Zonguldak Bülent Ecevit University

BACKGROUND: Patients on kidney replacement therapy comprise a vulnerable population and may be at increased risk of death from coronavirus disease 2019 (COVID-19). Currently, only limited data are available on outcomes in this patient population. METHODS: We set up the ERACODA (European Renal Association COVID-19 Database) database, which is specifically designed to prospectively collect detailed data on kidney transplant and dialysis patients with COVID-19. For this analysis, patients were included who presented between 1 February and 1 May 2020 and had complete information available on the primary outcome parameter, 28-day mortality. RESULTS: Of the 1073 patients enrolled, 305 (28%) were kidney transplant and 768 (72%) dialysis patients with a mean age of 60 ± 13 and 67 ± 14 years, respectively. The 28-day probability of death was 21.3% [95% confidence interval (95% CI) 14.3-30.2%] in kidney transplant and 25.0% (95% CI 20.2-30.0%) in dialysis patients. Mortality was primarily associated with advanced age in kidney transplant patients, and with age and frailty in dialysis patients. After adjusting for sex, age and frailty, in-hospital mortality did not significantly differ between transplant and dialysis patients [hazard ratio (HR) 0.81, 95% CI 0.59-1.10, P = 0.18]. In the subset of dialysis patients who were a candidate for transplantation (n = 148), 8 patients died within 28 days, as compared with 7 deaths in 23 patients who underwent a kidney transplantation <1 year before presentation (HR adjusted for sex, age and frailty 0.20, 95% CI 0.07-0.56, P < 0.01). CONCLUSIONS: The 28-day case-fatality rate is high in patients on kidney replacement therapy with COVID-19 and is primarily driven by the risk factors age and frailty. Furthermore, in the first year after kidney transplantation, patients may be at increased risk of COVID-19-related mortality as compared with dialysis patients on the waiting list for transplantation. This information is important in guiding clinical decision-making, and for informing the public and healthcare authorities on the COVID-19-related mortality risk in kidney transplant and dialysis patients.

Only a small percentage of insect species are pests. However, pest species cause significant losses in agricultural and forest crops, and many are vectors of diseases. Currently, many scientists are focused on developing new tools to control insect populations, including secondary plant metabolites, e.g., alkaloids, glycoalkaloids, terpenoids, organic acids and alcohols, which show promise for use in plant protection. These compounds can affect insects at all levels of biological organization, but their action generally disturbs cellular and physiological processes, e.g., by altering redox balance, hormonal regulation, neuronal signalization or reproduction in exposed individuals. Secondary plant metabolites cause toxic effects that can be observed at both lethal and sublethal levels, but the most important effect is repellence. Plants from the Solanaceae family, which contains numerous economically and ecologically important species, produce various substances that affect insects belonging to most orders, particularly herbivorous insects and other pests. Many compounds possess insecticidal properties, but they are also classified as molluscides, acaricides, nematocides, fungicides and bactericides. In this paper, we present data on the sublethal and lethal toxicity caused by pure metabolites and crude extracts obtained from Solanaceae plants. Pure substances as well as water and/or alcohol extracts cause lethal and sublethal effects in insects, which is important from the economical point of view. We discuss the results of our study and their relevance to plant protection and management.

Nanoparticles consisting of human therapeutic drugs are suggested as a promising strategy for targeted and localized drug delivery to tumor cells. In this study, 5‐fluorouracil (5‐FU) encapsulated chitosan nanoparticles were prepared in order to investigate potentials of localized drug delivery for tumor environment due to pH sensitivity of chitosan nanoparticles. Optimization of chitosan and 5‐FU encapsulated nanoparticles production revealed 148.8 ± 1.1 nm and 243.1 ± 17.9 nm particle size diameters with narrow size distributions, which are confirmed by scanning electron microscope (SEM) images. The challenge was to investigate drug delivery of 5‐FU encapsulated chitosan nanoparticles due to varied pH changes. To achieve this objective, pH sensitivity of prepared chitosan nanoparticle was evaluated and results showed a significant swelling response for pH 5 with particle diameter of ~ 450 nm. In vitro release studies indicated a controlled and sustained release of 5‐FU from chitosan nanoparticles with the release amounts of 29.1–60.8% due to varied pH environments after 408 h of the incubation period. pH sensitivity is confirmed by mathematical modeling of release kinetics since chitosan nanoparticles showed stimuli‐induced release. Results suggested that 5‐FU encapsulated chitosan nanoparticles can be launched as pH‐responsive smart drug delivery agents for possible applications of cancer treatments.

The Achilles tendon is the strongest and thickest tendon in the human body. It is also the commonest tendon to rupture. It begins near the middle of the calf and is the conjoint tendon of the gastrocnemius and soleus muscles. The relative contribution of the two muscles to the tendon varies. Spiralisation of the fibres of the tendon produces an area of concentrated stress and confers a mechanical advantage. The calcaneal insertion is specialised and designed to aid the dissipation of stress from the tendon to the calcaneum. The insertion is crescent shaped and has significant medial and lateral projections. The blood supply of the tendon is from the musculotendinous junction, vessels in surrounding connective tissue and the osteotendinous junction. The vascular territories can be classified simply in three, with the midsection supplied by the peroneal artery, and the proximal and distal sections supplied by the posterior tibial artery. This leaves a relatively hypovascular area in the mid-portion of the tendon where most problems occur. The Achilles tendon derives its innervation from the sural nerve with a smaller supply from the tibial nerve. Tenocytes produce type I collagen and form 90% of the cellular component of the normal tendon. Evidence suggests ruptured or pathological tendon produce more type III collagen, which may affect the tensile strength of the tendon. Direct measurements of forces reveal loading in the Achilles tendon as high as 9 KN during running, which is up to 12.5 times body weight.

Non‐orthogonal multiple access (NOMA) is a strong candidate for next generation radio access networks due to its ability of serving multiple users using the same time and frequency resources. Therefore, researchers in academia and industry have been recently investigating the error performances and capacity of NOMA schemes. The main drawback of NOMA techniques is the interference among users due to the its non‐orthogonal access nature, that is usually solved by interference cancellation techniques such as successive interference cancellation (SIC) at the receivers. On the other hand, the interference among users may not be completely eliminated in the SIC process due to the erroneous decisions in the receivers usually caused by channels. In this study, for the first time in the literature, the authors derive an exact closed‐form bit error rate (BER) expressions under SIC error for downlink NOMA over Rayleigh fading channels. Besides, they derive one‐degree integral form exact BER expressions and closed‐form approximate expressions for uplink NOMA. Then, the derived expressions are validated by simulations. The numerical results are depicted to reveal the effects of error during SIC process on the performance for various cases such as power allocation for downlink and channel quality difference for uplink.

The early detection and prevention of plant diseases that are an important cause of famine and food insecurity worldwide are very important for increasing agricultural product productivity. Not only the early detection of the plant disease but also the determination of its type play a critical role in determining the appropriate treatment. The fact that visual inspection, which is frequently used in determining plant disease and types, is tiring and prone to human error, necessitated the development of algorithms that can automatically classify plant disease with high accuracy and low computational cost. In this study, a new hybrid plant leaf disease classification model with high accuracy and low computational complexity, consisting of the wrapper approach, including the flower pollination algorithm (FPA) and support vector machine (SVM), and a convolutional neural network (CNN) classifier, is developed with a wrapper-based feature selection approach using metaheuristic optimization techniques. The features of the image dataset consisting of apple, grape, and tomato plants have been extracted by a two-dimensional discrete wavelet transform (2D-DWT) using wavelet families such as biorthogonal, Coiflets, Daubechies, Fejer-Korovkin, and symlets. Features that keep classifier performance high for each family are selected by the wrapper approach, consisting of the population-based metaheuristics FPA and SVM. The performance of the proposed optimization algorithm is compared with the particle swarm optimization (PSO) algorithm. Afterwards, the classification performance is obtained by using the lowest number of features that can keep the classification performance high for the CNN classifier. The CNN classifier with a single layer of classification without a feature extraction layer is used to minimize the complexity of the model and to deal with the model hyperparameter problem. The obtained model is embedded in the NVIDIA Jetson Nano developer kit on the unmanned aerial vehicle (UAV), and real-time classification tests are performed on apple, grape, and tomato plants. The experimental results obtained show that the proposed model classifies the specified plant leaf diseases in real time with high accuracy. Moreover, it is concluded that the robust hybrid classification model, which is created by selecting the lowest number of features with the optimization algorithm with low computational complexity, can classify plant leaf diseases in real time with precision.

Lipoma within an inverted Meckel's diverticulum presenting with hemorrhage and partial intestinal obstruction is an exceptional clinical entity. We report a case of 47-year-old male with a history of recurrent episodes of partial intestinal obstruction and melena due to a subserosal lipoma located in the base of an inverted Meckel's diverticulum. According to our knowledge, this is the first case of a lipoma within a Meckel's diverticulum giving rise to this clinical scenario without the existence of heterotrophic gastric or pancreatic tissues.

Epidemiological studies reported adverse effects of air pollution on the prevalence of respiratory diseases in children. The purpose of this study was to examine the association between air pollution and admissions for asthma and other respiratory diseases among children who were younger than 15 yr of age. The study used data on respiratory hospital admissions and air pollutant concentrations, including thoracic particulate matter (PM(10)), fine (PM(2.5)), and coarse (PM(10-2.5)) particulate matter in Zonguldak, Turkey. A bidirectional case-crossover design was used to calculate odds ratios for the admissions adjusted for daily meteorological parameters. Significant increases were observed for hospital admissions in children for asthma, allergic rhinitis (AR), and upper (UPRD) and lower (LWRD) respiratory diseases. All fraction of PM in children showed significant positive associations with asthma admissions. The highest association noted was 18% rise in asthma admissions correlated with a 10-microg/m(3) increase in PM(10-2.5) on the same day of admissions. The adjusted odds ratios for exposure to PM(2.5) with an increment of 10 microg/m(3) were 1.15 and 1.21 for asthma and allergic rhinitis with asthma, respectively. PM(10) exerted significant effects on hospital admissions for all outcomes, including asthma, AR, UPRD, and LWRD. Our study suggested a greater effect of fine and coarse PM on asthma hospital admissions compared with PM(10) in children.

The Polarimetric Synthetic Aperture Radar technique has provided various opportunities and challenges in agricultural activities mainly on crop management. The aim of this study is to investigate the sensitivity of 10 parameters derived from multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) data, to crop height and canopy coverage (CC) of maize, sunflower, and wheat. The correlation coefficient values indicate a high correlation for maize during the early growing stage. The coefficient determinations (R2) of 0.82 and 0.81 indicate that there is a strong relationship between the maize height and SAR parameters including VV + VH and VV, respectively. The maize CC is well correlated with VV parameter (R2 = 0.73), but it is observed that at the later growing stage the correlation became weaker. This means that the sensitivity decreases with increasing vegetation cover growth. Compared to maize, the sensitivity of SAR parameters to wheat variables is often good at the early stage. However, the highest correlation with wheat height represented by Alpha (α) decomposition parameter (R2 = 0.67). The sunflower height has an insignificant correlation with the majority of SAR parameters and only VH polarization shows low sensitivity (R2 = 0.31). The sunflower CC shows relatively higher correlation with VV polarization (R2 = 0.46) at the early stage while no considerable correlation is observed at the later stage. It is found that Sentinel-1 has a high potential for estimation of crop height and CC of the maize as a broad-leaf crop. The same is not true for sunflower as another broad-leaf crop.

The Pontocaspian (Black Sea - Caspian Sea) region has a very dynamic history of basin development and biotic evolution. The region is the remnant of a once vast Paratethys Sea. It contains some of the best Eurasian geological records of tectonic, climatic and paleoenvironmental change. The Pliocene-Quaternary co-evolution of the Black Sea-Caspian Sea is dominated by major changes in water (lake and sea) levels resulting in a pulsating system of connected and isolated basins. Understanding the history of the region, including the drivers of lake level and faunal evolution, is hampered by indistinct stratigraphic nomenclature and contradicting time constraints for regional sedimentary successions. In this paper we review and update the late Pliocene to Quaternary stratigraphic framework of the Pontocaspian domain, focusing on the Black Sea Basin, Caspian Basin, Marmara Sea and the terrestrial environments surrounding these large, mostly endorheic lake-sea systems.

BACKGROUND: Chronic kidney disease (CKD) and immunosuppression, such as in renal transplantation (RT), stand as one of the established potential risk factors for severe coronavirus disease 2019 (COVID-19). Case morbidity and mortality rates for any type of infection have always been much higher in CKD, haemodialysis (HD) and RT patients than in the general population. A large study comparing COVID-19 outcome in moderate to advanced CKD (Stages 3-5), HD and RT patients with a control group of patients is still lacking. METHODS: We conducted a multicentre, retrospective, observational study, involving hospitalized adult patients with COVID-19 from 47 centres in Turkey. Patients with CKD Stages 3-5, chronic HD and RT were compared with patients who had COVID-19 but no kidney disease. Demographics, comorbidities, medications, laboratory tests, COVID-19 treatments and outcome [in-hospital mortality and combined in-hospital outcome mortality or admission to the intensive care unit (ICU)] were compared. RESULTS: A total of 1210 patients were included [median age, 61 (quartile 1-quartile 3 48-71) years, female 551 (45.5%)] composed of four groups: control (n = 450), HD (n = 390), RT (n = 81) and CKD (n = 289). The ICU admission rate was 266/1210 (22.0%). A total of 172/1210 (14.2%) patients died. The ICU admission and in-hospital mortality rates in the CKD group [114/289 (39.4%); 95% confidence interval (CI) 33.9-45.2; and 82/289 (28.4%); 95% CI 23.9-34.5)] were significantly higher than the other groups: HD = 99/390 (25.4%; 95% CI 21.3-29.9; P < 0.001) and 63/390 (16.2%; 95% CI 13.0-20.4; P < 0.001); RT = 17/81 (21.0%; 95% CI 13.2-30.8; P = 0.002) and 9/81 (11.1%; 95% CI 5.7-19.5; P = 0.001); and control = 36/450 (8.0%; 95% CI 5.8-10.8; P < 0.001) and 18/450 (4%; 95% CI 2.5-6.2; P < 0.001). Adjusted mortality and adjusted combined outcomes in CKD group and HD groups were significantly higher than the control group [hazard ratio (HR) (95% CI) CKD: 2.88 (1.52-5.44); P = 0.001; 2.44 (1.35-4.40); P = 0.003; HD: 2.32 (1.21-4.46); P = 0.011; 2.25 (1.23-4.12); P = 0.008), respectively], but these were not significantly different in the RT from in the control group [HR (95% CI) 1.89 (0.76-4.72); P = 0.169; 1.87 (0.81-4.28); P = 0.138, respectively]. CONCLUSIONS: Hospitalized COVID-19 patients with CKDs, including Stages 3-5 CKD, HD and RT, have significantly higher mortality than patients without kidney disease. Stages 3-5 CKD patients have an in-hospital mortality rate as much as HD patients, which may be in part because of similar age and comorbidity burden. We were unable to assess if RT patients were or were not at increased risk for in-hospital mortality because of the relatively small sample size of the RT patients in this study.

Diabetic retinopathy (DR), which is seen in approximately one-third of diabetes patients worldwide, leads to irreversible vision loss and even blindness if not diagnosed and treated in time. It is vital to limit the progression of DR disease in order to prevent the loss of vision in diabetic patients. It is therefore essential that DR disease is diagnosed at an early phase. Thanks to retinal screening at least twice a year, DR disease can be diagnosed in its early phases. However, due to the variations and complexity of DR, it is really difficult to determine the phase of DR disease in current clinical diagnoses. This paper presents a robust artificial intelligence (AI)-based model that can overcome nonlinear dynamics with low computational complexity and high classification accuracy using fundus images to determine the phase of DR disease. The proposed model consists of four stages, excluding the preprocessing stage. In the preprocessing stage, fractal analysis is performed to reveal the presence of chaos in the dataset consisting of 12,500 color fundus images. In the first stage, two-dimensional stationary wavelet transform (2D-SWT) is applied to the dataset consisting of color fundus images in order to prevent information loss in the images and to reveal their characteristic features. In the second stage, 96 features are extracted by applying statistical- and entropy-based feature functions to approximate, horizontal, vertical, and diagonal matrices of 2D-SWT. In the third stage, the features that keep the classifier performance high are selected by a chaotic-based wrapper approach consisting of the k-nearest neighbor (kNN) and chaotic particle swarm optimization algorithms (CPSO) to cope with both chaoticity and computational complexity in the fundus images. At the last stage, an AI-based classification model is created with the recurrent neural network-long short-term memory (RNN-LSTM) architecture by selecting the lowest number of feature sets that can keep the classification performance high. The performance of the DR disease classification model was tested on 2500 color fundus image data, which included five classes: no DR, mild non-proliferative DR (NPDR), moderate NPDR, severe NPDR, and proliferative DR (PDR). The robustness of the DR disease classification model was confirmed by the 10-fold cross-validation. In addition, the classification performance of the proposed model is compared with the support vector machine (SVM), which is one of the machine learning techniques. The results obtained show that the proposed model can overcome nonlinear dynamics in color fundus images with low computational complexity and is very effective and successful in precisely diagnosing all phases of DR disease.

In both developing and industrialized countries, deviation from a planned time schedule is one of the most frequently encountered problems in construction investments. Various factors faced with during construction period prevent systematic flow of work, which causes time-based anomalies as a conclusion. Considering the vital importance of the construction industry on the macro-economic structure of a country, it is inevitable to be aware of considerable effect of the timely completion on the allocated project budget. In this study, causes of time extensions in the Turkish construction industry and levels of their importance were examined together. In total, 34 factors affecting project duration were taken into account. A questionnaire survey, including these factors, was then applied to 71 construction companies in Turkey, and the outcomes were evaluated by means of statistical analyses. According to the results, “design and material changes” was found to be the most predominant factor, followed by “delay of payments” and “cash flow problems”. In terms of importance levels of factor groups, financial factors were found to be the first group, while environmental factors were the least effective group. It should be also noted that managerial causes of time extensions are encountered in developed and developing countries, whereas financial causes are experienced in developing countries only.

The archaeological documentation of the development of sedentary farming societies in Anatolia is not yet mirrored by a genetic understanding of the human populations involved, in contrast to the spread of farming in Europe [1Bramanti B. Thomas M.G. Haak W. Unterlaender M. Jores P. Tambets K. Antanaitis-Jacobs I. Haidle M.N. Jankauskas R. Kind C.-J. et al.Genetic discontinuity between local hunter-gatherers and central Europe’s first farmers.Science. 2009; 326: 137-140Crossref PubMed Scopus (363) Google Scholar, 2Skoglund P. Malmström H. Raghavan M. Storå J. Hall P. Willerslev E. Gilbert M.T.P. Götherström A. Jakobsson M. Origins and genetic legacy of Neolithic farmers and hunter-gatherers in Europe.Science. 2012; 336: 466-469Crossref PubMed Scopus (381) Google Scholar, 3Lazaridis I. Patterson N. Mittnik A. Renaud G. Mallick S. Kirsanow K. Sudmant P.H. Schraiber J.G. Castellano S. Lipson M. et al.Ancient human genomes suggest three ancestral populations for present-day Europeans.Nature. 2014; 513: 409-413Crossref PubMed Scopus (750) Google Scholar]. Sedentary farming communities emerged in parts of the Fertile Crescent during the tenth millennium and early ninth millennium calibrated (cal) BC and had appeared in central Anatolia by 8300 cal BC [4Baird D. The Late Epipaleolithic, Neolithic, and Chalcolithic of the Anatolian Plateau, 13,000–4000 BC.in: Potts D. A Companion to the Archaeology of the Ancient Near East. Wiley-Blackwell, 2012: 431-466Crossref Scopus (40) Google Scholar]. Farming spread into west Anatolia by the early seventh millennium cal BC and quasi-synchronously into Europe, although the timing and process of this movement remain unclear. Using genome sequence data that we generated from nine central Anatolian Neolithic individuals, we studied the transition period from early Aceramic (Pre-Pottery) to the later Pottery Neolithic, when farming expanded west of the Fertile Crescent. We find that genetic diversity in the earliest farmers was conspicuously low, on a par with European foraging groups. With the advent of the Pottery Neolithic, genetic variation within societies reached levels later found in early European farmers. Our results confirm that the earliest Neolithic central Anatolians belonged to the same gene pool as the first Neolithic migrants spreading into Europe. Further, genetic affinities between later Anatolian farmers and fourth to third millennium BC Chalcolithic south Europeans suggest an additional wave of Anatolian migrants, after the initial Neolithic spread but before the Yamnaya-related migrations. We propose that the earliest farming societies demographically resembled foragers and that only after regional gene flow and rising heterogeneity did the farming population expansions into Europe occur.

The aim of this study was to compare the responses of colistin treatment alone vs. a combination of colistin and rifampicin in the treatment of ventilator-associated pneumonia (VAP) caused by a carbapenem-resistant A. baumannii strain. Forty-three patients were randomly assigned to one of two treatment groups. Although clinical (P = 0·654), laboratory (P = 0·645), radiological (P = 0·290) and microbiological (P = 0·597) response rates were better in the combination group, these differences were not significant. However, time to microbiological clearance (3·1 ± 0·5 days, P = 0·029) was significantly shorter in the combination group. The VAP-related mortality rates were 63·6% (14/22) and 38·1% (8/21) for the colistin and the combination groups (P = 0·171), respectively. Our results suggest that the combination of colistin with rifampicin may improve clinical and microbiological outcomes of VAP patients infected with A. baumannii.

On February 6, 2023, two large earthquakes occurred near the Turkish town of Kahramanmaraş. The moment magnitude (Mw) 7.8 mainshock ruptured a 310 km-long segment of the left-lateral East Anatolian Fault, propagating through multiple releasing step-overs. The Mw 7.6 aftershock involved nearby left-lateral strike-slip faults of the East Anatolian Fault Zone, causing a 150 km-long rupture. We use remote-sensing observations to constrain the spatial distribution of coseismic slip for these two events and the February 20 Mw 6.4 aftershock near Antakya. Pixel tracking of optical and synthetic aperture radar data of the Sentinel-2 and Sentinel-1 satellites, respectively, provide near-field surface displacements. High-rate Global Navigation Satellite System data constrain each event separately. Coseismic slip extends from the surface to about 15 km depth with a shallow slip deficit. Most aftershocks cluster at major fault bends, surround the regions of high coseismic slip, or extend outward of the ruptured faults. For the mainshock, rupture propagation stopped southward at the diffuse termination of the East Anatolian fault and tapered off northward into the Pütürge segment, some 20 km south of the 2020 Mw 6.8 Elaziğ earthquake, highlighting a potential seismic gap. These events underscore the high seismic potential of immature fault systems.

We study the effects of electrical and chemical autapse on the temporal coherence or firing regularity of single stochastic Hodgkin-Huxley neurons and scale-free neuronal networks. Also, we study the effects of chemical autapse on the occurrence of spatial synchronization in scale-free neuronal networks. Irrespective of the type of autapse, we observe autaptic time delay induced multiple coherence resonance for appropriately tuned autaptic conductance levels in single neurons. More precisely, we show that in the presence of an electrical autapse, there is an optimal intensity of channel noise inducing the multiple coherence resonance, whereas in the presence of chemical autapse the occurrence of multiple coherence resonance is less sensitive to the channel noise intensity. At the network level, we find autaptic time delay induced multiple coherence resonance and synchronization transitions, occurring at approximately the same delay lengths. We show that these two phenomena can arise only at a specific range of the coupling strength, and that they can be observed independently of the average degree of the network.

The aim of the present study was to evaluate the possible protective effects of Nigella sativa L. (NS) against beta-cell damage from streptozotocin (STZ)-induced diabetes in rats. STZ was injected intraperitoneally at a single dose of 50 mg/kg to induce diabetes. NS (0.2 ml/kg/day, i.p.) was injected for 3 days prior to STZ administration, and these injections were continued throughout the 4-week study. Oxidative stress is believed to play a role in the pathogenesis of diabetes mellitus (DM). To assess changes in the cellular antioxidant defense system, we measured the activities of antioxidant enzymes (such as glutathione peroxidase (GSHPx), superoxide dismutase (SOD), and catalase (CAT)) in pancreatic homogenates. We also measured serum nitric oxide (NO) and erythrocyte and pancreatic tissue malondialdehyde (MDA) levels, a marker of lipid peroxidation, to determine whether there is an imbalance between oxidant and antioxidant status. Pancreatic beta-cells were examined by immunohistochemical methods. STZ induced a significant increase in lipid peroxidation and serum NO concentrations, and decreased antioxidant enzyme activity. NS treatment has been shown to provide a protective effect by decreasing lipid peroxidation and serum NO, and increasing antioxidant enzyme activity. Islet cell degeneration and weak insulin immunohistochemical staining was observed in rats with STZ-induced diabetes. Increased intensity of staining for insulin, and preservation of beta-cell numbers were apparent in the NS-treated diabetic rats. These findings suggest that NS treatment exerts a therapeutic protective effect in diabetes by decreasing oxidative stress and preserving pancreatic beta-cell integrity. Consequently, NS may be clinically useful for protecting beta-cells against oxidative stress.

In this study, ground glass powder and crushed waste glass were used to replace coarse and fine aggregates. Within the scope of the study, fine aggregate (FA) and coarse aggregate (CA) were changed separately with proportions of 10%, 20%, 40%, and 50%. According to the mechanical test, including compression, splitting tensile, and flexural tests, the waste glass powder creates a better pozzolanic effect and increases the strength, while the glass particles tend to decrease the strength when they are swapped with aggregates. As observed in the splitting tensile test, noteworthy progress in the tensile strength of the concrete was achieved by 14%, while the waste glass used as a fractional replacement for the fine aggregate. In samples where glass particles were swapped with CA, the tensile strength tended to decrease. It was noticed that with the adding of waste glass at 10%, 20%, 40%, and 50% of FA swapped, the increase in flexural strength was 3.2%, 6.3%, 11.1%, and 4.8%, respectively, in amount to the reference one (6.3 MPa). Scanning electron microscope (SEM) analysis consequences also confirm the strength consequences obtained from the experimental study. While it is seen that glass powder provides better bonding with cement with its pozzolanic effect and this has a positive effect on strength consequences, it is seen that voids are formed in the samples where large glass pieces are swapped with aggregate and this affects the strength negatively. Furthermore, simple equations using existing data in the literature and the consequences obtained from the current study were also developed to predict mechanical properties of the concrete with recycled glass for practical applications. Based on findings obtained from our study, 20% replacement for FA and CA with waste glass is recommended.

Global optimization of Pd−Au bimetallic clusters in the size range N = 2−50 has been performed using a genetic algorithm, coupled with the Gupta many-body empirical potential (EP) to model interatomic interactions. Three sets of EP parameters have been examined in this work: (a) an average of pure Pd and Au parameters, (b) experimental Pd−Au-fitted parameters, and (c) DFT-fitted parameters. Stability criteria, such as binding energy and second difference in energy, have been used to determine the lowest energy structures, that is, the global minima (GM). DFT local relaxations have been performed on all the “putative” GM structures for 1:1 compositions of (Pd−Au)N/2 up to N = 50 for the three sets of EP parameters. It is found that the average parameter set a leads to a PdcoreAushell segregation, whereas the fitted parameter sets b and c lead to more Pd−Au mixing. DFT reoptimization of the structures produced by potentials a, b, and c shows small differences in binding energies. In addition, 34- and 38-atom Pd−Au clusters were studied using these three Gupta potential parametrizations as a function of composition and analyzed in terms of their mixing energies and chemical order parameters. DFT relaxations were performed on the lowest mixing energy compositions, allowing us to have a clearer description of the energy landscape for all three EP parameter sets at these cluster sizes. For the compositions, Pd17Au17 and Pd19Au19, DFT calculations confirm that some degree of Au surface segregation is energetically preferred, though it is not necessarily complete PdcoreAushell segregation, as predicted by the average potential a.