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Familial Mediterranean Fever (FMF) is classified as an autoinflammatory genetic disease inherited by mutations in MEFV. These mutations can affect the dysregulation of inflammatory processes in the human body and lead to fever and pain in the chest and abdomen. Many known missense mutations in MEFV are linked to FMF disease. Mutations in MEFV in most cases are located on the short arm of chromosome 16 and can impair the function of the pyrin protein. In this research, we aimed to examine the entire exons of MEFV for 13 cases (8 females and 5 males) with FMF diagnosis from Southwest Iran. Hence, we amplified and sequenced the exons of MEFV and then, in-silico analysis of detected changes was applied to estimate the probability of pathogenicity for the identified variants. Finally, we found five single nucleotide substitutions, including M694V (c.2080A>G), R202Q (c.605G>A), E447G (c.1430A>G), E148Q (c.442G>C), and V726A (c.2177T>C), in the under-represented patients. The most frequent mutations in our study were R202Q (38.46%) within exon 2 and M694V (30.7%) within exon 10. Other mutations accounted for a further 23% of the alleles, including E477G (7.6%), E148Q (7.6%), and V726A (7.6%). According to the in-silico analyses, including variation pathogenicity, protein structure, and allele frequency assessments, we concluded that all these variants could be considered in FMF molecular profiling in southwest Iran.

PurposeThe perception of sport consumers on peripheral stadium-quality services (PSQS) has evolved after compulsory precautionary measures were imposed on gatherings to alleviate the spread of coronavirus. This study attempts to reassess five principal dimensions of PSQS? Stadium parking, stadium cleanliness, fan control, food services and perceived crowding? through reflecting on the COVID-19 control and prevention measures established during this pandemic. Furthermore, it aims to measure the impact of the multi-dimensional PSQS on spectators' emotions and future attendance intentions.Design/methodology/approachThe purposive sampling technique was used to collect data from spectators watching the live matches of cricket at the stadium. A total of 680 responses were collected from spectators and uploaded to the measurement model. The covariance-based structural equation modeling technique was used subsequently for analysis purposes.FindingsThe study found a positive impact of the stadium cleanliness and fan control services on spectators' happiness and excitement emotions; and a negative impact of stadium parking, stadium cleanliness, fan control and perceived crowding on their anger, anxiety and dejection emotions. The happiness and excitement emotions of the spectators induced them to visit again at the stadium. Of all the peripheral quality services, the study found only stadium cleanliness service indirectly effect spectators' revisit intentions through excitement emotion as a mediator.Research limitations/implicationsThe incorporation of the safety procedures through PSQS can reduce spectators' negative emotions especially when they face psychological fear of the pandemic. These services work as a stimulus for spectators that directly affect their organism (emotions) and indirectly affect their response (attendance intentions).Originality/valueThis study contributed to sports research by novelty evaluating sport consumers' perception of the PSQS after incorporating COVID-19 preventive measures. It empirically examines the effect PSQS on spectators' emotions and re-visits intentions.

An electrochemical biosensor was fabricated based on polypyrrole/octahedral Pd-doped Co3O4 composite- and ds-DNA-modified screen-printed electrodes for detecting pralatrexate.

Stress-strain and moment-curvature behavior of the reinforced concrete (RC) square columns have been analytically investigated according to different confined concrete models. The effect of transverse reinforcement diameter, transverse reinforcement spacing and concrete grade on the behavior of RC column models were investigated. For different confined concrete models, the confinement effectiveness coefficient, effective lateral confining stress, confined concrete compressive strength, strain at maximum concrete stress and ultimate concrete compressive strain values were calculated. In the second part, a parametric investigation was carried out for examining the effects of different design parameters on the moment-curvature relationships. Analytical moment-curvature relationships were obtained for RC cross-sections by using the TBEC (2018), Mander model (1988), Saatcioglu and Ravzi (1992) confined concrete models. The effects of the design parameters on the RC square column behavior were evaluated in terms of moment capacity and the curvature of the cross-section. In RC column models, stress-strain and moment-curvature relationships are obtained and compared according to different parameters. Confined concrete strength and the ultimate moment values obtained from the Mander model were higher than the Saatcioglu and Ravzi model when the transverse reinforcement close to the minimum spacing values. The results obtained from the Mander model and TBEC (2018) are close to each other.

Deep learning utilizing convolutional neural networks (CNNs) applied to hematoxylineosin (HE)-stained slides numerically encodes histomorphological tumor features. Tumor heterogeneity is an emerging biomarker in colon cancer that is, captured by these features, whereas microsatellite instability (MSI) is an established biomarker traditionally assessed by immunohistochemistry or polymerase chain reaction.HE-stained slides from The Cancer Genome Atlas (TCGA) colon cohort are passed through the CNN. Resulting imaging features are used to cluster morphologically similar slide regions. Tile-level pairwise similarities are calculated and used to generate a tumor heterogeneity score (THS). Patient-level THS is then correlated with TCGA-reported biomarkers, including MSI-status.HE-stained images from 313 patients generated 534 771 tiles. Deep learning automatically identified and annotated cells by type and clustered morphologically similar slide regions. MSI-high tumors demonstrated significantly higher THS than MSS/MSI-low (p 0.001). THS was higher in MLH1-silent versus non-silent tumors (p 0.001). The sequencing derived MSIsensor score also correlated with THS (r = 0.51, p 0.0001).Deep learning provides spatially resolved visualization of imaging-derived biomarkers and automated quantification of tumor heterogeneity. Our novel THS correlates with MSI-status, indicating that with expanded training sets, translational tools could be developed that predict MSI-status using HE-stained images alone.

A saturation–capillary pressure relationship is proposed that is applicable for all wettabilities, including mixed-wet and oil-wet or hydrophobic media. This formulation is more flexible than existing correlations that only match water-wet data, while also allowing saturation to be written as a closed-form function of capillary pressure: we can determine capillary pressure explicitly from saturation, and vice versa. We propose $$P_{{\text{c}}} = A + B\tan \left( {\frac{\pi }{2} - \pi S_{e}^{C} } \right)\,{\text{for}}\,0 \le S_{{\text{e}}} \le 1,$$ P c = A + B tan π 2 - π S e C for 0 ≤ S e ≤ 1 , where $$S_{{\text{e}}}$$ S e is the normalized saturation. A indicates the wettability: $$A>0$$ A > 0 is a water-wet medium, $$A A < 0 is hydrophobic while small A suggests mixed wettability. B represents the average curvature and pore-size distribution which can be much lower in mixed-wet compared to water-wet media with the same pore structure if the menisci are approximately minimal surfaces. C is an exponent that controls the inflection point in the capillary pressure and the asymptotic behaviour near end points. We match the model accurately to 29 datasets in the literature for water-wet, mixed-wet and hydrophobic media, including rocks, soils, bead and sand packs and fibrous materials with over four orders of magnitude difference in permeability and porosities from 20% to nearly 90%. We apply Leverett J-function scaling to make the expression for capillary pressure dimensionless and discuss the behaviour of analytical solutions for spontaneous imbibition.

Summary Relative permeability (kr) is commonly modeled as an empirical function of phase saturation. Although current empirical models can provide a good match of one or two measured relative permeabilities using saturation alone, they are unable to predict relative permeabilities well when there is hysteresis or when physical properties such as wettability change. Further, current models often result in relative permeability discontinuities that can cause convergence and accuracy problems in simulation. To overcome these problems, recent research has modeled relative permeability as a state function of both saturation (S) and phase connectivity (X). Pore network modeling (PNM) data, however, show small differences in relative permeability for the same S-X value when approached from a different flow direction. This paper examines the impact of one additional Minkowski parameter (Mecke and Arns 2005), the fluid-fluid interfacial area, on relative permeability to identify if that satisfactorily explains this discrepancy. We calculate the total fluid-fluid interfacial areas (IA) during two-phase (oil/water) flow in porous media using PNM. The area is calculated from PNM simulations using the areas associated with corners and throats in pore elements of different shapes. The pore network is modeled after a Bentheimer sandstone, using square, triangular prism, and circular pore shapes. Simulations were conducted for numerous primary drainage (PD) and imbibition cycles at a constant contact angle of 0° for the wetting phase. Simultaneous measurements of capillary pressure, relative permeability, saturation, and phase connectivity are made for each displacement. The fluid-fluid IA is calculated from the PNM capillary pressure, the fluid location in the pore elements, and the pore element dimensional data. The results show that differences in the relative permeability at the same (S, X) point are explained well by differences in the fluid-fluid interfacial area (IA). That is, for a larger change in IA at these intersection points, the permeability difference is greater. That difference in relative permeability approaches zero as the difference in IA approaches zero. This confirms that relative permeability can be modeled better as a unique function of S, X, and IA. The results also show that an increase in IA restricts flow decreasing the nonwetting (oil) phase permeability. This decrease is caused by an increase in the throat area fraction compared to the corner area as the total area IA increases. The wetting phase relative permeability, however, shows the inverse trend in that its relative permeability is greater when IA becomes larger owing to a greater fraction of the total area associated with the corners. The area IA, however, impacts the nonwetting phase relative permeability more than the wetting phase relative permeability. Corner flow improves the wetting phase relative permeability because the wetting phase is continuous there. Finally, a sensitivity analysis shows that relative permeability is more sensitive to change in S than it is for IA for the case studied, implying that if only two parameters are used to model relative permeability, it is better to choose S and X.

Depression and mental health-related issues are increasingly prevalent in young adolescents and adults and so is the use of Complementary Therapies (CTs) to treat depression. Systematic reviews have found that, of all CTs, acupuncture, exercise, and the herbal remedy St John’s Wort have the greatest amount of evidence for efficacy in treating depression. We aimed to assess Mental Health Literacy (MHL) levels in the treatment of depression and Complementary Therapy’s (CT) usage in adolescents and adults. Surveys were distributed to a pre-existing cohort of community women; and a group of young athletes and university students (n = 156, aged ≥16 years). Participant’s level of MHL and the CT’s usage for their personal health was assessed. MHL regarding the identification of depressive symptoms was low, particularly in males aged under 35 years. The majority (59%) of participants utilized CTs 12 months prior to survey completion. Evidence-based professional services were perceived more helpful than self-help methods in treating depressive symptoms. Our findings support previous research indicating high levels of use of CTs. Whilst there was a favorable regard for professional services, greater education regarding the identification of depressive symptoms in young men is needed to improve the MHL in this population.

Zlepšujeme přesnost a rychlost výpočtu plně normalizovaných přidružených Legendreových funkcí (fnALF) pro ultra vysoké stupně a řády používaných ve sférických harmonických transformacích. S využitím jejich numerického chování byly navrženy dvě nové metody řešení problému podtečení/přetečení při jejich výpočtu. Aplikace těchto dvou metod je testována pomocí rekurze s rostoucím stupněm a pevným řádem. První metoda používá postupné fnALF a druhá metoda, označena jako Midway, zahajuje iteraci z malých počátečních hodnot, které jsou stále v rozsahu prostředí IEEE s dvojitou přesností. Problém podtečení/přetečení v metodě postupného poměru je řešen pomocí metody založené na logaritmu a aritmetiky rozšířeného rozsahu. Obě metody ověřujeme pomocí numerických testů a porovnáváme jejich výsledky s metodou X-čísla z hlediska přesnosti, stability a rychlosti. Výsledky ukazují, že relativní přesnost navrhovaných metod je lepší než 10-9 pro maximální stupeň 100000 ve srovnání s výsledky odvozenými vysoce přesným softwarem Wolfram's Mathematica. Průměrné časy CPU potřebné pro vyhodnocení fnALF v různých zeměpisných šířkách ukazují, že dvě navrhované metody jsou rychlejší asi o 10-30 % a 20-90 % s ohledem na metodu X-čísla pro maximální stupeň v rozsahu 50-65000. We improve the precision and computation speed of the fully-normalized associated Legendre functions (fnALFs) for ultra-high degrees and orders of spherical harmonic transforms. We take advantage of their numerical behaviour of and propose two new methods for solving an underflow/overflow problem in their calculation. We specifically discuss the application of the two methods in the fixed-order increasing-degree recursion computation technique. The first method uses successive ratios of fnALFs and the second method, called the Midway method, starts iteration from tiny initial values, which are still in the range of the IEEE double-precision environment, rather than from sectorial fnALFs. The underflow/overflow problem in the successive ratio method is handled by using a logarithm-based method and the extended range arithmetic. We validate both methods using numerical tests and compare their results with the X-number method in terms of precision, stability, and speed. The results show that the relative precision of the proposed methods is better than 10-9 for the maximum degree of 100000, compared to results derived by the high precision Wolfram’s Mathematica software. Average CPU times required for evaluation of fnALFs over different latitudes demonstrate that the two proposed methods are faster by about 10-30% and 20-90% with respect to the X-number method for the maximum degree in the range of 50-65000.

Background Colorectal cancers are the fourth most diagnosed cancer and the second leading cancer in number of deaths. Many clinical variables, pathological features, and genomic signatures are associated with patient risk, but reliable patient stratification in the clinic remains a challenging task. Here we assess how image, clinical, and genomic features can be combined to predict risk. Methods We developed and evaluated integrative deep learning models combining formalin-fixed, paraffin-embedded (FFPE) whole slide images (WSIs), clinical variables, and mutation signatures to stratify colon adenocarcinoma (COAD) patients based on their risk of mortality. Our models were trained using a dataset of 108 patients from The Cancer Genome Atlas (TCGA), and were externally validated on newly generated dataset from Wayne State University (WSU) of 123 COAD patients and rectal adenocarcinoma (READ) patients in TCGA (N=52). Findings We first observe that deep learning models trained on FFPE WSIs of TCGA-COAD separate high-risk (OS5years, N=25) patients (AUC=0.81±0.08, 5year survival p Interpretation The improved stratification of colorectal cancer patients from our computational methods can be beneficial for treatment plans and enrollment of patients in clinical trials. &nbsp

Background Colorectal cancers are the fourth most diagnosed cancer and the second leading cancer in number of deaths. Many clinical variables, pathological features, and genomic signatures are associated with patient risk, but reliable patient stratification in the clinic remains a challenging task. Here we assess how image, clinical, and genomic features can be combined to predict risk. Methods We developed and evaluated integrative deep learning models combining formalin-fixed, paraffin-embedded (FFPE) whole slide images (WSIs), clinical variables, and mutation signatures to stratify colon adenocarcinoma (COAD) patients based on their risk of mortality. Our models were trained using a dataset of 108 patients from The Cancer Genome Atlas (TCGA), and were externally validated on newly generated dataset from Wayne State University (WSU) of 123 COAD patients and rectal adenocarcinoma (READ) patients in TCGA (N=52). Findings We first observe that deep learning models trained on FFPE WSIs of TCGA-COAD separate high-risk (OS5years, N=25) patients (AUC=0.81±0.08, 5year survival p Interpretation The improved stratification of colorectal cancer patients from our computational methods can be beneficial for treatment plans and enrollment of patients in clinical trials. &nbsp

Nickel-based hydrogen evolution reaction (HER) electrodes have been widely used in alkaline and anion exchange membrane water electrolysis. Therefore, understanding the activity dependence on the KOH concentration (pH) of alkaline electrolytes is essential for designing durable and active HER catalysts. In this work, the HER activity and kinetics of polycrystalline and nanostructured nickel-based catalysts are evaluated in various pH and KOH concentrations. The results for nanostructured NiMo catalyst indicate that both electrochemical active surface area and reaction order have a promoting region under various pH’s and KOH concentrations (0.01–1.0 M, pH 12–14) accompanied by better HER activity (a lower overpotential for achieving − 10 mA cm−2) and Tafel slope decreases from around 180 mV dec−1 to 60 mV dec−1 in the same pH and KOH concentration range. The change in the Tafel slope indicates that the HER rate-determining step for HER at NiMo/C changes with pH and KOH concentration. The polycrystalline Ni displays different behaviours where a promoting (0.01–0.10 M, pH 12–13), stabilizing (0.1–1.0 M, pH 13–14), and an inhibiting region (2 M, pH > 14) are present. However, Tafel slopes of around 120 mV/dec are obtained for polycrystalline Ni at all KOH concentrations. The HER characteristics are inhibited at 2.0 M KOH for both catalysts due to slower OH* transport kinetics. The results confirmed the importance of tuning catalyst-pH/KOH concentration for better HER activity and kinetics. Graphical abstract

Minority populations in the United States face a disproportionate burden of illness from COVID-19 infection and have lower vaccination rates compared with other groups. This study estimated the equity implications of increased COVID-19 vaccination in the United States, with a focus on the number of cases, hospitalizations, and deaths avoided.This was an observational real-world modeling study.Data from the Centers for Disease Control and Prevention (CDC) were used to identify the remaining unvaccinated US population by county, age, and race as of October 22, 2021. The number of COVID-19 cases, hospitalizations, and deaths avoided were calculated based on case incidence and death data from the CDC, along with data on race- and age-specific hospitalization multipliers, under a scenario in which half of the remaining unvaccinated population per county, race, and age group obtained a full vaccine regimen.Vaccinating half of the remaining unvaccinated population in each age and race subgroup within counties would result in an estimated 22.09 million COVID-19 cases avoided, 1.38 million hospitalizations avoided, and 150,000 deaths avoided over 12 months. Some minority groups, particularly Black and Hispanic/Latino populations, were projected to experience substantial benefits from increased vaccination rates as they face both lower vaccination rates and worse outcomes if infected with COVID-19.Increasing COVID-19 vaccination in the United States not only benefits the population as a whole but also serves as a potentially useful lever to reduce the disproportionate burden of COVID-19 illness among minority populations.

Automation reliance and functionality are ever increasing, especially in supervisory control environments like unmanned aerial vehicle (UAV) missions. Of particular relevance is understanding how automation transparency, i.e., explaining the capabilities and limitations of automation to the human in real-time, can improve human-automation performance across automated systems that vary in reliability. Two hundred seventy one Naval Aviation trainees completed a simulated multi-UAV supervisory control mission for 42 minutes with three automated systems that varied in reliability. Participants were never explicitly told the reliability varied, but halfway through the mission, they were alerted that the least reliable system may falter. Results indicated human-automation performance improved after the alert for this specific system, but not as a whole, as one system’s human-automation performance deteriorated. This work suggests uncertainty communication should not only include the specific, real-time capabilities of the automation, but also communicate unintentional consequences it may have on the whole environment.

In the study, based on the non-linear calculation methods used to determine the seismic performance of structures in TBSC 2018, the stress-strain, moment-curvature, displacement capacity, plastic rotation limits, and deformation-based damage limit values of the reinforced concrete circular cross-section columns were calculated and compared according to different design parameters. The studied effects of the design parameters on the non-linear relation of reinforced concrete columns were also evaluated in terms of strength, curvature, and displacement ductility of the sections. All design parameters affecting the non-linear behavior and deformation limits of the reinforced concrete circular cross-section columns were taken into account. Deformation demands for reinforced concrete structural members are essential for detecting element damage. Based on TBSC (2018), non-linear relationships of reinforced concrete columns were obtained in order to calculate plastic hinge properties and deformation limits. For the Limited Damage, Controlled Damage, and Collapse Prevention performance levels defined for the structural elements in TBSC 2018, plastic rotation and deformation limit values were obtained according to the characteristic values calculated from the non-linear analyzes of reinforced concrete circular columns. For column models, damage limits and damage zones calculated based on TBSC 2018 were shown on the visually obtained moment-curvature relationships. Depending on the upper deformation limit values derived, cross-sectional deformation damage levels were determined and evaluated using the moment-curvature relationships. The variation of the non-linear behavior of column models by design parameters and deformation-based damage limits were examined both analytically and visually. The deformation limits remain in a safer direction as a result of increasing longitudinal and spiral reinforcement ratios for the reinforced concrete circular columns.

Movie S1 is showing the fabricating 3D printing ulvan biopolymer through additive manufacturing process.

Movie S2 shows the fabricating ulvan biofiber through wet-spinning process.

PurposeThe COVID PROFILE cohort is a longitudinal clinical study based in Victoria Australia, which was established to understand immunity to SARS-CoV-2 in alow transmission population settingand to identify immunological markers of long-term immunity and immune-dysregulation after both infection and vaccination. Additionally, this cohort was established as a biobank resource for researchers to address other health-related immunological questions.ParticipantsWe enrolled 178 adult community members, including household contacts, who had either recovered from a SARS-CoV-2 infection or were SARS-CoV-2 naïve. Only participants ≥18 years of age and, in the case of female participants, non-pregnant women at the time of enrollment were included in the study. Detailed COVID-19 clinical data, vaccination status, medical history and demographics was collected.Findings to dateAt enrollment, we found that 87.8% of COVID-19 recovered individuals were seropositive with detectable levels of anti-SARS-CoV-2 IgG antibodies. Seronegative COVID-19 recovered individuals included asymptomatic individuals or participants that were enrolled more than 12 months after their COVID-19 diagnosis. Except for one individual who was seropositive at baseline despite a previous SARS-CoV-2 PCR negative diagnosis, all household contacts and other community members enrolled as SARS-CoV-2 PCR negative, were seronegative for all SARS-CoV-2-specific antibodies tested. The infection rate (re-infection or new infection) during 24 months of the study was 42.7%, as determined by either rapid antigen tests, PCRs or serology screens. Of the SARS-CoV-2 recovered participants, 32.6% reported ongoing symptoms at enrollment of which 47% had already experienced ongoing symptoms for more than 12 weeks.Future PlansCOVID PROFILE will be used to comprehensively understand temporal immunity to SARS-CoV-2 and COVID-19 vaccines and to understand the impact of host immunological composition on such immunity and symptom severity. Additionally, studies focusing on understanding immunity following breakthrough infections and immunological risk factors that contribute towards development of long COVID are planned.Limitations/Strengths of the studyExtensive clinical information is available and longitudinal samples (blood, saliva and oropharyngeal swabs) collected at regular intervals up to 2.5 years after initial enrolment.This low SARS-CoV-2 transmission population cohort, enables exploration of difference in both the acquisition and maintenance of naturally acquired and vaccine-induced immunity not confounded by prior, frequent and/or undetected exposures.Extensive biobank of numerous blood fractions and biospecimen enables further exploration of mucosal immunity, nasal microbiome and humoral and cellular immunity over time.The cohort may be limited in addressing research questions regarding outcomes and risk factors and their associations where low incidence is expected.

Background Over the past years, the applications of mesenchymal stem cells (MSCs) grow rapidly in medicine as a promising option for regenerative medicine. So, increasing demands for MSCs and their derivations as cell-based drugs in the market are anticipated. One of the major challenges in MSC therapy is possible alterations in the stemness potential of MSCs during in vitro culture and proliferation. Microvesicles (MVs) reflect the transcriptional status of cells of origin. This study aimed to investigate the impact of 2D culture on stemness characteristics of MSCs by focusing on transcriptome in shed MVs.Methods and Results MVs were isolated from rat bone marrow MSCs using ultracentrifugation. Transmission electron microscopy and dynamic light scattering were applied to characterizing MVs. Then, some markers related to stemness and differentiation were evaluated in shed MVs during 10-day culture. Meanwhile the cell proliferation and apoptosis were assessed in cultured MSCs. Based on our results, not only MSCs-derived MVs preserved somewhat their stemness contents but also MSCs maintained proliferative during 10-day 2D culture.Conclusion Taken together, 2D culture had no significant effect on the biological state of MSCs which strengthened their applications in cell therapies. Further studies are needed to identify the protein component of MVs to give some benefits for biomimetic approaches.

Background. Breast cancer is still considered as one of the most important diseases, the most common cancer, and the second cause of death among women. It is necessary to evaluate the factors responsible for breast cancer (e.g., marital stress) since majority of the breast cancer cases in Iran are active young women hoping to live a normal social and sexual life, and because breast emptying has destructive effects on self-image and marital satisfaction. Therefore, this study aimed to determine the relationship between satisfaction and marital stress in mastectomy surgery. Methods. In this cross-sectional study, 120 married women with breast cancer were selected using available methods. The data were collected using a questionnaire with three parts including demographic questions, Enrich marital satisfaction, and Stockholm marital stress. Parametric tests and analysis of variance were used to analyze the data. Results. There was no significant relationship between marital satisfaction/marital stress and type of mastectomy surgery (P>0.01). Also, there was no significant relationship between marital satisfaction/marital stress and demographic variables (P>0.01). Conclusion. It was concluded that the marital satisfaction and marital stress had no significant relationship with the type of breast surgery. Practical Implications. Type of breast surgery had no effect on marital stress and satisfaction.

The cover image is based on the Case Report Dorsal intradural spinal arteriovenous fi stula associated with giant intradural spinal aneurysm, a case report by Ehsan Mohammad Hosseini et al., https://doi.org/10.1002/ccr3.7202 [Image: see text]

Göçme öncesi sismik performans seviyesinde, kesmeye maruz betonarme kolonların yatay yük ve eksenel yük taşıma kapasitelerindeki azalmayı ve bu davranışların tüm yapıya etkilerini modellemeye ve tahmin etmeye ihtiyaç vardır. Kesme dayanımı ile deformasyon kapasite davranışlarının incelenmesi için farklı beton basınç dayanımı, eksenel yük seviyesi ve spiral donatı oranlarında betonarme dairesel kolon modelleri tasarlanmıştır. Tasarlanan betonarme kolonların kesme davranışı ile deformasyon kapasiteleri, ASCE/SEI 41 (2017) ve araştırmacılar tarafından önerilen modellere göre araştırılmıştır. Betonarme kolonların moment-eğrilik ilişkilerinden elde edilen karakteristik değerlere göre elastik, plastik ve toplam yer değiştirme değerleri hesaplanarak yer değiştirme süneklik ilişkileri incelenmiştir. Betonarme kolonlar için analizlerden elde edilen kesme dayanımlarının eksenel yük seviyesi, beton basınç dayanımı, spiral donatı oranı ve yer değiştirme süneklik değerlerinden etkilendiği görülmektedir., At the pre-collapse seismic performance level, there is a need to model and estimate the decrease in the lateral load and axial load carrying capacities of the shear-sensitive reinforced concrete columns the effects of such behavior on the entire structure. In order to investigate the shear strength and deformation capacity behaviors, reinforced concrete circular column models with different concrete compressive strength, axial load level and spiral reinforcement ratios were designed. The shear behavior and deformation capacity of the designed reinforced concrete columns were investigated according to the models proposed by ASCE/SEI 41 (2017) and the researchers. According to the characteristic values obtained from moment-curvature relations of reinforced concrete columns, elastic, plastic and total displacement values were calculated and the displacement ductility relations were examined. It is seen that the shear strength obtained from the analysis for reinforced concrete columns is affected by the axial load level, concrete compressive strength, spiral reinforcement ratio and displacement ductility values.

Blood sugar (BS) has been proposed as a prognostic factor for COVID-19. In this historical cohort study we evaluated the association between admission time BS and COVID-19 outcome.First, hospitalized COVID-19 patients were divided into three groups; Non-diabetic patients with BS 140 mg/dl (N = 394), non-diabetic patients with BS ≥ 140 mg/dl (N = 113) and diabetic patients (N = 315). Mortality, ICU admission, and length of hospital stay were compared between groups and odds ratio was adjusted using logistic regression.After adjustment with pre-existing conditions and drugs, it was shown that non-diabetic patients with BS ≥ 140 mg/dl are at increased risk of mortality (aOR 1.89 (0.99-3.57)) and ICU admission (aOR 2.62 (1.49-4.59)) even more than diabetic patients (aOR 1.72 (1.07-2.78) for mortality and aOR 2.28 (1.47-3.54) for ICU admission.Admission time hyperglycemia predicts worse outcome of COVID-19 and BS ≥ 140 mg/dl is associated with a markedly increase in ICU admission and mortality.

PurposePresent research aims to study the determinants of big data analytics (BDA) adoption intention and outsourcing in the context of small and medium-sized enterprises (SMEs).Design/methodology/approachThe partial least squares approach was employed to analyse data collected from 187 SMEs.FindingsThe findings indicate that relative advantage, competitive pressure and environmental uncertainty significantly influence SMEs' BDA adoption intention. Top management support moderates the association between the regulatory environment and BDA adoption intention. Furthermore, organisational readiness moderates negatively the association between BDA adoption intention and propensity to outsource BDA.Practical implicationsThe findings benefit SMEs' managers/owners in making well-informed decisions in the BDA adoption process.Originality/valueThe majority of the previous research on BDA adoption intention is limited to large corporations. To address the gap on determinant factors of BDA adoption intention among SMEs, the drivers of BDA adoption intention and propensity to outsource were investigated using the technology-organisation-environment model.