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Whether the use of lecture capture technology helps improve student performance is a contested area of research. In most cases, the answer relies on the degree to which online recordings supplement or substitute for live or live-streamed lecture delivery. We present a parameter, the technical rate of substitution, which captures this information holding student performance constant. We introduce a method to estimate this measure, which we applied to a pilot sample of students in a first-year quantitative methods class. We find imperfect substitutability: live lectures are, in the context of our sample, a less resource-intensive technology than the corresponding online recording to produce a set exam score. Our main contribution is the proposed parameter and the method to derive it. Its calculation significantly facilitates comparison and consolidation of previous research and provides valuable insights on the relative effectiveness of different learning platforms to inform instructor best practice and higher education policy. Implications for practice or policy: Instructors can use our measure to evaluate their students’ effective use of online learning technologies. Course designers can use the measure to select the right mix of online and offline delivery methods. Educators can use the measure to determine the most effective platform for delivering introductory, substantive or review material. Our method helps researchers compare and generalise results from existing studies of the relative performance of online and offline educational technologies.

Age-related macular degeneration (AMD) is a leading cause of blindness characterized by degeneration of retina pigment epithelium (RPE) and photoreceptors in the macular region. Activation of the innate immune cGAS-STING signaling has been detected in RPE of dry AMD patients, but the regulatory basis is largely unexplored. Heterochromatin is a highly compact, transcription inert chromatin status. We have recently shown that heterochromatin is required for RPE survival through epigenetically silencing p53-mediated apoptosis signaling. Here, we found that cGAS and STING were dose-dependently upregulated in mouse RPE and retina during oxidative injury, correlated with decreased chromatin compaction in their gene loci. Genetic or pharmaceutical disruption of heterochromatin leads to elevated cGAS and STING expression and enhanced inflammatory response in oxidative stress-induced RPE and retina degeneration. In contrast, application of methotrexate (MTX), a recently identified heterochromatin-promoting drug, inhibits cGAS and STING in both RPE and retina, attenuates RPE/retina degeneration and inflammation. Further, we show that intact heterochromatin is required for MTX to repress cGAS and STING. Together, we demonstrated an unrevealed regulatory function of heterochromatin on cGAS and STING expression and provide potential new therapeutic strategy for AMD treatment.

The power of features considerably influences the classification performance of remote sensing scene classification (RSSC). Recently, deep convolutional neural networks (DCNNs) have been used to extract powerful scene features. Nevertheless, confusion and overlap still occur in the feature space, leading to inaccurate RSSC. To alleviate this problem, we propose a novel deep metric learning loss function incorporated into a sphere loss to enhance the discrimination of feature representations. Inspired by two representative loss functions (i.e., angular loss and center loss), the proposed sphere loss learns a unique cluster center for each class in a remote sensing scene. Because the cluster centers and features are restricted by an introduced geometrical constraint, the intraclass distance of features decreases, while the interclass distance increases. Moreover, we introduce a spatial constraint, i.e., a uniformity coefficient on different cluster centers, which causes the centers to form a uniform distribution that maximizes the interclass distances between features. Extensive analysis and experiments on three commonly used RSSC data sets consistently show that, compared with state-of-the-art methods, the proposed sphere loss can effectively learn discriminative feature representations and significantly improve RSSC.

Background: Determination of H3 K27M mutation in diffuse midline glioma (DMG) is key for prognostic assessment and stratifying patient subgroups for clinical trials. MRI can noninvasively depict morphological and metabolic characteristics of H3 K27M mutant DMG. Purpose: This study aimed to develop a deep learning (DL) approach to noninvasively predict H3 K27M mutation in DMG using T2-weighted images. Study Type: Retrospective and prospective. Population: For diffuse midline brain gliomas, 341 patients from Center-1 (27 ± 19 years, 184 males), 42 patients from Center-2 (33 ± 19 years, 27 males) and 35 patients (37 ± 18 years, 24 males). For diffuse spinal cord gliomas, 133 patients from Center-1 (30 ± 15 years, 80 males). Field Strength/Sequence: 5T and 3T, T2-weighted turbo spin echo imaging. Assessment: Conventional radiological features were independently reviewed by two neuroradiologists. H3 K27M status was determined by histopathological examination. The Dice coefficient was used to evaluate segmentation performance. Classification performance was evaluated using accuracy, sensitivity, specificity, and area under the curve. Statistical Tests: Pearson's Chi-squared test, Fisher's exact test, two-sample Student's t-test and Mann–Whitney U test. A two-sided P value

As a part of Internet-of-Things applications, various smartphone-based indoor location services have considerable commercial value. It is largely agreed that the integration of multiple sensors is the preferable solution for improving the performance of smartphone indoor positioning, thanks to the diversity of built-in sensors. However, heading error remains a challenge for smartphone indoor positioning, especially in complex indoor scenes. This article, therefore, proposes a heading estimation solution to enhance the accuracy and reliability of smartphone indoor positioning. The extended Kalman filter (EKF)-based solution fuses smartphone built-in motion sensors, magnetometers, building map knowledge, and fingerprinting coarse positions from Wi-Fi or Bluetooth. First, the context of pedestrian mobility and scene knowledge is inferred by combining these data. Then, a scene augmentation strategy and magnetic interference online detection method are applied to calibrate the gyro accumulation error and improve the heading estimation accuracy. Additionally, quasistatic and low-dynamic judgments and online calibration are used to mitigate gyro drift. The proposed solution is implemented on a smartphone device and validated in several experiments under natural pedestrian mobility and complex indoor scenarios. Experiments show that the accuracy of heading estimation is improved from 13.1° to 2.0°. The improved heading estimation enhances the accuracy of smartphone indoor positioning from 3.57 to 0.90 m. The proposed solution is applicable to real location-based service scenarios.

Accurate differentiation of intramedullary spinal cord tumors and inflammatory demyelinating lesions and their subtypes are warranted because of their overlapping characteristics at MRI but with different treatments and prognosis. The authors aimed to develop a pipeline for spinal cord lesion segmentation and classification using two-dimensional MultiResUNet and DenseNet121 networks based on T2-weighted images. A retrospective cohort of 490 patients (118 patients with astrocytoma, 130 with ependymoma, 101 with multiple sclerosis [MS], and 141 with neuromyelitis optica spectrum disorders [NMOSD]) was used for model development, and a prospective cohort of 157 patients (34 patients with astrocytoma, 45 with ependymoma, 33 with MS, and 45 with NMOSD) was used for model testing. In the test cohort, the model achieved Dice scores of 0.77, 0.80, 0.50, and 0.58 for segmentation of astrocytoma, ependymoma, MS, and NMOSD, respectively, against manual labeling. Accuracies of 96% (area under the receiver operating characteristic curve [AUC], 0.99), 82% (AUC, 0.90), and 79% (AUC, 0.85) were achieved for the classifications of tumor versus demyelinating lesion, astrocytoma versus ependymoma, and MS versus NMOSD, respectively. In a subset of radiologically difficult cases, the classifier showed an accuracy of 79%–95% (AUC, 0.78–0.97). The established deep learning pipeline for segmentation and classification of spinal cord lesions can support an accurate radiologic diagnosis. Supplemental material is available for this article. © RSNA, 2022 Keywords: Spinal Cord MRI, Astrocytoma, Ependymoma, Multiple Sclerosis, Neuromyelitis Optica Spectrum Disorder, Deep Learning

The gel polymer electrolytes (GPEs) with poly(acrylonitrile-polyhedral oligomeric silsesquioxane)/poly(vinylidene fluoride) (PAN-POSS/PVDF) blends as free-standing porous membrane and ionic liquid (IL) as absorption substance were successfully prepared. By tuning the content of PAN-POSS, the porosity and absorptivity of the blended membranes could be regulated. Due to the higher porosity and absorptivity, the ionic conductivity of GPEs with 15 wt% PAN-POSS reaches to 1.91 × 10−3 S cm−1 at 20 oC. Meanwhile, the electrolytes also show excellent mechanical properties, thermal stability, and fire resistance. More importantly, the high electrochemical window of 4.6 V (vs. Li/Li+) has been acquired and the testing cells with Li metal anode and LiFePO4 cathode show a tolerable rate performance. Such prepared GPEs are expected to be applied to lithium batteries with high safety and electrochemical performance.

Homologous recombination (HR) and nonhomologous end joining (NHEJ) are considered the two main double-strand break (DSB) repair approaches in eukaryotes. Inhibiting the activities of the key component in NHEJ commonly enhances the efficiency of targeted gene knockouts or affects growth and development in higher eukaryotes. However, little is known about the roles of the NHEJ pathway in foliar pathogens. Here we identified a gene designated StKU80, which encodes a putative DNA end-binding protein homologous to yeast Ku80, in the foliar pathogen Exserohilum turcicum. Conserved domain analysis showed that the typical domains VWA, Ku78 and Ku-PK-bind are usually present in Ku70/80 proteins in eukaryotes and are also present in StKu80. Phylogenetic analysis indicated that StKu80 is most closely related to Ku80 (XP_001802136.1) from Parastagonospora nodorum, followed by Ku80 (AGF90044.1) from Monascus ruber. Furthermore, the gene knockout mutants ΔStKU80-1 and ΔStKU80-2 were obtained. These mutants displayed longer septas, thinner cell walls, smaller amounts of substances on cell wall surfaces, and more mitochondria per cell than the wild-type (WT) strain but similar HT-toxin activity. The mutants did not produce conidia and mature appressoria. On the other hand, the mutants were highly sensitive to H2O2, but not to ultraviolet radiation. In summary, the StKU80 plays devious roles in regulating the development of E. turcicum.

The alarm is a core function of security monitoring information systems. With the characteristics of high information density, strong timeliness, and visual environment interference, the effectiveness of alarm information design is a significant key affecting system performance. The purpose of this paper is to study the design method of alarm information to improve the capture efficiency of users’ visual attention in complex information interfaces. By sorting out related design standards and research literature, this paper identifies 7 current alarm information coding methods. The four most used visual coding methods are chosen for combination. By selecting any two or three of the four coding methods for combination, 10 combinations are finally obtained, and 10 visual solutions are designed for experimental comparison. The experiment took the mine safety monitoring system interface as the carrier and tested 10 visual solutions as stimuli. By recording the subject’s time to first fixation to the stimulus, we compared the differences in the efficiency of guiding user’s attention under different coding combinations, then sought a better coding method for alarm information. Experimental results demonstrate that different coding combinations have impacts on the efficiency of visual attention. Compared with other solutions, the solution with the combination of three coding methods of color, flashing, and shape(size) is more efficient and takes less time to notice the alarm information. Whilst the attention level is less affected by the number of coding methods and is more affected by the types of coding methods included in the solution. For example, when the coding method includes color or flashing coding, the subjects noticed the alarm information faster and more efficiently, and no experimental failure cases occurred during the experiment when using color and flash coding at the same time. The conclusion effectively provides a solution for the design of alarm information in monitoring systems.Keywords: Alarm Information, Visual Attention, Eye Movement Measurement, Multi-dimensional Coding

The purpose of the study is to extract and construct the development and method of synaesthetic visual translation in product design, provide new design thinking, and enrich user experience. This paper employs a mixed method of case study, practice, fuzzy evaluation, etc. Through case analysis, the manifestation of visual translation in product design is summarized, the translation law between vision and other senses is abstracted, a method to achieve visual translation is built, and research conclusions are verified through design practice. Based on fuzzy evaluations, the development of synaesthetic visual translation is established, and a reusable visual translation design method is proposed, which enriches product connotation while improving comprehensibility, and realizes a multi-dimensional and in-depth user experience.

Armless people face more difficulties in daily self-care activities such as cooking. Most of the existing kitchen products are based on the needs of normal people and rarely consider the characteristics of the disadvantaged group of armless people. Armless people can only use the product through the feet, chin and residual limb, which has high requirements for motor capability. Therefore, it is difficult to guarantee the efficiency, safety and operating comfort of the products, which has also become an obstacle to independent living of people without arms. The goal of this research is to design kitchen products suitable for people without arms. The research uses the definition and evaluation method of user capability in the capability-demand theory proposed by Clarkson et al. to disassemble the motor capability in user capability into strength, dexterity, reach and mobility. Through survey questionnaires, we can understand the scores of armless people on specific motor capabilities and use their higher-scoring motor capabilities to match the demands of product use in design practice, so as to improve the operability of the product. Based on the design strategy of P. John Clarkson and others for products using hands, the author summarizes the design strategy of products that use lower limbs and foot operations from the 6 dimensions of position, shape, force, precision, task and environment. It is proposed for guiding how to design products for armless people, the author also designs kitchen products based on this, hoping to help armless people cook like normal people. The analysis of the motor capability of armless people in this study can provide a reference for product design for this disadvantaged group. As a group with low levels of attention in the market, design, and society, the research on armless people has expanded the connotation and scope of inclusive design to a certain extent.

Mobile navigation has become a necessary tool for people to travel around because it provides functions such as GPS positioning, spot information, route navigation, etc. However, when using mobile navigation, the elderly often encounters problems like complex operation process and difficulties in learning.Focusing on the elderly, the influence factors on usability of mobile navigation are evaluated in this research. As a result, a usability evaluation system of mobile navigation for the elderly was conducted, which is composed of 3 dimensions (effectiveness, efficiency and satisfaction), 7 first-level indicators (learnability, ease of use, memorability, etc.) and 14 second-level indicators (ease of learning, effectiveness of help functions, ease of operation, etc.). Using the usability evaluation system, this research evaluates the usability of some mobile navigation products, and puts forward design suggestions for product optimization.This research applies the usability theory to the evaluation of mobile navigation for the elderly. It is hoped that this research can provide reference for the age-friendly design of related products, so as to make it more convenient for the elderly to use mobile navigation and make their traveling easier.

In order to study how dolphins transmit information through sound, a dolphin sound-triggered underwater acoustic recorder was designed to collect sound samples of dolphins communicating. When working underwater for a long time, the dolphin voice signal recorder often faces the problem of insufficient power and limited storage space. In response to this problem, this paper proposes a dolphin sound signal recorder with STM32F407 as the main processor and MSP430F5438A as the coprocessor, which can work on the seabed for a long time and store sufficient samples of dolphins' communication sounds for scientific analysis. The recorder first uses short-term energy to detect whether the dolphin is coming, and then uses a function that describes the correlation between two different signals to calculate the degree of similarity between the sound feature parameters extracted at the sound collection site and the sound feature parameters extracted at the dolphin sound sample, then the similarity value is compared with the set similarity threshold. If the similarity value is greater than or equal to the threshold, the sound signal is stored in the SD card. If the similarity value is less than the threshold, it will not be stored. The paper specifically introduces the design of acoustic triggering algorithm and the design of dolphin sound signal recorder.

Modulation pattern recognition is an important part of underwater acoustic communication. Due to the complexity of underwater acoustic media (propagation loss, ocean noise, multipath effect and Doppler effect), underwater acoustic channel is considered to be one of the most challenging wireless communication channels. This paper proposed an intelligent underwater acoustic signal processing and recognition method based on artificial neural network (ANN) and signal feature extraction. Firstly, the real part and imaginary part of the signal are extracted by fast Fourier transform (FFT), the variance, mean and other eigenvalues of the real part and imaginary part are calculated, respectively. Secondly, the extracted signal features are used to train ANN classifier to realize the classification and recognition of different signals. In this way, the intelligent recognition of underwater acoustic signal by data-driven method is realized. Finally, the effectiveness of the proposed method is verified by simulation, and the good recognition effect is achieved.

In the field of underwater acoustic communication, some underwater devices often operate voice communication and digital communication separately when communicating, and the existing analog modulated voice communication and digital coded voice communication cannot distinguish between digital communication and voice communication in time, resulting in data The transmission speed is slower and the voice quality is lower. In order to solve this problem, the design proposes the use of hybrid communication for information transmission, and designs a special communication protocol system. At the same time, the system adopts positive and negative hyperbolic frequency modulation in the synchronization head and synchronization tail, and adds a spread spectrum communication data header after the synchronization head. The system uses cyclic redundancy check (CRC) to distinguish between voice information and digital information and to synchronize them. The system uses data communication to aid voice communication. The communication system makes the communication process less affected by the channel, has strong anti-interference ability, and realizes better data transmission. Simulation and laboratory tests show that the system can effectively improve the quality of voice communication.

T cell-mediated immune injury plays a critical role in the pathogenesis of hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF). Given the high short-term mortality and crucial role of T cells in the disease progression, it is necessary to investigate the dynamics of T cell clones during HBV-ACLF. The aim of this study was to longitudinally investigate dynamic changes in the composition and perturbation of T cell receptor β (TCRβ) chain repertoires and to determine whether TCR repertoire characteristics were associated with HBV-ACLF patient outcomes. Peripheral blood mononuclear cells (PBMCs) were collected at two time points from 5 HBV-ACLF patients. Global CD4+ and CD8+ T cells were sorted using magnetic beads. TCRβ complementarity-determining region 3 was analyzed by unbiased high-throughput sequencing. During HBV-ACLF, there was a significant decrease in the diversity of T cell repertoires and an increase in proportion of the most 100 abundant clonotypes of CD8 T cells but not CD4. Decreased CD8 repertoire diversity was positively correlated with the reduction of the Model for End-Stage Liver Disease (MELD) score. There was significant clonal expansion in CD8 but not in CD4 T cell repertoires in HBV-ACLF patients during disease progression. Patients with greater clonal expansions in CD8 T cell repertoires may have better outcomes. CD8 TCRβ repertoire diversity may serve as a potential predictive marker for disease outcome.

This paper examines the effects of cognitive abilities and non-cognitive skills on gambling behaviors in Australia. We use the scores for three cognitive functioning tasks as measures of cognitive abilities. Locus of control and the Big Five personality traits are used as measures of non-cognitive skills. We find that cognitive abilities affect both gambling participation and problem gambling. While locus of control does not affect people’s participation in gambling, gambling participants with strong internal locus of control are less likely to become a problem gambler than those with external locus of control. We also show that personality traits are important factors for both gambling participation and problem gambling. There is also evidence that both cognitive and non-cognitive skills affect gamblers’ choice between skill-and-chance gambling and pure-chance gambling. Our findings seem to support the view that market imperfection could at least explain some individuals’ participation in gambling.