, and the CRISPR-Cas system. The study investigated any association of the detected genes to the origin in the beef production chain of the L. monocytogenes isolates. Overall, in 60 isolates of Listeria monocytogenes, there were 7 STs, 6 CCs, 44 putative virulence factors, 2 resistance genes, 1 plasmid with AMR genes and 3 with conjugative genes, 1 CRISPR gene, and all 60 isolates were positive for proviruses. Among the 7 STs detected, ST204 (46.7%) and ST2 (21.7%) were the most prominent, with ST frequency varying significantly (p&lt;0.001). The predominant CC detected were CC2 (21.7%) and CC204 (46.7%) in lineages I and II, respectively. Of the 44 virulence factors detected, 26 (across Listeria Pathogenicity Islands, LIPIs) were present in all the isolates. The difference in the detection frequency varied significantly (P&lt;0.001). The two AMR genes (fosX and vga(G)) detected were present in all 60 (100%) isolates of L. monocytogenes. The only plasmid, NF033156, was present in 3 (5%) isolates. A CRISPR-Cas system was detected in 6 (10%), and all the isolates carried proviruses. Significant differences were detected in the frequencies of STs and virulence factors regarding the source and sample type of the L. monocytogenes isolates. The presence of both fosX and vga(G) genes in all the isolates from the three industries (cattle farms, abattoirs, and retail outlets) can potentially cause therapeutic implications. Our study, which characterized L. monocytogenes recovered from the three levels in the beef production chain in the country, provides the first evidence of the distribution of the pathogen with potential food safety and therapeutic implications.

The problems of modeling the human bladder and its stress-strain state under external static influence were considered. A method for identification of the anisotropic biomechanical characteristics of bladder tissue was proposed. A FEM model was created, which accepts into regard that the bladder is surrounded by fiber and affected by surrounding organs, and partially protected by pelvic bones. The model considered the presence of constant hydrostatic pressure on the walls of the bladder when it is full. It has been shown that isotropic mechanical characteristics of biological tissue can be used for studying the deformed state of a filled bladder if the filled bladder 300 ml is considered as initial non-deformed stage. This was shown by modeling and verification the effect of the external static force on the bladder. Numerical experiments were conducted based on the constructed model. To validate the results obtained, a series of natural experiments on the effect of external pressure on the bladder under ultrasound control was conducted. In the future, it is planned to use the constructed model to study rupture deformations of the bladder under the influence of static and dynamic loads.

Many tasks in a modern household are done by machines like e.g. a dishwasher or a vacuum cleaner and in the near future most household tasks can be done by smart service robots. This relieves the residents who in turn can enjoy their free time. This newly gained free time turns out to cause the so called spare time rebound effect due to more resource consumption [1,2]. We roughly quantify this rebound effect and propose a CO2 -budget model to reduce or even avoid it. In modern industry, automation and AI take over work from humans, leading to higher productivity of the company as a whole. This is the main reason for economic growth which leads to environmental problems due to higher consumption of natural resources. We show that, even though the effects of automation at home and in the industry are different (free time versus higher productivity) in the end they both lead to more resource consumption and environmental pollution. We discuss possible solutions to this problem such as carbon taxes, emissions trading systems and a carbon budget.

City zones have become increasingly overcrowded as a result of the extensive population widening ratio and the swift relocation of people from villages. The traffic monitoring process is a major issue in these areas due to the massive traffic flow on the roads. This research proposed a cluster-based improved authentication and communication scheme for an Intelligent Transportation System in Vehicular AdHoc Networks (VANETs). Our primary objective is to optimize resource sharing in vehicular communication. We enhanced the reliability, scalability, and stability of fast-moving VANETs by introducing cluster-based routing schemes for Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications. We used a third-party certification authority for vehicle authentication to address security and privacy concerns. Our proposed schemes support minimizing the end-to-end (E2E) delay and route request, in addition to reducing link failure. Our schemes’ leading yield includes throughput enhancement, TCP Socket Initialization time minimization, TCP handshake response speedup, and DNS lookup improvement. The schemes are centred on short-range peer-to-peer (P2P) wireless communication in a 400-meter radius cluster. This includes innovative P2P wireless communications on VANET using minimized resources. The proposed schemes deliver a secure authentication mechanism with a securely generated vehicle authentication key provided by a certification authority. Furthermore, we have developed RESTful APIs in vehicular communication for implementation purposes, and also offered and implemented algorithms for resource sharing regarding V2V and V2I communication. Ultimately, we evaluated the performance of our experiments.

The aim of this study was to investigate the work engagement and burnout in healthcare professionals in a private health unit in Greece. A cross-sectional study was conducted with a sample of 151 professionals (doctors, nurses, administrative staff and professionals of other specialties). The questionnaire included demographic and work-related information and the Utrecht Work Engagement Scale and Maslach Burnout Inventory. Analysis was performed by SPSS v.26. With regard to the work engagement, the participants presented a medium score in absorption and a medium to high score in vigor and dedication. In addition, they presented low score in depersonalization, a medium score in emotional exhaustion and a high score in personal accomplishment. Those who had a working contract for an indefinite period had higher score in all the dimensions of burnout. Vigor, dedication and absorption were negatively correlated with emotional exhaustion and depersonalization and positively with personal accomplishment. Healthcare professionals in private health sector in Greece present moderate work engagement and experience moderate levels of burnout. Work engagement is associated with burnout and plays an important role in its prevention. There are some significant differences in work engagement and burnout based on several demographic and work-related characteristics.

Background: Research articles are essential for describing new ideas, techniques, and procedures and consolidating concepts. It creates an opportunity to expose studies and publicly assimilate published knowledge. Therefore, one of them is the most used and accepted index to verify the author’s scientific impact is the H-index or Hirsch index. It provides a robust single metric that combines quality and quantity. Therefore, it presents disadvantages, (1) researchers with shorter scientific carriers may have fewer articles and citations than those with longer scientific life; (2) it allows scientists to receive citations even if no new papers are published; (3) it is only useful for comparing the better scientists in a field; (4) this indicator can never decrease; (5) it is only weakly sensitive to the number of citations received; (6) the major and minor (or no) contributor in the research gained equal h-index. Then, the H-index ignores the total of citations and the time of a researcher's experience (“scientific age” [sa]). Objective: Thus, the goal of this study was to present a new index system (GFsa index ©) based on the two variables completely forgotten (total of citations and “scientific age”), introducing a new terminology “scientific age”, to evaluate the best-ranked researchers in Dentistry. Methods: The AD Scientific Index was used, and all researchers included in this study were cited in the AD Scientific Index (2024) in the Dentistry field and had the Google Scholar page accessible for a consultation to manually obtain the total of citations and calculate the “scientific age”. The information was retrieved by two authors (G.V.O.F. and J.C.H.F.), who assessed the data twice to avoid errors or mistakes. For inclusion: a minimum H-index value of 30; for exclusion: (i) the author did not have a Google Scholar page; (ii) duplicated author; or (iii) presented any suspicious activities about manipulation of articles. Then, a dataset of all researchers who were reported in Dentistry was prepared (name, H-index, i10 index, and publications). The formula developed and applied was GFsa=(total number of citations)/(“scientific age)². The Pearson correlation statistically evaluated the data obtained; the confidence interval was 95%. Results: A total of 9,093 researchers in Dentistry were recorded, of whom 1,020 were included. Then, we collected all 1,020 researchers' Google Scholar data (publications, citations, and indexes), and each researcher's total citations and “scientific age” were registered and calculated. The mean “scientific age” registered was 34.18 ± 13.34 (standard error of mean = 0.4181). With this information and data collected, GFsa index © was calculated, presenting a minimum value of 0.2186 and a maximum of 154.8 (mean = 10.33 ± 11.82; standard error of mean = 0.3706). Then, the data was organized and sorted following the ranking obtained in the GFsa index ©. The Pearson correlation showed that the H-index had a weakly positive association with the researcher’s “scientific age”; this fact means that the H-index will increase according to the “scientific age” increase. Otherwise, a moderately negative correlation between GFsa and “scientific age” was demonstrated, whereby a higher GFsa © had a lower “Scientific age”. This assessment shows that the variables introduced were fairly used. Moreover, a positive correlation was observed between both indexes (H-index and GFsa). Conclusion: It is possible to conclude that the new variable reported (“Scientific age”) and using the total citations brought a fairer and more feasible evaluation among the researchers. Thus, we are launching the new GFsa index © and the new information named “Scientific age” for the first time in the literature. The future perspective of the GFsa © application will be (1) the evaluation of the 9,093 researchers in Dentistry (total initially registered), including more authors/researchers in the Dentistry field, (2) expanding the exposition of this new index for other areas of the knowledge, and (3) provide free access of all data through the website (http://gfindex.us.to).

Radio Frequency Identification (RFID) devices use radio waves to relay identifying information to an electronic reader using low-cost RFID Tag. RFID is expected to replace the conventional bar-code identification system due to its advantage like real-time recognition of a considerable number of objects. However, in RFID systems an attacker can get the tag that may lead to various security threats, and the limited computation power of RFID tags can cause delay. Lightweight authentication protocols proposed using cryptographic algorithms (one-way hash function, symmetric key encryption/decryption, and exclusive-OR) in order to cope with these problems. One such lightweight cryptographic protocol has been presented by Gope and Hwang using RFID systems. However, it analyzed in this article that their protocol is infeasible and vulnerable to Collision Attack, Denial-of-service (DoS), and Stolen verifier Attacks. A realistic, lightweight authentication protocol has been presented in this article to ensure protection against the mentioned attacks for IoT based RFID system. The proposed protocol has been formally analyzed using BAN logic and ProVerif as well as also analyzed informally using security requirement. The results show that the proposed protocol outperforms the existing protocols not only in security enhancements but also in terms of computation and communication complexity. Furthermore, the proposed protocol has also been analyzed for storage complexity.

Vehicle identification is an important task in traffic monitoring because it allows for efficient inference and provides a cause for action. Vehicle classification via deep learning and other approaches such as segmentation is a critical tool for re-identification. In this paper, instance segmentation is used to identify vehicle makes with license plate detection, allowing for better unique vehicle recognition for re-identification. A dataset is annotated and modified, for example, by segmenting it with polygonal bounding boxes that capture the vehicle's unique frontal features. In addition, license plate localization is performed. The results showed improved classification as well as a high mAP for the dataset when compared to previous approaches based on CNN and deformed CNN. Furthermore, a deep residual network and fully connected layer-based classification were utilized as the backbone for feature representation. Instance segmentation detects objects by segmenting and classifying regions of interest. The imbalance in the dataset is resolved using a mosaic-tiled approach, which produces greater precision than other approaches.

Although the fusion energy sector is at a nascent stage, the private fusion energy market has grown. There are currently 38 private fusion energy companies around the world aiming to commercialise fusion energy in early 2030s and 2040s. Given the capability of fusion energy in transforming today’s energy paradigm and the global character of the market, it is important to analyse how these companies are interacting with international human rights standards. Therefore, this work investigates the involvement of the private fusion energy sector with two voluntary international initiatives in particular: the UN Global Compact and the UN Guiding Principles on Business and Human Rights (UNGP). This study attempts to answer two research questions: (i) Are private fusion energy companies participating in the UN Global Compact? (ii) How are private fusion energy companies publicly implementing the UNGP? Content analysis of secondary data collected from the UN Global Compact, Fusion Industry Association, ITER and companies’ official website as well as published reports is adopted. In summary, this work finds that private fusion energy companies are neither participants nor signatories of the UN Global Compact. Their observance of the UNGP is also very poor. This study contributes to the field by highlighting this gap which the private fusion energy companies need to consider and take measures in order to create a salutary human rights sector.

Barbera d'Asti - including Barbera d'Asti superiore - and Nizza are two DOCG (Denominazione di Origine Controllata e Garantita) wines produced in Piemonte (Italy) from Barbera grape variety. Differences among them arise in the production specifications in terms of purity, ageing and zone of production, in particular with concern to Nizza, which has more stringent rules and can therefore be considered as the one with the highest market value, with even three-fold more average prices. To guarantee producers and consumers, authentication methods must be developed in order to distinguish among the different wines. As the production zones totally overlap, it is important to verify whether the distinction is possible or not according to metals content, or whether chemical markers more linked to winemaking are needed. In this work, Inductively Coupled Plasma (ICP) elemental analysis and multivariate data analysis are used to study the authentication and traceability of samples from the three designations of 2015 vintage. The results show that, as far as elemental distribution in wine is concerned, work in the cellar, rather than geographic provenance, is crucial for the possibility of distinction.

The COVID-19 pandemic has not only affected public health but has also significantly impacted the economy. Bandung, a bustling city in Indonesia serving as a satellite to the capital, has been hit hard due to its high population density, mobility, and reliance on the tourism, trade, and transportation sectors. Using a Computable General Equilibrium (CGE) model developed at the inter-regional level of Indonesia, this study investigates the microeconomic indicators of several economic activities in Bandung to assess the impact of the pandemic. Additionally, the study examines the role of private sector actors in contributing to the sustainable recovery efforts toward achieving Sustainable Development Goals (SDGs) amidst the pandemic. The findings reveal that Bandung's transportation, accommodation, food and beverage, water supply, and trade sectors experienced a significant decline in economic activity. However, there was a gradual recovery with increased economic activity between 2019 and 2021. Private sector actors and the health sector were the main drivers of economic recovery, with other sectors also contributing to the efforts.

Continuous and emerging advances in Information and Communication Technology (ICT) have enabled IoT-to-Cloud applications to be induced by data pipelines coupled with Edge Intelligence-based architectures. Advanced vehicular networks greatly benefit from these architectures due to the implicit functionalities that are focused on realizing the Internet-of-Vehicle (IoV) vision. However, IoV is susceptible to attacks, where adversaries can easily exploit existing vulnerabilities. Several attacks may succeed due to inadequate or weaker authentication techniques. Hence, there is a timely need for hardening the authentication process through cutting-edge access control mechanisms. This paper proposes a Blockchain-based Multi-Factor authentication model that uses an embedded Digital Signature (MFBC_eDS) for vehicular clouds and Cloud-enabled IoV. Our proposed MFBC_eDS model consists of a scheme that integrates the Security Assertion Mark-up Language (SAML) to the Single Sign-On (SSO) capabilities for a connected Edge-to Cloud ecosystem. MFBC_eDS draws an essential comparison with the baseline authentication scheme suggested by Karla and Sood. Based on the foundations of Karla and Sood’s scheme, an embedded Probabilistic Polynomial-Time Algorithm (ePPTA) and an additional Hash function for the Pi generated during Karla and Sood’s authentication are proposed and discussed. The preliminary analysis of the proposition shows that the approach is more suitable to counter major adversarial attacks in an IoV-centered environment based on Dolev-Yao adversarial model while satisfying aspects of the CIA triad.

With quick improvement in the field of network, everything becomes online. Remote user authentication is a mechanism in which remote server verify the correctness of user over common or public channel. Remote user authentication can be Single server authentication or Multi server authentication. The disadvantage of single server authentication is that the user needs to recall user id and password for each service, he/she need to utilize, however it can overcome by Multi-server authentication in which user needs to register himself with Registration Center (RC) for the first run through and after that onwards he can utilize each service (which are given by servers, associated with RC) by recollecting only one user id and password. In this paper, we analyze Chen's authentication scheme (based on multi server authentication) and show that this scheme is vulnerable to password guessing attack, replay attack, RC spoofing attack, session key verification attack and perfect forward secrecy attack. In this Paper, we propose a biometric based remote user authentication scheme in multi-server environment. Proposed scheme is more secure and efficient as compared to chen's scheme\cite{23}.

Children account for a significant proportion of the world's population and are a particularly vulnerable subpopulation regarding environmental factors. In a scoping review of a total of 3130 articles compiled from relevant medical literature, including 107 publications, we provide an empirical overview of the literature on masks in connection with children, particularly with regard to its' expected effects on viruses during the pandemic 2020-2023 versus scientific reality and evidence, including the side effects. While masks lack ecological validity from a strictly empirical point of view (transferability of experimental results from laboratories and modelling to the real world, e.g. to situations or environments typical of everyday life) and high-quality studies are showing little evidence of their effectiveness in real-world scenarios, whereas the side effects appear to be clear. An individual risk-benefit analysis is necessary and also a consideration of the situations, in which the use of masks in children could be justified. This review including the literature found and analysed will be able to help when making decisions in this regard.

Electric mobility is one of the ways to contain greenhouse gas and local pollutants emissions in urban areas. Nevertheless, the massive introduction of battery-powered electric vehicles (EVs) brings some concerns related to their energy demand. Modelling vehicle usage and charging behavior is essential for charge demand forecasting and energy consumption estimation. Therefore, it is crucial to understand how the charging decisions of EV owners are influenced by different factors, ranging from the charging infrastructure characteristics to the users’ profiles. This review intends to investigate the approaches used to investigate on charging behavior and highlight trends and differences between the results, remarking on any gaps worthy of further investigation.

The current health crisis derived from COVID 19 has become a serious threat to humanity. The collateral effects related to economic aspects are affecting companies, workers and, of course, families in general. The problems of financial insolvency are frequently present in debtors who have contracted a debt with their creditor. Therefore, the objective of the study is focused on modeling a debt restructuring proposal, through three hypothetical scenarios in which the debt is reconvened when some documents have expired and others are yet to expire. In each of the scenarios, the mathematical model is designed and subsequently corroborated in an Excel spreadsheet. The predominant variables in the restructuring are the adjustment rates used to update the past due promissory notes and the discount rates of those promissory notes that have not yet expired, capitalizations, transaction costs and, if applicable, whether the debt is in foreign currency. In this case, it is converted to the local currency, then the spot exchange rate is used.

The rapid development of three-dimensional (3D) acquisition technology based on 3D sensors provides a large volume of data, which is often represented in the form of point clouds. Point cloud representation can preserve the original geometric information along with associated attributes in a 3D space. Therefore, it has been widely adopted in many scene-understanding-related applications such as virtual reality (VR) and autonomous driving. However, the massive amount of point cloud data aggregated from distributed 3D sensors also poses challenges for secure data collection, management, storage, and sharing. Thanks to the characteristics of decentralization and security nature, Blockchain has a great potential to improve point cloud services and enhance security and privacy preservation. Inspired by the rationales behind Software Defined Network (SDN) technology, this paper envisions SAUSA, a blockchain-based authentication network that is capable of recording, tracking, and auditing the access, usage, and storage of 3D point cloud data sets in their life-cycle in a decentralized manner. SAUSA adopts an SDN-enabled point cloud service architecture which allows for efficient data processing and delivery to satisfy diverse Quality-of-Service (QoS) requirements. A blockchain-based authentication framework is proposed to ensure security and privacy preservation in point cloud data acquisition, storage, and analytics. Leveraging smart contracts for digitizing access control policies and point cloud data on the blockchain, data owners have full control of their 3D sensors and point clouds. In addition, anyone can verify the authenticity and integrity of point clouds in use without relying on a third party. Moreover, SAUSA integrates a decentralized storage platform to store encrypted point clouds while recording references of raw data on the distributed ledger. Such a hybrid on-chain and off-chain storage strategy not only improves robustness and availability but also ensures privacy preservation for sensitive information in point cloud applications. A proof-of-concept prototype is implemented and tested on a physical network. The experimental evaluation validates the feasibility and effectiveness of the proposed SAUSA solution.