123 research outputs found

    Board meetings and the information gap between managers and independent directors

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    This study examines board meetingsā€™ role in reducing the information gap between managers and independent directors. Using abnormal returns to insider trades as a proxy for insidersā€™ information level, I find no association between board meetings and the manager-director information gap for the pre-2003 period. However, in the post-2003 period, board meetings significantly increase directorsā€™ information level relative to that of managers. I next identify that board meetingsā€™ informational role is driven by the 2003 NASDAQ and NYSE board independence requirements. Further analyses support a causal link between board meetings and the smaller manager-director information gap post-2003. Furthermore, board meetingsā€™ information role is more pronounced for directors who are relatively new to the firm, diverse directors, directors with outside connections, and directors sitting on certain committees. Lastly, using a subsample of firms that voluntarily disclose disaggregated information on board meetings, I find that the form of board meetings also matters: in-person board meetings reduce the manager-director information gap, while remote board meetings do not. Overall, board meetingsā€™ informational efficacy depends on mandatory board independence, independent directorsā€™ characteristics, and board meetingsā€™ organizational forms

    Audio steganography with AES for real-time covert Voice over Internet Protocol communications

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    As a popular real-time service on the Internet, Voice over Internet Protocol (VoIP) communication attracts more and more attention from the researchers in the information security field. In this study, we proposed a VoIP steganographic algorithm with variable embedding capacities, incorporating AES and key distribution, to realize a real-time covert VoIP communication. The covert communication system was implemented by embedding a secret message encrypted with symmetric cryptography AES-128 into audio signals encoded by PCM codec. At the beginning of each VoIP call, a symmetric session key (SK) was assigned to the receiver with a Session Initiation Protocol-based authentication method. The secret message was encrypted and then embedded into audio packets with different embedding algorithms before sending them, so as to meet the real-time requirements of VoIP communications. For each audio packet, the embedding capacity was calculated according to the specific embedding algorithm used. The encryption and embedding processes were almost synchronized. The time cost of encryption was so short that it could be ignored. As a result of AES-based steganography, observers could not detect the hidden message using simple statistical analysis. At the receiving end, the corresponding algorithm along with the SK was employed to retrieve the original secret message from the audio signals. Performance evaluation with state-of-the-art network equipment and security tests conducted using the Mann-Whitney-Wilcoxon method indicated that the proposed steganographic algorithm is secure, effective, and robust

    Covert voice over internet protocol communications with packet loss based on fractal interpolation

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    The last few years have witnessed an explosive growth in the research of information hiding in multimedia objects, but few studies have taken into account packet loss in multimedia networks. As one of the most popular real-time services in the Internet, Voice over Internet Protocol (VoIP) contributes to a large part of network traffic for its advantages of real time, high flow, and low cost. So packet loss is inevitable in multimedia networks and affects the performance of VoIP communications. In this study, a fractal-based VoIP steganographic approach was proposed to realise covert VoIP communications in the presence of packet loss. In the proposed scheme, secret data to be hidden were divided into blocks after being encrypted with the block cipher, and each block of the secret data was then embedded into VoIP streaming packets. The VoIP packets went through a packet loss system based on Gilbert model which simulates a real network situation. And a prediction model based on fractal interpolation was built to decide whether a VoIP packet was suitable for data hiding. The experimental results indicated that the speech quality degradation increased with the escalating packet-loss level. The average variance of speech quality metrics (PESQ score) between the "no-embedding" speech samples and the ā€œwith-embeddingā€ stego-speech samples was about 0.717, and the variances narrowed with the increasing packet-loss level. Both the average PESQ scores and the SNR values of stego-speech samples and the data retrieving rates had almost the same varying trends when the packet-loss level increased, indicating that the success rate of the fractal prediction model played an important role in the performance of covert VoIP communications

    Geometrical and electrical modulation on the transport property of silicene constrictions

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    We study the electrical modulation of the transport properties of silicene constrictions with different geometrical structures by adopting the tight-binding model and non-equilibrium Green's function method. The band structure and transmission properties are discussed under the influence of the external electric field and potential energy. Especially, we investigate the effects of the position and width of the central scattering region on the conductance with increasing of Fermi energy. We find that the conductance significantly depends on the position and the width. Interestingly, the symmetrical structure of the central region can induce a resonance effect and significantly enlarge the system's conductance. Obviously, we obtain an effective method to adjust the transport property of the silicene heterojunctions. Correspondingly, we propose a novel two-channel structure with an excellent performance on the conductance compared to the one-channel structure with the same total width.Comment: 7 pages, 8 figure

    Lactobacillus reuteri in digestive system diseases: focus on clinical trials and mechanisms

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    ObjectivesDigestive system diseases have evolved into a growing global burden without sufficient therapeutic measures. Lactobacillus reuteri (L. reuteri) is considered as a new potential economical therapy for its probiotic effects in the gastrointestinal system. We have provided an overview of the researches supporting various L. reuteri strainsā€™ application in treating common digestive system diseases, including infantile colic, diarrhea, constipation, functional abdominal pain, Helicobacter pylori infection, inflammatory bowel disease, diverticulitis, colorectal cancer and liver diseases.MethodsThe summarized literature in this review was derived from databases including PubMed, Web of Science, and Google Scholar.ResultsThe therapeutic effects of L. reuteri in digestive system diseases may depend on various direct and indirect mechanisms, including metabolite production as well as modulation of the intestinal microbiome, preservation of the gut barrier function, and regulation of the host immune system. These actions are largely strain-specific and depend on the activation or inhibition of various certain signal pathways. It is well evidenced that L. reuteri can be effective both as a prophylactic measure and as a preferred therapy for infantile colic, and it can also be recommended as an adjuvant strategy to diarrhea, constipation, Helicobacter pylori infection in therapeutic settings. While preclinical studies have shown the probiotic potential of L. reuteri in the management of functional abdominal pain, inflammatory bowel disease, diverticulitis, colorectal cancer and liver diseases, its application in these disease settings still needs further study.ConclusionThis review focuses on the probiotic effects of L. reuteri on gut homeostasis via certain signaling pathways, and emphasizes the importance of these probiotics as a prospective treatment against several digestive system diseases

    Markov bidirectional transfer matrix for detecting LSB speech steganography with low embedding rates

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    Steganalysis with low embedding rates is still a challenge in the field of information hiding. Speech signals are typically processed by wavelet packet decomposition, which is capable of depicting the details of signals with high accuracy. A steganography detection algorithm based on the Markov bidirectional transition matrix (MBTM) of the wavelet packet coefficient (WPC) of the second-order derivative-based speech signal is proposed. On basis of the MBTM feature, which can better express the correlation of WPC, a Support Vector Machine (SVM) classifier is trained by a large number of Least Significant Bit (LSB) hidden data with embedding rates of 1%, 3%, 5%, 8%,10%, 30%, 50%, and 80%. LSB matching steganalysis of speech signals with low embedding rates is achieved. The experimental results show that the proposed method has obvious superiorities in steganalysis with low embedding rates compared with the classic method using histogram moment features in the frequency domain (HMIFD) of the second-order derivative-based WPC and the second-order derivative-based Mel-frequency cepstral coefficients (MFCC). Especially when the embedding rate is only 3%, the accuracy rate improves by 17.8%, reaching 68.5%, in comparison with the method using HMIFD features of the second derivative WPC. The detection accuracy improves as the embedding rate increases

    The management correlation between metabolic index, cardiovascular health, and diabetes combined with cardiovascular disease

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    BackgroundCardiovascular disease (CVD) has become a major cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). Although there is also evidence that multifactorial interventions to control blood glucose, blood pressure, and lipid profiles can reduce macrovascular complications and mortality in patients with T2DM, the link between these risk factors has not been established.MethodsOn 10 December 2018, 1,920 people in four cities in Anhui Province were included. Latent category analysis (LCA) was used to explore the clustering mode of HRBs (health risk behaviors). The primary exposure was HRBs and exercise and diet interventions, and the primary outcome was CVD and other variables, including zMS, triglyceride-glucose index (TyG), TyG-WC (waist circumference), TyG-BMI, TG/HDL, and cardiovascular health (CVH). A multivariable logistic regression model was used to establish the relationship between HRBs, exercise, diet interventions, and CVD. Moderate analysis and mediation moderation analysis were employed by the PROCESS method to explore the relationship between these variables. Sensitivity analysis explored the robustness of the model.ResultsThe mean age was 57.10 Ā± 10.0 years old. Overall, CVD affects approximately 19.9% of all persons with T2DM. Macrovascular complications of T2DM include coronary heart disease, myocardial infarction (MI), cardiac insufficiency, and cerebrovascular disease. Elderly age (Ļ‡2 = 22.70), no occupation (Ļ‡2 = 20.97), medium and high socioeconomic status (SES) (Ļ‡2 = 19.92), higher level of TyG-WC (Ļ‡2 = 6.60), and higher zMS (Ļ‡2 = 7.59) were correlated with high CVD. Many metabolic indices have shown a connection with T2DM combined with CVD, and there was a doseāˆ’response relationship between HRB co-occurrence and clustering of HRBs and zMS; there was a doseāˆ’response relationship between multifactorial intervention and CVH. In the mediation moderation analysis, there was an association between HRB, gender, TyG, TyG-BMI, and CVD. From an intervention management perspective, exercise and no diet intervention were more significant with CVD; moreover, there was an association between intervention management, gender, zMS, TyG-WC, TyG-BMI, TG/HDL, and CVD. Finally, there was an association between sex, CVH, and CVD. Sensitivity analysis demonstrated that our results were robust.ConclusionsCVD is one of the common complications in patients with type 2 diabetes, and its long-term outcome will have more or less impact on patients. Our findings suggest the potential benefits of scaling up multifactorial and multifaceted interventions to prevent CVD in patients with T2DM
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