Since August 2022 customers have to be asked if they are interested in sustainable investment when entering a pension contract. Hence, the provider has to be prepared to offer suitable investment opportunities. Further, the provider has to manage the new risks and chances of those assets in the whole portfolio. We therefore especially look at possible consequences for optimal portfolio decisions of a life insurer and suggest modeling approaches for the evolution of the demand and the sustainability ratings for sustainable assets. We will solve various portfolio problems under sustainability constraints explicitly and suggest further research topics. As a special feature for a life insurer, we particularly look at the role of the actuarial reserve fund and the annual declaration of its return.

We design and demonstrate a method for early detection of Denial-of-Service attacks. The proposed approach takes advantage of the OpenRAN framework to collect measurements from the air interface (for attack detection) and to dynamically control the operation of the Radio Access Network (RAN). For that purpose, we developed our near-Real Time (RT) RAN Intelligent Controller (RIC) interface. We apply and analyze a wide range of Machine Learning algorithms to data traffic analysis that satisfy the accuracy and latency requirements set by the near-RT RIC. Our results show that the proposed framework is able to correctly classify genuine vs. malicious traffic with high accuracy (i.e., 95%) in a realistic testbed environment, allowing us to detect attacks already at the Distributed Unit (DU), before malicious traffic even enters the Centralized Unit (CU).

This Letter reports the observation of single top quarks produced together with a photon, which directly probes the electroweak coupling of the top quark. The analysis uses 139  fb^{-1} of 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider. Requiring a photon with transverse momentum larger than 20 GeV and within the detector acceptance, the fiducial cross section is measured to be 688±23(stat) _{-71}^{+75}(syst)  fb, to be compared with the standard model prediction of 515_{-42}^{+36}  fb at next-to-leading order in QCD.

2D materials have attracted broad attention from researchers for their unique electronic properties, which may be been further enhanced by combining 2D layers into vertically stacked van der Waals heterostructures (vdWHs). Among the superlative properties of 2D systems, thermoelectric (TE) energy conversion promises to enable targeted energy conversion, localized thermal management, and thermal sensing. However, TE conversion efficiency remains limited by the inherent tradeoff between conductivity and thermopower. In this paper, we use first-principles calculation to study graphene-based vdWHs composed of graphene layers and hexagonal boron nitride (h-BN). We compute the electronic band structures of heterostructured systems using Quantum Espresso and their TE properties using BoltzTrap2. Our results have shown that stacking layers of these 2D materials opens a bandgap, increasing it with the number of h-BN interlayers, which significantly improves the power factor (PF). We predict a PF of ∼1.0 × 1011 W K−2 m s for the vdWHs, nearly double compared to 5 × 1010 W K−2 m s that we obtained for single-layer graphene. This study gives important information on the effect of stacking layers of 2D materials and points toward new avenues to optimize the TE properties of vdWHs.

Background: Outcomes after acute rheumatic fever (ARF) diagnosis are variable, ranging from recovery to development of severe rheumatic heart disease (RHD). There is no diagnostic test. Evaluation using the Australian clinical diagnostic criteria can result in a diagnosis of definite, probable or possible ARF. The possible category was introduced in 2013 in Australias Northern Territory (NT). Our aim was to compare longitudinal outcomes after a diagnosis of definite, probable or possible ARF. Methods: We extracted data from the NT RHD register for Indigenous Australians with an initial diagnosis of ARF during the 5.5-year study period (01/01/2013 - 30/06/2019). Descriptive statistics were used to describe the demographic and clinical characteristics at initial ARF diagnosis. Kaplan-Meier curves were used to assess the probability of survival free of disease progression and the cumulative incidence risk at each year since initial diagnosis was calculated. Cox proportional hazards regression was used to determine whether time to disease progression differed according to ARF diagnosis and whether progression was associated with specific predictors at diagnosis. A multinomial logistic regression model was performed to assess whether ARF diagnosis was associated with RHD outcome and to assess associations between ARF diagnosis and clinical manifestations. A generalised linear mixed model (GLMM) was developed to assess any differences in the long-term antibiotic adherence between ARF diagnosis categories and to examine longitudinal trends in adherence. Results: There were 913 initial ARF cases, 732 with normal baseline echocardiography. Of these, 92 (13%) experienced disease progression: definite ARF 61/348 (18%); probable ARF 20/181 (11%); possible ARF 11/203 (5%). The proportion of ARF diagnoses that were uncertain (i.e. possible or probable) increased over time, from 22/78 (28%) in 2013 to 98/193 (51%) in 2018. Cumulative incidence risk of any disease progression at 5.5 years was 33.6 (23.6-46.2) for definite ARF, 13.5 (8.8-20.6) for probable and 11.4% (95% CI 6.0-21.3) for possible ARF. The probability of disease-free survival was lowest for definite ARF and highest for possible ARF (p=0.004). Cox proportional hazards regression indicated that disease progression was 2.19 times more likely in those with definite ARF than those with possible ARF (p=0.026). Progression to RHD was reported in 37/348 (11%) definite ARF, 10/181 (6%) probable ARF, and 5/203 (2%) possible ARF. The multinomial logistic regression model demonstrated a significantly higher risk of progression from no RHD to RHD if the initial diagnosis was definite compared to possible ARF (p<0.001 for both mild and moderate-severe RHD outcomes). The GLMM estimated that patients with definite ARF had a significantly higher adherence to antibiotic prophylaxis compared with probable ARF (p=0.024). Conclusion: These data indicate that the ARF diagnostic categories are being applied appropriately, are capturing more uncertain cases over time, provide a useful way to stratify risk and guide prognosis, and can help inform practice. Possible ARF is not entirely benign; some cases progress to RHD.

Aim To identify clinical and laboratory parameters on admission and/or during a hospital stay that would predict prolonged hospital stay in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Methods A retrospective cross-sectional study was conducted at the Clinic for Pulmonary Diseases and Tuberculosis, Clinical Centre University of Sarajevo for the period 2019-2021 accounting patients admitted due to AECOPD. The need for hospitalization was evaluated according to the current GOLD criteria and certain clinical parameters. Spirometry testing and laboratory analysis were performed for all patients on the day of admission and on the 10th day of hospital stay. Linear regression was used to show the relationship between multiple independent predictor variables and LOS. Results A total of 50 patients were evaluated during their hospital stay due to AECOPD. Median of LOS was 22.02±1.06, with 90% hospital survival rate. Due to AECOPD the median of LOS in the intensive care unit (ICU) was 4±0.68 days with pH<7.35 in 34% of hospitalized patients. According to spirometry classification on the day of admission, 56% of patients were assigned to group 3 and 16% to group 4 with significant improvement identified on spirometry findings on discharge. Platelets on the day of admission were the only statistically significant positive predictors of the length of hospital stay. Conclusion Identifying chronic obstructive pulmonary disease patients at risk of frequent exacerbations and appropriate disease management could reduce the disease burden.

Highlights • T-cell receptor (TCR) interaction with major histocompatibility complex–antigen complexes leads to antitumour responses.• TCR sequencing analysis allows characterisation of T cells that recognise tumour neoantigens.• T-cell clonal revival and clonal replacement potentially underpin immunotherapy responses.

This research combines complex systems science, geographical information systems, and environmental noise modelling to analyse effects of future air mobility in urban settings and plan efficient routes for vehicles. The research used the environmental noise maps of an urban agglomeration produced under the Environmental Noise Directive (END) as input to inform the UAV operations. These maps reveal potential routes for the UAV operations where the noise impact of the vehicle can be embedded within a high background noise due to the existing sources modelled under the END. When an agent based model is superimposed on a real-world map simple strategies of the diverse agents in interaction with the environment reveal patterns, such as dominant paths, points of congestion, and suggest positioning of terrestrial infrastructure. We investigate how agents can overcome the conflicts and find trade-off solutions by interacting only with their immediate neighbours-therefore enabling autonomy, decentralization, and putting to use emergent self-organising behaviour. The potential impact of increased drone operations on urban and peri urban regions is significant. Route optimisation which does not consider the noise is likely to impact on quite areas within our residential spaces and should be considered as part of noise action planning.

OBJECTIVE Excessive crying in infancy has been associated with increased risk of later behavioral problems. To identify individuals at risk for behavioral problems and to understand the mechanisms underlying excessive crying and irritability in infancy, research into the neurobiology of excessive crying is needed. We examined if excessive crying and irritability in infancy are associated with behavioral problems and amygdala volume among children and adolescents. METHOD This study included 4,751 singleton children from the prospective population-based Generation R Study cohort, born in the Netherlands in 2002-2006. Excessive crying (>3h on at least 1 day/week) and irritability (Mother and Baby Scales questionnaire) were parent-rated at 3 months. Amygdala volume was measured at 10 years using magnetic resonance imaging, and internalizing and externalizing were parent-rated at 1.5, 3, 6, 10 and 14 years and self-rated at 14 years. Covariates included child age, sex, national origin, gestational age, and maternal age, psychopathology score, parity, education, relationship status and family income. RESULTS Children who cried excessively in infancy had higher parent-rated internalizing (effect estimate 0.20 SD-units, 95% confidence interval [CI] 0.14, 0.27) and externalizing (0.17 SD-units, 95% CI 0.10, 0.24) throughout childhood (linear mixed models), and smaller amygdala volume at 10 years (-0.19 SD-units, 95% CI -0.32, -0.06) (linear regression model). The pattern of associations for both behavioral problems and amygdala volume was similar for irritability. CONCLUSION Excessive crying and irritability in infancy may reflect an early vulnerability to behavioral problems and be linked with neurobiological differences in the development of the amygdala.

We aimed to investigate expression of the novel susceptibility genes for CAKUT, DLG1 and KIF12, proposed by a systematic in silico approach, in developing and postnatal healthy human kidneys to provide information about their spatiotemporal expression pattern. We analyzed expression of their protein products by immunohistochemistry and immunofluorescence and quantified relative mRNA levels by RT-qPCR. Statistically significant differences in expression patterns were observed between certain developmental stages. Strong expression of DLG1 was observed in the developing kidney, with a gradual decrease from the first phase of kidney development (Ph1) until the third phase (Ph3), when most nephrons are formed; at later stages, the highest expression was observed in the tubules. KIF12 was highly expressed in the developing structures, especially in Ph1, with a gradual decrease until the postnatal phase, which would indicate a significant role in nephrogenesis. Co-localization of DLG1 and KIF12 was pronounced in Ph1, especially on the apical side of the tubular epithelial cells. Thereafter, their expression gradually became weaker and was only visible as punctate staining in Ph4. The direct association of DLG1 with KIF12 as control genes of normal kidney development may reveal their new functional aspect in renal tubular epithelial cells.

Background: After successful reperfusion is achieved (extended Thrombolysis in Cerebral Infarction (eTICI) ≥2b50), decision on pursuing additional treatment strategies in order to achieve complete reperfusion (eTICI=2c/3), is multifactorial and depends on patient’s clinical and imaging characteristics. We have developed and validated a clinical decision tool to provide individualized predictions on achieving delayed reperfusion based on individual patient data. Methods: Single-center registry analysis for all consecutive patients admitted between 02/2015 - 12/2020. Primary variable of interest was perfusion imaging outcome in patients with incomplete reperfusion (eTICI 2a-2c), evaluated on the 24-hour follow-up imaging. This variable was dichotomized into delayed reperfusion, in case of non-observable perfusion deficit, and persistent perfusion deficit, in case of perfusion deficit captured on the final angiography imaging. Final model variable selection was performed via bootstrapped (n=200) stepwise backwards regression. Model was split into a training and testing set (80:20 ratio), with 10-fold cross validation resampling. Results: 372 patients (50.8% female, mean age 74) were included, with 228 (61.2%) of them having delayed reperfusion. Final model identified seven variables of importance including: age, sex, atrial fibrillation, Intervention-to-Follow-Up time, maneuver count, eTICI and collateral status. Model’s discriminative ability for predicting delayed reperfusion was adequate (AUC 0.83, 95% CI 0.74 -0.92), with an overall adjusted calibration (Brier score 0.17, 95% CI 0.15-0.18). Conclusions: Current model presents a tool that may aid clinical decision-making process in selection of patients for pursuing additional treatment strategies after incomplete reperfusion has been achieved. This is an important next step towards personalized treatment of stroke patients undergoing mechanical thrombectomy.

Background: One potential benefit of intravenous thrombolysis (IVT) before mechanical thrombectomy (MT) is pre-interventional reperfusion. Currently, there is a paucity of data regarding the occurrence of pre-interventional reperfusion in patients randomized to IVT or no-IVT before MT. Methods: SWIFT DIRECT was a randomized controlled trial including acute ischemic stroke IVT-eligible patients being directly admitted to a comprehensive stroke center, with allocation to either MT alone or IVT + MT. Primary endpoint of this analysis was the occurrence of pre-interventional reperfusion defined as pre-interventional expanded Thrombolysis in Cerebral Infarction score ≥2a. The effect of IVT and potential treatment effect heterogeneity were analyzed using logistic regression analyses. Results: Out of the 396 patients analyzed, pre-interventional reperfusion occurred in 20 (10.0%) of patients randomized to IVT+MT, and 7 (3.6%) of patients randomized to MT alone. Receiving IVT favored the occurrence of pre-interventional reperfusion (aOR 2.91 [95% CI 1.23 - 6.87]). There was no IVT treatment effect heterogeneity on the occurrence of pre-interventional reperfusion with different strata of Randomization-to-Groin-Puncture (p for interaction=0.33), although the effect tended to be stronger in patients with Randomization-to-Groin-Puncture >28 minutes (aOR 4.65 [95% CI 1.16 - 18.68]). There were no significant difference in rates of functional outcomes between patients with and without pre-interventional reperfusion. Conclusion: Even for patients with proximal large vessel occlusions and direct access to MT, IVT leads towards an absolute increase of 6.9% (95% CI 1.7-12.2%) in the rates of pre-interventional reperfusion. The effect of IVT tended to be more pronounced when Randomization-to-Groin-Puncture intervals were longer, but this heterogeneity did not reach statistical significance.

Production enterprises are enterprises that produce goods or services that aim to meet human needs such as machinery-equipment materials and labour. In order for a manufacturing enterprise to carry out its activities successfully, it must make the right choice when choosing its inputs. The correct execution of production activities and the selection of machinery, which requires high capital investments, also affect the efficiency of the enterprises, the correct use of materials and their costs. Therefore, it is an important decision for business managers to choose the right machine. At this stage, multi-criteria decision making (MCDM) methods are used for choosing the right machine. MCDM methods are methods used in the evaluation of alternatives using more than one criterion. In addition, the MCDM method is used in machine selection as well as in many areas. In this study, PSI, SV and MARCOS methods, which are among the MCDM methods, were used for peanut butter machine selection. First, the criteria and alternatives to be used for the peanut butter machine selection were determined by interviewing a peanut butter factory manager. In the study, while the criteria weights were determined, PSI and SV methods were used, while the machines were ranked with the MARCOS method. In addition, the MARCOS method was compared with other MCDM methods such as PIV, CODAS and WEDBA methods. After the rankings were found according to the methods, the relations between the rankings were examined using the Spearman Correlation method. The main purpose of the study is to determine the suitable butter machine for a peanut paste production factory. Contribution of this study to the literature PSI, SV and MARCOS methods were used together for the first time. In addition, no study has been found in the literature related to peanut butter machine. Therefore, this study is original and contributes to the literature.