A document by Sara Abou Al-Saud. Click on the document to view its contents.

Affordances, the opportunity for action offered by the environment to an agent, are vital for meaningful behavior and exist in every interaction with the environment. Regarding its temporal mechanism, some studies suggest that affordance perception is an automated process that is independent from the visual context and bodily interaction with the environment, while others argue that it is modulated by the visual and motor context in which affordances are perceived. We aims to resolve this debate by examining affordance automaticity from the perspective of sensorimotor time windows. We replicated a previous study on affordance perception in which participants actively moved through doors of different width in VR environments. To investigate the impact of different forms of bodily interactions with an environment, i.e., the movement context (physical vs. joystick movement), we used the identical virtual environment from Djebbara and colleagues (2019) but displayed it on a 2D screen with participants moving through different wide doors using the laptop keyboard. We compared components of the event-related potential (ERP) from the continuously recorded electroencephalogram (EEG) that were previously reported to be related to affordance perception of architectural transitions (passable and impassable doors). Comparing early sensory and later motor-related ERPs, our study replicated ERPs reflecting early affordance perception but found differences in later motor-related components. It indicates a shift from automated perception of affordances during early sensorimotor time windows to movement context dependence of affordance perception at later stages suggesting that affordance perception is a dynamic and flexible process that changes over sensorimotor stages.

65-year-old man was referred to the Oral Medicine Department by his General Dental Practitioner for investigation of a swelling in the anterior maxilla, which had been present for 6 weeks and associated with mobility in the upper central incisors

An easy-to-implement noise estimation method for tuning state estimators is proposed. It outperforms benchmark methods in terms of accuracy or computational cost both in theory and in a case study. We assume parametric uncertainty in the process model, which we transform into noise statistics using the generalized unscented transformation (GenUT). While most other methods estimate only the noise covariance, we also estimate the mean. Our tuning method is suitable for input-output models, demonstrated through a case study involving process simulators and industrial data. We present a theoretical analysis of our method, which is based on splitting one large GenUT to two smaller GenUTs. This results in two theorems: i) mean approximations for the two systems are equal and ii) covariance approximations are similar under certain mild conditions. These theorems confirm the validity of our method, and we discuss their potential to realize a numerically stable GenUT for high-dimensional systems.

The relationship between biodiversity and ecosystem function (BEF) captivates ecologists, but the factors responsible for the direction of this relationship remain unclear. While higher ecosystem functioning at higher biodiversity levels (‘positive BEF’) is not universal in nature, negative BEF relationships seem puzzlingly rare. Here, we develop a dynamical consumer-resource model inspired by microbial decomposer communities in pitcher plant leaves to investigate BEF. We manipulate microbial diversity via controlled colonization and measure their function as total ammonia production. We test how niche partitioning among bacteria and other ecological processes influence BEF in the leaves. We find that a negative BEF can emerge from reciprocal interspecific inhibition in ammonia production causing a negative complementarity effect, or from competitive hierarchies causing a negative selection effect. Absent these factors, a positive BEF was the typical outcome. Our findings provide a potential explanation for the rarity of negative BEF in empirical data.

In the Arctic tundra, recurrent periods of food scarcity force predators to rely on a wide variety of resources. In particular most predators use ungulate carcasses as an alternative food supply, especially in winters when live preys are scarce. As important and localized resource patches, carrion promotes co-occurrence of different individuals, and its use by predators is likely to be affected by interspecific competition. Here, we studied how interspecific competition and resource availability impact winter use of carrion by Arctic and red foxes in low Arctic Fennoscandia. We predicted that presence of red foxes limits Arctic foxes' use of carrion, and that the outcome of competition for carrion depends on the availability of alternative food resources, such as rodents. We monitored Arctic and red fox presence at experimentally supplied carrion using camera traps, between 2006 and 2021 in late winter. Using a multi-species dynamic occupancy model at a week-to-week scale, we evaluated use of carrion by foxes, while accounting for the presence of competitors, rodent availability and supplemental feeding provided to Arctic foxes. Competition primarily affected carrion use by increasing both species' probability to leave occupied carcasses to a similar extent, suggesting a symmetrical avoidance. Rodent abundance was associated with an increase in the probability of colonizing carrion for both species. For Arctic foxes, however, this increase was only observed in carcasses unoccupied by red foxes, showing greater avoidance when alternative preys are available. Contrary to expectations, we did not find strong signs of asymmetric competition for carrion in winter. Our results suggest that interactions for resources at a short time scale are not necessarily aligned with interactions at the scale of the population. In addition, we found that competition for carcasses depends on the availability of other resources, suggesting that interactions between predators depend on the ecological context.

Background and Purpose: The classical theory of receptor action has been used for decades as a powerful tool to estimate molecular determinants of ligand-induced receptor activation (i.e. affinity and efficacy) from experimentally observable biological responses. However, it is also a well-recognized fact that the receptor-binding and activation mechanisms, and the parameters thereof, described in the classical theory contradict with the modern view of receptor activation based on allosteric principles. Experimental Approach: We used mathematical analysis, along with some numerical simulations, to answer the key question as to what extent the classical theory is compatible -if at all- with the modern understanding of receptor activation. Key Results: Here, we showed conclusively that 1) receptor activation equations based on allosteric principles contain the logic of the classical theory in disguise, and therefore, 2) estimates of “intrinsic efficacy” () obtained by means of classical techniques (i.e. null methods or fitting the operational model to concentration-response data) are equivalent to the allosteric coupling factors that represent the molecular efficacy of ligands. Conclusion and Implications: Thus, we conclude that despite the right criticisms it has received so far, the classical theory may continue to be useful in estimating ligand efficacy from experimental data, if used properly. Here, we also provide rigorous criteria for the proper use of the theory. These findings not only have implications on ligand classification, but also resolve some long lasting discussions in the field of bias agonism in GPCR, which requires reasonable estimates of relative ligand efficacies at different signalling pathways.

Textures in Molybdenum-Rhenium alloys are inevitable during thermal fabrication. [110] and [100] are common orientations in Molybdenum-Rhenium alloys and effect mechanical responses. However, orientation dependence of mechanical responses in Molybdenum-Rhenium alloys is not quite clear yet. To clarity this problem, micro-pillar compression tests are conducted in grains with orientation [100] and [110] separately. Orientation-dependent compressive properties are found in Mo-14Re and Mo-42Re, but are not found in Mo and Mo-5Re, which may be attributed to activated muiti-slip planes as increased Re. Solid solution effect of Re not only rely on orientations, but also on Re content. Softening effect occurs in both [100] and [110] Mo-5Re. while, strong strengthening effect happens in [110] Mo-14Re and Mo-42Re. Our research clarifies that Mo-Re alloys with [110] orientation / texture could be preferred to obtain good strengthening effect.

Infective endocarditis caused by K. oxytoca: A Case Report

Background and Purpose: Abnormal activation of the NLRP3 inflammasome in macrophages is closely associated with Ulcerative colitis (UC), and targeting the NLRP3 inflammasome has been proposed as a potential therapeutic approach, but the underlying mechanism by which it regulates intestinal inflammation remains unclear. Anemoside B4 (AB4) has anti-inflammatory activity, but whether it alleviates UC by inhibiting the activation of NLRP3 inflammasome remains unclear. More importantly, the molecular targets of AB4 remain unknown. Experimental Approach: We explored the role of AB4 in the development of dextran sodium sulfate (DSS)-induced colitis in wild-type (WT) mice and its effect on NLRP3 inflammasome. We isolated intestinal macrophages and epithelial cells, and validated them in DSS-induced NLRP3-deficient (NLRP3-/-) mice. The target and molecular mechanism of AB4 were identified in LPS-induced macrophages in vitro and DSS-induced macrophage-specific CD1d depletion (CD1d-/-) mice in vivo. Key Results: This study showed that AB4 had a strong anti-inflammatory effect DSS-induced colitis in WT mice, whereas the protective effects were lost in NLRP3-/- mice. AB4 inhibited the activation of NLRP3 inflammasome in colonic macrophages without affecting intestinal epithelial cells. Mechanistically, AB4 might target CD1d thus reducing the AKT-STAT1-PRDX1-NF-κB signaling pathway, eventually inhibiting the activation of NLRP3 inflammasome. Macrophage-specific CD1d depletion had been shown to reverse the protective effect of AB4. Conclusions and Implications: Our data showed that AB4 attenuated DSS-induced colitis by inhibiting CD1d-dependent NLRP3 inflammasome activation in macrophages. Therefore, as a natural product with high safety index, AB4 might be considered a promising candidate drug for the treatment of colitis.

Urbanization reflects a major form of environmental change impacting wild birds globally. Whereas urban habitats may provide increased availability of water, some food items, and reduced predation levels compared to rural, they can also present novel stressors including increased light at night, ambient noise, and reduced nutrient availability. Urbanization can also alter levels of brood parasitism, with some host species experiencing elevated levels of brood parasitism in urban areas compared to rural areas. Though the demographic and behavioral consequences of urbanization and brood parasitism have received considerable attention, their consequences for cellular-level processes are less understood. Telomeres provide an opportunity to understand the cellular consequences of different environments as they are a well-established metric of biological state that can be associated with residual lifespan, disease risk, and behaviour, and are known to be sensitive to environmental conditions. Here we examine the relationships between urbanization, brood parasitism, and blood telomere lengths in adult and nestling song sparrows (Melospiza melodia). Song sparrows are a North American songbird found in both urban and rural habitats that experience high rates of brood parasitism by brown-headed cowbirds (Molothrus ater) in the urban, but not the rural, sites in our study system. Among adults and nestlings from non-parasitized nests, we found no differences in relative telomere lengths between urban and rural habitats. However, among urban nestlings, the presence of a brood parasite in the nest was associated with significantly shorter relative telomere lengths compared to when a brood parasite was absent. Our results suggest a novel, indirect, impact of urbanization on nestling songbirds through the physiological impacts of brood parasitism.

RATIONALE: Helium (He) is used in cutting-edge research in industry and science as a carrier and/or ionization gas. The global He shortages have dramatically increased its prices and reduced its availability, to what comes together the current energy crisis. A strategy is proposed to save He and energy in elemental analysis/isotope ratio mass spectrometry (EA/IRMS). METHODS: A method for analysis of carbon and nitrogen isotope composition (δ13C and δ15N values) is proposed using two or three sequential combustion reactions in a single EA/IRMS acquisition. The methods (hereafter called 2×EA/IRMS and 3×EA/IRMS) use the time needed for the peak center and reference gas (CO2 or N2) pulses to measure δ13C or δ15N in two or three capsules with samples or standards. The combustion cycles can be replicate analyses of the same or different material. RESULTS: The methods were validated with replicate analysis of C and N in RMs and laboratory standards of a broad range of biological and geological matrices, δ13C and δ15N values, and C/N molar ratios. The accuracy and precision of the 2×EA/IRMS and 3×EA/IRMS values were15 essentially the same, with good agreement between the mean ± 1 SD values from RMs and standard analyses and the recommended or accepted values and their uncertainties. CONCLUSIONS: The proposed methods save He, save energy, save reference gases (CO2, N2), and O2, while reducing the analysis and instrumental times by ca. 50 %.

INTRODUCTIONAbsent pulmonary valve syndrome (APVS) with an intact ventricular septum (IVS) or small ventricular septum is a rare type of APVS associated with high perinatal mortality in fetuses. Although APVS/IVS constitutes only 7.5% to 25% of the APVS cohort, most fetuses (80%) will not survive to birth without inotropic support or heart transplantation due to fetal heart failure, hydrops fetalis, extracardiac and chromosomal abnormities, and pregnancy termination[1-4]. A ductus arteriosus(DA) is usually present in APVS/IVS patients, and a large DA could result in bronchial compression leading to severe respiratory symptoms and signs of congestive heart failure early after birth[5]. With the improvement of postnatal care and intervention, the survival of subjects rises from 20% to 80%[2]. However, long-term surviving analysis remains unknown in patients with APVS/IVS.Symptoms varies according to individual in these patients. Here, we report a rare subtype of APVS/IVS patient with the combination of the absent pulmonary valve leaflets, intact ventricular septum and superior vena cava who develop a surprisingly long-term survival and underwent timely pulmonary valve implantation surgery.

For the automated analysis of I/V-characteristics of solar cells and modules, descriptive parameters are essential. In particular with the rise in machine-learning techniques and the related increase data volumes, there is a need for good, general purpose, descriptive parameters. The most commonly used descriptive parameters for I/V are the standard solar cells parameters, consisting of V oc , I sc , V mpp , and I mpp . Also other representations may be considered, such as one diode model parameters corresponding to a particular I/V. However, these representations are very coarse and cannot distinguish or represent many common (non-ideal) features of an I/V (e.g. an S-shape). In this work we propose an extended set of solar cell parameters, which are well defined, and easy to determine. We evaluate the effectiveness of the extended solar cell parameters by reconstructing the I/V from the extracted parameters. This allows one to “measure” information loss. We compare the accuracy of our parameters with other commonly used curve models for I/V, namely the one diode model, and the Karmalkar-Haneefa model. The models are applied to a large set of I/V (about 2.2 million curves), covering a wide range of technologies and conditions. We demonstrate our extended solar cell parameters consistently provide an accurate description of nearly all I/V in these datasets. Furthermore, we present our I/V analysis tool which we use to process these datasets. This tool is fast and capable of extracting the extended solar cell parameters, as well as parameters for the one diode model and the Karmalka-Haneefa model. Finally, we exemplary show how the extended solar cell parameters may be used to detect partial shading in outdoor data, by training a simple random-forest classifier based on extended solar cell parameters.

In recent decades, the demand for clean and renewable energy has grown increasingly urgent due to the irreversible alteration of the global climate. As a result, efficient organic solar cells (OSCs) have gradually gained attention as a study hotspot. To break up this dilemma, this paper reviews the molecular design strategies of benzodithiophen (BDT)-based polymer and small molecule donor materials since their birth, focusing on the development of main-chain engineering, side-chain engineering and other unique molecular design paths. Up to now, the state-of-the-art power conversion efficiency (PCE) of binary OSCs prepared by BDT-based donor materials has approached 20%. Our work detailly discusses the potential relationship between the molecular changes of donor materials and photoelectric performance in corresponding OSC devices, thereby presenting a rational molecular design guidance for stable and efficient donor materials in future.

Objectives：We aimed to investigated whether artificial light at night (ALN) are associated with Nasopharyngeal carcinoma (NPC) risk in Fujian province of China. Design：We use spatial epidemiology to understand the spatiotemporal distribution characteristics of nasopharyngeal carcinoma hospitalization rates, and use least squares and geographic detection models to understand the impact of nighttime light intensity on nasopharyngeal carcinoma hospitalization rates. Participants：Inpatients with NPC in 2019 were determined according to ICD-10 code and the hospitalization records of Fujian province were obtained from basic medical insurance for urban and rural residents in Fujian Province, which was provided by Fujian Medical Security Center. Variables: The main variable calculated in this study is the crude hospitalization rate Results：The NPC hospitalization rate are spatially positively correlated . The results of Ordinary Least Square (OLS) model analysis showed that ALN was positively correlated with the hospitalization rate of NPC. The R2 in the geographic weighted regression model（GWR）is greater than the OLS model, which indicates that the explanation degree of the GWR model variables on the hospitalization rate of NPC is significantly better than OLS model. Conclusions：ALN level was positively correlated with the hospitalization rate of nasopharyngeal carcinoma, which provide valuable information for the prevention and treatment strategy of NPC in Fujian province.

IntroductionMitochondrial disease (MD) is a group of disorders caused by dysfunctional mitochondria, the organelles which play an important role in the production of ATP and exist in every human cell inthe body, except for the red blood cells (1 ). Mitochondrial DNA (mtDNA) is inherited maternally and affects organs dependent on high aerobic metabolism, such as the eye, inner ear, central nervous system, skeletal and cardiac muscle. Mitochondrial diabetes mellitus (MDM), also known internationally as maternally inherited diabetes and deafness (MIDD) syndrome, is a mtDNA mutation disease, with a progressive islet β cell secretory dysfunction (2, 3 ). MIDD is associated with early onset diabetes and sensorineural deafness, but there are various other systemic features, including cardiomyopathy, renal problems, and neuropsychiatric symptoms. It was first reported by J.A. Massen et al. in 1992, who found a large pedigree with mt.3243A>G mutation, suffering from diabetes with the presence of maternal transmission, in conjunction with bilateral hearing loss in most of the carriers (4 ). From then on, there has been growing scientific evidence that a range of other point mutations in mtDNA could contribute to the pathogenesis of MIDD, such as mt-tRNA encoding genes, including MT-TI, MT-TS1, and MT-TK, and mt-proteins encoding genes, incuding MT-ND1, MT-ND4, MT-COX2, and MT-COX3. In addition, deletion and depletion of nucleotides have also been described in patients with MIDD (5 ). These novel mutations, however, are extremely rare compared to the proportion of mt.3243A>G, where there is an A to G substitution at position 3243. MIDD is currently found to be the most common type of monogenic diabetes mellitus, accounting for about 1% of all diabetes mellitus, and the incidence in China is approximately 0.6% (6 ). Because of its low incidence and irrespective of its complex clinical phenotype, MIDD is often misdiagnosed as type 1 or type 2 diabetes. Nonetheless, its treatment is different from the common types of diabetes, and incorrect diagnosis and treatment will accelerate the disease process and the occurrence of complications. Therefore, correct genetic diagnosis and treatment are crucial for patients with MIDD. This study discusses the clinical manifestations and treatment process of a typical patient with MIDD, and summarizes its clinical characteristics through a comprehensive review of the literature, with the scope of improving clinicians’ cognition of the disease and reducing misdiagnosis rate.

The expansion of machine learning applications across dif- ferent domains has given rise to a growing interest in tap- ping into the vast reserves of data that are being generated by edge devices. To preserve data privacy, federated learn- ing was developed as a collaboratively decentralized privacy- preserving technology to overcome the challenges of data silos and data sensibility. This technology faces certain lim- itations due to the limited network connectivity of mobile devices and malicious attackers. In addition, data samples across all devices are typically not independent and iden- tically distributed (non-IID), which presents additional chal- lenges to achieving convergence in fewer communication rounds. In this paper, we have simulated attacks, namely Byzantine, label flipping, and noisy data attacks, besides non-IID data. We proposed Robust federated learning against poisoning attacks (RFCaps) to increase safety and accelerate conver- gence. RFCaps incorporates a prediction-based clustering and a gradient quality evaluation method to prevent attack- ers from the aggregation phase by applying multiple filters and also accelerate convergence by using the highest quality gradients. In comparison to MKRUM, COMED, TMean, and FedAvg algorithms, RFCap has high robustness in the pres- ence of attackers and has achieved a higher accuracy of up to 80% on both MNIST and Fashion-MNIST datasets.