Network Traffic Classification Based on External Attention by IP Packet Header

As the emerging services have increasingly strict requirements on quality of service (QoS), such as millisecond network service latency ect., network traffic classification technology is required to assist more advanced network management and monitoring capabilities. So far as we know, the delays of flow-granularity classification methods are difficult to meet the real-time requirements for too long packet-waiting time, whereas the present packet-granularity classification methods may have problems related to privacy protection due to using excessive user payloads. To solve the above problems, we proposed a network traffic classification method only by the IP packet header, which satisfies the requirements of both user's privacy protection and classification performances. We opted to remove the IP address from the header information of the network layer and utilized the remaining 12-byte IP packet header information as input for the model. Additionally, we examined the variations in header value distributions among different categories of network traffic samples. And, the external attention is also introduced to form the online classification framework, which performs well for its low time complexity and strong ability to enhance high-dimensional classification features. The experiments on three open-source datasets show that our average accuracy can reach upon 94.57%, and the classification time is shortened to meet the real-time requirements (0.35ms for a single packet).Comment: 12 pages, 5 figure

An updated interactive database for 1692 genetic variants in coagulation Factor IX provides detailed insights into haemophilia B

BACKGROUND: Genetic variants in coagulation factor IX (FIX) are associated with haemophilia B, a rare bleeding disease. F9 variants are widespread across the gene and were summarised in our FIX variant database introduced in 2013. OBJECTIVE: We rationalise the molecular basis for 598 new F9 variants and 1645 new clinical cases, making a total of 1692 F9 variants and 5358 related patient cases. METHODS: New F9 variants were identified from publications and on-line resources, and compiled into a MySQL database for comparison with the human FIXa protein structure. RESULTS: The new total of 1692 F9 variants correspond to 406 (88%) of the 461 FIX residues and now include 70 additional residues. These comprise 945 unique point variants, 281 deletions, 352 polymorphisms, 63 insertions, and 51 others. Most FIX variants were point variants, although their proportion (56%) has reduced compared to 2013 (73%), while the proportion of polymorphisms has increased from 5% to 21%.The 764 unique mild severity variants in the mature protein with known phenotypes include 74 (9.7%) quantitative type I variants and 116 (15.2%) predominantly qualitative type II variants. The remaining 574 variants types are unspecified. Inhibitors are associated with 152 haemophilia B cases out of 5358 patients (2.8%), an increase of 93 from the previous database. CONCLUSION: The even distribution of the F9 variants revealed few mutational hotspots, and most variants were associated with small perturbations in the FIX protein structure. The updated database will assist clinicians and researchers in assessing treatments for haemophilia B patients

Promising derivatives of rutaecarpine with diverse pharmacological activities

Rutaecarpine (RUT) is a natural pentacyclic indolopyridoquinazolinone alkaloid first isolated from one of the most famous traditional Chinese herbs, Evodia rutaecarpa, which is used for treating a variety of ailments, including headaches, gastrointestinal disorders, postpartum hemorrhage, amenorrhea, difficult menstruation, and other diseases. Accumulating pharmacological studies showed that RUT possesses a wide range of pharmacological effects through different mechanisms. However, its poor physicochemical properties and moderate biological activities have hampered its clinical application. In this regard, the modification of RUT aimed at seeking its derivatives with better physicochemical properties and more potency has been extensively studied. These derivatives exhibit diverse pharmacological activities, including anti-inflammatory, anti-atherogenic, anti-Alzheimer’s disease, antitumor, and antifungal activities via a variety of mechanisms, such as inhibiting cyclooxygenase-2 (COX-2), acetylcholine (AChE), phosphodiesterase 4B (PDE4B), phosphodiesterase 5 (PDE5), or topoisomerases (Topos). From this perspective, this paper provides a comprehensive description of RUT derivatives by focusing on their diverse biological activities. This review aims to give an insight into the biological activities of RUT derivatives and encourage further exploration of RUT

A meta-analysis of the relationship between climate change experience and climate change perception

Will climate change experience shape people\u27s climate change perception? To examine the evidence, we performed a pre-registered meta-analysis using data from 302 studies, covering 351,378 observations. Our results find that climate change experience only has a weak positive correlation with climate change awareness in general (r = 0.098, 95% CI 0.0614, 0.1348), and the effect sizes vary considerably across different climate events. General hazard and temperature anomalies experiences have significant correlations, but other events exhibit no or neglectable effects. The moderator analysis showed that self-reported studies result in higher correlations, whereas studies based on victims\u27 actual experiences report lower effect sizes. Our study suggests that people\u27s climate change experiences may not be effective in shaping their awareness of climate change, which is likely due to people\u27s attribution style and adaptability. The importance of proactive education thus is further emphasized to raise the awareness of climate change

Two-element interferometer for millimeter-wave solar flare observations

In this paper, we present the design and implementation of a two-element interferometer working in the millimeter wave band (39.5 GHz - 40 GHz) for observing solar radio emissions through nulling interference. The system is composed of two 50 cm aperture Cassegrain antennas mounted on a common equatorial mount, with a separation of 230 wavelengths. The cross-correlation of the received signals effectively cancels the quiet solar component of the large flux density (~3000 sfu) that reduces the detection limit due to atmospheric fluctuations. The system performance is obtained as follows: the noise factor of the AFE in the observation band is less than 2.1 dB, system sensitivity is approximately 12.4 K (~34 sfu) with an integration time constant of 0.1 ms (default), the frequency resolution is 153 kHz, and the dynamic range is larger than 30 dB. Through actual testing, the nulling interferometer observes a quiet sun with a low level of output fluctuations (of up to 50 sfu) and has a significantly lower radiation flux variability (of up to 190 sfu) than an equivalent single-antenna system, even under thick cloud cover. As a result, this new design can effectively improve observation sensitivity by reducing the impact of atmospheric and system fluctuations during observation

How we learn social norms: a three-stage model for social norm learning

As social animals, humans are unique to make the world function well by developing, maintaining, and enforcing social norms. As a prerequisite among these norm-related processes, learning social norms can act as a basis that helps us quickly coordinate with others, which is beneficial to social inclusion when people enter into a new environment or experience certain sociocultural changes. Given the positive effects of learning social norms on social order and sociocultural adaptability in daily life, there is an urgent need to understand the underlying mechanisms of social norm learning. In this article, we review a set of works regarding social norms and highlight the specificity of social norm learning. We then propose an integrated model of social norm learning containing three stages, i.e., pre-learning, reinforcement learning, and internalization, map a potential brain network in processing social norm learning, and further discuss the potential influencing factors that modulate social norm learning. Finally, we outline a couple of future directions along this line, including theoretical (i.e., societal and individual differences in social norm learning), methodological (i.e., longitudinal research, experimental methods, neuroimaging studies), and practical issues