Two Improved Cancellation Techniques for Direct-Conversion Receivers

To solve the problems of carrier leakage and DC offset in direct-conversion receiver (DCR) system, the paper proposed two kinds of improved technology to overcome the problems in DCR system. One is the RF carrier cancellation technology; the traditional cancellation technology based on lumped parameter filter can be easily influenced by distribution parameters, the improved circuits use a 3 db bridge to realize a 180-degree phase shifter, and the method can adapt to a wider range of RF frequency. Another is DC offset cancellation technique; a novel DC servo loop circuit is proposed to replace the traditional AC-coupled amplifier circuit. It can improve the integrity of the baseband signal and reduces the complexity of the subsequent software algorithm. Experimental results show that two kinds of improved technology can improve the performance of DCR and expand its scope of application

Gliclazide impurity F: N-[(perhydro­cyclo­penta­[c]pyrrol-2-yl)amino­carbon­yl]-o-toluene­sulfonamide

The title compound, C15H21N3O3S, is known to be an impurity of gliclazide [systematic name: N-(hexa­hydro-1H-cyclopenta[c]pyrrol-2-ylcarbamo­yl)-4-methyl­benzene­sulfonamide], a sul­fonyl­urea anti­diabetic drug. Gliclazide has a p-tolyl group substituting the sulfonamide functionality, while the title mol­ecule contains an o-tolyl group. Both five-membered fused rings adopt envelope conformations. In the crystal, N—H⋯O hydrogen bonds are formed between HN(C=O)NH groups, building centrosymmetric dimers. These dimers are further linked through N—H⋯O(sulfon­yl) contacts, forming chains in [100]

Kairos: Practical Intrusion Detection and Investigation using Whole-system Provenance

Provenance graphs are structured audit logs that describe the history of a system's execution. Recent studies have explored a variety of techniques to analyze provenance graphs for automated host intrusion detection, focusing particularly on advanced persistent threats. Sifting through their design documents, we identify four common dimensions that drive the development of provenance-based intrusion detection systems (PIDSes): scope (can PIDSes detect modern attacks that infiltrate across application boundaries?), attack agnosticity (can PIDSes detect novel attacks without a priori knowledge of attack characteristics?), timeliness (can PIDSes efficiently monitor host systems as they run?), and attack reconstruction (can PIDSes distill attack activity from large provenance graphs so that sysadmins can easily understand and quickly respond to system intrusion?). We present KAIROS, the first PIDS that simultaneously satisfies the desiderata in all four dimensions, whereas existing approaches sacrifice at least one and struggle to achieve comparable detection performance. Kairos leverages a novel graph neural network-based encoder-decoder architecture that learns the temporal evolution of a provenance graph's structural changes to quantify the degree of anomalousness for each system event. Then, based on this fine-grained information, Kairos reconstructs attack footprints, generating compact summary graphs that accurately describe malicious activity over a stream of system audit logs. Using state-of-the-art benchmark datasets, we demonstrate that Kairos outperforms previous approaches.Comment: 23 pages, 16 figures, to appear in the 45th IEEE Symposium on Security and Privacy (S&P'24

Green innovation drives globalization: a longitudinal case study of Angel Yeast’s evolution from a start-up to a world-class manufacturer

In the increasingly competitive global market, emerging market companies, represented by China, have shown mixed performance during their development process. Many companies grow rapidly in the early stages of development but cannot maintain long-term growth. How to achieve sustainable development has become a major challenge for emerging market companies, and green innovation is considered an effective way to address this issue. Based on the resource-based view, this paper conducts a longitudinal case study on Angel Yeast as the research subject, dividing the development process of Angel Yeast into three stages: the start-up period (1986-2000), the growth period (2000-2010), and the maturity period (2010-present), discussing how Angel Yeast has grown from a small start-up company to a world-class manufacturer. The study finds that Angel Yeast has utilized its unique resources at different stages of development for green technology innovation, green product innovation, green management innovation, green marketing innovation, green supply chain management, and green organizational culture construction, enabling Angel Yeast to gain a sustained competitive advantage and grow into a global leader in the yeast industry. This paper expands the research on the evolution of emerging market companies under the resource-based view theory and enriches the understanding of the role of green innovation in the growth process of enterprises

Tesseract: Real-Time Cryptocurrency Exchange using Trusted Hardware

We propose Tesseract, a secure real-time cryptocurrency exchange service. Existing centralized exchange designs are vulnerable to theft of funds, while decentralized exchanges cannot offer real-time cross-chain trades. All currently deployed exchanges are also vulnerable to frontrunning attacks. Tesseract overcomes these flaws and achieves a best-of-both-worlds design by using Intel SGX as a trusted execution environment. Furthermore, by running a consensus protocol among SGX-enabled servers, Tesseract mitigates denial-of-service attacks. Tesseract supports not only real-time cross-chain cryptocurrency trades, but also secure tokenization of assets pegged to cryptocurrencies. For instance, Tesseract-tokenized bitcoins can circulate on the Ethereum blockchain for use in smart contracts. We provide a reference implementation of Tesseract that supports Bitcoin, Ethereum, and similar cryptocurrencies

Simultaneous Supplementation of Bacillus subtilis and Antibiotic Growth Promoters by Stages Improved Intestinal Function of Pullets by Altering Gut Microbiota

Early nutrition of pullets could determine the overall development and the performance of laying hens. With the aim to reduce the use of antibiotic growth promoters (AGPs) and to maintain the growth and development of pullets, the effect of simultaneous short-termed supplementation of AGPs (bacitracin zinc 20 mg/kg and colistin sulfate 4 mg/kg) and Bacillus subtilis (B. subtilis) DSM17299 probiotic, as well as the effect of supplementation of AGPs (bacitracin zinc 20 mg/kg and colistin sulfate 4 mg/kg) during the whole period (0~16 weeks) on the overall growth and development, intestinal health, and caecal microbiota of pullets were evaluated. In the present study, a total of 630 one-day-old Hy-Line Brown layers were randomly distributed into five equal groups: including the AGPs group (supplemented with AGPs based on basal diets for 16 weeks), the BA3 group (supplemented with AGPs and B. subtilis based on basal diets for 3 weeks), the BA6 group (for 6 weeks), the BA12 group (for 12 weeks), and the BA16 group (for 16 weeks). When compared with the AGPs group, the supplementation of AGPs + B. subtilis for the first 3 weeks could maintain overall growth performance, including the average body weight, average feed intake, average daily weight gain, and feed conversion ratio of pullets at 3, 6, 12, and 16 weeks of age (P > 0.05). Meanwhile, the characteristic growth indexes in different periods were separately measured. At 3 weeks of age, the amylase activity in ileum was elevated (P = 0.028), and the length of tibia was up to the standard in the BA3 group. At 12 weeks of age, the increased villus height (P = 0.046) of jejunum, increased villus height (P = 0.023) and ratio of villus height to crypt depth (P = 0.012) of ileum, decreased crypt depth (P = 0.002) of ileum, and elevated mRNA levels of sucrase in jejunum (P < 0.05) were all identified in the BA3 group. At 16 weeks of age, the secreted immunoglobulin A (sIgA) content in the jejunum mucosa of the BA3 group was greater than the other groups (P < 0.001). Furthermore, altered intestinal microbiota was found in the BA3 group. Specifically, decreased amounts of Alistipes, Bacteroides, Odoribacter, Dehalobacterium, and Sutterella and increased amounts of Lactobacillus, Dorea, Ruminococcus, and Oscillospira were determined (P < 0.05) in the BA3 group at week 6. Meanwhile, decreased amounts of B. fragilis and C. leptum (P < 0.05) were identified in the BA3 group at week 12, which were found to be relevant for the improvement of intestinal morphology (P < 0.05) by Pearson analysis. In conclusion, simultaneous supplementation of AGP and B. subtilis for 0~3 weeks increased the relative abundance of beneficial microbiota in caecum in 0~6 weeks, then improved the intestinal morphology by elevating populations of B. fragilis and C. leptum in 7~16 weeks, and further upregulated sucrase expression and increased sIgA content in the intestinal mucosa in 13~16 weeks

Determining the Quantitative Threshold of High-Frequency Oscillation Distribution to Delineate the Epileptogenic Zone by Automated Detection

Objective: We proposed an improved automated high frequency oscillations (HFOs) detector that could not only be applied to various intracranial electrodes, but also automatically remove false HFOs caused by high-pass filtering. We proposed a continuous resection ratio of high order HFO channels and compared this ratio with each patient's post-surgical outcome, to determine the quantitative threshold of HFO distribution to delineate the epileptogenic zone (EZ).Methods: We enrolled a total of 43 patients diagnosed with refractory epilepsy. The patients were used to optimize the parameters for SEEG electrodes, to test the algorithm for identifying false HFOs, and to calculate the continuous resection ratio of high order HFO channels. The ratio can be used to determine a quantitative threshold to locate the epileptogenic zone.Results: Following optimization, the sensitivity, and specificity of our detector were 66.84 and 73.20% (ripples) and 69.76 and 66.13% (fast ripples, FRs), respectively. The sensitivity and specificity of our algorithm for removing false HFOs were 76.82 and 94.54% (ripples) and 72.55 and 94.87% (FRs), respectively. The median of the continuous resection ratio of high order HFO channels in patients with good surgical outcomes, was significantly higher than in patients with poor outcome, for both ripples and FRs (P < 0.05 ripples and P < 0.001 FRs).Conclusions: Our automated detector has the advantage of not only applying to various intracranial electrodes but also removing false HFOs. Based on the continuous resection ratio of high order HFO channels, we can set the quantitative threshold for locating epileptogenic zones