Mixed Block Research Articles

Tuning polymer micelle size and dynamics with solvophobic block structure

Hypothesis: Micelles formed by copolymers with mixed solvophobic blocks have attracted much attention lately. It is expected that changing the mixed blocks sequence can be used as a tool to influence the micellization behavior in a way that is not equivalent to simply varying the incompatibility parameter for pure diblock-copolymers.Simulations: By using coarse-grained simulations, the micellization behavior of copolymers with twelve types of solvophobic blocks, which differed in the fraction f as well as the sequence of solvophilic units in the solvophobic blocks, was studied. To enable quantitative comparison of systems with different f, an “effective” incompatibility parameter was introduced.Findings: The micelles size distributions and dynamics were found to be significantly dependent on both f and the fine details of the sequence. When the solvophobic block sequences were obtained statistically using a model of copolymerization, a strong influence of the reactivity ratios on the resulting micelles was found. Even a moderate tendency to form gradient-like sequences resulted in a noticeable increase in the micelles size. The dynamic properties of the micelles were studied by investigating the rate at which the chains escape from them. The addition of soluble units into the solvophobic block was shown to dramatically decrease the tendency to form kinetically frozen states; gradient-like sequences demonstrated more sluggish dynamics. The physical reasons for the observed peculiarities are discussed in detail.

Co-salient object detection with iterative purification and predictive optimization

BackgroundCo-salient object detection (Co-SOD) aims to identify and segment commonly salient objects in a set of related images. However, most current Co-SOD methods encounter issues with the inclusion of irrelevant information in the co-representation. These issues hamper their ability to locate co-salient objects and significantly restrict the accuracy of detection. MethodsTo address this issue, this study introduces a novel Co-SOD method with iterative purification and predictive optimization (IPPO) comprising a common salient purification module (CSPM), predictive optimizing module (POM), and diminishing mixed enhancement block (DMEB). ResultsThese components are designed to explore noise-free joint representations, assist the model in enhancing the quality of the final prediction results, and significantly improve the performance of the Co-SOD algorithm. Furthermore, through a comprehensive evaluation of IPPO and state-of-the-art algorithms focusing on the roles of CSPM, POM, and DMEB, our experiments confirmed that these components are pivotal in enhancing the performance of the model, substantiating the significant advancements of our method over existing benchmarks. Experiments on several challenging benchmark co-saliency datasets demonstrate that the proposed IPPO achieves state-of-the-art performance.

Optical coherence tomography-guided versus angiography-guided percutaneous coronary intervention for patients with complex lesions (OCCUPI): an investigator-initiated, multicentre, randomised, open-label, superiority trial in South Korea

Despite the detailed imaging information provided by optical coherence tomography (OCT) during percutaneous coronary intervention (PCI), clinical benefits of this imaging technique in this setting remain uncertain. The aim of the OCCUPI trial was to compare the clinical benefits of OCT-guided versus angiography-guided PCI for complex lesions, assessed as the rate of major adverse cardiac events at 1 year. This investigator-initiated, multicentre, randomised, open-label, superiority trial conducted at 20 hospitals in South Korea enrolled patients aged 19-85 years for whom PCI with drug-eluting stents was clinically indicated. After diagnostic angiography, clinical and angiographic findings were assessed to identify patients who met the criterion of having one or more complex lesions. Patients were randomly assigned 1:1 to receive PCI with OCT guidance (OCT-guidance group) or angiography guidance without OCT (angiography-guidance group). Web-response permuted-block randomisation (mixed blocks of four or six) was used at each participating site to allocate patients. The allocation sequence was computer-generated by an external programmer who was not involved in the rest of the trial. Outcome assessors were masked to group assignment. Patients, follow-up health-care providers, and data analysers were not masked. PCI was done according to conventional standard methods with everolimus-eluting stents. The primary endpoint was major adverse cardiac events (a composite of cardiac death, myocardial infarction, stent thrombosis, or ischaemia-driven target-vessel revascularisation), 1 year after PCI. The primary analysis was done in the intention-to-treat population. The margin used to establish superiority was 1·0 as a hazard ratio. This trial is registered with ClinicalTrials.gov (NCT03625908) and is completed. Between Jan 9, 2019, and Sept 22, 2022, 1604 patients requiring PCI with drug-eluting stents for complex lesions were randomly assigned to receive either OCT-guided PCI (n=803) or angiography-guided PCI (n=801). 1290 (80%) of 1604 patients were male and 314 (20%) were female. The median age of patients at randomisation was 64 years (IQR 57-70). 1588 (99%) patients completed 1-year follow-up. The primary endpoint occurred in 37 (5%) of 803 patients in the OCT-guided PCI group and 59 (7%) of 801 patients in the angiography-guided PCI group (absolute difference -2·8% [95% CI -5·1 to -0·4]; hazard ratio 0·62 [95% CI 0·41 to 0·93]; p=0·023). Rates of stroke, bleeding events, and contrast-induced nephropathy were not significantly different across the two groups. Among patients who required drug-eluting stent implantation for complex lesions, OCT guidance resulted in a lower incidence of major adverse cardiac events at 1 year compared with angiography guidance. These findings indicate the existence of a therapeutic benefit of OCT as an intravascular imaging technique for PCI guidance in patients with complex coronary lesions. Abbott Vascular and Cardiovascular Research Center. For the Korean translation of the abstract see Supplementary Materials section.

BiSTNet: Semantic Image Prior Guided Bidirectional Temporal Feature Fusion for Deep Exemplar-Based Video Colorization.

How to effectively explore the colors of exemplars and propagate them to colorize each frame is vital for exemplar-based video colorization. In this article, we present a BiSTNet to explore colors of exemplars and utilize them to help video colorization by a bidirectional temporal feature fusion with the guidance of semantic image prior. We first establish the semantic correspondence between each frame and the exemplars in deep feature space to explore color information from exemplars. Then, we develop a simple yet effective bidirectional temporal feature fusion module to propagate the colors of exemplars into each frame and avoid inaccurate alignment. We note that there usually exist color-bleeding artifacts around the boundaries of important objects in videos. To overcome this problem, we develop a mixed expert block to extract semantic information for modeling the object boundaries of frames so that the semantic image prior can better guide the colorization process. In addition, we develop a multi-scale refinement block to progressively colorize frames in a coarse-to-fine manner. Extensive experimental results demonstrate that the proposed BiSTNet performs favorably against state-of-the-art methods on the benchmark datasets and real-world scenes. Moreover, the BiSTNet obtains one champion in NTIRE 2023 video colorization challenge (Kang et al. 2023).

Fine-Grained Few-Shot Image Classification Based on Feature Dual Reconstruction

Fine-grained few-shot image classification is a popular research area in deep learning. The main goal is to identify subcategories within a broader category using a limited number of samples. The challenge stems from the high intra-class variability and low inter-class variability of fine-grained images, which often hamper classification performance. To overcome this, we propose a fine-grained few-shot image classification algorithm based on bidirectional feature reconstruction. This algorithm introduces a Mixed Residual Attention Block (MRA Block), combining channel attention and window-based self-attention to capture local details in images. Additionally, the Dual Reconstruction Feature Fusion (DRFF) module is designed to enhance the model’s adaptability to both inter-class and intra-class variations by integrating features of different scales across layers. Cosine similarity networks are employed for similarity measurement, enabling precise predictions. The experiments demonstrate that the proposed method achieves classification accuracies of 96.99%, 98.53%, and 89.78% on the CUB-200-2011, Stanford Cars, and Stanford Dogs datasets, respectively, confirming the method’s efficacy in fine-grained classification tasks.

Speed and Accuracy Training Affects Young Children’s Cognitive Control

ABSTRACT Young children tend to rely on reactive cognitive control (e.g. strongly slow down after an error), even when task accuracy would benefit from proactive cognitive control (taking a slower task approach up front). We investigated if giving young primary school children opportunities to repeatedly experience tasks where success rates depend on balancing speed and accuracy by using proactive and reactive cognitive control promotes their selective use of proactive cognitive control strategies. Participants were children from the German-speaking part of Switzerland (N = 105; mean age 7.5 yrs). They were allocated to a “training with feedback,” “training without feedback,” or control condition. They completed a pre- and posttest (Hearts and Flower task), separated by six computerized training tasks over three weeks. We analyzed time-by-condition effects on reaction time, rate-correct, and post-error slowing. In line with our hypotheses, both training groups outperformed the control group on reaction time and rate-correct in the incongruent block. Contrary to expectation, feedback did not enhance the intervention effect and the training group without feedback additionally outperformed control participants on rate-correct in the mixed block and improved their post-error slowing. Thus, our short intervention triggered accelerated development of proactive control in a cognitive conflict task requiring accuracy-speed trade-offs. This shows that during the developmental period in which children are assumed ready for developing proactive cognitive control strategies, repeated experiences over a short time-period can lead to acute improvements. More research is needed to check for long-term benefits and generalizability beyond our sample and the tasks employed.

Semantic processing in older adults is associated with distributed neural activation which varies by association and abstractness of words.

The extent to which the neural systems underlying semantic processes degrade with advanced age remains unresolved, which motivated the current study of neural activation on functional magnetic resonance imaging (fMRI) during semantic judgments of associated vs. unassociated, semantic vs. rhyme, and abstract vs. rhyme word pairs. Thirty-eight older adults, 55-85years of age, performed semantic association decision tasks in a mixed event-related block fMRI paradigm involving binary judgments as to whether word pairs were related (i.e., semantically associated). As hypothesized, significantly greater activation was evident during processing of associated (vs. unassociated) word pairs in cortical areas implicated in semantic processing, including the angular gyrus, temporal cortex, and inferior frontal cortex. Cortical areas showed greater activation to unassociated (vs. associated) word pairs, primarily within a large occipital cluster. Greater activation was evident in cortical areas when response to semantic vs. phonemic word pairs. Contrasting activation during abstract vs. concrete semantic processing revealed areas of co-activation to both semantic classes, and areas that had greater response to either abstract or concrete word pairs. Neural activation across conditions did not vary as a function of greater age, indicating only minimal age-associated perturbation in neural activation during semantic processing. Therefore, the response of the semantic hubs, semantic control, and secondary association areas appear to be largely preserved with advanced age among older adults exhibiting successful cognitive aging. These findings may provide a useful clinical contrast if compared to activation among adults experiencing cognitive decline due Alzheimer's, frontal-temporal dementia, and other neurodegenerative diseases.

An Automobile's Tail Lights: Sacrificing Safety for Playful Design?

The counterintuitive "Union Jack"-inspired turn signals on versions of BMW's Mini vehicles was investigated to reveal potential impacts on human performance. When some Mini drivers indicate a change in direction, they do so with an oppositely oriented arrow. This conflict, between the task-irrelevant spatial shape and task-relevant location of the signal, mimics a "converse" spatial-Stroop effect that, in combination with the ubiquitous use of arrows on road signs, may be confusing. Participants (n = 30) responded-via right and left keypresses-to the directions of road signs and turn signals in both pure and mixed blocks. Reaction times and accuracies were recorded to determine performance in each condition (compatible, neutral, incompatible). Performance suffered when the location and direction of the stimuli did not correspond. When responding to turn signals the cost to performance was especially salient in mixed blocks. Thus, when driving on roads where the meanings of arrows on road signs is important, turn signals pointing in a direction opposite from the directional intention indicated by the signals' location are likely to be confusing. The design of some Mini's "Union Jack" style taillights opposes well-established principles of cognitive functioning, caused confusion in our laboratory study and therefore may be a safety hazard-a possibility that ought to be explored in more realistic (e.g., driving simulator) situations. BMW designers should consider universally adopting the neutral, "horizontal line," illumination style that is currently available in the aftermarket.

Students’ Evaluations of Multilingual Educational Slides and Their Visual Attention Distribution on Slides with Different Layouts

Following efforts to promote internationalization at academic institutions, the use of multiple languages on educational slides (e.g., PowerPoint) has gradually increased. Multilingualism in learning has its advantages, but having multiple languages on educational slides can lead to crowding and cognitive overload. To investigate how students perceive multilingual slides, evaluations were gathered from Japanese (N = 20) and Indonesian students (N = 20) during an eye-tracking experiment in which their visual attention distribution on the slides was assessed. The slides contained text in three languages (English, Japanese, and Bahasa Indonesia) and were varied according to their layout. One group watched slides with text separated in blocks, with one text block for each language, while the other group watched slides consisting of a single, mixed block with each sentence describing the same information in a different language. The students’ evaluations showed that slides with a mixed layout were judged as more crowded and required more processing effort than slides with a separated-block layout. Furthermore, while the students dwelled their gaze significantly longer on text in their native language (either Bahasa Indonesia or Japanese) on separated-block slides, for slides with a mixed layout, the gaze patterns did not significantly differ between languages. The results of a comprehension quiz taken after the slide presentation, however, showed that students performed better after having watched the slides with the mixed layout. Thus, although judged as more crowded and requiring a wider attention distribution, slides with a mixed layout may be preferable in multilingual education.

Effect of Integrated Yoga as an add-on therapy in adults with clinical depression - A randomized controlled trial.

Depression is a leading cause of disability and the conventional management has several limitations. Recent studies demonstrated the benefits of yoga in psychological disorders. To evaluate the efficacy of the Integrated Yoga Module (IYM) to standard care with added yogic education on lifestyle modification (YELM) in patients with clinical depression. A PROBE trial was conducted at a single tertiary care hospital in India. Adults aged 18 to 64 with clinical depression were randomized to either an IYM or an active control group using a computer-generated mixed block randomization sequence. Both groups received YELM in addition to standard care and the intervention group practiced IYM, for 8 weeks. The primary outcome was the reduction in depression symptoms assessed using the Beck Depression Inventory (BDI-II), and secondary outcomes involved self-compassion, brief resilience, positive and negative experiences, and quality of life, evaluated at 8 weeks. The mean ± SD age of participants was 32.2 ± 10.0 and 54.3% were females. The IYM group showed statistically significant improvements in BDI-II scores β = -6.7 (95% CI [-10.8, -2.5]; p = .001), resilience β = 0.4 (95% CI [0.02, 0.80]; p = .037), physical health domain of WHOQOL - BREF β = 10.1 (95% CI [0.7, 19.5]; p = .035) and negative emotions (SPANE-N) β = 2.8 (95% CI [0.1, 5.4]; p = .037). However, no significant differences were found in SCS-SF β = -0.3 (95% CI [-0.7, 0.0]; p = .053). IYM as an adjunct is superior to conventional medical management in reducing symptoms and improving positive psychological resources in clinical depression.

Response-Category Conflict and Control Mode Determine Memory Performance for Distractors in a Flanker Paradigm.

Cognitive conflicts can lead to better memory for task-relevant information. However, little is known about memory performance for task-irrelevant information. The present study investigated memory performance of task-irrelevant distractors using a Flanker paradigm. In two experiments (N = 699), participants first completed a study phase with 56 flanker trials. The stimuli consisted of trial-unique pictures. A congruent trial consisted of a target flanked by two identical pictures from the same category (e.g., all mammals). An incongruent trial consisted of a target and flankers from different stimulus categories (e.g., a mammal flanked by two identical birds), which results in a response-category conflict. To explore the impact of different control modes, congruent and incongruent trials were presented in pure blocks (allowing a proactive control mode) or in mixed blocks (requiring a reactive control mode). Afterwards, recognition memory was tested in a surprise memory test. In general, the results showed better memory for congruent than incongruent flankers in pure blocks. In contrast in mixed blocks, the results showed better memory for incongruent than for congruent flankers. Thus, memory performance for distractors varies systematically with response-category conflict and control mode.

Optimising physiotherapy for people with lateral elbow tendinopathy – Results of a mixed-methods pilot and feasibility randomised controlled trial (OPTimisE)

BackgroundThe OPTimisE intervention was developed to address uncertainty regarding the most effective physiotherapy treatment strategy for people with Lateral Elbow Tendinopathy (LET). ObjectivesTo assess the feasibility of conducting a fully-powered randomised controlled trial (RCT) evaluating whether the OPTimisE intervention is superior to usual physiotherapy treatment for adults with LET. DesignA mixed-methods multi-centred, parallel pilot and feasibility RCT, conducted in three outpatient physiotherapy departments in the UK. MethodPatients were independently randomised 1:1 in mixed blocks, stratified by site, to the OPTimisE intervention or usual care. Outcomes were assessed using pre-defined feasibility progression criteria. Results50 patients were randomised (22 Female, 28 Male), mean age 48 years (range 27–75). Consent rate was 71% (50/70), fidelity to intervention 89% (16/18), attendance rate in the OPTimisE group 82% (55/67) vs 85% (56/66) in usual care, outcome measure completion 81% (39/48) at six-month follow-up. There were no related adverse events. Patients and physiotherapists reported that the OPTimisE intervention was acceptable but suggested improvements to the trial design. 49 patients were recruited from physiotherapy referrals vs one from primary care records. Outcome measure return rates were higher when completed online (74%) compared to postal questionnaire (50%). Exploratory analysis showed improvements in both groups over time. ConclusionsIt is methodologically feasible to conduct a fully powered RCT comparing the clinical and cost-effectiveness of the OPTimisE intervention versus usual physiotherapy treatment. Considering the similar improvements observed in both groups, careful consideration is needed regarding the priority research question to be addressed in future research.

MD-UNet: a medical image segmentation network based on mixed depthwise convolution.

In the process of cancer diagnosis and treatment, accurate extraction of the lesion area helps the doctor to judge the condition. Currently, medical image segmentation algorithms based on UNet have been verified to be able to play an important role in clinical diagnosis. However, these methods still have the following drawbacks in extracting the region of interest (ROI): (1) ignoring the intra-class variability of medical images. (2) Failure to obtain effective feature redundancy. To address these problems, a U-shaped medical image segmentation network based on a Mixed depthwise convolution residual module (MDRM), called MD-UNet, is proposed in this paper. In MD-UNet, the MDRM built with a Mixed depthwise convolution attention block (MDAB) captures both local and global dependencies in the image to mitigate the effects of intra-class differences. MDAB captures valid redundant features and further captures global features of the input data. At the same time, the lightweight MDAB senses changes in the receptive field and generates multiple feature mappings. Compared with UNeXt on the ISIC2018 dataset, the MD-UNet segmentation accuracy Dice and IoU are improved by 1.33% and 1.91%, respectively. The code is available at https://github.com/Cloud-Liu/MD-UNet .

Mixed‐Phase Niobium Oxide as a Durable and Ultra‐Fast Charging Anode for High‐Power Lithium‐Ion Batteries

AbstractThe development of low‐cost, high‐power lithium‐ion batteries requires durable anode materials that can store and release lithium quickly. Here a mixed phase of H‐Nb2O5 and M‐Nb2O5 (denoted as d‐H,M‐Nb2O5) that demonstrates excellent performance as an anode material for lithium storage is reported. Experimental and computational analyses reveal several salient features of d‐H,M‐Nb2O5. First, the edge‐sharing arrangement between the mixed niobium oxygen polyhedral block structures helps alleviate volume expansion during cycling, thereby enhancing stability and reversibility. Second, the mixed‐phase structure facilitates a continuous pathway for lithium ion adsorption These characteristics allow for sequential transport of lithium ions, enabling fast charging. As a result, the d‐H,M‐Nb2O5 electrode material exhibits a high capacity of 142 mAh g−1 at an ultra‐fast charging rate of 100 C, while maintaining 85% of its initial capacity after 5000 cycles. Moreover, its practical feasibility is established by demonstrating full‐cell performance at a 5 C discharge/charge rate (13 mA cm−2), maintaining 79% of its capacity over 1000 cycles.

Frequency-guidance Collaborative Triple-branch Network for single image dehazing

Image dehazing is a crucial pre-processing step in many high-level vision applications, e.g., crowd surveillance, automatic driving, and remote sensing. Recently, learning-based methods have achieved promising performance by designing various convolutional neural networks (CNNs). However, most existing CNNs are based on a single feature branch and cannot fully utilize the low-frequency and high-frequency features of haze, which inevitably affects the quality of the restored image. To this end, we develop an effective Frequency-guidance Collaborative Triple-branch Network (FCT-Net) for image dehazing. It casts dehazing as a dual-frequency component restoration task and deals with pertinent features based on a triple-branch-like architecture. Specifically, our FCT-Net can be decomposed into four components: low-frequency branch (LFB), high-frequency branch (HFB), progressive fusion branch (PFB), and image reconstruction tail (IRT). The LFB aims to mine more contextual information with dual-path feature modulation block (DFMB), while the HFB aims to recover the missing structural detail via mixed attention residual block (MARB). PFB is a fusion branch built between LFB and HFB, where different feature streams (low- and high-frequency information) can be integrated together through continuous selective progressive fusion (SPF) modules. Finally, our IRT exploits all these derived features to generate the clear haze-free image. Furthermore, we utilize a multi-strategy loss to optimize our FCT-Net from the perspectives of pixel domain and feature domain, which can achieve better image recovery quality. Extensive experiments on different benchmark datasets show that our FCT-Net is able to get comparable results with other state-of-the-art methods.

Motor adaptation and immediate retention to overground gait-slip perturbation training in people with chronic stroke: an experimental trial with a comparison group.

Perturbation-based training has shown to be effective in reducing fall-risk in people with chronic stroke (PwCS). However, most evidence comes from treadmill-based stance studies, with a lack of research focusing on training overground perturbed walking and exploring the relative contributions of the paretic and non-paretic limbs. This study thus examined whether PwCS could acquire motor adaptation and demonstrate immediate retention of fall-resisting skills following bilateral overground gait-slip perturbation training. 65 PwCS were randomly assigned to either (i) a training group, that received blocks of eight non-paretic (NP-S1 to NP-S8) and paretic (P-S1 to P-S8) overground slips during walking followed by a mixed block (seven non-paretic and paretic slips each interspersed with unperturbed walking trials) (NP-S9/P-S9 to NP-S15/P-S15) or (ii) a control group, that received a single non-paretic and paretic slip in random order. The assessor and training personnel were not blinded. Immediate retention was tested for the training group after a 30-minute rest break. Primary outcomes included laboratory-induced slip outcomes (falls and balance loss) and center of mass (CoM) state stability. Secondary outcomes to understand kinematic contributors to stability included recovery strategies, limb kinematics, slipping kinematics, and recovery stride length. PwCS within the training group showed reduced falls (p < 0.01) and improved post-slip stability (p < 0.01) from the first trial to the last trial of both paretic and non-paretic slip blocks (S1 vs. S8). During the mixed block training, there was no further improvement in stability and slipping kinematics (S9 vs. S15) (p > 0.01). On comparing the first and last training trial (S1 vs. S15), post-slip stability improved on both non-paretic and paretic slips, however, pre-slip stability improved only on the non-paretic slip (p < 0.01). On the retention trials, the training group had fewer falls and greater post-slip stability than the control group on both non-paretic and paretic slips (p < 0.01). Post-slip stability on the paretic slip was lower than that on the non-paretic slip for both groups on retention trials (p < 0.01). PwCS can reduce laboratory-induced slip falls and backward balance loss outcomes by adapting their post-slip CoM state stability after bilateral overground gait-slip perturbation training. Such reactive adaptations were better acquired and retained post-training in PwCS especially on the non-paretic slips than paretic slips, suggesting a need for higher dosage for paretic slips. NCT03205527.

Single image deraining using scale constraint iterative update network

Rain streaks, which can be viewed as a type of noise, have the potential to destroy the structural integrity of objects within an image, leading to a dramatic degradation in the performance of advanced vision algorithms. Therefore, it is important to develop an effective deraining algorithm. There are three challenges in the current deraining task: First, it is difficult to separate rain streaks from the image background because of the complexity of rain types. Second, most of the existing methods use encoder–decoder-based structures, but the models are designed to be too bulky and inflexible to accommodate complex rain streaks. Third, many models perform the same operation for all rain types, which can reduce the generalizability of the model. To address these challenges, we propose a scale constraint iterative update network which divides the network structure into feature extraction block, multi-scale constraint block, and iterative update block. In the feature extraction block, the deep mixed attention is used to extract complex rain streak features, and the mixed convolution block is used to extract the background details. The multi-scale constraint block aggregates contextual features across different scales, while the Global GateUnit captures long-range dependencies. We followed a coarse-to-fine pipeline. In the iterative update block, the feature maps are updated based on features from different scales, gradually refining the image. The final optimized result is obtained by performing learnable up-sampling. During the whole iteration process, the parameters are shared to reduce the complexity of the model while maintaining the performance. Additionally, We also designed a dynamic inference mechanism, which dynamically selects the number of iterations for different types of rain streaks, effectively enhancing the generalization of the model. We conducted extensive experiments on synthetic and real-world rain datasets, as well as a raindrop dataset. The results of our experiments demonstrate that our method outperforms existing deraining methods in terms of effectiveness and generalization ability.

Flow cytometry analysis of PD1 expression on rat blood CD3&lt;sup&gt;+&lt;/sup&gt; lymphocytes stimulated by CD3 antibodies

The role of the PD-1/PD-L signaling pathway in the regulation of the immune response is currently the focus of research. Numerous studies have shown the key role of PD-1 molecules in the regulation of autoimmune, antitumor and antiviral reactions. The culture of rat and mice lymphocytes, as well as animal experimental models of immunopathologies are widely used in research. However, rat lymphocytes are almost not used to study the PD-1/PD-L pathway. There is no data on PD-1 expression or methods of its induction on rat lymphocytes. In human T-lymphocyte culture, PD-1 expression can be induced by NIB1412 anti-CD3 antibodies coated in the well of culture plates. In this study, we investigated the effect of G4.18 anti-CD3 antibody on PD-1 expression in peripheral blood lymphocyte of intact Wistar rats in vitro. According to some literature data, G4.18 anti-CD3 antibodies in immobilized form can activate isolated rat T cells, and according to others, inhibit allogeneic reactions in mixed lymphocyte culture and block cytotoxicity of cells obtained from rats with a developed graft rejection reaction. We found that incubation of rat blood lymphocytes with G4.18 anti-CD3 antibodies immobilized on plastic leads to a change in cell morphology and induction of PD-1 on CD3+ lymphocytes. After incubation with anti-CD3 antibodies, the proportion of PD-1+ lymphocytes among CD3+ lymphocytes was 12.056.04%, which is significantly higher than the proportion of such cells before incubation and during incubation in a cultural medium, which amounted to 2.602.62% and 4.595.81%, respectively. In the dot-plot graphs showing the distribution of cells according to the parameters of forward scatter and side scatter, PD-1+CD3+ lymphocytes induced by anti-CD3 antibodies are localized in the region of relatively lower forward scatter and greater side scatter. Perhaps these cells belong to apoptotic cells.

Power enhancement and phase transitions for global testing of the mixed membership stochastic block model

The mixed-membership stochastic block model (MMSBM) is a common model for social networks. Given an n-node symmetric network generated from a K-community MMSBM, we would like to test K=1 versus K>1. We first study the degree-based χ2 test and the orthodox Signed Quadrilateral (oSQ) test. These two statistics estimate an order-2 polynomial and an order-4 polynomial of a “signal” matrix, respectively. We derive the asymptotic null distribution and power for both tests. However, for each test, there exists a parameter regime where its power is unsatisfactory. It motivates us to propose a power enhancement (PE) test to combine the strengths of both tests. We show that the PE test has a tractable null distribution and improves the power of both tests. To assess the optimality of PE, we consider a randomized setting, where the n membership vectors are independently drawn from a distribution on the standard simplex. We show that the success of global testing is governed by a quantity βn(K,P,h), which depends on the community structure matrix P and the mean vector h of memberships. For each given (K,P,h), a test is called optimal if it distinguishes two hypotheses when βn(K,P,h)→∞. A test is called optimally adaptive if it is optimal for all (K,P,h). We show that the PE test is optimally adaptive, while many existing tests are only optimal for some particular (K,P,h), hence, not optimally adaptive.

Wind tunnel and CFD studies of wind loadings on topsides of offshore structures

This paper presents a comprehensive study of wind loads on various offshore platforms using both wind tunnel experiments and CFD at model scales. The platforms studied include an LNGC with simple topside geometry, a FPSO with complex porous blocks, and a JUP with mixed simple blocks and tall truss structures. The 3D-printing is used to fabricate experimental models to ensure consistency with CFD models. Sensitivity studies of mesh types, mesh independence, turbulence models, wind profiles and wind speed independence are conducted to achieve highly accurate and reliable simulation results. Comparisons between the CFD and experimental results of six loading components and surface pressure measurements at over 20 sensor locations for each platform show good agreement across various wind directions and geometries. The robustness of the experiments and CFD models can serve as a reference for future offshore wind loading studies. Detailed examinations of the wind fields surrounding the platforms and the effects of porosity levels on wind loading reveal unique internal flow structures that differentiate among the structures and provide explanations for variations in loading and discrepancies. These findings contribute to a better understanding of wind fields and loading on the superstructures of offshore platforms and can inform the design and operation of similar structures in the future.