Symmetric Stationary Boundary Layer

Considering the boundary layer problem in the case of two-dimensional flow past a wedge with the wedge angle $\varphi=\pi\frac{2m}{m+1}$, Oleinik and Samokhin obtained the local well-posedness results for $m \geq 1$. In this paper, we establish the existence and uniqueness of classical solutions to the Prandtl systems for arbitrary $m>0$, which solves the steady case in Open problem 6 proposed by Oleinik and Samokhin. Our proof is based on the maximum principle technique at the Crocco coordinates and the most important observation that when the fluid approaches a sharp point, it seems the self-similar solutions. Then we obtain the existence and uniqueness of the solution with the help of the self-similar solutions by the Line Method. Furthermore, we similarly establish the well-posedness results of three-dimensional flow past a cone.Comment: 34 pages, 2 figure

Getting the Most from Eye-Tracking: User-Interaction Based Reading Region Estimation Dataset and Models

A single digital newsletter usually contains many messages (regions). Users' reading time spent on, and read level (skip/skim/read-in-detail) of each message is important for platforms to understand their users' interests, personalize their contents, and make recommendations. Based on accurate but expensive-to-collect eyetracker-recorded data, we built models that predict per-region reading time based on easy-to-collect Javascript browser tracking data. With eye-tracking, we collected 200k ground-truth datapoints on participants reading news on browsers. Then we trained machine learning and deep learning models to predict message-level reading time based on user interactions like mouse position, scrolling, and clicking. We reached 27\% percentage error in reading time estimation with a two-tower neural network based on user interactions only, against the eye-tracking ground truth data, while the heuristic baselines have around 46\% percentage error. We also discovered the benefits of replacing per-session models with per-timestamp models, and adding user pattern features. We concluded with suggestions on developing message-level reading estimation techniques based on available data.Comment: Ruoyan Kong, Ruixuan Sun, Charles Chuankai Zhang, Chen Chen, Sneha Patri, Gayathri Gajjela, and Joseph A. Konstan. Getting the most from eyetracking: User-interaction based reading region estimation dataset and models. In Proceedings of the 2023 Symposium on Eye Tracking Research and Applications, ETRA 23, New York, NY, USA, 2023. Association for Computing Machiner

Study on evaporation drainage of deep coal seam gas wells

Targeting the problem of a small amount of fluid accumulation in deep coal seam gas (CSG) wells during flowing production stage, the evaporation drainage method is proposed to discharge the liquid accumulation. Based on the Dalton evaporation model and wind speed function, a calculation model of evaporation drainage was established for deep CSG wells, which was verified by laboratory experiments. Taking a CSG well in the western Ordos Basin as an example to analyze the evaporation drainage capacity, the influence of temperature, daily gas production, bottomhole flowing pressure (BHFP), formation gas water saturation on the evaporation drainage capacity was investigated. The results show that the maximum evaporation water production is 2,533.8 kg/d at a bottomhole temperature of 80°C and a gas production rate of 30 × 103 m3/d. It is found that the temperature and pressure have a marked influence on the evaporation drainage. By improving the gas production and bottomhole temperature, and reducing the BHFP can effectively promote the evaporation drainage capacity. The initial moisture content of CSG in the reservoir are inversely proportional to the evaporation drainage capacity. By adjusting the BHFP and daily gas production, the evaporation drainage capacity can match the liquid production rate of the formation. Evaporation drainage can effectively extend the flowing production time of deep CSG wells and reduce the costs of production

ApoE attenuates unresolvable inflammation by complex formation with activated C1q

Apolipoprotein-E (ApoE) has been implicated in Alzheimer's disease, atherosclerosis, and other unresolvable inflammatory conditions but a common mechanism of action remains elusive. We found in ApoE-deficient mice that oxidized lipids activated the classical complement cascade (CCC), resulting in leukocyte infiltration of the choroid plexus (ChP). All human ApoE iso-forms attenuated CCC activity via high-affinity binding to the activated CCC-initiating C1q protein (K-D similar to 140-580 pM) in vitro, and C1q-ApoE complexes emerged as markers for ongoing complement activity of diseased ChPs, A beta plaques, and atherosclerosis in vivo. C1q-ApoE complexes in human ChPs, A beta plaques, and arteries correlated with cognitive decline and atherosclerosis, respectively. Treatment with small interfering RNA (siRNA) against C5, which is formed by all complement pathways, attenuated murine ChP inflammation, A beta-associated microglia accumulation, and atherosclerosis. Thus, ApoE is a direct checkpoint inhibitor of unresolvable inflammation, and reducing C5 attenuates disease burden

Searching for autoimmune B cells in atherosclerosis

Atherosclerosis is a chronic inflammatory disorder of arteries and the leading cause of mortality worldwide. Innate and adaptive immune responses are involved in all disease stages. It has been suggested that adaptive autoimmunity may play critical roles in the initiation and progression of atherosclerosis. However, this fundamental question remains unresolved. Indeed, whether human atherosclerosis is solely an auto-inflammatory disease, whether it is a bona fide B2-driven autoimmune disease or both is still unclear. A comprehensive answer to this question would provide unprecedented opportunities to develop next-generation therapeutic strategies to treat the root causes of atherosclerosis. Tertiary lymphoid organs (TLOs) emerge in tissues in response to non-resolving inflammation, including transplant rejection, most types of cancer, autoimmune diseases, and chronic infectious diseases. Artery TLOs (ATLOs) have also been identified in the aorta adventitia of aged apolipoprotein E-deficient (ApoE-/-) mice and in human atherosclerotic tissues: ATLOs are organized into T cell areas and B cell follicles containing follicular dendritic cells (FDCs) in activated germinal centers (GCs). These data support the notion that atherosclerosis-specific B cell responses may be organized in ATLOs, which was the key question addressed in this thesis. The method of nested polymerase chain reaction (PCR) was used to clone paired heavy and light chains of B cell receptors (BCRs) in isolated B2 cells from germinal centers (GCs) of ATLOs and secondary lymphatic organs to express them in vitro. Using immunofluorescence (IF) staining, the reactivity of the recombinant antibodies in multiple murine tissues was confirmed. Co-immunoprecipitation and mass spectrometry (coIP-MS), Western blot, enzyme-linked immunosorbent assays (ELISA), and surface plasmon resonance analyses were used to determine antibody-cognate autoantigen binding characteristics. In translational studies, human atherosclerotic plaques were examined to test whether the potential autoantibodies reacted with their cognate antigen in the arterial wall. Histone H2b was thereby identified as the first common murine and human autoantigen. Importantly, H2b triggered autoimmunity responses in vivo, which was associated with disease severity of both murine atherosclerosis and human patients with cardiovascular diseases (CVDs). Immunization against the H2b autoantigen promoted atherosclerosis in ApoE-/- mice, which demonstrated the pro-atherogenic role of H2b autoimmunity in vivo. In conclusion, these data lead us to propose that atherosclerosis is a disease that is associated with multiple autoreactive BCRs and that murine atherosclerosis and possibly human atherosclerosis may be a bona fide autoimmune disease.Atherosklerose ist eine chronisch-entzündliche Erkrankung der Arterienwand und die Haupttodesursache weltweit. Angeborene und adaptive Immunreaktionen sind an der Entwicklung der Atherosklerose während aller Stadien beteiligt. Eine fundamentale ungeklärte Frage hinsichtlich der Pathogenese der Erkrankung ist, ob die klinisch relevanten Spätstadien der Atherosklerose ausschließlich durch Zellen der angeborenen Immunantwort wie Makrophagen gekennzeichnet sind oder ob autoreaktive B2 Immunzellen gegen Autoantigene der Arterienwand gebildet werden. Eine Antwort auf diese Frage ist dringlich, um zukünftige Therapiestrategien der bisher nicht kausal therapierbaren Erkrankung zu entwickeln. Tertiäre Lymphorgane (TLOs) entwickeln sich bei zahllosen autoreaktiven und autoinflammatorischen Erkrankungen wie Krebs, Autoimmunerkrankungen und chronisch entzündlichen Darmerkrankungen. Mitglieder unserer Arbeitsgruppe charakterisierten Atherosklerose-assoziierte TLOs (ATLOs) in Apolipoprotein E-defizienten (ApoE-/-) Mäusen und in erkrankten humanen Arterien. Fortgeschrittene Stadien dieser ATLOs sind durch separate T Zellregionen und aktivierte B Zellfollikel, die follikuläre dendritische Zellen (FDCs) enthalten, gekennzeichnet. Diese Daten deuteten an, dass autoreaktive B2 Zellimmunreaktionen in ATLOs stattfinden könnten. Die Methode der Nested Polymerase Chain Reaction wurde benutzt, um die schweren und leichten Ketten der B Zell Rezeptoren (membrangebundene Immunglobuline) in isolierten B2 Zellen aus den Keimzentren von ATLOs und von sekundären Lymphorganen zu klonieren und in vitro zu exprimieren. Die resultierenden rekombinanten monoklonalen Antikörper wurden in immunhistologischen Analysen verschiedener Organe eingesetzt, um in ApoE-/- Mäusen und erkrankten humanen Geweben deren Reaktivität zu untersuchen. Koimmunpräzipitation erkrankter muriner Arterien unter Benutzung der putativen Autoantikörper wurde benutzt, um potentielle Autoantigene erkrankter Arterien zu präzipitieren, die anschließend in massenspektrometrischen Analysen zur Identifikation der Autoantigene eingesetzt wurden. Western Blots und Enzyme Linked Immunosorbent Assays (ELISAs) wurden etabliert, um die Serumkonzentration der klonierten Antikörper zu bestimmen. Die sogenannte Surface Plasmon Resonance Methode wurde eingesetzt, um die Affinität der klonierten Antikörper mit Autoantigenen direkt zu bestimmen. Acht Autoantikörper wurden aus 64 Kandidaten kloniert und in vitro exprimiert. Humane Gewebe wurden benutzt, um die Kreuzreaktivität dieser Antikörper gegen humane Antigene zu bestimmen. Diese Untersuchungen führten zur Identifikation des Histonproteins H2B als ein bona fide Autoantigen der murinen und humanen Atherosklerose (der Antikörper wurde als A6 Antikörper annotiert). Andere Antikörper reagierten gegen unterschiedliche Zellen der Arterienwand einschließlich gegen glatte Muskelzellen der Lamina Media. Weitere experimentelle und klinische Untersuchungen zeigten, dass der A6 Antikörper in atherosklerotischen Mäusen und im Serum erkrankter Patienten signifikant anstiegen. Schließlich wurde eine Impfstrategie mit H2B Autoantigen in Mäusen durchgeführt: ApoE-/- Mäuse entwickelten nach zwei Injektionen eine erhöhte Plaquebelastung ihrer Arterien. Diese Daten zeigen erstmals, dass die Atherosklerose eine Erkrankung ist, die mit einer polyklonalen B2 Autoimmunantwort assoziiert ist. Damit wurde der erste und entscheidende Schritt hinsichtlich der Charakterisierung der Atherosklerose als Autoimmunerkankung gemacht

Real-Time Detection of Drones Using Channel and Layer Pruning, Based on the YOLOv3-SPP3 Deep Learning Algorithm

Achieving a real-time and accurate detection of drones in natural environments is essential for the interception of drones intruding into high-security areas. However, a rapid and accurate detection of drones is difficult because of their small size and fast speed. In this paper a drone detection method as proposed by pruning the convolutional channel and residual structures of YOLOv3-SPP3. First, the k-means algorithm was used to cluster label the boxes. Second, the channel and shortcut layer pruning algorithm was used to prune the model. Third, the model was fine tuned to achieve a real-time detection of drones. The experimental results obtained by using the Ubuntu server under the Python 3.6 environment show that the YOLOv3-SPP3 algorithm is better than YOLOV3, Tiny-YOLOv3, CenterNet, SSD300, and faster R-CNN. There is significant compression in the size, the maximum compression factor is 20.1 times, the maximum detection speed is increased by 10.2 times, the maximum map value is increased by 15.2%, and the maximum precision is increased by 16.54%. The proposed algorithm achieves the mAP score of 95.15% and the detection speed of 112 f/s, which can meet the requirements of the real-time detection of UAVs

The Research of Complex Product Design Process Model under the Concept of Self-Recovery

The working environment of contemporary mechanical products is becoming more complex, and the working conditions are becoming more extreme. This has led to a significant increase in the frequency of problems in mechanical products. In order to reduce the frequency of human repair after problems, the application of the self-recovery concept has become a hot research topic in the area of smart design. However, the current application of the self-recovery concept is mostly limited to the structural and parametric levels, with less research at the functional level, which may lead to a waste of resources within products. To solve this problem, this research combines the functional-level product research method with the self-recovery concept and establishes a design process model of complex products under functional self-recovery. This model extends the application scope of the self-recovery concept and improves the efficiency of resource utilization in the product. The design process model has six steps. First, according to the user requirements and the existing product, the initial function solving is carried out, and the initial function model of the product is established. Next, the main functions of the product are determined based on the initial function model of the product. Then, according to the determined main functions of the product, combined with the parameters marked in the function structure, the self-diagnosis function is designed. After that, the LT matrix and effect library are used to design the self-regulation function corresponding to the main functions, and the parameters are used to screen the self-regulation function design scheme. Finally, according to the design scheme of the self-diagnosis function and self-regulation function, the functional period oriented to self-recovery is constructed to ensure the realization of the main functions of the product. The effectiveness of the design process model is proved through the design process of an intelligent photovoltaic power generation system at the end of the paper

The Research of Complex Product Design Process Model under the Concept of Self-Recovery

The working environment of contemporary mechanical products is becoming more complex, and the working conditions are becoming more extreme. This has led to a significant increase in the frequency of problems in mechanical products. In order to reduce the frequency of human repair after problems, the application of the self-recovery concept has become a hot research topic in the area of smart design. However, the current application of the self-recovery concept is mostly limited to the structural and parametric levels, with less research at the functional level, which may lead to a waste of resources within products. To solve this problem, this research combines the functional-level product research method with the self-recovery concept and establishes a design process model of complex products under functional self-recovery. This model extends the application scope of the self-recovery concept and improves the efficiency of resource utilization in the product. The design process model has six steps. First, according to the user requirements and the existing product, the initial function solving is carried out, and the initial function model of the product is established. Next, the main functions of the product are determined based on the initial function model of the product. Then, according to the determined main functions of the product, combined with the parameters marked in the function structure, the self-diagnosis function is designed. After that, the LT matrix and effect library are used to design the self-regulation function corresponding to the main functions, and the parameters are used to screen the self-regulation function design scheme. Finally, according to the design scheme of the self-diagnosis function and self-regulation function, the functional period oriented to self-recovery is constructed to ensure the realization of the main functions of the product. The effectiveness of the design process model is proved through the design process of an intelligent photovoltaic power generation system at the end of the paper

Effects of Rosuvastatin and Atorvastatin on Renal Function

Background: Several clinical trials have reported inconsistent findings for the effects of rosuvastatin (RSV) and atorvastatin (AN) on renal function. The aim of this meta-analysis was to investigate the effects of these 2 statins on glomerular filtration rate (GFR) and proteinuria respectively, and determine which is better. Methods and Results: PubMed, CENTRAL, Web of Knowledge, and ClinicalTrials.gov website were searched for randomized controlled trials. Eligible studies reported GFR and/or proteinuria during treatment with RSV or ATV compared with control (placebo, no statins, or usual care), or RSV compared with AN head to head. Trials that enrolled dialysis participants and teenagers were excluded. Statistical heterogeneity was assessed using the 12 statistic, and pooled results using the random-effects model. The standardized mean differences (SMD) and ratio of means (ROM) were measured, respectively, to analyze GFR and proteinuria. Sixteen trials with a total number of 24,278 participants were identified. Compared with control, changes in the SMD of GFR were 0.04 (95% confidence interval [CI]: 0.01-0.07) and 0.59 (95%CI: 0.12-1.06) for RSV and ATV, respectively. The ROMs of proteinuria were 0.59 (95%CI: 0.46-0.74) for RSV vs. the control group, and 1.23 (95%CI: 1.05-1.43) in the head-to-head comparison. Conclusions: Both RSV and ATV improve GFR, and ATV seems to be more effective in reducing proteinuria. The validity and clinical significance require high-quality intensive studies with composite clinic endpoints of kidney and death. (Circ J 2012; 76: 1259-1266)http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000303369800032&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Cardiac & Cardiovascular SystemsSCI(E)21ARTICLE51259-12667

In Vitro Gene Expression Responses of Bovine Rumen Epithelial Cells to Different pH Stresses

Ruminal acidosis often occurs in production, which greatly affects animal health and production efficiency. Subacute rumen acidosis (SARA) occurs when rumen pH drops rapidly to 5.5–5.8, and acute rumen acidosis (ARA) occurs when rumen pH drops below 5.0, but the molecular regulation mechanism of the rumen epithelium after the rapid decrease in pH is still unclear. Bovine rumen epithelial cells (BRECs) were cultured at pH = 7.4 (control), 5.5 (SARA), and 4.5 (ARA). Transcriptome and metabolomic methods were used to obtain the molecular-based response of BRECs to different pH treatments; pH = 4.5 can significantly induce apoptosis of BRECs. The RNA-seq experiments revealed 1381 differently expressed genes (DEGs) in the control vs. SARA groups (p p p < 0.05) in control vs. SARA and 51 in control vs. ARA. Bioinformatics analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database revealed that drug metabolism-cytochrome P450 metabolic and alpha-linolenic acid metabolism changes occurred. These transcriptional and metabolic changes are related to the adaptation of BRECs to low-pH stresses. In conclusion, the combined data analyses presented a worthy strategy to characterize the cellular, transcriptomic, and metabonomic adaptation of BRECs to pH in vitro. We demonstrated transcriptional expression changes in BRECs under pH stress and activation of the molecular mechanisms controlling inflammation