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This study utilizes China’s records of non-accidental mortality along with twenty-five simulations from the NASA Earth Exchange Global Daily Downscaled Projections to evaluate forthcoming heat stress and heat-related mortality across China across four distinct scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The findings demonstrate a projected escalation in the heat stress index (HSI) throughout China from 2031 to 2100. The most substantial increments compared to the baseline (1995–2014) are observed under SSP5-8.5, indicating a rise of 7.96°C by the year 2100, while under SSP1-2.6, the increase is relatively modest at 1.54°C. Disparities in HSI growth are evident among different subregions, with South China encountering the most significant elevation, whereas Northwest China exhibits the lowest increment. Projected future temperatures align closely with HSI patterns, while relative humidity is anticipated to decrease across the majority of areas. The study’s projections indicate that China’s heat-related mortality is poised to surpass present levels over the forthcoming decades, spanning a range from 215% to 380% from 2031 to 2100. Notably, higher emission scenarios correspond to heightened heat-related mortality. Additionally, the investigation delves into the respective contributions of humidity and temperature to shifts in heat-related mortality. At present, humidity exerts a greater impact on fluctuations in heat-related mortality within China and its subregions. However, with the projected increase in emissions and global warming, temperature is expected to assume a dominant role in shaping these outcomes. In summary, this study underscores the anticipated escalation of heat stress and heat-related mortality across China in the future. It highlights the imperative of emission reduction as a means to mitigate these risks and underscores the variances in susceptibility to heat stress across different regions.

When the 5-fluorouracil, leucovorin, and oxaliplatin (FOLFOX) chemotherapy regimen is used to treat colorectal cancer (CRC), chemotherapy-induced peripheral neuropathy (CIPN) caused by oxaliplatin can substantially affect quality of life (QOL) in the CRC patients. This study compared emotional distress and QOL during FOLFOX in CRC patients with and without CIPN symptoms.This cross-sectional, descriptive, and comparative study recruited 68 CRC patients receiving FOLFOX at a local teaching hospital and at a medical center in southern Taiwan. Self-reported structured questionnaires (oxaliplatin-associated neuropathy questionnaire, profile of mood states short form, and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, Core 30, version 3.0) were used for 1-time data collection. The Chi-square test, Fisher exact test, and Mann-Whitney U test were used to analyze data, and a P-value

Changes in arousal influence cortical sensory representations, but the synaptic mechanisms underlying arousal-dependent modulation of cortical processing are unclear. Here, we use 2-photon Ca2+ imaging in the auditory cortex of awake mice to show that heightened arousal, as indexed by pupil diameter, broadens frequency-tuned activity of layer 2/3 (L2/3) pyramidal cells. Sensory representations are less sparse, and the tuning of nearby cells more similar when arousal increases. Despite the reduction in selectivity, frequency discrimination by cell ensembles improves due to a decrease in shared trial-to-trial variability. In vivo whole-cell recordings reveal that mechanisms contributing to the effects of arousal on sensory representations include state-dependent modulation of membrane potential dynamics, spontaneous firing, and tone-evoked synaptic potentials. Surprisingly, changes in short-latency tone-evoked excitatory input cannot explain the effects of arousal on the broadness of frequency-tuned output. However, we show that arousal strongly modulates a slow tone-evoked suppression of recurrent excitation underlying lateral inhibition [H. K. Kato, S. K. Asinof, J. S. Isaacson, Neuron, 95, 412-423, (2017)]. This arousal-dependent "network suppression" gates the duration of tone-evoked responses and regulates the broadness of frequency tuning. Thus, arousal can shape tuning via modulation of indirect changes in recurrent network activity.

While it is recognised that the numbers of students needing accessibility supports and accommodations are increasing exponentially, research on accommodations during the COVID-19 pandemic is still sparse. The purpose of the current study was to explore special education teachers’ accommodation practices at secondary schools before and during the unprecedented time of COVID-19. To better understand the experiences of participating teachers, we engaged seven teachers from a prairie province in Canada with one-on-one online semi-structured interviews. Teachers who offered accommodations to students before COVID-19 used a range of accommodations such as general technologies and assistive technology that fall into major categories of accommodations as defined by research. Evidence from this study indicates that some teachers delivered learning packages to homes or taught online classes during school closures, while some teachers did not. Teachers who taught remotely changed some of their accommodation practices during the school closures because in-person classes were switched to online learning. The implications for professional development are also discussed in this paper.

Existing protocol recognition methods cannot effectively extract the temporal and spatial characteristics of protocol data,which leads to low accuracy of protocol recognition.An application layer protocol recognition method based on one dimensional residual network and recurrent neural network is proposed.The proposed model consists of one dimensional preactivated residual network(PreResNet) and bidirectional gated recurrent neural network(BiGRU).The PreResNet is used to extract spatial characteristics of the protocol data,and the BiGRU is used to extract temporal characteristics of the protocol data.The attention mechanism is used to extract the key features related to protocol recognition to improve the accuracy of protocol recognition.The proposed method firstly extracts the application layer protocol data from network traffic,and the data is preprocessed and transformed into one dimensional vectors.Then the classification model is trained with the training data and a mature protocol recognition model is obtained.Finally,the trained classification model is used to identify the application layer protocols.Experimental results on public dataset ISCX2012 show that the proposed protocol recognition model has an overall accuracy of 96.87% and an average F value of 96.81%,which are higher than those of other protocol recognition models.