When Less Is More: Systematic Analysis of Cascade-Based Community Detection

Information diffusion, spreading of infectious diseases, and spreading of rumors are fundamental processes occurring in real-life networks. In many practical cases, one can observe when nodes become infected, but the underlying network, over which a contagion or information propagates, is hidden. Inferring properties of the underlying network is important since these properties can be used for constraining infections, forecasting, viral marketing, and so on. Moreover, for many applications, it is sufficient to recover only coarse high-level properties of this network rather than all its edges. This article conducts a systematic and extensive analysis of the following problem: Given only the infection times, find communities of highly interconnected nodes. This task significantly differs from the well-studied community detection problem since we do not observe a graph to be clustered. We carry out a thorough comparison between existing and new approaches on several large datasets and cover methodological challenges specific to this problem. One of the main conclusions is that the most stable performance and the most significant improvement on the current state-of-the-art are achieved by our proposed simple heuristic approaches agnostic to a particular graph structure and epidemic model. We also show that some well-known community detection algorithms can be enhanced by including edge weights based on the cascade data.

A combination of least significant bit and deflate compression for image steganography

Steganography is one of the cryptography techniques where secret information can be hidden through multimedia files such as images and videos. Steganography can offer a way of exchanging secret and encrypted information in an untypical mechanism where communicating parties can only interpret the secret message. The literature has shown a great interest in the least significant bit (LSB) technique which aims at embedding the secret message bits into the most insignificant bits of the image pixels. Although LSB showed a stable performance of image steganography yet, many works should be done on the message part. This paper aims to propose a combination of LSB and Deflate compression algorithm for image steganography. The proposed Deflate algorithm utilized both LZ77 and Huffman coding. After compressing the message text, LSB has been applied to embed the text within the cover image. Using benchmark images, the proposed method demonstrated an outperformance over the state of the art. This can proof the efficacy of using Deflate as a data compression prior to the LSB embedding.

Waste-honeycomb-derived in situ N-doped Hierarchical porous carbon as sulfur host in lithium–sulfur battery

Waste honeycomb derived porous carbon with a high specific surface area of 1683.6 m2 g−1 are prepared via a facile simultaneous activation/carbonization. The corresponding porous carbon/sulfur composite cathode exhibits a durable stable performance up to 500 cycles at 1 C.

Impact Analysis of Transition between Semi-Rigid and Rigid Barriers Using Simulations

Transition is a type of barrier that connects other barriers with different grades and shapes. Even if each barrier satisfies the performance, it may not be satisfied in transition. Therefore, collision safety requires a special design and examination. In this study, we investigated national and foreign standards and situations for the proper configuration of the transition and analyzed the impact behavior of the general transition using impact simulations. We developed a transition system that could ensure the stable performance of various grades by analyzing the behavior and confirmed based on the full-scale crash test (SB2 level).

Genetic Stability of TGMS Hybrids in Dry Direct Seeded Rice

Rice is a water-loving crop and traditionally sown in the nursery and then transplanted to the puddled and waterlogged main field. Owing to climate change, water scarcity and labour shortage problems, rice is now cultivated in the dry direct seeded method. Owing to potential of hybrid rice in increasing both rice production and productivity, many countries are focusing on exploiting the benefits of this technology. To break the yield plateau in rice cultivation, Thermosensitive Genetic Male Sterile (TGMS) hybrids were found to be very effective. In the present study, 41 TGMS hybrids and 9 checks were evaluated for their stability and adaptability by dry direct seeded method in four locations viz., E1 - Allahabad, E2 - Lucknow, E3 - Dhamtari and E4 - Raipur. The TGMS hybrid G44 was predicted as an ideal hybrid by the GGE stability model that possessed high grain yield and stable performance over environments. It was followed by hybrids viz., G10, G14, G34, G11, G20 and G47 that had a stable performance with high yield. Hence, these TGMS hybrids were identified as high and stable yielders across environments and suitable for dry direct seeded rice ecosystems. Among the environments, E1 (Allahabad) and E4 (Raipur) were considered favourable environments as they possessed the highest discriminating power. The hybrids identified in the study can be utilized for breaking the yield barriers in rice and can be recommended for dry direct seeding in marginal and rainfed areas.

The epidemic volatility index, a novel early warning tool for identifying new waves in an epidemic

Early warning tools are crucial for the timely application of intervention strategies and the mitigation of the adverse health, social and economic effects associated with outbreaks of epidemic potential such as COVID-19. This paper introduces, the Epidemic Volatility Index (EVI), a new, conceptually simple, early warning tool for oncoming epidemic waves. EVI is based on the volatility of newly reported cases per unit of time, ideally per day, and issues an early warning when the volatility change rate exceeds a threshold. Data on the daily confirmed cases of COVID-19 are used to demonstrate the use of EVI. Results from the COVID-19 epidemic in Italy and New York State are presented here, based on the number of confirmed cases of COVID-19, from January 22, 2020, until April 13, 2021. Live daily updated predictions for all world countries and each of the United States of America are publicly available online. For Italy, the overall sensitivity for EVI was 0.82 (95% Confidence Intervals: 0.75; 0.89) and the specificity was 0.91 (0.88; 0.94). For New York, the corresponding values were 0.55 (0.47; 0.64) and 0.88 (0.84; 0.91). Consecutive issuance of early warnings is a strong indicator of main epidemic waves in any country or state. EVI’s application to data from the current COVID-19 pandemic revealed a consistent and stable performance in terms of detecting new waves. The application of EVI to other epidemics and syndromic surveillance tasks in combination with existing early warning systems will enhance our ability to act swiftly and thereby enhance containment of outbreaks.

Ultra-high thermal stability of sputtering reconstructed Cu-based catalysts

The rational design of high-temperature endurable Cu-based catalysts is a long-sought goal since they are suffering from significant sintering. Establishing a barrier on the metal surface by the classical strong metal-support interaction (SMSI) is supposed to be an efficient way for immobilizing nanoparticles. However, Cu particles were regarded as impossible to form classical SMSI before irreversible sintering. Herein, we fabricate the SMSI between sputtering reconstructed Cu and flame-made LaTiO2 support at a mild reduction temperature, exhibiting an ultra-stable performance for more than 500 h at 600 °C. The sintering of Cu nanoparticles is effectively suppressed even at as high as 800 °C. The critical factors to success are reconstructing the electronic structure of Cu atoms in parallel with enhancing the support reducibility, which makes them adjustable by sputtering power or decorated supports. This strategy will extremely broaden the applications of Cu-based catalysts at more severe conditions and shed light on establishing SMSI on other metals.

Breeding for higher yield, early maturity, wider adaptability and waterlogging tolerance in soybean (Glycine max L.): A case study

Breeding for higher yield and wider adaptability are major objectives of soybean crop improvement. In the present study, 68 advanced breeding lines along with seven best checks were evaluated for yield and attributing traits by following group balanced block design. Three blocks were constituted based on the maturity duration of the breeding lines. High genetic variability for the twelve quantitative traits was found within and across the three blocks. Several genotypes were found to outperform check varieties for yield and attributing traits. During the same crop season, one of the promising entries, NRC 128,was evaluated across seven locations for its wider adaptability and it has shown stable performance in Northern plain Zone with > 20% higher yield superiority over best check PS 1347. However, it produced 9.8% yield superiority over best check in Eastern Zone. Screening for waterlogging tolerance under artificial conditions revealed that NRC 128 was on par with the tolerant variety JS 97–52. Based on the yield superiority, wider adaptability and waterlogging tolerance, NRC 128 was released and notified by Central Varietal Release Committee (CVRC) of India, for its cultivation across Eastern and Northern Plain Zones of India.

Numerical Investigation on Diffusion-Induced Cracking in Solid Electrolyte of Composite Electrode and Its Impact on the Li-Ion Conductivity

In this paper, the cracking of the solid electrolyte (SE) and its impacts on the effective Li-ion conductivity of composite electrodes of all-solid-state lithium-ion batteries (ASSLIBs) are investigated numerically. A two-dimensional finite element (2D FEM) model was developed for composite electrodes in which active material particles (AM particles) are embedded in the solid electrolyte. The 2D FEM model can successfully calculate and simulate the diffusion-induced stress, the generation of solid electrolyte cracks (SE cracks), and the Li-ion transport. The degradation of Li-ion conductivity for cracked composite electrodes is calculated with the homogenization method. It is revealed that the diffusion-induced volume variation in AM particles can generate significant stress and thus SE cracking in composite electrodes of ASSLIBs. The calculated results suggest that swelling AM particles are more favorable than shrinking AM particles for the structural stability of composite electrodes. It is also demonstrated that the evolution of the conductivity with the propagation of SE cracking is consistent with the percolation theory. The fundamental understating of the SE cracking and its impact in this paper may benefit the design of novel ASSLIBs with more stable performance and a longer lifespan.