Miracle-dz/UniFAR-FTUs huggingface dataset:
The kinesin light chain‐2, a target of mRNA stabilizing protein HuR, inhibits p53 protein phosphorylation to promote radioresistance in NSCLC

Radioresistance hinders radiotherapy for the treatment of lung cancer. Kinesin light chain‐2 (KLC2) has been found to be upregulated in lung cancer and also to be associated with poor prognosis. This study aimed to investigate the effect of KLC2 on radiosensitivity in lung cancer.
On determining characteristic length scales in pressure gradient turbulent boundary layers

In the present work we analyze three methods used to determine the edge of pressure gradient turbulent boundary layers: two based on composite profiles, the one by Chauhan et al. (Fluid Dyn. Res. 41:021401, 2009) and the one by Nickels (J. Fluid Mech. 521:217–239, 2004), and the other one based on the condition of vanishing mean velocity gradient. Additionally, a new method is introduced based on the diagnostic plot concept by Alfredsson et al. (Phys. Fluids 23:041702, 2011). The boundary layer developing over the suction side of a NACA4412 wing profile, extracted from a direct numerical simulation at Rec = 400,000, is used as the test case. We find that all the methods produce robust results with mild or moderate pressure gradients, but stronger pressure gradients (with β larger than around 7) lead to inconsistent results in all the techniques except the diagnostic plot. This method also has the advantage of providing an objective way of defining the point where the mean streamwise velocity is 99% of the edge velocity, and shows consistent results in a wide range of pressure gradient conditions, as well as flow histories. Therefore, the technique based on the diagnostic plot is a robust method to determine the boundary layer thickness (equivalent to δ99) and edge velocity in pressure gradient turbulent boundary layers.
Momentum absorption by vegetation

Measurements were made in a wind-tunnel of the drag on elements of a simply-structured artificial crop, and of the wind profiles above and within the crop. Analysis demonstrates (i)that the drag force on an element of such an array can be calculated from the profile of the turbulent shear flow within the array, using the known (and unmodified), wind-tunnel value of the drag coefficient of the individual element; (ii)that the zero-plane displacement (d) of an aerodynamically rough surface can be identified with the level of action of the drag on its elements; and (iii)that von Karman's constant = 0.41 ± 0.03. The relation z0 = 0.36 (h – d) is suggested for the roughness parameter of vegetation of height h. Calculated values of the drag force, f, on unit column of a real stand of beans in the field, using individual-element drag coefficients (Cd) and measured wind speeds, give f = 3.5 τ0 where τ0 is the downward momentum flux derived from the shape of the wind profile above. On the evidence of conclusion (i) and the dense and complex nature of the bean canopy, the factor 3.5 is attributed to mutual sheltering of neighbouring canopy elements rather than as evidence that the Cd – values are modified by turbulent shear flow. For the artificial crop, and for the real crop, recognition of the wind-speed dependence of the individual-element drag coefficients gives values of eddy viscosity, KM, almost constant in the height range h/3 < z ⩽ h and significantly larger than those found when constant drag coefficients are assumed. Constant KM within a crop canopy is consistent with the wind profile u(z)/u(h) = {1 + α(1 – z/h)}−2: an explicit expression is given for the parameter α.
A pilot evaluation of the role of a children’s wellbeing practitioner (CWP) in a child and adolescent mental health service (CAMHS)

Background In 2017, the Children and Young People’s Improving Access to Psychological Therapies (CYP-IAPT) project was extended to deliver low-intensity Cognitive Behavioural Therapy (CBT), delivered by Children’s Wellbeing Practitioners (CWPs), but to date evaluation is sparse. Aims To evaluate low-intensity interventions delivered by trainee CWPs for the treatment of anxiety and depression in a child and adolescent mental health service (CAMHS). Method The evaluation adopted a quantitative, within-subjects, cross-sectional design. The outcome measures of 98 service users aged 8–17 years were included in the evaluation. Service users were children and young people accessing CAMHS in the North East of England. Outcome measures included the Revised Children’s Anxiety and Depression Scale (RCADS-47) and Goal Based Outcomes (GBOs). Descriptive data relating to the types of interventions used and outcomes following CWP involvement were also explored. Results Analysis of pre and post intervention data highlighted significant reduction in symptomatology across all RCADS subscales and composite total scales, and significant goal progress as measures by GBO’s. Effect sizes ranged from moderate to large (d = 0.75 – 0.90) across all subscales of the RCADS. Large effect sizes were found for depression, total anxiety and total RCADS scores (d = 0.86, d = 1.12, d = 1.14), and GBOs (d = −1.33). Conclusions Findings support the potential value of low intensity CBT interventions delivered by CWPs in reducing anxiety and depression in this population. Recommendations for the development of the CWP role and CWP services are discussed.
Fusion of EEG and Eye Blink Analysis for Detection of Driver Fatigue

Objective: The driver fatigue detection using multi-channel electroencephalography (EEG) has been extensively addressed in the literature. However, the employment of a single prefrontal EEG channel should be prioritized as it provides users with more comfort. Furthermore, eye blinks from such channel can be analyzed as the complementary information. Here, we present a new driver fatigue detection method based on simultaneous EEG and eye blinks analysis using an Fp1 EEG channel. Methods: First, the moving standard deviation algorithm identifies eye blink intervals (EBIs) to extract blink-related features. Second, the discrete wavelet transform filters the EBIs from the EEG signal. Third, the filtered EEG signal is decomposed into sub-bands, and various linear and nonlinear features are extracted. Finally, the prominent features are selected by the neighbourhood components analysis and fed to a classifier to discriminate between fatigue and alert driving. In this paper, two different databases are investigated. The first one is used for parameters’ tuning of proposed method for the eye blink detection and filtering, nonlinear EEG measures, and feature selection. The second one is solely used for testing the robustness of the tuned parameters. Main results: The comparison between the obtained results from both databases by the AdaBoost classifier in terms of sensitivity (90.2% vs. 87.4%), specificity (87.7% vs. 85.5%), and accuracy (88.4% vs. 86.8%) indicates the reliability of the proposed method for the driver fatigue detection. Significance: Considering the existence of commercial single prefrontal channel EEG headbands, the proposed method can be used to detect the driver fatigue in real-world scenarios.
Coils and Magnets: 3D Analytical Models

This paper deals with analytical models for computing the magnetic flelds created by both kinds of magnetic sources: coils and permanent magnets. It shows that the same analytical model can be used for modeling a permanent magnet or a coil and highlights and explains the mathematical di-culties encountered in solving problems with cylindrical properties. As a remark, each type of source, coil or permanent magnet, can be modeled by both approaches too: the coulombian or the amperian one. The presented three-dimensional mathematical model is accurate whatever the magnetic source dimensions, so for the near fleld and the far fleld. 1. INTRODUCTION Various electromagnetic applications are composed of two thick coils that form a loosely coupled transformer. Then, the flrst coil produces a magnetic fleld which is partly picked up by a secondary coil. A good criterion for evaluating the e-ciency of such a device is the mutual inductance of the coupled transformer. The calculation of the mutual inductance between circular coils has been stud- ied by many authors. On one hand, the approaches used are based on the application of Maxwell's formula, Neumann's formula and the Biot Savart law. These approaches lead to expressions based on elliptic integrals of the flrst, second and third kind, the Heummann's Lambda function or the Bessel functions. On the other hand, authors generally use the flnite element method, the bound- ary element method or numerical algorithms which evaluate the Laplace's equation in all points in space. Then, this paper presents a method for calculating the mutual inductance between two thick coils which leads to an interesting analytical formulation too. As said previously, both models of a source can be used. Thus, this paper presents general expressions that have been obtained with the coulombian and the amperian models of a permanent magnet. But the point is that some conflgurations may be modeled indifierently with the two previous models where others should be modeled either with the coulombian model or the amperian current model in order to obtain inter- esting formulations for the result. For instance, the use of the coulombian model for a thin coil will lead to useful formulations whereas the amperian current model only will give good results in the case of a thick coil. In this paper, a thick coil is replaced by a toroidal conductor carrying a unifom current volume density for calculating both the force exerted between two thick coils and their mutual inductance. The Lorentz Force is used for calculating the exact axial force exerted between two thick coils. Then, the potential vector and the Stocke's theorem are used for calculating the mutual inductance of two thick coils in air. The obtained formulation is interesting as it is fully based on elliptic functions whose numerical calculation is fast and robust. 1.1. Radial Component
Blockade of VEGFR3 signaling leads to functional impairment of dural lymphatic vessels without affecting autoimmune neuroinflammation

The recent discovery of lymphatic vessels (LVs) in the dura mater, the outermost layer of meninges around the central nervous system (CNS), has opened a possibility for the development of alternative therapeutics for CNS disorders. The vascular endothelial growth factor C (VEGF-C)/VEGF receptor 3 (VEGFR3) signaling pathway is essential for the development and maintenance of dural LVs. However, its significance in mediating dural lymphatic function in CNS autoimmunity is unclear. We show that inhibition of the VEGF-C/VEGFR3 signaling pathway using a monoclonal VEGFR3-blocking antibody, a soluble VEGF-C/D trap, or deletion of the Vegfr3 gene in adult lymphatic endothelium causes notable regression and functional impairment of dural LVs but has no effect on the development of CNS autoimmunity in mice. During autoimmune neuroinflammation, the dura mater was only minimally affected, and neuroinflammation-induced helper T (TH) cell recruitment, activation, and polarization were significantly less pronounced in the dura mater than in the CNS. In support of this notion, during autoimmune neuroinflammation, blood vascular endothelial cells in the cranial and spinal dura expressed lower levels of cell adhesion molecules and chemokines, and antigen-presenting cells (i.e., macrophages and dendritic cells) had lower expression of chemokines, MHC class II–associated molecules, and costimulatory molecules than their counterparts in the brain and spinal cord, respectively. The significantly weaker TH cell responses in the dura mater may explain why dural LVs do not contribute directly to CNS autoimmunity. Description Intact dural lymphatic vessels are not essential for autoimmune neuroinflammation. Dispensable dural lymphatics in CNS autoimmunity Lymphatic vessels in the dura, the outermost layer of the meninges, provide a vascular path for immune cells connecting the meninges with the systemic circulation. Dural lymphatics have been proposed as a gateway that T cells targeting CNS autoantigens use to access the brain and spinal cord. Formation and maintenance of dural lymphatics can be abrogated by genetic or pharmacologic interference with vascular endothelial growth factor C (VEGF-C) or its receptor VEGFR3. Li et al. found that atrophy of dural lymphatics by VEGFR3 blockade in mice was insufficient to block autoimmune neuroinflammation initiated by immunization with myelin autoantigens or transfer of encephalitogenic T cells. These findings suggest that therapies aimed at disrupting dural lymphatics are unlikely to attenuate human autoimmune neuroinflammatory diseases such as multiple sclerosis. —IRW
The Research Based on the Discrete Cellular Ant Algorithm in the Geometric Constraint Solving

A constraint can describe a relation to be satisfied.Once the user defines a series of relations,the system will select a proper state to satisfy the constraints after the parameters are modified.When transferring the geometric constraint equation group into the optimization model,we adopt a discrete cellular ant algorithm(DCAA) by evolutionary rule of cells and characteristics of ant colony optimization.Discrete cellular ant algorithm is a new type of bionic algorithm,which uses the evolution law of cellular in the discrete cellular space and the characteristics of ant optimization,and it provides an optimal way for solving practical problems.The experiment shows that the algorithm can solve the geometric constraint problems efficiently.
Impaired flexibility in patients with tropical spastic paraparesis/HTLV-associated myelopathy: evaluation via pendulum fleximeter

Abstract Background Flexibility is crucial to the harmonious execution of joint movements. While skeletal muscle dysfunction in patients with HTLV-1 can interfere with mobility, it is unclear whether these patients experience reduced flexibility. Objective To evaluate the differences in flexibility between HTLV-1-infected individuals with and without myelopathy compared with uninfected controls. We also investigated whether age, sex, body mass index (BMI), physical activity level, or lower back pain influence flexibility in HTLV-1-infected individuals. Methods The sample consisted of 56 adults, of which 15 did not have HTLV-1, 15 had HTLV-1 without myelopathy, and 26 had TSP/HAM. Their flexibility was assessed using the sit-and-reach test and a pendulum fleximeter. Results No differences in flexibility were observed between the groups with and without myelopathy and controls without HTLV-1 infection using the sit-and-reach test. The pendulum fleximeter results of individuals with TSP/HAM presented the lowest flexibility among the groups with respect to trunk flexion, hip flexion and extension, knee flexion, and ankle dorsiflexion, even after adjusting for age, sex, BMI, level of physical activity, and lower back pain using multiple linear regression models. Additionally, HTLV-1-infected individuals without myelopathy demonstrated reduced flexibility in movements: knee flexion, dorsiflexion, and ankle plantar flexion. Conclusions Individuals with TSP/HAM demonstrated reduced flexibility in most of the movements evaluated by the pendulum fleximeter. Additionally, HTLV-1-infected individuals without myelopathy demonstrated reduced knee and ankle flexibility, potentially representing a marker of myelopathic development.
Exosomal HBV-DNA for diagnosis and treatment monitoring of chronic hepatitis B

Abstract This study examined exosomal hepatitis B virus (HBV)-DNA levels in chronic HBV infection (CHB). Patients were grouped according to the European Association for the Study of the Liver classification (1: HBV-DNA-positive CHB, normal alanine aminotransferase [ALT]; 2: HBV-DNA-positive CHB, elevated ALT; 3: HBV-DNA-negative HBeAb-positive CHB, normal ALT; 4: HBV-DNA-positive HBeAg-negative HBeAb-positive CHB, elevated ALT; 5: HBV-DNA-negative, HBcAb-positive; 6: HBV-negative, normal ALT). Exosomes were isolated, comparative analysis of exosomes and serum HBV-DNA. The HBV-DNA content was lower in exosomes than in serum for groups 1, 2, and 4 (all P < 0.05). In the groups negative for serum HBV-DNA (groups 3 and 5), the exosomal HBV-DNA levels were higher than the serum HBV-DNA levels (all P < 0.05). The exosomal and serum HBV-DNA levels were correlated in groups 2 (R 2 = 0.84) and 4 (R 2 = 0.98). The exosomal HBV-DNA levels were correlated with total bilirubin (R 2 = 0.94), direct bilirubin (R 2 = 0.82), and indirect bilirubin (R 2 = 0.81) in group 5 (all P < 0.05). In patients with CHB and negative for serum HBV-DNA, exosomal HBV-DNA was detectable and could be used to monitor the treatment effects. Exosomal HBV-DNA could be used in patients with a high suspicion of HBV infection but negative for serum HBV-DNA.
Semantic Relation Extraction: A Review of Approaches, Datasets, and Evaluation Methods With Looking at the Methods and Datasets in the Persian Language

A large volume of unstructured data, especially text data, is generated and exchanged daily. Consequently, the importance of extracting patterns and discovering knowledge from textual data is significantly increasing. As the task of automatically recognizing the relations between two or more entities, semantic relation extraction has a prominent role in the exploitation of raw text. This article surveys different approaches and types of relation extraction in English and the most prominent proposed methods in Persian. We also introduce, analyze, and compare the most important datasets available for relation extraction in Persian and English. Furthermore, traditional and emerging evaluation metrics for supervised, semi-supervised, and unsupervised methods are described, along with pointers to commonly used performance evaluation datasets. Finally, we briefly describe challenges in extracting relationships in Persian and English and dataset creation challenges.
Propensity-Dependent Model for Unbiased Learning-to-Rank

Most present unbiased learning-to-rank models are based on the trust bias assumption to learn a ranking policy by Inverse Propensity Scoring (IPS). The trust bias assumption improves the unrealistic noise-free assumption in the Position-Based model, but it assumes that the propensities are independent. In this paper, we improve this assumption and consider that the propensities of different positions are relevant. In particular, we model the relationship between different propensities as a Propensity-Dependent model and use both IPS estimator and the Doubly Robust estimator to learn the optimal ranking policy. Finally, we generate the dataset in a simulated study and then evaluate the model's performance.
Road Network Representation Learning: A Dual Graph-based Approach

Road network is a critical infrastructure powering many applications including transportation, mobility and logistics in real life. To leverage the input of a road network across these different applications, it is necessary to learn the representations of the roads in the form of vectors, which is named road network representation learning (RNRL). While several models have been proposed for RNRL, they capture the pairwise relationships/connections among roads only (i.e., as a simple graph), and fail to capture among roads the high-order relationships (e.g., those roads that jointly form a local region usually have similar features such as speed limit) and long-range relationships (e.g., some roads that are far apart may have similar semantics such as being roads in residential areas). Motivated by this, we propose to construct a hypergraph, where each hyperedge corresponds to a set of multiple roads forming a region. The constructed hypergraph would naturally capture the high-order relationships among roads with hyperedges. We then allow information propagation via both the edges in the simple graph and the hyperedges in the hypergraph in a graph neural network context. In addition, we introduce different pretext tasks based on both the simple graph (i.e., graph reconstruction) and the hypergraph (including hypergraph reconstruction and hyperedge classification) for optimizing the representations of roads. The graph reconstruction and hypergraph reconstruction tasks are conventional ones and can capture structural information. The hyperedge classification task can capture long-range relationships between pairs of roads that belong to hyperedges with the same label. We call the resulting model HyperRoad. We further extend HyperRoad to problem settings when additional inputs of road attributes and/or trajectories that are generated on the roads are available. We conduct extensive experiments on two real datasets, for five downstream tasks, and under four problem settings, which demonstrate that our model achieves impressive improvements compared with existing baselines across datasets, tasks, problem settings, and performance metrics. CCS Concepts: • Information systems → Data mining; • Urban computing; • Spatial-temporal systems;
Using A/B Testing as a Pedagogical Tool for Iterative Design in HCI Classrooms

This paper explores the use of A/B testing as a pedagogical tool for iterative design in HCI classrooms and outlines a vision for experiment-inspired design. The traditional focus on the statistical aspects of A/B testing education has meant that the equally crucial role of iterative design embedded within the experimental process has not received commensurate attention. By incorporating iterative design learning activities that are scaffolded by A/B testing tools, HCI students can gain transferable skills and experience in doing multiple cycles of ideation, prototyping, testing, and evaluation, and simultaneously contribute to continual course improvement. We reconsider the role of experimentation in HCI education as a means for exploring complex design spaces. Drawing from our experience in teaching this approach and conducting education research involving sequences of online controlled experiments, we present examples of how to use A/B testing as a pedagogical tool for iterative design in HCI classrooms.
Teaching & Learning Positionality in HCI education: reflecting on our identities as educators and facilitating the discussion in the classroom

UX designers and practitioners acknowledge users’ different skills and try to address their needs to design better products and experiences. As HCI educators, we searched for tools to help our students to recognize that they might have different perspectives from the users they will be designing for, generating bias and assumptions in the design process. Positionality refers to the personal and social constructs that define our identity, shaping how we see and interpret the world around us, as well as the way the world sees and interprets us. Practicing positionality in HCI education is a meaningful way to reflect on our teaching approaches, our measures and expectations of students’ performance and engagement. For the students, learning about positionality and reflexivity can have an impact on their design work and research, raising awareness on relationships of power and subjectivity. During this Masterclass, we present tools and methods that can be used for teaching and learning (T&L) activities about positionality. We invite attendees to create their positionality statement and share their experience, facilitating a discussion about the challenges that are common both to T&L and interaction design, such as ethics, privacy, stereotypes and stigmatization.